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- c763abe9-bfe0-4d2e-935a-460d060a0ace
- true
- Digit Scroller
- TURN STEP
- false
- 0
- 12
- TURN STEP
- 2
- 0.0003419868
-
8702
28366
250
20
-
8702.414
28366.43
- fb6aba99-fead-4e42-b5d8-c6de5ff90ea6
- DotNET VB Script (LEGACY)
- A VB.NET scriptable component
- true
- a5d5a292-9ba5-4db7-87cc-0bb840e03f34
- true
- DotNET VB Script (LEGACY)
- Turtle
- 0
- Dim i As Integer
Dim dir As New On3dVector(1, 0, 0)
Dim pos As New On3dVector(0, 0, 0)
Dim axis As New On3dVector(0, 0, 1)
Dim pnts As New List(Of On3dVector)
pnts.Add(pos)
For i = 0 To Forward.Count() - 1
Dim P As New On3dVector
dir.Rotate(Left(i), axis)
P = dir * Forward(i) + pnts(i)
pnts.Add(P)
Next
Points = pnts
-
10844
28201
104
44
-
10899
28223
- 1
- 1
- 2
- Script Variable Forward
- Script Variable Left
- 84fa917c-1ed8-4db3-8be1-7bdc4a6495a2
- 84fa917c-1ed8-4db3-8be1-7bdc4a6495a2
- true
- true
- Forward
- Left
- true
- true
- 2
- Print, Reflect and Error streams
- Output parameter Points
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- true
- true
- Output
- Points
- false
- false
- 1
- false
- Script Variable Forward
- 169a6bf9-7051-47c9-8af9-6d54359501ea
- true
- Forward
- Forward
- true
- 1
- true
- fafed710-e79d-472d-9b45-bedb0b22c125
- 1
- 8e991e99-5fb8-41e1-928d-1bba8fb9f7d7
-
10846
28203
41
20
-
10866.5
28213
- 1
- false
- Script Variable Left
- 2a3330da-d674-4b6a-a421-fc0cd3c74f7b
- true
- Left
- Left
- true
- 1
- true
- fcee0c3b-74ec-4be8-81f5-750eae6bcae3
- 1
- 8e991e99-5fb8-41e1-928d-1bba8fb9f7d7
-
10846
28223
41
20
-
10866.5
28233
- Print, Reflect and Error streams
- b03c6bec-85be-48be-b72b-ca5d2a557279
- true
- Output
- Output
- false
- 0
-
10911
28203
35
20
-
10928.5
28213
- Output parameter Points
- 770e8f58-8dfe-4f6f-905d-3f5cbadbdf1d
- true
- Points
- Points
- false
- 0
-
10911
28223
35
20
-
10928.5
28233
- fbac3e32-f100-4292-8692-77240a42fd1a
- Point
- Contains a collection of three-dimensional points
- true
- 970781a8-0343-4bae-b5a7-02468ff37b8e
- true
- Point
- Point
- false
- 44cddb8b-ba4f-4eab-b3bd-08f5b804d82c
- 1
-
8652
27616
50
24
-
8677.724
27628.84
- dd8134c0-109b-4012-92be-51d843edfff7
- Duplicate Data
- Duplicate data a predefined number of times.
- true
- 3c11906b-2011-4aac-bb44-b0a8260f0bbd
- true
- Duplicate Data
- Duplicate Data
-
9351
28246
102
64
-
9414
28278
- 1
- Data to duplicate
- b9352246-308b-4a41-a51e-8d16471b4ff4
- true
- Data
- Data
- false
- c4650d06-e701-488c-9dbc-a658d92b263e
- 1
-
9353
28248
49
20
-
9377.5
28258
- Number of duplicates
- ba80eda7-39e8-4da0-85be-76dd9f3294e9
- true
- Number
- Number
- false
- 20c0c200-b972-4cd1-beae-aa1e2ba08217
- 1
-
9353
28268
49
20
-
9377.5
28278
- 1
- 1
- {0}
- 2
- Retain list order
- 25332cf5-26a4-42d3-83b4-0b5265331fcd
- true
- Order
- Order
- false
- 0
-
9353
28288
49
20
-
9377.5
28298
- 1
- 1
- {0}
- true
- 1
- Duplicated data
- 8b096aad-41f0-4c90-bdc2-44ece26f1604
- true
- Data
- Data
- false
- 0
-
9426
28248
25
60
-
9438.5
28278
- 797d922f-3a1d-46fe-9155-358b009b5997
- One Over X
- Compute one over x.
- true
- de29117b-9a5e-4a92-97ed-3c2864e3cbe8
- true
- One Over X
- One Over X
-
9120
28334
88
28
-
9163
28348
- Input value
- b7bef66a-1949-4a17-83b4-4eb52de9765c
- true
- Value
- Value
- false
- 20c0c200-b972-4cd1-beae-aa1e2ba08217
- 1
-
9122
28336
29
24
-
9136.5
28348
- Output value
- c4650d06-e701-488c-9dbc-a658d92b263e
- true
- Result
- Result
- false
- 0
-
9175
28336
31
24
-
9190.5
28348
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 7b5f5b19-5616-42d8-ba58-288544f41550
- true
- Shift List
- Shift List
-
9498
28361
90
64
-
9555
28393
- 1
- List to shift
- aa9b1c36-5754-4429-b60c-d84826926824
- true
- List
- List
- false
- 1d9ca0e8-950e-46ce-8479-db13c1cd3229
- 1
-
9500
28363
43
20
-
9521.5
28373
- Shift offset
- b8123dc8-4417-4532-836d-1b3667eef304
- true
- Shift
- Shift
- false
- 0
-
9500
28383
43
20
-
9521.5
28393
- 1
- 1
- {0}
- 1
- Wrap values
- 712ba1ce-cc2a-4c2e-ab7f-c3dfb1e925db
- true
- Wrap
- Wrap
- false
- 0
-
9500
28403
43
20
-
9521.5
28413
- 1
- 1
- {0}
- false
- 1
- Shifted list
- ed039296-6dd2-44c6-9e1a-c1e8dfc59069
- true
- List
- List
- false
- 0
-
9567
28363
19
60
-
9576.5
28393
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 7f9d1c96-2fbd-4af5-9e4c-9dd734401acd
- true
- Shift List
- Shift List
-
9473
28255
90
64
-
9530
28287
- 1
- List to shift
- 9df69feb-1432-4fed-b436-f2fdcc9e6f5e
- true
- List
- List
- false
- 8b096aad-41f0-4c90-bdc2-44ece26f1604
- 1
-
9475
28257
43
20
-
9496.5
28267
- Shift offset
- 05577071-06fc-48b9-9ea0-95de0ac6cc56
- true
- Shift
- Shift
- false
- 0
-
9475
28277
43
20
-
9496.5
28287
- 1
- 1
- {0}
- 1
- Wrap values
- 1531b378-33ee-4cfb-96e9-50152c45e68c
- true
- Wrap
- Wrap
- false
- 0
-
9475
28297
43
20
-
9496.5
28307
- 1
- 1
- {0}
- false
- 1
- Shifted list
- ab6779f5-8519-4c74-bf58-f285580cb58b
- true
- List
- List
- false
- 0
-
9542
28257
19
60
-
9551.5
28287
- a0d62394-a118-422d-abb3-6af115c75b25
- Addition
- Mathematical addition
- true
- 6fcdde93-48bd-4eba-aff9-a0246408803c
- true
- Addition
- Addition
-
9386
28502
85
44
-
9426
28524
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for addition
- 66bca250-846f-4673-a9eb-159a32a2bd80
- true
- A
- A
- true
- 0
-
9388
28504
26
20
-
9401
28514
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_String
- false
- 0
- Second item for addition
- 90e15842-1d83-4cd5-9f4b-9ba16be36eed
- true
- B
- B
- true
- 6a8dea11-5285-47df-9db4-ae7cd329914e
- 1
-
9388
28524
26
20
-
9401
28534
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 1
- Result of addition
- 20c0c200-b972-4cd1-beae-aa1e2ba08217
- true
- Result
- Result
- false
- 0
-
9438
28504
31
40
-
9453.5
28524
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 6fcdde93-48bd-4eba-aff9-a0246408803c
- 1
- 38226a8a-96d4-43f8-864a-454d3069644d
- Group
- POINT NUMBER
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 7fac966d-75d3-4d85-b4ea-7a678a11276c
- true
- Shift List
- Shift List
-
10984
28203
90
64
-
11041
28235
- 1
- List to shift
- 53e4a544-1f0d-42c8-8181-edabc62890fb
- true
- List
- List
- false
- 770e8f58-8dfe-4f6f-905d-3f5cbadbdf1d
- 1
-
10986
28205
43
20
-
11007.5
28215
- Shift offset
- 8f9c061e-cd01-4348-99ea-9f0af62458bc
- true
- Shift
- Shift
- false
- 0
-
10986
28225
43
20
-
11007.5
28235
- 1
- 1
- {0}
- -1
- Wrap values
- ad18235a-a4ef-4d70-adcc-486461e889f1
- true
- Wrap
- Wrap
- false
- 0
-
10986
28245
43
20
-
11007.5
28255
- 1
- 1
- {0}
- false
- 1
- Shifted list
- db13a26a-6a2c-48a4-a5e3-a419afc7c1b7
- true
- List
- List
- false
- 0
-
11053
28205
19
60
-
11062.5
28235
- 9c007a04-d0d9-48e4-9da3-9ba142bc4d46
- Subtraction
- Mathematical subtraction
- true
- 8714601c-8d05-4922-a3e8-99ec5bee1bb8
- true
- Subtraction
- Subtraction
-
8971
28646
85
44
-
9011
28668
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First operand for subtraction
- 2e5c86e5-e70a-4903-9d2b-95c6bcb6c57a
- true
- A
- A
- true
- c74b06ba-0741-400f-a4c8-676744774743
- 1
-
8973
28648
26
20
-
8986
28658
- Second operand for subtraction
- 6085835a-7965-4b8a-83c4-098ca7abca0e
- true
- B
- B
- true
- 0
-
8973
28668
26
20
-
8986
28678
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 2
- Result of subtraction
- ab54d613-8d13-4335-a8f4-c01221b4b1df
- true
- Result
- Result
- false
- 0
-
9023
28648
31
40
-
9038.5
28668
- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
- a7f6c94e-b5e4-4c5c-a6fc-1eb1aab9a9c6
- true
- Multiplication
- Multiplication
-
8968
28717
85
44
-
9008
28739
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for multiplication
- f18d75e7-d9af-44e1-bb5d-d0526569a9b0
- true
- A
- A
- true
- ab54d613-8d13-4335-a8f4-c01221b4b1df
- 1
-
8970
28719
26
20
-
8983
28729
- Second item for multiplication
- 80a36f12-5318-43fe-8a19-c5f8cea93e2a
- true
- B
- B
- true
- 0
-
8970
28739
26
20
-
8983
28749
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 2
- Result of multiplication
- b6aa70cd-ffce-47a3-a260-712054f216e7
- true
- Result
- Result
- false
- 0
-
9020
28719
31
40
-
9035.5
28739
- 9c85271f-89fa-4e9f-9f4a-d75802120ccc
- Division
- Mathematical division
- true
- 5a82e036-1da3-46fc-bdb7-89e70238a8c5
- true
- Division
- Division
-
9377
28634
85
44
-
9417
28656
- Item to divide (dividend)
- 00d9aad6-1954-4e86-909c-12ed594c867c
- true
- A
- A
- false
- c74b06ba-0741-400f-a4c8-676744774743
- 1
-
9379
28636
26
20
-
9392
28646
- Item to divide with (divisor)
- 5971abd0-d534-469b-9280-deb118a30aab
- true
- B
- B
- false
- 0
-
9379
28656
26
20
-
9392
28666
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 2
- The result of the Division
- 26ccf0cc-83e2-418a-8f4c-3a22dcee2db4
- true
- Result
- Result
- false
- 0
-
9429
28636
31
40
-
9444.5
28656
- a0d62394-a118-422d-abb3-6af115c75b25
- Addition
- Mathematical addition
- true
- f3612ad2-8be3-46a2-b3c6-b260c7c8829f
- true
- Addition
- Addition
-
9496
28615
85
44
-
9536
28637
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for addition
- ae2bce56-0c27-47a9-845e-bcd3a3ec3adf
- true
- A
- A
- true
- 26ccf0cc-83e2-418a-8f4c-3a22dcee2db4
- 1
-
9498
28617
26
20
-
9511
28627
- Second item for addition
- 1f518679-1901-4e25-b47c-95c43779b806
- true
- B
- B
- true
- 0
-
9498
28637
26
20
-
9511
28647
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 2
- Result of addition
- 6ada5024-09f3-4903-bc95-bb9e58bfc140
- true
- Result
- Result
- false
- 0
-
9548
28617
31
40
-
9563.5
28637
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 69a46f6d-5884-4eb5-aed5-3b2d6e594ef6
- true
- Evaluate Length
- Evaluate Length
-
8822
27448
142
64
-
8900
27480
- Curve to evaluate
- ce38b61d-d6bd-4be1-9ba8-66ec9bf55379
- true
- Curve
- Curve
- false
- fbe57887-2062-42c7-8b43-1b8cbf0f868c
- 1
-
8824
27450
64
20
-
8856
27460
- Length factor for curve evaluation
- 039927db-1f2e-44e5-822f-a8fc97e34554
- true
- Length
- Length
- false
- 0
-
8824
27470
64
20
-
8856
27480
- 1
- 2
- {0}
- 0
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 7005dea7-81ff-4270-bacf-d190d0643895
- true
- Normalized
- Normalized
- false
- 0
-
8824
27490
64
20
-
8856
27500
- 1
- 1
- {0}
- true
- Point at the specified length
- 484ba687-c0e4-4304-a4c9-f88e8e6271cc
- true
- Point
- Point
- false
- 0
-
8912
27450
50
20
-
8937
27460
- Tangent vector at the specified length
- 72ce55c1-290d-4329-9208-b5c4d3190bc6
- true
- Tangent
- Tangent
- false
- 0
-
8912
27470
50
20
-
8937
27480
- Curve parameter at the specified length
- 930c51b6-8d37-4be0-9339-ccebaca39c9e
- true
- Parameter
- Parameter
- false
- 0
-
8912
27490
50
20
-
8937
27500
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 6a8dea11-5285-47df-9db4-ae7cd329914e
- true
- Relay
- false
- 6ada5024-09f3-4903-bc95-bb9e58bfc140
- 1
-
9183
28488
40
16
-
9203
28496
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- aaa5a334-801a-4f37-a832-229d9cc793e6
- true
- Relay
- false
- 236190cc-8c61-4e05-ad13-e2c8c13610f9
- 1
-
9897
28205
40
16
-
9917
28213
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 7b1b00c6-bee0-4135-8aef-c6998bb822a1
- true
- Relay
- false
- 1fe668b1-ad7d-42fc-ba89-f43371616761
- 1
-
9872
28526
40
16
-
9892
28534
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- fafed710-e79d-472d-9b45-bedb0b22c125
- true
- Relay
- false
- 08aafdf1-9cde-4d9a-a5c8-2f9081abd6d2
- 1
-
10764
28234
40
16
-
10784
28242
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- fcee0c3b-74ec-4be8-81f5-750eae6bcae3
- true
- Relay
- false
- 58040f5e-60b6-45ff-8eaa-20ac9a1bc558
- 1
-
10804
28514
40
16
-
10824
28522
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 0675152f-f085-47f2-9154-4be9991ccfd5
- true
- Shift List
- Shift List
-
10055
28670
106
64
-
10112
28702
- 1
- List to shift
- 0a6f1940-14a0-4c11-8624-be6ebfe9a432
- true
- List
- List
- false
- d6e1b8f2-80b4-40ff-a5ba-12ba23a8433f
- 1
-
10057
28672
43
20
-
10078.5
28682
- Shift offset
- ea53497d-2601-4b97-a4f1-ce79888ed6e4
- true
- Shift
- Shift
- false
- 0
-
10057
28692
43
20
-
10078.5
28702
- 1
- 1
- {0}
- -1
- Wrap values
- 1764e100-1227-4791-b676-d899f68c6060
- true
- Wrap
- Wrap
- false
- 0
-
10057
28712
43
20
-
10078.5
28722
- 1
- 1
- {0}
- false
- 1
- Shifted list
- c733a2e2-ed93-4f92-98e7-f6a908d64a92
- true
- List
- List
- false
- true
- 0
-
10124
28672
35
60
-
10133.5
28702
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 134af8dc-fd98-4279-ba9a-9b330f78353c
- true
- Merge
- Merge
-
10051
28608
106
64
-
10096
28640
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- a2d0a6fb-2703-40c6-af92-174831f5ba79
- true
- false
- Data 1
- D1
- true
- d6e1b8f2-80b4-40ff-a5ba-12ba23a8433f
- 1
-
10053
28610
31
20
-
10068.5
28620
- 2
- Data stream 2
- f53a7097-cfde-42ef-b02f-408031044329
- true
- false
- Data 2
- D2
- true
- c733a2e2-ed93-4f92-98e7-f6a908d64a92
- 1
-
10053
28630
31
20
-
10068.5
28640
- 2
- Data stream 3
- 5c136c4f-69be-407f-a1b7-5e2fcf65926c
- true
- false
- Data 3
- D3
- true
- 0
-
10053
28650
31
20
-
10068.5
28660
- 2
- Result of merge
- 413ecb15-763e-4e83-90bf-3ffbecc8e2c0
- true
- 1
- Result
- Result
- false
- 0
-
10108
28610
47
60
-
10123.5
28640
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- d6e1b8f2-80b4-40ff-a5ba-12ba23a8433f
- true
- Relay
- false
- 7b1b00c6-bee0-4135-8aef-c6998bb822a1
- 1
-
10090
28759
40
16
-
10110
28767
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- fd8d01b6-550f-461d-bf89-7d885534636d
- true
- Relay
- false
- 413ecb15-763e-4e83-90bf-3ffbecc8e2c0
- 1
-
10086
28589
40
16
-
10106
28597
- 2576f657-2f0d-4e3e-9dfb-c79eb4cd13d7
- 4442bb24-c702-460c-a1e4-fcdd321eb886
- Loop Start
- Start the loop with this one. Double click to rerun.
- true
- ee8829f1-a69a-474f-ac63-380a98834db2
- true
- Loop Start
- Loop Start
-
10852
29784
118
84
-
10917
29826
- 4
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 4
- 6cc73910-22ac-4eb4-882b-eb9d63b8f3c2
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Number of repeats
- 3ca87afb-e6e9-4109-b4a2-70e62bad5866
- true
- Repeat
- Repeat
- true
- 0
-
10854
29786
51
20
-
10879.5
29796
- 1
- 1
- {0}
- 1
- 2
- If you want trigger loop to restart
- 48ad2736-1528-471c-914c-0958dcd53bf4
- true
- Trigger
- Trigger
- true
- 3dae4219-1a09-4c78-83fe-fafea0163300
- 1
-
10854
29806
51
20
-
10879.5
29816
- 2
- Contains a collection of generic data
- 6322e428-eca4-423b-a4b4-7a28c279addc
- true
- Data
- D0
- true
- aaa5a334-801a-4f37-a832-229d9cc793e6
- 1
-
10854
29826
51
20
-
10879.5
29836
- 2
- Contains a collection of generic data
- 10678145-91ad-4efa-b802-df158d8d0166
- true
- Data
- D1
- true
- 7b1b00c6-bee0-4135-8aef-c6998bb822a1
- 1
-
10854
29846
51
20
-
10879.5
29856
- Connect to Loop End
- dba71230-81ce-4ad5-ad65-b40a07910eb0
- true
- >
- >
- false
- 0
-
10929
29786
39
20
-
10948.5
29796
- Counter
- 9d387d64-76a1-4df3-b7b6-8fa8c9cd26a9
- true
- Counter
- Counter
- false
- 0
-
10929
29806
39
20
-
10948.5
29816
- 2
- Contains a collection of generic data
- 6e3091e5-a7ac-4ae5-8dd8-482aad3c899f
- true
- Data
- D0
- false
- 0
-
10929
29826
39
20
-
10948.5
29836
- 2
- Contains a collection of generic data
- e5bf71f8-8f56-4764-8cb0-ff6b65c13310
- true
- Data
- D1
- false
- 0
-
10929
29846
39
20
-
10948.5
29856
- 15483310-2ce2-48c6-b803-9dee8cb7cc9b
- 4442bb24-c702-460c-a1e4-fcdd321eb886
- Loop End
- End the loop with this one. Double click to pause the loop.
- true
- 8e88c30a-54ad-4e0e-a86c-5a9cda0fd361
- true
- Loop End
- Loop End
- 0
- false
- Constant & Record
-
11055
29784
91
84
-
11100
29826
- 4
- 6cc73910-22ac-4eb4-882b-eb9d63b8f3c2
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Connect to Loop Start
- 2833f182-382c-4ec4-bab2-3c0ac238f8be
- true
- <
- <
- false
- dba71230-81ce-4ad5-ad65-b40a07910eb0
- 1
-
11057
29786
31
20
-
11072.5
29796
- Set to true to exit the loop
- 1f9ae913-365c-42e3-8e3f-cc69fed7e90b
- true
- Exit
- Exit
- true
- 0
-
11057
29806
31
20
-
11072.5
29816
- 1
- 1
- {0}
- false
- 2
- Contains a collection of generic data
- 3c417e2a-63b3-4784-bdb9-e29866396e66
- true
- Data
- D0
- false
- fa427076-9410-409a-a28f-ff2c773f6a9d
- 1
-
11057
29826
31
20
-
11072.5
29836
- 2
- Contains a collection of generic data
- 77f32577-d9af-4eb1-ada7-e225446be236
- true
- Data
- D1
- false
- fd8d01b6-550f-461d-bf89-7d885534636d
- 1
-
11057
29846
31
20
-
11072.5
29856
- 2
- Contains a collection of generic data
- fab7e2a7-7157-4003-b8e4-b15a9a4260d0
- true
- 1
- Data
- D0
- false
- 0
-
11112
29786
32
40
-
11120
29806
- 2
- Contains a collection of generic data
- 74f7012c-7fbd-4e26-8738-bbfa495bca3f
- true
- 1
- Data
- D1
- false
- 0
-
11112
29826
32
40
-
11120
29846
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 1d0c73ba-7b51-4bc7-8966-36d2b512a153
- true
- Shift List
- Shift List
-
10011
28075
106
64
-
10068
28107
- 1
- List to shift
- a78d97e7-8217-47e4-aa22-6304b88ce3d9
- true
- List
- List
- false
- 4eba5543-8aae-4c2a-972c-7fc31ea91b76
- 1
-
10013
28077
43
20
-
10034.5
28087
- Shift offset
- 850d7b43-afa3-4cf6-b5ca-c09fc145f711
- true
- Shift
- Shift
- false
- 0
-
10013
28097
43
20
-
10034.5
28107
- 1
- 1
- {0}
- -1
- Wrap values
- 010db27a-fcda-4212-a5d7-098305b3829a
- true
- Wrap
- Wrap
- false
- 0
-
10013
28117
43
20
-
10034.5
28127
- 1
- 1
- {0}
- false
- 1
- Shifted list
- 1cfa9398-84a0-4469-b446-2fb43cb74a8e
- true
- List
- List
- false
- true
- 0
-
10080
28077
35
60
-
10089.5
28107
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 305cdec8-fbd3-4861-bdfb-d54cf581c887
- true
- Merge
- Merge
-
10007
28013
106
64
-
10052
28045
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- 8ab8be51-71e4-41b6-9171-f19d1d81d758
- true
- false
- Data 1
- D1
- true
- 4eba5543-8aae-4c2a-972c-7fc31ea91b76
- 1
-
10009
28015
31
20
-
10024.5
28025
- 2
- Data stream 2
- 03846402-d78d-4528-b02d-7e5dbe3e22be
- true
- false
- Data 2
- D2
- true
- 1cfa9398-84a0-4469-b446-2fb43cb74a8e
- 1
-
10009
28035
31
20
-
10024.5
28045
- 2
- Data stream 3
- c3a9f6af-05a9-4180-b959-03b902ced0ad
- true
- false
- Data 3
- D3
- true
- 0
-
10009
28055
31
20
-
10024.5
28065
- 2
- Result of merge
- 03d583ba-67b6-4697-afd1-3a5f24c931cf
- true
- 1
- Result
- Result
- false
- 0
-
10064
28015
47
60
-
10079.5
28045
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 4eba5543-8aae-4c2a-972c-7fc31ea91b76
- true
- Relay
- false
- aaa5a334-801a-4f37-a832-229d9cc793e6
- 1
-
10040
28147
40
16
-
10060
28155
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- fa427076-9410-409a-a28f-ff2c773f6a9d
- true
- Relay
- false
- 03d583ba-67b6-4697-afd1-3a5f24c931cf
- 1
-
10042
27994
40
16
-
10062
28002
- 3e8ca6be-fda8-4aaf-b5c0-3c54c8bb7312
- Number
- Contains a collection of floating point numbers
- 6e5061e1-aa6f-42cf-93f2-4d449f23690c
- X/4
- true
- Number
- Number
- false
- c74b06ba-0741-400f-a4c8-676744774743
- 1
-
13384
28010
50
24
-
13417.65
28022.02
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 3
-
255;255;255;255
- A group of Grasshopper objects
- 23918f61-bd8f-4844-a493-022a9a563376
- da1752d3-a71c-4640-8df3-907d2d4bcbb7
- 25715f20-5ff7-4c61-9cc2-352c53d742af
- 3
- a0caceac-d6b4-4a28-9b82-8b165ea9f451
- Group
- 59e0b89a-e487-49f8-bab8-b5bab16be14c
- Panel
- A panel for custom notes and text values
- f83ca58a-6419-418a-b3fe-8b21595db4fb
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- Panel
- X 1024
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- 0
- 0
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- GraphMapper+
- External Graph mapper
You can Right click on the Heteromapper's icon and choose "AutoDomain" mode to define Output domain based on input domain interval; otherwise it'll be set to 0-1 in "Normalized" mode.
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- GraphMapper+
- GraphMapper+
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- External curve as a graph
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- Curve
- false
- 9da3814a-8dc9-4bab-b390-b390edc62a2b
- 1
-
9957
29248
47
20
-
9980.5
29258
- Optional Rectangle boundary. If omitted the curve's would be landed
- b0339b52-7de2-4662-a003-50ccabe57648
- true
- Boundary
- Boundary
- true
- 915ca187-0684-4984-90e1-1f06c10f7133
- 1
-
9957
29268
47
20
-
9980.5
29278
- 1
- List of input numbers
- ce0ef573-9001-4e88-a7d9-d6c99e0ca0c1
- true
- Numbers
- Numbers
- false
- f8cfb071-35b2-4c7d-b14f-b623eac5d707
- 1
-
9957
29288
47
20
-
9980.5
29298
- 1
- 9
- {0}
- 0.1
- 0.2
- 0.3
- 0.4
- 0.5
- 0.6
- 0.7
- 0.8
- 0.9
- (Optional) Input Domain
if omitted, it would be 0-1 in "Normalize" mode by default
or be the interval of the input list in case of selecting "AutoDomain" mode
- 144027f2-4301-44ac-8786-7ab7b995b198
- true
- Input
- Input
- true
- f570df43-5009-430d-bfd1-27f65f985d30
- 1
-
9957
29308
47
20
-
9980.5
29318
- (Optional) Output Domain
if omitted, it would be 0-1 in "Normalize" mode by default
or be the interval of the input list in case of selecting "AutoDomain" mode
- 0fb785c6-a8d7-4fe8-b1c6-d98c6ff80bec
- true
- Output
- Output
- true
- f570df43-5009-430d-bfd1-27f65f985d30
- 1
-
9957
29328
47
20
-
9980.5
29338
- 1
- Output Numbers
- d49245f3-5bf7-4e07-a2dc-594dca29df34
- true
- Number
- Number
- false
- 0
-
10028
29248
39
100
-
10047.5
29298
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- b129a78c-ce0b-4659-9392-e69777ed9c5c
- true
- End Points
- End Points
-
9908
29529
84
44
-
9952
29551
- Curve to evaluate
- 94a33f0c-dcb3-4361-ada3-e12df7594083
- true
- Curve
- Curve
- false
- 9da3814a-8dc9-4bab-b390-b390edc62a2b
- 1
-
9910
29531
30
40
-
9925
29551
- Curve start point
- 05980ff6-43ba-4938-bab8-2f2daec47ffe
- true
- Start
- Start
- false
- 0
-
9964
29531
26
20
-
9977
29541
- Curve end point
- 602db9d8-1f27-4fad-bab2-0fe9c4848923
- true
- End
- End
- false
- 0
-
9964
29551
26
20
-
9977
29561
- 575660b1-8c79-4b8d-9222-7ab4a6ddb359
- Rectangle 2Pt
- Create a rectangle from a base plane and two points
- true
- 31e437e2-63c4-4b78-aac5-4914c287fe8c
- true
- Rectangle 2Pt
- Rectangle 2Pt
-
9897
29398
198
101
-
10033
29449
- Rectangle base plane
- d5bfa5f9-7c76-478e-bc7a-ddb84429c3bf
- true
- Plane
- Plane
- false
- 0
-
9899
29400
122
37
-
9960
29418.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- First corner point.
- b818243e-e2de-44d0-af69-d029b2edee73
- true
- Point A
- Point A
- false
- 05980ff6-43ba-4938-bab8-2f2daec47ffe
- 1
-
9899
29437
122
20
-
9960
29447
- 1
- 1
- {0}
-
0
0
0
- Second corner point.
- 3f714117-1112-45d4-8770-7f2fa53939f9
- true
- Point B
- Point B
- false
- 602db9d8-1f27-4fad-bab2-0fe9c4848923
- 1
-
9899
29457
122
20
-
9960
29467
- 1
- 1
- {0}
-
10
5
0
- Rectangle corner fillet radius
- b4a33b7f-64f6-466a-acf2-773dc5713387
- true
- Radius
- Radius
- false
- 0
-
9899
29477
122
20
-
9960
29487
- 1
- 1
- {0}
- 0
- Rectangle defined by P, A and B
- 915ca187-0684-4984-90e1-1f06c10f7133
- true
- Rectangle
- Rectangle
- false
- 0
-
10045
29400
48
48
-
10069
29424.25
- Length of rectangle curve
- 1a0fa2db-8b1e-4c0c-a25e-46189cdeb411
- true
- Length
- Length
- false
- 0
-
10045
29448
48
49
-
10069
29472.75
- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
- true
- 54581da1-580d-4778-93ab-674f6e734ffb
- true
- Bounds
- Bounds
-
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29163
110
28
-
9855
29177
- 1
- Numbers to include in Bounds
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- true
- Numbers
- Numbers
- false
- f8cfb071-35b2-4c7d-b14f-b623eac5d707
- 1
-
9799
29165
44
24
-
9821
29177
- Numeric Domain between the lowest and highest numbers in {N}
- f570df43-5009-430d-bfd1-27f65f985d30
- true
- Domain
- Domain
- false
- 0
-
9867
29165
38
24
-
9886
29177
- 3e8ca6be-fda8-4aaf-b5c0-3c54c8bb7312
- Number
- Contains a collection of floating point numbers
- f8cfb071-35b2-4c7d-b14f-b623eac5d707
- true
- Number
- Number
- false
- 8b9ef3ba-f24f-4ab0-8eee-d5332f1092f5
- 1
-
9754
29257
50
24
-
9779.688
29269.73
- d5967b9f-e8ee-436b-a8ad-29fdcecf32d5
- Curve
- Contains a collection of generic curves
- true
- 9da3814a-8dc9-4bab-b390-b390edc62a2b
- true
- Curve
- Curve
- false
- 082832c7-f80b-4ab0-8cec-39daa2c6ee5b
- 1
-
9839
29608
50
24
-
9864.506
29620.62
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- db0c3f90-16aa-4bcb-ae4f-fc0bbeaa378f
- true
- Relay
- false
- ed039296-6dd2-44c6-9e1a-c1e8dfc59069
- 1
-
9628
28423
40
16
-
9648
28431
- dc6f76a5-ffd3-4a50-b42b-fcb46a544902
- c6c19589-ab63-4b60-8d7c-2c1b6d60fac7
- True Only Button
- When clicked, the button object only raises recomputation one time.
- False
- True
- 3dae4219-1a09-4c78-83fe-fafea0163300
- true
- True Only Button
- false
- 0
- neutral,N
-
10517
29811
66
22
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 236190cc-8c61-4e05-ad13-e2c8c13610f9
- true
- Relay
- false
- ab6779f5-8519-4c74-bf58-f285580cb58b
- 1
-
9562
28216
40
16
-
9582
28224
- 7cd2f235-466e-4d30-bd3c-3b9573ac7dda
- 4442bb24-c702-460c-a1e4-fcdd321eb886
- Fast Loop Start
- Loop Start
- true
- 6a0427dd-97fd-412a-be12-fe9558ccba8b
- true
- Fast Loop Start
- Fast Loop Start
-
9865
28323
127
84
-
9939
28365
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 4
- 6cc73910-22ac-4eb4-882b-eb9d63b8f3c2
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Loop iterations
- 62d27cfd-3b3f-45e5-aa28-62ccbed2e6b1
- true
- Iterations
- Iterations
- false
- 0
-
9867
28325
60
26
-
9897
28338.33
- 1
- 1
- {0}
- 1
- 2
- Contains a collection of generic data
- ed77f663-0b90-457c-afea-47cc55fafb50
- true
- Data
- D0
- true
- aaa5a334-801a-4f37-a832-229d9cc793e6
- 1
-
9867
28351
60
27
-
9897
28365
- 2
- Contains a collection of generic data
- 6157358f-b6ed-4b5e-b7de-1f696efcd3a7
- true
- Data
- D1
- true
- 7b1b00c6-bee0-4135-8aef-c6998bb822a1
- 1
-
9867
28378
60
27
-
9897
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- Connect to Loop End
- 6dea6cc4-dc4e-4113-9e42-6c3693b206af
- true
- >
- >
- false
- 0
-
9951
28325
39
20
-
9970.5
28335
- Counter
- daaf5468-a976-4ef0-a518-fb036bd9cf70
- true
- Counter
- Counter
- false
- 0
-
9951
28345
39
20
-
9970.5
28355
- 2
- Contains a collection of generic data
- b601bd0c-ff52-4987-a6d9-cb9fc1bcc354
- true
- Data
- D0
- false
- 0
-
9951
28365
39
20
-
9970.5
28375
- 2
- Contains a collection of generic data
- 8c825e90-4b27-4bb3-9e7f-bcb80b27812f
- true
- Data
- D1
- false
- 0
-
9951
28385
39
20
-
9970.5
28395
- 4e5b891f-3e8d-4b3d-b677-996c63b3ac70
- 4442bb24-c702-460c-a1e4-fcdd321eb886
- Fast Loop End
- Loop End
- true
- aaea4aad-2963-4409-84b7-3990db27a71b
- true
- Fast Loop End
- Fast Loop End
- true
- 0
-
10160
28312
91
84
-
10205
28354
- 4
- 6cc73910-22ac-4eb4-882b-eb9d63b8f3c2
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Connect to Loop Start
- c3bc5aa8-1b46-4010-93bf-b4a248668950
- true
- <
- <
- false
- 6dea6cc4-dc4e-4113-9e42-6c3693b206af
- 1
-
10162
28314
31
20
-
10177.5
28324
- Set to true to exit the loop
- 2e52e7cf-2d99-4181-98d0-2711d19de7de
- true
- Exit
- Exit
- true
- 0
-
10162
28334
31
20
-
10177.5
28344
- 1
- 1
- {0}
- false
- 2
- Contains a collection of generic data
- 2355d77a-2930-4385-a1dd-414f4809c4c9
- true
- Data
- D0
- false
- fa427076-9410-409a-a28f-ff2c773f6a9d
- 1
-
10162
28354
31
20
-
10177.5
28364
- 2
- Contains a collection of generic data
- d95e8708-b9cf-4d9a-945e-5db46367d6c9
- true
- Data
- D1
- false
- fd8d01b6-550f-461d-bf89-7d885534636d
- 1
-
10162
28374
31
20
-
10177.5
28384
- 2
- Contains a collection of generic data
- 15aa5336-9858-4ec6-beda-c3a2d7f52046
- true
- 1
- Data
- D0
- false
- 0
-
10217
28314
32
40
-
10225
28334
- 2
- Contains a collection of generic data
- d7b42618-d2bc-436a-98d5-a8857d8b2666
- true
- 1
- Data
- D1
- false
- 0
-
10217
28354
32
40
-
10225
28374
- 3e8ca6be-fda8-4aaf-b5c0-3c54c8bb7312
- Number
- Contains a collection of floating point numbers
- 1fe668b1-ad7d-42fc-ba89-f43371616761
- true
- Number
- Number
- false
- fb5477b8-182b-46c5-ac57-f253eb9baed8
- 1
-
10242
29273
50
24
-
10267.77
29285.28
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 3
-
255;255;255;255
- A group of Grasshopper objects
- e62a82d8-3c92-4e2a-9aca-b526644e6c8b
- da33a5bd-afb6-4917-a2ad-7b78b6875928
- a962b382-2559-410e-b76c-266d28450a4a
- 3
- ac124fdd-467b-493a-8722-fa10321d6afc
- Group
- 59e0b89a-e487-49f8-bab8-b5bab16be14c
- Panel
- A panel for custom notes and text values
- 0f23777f-356c-47ca-b703-f6f1e543bf2d
- true
- Panel
- X 128
- false
- 0
- 0
- 0,1/128,1/64,3/128,1/32,5/128,3/64,7/128,1/16,9/128,5/64,11/128,3/32,13/128,7/64,15/128,1/8,17/128,9/64,19/128,5/32,21/128,11/64,23/128,3/16,25/128,13/64,27/128,7/32,29/128,15/64,31/128,1/4,33/128,17/64,35/128,9/32,37/128,19/64,39/128,5/16,41/128,21/64,43/128,11/32,45/128,23/64,47/128,3/8,49/128,25/64,51/128,13/32,53/128,27/64,55/128,7/16,57/128,29/64,59/128,15/32,61/128,31/64,63/128,1/2,65/128,33/64,67/128,17/32,69/128,35/64,71/128,9/16,73/128,37/64,75/128,19/32,77/128,39/64,79/128,5/8,81/128,41/64,83/128,21/32,85/128,43/64,87/128,11/16,89/128,45/64,91/128,23/32,93/128,47/64,95/128,3/4,97/128,49/64,99/128,25/32,101/128,51/64,103/128,13/16,105/128,53/64,107/128,27/32,109/128,55/64,111/128,7/8,113/128,57/64,115/128,29/32,117/128,59/64,119/128,15/16,121/128,61/64,123/128,31/32,125/128,63/64,127/128,1
-
7915
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100
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29350.33
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255;255;255;255
- true
- true
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- false
- 04887d01-504c-480e-b2a2-01ea19cc5922
- Text Split
- Split some text into fragments using separators
- true
- eb4824b9-1b6a-4da7-afef-ca0073312fbf
- true
- Text Split
- Text Split
-
8565
29334
127
44
-
8647
29356
- Text to split.
- 162bd387-789a-4a1e-b1e2-dff8ebe83834
- true
- Text
- Text
- false
- 0f23777f-356c-47ca-b703-f6f1e543bf2d
- 1
-
8567
29336
68
20
-
8601
29346
- Separator characters.
- 6307c6e9-babd-4a85-bb23-641ced7a1e15
- true
- Separators
- Separators
- false
- 0
-
8567
29356
68
20
-
8601
29366
- 1
- 1
- {0}
- false
- ,
- 1
- Resulting text fragments
- d975738e-73d2-4393-a83a-2b9bf445bd2e
- true
- Result
- Result
- false
- 0
-
8659
29336
31
40
-
8674.5
29356
- 59e0b89a-e487-49f8-bab8-b5bab16be14c
- Panel
- A panel for custom notes and text values
- 2d00a82a-689f-4535-a590-6ea8f4f00616
- true
- Panel
- Y 128
- false
- 0
- 0
- 0,583/179789679820800,1153/561842749440,10997359/179789679820800,19/33177600,105664189/35957935964160,29407171/2809213747200,5264015321/179789679820800,143/2073600,25686901721/179789679820800,753352771/2809213747200,16748792509/35957935964160,25219/33177600,211860341359/179789679820800,983043073/561842749440,450217958983/179789679820800,1/288,842215449017/179789679820800,3467317247/561842749440,1431724785041/179789679820800,334781/33177600,452428920131/35957935964160,43445431229/2809213747200,3373656816679/179789679820800,46657/2073600,4798686576679/179789679820800,88063341629/2809213747200,1311836172611/35957935964160,1396781/33177600,8666608497041/179789679820800,30786738047/561842749440,11124681522617/179789679820800,5/72,13933895269817/179789679820800,48344323967/561842749440,17094249738641/179789679820800,3470381/33177600,4121049919811/35957935964160,351427130429/2809213747200,24463182807079/179789679820800,305857/2073600,28656580541479/179789679820800,482385079229/2809213747200,6632699163971/35957935964160,6555581/33177600,37951503498641/179789679820800,126370418687/561842749440,42980421657017/179789679820800,73/288,48206851661383/179789679820800,159001316353/561842749440,53586921538159/179789679820800,10393219/33177600,11815446530749/35957935964160,966420578371/2809213747200,64637603087321/179789679820800,777743/2073600,70235607695321/179789679820800,1141272491971/2809213747200,15169859899069/35957935964160,14515219/33177600,81467209666159/179789679820800,263363789953/561842749440,87085626163783/179789679820800,1/2,92704053657017/179789679820800,298478959487/561842749440,98322470154641/179789679820800,18662381/33177600,20788076065091/35957935964160,1667941255229/2809213747200,109554072125479/179789679820800,1295857/2073600,115152076733479/179789679820800,1842793168829/2809213747200,24142489433411/35957935964160,22784381/33177600,126202758282641/179789679820800,402841433087/561842749440,131582828159417/179789679820800,215/288,136809258163783/179789679820800,435472330753/561842749440,141838176322159/179789679820800,26622019/33177600,29325236800189/35957935964160,2326828667971/2809213747200,151133099279321/179789679820800,1767743/2073600,155326497013721/179789679820800,2457786616771/2809213747200,31836886044349/35957935964160,29707219/33177600,162695430082159/179789679820800,513498425473/561842749440,165855784550983/179789679820800,67/72,168664998298183/179789679820800,531056011393/561842749440,171123071323759/179789679820800,31780819/33177600,34646099791549/35957935964160,2721150405571/2809213747200,174990993244121/179789679820800,2026943/2073600,176416023004121/179789679820800,2765768315971/2809213747200,35505507044029/35957935964160,32842819/33177600,178357955035759/179789679820800,558375432193/561842749440,178947464371783/179789679820800,287/288,179339461861817/179789679820800,560859706367/561842749440,179577819479441/179789679820800,33152381/33177600,35941187171651/35957935964160,2808460394429/2809213747200,179763992919079/179789679820800,2073457/2073600,179784415805479/179789679820800,2809184340029/2809213747200,35957830299971/35957935964160,33177581/33177600,179789668823441/179789679820800,561842748287/561842749440,179789679820217/179789679820800,1
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255;255;255;255
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- 6587fcbf-e3cf-480a-b2f5-641794474194
- Read File
- Read the contents of a file
- true
- fa29e628-2090-4c46-8c09-20615141542c
- true
- Read File
- Read File
- true
- action = GH_LineParserAction.Include
- Return line
- 'Parse the line and return some data that represents the line.
- 'If the line cannot be parsed, you can return Nothing and
- 'assign a different action.
- 'The default implementation is to just return the line itself.
- 'If you return types that implement IGH_Goo, this component
- 'will work substantially faster.
- 10
-
7786
30765
196
28
-
7929
30779
- Uri of file to read
- false
- All files|*.*
- b9508b12-2cc1-4f4d-9ca6-7f22a30c05a5
- true
- File
- File
- false
- 0
-
7788
30767
129
24
-
7852.5
30779
- 1
- 1
- {0}
- false
- C:\FABIUS 4096 X.TXT
- 1
- File content
- 12097910-805a-4ef6-998c-9e5ce5b09bc2
- true
- Content
- Content
- false
- 0
-
7941
30767
39
24
-
7960.5
30779
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 3
-
255;255;255;255
- A group of Grasshopper objects
- e71ad0d7-3b06-4678-b7ce-ed5cd535f317
- 51570009-3d5d-4bbd-b8b1-bdfbbf85115e
- 0da2aad4-444e-4d52-8274-d2fb3e5aaf1f
- 3
- f9dde7c6-699c-440c-a632-c24a8eefd133
- Group
- 04887d01-504c-480e-b2a2-01ea19cc5922
- Text Split
- Split some text into fragments using separators
- true
- b761c393-2730-4efa-a305-9443ef7597fe
- true
- Text Split
- Text Split
-
8627
30747
127
44
-
8709
30769
- Text to split.
- c7fab27f-5725-4cd5-8379-6b7d5e760f4d
- true
- Text
- Text
- false
- 8a536d62-0be0-4943-a59f-2d6466d0d509
- 1
-
8629
30749
68
20
-
8663
30759
- Separator characters.
- fd51762b-3e12-4500-b43e-6405505e5163
- true
- Separators
- Separators
- false
- 0
-
8629
30769
68
20
-
8663
30779
- 1
- 1
- {0}
- false
- ,
- 1
- Resulting text fragments
- 6effe990-2695-4dc9-8bc3-19a78bb8deec
- true
- Result
- Result
- false
- 0
-
8721
30749
31
40
-
8736.5
30769
- 04887d01-504c-480e-b2a2-01ea19cc5922
- Text Split
- Split some text into fragments using separators
- true
- 364a8efd-eec6-404f-ab5c-e6e2078d6eb8
- true
- Text Split
- Text Split
-
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- Text to split.
- a662be09-6078-4b5f-8ec5-951f3dbe5db4
- true
- Text
- Text
- false
- b055e58f-3b57-49cf-ab76-33835accf6a7
- 1
-
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- Separator characters.
- c61c81d3-8364-4e61-85b5-46af31dd582e
- true
- Separators
- Separators
- false
- 0
-
8620
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68
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- 1
- 1
- {0}
- false
- ,
- 1
- Resulting text fragments
- f906afd1-1468-4e27-bc1a-ccca50b7e743
- true
- Result
- Result
- false
- 0
-
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31
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- 2013e425-8713-42e2-a661-b57e78840337
- Concatenate
- Concatenate some fragments of text
- true
- 87091d69-a60b-4a19-842b-a866901fe24c
- true
- Concatenate
- Concatenate
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- 2
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- First text fragment
- b12325ed-1f6b-4983-bb39-a82a446015b6
- true
- Fragment A
- Fragment A
- true
- 6effe990-2695-4dc9-8bc3-19a78bb8deec
- 1
-
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- Second text fragment
- 0a3b9102-73a4-4b03-8763-e99531cb10ba
- true
- Fragment B
- Fragment B
- true
- eeaadcbc-e19f-4e7d-ad8f-797c7c321297
- 1
-
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- 1
- 1
- {0}
- false
- *65536
- Resulting text consisting of all the fragments
- 428b4b1c-8794-4258-a90a-711dd03be945
- true
- Result
- Result
- false
- 0
-
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31
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- 2013e425-8713-42e2-a661-b57e78840337
- Concatenate
- Concatenate some fragments of text
- true
- afc5ea2b-b28a-4c04-a477-8796a5939be3
- true
- Concatenate
- Concatenate
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- 2
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- First text fragment
- 097ed67d-2e7b-4914-bdf3-f02afc65acc5
- true
- Fragment A
- Fragment A
- true
- f906afd1-1468-4e27-bc1a-ccca50b7e743
- 1
-
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58
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-
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- Second text fragment
- c4d40302-5b1d-42ec-8eac-05a22e88299e
- true
- Fragment B
- Fragment B
- true
- eeaadcbc-e19f-4e7d-ad8f-797c7c321297
- 1
-
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- 1
- {0}
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- *65536
- Resulting text consisting of all the fragments
- 3ce54405-e2d2-4a5e-ac72-d0e4f4ca3f26
- true
- Result
- Result
- false
- 0
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- 3581f42a-9592-4549-bd6b-1c0fc39d067b
- Construct Point
- Construct a point from {xyz} coordinates.
- true
- e71ad0d7-3b06-4678-b7ce-ed5cd535f317
- true
- Construct Point
- Construct Point
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-
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- {x} coordinate
- 7fcc7372-e36e-4d5c-87d6-b659a531b31f
- true
- X coordinate
- X coordinate
- false
- 6effe990-2695-4dc9-8bc3-19a78bb8deec
- 1
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- 1
- 1
- {0}
- 0
- {y} coordinate
- b1fc1dda-00d4-451d-a8be-115616047918
- true
- Y coordinate
- Y coordinate
- false
- f906afd1-1468-4e27-bc1a-ccca50b7e743
- 1
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- 1
- 1
- {0}
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- {z} coordinate
- f2f55175-b244-43ae-8da9-079ef747bf7d
- true
- Z coordinate
- Z coordinate
- false
- 0
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- 1
- 1
- {0}
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- Point coordinate
- 1aaece72-b107-4823-9e6c-ca26b6b9397c
- true
- Point
- Point
- false
- 0
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 3
-
255;255;255;255
- A group of Grasshopper objects
- e71ad0d7-3b06-4678-b7ce-ed5cd535f317
- 1
- 51570009-3d5d-4bbd-b8b1-bdfbbf85115e
- Group
- 3581f42a-9592-4549-bd6b-1c0fc39d067b
- Construct Point
- Construct a point from {xyz} coordinates.
- true
- 0da2aad4-444e-4d52-8274-d2fb3e5aaf1f
- true
- Construct Point
- Construct Point
-
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-
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- {x} coordinate
- 510af284-b3c7-4070-a1be-cd410899d051
- true
- X coordinate
- X coordinate
- false
- 428b4b1c-8794-4258-a90a-711dd03be945
- 1
-
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- 1
- 1
- {0}
- 0
- {y} coordinate
- c44d4c56-b7dc-4b23-9a1a-7d69b7d37585
- true
- Y coordinate
- Y coordinate
- false
- 3ce54405-e2d2-4a5e-ac72-d0e4f4ca3f26
- 1
-
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- 1
- 1
- {0}
- 0
- {z} coordinate
- a7b31229-98f5-4b91-af59-735fbc1070e3
- true
- Z coordinate
- Z coordinate
- false
- 0
-
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- 1
- 1
- {0}
- 0
- Point coordinate
- dc56eb11-1ba6-4fdc-9332-a1688428a3bb
- true
- Point
- Point
- false
- 0
-
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- 59e0b89a-e487-49f8-bab8-b5bab16be14c
- Panel
- A panel for custom notes and text values
- 213f2fc8-3c62-4add-b084-ae87fdec816f
- true
- Panel
- false
- 1
- f906afd1-1468-4e27-bc1a-ccca50b7e743
- 1
- Double click to edit panel content…
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- 0
- 0
- 0
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255;255;255;255
- true
- true
- true
- false
- false
- true
- 6587fcbf-e3cf-480a-b2f5-641794474194
- Read File
- Read the contents of a file
- true
- 149afc02-a382-4ca6-9322-7a4f060b8f7f
- true
- Read File
- Read File
- true
- action = GH_LineParserAction.Include
- Return line
- 'Parse the line and return some data that represents the line.
- 'If the line cannot be parsed, you can return Nothing and
- 'assign a different action.
- 'The default implementation is to just return the line itself.
- 'If you return types that implement IGH_Goo, this component
- 'will work substantially faster.
- 10
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- Uri of file to read
- false
- All files|*.*
- 4e906bfc-2333-4718-8a8b-42b774beb5db
- true
- File
- File
- false
- 0
-
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- 1
- 1
- {0}
- false
- C:\FABIUS 4096 Y.TXT
- 1
- File content
- 3d097a6b-53b5-4f50-b948-3a177d2c8203
- true
- Content
- Content
- false
- 0
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Data
- Contains a collection of generic data
- true
- b055e58f-3b57-49cf-ab76-33835accf6a7
- true
- Data
- Data
- false
- 0
-
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- {0;0}
- Grasshopper.Kernel.Types.GH_String
- false
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- d5967b9f-e8ee-436b-a8ad-29fdcecf32d5
- Curve
- Contains a collection of generic curves
- true
- f2aa309b-3dac-4084-aa45-453eaa9db884
- true
- Curve
- Curve
- false
- 0
-
9560
29645
50
24
-
9585.656
29657
- 1
- 1
- {0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0;0}
- -1
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- 00000000-0000-0000-0000-000000000000
- dde71aef-d6ed-40a6-af98-6b0673983c82
- Nurbs Curve
- Construct a nurbs curve from control points.
- true
- 5953c941-4736-4fdc-be71-5b01d5096fc8
- true
- Nurbs Curve
- Nurbs Curve
-
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- 1
- Curve control points
- e8a36df3-789b-4e83-a172-c94aab9f8a4b
- true
- Vertices
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- false
- 8d8f2080-094e-4467-95f2-a8b6da5f1972
- 1
-
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- Curve degree
- a1808e6a-4721-4f1a-a284-1c1247923816
- true
- Degree
- Degree
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- 0
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- 1
- 1
- {0}
- 11
- Periodic curve
- 23a8e221-1a6b-4bde-a02e-514c56bba545
- true
- Periodic
- Periodic
- false
- 0
-
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9678.5
30600
- 1
- 1
- {0}
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- Resulting nurbs curve
- 10c46a26-f75f-4b1c-852a-eb8916fad3c4
- true
- Curve
- Curve
- false
- 0
-
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- Curve length
- e9ba44ba-d3e6-445d-b6f9-78278a0082ca
- true
- Length
- Length
- false
- 0
-
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- Curve domain
- 5da61cb6-d609-4f66-abc9-15278dfb1282
- true
- Domain
- Domain
- false
- 0
-
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-
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- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 8d8f2080-094e-4467-95f2-a8b6da5f1972
- true
- Relay
- false
- 0089c2e3-9879-4f71-a687-a024344de1f1
- 1
-
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- 6587fcbf-e3cf-480a-b2f5-641794474194
- Read File
- Read the contents of a file
- true
- 13aab24b-b036-4a08-a6ee-d32ebb1217ee
- true
- Read File
- Read File
- true
- action = GH_LineParserAction.Include
- Return line
- 'Parse the line and return some data that represents the line.
- 'If the line cannot be parsed, you can return Nothing and
- 'assign a different action.
- 'The default implementation is to just return the line itself.
- 'If you return types that implement IGH_Goo, this component
- 'will work substantially faster.
- 10
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- Uri of file to read
- false
- All files|*.*
- 64b96e62-3d7e-4959-893b-b1cb268333af
- true
- File
- File
- false
- 0
-
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- 1
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- {0}
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- C:\FABIUS 16384 X.TXT
- 1
- File content
- bf9d0fa0-6c87-413b-abf1-9a7fed38d319
- true
- Content
- Content
- false
- 0
-
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 3
-
255;255;255;255
- A group of Grasshopper objects
- 5b00838f-4808-4364-bbcd-4705dea61ca6
- 8386555d-1604-4e1b-ae8f-630eff298486
- 9ec4a0af-799b-4e1f-a413-0ecab486e883
- 3
- be8005da-b6c8-4939-ae79-fcd9991bdca6
- Group
- 04887d01-504c-480e-b2a2-01ea19cc5922
- Text Split
- Split some text into fragments using separators
- true
- d4c354e4-6a25-40e4-b57c-0b9d21a35f38
- true
- Text Split
- Text Split
-
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- Text to split.
- a67e2d37-6782-4828-8780-a248f66e2fe8
- true
- Text
- Text
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- 150c505d-ca0d-4cd7-8862-2f22baf8add1
- 1
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- Separator characters.
- 47216bb8-a906-4cac-b6f9-27c8af000f08
- true
- Separators
- Separators
- false
- 0
-
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-
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- 1
- 1
- {0}
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- ,
- 1
- Resulting text fragments
- a3fc0dec-53ca-4b10-9e78-ad3723aca7db
- true
- Result
- Result
- false
- 0
-
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- 04887d01-504c-480e-b2a2-01ea19cc5922
- Text Split
- Split some text into fragments using separators
- true
- 07f4ba56-a85f-400d-9a35-83a531f8b2bd
- true
- Text Split
- Text Split
-
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127
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- Text to split.
- 577015bd-4f82-4784-a345-940c0d3f96c2
- true
- Text
- Text
- false
- c4a5c37c-b696-47db-8f86-ef64754026fe
- 1
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- Separator characters.
- cf445915-90e5-4a62-881f-587f4a096032
- true
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- Separators
- false
- 0
-
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- 1
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- {0}
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- ,
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- Resulting text fragments
- 840d554c-b279-4cbe-be56-996c05ad1dce
- true
- Result
- Result
- false
- 0
-
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- 2013e425-8713-42e2-a661-b57e78840337
- Concatenate
- Concatenate some fragments of text
- true
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- The bulge factor for Tangency and Curvature modes
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tNdxXI3n4/j/o8XSGkkshNYaIaSFWLrOCI1YCI3GQRJCI4Rw0Cw0OyyEcJAkIWlpxI6E0HIkJMlRqVPCQbPQ7Lv3p9fnvj+Pz+/x++/7PX94dr2uc5/rPvfjnPtcFE0UCsU//z7+438eVmb//jNxbMjs+QuGLJg3b8F8F4cJMxcumr1g/qD+vfp80cutzxfuHv/+4erax8VhyOLQ8MULZw6aP3Nx+MJpoS4Ofounh86eMXLmMv8Fc2fOH9S3r5ubR5+ZA/rP6N+3b98vXJv+Z5V2//XivYbPXDBvZvjCZb1GL144fdGQxQuXzDT/d/bDJY2rWU5bOCNk9pKZXwTNa74gbOb8+f95lnnQtPBp/3mShYWF2X9O1LqrQuH2r780fGTV/IN//2j5n3+qFWYKs7erzRQPFGb/9abe/WOmsOUNtmt1YsqYjwpb/f5eYb2uiaNpRPtlnzT8O3+I51p/8N9X4r9Giv/1MIn/Xei//+9i+f859v/2QzoXZSMWaI22aIf26ICO6IRd0Bm7owv2Qlfsg274BbpjX+yH/dEDB+BA/BI9cRB6oUBlo2pUfMUYFYMZo2IIY1R4M0bFUMaoGMYYFcMZo8KHMSq+ZoyKEYxRMZIxKnwZo2IUY1SMZoyKbxijwq9RJapRh4oxzKMadagYyzyqUYeKccyjGnWo8Gce1ahDxXjmUY06VExgHtWoQ8VE5lGNOlQEMI9q1KHiW+ZRjTpUTGIe1ahDxWTmUY06VAQyj2rUoeI75lGNOlRMYR7VqEPFVOZRjTpUqBp1QCWqUI1a1KEBFdM4HpWoQjVqUYcGVEzneFSiCtWoRR0aUDGD41GJKlSjFnVoQEUQx6MSVahGLerQgIqZHI9KVKEatahDAyqCOR6VqEI1alGHBlTM4nhUogrVqEUdGlARwvGoRBWqUYs6NKBiNsejElWoRi3q0ICKORyPSlShGrWoQwMq5nI8KlGFatSiDg2oCOV4VKIK1ahFHRpQMY/jUYkqVKMWdWhAxXyORyWqUI1a1KEBFQs4HpWoQjVqUYcGVIQ1ao0O6IpK9EMVhqEaNajFVNShHg1oQsX3rI8O6IpK9EMVhqEaNajFVNShHg1oQsVC1kcHdEUl+qEKw1CNGtRiKupQjwY0oWIR66MDuqIS/VCFYahGDWoxFXWoRwOaUBHO+uiArqhEP1RhGKpRg1pMRR3q0YAmVCxmfXRAV1SiH6owDNWoQS2mog71aEATKpawPjqgKyrRD1UYhmrUoBZTUYd6NKAJFUtZHx3QFZXohyoMQzVqUIupqEM9GtCEigjWRwd0RSX6oQrDUI0a1GIq6lCPBjShYhnrowO6ohL9UIVhqEYNajEVdahHA5pQsZz10QFdUYl+qMIwVKMGtZiKOtSjAU2oWMH66ICuqEQ/VGEYqlGDWkxFHerRgCZURLI+OqArKtEPVRiGatSgFlNRh3o0oAkVK1kfHdAVleiHKgxDNWpQi6moQz0a0ISKVayPDuiKSvRDFYahGjWoxVTUoR4NaELFatZHB3RFJfqhCsNQjRrUYirqUI8GNOG///H9LyzQGu3QAZ3RFT1QiT7ohwGowhAMwwhUYzRqMA61mISpmIk6zEU9FqEBjWjCelSsadQCrdEOHdAZXdEDleiDfhiAKgzBMIxANUajBuNQi0mYipmow1zUYxEa0IgmrEfF2kYt0Brt0AGd0RU9UIk+6IcBqMIQDMMIVGM0ajAOtZiEqZiJOsxFPRahAY1ownpUrGvUAq3RDh3QGV3RA5Xog34YgCoMwTCMQDVGowbjUItJmIqZqMNc1GMRGtCIJqxHRVSjFmiNduiAzuiKHqhEH/TDAFRhCIZhBKoxGjUYh1pMwlTMRB3moh6L0IBGNGE9Kn5o1AKt0Q4d0Bld0QOV6IN+GIAqDMEwjEA1RqMG41CLSZiKmajDXNRjERrQiCasR8X6Ri3QGu3QAZ3RFT1QiT7ohwGowhAMwwhUYzRqMA61mISpmIk6zEU9FqEBjWjCelT82KgFWqMdOqAzuqIHKtEH/TAAVRiCYRiBaoxGDcahFpMwFTNRh7moxyI0oBFNWI+K6EYt0Brt0AGd0RU9UIk+6IcBqMIQDMMIVGM0ajAOtZiEqZiJOsxFPRahAY1ownpUbGjUAq3RDh3QGV3RA5Xog34YgCoMwTCMQDVGowbjUItJmIqZqMNc1GMRGtCIJqxHxcZGLdAa7dABndEVPVCJPuiHAajCEAzDCFRjNGowDrWYhKmYiTrMRT0WoQGNaMJ6VGxq1AKt0Q4d0Bld0QOV6IN+GIAqDMEwjEA1RqMG41CLSZiKmajDXNRjERrQiCasR0VMoxZojXbogM7oih6oRB/0wwBUYQiGYQSqMRo1GIdaTMJUzEQd5qIei9CARjRhPSp+atQCrdEOHdAZXdEDleiDfhiAKgzBMIxANUajBuNQi0mYipmow1zUYxEa0IgmrEfF5kYt0Brt0AGd0RU9UIk+6IcBqMIQDMMIVGM0ajAOtZiEqZiJOsxFPRahAY1ownpU/NyoBVqjHTqgM7qiByrRB/0wAFUYgmEYgWqMRg3GoRaTMBUzUYe5qMciNKARTViPCk2j5miBVmiNtmiH9uiATuiMLuiK7uiBnqhEb/RBX/RDfwzAQFRhEIZgKIZhOEZgJKoxCqMxBjUYi3EYj1pMwCRMwVRMx0zMQh3mYC7moR4LsQhL0IAVaMRaNGEd1mMDKrY0ao4WaIXWaIt2aI8O6ITO6IKu6I4e6IlK9EYf9EU/9McADEQVBmEIhmIYhmMERqIaozAaY1CDsRiH8ajFBEzCFEzFdMzELNRhDuZiHuqxEIuwBA1YgUasRRPWYT02oGJro+ZogVZojbZoh/bogE7ojC7oiu7ogZ6oRG/0QV/0Q38MwEBUYRCGYCiGYThGYCSqMQqjMQY1GItxGI9aTMAkTMFUTMdMzEId5mAu5qEeC7EIS9CAFWjEWjRhHdZjAyp+adQcLdAKrdEW7dAeHdAJndEFXdEdPdATleiNPuiLfuiPARiIKgzCEAzFMAzHCIxENUZhNMagBmMxDuNRiwmYhCmYiumYiVmowxzMxTzUYyEWYQkasAKNWIsmrMN6bEBFbKPmaIFWaI22aIf26IBO6Iwu6Iru6IGeqERv9EFf9EN/DMBAVGEQhmAohmE4RmAkqjEKozEGNRiLcRiPWkzAJEzBVEzHTMxCHeZgLuahHguxCEvQgBVoxFo0YR3WYwMqtjVqjhZohdZoi3Zojw7ohM7ogq7ojh7oiUr0Rh/0RT/0xwAMRBUGYQiGYhiGYwRGohqjMBpjUIOxGIfxqMUETMIUTMV0zMQs1GEO5mIe6rEQi7AEDViBRqxFE9ZhPTagYnuj5miBVmiNtmiH9uiATuiMLuiK7uiBnqhEb/RBX/RDfwzAQFRhEIZgKIZhOEZgJKoxCqMxBjUYi3EYj1pMwCRMwVRMx0zMQh3mYC7moR4LsQhL0IAVaMRaNGEd1mMDKnY0ao4WaIXWaIt2aI8O6ITO6IKu6I4e6IlK9EYf9EU/9McADEQVBmEIhmIYhmMERqIaozAaY1CDsRiH8ajFBEzCFEzFdMzELNRhDuZiHuqxEIuwBA1YgUasRRPWYT02oCKuUXO0QCu0Rlu0Q3t0QCd0Rhd0RXf0QE9Uojf6oC/6oT8GYCCqMAhDMBTDMBwjMBLVGIXRGIMajMU4jEctJmASpmAqpmMmZqEOczAX81CPhViEJWjACjRiLZqwDuuxARU7GzVHC7RCa7RFO7RHB3RCZ3RBV3RHD/REJXqjD/qiH/pjAAaiCoMwBEMxDMMxAiNRjVEYjTGowViMw3jUYgImYQqmYjpmYhbqMAdzMQ/1WIhFWIIGrEAj1qIJ67AeG1Cxq1FztEArtEZbtEN7dEAndEYXdEV39EBPVKI3+qAv+qE/BmAgqjAIQzAUwzAcIzAS1RiF0RiDGozFOIxHLSZgEqZgKqZjJmahDnMwF/NQj4VYhCVowAo0Yi2asA7rsQEVuxs1Rwu0Qmu0RTu0Rwd0Qmd0QVd0Rw/0RCV6ow/6oh/6YwAGogqDMARDMQzDMQIjUY1RGI0xqMFYjMN41GICJmEKpmI6ZmIW6jAHczEP9ViIRViCBqxAI9aiCeuwHhtQEd+oOVqgFVqjLdqhPTqgEzqjC7qiO3qgJyrRG33QF/3QHwMwEFUYhCEYimEYjhEYiWqMwmiMQQ3GYhzGoxYTMAlTMBXTMROzUIc5mIt5qMdCLMISNGAFGrEWTViH9diAij2NmqMFWqE12qId2qMDOqEzuqAruqMHeqISvdEHfdEP/TEAA1GFQRiCoRiG4RiBkajGKIzGGNRgLMZhPGoxAZMwBVMxHTMxC3WYg7mYh3osxCIsQQNWoBFr0YR1WI8NqNjbqDlaoBVaoy3aoT06oBM6owu6ojt6oCcq0Rt90Bf90B8DMBBVGIQhGIphGI4RGIlqjMJojEENxmIcxqMWEzAJUzAV0zETs1CHOZiLeajHQizCEjRgBRqxFk1Yh/XYgIp9jZqjBVqhNdqiHdqjAzqhM7qgK7qjB3qiEr3RB33RD/0xAANRhUEYgqEYhuEYgZGoxiiMxhjUYCzGYTxqMQGTMAVTMR0zMQt1mIO5mId6LMQiLEEDVqARa9GEdViPDajQNmqG5tgMLdASrbAFWqMN2mJbtMP2aI+d0AEd0Qm7oDN2Rxfsha7ohu7YDz1wIHqiFypxMHrjMPTBEeiLo9EPx6I/TsAAnISBOAVVOB2DMBhDcA6G4nwMw4UYjkswApdjJK5CNa7FKFyP0bgRY3AzanArxuJ2jMNdGI97UYsHMAETMQmTMQWPYyqmYTpmYCaewSw8jzrMxhy8jLl4DfMwH/VYgIV4B4uwGEuwFA1YhhVYiUaswVp8hiZ8iXX4GuvxLTbge1Tsb9QMzbEZWqAlWmELtEYbtMW2aIft0R47oQM6ohN2QWfsji7YC13RDd2xH3rgQPREL1TiYPTGYeiDI9AXR6MfjkV/nIABOAkDcQqqcDoGYTCG4BwMxfkYhgsxHJdgBC7HSFyFalyLUbgeo3EjxuBm1OBWjMXtGIe7MB73ohYPYAImYhImYwoex1RMw3TMwEw8g1l4HnWYjTl4GXPxGuZhPuqxAAvxDhZhMZZgKRqwDCuwEo1Yg7X4DE34EuvwNdbjW2zA96g40KgZmmMztEBLtMIWaI02aItt0Q7boz12Qgd0RCfsgs7YHV2wF7qiG7pjP/TAgeiJXqjEweiNw9AHR6AvjkY/HIv+OAEDcBIG4hRU4XQMwmAMwTkYivMxDBdiOC7BCFyOkbgK1bgWo3A9RuNGjMHNqMGtGIvbMQ53YTzuRS0ewARMxCRMxhQ8jqmYhumYgZl4BrPwPOowG3PwMubiNczDfNRjARbiHSzCYizBUjRgGVZgJRqxBmvxGZrwJdbha6zHt9iA71FxsFEzNMdmaIGWaIUt0Bpt0Bbboh22R3vshA7oiE7YBZ2xO7pgL3RFN3THfuiBA9ETvVCJg9Ebh6EPjkBfHI1+OBb9cQIG4CQMxCmowukYhMEYgnMwFOdjGC7EcFyCEbgcI3EVqnEtRuF6jMaNGIObUYNbMRa3Yxzuwnjci1o8gAmYiEmYjCl4HFMxDdMxAzPxDGbhedRhNubgZczFa5iH+ajHAizEO1iExViCpWjAMqzASjRiDdbiMzThS6zD11iPb7EB36MioVEzNMdmaIGWaIUt0Bpt0Bbboh22R3vshA7oiE7YBZ2xO7pgL3RFN3THfuiBA9ETvVCJg9Ebh6EPjkBfHI1+OBb9cQIG4CQMxCmowukYhMEYgnMwFOdjGC7EcFyCEbgcI3EVqnEtRuF6jMaNGIObUYNbMRa3Yxzuwnjci1o8gAmYiEmYjCl4HFMxDdMxAzPxDGbhedRhNubgZczFa5iH+ajHAizEO1iExViCpWjAMqzASjRiDdbiMzThS6zD11iPb7EB36PiUKNmaI7N0AIt0QpboDXaoC22RTtsj/bYCR3QEZ2wCzpjd3TBXuiKbuiO/dADB6IneqESB6M3DkMfHIG+OBr9cCz64wQMwEkYiFNQhdMxCIMxBOdgKM7HMFyI4bgEI3A5RuIqVONajML1GI0bMQY3owa3YixuxzjchfG4F7V4ABMwEZMwGVPwOKZiGqZjBmbiGczC86jDbMzBy5iL1zAP81GPBViId7AIi7EES9GAZViBlWjEGqzFZ2jCl1iHr7Ee32IDvkdFYqNmaI7N0AIt0QpboDXaoC22RTtsj/bYCR3QEZ2wCzpjd3TBXuiKbuiO/dADB6IneqESB6M3DkMfHIG+OBr9cCz64wQMwEkYiFNQhdMxCIMxBOdgKM7HMFyI4bgEI3A5RuIqVONajML1GI0bMQY3owa3YixuxzjchfG4F7V4ABMwEZMwGVPwOKZiGqZjBmbiGczC86jDbMzBy5iL1zAP81GPBViId7AIi7EES9GAZViBlWjEGqzFZ2jCl1iHr7Ee32IDvkfF4UbN0ByboQVaohW2QGu0QVtsi3bYHu2xEzqgIzphF3TG7uiCvdAV3dAd+6EHDkRP9EIlDkZvHIY+OAJ9cTT64Vj0xwkYgJMwEKegCqdjEAZjCM7BUJyPYbgQw3EJRuByjMRVqMa1GIXrMRo3YgxuRg1uxVjcjnG4C+NxL2rxACZgIiZhMqbgcUzFNEzHDMzEM5iF51GH2ZiDlzEXr2Ee5qMeC7AQ72ARFmMJlqIBy7ACK9GINViLz9CEL7EOX2M9vsUGfI+KpEbN0ByboQVaohW2QGu0QVtsi3bYHu2xEzqgIzphF3TG7uiCvdAV3dAd+6EHDkRP9EIlDkZvHIY+OAJ9cTT64Vj0xwkYgJMwEKegCqdjEAZjCM7BUJyPYbgQw3EJRuByjMRVqMa1GIXrMRo3YgxuRg1uxVjcjnG4C+NxL2rxACZgIiZhMqbgcUzFNEzHDMzEM5iF51GH2ZiDlzEXr2Ee5qMeC7AQ72ARFmMJlqIBy7ACK9GINViLz9CEL7EOX2M9vsUGfI+KI42aoTk2Qwu0RCtsgdZog7bYFu2wPdpjJ3RAR3TCLuiM3dEFe6EruqE79kMPHIie6IVKHIzeOAx9cAT64mj0w7HojxMwACdhIE5BFU7HIAzGEJyDoTgfw3AhhuMSjMDlGImrUI1rMQrXYzRuxBjcjBrcirG4HeNwF8bjXtTiAUzAREzCZEzB45iKaZiOGZiJZzALz6MOszEHL2MuXsM8zEc9FmAh3sEiLMYSLEUDlmEFVqIRa7AWn6EJX2IdvsZ6fIsN+B4VyY2aoTk2Qwu0RCtsgdZog7bYFu2wPdpjJ3RAR3TCLuiM3dEFe6EruqE79kMPHIie6IVKHIzeOAx9cAT64mj0w7HojxMwACdhIE5BFU7HIAzGEJyDoTgfw3AhhuMSjMDlGImrUI1rMQrXYzRuxBjcjBrcirG4HeNwF8bjXtTiAUzAREzCZEzB45iKaZiOGZiJZzALz6MOszEHL2MuXsM8zEc9FmAh3sEiLMYSLEUDlmEFVqIRa7AWn6EJX2IdvsZ6fIsN+B4VRxs1Q3NshhZoiVbYAq3RBm2xLdphe7THTuiAjuiEXdAZu6ML9kJXdEN37IceOBA90QuVOBi9cRj64Aj0xdHoh2PRHydgAE7CQJyCKpyOQRiMITgHQ3E+huFCDMclGIHLMRJXoRrXYhSux2jciDG4GTW4FWNxO8bhLozHvajFA5iAiZiEyZiCxzEV0zAdMzATz2AWnkcdZmMOXsZcvIZ5mI96LMBCvINFWIwlWIoGLMMKrEQj1mAtPkMTvsQ6fI31+BYb8D0qUho1Q3NshhZoiVbYAq3RBm2xLdphe7THTuiAjuiEXdAZu6ML9kJXdEN37IceOBA90QuVOBi9cRj64Aj0xdHoh2PRHydgAE7CQJyCKpyOQRiMITgHQ3E+huFCDMclGIHLMRJXoRrXYhSux2jciDG4GTW4FWNxO8bhLozHvajFA5iAiZiEyZiCxzEV0zAdMzATz2AWnkcdZmMOXsZcvIZ5mI96LMBCvINFWIwlWIoGLMMKrEQj1mAtPkMTvsQ6fI31+BYb8D0qjjVqhubYDC3QEq2wBVqjDdpiW7TD9miPndABHdEJu6AzdkcX7IWu6Ibu2A89cCB6ohcqcTB64zD0wRHoi6PRD8eiP07AAJyEgTgFVTgdgzAYQ3AOhuJ8DMOFGI5LMAKXYySuQjWuxShcj9G4EWNwM2pwK8bidozDXRiPe1GLBzABEzEJkzEFj2MqpmE6ZmAmnsEsPI86zMYcvIy5eA3zMB/1WICFeAeLsBhLsBQNWIYVWIlGrMFafIYmfIl1+Brr8S024HtUHG/UDM2xGVqgJVphC7RGG7TFtmiH7dEeO6EDOqITdkFn7I4u2Atd0Q3dsR964ED0RC9U4mD0xmHogyPQF0ejH45Ff5yAATgJA3EKqnA6BmEwhuAcDMX5GIYLMRyXYAQux0hchWpci1G4HqNxI8bgZtTgVozF7RiHuzAe96IWD2ACJmISJmMKHsdUTMN0zMBMPINZeB51mI05eBlz8RrmYT7qsQAL8Q4WYTGWYCkasAwrsBKNWIO1+AxN+BLr8DXW41tswPeoONGoGZpjM7RAS7TCFmiNNmiLbdEO26M9dkIHdEQn7ILO2B1dsBe6ohu6Yz/0wIHoiV6oxMHojcPQB0egL45GPxyL/jgBA3ASBuIUVOF0DMJgDME5GIrzMQwXYjguwQhcjpG4CtW4FqNwPUbjRozBzajBrRiL2zEOd2E87kUtHsAETMQkTMYUPI6pmIbpmIGZeAaz8DzqMBtz8DLm4jXMw3zUYwEW4h0swmIswVI0YBlWYCUaseb/gdaK/9+HfkFHQ2fDVOH8+dqpZiYfr//u315p929fIJIOa680SZ8udbOpLY2fGJeKKYP2/dsXSj1v28f/Pn+10F8M/MvMZbXUX3b9oLZ17TrRxmzzALNpP0p9S/eGqk+MPwrTD482r/lOI/UT/V6Ud6jYJDwjFG3MCrZJ3SP10cPOhp/Ffd8xaWYt4qUes7LyaatnW8SqST0yL0Tvl/qeQfeetK79RXi32ffF4PmHpO59Lbe6Tc02McLiQOXa00ekvvh2+r/ns0NEmsZZRAUdl7pjqz2P21XuFF8GdVQcPHNS6v17r/n3PHeLbeOGZ1eEp0t91yPVo45le8Q6x51lH047LfXPi7/89/z3iZe6ruM+Xn1G6mMeRz+zfq4VQ1vcXv86/5zUp7h9/+/72i88nL6/OT1JJ/V/UibU2jw9IOy9VpZ6rc2WeknPAf++34Piy5f7f2m1OEfqK36yq7F9kiC+b/dB5QP1Zam7JtQZ29QcEiHz+v9x+FCu1K1H/FHVtjpRqH/4a214+TX59SccqPzEeFhcan49b8TAP6Reu3/RY7uqJNFTOc7vi+QbUm9j9lVFu8oj4mjed8vi292U+vpRluXtHyeLur6G/elzCqR+6NsbjzpUHBW/7xizfE7uLalXvP3ZYF+eIppsONQz1+221H8y933YseyYiP/0gaL4yB2pb/L5oLTTo+PiQ6u/tMd7FkndecevJZ0NJ8Tuu+2WTjx/T+ozpp6cp1mQKkKbvjWrnnxf6leGNn1q/TxVtGoV+eWKZg+kvmHGhNAt80+KomVb/+x2vlTqf+5OeNLq2Unxovxo0savDFLfr38+Z+u8NFHxeVrbk90fSb33o/41Nk/TREjL3n572pdJvfnRyNm/hJ4SS4ZP9ZzVqlzqrZufN7auPSUqX6oedWtZIfVJt97Nip2bLiKO90v+wPax1E+X9q2yfZIuMoyXTrR1qJT6nIa5wdvm/CpmXDljvuGLKqkfe7PncZuaX0V6TF/zH0Yb5e/dvutB22dniNdjOx8c8H211HWpdeVtqzNE/Pj3F4t310g9qNZuxo6Q0+L9go4/7c9/IvWPLT3KPjGeFr0D7+rymj+Ves6ZMdPiZmWKy5sLP9k/6pnUTYdnGuyqMsVoU/M9s3c9l/rGhYum7gz+TfiMPNjUM8Ik9X5py0vbVf4m3n3TcruN8wupj6pb/t2umWfE7UxFvLFE7vlnFpW0f3xGHG1/qMPL7S+l3mdF0OTdQWfFTM3HbrMmvJJ61z2+xR0qzopnO+YOi+pQJ3W3ZT2+jZ+RJdKGbPhyY6XcHScqiuzLs0T10bn7z5/+U+rzQq9N2DP9nLi1s1XV3J9fSz2wOPp2x7JzQrt2SMyjeX9JvWXKQP+9086LpNeh48LH1Ut9XGFpQadH58WkZcsXrVK+kfrgHuFj9ql+F/v+zrw6te9bqR+d++ZGZ8PvYtrNXz9a5fZO6g5x/brqe+uEdmenN94eDVL/qj44WLNAJ7aP3v9Tl+F/Sz3tfcwhvxM6sadfntvuqe+lfuP84Qrr5zqxsfTpi0/X/iP1YveMz272uiCWrn47VjtRIf673xxyevqW+RfEhb8Ot81+JfdWp47sH3P8gjg+4PEo3bYmUr/SI8bQ6tkFcSrmiwzjIDOpu/T7rnNBz2yRsHXHvZhauav7dZiydV622LI1oqvZgQ+knjc7J37ssWxxOuH7jw9MMZf6pLIJ922eZot5WR9bX3NsKvWadfp2t1wuillNg8vvP5P79n96BfwSelFc2x+3btDFZlIPvrFg+7iUi+JBmtWob7UfSl3TR1PYuvaiWJ+/1HbvegupB3z2k01hjxwRGRfntXpJc6n/MnmGX+zcHHGvxa674WGWUr/g3XKz/9Ec4W7TOvld+EdS//11zHXbJznC8+S28duirKRu7lpkcbv7JbH4yoWg3H0fS33u6Nqh2+ZcEomH8qc7XGkh9VXDc9aOT74kHj5eber5rqXUv9JO+r1NzSXh1n1Q6JC91lJfFHTk3e1ul0WvlUtblQ9tJfUhHZP7b599Wax9+LXt5Tq5z78yftGEI5fFr6O+HyuO2kg9NzfheNvqy2LYn3kzEma3lnrHx5ur7zhfEeGvsg6McrWV+mK3j5x2hFwRXrM6uW//R+4HrKynTEy6IvROFS1K7raRuqPFLzs+MV4R47JGfqD+ra3Uh1VE6+92zRXas8cvPE74ROpxkY8t4mblCsPnJsOiXXZSX/nbbmXA4VyR33l9xS+72kndUr1nqV1Vrii70Xlw2qH2ct9//1hRl6vCZ3FVsFdWB6n3uDK0PC74quiYp8pKLrWX+oiga598m3hVGCwrUkI/7iR1w54JI9tVXhV5zhmHG3w6S329x52V9z6/JgbenWrzxMdB6j+s/eLEzpnXxAuzl7e+rJP74kETH3576JrY0OT9tJOJn0q9fL1zi/aPr4kBW8+22KxylPqL32O+LHa6Lr6pGpfRxvEzqf+1aNasXUHXxaBzD3//6YncW3nt2jIp4bpw763sNOick9QPHjM/077iuvhR3PYL3fG5/HnuFmUo/ixPXHZqEzRzeRepr7j1ynz3jDwxdMmHLxcFd5V601kuXScfzBPr/Q87Pp7sLPUzHcyHdyjPE6+O9E75cHI3qVevHR103/EPMWGv/60eQd2lvmRmyard0/8QCaPmzT24tIfU+2pXbJ984A+RfVpz58I2F6m3/Od1coeyP8TrlKSmJed7Sv1227ZZ9z/NFyf7rIzwedVL6tc77rm6e1q++HzQg70n2rlK/X62763J+/NFyt5lb7J+l/uCD8qKOjzKF/cm+5W9mdtHPv9/2hTfd7ghDh6zPh3byU3qv+bvubNbdUOUzrgfn3VX7jWjuudP1t4QkSe/Uu/f8YXUl7+apetguCHSioe0CZ/iLvVXo1bfedpSL7Zd/ebuTJe+Us86mnv1j9568Vu0aH6kST+p/9n+4W/HvtGLGQcm/hpWKvevLX5O/GmBXiRPH3rMlN1fvs7dDvw872e9KHpjv/G7Ex7y9VE9DB91Qi8WLJ2YUntwgNTv7LOc0POGXpyK1n9ZqB0o9S+vVrh9/FwvtuZd7Doy8Uv5vrelx0dPW9wUI+Zc7bIh3VPq4aqdpXm9boqP5t7MuHx9kNQ/7vU4JWX0TVH6eceOg2q9pD5hRvbimPk3hfZp+y9af6SU+o0Mg0fo5pticcbztNIEuc9oXvvnyOM3xdb6tff3DvlK6mJwTEqP/JtCTCl48H2V3HO7zQz86NlN8ejk2NFLNIOlfmRI26ZPPi4QA7b9+y3zGiL1JkkDE6/1LBC7E3/M+vml3I/cDxHJowrE4JF7bpUf9ZbvV4fd9BvmFYjq8YGbquYMlfr0504Bs3/69/UvFMw623uY/Lldf+WOz7ECocg88I36rdxPNdsz0vmPAlHaQ7dp4vXhUt+sdcz48GmBWDjc6cr0Az7y7/KLG22qrG6JgA5LWuSs/lrqqbfbzrnscksceXf4xp4ZI6R+t9+MtEO+t4SL/YZ7NqNHSj3iYftnUaG3RB+bkZOHCV+pO329xz4o5pbY8O5t+eT+o6S+de6QQUNSbomlDs+mLe03WuqHN079xjHvlkiv/9TxnOc38v3hg0Fjm9TeEuY5V6qcP/eT71ftHYYaPioUxc0GDDh2Qu77s4d2/b1HoXBcq+v/ftAYqbddUP7XnpGFou705ou99HJ3LuqSETm3UJzyHFAzJnis1Add6Ttt8qZC4ZzsXblcMU7qIQ971g84WigyPZI6ndsr9ysznZbbXS8UO81GdnH5yl/+/W3epfJ1TaFo9W752ftVcj99pN+Xty1vC8Wx76483DpePv9OYyJOdb8t2jyc9J3v4Anyfunv4PgtI26LOT5rzvR9LffC71SJC+bcFjExj71Tj0+U+sb9HbaN2nhbjMt+t1E/N0De5/SbN6tH8m1hU/hk8NGe38q/F5M72ze/dlv8Yf3o6/F1creoenGysvq2UPmOP1j++yT5e9R0V9ec5ndE8fOJEXM1k6V+SZG9Yn+3OyIq8GZbs+BAqRc3aX5s1dd3xFjzi6Ys5XdSv1pgdmby7Dti8a6o3Scdpkh9zf7++z023BFrz7/P/7PpVPk6X/hsWpsjd8SqdeVB+0xyt1jQv/5F7h0xPu5lj+lhKqm//ulOUL7xjqi6unjaoCdyfzMv4FCyxV3xezunsNqQaVL/fuOHmeud74qggvCo5dVyvzfy093Tfe6KIx2v3HsZOl2+H+be9vUKuSvGdn73m+qV3J+uH369XfRdsfGR5cobkTOk/seXm2z/PHxX5NofjB7RPEjqGT8d7qK/cld4Gc5+8yBO7msLY/9Jrrorztn3GftLj5lSX1jsueeHD4tEsM1k+4gLcv9kz/K/p3YtEsXaxGE7JgVLfWSL9p0GDi8SK5b1XNzwWu5+t+82tJ5VJGZ8MXriqe2zpG5lPW3H0/VF4qrS+/CVASHy99123JPLiUWiz+Xfuw01yH2425ev910uEkvGrzzWf+NsqeeEb/81orJIPNjywPJo/zlSfxt0s8uYZvfEi8uRnx01yr1r3vDh3brcEz+uufZoyJ65Ulcv8bZtMuyeWKzc77FmfKjUR79WbCqaeU8kBpQ6Lmg1T/6czzqUdOKHe2Jhr7cH2t2U+z9uPnPWH7onUp5os2Ni50u99tbTvMBL98Sc0pFbCycvkPqA3dF/uD2+J+7enRe7qnWYvA9cXB9i0bRYzLi5c0zzFXI/fNwy/oFTsZj64ZMtmgq5/3Vm2Yw072KR8+lXs9v7fS9/Pt/Unl0fVCwcm9U8TTkn912r6vdPiioWNuqFHqN7LpTvw7ftbXolFIuJ1UtnmO+Te8kfly2a5BQLj+rlm27bLJL3b4O+WXurvFhYTzuVfyVa7nl5b5cf+uC+uLLzse8jRbjUL59982zJZ/dF24seXZ1XyH1Ayqzi4UPui9kFLdQH/pL7kdkjB9jNuC9a5T1YPmHJYqkHpm3/0Lj2vli8ytJzxF9yn6vo8tXpA/dFy/Qc47rlS6TebJzu0Q/Z90VuaUVic8VSef/8V9vH48rui+ODrsc/+lHu2f6Xhn1qViJ6r1S+aGUTIZ/nST+zZ5+WiEM3J17X7pW7SuHc+sxXJcIsZuzY2J7LpH42+WD4D9NKhL/zD8denpd7p4Cmjn5rSkTh7UHm2WOXS333b0vbtt9fIu4vTVlpUS332eNajCrXlYivOuUp89askO9Xwy7pjhpKhP3LUeGtO0bK17/DmtBFigdiw5YfvCrOyP2zTS1GDnR4IAIKJlzynrxSvs7DHScqlA/EAoNTry/fy73uSsCmS1MfiJ+OZO/54+AqqR9r2a9sw+oHwvaHIA8z39VSvxXx+YRR+x6IjA9++fTha7nrI5c9avn7A/F1SEuvvmPVUl+0cu6qm6UPRNkly77jk+V+8acOXbe+fyD02ZPXF3ywRv5dG6i5PaZTqTjj0H9w6hS554/LWGftVSoCbk2LeHFG7rGnVD3yvysVh8pdPHbarZX6RxY+lzeuLBVdt3yvSV4q95a7LUcP21MqqhN++tm5SO5H2rtkKc6VCo+aqUPaDlwn9ZnT2lieKSkVdRe8f1uyR+6JXrZ9FjaUijmXbd77mkVJ/UMxuXs3+4fi06WfdIoPkXtOeJPnpV8+FCset/58ll7uXyrNIn6Z/FDsCxzQ6eSAH6S+zG7Q+WErHopjii62KxPkbhy3+Ez9rodi9/RH1vnW6+X77YsxM4+ceSiGfHiv4+FVcp869bvTAcUPRbWhZMhHz+Tu49P0SLO3D8XbMx02/T3lR6nbuozaec/KIIp2dH6nvin3yx84dzlhbxD7FNd2xQ2Nlno/t05/rXMxiNxhfmHDz8r9+tMeFgGeBhF9uv8ajdsGqbdf4zW+h69BHNCNKVhyVO5pvd2L/55sEPVNM2f9/flGeT/coWTrjbkGMS8417vrAbkP7/p6uXaFQYQ+dQj9q/Mmqe81uG0O22QQPY/tfhi2T+4dVF/kit0G8VnkCO12hxipN++zwanFUYPYu3nh8bkH5T6iX8be+2cMwrLix+avuv4k309+dnFLumYQ1SudU3sfl/sh9ejiRcUGsW78J1qnfpvl/Zv//K1eNQax2rz/ncLf5T51aP54i7cG4W0bNXrIyJ+l/kWQtvPN5o/EzaoW5ouK5D5pZbMnce0eicqdyyNOfaGR7zNNbE5N7fZIDIrs+WGrSLn3enJx4ecDHgldRJ/kcZfkfjPZ6vMan0fiaP/WDyJbbpF6ykd5OccCHonlw++03zxJ7h073/QNC3kkIqabHkQnyn1ol+LTfSIeif7femvnv5L7hchYxcsfH4mne+zvK7/aKnXXqPhPT+54JALmff5hE43cf9CsbLPg8CNxamtwfOpDuXvcPnmnx+lH4s8cT5sxrr9Ifcq4A1OrLj8SE+PHPixfI/dzuYnJ++88Esc771w2p1Duxfuapk2qfCR+rBYTKrvGSt3u0asFNq8fiQGPU6oDIuVe47StNLdpmeiSsOjwxZty7/7ju79WtikTK0b6mjk7b5M/b7u7ZvT5vEzo2luG/rha7r/NsGhd4V4mNm7aMr78rty1Q1dYbPMuE9mW+b0G9dku71fNfTXe/mXiM9/Dwds3yX3EGfeElzPKRNMBr+eYKuWeU/Bg0L5FZaJV5LIk3yE7pO5oUTphxLoy4Z5ydWOKVu4fTztjfLW1TJjajYps9Y/cu7lW1u4+UCYeDe5RGTklTt6ftLkYODitTHQ3CVfTebl//4+2T9WFMmHVtMWFUIedUu/tdj5o480yseODtL9frZV7lxHDn/d4VCbOjyr8+sdKub/0nnjtuqlMeHfb/aHzyF1Sf7zhr2ezFeXC5qf4HXdT5R5e13lCM+ty8fP5GwE7Ptktf64MGfXazuVCfWlVUshquY/rt+XGgN7lwvJc/zJfo9xvRS68pfcqF14W56cOHRsv9feVVn/PHF0u1oS9ixh3Tu57ZzUZ+ua7cnHwixfrIrrtkfqenIcHN84rF++aHSn8dbvcXVK62LRfWS462nY5Z9V0r9RDrg+JPhxTLlq9Gv/TqnC5r6385b1bfLn49FCTX6weyz3o5fR5WUfLxY6t59tlTtgnf5571+YNOfvv6//0cM7aq3JX+kxqc/VauTA9SQvO6KSVesbcK16+xeWiTYc3gz2/lfujsEFf/VFdLjYqJs8dFyt3z9e/2vq+KRffOaatbrgh99dR7U/mWlSIrIVbOnlY7Zf6/F+9WwyxqxC3Kgc9bva13AeNf//Z2a4VoofN4QWz18v98eYmNa79K0TR5akBqhy5d2j9ZmLCsApx78x2j1qzA1I/PkQ9s82ECjH0i5ZJHw+WexvVZ5ZRMyuEfUa7QZfWyP2XU1MHmcIrxN8XY2JaZ8tdceng62+jKsTo3ee6vTE7KHWH6G96XvilQlxqtixxibfcf9akF31+sEKkDWjYGrNe7q7D2pp+TKsQe7KervzyqtxtOyTPqbpQIVznTahbZ5Ug32+zdwjvmxViReyuNcF+cnef+2bmXkOFyGm76ER5rNy9X98v/PN5hbDVVTZtuCf31X3FuhH/VIhTqUM+Su18SOrDurQNiW/xWJyttfNWBMt9Wu/hy590fCxetHL94mmK3NdPTUnt3/OxeNXvx2+X1sn9bkprszWej8Vvr0f02+eZKN+H+4qZV0Y+Fn2O6ofN/EHuYasf6y0nPxYh9zTNruXLvem5k1+OnPNvv/np8z/sDkv9lJV3fPSyx2LtOreI72fIfc25PtXZ0Y/F1JgfPvn1uNzHbm3a7u2Ox+J2RK1y51u5v2yqdOx1+LH4ZPCQ4E7Dk+T39fPEd1MyHov9ZqF/ecfKPaAqc1fMpcfiXfmI6R+Xyb1+5JXXGYWPxfSh2TYRrkekHnelpGlp+WMxusOJhT+slvvBxSPON3n1WBT9+Li67w25L8sNaOtoVikqj/Ys3dA5Weq+N4abi1aVwv6k8tSaMLlbRX6zKsChUiy0unytY7bcx1TvWz6/d6Xo/8YvaortUXn/oJ32XO1VKTq5TBnkPUvuwaW/Fvw8qlLsPzdmzI0zclfdz2i/O7BS/DZicTtFyxT5OreIOHdgbqVYM+J17Z0ZcvcMb3YycXmlaLmjwsH/N7kvuhXyJHFDpZjQtY9FRMtjUt9npp1+MK5SpP2V8mpwsNzvuhy2ij9cKb7tZOH26zm5/9Y2/KEmo1I8sLjZ8kab41IfMuMv/ZpLlSL34aK7mvly315kf3d+YaUY/fHAm2+vyP1swvWqieWVonPF10M+djwh788PVNZ7vqwUwTMSv8+NlPvlPb7/7o2qxN+2vfe6FMl92c6iV29bVomIJn7mHdunSn1L6+lXb3WqEtcNPksjfOReOOLckqSeVeLqpaxLzkvl3jvq7IsIz397hr9Vr0S5z/Hr4Tp0ZJW4K5KCo2/L3bGgqOvHk6rE8m2DnvdvelLqLc035+tDqkRV1obfPfvKffs/Nu01S6uE52+m59tnyv34kF6KkeurxJJzl3YM2y731g0JS5psqxKWM0b+MfKK3C/4fLno1MEqYfX41KHE+v/Rf0h/okqrEs+nftp3Yvc0qQ/85dbt5heqREmbxM3fBcr9asfJXY/fqBJJp71zftssd/uqj++MKq0Si9NMlXMvyD2/xYm7xtoq0bBmc7PwOrmvnmzmuPpdldjyYV2fgq6npN41Ki/Z2tIo/npsXLJ+stz3L7s1a4+dUfQu61Km+VnuU1JLR3/e1Si2fj1p9YuLcveec3p8Ul+jOPad47dJ9f/jdRTdFnbxNorIy62W/dozXerOvZrs2jfWKAo/OlFlN0Pu1QHWF1tPM4pXbRenFMTJ/bOSbuVrFxiF37lbf5Tly71mjJOpdqVRVI53HfN101/lfUvJvYdjYoxixKTKgc085f5+vnPSyV1GUWzrs7ndIrl3afvSy+qIUcz6bt+odcly3y867pp22ijiZ/ZaPqTsfzy/ybYTJy8ZxartrraT2mdIPWLK14sbbhmFj/p++ytj5R6yufejr8qM4sGDqTEbN8n9hNfg6jUmo2h2rGZmQo7c199Zsy7rvVH8HJh40Pa93G+drjv0wqpauLTKUt7vf1rq91YdHvZph2pR02R8//rv5e6jPDZ5ZLdqcbV2t3puitx3X+p8f0H/anHj4HnbvlVyT7rS+ezmodWiJO15jb9jptQndL394vC4auHZKeTNte/kPs1pweKz06pFxYDZfXfslHvnrU6eVxdUi147vX757bbcPSzdPW+urBb5bZXN3Gx+k7roWDH31qZqcaHullrxjdwd16y7cGNntXjd+vs6pxi5Bw6a/cXlw9Vi6pD9Y/ZdlXtZYd3pjF+rRY/ED6IXfHhG6qfnbR66/2K1KHD9Zv22oXLv/Dqx4Ieb1ULrOX5gqyi5fzc8c3zQw2rh3cd8S1m23M2GDb3k+bRa3BkyZ0lzs7NS//Wfe5+0fFct4kZk3v7hK7mvvfyR932LGrExwXvnxDVyT/x6mXJ/2xpx+YvNyasuyL3s6LUPpjnViDmzxcu3TbLk792Ok1Ht3WpExrQ+AXmD5f75N9W//SFqhKHFgosv18l95Pl+u5aPqhGtv/doP/+S3K9Fhdh/OrlGfFjcdLDXh+fk/bPZxP4XQmpE/MBNnWd8LXebKRWPJi359/Ujzm4v2ST3w5sbbJ6tqxH/5F3fmJwv987fbbuwfEuN+OGz/qV5rc7Lv8shxysU+2rE0nUXFg4ZL/cZn49ZpE6pEUVLVnRrsVPuFg81QW9+qxGu4ZfKXB7I/VjaxhNzr9SIuuHjVu379Hf5+sTMHHm3sEakRva+PzNY7v84jO3tWVYjOl44f3f1Ubm3rNo4dtfzGjF/5MUxT01y//Nj/5QXDTUiwd619cQOOnn/v+jdF4Mtn4gPlrRoN81L7va7igybPnki1K7hSbHT5D42zjc53+mJuD+4xYkXUXKv/jj7R0u3J+LuRWX7iCS5T7I5FibEE1H/s/Pdrnlyr/tsU+A83yfC7Gl8gcIk9+FtygfHfvtE9OzR542Z7QWpf/rGu0N68BPxeki//r085O768YgHeYueiJglWRFrA+X+5cFYdan6ich4FHvkH7XczZvrG4w/PRHtO4z79dAhuRfMT/26dtcTkX5x9I/h1+R+PO/lFOPhJ0K0O2QZ+lzucy4Huj9IfyK+jBrYPcY2W+pLNmdduHbhiXBxzNIXDpD70SvG96n5T0TcyP3GoVPl3iZYV/7z/SfiqzY9Ax9Gyf3J5u4hs4xPxN/XF7TZnyz3q0vbRvX/84nYOcfn/Ua93P2HruitMKsVjs2DFXtey31+9cTpF1rUijfeXze9a39R6u2anLJd0aFW2Owf+tpjiNy/SNvl1dO5VuQ+WJuVPVvufTY4Fd11rxUZw98rwzVyb5gw797yr2rFnw2bQkedlnunljsHth1dK4Y6F3UdXSr3KYkFr45MqhUH+4RMXtI0R+rPX4z8u++sWnG3fPfzSy5yD/hx0DdnFtWKtPXH8zz95e68p/JRP3WtOPn0dHHxCrnvrY05djSmVpQsP9ZEe1Duo2Mjk+121gp9mxndYq7LvfTdhzdXHqoVlW1jBux7JffHmT+2u3+yVsR0yWp3r8Ml+T65eFKk6/la8dA65OQAb7n3uV3xYuW1WpH0U2WVLlTu86dvWXjxTq0oaAhLmL9N7icX6V8rymvFuk+c8gefl/u4dnZL+z2vFbXbFL6DquRuaF7xZMa7WvHu6hPzKdaXpR6q+XXUhg+fio96pz5MGCD3eZGttyW2fiqynv2d3WqG3Lu13njmbOenotvkudsSYuSeaXY0I7fHU5ExZfGg7zLkvmvCx2v/6P9U5D9avf9Lg9xr5o1qc23IU2HqcuewsLwi31dfWc0+/81Tsabj0X6z3eVuefvl4uTJT0XV0XbumVPk3vDVUffNs56KDS+c1rtskLvvwao9sxc9FX5rMm0un5L7g11Tkj1XPxVjtiX9HlUq93VN8sZ+uOmpGOWZtjCkea6836g0/Xx1+1Nxcs2KVt+7y72N5pdJ6w48FTrNL2v2TpV7bOTqo+7Hn4r1txYmmTbKPTHohxUPfnsqPFusmDsrQ+76QSsurrz0VJxd+tcJszK5awd5Rra5+VRsuWE/Ofvjq1Lv/yBpb0LJUzF4YfOxiQPk3vFB4mc9jE9F/9BLy47PlPuorz81P/Lqqfht0+DTxVvkrlppMaDTP0/F+IWBz7ufl/sfzmPPbrR8JqoPFTXbV/M/1h33Zt2zNs/Euv3BZf0+uSb1DNX7TV9/+kz0q9wX/HKI3Lu0nZW32+WZqPvIIuJmmNwX7PHyetz/mVhYYPXu1h65/7FhW/HnQ54JO7dmhW+uyd26ZM2u70Y/E03m9asaXC/3B806L4359pkwd7hmd+Lz61KvffnT7LSgZ0I/rsjXa5zcxQd/zrmx4JlotXn6LJNa7v+HTPsOx/oLHweePSqaIkTD3isjHGRkZO9VFMpIRUIKJWQlM0TJalHJSFEyiwYZJRKy1/O8Hyol/M7z+X5/3a7r++/rel/nfd7n3Oe+73M9jy1XmP/34FmUM2Rp1FgC7ptxOHT28ix6TB/5rboP/P6JdxHkxFm0wbaS/hPrW6jX7HQXJrJmERtt6s3NyuCB4fuP9hTOIs0/5cmnPcC7nLulax/PorvbbzTMpYKLfGH+ml09i2ilyramN4Av1Eu4nm6eRSRaa0/HOXC+xOwqtY+zKPFEQ8H+Xe/++ZxDRd9K3yza5iJx38gMnPNHb8PTsVk0OX7X6WwYOBo863WMMou6lNRv1T8EJ7v/fsO2NItG7vZYyXwDj0nv6rnPREKeVdYutWzv//lt+6gUtImEamjPFZxUBycHX517w0NCLvK/6LVOgM+W+ZMNhEiIfY2Hq3wOuE1zfUSdDAk5MZjd0nsPXnKZ/Z60KgndrhDMPbcMPj9NtkvVJaFBRW29NskPsF8qTAlkUxIKViT76xwC38+4gLQcSCil1mFd71XwjU6+x2PcSGgX021SYi34lwE++je+JHRd4vUaDwKcdaKOZTmIhMQu9idKbmyD81vI6S8Sgd/rIp5ZJQLeazCuaphAQm+dJOMttcBLpNc4H7lOQpoRVfYr9uD0LHvbT90moWWu9LkqP/BBFo/EgAck5O8TcSAiDtyZPzD1VAUJrS2QNXAuAE8WsP7iWktCB2N1J/RegHty/LQ1aCGhIltbDs1P4F7GVmuFO0loOHjulT4Z/EJj0NTiVxI6a5/W58LSDvtuenqucYyEmnhLra/sAk8fseaNJPC6ed7jr90H7j144IjqIgl9F+gSZbQCp9ypOuRPS0bissFuDifA399iSNNhIqMa8Y7al1Hgx+nutG9cR0ZrRNdKyOWCO7U0svdsICPlU+qZ5c9WzcfjysGsrWT0VzF4QbcT3Iq8K9p2OxkVOlUrjs2Ai+q/rt7AR0YCQnN6aUwf/zmdRfl4/W4yclz8y2m5E3wjlzjLaWEy8uW/k8m/D/zSij83twQZKQaXVi9arhpnrp/npQwZSRq8OTFyArz3+ktW571kxEpE3/oaDV4Z6jf0S4WMDEtDNIdvg8+YOufGITIignZo/q4G30c7pc2jTUbn87sTeD6B/2KKayk8QEZn3ixyGRPg2VHPpcQPklFA9Mf2+LUd8N6YxVMPzMhozja+oFcAnEe2O0HImoxKHY0iFDXAgye+Xsq2JyM6BV6nXHtw+axiY7ZDZNT85c8OrjPgUcPj00FHyEgt6N3TnKvgv/VVHQc8yOiGoSeX7D3wTd5OmZreZBRyPlmqowHcVnVtQfZJMtrEtjAR/g08VZYteN4fx0OFnKL6n1XPX1TaphtERlbt7xmYt3b+8+em7sFJ58lonb669jcp8KOT53N7wsmo79L3gXoD8IrfvjHckWSUb72updwNXKFGUc42hoz4flNmysLAWdR7M64m4H1ZqlF5lQWeFOlV/SqJjHYZhuV8qQCn76HPmE3D8c+jzETzEXx65L0ERxYZddB0usrPgCfTLgUq3SSjqe/CN/2Zu/757kPvA63yyCiS/e/dV7vB/VUTxHyKyIhNc/kkNwL32ZlyNfQ+GX0rfzsYbg8+wK6dF/cQ74smMTF/Brz2KZtbyhMymvQYCvC/Bp738FRHWiUZVQfTBawpBvfN/jWd/JyMDtbkd15/Dc59WulR7Esy+h5LF6Y2vOr51B7uC/VkdDbawG12BbyII0HSq5mMTN9eO3Wfu/ufE184xsxbyShzx7dr/org+S1a2gofyIhGWvCJvgW4/NKs9qYOMtrfe6BO1Bf8zXfG8YluMqrw3PZgWyz42dMR4tVfyOjekKnThiLwTQdObrzST0ZJpnl1W+rB4zsHU02HyKh/x4PXe76Bk86vPN00SkaHfRYcNBbB39YvB32YICPREwzHPbZ9+ufaLns+R86QUUOTRl+GHHi4T8NHJYKMMn4w3/5kAl4erHV8ZJ6Mwp8XF/J7g8c/2ZgVt0BGxldOdvtHg3P+KvOQ/EtG0kQEb2c+uNDci/ctK3j+3BuPqb8C36H28YMLHYEMNCVvP/kKvu94ruccI4Fe75molPsDfoiflBPKSqDjKVqpLzg+Q96WT/BmZCOQ3ZSUoKUceE+pS0fURgKtS8+ynjcBb/vp2EG3lUA/ctw23fQGb3l6yTuYk0DRkkd1LK+A9/FO5kxxE+jgzqO9mwvBzzeWedrwEeh5okjt1zpwk27OtppdBLp55OS3x9/Ax1gcP+wQJFB7//SexL/gjys7jwWLEGiNolFIIFfPP6f9NnGjTRy/d7dCu+decB/pzd47pQmUdPIAu4fFKufo6faWI9Da1J27fE6Ch9V0fi3dS6D92jY/QuLBX3I/Cp9TJhA7XYh/2j3wNQsC9ZJqBDr7fEdsVTN4Epkm76gGgU6Ytu4ZHQa/Hc6/K3U/gZDMWgke2i//XHetr2atLoGyp92uOvCBq3yaohnVx/te76KYrwpuuqPwKONBAhmqRGz4aQeevv6F505TPM4Dc0azs+CyrUe3KloQyLvPnL48BXw8uM9Nz5pAdZfW/txZCu6tFehkbkegB8P0zekfwC0P3liycSRQq+0bV44Z8Pa2Gj3bQwSyGRgpy2bt/edb2I+oWbgS6PyjyTsSwuAn7XcPHHAjkOgrL9EmHXBxziIZ5WMEkranEfA4As5UXyS3xwvHw80DERvCwY/OkMZYThCoYsewXF0OOMd+B9PJkwQytwnhC6kGr47pPtHoR6D3B2pl1b+A3y48pJMVQKALi252zAvgm1IZur2CCLTCKhb6ZWsf7PvJ8V2KITh+pLuulsmBL3opSy5dIBB/i+zZNDNw426VPzXh+Pnj3DvDfMHlN2lcCYogkKf1yaBT8eAbU4u/SkURSJmP19vzPnjc4MLvgSt4nrycI55vwEPC7wzExRFoB+2RttNj4PHLFilyVwk07bx2+0WGr5DHevK2dV0j0C9psZLru8Fpw8x8TqUQSMBrIrBCE3xMQ+g6czqBOMKD3XsPgQ+pr8nKzCCQBYX/CNMF8EiX14FCNwhU3SXhoHID/Lp2iPzDHAJJutHs838Gfk9ApF0mF5/fK2tJZZ/BKR+mzR7mEeiQ29sjf3+CO0b+qBIqJBDf987LBlv7//m3qfB1WXcIFKDerHlTDpxmcsCI5T6B5hNtIv6Ygeeknrpwuhjvr6ORiuNJ8MGNefndDwkUzxlq2pAAHnJqvk6hFM+nsu+JbDH4lrT5vqtl+NzJu5sVtYJPrNf6OVxBoCpuGY5dk+BPSTGbFKoIFL7hGOk287d//rksTiHsOT7X1oYtIkLgORu3HGmqIdAGa5mUCh1w2rd/c5hqCeS1O0pF/yh4XqLMzP46Ammvab83eBFcoOm+2bkGvI/f7n0MzQVnOuTXVtyE5//99c3dteArd3N8el8T6N3gr5W3/eBz/OYS9K0EGv7CO3huCfzO3trNwu8IpKSazcnJNvDP1XeLCOh9INC1OjmSPy946sMvbi7tBLr32NurUxz80YrUl4AOAoXV+kbsVQWXd7wWGdVFoOtHT8tkGYLzLPr5Jn8ikBnL0+O0DuBlzXYZmT34vOsk7fH2BKcVbWfO7iXQ0Y0udp+DwIve+ddlfiVQxM+kFd0r4GbHplqSv+F10y5ge3od/HPomGD0IIFU1fZcELsDziwt1Hv2O4FC9O7r5FaCy5H9pl1HCKS/bcSRqxk8yvb2If0xAs18iX2e3A2uOnZNWWyCQB+PHLfbMAqe0igeyjxFIAljG8mrP8DL4zwUBqdxnAgh2Q0Mg//chVXTpXyWQH2J252St4DHMtQxXSYTSNh9rpBzD3gr7ZKEKQX3A73fmW7JgVcys/VwzBNo6AZHoMh+8O1Ht7P1/MB5ntxEKjMH3+Zt+jHtF4G63mt4aLmCy+qOiZr+JpDUmsHu9lPguvd28DIsEqhBYavikXDwU4XqJeV/CTS20zHsZyL4kmv6d5dlAt1N0LkfewvcfDSsjmUNBdH5nX606xE4XY+9aTENBZ1lTI1+/hKcySAuyYiOghQ6Topbf1g1T79LCWP0FFTR9CWF0g/OeKFc/wIjBX3UqHqWOAu+cCDnzQZmCtLbSZ8uvQyuKVG7+SYLHqejYdfH9UMwz8Y8CZG1FMRuz2FzhhecqewTz8N1FORjJSCxXQK82ps8Ks1GQS7rpXNqVcGN/kZdK2GnoAdnIvOOGYELdajtEt5IQR6yMXs3OYLHJVbkZG+ioLzMEtMaL3CaD1nr2LdQkH9V4NTxc+C7KVmnQrZSUPjB0DWcseBffhzvGOGgIOZmzyvNmeAMqEbRkJOCTmr/CA28B37Pxyz/ARcFHYmf/Cr6DPyR9OgOVm4KurxOOLv/DbgENyo+wkNBrc03KpN7wA3P7baq4sXzsdEXMpgAfy3rzLOWj4JY+tAozW9w9ms1zHb8eN0oebPPmL//c5LkZv68nRQUVHRP5QwnONEqd2xiFwW5e2Y2SAuDG0n8GhXbQ0FhSy2RM4rgQcuKtz0FKOiUe8G5+3rgx5503CwQpKADX/OyPW3AbbzvjfQJUdDVZ2Zjoh7gur05QRtE8HcdNbSYDgBnEUtz0RClINt96n0lkeCTY2fzvMUoqCNiPOR0Gnj3hIROqjgFEdZc0oqF4Ewa+UbPJChoIfwR+W85OM+ONy97JfE4QTlV9Y3gkS1x+b+lKKhbffhybBe4asLgmi0yFDSnk2xqOQJ+o+D5F1FZCvI9/G7Ljh/gjrIbldTlKEg4r+HdOP0w1FPJLzuM5SnozMHnAWVbwLcf3pBqr0BB9x7SrQ3fA77B+OGtI3spyGTjmkhjeXBthTK944oUxJG+6zuPNnj6Mm+ilxIFXROe4Z22ADdWmAn1VKagl1aETPURcMrSbl53FXxeVNu2x/uBh65v8nHeh9ffR6XT+RL44K3PZy1UKSiqnWQnkwxe5O+qqaNGQVxXXxbR54GPVXu1yalTkPVsVNXnUnAD3mVRPkRBcep7Y4vrwGVz99gwaVBQ77MmzksfwVnKpuynsS+d0Ha2GwLP53JRfa+J94X7jY00BfzNaDJNsRYF3ec5T8NMO/LP3walPIreT0HpBuk2AxvBjfz8TVy0KUh+yNG6aic460Pd4b06+Jx67PyTJAPer8p3hkWXgkJjdJGPJni93WbmHuzea1V3HTADXz6mnFegR0FqN0Nv7nYBPzRzx8j3AAV1ddx4snISPPFiMOtefQrSnRd36AsD9+luHvqNnXmmO6kqEdzx9v3eZwYUJChtYpN+Czw9X3Mx0BDn1QybgjOPwE0yCvXkjSgo2fxlkGUteK7cQtM09iOVru1ybeDKHFahtw9S0JSy2N3NA+BprX0BVsYUVK7LvjxHAv9Y8/AJgwmep8imd50r4G0SpH1PsMuT9m+uYB/9569EarY6m+LxjV+9S+cD77+oqsdoRkGPrzz5HSQFvr8usfs+djMz0xRHBN7O0//G2Byfxwc9mcgEfMlNX4iEfXdvNuvuQ+BnaRbm4yxwHdn3a4DRFzy9g11Z2JKCJKWMuKcugJ+Trvxdiz1ima3yQwJ4y5stajZWFLTjZc3jshxw9iwTlins44pDzJkl4IWdCUdDrClIpWnjs9AX4AqNvy3X2lDQB62ZOrf34MWvKgfSsT8b5d9p1L/qe9eS1++yxedU+uhH2Vlwnco3Q3exa74O6uRaBt8T7+UmZYfzkruUAA3b2D/nml3MKsVeWe5UN84LvlJ6K07OHp/ffeN32yTAWdaFqpVi/6ZU0/NUDdzT+XmZpAMFaSd1meQeBI/hD1q4g31LqTxrjBN4bdkXtp2OFET2GWf08wG/oUWznIb9yySztuN58PqEdW9ZnSjoRPjTlzrx4H7t20NDsBO5uwOlssEfxB7gncau/TTMi6sYnM/h0QM7ZwoqZN9wna4GfPatp1wjdpsK7r8zb8HNpRIqJQ/heHb5lfq5D1zHVRKlYec3XnO0fhpcq8ixbRF7m3D20ZK/4ConhU4dOkxBv6bU0jLWjf/zdxKZQq+wdzc4/IrgAZ/hqfnN74Lr5o/AyJPi4AubU2cuYPer5NdyVAX3MNnN0oudj3dM+IARuKi6m7mCK87z88eU5R3BGw9afojHvumO4Wl+b3CNipHLw9iP7VT7uC4EnEaXNUT5CAWl3p2z+R0Lfl2ipDIO+2CLBO1oFnhc61P1fux1MqUfPt4HFwtct03yKAW1x5u8fPkc/JhZpG4I9rTTfR8etIK/Zlz++Bq7jpLimsxecPsCnbrNbjj++3RMoqbAG46IbHfCvnPox3P/xVXPn/AdyMeuK6eq47p24p/rPfm0fQq77Jqtkybc4A0l3B+k3Cko8talu2pi4M6Ks7R+2C/4JV0U2wd+wGDxeRl2x1pzfy5D8LpPYyvz2D+n9Z1ncgCPu2rWKeeB1/Ohcc4PT/Czxe/VT2G/bfS+83sw+PqmGe1i7Gu3R/F/jAH3SlaYHsMewnY/rDYTXL9uj8rOY7j/MTw9X3IP3PyljLwd9jtruM9lPwPviGj5dhV7vd7E5rgW8L5jllqN2FNZhV4EfwGfnhJz+Y29YHB30PFJcLXofE3x4xS05qe8tu0f8JZw5gkn7IVDZTv0WCf/uWDldccE7DvT6Jj3bgfX9ovLrcFuIB+5skcUXFVjY80UdpWFQvotKuBSzw3KOD1x/ufo4qAzAHc9bh6njX3PzQgFih14ToKigS/2kcOShwePg8/Qr1CuY3dsNUlrCwJv3ZoX+wq700fPTy+vgL+13Mw1gV25nWH3wwzw9+fkb7F7UZDFifuBOXfByw8MCChgXxM6+Sm+CrzGcaTEDnvFlJXG+Tfgh3mZNM5jj0mJeOzdA96etvT1Jnb6vRvFHCfAtxw+E/8Ku65x5gPD3+C3w9gthrAn09Yp7GOZ+uclNi5ytN4UJM4g2STKBf4rYl52J/bEc1FO20XAFTt0rRH2HSPBiyzK4Lv2tOQ6YueifXrz9wHw307DXEHYNzwn9CdswR/bk+pSsD9m7v/9+Rh43mel3IfY6foUHr4OBH/hTVv1BvtapvLjT6PB5QPC2b5j/yqwXeTOdfCrm78VLGLnjhacSb8DvpNL6dJmHwoa3p5THvUUvIw5+54odmkLvYtnX4P7sG7i18R+k3PK3OMzeMNowpg19qePLIVsxsEDaFbovbFn3TNb0V0AP2ylGRKGXbD18Ze9zNP/XOCUsFkK9ujfulWCnOCX/IOjirAbiY9kcgiD72cjdj3D3m7tGsqoBP4gWFnoLXYlmzT3n3rgdhfn079irxm2Nx21AXcPqgicxR51IVa12wO8V53p3TL2IXsGsaaz4JqqrtfZTlDQhHURd0UUuK3b3n5e7DdHzdgK08EHFEdzxbGfZBijTSsCP/W8eVQFO7+Qwe/LleDm4XseHaC6yGHiTDO4U74yjTV2Y232KbdPq8Z/rfjVFTvnivqo1Rh4GM9+PV/sDPyfh3R+gfNb+2mdw377VsOAAtMM1JfyjvZI7G9vkb4JbAO/Sn9k4Rp2F3udga1C4JEpm6tuYDfY+mSQQRE8X6OVowj7d26h4R+64BXeR7Y8xl7/MHFsxBrciuFu2TPsncvfprrcwUdDHf/UY//AyUg0BoDf/yIz/pb6XSPzP8sjwX/eaAvrwh7BeXOpIA087FNH01fsseIL9GmF4IwCLdUj2C2s5tdFVoCL3ldwm8EuGBS9NaAJvIk7rm4ee7PQvR3u3eDlFXs/LWIXSjIRth4FVzBKKqD1pSDXi76yuj/B/yCSFAv29ZY0ansZZ/85Q/y1QHbszdN/9QQ5wF1aHoVvxb653N6CQxC8SzrwIDf2oGubDzHuBX+Qy9jPj32ql9/rpw54QckJBUHsnk4hZ0etwAXyKqzEsM/p8Ud0u4E/S/isIY09T5rpWtMZcCazugV57LtZxXMqLoPvLLIKVcZuwBdzvzAV3FPlWLca9pX1vFVpBeCUR/Urmtgt6waaIsvBXV8KLOlg/3SqvTOgETxQVaNNH/uu9Kkh9y7w9Xurgg9ivz4jRliPgBcziS2bYnfyubqi+wO89vQeR0vsIXqb2RQZSFBPnwqn2WDXHirjEdoKPv3kYbE99rauU2LbBMB1fwvkO2F/Oa6nwqQA3kpMBx/GzrVeQf+XNvivv/ZyR7A7OynajlmCv7z2/L0b9ldcBz0+HQW/6mJifAx7dIF/QLM/eEuI0RNP7GkRDy5XRoBXBfYve2PnsJtLKUoBH04TlPXFfnBQLz89f9XzM/uMT2GP+3HnSVQZeFCSmKUfdR0it9afbQA/0LCgfQb73sy4jx6d4Jac2TvPYm8yWj9kMww+V8g8FYjd7W0aoTcPflt51+1g6nvFU9bw0JKhfwhq1gvBHp97mHkLK7gm/7u+89hb/KU3rNsEriqw4hKKvcKRjpN+OziZzP85DPtWjh6+vzvB/eJm0EXswUceC82LgC9+3JZ5CfvbdXFS0zLg1nkGYxHYu/qPKQ4rg1/dKCIcif3rPT3UpwledN3YKQq7rq6wXqc+uJeRSVQ0doUYVpO3ZuD6a58WXsGuZTFr3WAHLvWIrToGu0h4h3O1C7iP9sfmWOxRP6vcy46DJ8qca4nDnnU998SDU+B6fuca4rGzmMQE5AeBozfqFQnYC+n8L9wIB2ecEL11FbvebefIlCvgEw9vXkzEnsJpkBB3DbzT8pfTNex9VnvTIjLAZTMjZZOwUwx254Tkgr9bubEmGfvayQ2F/nfB8+YjXlM9U3Cl2PsxeBVzREwKdqUfM+VHq8B7dvTqplLXwfBrjeMrcIWcpiWqc/G/a7R8A96fd+FhGnYHz5p3Ru3gNPKKjunYL+4q6dLuAe/25Ke/jj1A8+ZX1UFwoWL3IqrX1yaOyE+AO36W1c2gntPMizPiBDjp1L0Bqnu98f+x5/eqeXaTAjKxXzngscRDQ/xzB/ddLFnYT2y2Z9jKAh5Z7pxOdUbBg+vXbwT/XfZi5w3s6SEaWxm4wEW+2d2hesVmed4lfvBCFx2xbOzq40ICP4TBm3VS7lHd8Be3xIw0+FK6jWAOdhn1DQojSuCt8Tk5VD/7jF7tqwY4uhew+Sb29uO/tbsOgP8amIqgOpfBrNE7U/CcSuY5qhvbfbdstAXvcet2ukXNA6mfHWsOgz+cc2ykOtvSu6Plx8AdrfNEcrHvTKj3Lj4Jnhn7MIbqwnpV/gWB4FZPIsepniH4MCQ7DPyzkMT+29gXRAsiUqPBXVMKM6nebZ4VF58ILsf6c5bq729cS7l8HZx5yw6NPOyXmaJvnL8FzvqaP4Hqhdcu5J+5Ay79eeUz1YeVzzzweQTOl1vNn4/957JXmdtT8DhFWzeqp39zrXaqBRfy7yikeuQXuwar1+DCy5IjVI+YNX17sA083NKLvwC7xfYDnTqfwT91RdtSvdIR9akNgBs1R8VTPaBs77DCOPg++2MvqW7DLzktQQZfeCQ6S3X+mwLzAgvgj4fecxVS67UU71/eNZR/Hr1sqUX1yLYt9BzM4Ivrazyo/iRs3Tq2DeA1HEwxVB9Vp9/CyAnOwiN39z9n+cu9zAeewafZSPWQgbndP4XAdXbJ9FPd99WU2KwU+Ik9dPNUj7r/XW5UEXyfYCVjEbV+Zffu60fgT4UOclBdN61jf7ce+Lhw4y6qn09pNXxvAv5WhE+c6gtp9RZNNuBHRR1kqR5247nDi0Pgj0SDFKjel/fkSIXH//XO+/e9Snz/7zjST/L8Cs/+3/c+fZp1Lif0/85T7nnypbSo//tdnlWxsQlXwVX/dx32lF5KjkwH9//fdRPJP5d14Sa44/+us2aCX15AEfjY/+6LvK/X/RMPwUn/u48tOkeeuFeCb+b6n31v2eDw3Pkl+LnN/xMnS+/N662bwX1Yrf6LK9FQg1bjD+Alf/4nDrn4tTp0P4HH9v9P3F57pNyr/g088sH/xLmDlMz3vWPg562i/zsXalnCU5IkcK26K/+doxUK35zgL/DwNu//zp2HwrbFHSvgA8Yy/51TVRc2um1McxBvC93/nev9ZxjWsrODk3yc/ssDGif/bmLaBs4s0/A/ecN0bvvKDnDTTNYeap4R4Jjc9UsQnKNd6r+8FPtiQJQkCV5QK/tfHvt+4JPs2F5w23WbSNS8N/zknco3dXBF2rf/5UmN5XqtT7rg3HHO/+XVXMFnBh+MwXX5mv/Lw/fFHpk3W4MH3qONpfrC2kL7l87gpy+uF6U6Z1OWa6U7+ITR9//qQrztNc+HJ8CJiQvOVG95FXm6KAC83eHLf3VHek1I8M0L4IbFs5epvm7TqYvpkeD23U+2UD35h1vM1QRwm5v8t6h1sP+OfVJUGnjGRVFhqo+JmGSG5oCHxzU+oNbZywH7b58tBF+jMixBdfc4xXu+JeCpVmfvU+s463GxUo8K8HcffQSoXsvC9+zQC3CLO2VZ1D4hy2tTnU0TeNqdvWxU941laDF5D77Tri+E2oe8dlto1+sGL30dO0btWwZ+TvagfvBdR4WNqZ6p8nVQcRRcpyXpEbUvOiP+YUJqFrwp5w4b1cOaawmhn+BijtrHqH2XBWPpb75l8PUCajXUPm1p6DYNJ+P8P89NcV9P9QXrZJYNbOCPEhJt/+v3HC5tZOYAX8celUPtG8PHTnOt2QGev7DxG7XPjJpz2bkgAK47PM9F9cIzpiJkCXBh0qwxtY/1OKIuM66w6vkrz85T+17dx2LKA2rgt/avL6T2yVnmnJqfdcBP5KQ3U/vqYGV6/baD4Dqf6IeofXiqNcn0tRW4UuWfeWrfzpXRY1vrBP7nMNcaqkfP1h1+6ga+tGORltr/X9W6f+yRD3iKjPwS9R7x+ULSyTtnwDdmm89S7x19MYGBt86Dj/762kW9p9wzdAq7fhm8QcnmCfVeU5KnEZ0YD14ToRRJvQf5nt6VGJ0K7ro0f/Ayta9Lob0elg0+nrDAQr1P7R0auBlYAG74oqiKei87KFNTdLIY/NLZQ47h1HgzT394rBz8Va8/Qb33FWzyrTxcA/6BXSHwArU/VNZ+adsIns46QqLeK/mjOZpN36363iOvbM5hN68eeX+gCzx893JJEPbm2MfdGl/BMxKb5qn33FcFQf1KI+D1NGrCAdgZS9VGpWdWjVMcfMAfOzJdmhH+AX7h3FXL09T42fb0B/8SeFx3uOFJ7N4pPkucDD/+eVSosfgJ7A8MeBk2rgeXchn/4YW963HTOpat4FvdlIqOY7+tcHwLDS/4E31e5IG9QZ6e5/ce8BdBXtVHqfGwkrabEAfvGp7mdcXu+plfbEIePLbnsOshah9FuiU7qAo+M3Au2pG6Pkc5VHq0wS9kjSXYYZ/WDtNsN1r13pta/tbYz0Z/PfDGElzJnl/RAvuuTRKmrxzBd5KYu02wHyv2sak6Cn6JN8jEiBrn63KcH3uD/9o9lHsAu9Prare7/uBE4d1Wbeq5dnjtnRsCnnFdpFUDO/3ul34ZEeCyux7lqGLvdrgZfC0OfPPVUG0lap3l8wi/kgIuqfz+mRz2Z0e3RIffWDX/s00rktidF/ITgvLBe2IjN4pS+41QjtRTD1btVzr/7B5qH3vaPet4Gfiu2MxkPuyCPEm5LtXgddtnV7iwRySnFdk1gHeXMctswV5afbLY7O2q+Qe27mGj9o37eZ/od4KXia3tYcJulXn9qWYf+COlREMa7Nfn+muUh8GZ8zmC/5ygoBjN6TqZaXAWVmPXOexsMtXNIvPgAZk9NNPYdQQN3u78C352q6n1MPYKpWttXPQ//7n8m31OfdgPSsV1blwHvi5x+5ZO7HIhCp9ZtoDrfXAKbMV+WSmql4YHXDzAM6oO+1e+c/2/d4N7L11Xr8L+NJZ1kBADf+2ukPUQ++MTkt8n5MD7VUMzC7AnmnwbHtwHzpl8VzkLu6z21tGe/eAPGHrPJGLXnm4ebTcEL6qSMLqMvcNrdvSNBfhfx4dVQdiL3UJHXzmApwu6PPfBnvLj5EjVEXD/bkVjF+y6955+f+wFXl7O7WuJ3TLUcPCuH3hV2vh2PexN3bz9uefAFbt8jJWp45/e/SXjEriD9QlGMervHT4mXddiwYeibyEe7PJ7Uz5cSQZXcSv5uQ47S8T31+FZ4Hd9FISXfCjorYXkq6A88DMlTW3T2AX6jz49dR+c+8XodC923cSAkuNPwLNq1ge1YJ+jM89zeQ7+zbbo1FPsdr+G0+zqwS2bN3UUYL+vzXPFrBX8+dvbGUnYr/R8D9LvALd4lv3qAnbJEsHjmr3g7ifV9Dyxu1W/t1b+Du54+KGgFXa9nw1aMlPgh69ucUTYX6oS4iJz4C8ywr8LY++yUtm6cxGcpXL56Ubq80OXFznpfkEf8jLq829vCnpu9fTbhrXgDtLr1Aexl4yVvWLeDO6413ekGXtsvFPuGm7wktKolmLsF2eSLizsAhfT5Z9Iwv7bQt6OLApOOPxSPYtd7w6fzLgseLnCy1f22DVdZBgHVMCv/eb1U6O+N0j78yctcPNXxUZ82J8ckS36YABudf+v/hrq76fLH083m4OTp+PcB7woqCryr8pLe/Azo53ZL7FfSLi0UuEKXq+EprKx10+r1JZ4gp/uEzU4h92udC6k8DR4sspUuQ328zznFXKCwRn1XovIYc+Myp9IvQjudmP51nrs/S4KGfEx4DEZLznGPCkoj/f3/stJ4IVhMpEvsZfsrpwIyQSfT/edTMOu2ygf438b/KdhjLoPdgFJBQHve+AGFlHntbBrWQc9O1IKvtzhcpsDe8jcS32HZ+BHY1jvTBynID6vxo/mdeAWhMeV59j16/dbGbSAN3lZa8Zh35tCadP8CF7ne6fFAbvP70gd5S/gfqWC/KLY2y4+KZUeWvVeq0TVX8coKE1AmFN4Evz5lqzt9dglJJLO8FHADwfMlcVjZxC/0cLxZ9U6/FZltMFuMD3DwUa78M8T9Tex8GGPPCxuz8AKzuTF8HTEA+eflN/JfzeCdxM319/HrnNjvn6OC9xL5gi9L/V/JlFVE5M7wT/6vk6TwW5mMkg/JAJ+j1PzJcUd94fNNFt7ZMCNyXsDS7GfTCjmalMGF9ZbV30Se8uy36ZmTXAhCZ7LEtiZdgwu1+iD6xY8ezfuhutI/Pn+MrNV4/TIJ97G/jr4/aP7duBNRu1N9ti1rlqdue2y6vlNbV4bsf8YSBTLOA4useQZ1HSUgk4N/fl49RS4+6euiSDs2y1YvSKDwP8kq1eKYfeQkp0LCQfPvvSut/cIBQnnDnr6XQFPiy4wi8H+iXSp/fg18A6D4U2K2CknwwQPZ4Cv9b7NNeSK77mBKsetc8Fnns8disXOoL8xw+guuLn32DdZ6v+yGA6Xaz0GP6MTnfzZBdfxnPM1SlXgHF/6/EOo/wd7U/1I8hV4zPOx8zuwe0x4Jex5A36zuOjOi8O4zjJ0WW1vB9f4so3kiD35qRrjhh7wZnppw9+HKOg9/1gOwyB4f/VwRTL23I/r+RbHwYcThcTFse94M3GZTAYvQWP5dc44/9iUfBxZAE+ZYOe2wX5tewx975rf0HdpxEZPOOH4nCzc3sYMvvepxlgQ9uBWkS2NG8DflW6VYcauPyhLruJc5Q9nDqU44vN16GtxCT+41dl7Pjuwq55DRnnC4Dw64paFDvhec8izJV0afI4wWy+OvXG7p1CcEvgw9++kh/YUNJSm4xqmAT5ptNwvjV09cjnI/wC4Er/a1EM7CvKyveZzzBSc1j3xsTh2ktiPfY624J90PooV2eI8U8s9bHIYPPBQnwUf9nfHiaP7j4ErT0btTrXBcUXjVLP3JPjIx+IUZuy7P6NpkUBwsc+CuUHWFDRz/wyZJwz8akGr1rgV7qvTOl+zR4MPTfv7WWL/SiPhT5sIrnFhUfyFJV7PTH1iPh0801npuAD2Rxok9bGb4E199LtiLCgoaqnPoacIXKhAxWzaHOcBSqtu60Pw0Y4nZEPsOca+y9WV4J8ZDP/cMaOgWjX/8JKX4OzHej3osHd8DX9/sxlcvklDzsEU39eklIcTP4CXp9tYPzKhIFZWhVfhn8DH1y610GJnWct69PQ3cImt7LHmxrjvjdVtdR0Dl/PzTrx5ENe7q6d/mJPAz1bPd04YUdClZ+yDWr/AN3lEm8tgf6ORESe7Ak60MdMFGOL71OdLP3cy/YH8o2c7UGmA733Farwb2cF92e2Hf+pTUIa55MoKB/iwJ4VZDntYaUXm7A5whVzGA94HKEiKXma2TxBcnOF81m09Cgp9Tv7VIgneuqi61KVLQenntCqe7gWfpZXyYMTOyOItVKgOvuapaoecDgUN73ugn6wL/rTfdJ+zNgXNEyrcYcbg8x42GZf34zq7Rj/T2xr8fqDa2F0tCuISXtNo6wy+cJLY0aqJ+w26Sxna7uDac64qExoUNL40vVX6BHjM1EU5euwDmuZK3AGr5pO2n54H4b6r+OUyw4VV6xBzvVBanYKIBhUP8mVww+cBW7TUKKj69ivfL/HgylGdeqaqFHRk2oCjIRW85NldFYd9FPSwvtG2OBt8JoM06qpCQTZVXAppBeDfxm/peijj/PZS8O6FYvDDc1UWx5So99/GUvdy8LpUJWZ3RbzODo0mxjXg2To8zof3UpCDNvm8QiM4Zbu7iY0CBS02Me7jeQf+ooez20Ae34/mXkXQdoGz/1WaVpGjIJHpj7bjfeCPq9/GCslS0K+uobJ3w+DXdvWVbJDBfcv7pLTSafDJdadMfkpREPnrucW0eXBzjXSPz5L4XExKDgb/BX/j70hUSOB7xwN5HWf6RciHR9tGr4njPi13vYDmOvDer/Rax8UoCNHIXti9BfxG+/olVVFc7x5vNGbgAZc+TrNpvQiuy/u2JI3uBrfiWgjuEaKgPy+u6zWLgWs9XSd7W5CClCZ/eBXJgdOnOsp4CODvmgn6G7kP3DeRyU94DwVx+3v+dNsPXqgoTYzsoiD/NHobbUNw/YHFgps7cT7sCuHeZQGu2pQUa8WP+9UNKxor9uBbxfhvMPHhenSupKHXFVzw7Mf2cl4KOnqjIK/SE1zUsVfwMA8FHVT/+SXpNHj8b99URm68nr53PXyCwU1p32y7y0VBRUEvdfUurnp+eNcdPU4KKv8qdYY/BjyRUqMxxEFBd40nSAvXwGPj+3sDt+K+q6T9SVsG+Gezd35rt1DQMnNTTVEu+FvtT7SZmyhoX2om64W74GvpjS/t2UhBkw+3p1s8Brf8GUW6x05Bh/qYDwtXgT86P6ApwYbrWv0O17+14IuiT/3vr6OgE3vXZ354DX6H4n9RYC3uQ8RC6G+3gZe4XnTLYsH728Ca4/cZ/HKPGed6ZgqaMjU5oj0Avu2FfWowI+5bjD+ZbhkHj366/dN3egpqPSl05DsJvG5q6+cDdLjfK3ye9vjXqjiR+pR0lwa/l5tp/MIK+GtDMg3jGgqi0fO3MGT6+8+zZP/wOS8TSHPyaBcHO/gf1dSxx38JZM0n6znIAT7jdtyCZpFAhYfE2e7vAL8VKehs9JtAAglZNX6C4N5JEbTJvwg0TfPSf58kOPnj/n1dPwgUc+2dFO1ecOE9EnSb5wm07eaPyWY18NPSm6yMKARiFnC6HacDHv3gnVg4mUD19TvNTQ+COyXvv/h4lkA/P9j+3GQFPuziYvF1mkCPXdhjOx3Bn5rvyKSfIpDuUYN1qUfB72acMxOaINBcIWOApTe44M0If50xApnOKjVs8ge/vM9k2XmEQHGM7ykfzoGLUhYn/L4TyK/73lLspVXPi1fIRgwSSM/vwYBuLPiIf1nH1W8EclW4k74mGXzXY6XXaV8J9OCd146qTPC1TolrM3oJ9M2h5uTJ2+A3GrZkpPUQKOeyQ4zgPfAhNTHvq58IZJmw5N77GDzSVSfsUheBhn0taK9WgZMODLad7iAQzzyDreYr8M/VV+yc2vH+vq84QnkNbnG2e+v+DwRyrlqz83YbOJe1N82edwRSjT8ba/oZnClpaduaVgKdcLmTs/QNvGZe3+rTa7yPhVzWd8fAldbzld9tIlCKrmGxBQnc9oit3NkGAi28qLj59ye45L1vraiOQJf3fxDOXwZnJB4E09US6HovjbYB49I/Z+5o2ldXg8/FxfLp2fXgRwu01oY8J9ApXcMdSVvBKXnaI9JVBIr32tEpxwsuy7OmaaCCQDYxESyde8Bz0yrvxpYRSLL0XdVpcXD75eo4mVICpcZoD7DLg/9sOuX18SGBlv0lA+/vA3+wQU/rRDGB3pe0hujsB7/TUrOe4T7+Lj+bia8G4Nkd7i1pdwgUzsdc5W8OnsT53X93IYHazdjHWOzBvz/+znI/j0C57Jknsl3AQ5dFIiVycR4YbTOQOg5+qCZq9F4OgTZu+Bzw8iS4gsA3od03CHQu+cPMwcBV3/tnl15aBoF6j3fc+xIKPn/bWpM+nUDnby3ecYsCd1JO2OyTQqAf5xy/zyaAt9+YfdZ2jUBMWYxWAWngx8KK5aWuEiiCi+n3Yja4Z+DGC9FxBNr6xKMltACckfF0St8VAlFGJBtoisEjchXPiEURKGHr4cHwMnCa+l7eMxEE2lO8yLOmGvztxHhsVTiBNLRWToXUgwfe/lO9cIFAMpVuvT9bwF/F1pTIhhAowEnI0vcjuJU9ydkjiED8nCqfRnrAc3qdW9MCCCR74doh+0Hw/F9TRK0fXoelHeNvx8G3lUa1jZwk0NM/7V5qZPAiUXk3hhMESlpIH7n/C7z0Bn0JnxfOG+WOppwr4K7OvHfljxEImbEWXWRchn7s2xNLbTecB3yuDE+uB39VyPbQ2JVArJav6My2gnuYXa6wOESg0S3XV8p4wMkJYcctHAnUV0z5yLEHXIwvuOmgHYFuipUHBoiBj73/26plTaD77+qmOmTBE/zzA2UtCPRVZFlQSgX8xDRvK48pgeRN9QWiNcFrtwjV0RwkUNns5cH+A+AubxIcB/UJdPJMqrWcKbj2N/mM57p4PVXsQi/bgKfzsZ5N3I/z9s1S6y5n8JtaG34c0iDQPrlLn3a5g+tO2m0SVSNQcs+Dvz4+4IdvsL6fVSbQ2MzGVxX+4NnV1kIlewmUfyyVb+kcuFDkJd5jcgSio+ferHkJfIR+7CGPNM6fh6PSLsaA27KNf20Vx/VavDb/1TVwOpXlwjMiBJrQeqC0fB3crOcx63ZBAul/ljuodAt8ajaLuWoX3scMja++ReCuAu63zPkI1NJZ8z2/BJynsaV9lJtA7JnXHT6Vg/vdTblxhhPXo+8vEVMN+KT8zTUrWwg0XrEnVr5hVfxody9d3EigAsNnSodawe127k2hYSPQMfGA/VEfwatPt9YHs+K85GBa+KAH/Lv4k7hZRgKx+O13/DCwKg5Dt5Mc6Qgk0Wp0mDQG/qtBfapxhYy40r2L15HAi4/7hIv8JaNapkJ1oZ/guV/oSqMWyGi/1wobWgKf8/I9PzBPRouGF7ks6Vf++SUNiWE5gozyE/bZua8FT5JqGQ2fIaN7V/e9ObMJvO/O0OWWCTIKR2lHL3KB70rfVbd+lIwY1Y8IxvGDS2jq3DAcIqOR+RqWZCFwC5GtWyP6yYh41MiSLgnuP+UlUfmFjM48y955XQE8nEt2dLibjNy9fYzSVMFjOA5prO8go0sGhy9f2w/uRF5Qlf5ARrochc1XDMCfKG75erCVjB4PnWYLNQP/2d2x070Zz1NwxfKULfiDsWPrgurJKOJDVNrhQ6vWLXJTTuRLMuo2Nn5v5A6+rZD3c8JzMnp4//ovBR/wwIHh59cqyWjr1cfrefzBI/TaDK4+IaMi0/G1K8HgovJWkVEPyaiR5tpMfzh4wZafvsH38feepS95Hg3+UVmL5VgRGXlY3DqQehX8YV6XhWkeGf1hbX7qlQbO/87WTO4mGanMfvutnr1q/mfD6DZmkdGUuA0Tez64nN9674k0Mur/kt3Xew+c8HkbV51ERsJzImcKHoNfeZrqEZNARkftA956PV21X5sOLpvH4Pl8o+2XfAlu6TdozhFJRpHqlgWzjeChHUYeneFkZMc9z3v/Lfj+n8lq8efJSJzh1P6jHeC/ZJs+aQSREcNp543bv4A/Ul9SJPmTkXW15aW3A+Brfzoevn6SjJz5iJRzY6viVmizhao3GbWXdmkKzYLTONps6vUgowa3u5c/zIM/zve85X8Ex8/CNkf/RXB31/QV5kNktObvsQFWmjUa/9/1NsnIXrfH8WzX9MmOHryeM0VllzUZXdxOs6mICXxXvAB3kRkZTeQsxFFYwZ0YLLoFD5KRelaCriobuLZr0oncA2SksKVINWIjOJHlMsqhTUbKdsI+LVvA4xJ0NaIQGVUv/+li4wQ/3Pz+AkWFjCQ/s5wx4wY/aH4133YvGeUSmgeSdoDfiNpTViVDRpxXkg627wRX/SLzaKsEGUUxzVxkEwC/UOiS5S1MRjG/tUf1hcFNadwCX+wmo09MiWcuiYFzR8/pr+Ujo9OkRsnnkqu+V6Z1k8V2MroTNMBOyICf4n3UlbqVjL759XIIKIDfOu6d2rGBjLSKyjRtlMAFaNss160jI/02r4SofeC3Ax5xaDCRkXwa7WK5OvjaD+NfT9CS0bmLIZeHNMGz6kvtZRZJSGWhX2y9Drih9Qf2cwQJFYvJTCscAD9r+Hfg2RgJVXCFNDgagvPrc3aSv5JQZGhLabgxeLLjWhJPJwl5fhQuzzcD73vSpIhaSKhBseBNoyU4j712mU0tCSmdN5kdtgFv/xnp6V5BQhwblXfSOoBvScw47PWAhGgX/Q/zOoN/MLl6w/02CY12bru31wV81PDSHtvrJCTcoPj34FFwMzNc1BNISMpv2vKIBzhf6YL0jggS2rfWpDTAE9yKo/sVJYiEYiSDN0X7gN81OV5Z40tCvZQrfuknwdmlKdtC3Uhof19WR77fqn05Ujmx14GE3D+/l34UAN6szyg3YkpCLCr7r1QFgff2yP65oou9fHtvbQh47YV0HQFVEnpqH7inKRT861IKd6UMCd1ICzvy5iL4Nqeki0iIhFLF7NJaLoO/b/0b9oKHhI7LiDx/Ew0umqDHK7+JhJ5s4mprigW/NjnldIuJhGRizTteJYALcx3Xp1uaRScK19Q/uwa+V0F71JEyi+pemGQ/Tlnl0sz7isdmUWGIz+HC9FXx1qRjPN83i0y7o1kzMsF3nEkWlP04i66xf8y4kg1ufyq+xb15Fv2oCl4XeGvVvtzq0kiqnkVby8sPH80D/3ttc2LZ41nEJVWZYly4Kj+cnX/xrnAWHSkoK9x7F7xop1jn16xZZDMynMLzAHxxwbd7OHEWqa0Pc1rzcFXe+BP2dujyLFKMf7k8+Bg8p3RnzafgWbRfuD/gVRn4LyXuh/W+s+jAj20NOZXgm8RV7xYenUW7D98bDnoGLl5sWxpmN4tqRDu7zWvAVxwM2s2MZxHvia7rIrXgiebkddv3z6KgLJLwct2qfMsv5d2jOIsMz7tdbmsEZ35D/nFVfBa5Kp17cOs1uPGzPY/Vds6iOaOAGydawePfvcwf2or3MT3bQuU9eKZG9acLrLPonrlyG107OGspl9mmlRn0kiN5Q2sH+BjP123ZczNIp+/HpsRucNfODXJ84zPI8G9xl3kPeExow93rfTMoU4bFZnPfqvG3rr/E0j6DXmdYp7b3gy910zedapxBBytGE+IHwb8btwa1V82gfJ+1WnrD4O/0LxcIl8ygoHWcxcuj4B87HU3P3p5BM7ou759MgE8qh4fXpM2gX8pq+e7T4AeWBDUWY2bQtDedxDYSuEVvVLJ06AxS6Fjn0UiA2zYPXXTym0Ho/RPTU/Or8t7Uua0XPWbQfSnL8e2/wOWKbpjnOMyg9n2G4nW/wftTkjVLTWZQ+oNf2z3+gp+JLpuo2Y/HKasqZVlZtZ6ptuavFGeQGN0ccZeG5p8rbum/WC02gxqbGT/p0YOPFt25+JBvBjlU2h3+zgieprfTLnPzDJLYaB4XwgL+SK9i/XmmGZSVb2O3eR24p1tvkc3iNAr/1NFYxAbe1MEiJUqaRvLFMm3KG8FFDGrvzQ9NI8H3XwPebAYP3nJpV2X3NJJN1H1qzQHesacv+1TLNLq+0ps0yAl+T9Bhz54X06honJ3Bkxv8ZHJqzfvH04hnyGo9mRc86bXgqVMFeHzb3ff8+ME/7Xikuy5jGh2/TuqZ3wW+jq5H52bcNGLul8vyEwCfYjcJEA2bRlaHvKZJQuDqIk3fiv2mUazD5rfHRcH5ry9cEfHALnJfaVAc3Fq4KCTbfhqZ6pVJW0uBP9TNeMliPI24PEtLX8uA6/Jn25/QnEbWV8VqlOTBb9VFWbXKTyNDtjvGhXvBQ1QVnvIL4++6V+q2URlc7mV0zAnuaWRT+HlN8L5V61Pr3VnGNo0KPt3dMaAG/pOnI3uOZhrxPX9as18DPFW5fFb0xxSqvpLZl68FXiu45YP9+BTiNh4LotMBp6lb0L3UO4Uu/1FOOaQHPvLJzzn//RQ6HSotWqUP7qiTw/vi1RQKGvJS2WAEHsiZEddWNoVKrRLrjxqDn38U/6S3CI9jotNQYQrO/rU481vmFHK+rbCP0QL8xF85g774KfQ2lV3Iwgo8i/NIS3vYFPJYjojMtgG3oovaXes3hdhsDG1H7MB7Ts47FblPoeke7ixRR3C7jSwXo+ym0MuMJwd9nMG33xW7fthoChlldZwoPgy+T+jtHVk0hZZnNZYmXcE3Pz9SvSQzhYpbGn4JuIHLjPv3vtozhWLyxJ2cPVbt1/VYttBtU0j+gIF4ynHwZik1ZwXWKTTzZ+5Is9eq+E8T7hj+O4l+x9LTLfiAxxn/PBNPmkQ8/g7MgidXrX+wrYnU0CRSIfWdNjsNPjnNeqylcxJxbzutGey/av1lOl47N0+ig8vMfrcCwIuSw4KnqybRztYUxoZA8P2i05f9Hkyilo/rF4eDwRl6FubmcibRlbJTJnTnwbutk9/5XJtEc/71tHyh4HTSpdyDlyaRUsbaLUrh4ArNVmMHAybRKS3bi8aXVuUTy2jlsmOTaORAjZHrZfCc707cWxzwODaWp/2iwNsOzqf6HJxEYQxqlPArq/KGgl9pLZpEwvM3WuNjwfP+rA1eLzuJCkZvLqXFgzeW/f5hsWcSfft6Nir76qr37gyXSuGYRCayTsdyr62a/3Wy1HvmSfSqOOHm7WTwmZ8319AuTqCifDPx3FTw21fJ96RmJtASG2V9djq47caDSjbf8PO36vanZYB7+4qUBrZPoP2DPO/issD1mmh3pdRPoGP7Xe6GZYOnqB26drd8Amnt+/Xp1E3wubF3LFVFEyjG8qDt4VxwlVujKXUZE6hTr0fEKA9cY1hftSl2AomxcxopFIAbFd9iaTg/gRZ+x7/gLgIX1L3BWO07gfbWNoWt3FmVT3b8VC1xmUBjKVZJA/fAw3J8KzItJlC3YhflxYNV+ZDSHhKuM4GSGMdzM0vA33yZyXBVnECP1ynd9HsE3nU2a5u6yAQy3Hx2Ur8UnLTh2cpm7glU+dD5Em8Z+HKflOPwugkUYvbo+Gz5qvhvntj7cHkcRZgoZFdXghPyvRn+5HEUOv+CN7oKXLZ+KUF+aBzFxwhOmT4Hd11rxk/qGEd87gcZttWsOo+HvtjkN46jHWQe7y8vwDfE5CPLynHk+DCSL6sWnCfy5eDynXFkYxbBZ1cHbqGucSA/cxxZlm7z3tIATtbWOK8dN46+DhswvGsEV47/GvPt/DgqUZKeuti8Kv/sVjl3xnccbdMc4t37Blxy9Jwto8s4+v7lUvZoC/g2lbfiSebj6LWMhmfK21Xvrbeh5dIeR6caDSLQe3BjXuPvmQrjSPDEt6mxD+CbYgd7tglhd9HKjW8HD3iiS77KOY4eydfmS3esWh/LMmk61nHU9r34Z1sneN8v14JTi2OI3H4s/UQ3+OHiONve6TGk/N46iuUz+EK1t6VG/xh6xTHalNsDrn8I5d36MIaSHeKtFXtXnRc/TZO/tWMo/lXr3pY+cD+lR64WpWOIc0T4mH0/uMHK67GCvDFU3Sc/NfZtVTyMvR6fSxlDV/ZF154eBK9MnvZVixxDRzc3jP8ZAtf67ht18ewYEvx17WjY8Kp4uxuvXH9sDGX+zZOnG12VH9xCE1fsxpDdizK7S2Or6t1SSJqi4Rg65xTVuWZiVR4+U23lpTqGRC6NFZybXHUe75z6nCkxhphc776fm1rV/zC8F27aMYb8K/HNfAZcTXeN2Qz7GLr99p1I3+yqcyci77CBBr/3LJ2zEXlVfZRJMpOijCJjbs2ZKmJVvbZB6gbfR5Hm3cuf98yBc7U5irl0jqKgW5/54+fBk2uYdvs3jiLyeoNmyg/waLKt1KWKUTQbS3lr9WtVvOUetU8oGsVxPidbsQB+RFSlJPX6KGL9dubP5j/gfxu/y2dcGUWBtx7s8V0E/6LrvnA9eBSV634sbf4LHtNZS5vqNYqKOUQLeZfBdxdOO8U7jiKFrpWVkyvgvDV9my8eHEUP64pevVpD+88Zb52X9FMfRaTUC9PstOBsW8srD0uNIpeAiXAHOvCTfS5VBvyj6NAPq0v59ODVng5qMhtH0WNGFcokAzhd3qmDW2hHkcrC5jZJJvC5RO+5OcoIqj/mueMkM/jkrnXKbd9H0Jja2/4SFnDWYSbhu50jiCejbdMUK/ihCraWC40jqL+Vo3rPOnD++CZhs4oRRDLQ7XNYD84t9PYgf9EIenGL7UwiG7jlm1Kt6fQRNOAsFF3HDj71+/9xdd/xWP3vH8CpjEIoKUSFrBQiReVURnalbEUhO6KtkpEKIVqyV0YZJSqNy95773Hb+77vxoeofv76navvv8+HB/c5zv0+9zn3uV6vldy590eIjLXHN9K5SNfdTxTduD5CLGw9LrplHelfyzstDzqOEEM9P7O11pNupqfybclshKjSE4CLPKRfTq+5+1FnhDCTjTr+bAPpYemdWz0OjBBf+izt8nlJHynOrJXcubxd+08xdW8k/Vrrgye9giPEoZgL0gubSOccjfIOXjtCMH581cfDT3r1EEfkgb/DhPtdTqFdAqTn2PycHJsbJmalkqfVNpMuYW99I3RgmLAfva1rKkj6OT5DA8XGYeIILZdwEiJ9dfhXz87CYeKhnWPFjS2kUxPv/r3+dpj4sLN4/N5W0vmf+IxuTBwmSltnEsK2kb6C5qWUEz5MsPgJLbwQJl1LV5lR12+Y8GwOmYkTIb2G00qDcmmYKP/o45MkSrqi2iPuK7bL2+Wokp+8nXReS0snFqNhouAA17MkMdL9uPUsnmoMExsCdATixUk/s6luWnjvMNHxREsrUoJ0obVHt2eIDxNUFweRcEnST6hwrN2zaZhgquN8fV+K9Iwb57PyWYcJmRUpI547SK+g3edWWRgiAipjmpylSXdhiTwAE0NE3j7ny+Y7SQ/YlbNPpWuI0Ih60HB0F+lfS9o5PlUNEZvNr4zKyZDuPveneM+nIeJNR95HPlnSg2+stc58NUScMG7R/Yv8w4duumjUEHG0yyKBIke6oO0Oz4igIWKBZehz8W7SS/3frGS/NUTMs/2JSZAn3cmQ+/FNlyGC+bqWjpcC6W1beuWnTg8RXDtsS0z3kJ4j/3TSWH+I2C75g323Ium0stdQpDJEON2LF2fdS/ozilf+DpkhYoMW78Ye5CLHTlPCtgwRF46s7MvYR7qtj7fKPOcQQf0l4HVLifTh4I1t5gxDxN2Qjb+1lUmv4FHK/kKlEHOPs81495N+UmG2WXCQQtj/SnrRj3zYe6fmzUYK8XA6F14eID1wsXt9ZyGFePIhpcbpIOk7GWoPKrylENSswyW7VEhX0iyqeZhAIbTZ9dPmkM/2O5WPhFGIdS0RtzMJ0uVF7BUO+FKIO/Bdw+kQ6fP5qvyPPCjEbiE5JrHDpItHXfcatqYQLl9EPvch52f1cFQ8RSH+1CVeeHKE9PDge4P+ahSisyFgi7Yq6Tu4f0+2KlAI18vvGpeQ76tgeSiynUIUBf25l6FGOq9WVa3rBgqhPqupbqFOesNDw5x8Jgrha32ZfbUGej1/UlVX/RwkwsLtBnKQh11/66c7OkicmFtVYnGUdGVr/ZvhbYPE5RiF/JWapAtnHpXtLBskbF36S1OR75kyfin4fpAY/TQ3oaNFuoCJ+LBVyiDx2PmE5AxyqTnduYRng4RUK80/SJv0k9f0a4fuDRLxWcAkpUM6e2Scr8i1QWIT+6vUUuT8tJcbz9kPEqGqye6WuqSr8r8LjjUZJNyn4s7/h7yiYfVst+YgMVT56N5DPdLT/3Qob1QaJDqrnDu26ZOe2Hz4xgnJQYL+Q9ziHfKK7pNvAvgGiSWb/A3qx0gv5V07UrR6kJDbv5m1BXkqpyX/r4UBgj1aQ/HscdKlf4gayU4OEJ9T5ROnkXu83Rlt2zVAbHbtO3HlBOlirHu/R1QNENIzR9T/IKclz1rW5g8Qi0xn7vgZkK6rRh/+mz5A/Ly5k3n1SdLvfq2/Jxc5QIRSszoDka/ZyaR3LnCAUGod/s1+ivSevwxKYZ4DxBO3mstByBX4hI8XOg0QYy12amsM0f4ff/90znyAyOz54OyPnMdvBbeg7gBhKVZEYzAi3adsd7HWgQHiCNe9tuvI1e0c31yWHiDOvWMToiHn2vi5P27zABE+fKr6vDHphS92GFSzDxD3xOwHu5ATteZ8kwv9xLcsHWs9E9JPeRiIHejqJwrPMZ/6inz44mRTUH4/cbIyNm+nKelsvHliPS/6iZZ1W4MjkTeMSklKefYTjzlDe1nMSN/VEz94xbyf8Ni5kOKOXPmpsXHR/n7i9CVbajdyq8fOj9g39xP1Pv0fVc1J/+o88tRwqY9wCXBnSUcevPLVheiePiJGV6pnrQXpr4sCtgx/7iMUN67f745cslExWzK6jxAtVBJvQT6trSF+4VYfsTnlVaLCadJPX9sT+OZ0H6GUeiUnHDk383nKt4N9xBPhNFMacvcDW+T3CPURX+dOROidIf3c3mDfy396iTVn71xORV4rWNb5rq+X+LhfjcZoSbqYacH+b197ifZ3GZxmyOtrLLJkY3uJNufa5mzkVhznlF28eok6x3eHmK1Ib312i5Jq2UtYbLxkaob8CataxhDRS6zdK7QtA7mpgVyc4NZewnC45MUf5NTvqQVGDL3E1P0blfpnSe+T/7k+ZKCHSG07kR2NvEtXN7asoIf4AKcNppDvyiyz+x3XQ0hdePN27znSf0k7uMt79xCNylYtPsjt9m8tsT/bQ3gk3sqvQV4sVHg2+nAPoXJI0H6DNekR29ccb9zWQ9z9YDBggby4NyF81YoeojBPTiwRub/2Zrm9lG6iubv2wDjyXH6atENRN/HwjbK4tA3pY313A18kdBM3owLHLyCvJCRPVPt0Ez9rmn2zkQcp8PgsnusmHGTElqjIbyg5Cu9Q7SZmzZ+ckrUl/Y2/kqKZSDex5a586AXk3Ec9C++v7CZkzq97+wq5Wf36iryhLkJbVvXLGHL/1ia94eIuYt/VtnfC50m3TPUw4k7qInQFeyItkJvYRY8c9OsiklSsLz9BnqM89MfBposoELihVot8LrAk+YlaF3Fj5S72VXZoe1UyegtEu4izBwLrlZBLTvxIm1rVRYTPRD26gHxh7TAH70gnwc7iYpiAPMI0nf1QaScRKLlKqBW5drN9mkNyJ8ES7DDLbE964LadY2F3O4nG6YTKvcg3FdArPtl2Emdt3r21Q378QOKJYfVOYtQy7vVT5PNuvH7sYp1EzC27/BLk9kXrrBWYOwmGy6z9NOTrzPVo5qMdRO2Sl6CQA+m29o5yvmUdxJo3Fde0kLOZ/N6e/rKDmJzv+uaB/NKGB40N/h1E3vTrR9HI3xy9o/jf+Q4ie/9uwzLkj0PUjQWPdhAM6ywOzyJfXbZDUVW8g4j9s8l0gyPpr5WvtNqzdBDHOk/F7kd+l26yN3isnXieOs97Fjl9dP50Tnk7UXtvsugu8jQ1Z52OlHZi00OOl2nIG9PzGX/fayeCsw4X1yCXcuz12WbfTuhlWAvOId9fAg3qmu3EC5ruey4n0m9LETMOEu0Ep2dzuBzyu7d2dD1kbSdqCitzTyBn0z0a8Wa8jXgT/WfLReR0bk3p1oo24qX0wdYQ5Fuvtj2eT20jaB90OzKQqwQHtwg8aCPiYqk7qpGrr2eYUXFoIzj3jjeNIR9Jy+w/q9VGPM6drV/pTHq2wLpMP8k2wnDTp+1bkHM8fWqasrqNMFvD0K6EfGYsaqhyopWgVDuNnkS+F27oTVe2Emz8qUYuyKdHbjxfm95KNPKaSfkj/3m7t1Q2oJXwkhO2iUGefKSjzcCxlQjmjGLOQ16a/7TmknYrsebKGZ5a5Ba3lVOfSrUSfvKLIUPI6c7djh/WtBIxa/56LiB3m7i3oWuyhTgQTeta60K6D4962mJVC2FjYpglgtyLmVNc8FUL0WyVsrgXeRlrZ4hKYAtx6o5lkQ7ysLqHw5ZOLUTreiqTJfJ9GZxi3jothNav0oqLyGua9xkm7Ggh9Pw0OfyQi/p0uxeztRAxNp2tT5DLEUVew1PNhHF8i2gK8tdrs28y1TQT83dDl94jX/fSylHsdTNBPD1tWYF8MO6+1tGgZqLU2/9YB3K+d6389s7NhOOm4/VjyH8PzPbd120mAoiFgZ/IWVIuPU2Tbib+juX7M11Av2cP45Eq9mZialVF0Xrk7RESlMnpJuKor96zbcjlv127ylbbRBw64s4sg1wk+sYK6YwmQo/deN0B5F6W2b66D5sI1ke8XzSRr4h8tujs0kTkWZayGiJ3vZzq+FCvifCiXPzPCnnbKqPGjJ1NhJaZaKAz8vnra2XrOJoIse6+0qvIy7T235udaSROaEWn+SD/a3i4fW1dI5FuZLjvIfIJHu+tMpmNROydnx7PkG//YGR9LLiR8FnreCYeebQBf5zrhUZCjit8IR152O8t7SH6jQT3af2j75CXLr1nzd7VSKiHu2t9Qf5pcNeehrWNhMDGBsYy5OKZtRbU2QYiYZ2cex1y9x+dXlz1DcTpy6ZRbchtfj+Jkc1qILi+M/v0IV/oPfTxeEgDEclKEx1FbhzH2+Dm2kD00yr8Z/D+tDg+FHqsgUjJUUr7jt1E9Fu2TAPxnHf84SLyKOGyvw2cDYRQqrviClfSOc1q11H66wmr/ItJrMhN2+y3CsfVE7I2VzvXIh9rzpM4Z1VPMHhztvMgP9S8Rjphaz3Rkg0x/MhnpnOkKAN1xD4Tlt1bkesw/hYVjq8jFOIsw7YjHxmVFjh3to5QvbK/UAq53TN/joRtdYRuEEuBDHIRc62lwcFaIspEKlQBudK37LFtCbXE8IZV8krIzxX9qD97rpY4WjybdhC5/Xfd3HjhWsJZVOXnYeR6SePPBik1xJtCgk8DuQzj/NVtiTXEpXFlHm3kwxdTDM9a1xD+r9zG9ZBbvt8qFy9SQ7QMCTw7gXyAI3DN4FA1oSN3cZshcrouG2VrUjXBthRz3wS5GnPJeyubamLmcm2tOXKLxNbAONFqwiNKiH4GubTPmTMDw1XEtv2ZP88iD+fylNmaXEWYzz7qsUFeM6r+19K2iigX60yyQ1430F4bu72KUNv58Lgj8leKmpH9I5WEn/ibAWfkk+Gv7ba8rCT0BY8YuWLfySdveb6SuPxH8e1FvJ87437HiFUSPml3fnggvypkWN43WkGIf1u97QpyUT2NUKGUCsIp8/2ea8h5Q3xNzthVEIm59go38N9d4N8aI15B7Pr+Q/Am8nVxfGO9Y+XEvNvub7eQM8QHZgimlhMVplPvvJD77rvpcdq+nDjBOW7tjY+r2h/7oiXKCc7dkwy+yOX+Mv7pGS8jxrIygvyQX85JK9qcVkY8bhpn8cfvR+Ef/hYOZUSbvq7HPeRLA1PaUZJlhPMp3/r7yC/OPV7bM1FKNMTICwYgNyz42SiQXkp88P9tEYhcUG3jE3PHUsKQ52ZIEHb6onGkVCmht0499yF+Xzem8XdPlhDntk3UBSNXvbO9l/9VCVFb860nBLnNQY9YM6cSYmfsVH8o8qiZp2df7CghePYZdDxCflrksUjXVDHBfy6pLAz5kOiFEb7XxYSDpNmrcOSb6OIpps7FRAF91P8xci7tEvsI6WKiNeyj6RPkktnqUp3TRQTn+QOiT5FXu2VObcooIoLsW0exNyUzZJi4FBHn9UfjnyF/raxy4fnOIkI8qsbwOfKtVHuZjplCwgkGV0Qgb7P0oW7MLCQixD3TsD//G/jG+EIhkXtmUusFcgPRe+7PdhUSh4VvDWNvX3VZvn22gBC5eet6JP6/fzb6zptVQIR1y62OQr5fb2eukWsBwbSrNxy7TsLC5acyBYTo/Fe+6H/2/3WX1/1A5F1YH4nd9/PM7A4rIMJC1m+KQf7W3cDt1cBXIlj5Ryj2mPupNKmzX4mL2lNMschbRWju6YNfCErG9qvYjY/t/C557gthfKdxGDv19+nLaZTPBLMI37E45OfZ/X5KWH8mmg1F87C7q8ZdTR36RKgc38QfjzzENGde3OYTodW10RN78vcv11OG8wlTW9VO7IGvCn6J2eYTLNs/KiTg8w7LZ8+XIx+JbvEnD7H/9Mte2n7+IzHjShvC/vZJzK3k0Q+ECdvo3kS8zsf5/xG1+0B4Sz94gP3BKgevpLH3xOYjcx3YzXg1GETt3xOja3eIJSG/JCrknTieR6wu1LuIXeIKjVHEIY/YvNouH3uyboFPwkQu8Ub2LmMy8sdDASuFHXMJJ9lcDexpF0/4xU++I3xLVwRgF5PkYdrm9I4o8r9Wjf3Uvua7cVM5RNP8FraXyOcqg5m3OucQM/GMWtiDmI7ei51+S7Rs3n4XO41ziWWLy1ti7Y5HgN2RLfN+zMwbwrFMZx77+k2nVwtdeEN8kTOTSUG++dTqgOjZbKKLtdAGO3PP2zWCrtlE6TG/59g/PcnhVerPIjZ7p1Rhb7y0tHHfQCbxKXLnIvbX/of49g5mEBEyfFKpeD355cWvSHlNdDk4G2Pf8DdfYM/QK2LLVklf7HwFtM0Kw+kEa/fxDOxHHUSF5EfSiG/9w63Yhbaf3LJ7NJX4rjS6hN1U8PZWubEUgqXIUDgN7x/P5G2y4y8JLzEFDeyj5yuFZSaSiVyatz125tWTIrsmk4iVocQD7EYPWLbvnEokVhq6pGK/ySksJj2dQMjeYSvDPlukJL5jJp7oPsRPwf63Sl9CajaOePoxYgl7U3SRgUFfLLF2ZcCGdOQvpyinjg9EEy67pqSxZ9f+MdKnRBLaR78cwc4TxmuqOxxB7DFkMMY+7S9lrj36jJizeOeAXfuX8mnN8SfE8bOdN7AfUNa01JgMJ35auwZgr3tscFZt+hHx1fbKc+wbs9+V+fWEEDx2s0nYfydC1Z2BQELSvj0L+7n4srqbw/cITge5j9jN1Kqaro37ErUOSwXYqSeeZkx0eBG2jvvKsSe0hecODlwl2h1HqrFTojd75jS6EiJOK+uxc9cI8B4ttiS0nMIasDPQ1q+q6uj5+r+e6LstfX7JEv739yg0CqgHzbrC//7dcetQfv25q/C/r/PVi+B1RmNe8L/bdSZdlSlrzhf+dz8svD7AmDN1D3b8z35b/1Hud95YIGz5n/38fLfwQv5QCAz/z/8l/6v/jf65R2Bv8+//sfL29WuDM+Fw49y///cLbA5XhqaeQKblv8dJNK/hpZGJZyBu/u9xpWlw0H1sLAKOnvz3ODR32+Y2MRIJiur/HrefhRkvTA1Fg7z0v8e5hkCP08xgLGQxvPjnfTHA1Pnuv7k4WPf+3/fRtEFhzvxsPOxWYf/nfRdU+/LtwkwCnL114Z/3qb3+gze/phOB0+DwP+9r5kz77MWpJJgI8vtnHcgvUctamkyGK7N7/1k3IhwFM39PvAR+EfN/1hmbq/TXf8ZT4NbXmX/WJY+i4ld/x1JBXXHun3UsUvhROsNYGmzpOfPPusd2wSyNcTQdONv3/7NOSt3Ykrpi5BUwbr77z7pqLzDwcuXwa3hmq/TPOsy1PSp51VAGyO4w/mfd5nA4mcREyYSdz3r+WefT3jMlMg9mgcPN8n/OC4munQ0r3bJhRnuDLXYWo53H/eayoXdl8T/nnUqP2/WrXN/AC+naf85Te17X6N+dfQPbCmUKsA8ObKxjuvAWYreP/nMedKVZ6vnPvIVDG6f+OW9qfkqqYXbJAYWofezYDfhGde5N58B3enkNPi9HDIlUszi/A7jzKBD7z9nT2ven3oE5BGn+c95nf1zJ6pQLQlLZK7FPrS7TfDCZC4QU7TP+XHEl61v5asc8uLtC7RL23wWbjwZM5IFefqQk9rilQ2VrHN4DE+tkD/6co8VvpR44/h427t8SjJ2h+noJm/0HMNkudRC79IeHqkFjH4Bt1fwE/txV6hNZxG73EW7aX3qM3a0o4fDD0Y+gsfXBAez3ViUWcJzPBz1BIQr+HMhSHUkEj+SD52m+u9gdA4O+rrX9BEebzmzHbplx6WDI8CfYpNlQhD+XOjw4+ZnT5jM80NM7jd3UTmJ/6NBneM6f8x1/7k26Sf/IZf0FSq/23McePpm97xHlC0gnx/Nh1/h87j33ua/w7HDHS/w5PGCYWTFs8CuEyp2UxX5tf9S7dWcBLvpTcvHn/AHPbfLhAwAetif3YleOq+pYLVsAMOv6Dl9HmDMsbqxyLYDbon+lsVczbzMOyCqAicaSOHydMla2/6n2XAGYuHtzYqcf0G5dI1MIpzbRr+HrnQkdHZ7qC4WQcqqhB183SXw6eDIwsxAcBZuUsffJbw3TmS2EzblpYfi67IgKrYFtVxF8eMQ0jK/jnqpkcda4FEG7augu7JSLJvpBGUXQd5p6EV8Puk1OBunOFMER84oMfF3JEGRTzb6zGCbv5Q3i69BXLMWra52L4f3YKQ7snu0rNR++LgZVISVZfD2brCTqrzddDB1G37Xw9a/Ljm0lHNIl8F56vRm+Xk61/o+xzqkE8sIFrfD1dZtuIhH8qgQOFj41x9fjLX+23tKfKoH8Db918PU73z7n/LU7SiGYuUoWX+97Gd35r86xFLxZ3Vfj+wOPjpkohKSXQsMNm1Z8n+Fk6qzbsclSaAtje/wA+V3ngxmcUmVwVrNGDd+vMNyuMlHvUAafjzCP4fsed+onREPTysClbP2Nu8i7GvZZHZ8og7xErd/4vorMjHAkl2Q5tG3/z9UHub9ybGuDfTmsX3m+8Q7ytzxJnI9Sy+G+XtdWfD9nN5e41onxcvhoE3Ya3/8xmt7swy1RAd/Gyvw98f73u57faFcBbmnpkdfx+bdQhv4opQLUEhwjr+L9fF9O0mCsArjHdt69jD3N1XKdeCX4RG8wwfe7lOo7Hzedr4QQ+oH1+P6YsfOZyrCXlfCA+2PuBeQzyZNLBqOVMCIQoYLvv4UfcpRZL1YFTdtGXzsgDwsot2q2rYIHAol/zyP3UZ8KDU+uAtOhmj34fiA1+DOcHKkCa1kzfXz/8E/51pn126thRdh+TXy/ceXNxU0tNtXQ7GQujO9PCmrsUn2cVA0n6NHdxsizcp87nRquht/ig+6nkNfKbQrjEa2B311Lo8fxut19L6/FugYUEosU8f1VbteCjseJNZA78NtKC3mZyPP5U0M18Djfw0Yd+Y8AyoYNIrXAIDRE4Pu93i5usq3naiH6yyr6AeSHUjk1nyTUAid34PV9yPlZAi0MKbWQdUq4VR6vq0LpLhuE6+D0A7eV+H5123Y5z9azdWB/acNKfH97pGrA70l8HdyNTW8SRX6d7UqA4WAd1JsUu21B/o0lPXDDtnqoeTvdzYcc2uTut1rVwxW/jHX4/vx3w69eT+LqQc3Bfz2+n++7uHjRcKAe5AtpPSzI509oZa3haoCWbGsXRuQFWWEJkzINYLRNu/gX/v5CKC2s6lgDPClg7/2GXI/d1CvdtQHEGTk+TiO/sdPZPiCkARz5XxqOIK+3SdNzzGqAp6w73/Qi70xs2aVd3wC1QdTKVuQqtZlsUnMNIL9TKaYWedGTH0OrORuBeY+WdCnyqzbW7yd2NULZOwv3z8i5dmfdrdRvBHuftAs5yE3tgvTTLjRCgpLlFvz9UVN+OveD4EYwPJDiE4f8PEdenX1mI2zLSXr6FPkRDaO7mnWNsCP4kmkQ8uqdMnskZhtBzH9npTfy10cHelnWNkGq4MDQFeSrXq/yGtvZBO0JT1Oc8M/3795UrtcEt+QM1+Hv4yJfLaW+dGmCoFw+4VPIbb/Nyvo/bILts90tR5F3BDzKss1oArGLDyX2I89bYyeqXtsEx7L4BHYhf5Q0HSw60wQcC7bpW5FX/YiYXcnRDFTfEy3rkOd0DhwZkm6GJrfcp6uQdynvDCzSbYaCJpu5H+j7UM+h4bJ452aIz5PuGUUurmf3405QMyTsaDFrR/7ElYPX6nUzuOludihHnh4sKUHUNIO8VsEq/H3uFxaWHULTzWDmfnnHS+Q8QpOCv9laYLfaVNdj5EllnAw9O1pA1aOayxd/z+uR0ZCv0wI3Fz5WuSHf0UMNjnBqgR2ihsxnkB+q/qt0LbAFviTsKdRG7jT0X4PRqxbQeTo7r4i8ymHWYE91C9DjOV4JI1fjoH5dP9UC3xb5WzmQ52cw8NDXtEK0V8SlefR9fZKwwIkGqVb4D5jvUZDvYpS7nKndClIC3atrkLedlfIKcmyFhLoHv94hD0oecXEMaIVuNm+jaOT2ynsPaaa3QieHlMBd5N8sJ75vr2oFOZkJdWfka6Y+BaycbIV0BqEWA+S2q20YBle3gZGVSPE+5OWrgk59lWwDiUfHuISQdzM1343UaoNvBt8/rEBe2VYTds2hDQp+nckfRc9veCcz3jB80AY3Azu4q5CXl84o7U5rg6G65M+vkbN6MDaurWyDjAssH4KR/3wUd3BqvA0GOZQZ3ZAvXBS+Xc7aDnrnrjw5jvxicGNookQ7bNGnXZRF3nlsysNLsx2CFrrDOZFX18RuN7df9mnr+Rn0/MxMAHeS4v12iJTIiapGXksYznCnLv/8EeqtVOR5jy7+nS5vB/ObKhF+yH06znSUj7UDe/+XKUvk7n3MVxJYOiDkVKC7MvKN8WptN8U74FVhgRQPcp11wz+NjnbAjy2XuWfQ80jHO+NbZe06oPzZZ5FS5Ow8O9zW3OsAtRepZ6KQX9skWDL0sgOsF4+CO/Kjikz1n8s64C9byhFN5CXXrIKfjHYANad+ZDPyX/aRf12YO0EkqDKZip7XEmvg3qoh1gnv5iO8ipF73Vg7I6jRCatU1dyeINf7VWX9w7YTvuZUXjqP3NbJ1bvmbidUvpYMUET+R3GdamJyJ/AXn81gQj7V/j75emknnO5w6W5Gz7PtizV4eWykExwUNLnjkUtdLzq8nakLnGMmdFyQJ79tufRLtAsaL2vd34f8x1fVA/VqXVBSdbp4BfLvv/MeJ9p0gcEVgV/V6Pm95z5FN676dcGG3VckHyNv7Ryd1E7qAqssK31z5F2NoYOCJV0wkFFjuw153GE+c+pQFyRxv3IeRc8fVjaUnCxa2Q3356cs05EXQ3F5uEg3fKu7fcAF+Z5suRwb1W6Ysjb4uwt5ssuGdXusu+HC0qnkOfT8pEme1cAq327YcP7SjizkdquofC0J3fCLNSbYBfkK44D8hKJuGJn/Wi2FvGdx4IsbpRvymEr6R9Hzn19NQraorOgB3uqI8njke3L5u9cI94AzSN8xR26xij7VdrgHOI84MPMgf5/popdwtgcKU/cbV6PnV/kt6n85e/eAo26oqzfyZ18OzynG9wDfk5O6ishtjTu2MxT2gAaT++QEep62WDskomKgByzUOjSikFds0VEPZeiFIAmPM3rIhUI6RIy39sI0yOz6bUV6ks60jOChXhgxWXz7CvlctbANxbIXGAKKJ0yQp65n+PTSqxfWKV2pX4W87ubcLsfYXmiOZzybhZ5Prr6jmi8NvTBjfirSBPkF7z3Gs329EGJ12pMB+ddHI38z//RCGCf7n5foeem3KmaZF4T6QEHh+FZd5JXGdyx2qvSB92r+/jn0PHbwe6lVU6f74KKK2d4w5Ezs62JTbvVByQKjmDzy1bEtYtbRfZDduyK1CT0fnij087Hglz5wYjuW74bc0raf0tbTB+FinaYcyOOO9K0OWeqDEJPHvqnoeXVG1e0rNTb3Q9/JSwpH8PPt16rLF/f3g5uxi0MXeh5+j1rN8WzzfliQu7TlInKPzSzPrD37wVD99klm5BRjInxDZD98e+C94gV6Pp/ph4BKWX4/6IddkpRGbmItHnq5qx8uBeuXfkbP/x/WrfcW+dUPL46xNOsg5971lmmcfQC+6Dw71onmC4qZHoZ92TwAp+L/22uLXF7B1zpMegDWCgg/mEPzCxVzoZfOHxiAaHnuQ9eQb/RNLFTSHYDHfAWmf9HcRJZchAa7xQAcy5Fq9kP+Z/Phv71OAzCXoJfGilxN0nws03MA7LXFOgPQvEYk5dmv24EDkFr/1pIN+aZzzxX0IwegcytdKQDNgzDLz4ZufjUA5fNDNizIj+4TYJvMHwD3ofu9PmjepPfRo5i8qgHoOEKJW0LzKQk+ORo+XQPAcIr+6hJyFaPmP7qTA3BC4fPiJJp/sTgqX8T7awAOj6k+tEQue54pqH/1ILhYBJ9uOka6sZeTcQrfIGy7Eu+gilxg5dUtFyQHwYLLL/Mtmt/ZMSPRL680CNasKpJbkde9vvhoXnMQRtQ62gLRfFAah5zcZ5NBKP1q8e4Hmifi36b48bb9IIQEtH09jfywBCF66NogJFBOfCtG80pfbi84M9wfBL7dPfoSyKX9GYPh2SDc2OpXF4DmobzDKN63UgZBJsbUdQrNTym086oqvx+EaprLLm3kZoYsNT/KBmFzWTNrCprP+ljFtjG7bRA2KMUuMiJvi3cUchgdBO+pkZXmaP6LZ8ikZ+vPQQjgBqG3aF5sVOyXdjsTBdj9VLVYkIs9sLIJ2kCBL00P75ihebQX0UHCh7ZTQMg4v/AVml/LtXXxoitQ4IDm2OpFNO8WdXTgUqIaBVTqFYw0kd9ifrNkcIoCnzaXJoajeTqNzxFcjDYUGLz9ea4Hzd8VtBxJz/CggPm1w3tFkQutUS028aXAYvvNqw6HSF9tvcVwRTgFtjZGZLxG84Dbd+uYpidQoI6nrG0GzQ+Kb5SoPP6WAh5TclRp5C6MzDE/CimgdYzrPwc0nyilINL4vJECuizPxpPQPOM23dfmyoMU+FD0p7AXzT/OaHxW7KJSgHGP7x0e5AOBFubXGIZAabf1Ni00X+n606+Ih2sI2qoH4j3RPOYOioBt1pYhqHA5/PcVmt/U3/dzv6bMEHQu1ip2oXnPutvtRL/KEKjONakzI18Yv+hwSX8IPC7FScqiedIIh/NvWM4Mwcz9gH5jNH/6vEyNK8JlCDT4JmxuoXlV8czA2xK3hkB6y6b3cWi+1bo29Xtu0BBcgKvNhWge9tb4vOPhqCFYY+/8fgDNz1p+L++sejUEMrNnrH6jedtWuRNKBp+GQPn15+qNyPdrg3d71RAkx/73U0aG9GwX6VdmXUMw7u/fr47mf7vdEzK6J4bA4O+wjymaF1ac5/c2WxiC6oTwPkc0X0z19xJsZx2GgO2bqNfRPLLd+7QbJzYNQ77H73f+aH5Z0dg6tFJ8GDjqm6UeoXnnvtDzRsTeYVCelj0WgeajeTacKXmrMQyOXNlbYtE8dYr6SKOI0TDc30WPSEDz12vP3b8SZjsMt1bFfEpE89pBuSVpfy4Ng8Y+K58ENN+9UMZqbe83DBOXpqZi0Dw4X8C7iPrwYdh/b/7HczQ/fj+MT10hcRhcb2jEhKJ5c0lNT4unb4fB+t0Lyt2tpHMIcrb/KByGeO7Cgmtonr2qZOmVQeMwrGIMUnRA8+87Xc40vR4YhsWYlsPGaF7+4Pyhw6uow2DUcGPgCJqvv7Y3ac7k7zA8trDlkkbz+ISEZ0v62hFIYvGpX4fm983kXo8uCI4A56tSgf/QvL/XWW5BjZ0j4Kkv/a0D5QM0ZF67EHJgBG4SH09+QHkCcnuTGlt1RiBd4ur+Jyh/wMFb+yCf+QjQxK+luqK8gj9feVNNHUeAe7j1+VGUb/B6bRrrs+sjoBX/Zo0gykO4AU8NG++PgJihwtIcyk/Qeex4l/X5CFz6GOxUwEn6FEty8IGUETh2ZsEoGOUzeD36bOeSNwJ6n959NkV5DicmBFkiS0egglgdKYzyH2h60talLSNw5NxR6jjKi3hUedh9emgEJjPL81+jfImoq1lSXN9GYF/r5LwLyqNwr/riI7tiFFLf8aVJo/wK9cbXbnrcoxBuX1o5jvIumG6/mzy/dRTETtqZJqB8DO2pVWM3ZUbBQ9zbyBTlaSgnlJmHqIxCCj0KOFD+huUAPxGjNwpnRfXCgYF0016Be2kWo7DzqXTDBZTvcYOrV/KN0yjsCuu7JIDyQPZccRLMvTEKSx1r75Si/BDn1lrj3Aej8OnlRaozyht5voqp/s3zUbjxvriEG+WT1O9iv56eMgr92lWLOSjP5M2mTp3YvFHYI37y8UmUf7Lf1uJgaOkodEYqPKSivJTgLm/VWy2jIOKrNxKA8lVyXsqeOj80ChWqdyOFUR7L6SQdWx36KFQ3Vme+R/ktX2PfOEszjgFTFp+QNsp7uRh50Go11xjoTbmOd6J8mAcbyvdQhMbAQLSD3Q7lydToCg/l7RwDqbs2ATSUPyPuv/XMvQNjkFAqY3Ud5dWcMwiNOqkzBmaSpx/+GUd5bi0HHwuYjUHG7U3c3igPh4X5m3K//Ri4Cz6dZED5OcGM1/xjro5ByMg6vtsob+elerizqf8YuBxsiZxH+Txsf1YPcT4Zg0NcEu5uKM/no3Zcf2HiGMjW2ESOoPyfj/f4TFzfjoGp1QSvCcoL2v1k35FNhWOQriw4XI7yhQq3FIR/rh+DKHW3FXtQHhHPhPsRi74xKBsxuxiL8ovKuHjU/pseA+3/TsuyoLyjq6ftgh8ujoFg9QrCGeUjbfGX27hlzThIiXZH1aE8pQjPfS2vNo2DpoK31i6Uv2T0VvWTvPg4cEQ8UwtEeU0HnDcX5e0ZB2eTyocjKN8pYkVwn4LaOIj1VooeRHlQW2XPM2cajMMi/dTqMJQfNWh2WUb47DgkFO3aP4zypgT6go89ch0H11qRfHmUT0U5+cBi8dY4pI+z+t9BeVbOfSq6VkHjcG/fp5gqlH/10+0hT8GLcciR2rpqHcrLEtpk/Io/bfn3u23PM0L5WhGHfZjd3o/DzvmCd89RHpfQyl8CBaXj8HKU+rcd5Xe5WWUOrmkZB5OQT894UN6XVehjveOUcXBylrmpj/LBUg6lGIZSx4G+wTrjLsoTu90xOlf1Zxyu7Lu8Ix/lj1V/NF3HwDEBjQFBP6dQXlnjHfYcGYEJ0CluXyuA8s0OHVlXYSo5Ad8DH146ivLQwsv9jt7eOwEHrkyLX0T5aXGVfuLR6hNQMqMs+RzlrelLKp/JOzkBDlLl1z6jfDZTsZbByrMTELRtjLcP5bltfPwgtd11AsKuzK/8jfLfZNkjUvtvTUCyo9UhPpQXt3eLVsdg4ATkVgfW7Eb5cvy+4zv7IibgE2U2VQvl0Z0i6mJbUibg0FmmttMov66rzVS0NHcCpPQNTrmivLss129vsoonoJVmKXob5eNtnGcjHjdOwNVC0AhAeXqGWoJF7v0T0KS15nM4yt/7dTRdTmdmAg7y9fu9QHl9GYyEn+DiBLCkDcfHoHy/GxVu2ROsk7BXo2J9HMoDjNHpe53FOwlfFg52x6D8wK4MGTdX0UngcmNYeIHyBo0ieGkSuydBf6DB5THKJxQ8oS/WQ0zCCP2KciDKM1QtiGR+oDcJzSkFll4o/7DIv/a+jPkkBB7w6XNDeYmiqz4n1ttPgj/30/eWKF9xjZWWvsOVSXgc0jOlg/IYY0PPei35TsI39gM396D8xo2Wv3Y+eDQJxNs4h80o71HNcf0Jzthlt1x6x4DyIc3F8/qDX09CUoiGJQXlSTIM/mhgyZ+Ej8RNh0KUP5n8bk7gRvkkCDTGtkSjvEqj4Kr3Iy2TcHnuQ/xVlG/5n/D7SG3KJBhcbmnUR3mYLBNzX1PnJuHv8VXnRVB+5gznx00Mvych1MHS8gfK22y6bBV3fM0U/PJlhBKUz8kTdVDvxcYpMJBg83+E8jy1X7zh7RWdAul78bnmKP9zkFP8+6bdU7DZclZfBOWFGvCs69UjpsCMsuXkOMoXnd5OrfDUnYIHUfbF6SiPlNiomZVgOgUvTf7GOaL8Ur7FtHtF56eAj2XLjDjKO5XgzNLq9pgCaiJzGgXlo8onL0xP35mCg4ILrS9QnurSmj0O/z2cghSlg5ePo/zVKrcNeb9eTIGgl+D9lSiv9WWdcfXPlCko4RvnfIfyXc9VFMZNvZsCnuJZjnMoD/ZC6LZdnYVTsCfN35cD5ccmVuo5Qd0UxBixuuehvFkO++3HY7qnYOWL+i4LlE87FBrScnl8Cp5d2A8MKM+28LonVf3HFGQMZ2xNQPm3ukcHIteumIaSNUEMh1Fe7vmpz3X1a6eBpf2gVS/K1+Veucn7gcA0aHDvOnwV5fHuePc3fb/ENHgerEpai/J7JQMfqI0qTEOPv09QIsr7/W7SpP7g8DTcf1W5sAflA/Ny/3kpqj8NzeM8s6UoT9goda/VB7NpODje7XgS5Q+Pfct2ULObBv6M5xf7UF7x8QcJnyo8pmHap3ylHc43jtXRV78zDTenR4VnUB7y01kaX37QNKSFX21wQ/nJGk8HecUjpuGX0hIHHeUtt/12PhiUPA0TaQs9biifuTd/+u7Em2mYS/2pMoPynH9dgXGVr9OgPem5xw7lP0u2a50JqpqGWyt4ivpQXvR5m599jW3TEGCuM3oS5UunXd5jzTk0Df2S2YllKI9aR+DWkNrcNMyfbVpURPnVHWxaJu6L0/A+U5WahPKubcL485+xzMB5+2c+XCgf2/b2Ncbc9TPgFHTu3XWUp71tw5xY1ZYZSMrdf28A5W9nr+ISad+x/PMbPi2pobzuMBP32e69M6DscoM3BeV7U1zfeneozsA464Y2ZpQHvubHxdaaYzPg9VH8oA3KD1/Rbkz5YD4DEQ3H9QDljX9X5YqPspsBYrMs6yaUT66WrLvmmscMqA6dd72A8sxbo4p5dbxmYCXlmV8Ryj/3XCkHGwJnIPyonRYPyku/PW641P50Bg7m3ABrlK/OETZf9ihhBnR3Xx/PRnnsQbeHN6pmzsBWFbayRZTfHnN+cmzq4wxczu8yVUN57xXEgExQ6Qz0fgtLDkD58M+J+HGRxhmwihlIr0N58jL9HGw5PTOwp+WiExfKn9/QzxaqND4DT3l+jh9DefXqOv5u77/NQMwRoe0PUb69iZdLsvTfGVBIitpWgfLwS6Xei0esmYXFAdEBBpSfL2N4hrq0YRYOMzqf24vy9jPPWc8bb5uFn84S6U4on19oU82+dOlZeDHJ/TEa5fnbxyamf9s7C7tjBkNrUf5/WeAvDQXVWdjHaiC/iPoCVveNMjvrz8KDVVsSxFC/QBur39AL01kwrWTqP4b6CEa+01sLbGZh82jJ1BXUX7CPyay913UWrh3ZXBWJ+g5OCIwM0G7MgoxgredX1I9gH1k6tXR3FtayvVjRj/oUktx20/6EzkLHDw2r35mkW3DbT/4Xufz6BSKe8qG+hou+qQ1jL2chl804RR71O9Rb7Y+uezMLWWmaj3VQH4RIj4vW68+z4CCx1/Is6o+gl4bV3SmfBSm2mdWXUd8EX9gKMd2mWXATVXzqj/opZk4LaK3tnQXNJ/1MT1Gfxbr/DsmVj81Cdc17s0TUf6E01NN+hT4LNfeCn2aivoxJ+zOKgr9n4VODwqf3qF/DL0JZI59lDor/3qz6ivo4oiymGfTXzcGuT8plxai/Y/Lmd8uOzXPAM38kuwz1fYzndVqYis+B6aJTQDnqBzlRKUFrkJuDVeYPjcpQn0jqvUu8xIE5oP714i1G/SOzs4ZliRpz0CMuVPMF9ZUkH3D+9ef4HFDsVK/noX6Tg6ynXx83n4PjWTVbMlAfCptlS+tz2zkY035eGI/6U1oofm7trnNwZ/yu1WPUt7JqSvwK+43l7Yq88scP9bO8SL01sNdvDqT6daM9UJ9Lq65emmnwHMTFTqtYof6X1N22VRefz0Gj8v4RbdQX82dN5ME7CXPAd39LmDzql+lmq1nyez0H6b3eR/lRH42JcC/jnbw5eM+ry/LXDPVliH/SuFgwB3MRDs2DqO/GZpN5qUnVHKhZlWcUoX6c88fzryq2zMHS4snn8ahP53p5n/GavjlYE/f38W3UvxNt0G7ZMra8XeKfk01RX0/Y2KcHj2lzwCx0q2Y36vexG8qo116cg+iyvWxrUB8QVXL6iecKKvBsH7LuR/1BNdv21eiyUKGI6VrHW9Q3ZOfXxcLHTgV+ZpqjH+onMteZVx/gooJ8tLbgKdRn9GT8k2/CBiqYi/rStqH+o5MXDb9a8lPhZf+LiRnUlyRR9Yu+cQsVrjA/ZvmA+pUYW8aEqkWoMFftrncH9TFxvjhDXJeggp7dwS8aqL/J+07KCeGdy9u1ecmEDfU9MV7iPlkmR4UNRz4K16F+qE4++iFbRSoo63lvDkF9UrkMLzf9VabCutZzmvqof2qqMbQ9nKCCYNSFVDbUV6XkK+gpokaF6qfvVcpRv9WP+18ZMjWpIE034PBGfViRrLO28npU0OU34VVC/Vm5bLtSc05Q4UDBgPkc6tviz2Et3WVEhZJ+1oFE1M91zZErP8mMCvkls0lGqM9r9+YBvw2WVFjBlfOaBfV/3bUVEPG2poLdNRrdBfWF/Vd1IWzMjgr1qlX8lahfjGsmpEHTmQrG/xGtW1EfmdGXg91JblTY3fxS7DLqLwvPOZS9eIkKEhPG68tQ35nRSic9vetUOCv8JnY96kf72Pg8O+IWFTzUNjScRn1q55yy2we8qQA/plKTUP/auxsJBcL+VOAojN81jvra5FUcHSwDqHBhU6qtBOp3YwGOhqfBy6/f+LKBLeqDC2WJoVeEUWG22G8hBvXHrTDbW//jKRXuhRhZtqK+ucnzjDaCkVQ40uZ6nxX10z3ylckiYqnwOdrs+j7UZ7dtgCHLIpEKrU3Jirao/879S8HZSynL26sxUhKM+vKcEspK/V9RgUh7I5GL+vX6Qq90hmdR4bh/6vkO1Mf3VelwZGQOFb4ccPadR/198bJJq2PeU2H1fKLvBtT35yIkJRL5iQq2KYtOMqgfkO+b42gYUKHgm8hhDdQn6MLLbnC3mAqRCk0sZqh/8OWzAhv3ciokWxeUOKK+Qqq5lqBZNRXWc2bcvIb6DRN1Lt84UE+Fj9rmCr6oD1H+9jZPvmYqTMSGUQNQf2KFjZIQrY0K7EtCeSGob/HKt7xzxV1U4IxpePAI9TNyVyYcDe2jwpMVN91CUZ9jkCFPjTFl+fivX7gQhPofZ//IzfGNUuHcJ7GAu6gvslpNLrttggqynkNlnqhfUpVitDZ4hgprknmkXFEf5Z3Zn6yHaFQwjEj4YIn6K98tXoqd/k6FbrvrV/VQ32WQglpj+DwV7N/dd9qH+jE3XhuL3rNEBdcXxRFbUZ+m2CXaqqa/y+/3kK0szKh/U/DrKmaHlTRw0Ij4MI76OpUnm+N+MdPgwUOpnArU73kmflur/xoaxMu1LCajPlCL3IIEjrU0GOl+/uwO6g/tkH+8OoSbBvPUW4EmqG+0/mrIarYNNPhzIbBnJ+onrVTKS/DeRAO+6uoQBtRn2h2zuZUuQAP7Op30BtR/elNjLO7MFho8dOeXi0F9qfrGOsylwjRo+aIp6YD6VUcDgpnExGjAEjvxTA71sWbvY4n1lqTBYgW3z3+ov5XRanNzuzQNxh+2T+ejvlfnN+oJErI0eJZv0OuJ+mGdn7FxXJKnwfWLUSbKqE/WS4WFJ1+RBq+Y6q1/ov7Zr1GU97+UlvdPK9OqbNRX+/eaycKegzToEz+tYof6bR9dVOh0OkSDuBX0jZtRH278ipMmUao0cF5DeVKH+nPVg+KvlmvQ4Im5zpfbqG9XyURo34wWDSZtdcOlUT/vsdiOFxx6NJCqWCnYgfp8l9e8OInjy79nR6ilN+r/ldN9pqNycvl42MJlJYH6gscW10bpG9Gg5ke8SC3qF3YqTg83NaVBWLR1livqIz5VVydvaUGDgDvurFyov7jxBPWWpSUNUs5MyWeivmOe0CceZudoEC01qaiN+pHdug15j9vSwH30Ae8w6lOWjui0O2RPA7k7w+2eqH+ZRa3LYYcTDSoz193hRn3NNheEhbgv0ICrfgdPMup35i156E9zo8FEgXqEIuqD/sy2OrnGY/n1l1ziKUP90QniYZ4JV5b/j8bVASdR3/Q63n3sHteXj//1Zoz9qJ+agcZvqnKTBp8CZG7Zoz7rxWknm1VeNFAUNVlJRf3X+sYusqXeNPBc6n1+GfVlK4S7wx0/GogUVhxZ+EQ6N+/A+r33aDAXLMjsifq4g87tkB1/QIMz9X1jv16TfnNFN+/joOW/y8s+cw31fT/08q9SDqHByr/x/D9QP7i3WZtezyMa3Fnz4rIr6hNfweiXeO0xDX54Tq4YR/3jY4WmdZzPlt8viv7lZ1BfOQV2N8ZHLB+HLywqmlG/uT/lV+auKBocP2u65ijqQ39emumYF0MDj1s2YR9Qf3r6S3MWpXgaOH0/ayuB+tbpx7fcz0ukgd0XuftPUT/7aRYJ6q6XNPgvOuvvCtTnPuD87khCKg22seQ0uKD+9xVO6325XtHAm76WoR31xcfyJr27nkGD2/AoTAX1y1PCWrt6s2gQycX0MAn10d+iiy0ceEuDsdSd31lRf/2GjeLrn71bXme0qmucUN/9ZPAl6ek8GjSEPBeoFSX9o9sXzQMfaRDTpD0iLUh61x5wuveJBtKMYbsCN5AeF6YRUfuFBvu9Ny2NcZDOpCfTuraABsMcvgaqzKS/5LYR0SmiQeZTN8XoP0v/7xJH++75lNDgl9CN1z9+kr5mIJk5t4wGHdG7P+rOkb5iR2MipYIGun1iZxPGSP8Z72fNVk0DZqve1J/9pL96T9eSqaVB4r62x1odpB9OMjfXr6fBlR8BkpENpD+X5Yiyb1xe325dcJqqID3nzjmu28008Po5fUa5kPR9vcWfg1uXj58kJ9b7H0nfevNl8ot2Gmxs0nRueUP6B82g+vhOGnTmdAdvSSed+dVKIqmbBmv1L11ySECvXz9lPr53+XgwN9/29gXphhOCjJH9NMhVaIpYCCO9h4H/dMggDYQ/rKMQgaSzvzHl9hqiwQr5Y3/8fEnfe/GlsOMIDQR03tIrPEkP7Gx5cnyMBloTZ4rZLpF+yL7EdfcEDdpE3S7pOaP9pmGZyzlFg1SZhdXBNqR/5HjhND5Ng72qTPdrLUi3DfR49nmWBieCn9HZDEkP8f9+MIi6fL4TeaWnpUd6va+MjTGdBkoTu6PvqpP+6cEhTqHvNNC/zzdScJB0oRFdtYEfy+vJmcOSi3tIF5jxYY35jwanXP1cFHaRrljOd9Z4Yfl8YfQu11mMdO0dJ06yL9KgZ/8LpiQh0i+LXxz+vESD6tKfVl28pDMOV/I5/KGBI6dPNScn6UZ2OfNcDHQ4GD2lqcZCOovZQ/93jHTwPdnVc/Xv4v87W/XXipMr6SDqMh2Q/h/pit9zS2ZX0cHa471Rzxzpa/6Oed1lpoOhYoUqxzjpS5UNfzey0kGgLMHw4ADp6pl0rZer6TDsXBTi3EG6kUabtSwbHd6nRfx40UA6+541J/PY6cAqHRZQUUF64Yyw4L61dFjbwG7wo4D0E7fyy3M56TARefbYto+kS59yM5HhpkPgl/67um9If8Q90ZK0jg4uD2rnr6SRzny87ggvDx1W3bB/FRdPuoRHXYrvBjr8kRmJq4wgvf9K1OoZXjooe7j20B6h/VMw52KwiQ7+ClJn+QJIz5r17crhowNHqMzuQz6k577ZZMgtQIebDaEG52+Qvjvq4pDjZjp0uhuVBrqTfnzJMLBAcPn1SN15mO1Iem1OqMG6LXTIH1+V2XKOdJ51VBWrrXQI7m2SnDcj/XuWulH6Njqs8K1fKXCS9P90z8dQhekQFN+uclCHdINMSUF5UTr8NYbeM6qke3k5dlzcvry9IgZDXvtJv6DA3PZabPl4GDcwiJMn/fRMj8CwOB2uLnjuLNhBuq5FY9ZGSTrcFvW62i9COufrimdHpeiw7iOT/B8B0qn26Z0eO5aPw8fZ5zbzkN7jaOUZJU0HjR2bViuzk85R2OZTuJMOxU9qJIxXkS4cu/iDsosOrRGGJR5Lv8jPGzrQxSBLh5Pvd/eFfCf9CCfPXgE5OpTKd197NU16gtgs1+7ddLgn9vVp2TDp53JUL6jL00Hq7hHlwR7SfbLYDQ0Vlo832XLbxRbStw4eqT67hw6TfxIENtSSzls/2OaoSIdNdaJndpWSrp03esttLx32BIbLHP1CerTX8TL3fcv7+ciuMMtc0g3ztuRdVKLDwA7p+1czSF+4bXTSRXn5//7h8/qQZNL9g+cTbffTgSeOZe/LaNLHt7Flmh2gw+8Z6e+fn5Ce+ePxVd2DdFDgVNdrfkj63MEY5v0qdHjSb6U2cZd0gxjZs2IEHW68f9D95xbpysLGD9ceooPB9UIeniukc+8RevRt2Q/HrqBLXCD99Ytw99bDdCjTPHT54HnSG+3K9r47QgdHzfNxJ86Q3vKrbDRElQ6X5Ewv2xqRfur7y7v2anRItv3545o+6etkr/OrqC9vrzCPaJAG6aNfTrzi0qDDnUfejLEqpFd3qasMLPuaRubQN4qkM086db4+Sl/+nGbbWLyLdLsL3T5XNJePQ2ej8lYx0p+vzDh0UIsOURbBHmNCpF82/rWJUZsO+60+ts/zkm4j0sddtOyvVW79WM1Jeuz2S3J3dJbX1TXX6/hZSDfm77y1X5cOl3eq2+z4u/D/nvZO6ve3Zefw9Piw/z/SDz+7l5umR4dKpZAanTnSY3U5Myz06WAjL5hgPkZ6twplgv3Y8jpZFKns1E96Z+Y29/xlF+33eXajnfSq9Dkd2+N00JRRy39QT/rYStdbHCfoMMKtk/S8nHRd1WL2nGXfkLlklAKkd0VzMRgZLK9LDB+ac9+TzjzmefrnsktPtAqUZJF+x0dqx+OTdBjflybblEJ63KkjrjKn6CAOt9cPxJLu92ZCpmLZbxpHl848I71Z+6jHGUM6yPynrrkYQvqmzT4Efdmr8nOiWO+TnmVY+MLXiA7x3wRKNtwhXUVDOnCdMR2M9mSC8DXS845M8sYu+1nrx6Eybmh7g4TVJE3oEPaVvveAPen6+5Y2vVn2GPpYnqYV6TvXxkQqmtIhXeThWkMT0oVddzV9XHbK4g/i7HHSWRWai5TN6LD+o6yuiybp6x6+8fi47PrKGgrXD5Hu0T8zucd8+bjlUF7w20d6ePyrXdnL/u7WmqhQWdIr93CoS1gsv39jswWjJEhPLpZXiFn2E2e3eqVsJb2Gk1ix7jQdWJ5qFr7dRPpNA71c32UvZVo/8oWL9Fx2z5Pflj3qhs1UBSvpEj0UitUZOkzVbW5tZiD9P71oh5plD1vkTeybn/9/N88umNljSQclMUmjCSrp+kNWl6OXPSNLdO7bOOk6EiHMK62Wz1NH2i78GSBdlWaacn7ZCweY2lg7SW/LrDldsewnvl/Zvr6R9J/RczISZ+nw3Xz8tGAl6YxPykX8l32FJ88d8ULS3RoMCcqyS2u+CZL7SLo8PLt/4Bwd7lu4+e1/Q3pdnT/Tk2XPWfHXTj2NdK29mz5PLTurBvO+Y/Gkryk/8PaQNR3ojDt+mESQnpA5MBO+7Lo0jrhzj0h/qjt1aWTZu7/oKDk/IH3PgoreHhs6tHDeKrzsTbp704ebvst+MVpRyes66U33ZFc3LPsL5dXx9y+SbiN2bZ7flg6h494LjxzQdg2bH7dZ9lcjkqqRZ/+PjPuOxvKNHweOsiPJykhkjyiyIrPsmT0K2UIiSlllZGSXJEIhW9rChexEys7em+fRItXvfj7f7+95d87339e5z31fz3W9r/fIOf3z/HouSynmB2qjQh5bgRtL0xjjMX9kzl5aZvzPeyQMyGVd8OgqxfnOl9rgbq8PyQdh/vvBl3GkCm7yXhz/FvOEgF9zbfLgnZbsMjuYG8XJTPUc/Wd/GCJoTrhi+xnyu2dYGDz8COnlK5hfqKx9Oc0Dzqp56NpzzF9rTyatHAC/zOTGu455qGG3/bd94GfULS4KuWHxVrks8Ica3FbFycMec3fz9GkKMvBR8t/M6ZiPHJNM37v9A+rdYtSVTsz9jPepseHBv184m07ijt2j2ZSZQ0vgmtQDgVKY19rQhApPgfeSneB2xtzDuWPfsWFwSbn3KXcwL6M9nKXwCdzga91AE+YZNQ486h3gpxvUN/GY51r3ZOs2gisoBi9xe2D9mG41s2k1uPdSRKMu5mLRjlG2VeDFez3CAjDXLaDDORWDb0UeFc7BnAG3Y+aVBz5wt6+hDfNEL58Xl++DD/adMtzAnGctd29ICvjwjks/iycepXF3O0XFgje0M9oqYn4yXeJFwg3w9lHWWXvMpye2SNKDwC9kywdEYH413lHr4SXwUVZJpkLMa048iCv0AD80WfiuDfPMioGOCkfwclK1mEXML/epU7y2Bq8eTHWnvoBHwr10J+tNwHdTCLoLYf6DzeFSmw74KdOr8acxl3RyffRR7Z9zzN8ZOI/5sz6tnkEFcMpxFqMwzOW2RHcmjoGjLzxbmZi7fjrOtygC/tTKc+Al5nULMdo4XvDOVen1j5grnNG5sMUOrvbjmcYS5j3v0uNJ94Nnpe0bIfPCo6qU5GJqWnCJ+x5v2DHXbzdr2bcLvDGme+Io5oLipBMHfn0n+rU4DXMtzC/qVPzg2QT/5NrAdRbz8yFBdCLL4BE3jp7ww9yX9DrPsWlw736/qmjMxXDvpRS+gEvhraMzMf9lFa6h9hk8+VtpbTnmGSpVZ3TegxsnHrZqwNy8xM/B5B149S9Pu8+YHy4Z8rJ+C+66S7BrBnMHpx9XHJ+B+28vlH/D/Drr+A2PEvBFJL+LwhuPDIXz4i49AjesTetixlxP1Dg1KBPcZc6NiR9z3+lfGTdSwddesw1KYU5t+vRhbBx4qOI2pxrmR9+FPk65CW5PZjFnSPBG/yf3r4F78l+QtcP8vnRWSZ7fP+/X9tjvgflxC/LyYk/whKzLwQGY17W8rqg6D35kIP/KDcwvRjVWVtuA98tQUCVgbkMh/rTxDHhW5J0jGZgnC5M97dAFT2M+vf4Icy493cpP6uBVDb/1yjH/qLWvYvgEeNPqHZ3XmE+E2JZNSYGfj/qy1IC55YB0yZIo+FeSRMn3hPV05D7BHwZ/Y+N0sBdzFafi/G0O8N0Hd70awTxcxyyPjAk80ZLi9wzmIfVPsmn2gDMX7OBXMGcvLb7PuBtcXswt8yth/+/b32Xf+Ub0vgd1P38R1t/Yncz7FbxJ1p1ulw8eVdL9jhdZAdf40PSFGvMU5tXoYzPg1A08LgyY14g9vqEwAs5E31TOgvk5e4FgtV7wi7rTrzgxl78eGKjTCT7ztPgmL+YU9Jm+Jk3gb3nlmYQw/+CW5mldA/5cItdTHHO6Jy7Ojs/BpfkW445h3l7FdM6jFLx9L22gLOa+J3MtLz0GZ/n09Ygi5k976E2CHoAfFbr1QgVzrtZzujfSwIPe3t9zCvNGw7sasfHgZMe+H9fG/N7l50opEeCXVCyl9DHv56qRuX8d/FbtJQpjzCVpKyTy/MG5Xi1XmmL+bTxBqPgCeO0tO2lLzPcfsuOpcgL/uGmeYoP5LikO9mpbcD15m86zmD907mBsNAXfkZ6adsB8aNmTtkMP3DzIctgJc8cpkt2fNMC/XOJ+6or5caPYnSFFcMqQ2+4ehPUIUX+blAbvZlzb7YX5lHbI6qIY+MOp8AgfzP/cXJrF8YEP/w5Z9MU8MM1gbIvzn/PaYjjuj7msSEk/KTP4V1YrtwDMOeZIuqnpwDu8vSOuYP7Lxqh1Hzl47P6zsUGEfdh/Hx34/ZXoVqdEr13HvCBm7BXPN3DnjG6LEMzPSh6sFF4F3y10gicM88SLVk+OzoI/qzYdDMdcpjgpR34UfGx7K/gmYd+ON91T7QM/k/uXMRLznw5fk7Q/gBsUHL0XhfmeIJ4Y42Zwsktn6G9hXlavG25VCx5JdyggBnMtP7+rDi/A6Ux1PsZi/r39nq97Gbg7XzBXPOarP966++aD56XYnL2N+azoqMPVLPDqA+GpCZhfT9qxCr8DHvIhvDYR89t67CYxt8Ft45dGkjAPuymjkxwJrn5UFZ+MeYaZsVpGMHh48+4/KZifmPBQyL0M/riqjCQNc8GTN48VeYHbfC3bJvib6PsiT53/2U8d35U7mHN+ruR9YwfO7mHXfxfza9It7A1m4L8lP71Ox/xI3TBjuz74Qp9w2j3M58LWaHpOgZ/meOOWgfnHONJdQ0rgk2HdMvcxf7Wy/9fEcfBXl1/9IbhQJf/mgjj4h5iX9ZmYx07KLG/wg68+pAt+QNiHOM3pn1zg2txbUlmYF720+ELCAo7nezpLcNcLrp+p6MGZX7inZGOu8jzgPQMF+NKyicJDzPXuRL5j+7NJ9BNHMkYJ/pc57e2h7+AXrZyv52CuoJj3TGgNfNfmCEsu5hZ0lSWSc+DaFrxlBJdPqH0kNwbuM2+qnIe56buOTJV+8PsyyR8IXlM5kKrVBU4ng7N4hLmo9UycUQu4kn38GMH3vNu4aVkHXj0V6PAY84i1nWv2L8G/tLRMEDxwnMrfrRyc8UCsbT7myfeYLlwsAJ+g7+kluC7nIacr2eCmokXaBZjjLojaht39Z52OB98SvChexvRWAvhzuRPChZj7B6vqJUWBr89RpRH8uKqexr0Q8Gb/xF8Efz5krpgTAH5poO/cE8xztRykn3iDV+6Zqif4/URPsUoX8AvSbw4WYS5ceZnv9dl/vvvk3FWCd5SEctabg19lHvpI8JWbMUxtBuA6cUL8xZh/lU/d8/E0OPcdowCCK3U/2D14EpxH+0wTwTlPFeyMy4BrWh3bW4L52IOKr/NHwGV4180J3jnwemVdAPzR69hMgov+aJj5cRD85DfyUYIr7nSM/GUBVw514CjFXHnhcy/lXvB7fVnmBL9YM9K5lxJ8zfxtQul/eXW2ifUvHvo0rep3BNfnXavh/gFu8uX+N4JfePn9ueA6+N5jdnxlmD+S/VsqMQ/edp7UiOCihZT5suPgD0OjrxBciYIhS3kAfH/iehbBGczZ7mh2g/ely9cTfDT90G3DVnCeLOfx/7xTKNICgT/N8ftFcM3vksHnXoHbPTrPVE64d8zyl10rwKPyj4sQXFFU1cunEPxM4aIiwWXltZ0DH4J/fBKqR/BgFWO70HRwkuIflgQ/rWZlFp0IPlNs7Ejw98oO+onR4NdLbrsRXF3B/VR66D/7VlLiSfD5Y75KDwP/r6+LXD2O3Y//857Uw+HiFa7/97u0B2P4X537v+tM4kjmQhb/93dZcWUwtxqCm/7vPjzky6Xr1gSP/999u3+siHxAGdz/f/f5htbT32Oy4H//91wSXd98m5MAp8z+n3PcSmpYXRMEF73/P+e+1dw++50bPDXtf+KkhfLT6B/Wf84x7n/iKsNiuI+CAbz12v/EYfHLqQ/0VOCPz/1P3B4TWG5mIfknPsUz/4tzt8LN2oM/cUS/2/8/9yLqxM4LgQ1wG/Wa/+5R0/Tu8iML4PeNH/5372xz6QpkJsC3us//d0+jL7NknxwEN7tK/d+9DnPgvnv6Izj1euJ/eeCmi1CCQRv44arv/+WND5FHo8zrwT05lP7LM9n1CiFnX4MfNXH8Ly/JsWkEuFSC16s6/5fHJm7re3s/Afe7rfFf3hvntXAJyAE3ufnnvzwZMWh/NuQeuAxd8n959XClh3lUErhDztZ/efhAib9Bwi3wVNHjDYS83dkRcvpuGPjtXSr2BC9liDmZfQV8dxfzDqEuyIakyhRcBN/j+fS/OrLNlH2k3A18ZWSPCMHT+p8IvLQHdznCU0OoU6+bnh2sswS/bDGnQ/Cjk3UsLUbglw6d6SfUwTnxDvouLfDnu+zOEny0tI+iXwX8Ad3PKUKdVbaf/DMqB87xlsWJ4Gd1Vr/PSoJX9hdNEup4tdfW2qoQ+MKZHBuC7/5APv/tELi38HwPoU8Q9mQc/80G/lTYXYPgZrrcA+T7wBWH6Z8R+pCdi2LddNTgH7TruAg+My7fykwKfnLWOoLQ54g80ERcWxtwjrrNc4S+yLDY7BU/DnyK+4sGwTX2OlWIL4JrjgZkE/ou34+XCo9PggsX+GwS+rTWzfCHSkPgtcwZ6gTvDE1OP9UD3rn3XQKhDyy5lpuo3w4ulPSml9A3qq8/jTZrAK+/qsFMcKXpxlC7N+COzoJGhP7zoENvoPNTcI2LPJGEPtbOb87Hq+if52lWnxH63hD+LdfLueA1TcojhD5ZOGKPfXAGeCx3x29CX62TdcgyMvmffbOUZSO4RNhxo9sx4KZy4qKE/rxESVfrTjg4y5SuDKGfV1xwUMm6Cn4gR1w+FXOZtKty+b7glVUuUoR5YdUiRbLMHVz8YCQfYb5Y1C0VeuEATnaVYQ9hHuGIaz1UawU+8SZmkTDXsErNsDUbgw+Re9YQ5iBzJ7J9H7TBQ0IEIwhzU6AaL3WfKvhuBlGVOEKe/6pOOioP7qo8vE6Yy67ku27NHAV/+DM5hTDHiUbcxq0Ig4/aFgpGY87T9GLxKw/4cpJrOWFOfJ01MblzAPxZHKtABOYFBvTDuxnBd81u3r5B6D/ZlT/toQHPfiw5S5hb/+r4dTCRgb/ctyUSijmNo3mk/Nd12J8bPmeDCflZu+uy9gz4wyNlIdcwp6czdLHqBX+w0xB7lfD+kCFz9ybwYovn4YGE/jbCW/Pqc/B8knDHy4R+mG2vXMxjcP0pdjE/wj3VrhHKSAOXmvMYvUiIN7XAA0UR4D0dhpe9MSfXUKV54w8+sp2F98S8t4zjV5sT+KYzt6k75m07lCuDpv+s0zr1ngshf3ZRji5ogO9xLK87jzn1DGfXT2nwLE72ZnvMnx3WRlT84KOHLhfbEerRg4RKNmZwiy8mXtaYa8Ws5wqRg6tcPLHHAvNaE+9UuW9rRM/LLok8Q8i3qXSRWrPgLPlMg4aE38X5McCyD5xBaIRUD/P676/d3JrBXx+wJdUi1F/X99ZXXoAbP5rqVSfs8zca/Vv54FIMVUHKmD/2uqZ87w64QTUJToHQ588cOvYkElz158/jMoT11Pzle30ZfGvPG82jmPuUc7K1OYN/ZjvDJ0boZ1qv0w6agavt+dAuQOgnL/P/nT8FPpV5SIYH89gozs0fx8G/Hz/hykHIM9Ju85QC/6x/67c1M+Yr/HtHWFnAe0uV9u7FfPkKW48gBXjPm8ZwKsydW+JaZL+vQt7m164kxTxcxLdGcw5cJC7s3rY3HgXp9lRZ9IPf49gjt4n5HocXRa4t4Bl3b8QvYy6sKJgb+BLcXMc7dRrzHYOjGdEF4Ef26et8wVzyxVhy+l1wd6Ok8k+Y31Y8EVcYBW7w40FtO+ajXmciXwWAJ4S896/HXPCudFirC/jSvGvPS8xlPq5cGzAHJ6l7+rEU86v0cVfmT4MrMI345BH+HZ6fO+CHDHhXFF1pOuYMfW/8KQXB2xXsb8Rjju+74M/KCn5wbHI9DHPlKZ3LgpTgbwpTcf6YX2p0DZT9sUL0dAuPCDfM6a0GgzTnwQdlDPJtMN8srwq1GAAfYeUwNsB8Lwl9lGsruLV5ToQK4f1tZAmBr8BDBnIUj2He1lOcHl0ITk7z+fJhzI+p8jxKTwe3m5sQY8I8Ov9GZWE0eOea69ndmJNRrKJXgeD3JLYovnph/QMutKfVFfyk8oHD05jT3badHbAArzupUtGD+bP8/F/zmuBkw0OFCPP5ulCmn7LggVqnqMswV+PbJ0klBD6m39edgXnkdrgBGxt4wImPPyIxP2G84yNEBR6D8wn2xfyDdGma3M9loodOTtraYk7dgGq0FsBvMmimnMb8gLTrguUg+CT78wOSmK+S9rG6t4GLyx1dZyM8v6Cke/U1uJ5KNT0p5jxkQzdinvzz3acn/RcuYP3A2Hhdxj3wsFe5HN2Y30xJ+Ft0C/yTVDXJC8zTPh0+VX0F3LDVhPs+5oXkk4kdbuDMo8J+IZjT2NFMDFuCD73E/XDAnHl57viyFviLIKMiDcxvVNcn/5IDD1CbuCGA+dG5mU1aYfCrYhJhlJjbPH1ky3kAnMkbPZj3xCO+HKNOMWrwDFfK3hbMM5LU1JW2log+/8aXJx9zht7PDfqL4Hft7MJuYD6r5ah1dgj81VuulbOYZ/kbDni3g4u0bZ9TwNwxm8Qn9A14DNfRASbMhxbH9iYVgZez4/XWPLC4vWRRnZMB3kHqVNOCubzLF++nMeBsB/IOZWNOc3hCvPEqOPuHGn9/zPWNx398cgf37n3zTBtzRlKLD9NW4LxmaYNcmGe1tJd/1Qa/Ras0tuFO+Dta3QNyBfDAS/dRI+a7BRvTWUTAl1ZuBaZiLhzplCPIDj63MUxyHvO31SdeydGAp0tZmR/F/Hvh1Ij29iJ8t7/x0h83PPJ03NpnswQ+fueDUQfmJ8/wW1wYBo/4wb+chvlts31lwR3g7Nd8FM9ivqvPiymxGvxFh4ayAObxKxu3c4rBxVZk11Zcsfwfac5edR/816VP6lWY0122r34XC55UdUchAHOv7H7vviDwHxvbnXKYf6ePlpv3AO/O8Pu25YJH3w6eZtuyBvfzdS9/g/mbpDV6Wl1w/baT+EDMySsduLhOgOuVG7yVxjzeN1pDQhTcU2B114YzHl1LMYhU5fjnPdauLUWY074unThDC778YddvB8xZErMtXH4twPOpZHlsmFcuCy5fWQY3Ccmq+OCE9cMLZx7EfQGPs6Q6FI65C+XxC9nvwbmZfVePYd5pMGvz9C14424SxunzWD/pGXWhqQT8LfVgdDLmKx9UHw5kgv98z6J9EvOX77W+LcWBS672Gi464lF3Ta/Pn2vgjEoCd1MwT+YQZGC8AH5l9QCLAuYBj2IG+G3BM1uq28cd8GjCx6BVXg9c0WZvyU3Mn7N/nNBXBK9UZH/Oj/mHYV9+RzHw5iPDY832eKSa9/BuACe4i40OvxPmlxW7jsftAV+NdAwnwfyv57XdOTvzRN99knX1/jk8sqI6svvFCjgto7WjFOb2HAEyHSPgffUHvrSfxaO8PysPxjvB33qoGZ/FPOjKcflvNeADDbV1G3Z4tD34aw9tGbidvB9XOOZPWL4f4MkC/yql5boXc+rlaQfZ2/+45KG7mbZ4RLGeMKcfDH7958gjfswPv+oocvICV285G1tmg81r6/5l1+zA2f0i1KUwZ7xyeTNF/5/fmyXa/tIay5OhdcHFSuD7uiSZ5TDnydUzaBQHP5frw/PKijBfCLgOc4GLzDfOS2HeYHauA08H/rdlt2O5JTaviTEG0f6ZI3rOBH2sAOaUwy5X+NbAHTyrrR5Y4NHdksRWpTFwOtOJjr2Y2/xud7foAj9jZTUQZo6tx+ysg28d+CuBP1fWzfAoMyynMq4cnMa7sMgG88WidauCbHC3v+Lnm02xufXqy3MNCeCN4x4PxTDXEPNsGgkBX7OTtUw+g0d3qhJjf3qDGwp4RW+a4NH+tqfPmc6B05vNCZzB3I3B89RRQ3CS6GDJSmM84j/moGygDC67SJdNgzkJ/lS+pwS4raafu6MRdu4GA1djuMFH2WLjXxniUVLGOCrcC85wW4KUBvOU9ONBLX9niW52V7XBygC7R+k1JbPr4DZfs1sK9LF+JtHJgnwC/KGSIC1OD48eyomE8X8EV1ioviWH+X4xVuHT9eAHTE7IB+tieX5H1cy1EryuLZYF6WD52biLMiYHPD0pnv2PNh75Ua2qlySB71nhU1bAvEBrZE9XGLgdr3yInxY2b+bPO+MugptGVfQUaWJ9kYybCbMD+OZ1H6nR03gU+LKpT94YnCXCIYsO83uZvptnVcGF5H2oT5zC5o7juPKIo+AT5276OmvgUV37Z9oSHnDOxZjueHUsnktf0X3aB/55y4frqRqWl+y0X2+Rgh/CHzb7pIpHegXqe3nxM0S/4H/n4oYKHg0+9WHRnQKvuvDCnRbzBeH8Hv9P4JOsAQqHlbF5x6RD42EjuBnt+xHZk9gcerjXr6MK3F+xSEdbCevr3Focv+eBO1JRhlgo4tF07zPmw6ngAydGLjqewCNdgboko5vgLBy8XB4K2HynwDIY4gdO5fH5urc8VkeO7KyXnQeP8V+J8ZHDo3OX0cjoGfBlFs+TXrJ4NPWtLo9eA7ylxSDNVQaPvvK5n1aRBud4cC/y7HFsjuBW7LzEBz5vrbvHRBqPuFqa5QqYwOWCPXnVpLD+qu9R0vBu8GGlvw1HjuFRDWnE4N5v05DPH9HPsh7Fo2wGPubTs+BMCY8if0vgUQfOWDe4D/x6Q3vW+BE8ejS4HPqiGXzzW4JgnTgejZtOvFp7AU46R8aVIYbVU48jP4UKwMnPyV65KIpHYiWzp5zugreYqEhpiOCRsY5AQU4UuPWSlBaTMFZPZXgOjgWAh94XeTohiPU5EmzPOF3BL8gruxUJ4JHSkJ2HrQX4EZZEV29+POrqMdPO0gTP2KdQJMGHzcvN/mbjsuAfXzsKrvLiUWuYShqvELifw5GRAh48yiUzonVlA3fRbG6wPYTNcbd160upwJVLTT7Rc2N57+XK682fU0Q3+rmbqpYLmwf9/2yfWAQ3HaWzc+XE5pejdvGRQ+CvgvLe03HgUV/X90sf28GDbv7SrzyARw7VHc85q/953tlszIANj07jFy08isGr/TYCFlmw+GQIdHxzH/wF/T7GMGY8CjEuGKaOAyf7/LeIkQmPXmTWtthcA//eTC2fy4jNoTeZxCs8wWUiw96I7sPyiT4T025b8NDAav6qvXiE/yp7w1oP/MsfxivS9HjUz78npEoRXKB0qbhqDx71qkjQ7xEH/+xX+FqMFo8SzI3lXbnAh6afZ+ZR41HPYWmKJjrwSusIAyYqPBqmLbnG+2eS6GrKt9+HU+AR/b7MnBtr4M/k9emWd+MRR+f2tZkx8NULWvRGu7C5wOETk1Y3eE8ldXslKfbdyyculSHwzU5eOToSPCrndshkqgRveSZm7vwHhySGQtODc8D561q53uzg0G6fWa+FJPAD85kxVL9wyGltg98sHLyT0irtzBYOOScztr7zBb+3/5Xc/R841F/03lLaEZzTNMB35BsO3Y8tnyowATfNPyfP/hWHwnzOXuBQB89+qhF3Bo9D2ecTfydLgT8XJ3G8tYFDQgIU2TR84DFMAa9fr+FQI909s0gmcIbp1JiZFRzSXxIRIyMHn/ls9JF2GYd4Z58Lh3+bIHo/e3n0kUUcaj2naE42B37m0KtivXkcousZeBPZD15VEy7tMotDd3PKbGlbwS38jhy6No29h+Tr6dRX/zxftuAWN4lD3K0bYVxPwBm/z1Gnj+PQotoWY/E9cMNjnn+yRnHInPESuXwMuNxYo2rOFxxa/9Zl33EVvP2UZnfWEA755qWIn/UA34vs8u4OYOebbOD/1Rr82XTgy9g+HJr5kKd0Wxecs2M/ZdBnHLrcrJQipAhOfrIm0akHh3r3jgS1iIGH/6TS0+nGoQ0FLRJXLnDNgWxZ0Q84JJVqLUpDD358v6QB5XscyunDUdv/Hoc6dfl63FgbFg9ITOzpGLhLgvFyZQsO0ai6dFPWg0fNxLqHNOHQtXOvyZ1ywW1FGck0G3HolL75ZPMNcOlL45U09Ti0vRLnL+4ELmO65dtei0OWJrU990+BpwhcVr35FofSVV1o6QXBD/EHcsi9wSGBsgPS0VTg9lnHduZf4tDvo+FnKZbGiN7NujSe8hyHclNss+Leg98KXW+Uq8IhiqPhu1jLwPm0HucOVeDQ+eihR08SwIeTr165XIZDh3OcklUugvfrbqjvKcGhnfjj42PG4O9NM0iyn+CQxeilnJtS4PUZzCUiBTjEwmS+cIQZfJ8Ui0rVIxzq4xTtmPg+SvSyUNsa6Vwcqq83tMoYBL99spqzKhuHmDikiiyrwc8X7Dsr8gCHvOjMPhx8AH7rmllwVgYOrT47NbQcDM7LFxNIm47lmaHHE+gceFx1vbZ/Gg7d9OT5cV8V/C8XD24gGYcU1q9IBh8Gv0s64SGTiJ37t4AcF3Lwe1vqzxPjcWhX4ldri/kRiIfoxx3TMTh0+92An2E7eBWvR8mxaOyeku//a1ACLqFBb3o9ArvXBY8ZzG+Db3twNNaHE+Lnbo2TD3jBYfHNvyE4lBayw3LNGHx9z8aM/HUszme/SWVIgd/8wnPH+yoODW8XCyJm8A+2yaTZATiU7KhPsfrjC9SjKweF2vxwSMmVdYZ3GPy0VDXF6kXsXlzU7bOvAR8occnc442d11WptYJs8Cku2RkBTywPRBxS/xYGnjJuOH7CDYfOsngs6J4Hv2E/F6vrjENPHnnhi0+B4wRVZ80ccegYbcJlRiHw9E+vVqzPYfmZUirqBg34IYZnD61tsbz3qE3u18ow0W1ySndMrXDoS2ld7vVucFYjCTIdcxwq5rvVR1EFXvetv1z+DA5NPru/kJEGnu1lRMpnhENR7N7rxwPBN+5Y/aTSx6HonGt/hq3Ak3UaUha0sXweqSQSowjub+/a3Xgah65cPBKtwg3emqNYlq6OQz2jbcKkZODd79REXVWw+E+IEng/M0T0AM94raNKOET7bTw5uxU8iUtp93d5HKp+pBt2rRj8g1KM3QsZHGp5rUTheBvcgvLlGR8pHNLVFZQzuQjOHHVg7rAkDoUMXBbROwN+K5Gd6bMYDjUVp+AMZcCl3kqOXhfGoReGU7l2B8DDrWdUeARwSHr7neHlnUGic1zsOlnPi0NoM2lv+jh4SsG9fituHDpK9eBbYyO43unflGscOMS1KcmylQ/+SKT103U2HKLuSo2UjwFnf9kjQ8GMQ69DSSwjLoCnN1NJx+7D4kesOHfIEDwmz62Dih57vqg6QF4KfGXz91Y4DRbn68bLj1jA95fPNn6jwH5XYuT+A9sDROch1ed32oVD+Ufsd2WMgguf9uX58HcD/fgz0XW4AXx86eEryZ0NZKf4K+bNY/DPNjILCT83kHH5HS3rW+D8q7nP5r9uID/R2IMUF8BfNJxjP4HbQF2H8rlrDcGbKnc4Y1Y30HPO/HOhUuD0Isw1PYsbyNJOAa/HCm7KZvaTaW4DqZ2nWOb/1U/0c42Bn0ymNlBLdKYdzTh4ZLGmbtzYBkpLv2633QhecCH7fN3wBory5fzzrQD82X0nzpX+DVRfNGryOxa8Nj05gOnzBtI7yujD4AOe5CvqJ9u9gVTIfjlLnAGfe316v9n7DXTnY6uOtSy4sCWFpVcrtk50VzKZA3zcLVMt7N0G0uHyF+n920f0l5Snem+jDUR6yFr38Ay4jqAR/d23GyizVLIgpA28xIEVf+8V9jz3B/25UvBXbWThd59toGo2vKl1Mrjdi+iahApsP00Nu4Yvgw/eESoIL8HWExze6WoNTv7WX9mncAPV0DE6kiqDT/FRxVo82kAXJQJzCw+DnzGIi1Z4uIEu5e3Psqb6Z/0/q+TZMjdQWaGMK/tqL/Q/X5XzNu5uoKl1Dsb5HnC+9T+N71I20OuE5Yr6l+A18m1ZyQkbqA33xqQwE7w2NVTamvD/Q36J3pMZBh79dX8MV9QGUnZQW890Bq8yDc36Er6Bvq027inWAQ8IbPFLC95Axae7A5olwEWe/6TTurqBtFIPKK8xgU8jCe/v/huIwkMlkG/7M9FPBibefXhxA82Odkm6jYPbPzkVo35hAx1IUgx+0wQuPRqjNeW6gQybVr3YisFn+LP6r53fQO8DpZgiE8EzptuPM5zbQOeu6Yb/9QcPSj3v9tB6A0km2bdEW4N/z2i5KGy+gQyiY79yqYCb0Vsalxtj63Hq4mzkB0+KitxzRB+71+EHjfxpwQOnmx4/0dpAdW+sH0rjPsF5caVxHtTYQDnJRhy7BsDR3qsBCcobKNb5be94DXiqFumLLQUs/2RojHTkgYd9bhg+J7OBbLpuqjXdAu+msliqP7qB8hj/snZ6g1+0cZrjFN9AItyiXlOm4FWCaT1+QhtoX6KnCeUJ8Mgb6eXNhzdQIef+QQUecCNqgTBG7g30efw8fTAl+NWq31rW7BtIMCGRvGu1B/JJ9hRtFvMG8qx59UG8F7xvKfv9MMMGMuVZC3hQDW59kyxu/54NxD0kvY89F3zgx5SeJiUWz0UhpQXR4CpGHEwBZBsoVbPCUs0bnLyFtVX51zq6l5HJv2oK/tJS+noMbh2R/aE+XHgCfErfQb99fh3V3q6yv8gLHqcbrPJ3dB0pnVNe06IG/3P2oo1o7zpib9P7IrnxkeiaL0Uf63esI+0sd1mhAfBbtkWHXOrXUZEvK6NEHbjS1nK//0vsu586gk7lg4el/Om8WrqObG8uh3nGg58w+Up1OW8dKT7vlcr1AzcxWEhyubeOjij05c1Zg9ee+e1hkLCOvjZIjJ5QA497bpclFrGO7pJy4HOEwRvYThwhDVpHnPMNG8z7wJlNug53+qwj0Zjoj8dx3US/dswi4rbzOnqMd+s+Vw8e6MxpfspmHflKyu8UJYJL6Xk+3DRaR2osm/5M58A1R9Jd7p3G9tnlmsXDI+Bi4TtPpRTXkS5tboPOny6ia5NsRzcfXUcM+lw9LF3gN8/9WNMXXEdRv1Mf7coGP9HlsNrJuY5O56Sa7/MGT08qjVFjxNYfd4dS5ST4nxWjjnLKddS868/nRHrwuxxdL/b9XkM7hpxDJOMfiP5YtsjEE7+GajpEpFMr/vFjXoVv59fQlRUDMs0w8Nm24mqy0TU0Zpxhz2kMHh/4M0Xl0xr6VEt+YT8veJsfXuZy6xpKZ72mKrbZCf3wI4WynJo1dN/5/W+XJnCPtCs7jU/XkEnzs9p3d8BpgqxERwrWULH9SJaaKzgzX5LKSuYa8nAYrJ6WA3f/1au2mbSG6Kf5jxbSgK/szMrhIteQ/7Q41+2R90Tf8yJKeC5oDT07ppF5pxzc+UQYxyefNeTmWNhaHwYediSX+YXTGqp6HlZHfwb8fkXtwUSrNURDO5MZyg/ufbZCyd5gDdH1dV/b/7OD6H9Nza4Kqa8hvb9iQR0d4PaH0wbnZdeQwFRX1eMs8MD3Zo7ZYmuoQtJPNe8ieG1NDJcezxrKn29QfacOvtPNtw/HvIYuKup3U7KCU6vzaNymWUPS8cnkF5faIR8+D6k99HcVLep8+/urFtycWy2iZHMVReHbhkqSwXv6Lz8UX1hFovjT5aHO4NvhwiyFI6tIKSv1XqA8+DXWS+usPavoLHvts1Q6cO8h92NhzauIyuQte+9kG/SHxpJz429WUcqIz4LcS/CTekv7ZMtXkcp6vmxjLLj6QENNZN4qItdiPHzxHLiN4tzq+7uryI31TLOaNPibv3Gl1HGriG1hXU6BGrx5dOXvydBVFHHT6p75WCvRO9o11z39VtHCp8Xf6c/Ao1YnwpNcVxFfzfTNP7fA84tIUanNKqrduqQRexbcKP1nWb3hKrJdLbE6IQ0+H3vAvFN9FfFeiBvdRwO+k15b1y27ioQjvi/STbQQvYhFfb1DFDsXhep7Ei/BLYvp1mu5sedV43YFxoNT60Q1P9m/ihgek2vMOIIf1uEIiqNcRce9Sv0C5cFHXVWYXH6toL6TiyWSDOAK/d6ZcusrKHualoJhvpnoWXr8rLumV9C1Xu1M5jrwNZaFhOb+FfT2WW2E6h1wTUFVmrCOFeRQ6/Il9QL4QeH6pGN1K8hPTOj1Hg3wmTvbwqNPV5DgnTapUg5wivdxo6H5K6hbCudyabOJ6Lo8zM/YM1aQraS4x7n34GHkJ6vK4leQa/+Cmd8j8HOMz6fkwlZQasNFtfJr4FWiono1fitI5s+GJoMpeNp9u++yritI8qB/SIYY+HuRPYsl1itoSnXqtzY5OJ/2H1E2gxVkxEwyxjP2juhveclar6ti+9bgJcPzCpyleaVhSHoFCXzKP6iVBI4/eZ9PQmgFqTPslN11By9qWP1+nWMFORo/+LVHHZzqXY/KO/oVFK0Yc7CEE/wCtxwNGdkKmtudKe77vZHotIrsNvLflhEjR4jyuY/gMsJXT7gvLCP+vqcel4vBA5vsniV/WUYh9NHNzyLAbYcHO6q6llEVOujCfg78s+au2M6GZaSc6OZYJA++zv7n59jzZezO8Hy0ZwL/WoXnXipcRmWop0llvQHu3Tgj5dr9ZbSc1Gmm3QE+9+fey6Xby4jKWvxeUD74fo42mYmwZWTzsT+nNwz8A/lKYpffMlo55RthYQtu7GfV8cJlGdGxuVvskgPv2e+9dsdqGY2zr4oP7gdPLUna7aO3jOjJVjn61+uJ/lz4KLOq8jJabGE9/vs9eHxtm9CeY8voB+1wvP4T8OKlIc2PfMvocIitTGsEuE/mRtBt1mUUI3VDw8MBXOVYXoc6zTL6STnfLnMS3CjjtvLmzhKS+jE6KMYBTm5sM5W5voR2L41RZGDj0/93/PXat0pTS0g+quKlaAm407pP72DvEqKNpZnZ5wIeIyV33Kt1CfU+En+qywPOc3d2bvvNEtKifq48NFIHdUrMGB9euoTEmFIrq++Bh36xsyd7uIQUR1j4NkzBjax+yl9PXkJk3WNvru4DDz7Gemv95hLyOT2cZNFVS/SK9uoztgFLyIT7VGtMHDifxWp+o9sS6jN6HMSgDc421xjNa7OEnKIaW5cpwHWMrMiu6y8h99rSDo7mGog32cGD3cpL6OxCeXbOTfCDvy/OcRxbQi33jM4GqYGrvDrr6Mi3hNKeGh8uIgU/wDeXmceyhJIOF1KIN7wleuV9swcjVEvI9kXgIYpwcLet3V4MvxZR5iDbLWlVcK4UM9aTq4to6Dat6WtS8M/7qx47jy+ih5ZbGcmN1VBffBMORvcsIpZTT73rb4I3trkm5L1bRP4k/HMap8D3qjT9fvViESmSu+znpgT3XjoW0Fq4iORG8qgM298Q/UWeLmlPxiJavsQ30BsH/nau/Elv3CKiuKWbWGkA3lpBHvApeBHZHklQmdoHnqtF6tfhs4iKXC5vufe9hr6Ix6aoxmER3fh4v1UzA/xXTi9v0ZlFVHKp4NU1O/DyrzKLiacWkWimXh85L7jGqAmFr+wiMhvQFZ2bewXxFkQSoSe8iPbu9nzHWQrusZ/7Ai/HIkoLCCwo8gW/Op7Wht+ziGaU1EfiZcF5Owwe1f5ZQBvXH3m2/H4J+VZWheLmxgKKGvW2Nm8CL2t2/KU2tYDeclwvU4wDH6V7Gf/78wIKKspxu2oC7uyo3FTVvICy3SsS9rCDx8dTlzq+WkD94YE83ydfEP3eLT4DuqIF5Kn2jkemGLxbJf951f0F9J7XIrHzEriXZv6iSfwCqujZcHtzAvxlotqP1WDsuxanS3d2g2sIPJy/6bOAInTIze92PSd6ycJEE5PDAqLd98kh6h54muLRjByTBeQhrdnR6Qju3VLjLaixgEzR11vu4uCd3M8Mi44voOIn5+7a/nxG9KTbp08LCGLr1CJdyn8H/vVFiW022wIKHDgddCoRPMH8QNY+mgUUupmkeMIG3Hq7dV/Yr3nkKyHFHy0IPl6Ba1pcmUd6BX6Cwl+roN6hnnqDsXmkdSf2OE8DeJvD470V3fOI+leuik8C+KWAgrc0DfPow4k+uf224HgF5m6Hqnnk0iFJRycC3k56xPT5o3n0re9pie3Pp0SfWhQ3I7szj07vnCIlawWXvWs8ohs1j8ZI3m/t3AFvnO3dTAqcR7m36MP0ncGrSvD5PW7ziG34Q/CmNPiK68wOnTX2/rwXX9Z2gw/9nSQ7rTuP9tc5hCv3VRL9ZiBP41XFeWROZWc2mw9OUtKvUSQ+jzLFeJQmAsAlqaTu9B6cR+shLFySWuB1Ws61v/bOI+6h1MHeA+AXxTJaD5LOI8qdmkcPBipg/VI/apXwc8iY0rRX7jq4tfXjYsvpOZQcK7krhAf8/qeGdJ/eOXSr5tKaZ2s50ZnqLyTeaJ5DdWdZTci8wak3azOTX84ho/Ef8yrM4KmP2lseFM6h72kdroK1ZdCXij1kf3xvDkmyHY5+4Qwe3KaVWxgzh+7UXNpaoge30X7vVBg0hxTEqS+2vi6FvmuA3+eR5xySkmC+r3Me/PET445M2zl06HY+nz89eDZSDUvSn0OFR4qr1atLiB6dN3U//OQcSjz7bfcbF/BEVnY+H4k5tKaqVPx5PzhurIXf6tAcunmDyzC1oZjoSl71Rcr75tCuIwfu/vABj8jvf8NLNodevH/ATcIN7p/ac45scxa5F5HElnYVEd2T3zd/bHoWBdjH+e6EgMfNXUh71TuL+FL9L65LgE+89pO53TyLGqbmD0ZOPoG6kCh659zLWeR7kGp/bSr4A+Gj1UcKZ1FXMX7i7mnwvvesFdvps+g87zt2xu1CyMM7bsHvbs2iXRLpRkfKwT8oPT4Sc3UWUT1IYVh2BFfuONmp6zGLPHKn5zTZwL8YPjpHazOLkl1b7TS6Coj+vfQovlV3FoW+S/g9HgG+v+zk7XDFWdQk8kiPXRHcpWW/gpz4LDo2FteN38wn+vbAGukK1yzarbNJ5V4KnrxAuvaAfhY9zyi9et0ZXH/uEqXu3xnkFPwmR4wb/LirjcX39RlkfdDo15Whx9BnerTNZU/MoH7lyd0OaeCzHNV1Gj0zCBsXZGcMwePvHF6Yb5hBod9JaMj2gPsVLHneqppBTzy7N9+0PSJ6Vvq8icCjGaTrxu9OGwUeuTmT35A6g6oHtka+qYN3Gjz0so6YQXXb+fVXyMANGZurNvxnUJXrys3Uhjyivzn9PTjCeQZNc5HcORUOnuHQNMBsPoP0i+LsE1TBKZmq2h6fnkF7TF8be5GBT7JLWR2VnUFy549/mnyXC/HGUJr8VnAGHbdT1lmOBO9VuRSkzjaDvlgUHorRApcMfs/RTjWDDPWHq6tpwXW/rgbrbU2jRwEL10O7c4i+QU1S9GFxGhWVxLf3p4LTH2XL1xueRmmtUmT1luBqrYpB7R3TiItxd7TCQfDvuPOSGm+nUatVu1dc20OiMwb7ddeUTKNCaprxBjNwxbcq56QeTKPchDZ21pls+L2uSfOF8dOo88XTgRg/cO0YlovswdPI96VEB9tu8HWLAJI4r2lUKnH1ceOdLMjDvGo5W3bTqFwkhyVKCFxW5pe5i8E0wnHndjnUPCD65fZ9Yj0np9Gu375XTI3BOWdnBBQkplGX4L462/lMoj8xbjTI5Z5GYdfSNK+GgC9FzBVTMEwjPwW5t09YwN2Tr6t5kEyj9nWv2sWK+3BfWLM5Ozem0IjC8oaCDvigzBkVsckppBLy+vv92Qx4T0TK89ieKTTlqexNdQOc4Y9K2HzDFHrmavUtnBu8iuxYsVrVFDKsthOiqLsH9U5HUP5B3hRiuC2Rl2oH7jf1UepryhQiKdLdEfqTTvTX/B9ydG5OocP4vq6mh+DBtU+iHvpNocl7BZXOauCl2WPL+PNT6P4vc1maubtEf0gz2K9hOoV4pAx+VMaCsyWv6N/RmELupz7ctJQEr9zvaDEjPYXubG97/+2/Q/TajgtbR/mx/TFe134cAv5AV0IhhHkKvUqse3xKENw8qZq7nXwKXd64ST/1MY3oOST0lYzfJ9HYgifzlWvgbNdZcdZzk+g2dd1pCkHweudnC7n9k6gpcO5I3OdUiIfK0gfzLZOo6G+IFXk4+NvVGkaxV5NoN7Iw9pMAz7WON/IpnERH3UJzPo+lwO/FPbV5mj6J/nDqfuRLBB8KeiaPj55EZybt3J1VwFOyyDeOXplEJfkVm6n4ZPhdm7QRF90m0afF1O/l+eDtnAd+lVlOItxP9PO5FbjBZ2/rJS1s/fVGYY/pwY+Snizkl59EL059ZLzelER00f6CuXPCk8jnjcJxhWvgRmOvuTIOTCI16V0XRo+B6x/wM+6hnkSPpSQD2voTIV8xNkVRbU+gUMsu3fva4M9/xDSeXJpAqU8az4rXJRD91/MUav/hCXRPa+dZiDR4Oc0D+ycdE+iyXIhhXOltol99cqbzS/UEOu/uLG0kAN572sKYvmQCxXqvOXXkxhOdrkH6q3LmBHLqDZr6fhA8RcLjzcW4CbRH9G7Zp6w4ojuRueTnXJtAqt3bzdYHwWs4omu6PScQf/BdkficWKgvS5y7/thg63+ZMHSeDzwryjVYVG8CNZOf+jhWFAP9WHu6hKXiBJrgtaHdlgTvcu/mihCbQHfIXkVVvbkFdecAj14F5wQS7olSItcA18lKqhvaM4HmRjRE1rujiW78iR9PsT2O1H3fnvayA3e5wvnXcngcRT6iir++EgV5PuB5SVH1OGLdl4c/EAx+kCPs78/746g10fKS2l7wmeWvpJrXxhGu24ZsMy+S6OqTntWpNuOocUMpQ0gO3DCTR3L8xDgqp/ghNtEVAfk5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28891.32
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- Vector Display Ex
- Preview vectors in the viewport
- true
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- Vector Display Ex
- Vector Display Ex
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27264
76
84
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- Start point of vector
- 5550e5e9-4471-419b-8cdf-22d1a7c9f9f5
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- Point
- Point
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48
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- Vector to display
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- Vector
- Vector
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48
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- Colour of vector
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- Colour
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48
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9185
27316
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255;0;0;0
- Width of vector lines
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- Width
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9161
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48
20
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9185
27336
- 1
- 1
- {0}
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- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
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- 92df39c6-f1a0-40bf-be65-baededdefc8f
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- Format
- Format
-
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130
84
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28634
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- Text format
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78
20
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8676
28604
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- Formatting culture
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8637
28614
78
20
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8676
28624
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- Data to insert at {0} placeholders
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- Data 0
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- a16e0194-897c-4ae3-a86c-9b0a83b06ed2
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8637
28634
78
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- Data to insert at {1} placeholders
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8637
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78
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28664
- Formatted text
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28594
24
80
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8751
28634
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
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- A wire relay object
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8557
28579
40
16
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8577
28587
- 9abae6b7-fa1d-448c-9209-4a8155345841
- Deconstruct
- Deconstruct a point into its component parts.
- true
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- Deconstruct
- Deconstruct
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27316
120
64
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27348
- Input point
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27318
27
60
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8500.5
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- Point {x} component
- c5098eba-f62f-4204-b86a-be1c52aae0ee
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27318
65
20
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8570.5
27328
- Point {y} component
- 5da2d624-4c9e-4761-99f7-447ce0d151b3
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- Y component
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8538
27338
65
20
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8570.5
27348
- Point {z} component
- 5c28713c-6330-4532-b78c-b6594dea3eb7
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8538
27358
65
20
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8570.5
27368
- 74cad441-2264-45fe-a57d-85034751208a
- Explode Tree
- Extract all the branches from a tree
- true
- f74eae17-b09c-46ae-a891-13e3f5c122a6
- true
- Explode Tree
- Explode Tree
-
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27283
78
44
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27305
- 1
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- 2
- Data to explode
- bf93038e-70a3-4294-8e4e-1255776bb924
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- 2
- Data
- Data
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41
40
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8687.5
27305
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- All data inside the branch at index: 0
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8724
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9
20
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8728.5
27295
- 2
- All data inside the branch at index: 1
- 9d43af13-00f9-48eb-b21e-66c4781aff05
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8724
27305
9
20
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8728.5
27315
- 9c007a04-d0d9-48e4-9da3-9ba142bc4d46
- Subtraction
- Mathematical subtraction
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- true
- Subtraction
- Subtraction
-
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27278
70
44
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27300
- 2
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- 1
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- First operand for subtraction
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- A
- A
- true
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- 1
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27280
11
20
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- Second operand for subtraction
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- B
- B
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- 1
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8822
27300
11
20
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27310
- Result of subtraction
- 33c98b11-df16-46d3-b656-96b33d6aef91
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8857
27280
31
40
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8872.5
27300
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
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- Format
- Format
-
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130
64
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- Text format
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8801
27191
78
20
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8840
27201
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- 1
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- Formatting culture
- 6857890b-c6da-48dd-b132-9e47656b3e39
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8801
27211
78
20
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8840
27221
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- Data to insert at {0} placeholders
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- 0
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- 1
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8801
27231
78
20
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8840
27241
- Formatted text
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- Text
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- 0
-
8903
27191
24
60
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8915
27221
- 59e0b89a-e487-49f8-bab8-b5bab16be14c
- Panel
- A panel for custom notes and text values
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- Panel
- X0-X1
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- de99d806-0033-411c-be6e-993093e9e3ee
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226
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8732.647
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255;255;255;255
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- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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- true
- Merge
- Merge
-
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27279
90
64
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8974
27311
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Data 1
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31
20
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- 2
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8931
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31
20
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- 2
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- D3
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-
8931
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31
20
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8946.5
27331
- 2
- Result of merge
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8986
27281
31
60
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9001.5
27311
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- d07e1734-c175-41dc-9d25-373919246eee
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- Evaluate Length
- Evaluate Length
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10108
27619
142
64
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10186
27651
- Curve to evaluate
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10110
27621
64
20
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10142
27631
- Length factor for curve evaluation
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- Length
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- 0
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10110
27641
64
20
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10142
27651
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- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Normalized
- Normalized
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10110
27661
64
20
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10142
27671
- 1
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- Point at the specified length
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27621
50
20
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10223
27631
- Tangent vector at the specified length
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10198
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50
20
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10223
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- Curve parameter at the specified length
- 0b8eff06-2ff1-453a-ac98-75c220a7d25a
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10198
27661
50
20
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10223
27671
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- Rectangle 2Pt
- Create a rectangle from a base plane and two points
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- Rectangle 2Pt
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198
101
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10150
27549
- Rectangle base plane
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10016
27500
122
37
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10077
27518.5
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-
0
0
0
1
0
0
0
1
0
- First corner point.
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- 1
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10016
27537
122
20
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10077
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- 1
- 1
- {0}
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0
0
0
- Second corner point.
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- 1
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10016
27557
122
20
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10077
27567
- 1
- 1
- {0}
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10
5
0
- Rectangle corner fillet radius
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- 0
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10016
27577
122
20
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10077
27587
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- 1
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- Rectangle defined by P, A and B
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10162
27500
48
48
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10186
27524.25
- Length of rectangle curve
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- Length
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10162
27548
48
49
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10186
27572.75
- 74cad441-2264-45fe-a57d-85034751208a
- Explode Tree
- Extract all the branches from a tree
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- Explode Tree
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27624
78
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- Data to explode
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- Data
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- 1
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27626
41
40
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10321.5
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10358
27626
9
20
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10362.5
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- 2
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10358
27646
9
20
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- a10e8cdf-7c7a-4aac-aa70-ddb7010ab231
- Box Corners
- Extract all 8 corners of a box.
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94
164
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- Base box
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- 1
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21
160
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- Corner at {x=min, y=min, z=min}
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10166
27330
45
20
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10188.5
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- Corner at {x=max, y=min, z=min}
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- 0
-
10166
27350
45
20
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10188.5
27360
- Corner at {x=max, y=max, z=min}
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10166
27370
45
20
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10188.5
27380
- Corner at {x=min, y=max, z=min}
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-
10166
27390
45
20
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10188.5
27400
- Corner at {x=min, y=min, z=max}
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- Corner E
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- 0
-
10166
27410
45
20
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10188.5
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- Corner at {x=max, y=min, z=max}
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- true
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- Corner F
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- 0
-
10166
27430
45
20
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10188.5
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- Corner at {x=max, y=max, z=max}
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- true
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- 0
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10166
27450
45
20
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10188.5
27460
- Corner at {x=min, y=min, z=max}
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- 0
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10166
27470
45
20
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10188.5
27480
- fbac3e32-f100-4292-8692-77240a42fd1a
- Point
- Contains a collection of three-dimensional points
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- true
- Point
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- b4ccb984-448f-470a-80f3-02e69cdd354b
- 1
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10154
27304
50
24
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10179.66
27316.02
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- Polar Array
- Create a polar array of geometry.
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- Polar Array
- Polar Array
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191
84
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10295
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- Base geometry
- 6a69a647-aacb-48b8-ab0e-694504f42f0f
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- Geometry
- Geometry
- true
- 029f8972-c08f-4c74-9db9-d1602083474e
- 1
-
10170
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113
20
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10226.5
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- Polar array plane
- 8b5aac2a-2c0b-4d67-90cb-023cbd588d4b
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- Plane
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- 06ecc8ab-7209-4438-836b-119c5732583d
- 1
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10170
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113
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10226.5
27202
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0
0
0
1
0
0
0
1
0
- Number of elements in array.
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- Count
- Count
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- 0
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10170
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113
20
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10226.5
27222
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 420355a6-aff5-4db9-a9d5-990bea2c4892
- true
- Angle
- Angle
- false
- 0
- false
-
10170
27232
113
20
-
10226.5
27242
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- e68c5fe8-1fed-41da-98f7-f3dac4eb9545
- true
- Geometry
- Geometry
- false
- 0
-
10307
27172
50
40
-
10332
27192
- 1
- Transformation data
- 534ccd7e-686f-40ce-936e-3a8bf42c0ed5
- true
- Transform
- Transform
- false
- 0
-
10307
27212
50
40
-
10332
27232
- 74cad441-2264-45fe-a57d-85034751208a
- Explode Tree
- Extract all the branches from a tree
- true
- 8ee13ade-d6bc-48c9-a10e-035cd34ec578
- true
- Explode Tree
- Explode Tree
-
8696
27090
78
44
-
8751
27112
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data to explode
- f0706de4-e458-45ae-8fe4-2e2801f1a5ff
- true
- 2
- Data
- Data
- true
- 484ba687-c0e4-4304-a4c9-f88e8e6271cc
- 1
-
8698
27092
41
40
-
8726.5
27112
- 2
- All data inside the branch at index: 0
- 15ba0a9e-7c13-47c9-a120-0c7ab3977abd
- true
- false
- Branch 0
- -
- false
- 0
-
8763
27092
9
20
-
8767.5
27102
- 2
- All data inside the branch at index: 1
- 49801c49-68b9-499a-8324-7a78a638a3e8
- true
- false
- Branch 1
- -
- false
- 0
-
8763
27112
9
20
-
8767.5
27122
- 9abae6b7-fa1d-448c-9209-4a8155345841
- Deconstruct
- Deconstruct a point into its component parts.
- true
- f3f58225-4602-49ba-91e6-6b555431f93f
- true
- Deconstruct
- Deconstruct
-
8828
27095
120
64
-
8869
27127
- Input point
- ef106332-e5b6-400b-9328-8410a73fba9d
- true
- Point
- Point
- false
- 49801c49-68b9-499a-8324-7a78a638a3e8
- 1
-
8830
27097
27
60
-
8843.5
27127
- Point {x} component
- 3c6f247f-4c49-4f68-b5b5-0ff3d33ed74d
- true
- X component
- X component
- false
- 0
-
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27097
65
20
-
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27107
- Point {y} component
- c349f021-de67-4c6a-85cc-018bf530b608
- true
- Y component
- Y component
- false
- 0
-
8881
27117
65
20
-
8913.5
27127
- Point {z} component
- 331e46af-08fb-44cd-926d-c48814f1b83f
- true
- Z component
- Z component
- false
- 0
-
8881
27137
65
20
-
8913.5
27147
- f12daa2f-4fd5-48c1-8ac3-5dea476912ca
- Mirror
- Mirror an object.
- true
- d58d961c-ae9c-4fab-832b-12998948c201
- true
- Mirror
- Mirror
-
9505
27527
126
44
-
9567
27549
- Base geometry
- b2a4d631-1ae1-430c-ac1f-6e7474481ae5
- true
- Geometry
- Geometry
- true
- fbe57887-2062-42c7-8b43-1b8cbf0f868c
- 1
-
9507
27529
48
20
-
9531
27539
- Mirror plane
- f5855df0-191f-4026-b8aa-26f9286fb056
- true
- Plane
- Plane
- false
- 4825d5c1-ae87-4bbc-96d9-f6813501ff2c
- 1
-
9507
27549
48
20
-
9531
27559
- 1
- 1
- {0}
-
0
0
0
0
1
0
0
0
1
- Mirrored geometry
- 1af07c62-ff38-4cdf-aee3-f6ec7a28a8a9
- true
- Geometry
- Geometry
- false
- 0
-
9579
27529
50
20
-
9604
27539
- Transformation data
- 39ae8c27-b896-4798-a3b2-59a4b6329b04
- true
- Transform
- Transform
- false
- 0
-
9579
27549
50
20
-
9604
27559
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 3a0b8b19-f25c-4518-a98f-627474f69fab
- true
- List Item
- List Item
-
8779
27541
77
64
-
8836
27573
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- 1001d769-275c-4259-b1ac-c87542504c18
- true
- List
- List
- false
- 970781a8-0343-4bae-b5a7-02468ff37b8e
- 1
-
8781
27543
43
20
-
8802.5
27553
- Item index
- 097d2964-74f2-443f-a872-0e24902794a0
- true
- Index
- Index
- false
- 0
-
8781
27563
43
20
-
8802.5
27573
- 1
- 1
- {0}
- -1
- Wrap index to list bounds
- a14f2e60-f3b0-4b1f-9664-41adbbd76081
- true
- Wrap
- Wrap
- false
- 0
-
8781
27583
43
20
-
8802.5
27593
- 1
- 1
- {0}
- true
- Item at {i'}
- 4ed77016-2fe9-49fc-9c97-a8f70ec22370
- true
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- Item
- i
- false
- 0
-
8848
27543
6
60
-
8851
27573
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
- b1a15299-df6f-41a0-bae3-3358fad867da
- true
- Line SDL
- Line SDL
-
9578
27409
111
64
-
9653
27441
- Line start point
- c1c4fc3b-1eec-4434-83fc-26979a82bcf3
- true
- Start
- Start
- false
- 4ed77016-2fe9-49fc-9c97-a8f70ec22370
- 1
-
9580
27411
61
20
-
9610.5
27421
- Line tangent (direction)
- 573f9951-0238-4b24-963e-4796a8be1751
- true
- Direction
- Direction
- false
- 0ad32c15-e0bb-438f-9a7c-fa7f5af22f77
- 1
-
9580
27431
61
20
-
9610.5
27441
- 1
- 1
- {0}
-
1
1
0
- Line length
- 6de70698-9aa8-4be6-af4b-a303befbc25f
- true
- Length
- Length
- false
- 0
-
9580
27451
61
20
-
9610.5
27461
- 1
- 1
- {0}
- 1
- Line segment
- 4825d5c1-ae87-4bbc-96d9-f6813501ff2c
- true
- Line
- Line
- false
- 0
-
9665
27411
22
60
-
9676
27441
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 54492cdf-eec5-43f9-b305-c633663f407c
- true
- Merge
- Merge
-
9677
27561
90
64
-
9722
27593
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- fd0b6619-1604-496d-ae9f-03fb46558d80
- true
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- Data 1
- D1
- true
- fbe57887-2062-42c7-8b43-1b8cbf0f868c
- 1
-
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27563
31
20
-
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27573
- 2
- Data stream 2
- f9761a1d-3802-42d1-bef0-f0706c242541
- true
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- Data 2
- D2
- true
- 1af07c62-ff38-4cdf-aee3-f6ec7a28a8a9
- 1
-
9679
27583
31
20
-
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27593
- 2
- Data stream 3
- 3d143dcc-983f-4265-bbd5-3cca664fd9f5
- true
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- Data 3
- D3
- true
- 0
-
9679
27603
31
20
-
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27613
- 2
- Result of merge
- 7b24f9ce-d158-4f9e-8e14-e345e0de6d31
- true
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- Result
- false
- 0
-
9734
27563
31
60
-
9749.5
27593
- 8073a420-6bec-49e3-9b18-367f6fd76ac3
- Join Curves
- Join as many curves as possible
- true
- 0d824c3b-96fc-42d2-a484-6f796091f7f8
- true
- Join Curves
- Join Curves
-
9044
27636
132
44
-
9127
27658
- 1
- Curves to join
- 9c3fee6b-58aa-41ca-93bc-ef2f1243c2b2
- true
- 1
- Curves
- Curves
- false
- 7b24f9ce-d158-4f9e-8e14-e345e0de6d31
- 1
-
9046
27638
69
20
-
9088.5
27648
- Preserve direction of input curves
- cc5a0252-614e-4554-b451-d40d7f81c38e
- true
- Preserve
- Preserve
- false
- 0
-
9046
27658
69
20
-
9088.5
27668
- 1
- 1
- {0}
- false
- 1
- Joined curves and individual curves that could not be joined.
- fa54f823-8a2e-4f67-8c01-f0cd00a64ba4
- true
- Curves
- Curves
- false
- 0
-
9139
27638
35
40
-
9156.5
27658
- 75eb156d-d023-42f9-a85e-2f2456b8bcce
- Interpolate (t)
- Create an interpolated curve through a set of points with tangents.
- true
- 547daed3-e526-468b-800a-64b6209048bc
- true
- Interpolate (t)
- Interpolate (t)
-
7752
27939
244
84
-
7944
27981
- 1
- Interpolation points
- d1922547-7b3c-4853-8b35-dc9cf830798c
- true
- Vertices
- Vertices
- false
- 970781a8-0343-4bae-b5a7-02468ff37b8e
- 1
-
7754
27941
178
20
-
7843
27951
- Tangent at start of curve
- d486fe76-ae79-45ad-8054-bac4bcefd8fc
- true
- Tangent Start
- Tangent Start
- false
- 0
-
7754
27961
178
20
-
7843
27971
- 1
- 1
- {0}
-
1
0
0
- Tangent at end of curve
- f1998f4b-2ddd-46c3-9feb-f37c4f3ece6d
- true
- Tangent End
- Tangent End
- false
- 0
-
7754
27981
178
20
-
7843
27991
- 1
- 1
- {0}
-
0
1
0
- Knot spacing (0=uniform, 1=chord, 2=sqrtchord)
- f99689a7-e708-475b-b74d-a577d35e724a
- true
- KnotStyle
- KnotStyle
- false
- 0
-
7754
28001
178
20
-
7843
28011
- 1
- 1
- {0}
- 2
- Resulting nurbs curve
- 473f7647-6e58-4b9e-91d2-8f585d5a6649
- true
- Curve
- Curve
- false
- 0
-
7956
27941
38
26
-
7975
27954.33
- Curve length
- d2ed8027-a0e0-498f-a043-e358e6bb5ab0
- true
- Length
- Length
- false
- 0
-
7956
27967
38
27
-
7975
27981
- Curve domain
- 1f348736-b2e3-4af7-86af-c1a614441e90
- true
- Domain
- Domain
- false
- 0
-
7956
27994
38
27
-
7975
28007.67
- e9eb1dcf-92f6-4d4d-84ae-96222d60f56b
- Move
- Translate (move) an object along a vector.
- true
- 49641e2a-6345-4e2b-a88c-65b810efe4e3
- true
- Move
- Move
-
10272
27361
142
44
-
10350
27383
- Base geometry
- b507da92-7dc2-480a-9fa1-0f0e90fa2618
- true
- Geometry
- Geometry
- true
- e68c5fe8-1fed-41da-98f7-f3dac4eb9545
- 1
-
10274
27363
64
20
-
10314
27373
- Translation vector
- 42a20604-cfcb-42de-99b2-15990d9215e3
- -X
- true
- Motion
- Motion
- false
- 06ecc8ab-7209-4438-836b-119c5732583d
- 1
-
10274
27383
64
20
-
10314
27393
- 1
- 1
- {0}
-
0
0
10
- Translated geometry
- 9f7378b6-9894-4b84-998a-f5226749112f
- true
- Geometry
- Geometry
- false
- 0
-
10362
27363
50
20
-
10387
27373
- Transformation data
- 3b7e5e45-5dae-4b9a-a940-d75a94b88f48
- true
- Transform
- Transform
- false
- 0
-
10362
27383
50
20
-
10387
27393
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- 921a4c47-a14a-4ae8-a939-3fa685fa688d
- true
- End Points
- End Points
-
9466
27790
84
44
-
9510
27812
- Curve to evaluate
- c0dcc44b-e03a-4be2-b2ca-2d753dc405e7
- true
- Curve
- Curve
- false
- fbe57887-2062-42c7-8b43-1b8cbf0f868c
- 1
-
9468
27792
30
40
-
9483
27812
- Curve start point
- c475072e-1fe0-42c5-b3e5-ace9a4f477bc
- true
- Start
- Start
- false
- 0
-
9522
27792
26
20
-
9535
27802
- Curve end point
- 796038b0-8393-4141-a4f4-fa10cae2524d
- true
- End
- End
- false
- 0
-
9522
27812
26
20
-
9535
27822
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- be9b2731-1a06-4cce-84c1-1c4881f7601a
- true
- Line
- Line
-
9615
27790
102
44
-
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27812
- Line start point
- 3025a762-b90d-46e1-81c6-2d91538603f9
- true
- Start Point
- Start Point
- false
- c475072e-1fe0-42c5-b3e5-ace9a4f477bc
- 1
-
9617
27792
52
20
-
9643
27802
- Line end point
- 950fbbca-eba8-46d3-b614-dfc70b04ce67
- true
- End Point
- End Point
- false
- 796038b0-8393-4141-a4f4-fa10cae2524d
- 1
-
9617
27812
52
20
-
9643
27822
- Line segment
- df9ef313-9e68-44f2-b57a-df8a5f0a17a3
- true
- Line
- Line
- false
- 0
-
9693
27792
22
40
-
9704
27812
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 98c446bc-5e7b-4949-bc4d-55a5abdcc6dc
- true
- Evaluate Length
- Evaluate Length
-
9759
27781
149
64
-
9844
27813
- Curve to evaluate
- 0e75f930-85f2-4e6f-a02a-e76d332f1e8e
- true
- Curve
- Curve
- false
- df9ef313-9e68-44f2-b57a-df8a5f0a17a3
- 1
-
9761
27783
71
20
-
9796.5
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- Length factor for curve evaluation
- a7c5e0af-e582-4ad0-93df-3660492d36df
- true
- Length
- Length
- false
- 0
-
9761
27803
71
20
-
9796.5
27813
- 1
- 1
- {0}
- 0.5
- If True, the Length factor is normalized (0.0 ~ 1.0)
- d300cf4d-5b21-482f-98fb-a6424261ff24
- true
- Normalized
- Normalized
- false
- 0
-
9761
27823
71
20
-
9796.5
27833
- 1
- 1
- {0}
- true
- Point at the specified length
- 25200f80-2e95-4f38-ab66-a92c473cb11e
- true
- Point
- Point
- false
- 0
-
9856
27783
50
20
-
9881
27793
- Tangent vector at the specified length
- aed17c8c-373a-4521-b837-4c123720e32f
- true
- Tangent
- Tangent
- false
- 0
-
9856
27803
50
20
-
9881
27813
- Curve parameter at the specified length
- d10df88d-d7b4-44a1-ba2c-423feaf79c00
- true
- Parameter
- Parameter
- false
- 0
-
9856
27823
50
20
-
9881
27833
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
- 6702c62f-e4c0-49b2-83f6-4419cd923fb7
- true
- Line SDL
- Line SDL
-
9968
27793
94
64
-
10026
27825
- Line start point
- 2ef5a359-b0b1-41a3-982d-a20728a8dc11
- true
- Start
- Start
- false
- 25200f80-2e95-4f38-ab66-a92c473cb11e
- 1
-
9970
27795
44
20
-
9992
27805
- Line tangent (direction)
- f4198ebb-ed97-4f14-93e1-dcf5e71fc811
- true
- Direction
- Direction
- false
- 3641d63f-f6a1-410a-bb98-c00fec3be173
- 1
-
9970
27815
44
20
-
9992
27825
- 1
- 1
- {0}
-
0
0
1
- Line length
- 932422c3-938f-4896-bfba-93e9dc63dd8e
- true
- Length
- Length
- false
- 9f3a6cd3-00a5-4f12-84f7-3a56eb5630da
- 1
-
9970
27835
44
20
-
9992
27845
- 1
- 1
- {0}
- 1
- Line segment
- 308c9394-dd98-4fc8-971a-a1b8bf4ce995
- true
- Line
- Line
- false
- 0
-
10038
27795
22
60
-
10049
27825
- b6d7ba20-cf74-4191-a756-2216a36e30a7
- Rotate
- Rotate a vector around an axis.
- true
- ea049eb4-e34b-4db1-971c-23f959a7c78a
- true
- Rotate
- Rotate
-
9733
27889
185
64
-
9871
27921
- Vector to rotate
- b8b25cd0-c4e0-4e97-a694-3999684b1fa1
- true
- Vector
- Vector
- false
- aed17c8c-373a-4521-b837-4c123720e32f
- 1
-
9735
27891
124
20
-
9805
27901
- Rotation axis
- 5738ea86-6bef-4d8a-821c-df3f2582e45e
- true
- Axis
- Axis
- false
- 0
-
9735
27911
124
20
-
9805
27921
- 1
- 1
- {0}
-
0
0
1
- Rotation angle (in degrees)
- 22b5c062-1d46-4959-bf7f-ce186f811a1c
- true
- Angle
- Angle
- false
- 0
- true
-
9735
27931
124
20
-
9805
27941
- 1
- 1
- {0}
- 90
- Rotated vector
- 3641d63f-f6a1-410a-bb98-c00fec3be173
- true
- Vector
- Vector
- false
- 0
-
9883
27891
33
60
-
9899.5
27921
- c75b62fa-0a33-4da7-a5bd-03fd0068fd93
- Length
- Measure the length of a curve.
- true
- 22c2fd8f-4f4b-486f-a523-4871ff61a4d0
- true
- Length
- Length
-
9565
27704
92
28
-
9609
27718
- Curve to measure
- baa1397b-52fd-4f3f-be30-f33ffcadbf13
- true
- Curve
- Curve
- false
- df9ef313-9e68-44f2-b57a-df8a5f0a17a3
- 1
-
9567
27706
30
24
-
9582
27718
- Curve length
- 0d72d33c-7529-4646-b0d3-e06c84ee7c1f
- true
- Length
- Length
- false
- 0
-
9621
27706
34
24
-
9638
27718
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*SQRT(3)/6
- true
- 3d1f2fa7-968c-4d68-8a1f-878b5c7ca144
- true
- Expression
- Expression
-
9739
27686
158
28
-
9808
27700
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- fd1f6b44-7166-48cf-a064-4545c7281f0f
- true
- Variable O
- O
- true
- 0d72d33c-7529-4646-b0d3-e06c84ee7c1f
- 1
-
9741
27688
11
24
-
9746.5
27700
- Result of expression
- 9f3a6cd3-00a5-4f12-84f7-3a56eb5630da
- true
- Result
- Result
- false
- 0
-
9864
27688
31
24
-
9879.5
27700
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 57393fcf-4116-4c07-92dd-e41339c0f525
- true
- Evaluate Length
- Evaluate Length
-
10128
27772
149
64
-
10213
27804
- Curve to evaluate
- ce65bcce-f09a-44b3-94cd-cc73bb237aaf
- true
- Curve
- Curve
- false
- 308c9394-dd98-4fc8-971a-a1b8bf4ce995
- 1
-
10130
27774
71
20
-
10165.5
27784
- Length factor for curve evaluation
- baafa833-4ef8-425f-b607-a7876121b49c
- true
- Length
- Length
- false
- 0
-
10130
27794
71
20
-
10165.5
27804
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- de9b5e2c-f3fc-426a-a76a-87c3039c08ba
- true
- Normalized
- Normalized
- false
- 0
-
10130
27814
71
20
-
10165.5
27824
- 1
- 1
- {0}
- true
- Point at the specified length
- 53ada397-2c9c-431e-8a96-ba407a255873
- true
- Point
- Point
- false
- 0
-
10225
27774
50
20
-
10250
27784
- Tangent vector at the specified length
- dd888f3a-4b87-4d6a-85e5-fb0aa6030ccb
- true
- Tangent
- Tangent
- false
- 0
-
10225
27794
50
20
-
10250
27804
- Curve parameter at the specified length
- cfa9c748-f17c-4de8-8706-d009df92c6cf
- true
- Parameter
- Parameter
- false
- 0
-
10225
27814
50
20
-
10250
27824
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 643548c7-e04c-46c8-a912-73b81340f60c
- true
- Polar Array
- Polar Array
-
10307
27711
191
84
-
10434
27753
- Base geometry
- 51b4c9be-a0a6-48b0-8a51-2b635cbf72ca
- true
- Geometry
- Geometry
- true
- df9ef313-9e68-44f2-b57a-df8a5f0a17a3
- 1
-
10309
27713
113
20
-
10365.5
27723
- Polar array plane
- 14495758-452f-4515-833d-6b411c69c0fe
- true
- Plane
- Plane
- false
- 53ada397-2c9c-431e-8a96-ba407a255873
- 1
-
10309
27733
113
20
-
10365.5
27743
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- eea66035-3fac-4d03-950f-8296730c879e
- true
- Count
- Count
- false
- 0
-
10309
27753
113
20
-
10365.5
27763
- 1
- 1
- {0}
- 3
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 2123eff2-fbe6-4059-9ae7-dcce8ac7add1
- true
- Angle
- Angle
- false
- 0
- false
-
10309
27773
113
20
-
10365.5
27783
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- f9dcf267-1e15-4850-9ec4-8e7ad6d9f2ad
- true
- Geometry
- Geometry
- false
- 0
-
10446
27713
50
40
-
10471
27733
- 1
- Transformation data
- dd83b124-9569-4709-9a61-1a92bc7b736c
- true
- Transform
- Transform
- false
- 0
-
10446
27753
50
40
-
10471
27773
- 8073a420-6bec-49e3-9b18-367f6fd76ac3
- Join Curves
- Join as many curves as possible
- true
- 5f125462-d0f8-4183-b286-475d3acf0b80
- true
- Join Curves
- Join Curves
-
10672
27725
116
44
-
10739
27747
- 1
- Curves to join
- 12e37bce-c053-4efd-a977-c0f522b26642
- true
- Curves
- Curves
- false
- f9dcf267-1e15-4850-9ec4-8e7ad6d9f2ad
- 1
-
10674
27727
53
20
-
10700.5
27737
- Preserve direction of input curves
- d117240c-4ab9-460f-bbfb-66dc61b43975
- true
- Preserve
- Preserve
- false
- 0
-
10674
27747
53
20
-
10700.5
27757
- 1
- 1
- {0}
- false
- 1
- Joined curves and individual curves that could not be joined.
- 313dc56d-5db5-4cb0-88da-248d848cf9d0
- true
- Curves
- Curves
- false
- 0
-
10751
27727
35
40
-
10768.5
27747
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 3cc94df5-d9f1-4979-a5ab-be1fac63184f
- true
- Polar Array
- Polar Array
-
10314
27833
191
84
-
10441
27875
- Base geometry
- e6740668-b9bc-4cec-88e7-68ca31ae6aee
- true
- Geometry
- Geometry
- true
- fbe57887-2062-42c7-8b43-1b8cbf0f868c
- 1
-
10316
27835
113
20
-
10372.5
27845
- Polar array plane
- 50d41db2-0be5-414a-a105-cf75d7ca3326
- true
- Plane
- Plane
- false
- 53ada397-2c9c-431e-8a96-ba407a255873
- 1
-
10316
27855
113
20
-
10372.5
27865
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- a4c562c2-1370-489a-8662-0f28f19bec21
- true
- Count
- Count
- false
- 0
-
10316
27875
113
20
-
10372.5
27885
- 1
- 1
- {0}
- 3
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- b42ad307-1e85-4873-992e-8cb29886ba06
- true
- Angle
- Angle
- false
- 0
- false
-
10316
27895
113
20
-
10372.5
27905
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- bc6ee7cc-dfce-484f-b2eb-2a5a4d0007c8
- true
- Geometry
- Geometry
- false
- 0
-
10453
27835
50
40
-
10478
27855
- 1
- Transformation data
- 914dfde9-23d3-4c32-8acf-801b3a0a96f7
- true
- Transform
- Transform
- false
- 0
-
10453
27875
50
40
-
10478
27895
- d5967b9f-e8ee-436b-a8ad-29fdcecf32d5
- Curve
- Contains a collection of generic curves
- true
- 74f760b9-aa8a-4167-9ec4-7a13306ccf56
- true
- Curve
- Curve
- false
- 0
-
6354
-3802
50
24
-
6379.229
-3790.325
- 1
- 4
- {0;0;1;0;0}
- -1
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
- 00000000-0000-0000-0000-000000000000
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
- 00000000-0000-0000-0000-000000000000
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
- 00000000-0000-0000-0000-000000000000
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
- 00000000-0000-0000-0000-000000000000
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ZNx5ONVbGzdwU0qUIUMyS8g8z6x7741UKho0aDAlITKkooSkQkVJcxEpkog0KJVCGTLP7I1GU6MQqve31+O1zvW+/XE6z6d9tr3Xb617fb/nOtfDwcnBwfGP+sX+nf1LgIv6y/rVXjv9/Bn+u3b5+2nIO20PDNrp72dprKWrr6Wnq29gQv2Njo6uhjxjj2/wnsDtln7b9wQHuvpqyDvscfPd6b58+/61/j7b/SwNDfX0THS3mxq7GxsaGurrzGD/FEn85lpLtvvv2h4cuF9r5Z5AtyDGnsCQ7TzUn84M+d9Pm+0a6O61M2S7vscuPv/d2/382K/i8XANdmW/aNasWVzsDyqkwsGhR/1+ZpJfgI+b+htB9l/4Ijk4uMYPcXH8ifjfl5r4x8UhOvUFJYXvbnXkbxR+9pdD6DCn4rdlC/ZLTFJ/Xjr1WiHuqReyPw03D8f/8+sb+n9lyp/9vzLj//tnya+DzmHxTmcz0P9+L0RXozf3cXx7PvW/y9BmvYva2WZVU16L5n4beHy7pAGF4z9vRl/KZm/l9GpDW/DrOlHVlcWc6+ewpl7fjZzMlFY7beyd+ufeobIb+Qs5NT5M/fMfkZEw49ftv5/QEH6fPnTjQH2ZU13/1M8dRKKfXc9zpg9Nve9XVJI5ZuBk/m3q/b+h0G3Pr9xO/z71c34gPbFjvJxzf079vJ+ov2KVv9Pe4amf+wtdj5Bovd39a+rnj6BNRizgXDY69TlGkchgRqZT/tjU9/qNKlL9RLKlx1EG/lzjKGq9URhnzATaij/fJDKb8/ed09dJJI4/5x/0o6TUPnvDX/QWf95/KGvfifucJf/QS/y5OUD3nNqp22c54Br+/BwwJ/Akw2kZJ4Th78EJffY/Rjn+ccJ6/H24oFTFKft2Phfo4+/FDalcj12cvLhBEH8/bjjYJSPGKcMDA/h78sDGh5FvbtfxQDn+vjPA8MyHg04xMyANf+8ZIOy3VI/TnBcO4e/PC0N2dz7e/soLzngdZsKbhcKXnNJngjFej5lw42/wKs6Ns2AeXpdZENnWyp09hw++4vXhgy0FFg+dSvigEq/TbDA9leLLuXc23MTrNRvEvHkUstX54TBeN374bu3V5NTND9vw+glAtVzVcc6zAmCO11EAMse1rbKXzgEJvJ5z4EjTmR9Of+fAT7yuc8E1dzSDM38u1OD1FQTLOGfn7B2CcBuvsyAI5LOOqs8Vgv+ttxCEpgj3RngJTa27EHw+wbBoLhGaWn8hcArbk6wuIzz1HIThldfNbxF7haeehzDoObUta64TnnouwpDC4L+hriEy9XxEYK6u5b+IGJGp5yQCB2T9NzZ3i0w9r3nQz5+ar24+b+q5zYMNv+vnRJ6dN/X85kHZRx6v5q/zpp6jKBg0GpWoLxOdep6icP2Fl3RkuujUcxUFobsXQ5r/ik49XzEIv1xVq75RbOo5i8Hg8b9qkfliU89bDDbt1TnSPEd86rmLw2sPN5a6l/jU8xcHo9VJppEl4lP7QBzSUdmZZmmJqf0gASKaY0PqeyWm9oUERCxQs4usk5jaHxLwZebm683q86f2yXzY/OvEpHrM/Kn9Mh8qep85RXbPn9o3kmBS+z232Uxyav9IQsbThfwaZyWn9pEkiN5etz3yq+TUfloAUeePPmteumBqXy2Ab0ceSWqkL5jaXwtga9BAUOTfBVP7TAqqXGTeNm+QmtpvUmC2cpWqRr7U1L6TglvmkVGRc6Sn9p80iC/O72zeIT21D6UhWvyDkUaJ9NR+lIYf3BKJkdIyU/tSBly+2w00h8hM7U8ZeMsMtdGok5napzJgUZV9LVJddmq/ykLWI+bv5iOyU/tWFubfFFqr0S07tX/lICaJnhNpJje1j+VgODJ4VkuS3NR+lgM3/ww3ja9yU/taHry0fJnPleSn9rc8yC06EjfgKA9heJ/LQ7PUVRPxQ/JT+10e4kUefIBsefiE97080PlqT/u0ycP/5qc8/P73GSXzKsA6fA4UIHeEc+i5vgII4POgAF5DCy4OuCjAS3wuFED2vf4S8ZMK8L+5qwDN7fbDUKQwdU4U4GTd9lSfzwpT50UBbF6Hr0wWU4RUfG4U4U/xuYnndEXYiM+PIhTcz7014K8IQvgcKYJv9pt14lcUoRyfJ0VQTOvlolUowkF8rhSh9cLEXZ9RRTDA52shnEoQ3ZKstHDqnC0E26Oas184Lpw6bwth8qDtg4HwhVPnbiEUBG/zEM9eOHX+FoK3zz5hWttCKMXncCHIuyUW+/AqQRg+j0rQvCHLJ1lfCXTxuVSC+FUv579wUYJP+HwqAd22s3TghBJcxedUCX5b/AoUL1KCdfi8KkGu/lx52mclEMDnVgl2qKlU+4gtgpf4/C4CWWopk+mLIBSf40XQJLFR5YX/ItDF53kRxM8NbBy4vAg+43O9CBgz4iLFKxbBNXy+F8H4RJoWbXQROOFzrgx5P550+Cgpwxx83pXBq6/pWLKjMrzC514Z5Lu/GL4IV4YwfP6VoaV55ruB28qgh+eAMpyslk8Qb1OGfjwPlMHmlakljVcFUvFcUIE/j1f3++irwAY8H1QgP8/nXLKLCszFc0IFvG9FW784oQJleF6ogOK1K98HHqtAOJ4bKtB2tvCq+GcVMMDzQwUS4muW08RUYRDPEVWwO/x5zIeuCml4nqjCv/2cGcn+qrAJzxVVuL97wZoXl1VBCM8XVfDdoc8x+EYVyvGcUQXFrfZ3xEdV4SCeN4uhbe32TTSlxWCI585iSFwePtPXcTEM4vmzGJbQzxUkhy+GNDyHFsM/k1zXF7cXwyY8jxbDfe03cwdbF4MQnkuLwUe5t0icVw3K8XxSg4UyE140fTUIx3NKDdrniYr7uqiBIZ5XapAwW/Nl8gk1GMBzSw2WcNrufvFYDa7j+aUGf0a3ygx+UoMNeI6pQcGXvRXiYuoghOeZOvh+SNhLo6vDazzX1EGpM1PJ118dIvB8U4fO+pK65MvqYILnnDqcedMR/uKNOnzB804dlj4fVh8cUYd0PPc0gOPBnDZxJQ34X77SgId3lGNojhogiuegBvinI33fcA2oxPNQA1QubehOvq0BUXguagAzMeDEi1YNMMXzUQPOHos1G5yhCd/wnNQE+0Npn8T1NeEWnpeawB3yJInmognb8NzUhCLfJprvCc2p+akJge5fviQ/1oRqPEc1QXXTzMsvPmnCYTxPNYHlIL90UFQLzPBc1YKzS0xHxOla8B3PVy2wt1qdRvPXglt4zmoBj6GPg+9lLXDB81YLitSj/yS/0QJxPHe1IFDxStaLES2oxvNXG1QlC9cPLtSGw3gOawNLsIZHwlEbzPE81oZk3s95tHBt+IHnsjas/MOxzfe2NmTi+awNM4YlBc61aoMLntPasHXPhc5uLp2pea0Dj78t0g+R1Jma2zog7nvvOL+ODrzC81sHAj9ZdafY6oA8nuM68Nat0shoiw4cwPNcB9SY609UBulAK57rOhCz8f07l1gdMMDzXQd6G3ebjaToQAKe8zpg5fAnIe6BDgziea8DFyuPf5J/qwN2eO7rwIituFXhex1Ix/NfB1aXXE9aPqEDHBx91D2gCzmW2gPdwrqwGd8HujD7UREtRFUXHuJ7QRc8DezO8yNdEMX3gy6U3G38krJOF3bje0IXZNVdbYx8daEK3xe6EJoxdKkyShdU8b2hC80KoT9cLuhCNL4/dEHvCu/Skbu60I3vEV04Of/MtbgyXbDA94ku9J+RG5Hv0oXz+F7RBVvBbPvCn7owjO8XXbgea5K2fLYeOOB7Rg/+zij93S2vB9n4vtGDTZGODiHGejDrGfve0YPCya4M/pV64IHvHz0Q2ef9J8VDD57je0gP/H6OrDEK0wNpfB/pQYXf4azKRD3Yh+8lPVDuF+R0vaUHjfh+0oOo7ZfXjxTrgQ6+p/SA2a2aE9ekB/H4vtIDs833eRQG9eAzvrf0ILmF5lzIpQ/W+P7Shx+r3+Ytl9SHFHyP6cPKt5tm9WjrwyS+z/Qha+mnrSG2+rAB32v6wFsadJ9/iz4U4PtNH9yAQyA1SB+Ewtn3nD4UF8W7GcXqgy++7/RhgbHko8oUfXiN7z19CLl3Q9D1gT4o4ftPH+o19TxHqvUhAt+D+qCVWfwk7r0+dOL7UB9ilZbPU5jQBxN8LxrAx2stOwuFDSAJ348GQJfyeL5c1QC+4XvSAK4mfxPvsTIAe3xfGsC48MFdIesM4Ba+Nw3A6QTfK35fA+CpZN+fBnBvVvKC1CgDcMH3qAHMjVYMMLpgAE/wfWoA3v9yyivvGsB8S/a9agBloeayrmUGEIzvVwNQHCkPHuk0gFp8zxpAeMDayrifBqCB71sDaB/sVlCYbQjH8L1rCEZeu/YVyhvCe3z/GsLpd7/fLjc2BMD3sCF82RqzqGeFIVzG97EhLGsXORDiYQhj+F42hIx11+r5wwxhLb6fDYGrTn1xaqIh5OJ72hC22j88ZHTLEARi2fe1ITwut26uLDYEL3xvG4I4o07DtckQXuH72xACi7ccHhkwBPlJ9j1uCG9N+9viuIzgAL7PjUDtfoiOgqQRtOJ73QhidLiPFmobgQG+342g9/apruW2RpCA73kjsFKRNujZbASD+L43govXb8WGBBmBHb73jWBExrCHP9YI0vH9bwSrL7wwTk0xAo4Wdg4wghzRlSeNHhjBZpwHjGB2Qvv7ymojeIhzgRF48u8wd31vBKJL2fnACEpifiaOjBvBbpwTjEGWK+JznLAxVOG8YAyhBwWQgqoxqBaxc4MxNI+dP1toZQzROD8Yg17wosHl64yhG+cIYzj5NY/e42MMFjhPGEO/t9WFkChjOI9zhTHYfqz4yn/BGIZxvjCG667rbVPvGoMDzhnG8Lfz3WWjMmPIxnnDGDZt2P2zstMYZiWzc4cxFDZMLnX9aQweOH8Yg8iq4ykjfCbwHOcQE/CrEBuNkzcB6VnsPGICFTbXVygYm8A+nEtMQPmFVnrhChNoxPnEBKIsisaXe5iATig7p5gA88ESx55QE4jHecUEzPQbb4YkmsBnnFtMIDnH5S//LROwxvnFBH4sHlqbWmwCKTjHmMDKG/tvGzWZwCTOMyaQJc/LVTVgAhtwrjEB3sunN7hymUIBzjem4CYhd3dkvikIrWPnHFMoPn17Rry2KfjivGMKC+aabFawNYXXOPeYQsjxV/cKN5uCUjk7/5hCPY8jn32QKUTgHGQKWhFd23qOm0InzkOmEDuxszAkxRRMTNm5yBQ+howICDwwhSScj0yB/iPKPbXaFL7hnGQKV3cJPjZ6bwr2OC+ZwvjnS0JV46ZwC+cmM3DyUN3hKmwGPNfZ+ckM7rEKno6omIELzlFmMNeZJhpvZQZPcJ4yA+/mam+FdWYwX5Sdq8ygzHHTi0IfMwjG+coMFKs/SthHmUEtzllmEG4X5Ndz3gw0Yth5ywzaX/57FXLXDI7h3GUGRiheSqDMDN7j/GUGpx/PD0ztNAMYY+cwM/hieOO10U8zuIzzmBksy9OVq+IzhzGcy8whQ6N4j6u8OazF+cwcuG4tqxoxModcnNPMYevCFsX4FeYg4MrOa+bw+Kr7fgUPc/DCuc0cxBd8qykMNYdXOL+ZQ+DZA8r2ieYg38DOcebwVojvYM9NcziA85w5qMWfbQgpNodWnOvMIWamoppAkzkY2LDznTn0RuVEpA6YQwLOeeZg9desxYjLAgZx3rOAi/vLNavmW4Adzn0WMDK8JtpV2wLScf6zgNW7u9tHbCyAI4edAy0gZ8BXN36zBWzGedACZu/4fVQhyAIe4lxoAZ69R5iFxy1AVJ6dDy2gZIuIoX2KBezGOdECZNuuxvUUWkAVzosWELpWvTek2gJUT7NzowU01zwwEXhvAdE4P1qA3nLrU6njFtCNc6QlnCyr/WAkbAkWPOw8aQn9tC0WVSqWcB7nSkuwfdp32tXKEoZxvrSE6yYhfSNrLcEB50xL+JvPBfE+lpCN86YlbNI+lawQZQmzdrFzpyUUZkkNFZ63BA+cPy1BRPkWw/6uJTzHOdQS/FINLvaUWoI0i51HLaFC+sW3kE5L2IdzqSUon1+xROCnJTTifGoJUfPar6TyWYGOIzunWgHzpOewkbwVxOO8agVms38uqzKygs84t1pB8pFDqa4rrMD6JTu/WsEPDoGxEXcrSME51gpWHji/Mj7UCiZxnrWCrFGlGwqJVrAB51or4A3Kmyi8aQUFON9agdsXy9X2xVYgpMHOuVZQvLPiVk+jFfjivGsFCz44/QsZsILXOPdaQYjLu3UCXAiUrrLzL4L6Dv/s1PkIInAORqC1fpLLWBtBJ87DCGLrj22sskFgIsTOxQg+rhDLdd2MIAnnYwT0N6m8o4EIvuGcjOCqtdaW+OMI7KPYeRnB+LPH+QopCG7h3IzAyXzJ7AeFCHj2s/MzgnuFDS721QhccI5GMFfP5UHPOwRPcJ5G4H1ncM7ecQTxOFcDuCdZ6MXMAjDD+RpAuD6qq3YewGecswGeCb45JiUHkIzzNsCuFYIGnmoA1jh3A0jFrWPlUtf9D5y/Ad68vhQ7AQApOIcD7OXtNbS1B1iJ8zjAImvVnoT1AJM4lwM0RPrFd7gBZOF8DhD5rMBY2Q9gA87pANp/xnt37wfglWbndYAuM9rJomiAApzbAeL2HTXlTQBww/kdwLSw+r3DJQChJnaOB/j0c17CpQyAYpznAc7qbjL/mAfgi3M9AMM/5aPOU4AFJ9n5HuB79sfEsNcAr3HOB7jWr2FZ1gAQgvM+wArVoM9CLAClJezcDzCx/dEZ536Aepz/ATLT/lll/AKIwD0AYH2PTf83Dhpo4T5Agxly8WfNBWjQiXsBDfI310OMBA1icT+ggevF+YO1ijQwwT2BBoKtW89JadHgI+4LNHgqdoPuaUqDJNwbaOCzZmAo15oGdNwfaCCZqHthYhUNvuEeQYPyt3utbZ1pcBX3CRrsESj+muBJA3vcK2iwcBnPpY4AGozjfkGDuqPLbJUP0uAW7hk0OFSa8H33MRo44b5BA03ulstFZ2jAo8juHTToABk73ms0uIf7Bw2Oh7v/dMiigQvuITQwfpJ59dJ9GsztYPcRGnz4/XXpx+c0eIJ7CQ3OGBv90qmigTfuJzSg7TmQEtZCg/lJ7J5Cg6/3SpaX9dKgDPcVGlz5NmtU6AsNgnFvocFyrVXXnX/TQHEFu7/Q4LfP2RUZPHSoxT2GDjczO8a+CdIhHPcZOqz7pJBuLkUHDV52r6ED9yKvVTHKdGjH/YYOeW4547W6dDiGew4dtqUM35CypIMR7jt0mMM0c/S0o8N73HvoUCQVOZm7hg6ncf+hw86N5TcnttIBcA+ig8S5OWtsvenwBfchOpQ2rvmbsIcOl3EvokOQyMXMjgg6LMP9iA4KDt1rlePpMIZ7Eh1qTihzBJyjQwbuS3Q4WOl7u+g6Hdbi3kQHdb58J94cOnCpsvsTHdpsf3M6PqJDLu5RdDgaje5cekWHrbhP0cGw5MiGjzV0EOhh9yo6vPtXya3bQYfHuF/RIdFS5G7YRzp44Z5FBxS2YVPZdzqIX2T3LToMPbw6Q/gPHV7h3sWASyPvc51nMSAQ9y8GLDVQ35wxjwHya9g9jAGjAQEzv8sy4C3uYwy4cffBPXM1BhzAvYwBa4b+bIkxZICaALufMYBT3ZqvDhjQinsaA+56xRZI2TMgBvc1BmzJqN3muZ4BBri3MYD/vTh/nhsDenF/Y8AjhS2FE7sYkIB7HAN2bEtztd3PACvc5xggdqVPIDGaAYO41zHgZbv2w45TDLiI+x0DAuaHuCtfYoAd7nkMkHN6MjcggwEjuO8xoPoM1+OiPAak497HgLA6u+28TxmwGvc/BiwWPCXk+JoBHFrsHsiAFvumoksNDMjBfZABR2KldnxkMmAz7oUM0H/tKqLbz4DZn9j9kAE9M249DfvFgIe4JzLgFOOLVxmHNXjivmgNlpEGosIC1iCawu6N1jBQHPrMWcIaSnB/tIYLk8+9MxStYTfukdawxGym+HdNa5DdyO6T1vBr74oX5qbWUIV7pTWk3T/jG2NtDaG4X1qD4882ibpV1qAqwu6Z1vBPR/6llLM1NOO+aQ13/Dz9PD2tIRr3Tmtwzs6WzAuwBj3cP62Br//Hq4kD1tCNe6g1PFAx3W17zBpO4j5qDdu3H5JKPGMNFriXWsO8tNKyjqvW0I/7qTW86OYPVM6yhvO4p1qDv+xqmYD71mCL+6o1yGw+/7rouTUM495qDZUXmEG8VdZwHfdXa9jfoiTn2GINDrjHWoOKmE/FpV5r+Iv7rDU0rc7b83HIGrJxr7WGwwmj8rq/rWET7rfWoPvWsiqMxwZmDbF7rg2w+KP3lgnaQCHuuzZwYmmForCUDXjg3msD5keF3jor24BIBrv/2kDfK6f9Gbo28Bz3YBs4x3VF6buFDfjhPmwDNvCuxtzOBqS3sXuxDfw8uDgsZo0NVOB+bAOpRf7KdVttYB/uyTaw6vf9OilvG1Cez+7LNvDHaPKA5x4baMS92QZuB9NV8yJsIAr3ZxvYeO9Yw0ScDejgHm0DM7+9Dbc9ZwNM3Kdt4L6mmFridRuIx73aBtx9nJs67tiAGe7XNiCcmRqh/MgGPuOebQPPPn5SD3hlA8m4b9vALiWtlqIaG7DGvdsGpNyCo3g7bOAH7t828ObaY03HjzaQgnu4Dezt4mi79N0GVuI+bgOLpJZEf5y0gUncy22hYcMJbd1ZtpCF+7ktRCY3tIfNs4UNuKfbgnajZEyZrC3w/mT3dVvoEnbRFVazhQLc220hblVGp7OhLbjh/m4LpicGj2aALQhls3u8LXyq0NP/vtwWinGft4Wzs/Yzzdfbgi/u9bbAsH12PMbNFhZsZ/d7W/h+eIZh3S5beI17vi1ce7G8W2q/LYTgvm8LK/4lxnlG24KSLLv328KERatR3ilbqMf9////nf3fGZzuXP3v3z/W//ffF/Bw+/5lu88O1xjzAL3pP6++XDvOdvlziUvbMpdPu6r336/YDU9S7jzterIvWWzfoKEy6vbMY9o/P5StwK+PPUy93mfa7c2E77J9OHGoWmVZwLRvvn7xJH6fEHHqfYKnXfz7Yy+2W/Sby1812DftnsqBlvj9PbdQ7x827WL05wJsj3YLDRSVOzTtsYwbzX/ZP1f9DfVzI6fdd7HCJbZnbFvtVspzeNr7v+lvYvv5Y60jbs+ipz07qWse2yvcnOM4QmOmXZ9f9vUfyp9ktctdNTg27cetf4Ww3U/aqcD86/Fpl1Fxl2e7fHC1XVtm3LQnx+14NUm5iB90hXicmPYIYy53tvOU5QSIyp2a9vhmvckJyqWkBbjbfBOm3e3H2Cm2G4AV9X0Tp/3+5zWybK/O3nUuROX0tO9j0W+OU16GLrqW8pwh6//glRrbUfNLddFe4uHjLbd+U75vRf8vt2dJ086sClVgu3DUnOd5l89O+0BjVtIY5d4OmrEcocnTXrhoOxfbGUlL165af27aW5UyvEcpv6zqJnvV4Py0c/vtrB6h/OynkM+DwhemvTs/U43tJ7OO3jP/StzmqkvUL8qPLk06EFt1cdrTb8Q0DrPX/9Jl27bMS9PeOSCiwPaNwSlCqkcvT7u1yMSOn5Tr37rWHuJxZdpnz9HP/EF5/MyL6aW0q9Pe/jP7/XfKS11O+YnKXZv2ppoNC9jODD9k4j5JvNpTadk3yidEDTnbfFOmvZl7Iugr5bPOqHhGdBBfaFl67gvlayUlKlWWpU677QOv+0OUux7h1ql5SLz6Q3nVIPu55w0mhahcn3avNy+6Bigf31P/WyaZ+Pnbup/7KR+5UbC1lCdt2kVbvwz0Ud4gfOalbxDxmWurPn+mfNuRXaqivcQtzpxnfmKvTznjRJFD+rSHqctUf6T89QWxH27PiBvFyBZ8YK/bg16n2Vo3pj01wfnMe8odm7OK8i4Tj/A+4f2Ocqu0XfIb+TOm/em8Haa9lM9+pXaEI5Q4l+TZf92Ur2/q6bv5mfhu9PQJi32+vE+vXLX+Jjnv2uG7mez5Odsif6SUuJe8/4IuylfoMiWuGtwi3ytC7nEH5W9W7jtgk0b8UYr4qnbKm0v4egaFM6f93JaG1lbKf3Ql2iRFEC94XenUQrkcSzDL/CvxVfW+r5soV/8RNffdlqxpL/4hqdnIXk/N/sDYKuItDRrR9ex5mGjdomt+e9pdxoerailP5U40b8skHun/gLeG8l0r316LmJ897VreOTrVlD+WmeBWPUr83NisZZWU806KedX8In4+s9/xDeULV8lUhXjcmXZlI58l5ZSz1grqyDYQL1ZLXlxKuYZc/5lSWg75/AneoyWUqybcHvXNJb75fPvd5+w5sM7RWVTu7rRr0yodi9nz831rcdEJ4i08op1F7HMXgBTdJ4kviwhf8YjyK2PP6UcMc6d9vmxZeiH78xxZOdzqS7z3+bnufMpXx5bd0EgnHuCX+C+X8s8zVdZHdBD3n6Bx5FD+t3rXrEaRvGkfe6Dak8Xe5/vOP1JZRtxc5n7KTfac8U33DoskbnXA1jKdPVdrTkrVPCTOk6N+P4U9H2LWVil+I65Zep33CuXiWj8OhKjcm/ZNL1q1L7DvKXEPzYqtxJ2t+7TOUp5lntElk0zcZymTM5FyBauCEwHVxM8y72bEU16+5bhlKU/+tHt3M6SOUb4oQH5ovgVx+Ye7thym/EBX0GXfIOKm0l+8w9nrefLg8udZxIsaAmn7KdcZNBqf10t8/oFkZhDlxg3nb+2QLCCvd+xGfpQ/PXbJqciBuPXESzcvyi/lGvEIHiN+Yn2qtRvl7TTXPLdn/3n9yle9zpRHhApvLRwhvj7Nw2wd5RINFrNna92fds7qG3YrKTf83nJ/y3biF6qSZy+h/MyFZpe8y8TnzNY7iCjXS1Xnn9FIXFxvyxVjyse6Xhds4C+cdjmJvh3alO8Vv7Ylm068ISmxTZnyrm9XZnCEEt8c8ueLDOX2PfnZa/KI624rThelfIHE29U3PxP3L3QYnc2eAztbR8flHkz76SSpdxyUX2M8vbRyPfGz+bs9Rv6yUPjJ7VbXTxJXdo3fO0D54KWHrF+lxAcDz87vptxc8PKhpX+IZ1lcYTRSvqz0p8wVg4fTLnjs2nA55W+KUh9/8yEucjJKpYjyU6NH1lmnEU/5Lt56h/KMneFfzrUTjymS4Eqh/E6D55EB4Udkn69XS01kf86s+QvQUuIokZkbRfntce/s0xHEHZJyNIIoX2CjZ/HxAfG7fX8F3Sl3dYc3pl+J9+yVdVpNeYKHx5oTyo+n/VCU7ThQvsrHu717C3H5rIujWuz1jJXaanCW+JpB1aXS7O+VYsk8WkX8cVpf3yzKxfTObOrgLiL75NizxuE/LCRD76jXMid+OWcvTzfl8Wp1tlGBxJ8dfxNUQfmBQI3Cpkzid/qcZAoot0hLkV/cQ9xh8vbEZcoPS3cdOTD/ybQfWYH4jlD+7mP8h5pVxJeWB4Av5aJHnNDCo8S/5J28tJryqpcdp0OKia8vqBQ1odzj2CPWm1/ENRrtMqQpb7pydJGM5lNyH4UILeOgfFdEq/tuD+JxWyXGeyep+0jV9OLLS8Rd8ixyX1H+qVbntXgDcd+fSz1vUN5TAkM7ZxeTXMf/U+wI5Zsk3s96SiOeSWt+6E755oOnFgjtJ15gc8CORnnIZK6Cey7xFZobimUoH7t/V6bwE/HW/eXzfk9Q8zZ9YA6f3DOS56VF6A2Ud216+t3ZibjtAW96NuU6z/a8zjlBvODA0Jxoyt3LtyRylhLnP3r9yibKZfUKl6+dJB6RFNavTbnjNeewBsnnZF6ZrRvipjxf9/XrA4bETz0audo8zkL7OQvmKDsS/yggMnaT8sun7iyt8SW+4S/j+17KHxyxOrDvGHFjc9HDtpRbnhxIV0gn7uH768Y8ysfUDV5WPCPe7GCzmvWbhR4mnG4O6iD+rt0+IpNy56AwpvQocW0HUA2kXP3DlvZSkRfT7ueL6KaU+yinvfHTIl4Zs67s7xgLeYXm3JZYRlzt8f7sEspzxzsPPd9OXFjo1GA05U93HrHZGUncK8cj3IZy3hljE8JXiA/MLNzIQ/lmp/Drjx8S3ymoHvJilIVKeJxN3BuJP9q1ofIA5bnpb57wfyMe+viZgxHlNUf/ahXwl5B9/qDmz9AINZfilU9uViFufOr9mzTKT/Z7tvEwiHOJ2WWvp9xvRpfgna3EJfj0LvNR/sXwqs66UOLqW18nPPpFzf8LD8z+nCX+KFIucgflFixNzRt5xI9lmHnMo9x23h/eFdXEkbCA7tNhFtL1nV8+/Jn4R889TA/KNcS9fS/zvCTP8c8S99mUZ/+t/8WQJ75Bw6bwzk9qv11TcxswJx50XfbtSsq3V1jlnl5PfPRBSOrQDxaKCmxgmgYR9yntVo6lnGPf9cHuk8TH9vesVaL8WYBz69Es4i/1vio8+U7tn71pKVplxD+vDox2pNx3QNS6qYd4/6XSwPffWCjSGr0I+0M8PsboXTDlO1oyxBUlX01736UZVVyUm6W8or82IP70refCk1+pfcLPa+3nQPxDYyRLnPKG51XzRX2Jf4kIHLn8hTrXO/2ePTpK/KXU0q3ylCeFGRhtSyMeXjx7TuoQNW+5N4fxPCOOsvPGZCm38RE7kdlO3ChbU+LiIJWjbKJ3rhwhfsfdY6sI5Yriz+b+FC4leTVX99XRAWp/StWEntMkLsPlZTXez0LzJXJvmy8lHlVYW7KTcv8FDtdYHsSlAzWWNPdReWbFqTWHI4jnhum/QJSnPkJlypeJ3xNPVs74zELpYot+vXlA/F3XpC8f5bonh7t8G4izZPhid35ioaLEteGCX4nv114XVPaRyhuXOhvyZpeR3FUXLCtPudg/0c41ysRnRP+KCPlA9a/8kKRfNOLGzK0Jb95T+VDBZzx5C3HOfj26JOVxA8v5TfYTZ+3/Erf9HQtteO72qjWJeNIhPvecXioPLOxT3J9L3MV19MnPHhZKtpylJFlF/NEKlVOGlP++2frq4Sfix07w1AR1s1CmhRvXBu5yMv8bRwJyWCzU+O5S24gsce0Et10fmCxU5+az5KwZ8ZP6mYXzKZ+lfsNO34n4qqjFDLsuFnJbLNBeG0B8VyuaFdzJQoVnHcd2nSA+4m87camDyicloimzM4kbp58Vft5O9Yih3uqMV8SD9aKhu4167nOMw+ndxPn37Tg42UrNpZv773RNEJ+dc+apKOW/z3Ns2CfxetpNFTePqLZQvebL3FARfeLHds2TMW1mIfm7jYLZK4lP3uRXsWlioZX3/MRsvP/jF5L5VjSy0LDvx5iuI8RFB2Y8dmhgIXil67InlbjuytuaDvUs5MLUuyLwlDi63bpxeR3VF34+ME1rJb7ctlufXkvNB7kwXdNh4gLvRfMMaqj9pqMY8VbwzbRzD74pU3zLQiMHrBTc1YlLHlvjLVBN/dwce6FRW+IDL3gTv1ey0IXkArtYN+I1V0x16iuoPPD3dal0OPFcfYZlzhvqvt5bHpVzgfhoadidI69ZiK7RGoruEw9vtgjZUM5CwTlzMmtqif8w7YlXLqPulwqPWdsGiZ9YXPrx6ysqJzi9OjM0s4LszzW2+wteUueO449N2ELiN/pfmgaXUOdL/o3kLES8Iv+qjPYLFqo/WsWXtIm4qKjpgg/PqH3rmCQkF0LcQmZUKbmYhYJyklUzE4mzLljp05+ykFSRnr3eHeKuknvN+oqovr80d8/j18TjJ/h04h6z0KH76BrtPXG5A258qo9YqOPu75Lyf8Qdi4eKnj1gIUkRVru9VCW511oXWK4uZKF12a3dtUbEr7I2RbEKqLkh9uDtmtXEL/2Uj9yRz0JhYXpXm3YR/76sV6s/j4XaAvvtnI4Tl0LikTtyqfuifPvrpnTikxuMdrFyWKh1uYj42ufEQ7YUf3a8w0J/sqzV6zqIW27S6Cu+zUKmxiacK0aJN9zj8FDOou7xormJ5SJV0/5Ys3jlsVss5Glf2wBaxOs5+6++z6DuWQmfkodLif96x7/M/AY1Dw3z12lvJ/5aNMcmPo3KV6FuMekRxMv9thxtSWUhuyXzV8y/TDw3OJNHJoWF7m7aeD32AXG6i1L+5qsstO36qfCJeuJRuu7Hki+zULHA7HbvL8TPFP/ZX3GRhSo2TWa38lVPu8OrkwfHzlM56nv4V+tFxItH84/Jn6P2Q87JC3eBePL8uYn0s9S5KxRIm7+Z+CQPLX7rGRZSWlHMHbGX+IW3P/2DE6nzfsM+/8Np4pZ1tbrRp6jz8sg6c2kOcavKI+UnTrCQwwKJrttviBeMvlROjGOh55UStgIfiD9QA5uTx1loQDy8w5vj7bS3fb03/8hRqve5eySVSxEfyWpN3nOEhdSEXu9QNCYeVhRwf9thaj3tj9uHrSZudZ3uzYik9udPb9P6XcSF1ERvyx9iIc2dIotUjhP/czp/1+gBKi/tnckbmk582/MfN8tDqXmiWVBf8Yz4i523ViXuo9bthUekZAfxsytzN60NoeZwwJJZniPEH/kOFAsFU3N7p++WXOGaaW83hcCyABbqzCoNGdMgfoF10XuPP9Wvvyovs7IjfjJ06IrMLipXn7OpjnQnzr9Zh+uZNwvNS374qyScePZKtxMbvai8tGXsIedF4o+6jhkObWehvrdbBazuEze7lvttvzsLxeiofNhbS7whYqjgnwsLLZbzM7k7QNxewnlf+FYWuvPy/J8A7tppf/ZNWnfEmcoJq1SF+YWJM/q2NnlupNb5u03ddVnislHrnGudWKj6ON3EVIO4trnVI721VN+5sg3emhJP+rLtwwlH6vOsq3nnuoT4Ei3+5p6VLHTzSIH08FriF9MuRmrZs9DOXMUP0W7EHXYHMYOWUvNZQNZYdDdx88QZ7/JsqV4Td0ng+kHii+lVRz4zqP3wKWKbVhxxltvKpxI0FhK8lb740XniMl2yEciKhbbqvvWgZxB35u96tc2c+l6192dX5P/n9fKGUftMWKiqnEfM4QXxlye6c44bstB693UHG98SP+OXQTujR91HM/Qt13cSnzHkrHtWm4WMzRasbO0jzp/9PviUBgtJVO/LXD9KfLO2PnfUYhba23HHromnjswxxtIGX2XqPhrkW+QoQrzW06Rz1UJqHXhrjCvliMdoK4qpy1NzplInlKFJ3Pm+yZ6/0lROS1j74ZEZcaWx4p9vJFmIf79joJYdcbclfMdOiLOQdLLOgtR1xLdlHly8dB6VW7iGmoTdiYvRk2omBVnoHnfw1YjdxJmPWgJuCVD7fPEN36GD//n8aR9m2vOx0LKg1aYb4oj3vfM7/mkGNU/84c/z88TrRE2+hHJRfcFDOU8lg/j6IUkt3n9MND8kZ0V8PvHdNzhpxyeYKKB6T+WX58TLNn2X5RljIvcSgYWr3hJPCuZ4HjLMRGm8o/Z3Oog38W6W7vnGRKV1t2l8fcRPGizRYAwxUcXc5N9uI8Q5EqU+X+5jopFY0V2PuevJvD201O7LByYqWhSaJChMXO3MBhvjXiaS5prr5SZL/E3fp5a9TCZqeMjffU+d+ObjOWN325noc1zaMIcp8eCHYSmsZiYSuTR+xd6WeMk649e8DdT6SKo3nl1D3FSz12tRDRPJR1mf6nQh/npZcph5JRM11S8vl/cjHrXs6G+7ciZSeG4e7BZGfG4GV+eKl0zU8ZXnZOox4hv/+Usve8ZEjbonBZhnia/1ciywLGKilEcFnyTSiD+5ybii+oBanw32EqtyibeF/q2dnc9Eho/kzhx+Styoce3S9zlM1HL+2+r7FcTNJQw57mcx0TaefSvftxDPd8j8eiCDeu5nPA8KfSBO920RtrjORObpHi2mP4i/9OR0/XGFifTPi6x1+Uf8yMEjLdcuMNGYIN/AYYGGaY/bxPS3PstEMqptZ9IliV+1TFPqTmCiF/cFbEuUibsqHvsWGM9E6LDy70594kvebXk7eZSJWuOvpw8D8cMbRR4dPMxELpYjiG8l8Yn9ubd/hTMRKyuhZIEzcZq/S6pHKBPNaWhfuNiLeEHujrMVe5gop8XY2WAP8Tfiiw+rBDDRsNkMF4so4qWDSp5hvkwUJXVpMe0U8bp/Y6ZlO5gocrf9Xfpl4mW3XcZnujNRvM2Oz5BJPOuDQRpsZSLfEYMq80Liata+Ors3MtGQ97ij/kviSrxSV5PXMpH/6rHdKrXE90kEfc5fxUR3t/nIz+8ibi36iv/1Muq5R8evn9FP/O6yMJ4GGybq00ic83WE+N6ihTWNwERGB26bNnE3kvkm6elVbc5EN47ObnggRPx6+azqJ0ZMJHimvTZZhvjplq+/r+sy0eIVNmqBasSDZ8gMHtKg9id/YPNSY+LFBXdT1qhQ78MXUyVjTTx34L2orCITPbuWzv3F4T/vs1LCliXNRDOPfw18vIX4TclnuuckmKhH8qjwYW/i+6QDm2xEmOhBRGzzkr3Eje690xoQoM4d9/xHs6KJexW9Nz86k4lOWq3ILU0g7p7sPi7JxUTfXJfkh18hvlXC1yttsgu5Byx8pJ9FnD9CJXrhaBeqjfr78H0h8Rshncsvfu9Cp/78ykx8STxq8svTmYNd6FubymGzWuKyHt2tPh+70Kvue+asTuKXbVddKuvuQnYDhRWH+ojf2zfKPb+jC/EvXKciPUJ84m+esEtTF1pAz7Ur4Goi+ZBzz8urNV1oUcPgIjtB4n+K18xvfNOFHgToFrZIEecODxfkeNWFImbf/OamSvxpOP2WYnEXspHaX9VnQHx7P1+v+cMu9OVHE/jSiLe/cH6y/F4Xkvz+xbp/BfHqig6j1dldyKN0rMZ9E3FG2DLHVRldCHLU21o9ie97F83PSOlCqg9erl8aRLzzbPR2zYtdyGSEg3H/EPG5J7Ztm5vUhSZfq5yWjif+QtDu94cTXWijUKTFofPEt56O1y842oV2+Gwy7Uonbpx8bu7+SOr1AbwRRnnEN8V8jTUI60IjfZ0z454Sf5RolPkxuAuN85i/bn9DvDJKzfuUXxf6dOrww0XNxAOT0t9qeXWhYDW5Wp9e4sj6Qssr1y7ksv8A750vxMcV5sc4Onehm+uF1vSNEz96eXlH49ouJMrrdEd+ZvO0z6/a17pyZRcS2VgjsGYe8UrTf+HPlnSha+95dkbIEb+avqFWmdaFkpRjHt1SJ/7+5fy30WZd6H1O369KY+KSM4f2t+lT62xTLdbPIL58zeUmJc0upC3cLMTtQPz7U953nspdiPt+LlN8M3EPm0Xp1+So87JHeO8iL+JDMXxSNfO7UNzagjqtYOIhgV1Lfwl3oSDNLR/1IojPnezVE+HvQo41Ldm68cQ1KoNaF/F0oQDRMWn188R5PnNY6vzpRP2jF7Tk0om3eYq46450oolbqW1zcolfF16yYvHXTmR/eUJstIj4TKG1fyU+dyLRS5c72suJj5/g2f+nuxMtrY1UfNTwn9e7mj5va+tEBQ25vYks4meyPzdn13cilG8sun2AuM4RmechlZ1o3bjGXb1R4lpnRsONX3WiwAd3b49ztUz7tYIs8a9POpFgxCfOp3OJf7waHnvlfidqDOTJ2r+A+NyIt130HOp7maDLOsrEeVNmibIyOtEMrrbaHl3idZw5OoHXOhHtmBScsCT+hWe18eS5TuTKu7FXbynxId6L6gcTOtFrw8G79WuJb5xhKfzrWCfKX2KS6utCfAJxD7pHdqKTXbdyOHyJH+0offZmfycy4rhXe3Iv8fvRfgnKgZ2oT6z2n/hh4rXzRl1Dval1aDlqcOEk8Wc6O01K3TpRJs1zh9hF4mGjXRIznTvRnTiOxLgbxOddOcgDazrRXNHhzIlc4gvFDnHtXt6Jbqz+mLX9CfH6Byri5xidqKwsOv5NOXHnzxWM++ad6Nn76CUqDcTFn7w5VaHPXuf0xnAmcYXrp/82q1PrCTc1avuIn+VPTWpf2Ily9jrbSf0iHih60KlJqhO9kD0r78LRSvKhZpFd+bxOxK+vk3OVn7hv6YR/Ln8nspUT6m8WJ9440l+bwN2JVqfKVc9SJP5PF3Z7TXSg7zkODgaaxEsHnq42/tmBxDdd9t1oQlzJXvfgn/4OtLOAS2ofg3gcM2D4cW8Hsr0XuzZhJfHHDNen/u0dyHMOXeT6RuK2H/o7peo7EE3FcsUdD+Kct7k3PHvTgVYOJP/N8ye+8l6m/qYXHUg/b7dcbijx2JnvgwcfUi7349bNI8RvuJbIh+R2oGcCS5POJxCf073ZYvRmB9q9PbM96hLx4YqGKv9rHShNYMUezwziEk6rWljJHejQi6AtjLz/fE7Pfy5LTnagOm73eMknxN+tl/LPONKBCn9vn/hcRvxXZQ/vnwMdaKFTdVpeHfF9gec1lwd3oKXwNTyok7hFR9znBJ8OJGuhEqP1ifiTJYKWb906UOO85nu93/+zzocO6HBv6kA7Slz/npok7nxL/7W2Ywfy2GboZjSzjZwXmUt8a+06UBn/i5YmYeI8q+TG/VEHmt29f4OfNPGHl/WuHTbqQEkdbV3/lInfN13x96RmB3Js2uYaq0vcZu6Q9GmlDvRo16nOORbEM66c5Tgh1YHkub7bxdoSrx2qyTkkQj2XVOGUfw7ENwWoaXrzdaBVXIc7djkTP/HTJNKeowPFhnYMN24nHhyTlKs82o4mR+9/MNhNvCSw4/nYUDs6O55380Qo8aTFeQ9K3rej5lNBBqxo4o+Niy9Gd7Sj5avSjiw+RTzeLNffqr4d0TZ8SfK9QFy82dTi2+t25O7Au/lWGnGvbBHei8/akZN7amPnHeJ/1o3Wmxe2I1VG6BjfQ+JCzpm3mrLbkc9ihxfaJcRvan6N35HWjma0fVRdWUV8tVLSke8X2lF4Cu/i7c3EPfZ4nQ9KaEdPNh8oCu4mflKPVjkU045kDki2H+gnXmk9ttDlYDuq5iwIPzhM/JCX762KIGodjiunhfwlnr04cqumdzviWOZA85rVPu123bL2x1za0UwpsTWrRYgnZuvt7XBqR/UhW+oNpIl7BuV8UF7RjgbCxR8JKhNPbz92xZvRjsr+6XK+0ya+x+ZpeoZpO1oVnJGeY0o8q3Y5Zwf1uud8/lcCGcRnrDJ9NJN6X4e0uA9aK4jH2Zyq16A+R1MXx953TsRrPjmvWUZ97oh5rcsTXIhri96juVDf89A2ua2G3sTVHDLT/Kh1uZzad7M+iPi5V1sO7aHWkTNq5UKvg8SHTL+1B1Pr/iTYu+JXDPFk0ZgnvtRzin269VxYAnEbx6VqW6jnGhfkGP37AvGwSC81W2of6B/ZFeefRlz1tfhLFWrfOD7pzejKJn6pOW6ck9pnsSUfahmFxEv6uFsaqX05sSiX+/oz4s3lz7amUPs4Y2uE6dhr4meLec57UPvetPGCr209cYXr0scVqHPy7r31ufiO/zz3qnUmLdS5aht8m1/xnvgmWe7sI9Q5/Lcy9gnHF+I3/4X1a1Dn9k3429tao8QL3aTHq6hz7sY/FraWOvf/1xnl1j3bqbngke2lEshHfDHalDFKzRFJh6O3jor85/XBZauiqLlzSP357yQp4hfujr6bQc0pz6posYtKxLt7XHZGUXNtkab9SLIm8R139n8cpebg+4rTyXFGxB0Dil09qbn5+Gn7t72I+Aqn3J5qas4aNdz+52xH/NjmJl8tai6b3D7z1NiRuJjPQ75j1Bznb1m0iH8T8RiXvuJ2au7PmpjQaXYj3qz057QydU/E/Ljfcd6H+NEnJ+J9qHvFfOS33Jpg4p83m93LpO4hrdLgMZ6DxCMjb87uoe6tBbVt23KOEI/nOnRZmLrnbHa8c1h18j+usdvPnLoX+QZWl31KJl7Tqn10K3WPlv/99njvNeKfYvYNhVL3bnLxicX/bhIX3Dv7VgJ1TzuMcswJzyW+svT202vUve7vquYy/JD42iOqhreoHKDJ/C7j9oI4L2u1WBaVG5Y8WEIrf0PcV517+w0qZ0j2KJUurCeuIDJf/SKVS8at4tL3thP/khHid4zKMT19R9pLeomfPjrbaDeVe0b2LXabMUA8+nfpMUcqJ622TzJCP4mfmXl9lwaVqza0fVm9e4I4unZ1gIPKYd1jPvfOU7ns/3runRK+Giq3cRkvdXjIT1zXQrommcp5c5VqVGrmEZ+Me07fQOVC3ZuOBl1SxJ11q3zmUTnyvaNOQO9C4m2a7o6vqdx5vaC5jalO/Bpf3ngIlVP3FDzZWa9P/PHAZz85Ktc693hKPzUnvibP5v4LKgdbVXsOXWUQf8M9u2kLlZvH3J1b9y4nnrMrouknlbN9GN9bl6whvsdv4ulhKpdnib7rn+tMXPRE09k5VI5f+eE3X7Ub8RU7AzwSqdwfGzlHL8qbeG+lqa4g1RMevOXZphX4n/e/n8p9lOoVoNwcX7efuJ2v0rsxnxZklnf0gU8k8bxjNi0eVG9Z80q7Y/IYcReOxE8VVM9ZZfHrZ3QCcR+dS1LqVC9qbxf8y32euNhHjrAjVI8aSXv9a/814u6eO+a0U70r1Ty05WMG8a3BB9pVqZ42yki8tiyHuLTTSF8A1esuFMUvu3Gf+LbWM4z7VA+02/y3ceQJ8fcO0l9/UL3x0e9Yc/SKuNm1bcNqVM9kdPeHhlcSl9Iwct5C9dIC/f5TBfXEVT9FqMdSPTZ+xc69PW3ExRmLd+VRvVddaovWjB7iPDoKqg1UT54XVpMn95m4iqi7x1eqV5dcYP3V+Uo8puT7Yl6qhy9dUSJiOkL8rX9rhATV2yV3l/Qb//nP57+hFrCQ6vlbzWjRmlTv/7++QZeHW4397wUuFnZK8hNvET9upR7RjOYcz/s+KUx84f4P6irBzWitW+vz5vnEu2NWNMh4Ua836FtyU464gdsfC8HNzeiJ0ONoP2Xiw7ymAROrmlH4FtM9GprEL2jZ7+tlNKMQWT+JHn3iQnqxm14ZN6Nc2Lcz3oz43r4V8qnqzSi/J2GnFo148fHfdfvkmtGNpNni5UuIL4kY2bt8XjNqTXfc5bSSeIz9/QWSM5uRoNPgrs61xG+vv1PSM96EBhXCxDc6Ez9UsXnfjS9NSOLnw+1VrsTXu9pZe/Q2oaNbwjYZeRFfajWhJdvchNwa7/1M9iN+9hEvreEN9T5d3jpfgokf1eE6fPhpE3qGKgQtwohH1sf+0cprQryG8xIjIoln+zIeNaU3IcHEtPyio8QFDBqL955vQjMHh0OGThA3PdkvLhbfhCrKL7eLJRGvbDWpuHOoCdHz7ZkGF4mf0g7poQU1oVk+9ZHLUogn627dXufZhD6NSpQ6ZRBfW5q7dfOmJtRUsfDWxmziNR26zb0rmpBMy3z1NfeIi+pnNnrQmpBBltFKxkPiQxK9br0GTWhuVJuwWjFxGZXbx51Vm9A219CQma+IC85tdqyVakLXFe8e6HhD3Hy58SsQbEL7jqstyqj5z/78cqMvm6sJta1+sntHE/GL6ycqREcakay1o4tcB/HOMZGAfX2NiMv053B1N/EZohXvWzobUbPOG+2gj8Rjw/5p6dc2ItYmCRHBQeJ6q89siH3ZiCYU0JXU78TFKj29uwobUZHxs3q10f+sW5/zLo2sRtR/Vb8ga5I4k77Oe++VRuRzfx1DgYs57RpPDL2LExpRieVk5MmZxJtWdO/hjG5EYzukAn8IEFd7aZwMexvRZNsrsRUixFlhso1h3o3o6gMV/6sSxKM1Q0zytzSir5kJER+liZvckKv66NCI1D/utF+kSPzC8fFz4taNSM3AvGmTCvG/0h/S6caNiDGcKXNUg/jgv6IJb7VGVKa0XzVLl3jnz403Tsk0omrP42MvjYjTr57LyhVqRI+42hIazYm/WL5c9C13I+odODzcAcRf59sNfBppQK9fvlRutyFu/MTF5G9fA3Lr/KpWs4z4BktXHuEu6vWmB3mKVhEfKBXdIF/bgK6d/lt4ZS3xLdvoFhovG9CdVUq2ezcSn7P6ziODwgbEGfvk/pKtxK/0ibaZZjagnJn5fILuxJeYGqSZX25APMbCttU7/rPO3S/kzU41IF7Vv35RvsRfVftvMoxqQN8OFx/TCiB+c8bABs09DSg/quBc3R7iYh4dSopeDUibuS3FJ5R4geu7snnODUj25Zabk+HEo1quLeFa2YA2PfPKiz5M/HjJzbtD0IBO3tnwkvsY8ZCZ8TOb9RuQ8lXF3v3xxBWMWtYXKTcg46etIp8S/vPc7edkXpFsQAWGWZuWnyUueeA290GBBrRe+F1xxgXicn0quzf+q0f1YoPWv68Q/xHwfUTvRz06fHXZD/p14p67/VP4PtSjW0EpVYcziGcf5NzT1VKP3l+53VaURZxp+O9ATkU9UjS2lRvIId468eD5gaf1SNvEM004n7jW00A7u9x6ZMWQ8dV+QDymcJe0cFo92u5z/pB10X++lwnTuuVsPRL4Lffe4RnxJ97f3lw8Vo8WqkukrH1JXEmsPN85rB7t+TXxaFU58aeuYbMX+NWj5iJPE3ol8e/p0s1NLvVo2+zZiho1xDmVcmVPralHVcvuHZzTQHxPp86gjW094t1rs/pjM/HV9qdsx03q0afXJRmF7cSHzPIMs9Xr0bUd9KhwJvHcqIAXzrL1KFrk14BlL/G8jmvfZwnXo4dvFg4MfyBufpPjbT53PcoK1j6a1kd8xxP7rZtH6tC7mITypUPEyw11s7j66lD59eb8T9/+s69g1aOMjjrEZ35rzcFh4gH95mfs3tahXL2SnNlj/9k/o4fQ5+d16H7YaNWpCeIHcs6VHsmvQ/0FOoUC/4gfvfdDQyGjDt0u8wmM5CL//wqqjT8PPD5fh0QPFfF9mUH8dt+3J45xdchdc0n0aj7iLzL0hj8erEOTFsv6cwSIv9wzvDh0dx36WzPPmluI+LHVHtv53euQy0bei6vmET+ecf3OxXV1qM/o3PAZceL+yiV8qnZ16OGylZtrJYmL55VH5JvVoStJpW08MsS7tbMkLTXrkEHlrT268sQD963ueCVXh6qGC0ycFhKv1r5UtUykDg3/e6AepEy8JMdh+C1PHZq9OWH9scXECz/pbHQcrUVuiRqlZzWIl68Y4Kzvq0W+bbEHL2kTN3gq/8uhsxadKnx4/IIecant7qZv39aisbj6H6cMicfeM2pa+qIWbTDkLgk3IV5nIVjzMr8WHbt6mMPTnLhm/mpNi4xaZOd88YGNFfF7letH7p2vRcbo0jcZGvGL+p46qnG1aPLXx4IvDOKVEYU9lw7WovFL/XMe2hJvUAoUmru7FkWsl5sRupS4pGt+SbhbLXr/gy/dwJ74fosjf4fWUuuw1+z/tHfn71Tt7QPHm5xEhDpKGUpSyhDqlFJ3OAgVdQwZooQKJZSx0CmhQsYSmQllyjxP27TZm0oiqUyHypipU3S+vnU5676e5z94rs/7t/2yrb32Xmt91vbLbaL/COWKLj31hqrNYF+v8U/QUcpdAwu31sk1Q45yD3O3NuV+j/tFZcWbQfdkhnWrLuXGIbtpEYLNoKJs3W2tj95XtRUrC3czZLu0y80YUu6ms/1vq8XNYOtZdeWGMeUDCw/tjvvUBFb+37NZTqHz4XDhkFVzEwRynRl0P005a2iqgExOEwi7dImPm1PuJL3sxWRYE7j16nuYnKX8AzNgTZ5bE9wrqxqlWVK+1WPoy+XTTSB+k89743nKxWrj3GQONsFteyMtVxt0viUIZA+KN8Fp+eA/Gm0p352eEBfP3QQr6Mxw3kuUp/Gf1TOYYsKrL0KyBg6Ux3XbtXN0MOHb8ZiN95woF6jPkS0rY4L7Z1tHhgvldz0XXbwQz4S37Lm7Z6+g66h1+f11Pkw4Mx5qK+pOeXK0ZU7NeSaENyiKq12jPIcz+JnNMSaoGgzamV+nfHtmzyTvLiZYvaZrunpSvjEmdFvxOiYsfMbHuOVF+aW4RleTBUw417tmMsiH8q+HvUcW9DHgTi7789DblF+VSPePrmdAZIXchSBfyoWHlpnvT2MA7Bp+4eNPeZ7b706vAxmwrtuRwyWA8iml4WeXHBngs0xsk1kQ5S27XVw4jBhgp6e36WAI5SqC4BJ/gAEtZYZrRO9Rzpbo2C63iQFyloGs3+9TXhepGM1YxoBbEQYLmh+gdWx9XKvJcCNYP+Jli4igPLHI48bo80YIerFtu2kk5YviHmW65zWCh9aiq8LRlB/urDPniGiE4o0s397EoONl65IU5tEIfHyx2QFx6PoK3XVNxLwRzmWpZR9IoDz43cnpVLVGyBKwWfIxEa3DF+R5fpNshHZ+73TfJMrlBafainnm9mchR/m2FHSe50UdU5xuAMUHTgdojynP5JO+WdPRADyiB/fqpVI+ZuPtolbeAH0q3wp70yj/08jyt4b4BnCaWEm3zqD8l61/lmv4NICWDa/9SCblJV9PCTWcb4BxWZ9y6yzKRb/8qa92rAFUhyeKe7Mp7/5T+XLNbw2w6XyvnV4u5damY06K6xpgQ2jvIC0PXUeTOZYl/9Dhkv6NnRIFlCucTNHa1UsHsURtvbuF6HiVM7Zn1NFBzXjAaLiI8r/0lnJvSaWDnUaLlmoJWs8rRacjA+iwemX6vvBSykeEewdWOcz5Nm7Jj2WUS/3x/pOPwZwzg8V3VFC+nzeB5ft+OjwceankXEl5lGrCXtuNdGBK2bkVVFFezL4vqGcpHRqYrP0TNMr5Fzzl1hmsh21Re7y31aDz00q2uLq5Ht5PJ1ufqEX3/Quv7+3MqQdm/NfIW3WUX5RJSY4Pqwe71mdiWfWUS669O8XjVg+cXK2rX9HR+jZ2+rqHaT0Yrkq3n2pA67zAgPaQSj14NbMc5GZQ/ge93kZ/Wz1oKt+I2sxEz+ePaaOtqAepCy9vyDVRfsBkLEhqog5URRMWqTZT3iQrlhjWVgfr2aM3aj1D77c8duXikjrgOGH/Wfs55Ubv495bxdQBS2ejs84LtM5oGXO3eNbBmiQD2tEWyu91jSTvtayD41wNb9ReovtvnGla7JE62G7fyNjXio7jmlThZbJ1sJWDI1biFTqOxk/ZbFbXwa6GPWZ8bZTnmylatnyrhcN8i4UWtlNu/utaZbn3tRCQxtPZi/yTV0/kQ1ottOj+mkx7ja5rqd9cFybXQmRBjm90B+W3l93rNPOtBU/BhyFObyjvb3Kqr7WtBQ4p+4ZDnej7g6i84lbdWliU2ykn8JbyQrqUxp09tSBv5PHpA3Kl2rv9Q4K18NZ05uPTd5SXRt9aq7m4Fq4ajio6vadcx3tXf3p/DdzunJ6V66Lc4E60FldjDczIPRb9gjy4vkT/YkYNRItH1T7tpjw9woGlObgGMm+bfTrXQ7l6S4yulHMNJEx6RQj0ouuxm0XL70QN6F8N6GMgb+PWnxhUqIF/tJc8c+mjPCRLQUVDtAaCHY3PifxFuYme7sFkthoIPbqmgI7cd0Zg9peRanA6G08/3095ggrXGbMX1ZC60CaJYwB978oM8a7Iq577e6fTKAV5H22pmWBENaxy0Pys9IHyLI3Mby4e1TBot87+NXK/m8yjr8yq4ZJHwIfzHykPM/U9K6tWDSeN/jb5jvxVGoeiv0Q1mFoEvr/9Cd0vjp16/5G7GrKUgy7zDlK+8todZZUpGlzxExOLRE6f8LSPeU0DtzPOLBuH0Pm5fpf1TCkNSqUerkpAfs7yirReHA0MRRJOigyj7+HGm6ozvWjg/su98WjknAMTW5Zb00C94vyrtSPoPuUTY2yhRQM2Lj7eQOS7/F+eKd9BAyuRqwW/jFL+q4aUylo+GmQfsmtwQl6iqvDNfrYKjj6g6QwgL/YI9GZ0VYGCt6ypzhjlR8MiR0RrqqAtxvZrGXJXnlZpj5QquC8msmXLZ8o/XovUavergqvl3RO+yF/UHjssYz/3uhy7LMeQOyorid3Wq4KPZhEBx8YpH+bJ7evZWwUZdu6XMpH37ui/Lr++Cn7t3sfPOYE+z+esLCFLqqCLVTTwLPLD55QshwYqITvQ4V05claW3GxlRiUkSxhzrJ6kPMPWoe9hZiW47f4mYoXcwDZgdjKkEjTtDKVKkHOMsn0/7FIJbE9cd3JMofvjrrf9CcaV0OmqesAQudPG70WzipVQ/vn+8UfIu4/puOpsroQt2ru9xpD7GNWIprJXgkBzR4vcNOXHF4iXLRmtgG7YrO6B/Ii+vrJRSwUI9z0eoSFv4FxbmJVfATnbBhhLv1Du4ikjyP6wAsQvqA4dRO624qSd6bUKkCrZoOuNXJNfP6/AvAIMk4u4apBXnmEMcalXgCCXyqZFf1NevcWC96xkBSh+6gyXR64ANdJlPHP7ufHOlcvI7U/dOsA7XQ7tp5WbniDPPKimdL6jHNomPoR3I7foDNpDKyuH1CDlj7xfKbcynRRdF18OgkdXVKohr44aZ7XzLocjth+2uiIPWb6iq866HCyOnBJ/jPzkl8p0oaNz29k/wmhH7pPledlh59zrOk/xLv2G3ldenQyDrxx8WKs5ZZE/vz/WpDpTBkapQcUnkAubzWydpJXBzZeem72Q0z2dHWN9yyDuVrJuOvJx2S25mrplcNBiWqsVefP5sv4ZwTLw9zomMIP8pcLw8pT+UtC/5V25fobyKR4jUb2MUvjV46jq78jzO5J2LHEuBe6Pmk8tkBtfPL87U6EUmNlcbN7IWcv2yhizlcLJHew6ScgtOKOE2f9/LoxwTFgtco69/Gz54SXQECb4tg/5oXHpD2ZmJeDCV7hl8Szl30ePl3NLlMAp92B3IeT1Mkvulk4WQ9WygoE9yEtkYo5blRaDrK6ApQ7yYP77a9d4FcO5UzHLbJC/WHiolaZZDA03VzC8kN9bvu6O7ZpiOOzBXxiFXD3TWF6wqwjELc605iJ3e2vVT08ugrI0580M5MPbgnwd7YpAVXLuNo48dukGKZG9RVDKm3Z1Gm+/+0Rj8+IiSJt28GX/TnmKvp/51cZC4C7V7hdE7m86/lUspBD4s83uSmO/SL/TeqIQpK+l+SohV314eN110ULIFBPp1UZ+gJmVKDVSANOcsffNke9o3y71Jq8AVEeG0y8jz3w0me3tUQBf+ookPZGr6W/fvVOtAGqt4vmCkfuZLS/o4i4AZT3Jy7HIT+c93eX3Oh8k39YrZyB3fKmWvScuH4JCn/mXIL8/NSnZb5UP+s639OjIx4TbHwXtyAfo2xjTilxXc6XQgdk8eBebd7Ebea1jZfBgdR7IfFSjDyFfXrBoWZhfHoycrc/8grd/bthVWS8Pvqqv2LYYzX8tlIkcGhPKA5Hf38lxINcQETOOHMiFnvD+Ll7k4sx4hnpmLmzYWyG6HvnlPzbJTzvngkTxCLsYchf3kuQ4xVzouNIVLI28o82NV4s9F0yyRmhyePvZzn/OvMiBQ57GUQrIx5RLhpIicsB9w4nNasiPZOkd1zHPAac3LCe1kIcL61YulMwBG03jQ3rInem0bWlT2aDkojdyAjl9QXqwQVk2NPYzNMyQpx8Umv3FOxv2vvQxs0TeYiJknqWVDYOGIH8R+SaN/EYTvmxYG+n38jJypuln2eXdWbByarGsK/KLJ14+yE/JgvNb1uh5ID9qeHahuX0WpNzf/rsncpnRzDPc8lmQ4BE144N8qUQ+o2RJFpRvjf/TDzlfsoesJeMpJEhatQXi436LK4w39CkEZnAuuIf8k5/190rjp6AWF/rtAd5P7rDTNpufgvbyvxsjkSeufFC3bjQTQtXXOsTi/VGyl6jLzwQ5E8aXBORcC7YEXrqWCbC7RTcZucLpoqn16pnwx+y7gCfI/1DabsjgyYRfjQMepyMfkPMpc+7IgKEup4SnyM2T6jaKxmeAvtzqaznIHYpHvZ5bZ4Di3U7IR77l0uJBt50ZYNYl0VOIXFGJJVp3Jh0S1Q2tS5A/6Xx3Jt03Hf4+lfKmDPmZijApVqF0eHvr6M5K5AXZO6dPZqTBgUPOjjTkVyC3tEAhDTIS5eNrkPtlCNzkeZEKjy2Ti+uQ1wtfOGxllgqC/uUVdOQi15JX0SafwKiXQ3Yjcs7bzzr4vZ7A1YisECbyv1/1x15e8wQO7de2aEbe8HroHDP5MdiZiG1+jty4r3f75r2PQaf+S9sLfBy3MafdG1OA0/7qlZfIb1ellLadSAGBtjM8r5BzpLp6So8kw8gR4/A2vJ0mhUO3PJLBymR29Wvk7DOzPD3cyeDP1+bdgXzneEb73rgkGLByGn6Dz09Tw+jgHUmw38VE7S1y4YFZi6HqR9A3zvLgHfKElWESKnqP4DfLN+/fI//njMRE5EAiJCVqCHYjZzMqKpx2ToSSBTnHepA/NFS6psWeCLZZdm69yDXrq1WTIxJAQaYtpg+56XdFzkWSCWByVabkL+SXDhW1GJTFw4bLdc39yJtmJcOztOLBRrzjzQDyhbqRp5Z3x8GoXGLXB+S9gcu2mNvP+dKT7z4inx68OFyyJA6yhPe0fsLr6r2WbN7QWBD2PFUziNfhqh2uNptj4WHP9/Qh5PsfBCjU5cdA/MRvQcPI5ZQ/Ld2gPud5Wy+OIJf9oMB07ogG9oJplVHkbkkhwc+to8FQO3/1GF73lBk5ujNRYDF+vRs77+A5RVahKBDWsHn0GV+PrgubChQioSbkjsU43o5YsKGV2UOQoX8SmkD+1ybhAX6vCKhsfvAC+97ox5eYyeGgmZNwbRJ5RvX2hR6ND+B6K++PedLzvrM801d6JAxu8Ew3Yk8pkFzbwx0G3aOHf8yrnveT7Y8Sg3fch/r6DT/mW8+7joqArIrePQj96BiMnb7Jv2zaORQC8rR/zM+ed6mHsxrJESGwtaEoCfvvzWfbDMqC4RhPxo/53PP+obvZbHl3EGj8JfsIu+aXnWMlS4JgdKPaj/nf8y4ie/+qzeZAOHZgzB87X+70sg3qAbDEUGIGu1ucduhz67vAe+S76Qzym/LGyqxC/tBUZEbDPubHaWxl5guBa0/9mHc+70XXCx2YybchvnTcAfsmY1N/6REfcOnmr8N+0fSXpOAd3nAp9c2P+evzXtiSWD7tfBOE5H7Oa5/3G9NK7QZlN+BiyPpw7Cu43s59DtdhoCG+FbvcqctsG9SvwbuusuV4Xv5N41UqrELuIPzadh/2da5yjsxkV+DO/Tmfft63RxnM7acTyDv8nGc/70u0neb25xL8tfbn/Pt/P2ehoLnXtQW++J/z8ufdkEtvbvtW8Ir753z9f9+X9I257ZjBVrOf8/j/ff6xE3PPNwS28J/z+/91OeM514B9Hfxzj97/64G3gzR32Mr8l//78//4vwG0slX7/nFf5DH/mP0/f4FEIpFIJBKJRCKRSCQSiUQikUgkEolEIpFIJBKJRCKRSCQSiUQikUgkEolEIpFIJBKJRCKRSCQSiUQikUgkEolEIpFIJBKJRCKRSCQSiUQikUgkEolEIpFIJBKJRCKRSCQSiUQikUgkEolEIpFIJBLpf6//Aw==
- 00000000-0000-0000-0000-000000000000
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
- 00000000-0000-0000-0000-000000000000
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11471
27792
148
20
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11553
27802
- Rotation angle in degrees
- 08234d50-5319-4eda-b011-e5a672193566
- true
- Angle
- Angle
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- 0
- true
-
11471
27812
148
20
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11553
27822
- 1
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- {0}
- 45
- Rotation plane
- 71cf7492-5d81-4727-b72d-dda2eb760d72
- true
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- Plane
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- 0
-
11471
27832
148
37
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11553
27850.5
- 1
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-
0
0
0
1
0
0
0
1
0
- Rotated geometry
- d2a443aa-c60e-47a5-abed-2e2835b68a16
- true
- Geometry
- Geometry
- false
- 0
-
11643
27792
50
38
-
11668
27811.25
- Transformation data
- 897ce37d-d731-4fb4-b8fe-75df1d5dc9a2
- true
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- Transform
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- 0
-
11643
27830
50
39
-
11668
27849.75
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- e7a5cf4c-3f82-4f47-b79b-d8e2537d8afd
- 1
- a941ff94-f01d-41a5-8c0b-c7127477058b
- Group
- b7798b74-037e-4f0c-8ac7-dc1043d093e0
- Rotate
- Rotate an object in a plane.
- true
- 8c984148-7404-4d11-8d34-bca11770b24b
- true
- Rotate
- Rotate
-
11745
27792
226
81
-
11907
27833
- Base geometry
- 7f4e85e8-1d1c-48d7-8d91-6d18ec61aa57
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- Geometry
- Geometry
- true
- d2a443aa-c60e-47a5-abed-2e2835b68a16
- 1
-
11747
27794
148
20
-
11829
27804
- Rotation angle in degrees
- 7c6018ba-c804-42dc-9996-5cae1df22202
- true
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- Angle
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- 0
- true
-
11747
27814
148
20
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11829
27824
- 1
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- 90
- Rotation plane
- 6f386100-34ea-43f2-b91b-92333417f7d4
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- Plane
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- 0
-
11747
27834
148
37
-
11829
27852.5
- 1
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-
0
0
0
0
0
1
1
0
0
- Rotated geometry
- 187503ea-36dc-430c-b32c-9a0fc88ca815
- true
- Geometry
- Geometry
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- 0
-
11919
27794
50
38
-
11944
27813.25
- Transformation data
- 2edb102d-c38c-4b17-ad62-8b711fbd4fa7
- true
- Transform
- Transform
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- 0
-
11919
27832
50
39
-
11944
27851.75
- b7798b74-037e-4f0c-8ac7-dc1043d093e0
- Rotate
- Rotate an object in a plane.
- true
- f23308dc-6e0b-4773-8442-547e1fc6aa65
- true
- Rotate
- Rotate
-
11750
27886
226
81
-
11912
27927
- Base geometry
- 2c0ae8e6-3630-4763-8c31-b9bbfd2e3c67
- true
- Geometry
- Geometry
- true
- d2a443aa-c60e-47a5-abed-2e2835b68a16
- 1
-
11752
27888
148
20
-
11834
27898
- Rotation angle in degrees
- 92a62df3-18a7-497f-bad7-10c8f60f9a2d
- true
- Angle
- Angle
- false
- 0
- true
-
11752
27908
148
20
-
11834
27918
- 1
- 1
- {0}
- 90
- Rotation plane
- df893b4e-64c0-40e3-aab8-e58edaf6b4f6
- true
- Plane
- Plane
- false
- 0
-
11752
27928
148
37
-
11834
27946.5
- 1
- 1
- {0}
-
0
0
0
0
1
0
0
0
1
- Rotated geometry
- 95df8731-1a7f-41e7-a9cb-ee4366bdc926
- true
- Geometry
- Geometry
- false
- 0
-
11924
27888
50
38
-
11949
27907.25
- Transformation data
- 185ac99e-4fd1-4677-b7ff-41c7d45269a5
- true
- Transform
- Transform
- false
- 0
-
11924
27926
50
39
-
11949
27945.75
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 0904875c-3233-4683-9546-caf8a1b3bca5
- true
- List Item
- List Item
-
11675
27613
77
64
-
11732
27645
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- ee418169-09f2-4e76-b5d5-545d268e3f85
- true
- List
- List
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- d2a443aa-c60e-47a5-abed-2e2835b68a16
- 1
-
11677
27615
43
20
-
11698.5
27625
- Item index
- 0b00e8eb-bba4-4229-85d7-4a747af6e274
- true
- Index
- Index
- false
- 0
-
11677
27635
43
20
-
11698.5
27645
- 1
- 1
- {0}
- 1
- Wrap index to list bounds
- fae23512-71a1-4420-9312-ebcf2925939a
- true
- Wrap
- Wrap
- false
- 0
-
11677
27655
43
20
-
11698.5
27665
- 1
- 1
- {0}
- true
- Item at {i'}
- 1e161022-56a4-4db7-b405-3a1b081e4b21
- true
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- Item
- i
- false
- 0
-
11744
27615
6
60
-
11747
27645
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- e524ba89-65f4-457a-8f3b-566e3d69b338
- true
- Evaluate Length
- Evaluate Length
-
11643
27536
149
64
-
11728
27568
- Curve to evaluate
- f0ab2af7-69c9-43db-868b-caa852889764
- true
- Curve
- Curve
- false
- 1e161022-56a4-4db7-b405-3a1b081e4b21
- 1
-
11645
27538
71
20
-
11680.5
27548
- Length factor for curve evaluation
- fc420753-ba03-4fef-a0a8-a524c2294e69
- true
- Length
- Length
- false
- 0
-
11645
27558
71
20
-
11680.5
27568
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 8f83b134-0f2b-4506-a36b-358c77416dd0
- true
- Normalized
- Normalized
- false
- 0
-
11645
27578
71
20
-
11680.5
27588
- 1
- 1
- {0}
- true
- Point at the specified length
- ac15329e-7811-4638-9e02-958d44a78172
- true
- Point
- Point
- false
- 0
-
11740
27538
50
20
-
11765
27548
- Tangent vector at the specified length
- 68eeceaf-bc83-493a-bd93-69c0745eb406
- true
- Tangent
- Tangent
- false
- 0
-
11740
27558
50
20
-
11765
27568
- Curve parameter at the specified length
- e5f26acc-dc65-4f84-b199-bac1f44df9f2
- true
- Parameter
- Parameter
- false
- 0
-
11740
27578
50
20
-
11765
27588
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 17a07c24-0f69-4fa4-97bb-e3c74ef6d55c
- true
- List Item
- List Item
-
11964
27657
77
64
-
12021
27689
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- a7eca345-3aa0-4a12-8aa2-d6a39cf2468e
- true
- List
- List
- false
- 187503ea-36dc-430c-b32c-9a0fc88ca815
- 1
-
11966
27659
43
20
-
11987.5
27669
- Item index
- d14122b2-7acb-4746-a18e-74977033a79e
- true
- Index
- Index
- false
- 0
-
11966
27679
43
20
-
11987.5
27689
- 1
- 1
- {0}
- 1
- Wrap index to list bounds
- 54a61329-e56d-43ff-bc17-2fb9301f00ac
- true
- Wrap
- Wrap
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- 0
-
11966
27699
43
20
-
11987.5
27709
- 1
- 1
- {0}
- true
- Item at {i'}
- 8cb14055-5fd5-4d4c-bef3-3b128ef5471a
- true
- false
- Item
- i
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- 0
-
12033
27659
6
60
-
12036
27689
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- a3a0987e-4742-48b6-afc7-5797464d4f9b
- true
- Evaluate Length
- Evaluate Length
-
11932
27580
149
64
-
12017
27612
- Curve to evaluate
- 30685dfe-7c69-42e5-8c42-242b51d3ca47
- true
- Curve
- Curve
- false
- 8cb14055-5fd5-4d4c-bef3-3b128ef5471a
- 1
-
11934
27582
71
20
-
11969.5
27592
- Length factor for curve evaluation
- 07212ece-558c-4b90-aab4-fa97e1419910
- true
- Length
- Length
- false
- 0
-
11934
27602
71
20
-
11969.5
27612
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 24e30027-61a0-4bf9-8e3d-aaabcf947974
- true
- Normalized
- Normalized
- false
- 0
-
11934
27622
71
20
-
11969.5
27632
- 1
- 1
- {0}
- true
- Point at the specified length
- d862f42d-b7d5-4961-8f17-2c24fd595947
- true
- Point
- Point
- false
- 0
-
12029
27582
50
20
-
12054
27592
- Tangent vector at the specified length
- f285b504-4093-46e2-9eb0-9a385df801db
- true
- Tangent
- Tangent
- false
- 0
-
12029
27602
50
20
-
12054
27612
- Curve parameter at the specified length
- 5a57e3ed-694c-4971-b6d3-c608b9faaea3
- true
- Parameter
- Parameter
- false
- 0
-
12029
27622
50
20
-
12054
27632
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- ed800b1a-87bc-41be-b147-fd8cf8fee48b
- true
- List Item
- List Item
-
12047
28039
77
64
-
12104
28071
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- 7cdfb12e-b2df-4b62-9889-6b875368dc1c
- true
- List
- List
- false
- 95df8731-1a7f-41e7-a9cb-ee4366bdc926
- 1
-
12049
28041
43
20
-
12070.5
28051
- Item index
- 46a9e4b4-4ee0-4a14-8717-9ee715e06e09
- true
- Index
- Index
- false
- 0
-
12049
28061
43
20
-
12070.5
28071
- 1
- 1
- {0}
- 1
- Wrap index to list bounds
- 385de72d-084e-43f5-87e9-f9b7a9fd90b3
- true
- Wrap
- Wrap
- false
- 0
-
12049
28081
43
20
-
12070.5
28091
- 1
- 1
- {0}
- true
- Item at {i'}
- 1ba44e11-3244-4b08-8f5a-53473e7444b0
- true
- false
- Item
- i
- false
- 0
-
12116
28041
6
60
-
12119
28071
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 74d54793-b4ac-4902-b2db-7eb97fad4e83
- true
- Evaluate Length
- Evaluate Length
-
12015
27962
149
64
-
12100
27994
- Curve to evaluate
- bcac2eb2-1cf5-4798-b21c-3c1c4e53b1a4
- true
- Curve
- Curve
- false
- 1ba44e11-3244-4b08-8f5a-53473e7444b0
- 1
-
12017
27964
71
20
-
12052.5
27974
- Length factor for curve evaluation
- 942ec385-14c4-436d-82bf-254a62c4a81d
- true
- Length
- Length
- false
- 0
-
12017
27984
71
20
-
12052.5
27994
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- c507fc36-6518-440d-8b39-378189e13d72
- true
- Normalized
- Normalized
- false
- 0
-
12017
28004
71
20
-
12052.5
28014
- 1
- 1
- {0}
- true
- Point at the specified length
- 228ba4c9-f335-40d7-830a-930ba0b8f370
- true
- Point
- Point
- false
- 0
-
12112
27964
50
20
-
12137
27974
- Tangent vector at the specified length
- d66d6972-1966-4d7c-9727-8ccdb137e40d
- true
- Tangent
- Tangent
- false
- 0
-
12112
27984
50
20
-
12137
27994
- Curve parameter at the specified length
- ac5a3688-b5cc-4a0b-9013-606a50e82bfa
- true
- Parameter
- Parameter
- false
- 0
-
12112
28004
50
20
-
12137
28014
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- e22a8212-4fbe-44d1-8960-60bce1b0633f
- true
- PolyLine
- PolyLine
-
12318
27769
116
44
-
12382
27791
- 1
- Polyline vertex points
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- Vertices
- Vertices
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- ba092d75-6ec4-47d7-beb9-6b24514697d2
- 1
-
12320
27771
50
20
-
12345
27781
- Close polyline
- 44054ace-1398-46bc-9f17-4f9d8eeb27bd
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- Closed
- Closed
- false
- 0
-
12320
27791
50
20
-
12345
27801
- 1
- 1
- {0}
- true
- Resulting polyline
- 05892abf-8ecd-4e8f-8e64-1a63af85f8a0
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- Polyline
- Polyline
- false
- 0
-
12394
27771
38
40
-
12413
27791
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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- 02c8e8c3-a797-4e87-96c5-9928bebed6f3
- true
- Merge
- Merge
-
12183
27717
90
84
-
12228
27759
- 4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Data stream 1
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- Data 1
- D1
- true
- 228ba4c9-f335-40d7-830a-930ba0b8f370
- 1
-
12185
27719
31
20
-
12200.5
27729
- 2
- Data stream 2
- 372d7189-edd9-4199-bcd3-a3c8ea2484c4
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- Data 2
- D2
- true
- d862f42d-b7d5-4961-8f17-2c24fd595947
- 1
-
12185
27739
31
20
-
12200.5
27749
- 2
- Data stream 3
- 74aa7d1d-4920-4190-a60a-f45e0bd11a4b
- true
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- Data 3
- D3
- true
- ac15329e-7811-4638-9e02-958d44a78172
- 1
-
12185
27759
31
20
-
12200.5
27769
- 2
- Data stream 4
- 16d89d23-f403-40cf-869a-c47a5a6016e9
- true
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- Data 4
- D4
- true
- 0
-
12185
27779
31
20
-
12200.5
27789
- 2
- Result of merge
- ba092d75-6ec4-47d7-beb9-6b24514697d2
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- Result
- Result
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- 0
-
12240
27719
31
80
-
12255.5
27759
- 61d81100-c4d3-462d-8b51-d951c0ae32db
- Triangle Mapping
- Transform geometry from one triangle into another.
- true
- dc21fb8d-0ffb-45b1-aa92-8716354d0746
- true
- Triangle Mapping
- Triangle Mapping
-
12373
27648
126
64
-
12435
27680
- Base geometry
- 2746e58e-6745-45e5-bab3-d884e451357f
- true
- Geometry
- Geometry
- true
- bc6ee7cc-dfce-484f-b2eb-2a5a4d0007c8
- 1
-
12375
27650
48
20
-
12399
27660
- Triangle to map from
- e74900ea-b0f1-4464-9528-06aa310a52a1
- true
- Source
- Source
- false
- 313dc56d-5db5-4cb0-88da-248d848cf9d0
- 1
-
12375
27670
48
20
-
12399
27680
- Triangle to map into
- 909b36f8-16c1-4204-b306-99fd4cd11f04
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- Target
- Target
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- 05892abf-8ecd-4e8f-8e64-1a63af85f8a0
- 1
-
12375
27690
48
20
-
12399
27700
- Mapped geometry
- 311286dc-fe96-40a7-815b-24a54f71dd3c
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- Geometry
- Geometry
- false
- 0
-
12447
27650
50
30
-
12472
27665
- Transformation data
- e745e45c-567e-4db7-8ebc-2f3073131b2f
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- Transform
- Transform
- false
- 0
-
12447
27680
50
30
-
12472
27695
- c9785b8e-2f30-4f90-8ee3-cca710f82402
- Entwine
- Flatten and combine a collection of data streams
- false
- true
- 779daf5b-bb9f-4b0f-8250-d59d858f4457
- true
- Entwine
- Entwine
-
12189
27555
85
64
-
12229
27587
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data to entwine
- d3f7a5c9-5e8b-471c-8ae6-8a3fb0d3b7f8
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- Branch {0;x}
- {0;x}
- true
- d2a443aa-c60e-47a5-abed-2e2835b68a16
- 1
-
12191
27557
26
20
-
12204
27567
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26
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31
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85
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26
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12360
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- 2
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26
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31
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226
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148
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148
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148
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50
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50
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103
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27965
44
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27965
31
24
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27977
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172
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123
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123
37
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21
28
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11835.5
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28329
21
29
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11835.5
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77
84
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21
80
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28
20
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28
20
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11793
28250
28
20
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11793
28270
28
20
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11807
28280
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210
121
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132
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132
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132
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132
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132
20
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12038
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50
58
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50
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108
44
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38
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42
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11933
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42
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11946
28240
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70
44
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- 2
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11
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- Second item for addition
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11
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31
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70
44
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11
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11
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31
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28357
226
81
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148
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148
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148
37
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0
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50
38
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12434
28397
50
39
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12459
28416.75
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28460
226
81
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12428
28501
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148
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12350
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148
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12350
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12268
28502
148
37
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12350
28520.5
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12440
28462
50
38
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12465
28481.25
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12440
28500
50
39
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12465
28519.75
- c9785b8e-2f30-4f90-8ee3-cca710f82402
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85
44
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27556
26
20
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12603
27566
- 2
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12590
27576
26
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12603
27586
- Entwined result
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12640
27556
31
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12655.5
27576
- c9785b8e-2f30-4f90-8ee3-cca710f82402
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12590
28234
85
64
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12630
28266
- 3
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26
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12605
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- 2
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28256
26
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12605
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12592
28276
26
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12605
28286
- Entwined result
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12642
28236
31
60
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12657.5
28266
- c9785b8e-2f30-4f90-8ee3-cca710f82402
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12718
27592
100
64
-
12773
27624
- 3
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12720
27594
41
20
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12740.5
27604
- 2
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12720
27614
41
20
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12740.5
27624
- 2
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12720
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- 760cce7b-3054-4829-8291-596dece49fae
- true
- Merge
- Merge
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28499
90
64
-
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28531
- 3
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- 2
- Data stream 1
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- Data 1
- D1
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13128
28501
31
20
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13143.5
28511
- 2
- Data stream 2
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- Data 2
- D2
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13128
28521
31
20
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13143.5
28531
- 2
- Data stream 3
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- Data 3
- D3
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- 0
-
13128
28541
31
20
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13143.5
28551
- 2
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-
13183
28501
31
60
-
13198.5
28531
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
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- ba33b008-e040-47d1-8e6f-3b360b5bf43c
- true
- Polar Array
- Polar Array
-
13245
28406
207
84
-
13372
28448
- Base geometry
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- Geometry
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- 1
-
13247
28408
113
20
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13303.5
28418
- Polar array plane
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- 8466f10c-3993-400e-8742-e7e3f179651f
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13247
28428
113
20
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13303.5
28438
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0
0
0
1
0
0
0
1
0
- Number of elements in array.
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- Count
- Count
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- 0
-
13247
28448
113
20
-
13303.5
28458
- 1
- 1
- {0}
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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- Angle
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- 0
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-
13247
28468
113
20
-
13303.5
28478
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
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- 1
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-
13384
28408
66
40
-
13409
28428
- 1
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- 0
-
13384
28448
66
40
-
13409
28468
- 8073a420-6bec-49e3-9b18-367f6fd76ac3
- Join Curves
- Join as many curves as possible
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- true
- Join Curves
- Join Curves
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13292
28289
116
44
-
13359
28311
- 1
- Curves to join
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- Curves
- Curves
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- acba9f12-7c5f-4b20-8140-fb2b4854a190
- 1
-
13294
28291
53
20
-
13320.5
28301
- Preserve direction of input curves
- 580c60ac-9f04-4a69-a4c5-792bfb2af31d
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- Preserve
- Preserve
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- 0
-
13294
28311
53
20
-
13320.5
28321
- 1
- 1
- {0}
- false
- 1
- Joined curves and individual curves that could not be joined.
- b1b2d77d-acac-4f93-9d49-1df12c7f025d
- true
- Curves
- Curves
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- 0
-
13371
28291
35
40
-
13388.5
28311
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 60b468ed-f005-442a-98a1-2f5f06f6910c
- true
- List Item
- List Item
-
13024
28677
77
64
-
13081
28709
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 1
- Base list
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- List
- List
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- c7759ede-6017-4b39-8cfd-985e47669aa1
- 1
-
13026
28679
43
20
-
13047.5
28689
- Item index
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- Index
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- 0
-
13026
28699
43
20
-
13047.5
28709
- 1
- 1
- {0}
- 1
- Wrap index to list bounds
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- Wrap
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- 0
-
13026
28719
43
20
-
13047.5
28729
- 1
- 1
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- true
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- Item
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- 0
-
13093
28679
6
60
-
13096
28709
- b7798b74-037e-4f0c-8ac7-dc1043d093e0
- Rotate
- Rotate an object in a plane.
- true
- 345e50d9-106f-48b0-8a5f-82619b7a42d8
- true
- Rotate
- Rotate
-
13158
28714
170
64
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13264
28746
- Base geometry
- c286fcd0-5674-4abe-97c2-0bcf4575c810
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- Geometry
- Geometry
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- 3914ac59-33d9-41bd-9611-37164936a031
- 1
-
13160
28716
92
20
-
13214
28726
- Rotation angle in degrees
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- Angle
- Angle
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- 0
- true
-
13160
28736
92
20
-
13214
28746
- 1
- 1
- {0}
- 120
- Rotation plane
- 6eeefe70-d133-49f6-87f3-0b41ae5f41ef
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- 8466f10c-3993-400e-8742-e7e3f179651f
- 1
-
13160
28756
92
20
-
13214
28766
- 1
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- {0}
-
0
0
0
1
0
0
0
1
0
- Rotated geometry
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- Geometry
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- 0
-
13276
28716
50
30
-
13301
28731
- Transformation data
- cb9754f9-2131-4039-acb5-708b06b2b6e8
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- Transform
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- 0
-
13276
28746
50
30
-
13301
28761
- 75164624-395a-4d24-b60b-6bf91cab0194
- Sweep2
- Create a sweep surface with two rail curves.
- true
- 2b841695-b801-4232-8cec-df1e95b3ffb0
- true
- Sweep2
- Sweep2
-
13560
28253
125
84
-
13646
28295
- First rail curve
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- Rail 1
- Rail 1
- false
- 5ef63ff9-6730-42b3-b53c-8762ec52dae5
- 1
-
13562
28255
72
20
-
13598
28265
- Second rail curve
- 77951b5e-c755-4586-93e1-b5073c2e9e8e
- true
- Rail 2
- Rail 2
- false
- 25b86b00-4b1e-44df-819e-b87ac8d0f104
- 1
-
13562
28275
72
20
-
13598
28285
- 1
- Section curves
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- true
- Sections
- Sections
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- 3b6ac9ce-f66a-47f3-8b74-010a93404a3e
- 1
-
13562
28295
72
20
-
13598
28305
- Create a sweep with same-height properties.
- 1e488029-c63b-4aef-bc34-8917303e40cc
- true
- Same Height
- Same Height
- false
- 0
-
13562
28315
72
20
-
13598
28325
- 1
- 1
- {0}
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- 1
- Resulting Brep
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- true
- Brep
- Brep
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- 0
-
13658
28255
25
80
-
13670.5
28295
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- ed0799d7-3bc0-4ce1-9e3e-b4eafc3d5546
- true
- List Item
- List Item
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13160
28860
77
64
-
13217
28892
- 3
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Base list
- f7743e62-b11d-449c-805b-d4e4257f458b
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- List
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- c7759ede-6017-4b39-8cfd-985e47669aa1
- 1
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13162
28862
43
20
-
13183.5
28872
- Item index
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- Index
- Index
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- 0
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13162
28882
43
20
-
13183.5
28892
- 1
- 1
- {0}
- 12
- Wrap index to list bounds
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- Wrap
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- 0
-
13162
28902
43
20
-
13183.5
28912
- 1
- 1
- {0}
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- Item
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- 0
-
13229
28862
6
60
-
13232
28892
- b7798b74-037e-4f0c-8ac7-dc1043d093e0
- Rotate
- Rotate an object in a plane.
- true
- 8127be20-15af-4403-a90d-24fce3ed1524
- true
- Rotate
- Rotate
-
13382
28749
226
81
-
13544
28790
- Base geometry
- 8a7ab199-336d-490b-bd2c-28be72aef29d
- true
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- Geometry
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13384
28751
148
20
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13466
28761
- Rotation angle in degrees
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- 0
- true
-
13384
28771
148
20
-
13466
28781
- 1
- 1
- {0}
- -90
- Rotation plane
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- 0
-
13384
28791
148
37
-
13466
28809.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Rotated geometry
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- Geometry
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- 0
-
13556
28751
50
38
-
13581
28770.25
- Transformation data
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- Transform
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- 0
-
13556
28789
50
39
-
13581
28808.75
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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- true
- Merge
- Merge
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13370
28599
90
64
-
13415
28631
- 3
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- Data stream 1
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- Data 1
- D1
- true
- 3914ac59-33d9-41bd-9611-37164936a031
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13372
28601
31
20
-
13387.5
28611
- 2
- Data stream 2
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- Data 2
- D2
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- a0df3237-16e5-4cbd-a199-50b04c6274bb
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13372
28621
31
20
-
13387.5
28631
- 2
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- Data 3
- D3
- true
- 0
-
13372
28641
31
20
-
13387.5
28651
- 2
- Result of merge
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- Result
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- 0
-
13427
28601
31
60
-
13442.5
28631
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- Flip a curve using an optional guide curve.
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- Flip Curve
- Flip Curve
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13434
28501
88
44
-
13478
28523
- Curve to flip
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- Curve
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- 1
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13436
28503
30
20
-
13451
28513
- Optional guide curve
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- Guide
- Guide
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- 0
-
13436
28523
30
20
-
13451
28533
- Flipped curve
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- 0
-
13490
28503
30
20
-
13505
28513
- Flip action
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- Flag
- Flag
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- 0
-
13490
28523
30
20
-
13505
28533
- 22990b1f-9be6-477c-ad89-f775cd347105
- Flip Curve
- Flip a curve using an optional guide curve.
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- Flip Curve
- Flip Curve
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28778
88
44
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13701
28800
- Curve to flip
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- fd3fe45d-1cc9-4719-8b08-78676aec904b
- 1
-
13659
28780
30
20
-
13674
28790
- Optional guide curve
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- Guide
- Guide
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- 0
-
13659
28800
30
20
-
13674
28810
- Flipped curve
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- Curve
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- 0
-
13713
28780
30
20
-
13728
28790
- Flip action
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- Flag
- Flag
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-
13713
28800
30
20
-
13728
28810
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 9935447c-3f80-44d3-8052-01fa076971e7
- true
- List Item
- List Item
-
13116
27951
77
64
-
13173
27983
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 1
- Base list
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- List
- List
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- 311286dc-fe96-40a7-815b-24a54f71dd3c
- 1
-
13118
27953
43
20
-
13139.5
27963
- Item index
- 005f07a2-8048-404f-883d-5a342c3566e4
- true
- Index
- Index
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- 0
-
13118
27973
43
20
-
13139.5
27983
- 1
- 1
- {0}
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- Wrap index to list bounds
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- true
- Wrap
- Wrap
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- 0
-
13118
27993
43
20
-
13139.5
28003
- 1
- 1
- {0}
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- Item
- i
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- 0
-
13185
27953
6
60
-
13188
27983
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- f82a0798-5b96-45db-b9f8-e020f2a5c1c6
- Group
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- Curve Middle
- Get the point in the middle of a curve
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- true
- Curve Middle
- Curve Middle
-
14260
27996
101
28
-
14304
28010
- Curve for mid-point.
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- ff4b1356-82ea-4cf7-9d66-2ed9f409faef
- 1
-
14262
27998
30
24
-
14277
28010
- Point in the middle of the curve
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- Midpoint
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- 0
-
14316
27998
43
24
-
14337.5
28010
- fbac3e32-f100-4292-8692-77240a42fd1a
- Point
- Contains a collection of three-dimensional points
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- Point
- Point
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-
13690
28056
99
24
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13777.65
28068.02
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- 1
- {0}
-
0
0
0
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- Relay
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- A wire relay object
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-
12392
28034
40
16
-
12412
28042
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
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- Polar Array
- Polar Array
-
13659
28356
207
84
-
13786
28398
- Base geometry
- fcd5c8ad-c3be-4e0f-aa7b-6a718f026e43
- true
- Geometry
- Geometry
- true
- 0490c4ad-b715-43e9-85d4-2fa26a0f17a7
- 1
-
13661
28358
113
20
-
13717.5
28368
- Polar array plane
- 1b718b59-fd18-44eb-b17c-1fd6a1a0c6a7
- true
- Plane
- Plane
- false
- 8466f10c-3993-400e-8742-e7e3f179651f
- 1
-
13661
28378
113
20
-
13717.5
28388
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 17c2c2bb-1438-410d-9450-05653a3d6610
- true
- Count
- Count
- false
- 0
-
13661
28398
113
20
-
13717.5
28408
- 1
- 1
- {0}
- 3
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- cd9bc5d0-c344-4716-a064-eecf171207ef
- true
- Angle
- Angle
- false
- 0
- false
-
13661
28418
113
20
-
13717.5
28428
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- 8417b745-f41f-4d9e-8bbb-9e5377f43932
- true
- 1
- Geometry
- Geometry
- false
- 0
-
13798
28358
66
40
-
13823
28378
- 1
- Transformation data
- 9beef5c1-f0e3-4213-8b40-a8de215f7c5b
- true
- Transform
- Transform
- false
- 0
-
13798
28398
66
40
-
13823
28418
- 75164624-395a-4d24-b60b-6bf91cab0194
- Sweep2
- Create a sweep surface with two rail curves.
- true
- 1df9d5e6-0ba1-4a1d-98c6-385bff3e9a5d
- true
- Sweep2
- Sweep2
-
13628
28616
125
84
-
13714
28658
- First rail curve
- b18cea78-d396-434a-b057-a5994b6649ae
- true
- Rail 1
- Rail 1
- false
- 788c609b-314a-42fc-9ea6-dd50e84c46d0
- 1
-
13630
28618
72
20
-
13666
28628
- Second rail curve
- 33b8c586-75e6-4631-828e-efad1f382d6b
- true
- Rail 2
- Rail 2
- false
- a9ba64db-3550-4932-9fee-3e0b1c0f003b
- 1
-
13630
28638
72
20
-
13666
28648
- 1
- Section curves
- 983cc157-3d94-43a5-9ddf-15500de2ac90
- true
- Sections
- Sections
- false
- 3914ac59-33d9-41bd-9611-37164936a031
- 1
-
13630
28658
72
20
-
13666
28668
- Create a sweep with same-height properties.
- 4f12b42c-ec4a-489b-887b-9f59ee1a5034
- true
- Same Height
- Same Height
- false
- 0
-
13630
28678
72
20
-
13666
28688
- 1
- 1
- {0}
- true
- 1
- Resulting Brep
- 3ae18dd7-3009-43a7-983b-2c350bfef07c
- true
- Brep
- Brep
- false
- 0
-
13726
28618
25
80
-
13738.5
28658
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- f9e9b3d3-0249-4fcd-9010-bda7192c49ec
- true
- List Item
- List Item
-
13278
28503
77
64
-
13335
28535
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- e3fa9389-8bb9-4073-bc9a-8fe79cbc3dc9
- true
- List
- List
- false
- c7759ede-6017-4b39-8cfd-985e47669aa1
- 1
-
13280
28505
43
20
-
13301.5
28515
- Item index
- 1f0c42fb-a12e-4e1e-a081-0ae5918b3e34
- true
- Index
- Index
- false
- 0
-
13280
28525
43
20
-
13301.5
28535
- 1
- 1
- {0}
- 6
- Wrap index to list bounds
- e30de5c8-e07a-4549-97aa-1294a3f1ea5c
- true
- Wrap
- Wrap
- false
- 0
-
13280
28545
43
20
-
13301.5
28555
- 1
- 1
- {0}
- false
- Item at {i'}
- a9ba64db-3550-4932-9fee-3e0b1c0f003b
- true
- false
- Item
- i
- false
- 0
-
13347
28505
6
60
-
13350
28535
- f12daa2f-4fd5-48c1-8ac3-5dea476912ca
- Mirror
- Mirror an object.
- true
- 4b52ff38-2edb-42fc-ad3c-aad65645bfbf
- true
- Mirror
- Mirror
-
13879
28584
305
61
-
14120
28615
- Base geometry
- 505f36ba-5d42-4711-bb2f-12412b8d9067
- true
- Geometry
- Geometry
- true
- 3ae18dd7-3009-43a7-983b-2c350bfef07c
- 1
-
13881
28586
227
20
-
13994.5
28596
- Mirror plane
- f2f9db89-552e-445e-8378-f2fc9f019f55
- true
- Plane
- Plane
- false
- 0
-
13881
28606
227
37
-
13994.5
28624.5
- 1
- 1
- {0}
-
0
0
0
0
1
0
-0.707106781186548
0
0.707106781186547
- Mirrored geometry
- 9e81018f-eb0e-422b-8b03-5fa6f29962ba
- true
- Geometry
- Geometry
- false
- 0
-
14132
28586
50
28
-
14157
28600.25
- Transformation data
- 9cd75d03-875f-4f14-a38a-33fee0ebdc03
- true
- Transform
- Transform
- false
- 0
-
14132
28614
50
29
-
14157
28628.75
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 2aa02528-07ad-4eb2-a14e-23480eb36571
- true
- Polar Array
- Polar Array
-
13970
28697
207
84
-
14097
28739
- Base geometry
- c7101f1b-5f11-4b5a-8ce4-aca0d3add6ab
- true
- Geometry
- Geometry
- true
- 060648e6-d9c2-477c-ba2f-71b14f63a036
- 1
-
13972
28699
113
20
-
14028.5
28709
- Polar array plane
- a8471fed-2546-4fb0-93a9-d9cebc0b92ea
- true
- Plane
- Plane
- false
- 8466f10c-3993-400e-8742-e7e3f179651f
- 1
-
13972
28719
113
20
-
14028.5
28729
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 0e17a2e0-16f2-4382-82e4-704ea4d7c239
- true
- Count
- Count
- false
- 0
-
13972
28739
113
20
-
14028.5
28749
- 1
- 1
- {0}
- 3
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 5bc28fd2-567f-42d5-976a-afe024f38684
- true
- Angle
- Angle
- false
- 0
- false
-
13972
28759
113
20
-
14028.5
28769
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- b3e9652a-0589-4dbf-b8e1-243721b1bfc1
- true
- 1
- Geometry
- Geometry
- false
- 0
-
14109
28699
66
40
-
14134
28719
- 1
- Transformation data
- bbc36e0c-38f8-4c59-8ccd-b9ec863cf0e6
- true
- Transform
- Transform
- false
- 0
-
14109
28739
66
40
-
14134
28759
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- a1881539-51c5-48a1-b579-c1eeb39cdbdd
- true
- Merge
- Merge
-
13961
28480
90
64
-
14006
28512
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- 38b8585d-bfe9-4a59-be1f-6f310459249a
- true
- false
- Data 1
- D1
- true
- 3ae18dd7-3009-43a7-983b-2c350bfef07c
- 1
-
13963
28482
31
20
-
13978.5
28492
- 2
- Data stream 2
- 6b0e7e6c-52be-48fb-934b-f4c80cd0c3fe
- true
- false
- Data 2
- D2
- true
- 9e81018f-eb0e-422b-8b03-5fa6f29962ba
- 1
-
13963
28502
31
20
-
13978.5
28512
- 2
- Data stream 3
- 264bee91-6031-4c1f-aae1-ef024f5be16e
- true
- false
- Data 3
- D3
- true
- 0
-
13963
28522
31
20
-
13978.5
28532
- 2
- Result of merge
- 060648e6-d9c2-477c-ba2f-71b14f63a036
- true
- Result
- Result
- false
- 0
-
14018
28482
31
60
-
14033.5
28512
- 57b2184c-8931-4e70-9220-612ec5b3809a
- Patch
- Create a patch surface
- true
- 896526e7-4b6f-49d0-9eba-8afd5bc1f034
- true
- Patch
- Patch
-
13765
28213
119
104
-
13841
28265
- 1
- Curves to patch
- 57e2c7ab-acb9-4ad3-98b6-2608f40034d6
- true
- Curves
- Curves
- true
- b1b2d77d-acac-4f93-9d49-1df12c7f025d
- 1
-
13767
28215
62
20
-
13798
28225
- 1
- Points to patch
- 63afc207-44e8-434b-a8b5-07bc63a085f4
- true
- Points
- Points
- true
- 5cacee03-857e-4f27-8db3-fad6acaee1f8
- 1
-
13767
28235
62
20
-
13798
28245
- Number of spans
- 94205002-ff33-4d56-aa50-8c9de91b06d7
- true
- Spans
- Spans
- false
- 0
-
13767
28255
62
20
-
13798
28265
- 1
- 1
- {0}
- 16
- Patch flexibility (low number; less flexibility)
- fc501350-14e6-48eb-a9a6-29dedcd983f8
- true
- Flexibility
- Flexibility
- false
- 0
-
13767
28275
62
20
-
13798
28285
- 1
- 1
- {0}
- 8
- Attempt to trim the result
- 5159e24d-fc93-4859-a5c5-506c1538b080
- true
- Trim
- Trim
- false
- 0
-
13767
28295
62
20
-
13798
28305
- 1
- 1
- {0}
- true
- Patch result
- d636886e-6a7c-4eda-b4a4-ca364081a1e2
- true
- Patch
- Patch
- false
- 0
-
13853
28215
29
100
-
13867.5
28265
- f31d8d7a-7536-4ac8-9c96-fde6ecda4d0a
- Curvature analysis
- Analyzes surface curvature
-
Dgva7o5MdBxh6ffAWXPPNJAy7sRtRKbicMvX5SX8WMHBAH39x104KL4LljbN5bT66X9MvUq3rFpnJek0kQoWLPiYB5rRYiPhXSpDhdptFKa22IUpk38BjRJJbWayiQM/IqWsrckG0u3neyIDB+vNV9gfwxw3xYacnqWl6buiR5MjUZqtmlfMl1V3CqI0H5r0yBdeefC9P8EqNGJCvJnw1a1YS2SV71vSGcSv8dPB0CPABJSGmuivV2FnQ9jidF94008wEsXLUyS5nOU1Dk1Qc01c8+EBpmJWSgLVnkuES4ixjYcJOS8MhPM24U/fe7Z6Nnw3AwvUrBTQQtyNvbALV6+da2btb3BxHA+gMfsKy3zO6my5QeQEXWISmkIi07l3HLcD42GzR9mr2hIaxbAcLujonUPL0QfVOohxSxVPl0TdUgf+yxcGnUg8nhTKUceklz42bU5uqyDFpHLkriYWBhuDO13c9DCDSBYpoDmKNQ873akOYIlLkLIiNlQpr42pQTW+Jqgprmurue/FlqPn5vXpXI15RxeZ7zgUXVa3TR1Rv3kQTlydekocJDSsTCnLSvbR1Zgv7BSoDVx01bcCdxWO8/E6TLL+scAM0VFzpuaO21UTs2S8dFcB0ZzjGdhQopTpCdcgPYzWnLc1pzwU2SJXflZvfDP8a3uyP5P62HZi6N3a757+lFtvWYd6ingE2jVA1Ahe/hN3KZgcre5PJU/MiYB/yjXGeUfBuVoWRkhey/N3yW1FTkwqCSP+AXxsXcG+ChRWt0b6vglVHD8Sz8GA17SEKgL/612JAeq0Wj9YDw9VevXiE5OXkf405M3etTYGHJya7X4r25Am+ug8Wl6TjMCV1RsKYVZJmzgPkvdLhfxs5nrYA3gWSrzWmooYWA1FOdRA1rYlklughEoNzrlwHt2Re5Mu9r39nHPmVO0aQWyqAkJunN++3c39WdWcRs1SyQIQJyx2+DelsY4AIQmWnI/hN2I+GQBMkpm0bKx9e7BCq0pDvcgJaDb0LnJnaPfVqNDaHt3UUPSmN0QwY1sgVOXl61w7zUUPmrdMX4/Jq4F7tLueSSeCRBh7MNBmAMeS6F6PAM8RMfY2oyfyunRv+dE8b0PSbKtNcDCBctcQ7UpUWEsisxYLHyW814ci4ujoinrNsaoYuNbejPlF3beBHiVl15ILItltUFjkAVv5XWzHAwcScTzNf0iloA4V76NQXpTpjlUcGfjP7Q7VV+I52aV/6rtmuCNeADTq7CKEpYWZHibaxhwEVpMCUE/t4aKr/8xUk9DoOJvNvS8gtdvvsFOk6HS3CHQztQzkfKxBSUmXw6Vihu9ETGp9jhALb6DrTZfFLpeEaJ/lZURi0TXhJ2wMDKjDHXTp9HwCR8bk4q8gA8QdqNZFV9zJ0Xg3o6EP33WdnOvjHZOXQGzcG7Ao3f5153utPmym1VNPJL0bEMWTr4J5Eh8404Sgr8OYGbI57svKELbHP66gFHZTUlY4DBW1PwGJoAZZse8FxRQ9+Lxj8Dn4ZULg9Ar+bZm29Mkrf00tdNy3LVbkE6la0keSVGfV4y0nigEkidW/a4YBojauVuWUEWiR/t3l3fmOjDWfRi7utdfBRYnUwdQLOeftegMw+UI568GB3+3Kei4aWlrfYiHGZXQwFCaUM60Mol2NfxGpkYqSt4XZLV8dyHCz1CZrvKgUgysMtdLjreI2L0CxQ0L7+JL27QrMigsFeJ2Vj/U3RlrEHQABc4goNqQoWTvClSY9yBrtvgeYzj196EycmSW4H/x3lji56Cg9J9uyYf4GU3YD7XCbiVhGtLI+uVMyx3iUHRQEr+2oy4GYTviR5vIcvi7tualfEMuG61dce84czN3KCBXa/KbfPqXl8/w8y62CBAnMzVxwfcAekM9QNAKqSTQlma6AJUHSKmMZd7DmJBM3aaLKR2Q5i5Li7JnUoE1t9fwCVJh10vFLMD3gqglGUwSQx5t2JaNPbg40IXZtiFaLyW444IciaW7V245k/rvN3nKpcM8LqbY6HDfWcBnmwdwjB3pnYJld03OQWRTTI0zhWVETBC/Hzi8u3v/WRQPQjY6e3XkJf+QfIxA5bn0IF4i6Kr2kaLDAs7did3bjQin0ruWLtl6tDf1eP/tVM9sxgDR+O3vfFzMsWP2gwe5Nd2jVU7bdtyzYCLJiAQ3uLGKwumfrOjQazACFoihok3Ed/rZqFQpkWVD0+SRxHiNYKHO7y+7vF3K1hIezX514Tk4lTg8jgFtPG1QeSVSk4gn7kYaXwylWDriugI2BIYb9Zj1Y0IRbbKRjNKYASIOt6qJUWPHa1sdiQPaQZ6+argVtpn8+Yd/pYH+ANNT4FykAEL6bs2ykACiTm8dBgYTwTxDuy0BJVEp9ZNdgZbdYUBpC96W54Umu2MNqLFTBFAqwydTebMoSY6gf5ZddIllpo+7CB9LZSA1qZvm0YvDXqfMvau2uXVdFfIg7eeVzXP1gWvHxSC9c7vJmWDI333KTYqBWaanK1OuAMY4MQ1XqEX9qcj/RIdQApB6/g+mj9GZclwsN0v1Ryt2RnimZaKW6dTjqvZ0yDEUMefbx+PWAj8Nly7+ls6rbIiYQbNpd8DG1N9vGFaiIr0z595y8l0HbqxqTkRTWgtwXkJfWTQHbiJ9TAruyHgJfBb7wP09IQRrf8r2lets8rUOVRtk77Ysw+fpLoGX/dKaiaxbmKUYIQEWmRVZ9N7p5KhuTfw8b/BEz2uBQRFCW6LAUOGi71aSsXZCwOtGLwSZccWF0W0YC6CeFEoH2Q2NScycr+84Xa5jfg4FOgHPFZHe1WMl5B1SqDDcAMywRnit+emd7BOnc5ZWDilrcjLhaMSXLW23LOOlpy3ex9tFRaK3fPsC0K6SUW8vrlmVfzsA7+MBSsS1UaHgERF71soPaJrEJkGjtfI1emx13dcuQB2PbgAXXHijArUkYhLFXT+Lrvx0RyZMt+WgAGZFscawvXPf8Po2y+RfqfMs40YlnA4BabAMXuRKWGb62UDpkFMCxZF+ppmAGgcv3u0efbPUVfrAUwzr6kVzpil5C19hRgmBkZ8nxH3k0wTEdLiqTckXAR3qixSoPzF1jLMhGL9v7VHXId+tWEiEEzLbO8TxjtJJLR8kg8pQqvllrT+kTx49HB/t2thwRkGZTFECE45X0G9VIGrg4Ss8GxC5TL7HCE3SRe7Z1dXXTH6nnZIKy3u2wqUuX/mU7l7PXeaycvqON3Lh7e89cR4SN41YBeCg5qP+9nob9M1TqctwFl6zfeOfqAneJ/Fvr7OaQtO/myYDK9oXk7zmklEpvb1zseiUrGGJ/we8kc5SAu4m/ei9LJxnu6aCnUVxwgC88PFDGrxSyxzaOxQd3RmC3XR/QtCgQ3Esnfqxq+jr+Sf7r4VnBHqrqYI2XwICGe8/wKzfMxcsiPLvr3xhIaOQ83LSjA4ljK77aLfSgDIADhydkgEUnrpbw2xzm8GTxJ8Ah9f2PT22E+re+wSO6g4dAYf8JKO8VIlgBzue55mg5TodX2kD9c7/288bd9rybFONufvKEJqo1Q1nR68Y+Nk/N0g38UIvqVX3hICwsyWe22ssdGk519bMO1xU8J7gHSPaTOSvGkQLvyp7iJg8RnGcFeaHOL4nUOlqmruK/l3onPldDd11467qO98672mTjm9LY4t7qeamNQuAHGDFxov3dkCCEoH9V8CVjfTiCBXC85+edhXeSAWq8J4n5DS2Xba20M2uqyG2EMszsTtzcOrpMrbxo4zblE5A9HOGjSwvoBnGL98lXByKnVHhSOneWSBKu6KcwQGom/bD3wbnArfHJyZsDB/wJq3TvxlA42LFNrZs0qhr2gFBhye5KFcd2gVa9fdwpsseVV4BXyKf2aoR4PWstTyksOm9XSdB3ZzNmyHvLxxXr5zi9aD0n7LXW/+ZlaX5npkW19ZmV0R3/8a5MyU/KOPiuLxrVASYPPuP4u8uad3/aMHFXfeYM9KwXTKzEgMgnupfcmsYvxgxQs2Jr2bBrxgCJY14tnM0mL4G7vlVUKpqwBJR+jnEPGjBpIjkY3+UtrFxaQ0jTrTlPE0XiZpKNGeRN+kxmxBf4pTcRyf4ox7+cJhPVZgtInvUFqmf3/jYB/FwjcJx6bj8UWSA1k5ShG7YnUxOky4q7pFnUl3CttisE+XbjzcEv51aPdKRdyr+qBbHe6A1wdjPN23CsAic5mnqUDW7jiT4ttXA+O5+s86l9+k7B24PCsVLH5oRpQztqu9PpMLXViyiDeE2E1jDLABu3fwwqCuLELA3iCG3md0DwGygxmfB1sFnsj6eAj/M3Fap15oYpKDL4frhqosxdS29DwwtAR3UWjXou0QXmdrH/fDcgiLoyG7Di7c7zqtfSJOGavgS0cY1iKGlCEsvCqIdSeu1SA5FnahMp5Q5S1Q2J5nuPmHOQg5RErgxox/2oQ5EU9V5DiXCO0vGUSttT+C0FLAiBlJDHl8/QytYWPCtSYAbVnsXVaEMBhPYcPC0/pbSuBUF9WUbz1A3e4+mtgfJp9hsOmWXtKeRi7CbxHuMnjrkVUiaGKg2T1quCpZRZ9eCvuZOaestY/DFdH3z34DYaAy8kyAl781guAVsECUDslLb/MEQvDuldd36HIt/85NeOLz5zDZC4B6CRCxGA8jpk7NT5jTz/eOTtgex01z8SuJP+y1tzEma2zL2Uebct3i8DiUta8B6mXw8DuTE0OzJ+BOGlLNAQQbvmCiltoegyFm6yJuhTMVfVeWJ6UDORR5mYV6X0EVggUDgCWQ+by5AQu9ltCxBTNFbGfMvrFx/qnETE6sUmGtxypz+byDFfaBQfy+gD6w0qtiQ2+NVw9qZHUyOcfOEcgG39TCqkDnndrTNs6kyq5wdswSWSx6eSHkbjPcTVg5EWjJy26zhIrtW5BNktdOCcl0OJ/LdlIT7C5x3E7/Wwhndo7JmmZKQkCtd+ROg+3ikiZtOxeiQ6gspISnTfZ2xI/ZFBGrZWm7L5Br6Iw1mOYy+SiT74eDCNdRUi3qofbrM3uJTSaiWmH2YGmr7wjVA4FxlDmj1BvY/JAreb8Pp7mhhymNs3cGoKiTQkyQ3vAHt+Gtl5qiIJDWVOMGd3RxOcWp1+Betq2+SXwGVsFqGWImiUHmit1EjtjFBT2fxpZZRvaSD+BLAA4rnnpGB12lFiedY7EBb8JiHuXT7p+xvIEKGa79gpFrRHCv+06+T7FZ/4tZ9MP+LQwLN74eWhuXVHQzAlBkrbUz7aM/IunpmqL6bRRS5vIC83ux1F0CAfyFivgQ7W8SVvUa6SRznzZIcOuP3QE2WF7LuSRlW5/DrXst+Qgmr3LBLQQ7w+Bgu5JQDSjxYHtBizA3cEuwkme822wtkejGOyZSLXHpr5KopDlrKD+1t90R02ROEl2DvRL7Sex7phWmxzZQqYrx3qWrdgtgHeyrYdzduVk1RJEYtP4xzDQz0B46d82TdmDVppxlha6tywTXkTeSCHZtSxQl96DpB8GoeGl3bZ8ugmmT0R/bZC9Chm1nVCwfJQd3pjEqoK49W1YkSPPL4j+U+EG+3Jg9J+Z/qGbhh7MNImdm0wpJH3zD3ET9V+gu9af2kEr1IY2xDQXM//X0oHSSAGeduF337QvGD3laKNAmsQ66X5QLWq5PI8etpO9M59SssrxTtAq6+djJTW/U3WIv6ixvBrQ5TWEmdVI9PMutfUcmxSepV/+lCxSLYwpvkh+WsxXEdhAaaeXEslMzFBXj5/QGewWU0ooHdFzIGvDHfWhzPPFgJw60srvVrdn3hAlGrvpByfn9cqlaNdAakNo+ZlO2UTNcye1OJ+7eYkGTuJPm6L2sz24cU43ct4UzTTG/4pnZR5UkzBE9BX8lF4AHlkats+UCWehs7OyaOj0pmCXggyuCRwqtLevDIOd2JBYL2SUoB6XNy8/PdEJbKFgdYmr/NBHgJ/z5Z13GHqsYC3LCXlXDsY5+tp+IGlzaIGmGmITat+acHduVsYrFUqj3vDKbnutqUJVScKZvlztLjzVQwqKmTxmLZfEm8PHpdUFAtPObmXMZwCNRpRfJRYagNq8pvQJI63qXWglmad43M6I88EKI2aL+NywbMX4F0Cepr2oKgnuFaGMdgAFnRUGM2SdQpl92kg1gdhSCaNnEZOhgWA9E9o3ZUT/jxCbA/8NcZVZDFvM7oEqss5iaqvbI1g7jyeTqQ4cAHtwMOYhNx5PBDh5mt2yMQQ8MXGQsh94uY2iabtAW4UZDKSpyf9Z12wDJnjiSN2M1PsvtU+MXNqVV8o4vlmgZjbkEoow0/clwezog8FLHroxGDFNaxt1nvf8NocbL86e7qpuub6Q7TGTMeDtxkFSM/BGSCQWchrr3G3uCpEORC6r6QHHFV1L+GLUq/oiqKFC/vYMXH5e2EL73fp4odGSb5FNGfRWb7uat+UTusbKisiQ3Y2PF9Rqx2/BWYKyMNvWWI6QHl1rLfZzU4XjY5N6Xcm+Kf92qxgIVfz4IgQ8Mb4PGQBrdXht06iESJhjpg5tUPwPbQ7rMI5z6cYcUkiP/9ECJ3vP0z5WajKu1UmnoUu5YHkjhUmEguwQv7EHnshhCNB8JJtvoj/bgAxxuSlEMwio16IVT+6BoQTjQId9UFpg8YOR4JskNwc/0ux/htq2VPJ0N1CA/tsXiltz1L6msGtY/vZ01FWXzqYEI7S/ACb7xus1cRHWVAgMNplkpU8TTQaac5yiMxtl1fqgwjKpkZKsOYWsHwPc5lznhFzStLjz98WJgu0VoFVxDx+ZMN1njhJLyLhbRoUjGgKBVSYJkqEuaMwyfqwQzh1ldYERl0hk+ZPxn9pqMvtbH6jbAucPP6f+oftTHIVNvBaEXNrizHXfguLUfQ13xDJX7J2TVbwH85fs/kzS71KsVGwoqhF3SCbcYMagRq+liAUSSTpmjEdE2WrQsioSDEcBe34jnQKTexK+w8h5yJ2Em8zb0PAaepE3mz1jIDIYS9tdEb/imsh6/Lj96B4vaYt7t060eDIDfwuD8ugUptT8YvdHrRiCYIQeHLRrn7AljXu8uPUH33EHHDbnODCQaTzbJihWOx6woDCU7v4RLbUa3TbGE+B9BN70afZbgjNxF8sakfu8UprzWjGoo+VmLVEdSMidcXJs5OWQ/tLH4YqI4XuM6aPcrZES2luMEL6vfP/d1ZXGgijD8A0VaOSvQLqv/HfE5i5eRDI5/PvHf0JBTvSFbaVKKm26mnV2J6tQ/GfZ6N1Wqk6dbQfRS4alk12AaeccqtYH61/GWgm0LQNBvG56YWXT/ZPp5l9QUwThzOrMGYzPbOy0Jh7QU3TgB7O4kDd4LYbDxsrS2tjFSIVw/TR84TihpJ9/SOAOICqYaO7EXf7AXz/RdQtEOvS1thSEfWAnLoxHaQVdZqyRdKxB2uFCPbJX8W63yQJnUA2aEMazmLuqSGNt8yU8RSfTtEVg+qHpk9/MtOqbnHWYXUrKP/QQkbm3UkN6ZbltWfRmAy/g/oaB7pCD/cCrLPhi+6wTGh6/0iHhg6NcvDfFsB6S9WqAoezZlwuNJPWsy1hwrxN2LGeRFYtcpQhU4ashOURjNpcp/Fk33tPCUk95FS8cCq4lpE1zckBSVypkxX0Kyqb42w+cJknh0JdHzDDFaSKbrvw9rOLIEBudL7iidsljuwakH1zOZaoZb70C/rVsFD73Ly8K0krhQORI4SSaDFXTjPeJK5N+V76EIkruezAjoGPUEZagHwIknCVcKKPcomIyQNxq9Nu0Xu64r/uaVV0bEe9I68PooJNCFhLdlnmyO9J0Ta7DBpnN4wSPLW47LvzrUwT0SC91CYNghlUl+/LguoUqhCzL+zR6YUmk3riB6RTqLhxC6ULZakm0sIhRCpfe1haX7dlvpbLrK6JVeAE9qGchHdx0mlODRDtyJKSBjcgGqME0XuVb+UG/ObYoByeU6WkxhkWT9TPVoKdTfVsFXG9qaysp7wG+22wcExIKvrZ8OKWhZfA3oqqTiEljdJLafzqpY1pd36TEnggsDaSM6HNpiwhV2AsjZ5rJ7ZZgWxiuPxf5hlB9YFemMSXO0Js3nZ/JAGove1lHXTD4FvHcBydqKwhJML167x5Qis0POs35jTpFEGtGl4KHa/44TCA8u2qSL5i0vJh2mVVwLpdcfikkAwz1etwfll93B94qbHbYQ8OS5bMsTHEs7NyIoQ2V8Lvgtxt6RmR+2Fi5g7ogitfwwgJ+HWxp/zK97TtaVqMzH3FAjrqBI/K4c3lwlzCp3bCwwEIhG4tdrgAPEWPVIe63qyxKCIDdag51oCqpzJBpu/ij5IqgAzNINnVACg0IBTN3EEGGXOvWkA1BvjEAOvEcpEP1fEloVcSKoJPTkUvfVqzJ/3PjR5JKWol7RP1A8xYhpx6Nd84lXcA1YQbE+Qp3gBDPW3qx6KEY9rcPAbkTRF52y1tLmjK2B9ziBAWtpYA1ul4Bgu7LqhhuwJV16hHxj6mutYZyhb5IYjSw6Snlldpg5ZUIHveqM5eaHsAhHu5UWIkJL6qkqp3PNG2JnVwn5T0ABp6m6yJxblf7Kp2jwJ5+Op90/ELmYXIVop4XDxvruj3gzrB7dr/MthjcFgeFBEIjxC4fzpmc8xEbZ/ACvOxr3e00ZK/7vzlbj/DIVXvOzbya8QRT7oXHTvHnX6ksP1n2ztNUpM/eHMd2EUZjqoiBqZvvnBJ1OR4ZBGz3lW6UkEzBRFz81bgDZenh9J7vK4uGaNK3GQrvj8T7QYo4v+nXwNr5AI4qFpmEX9tBAeW8KuZF4Hmf55TLkbRaAj7ZMaXkNIzt4WkIk/nQlDEUIUu1OOaT6tqMVnIuKyx7lWAo3DNgAw+AXZ4Y5osbILWUq3TovGFIDTU+sglqD9e6l4b/fhfNTKvH7XvTYZoHiPXkPQ/Q+Qch2g+hikEo9UfSzY6gDv7CxHe1yYuPkPESLHKPY0wX10BtcIu/8wyJwzZmSBrjXC7HILWHwUpLwSDsWBt0gPJ+Oep5R8rEnn1lXEjFCcbuynQOkM7YMutu1ICAwfCtAjcpyc3fAIfvtA9RAWVz+98XusyN/p6/Mwg/+W7V0nccQ/I0Edix2FHRy95oIyH6bzArX0aT5ztUMXt2uDO8dXbK6FcMb2dzdVm50fNqzWvh1wwhWq1ukJLKMn6MXmtdPOPi6RueJ8fN0BHaKqPzAFE0NA8m4sNj7ovZHkZo2aXR+PmtlmUV1jWnil/XotI0HTZsA5v2nYU9s89nYvjpDByaJ5RbkjmOfkPa0WmqOeir/ywDCBcg7KgG4DgVdcXfFfid6AIRcQBpmzUb3y/97IqAZdN6nvHbrDljBNSf8PeWqJiuYARHSlp6iJcWVlA5tesrRaryp7Pljty/UrAdpCy5aGq/yD4O4s2JcGe95XOGmfhv+8C/HH9RrJPAhnWqJiOEz6lx/Qb3GTuXXEMeT8YXNDDoNVt2Mah1YsglguWjt7yXo6su3Opn4CY7elim1ptXYoXu0tQ0TfpGdM09iD/qDjNOo/fPOZ0LHU/MpSfJnrbNNK9qhINOZ9XbXmYg1dnGB+ZDjORdKNzMTHsQfAf9Opwd/EmNF5Xe9RUWDlKa+DxNH16b/kXaOVDjOgVuOEFPH3u/hc4OxlmEdFPXRwIbbK+cH1JkgSy/dCR+FLDQaFR2DnVq4EMcbj/EP7IwjlXlz40rlAdSFYmyuuoaTzsFnPixY8RwgQwn7WC6IQPyzQM7XMhol7oc8dvUREtnuvcCMPUodmnE45rFbUA9jgV+O74GZR6O8fqyGx0wVGvLmhzvyTwjkj2KUyHQRCpok+p5Xwt3f9dAckvhEfvERQXM2wwt1ogk3KLaGmEU0m7O7pPstUbGku0NHFrr4UElmTcQ6xoJy/Sn1FhOEQbrj/6KlpahrNlVkgdLr5xEeyMEYN+U+VVcToT2KqKnQ+XDD+Ca4Xx9ocDu4ftSGaJxTNW6sXrAQUDmX5iy8m1lHZo5E/IarmKd/dmYGa6cxwb9Fbr5Bsi7Ltkkdya0y0sBUUsYPwHwpEIs/NM8OsB3ugdQyDSoph8By4L2TDOQ66LCt4RWziZZPAQ2pdWLDpLOUFcqjCxDLSE7gcQLw7Ml/WqJDeHozExwqPlikwA6ZBBpp3LtMZ9gfrnYk8rRUAFJE2N0iW76lavzw/oEG9RuSn8fNUsgDnt8DSAvZ6e0SLVWlMak9H7rIV6fYq162nW0SMc340PlhvKcI7RO1WVGky1QIaPW3dWvM/fKtSMtpShGzzHZKM1Zt1UEcwLwZn+UiF3vZh/HIzJbWY/Rfu+dUz5nCa/Z8MGxmbaLmw8bsALtzchPDyKBivTNZeaFC0ow/fAPmzi4Ug6xy3iULQxoQHhiWLns4KwqfCLvm+mJgC0S2eXLlniIt/bxuyHKMfbmzBCeeTRvlrRRfTjvQfg/wFemk0Lhu9I6KBteJKOSrcUKwV0CMlpynnLlfQHn+kvUKGFsVevjFrEfWlYX8JNi4ifWCaSP9VaxoU+54sE3tFE6BNHJU6B3Rc7ZoM6jaHG+99AGT2s9YZJ+mLISiywAsQCnk1N27MKojmOGpYVz4ZqtMbySQUU9BoVMoMHEHw5iB8c/Arl1pXixUPKo2swJ0to9g6PnW1J7a/so08paKE4rNJ367Uzr8oV5zRWqdDefxYkNT22D8jWfSzNuZp2879iKVoOjVBN9T9jqj+Lnp2qw/Vic3XmYlcXXBBtf+Va6nsNN3wltm/Si8zEReYRddnr+s5FbF4je4xWYyYMLIzEQYYSgk/0R/pPqnC1ByPBqiUJcWSYKIP+GxnqySfTMuugYNViB+lVe/LJYpm4XDQii+uzqPHuHuxQs4NM6ZKw59WLZauD/h2+PF+/mCnRJRLGJTeNmrZym+XN9k/ljwAogfvo7l/RMcPB6k8pxATO7e39yZCPTMV3uBVtfnqQqOa6nj7wRmIRH0yk+BCEYRU8JfocItc5GZXlsZAEoAsOxg3xbV0oFrNmtqyjZpUpuBoSe96ErcGeCN4l9wZrgSbf/cDXOOjtN8EVSKe21Is5VhbhOPiHaNi49X1GxVVtSCB6Y3hoY8WLYK4pf7LueEunQV4Y54AdojBifCzq7On0UYy0ij2Fcu3+M7XUzsqRs6rSJICB2TnEebjhbD9LpBtk0tr3kM5KKFf2nCyitSCSOaQpk3JfNKEVGcX3EJQl7SZb/wzjRFrwG2miZxLVpuNBvVHZdkdpbbMEwlhuczV2mHyjzTmTK0T4XIYADTM2G1/7v0g/RtNIWuAvYGRnDz5DYgGqF2C6NbPKA4LK5uG7l0LnyXWVRPVDdwv7vksr3YC1EjPXIVkjD9ycZrtKiUU5ujMgdQZkDrjesT9nQoL4TVLpeY4SpFMp0wznhR/4oHRtj9MX57rJRuGAp/Vlgng+3opm1nfhBVjdo7WXCeif1Bvai900XlCQYyoWYZe/ZWAYXGQySaTEbtV2ltKktifqQQDLWn+CNprKEkITXqeHkd6QNGuixWXqmJ5qLg3qWNbPBDxZguJ4z+LgCNxVYQYmAbTM4nKhmsmKrJKA5hl/mbJY0jEK3hrdNFjMgeJR6tMj14C6P7gsXe7DmOtnlacaoLW7xUGiQDgflJKxuDJhroao//plfaPQadBNx4lFO+J3ilRl9xyH6fsUN9WAYg4gxscXWOkHJ/dXffmtvq1ShgtNY4HQDfYQ/Fxh60oamLXGX5aI+GkteYtZ6VZJsVfD1lztC/YU49YEw/5O9+hUtzQglh6adxwvF9ljQe/JftNuLXYPCohciZpw9HgTWV2O9qlbufrIVKHhyRynsQJz50FeFuAWIhl6t+pIt/nZOEXDOUHZ25W0tK+n+hE+eAZUXK6Rim77lXGLQK6hDqjmUWmsax7250wa/3TmyXA/X+UEDM/AIKOl38ckiEKfXGGz5UpyveB5fuPqN5051jMpbF4Ev8YACgaZDZNoegPgOTcB0dOCcYCUsfQLLYPEPOq5u1clPKRbUCNONNp/v94ZAzNWCzmq7/EwzO8PhLdfFD6AZ9iqu05WMUwljOw5dWvLrkOCUb1MQKnz7N6qDvrj7lDDK0dlDaitM3ZeoGETYt3DqJHTxNgpVf2srdNQE9rJ4NmTDr+tVRuAJZdrHqU1mkrwQZKAgR4CmS2PgXazu0pTt1eG4CxTuJkWQeGh40Cw093bk4zM5Tj50ZDgQ7jBgUyfg+dQe/bqiHlm1V/TjPpy7nlXX8rmN509uER2JaPlHkaAZMLrQ1W8XdxHIsVnU+L87PCoa53mcXXEsM2/25W9LHeE57ZE8NMnOjGezctEhbPrWdryfcrrKCgaIBY1AuEQXit7qYWIEaIn5fWOSHJLwRQu7mB8jKh9axfIJCBbhsH1jlZbMSCLSzhfj+E7K5ThwTTMIhe1xNvBfVDE+Bqgp23A61C0jNl2mv7z5gjSVZonVikcNT3pfm1D9HLEmwOz8KOi0uQJc6mIzrd7q3T8Tmh/9rWDSz2Ta3Jgk5MshF9V6RZG2YHN/SU5r5cTf8rCF3kKKIgFIIC0LSCOcVkzWuk6dcKVPUiJZMnHrUBcrcD7UUBdFKiUWfzTieuBQfuI1NmiE3KWuuE8DgeXHjXX2OxCJQo3wMQIODmqFvPd6SrbMlOE0XudzWJ0iRxv+njM8nLzgB7RW1qWNjLINmnRsXsWPqFCWWSLV0GBu9Ji+7q8qQkwhqMg0BhQUkFvvZhN+RxmL+sZLLirRrQQHQ8UDK3MLxFxvX0D5NSGCrczVSuvxU8BAVFYbEBO81b01wMYsSyK1T9UbPnAQImBWajfZ8n6fLD95dDuPepbRXr8d3iwl96dxbufs+6SZreiX5AaLsiGddBm/7oRo5JM2NA1lZehAjuzXEULAXZalN7zagjWxDqBcpCLf/dq6kZ/mLjHKBIXjWfV7Pop8bvxg7rVDP7F3fIuJFl2rOV6T/dftQxTYgb8SburxI7kipbud159KlgmtioRByhhAYNoPwJyM2vZ1qggLgV3fB9mebC74+zy/WT9smC5lwrWUru07WYSW++dDajxs9wPo5JXJdNpk+pFYs5OuwUrYjrwzp9YWL2mlgC0/Jb0cwCIWYO7q12KZ/qEfNjx8A5nqkACIY5Gg+LOmk09qJAfmlb6h4ZakMCh2nolxCDE8SaO0bTVCZZRwkViHYbpEyYfNfEgt8JP+ajH5XsBMbwlktqh/6IO3g/0AjYwrMIwZTPjtSElANih92QI8vu5jxcbfQCaMKECfH6NOGYBWp58+hzO9rGCxN0WRRStus92q5LVnY7TLWqUP7MNFT1XUtfWi9GPz3jwjcJW9WfkgwTJnrhb8fJvuoLOJbRdiL5qurWiWro8gJ/ax8pipeH7EQTvpIuQMWJaR8K3LOJux6GPTaOcDnmoQF3DQ4WoSYEY73nvRh1Q1jO5vu1z9kH/PBAZLvYZc4czMON+WBdttfk/dAUx3ZkN0fZOOyrbnKdcc91DTn0vJ8JeKHVSyUhGPm2HZeYtuUBB8sApWxJmLkrPuGgQBFOxdecFCLPp0DC+XjsGM+CVQZl8zwsUljCa8esedjG6pcmbNL8cDukRgFhQq/LbcdumKH5FiIVxT1D6LvnQfEFkHBRYLwxtyxY083YhOoSx41/+aUbwVnb2VME7JdjqoxJ6URgGbmK8OWfQMw7sPApWIb0O57H0TaRXLmNZXgI2m8q2xuPiXOU95eKRNBYBKBZAxgMMm86/pkyG2cpebg7t9PtvaKD4Hw9aUT5gKpGiLZLV6wvZYQghpUgpumbeLmTYCGfMskv5qOdtHZVlFyLtjxN5I7KCpQZgP3BHrU9p7xEWJUnAMAiK+jQpDuf488UyBNvCvs6nX2jyb5XQGMtjgJnbo6oYaVrr/dI/iX7Q7sSUotPpW/hpmitV3aOOIHReYq3rupDd4Wm+22X9ZcPaM4a3uv1rOdlcbvNq/ubkn0newgX1VRt/g5h0+Chj1L7zD88ikWvCGdukYMx0wx1NKrWF//18bJxF7NaGi1Diy9qpL7yNDgg3kMrqR6PG/YZ28zJ8xFtQIGtejN1o33M70t2+bYpAuQcwIX5VSERB3rvwvZy78GE1Gqjlh6wqxvzwQGEKfB5N4bTLadOf2YarkAQJO7x5+4awEkl46e+jg4S8D124ukD+xC3FpfzvkvZmfsfNHZiXCGP0epfE+aPgg7MMdV65Jz/CYjH2RmxM3Oc32BOEHO9Vv8jvR8s7CD4hR3YJk76ki7v4FmFTh7DYpmRSHu9x8SELM7Gp2et0fqxUMgfdQAIqOe8daC4K8UGEXlbetNIgVX+q/atA9Yl8rWREOJohrX/98wO2XpLr+EHUEJnQYIndjSSEpWEdF/WP/SkL5+MZCr8AlGuButqWRVRcgAOpe9CszwTLeyQvAq5Xq9UsKzhixm+vxuW/BJEnZFWoGCU4BplM2PHSpWq0z/jSQ34m9DQbX9h5zx94nkHU2gqnniZWOpeJaKsOZJN48u8dOPllUgp/KAywyR45cjCf8oSgU434HGsBj/QlcEc/Fw57BrWu2rlQ5Kl+xDeuShgH4G0CxefTg8JjWKspV36t/vSIwGqNaQkxQieSHbjqcef4+Zt4hib87aAlvzgYmlffNK4LkqJUnE/nrkTaYBdWC4/ZoelGIgXjUvvWCV6JqhCPtCMQGQbxHa2+2+aBDb4S0rClGWurusZrFeiOPv1+it6qU2mHmooc/XwSaDiWb8bSWgvwRkx8P9dRu5212IPWn5M2f3bqW2z6DEc+ndZpe8EQC1cF6RuUGbI7d8V+8gX1FpBf4pbdfYTillPkoc6gnS2XbH+4Z2R0EEgniR8dyVU5iZxwoq8GcN66LZT5HYkRv4kqivdFbtlveo8aMvqzNc2SDvofMweHxQ2xApb0mjidWp1YI59Oif2+iwYXGtrZVy+Ti6UVaNuulxT7xEkVhjN5ry6X6xAn+HAtgRdn0oqAcSast3FcVCVCcCF1v8cQgntYHfjLKFCROfsNbnPTc5rmL6gdKM/dj/MvytFKk59vjo2CTSdRUY2krRPQppAyGhw8EZUKDB4IAir1njSm9H0V72eunJcTsB92Jue/q5nTNw9L+CeMF07L02x0oSRGAwCl+g0xVvMbAFiM6YNhuhVD27fHiafvFztiuWtQKNeYsi704y6k1Mzhdg+a1E82OhoUTQ7dAl7DWN6LqLhnlv9wJguQirZ2hfaaR73qfYbgcmvYKhnAjSbwd3SaLHkXhHA0AtVhjlGk+0ZZZ/TkMd5S8cHjmC7NtIer1KF0J8KEHWlXbDowLR14FuBSgclqWLPI3ON1CKc6C5uqDIW5VJSu67rHZXVITFIAifVwJgmRYDOWemal8E5DwY/4/BBKzzTgVy0N+dE8BPkHueHChvo3TYJjBwRwK6/A5c+u4Biavfk0TApG8io9uo3dsziQInVyJ+p+vW07+q8+xXx793xZSzBkfb3LEp5fxr32NQ15zj2BbUfry1hXVmlLut0gHZmp0kl0/7h01LOyGhUWwSnNX52O1VgT4ivBXRqsMCttEw4+ZXlJ/liVyaubfDLkOfcrX+ACcpp2aGHfmA4TTm0Bk/66ewKbn1S7pSMy9AVcaI4Z3q8udRy+Aoy9Y0JwiRclXPkdC940fo3p/aXiZG0DUVZgGhP+BtWxgkjjUu3xwI8ddXHqV6YHBAvNOp36FiwPGjeUdDgM/Jr6NBdeH7f7BdICbI0RiQqUfmnLj3cQPqe/q0VNjQhgYrd1NBBQ0Y3krpWDLWOE4+7O9SHYyOqAnybAbe4tL24WfIbWn++gxysoHz+z+HT8wp3Iw8su1uy2N+6wgiRUmoisFM0S+Cm1F9JTs0EBqPlNDxUqEyq7asWXYNbftWowE21fz1EN18GBl4SPu4k9+7/nh0AQPa/4c06w0kEpYN6F3viPzjzZ71QP9GBWsNBGnEQFk+v5NSJwgfYWeQ71374ezDZRm2V8UMSIuuV0+PrslYA8QcqjVyGHZuCHGmBoEuw7Fm8AT8WAM/DGGG6vZDn8tg+KgK30+cmRH2pF2Unlsm5XQULLIVVfL0HL73U33OSrBs2sNx4wDXzS+JaUdkMiIt5HkKuzakzFRZswFY3/ltYHwUKceS8Pl9xrBRBPnPe0T8IcV4rARmwYc/P4S2NdQDivHCkcOjPwiokjsU3O7AUSLhz4gOmL/PY68LriPPwNUl8emWtZvn5xyTAD7QusQllg5+p6tSnhv0kGc3ZrGdW0BpjSjWovxoHBwgqF2eOHmBSooK+wZq4w3qVD0XtqmNR7lE5xdvNDeX7Q15eUOCqj0wJ7vMmZMIUnnjsd3ZvuUNqVRlAXqkf79t+mrk5zoK6ZaqCeto4k6W3sBbLq3P9gR/YfAdkpY+ZCMuWagRnAtbbqWqAUlfIypZiFY8QfAcmLkfGk1lZWNPBif28FnEQoT8bz1u95WTNXdoKzlNKALCX3cHjafWXK4zG1hHmnSPEACJvqbNV7i+v7DGQkvEWkUuYkdjc0nWUN8m0gBQ4WGdY6tlO1IjVyU7+m9CIMxl75uDWuTBPleLP14kcaF4rPfInw0Ls2gytgZ3H7V2nLHraCKYo+4JVkBs7Thjg/OOPrXcDaf+9O3EQV8ZV/NkJVKORsB9BACkafuzpjkq9k7nboDVHBzXvEwIFujTEy52ZMZuDJZWM70J6nVJt1YqVCy1NFkFYyU0AUhbLHSU5xRrnaIIsifwkTEiTzVbL0aTEJYiE1TSGwt/Rdsaiowboe34+G3yUrsqtMPHBio0S2yli0P+lXHgBpJ5qNyRtmmXsSi45eeyXultbDwl+zrEOJRfpYPGtVWydSDi/iIVf+rWveXsAgoSijJfSU35LASsgiYRA35Qne4IceE34e3oS9/9Tb5QXRBzER4nIJHjFq5vaNW648S6yVIPMSA8pfQThTC3xl3fVLuSklUIFdpxUb2Vyz0wODSV1fYAVWJOSt6iD1wQ70wYmmm2pO1zVV+kjOy4CUoPnBHkD8sVABGe7s2Iup3rI0fyQOgHYQ82G7CABt5NLQFqdQwyZ/s+iRMoZc2QgiVJ3wZYrA/QqtQ86GT7sdr3LN2WqYMpMhxXT3IljWTD06DuIYxmOFhk2/koBgw4pFbQhM+3J/FAzkQqIlUgg07GqlIBRFOiIqkFl1H1FOmz/8vY2/tbENgDZYG3rGmEI4UqW9WHeTukRMRWDWutxuiutnK7fQRbHfmUwBFd+J3yGA7yayUgHFlKh0tiYAi+8aLGbkfXKco6Oc5vVk+u/mpZ4+C/yHjNRLvsohkdoGCOH9X7X5SyRpbzYm5QddQuQDcmvHB+u8F+iUF5wFdipBo1BV4WUjqK7yJ2Us473AP/Rfwe5FE9HcN9tjF2t1Tjt9WtoO6bUSp9wyPq65gfUURJIeGvE2rHYYKIiKh1zYIlZk3iQhO+97g/C54BhkKh5WurBCrr4vq0lbWQUy9MrI3CzYYoHcDjLdLeaYY458b6tJUilWoZHcL+FpCPs3RHqdr0FTQH34SPxWY3aIx8ZPMAIm3j5KTYSwO6bU9dBrHSkFl9s/e7Q2StqiAy5TPwkYjTNhpL6QLfVIqwSCq7aIaVEHNyFdX7tfGB6WaVD91KCMENFogU3xXgERceJUijXXuaPxAcikK3/0udmYf/eseOAwixELD0yuhL9aHUOI1gkF53fAkIOQQefRvvzzxVGiPN3Jy24P7YyQ89EtTVihxWF8hMtjyatlOQEqzx8YJm5j5yv6f9OCTVudG6qpmcmbwLkGU4nUnLy3Q9n1IWZwFzIyX60pMHzrdcb+vC0yhWzApglmVi0uSDKviHCNVajjPAE59qAnYg2AKz2cgXoXPbGlzzyCSOASaoSLtXNnZjMQTc2S+C127Xm7w2UY7u0ug1yVxgdc1Q3asjjD3CetFENtWNmwbLxv2Z9quorzWPWrL3zz3OA9iV4kJ66S2WWlL70qqSnBaW1NYG5TXMXnJ1XkRWtitCvEXIlA4sMCfu770sB4YApiqjR6yHez32G58lI9tDkU9HPOw4tkSZ+hzMfHlKEjK5+hK4eRUyBPUiJppNsDeATGZabpkq5gBlSYt2r9DQAoHfk8PVXT/ZDmrXXmEOtCE+Ph5ZS3K4JvIngclSLr7XQxqDlfHuZIlGca2qaXmXNrY8OiK/ZmMeLbdLBXVLewWaQ33eoEpsNjD+2RewzdmRXwbc4hNUe+kQSZEjlTlQIExmUqDgAAvnDy3V6l5WYSBI9cUqhVzIGVIfE/RQ+JDWjOtRthIbU9L5LloBq4RXzb3JGKVvEMZLjhWgB5HhYY1CnBZqYZiF7EKLyP4x3/j1LtlSY0FOoZoV2pBw1vWYVkIBK4DVupdLiT3V/WlGnzJrpbpf0RQ5wxscktxOTKqX9c8WHWli2kO7Qw286lrFDNNSbG4rLq45TbTEvqmVGGLWCFEFp5YHQNVolfnEx9hI3wStevIaH+LYG0NYetxGaD62LfPzfwFinWphvhVDen1uRLKpJkOBHUMI9PY06gK04hgsKgwaAzySA2LUzr2eZ2iu0t9YpcrjxuqQyFTr/Kef8r/s9RjM6R2FRtievUCRCat73MPn3VX82/V6BENIOFuwmLXAEWbsgGYjQJFm3TutCv5UoFsbHxvENaGG+4q+OyOR+m8zPJeEYRXldh7eEaky+Vj7jDC8wCrffxRDTR7saIh6oP64+FtDI83Jtp9p7WAodBaWYmzlOohChkAHx4N0l7ydhjbqqxtAorZCPpAOK30zlnZqQkBNISwSwniFExsk18F42NLYkgFdQUyoyBfqK7tUQBfthY4req90SkMz+dCsnENivo8/YZ8lRdSQyW8onoL8H/rxY7l+gjVrSg6rQ44k1BXdReJbJEqfn2IUiKvqx5yNBpef/b6poXzdYWkJIIboxvA+DZpdm4Vn/wfRYhaAxckvepWKI+pi7Naw+ni6lkKFMwTht6poU5tBz40ldu8tIM01oQv0HkXstkD+5Li8QKNJWIKgDTLV1WbHJxtuwusS4Bh6L/7Hht7GzcXPHHuF8wbhklxUelRbL3HBvwyiw5+kAfVNRWI1hyjg/sTDtYYstj4DU+iMK/43x2mM5EbTlwjHIQn7buJydSLq0VTfEyGvJ9btO2XiDxNV6ZYCTtKxJ2I9axioXziBGAshbVJaGq9qBRTF6/ut4JOzbmjT69Rs4mGqg7mM2REy4OY0pZYA5JYzUVDJGJiosTxfEiAPW4z8cA2LtEI/3PZ0UaU356y8qyHmbQlf50AgbjhWbnqtn0jmQXJ8tsAUQIwNMx/FjJwXNC3sTOR5QkRpH/NAuKnYPCRFgg4Gt6kRDNs5W6SfspR38jwT6/TMsl2fhZVsjzOcsDMc2l/lnfnNU6pllxjtwxQLmTow/0vZ5YXyo1z3ir5LuAnKp4DEG5a8cpqZB6SyNDi62ATRcE+lkd7uh31zA7Br+5Jw1EUGTj/5M5QpULckP8lPZ0yD0DHBwYSlrgZuZnKn5R/Q8K0pf7pv1CmHamXONaOfFtFTwumWQpF+iBpz5yf02HXUMvYZYOi0UkxGm90W1uuzPoulU2l8GuyJLh2G4S9BS30648fR97d5zuTGFFZC6W3iHYhEIoi5++Pf9fQsdLjO3SiJNmwT6cqqqNJIapEOGn42iid6kVveJVnzaxtoStohjWeQVSLNdqvfzqKdxzwkYLj5BCKdHQcfdUxwjOUALVgvOC+OALxyiAC4cRzAJ1JJ+OYouJ+ir8cAtrYQ0IZQ8KKv9CYSUbjSNZUuiAiYbUgMhx4Uphmb9KThovz4D+A/aAJj/AQq3caT1s3SaOEQ9CsZBvDvRqv+3pMyWUrsYw1GsXtm97TGLw7lOqwINVQ1agu9iM5WTpKsxOlLCx958KX3+1CW1P/FYAENHGfh498G5sKs74Bplal3y3c2Reyfqwr96cxgVO7cLoIdrGP3CM/H815T8W7iBxrgQzilRLQgvIDueYxtSjqtj3MeKoufwVbW12VyNJem6mpT1Y0BRuZvDTWBQ32zmLAD88Z+P4YP6iL0wWplsMfcYZ0MiRkPW+gNTPQhae/6jlSnceHnAyutvI5/EefPSgE17T8VCK9+WzEDvK7sM5IA+085pi4dfKB+2zpEFlZ4W3q6jZIE4V5NrYLhMoPr/zYeA7eD3DoJF6ktNH3RBjJS7t3E5QZPJtJStSUXFakoBK0yBFMwIF8kERqCdnrrYs+JRDvxEaJXOlp+eFn1+StwAeRaetPyVoA2GFXW5S2A8gtzFSJBDefmgrSyFTBr/hUuLuND19YSgiwtznoSjzp3iKVzTmLadw82DZTZ2haKvNgqe/QGI5GXfz2M/jHca7hhY6Y8J66+m4UsSgWVCFwz2ApPm8hlBgu/O7Rjs3B1+yG6HQPQAwiD/IPHB2Mt2A4a2g1WqDoCmpRGH8DFh37KNfIvtP0V1n4Tt0WIVMNchfRoc0c6Q3TVT84CidPMA0Hh3odRZfJ1BVsz220DnSlpXjYn8TVdYOrjDonUJo/sZgdiE9rYFyb6kdGnrL57cMEN1xo+XMssN1NTj12/1G5ZYNVod85gnKdU6WcS4QaiphZBWyLa4VYdnEVI1LQyamDdIcasteR8SEAjFak5w/OWx+sYUseaUMfbHRw0d3n6WrvZeCG+F9ZWsqN/sKmh2N5boWqKqPNMTKHkEEu45yaxKL4+jlD8hE++/Vzot6fnSCWo7C/U3BjaiTs8NC+OLym1v37YvAORRBifdywfRruNfM7vM5KzKljgEthHgTbLXFbCOej2gtfcgUC8TUmaN8GlENYc+VRatqeT4bMFMB8dw0uohEIpXAYfxbrgl/pZMlWan8gyLJfiTGDlS9xeH0k44P88afbdcGvb8VaXyJiOYtAPoJIZ91XLkMzkeHWOwsNhSCvq6GFG7F4RFTeXPFXHR33dhF96G5khNLXShT0S9dEuxxMtwvWB+GpxV9AlB2r0ZYERuYutxJJ9Y4EPI583Vh0OqZGY3tbRM7JgINxOVR+OfMeqVsJyIOpeatUINdRBnOuN/kF9kAGqAFDhh0utK38ou4Lm7YOqpB87wHX2yDDE1g2BegIGvfVEkofR/9BGNy6qIwAFVclKYYlL/gyhWQ2XYzAZXeuA9D3+0nKAWWlRQP1CrcNCzslFwdhUFLfmqYruyBL2hp9wvbxe/b6sLrKjeVX3uqxm4+05nh35gG6aGjnsk03SDtZ5x7pweiTqMJIexi91VwcwEjHdePbfG82nP41FjUJg1/GocLAp6nkeI+IzgauDd9A0xQkwDYyseGg38GvTTin6S3rB5fkts9fBTs9wxyGnLyNWt2bohYFjgM51AM9obWKRBRnfyf9XsxjI/S8yxjKfsXoIijKYOMeNDyJvfAftn0thRF6NGa9ODQ9Pl0qzGJNMEB7/tRGlrU1nYEJnHch1et4ZgF9R+SoMuJoWbXMdXlPMdTfjji6f6ZlySZvCLsvR3UpMw+k0yAF/IMb5Eaeg4JIPENuSx8c4EovfcWVXEyuGV7TbirfpU3oAKidRGBlfjrst2CladThWq8wHHAqYi/idNH3ylBxzgECpii/i+xOy923uRUAcfo1IKDpgJRIBs1/SVsC1nzk55gHsLED+kFq3nLL6U9UjdsoOh9JYS/2n4J4RyUWbm9NKBM179G2eo8SLT9qurYxPe1KNEkfE4tc5LnW7JB2PoMwzqcBug+VYCpp2/BtFRPRq153uNdP38TD8two7X1Um+LtRveOguXOlTU1pnOYM/tD2B+weE3soNONoiC5WGdVkhm5o/0cQakwvfSswIaURp2cciR73EfRJm0csXT5gFKL6hZUeQUg8eXRCfPZhsNBipp9BDwrv/JBff/L7uYTenm2CAoWkNmsmC75V/i0Is/I2dpVSqtYV73V0u+rj65OuXlMimDGHr1RWrMIGcm28lvgiS8lhXrHYxbHBMJg3zm1mBa8hPm98njUQeeVSgY0rEfkzvcq+3plGEMnPcppWSBoUc/qNYUTVtLSy9FTrMB8vfns1VPGeEcgVSJeKq3r9G9oyJgt/oYv3PEVkRpqRGaHCNHRzuMKAsdctagK/a/GIqRbYBTSd0C8iq33pK8lgwJ/qRJpIarACktz+r0aObFMFwrT0vPSRydzjJexrQh/SLfl0P3cESGEiWXIZnJ9ESeDpbzzhYzD/3/vfxudHViBy9tQ9Z6hxACD8+h0zhy7XxlXDL7Pb7XYqLIgSm43hkESKdCznTlSR+JxZwO3/4b+S/RWkQcR2FRZ3Le0sOIsSfpSk4BXBAIL07S2zJjRcoBildAHUtTb+306g/1eVQJ9mmIXjzCycaXJCAhGQU6Is1Gj+4S3/M4YBu0x+dd01a5YEMIPOryXqYo8yH3Sp8PlhYRqWz4EtbUn3nkYhXRGPYN/WcXciLxj/EqLgE9c61oYWae9NUaK481ke6sHYbBCqubt9GvkBgfkAVxeSE5GopuigORW0QMbZWuIb14ATb3CH1iLtiR2N6ue9UJWMVf0VHssaPWvj7f403EnJ29C5QRigxM+4ESwKEmsshyHEHtqJ9svWtCqi7/LsUoSe6mx2KYCG5hntiCgCecNO4+qJdUfPMZO4y8Z/GplfBrFTvJK4Ea2dNLmKfIjrrH8H8xLmT5YGdgZjTFYTUxwxxIgbvZ7uz2zszYOXZtzy3UvEwq6uy8VzndeL7mfywz37cgMU/+GlFAaEx4sDQR1JD6w2UiJ+aXf/H/xt0Cd1m0HOZhQ/AWd5iQe3JiKYJ8dvKP5VGXhhvq5ZagDA63qGcoGBHGHpkzyxsNYuwYCowqb10GQ3pLgELQkWNaU7WMRT6DGRnAiN2l7+dje/GbR/rhnAmVNp6FHTE0bg9r7CdkTgDZLnJP721hi67wC2dCw0/ncoZcfLF7JqHuGdjv8plsN3dMlPBGGQlOSo3hjMI2A1B3FJ2G5rq0dJ5FwVewKoRcISX2w1FbYf3uRbrI9rYVOeMiVkHcK2uPFNOVPJkJxmkhViPLbz4fIptiv93a16NQh9oUQWTnGjzS2yeDWTjXKqE19pFwPad8h1+SpvOvqOBq1cTM0CH6V6R0fgaoaFooS+XHp/6aZIL7tRU6QucqC036fTqPn79PtCpYHfQ7wEu3KtBWXstpvXTiKXnf7RWrqpZDmtQ9ZCP7J+F368eBuX6JerduD0VEPtWZXzlVL753prlcvROvBhGfRC2FEL8xhi8ObobCS9kAnTLqBq+kxT10H1158SbvW90EAkE/I+2kFok2JcSDuLJlWJuy9fOz2fPUIEzkRq/BUCXQKoc7SGe38Shum0HOf4qYq0IAnI14KEIFR4+8MJDCewWeLbYEiCjArZBLYcba8Csw0pJOKZmWA6QeQKHk4OFSl9vVraA22b6JP+AyPJQKlVjho7NPAon0sMNi4jR5p+5JxXk6jCX+BQTHYH/Zta766u7Mp/t5pVo3NbsyEQNrXhtyN3FaVT8M+pD+tcDW3076qCwMJV+acPSQtb7WzsU1MHHyPYszXfdNtOcvAkozjEulKnXSYojb/tK2tLXkWeIMIN6kTrD9aWEL9Muau+m7BDoTVafzj8RoaM5w8rIFv8qc+PAY9EOxX9Bqs6k47NlynRwgZW4WobWhovs+ILt0UBmKAuTqgDNh1fzC+U0vsNm8prCEd+3Hl4DWOYLpZmwVB22A/YkTzU72T7A3BkFAxY9ipANs2lZX0uJXF9hym5alc0q/fJyJ4tAFoBJdqz8l1efwZMyLLMti/Eq6TlfR4uvTfuCKvpMDfYF+/0W2ZZi3k5nuIxeZkgAz9NWE4phjoGdPHjXVWPBtO5mhTC7mnIGPS/h0E/nlD30gts/rgLAbdLZlBvmJKJ8bkPBdn97HGC3YiGqQluO+zCPLH+ehi/V0Jix/nVO+okrMRLtR3kYuuCwlN8+bOGae6DWHo5VZhLzYHzc5EBL7Pamyt6UPjgAcOuclmIv2JBfo6h5UGRKsF2mXbVx67btqVBLd/JK8c/sKJzM0/5bHrhPLT5ILmmeZB0QP4D9oegX8KL4fH0YthOd0oEK9lIN7Ip62Yb2wLq4LWCZUTuaIO9u3CZ03wxqSlybijOGdQDp59MqJWRtjPtq0/7UnlguuBCXuDTmlCY+0of3avFvehcZRALSgM0VL+NG/Y3QqUv8ydCyUZF+TFodTsUv6x5RnCJbg6lI0tVOrlpJjC7XO1zaiwxU0dnRDk2nGB+bh0PTKYcv78it0B1DcK2pL0atkgOLWTCVFF3bK5IWGBjCSFRRMDOhgqtLm/eiLN5Z8dcpayS0QqP8UbM5I3wb5I2GRgS2S1iKXpNiREidscs3zIZPbXd1yFtsmRDEo14gZEnoKwYwfprFhMA7bHbpRbmZT4p0gNcR0ws6K3Z8Q2Adc4xl0kS9kVnB+YotEbObiEBKDpbPY9TlwBAqSi4+m7nr95xXzBBAzuPtJofbCRGZmrgxRvo9bLzen2cS/Kv1NkCD4ZfhcxtbXI+vumeh3LekjXajczhZxPiHssrfz7h2D8YUDp1hAAKlzp9+zBf3JcAnqvtMlCHtEheFgNco7Wwer2yWHgscISn3n7LmwAc+7Fd5EJYFwHsA4vuNXw3Xrkx4aiRojLTl2NOBmfOKLtfmGtHricfNFwwUGZxaFLll4MQDfz7TFQSmggOdYmOLFZedAWAsRRPRCZ8y6UiCZLkxkH0tXcBEDsxgIOeZXjYdtree4hmkwPn3+Rq3mbe1j7We1nQvO/4d9Tdl6bHjRvZf7G2Z9+l0hBfuiHxW6ZD7O/mWDDepJ5EkXtqWdBDcvINpR68nSEtU9Wg58NyRzvvKMAqyfgf+vttt3B29r1oaJ5Qm/nT7wLmDJuUXRt/z2jz+4Z6u2xB8iWmqbO6MeNMBG1ZVdzvXN+xsL/DCAUy+4X4Op5LWQxD6Zpw13qVqAyzAxlvWDfuwgOoGxAPLPhdC0IE99Fzw1MCsWwPFxuz5SMUBX0hNaVQ32yGG5JGYpOjmgGNUR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T4fUA/K0cC3QWjo0THlaTA==
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- SEEDstudio | www.studioseed.net
- dga_3@hotmail.com
- Daniel Abalde
- www.studioseed.net
- 5
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28360
167
64
-
14000
28392
- 3
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- 2
- ac2bc2cb-70fb-4dd5-9c78-7e1ea97fe278
- 3e8ca6be-fda8-4aaf-b5c0-3c54c8bb7312
- Base surface, brep, mesh or curve
- true
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- Geometry
- Geometry
- true
- d636886e-6a7c-4eda-b4a4-ca364081a1e2
- 1
-
13897
28362
91
20
-
13942.5
28372
- Number of divisions in UV directions
Note * Only subdivided surfaces, breps, and curves
- 80f3a926-2bb6-4559-ab18-aa854690d208
- true
- Divisions
- Divisions
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- 0
-
13897
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91
20
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13942.5
28392
- 1
- 1
- {0}
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- False = Mean; True = Gaussian
Note * For surfaces and breps
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- Curvature type
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20
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13942.5
28412
- 1
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-
14012
28362
48
30
-
14036
28377
- Values of curvature
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- Values
- Values
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-
14012
28392
48
30
-
14036
28407
- 66d2a68e-2f1d-43d2-a53b-c6a4d17e627b
- Control Polygon
- Extract the nurbs control polygon of a curve.
- true
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- Control Polygon
-
13615
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98
44
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28173
- Curve to evaluate
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13617
28153
30
40
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13632
28173
- Control polygon curve for input curve adjusted for periodicity.
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13671
28153
40
20
-
13691
28163
- 1
- Control polygon points.
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- Points
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- 0
-
13671
28173
40
20
-
13691
28183
- ac750e41-2450-4f98-9658-98fef97b01b2
- Brep Wireframe
- Extract the wireframe curves of a brep.
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- Brep Wireframe
- Brep Wireframe
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130
44
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14001
28245
- Base Brep
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13937
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52
20
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13963
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- Wireframe isocurve density
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- Density
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13937
28245
52
20
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28255
- 1
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- {0}
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- Wireframe curves
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- 0
-
14013
28225
50
40
-
14038
28245
- 3581f42a-9592-4549-bd6b-1c0fc39d067b
- Construct Point
- Construct a point from {xyz} coordinates.
- true
- 8607557e-920d-44ea-897a-c3388ebae07b
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- Construct Point
- Construct Point
-
13825
28112
117
64
-
13901
28144
- {x} coordinate
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- X coordinate
- X coordinate
- false
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- 1
-
13827
28114
62
20
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13858
28124
- 1
- 1
- {0}
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- {y} coordinate
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- true
- Y coordinate
- Y coordinate
- false
- 6abad9f4-df4e-4bc9-a13a-fc424fe4c40a
- 1
-
13827
28134
62
20
-
13858
28144
- 1
- 1
- {0}
- 0
- {z} coordinate
- 17551570-925d-489c-8f4a-c7e1fe2c3dbb
- true
- Z coordinate
- Z coordinate
- false
- 6abad9f4-df4e-4bc9-a13a-fc424fe4c40a
- 1
-
13827
28154
62
20
-
13858
28164
- 1
- 1
- {0}
- 0
- Point coordinate
- 51179561-239d-4312-82e0-f4e7f66516de
- true
- Point
- Point
- false
- 0
-
13913
28114
27
60
-
13926.5
28144
- 9445ca40-cc73-4861-a455-146308676855
- Range
- Create a range of numbers.
- true
- c9a8dc4b-abf3-4367-b392-ec2e73e5858f
- true
- Range
- Range
-
13832
28046
144
44
-
13930
28068
- Domain of numeric range
- b84b7aad-7c57-4840-9ae9-d3962839170d
- true
- Domain
- Domain
- false
- 0
-
13834
28048
84
20
-
13876
28058
- 1
- 1
- {0}
-
0
1
- Number of steps
- aaafd565-907f-48bc-9256-389f9fbad5aa
- true
- Steps
- Steps
- false
- 0
-
13834
28068
84
20
-
13876
28078
- 1
- 1
- {0}
- 6
- 1
- Range of numbers
- 6abad9f4-df4e-4bc9-a13a-fc424fe4c40a
- true
- Range
- Range
- false
- 0
-
13942
28048
32
40
-
13958
28068
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 450ec7d6-6e26-4b9a-970b-d0cbf1772eec
- true
- List Item
- List Item
-
12953
28194
77
64
-
13010
28226
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- c4d83e97-6acf-4921-9e15-25465eddb845
- true
- List
- List
- false
- c7759ede-6017-4b39-8cfd-985e47669aa1
- 1
-
12955
28196
43
20
-
12976.5
28206
- Item index
- 3c027a27-2646-4367-9902-c20adeb5f6af
- true
- Index
- Index
- false
- 0
-
12955
28216
43
20
-
12976.5
28226
- 1
- 1
- {0}
- 0
- Wrap index to list bounds
- 58f4d409-cc2a-44ed-849a-d0442067a074
- true
- Wrap
- Wrap
- false
- 0
-
12955
28236
43
20
-
12976.5
28246
- 1
- 1
- {0}
- false
- Item at {i'}
- 04070efd-05f8-4658-8331-40f0368aa8fa
- true
- false
- Item
- i
- false
- 0
-
13022
28196
6
60
-
13025
28226
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 15462838-16ed-45b2-ae57-bf3140d2a0c4
- true
- Evaluate Length
- Evaluate Length
-
13097
28106
149
64
-
13182
28138
- Curve to evaluate
- 765a521b-aa26-4ea8-bd44-2d1ac48c4a29
- true
- Curve
- Curve
- false
- 04070efd-05f8-4658-8331-40f0368aa8fa
- 1
-
13099
28108
71
20
-
13134.5
28118
- Length factor for curve evaluation
- 89441ced-3308-4968-9a08-ca77e5fff5ca
- true
- Length
- Length
- false
- 0
-
13099
28128
71
20
-
13134.5
28138
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 554ae01c-34f4-406a-9d3f-a64da5656529
- true
- Normalized
- Normalized
- false
- 0
-
13099
28148
71
20
-
13134.5
28158
- 1
- 1
- {0}
- true
- Point at the specified length
- f37cb892-e085-4d02-b622-0cf629b13abf
- true
- Point
- Point
- false
- 0
-
13194
28108
50
20
-
13219
28118
- Tangent vector at the specified length
- ccaef106-f7ec-4a61-955b-726eba10cb0f
- true
- Tangent
- Tangent
- false
- 0
-
13194
28128
50
20
-
13219
28138
- Curve parameter at the specified length
- 4158be2d-5059-4c52-9111-20bb07143d0e
- true
- Parameter
- Parameter
- false
- 0
-
13194
28148
50
20
-
13219
28158
- 269eaa85-9997-4d77-a9ba-4c58cb45c9d3
- Discontinuity
- Find all discontinuities along a curve.
- true
- 787bc2e4-45a8-4f65-ba4a-1370065d5bd7
- true
- Discontinuity
- Discontinuity
-
13221
28182
196
44
-
13348
28204
- Curve to analyze
- c620e97d-b1df-43da-84e2-a8167399f250
- true
- Curve
- Curve
- false
- b1b2d77d-acac-4f93-9d49-1df12c7f025d
- 1
-
13223
28184
113
20
-
13279.5
28194
- Level of discontinuity to test for (1=C1, 2=C2, 3=Cinfinite)
- 0ba9154e-97dd-41b5-8079-8af2e09ec5d7
- true
- Level
- Level
- false
- 0
-
13223
28204
113
20
-
13279.5
28214
- 1
- 1
- {0}
- 1
- 1
- Points at discontinuities
- df6e61e1-1184-4a91-97bf-62962510ac96
- true
- Points
- Points
- false
- 0
-
13360
28184
55
20
-
13387.5
28194
- 1
- Curve parameters at discontinuities
- c974fe53-cc46-49c9-963d-cc9c7e724e14
- true
- Parameters
- Parameters
- false
- 0
-
13360
28204
55
20
-
13387.5
28214
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 413dab6f-30ff-4b34-9f67-90b9f0ff1ee3
- true
- List Item
- List Item
-
13331
28105
77
64
-
13388
28137
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- b430cc72-3de3-4425-bb1c-86715c095b3c
- true
- List
- List
- false
- df6e61e1-1184-4a91-97bf-62962510ac96
- 1
-
13333
28107
43
20
-
13354.5
28117
- Item index
- 4a487015-cb96-43bd-9f37-765100234d74
- true
- Index
- Index
- false
- 0
-
13333
28127
43
20
-
13354.5
28137
- 1
- 1
- {0}
- 4
- Wrap index to list bounds
- d8cac58f-189f-498d-8607-9f7a513a1b26
- true
- Wrap
- Wrap
- false
- 0
-
13333
28147
43
20
-
13354.5
28157
- 1
- 1
- {0}
- false
- Item at {i'}
- c0156a88-eddd-4204-a1a9-6d6859b95655
- true
- false
- Item
- i
- false
- 0
-
13400
28107
6
60
-
13403
28137
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 2b4ed57e-fb00-43dc-8e5f-783398616385
- true
- List Item
- List Item
-
13324
28027
77
64
-
13381
28059
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- 5f3a2d0d-f2d2-4ee0-8ed5-2c4dbae31185
- true
- List
- List
- false
- df6e61e1-1184-4a91-97bf-62962510ac96
- 1
-
13326
28029
43
20
-
13347.5
28039
- Item index
- dff5cd65-cb06-41b2-b199-a1946585a002
- true
- Index
- Index
- false
- 0
-
13326
28049
43
20
-
13347.5
28059
- 1
- 1
- {0}
- 1
- Wrap index to list bounds
- e7e6673d-186e-4a1a-9466-639bf1eeddd1
- true
- Wrap
- Wrap
- false
- 0
-
13326
28069
43
20
-
13347.5
28079
- 1
- 1
- {0}
- false
- Item at {i'}
- 330006fd-b3f1-44f3-8f7d-9b4cca70cab1
- true
- false
- Item
- i
- false
- 0
-
13393
28029
6
60
-
13396
28059
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 2ac16693-cfbb-413e-95aa-4f61e4c28f43
- true
- Merge
- Merge
-
13448
28025
106
84
-
13509
28067
- 4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- 4aa7a97a-2fa1-43b2-971f-37891cd5c08c
- true
- 1
- false
- Data 1
- D1
- true
- 330006fd-b3f1-44f3-8f7d-9b4cca70cab1
- 1
-
13450
28027
47
20
-
13481.5
28037
- 2
- Data stream 2
- cf5915bf-66c0-4066-92ac-d3d1b8b959eb
- true
- 1
- false
- Data 2
- D2
- true
- f37cb892-e085-4d02-b622-0cf629b13abf
- 1
-
13450
28047
47
20
-
13481.5
28057
- 2
- Data stream 3
- 8e0e32cb-a4ba-4c66-b3e7-461cba5c8d0b
- true
- 1
- false
- Data 3
- D3
- true
- c0156a88-eddd-4204-a1a9-6d6859b95655
- 1
-
13450
28067
47
20
-
13481.5
28077
- 2
- Data stream 4
- 5703caee-1e91-455a-b652-9f6cfe30e0f8
- true
- false
- Data 4
- D4
- true
- 0
-
13450
28087
47
20
-
13481.5
28097
- 2
- Result of merge
- 7c15dd75-0fb5-4a70-8968-035294646203
- true
- Result
- Result
- false
- 0
-
13521
28027
31
80
-
13536.5
28067
- 75eb156d-d023-42f9-a85e-2f2456b8bcce
- Interpolate (t)
- Create an interpolated curve through a set of points with tangents.
- true
- 4f97cf3f-ae0c-4d3c-9f34-ce92704918f5
- true
- Interpolate (t)
- Interpolate (t)
-
12805
27979
244
84
-
12997
28021
- 1
- Interpolation points
- d554d29a-fd6e-4dd5-8e2b-3e23c028de73
- true
- Vertices
- Vertices
- false
- 7c15dd75-0fb5-4a70-8968-035294646203
- 1
-
12807
27981
178
20
-
12896
27991
- Tangent at start of curve
- dadee473-b312-46ba-8f68-cd9361f1f948
- true
- Tangent Start
- Tangent Start
- false
- 0
-
12807
28001
178
20
-
12896
28011
- 1
- 1
- {0}
-
0
1
0
- Tangent at end of curve
- 30e48b0d-5118-47d5-a050-92e2ccd4925f
- true
- Tangent End
- Tangent End
- false
- 0
-
12807
28021
178
20
-
12896
28031
- 1
- 1
- {0}
-
1
0
-1
- Knot spacing (0=uniform, 1=chord, 2=sqrtchord)
- cc4486c6-435b-494a-90b6-38e39bf80feb
- true
- KnotStyle
- KnotStyle
- false
- 0
-
12807
28041
178
20
-
12896
28051
- 1
- 1
- {0}
- 2
- Resulting nurbs curve
- 0ad4a801-5c37-4f86-b0c9-cfa2810fbeed
- true
- Curve
- Curve
- false
- 0
-
13009
27981
38
26
-
13028
27994.33
- Curve length
- f19d34d8-952c-4b7b-9d1c-7cff6f55186e
- true
- Length
- Length
- false
- 0
-
13009
28007
38
27
-
13028
28021
- Curve domain
- 03e24465-d0af-4b53-bf1d-8f60b8c8be45
- true
- Domain
- Domain
- false
- 0
-
13009
28034
38
27
-
13028
28047.67
- 14cf43b6-5eb9-460f-899c-bdece732213a
- Blend Curve Pt
- Create a blend curve between two curves that intersects a point.
- true
- 81c31b9d-d9f4-48ac-8b75-2e11cf294f83
- true
- Blend Curve Pt
- Blend Curve Pt
-
12468
27031
167
84
-
12592
27073
- First curve for blend
- a4c7118a-7572-41be-b304-670fa4f0336a
- true
- Curve A
- Curve A
- false
- 5a30bc9c-1f0b-4a38-8546-68bfff78fe07
- 1
-
12470
27033
110
20
-
12525
27043
- Second curve for blend
- b9be3c42-571a-4365-b65c-6eb712673f9e
- true
- Curve B
- Curve B
- false
- 781927c7-3272-460b-af8b-3107b52db860
- 1
-
12470
27053
110
20
-
12525
27063
- Point for blend intersection
- 56da942a-7d64-4a15-a453-bd453c33c962
- true
- Point
- Point
- false
- f37cb892-e085-4d02-b622-0cf629b13abf
- 1
-
12470
27073
110
20
-
12525
27083
- Continuity of blend (1=tangency, 2=curvature)
- c921ac17-e66d-495f-b864-733f670a6de1
- true
- Continuity
- Continuity
- false
- 0
-
12470
27093
110
20
-
12525
27103
- 1
- 1
- {0}
- 2
- Blend curve connecting the end of A to the start of B, ideally coincident with P
- e7179353-b7a9-4734-995e-1ac6997baecc
- true
- Blend
- Blend
- false
- 0
-
12604
27033
29
80
-
12618.5
27073
- 62cc9684-6a39-422e-aefa-ed44643557b9
- Extend Curve
- Extend a curve by a specified distance.
- true
- 78bea16c-c7ca-42a2-8f5a-2cbb175c6b39
- true
- Extend Curve
- Extend Curve
-
12880
27754
124
84
-
12960
27796
- Curve to extend
- cb01bec1-5994-48f1-bdcc-f6c296ef31f8
- true
- Curve
- Curve
- false
- 0ad4a801-5c37-4f86-b0c9-cfa2810fbeed
- 1
-
12882
27756
66
20
-
12915
27766
- Type of extension (0=Line, 1=Arc, 2=Smooth)
- cea346a1-d619-486a-907c-9d9c84e216d8
- true
- Type
- Type
- false
- 0
-
12882
27776
66
20
-
12915
27786
- 1
- 1
- {0}
- 0
- Extension length at start of curve
- 2cc7cbe5-f621-4395-9528-fb47068a8b5f
- true
- Start
- Start
- false
- 0
-
12882
27796
66
20
-
12915
27806
- 1
- 1
- {0}
- 0.0625
- Extension length at end of curve
- 3bcb9a0c-7d15-470d-b3db-f84b1b79ace3
- true
- End
- End
- false
- 0
-
12882
27816
66
20
-
12915
27826
- 1
- 1
- {0}
- 0.0625
- Extended curve
- b7ece470-8963-4e98-b9fc-c87e811ab6a6
- true
- Curve
- Curve
- false
- 0
-
12972
27756
30
80
-
12987
27796
- afb96615-c59a-45c9-9cac-e27acb1c7ca0
- Explode
- Explode a curve into smaller segments.
- true
- 8ffd48b3-48cf-434f-9acc-297e520858bf
- true
- Explode
- Explode
-
12859
27691
134
44
-
12930
27713
- Curve to explode
- d9fa462d-da4f-4ce6-92e7-51395c617b2d
- true
- Curve
- Curve
- false
- b7ece470-8963-4e98-b9fc-c87e811ab6a6
- 1
-
12861
27693
57
20
-
12889.5
27703
- Recursive decomposition until all segments are atomic
- 16058c48-486f-427a-802c-3b8a1a421834
- true
- Recursive
- Recursive
- false
- 0
-
12861
27713
57
20
-
12889.5
27723
- 1
- 1
- {0}
- true
- 1
- Exploded segments that make up the base curve
- b6507732-c5c5-43eb-bc89-4c7b87a994c4
- true
- Segments
- Segments
- false
- 0
-
12942
27693
49
20
-
12966.5
27703
- 1
- Vertices of the exploded segments
- b55cf522-ec7a-460d-b821-829569c85064
- true
- Vertices
- Vertices
- false
- 0
-
12942
27713
49
20
-
12966.5
27723
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 8a512fa1-3acb-436d-b89c-8cb084c66169
- true
- List Item
- List Item
-
12875
27563
77
64
-
12932
27595
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- eeb4e85f-0bf6-474e-88c8-cc8acc779e91
- true
- List
- List
- false
- b6507732-c5c5-43eb-bc89-4c7b87a994c4
- 1
-
12877
27565
43
20
-
12898.5
27575
- Item index
- 0eb903a7-7ee6-43b4-944b-4f4e6ad99965
- true
- Index
- Index
- false
- 0
-
12877
27585
43
20
-
12898.5
27595
- 1
- 1
- {0}
- 0
- Wrap index to list bounds
- 99da5bf6-85bd-4a71-abf4-b7e058ad3f67
- true
- Wrap
- Wrap
- false
- 0
-
12877
27605
43
20
-
12898.5
27615
- 1
- 1
- {0}
- true
- Item at {i'}
- 36f43267-27de-4174-8fa7-7181d7f6dbfa
- true
- false
- Item
- i
- false
- 0
-
12944
27565
6
60
-
12947
27595
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 50b2e22f-d285-4505-b5fb-8235c2d94057
- true
- List Item
- List Item
-
12891
27628
77
64
-
12948
27660
- 3
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- Base list
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- Item index
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12914.5
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12960
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6
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12963
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- ae4835db-ae71-4361-8536-1a5e50386819
- 1c9de8a1-315f-4c56-af06-8f69fee80a7a
- Smooth Curve
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- true
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- true
- Smooth Curve
- Smooth Curve
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- Curve to smooth
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12844
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- Number of recursive smoothing steps
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12844
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- Determines how the start of the curve is preserved
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1 = Preserve first two points
2 = Preserve first three points
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12844
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1 = Preserve last two points
2 = Preserve last three points
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- 0
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- Tolerance angle in degrees for kink smoothing
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- Resulting smoothed curve
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- true
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- Fit Curve Smooth
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- Curve to fit
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12774
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158
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12853
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- Degree to fit the curve to (if omitted input curve degree is used)
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- true
- Degree
- Degree
- true
- 0
-
12774
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158
20
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12853
27332
- Tolerance distance the fit curve is allowed to deviate from the curve to fit (if omitted document tolerance is used)
- 4d424ce7-e6aa-4f9a-9a9f-48d020d08f2c
- true
- Deviation Tolerance
- Deviation Tolerance
- false
- 0
-
12774
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158
20
-
12853
27352
- 1
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- {0}
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- Tolerance angle in degrees for kink smoothing (if omitted document angle tolerance is used)
- b006e454-520f-4644-b3a5-7101f3f1e20e
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- false
- 0
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12774
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158
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-
12853
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- 1
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- {0}
- 1E-10
- Resulting fitted curve
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- 0
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12970.5
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- Fit Curve
- Fit a curve along another curve.
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- Fit Curve
- Fit Curve
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27251
- Curve to fit
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12743
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113
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12799.5
27231
- Optional degree of curve (if omitted, input degree is used)
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- Degree
- Degree
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12743
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113
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12799.5
27251
- 1
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- Tolerance for fitting (if omitted, document tolerance is used)
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- Tolerance
- Tolerance
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12743
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113
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12799.5
27271
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- Fitted curve
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12880
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12895
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- Rebuild PolyCurve
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
- Rebuild a curve preserving the kinks in the polycurves
- true
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- Rebuild PolyCurve
- Rebuild PolyCurve
- false
- dga_3@hotmail.com
- Daniel Abalde
- https://www.facebook.com/DanielAbaldeDesigner
- 4
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198
64
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12869
27145
- 3
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- Polycurve to rebuild
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12717
27115
140
20
-
12787
27125
- Factor that multiplies the length of each curve segment to determine the number of control points for that segment.
Control points for each segment = length of the segment * Division factor.
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- Division factor
- Division factor
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140
20
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12787
27145
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- Tolerance angle to determine the segments of the polycurve
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12717
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140
20
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12787
27165
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- {0}
- 1E-10
- Resulting curve
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- true
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12881
27115
30
60
-
12896
27145
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- Digit Scroller
- Numeric scroller for single numbers
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-
- 11
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12646
28092
250
20
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12646.65
28092.02
- 8073a420-6bec-49e3-9b18-367f6fd76ac3
- Join Curves
- Join as many curves as possible
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- Join Curves
- Join Curves
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12510
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116
44
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12577
27449
- 1
- Curves to join
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12512
27429
53
20
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12538.5
27439
- Preserve direction of input curves
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12512
27449
53
20
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12538.5
27459
- 1
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- Joined curves and individual curves that could not be joined.
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- true
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12589
27429
35
40
-
12606.5
27449
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- ca78e54f-2c7c-4550-9fbf-85e4695e34e4
- true
- Evaluate Length
- Evaluate Length
-
12419
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149
64
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12504
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- Curve to evaluate
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12421
27238
71
20
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12456.5
27248
- Length factor for curve evaluation
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- Length
- Length
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12421
27258
71
20
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12456.5
27268
- 1
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- true
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12421
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71
20
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12456.5
27288
- 1
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- Point at the specified length
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12516
27238
50
20
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12541
27248
- Tangent vector at the specified length
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12516
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50
20
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12541
27268
- Curve parameter at the specified length
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12516
27278
50
20
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12541
27288
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 34c4c1ac-606a-4181-b6ea-85caebd18dee
- true
- Evaluate Length
- Evaluate Length
-
12415
27348
149
64
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12500
27380
- Curve to evaluate
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12417
27350
71
20
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12452.5
27360
- Length factor for curve evaluation
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- Length
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12417
27370
71
20
-
12452.5
27380
- 1
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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12417
27390
71
20
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12452.5
27400
- 1
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- Point at the specified length
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12512
27350
50
20
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12537
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50
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- Line start point
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- Line tangent (direction)
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22
60
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- Create a line segment defined by start point, tangent and length.}
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116
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- Line tangent (direction)
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66
20
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0
1
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66
20
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27298
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27248
22
60
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- Flip a curve using an optional guide curve.
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- Flip Curve
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27171
88
44
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- Curve to flip
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30
20
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30
20
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27173
30
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30
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- Polar Array
- Create a polar array of geometry.
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26919
207
84
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- Polar array plane
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113
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0
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- Number of elements in array.
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12456
26961
113
20
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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12456
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- Divide Curves on Intersects
- Divide curves on all of their intersects.
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174
44
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113
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113
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26864
33
40
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- Merge a bunch of data streams
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106
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47
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47
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31
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- Flip Curve
- Flip a curve using an optional guide curve.
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88
44
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- Curve to flip
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30
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- Optional guide curve
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30
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30
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- Flip action
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28925
30
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- Merge a bunch of data streams
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90
84
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31
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31
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31
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31
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29795
50
24
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133
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- Profile curve or surface
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60
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13664
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60
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45
40
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13770.5
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- A wire relay object
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40
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13504
29764
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13565
29898
50
24
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- Extrude
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29873
133
44
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- Profile curve or surface
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29875
60
20
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13717
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- Extrusion direction
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13679
29895
60
20
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29905
- Extrusion result
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13763
29875
45
40
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13785.5
29895
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- Relay
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29859
40
16
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13519
29867
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50
24
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29648
117
44
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- Profile curve or surface
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44
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- Extrusion direction
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44
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29650
45
40
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40
16
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50
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26558
38
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- Index
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12538
26578
38
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12538
26598
38
20
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12557
26608
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26558
6
60
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26588
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- Retrieve a specific item from a list.
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26571
72
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26603
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26573
38
20
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- Item index
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26593
38
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26603
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26613
38
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26573
6
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- Merge a bunch of data streams
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31
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31
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31
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- Join as many curves as possible
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- Join Curves
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116
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- Curves to join
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53
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- Preserve
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26493
53
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- Joined curves and individual curves that could not be joined.
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35
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- Join Curves
- Join as many curves as possible
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- Join Curves
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26518
116
44
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- 1
- Curves to join
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26520
53
20
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- Preserve direction of input curves
- dc69c91d-b4d8-473d-80c9-ccbca9c4442e
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- Preserve
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53
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- Joined curves and individual curves that could not be joined.
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35
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- Solve the arithmetic weighted average for a set of curves.
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- Weighted Average Curve
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- Set of curves for averaging
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- Collection of weights for each curve
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79
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- Optional Refit match method.
(No Integer or 0 = Off, Integer greater than 0 = On and curve degree of refit)
If an integer greater than zero, Refit match method is used if possible. When input curves are refit their control points are redistributed, added to, and removed from based on the curves curvature and the input integer degree, while trying to maintain their shapes. Refit results in tighter shaped averages, with curvature based control point distribution.
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79
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(No Integer or 0 = Off, Integer greater than 0 = On and amount of sample points)
If an integer greater than zero, Point Sample match method is used. When input curves are sampled their control points are recreated by equally dividing the curve by the input integer point count. Point Sample results in looser shaped averages, with uniform control point distribution.
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79
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- Arithmetic mean (average) of all input curves
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79
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- Numeric slider for single values
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275
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- Numeric slider for single values
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275
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- Create a polar array of geometry.
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- Polar Array
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- Geometry
- Geometry
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113
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- Polar array plane
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113
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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- Transform
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- Divide curves on all of their intersects.
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174
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- curves to be divided
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113
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113
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33
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- Retrieve a specific item from a list.
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43
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43
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- Numeric scroller for single numbers
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- 12
- Digit Scroller
- 11
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29924
250
20
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- Retrieve a specific item from a list.
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77
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43
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6
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- Contains a collection of generic surfaces
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- Group
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- A group of Grasshopper objects
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- Group
- ᑐᑕ
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- Relay
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- A wire relay object
- 30377d3c-57fd-4ec7-9de3-54b95b3a7509
- true
- Relay
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- 6457973d-18aa-4d88-958b-85acd494ab86
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- Simple Mesh
- Create a mesh that represents a Brep as simply as possible
- true
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- Simple Mesh
- Simple Mesh
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- Brep to mesh, only breps with triangle or quad faces are supported.
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- Brep
- Brep
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- Weaverbird's Catmull-Clark Subdivision
- Calculates the type of mesh-based recursive subdivision described by Edwin Catmull and Jim Clark, at first in their 1978 paper. The resulting mesh always consists of quad faces.
Provided by Weaverbird 0.9.0.1.
- 2
- true
- 94698773-e34b-4d6a-ac31-6a2b9cabaed4
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- Weaverbird's Catmull-Clark Subdivision
- Weaverbird's Catmull-Clark Subdivision
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- The open or closed mesh, or closed curves list, to subdivide
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- Mesh/Curves
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- The number of subdividing iterations for each face
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- Level
- Level
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- {0}
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- Defines how to treat the naked edges
0: Fixed. Naked edges will not move or be modified.
1: Smooth. The naked edge will tend toward a spline.
2: Corner Fixed. Corners (2-sided vertices) will be fixed, while other naked vertices will tend toward a spline.
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- Smooth Naked Edges
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- The mesh after the subdividing process
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- Output Mesh/Curves
- Output Mesh/Curves
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- ba2d8f57-0738-42b4-b5a5-fe4d853517eb
- Deconstruct Mesh
- Deconstruct a mesh into its component parts.
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- Deconstruct Mesh
- Deconstruct Mesh
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- Mesh
- Mesh
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- Mesh vertices
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- Vertices
- Vertices
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- Mesh faces
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- Faces
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- Mesh vertex colours
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- Colours
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- Mesh normals
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- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- c26cf418-61ae-489d-9e07-58009252dd8b
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- Pull Point
- Pull Point
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- Point to search from
- 00a77e54-a567-4ff5-9386-fce2c71d125d
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- Point
- Point
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- 6123bda8-5a08-4619-9c3c-d457a3a15fa2
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- Geometry that pulls
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- Geometry
- Geometry
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- Point on [G] closest to [P]
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- Closest Point
- Closest Point
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- Distance between [P] and its projection onto [G]
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- Distance
- Distance
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- e2c0f9db-a862-4bd9-810c-ef2610e7a56f
- Construct Mesh
- Construct a mesh from vertices, faces and optional colours.
- true
- 4214bc60-7b85-4968-9449-f2b31fe09985
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- Construct Mesh
- Construct Mesh
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- Vertices of mesh object
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- Vertices
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- Faces of mesh object
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- Faces
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- Optional vertex colours
- 5e9b3fa3-40e1-4c58-9578-6375f7b2765f
- true
- Colours
- Colours
- true
- 0
-
12579
29575
52
20
-
12605
29585
- Constructed mesh
- e2eb27fa-4759-4c6b-b0e2-999e4b9cb9f0
- true
- Mesh
- Mesh
- false
- 0
-
12655
29535
28
60
-
12669
29565
- 079bd9bd-54a0-41d4-98af-db999015f63d
- Fan+3
- Private Function appendprepend(ByVal i As Integer)
Dim srsEnum As IEnumerable(Of Integer) = Enumerable.Range(0, i + 1)
Dim arrVal As New list(Of Integer)
arrVal = srsEnum.tolist()
arrVal.add(0)
arrVal.insert(0, i)
Return arrVal.toarray()
End Function
Private Function matchDbl(ByVal a As list(Of Double), ByVal t As Integer)
Dim i,k As Integer
k = a.count()
For i = 0 To ((t + 1) - k) - 1 Step 1
a.add(a.item(k - 1))
Next
Return a
End Function
Private Function matchClr(ByVal a As list(Of Color), ByVal t As Integer)
Dim i,k As Integer
k = a.count()
For i = 0 To ((t + 1) - k) - 1 Step 1
a.add(a.item(k - 1))
Next
Return a
End Function
Private Function evalP(ByVal op As point3d, ByVal tp As Point3d, ByVal t As Double)
Return New point3d(op + (tp - op) * t)
End Function
Private Function evalV(ByVal ov As vector3d, ByVal tv As vector3d, ByVal t As Double)
Return New vector3d(ov + (tv - ov) * t)
End Function
Private Function evalN(ByVal u As Double, ByVal v As Double, ByVal t As Double)
Return u + (v - u) * t
End Function
Private Function avgVec(ByVal v() As vector3f)
Dim i As Integer
Dim tv As Vector3d
For i = 0 To ubound(v) Step 1
tv += v(i)
Next
tv /= (ubound(v) + 1)
tv.Unitize()
Return New vector3f(tv.X, tv.Y, tv.Z)
End Function
Private Function roundClr(ByVal r As Integer, ByVal g As Integer, ByVal b As Integer, ByVal i As Integer)
r = CInt(r / i)
g = CInt(g / i)
b = CInt(b / i)
If r > 255 Then r = 255 Else If r < 0 Then r = 0
If g > 255 Then g = 255 Else If g < 0 Then g = 0
If b > 255 Then b = 255 Else If b < 0 Then b = 0
Return color.FromArgb(r, g, b)
End Function
Private Function avgClr(ByVal c() As color)
Dim r,g,b As Integer
Dim i,k As Integer
k = ubound(c) + 1
For i = 0 To k - 1 Step 1
r += CInt(c(i).R)
g += CInt(c(i).G)
b += CInt(c(i).B)
Next
r = CInt(r / k)
g = CInt(g / k)
b = CInt(b / k)
If r > 255 Then r = 255 Else If r < 0 Then r = 0
If g > 255 Then g = 255 Else If g < 0 Then g = 0
If b > 255 Then b = 255 Else If b < 0 Then b = 0
Return color.FromArgb(r, g, b)
End Function
Private Function evalC(ByVal oc As color, ByVal tc As color, ByVal t As Double)
Dim r,g,b As Integer
r = CInt(CInt(oc.R) + (CInt(tc.R) - CInt(oc.R)) * t)
g = CInt(CInt(oc.G) + (CInt(tc.G) - CInt(oc.G)) * t)
b = CInt(CInt(oc.B) + (CInt(tc.B) - CInt(oc.B)) * t)
If r > 255 Then r = 255 Else If r < 0 Then r = 0
If g > 255 Then g = 255 Else If g < 0 Then g = 0
If b > 255 Then b = 255 Else If b < 0 Then b = 0
Return color.FromArgb(r, g, b)
End Function
- true
- Replaces selected faces of a mesh or the interior of a curve with a frame around the edge by creating 3 new points along the edge and removing the face's vertex.
-
251
91
- true
-
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
- d83cd624-e7c4-45b5-b4d0-2a3985556ca5
- true
- Fan+3
- Fan+3
- true
- 0
-
Component.Params.Input(0).Name = "Mesh or Curve"
Component.Params.Input(0).Description = "Open or closed mesh or curve"
Component.Params.Input(1).Name = "Index [Face]"
Component.Params.Input(1).Description = "An optional integer or list of integers which specify the faces to be modified if the input is a mesh. If no value is supplied then all faces will be modified"
Component.Params.Input(2).Name = "Along Edge"
Component.Params.Input(2).Description = "Evaluates a new vertex along the input geometry's edge"
Component.Params.Input(3).Name = "Close"
Component.Params.Input(3).Description = "If true then additional faces and if needed vertices will be added to the mesh, covering the complete areas of the existing mesh"
Component.Params.Input(4).Name = "Color [Vertex]"
Component.Params.Input(4).Description = "(If applied to a mesh a list of colors corresponding to each mesh face, if applied to a curve, a list of colors corresponding to each control point plus an additonal color value for the new averaged center"
Component.Params.Output(1).Name = "Mesh"
Component.Params.Output(1).Description = "If successful, a valid mesh"
If G IsNot Nothing Then
Dim bM, bP,bmC,biC As Boolean
bM = g.ObjectType = ObjectType.Mesh
bP = g.ObjectType = ObjectType.Curve
If (bM Or bP) Then
Dim msh As New mesh
Dim crv As curve
Dim av As point3d
Dim ac As color
Dim h,j,jj,k,u,v,w As Integer
Dim cv,cf,ce As Integer
Dim x(),y() As Integer
Dim mv,fv,ep,tv As New list(Of Point3d)
Dim mev As New dictionary(Of String, Integer)
Dim mf As Rhino.Geometry.Collections.MeshFaceList = Nothing
Dim mtv As Rhino.Geometry.Collections.MeshTopologyVertexList = Nothing
Dim mte As Rhino.Geometry.Collections.MeshTopologyEdgeList = Nothing
Dim ev As New list(Of vector3d)
Dim ed,en As New list(Of Double)
Dim mc,ec,tc,cc,fc As New list(Of color)
Dim xf As New list(Of meshface)
If clr.count() = 0 Then clr.add(color.LightGray) Else biC = True
If bm Then
'Start Deconstruct if Mesh
msh = g
If msh.Normals.Count() = 0 Then msh.Normals.ComputeNormals()
If msh.FaceNormals.Count() = 0 Then msh.FaceNormals.ComputeFaceNormals()
If i.count() = 0 Then I = Enumerable.Range(0, msh.Faces.Count()).ToList()
mv = msh.Vertices().ToPoint3dArray().tolist()
mte = msh.TopologyEdges()
mtv = msh.TopologyVertices()
mf = msh.Faces()
cf = I.Count() - 1
ce = mte.count() - 1
'Assign Colors
If msh.VertexColors.Count() < 1 Then
msh.VertexColors.CreateMonotoneMesh(color.LightGray)
bmC = biC
Else
bmC = True
End If
'Assign fake edges
mc = msh.VertexColors().ToArray().ToList()
Else
'Start Deconstruct if Curve
crv = g
I.clear()
I.add(0)
Dim nc As nurbscurve
Dim pc As polyline
Dim nps As Rhino.Geometry.Collections.NurbsCurvePointList
nc = crv.ToNurbsCurve()
nps = nc.Points
pc = nc.Points.ControlPolygon
If (Not pc.IsClosed) Then pc.add(pc(0))
av = pc.CenterPoint
msh.Vertices.AddVertices(pc.ToArray())
msh.faces.addfaces(pc.TriangulateClosedPolyline())
msh.Vertices.Remove(pc.count() - 1, True)
msh.FaceNormals.ComputeFaceNormals()
mv = msh.Vertices.ToPoint3dArray().tolist()
mte = msh.TopologyEdges()
mtv = msh.TopologyVertices()
'Assign Colors
If bic Then bmC = True
mc = clr
If (clr.count() - 1) < (mv.count() - 1) Then mc = matchClr(mc, mv.count() - 1)
ac = avgClr(mc.toarray())
cf = 0
End If
cv = mv.count() - 1
ce = mte.count() - 1
x = appendprepend(cv)
'Match variables and colors to vertex count
If (T0.count() - 1) < cv Then T0 = matchDbl(T0, cv)
If (clr.count() - 1) < cv Then clr = matchClr(clr, cv)
If biC Then fc = clr Else fc = mc
'Edge based vertices
k = 0
For j = 0 To mte.count() - 1 Step 1
If (bm Or (bp And (mte.GetConnectedFaces(j).Count() < 2))) Then
u = mtv.MeshVertexIndices(mte.GetTopologyVertices(j).I)(0)
v = mtv.MeshVertexIndices(mte.GetTopologyVertices(j).J)(0)
ep.add(evalP(mv(u), mv(v), T0(u) / 2))
ec.add(evalC(mc(u), mc(v), T0(u) / 2))
mev.add(u & "," & v & "," & 0, k)
ep.add(evalP(mv(u), mv(v), 0.5))
ec.add(evalC(mc(u), mc(v), 0.5))
mev.add(u & "," & v & "," & 1, k + 1)
mev.add(v & "," & u & "," & 1, k + 1)
ep.add(evalP(mv(v), mv(u), T0(v) / 2))
ec.add(evalC(mc(v), mc(u), T0(v) / 2))
mev.add(v & "," & u & "," & 0, k + 2)
k += 3
End If
Next
'Face based vertices
Dim xv(),mt(),ei() As Integer
Dim xc() As color
Dim xn As Double
ReDim ei(3)
u = 0
v = ep.count() + cf + 1
For jj = 0 To I.count() - 1 Step 1
Dim tcv As New point3d
j = I(jj)
w = v + tv.count()
xn = 0
If bm Then
If mf(j).isquad() Then h = 4 Else h = 3
ReDim xv(h - 1)
ReDim xc(h - 1)
mt = mf.GetTopologicalVertices(j)
For k = 0 To h - 1 Step 1
xv(k) = mtv.MeshVertexIndices(mt(k))(0)
xc(k) = fc(xv(k))
Next
av = mf.GetFaceCenter(j)
ac = avgClr(xc)
Else
h = mv.count()
xv = Enumerable.Range(0, h).ToArray()
End If
y = appendprepend(h - 1)
Dim tev As New list(Of Integer)
For k = 1 To h Step 1
ei(0) = mev.item(xv(y(k)) & "," & xv(y(k + 1)) & "," & 0)
ei(1) = mev.item(xv(y(k)) & "," & xv(y(k + 1)) & "," & 1)
ei(2) = mev.item(xv(y(k + 1)) & "," & xv(y(k)) & "," & 0)
ei(3) = mev.item(xv(y(k)) & "," & xv(y(k - 1)) & "," & 0)
'Define new faces
tev.add(ei(1))
xf.add(New meshface(ei(0), ei(1), ep.count() + jj))
xf.add(New meshface(ei(1), ei(2), ep.count() + jj))
xf.add(New meshface(ei(3), ei(0), ep.count() + jj))
If c Then xf.add(New meshface(ei(0), ei(3), v + xv(y(k))))
Next
fv.add(av)
cc.add(ac)
Next
Dim om As New mesh
om.Vertices.AddVertices(ep.toarray())
If bmC Then om.VertexColors.AppendColors(ec.toarray())
om.Vertices.AddVertices(fv)
If bmC Then om.VertexColors.AppendColors(cc.toarray())
If c Then
om.Vertices.AddVertices(mv)
If bmC Then om.VertexColors.AppendColors(mc.toarray())
End If
om.Faces.AddFaces(xf.toarray())
If i.count() > 1 Then om.Vertices.CullUnused()
A = om
End If
End If
- Imports System.IO
Imports System.Linq
Imports System.Data
Imports System.Drawing
Imports System.Reflection
Imports System.Windows.Forms
Imports System.Xml
Imports System.Xml.Linq
Imports Microsoft.VisualBasic
Imports System.Runtime.InteropServices
Imports Rhino.DocObjects
Imports Rhino.Collections
Imports GH_IO
Imports GH_IO.Serialization
-
12408
29761
72
104
-
12447
29813
- 5
- 84fa917c-1ed8-4db3-8be1-7bdc4a6495a2
- 84fa917c-1ed8-4db3-8be1-7bdc4a6495a2
- 84fa917c-1ed8-4db3-8be1-7bdc4a6495a2
- 84fa917c-1ed8-4db3-8be1-7bdc4a6495a2
- 84fa917c-1ed8-4db3-8be1-7bdc4a6495a2
- 2
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- true
- Script Variable G
- 02277887-37da-43cd-9045-2ab622639ff1
- true
- G
- G
- true
- 0
- true
- 979517f2-242e-4e4d-bb88-dd2fc0fa6486
- 1
- c37956f4-d39c-49c7-af71-1e87f8031b26
-
12410
29763
25
20
-
12422.5
29773
- 1
- true
- Script Variable I
- 8bd25a8a-91d9-4eb6-9e52-e603199172cb
- true
- I
- I
- true
- 1
- true
- 0
- efe48ae7-2987-421b-a33a-1f7be1c3f050
-
12410
29783
25
20
-
12422.5
29793
- 1
- true
- Script Variable T0
- f73ae574-ad64-4c32-ae83-7e8f37868e39
- true
- T0
- T0
- true
- 1
- true
- 0
- 8e991e99-5fb8-41e1-928d-1bba8fb9f7d7
-
12410
29803
25
20
-
12422.5
29813
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Number
- 0.00390625
- true
- Script Variable C
- 541f6166-b28c-4953-9587-28afbe302f37
- true
- C
- C
- true
- 0
- true
- 0
- 3cda2745-22ac-4244-9b04-97a5255fa60f
-
12410
29823
25
20
-
12422.5
29833
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Boolean
- false
- 1
- true
- Script Variable clr
- 14fbe32e-4185-4da3-b3dc-3e17bbd88a35
- true
- clr
- clr
- true
- 1
- true
- 0
- 24b1d1a3-ab79-498c-9e44-c5b14607c4d3
-
12410
29843
25
20
-
12422.5
29853
- 1
- Print, Reflect and Error streams
- ee0a4ed3-d78c-40ef-847e-90017eeb7dc0
- true
- out
- out
- false
- 0
-
12459
29763
19
50
-
12468.5
29788
- Output parameter A
- 16e90cf5-2746-46b7-bcf2-2c1b43dfacf2
- true
- A
- A
- false
- 0
-
12459
29813
19
50
-
12468.5
29838
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 5fa3dc85-5552-4797-8ef8-852841306048
- true
- Relay
- false
- e2eb27fa-4759-4c6b-b0e2-999e4b9cb9f0
- 1
-
12568
29391
40
16
-
12588
29399
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- cfcc5b9b-e104-430a-a736-e9cfea660979
- true
- Relay
- false
- 979517f2-242e-4e4d-bb88-dd2fc0fa6486
- 1
-
12412
29944
40
16
-
12432
29952
- f12daa2f-4fd5-48c1-8ac3-5dea476912ca
- Mirror
- Mirror an object.
- true
- 8ca2ca44-079d-4e4e-83d9-78c3dacd6aa1
- true
- Mirror
- Mirror
-
12299
28774
305
61
-
12540
28805
- Base geometry
- f0451bfd-6b26-4476-a72d-80f6e314bf50
- true
- Geometry
- Geometry
- true
- 8ad5c4e2-d150-4afc-a797-fd8b0b4ef95e
- 1
-
12301
28776
227
20
-
12414.5
28786
- Mirror plane
- bdda47f8-b994-4250-b1b5-b26f29b09a23
- true
- Plane
- Plane
- false
- 0
-
12301
28796
227
37
-
12414.5
28814.5
- 1
- 1
- {0}
-
0
0
0
0
1
0
-0.707106781186548
0
0.707106781186547
- Mirrored geometry
- 3b6274c6-0db1-455b-9b83-56ddcc437d14
- true
- Geometry
- Geometry
- false
- 0
-
12552
28776
50
28
-
12577
28790.25
- Transformation data
- c350c7c4-7044-46b5-b160-4695143dbec2
- true
- Transform
- Transform
- false
- 0
-
12552
28804
50
29
-
12577
28818.75
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- b05b3657-d031-4156-a0f9-5d9aa404e206
- true
- Merge
- Merge
-
12673
28874
90
64
-
12718
28906
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- 343f6de4-eecf-4785-b593-7aaf75b8cc9e
- true
- false
- Data 1
- D1
- true
- 3b6274c6-0db1-455b-9b83-56ddcc437d14
- 1
-
12675
28876
31
20
-
12690.5
28886
- 2
- Data stream 2
- bd4c1892-0bf0-4db4-a530-98e1456b3833
- true
- false
- Data 2
- D2
- true
- 8ad5c4e2-d150-4afc-a797-fd8b0b4ef95e
- 1
-
12675
28896
31
20
-
12690.5
28906
- 2
- Data stream 3
- d82bb646-e7ea-4620-a4e6-a21543407c90
- true
- false
- Data 3
- D3
- true
- 0
-
12675
28916
31
20
-
12690.5
28926
- 2
- Result of merge
- feee9bed-0a55-4a71-bbe4-7083862058a6
- true
- Result
- Result
- false
- 0
-
12730
28876
31
60
-
12745.5
28906
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 4b3c5c37-6f6a-4f2d-90a7-ad7b24cb571c
- true
- Polar Array
- Polar Array
-
12793
28758
207
84
-
12920
28800
- Base geometry
- 035d7fb3-c2cf-4600-bfd9-842d930e39d5
- true
- Geometry
- Geometry
- true
- feee9bed-0a55-4a71-bbe4-7083862058a6
- 1
-
12795
28760
113
20
-
12851.5
28770
- Polar array plane
- 1786f70d-6c1f-4d8e-8097-e7d5e5b74c63
- true
- Plane
- Plane
- false
- 8466f10c-3993-400e-8742-e7e3f179651f
- 1
-
12795
28780
113
20
-
12851.5
28790
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- f62765ec-b9fe-48ee-8fff-50fd1b505801
- true
- Count
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12932
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66
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12957
28820
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12526
28939
40
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12546
28947
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92
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29248
34
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13858
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13841
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34
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13858
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255;255;255;255
- A group of Grasshopper objects
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- Group
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255;255;255;255
- A group of Grasshopper objects
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- Extract the end points of a curve.
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26
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27883
26
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- Create a polyline connecting a number of points.
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27794
116
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50
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14320
27816
50
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27796
38
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27816
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- Create a polyline connecting a number of points.
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27919
116
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50
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- Close polyline
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27941
50
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27921
38
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27941
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- Merge a bunch of data streams
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31
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31
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27838
31
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- Join as many curves as possible
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116
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35
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- Number of items in L
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- Measure the length of a curve.
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- Item to divide with (divisor)
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66
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66
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66
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120
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110
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- Weld threshold value for Vertices
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15100.5
27746
- 1
- 1
- {0}
-
255;255;255;255
- Colour of the specular highlight
- 28cee4bd-1a24-43e1-868f-385a08024a2e
- true
- Specular
- Specular
- false
- 0
-
15060
27756
81
20
-
15100.5
27766
- 1
- 1
- {0}
-
255;255;255;255
- Emissive colour of the material
- ef1c2dee-aefd-4179-97bf-7712dadef0fe
- true
- Emission
- Emission
- false
- 0
-
15060
27776
81
20
-
15100.5
27786
- 1
- 1
- {0}
-
255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
- 426b9a64-97a9-44e8-9e95-0216b51823b8
- true
- Transparency
- Transparency
- false
- 0
-
15060
27796
81
20
-
15100.5
27806
- 1
- 1
- {0}
- 0
- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
- 1796cfa4-59c9-4dd0-ab45-9d85a728a169
- true
- Shine
- Shine
- false
- 0
-
15060
27816
81
20
-
15100.5
27826
- 1
- 1
- {0}
- 0
- Resulting material
- 326fbc08-dea2-43c0-83cd-c5852522fa30
- true
- Material
- Material
- false
- 0
-
15165
27736
40
100
-
15185
27786
- 12bb406c-41bc-4c8a-9b96-6924df61b6d6
- d2580c41-5c48-4997-87c5-b6333b5e21d7
- Mesh Rebuild Normals
- Rebuilds Mesh Normals
- true
- 4ad1e8d2-5eec-4a0b-ab32-27566d3371b2
- true
- Mesh Rebuild Normals
- Mesh Rebuild Normals
-
14995
27571
84
28
-
15037
27585
- The Input Mesh
- 67d0048a-9807-4193-bec0-59a715e5ae19
- true
- Mesh
- Mesh
- false
- b013ce48-f199-40ec-bce6-4f6f401e0259
- 1
-
14997
27573
28
24
-
15011
27585
- The Mesh with Rebuilt Normals
- 4c36b0a7-9a92-4045-9c7b-9705ffc8e3a1
- true
- Mesh
- Mesh
- false
- 0
-
15049
27573
28
24
-
15063
27585
- 4bfe1bf6-fbc9-4ad2-bf28-a7402e1392ee
- c2ea695e-1a09-6f42-266d-113498879f60
- MultiPipe
- Create a branching pipe around a network of lines/curves
- true
- e65bd057-1477-4024-bf3f-a43c107821f5
- true
- MultiPipe
- MultiPipe
-
15155
27177
186
184
-
15304
27269
- 1
- The curves to pipe. Also accepts meshes
- 9d5ac057-127f-4e4b-b6df-8548a8e2f2de
- true
- Curves
- Curves
- false
- c6bade99-c83e-413c-befb-c3d58ce01183
- 1
-
15157
27179
135
20
-
15232.5
27189
- 1
- Pipe radius. If one value given, it is applied to all. Alternatively, provide a list of radii corresponding to each point in SizePoints
- 8799a98a-0c75-4383-b675-a8bdd2e6b449
- X*65536
- true
- NodeSize
- NodeSize
- false
- d2521a95-eb69-45eb-8202-b014e1e92713
- 1
-
15157
27199
135
20
-
15232.5
27209
- 1
- 1
- {0}
- 0.5
- 1
- If you are supplying multiple radii for NodeSize, these points identify which node to set as which radius. If only some of the nodes have their radius set this way, the values will be interpolated across the shape
- 176f6124-ddbd-40b8-97e7-372416d6976a
- true
- SizePoints
- SizePoints
- true
- 0
-
15157
27219
135
20
-
15232.5
27229
- The distance of the first edge loop away from the node as a multiplier of NodeSize. If this is set to zero, no intermediate edge loop is added, to give a smoother shape.
- 4833559f-205f-4c7b-8c61-5a9d655a6a5d
- true
- EndOffset
- EndOffset
- false
- 0
-
15157
27239
135
20
-
15232.5
27249
- 1
- 1
- {0}
- 1
- The size of the struts between nodes as a multiplier of NodeSize. <1 gives tapering struts, >1 gives bulging struts
- 13260dff-63c9-4a5a-a106-7475f418b115
- true
- StrutSize
- StrutSize
- false
- 0
-
15157
27259
135
20
-
15232.5
27269
- 1
- 1
- {0}
- 1
- Approximate spacing of edge loops along each strut. If set to zero, no additional edge loops are added
- 441666d9-3257-4d33-94db-64e10261e09e
- true
- Segment
- Segment
- false
- 0
-
15157
27279
135
20
-
15232.5
27289
- 1
- 1
- {0}
- 0
- When the input to 'Curves' are smooth curves, this sets the maximum angle between consecutive segments when discretizing
- c77d7fd1-e082-41c9-ae77-a131386c9277
- true
- KinkAngle
- KinkAngle
- false
- 0
-
15157
27299
135
20
-
15232.5
27309
- 1
- 1
- {0}
- 90
- If >0 this attempts to fit a cube at each node. Should be a value between 0 and 1, where 0 = never, and 1 = always, depending on how close to orthogonal its connected lines are.
- 1cdffb78-f04a-4d16-9fed-7de9da78bb39
- true
- CubeFit
- CubeFit
- false
- 0
-
15157
27319
135
20
-
15232.5
27329
- 1
- 1
- {0}
- 0
- Cap option - 0:None, 1:Round, 2:Flat
- 5811a0ea-ed73-4508-ab04-c5f12074a47b
- true
- Caps
- Caps
- true
- 0
-
15157
27339
135
20
-
15232.5
27349
- 1
- 1
- {0}
- 1
- Resulting Pipe SubD
- 1867f002-ba43-453d-9003-2fa07903686d
- true
- Pipe
- Pipe
- false
- 0
-
15316
27179
23
180
-
15327.5
27269
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- d98270ba-9afb-47d3-9937-cf8259edcdee
- true
- Merge
- Merge
-
14519
28090
90
84
-
14564
28132
- 4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- 86ac1872-92ab-4b63-a9e4-484713be52be
- true
- false
- Data 1
- D1
- true
- 960f7236-e5a9-422d-a2d2-dbf7ecde4556
- 1
-
14521
28092
31
20
-
14536.5
28102
- 2
- Data stream 2
- 179555f5-43af-48e9-9fc2-4f3b7acfb0fe
- true
- false
- Data 2
- D2
- true
- 0
-
14521
28112
31
20
-
14536.5
28122
- 2
- Data stream 3
- fcc88034-d9de-4584-9e6a-4b7aaab42489
- true
- false
- Data 3
- D3
- true
- c4c58973-5656-4a93-b5f4-7f922145a19f
- 1
-
14521
28132
31
20
-
14536.5
28142
- 2
- Data stream 4
- 65b533b7-98c2-47f6-a1cd-017b3924e9a2
- true
- false
- Data 4
- D4
- true
- 0
-
14521
28152
31
20
-
14536.5
28162
- 2
- Result of merge
- 64bc1acc-a9db-4735-b25d-7fc33d153fd3
- true
- Result
- Result
- false
- 0
-
14576
28092
31
80
-
14591.5
28132
- 8073a420-6bec-49e3-9b18-367f6fd76ac3
- Join Curves
- Join as many curves as possible
- true
- fd92a202-6283-4250-8b87-a63ec2749b47
- true
- Join Curves
- Join Curves
-
14651
28165
116
44
-
14718
28187
- 1
- Curves to join
- 81a540c7-0c42-4b17-ae37-fcc96a189b33
- true
- Curves
- Curves
- false
- 64bc1acc-a9db-4735-b25d-7fc33d153fd3
- 1
-
14653
28167
53
20
-
14679.5
28177
- Preserve direction of input curves
- 8c16c48d-153e-4180-ab2f-c3f6b58158c7
- true
- Preserve
- Preserve
- false
- 0
-
14653
28187
53
20
-
14679.5
28197
- 1
- 1
- {0}
- false
- 1
- Joined curves and individual curves that could not be joined.
- 54ebf683-fd9d-4ded-8395-0a2c3898d0ef
- true
- Curves
- Curves
- false
- 0
-
14730
28167
35
40
-
14747.5
28187
- c3f9cea5-6fd4-4db5-959b-08cd08ed9fe1
- Simple Mesh
- Create a mesh that represents a Brep as simply as possible
- true
- cdeb0ed4-1a13-4341-9034-684797145956
- true
- Simple Mesh
- Simple Mesh
-
14858
28051
81
28
-
14897
28065
- Brep to mesh, only breps with triangle or quad faces are supported.
- 3948c631-d998-4834-bfdc-3fc92eb3b4ed
- true
- Brep
- Brep
- false
- 0
-
14860
28053
25
24
-
14872.5
28065
- Mesh
- 49844cd2-dce1-4c0c-bd49-b5e0b6dd8e38
- true
- Mesh
- Mesh
- false
- 0
-
14909
28053
28
24
-
14923
28065
- 9266a2bb-918f-4675-9c91-f67d0dd33eac
- Quadrangulate
- Quadrangulate as many triangles as possible in a mesh
- true
- 8665abfd-c7fc-4786-bc40-b494c4bfa4bc
- true
- Quadrangulate
- Quadrangulate
-
14858
27970
148
64
-
14962
28002
- Mesh to quadrangulate
- 2f0e53af-4c1f-4ce1-bb65-8ce06ec8be50
- true
- Mesh
- Mesh
- false
- 54ebf683-fd9d-4ded-8395-0a2c3898d0ef
- 1
-
14860
27972
90
20
-
14905
27982
- Angle threshold. Triangles that exceed this kink-angle will not be merged.
- 7dd61ecc-f1dd-424a-958c-4cdac6b8c9e0
- true
- Angle
- Angle
- false
- 0
-
14860
27992
90
20
-
14905
28002
- 1
- 1
- {0}
- 0.034906585039886591
- Ratio threshold. Quads that have a ratio (shortest diagonal/longest diagonal) that exceed the threshold, will not be considered.
- d6e66e82-f7a2-44db-84b9-4e87f8830fd1
- true
- Ratio
- Ratio
- false
- 0
-
14860
28012
90
20
-
14905
28022
- 1
- 1
- {0}
- 0.875
- Quadrangulated mesh (not all triangles are guaranteed to be converted).
- a7da4a92-991c-4900-b5d1-360021364e54
- true
- Mesh
- Mesh
- false
- 0
-
14974
27972
30
30
-
14989
27987
- Number of triangles that were quadrangulated
- 9700fcbf-be9e-450e-b55e-ba2b4a83e357
- true
- Count
- Count
- false
- 0
-
14974
28002
30
30
-
14989
28017
- 4c0d75e1-4266-45b8-b5b4-826c9ad51ace
- 00000000-0000-0000-0000-000000000000
- Divide Curves on Intersects
- Divide curves on all of their intersects.
- true
- 2f177179-4697-4a93-a401-219c588e7391
- true
- Divide Curves on Intersects
- Divide Curves on Intersects
-
14794
28166
174
44
-
14921
28188
- 1
- curves to be divided
- e220dfce-a878-44d3-8a16-63de991c5b32
- true
- curves
- curves
- false
- 64bc1acc-a9db-4735-b25d-7fc33d153fd3
- 1
-
14796
28168
113
20
-
14852.5
28178
- ZeroTolerance
- 00c0f45e-ba64-4d33-9e88-f6c1deb34897
- true
- Tolerance
- Tolerance
- false
- 0
-
14796
28188
113
20
-
14852.5
28198
- 1
- 1
- {0}
- 4.768E-07
- 1
- aligned curves
- 6da19130-89a1-437b-b23f-cb65a54edfae
- true
- curves
- curves
- false
- 0
-
14933
28168
33
40
-
14949.5
28188
- 59daf374-bc21-4a5e-8282-5504fb7ae9ae
- List Item
- 0
- Retrieve a specific item from a list.
- true
- 2f9c982a-f0ff-467e-ac38-6065e3546417
- true
- List Item
- List Item
-
14865
28223
77
64
-
14922
28255
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- Base list
- fec5ed95-cdff-42cf-889b-c85d2af22ad9
- true
- List
- List
- false
- 6da19130-89a1-437b-b23f-cb65a54edfae
- 1
-
14867
28225
43
20
-
14888.5
28235
- Item index
- 0e1643b4-dc6c-4a34-9c1e-50d0d823a23e
- true
- Index
- Index
- false
- 0
-
14867
28245
43
20
-
14888.5
28255
- 1
- 1
- {0}
- 0
- Wrap index to list bounds
- 3b1b18e4-5dbf-4177-a14b-2f72fd73de68
- true
- Wrap
- Wrap
- false
- 0
-
14867
28265
43
20
-
14888.5
28275
- 1
- 1
- {0}
- true
- Item at {i'}
- 2f6f0afd-993f-47a5-8a5f-5b97369eb913
- true
- false
- Item
- i
- false
- 0
-
14934
28225
6
60
-
14937
28255
- c3f9cea5-6fd4-4db5-959b-08cd08ed9fe1
- Simple Mesh
- Create a mesh that represents a Brep as simply as possible
- true
- 916b40c9-fae5-4a15-b308-c086513aa6ed
- true
- Simple Mesh
- Simple Mesh
-
14265
27486
81
28
-
14304
27500
- Brep to mesh, only breps with triangle or quad faces are supported.
- a3400c94-1368-45d9-919d-f308d19cb831
- true
- Brep
- Brep
- false
- 02d977a4-4efe-4e2d-8407-51dd988709ae
- 1
-
14267
27488
25
24
-
14279.5
27500
- Mesh
- c141638f-f968-4458-8a65-656377164c14
- true
- Mesh
- Mesh
- false
- 0
-
14316
27488
28
24
-
14330
27500
- 8307c31e-e307-48e9-b7c3-f970591e86d2
- 2cd3c35a-cada-1a81-ddba-5b184219e513
- ggNetworkPolygons
- Polygon from Curve network
- true
- 03dad908-8250-4fe7-9faf-aac50ee62be7
- true
- ggNetworkPolygons
- ggNetworkPolygons
-
14343
27745
134
44
-
14438
27767
- 1
- Input Curves
- 0124ecba-9dc2-4ca3-80ff-7428af38b8cc
- true
- Curves
- Curves
- false
- 4cb9ae17-9c50-4f01-abc2-ce86d43083b0
- 1
-
14345
27747
81
20
-
14385.5
27757
- Number of edges considered to be a void or perimeter location
- 5e4caa1c-831b-487e-bdd5-a88cf6ee8f05
- true
- Perim or Void
- Perim or Void
- true
- 0
-
14345
27767
81
20
-
14385.5
27777
- 1
- 1
- {0}
- 4
- 1
- Resultant Polygons
- c3015044-b271-488b-bb89-63d99aa97c9b
- true
- Cells
- Cells
- false
- 0
-
14450
27747
25
40
-
14462.5
27767
- 3c5edcba-b7a5-4710-b076-4b19a7080a2b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Center
- Returns the center of a geometry and the Diameter of it's bounding box as the Dimension
You can Right Click on the component's icon and choose "ForAll" option to have center point of a group of geometries.
Besides You can Right click on the component's icon and choose one of three provided options (Spacial/ Planar/ Basement ) to have Desired type of center.
- true
- 6ec8f57d-f6b6-4f61-9fa6-ea4d3930062b
- true
- Center
- Center
-
14451
27607
129
44
-
14515
27629
- 1
- Geometric
- 25a6dac4-741b-4cf2-b6c4-46916348ea4c
- true
- Geometric
- Geometric
- false
- 83c37836-d997-40ad-b3dd-9f1c8098cd80
- 1
-
14453
27609
50
40
-
14478
27629
- 1
- Center
- 5be92eb5-02c1-4a50-802c-7ab01a573a0e
- true
- Center
- Center
- false
- 0
-
14527
27609
51
20
-
14552.5
27619
- 1
- Diagonal size of geometry's bounding box
- 8fe3d4fd-0f58-4b7a-8a93-086ba2ce3425
- true
- Dimension
- Dimension
- false
- 0
-
14527
27629
51
20
-
14552.5
27639
- 4d2a06bd-4b0f-4c65-9ee0-4220e4c01703
- Scale
- Scale an object uniformly in all directions.
- true
- 22249883-3dfd-42f2-938f-5dbb9209cffb
- true
- Scale
- Scale
-
14251
27550
191
64
-
14378
27582
- Base geometry
- add7ea7e-611e-4934-b67e-62bdab122d97
- true
- Geometry
- Geometry
- true
- 83c37836-d997-40ad-b3dd-9f1c8098cd80
- 1
-
14253
27552
113
20
-
14309.5
27562
- Center of scaling
- 15215e10-f506-4266-8884-84f12e90ff86
- true
- Center
- Center
- false
- 5be92eb5-02c1-4a50-802c-7ab01a573a0e
- 1
-
14253
27572
113
20
-
14309.5
27582
- 1
- 1
- {0}
-
0
0
0
- Scaling factor
- 9bb0c08c-8fbe-4370-9fac-438da46c2bd9
- true
- Factor
- Factor
- false
- 0
-
14253
27592
113
20
-
14309.5
27602
- 1
- 1
- {0}
- 0.33333333333333331
- Scaled geometry
- 02d977a4-4efe-4e2d-8407-51dd988709ae
- true
- Geometry
- Geometry
- false
- 0
-
14390
27552
50
30
-
14415
27567
- Transformation data
- 4354deec-6b6e-4a5c-b887-e54017812829
- true
- Transform
- Transform
- false
- 0
-
14390
27582
50
30
-
14415
27597
- deaf8653-5528-4286-807c-3de8b8dad781
- Surface
- Contains a collection of generic surfaces
- true
- fef8f6d8-5af6-4935-8408-78241f7e4d7b
- true
- Surface
- Surface
- false
- cbd6bf4a-bfcb-42e9-b3ba-b33cb2875e0a
- 1
-
14345
27436
50
24
-
14370.65
27448.02
- ba2d8f57-0738-42b4-b5a5-fe4d853517eb
- Deconstruct Mesh
- Deconstruct a mesh into its component parts.
- true
- 2b056227-09bd-4857-a416-66e816e2af0b
- true
- Deconstruct Mesh
- Deconstruct Mesh
-
14436
27437
97
84
-
14478
27479
- Base mesh
- 2f090a6d-532a-430f-aed9-fb570dbc2522
- true
- Mesh
- Mesh
- false
- c141638f-f968-4458-8a65-656377164c14
- 1
-
14438
27439
28
80
-
14452
27479
- 1
- Mesh vertices
- fd84477c-fe0f-4f05-9828-1aa854d22749
- true
- Vertices
- Vertices
- false
- 0
-
14490
27439
41
20
-
14510.5
27449
- 1
- Mesh faces
- 3a3c7504-af86-4050-b2f7-9453abe99352
- true
- Faces
- Faces
- false
- 0
-
14490
27459
41
20
-
14510.5
27469
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- 8bb07237-8043-4bfc-9482-36c5f324e171
- 99e87cc0-6a4b-442b-884b-8221f251b9bf
- 37da5568-8830-4120-984d-a49aa9cc6b49
- d992dcbb-ebd0-41d4-96b3-793a6c463864
- 72
- c841106e-9c38-4f8e-ab0b-0f61d5cb6dbd
- Group
- 3e8ca6be-fda8-4aaf-b5c0-3c54c8bb7312
- Number
- Contains a collection of floating point numbers
- b22d0187-dac5-4128-a6af-18259df683c4
- true
- Number
- Number
- false
- 82cdb6c5-d11c-4816-899a-ec7feeb75410
- 1
-
10006
-1986
50
24
-
10031.56
-1974.887
- 1
- 1
- {0}
- 1024
- aaa665bd-fd6e-4ccb-8d2c-c5b33072125d
- Curvature
- Evaluate the curvature of a curve at a specified parameter.
- true
- 392f2379-ad99-4bbb-b55c-4c4d0fd186f2
- true
- Curvature
- Curvature
-
9964
-2379
125
64
-
10028
-2347
- Curve to evaluate
- 0145d000-91b1-4ab9-bcfe-17c9d2e5d01e
- true
- Curve
- Curve
- false
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9966
-2377
50
30
-
9991
-2362
- Parameter on curve domain to evaluate
- 2b184f5f-60fe-48a2-84af-24f1707371c9
- true
- Parameter
- Parameter
- false
- 9b047484-149a-4c2c-bc3b-133bf8a16042
- 1
-
9966
-2347
50
30
-
9991
-2332
- Point on curve at {t}
- 27d02d99-f186-4f18-959f-fb55050714ad
- true
- Point
- Point
- false
- 0
-
10040
-2377
47
20
-
10063.5
-2367
- Curvature vector at {t}
- aeb40292-7614-4530-8cb6-cb15afc4abd7
- true
- Curvature
- Curvature
- false
- 0
-
10040
-2357
47
20
-
10063.5
-2347
- Curvature circle at {t}
- ac4108b8-b50c-4b2f-9d58-db3abf48d468
- true
- Curvature
- Curvature
- false
- 0
-
10040
-2337
47
20
-
10063.5
-2327
- 2162e72e-72fc-4bf8-9459-d4d82fa8aa14
- Divide Curve
- Divide a curve into equal length segments
- true
- 1c788573-d7bf-4f72-a121-cbf3b62252c6
- true
- Divide Curve
- Divide Curve
-
9965
-2293
123
64
-
10019
-2261
- Curve to divide
- 7bb740f1-89a7-41ba-908d-6172c795d802
- true
- Curve
- Curve
- false
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9967
-2291
40
20
-
9987
-2281
- Number of segments
- 31973aa3-a6c4-40e2-8334-3d5983744459
- true
- Count
- Count
- false
- 41d4fcae-5924-4999-8519-7d3c327b7aea
- 1
-
9967
-2271
40
20
-
9987
-2261
- 1
- 1
- {0}
- 32
- Split segments at kinks
- f686c8ca-6a0f-4056-b538-82d1db5c6c23
- true
- Kinks
- Kinks
- false
- 0
-
9967
-2251
40
20
-
9987
-2241
- 1
- 1
- {0}
- false
- 1
- Division points
- 6c829d37-82dc-4ac3-941d-503e2491d515
- true
- Points
- Points
- false
- 0
-
10031
-2291
55
20
-
10058.5
-2281
- 1
- Tangent vectors at division points
- 1c759179-d2dd-4f1d-8b1b-e5fb56023536
- true
- Tangents
- Tangents
- false
- 0
-
10031
-2271
55
20
-
10058.5
-2261
- 1
- Parameter values at division points
- 9b047484-149a-4c2c-bc3b-133bf8a16042
- true
- Parameters
- Parameters
- false
- 0
-
10031
-2251
55
20
-
10058.5
-2241
- d5967b9f-e8ee-436b-a8ad-29fdcecf32d5
- Curve
- Contains a collection of generic curves
- true
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- true
- Curve
- Curve
- false
- 506f2123-b521-4a52-9165-68e803a30009
- 1
-
10010
-811
50
24
-
10035.56
-799.8869
- 23862862-049a-40be-b558-2418aacbd916
- Deconstruct Arc
- Retrieve the base plane, radius and angle domain of an arc.
- true
- f3a56189-a559-47f2-af99-08d4a3d06a47
- true
- Deconstruct Arc
- Deconstruct Arc
-
9976
-2462
102
64
-
10010
-2430
- Arc or Circle to deconstruct
- 6cec1ee5-525e-453b-ad11-20021ffb74ad
- true
- Arc
- Arc
- false
- ac4108b8-b50c-4b2f-9d58-db3abf48d468
- 1
-
9978
-2460
20
60
-
9988
-2430
- Base plane of arc or circle
- b86f8283-6c12-49a0-bd2b-33920875eaa4
- true
- Base Plane
- Base Plane
- false
- 0
-
10022
-2460
54
20
-
10049
-2450
- Radius of arc or circle
- e440447f-77d2-4617-ba70-c50ae59a1c77
- true
- Radius
- Radius
- false
- 0
-
10022
-2440
54
20
-
10049
-2430
- Angle domain (in radians) of arc
- b91b85ff-7309-4c95-aa1c-b70e2d0d927c
- true
- Angle
- Angle
- false
- 0
-
10022
-2420
54
20
-
10049
-2410
- 797d922f-3a1d-46fe-9155-358b009b5997
- One Over X
- Compute one over x.
- true
- e5e088e3-6608-44e6-a7d7-7eb73fb9b2c8
- true
- One Over X
- One Over X
-
9983
-3051
88
28
-
10026
-3037
- Input value
- af3506ed-2063-459e-aa23-5a1fdc8a363f
- true
- Value
- Value
- false
- 2cd82ac7-4de3-4efd-b21c-bb675514f953
- 1
-
9985
-3049
29
24
-
9999.5
-3037
- Output value
- c1491a51-714b-4cb9-85b6-34a38ca75a1f
- true
- Result
- Result
- false
- 0
-
10038
-3049
31
24
-
10053.5
-3037
- 2b69bf71-4e69-43aa-b7be-4f6ce7e45bef
- Quick Graph
- 1
- Display a set of y-values as a graph
- 52fc7e98-c167-43e7-87c2-59064227472a
- true
- Quick Graph
- Quick Graph
- false
- 0
- 9ffa872c-e479-408b-8f5c-98a77c7ef2dd
- 1
-
9960
-3288
150
150
-
9960.564
-3287.887
- -1
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- c95358a1-3288-48df-a244-8bf7e0c6385d
- true
- Line
- Line
-
9976
-2987
102
44
-
10042
-2965
- Line start point
- dda79b74-b3e3-445d-8e48-4096cd5b33ec
- true
- Start Point
- Start Point
- false
- 27d02d99-f186-4f18-959f-fb55050714ad
- 1
-
9978
-2985
52
20
-
10004
-2975
- Line end point
- ebc36594-9c20-4f70-988a-0ab4624f67fd
- true
- End Point
- End Point
- false
- b86f8283-6c12-49a0-bd2b-33920875eaa4
- 1
-
9978
-2965
52
20
-
10004
-2955
- Line segment
- 7785f9df-f096-491f-964e-599a2aec932f
- true
- Line
- Line
- false
- 0
-
10054
-2985
22
40
-
10065
-2965
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
- 39e437ab-17e0-4324-8544-cb86abbc9e57
- true
- Line SDL
- Line SDL
-
9972
-4871
110
64
-
10046
-4839
- Line start point
- 41670e9e-038a-4b55-9192-201b8ad9b7af
- true
- Start
- Start
- false
- 27d02d99-f186-4f18-959f-fb55050714ad
- 1
-
9974
-4869
60
20
-
10012
-4859
- Line tangent (direction)
- 7a745369-90e9-483d-ae37-86261addbb34
- true
- Direction
- Direction
- false
- 2fcc79ac-e62a-4a44-84e2-59411080f035
- 1
-
9974
-4849
60
20
-
10012
-4839
- 1
- 1
- {0}
-
0
0
1
- Line length
- 8ebf383f-28be-4dbc-9a3f-e05ca0ef3e02
- -X
- true
- Length
- Length
- false
- 37bb12ea-34eb-418f-9b39-ae27a2fe2897
- 1
-
9974
-4829
60
20
-
10012
-4819
- 1
- 1
- {0}
- 1
- Line segment
- 2158b91e-623b-4f9d-8297-f4edb0d6540d
- true
- Line
- Line
- false
- 0
-
10058
-4869
22
60
-
10069
-4839
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- c6073d46-269e-471f-9961-e21811a07752
- true
- Evaluate Length
- Evaluate Length
-
9952
-5784
149
64
-
10037
-5752
- Curve to evaluate
- af95f296-ac3c-495a-9314-f578c0929d0c
- true
- Curve
- Curve
- false
- 88d2e234-202c-4e3b-adb8-c6bf7cc9988f
- 1
-
9954
-5782
71
20
-
9989.5
-5772
- Length factor for curve evaluation
- 082891a2-5a2f-4b4c-b46b-91e2da8ce77d
- true
- Length
- Length
- false
- 0
-
9954
-5762
71
20
-
9989.5
-5752
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 71ea8ef3-18b4-4e5c-ab66-8d3bbe633f6e
- true
- Normalized
- Normalized
- false
- 0
-
9954
-5742
71
20
-
9989.5
-5732
- 1
- 1
- {0}
- true
- Point at the specified length
- 58715e09-1461-47aa-b311-c9878cbef364
- true
- Point
- Point
- false
- 0
-
10049
-5782
50
20
-
10074
-5772
- Tangent vector at the specified length
- 78cd4516-cf88-4c55-b855-7036ef090b35
- true
- Tangent
- Tangent
- false
- 0
-
10049
-5762
50
20
-
10074
-5752
- Curve parameter at the specified length
- 0351b476-a056-45f8-868d-0f74aeb0b6bd
- true
- Parameter
- Parameter
- false
- 0
-
10049
-5742
50
20
-
10074
-5732
- 2b2a4145-3dff-41d4-a8de-1ea9d29eef33
- Interpolate
- Create an interpolated curve through a set of points.
- true
- 93569eee-4485-4e75-b081-b5a4f7d2e796
- true
- Interpolate
- Interpolate
-
9914
-6115
225
84
-
10087
-6073
- 1
- Interpolation points
- dde1eac0-839e-45a9-a2e5-3f21c6dc288e
- true
- Vertices
- Vertices
- false
- 043ef658-425b-4fc2-a0ed-57be30e7b117
- 1
-
9916
-6113
159
20
-
9995.5
-6103
- Curve degree
- 08e55262-47e4-4f8d-bebd-c3a698f87d4e
- true
- Degree
- Degree
- false
- 0
-
9916
-6093
159
20
-
9995.5
-6083
- 1
- 1
- {0}
- 1
- Periodic curve
- 2ad1ddf0-9cf3-4806-837a-41b2fddf6642
- true
- Periodic
- Periodic
- false
- 0
-
9916
-6073
159
20
-
9995.5
-6063
- 1
- 1
- {0}
- false
- Knot spacing (0=uniform, 1=chord, 2=sqrtchord)
- eae7757e-1299-4541-a34c-bcc676de11c9
- true
- KnotStyle
- KnotStyle
- false
- 0
-
9916
-6053
159
20
-
9995.5
-6043
- 1
- 1
- {0}
- 2
- Resulting nurbs curve
- 098a4c87-ff22-4643-a81f-d1664572e52a
- true
- Curve
- Curve
- false
- 0
-
10099
-6113
38
26
-
10118
-6099.667
- Curve length
- 54263cd0-b37d-47d9-868f-db90f9b3858d
- true
- Length
- Length
- false
- 0
-
10099
-6087
38
27
-
10118
-6073
- Curve domain
- ad91ff97-0733-42e1-ab10-73c9b30777cd
- true
- Domain
- Domain
- false
- 0
-
10099
-6060
38
27
-
10118
-6046.333
- 3e8ca6be-fda8-4aaf-b5c0-3c54c8bb7312
- Number
- Contains a collection of floating point numbers
- 9d77a9be-7ee4-404f-b9d9-0b021cd89431
- true
- Number
- Number
- false
- b22d0187-dac5-4128-a6af-18259df683c4
- 1
-
10010
-6145
50
24
-
10035.56
-6133.887
- d5967b9f-e8ee-436b-a8ad-29fdcecf32d5
- Curve
- Contains a collection of generic curves
- true
- 61019724-eb0d-4b80-ba89-1f6601b8fba6
- true
- Curve
- Curve
- false
- 098a4c87-ff22-4643-a81f-d1664572e52a
- 1
-
10010
-6242
50
24
-
10035.56
-6230.887
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 9ffa872c-e479-408b-8f5c-98a77c7ef2dd
- true
- Relay
-
- false
- c1491a51-714b-4cb9-85b6-34a38ca75a1f
- 1
-
10007
-3070
40
16
-
10027
-3062
- 76975309-75a6-446a-afed-f8653720a9f2
- Create Material
- Create an OpenGL material.
- true
- 09c6c5c2-7cc1-43ae-a3a3-04ac393041d8
- true
- Create Material
- Create Material
-
9951
-5631
152
104
-
10049
-5579
- Colour of the diffuse channel
- f7a4b8b1-069c-43a0-b602-1833de12db7e
- true
- Diffuse
- Diffuse
- false
- 0
-
9953
-5629
84
20
-
9995
-5619
- 1
- 1
- {0}
-
255;248;248;248
- Colour of the specular highlight
- 0cdf7eb3-a2e9-4b8c-80df-5796a2c42d29
- true
- Specular
- Specular
- false
- 0
-
9953
-5609
84
20
-
9995
-5599
- 1
- 1
- {0}
-
255;0;255;255
- Emissive colour of the material
- f9ec374b-4e7e-425e-80dc-7d1913f5d442
- true
- Emission
- Emission
- false
- 0
-
9953
-5589
84
20
-
9995
-5579
- 1
- 1
- {0}
-
255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
- 7d73c7ec-e469-48b9-9f6c-3af7d21e5a0a
- true
- Transparency
- Transparency
- false
- 0
-
9953
-5569
84
20
-
9995
-5559
- 1
- 1
- {0}
- 0.5
- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
- f29297e6-80ae-4e98-8057-425ad865e68a
- true
- Shine
- Shine
- false
- 0
-
9953
-5549
84
20
-
9995
-5539
- 1
- 1
- {0}
- 100
- Resulting material
- 1ce09a68-c1f4-44f0-990c-4d96308dc9e1
- true
- Material
- Material
- false
- 0
-
10061
-5629
40
100
-
10081
-5579
- 537b0419-bbc2-4ff4-bf08-afe526367b2c
- Custom Preview
- Allows for customized geometry previews
- true
- true
- e286f87e-7fc1-43eb-b9a4-a2366f90ae24
- true
- Custom Preview
- Custom Preview
-
9993
-5701
76
44
-
10055
-5679
- Geometry to preview
- true
- 366ececa-ed22-4724-b989-f09e6937697d
- true
- Geometry
- Geometry
- false
- 88d2e234-202c-4e3b-adb8-c6bf7cc9988f
- 1
-
9995
-5699
48
20
-
10019
-5689
- The material override
- 027c3144-be54-484e-975d-ce396e8b251f
- true
- Material
- Material
- false
- 1ce09a68-c1f4-44f0-990c-4d96308dc9e1
- 1
-
9995
-5679
48
20
-
10019
-5669
- 1
- 1
- {0}
-
255;221;160;221
-
255;66;48;66
- 0.5
-
255;255;255;255
- 0
- 76975309-75a6-446a-afed-f8653720a9f2
- Create Material
- Create an OpenGL material.
- true
- 3f7e06d6-03e2-4aa1-b86d-542eceeb31ee
- true
- Create Material
- Create Material
-
9951
-1711
152
104
-
10049
-1659
- Colour of the diffuse channel
- 7f94db8a-e3ab-4ce3-9b03-f3ec7b4f851b
- true
- Diffuse
- Diffuse
- false
- 0
-
9953
-1709
84
20
-
9995
-1699
- 1
- 1
- {0}
-
255;211;211;211
- Colour of the specular highlight
- 77a29782-5647-44c5-a815-16be8fea0af6
- true
- Specular
- Specular
- false
- 0
-
9953
-1689
84
20
-
9995
-1679
- 1
- 1
- {0}
-
255;0;255;255
- Emissive colour of the material
- 46d73d35-3d8f-4a3a-af59-d7f2aff6c5e4
- true
- Emission
- Emission
- false
- 0
-
9953
-1669
84
20
-
9995
-1659
- 1
- 1
- {0}
-
255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
- fa2a385c-186e-442f-8652-d241044e2bdc
- true
- Transparency
- Transparency
- false
- 0
-
9953
-1649
84
20
-
9995
-1639
- 1
- 1
- {0}
- 0.5
- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
- a1f22685-5539-4143-83f0-28d6fea1c703
- true
- Shine
- Shine
- false
- 0
-
9953
-1629
84
20
-
9995
-1619
- 1
- 1
- {0}
- 100
- Resulting material
- 71d2a512-f0b5-4c06-9af5-6682789399fe
- true
- Material
- Material
- false
- 0
-
10061
-1709
40
100
-
10081
-1659
- 537b0419-bbc2-4ff4-bf08-afe526367b2c
- Custom Preview
- Allows for customized geometry previews
- true
- true
- fd34a320-94b5-40d0-945e-128f98958485
- true
- Custom Preview
- Custom Preview
-
9998
-1797
76
44
-
10060
-1775
- Geometry to preview
- true
- e50fc350-2355-4f9b-a8ca-f8fa8ee0fe7a
- true
- Geometry
- Geometry
- false
- f1cb17b7-ee0e-49ec-95f6-e24ed89eb56e
- 1
-
10000
-1795
48
20
-
10024
-1785
- The material override
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10061
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- Draws Rhino Curvature Graphs.
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10059
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10059
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- Numeric Domain between the lowest and highest numbers in {N}
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11
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31
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11
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31
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- Line start point
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60
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- Line tangent (direction)
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60
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- Line
- Line
- false
- 0
-
10050
-8660
22
60
-
10061
-8630
- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
- true
- ba56bd15-a937-4134-b114-22288d1d8745
- true
- Relative Differences
- Relative Differences
-
9961
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116
28
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10008
-7273
- 1
- List of data to operate on (numbers or points or vectors allowed)
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- true
- Values
- Values
- false
- 647cbee9-b7ae-4ea0-b4ab-f4da190eb2bd
- 1
-
9963
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33
24
-
9979.5
-7273
- 1
- Differences between consecutive items
- 0184d168-0386-49c1-b31a-26709654c038
- true
- Differenced
- Differenced
- false
- 0
-
10020
-7285
55
24
-
10047.5
-7273
- f3230ecb-3631-4d6f-86f2-ef4b2ed37f45
- Replace Nulls
- Replace nulls or invalid data with other data
- true
- 0c7c7c95-97a7-4563-a12a-9563d31cdc34
- true
- Replace Nulls
- Replace Nulls
-
9949
-7231
139
44
-
10044
-7209
- 1
- Items to test for null
- 92822bb1-7769-409e-90a8-d85daeb55de3
- true
- Items
- Items
- false
- a977fbc0-84f5-4e43-95a7-67c5b348d463
- 1
-
9951
-7229
81
20
-
9991.5
-7219
- 1
- Items to replace nulls with
- b6e51378-6b06-427f-8abd-236f3c97756e
- true
- Replacements
- Replacements
- false
- 0
-
9951
-7209
81
20
-
9991.5
-7199
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- 1
- List without any nulls
- 647cbee9-b7ae-4ea0-b4ab-f4da190eb2bd
- true
- Items
- Items
- false
- 0
-
10056
-7229
30
20
-
10071
-7219
- Number of items replaced
- 08012c5f-2494-4280-8679-3550bc040d3c
- true
- Count
- Count
- false
- 0
-
10056
-7209
30
20
-
10071
-7199
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- a977fbc0-84f5-4e43-95a7-67c5b348d463
- true
- Relay
- false
- f220f792-98bc-4871-a83a-7b9f2394f7fa
- 1
-
9999
-7168
40
16
-
10019
-7160
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- d8ad52e1-09c5-4d42-8086-8d7eedd452d8
- true
- Relay
- false
- 738d8220-3b26-49b2-a359-0fc4d671538d
- 1
-
9999
-7532
40
16
-
10019
-7524
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- ba56bd15-a937-4134-b114-22288d1d8745
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- 8
- 706f98f7-dadc-407e-aa85-a18396faebd4
- Group
- 2dc44b22-b1dd-460a-a704-6462d6e91096
- Curve Closest Point
- Find the closest point on a curve.
- true
- 0ad77a74-a6cb-4ead-a94b-733d2c9648fe
- true
- Curve Closest Point
- Curve Closest Point
-
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108
64
-
10009
-7000
- Point to project onto curve
- 9f9c80fc-d00e-49c9-aa23-609fcda8695e
- true
- Point
- Point
- false
- a51b782b-6704-49a9-a51b-a4e396fdbaa4
- 1
-
9967
-7030
30
30
-
9982
-7015
- Curve to project onto
- 1f0af507-9f3d-4a49-8925-04e0ddea3f23
- true
- Curve
- Curve
- false
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9967
-7000
30
30
-
9982
-6985
- Point on the curve closest to the base point
- 799b4d40-43b5-4e1b-8362-dfbc12fe1f3d
- true
- Point
- Point
- false
- 0
-
10021
-7030
50
20
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10046
-7020
- Parameter on curve domain of closest point
- b1b7b290-2df9-4c62-9001-c4d1dc77bede
- true
- Parameter
- Parameter
- false
- 0
-
10021
-7010
50
20
-
10046
-7000
- Distance between base point and curve
- a28534e6-7bd6-4a36-9d3e-bb5a1b9cb155
- true
- Distance
- Distance
- false
- 0
-
10021
-6990
50
20
-
10046
-6980
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- a6dec17a-ad86-4475-a454-847e8c3add0f
- true
- Line
- Line
-
9968
-7111
102
44
-
10034
-7089
- Line start point
- afed6915-0771-412d-96c7-6bafa09d3ddf
- true
- Start Point
- Start Point
- false
- 799b4d40-43b5-4e1b-8362-dfbc12fe1f3d
- 1
-
9970
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52
20
-
9996
-7099
- Line end point
- cc4ad886-f221-460d-beac-56c0ec098608
- true
- End Point
- End Point
- false
- a51b782b-6704-49a9-a51b-a4e396fdbaa4
- 1
-
9970
-7089
52
20
-
9996
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- Line segment
- ab137ead-7ffb-4e8b-9d5f-8e28876ba368
- true
- Line
- Line
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- 0
-
10046
-7109
22
40
-
10057
-7089
- 2fcc2743-8339-4cdf-a046-a1f17439191d
- Remap Numbers
- Remap numbers into a new numeric domain
- true
- 1202f34c-896a-4a2d-ac18-9ccbbfba57ec
- true
- Remap Numbers
- Remap Numbers
-
9942
-8361
154
64
-
10042
-8329
- Value to remap
- 2f12ad4b-ffd7-4d3d-892a-515957d1d1e8
- true
- Value
- Value
- false
- 7ad3124c-8aa7-4d9e-a05a-104d04fdf956
- 1
-
9944
-8359
86
20
-
9987
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- Source domain
- d3b9dd7c-4d3a-465d-b521-55c5c3a19803
- true
- Source
- Source
- false
- dca02922-ac37-430b-ab22-78b94c55370c
- 1
-
9944
-8339
86
20
-
9987
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- 1
- 1
- {0}
-
0
1
- Target domain
- 1b8223da-d2b6-49bb-9fda-f21d22670fb8
- true
- Target
- Target
- false
- 0
-
9944
-8319
86
20
-
9987
-8309
- 1
- 1
- {0}
-
-1
1
- Remapped number
- f9dd94e6-cd65-4619-ac80-ec7ad7c99ca2
- true
- Mapped
- Mapped
- false
- 0
-
10054
-8359
40
30
-
10074
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- Remapped and clipped number
- b8acb2cb-0e9c-47b4-87f0-fc78fc8bc865
- true
- Clipped
- Clipped
- false
- 0
-
10054
-8329
40
30
-
10074
-8314
- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
- true
- f5f6654c-bc77-467b-ae7a-363002168987
- true
- Bounds
- Bounds
-
9964
-8279
110
28
-
10022
-8265
- 1
- Numbers to include in Bounds
- 5ed57d01-d537-4306-b31f-6151f7a5d7c8
- true
- Numbers
- Numbers
- false
- 7ad3124c-8aa7-4d9e-a05a-104d04fdf956
- 1
-
9966
-8277
44
24
-
9988
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- Numeric Domain between the lowest and highest numbers in {N}
- dca02922-ac37-430b-ab22-78b94c55370c
- true
- Domain
- Domain
- false
- 0
-
10034
-8277
38
24
-
10053
-8265
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 7ad3124c-8aa7-4d9e-a05a-104d04fdf956
- true
- Relay
-
- false
- d8ad52e1-09c5-4d42-8086-8d7eedd452d8
- 1
-
9999
-8232
40
16
-
10019
-8224
- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
- 73e68a66-19a6-4de3-9fcc-94a55a1fbaa4
- true
- Multiplication
- Multiplication
-
9984
-8560
70
44
-
10009
-8538
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for multiplication
- 3e91af86-ae95-49b4-953b-1bdca4876732
- true
- A
- A
- true
- e4d3ba31-7bee-4efb-bffa-c073df86d4b8
- 1
-
9986
-8558
11
20
-
9991.5
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- Second item for multiplication
- 9a426862-1a9b-404d-825b-aad499ea1646
- true
- B
- B
- true
- a2ddf12f-aac3-4d45-a4fd-5a6a2862a019
- 1
-
9986
-8538
11
20
-
9991.5
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- Result of multiplication
- ba7a7432-a3b0-454f-b76e-490efbfd84f3
- true
- Result
- Result
- false
- 0
-
10021
-8558
31
40
-
10036.5
-8538
- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
- 5c595042-09b7-49d2-adda-e05d7e0ccf7d
- true
- Multiplication
- Multiplication
-
9984
-8453
70
44
-
10009
-8431
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for multiplication
- fda3567e-9562-47c2-8605-514cda5fef2f
- true
- A
- A
- true
- 7bba4d57-4bbf-4cae-bfdb-38747fb81511
- 1
-
9986
-8451
11
20
-
9991.5
-8441
- Second item for multiplication
- 2215c049-122f-4dfe-adb8-13b71bbe179b
- true
- B
- B
- true
- f9dd94e6-cd65-4619-ac80-ec7ad7c99ca2
- 1
-
9986
-8431
11
20
-
9991.5
-8421
- Result of multiplication
- e4d3ba31-7bee-4efb-bffa-c073df86d4b8
- true
- Result
- Result
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- 0
-
10021
-8451
31
40
-
10036.5
-8431
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 7bba4d57-4bbf-4cae-bfdb-38747fb81511
- true
- Relay
- false
- 1a924b4b-4576-4ca9-9ace-b4586f3dbb90
- 1
-
9999
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40
16
-
10019
-8380
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 1202f34c-896a-4a2d-ac18-9ccbbfba57ec
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- 7ad3124c-8aa7-4d9e-a05a-104d04fdf956
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- 8
- 672143e1-403b-4ded-8245-a5967747a93d
- Group
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 14abf694-ab0d-4e9c-b615-17422f37db8b
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- a6dec17a-ad86-4475-a454-847e8c3add0f
- 4
- bc096874-68c9-4da7-b04d-87346ea2cee9
- Group
- 59e0b89a-e487-49f8-bab8-b5bab16be14c
- Panel
- A panel for custom notes and text values
- 7a24aebb-8515-494f-8357-62a3079f181f
- true
- Panel
- false
- 1
- e96b0bfa-693f-4be8-bcb4-c9e4a7df9692
- 1
- Double click to edit panel content…
-
9933
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185
271
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- 0
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9933.656
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-
255;255;255;255
- true
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- true
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- false
- true
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 38446e0f-6c71-47e9-8fe3-b81bd1b80646
- true
- Relay
-
- false
- 7a24aebb-8515-494f-8357-62a3079f181f
- 1
-
9999
-8027
40
16
-
10019
-8019
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- dd7ae928-e56d-4423-b7b1-b1999182a279
- true
- Relay
-
- false
- d8ad52e1-09c5-4d42-8086-8d7eedd452d8
- 1
-
9999
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40
16
-
10019
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- a7f4eade-848d-4816-aec1-6be410ac9ba9
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- 6
- fe28ddfd-a038-4308-ba76-4dd1ef8d6ca0
- Group
- 76975309-75a6-446a-afed-f8653720a9f2
- Create Material
- Create an OpenGL material.
- true
- d060375d-95b6-4631-b2a4-f7b036781fcd
- true
- Create Material
- Create Material
-
9943
-9356
152
104
-
10041
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- Colour of the diffuse channel
- 2d1e7797-e9d1-46b9-afbd-27fd6de8a97f
- true
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- 0
-
9945
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84
20
-
9987
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- 1
- 1
- {0}
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255;244;244;244
- Colour of the specular highlight
- 1140464e-8ea2-45d8-9e4f-39a4792d8bdc
- true
- Specular
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- 0
-
9945
-9334
84
20
-
9987
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- 1
- 1
- {0}
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255;0;255;255
- Emissive colour of the material
- 2a2fd82c-a2fa-42d6-bd2b-bb6492d92296
- true
- Emission
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- false
- 0
-
9945
-9314
84
20
-
9987
-9304
- 1
- 1
- {0}
-
255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
- 601976f0-0074-4c86-95a3-8af8555efda2
- true
- Transparency
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- false
- 0
-
9945
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84
20
-
9987
-9284
- 1
- 1
- {0}
- 0.5
- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
- 36c9195d-3653-493d-96ae-18ee92edf3c1
- true
- Shine
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- false
- 0
-
9945
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84
20
-
9987
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- 1
- 1
- {0}
- 100
- Resulting material
- a60dfd82-1200-461e-adaa-dbe168e52b95
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- 0
-
10053
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40
100
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10073
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- 537b0419-bbc2-4ff4-bf08-afe526367b2c
- Custom Preview
- Allows for customized geometry previews
- true
- true
- e6ab2132-8ade-4cd0-9f86-7b003f496cc3
- true
- Custom Preview
- Custom Preview
-
9975
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76
44
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10037
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- Geometry to preview
- true
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-
9977
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48
20
-
10001
-9413
- The material override
- 7e020275-8c13-4ab0-a818-f4fdb783efa4
- true
- Material
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- a60dfd82-1200-461e-adaa-dbe168e52b95
- 1
-
9977
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48
20
-
10001
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- {0}
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255;221;160;221
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255;66;48;66
- 0.5
-
255;255;255;255
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- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- Evaluate Length
- Evaluate Length
-
9944
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149
64
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10029
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- Curve to evaluate
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- f05ffc93-07b8-46d2-ad82-99badcc3922f
- 1
-
9946
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71
20
-
9981.5
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- Length factor for curve evaluation
- e5fe91f6-0639-499c-a4ae-9f0c0eef4a2a
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- Length
- Length
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- 0
-
9946
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71
20
-
9981.5
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- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- c6059186-4abf-464e-99f3-ca462b937ada
- true
- Normalized
- Normalized
- false
- 0
-
9946
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71
20
-
9981.5
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- 1
- 1
- {0}
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- Point at the specified length
- a87341fb-0950-4665-a5d5-5556809dce9d
- true
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- Point
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- 0
-
10041
-9513
50
20
-
10066
-9503
- Tangent vector at the specified length
- b0640b2b-fc07-469f-95b9-20a0b867fcf3
- true
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- Tangent
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10041
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50
20
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10066
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- Curve parameter at the specified length
- 90ffd65c-887d-4d73-87af-fb935a6fbc19
- true
- Parameter
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- false
- 0
-
10041
-9473
50
20
-
10066
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- 2b2a4145-3dff-41d4-a8de-1ea9d29eef33
- Interpolate
- Create an interpolated curve through a set of points.
- true
- cfada4df-fc13-404d-af10-950fb721cf37
- true
- Interpolate
- Interpolate
-
9906
-9860
225
84
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10079
-9818
- 1
- Interpolation points
- e1f121b0-c3d0-409b-89ff-8cb96cb037a7
- true
- Vertices
- Vertices
- false
- 2b484d46-7738-42ff-b212-eea1c16c05f0
- 1
-
9908
-9858
159
20
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9987.5
-9848
- Curve degree
- 11c02992-98fc-4278-a08e-21233b0cef25
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- Degree
- Degree
- false
- 0
-
9908
-9838
159
20
-
9987.5
-9828
- 1
- 1
- {0}
- 1
- Periodic curve
- f2376d2e-d76c-48b7-b6a0-e908aeff42b7
- true
- Periodic
- Periodic
- false
- 0
-
9908
-9818
159
20
-
9987.5
-9808
- 1
- 1
- {0}
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- Knot spacing (0=uniform, 1=chord, 2=sqrtchord)
- f319176f-add3-4804-aa1c-0e23c6e43d87
- true
- KnotStyle
- KnotStyle
- false
- 0
-
9908
-9798
159
20
-
9987.5
-9788
- 1
- 1
- {0}
- 2
- Resulting nurbs curve
- c32bd525-2467-45e9-a83b-330bd9f9b05a
- true
- Curve
- Curve
- false
- 0
-
10091
-9858
38
26
-
10110
-9844.667
- Curve length
- f39a78be-73dd-47e2-b61e-cac29e40317a
- true
- Length
- Length
- false
- 0
-
10091
-9832
38
27
-
10110
-9818
- Curve domain
- 7beff1f3-362b-4581-bc57-306a4c7dd5c0
- true
- Domain
- Domain
- false
- 0
-
10091
-9805
38
27
-
10110
-9791.334
- 76975309-75a6-446a-afed-f8653720a9f2
- Create Material
- Create an OpenGL material.
- true
- 7294d388-125f-481f-a647-b6308d54f922
- true
- Create Material
- Create Material
-
9943
-9997
152
104
-
10041
-9945
- Colour of the diffuse channel
- 207b8415-27f7-42c6-8c64-3adb873fcfd8
- true
- Diffuse
- Diffuse
- false
- 0
-
9945
-9995
84
20
-
9987
-9985
- 1
- 1
- {0}
-
255;219;219;219
- Colour of the specular highlight
- 21f309d1-3695-49b0-a4d9-fec85b3b39da
- true
- Specular
- Specular
- false
- 0
-
9945
-9975
84
20
-
9987
-9965
- 1
- 1
- {0}
-
255;0;255;255
- Emissive colour of the material
- 6f9a8ba2-dd2e-4732-95dd-5d9316fff397
- true
- Emission
- Emission
- false
- 0
-
9945
-9955
84
20
-
9987
-9945
- 1
- 1
- {0}
-
255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
- e715ae77-2790-4464-a60f-20723da9f4a8
- true
- Transparency
- Transparency
- false
- 0
-
9945
-9935
84
20
-
9987
-9925
- 1
- 1
- {0}
- 0.5
- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
- 7ce4fc74-7bad-4ffe-8f64-8bef1035495d
- true
- Shine
- Shine
- false
- 0
-
9945
-9915
84
20
-
9987
-9905
- 1
- 1
- {0}
- 100
- Resulting material
- 6836f515-706a-4c69-8769-5d7de637fb53
- true
- Material
- Material
- false
- 0
-
10053
-9995
40
100
-
10073
-9945
- 537b0419-bbc2-4ff4-bf08-afe526367b2c
- Custom Preview
- Allows for customized geometry previews
- true
- true
- 1b4bdbab-a9a8-46a5-9b85-fb462a146f44
- true
- Custom Preview
- Custom Preview
-
9969
-10068
76
44
-
10031
-10046
- Geometry to preview
- true
- fcfbcdbe-cf60-4a0a-a572-9be6f997c1c5
- true
- Geometry
- Geometry
- false
- c32bd525-2467-45e9-a83b-330bd9f9b05a
- 1
-
9971
-10066
48
20
-
9995
-10056
- The material override
- d553ab6a-7371-4cea-9568-4cd00d85c970
- true
- Material
- Material
- false
- 6836f515-706a-4c69-8769-5d7de637fb53
- 1
-
9971
-10046
48
20
-
9995
-10036
- 1
- 1
- {0}
-
255;221;160;221
-
255;66;48;66
- 0.5
-
255;255;255;255
- 0
- 2b69bf71-4e69-43aa-b7be-4f6ce7e45bef
- Quick Graph
- 1
- Display a set of y-values as a graph
- 56af251d-3d47-4643-b347-7bf5b002ee75
- true
- Quick Graph
- Quick Graph
- false
- 0
- dd7ae928-e56d-4423-b7b1-b1999182a279
- 1
-
9951
-8189
150
150
-
9951.656
-8189
- -1
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- cbfa1cea-d734-412a-9be0-6401ec23dd98
- 31841e7d-30a7-4a57-896b-1f20e5587acb
- b6ffc56a-73f4-47f7-8437-21b6159fbd45
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- 413b9ac5-2c61-4259-ac47-0a6f9a2858bb
- Group
- afb96615-c59a-45c9-9cac-e27acb1c7ca0
- Explode
- Explode a curve into smaller segments.
- true
- cbfa1cea-d734-412a-9be0-6401ec23dd98
- true
- Explode
- Explode
-
9952
-10388
134
44
-
10023
-10366
- Curve to explode
- 43baeead-f9c8-47f2-9c89-0a396d14aebd
- true
- Curve
- Curve
- false
- c32bd525-2467-45e9-a83b-330bd9f9b05a
- 1
-
9954
-10386
57
20
-
9982.5
-10376
- Recursive decomposition until all segments are atomic
- 94640383-7f38-4060-b9ca-a1cfe4f88fda
- true
- Recursive
- Recursive
- false
- 0
-
9954
-10366
57
20
-
9982.5
-10356
- 1
- 1
- {0}
- true
- 1
- Exploded segments that make up the base curve
- 657f9a26-0555-40a8-85a2-d714bd1df761
- true
- Segments
- Segments
- false
- 0
-
10035
-10386
49
20
-
10059.5
-10376
- 1
- Vertices of the exploded segments
- 809ed96a-10d8-4c3a-a4a0-e57d4943e734
- true
- Vertices
- Vertices
- false
- 0
-
10035
-10366
49
20
-
10059.5
-10356
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 31841e7d-30a7-4a57-896b-1f20e5587acb
- true
- Evaluate Length
- Evaluate Length
-
9944
-10471
149
64
-
10029
-10439
- Curve to evaluate
- 4a600545-9fa4-4f1d-bfe0-9bb880d0bed0
- true
- Curve
- Curve
- false
- 657f9a26-0555-40a8-85a2-d714bd1df761
- 1
-
9946
-10469
71
20
-
9981.5
-10459
- Length factor for curve evaluation
- 927fd2cf-9764-4e69-adbf-4969e5523072
- true
- Length
- Length
- false
- 0
-
9946
-10449
71
20
-
9981.5
-10439
- 1
- 1
- {0}
- 0.5
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 9a25c2b8-5a3c-4040-be32-e1f6587022ee
- true
- Normalized
- Normalized
- false
- 0
-
9946
-10429
71
20
-
9981.5
-10419
- 1
- 1
- {0}
- true
- Point at the specified length
- 88e80ba7-d7e1-4739-8bc9-2649e0568988
- true
- Point
- Point
- false
- 0
-
10041
-10469
50
20
-
10066
-10459
- Tangent vector at the specified length
- 74a893b0-4992-4e9e-8839-51defc56f76b
- true
- Tangent
- Tangent
- false
- 0
-
10041
-10449
50
20
-
10066
-10439
- Curve parameter at the specified length
- 572b8234-c8fb-4fcc-b7ec-a320da596eeb
- true
- Parameter
- Parameter
- false
- 0
-
10041
-10429
50
20
-
10066
-10419
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
- b6ffc56a-73f4-47f7-8437-21b6159fbd45
- true
- Line SDL
- Line SDL
-
9964
-12191
110
64
-
10038
-12159
- Line start point
- c9666999-2358-4b17-8320-a71d84c28fa9
- true
- Start
- Start
- false
- 88e80ba7-d7e1-4739-8bc9-2649e0568988
- 1
-
9966
-12189
60
20
-
10004
-12179
- Line tangent (direction)
- 2f910283-5649-449c-be0c-b136a4148d2e
- true
- Direction
- Direction
- false
- 509ce120-a6c6-472d-a7ba-325df3973ff0
- 1
-
9966
-12169
60
20
-
10004
-12159
- 1
- 1
- {0}
-
0
0
1
- Line length
- 3f7a29c7-d6dd-43e5-a2bc-9d2174148239
- ABS(X)
- true
- Length
- Length
- false
- 9f9eae92-60c1-4f4c-87f5-b8931d6fd9c9
- 1
-
9966
-12149
60
20
-
10004
-12139
- 1
- 1
- {0}
- 0.015625
- Line segment
- f0c191c1-9621-4bbc-8f42-70fddab36b4d
- true
- Line
- Line
- false
- 0
-
10050
-12189
22
60
-
10061
-12159
- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
- true
- d78b1c8d-4c32-45a1-9cd0-3f1c128e80c8
- true
- Relative Differences
- Relative Differences
-
9961
-10814
116
28
-
10008
-10800
- 1
- List of data to operate on (numbers or points or vectors allowed)
- 762d66b9-1570-4d0e-934f-ad1eb4519fa1
- true
- Values
- Values
- false
- 36b3a4ab-79e8-4ae2-bcf6-59f01b423655
- 1
-
9963
-10812
33
24
-
9979.5
-10800
- 1
- Differences between consecutive items
- 7338c244-af88-4723-b45a-08577283c18b
- true
- Differenced
- Differenced
- false
- 0
-
10020
-10812
55
24
-
10047.5
-10800
- f3230ecb-3631-4d6f-86f2-ef4b2ed37f45
- Replace Nulls
- Replace nulls or invalid data with other data
- true
- 60ac2b1a-ed32-485c-b398-5132c0ce38c7
- true
- Replace Nulls
- Replace Nulls
-
9949
-10758
139
44
-
10044
-10736
- 1
- Items to test for null
- 8b748710-2523-4d4d-a9f8-7949b3dbbaec
- true
- Items
- Items
- false
- 55a89bb9-1cb3-4508-a64e-593c4f56d389
- 1
-
9951
-10756
81
20
-
9991.5
-10746
- 1
- Items to replace nulls with
- 78bf5914-83e2-4bf8-abe7-ef8d3f6c72a5
- true
- Replacements
- Replacements
- false
- 0
-
9951
-10736
81
20
-
9991.5
-10726
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- 1
- List without any nulls
- 36b3a4ab-79e8-4ae2-bcf6-59f01b423655
- true
- Items
- Items
- false
- 0
-
10056
-10756
30
20
-
10071
-10746
- Number of items replaced
- f2ac4a82-0586-43fd-ac95-daa25658f827
- true
- Count
- Count
- false
- 0
-
10056
-10736
30
20
-
10071
-10726
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 55a89bb9-1cb3-4508-a64e-593c4f56d389
- true
- Relay
- false
- d8ad52e1-09c5-4d42-8086-8d7eedd452d8
- 1
-
9999
-10695
40
16
-
10019
-10687
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 7054797c-3a92-4321-8597-127654b4ca6c
- true
- Relay
- false
- 95512bec-3e3b-4a1e-968f-fdd54a0ed3fb
- 1
-
9999
-11059
40
16
-
10019
-11051
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- d78b1c8d-4c32-45a1-9cd0-3f1c128e80c8
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- 8
- a7355444-5015-436e-931d-6d44c0532770
- Group
- 2dc44b22-b1dd-460a-a704-6462d6e91096
- Curve Closest Point
- Find the closest point on a curve.
- true
- dc265006-688d-45d2-a2b8-861a06b4a669
- true
- Curve Closest Point
- Curve Closest Point
-
9965
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108
64
-
10009
-10527
- Point to project onto curve
- 59eb5142-8d20-4b58-9832-b73d38c01f5e
- true
- Point
- Point
- false
- 88e80ba7-d7e1-4739-8bc9-2649e0568988
- 1
-
9967
-10557
30
30
-
9982
-10542
- Curve to project onto
- 4e26aed9-39d5-4a12-91ee-5be2f0b044cb
- true
- Curve
- Curve
- false
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9967
-10527
30
30
-
9982
-10512
- Point on the curve closest to the base point
- 40443f53-c592-445e-a339-a109be0a51bb
- true
- Point
- Point
- false
- 0
-
10021
-10557
50
20
-
10046
-10547
- Parameter on curve domain of closest point
- a0713c1c-c26e-441e-93b3-f8edf5c233b2
- true
- Parameter
- Parameter
- false
- 0
-
10021
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50
20
-
10046
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- Distance between base point and curve
- b2882fd2-b8b7-4172-8f26-363ace0aa2a4
- true
- Distance
- Distance
- false
- 0
-
10021
-10517
50
20
-
10046
-10507
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- a4a2e4fe-4294-43c1-8033-d508439ba3f1
- true
- Line
- Line
-
9968
-10638
102
44
-
10034
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- Line start point
- 223c6b86-f150-4be0-be87-6066ca661b45
- true
- Start Point
- Start Point
- false
- 40443f53-c592-445e-a339-a109be0a51bb
- 1
-
9970
-10636
52
20
-
9996
-10626
- Line end point
- 9b417723-48ba-4f1a-a0a5-971d61bf310e
- true
- End Point
- End Point
- false
- 88e80ba7-d7e1-4739-8bc9-2649e0568988
- 1
-
9970
-10616
52
20
-
9996
-10606
- Line segment
- 509ce120-a6c6-472d-a7ba-325df3973ff0
- true
- Line
- Line
- false
- 0
-
10046
-10636
22
40
-
10057
-10616
- 2fcc2743-8339-4cdf-a046-a1f17439191d
- Remap Numbers
- Remap numbers into a new numeric domain
- true
- 1dc07ac1-cc4d-41b1-9a13-a43c87efcff3
- true
- Remap Numbers
- Remap Numbers
-
9942
-11889
154
64
-
10042
-11857
- Value to remap
- 4388d5aa-717b-4e61-958d-f0267b4a896b
- true
- Value
- Value
- false
- ef3c8bc1-7cba-4c60-9fcc-d378b603bd10
- 1
-
9944
-11887
86
20
-
9987
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- Source domain
- 6255db04-e743-411d-bd22-b9b95f602d3c
- true
- Source
- Source
- false
- 94bf725f-3745-4e94-93fa-23d17c538a20
- 1
-
9944
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86
20
-
9987
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- 1
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-
0
1
- Target domain
- 5c9dd6aa-a9b2-4bb6-bf8c-c95a44b4a77b
- true
- Target
- Target
- false
- 0
-
9944
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86
20
-
9987
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- 1
- 1
- {0}
-
-1
1
- Remapped number
- 7fde5602-5527-4b53-9098-bc2f764c30ec
- true
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- Mapped
- false
- 0
-
10054
-11887
40
30
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10074
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- Group
- afb96615-c59a-45c9-9cac-e27acb1c7ca0
- Explode
- Explode a curve into smaller segments.
- true
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- true
- Explode
- Explode
-
9952
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134
44
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10023
-13786
- Curve to explode
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- Curve
- Curve
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- 1
-
9954
-13806
57
20
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9982.5
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- Recursive decomposition until all segments are atomic
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- Recursive
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- 0
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9954
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57
20
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9982.5
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- 1
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- 1
- Exploded segments that make up the base curve
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- Segments
- false
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10035
-13806
49
20
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10059.5
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- Vertices of the exploded segments
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- Vertices
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10035
-13786
49
20
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10059.5
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- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 7b233811-8adf-47e6-9487-409c1062dec0
- true
- Evaluate Length
- Evaluate Length
-
9944
-13891
149
64
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10029
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- Curve to evaluate
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- Curve
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9946
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71
20
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9981.5
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- Length factor for curve evaluation
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- true
- Length
- Length
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- 0
-
9946
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71
20
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9981.5
-13859
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Normalized
- Normalized
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9946
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71
20
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9981.5
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- Point at the specified length
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- Point
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10041
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50
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10066
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- Tangent vector at the specified length
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- Tangent
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10041
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50
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10066
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- Curve parameter at the specified length
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- Parameter
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10041
-13849
50
20
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10066
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- Line SDL
- Create a line segment defined by start point, tangent and length.}
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- true
- Line SDL
- Line SDL
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9964
-15757
110
64
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10038
-15725
- Line start point
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- Start
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9966
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60
20
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10004
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- Line tangent (direction)
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- Direction
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9966
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60
20
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10004
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0
0
1
- Line length
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- ABS(X)
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- Length
- Length
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9966
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60
20
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10004
-15705
- 1
- 1
- {0}
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- Line segment
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- Line
- Line
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10050
-15755
22
60
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10061
-15725
- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
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- true
- Relative Differences
- Relative Differences
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9961
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116
28
-
10008
-14220
- 1
- List of data to operate on (numbers or points or vectors allowed)
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- Values
- Values
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-
9963
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33
24
-
9979.5
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- Differences between consecutive items
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- 0
-
10020
-14232
55
24
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10047.5
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- Replace Nulls
- Replace nulls or invalid data with other data
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- Replace Nulls
- Replace Nulls
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9949
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139
44
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10044
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- Items to test for null
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- Items
- Items
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-
9951
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81
20
-
9991.5
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- 1
- Items to replace nulls with
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- 0
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9951
-14156
81
20
-
9991.5
-14146
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- 1
- List without any nulls
- 472f4653-0d63-489f-aa1e-78a685ed3cd5
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- Items
- Items
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- 0
-
10056
-14176
30
20
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10071
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- Number of items replaced
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- Count
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- 0
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10056
-14156
30
20
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10071
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- Relay
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- A wire relay object
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- Relay
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-
9999
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40
16
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10019
-14107
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
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- A wire relay object
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9999
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40
16
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10019
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- Group
- 1
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255;255;255;255
- A group of Grasshopper objects
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- Group
- 2dc44b22-b1dd-460a-a704-6462d6e91096
- Curve Closest Point
- Find the closest point on a curve.
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- Curve Closest Point
- Curve Closest Point
-
9965
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108
64
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10009
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- Point to project onto curve
- eb35bf93-9f3b-47cb-88b9-37c7e236dd69
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- Point
- Point
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- 6e7b083f-f8f4-48fb-852b-f44d90379368
- 1
-
9967
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30
30
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9982
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- Curve to project onto
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- Curve
- Curve
- false
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9967
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30
30
-
9982
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- Point on the curve closest to the base point
- 2d839212-b8d4-4812-98d8-b6368d1ce218
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- Point
- Point
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- 0
-
10021
-13977
50
20
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10046
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- Parameter on curve domain of closest point
- 3c21d431-d450-4778-9e83-e0e5c534de56
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- Parameter
- Parameter
- false
- 0
-
10021
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50
20
-
10046
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- Distance between base point and curve
- 8ee23322-d45f-45c7-a334-0d6117e065d5
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- Distance
- Distance
- false
- 0
-
10021
-13937
50
20
-
10046
-13927
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- e95f78aa-eafb-4329-9993-de6cbe543737
- true
- Line
- Line
-
9968
-14058
102
44
-
10034
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- Line start point
- 85df0df4-eafa-4d92-af84-501c0c3f6b89
- true
- Start Point
- Start Point
- false
- 2d839212-b8d4-4812-98d8-b6368d1ce218
- 1
-
9970
-14056
52
20
-
9996
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- Line end point
- 4f8840e6-cde4-4eeb-82fd-27ff532598eb
- true
- End Point
- End Point
- false
- 6e7b083f-f8f4-48fb-852b-f44d90379368
- 1
-
9970
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52
20
-
9996
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- Line segment
- a43ca145-0b7a-4245-a9fd-9ee3155f0628
- true
- Line
- Line
- false
- 0
-
10046
-14056
22
40
-
10057
-14036
- 2fcc2743-8339-4cdf-a046-a1f17439191d
- Remap Numbers
- Remap numbers into a new numeric domain
- true
- 659f6427-1e0c-4b4a-b76b-5960c7fe394d
- true
- Remap Numbers
- Remap Numbers
-
9942
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154
64
-
10042
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- Value to remap
- babfbfbd-b943-43e7-94d0-48b810e96707
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- Value
- Value
- false
- b1f209e2-7620-47ec-8679-406efde82380
- 1
-
9944
-15453
86
20
-
9987
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- Source domain
- 7e5a984f-1c76-4f46-9bac-02510837c41c
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- Source
- Source
- false
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- 1
-
9944
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86
20
-
9987
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- 1
- 1
- {0}
-
0
1
- Target domain
- aaa645f7-2720-4872-bd9c-becfeabba234
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- Target
- Target
- false
- 0
-
9944
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86
20
-
9987
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- 1
- 1
- {0}
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-1
1
- Remapped number
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- Mapped
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-
10054
-15453
40
30
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10074
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- Remapped and clipped number
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- Clipped
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- 0
-
10054
-15423
40
30
-
10074
-15408
- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
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- 8999696a-74f0-4557-97f6-38fc25e0e737
- true
- Bounds
- Bounds
-
9964
-15373
110
28
-
10022
-15359
- 1
- Numbers to include in Bounds
- d965d7d1-9aee-406b-93c4-18f3199264c5
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- Numbers
- Numbers
- false
- b1f209e2-7620-47ec-8679-406efde82380
- 1
-
9966
-15371
44
24
-
9988
-15359
- Numeric Domain between the lowest and highest numbers in {N}
- d6f9116b-a2e0-49bb-840d-45e874d72f8e
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- Domain
- Domain
- false
- 0
-
10034
-15371
38
24
-
10053
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- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- b1f209e2-7620-47ec-8679-406efde82380
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- Relay
-
- false
- bfc69fd4-c68c-40ea-b4e6-b6f9c5550d3e
- 1
-
9999
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40
16
-
10019
-15318
- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
- 2dbc970d-71e3-4f0d-8142-558c895fcd12
- true
- Multiplication
- Multiplication
-
9984
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70
44
-
10009
-15632
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for multiplication
- a4c5348c-e748-41ef-98ab-8ce70441ac52
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- A
- A
- true
- 6a969140-0075-4523-a327-0427abb39edd
- 1
-
9986
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11
20
-
9991.5
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- Second item for multiplication
- a60361f7-90d9-488c-8408-62be9d12b55a
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- B
- B
- true
- a2ddf12f-aac3-4d45-a4fd-5a6a2862a019
- 1
-
9986
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11
20
-
9991.5
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- Result of multiplication
- 25faccb1-b1d4-451a-8577-baa88375614a
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- Result
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- 0
-
10021
-15652
31
40
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10036.5
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- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
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- Multiplication
- Multiplication
-
9984
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70
44
-
10009
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- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for multiplication
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- A
- A
- true
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- 1
-
9986
-15524
11
20
-
9991.5
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- Second item for multiplication
- 7f19a3fd-9268-4d35-923b-1f1b4d34063d
- true
- B
- B
- true
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- 1
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9986
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11
20
-
9991.5
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- Result of multiplication
- 6a969140-0075-4523-a327-0427abb39edd
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- 0
-
10021
-15524
31
40
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10036.5
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- Relay
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- A wire relay object
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9999
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40
16
-
10019
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Group
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Panel
- A panel for custom notes and text values
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- Double click to edit panel content…
-
9933
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185
271
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9933.656
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255;255;255;255
- true
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- Relay
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- A wire relay object
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- Relay
-
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- cc56ef11-96b9-4530-972f-8cbc81a613c9
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-
9999
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40
16
-
10019
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- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
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- A wire relay object
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- Relay
-
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-
9999
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40
16
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10019
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Group
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- Create Material
- Create an OpenGL material.
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- Create Material
- Create Material
-
9943
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152
104
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10041
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- Colour of the diffuse channel
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- Diffuse
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9945
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84
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9987
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255;236;236;236
- Colour of the specular highlight
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- true
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- Specular
- false
- 0
-
9945
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84
20
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9987
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255;0;255;255
- Emissive colour of the material
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- Emission
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-
9945
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84
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9987
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255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
- c9f6e496-b903-45b9-8a99-d21e70ba539f
- true
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- Transparency
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- 0
-
9945
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84
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9987
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- 1
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- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
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- Shine
- false
- 0
-
9945
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84
20
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9987
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- 1
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- Resulting material
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- Material
- Material
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-
10053
-16475
40
100
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10073
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- 537b0419-bbc2-4ff4-bf08-afe526367b2c
- Custom Preview
- Allows for customized geometry previews
- true
- true
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- Custom Preview
- Custom Preview
-
9981
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76
44
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10043
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- Geometry to preview
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- Geometry
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9983
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48
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10007
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- The material override
- 2bc8915f-ffa9-4d17-ba15-fec42d891d00
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- Material
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- e1aab404-042d-4716-b005-688a9ca6723e
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9983
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48
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10007
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255;221;160;221
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255;66;48;66
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-
255;255;255;255
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- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
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- Evaluate Length
- Evaluate Length
-
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149
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10029
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- Curve to evaluate
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-
9946
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71
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9981.5
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- Length factor for curve evaluation
- d5c9ef82-210b-431c-8664-0c3a001c526d
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- Length
- Length
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- 0
-
9946
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71
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9981.5
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- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Normalized
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9946
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71
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9981.5
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- Point at the specified length
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- 0
-
10041
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50
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10066
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- Tangent vector at the specified length
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- Tangent
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-
10041
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50
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10066
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- Curve parameter at the specified length
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- 0
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10041
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50
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10066
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- Interpolate
- Create an interpolated curve through a set of points.
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- Interpolate
- Interpolate
-
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225
84
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9908
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159
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- Curve degree
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- Degree
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9908
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159
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9987.5
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9908
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159
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9987.5
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- Knot spacing (0=uniform, 1=chord, 2=sqrtchord)
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9908
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159
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9987.5
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- 1
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- Resulting nurbs curve
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10091
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10110
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- Length
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10091
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38
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10110
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10091
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38
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10110
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- Create an OpenGL material.
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- Create Material
-
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152
104
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10041
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9945
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84
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9987
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255;211;211;211
- Colour of the specular highlight
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9945
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84
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9987
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255;0;255;255
- Emissive colour of the material
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9945
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84
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9987
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255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
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9945
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84
20
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9987
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9945
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84
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9987
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10053
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40
100
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10073
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- Allows for customized geometry previews
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- true
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- Custom Preview
-
9981
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76
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10043
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9983
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48
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10007
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9983
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48
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10007
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255;221;160;221
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255;66;48;66
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255;255;255;255
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- Display a set of y-values as a graph
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150
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255;255;255;255
- A group of Grasshopper objects
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- Explode
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134
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57
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9954
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- Exploded segments that make up the base curve
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10035
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10035
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49
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- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
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- Evaluate Length
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149
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- Curve to evaluate
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71
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- Length factor for curve evaluation
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9946
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71
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9981.5
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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9946
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71
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50
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10041
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10041
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50
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- Line SDL
- Line SDL
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9966
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60
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10004
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- Line segment
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10050
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22
60
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10061
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- dd17d442-3776-40b3-ad5b-5e188b56bd4c
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- Compute relative differences for a list of data
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- Relative Differences
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10008
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- List of data to operate on (numbers or points or vectors allowed)
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33
24
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55
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- Replace nulls or invalid data with other data
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- Replace Nulls
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139
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10044
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81
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- Items to replace nulls with
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9951
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81
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9991.5
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- List without any nulls
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10056
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30
20
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10071
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- Number of items replaced
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10056
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30
20
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10071
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9999
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40
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9999
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40
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255;255;255;255
- A group of Grasshopper objects
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20
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9987
-20647
- 1
- 1
- {0}
- 0.5
- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
- a80c1418-2b1d-4212-9317-98a17430aa75
- true
- Shine
- Shine
- false
- 0
-
9945
-20637
84
20
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9987
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- 1
- 1
- {0}
- 100
- Resulting material
- 0e7af99c-258c-466e-bdc8-84be0f45d103
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- false
- 0
-
10053
-20717
40
100
-
10073
-20667
- 537b0419-bbc2-4ff4-bf08-afe526367b2c
- Custom Preview
- Allows for customized geometry previews
- true
- true
- 95283d2e-b9a5-4543-9817-23b8a8696854
- true
- Custom Preview
- Custom Preview
-
9981
-20785
76
44
-
10043
-20763
- Geometry to preview
- true
- d5d56c99-8d84-4829-9b30-ecef418db18c
- true
- Geometry
- Geometry
- false
- 92df9f80-016f-455d-a9c3-bbe35cffa3bc
- 1
-
9983
-20783
48
20
-
10007
-20773
- The material override
- 3d0b983f-28b7-4e8a-b9d4-21d5070de639
- true
- Material
- Material
- false
- 0e7af99c-258c-466e-bdc8-84be0f45d103
- 1
-
9983
-20763
48
20
-
10007
-20753
- 1
- 1
- {0}
-
255;221;160;221
-
255;66;48;66
- 0.5
-
255;255;255;255
- 0
- 2b69bf71-4e69-43aa-b7be-4f6ce7e45bef
- Quick Graph
- 1
- Display a set of y-values as a graph
- 09024d99-a87c-4956-b0e1-7bc86894ca46
- true
- Quick Graph
- Quick Graph
- false
- 0
- 9c62f0e6-beef-403c-9c83-e0860071b8af
- 1
-
9951
-18980
150
150
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9951.656
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- -1
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
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255;255;255;255
- A group of Grasshopper objects
- b5568a68-fe32-424e-8c33-57bdb7be33cd
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- Group
- afb96615-c59a-45c9-9cac-e27acb1c7ca0
- Explode
- Explode a curve into smaller segments.
- true
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- true
- Explode
- Explode
-
9952
-21025
134
44
-
10023
-21003
- Curve to explode
- c96c9a02-1f26-40a5-9026-8ac73a753ab8
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- Curve
- Curve
- false
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- 1
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9954
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57
20
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9982.5
-21013
- Recursive decomposition until all segments are atomic
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- 0
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9954
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57
20
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9982.5
-20993
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- 1
- {0}
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- 1
- Exploded segments that make up the base curve
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10035
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49
20
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10059.5
-21013
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- Vertices of the exploded segments
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10035
-21003
49
20
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10059.5
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- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
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- true
- Evaluate Length
- Evaluate Length
-
9944
-21108
149
64
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10029
-21076
- Curve to evaluate
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-
9946
-21106
71
20
-
9981.5
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- Length factor for curve evaluation
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- Length
- Length
- false
- 0
-
9946
-21086
71
20
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9981.5
-21076
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Normalized
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9946
-21066
71
20
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9981.5
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- 1
- 1
- {0}
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- Point at the specified length
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10041
-21106
50
20
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10066
-21096
- Tangent vector at the specified length
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- Tangent
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10041
-21086
50
20
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10066
-21076
- Curve parameter at the specified length
- 1e9137ad-19c0-44de-93b0-ed22758d1b72
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- Parameter
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10041
-21066
50
20
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10066
-21056
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
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- true
- Line SDL
- Line SDL
-
9964
-22902
110
64
-
10038
-22870
- Line start point
- cccde99e-d1bb-42cb-9308-b60adc13598e
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- Start
- false
- c117a95c-6877-440a-be04-f9bf41059d4b
- 1
-
9966
-22900
60
20
-
10004
-22890
- Line tangent (direction)
- 8d269f2f-2e46-408a-b010-ea591ec9a0cd
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- Direction
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- 1
-
9966
-22880
60
20
-
10004
-22870
- 1
- 1
- {0}
-
0
0
1
- Line length
- 10f261f6-bdba-47f2-88ae-420dc21f40c9
- ABS(X)
- true
- Length
- Length
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- 1
-
9966
-22860
60
20
-
10004
-22850
- 1
- 1
- {0}
- 0.015625
- Line segment
- 401ad277-e9e4-4f79-8da6-d199f80326f0
- true
- Line
- Line
- false
- 0
-
10050
-22900
22
60
-
10061
-22870
- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
- true
- 865c8066-5247-4b0a-96a1-4424156c0cb8
- true
- Relative Differences
- Relative Differences
-
9961
-21451
116
28
-
10008
-21437
- 1
- List of data to operate on (numbers or points or vectors allowed)
- 22bbf386-4b21-4caa-b85a-18d67d6107e9
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- Values
- Values
- false
- 5be97c92-8ae7-4d99-a8a3-607079460d5e
- 1
-
9963
-21449
33
24
-
9979.5
-21437
- 1
- Differences between consecutive items
- f3da83a8-552c-4482-9825-f165df6fa732
- true
- Differenced
- Differenced
- false
- 0
-
10020
-21449
55
24
-
10047.5
-21437
- f3230ecb-3631-4d6f-86f2-ef4b2ed37f45
- Replace Nulls
- Replace nulls or invalid data with other data
- true
- dc8e38ea-6a83-4745-9d49-e94867a156af
- true
- Replace Nulls
- Replace Nulls
-
9949
-21395
139
44
-
10044
-21373
- 1
- Items to test for null
- 8156fbf8-f136-40c5-b535-ed951f9d17f7
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- Items
- Items
- false
- 362fefaa-7013-4c74-8cf7-e74beaf18bce
- 1
-
9951
-21393
81
20
-
9991.5
-21383
- 1
- Items to replace nulls with
- 5e913941-5ebb-4f96-9c6d-9694825347d8
- true
- Replacements
- Replacements
- false
- 0
-
9951
-21373
81
20
-
9991.5
-21363
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- 1
- List without any nulls
- 5be97c92-8ae7-4d99-a8a3-607079460d5e
- true
- Items
- Items
- false
- 0
-
10056
-21393
30
20
-
10071
-21383
- Number of items replaced
- 2f70f5c7-6a5d-4968-9d65-4ba70ef85dca
- true
- Count
- Count
- false
- 0
-
10056
-21373
30
20
-
10071
-21363
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 362fefaa-7013-4c74-8cf7-e74beaf18bce
- true
- Relay
- false
- 0928c206-a25e-4834-9a06-eb4c248c6ef7
- 1
-
9999
-21332
40
16
-
10019
-21324
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- bced28c6-c3d6-4c77-97c8-51f4de83d178
- true
- Relay
- false
- f63f83de-17f7-454a-bc36-895bc7488c7e
- 1
-
9999
-21696
40
16
-
10019
-21688
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 865c8066-5247-4b0a-96a1-4424156c0cb8
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- Group
- 2dc44b22-b1dd-460a-a704-6462d6e91096
- Curve Closest Point
- Find the closest point on a curve.
- true
- 096e1e94-cef1-45dd-9170-91b3022799a9
- true
- Curve Closest Point
- Curve Closest Point
-
9965
-21196
108
64
-
10009
-21164
- Point to project onto curve
- bf711b90-da21-4a31-83ef-a5fae2b85980
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- Point
- Point
- false
- c117a95c-6877-440a-be04-f9bf41059d4b
- 1
-
9967
-21194
30
30
-
9982
-21179
- Curve to project onto
- d616f966-5201-4834-912f-5594394dd8a5
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- false
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9967
-21164
30
30
-
9982
-21149
- Point on the curve closest to the base point
- 26daa500-5e3a-4c10-b67b-5c34dbb5336e
- true
- Point
- Point
- false
- 0
-
10021
-21194
50
20
-
10046
-21184
- Parameter on curve domain of closest point
- 2457c44a-4724-4030-877f-29aa2ae799f0
- true
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- Parameter
- false
- 0
-
10021
-21174
50
20
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10046
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- Distance between base point and curve
- c0d86339-7732-4312-a9a6-a9647a257181
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- Distance
- Distance
- false
- 0
-
10021
-21154
50
20
-
10046
-21144
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- 1691d791-4089-4e1a-b6a9-744569a38353
- true
- Line
- Line
-
9968
-21275
102
44
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10034
-21253
- Line start point
- 70841617-86dd-46b4-a70d-871f1e7eb6d5
- true
- Start Point
- Start Point
- false
- 26daa500-5e3a-4c10-b67b-5c34dbb5336e
- 1
-
9970
-21273
52
20
-
9996
-21263
- Line end point
- 8a193f72-6e7c-4093-a705-db8675e7aa97
- true
- End Point
- End Point
- false
- c117a95c-6877-440a-be04-f9bf41059d4b
- 1
-
9970
-21253
52
20
-
9996
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- Line segment
- 9b8925fa-9a9d-4705-8727-ff9576da78bc
- true
- Line
- Line
- false
- 0
-
10046
-21273
22
40
-
10057
-21253
- 2fcc2743-8339-4cdf-a046-a1f17439191d
- Remap Numbers
- Remap numbers into a new numeric domain
- true
- a1441e70-b9c0-4e1f-8831-9ef3c2ef0635
- true
- Remap Numbers
- Remap Numbers
-
9942
-22600
154
64
-
10042
-22568
- Value to remap
- cad3e760-fb48-4120-9d69-67f35f3611ad
- true
- Value
- Value
- false
- 04af94ae-ad62-46dd-bb3c-5b6585083350
- 1
-
9944
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86
20
-
9987
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- Source domain
- b3b78e1b-c8d1-4754-b6fa-ff02d55ecc97
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- Source
- Source
- false
- 530027ad-30c9-438e-8038-d5cadaa47365
- 1
-
9944
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86
20
-
9987
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- 1
- 1
- {0}
-
0
1
- Target domain
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- Target
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- false
- 0
-
9944
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86
20
-
9987
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-1
1
- Remapped number
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- 0
-
10054
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40
30
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10074
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- Remapped and clipped number
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- 0
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10054
-22568
40
30
-
10074
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- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
- true
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- true
- Bounds
- Bounds
-
9964
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110
28
-
10022
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- 1
- Numbers to include in Bounds
- beb8a25a-99b8-4e6f-b2e8-7ea93528c19d
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- Numbers
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- false
- 04af94ae-ad62-46dd-bb3c-5b6585083350
- 1
-
9966
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44
24
-
9988
-22504
- Numeric Domain between the lowest and highest numbers in {N}
- 530027ad-30c9-438e-8038-d5cadaa47365
- true
- Domain
- Domain
- false
- 0
-
10034
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38
24
-
10053
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- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 04af94ae-ad62-46dd-bb3c-5b6585083350
- true
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-
- false
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- 1
-
9999
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40
16
-
10019
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- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
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- true
- Multiplication
- Multiplication
-
9984
-22799
70
44
-
10009
-22777
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for multiplication
- d88e451c-a221-4a3c-bb80-172596ebe09f
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- A
- A
- true
- f4a5a11b-11a6-4bd1-bad5-e11c598ba2ee
- 1
-
9986
-22797
11
20
-
9991.5
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- Second item for multiplication
- b35a5238-7c06-430d-822d-ed17cada8dd5
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- B
- B
- true
- a2ddf12f-aac3-4d45-a4fd-5a6a2862a019
- 1
-
9986
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11
20
-
9991.5
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- Result of multiplication
- 47728caf-51cd-404e-8626-f3bf6658ad3e
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- 0
-
10021
-22797
31
40
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10036.5
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- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
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- true
- Multiplication
- Multiplication
-
9984
-22692
70
44
-
10009
-22670
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for multiplication
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- A
- A
- true
- 9264f0ff-aad0-4d8f-9480-080924b6c884
- 1
-
9986
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11
20
-
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- Point
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- 0
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10041
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50
20
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10066
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- Tangent vector at the specified length
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- Tangent
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- 0
-
10041
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50
20
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10066
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- Curve parameter at the specified length
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- true
- Parameter
- Parameter
- false
- 0
-
10041
-24547
50
20
-
10066
-24537
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
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- true
- Line SDL
- Line SDL
-
9964
-26408
110
64
-
10038
-26376
- Line start point
- 4d01d89d-867d-4d26-9b8a-a52db8d57201
- true
- Start
- Start
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- 1
-
9966
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60
20
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10004
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- Line tangent (direction)
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- Direction
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- 741882bd-0b22-4cc0-bb89-e4127163437d
- 1
-
9966
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60
20
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10004
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- 1
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-
0
0
1
- Line length
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- ABS(X)
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- Length
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- 1
-
9966
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60
20
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10004
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- 1
- 1
- {0}
- 0.015625
- Line segment
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- Line
- Line
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- 0
-
10050
-26406
22
60
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10061
-26376
- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
- true
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- true
- Relative Differences
- Relative Differences
-
9961
-24932
116
28
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10008
-24918
- 1
- List of data to operate on (numbers or points or vectors allowed)
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- Values
- Values
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- 1
-
9963
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33
24
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9979.5
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- 1
- Differences between consecutive items
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- 0
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10020
-24930
55
24
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10047.5
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- Replace Nulls
- Replace nulls or invalid data with other data
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- fd96bb10-3b69-4007-9f9e-f7f130eb78a6
- true
- Replace Nulls
- Replace Nulls
-
9949
-24876
139
44
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10044
-24854
- 1
- Items to test for null
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- true
- Items
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- 1
-
9951
-24874
81
20
-
9991.5
-24864
- 1
- Items to replace nulls with
- 6da97a30-673e-48d3-84ff-121d88d007e0
- true
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- Replacements
- false
- 0
-
9951
-24854
81
20
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9991.5
-24844
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- 1
- List without any nulls
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- Items
- Items
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- 0
-
10056
-24874
30
20
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10071
-24864
- Number of items replaced
- 3aabe34e-c4fa-4fef-ab2a-4c25e2a691e9
- true
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- Count
- false
- 0
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10056
-24854
30
20
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10071
-24844
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
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- Relay
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- 1
-
9999
-24813
40
16
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10019
-24805
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
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- true
- Relay
- false
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- 1
-
9999
-25177
40
16
-
10019
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
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- Group
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- Curve Closest Point
- Find the closest point on a curve.
- true
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- true
- Curve Closest Point
- Curve Closest Point
-
9965
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108
64
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10009
-24645
- Point to project onto curve
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- 1
-
9967
-24675
30
30
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9982
-24660
- Curve to project onto
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- Curve
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- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9967
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30
30
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9982
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- Point on the curve closest to the base point
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- 0
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10021
-24675
50
20
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10046
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- Parameter on curve domain of closest point
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- Parameter
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10021
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50
20
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10046
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- Distance between base point and curve
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- Distance
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10021
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50
20
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10046
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- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
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- true
- Line
- Line
-
9968
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102
44
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10034
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- Line start point
- 22ee8f64-2936-4bcf-af82-1ff24c9c31f9
- true
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- Start Point
- false
- 1c19cb76-43c3-4381-8e5a-e8c556ecf262
- 1
-
9970
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52
20
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9996
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- Line end point
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- End Point
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- 1
-
9970
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52
20
-
9996
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- Line segment
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- 0
-
10046
-24754
22
40
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10057
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- 2fcc2743-8339-4cdf-a046-a1f17439191d
- Remap Numbers
- Remap numbers into a new numeric domain
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- true
- Remap Numbers
- Remap Numbers
-
9942
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154
64
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10042
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- Value to remap
- ae0667bd-2d88-44e1-baf8-ed8733eb7854
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- Value
- Value
- false
- 83a435db-f239-4ad7-b65f-fe31ed748d9c
- 1
-
9944
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86
20
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9987
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- Source domain
- d0a72c88-cd36-4ef1-9985-ac04db8a8731
- true
- Source
- Source
- false
- 2ef226e8-d1f0-4285-bad5-11dc292724a1
- 1
-
9944
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86
20
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9987
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- 1
- 1
- {0}
-
0
1
- Target domain
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- true
- Target
- Target
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- 0
-
9944
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86
20
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9987
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- 1
- 1
- {0}
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-1
1
- Remapped number
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- Mapped
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- 0
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10054
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40
30
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10074
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- Remapped and clipped number
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- true
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- Clipped
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- 0
-
10054
-26074
40
30
-
10074
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- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
- true
- 1b6bacd7-67d0-4f16-bd5e-99a18690b8aa
- true
- Bounds
- Bounds
-
9964
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110
28
-
10022
-26010
- 1
- Numbers to include in Bounds
- 9360de34-e5bc-46d2-8019-9bf13a2a372c
- true
- Numbers
- Numbers
- false
- 83a435db-f239-4ad7-b65f-fe31ed748d9c
- 1
-
9966
-26022
44
24
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9988
-26010
- Numeric Domain between the lowest and highest numbers in {N}
- 2ef226e8-d1f0-4285-bad5-11dc292724a1
- true
- Domain
- Domain
- false
- 0
-
10034
-26022
38
24
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10053
-26010
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 83a435db-f239-4ad7-b65f-fe31ed748d9c
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- Relay
-
- false
- ff917474-e27a-48ee-86c6-2399e98eb9b3
- 1
-
9999
-25977
40
16
-
10019
-25969
- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
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- true
- Multiplication
- Multiplication
-
9984
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70
44
-
10009
-26283
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
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- First item for multiplication
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- true
- A
- A
- true
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- 1
-
9986
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11
20
-
9991.5
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- Second item for multiplication
- 439ef53a-a40c-48ce-bee1-7d64264f64b1
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- B
- B
- true
- a2ddf12f-aac3-4d45-a4fd-5a6a2862a019
- 1
-
9986
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11
20
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9991.5
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- Result of multiplication
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- 0
-
10021
-26303
31
40
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10036.5
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- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
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- true
- Multiplication
- Multiplication
-
9984
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70
44
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10009
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- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- First item for multiplication
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- A
- A
- true
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- 1
-
9986
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11
20
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9991.5
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- Second item for multiplication
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- B
- B
- true
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9986
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11
20
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9991.5
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- Result of multiplication
- ef54399e-d0dc-4977-9a91-e1732e255135
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- 0
-
10021
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31
40
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10036.5
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- Relay
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- A wire relay object
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9999
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40
16
-
10019
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Group
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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255;255;255;255
- A group of Grasshopper objects
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- Group
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- Panel
- A panel for custom notes and text values
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- 1
- e7099fe1-9f7c-49ca-bf44-6736df5e3b63
- 1
- Double click to edit panel content…
-
9934
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185
271
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9934.656
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255;255;255;255
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- Relay
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- A wire relay object
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-
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9999
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40
16
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10019
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- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
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- A wire relay object
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9999
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40
16
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10019
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- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Group
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- Create Material
- Create an OpenGL material.
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- Create Material
- Create Material
-
9943
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152
104
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10041
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- Colour of the diffuse channel
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-
9945
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84
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9987
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255;224;224;224
- Colour of the specular highlight
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-
9945
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84
20
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9987
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255;0;255;255
- Emissive colour of the material
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-
9945
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84
20
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9987
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255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
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- 0
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9945
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84
20
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9987
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- 1
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- {0}
- 0.5
- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
- 201dd6ff-6bae-487c-8174-a2b97855875d
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9945
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84
20
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9987
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- {0}
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- Resulting material
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10053
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40
100
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10073
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- 537b0419-bbc2-4ff4-bf08-afe526367b2c
- Custom Preview
- Allows for customized geometry previews
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-
9981
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76
44
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10043
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- Geometry to preview
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9983
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48
20
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10007
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- The material override
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9983
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48
20
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10007
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255;221;160;221
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255;66;48;66
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255;255;255;255
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- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- true
- Evaluate Length
- Evaluate Length
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9944
-27171
149
64
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10029
-27139
- Curve to evaluate
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- Curve
- Curve
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- 1
-
9946
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71
20
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9981.5
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- Length factor for curve evaluation
- edb756de-0121-4df0-bd3e-d77b136c4316
- true
- Length
- Length
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- 0
-
9946
-27149
71
20
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9981.5
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- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 4e29cbcc-3a41-496d-abf2-bea7fc776a96
- true
- Normalized
- Normalized
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- 0
-
9946
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71
20
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9981.5
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- 1
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- Point at the specified length
- b34dac8b-8d64-4e79-82bb-d85237582fc3
- true
- Point
- Point
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- 0
-
10041
-27169
50
20
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10066
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- Tangent vector at the specified length
- d4ad06af-261d-480c-9b76-80b8b35af349
- true
- Tangent
- Tangent
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- 0
-
10041
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50
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10066
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- Curve parameter at the specified length
- c971b7a0-0366-4c4c-9464-7f4df888cb5a
- true
- Parameter
- Parameter
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- 0
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10041
-27129
50
20
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10066
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- 2b2a4145-3dff-41d4-a8de-1ea9d29eef33
- Interpolate
- Create an interpolated curve through a set of points.
- true
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- Interpolate
- Interpolate
-
9906
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225
84
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10079
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- 1
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- 1503e6d5-6140-42c5-a21b-4dba42363436
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- Vertices
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9908
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159
20
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9987.5
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- Curve degree
- 5f85b622-d830-4a07-bff0-f8530b2c4a57
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- Degree
- Degree
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- 0
-
9908
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159
20
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9987.5
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- 1
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- 58ad891d-4a3c-47c1-9618-6af0908ce9a4
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- Periodic
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- 0
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9908
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159
20
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9987.5
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- KnotStyle
- false
- 0
-
9908
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159
20
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9987.5
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- 0
-
10091
-27545
38
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10110
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- Curve length
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- Length
- Length
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10091
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38
27
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10110
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- Curve domain
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- Domain
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10091
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38
27
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10110
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- Create Material
- Create an OpenGL material.
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- Create Material
- Create Material
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9943
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152
104
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10041
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- Colour of the diffuse channel
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- Diffuse
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-
9945
-27672
84
20
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9987
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255;199;199;199
- Colour of the specular highlight
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- Specular
- false
- 0
-
9945
-27652
84
20
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9987
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- 1
- {0}
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255;0;255;255
- Emissive colour of the material
- 5869d24e-a5b5-410d-82a1-847611623bed
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- Emission
- Emission
- false
- 0
-
9945
-27632
84
20
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9987
-27622
- 1
- 1
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255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
- 3b1b263e-3d61-47b4-95c4-821fcef67b0b
- true
- Transparency
- Transparency
- false
- 0
-
9945
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84
20
-
9987
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- 1
- 1
- {0}
- 0.5
- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
- d4f5488e-4a4f-4c05-a6b7-8bd31d59b4c7
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- Shine
- Shine
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-
9945
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84
20
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9987
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- 100
- Resulting material
- 1bed5aa6-f478-4993-a204-8cfa72a07424
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- Material
- Material
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10053
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40
100
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10073
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- 537b0419-bbc2-4ff4-bf08-afe526367b2c
- Custom Preview
- Allows for customized geometry previews
- true
- true
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- Custom Preview
- Custom Preview
-
9981
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76
44
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10043
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- Geometry to preview
- true
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- Geometry
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- ff468b81-65e8-4cdf-b877-b88d817f1f2d
- 1
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9983
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48
20
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10007
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- The material override
- 2808fa60-8978-4b6d-ae88-09a8be1d2563
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- Material
- Material
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9983
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48
20
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10007
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255;221;160;221
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255;66;48;66
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-
255;255;255;255
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- Quick Graph
- 1
- Display a set of y-values as a graph
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- Quick Graph
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-
9951
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150
150
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9951.656
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- Group
- 1
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255;255;255;255
- A group of Grasshopper objects
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- Group
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- Explode
- Explode a curve into smaller segments.
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- true
- Explode
- Explode
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9952
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134
44
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10023
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- Curve to explode
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9954
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57
20
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9982.5
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- Recursive decomposition until all segments are atomic
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9954
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57
20
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9982.5
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- 1
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- 1
- Exploded segments that make up the base curve
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10035
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49
20
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10059.5
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- Vertices of the exploded segments
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- Vertices
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10035
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49
20
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10059.5
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- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
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- true
- Evaluate Length
- Evaluate Length
-
9944
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149
64
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10029
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- Curve to evaluate
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- Curve
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9946
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71
20
-
9981.5
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- Length factor for curve evaluation
- 652c5ab2-febc-4340-94df-6611e53df831
- true
- Length
- Length
- false
- 0
-
9946
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71
20
-
9981.5
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- 1
- {0}
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- If True, the Length factor is normalized (0.0 ~ 1.0)
- 9ec37965-bbaa-472e-adc1-1aa463e2e77f
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- Normalized
- Normalized
- false
- 0
-
9946
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71
20
-
9981.5
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- 1
- {0}
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- Point at the specified length
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- true
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- Point
- false
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10041
-27958
50
20
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10066
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- Tangent vector at the specified length
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- Tangent
- Tangent
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- 0
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10041
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50
20
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10066
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- Curve parameter at the specified length
- a5197d5c-aa87-4482-aaba-20779b7b231e
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- Parameter
- Parameter
- false
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10041
-27918
50
20
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10066
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- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
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- true
- Line SDL
- Line SDL
-
9964
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110
64
-
10038
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- Line start point
- 71f5a683-8e56-4a2f-81f8-5f9808eddf57
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- Start
- Start
- false
- 4078e208-ec63-43ca-9706-3bca2f569fa2
- 1
-
9966
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60
20
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10004
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- Line tangent (direction)
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- Direction
- Direction
- false
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- 1
-
9966
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60
20
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10004
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- 1
- {0}
-
0
0
1
- Line length
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- Length
- Length
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- 1
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9966
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60
20
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10004
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- 1
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- Line segment
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- Line
- Line
- false
- 0
-
10050
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22
60
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10061
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- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
- true
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- true
- Relative Differences
- Relative Differences
-
9961
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116
28
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10008
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- List of data to operate on (numbers or points or vectors allowed)
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- Values
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9963
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33
24
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9979.5
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- Differences between consecutive items
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- Differenced
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- 0
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10020
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55
24
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10047.5
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- Replace nulls or invalid data with other data
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- Replace Nulls
- Replace Nulls
-
9949
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139
44
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10044
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- Items to test for null
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- Items
- Items
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9951
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81
20
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9991.5
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- Items to replace nulls with
- a3f4d718-1001-4437-b607-f5fed9eff18a
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- Replacements
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9951
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81
20
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9991.5
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- 1
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- Grasshopper.Kernel.Types.GH_Integer
- 0
- 1
- List without any nulls
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- Items
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-
10056
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30
20
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10071
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- Number of items replaced
- 29929c88-87bc-4ed9-a28e-5f9a48da5860
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- Count
- Count
- false
- 0
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10056
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30
20
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10071
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- Relay
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- A wire relay object
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- Relay
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- 1
-
9999
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40
16
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10019
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- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
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- true
- Relay
- false
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-
9999
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40
16
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10019
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- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Group
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- Find the closest point on a curve.
- true
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- true
- Curve Closest Point
- Curve Closest Point
-
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108
64
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10009
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- Point to project onto curve
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- 1
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9967
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30
30
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9982
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- Curve to project onto
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9967
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30
30
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9982
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- Point on the curve closest to the base point
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- Point
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- 0
-
10021
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50
20
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10046
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- Parameter on curve domain of closest point
- 679c843b-31f4-4e05-b990-e840a91b4713
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- false
- 0
-
10021
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50
20
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10046
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- Distance between base point and curve
- 6fa34270-3ef8-41fd-a4a1-154817bd8fb9
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- Distance
- Distance
- false
- 0
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10021
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50
20
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10046
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- Line
- Create a line between two points.
- true
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- true
- Line
- Line
-
9968
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102
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10034
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- Line start point
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- Start Point
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- false
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9970
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52
20
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9996
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- Line end point
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- End Point
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- 4078e208-ec63-43ca-9706-3bca2f569fa2
- 1
-
9970
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52
20
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-
10034
-1141
40
20
-
10054
-1131
- 1
- Knot vector of Nurbs-form.
- 76456d8d-19af-4eb2-af98-81629b18ee44
- true
- Knots
- Knots
- false
- 0
-
10034
-1121
40
20
-
10054
-1111
- 1817fd29-20ae-4503-b542-f0fb651e67d7
- List Length
- Measure the length of a list.
- true
- e2702e73-2b57-4491-93aa-1cea88badf67
- true
- List Length
- List Length
-
9978
-1211
97
28
-
10011
-1197
- 1
- Base list
- 3eb1b898-88e7-49f3-b62d-b20ae54213df
- true
- List
- List
- false
- 983acda0-f9cb-4339-b8f5-963587e0cafd
- 1
-
9980
-1209
19
24
-
9989.5
-1197
- Number of items in L
- a927a6be-3516-43fe-8365-bf443ef1923b
- X-1
- true
- Length
- Length
- false
- 0
-
10023
-1209
50
24
-
10040
-1197
- 41f43104-c70e-48d0-a336-36da01af23c3
- 1c9de8a1-315f-4c56-af06-8f69fee80a7a
- Curve Degree
- Get the degree value of a curve.
- true
- dd4f9b33-eb2f-4c2c-a9da-2d65d6783044
- true
- Curve Degree
- Curve Degree
-
9980
-1079
94
28
-
10024
-1065
- Curve to get the degree value of
- 6a0046e4-5b4d-448f-b2b4-cade479dcad1
- true
- Curve
- Curve
- false
- ee782a63-64f0-4f70-a960-95d38003cbb3
- 1
-
9982
-1077
30
24
-
9997
-1065
- Degree value of the curve
- 272db34b-cb01-4ac1-bae9-e94d23c75f3c
- true
- Degree
- Degree
- false
- 0
-
10036
-1077
36
24
-
10054
-1065
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- A-B+1
- true
- d2d17992-1f6a-41ce-a0e5-0a8d83ef92d2
- true
- Expression
- Expression
-
9973
-1275
108
44
-
10017
-1253
- 2
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- 9756e426-55fb-4678-a28c-dee3f43c22e5
- true
- Variable A
- A
- true
- a927a6be-3516-43fe-8365-bf443ef1923b
- 1
-
9975
-1273
11
20
-
9980.5
-1263
- Expression variable
- 211996a5-6e8a-4a9c-88db-d132592dde1e
- true
- Variable B
- B
- true
- 272db34b-cb01-4ac1-bae9-e94d23c75f3c
- 1
-
9975
-1253
11
20
-
9980.5
-1243
- Result of expression
- 82cdb6c5-d11c-4816-899a-ec7feeb75410
- true
- Result
- Result
- false
- 0
-
10048
-1273
31
40
-
10063.5
-1253
- 448de216-3a12-43cf-a135-e3bfafc87744
- B
- Second item for multiplication
- 12e4c4ab-282e-49fd-8fbc-2e50fd9bf37a
- true
- B
- B
- false
- 0
-
9989
-12026
60
24
- 448de216-3a12-43cf-a135-e3bfafc87744
- B
- Second item for multiplication
- fba3b68f-f744-41d4-b4d2-9d899b5a7f88
- true
- B
- B
- false
- 0
-
9989
-15586
60
24
- 448de216-3a12-43cf-a135-e3bfafc87744
- B
- Second item for multiplication
- 8b4a365c-1645-430f-8be6-7fb0019a20f5
- true
- B
- B
- false
- 0
-
9990
-19286
60
24
- 448de216-3a12-43cf-a135-e3bfafc87744
- B
- Second item for multiplication
- 3d196e4e-a427-48b3-a97c-9aae81c0ab45
- true
- B
- B
- false
- 0
-
9989
-22740
60
24
- 448de216-3a12-43cf-a135-e3bfafc87744
- B
- Second item for multiplication
- ab1ac911-2029-4ebc-a2e6-4e954cd90453
- true
- B
- B
- false
- 0
-
9987
-26232
60
24
- 448de216-3a12-43cf-a135-e3bfafc87744
- B
- Second item for multiplication
- 899223b6-df9a-403e-bae3-eb7c226d4aab
- true
- B
- B
- false
- 0
-
9989
-29565
60
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- Relay
- A wire relay object
- 62804d7b-bdd9-4ed1-b6e5-f970e801b6a3
- true
- Relay
-
- false
- 9c62f0e6-beef-403c-9c83-e0860071b8af
- 1
-
9989
-18356
60
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- Relay
- A wire relay object
- 55512720-2a0e-47cd-b00a-dc2b37b30de5
- true
- Relay
-
- false
- 7af0cade-f743-4780-907e-050ed9fcd4f9
- 1
-
9989
-21791
60
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- Relay
- A wire relay object
- a7aa0c22-62a5-48d9-8db9-35e295bd33c0
- true
- Relay
-
- false
- 238ccd66-333b-42be-b89d-c7a89f7d43cf
- 1
-
9989
-25268
60
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- Relay
- A wire relay object
- 2f70e9a1-868c-4cc1-a692-dd23505afa99
- true
- Relay
-
- false
- 4ac110ab-0df5-451c-94d6-c95b7b9e23dd
- 1
-
9989
-28628
60
24
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 532c0140-0dbd-4867-a53d-0a5b1e3f1497
- true
- Shift List
-
-
9992
-7434
53
64
-
10025
-7402
- 1
- List to shift
- 7d76ee9a-e8ec-4986-8d85-406e5c4305d4
- true
- List
-
- false
- 0184d168-0386-49c1-b31a-26709654c038
- 1
-
9994
-7432
19
20
-
10003.5
-7422
- Shift offset
- a96c7aa5-08ee-40cc-a832-e9d67163b5a8
- true
- Shift
-
- false
- 0
-
9994
-7412
19
20
-
10003.5
-7402
- 1
- 1
- {0}
- 1
- Wrap values
- 40b4295e-9407-40bf-80d0-c4d99f8a0aeb
- true
- Wrap
-
- false
- 0
-
9994
-7392
19
20
-
10003.5
-7382
- 1
- 1
- {0}
- false
- 1
- Shifted list
- 738d8220-3b26-49b2-a359-0fc4d671538d
- true
- List
-
- false
- 0
-
10037
-7432
6
60
-
10040
-7402
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 46418f77-df32-4b35-861e-15218fba9785
- true
- Shift List
-
-
9992
-10955
53
64
-
10025
-10923
- 1
- List to shift
- 109e878a-7998-4679-b117-34d7b6cf17de
- true
- List
-
- false
- 7338c244-af88-4723-b45a-08577283c18b
- 1
-
9994
-10953
19
20
-
10003.5
-10943
- Shift offset
- 0544d4a8-798d-4542-bf03-ac1d99f27a76
- true
- Shift
-
- false
- 0
-
9994
-10933
19
20
-
10003.5
-10923
- 1
- 1
- {0}
- 1
- Wrap values
- 2533a264-171f-404e-a1c6-c06a3b9b8e6f
- true
- Wrap
-
- false
- 0
-
9994
-10913
19
20
-
10003.5
-10903
- 1
- 1
- {0}
- false
- 1
- Shifted list
- 95512bec-3e3b-4a1e-968f-fdd54a0ed3fb
- true
- List
-
- false
- 0
-
10037
-10953
6
60
-
10040
-10923
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 8fd33484-455a-46bc-a886-7e889984cd34
- true
- Shift List
-
-
9992
-14390
53
64
-
10025
-14358
- 1
- List to shift
- be257533-ca89-454e-b4ba-f9b6b4680c16
- true
- List
-
- false
- 72af1623-98b2-41a3-b5a9-7e1bda1d7111
- 1
-
9994
-14388
19
20
-
10003.5
-14378
- Shift offset
- 2d8260d3-7cf6-48ff-a5e8-331b238050bf
- true
- Shift
-
- false
- 0
-
9994
-14368
19
20
-
10003.5
-14358
- 1
- 1
- {0}
- 1
- Wrap values
- 600f582c-be8c-4052-b082-957c3db424ca
- true
- Wrap
-
- false
- 0
-
9994
-14348
19
20
-
10003.5
-14338
- 1
- 1
- {0}
- false
- 1
- Shifted list
- 5fcafa9d-43c7-4d8e-b1fa-7217ab260d93
- true
- List
-
- false
- 0
-
10037
-14388
6
60
-
10040
-14358
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- 03e206f6-06e3-45a0-bd1b-462b7509ec07
- true
- Format
- Format
-
9962
-2581
130
64
-
10054
-2549
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- 60aa4b83-1c3e-42c0-a0fc-3958ecd7d990
- true
- Format
- Format
- false
- 0
-
9964
-2579
78
20
-
10003
-2569
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- 961c16c0-6ded-4a47-a9b4-6bac4a3ee77c
- true
- Culture
- Culture
- false
- 0
-
9964
-2559
78
20
-
10003
-2549
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- a12fa6e2-f7e6-44db-89fd-2ee48c469cd2
- true
- false
- Data 0
- 0
- true
- 2cd82ac7-4de3-4efd-b21c-bb675514f953
- 1
-
9964
-2539
78
20
-
10003
-2529
- Formatted text
- ad720d66-d245-44d9-b76a-dafa2c256b04
- true
- Text
- Text
- false
- 0
-
10066
-2579
24
60
-
10078
-2549
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- 939ec527-c895-4c10-8020-fc9e4da28bdd
- true
- Format
- Format
-
9962
-3425
130
64
-
10054
-3393
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- b40b6ba6-8d3b-4054-a253-f920a6f3f288
- true
- Format
- Format
- false
- 0
-
9964
-3423
78
20
-
10003
-3413
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- 6e07828a-1ec4-4e71-8198-90b5c6d06fdd
- true
- Culture
- Culture
- false
- 0
-
9964
-3403
78
20
-
10003
-3393
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- 2cfebbbe-71fe-4a4a-acdc-4ef62d2bc7f4
- true
- false
- Data 0
- 0
- true
- 94c91859-db24-4e5a-aaa7-9df679d51de2
- 1
-
9964
-3383
78
20
-
10003
-3373
- Formatted text
- 2ee62344-eed2-47d2-aae3-277cb264e100
- true
- Text
- Text
- false
- 0
-
10066
-3423
24
60
-
10078
-3393
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- f7c23408-ec08-4cd6-9afd-7fd502247d57
- true
- Format
- Format
-
9954
-7698
130
64
-
10046
-7666
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- 5dc2652c-c8e1-468a-b333-c5da7a8fe3b3
- true
- Format
- Format
- false
- 0
-
9956
-7696
78
20
-
9995
-7686
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- 618ca455-8d0f-4f78-befe-37c22b75ce12
- true
- Culture
- Culture
- false
- 0
-
9956
-7676
78
20
-
9995
-7666
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- 06eab3da-eb92-49cc-8526-a9f59c60cae8
- true
- false
- Data 0
- 0
- true
- dd7ae928-e56d-4423-b7b1-b1999182a279
- 1
-
9956
-7656
78
20
-
9995
-7646
- Formatted text
- e96b0bfa-693f-4be8-bcb4-c9e4a7df9692
- true
- Text
- Text
- false
- 0
-
10058
-7696
24
60
-
10070
-7666
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- 318a5c49-4892-4094-b625-e4cbecc814eb
- true
- Format
- Format
-
9954
-11218
130
64
-
10046
-11186
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- 1c5694f5-cf69-4c42-a1bb-3da554b0635c
- true
- Format
- Format
- false
- 0
-
9956
-11216
78
20
-
9995
-11206
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- c5c61685-06d4-441e-9a4c-b2d1b2631663
- true
- Culture
- Culture
- false
- 0
-
9956
-11196
78
20
-
9995
-11186
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- 09e97d28-ec29-4afe-8e36-634ce9ae03a8
- true
- false
- Data 0
- 0
- true
- 05a6550e-e7dc-41fc-8983-e7c430ad5012
- 1
-
9956
-11176
78
20
-
9995
-11166
- Formatted text
- 5a745073-b64d-4e12-bfb6-7d824ab5280e
- true
- Text
- Text
- false
- 0
-
10058
-11216
24
60
-
10070
-11186
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- 8e870804-f0af-411f-a9d2-ed416c5c6187
- true
- Format
- Format
-
9954
-14674
130
64
-
10046
-14642
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- 520f052e-3f14-4220-ac0e-0b03931a1266
- true
- Format
- Format
- false
- 0
-
9956
-14672
78
20
-
9995
-14662
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- 19f9fdd9-7ac8-42d6-978d-356e3e565021
- true
- Culture
- Culture
- false
- 0
-
9956
-14652
78
20
-
9995
-14642
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- dd7860ba-e2ad-44a8-a3cf-a0d9a45c0842
- true
- false
- Data 0
- 0
- true
- e9df2d08-5a93-4bb4-9361-d5b6b5a545a5
- 1
-
9956
-14632
78
20
-
9995
-14622
- Formatted text
- 3d034f31-d797-4424-8cef-9499e7099fc1
- true
- Text
- Text
- false
- 0
-
10058
-14672
24
60
-
10070
-14642
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- 7ce3ce15-850b-45e1-ad59-92f757c03b5c
- true
- Format
- Format
-
9954
-18461
130
64
-
10046
-18429
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- 40164056-ab05-4230-b49c-dd067f9305d2
- true
- Format
- Format
- false
- 0
-
9956
-18459
78
20
-
9995
-18449
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- 2db5bc1b-d60e-4c5c-8b12-9a60741a0086
- true
- Culture
- Culture
- false
- 0
-
9956
-18439
78
20
-
9995
-18429
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- de3f0b39-9873-400d-b1b9-85a5e16c03e0
- true
- false
- Data 0
- 0
- true
- 9c62f0e6-beef-403c-9c83-e0860071b8af
- 1
-
9956
-18419
78
20
-
9995
-18409
- Formatted text
- 84721e9b-8e00-4fcb-9746-ae1b23e91d8d
- true
- Text
- Text
- false
- 0
-
10058
-18459
24
60
-
10070
-18429
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- 1ef06ab7-bb52-421b-9d4f-0f74a7b338d7
- true
- Format
- Format
-
9954
-21883
130
64
-
10046
-21851
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- c23477a4-43c8-4198-a584-157e995bc70d
- true
- Format
- Format
- false
- 0
-
9956
-21881
78
20
-
9995
-21871
- 1
- 1
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- {0:R}
- Formatting culture
- abd47b9e-8af3-4412-b330-03721da886d7
- true
- Culture
- Culture
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- 0
-
9956
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78
20
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9995
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- 1
- 1
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- 127
- Data to insert at {0} placeholders
- 31b965f4-66e2-43d6-bc73-414c25ca61bd
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- Data 0
- 0
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- 7af0cade-f743-4780-907e-050ed9fcd4f9
- 1
-
9956
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78
20
-
9995
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- Formatted text
- 9ea884c7-deed-4580-b340-ef5d5dc73681
- true
- Text
- Text
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- 0
-
10058
-21881
24
60
-
10070
-21851
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- 3971560d-877c-4cb3-9aad-0356911759f5
- true
- Format
- Format
-
9954
-25385
130
64
-
10046
-25353
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
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- 1
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- Text format
- ea427ec3-5a35-4520-8ccf-18df23fc6a20
- true
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- Format
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- 0
-
9956
-25383
78
20
-
9995
-25373
- 1
- 1
- {0}
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- {0:R}
- Formatting culture
- 933deb80-43d7-4dd9-b413-0db54ca26dd1
- true
- Culture
- Culture
- false
- 0
-
9956
-25363
78
20
-
9995
-25353
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- b0eac621-7855-4073-b49b-fa4116b4784d
- true
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- Data 0
- 0
- true
- 238ccd66-333b-42be-b89d-c7a89f7d43cf
- 1
-
9956
-25343
78
20
-
9995
-25333
- Formatted text
- e7099fe1-9f7c-49ca-bf44-6736df5e3b63
- true
- Text
- Text
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- 0
-
10058
-25383
24
60
-
10070
-25353
- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- c4c5c32f-2de8-427e-a283-c44a57d51434
- true
- Format
- Format
-
9954
-28732
130
64
-
10046
-28700
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
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- 1
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- Text format
- bbd9f5ee-62b0-4987-bce7-1fe240ab5162
- true
- Format
- Format
- false
- 0
-
9956
-28730
78
20
-
9995
-28720
- 1
- 1
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- {0:R}
- Formatting culture
- e20d6918-7775-473e-a0be-b717596cb7dd
- true
- Culture
- Culture
- false
- 0
-
9956
-28710
78
20
-
9995
-28700
- 1
- 1
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- 127
- Data to insert at {0} placeholders
- ce53e26b-c513-4d62-be4c-647c68ce1540
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- Data 0
- 0
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- 4ac110ab-0df5-451c-94d6-c95b7b9e23dd
- 1
-
9956
-28690
78
20
-
9995
-28680
- Formatted text
- d93f190c-e272-4223-ac4d-69ddd085d784
- true
- Text
- Text
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-
10058
-28730
24
60
-
10070
-28700
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 81eaa78b-b49c-4af4-a9e1-8ed2469b4e8c
- a03f91ac-0515-47e3-b1da-acb30c73ba6d
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- Group
- afb96615-c59a-45c9-9cac-e27acb1c7ca0
- Explode
- Explode a curve into smaller segments.
- true
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- true
- Explode
- Explode
-
9952
-31204
134
44
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10023
-31182
- Curve to explode
- 757b62fd-392a-4568-8b6b-502c736a7d1a
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- Curve
- Curve
- false
- 82d46f90-f3a3-4dc9-bab4-8b7484395e05
- 1
-
9954
-31202
57
20
-
9982.5
-31192
- Recursive decomposition until all segments are atomic
- 0baeb68c-d1b8-42b0-96d5-9fadc48e843b
- true
- Recursive
- Recursive
- false
- 0
-
9954
-31182
57
20
-
9982.5
-31172
- 1
- 1
- {0}
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- 1
- Exploded segments that make up the base curve
- fe3f9ab1-bf7b-4288-8d97-e7946294e33c
- true
- Segments
- Segments
- false
- 0
-
10035
-31202
49
20
-
10059.5
-31192
- 1
- Vertices of the exploded segments
- e0fac1f1-e34c-460c-bca6-4d652b5d1e7c
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- Vertices
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- 0
-
10035
-31182
49
20
-
10059.5
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- a03f91ac-0515-47e3-b1da-acb30c73ba6d
- true
- Evaluate Length
- Evaluate Length
-
9944
-31287
149
64
-
10029
-31255
- Curve to evaluate
- dd3f8489-93cb-466e-a726-1d6ce1c1fa21
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- Curve
- Curve
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- fe3f9ab1-bf7b-4288-8d97-e7946294e33c
- 1
-
9946
-31285
71
20
-
9981.5
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- Length factor for curve evaluation
- 71c1961c-f265-4c01-a5d9-26dc87f04220
- true
- Length
- Length
- false
- 0
-
9946
-31265
71
20
-
9981.5
-31255
- 1
- 1
- {0}
- 0.5
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 59c6efa1-7240-4201-bc6c-5c31a378fbcf
- true
- Normalized
- Normalized
- false
- 0
-
9946
-31245
71
20
-
9981.5
-31235
- 1
- 1
- {0}
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- Point at the specified length
- f2e837e8-96af-4a0b-b80b-0dac5228b855
- true
- Point
- Point
- false
- 0
-
10041
-31285
50
20
-
10066
-31275
- Tangent vector at the specified length
- 421d155b-e6ee-493b-b76e-514be889455d
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- Tangent
- Tangent
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- 0
-
10041
-31265
50
20
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10066
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- Curve parameter at the specified length
- 86747235-7923-4162-bf80-d06ce685768a
- true
- Parameter
- Parameter
- false
- 0
-
10041
-31245
50
20
-
10066
-31235
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
- 72305306-f2af-43c4-9fd0-d3e8e9bc541b
- true
- Line SDL
- Line SDL
-
9964
-33067
110
64
-
10038
-33035
- Line start point
- 921670be-6896-4871-8936-b58984df4f0a
- true
- Start
- Start
- false
- f2e837e8-96af-4a0b-b80b-0dac5228b855
- 1
-
9966
-33065
60
20
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10004
-33055
- Line tangent (direction)
- 73b544b6-a2ee-4c7a-9bdd-d84c5868e8e7
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- Direction
- Direction
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- b236cb6d-586e-4db4-8608-bc3cfb183bfb
- 1
-
9966
-33045
60
20
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10004
-33035
- 1
- 1
- {0}
-
0
0
1
- Line length
- 51d28f88-0bc1-4904-8e9f-c19e3e5f0f68
- ABS(X)
- true
- Length
- Length
- false
- 8e9b755e-d14d-45f3-810d-0016d1bc6909
- 1
-
9966
-33025
60
20
-
10004
-33015
- 1
- 1
- {0}
- 0.015625
- Line segment
- 0788f4f1-f5fb-4cbe-9fa5-9ccae96bc71e
- true
- Line
- Line
- false
- 0
-
10050
-33065
22
60
-
10061
-33035
- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
- true
- dd9ded7c-395b-47d9-ac3c-e415673778cb
- true
- Relative Differences
- Relative Differences
-
9961
-31630
116
28
-
10008
-31616
- 1
- List of data to operate on (numbers or points or vectors allowed)
- bbe33525-f6e6-4c7a-ac43-89d73b365178
- true
- Values
- Values
- false
- af79ac58-6083-46fb-bd71-4571d4768b45
- 1
-
9963
-31628
33
24
-
9979.5
-31616
- 1
- Differences between consecutive items
- b0b2a1b6-2a67-466d-9bdf-e8b50dccde48
- true
- Differenced
- Differenced
- false
- 0
-
10020
-31628
55
24
-
10047.5
-31616
- f3230ecb-3631-4d6f-86f2-ef4b2ed37f45
- Replace Nulls
- Replace nulls or invalid data with other data
- true
- 22fcc540-2869-4d46-b91a-7baf5b3b0523
- true
- Replace Nulls
- Replace Nulls
-
9949
-31574
139
44
-
10044
-31552
- 1
- Items to test for null
- 0d06677d-66cc-4a32-8338-5014731a3e32
- true
- Items
- Items
- false
- 43a91f6e-e3b9-4aad-adac-77d060886b47
- 1
-
9951
-31572
81
20
-
9991.5
-31562
- 1
- Items to replace nulls with
- 5531ecac-6e38-48ea-8b2d-03e1ad1d5b28
- true
- Replacements
- Replacements
- false
- 0
-
9951
-31552
81
20
-
9991.5
-31542
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- 1
- List without any nulls
- af79ac58-6083-46fb-bd71-4571d4768b45
- true
- Items
- Items
- false
- 0
-
10056
-31572
30
20
-
10071
-31562
- Number of items replaced
- 5fb3744d-0f50-472a-b0f5-33274cdac75c
- true
- Count
- Count
- false
- 0
-
10056
-31552
30
20
-
10071
-31542
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 43a91f6e-e3b9-4aad-adac-77d060886b47
- true
- Relay
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- 213ef2cd-1c24-4d88-8ee3-8563f616e74b
- 1
-
9999
-31511
40
16
-
10019
-31503
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- d519f8f3-6b31-4df4-b45f-1a71a2d468c3
- true
- Relay
- false
- 628a45ae-3f38-4501-9306-b3bfe07a4a69
- 1
-
9999
-31875
40
16
-
10019
-31867
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- dd9ded7c-395b-47d9-ac3c-e415673778cb
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- 884f7be6-32bb-4a29-903a-e313a43a21a0
- 3b821991-b5a9-4b03-b173-4a07543fc3bf
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- 27b1909a-f125-4246-82be-4d422422f56c
- 8
- f27ff281-d697-4da1-a47c-31749f573a6d
- Group
- 2dc44b22-b1dd-460a-a704-6462d6e91096
- Curve Closest Point
- Find the closest point on a curve.
- true
- 471229c7-3a45-429f-b0fa-94a45dae9b20
- true
- Curve Closest Point
- Curve Closest Point
-
9965
-31375
108
64
-
10009
-31343
- Point to project onto curve
- a22e5dc2-7aea-41cc-bc34-0af6fd6dff09
- true
- Point
- Point
- false
- f2e837e8-96af-4a0b-b80b-0dac5228b855
- 1
-
9967
-31373
30
30
-
9982
-31358
- Curve to project onto
- fe5ffe52-63f4-4054-b970-a8cd10e33174
- true
- Curve
- Curve
- false
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9967
-31343
30
30
-
9982
-31328
- Point on the curve closest to the base point
- 47b0dbfd-13d8-4a67-86d8-a24e8f565729
- true
- Point
- Point
- false
- 0
-
10021
-31373
50
20
-
10046
-31363
- Parameter on curve domain of closest point
- 6ac0259f-1c38-4ef5-94f5-eec70f4d8db9
- true
- Parameter
- Parameter
- false
- 0
-
10021
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50
20
-
10046
-31343
- Distance between base point and curve
- c71ef2fb-fa1a-46b7-9f20-bd7f75e661ca
- true
- Distance
- Distance
- false
- 0
-
10021
-31333
50
20
-
10046
-31323
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- c354b686-ceeb-4f9b-967c-89b7a10a2e8d
- true
- Line
- Line
-
9968
-31454
102
44
-
10034
-31432
- Line start point
- 6149bcaa-82a0-4690-a0bd-5813e840ea42
- true
- Start Point
- Start Point
- false
- 47b0dbfd-13d8-4a67-86d8-a24e8f565729
- 1
-
9970
-31452
52
20
-
9996
-31442
- Line end point
- 718fc483-7ccd-484f-a141-81ad5db06e46
- true
- End Point
- End Point
- false
- f2e837e8-96af-4a0b-b80b-0dac5228b855
- 1
-
9970
-31432
52
20
-
9996
-31422
- Line segment
- b236cb6d-586e-4db4-8608-bc3cfb183bfb
- true
- Line
- Line
- false
- 0
-
10046
-31452
22
40
-
10057
-31432
- 2fcc2743-8339-4cdf-a046-a1f17439191d
- Remap Numbers
- Remap numbers into a new numeric domain
- true
- 16a99370-5eb6-4fce-aeec-d7680f2fe05d
- true
- Remap Numbers
- Remap Numbers
-
9942
-32765
154
64
-
10042
-32733
- Value to remap
- a6e1fcd6-e49f-46e9-a872-7e47b8af5ea9
- true
- Value
- Value
- false
- b6b279d5-4ed9-47c5-ab20-b7eca939f3fc
- 1
-
9944
-32763
86
20
-
9987
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- Source domain
- af14e9d0-e86c-496c-b6f9-9f6bc2814eef
- true
- Source
- Source
- false
- b22c79a2-0d33-46d7-9284-57f3b4abbb8f
- 1
-
9944
-32743
86
20
-
9987
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- 1
- 1
- {0}
-
0
1
- Target domain
- d4fccc4e-bf36-471c-9b81-ba3f8d701373
- true
- Target
- Target
- false
- 0
-
9944
-32723
86
20
-
9987
-32713
- 1
- 1
- {0}
-
-1
1
- Remapped number
- f42a7e48-9398-409b-8a64-da1367bb2942
- true
- Mapped
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- false
- 0
-
10054
-32763
40
30
-
10074
-32748
- Remapped and clipped number
- 689f688b-07fe-4428-9c4e-370f641273b0
- true
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- Clipped
- false
- 0
-
10054
-32733
40
30
-
10074
-32718
- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
- true
- 5fe01426-5385-4a08-b8ea-7640aed5ecfb
- true
- Bounds
- Bounds
-
9964
-32683
110
28
-
10022
-32669
- 1
- Numbers to include in Bounds
- 5554d382-be36-4514-8504-a01372c39b80
- true
- Numbers
- Numbers
- false
- b6b279d5-4ed9-47c5-ab20-b7eca939f3fc
- 1
-
9966
-32681
44
24
-
9988
-32669
- Numeric Domain between the lowest and highest numbers in {N}
- b22c79a2-0d33-46d7-9284-57f3b4abbb8f
- true
- Domain
- Domain
- false
- 0
-
10034
-32681
38
24
-
10053
-32669
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- b6b279d5-4ed9-47c5-ab20-b7eca939f3fc
- true
- Relay
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- List to shift
- 583b1759-3c4b-47bb-9e27-6b11fa36060d
- true
- List
-
- false
- f3da83a8-552c-4482-9825-f165df6fa732
- 1
-
9994
-21583
19
20
-
10003.5
-21573
- Shift offset
- f08dd486-1be7-4f98-aedf-61299fe3a4ed
- true
- Shift
-
- false
- 0
-
9994
-21563
19
20
-
10003.5
-21553
- 1
- 1
- {0}
- 1
- Wrap values
- 58fd8c5f-5878-4464-b802-3b968b4db22b
- true
- Wrap
-
- false
- 0
-
9994
-21543
19
20
-
10003.5
-21533
- 1
- 1
- {0}
- false
- 1
- Shifted list
- f63f83de-17f7-454a-bc36-895bc7488c7e
- true
- List
-
- false
- 0
-
10037
-21583
6
60
-
10040
-21553
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- a6f8cf40-4283-40d2-bc90-805bb563f9b1
- true
- Shift List
-
-
9992
-25085
53
64
-
10025
-25053
- 1
- List to shift
- 5499e5b9-8cb2-49eb-9c30-f42c02160bb0
- true
- List
-
- false
- 53cd2fb9-04f7-425c-aaa0-2f8eff8d768a
- 1
-
9994
-25083
19
20
-
10003.5
-25073
- Shift offset
- 1729daa5-e944-4ea1-b8b3-d12f2997dc4e
- true
- Shift
-
- false
- 0
-
9994
-25063
19
20
-
10003.5
-25053
- 1
- 1
- {0}
- 1
- Wrap values
- 8d1dfbee-0649-4ac4-af78-b408219fcce4
- true
- Wrap
-
- false
- 0
-
9994
-25043
19
20
-
10003.5
-25033
- 1
- 1
- {0}
- false
- 1
- Shifted list
- ab4f4689-c6b1-486b-8d63-2934c6b34e6f
- true
- List
-
- false
- 0
-
10037
-25083
6
60
-
10040
-25053
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- ff2559cf-18b3-4cad-b391-315893967bf2
- true
- Shift List
-
-
9992
-28449
53
64
-
10025
-28417
- 1
- List to shift
- 273f5044-a2c4-4e53-b232-745a3aba44a6
- true
- List
-
- false
- 2d37b54a-d252-4d91-af08-37f5c09e7e4a
- 1
-
9994
-28447
19
20
-
10003.5
-28437
- Shift offset
- 5b25285d-2173-464a-b270-22bf8a418ba0
- true
- Shift
-
- false
- 0
-
9994
-28427
19
20
-
10003.5
-28417
- 1
- 1
- {0}
- 1
- Wrap values
- 4a0100fa-492c-44ed-8efd-286b52e4296b
- true
- Wrap
-
- false
- 0
-
9994
-28407
19
20
-
10003.5
-28397
- 1
- 1
- {0}
- false
- 1
- Shifted list
- d57b5cda-0b57-4731-b527-b630d209be02
- true
- List
-
- false
- 0
-
10037
-28447
6
60
-
10040
-28417
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- 27b1909a-f125-4246-82be-4d422422f56c
- true
- Shift List
-
-
9992
-31775
53
64
-
10025
-31743
- 1
- List to shift
- bfcc7bea-5c84-4cb4-9ff7-0de9927cd430
- true
- List
-
- false
- b0b2a1b6-2a67-466d-9bdf-e8b50dccde48
- 1
-
9994
-31773
19
20
-
10003.5
-31763
- Shift offset
- 4f2a1b86-0f17-49bd-9fca-cbdc3d33ec14
- true
- Shift
-
- false
- 0
-
9994
-31753
19
20
-
10003.5
-31743
- 1
- 1
- {0}
- 1
- Wrap values
- b943df66-5f34-449f-a95b-f9c2d9811644
- true
- Wrap
-
- false
- 0
-
9994
-31733
19
20
-
10003.5
-31723
- 1
- 1
- {0}
- false
- 1
- Shifted list
- 628a45ae-3f38-4501-9306-b3bfe07a4a69
- true
- List
-
- false
- 0
-
10037
-31773
6
60
-
10040
-31743
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 55fcfa84-e04c-40ca-ae46-cc937e27bc97
- 3472779d-20db-40dc-8dba-0814a38b261e
- 9b318109-1854-4397-bf67-7f973c203aaa
- 8d65e4f1-504b-4486-8089-12d4064e8ba6
- e027a95f-405b-4d15-be30-520d91dbc5fc
- 884f7be6-32bb-4a29-903a-e313a43a21a0
- 3b821991-b5a9-4b03-b173-4a07543fc3bf
- 311bc15c-dfda-4a2d-a0a3-be16e5695d2f
- 857bb5ff-1ad6-4170-8b10-ee3ac17d9761
- a2874c09-6237-43a6-9770-654bb457fea2
- eef9bfc4-b532-42a0-bd17-b8664766f22d
- dc8cf255-b505-46bc-b318-2ae7c8c46b35
- 76231faf-dae2-4926-9f6b-2c8077bcac89
- 0343763a-82b3-483e-8d95-68ddd2c05938
- 8951eabd-7737-4a9d-88fc-d15ea0349bc1
- 7248ed6f-8fe9-480c-a442-80bf5073e3d3
- 7bc36f90-e59b-4ccb-9ddb-02043549301b
- 5c80a561-0d3a-46cd-a6f0-592d796712c5
- 87a2227f-c42b-4756-b84e-5cb0c48ee4fa
- a9701972-e21e-4da9-9c28-b38c5fd5ee91
- c192e380-8d44-4588-9699-871bb46e733f
- 8fe511eb-1233-498f-a8f7-d34dd4f617ff
- ec2ad91e-428d-4859-a2f4-c060e48f0123
- 6cec9000-baec-41ef-973b-b71a94f021fc
- c6ae0cff-05a7-4886-8aec-979f2907fe15
- e255ea20-b4ac-48b1-9e1b-0980e7594d5c
- 4a75522d-3e59-45b0-a235-b3d518b6df35
- cd5303fe-9c39-4150-8623-a6ac735d2876
- 0ef4bcf5-e770-4833-ad57-d7559ac0cfa8
- e328ed3a-fdf2-475b-930e-eac036796207
- 31d327cb-78e9-4772-9b77-ece7f5772c9a
- 4b4766df-9c4a-478a-a5ec-86bcf578667e
- ddda8bc0-631e-4735-96ff-a584cfbe1986
- 33
- 69a821a3-8a73-4cec-baac-b9a13a42017b
- Group
- afb96615-c59a-45c9-9cac-e27acb1c7ca0
- Explode
- Explode a curve into smaller segments.
- true
- 55fcfa84-e04c-40ca-ae46-cc937e27bc97
- true
- Explode
- Explode
-
9952
-34107
134
44
-
10023
-34085
- Curve to explode
- 7da04cc2-bf5d-4d0e-bcab-169bff54c587
- true
- Curve
- Curve
- false
- 88c9d358-2164-494c-93cd-620bfe195f0b
- 1
-
9954
-34105
57
20
-
9982.5
-34095
- Recursive decomposition until all segments are atomic
- 4bf6b70a-6c34-468c-aa86-94afd01fb357
- true
- Recursive
- Recursive
- false
- 0
-
9954
-34085
57
20
-
9982.5
-34075
- 1
- 1
- {0}
- true
- 1
- Exploded segments that make up the base curve
- 6c4a04a3-a43f-457d-983f-5cf6e15c55b3
- true
- Segments
- Segments
- false
- 0
-
10035
-34105
49
20
-
10059.5
-34095
- 1
- Vertices of the exploded segments
- 4cbdd9d2-e4c9-48ca-a29a-60721e988124
- true
- Vertices
- Vertices
- false
- 0
-
10035
-34085
49
20
-
10059.5
-34075
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 3472779d-20db-40dc-8dba-0814a38b261e
- true
- Evaluate Length
- Evaluate Length
-
9944
-34190
149
64
-
10029
-34158
- Curve to evaluate
- 61ed4f99-0318-4550-9b89-e471060e49cd
- true
- Curve
- Curve
- false
- 6c4a04a3-a43f-457d-983f-5cf6e15c55b3
- 1
-
9946
-34188
71
20
-
9981.5
-34178
- Length factor for curve evaluation
- 9f2f27a2-8d4e-4115-b063-8157dc5bc3c7
- true
- Length
- Length
- false
- 0
-
9946
-34168
71
20
-
9981.5
-34158
- 1
- 1
- {0}
- 0.5
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 5a640dfc-16bc-4d45-9299-3990b3d869ea
- true
- Normalized
- Normalized
- false
- 0
-
9946
-34148
71
20
-
9981.5
-34138
- 1
- 1
- {0}
- true
- Point at the specified length
- 83d865c2-6775-4675-9f8a-220e22ddae31
- true
- Point
- Point
- false
- 0
-
10041
-34188
50
20
-
10066
-34178
- Tangent vector at the specified length
- 93b233c7-cc87-47af-a8da-a31536701d3a
- true
- Tangent
- Tangent
- false
- 0
-
10041
-34168
50
20
-
10066
-34158
- Curve parameter at the specified length
- c83c9c3e-20cb-4973-90a0-33613bc0b9bf
- true
- Parameter
- Parameter
- false
- 0
-
10041
-34148
50
20
-
10066
-34138
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
- 9b318109-1854-4397-bf67-7f973c203aaa
- true
- Line SDL
- Line SDL
-
9964
-35970
110
64
-
10038
-35938
- Line start point
- 7517af86-db7e-4c90-b088-ebb63aeb9947
- true
- Start
- Start
- false
- 83d865c2-6775-4675-9f8a-220e22ddae31
- 1
-
9966
-35968
60
20
-
10004
-35958
- Line tangent (direction)
- 2a40b560-e61e-43ee-857d-4d109c9e2564
- true
- Direction
- Direction
- false
- d3dbebd8-864a-42c4-a1e6-9bde8c219738
- 1
-
9966
-35948
60
20
-
10004
-35938
- 1
- 1
- {0}
-
0
0
1
- Line length
- 9a51e0da-5a90-4c2f-a539-6f1169e6adcf
- ABS(X)
- true
- Length
- Length
- false
- 7feacf97-94fa-4c5e-b845-893325d06a8a
- 1
-
9966
-35928
60
20
-
10004
-35918
- 1
- 1
- {0}
- 0.015625
- Line segment
- 6760dc6d-999e-4284-b361-b5cb2b5a6f55
- true
- Line
- Line
- false
- 0
-
10050
-35968
22
60
-
10061
-35938
- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
- true
- 8d65e4f1-504b-4486-8089-12d4064e8ba6
- true
- Relative Differences
- Relative Differences
-
9961
-34533
116
28
-
10008
-34519
- 1
- List of data to operate on (numbers or points or vectors allowed)
- 8bdef77b-f99e-4151-baaa-1479ad4fb2a0
- true
- Values
- Values
- false
- cfb237b9-cda4-451f-88cf-681e8c1a12e1
- 1
-
9963
-34531
33
24
-
9979.5
-34519
- 1
- Differences between consecutive items
- 8945d4e1-f472-463e-8ed0-f9b54de13e94
- true
- Differenced
- Differenced
- false
- 0
-
10020
-34531
55
24
-
10047.5
-34519
- f3230ecb-3631-4d6f-86f2-ef4b2ed37f45
- Replace Nulls
- Replace nulls or invalid data with other data
- true
- e027a95f-405b-4d15-be30-520d91dbc5fc
- true
- Replace Nulls
- Replace Nulls
-
9949
-34477
139
44
-
10044
-34455
- 1
- Items to test for null
- 50e47417-d5fa-4fd6-80cb-1cd3825f090d
- true
- Items
- Items
- false
- 857bb5ff-1ad6-4170-8b10-ee3ac17d9761
- 1
-
9951
-34475
81
20
-
9991.5
-34465
- 1
- Items to replace nulls with
- 49bb910e-eb21-4eb7-a7f1-549dcb632f72
- true
- Replacements
- Replacements
- false
- 0
-
9951
-34455
81
20
-
9991.5
-34445
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- 1
- List without any nulls
- cfb237b9-cda4-451f-88cf-681e8c1a12e1
- true
- Items
- Items
- false
- 0
-
10056
-34475
30
20
-
10071
-34465
- Number of items replaced
- a42bf3d3-1e96-403d-b483-d487b33f5cb5
- true
- Count
- Count
- false
- 0
-
10056
-34455
30
20
-
10071
-34445
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 857bb5ff-1ad6-4170-8b10-ee3ac17d9761
- true
- Relay
- false
- d519f8f3-6b31-4df4-b45f-1a71a2d468c3
- 1
-
9999
-34414
40
16
-
10019
-34406
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- a2874c09-6237-43a6-9770-654bb457fea2
- true
- Relay
- false
- f50a8f1c-4788-43be-b2e2-986396a4b91f
- 1
-
9999
-34778
40
16
-
10019
-34770
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 8d65e4f1-504b-4486-8089-12d4064e8ba6
- e027a95f-405b-4d15-be30-520d91dbc5fc
- 884f7be6-32bb-4a29-903a-e313a43a21a0
- 3b821991-b5a9-4b03-b173-4a07543fc3bf
- 311bc15c-dfda-4a2d-a0a3-be16e5695d2f
- 857bb5ff-1ad6-4170-8b10-ee3ac17d9761
- a2874c09-6237-43a6-9770-654bb457fea2
- cce0cf82-c2e4-4967-b2d7-8d1450f4e4ff
- 8
- eef9bfc4-b532-42a0-bd17-b8664766f22d
- Group
- 2dc44b22-b1dd-460a-a704-6462d6e91096
- Curve Closest Point
- Find the closest point on a curve.
- true
- dc8cf255-b505-46bc-b318-2ae7c8c46b35
- true
- Curve Closest Point
- Curve Closest Point
-
9965
-34278
108
64
-
10009
-34246
- Point to project onto curve
- 9f2045f7-84db-41a3-80a7-b78554fc6dc3
- true
- Point
- Point
- false
- 83d865c2-6775-4675-9f8a-220e22ddae31
- 1
-
9967
-34276
30
30
-
9982
-34261
- Curve to project onto
- 53c74feb-bd8c-4934-b455-c4061c58e591
- true
- Curve
- Curve
- false
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9967
-34246
30
30
-
9982
-34231
- Point on the curve closest to the base point
- 3800975a-d9c1-4d01-8d3c-5fe396f11ea9
- true
- Point
- Point
- false
- 0
-
10021
-34276
50
20
-
10046
-34266
- Parameter on curve domain of closest point
- 802dfdfc-00c0-4e0d-88cd-b70ffb31a626
- true
- Parameter
- Parameter
- false
- 0
-
10021
-34256
50
20
-
10046
-34246
- Distance between base point and curve
- 3a8aa4d2-6fcc-4120-8b54-3111253d7cb2
- true
- Distance
- Distance
- false
- 0
-
10021
-34236
50
20
-
10046
-34226
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- 76231faf-dae2-4926-9f6b-2c8077bcac89
- true
- Line
- Line
-
9968
-34357
102
44
-
10034
-34335
- Line start point
- 2b14c6a3-4ad6-47d8-87b3-1587dd6eecf0
- true
- Start Point
- Start Point
- false
- 3800975a-d9c1-4d01-8d3c-5fe396f11ea9
- 1
-
9970
-34355
52
20
-
9996
-34345
- Line end point
- 1672f208-89e5-473d-a789-52bcc3c501c6
- true
- End Point
- End Point
- false
- 83d865c2-6775-4675-9f8a-220e22ddae31
- 1
-
9970
-34335
52
20
-
9996
-34325
- Line segment
- d3dbebd8-864a-42c4-a1e6-9bde8c219738
- true
- Line
- Line
- false
- 0
-
10046
-34355
22
40
-
10057
-34335
- 2fcc2743-8339-4cdf-a046-a1f17439191d
- Remap Numbers
- Remap numbers into a new numeric domain
- true
- 0343763a-82b3-483e-8d95-68ddd2c05938
- true
- Remap Numbers
- Remap Numbers
-
9942
-35668
154
64
-
10042
-35636
- Value to remap
- fbb75435-dbda-4a99-b5de-a7f860bb107d
- true
- Value
- Value
- false
- 7248ed6f-8fe9-480c-a442-80bf5073e3d3
- 1
-
9944
-35666
86
20
-
9987
-35656
- Source domain
- bda3bd9e-69c4-4252-8fbd-8445a285ec60
- true
- Source
- Source
- false
- 4cc59e7a-388e-4875-939d-e051a56dbf0a
- 1
-
9944
-35646
86
20
-
9987
-35636
- 1
- 1
- {0}
-
0
1
- Target domain
- 6ed6b452-6999-4bc0-9d9b-1edae4d23e5e
- true
- Target
- Target
- false
- 0
-
9944
-35626
86
20
-
9987
-35616
- 1
- 1
- {0}
-
-1
1
- Remapped number
- 0eaed2fe-a667-4ec0-bd86-4b5c20e158fe
- true
- Mapped
- Mapped
- false
- 0
-
10054
-35666
40
30
-
10074
-35651
- Remapped and clipped number
- 43ee08e0-34ae-4987-87d2-49bd6063b895
- true
- Clipped
- Clipped
- false
- 0
-
10054
-35636
40
30
-
10074
-35621
- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
- true
- 8951eabd-7737-4a9d-88fc-d15ea0349bc1
- true
- Bounds
- Bounds
-
9964
-35586
110
28
-
10022
-35572
- 1
- Numbers to include in Bounds
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60
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- Group
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255;255;255;255
- A group of Grasshopper objects
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- Group
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- Explode
- Explode a curve into smaller segments.
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- Explode
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134
44
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10023
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- Curve to explode
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9954
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57
20
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- Recursive decomposition until all segments are atomic
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9954
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57
20
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- Exploded segments that make up the base curve
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49
20
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- Vertices of the exploded segments
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10035
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49
20
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10059.5
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- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- Evaluate Length
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9944
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149
64
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10029
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- Curve to evaluate
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9946
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71
20
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- Length factor for curve evaluation
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- Length
- Length
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- 0
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9946
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71
20
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9981.5
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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9946
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71
20
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9981.5
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- Point at the specified length
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10041
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50
20
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10066
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- Tangent vector at the specified length
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10041
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50
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10066
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- Curve parameter at the specified length
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10041
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50
20
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10066
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- Line SDL
- Create a line segment defined by start point, tangent and length.}
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- Line SDL
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9964
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110
64
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10038
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- Line start point
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9966
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60
20
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10004
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- Line tangent (direction)
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9966
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60
20
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10004
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- 1
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0
0
1
- Line length
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- ABS(X)
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- Length
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9966
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60
20
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10004
-38651
- 1
- 1
- {0}
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- Line segment
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- Line
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-
10050
-38701
22
60
-
10061
-38671
- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
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- Relative Differences
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9961
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116
28
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10008
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- 1
- List of data to operate on (numbers or points or vectors allowed)
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9963
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33
24
-
9979.5
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- 1
- Differences between consecutive items
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10020
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55
24
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10047.5
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- Replace Nulls
- Replace nulls or invalid data with other data
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- Replace Nulls
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139
44
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10044
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- Items to test for null
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9951
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81
20
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9991.5
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- 1
- Items to replace nulls with
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9951
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81
20
-
9991.5
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- 1
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- {0}
- Grasshopper.Kernel.Types.GH_Integer
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- List without any nulls
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- Items
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- 0
-
10056
-37208
30
20
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10071
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- Number of items replaced
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- Count
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- 0
-
10056
-37188
30
20
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10071
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- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
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- A wire relay object
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- a2874c09-6237-43a6-9770-654bb457fea2
- 1
-
9999
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40
16
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10019
-37139
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
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- A wire relay object
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- 1
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9999
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40
16
-
10019
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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255;255;255;255
- A group of Grasshopper objects
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- Group
- 2dc44b22-b1dd-460a-a704-6462d6e91096
- Curve Closest Point
- Find the closest point on a curve.
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-
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108
64
-
10009
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- Point to project onto curve
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9967
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30
30
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- Curve to project onto
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9967
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30
30
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9982
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- Point on the curve closest to the base point
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10021
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50
20
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10046
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- Parameter on curve domain of closest point
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10021
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50
20
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10046
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- Distance between base point and curve
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10021
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50
20
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10046
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- Line
- Create a line between two points.
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- Line
- Line
-
9968
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102
44
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10034
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- Line start point
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-
9970
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52
20
-
9996
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- Line end point
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- End Point
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- 1
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9970
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52
20
-
9996
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- Line segment
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10046
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22
40
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10057
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- 2fcc2743-8339-4cdf-a046-a1f17439191d
- Remap Numbers
- Remap numbers into a new numeric domain
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- Remap Numbers
- Remap Numbers
-
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154
64
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10042
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- Value to remap
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- Value
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9944
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86
20
-
9987
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- Source domain
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9944
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86
20
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9987
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- 1
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0
1
- Target domain
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9944
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86
20
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9987
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- 1
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-1
1
- Remapped number
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10054
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40
30
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10074
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- Remapped and clipped number
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- 0
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10054
-38369
40
30
-
10074
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- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
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- Bounds
- Bounds
-
9964
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110
28
-
10022
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- 1
- Numbers to include in Bounds
- 49415ea8-f221-4f10-a9df-e369069dea33
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- Numbers
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- 6d25ea6f-a7d2-45e7-b706-0a351dae8af6
- 1
-
9966
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44
24
-
9988
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- Numeric Domain between the lowest and highest numbers in {N}
- ea35401e-6ba0-4caa-8035-59c0f52f7ed1
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- Domain
- Domain
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- 0
-
10034
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38
24
-
10053
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- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
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- 0b398c44-b153-429a-a1b5-6f1d3fd52e44
- 1
-
9999
-38272
40
16
-
10019
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- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
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- Multiplication
-
9984
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70
44
-
10009
-38578
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for multiplication
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- A
- A
- true
- bfad49f8-a916-48ea-8af7-841039669257
- 1
-
9986
-38598
11
20
-
9991.5
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- Second item for multiplication
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- B
- B
- true
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- 1
-
9986
-38578
11
20
-
9991.5
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- Result of multiplication
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- 0
-
10021
-38598
31
40
-
10036.5
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- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
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- c45dc8c8-8f0b-4673-a31f-e8a700458ba9
- true
- Multiplication
- Multiplication
-
9984
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70
44
-
10009
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- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
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- First item for multiplication
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- A
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- true
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- 1
-
9986
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11
20
-
9991.5
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- Second item for multiplication
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- B
- B
- true
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- 1
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9986
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11
20
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- Result of multiplication
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- true
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- 0
-
10021
-38491
31
40
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10036.5
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- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
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- A wire relay object
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- 1
-
9999
-38428
40
16
-
10019
-38420
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- Evaluate Length
- Evaluate Length
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9944
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149
64
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10029
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- Curve to evaluate
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9946
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71
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- Length factor for curve evaluation
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- Length
- Length
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- 0
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9946
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71
20
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9981.5
-39663
- 1
- 1
- {0}
- 0.5
- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Normalized
- Normalized
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9946
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71
20
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9981.5
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- 1
- {0}
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- Point at the specified length
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- Point
- Point
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10041
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50
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10066
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- Tangent vector at the specified length
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- Tangent
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10041
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50
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10066
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- Curve parameter at the specified length
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- Parameter
- Parameter
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10041
-39653
50
20
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10066
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- Line SDL
- Create a line segment defined by start point, tangent and length.}
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- true
- Line SDL
- Line SDL
-
9964
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110
64
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10038
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- Line start point
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- Start
- Start
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- 1
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9966
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60
20
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10004
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- Line tangent (direction)
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- Direction
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- 1
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9966
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60
20
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10004
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- {0}
-
0
0
1
- Line length
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- ABS(X)
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- Length
- Length
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- 1
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9966
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60
20
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10004
-41423
- 1
- 1
- {0}
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- Line segment
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- Line
- Line
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- 0
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10050
-41473
22
60
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10061
-41443
- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
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- Relative Differences
- Relative Differences
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9961
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116
28
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10008
-40024
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- List of data to operate on (numbers or points or vectors allowed)
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- Values
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9963
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33
24
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9979.5
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- Differences between consecutive items
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- Differenced
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- 0
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10020
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55
24
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10047.5
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- Replace Nulls
- Replace nulls or invalid data with other data
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- true
- Replace Nulls
- Replace Nulls
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139
44
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10044
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- Items to test for null
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- Items
- Items
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9951
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81
20
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9991.5
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- 1
- Items to replace nulls with
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- Replacements
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- 0
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9951
-39960
81
20
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9991.5
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- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- 1
- List without any nulls
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- Items
- Items
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- 0
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10056
-39980
30
20
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10071
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- Number of items replaced
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- Count
- Count
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- 0
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10056
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30
20
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10071
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- Relay
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- A wire relay object
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- Relay
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9999
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40
16
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10019
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- Relay
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- A wire relay object
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- Relay
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9999
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40
16
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10019
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- Group
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255;255;255;255
- A group of Grasshopper objects
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- Group
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- Curve Closest Point
- Find the closest point on a curve.
- true
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- Curve Closest Point
- Curve Closest Point
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9965
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108
64
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10009
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- Point to project onto curve
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- Point
- Point
- false
- 2197bce1-f68f-471f-bb60-8dc1126e5d5c
- 1
-
9967
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30
30
-
9982
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- Curve to project onto
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- Curve
- Curve
- false
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9967
-39751
30
30
-
9982
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- Point on the curve closest to the base point
- 3a62e2ed-5f18-4b58-9b7c-abdf3421393a
- true
- Point
- Point
- false
- 0
-
10021
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50
20
-
10046
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- Parameter on curve domain of closest point
- 83debea0-1051-453f-bde9-e3f7b530cf31
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- Parameter
- Parameter
- false
- 0
-
10021
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50
20
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10046
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- Distance between base point and curve
- ac24d5d1-09fd-4f88-afb4-757428af69d4
- true
- Distance
- Distance
- false
- 0
-
10021
-39741
50
20
-
10046
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- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- bb0fcba4-e38d-46cb-8c0d-ec2d7b6870f7
- true
- Line
- Line
-
9968
-39862
102
44
-
10034
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- Line start point
- e7174931-751b-471b-9d05-c8e854a34450
- true
- Start Point
- Start Point
- false
- 3a62e2ed-5f18-4b58-9b7c-abdf3421393a
- 1
-
9970
-39860
52
20
-
9996
-39850
- Line end point
- 5022a9dc-7236-47d8-b9f4-5632b4ffc849
- true
- End Point
- End Point
- false
- 2197bce1-f68f-471f-bb60-8dc1126e5d5c
- 1
-
9970
-39840
52
20
-
9996
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- Line segment
- 0dba2486-babe-430b-b4ed-658b8e1f4191
- true
- Line
- Line
- false
- 0
-
10046
-39860
22
40
-
10057
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- 2fcc2743-8339-4cdf-a046-a1f17439191d
- Remap Numbers
- Remap numbers into a new numeric domain
- true
- d9e1fe07-f0c7-4e80-b5d2-caeab5dde50d
- true
- Remap Numbers
- Remap Numbers
-
9942
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154
64
-
10042
-41141
- Value to remap
- 066e0dcf-6a72-490b-b2ae-8b5f43523539
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- Value
- Value
- false
- c33e604d-7d26-4a47-9c7e-09025971c3f9
- 1
-
9944
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86
20
-
9987
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- Source domain
- 03322ba0-3e54-40b3-81b6-8f2ab7084a86
- true
- Source
- Source
- false
- a4fd12f3-8762-4a35-9260-df1832024df6
- 1
-
9944
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86
20
-
9987
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- 1
- 1
- {0}
-
0
1
- Target domain
- 5a53d579-91f4-4cc0-a385-29d140583b42
- true
- Target
- Target
- false
- 0
-
9944
-41131
86
20
-
9987
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- 1
- 1
- {0}
-
-1
1
- Remapped number
- 807e84d5-b94b-408a-8a48-36cde0f92684
- true
- Mapped
- Mapped
- false
- 0
-
10054
-41171
40
30
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10074
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- Remapped and clipped number
- be36f863-63cf-4d84-b24c-6c9ed4afafb2
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- Clipped
- Clipped
- false
- 0
-
10054
-41141
40
30
-
10074
-41126
- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
- true
- ef83b5ad-5921-4e34-ac03-3937ca0519dd
- true
- Bounds
- Bounds
-
9964
-41091
110
28
-
10022
-41077
- 1
- Numbers to include in Bounds
- 37f8d950-af9a-41e0-8683-b78b995f174e
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- Numbers
- Numbers
- false
- c33e604d-7d26-4a47-9c7e-09025971c3f9
- 1
-
9966
-41089
44
24
-
9988
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- Numeric Domain between the lowest and highest numbers in {N}
- a4fd12f3-8762-4a35-9260-df1832024df6
- true
- Domain
- Domain
- false
- 0
-
10034
-41089
38
24
-
10053
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- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- c33e604d-7d26-4a47-9c7e-09025971c3f9
- true
- Relay
-
- false
- 9ea69cbf-fd9b-4e3c-ab23-c9527df04c08
- 1
-
9999
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40
16
-
10019
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- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
- d1729450-c8f6-42b2-898a-ab0ea260f401
- true
- Multiplication
- Multiplication
-
9984
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70
44
-
10009
-41350
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
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- First item for multiplication
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- A
- A
- true
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- 1
-
9986
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11
20
-
9991.5
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- Second item for multiplication
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- B
- B
- true
- e1a9abe3-f7cd-446d-828c-eb66e5fcbf81
- 1
-
9986
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11
20
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9991.5
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- Result of multiplication
- e0ca5b10-1779-4d5d-87fc-94ba5230a35f
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- 0
-
10021
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31
40
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10036.5
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- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
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- Multiplication
- Multiplication
-
9984
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70
44
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10009
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- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- First item for multiplication
- 49f0fbb6-c811-4993-b14a-0ef22ebffa6a
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- A
- A
- true
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- 1
-
9986
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11
20
-
9991.5
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- Second item for multiplication
- 7d87e8bf-c9a5-4ff5-acfe-c28644bf1036
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- B
- B
- true
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9986
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11
20
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9991.5
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- Result of multiplication
- ae312712-fc06-4768-8371-d8eda762ebfb
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10021
-41263
31
40
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10036.5
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- Relay
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- A wire relay object
- 6432047b-8976-4090-9ff0-8e30d5a49928
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9999
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40
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10019
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- Group
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-
255;255;255;255
- A group of Grasshopper objects
- d9e1fe07-f0c7-4e80-b5d2-caeab5dde50d
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- Group
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Group
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- Panel
- A panel for custom notes and text values
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- Double click to edit panel content…
-
9933
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185
271
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9933.656
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255;255;255;255
- true
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- A wire relay object
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-
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-
9999
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40
16
-
10019
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- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
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-
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-
9999
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40
16
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10019
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- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Group
- 76975309-75a6-446a-afed-f8653720a9f2
- Create Material
- Create an OpenGL material.
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- Create Material
- Create Material
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9943
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152
104
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10041
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- Colour of the diffuse channel
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9945
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84
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9987
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255;163;163;163
- Colour of the specular highlight
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9945
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84
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9987
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255;0;255;255
- Emissive colour of the material
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9945
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84
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9987
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255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
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9945
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84
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- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
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255;255;255;255
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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159
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- Create an OpenGL material.
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255;221;160;221
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255;66;48;66
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255;255;255;255
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- Replace Nulls
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139
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10044
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81
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9991.5
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- Items to replace nulls with
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9951
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81
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- List without any nulls
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10056
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30
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30
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9999
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10019
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9999
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10019
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255;255;255;255
- A group of Grasshopper objects
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- Group
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- Find the closest point on a curve.
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- Curve Closest Point
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108
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10009
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- Point to project onto curve
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30
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9982
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9967
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30
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- Point on the curve closest to the base point
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10021
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50
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10046
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10021
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50
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10046
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- Line
- Line
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102
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- Line end point
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52
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22
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- Remap Numbers
- Remap numbers into a new numeric domain
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- Remap Numbers
- Remap Numbers
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154
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- Value to remap
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- Value
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- Source domain
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9944
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- {0}
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- Target domain
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9944
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86
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-1
1
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40
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10054
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40
30
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10074
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- Bounds
- Create a numeric domain which encompasses a list of numbers.
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- Bounds
- Bounds
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- Numbers to include in Bounds
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9966
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44
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- Numeric Domain between the lowest and highest numbers in {N}
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38
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- Relay
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- A wire relay object
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9999
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40
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10019
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- Multiplication
- Mathematical multiplication
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- Multiplication
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10009
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- First item for multiplication
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11
20
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- Second item for multiplication
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9986
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11
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- Multiplication
- Mathematical multiplication
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70
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10009
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- First item for multiplication
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9986
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11
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- Second item for multiplication
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9986
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11
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10021
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31
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9999
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40
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- Group
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255;255;255;255
- A group of Grasshopper objects
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- Group
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- Group
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255;255;255;255
- A group of Grasshopper objects
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- Group
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- Panel
- A panel for custom notes and text values
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255;255;255;255
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9999
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40
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- Relay
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- Group
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255;255;255;255
- A group of Grasshopper objects
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- Group
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- Create Material
- Create an OpenGL material.
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152
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- Colour of the diffuse channel
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255;0;255;255
- Emissive colour of the material
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255;0;0;0
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- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
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- Resulting material
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10053
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40
100
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- Allows for customized geometry previews
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- The material override
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48
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255;221;160;221
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255;66;48;66
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255;255;255;255
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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149
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- Curve to evaluate
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71
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- Length factor for curve evaluation
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- Length
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71
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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71
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- {0}
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- Point at the specified length
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50
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10066
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- Tangent vector at the specified length
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50
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- Curve parameter at the specified length
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10041
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50
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10066
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- Create an interpolated curve through a set of points.
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225
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- Interpolation points
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159
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- Curve degree
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159
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159
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- Knot spacing (0=uniform, 1=chord, 2=sqrtchord)
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- 758d91a0-4aec-47f8-9671-16739a8a2c5d
- Format
- Format some data using placeholders and formatting tags
- true
- afa7eb49-ddb4-4ad5-a083-3d766e0880af
- true
- Format
- Format
-
9954
-46061
130
64
-
10046
-46029
- 3
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- 7fa15783-70da-485c-98c0-a099e6988c3e
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 3ede854e-c753-40eb-84cb-b48008f14fd4
- Text format
- 7bf1dd08-d03f-4722-8b14-ce8a5c3e73c2
- true
- Format
- Format
- false
- 0
-
9956
-46059
78
20
-
9995
-46049
- 1
- 1
- {0}
- false
- {0:R}
- Formatting culture
- 76b990d4-17a6-41ec-9954-fe5f0ce9f3a6
- true
- Culture
- Culture
- false
- 0
-
9956
-46039
78
20
-
9995
-46029
- 1
- 1
- {0}
- 127
- Data to insert at {0} placeholders
- 6f7ce437-9a98-4e7e-9b72-0414b6875dbb
- true
- false
- Data 0
- 0
- true
- db990e5a-7101-43fc-8c86-5d17627520de
- 1
-
9956
-46019
78
20
-
9995
-46009
- Formatted text
- 562d6de2-a470-4c87-851a-60f7d73c45ec
- true
- Text
- Text
- false
- 0
-
10058
-46059
24
60
-
10070
-46029
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- a74a9afa-f0e7-461e-8d02-835f7eb99731
- true
- Shift List
-
-
9992
-45777
53
64
-
10025
-45745
- 1
- List to shift
- b3c5bd37-19ee-4b56-9f84-99eeaf530316
- true
- List
-
- false
- e7ce9bba-c98c-4fa4-a826-13e1be5ec64f
- 1
-
9994
-45775
19
20
-
10003.5
-45765
- Shift offset
- 300e0933-a303-4121-98a7-8acbc90708a8
- true
- Shift
-
- false
- 0
-
9994
-45755
19
20
-
10003.5
-45745
- 1
- 1
- {0}
- 1
- Wrap values
- 1468092c-80ba-44ce-aa43-edc3111555c6
- true
- Wrap
-
- false
- 0
-
9994
-45735
19
20
-
10003.5
-45725
- 1
- 1
- {0}
- false
- 1
- Shifted list
- af081197-1368-48fe-8c47-3880d86c7e8a
- true
- List
-
- false
- 0
-
10037
-45775
6
60
-
10040
-45745
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- fb655f23-53fb-4216-9244-493c145ef300
- 5ee7302e-0432-45a9-b320-4441d0df5f9d
- 13a26b56-0263-46e2-aa96-b8798a43d2c3
- 5d6eced0-8de4-4481-a643-7bfe45510c30
- dd157dd8-02bf-451c-92e4-60a66dd76cd9
- 884f7be6-32bb-4a29-903a-e313a43a21a0
- 3b821991-b5a9-4b03-b173-4a07543fc3bf
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- a86281e6-4353-4d3f-9eb1-d7653305fca6
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- a8912d4a-a935-4bad-872b-dc57f88db955
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- eb6c4f88-5269-48a2-8baa-1cf1c83bc615
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- d23e8755-9d1f-4297-8921-86492be2c64d
- 793cf638-778c-4687-846d-12a170db3db8
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- 27ab95a4-918f-4a4e-ac15-19cd1893c17b
- 4fb50094-0407-4547-a635-d1cc9774cae0
- d56f82fd-936d-4975-aa5c-00df0fa76fe7
- ff508ccb-efa4-4301-a9ce-0c59234fafca
- cd2a4e73-beef-4881-af60-1072c3d132d9
- 05e896ad-741a-401e-ae86-0f19c9494cec
- 33
- 0d3e5c8a-1561-4e11-9e1e-e2fca33efcdb
- Group
- afb96615-c59a-45c9-9cac-e27acb1c7ca0
- Explode
- Explode a curve into smaller segments.
- true
- fb655f23-53fb-4216-9244-493c145ef300
- true
- Explode
- Explode
-
9952
-48076
134
44
-
10023
-48054
- Curve to explode
- 9767cfc5-25e4-4f8a-945a-f881a57c21aa
- true
- Curve
- Curve
- false
- 5dd2e2a9-34a6-4201-8cc9-620d4b4583f6
- 1
-
9954
-48074
57
20
-
9982.5
-48064
- Recursive decomposition until all segments are atomic
- 183a96dc-67cf-47eb-b503-33704d2de613
- true
- Recursive
- Recursive
- false
- 0
-
9954
-48054
57
20
-
9982.5
-48044
- 1
- 1
- {0}
- true
- 1
- Exploded segments that make up the base curve
- 34e69f67-2c8a-4d6b-ab01-779325b2045d
- true
- Segments
- Segments
- false
- 0
-
10035
-48074
49
20
-
10059.5
-48064
- 1
- Vertices of the exploded segments
- 0f682b44-c403-4726-bb64-4d33dc0bd13b
- true
- Vertices
- Vertices
- false
- 0
-
10035
-48054
49
20
-
10059.5
-48044
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 5ee7302e-0432-45a9-b320-4441d0df5f9d
- true
- Evaluate Length
- Evaluate Length
-
9944
-48159
149
64
-
10029
-48127
- Curve to evaluate
- 9a07bf97-34e2-444a-8e99-64a693f04333
- true
- Curve
- Curve
- false
- 34e69f67-2c8a-4d6b-ab01-779325b2045d
- 1
-
9946
-48157
71
20
-
9981.5
-48147
- Length factor for curve evaluation
- 1e21ec69-139a-4764-8822-04b4e11b8847
- true
- Length
- Length
- false
- 0
-
9946
-48137
71
20
-
9981.5
-48127
- 1
- 1
- {0}
- 0.5
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 7a7b5c58-fd2a-4808-a6e6-c31ea12bbff4
- true
- Normalized
- Normalized
- false
- 0
-
9946
-48117
71
20
-
9981.5
-48107
- 1
- 1
- {0}
- true
- Point at the specified length
- c9713282-cead-492a-b99c-1e8de818a7e4
- true
- Point
- Point
- false
- 0
-
10041
-48157
50
20
-
10066
-48147
- Tangent vector at the specified length
- 6dc474d9-a129-4a18-904d-35c727af5e6f
- true
- Tangent
- Tangent
- false
- 0
-
10041
-48137
50
20
-
10066
-48127
- Curve parameter at the specified length
- d98fddae-6984-4a43-a07f-a359e67c1f4e
- true
- Parameter
- Parameter
- false
- 0
-
10041
-48117
50
20
-
10066
-48107
- 4c619bc9-39fd-4717-82a6-1e07ea237bbe
- Line SDL
- Create a line segment defined by start point, tangent and length.}
- true
- 13a26b56-0263-46e2-aa96-b8798a43d2c3
- true
- Line SDL
- Line SDL
-
9964
-49939
110
64
-
10038
-49907
- Line start point
- 8ca90ede-8f05-48ff-96b8-962e60d968de
- true
- Start
- Start
- false
- c9713282-cead-492a-b99c-1e8de818a7e4
- 1
-
9966
-49937
60
20
-
10004
-49927
- Line tangent (direction)
- bd0c3312-24f2-4240-adc6-f68e9266b467
- true
- Direction
- Direction
- false
- 24cf92d8-0bb7-4e09-b78a-c442ecd7a305
- 1
-
9966
-49917
60
20
-
10004
-49907
- 1
- 1
- {0}
-
0
0
1
- Line length
- 5864852d-a783-4dfb-9d9b-aac5448bf4c7
- ABS(X)
- true
- Length
- Length
- false
- 387a9351-d494-47cf-851b-b4e757e2966e
- 1
-
9966
-49897
60
20
-
10004
-49887
- 1
- 1
- {0}
- 0.015625
- Line segment
- a60b1219-855c-4105-9d60-d49e4c21af43
- true
- Line
- Line
- false
- 0
-
10050
-49937
22
60
-
10061
-49907
- dd17d442-3776-40b3-ad5b-5e188b56bd4c
- Relative Differences
- Compute relative differences for a list of data
- true
- 5d6eced0-8de4-4481-a643-7bfe45510c30
- true
- Relative Differences
- Relative Differences
-
9961
-48502
116
28
-
10008
-48488
- 1
- List of data to operate on (numbers or points or vectors allowed)
- 28b0ff60-628d-4633-8c52-3036259e9a32
- true
- Values
- Values
- false
- 15c4058c-d4ef-48f0-8cd6-a6e9d66cb373
- 1
-
9963
-48500
33
24
-
9979.5
-48488
- 1
- Differences between consecutive items
- b56f4c54-4961-4b83-92cb-a5fc08f6b38b
- true
- Differenced
- Differenced
- false
- 0
-
10020
-48500
55
24
-
10047.5
-48488
- f3230ecb-3631-4d6f-86f2-ef4b2ed37f45
- Replace Nulls
- Replace nulls or invalid data with other data
- true
- dd157dd8-02bf-451c-92e4-60a66dd76cd9
- true
- Replace Nulls
- Replace Nulls
-
9949
-48446
139
44
-
10044
-48424
- 1
- Items to test for null
- f6c4fa24-bc33-406c-b097-e39a132737fe
- true
- Items
- Items
- false
- 4b41e74f-ded6-4ba6-9d30-a92b8bd882f4
- 1
-
9951
-48444
81
20
-
9991.5
-48434
- 1
- Items to replace nulls with
- 8b3a37a0-c996-4736-88d7-5ab7c63a7236
- true
- Replacements
- Replacements
- false
- 0
-
9951
-48424
81
20
-
9991.5
-48414
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
- 0
- 1
- List without any nulls
- 15c4058c-d4ef-48f0-8cd6-a6e9d66cb373
- true
- Items
- Items
- false
- 0
-
10056
-48444
30
20
-
10071
-48434
- Number of items replaced
- a2be282f-7c76-48da-8645-5a7224e1ee72
- true
- Count
- Count
- false
- 0
-
10056
-48424
30
20
-
10071
-48414
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 4b41e74f-ded6-4ba6-9d30-a92b8bd882f4
- true
- Relay
- false
- 666594ae-a74c-4919-83c2-fc42803f75a7
- 1
-
9999
-48383
40
16
-
10019
-48375
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 6793e99e-b90c-487a-b317-04ab2dc48de9
- true
- Relay
- false
- 75d25b48-e81a-46a3-9843-ac009cb61913
- 1
-
9999
-48747
40
16
-
10019
-48739
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 5d6eced0-8de4-4481-a643-7bfe45510c30
- dd157dd8-02bf-451c-92e4-60a66dd76cd9
- 884f7be6-32bb-4a29-903a-e313a43a21a0
- 3b821991-b5a9-4b03-b173-4a07543fc3bf
- 311bc15c-dfda-4a2d-a0a3-be16e5695d2f
- 4b41e74f-ded6-4ba6-9d30-a92b8bd882f4
- 6793e99e-b90c-487a-b317-04ab2dc48de9
- f9c91711-b3d2-4453-a9eb-775517adcba2
- 8
- d8641b5a-18fd-47ec-99cf-7eb566173a48
- Group
- 2dc44b22-b1dd-460a-a704-6462d6e91096
- Curve Closest Point
- Find the closest point on a curve.
- true
- 3a93d28b-110b-43b0-b8c2-580efd293bb4
- true
- Curve Closest Point
- Curve Closest Point
-
9965
-48247
108
64
-
10009
-48215
- Point to project onto curve
- 86defb83-e045-45c7-ac87-bf491e14b959
- true
- Point
- Point
- false
- c9713282-cead-492a-b99c-1e8de818a7e4
- 1
-
9967
-48245
30
30
-
9982
-48230
- Curve to project onto
- 8a7848dd-9c5d-4065-88cd-d13e51ecd083
- true
- Curve
- Curve
- false
- 8e01634f-6886-4da4-93cc-d84f2949b7f1
- 1
-
9967
-48215
30
30
-
9982
-48200
- Point on the curve closest to the base point
- e097ffc2-4a02-4b14-a35a-099424ff6a9b
- true
- Point
- Point
- false
- 0
-
10021
-48245
50
20
-
10046
-48235
- Parameter on curve domain of closest point
- 58554dae-a515-4393-86fb-82d921c5d519
- true
- Parameter
- Parameter
- false
- 0
-
10021
-48225
50
20
-
10046
-48215
- Distance between base point and curve
- 799ed65d-4182-4ee6-bb81-1758bc6d3f32
- true
- Distance
- Distance
- false
- 0
-
10021
-48205
50
20
-
10046
-48195
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- 293f4269-47f2-4643-ba3b-3e13a4fe7883
- true
- Line
- Line
-
9968
-48326
102
44
-
10034
-48304
- Line start point
- 4fb679bc-7f98-4a03-add5-497b6adf005f
- true
- Start Point
- Start Point
- false
- e097ffc2-4a02-4b14-a35a-099424ff6a9b
- 1
-
9970
-48324
52
20
-
9996
-48314
- Line end point
- 4c7dad60-41c8-4994-9282-109ef32dfa79
- true
- End Point
- End Point
- false
- c9713282-cead-492a-b99c-1e8de818a7e4
- 1
-
9970
-48304
52
20
-
9996
-48294
- Line segment
- 24cf92d8-0bb7-4e09-b78a-c442ecd7a305
- true
- Line
- Line
- false
- 0
-
10046
-48324
22
40
-
10057
-48304
- 2fcc2743-8339-4cdf-a046-a1f17439191d
- Remap Numbers
- Remap numbers into a new numeric domain
- true
- a86281e6-4353-4d3f-9eb1-d7653305fca6
- true
- Remap Numbers
- Remap Numbers
-
9942
-49637
154
64
-
10042
-49605
- Value to remap
- 26f31415-96f7-4bd3-b74b-bd5d01d9d20f
- true
- Value
- Value
- false
- 08e55973-3950-4b60-89f4-5a5d6d781df6
- 1
-
9944
-49635
86
20
-
9987
-49625
- Source domain
- ff3e2bfd-dae3-49c4-9eea-ec4da89835ef
- true
- Source
- Source
- false
- a6f1e98e-c654-4b65-9a18-c0d2a1b3b551
- 1
-
9944
-49615
86
20
-
9987
-49605
- 1
- 1
- {0}
-
0
1
- Target domain
- c324c9be-cf72-472a-bdac-be927c4f0854
- true
- Target
- Target
- false
- 0
-
9944
-49595
86
20
-
9987
-49585
- 1
- 1
- {0}
-
-1
1
- Remapped number
- 4f4db73d-5173-4701-a0c5-73cdda611bc9
- true
- Mapped
- Mapped
- false
- 0
-
10054
-49635
40
30
-
10074
-49620
- Remapped and clipped number
- 07e65e72-7094-478b-8fa8-1dd7c589b1f2
- true
- Clipped
- Clipped
- false
- 0
-
10054
-49605
40
30
-
10074
-49590
- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
- true
- d727fe22-76d5-43e4-a2ad-e015518775ab
- true
- Bounds
- Bounds
-
9964
-49555
110
28
-
10022
-49541
- 1
- Numbers to include in Bounds
- 937f8b64-1f53-47a0-aace-e59d4558007d
- true
- Numbers
- Numbers
- false
- 08e55973-3950-4b60-89f4-5a5d6d781df6
- 1
-
9966
-49553
44
24
-
9988
-49541
- Numeric Domain between the lowest and highest numbers in {N}
- a6f1e98e-c654-4b65-9a18-c0d2a1b3b551
- true
- Domain
- Domain
- false
- 0
-
10034
-49553
38
24
-
10053
-49541
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 08e55973-3950-4b60-89f4-5a5d6d781df6
- true
- Relay
-
- false
- 6793e99e-b90c-487a-b317-04ab2dc48de9
- 1
-
9999
-49508
40
16
-
10019
-49500
- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
- true
- a8912d4a-a935-4bad-872b-dc57f88db955
- true
- Multiplication
- Multiplication
-
9984
-49836
70
44
-
10009
-49814
- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First item for multiplication
- 126229b7-a3c9-48c2-907a-2efa6caee85a
- true
- A
- A
- true
- 40f47511-ffd1-477e-bc85-8e0aba14854a
- 1
-
9986
-49834
11
20
-
9991.5
-49824
- Second item for multiplication
- 63bd6145-31be-4e5b-be6f-5fdcbd3d404b
- true
- B
- B
- true
- 8f638ca0-ed19-449b-9dac-37d0d7994511
- 1
-
9986
-49814
11
20
-
9991.5
-49804
- Result of multiplication
- 387a9351-d494-47cf-851b-b4e757e2966e
- true
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- Group
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- Explode a curve into smaller segments.
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- Explode
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10023
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- Curve to explode
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9954
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- Recursive decomposition until all segments are atomic
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10035
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49
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- Evaluate Length
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- Curve to evaluate
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- Length factor for curve evaluation
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Tangent vector at the specified length
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- Create a line segment defined by start point, tangent and length.}
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- Line SDL
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110
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- Line start point
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- Line tangent (direction)
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60
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0
0
1
- Line length
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60
20
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10004
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10050
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22
60
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10061
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- Compute relative differences for a list of data
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- Relative Differences
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116
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10008
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- List of data to operate on (numbers or points or vectors allowed)
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33
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10020
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55
24
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- Replace nulls or invalid data with other data
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- Replace Nulls
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139
44
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10044
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81
20
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- Items to replace nulls with
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81
20
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9991.5
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- {0}
- Grasshopper.Kernel.Types.GH_Integer
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- List without any nulls
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30
20
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10071
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- Number of items replaced
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30
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- A wire relay object
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9999
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- Relay
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- A wire relay object
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9999
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- A group of Grasshopper objects
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- Find the closest point on a curve.
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- Curve Closest Point
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108
64
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10009
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- Point to project onto curve
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30
30
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- Curve to project onto
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9967
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30
30
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9982
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- Point on the curve closest to the base point
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10021
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50
20
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10046
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- Parameter on curve domain of closest point
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50
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10046
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- Distance between base point and curve
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10021
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50
20
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10046
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- Line
- Create a line between two points.
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- Line
- Line
-
9968
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102
44
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10034
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- Line start point
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- Start Point
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9970
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52
20
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9996
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- Line end point
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- End Point
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9970
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52
20
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9996
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- Line segment
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10046
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22
40
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10057
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- Remap numbers into a new numeric domain
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- Remap Numbers
- Remap Numbers
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154
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- Value to remap
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9944
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86
20
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9987
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- Source domain
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- Source
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9944
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86
20
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9987
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0
1
- Target domain
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9944
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86
20
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9987
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-1
1
- Remapped number
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10054
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40
30
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10074
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- Remapped and clipped number
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10054
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40
30
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10074
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- Bounds
- Create a numeric domain which encompasses a list of numbers.
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- Bounds
- Bounds
-
9964
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110
28
-
10022
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- Numbers to include in Bounds
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9966
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44
24
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9988
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- Numeric Domain between the lowest and highest numbers in {N}
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- Domain
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- 0
-
10034
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38
24
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10053
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- Relay
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- A wire relay object
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9999
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40
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10019
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- ce46b74e-00c9-43c4-805a-193b69ea4a11
- Multiplication
- Mathematical multiplication
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-
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70
44
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10009
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- First item for multiplication
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9986
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11
20
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- Second item for multiplication
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- B
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9986
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11
20
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- Result of multiplication
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31
40
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10036.5
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-
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70
44
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10009
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- 2
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- First item for multiplication
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9986
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11
20
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9991.5
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- Second item for multiplication
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- B
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9986
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11
20
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- Result of multiplication
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10021
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31
40
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10036.5
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- A wire relay object
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9999
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40
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10019
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255;255;255;255
- A group of Grasshopper objects
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- Group
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- Group
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255;255;255;255
- A group of Grasshopper objects
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- A panel for custom notes and text values
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271
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255;255;255;255
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9999
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40
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10019
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- Relay
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- A wire relay object
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9999
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10019
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255;255;255;255
- A group of Grasshopper objects
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- Allows for customized geometry previews
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255;255;255;255
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- Evaluate Length
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- Length factor for curve evaluation
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- Curve parameter at the specified length
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- Create an OpenGL material.
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- Amount of transparency (0.0 = opaque, 1.0 = transparent
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- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
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- Resulting material
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- The material override
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- A group of Grasshopper objects
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- Start
- false
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- 1
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9966
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60
20
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10004
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- Line tangent (direction)
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9966
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60
20
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10004
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-
0
0
1
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9966
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60
20
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10004
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- 1
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- Line segment
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-
10050
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22
60
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10061
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- Compute relative differences for a list of data
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- true
- Relative Differences
- Relative Differences
-
9961
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116
28
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10008
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- List of data to operate on (numbers or points or vectors allowed)
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- Values
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33
24
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9979.5
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- 1
- Differences between consecutive items
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10020
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55
24
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10047.5
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- Replace Nulls
- Replace nulls or invalid data with other data
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- Replace Nulls
- Replace Nulls
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9949
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139
44
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10044
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- Items to test for null
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- 1
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9951
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81
20
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9991.5
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- 1
- Items to replace nulls with
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- Replacements
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- 0
-
9951
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81
20
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9991.5
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- 1
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- Grasshopper.Kernel.Types.GH_Integer
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- List without any nulls
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- 0
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10056
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30
20
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10071
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- Number of items replaced
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- 0
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10056
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30
20
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10071
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- Relay
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- A wire relay object
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9999
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40
16
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10019
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- Relay
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- A wire relay object
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- true
- Relay
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9999
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40
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10019
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255;255;255;255
- A group of Grasshopper objects
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- Group
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- Find the closest point on a curve.
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- Curve Closest Point
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108
64
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10009
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- Point to project onto curve
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9967
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30
30
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9982
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- Curve to project onto
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9967
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30
30
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9982
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- Point on the curve closest to the base point
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10021
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50
20
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10046
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- Parameter on curve domain of closest point
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10021
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50
20
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10046
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- Distance between base point and curve
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- Distance
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10021
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50
20
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10046
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- Line
- Create a line between two points.
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- Line
- Line
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102
44
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10034
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- Line start point
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9970
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52
20
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9996
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- Line end point
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- End Point
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9970
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52
20
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9996
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- Line segment
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10046
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22
40
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10057
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- Remap numbers into a new numeric domain
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- Remap Numbers
- Remap Numbers
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154
64
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10042
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- Value to remap
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- Value
- Value
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9944
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86
20
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9987
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- Source domain
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- Source
- Source
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9944
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86
20
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9987
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0
1
- Target domain
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- 0
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9944
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86
20
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9987
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- {0}
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-1
1
- Remapped number
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10054
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40
30
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10074
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- Remapped and clipped number
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- Clipped
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10054
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40
30
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10074
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- Bounds
- Create a numeric domain which encompasses a list of numbers.
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- Bounds
- Bounds
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9964
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110
28
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10022
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- 1
- Numbers to include in Bounds
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- Numbers
- Numbers
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9966
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44
24
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9988
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- Numeric Domain between the lowest and highest numbers in {N}
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- Domain
- Domain
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- 0
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10034
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38
24
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10053
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- Relay
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- A wire relay object
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9999
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40
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10019
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- Multiplication
- Mathematical multiplication
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- Multiplication
- Multiplication
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70
44
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10009
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- 2
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- First item for multiplication
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- A
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9986
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11
20
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9991.5
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- Second item for multiplication
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9986
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11
20
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9991.5
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- Result of multiplication
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10021
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31
40
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10036.5
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- Multiplication
- Mathematical multiplication
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- Multiplication
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9984
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70
44
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10009
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- First item for multiplication
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9986
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11
20
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9991.5
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- Second item for multiplication
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- 1
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9986
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11
20
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9991.5
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- Result of multiplication
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10021
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31
40
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10036.5
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9999
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40
16
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10019
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255;255;255;255
- A group of Grasshopper objects
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255;255;255;255
- A group of Grasshopper objects
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- A panel for custom notes and text values
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- Double click to edit panel content…
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185
271
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255;255;255;255
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9999
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40
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10019
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- Relay
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9999
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40
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10019
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255;255;255;255
- A group of Grasshopper objects
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- Create an OpenGL material.
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152
104
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10041
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- Colour of the diffuse channel
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9945
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84
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255;125;125;125
- Colour of the specular highlight
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9945
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84
20
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9987
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255;0;255;255
- Emissive colour of the material
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9945
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84
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9987
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255;0;0;0
- Amount of transparency (0.0 = opaque, 1.0 = transparent
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9945
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84
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- Amount of shinyness (0 = none, 1 = low shine, 100 = max shine
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84
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- Resulting material
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10053
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40
100
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- Allows for customized geometry previews
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76
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48
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10007
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- The material override
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9983
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48
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10007
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255;221;160;221
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255;66;48;66
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255;255;255;255
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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149
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- Curve to evaluate
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71
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- Length factor for curve evaluation
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9946
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71
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9981.5
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- Create an interpolated curve through a set of points.
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225
84
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159
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159
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159
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38
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38
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- Create an OpenGL material.
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152
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9945
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84
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255;99;99;99
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84
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255;0;255;255
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9987
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255;0;0;0
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84
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9945
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84
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9987
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10053
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40
100
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- Allows for customized geometry previews
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76
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48
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10007
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9983
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48
20
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10007
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255;221;160;221
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255;66;48;66
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255;255;255;255
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- Display a set of y-values as a graph
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150
150
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9951.656
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9989
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60
24
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9989
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60
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130
64
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9956
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78
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9995
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9956
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78
20
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9995
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78
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10058
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24
60
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10070
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53
64
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10025
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- List to shift
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19
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10003.5
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- Shift offset
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9994
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19
20
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10003.5
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9994
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19
20
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10037
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6
60
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10040
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116
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9961
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66
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9961
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66
20
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0
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1
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9961
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66
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9994
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10051
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22
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10062
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110
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- Vector to rotate
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49
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9959
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49
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9991.5
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9959
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49
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33
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10048.5
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77
64
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10032
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25
20
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10007.5
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9995
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25
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25
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10044
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24
60
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10056
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96
44
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10015
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- Curve to pull
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9965
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38
20
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9984
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- Surface that pulls
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9965
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38
20
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9984
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- Curve pulled onto the surface
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10027
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30
40
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10042
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77
64
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10018
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9981
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25
20
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9993.5
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9981
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25
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9981
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25
20
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9993.5
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10030
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24
60
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10042
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- Pull Curve
- Pull a curve onto a surface.
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9970
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96
44
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10022
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- Curve to pull
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9972
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38
20
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9991
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- Surface that pulls
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9972
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38
20
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9991
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- Curve pulled onto the surface
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10034
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30
40
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10049
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- A wire relay object
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9999
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40
16
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10019
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- A wire relay object
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9998
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40
16
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10018
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- Relay
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- A wire relay object
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9998
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40
16
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10018
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- Group
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255;255;255;255
- A group of Grasshopper objects
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- Group
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- Contains a collection of generic curves
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10010
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50
24
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10043.56
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- Test a data item for null or invalidity
- true
- b62e3e22-7076-4e38-b0c0-3a8ccedccce4
- true
- Null Item
- Null Item
-
9963
-4505
112
64
-
10001
-4473
- Item to test
- b00eb695-8ca4-49b1-a8c0-8d3c2704c4d4
- true
- Item
- Item
- true
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9965
-4503
24
60
-
9977
-4473
- True if item is Null
- 80f66cc8-3f0d-4c83-97be-347c0623d535
- true
- Null Flags
- Null Flags
- false
- 0
-
10013
-4503
60
20
-
10043
-4493
- True if item is Invalid
- fa4825ee-2e30-44a8-a178-3b23efc3f398
- true
- Invalid Flags
- Invalid Flags
- false
- 0
-
10013
-4483
60
20
-
10043
-4473
- A textual description of the object state
- feb343ba-8670-404e-90a0-8432d136436b
- true
- Description
- Description
- false
- 0
-
10013
-4463
60
20
-
10043
-4453
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- acdf8d21-9795-4b3c-8d54-a8219340557e
- true
- Gate Not
- Gate Not
-
9984
-4563
70
28
-
10009
-4549
- Boolean value
- 4a19fc6e-2d7a-471b-bcce-d5a1412e0f43
- true
- A
- A
- false
- 80f66cc8-3f0d-4c83-97be-347c0623d535
- 1
-
9986
-4561
11
24
-
9991.5
-4549
- Inverse of {A}
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- true
- Result
- Result
- false
- 0
-
10021
-4561
31
24
-
10036.5
-4549
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 0fb387e0-8efc-430a-ad2a-08f863556546
- true
- Stream Filter
- Stream Filter
-
9986
-9145
77
64
-
10025
-9113
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 06399296-3657-4782-9f14-124355221b9f
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9988
-9143
25
20
-
10000.5
-9133
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 3ce03926-3ca1-4b34-9f25-cd3e173de9c7
- true
- false
- Stream 0
- 0
- true
- a09d1915-e012-4d72-94f9-1f234a1c91ef
- 1
-
9988
-9123
25
20
-
10000.5
-9113
- 2
- Input stream at index 1
- 857fca33-c58b-41c7-8da9-c407944e98d0
- true
- false
- Stream 1
- 1
- true
- 6bd020fd-c652-4ed0-a741-6c88bd6ac075
- 1
-
9988
-9103
25
20
-
10000.5
-9093
- 2
- Filtered stream
- f05ffc93-07b8-46d2-ad82-99badcc3922f
- true
- false
- Stream
- S(0)
- false
- 0
-
10037
-9143
24
60
-
10049
-9113
- 6b5812f5-bb36-4d74-97fc-5a1f2f77452d
- Pull Curve
- Pull a curve onto a surface.
- true
- 67c2acc7-61e8-4dc8-a403-e7221b033383
- true
- Pull Curve
- Pull Curve
-
9976
-8754
96
44
-
10028
-8732
- Curve to pull
- bf9a89d7-1a9d-482a-bf2a-6b0992a45c8e
- true
- Curve
- Curve
- false
- a09d1915-e012-4d72-94f9-1f234a1c91ef
- 1
-
9978
-8752
38
20
-
9997
-8742
- Surface that pulls
- b5456d1f-1e8c-44b5-ab48-3f4ff8a70665
- true
- Surface
- Surface
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9978
-8732
38
20
-
9997
-8722
- Curve pulled onto the surface
- f6a8a08e-b879-4b59-a042-87b09c2b6c2b
- true
- Curve
- Curve
- false
- 0
-
10040
-8752
30
40
-
10055
-8732
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 3aa22581-402f-4750-9268-ebe07eb256aa
- true
- Stream Filter
- Stream Filter
-
9980
-6015
77
64
-
10019
-5983
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 0b765458-3919-4cd0-993f-6aa485fe7bf3
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9982
-6013
25
20
-
9994.5
-6003
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 90c1f92c-2d02-411c-9226-2b4827ecba0a
- true
- false
- Stream 0
- 0
- true
- 58715e09-1461-47aa-b311-c9878cbef364
- 1
-
9982
-5993
25
20
-
9994.5
-5983
- 2
- Input stream at index 1
- 37f8811e-d59a-4893-874f-2b9c4546f538
- true
- false
- Stream 1
- 1
- true
- 4a40ed77-eaa2-427a-b632-c4c14ac83a0b
- 1
-
9982
-5973
25
20
-
9994.5
-5963
- 2
- Filtered stream
- 043ef658-425b-4fc2-a0ed-57be30e7b117
- true
- false
- Stream
- S(0)
- false
- 0
-
10031
-6013
24
60
-
10043
-5983
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- cffd2b57-8bcb-4248-b984-bdaff8648b5a
- true
- Pull Point
- Pull Point
-
9946
-5913
139
44
-
10008
-5891
- Point to search from
- fe439557-86d3-43a2-8342-9265ab7171de
- true
- Point
- Point
- false
- 58715e09-1461-47aa-b311-c9878cbef364
- 1
-
9948
-5911
48
20
-
9972
-5901
- 1
- Geometry that pulls
- 9eeef12b-bde5-45d2-bce9-93075540eb20
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9948
-5891
48
20
-
9972
-5881
- Point on [G] closest to [P]
- 4a40ed77-eaa2-427a-b632-c4c14ac83a0b
- true
- Closest Point
- Closest Point
- false
- 0
-
10020
-5911
63
20
-
10051.5
-5901
- Distance between [P] and its projection onto [G]
- c687cd8d-0db6-4027-9696-f010a1126597
- true
- Distance
- Distance
- false
- 0
-
10020
-5891
63
20
-
10051.5
-5881
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 345d893b-ae16-4ece-bd87-af320cd62598
- true
- Stream Filter
- Stream Filter
-
9981
-9703
77
64
-
10020
-9671
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 77af05a8-653a-45bd-830f-5a0030ac485c
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9983
-9701
25
20
-
9995.5
-9691
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- a3a17ee1-6a78-4b93-a151-c427f687d7e9
- true
- false
- Stream 0
- 0
- true
- a87341fb-0950-4665-a5d5-5556809dce9d
- 1
-
9983
-9681
25
20
-
9995.5
-9671
- 2
- Input stream at index 1
- d52d4520-ddac-4ef0-93e6-a0f531a518f5
- true
- false
- Stream 1
- 1
- true
- d93903ee-cfd9-4f91-a642-a9eaaec44230
- 1
-
9983
-9661
25
20
-
9995.5
-9651
- 2
- Filtered stream
- 2b484d46-7738-42ff-b212-eea1c16c05f0
- true
- false
- Stream
- S(0)
- false
- 0
-
10032
-9701
24
60
-
10044
-9671
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 1da4a747-337d-46d9-818d-512d2d11e43e
- true
- Pull Point
- Pull Point
-
9950
-9617
139
44
-
10012
-9595
- Point to search from
- 5e66e12e-afa5-4667-a021-d5ac897d3938
- true
- Point
- Point
- false
- a87341fb-0950-4665-a5d5-5556809dce9d
- 1
-
9952
-9615
48
20
-
9976
-9605
- 1
- Geometry that pulls
- 54065e6e-a92c-4ad6-99ee-f60600a2edea
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9952
-9595
48
20
-
9976
-9585
- Point on [G] closest to [P]
- d93903ee-cfd9-4f91-a642-a9eaaec44230
- true
- Closest Point
- Closest Point
- false
- 0
-
10024
-9615
63
20
-
10055.5
-9605
- Distance between [P] and its projection onto [G]
- 2e023752-5825-4542-b000-932bfa2ad17b
- true
- Distance
- Distance
- false
- 0
-
10024
-9595
63
20
-
10055.5
-9585
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- a8f38f9e-b3b6-41bd-8db4-16fabd280f08
- true
- Stream Filter
- Stream Filter
-
9968
-12697
77
64
-
10007
-12665
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 765f81d8-ff1a-4ba1-a493-527c32710a12
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9970
-12695
25
20
-
9982.5
-12685
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- cf08a60a-85fc-4f3b-9da2-15233702dcb6
- true
- false
- Stream 0
- 0
- true
- f0c191c1-9621-4bbc-8f42-70fddab36b4d
- 1
-
9970
-12675
25
20
-
9982.5
-12665
- 2
- Input stream at index 1
- 48956a2f-d6d5-40df-a623-85bf867ad2c8
- true
- false
- Stream 1
- 1
- true
- 21adf162-6466-48ed-b0e4-8aa61cab45ec
- 1
-
9970
-12655
25
20
-
9982.5
-12645
- 2
- Filtered stream
- 1e2a7b7f-adc5-4de7-b89a-18f9809254ce
- true
- false
- Stream
- S(0)
- false
- 0
-
10019
-12695
24
60
-
10031
-12665
- 6b5812f5-bb36-4d74-97fc-5a1f2f77452d
- Pull Curve
- Pull a curve onto a surface.
- true
- 99f6eb91-99d8-4603-b7d0-eca216200d71
- true
- Pull Curve
- Pull Curve
-
9971
-12281
96
44
-
10023
-12259
- Curve to pull
- 0fc24e2e-c021-40bb-b392-83f0246cbe7c
- true
- Curve
- Curve
- false
- f0c191c1-9621-4bbc-8f42-70fddab36b4d
- 1
-
9973
-12279
38
20
-
9992
-12269
- Surface that pulls
- d0cd04f6-9e03-4121-8fb3-ce8a508d7d13
- true
- Surface
- Surface
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9973
-12259
38
20
-
9992
-12249
- Curve pulled onto the surface
- 2a1421bd-02db-438e-a5d2-207894cd0bdf
- true
- Curve
- Curve
- false
- 0
-
10035
-12279
30
40
-
10050
-12259
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 27beda7a-8035-4b7f-baa6-07b36b445f36
- true
- Stream Filter
- Stream Filter
-
9977
-13260
77
64
-
10016
-13228
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- eb605005-2673-4e61-ba1f-8c64b2ef9ade
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9979
-13258
25
20
-
9991.5
-13248
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- f7702fdb-1b65-460e-9e74-92dca8113c0c
- true
- false
- Stream 0
- 0
- true
- 042a386a-fcdb-4902-bf3e-1cca2eff73b7
- 1
-
9979
-13238
25
20
-
9991.5
-13228
- 2
- Input stream at index 1
- cfa06fd1-5b9b-4ca9-ad9f-5fb3d360486e
- true
- false
- Stream 1
- 1
- true
- ad599a39-f198-4941-8d4e-7089ae235a5c
- 1
-
9979
-13218
25
20
-
9991.5
-13208
- 2
- Filtered stream
- 33a6314b-e63e-4e80-b5e3-dcd21060daa4
- true
- false
- Stream
- S(0)
- false
- 0
-
10028
-13258
24
60
-
10040
-13228
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 344c01b0-b3be-4158-b3f3-3e875533be20
- true
- Pull Point
- Pull Point
-
9946
-13174
139
44
-
10008
-13152
- Point to search from
- d8d70767-e3b6-4210-87e4-db9f5422e6d5
- true
- Point
- Point
- false
- 042a386a-fcdb-4902-bf3e-1cca2eff73b7
- 1
-
9948
-13172
48
20
-
9972
-13162
- 1
- Geometry that pulls
- 3e9f1b53-15bb-4e99-8471-f8f99e6dd451
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9948
-13152
48
20
-
9972
-13142
- Point on [G] closest to [P]
- ad599a39-f198-4941-8d4e-7089ae235a5c
- true
- Closest Point
- Closest Point
- false
- 0
-
10020
-13172
63
20
-
10051.5
-13162
- Distance between [P] and its projection onto [G]
- 3619df5e-57e4-4d5b-94ee-4852c16b2c53
- true
- Distance
- Distance
- false
- 0
-
10020
-13152
63
20
-
10051.5
-13142
- a4b285fe-2e13-4204-b65c-189aa6704da5
- CURWE CURWATURE THIRD DIFERENCE COMBS
- CURWE CURWATURE THIRD DIFERENCE COMBS
- CURWE CURWATURE THIRD DIFERENCE COMBS
- CURWE CURWATURE THIRD DIFERENCE COMBS
- CURWE CURWATURE THIRD DIFERENCE COMBS
- 50e1ac8e-1daf-4c52-bfc9-ae6c4c4b5d7f
- true
- CURWE CURWATURE THIRD DIFERENCE COMBS
- CURWE CURWATURE THIRD DIFERENCE COMBS
- false
- e29ca557-b1ee-475d-8cd9-63721b3e955d
- 1
-
9889
-16336
260
24
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 4337397e-3fc7-4255-8ed1-ffd880a2c289
- true
- Stream Filter
- Stream Filter
-
9981
-16279
77
64
-
10020
-16247
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 65692a58-3f42-4520-b6a7-f0151dcc0718
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9983
-16277
25
20
-
9995.5
-16267
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 2468b678-acbf-4073-b3ae-54742b7c16b3
- true
- false
- Stream 0
- 0
- true
- 0f214bdb-5cad-4d4f-8eee-7b8f3600bdca
- 1
-
9983
-16257
25
20
-
9995.5
-16247
- 2
- Input stream at index 1
- f5e32804-3e4e-4b0b-a77b-6482c099a921
- true
- false
- Stream 1
- 1
- true
- fa5104ec-99e6-4c5c-94e7-3b82a0aab230
- 1
-
9983
-16237
25
20
-
9995.5
-16227
- 2
- Filtered stream
- e29ca557-b1ee-475d-8cd9-63721b3e955d
- true
- false
- Stream
- S(0)
- false
- 0
-
10032
-16277
24
60
-
10044
-16247
- 6b5812f5-bb36-4d74-97fc-5a1f2f77452d
- Pull Curve
- Pull a curve onto a surface.
- true
- da88dd80-8efd-4e21-a39e-70ce76cc2119
- true
- Pull Curve
- Pull Curve
-
9976
-15858
96
44
-
10028
-15836
- Curve to pull
- 7d3eb441-b313-4123-b7c6-6acfea0e0451
- true
- Curve
- Curve
- false
- 0f214bdb-5cad-4d4f-8eee-7b8f3600bdca
- 1
-
9978
-15856
38
20
-
9997
-15846
- Surface that pulls
- 35ff5b6f-8d0b-47ef-92d9-7c8f0c53416d
- true
- Surface
- Surface
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9978
-15836
38
20
-
9997
-15826
- Curve pulled onto the surface
- 4ce8f03b-1734-4055-b3e3-dd585ded15d2
- true
- Curve
- Curve
- false
- 0
-
10040
-15856
30
40
-
10055
-15836
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- e63d5bc1-5483-4565-b5c9-382b62dd7532
- true
- Stream Filter
- Stream Filter
-
9979
-16905
77
64
-
10018
-16873
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- ce043f9d-fe44-4b8a-9441-a4276d4b4af8
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9981
-16903
25
20
-
9993.5
-16893
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- dc38c735-e61f-40d1-9269-c26f9f69c8ad
- true
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- Stream 0
- 0
- true
- 4c437000-729e-49e9-9151-342e882d2ecc
- 1
-
9981
-16883
25
20
-
9993.5
-16873
- 2
- Input stream at index 1
- 426541d6-3cf4-43c2-8d13-42c3fb62ef71
- true
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- Stream 1
- 1
- true
- cdf037a9-f123-4d5a-86f7-16caaac5483f
- 1
-
9981
-16863
25
20
-
9993.5
-16853
- 2
- Filtered stream
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- Stream
- S(0)
- false
- 0
-
10030
-16903
24
60
-
10042
-16873
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 05d4fb4f-a50c-46d2-9aa5-be6d19680490
- true
- Pull Point
- Pull Point
-
9950
-16801
139
44
-
10012
-16779
- Point to search from
- 0e77c4aa-a22e-4306-beba-f9596e55ae3c
- true
- Point
- Point
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- 4c437000-729e-49e9-9151-342e882d2ecc
- 1
-
9952
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48
20
-
9976
-16789
- 1
- Geometry that pulls
- 935e197b-5830-4f82-9942-4df625646cfd
- true
- Geometry
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- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9952
-16779
48
20
-
9976
-16769
- Point on [G] closest to [P]
- cdf037a9-f123-4d5a-86f7-16caaac5483f
- true
- Closest Point
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- 0
-
10024
-16799
63
20
-
10055.5
-16789
- Distance between [P] and its projection onto [G]
- 83b3f5e8-b221-404e-8d7c-8b3273cef8bd
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- Distance
- Distance
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- 0
-
10024
-16779
63
20
-
10055.5
-16769
- a4b285fe-2e13-4204-b65c-189aa6704da5
- CURWE CURWATURE SECOND DIFERENCE COMBS
- CURWE CURWATURE SECOND DIFERENCE COMBS
- CURWE CURWATURE SECOND DIFERENCE COMBS
- CURWE CURWATURE SECOND DIFERENCE COMBS
- CURWE CURWATURE SECOND DIFERENCE COMBS
- 30482e7c-7286-4502-a14e-85a6c35b7c79
- true
- CURWE CURWATURE SECOND DIFERENCE COMBS
- CURWE CURWATURE SECOND DIFERENCE COMBS
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- 1e2a7b7f-adc5-4de7-b89a-18f9809254ce
- 1
-
9883
-12746
272
24
- 448de216-3a12-43cf-a135-e3bfafc87744
- CURWE INPUT
- CURWE INPUT
- CURWE INPUT
- CURWE INPUT
- CURWE INPUT
- cd5b889e-e4dd-448f-9673-4b231165ae21
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- CURWE INPUT
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- 0
-
9976
-599
101
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- CURWE OUTPUT
- CURWE OUTPUT
- CURWE OUTPUT
- CURWE OUTPUT
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- f26535d4-91e9-4d8f-8216-dab8258daddf
- true
- CURWE OUTPUT
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- 41be65b0-4832-475b-82e4-72e5cbea050c
- 1
-
9963
-738
112
24
- 448de216-3a12-43cf-a135-e3bfafc87744
- CURWE POINT NUMBER INPUT
- CURWE POINT NUMBER INPUT
- CURWE POINT NUMBER INPUT
- CURWE POINT NUMBER INPUT
- CURWE POINT NUMBER INPUT
- 7821d745-ea35-4b5e-9bc1-0ed25432d936
- true
- CURWE POINT NUMBER INPUT
- CURWE POINT NUMBER INPUT
- false
- 0
-
9938
-2092
178
24
- 3e8ca6be-fda8-4aaf-b5c0-3c54c8bb7312
- Number
- Contains a collection of floating point numbers
- 41d4fcae-5924-4999-8519-7d3c327b7aea
- true
- Number
- Number
- false
- 0
-
9995
-2126
52
24
-
10035.56
-2114.887
- 1
- 1
- {0}
- 256
- a4b285fe-2e13-4204-b65c-189aa6704da5
- CURWE POINT NUMBER OUTPUT
- CURWE POINT NUMBER OUTPUT
- CURWE POINT NUMBER OUTPUT
- CURWE POINT NUMBER OUTPUT
- CURWE POINT NUMBER OUTPUT
- 63995dad-5a38-4819-9bc6-c7368d2aa8c0
- true
- CURWE POINT NUMBER OUTPUT
- CURWE POINT NUMBER OUTPUT
- false
- 41d4fcae-5924-4999-8519-7d3c327b7aea
- 1
-
9932
-2195
189
24
- 3e8ca6be-fda8-4aaf-b5c0-3c54c8bb7312
- Number
- Contains a collection of floating point numbers
- 811f77e7-8403-4ccc-a67a-e88eab309b40
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- 2
- Number
- Number
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- 0
-
10001
-4115
50
24
-
10034.56
-4103.887
- 1
- 2
- {0}
- 0
- 180
- 448de216-3a12-43cf-a135-e3bfafc87744
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE INPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE INPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE INPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE INPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE INPUT
- 8bb07237-8043-4bfc-9482-36c5f324e171
- true
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE INPUT
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- false
- 0
-
9856
-4086
341
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE OUTPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE OUTPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE OUTPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE OUTPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE OUTPUT
- 99e87cc0-6a4b-442b-884b-8221f251b9bf
- true
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE OUTPUT
- CURWE CURWATURE COMBS TORSION ROTATION ANGLE OUTPUT
- false
- 811f77e7-8403-4ccc-a67a-e88eab309b40
- 1
-
9851
-4169
352
24
- 448de216-3a12-43cf-a135-e3bfafc87744
- MAGNET SURFACE INPUT
- MAGNET SURFACE INPUT
- MAGNET SURFACE INPUT
- MAGNET SURFACE INPUT
- MAGNET SURFACE INPUT
- 1bf8b430-d382-4280-aaec-0188aafb741b
- true
- MAGNET SURFACE INPUT
- MAGNET SURFACE INPUT
- false
- 0
-
9938
-4329
156
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- MAGNET SURFACE OUTPUT
- MAGNET SURFACE OUTPUT
- MAGNET SURFACE OUTPUT
- MAGNET SURFACE OUTPUT
- MAGNET SURFACE OUTPUT
- fd8be7fd-657d-4392-aabd-296e39ed305b
- true
- MAGNET SURFACE OUTPUT
- MAGNET SURFACE OUTPUT
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9948
-4422
167
24
- deaf8653-5528-4286-807c-3de8b8dad781
- Surface
- Contains a collection of generic surfaces
- true
- d2b2d690-7218-44bb-aa7c-3040cab09077
- true
- Surface
- Surface
- false
- 1bf8b430-d382-4280-aaec-0188aafb741b
- 1
-
9999
-4359
50
24
-
10024.66
-4347
- a4b285fe-2e13-4204-b65c-189aa6704da5
- CURWE CURWATURE COMB SCALED LINES
- CURWE CURWATURE COMB SCALED LINES
- CURWE CURWATURE COMB SCALED LINES
- CURWE CURWATURE COMB SCALED LINES
- CURWE CURWATURE COMB SCALED LINES
- d992dcbb-ebd0-41d4-96b3-793a6c463864
- true
- CURWE CURWATURE COMB SCALED LINES
- CURWE CURWATURE COMB SCALED LINES
- false
- 4a88ebb8-f367-4644-9b81-883895d1f5b5
- 1
-
9913
-5503
239
24
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 4a88ebb8-f367-4644-9b81-883895d1f5b5
- true
- Relay
- false
- 88d2e234-202c-4e3b-adb8-c6bf7cc9988f
- 1
-
10000
-5497
40
16
-
10020
-5489
- 448de216-3a12-43cf-a135-e3bfafc87744
- CURWE CURWATURE FIRST DIFERENCE COMB LINES SCALE
- CURWE CURWATURE FIRST DIFERENCE COMB LINES SCALE
- CURWE CURWATURE FIRST DIFERENCE COMB LINES SCALE
- CURWE CURWATURE FIRST DIFERENCE COMB LINES SCALE
- CURWE CURWATURE FIRST DIFERENCE COMB LINES SCALE
- 1bfd648a-9dbf-4c36-aaf1-6faf76bdedb5
- true
- CURWE CURWATURE FIRST DIFERENCE COMB LINES SCALE
- CURWE CURWATURE FIRST DIFERENCE COMB LINES SCALE
- false
- 0
-
9864
-8490
318
24
- a4b285fe-2e13-4204-b65c-189aa6704da5
- CURWE CURWATURE FIRST DIFERENCE COMB SCALED LINES
- CURWE CURWATURE FIRST DIFERENCE COMB SCALED LINES
- CURWE CURWATURE FIRST DIFERENCE COMB SCALED LINES
- CURWE CURWATURE FIRST DIFERENCE COMB SCALED LINES
- CURWE CURWATURE FIRST DIFERENCE COMB SCALED LINES
- 87c359c8-b31a-41d3-b2bd-e7427c264c27
- true
- CURWE CURWATURE FIRST DIFERENCE COMB SCALED LINES
- CURWE CURWATURE FIRST DIFERENCE COMB SCALED LINES
- false
- f05ffc93-07b8-46d2-ad82-99badcc3922f
- 1
-
9866
-9208
325
24
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- 4ce1f53e-bf61-44f8-95a4-3bf2d4d1053a
- true
- End Points
- End Points
-
9986
-5087
84
44
-
10030
-5065
- Curve to evaluate
- 8dae861f-afe2-42b0-9cb4-014ad80440a7
- true
- Curve
- Curve
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- 2158b91e-623b-4f9d-8297-f4edb0d6540d
- 1
-
9988
-5085
30
40
-
10003
-5065
- Curve start point
- 02964a7a-328e-4e32-b6c3-ac54c648bd49
- true
- Start
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- 0
-
10042
-5085
26
20
-
10055
-5075
- Curve end point
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- End
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- 0
-
10042
-5065
26
20
-
10055
-5055
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
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- true
- Line
- Line
-
9980
-5317
102
44
-
10046
-5295
- Line start point
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- 1
-
9982
-5315
52
20
-
10008
-5305
- Line end point
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- End Point
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- 937ad2f4-5ea8-48a5-a340-e4353478cf5d
- 1
-
9982
-5295
52
20
-
10008
-5285
- Line segment
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- true
- Line
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- 0
-
10058
-5315
22
40
-
10069
-5295
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- b0c7518a-4219-4602-839c-235029b1a34d
- true
- Pull Point
- Pull Point
-
9958
-5252
139
44
-
10020
-5230
- Point to search from
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- true
- Point
- Point
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- 02964a7a-328e-4e32-b6c3-ac54c648bd49
- 1
-
9960
-5250
48
20
-
9984
-5240
- 1
- Geometry that pulls
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- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9960
-5230
48
20
-
9984
-5220
- Point on [G] closest to [P]
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- true
- Closest Point
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- false
- 0
-
10032
-5250
63
20
-
10063.5
-5240
- Distance between [P] and its projection onto [G]
- e90fc0ab-3867-40e6-8233-7a7f6cfaf7ce
- true
- Distance
- Distance
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- 0
-
10032
-5230
63
20
-
10063.5
-5220
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 4a12da5d-898e-4144-8e8d-1b907f89642d
- true
- Pull Point
- Pull Point
-
9958
-5171
139
44
-
10020
-5149
- Point to search from
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- true
- Point
- Point
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- 880ada06-8e88-49d0-a801-f5c9b0f2ca43
- 1
-
9960
-5169
48
20
-
9984
-5159
- 1
- Geometry that pulls
- a05f35ae-e2dc-4338-a49b-4407ac509c21
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- Geometry
- Geometry
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- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9960
-5149
48
20
-
9984
-5139
- Point on [G] closest to [P]
- 937ad2f4-5ea8-48a5-a340-e4353478cf5d
- true
- Closest Point
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- 0
-
10032
-5169
63
20
-
10063.5
-5159
- Distance between [P] and its projection onto [G]
- 933aaf31-a580-4971-99cd-3b6db6bd23a6
- true
- Distance
- Distance
- false
- 0
-
10032
-5149
63
20
-
10063.5
-5139
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- 3697088f-7b9c-42f6-bd64-2174aa7f816c
- true
- End Points
- End Points
-
9972
-8813
84
44
-
10016
-8791
- Curve to evaluate
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- Curve
- Curve
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- a09d1915-e012-4d72-94f9-1f234a1c91ef
- 1
-
9974
-8811
30
40
-
9989
-8791
- Curve start point
- 9657b5c7-9576-49ed-a6d7-ae032aeec3e9
- true
- Start
- Start
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- 0
-
10028
-8811
26
20
-
10041
-8801
- Curve end point
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- true
- End
- End
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- 0
-
10028
-8791
26
20
-
10041
-8781
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- ca04f8b3-a611-47df-b7e3-410b2099d099
- true
- Line
- Line
-
9963
-9036
102
44
-
10029
-9014
- Line start point
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- true
- Start Point
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- 3eca4bac-2695-407c-9f4e-de9f268b685e
- 1
-
9965
-9034
52
20
-
9991
-9024
- Line end point
- d59b3a89-55ca-4698-a494-1201157d81dc
- true
- End Point
- End Point
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- 829d4ae8-b090-4cbd-84cb-f25ffc968842
- 1
-
9965
-9014
52
20
-
9991
-9004
- Line segment
- 6bd020fd-c652-4ed0-a741-6c88bd6ac075
- true
- Line
- Line
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- 0
-
10041
-9034
22
40
-
10052
-9014
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 8ab55463-0601-4907-8574-cbbcbe9cdf41
- true
- Pull Point
- Pull Point
-
9945
-8971
139
44
-
10007
-8949
- Point to search from
- 0e73b6dc-4f45-4736-bd0e-75ae29de8c32
- true
- Point
- Point
- false
- 9657b5c7-9576-49ed-a6d7-ae032aeec3e9
- 1
-
9947
-8969
48
20
-
9971
-8959
- 1
- Geometry that pulls
- b6589601-2a37-4656-b7c4-890bc1b15999
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9947
-8949
48
20
-
9971
-8939
- Point on [G] closest to [P]
- 3eca4bac-2695-407c-9f4e-de9f268b685e
- true
- Closest Point
- Closest Point
- false
- 0
-
10019
-8969
63
20
-
10050.5
-8959
- Distance between [P] and its projection onto [G]
- e7e57fe1-4371-40f7-8233-7868f5beca3c
- true
- Distance
- Distance
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- 0
-
10019
-8949
63
20
-
10050.5
-8939
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- b583d1cf-7a3f-4052-8904-153d81fdfdee
- true
- Pull Point
- Pull Point
-
9945
-8892
139
44
-
10007
-8870
- Point to search from
- 4fffb62b-fa07-4251-9e58-7a65bd99eb48
- true
- Point
- Point
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- 3d1c3c8e-ba45-4486-ad01-a0d1d102f456
- 1
-
9947
-8890
48
20
-
9971
-8880
- 1
- Geometry that pulls
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- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9947
-8870
48
20
-
9971
-8860
- Point on [G] closest to [P]
- 829d4ae8-b090-4cbd-84cb-f25ffc968842
- true
- Closest Point
- Closest Point
- false
- 0
-
10019
-8890
63
20
-
10050.5
-8880
- Distance between [P] and its projection onto [G]
- 590f8387-cbeb-4dcf-ab7c-2ee9a7c60ed0
- true
- Distance
- Distance
- false
- 0
-
10019
-8870
63
20
-
10050.5
-8860
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- b0c7518a-4219-4602-839c-235029b1a34d
- 4a12da5d-898e-4144-8e8d-1b907f89642d
- 4
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- Group
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- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 3697088f-7b9c-42f6-bd64-2174aa7f816c
- ca04f8b3-a611-47df-b7e3-410b2099d099
- 8ab55463-0601-4907-8574-cbbcbe9cdf41
- b583d1cf-7a3f-4052-8904-153d81fdfdee
- 4
- 772ea870-567a-4c8e-ad36-cc1a3d7ca545
- Group
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- a4a57a95-519b-4236-a616-ec04d6438608
- true
- End Points
- End Points
-
9968
-12366
84
44
-
10012
-12344
- Curve to evaluate
- d142dd1e-e179-418f-b26a-0b0d1dae7ab5
- true
- Curve
- Curve
- false
- f0c191c1-9621-4bbc-8f42-70fddab36b4d
- 1
-
9970
-12364
30
40
-
9985
-12344
- Curve start point
- 126cde73-2db3-4894-9089-9c82ea8d9b3e
- true
- Start
- Start
- false
- 0
-
10024
-12364
26
20
-
10037
-12354
- Curve end point
- c886c9ca-e196-4a6e-86e8-e74a60881897
- true
- End
- End
- false
- 0
-
10024
-12344
26
20
-
10037
-12334
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- 598915a3-e2fc-4bfb-b83f-aae6b06a75b4
- true
- Line
- Line
-
9959
-12589
102
44
-
10025
-12567
- Line start point
- 40d6e324-be45-4d56-b251-3dcff95ccada
- true
- Start Point
- Start Point
- false
- 608f6c3c-fd1f-4abb-ab11-9dbcb84297f7
- 1
-
9961
-12587
52
20
-
9987
-12577
- Line end point
- 1ba5e492-30bf-4985-b02c-c43e3b73f577
- true
- End Point
- End Point
- false
- e3ae76f8-04a9-4f7b-ba81-3036c248ecd0
- 1
-
9961
-12567
52
20
-
9987
-12557
- Line segment
- 21adf162-6466-48ed-b0e4-8aa61cab45ec
- true
- Line
- Line
- false
- 0
-
10037
-12587
22
40
-
10048
-12567
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 09211b76-ab65-4e72-8300-b36fcf6d33fe
- true
- Pull Point
- Pull Point
-
9941
-12524
139
44
-
10003
-12502
- Point to search from
- ac3a9740-ea3a-4365-ac94-3d1adb5db8c6
- true
- Point
- Point
- false
- 126cde73-2db3-4894-9089-9c82ea8d9b3e
- 1
-
9943
-12522
48
20
-
9967
-12512
- 1
- Geometry that pulls
- 3893bd59-caa5-4dc9-88bd-a5638da7ea20
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9943
-12502
48
20
-
9967
-12492
- Point on [G] closest to [P]
- 608f6c3c-fd1f-4abb-ab11-9dbcb84297f7
- true
- Closest Point
- Closest Point
- false
- 0
-
10015
-12522
63
20
-
10046.5
-12512
- Distance between [P] and its projection onto [G]
- 55874175-aeed-4069-9e8c-1eaaf48001a2
- true
- Distance
- Distance
- false
- 0
-
10015
-12502
63
20
-
10046.5
-12492
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- ef4b781e-70ad-4c5e-a3b3-3c742b04b013
- true
- Pull Point
- Pull Point
-
9941
-12445
139
44
-
10003
-12423
- Point to search from
- cfba421d-b82d-401a-b22a-40856c2c259e
- true
- Point
- Point
- false
- c886c9ca-e196-4a6e-86e8-e74a60881897
- 1
-
9943
-12443
48
20
-
9967
-12433
- 1
- Geometry that pulls
- 087a1959-4b4b-453c-b2bc-a946e32d298d
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9943
-12423
48
20
-
9967
-12413
- Point on [G] closest to [P]
- e3ae76f8-04a9-4f7b-ba81-3036c248ecd0
- true
- Closest Point
- Closest Point
- false
- 0
-
10015
-12443
63
20
-
10046.5
-12433
- Distance between [P] and its projection onto [G]
- e47640d6-f942-4fb8-806e-736ae5daf030
- true
- Distance
- Distance
- false
- 0
-
10015
-12423
63
20
-
10046.5
-12413
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- a4a57a95-519b-4236-a616-ec04d6438608
- 598915a3-e2fc-4bfb-b83f-aae6b06a75b4
- 09211b76-ab65-4e72-8300-b36fcf6d33fe
- ef4b781e-70ad-4c5e-a3b3-3c742b04b013
- 4
- 84271252-bd7b-4112-8561-43533ed4300d
- Group
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- fcdc1273-4010-457e-80e8-d6d2a5d24510
- true
- End Points
- End Points
-
9980
-15945
84
44
-
10024
-15923
- Curve to evaluate
- 596b6dfd-cafe-4d30-b26e-8cf2395a2f0f
- true
- Curve
- Curve
- false
- 0f214bdb-5cad-4d4f-8eee-7b8f3600bdca
- 1
-
9982
-15943
30
40
-
9997
-15923
- Curve start point
- ad6e4059-cf08-4266-9c07-b1a6d3da3632
- true
- Start
- Start
- false
- 0
-
10036
-15943
26
20
-
10049
-15933
- Curve end point
- 47fbfce5-2649-4fe6-84d2-5ca940b91239
- true
- End
- End
- false
- 0
-
10036
-15923
26
20
-
10049
-15913
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- efcfa711-59f2-48c9-bcfb-c0892d3a75e4
- true
- Line
- Line
-
9971
-16168
102
44
-
10037
-16146
- Line start point
- d928da3a-7042-4685-be2a-1b49f40f181d
- true
- Start Point
- Start Point
- false
- 23d52e4e-bbda-4d7f-844c-64c4e07fdc3b
- 1
-
9973
-16166
52
20
-
9999
-16156
- Line end point
- 0699787b-b73a-496f-aeaa-4e621de61a86
- true
- End Point
- End Point
- false
- f476e52c-9f16-4cf9-9dc8-53464df41ada
- 1
-
9973
-16146
52
20
-
9999
-16136
- Line segment
- fa5104ec-99e6-4c5c-94e7-3b82a0aab230
- true
- Line
- Line
- false
- 0
-
10049
-16166
22
40
-
10060
-16146
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 9961c67c-7b6b-4764-bdd1-a1e48583f369
- true
- Pull Point
- Pull Point
-
9953
-16103
139
44
-
10015
-16081
- Point to search from
- 10023702-d29c-4ed1-a06b-2e077fc9a36e
- true
- Point
- Point
- false
- ad6e4059-cf08-4266-9c07-b1a6d3da3632
- 1
-
9955
-16101
48
20
-
9979
-16091
- 1
- Geometry that pulls
- a5a19b7e-cc7b-472d-af7e-50bd165f0291
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9955
-16081
48
20
-
9979
-16071
- Point on [G] closest to [P]
- 23d52e4e-bbda-4d7f-844c-64c4e07fdc3b
- true
- Closest Point
- Closest Point
- false
- 0
-
10027
-16101
63
20
-
10058.5
-16091
- Distance between [P] and its projection onto [G]
- 340b9418-c6dc-4b6b-b0ff-952302865f58
- true
- Distance
- Distance
- false
- 0
-
10027
-16081
63
20
-
10058.5
-16071
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 849936c1-69a8-4734-8c4b-cd2e6354bc19
- true
- Pull Point
- Pull Point
-
9953
-16024
139
44
-
10015
-16002
- Point to search from
- 7804dddf-f9e6-4021-aba2-4f4236e58c4d
- true
- Point
- Point
- false
- 47fbfce5-2649-4fe6-84d2-5ca940b91239
- 1
-
9955
-16022
48
20
-
9979
-16012
- 1
- Geometry that pulls
- 52da7787-182c-47ab-b503-dbddb37e317d
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9955
-16002
48
20
-
9979
-15992
- Point on [G] closest to [P]
- f476e52c-9f16-4cf9-9dc8-53464df41ada
- true
- Closest Point
- Closest Point
- false
- 0
-
10027
-16022
63
20
-
10058.5
-16012
- Distance between [P] and its projection onto [G]
- 351ed84f-f1d6-4fc1-b0a9-9295c12aa741
- true
- Distance
- Distance
- false
- 0
-
10027
-16002
63
20
-
10058.5
-15992
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- fcdc1273-4010-457e-80e8-d6d2a5d24510
- efcfa711-59f2-48c9-bcfb-c0892d3a75e4
- 9961c67c-7b6b-4764-bdd1-a1e48583f369
- 849936c1-69a8-4734-8c4b-cd2e6354bc19
- 4
- 20768bee-5b47-4218-ad74-075117bbc07d
- Group
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 22729d4a-b218-4fd7-989a-a31c84d0f10d
- true
- Stream Filter
- Stream Filter
-
9982
-19922
77
64
-
10021
-19890
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 8c435c18-1c44-4dc4-bfc6-2d79f98fdc94
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9984
-19920
25
20
-
9996.5
-19910
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 4b62bba8-d476-48b3-901d-1d8c18192635
- true
- false
- Stream 0
- 0
- true
- b222f383-0934-4242-940d-878ab3058ed4
- 1
-
9984
-19900
25
20
-
9996.5
-19890
- 2
- Input stream at index 1
- c04c446d-807e-48cc-b595-607445751779
- true
- false
- Stream 1
- 1
- true
- 70dbeb6f-403d-4459-9312-a0aa407b68fe
- 1
-
9984
-19880
25
20
-
9996.5
-19870
- 2
- Filtered stream
- e2196bca-51e1-4e30-9af9-41a11d87bd51
- true
- false
- Stream
- S(0)
- false
- 0
-
10033
-19920
24
60
-
10045
-19890
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- db7d019a-d6ff-498f-b514-5ea0e3912544
- true
- Stream Filter
- Stream Filter
-
9949
-20457
77
64
-
9988
-20425
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 613da226-e593-4484-90ed-b34623433f20
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9951
-20455
25
20
-
9963.5
-20445
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 24cf5d70-fc28-4a67-aa22-b6cd66137b41
- true
- false
- Stream 0
- 0
- true
- e4642eb7-9328-471f-b935-fefc6d0913b2
- 1
-
9951
-20435
25
20
-
9963.5
-20425
- 2
- Input stream at index 1
- 18e84f39-6a41-4c97-89b1-a57ebb0eea77
- true
- false
- Stream 1
- 1
- true
- c046a698-34b6-4f2a-8d95-ed65bd2086e5
- 1
-
9951
-20415
25
20
-
9963.5
-20405
- 2
- Filtered stream
- 37e45a94-23d7-420f-b036-38884c3e20f7
- true
- false
- Stream
- S(0)
- false
- 0
-
10000
-20455
24
60
-
10012
-20425
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 160e178b-42c7-40d2-a1ec-81249c9df8bf
- true
- Pull Point
- Pull Point
-
9943
-20366
139
44
-
10005
-20344
- Point to search from
- 3300ce3f-1a44-48bd-978a-9d57fd4e6e33
- true
- Point
- Point
- false
- e4642eb7-9328-471f-b935-fefc6d0913b2
- 1
-
9945
-20364
48
20
-
9969
-20354
- 1
- Geometry that pulls
- e24d1cb7-7a82-41f9-bb3f-f181c46c8f0c
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9945
-20344
48
20
-
9969
-20334
- Point on [G] closest to [P]
- c046a698-34b6-4f2a-8d95-ed65bd2086e5
- true
- Closest Point
- Closest Point
- false
- 0
-
10017
-20364
63
20
-
10048.5
-20354
- Distance between [P] and its projection onto [G]
- 1c849118-22dd-418b-947c-ff3ddb1925e1
- true
- Distance
- Distance
- false
- 0
-
10017
-20344
63
20
-
10048.5
-20334
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- 24f73fbe-7c1b-4353-afad-1e194fccfe9e
- true
- End Points
- End Points
-
9973
-19553
84
44
-
10017
-19531
- Curve to evaluate
- 5b6be24b-2758-4b27-9dd3-1ef676245627
- true
- Curve
- Curve
- false
- b222f383-0934-4242-940d-878ab3058ed4
- 1
-
9975
-19551
30
40
-
9990
-19531
- Curve start point
- 12fc18e8-0eb3-49e0-a61c-f9a180f96129
- true
- Start
- Start
- false
- 0
-
10029
-19551
26
20
-
10042
-19541
- Curve end point
- 322a5174-be44-4720-834f-ce33a53f5317
- true
- End
- End
- false
- 0
-
10029
-19531
26
20
-
10042
-19521
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- e74a4531-a913-4207-a3ef-b18838106767
- true
- Line
- Line
-
9978
-19803
102
44
-
10044
-19781
- Line start point
- f951e113-ba16-4a17-a9f4-70cc3473f420
- true
- Start Point
- Start Point
- false
- 90645e4b-b95c-4f00-b0f8-9df3301174b9
- 1
-
9980
-19801
52
20
-
10006
-19791
- Line end point
- 657fa111-ec85-4e83-8d58-219a0f05d261
- true
- End Point
- End Point
- false
- adb6ba5c-3705-466e-a86f-e45769a74f16
- 1
-
9980
-19781
52
20
-
10006
-19771
- Line segment
- 70dbeb6f-403d-4459-9312-a0aa407b68fe
- true
- Line
- Line
- false
- 0
-
10056
-19801
22
40
-
10067
-19781
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 7d6aab00-a74d-4d7c-896c-db710a806431
- true
- Pull Point
- Pull Point
-
9954
-19733
139
44
-
10016
-19711
- Point to search from
- df282230-8696-4d69-9f31-e4c75d98c27d
- true
- Point
- Point
- false
- 12fc18e8-0eb3-49e0-a61c-f9a180f96129
- 1
-
9956
-19731
48
20
-
9980
-19721
- 1
- Geometry that pulls
- 1600942f-2c56-442e-bcdf-d19926b2931e
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9956
-19711
48
20
-
9980
-19701
- Point on [G] closest to [P]
- 90645e4b-b95c-4f00-b0f8-9df3301174b9
- true
- Closest Point
- Closest Point
- false
- 0
-
10028
-19731
63
20
-
10059.5
-19721
- Distance between [P] and its projection onto [G]
- 68d15499-e10c-4cd6-8720-45fa711f5ebe
- true
- Distance
- Distance
- false
- 0
-
10028
-19711
63
20
-
10059.5
-19701
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- fa53342d-6132-4ee6-ae1f-5b8810239bf4
- true
- Pull Point
- Pull Point
-
9956
-19642
139
44
-
10018
-19620
- Point to search from
- 19f00c4a-114d-449c-ab4b-c4f5fabf036c
- true
- Point
- Point
- false
- 322a5174-be44-4720-834f-ce33a53f5317
- 1
-
9958
-19640
48
20
-
9982
-19630
- 1
- Geometry that pulls
- f79da562-35aa-490d-bb37-da7addcb9b3f
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9958
-19620
48
20
-
9982
-19610
- Point on [G] closest to [P]
- adb6ba5c-3705-466e-a86f-e45769a74f16
- true
- Closest Point
- Closest Point
- false
- 0
-
10030
-19640
63
20
-
10061.5
-19630
- Distance between [P] and its projection onto [G]
- c031ba09-9341-4a49-ba56-fc10dba672f2
- true
- Distance
- Distance
- false
- 0
-
10030
-19620
63
20
-
10061.5
-19610
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 24f73fbe-7c1b-4353-afad-1e194fccfe9e
- e74a4531-a913-4207-a3ef-b18838106767
- 7d6aab00-a74d-4d7c-896c-db710a806431
- fa53342d-6132-4ee6-ae1f-5b8810239bf4
- 4
- ac64e75d-119f-4646-a091-52ab781d96c8
- Group
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- a2a12fdc-a10c-49ea-a720-42d451fd7849
- true
- Stream Filter
- Stream Filter
-
9989
-23368
77
64
-
10028
-23336
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 16540671-f5c3-4dd1-ad0c-ac9d7b999f04
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9991
-23366
25
20
-
10003.5
-23356
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- d10d547d-7027-44d3-a3e8-e872073e8858
- true
- false
- Stream 0
- 0
- true
- 401ad277-e9e4-4f79-8da6-d199f80326f0
- 1
-
9991
-23346
25
20
-
10003.5
-23336
- 2
- Input stream at index 1
- 1f1f4ca7-5552-43a4-8c5c-0e8f3195d14b
- true
- false
- Stream 1
- 1
- true
- 6b2d15eb-786a-4e29-b115-79c493b34b7e
- 1
-
9991
-23326
25
20
-
10003.5
-23316
- 2
- Filtered stream
- 8c57285f-88ad-4e27-b2fe-21dfb8d0c116
- true
- false
- Stream
- S(0)
- false
- 0
-
10040
-23366
24
60
-
10052
-23336
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 950bc8b3-379a-4e82-8f16-299c99da4440
- true
- Stream Filter
- Stream Filter
-
9956
-23957
77
64
-
9995
-23925
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 96968d9c-b897-4ae9-b053-bec42f9ffd50
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9958
-23955
25
20
-
9970.5
-23945
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 6909542d-0bfa-4ebf-a069-5edc7082b3c8
- true
- false
- Stream 0
- 0
- true
- b7c4cf28-434c-49cc-a026-b1e3b810d747
- 1
-
9958
-23935
25
20
-
9970.5
-23925
- 2
- Input stream at index 1
- 8bac3437-c56f-4736-ac60-457e51985cd9
- true
- false
- Stream 1
- 1
- true
- 7d2bec86-c155-449a-9b14-ae71252ef547
- 1
-
9958
-23915
25
20
-
9970.5
-23905
- 2
- Filtered stream
- bb1a355a-6f7f-4b8d-93f7-c629eab0cf46
- true
- false
- Stream
- S(0)
- false
- 0
-
10007
-23955
24
60
-
10019
-23925
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- c105f0d1-4e25-4771-9fbe-af4d0af47e02
- true
- Pull Point
- Pull Point
-
9950
-23866
139
44
-
10012
-23844
- Point to search from
- 4c3753c9-a621-4c2b-9e72-e8913618d3fd
- true
- Point
- Point
- false
- b7c4cf28-434c-49cc-a026-b1e3b810d747
- 1
-
9952
-23864
48
20
-
9976
-23854
- 1
- Geometry that pulls
- 099c64d2-359a-49be-877b-7d89ead7bb5f
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9952
-23844
48
20
-
9976
-23834
- Point on [G] closest to [P]
- 7d2bec86-c155-449a-9b14-ae71252ef547
- true
- Closest Point
- Closest Point
- false
- 0
-
10024
-23864
63
20
-
10055.5
-23854
- Distance between [P] and its projection onto [G]
- 591a4bc7-5055-48dc-83c8-500a6596d1a8
- true
- Distance
- Distance
- false
- 0
-
10024
-23844
63
20
-
10055.5
-23834
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- 686e2d2d-d42a-4d0e-aed8-49dfb9e864a1
- true
- End Points
- End Points
-
9980
-22999
84
44
-
10024
-22977
- Curve to evaluate
- 5e51f792-f408-446f-907b-08f25ff1d208
- true
- Curve
- Curve
- false
- 401ad277-e9e4-4f79-8da6-d199f80326f0
- 1
-
9982
-22997
30
40
-
9997
-22977
- Curve start point
- f478f996-c502-4760-9e7b-7376bb2984b5
- true
- Start
- Start
- false
- 0
-
10036
-22997
26
20
-
10049
-22987
- Curve end point
- 63430855-8e22-489b-b429-7ba46024fbf4
- true
- End
- End
- false
- 0
-
10036
-22977
26
20
-
10049
-22967
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- 9f9c8983-e06f-45f2-b028-00b48a4df33f
- true
- Line
- Line
-
9985
-23249
102
44
-
10051
-23227
- Line start point
- 1909a56d-98b4-4f6e-ada0-239af8da5224
- true
- Start Point
- Start Point
- false
- cd8785b9-1101-4044-8df4-c8f682f35708
- 1
-
9987
-23247
52
20
-
10013
-23237
- Line end point
- 024bb59e-b534-41d8-8dac-da2ed1ed48d2
- true
- End Point
- End Point
- false
- 719f0cac-c2d9-4cc7-8323-fea1913404c2
- 1
-
9987
-23227
52
20
-
10013
-23217
- Line segment
- 6b2d15eb-786a-4e29-b115-79c493b34b7e
- true
- Line
- Line
- false
- 0
-
10063
-23247
22
40
-
10074
-23227
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- cefafcd2-5a1f-4a1d-b499-f050365587e0
- true
- Pull Point
- Pull Point
-
9961
-23179
139
44
-
10023
-23157
- Point to search from
- b1b0f3d1-1f96-4a3e-b598-ad4c4ba6d677
- true
- Point
- Point
- false
- f478f996-c502-4760-9e7b-7376bb2984b5
- 1
-
9963
-23177
48
20
-
9987
-23167
- 1
- Geometry that pulls
- 3472d452-c5a8-4af9-9e57-842033d92c4a
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9963
-23157
48
20
-
9987
-23147
- Point on [G] closest to [P]
- cd8785b9-1101-4044-8df4-c8f682f35708
- true
- Closest Point
- Closest Point
- false
- 0
-
10035
-23177
63
20
-
10066.5
-23167
- Distance between [P] and its projection onto [G]
- d0418efe-9d2f-4140-b0a0-6665b510ad18
- true
- Distance
- Distance
- false
- 0
-
10035
-23157
63
20
-
10066.5
-23147
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- e2191903-1f01-4664-a19e-660b79cffb85
- true
- Pull Point
- Pull Point
-
9963
-23088
139
44
-
10025
-23066
- Point to search from
- c859b327-f96f-40b8-b105-2fc1bbe2eb9b
- true
- Point
- Point
- false
- 63430855-8e22-489b-b429-7ba46024fbf4
- 1
-
9965
-23086
48
20
-
9989
-23076
- 1
- Geometry that pulls
- 81e43296-a5f7-406a-b861-f77334fc2b9a
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9965
-23066
48
20
-
9989
-23056
- Point on [G] closest to [P]
- 719f0cac-c2d9-4cc7-8323-fea1913404c2
- true
- Closest Point
- Closest Point
- false
- 0
-
10037
-23086
63
20
-
10068.5
-23076
- Distance between [P] and its projection onto [G]
- 0a0205a7-4b56-4159-bf5d-5817ec1dfbb6
- true
- Distance
- Distance
- false
- 0
-
10037
-23066
63
20
-
10068.5
-23056
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 05b5844e-2d39-4d8c-8fc6-aba933fe2cdf
- true
- Stream Filter
- Stream Filter
-
9980
-26890
77
64
-
10019
-26858
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- a6ea476e-4929-43f8-bff2-318edbd3f6cf
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9982
-26888
25
20
-
9994.5
-26878
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 865683a0-1af5-4472-a1a5-3837f9e5259b
- true
- false
- Stream 0
- 0
- true
- 9a49f9f1-63b1-4713-8686-8e16f1aa6c2b
- 1
-
9982
-26868
25
20
-
9994.5
-26858
- 2
- Input stream at index 1
- 39830d77-e0b2-42c4-bba3-de726f5a643b
- true
- false
- Stream 1
- 1
- true
- 6ca20d94-d8d9-442f-acb2-5009044f939e
- 1
-
9982
-26848
25
20
-
9994.5
-26838
- 2
- Filtered stream
- 04846c6f-286e-480c-9c95-cf2ed46d9350
- true
- false
- Stream
- S(0)
- false
- 0
-
10031
-26888
24
60
-
10043
-26858
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 6f1c9af9-729a-48db-aa0a-03345ee8b37a
- true
- Stream Filter
- Stream Filter
-
9980
-27409
77
64
-
10019
-27377
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 11c13f00-254d-4f21-85ff-63095ff8a336
- true
- Gate
- Gate
- false
- 802b0d79-1abc-4cd7-ba38-3ade85c28c58
- 1
-
9982
-27407
25
20
-
9994.5
-27397
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 1bf9cc42-2433-4a45-b426-0d5040be72e3
- true
- false
- Stream 0
- 0
- true
- b34dac8b-8d64-4e79-82bb-d85237582fc3
- 1
-
9982
-27387
25
20
-
9994.5
-27377
- 2
- Input stream at index 1
- 4b9ef8e6-736a-4b48-a1ce-e900ffef3f62
- true
- false
- Stream 1
- 1
- true
- 0170897e-17f0-4697-8902-62eec306f948
- 1
-
9982
-27367
25
20
-
9994.5
-27357
- 2
- Filtered stream
- 9e6fc360-1810-4da7-a170-2f0668ae3de2
- true
- false
- Stream
- S(0)
- false
- 0
-
10031
-27407
24
60
-
10043
-27377
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- 0ec36096-bea3-4a12-9729-2f5990a754ac
- true
- Pull Point
- Pull Point
-
9949
-27318
139
44
-
10011
-27296
- Point to search from
- be30d659-fb5e-4f47-9d99-ce85f7cebf13
- true
- Point
- Point
- false
- b34dac8b-8d64-4e79-82bb-d85237582fc3
- 1
-
9951
-27316
48
20
-
9975
-27306
- 1
- Geometry that pulls
- 7996147a-6704-4c36-b2db-50e411c5b809
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9951
-27296
48
20
-
9975
-27286
- Point on [G] closest to [P]
- 0170897e-17f0-4697-8902-62eec306f948
- true
- Closest Point
- Closest Point
- false
- 0
-
10023
-27316
63
20
-
10054.5
-27306
- Distance between [P] and its projection onto [G]
- de8be8d3-73d8-425a-a946-31739fec03e9
- true
- Distance
- Distance
- false
- 0
-
10023
-27296
63
20
-
10054.5
-27286
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- 39d9776d-f76c-4f82-bce1-ae05c71a08cd
- true
- End Points
- End Points
-
9977
-26521
84
44
-
10021
-26499
- Curve to evaluate
- 2b4700db-1406-42ff-aa0c-ce5673a87970
- true
- Curve
- Curve
- false
- 9a49f9f1-63b1-4713-8686-8e16f1aa6c2b
- 1
-
9979
-26519
30
40
-
9994
-26499
- Curve start point
- 94a350bc-140b-421c-bbc4-dbecf9d24995
- true
- Start
- Start
- false
- 0
-
10033
-26519
26
20
-
10046
-26509
- Curve end point
- 431f4190-46e7-4bae-a59d-f8b048d6e94e
- true
- End
- End
- false
- 0
-
10033
-26499
26
20
-
10046
-26489
- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
- true
- ae24f77f-23d9-4cb6-84bd-e53fb80427de
- true
- Line
- Line
-
9968
-26771
102
44
-
10034
-26749
- Line start point
- 5b425db6-b031-410d-a08f-942dcefaa75e
- true
- Start Point
- Start Point
- false
- fd2b2675-0ad3-4ab8-9904-f69a6e4c20ca
- 1
-
9970
-26769
52
20
-
9996
-26759
- Line end point
- 6a96f43e-59c8-42ba-9a55-badc60c11f0e
- true
- End Point
- End Point
- false
- 168acd41-a9b7-4581-a4a4-fe7b47df39e5
- 1
-
9970
-26749
52
20
-
9996
-26739
- Line segment
- 6ca20d94-d8d9-442f-acb2-5009044f939e
- true
- Line
- Line
- false
- 0
-
10046
-26769
22
40
-
10057
-26749
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- cf106e66-67a2-4127-844d-20791dc209f1
- true
- Pull Point
- Pull Point
-
9949
-26701
139
44
-
10011
-26679
- Point to search from
- b3780019-53f1-4c4d-9103-00d1b3599506
- true
- Point
- Point
- false
- 94a350bc-140b-421c-bbc4-dbecf9d24995
- 1
-
9951
-26699
48
20
-
9975
-26689
- 1
- Geometry that pulls
- 70485353-9b85-4e09-957d-2c142f55e863
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9951
-26679
48
20
-
9975
-26669
- Point on [G] closest to [P]
- fd2b2675-0ad3-4ab8-9904-f69a6e4c20ca
- true
- Closest Point
- Closest Point
- false
- 0
-
10023
-26699
63
20
-
10054.5
-26689
- Distance between [P] and its projection onto [G]
- c218ffee-f5fa-4436-a3a7-4119da79bce9
- true
- Distance
- Distance
- false
- 0
-
10023
-26679
63
20
-
10054.5
-26669
- 902289da-28dc-454b-98d4-b8f8aa234516
- Pull Point
- true
- Pull a point to a variety of geometry.
- true
- aabab78d-e59f-4a58-9fec-eb1130dd5718
- true
- Pull Point
- Pull Point
-
9949
-26610
139
44
-
10011
-26588
- Point to search from
- ebd90529-688d-44a2-a7d9-5e296817480e
- true
- Point
- Point
- false
- 431f4190-46e7-4bae-a59d-f8b048d6e94e
- 1
-
9951
-26608
48
20
-
9975
-26598
- 1
- Geometry that pulls
- 9911dff6-d919-4269-a928-c3fccf079da3
- true
- Geometry
- Geometry
- false
- d2b2d690-7218-44bb-aa7c-3040cab09077
- 1
-
9951
-26588
48
20
-
9975
-26578
- Point on [G] closest to [P]
- 168acd41-a9b7-4581-a4a4-fe7b47df39e5
- true
- Closest Point
- Closest Point
- false
- 0
-
10023
-26608
63
20
-
10054.5
-26598
- Distance between [P] and its projection onto [G]
- 775a7539-c249-4436-a3b1-89387fb4bef0
- true
- Distance
- Distance
- false
- 0
-
10023
-26588
63
20
-
10054.5
-26578
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 04872530-3f20-4b2f-bfcb-1e4ced53d625
- true
- Stream Filter
- Stream Filter
-
9981
-30149
77
64
-
10020
-30117
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
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- Gate
- Gate
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9983
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25
20
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9983
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25
20
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25
20
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- Filtered stream
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- Stream
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10032
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24
60
-
10044
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- Stream Filter
- Filters a collection of input streams
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- Stream Filter
- Stream Filter
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9974
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77
64
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10013
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- Index of Gate stream
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- Gate
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9976
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25
20
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9976
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25
20
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9976
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25
20
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9988.5
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- Stream
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10025
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24
60
-
10037
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- Pull Point
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- Pull a point to a variety of geometry.
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139
44
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10005
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- Point to search from
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- Point
- Point
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9945
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48
20
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9969
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- Geometry that pulls
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9945
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48
20
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9969
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- Point on [G] closest to [P]
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- Closest Point
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-
10017
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63
20
-
10048.5
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- Distance between [P] and its projection onto [G]
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10017
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63
20
-
10048.5
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- End Points
- Extract the end points of a curve.
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- End Points
- End Points
-
9983
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84
44
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10027
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- Curve to evaluate
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- Curve
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9985
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30
40
-
10000
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- Curve start point
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10039
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26
20
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10052
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- Curve end point
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10039
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26
20
-
10052
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- 4c4e56eb-2f04-43f9-95a3-cc46a14f495a
- Line
- Create a line between two points.
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- Line
- Line
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9974
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102
44
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10040
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- Line start point
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9976
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52
20
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10002
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- Line end point
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9976
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52
20
-
10002
-30023
- Line segment
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10052
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22
40
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10063
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- Pull Point
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- Pull a point to a variety of geometry.
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- Pull Point
- Pull Point
-
9955
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139
44
-
10017
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- Point to search from
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- Point
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9957
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48
20
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9981
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- Geometry that pulls
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9957
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48
20
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9981
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- Point on [G] closest to [P]
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-
10029
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63
20
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10060.5
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- Distance between [P] and its projection onto [G]
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-
10029
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63
20
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10060.5
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- Pull Point
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- Pull a point to a variety of geometry.
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- true
- Pull Point
- Pull Point
-
9955
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139
44
-
10017
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- Point to search from
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- Point
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9957
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48
20
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9981
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- Geometry that pulls
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9957
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48
20
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9981
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- Point on [G] closest to [P]
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10029
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63
20
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10060.5
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- Distance between [P] and its projection onto [G]
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- Distance
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- 0
-
10029
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63
20
-
10060.5
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- CURWE CURWATURE COMB LINES SCALE
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- CURWE CURWATURE COMB LINES SCALE
- CURWE CURWATURE COMB LINES SCALE
- bfc5f4ab-3919-4abb-8151-d9a52a9477f3
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- CURWE CURWATURE COMB LINES SCALE
- CURWE CURWATURE COMB LINES SCALE
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- 0
-
9904
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232
24
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- Relay
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- A wire relay object
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8313
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40
16
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8333
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- When clicked, the button object only raises recomputation one time.
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- True
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- True Only Button
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- 0
- neutral,N
-
10222
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66
22
- afb96615-c59a-45c9-9cac-e27acb1c7ca0
- Explode
- Explode a curve into smaller segments.
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- Explode
- Explode
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10682
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134
44
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10753
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- Curve to explode
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10684
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57
20
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10712.5
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- Recursive decomposition until all segments are atomic
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10684
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57
20
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10712.5
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- 1
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- Exploded segments that make up the base curve
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10765
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49
20
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10789.5
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10765
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49
20
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10789.5
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- Curve
- Contains a collection of generic curves
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10525
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50
24
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10550.66
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
- 00000000-0000-0000-0000-000000000000
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
- 00000000-0000-0000-0000-000000000000
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
- 00000000-0000-0000-0000-000000000000
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- Scale an object with non-uniform factors.
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- Deconstruct a numeric domain into its component parts.
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- Deconstruct a numeric domain into its component parts.
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- Extract the end points of a curve.
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- End Points
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- Create a rectangle from a base plane and two points
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- Retrieve the base plane and side intervals of a rectangle.
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- Preview a Drawing in canvas.
Note: Right click on the component to save the image or svg
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- The shape to be used at the end of open path
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- Create a polar array of geometry.
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- Solve oriented geometry bounding boxes.
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35
40
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10899.5
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- Applies Stroke properties to a Shape
- true
- af8252e4-c4e4-41ca-bc69-621892a52ed3
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- Stroke
- Stroke
-
11770
-711
210
104
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11934
-659
- A Graphic Plus Shape, or a Curve, Brep, Mesh
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11772
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20
-
11847
-699
- The stroke color
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- Color
- Color
- true
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-
11772
-689
150
20
-
11847
-679
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- 1
- {0}
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0;212;212;212
- The stroke weight
- 79086af1-8739-452d-b958-b2a7b7ee8dc7
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- Weight
- Weight
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-
11772
-669
150
20
-
11847
-659
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- {0}
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- Pattern
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-
11772
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150
20
-
11847
-639
- The shape to be used at the end of open path
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- End Cap
- true
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-
11772
-629
150
20
-
11847
-619
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- 1
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- A Graphic Plus Shape Object
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11946
-709
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100
-
11962
-659
- db7d83b1-2898-4ef9-9be5-4e94b4e2048d
- Deconstruct Box
- Deconstruct a box into its constituent parts.
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- true
- Deconstruct Box
- Deconstruct Box
-
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84
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10866
-381
- Base box
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- Box
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10833
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80
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10843.5
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10878
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20
-
10892
-411
- {x} dimension of box
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- X
- X
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- 0
-
10878
-401
28
20
-
10892
-391
- {y} dimension of box
- ed2e0d66-3dc3-4a72-86e9-120e54328e2f
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- Y
- Y
- false
- 0
-
10878
-381
28
20
-
10892
-371
- {z} dimension of box
- 826941b6-6f7b-4138-90df-9d21f072906d
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- Z
- Z
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- 0
-
10878
-361
28
20
-
10892
-351
- b7798b74-037e-4f0c-8ac7-dc1043d093e0
- Rotate
- Rotate an object in a plane.
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- Rotate
- Rotate
-
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226
81
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10753
-998
- Base geometry
- b83320a7-545c-429a-a27a-22fc4971d37a
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- Geometry
- Geometry
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10593
-1037
148
20
-
10675
-1027
- Rotation angle in degrees
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- 0
- true
-
10593
-1017
148
20
-
10675
-1007
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- {0}
- 45
- Rotation plane
- df17c062-6ed2-496e-a8b5-d8d570ab9bc2
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10593
-997
148
37
-
10675
-978.5
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- {0}
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0
0
0
1
0
0
0
1
0
- Rotated geometry
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- 0
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10765
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10790
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- Transform
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-
10765
-999
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39
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10790
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- Ellipse
- Create an ellipse defined by base plane and two radii.
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- Ellipse
- Ellipse
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11043
-292
211
81
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11200
-251
- Base plane of ellipse
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11045
-290
143
37
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11124.5
-271.5
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- {0}
-
0
0
0
1
0
0
0
1
0
- Radius in {x} direction
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- X/2
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- Radius 1
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- 09dd62e4-baf4-427f-8bf7-9dcb47097299
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11045
-253
143
20
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11124.5
-243
- 1
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- 1
- Radius in {y} direction
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- X/2
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11045
-233
143
20
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11124.5
-223
- 1
- 1
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- Resulting ellipse
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11212
-290
40
25
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11232
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- First focus point
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- Focus 1
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11212
-265
40
26
-
11232
-251.5
- Second focus point
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- Focus 2
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- 0
-
11212
-239
40
26
-
11232
-225.8333
- 825ea536-aebb-41e9-af32-8baeb2ecb590
- Deconstruct Domain
- Deconstruct a numeric domain into its component parts.
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- Deconstruct Domain
- Deconstruct Domain
-
10820
-241
108
44
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10872
-219
- Base domain
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- Domain
- Domain
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10822
-239
38
40
-
10841
-219
- Start of domain
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- ABS(X)
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- Start
- Start
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- 0
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10884
-239
42
20
-
10897
-229
- End of domain
- 9c7fe524-e2c2-4733-a305-6c3b0bd827b1
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- End
- End
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- 0
-
10884
-219
42
20
-
10897
-209
- 825ea536-aebb-41e9-af32-8baeb2ecb590
- Deconstruct Domain
- Deconstruct a numeric domain into its component parts.
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- true
- Deconstruct Domain
- Deconstruct Domain
-
10818
-184
108
44
-
10870
-162
- Base domain
- 3f278867-77af-4574-9fc1-951552bef148
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- Domain
- Domain
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- ed2e0d66-3dc3-4a72-86e9-120e54328e2f
- 1
-
10820
-182
38
40
-
10839
-162
- Start of domain
- fa179bd7-3caf-4ff0-bf57-3128d60df3b7
- ABS(X)
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- Start
- Start
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- 0
-
10882
-182
42
20
-
10895
-172
- End of domain
- 0af08690-d4ea-48c3-8fe8-7d930c816d3c
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- End
- End
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- 0
-
10882
-162
42
20
-
10895
-152
- a0d62394-a118-422d-abb3-6af115c75b25
- Addition
- Mathematical addition
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- 548a5159-28a2-46e1-bd31-a35248f6cea4
- true
- Addition
- Addition
-
10943
-241
70
44
-
10968
-219
- 2
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- First item for addition
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- A
- A
- true
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- 1
-
10945
-239
11
20
-
10950.5
-229
- Second item for addition
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- B
- B
- true
- 9c7fe524-e2c2-4733-a305-6c3b0bd827b1
- 1
-
10945
-219
11
20
-
10950.5
-209
- Result of addition
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- 0
-
10980
-239
31
40
-
10995.5
-219
- a0d62394-a118-422d-abb3-6af115c75b25
- Addition
- Mathematical addition
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- true
- Addition
- Addition
-
10945
-184
70
44
-
10970
-162
- 2
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- First item for addition
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- A
- A
- true
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- 1
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10947
-182
11
20
-
10952.5
-172
- Second item for addition
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- B
- B
- true
- 0af08690-d4ea-48c3-8fe8-7d930c816d3c
- 1
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10947
-162
11
20
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10952.5
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- Result of addition
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-
10982
-182
31
40
-
10997.5
-162
- 5881d944-0281-4fc8-b203-ce6a55dbf2a6
- a48ac930-c378-48dc-84da-26b2af9d8302
- Solid Fill
- Applies a Solid Fill color to a Shape
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- e544f35b-a65c-4604-8ec4-0197ac401c45
- true
- Solid Fill
- Solid Fill
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11213
-477
162
44
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11329
-455
- A Graphic Plus Shape, or a Curve, Brep, Mesh
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11215
-475
102
20
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11266
-465
- The solid fill Color
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- true
- Color
- Color
- true
- 0
-
11215
-455
102
20
-
11266
-445
- 1
- 1
- {0}
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255;253;253;253
- A Graphic Plus Shape Object
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- 0
-
11341
-475
32
40
-
11357
-455
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- Stroke
- Applies Stroke properties to a Shape
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- c60c0fcd-fecd-4bfd-abef-dabf43b0a95f
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- Stroke
- Stroke
-
11274
-382
210
104
-
11438
-330
- A Graphic Plus Shape, or a Curve, Brep, Mesh
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- a70c88fb-eb29-4569-a95d-7b398b6e49b6
- 1
-
11276
-380
150
20
-
11351
-370
- The stroke color
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- Color
- Color
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- 0
-
11276
-360
150
20
-
11351
-350
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0;212;212;212
- The stroke weight
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- 0
-
11276
-340
150
20
-
11351
-330
- 1
- 1
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- The stroke pattern
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- Pattern
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-
11276
-320
150
20
-
11351
-310
- The shape to be used at the end of open path
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- End Cap
- End Cap
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-
11276
-300
150
20
-
11351
-290
- 1
- 1
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- A Graphic Plus Shape Object
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- 0
-
11450
-380
32
100
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11466
-330
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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- Merge
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11720
-575
122
104
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11781
-523
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11722
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11753.5
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11722
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47
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11753.5
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- D3
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11722
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11753.5
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- D4
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11722
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11753.5
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- D5
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11722
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47
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11753.5
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- Result of merge
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11793
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47
100
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11808.5
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- Solve oriented geometry bounding boxes.
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- Bounding Box
- Bounding Box
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-
10950
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172
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11087
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10952
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123
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11013.5
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-
10952
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123
37
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11013.5
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0
0
0
1
0
0
0
1
0
- Aligned bounding box in world coordinates
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-
11099
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21
28
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11109.5
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- Bounding box in orientation plane coordinates
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11099
-716
21
29
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11109.5
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- Create a polar array of geometry.
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- Polar Array
- Polar Array
-
10354
-1
226
101
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10500
50
- Base geometry
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10356
1
132
20
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10422
11
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10356
21
132
37
-
10422
39.5
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0
0
0
1
0
0
0
1
0
- Number of elements in array.
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- Count
- Count
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- 0
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10356
58
132
20
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10422
68
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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10356
78
132
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10422
88
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10512
1
66
48
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10537
25.25
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- 0
-
10512
49
66
49
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10537
73.75
- 8073a420-6bec-49e3-9b18-367f6fd76ac3
- Join Curves
- Join as many curves as possible
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- Join Curves
- Join Curves
-
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116
44
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10743
-80
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- 115805d1-8d4c-48be-b77a-c986e4fcad30
- true
- Shape
- Shape
- false
- 0
-
11704
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32
100
-
11720
-77
- 5881d944-0281-4fc8-b203-ce6a55dbf2a6
- a48ac930-c378-48dc-84da-26b2af9d8302
- Solid Fill
- Applies a Solid Fill color to a Shape
- true
- 094b241c-4ba3-4343-8745-17a25e1a18d5
- true
- Solid Fill
- Solid Fill
-
11197
-646
162
44
-
11313
-624
- A Graphic Plus Shape, or a Curve, Brep, Mesh
- 23bd9ad5-0ed7-4bd5-9ebf-540a6ef29898
- true
- Shape / Geometry
- Shape / Geometry
- false
- 459c146e-b950-4487-9814-03c0b98d439f
- 1
-
11199
-644
102
20
-
11250
-634
- The solid fill Color
- 821cf43e-983c-41cd-9ae5-93e78e154639
- true
- Color
- Color
- true
- 0
-
11199
-624
102
20
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11250
-614
- 1
- 1
- {0}
-
255;255;255;255
- A Graphic Plus Shape Object
- true
- d91d7edd-1058-45d7-83bd-c03acddb095d
- true
- Shape
- Shape
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- 0
-
11325
-644
32
40
-
11341
-624
- 030b487b-a566-476f-96a4-a0ae2ad283af
- a48ac930-c378-48dc-84da-26b2af9d8302
- Stroke
- Applies Stroke properties to a Shape
- true
- 7b5a9a86-c795-4535-9dcb-e11a8115d709
- true
- Stroke
- Stroke
-
10336
150
210
104
-
10500
202
- A Graphic Plus Shape, or a Curve, Brep, Mesh
- 41184173-460d-4935-8d2a-b395bd72e4cf
- true
- Shape / Geometry
- Shape / Geometry
- false
- d5b4aeff-ff26-4ef9-b2e5-496815defd19
- 1
-
10338
152
150
20
-
10413
162
- The stroke color
- cd2a8d19-a05c-4b58-928a-acec91724c8f
- true
- Color
- Color
- true
- 0
-
10338
172
150
20
-
10413
182
- 1
- 1
- {0}
-
0;212;212;212
- The stroke weight
- af3deb4d-921e-419b-bb17-e6ea5c6560d6
- true
- Weight
- Weight
- true
- 0
-
10338
192
150
20
-
10413
202
- 1
- 1
- {0}
- 1.599609375
- 1
- The stroke pattern
- 044c0805-b6e4-47b3-8a63-28db1416baf7
- true
- Pattern
- Pattern
- true
- 0
-
10338
212
150
20
-
10413
222
- The shape to be used at the end of open path
- ecd41d37-9728-4d7b-89b2-ce69e6e82acb
- true
- End Cap
- End Cap
- true
- 0
-
10338
232
150
20
-
10413
242
- 1
- 1
- {0}
- 2
- A Graphic Plus Shape Object
- true
- 459c146e-b950-4487-9814-03c0b98d439f
- true
- Shape
- Shape
- false
- 0
-
10512
152
32
100
-
10528
202
- ae8329c9-147c-4440-b557-2977e71e7195
- a48ac930-c378-48dc-84da-26b2af9d8302
- Blur
- Applies a Blur Effect to a Shape
- true
- d1f66e6c-d809-4b52-ab33-d5f0fd7fa67e
- true
- Blur
- Blur
-
11388
-622
183
44
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11525
-600
- A Graphic Plus Shape, or a Curve, Brep, Mesh
- 7f9fbeac-12da-452a-8949-36ad5971594a
- true
- Shape / Geometry
- Shape / Geometry
- false
- d91d7edd-1058-45d7-83bd-c03acddb095d
- 1
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11390
-620
123
20
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11451.5
-610
- The radius of the blur effect
- c35e1a89-d0f8-49d9-8a3c-0ee5cb7cd0d6
- true
- Blur Radius
- Blur Radius
- true
- 0
-
11390
-600
123
20
-
11451.5
-590
- 1
- 1
- {0}
- 1873
- A Graphic Plus Shape Object
- true
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- true
- Shape
- Shape
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- 0
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11537
-620
32
40
-
11553
-600
- 310f9597-267e-4471-a7d7-048725557528
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- GraphMapper+
- External Graph mapper
You can Right click on the Heteromapper's icon and choose "AutoDomain" mode to define Output domain based on input domain interval; otherwise it'll be set to 0-1 in "Normalized" mode.
- true
- 86516fa6-1a29-401a-89ee-beff2a4a71be
- true
- GraphMapper+
- GraphMapper+
- true
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10422
-239
200
155
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10569
-161
- External curve as a graph
- 2a62c603-ff0d-4b02-9c51-19896bb4670e
- true
- Curve
- Curve
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- f110d2a6-04ba-40d1-8ede-576629de1ee0
- 1
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10424
-237
133
20
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10490.5
-227
- Optional Rectangle boundary. If omitted the curve's would be landed
- 3676e81d-aa14-4d99-8a29-6dd22cb97c19
- true
- Boundary
- Boundary
- true
- 0
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10424
-217
133
71
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10490.5
-181.5
- 1
- List of input numbers
- b636a3d1-7793-408c-84e3-26e2731f59c4
- true
- Numbers
- Numbers
- false
- dc1f0f58-8adb-425c-a5a4-72b7549f074b
- 1
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10424
-146
133
20
-
10490.5
-136
- 1
- 9
- {0}
- 0.1
- 0.2
- 0.3
- 0.4
- 0.5
- 0.6
- 0.7
- 0.8
- 0.9
- (Optional) Input Domain
if omitted, it would be 0-1 in "Normalize" mode by default
or be the interval of the input list in case of selecting "AutoDomain" mode
- d7a1fb96-cedd-465e-a75a-08f646090e4d
- true
- Input
- Input
- true
- 0
-
10424
-126
133
20
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10490.5
-116
- (Optional) Output Domain
if omitted, it would be 0-1 in "Normalize" mode by default
or be the interval of the input list in case of selecting "AutoDomain" mode
- 87642418-c6c9-406c-a417-46458eb64db2
- true
- Output
- Output
- true
- 0
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10424
-106
133
20
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10490.5
-96
- 1
- Output Numbers
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- true
- Number
- Number
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10581
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39
151
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10600.5
-161.5
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- e997adff-dd39-4839-a3ba-005ec6fc52aa
- true
- Merge
- Merge
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10052
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90
64
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10097
-258
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
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- true
- false
- Data 1
- D1
- true
- 0b623e50-0ddb-4c5a-8522-9b22b8669904
- 1
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10054
-288
31
20
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10069.5
-278
- 2
- Data stream 2
- 06b3985f-140a-46bf-bc8e-d38d13cbc7bd
- true
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- Data 2
- D2
- true
- 000617f7-d240-4fc8-ae4d-4525fd018986
- 1
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10054
-268
31
20
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10069.5
-258
- 2
- Data stream 3
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- true
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- Data 3
- D3
- true
- 0
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10054
-248
31
20
-
10069.5
-238
- 2
- Result of merge
- dcf72494-3a24-4054-8e57-73ff14e59867
- true
- Result
- Result
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- 0
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10109
-288
31
60
-
10124.5
-258
- 8073a420-6bec-49e3-9b18-367f6fd76ac3
- Join Curves
- Join as many curves as possible
- true
- cde9ae79-6dfc-4694-91e2-ee29e1d1dcd7
- true
- Join Curves
- Join Curves
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10156
-205
116
44
-
10223
-183
- 1
- Curves to join
- 7e85ddef-afbe-4a51-8eb9-f1bf04d0e562
- true
- Curves
- Curves
- false
- dcf72494-3a24-4054-8e57-73ff14e59867
- 1
-
10158
-203
53
20
-
10184.5
-193
- Preserve direction of input curves
- e052876e-6956-4144-81f8-c77fa5c3b19b
- true
- Preserve
- Preserve
- false
- 0
-
10158
-183
53
20
-
10184.5
-173
- 1
- 1
- {0}
- false
- 1
- Joined curves and individual curves that could not be joined.
- f110d2a6-04ba-40d1-8ede-576629de1ee0
- true
- Curves
- Curves
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- 0
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10235
-203
35
40
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10252.5
-183
- 6da9f120-3ad0-4b6e-9fe0-f8cde3a649b7
- Gradient
- Represents a multiple colour gradient
- true
- 4ce826ff-60b9-473f-b4eb-19a5a0af2170
- true
- Gradient
- Gradient
- 2
- false
- false
-
255;255;255;255
-
255;255;255;255
- 0
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255;0;0;0
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255;0;0;0
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10096
-110
250
64
- Lower limit of gradient range
- 945cfa44-8efc-4474-beb8-68346657865d
- true
- Lower limit
- Lower limit
- false
- 0
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10102
-108
71
20
-
10137.5
-98
- 1
- 1
- {0}
- 0
- Upper limit of gradient range
- b5bbc1f3-0799-4b1f-8720-7900ecb64630
- true
- Upper limit
- Upper limit
- false
- 0
-
10102
-88
71
20
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10137.5
-78
- 1
- 1
- {0}
- 1
- Parameter along gradient range
- c8a087a3-d6c3-4075-94f5-b6f03f5a18b8
- true
- Parameter
- Parameter
- false
- 0
-
10102
-68
71
20
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10137.5
-58
- 1
- 1
- {0}
- 0.5
- Colour along gradient at parameter
- dc1f0f58-8adb-425c-a5a4-72b7549f074b
- true
- Colour
- Colour
- false
- 0
-
10346
-110
0
64
- f44b92b0-3b5b-493a-86f4-fd7408c3daf3
- Bounds
- Create a numeric domain which encompasses a list of numbers.
- true
- 73688d20-ee53-456b-b585-492357d5b4d0
- true
- Bounds
- Bounds
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10159
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110
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10217
-23
- 1
- Numbers to include in Bounds
- 53f4ce57-ff16-487d-8441-74fef124b562
- true
- Numbers
- Numbers
- false
- dc1f0f58-8adb-425c-a5a4-72b7549f074b
- 1
-
10161
-35
44
24
-
10183
-23
- Numeric Domain between the lowest and highest numbers in {N}
- 0ff1a809-670a-45b7-b851-7fc3bf208445
- true
- Domain
- Domain
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- 0
-
10229
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38
24
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10248
-23
- ae8329c9-147c-4440-b557-2977e71e7195
- a48ac930-c378-48dc-84da-26b2af9d8302
- Blur
- Applies a Blur Effect to a Shape
- true
- e1697a07-a9ef-47c4-be33-bd2577c238b3
- true
- Blur
- Blur
-
11400
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167
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11521
-680
- A Graphic Plus Shape, or a Curve, Brep, Mesh
- 55536ade-da41-411e-869c-66f8f104949a
- true
- Shape / Geometry
- Shape / Geometry
- false
- 9b545ea8-d3f4-45eb-ab0f-79f46e4a2580
- 1
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11402
-700
107
20
-
11455.5
-690
- The radius of the blur effect
- c5060ea3-181f-4105-bb73-304ce2614be6
- true
- Blur Radius
- Blur Radius
- true
- 0
-
11402
-680
107
20
-
11455.5
-670
- 1
- 1
- {0}
- 4
- A Graphic Plus Shape Object
- true
- 8ea3d944-5234-46ce-8de0-309341193327
- true
- Shape
- Shape
- false
- 0
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11533
-700
32
40
-
11549
-680
- e168ff6b-e5c0-48f1-b831-f6996bf3b459
- Interpolate data
- Interpolate a collection of data.
- true
- c38bf768-8e55-4765-a68e-79216a92a01f
- 1
- true
- Interpolate data
- Interp
-
12304
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12329
-421
- 1
- Data to interpolate (simple data types only).
- ee7aa4b8-d343-4799-9e97-44326e8b51b2
- true
- Data
- D
- false
- ba66facb-933d-4bdd-9084-fdf31378561d
- 1
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12306
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11
20
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12311.5
-431
- Normalised interpolation parameter.
- 651ee240-e128-441b-b3cd-7c874bf4a566
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- Parameter
- t
- false
- ef04d9bd-6df7-4f34-9b5e-95c0bba48b81
- 1
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12306
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12311.5
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- Interpolated value.
- 15f97ead-92d7-4e3c-bc72-cd786e882edb
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- Value
- V
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- 0
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12341
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10
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12346
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- Red
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255;255;255;255
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- Relay
- false
- 7fd0d788-1237-49d2-b610-14b9cdecf740
- 1
-
-14100
1403
40
16
-
-14080
1411
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1285/256))
- true
- 77885843-cab1-42df-89ef-8ef6f86566c5
- Expression
- Expression
-
-14842
1134
207
28
-
-14736
1148
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- 1995246f-289e-4ca3-ba04-aced7cd0dd72
- Variable O
- O
- true
- 898a5c5d-3c47-497d-9e6c-94065d0c488f
- 1
-
-14840
1136
11
24
-
-14834.5
1148
- Result of expression
- 5293ab1a-72a3-466f-8acb-12d53fff800e
- Result
- false
- 0
-
-14643
1136
6
24
-
-14640
1148
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1423/256))
- true
- 62e50431-70a5-40a1-bbba-f39166ca5d3f
- Expression
- Expression
-
-14842
1083
207
28
-
-14736
1097
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- e995b869-e468-49a5-8a2d-d6a6c4ee65bb
- Variable O
- O
- true
- 898a5c5d-3c47-497d-9e6c-94065d0c488f
- 1
-
-14840
1085
11
24
-
-14834.5
1097
- Result of expression
- 0c05c4dc-a41d-4f25-8fa8-59904954782e
- Result
- false
- 0
-
-14643
1085
6
24
-
-14640
1097
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1488/256))
- true
- 6cddbed6-1dd7-44ed-a9e0-86fb89ef71a3
- Expression
- Expression
-
-14842
1032
207
28
-
-14736
1046
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- 188ea3f9-3d71-488d-a663-f1aebd24f572
- Variable O
- O
- true
- 898a5c5d-3c47-497d-9e6c-94065d0c488f
- 1
-
-14840
1034
11
24
-
-14834.5
1046
- Result of expression
- b808466f-043c-43c9-872f-0833987d5625
- Result
- false
- 0
-
-14643
1034
6
24
-
-14640
1046
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1644/256))
- true
- e469ff08-a104-48ec-9f4e-573c7b3bfe16
- Expression
- Expression
-
-14842
985
207
28
-
-14736
999
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- e21cd616-c856-435f-b9bb-99df4f859c1a
- Variable O
- O
- true
- 898a5c5d-3c47-497d-9e6c-94065d0c488f
- 1
-
-14840
987
11
24
-
-14834.5
999
- Result of expression
- 88231914-12a4-4ab2-8751-7897fa9c1043
- Result
- false
- 0
-
-14643
987
6
24
-
-14640
999
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1709.5/256))
- true
- 20d5d108-2056-41af-930a-8e90a1009dff
- Expression
- Expression
-
-14850
937
223
28
-
-14736
951
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- b43f180b-fc85-4b05-92b0-c3331dbc3dea
- Variable O
- O
- true
- 898a5c5d-3c47-497d-9e6c-94065d0c488f
- 1
-
-14848
939
11
24
-
-14842.5
951
- Result of expression
- 59be1fbf-4cb3-42fe-8174-bf8b71739b0e
- Result
- false
- 0
-
-14635
939
6
24
-
-14632
951
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1794.5/256))
- true
- 87e01a5c-d135-4116-817d-da2496621529
- Expression
- Expression
-
-14850
882
223
28
-
-14736
896
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- dc9595aa-3dee-4da2-8d0c-c395029d8a6a
- Variable O
- O
- true
- 898a5c5d-3c47-497d-9e6c-94065d0c488f
- 1
-
-14848
884
11
24
-
-14842.5
896
- Result of expression
- 34ff7268-139f-4f7c-918d-a790b243fd03
- Result
- false
- 0
-
-14635
884
6
24
-
-14632
896
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1874.5/256))
- true
- 03b98b72-99ad-4536-9e58-90622f9ef991
- Expression
- Expression
-
-14850
827
223
28
-
-14736
841
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- 5853fbe8-0752-447a-bbce-fb563454ca9e
- Variable O
- O
- true
- 898a5c5d-3c47-497d-9e6c-94065d0c488f
- 1
-
-14848
829
11
24
-
-14842.5
841
- Result of expression
- 47598a96-ccb9-4b95-ba69-e34e2d68ea96
- Result
- false
- 0
-
-14635
829
6
24
-
-14632
841
- 9df5e896-552d-4c8c-b9ca-4fc147ffa022
- Expression
- Evaluate an expression
- O*256/(2^(1910.9609375/256))
- true
- 55a8e211-f823-44ad-b334-d360d90f528a
- Expression
- Expression
-
-14875
777
273
28
-
-14736
791
- 1
- ba80fd98-91a1-4958-b6a7-a94e40e52bdb
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Expression variable
- 350f11e7-3838-41b6-a4ae-3223f4993da3
- Variable O
- O
- true
- 898a5c5d-3c47-497d-9e6c-94065d0c488f
- 1
-
-14873
779
11
24
-
-14867.5
791
- Result of expression
- c8faf00d-35ab-4093-8e9d-f4865d3ec68f
- Result
- false
- 0
-
-14610
779
6
24
-
-14607
791
- f31d8d7a-7536-4ac8-9c96-fde6ecda4d0a
- ⦿옷⦿ᑫᑭ⦿ᗩ⦿ᴥ⦿ᕤᕦ⦿◯⦿ᗝ⦿ᗱᗴ⦿ᑫᑭ⦿ᗩ⦿옷⦿ᔓᔕ⦿◯⦿ᔓᔕ⦿ᗱᗴ⦿ᑐᑕ⦿ИN⦿ᗱᗴ⦿ᴥ⦿ᗱᗴ⦿Θ⦿⊙⦿ᗝ⦿◯⦿ᗱᗴ⦿ᴥ⦿ᑎ⦿✤⦿ᗩ⦿ᗯ⦿ᴥ⦿ᑎ⦿ᑐᑕ⦿◌⦿◌⦿◌⦿◌⦿◌⦿◌⦿◌⦿◌⦿ᑐᑕ⦿ᑎ⦿ᴥ⦿ᗯ⦿ᗩ⦿✤⦿ᑎ⦿ᴥ⦿ᗱᗴ⦿◯⦿ᗝ⦿⊙⦿Θ⦿ᗱᗴ⦿ᴥ⦿ᗱᗴ⦿ИN⦿ᑐᑕ⦿ᗱᗴ⦿ᔓᔕ⦿◯⦿ᔓᔕ⦿옷⦿ᗩ⦿ᑫᑭ⦿ᗱᗴ⦿ᗝ⦿◯⦿ᕤᕦ⦿ᴥ⦿ᗩ⦿ᑫᑭ⦿옷⦿
-
7H0HXBNJ+/+iIE2KgqKHJVhREcGOwkkSOqEoqNgJJEAkJDEJKmfDroAdFVGxK1bsvaAi6tkVezn1PEU9Tz3LqWf5z2x2Q3azuyQvAfL+/q/30YN5spPZ7/PMU2aeecbCTxqfmiKUKH+APyYIgpiBv7YycWqiSDJspFCuEEklkBQJmiEZ/jGHH8GfCxLyBUI5/IgZRrbCScF+sNkSNP07cumOCStqhq9YEbYn5GLKffNIuXCkSDgK0q0AvVZUEuhFYIc1hwkVSdFpMiEk18S+2AajhUvlKXwxpLQAratWrfqBPxUlFAvjlUIBThOJRD8c/YQJIolICd4iUi6VCeVKkVCBdwv/mvrxlej3WIBfdj1KyZg3/a6FtZ9QES8XyZTYy8MhIqbh/BQh/turmjFBge7uj/cseZE3E/z7eHEB+PfR4h2PFu9Gf0B/3b0O/jtvNvrv3EfzFqo/eTknHP68YArsYRF85PGyteqfH2UveJS9UP2xR4s3qntTfUzVyYvFu2D7komEr8afxYaEUTcSh7e87HszctEPZzH9nLtJ3SH2L9bC+BT6M/ZG6DdqDGCjemzYOPFhl30GpareEftS9N0xVNEeMHzwZ7WRVCGMoa36IpwRGF+w3gjsw+BFOevuHhgUY9kHSBicCgp8msA/NngrV5qqmkA18SkAhG04EEZMfmpgzbWi+fJEIfrJJuDXJNB+2hlI1kCpNAWfQU6tD/mY9QPirP4q+NcSthC+BraawlZUNvEvYEvik6TobGyKNmw/jizpG2irag5WlH0/2jFBpE08COPYXMjuZdknXsbjp0lTlZqvbRUol6bKtN65dmAQmyeKk/Pl2BSDn4dvbkb4KGwxV30uDR0y9rg9W6EQpsSJ0wJSxWLNcbEjUxMShPIEkSLJjdVPpZF8Orl7wP/cWNxUsTJVLvSRCFOVcr7YjRWZGicWxYcK06KlyUKJjwT0Zod33a9Mn8GezbFearFTlRhqsNkmTBSfxBeKWZHyNKm8RrAA12KrSpc3GubZj1dQa47oe6nVLwT4rMqGaU7zPfhrm+jy2t5BqSl8Sdkbe7p3c+9U4TfGeiG9MaLxkiu+TBvWrrg0st6Y3dGvf0a+EF7SDB0U+f3MPEGfnnXKVG1EHBR+tRDkA75bq9oIogDba6naEUwyUKkO7FtmOTzX9jk1qGBjQP5au3Mnxn9YRBwOKomWXKlEyRdJhOr3QQHmSOWYYcKnSy2uVCxNleP2Af6fStM3YbMSYb8saQIrUM5XKJKkMmA5WFLVW9UI9oOjhYOThM3/16u/LGiOabTL8+uCdYBkgpHcE+/eHVjnZMTi/vW2Zp9EHACpBkZ63vvs+RXLJnBWOCdHthh9qoNFsN8wAi7wb+1giULJl8QLA1NFat6M3eNut77nwfCs75cvH5yRKKAAwyJcFJ+s2YxYsZVKuSguVamalQiuKlTAmxgM+HZVCPyCPi/GDnifGJ7R4aX7l+epizSA/xF75/pv91uEZvfeMSzn/K9WGsDLx3x3K/Ww9iv4teBP5+2h9QCpJkZ67NKDX+ieydu8erPnK6GdKyCZYqQdp9kjvzg3CDr29OGc7vYuDwDJDCO9u/54/2qHUt7Kp8+GTInZ/ByQamGkFYc7OV7/VjvwiEmN/eOb5HwBJHOMJCvg5W226+GfXn82O7jl+FGAZIGRJn08jNgeNY3Yfri7yZV9gWsByRIjzTh5qu+x3214W6Y8ntf9+ad2gGSFi+He9i+Kn2/z3/Rwc6yX64HPgGSNkWoeSr5u5vXdd+Wr+Q93dhhwHZBqY6SM8S2/vroRF7DQJvLV+0jngYBkg5FGf6jv0k6WE7pmfKb50k8z+wOSLUb6+rhFjwuvuoTs84pqP2JV7HtAssNI3w6ylw9cuMYv1/LHlTW3p1gAkj1Gatp0+blZnR8Fzcs7U7Qz8MsCQKqDkZaEvuQVbu7Om7+3XaO8gb3dAKkuRnq1pnaj7Q/sI3bG9hbcd25WBEgOGMnF8ng7j9C37P3RXwvnmdXvDkiOGOmnwbLldbu9Dl5oesB6hG3wYkCqh5EevHi/YdaU+kHbjic/sd+ydCMg1cdIpa39i/+d24t7aCm7Q/y4j48AyQkjTZiVY3Hm9beAGW7XCn5dNzEJkBpgpIR6UZ9Npo0NmG6yTy5xCZ0BSA0xUkTO/kmja4azVw9LrPvSYsq/gPQTRjqd2qnz3+PTww4/WHf7ukXaREByxkgXuy4YNf/E5ZDtdTccYhVPbAtIjTBSztSSfV+Wp7C3vnWxFUhyoUQ1xqdDkWhaXacc/7l/+3c8wfN5CUhNMJL31aYlC/KOsdeN3TIpJXnMJkBqir/Xg/wBG6Z2iZiY8OwegmTHARILI+WJUrJ3r3H3X2eWe+vw9357AckFI8X2jWpYv9AhbPu8CaEuE152A6RmGOlLxttJ25ce8d3dxn320Hqdfgek5vhM8WpfePell1++Z9N2Tbot/l1L57Wg03mT5ZfMbh+rEXRsb9ish4V8UwPovBoG03mxVajzOkXvX/w1+CY3v9fzbux9V5UaOk+2u3FBLfMU/4Kbbl1mTnoxWEPnbS64uG3Sq99Cd8bZx76y6WWvofMm9g3/cGb96ICN0plBMzhpJzR03pM/D6x4GxjMmdmuzRwkiPVEQ+ftKjj+PWjPAN6sJplvzi0utNPQeX2jG51u0v8He8nJzisto7+919B50d4NU6a1eBmRGW7yfrJN6BcNnTcuUCkdvs4z8FCNa1N+q33snYbOW9ouvEnAv0PDdyiWLt3QduIODZ33JWe036ZgJHBn/UyfZ5P7/q2h8xbM8O982XlMwOoea/yfFu1qrqHz3kyoU+fStLCgpUFNd0e3b/NRQ+dZhXX9eGV5s6CCkFu9hrYouaCh8y5H/r29/bMw/43NVzex8VS4a+i8jHZr0pwjeYFz03Kdd17tc1BD5+1bUmTubC7nre9/o4n59aIBGjqvze47Z95+eBmatepth6j+TtkaOq+Gz875vxwYH7Hon54+HWf8KNHQeSf+jPz7J7u2oUvcli+32hCwVUPnfSjoF2BV4Bt6oHmHOol9em3V0Hl3h7FEB6/3CVrmcq3PjWGHVmjovIzh7E9Z51cE70h757DySdhoDZ2H/J7YLXLPG87cFm9fD8nyvqmh85CoAc8KS9aE7LzW8IBZ5p26GjqvT1efHIeoduzdg2eGuM55NUVD501vOMo5d9f50MwxfKeiP4ezNHRev9Rh3E5FaaG7zH22O76XN9fQebyLDYqX768TkFc4IaHero4/NHTee88F/l5v3wTt4q48WDKkRYqGzjP7a2Yqe0BG0Ize7EEXpEG+Gjpvy7uI9d0+tfDbY7Xj7+MTF8g1dF7zj7/+6etyPHBZrS2sqTGmDho6z6vtYV4HbreAHaeDu7KTd87R0HnJAZ59a+1awZloMzVr/P2z9TR0Hi96yuDNy0wDlsR9XO906JdegNQCIx1xeb0odnoD9rTT2bd8th05BkgtMVK669xNzZvM4xxqczB68cBHDQCpFUYaz9sz8HRKfsC+lG5LZ/dv6gRIrTFS+7usJYJPPv6Z3ZY79eivgN/lio+w/1XbpSPbhORusG/1vKhXBiC1wUgL6/wI7yoYG7b8ZbN3dxVhvQGpLUZa0377glvuM31nsaKnRRbNuQNI7TBSkzU+v55LSQrYvWbb7eVIFy4guWGkjSa9W5zhRXGnXc0dZu5tfRaQ2mOk4vn2tX5++1vY+rXLH4ZfOHIEkNzxqTdtdXFtm9ch63u728eENHMGpA4Y6d+GXdYO7Rjje2TVP7/zzrpJAckDI/3z6cmGC43eBE37WXJlbrOrYwDJEyP96nay/rmas8OOzfzg8tKi7lJA6oiR1k3t5pY36DZnZxOl/a9NSqDF7oSRnv6yb9L9C4qQLTyn4DOCXziA1BkjLeshe9j1TlrAbrHFvjlPd3YApC64Zitp1WzoycGBs+vsPBf6cX4AIHXFSIoaqU7hje1D5u94v2P4u33egNQNIz3uZOpgef9Q2OwV2cNdI4K6AlJ3XLD7NIz1D2vOzePZP3hWZ9YkQPLCBWCh4GLT/WeDZhw6vnzeirQQQOqBkRp8uTXZ08Y2JHNfkvevx0yhquyJT9g+e685R9mET0/gDP8xcSx8ZW+MZHphYxP/yZn+m5/uXfN69dq5gOSDG45fd7/z8esZuKHm1sarAle+AKSf8ekwssncU+b9/KeWrm119ewLqL564QIwMzIiclq0b1aPcaErM1ITAMkXNxzdXD7d3XA39JBb1x6TZx6AGoCNK1jZ5gv5+16yZ3bbu/EZJ30mIHEw0iWbY5JO7++zCxZEud836QLNDRfXNgevXcxoncudv3zpje8ttkKx8cNI3Uvc+3d1bBows/STT3zs0TOA5I9PPf7q758ylvjuOjXqr50mHaDGDsBISX3vdPOYwWLnhK3N3Xg+ORiQAjHSXN/P3h2FL0MWNPbKGeD0qgcgBWGkO5aIt2zLO/a8J4uyozb1rQNIwRjJKaWx3+ZmDhGTXx+IXjX9yWxACsFILkOz1ljm9gxOv9LuX2tRX+h9h2Kk/aPYt4pN2aE7217c2ScvDHrEPHwut3jhdLzxjeBFwX9lyjZ+9AGkMFzmzb7+M4zdOfSoo4lzTF43D0AKx0g9/5Z+3OZwIyhXuM1G6ejtD0gRGMk3a5qPpNmWwJzUzXevrc29CEiRGCnkx1irp39d5C2688uRUQ7OVwGpN0Y6vCb/wBCeO2+f/eHVn2XdOwFSH1zYxt7rrzx3KHTeROd5Vg//gMohCiPFPvht8O+bWLwNSZ1epSflzwKkaHyEr1ovPGRrzd7sfuPXmL1dfwGkvhip0Df4KvJxmW/W85M1h3nV3QxI/TBSm8e9l85usjd000q5f94M20+A1B8jXYk+u6+tZRpveasB2aKXw6CIxmCklTcnXGnluiwgY9mHxRu719yv5YoOQGhc0akbnsWwW50Nmvj8dJaV3ThbA7ii+IqYlit6dH3Wz/nfCkL2FHpHnzmkqEv4rlrhqSlxQjnRFzXHuqLyMjtgn1Sw+Kx4qVisWpqEPmeCWMpXiiSJLJlUJFGyJGjHCsrXJzugVEPSen+8PQIdj2rhHl1IrBUFvON4IYJxZcOjJQ3H3e4efuDS+KSwdpenWqvIWkueJDjVK6sc8EEB2tQcbVjLQWILihAkCCiSQrZZpGikFO0HOgIXD9zkjLu0tcg2Eq5jKZRCidKPr+TjQ0N3QbS+uBZHDgBJQjQYpv0h00i+Mgl/9ZpjPMaZBiuFKQhStndSS4Uw/Ay+BAi1CyYOpnTicES4fpPk2zneLLdTuzzkdYcQsLfkpspH8uGiIFEioMtei0YievqP5ItT+UohS5kkZMXjHUCR4KO/Cll8JfhRIRPGixJEQgFLxpeD71QK5e61gkQCgVCixotSWsgxCc2ItQSmjKQrqz04SKHZKRASAFanc4isRpBbgFrzlDU6+mEiiSwVXWs0x0CmgqYOF319pZQlxDCiXox7/bztn9mrg7MGWXfsu/r9RKI2QPvQejmsubzJQI7MKjoZunOQlRAhOBnesMkIzeYg200JCJmUg1DLSFwWWECLqKRFIE0BglcuavNHNy/wCfUO3Xr9xkGnnMZyolio+9UWizJSeeh97z9PXFo7N2B6zXR3737TdxsAPSBBDOhdrnGqtgo9aaoSE7BaDPDVi0R1rRo6MNHGKMdRwuU8aMG9RZ6RvnvsHv0UcH1AFFHI0H60hUzVrAUTFQ6IHji8waTIG+CwkoxDuh1wy8yIOJiUg4OTeqqzRgLlJ5UzISF4bFGLx83krQr+ufvat5df6q9PKgWRWFMmRIDcEBCpoTsi8SJ5vJhRNs71v/kjaP3xsE188V9Fjo99jQQRVk0mRNJrnMJsHbROlLbO/Vmcy1f5p9DsASW3OuRvciS8V20/0UiRQMhCFam2uTOnAbYN9hhu28AEAYpqRCpfzBILJYnKJJZCmAhzFhQ6GTfyqhr9ELXQJ1B1hbUzEDQEwPqR0sQVAwX1tUgfE2enNnECdDSUL9lreer0209rB02ZfnTT7OCi70Zs4IC4+UJ8WFRih0wD1B9FVAaOzl+uq/JaoTeEywUlRJdH14lt1VAZvtzq6YUev0zfQIIIvg4FRGhzeRBNNb/X6WRiSeh2eVxny6NLQw0AEfK9iAEiIELV7BDDh1iQIxqcwjUmHaecomRikVLNJagvk0WSZJoI5tdOpnljmgYfmvXlWf0RGQOI7AqFz2mzS9VscE0J+JH+LxM/fL9UCz/M46RSsZCvVoCIlmuDK5Za7Ph4oUKh2T2lroEKD6YLqEJMas4sv8evlX/zAXt1J7M//AUhR4mxJerQaLMGbzc4bx5g6mQwpRWz4kJ1ouXp6AlLs2i+JBEwFnN9UMkV6IDUnkbC/LzQTPbksJszFh4MeURAygLrVBurMkploIVqFlq0gGbR8oL0RKt5WcQBowuhznCRgwFSzg7eqzZgmrTKgAyd/PQC9qUIc5Nw5aflJq0Ys+j6X6XJ3Pytbb5dvNTxOoV5JvpHFgz4tqZdIAJCI5SL4lV+k27eEdm6G9BxIC+OG2CZCEk4Sb1M1Db0Jsd/9ICTGCPM6RgR5zqtea7pUd89MS0abDp3uz7hde38hPFSgJE8NV7JYsvjtV1WMxqW9OwjBK8gHKlaoYnjK4QsmZgvEbqx5HyBKBVwSiIAfxPF6tgbrt1IWHx5vG4rNORNXsZxazGM/AFdEY/lIG+sgG49T+nK7gZUC71WaxqB72aB0JGripegS1s2MMr3frA3/YXz24EBB4Z3nOsfUXSP8N41qd4VbSxPNMnhWEVFM4mDXIZArWQjiEwLqBkoUHotOzhz1DKEiooKN1WcSQnUmksm+Xc9RgccbNqrXmvF0sZE3Yn2Fgl709adGjSD687zGC4xlI6TCRfxsNJzGaKPaj7phInfnsMnjmbe98vIvtFx/Cjrf4iOiqonbUcFa68MLOZaMmFBlpHyFiBYbE2F4gr+QmXDlyjaYPBQgmKxv9jB9H0Bd9vr5coXbz4+JCp8tEttha9qrgxIIi2YINlujq9AWNBp9A7zx6U17vE9YF7fLpnI0gGLiYIfAeZPxEjgicRoK/OaNLg6cKUpAH4w8eDkgw+P1k1Jk9Nt6IaiPQfLaLpCN5aDrOwAoNsOoHuoBV0JCBHd9VLN1sHwUyqHjfLllj6r8/3Utr4Rm5xOd7wZxSetbvaDz2nLjaq5PG1MzgGpqDaeBDw2iE0pW9tRAL4Yio1e2rh2BPoxBnReCpIb1h5YL2KP78g7na49zCWpGqEiVay9uoC3G3xe/YkB8IkKgHQzLgQAm1eWdPNqxDFRO1H4Ju6+oxHiZ08GvSa8kXXvVPAuMAlOlkScWJaIXrFCCz+RAli5NLh7JVRCvZXWHg8aoH+bCL+BEnFyAhvt+LRgJxC1sLeMksqVEZoZghQSS05A01Fi1b2RGYZwkFgfwLD6XPiXyLArJQhHGulzygY/MxUsEQhH493B/2OstKJj5ct+4TzTDp+5C9ecD1gVETyQAJUpD7BOWzma0jDMhSsXwp1IPksMPs6KEypHCYUSlnKUFIvsdFOV5BxD7SFpsQ1t1cNzLWyHea4eWg7ZewB3W73Uoz38chZ4D7lS9Z6Ub9Wm4bLHJi9W+c8aPGnzd5tdDYgyGYU+Tb0PRCCWpy/JG00G8F5XQrAiKc1wPmhtp9eWoy0KlhCEPPRQPdnzc+fd7Z9wNl7px++z3SuLuCHiD56lBkqDVB5MZJfYADABqWGAqbCNnmZFJVSq5VBKlJJS0oL63N/D3XrMrcbUEdOb6zpNDG9SanFVMrKdDZdByS9fhwuhwfSQNZ0eOruUz/vm5RQ4aX0T8xfNxxAXDi1QMKL8eLpH3RyiLsKABDFlAvhVwIpL05ywbiwltogHY3HVRpL7OJ2UFTnrmXrc2st4OEVXjIFgWWwGGN+jDLe/AuqmSlBa0fUvbI3uNcx/aqL12A43rQKIjh2ql7QdO1VzeTOwwbEddnaJgb47tvgWeqSHeVR0BoI44dOmUzDEppqB+zlI/iZKRUW3IdEABQiXC1eBSK5aS2tDCdSEJCd+Pu9v/8wlQQ6720RaE1WWH/6wtsoqI5UHWOyxI++cDw0OmPI4f4Dtm27rDQBYDCNgQKKqZSNJtZAOP9MJofvzphd5cwkPAikDGJSXqnlNfTjlKv90Ydp+/4PmQZ9nuOyxrxssUQrlgBn+o2Vy4Kpq9FWjfQzRgeeh3Wo78Fh7eWwl59obgK37NzKxNWlj9bCVKmHuTS8DG8WYgxOf/d2iNDzr/qduDRf1W1R9RtGKq9JH2ymX/epx4fTCjGJthMYo9mtaIzl7hz3nwCrx657jLIKIK7vqzD+VpOmeRHHARP0oIUcwXiiHHbAS+KokHrFUksgSKRW4RcS+CKMrWPF8CXDyWYpUmUwMMwvjpIAowrOhUiXwUWhQJWipB9Ev4CNoozuLmwT1KrogPih8SFlKIlz2VUoT4dKVOnoAn4ERRIpUINQxgCAfN2KETXtBnPQBXRkO4rTLxadQ1lJY6BeAeqoy0hedD79LTe1gx5v0fMfmtEPXlxtwk+bEcPGVRrPmhRwadaLGB7e6TSqqmiyAGwwRmk2pmjI5iKxYy0Qz5Qw0I8gjKwGu+KKYYYCBj1JCZlsrcnb/fbv955kG/HosY1JsxfR5RRUFQIXFiAqQGyNS2PokdXQOTmBFy1OFbugsJnJLpNDUC64e7h6s8SxPdw9q/8p8s3DlxqWtgqdsPeK4yrXzJ+Lyabi6I+3lUw1aZbAu/RQT6zyqh3Xk3A8TvaxsY1VaKzAJkGtlieMM/tP8+xNrznU+GrIl++LRPvyXxK3TKk5vNeGqtEwQJVN+4kIto9e+UitihodewHh4lXRxbG3PzbtlWXRrxWXisr851rEWNGpCZYDDYgQHKBu9Nppaq6xUmQXXBx3B6MXZNbsc5OVvP3E/sE36bEMkkRsAIXRO0yIE5jTmt9kgNH6bP7ttux8+Jez8B002Xs173Ym41ofGFjKpGFh0bZ/NggbnLvh6hgTmvOLPCzCDp0ySS1MTk8pWyvVZbyUfwaYdrfbKpAZRV3wLC5HYywBfPheui5Hxbc1F7C9puUl4xouOGweOZcMqJ6so9u2VhtGbRgfMNk09Gbz3ZiZx9aYfLDMGvlB79UZNKc+FimrqdKG01Tm/VaUr7/TwczhZURcqvRCJhOg15VJJ52Igs5f1cqFqq6avQJgoF1L7lxdW2rayGLXAP/N0XvYf39+1JTpLfuiD2s4S1m7w2Qnef/slpvePvVTdzpJaMvVwlOCQRVIBnp5FyYgt83e4H+mx33/v8N/TD8Y+/4Moq3gH2rKqplQGM+wZmVF40SjcHwIrapbDCvdQiVQJzBc/Hp6mdPXwASEriCxS3FiePrD4msCN1dFHMUKuRH+h9lZnNLGaMTZvoN+0c56Pkub+KCbaNfgFUco0ilwKDVJlMEt2kYlZrOphFmnmwK70O4Sl2iiHzJKkyuMUDDNo7j+OU7x/fhMy+bGz5PnkJncqEipXlB2duCpF3gCqbC12BHD7/nFJPy8V0+QM3lb3gq4eR4ddDJvT52yYk8fuPtUb9gIA0i9hANyiAACqFr08UdyUoSlPlACM2mGd2jW8lf+6JXUGfLL+7Q3JlKEPUpgyVXtlAJB/kQGATT0u4o6mLULjaP5np8vpEDTI6XJy1R6Dni4nH103RNrw1VPUacN/ed/gLMu5gvPAjo4Hxpu/Ta6SZMClQbIqNQAj8ktoGLFt+g1OLLsEZ4Q9HSNYic33zpg1k7Pg5Bbeks8HxhBft49QzE+jZgQprKDzDBzYrFEiuZAlhz1hhb0ocSdnAFEMRAt3E1a5mJPzyCqK+TYOYt8RO2yXrqWAbnCQuZ445nXoMLeMWjxyfepwv4JXn4TdWBuJsaMdFrOGgX/kIr5Y9x2Kn8qi3QiZUBLIY6VgfegW0pIrfTEOS3sHgPQBXQH9xEYsTkCNDlysy1qhrQkXSSrUCm2ZXNHGqtJzcPbDJRWBKCEhVSFkxSfxJRKhmPLFb7fv8vjkvRzfw/lDL/7SKuAscb3JT9WD9noTTjC4kTPlIJ+On1IlCml7nYvArD9eLV6nGVCuUnVRv3/++eeHPlEzi8gYuNaVKubLWUmixCQx+EutFs4N+3ZpxomJYRu+flvoPP37SWIAF4V1oh3AqSmVwZ0YRu5YGAN3fvxAfugTTDf1TxEpFCLgC8YT2ISrEErmSNduybuxZVXo7toTXzaZ8vQwkTmqHinyN8oolcGc/YVMzAHapPqZA/mjT3jdjZ0CvxLlCRgOiLPlQkl8mmoDyIcllfFHwP0iT/S3sk9Qz6jeuXfljV2deXNmTvgm29EziXh8P1qjf+3j+wRqZTCvASPzzhyr7mi7bFPvIWFTz7QcDvqUcVCRJJKkSYDrBNgH2CWRwlNtnuAnsXQUSoS/ekBSCn+0qoF6aSvs5rKbz/7hzNrq8s8S+Y9EUppZElXaBtZcGZwbfYyJc67Vzjn4kADRc52kbtk6CaMizOP59w5wqeW3f/fet9dGrDUjKkJan6mMYnCO2HBVPgT0U89ouVUuqFuF+al1ERo/taHpmKgTh95HHLMo+KNV1zFuhLey5aYqlNIUFnb/CNFNhZjSnQZqzRYDSVdgmQewD3QzO1EoTREq5WksmapDhV2wJF6cKhAGS/oIJdjpAXrnlVyLlmmsWnwg0W3hzRIyqVwZIBIrywrr64x9BgcpPQmwz6HMla/JRbqfpN2toYyhAnFslFIcHp08eosaEwpOP28VOK1AvLmuQ6f5RLHEe9UWSzWlqpNdZnOQWxA5X0o9cpQDC8Hrk49aL1rDhUGPnsnpCr409srt/rD+2+AD6zhDOjYnRT//0RQmYUXWEQbAqjsjVqUnqlTn4jcgmWMhF/wQdHbur7z/w0KIeXx4I8eD88MMtW1kq2qBBwb4R+H/a2u6PcQnELyapAOdGjPScJtcIrvKwu2Vc4oYwm3WTK1iSgYOt9ds+EnxMLNu0JJZq/6wenFkiRGE27EQElrnhTW7WorREGOG7du3V0G4XbrM/9i92KYBC/94tF+obPfCKMLth1lM3FmZaQTcqZJw+8Y/q+35T15xJ1msWD5h3P1Iowi3YzMYp85MI2AOUp3hdmnGM7s1rKfcHV/OvBg5vGOGUYXbD6czzqxp1V0UzYjC7Zxgr+KbzbpwdvS1i/AoHJpczeF27FTGaTelujlXqeF21oWWf3a5Ycld87ZjbQs72+1GEW6jPgRtuA0UIeanOiL/B8Jt8iUu1Rxux+YWMYTbKxdrubSVEm4PEFh38B7iEzy58d0BLRvu2GXwcDuw+ZYWBTf282Z95gx/nTmJa4AQkgWRow0hH+boVTlUj3B732WvyeIrTwI3ijtJeW3/GmrwcJusIwyAFZAjBqxiF1Wpzq3ucLsenRoz0nCbfLdUlYXbrDtMu9vptyp7d9tqxoaSuQP6c7MjFnxvNtZklRGE2/Z3mPYKCm8bwRbdgwcPqiDc7pjjuq5779YRcxI71jzb5c+DRhFuy24zcYdlDNypknD7Zg7PeUfBiuDsl3fTHke7WBtFuH35FhNzgDapfuYg1RluWwXvbFbS34qdnd7swfab30OMKtz2YGTew5vVvUdqROH23e5r7L8fasWd6DFrZwu7xpurOdyee5OJc77VzrlKDbft2jV38WoRE5qZcWied5pio1GE26gPQRtuA0WI+an1kf8D4Tb59tNqDrdj7jHtbuffrZrdbU477uLhfdJCZi+NvXbst4avDB5uk1PBDRBCBt1j2rH9dLeydrefzb/voFRGh+y6OeNfu70/3zd4uE3WEQbACsgRA1Yxd/+/2t12olNj7O8jFX8qxwfvSmz6PVIem0mKa9VXKlGUFoVfQ1eWsrGfnA/UWB/wElIWqRcdj0iT72WuxZPGJwsF6ocYR0oRgRM/oKsgTeMgKzcXASHiUFWYMeMiKzdorQ7iNVep63WiJ6agfi8bEVpVFUTjaOlVncD53qHhvBHbRdyVA13D05BOnRnBMa77huB6K0SUumwjmJqsTXqtGjaO4qfIxNALAagpRMo0PDoLpK1Vu//n17+Xdqntt6Cu/HvDF9m/MqJn7qfqlmKNAyMY3D8BED3MZ4IICJ0ReIyojOtREs42Kp4vRuvn05cRbuk4LaHZuTmhG0NmBvUvamnPLNhohxSOPNpcnmCTb3c3hGCvZxTsdcbANRGitgoNEBqrkPr5cKedK6NDl3yLGTyzZ94MosPoJ0oUKVlR8XJ4WE6Pm3Sbh6emoOfpFNijqBpUiNCy+UznG8mcYhQK0vB0OvVFN2Et8F5gI27Da6FfoD66BivJ1QLOcYJodNlXmMFbC9RFoa1R4UtN0PgIVosdhywB/0ZExTldZW7ucYS1DMjcL1xtmRvcb/bxobWW4RuHDemYzW19voPX5N94KwNWvVV6NSReVWHTR5jCl7FUZ0UVut+R21r1HMZV1Z2BfJZEOAo2oUKgOjSsk7XLGM7+lHV+RfCOtHcOK5+EjWYYoRa7iWQ9CsulJ9EWlvsOqAl6FZazRbkNQxQ5HA71xYgH5CmBA88Hbhz/cM3MnJMPDFjRH4ka8KywZE3IzmsND5hl3qlrgKpysRCe1ZSqbiEHKUzUKxSxUY2H6SC5VbMukjOBssCdH0PvCtgdLIhnnFXPa59xxtrLwyfy0LUX9ucv8NaOXBHZ+/NRBwPgw0pkwgeIT3WYAgu0Ss9IFRDeCPmPfpXmbKL58kShkolpH4f03nagj2Pogf7+Q2bPeUcspllL9bw207D2yigd91DIxBVfoXFyRa9lOTtU4cmEAkz5UjImtPebkHMf7vCyxaF9t7VdRDz9UysMfV6bMVi7wRljzVWpE7gep31LdFMuIkvUrzCHsxoDWAs1XiwqD48v40ysw8+e4s369iHRv8fVt8QIgKvqQDsCwAmVgQhQEQyIzBXiK5Q/ITR2ffv80PeDevYInvb+m9Li5B1imXTsG3W/hcdbXdydaMBZo5JE8UksoSRemiLjKxTwphCWGMwg6Odj5l+3gB/5PbFb5J43nLkt3r4ekuV9k2q82jKpatejpLtvPFbSXfuaHtAaG1fRSmiNMFcDGnuRapUWFuhVjYTyxcUv9lq59I2OWKEctT2i7cgjROGjc2zUhKo2/jHAuEEMPThU1/nkoBjqpbG88bhAVfaFUIZYLB0lVKjuCIB74fDnMp+SNSac+npvsj2v3qoz7zHAGlACBnP/4vDJ7Ew3mY2m0AZZmgxUaOM/vMGHFvNtHEQ2jKnQxpuhOOaNjB5zcr16A2FuY/pl+d7wQPbijysmOI1K+90QmOczYe6Rj2PemA7z8H0BF88iRdz0gQ17il6E1CGG9mFwv1EmFsWjVSa1jRcd0s5hwAcDLoESPClmpRB60ck2TW84yjl31/nQzDF8p6I/h7OYhqW9g0ak6xzbc5DReQDOLMqdshMc5MzyUzbqqqy4t4rbcCv0AjkCL+E3maPNwQJcBgYIzsw2OWbpd/AvpzCbdg6XcboJDd1adfWaloxYqNrpO1aNBx0u/AhTsNw4QCQHel4E3GR0hYjIL0r+uJtPEY7fuzAgd369P9qMHEK8TN6ErT072Fqzw4Q0Oxq/Pn5vcav5wcuSk5K3jdi4uqKzI5uDJEF2erCpoo8VHKRB3ikNkMoLmZtEwataBXqhlLLUdez8355HbJj1Z8brYxJicSoTjjZKnHJRKor3ThhfMNN3xfxtiuxBRfkGQAmINQNKo5dXaYyGD9QiOk0m1MSmWaAceLtJUuD/y91DhXKJUOwOP6NwDwwapnLNKFNjlL2wKaSeCkyuUQNVjgX0pXXgL1mhV++th3cwgYe3HmpfUfUZZTRmDpogNOYgd//DAdOffAo+uH/PwR3Jj3ikIud8gLr2fYd0U8aVzZLBJzSyK1gSqVKoujFDKRyN3ShJ7aXzLjYoXr6/TkBe4YSEers6/qAYiha2CBWq6JJyH8hFomS86UWaW+wdSa2sGjTiTR6Wsj7muoB2g8Kir0IojwbDx7+2pZ80NU4shIFvfDJ6m4VApMTeHSgNOHEep68n8VG9vK11dx8bedMc8NELxKTTuVZhfHmiSMITJhCEwlrV3Afmqmq2W6rao6UyzVaiMPhFJbPznjc/ZYeCGCmXymCpZ9WozPFRqRJkYRO+720N95iDJQJYFFqtAyxhI5zNGk2o+RVj2+kqGw8zYEV8MRdecKJmTa0oJYhxU9S/m/aX82Vlik8lqk3pRNVovMX3ngv8vd6+CdrFXXmwZEiLFAN5i2T5N4C3iLgyeYvprXH1wDJ6zMlX5hoIc/KN2QbAPN2GCXPEBsfchQ5zz7V9Tg0q2BiQv9bu3InxH4jXPZkFyqWpMiLmtXHMOVLNa1xN6GY1ha/DZiXCfqEZ1DC7GEMUNYL9cMD6pQ7jdipKC91l7rPd8b28OSDhnixZfgGpBkYizxhAqolQ34UMSKYY6UfP1nffXndib677bFqNJxccLYL9hhE4AzUqde2ldxHru31q4bfHasffxycukFNAqG1KSDxGcB6r2NWMjl1GZEG92h7mdeB2C9hxOrgrO3nnHINbUK35U9Tz3pDF/PWc7bLkh33/utS+mizoQ1/ENwZWWq0sC5q1/qkv0j3mv8OCNqcTVaPR5skBnn1r7VrBmWgzNWv8/bP1DKTNyfJvCG0+hFGbD8G1eQujx5wXPWXw5mWmAUviPq53OvRLL+NdV4xkM2F+2RfHvCUd5l/iBp3uZLUhbN2Rmt+QpG8LqIrC674x0yRMyFfALEJ0uVx13xewk9gtg7ptvRxxeb0odnoD9rTT2bd8th05pk+Zel2RUwJp/bkIvQ6TYuvlKmjtqZVJyXibrvquvhQVAJRvdnLaQv+YUXsjMjr9EZhcICA5w0aVGDkWQAABesOm2iZYhgKk39Wd5V5P0MWk4dtZXJnf3g++SdtLZlXz9QQvMAAsKPdJanEhANjcakU3t4x0/Tjdde6m5k3mcQ61ORi9eOCjBlW0fpw0j2n9eP/c/60fY/zZltwif/7Iif75g/wOvdiX2scA68cL6/wI7yoYG7b8ZbN3dxVhvQ2wMhozj2ll1GIe1foxHUj/yfpxpvNvEV4/7/TfvH5SvZTBigYGWD8mJ6IYACUg1gwoJc09VXkLsOQ9g2pfgEUlhnYBFiCF6dPWdPrUaPzD8bw9A0+n5AfsS+m2dHb/pk66+IcUwWPlu4e3rjG5hznXcMhdjR7y5P5XbZeObBOSu8G+1fOiXhmGgTwpJS2oz/093K3H3GpMHTG9uQEgL3RjgtzXDYe8jdFDTjYahoGc7OYZAHKPOYzJFbNxyNvSQV4v4UBB7qmz/su2PP7lXKOxK4lJT/6jZWKpgOKuTjMahFthT+BxjyrjXJHCR88ZYNfX65iItqDPi7ED3ieGZ3R46f7leeoiyqFp52NhBF1BBOBFPjul8mu13bMHHGTlU71SzMviIaFqIJTv9rtjgFPE7isBe6cP+Pilm/9SA8ZDhj7v6gqmLgRIQJmuOwtI2VO97t3s0kcIRAMt4yEQwmxFqUIE6SwwPpGYBSRFLScsPpisfHj6Op4SxUu13tawWx0akDtz6imHrolECbFUf4/2ZYNlJINbe1dUYhjginxqFDdDal+MjUu1jgmW7bGJJihjlzKJr2Sl8JOFrFQZug4Sx4dljWhvJcyvOaxl3mZF6BL7DYmZmVvsSYVzsG4pCufgFINz7yMm7H5U3Et34EJh10qB1hM4F/wKXfyEpJAMJCVYS90Ox0+Z1Sc095k8psm2LOJuxX90Ya8BwEJFnRYsIOqY/WmH0Niffk1rJGfvsOccWCV+3XOcBfFogp0/3MaA6c50q3F0dcYOmKgfxS0REE3wIwAD5rYm8FX3mYulkkQQeymw1Rl37IswuoIVz4d5sCxFqgxEHIBDcVJABM+rukyVwEfhnotEKgc2Di0SgTa6s7hJ8CJzlL+Dwodo3BIOLINSmgjP2mkm2CpHSVkpcBFfN9v4I/bO9d/utwjN7r1jWM75X60YYdM+hU36gB7HsUqf0x7HegGopXrZyjplthIbEOXLDu/obxdwY1nQVp7zqJvbiuoY0FiSNZABThzdggjNptT+mRxkxnO9jGUzgjxi+30QMwwwugjYR/n1Y/K4q2E7rkccjPH2ia7eFUWASndGVIDcGGnRpPJOX3UOTmBFy2FlKziLidwSKTT1AloIazwsgEV9c3K/+Vm/TN/fl3cgv/vXNR8vXyOwzCpc3ZEW2zRplcG6nFIm1gVVD+vKd2eYlpMaR6KXuQKTgJf5EyVA9c6wRp969opnrbx3wRPvSQ7EFc4gbYyh/WkrIVWzwZliwlVpmSBKpvzEhVpGr4NaraKhsQKIjBSq7KIewDT8UfOye9tf/Tdmj0eyM1+SIkisY+0wDSdUBjjdGcEBykav25Vbq6xUmQXXB52QObsKTtqlBM+q8SBrdCf7hcQQRb3srx2ilJEqAyF0TtMiBOY05re5ITR+29mlfN43L6fASeubmL9oPuYo0RvlAR+NFeXH033hgKM+1wbzG3BPGESICeBX4HelsQC2cqXqFmagbDF5hb4X5rqN08lxko/57lbqYe1X8GvBn87bQ+tRj1vbi8Yp+pxwa1SsOuGm7Sp95SCFzsV6LSugA9DAgLpYz05vrx4OfkGbFvzVl39k2kVSmQ74NEWZDrS5PE/JXNIzDbEP523yzO02ZmLGSAMcX+sOAZJRCuF+DmLfqFifs+sNUIBwuXAViOSqC6Spje3NTcueZNlMDEh34A/c/+bxbuK09MMf1p6WZaTyAPP0eN824o+lIXnLTLaafD+XYADASp2ZAAMSVS1OlMpmwM90Quj+aB9pZ6pQY43ykkGryqccVLaKexs4s56k/i+TT1rVRY9uA2b4j5bJheoqXqhTy+ZEuca0qZgDTGJtyvaZx0afcg6YYpu81Kq5cqIBWJvDyFpZNbGWyj+eq985+No8DX1OyUxHS3O31rmt/BY2nL6tb+vDxDs5THlUNUJVrQY3jFZclU7azoa8IPMBRL1gimGGsT1CYxg5JU73R3bb5bt10NAGmf2OEBM9HeHWgRIufcLC3EJYKk6ox+HvDlxpCoBctYGBdiMo6wYNDsvOfAuAkOhkER+79OAXumfyNq/e7PlKaOda/oC12EH5KV1B9+MgK98Db6SUMiGpkIN4vK/oWXA2TwMUuNwAEzOhtyGVsFzxc8wAPdSwoj+pdJoCrkZLRwkF1EakJHWm4w0Pfti+xT1bH8j1bEvUMWhJGIqT8lh7eTomO6Bt29Con4MWPovwPDfYq1NFdQyPg8yFMJtSZvVMR2Gu6JJwSw32q1e34qUShTA+FRUPmOVAvbo56r4r8i2kHSfvSFTw4PTF3gQsrcv61Q5/CUSDq4RbGGyDqWBLN+dC2DCV4E6nEs7ZNn/n2VUaNu3v16Hu1yb4k+smycT8eCErPFUsptAFdA5ze/w5CXwOyqxIMpIvFglUQj5KBPMPQZgi110T7DjNHvnFuUHQsacP53S3d3nAME6q+k4aZF3RdeQgD/8+hdbZoNh8MwXo/l3RuV8fGjW0CoQSVi2AShIiRp1Yc/HkpS1XQwIWZp1YO+D9s2Ci+4x2pO0+q5rLm86TPh5GbI+aRmw/3N3kyr7AtRWdzo04yOW/aYvorOAg6X/Tln7SETlnNXJygqhB0aLOrit+ND0N4QXsOm3epqRX5hdi1XZMQKi3dIhUg89igJYHI1oP3xrHcdbmTMdZoZObSDjPiuNQUcVdHzWQkLGgCxBUp6lYTcllsmGqyCSpKF/tuapZ8IYyzawpF84CvRbCGqiODENfAbVVuOgLqOubhIW2urZlbsi21ImrbiR8IhWEQN+KYmMCba4MKDwYoQAijhmqDoix59+QtaVh8m/IuWsGyL8pfcOUf5P/Bofcw+ghn3HyVN9jv9vwtkx5PK/780/tDAP5mK+twj3vjQ073N/kcOQmp1IDQJ5lUcwAudgCj9A86SDX++SkHQ55FZycJEdjGicnye6ZxsnJd9cf71/tUMpb+fTZkCkxm59rnJxccbiT4/VvtQOPmNTYP75JzheNk5OyAl7eZrse/un1Z7ODW44fBUhmCLW7Aki1MBJZUADJHCPlNJZ4PJicFDS9wZb2Jk9KHmgdxYTCSyl9kr3tXxQ/3+a/6eHmWC/XA58NcBSzIx3/m4UWtb+/wypgg6kg7sZzeyL/HVSL/VyxVAHdRXQDR/dyq80CRPAAZhI8sajqAA0pYZyp10GgmoeSr5t5ffdd+Wr+w50dBlwvd4ha4FB9SNdJFg0015+n0NiHYu36BKC+1Gub31m124ZeDCFFD5JLYVYgfV5Q2xmXih+JJBHbl9jUtvzJYUJF9tpICom8jVdRhQTiwpw/MbOrXSEwi4Ow/qT0w+mwqqdOidDEirp4pKCH3ZuOrYMXLO4/1CvB7J4Rn6kajMoMA0oeL/WrVecWic8rdLKhmOFTDoZ6eO4Z/VZJyiiLNw1ZByL2DpvbP6FfI6fq3M+9gwkR9YZcLS4S9Kd+bmxb9e4hhEgFD1YnElgggm6irmAzPKb+v4p/g1c7Km9euBqcYgy7lgCkTy+ZQMp/qd++bks/kerN1UtVZSKjKlhKq6A2nWTd+LLUOeyg3cJ6XuMWtSDuIuL9au8iqimVcsiEER2Ll7gvCndpKA3jy37hPNMOn7kL15wPWBURPFB7IV7bEtLdPOJC3M9Vp7qNkmKrrLoZwozxLb++uhEXsNAm8tX7SGeKIVHvDegKWyxQ0K8BbOcpD+e95yCyv/TL/tZpm3ajufjqTymzOPmblrU492D4JOJiJ7ofS2PWCcRyt6lIKq6iWjyJg9hDsKhvVsjnIIV/6WXrbFGwhGCm0UOVWzN0/W6vvgGL5n+o8y76uISoifzBs9RAaZCq2iVIQqWGASbWX/oZu/K30Mh7zdW3hQY0DSojcAtN+7BbHS6EBtNDnen0kPHfhDD6Q32XdrKc0DXjM82XfprZv/JvQgCeE8u6GM3OofDJa3CRlVZ65ZPochPC6w+PrJv9fNF356f8unZ+dRoZ8CaEbwfZywcuXOOXa/njyprbUywqOucQDtIAwrOFcs4t4iBvrPTKJtHhJoTG0q4suRk/ZKLD7b494u5sMehNCDeat/7IY3dmb2vcuejAc/k9A+BzxooJHyA+Rllz38A3IbRqP3PMj8z1fnMOmpi6OExtWb03IQCujGbkSqRRceXNMZwrhr8JIfrQ8fsc80fsLAsvYUp310fVexOCLVelTqjr/jfjIvesiiv3JoSuPtzi/N4T/eesmzZPsbUh6fBj1d+EYItaGAZEBFb4wmsXhMau/7fdhPD1cYseF151CdnnFdV+xKrY95V0E8I9y2KGmxDWWmrZ9Uq/CeH8YN8r0rB+/oc6bdooOH72HwPfhGBo4x/DQUoghrQ3IQAMq/kmBLI9r/abEFDAaG9CAIBhk7kr3WQ2mo0rsjQZqGIZeZvDADtXLEumnStEjXk3OsyNtKpS06bLz83q/ChoXt6Zop2BXxYwDcuAVZWyHIoZqip1dij+X1UlFX8upxV1v3PwcuBUn462tcQezwxQVenG0jOzH7q0iFj2tca9gli7Cq+ZZHOQKZCdtPWCBjsUV3JVpQXiVVfXXFgfvm3kFve2nRP8DFBVKdI836+zQwx79Wvb75FXP70wAEqdGVGq7VBceVWVyFnv1V5VCZUY2qpKAClMn3b/L9OnS0Jf8go3d+fN39uuUd7A3m5VpE+zazPpU+/a/9OnGH8e/ej48dK9jIANiz3Tdzw6uNEA+vTVmtqNtj+wj9gZ21tw37lZkQE0RVZtJk0hqF3Z+rTfiDnBIzmpfhldmtRY3aP9GAPoU/IigQFQ8mZEybF2JepTsg2tdn2KSgytPgVIYfrUi06fGk1MQJ5ORlu/a5k1U0gw1hqHvAcd5Hons9XBIa+CZDbyNolGMht5bUUjmY0c0Gkks5EjDY1kNrLR1EhmI0uDRjLb9C6XWTMOPObOD7shjGavK9VIZjuZO8lhzy/CwMlmT2/1OjLuX0CywEizLP6O/K1eYPjeU153C3IzGwGSJUZaeMil7uXdoohZd2KW/mQ385lWChy6oUclsy6Wx9t5hL5l74/+WjjPrH53A6TA9TSY1FhXodSQ675pSA257I2G1JBT5jSkhpxEoMUTUzqe/DRYtrxut9fBC00PWI+wDV5sAJ540/HEiG6IKG3tX/zv3F7cQ0vZHeLHfXxEMRQD37G02iVlmuBOBnuh75P07qvStlXfHUvvTYsr+Y6l4remxf8VN0T40Imq0dj5CbNyLM68/hYww+1awa/rJiYZaO2PLP8GMPQPzZgMfaEZbuh/NnrME+pFfTaZNjZgusk+ucQldIbxrrfGfGM6nNHgG56I0osOc73NpA1SdWbywYv3G2ZNqR+07XjyE/stSzdqmEmy/GqYSfKM0TCTZMZqOFfpe9x+O9P8nP+m4sUXe7o3c9RwrnZt5GQUhD/gbUv6p83S9Z0ztYwr1PqUghSRs3/S6Jrh7NXDEuu+tJjyrwGMqy8dJy2jFo9cnzrcr+DVJ2E31sa/ifXysJ3EMPCPHKhK3csM/oTvQUpYETKhJJDHSsH60G2H8XRqp85/j08PO/xg3e3rFmkTGYelXcaP9AFdpwYI8fa3gts/XAS5rBXqmXCR0pZae45MeReNVaKNl7OENQlSYd3PJL4EGDnKF1eIhkUN7CbgZI3wG5qibPGYuMPop+pBe4cRJxg8+jXlINshJPl0mRgzWlVLJoZZPIBWrTTevHnzQ5/qgSwiY2DBqlQxX45uXIqh+0LJm5yT23JG5fUMO5ZT798uf2/eRarKinVCUZUVp1QGd2IZudPdGLgDtNEPfdKVmvqniBRoHeR4AptwFULJnN19ZfveDMqMmHjSw8/55OaxROaoeqRYFS6jVAZz7BmZA7RJ9TMH8keTObhlomNON3YK/EqUJ2A4CvCoUBKfpqri6MOSyvgjYNFHT/S3sk9Qz6i359YO2DX6K2ddt79aP9zVhVhYoXa0Rv/aB+MJ1MpgXmFLJublVA/zdKjMaVoOB33KOKhIEknSJMAJBuwD7JJIJZB14CexdBRKhL96QFIKf7SqgZKPooVNe/Re93t45sl7K6T9Ai6TyqslUeVZY82VwTkZI+eCqp1z8CG4RaNX7k1d1QK3SJLIrAjd78YfXSZyD56RNKbF87PtPhAVIa3PVEYxOEdsuCofAkYcZ7TcKhfUrcL8VDZC46c2NB0TdeLQ+4hjFgV/tOo6hrT1x1Ut5ETKhSNFwlFENxViSpcq15oNyxgpNBaD0Iq0iUJpilApT2PJVB0q7IJV6WHBkj5CCRa/0DuvF7suGDX/xOWQ7XU3HGIVT2zLNFbtbUoi3bYf+EcmlSsDRGKl6oup3H1a7DM4SEnrYjTZi2L7siYXGduaNo2OMhoOxLFBT2KiY9TJo3fbVGf5vvRGEVOuX8mY8GIm8SCzBd6rtliqKeXFyWGpzS1XbRH57elcc1X3nj1uVTROns1BzkPkfCn1yFEOsra1Xpnz9aI1XBiWdKRQLhfRXILhZB06tLbLTf91tc3OTD65zaHiU5iEFVlHGACrsYxYRbeuUp2Lr2OaYyEX/BB0du6vvP/DQoh5fHgjx4Pzwwy1bWSraoEHBvhH4f9ra7o9xCfU4TaHTo39r6r/f1TVP2dqyb4vy1PYW9+62AokuV8YYTNkVf/ObYoZqvrvdtXraJGOVf0PcnOGT7p/IuRgzYg2K5DGTwx4fN3QOtKCg7hBhGiLoJu20dKRlVHVv3GdnXsP3V3KnTzcaUfGgZTQaq/qf8+VCRUgN0YTO+h3kshwVf0nJvVyWDOrTtBmj+Xs5yFbhhhNVf8sRtYJqod1VV7V3+zp5I1njjr6LXlzrtGl46+8STudVV3VH9UytGXZgZapsqr+04ae+XqvUXrgVs5Br2WzZhKzEaqnqj+qbGjBAcqm6qr6H7nuceLopmJOvtmysM0frt82hvoYAKEsRoTAnMb8Ni5C47f5s9u2++FTws5/0GTj1bzXxNp+1uipQJlUDCy6ts9mQYNzl7ItElHZ81hxDYC4XJqamAR8OIUQXarRpzjEgiLRtLpOOf5z//bveILn85J2tNplFDSIuuJbWIgI3AG+fC5cdCHj25qLHG5f0ZNajmXDAq0YFpSvbt627YZH46OCFyqCJ68r7lBa8cvASC5UUOZd2YiJc4Lm9vjRe4hXi1UVdaHSC5HBEL2mXCrpXAxcUHe9XCjsUnWBMFEupPYvbaZZL8iNeR8y5eKN2tYHS5qSjlyhD1IcuVK1G3x2gvevzfj+T9pXt7Oklkw9HCU4ZJFUIIpnKJYTPTbOuv3XvaETG0zMftTVy4woq3gH2rKqplQGM8BkZWBGdvUwg+z+IPrsWLiHSqRKYL748XDt1NXDB4SsILJIcWN5+sQnSeUCN1ZHH8UIuRL9hdpbvdLtme32rEec2WdlV9LZQZOJdg1+QZQyTUxxoWYZqTKYJWZklp9RzBzYlV7ear2yhW5JqjxOwTCD2p3tup/Vz4M7r2jRgRFTbv5TkVC5ouzoxFUpcnh29LIWOwK4m1u56+elYpqcwdsKi6nLq9VsdsSOwb/t+VVWsrN6w14AwPv2GAC3KACAqkUvTxQ3ZfRVK9K+mgbGfnTnbbzU81/n+r2yqvf0MABgBhMA/Xq3xx1NP+S/Kx/H+2rTkgV5x9jrxm6ZlJI8ZlOV5eMc9mDKx/mzQ2Xn44x6Wqfepbhtvrs//j1v2ai5oUaQj7Pbg2l3M8vDCJIKbty4UQX5OBPWvmLb3NoatuJxmKDTj+QeRpGPI2DkjrcxcKdK8nFuFZm0PmOl4GWP/9Gyf+snh4wiH8eRkTlAm1Q/c5DqzMfZYd7NZP7vsexdzg3Yvzv3am5U+ThFHZiYt6x6mGec+TjSuTv7vUvoGbF/VmTC0FuDnKs5H0fJyDletXOuUvNxFqeE5XKfewbPEY2/yvE4W2oU+TioD0GbjwMUIean+iP/B/JxJjzIH7BhapeIiQnP7iFIdlw15+MUeTLl44g9qyYfJ6Fx2AKl0yDfKW9zbnLmxc01eD4OOTY3QI7JYU+mHJNsz8rKx+FNyOGNtEv1PbAkLKxls9o1DZ6PQ9YRBsBKzIiVn+f/V/k4AXRqbMQxUTtR+CbuvqMR4mdPBr0m7pT0ToVnJwPlfFmS9glTPbYvWviJFDJ4eky9m5PWXnXKlMWHRfgS4TdQSl6eKCV79xp3/3VmubcOf++3l3Z82js5mkQt+bOMAiosQvMoFoVUks896SiV6t4o8mlawDtq6nPhX6JUXilBOMUuFsU2UUIxYJhQEAz0+mi8O5StKlYG0rFS7zNpbdWyXfln0uyy0npM6VKHc7TIbl/38BqZGmfSst69a5R++3bglKSngxo3N4/QOJM2x/Mtn7MpMHyz+7+t7U1dFmucSTsXczD0jtsizp7LCbNcL3TI1DiTNsc+rM3iwLkBq1vcHpbb8cgPjTNpF4fE3vNv8TFi0+fxM+v63emgceC/R/jV04taFQXN7d9bvrjx9AKNA/9zHvGLo+/I/AvE9XscjNroqXHgf0njR84J0705m9Kk95evdN2oceC/46U13zckhPpvcMwctMryzjRAssJIxxTXHqRalYTNzLs83vO0w05AssZI871S/1gw5rfgefz53R1aKQIAqTZGqlu3WcvOJqyQgqnPrgUnDJ0JSDYYaZpVdHKvUEHgpgdFPyn8vK4Aki1GGjaMteGPqE4B82avHP9i5KX5gGSHkbzOhx6eHhoZPqOdzGnImOMjAMkeI7XZmpBwu9OFkIIatUJWxHwPA6Q6GMn91MMjLTxP+mb9Eh13bdnSC4BUFyNdbtx2xt7kewGTf/7009Usq7GA5ICRgg4GjV7yJjGo4FFq45wadw4AkiNGkjXtaBN+ZTc759ibq4MH1E8EpHoY6Y+oYz/uXrNkH2oi8vwccnQoINXHSPEXbli2WZ3rf6TpqzZT//KaDEhO+OCvPUkInvaNl/FzN8RvyKl+gNQAF7YYx4yjS8zZ+3ZcfFrcO+EPQGqIkTr3jbBOPuIbvmvC99XLJ+byAeknjGQTv8bx/Pi4wKOTtp2bb9pmKiA5Y6QXnd58jn35MHzVxAf7TkfO7g5IjTASR9r5U97LJL+Jc5vvfv15ZxwgNca5fEf4+cqcQk6e+fiX4wvPZABSE4zkedW2/ujXByPWFLcf91PtZ38BUlOMtKWj08uT1804c5t1ljh9OAffi4WRSrlFjqWnFnG29Bj+tEa9I3JAcsFIg2Y0Kd3j/Slod+6HwV+O7AwBpGYYKXvN9Z1Re3N46e36ZrHfDl+ldUQT6i3qSlR1uzQubfCMO93X8afXAy8MNcARzSA6xVYv4UBB7qmz/su2PP7lXKOxK4lLkP6jZWKpgCLvgO5+1FbYE+pMUbTiuyKFLxYD1YUV09cx0YCs1iiHpr06ihF09WZAnHKrazHUylQ+8wMOkt5VrzxM+7I8TNVAKN+to1ntvW7OpbzMd+fjrXqP+G7ANExDu8auHOQyBEhA6e7N4iD5XfXKIejSB7hZcnTFTyCE1YKlChGaeAHGJxLDu5/VcsICfheLDwO1eEoU/4hvdPHnAYu5k11s2tzymtCMuHGq/h7tjdMyksHjX1dUYhjgiulqFLvc2kl+et5e2h6baIIydimT+EoQ9SQLWcBtUd8GRb/D+v1JE+n+G+tCsz/888il16nRpDV2rFuKNXacYnDufcSE3Y+Ke+kOXCjsWvusegLngqcD4UvdQjKQlGD1qbdn74fcq5ysxoW/rBrzKaniyUcGACudESwg6pj9CUb+d2bBkGcWyH59lZ1ZaNGd6czC2m6VcWbhtymj14++PiNor1mrJk1bNhhvQGNJ1kAGOLPQqDtTivf7blVyZmHVHFHbFWtE4XumecY8rtdxRbWfWTjfjQkVIDdGur9SdWcWpt4pcNv3JC1kzpps2xUXopYbzZmFsYysi64e1lX5mYVn9Yslize34mYEnzBbuObElWo+s4BqGdqkc6BlquzMwunJuZvDvlr4LbjzvoXHs5hWRnBmAVU2tOCs7VaFZxaG91vfpn/aF07e6FoPavf8k1g5pPrOLIxlRAjMacxvC0Fo/LazS/m8b15OgZPWNzF/0XzMUaI3il6dF+XH033hgEO8uRLzhEGEmAB+BX5Xmub1jkDZYvIKfS/MdRunk+NEXvWkHre2F41T9LhhptEw7IYZbVfpKwdZNlS/ZQWdrriUTp3eytlHylm3//ema1kbWpO25uHTFFvzaHN5npLjsaIBc9uuC9p8OG9B71PXJxrg+hhHCJCMUgj3c5A/h+q149YABQiXC1eBSA7EF9Cpje25gZsnWo119587qCjuXsvjxFLFln74w9rTsoxUHmB/9Zt96sCAuQETrzUV32gdWuFj8ACwoqFMgAGJqhYnSmUz4Gc6IXR/tA+CWjDw0hrlJYNW5WTu+HNul9H+h1wSj2/cnfBPXfQID2CG/2iZXKje8EOdWjYnyjWmTcUcYBJr5XZzZj1tODNsdqenQ6723n7IAKxVMrKWV02spfKP5+p3D13516gGetjcNHvqxplhZxb0qWP/9Oq7RtWKq9JJ8BpVmZbSBlEvmGKYYQxFaAwjp8Tp/shuu3y3DhraILPfEWJBYUdYqFMJlz5hDq8Q7ioL9bh8rQNXmgIgV5ULRbsRlHWDBodld64JgJDoZBHJm33lD1iLHZSf0hV0Pw6S7gNAL+VQ3cVWyEGCfCp6wo/N0wAFLjfAAsDQ25BKWK74PWIAPdXRP/iTSqcp4Gq0dJSQ5tzOtQBX504xCwNmNy3IEO8JsyPqGPRKVoqb6rD2crM2bPs5dbHw5u7o4fZtrbxzx4rqGB4HGQ1hNuVQ3T42HYW5okvCLTXYr17dipdKFML4VFQ84E0W1KubNTeljO4z9GRgwXVu33n8C/HEXISyfrXDXwLR4CrhFgbbYCrY0s25EDZMJfDoVMI52+bvPLtKw6b9/TrU/doEf/K9xTIxP17ICk8Viyl0AZ3D3B5/TgKfgzIrkozki0UClZCPEimTWFIQpsh11wTkvX2GcVLdr6xB1hVdRw6y0huga025+WYK0PWu6NyvD40aegujEt4aCJUkRIwSgJ0n1o5MLL0WPv/VL4FnHtcqJLrPaEfa7rOqubzpTM5lqOh0bsRBciByqyldhhUcROZN6z7riJyzGjk5QdSgaFHCtzBgVerDCxeDDzu680Ydf/WCmOCNCQj1lg6RavBZDNAKYkSL5V2lDhY+UIvoNJlQE4fmGpk+7qHApRWK3eFnFO6BQcOgk5solJNyi+Gfiiru+qiBhIwFXYCgOk3FauqUY5JhqsgkqShf7bmqWfCGTcXXplw4C/RaCGuguk0V+gqorcJFX0AJxSS/jlb3rAK4+w/vlicuHmdK2piAb0WxMYE2VwYUQYxQABHHDFUYQmOojKbaPVlbGuYmoUoodr+2J9MFA1N64pCHGz3k5Iw6w0De4FD71iU/EkJX3Jrp2PHz+ScGgDyazQR5ZzYOeQQd5HrnctrhkFdBLidF6iWey0mReonnclKkXuK5nBSpl+pcTu3USzyXkyL1Es/lpEi9xHM5hwY1e1Hv0FPf9QIev7/j7OlaKW9QeCmlj5y0aYCUt0g6/jcLLWp/f4dVwAZTQdyN5/ZE/juoFvu5YqkCuovoBo62U16LZrY1CxDBi36S4M04qg7QkBLGmVgagm7b++RE1XKHqAUO1Yd0nWTRQHN5FaOxD8Xa9QkOYuql19q1s2q3DT1DIoWsAXiAX+jzgn7jTLjqkj3Td/oifuzpE+fXV2SvjaSQyNt4FVVIIC4c64WZ3TdaCimLg/h6UfrhdFjVU6dEaGJFidJty4Kpv91r5j+VN+aPlLc7EAOmRUzsG/7hzPrRARulM4NmcNJOGAAlU0aUznTX7654t0h8XqGTDcUMn3Iw1MNzz+i3SqZ9PdiTL/zNf6lLymn7POXt6tzPvYMJEfWGXC0uEu2lnxvbVr17CCGK16h0AS0QQTdRJ1ayX5y6tGxL0FT+8at2497MM4ZdSwCSGyNIpl767eu29BOp3ly9VFUmMujGIr2Csv5++sj1kZeClywO/P0aaw2xTp8F3q/2LqKaUhno3KNPCQDo7O6OO0a9ERrD+LJfOM+0w2fuwjXnA1ZFBA/UXojXtoSmNOC6EPdz1aluo6R6FZsjH8vQdW9AV9hiOUhhDwDbecoTk+85SFKPStimTevY36FW2i7OoSzT3dfazjlBXOxE92NpzDqBWJ4WJ6u4imrxJA6yH4IVSSlj+Rxkbg+9bJ0tCpYQzDR6qL41PFeS7bTdd9FTh7ClvcTE++Et/cGz1EBpkKraJUhCpYYBJt8e+hm78rfQyHvN1beFBjQNKiNwC037QuM6XAgNpof60OkhbuvzHbwm/8ZbGbDqrdKrYWPyOnQKX8ZSrdNQrJfTueatVc/huz3ouRQ+SyIcBZuEclE8ZiB1UkvkI2EMI6RaKdcg64or8JxiwovR7BwKn7wGF7kVppeiskW3oVSLu2A4lG/5S7uC01eLtwavXNf63OIN3TyILhLagbaLpGoub86RT8dVdM4hHCQSwrOFrg6Ea7he2SQ2qvEwlQcbt3TajivnFrIPpfsXX4ypOYC4+6d6Xnv3D2svD5+S/LPjhYtnBhxp/LzrjCcSsQHwQRjxAeJTHRkGFmjixkgVEN4I+Y9+9cNtovnyRKGSiWldljfM7dV7Tdg+pzqrR/kfIqWFqJ7XZhrWbnBlCbiyPYyJKzOMiitvjuFc0ct82aEKTyYUYMqXkjFtL/rc3fN5WdCsBpF5zlNClhEZE4Y+r80YrN3gjLHlqtQJXGbUjlebcRHHcP0CMmc1BmhgIRaVh8eZk00HRrwd4zepgaVM9rTmSGJWLVfVgXZWLU6oDERuhTEhsiwMt+tRCI1d3z4/9P2gnj2Cp73/prQ4eecdkceqb9Q9GcZbHWEQDThrVJIoPgm4lfBsIV+hgHUQ1FkxmPnXLfggn+6mGq+2TKra9cgTNQ3D8kS1s19A63leRXfAG2GuBjT2IlVpG3iESTUS6jtilwdYT/3rh9/KAR3OH9mUQTT85nSOjZpQ1cY/hoN85RXDAI4qtSUHxVAvjeUdjkmUqpgn4aAWzAdSqNYHYAFB+HOZT8kaEz6OElGyPa/eWqLvMcAaUAJmw4WAYZM5mm4yG83GFVmaDHQzNnmbwwA7V0E8pp0rVzXmfekwD98XcPEsUsRNH9iwp+hFSB1irSn0FnqZWBSPHgvTVqR0SDuHAX8AmCcleFLMSiH0opOeJNezYBqWdgksIl1XOOdykO79itG1Y4qFmxMc5GHfYhv1aiTuOeH2xCoY6lICL+E3maPNwQJcBgYIzsw2OWbpd/AvpzCbdg6XcboJDd06AlUvWjJioWqn71g1HnS48CNMgVvjAJEc6ByYnYAmMxH5RcmfJzlDrkV9KAyemhccl/x0AvHKQBO29uxga80OE9Ls6F47xvukR4/gjT2Gz0982kpZ0dmRzUE8IDs9KLMXVnAQi37FGiCVt7LUJEoYLwUaWh+UBrhmHP3yMdVvU9CXdys3L7lKRImjjRKnXJR6tticvfz2jeADATt8dnLzMgyAEhBrBpT29y3GZFAtS4zZLqoqg9Ax0gEgctY70YaputK2YVh7ZSx4oxLziXKh6TOKFKZP+/2X6VNyEaAq0qeHI5j0qSDif/oU409dixMHMhrPDF/9sbf38huJpQbQp+TiTgbQFLsjmDRFVkRl69NVvPWTG5a8ZK/4I2fR/mMDlhlAn5IXCQyAkoARJe+IStSnZBta7foUlRhafQqQwvRpfzp9ajQxAXk6GSaZrYtJw7ezuDK/vR98k7aXzOpjgJBgfzhTSJATjkMeQwe53sls9jjkVZDMRlE5D1f1FJXz8GQ2isp5eDIbReU8PJmNonIensxGUTkPT2Z7/qb04Pu2y32zB278yeJb0UCNZDal6bY+p3hnOHN5d/7deCWlsUZhwqBZJfLf/XaFbKl5ZpA0f/VprTw3+CFKwSRX6jNAntsAg4mGdRWKxn9Ws5KigCMONzlTQIsnpnQ8IZdINABPBtLxJHf/wwHTn3wKPrh/z8EdyY+IpwPNIvkSoVi7GCydOnRls2TwCY2K1iyJVClUlSRSCkcrWapCsJSvTa7xSDEUXXSkdVS8XCoW94F2DjaWHRR904ukP/fenXSDP2A459ivp7z6fq3xhU5/WvRVCOXRYPj417b0k6bGiWGGF6w6C8sFCURK7N2BXwL3Rh6nryexBC8LrJ3zwUZYQUDtenGR9OlcqzC+PFEk4QkTCGbTWtXcB94PotluqWqPlso0W4m62y8qmf2oSVCxHQpipByeNlSKVKMyx0dFNaHk/FHBEgEs1oXDa2IJG+GGjUYT6uGLsRLGqjAC3joi4ou5sIKUhvlSyoX8FPXvpv3lfJn6GUxUB9GJqtEYc3LFUQMt8JHl3wDW3DGYyZq/D8Kt+WCjx5xcytV4F1XfMB4HuKw+DjCEDnO9zaQNUnVmkqJGL24mKWr04maSokYvbiYpavTiHtTL2nVy437OC5rdkB/TtN+IEg0PircoO6dZdLOgNf8M6std7OqlZVyh1qcUJHLhXwMY16F0nDTS683IBY6r7HozXxHT9WaypMq+3iyq3akZJ560C8sdWa/1nn1TiOVZq+d6s+4ipsti7EVGcEdTaWlpFVxv9vzVrrh5BT8FLu4+b9jRNzt3GMX1ZqVJTNwpTDIC7lTJ9Wayq9E/N/3qxs6tlcvv0OTbeaO43iyHkTkyY2AOUp3Xmx14N/v5FMVL7v7hIxp8zD5PzFSu7uvNghiZx6oe5hnn9WbH+3Zq9eDcEu62htsOJwZnEvcBq/56s0+JTJy7nFjdnIMPVdr1Zr32Nnz20+lfuIc3FDq26LKVWM+uuq43Q30I2uvNgCLE/NRhCI2f+t90vRn5Co5qvt5s8HCm681Mh1fR9WYfFnp3uP05eI1/ulWxxYyPBr/eLCph4uS7w1pxM7b+iJ2z8o+vBriyK3o405VdbsMr63qzsW/3ceY3HBE2ZXnq3dhFTZ8Z/Hozso4wAFamjFjdq9ooobqvN4ulU2P/K93/H5XuJ99cVGWl+w8nM5Xu906ujNL9e+soGvXYND00I7Fls5KpdTkGPKNuaB1pwUF2JzNVOs9KrpLS/ZYLsvxW5D8I2YRMKrkzMtG92kv3CxhRAXJjNLGDfseFDFe6/6+vjY80bPJ7WOY1n/YLrc+eNprS/Y6MrPtz+P8fpfud7onqKo7sDpwd971J42u9blZz6X5Uy9DWXgdapspK9wc62+bePd47cIt4/IES289E7Vw9pfsFjOB4J1dh6X4T2/s/HKXBoVnNCkafbzJojzEUwQAIOTIiBOY05rfxERq/zZ/dtt0PnxJ2/oMmG6/mve5ErD6AHv2TScXAomv7bBY0OHcp2yIRlT2PVdAAiMulqYlJLPUFtfpUgCDf5kg7Wu1aCRpEXfEtLEQiRwB8+Vy46ELGtzUXyZdV9DiWY9mwQCuGBeWr175yIXS435GA7UNW8S8sW+hU8Ru/SC6UokHNX6JHjWJnpNzf03XVGX5FXaj0QiQIoteUSyWdizkIa4ReLlRt1fQVCBPlQmr/8ta/lxZ/+CIOK5izbdeMZT0lpHNV6IMU56pU7QafneD9P8mY3v+yrLqdJbVk6uEowSGLpAJRPENFnDE7l0x2fWYTtnjKu+vDD5YKibKKd6Atq2pKZTAjn5EZ6dXDDLL7g+izY+EeKpEqgfnix8O1U1cPHxCygsgixY3l6ROfJJUL3FgdfRQj5Er0F2pvNbdg0+W8Ds8jNnQqOtAysd1mol2DXxClTBNT3JpZRqoMZsUwMsvDKGYO7Eovb7Ve2UK3JFUep2CYQXeQJbVsn5qEH311zG3vJ9eMioTKFWVHJ65KkcMDope12BHA3Vx3hH5eKqbJGbytM7xD4vo9VweuX2825rYkakz1hr0AgIcyDIBbFAD8P/a+A6yJ7Xl79aKiCDZEENSIDVGx9wYJnVAUu141kgjRQDBEAStiw4JiQ0UExI69AaIComLvHTv2jvXa/c7Z7IZsJbmEJPf//Xgen0d22M3mnXPmzDnzzgw0LRp5ovhSxlyaYsft7nUuF7R2W/brb++EyfJmpKVMxynCAAA5GwADeobijuYo5L/FxyE3AdcZH+dxGBsfxzysrPk4/zwdNfzH894+GdUmlONnL+xjAHycO2Fs0c19YQZAKrhw4YIO+DhxN/atGuoa4LHRb3BH87NnfQ2Cj7OAVTtCQ9COTvg4jf9ZPjAksZzj0pTWJ1xNR+82CD5OD1blmBuCchB98nFqSPf3Caxs5r7llHuQ0dlefxsUH+e1jE15x2T6dnYNiI9zf3nfFvVzDrku2r6n1/KJVzvrmY+TyKo5ud41V6Z8nLmdhQcjehTyN5u0Dpw9e+4Wg+DjoD4EIx8HGELMTw1A/g/wcba1q/Pq6LUK3DjbDiF1Pp8ZoGc+zms5Gx9nmVw3fJxaW42vDbrn7bW65+s6m+83Xqx1Pg55b64FjsljORvH5JC8rPg4bVbNujFo0Urn5D0Ja4busfygdT4O2UZoAatlrFhJ5P9f8XGETGZsXI64hdgnjZeR7St59njoO2KkpM94mDvpJhOEBlEzTDUIXzR2FoeFwuwxZTQnspUiy5QjgJX2AuEn0I6857xj5s+Px3O3dRvztHztwzLG96NGclSFlPFX2R+YMF/VVCyaUUnOe1JzVCqfRsOn6eAFRqUFD/4jjspLVxHuw3Ze+ab+IglQmEjoAex6BP44VK0KVYqYVKlxTpq9cmyXfU6aRVz9S00+P+FHFzT1a/k1+oNKTlqDRT4jmrc29dxSq0O1N5ub/FbJSbv+59d7x3Z7XDbJygWs9o/LVslJCxsgOF+j0jGvg318RyU9D5+okpO297q7dEhWB++kMbcCeV18BCo5afc3xrp9bfnGd8Z9N05k8sPXKln9ExBpxhezIfx988tbVji9dq9KVn+35aeaPNk823H7k4pbakcs81LJ6l/m2+tW0JUXrssPXMwM8M2LBaLKmOhqrRUuycOcXRIPDDftM+7SSyCqgom8Dy39MOaer8/GL7K768/4NQQiE0zkXuWPTNBG4BK7Ttai69gPa4GoKiaqUvPvZT92jfTal+ccfSz41iYgMsVEM6fcnjq2zzLulj0WxybNLIRpeGb4GwbEVhxUI8N5naRG1Xffo0yBqBomso8ZPCyw0R6v9RHHF7ont5sERNUx0dzB8rteYUt85z+p39fspAPEsAYmur2627jRaUO8NtQZ1mrO6iorgagmJso7OeZg08zBHhvDIjhdJbeglmthooHhHRv95Nu4R9V2M1roVr0REJnjd6U/9F/7a4Dr2rv9hm6+LIfI18ZEdx1GVrq+CnFeuq77vB9Nls8EIgtMtGjRintt/7Hy2mHWZq7k+dhwIKqDiTK+zp1XeLKH29qsft7RQ7fOASJLTHSpxdwGsrp5vKzCl3yfMyfjgMgKE03qGVXnuKgL95Bv81Prw+72BqK6mGj2Sz+7TmM+Os9Lad19e523d4DIGhOdc5b2Lfid5Rpf3XpjygHXJkBkg4l2DkhNvDzvtWPi1Ib9nsefg4OtHj6iKkoWFd4Jc5xp0ednl9/2EUBUHxOlPl/Ts+PMRh7ba/7DnTR1ZigQNcBET9feCopw+eaTYR/Qc3FqNKxJwcFEpl23TG5555pLVqRFYPbwF++AqCEmurVqUpfsGl18YmJbyocPW1geiGwx0c+mGdXTPrz32XOkzru/1lhUoqRoQrtFa5fT5q1+c6dhhE/036sW3X+47L4WUjRHMxm22qMP7Ew4fsolcVvhxDM2k1OIR5AuEaESqZCGd8DUBLUpdoeSKYqWdQ8LFkgkwHRhFfPVJBqQzRrtq1FPRzGBut4M2KdcDM+HVpnOZ77HRSLCNWs4UczDVLwI7Xer2PNFlkNSS96689vbNax/UJs0TG27xnZc5CQESEjr7sVykZRwjTgEHfsCN0uGnvgJRbAksDRMjBIvwPuJJbDBs3KccIDfxRHAjVoALYp2A3cNuXf0PjczPqjepKZ/fSIGTpWfQw2cFou0vv+1Q0cMC1x+4QYR5aaS/DRsUdoKm2jCYnXJgwRysOsZK+IAt0XZ8ok5wjrZ4tzzWR97eO+a3bjW06HO5qQzduyxNGfsuETr2vuCDXZnOu1F1eLBwU6Js2oIXEOcDoQfdYvIQNKCteX31yE7Bp3mz99z1uVUZqNdpScfaQGsCFawwFDH1p9AhGH9+V/Owr/KWSD79TrLWbCJZMtZSIwoi5yFVpG1H3Pliz0yrzWraffJ1UOLiyXZAmkhZ8E8kpXiHaGTnAXLJa7dDtnMdDwQPeitx7JffnrPWTgWwYYKGDcGGl/RXc7C9If2P3a2yOCmy+o1XVJvYG+DyVmQs6qOrx/V6TxnQei1rU2VqCsec2RPdzV/KZyu55wF1Mowk84jdJezcGXwRM+E7/U9U/L3PzvWodFhA8hZQI0NIziJETrMWXAYVKW98EKs25bYIXt+tCoi9lHWX86CnBUhMKcxvy0IYfDbTq0W8H91reMWvbF+pZeNJmUTvVG0P56/M1/9gwMusT0l5gmDHeJo8CvwuyJVezgCY4uNV+h7Ya7bFLUcJ/KpJ/17U71oXKJBG5ncOKyNDNVV+slFouLKoI/lptRZx3/GPfeZGdXl1sKs8+9IoXl4N01oHr1ckqe0p02m/+suk71WD+q42fnBhGQt9Ig5BAEKpR2EmVxkc5xGETdLFCB8XNgJxTIwfIGcfrHtN7x3UUb7Dp6LbP5p9E+kTQJxWjrjN1OnZbGoJMB2n/86cfLSRq4x917GfMqpZ6UFwJaxAgZGlF6cKMWaAf+mPcL0Q00ENWbRpQmqSxaryr84ecx7+9u+q95ePD0t5dGLmmgKD1CGS0SoTKQM+KFOrRPX325Q89I5wCTVrrudM3dN3iHv6NfbLKb86bdbC6qVsKp2kJ5US+cfx2nWbK7kXqkv4sq7ba/90fXA1sHdX72QmemvV2oVnsImwV6poRSjDXa9YIphC6MYYVgYuVfr3J3Qea/j9qHDLecPOEwsKGwOC3XK4dEn5PCKYFRZpEGHtdY8aTCAXFEuFH2MsPgx6OawuLGaEAwStVZEcrCv5BemqIP2r9QF3ZmLREwFoD/n0jVcy+UijlNLm+HnxFcBBR43wALA0NuQhnDs8GZhAD1F6h/8n8KmhcHTaGm4iCFv5+HUWevGdsp0yYqqOub0pQU3iTYG7btK044Ou16SjWlc7XOLET87c9ffiq1/KGOdZWltDJ+LhEKYjbh0LcbmoDCX9ki4iYr6ladbAdKQMFHAeHR4wHYV9KebaX2W1ch9VM1trlHKwv4vEGIddpPi51K3vwSh1k3CTQy2YXSwRVXiQdgwkzCGySScMWv0sW0nqffsD++8HK5McyE3Jw6VCAJEHJ/xEgmNLWBymFvh94XA++CYFYdMEEjEQsUgDxfLgzhSsE2RqW8JyLF9lveka6KsIlYXXXMusnIKQNeENvhmBNCdUtq5bwEXNbTVohy2BoRGEiLG0F/ynF/HO5WdZjXwGdU5yecN0X1GH0R1nxWXS5rOZC5DaaezDReJg8il0roMyVwkaAqj+6wmctZK5GSEoQaHFi180TdaVYnpe9kn7a7VwPA67ZcSCd7YAKEP6RClWp/FAC1HVrQsp+jUwcJf1LhfZKhIFYdGKkwfBy/g0ookDvBvwhzc3EdAJzdQJCNxi+FPaQ23BbpAQsWCR4BNdaRC1fS5F6SFqTSTpLR6rc5TzIIiJzq9NuDBWaDRQZilomUq9BXQtQof+kJaKIxN48N++7zgHxTt9btt/uIhKTABvxVNYAK9XBZQOLJCAYY4tlCNRRgWKoOpdk+2ltppF1QGxe4TJ7MVu588GYdcYvCQkxl12oG88dlp30Jq/uZNvz895WHh5AZagLzpdDbILabjkAczQa4xl7MaDrkOuJw01Eucy0lDvcS5nDTUS5zLSUO9xLmcNNRLnMtJQ73EuZw01EucyznnrzlugrRrztk7Ltao/fj83xTKGxy8tKOPTNrUAuUthEn/tl7HWt3dXcV1k5Fw1PUX1Yn6r6U47OdJpGHQXUQDOFSnvCLDbLN1FcNGP0GwM47iAeiWEu4zMRqCeuF9MlG1xFekgEP3R+pOsn7Ack3MR/c+NGfXeVzkZ6RGZ9fWimgbmkMihaoBeIBfmHlBVrIBafOHhTnueX5sqsXQ1j1KE2sjGSRyGK+0BgnsC+UTsWW3iGKQFnCRLhNp/XAmrGorKRGqWNGiZHLhh5/RgEG8pek1FyVVSLDRIi1ien+fzyc3Rrhukc51j+FG5mkBpZ+RbCjlRmrWEL6lHz6v0MmGYoZPObjVw7lnLKGSnx0m/I7O9kh3bh89hyM+ps94bgE2iOgDchV5CH+iZm6svTJ6CCEKUKl0AVcggm2iBWfR1G5NEl6td1oiNrflWNcaYQhRSwBSY1aQfkZqFtdt4ixWfHPlUVXxkEEDi8wGKrzu0wGrTe7wYwIGXVp4ZNV5YhQRfy41iqiUlAU6V5kpAQCdbZG4YyRFGBbGVwN8+Eatv/GWrzvrutbXYwj1IJ66EhoxgNuQGM9VUt3CpRoVmyOnZagbG1AXtpFcJHMSgO0sbcbkJy4yclIZhGnPd53lm+0w0GfFtSc1uxs1IRX8Q+OxDMs6QViSFSebuNJa8SAusguC5Uc7xjZzkZhJGq11ZihYIjDTmKFyrLw8eIj7Cf56/oUJWQ6p/YmWyAXcSw+UikjXLkEQOmpYYOoySbPFruQQGjnWrL8QGrA06BiBITRq1+IaPAgNZodCmewQr9nZ1l1n3OenuK59L+9qVY98Dh0sCOUozmlozsuZXPNmivvwaA+alyLghIjC4SWRTByALZBqmSVyShjLG9KdlKuI1cUVeE47YvJRdg6NT16eh4TEaGSozNAwlOJwF7wOfXGBnrWXGf3qxptTI3Cfe6+hxG9ZAX0A1UVSXC5pzpGz40o75xAukgbh2cZUByI+RiM2ianifdjKg9kP+LPt2Yv6Tssuju3fpH/qGmL0T3E/NfqHXS8Jn1p16xj3fHyOvyHr59Bqc3q10QI+0az4gOGjD4aBMUrcmKAAogdC/tGsfrhpP4EsUCRnU5rE8fj2bjf/OGYaffy1uWJzUk03xf1UpWHXtW4sgVaGsGrF1aC0UpSDa0Wj5asaavBCRULM+NIqRr68ds5E83keh38+XHs9ZZQ1UTHe6P1UxWDXta4YM57CnMBjRup+1ZaHLIjRbENmrcQA3VhIxCXhYRY0+vy4+LNO2xDB8TcuiyKJrFqe4gFUVi0uKAtEQlgR8YvB1/VxCMO6vmuJ16eh3bt5zP70S258tOAjUceKT1SfDNNDucMgLuCc8CBxQBBwK2FuoSAsDNZBULJisOVfvc0HObub7n2pY1JxXQOeaPkYjCdKZb+Aq0/nlDYCboO5GnCxFytK28AUJsWb0H7xqW5Tojw9PNw2WT0sGHrbkhjIrcTk2CgFul78B3GR33Py4QaOjtqyEsVQI4vVwwcbUYpinoRELcgHClOcD8ACgvD/xT4lZ5LPFPqCOKT1XL+1RD9hgFnSAmbKg4Bhk1nGNJkNJnBFHk1a6oxNDnNoIXKVOoctcrVEiXkYE+Y+Ga7nTyHHeFFDrLqLX3rWINaaQrvQh0rEAWhaGNWQMiFt7Q38AbA8ycGdEk4w4Slq2UlyPQu216KWwCLK1YUzjoukLMhHz45pDm7yuIh8Qb6p8jQS95zw9aSKB7SlBF3CT6qEXvYQ4mNgsPDkwnI5lZ2z3tbxNm1R6yIuL8cgN/FFzQtljBgrrjM/WPE+6OvCP2HbuNVzFcuAzYHsBJTMRNQXrX4OH7c9d/RjX9eNsiXJlpaTiJTUck7U2eFEmR3lSLOjU7pFnzjPrt7zbGxnu+d2mlza2bGMiyRCdbahZS8kc5GYBfkqIJV0slTfXxQgBRZaE5TabF+fYtLNgrste5ZX9wtpvYgocakocUtEaeak6WPf7P7quHFRpd4e3n8aaQElOStKIxfkY2NQOZZY2S6KKoPQMVIDIDLrnbiGKR5FXcOw62Vx4I2OmK+0B03fUKQweyr/j9lTchEgHdnTkLls9pQ793/2FNNP24zKL7LanXNKSxicOvemTUMt2FNycSctWIoxc9ksxYC5ZW1PV9Z6PHPrniXuGTKrimM2l2uuBXtKPiTQAkpcVpQc5pahPSWvoXq3p+iIYbSnACnMno5nsqcGsycgTyftkNk6lrN6H8sLdU7/7Bi062psXy1sCYpi2LYED5RnKhOYINeYzFYdh1wHZDaaynm4qaepnIeT2Wgq5+FkNprKeTiZjaZyHk5mo6mch5PZXvWXbVw/uhV3x0Uv4blll0NVyWwvTOXryx1yjP0nqveK07F7VAoTTpaOkZ64+NFnT+p79wlfR1lReG7wj2gHJrlSnxZ4buFaGxomOhwa/65mJU0BRxxuMlOAohMjJp2QSyRqQScRTDpJyHwweM7jrx5Zmfuzdo99SNyKVfAThIgk1GKwTObQzokTCu9QqWjNCZHKRYqSRHJRhJyjKARLz/Eh1XikeRV1bKSJf4BMKpH0hescvFicKFrUm2Q/W16rH2V3p4tbTMy7GV4Dkxkzoo37h4lk/cDr4x/bxFk6fpQEMrxg1VlYLkgolmPfHfglMDZSGLWRpBK8LDCV8+GE7JgFzG5XHhI1h1fFWyALFIfwRaMJy6aJ4nJf2B9E9XplxfV+0lDVq0Tb7ew/1uny9ln51VAQ/WQw21AuVrxVJfyt6CaUTBDuESKExbpweMtVhhdhwEblEurhS7ASxoptBOw6IhZIeLCClMryJZeJBMHK340GygShynuwoRrJNFQNZjEnVxzV0gEfefxrYTW3n822mtedja/mEw0ec3IpV8M9VJWzpgMIlekAk5gw13iZNEV0t0zS1OjFl0maGr34MklToxdfJmlq9OIe1M2UVT0/zdnL3bGgllGwoFIXFQ+qQ5GshonJFueDRTvHZlrfKE9ZXKHVp29DSSr8q4XFdTKTJg20vRm5wLHO2psZxbO1N0tcXtbtzT6uMfvU+dQ+3wUdhv1Iix6SagDtzZB4tmYxr5cbQI+mBw8e6KC92epl3n8fW7TSKdHt1fisJxE/DKK92c3lrE2YDEE7OmlvduB7rah3o3d476v68nqfXs2JpFd9tTfbxaqcRENQDqLP9mbXernk7sso75QwK/bPzkD3fQbV3iyGVXly/SjPMNub/cwOvmB7dbb3pj1+bVPOj47Wc3uzkaya4+tdc/CmMmtvtvNv21VHzn3x2Duy3rP9H3cZGUR7M9SHYGxvBgwh5qdOQRj81P9SezNyCw49tzdbEs/W3mx0vG7am7VdfrqvtKqvS9bMzG4Lr4YUaL29WZXTW8RN0/s67l32uIZfHMdYCy27FsazteyaGF9W7c2GrE437bOxlu8c45bDa29I3aj19mZkG6EFrEazYtU3/v+r9mZTmczY/0r3/6vS/eTORTor3c9dwVa6v/yKsijdn7+4+X1uxWDXjNdjv67tt4jY2r10OeratpHGXKTXCrZK5/YrdFK6f8Bc+1MWG2q6z+0jrFJzfo9qei/db8GKChg3BrN30CxdSHul+2uaxG7u4+Hpsi04zWrs+iDisb0+S/e/jWdTXYFuFzJcdTov3d++n41L4FA/7+jKSZ9qHh7F03PpftTKMNZeB1ZGZ6X7FyfwrSc/TnDPGlLxW3yNq8QyW/op3W/BCk75FTos3W8+2/Zb9f6rfWL9Ln1uL3tOLMKjv9L96JxmRAjMacxvm4Yw+G0uTvYt/vS86rT5Xv0tl5PekaoPoKl/oVIJWNGpPpsxA84di0Mk4uL7sQoaAHGZdHxgEEfZoFaTChDkbo6Mb0utlaAiVBff3FzEJwHgK+DBQxcyvs14yPdVpU3HMi9+LXAVw4L2q39bl1yrmri7x/IXQQevXuxP5AH/q45fJBeq84Sh29pEH3A8aJV+9mv13AGldaGichFPiF4DHt3oXMFFOiVo5EJVVUxfoShQJqL3L09Fd8t7f/MJLzWmdnbBuiI3Ul4VeiNNXpXiutZnJ/j+tqzf3yxB386ScmRq4CjBVxZLheIAloo4vTZ7zJjr4++5zFzuHbV12XziWMUfQB2rSklZKANMVhZlPF1lEO4PoknEwsErRCoHy5cgAJ6d2rXpCbasYGcR3JLTtmdAkFQmbMlp1zNsnEyO/kLvrfrPuHYz/1Qjl8WDn70ounVKSlzX4Af4yyMlNF0zi0VloazLrMrK1o+ySDMHPkojb7V28UF3yHjZqDCWGRR916R261G+vJkHU5b6fejUpDRb5dKqoz1PYchhguhFijpcef1bJ2jmpWKWnMXbyrOYKzSuXOiUsWBWenf3r7P0u+0FAFjgANykAQCaFo08UXwpYy5N4ZzzuPrsg77O8/feGrKnXp+6+k0RBgA8WMUCQNqxVbijGYX8t/g45CbgOuPjTF7NxscxX13WfBzO1vBJ+3Nuctc9OfL63c0pRw2AjxOxmi26KVxtAKSCEydO6ICPUzCiXGan/sOdt9+W760a+DbCIPg4fqza6WEI2tEJHyfHFxnZ1NfUfX6DqF0NV/09xCD4OHasyjE3BOUg+uTj9LkU9yT3BM8rKqX9/AO7dhgbFB8HYVXea71vEw2Ij9O6qvXTatvy+TMePWk471DXbnrm49xMYOUo6l1zZcrHablReJ13I8ltedrCNXF/7000CD4O6kMw8nGAIcT81OnI/wE+ztO1t4IiXL75ZNgH9FycGj1Zz3wcJJGNj3OV6tKWCR8n6kLi1GUnUtwWRCwbLMlot0XrfBzy3lwLHJOfq9k4Js9XlxUfZ+Exr9WF44e5pq8PbPb7r9zNWufjkG2EFrC6yopVrm5dHX3zcaKZzNi4HHELsU8aLyPbV/Ls8VBi81+TPuNh7qSbTBAaRM0w1SB80dhZHBYKs8eU0ZzIVoosU44AVtoLhJ9AO/JMu26Z3PLONZesSIvA7OEvmN+PGslRFVLGX2V/YMJ8VVOxaEYlOe9JzVGpfBoNn6YTLOdlwYP/iKPy0lWEe7njnHxTf5EEKEwk9AB2PQJ/HKpWhSpnMKlS45w0e+XYLvuctKXjvof/VW+Az+oFSb2mTzvRWyUn7WTHJYfuV3Jz2t6p9rvO3be8VclJqzZ6rpnx6bNOc7u1jnvRvnGUSk6aa7c/R15/3+69pmbGwrvTe4ep5KQ9qHNmZPA+e6e0I43tvq5atkclJ62JtPv78jOmOaUszhQH5Dx6qZLV33jnU6MrX067xc7J/nnxard1Kln9tROu+E6/NsJzzkGv32nZ39qpZPUfrDqhKLPnKZd9vR/Z8cMjOwBRZUz0app566X1OjnGzPlnutPnreuBqAom+jHj60/3Tst4Sw+0enrgH/cAIDLBRDWP1y+anr6JP9/omlvv/rd2AFFVTHQ6YWmlH+2F7gtFlQ6/SenwFxCZYqJvnnc8B05L89xdafeW0yf2nQEiM0wUl/L85nHZNffUGOGD16bb7wNRNUxUWbw+KTr7p2/yvr1P9l65C1+jOiZ6W9d148LcaM+U4XcqPlrVEn5WDUzU7JnxtmrZaZ5L288UrYi7FwRENTHRcX+zG0UdTjtuqSF5PuTiqmAgqoWJRizYMA/p2Yp7KOdd7L2+djeAyBwTydzO3tvuM4u726tafN9vtaoDUW1MdOpsXqL8dBOPuMKcFq+SU0YBkQUmqhDcPacobpfbZsv6WROyu48GojqYaJjd3NXD41f7rl1REFLn+KeTQGSJiT6vWNfn64fPvknb3Fv1HWrzHIisMJHbg4F5Xtc2e8y+3/nE5677ugNRXUy0qaj19N1z17tNX/N7VZvmAfAua0y0KNPEuN22Cz4znozpMnzYSTMgssFE78UH3r3qftolel77dht+zXUDonqY6JG1Wf2Ca0Xc2S0a7u39qmYuENXHv1fbGd0+H4t22td6Zm37QYHxQNQAE3Vuc3egdbilz+JJ3V8V3C1YAUQcTMR9EhwlW33Wd9a0rfYHbzc4B0QNMZHJ6QMFn6dP8V4TsvSKRWhEEhDZYqJyJ+ZVmB/ZwS1q0KWaO7xSoykpmtBu0drlxKJ292vHPnBaHNCg3fPlH1vSGBtNUzRnMhm22qMP7Ew4fsolcVvhxDM2k1OIR5AuEaESqZCGd8DUBLUpdoeSKYqWdQ8LFkgkwHRhFfPVJBqQzRrtq1FPRzGBut4M2KdkJeVDq0znM9/jIguTNGs4UczDVLwIPYs/bnmVDVldfXZcuBCckPoyXYs0TG27xnZcJB0CJKR192K5SGqSRhyCjn2BmyVDT/yEIlgSWBomRokX4P3EEtjgWTlOOMDv4gjgRi2AFsWtTl03rLGW+WR1qJS18tbk28TAqfJzqIHTYpHW97926IhhgWtikkFEuakkPw1blLbCJpqwWF3yIIEc7HrGijjAbVG2fGKOsObP4p86YpfqtPMpN+U913kF6YwdeyzNGTsu0br2vmCD3ZlOe1G1eHCwU+KsGgLXEKcD4UfdIjKQtGCVX1y95e0KFb1X+SKZ188JKpSefKQFsBayggWGOrb+zEIY1p//5Sz8q5wFsl+vs5yFkclsOQuc5LLIWTj3pMjydmVb76TvPTrXq3rGTIuLJdkCaSFnYVgyG8XbPVknOQs3bc5HPu8gcVttLxmY9yY4T+85Cx1YUQHjxkDjK7rLWYjfsPjLp89DXJc9SsiV/ggnnsboM2ehKqvqvhqqO6PlnIUhCRZhErcK/LmNhlSZv+1ZFz3nLKBWhpF0DqyMznIWmtTn11gQxnc8POH2n6oDjCUGkLPQgRUcTrIOcxYswlu3nXLnjtviDvvPmiw2OmwgOQtVWRH6qvTbZiMMftup1QL+r6513KI31q/0stGkbKI3ivbH83fmq39wwCW2p8Q8YbBDHA1+BX5XpGoPR2BssfEKfS/MdZuiluNEPvWkf2+qF41LNGgjk7oXayNDdZV+cpFRe8ugj2Uhd5rk2ritPrMqnFw9POuDJSk0D++mCc2jl0vylESDdl64HjreMXtD7DWh4IalFnrEJEGAQmkHYSYXmbdXo4ibJQoQPi7shGIZGL5ATr/Ypp1wSZ8+ZQpv1hGvS+tuF0whTktn/GbqtCwWlQTY4Qv+d35U4Hmt6Vp/z4g29uZaAGwCK2BgROnFiVKsGfBv2iNMP9REUGMWXZqgumSxqmG15SNinjpwd661vvnz0tN3NdEUHqAMl4hQmUgZ8EOdWieuv92g5qVzgEmq9XffgvzdI8tr73VX+5DZ3o5aUK0Pq2q76Um1dP5xnGbN5krulfqxkv+yRBNnt5mOrW1XVc3w1V+v1Co8hU2CvVJDKUYb7HrBFMMWxjkIw8LIvVrn7oTOex23Dx1uOX/AYWJBYXNYqFMOjz4hh1cEo8oiDTqsteZJgwHkinKh6GOExY9BN4fFjdWEYJCotSKSg30lvzBFHbR/pS7ozlzELBWA/pxL13Atl4t8WFvaDD8nvgoo8LgBFgCG3oY0hGOHNwsD6ClS/+D/FDYtDJ5GS8NFDHk7p49umMw5tcBz9SVRcguvEU+INgbtu0rTjg67XpKNqfTzt5Ho+xDnRU7vexQ+dCk1a4PPRapAmCHXkdpibA4Kc2mPhJuoqF95uhUgDQkTBYxHhwdsV0F/uulV68XR2rz1nsnVhS4OMcNqEbkIxc+lbn8JQq2bhJsYbMPoYIuqxIOwYSYhhskknDFr9LFtJ6n37A/vvByuTHMhNycOlQgCRByf8RIJjS1gcphb4feFwPvgmBWHTBBIxELFIA8Xy4M4UrBNkalvCcixfZb3pGuirCJWF11z4ASuBeia0AbfjHiIrNRz3wIuamirRTlsDQiNJESMnorlu8bx9brBTvHl/uT+qC9+SnSf0QdR3WfF5ZKmM5nLUNrpbMNFEiByqbQuQzIXmb2W0X1WEzlrJXIywlCDQ4u+p+KMR4VPrs1wW3LH/7PTn6zvRII3NkDoQzpEqdZnMUBLxorW8LU6dbDwFzXuFxkqUsWhkQrTx8ELuLQiiQP8mzAHN/cR0MkNFMlI3GL4U1rDbYEukFCx4BFgUx2pUDWtlskLU2kmSWn1Wp2nmAVFTnR6bcCDs0CjgzBLRctU6CugaxU+9IW0UDRPMQreIJ3lsSo9039aRPJOUmACfiuawAR6uSygkLFCMVy5UM1FGBYqg6l2T7aW2mkXVAbF7jlr2YrdV1dCPs/gIScz6rQD+TvJsqTKxoN5+wq/j2zWeugnLUD+dB0b5NfX4ZDPZ4JcYy5nNRxyHXA5aaiXOJeThnqJczlpqJc4l5OGeolzOWmolziXk4Z6qezQRKVe4lxOhwe9e8aOu+m6a+jsKKs+3k4UyhscvLSjj0za1ALlbQGT/m29jrW6u7uK6yYj4ajrL6oT9V9LcdjPk0jDoLuIBnCoTnlFhtlm6yqGjX6CYGccxQPQLSXcZ2I0BPXC+2SiaomvSAGH7o/UnWT9gOVKyUf3PjRn13lc5KJmYX5rRbQNzSGRQtUAPMAvzLygafvqnR5xzMwn2n1ng72Hti4rTayNZJDIYbzSGiSwL6yagi27RRSDtICLvKUG/Nmwqq2kRKhiRc8BSd2d3sJrk+u8kxPfe3SrPE2LtIjp/X0+n9wY4bpFOtc9hhuZpwWULiazobQnWbOG8C398HmFTjYUM3zKwa0ezj1jDpUMiDuddK7ZIrft98Z5WL94+E6f8dwCbBDRB+Qq8pCvGsZz7ZXRQwhRgEqlC7gCEWwTLThrOvNvfOie67PyWlSsS3KXOYYQtQQgPWaOWgKQLmoY123iLFZ8c+VRVfGQQQOLzAYqd5X4YWabYI/ML4fMF5w/P5UYRcSfS40iKiVlgc4hVnQ2J+OOUSzCsDC+GuDDN2r9jbd83VnXtb4eQ6gH8dSV0IgB3IbEeK6S6hYu1ajYHDktQ93YgLqwjeQiO+DMO0ubMfmJi0SnlEGYdn4nz41nxwr5ay/4Xe3qzEkiHnai8ViGZZ0gLMmKk01caa14EBdJg2D50Y6xzVwkPkWjtc4MBUsEZhozVIMSGvaI9R3gHP1g5P64Rp2JrNfKLuBeeqBURLp2CYLQUcMCU0iKZotdySE0cqxZfyE0YGnQMQJDaNSuxTV4EBrMDi1kskO8Zmdbd51xn5/iuva9vKtVPfI5dLAglKM4p6E5L2dyzZsp7sOjPWheioATIgqHl0QycQC2QKpllsgpYSxvSHdSriJWF1fgOb1Ny0fZOTQ+eXkesiNNI0NlhoahFIe74HXoyxN9nXI2cNUX7jqzM5Ll63vWJLpI6AOoLpLicklzjpwdV9o5h3CRlxCebUx1IK6nacQmMVW8D1t5MIeHn2Zvav7QedPqfUZjt9W8QIz+Ke6nRv+w6yXhs3fEe4+iLpfco/iRw+csFf2jBXzyWPEBw0cfDANjlLgxQQFED4T8o1n9cNN+AlmgSM6mNLfK4jDvidedcu6Htu54bvFFotIU91OVhl3XurEEWklg1cpsg9JKUQ6uFY2Wr2qowQsVCTHjS78da5hTvvHYyk7JI6/fWbKiIjH+W9EbvZ+qGOy61hVjxlOYE3jMSN2v2vKQs2mabcislRigGwuJuCQ8nuaPlB54XYMfY/aqctPOXYipbZV4igdQWbW4oCwQ2cGKSFwavq4vQhjW9V1LvD4N7d7NY/anX3LjowUfiTpWfKL6ZJgeyh0GcQHnhAeJA4KAWwlzCwVhYbAOgpIVgy3/6m0+yNnddO9LHZOK6xrwRD3TMJ4olf0CrjpQ13UNI+A2mKsBF3uxorQNTGFSvAntF7eee6txxoa1/Jg/oV/Tq64jct0rMTk2SoGuF/9BXMQVYtiGltqyEsVQI4vVwwcbUYpinoRELcgHClOcD8ACgvD/xT4lZ5LPFFpEyeu5fmuJfsIAs6QFzJQHAcMmcxzTZDaYwBV5NGmpMzY5zKGFyNXrLWyRqztbcMwXM2Huk+F6/hRyjBc1xKq7+KVnDWKtKbQLfahEHICmhVENKRPS1t7AHwDLkxzcKeEEE56ilp0k17Ngey1qCSyiXF0447iI0c589OyY5uAmj4vc3JFvqjyNxD0nfD2p4gFtKUGX8JMqoZc9hPgYGCw8ubBcTmXnrLd1vE1b1LqIy8sxyE18UfNCGSPGiuvMD1a8D/q68E/YNm71XMUyYHMgOwElMxH1RaufjYIqm6okPXXdv+li5ekOkk4E/ZRzos4OJ8rsKEeaHcc9/nlSdaERN3vvPOPdzfMXlHZ2LANqhOpsQ8teSAZzZ0e+CkglnSzV9xcFSIGF1gSlthsco2dPW+Gxfcyu5YmCWaOIKHGpKHFLROlGn+dNGg744Lwkq4913IAr17SAEhjWLCgd25GPjUHlWGJluyiqDELHSA2AyKx34hqmeBR1DcOul8WBNzpivtIeNH1DkcLs6ZL/mD0lFwHSkT3dsZXNnkZv/Z89xfQzL9cjueh8f49dydautT9fa6INe0oq7qQFS5G2lc1SxG8ta3s6U7zuTY+209yWP7KqXdu9bVct2FPyIYEWUIpmRSlkaxnaU/Iaqnd7io4YRnsKkMLs6VIme2owewLydNIOma1jOav3sbxQ5/TPjkG7rsb21cKWoPFWti2BuRLyZUyQa0xmq45DrgMyG03lPNzU01TOw8lsNJXzcDIbTeU8nMxGUzkPJ7PRVM7DyWxfzLo34n297rzqZ9KFSlOsI1TIbKPjp4xoHbeRF1V+hrtlxuVTKoUJ19k8vnVgZ23vgyY1jtTrVoNa2g3+Ee3AJFfq0wLPbbnWhoaJDofGv6tZSVPAEYebzBSg6MSISSfkEola0Ek8k04SMh8MnvP4q0dW5v6s3WMfErMDK/gJQkQSajFYJnNo58QJhXeoVLTmhEjlIkVJIrkoQs5RFIKl/drkGo80r6KOjTTxD5BJJZK+cJ2DF4sTRYt6k+zn21O1zjZ+4OW8bPHln21Ot2TkXxv3DxPJ+oHXxz+2ibN0/CgJZHjBqrOwXJBQLMe+O/BLYGykMGojSSV4WWCK2Q11Qu5sAma3Kw+JmsOr4i2QBYpD+KLRhGXTRHG5L+wPonq9suJ6P2mo6lWi7eb/kjmZF2zKr4aC6CeD2YZyseKtKuFvRTehZIJwjxAhLNaFw1uuMrwIAzYql1APX4KVMFZsI2DXEbFAwoMVpFSWL7lMJAhW/m40UCYIVd6DDdUVTEPVYBZzcsVRLR3wkce/FlbzvpvZVnPuZnw1X2nwmJNLuRruoerw9WyY+6zHMV/FhLnGy6QportlkqZGL75M0tToxZdJmhq9+DJJU6MX96CMl+S8TFi+lzvv/efz7R/fqqviQdmPmZ9+JP+tZ+bjvn1CLr5rTFlcodWnD7iTCv9qYXFNYNKkgbY3Ixc41ll7M24mW3uzgoyybm+2suk14yGbZrnv6eQ/duHjBmsMoL1Zr0y2ZjH2mQbQo+nWrVs6aG/mG973RkPJB9+ZR9bMnSidbWIQ7c0sWLVT3hC0o5P2ZsvLZw66NPW8V/bPjheC/AvGGkR7s7cZbMoB1kT/ykH02d4suFxRor8wyzvnxZKJQUsPzDCo9mb5rMrbox/lGWZ7syt3C91//nD3TZcUfLmwblKyntubJbFqbp7eNQdvKrP2Zk4BKSb9WsjdYv50a2FuNYBnEO3NUB+Csb0ZMISYn7oaYfBT/0vtzcgtOPTc3uxiJlt7s/WZumlvxqnRd9w/EQdcdn5HXPvyR6zSenuzJp0r+5189swle/DBhJcmR0odaVjIRc5msrXsyswsq/ZmOb/vN3Z72cR1VdGmYRfd+6/Wenszso3QAlbrWbGK060fqu/2ZolMZux/pfv/Vel+cucinZXujzrAVrrf8UBZlO4fZ/fnwM/a/bzntbhx/MXoLUTqWely1LVtI425yOQDbJXOgw7opHR/4a/mo9NbmnvvNZ0x3bvaxmZ6L93fjxUVMG4MZu+gWbqQ9kr3D32UbIX0CvJMH7Jnj22Fli0MpnR/S1bVWepHdTov3R+yMqxupdiqjouH3j6Q1OHgSj2X7ketDGPtdWBldFa6v3V+crMHlwdxlyybtmHJhPSKBlC6vx8rOI4HdFi6/20V82GLxTcds8N7Zm+acmW7IRTBAAi1ZEUIzGnMb1uDMPhtLk72Lf70vOq0+V79LZeT3rUnVh9AU/9CpRKwolN9NmMGnDsWh0jExfdjFTQA4jLp+MAgjrJBrSYVIMjdHBnfllorQUWoLr65uYjDIYCvgAcPXcj4NgPb+4OlTccyL34tcBXDgvarH2n/tWKLE494S8ac925baSuxN+O/6vhFcqFa7LQLb3Gthse+V+nun7lDSl2iPioXsYfoNeDRjc4VXMTikEYuVFXF9BWKAmUiev+ydquCB09dUrhzTDYeyXo2P5WUV4XeSJNXpbiu9dkJvn951u//9qC+nSXlyNTAUYKvLJYKxQEsFXFWpD3hZ0V99U4UeRU2+DCgIXGs4g+gjlWlpCyUASYrizLy9aMMsvuDaBKxcPAKkcrB8iUIgGendm16gi0r2FkEt+S07RkQJJUJW3La9QwbJ5Ojv9B7q5W3p9/ynDDPceaIFnOMJnr0Ia5r8AP85ZESmq6ZxaKyUNYeVmUlGcTMgY/SyFutXXzQHTJeNiqMZQaN/92gxfDZa30Olqv88siNrg9Ks1UurTra8xSGHCaIXqSow5XXv9ohzbxUzJKzeFuHxUYTNzTd6HG49q0GDROjBuh32wsA+HIQA+AmDQDQtGjkieJLGXNpCtuQVdMCLSo4zm9T85iQb/9YvynCAIBcNgDS1h/EHc0k5L/FxyE3AdcZH8f1MBsf596hsubj3HqVP2p7QV/3lDf19lvsmljTAPg43MNs0U2HwwZAKsjJydEBH2es7eGE5ZMC+FkvgVv+KiXfIPg4dVm1U9EQtKMTPk60TUytW74nnfe6ipP38g8YGwQf58MhNuUAa6J/5SD65OMgj/8JuvF1uHfSqzvlxNWGLTIoPs5pVuWl60d5hsnHGdCmS/Ssg3K39BzTiF/dHV7qmY+Tyqq5hXrXXJnycWoHd+gxLj/LMXnQhF4XRD0EBsHHQX0IRj4OMISYn5qM/B/g43Ruc3egdbilz+JJ3V8V3C1YoWc+zunDbHycpMO64eNcsNhxz3nDbo+YnKwFcwfKzmqdj0Pem2uBY5J/mI1jsudwWfFxhhy6XqflxnkeSTa3bnR+8PmU1vk4ZBuhBaySWLGap1s/VN98nBQmMzYuR9xC7JPGy8j2lTx7PJRY0d6kz3iYO+kmE4QGUTNMNQhfNHYWh4XC7DFlNCeylSLLlCOAlfYC4SfQjjzuk+Ao2eqzvrOmbbU/eLvBOcb3o0ZyVIWU8VfZH5gwX9VULJpRSc57UnNUKp9Gw6eJgOW8LHjwH3FUXrqKcE9O2JJv6i+SAIWJhB7Arkfgj0PVqlDlWiZVapyT1kI5tss+J21YQI0ez0Yfd1n84OOZde3WCVRy0jg/rvjd+1TTLdmqbZrHj4UZKjlppibTw6//ljslDxvTyWxmXblKTtqOo7Xv/E686b40dVf9qXmD+qrkpFmNONhlXI9EtzndJh8US2xzVHLSnAaFPr+71sUzttBh/9TOxwNVs/pbhm6KGj/ZeVn9zhXGLJngopLVP9Ds1Ztt7V56rho4KPPWkknXVbL6jXf+PLuvnNgryyqq3qbsQT+AqDImqji4/z+8tdku+56eiBnTb2cIEFXBRM3v+iQ9mRvuuyHl98+hb1ucACITTFSv+fePH96Pcp25xnGEqdm7N0BUFRPdK/ywIeyfAJcV/ibDd99rB0sSmGIi/pNnw7asn+mz7cyG+PJng24DkRkmmuNr1ua2W75T1nKjkNWfKlwBomqYaGLF4/HRHXJdExef4+wfutceiKpjos4v8iPH+Af4bNzz/Hvzrq09gagGJipXzWXb3brb3aa71bl5tXBLPhDVxERN3AcXVned55sQ0szTJ6vGLSCqhYlud4rMaT8gnDd7ZN/5LRutOQ1E5pjoyYGEWccXmXpMf9Pw6PukCvuBqDYm2n1h/+y6MR1cVsW/iu5R8Tn8yhaYqM+ptOcz5Q0990esf3V8Mr8VENXBRI86TejueMPbZY/1HPPKzfdPAyJLTPTqQj/3UX/14WYlN/vteFYKB5sVJqo6+cOLlX2mec/LtR9zNn32BiCqi4l2xdccF3Zhk9fMEUZrP0ZbQJE1JmoQdKdbL9N2Pmvbxs/Ku3YcfpYNJnKbeaDp3gJ374XWtfdWrpBqBET1MJHlzsC3W/PWeaXt+nqqbu3uK4GoPibiPZobsWHmNt4Gy1Y9M2r03g1EDTDRRrlFjc8rFnrGyVfZ1iq/Gb4GBxNt2fPyzm+XQfzU2Pl2vVK7HQOihpjIImpsu4597NzTE1Jt6tSvWxGIbHEDV3FH+LVFeb5Jrqey/pkWMReIGmGinLWZ3x+F9vWcIVvyLPpzeholexPaBVqTLTS3NG1z4b73kpF/bzk3oHUQjR3SNHszlcnm1R59YGfC8VMuidsKJ56xmUyMdldyiQiVSIU0lASm/qhNsTuUJFK04ntYsEAiAVYNK6avJgeBbPFoX416cIoJ1HV0wBYmLScfGmw6d/oeF5mao1kvimKKpuJFaL/bcC6/bx1heaf197m1mvVs8kqLDE1te812XGQjBEhI6wnGcpElORrRCzr2BR6YDD0MFIpgtWBpmBjlZID3E0tg72flOOEAl4wjgHu4AFoUAx59dtx13NhnZf7fzx3v/PQjxlSVn0ONqRaLtL41tkNHDAtcY3IMIgBO5f9p2L20FTbRhMXqkgcJ5GBDNFbEAR6NshsUc/DVv/m6vJ+18712XLw2aGlhXi/S8Tv2WJrjd1yide19wQa7M532omrx4GCnhGA1BK4hzhTCT8FFZCDpixhVn7yk4sZ/nNLPJyCDBjyNKz0vSQtgTWUFCwx1bP1ZhzCsP/9LZ/hX6Qxkl19n6Qx+uWzpDNVzyyKdoeiefMzqPx/cD1pvrlkpbGiQFhdLsgXSQjoDP5eN/d0lVyfpDB6FHxb3WXPDeV/spCZHJwpX6JfXAVBpzIoKGDcGGnrRXTrD7JmP0/pY7vGO6v+p957gD3kGk87wM4dNdc8N1Z3RcjpDM99vH6ckWrlmtV9tffFd8t96TmdArQwjHx1YGZ2lM6z7FWz7adMOXmw9s0Sbe5OJB4z6SWdozApO9VwdpjO0q/st9lTn9W4Hp1uaV/QZ+9tA0hnQOc2I0HOl37YeYfDbTq0W8H91reMWvbF+pZeNJmUTvVG0dZ6/M1/9gwMusXMl5gmDHeJo8CvwuyJV2zsCY4uNV+h7Ya7bFLUcJ/KBKP17U71oXKJBhxnza1iHGaqr9JOLXL1aBi0uXwTY/dnRMd59hufrjouqfD9NitrDu2mi9ujlkjylLvKPd3vEDfVMsriY63WsVlsttI+pDgEKpR2EmWDZuapRMM4SBQgfF3ZCsQwMXyCnX2wfcG9d3/fpBn8zXzCj4sygt8Rp6YzfTJ2WxaKSAMs4en1l+yvzvWeVO9DmbW5diRYAe36VDTAwovTiRCnWDPg37RGmH2qOqDGLLk1QXbJY1ZNrTkzlzzzqu3fG1aVzq0pzaqLZPUAZLhGhMpEyFog6tU5cf7tBzUvnAJNUO3Dm3Vo2o5+5JDrn9Z7x9PlXLag2l1W12/SkWjr/OE6zPnQlt1F9Oa3pymYdCjzm/i3vuzM2OEp/bVSr8BQ2CbZRDaUYbbDrBVMMWxg3IAwLI/dqnbsTOu913D50uOX8AYeJtYbNYQ1POTz6hPReEQw4izRovtaaJw0GkCsqiaKPERY/Bt0cFvdcE4JBotaKSI4DlvzCFHXQ/pW6oDtzkd95APTnXLpebLlcpDCvtMl/TnwVUOBxA6wNDL0NaQjHDu8jBtBTZAXC/ylsWhg8jZaGixhSeqzDWufubnuIu6xKzq+RRgPERBuDtmSl6VSHXS/Jxszn3/r0c0I7p9RH7++u2NpraGltDJ+LfIcwG3Hpuo/NQWEu7ZFwExX1K0+3AqQhYaKA8ejwgJ0s6E83U47+Zfr24lzXLQcPxl6cOaIjkaZQ/Fzq9pcg1LpJuInBNowOtqhKPAgbZhI2MpmEM2aNPrbtJPWe/eGdl8OVaS7kvsWhEkGAiOMzXiKhsQVMDnMr/L4QeB8cs+KQCQKJWKgY5OFieRBHCrYpMvUtATnsz/KedP2VVcTqomvORRZCdE1og29GPGRUqee+BVzU0C6Mctg1EBpJiBg9eZl7cv3K3x34y+9+PfGgTS8novuMPojqPisulzSdyTSH0k5nGy4yDyKXSusyJHORCXmM7rOayFkrkZMRhhocWrTwDZ5h3abuwz2+80ctWDt5dtNwIvcbGyD0IR2iVOuzGKA1ihUtnzydOlj4ixr3iwwVqeLQSIUE5OAFXFqRxAH+TZiDm/sI6OQGimQk2jH8Ka3htkAXSKhY8AiwqY5UqJpWy+SFqTSTpLR6rc5TzIIiJzq9NuDBWaDRQZilopsq9BXQtQof+kL6RetJ+oeo7ddd40w21D/24Ml8UmACfiuawAR6uSygGMUKhY9yodqEMCxUBlMIn2wttdNJqAzq4FfPY6uDjygh32zwkJPJdtqBXFR++L5a34vcoo0u5rdJL79HC5A/P8YG+c1jOORbmCDXmOZZDYdcBzRPGlYmTvOkYWXiNE8aViZO86RhZeI0TxpWJk7zpGFl4jRPGlYmTvNcmnjm2kr+3247Jn71lviPq0GhvMHBSzv6yHxOLVDe0pj0b+t1rNXd3VVcNxkJR11/UZ2o/1qKw36eRBoG3UU0gEN1yisyzDZbVzHsARQEm+YoHoBuKeE+E6MhqBfeJ3NYS3xFCjh0f6TuJOsHJteRfHTvQ3N2ncdFcjUL81srom1oeokUqgbgAX5h5gUNrFE0tS+X67319oEQ35QvN0sTayMZJHIYr7QGCewLf+Ziy24RxSAt4CL3qAF/NqxqKykRqljRonTMSDL9vsMS37RfW6uPbldoo0VaxPT+Pp9Pboxw3SKd6x7DjczTAkq5rCil5mrWK76lHz6v0MmGYoZPObjVw7lnzKGS+cGH7Zd78vjRd8aLJofMdNBnPLcAG0T0AbmKPOS5hvFce2X0EEIUoFIEA65ABNtEC061mae69Yr6w9uYcq/O6jqeJoYQtQQgXWUFKVfDuG4TZ7HimyuPqoqHDBpYZDZQLQPX9vS72dttfY2Ba3bZuxgRo4j4c6lRRKWkLNDZxorOylzcMdqKMCyMrwb48I1af+MtX3fWda2vxxDqQTx1JTRiALchMZ6rpLqFSzWqQ0fO2FA3NqAubCO5SBJc6s7SJlN+4iKyI2UQpr0rONannKvEdW/Ea/mI9JhaxMNONB7LsKwThCUeIZNMXGmteBAXSYBg+dGOsc1cZPYRjdY6MxQsEZhpzFBFeJV3n/w82SWn2abm1ZtPGkG0RC7gXnqgVES6dgmC0FHDAtPwI5otdiWH0MixZv2F0IClQccIDKFRGxrX4EFoMDu0jckO8Zqdbd11xn1+iuva9/KuVvXI59DBglCO4pyG5rycyTVvprgPj/ageSkCTogoHF4SycQB2AKpllkiZ4uxvCHdSbmKWF1cgef080w+ys6h8cnL85BDZzQyVGZoGEpxuAteh/Zbfn/RNWaTVZhb/GKHtvd3/ya1gEQfQHWRFJdLmnPkxLnSzjmEi3yF8GxjKhHx+IxGbBJTxfuwVQ4bmzhu+ub56z2XXQgxzp7fYhwx+qe4nxr9w66XhM+cPw7PNmz+7bz01uN4n4IBG7WAz0VWfMDw0QfDwBglbkxQANEDIf9oVlrctJ9AFiiSsyntts3bUfYPE72XbWqdwXvTaDNRaYr7qUrDrmvdWAKtbGbVyjKD0kpRDq4VjZavaqjBCxUJMeNLq5jF0x/caBw4gr91+Yq/Ny+sO56oGG/0fqpisOtaV4wZT2FO4DEjdb9qy0MKzmi2IbNWYoBuLCTikvB4PvpxZ9c3OdxZ+dybrcdfdiSyanmKB1BZtbigLBA5xIpI0hl8Xd+OMKzru5Z4fRravZvH7E+/5MZHCz4Sdaz4RPXJMD2UOwziAs4JDxIHBAG3EuYWCsLCYIkEJSsGW/7V23yQE7/p3pc6JhXXNeCJ9juD8USp7BdwtQt1XdcwAm6DuRpwsRcrqt7AFCbFm9C3n3rYxGr8b1PXhGmPl27YZX6YOPiYHBulQNeL/yAu4gcxbENLbVmJYqiRxerhg40oRZ1PQqIW5AOFKc4HYG1B+P9in5IzyWcK/VAiref6LTP6CQPMkhYwUx4EDJvMO5gms8EErsijSUtNs8lhDi1Err6cZotcPT2NY76TCXOfDNfzp5BjvKghVt3FLz1rEMtQoQ3qQyXiADQtjGpImZC29gb+AFie5OBOCSeY8BS17CS51AXba1GrYxHl6sIZx0XyLuajZ8c0Bzd5XCT+Yr6p8jQS95zw9aSKB7SlBF3CT6qEXvYQ4mNgsPDkwnI5lZ2z3tbxNm1R6yIuL8cgN/FFzQtljBgrrjM/WPE+6OvCP2HbuNVzFcuAzYHsBJTMRNQXrX76LXHeHF9utdfMjGMnJ422Jg6bck7U2eFEmR3lSLMjaeETq0On7X2zhl6tP9hopG9pZ8cyLpIN1dmGlr2QzEXSLuargFTSyVJ9f1GAFFhoTVAqbDbmc7b1dueFq5emv7z40pSIEpeKErdElCpeXfn2p8DOY6t1J6vEjZ8aagGleFaUoi/mY2NQOZZY2S6KAoTQMVIDIDLrnbiGKR5FXcOw62Vx4I2OmK+0B03fUKQwe7rrP2ZPyfWBdGRPM8+y2dMFZ/9nTzH9TN4wcIfHxz1ey++MmPTTfvJjLdhTct0nLViKfWfZLEXK2bK2p8HjGiU2yu7Fjb8eGnKzZ6sdWrCn5EMCLaC0gBWliLNlaE/Ja6je7Sk6YhjtKUAKs6e7meypwewJyNNJO2S2juWs3sfyQp3TPzsG7boaW+rel2BL4HCWbUtQXwn5HibINSazVcch1wGZjaaoHm7qaYrq4WQ2mqJ6OJmNpqgeTmajKaqHk9loiurhZLavprvuFon8XNedmHs8eFPRWBUym12DbmHBzcq7rvjs19B4ULd5KjULr4wZfH9bvY2eq6vPjD5tL46g8NzgH9GfP5OK+GmB57ZXa0PDRIdD49+Vs6Sp7YjDTWYKUHRixKQTcvVELehkH5NO4p9/XtOq/wL+gdO+R9z+pNgSi3wUZ68SFcMWqbIoLnQUAitJYQ+oQs2EreHq29fbqZ+d7aQ23fpOsW3p21wtb5RcQbIiXxowViRU3sT0Fah1SoplajeockI+5AML2YnHcDp6PZ/GKzXC4KLxSlFHh+SVrvwVlbV28SCP9E1bfByftLitLa+Tteh2MRacCQKZWDBKQs806hPa8fSKJVmO6Uk8k47PTmWxoz8AexTHl+pe+ZboXpFLe5Z2fYtzQt7mY+4V9ZjxkBPUHtm9YvNCzYvdq+KBTovatbFWth/HI857pjS9c333lw+sqDG5WnSHhKX1snrxFJDkOtJB4sSDkGA2ZD+TDUnIfDB4zuOvHlmZ+7N2j31IzDCu4CcIEUmotaaZzIedEycU3qFSMJ8TIpWLFGXN5KIIOUdRZ5p+dJJKyNK8ijp+lol/gEwqkfSFvjK8WJxsXtSbNEZ9Wte+ZLU3wHHX4lRu10n79jKNUeP+YSJZP/D6+Mc2cZaOhzMjQAKLWsOSY0KxHPvuYG8D46uFURtJesSrjlN5Y07Ig5NAj115SNQcXhVvgSxQHMIXjSYMChPF5b6w/ZDq9cqK6/2koapXiYPB2X+sk/n9k/nVUBD9ZDBjWS5WvFUl/K3oFmWZINwjRAgL/ilHe2V4EQZ9VS6hpwQSrEK6wvjDpkZigYQHq9ApVVPRXy4TCYKVvxsNlAlCiw2IYqimMw1Vg9kQkAsaaylIQB7/WtgRDDvFtiPgn8LNQ4bBY05eTgw3MNPjOBvmLY/jmGcyYa6xq10V0Z2rTVMCHHe1aUqA4642TQlw3NWmKQGO78ImfnuZVrhuBv/ggw6XTm3y2ELxwqFFpR0t5OLhWvDCDzCpy0BbJJKLpOusRaJPAVuLxKe3yrpForCJZYcZJ975bmtXqd+djn+JDKBFomcBW8OpTgUG0Oft0qVLOmiR2GzI6nThzFreieaDPthYJswxiBaJtqzaMTME7eikRWLVT096/nX/qMusy/PvH1hlRGwqra8Wid9vsSkHWBP9KwfRZ4vE6NMNO/z6G/HJPu6QWiNxA7F0or5bJF5mVV62fpRnmC0SpVfOrS26WI2XXUf02a+xZTM9t0hMY9VcvN41B28qsxaJj2/MP/Nx0UPv/Z4Lpk+dMOaqQbRIRH0IxhaJwBBifmoWwuCn/pdaJJLb+Oi5ReKdArYWibsKdNMisUVtPq+F5w+XzfMDLDumcIi9v7XRIrGa2L5fbOU3vOV1580dMnxyVS20/btZwNb271hBWbVIzNif+iDg1hLnQye6FBnXlxqVfgqTsCLbCC1gtYsVq0Td+qH6bpF4kMmM/a/Hx7/q8UHufqazHh8LbrP1+ODfLoseH68e5p768L2LV/ro3gtOv08q1GIxC23bSGMuEnObrSWC/LZOeny4eL71/f56kePhN9tuZddsTCwtr48eHyNZUQHjxmD2DprlFWqvx0fi1wWnY8+U81kwffK3g3WHTjSYHh9dWFXXWD+q03mPj0knarY1/XGBH11veKjJnMlmeu7xgVoZxiYNwMrorMfH9LhqV3ZmTPfYaPTcvso5pzsG0ONjJCs4/Ns67PGBjOnz9tvcLc7JvdLd4ybVSTeEajkAoS6sCIE5jflthxAGv83Fyb7Fn55XnTbfq7/lctK79sQyJWiOcKhUAlZ0qs9mzIBzx+IQibj4fqzUDkBcJh0fGMRRNrnWpFQMuSMs49tSi6qoCNXFNzcX6XcP4CvgwUMXMr7NwNV7pc3bNC9+LUgTUmBB+9W7Hx7dak30fV52avjNdtIjxDqk/6o1IMmFemnX2OZsrRfeqz1XCSZ17TW1tC5UVC7iB9FrwKMbnSu4SI97GrlQVRXTVygKlIno/Uu/Z21jCl//5ZL4o2hID4e3x0kJmOiNNAmYiutan53g+9uxfn/ze/p2lpQjUwNHCb6yWCoUB7CUzjrU6tzW7DYxvjPc132IjPzbijhW8QdQx6pSUhbKQFiV8fquQbg/iCYRCwevEKkcLF+CAHh2atemJ9iygp1FcEtO254BQVKZsCWnXc+wcTI5+gu9t3p3Qa/Ax6P2u2wfPH+85/aqB4nrGvwAf3mkhKa9brGoLJR18y6bso7pR1mkmQMfpZG3Wrv4oDtkvGxUGMsMepH+/tnfk5d4Tu+9bufL+XsOl2arXFp1tOcpDDnMJL9IUYcrr3/He5p5qZglZ/G2ijhebnl223znnZ7isumh/yz9bnsBADY4ADdpAICmRSNPFF/KmGvYbNv5M/VCw90uCTZBby82fVuLtJTpuJYAAODpXRYA0k7fxR3Nw8h/i4/DezQ3YsPMbbwNlq16ZtTovVtnfJxR99n4ON+pnqWW+Tibfnu/dDer4LXE06Hd++ofAwyAjzP8Plt00/O+AZAKMjMzdcDHKRzwTTZk1U2fNRH9nyV+865mEHycTqzasTUE7eiEj9O+iLfA7+0hrw3L824Gf9kbaRB8HDNW5XzXz07DgPg46/3Pb93hM9ljcb3UlY7BqQ8Nio/z9B6b8i7rfZtoQHycN5kHpRWGN3eMLsx7s63TnxQ983GyWTWXpnfNlSkfh7NAGv1kLJ+7pkbDnOGeVisNgo+D+hCMfBxgCDE/NRv5P8DH2Si3qPF5xULPOPkq21rlN2/QMx/n6X02Pk7Wfd3wcfrcq3JkWe+7LpvH5fce0JM/UOt8HPLeXAsck8L7bByT8/fLio/z2an+NIuBp71jl79bFvAzMU3rfByyjdACVlmsWG3UrR+qbz5ODpMZG5cjbiH2SeNlZPtKnj0e+o4YKekzHiZIuskEoUHUNFINwheNncVhoTBFTBnNiWylSCXlCGBJzkD4CbQjb8uel3d+uwzip8bOt+uV2u0Y4/tRIzmqQsr4q+wPTJivar4Vzaj8l0nQyqfR8GmCYN0/Cx78RxyVl64iXPPA0/mm/iIJUJhI6AHsegT+OFStClXmMqlS48Qze+XYLvvEs00uHazNHa7ylodOCcgo55yoknh2fWX67smXZS779nMjCoUxhSqJZ9eqx0rmWb1xPvReJOuVeKynSuKZd9tH/in2y1xWZczcPqQws55K4llMZNK0wTM43gtOOoxo/6nHD5XyH/VeHI8X51u75BysfHv6y20XVcp/dFq+HOE32uux5fCg2Isf3Lgq5T9is4dM5Jx289k+aUXgxIMFn1TKf9Qbva5Loy2pbrtsGn6IrvLXfSCqjIukq7Ns6s9wXJxwrabT4QYSIKqCv7zV8IvBT0K8N7Xpt0U+53Z1IDLBRDv8X7t+PhLpE7NhxI9e34fOB6KqmGjgcOnCr+nhTqkCfpcN0n2w4oUpJlq7pvGdaesGOM+Ib9HMu27NICAyw0R3vOPCM3oe5s8aef1e9Y6LegFRNUxUZ+/Jq1F+t9znD912r13u5lpAVB0TSasmHD7as4vT+uaBjT7vtrEAohqY6H1Iz+prxg9xXbf3rWfN6re2AlFNTISstPO+2a+i64ajx+b7Dpz9NxDVwkRbyy2bFFrpk+9u66buO9OfNAYic0zULbnG8UX2C3xi74w+/32K9yMgqo2/xsPenPA39Z33xVQKuN3z4C4gssBEf0bbvWsyZrPT7NmTPd8Ml7gDUR1MdFiArEg909F9Xt8GT326Rn0FIktMNHba5LE7D4z3mrNrwd8PnlzrBkRWmKjjkzc7ozxzvOcNmd1ubd7zF0BUFxPNHyf3GTajBn/WkPHblkSv9AUia0x0pOLLC5WizPl7OvwwrpI57iYQ2WAi85Getu27prke+vVA1lDsvAyI6mGiqTlTM+PjJJ5Ljx6zOv3gNES+Pq4vsc36RutveBz668QfpwdecAA0wETn3P2OSj794xNjO85K2i9mBRBxMNGjGS8ipr6s7LTm5Nls2/kFrkDUEBPtne5S0eHWes9Dz143Hh/QyBaIbDFRU5OPrttGn/de9DLoclxQ8C5Kiia0W/TspfOrTVpFT/fcWvBj2IU/ph9ojI2mKZpHmAxb7dEHdiYcP+WSuK1w4hmbycTNXCWXiFCJVEjDO2DqltwUu0PJFEX7P4QFCyQSYLqw1hpqEg3IZo321aino5hAXW8G7FNCH+ZDq0znM9/jIs4PNetMU8zDVLwI/a7BfunwX4Ka3rNWckZwMm700iINU9uusR0XkUCAhLTuXiwXGfRQIw5Bx77AzZKhJ35CEawdLg0To8QL8H5iCewErxwnHOB3cQRwoxZAi6Ig8UWey5bPvJWSe9IKBTariIFT5edQA6fFIq3vf+3QEcMCV5uHBhHlppL8NOxl3AqbaMJidcmDBHKw6xkr4gC3RdkbjqW91wHzvgN/3HY+3KF/i86P77iQztixx9KcseMSrWvvCzbYnem0F1WLBwc7Jc6qIXANcToQftQtIgNJ3wR5QH1kW6cknwX3q93v1vClU+nJR1oAy5kVLDDUsfUnD/lfzoI2cxbIfr3OchbqFrLlLBRotlaqmbPw8cvIiI9Xr/ksvnbF7WCjms+1uFiSLZAWchYsCtko3uULdZKzIONV9Zj/1Mdl0e1Ko5f6zW2k95yFtw/ZUCnQz5qoRnxFdzkLv9eOXzKmtxkv3ezu/oerFzU2mJyFfFbV7TFUd0bLOQtX+tsMNg6b4H4orrX91jMLZ+o5ZwG1Moykc2BldJazsHAFz2jN4DncbM5QScf4JGKZBf3kLKDGhhGcgoc6zFnoUX+Cz/xre1znGQ2u9HZAxDADyVnIZ0Voj9JvO4ow+G2nVgv4v7rWcYveWL/Sy0aTiFo3Rhtp+jvz1T844BL72GKeMNghjga/Ar8rUrXZKzC22HiFvhfmuk1Ry3Ein3rSvzfVi8YlmvSb+oL1m6K6Sj+5iPmXMmh4W7NSyzPikF3cdSeTl2dV8KtBCs3Du2lC8+jlkjylCw9MHMztbLhJ43s+2zuhykBtNJOCAIXSDsJMLtLji0YRN0sUIHxc2AnFMjB8gZx+sfU4frjXi/W7nNa0f55z2jkxjzgtnfGbqdOyWFQSYHuPNK0T3K+772LjXadNO+WUuog+AMyOFTAwovTiRCnWDPg37RGmH2oiqDGLLk1QXbJYVaent32HDTjmttKj5ZL6kws/1URTeIAyqNWYKzpx/e0GNS+dA0xS7b6fv5PfPnVyTcjuFXVtYuNzWlAtwqra158Nxz+O06wrZclNleW2j8YMsbVySzbuu9HWMStHf02Vq/AUNgk2VQ6lGG2w6wVTDFsYjyEMCyP3ap27Ezrvddw+dLjl/AGHiVWDzWE1Tjk8+oQcXhGMKos0aMXYmicNBpAraoKijxEWPwbdHBZ3YBSCQaLWikgO9pX8whR10P6VuqA7c5GTjwHoz7l0tcdzuci2x6XN8HPiq4ACjxtglV/obUhDOHZ4V0GAniL1D/5PYdPC4Gm0NFzEkLfj4XnDpUVwhFO8VYT8Y/t3xL7NFdEGzTR9K7HrJdmYL5GHzwX/nM1b1rPNqGY/V30srY3hc5FjEGYjLl1F7DkozKU9Em6ion7l6VaANCRMFDAeHR6wrw396eboHl07NzD/7rsmefUUk/xsYm87k+LnUre/BKHWTcJNDLZhdLBFVeJB2DCTcJzJJJwxa/SxbSep9+wP77wcrkwjHnOb9hWFSgQBIo7PeImExhYwOcyt8PtC4H1wzIpDJggkYqFikIeL5UEcKdimyNS3BOTYPst70nVbVxGri645FxkE0TWhDb4Z8ZCWpZ77FnBRQ3uyymEPUWgkIWL0iSgmlqcffyrPP/D11ujZogntiO4z+iCq+6y4XNJ0JnMZSjudbcD+AiKXSusyJHMRx8eM7rOayFkrkZMRhhocWrTwxdd0S7GIq+C1Iu1Av55D0v4mEryxAUIf0iFKtT6LAVotWdGyfKxTBwt/UeN+kaEiVRwaqTB9HLyASyuSOMC/CXNwcx8BndxAkYzELYY/pTXcFugCCRULHgE21ZEKVdNqmbwwlWaSlFav1XmKWVDkRKfXBjw4CzQ6CLNU9FaGvgK6VuFDX0gLxbvs2ctDvN+6Z7x/8MKm+qUGpMAE/FY0gQn0cllA0ZIVCkvlQpWPMCxUBlPSnmwttdNXrAwq2hc8Yqtof/oRDvkJw4ecxKjTDuQd3o9KnHSgpuea5N6fTlcTzdQC5HueskGe+hSH/CQT5BpzOavhkOuAy0lDvcS5nDTUS5zLSUO9xLmcNNRLnMtJQ71Ucjmp1Eucy0lDvcS5nBK/kxcrV6nLW+sZMrvuV/4nCuUNDl76TSiJtKkFytspJv3beh1rdXd3FddNRsJR119UJ+q/luKwnyeRhkF3EQ3gUJ3yigyzzdZVDLv5BMH2N4oHoFtKuM/EaAjqhffJRNUSX5ECDt0fqTvJ+gHLBcNLN2nPrvO4yLxCjc6urRXRNjSHRApVA/AAvzDzgr6Prng0WdrYOfPQqC55IUVDShNrIxkkchivtAYJ7AvzC7Flt4hikBZwkc3UgD8bVrWVlAhVrGhRGvppYs6FcjKnrEeJTX0zDpbXIi1ien+fzyc3Rrhukc51j+FG5mkBpXmsKEkKqYcPbH5aSz98XqGTDcUMn3Jwq4dzz5hDJYG/mvXOTmzmEn2h42oTr8bV9BnPLcAGEX1AriIP2aNhPNdeGT2EEAWoVLqAKxDBNtGnePq07vzj8h7PzKZbk8vxJywyhKglACmJFaR5hZrFdZs4ixXfXHlUVTxk0MAis4GaUKvP2MGXl3pvbZcx/6dLK2KfO2P8udQoolJSFuhMYEVnVCHuGJ1GGBbGVwN8+Eatv/GWrzvrutbXYwj1IJ66EhoxgNuQGM9VUt3CpRoVmyOnZagbG1AXtpFcJAi68GdpMyY/cZEej8ogTJs9f+iV67eeuu516B9muaxlVeJhJxqPZVjWCcKSrDjZxJXWigdxESEEy492jG3mIn6PNFrrzFCwRGCmMUN1f8y+kZXM8z2Sjo94tONLfhzRErmAe+mBUhHp2iUIQkcNC0x2jzRb7EoOoZFjzfoLoQFLg44RGEKjtjevwYPQYHboDJMd4jU727rrjPv8FNe17+VdreqRz6GDBaEcxTkNzXk5k2veTHEfHu1B81IEnBBROLwkkokDsAVSLbNETgljeUO6k3IVsbq4As/p05t8lJ1D45OX5yH73mhkqMzQMJTicBe8Du23nHihtYXrzXWOsePKrcnavnMc0UVCH0B1kRSXS5pz5Oy40s45hIsUQXi2MdWBuPNGIzaJqeJ92MqDuUzxE1xcupafHTBB5Gob8xcx+qe4nxr9w66XhE9X73GFvxI/ex/oeefMyrxX77WAz0lWfMDw0QfDwBglbkxQANEDIf9oVj/ctJ9AFiiSsynte+RS352Zrt6L+341TVz5nEglr6i4n6o07LrWjSXQSgqrVhYYlFaKcnCtaLR8VUMNXqhIiBlf+kImKyMHdQr25M5IrTjItANyiKgYb/R+qmKw61pXjBlPYU7gMSN1v2rLQy6/0WxDZq3EAN1YSMQl4fHtcyfTQU5mXjG/P7eq37pDQyKrlqd4AJVViwvKApF9rIjEv8HX9bMIw7q+a4nXp6Hdu3nM/vRLbny0gBg5wj5RfTJMD+UOg7iAc8KDxAFBwK2EuYWCsDBYB0HJisGWf/U2H+Tsbrr3pY5JxXUNeKJ+bzCeKJX9Aq52oK7rGkbAbTBXAy72YkVpG5jCpHgT+u3tk28VHN5WdUvzd/p6Z9V64mlsJSbHRinQ9eI/iIvwIYZtaKktK1EMNbJYPXywEaUo5klI1IJ8oDDF+QAsIAj/X+xTcib5TKFFlLye67eW6CcMMEtawEx5EDBsMp9jmswGE7gijyYttb8mhzm0ELn68JotclX4Gsf8PBPmPhmu508hx3hRQ6y6i196EundZmir+VCJOABNC6MaUiakrb2BPwCWJzm4U8IJJjxFLTtJrmfB9lrUElhEubpwxnER+w/56NkxzcFNHhf5/T7fVHkaiXtO+HpSxQPaUoIu4SdVQi97CPExMFh4cmG5nMrOWW/reJu2qHURl5djkJv4ouaFMkaMFdeZH6x4H/R14Z+wbdzquYplwOZAdgJKZiLqi1Y/YzvVya9w6Sk/rv9tq6f7E6cT9FPOiTo7nCizoxxpdjSrsvYd0mCcd9Ld3gE5F4qOlnZ2LOMiTaE629CyF5K5SM0P+SoglXSyVN9fFCAFFloTlPqta2neyfeLz6Jl11Pah11yJqLEpaLELRGltYFj7V66jeav6RFUodqBLylaQAkMaxaUXr7Px8agciyxsl0UVQahY6QGQGTWO3ENUzyKuoZh18viwBsdMV9pD5q+oUhh9vTCf8yekosA6cie7nrLZk9nvv2fPcX009/12JhZ9bu4ZrhOqH5hxGCZFuwpubiTFizFtrdslmLl27K2p91M1rSKuzHFKyFo6ObuSUYhWrCn5EMCLaA0kxWl0LdlaE/Ja6je7Sk6YhjtKUAKs6cXmeypwewJyNNJO2S2juWs3sfyQp3TPzsG7boa21cLWwL7t2xbgrpKyC8xQa4xma06DrkOyGw0lfNwU09TOQ8ns9FUzsPJbDSV83AyG03lPJzMRlM5DyezzX3f8v21NfO9olu12jx020QXFTKbaF6574HC/p77h8mLnvXb+FalMOHcQhf/Rh0uOG51vNstpGPQUArPDf4R7cAkV+rTAs/tstaGhokOh8a/q1lJU8ARh5vMFKDoxIhJJ+QSiVrQyRUmnSRkPhg85/FXj6zM/Vm7xz4kZgdW8BOEiCTUYrBM5tDOiRMK71CpaM0JkcpFipJEclGEnKMoBEv7tck1HmleRR0baeIfIJNKJH3hOgcvFieKFvUm2c+ZzeN9HjY+6rNgSeySww/eP2Oyn8b9w0SyfuD18Y9t4iwdP0oCGV6w6iwsFyQUy7HvDvwSGBspjNpIUgleFpjK+XBC7F8Bs9uVh0TN4VXxFsgCxSF80WjCsmmiuNwX9gdRvV5Zcb2fNFT1KtF28/+Mdapg9yq/GgqinwxmG8rFireqhL8V3YSSCcI9QoSwWBcOb7nK8CIM2KhcQj18CVbCWLGNgF1HxAIJD1aQUlm+5DKR4P+xdx1gTXRLO4Ai0gVUVISIiCio2LuSBAgldLtYKKFoKIagqKiAihQL2MBGExUQxQJIUUSl2LuIvWIXsXe8u5sNks3uSi6bgp/f8/zPf80xcfedOfOeKWfGr+HPrSay3QIbvgOr6lUsVZUaMkd2HCUowIfUfwLYfNJLPDa3eslj82tSjzmylav0BlXln+Jh/qnhOkAVFuZC06QySXw0idKjl0eTKD16eTSJ0qOXR5MoPXp5J6ixdDPruimxlkVXH3bcnOy9XYBBQYuKqi3I7r4EMOh1LHFJ6QwzZBdjsc0wK/qGN8PM+ZuoZ5jl9Yw7cjHU3mqd80lOwMSVZCmYYZb/DW8iTNo3KRjEdOrUKTHMMHv+iqaolv7KpuiUU+KhRQOMpGKG2Wpc6SyQBumIZYbZj5qD1v3KVC33q9WNZSYW8Vc5SmqGmReucJylQTgkSc4wSztzLdQ52cluk+yVjT6fo/pL1QyzMbjC6y0Z4UnnDLMlz2NXyk++Z7G0fvLT7tsqSBKeYdYBV3KyEpcc+CWRzTArLacbdOkiY300Zc4WPcar4VIxwww6Q2DOMAMMIXxOrSZhnFNb0gwz5JwNCc8ws/qON8NM57t4Zpi16tfhccyuE5SIDpmHtmc/4S8VJmKG2cJPznkLrqy1KuhzY/Gl9x98CZjLZf4dby6X6XdRzTB7oT4hVu1RgM2um6oP4zMPrCB8hhnSRhCAlQ4uVgrf/1MzzG5gmbF//fn/r/78yPFEYuvP/+U7Xn/+AkHbSUB//sAx1sane16wzT9kHLDvqPUBAi+iE20jFaikD9/x2pnfF7SRoujPf+SLTokipYdtltqQ3psK8/n7z0qiP/9ZXFQKxGsNcX0H4e4EEdefP/jegtfTWCaM5EtLp/bvPpG/J4ck+/On44ouTjKiE3t//oFbajUnKkZbrjvq5u0VNUJbwv35ISuD2WAdsDJi688fu6vNzQ4yaozkqrj7bQtGt5eC/vxnccEp+C7G/vzhAekP1st2pYcV5qSPVQ+qlIZOFwBC6bgIAXsaPrfdJGGc2ywovY1/jb5Kybirm3k56c1A/hYD0P2+wAAWwOiCZzYFDJwH/06R+P7+PtwmA0CcHRDs7UNumEIrTJsH5MhGzKcVbIjQaLGp+JaWkm7WA/i60cCgCxLfnjRSZH1z71xp/X4s4FMYC9RXv/jWa5C3TYZDXuUpg3knL/HPsPu/xnohjlB5b29VX1NJoKwd29bFeeSM1OYeocJKSVUgeno0NO1MoJKO1wt1hFLmbl9PpjebiX6+DOo8eIS81z2zojP3CmfvbMMfSpE3h76IcnmK+znhuxN4/72477+5XtKHpQbNFOKgBD6yb4CnrwdO2xuF49Pnmfh/sd+udenV6YUGd/h1lfcDgrrasCIKYUTiCoMtGWEgjz8kYTIWfW39AzgAfbl5gLFTI9PRgMsKeBZ+JuT+oz18AtieJuQBo4PmsDnQH9BPq7Ivi9Tl5+6yyuHI3WTXHKHx8xr4D7hw5rNQRmP+XhKFsKbjCstGKnYO+FNCnVbb/w50+wez3YNwdlCsUkZ9wXtZ20OD1U22UU/oN8dVbq44BtK4hhy8BXpRQByWtPHF9cKdUmFLjnPaOtf35VONAluHlR5TAo9r6bWVrNsLAJDGA6AaBQDQtAh1EuVRGXb/iXNHiwd2u3nKpmCp/Hf9jyWbEFQm5nvAAAAsPACyHOt5B81bpJZVj4Oc9C22epwnv/DqcRb/EnU9zt1W5853XjPcclfGm52muXO9pKAe5+EvvOzm+V9SUFSwb98+MdTjqH0yuPFGbYTdrq9Rlh5es55IRT1OEa50dkqDdMRSjxO08E2/9LJUh607B08d9Vmht1TU46zFFc5iaRAOSZL1OEW3kgpm9q01W6GppF73bF+EVNXjzMIV3gTJCE8663FetXL4HqakYb58a4cfZ3a0/SDhehwqruT6SlxyIq3HeW0z1ac85LRNrFbhw8QPowdKRT0OdIbArMcBDCF8Tr1N+gvqcc5ZOZ5gffhsH6U/p1PAuKgECdfjDCZV4tTj6JEqxVKPY7ipwsVkyQyLjVXGj8sOyOUTXo+D9M0JqDEZCCKHWWPSix85AutxnJQMX0+uHWFT0ilq+KG2lA+E1+MgbQQBWOnhYtWeVPlfqse5g2XG5hz1Nfa1z6IdKnFgPX089Q1/psQpGLwgSWe7BfoIXiMVIn1hYO4bFAheEWvI5szvw71KSnYD2+l5g/8CquY9Wvo8ZPGLtpRtJ8+W6MfetMR8PsFMTuNFAf1r6wKYMIfG961QtBJ5uamJWtnwayj1ND5gz64ONPD/+LXy0lUSVc3rVYWKC5MFCIzpaQ3Y9RDez0Fi5YryLpYohb541rtBt0V/8Sz/ilG3n9cWW6b23Xj245sNsxtdPEseU2bSMU6OWuymn/1Ix1a70cWzxXMjyEPlR1hHUwfsLWKMYzW6ePbiqVJh7/Xf6Qdfetos/GBY1+jimWuyoTq5U6ZtzE+5h/bnXvk2urpPr6/c5LugzmFltUaWndajWY2u7t8YupEd/6INI3aKc/ZWWvDmRlf3sx5Fp9rvO0DJmRhiahjkcKTR1f3RfhlLF797QU8LvVzeQ71VIrDUFl7aMDelfFw3VepR9laTH64OO4ElRXjJsuOuzH4p3y0TI2MvZd/d4AAsKcFLXTnag95eZ1Oi7si1z7UdAt5WV4aXhnW8IqN5mc04oDkmsP2TOC1gSQVeclplWTc9sMyiYGLCt12/nKKAJVXee+le3mRlfdc+87SsgdaLDgOBJTV4KeSu0Q6LxR0pBQ/Wf38Sn1cGLKnDS5e3LPqlcijKMkrFbZzmZNNIYKkdvKRePWohM07W4WieVzBHuewRsKQBL71580T1WboCLX5wXYe3SXo/gSVNeMnexidlye4g+9Rrfs/WXDl8HljSgpfMDC0cnvRPoORMmzaklde4G8BSe3jpZbuaNQM11lhnfL5id/VTx1/AUgd4SeNi+IuVz485rJ14Z5nvYVs5YKkjvLR+14jywuG9Gant98hOV5FJBpa04aW+y1Zudz/xyyrmTQF12M/LO4ClTvDS5LGvB3D0B1puWHn756oj7UEpd4aXljqrDtA4oGWVNTXB6Ioi5yuw1AVeslrHPnnySTI98rXCits6p08BSzrw0jgDNdWA9zaUQ9cLD3cgaYMYdoWXElQrxgyLHEQv+LimmOXd2RtY0oWXrFNGvEooGeQQX1fiPHf63nhgSQ9eeiivtljLx5qymSM7tedhvwXAEhleOnd5xgan1o/tdlOK6QcTMj2BpW7wUr3qtZIP8e3py4zbTxpwddBbYEkfXjp9Y73K6xO3bbawP5yJP0H7KHBFE7RbqHbZgFn1dHffc/Zh045cmXz0dQwBVzTvYRm29l6FOZvLT1lszX644IxOaAp/CNIiJJAV4IlSd4A16dQQ/kZDpSjUuz3Iz43FAkwX3Ba/iYUGSLOG+miC0VF4oamnGcBPKQFPM/I0tDPzXSopQ/DMjDtV4ncdJvdBUN9t2/za6WyZWWYb/daFGi7UVm9ObknER2MjKukwCJAn6nFvFZV0QPBojBeRGOwMHLPYUMTPkwn2/Q0I8oUKL4Dn82WBU5wb9IQMnLvIbqCj5oF+M2hHYOlZRi112+Jjbt1Hzb7Jnzht+HcEE6e/lwj3f40gjcGBK0m8p+OmF/kJOYe0D7zRPH+Li+PjxgG8ntlMMnBsaZjrhJ1hPS1/I3gOw9j6wEuDDp3H9yMjYuzwz6LE2HkrhEvvE6zs5mjSC9OkgcoukGcVErhuvHIgXqibiQQSfZbr/dyOmksOmR+ZlLCz1e4pac0vPiIArAxcsABVh/nnPgmDf/7dWfi/7iwgz/Viu7PQTqYS587CW+G4sol3FmSiwqtCc1MpudsYRRONduwnkCyRFoiAOwtqIEKYJd6tZYQiy//3zkJpgmaPae86WCydsGv0+PqVIRK/s/CdhIfKW8lwYhPyK+K7s3Ax32LOVZ8Y28O3f2x5uebGPqm5s/AUV3R3pPU4Q/CdhV0TvT4Uhs+3yFlcsy4qIQ4xYEnsdxYgK4NZdA5YGbHdWRhJ8nXPjxjOCK/LDRvY/Qx/Ll4ydxYgY4MJzlvEEU6kdxbWqb0he1G9bXPbqS28YK/VSkruLDzFRehOw7ntAQnj3HZqixvj5/CO9Iidum1edF9Ywn8ahYbguZgzmh44oPLPoIRPwoCH6AX8ETh3zW88qBEwtrC+gmcv+Oi2qGm3FxBRT/TnFjxF81aEmBVTpVjJnRUjeFT6QSXlKwoXVmjSsMpTz5z0NI1vmsXItL5s6NZxKCI1D34bJTUPffynk9KSYV6DTNIr6IkzmBpPq8ZoEDAI5ioIUCCqEhZQSacVhcq4aUMA8fTCyNOXDagvsI5Otqa0MWe13gfbHF6r99JxjPNq/m1pzvuy4Lb8vfQnwBwXVDMjZpZTs1S7bOpEfbeOAMBKcQEDNEoihyguZ4B/ZyAJ6z/Bi6AKOLJUgmSJY1WvOlzWvfjLwDyenRb8WU/3qQZ0hQcQhkVIIJvZkPCDDrUUqovRpF7NOwAjREuZoz5wzpSuFnGfk1dy3GvsCRBtNq5o0yQkWrTzcZxwE+X+PBD1/bST8yJD6iyyB/Re09qxzwDJDURVpHFtEjgQNVDAaANeL7DFYGJ8SMIgRurVjnfmDj1otmfqdO3YCUf4uwZrgd04OWDoE6zhZYJZZaYQY9T60QL8AMi5PUGhn/H8/TOQc/h7eponoCRNYkRksu/PDywgDtS/1VTQzakkH1kA9GdUtKlqpVTSFFnMopUmRtwojEaggOEGsMsveNoI8Ccb8SaCAehxr/6B/4tr04LAaHTAPCbGvZ0p33qs+9opkxIv+6N84vmbt/ltDDRcFWXmHPz5H21M1fKa1xl5ZrsLbiuH64ZkNdfGMKgkLxDmVlS0OWIrIJibGxLu0Uj8DdEtjwD/IKZHMKQe4EwKjDF2hlUuskOH2WVUMO89vDdrMH8twu/fFXR/+RYJNwnVMGyuaLCFtaGBsMEm4RGWSTij2v19/yEBdpHv3tj2vbLEAjmBOJDl5sEk2wezWCi2AOvA3If3PX/we6DO+vrPdWP5enKVfJ4vx4ccALgp7KZbAmRuH+c50SYlN1puKrpaVJIpiK4SavKtFY3Uudl7vwNIatA8RQ44/w80kiBiqAAMu0Gf2HbMWkpWO/U8e1Xd7vzHZ+iHBI/P3I//tJ2RtQzN3c46VFJfELk01CNDMpVkIIt5fG4icl0akGPzqRqoWuh566y3sx9sI9tHyobM6vvBcQl/gTesIOgpHf5VwncxgFZnXLTUZcV6wOI9qMK4+YHMxjh0b1Tp09cWONIyWX3BvxPUl241AzzkejPZiNpi8L/mGu4OEEGCggV+AnCq53NFjSplJDE1Z5M0V67qNO4uqKOgyVWPBu4CoQJh2ty5qOBZAeIqnup7okJxQVtVdcktNmXtimrz8Sdb1yMSE+BboSQmoI9FAUVnXCjUG4jqMQmDqKSmpT3SWhIzE0gEHe3fgmFYzI72z2V4kNdIPeTIijpiIHfr9stOb/YS+m4ree0u/c2uEQD5NDk8yMfL8SB/ggW50LWcajzIxVDLiVJ6yavlRCm95NVyopRe8mo5UUovebWcKKWXvFpOlNJLXi0nSuklr5bz4Ra97wMO9LZLn+p9JibPrq9AyRuovKjahyzaJKDk7SmW/PVty/rc2a9ouauVp3vVc3V++Wtyg/00VkAQeFyEEjiCh3J5jN2mb+kLTvPxAcffcH8AcilBPxMuQ2haeh9ZqPrHRxQAB+0vNXWTjaOSfEG7Vo0auz5OJVnLCBW77sLNtkF3SAJA0QB4AH/Argv6dirIZlKGttXO+6YLa2zKpzUn14YwSMg0XnMNEuAXesvAtFsnYJBWUkmTBBP+eFi1byiJaIwVKkp+xVYvXmfvoRVo0jWHOWV2I7AsIny8/ceTO0MsMwOiraKo848TgJI1LkojZASDD3jnNBNH3r6CNhuEGW/Lga4er/YMO1Uy7krZJvO3s6wSp3tFTnp1e6Ek87k3YSVCT8jJ00jThMzn9m7IHoIQeTTqdAEyEJ9tQs9a2rqY313elhHey3zN+ZGZ9dKQtQRAcsEFyVpGuLxuD3Nf7ps3hKp+qwyUWMQ2UDVO33rPrultl6NpdelHUlIYfxaR97uCWcSGFVGgMxYXncENZ9FnJAxifDnBntGq31fahu1nLVMdrKcIBuIFmbAVBrjd+PO5DaVu8wKEajaHvJbR1NxAU2GbSSUVgLCdRb0x+YFKShOO6pqWpt1YVseJHLKUnrR5SifGlaq7/MFOKB+LQet8i3+y4kgT11wr7kMl5YNgOaLqWAaVlC0c16lCYDGBnYYN1fjyTe0OJ02yPMLJtiKfMuInubYWwHfRgWq0JO4jgQ+kNTgwJQpJdn9OoSFzzZJLoQGWBtIRMIUmOJq4HQ2EBrZDz7HsEK3n2X7Dl95jpFimvuUM79QVGYf2cwskc+M0KPFyrKN5T+73eNke6F6KG9mfOQ/8iMn29YAJsklmCXklDOcJ0SLljZabiitwcrouXwlV56CcyWVppEPyQhkqVSgNxQ3uAo+D+pa6esmu6/p8to50OR5wfeatrfxHJOgHBI9I3I//tOeQt+Oau+dIVNI1EJ5srD4QZ+SFqiZR4T4PXnuwlXLRE9KeL7Y96Pyiv+WDBTL82T/u9wWzf/Dnf8IncOyCS0mDDpnHatpsyev2wI8AfI7h4gOojyQqDBSgwo25XCBGkZD/Cdc/XGWcG9ubycET2ojjIT1vnZC3y7wczN42fslrfqFxvy8oNPhzwo0lIJU9uFLZLlVSqTvKk4pQ9KUGGbxApidsfFEFMyRmd42F3FrqIaWiXfdLZ7nxC8YO+r6gYODPCReMKo1rTsAwo6C/qk8jVcgL55B1acAAcixYvn/C41TxvW8bzV9YHvlaPkejV30//qpaGvcHBKtqeQuiQOQQLiIZ8jxef0HC4PV9a20/TB05wjryw0+Owomb7/llzP0Xm14MM6rBw+AncPI8H18PH+BYCd4tdAsKAvsgNFTFwPTfNOcDebsb7XkFdZL7uRB1osvl4TpRweoX4NN5grwuZAZcBz5qgGTvy21tA15h4j4J6otb3H50e5bnK7O42s7XW3cs5J+y3gbrYNOwIG7yn0QlLQUxNEUtbUmEMBTKYo2yhzWK28yT76IWWA8UxI0PgA0Ewf/9+0xJXmi/CH3sCoLPJdtL9AMMmDYqYCo0EDB4M7/E2sxSk7hCahNB46+RaQ4CMlcT5PEyV/YNmL/Cwtz+kOX5U6QyWtiUTiN9X9i04+81BY2aD2T5ekDXwgQNKRbSXeyA8wBATxzgmyyyH9+vNMlOIvtZ4D2WYAss/vWmwhlHJb1UqIRixyiBm+OAO6BQqdIQjeSdnHh8omgN2lI+WYL/UhvoY2tPng5M9jy5WuZoW/Oi2o52KsaaF3nrMhjrSg6QeRHQEQXu59g/zH0e6HHBv4LnuHW19GUDNgesToCKmfjlhSofj29mKV20htqlMpweVTjui+aTjwxFcHdQBHaHDGJ3TF4mO3DvagXbQ1rBE6ynxbxu7u5YTyU9B8Vpilq9kEwl3VOobATSnyJLui5MjwDAQguD0uF1SQe6vftlFrfUIPQCLYW/AlGGKogS9Y8o2THfx/ZJMrCIM0zo8MLSaykBKF3DRemMQiWsgw26hFvtwu0yCB6MmgAQsuqdn8O4PyXIYfDnogh4QxrzBTXQ9BVCCranr1uYPUU2ARKTPR3cBs+e6rX5Z09h+eyYaxA/0IjMiDkzqkeA76tZBNhTZHMnAizFwDZ4lqJXG1Hb0+ebLXxXL4pirB2wdF6n8qxoAuwpMkhAAEp6uCi1byNCe4rkUInbU0hjMO0pgBRsT2ux7KnU+ATI7URMMdtgmU5vV9ECzfM/mvnsu7rKmQCX4B2uS/CiwSV4gwW50MVs6jzIxVDMhtI5j2fqUTrn8YrZUDrn8YrZUDrn8YrZUDrn8YrZUDrn8YrZ9B+8KlZR/Eo7opv/ZNZT83uNitkuvap5P3rECkrM01393poPuN6oMeFHr47xZZtSKHEddMenG3WcKlDnBv4lVMVEduojoM6tjjDVUBKjavx/PStRGjjy4EZWCgjIpBWWTJAtEgmQyVssmWwuuD95xeMv1kUFeUX7Zz/gvx3Y2tHNn8kSbAaLZQ6NKORA8BuNOlqT/QM4TG5LIg4zhEPmNoJFfW1kj0eUR2mKjVRy8WAHsFjOIM+BHzYe/oqwn7bVZn0U2kRQ12TPf3jc1EkTy34qjA9isscBj8/7Z3uYBwS7s8AKL7DrLNguyNOXA787cC4BcyMPw3YiRMJrCyxY80EhzWgNmN3hNFLYCpqinRvb29efwfTio00l7sfO4HyQxp+35X4+LiCw8af8ttvcZTbl0/TWlWoQiI5s8LYhx5f7VG14T4W2odhu86z9PcFmXTx4ZdqCH4IJm0YfQSd8FtzCmOtGgFNHfN1YNLCDVCP64rCZbn4Nf241ke0W2PAdWFXfYamq1JA5suMoQQE+pP4TwObRrfHYPLw1j83fSz3myFau0htUXYJ7HWBew3WAD1iYC02TyiTx0SRKj14eTaL06OXRJEqPXh5NovTo5Z2g0jfq9QvaRrUs9FB2VIj3qRNgUNCionsyiO6+BDDoRyxxSekMM2QXY7HNMFNVqcSZYXZTWSB7SPAMM5v655oPLk6gJG1b2bdbn+RgKZhhpgxCgjkRRlZFIjUV/IOYjh8/LoYZZvTdnY4nftGgZldmVYyZQ0dMh5HQDLMvynjSqVWWAumIZYbZ4sC++/I+VFlmm4bmlNcXekrFDLPHuMK5KQ3CIUlyhln71ZsqfxzLtyxJP3z6yoAfM6RqhtlFXOFVSEZ40jnDbPiK8iqFV3TKmovXTT4EXSuV8Ayzw7iSOyBxyYFfEtkMswUDR8XUVU+0T18T+lSvxruNVMwwg84QmDPMAEMIn1M/kTDOqS1phhlyzoaEZ5g5quDNMBuhIp4ZZoMHfU2mnvC037AmYff22sv86W4iZphNnTOU+bhVvtXyxFUqC4ebGxMwl8teBW8ul7mKqGaYlXfowTD4EGmZ7ifb+phc9o7mb2EEVkgbQQBWI3CxMhWvlyDpGWafsczYv/78/1d/fuR4IrH1509VwevPHy5oOwnoz3/g+Mn5K8YNNQs/R7+/JKJ8A4EX0Ym2kQpUUrIKXjvzDYI2UhT9+W+Z9BkXHmJtVth1VlJ9TCh/00VJ9OePxUUlXDIxE1TfQbg7QcT15+8afCTJlb7dLpqd2Ms24so8qenPPw9XdH6SEZ3Y+/PXqD3WD184hbryuPy2tAPOYyTcnx+yMpgN1gErI7b+/PWvglxDXb7SNzw06XT84vWjUtCfPxYXnHAVMfbnl7Pslvh6uqVD6tqxKe3i/QulodMFgNA8XISAPQ2f276QMM5tFpTexr9GX6Vk3NXNvJz0hj/0qwTd7wsMYAGMLnhmU8DAefDvFInv7+/DbTIAxNkBwd4+5IYptMK0eUCObMR8WsGGCI0Wm4pvaSnprSqArxsNDLog8e1JI1WqNvfOldbvxwI+hbFAffXoA9rn1M7VUiPPKuTIvGhb2/yxXogj1MMpPQ3r09Idlh6jsBaeVfve3CNUWCnpDYieHg1NOxOopBpVoY5Qytzt68n0ZjPRz5f1u8plbI0otttHBKVs+Wx6BnF5CvoiyuUp7ueE707g/W/hvv8lVUkflho0U4iDEvjIvgGevh44bW+qXcjHd1TI2B2xWVFmVNDPlV9XeT8gqKsNK6IQRiWuMI5IRhjI4w9JmIxFX1v/AA5AX24eYOzUyHQ04LICnoWfCbn/aA+fALanCXnA6KA5bA70B/TTqltCwoy3wxTtE5c4PNI7We3Cz2vgP+DCmc9CGY35e0kUwjqIK6xMqdg54E8JdVpt/zvQ7R/Mdg/C2UGHyqPMWr+5QM95laZz4sEn1ea4ys0Vx0Aa15CDt0AvCojDkrb7gapwp1TYkuOctjYwO745bZpKPVp42NFp2OhbknV7AQCu8QCoRgEANC1CnUR5VIbdf4Jx7UrO5YWJ9nlZrR+frLk8QbL3gAEAivAAmJCtyjtofiW1rHoc5KRvsdXjLFDDq8exVBN1Pc76C1XlZzT6WOea0mc7WM/Wk4J6nBA1vOymv5oUFBVkZGSIoR4nOUF9i4uTs1Xxta12Ox+MPiEV9TieuNKZIg3SEUs9jsPC+QNyQu5YH3T9HFP6bmSeVNTjOOIKx1IahEOSZD3OzeOFeptIRVbRFaUPgx0yJ0hVPc4oXOENkIzwpLMex/zTms8lWyeYHXKfZFlxO2aDhOtxjHAlpytxyYm0HsdlxeuHvhM3mW3s0bl4uvqUeqmox4HOEJj1OIAhhM+p30h/QT3OQ3m1xVo+1pTNHNmpPQ/7LZBwPc5hNbx6nJ2CR1qR1OMYT62bMCI8h7HVtUgztJPsfMLrcZC+OQE1JkVqeDUm+9REVY8TnXrxdsGNDZS4y+nTjnyOP054PQ7SRhCA1U5crLaK1+ZKuh7nO5YZm3PU19jXPot2qMSB9fTx1Df8mRKnYPCCJJ3tFugjeI1UiPSFgblvUCB4RawhmzO/D/cqKdkNbKfnDf4LqJp37vKMDU6tH9vtphTTDyZkemI+n2Amp/GigP61dQFMmEPj+1YoWom83NRErWz4NZR6mnbgBf0ONPD/+LXy0lUStVhdvlLFhckCBMb0tAbsegjv5yCxckX5A0uUA3PtqSOMJ1uV5ITZxdTlXEdYeUB87AAWt4e1EHMBh1iEAPrlwU2BwuFI+Kfg8ZZgPdRs/wBw0KUXWaixJNv77FtX3TfabBV5XKRj2ZqbeE+Mwkt860J00zbrUEYilVHRaprOAquqZSKoaRp3bafuozQWrTir3t+d5OxNYE0T0cM1Aqmk0vZl3OEaglNrN0IINXdAXDcavw7BDrU9qF99wNxEX1QUdUIXfunYs5aa+/LQ3Wcb2vPPI5fHUBTe54QfIx/DQJFRSUaeRjLTLBMIeAsJVOeJTDD8AyHEv+/QEarvmH6kov9963iLo3EW8lHV/OE6+McEw3W8BZFgpI6LEUKZZP8PjKD8FlzKAuD0Ry2KGLshZ+st88xNtYuV7TJ+8O9F8MdQJg5yPxYJPkq4+LQtgw3/TxKG4e/1s6P2XrKcRR617jtT15vf8CtBoxix6mmx/JCudky3oGA2t56Vm4DhWnew8W3TjLvu9tGnz/j5WOZu33tjG2kwDfOpBJm70aIwZl2/DOoshtL3Nh9AWVfArAtZg9GWCo5zAQFAfd/YbuOORq07Y78j6Ih1WpCxOXJmQpBgURT30z/Zd6TRI8K+dwOgSqSgdWuNhaDCtO+oxSnIIZe+/mQGKkZHwpemfA81t4kufHZgo4HPAQ2orAV4d4sQwHVrOARDx+dJffpLNp13HsYJLJsSxKkOwgnemvXwVhLYmq36f6CoVl602j5kyE2ZnO4n5Bi+7ry11GfbdGb0n8DIkV/jW/9Mkd8rh1N/3KKTpu9bMp3JPalxy1+4/VqEPpdlyjgZnGS40CIvb57RZpTSKewnE4yCNl4VQiPNZACkD6Nu3otUUtj3E8KcycgNZzJvdDjQW6QPvbvgxMI+FjvyPugY1ZE0CTyi+dZPTnLq9clml+7E0A79r8xs7hYOAZSPBB/RBFVzMwSYULG8TuYIfWkYg4Y+T7XtuR0nGXcoWQusXM+uP+aNSDuLuYLqGYyGOupGBTgUQAPeqGBbCFQO3fjs47Y+41cyCk87HKP/StHnr8b+bZ4EQ3lY4ZUOv2+k+JOZDT+gKGjqWlP6UI37N2lnKkamVSirvLHZ6dRXfZKNfhesxxQsGv+9JsTYRrMBZdyxjagtPEtNyprdwjPxZ1hRavwk6/xdmfZmNca3kC08keviaOGp+RsrYEOwfd3cWejb4OrTCPsfCyzsVsf3vWDQ5nU2vzQmwF8l/18dPJFUScDIxNL+ZVi9KdmArPuVCdHBs8kYkfrJb5r20comcmnWJX8n6jAMjP6v/p1IM0QERia4GPUuE6Z/p9bv/p2/DQAqSrsebOq06MYw+8ILi33sjC8ul2zvThKNqyuovTvD1GggSrBBBd8d1aA6Pbrn0IZ1np5cWCK7JL8b/401RRcfXy/giA8cf/kNKpgqxIpEdXHw8gKjh24s1u9zJuyRoIKa2NXf9O5SH6sV2tl9ZB5fvYv1CCidp5qKVAqVZPW1HLKVKNGkh8Dql/Jmuh0qkDcEnGWCwAdGfVHNqxFO2dF+drkXjimMKe7cvwmuRxOaa827Y0T6aWNMTTriYu0aljCqubsrnUoaBmKViLq7DlFJz/ix+lPNjDJXggGQVqDikh2sunbEHA/azg45Sv1eLawSyAJ7NQ2Y5u4n4M0Tv+C9OaAlUpABhjRQiLIYJbD/H15LyN6fR37epT7GKi2iYHjPfucD+fUS/La44P/yGQ/+jM8SgV+gqLu5UVXujgAvKGEFKRb+MLTvfzvU7vBEmcOOWR2f/Z+WorkS+QabglIztBAzQD/AhoAJRkaKCWa6lf6L9sVPzHZ6Mtwmaq1eIRqCyR1bgUMwg8ZWiJ5gWm/bqNn5lw1tzeAre0Iude5GDMHIZfmFOE8/Qc+5Rhsf73bOgwCCyQaxwtzny/ixaj7BRE/1tpk9gW2T03r8+pKnawskSDCuuG8OaMnfSDD01zdab73b0W7lDFpA2bo2vSVHMMq48D8eIxH4JUAw2sV9el795WWbXB2tNeDr2ceSIxjIFGASDLAhYIKRlWKCWSG3gu6Wdc28ZO/Fdu0fn58mGoLhhOESTJgYCCbPsKvKw7zBZqsGzDeV2+53nRiCyXJa3670kRo9ulXK6vHPSYUEEExgGN4+dw0jmGBqf40duWLKd8p+m/OVnwu9aiVIMFa4bw5oyd9IMIpukSYPLKPsC0393dUGZkqQYMi48CtLBn4JEIzB2SVf/TXqaeH3wlMePAzVkxzBQKYAm2DCeAQjh0UwKfGrgl/ZfKFvnNMhaHOMCb91l7cEu7xwmp5vGMr9AjkowI9J9gQ0gBwcBNZmB7LcPJg+ASxPcKQoWKvlBf09qG6b4+Yd1KS8w6+RPW+9vdaRslvjaaTs43Na8owAj9lMz4YvoT26YLyS+3lTITaikmZqlEPD6FGYSZ5GmqleLph/ACECORgl/wD+HzL/YL/87hiXypdmy87khim8dbiKzD8snZi65Gagq1ViacqmJ4krx/DWZUnNHDGG/IdR8hOYVgucZQGLEVVaLwtU/Bj9RpuXfNpg8No4eU5zpEX81jGlksxAuW5FLXnZSSWltBNrOIb3oEr+wSzWjCDgHfy9G15W/vefIcpdaDrCeRFKngRLVhqWv3ebRzCLE8xGT5Mcdthfd/7ganpkWMyVDQ5XU3FF1obG/SWUed3wgiiERmqHJzRgM0qCgVoxaFyDCn5lScO+h2TD26NYZKMPPiV3inUQkw21hwL+CT6DiSqr0EkuL0lnSyw27Jlhe1VNewBSVm3sgjlgUqsBfER6HPxXTQVZyvSP+a7WtdHBlMkxVlFOlKnnAqzMmnueBYRaqoYnVLJaOTLfhZcUVIWVncmdFoQ+9XO/j6Gitg5j6Qy/nZOueSbjKnor0NIJlk1BnxKu4ho0rl0qpaBRui7ENzClt/oLKH3H8qEmSVNvUA/octRP616NEhOlk+l4lE62+Efp6AnizjsWxB+KMI/UK6WXj8kfI3WUTqLjsoPlf4/SwyiPNyxdQGakVcrGHd9xhyGFlF5qgWv9Lf4zlC7/iqNnNsyEFt5nQUxifvJVsVE6Y9wy191bW1lucv+0s2PxgrEEUHqYOZ5Q79MIp/SykbenJbjtpO4LnH1/fO2FPlJF6ZBdwqR0QMVhSm/9F1D6wUxqTI79XcZen8+9tuwcFCsmSj9MqsCh9FGkin+UjtpS6NsvC9pkpsMOtyslJzfmxksdpeeCcsU0JCtJYg05SgWlu4bsXNJOZ5Hl7sutS1e5MtpJIaV74gptlHiFJklKXxg9JamovL9t1EuHl71JSq5io3Sv9i5fZSJDLVfIHGL7d7ONIoDStXCFWv2LcEpP6+YX6XkzhrLB7HHYsNT5e6WK0iG7hEnpgIrDlC7/F1A6Y+P6RP1x+lbbP08dT0swGi4mSr9Iw6N0R9o/SkeVVmSQyqPqpZr228c+jbsSOGOs1FH6SRqeIUmh/fco/eaA1FnnNSOoaV9brbCzuNFDCik9BFdojuIVmiQp3WPeR38TeVnGsg3VxtV+cdfERukrJ2nFlGxqQzm0//yTCievGgIo3QhXqCRaBdGUnn8rospt8izq0dPlw8f/kP0mVZQO2SVMSgdUHKb0Nn8BpQ+qY7dTUso0L67LmV3Q5bqsmCg9OwKP0lkR/ygdVVp1GUeOzLpfaZvobBtavmiIhtRRekYEniFZH/Hfo/SqlUHmFqXylvFnbNib7p75KIWUHoYrNJZ4hSZJSu/Y40ROTsENq0g394mfWFtviI3SLxlH67E7H6cVPXzBsD9zMo4ASp+EK1TzCMIp3eSabpjR7WH0qKg3S20nJneSKkqH7BImpQMqDlO6wl9A6b1nxeYfq6i1KXjs7OR/8Y2BmCh92Q48Sjff8Y/SUaWl1iNg3/y6now1/Qvae3W4vEXqKD1sBy477PjvUbp6+IBRCvk9qCuYd+eojHXsLoWUPglXaObiFZokKX1o6Ybwbs8DHPbf9f2yf/nUzmKj9I8J252+vPvokJRt1cd5qs4zAijdFFeoOjsIp/TaU5pnDe7bmq+Pv/zD9LTJC6midMguYVI6oOIwpbf9Cyh9wdcXWQ+3L2UU3x906dQu60wxUfr0CjxK1634R+noB7BNM29/i99BXafZwVyuko3PD5Kg9CkVeIbEsuK/R+l9qx31678ts0qfajL9u/kLJymk9AG4QtMVr9AkSelzbmcuric9tIsc6r+rYMMYfbFR+ssL46zc5ZyoRck9683OBhwigNIVcYX6qZxwSrfv1/5Sp4MeZvvi06jDF+YelCpKh+wSJqUDKg5TuuJfQOlj6WbWdVNiLYuuPuy4Odl7u5go3fkZHqVrPPtH6eijLYvL3j0eMcRs+Swj15Hzbx2WOkq3f4ZnSEY8++9Rulv/8y8i3MypsaGh8ZTjhvi3RCVD6Ya4QtMQr9AkSelbBiy4k/5ut32RDUX3qkdRtNgoffaS0Nk5hcG2K/atnHa/5toIAii9/imeUF88JZzSl/XaaP/A4IT9yrWr1h65//apVFE6ZJcwKR1QcZjSlf4CSk/fqNcvaBvVstBD2VEh3qdOTJTevlUlDqV/lKv8R+lo0mKydMftuphvVUI/1v9N18JVUkfpmqBcMQ1J21ZinRklFZTOYTkNNpp4zPxgTF/5n31cp0ohpf+SwxMasBn/K5R+qeSl5pGnKdaxR67Xnp70SEVslP5/zsnCE+pLXKE+kKskmtJtq836KLSJoK7Jnv/wuKmTplRROmSXMCkdUHGY0pWxKF0Kepn1vT929Ko51Zb7pkaGdXKyo4iml5nJdrxeZq/SxNDLTG+ZTYGzXG/7sMudEm581yaoWaat5vMT7WnpNsnqnhZ9o1w1CehlZrQdr6WU1naCe5nZBg3sYady326/797juyoM7kmwlxkJ980BLfkbe5kd7+vWl/aZahe7zXXyL9m7LyXXy6w6DQ/+MsnAL4FeZm9Y65PaKkym5T78NrNnv6kfJNfLDDIFpWYYvcyADQETjIoUE8y6rWeuJTKm0fcu+GLHcpnTTjQEo1iGRzCnT4iBYC6UBXm2OlljtXSZfE10/ve+xBBMygk5ldqL0ZaZxcWrLi6bMZgAgpEvw9vn704QTDCrNndI/vV9Aj3azvZM6IwZthIkmLsn8N4c0JK/kWA6b/7Y+tOnW/Qo05F3xlQ+mC45gsnHhT9NMvBLgGCYstNzNb/V0SNaXawwzZc9IDmCgUwBJsEAGwImGFUpJhiW48mLbRU701Jt/CM7f2F8EA3BfKvBI5iiGjEQjEbuoKNGurk2WRfGzf7Rh5FKDMF4jRo+VE/rm8O25C2LlCpKbAggmE81ePv8YQ3R7f61BtHuX9lLT0ieslve/vJmCRLMedw3B7TkbySYDW4d3ZNKX1tnOB3sEV/X9oXkCGYnLvxrJQO/BAhm0Fv3rQsLNWy2JY/9cFqNuUxyBAOZAkyCATYETDBqUkwwD7fofR9woLdd+lTvMzF5dn1FRDCylTgEc1O2UvQEU2RX7qK7wMR6wzy5Vb33P8slhmDmGla5yA4dZpdRwbz38N4sIjyYLyBWmPu8lh+r5hPMmNkTykYNP2u/ufWC2mQH1w8SJJjHuG8OaMnfSDBOO3ut3FqtZHG0/9gRu7ViXSVHMBdx4a+QDPwSIBi3br/s9GYvoe+2ktfu0t/smuQIBjIFmAQDbAiYYNSxCObUFjfGz+Ed6RE7ddu86L6whO9VFBgAo5BdzBmCs76x6IVKYzOh8cIAesB3g5jefoAykD2ZXsAfPcnu88kAnGwOOTDA159jQgag9QbXwVILFjQyve+iJtVYbB0ReH/IzfmWuSyFQ2ueHOiH/twCYmhYaSrG5lRSmF85NM4ZhZpkaKSw2QKzNPGyfurQAzTCAPXtuqxOuvFlS1f6nokrqxQnfIlGmFzw24JTv7kf/4mPtt12k8+4fpeSNrB1jYWnTUlz+YhBJc0EAVqGmhbNoJJKWQIDNPFqALQhgHh6YeTpywbUF1jvhd64W+3XhEV6D2glqlWuH0M+DuIDqq0578sCYDVa+hNgeTrMjCTbWMpSu+tRG4psHhAAGJmFBxigURKhsbkAIAHQBh9IwvqvbqxQ1AbJkruvUcV3on7DErcKWdsNP+d9eXFtUQV/7p8BfVGw1gb+nHB7Ckjm/iw8yZjNkvREVPnfkjgqwHN4U5+VGY3MMXobyf0LDpdQx5glWvUY/zm52B5Jav6CFTTcTwmXgwqNa1L2UdB4TRuyuTCvtcPiNXLR9XzOhXjKrgn6Hbb7m+5CzK4O4AAk1XSnSY/7BYDVuJuE7MYGnxmgLbJbiG8QuuM07qqh/vQTrvTV7Q6csf201hLtEVDGZ0OfNxUqRyopZTkA1W1UenoCrC4Tjp4mcN8PcJTY0IOgvtmTguXfurp9tw6f7vI48vUDJ/434/6E4JvBn//J3no+VJBn0GIZqdZjhqW/vfiyufZ2EpUUB0Jkjrqr9wC7ejkqQWF6kpCEgA8g0aPikztjTEb7pOXm4cdrsi9YJrbh30oU4GuCWwn69E/YIPcoAdjULcPDBqE+4A8pkLANfpff2Ph7s5hkI19/4OjnzWYyg9D5+3u27ti33xbZFr3tGb5eb90M/oMOBfwRwYMO9+M/YeVcdOV8TM/NtLXbtlTVG+zpgonV+CCmOfcZG6y5EPg54uJHWiY9jIHiGeExhirXEnnCJg9VfDOPHnnfpdjVctnDjMmqdUN3Ns8QNJc36uGd3oqKwhthajRQm2He0MDijQmncmpXG3a1XB1U27riswl/hZ2KCwfwbvzIlr4sDpMt6BRhbYse3C8EAfzhEcBicQ+e5AAvMrSpAG8A/NWm1ZafWj+udv7LQIs04+onr9/V0XGeTwB4/uWmohoF6HgxgOpmVIqpAlaLmj8eJbBwRF+L5cWWS1k67WrclM4jK8uRleOEVZYjvyhEZbmWtb8nMwQUIx08G3CliCo0nceP1qXPf8LY3TVCwfptMWI8IB3tHMD99E82bv7wI+k7vBxoEVtDXwx++mhlc/lgJcCGoKxPosZ4dgBsUSRpe9ZgFPjLynmly4gYD5bsOlo32nlgLbMvJEtTVPH1O9Oz3vPVS4eNa9YWei8+VI5fsqwA77L/q2h5UlH403cGz+xX3vkytNPGCRsJEGhKEZ5Agc2LUQTePCT7oyKpv8NpTEFoOiVpddyVw/tXOzUNyf6CSPb/I5J94hPGzvpaYVZizJFbF6qsTQCSJFwk9xUKNDzHyFFgQanGNcwA5eLYkuOzWJd0VsXbFM87LvvRREP3D/XzXAgFzYuLkWkv4hm4FrYf6FXhcjRQ3WAG1sRi4I8ak2YPKebYJfyYotdvnkUf/nyTYzCLRaYFs+cyBS97tcLAVQf6EsC94NfIwLcCgD8EBbO93DyYfZvEumftFu2pSlWgL391hNqvt08Kbh1+o2cUwL3RWlMxZQFWNxvElAreQUBiehdAPFvAxeMpHqr/Av3roIcXCDwLesanuxN9hsd5sxWpE9ZUPdpDwX3d1uhvCn/8JwYj2uBxqKT7IFraqCfyFOCEmC3g7eGhpeHC1RMyxwewbSBi6C5frJLbthc1l+irI8aPYsVm2OBfSYJ/VPBKEm/hT7AdDfuiTbthbnvgTd11hfblqwmAzQwXtrrd5Zh5FTTcunK1DAQMsGfQnuP4MHm7DhVCr5+Gm3IzyhzSZulUvgvetoRIrWuuYfsEq1UdYNjIAptQkQaiBxs2rZbqWqQPqjMyVLQ2W19OJcUcPBogFtcijF2G41qEzSr751rguhbJz7Lu1I5JsFhzZ82bnb26XZBm14IEyhrz/BQWUPbfcy2G/jycdurmDoek29/376e4ThGhazFWaePp3eMuW2/R7UJ53y5WgwiB+uEKdFaZGF0LOdkjnj9/WdgkVE9MXsXRMhahayFD7XRsT9J+qwSdZW989s1PJwJJH1wkmWXicC0KfMODfoQE2mbRrVU8u2qlS5trAdkPTNcCUDeYgdsT61qA9Cs61+LQhaGRSSmLrVf1/JCc/+xdrYhdibDpZTiuBGlymTDZoia4ErS2BarV3zrZr7S/6uEzpG4fga4D0QYNOAOTQHQwz8BhU8uESRQ11XXY7tzebfLg0Yy1+WfDZm451Vb6XQVATfBgmlAmVKLh/3AVkBZYwq4BpDaYrgGAFmyYOmBmq72750etiqauO5HN2PS1cCH/+zgzWW7z+W2SkOZfk0Ke58tmktngL5EDuNfy0YD1rZ+c5NTrk80u3YmhHfpfmYnyIALAkv6oguHj7T+e3BlimRkQbRVFnX+8uSq4F4D8xgkQbnCgNYrfQLp2Aoa8o9RDjjRjUgt5mH0ZDuRhDJ6Wa0s95PTu2QY5VQWMVV+ps97ERtCIgRx5fCIAcrOFeJCbzedB3gkL8v7pzuVTczItM9LVzhxf/HEj/5vS2QHBgfyQK/EgpwawPfmLmuVpASzgjcCPDIA/Qn8bRQq6FLI3+LuQ98p2CwryCQgMZLJheQTJWpvzAEMGHIAlnr+FPBUBSzwHArlfgCU5eAkpVwVr8xl88IPHOFSNsKoNCSLrRlHS/B/XbRkdMhkFJ0GNQAiSxBMkVyadsWSSvHDjtdpns2kZe3r9PH9hwDUU8uKXCV5bnp7w3xQMAHkzga/7enCPpk2LAH1w7jTTwq47LYmhfvdpu1URbezcAgPhhk68jUfgAW62wYuOx7pWWW+0ro0NzPw0urkbZjWwUY4fJ5FiqKCbwL9h1ls8oeruyTgOC6cLlnBUf9pXPlrSh7FyWy/XCezvmvwFpfbgkRuMIDS9dKznOGYQBxAO1GQOvHAD9iIjg92zyMD/9/Wf68by9fTlzEcVSHf5lXZbKnbZLvXKn3o5pnMlxtMIlrc2LAlR+6iwspxEuo8aijsArMYKVUimDP7joGcA/MPoRthrazdG8v5OjOKYra0qj3/ryh+5Qn0t7qd/cs+JPvCOo5K+xGImtSIgaIQ68GqNYwczyb5eXHXwDSLbY3lPk+X2D6/PKjDbUTrBPWu+4iJ+5xASsiXLzVuwnKzxGuEn3tMwIIGoHgDgimcgAJH5AyAdkYBYc7cFKiaVuexMW8oUs8QFMXfvRr7cxB+mhr+JAQtiWRTITMJFBqkqsn9AphcFag4W7MYie/5eBc076CJxKRW8TYBRqPm6w3L5QZtS7PNujTk09vS0Yj6sGv97AkjxLYoCp4IYPJx8YnjpFB0sSz1qkcmZXIofY+eRtYOPGDnxv5sCFDe3D0C5GCmHAbWBI5MNtokkw/eJyP5Mb24to5G9wzgy8L+ZvdALfU09tK8fGZ5lvba2Z3CvgLdf0Z9E8C4Kb6WpqMVRSftWlXPjhfcFUDsOHAhXCWWjVajwm0KXz1BfzS/tvbXq5wzzIhbr5pGBzPt8ryZDEYyeUv7I+kib1lzzvJ5KSgFRMaUIsj5w2IJQEa7wETASTHYQE9xlCymLUHFBZkcQtd3MoGAWSpNQ+HPCt9NNGIIvqBB8hSCAt1PXlpqdnNWlZqlV6DDKul6pgwZHTOKIJTvJ6l6Bk518pd/8Lvl/d3Zy0KsFa9vMP2AW6cHa8iF1l7s0Zyc9QVljpmBGdZeG5hUkklizk1EzyZujAhn2R37N2HZ64p4lIsxOarVtY9Jzs6H5hk4r9o7veXg2AQLVwhUosHnFmJ28dSi2/5L+xlYlLwZd++H96I4Is5Mb3o8zsBmdZrn/9bOKTz2PKhCAZJk+HpJb9QVa2YsiO2kX3L1taraved4gudRhI0dUS1t2ErIfmNlJQN1gBtYlNjsp2sLHoP29Z6VeDrddcyX9Y9db18aLufDRsWsFTrbyiw5m26n/M1u57ua7CXkPZzEyTlSEkfIW3BVh4SPRBo9DJVmBaGGm5chdBRpPEVH4mFvQzqT96UX0pHeMsvsnL65seYWPgBrhwHZRp0LUhY8LNh/xDtRJpafo7593m/O1i5QVPkJqhZndBNCDDZteS3UtHlXvK1ft8dgm55VN9IxnijVicS3un8W7U3X/zL87VfiuhV3HuyHnSlj2K3borLfNHLVaml2Li2fxLo6Enf0P3qmqiNyuy5473mx5scyo8ulVRiJ0LdbeCZeL61Jik73+fImz28sOBAjUFFegwOYVo2vh4W75IN/Gyerw0tWlnwf9cBSha3FtZJh3VOAxq5TRd8a6RLmkEIBk3Bk8JM3OiOVOlYtex3PPDM+Ypz5LuTnCXPOEtLkWkP3AdC0AdYMZmIzFwDej9eNuG9laJF4t+JLV3aIDyrHdEWxGJOhaQGlNGisgiBnEcfBnzW9QDTSwDWF/A2psRIa8jblubF8mZz43IR0A0Bl7ftM8D/156us9fe7bp3fbvtL00sm7WI+M4WlAa02FWItK2neqHHxRNE+jAiDpU0IF1rUceQAEMd3YHj5kL3YAuuYVfurQY+OxueZHF+nYWb3J4u+F3Br9BeGP/8RjRJs9HSopBQTJDPWkHAo4a6cwb1Y1sfOaJh1WkT85HQVZY/W8Nt+2PpA5X+/mCvp8RMYF/hWUjAtvRdxuhg6kQzjg7TspXJKiC1fFgCPvVPo0sgd3g4IaN9VxGipkSNvNf8iFdzjGlkIsE27i7sKqFYqGTpgqDVQtoRLKpua+XATI7kzOPCbTH4QFajLnywkiB7IDZvH8BdA/AxBEhUy5fVWfu9rnHFI6Xz/tOSfJjF/LeP+EoJY1rIgCKBIuUIAawVzQraV6Y0vdv5de9HhNORp9QnFZyr5+YvHGDEzwEj3pxv8SPfje2MQfl2/qa9vZlYT1Mq880emJNHtjOiZ40ewPxv/BRM/DvIHfKm/vsUkM/ZJrpNQrSYTeWOsnSzNPlmiZb6o7o3Ph2OtRBAj0rDGeQIHNK0Zv7D39zCfjTvMt9l5n3fV7lLBahN7Yz67vHJmG6mYreoZl9OuywJgAJENxkRxnLJZEj1XsrcA54Wus4kb8cpo23CBV2rwxyH5gemOAusEMrP8XeWMn4lS0RmZPp+++HHL6/ZTeK0TsjZ3tXYHjjXF6C+R9CPLG3B/Ztl8QZJP2qdz56bmUbQR6Y0SbPcChKANBwnQotvbGTPcQ7Y3dH0BZdEh+sl1YF9XEHoOHXmsJ3hgHFzxGb8GkD6HeGNJ2S5k3BqkWppOxFYGOeLyxjFWqaz0UJtCKDX+VaLzVviYV3hgHFyhAjWAu6N5SvbHiQi8/2Wn+tkufzpw5tXVSiVi8MY4Xnjf2gfnPG8P3xjYfvRq7OdPLrOR71xVbfjCPSbM3xvLCO3Kae/0HvTHjMb90P247a7u670n53M+l30TojdFNVa63fmJCjVJrbfVlwMQwItxrXIECm1eM3tiJ5wtvVL9dZZn9OOf7tHIDUxF6Y5ui5uyQW6ttvW/I4rmGhjvaEOHXMnH9WqZYvDEXr/Clt2YY0mL2/Jq5JqXmh7R5Y5D9wPTGAHWDGdgAi4Glsewu3HSUjLxzHiM7y+AK57yHrZjL7kxm4pXdXZ1BdNmdid+SqVv8rewKFTz6aeUcTRVh2R3RBo9DJRnMxKsf+zFDJGV3eQzTe+2qztvmjHw+cxh7yKOWV3YHqBEObNkzRF52p1yzMnrJ/au01FHKs55/b3dfysruILXCLLsD0IMNW4+W6lrM6B4/xTN7l0P+q4laW12DT4nFtTALwHMtSv3/uRb4roVlyanvHyZesNhXEj9eblvIK2l2LYYF4J2f1AP+g67FxYTX+o+yPpinRIR0C6vcaCNC16LjbV+NoCO59NXu9bpdr4y9ToBAn/njCRTYvGJ0LQZRV52cXLfVfOX0eOX1EwfeFaFrUaP+M9/mpofNVhKVSpso85oAJBNxkQz0F4trEaQtt2DcvHmUGL87eUNST7pJm2sB2Q9M1wJQN5iBDf+iRA91g0uNV2mOZcot/w2L3mpmiDjR88wPL9ET5yeiRI/m9kW9nfQplIRh/Tx6GZ+cR2Cih2izp0Ml3ffDy1UU+Ikt0XO38MHP4h9ljEMWu60iZBcGtoRETxwueD5+Ik70IG23lCV6INXCzF8U+Eki0WP2femtWbVTHaJfdDdOGjrORSoSPXG4QAFqBHNBz5bqja04OOfB/UU/rVa4Tiqxn3j4jFi8sZD1eN7YsPX/vDF8b6xzyVWHrD5X6NnLF/aQWT5lhDR7Y5z1eEfOmev/g97Ypkeui41utrFPtjio+WO4laYIvbHncbL0Pe3fWxbunjzy5XO2KgECZeAKFNi8YvTGnCYnGX5yGegQnuUUtiZ/+QsRemPfXFMCNKewrXPLavXaW52+RwCSBrhIqq8XizemeDrT1zDf2ezg+sftHOPICtLmjUH2A9MbA9QNZmCjlpToSe4b7zpmAJW+bF+rNhWrtWvEnOjpG4+X6JGNJzrRw6Hcq/Gy7EYN0yJVHL09Z7EIEz1EGzwOldQ7Hi9j0SFeJImeYudRkRWGmxkxxz88J3GUZVteokcWF7baOJEnemJ6fxunX13hED3xSvJLhw19pCzRA6kVZqIHQA82bL1aqmtRObavffed+RapLye7DMoMayUW18J1E55robPpn2uB71ocT13RXWOsh/0atbs1W/TDnKXZtZi0CbeGbNN/0LXwkRubYNg913x1Wv2zVcZyViJ0LQaO07HwnupoF9E26YPGEXcaEf0VcAUKbF4xuhYP2h5JPeV1zXrPl7ZrLpQpbRChazFuXdfdhjtnW+xe+uZ5zeW6OgKQVMBF8kOiWFyLoXOnZptGFJoVd8o/+0W9dIK0uRaQ/cB0LQB1gxm491+U6JkfuPjXznRFu/0V8h+TV5tbizjRszIRL9EzM1FEiR7rGO+dW/Z9tg4Pu2O7XG5GKIGJHqLNng6VFJWIl6vgJIot0ZNT76eoX3PLIa3oaEbVjvjklpDomYkLHiNRxIkepO2WskQPpFqY+QtOoiQSPf31ZiYvV3lhubd7ztBz7hcNpCLRMxMXKECNYC4wxuKCkp0rx2T8zLHJKx017mRxEP88J3l76FDIzwN4B/Z+mPNdvFgBbhxff2+YDbinTfTtfHBoty+3dt2yLTYZMmJpdCEZ7ZEEu5XDn/9pK498F/Bpr2aV1WbmXhWO1iiL5m7ldHCGfBmJZEUVbGbet9t1ap+SQkkPipUn8f6LM4PVwYRYdcDaeISog3PRlfMxPTfT1m7bUlVvsKcLoerwyZF1OcHvl/2O1R+Xzky/25kAdSgIK0dXB9WA69Q548N4LU/6YMnAJTLnrtH4SGpY6OhnBTevh6PGzNBHj6EO5fjjzCU4GtW08AiSCwmO6Nn8ClV8UnuesfHmgiPzNLtcJkAggSswBBI3p4o6T2EFTyB9sQQSe7W4nWJxF4dw72+9guOGq/AfPi0AHoGYMKjpg1j1LUI4bDcPDhQMZAI/AG2DIFAocHy+acdiFcPkWybaTym7TZ90WD7w9A2sJxM8Fv9eayqSEVTS/RwAyQzUAPxNwA3OEartWLuGADwTnOiBNRTmpO9WneNb6xy2BKt8e9fjYB2BQfdJReFP3xk8s19558vQThsnbGyurkVSSRdBhNCjo+kQQkId62CIAFDYHK6KoEIU8K10uItTudWmaZv8X29T5A9+tXYBvy0IEfdjws8k72AMLqI68fI0UliOcM2x1LgYNGwSVARezdxZvzmgtV1MjaKSUlHfCj4E5ABdF3h/6ENRvL0p7tvf38uzNv2wrM3LCfaMVv2+0jZsP2uZ6mA9hT+UyQDMS9PtTDcamwlGTt3ILOCvNxx/OfMCYIvTNDNj0vW1ZugMWco2RuyL0w9zhgk+kmD4A/y0qbDNpJLUDwGwnUU1LR+AY26+UKZFHfzH/7htEvWeuMrZadisyjKeGdjWin/YsxK0PzA8IL7FP1kZcoL6w4frXWzjVIqCHRY5GDbXyvgAIIFgOaI6j4B13pcv0NkQDyxVCCz8/fXy0GyN20+qzNcb320z7/IM/ssvbRu4RHCy3++lP8FkHbt4861hj6lrrjOzc7sumkAATIDW4MCkni+cMVbmKhXT24+JgVKf+ISxs75WmJUYc+TWhSprN3WbEG+HAEsD6cg+VCZqRwOhge2Q6V8UJVz6Ye6CSxZy1kcXFOnr1g3ZLeIooUIeXhfWSbki6sK6vjax+y8FZ/NN+wuDfl7eEEdglBB5kiAg0PUlF6+RaEau2Lqw+jPKAr1HF1qmaHQ98eRMZn1LiBJOwgVPIVfEXViR1CVlUUJItTCDXxm5kujCanWw397b+3TNN0zaPXjzi8XS0YV1Ei5QgBrBXND/L+ICmy/rt8gf22u+IePtzNVDWr8TMReEHcDjgov7RcQFHpNGJMr2GmOXF/xppfaNTkRyAdKnIsCcBR7AM2fkA2LjgkXru01UcUy2yKozcrvv+SCyJXABoEM44IXtFzEXIM/nUsYFkGphmjhAtSTABYZ3NH0Gs1fZhc2IZukE+8tKBRdAaoQJFKBGMBcMaHnRUNbzmMLUnePss79NW84ZpZol4mjoKN0KnGjo465CFQk0MRq6bNyuk1nnJtNjfhaPLWllekuKR7xFUkmDdDFrRdMhhEQRDXUPf+9uF9zVIdHPPOI++/Z8CUdDIQww44HKusKlspsUDS2f9PHd+J8TbLZcoc97rLypToLR0Mdd8d7+cFdefnpgC4qGbrfos2Tb+Wzqfn8lxnTnk3tEEA0t6FaBFw3tJpRpaVo09Pwlr4ta8eNso59vuJ5tMkJU0dCq2bqt5E9utNtVOnRdcrzlWwLCfPtAsDDDfFHdBOqQmhsNdTh6wGTSnQMOce51Dju2P/4hgmjo1+Jby8YW9GOsqS7uyXatPUFENBQXpmHdhDPGf46GIif7SjQaCukIdjS0G88ODfqLPOCe6sNnrjnU0SHh+siZCRsUwkXsAeeS8WomXckiqplMNhkiV5f93i5G+/5NbZexngR6wMiTBAFOXDYZr+xvGVlsNZNWed+3Uud52xbN3qJ0fFu3mJbgAbvigjeILOKaSSR1SZkHDKkWpmO3jCyJmsmnI3pmFT3bbrnzmnLuuVbjJ0iFB+yKCxSgRjAXDP6LuOChcgitz+pTNruVyj/rJRvsETEXhOjhcQFZT0RcMODReCfLzkybQ06Bxivrk/QI5AKkT0VENFQPz5xZ6YmNC2Z2OrDJc7ai7fYvDy4NPrK2RdTPk3HB+6IrYi5Ans+ljAsg1cI0cYBqSYALQvrNNXjInGEfc/1UbVDy+DCp4AIyLlCAGsFcMASLC/qnO5dPzcm0zEhXO3N88ceN/CaHzg4IDuSnASXeJqYGsD1/X7iEPqIFsIA3Aj8yAP4I/W0UcehSyN7g70L3YtluQUE+AYGBTDY5AHrSIFlrc96+Q5aHAksy8BKypAtY4l1NRFZRAEty8BIyqaZgbT6DD34w9IIq/VNrcl0PqipRl3/u9+rNBWYOCk4CokcKksQTJFcmQ1ukTJBB6kYyQQaWGskE6cs1kgmS2psuk6PDVU44nOlnszPoR3ezzRe/ESCTYS0va9Cm7NqkiNsDzbNO3ypf8XFtNxFnDazc8LIGdTNFkTWo7jzhnvoaQ1rWlM+zvOxjzklxh/pIKsnMDS9rACAkiqyBtqlMP4X+821K/M7eM2jTL0zCWQMIA8y4ubabCLIGHE3VAacU31JTdlMmbP9abSHBrEHdTLy3PzmTx8rDW1DWoI/cgTHztdpRt2ovu3D8cOw0EWQNyjzxsgYsTxFkDdYM+VZaSH9sH9tx9QOTyt29RJQ1+PD0eUq7DpesDodUxi1I1m92m1ofKumwJ144fL0n4VkDWy8fQ3adMj1nPnXJsw1vN4kga9A/lrpt/IIh5ms8Na+1nr9uDwEwsXBhMvckOmuAHEwk0awBpCOYWQMAGtgOjfiLIkUfp7TtXu/MoK2OVp6qvVxxtogjRaUeeJEiHw8RRYpmdF/rbv6GaZluMa9D2YmxgwiMFCFPEgQEOwo88IIdcR5iixSpvVns55H/2CJ+scIOCjVqVUuIFPnggmfmIeJIEZK6pCxSBKkWZgAkzkMSkSId99uPMzotoOZe9b/ksuzZXamIFPngAgWoEcwFI/8iLhjvxNj1TY5FzdzvL7d6h953EXPBMnc8LjBxFxEX7J4aU/h20CLrHDV3I7ZHBpNALkD6VASYs1B3PHM2zl1sXKDuEuS2tlCdXnysa5uc7va1LYELTHDBa+UuYi5Ans+ljAsg1cI0cePcJcEFI1kRj1ekaVDXDLk3IY81cqxUcIEJLlCAGsFcMKpFRqiRAdFGEWpkEKNRhBrpNzSKUCNppOkRahnZ4EvPtyrYJy5P7f1mbvRzAiLUo1tehHqq/RNF1zCK5b6bA2/eTwhZIOII9e14vAj1PsE22wREqB930slqO9nPboWTq0byo/W+UtxaO5JKqsbugZwOISSKCPXdc9SrPSe9sy/R+3b44v0ZmRKOUEMYYMZoy+JFEKF2N575rWi6AX3TvJ7ny05tuy7BCPU+3Lff2tAFe0wLilCPmP7gcciqZ3bxUxeXXFpi1uT2BUJEqDevw4tQ+68TQYT669UzGi6sd3Z7tBmVJ698fCeiCPWTHhbdh/SKtdx/vu2HvmlunQgIvW5chxd6jVhHeIRavavLntkRQ2g5b7csXdbj2WIRRKjzSIcu3Rzu4hAzi15YVh+qTABM/rgwTVlHdIQaOVFFohFqSEcwI9QANLAdGvsXRSUWDrD/eexDoc1Bq0UzHLafsxRxVEJ7HV5U4tVaEUUl+mseTkk+PJxaVGv9ssp8oiKBUQnkSYIAx1prHZ5jTRK0VaKKSty52HF+Sk0kNVamQHmhdc2slhCVAHQIB7zqtSKOSiCpS8qiEpBqYTrbpHWSiEpotVeJvnzmJS3ybA9lhaMe16QiKgGpESZQgBrBXGD2F3FB4mpaSEBRb7vC6Kejxpmv+yZiLliwFo8L7EXFBbWvyn/5DKyzz7V79nNb3JcxRN5xQvhUBJizubjmzH2t2LigyDfOzZHawTJq8ZeHB3rlG7UELrDHBW+EqLkAeT6XMi6Yi2vi3NdKggsMOOMcJx5+Z78qKeNj0qSxs6WCC+xxgRrRwAWUFhmhRgZEG0WokUGMRhFqpN/QKEKNpJGmR6j1M+jGQ4rz6HsjJl66sv9VZwIi1FQsmUj75LSqJbs455TfWu8b386HZDInB+f5iJucdjsfb3La1vx/k9PwJ6ftPLfq+ZByG3rkC3+D3d1tjaV5clp1Pt54qLL8/+DkNGX5292Vffwo2fGRtovlap6KcHLa+zYu67cqmdOXmfXT36R8yIEAge7DFSiwecU4OW1w/RfKniIF823fuyu9KvNREuHkNDPLg/160pIckjpYhexT697sshAAyShcJDn5Ypmc1mNoW8eTT59alEwu3vxC6ZiztE1Og+wH5uQ0QN1gBqa1VAYedSX2vMZ1GfME85Cgk8f8douFgUcU4zHwt6J/DIzPwGPabH0bH/rAPCsgWWnF99g20szAQ4rxzIx+8X+QgTcofqwwejXXJv1FsuGq1ulRImRg/8Sgzm1WKZvFT71VmDSoOJEAgariChTYvGJk4COj3lf0yd7hkHBRObqv8fLxImRgpq17Wdz0VLO46BFW645Oa0sAkk+K8JC8XCQWBjbOMZpnfK2dde7LfKuP1Cla0sbAkP3AZGBA3WAGNv+LYtRrg9rJLdLXsM2pM1A260QV9VSCZUV4MepJRSKKUVfvpY2SDV9Fj13DkaccnHWQwBg10WZPh0oKK8ILs7KKxBajnjFotuH6g+0dCn0+yIXI7TzYEmLUk3DBMy8ScYwaabulLEYNqRZm6JVVJIkY9bbIZSZZQTMtM1dH1BhyUsulIkY9CRco8wYusMDiAumt2G3TVvWwykYv+6Pqqw2rZl2Yj/VkBFXs9s7Fq9itPyiKit03w7cmMQZzzPI+VupSGUv6EFixS3SgKZJKMszFq9gFEBJFxe7ppwZjl/QzM4vaFrkuntkXkbYVe8UuhAFmzapGrggqdrWpoVlpe40dIueseauZbl8qwYpdQMY4b//iIM/aWGJZGyms2LWdeEV3gZ2W2YrXDpzC3OO5IqjY1c3Hq9h9lyeCit3Shz8unjCwdki6dHjrggcXjoqoYnfh9ZsKOT5h1KTNZw96tHu7iIBS1M75eKWo8vmEV+wmV1WlRpUpM5JWs8LabXbhiKBid+f6MRNGzupkEe6h8/l7n3M0AmACtAYHprt5RFfsIsPtEq3YhXQEs2IXgAa2Q/S/yANmDFmatzNroXXeJlLOk12c0SL2gNfm4XnAXsLZrKZ7wM/WKbxTTJW3Cz8ScLm+9RYiO1EjTxIEOHGr8/CcuAV5YvOAjXI1b+5OUKXFXPpJOz3x6ZKW4AF74YLnLKQFE9oDRlKXlHnAkGphOnYL8iThAZ+Z8Tlxy8tuVkemev2K339uqFR4wF64QDk3cIHVX8QFnTrdHfxM1ds6X/u02eudg9VEzAW3c/G4YF+uiLiAWtkhNHjeVfOELoONe0/p8IvI/kIIn4oAc1adi2fOynLFxwX3Ayuft19NT/3aUa3GYW9hS+CCfbjgbc0VMRcgz+dSxgWQamGauDIhgw7EcEGPy2NnHL16lxL54KRy9+jV26WCC/bhAgWoEcwF1lhcINUVu8iAaKOKXWQQo1HFLtJvaFSxi6SRplfsDtdse0rlxWGHzYdWs1d8H5CJgpOwFbs2LbVeqNXV1le1ktqbxR7/euJF0sUKsdQLxVXj1Qs5Vv+rF8KvF8rUHKCoctaXsaPg3eLrWbqIe/rSVS+0shqvKCKk+j9YL6Q4YFJy9esplmvfLZz8KPHEJhHWC71YYpjYc9BN6+hpHOecVX7NbkUJCNQTV6DA5hVjvdC2wdZfrHNf2iX7hXtM4XT1EWG9EEsuz2V6pySrtN7lHFf6L2MCkByFi6RRtVjqhdR8e49b1fY1bUPnmOgp00OVpa1eCLIfmPVCgLrBDGzbUhm4ZuP46trjv2zDL7c/aLptQIlYGLj3HTwGfnH7HwPjM3CvSyEeR9cYW+a3WeyS67DrkDQzsOEdPDOjcec/yMCfypRUszinaLs+1D9r/TLpqggZeGGlRn+V7xcYEV2nByqtCG128zFAoPW38QQKbF4xMvCXBLVJnDbrKEvfLjrnZq/pKUIGTt1wiWVrtMRuBdt12PBVZmkEIFmFi+Tx22Jh4BdGBjpnNZ/bbbHZ5LZw+JjF0sbAkP3AZGBA3WAGZvxFMeoTR9MK5sYbW6zuYPq+j6HWWBHHqDm38WLUVrdFFKM2Cmkzzf1Mb8vMy9tq4z+8TCcwRk202QOnJd7GC7O63hZbjDpMdzO7eJ2bxYFtM+8M1Rka2RJi1Fa44A26LeIYNdJ2S1mMGlItzNCr621JxKg7fO386aCuNmXvEvfgGyZ+m6UiRm2FC9SgBi6ww+IC6a3YbRU76EJS61paXskRxbT9weoirtjdew2vYjfimigqdhM+UDyczEwtDs4dN7qV7hcWgRW7RAeaIqmkrGt4FbsAQqKo2O17lNnZZUid/fZPqqZHF7/k10/xV+xCGGDWrG68JoKK3V8P9fIyZ71kHL3A0VfQuLNUghW7Ebhv73+NZ23ssayNFFbsrnyzrbqVl7bd6uJOeqvV90wVQcVu2nW8it2510VQsVvz80pV1Itd5mmTJ3zzCXvvJKKK3R8Ta5mdz96wi+lwaOQO1cTHBJSiJl3HK0WNuU54xW6rSUe0+5zo71AQan66IHoA/80QYip2z32V/9TKsavF7kelrYzTrm0iAKa5uDC5Xye6YhcZbpdoxS6kI5gVuwA0sB1y+Is84HYBNfpBma8Y4Q8qHZ/R7vcSsQfc4TqeB/yiSkQe8CAFy4hJk3UZcY+iDrHSBt8h0ANGniQIcOI0ruM5cfVVYvOAp+pH7nI0krVer3mzu2HW9kstwQMGdAgHvKoqEXvASOqSMg8YUi1Mx66+ShIe8A3l+FfXFW/Y7QmL0Ss8ZnVHKjxgSI0wgQLUCOYCx7+IC+7/mvkqOVWPGn327aX1/U53ETEXzKzC44JBouKCx1usdPR3Oduk2ex+rvuePJxALkD6VASYM1dcc2YlPi44nOpRctVyl1ly6v2VXnIPEloCFwzCBY8sai5Ans+ljAtccU2clUS44NbwdRabDt+jFy2f/k3N5vZtqeCCQbhAkRu4wKml1qa8H5MwefjdtXZZ5a2X3/m8dLpYalNCv+LVpoz6+q82Bb82ZVvizZjpqb6U3U/q5B2/W/IbZCmrTQn5ipeA9/z6H6xNedSr9zz58T/oWxZnXoz7UBIswtoUjv6jWVP0O9GTFZx36psVHSVAoI64AgU2rxhrU8a4DN44ftYp2/Tq8T1Ll9yzEGFtCvlNXmRbw0uMXQfk43tXFhHRz9UIF0mtr2KpTVn4yTlvwZW1VgV9biy+9P6Dr7TVpkD2A7M2BVA3mIGdWyoDZ8+JfavmP8l2ZZr6KGbHomqxMPDVn3gMvP7nPwbGZ2D67qrMyiski8NDXk/td6y+tTQz8MWfeGbm8M//IAOvVukf6MXZTM/dEvpc79d+RxEy8MAttZoTFaMt1x118/aKGqFNgEAzcAUKbF4xMvAexpkacr4KLaOKJD/F/ZSMCBk4PEvW51an/XaRj4ZavV13KJ4AJMNwkWT9/B971wHWxLZ1g3RQQAVERIwdFRR7V0hogVAE7FgQAgSBYAB7QUB6E1CQIkWkKCoCFuwdC2JDrFexN1QU7O2fScFkMjMmMgPD+73ve/fqnJTJ2vvsvc/a65xpkQy8592dm9c7JBsnTFZ0sB8/L5toGZgTPxAzMOBuvAzs8D/Eh0bOm1y2aU8MPe7p9S8X5u/qjDMfqvsDjQ99/x0nPtTtfaetnwxuUzYYJF06Qf8QiSEfinXY06GQtH+gUXpyP1qMD00N9xqlnu9ELTn9to9Z2GPFtsCHAj6EAt697zjzodDYTTA+lONaiDQf4FqtwIdefnX58p6NqiaB4erv22ePKyAEH8pxI0SgADfi5QJHpFxAXHXoXr0jnp9og4yilSav0jtqMgXpzjBShz7+iKYO3f8RD3XokonH43QU3ljEeD6Y/Vx2q/Ceh+apQ7EmmkIppNqPaOpQACE81KFDK5YpF71MMd5Wl6n802j3w1ZWh3IwQNRHVn7EQR1qVrLYqarxnHn6iQdXz7dXG96K6tD9qL8+9yM/2kxFijYEVIeOvPhN7tD2D2YbDtZ6vrd1VxK9pWarQ29+RlOHFn3GQR3aZ2BYnMzW/jaZb3Lvjq2dG4GTOjR96L1NyQmmxuXZr92Kgsw1MJA9Vn9Gkz0e+4y5OvTOnIjtxq/mmOy/P7h26dKdz3BQh/orvxtn/22z+YadjmOr5OWa/eQTD47XoMCU8hlrdSiUbm9VdSjHRxDVoQA0vDg07X9oBRz744DXxZUOFjnD76z7T+bWMpxXwPTPaCtgsmQxS/wV8NRC55BVIx7QivTt4m7sehqF4QoYWklgscXvM+oWP9FYhdcKODzAx+G/HqZWh7coRDmouY1vCytgMip47SWMYBKvgKGpi2ArYI5rIW/7+9waK2CFLK9Rhpc3UjdMGTmsgrmZSogVMBkVqPZNuWD6/1AukFoSNVLmWE+jtFypzokBNgY454KNn9BygecnnHJB3NWDesMmzzI6+HSL2twZ63pgmAugayoMwlnCJ7RwtvpTi+UC6RWe+2TlQswjOip11R3co64t5AJPVPCmfcI5F0Drc4LlAo5rIYa41Z9aIxfskUsIdLq1ySRQaeC+PiVFMYTIBZ6oQAFuxMsFM9qqNqU3+b+0wPuzKOU5lKQjaawylPvDTpvi3L4CRZti3L7inzYFVZuyTfWw+gt5M5OSi+8yek26/InI2pR5oK0RG/BT21f8/9OmFHYzt7NyHGcU43FojH5fbTy1KQ1zzi4JXVpvWjRsYJysncEwDAxqhWpQYPK2oDblBbnf1SFHcyiB8UMudycbHsdRmzJQ/ZtNydjvJnlLS66snUrRxgDJ0ahIGrSvaAltyuxFoxmPZfZarEuJ6bBirMkgomlTOPEDUZsCuBsvA89sqxm4vmAB+dzR9ZTQpN2rJp95kNYiGdhLBS0D01X+ZWD0DKxx2lXPk2xuXUphB55RXR1K5AzsqYIWZuar/D/MwOVXHewH9Vc32zw768ERw25OOGbgJ6qPe61dMYsSfUIuI6fEvtkP/QIMOg3VoMDkbcEMrOI40mP1ugkWJVvbh1xReDgOxwxcOEOf/jJ4nlH69w83THxLbmKAJAUVyTEqLZKBH87q3+9nTq5t8HFjrxWVqt+IloE58QMxAwPuxsvAs/6H+FATG9nOTkdlbAv8qtfYjg+txpkPbQ9CjMiHfuxQgQ8fuuBk5Kh4mWxq7LC7B7Tc7hlgyIdiHfZ0KCQlECRESo+kUtFSfOhxXSfvdeTBlMhGg/JV605HtQU+FPAhFPDqOlTgy4dCYzfB+FCOayHSfIBrtQIfekTfM6P21lezsF7Vl+Yt/65DCD6U40aIQAFuxMsFs5FyAXHVoeRXTiOvjfxmebjPzMaVkzyicVaHdlOuQFGHyipLFPLFVIeuXihVf2W1nlla5pnh8fE6ehiqQ7EmmkIppK4gQojqUAAhPNShDje/S8nEy1C2HPjw+N7mJSatrA7lYICoj1RVliwwiaUOdd6wclzozxG2+evPX/zvYX+nVlSHyqL++m9K/GjjhBRtCKgOfZWdWz+OeZa2684jl5cqL7fioA5VBikzRHXoB8lCi3jq0Ln13YeGJV0wLhxw8vj9kgP6OKlDTxbmHSsMf2GaUGarrDd9jS0GskdFECxE2eMvZZGqsrnqUEYPdqYfdZBVeeiAeRr2VqNwUIe20+zLUHggY1vifei+OnVwMgYwfVBGg+mVhMH4z+pQKN3equpQjo8gqkMBaHhxaM7/0Ao4ssiw/+vYIkpumkaV2uz1qTivgE8ro62Ad0kWs8RfAXvemzpgzdvx9Jj9Bq8GnTMoxXAFDK0kMFjEnVRGW8SVi8YqvFbAIUtSrl0eyTZLytB55WF43KstrIB3oYK3VcIIJvEKGJq6CLYC5rgW4sKuXMJCEyNF0MngKf6m+rYpCfLVxkvOXCfECngXKlBbm3LB3P+hXKBbHfyw+72tJocTeux//G4RA+dc4ImaCxzxygUR0iGBzN0qVgU5bps+9E1ZhmEugK6pMAhnHqjhbG7L5QL/utCoggtf6ZGvds79MKPvy7aQCxxRwbPEOxdA63OC5QIP1BA3t1VyQfao+6VPp00zXRf00/Bt8oLjhMgFjqhAWTblgnlSXI2ESC7QGCa1o8HltlmUZtX4D4lZx6TpzAVNv/h5hs68odPou+TimD+fKy0X+sU8NsvUlemPSJjKIRhkoRBhCn4CnzH14TOmYNd3oQ/Ln+y8mMF2dmf46XNezHudsw8Z+C+D7cvycvZnuPLeInTJ34PNCnD3EC+9BOwJrPx+3M5sP+veoo05Xer+8EtFjCz6EnFtOIJCOnbzFIn0EVYJAySbY9WnJEk2PZp4WHcGDL5usD/fW2to8Ni5r40zfvycpO7XSxZDVnbtVJsPZ/OWmhWyIizCKctONDd0TqCQAkG8yBSQmYXiFUohZdWcguYd0A2R+uNfpWhuZEd2AEMfcD6vZSKI8dzQj6zn5wt4HQO4mQFkZzbwIq4LA56m91eOOaCDEvDNZs5efsBXOwM1itC3Cn3BEg8mUDUwFgUAL+bcoB9gB7KzN4gh2Zl7iftFLsAMZLO8+B+j58VcyCDbezB9WP39ON5pB5RtwKu8vYHoNwD+vB5Ht5B+lxusY7JlJo2o1SgW9gUrEAtRX+BexjzATeC4P4qxa6+eag3pkPwCFsuL4SwQVKDJmj9FxSx1tEyFg2CTReEJ3MzTN2wbPUyPXNPTNVk8eaqwOgMhRPGv45GFODPSCTYLKVFJRjdOiaRrCfHRdXT2cQcsTF4M5DIWmzMtBeYL/Nk2epfkGif3pkXcX19/lEEbKZyveR8oitPvETyQItWgIQU4uxBS7SRHqkeTapIM9uEYYkFVOKqnQuO0L2a7WXcWL6m0nA1ZXfE/EabxKDCGi2NdQ3Wsq6d45c18pKXugB9dtHaSpU33UOq/MXTdbwh3BehA3CDTGT7u/h7CxQvYgZFGQLi7NcPZLwAI0OAk9eK8mdvp9QI+bTAsvvK+QeOV5a1s1yUfnDRsz8hHiHch2psQGJSAK8+6B+B2AsCtViRq7gWi5l2RkkLCpZkixdmPwfnBsL+31y+jcI/3U+jrBljXfExXuQGlzv1EFxXcq3+qJqCRr7nVhC+FNB+EKsUY1JdBoYriQIUY22HX+jYcUSlHhw0kDT8g9ZPpsBhVFy/srXWwu21Bw5qcL/bSip1oYJEA/HbTpb5swAQCHyo9w2CocIxH8Bb+dcynYhUPJwsKHE71HJx4U9EZaSqq/LCpeLTGgB6dMcBpGvub8HGHijYgTQPmWdGJKIuAdX9HcBHqTHYF0j4HbbIbi032AT8I+C/TB4h/TCDwLYOF//XEpyd0opNtQ+22jD7iPHYFwt2I9sCahsTFjg5gdxbArha2wi8BRk9JVOG3B78cLPCBL4afftLZLovuukpRSz+WZcmleQsfwSUD+7O4V/+kfy0d3fPznfw7Vgf1R40LjignN3f6OVJIZBAaeGlnEAcaiXgQdbCSJzO5k4/M9COD1oLF6B0rvu/7n2zj7NTyQ4qnGuOEUx7HyGZezu4wKU9gDPN5dp4HiC8sMSRNJdWeEa2l0ADpAgWExp0WsJgcVfa5WXApw6R8t8rM29Tll4VJId47EWCBDOOBTNZpNGSgrtLuD8gMMAYm0FJ/YE1Fdv09CgZuMK+zOLEMFB0gCJkuLDjS1dF8qmnMnXX7epEXjBBO6QLfJ5rSBQdx8aCTqB50nB+pFyBF6gmr9C+UGXvT8w4njDysN+UghE8FJSg2LH/xK6Y+wBINCM3eZN6yiezDcHfmoK1nY+tIBv7MGABfOP08ruGwZ8Rh26RKLcW1vbUnwd8JDLPLGxEXtXgg1FSd4gjyYUomoJDKqpQoRneg8H4ppwaH/WkDXG7YnB2eYBJvp3tryLCpq4R+mpSx6PYE4z9WR9CY1tzwnAT4EoiKIWx1lMlBRaLwrAIECWCpwABn2QrjVbC4lG4y0c+cWmJ9YI8U7cArmf7ChY89wy/AS9Tg/OuYT6fbPAg+w0LwhQMBbzq5IE0nom//q3Wp8JZtV2Wxdu6pJ8y7DR4tsv2P/OIUyvY/8pNT/7b/oW7/O790+cWDnSZQsxd1iBmRp4DdBnzo/MNgj1Pt81Moe5yynrUKh9e62/8GDnUKNn2RaLvv3VoT2+MGujhu/4MuNDEw6PynaAYFJm8Lbv+ruPPz/jKZs0bxchOe6ZftjsRx+x/Wyx9wajxCnRoPT7XE9r+h6gOHrTQbYxYUf/3J6Umljn+9/W8oPtv/OPEDcfsf4G68DOyKlIGP5EVPKvixy3LPsQmOZw/6dRL+PVzKRjj1ogXpIbxXiuZeNy8WUNf6uPMkL9wIA0+5rpO/O/yke7VVMXvBCMUjaVZwtyRa5vCu//FYSIhBm+uouRSSUR0C/VPSvYbS//DL1o7hciT+P/FGPHdgILmD5sMYk07jLlGzRz46uussZIdFuxP7hF2BH7w6UgP8/FneMA4BvEWJOwj5IBXeVYgZgRE4vwIuw7qKpfXQ7c6PioyzQ/IOfe9nowG9XRE3Aa/97TxsghbqA2Ctlniau7A8ZsyD2A0J4p/rSnI7D5ah7HXSSs3ztRbeYyBFE0ZY6Y8IS9FgAJaiIeArRYODV4oGi+7+JcY3z8gYW5UMrCqx32ytD7lT0TxB++P0O+HpdUUnZr3lwSUn2n3Q76Qr5vRDg17rMBR697/z7qpCib27qhDOu6sKkby7qhDWu6sKYfFf2Odll+Pda2gbaW+ifAs/ToTerqh3A9dw8e4xJyAQeyBBTHbvvTc8JoKSeLKIvulLuTB5LGvP8HJeJoyyhFm7szF5CZPNILPBT+JxUbDgbXwesMPEO8Sm+Mfai/br/AphbkQEP9If/Xc/c63f96W+VtvMaR1cu6vnNjd97ARANT/JbeMHitQ5wHKPNPkkD3LmXwUUEa/+c0TB2avPy37/NM94hNURdaluMzaPNvw7r4bYBWptDOIKSfskxOk9/yquSD9MjpY0sIDvgbEBeBnBCOAQnBXA67BmGP+e9XFn5xqLVMbODv7qE0xF7ll0JyF4EY/wErjvFATphX/l66JI/9nZWwBpZoX6jJev46nldz1jP/YMXPW3SENcHlomY+DyRh+ghvD6S5ePzJbc5SOzYQ0RmY1oiMhseENEZsNXi79WKj19U0XfeHv54SWdu10VuWcYQwAX8XD5+FBo0eL9ly4PRVocl8cdaaPo0Ik+vYrMUwK237mWm1r1t0hjIzZHM8T8CKghfP5ybZQr+dooF3ZtlIu4NsqFXxvlwtrg0JaC8jn0wfR9aodyvviOGQ69XZi1US4uvk5mQSFm/V0pA4VYjFIGX4hJK+9O979w0Gr92m7rlWqfUP8OYoiT2x+4VhXZP5WakJFW87PPjm4YOPnlIKgFfP/KyWVO7JOcAuC8CcYKnOsIduCMwVmCMwBrixiF93b3Ncxt9p4ee2dXapSO6I2L0nKcq3i4vEWHMxDAF/2dy9Mk5gOAt8C5PA2JEQBGYF2eBs8JfI18F1ScdtiobMDg2Lkawx9Bb1fU5Wl/ZgWsA3orZhcxTfaMkM4eM36cuIfHoVnArg/UAmwkCxBLfTX/3n2nR9vI9HyP4a8DPQpiEO4GI/XVktNo6quA09iqrzane3bZTqKa7Jo379CqslQ3zNRXAx5OSYvV3Wu1LYttujlc5TMG6isjEBpk9VXAaZzUVwdyd29U6O1lkad2YuIMpqxwg6E11VccQBC1M1mLT+Onvjo/+4nyV7cEi5RqTxWfBd6Q7dmtrr4iLUZDBuoqOKuvPh9yPJ3ZId5yWxer/GdHTKwJpL465o+GE9n/NC9S+yFFauKor8a/7r/hoIqy8fbBNedn7B21HP5OMFFfBS4/jaa+WiZRjBZDfSUjqzV0U28/89Dqdt/oY6inMFBfQWMaBuqr+SAqyOqrZZKFZ3HUV5rbLTd0DySZJHeQSxnBTp/Z6uorDgTI6qtl/OnkjzSdiK6+OmZEu0r6mG4U/eKk9Lyxnbbjr77yB4LUGgDV/bAl0VNgdNXpf+orVPXVhqUDjS723UE9uE0/4q5ixADM1FfQ+dfcILISmCOgrcmwCSkPuLrmNDHVVwq8b8BDfWW8erLNzXNGZsm7jtyKGhqWhaX6qrkxD7DY/NVoFgNmZ0tajH//Co7LfBmCP76XOdvZz8+D5evLYA+2YrB9GF6Dwdf4DTa3mAdAxvRxVwaXg/P8OH/+7fG//87FsAXFYl0Sypd1ChtFyb+/cPZ69udZOIrFsF6tAX5BXoXmF4ErT7eEWOyjndfVZO9fNltjPwTPz72n/ddisck4iMV+8sId/JJWmQpOHl7BEIBUMPydWAyp6MJELAb1JUzFYlAKHQOx2LFFp+HFYu871VAUGn35NljcNtiq83o/bOu2vLY9dHb/66kLVFfhylap5aCxVWrZGLNVbuW7RzuVmVjt2rjyHWPQQk/M2KqeT2UuZBz3NQqe9LnfVtvy5xiwVaQcNLYKgAYntqrGoKzLrm+3jPecuNVh5cDncoRhqziAIHINxdk4slX0I9WlOV/oJjE1CmbvqHXTCcZWzc9GQwbqKjizVTGDjRlutz0tIweHNXzIezSTSGxVFhpOvln8SL2kDbBVm0+ayV57a5S78AtZSqr2OI5sVdYWNLbKcAvWbNWjQQ63vjuk2BQkjv40tb/1EgzYKmhMw4Ctit+CxlYBqGDOVtXvmC8fs36Lefj4Zyson2KNW52t4kCAyFYBEPCm09K2ylY9zphxPfUY2SRkwHmL7VEaw1uErdLLQ2Or9Lb+Y6vQ2Sp52ohhJeXDTIpWnBrjf/Rdb8zYKuj8w2CNq5WHtsY9u5XAbFXzSQt4tmofw6jq14oKi5wCy3MbY/ZYEYytWroVzWLA7GxBfkct4cdMjUHtrTfccL0yqvBaexz5nW6zE+9uHGpntEf1gbbZ9ZkOGPj+zVw0JMNzW4TfmVM0vefDTZ5GG79EyERV6EYTajPgT16AQOR3AHfjpdhlSCmWMJs3oCtkbDZvQHeLYbB5wzfzNMrmDcNMPuTLCQ+51tHdqqru5ka7i4yOGQZaG2IDOXTKYAD5/Hw0yMn5fMhXIEE+NNf+9OxdhWYFuaoXTqz+sFH4l5qzWQG+wpC350NOYbFdf+c6ziUqywv4ReClPsBfwf/CHtJoTHYHP5dTkvzuDfDs4deOZsIHDEqoAUP8Sgu6igOG+EkDWnsCQ9IkeLIJGJLhDUFNrkAzmSdkGbByhnWWrBtrrvTTSzeLTP+QXDhGej8MhKLOArExiW9jrrlWtg3Cc97zjOoDbi/oUWrHzn36uCcCV8Lz7EY0wvPsBowJz7ozPvoFhxbTD3wxpqQtzAnEjPC8XRL5rdqg3rrMvaBon4ubFgaE5/6NaIQnAA1OhKf0pgWVfWla1vuTBw4wal9AJgzhyQEEka7y2Igj4WkZEhExbIAvLWPE5ZCZz6YmEYzw1EJFBuoqOBOek2sNpIapXDYrUbvx3y6qTgiBCM+lG9Bw0tvAT6yriE94ep1Vs9cpHmd+cMntKY3jv8bgSHjOSEEjPJ8nY0146vbNcT+t602PpspH1wwKt8SA8ITGNAwIT4sUNMITQAV7eV4/RZsL1wdTcw6+2h7wsb9VqxOeHAgQCU8AAt50Wt1WCc849xp195OGFutkny5wrk/fjD/hOZ9Cqk09zX18pmhJBJ61u+kf4YlOeF5def2WzIJtphsW1HdRXO00HTPCEzr/MHis5eVUnlYCXtSTSmDCEy953livjPVjLluZbr+XMWr0j+MfiER4AhYzRLUYMDv/l+R5MkOHDB3Vggyu684nvX0uKZsXvNy+zX+szmgcGVysmTLANeI3obmG0aYWYXDNl+sURcwNND08aBPL6vDJHEIxuDJUbsSDX9WqUcH5w6sZ1hCeToQu+QnL4OolodGJzxP5kAcSHvJTLhPcVu+KMMpM2OmXNPtUATaQQ6cMBpBrpaNBfjOND/naNsngQhlCAQYXuiwVYHChxbQAgwudSgIMLtTk4jO4VxzP7RuouIye0W9mEvPVvCQMGNygtsHgJiWa1Xfett8yI2FMiP1MliquDG6fLmdQGNxczTPYMriWB/rO0g+dY1Ve1BDuq9lvHmYM7peNhbKpYz5SAlkK9tU2P+9iwODqgNAgMrgANDgxuOlZcY/0S6eYhbxTdKIldX9OGAaXAwgi/9YIAQRTBpd9b1i30K6atMTh+3b3uXDOnGAMbqUmGjJQV8GZwZ3Qc0ORpmIwNWqudtL89fGeBGJwV6Li5Kh5hhepg4nP4I7LlHEs6b3GItt8vGe01L2rODK4deC8Q2Rwy7pIFKPFYHA/ZU20ynySZLz759VOMwNmrsaAwYXGNAwY3McgKogMLoAK5gyu/8WwJ++T9Wz2TpjdRWt/+vJWZ3A5ECAyuAAEvOkU0lYZXI2n1nM33HxttP2GsX/440WF+DO4/hSSYdczKJLVYq0z/xhcVAY3tTJ1Jm3KJ9p2g8C4wvMd4jBjcKHzDwPZnh5oa+QN1l3PEJfBbT6LB8/gbjR7NGBW6GSL9JrPB8qn3NlKJAYXFFpqoVkMmJ0tSHjeU5A/71M+3rRkAL2eROp1HUfCM+DclaFymxtoa+/6lC84Fj4ZA98PR0VyvtaZliA8VQosY596FppFe0627KNkfZRQhOdPXoBAlKwC7sZLsesIz75BV8jYsG/QUw0xYN+qNc6gsG9lGnzIQwkPubzP+GUkNRv6tqGpo1esjVyMDeTQKYMB5JVd0SAv6sqHPKxNEp5QQk2A8ISu4gQIT2jtKUB4QqeSAOEJNbn4hGfDWINjd16NNSkY2mOQ7ujkRxgQnuFtg/AsV551lRw02mTngsfWtocbzuJKeDqqohGe1SoYE5615wadz5/rZbR+frth9n6qspgRnn2vq2o1xj0yLc93X1rk4/YDA8KTropGeALQ4ER4bj00YcAbuXFm0aZ1W3Z1nBRNGMKTAwgiXdVHFUfCc91CL5Mua1bRdzWur5kWXzeFYITndxU0ZKCugjPh+dMpVsUwJYUaXDZ11Nwnh9oTiPAsQsUpRIWfWCOIT3iWpFbqDFXVpmW12+Jx8dJkFxwJTx01NMLzsSrWhGfIzTPd7xpXWgbtUWVpWs7qgAHhCY1pGBCe6mpohOdjVewJT6ehfsVZExeZH34if+Ni8mGHVic8ORAgEp4ABLzpFNlWCU/XF9bv5xwbT1n/8pZGZJJe1xaRrHp1PIMiWa1T+0d4ohOel95WVqx9ZGET9eLYuoaOy+ZgRnhC5x8GKjdX0NaIKrcJHQlMeOIlWX2b3GBHMrxndFQrvlf2uHGEOlESsJg6qsWA2flPsvr3DO7RYNPnysNZVmsTqFsyOrtNxZHBxZopA1zjlBqaa6SrtQiDu1Gxn7XNxE30BLLR6h+VtUsIxeDKULkRD1GyCswfXs0QRXg6EbrkJyyDW9cBjU6s7MCHPJrwkNvJF5iM6DzDOOetyk+7q59fYgM5dMpgAPnnjmiQ3+zIhzymTTK4UIZQgMGFLksFGFxoMS3A4EKnkgCDCzW5+AzuhoM9O10uY9rG3J6Rpq0a8QwDBje2bTC4/V7I0d8lHTPONLPode+amwquDK7MLDQGN2QmxgzuyLQL4Z36dDTddzn0PxnLtdcxY3CXVsckxMvJmG7Y4TvkweGsOxgwuN9nojG4ADQ4MbhuL8t2Tj96h1r2cmv+No1RNwnD4HIAQeYpZ+LI4F7v4BO4cscOy32J8evi+nQrIhiDW4SKDNRVcGZwU6fd3K1ZpWceVaA9ulNdaQ8CMbhOqDiNmMlPrHHEZ3BHVC2NOXT4vHVpvxw5q9q+j3FkcCtnoTG4SbOwZnDpe2dJ7z1fSQ/z2KA/2bO7HAYMLjSmYcDgnpqFxuACqGDO4PZ8eefku7N02/Q1b+bESj393OoMLgcCRAYXgIA3neLbKoOrfflton/aFkpe16AHSx9THFtEsqrmhCZZjZ/9j8FFZ3CvrB7nduBSmOW2RcP0Ykd9kMaMwYXOPwxkewpOaLK92tkEZnCbz+LBM7ij+x54cPuohm3x5DVz5oac6EokBhew2P7ZaBYDZmcLEp57Cn4+j454brN7dp3dMxr1DI6E5zPNMz7J2/tRI2knZDdsOXEFA9/3QEXSaHaLEJ7jrkWUdC0cbpsyJ/LOLZ91FwhFeP7kBQhEySrgbrwUu57w7Bt0hYwN++Yvs9P+NP0sJZ5++1vhFe/uGLBvZTPQ2LekGXzIEwgPufrRUzPjB2612H5oc+KU09fXYgM5dMpgAHmRExrk0U58yBPbJOEJJdQECE/oKk6A8ITWngKEJ3QqCRCeUJOLT3gmbble4rA3hR44aGq08TvPbAwIz6S2QXjeHhy+lNLngdFhq9fMTjarc/CVrNqjSlanYEx49tJ3D8pKsjbak7LJhzXLThEzwpP9OUEpJ6OOtrlD3XOXyhkLsJCs2qNKVqfgRXiOWlEp+3xYJ9M9izqdSgolLSYM4ckBBFmyao8j4Wl8o8f+zcOsLDKmj2RKZf7SJRjh+X0KKhU8pUUJz5Hjllp6J8ualVV+Cu/t2O4+gQjPIlScQqbwE+sG4hOe5bNuqu07cc46Q/ZW3H9ZqTJ4SlYdUCWr9lgTnu0Mqu4ajAmmZidsHk7ptuEkBoQnNKZhIVl1QJWs2mNPeJLkswxjSHTT9IYtZx1vUh+3OuHJgQBZsmrPn04b2yrhOXvCiq+LDjwzK0mUkWl4JvOxZSSrjqiSVYd/hCc64RlP2vbuaux52p6fgefnB/ZOwIzwhM4/LCSrjqiSVUcCE554SVa12Z8c0tol0UtTvxsNCAhWJxLhCUpWUS0GzM5/ktW/Z3DpD7wKh38hm5beUri8J92wD44MLtZMGShZdUCVrDq0CINr7O/1QubJc/NMdojbnOk2NoRicEHJqiOqZNWBXzMkE55OhC75Ccvg1tmhSlbt+JCnEB7y8X22J2XcqqGVm+2eWELdHIkN5NApg4Vk1RFVsurIh3xTm2RwoQyhAIMLXZYKMLjQYlqAwYVOJQEGF2py8Rlci5hq9iOTUssi6bOzWQU5FRgwuKlI5tJ8GGPSadwlavbIR0d3nV1iIhxkT+wD/ydsL34a7UgN8PNnecPYg/c2Je4LYD5QhTcCXfFxR+FMzBuCPwEOEnjgfoLo6pJ3/W8zRVPJCZ1DqRSSrx2PrDlmzIM/DQn+n+tKcjsPlqHsddJKzfO13ip079I0Gk0Ye6U/Yg++BwZ48DIC6uAQHOTgdfi1Zbju8z0TPluUpX5w+nq4xFLknkXA5lz8UzBzcFsbfGdeP2rkjl/z47KefBczmKEZYow71BDpbaOTscHeP8r+mY75lqGJ7Nm27g24djL6xaJ1Mp7GYNzJmLHWV2PdLg2L/JDtLo8yNs3ErpOx51Jq6mGWeeHO+sYfNcbdMOhk9IpF62QA0ODUyXjD/JDs63vJdEOfsTPj1LYXEaaTwQEEkYdWicWxkzGreMHiRW8/maX0mLHjwcXDrwjWyfgag4YM1FVw7mRUt1cNsWjnQwn7et7aV3afDoE6GVdRcToSwy8wM4jfySi8M6dhVMga0yj11/GOy4dtxLGTERmL1snwicW6k/GiT7W36vjh5olaXeL1Jy+egEEnAxrTMOhkhMaidTJ8YrHvZFy/N86/csRk6y2T1jn4uZV1aPVOBgcCxE4GAAFvOm1uq52M20sbOmoryJnljZT6scxx+PEWkW7rx6FJt+ti/3Uy0DsZ2bHJ7zRd19LWuihdG1+nbYhZJwM6/7A4bTgOTb6qHkfgTkbz2Wz4TkZon+g1pVO22+bvOOV3MkljCJE6GYDFSKgWA2ZnCxL/XSffsrVopJvtHDp5uhvdqwRH4t/VqshQKfAaLYz9tHjAS9e1GPj+zVg0JE/Ftgjx3+Ppw0s3gmkmBQUFe/2CP00kFPH/kxcgEKXbdU0pNpPwLDR0hYwNCx32ooN/rtQho5hPgZOTz8eUYMBCr45BY6F9mhYJWYSHvMRwv0PdmJVWaTNGFpjULs7EBnLolMEA8uVxaJB7xvEhz26TxD+UUBMg/qGrOAHiH1p7ChL/kKkkQPxDTS4+8f+93z61be/f2ZQc7/JWOkNTHgPiP6dtEJ7rr18LrAx8Sk2du/ut9tSsYbgSniWRaIQnOxJrwvPKysTFnXuYrq/psyMnO98AM8Kz+8tkcqaxrcnOEbM2fh5E2Y4B4bkzEo3wBKDBifD80GHKiE9hy4z2vB55dkaHxLeEITw5gCDSVamROBKeJ7WCKroc17DYHDPKr9fyY0yCEZ6hqMhAXQVnwrOhZHnOwikHLA4s9KiLKdB4RyDCcy4qTpaR/MS6hfiEp/8PmnNFjRVta+6d7R3nxeL5eDXNKDTC86tkMVoMwnNReq5OnpkuPbTL3oqJPfOfYUB4QmMaBoRnpyg0wvOrhOFZHMJztJVB+OfAmZYpBvX2FzVDWK1OeHIgQCQ8vzZNp9y2Snh2a6RE1UTXWhYa0AtW/eht2iLS7SNRaNLt1VH/CE90wvN8Y4fLMXHx5sUd7O486TN0HmaEJ3T+YaD2PBCFpvbMiyIw4YmXdNvZfYlF3/aJ1pkJVKfd5VZJRCI8AYsloFpsdcta7H9Nur1MZdvH6DFL6Ed+FY6+scBZDkcGF2umDHANT1TXmBbVIgzu2CujZpd9pFIOhubPSiBd1yIUgytD5UY8ROk2MH94NcNWwtOJ0CU/YRlchUg0OvFzBB/yPMJDHrJi7cLXuz8b5cXJT6ZZ/+qNDeTQKYMB5DLRaJA3Nnl5fptkcKEMoQCDC12WCjC40GJagMGFTiUBBhdqcvEZ3JUsT1bF5Qabkpx3Fos/L+iKAYNbgGQuVOm2AlffLLl4u+mNMCripjEEKXHTOJypmwZhgYOGIPgfI0otNI3gIeQ+EwHVDxciGQNVyC1D+wslN+dNMEbgXEcwAGcMDnzOACzwtzatGHOk4xib8Bh9/7lOse1EbxyGnRZHz610vpDZb6+9UWnS44528WQFDPTcz5Og9tjWNtob0t3rPlTYHKVkPir+EFXUIx/X9sbSYrT2xphijNsbfXVNjFJDj1vkyM5aOYY0uxtm7Y2PU6TvRs0MpmbcuNsovZxqgUF7w78Yrb0BQINTe+P44ozsUSsLrY4UnOt59MElO8K0NziAIJLT84txbG+U5bzpWVC42CJ/lMch/XU77AjW3qCjIgN1FZzbGzrpVe3jNaMtNxUkzszK2zyPQO2NPqg4qRXzq87txG9vrLLY4Za5cLrtFu+GeW/fVTzCsb1xtxitvXFMshgtRntDsbLX2/A9q2zSvjKV+i988QaD9gY0pmHQ3rhZjNbeOCZheBanvdHlRsn1tKdetsFrF+nfzrja+kdxcyBAbG8ca5pORW21vZHRc0LKDPph0+03DnVdtdd3ZYvouVfvRtNzT9r9r72B3t5YHjv6ZKT9M6uNcd1MgxqvYPcwRej8w0DTunw3mqbVbTeB2xvNp7jh2xvH/Ayotw4nWmas2LLm9qvkHkRqbwAWs0e1GDA7W7AbkLXv4+IU637muw1PXu0cH3Adx27ArFRNPy9zWXpE71lKUUXPxmDg+wNRkdTc3SLdgODzXuTobanGB15nZybIvx5PqG7AT16AQNRzA+7GS7E7CE9NQ1fI2FDTbhtXzRsSn0cNbBdsobXv6jkMqOnLu9Co6WO7+JDvJDzkjBm7LtX4Bhgd2Rpz3dX5hhY2kEOnDAaQV+5Gg/xQk5fvapPdACihJtANgK7iBLoB0NpToBsAnUoC3QCoycXvBkhVRMpGLRthHjjjSqedVjlBGHQDitsG4XnC/YTu41M9LOPHx2Q0Wt2Nx5XwVNuBRnheLsKY8Jw1rTh7fdYWemzcwUGjlNUfYEZ4Jg8/EzzHx5eWu/euPun8p3sYEJ7td6ARngA0OBGeKb3zZZQZiSZblIYXO74yrSUM4ckBBJGu+lyEI+G5rG/PIQU7NEziXmQ4JGVcDSEY4fm4CA0ZqKvgTHhW+uxYsX10mXl5vcN7luXIwwQiPA+h4lRQxE+su4lPeC60nXPnXuZe2laDQwEjy7aMwpHw9N+BRnjO2IE14bk6eK6d7/lY470yxn56Zzt8w4DwhMY0DAhP3x1ohCeACuaE54i6+09mryXZHB406OiP+xMutDrhyYEAkfAEIOBNp5K2SnheljpEP5Iw2aZgqfP1/LR9y1tEz62zE03PfXfHP8ITnfBU6D+l163aNEqKypPaL+ddAzAjPKHzDwMJqNZONAmozE4CE5546blrT56p+DHyoUnCnRqpju02hBOJ8AQsVr8DzWLA7Pyn5/57Bpdmv2321GOKtqUXTl+dv/zETxwZXKyZMsA1zqK6RtmOFmFw38/Uz7+SudYysvfm4pFFr18RisGVoXIjHqKe+25TzVBKeDoRuuQnLIPrVIRGJ9KbVj1lhIf8xpTnfXtOe2+ScGBKt/hp165jAzl0ymAA+YKdaJDb7+RDvqdNMrhQhlCAwYUuSwUYXGgxLcDgQqeSAIMLNbn4DO4Wnce3yndpWB9U7ni8+7iOWDC4e5HMhSohlqX9jYaY+y4YETF3AEFFzB2EMy93BBYp5fPltz+sXWWd4ZN4TdN36WaYuxdBinf5T3Or72hFu7PPnpkemXkw9aXycXsMlMQm+6BK4n1IZkGV2Svx9eeSC+0F3gpjIIFRBCsJvALOVALDsPaC5giknyXK0AqM4SG6b18ENc3+ttHzWH5D7qM6qT+tPGrAcOsLAadw7Xl4XEXreehdxbjn8X24zHNvswe0zA7Sv4yUzVIx63k8/dXJKc98oMmeBs+To/YMmYZBz8P1KlrPA4AGp55HUeeOfRsYT6wOzy2evuOQugpheh4cQBAZa7urOPY8ZpdOmKkdPspinf7e4p3t3w4iWM9jAioyUFfBuedRPDSu/4nOAbS9I06d9B2+rZZAPQ91VJxIV/mlaDnxex5HVp64M2vPR3qEAjn50trKEhx7HpVX0XoexZLFaDF6Hg9Kw+YUTr5ofXD8/effH+ysxKDnAY1pGPQ8zl5F63kUSxiexel5JF3b0vlquwRK5qB+5JNjk6a1es+DAwFiz6O4aTodaKs9D/WLed3n3jW0ym/Y7HqKGXSlRUTePtfQRN6Dr/3reaD3PEbuPK881n2KefK2ObeCt01QwKznAZ1/GAhdPa+hCV2nXSNwz6P5vDd8z8O/z8mLA2Jc6EVeC/Tv/qDPJ1LPA7AYBdViwOxswRbBvLMvOm9662mVnGxjuN+8eDeOLYL+tl8aVqV3NTswPK3b5beZczDwfW1UJOWutUiLoE7pdXil3RqboI91PXIsh34jVIvgJy9AIIq8AXfjpdiDhOeroStkbPhqvR7j/Lz7tzNL/mDXU2HGuEgM+OojV9D46p1X+JAfIjzkY/wb/psQP9tys+blY1anOg/FBnLolMEA8kPX0CAvavLyw22yRQAl1ARaBNBVnECLAFp7CrQIoFNJoEUANbn4LYKj2fu/PvK1twxmJzwL+rB3GwYtgiNtg/DUUJ7q/fnMLPrRN2kLL2XVncWV8NSvQiM86y5iTHh2JGXs7Eu7apSme2/tQfnwQ5gRni6OBnLKNgZGh8o8U6baGDT7MViOFJJeFRrhCUCDE+G5Sj2GWTZ+KiWx1OjqkV7zDxKG8OQAgkhXqVfhSHh6739Y6j7/sln+0oHj7D00fxGM8CShIgN1FZwJz7OZs5QeKR43ixyS4LVIepwTgQjPmxfRcDp1kZ9YjxKf8MyYevHZjBkjjdZN/5XeN2yUOo6EZ3wVGuHpX4U14XlmbnnCKN9JpmEq+28fTfpwEwPCExrTMCA8o6vQCE//KuwJT+eaqqipfS5SIje/Mdv73+H5rU54ciBAJDwBCHjT6VhbJTxrGN9LleL62ISN/uB5J2W+fouIvMdcQhN5f676R3iiE57me+3P5PppW4We7VR6q92yW5gRntD5h4EudMQlNF0o+RKBCU+8RN7s5IfVmkFUWvgYDfmYJ35RRCI8AYu1R7UYMDv/ibz/nsF1is9xl0odZrn3R+38oEbNABwZXKyZMsA1HlehucblqhZhcI1mKX04N6GrVcqd+QfDqpcYEIrBlaFyIx6iyPtzU81wnPB0InTJT1gGd+lFNDrRo2nVc4LwkMtVp7z57qxH295tVNf0vMae2EAOnTIYQB50CQ1y9iU+5CfbJIMLZQgFGFzoslSAwYUW0wIMLnQqCTC4UJOLz+Be85x5v6h7nmWaWkjQ+YHMpRgwuKeQzIWqJm7/W1oruZ5Y6M0wimKhcQRNsdBrYIlTwRfAggkNS8g/UART4VE8tMWafFqnSVt8GslQqGp8OdpfyfF5b4MxDm8EwSy8UTiD8IbgH6oot3PJ9bgTtpvNzh34tGZpBNxPEKUBaOKJ8lWZAx1jFF9TN2hHRsyau7I9BqJ8uVtQ65xpG42Q6B7Dlj1a4228s12XvPAe4RRcGyHbGtAaIZ4NGDdCap/YP1w0/7PF0ccnMsMXm77ArBHC3q1FvxNUZxbZI8pn893NgzBohOQ1oDVCAGhwaoTsZGRXdnM5SA2f9/aijVvjXMI0QjiAINLYCQ04NkIerlC6PmxuZ+N4+zVPE77WORCsEbIaFRmoq+DcCFmX/lhVOvqH+da4uDEVO7MmEKgRMg0VJ0oDvz6tIH4jpHxrQVrCmTLrYKNM7+DJ04fj2AhRaURrhLyXLEaL0QjxmpGsplzzwWrDur6+Bx4XumDQCIHGNAwaIUqNaI2Q9xKGZ3EaIYPKZDuWDwi32nfu4hS/zKIhrd4I4UCA2Ah53zSdzrbVRsjYxusmfu5DjY9kt59FuakWhH8jxJ9CKm5EU377Nv5rhKA3QkIeybo+kL5ITaBPiHkdejAHs0YIdP5hoH4takRTv6Y0ErgR0nwyHL4RUtFly/mxD3Ktj0zZ2eA6cUsukRohgMVCUC0GzM4W7BuMKIs9cK9U1bik8UiHbwmdCnHsG1ybqjNTwW+xxaH4IQO3X4gNwcD3nVCRtGhskb7B+GHlFclrtC0jku1kzJ9EMwjVN/jJCxCIym/A3Xgp9hzhSWzoChkbEpsRKfXV3XWq5R4n//pnjnlvMCCx2zWgkdjv3/MhP094yC/VKg9W19OhbA6Y+Kx0sdJ0bCCHThkMIP/ZiAb5myYvv9Am+wZQQk2gbwBdxQn0DaC1p0DfADqVBPoGUJOL3zfop9xgVuRWZR330uNqvId3MQZ9g8q2QXh6Wg9ZkKPKMi59Zhctrd9eClfCc3A9GuH55i3GhKei26L5mXoaJutPUIJ23Or/CzPCc+PU2IoVy2zNSuVlFrGMFkZhQHgOrEcjPAFocCI8R8r4flWrXWaentg+41e/femEITw5gCDSVZr1OBKew70/VQYwLpimd5l8i34kPpJghGc7VGSgroIz4dnjm3TtxCfraYcSXvp5f19wk0CE5+23aDidectPrBeJT3heri97eNDBxna7PrlPjxPJFBwJz4R6NMJzcT3WhGe45sXZGhb61oHvnpVcfL1+LgaEJzSmYUB4xtajEZ6L67EnPK/c8LwTda2PcZQFWU1PUUav1QlPDgSIhCcAAW86VbVVwjNvtm9sxNDBxuXeXoVMus+RFlF+j3uHpvz+Wv+P8EQnPNn5Y4b3ODjEPMu10dXk3dsemBGe0PmHgVh01Ds0sWivdwQmPPFSfn9/82rqqNvvzGPXjCErqCUcJBLhCVhMBdViwOz8p/z+ewZXc16B58mXySYHfKrHK8npb8KRwcWaKQNc42k9mmtcrW8RBnfii8GqavXSVum6QS63j9CPEIrBlaFyIx6i8vtrU81wifB0InTJT1gGd/lbNDrRs2nVc5nwkGe7L9R7ae5Gz5jgIata/jELG8ihUwYDyAPfoUHu+44P+ZU2yeBCGUIBBhe6LBVgcKHFtACDC51KAgwu1OTiM7gRD00deo+4ZLTd6L9xPiM9ZmPA4F5FMheq8ltFUPosufYb8nYYgTHkFQhCY8irYFehwi+Bf0gqJECh/VQRfKHjeOjAtfkkT5PS+BqS2VB14PK0vxOC898HYyj+EIKF+MNwpuGPwdqkdK2p3OBbuZaHntX1CXDp3Qv2d4gYo2ngTwFyxUf7PcuvJVjsN7i1+kpDIxMDOfipL1AjVbeN7ojOfZJ6TWCFUdkI71XhKcu249odSVCsQOmOsBUrsO2OZBaXulSpPaKvO+8WKm3V2Qqz7ohaRdIImZM76JtLL61gDn42AYPuSDwIDWJ3BIAGr+6I248td0qsbfcGmhR+c2HUEKY7wgEEkdsOhQCCaXdkRy/2sHqmpU1KSJlC3p0ZBwjWHVmJigzUVXDujmglxugNoIw0TmQsrvwULONHoO6IBypOcxUreJH6OvG7I92/dZry3G29zYEfcdo/+57zw7E7cgpEDbE7sleyGC1Gd+Ryfar16dg6y+BQ6tspJMPHWHRHIDENg+7ICRAVxO7IXgnDszjdEfewSkv2Dm3a2mm9Sq/2jXZt9e4IBwLE7sjepulU01a7I1cuaTfK7rKiHR2/Mu17wfJb+HdH/CkkDaUKFDn4B8WKf90R1O7ItYMbD2q1m2ieeTslK+7+FFnMuiPQ+YeBJLYzaGtESayiUgVxuyPNZ8jhuyMk+4i4rqstjEoqUudYb8kzIVJ3BLDYL0U0iwGzswWbCf31woyuRXQ1OVRvU7VX/+4VHJsJ+dPdGsvXLjPdtfpJYnhy/CIMfP8VKpIPgLKiBZoJ5tV3qmuSppomXr8Z3i/24ChCNRN+8gIEohz8Q1OKvUF4Zhu6QsaG2b5S96Rh4rgw48hn+UPemQy7gQGzPYnvl7DM9qgmyG8SHvI1Y9xG6OeeMU+Zx+j0rGZSJ2wgh04ZDCCfoIQG+QglPuS32mQzAUqoCTQToKs4gWYCtPYUaCZAp5JAMwFqcvGbCedvJXV4ffKuZRq78cL6k9QPGDQTbrcNwtMtNvz0twO7rXe6mC5YnvhWBVfC86M8GuFZI48x4em2KJB5aH+Byf7/NO/0mqg6BjPC0/u5dY/p3T7T0maW3e28d4U+BoRnozwa4QlAgxPhuVqvlCxz+6x1aC/ZR+eXhbkShvDkAIJIV72Ux5HwNL/940pISZnNts9XggwKWEYEIzxrUZGBugrOhKejlFRjatQVat7a6bPn3VFYTSDCsxIVpxPy/MR6h/iE5zOT+Ky4yn02cR/yNOZ2VM7EkfDUU0AjPLUVsCY8Q3su2rCtZgyltCwm8p7SC08MCE9oTMOA8OyngEZ4AqhgTngOL3ze8cbFXMvUF+0mhekkdWp1wpMDASLhCUDAm0532yrhuUKz+zKV071tYx48GVHzcGo6/oTnfAppJYgqohzcSeEf4YlOeDbu/xX89s5+m9L6KYm1lxK6YEZ4QucfBgrS5aCtERWkvgoEJjzxkoOfO1+/cn33NPNE7bz2Mz9NXE4kwhOwmBuqxZxa1mL/a3JwpYgDIVOtNprH11KP9FRvF4ojg4s1Uwa4hj2qa1gotAiDu8pjjeGp90+Nkkf+NPaY49BAKAZXhsqNeIhycKemmuE/wtOJ0CU/YRncdHk0OjGpadVzj/CQWzMaogw29zGN75es+dLMLRgbyKFTBgPIMxXQIE9u8vL7bZLBhTKEAgwudFkqwOBCi2kBBhc6lQQYXKjJxWdwP7h1WX9qU5ZxvKbu1Fy9LljIwWuRzIUqB1cT1kBLLggX+QAYpbHIaxAkxyKvg3MFkRfBy0EgoQr9R4tgLfoKzMXhKRQSAwx+/oK64wdIRkQVhyvQ/lId3vRGGKM1jSEYq2kczkhNg7DG+aly/Ujjeg3zkEEaM4ZVj3gH/2NE+aGmkT9FzdmLRjMey+y1WJcS02HFWBNxT3xGtFUqhRTXvgKiEX+IWXwc0ILx8cWx2TZ31KptYrU1/wvQrB8mEB+vP8m4O0vRgHa0bobut+DH2oIdrkNDYi4Pi7BeV+yfqnFyxmGB+Gi0yvs/+9Jik5K1Yb1qZjb0EIiPx/a4ZzZeTjNJCNz/yujbiZ/AkCxvyPxnxSbm8nrb6JudtlmrP/IEhuR4Q7dGb2SvfylPj5plX5RODUgFhuR5Q9seRWTbFJcY75q+1LCfny14Gwq8oSf2pddImd1tCm9Nfq6XWb0HGFLkDemeq+hgZZdlFS71qOv+qaueAENKvKHH5DEn3Ae+Nl1XufxIzPd+14AhZd7QnrNlld87OlgUvqualjZTswsw1J43lLMjcFXfp8b07VlzDPqyzuwChjrwhrxS5+cHhQ80i1AY4eW6fGUdMKTCG5pSPU23gp5jcvjeHZfbe1hhwJAqb2j1kdJvtiOG2eTm2eh5l8+YDQyp8Ybu5HgPMdvTnrZ1ELPbosXdOwJDHXlDVZP733/5c5DVnj29qxNfnd4IDHXi2+uN1pi0kq02h9bETBug/eEAMNSZN9Tb6bH1hOr1thuyrS5Grk8CH4ehzhuinZ8R+6Q0l1pWIzt5xazDJsCQBm/oVccnccM7xdEKPl2zrv7Y5RcwpMkbaretcM/Sb+r0rFVJbIahXSEw1IU3lHvC9k3o3LH0qD5Bl2+uXjMeGNLim7Ii3MH4myp1R7k0RXqlyWtgqCtv6NyU4DD9nYfpsaOzJ7OWz+gGDGnzhlwiq0NuG92kxNyw+M9VaZEZMNSNN9Q4sfHhVLm19IOdY38t/PrACxjS4Q09zMzzMdBqTynz8jp1ni4DPhykO/8DfSs3jkm7abplwUIbh+drwZ+sy3eALlNHDInrSs+PkJJ+ctbQHRjqwRsyPOzouotx2CJj66jJLoHM68AQmTdUu2TMdesaeWqSSpWW59CCm8BQT96QBjvsvJb3LPqhJ0nbvgTKPxQpF3qREMoFqaLBtB1L35gX72NtDpvTcAuDcuERUvTScCvflXr6nGl60cPlF3RWCm9rlDdd6uvFcmWIMp5I7d5+vHeAjGcAezEDWGP7s8h+3s5eXkB88mO4ezN8/P0Gi0V5QmMX7K2J7iziDYhbIgOlcZ1aBRh6AUOLLATvUUg1ahJ1FdSonN8N/GoG90Zgf9t7y7P9f1xMszxaaOgSN+1ntLCJOR8h8st4l/+UDfedDjeSfXvJfFddjs7JBx9VmruG0KOQXoIAucLSCTEUUq0wQPxuJ9ISa6Q9A3ANPyYAkivDheXty/Jjcnhx4P6YXmTAU5r8hOwMLMWcgWqE6QKLYru68Q+7XH1KSza23LdBRXeAsD6g6XtE9QG/hzAnFvQ4HoMCV6Vaq1Cp8ry+3u85B20K8b0aslRGcnQD3kRz/W0ufw9nf7K380IGGahNwA7tAmc/BjcQwJ9xYx4WZH5yoEluQPug+hlWRRBOjfexopVh0wjm1vvIc3YTOOsFdqaCzi7S25cQuJ7TGGx/JvBKfh+bAQUSFqxxZXrWdz/XmJWOt7O1qeumIwwW/zNFwWoawQOsGlSwAFfn5Z/HiH23Hu0WJu1Wo5Rne70dv0rBQuhXqZqCrVmwyUJn+Lj7e4jmIXkEjMulmt7Kz0TOoAzJBQAD+ACym7OLP4sNBBuWjzuZCbiuF+cLBvO+iDfuR3Zx9iEvYJD9Anx9vZiAhRawgEHg/dyPDPAB3+rs40r2YbGBHMdcDryEc3Ewmerh7OPO4Nh3ts0csi+/UcYRBbHc3b2A2cHwX8Jg+HBe47+ERfYGnEDM3Agt3lFhE/EJ6AvENTiJQprcETC4BhWuJfiSQurRUaJc2fF3ruTdELwALkY7RWumvUWBztakrDWDb2GYLKERqLnJUoFCmggiFAsb/aMopOEdJUqWvYT8kaOd47oeDzDgpbCQfdTTilnKXGq14fr7kNGGB4UPjZRDcAv+dcwDBYDKAFRUAL9p5faiHIn/T+1kQQPxFUpIBhpBcyOD8i19ziwWthbTTzAu6BkONiSvJg8dbDgA1mR1By4w+2cMs8joKWuzL70EKnZr+iAYsdvvMTxMp4FqOuXWMd2fyxk0jUt3OxawMAFTAmg1P1+GC9MNDO/cLABrnpzo+xeenZGjpvrIagcYXIJ0HjifJxqEuJcxN4oUlRtl4Dt82lQwykikQOznCCYrAJHFDG5elACYytT+36oX3rDeNydGLnhQV2GRnTzvg0WXafwBPMAZgApOj46SiRD7c7PU7wwuCTpyR12lg2KWWAdtUQ/cu0uZJbxEaZLPiC5Rfg/hgZAGKkLAnObVbU+Q6rZzac70H2O7mAfl6cq/7L1C+HhKBTpQo5EdTOjiEwcUKpvBrda8wPfyKmFghegG/BWou5aBMk+2P9kXnFFAsOX5K1h78Uq3VeJtHIVQm/D3LVpF80fExdiOQprXDcD4Lqx66jtQSHWTjFbg3IAABrC/zudVmfMk30jTqIkzc1+c8V0kHKQcwHeLBinu5T9VShcOeBy6YbTcOiooSEup/eDeza2UZlBIc7ohamD3U0gO3UQqJTRVlhYHIL5f6Lky2Vy5HXyyXXVGUffjzFDz0LlVoy9nFJGFp6UJ/82i0/L30B+7EsNiKNa92aaR75lp46sSpmIAGA0VMMCjWqWI4uYM8DXDSUj/1IsUVXzhFpwtlTm2RImq70ZOci3+UmGd027x1HGd5mh2ovkAkRIwhulSXzawBBf4LDljioPejAHNK4Ahpi2aKq89ptTNbKenrQ81nf4DA9OORDXtoFYyLVx9HD9ZolKrPV0gnsOrV8yN2csXPKZGp8XrsVTPLhZWSYJvFxUFca5inhiVqNyYVAwrCgJWvcAU4yXGp0iJkVLd5b/Fo0uNdsyeqxU17TBd6Neog8IQf5D6NGG6uTHYDAAKP9EkiaTRH0JleQOQc+UpnI9x/f0xnMUhmD79/EFiCdxwJVZGhHb0/nzDIuaAfZW4oJtQSBs7AaA/h5X1H6OQwjuJZEoEVQ+SDxrTBUAB6QaWL4MNVhvg7gauj/uB29E4iZXzJ25M8wPZaNYShit8EhlRtunqqHlU090Ty48GzXk9UzjGTAN3FYhixb/+pxjTf/Tlxu8JD2wz08fv0Pl5xKu5MYZOISWBMMtQ4ETyYRyYm0sJ9xUwfxO75cLy8WO4BHDcA9zgBM9uLvxBt9eK7mCz7aZP/KWc8cLxWvn354ouf4UGMQ8JN3mwOcHBFihPBWHjhYRnSCHhgkrvhqGjWNah799aDb62xlRYu2/P8PVydmFwdsHBxAKkgtmA/z5QPOsnsJmS6+RLmP4eZBawTGGLHwmgDXyU+xTdYyA0LC666hTSXBBdZdjmmwyVZNHsua8JJjU//lbMpt2n8M+r7MJ64ncmzarMdE9Nau8D1cLlM+eDRMtn7uU/TWeoYKG501mHQnICkcuBLRkyKST7Tojls5jIdWtCji3kaqBrwcK3Nj3w86aBV812p3i1+7TptLoQfO15DgLf0hEexXwWA2hZoKI1qVOLFlj8GxVRy/dGU8uDRa47gw2zKaK5gVuTkyBBwwIfASyql3FNDX+2CSQxNWeSNNeuoE4btGu9MZxde1DBWSAREaZlw8GWs0eL4/0814ffi+s3Na93ZLm/1d6d6w7STMZBHtTG+VUwjQnOZTygsECFYlJTonqOlKgIo66GRkts1NUbFmedduypQjnKTtf/7mSbh4G6WqcTmrpavQnyF4SHHCqbwwbyUf7JQ2RNbS3i3dpv3Js0ozsGkEd1RoM8uDMf8peYCTZV+ZC3gGATRl/JF2zC6Cv5gk0YfSVfsAmjr+QLNmH0lXzBJoy+ki/YhNFX8gWbZ751fbVNeSQ9fjOphnZ4hYuI5A10XljvgyozMZC8vUKyfy+rUwb/7VYyy5dxXVDzQk3Y/p25ZD/Vi+UHloucBo5oUS6HMNt6mTF9XDnNARfeB3CWlOA6kydDEK+9D1Wj/vEWRcCBe5EEJ34kg/2Bm7Dc9QkKaYlkbf5u3G4bUEj6slmcIxtYoCoQWRcUvKJ/ZNju4aabYtfLBqXve9CcXhskIEHbeM0NSMC6cENHXtqtFwlI0RRSqGjDHw0rjSZJhCBW8A8ZqHddOWtnvsWBsMJSS8WFlzCURaydavPhbN5Ss0JWhEU4ZdkJDFBagoqSR0fJDinQt+PPK85k42DGn3LgUo+vPUNulThFT7J6/XONZfErh1vdjBNPtWY/9zbPieAbcnJUUpSE/dyBTd1DECIuPK4sb1D5BGQgodgEC8723uNq6z0KrUK9No4mHa3NIkLXEgBpLSpISyTs6/Y1YXJ/eRNV9dtlOI1F5AB1fXPOllXui61zAipCtoysURTuIvI/V7SL2DSCBzreqOi4NPV065AS46tpNnSZIV+oG7ZUmmXb0maJEvGimVAGAdyewv3cJqnbEhaPZRUvEUL3XojbG5DgkIunHXmHXIgSUI0U0mXJUp14bdrI7mvKdWpLLZPD+xaFlF05LUx2cvqxCGldaPBPURwa4jDYWP4YBMsO1scKKKTbkuU6FQ5YDGCmIUNlajSk2kV5Ei100a3kw/5blglHIlPgvfBACQy1dEngwfEaFJjOSJjs/txCg/aaW6+FBkQajo+ALTSyyITqSAWh4cWh10hxiNq/csjY4Pv0LLPsd/5ju3aH8tDezr5kLk8Dw5cjleb9ue/jd3s4+1KcyT6MJeAlBpvpwkuQYoUl6L4vlDuEY8oFhsXFFaicZLtUcNQ5MDV5OyrpiaZEgUqF04bikrvA7cD+ysm2czrbjB9vukfF1VDmvS6kDOd8gGiJxL38x1OwIFvgmjvnSBSSNAhPEeyc20ghfdGUSE3SgXs/PJ+A1yD8WF1acTuUulWqbHKZ3nvhozJ5P1e0+8e7/id8vp94kZDcxc08ZcqGMs3B+doY4PNWEw0fwH1aQ2GgwBFuLOYCMYEE/UdUNoKmxe3g6Mx2Z/ijGS3M+PzO+f2e0DYusp5eE74Y8hxr7vtFjca7jnmwBKxyB9UqVwhllfqjfKtIlL5UOQHPl+HKC77w55uNMe0XZ+tukmHbL3xd/5CVwoax5rxf1DC865gbRoXKDScgzSi6Xu1FJTVqSrYg69aEAWdh4cX8Ex6r91z6b1D+O8vkoHoDX+mxL4VVtVTuB4iqavkDeCDyRBMNkRpNfl5/g5TXixOsGmePH0cLbfzhr3DydoOwjbnfKL4YZkLTCkM4gZOXeDBdPICyEtxb6OwHrHQFVDG89C/e4gO6hRvufkV9kntdAp1oqSZPJyqqfgGubhXN6xJ2wHV4pQaY7Jk+Ll4BruC2XDL3TuAPPrNUn/5L9QQ9rHLmhkDmi/bCzodU2DQNtHTyn0Eh7QYxNISVtqRwMJQoYk2w4XmUCdejBDdqgXogPy4/4MF09wD//LumJK+wgT8wE5rPhV2J+zWirsS7jvlkbuQBpgULWAcqCBhvMr8lfOMK6k3iNK6kyH90UmibA4POVYgmWudqZRPm9UiY2+wzqzpHOkUNnNV1PPOlZUfh559aB3j5M329mC6cbWHin1LazRqoB4D05A+804vsLfQpYsVJ6KEVaLcl+lhW4XEJDgP+ps07DFiUuDkBFLTaMKeT8vMJzOmk4DdBTydFOn1UCmEcy9NHkWJTdzMmG4g5TUfpC9sL1j4No5V6rDSytUycIK19Iuz9jr84xRh6ZmHVwAG277sbWMatvN3oWzbEAYNTjL9o804xhhXovNWugJz8iQaSrgPDhQVEaElQsv440nzd2aNGoXmBo1+O3jdZGCWKKEqUP6L040WtwpXVtrYRY1ib+l2UN8IApSeoKN3RFjnZEVXtwj2RGSyMxAAIqnpv9UOfOR7zGZZo+sJBihdP37WxeAo96aeF4umCLmjxlN7lXzzl2celZ68Y424BlpmORiMb6rc5YhBPoSc4YRAp5ndBixTTuuAdT6W7548+JbXaqMjrLbPXqLlTMIinUJIAA5ToqChRuuAYT6E5tNXjKcdjEOMpgBQvnr4n/JoAOp2wEbONlOr6Lobqa7L3g5FHcXWMPQZLAnIXtCWBVhPkDZiJ2TryIW8BMRvM8Xj8UA9zPB5fzAZzPB5fzAZzPB5fzAZzPB5fzAZzPB5fzNbrQd3BDkpfqId19z71fGZyX0DMVnO912271VvMgo5teGg0N7KfwOmD89LcOn4wfmGZVHXcNnxFhqrA6YMKvScsLonabpR8L6ynxrz8uyISOE5DD85noSf1YSCBa8TMa5Rb0Gv+7sxKmAMc+V4DFRGI2EQGySbQIxIxsMkHJJuk7q+dGfb4M+3A/j0Hdi98ILxxUNbO2YfhJXpaL1Kk1DMm+4Lv4J0YA57oSvZh+TO4pxWBz1TiPvUGnv+DnvEIcyvihE9lBxc2y8vLHkyB4MXfe0jrJ0NCa/ef5VGGHwzoyWkbn6rNahyBFFoVpvox2I7A7fO/tq8JK2CBFyj+Au6Hc5KQK9Of99uBkgVsmzwMzIOYRBYpIvsak2I0gIg8lkoKDKMqWTuz3Zk+dIabUEZV5l62Z7p7CF1X5F53ZPkKXhUO6/SaJcarojUqVDkg2rHBjYj+TO5dyfPvCm5CsZ2X0HxcwXO8+PBKKYIXwV6OwCVO8Q8qbpoutXcAj6lw9qKCh0sJZDbOaftNf5eZznb2bXoPz1U/Ej7PQ08cxYj7g/o/Bol+nwZaot+lwU/0nwiPOfQoV+LyrTtQdwpsbdop8BmzNNmSR9/DnNHLT5MwZ/Ty0yTMGb38NAlzRi+/uDL6Nnflo7yJ1oFuGmE0I7968Y++h57ui0EG/YJkLkWH5MV5AZ4mu15/ZowmF74XPhSP1y60Bv7FBuKh+GcJavMbjT5kW1+Gjzmd7M37DPHaiNBTjFFvS/SsPsgLxPV/YB2X3B3s8VBJpMsi6zkpKsmlu0hjEU1c0Z3rv/wzK8GDBwLAwz09nH2ATAZ/skDatBxPzYfUIP015eT+i52F24gm3E8QbSPyB7B/5guFtAGEpABJbhHVvVXkFrIuALRNkeHAgQO/JDkikCxsGPBUqgAvZzanO+kF1ijwBwTeZxyYv6qD0bbrZ2WfUsrvQI5e5X0IzNGr/BE8rLMW1TpLiGAdIBr9kkST1MPUm+nHOezYRchM/BACa5zCyzVDRm51tdi5vdYsMqj9QGHjcD8Rhvr9PYKHcbxRjeNCBOOA9hE0jvQfjDPa2Bv8So5NgNvxA97K8HFZxj2qcSKZ5eu8CDzZcSjnb79fAT+jfJ1CzxzJHWEaMTH8v7H1l2jCu98dBT5fdPe70CgexpuJajzb1jGeGMdvyvzBghN/W9DPg+mzzAeodAHzAebyYfmApgP+5MVawhkE/2oIDnk7L+VegLXj7auJx2veXzPf/O5m92MjpA0gZ6h5wImpeZfxsJwpquXGt7rlwDeBfRiJBDaduCw208cdPRDurSBf3pR106hwXsTszwV9rgsHQsSa6fcI5hbpQOXWEOCy4qxIWdWTU1bx6tSvSHVqV5kVDicONtoeVdj1pN8oyOPaeM/fIduxGYuZjCXCZSqIKZIerr8xeFaRnwDjwzl21p3B8mb4s5eRfbkf6KdK42rAaD72DB/eIgW5eIU+ZwPtXkV7kcLjKtOAf/my2P7cpwfyXyU29pEU0i0Q+xTYHqU0lXRStKTlr4Jhl7zmfGw42y059yhWRT+6v27Nmkx706P5Ux9pyxy9D3niNe9TYZ54zR/502JYNdW+n7UL22wzM7FPbU25WnMXw7EU0g0QOSPYOHKEQrrYXSJ5vIajQAlDZi1msNlMhCdd3FKJCLqpYm1Z/OTm7siQ8y7Nn8IQrKAxAgOsTqJiVd6yMZdPVsrzllzgi8Bi57+s/34pMHgVH/8ixZDyS5aT26BZVYG/MOC/FPxve8GyR/gdTcvtb0hh7N/R/X91dD/08UQtdnT/QF20o/uVdPE4uv/KyK7ft2/wpmQuMxyc5SwLOdehWXvUsY6RChSSni7aSee6ui1ydL9JSlLo5wK6ZeQtpx30vZa/Wv3ofnVUVAC/IczaQbLtQtgd3b/iclydSeEk8+Aa12F5W6UuE+bofhKq6T62zuKhxY/ubyf7+dKDlAE2cT8qN23bEpjbykf3c6IM4tnrQJRpsaP7DRyWDgGKYOOy6S+dL6X2FH4KWesc3a+OCo6Sbgse3X98VVIxWXu/2RZdsyrHYBlzIhyCASBEQkXoY9Py8ztS3WZqPHDQr4nVxgX3dAuvbn47XPj0Ac7WP1+WF5DRRWs2BQScR/5ukTB/v593ggaAOJsV4O4B1HB+DA5VI8kJENBHNiLerehZCQKD4uJ77BgppAeArzMVJF2g+Pankmb1aO52LPXftwVc5WEB+9M3myjt8gz9ahn2yrGf1Tpv4W1Yf/XEL+jjxjOlvukv70bLqOicn/hzSllzS6jAY6QgEL0eVDjvTKaQlvaQqIRqz52+rgx3NgO+vnwzZNW2jt6etms7fl839lZQOWRfFeeNMPuquNcxn53A7/dB/f2uPVq7WGryTAkKJfCWmSxXpgvKiThlB+I6Lh3Tz2SfzaIFw/vF3RX2Vf4HiPpq0wgexpiFagy71jEGtPwhSdKxGGzlw/IH0pezC8id6hlOBJaswMrCW588dKKLB4vtqk8eNtFvEduf8xf4avXmwyFF8dOnmmbP6zqz6u0H4eM1FMEvcPBf5gXz1MzfQ3gYywzVWBMIMXPAj5KoWtX4TXT7BLAX+KHMoMt2J370sncz2xf7Ymbqz20NzVkqN9ccw6ncQA5uEL0sYg4z6nb/HpJVqbxIjlJtaXfod/Ql/ZNx3ImXT3zCPnZt3WUvAIAHH4CbMACAoUWiSpSfypCPpriU0Lh4P6XSNi3/4Qelk8EnW3eLMACANRoA0yb34BeaP9qYHgf6pO8W0+NIk9H0OJdEK0uM9Tj/3d5+Ll01kbb5tFy2tXXicALocaTIaN3NT60T9IVFBdnZ2S2gx3EaPfmzknNv4y3JZ2ujfs0+RAg9zuseaNZ5RATrtIge54e/jrFK1ShaYIKvQ8ejh/sTQo9zC9U4l4hgHFJr6nHe+oQcfb9wq1HYkMdmiS8+fSKUHuc0qvEOtnqxSyA9zsG8IWvC1PJtjzbG6U3q/mJBK+txdqNaLr/VLYerHueT18D05zIPKBuulJ5RGqBgTAg9DqeGQNTjXGqqU3/+L+hxDA87uu5iHLbI2Dpqsksg83or63FMyWh6nCHkltHjOHZr11fZUd46/8HKjQrzx7TDXI8DXZtjoDGhktE0JmPJeOlxAkmJ1pH5b6khtwPjrr2p2Yq5HgcaIzDAaggqVn3J/6/0OL+Qwtiio8xBTJtt1H1HbL2ePZ79VrhTMiUA3CBpznb29RDdRipB+6KPCdPPF9wi1tTNWWbA3UpKdgZP2nMHvwHW82qXjLluXSNPTVKp0vIcWnAT8f5EOzmCgyL+p+gAhDBbwf1WMF4J3dwkplc2fRqMnmYyeJyXJhX8v7BXJn6QplAnaVZ0cGB4AQZjuNKAuL6U/3Ecs3JNCdoR1pRZ62MC6iw/m29cpOmXGqk/R5gLMgNFA/6imQixrOa+gewHRDvu0wED/MBUz3mylQfLyxU8vA6UQrlxXscpA/yd3f3Ee3woZGuYHJ3lspDh2vQmuFsXpbG418UNCXpA+FSv4Bx7DCNmkqOSeqvDHFYDQgTWrzCH1YD/hx5WY7Pu3iSHildGIRfKAhXe2VZDD6sJnp695ravk0XKsaxNT1OiJ/HH+Tvt/vowG+gXwxxmg2RpZXBrNM+M8CTjt9BFo+vCKCmJ6y6f3vr0V3OshX0xZ0ghGYN2TYcN9XkU0mj1VnlMnzL4NLx5fsBv8HH/nfZ+/52z5FhhOM5+FcyZOki26mT2e7YBicA/gA2fsLV6j80feGmhReJt+X73+u8djGoyeSr3k2BOhuUN4GE0A1Sj9W5Zo/HXRDJ0Kjeggm9Z0zTvObbhz1GkJNfLhPegYKaPH4PNURsBXyEUMGFtlX1rhnWf611N0sy3pgx70DUbait56wB/5wVeTbvzSRCSH/xWQ9Hd04Z/PBnpL9MbmlG7ohpVVV3kZCTU4+Z5zs7gHj4BCx70DAhUR5cBI53oQw04VzF38U5Ublw6Zgz3XHBdTr7hpXQppJQ+5dF9W3mvKvPM8iPt1uztGSqsEXTwYLr5k8GncAqndTBfIT0BuJutmxtYgjl7efEeVskEHzMGHnU8GBZg6OPZkG4BZvu+uEhlUUh64K57RwpcZn5IISl0bq5+pgPnWaXA3PQDbxj2h0YvHSL9NnqJedBmX3vFAL0t0MdhwP7EPy5soI+obu4cy6WQ+oFYpRjDzbF9FJJOZ8nUMlwLsjheAYvLgQa7foN7/jQvfPZATeeNQaIIleYmHjDNnU/AL++E+ssBLyEAjcbxQAl6C8rgISpo5+q8GrZhk1riNdPchDq5hB+yws/Y5BzB0lLw/+yEBn9jyz4NmQ+/iDKmuY815s4IUOUJ/BJYi0CfT/qXkaK5FvnKCwXHjOASDIkKTghegmmHlGCmndv1JrZfd7NYvzeyZz7pC6fLDtzzfshcpk/8s0z7ct8ALuxdWF7gahbULIJPRwYnBNmP86niLRTTbWaMY10rMQsJPZhaNCM8GuX+RJ+ZIzQsLqrhFNJLHQDVVNhkVEMhnddp/jLRt3zcYNN1B82CvXQ6PnFWrvrTmaaYLRPFOPMUyarqHEKCc8QMKGXgWhHWaJWq5/teNL9iXLxLXUc5ME34jEoZczjZLffqn5LpsrGHc7e62VKD0le+HPnsUXRzk2k0hfQctPVZ2Ji2lUK6p0OElEIiCa1D+E4CE9OQbNeFJjDzwIUJk2NLQ/hTPgZ1ia3eNsEoLC5CI0Y/chL6+kOBN8v+agXibW7MXr7gMTU6LV6PpXp2MQYGrUY1KDB5EVZ0zUNyKCySR2YOXz38rK555kLtBtngt77iITlUFMmhf0TSKHlIgsa5eNsgB7mtI30aO2OA5DFUJPfqiKzlJDw8TJUbmIFMixJLoBv2/rAY5kIoGl4c9AwHYJ+B3/DiB/wST5oKuhsvA0u31Qycf2m8uce52aYbTDYHbVHuObtFMvAHXbQMfF33XwZGz8Akd39Fq1vLzVJUVadOik2SJnIGbtBFCzMvWn2naCtk4O3z7RrXlSjaRNiT+4+2TvfGMQNDtzliYND7qAYFJm8LZuCdOSfypj1bar3ui1y3Pgqfu+OYgc3Dsmg1VoHmqbJrgxuuUxUxQPICKpLHdVskA0P3exEtA3PiB2IGBtyNl4FlkDLw7Yhe8Xf1rExTqvd/3tbbVFOY4bQL8PLiPhNYtHfKIVmp3Aej2/p4LWtyDdg9t5xPcuY9KpzzINnFzmwmw38ZGNH5Ch/x1OjRA4IS+mfZmJYPU+zS//pKf6RbFt07/ntMXIjVKaQNIMTKVDjBzhkKaY1kh0Co2/EB8GM4s108yG5sFrznPc6f/HUmM90m4WoBU9qCdbE5W7BxDns6FFKiLqLeZCWFFCF6DoSEFLaA0MkDiHq+gCHhCcOPL54GLOuZY7a2etn8ted3xWAubPo/9q4DrImsa4+KioLYBcQSsIEogtixkAmdUBR7WY0QIBqSmICIWFDX3rCC2FARFQv2uiprw97Xtde197qWVf+5M5OQmbkzJMsEsv/z7ffsfjonmcy859zT7rnnHEz5bCe65hO89fWbPy1rHp3FA3hjOcFLqGfcKD4HQsQwl7ef/wBBJLFAgcT1Cx8AhYyuu6lOLrnCWZYUjcy7irtNitYoGDopNiIgWkYdq3L3kREI6BrSYLDgpRygu41KrRyijRfAuGsMQShkV8ao9q+pnCFab/VDtv1RHyVVyrQ/wZQyHcUUQI3lBCpBZwvKstmC6Zf3Va24zyFsXMxXl4TU9pWoilU3Hh4ycdSCBW0n3xHxakkk0UJAN7ZeA3Q+2anIMJWP/hCMD4zP8slcPGTR5LCFWWxPxlT5BTRDkRyPIlkOZMUyU+VfR5FZDqbo++OybUUDUW9h2KZvt0aEzp3bnse+P3wnmiahyEqA0BshAhl8k4UjZJTKIiHCQFHHEyIChSgqce2yiKvJwkUPX62Mb9o3kbYZB74NqWvHL/O+3t6RGJyHOqjlREi6g3GKqTKBgW6RQBGwnVbl6cPMYyG/zbXqGj7PhyokZTBZZ7w/ftEUbz+L8+1/ddBqm3Js2uZ5z1CxRYsvogWrTvutCAvsS99IUkC6abDpGUfdZGMwyaGg11ii0qjOGSe9nCRH9nbx2XdqW0aA3dgxzEdiuvbgqqGwDUKR+SBldhqqWj6gyJg6RqmWKuDHC10223r/nB/7+/rQSce9m1TcFdWNWkWKrw8W604hFqZlPC5nie9apfinHVs6OcL1frmiaplYFJkLwAqHOkaYdp5SB1rxzVpQg4PFvb4OuyxKC2n63HtjY+cWR/t+poYWFXS2hHnQv4BUGExtppSZUnaHxGd/zqUbe8vLipyrjsWlhgOm+DrGKWNrQqikMXFs58To6XZDlwn/egjTNLiMbIZaoqoiAA2ph8r/P4qAl8esSfrj3AffVZPeSc48W3LRxBFwaB2uCLidcTrL8Aj4o8XruRHvZgTt6Nwxtpf97c88RsB0T4KHIE5chyuIQ5m6ylQR8OZhzVMjb+4Om7js1hZx5IZy/4UIuB0neG5GajCjI2C66TKzCBgXLdbADq1TEhFwhyUaq9O1XgUtz8osPVGRLDWLCLgdJ1BuOltg+f/IFkShb14Flf0leM/zusHpe/tXMbEteO/AZQtuGRcaG24LZFlZvU+8cBZPU3WeP/PB0bo82gJ6TMWDOnvrwKXOHjsUmy2oKdt7KKrzw5A18S97vc9QLv8v2IJbnOBdMjK1YLQtoPvnZmYLcNFiVXGPjUw68GML7p3eEHxq3kt0Up/3aa97T/5qFrbgFidQl3T5iQpstsDme2j+g7HNxTOWuvTvqf5GFYQKoUB5go1zw08fNOkORENCnCfUzQUHB6UEoH+yYrhELouSxSfB93JT+y5x3ZuJpu9tMVZad30zlqdhRqY6kqHYiVEk0R7D7i60AmUrivSyN0rJW4MfxxvBS1lKiiV9HTP2WTv47pwaVLfprFZp1HgS+lrE1cJ2pWfP/fPGvVFLhRuXeD6tMD5gfVG1U3cUSbBn3XAdj0NjlHaqAbppC2TRhDjINALALXi3o4ZJvV9c2+e9p/H1x3+7nlhKa5gNmOwnl8RAMuB6NN7X2UkSEBVUXZcRIUPtjVNItnRAAollAa8wvF125OZpbX0mVxmcu2DgeGoYXIn8JgssNLIpkJFwIkMXldKFIOMixM+BJUjkgqgCqrYZEzHsEqQCWbYXpjac3Xt7vwnCAzY9pj+fH0Hd5NP/PWYSUJ9oCpxCOHES2Ws1dUU2Td1xdLNT24Vx4uz9c1vvd+66j+blgMRwqBJyTKwMC9QNw6VqcCJYQJ6uECikMUTrYefQsO4C7M9SF/h5sWF3E7useNczeGfZUU8eP0l4AH8SiL9FUgxFLRVF1gHUZmCo3WWgdghFFhunoyuh5JviR3Ggr7ZK0F7i/8Ul5IDt7uRodKYj5dVKCZlFQ8JCnUe6Tiuqep6PImsAKu5CoKLpqCzHUTFKPdtgSkKq1kjBKksWjobiMvthuy+fbsiEqeOvZiHfNz6jFgQRXYKY58HJ67wvp+skBJ+hEHzBISCXk9V/tSi3jeWguMENPvsvVtet4b3b8bnpi3LjUeQrQHU31CV6hCLX7f9XlMtdlDt174iK3WQV/Oa0aLj00K92FrwV5dLXX1GVCBYyfLYn22NBz3G/sjfTolwj6x+NKsrd6HfrSDt5Ze+V/Q+fOl6+3x98FuUWVedhHPuLk2PY6izGqtvzycvH9A9aGpIeELmvxtBP9UxYdbtyxp1Tj4+VE2UoytZOaH4umQfZP8+J5DH7Yqm6/UMqrdH5SY3gOYkLG7+2etL4X1fdepig6vYHqSDgQaCVCIgbaWKt2UysIKbBzikzp6LzDm8QL/qyJ5mazuwmlUuSqKbVSJSrCwWJMrVUoAZ3IoMDuPdCi5AhD8IcNl+oTr7yh9P18DGr/MbnLbjv/cu0xkWVy00o0kArlykMubyCIg46yCuZPeSn9sb+9qf3yJDp48fbVbR2a8AP5PQlwwPkjrW5ILevrYXchg1yj6xuR/vlrvNbm1X51KExHxdS39RfrUxQUSG31kKOKvWbk+GXiB7R4JK29RuMC/WEghhwX9wlUUs0mlilSiVVk/zQlA700QJGT6hhJK2nRY/iMJLWaNB9T4xUBoEnmzCSBUmis9wy0GcghTPAc4YKi2WDjsO3Tl/vnXZ7smPNgWtuQiBkCguNx4iWxwS7Kv83Ep7rzsQ9CJlXR7ytY4cVL//6balJE57vbbkSnpdseU54trzudulN+yeibX2Wdl8x5vsy3hKeo69n14/vrwybVbpGpw0Ph+/iIeH51pYr4YlBY6KE58WRJzrnHv4taH/TUrlOoQ5ZZpPwxAFhTVc9tjVhwvPPfbWf9Ot9OGjnzdFt78Yue2pmCc9bnMjQRcXECc9WsRWqhnwcEJgqR49aT2+cYkYJzxOcOB201RrWKuaf8Hy3ZqZzwOg2IfuWXZGHnwyPNmHCs5EdV8LT1o7vhOeFrHFPa9+YG7Cn3+FML0WbAB4SnnSdxkPCs4EdV8ITQ4X3hGebPuN/KXv2Nbr4xQr7Bs19Iks84YlDwJrwxCAgl1PV/2rCcy5ayWaE10/vXY5r028M9m1i+oTnIBRJsiML1Zku0RsU6WP3v4Qnd8Iz+8Y1z7qhvUNzvz+YUaa1YDNvCU/6+uOhgDzRjnVAajaKxNmZccIT9yJMkPBcuK/LsSk/RgoXHnrTJqbpdz9zSnhiHIvk5Fif4uWY9vktuyeppPov76QXgrsFS9UKqdwNfEbj5h8wMAJvBmxIo2ALjxYebYoxg1tv/nT3Fn1ahKzpmvftw9g2sSbM4PKdKcNEI4xTNHztiiWDW61m63rZDmN9Ni63c1n927hCICzmDK6FiNB48Ki2igisH9JnqGb26UR6yG+2GdxFtlzpxDm6qKe62UP+/eldywtjwsKmtlMuanymvDc/kNOXDA+QL7Hjgny+Tspr/CczuPQMoV4Glx6W6mVw6c60XgaXvpT0Mrh0lhuewR24OLrqR+HToPlnfw+bkry0Mg8Z3Jps7Kp1f6ZPtQ7nRCtaPziYezyROvm92qFd9P/Bx5pUJWYewRrwM29RkfhwIT9EjlGivyfkk9C+/8yPwbsy0JRWYa/PwB32mX9rfXRuLH1dLkSRK2BdpqDAApEsrcXG0h8Tt2ZVd7NAd/a3y8hWhVCHD1UI1P5D5WTFQjlZ8E0IAwuILHwr+ACMXQVU+JkE9eSTdnF9xb89nJ/zJaX8fZY3Yib2C0iFqVJ630QDVSkryzJQxK4umbPTscyWN6XZtBiV5qlFI4/3vvQyaPKaVf6vps8P11OaXnNS4+Vtu/jvfO3V9PGvPXL0lGbQ2VmBIW9u+sxuXblDtZ/vj+opzZU7mji26fMmdM6NuWdvnFlZUU9pnhmcf2Fdt2n+2bYDQlDbfXUxUlmS5P8jf5Fs5JuwGVer5YTUeDAEI5UjSdfaLlTPeVZePL1vtw1LRAkZGKk8Scp5MHVF6OatwtxeI9wba8L2YyRLknTi2KDWAdVb+c2f+8V3tF2Z0RipAkmyvyeZUz9yYsj8p+cWuDsFfsJIFUnSvaAWf5/eHy7ckrZrdoLXIQFGsiJJ7b9+/PQ5/6LvzteNFsUNGNwbI1mTpD9ezb2/OXeMePqDxct3r31aCiNVIkn1Dty/+iZ7ATquZf9S+VuXdsdINiTJp++Yc1W33ROvvzC8829zQoBNqkySqrar1ybx43nfbbLV7UfMX30LI1UhSTGNB70PH3PNd/GjdqMHrd06DSNVJUlJDzysqntaiqc8vbJ8S4OaYAezGkk6fyauTHxbG2Gae6P3fZOePsNI1UlS37TpAacc66BLLx4I8ZzcGZBqkKQl5ax+fKuqCpl7OjS83dTLrTBSTZL0vOrD2Z7VZgeu/ftSyOVPtj8xUi2SFB4z08/21Ufx3OETAi/0zt+AkWxJ0tA/6/beeHGK9/51wwL/9rpxFiPZkaT6TmcX90xf5L/v97UNB6auXYKR7EnSxTFTpgyI8PDL8bCbfL7j+XsYqbZWolwXf0ipstU/Y82QqTbNyyzDSA4kqZ9N2XLH6+wJWB87+ueX2mdfY6Q6JKnFs8ptagyf5zcruUmiStM6GSPVJUk/Bm+cX/n4nYA092Fner2v+wIj1SNJY9VJUevG9gpOrbf97Y5DPbtipPpaNB5uyJx687xwvtfJHV7bROcxkoAkiS5cyffPeBW4xG5o8Jhvq+0wkiNJGvbZ4sO9NmLvVVeG9xpYbddYjOREkhrnHRl7qnKXwNTzSb9798gbynAvgB6CatO1+eUjFtRShGwcM+DOibAP33hwL+zYFFvN6D25GUdP+C7ZcH/kqTqjMqlzdHxHqOTKKEjTDrbt4cbkNwRkKyAsJgcnAeMkcjmmusgGBAZ27qCrNeijMUf8kARDXWrMlc52zMfbDkDOP95GkVRH4/p3FLQGIh4E+m5fD/9jO8B3p2haL830td8XvuexMxDfUxqdUSQLABQFTT/MRJEMR6MGdLTuJsVEAx8+HSWNVMaplBoZnkfHnk8mx+e4aOVEIMFCNwmYGRoJRbFJNdXOu4LGIaszXUI8U+ucp7odut9huh0FJN4TEc64xHDANcnRLMZKlCrqWInm5EKLKmAXfnI1TjJUKsDcFrCjO1iikRKKAN4PsVPl5PSetsEL/+m9bPb428NoOTjytpBx71oK79z7RAq7D/SQYXUREHZGLYCRwDn2lKrjZdgntfveUjqQ8NYZZ8JnD63zIGTln5NP1l151ZUKlvaeTLB0FFOAlcoJFibqpP2xZ92nq1966PwtVdA9K+SvvUZbUndkK/uS3dUEYqkiJj6WaYfKs2C8p5Tuq1pLJAFlS5EYGNgNBNGSyHilGlM2SkUMfi5Wjv+AG/lDJF0jiJQoBIOlAk2CSiWXYRwarMSI2PeJWyYowFfB0VoFGOwlx0cb4xfdBKJYiSJGivO3X+gAgUq7sYYXESljYuR6La2wz4C2VnGYEBhoG+l+PSdsDJmgf8BQhiMo8gUwvKYItoX4DEWuGWcrDWyjN2Zn4t0dO+x8V+9Yes81uJSYR2NJ10BFNZaWKPI3QGgWVPtPR5GXxhlLJ4o8klO08Z5yBGDYR6GQqb7ny+KTugh3P+qjyvByeExNzbOIhfY674oCQ+UBJyrXSsYm6m1H6g8lNmbaVavAaAEo92qGr2Iqt2Qafb3g7O7mLhgj8HBzd4FPuLxre+fzuu/CJSmrFb3/iqae5qwYqrsRpDiugGYK1p3jZN1Rc3VnuGpi6hIdJCREE1Mwg1oWDdQ7YQWg7DmTWCrNwWebz5p6jpYPjlhQhxEb2a2kqEwpJSK0DHxHsLYIaBmjKhYbdwfGCkNkuJSwi0YAM8mqa0ryrUNhKRK/33avHEJt41KevDEzTNMSTAHOA05wrjkaV7TYhLBSBRbcGHQeVQ7ZHC8aL9xmsWfbz2k7D1BDFF25DTNEKSCZAqFznAgd1flttdn8thOLJeLv7W39x2fXK/+sQTL1vSzxdoMRPmLDEwcotdsn6QljEWI09lfM70rSb4mJKVtSXoHvRbpuow1ynOhZT/hzM71oLcVQjMNRZKsrhvFNaLXVPygy19UEbUH7+gcPl3iODkkL8z74yFc1uyjddGmeUq1YFbLZV4NOGPfDSn0/UlRUT6k3imx2Za2Z3Y0i2a7QVqBshtgOB0grF85RMjVRngc3tvXFvaunOa7wWXlC06Tnxb92UJelj/bLzGVZQCoMMM/9F14P2f7CO+PEJ/sGP/t04AGwJZyAYRJVIk4UYTPAZzwRtn/eMJwqbaEXdIQozksOrfrcIrvbuetPxfPr3hzaPXmtR7VABaYpMWb4jlCpsRBc717lhGiEc2+XojnANNYe/m3uGFdxPXTPusCkVOEoBx5YO4WTtWNKiLUw/zi1C8+tZxPyj6bPdm4Tun+xzY2Kk1/vLrnWsxVFhE7aDC0iwqJebImRhtGBzTCil21vDW+7zXtjv1/spvfcTw1Wa4BCkniQ+vSRRUdL1VIMCkjrfbaa/hYiZRwGOVHOgt8mquA2eHBIDL4GiSVwQMsgi0jf7Cv8gRnsgH7KUNB9UCS8AQb6E+gxgDwUQRsUdVi2UKwHCkg3KFVSNfA2wGkIQsY14PiadpKBmvSDNSAbrUyURsGNyPmnvWIdJmYGLetfZUDPpVU7UXVMT3wCMlPHkNcL0zEd3C5aLL8a551969suiaq6b1F1jBhFQgHMFiisqH4yDnNRU8KN9Nivy25FKhUaaWQCLh74gHYollmPz7eyeHcLXRZ/8+8WB468ph3t0d2XGf5SiLyrhKskbP1hsKWUFwHYSJVQh00lnLJp8N6jjTJk0rvXwW6XxvpSa/27SVVySaQUPzUH0QVsDnNz7fdAsa1G7/AlIeSJsvhYgRILU9SGawL63j7HczLPJFDIRjQftWvA2nzUQoSULvLarwWMmkZ7dFN3WhUKQPtzk5Z7TXIK3vVOcSX5eMAKqvuM34jpPhOXC1vO9FoGHppq1gLIrYS6DMtRxLoBq/tsIHIOOuTUFFEDogWFL33C0mzRRXvf2SvWnNgSG21Fgc+aFBD4lg6VyvsqxtAqzYnWZ6didbC0D8qorm/AVV0PnNwYqRpyiKKoirsWbiABY7FbYEF1EsFqeJdommEqyiIpKl+riIhVAKbWMPlaXwRWgVGJMLtQHFv8TBcu/aTow8/uVkjbNnlV/S7CiVPPS5wSum6jbUyAt4JsTOCXTQFFaU4oMBEnDVVds6/GpmtLfqqx653IrxQcnhk8pdQD+909Rj/koRr7ihNXNfZZHeT1zB5yekUdP5BnXO+24NujFL+5e6UflwROasQD5L4NuSDv1FALeX3eajkrayEvhlpOSOmltpYTUnqpreWElF5qazkhpZfaWk5I6aW2lhNSeqmt5YSUXmprOZvbrtvZ+qzMf8/Yp7H1S7ttZJS8AeGFt5umFW3yUPImYOO/U/CR5re2VPRbYxE1+MrTKlT+VyeS/ZSm30ynvBzLanPykymi8M0BbVdylbZVuVGz8eiFqoU+IgMc2IeM6BDSFei1q9Dc9SEU8XAyKnftoBsJQHYfJ1qPs9cFbR9S2Xb++1zfg9kTf95KfXaXx8kA9G28oiokLC4McyLN7huGQpqBIt5ORk20qqkridDHCorSuJ+RByQtRvhnTru3SSw+2orHsohxPUI/Hs8e4bdOOTVgCpp0iAeUPDhRcnIyrqlBM90IAHyx4ZjpDQLQ1Z6xb5VYozeqzJq4y2e14/i0461rtCzJ/dzrpBDBN+TKiRBfJ+Pc2Ka63UMAEQFPlDIOVD5hFoiim6Dg1O5x3a32auuA+Zut28yoO/o3c9i1xEDy4gTJw8m4fd1GjEEJBSKDbyyyKyh55U3zonKv+uUe25Tm9E+fRyU/HQFDpwknOnV1vqgjm2E0w+mN9GMZJpjemOnENb1xmnGmzrBt2iGlpue3e2nvt6xdgiShXGZ9E01vpKs4Hg6iL3PiGks43zhbZ8j0RtmfgkvuYQHeC1ulRZ4Y05gaH/EzvZFvlyAWlxoOmFKMNHaFb6HR95pLdHojLiOs0xun6fSQE5seEjU53aL9hDviTL8Vb+Pb2zPy0HESlYDI00Dy5WyueRPie9rdHvxcikSgkCaCS1K1LJI0kAapJfqRMI4nhGXK9ciG4op5Tgeb5OPVORCfvLQIWd7EKEVlg29DEcld7HGgb/k0L2H12YCOwl+7+1z1HxRHc8PxGzBdJOJyYWuOfjquqGsOQZH9AJ4N0DW3EEW2NTGqmqQS8TykTMCz3ZO3T1nf+NegjfYhnUKn9/6T1v0C/z5z94+8Xhg+Nz81yfy++QE6fnol9KR6th8P+KzjxAcTn5KoMLDECzeGE0B0ROj/MMtGuGpxK3WXqGOk8VxME53Zd+iQZ7Jobuu1sX6jT1PNSTni+0ymkdd5V5YYVxZwcmW6WXHlzUEtV4wyX5VxhaeSRpHKFz6KpLlYGLdmsO+s9T0Ce4R0p62mEPz7TMaQ13lnjI2IUCcgzciMV51EyKYmxgVkDjoM8MBCLisMD4u8qJmOK0N9Vrr0epWfvWMgtapWRNyAWVWrJZgCkeWciKQ20dr1Bmx2ffPc4A/9vDoETvrwPd7y8HXqoUfyFw0vhumoizCoBlyQGCuLjMXcSnC2UKLBIl29qhjS/BsWfNBPd8OelymTxHUj6kTjmpB1oszqF+zqQKZdN3IHvA7pagBjL1NEyhOiwLFcAfEk8OpIhcUk4bRRgQfbLx3r3bZ1f6rwsTk2OkJxG//eKDIUYOgOLW1JxzE0SmN1DCUlyoeQKP2DWqAeSEPkB2JlMbHgzwU+pSA5FN5gk27PqaJE/AxTlMjrvC/mDyRgdlDAKokAYORibmj2G1d0aTJk46qUoFAhpW9z8LBz1bkJ185VGx3mjdgwD93ld/YEckSU0tfeS/YsqCrlVW1CEuTxMpVcFokfCzO8q6lDCOYPYOYpHvumXBBHuYtBepLez4LrsRisoNGNaB68w4VsHsxM3BzCHFoXSDdTrT2BdDMFv0TvZsrWrbQUC53PbqVsuqmun0yN6Rxd630qv6D8efMp/ED7t2191scvr9ljRNmy/6LrMb3H4TXPaWcfJN0Py0BzLticmbqah67H21zIrsfQAp11Lvm0TqFcINWLkEYq8Ym3hqM09qXz7L2zPL0npShUKVX/ojanL4UyUUILRanPnDVbk2LKBS+8uNh51nnrIhd9zcfFmgOlBS6MTpCc1S5EB2fgGBkAEL3qvcSbROMS8xmaaPqCI0Xq08b/MX1KbwJUTPq0njOXPrV0/p8+JflT5kOfwDXNbobNHd7u6eODA8byoE/pzZ140BR1nLk0RTVnU+vTy313re/cA/Xd2cZWsGdFRiQP+pSeJOABJUtOlH40MaE+pdvQEtenuMSw6lMMKVKfNjH7mIC+nPgpZmtdyv7tTJHKZ+dH79jNl2d24yEkuM4ZElzUhQTOvBWzVdFCXgzFbJDOeVpVD+mcpy1mg3TO0xazQTrnaYvZIJ3ztMVskM552mI2p3sv9lWq+EW0v97OR0Me+9zRK2Z78/vYHv88GR6S9nrmwLn+HlP1GhOiNfNC/viS5727to37zeONExl1bvjuK/SALq1THw91bi68iYZVMYrGv+tZCWngqIWbXinA4IkFG0/oLRJ54ElTNp5k7L7bZ/JfnwP37t6xd8vQe7RWNuEShVTObODLpg6dhQIV+AbZFgZ0dRUolPFSoiURGLREjMKBJ/noPR4hj2KIjrSKiFQr5fJuwM6BiwUHRd90oenPbi0/Nx5S1cdvcp9RtoeF1Vhng1v20EjV3bHH1/5sIx9lwmA5qPDCngdvFxQliyffHfNLwN7I/ZRsGkvKsqndQUIkoDGmdtuLkJTJooohEnWMTCGWRlPMphVxuZssJpZyvQJxvbtSpX+VqrvFC4YKK/k3zq+MgxiuBqcN42XEU5XXPhVsQakliYGKKNCsSwtvqQrgItiw0buEe/igrEZ3yToC9KKQyEWgg5Se+cJb8Ov+btFLLVHpvkOKqqvZG3N6x1GeEnx0+efBmg9rzGXNZY211ryZ2WNOb+VqvknVGM7jAAN1xwGa82Ymi7MfPqRHr9ZMQnr0as0kpEev1kxCevRqPahb1s1/mdOkUmC23bh1oyve+93wfvj07r48WFA3NnZViEgbnp0wxCf35WdpW8G6d9TOd+SeYAj2HzWmDw1vGFhbu5uoEISppAp/sSCOvIdhe4X0Lsacj8VsyEf7gKHyjwVrz5qDjRwR5uUygrZSImRnc8buIVcFRV1CfrWNKUF3gQTQwTNWosAsGfTFJzea0Kbj2u6B+47/4vv20smP1L1CH+IOzL1CLYH/QTAo8gRAspatpuJ28xKpqSgbiUGr0wxbt279aUwfQAGVMaD1VIJcosa3IOXAR4HyJjTarmHvug/Fs6uOGrugS7tDtP6q5E0g/VW1FFNw5zInd06aA3cwbfTTmMKj+r5xMg3e0TiSwiatCoEPft0QXCtV3DE4Y+WflZTlT1PbnlgSd4TkdwsopmBOHidzdpoDcwB/9JlTphDmtBXGgZ/EeYI9jgb7qlQRmUT0Y+wkUKokw0D7Rg/8bwWfgK8o24E3v42c6xKy8EDbL+pxg8OoR9y7692fecSdQjUF8zZwMm9lyTDPgB6bFoVwsFMBBzWxMkWSAvN0MfZh7FIoFYB12J/kykScCP7qDkhxkhHEBTgf1ya0sL2WHLh/d8+1n5atvUZrlBYLq5gmL5uCc+mcnJtV4pwDXwKbLUZV0VQjUtUyRQy3Ivw9VFa3tjg6eLrtuWUpXRy2UBUhq89UQOGdI5VEhA8BworjDLfKEXerSD+1BZufam+RHHFo34ewg5a5Dxu3SaZt4hEzeAThaulwmTSR6qYCTNmK3poIQUMijV7GB+8tGyNVxknj1UkCFXFDTeVAotArUNFNqiCDFHbnlT5ng+tZmRuOVLpNT+w/KqU6nhgpqP2UwdhPQ5Fmbvl42RZkI7KMCKnlxloQBw15/bXY4Gcq8Wc0yKNfsLZG27ZrU71Xb67/7lM1+460MdjkXSFjsLWUwoLha9KQHW5lyvjPGvni713TFI5FDYZnoUhTgJw3VI8cQBGBm1E18DW767kwAuVwqVotYxln4fFsYVfPN4Ehi4/U7blL2Op70ZcwDSu6juABq1qcWFm7FavO1SYry5MhF/gQcHZuZd76aSklPT7tRdQd/VkWt210q2qpDQy0HwX/b63v9lC/oQu33dnU2P/68/+r/vz08UTF1p9/tBtXf/4BTN3JQ3/+XVXrO6QfvxO6+OXuiZOaf6AO6inaQXS+daQliiS7cbUzH8bUkaboz/9+1h/Tqynre6f4NljoesMqrcT788dwojKgeLUhZ+xg3Jkg/vrz1zzmOOKHfUfhdt/9x6r0uGdtNv35IzhZF1gyrCv2/vxlW/b0n+54XTirRdXku9Htbpdwf35cy7A2WMe0TLH15xeOTfv9UrW9ATmB9jJRTrMyZtCfP4YTnAFuxdifv/e5czdvRVUQr3LY3OaC4u1cc+h0gSEUwYkQtqZJv82DzW/zFTZ1/dnpsnDt7XrrLi577UltMYCf71Mp5ZhFZ/psliw4ty7YIpEVfJ9sk4EhrlYmxMRiPpxGiqdqjGnzQB/ZyPq0zIYIekRD8c3LQ/5sgeErEYGkCx3fJiJkY4uinrmqUfBY2FUSC3ixb/jt9jcWzRavu7n59LNbXy8WfawXzYVasS2m3cgul/1nv8r7W9ZjfZGblafkIX8A9OqLYNKZhiKnWhjlQlkTyzdKGqOWwv3LXvvL97pdq3VobtSLNwdW/kEdvVLOB/8i5PAUcZ331Ym9/++c77+rRUk7SzrJNMJRAo8sU0bJIjna3vhnbHtbN+Jx0Kw/qnY4f6jBSaqsam/AlFUdxRTM2MjJjFUlwwy6+4MYs2PhFqxQxmPmSxIJcqfO7p2wkBWLLOKaCTw6RcYq1VHNBC07aYap4/G/wL3Vf0p5tmiz565/diXv9jmdX/Wj2jXwAxHxSXLIaMwCkimYtYiTWbPNYuWAWxnlrdYsSHQrEtSDNRwrqPS5b1mz7nn7pXfIq9enpbRdUULlorLDU0QocnAK9DyDHX6i9fktjPNSSU3O4W19P/d5dVyQJHSBTfveD9Lvu5Vs2IsBsE8LwFUIAEC1GOWJak0Ze/+JxS3uBmR+HO+zaaLlZWX9ZbKSPQeMAZDJBUDPuS20jmbL/1g9Dn3Sd7HV4/R056rHcXI3dT1OWIPsjUmf833nDhuwZNf94FgzqMfp7s61uxnkbgZFBYsWLSqGepxfD/zZaVLCycA9J4Z+n3b82UazqMfx5uROG3PgTrHU41TJPicZNbwsuv2F9eDa/RL9zKIepxknc5zMgTlISdbjPHfuG1/5Zt+AhZ+GeskapL4zq3ocO07m2ZQM88yzHudJ1l2HPtUvhGQ6Zs6IfdbmegnX41hwcu6rWYQpJqvHWdezTK8+/uqADauczow/MGeTWdTj4D4Eaz0OpghJP9Xz/0M9zvOHGzKn3jwvnO91cofXNtH5Eq7HSXfnqscZz3RpTVKP02PX7Ipt74kCc1LL5Tb1jH3Pez0OPTbnocZkoTtXjckMd1PV4/x93VXco+we38XvhonWjrIcwXs9Dl1H8IDVeE6sRhSvtSzpepxWbGps2EGZqyw0R7TrQJj88V/9aHPyuiaAA5L+aokqlnmM1Ijti4Y+Mo0KHBHT7eYkNSeOkgokoJ1eDPgFeIPNC1fy/TNeBS6xGxo85ttqO9bnY+7k6BMZ8lchAlNhYfrnrSBSST/cZKBU6u4Gqaf5Ao701RKBf6lSGfEQQc99bpxfKUIqxxgmjQrE9PoI7e1wthKsbM3Gysw5MxNeBH32XzisliZjWjPatoYfKBqIZ1oiVrea+IJAg2k7YgRgggaYenx8VaxSHgU61IFSqGj8c7gbEC+J0Rike+lHw8qJlZFDpVG6L8EenZnGIq4bqhKcUeQ7ONtXGlrMVE6E3GoI6UgDIAL+K6QjDfiX3pEmdOLtzhH5z71/PbU9xfJt2GV6R5oJvVaMva7qH5Cel7noUfqMzlq69qTdv+5YQ/9hSMcaNk5bgaPRJBuh3Gow6U//EY3KBO/vv/DESs12r6Jwi39nzh1FvgG+LoGq+mwUeduwRGbxWYGRdwM12DsoYgrMXsHf8ZAj2b1Dt9GQxjlsvKrmV7DaMEMQn6CGG+xazkMsB/os9F00YnKjnhHTenKyrLyIuBOk/StJMAXTHnMy7VbxMk0bE1mIRYRCBV8Zq1v3OG+0a5TNyDn5kNOAZQqNVI1XG2E/QVGYUF61TZ19wErqiW7tO6fKpfDXyXRelQ9JiJcMlutO5yO0JD/4VXfm6Wn3Qtsf/UvzxsXUS5xMPdGQ0f6Is6c8KexSovkEFDx6DwhOQbcAmo45uQC/yruIVxMReilPCBv+XQ+3N6RJb8Nm0rs+uBNWXn7Wf/meA6XH7nScRK0RjIiVRccLwKhNqlkH9optzK9DWHQ0cMEkcjk5kVIGZomBfsZuUIDpM9jYHgFyfN9QpDJR5D4YNdkdhVnm+yhyqMhTeyvhA0mxtakBDwx90d3fO19werk5aNWEE75zx1yh5mstWF6x0MCGPoe6qGssC0XuAqzShbA1tgtFrjDn9HJWyxAcVOJSAU/fWEdW/NzkqO+Sh11S9rx3es5IpUUbBkxR1xP25qc53xyTEjNIoxlbJ2MFmqhw9dXZuON4809lIsNWpZcfIp/fZQ5VLsG3iwv+3ZzwbyoZ+BmVMUWdXUysCFDlib0JlCP0IaT/UlMUlSNfSVWQ5w0zMIgILAjSwLRlPY5zIvfVrMZ1/WZpXpU99nczqrmsRPT7ERCZPsMbljYivgAC+0ilHESzoGYRjEAGC0Kgwe9qWKCorPvcJcGnWuCqwB+BDmfepnM8H3MwDoVsKKpTUKQTOKuZATVGV1CkbvOih4mqPR3cfCfu85sgr1P1ocTqbGGNS3kLEw1obMrG1Rp4QgJvMQNKGQguQpkmON3Brefqsj4Zd3yCz33f701dH/6wslviamHGNKn9/qzV0WGi8UtGPWv9+MGMohrTGSjiBXh9HKrTVqOIh1mclEYQShyiFRKITmPjnW2g3soDgYkM56U7lH1TRmeLO0287b3ocLfu78p/XcQdf1iSq+xfRSAJ+UfTZzu3Cd2/2OZGxcmvd/PA0CacDMUWL0tEVzQkPaBIZh1Lavvlt7mBU57Nu97yzdfahiHpwUTSo1AktzTs/tuhcOfA5feRXdubHijyYGwMyeqcSFZozojljGweVplQzJil5dAl9AN7hQTDBIRM9RLh7O7CvwV+ReoPeIhXRgTEjbTA7f6rFvhk6d/WNav/UzSlTYNJX5fMyCsWCxzQgssCO7f4nwXmtsBVJzzPb9NohXfuzNPOj747XTJnC+zXgkvNdDSL2ggEKVYL/LTG4exdP5+K9v8xMnBu/Z6xJrTA9GOOPDC0JSdDscVbjBZ4xxw3Ifr9RPCmZZGtL/dbecOEFtglq1zvM78owrb8I7q47WL3vjwgWY8TyRotisUC0897mZsFxvUHqwV21lWct2ezwNenOqXedA72Tb+8+3NOA99a1AxneIJcTgz+Ze6d4klWETH9PEwhT9KJBvTMLX4nCTkPHJ8WO1yilknjk4BG11b4GFaNfvD2puT219OEE7OHZtdK2mnP9sjMs+MFNEMhroEiT8DpUSsRrGDnGIpcNK4JRI1wLQAaqUQdGSuIVivhktcvVfax/Ky6ftlJye9cj9rnFOUItonVXh0UecTe/2UUitxk9oEwMoWtV+gUi2k9FcZIeMJwQNjNKq/ipodNe231Z1LG5qe8FzYdTPlsJ7rmE7z19Zs/LWsencUDeBc5wTvuZty8PQdCxDCXt5//AEEksUCBxPULHwCFjK67qU4uucJZlhSNzLuKu02K1igYOik2IiBaRh2rcveREQjoGtJgsOClHKC7jUqtHKKNF8BMawxB+CD1rtuPZJ1b5Tuu87FTmaWOuFKlTPsTTCnTUUwB1EVOoI7rjrl3YLMF0y/vq1pxn0PYuJivLgmp7StRFatuBjxkrKgFC9pOviPi1ZJIooWAbja9Buh8slORYSp/wqWjSc8m1g/M6tLX12vi0Ey2J2Oq/AKaoUiOR5G/XcmKZabKv44i91xN0fenVMt67j7fD/itTNvWZ0KDcD77/vCdaJqEIh8BQm+ECGS6TRaOkFEqi4QIA0UdT4gIFKJNZ4dVrOUe6pOdPXbDjaMbp9M248C3IXXt+GXe19s7EoPzUAe1nAh57mqcYqpMYKBbJFAEtiYlzHSt7eCX03KUy+E0X2poWwaTdcb74xdN8fb3ON/+T1ettvFi0zbPe4aKLVp8ES1YddpvRVhgX/pGkgLSTYNNzzjqxheDSQ4FvcYSlUZ1zgj7ErR0/Ly2QTsuPLxlH73Rm/lITNceXDUUtkEo8rgZBttpqGr5gCIXmhmlWqqAHy902exw3ZfgGrbFd/zYs/ePv/CbTK0ixdcHi3WnEAvTMn+83207+USaeJ2L5SJ0jaNNUbVMLIo8BGCFQx0jTDvfaAat+GYtqMHB4l5fVas86iBLbOG7+EPbtWVVn6jrq4LOljAP+heQCoMpx214eNebp3z3HZt6vcWgVe48wHSBE6b8ZsYpY2tCqKQxcWznxOjpdkOXCf96CNM0uIxshlqiqiIADamHOv4/ioDLZlRKurb6rs/8qxvvSLZa+po4Al7RjCsCnm6czjI8ArZr9GzGzJo+/mltB/6uenDvGI8RMN2T4CGIW96MK4hbwNRVpoqAlxy5EP1hRFPxzvd7/3qbK9z2X4iAp3OCN85IDWZ0BEw3XWYWAeOixRrYLWhWEhGwd82+z3L+qR22vO2WEc3bXQ82iwh4OidQ43S2oNP/I1vwuHLO/Aqdcv13HV4YH3On41IT2wI/Tlvgbipb0H3LIheZ707/7QdcX6xebjWUR1tAj6l4UGc+nOqsQ/HZgvEbXiTXm+wTcmDDRKWlSFPuv2AL3DnBa2xqW0D3z83MFvhwqrgOJWILVlaoXL5sbjl0fvLtJxNUgr5mYQvcOYFqrLMFndlsgc330PwHY5uLZyx16d9T/a06NRYMBcoTbJwbfvqgSXcgGhLiPKFu+Dc4KCUA/ZMVwyVyWZQsPgmK8ank8m3qvqwelLUosaaPk+1XlqdhRqY6kqHYiVGkd1MMu7vQCpStKNKuqVFK3hr8ON4IXspSUtwqsnN43oOqAet+TaqTuJd2ysIC+lrE1cJ2pW2nXey2MjnHb8njh2tG7i01s6jaqTuK9GzKuuE6HofGKO1UA3TTFsiiCXGQaQSAW1CMvo1/98we7eW7+WTQHId7H27RGmYDJvvJJTGQDLgejfd1dpIERAVV12VEiLipcQrJlg5IILEs4BWGyyoeUg7r5rfm7pZPcXsqCamqmvwmCyw0simQQTmRoYtK6UKQcRHi58ASJHJBVAFV24yJGHYJUoEs2wvL6h/KaBXqIR5XZvSwoG2TqTNI9X+PmQTUJ5oCJzdOnBo21WrqLmyauuPoZqe2C+PE2fvntt7v3HUfzcsBieFQJeSYWBkWqBuGS9XgRLCAPF0hUEhjiNbDzqFh3QXYn6Uu8PNin7zc1x/P+sN7dyvp5jJVWo2HPwnE3yIphqKWiiLTAGozMNTuMlA7hCKjjNPRlVDyTfGjONBXO1Zq/pbMgK++GxeNWjPh54SGlFcrJWQWDQkLdR7pOq2o6nk+ikwBqLgLgYqmo7IcR8Uo9WyDKQmpWiMFqyxZOBqKi2XkounjjlcJOqA8P3LAt9HNqQVBRJcg5nlw8jrvy+k6CcFnKARfcAjI5eT9Xy3KXTCrYtO+69sF5r6fNGvlmNDxHM/HU1FuPIrcAKjuhrpEj1BkX9P/FeVyF+XW8RzR7F16G98Mt3PpVySfX/JWlEtff0VVIljIcK0p2R4Leo77XFMzLco1sv7RqKLcmJs/J+66s1m8IWR7y7lNO1fksyi3qDoP49hRTo5hq7MYq26VR4I32t497jN+8qIWGZJ+B01YdXsmsVSag882nzX1HC0fHLEYwIPsb+FEck3TYqm67eSR/ecn61XeW8IDFky9mmphVlW3P0gFAQ8CrURA3EgTK2QzsYKYBjunzJyKzju8Qbzoyx7qRLOy3aRySRLVtBqJcnWhIFGmlgrU4E5kcAAf3UqLkCEPwhw2X6hOfvP72B7/PBkekvZ65sC5/h5TiyqXm1DEQiuXKQy5vIIi/7hoIUfNHvJasSpks68GnTDuh5X6fqSIH8jpS4YHyEu7ckH+VSflIjbIPbK6He2Xu85vbVblU4fGfFxIfVN/tTJBRYXcWgs5qtRvToZfInpEg0va1m8wLtQTCmLAfXGXRC3RaGKVKpVUTfJDUzrQRwsYPaGGkbSeFj2Kw0hao0H3PTFSGQSebMJIFiSJznLLQJ+BFM4AzxkqLI3zjow9VblLYOr5pN+9e+QNhUDIFBYajxEtjwl2+fw3Ep7H7qW/qXQiJGxeQ//Amn/f627ShOdBZ66E53JnnhOeu8QTO7ZftCls8X77UMW6zA68JTy9kbmKCvHi4C0Hwz2XjEMr85Dw3O/MlfDEoDFRwlNxXyYd+0QRlDGvYel9lcc0MpuEJw4Ia7pqm7MJE577Hnc8FSa/6Tdhuse72+6xHcws4bmOExm6qJg44RmYM7xRzzGfgtevi1vzZcilF2aU8FzAidN0Z61h9TX/hKfb8qzmNypc9d9Qtt7LSg17tDNhwvOtM1fC84FxOtqAhGfjuV5z3z5JDduR32DfmT1+1XlIeNJ1Gg8Jz9fOXAnPB0aqZ0MSnlW3VL+lHGXju8VvadjJyi8mlXjCE4eANeH5QLec/P6rCc+LaOstXe5HifZMyWrq2PhBvukTnoNQxNeFLFRnukRvUKSRy/8SntwJz5+Hy22u909D70mBR9fV7WK1hreEJ3398VBALnJhHZCajSLtXcw44Yl7ESZIeM7IHXV2xf2wgG2iLQ9brtzZ1ZwSnhjHWnByrFHxckz7/Jbdk1RS/Zd30gvB3YKlaoVU7gY+o3HzDxgYgTcDNqRRsIVHC482xZjBrevQRfZDNi10crznEMXRaRVMmMHlO1OGiYYDp2hUdSmWDG6LCVNsP2zegKZ9bmsX9eFHIW20ijmDayEiNB48qq0iAuuH9Bn8zT6dSA/5zTaDK3XmSicO0LlpAWYPeZ85a7YmxZQLXnhxsfOs89aj+YGcvmR4gDzWhQvyQTopD/xPZnDpGUK9DC49LNXL4NKdab0MLn0p6WVw6Sw3PIOL1swL+eNLnvfu2jbuN483TuQhgxvExq5a92f6VOtwTrSi9YODuccTfSi/VePQLub/4INNqhJTj2D+L+wmFYmPF/pj5DAl+ttCPwt1vmEfhIJOV1+FA8HgAfxT/9YW6Zxa+iqdiyJBQDFOQYE9IhkczMbgHxO3ZlV3s0B39rfLyFaFrKYmRQN1/1DZWrFQtup9FcJMPSoLC/U+AWOcHhnKrmGfLT7cayP2XnVleK+B1XaNZXstZq5Xj1aYfqU3UzRQv7JyLgNFhjYnE3k6zol506RNi1GTrp2Ws6dTZoYwc+jT93XcrufraVKZR0AjudOroPTM6r6KLQ4X9TRp9eNtr/nWvOSbfi9328tnFz31NOm1Xyfd/GPZ7tCcvFq13JbYVNHTpANH/lzu/2Sm75a8lSfbXt7wJ0YqS5L8f+Qvko18EzbjarWckBoPhmCkctobtl2onvOsvHh6324blogSMjBSeZKU82DqitDNW4W5vUa4N9aE7cdIliQJ+WuiWilWhu4fOmj/7O2PbmCkCtpX/tn16M/pW70PPqye/SUoai1GqkiSDvgNOTrSe7vPAaf1qZeC45wxkhVJqjN+ca09P2UhuxJc466XCZJhJGuS9EvkAr/oZ6XEq4f9evjI/NpHMVIlkvTWO7rrxIw63imnXgx937f5ToxkQ5IqHE3c2ippQNDy2T6bfowI2oaRKpOkj2e2X10T89N3SoZjynnHB50xUhWStD5vfNmTDRJ8fksddmzlyRsTMVJVkvRj+6OcZ7eG+8+R7wkfIKn8ESNVI0kpKWr/Fm9cQ5b2KJUnSA6NxUjVSVJn70svWzd5Hjjx2fM/J78vvxkj1SBJXlfFbXfVdhIvjrx7tFLq7XIYqSZJel714WzParMD1/59KeTyJ9ufGKkWSRLcXtzZL9kNzcl71PnFicChGMmWJI3a1KSicss175Vf4n7p/EuzFxjJjiRlr23yMXZYHd/FJzv/siJ+QVmMZE+SnH6fOPmWz210z+4/VqbO/QtIVG2S9PV6nzeL/hzst+9cvWMLhjUQYyQHkjR/rTAj4KG7357XDzWxXQ4cwkh1SJL772cmeAVjrNzQNuGf9a5AbOpqBfvis6vny3dG15X7MXrBxswRGKkeSYqI0Ig/trdBp+1ZdSTg2lggNvW1IroEkX527RGS5nqqQbPUz2swkoAkLa03O3NL8itxTulm2/bcX5uLkRxJUpWlbqkHm88Tb8sSDJi04+1wjOREkjZIA94F1/lTnD4tbOKHL+VSGD4H0ENQfbq0TOmWd8oP8hmf8CFo9RnPbzz4HCFsiq1m9J7cjKMnfJdsuD/yVJ1R1NY85X1HqOTKKEgnD7Y948bkNwRkfyAsUAfHA+MkcjmmusiuBAa286CrNeijMef+kARD/WzMv67SMh/vRQA5FHkbRb56GNfUo6BfEPEg8M60k57/7fzRL/Bg1S1T5wkv/M5juyC+Rzc6o4gNACgKmpOYiSIWLY2a2tG6mxQTDXwidZQ0UhmnUmpkeHIdez6ZHB/uopUTgQSL5yRgkGgk/PBsg/ZWL/r/DDrwSxOHLE23stQiA93vMIsMCki8ZyeccYnhgOuNh1nMmihV1FkTzcmFFlXALvw4a5xkqFSAuS1gm3ewRCMlFAH8VFRjq5PHZtiEbflralhStRpyWmKOvC1kBryWwjv3PpHC7gM9eVhdBISdUSBgJHCOPaXqeBn2Se1muJQOJBSs75PTa/p/kfvtbjvn7OH6KaWpYGnvyQRLRzEFWLios4KFiTppf0JZN+/qlx46f0sVdM8K+Wuv0ZYBlLeq7Eu2XBOIpYqY+FimHSrPgvGeUrqvai2RBNQyRWJgYDcQREsi45VqTNkoFTH4YVk5/gNu5A+RdI0gUqIQDJYKNAkqlVyGcWiwEiNi3ydumaAAXwXnbRVg2pccn3eMX3QTiGIlihgpzt9+oQMEKu1uG15ZpIyJkev1ucI+A3pdxWFCYKBtpPv1nLAxZIL+AUMZjqBIJFgdNUWwfcVnKCJqaYreeoMangk+13M4utB659Kuv+7y5NFY0jVQUY2lJYpIAEKzoNp/Oor0Ms5YOlHkkRytjTeaIwDDPgqFbGD5upPCGnf1XeLYomfZBK9oar6eRSy013lXFBgqIZyoYHJTwnuU+pOKjRmB1SowWgBqwJrhq5jKLZlGXy84u7u5C8YIPNzcXaAsS0OTj4T4iNBdpZd7tW9iQW19WzFUdyNIxVwBzRSsa8/JuhYlw7rC3RmuQpm6RFsJCdHZFAymlkUD9U5YASh7Rv3iuvTIS+fQfc6zq7RZXw8tSguTojKllIjQMvBtwtoioGWMKmNs3B0YKwyR4VLCLhoBTL9sL7tDXQb5j7tt4xX15W0DaphG3pgZpmkJpgAnhBMcUUvjKhmbEFaqwIIbg869zj2G3n66xD+jxeetNeRbqF3QKuhqcJghSgHJFAi150QIW9Ok3xbG5redWCwRf29v6z8+u175Zw2SD1C9UbwHYYSP2PDEAUptAUp6wliEGI39FfO7kvT7ZGLKlpRX4HuRrttogxwnetYT/txML1pLMRTjcBSp0xHD+Ca0BOsfFPnHywS9Qtcqtn18N3dF6MG7XQbF3/rrflFa7NI8pb+npWVtOZQTkrNuWkIN0XzLonpKvVGkdkfWQtrdKFKlI7Q/KJshtsMB0sqFc5RMTdTswY1tn8Xt/Bu9OBi0YaO74NyMrBXUZemj/TJzWRaQCgNs7Jkykzu88A2ZWmbfj4niFs48AFaOEzBMokrEiSJsBviMJ8L2zxuGU6Wt/oLOFcV5yaFV4w5/dZZfeeyTGnlUun3y8BHVAhWYpsSY4TtCpcZCcL17lROiEc69XYrmANNYO/Gq46QthyRBU66FPL6XWXYvD6x958XF2iclxFqYf5zahed+tNVT67gvzrH2m/V68fZJl3pVK7l+tBVFhE7aDK0swqJebImRhjGczTCil21vDW+7zXtjv1/spvfcL6buXYPqkniQ+vSRRUdL1VIMCkg/frZC/xYiZRwGOVHjgt8mquA2eHBITMMGiSVwassgi0jf7Cv8gZmb7bBPGQq6D4rs9cRAfwI9G5CHIhs8izpBWyjWAwWkG5QqqRp4G+CIBCHjGnCmTTveQE36wRqQjVYmSqPgRsTxj+3zypTZ4LuiZuj+k3Ob/ELVMT3xschMHUNeL0zHdGl8xV1pEYRmbLRt9zK1dLei6hgxiuwGMFugsEr7yTjMRU0JN9Jjvy67FalUaKSRCbh44FPboVhus1/j2+vb9bBludbTAq41HUg776O7LzP8pRB5VwlXSdj6w2BLKS8CsJEqoSubSjhl0+C9RxtlyKR3r4PdLo2l9nuu1E2qkksipfhROoguYHOYm2u/BypwNXonMgkhT5TFxwqUWJiiNlwT0Pf2OZ6TeVCBQjaiI+l4T9aOpBYiRF7ktV8LGDWN9jyn7ggrFICAFa3tgzp89969vdnoYUkjqfsRZfEbMd1n4nJhy5ley8BDp80UgNxKqMuwHEWGe7K6zwYi56BDTk0RNSBaUPiuXCs3I96mZ+iahsiKCjvnUWegWJMCAt/SoVJ5X8UYWnJOtAZ7FquDpX1QRsl9A66Se+DkxkjVkJMVRVXctXADCRiL3QILqpMIVkO5TDdMRVkkReVrFRGxCsAoGyZf64vAKjAqEWYXimOLH/TCpZ8UffiB3tLlb20Kf75MtGf4r/PfV+nZn7YxAd4KsjGBXzYFFHJOKAbrDFU3sy/RpmtLfkq07e9J5tSPnBgy/+m5Be5OgZ94KNH29uQq0W6ngzzC7CGnV9TxA3nX4Ngprv3kPjM9Ng1y+PuvHTxAntuKC/I1rbSQd+etlrOyFvJiqOWElF5qazkhpZfaWk5I6aWulpNZeqmt5YSUXmprOSGll9paTkjppbaW812Np2Pv1N3gu3je38HVl2puMEregPBCpY9etMlDyVsPNv47BR9pfmtLRb81FlGDrzytQuV/dSLZT+kEznTKy7GsNic/mSIK3xzQtipXafuXGzUwj16oWugjMsCBfciItiH7wP7AVWju+hCKLDZum99BNyeAbElO9CNnrws661f384Nstfdi98zj1WPQJzyOC6Bv4xVVIWFx4Z6WpNl9w1BIM1Akh7nhz4VVTV1JhD5W8HOOXZd5hLecFDjLTfLz8Md7oTyWRYzrEfrxePYIv3XKqQFT0KRDPKC0mBOlGS2N63TQTDcXAF9sOGZ60wF0tWfsWyVWiR+tt1+qEPxbqLRXHY9jwpLcz71OChF8Q66cCMk1cj+3qW73EEBEwBOljAOVT5gFougmeCAc1Dpxw26Rb+ql3fWPTDhf2Rx2LTGQVnOCtNjIfd1GjOkJBSKDbyyyK6i/8lqVcY656ptzc/dSm6D1j0t+ZAKGzhxOdCbr9nR7shlGMxzpSD+WYYKRjhU9uUY6fjDO1Bm2TTv0bMofQ/2ai9dO2HC4e7nzLU000pGu4ng4nW7pyTWr8Idxts6QkY4TBCezAkIFvlsnOh5ultvvhAlGOvLtEsTiUsMB0zMjjV3hW2j0veYSHemIywjrSMcPOj3Ui00PiZqcbtF+wh1xpt+Kt/Ht7evS89BxEpWAyNNA8uVsrnkT4nva3R78XIpEoJAmgktStSySNJAGqSX6kTCOJ4RlyvXIhuKKeU4u7fLx6hyIT15ahFRoZ5SissG3oYjkLvY40Lfc3i5v/eR7nUPXt1x7SFqlInVIXFn8BkwXibhc2Jqjn44r6ppDUKQJgGcDdM0tRJG67YyqJqlEPA8pE1B0eimSLSXf8oMWVs+4dDLXWUFriYF/n7n7R14vDJ+aq8YM3Fzhrd9vNb1kDS+1zuMBn+qc+GDiUxIVBpZ44cZwAoiOCP0fZtkIVy1upe4SdYw0notp3qe/rB54Yb1w0987hOmVNlC3KMoR32cyjbzOu7LEuPKzLRdXPrY1J668OajlilHmqzKu8FTSKFL5Qhnzalyv/VGVt/mu9ezt2cb971ZUxoTg32cyhrzOO2NsRIQ6AWlGZrzqJELs2hkXkDnoMMADC7msMDymSNOW25/vFTrhQIIq+FsINQIrLyJuwKyq1RJMgUgFTkS+ttXa9d5sdn3z3OAP/bw6BE768D3e8vD191QeE79oeDFMR12EQTXggsRYWWQs5laCs4USDRbp6lXFkObfsOCDfrob9rxMmSSuG1En+mdbsk6UWf2CXT3Rtqg74HVIVwMYe5kiUp4QBY7lCogngQ/FCZBJejqWEs6raNnUwmmEkip8bI6NjlDcxr83ivwBMHSHlrak4xgapbE6hpIS5UNIlP5BLVAPpCHyA7GymFjw5wKfUpAcCu+6SbfnVFEifoYpSuR13hfzBxIwOyhglUQAMHIx9zH7jSu6NBmycVVKUKiQ0rc5eNi5WtuWa+cqU4d5XzbMQ3f5nT2BHBGl9LX3kj0Lqkp5VZuQBHm8TCWXReLHwgxvdeoQgvkDmHmKx74pF8RR7mKQnqT3s+B6LAYraHQjOgrX70B2FGYmbg5hDm0HSItTrT2BtDgFv0RvccrWwrQUC53PFqZsuqmun0yN6RxdP34qv6D80Vg5HEj0rhS8sd35mtdqeeX+i1bI9MaHKz55h3X65U7oby22W21qfbbIDebmYxFaB7IVMrRAp3qHfFr7UC6Q6kVII5X4GFzDUVq0qcLC5jtO+myoHDSz2p2q1GHLpVAmSmihKFktQW+Wz+2ObmiQZ7ksY+9jHlCqwInSz/aM9pCc1S5EW2fgGBkAEL3qvcQ7R+MS8xmaaPqCI0Xq037/MX1KbwJUTPp0Yjsufaps9z99SvLni8SnX1ZkG3RFxQkfr7Qpv54HfUpv7sSDppjQjktTJLUztT7dIDyozlx2MmTCgUHJgVfXn+dBn9KTBDygpORESdrOhPqUbkNLXJ/iEsOqTzGkSH3a3+xjAvpy4qeYrXUp+7czRSqfnR+9YzdfnlnkIxlYSODTjisk6KiDfABvxWxVtJAXQzEbpHOeVtVDOudpi9kgnfO0xWyQznnaYjZI5zxtMRukc562mM3p3ot9lSp+Ee2vt/PRkMc+d/SK2Wysjz0//cBauLzuncbND/ZroNeY8MKlKjP2jVP6HagytfWYWRM9GHVu4ENQwaR36uOhzu0X3kTDqhhF49/1rIQ0cNTCTa8UYPDEgo0n9BaJPPBkIBtPMnbf7TP5r8+Be3fv2Ltl6D3q6cCy4RKFVM7s6cumDp2FAhX4BtkWBnR2FSiU8VKiJRGYvkTMx4En+eg9HiGPYoiOtIqIVCvl8m7AzoGLBQdF33Sh6c9HZa2uft3j7be3R/UzE9KOxbPpT8seGqm6O/b42p9t5KNMGCwHFV7Y8+DtgqJk8eS7Y34J2Bu5n5JNY0lZNrWrEiKb22Bqt70ISZksqhgiUcfIFGJpNMVsWhGXu8liYinXKxDXuytV+lepuru7nUqYndsmvzIOYrganDaMlxFPVV77VLAFpZYkBiqiQLMuLbylKoCLYMNG7xLu4YOyGt0l6wjQi0IiF4EOUnrmC+/Lr/u7RS+1RKX7Dimqg8zemNM7jvKU4KPLPw/W/EYbLmt+qY3WmkvMHnN6K1fzTape4DwOcEJ3HGAwb2ayOJvkQ3r0as0kpEev1kxCevRqzSSkR6/Wg4p7nu5q/02O5pwJ7nVnYfpHw5vk07v78mBBI9nYVSEibXh2whCf3JefpW0F695RO9+Re4Ih2H/UmD40vGFgbe1uokIQppIq/MWCOPIehu0V0rsYcz4WsyEf7QOGyj8WrHXvDDZyRAhynhG0lRIhgs6M3UOuCoq6hPxqG1OC7gIJoINnrESBWTJ42rRq59ljX+z2S98T37LPbwH1qHuFPsQdmHuFWgL/02FQpBuAZC1bTUVA5xKpqSgbiUGr0wzr16//aUwfQAGVMaD1VIJcosa3IOXAR4HyxnX0h74ZPgHBKX3ftLvxl2sdWn9V8iaQ/qpaiim405mTO63MgTuYNvppTOFRfd84mQbvaBxJYZNWhUCZU+PJPU/5gwMB4xbVu1/Zf78blTnEHSH53QKKKZjTlJM5AnNgDuCPPnPKFMKctsI48JM4T7DH0WBflSoik4h+jJ0ESpVkGGjf6IH/reAT8BXV8K/mbRKPdg1Ot2r5aPLw4dQTv9bd9e7PPOJOoZqCebU4mWddMswzoMemRSEc7FTAQU2sTJGkwDxdjH0YuxRKBWAd9ie5MhEngr+6A1KcZARxAR7z/3zjsTzYM3TjkB0P/F4EUNvXlY2IhVVMk5dNwbnSnJz73KmkOQe+BDZbjKqiqUakqmWKGG5FGLR9Zs62iwsD0tYf39FleoaEqghZfaYCCu8cqSQifAgQVhxnuFWOuFtF+qlRbH6qvUVyxKF9H8IOWuY+bNwmuRl1E4+YwyMIV0uHy6SJVDcVYMpW9NZECBoSafQyPnhv2RipMk4ar04SqIgbaioHEoVegYpuUgUZpLA7r/Q5G1zPytxwpNJtemL/USnV8cScQe2nDMZ+GoosBNinQzciy4iQFKZLq42CoSGvvxYb/Ewl/owGefR7ldYvv3eL8Zs1LNYurbrjM9psbPKukNnYWkphwXDKhBU5q+56oZNVYserqcOrFzUYnoUi8wFy3lA9cgBFpnU2qga+Znc9F0agHC5Vq2Us4yzaOoyfcbhVpnjN6JGSIZP3Di36EqZhRdcRPGCVwonV8OK1ltpkZXky5AIfAs7OrcxbPy2lpMenvYi6oz/L4raNblUttYGB9qPg/6313R7qN3ThtpRNjf2vP/+/6s9PH09UbP35H3fm6s+fz9SdPPTnn9/HOerCuN4Ba+oKk1eOiLjL40F0vnWkJYo87MzVzvwGU0eaoj9/ZuWVC7Nnng3bvK1zxDGr5KAS789/gROVfDOKHYw7E8Rff/52zX9ZP2zLLNH25ekpcrcogdn059/PybptJcO6Yu/P30Nx7Muv15P9ZoypN2lI2ICXJdyfH9cyrA3WMS1TbP35Ry5bkXa66W+hSxqMFOSt70k9elAy/fkvcIKT37kY+/OXSxuyHI07LRy/YI+ncK8v9SRvyfXn38+J0DZd+BnN5rf5Cpu6/ux0Wbj2dr11F5e9pva5t8LP96mUcsyiM302SxacWxdskcgKvk+2ycAQVysTYmIxH04jxVM1xrR5oI9sZH1aZkMEPaKh+OblIUJvDF+JCCRd6Pg2ESG23kU9c1Wj4LGwqyQW0FcXH71+9lL+q5Dxon7L5jzsf6ToY73og8mvlpkZ4fYqeH7to9efrGwfUlQXKiUP6QLQqy+CSWcairT2NsqFsiaWb5Q0Ri1lSdY9ulhrXJUawTtjv9R6MHzpZNrhKfyLkMNTxHXeVyf2/q6c7+/oXdLOkk4yjXCUwCPLlFGySI62N49WHZ+lGd3cb69i/+pyjuVUVFnV3oApqzqKKZhhy8mMSiXDDLr7gxizY+EWrFDGY+ZLEglyp87unbCQFYss4poJPDpFxirVUc0ELTtphqnj8b/AvVWP379HrBv0Xbiu955SCcP+GEW1a+AHIuKT5JDRmAUkUzCrDCezvnQxh5UDbmWUt1qzINGtSFAP1nCsoHFOo/em2jqGzV6qvD63rdebooTKRWWHp4hQ5OAU6HkGO/xE6z28jfNSSU3O4W19bhu6/JRbUNC+RN/lZbIt+pRs2IsB0EgLwFUIAEC1GOWJak0Ze/+Jw35N4/plzgxIq/rHqgN2pX1K9hwwBkBFLgB6/tNF62jG/MfqceiTvoutHifPm6seZwbTs+S5HmdxVlLtirMGCFfbZrlV+ud0YzOoxzngzbW7ub1kLDS1qGDOnDnFUI/zbNCiHnkNs0MWHJTs6NS17V6zqMfJ4eROpjlwp1jqceb5DJnUYebd0HkrPH8Mvty9m1nU4yzkZM4Mc2AOUpL1OL+KJmV9X3/RO6PO+5xOEyd1Mat6nPGczBtR4mGiGdXjBN/ynrU1wNJ/xteO71reXXy4hOtxFJyciypxzpm2Hqd6xcm3T7kErro63T1nUa/bZlGPg/sQrPU4mCIk/dTY/w/1ONeWINLPrj1C0lxPNWiW+nlNCdfjlBZy1eO8YE+W8lqPU63jzM+5uVFoel69WrlRO9fwXo9Dj815qDFBhFw1Jp+YiVKe6nF2TSh7foVl+5Bfj6tcgke+mcV/PQ5NR/CA1QtvLqzuF6/OLel6HBmbGht2UOYqC80R7ToQJn/8V7/X1J2SrgnggKS/WqKKZR4jNWL7oqGPTKMCR8R0uzlJzYmjpAIJaKcXA34BKnlL683O3JL8SpxTutm2PffX5rI+H3MnR5/IkL8KEZgKC9M/bwWRSvrhJgOlUnc3SD3NYNCzq5YI/EuVyprlSqNySdv8ShFSOSigigrE9PoI7e1wthKsHMLGysw5MxNeBH32XzisliZjWrMB1FyQHygaiGdaIla3mviCQINpO2IEYIIGmHp8fFWsUh4FOtSBUqho/HO4GxAvidEYpHvpR8PKiZWRQ6VRui/BHp2ZxiKuG6oSnFEkpnU+3tsYUsxUToT4t4Z0pAEQAf8V0pEG/EvvSBM68XbniPzn3r+e2p5i+TbsMr0jzYReK8ZeV/UPSM/LXPQofUZnLV170u5fd6yh/zCkYw0bp63A0WiSjVBuDbFqv+zorXvCZRNCxg7y9o0vCrf4d+bcUUQK+LoEquqzUaRf6xKZxWcFRt4N1GDvoIgpMHsFf8dDjmT3Dt1GQxrnsPGqml/BasMMQXyCGm6wfxFNXVL/QYOA9a6uS6RPVv/OybLyIuJOkPavJMEUTOvKyTT/4mWaNiayEIsIhQq+Mla37nHeaNcom5Fz8iGnAcsUGqkarzbCfoKiMKG8Kr9goThmgpP/yvRLM4/8tqwrnVflQxLiJYPlutP5CC3JD37VnXl62r3Q9kf/0rxxMbUTJ1M9WzPaH3H2lCeFXUo0n4BvIdN6QHAKugXQdMzJBfhV3kW8mojQS3lC2PDveri9IU36UDaT3vXBnbDy8rP+y/ccKD12p+Mkao1gRKwsOl4ARm1SzTqwV2xjfh3CoqOBCyaRy8mJlDIwSwz0M3aDAkyfwcb2CJDj+4YilYkiYnDqvjsKs8z3UaRZq6LWz1TCB5Jia1MDHhheQuts+2D7Jiv/9T5vl7h+nEttUmzB8oqFBjb0OdRFXWNZKBIEsEoXwtbYLhTxbmVctQzBQSUuFVBcOuz64+Xfgk3BOyplV+vZKMaOkUqLNgyYoq4n7M3bcL45JiVmkEYztk7GCjRR4eqrc9SpnBU6wydge/2px2ef3kEd7oO3YCku+J044bcrGfgZlTFFnV1MrAhQ5Ym9CZQj9CGk/1JTFJUjX0lVkOcNMzCICCwI0sDIWY/jnMh9NatxXb9Zmldlj/3djGouKxH9fgREps/whqWNiC+AwD5SKQfRLKhZBCOQwYIQaPC7GhYoVv0n/NangAfihRdqRH2bnirmeD7mYBwK2VBUp6DImk4YqhlQY3QFRSZ3KnqYqNrTwc134j6/CfI6VR9KrM4W1riUtzDRgMambFytgSck8BYzoJSB4CKUaW+Stx/63OtccO6cH1MXZ8t7UteHP6zslrhamDFNar8/a3V0mGj8klHPWj9+MKOoxnQGiqwGvD4O1WmrUWSxWZyURhBKHKIVEohOY+OdbaDeygOBiQznpTuUfYeCbXq96xAUOKeOq3+jDWe3cccfluQq+1cRSPXUOu6Lc6z9Zr1evH3SpV7VeGDoHE6GYouXJaIrGpIeUCR3Np7wY0yWpd+Ghy0T30W4qAxD0oOJpEehSGY0E7WRpDz03dfyYLcJ2Vcq8IDkaE4kNZ0YsZyRzcMqE4oZs7QcuoR+YK+QYJiAkKleIpzdXfi3wK9I/QEP8cqIgLiRFjjuv2qBR945oW6XsDJkav6o9g2e7rhZLBZ4axcuCzy3y/8sMLcFflhBOqZbzM/giQsGL0z/FjrLnC3w5i5caibbLEq4EaRYLXCLCyv8/dbmiadcvK/yXXsBNaEFph9z5IGhSzgZii3eYrTALUclyjK/5YjnB24YuWH2Ny8TWuDx3zY4fN1tI5xX7uWWjtalP/KA5BROJMd0KRYLTD/vZW4WGNcfrBZ4rq7iXMFmga9PdUq96Rzsm3559+ecBr61qBnO8AS5nBj8y9w7xZOsImL6eZhCnqQTDeiZW/xOEnIeOD4tdrhELZPGJwGNrq3wMawa/UDyz9Y2ns99s8d0lDzaeGQb2yMzz44X0AyFuAaKdAMQW4lgBTvHUKRjF6OaQNQI1wKgkUrUkbGCaLUSLnmJ/RW2IYkOQeM2P77wOfLEq6IcwTax2quDIuFdWOtNRqGIXxdGWtbIFLZeoVMspvVUGCPhCcPo5JSdPjnbw7atchY7HbFoxXth08GUz3aiaz7BW1+/+dOy5tFZPIDXkRO8ll2Mm7fnQIgY5vL28x8giCQWKJC4fuEDoJDRdTfVySVXOMuSopF5V3G3SdEaBUMnxUYERMuoY1XuPjICAV1DGgwWvJQDdLdRqZVDtPECmGmNIQjvXLjac9+yatdEs0ds3z+1UllaVaf2J5hSpqOYAqiOnEC11NkCJZstmH55X9WK+xzCxsV8dUlIbV+Jqlh1M+AhY0UtWNB28h0Rr5ZEEi0EdLPpNUDnk52KDFP521wWROx9OFg04e935QdN/2c+25MxVX4BzVAkx6OIpCNZscxU+ddRJLijKfr+TFu9ddPdumH+aS9mV1R+HPSEx74/fCeaJqHIQIDQGyECmW6ThSNklMoiIcJAUccTIgLf7h5+KWlPp5+hmSnqHd9Sz/jRNuPAtyF17fhl3tfbOxKD81AHtZwI6dHROMVUmcBAt0igCPQva2+9TRAYsAnpOnPCspdzKAiUwWSd8f74RVO8fTDn2ws7arWNik3bPO8ZKrZo8UW0YNVpvxVhgX3pG0kKSDcNNj3jqBtfDCY5FPQaS1Qa1Tmj5c3Qv5SzDoZOsRwt7vnP0d7MR2K69uCqobANQpGuIGV2GqpaPqCIVyejVEsV8OOFLpsuipvDL6fW8l7264zNmnnLvlGrSPH1wWLdKcTCtIzSfk3Mye8y/5Vd7m0Z8KDUL0XVMrEoEgbACoc6Rph29u0ErfhmLajBweJeX3tf/PrjYPZ27x1v7R9VE8+cQT3or7MlzIP+BaTCYJp6RP522KfOfjuinud/XDg6mQeYvDhh8uhknDK2JoRKGhPHdk6Mnm43dJnwr4cwTYPLyGaoJaoqAtCQemjY/6MIeHv9YMXGhhtDdu1vVPdzm0vfTBwBW3XiioA/GucOGR4BT1q1uP+yv3r4761mZzHIcwrKYwRM9yR4COIqdOIK4n52LLYIuNPkVlL7BfN8Nza1n1ezRsMp/4UI+GNHLvCeG+lOGh0B002XmUXAuGixBnY/jXQ0+YmAVzwaNLLDvEf+y98/WJ3d7fsns4iAcTFiBeq5zidV/z+yBT6D4nbbCwf6Lqif/JvF3CZSE9uCzR25bEGGqWxBfXH84cxeTUPTnjlcHXDjw1882gJ6TMWDOtvEqc6yis8W7Hz88vKw6i1Dlof5Dblc7/7s/4ItyOAEL9XUtoDun5uZLdjEqeKySsQW5DhfGbku/1TIhm4J/Zp/s0w1C1uQwQlUqs4WaNhsgc330PwHY5uLZyx16d9T/a06NRYMBcoTbJwbfvqgSXcgGhLiPKFu+Dc4KCUA/ZMVwyVyWZQsPgk+Q/Dch/MLD2WIdq85f2qyy7WjLE/DjEx1JEOxE6PIoQ4YdnehFShbUWRlB6OUvDX4cbwRvJSlpHjEjCVTPMdeFE3VHPvhWH9fGjWehL4WcbWwXenGreIVrU8u8V5++dUZj+mbXhVVO3VHkbwOrBuu43FojNJONUA3bYEsmhAHmUYAuAXFyOpsVP2XO5PDlnYqs3Xn5jaPaA2zAZP95JIYSAZcj8b7OjtJAqKCqusyImRnB+MUki0dkEBiWcAjneAtCV1+lg/6NTA+5EmZbnFUVU1+kwUWGtkUyGzgRIYuKqULQcZFiJ8DS5DIBVEFVG0zJmLYJUgFsmwvfMwNdNtdP0k86dW9oLa9baidcfV/j5kE1CeaAqd0TpxmddBq6ng2Td1xdLNT24Vx4uz9c1vvd+66j+blgMRwqBJyTKwMC9QNw6VqcCJYQJ6uECikMUTrYefQsO4C7M9SF/h5sfX+r9Czx6qLp/663X/wkwMz4U8C8bdIiqGopaLIB4DaDAy1uwzUDqHII+N0dCWUfFP8KA701VQjDrf3ar42aN8/Tgk9u6bUp7xaKSGzaEhYqPNI12lFVc/zUeQdQMVdCFQ0HZXlOCpGqWcbTElI1RopWGXJwtFQXM69/fR79YQ3Aem+v93xGLK9H7UgiOgSxDwPTl7nfTldJyH4DIXgCw4BuZwS/qtFua/nTUz33FMpeE9GYtKlI4tecDwfT0W58Sji64WhuhvqEj1CkUZe/yvK5S7K7XhKKQxfci54xjTXrJdxx7J5K8qlr7+iKhEsZBB5ke2xoOe423uZaVGukfWPRhXlrrs2Z9Qeiwi/7OsnPv76tl4Un0W5RdV5GMdacHIMW53FWHUbE/PlmSp2RcDetxKbY2l7ERNW3Y76xXXpkZfOofucZ1dps74eyoPsO3AiWdWrWKpuVwyYtiNgwWW/ZS3XT/2Yl9fBrKpuf5AKAh4EWomAuJEmdjibiRXENNg5ZeZUdN7hDeJFX/ZQk0xlu0nlkiSqaTUS5epCQaJMLRWowZ3I4ACKND1ChjwIc9h8oTrZxvrY89MPrIXL695p3PxgvwZFlctNKKLoQMplCkMur6BItM6rSTR7yP+elpa15VBOSM66aQk1RPMt+YGcvmR4gFzuxQV5lE7KR7BB7pHV7Wi/3HV+a7Mqnzo05uNC6pv6q5UJKirk1lrIUaV+czL8EtEjGlzStn6DcaGeUBAD7ou7JGqJRhOrVKmkapIfmtKB/8fedYA1kXXtUREQVOy9RFwVFRG7WMkkhBYICjasEQJEA4kJqKjYO/YuYu+9F1SEtXfXtbv23nuv/9wpITNzZ0iWCWT/5/N7dr91TmYyec+955x77rnvkVKAMRNqmIiKtJirOExEOQ1m7ImJCiDwZBMmsiNFTJU7+kt70jQDImfoYNmg8nsXWOmKfN5ExZgPX+2HQyBkDxaGjhFKx4S6Ev8bCc/mLsuivys6KjYWm1Z0+aEWWqsmPGt78SU8C3kJnPCc03vYzPLRDj6Lft6sHhUyKUqwhKfnyHM9Stuv8dv7sI6mwZuoYwIkPGt58SU8MWislPDsubvwra8/j4pT/05pN+9UvgU2k/DEAeFMV1X2smLCc4/z96sLmv70Tx3jP0RypXpjG0t4luRFhjlUrJzwHLByz/FS71KlMySDOrgeLtfchhKev5vz4fSxOeVYB9l+wjPu/fsmd7Yn+02eV0Wz1fuPlVZMeHb14kt4Bllmo81IeOon3xD5lB/vnfpF9cvRpfJpARKeTJsmQMKzixdfwjPIQvNsTsIzZXfPam8b/ZCsTIpwn3rYvVCeJzxxCDgTnhgE5HQa/F9NeHbZcLzzwW6HAxanyX6cUXfuZP2EZy8U2exFFqqzQ6I3KDLV638JT/6Ep+ufzXps7NxOuqrc5wrNni0YKljCkzn/BCgg3+jF2SB1FYos97LhhCceRVgh4TlsxLCWR3a4KtKPJC69FxoitaWEJ6ax+bwam5q7GqPe3zEsUacy/fGuJktwj0CVPk6l8QCfMXj4+vUMxcmAzSEKtmtQv0HTXMzgtih+0T3oayPZOsfVL86nXJ9lxQyu0JkybGiM4R0ag71yJYM7qkYjw7p9zWWrj35uMNjze3ebyuDaSQiLB1/VFpOA+UPGDENsPp3IXPLbbAb3XHO+dOIx46onyeYhd05FbzhsDkM3VM90XJSy97EwkDOnjACQ/+3FB/lJ4ygf+p/M4DIzhCYZXOay1CSDywymTTK4zKlkksFlqtz8DO75C8Um7RuhlR0oNqHJ0CljGgiQwR3Gpa4y9yZLS7Q4J1na5H7G5uMD6A1RyxzcDfsfvLVJcaLvEUQ/HI9xIm4w4wvJlkrM38zxadgQ4fgoFH6mITMHEpY+uD73bz2TMcSFdO7ZAcwk6HaUKSbVPZxL3b/GbFtR0sMO3dWtXMoqXRA9+eLsn/WHrmOnbHVsei9EsaZiDm2afgRK/Gwih+qt2EKPaRn1Zsq3rxB1H7vzbX/O38ZO35kKszO6TIZFM40upwLnocglcFor3lSBIwQzr3Vy0bzGz6w0zP9JF+9Fpd9P+bo47W8T87pp+fB2LdM7++7v8mdDD1nnMBPzejPjfdPmDm+lG25H/vPc4f1GE/PaaHytRi52TrL0ewfu16xZbZeJeQ0qXTJyzrofQfM7NXz8yGc62DsrSIp8fx2brx70RjHpaol1QaXu98FE9qToWrM5+unPHOTJ4e03pEoSUjCRAylad3/C0uAt28SbOw30rGlQpGMiR1JUR7euc3zjVgGL2r5vdPZnqWRMVIi6a9Noh/qZjf3XnF7RwrV+wUOYyIkUtc5MXVP38FHFOoW8aPFZPYdjImdSNGFTegndptIBaalr1Bc2OW7CRIVJUcenssxBxZoG7bqIrLoZfRbcVYQUVSpd6seIXj99liVq3igPfx2HiYqSIpeqU3uf/5xftnTw3Q5Lvf9ugIlcSBHys8mrFeNv+C0Zdq3I3KjRkZioGIV8vgbDx6cFSNbWGDu3zYUOYzFRcVJU7WStcoEh0wJS7wxfETnjBNi1LEF9l49/7yJz5sk3vT5z+nvxCwcxUUlS9Nk+on7rAHvFZp8aY7u2cY3ARKVIUd2jAzb/2c4/cFONJa/a5C8DHliaFD0v/nBqoxJT/dd8vhB08VPZ35ioDCkqXPfv5eX2jAzcdyAiZH+JN3MxUVlS9KXJyakbjwSj8yVFPb76TPLCROVIUaFPI12GVouTph3OOJcaM6M7JipPfdcuu8mvDXV9Np1pu/XAp6ojMFEFUvSzWsjXcyWe+m2IfXZ4uXPSOUxUkRT9Lhx3PrRKEfHCoGqPjm2tNhATVSJFHuVW/9Pe55zfrnx7SofteDcSE1UmRaf7rlzQ+tpF79Wfnm3Q377fHBNVIUW90zpK3X43UqTVXn2oX2i7jpioKimqcKVqVLNagxQ7UscM7jPpZwAmEpGibc21Tf6Y3sZnarLoRKw0FSBfjfqu5DIBTvtHyveUHf3Yt/3v+5jIlRSN27Cp+m3xb+ncLelN3i47854ViAA7BLWo/ffeeCkLmyHdIb2vlVb5/VGAQGQkl2ErHZW2OeXICZ/UDfcGnao0ZAm9447PQJ1GGwmh9+DaSK5J3iEiSYOw1Ts4Mxir1Ggw00VSFZjJ8cE0a9BXYzcDIgXmBt9Y0H0LPYYTFEBOSt5CkeOoZUwfWSRCxIvAOYRE+UanLFnpO2l80lq7GhEVBeQQErqfoxuK3AAARUITFZOxtQtqUSuPJu1V2NDA21RHqiK0sTqtQY1n3LH3U2vwji/UOBEpsUWeEnQXjYCiOGR9idcjxv0S71hft+OLi+IB9MoD4/ewKw+yRIKnLNzwEcMD1wHUJhpQ5MtpA4p65ESLzFIXfsY1VtlXJcLCFrD321tpUBGGAN5fL+yMXdnRo9FdO3r26NH7XlNGto58LKQxPCURXHufyMEuhR5HLCkBg51VNWAhcNU6qvTxauyT1A65igkkFKzp27UO+w8XlIw953J+2OFVzehgUc9kg2WUWAOs47xgYUOd9D+jOHf0qubvO2trMTRtqeZ1yyRHP9qvcvEhedhEclVcdHwM2w85cGCcls94K+WJlKDAKQIDA3uAKEoZEa/VY8ZGGxeNn6DV4F/gQX4RKTeIIpRxot4qkSFBp9OoMQ311mJC7H7ikQlx4FZwCDcOtADT4E2Q8YseIkmMMi5aheu3a3B3kY7agsPLjbTR0RoT8ivsM4AAKxYbBGb6RmZczwsba0wwP2CuwhEUaSDBFF5aAttsfIZiC1VrEO6Flrv3c/HRttLhe/o067c7KlJAZ8m0QDl1lo4oUl9CpgXY1j8ZRWpILHKWrrTxSPbbxtnnCMCwj0IhO7tc9HBahW3oiqcRHxyOJBSmJ/E5hgV1XXBDgaFSkRcVbNzk8calaftiS/piNfaPEoHCMHd8FtO1pTaY2gU3Tw9P0VBRAw/P2lCVySIKHei1oljQ5HHrg6L7nrjCKKMzPghSRpcls4bqHHhV99NWwxm+6pnKBNeEkqA7Bd2q1VHAvBNeAKqe0zMCWkwYMVS69XT6XftVI+rlhNckp0rJJyGsDHzvsIIEWBmLahtrhgFnhSHSX0X4RQuAuTuvzfTN73Xi5TszVN339najL9PIB7OXaZTAGuBU5AWnuMSy8sZahJfK8uCWoFN1XPOUUZ3qK3amPp9+tMdxT/oSxViYw16iZImsgZADL0I/jXHbaK647cQCpfynV1nfkauqODyrPvgAPRrFiQlDpXLzEwconReUjISxFWIU9lcs7ko0Jc/EjC05XkHsRYZuSWYFTsysJ/y92VE0JTEX4xAUeSbHML4Brcv6gSIn5VYgEE251OXV4p6dZFurbJA+iF9eICe8u4xIqVHHfUfm+vXw3RpV37nGuEqzcxopdUaRJ3LO6to9KHJLDiUN5XLE5XCAqHHhFqnWE4V8cGdb4sCr4ui6Jf4HCs69vNc1wo4+LaXUzexpmSXKtgdNzNXqXSc/kE6z+6u/f7yksgCAXeQFDBtReRJEET4DfKYRwvXnDSuookrCoHtOuC55rGrZs8379Z92z2eTaNreSVfWni3hH4dZSkwZPgN1emwJbvIsezEa6ta5ds4CYIZq05sWe2postdv18rqrXpo/64ggGozeVW7K49UC4uPp7UVmKS258sVr+R19krmVv/wodjB5R3yjqTWSULYpC3QciNs1YtNMdIxjuFyjOjFsjf7N9vuvbFrj3LJHdPprUBLgZKTeJD6lKqjolR6FQYFhKSfq/q/vkQbi0FOFL7gj4nMegy+OCRaZIPEEjjKZZZHZG72Zf/CLHVAP2Uu6FIUGS/FQH8CPTCQiSKDpDltqy2Wm4AC0g1anUoPog1wboIY4wZw0I3qeaAn42ADyEZrB6gi4U6k9t+GDt2ub/Getyra845fo2V0G9MR75XMtjHk9exsjMeD4YqMwUXQndU85X92vbQ4pzZGjiJjAcx2KKz8fhwOc05TwjVM1G/MbkVo4wyqiAR8eOCt3KFY1micr7vrgLMBczfFbXadViiIcQjI+Fz28pcmFNwkXCVh6waDbbiDBMBGmoSxXCbhVNHq7xs01QaNffc60OPCMB/6qYD2Kp1GGaHCz9dBbAFXwFyPug+U5RpMjmkSg3yAOj5GpMWWKXrzLQFzb5/nPdmnF2hiC2hKQ6ScNKV2EqRFjud+GeDUDNQhT+O5Vo4DMwMcUyeekSxJ8zl4LlDpTQ+f8Qexw2ficnbTmVnLIAD9ZjBAbhk0ZFiMIlIpZ/hsJnIVjcjpaUMNDC0ofF4hLf66UDAscPary9NePT+aRIOvMDlA4Fs6dKngsxhDqwUvWp7SXA2wqBdl1eFX56vDB0FutEoPOW6RU8NdBneQQLHYI7BFdSKhaqiWmY4pJ5Mkp3otJiFmAehvw9ZrVQmYBRYlwsoF49jip7/w0U8Offgp322TNk578Hpc8KZyr0ss7REyiLExAX4VZGMCv2wNKFrwQuFpdFTjbL5um2kthanbXvO73ZHfydu8Mx6WXPU1IHKNAHXbRaV8ddv2RsjH2zzkzIo6YSBfOG/Ry5cVm8lWtcloMVnaIscNrTDIk3z4IE/woSCfIFgtpwsFeS7UckJKL6laTkjpJVXLCSm9pGo5IaWXVC0npPSSquWElF5StZyQ0kuqlnPesPCGMa/OB+xZMtl1UYsvn1glb2DwwgliGUWbApS8TeTSv2vg4Xo3tzrJVttF9r78tBhd/yWJZD+NHpwdlNtzzDZXmTouEt8coPjLdRSpuUVd9JiFqtm+Igsc2Ics4BKZAPYHrkJz1wdRRG3ZNn9FY/MAkqecICnnrgv6/fXILvsJwf57u2uOpLv8pRCwhwBzGy+nBglbF46TkG73DcsgTUKRgewNfz6sShtLIkyxgqLk2H5VzXM3X8n36E5UvHt4Twshawg7BH88vmqgbK12gt94NPGgACipeVEKl1hGf+BubBaATzYcM5OWAcbaM54WhdFFvB17TkQnNng4J0XXslJe7udeJwcRfEPOXoIkWbifW8e4ewggIuCJ1MaCyifMA9FsExSchLjHS+88Lxi0q/TkwfduFyltC7uWGEgGXpDUFu7r1mC1VMgaMvjGIreBGlHx+cazP7oHjt3h5nJNHvEh7/soYOj05EWng4QKjJK5HKMN9nlkHsuwQp/HqxK+Po8HLXN15m3THpaqlIeiUgNXhJw5Wbx+gRlW6vPINHECHFm/LOFrYHjaMl9nTp/HTZoT31ppB/hOiGg/o9PzLYlW6PModEgQg48aHpj2WOjsst9CY+4152mfR3yMcPZ5PGi0Q5O47JCk1un6XqNuy5fIlr6N9ypfmZmHjlXqRESeBpIv5wrNaxH3Ubs9+LkUpShONQBcUunVEaSDNMssMY+E8bwhLFNuIjYXVyxy+ux3DK/OgcTk+SXIFT+LDFVRfBuKSO5irwP9ld8cVBfvZyzzG3X4VJPI3/vpTBAF8QewQyTicnZzjnk6LqdzDkGRjwCeDdA5NwdFnvtZVE1ShHgfckxA0fm7lMGjz7Izsl3OmsK+/dvSWxCTP5e9+0dezw6fTg2HvuszuEXARPsLn65muPgIgM9dXnyw4ZMXFQaOeOFGfwKIVgjzD7tshK8Wt0iYUh+tiudTWszZQq3llRuiGTs9Vzyu+pjenMeeuJ+tNPK64MYS08oZXq0csimtvMmgtGKR+3LBDZ5OFUkaX7hiWqijkfft/TaNunuqZ/XQ7XTFBOH3sxVDXhdcMUUlhDkBaUb2etVVgjzys2xBVtGIAb6w0Kizw+PsoNpdb3zM57s0OLPviRtxn+lVtRLiAeyqWkpgDUSu8CJy3I/y65O5/PqWGYEfurZs4T/2w894x0PX39N1THyj+cUwrYwrDLoDFw2IUUfEYGElOFuoNGArXZOqGNL9m7f4YJ7uhr0ve0wS1y2oE13pR9aJsqtfsKtz2X7dwh3wSmSoAZy9Oi5CkxAJjuWKiDeBtwCZ3blgEVFQYHLD0/0rJ2qL0QcfV2BjFOS28++MIssBhp7Q0pZ5OIYWWaxWweSIkhIjyvSgFqgHMhD5gRh1dAz476yYUjQ4GE7FyfTn9KFEfA17KJHXBZ/MH0jAykEBKyIBgJGTeYrNb1wxR5M5G1f5RNkOUuY2hwA7V/F+fDtXGiPmU7kwD94tO3sCOSwZHl6+pfpZQHHaTy0alKCJV+s06gj8WJj5/KcVg7B4AHNP8didGlEs7Snm1dQz+Cz4XoulCobcAprhlwEkzTA7cXMQC2gDILynlD+B8J6Cb2LynnLxmubjkAvJa8plmyrL1HrM5hhJ+un6gsdWabUGTHxtL5vreMWl8KR99JNl5vEjM9kQ66iHp3l+mu83dcu2CVN86t4RgB/5eQDJjwwt0LkbcIzBKcoHUpVQVYQW741rPkrBHYYqFiSPlmz30cZ+v3ltOR0llI0Smi1KmnKp94ac6um9+UkP715zjnkLgNIVXpTOBLA4I3mrXQiuZxAYmQEQs+o9z+mk8RHzBZpo+oojRdrTaf8xe8okAcole9rOn8+etvT/nz0l9bMt+epa0ZVWiqn+7s+Th9rnE8CeMsmdBLAUCn8+S+Hjb217Wn5oTNuwtiWD123qOyrMbcEaAewpM0kgAEoteVFq4G9Fe8r0oXluT/ERw2lPMaRIezrd5tcEzOkkTDFbk3zl306W6KS7PnrHbLk4ub0AS4IS/nxLAicj5DMEK2YrRkGeC8VsEOY8ytRDmPOoYjYIcx5VzAZhzqOK2SDMeVQxG4Q5jypmc737Yl8Rp6+S9Cq7HvV5LL1tUsxmt9rQePZaGbryzN4FLV4EPzUhJvzmuODg5apRfvO8qtQYdf2niFXnBj4EbynHYOoToM5tpmBDwzkXh8a/46yEEDhScDMrBVg6sePSCZMiUQCdzOLSScqeO13GPfjiv3fPzr1b+96lnw4sGKKMU2nYNL9c5tBNLNKBO0haGMDuKorTxqsISiLQkolomgNP8jE5HiGvYo6NdA6N0Gs1mvbAz4GLWQdF37Rl2M9J5UutQc98Cd7ps+pwy0dt73PZT8cOBpU+DHt96mtrSLUJvTWgwgt7H5wuKFIdT/52LC4BeyP3hq9iqKQgl9nViZEkX8zsekmQ4eMkTkFKfbQ6Tq6KorlNZ+Jye3V0DO16IeJ6mFZnepVuu/1K9Rc7DvE95oKDGKIHpw3j1cRbOVBvBZtQeuUA/7hIQNZFwZuvELgINmxMLuERPiirMV4qHAq4KJQaCWCQMnFfOFm/8e92nfRKnfEecqjOtnlnzmQcFSjBxxz/Anjztb583nypL+XN59g85kwqV9tNqi7mPQ4w13gcYK5gbjI3mfMhHL2Um4Rw9FJuEsLRS7lJCEcvFUGdLTn5jX7+fPHyTS2U83vMK2Q+cz6T3VcADzqPS12FQuf2X5XQR7r55RdVM9Had3TmO3JPMAj7lx6zh+YTBlagdhPjRAqdKs5XLooln2HeXiGTxZj3tdiEfIwPmDv+scWaqwJs5EgQ5C/Woi2fBHkVzNo95KugqEyMX4qYErALJAAGzxhlHObJ4McBHT4E/TPhnHz+vKKNtA3W7KfvFUqJJ7D3CimB8C1jUEQEIFnDVVNRRpEnNRUFIzBojZZh+fLlvy3hARTRFQOopxI0Sj2+BakBMQpUNyvfVNxb5kaC/+rSLlMyv68twuBXJR8C4VelJNbQTmFe7eS3Be1g1ui3JYVHVX1i1Qac0TiCpibKhMBzFNUURe8UCPQ78ONQ56gRdeLoyiGeCMnvZkmsoZwvwXzKwaxJ3isH6MdUOQWyUU4zcSz4Slwn2OsYsFtVcRGJBB9ja5FWp+wH6Bsb4H/L+gR8Rp13z/dm10NvNOWJr2xYrz576Efcw0yezz7iTpNaQ3kPeJV3PW+UZwbHpl02GmydpUFDjDouMQ6LdDH1YeqK08YB1WH/pdEOwIXgr55AFKscSFyA6jGqluODYfvcAlKGLexcSV2azv9VMDQGVjFNXraG5v7i1dzRPNccuAlstlhURVOCSFWr46L5DeGHZac8p+xrqtjV6J3DyA/L6VzGjpwxU5ZEcI0UkRAxBFhWHGeFVdXwsIqMU+dzxanl7QaHHtz3QZHhuPlhzaaD3embeEQvHlGIXtVfrRpAD1MBplxFb7XEgJDIYJLxwbllo1XaWFW8PlGkIx5ocPEnCr3849qr4shFCnfwyuyzwfeu7A1HurxoR+xfOq0+nmg+SH3KbOwnokgkwH4edCOygAQJVnAWxEGXvL4UNviZSvwdzYroy0yes7Jv/Mjg5QUeqB3ryPYyGmaTT4U0zKYk2S2G6/cq8nP94ROy3RMcN44uMsQhp4vhKSjSGyDnDbUjB1Cks8KiGvjSYSYhjEjbX6XXqznaWewvHqJ2L/s6eBfad37dKxuu5XwKM7Bi2ggBsArmxUqau3Eolax0IJdc4EMg2Lm55OZvRxUZ8VEXUU/0d0HctzG9qiO1MKA+Cv6/sGnYQ7/DuNxO4TJj/+Pn/1f8/Mz2RLnGz79TwcfPP5ttOwXg53/4Zrld8yfhPhkXm2xNGe/L6LKZo4PoQttIRxTZruCjM1/LtpHW4Of/0ij5YdI/XtKplV4+f5/cr0ae8/Mv5kVldt6syqFrB8vOBAnHzx/72e/vganT0P3FS+7zT/m4xWb4+ZN5VTcib1SX6/z81dwj9WMOBCjmJL96fLKAYRljOzO3+flxK8NJsI5ZmVzj558v2nZ04bgxkuHnWvfd29D+kw3w8y/mBWe2Ihf5+fflr9Go2YtVsgV9fhVqmbBltS0wXWAIJfMihM1pMm5bwBW3+Yjr1P3d+qJ4za0qa/9e9LoRoysrON+n02owj86O2Rw5cG6StUWizrqfpMnAENdrE6JjsBjOoMJTNZbQPDBbNnK+LaSHbJbQXHwzMxGXdhi+SglIujDxrSVBHobk9MxVqazXwq6SWEB/+jGlqG2xKQdkYwqF1J027tb1nLf1YoRQJyo3jw5zyZCtv3Tu755rdZqchlDDM5EiAL2qEtjonIsiBdpZFEIVJqZvpCpar4LHly5jr/2demu7984W+Wb6lyo/j3F4Cr8RcniKuC747MR+/9cQvt//OiSvgyXjyLQgUAKvrNZGqiN4aG92Blb1HqqO8puz8VTklUti+qrGkXoAe6waJdZQxkNeZfyTN8pghj+IJTsWHoFx2njMfSkjQO7UzbM1tmTFVhax7qIGrSNitPpId1HD1oZ++nj8L/Bodf8kdEzDZdGyKctLr8r4WuoH3a+BLwiNT9RAWmNmiayhrPO8yjpmEzMHPMqiaLV0VqI7LkHf28Azg/5+3dtnSsJjxfbbJ5q/TV8syclSOafqaCQhDDk4BfoXSx0yyfrfIZZFqaQl54m2esQO2q2Jiw3atm/EPXGBToXydtmLAfA+hATgKgQAYFosikQpV8bNP1Hq0Z8XtigbSkc2e/Ly0UqPpgxXlsvngDEArvIB0PFkCBVopv7H6nGYnb5zrR5nSju+epzwdtauxynevmd0n1VL5GmVx81bOKL1JRuox5nUjm93c2Q7GygqmDhxYi7U49TdvKXx6+0X5SOqHj9dt9SVvjZRjzOQVztxtqCdXKnH2VwuaZD7mUk+I2+mXv4zXXrFJupxInmVE24LykHysh7H7Unsomqly/ksaeK66/OPxLc2VY8Twqs8Wd4ozzbrcTwbP6v4PP93ybgAX0nzmLPl8rgepxWv5hrmueasWo+zsYrL5JgNy4LXf9z9dVaVb59toh4HjyE463EwQ0jGqQv/P9TjVLhSNapZrUGKHaljBveZ9DMgj+tx/mrHV4+zlx3SWqUe53DsoHfB3Y/6po9rVq61X9BSwetxmGtzAWpMzrbjqzE5zE6UClSPs+Gt4tnsWYFBKw80nvH0hvcCwetxmDZCAKz28mK1JXdtbl7X4yziMmP9MtR11cHrJLsPKDSPH3R9Td8paZcADkj66pW6GPYxUgu2L/6Qqg06cETMuJuTWI84SipSAjq9aPANcG6M5tomf0xv4zM1WXQiVpp6kPP92Ds5pkLW+CsUipkwhel5K8ioZB5uMnNUGp8GqafxAJxdZSTgH/qoLDGmAHqmnt+xIqEqDaYwVaQ/ZtcHUo/D1UqocjGXKpdMn5zwIuCL75x+ZQwpE93pZ+zsZaBoIJ7tiTjDauIGkQGzdkQLwAQDcPV4+6oYrSYSMNSBUqgo/HN4GBCvjDaYZXuZR8Ps5dqIvqpI402wV2ensYjr5poENxRpIjuGcxtDipnsJUhpGYSRBkAE4lcIIw34h8lIEzzmVpvQY8+9R5/aMdzxreIik5FmVKelw67ruvnNy1wy/9G8SW0oOXXS7l8z1jC/GMJYw6VpZ3A0mlQjVFvtRlSpsb9vmt/YA1+nLBx273NOtCV8MOeJIo2AXlOhpn4VitSW5UkvPmfQ8q6nAfsNcdFZbi/r7/iSY7Bni/ZJEOIcLl2VkGXNNswRxCfo4Q7767akqDqRk2XLHq0s9kdKW3delTlIiCdB6F9JgTWUVpVXaaVzV2nUmshOLiEMKrhlmHHe47qh5iiXk3OVkt2A1XEGlR6vNsK+gmYwobpyuBgduzbNG13n9da/71/5rzN15RCUEK/srTGezkcYSX7wrZ7s09Oe2dIf/Uv3xqdUZ16l5pOx6I94OeXJwa4iyCeg4DE5IHgHuh2wdOzOBfhVwYd4CQlhlzLFsObfVXB/Q7r0JVwuvd392woHzVnfxWkH8g/bVY3OhOkUGqOOiheBVpt0tw78FVeb34qKqCgQgik1GrIjpRr0EgN8xh5QgJk92LheAXJ831yklqBIBXDqPgyFeeZ7KPItx117i+ANSbG5aQAvDP2hZe+FHRJ/O+U3u6RyWJcge/qJazuOn5jtwobZhzqnc2wFipQDWM0Tw+bYbhQp6mNZtQyhQS0+KqC4RBbdfGNr0MqAhYUO16t1q+RDViotyjxgcjqfsF9ux/vLv+Vuz12B6mScAYkKH69O/qlrxlX9a2HA+pgCjaZ3f04/dI1TsOQW/G+kfPA/yhv4WZUxOe1dTMwIUOWJ/RKoRphNSP+lpcipRr6RpiDTG+ZgEAmYEKSDWcp5HOfE5ldTalaWTTG8Knj0szvdXRYh+H5ERKbPfMLSGsQNYGEfodWA1SyoWQQtkMGEEBnwp5q3UPyj/PHpV96UVqyoVPHGgblTW/G8H7sxDk1sLqrjUSQBnJ5NgTqjyyjSITjny0RdWgsPnzH7ZKM0lYo/VDqfzY64VLBlohnEplxaLYUnJHCKGVDKQGgRqrSkLs9Wllz+3GfhpZsuI9q0nU2fH76wslvianbONNErfcXKKIVkZOqQZ00e35+UU2c6CUUMQNfHoTZtJYqobeKkNILQ1iHUIIHYNC7dlfU3mXlgYaLGdekJVZ/dkyHqIXYufotvJ/fOVBZ4yL/+cCRn2b9agfR8ueKVvM5eydzqHz4UO7i8gwAK7cmrUGzycqzocoZkAyiST+qI39q1WiTe0KS+/I8XkwPMQ7IBG8kG2SJ5SPlHndadagTt/lmr9R+3tY8EQDKQF0lxMGstZyF5mAthmDFPy2NLmAf2slkMExCyzUuom2dt4T3wK9J+wJd4BSRguJEeeNl/1QN3dblQIHLHRb/tM94U8Ppas0yueODhIXweuFfI/zwwvwceXtb3W9vEs96zEk+fK1JpaoYte+ChIXxmJt4mSrgRJFc9sCjNLiL44yG/1MI9ylx/s76pFT0w85ijAArtw6tQbPLmogfuXVxTqd+wk9JNDapVlIY3mW5FD3zGKfnMlW0H/HZKitwuqizkLwCSHXmRlIfkigdmnveyNQ+M2w9OD9zLWHG+nMsDX5/gOu2GW6DPvIt7vqyr7kP3cE4hCRoN0fiXvXeKJ1klRPdzRZwm0Tg0oGdu8ScpyX7geLfY/kq9WhWfCCw6VeFjXjW6V5+ro363nCKf0vp4rad9Rsm5Xpl9djxLZi7EpVBEBCB2lsAKdo6i2DMtIoEoFUIBYFAp9RExoii9Fj7yPNbGKuZ/D/XNuOlR6vvqMbqcHMG2stmrhCJVQjjrTYag2K9mpWUtTGGbFDrFYFZPhykSnjAMXpPUvkuZh+J52789GnBm4z+CFzZlDP9STnJNGrjt9ZsrjqWPTBEAPCde8JAQy/rtVSSGGBbydvXtLoogJigYcV1DukMhY9puepBLznCOKcUQC27ibpFDawgMneFFJWBoWXSsylOqJhAwEtJgsOClHIDdRqfX9qHWC6CnNYYgFLI/943uMLhlyYDFHSeLhs94S98WcKS+gj3KjBJrAOXECxRi9AUruHxB8sV9xZ32VVSMiP5WO2GaFz3Z7mTsAQ9pK2rHgbarz8B4vTKCoBAw9qY3AJtPMhWZeaR9fpNRaTcr+U0MXV274BlnBdebsU1+lsxcJEeiSP0gsmKZbfKvo0j5IGvw/twteu7318a3g8a9Gb/LbUslmYC8P0InmsaiSD2A0BsxAuluswJHyCKTRUKEgaKPJ4YIFKKZL4odi3BLDUqtN+WHuOLikozNOHA3pK4dvyz4fHtHYvAXNEC1lyDVgywzTC4EBsZJAkXgftCxWT9OLAlcWK5BqMLlsxsNgQLYWGf9fvyiNX59ed5f7xJEWZuVXNbmecdguV39r5LZy0/Llir8w5kbSXEQNg0uO1PN2L4YdHLI4hoboLWIOaOyZkjQ3LOX/BeMT9i4uPOWcexXYof24Kq5sPVCkaogZXYaalo+oEghNsM4n2kpBr4822mzc9bALT6hqqAZhirjuh2eKKVXkeLzg8O704TZWZnPp/q9H3FucECqRHH/XehE55xamRgUqQzACoEGRph1LhkMrfjmLKjBweKfX9sPzTw18M55dETnlFbpnXfSC4ILGX0J+6B/lig7mB75Huy6KmaF77Qu3f508W+0XwCYCvHC9NtCY1yYGFSq6Fiuc2LMdLu500R4O4RZGnyMbIF6ouISAA1ph1b9P1oBj24Q1/jrujt+I19lBPVMExex8gr4WhDfCviQZeGQ+SvgpJRFO1qfkftNGhi6z9/w84mAK2BmJCHAIu5KEN8i7kxQrq2AYwtt31spXh68sYOo+2I3X9//wgr4EC94aRZaMItXwEzXZWMrYHxocS7szlgYaAqzAlYqJOiY+QX89yUeaXjW0a6hTayAD/EClWaMSVf/P/IFcV8HlRndt3bAgjlNmj+Ye1ZlZV8wlNcXxFjLF3TIlJcXx57znT7Xd/q2PcNHCegLmGsqAczZEF5zps89X9BtfObJutd1PhNu1Fy3dYi78LTrVvAFMbzg9bC2L2DG5zbmC4bwmjh9nviC/N8bprzsWsFn78TKKXbTz2XahC+I4QWqh9EXrOHyBUV/Bh+7P6yefNLC2t066r/Ts02FgoHxBBvn5p8+qBUGhoaSOE9obP4NDkqJAH9yXH+lRh2pjk+EbwfpXlc2tPLw2bCszPF9HS6c43gb9srUKDIXOzmKTAvEsLsDrUDZhiK6QIuMfGHw5TgRvIqjpHjX70udzy12VyxuV0CTsFHnSF9PQn8WcTW7XemCipW/A8Y295t1d7185vFvUTm1TmEoMiWQc8N1JA6NRdapFGDTFqmjiOGgNoiAtqAYjdr+ukr9LecDRzVuHYsmTOzKIMwGSpZplNGQDLiJTPB5dpIERAc11wUkyOhAywxSWSYg/sS0gGKyttyFx290p+U7V48Z+WH198l0U03eyQELQ2wNZAbxIsMcKvmzQaa2GD8HlqDUiCKzpBQZE9HsEqQCObYXule4fLaGbpvfovqK0rKdx/X0JKDJ97GTgKZCa+AUxYtTt0DKUq/lstStktxP7RDHylelz2iS7tZuHyPKAYnhYC3kmFgBDqj/CFHpwYlgEXm6QhSniiaoh92CFWEi7L9VteHnxdwy4le0mVcY3fYuqunD0QWc4W8CibdIibmoTUORgwC1SRhqd1ioHUSRHZbZ6CIo+UvxozjQn3Yxo02vjXcaSlZs7e24sdGX4bSflk/MLhoSZxs8Mm1aTs3zLBTJBKh4ioGJZqKyGEfFIvNcFDMSKr1BBWbZYHESPLteasLC6S0KB6Xb1T7e8fC4VHpBEMESxD4PTl4XfDpdJyH4AoXgKw4BOZ3W/VeLcq+9brUALSmRzft70ZTvE4rPsn5RbjyKlJRjqO6BhkSPUOR94P+KcvmLcr/G1wkZWeWyIjnk597OO53vCFaUy5x/OTUi2JKhuJykx4Ke43aQ22hRroX1jxYV5Uak//7VTLtWMmNGzPLrb5WIkEW5ObV5mMZ+BvJpDJuduVh1ayjmnO92h/igA/XPfpj+bO5eK1bdnp4R0GLCiKHSrafT79qvGlFPgLH/lBfJ24G5UnX7o22L0l4bbkinSOcMtX/ofs6mqm5/kQYCvgh0loDhRrrY9VwuVhRdfdf4yRPQmYc2yOd/TRtMT2e2V2mUiXTXaiHKJcWiAWq9SqQHTyIXB1CkmStkyIuwm81na5PtVhsaz14rQ1ee2bugxYvgpzkdl5tQpBU1LoezxuVlFGlshHyDzUPeqOO+I3P9evhujarvXGNcpdnCQM6cMgJA3kLOB3lDOQX5Ri7IG6xof6Tr5rWyNStcTh0c+nEO/Zf66rUJOjrkhSnIUa0pORl+ieCIBpco6jeYFqqIRdHguXhIolcaDDFanU6lJ/VhyO8vpQBjJtQwERVpMVdxmIhyGszYExMVQODJJkxkR4qYKnf0l/akaQZEztDBMm7Dpuq3xb+lc7ekN3m77Mx7CITswcLQMULpmFDXpv9GwrPx7WGnv01a6zPnd/757+pf4HobYRKen/35Ep5X/AVOeB6c+uJonwvpvmsfxy+7U//zDcESnruO1d/jOOkfn7SO6ZczC/TP8Yo6DEU++vMlPDForJTwnNG5UZNVO9ZKlkV4TviGNk23mYQnDghnuuq5vxUTnvafrrV52XO59/bi55vNeRhS2cYSnnd5kWEOFSsnPG+PG+NeumB9n01pb59HDi8w3YYSnmd4cTrkTznWzbaf8HQ/PiIpOrVkwNSTXp+6eAx/ZsWEZ+0AvoRnxQChE57zh68bFZFUz3t8wW2DDWvndBIg4cm0aQIkPGsF8CU8MVQET3g2yj/Z/8aGGb4TkqoPDn0fnpznCU8cAs6EJwYBOZ22/FcTnkewmK1i/lKyMS0ef6h67XlT6yc8e6FIUgBZqM4Oid6gSPeA/yU8+ROenf+4NXPLro5+s89Xefrl/KOVgiU8mfNPgALywQGcDVJXoUi/ABtOeOJRhBUSnnXXLi6a9DxJNqlS25IvJ/d+a0sJT0xj0bwa6567GqPe3zEsUacy/fGuJktwj0CVPk6l8QCfMXj4+vUMxcmAzSEKtmtQv0HTXMzgntRWK3O+L4qO3lGzb/uaVYOsmMEVOlOGDY1Q3qHhH5ArGdxrx3tfct92SLa09psZSzrOOWlTGVw7CWHx4KvaYhIwf8iYYavNpxOZS36bzeAu9OdLJ842rnq22TzkmnKp94ac6um9+UkP715zjnkLAzlzyggA+ZIAPsjnGUf59v9kBpeZITTJ4DKXpSYZXGYwbZLBZU4lkwwuU+XmZ3C/OS44eLlqlN88ryo1Rl3/KRIgg7uDS11l7k2WlmhxTrK0yf2MzccH0E96lju4G/4/eHOT4kTnI4iGOB/kRNxi1peSjZWYv5zz87ChwvlhOLMjw6SZBw5LN9yf/Ld+yhjwQkiQRgKjiS3zMV9FKn8nl/J/jdm2oqSHHbqrW7mUVbog+oKjsL/JH7rCnbJVOO1miJJpcg7F0j4Dz5qb/IGTQCSXCXDaP1K+p+zox77tf9/n/oHs9oQ0aXaWmEm7aKYl5tTjHBRZDk6pDjfV4y7BbG6dXLS5VectKXm6VSC6ZkW4T7EO7wqZ2FyV59n8B88r0Hl+S8MvblB5mdjcBrtixxVso5fvduoU5Xn85A4Tm3v0xKmHH/1Lyqaopr76lKbYbmJzY277ZiSeqS0dd+9+gxEO81ZiooKkyPfXsfnqQW8Uk66WWBdU6n4fTGRPudFmc/TTnznIk8Pbb0iVJKRgIgdStO7+hKXBW7aJN3ca6FnToEjHRI6k6EXx1vHVnleST1YnodMmfXHDRIVI0T93ai6cEu7sP04kWT3Wq00CJnIiRf2q7tDE3TuJrvY6X3/1t8wjmMiZFL2+cGjT5I2lfNN/9y53t4zGAxMVJkUT6wxOOxmmk+7L6P+86Z+rSmGiIqTIu9o56anI+YpFp978aLF6awdMVJQUbXW9cmTvZlXAnuRNU28WqpYfE7mQogdXkQdb/94UsNW9o9zee+diTFSMFJ1Kb9dhZ8cJQeM/vO7Wat6IQExUnBSVufSh14inh6QjC++bW7/BhROYqAQpGj83cnrtDZ/lWxeLez1H93bDRCVJ0c8ns8p2vaCTrjuO3K524VUoJipFij5/Ofi1ZgM771Xabsfab/8bDJvSpOh58YdTG5WY6r/m84Wgi5/K/sZEZUjRywbowm0bk8SLT7q/D6448yomKkuKqrdrM0vyokVg2sKTr2+rjgN9lSNFKxJqZFTuHCAZ3/hJtd0VnZMwUXlSdDmy3qKyC85J1o6fle9T+Y4jMVEFUnRoWaP4S36R6Jb1QxKRunNGYKKKpKitru+7mhNGBRyo+HPQPtdppzBRJVLU331Fr42Bi33mGL5XFld1ScNElUnRhi79/JKmVQnYWKZDg2+jZwGlVCFFasONvxz/Xuk9Q398ybB8+8DYqEqK8n9wkjU42U+ycsDKViVG1LuNiUSkqGkn54O9Qk+KtzoO2tlnXflemKgaKXJt/abJ3TZ9fFLOvrhfvuShJZjIldLX1dPhcu9/JAuXjQ47Ffu+Oys6qY5wRCdHWgeID7S67jPqL3vRmQK1zwoQnezmMmylo9I2pxw54ZO64d6gU5WGLKG34fEZqNNoIyGcH1y7yzXJO0QkkxC2pAcHCWOVGg1mukj+AjOJP5hmDfpq7A5BpMDciByLxN+GHsNZCyDHJ2+hyD+hltF/ZDELES8C/W09Xrk2duw8XbKs8m50bvcazwUkFhK6yaMbirwGAEVCsxeTUeRhqEX9PZq0V2FDA+9dHamK0MbqtAY1nobH3k+twdvAUONEpMRWfkrQcjQCiuLT78en+ibVC56+o0y5QQ3vBdHLEYzfwy5HyBIJnsdww0cMD1znQ22iK0W+nHalqEdOtMgsdeEHX2OVfVUiLGwBG8K9lQYVYQjgvIAjk5BNUWeCM0rN89jQ768ujBQe+VhIt3hKIrj2PpGDXQo9o1hSAgY7q5TAQuCqdVTp49XYJ6ltcxUTSChYQ8/OsfNPjw5ete7xgU0Lp8bQwaKeyQbLKLEGWP/wgoUNddL/7OHc5quav++srcXQtKWa1y2THP1ov8rFhyRnE8lVcdHxMWw/5MCBcVo+462UJ1KCqqcIDAzsAaIoZUS8Vo8ZG21cNH6sVoN/gQf5RaTcIIpQxol6q0SGBJ1Oo8Y01FuLCbH7iUcmxIFbwcncONAXTIN3RsYveogkMcq4aBWu367B3UU6al8Or0HSRkdrTBixsM8AVqxYbBCY6RuZcT0vbKwxwfyAuQpHUEQahim8tAS2A/kMRf4IswYLX93GFZwHSuMDknvN3ig9fN1RQGfJtEA5dZaOKIIChKZArX8yijQPs8hZutLGI9mEG6ekIwDDPgpvj/zzQuOqRb4rJvSf/eLbAdEbemafY1hQ1wU3FBgqHryoYOMmj3czTXsaW9Isq7F/lAhUi7njs5iuLbXB1C64eXp4ioaKGnh41oaqLKXl/H1+vxPQtJk7y45QV33HqK0zPghSW5cls4bqKvCqrljeqC77cIavpKYyQUChJDhQQQtrdRQw74QXgFNQJOVfstu9e8Co8z9EzSuMorN2WEh2klOl5JMQVga+oVhBAqyMRQWPNcOAs8IQ6a8i/KIFwLQY4F5iSrF53qnzW2l3xGw4Rl+mkQ9mL9MogTXA8eAF548wy2oeaxFeKsuDW4JOd4eNTpU/Boqnay+EDXwiqk1fohirddhLlCyRNRCqwIsQNqfJuC2NK247sUAp/+lV1nfkqioOz6oPPkCPRnG2wlCp3PzEAUonCyUjYWyFGIX9FYu7Ek0ZNTFjS45XEHuRoVuSWYETM+sJf292FE1JzMU4BEV+dscwvgEt1vqBIje7W4FV9JKuSJ8k1UifBX9fqZuxwYle+WkhGS8jUurXvkvCyKKuPpNjJsxf9O1Z25xGSp1R5Ht3zpLbPSjytjuUSZTLEZfDAaLGhVukWk9U98Gd7Zz+noe6/10YHZ4Udy9h5MbO9GkppW5mT8ssUbZ0hn9MHV8k/Ltk041WIacnlC4nAGCPeQHDRlSeBFGEzwCfaYRw/XnDCqqoOjFoB1JclzxWte3c2d/FRXzlaxZ/lW1v9jSlhH8cZikxZfgM1OmxJbjJs+zFaKhb59o5C4AZqq1bwP/zhNRMxZ52zU6UvTN7gwCqvcCr2hN5pFpYfDytrcDMtZKLbqXWn6kaMMEp7PPnknWa5x1zrZOEsElboDVI2KoXm2KkY9zL5RjRi2Vv9m+23Xtj1x7lkjum0xuhlAJ1KPEg9SlVR0Wp9CoMCghzP9eRgPoSbSwGOVENgz8mMusx+OKQ6JsNEkvgfJdZHpG52Zf9C7PUAf2UuaBLUWRBBwz0J9BTBJkoMrlDTntti+UmoIB0g1an0oNoAxymIMa4AZx+oxoh6Mk42ACy0doBqki4E1m2f/+o880XBGWU8J1a/9sDeiNy+454A2W2jSGvZ2dj/NufaLI+rZV42YtPWy4PCs1xm245iswHMNuhsJr8cTjMOU0J1zBRvzG7FaGNM6giEvDhgfd3h2L5+nJpnb5WuiytZtKIMptX0StynLOey17+0oSCm4SrJGzdYLANd5AA2EiTsI/LJJwqWv19g6baoLHvXgd6XBjmQz8q0F6l0ygjVPihO4gt4AqY61H3gVpdg8nZTWKQD1DHx4i02DJFb74lYO7t87wn+0gDTWwBd2lEB07uUjsJEpTjuV8GODUDdfLTeNgVCsDm0Ze9Ku48jWYYgvw+VAq/TA+f8Qexw2ficnbTmVnLIAAnpxIgtwwaMixGkU4dOMNnM5GraEROTxtqYGhB4YsSpR35K8opaMfErr5F4jN70GuByAEC39KhSwWfxRhaQbxoSTrkaoBFvSirOL86X3E+CHKjVXrIGYycGu4yuIMEisUegS2qEwlVQ7XMdEw5mSQ51WsxCTELQNMbtl6rSsAssCgRVi4YxxY/EoaPfnLow4/+Jj0YFdW431vv6XuP7f6xfc9XxsYE+FWQjQn8sjWgCOKFQmJ0VPttvpibaS2FKeZet2m0Q/3Mxv5rTq9o4Vq/4CEBirmrdeAr5i5vhDzd5iFnVtQJA3kbVXBL9wMNpTPGDPnwssTB1wJAPq0jH+TjO1KQHxCsltOFgjwXajkhpZdULSek9JKq5YSUXlK1nJDSS6qWE1J6SdVyQkovqVpOSOklVcvZR3H6vptLE/mM6xeevT6/MZVV8gYGL3T0MYs2BSh5y+DSv2vg4Xo3tzrJVttF9r78tBhd/yWJZD+NM5wdlNtzzDZXmTouEt8coEjNdRTTuUWt9ZiFqtm+Igsc2IcsIBhJBfsDV6G564MoMsSybf6Kxo4CJHk5wVzOXRfkG3q0y4mMbv7zZPL5lS4WGCRgYwHmNl5ODRK2LkwJI93uG5ZBmoQiyewNfz6sShtLIkyxgqI08l65Yy6pBQJGVuy0t3yrjCQByyJGdAj+eHzVQNla7QS/8WjiQQFQGsKLUmyYZZwI7sYOAvhkwzEz6SNgrD3j3iop0+lT/0RP98BlPnWf35twLiwv93Ovk4MIviFnL0GmWbifW8e4ewggIuCJ1MaCyifMA9FsExScLW6DDjV6OVGWotz6cGLlwgVtYdcSA2ksL0hDLNzXrcHqs5A1ZPCNRW4D9eXql8Z/NU32njtCvKXg5mmavG+ugKGj50Unxrinm8nlGG2w+SPzWIYVmj8+D+Nr/njJMldn3jbt5Q6jKgRfLhWwY/9e16Qfra5Zqfkj08QJcI79aRhfV8Pblvk6c5o/Zrj5r56TsTB4idhrUcAfoxdbo/mjwCFBDD5qeGA6ZaGzy34LjbnXnKfNH/Exwtn88ZLRDv3JZYcktU7X9xp1W75EtvRtvFf5ysw8dKxSJyLyNJB8OVdoXou4j9rtwc+lKEVxqgHgkkqvjiAdpFlmiXkkjOcNYZlyE7G5uGKRk1P4Mbw6BxKT55cgz7pYZKiK4ttQRHIXex3or6xZaULFbaM6B+y41uRVCYeOvekhEv4AdohEXM5uzjFPx+V0ziEo4gjg2QCdc3NQ5FcXi6pJihDvQ44JKDqLH5zoF+XhL9lV3ytqTJX6vxjkGfj97N0/8np2+JRKHh/R9pa/fMr+qA3n/h4xVwB8PnThwwcbPnlRYeCIF270J4BohTD/sMtG+Gpxi4Qp9dGqeD6lqa9+rfN1dmfx6FFVHH2KXKJTK9sT97OVRl4X3FhiWrnDq5XLNqWVNxmUVixyXy64wdOpIknjC1XMii8e1wrcHOy9s1mvB3Ov+9H3juyD8PvZiiGvC66YohLCnIA0I3u96ipBvnaxbEFW0YgBvrDQqLPDI+1E3Yef9rwI2FU4ILFPvWg6IbWDhHgAu6qWElgDkWdd+BD5pwvl1w9y+fUtMwI/dG3Zwn/sh5/xjoeu03mTyW80vximlXGFQXfgogEx6ogYLKwEZwuVBmyla1IVQ7p/8xYfzNPdsPdlj0niugV1onu6kHWi7OoX7Oo6tl+3cAe8EhlqAGevjovQJESCY7ki4k2gPzxzY3jZW6r3fhv7dLY/nf6NXozhwBXYGAW57fw7o8gugKEntLRlHo6hRRarVTA5oqTEiDI9qAXqgQxEfiBGHR0D/jsrphQNDobzczL9OX0oEV/DHkrkdcEn8wcSsHJQwIpIAGDkZD5k8xtXzNFkzsZVPlG2g5S5zSHAztWELnw7VyOMmB/mwjx4t+zsCeSwZHh4+ZbqZwHFaT+1aFCCJl6t06gj8GNh5pOiVgzC4gHMPcVjd2pEsbSnmGUnmXwWfK/FUgVDbgH3MNKN5B5mJ24OYgFtVwgZKuVPIGSo4JuYZKhcZKf5OORCkp1y2abKMrUeszlG5n66vqD60XdfOOL5EWnwDoeajqP8xWf+BWkykyIxpcXPRo8nzpfMnLzm0dj8hd8IQJr8qytJmgwt0PnQ9RiDaJQPpCqhqggt3jDXfJQGNRWJtj6p4LO9Z1LijG7q33SUUDZKaLYo3dK8Wlindl+/tIbVB6AdHHUCoPSMF6U7XVlEkrzVLgQBNAiMzACIWfWe5xzT+Ij5Ak00fcWRIu3pkf+YPWWSAOWSPVWF89lTRfj/7CmpH0TpkbDa7oliKfotdEqNj0sEsKdMcicBLEVEOJ+l6BJubXv6qkDHgmNbHA7YVmtt8JExsasFsKfMJIEAKCl4UfIJt6I9ZfrQPLen+IjhtKcYUqQ9PWrzawLmdBKmmK1JvvJvJ0t00l0fvWO2XJzcXoAlQY1wviVBZSPkxwQrZitGQZ4LxWwQ5jzK1EOY86hiNghzHlXMBmHOo4rZIMx5VDEbhDmPKmZzvftiXxGnr5L0Krse9XksvW1SzJb/YaPjadP3yFdvLhl+3DPxggkxIVJRVDvoMCob2+dq42qNe5Vn1bmBD0EHJpOpT4A6t+OCDQ3nXBwa/46zEkLgSMHNrBRg6cSOSydMikQBdHKCSycpe+50Gffgi//ePTv3bu17l346sGCIMk6lYTP/cplDN7FIB+4gaWEAw6soThuvIiiJQJ8mopMOPMnH5HiEvIo5NtI5NEKv1WjaAz8HLmYdFH3TlmE/C34bGTfrS0rQApc74+dcRPpx2U/HDgaVPgx7fepra0i1Cb01oMILex+cLihSHU/+diwuAXsj94avYqikIJfZ7SVGpnbGzK6XBBk+TuIUpNRHq+Pkqiia23QmLrdXR8fQrhcirodpdaZX6bbb73AfcdUpnY+54CCG6MFpw3g18VYO1FvBJpReOcA/LhKQdVHw5isELoING5NLeIQPymqMlwqHAi4KpUYCGKRM3BfO4G/8u10nvVJnvIccqidt3pkzGUcFSvAxx78A3nx/Zz5vvqMz5c1P2TzmTCpX202qbuM9DrDOeBzgtGBuMjfp9CEcvZSbhHD0Um4SwtFLuUkIRy8VQY2bW7P3HbcV6I7bjgEPxcnLzafTZ7L7CuBBz3Cpq1Do3P6rEvpIN7/8omomWkunyXIh9wSDsH/pMXtoPmFgBWo3MU6k0KnifOWiWPIZ5u0VMlmMeV+LTcjH+IC54x9brDXpBTZyJAjyF2vRlk+C5OvF2j3kq6CoTIxfipgSsAskAAbPGGUc5sngDP6iOUsylz+RDW9T+Fe7jTPpPWQcpMQT2HuFlED4PjIo0ghAsoarpqJ2rzypqSgYgUFrtAypqam/LeEBFNEVA6inEjRKPb4FqQExClQ3AXMThkRF71asDl+z7slLZQEGvyr5EAi/KiWxhnaq8mqntC1oB7NGvy0pPKrqE6s24IzGETQ1USYEzkTlePnUoPpt5eN+VNBsPp1vI105xBMh+d0siTWU48yrnHy2oBygH1PlFMhGOc3EseArcZ1gr2PAblXFRSQSfIytRVqdsh+gb2yA/y3rExyFtmXPXwsfGhu898OBcYmGEfQTv4XDTJ7PPuJOk1pDeZ978invZU/b4RCic2zaZaPB1lkaNMSo4xLjsEgXUx+mrjhtHFAd9l8a7QBcCP7qCUSxyoHEBageuyRVuRxRbrfPBG/knC5De5RBlBYDq5gmL1tDc/d5NXctzzUHbgKbLRZV0ZQgUtXquGh+Q1i50qTwKuPaBG79ZXf3yH73NLoh5IyZsiSCa6SIhIghwLLiOCusqoaHVWScepYrTi1vNzj04L4PigzHzQ9rNh3sTt/EI/rxiEL0qv5q1QB6mAow5Sp6qyUGhEQGk4wPzi0brdLGquL1iSId8UCDiz9R6OUf114VRy5SuINXZp8NvndlbzjS5UU7Yv/SafXxREdC6lNmYz8RRQYA7OdBNyILSBAlO6SlVsHQJa8vhQ1+phJ/R7Mi+nOzylza1rmL78SZQ1Vo6xV0ngtH6qmQLtqUJLvFcNCiZlX/DFskTX5Sp2fKo6G9c7oYnoIiCQA5b6gdOYAifXtZVANfOswkhBFp+6v0ejVHO4ufuy4MnjOks3i0z5cNx1DZgpxPYQZWTBshAFZKXqw65W6oQyUrHcglF/gQCHZuLrn521FFRnzURdQT/V0Q921Mr+pILQyoj4L/L2wa9tDvMC63z3GZsf/x8/8rfn5me6Jc4+c/3ouPn38N23YKwM//3adizLekQ+LNaeW6L/hWa5mAB9GFtpGOKHK0Fx+d+X62jbQGP/+MHdd2d+qhE88uvXdzfMnN+/Ocn38bLypr8mbhB107WHYmSDh+/u5Pk/a0+VJOPK9pcKmxl1beshl+/kW8qpuVN6rLdX7+/duOHsxX5mzgri1HVtb7rGJw9+U6Pz9uZTgJ1jErk2v8/Pec/DwN93/7zA/eEHxTXFRhA/z823jBWdMrF/n5pzUZtbD43LmyrdM2behbvXg1W2C6wBBaxIvQLOPy8y+uuM1HXKfu79YXxWtuVVn796LXjegUA/j5Pp1Wg3l0dszmyIFzk6wtEnXW/SRNBoa4XpsQHYPFcAYVnqqxhOaB2bKR823ZhAgmQnPxzcxEXHtj+ColIOnCxLeWBPmizOmZq1JZr4VdJbGA/vQ+1/90ce/RWTa+5uz0k1Nb0rmO/lVbL0YIVUh8Y3unvl6+06/XfjBr5nNZTkOo4ZmICKBXVQIbnXNRpExvi0KowsT0jVRF61Xw+HL3r8qus4/0VKQ6tN4Xsfu7nnF4Cr8RcniKuC747MR+f2He35+/d14HS8aRaUGgBF5ZrY1UR/DQ3hR98uKxTCX3TSm1qXTi+Qb0EwCO1APYY9UosYYysMnKo4xXSpsIfxBLdiw8AuO08Zj7UkaA3KmbZ2tsyYqtLGLdRQ1aR8Ro9ZHuooatDf308fhf4NHqgvSefUo8+sd3jrfj1lTV9Uy6XwNfEBqfqIG0xswSWUNZD3iVdT1vlMWYOeBRFkWrpbMS3XEJ+t4Gnhk07Gm+CcnjV0hGSO/opT9C0ZwslXOqjkYSwpCDU6B/sdQhk6wv0duyKJW05DzR1vNbn/vszd8yaOaDfQ7hhm3H8nbZiwFgTwFwFQIAMC0WRaKUK+Pmn9A1zrwhudPYb9yYM5vqnwjxYriyXD4HjAHwXMkDQMebSirQPP8fq8dhdvrOtXqcpb356nFie1u7HqfjqrKlw0ZNR7eL/8kc8mt5kg3U4yzuzbe7OTtvwiV6UcHIkSNzoR5n3/Q7t9On3gqe9naFz6WBchebqMdJ5tXOCFvQTq7U4wwYd3JO2KgMdFydtE9HnnWpZxP1OAN4lRNrC8pB8rIeZ+Xqo4GKzz/FO+c/3Hv37ig3m6rHieBVXpc8XybaUD2OtJNf4+jIdd6rzn++lNF1zJU8rsdR8GrOJ881Z9V6nKXi9Id1Gt8NXD9aNabfk2vtbaIeB48hOOtxMENIxql//3+ox8n/wUnW4GQ/ycoBK1uVGFHvdh7X49zvzVePc4Yd0lqlHqdt8LUvj7Y8E894stDJbsbiuoLX4zDX5gLUmNztzVdjcoWdKBWoHmd0nUtXhgWlB8wpHray68dBNQSvx2HaCAGwOsOL1aHctbl5XY9zgcuM9ctQ11UHr5PsPqDQPH7Q9TV9p6RdAjgg6atX6mLYx0gt2L74Q6o26MARMeNuTmI94iipSAno9KLBN0BHXtNOzgd7hZ4Ub3UctLPPuvK9ON+PvZNjKmSNv0KhmAlTmJ63goxK5uEmM0el8WmQehpvwNlVRgL+oY/KElsR9EHbLseKhKo0mMJUkf6YXR9IPQ5XK6HKi1yqXDJ9csKLgC++c/qVMaRMdO9OzwXJQNFAPNsTcYbVxA0iA2btiBaACQbg6vH2VTFaTSRgqAOlUFH45/AwIF4ZbTDL9jKPhtnLtRF9VZHGm2Cvzk5jEdfNNQluKOLX6RjObQwpZrKXIG6dIIw0ACIQv0IYacA/TEaa4DG32oQee+49+tSO4Y5vFReZjDSjOi0ddl3XzW9e5pL5j+ZNakPJqZN2/5qxhvnFEMYaLk07g6PRpBqh2pp1Ii3j8Jc23nu3i88VWYI+zYm2hA/mPFFEBvSaCjX1q1CkVac86cXnDFre9TRgvyEuOsvtZf0dX3IM9mzRPglCnMOlqxKyrNmGOYL4BD3cYV/q2MXTo/18/5EDVy79MmCdhldlDhLiSRD6V1JgDaU15FWaW+4qjVoT2cklhEEFtwwzzntcN9Qc5XJyrlKyG7A6zqDS49VG2FfQDCZUV9pGNdIr/PoWlN6h8PPOfbwbM3XlEJQQr+ytMZ7ORxhJfvCtnuzT057Z0x/9O/fGp9QqvEot1YlFf8TLKU8OdhVBPgEFj8kBwTvQ7YClY3cuwK8KPsRLSAi7lCmGNf+ugvsb0qVf4nLp7e7fVjhozvouTjuQf9iuamPpNYKhMeqoeBFotUl368BfcbX5raiIigIhmFKjITtSqkEvMcBn7AGvJ2H0YON6BcjxfXORWoIi9cCp+zAU5pnvoUiRjjmtnymCNyTF5qYBvDD0hwZViYr9WTpUMebPVr7q4gH0HkV2HD8x24UNsw91TufYChSpC7CaJ4bNsd0oUq2jZdUyhAa1+KiAH8av1i7zcrVr8t0jEl/cKL3yDSuVFmUeMDmdT9gvL8v7y7FRYgNpNEvrZJwBiQofr45Pdft1Xad195ucMaFVjY7fPtDHJbg7t+AvwAv/19xteUzBz6qMyWnvYmJGgCpP7JdANcJsQvovLUVONfKNNAWZ3jAHg0jAhCAdzGXO4zgnNr+aUrOybIrhVcGjn93p7rIIwfcjIjJ95hOW1iBuAAv7CK0GrGZBzSJogQwmhMiAP9W8haKv6nZYhzIhQZs6rDvfqsSdmzzvx26MQxObi+p4FBkPTs+mQJ3RZRSJ6ZnzZaIurYWHz5h9slGaSsUfKp3PZkdcKtgy0QxiUy6tlsITEjjFDChlILQIVVqT72+mi8ttkuzssNehfPygyfT54QsruyWuZudME73SV6yMUkhGpg551uTx/Uk5daaTUGQs0PVxqE1biSJDbOKkNILQ1iHUIIHYNC7dlfU3mXlgYaLGdekJ3wMNqjR4wuBNslE9p/eVrrBvzr/+cCRn2b9agUguupVaf6ZqwASnsM+fS9ZpLoBC9bwKxSYvx4ouZ0g2gCK5o2LJOiM6l0VTnDo133L4ps48JBuwkWyQLZLyjePu1f7k7bP7bOX6N1JeaQVAsgcvkmE9WWs5C8nDXAjDjHlaHlvCPLCXzWKYgJBtXkLdPGsL74FfkfYDvsQrIAHDjfTAV/6rHnjB6LHFThT8Hph86HGtqDl2A3PFA89U8nlgg/J/HpjfA1cbtefmkNTPfgtKuNxpcTe2ki174OlKPjMzziZKuBEkVz2wyxKPXuVv/ZDPiaj3tZ7zoRgremDmMUcBFJrEq1Bs8uaiBz47/2WQ94vRfjsdXf48/fxjISt64JW3nvTr0mx+wMrBdsOT/uydY0oJDEk1L5I9lbnigZnnvWzNA+P2g9MDG4wV51e5PPD1Ca7TbrgF+sy7uOfLuuo+ZegZzpAEjYZo/MveO8WTrBKi+7kiTpNoHBrQM7f4k5RkP3C8W2x/pV6tik8EFp2q8DGvGr3ZkFHDnMs+8tlzzGdM+4rKolyvzD47niUzF+JSKNIIQOwsgRXsHEWRyuzTjXxZ/VIhFAAGlVIfESOK0mvhI2+gR8tbl/+c6528cs6zFZPe/JmTI9hWNnuVUKSBkrPeZAiK1FKy0rIWprBNCp1iMKunwxQJTxiWWVdj0YjBX6QHyq6pVqRGvSTBC5syhn8pJ7kmDdz2+s0Vx9JHpggAXmVe8EoqLeu3V5EYYljI29W3uyiCmKBgxHUN6Q5f8jJsNz3IJWc4x5RiiAU3cbfIoTUEhs7wohIwtCw6VuUpVRMIGAlpMFjwUg7AbqPTa/tQ6wXQ0xpDEArZb8mRg6rAD/LFszYWd5977Th9lFFfwR5lRok1gKrMC1RJoy+4xuULki/uK+60r6JiRPS32gnTvIrQDauxBzykragdB9quPgPj9coIgkLA2JveAGw+yVRknskveGjtH4bemfJk/cObzl6xjbnejG3ys2TmIjkSRdAeZMUy2+RfRxH3Htbg/VncrZvP0cdVZaPHlTpx5cJ6Ovg54/0ROtE0FkW8AUJvxAiku80KHCGLTBYJEQaKPp4YIlCIXs8NSlgXP9V/x8Swh6L8DuMZm3HgbkhdO35Z8Pn2jsTgL2iAai9BmvawzDC5EBgYJwkUgatDPjcqHVtUsu3C476vRJp2NAQKYGOd9fvxi9b49e68v961B2VtrnNZm+cdg+V29b9KZi8/LVuq8A9nbiTFQdg0uOxMNWP7YtDJIYtrbIDWIuaM+2sCfU9+fRowtYGj3M5rqoj9SuzQHlw1F7ZeKNIQpMxOQ03LBxSp1NMi01IMfHm202b+7ZADl26OClglW9YWuTh0E72KFJ8fHN6dJszOyrzfYJ9aN1+cbKRd9JvgsR9m59TKxKCIJwArBBoYYda5Zk9oxTdnQQ0OFv/8MhQt/iW53hj/aWV+31/Y9Cx9ABQy+hL2Qf8sUXYwKd5cfykrPMYvzdkTPVmqeY6NcQw+anhgKtHTMmNcmBhUquhYrnNizHS7udNEeDuEWRp8jGyBeqLiEgANaYf++X+0Ar4xvnzxRuET5bM+vXYYW+38QiuvgF/04FsBX7YsHDJ/BdymW/4Dlbo7yJOHFctQqGusE3AFzIwkBFjEPevBt4i70yPXVsB36nRqc+X+Nel45amJE/wyJvwXVsCXecE7bWE4afEKmOm6bGwFjA8tzoXdHQsDTWFWwDN3qJul3KkZOLN5gXb3ksf8sIkV8GVeoE4bY9Ib/498wR27fJc/vWghXVRM77QzoE6mlX3BdF5fMNhavuD1+k0DH52s6DundlLU1+EqNwF9AXNNJYA5m8przsbkni/Y/Vpx80P7QeiCxwnvL53Sdfov+ILBvOD1s7YvYMbnNuYLpvKauDF54guKj3vRbc/oEgGr9y/4x3FFQhOb8AWDeYHqZ/QFN7l8QdGfwcfuD6snn7SwdreO+u8l6WvBYGA8wca5+acPaoWBoaEkzhMam3+Dg1IiwJ8c11+pUUeq4xPhnA7X7iqPfbyv2CmVlW4+beBUjrdhr0yNInOxk6PI8m4YdnegFSjbUGRUN4uMfGHw5TgRvIqjpLhh/ILaF747yNd8r1QXGRx9n76ehP4s4mp2u9La2NoPq8s6iJe4f9m9+GRijrtShqHI0m6cG64jcWgssk6lAJu2SB1FDAe1QQS0BcVo0eWykw8HSwPXxh70P75GWZtBmA2ULNMooyEZcBOZ4PPsJAmIDmquC0iQud0sM0hlmYD4E9MCislxu1vymKM7sRlavODH8JqT6KaavJMDFobYGshM5kWGOVTyZ4NMbTF+DixBqRFFZkkpMiai2SVIBXJsL1R6Xb7S7LtBgcvbrhvcdf2b6vQkoMn3sZOApkJr4JTIi5O2G2Wpb3FZ6lZJ7qd2iGPlq9JnNEl3a7ePEeWAxHCwFnJMrAAH1H+EqPTgRLCIPF0hilNFE9TDbsGKMBH236ra8PNizzzmdAyZ3zZo4ZA1T/f1SWauvck3gcRbpMRc1KahyCWA2iQMtTss1A6iyDHLbHQRlPyl+FEceFea3u02/DyeKd387fux6g+D6CDnE7OLhsTZBo9Mm5ZT8zwLRS4AVDzFwEQzUVmMo2KReS6KGQmV3qACs2ywOAmKCzKz74TUS+98UjRTt6b8DJlJLwgiWILY58HJ64JPp+skBF+gEHzFISCn0+3/alFugSRD5dWZxQOWzpjiHrWtQRme9xOoKDceRWp2x1DdAw2JHqGIfff/FeXyF+U2erC22afqZ72H/2qxpv3679GCFeUy519OjQi2ZPijO0mPBT3HXaG7jRblWlj/aFFR7pO+0zJ9R7+WrJmW1HV9WkA2JxEsK8rNqc3DNFaMV2PY7MzFqtvG8xZuDR1TRbo/qp3d8Pa/5Vasun2UlH/JbvfuAaPO/xA1rzBqrwBj/0c3PiTfdcuVqtsve5zOOx+sLN7/rvGNOy1+z7epqttfpIGALwKdJWC4kS72DpeLFUVX3zV+8gR05qEN8vlf0wbT05ntVRplIt21WohySbFogFqvEunBk8jFAZx+g7FChrwIu9l8tjY5/8NGx9Om75Gv3lwy/Lhn4oWcjstNKKKgxuVw1ri8jCK+xqjmrs1D3q99l4SRRV19JsdMmL/o27O2wkDOnDICQB7UnQ9yH+Mov8cFeYMV7Y903bxWtmaFy6mDQz/Oof9SX702QUeHvDAFOao1JSfDLxEc0eASRf0G00IVsSgaPBcPSfRKgyFGq9Op9KQ+DPn9pRRgzIQaJqIiLeYqDhNRToMZe2KiAgg82YSJ7EgRU+WO/tKeNM2AyBk6WMZfPR0u9/5HsnDZ6LBTse+7QyBkDxaGjhFKx4S67v83Ep51hh3V363/Q7aoXr4SHSqfHmbVhKdTV76E57NwgROepzf1L3H3Y03xvI/p+R0rDz4vWMJzzOB6MzpmrvMZ3/Ne2JPhH18KkPB07MqX8MSgsVLCc3adV386tr0t2916+Jf2ZTaqbSbhiQPCma76FW7FhOe7l+FzHY7FKXZW+KPJoOqrtttYwvNDOB8yzKFi5YQnsvw0cqheR5893dvJlYtUATaU8LzDi9PlcMqxPrD9hOfOOS3HjXo/03vS1weqmXMLZlox4dmqK1/C06Or0AnPlI3RXy7H1vRJ9kj/trTWdp0ACU+mTRMg4dmiK1/CE0NF8ITnoWOhe581F/lntGk2svSrDwfyPOGJQ8CZ8MQgIKfTw/9qwjPqaO9PEf3XoCOj/MObhUycav2EZy8UmdaVLFRnh0RvUETX9X8JT/6E58E57erYNe6M7lp6ovn28rJDgiU8mfNPgALyKV05G6SuQpHRXW044YlHEVZIeB5NP9/vfKtZQXuj0t3OD1hR0ZYSnpjGBvFqTJe7GqPe3zEsUacy/fGuJktwj0CVPk6l8QCfMXj4+vUMxcmAzSEKtmtQv0HTXMzg9hi4atCvYt280/0nayMejT5mxQyu0JkybGhE8Q6Nbl1zJYM7fVr/hPW+3+Vbqo4Oel31RbhNZXDtJITFg69qi0nA/CFjhkc2n05kLvltNoO7M5wvnbjRuOp5bPOQ39K8Wlindl+/tIbVB6AdHHXCQM6cMgJAvr0rH+TrjaP8yX8yg8vMEJpkcJnLUpMMLjOYNsngMqeSSQaXqXLzM7hIRVHtoMOobGyfq42rNe5VXoAM7lMudZW5N1laosU5ydIm9zM2Hx8gpX1XhYO7uf4Hb29SnOh9BOsnyv0oJ+ImM7+YbK/E/P08d0Dbm3J/HN4RimHczIWJpSe+z/5br2UMfyHMcLPDSYL5TDE5FJ5xDYVfY7atKOlhh+7qVi5llS5oJSNVaPqHrn2nbLVPvxuicPoHOHRM/xA0R0P7BFSTrq3fNLnbpo9PytkX98uXPLSE51dCEqI0cXbmmcnFaKZ55lTnLBTZBY6ujjZV53PBDHGdXDTEZ7zGdLoWtN93S8ipDXucNoeZGOLP+1zrnB1QzXuturG4Tqv9A00McbuujXq1b+8sHVFh3fd/+gT1MDHEG6avTa+ddtZ7/dQmjg9Cr78xMcSdElq20M8rrNj055FxD5cVlGGigqTI99ex+epBbxSTrpZYF1Tqfh9MZE+KrjWbo5/+zEGeHN5+Q6okIQUTOZCidfcnLA3esk28udNAz5oGRTomciRFlx0/NpnrvUUx7bqz/OmZw18xUSFSpKow5VQJTze/1WvqhumXJhzFRE6kaNjYTu3XLtgj27EurMufVZd6YiJnUuS/t8+ju17rxCtDFEc6x8YswkSFSZEyYerTW2Nq+Sz9Hb2ltNe985ioCClyHuesuFuxl2RPuz+fBOuvjcJERUnRnIqurf+6IJKtKDW5luLzLDdM5EKKNrZ81uriCfvgLYWe9Ll60H81JipGiio/8j+p8fSTHFjbs076i24A3uIUhq1/jR/06Jt4aZdku7d9kFKYqAQpet9/xMJdk72Cth4PflD77DUnTFSSFKH2ES4VE2b4rmrd6J8hFWpUw0SlKE+8PWrHl1pV/HYOKNzQdVWL9pioNCl6Xvzh1EYlpvqv+Xwh6OKnsr8xURlSFPtx75RaG5cEJs+e+XDlkdSemKgsKWpzzXHlmMMh4tmbGq355+y77ZioHCn6W3Rj45plJfxH7Jn6bNatkQcxUXlSVPSK96sq78O8t7i/SCx1V4ZiogqkyOm19o0+cC26eWTfQsOiJYmYqCIp+vNs7/HvF7+Uzb76T8aYk6MDMFElUvQibGKfsct3+412m9270o8fbTBRZVI0HHmXf7Z2uvfm7kN2SFt9rIeJqpCiPtvfKF0KLPab6YeeWupRrwomqkqKxp/1WGXf55J449oWIZ+PX1BjIhEpMgyRKZXLyvtPf9znr+ZHF2dgomqk6Nuy/TVvnZskn1fy9ejHAUN3YiJXUtShTv8tlUO6BC+sJFqq6Pb9MitkAXYIfhy2Z8vP80LsFTPCPb9X3t3rTwFClhdchq10VNrmlCMnfFI33Bt0qtIQugV38Bmo02gjIUQgXFvONck7RCS9ELbOB6cLY5UaDWa6SFIDM9lAmGYN+mrstkGkwNwwHQvPl0Uew6kMIGcqb6HIpEjLOEGy6IaIF4H+thVz64g0K6f4LXr4f+x9B1wTWdf3oKgIKlbsGrFhQ1h7JxN6VcBeIwSIhiQmFBHUIIooNuxtrdgLdrG79r6ua9+1d11779/cKSEzc2dINhPIvt/j89t91jmZyeR/zj3n3HNPubX8o7rMXgG7DQk9+dEFRZYAgCKhIY3JKDI70qShH61CZZho4AOtI2URqli1SivHY/PY+8kV+GwYSk5EUmw7KAVzSCOgKGbWq3OlUZU7vttqHn6badOLPqGmpP572DkKeSTBgxsuuMTwwDUm0ipGVdiYO6qiGbnQIvPYhVfDxkqHykSY2wJOiQdLtTJCEXBMvVmXW2VsuN882+ilB2eNCmLE9cjHQkbIUxTBufeBFHZPaOFiBQkQdlZ+gYnA1ekh08TJsU9SZ+kyJpBQsHQzlpV5/uWb34Tzv3Q58zKI3iTBjnomGyw9xRJgTeIFCxN10v485zz7q11k6MzNZdFdSxUvO4y086X9KkcvsmObKFCmjI6LYduhEhwY77LR30pZIilIhYrAwMAeIIqSRsSpNJiyUSmj8VpbBf4FruQXkXStKEKqFA2WibTxarVCjnFosAojYvcTj4xXgltBua4SDAtT4OOS8YuuIkmMVBktw/nbN7i/SE0d1uGJSaroaIVBmyzsM6BVViwmBEbaRqZfzwsbSyaYHzCW4QiKvAcMrySBHUs+RZFLptlKI1vzVenj8FfLl6ND5p+6ODRo8LHRAhpLpgYy11jaochbgNAUqPbPRJEnphlLZ5o8kpO58T51BGDYR6GQNaiS9suQQf8Er9zee+b6JSJ7erifQyyo64IrCgyVW7yoXCocm2hwxGk46NiUCVot/aJEIIWsKb6K6dySaw31goubq5tolMjd1a0RlGXtly+JzejSISgnc5KyWLM+iYyEO/2DIAl3eTRLsO40L+t+s1Z3hi/PpibRlUJKNEYFc63lUUC9E1YAyp6vGXu71Pae6LUtK2OUbVpxej6BiR1QzGWKjYTQMvBTxmoSoGVMyoJsEA6MFYZIgoywiyYAE7172Po+E8aHTPfesvLe4Edd6ds08sHsbRpFsAQ4t3jBuRRpWiJkQ8JK5VlwU9DJXnk+pmXRFh7TqjZ/Vy/tHn1/XVKfwsPeouSRLIHQaV6EftP7bS+4/LaTC6SB39tV9hmzslaJp3WT6VlodngLwzDPQOMDByi9gyjpCWM7xCjsr5jflWTYZhNTtqS8At+LdN1GGuU4MaOe8Pdme9EUxViMu6LIRiWG8d/QDK5vKDJFaYFWo1tPtvB6v+aDV86yNjXjp59fak6HXoanNKN82Iz3T274jfEZNmf464Cm5npKvVBkvZIzDzcXRZYpoe1FuQxxFRwgSi5cIuUaIuUPbmwzqvv1TxIneS16uMB7c6Mt9OOZkp7UzexlmUfKD7ARGevbl197P2hj1MxfFo0+bPYRPgbYXF7AMIkqFCeKsBngMy0Qrj+vWE4VlTwGHUuK85JHq27s3adhsW3u6B7V9ED7TM3P8n5KTFNizPAartZgW3CDZxUXo2EuvRqZ5wAzWDuhs1aa/uB3322ha8pM3mL+7GqMtWN5WTuikFgL84+ndRG4nW3rj39kpV/IDshOyfGZV/loYOG1s7WXEDppEzQxCdv1YkuMNIwvuQwjerHyjYQ2Wz029B1QJbPHPvqvqQiSU+JA6NNTHhUl08gwKCDt/LnqBJpLVLEY5ESKDP6YyLzH4JtDYpg2CCyBoi+jLCLzsC//F2axA/opY0H3RJHAKAz0x9DSgoMo0jnK3AHc4kADUEC4QaWWaYC3ASosCBnXgpI4ajqChvSDtSAarUqURcKNyOXWXvO+Pt/tv2rwx7If1nU6TtcxPfCpymwdQ17PT8d0vPEttExgE6/x7qsH1g9Fm5irYwJRxB/AbIvCEvXH4zCbGxKub8B+fXQrQqXUyiLicfHAh77Dc+wfNDg/Pe1H8LwW6jqyRzmZjHIh/XPZ218aUXCVcJWErR8MNl0JCYCNVAmvuFTC6TJ137q3VgWlv3kZ4PrnaC96lkSoTK2QRsjwSjyILuBymJtR94EEXq1BQSch5InyuBiRCtumaIzXBMyzfZ73ZGdz0MgmNDStGMXZ0NRWgvyQmbv2nYBR01LloPoKWCgA131+zou0nRc862epjd52D+Po7jP+ILb7TFzObzkzcxkEaNRZHiC3DOoyLEYRuyhO99lI5KrrkdPQRA2IFhS+DbNljrKP+0KmN295+Josiz5RohQpIPAjHTpV8FWMoYVJEg9a72QF6mBRL8rK2K/Ll7EPnNxomQZSmGGu4nbCDSRgLPYIbFOdRLAaymWmYTJnkZjL17ISYhWASThsvtaWgFVgUiCsSjCOLV4nhks/KfrwemDVoLkns3P6SvY1aPDrzxa9xIyDCfCrIAcT+GVLQIGLOCcUmIiThuq11Wd4M7WlMBnef91u8OuUPg5+40WSVentOscLkOF9QcaX4X1KD/kbq4ecmVEnDOTPf/k2rGSpF95bL00st6Wlf3kBIBdH80HeLpqC/K1guZyOFOQFkMsJSb2kcjkhqZdULick9ZLK5YSkXlK5nJDUSyqXE5J6SeVyQlIvqVzO951XHB3Ye4L32KI7x8UkrdzMSnkDwguVPmbSpgApb++4+O8ccKTZjc323qtsIwdfflKWzv8KRLCf1kic7ZQX51htzt5yZSR+OEB1OldT7c9NmrfHTFTN9xVZ4MA+ZELXkSCg165CY9eHUKQZ2yvni11X148ZIDuaE+3MufOCtj5rUPRmfCfxqlFByzNOz80056yNoZCYx3jmKiRsXxhAmd1XLIU0CUU6ykyaklVJnxJhiBV8NnIbqauuzxvJhC6PvYrXqLBfwLSI1O7B70+sHO69RjXBNwNNOiQASs14UaolM61RQlP9WAF8seGYGQwX0OeecR+VFL0wYfalw928VrxfNzB9oOhyYZ7nXieFCH4gV1yCiGWmubGN9aeHACICnkhVLMh8wiwQTTfBJ4wFlQ28u/eO56qjDbaeDN+Ubg2nlhhIbXhBaiYz7Vy3Pmv4Qp7I4AeL3ArqZdmRS0qL3/uN7T3Cv9zz2oxcvMKYuIChU5cXnap6X/Q9l2G0womQzLIMC0yEXCjjmwiZbpqpM+6YNle8MMWuXkPPzRP7fP6z4il60qNwEyGZKk6A4vb5Mr5Rh9NMs3XGTIT85d66Y07VfgYuHZuwplVl/7sWmAgptEsQg0sND0wpJhq7/I/QmGfNhToREpcRzomQ6Xo99IFLD0kanmneLu1W4BLvpa/j2lWtyYxDx0rVIiJOA4mXc7nmDYn7qNMevC5FKlLKEsElmUYeQRpIo9QSsySM5w1hkXIDsrG4Yp7TniHH8ewciE9eRIIsGGKSoiqDH0MRwV3sdaC/suye259uHYnxmJcUeiKpwpvvdBcJfwDbRSIu57fmmNVx5q45BEV2AXjWQ9fcbBTJGWJSNklp4n1ImYCvuRkZ135W9vVPq3D84eDVQfRZE+TPZZ/+kdfz7apeZ7F32JzZQXNTY566Zev+FgCfFbz4YOJTGBkGdnjiRgIBREeE+YedNsKXi1s6XKqJlsXxMW1RvV06x78cArf5K78kqYPG0plG3M9mGnldcGWJcSWLlyvjrYorrw5QXDHJfDniCk8tiySVL5QxE2bM6nJmvUQy7tD2HouTPtMtWPEg/H42Y8jrgjOmjIRQJyDMyN6vOkuQtUNM25BV12OAbywU8vzw+Lz1y62RTX713zdnZNS9IrVu07NqJcQD2Fm1FMESiCzgRWTSEMquf+Sy65umB7zr26G9X/q773F2h6+/pfOY+Ebjk2E66ncYdAMuSoyRR8RgbiWoLZRqsZ2uQVYMaf6N23wwq7th78uWSeK6CXmi8iFknig7+wW72pdt1008Aa9BuhrA2MuVEYr4SFCWKyLeBPrDt2R1b1uyf0vx7Ar9kHdt+9IHjJfgcmz0hII2/r1QJBpg6AZNbZmLY2iSxuoYTEqUJyFRhoVaIB9IS8QHYuTRMeC/83xKUXIwx5Qihj2nixLxNWxRIq8LvpjfkYBVgQJWWgIAIxfzJ6s/uGJKkzEHVzaifIWUecwhwMlV+yF8J1e/6DH/zIV58E7vcyeRIxJdn6od5E/9y9F+apmgeEWcXK2QR+BlYcZ3Sq0ehPkDmHmKw+5UiGJpTzFKTzL7WfC9FosVDLoJDYk3K8iGxOzAzSHMoVVAOqRS9gTSIRV8E7NDKlcHVBsOupAdULl0U01vuQbTOfp2/nR+Qfkz5VCTcVrXzQHT7v15+uv5P+ktsIzrpMzsm3j9QuqL1E2NfLKmpdXKedRukQCdlHMUZCdlaILOCsVxRvdRPpBqhckiVPgUXeNRSkpcn9ZhczPf/Sunr5r4qclJOkooGyU0X5SaH2llt/ZQHb/0Vq27zt1SOVYAlBbwopSlYHWX5M12IbpCA8fICICYWe+F3ngal5hP0EDTZxwpUp9++Y/pU2YToALSpxWH8unTH0P+p09J/oQ/qvntfoIbuiXyupNf7JJoAfQps7mTAJqi/FA+TWE31NL6tHnDM3dqJmm8s/akbHwVP6WmAPqUGSQQAKUfQ/hQejfEgvqUaUMLXZ/iEsOpT3/o/dOvVr8nYC4nYZLZWtlUfT1Zovbc8d4jZtPFyaECbAku824Jzukh/yZYMltZCvICSGaDdM6jVD2kcx6VzAbpnEcls0E651HJbJDOeVQyG6RzHpXM5nznnz2l7T9L9tXa8XDII89bBsls7ie7jTvyZK//BvWzS+Edj58zaEwob4Q8za50yG/e7Us2zk3/iGHluYEPQQWT2alPgDy374KJhkMBisa/61kJaeBIwc3MFGDxxJaLJ8wWiQLw5AcXT+bn3u49/v4nv92523dvHnqHXh1YrKtUKVOwmwFzqUMXsUgN7iDbwoAuryKlKk5GtCQCw5uI8TrwIB+zxyPkVYzRkQ5hERqVQhEK7By4mFco+qoLQ3/GZJZufKXNE+/9txNbKlfN5yybteuulWnCsdenvra+pyp+sAJkeGHvg7cLipTHkb8d80vA2chd3UoGS4pxqd1BYqSzHFO77SSIbrzEPkiqiZYrA2VRNLPpQFwOlUfH0K6XJK6Hq9SGV+m62zNFLl7fSX7cEQexqwZUG8bJibcqQb0VbEFppIl+ykjQrIuC16YkuAgObAwu4R4+SKvRXyoVBnpRSBUS0EHKwHzhbf31f7ftqZGq9feQovrT6o05s+OoQAE+pvwLYM1j5XzWXCanrDnYM1k35sxWrtYbVI3gLQfoqy8HsOHC3Kp77EN69FJmEtKjlzKTkB69lJmE9OilPKgbNTzDd8Q7SZbJF2bW8+qwx/ge+8zuvgJY0CJc7CoZNidhZfwQz5znn2RtRGve0DvfkWeCQdi/NJg+NL5hYDXqNFEpClHLlD6BoljyGcadFTK7GPO+FrshH+MDxso/tll7qAYHORIEOc/atNlIkC1q1ukhXwZFTUJ+qcaUoLtAPOjgGSNVYpYM+sMfzmokXb05JWjuo2vOpTfnPqKfFXoST2CfFVIE4YfLoMh9AMlqrpyK6+pCyakoFoFBq9cMM2fO/GlKH0ARnTGg9VS8QqrBjyAVwEeBz0AbNtzl0LW6IRt7yi9WSJ9BP5ixCyMfAumvSlEswZ3zvNw5Zg3cwbTRT1MSj2p7xcq1eEfjCBqbKBUCZc7Bve1X31pyxydVnGTffnEZ+tRDO+KJkPhuHsUSzNnLy5wt1sAcwB9D5hTNhzltxLHgK3GeYK+jxW6VKSOSiH6MnUQqtXQYaN/ojv8t7xPwFfUmpk73kmeO+6z4svhPdKB9ZXqJe7jB89kl7jSqJZi3mpd5iwqHeUb02LTNh4Od8jiojZErk5SYp4uxD2OXUqUErMP+S6FKxIngr26AFCsdTlyAh/DrNvn29OFtdPvv9xNzAh7PZDRKi4FlTJOXLcG5mbycm1jonAM3gcMWk7JoyhOharkyml8RHs3tfeaL4oHPtvphVxfVVo+iK0JOnymPIjhHSksIHwJsK06w3Ko6uFtF+qlFufzUqrbJYYf2vAs5YJfzoEHr5Kb0QzxiJo+oq0aWIJcl0t1UgClX0ltDMWhIpDWI+OC9ZaNlqlhZnCZJpCYeqHX0IxK9/JShMiW5SeF2XplzNvjelX3gSKeX6YH9S63SxBFjCqlPGY39RBRxGXYcT9uCHEQWlSDlh3EmxEG3vD4UNnhNJf6ORnn0JzdGvWhRqZl3eu8bPT2PVTzDGK1NPhUyWpui5FtkOeTRqv6ibPGqt559Wm5eZfaghiko0gAg5wHVI/tRpMYwk3LgK4UbuDAiVYJMo5FzjLPY+fpDjvjBFHFarx9D4qPVZ81fwgysmDpCAKzK82JlN6xAdS4VrCxBbrnAh4Czc2PJjZ92MtLjoy6ibujPYrhtY1pVO2pjQH0U/H8pQ7eHfod+u23Lpcb+15//X/XnZ44nKrD+/EnD+Prz92brTgH682d+vHJ5drpr4PKSNxffyQii50mbWYgusI60Q5HEYXztzGPZOtIS/fl7fQlST9s90idLOrJdrRZn3hd6f/4IXlR6F6w25N07mFYTJFx//g917z+yS2osSUtYePJbkJo+sqkw+/OH8LLOq3BYV+D9+VuVq9/865a4gOlV65SVPtq+uJD78+NahrPBOqZlCqw///N5GbWe9X/qlf6rrOrbVVGvraA/fwQvOL2HFWB//u72E86drtw4JD1xRu8eAYs8rKHTBYZQCC9C2Jom/bZiXH6bl7hxk5+dLopX36y15sKily3oLQbw+j61SoFZdLbPZseBc6u8IxJ53v1kmwwMcY0qPjoG8+G0MjxUY0qbB+bIRs63ZTdEMCAai+/Bg8ifGgxfqQQEXZj4NpQgazTm1lxVzHst7CqJBfSnR4xRnt1Vaq/3+FXDY+yXD6L3OvpXY70YLtRTr/cN0PRGgbnO/uN6Nb7qaa4LpTuI/AHQqy2BSeccFDmuMcmFKkUs30hZtEYG9y8XDgsNj5gbL97/81j38+Xn0qvti3viN0KKp4jrgq9O7Pfv4/39WzWF7SzpJdMERwm8slwVKY/gaXvj5N1BE3tvvteK6XYnRhfpyJBV6gFsWdVTLMGMNbzMWFw4zGC6P4gpJxauAUpVHGa+pBEgduri1gnbsmI7i9imIvdOETEqTWRT0S+dtMM0cfhf4N7qlCovzq4u9cJ/d9lO63dnPqhOt2vgC8LikhSQ0Zh5JEswaxYvszKtYuWAR5nkrVbKC3Qr4zWDtTwr6K+KXya1aVjff/+l15nvbBkVJyZulc1lRwsJochBFeh5Fju8JesOa0zzUklNzuNtdbu389mWQauCZuwSe2lCbU8X7rYXA2AnBcBVCABAtZjkiVKmjLv/hPTw+84Tutz33H5maNcbNr8kFG4dMAbAQj4AekzRUI5m8f9YPg5z0neB5eOEavnycWppLZ2PM/6yTemaIU4BG5uE1q96unOCFeTjdNXynW56a60gqWDEiBEFkI8TgbR80eDi45A56Rs/zW1Ux88q8nE68nLnF2vgToHk40x+18xhWpkm6NjdvezSPjRYYBX5OC68zKllDcxBCjMfZ9sQR7+9d0eFzMiWbHs8P72YVeXjVORlnn3hMM8683FmzxnRoOGMMM/JZ4Z+6Pek7qdCzsdBeDn3wSq2KRbLx9l5aPnNVxPC0W2pgcOjKrRPtop8HNyH4MzHwRQh6aeW+L+Qj5NxznVl8SGXxBvWtO/68cSf8kLOx5mp5cvHGcV2aS2Sj1NlzbTUoGG3Ahf22VGx0smakYLn4zD35gLkmEzX8uWYZGgtlY/TNvTELmlXW3Fqq9XrbosmaQXPx2HqCAGwGsWLVVzBWsvCzsex41Jjww7Im8iD10p27g9RPLrf9yX9pKRbPCiQ9NFI1THsMlITji/qecq1alAipj/NSWpGlJKKpKCdXjT4BqjkaVO8pdJlVf2yHg053/bY4gOc78c+yTEksuSvZBimwkIM660gUsksbjJSKvVPg+TTvAIlfU4S8A9dKssNRNBhL+XHS4fJFBjDZJF+mF4fTj0OZyvBypJcrFySNTn+H/9PPrOHOWnnT2zanx4L8gZJA3FsS8TpVhM3iLSYtiNGAMZrganHx1fFqBSRoEMdSIWKwj+HuwFx0mitUbqXWRpWPFAVMVQWqb8J9ursMBZx3ViV4IIin0FtXxFoMlNxCXItGtKRBkAE/FdIRxrwD7MjTfC4m53Djj/zGHt6m87udchFZkeatJ5LR19X9/Ode3DJvIdzJ3Wm6FSl3b/uWMP8YkjHGi5OO4DSaJKNUG49Xn64/OSLL9AZRxTz9u4a7GUOt4R35txQ5CPg60Koql+JIs+jC2UWnwMYeTdQi/0GZXSe2cv7O77lSHZrHzoS0jiHi1flvfNWG2YI4uI1cIM99Mm0N7t/lgwaq3rf3Ft68h0vy0pIiCdB2r+SBEsw7R4v064VLNOoPZFtoIRQqOCW0fp1j/OGWqNcRs7Zk5wGLFdqZRo82wj7CprChPJqbdq5UvUv9QueejC32vV5PTczeVUiKD5OOlihr85HGEF+8K1u7Oppt3zbH/1L88bH1N95mXo0mtX+iLenPCnsMqL5BBQ8Zg8IXkG3BZqOPbkAvyq4iJeXEHrpoBg2/LsWbm9Ik27PZdK73bsVUkJxzmfxrv1FRu+oQ5+bYx8WI4+KE4FRm3SzDuwV15jf6iFRUcAFkyoU5ERKOZglBvoZu0IBZs5g43oFSPm+sUgtQZGbYOpmOAqzzHdRZL/ZE7tL4wNJsbWpBS8M/aFZj3dsP1/NM2T5uAf+b2IudWLOvID+xHw3Nsw51OausWwU+RtgNVcMW2M7UeQCe04vb7YMwUEVLhVQXNK7Ov7+qCfis62Fa9vIMz2uskJpUcYBY+56wn75Cd5fjkmJFYTRTM2TcQBNVPj66kjjS4+TnzruN7X+4yoNhpT9iy6X4O6Cgn8bL/xrCwd+VmaMubOLiRUBsjyxXwLPgGUMIf2XmsJcjnwhVcFBD5iBQSRgQZAGxoHLwPQ4mfNiSoOa3lO0L4od+9iUbi5LE/1+RESkz/iGpfWJG8DGPkKlALtZkLMIRiCDBSHS4k81bqM4dU16n9FLD3mkNxsoXuXVYQHP+7EH49DIxqKagSLtQK3mfKgxuowiVdXmbxPVu9q7eo3b452mqFHugdThXH6NSwXbJhrR2JSLqxXxgATeYgakMhBchDenP5T+s9sLD5+sp0WrVSh6hn6IZusDS7slruZnTJPa7cteERUiGbMw5WmrR/cmmWtMJ6FIG8DrE1CdtgJFmllFpTSC0PYhlJBAdBoX7yr7Gaw8sDGR47x0gwd74y7XPf28ls9Y74TgL54PHvLvP+zIVfavdiCtP/6RlX4hOyA7JcdnXuWjgQIwtC4vQ7HFy7GjMw9Jd3gNSZvfD2x76uG7682RMunRXvuMQ9KdjaR7vkgiZ8qtODikbcjW5qO+29ir9wmApCMvksXUrL2cic3DHAnFjFlaHl3CLNjLZzNMQMhWL2Eubo2Et8AvSP0B3+IVlQBxIy1wqf+qBR6am9y58+qX/ruO3/+YPP/U2QKxwJ4aPgtcT/M/C8xvgQ+/qfrH+fGfAndt/f2jZ9GyadZsgVENn5ppaxW5EQhSoBZ4ddtxWTk3n3ulhn45vaxs8gcLWmBmmaMADHXlZSi2eAvQAj/9/UbA+YTHkozkIY5fjtaJtKAFHjkkesDgzAPe28PnrstcJT4pAJLVeJEsqykQC8ys97I2C4zrD04LXE+fcV6aywJfn+A87W+XAK+5F3M/ra3r5USPcHaNVyiIwb/ss1M8yCohpp+HKBVJetGA1tziT5KS88DxabEJUo1cFpcENDqV4WNcNnpqcNEtXz6X9k2dLO/1S9xfh7lemV07nkczFuKKKHIfVI86SGAJO8dQ5JxpTSAqdqUA0MqkmogYUZRGBZc8ZVOXCzZua4PWeM7ofmlde/pwTRNLsC2s9mqgyF3u/i8pKHKV3QfCxBC2QaJTDKb11Bgj4QHD/hMm77nYdFbAuvR+Pzsd3nZJ8MSmA7pPVSTXPAO2vHx1xa7S0SkCgHeOF7wjw0ybt1edEDHM5e3r018UQSxQIHF9u/aHQsbU3XQnl1zhHEuKQRZcxd0kRSsFho6ujASIlkllVW6ecgIBfUMaDBY8lQN0t1FrVEOo/QKYaY0hCIXsWEf3nNXrwrxnOxwa8Vy0pRtdyqivYEuZnmIJoM7xAnVEX+ZehssWZF7cU85+T/WQ1OgvjeKntStNV6z6GfCQsaK2HGg7ew2P00gjiBYC+tn0WqDzyU5Fxql8v4lTtkpm1ZDs1RZvlnTNtwHXm7FVfh7NWCTHoMhbJZmxzFb511HkhtISfX+aBy8a4fblg8eM8kuvqtffPyVg3x+hA03pKPIaIPRKjECm22TjCJmkskiIMFA0cYSIQCH6eOBk+PQlxT0m9vi8pGqThVGMwzhwNySvHb8s+Hp7Q2JwHuqgFpcgj5SmKSZHAgP9IoEi4BX8eY3D2IPiZQ+ez2mpqDyRhkBRTNZZvx+/aIlff4P31/+ppLSNI5e2edYjONC2+WfJrOVnvJeG+PVhHiQpId00uPRMHf34YjDJIa/XWKLKpM4ZW+5dkZ5sNVsywcF/7PNTlZaxX4nt2oOrxsI2CEXuqTDYzkBVyzsUOasySbWUBV+e77JZntrvsvTKS5/lvYqJo4L/HEzPIsXXB4d1pxHz0zLR3UvErLiw32N6SGdVzb6DAszVMjEocgeA1RXqGGHa+YoKmvHNmVCDg8W/vh4ui532rd1ujxk9Ex0z59jdohf6620Ju9A/j5QfTPc3Vk7cX2K/x7Tex8Y5dnT8RwCYzvLCdFhlmjIuRQiVLDqWq06MGW43dpkIr4cwTYPLyCaoJSonAdCQeqjs/6EdcPl5Px9+qpXjO1fUPE3tfviWhXfAv6r4dsDjTdNZxu+A7+pWqWoHu/mujfxybHYb+1cC7oCZnoQAm7gFKr5NXBZbV1lqB3xbfbNbDd0xdE+R7IyOlx1O/xd2wON5wRtpogYzeQfMNF1WtgPGRYtzY5elKowdcNuocd49Hl/wOfCyg2fazfsVrWIHPJ4XqJF6W1Du/5AtmFZyo8POtAtek1p+/ydkSN+vFrYFKK8taGopW5DhHvPsza0L/rntdn558cZ3oYC2gLmnEkCdefCqs9YFZwu2nnuluba8qe/kSJ/fapX0/eO/YAua8oLnbGlbwPTPrcwWePCquNaFYgsGT5neRTHpumfWno2xkohIF6uwBU15gXLW24LyXLagzPfg4/dGNwuc9Gujfj00XyvQ94LBQHmCg3Pjqw8ahgPRkBL1hPrh36BQSgT6JysTpAp5pDwuCT59aqbs8m/fjwVtDXna3WHwwXYcb8PemepJxmIXiCLhsRh2t6EZKFtQpGWsSUq+FPhyvBG8jCOl+OSXFR7vuvUPyth54Xfl6+KM/ST0ZxFX8zuVnrsuYMwW59uo7k2JylvQW3PN1U7hKBIay3ngOgaHxiTtVBF00xbJowhxkGtFgFvwE4d5FTr1/ccjJOfKXxc7/fjrMqNhNmCyt0IaDYmAG9AEX2enSEDUUHVdVIL4xpqmkCozAfEjlgW8ifioJiffVvwknvhzv/PBgUXj6aqavJMDFgbZEsh05kWGKSpF8kGmkRivA4uXKkSReVSqGRMx7BKEAjmOFyp3jn/V1PZ10KaSXrVfLf7Dlh4ENPg+dhDQkGgJnBrz4iSKpTR1BS5N3XFk09PbxLGBK/dNb7XPpdsehpcDAsPBKkiZWFEOqOt1lWlARbCIrK4QKWXRROthl+CQcBH237JG8HqxC4dbB89r5uc7JWPHiU0RO0vA3wTib5EUY1GbhiLpALVJGGq3WagdQpHhpuno0ij5S/FSHOhPOzfNKzl31tTgrU3Rb2uz62+k/TQbMTtpSJyv88jUaeaq55koMhag4iYGKpqJymIcFZPUcxlMScg0WhlYZcnikVBc/ijxTTlg0h2PaYqUdyOL15TSE4KILkHsenDyuuDL6ToJwScoBJ9xCMjlVPG/mpQ7sGfV4wcPrQna5lixqF3rou143k+gpNw4FLkCUM2FukQPUWRn7P+ScvmTck/VWGWb9ttKz/2/L11U1CHTXrCkXOb6M1eJYFuGS7FkeyxoHffpWCtNyjUx/9GkpNweZd8t6repuP/eo0fHS5RbJgqZlGuuzsM49hsvx7DVWYBZtwPKd7ziecZJMn/Uq2Nq2alWFsy6/Zqxt0tt74le27IyRtmmFT8sgOxv4EVyeWyBZN1mVtV4nJyyJmTB1wnH6v7zNtWqsm5/kAoCvgl0kABxI01sJS4TK4quuyNj8gR0xuH1gfM+76J3BSwWKlNIk+im1USUK4hFiXKNTKQBTyI3B1CkmTtkyIuwh83nq5PdT3Ybd+TJXv8N6meXwjseP2euXG7E5JGSSx1LLi+jyCcFBbmT1UM+o3zYjPdPbviN8Rk2Z/jrgKbCQM5cMgJA/oMX8g96Ka/MBbl7dujRvjlrvFdnO54+NOr9bPov9dGo4tV0yEtRkKMqw+Zk+CWiRzS4RLV+g3GhllgUDZ6LuyQaqVYbo1KrZRqSH9oifp4UYMyAGkaiPC3mLg4jUUaD6XtipKIIPNiEkWxJEpPldn6eA2mcAZ4zfKJS44RNNbv2Dv61hmhpSL+vlyEQsoWFwWOE4jHBrir/jYBny3s3xzidb+W9YtWAGRtDfcUWDXjuGcoX8FwwVOCA52DtHPm1LveCDtR/l5MRW7moYAHPxj6ZJb4tnOS/88jp8VN/uNcTIOC5ayhfwBODxkIBz4oXN2b23uHk+6vD8DLb+r/YYzUBTxwQznBVzlALBjxbZIvrOPxtE7xeNeLXXpsdx1pZwHMFLzJMUbFwwFM3all9+egpPqvaOzRK+RT6yooCnlm8OI0fShnWqtYf8LSb3OW38RU+hujSr/XvOr1zDwsGPJ8P5Qt43jJNRxsR8FTbbBrw+c2YkDnlH3Y7cblUhgABT6ZOEyDg+WwoX8Dzlonq2ZiAZ48lJzKbR/n6pp1cq5y1JPNloQc8cQg4A5639Mup2n814Jka8Jtz8OTUgH1fHW6PHPjxmuUDnoNQRKwgE9XZLtErFKmj+F/Akz/gWXXN01o3T+b6rvX9sHyQk0NXwQKezPUnQAJ5FwXngNSVKNJKYcUBT9yLsEDA00npeHRGTg2ffXEPnMJVZedYU8AT41gTXo7VKViOUe9vF56klhn+eGeDLbhrgEyjlClcwWe0rj6+A8PwZsDGNAq2dW/u3roAI7ib6y069Ee/Nh7L7rS7u1F2V27BCK7QkTJMNCrzikZpRYFEcMv477xYLHJ94Iy6zdZMa5Nz0aoiuLYSQuPBd7VlJWD9kD5DdasPJzK3/FYbwZUO5Qsn9ta7aTWsHvLmR1rZrT1Uxy+9Veuuc7dUjhUGcuaSEQDySAUf5P30Ul7zPxnBZUYIDSK4zG2pQQSX6UwbRHCZS8kggstkufERXHkj5Gl2pUN+825fsnFu+keMABHcWlzscro72bN8+98lS1vdO5BzItGT9l01Du3k/h98wEk5YvoRhEu8D7MnbjP6y8khS0wUeO+BiQ7vDVDmMNWc8YCxeMb/6X9rw/TOMHN1j0WRTkChLkOBHSMFozaXYPwYtyW7gqstuqNflfkr1UEr6DOw/Gh/6KJgn68oMG6HMJ/xCQ52Mz4FD0/Q/kBZ+mXZ3gY3f58UOLfCy7GP/Edt5/up7HFfDHp+OpvZoNFInc3J1WkoEg16Kk405KpIMO3cuAC1s+ZOy4sxu3T+S9/M/eNJ0vh6Btq54qjr49yn7gjITYkYlbr73V8G2rn36QOdt/x5InCZZ8rG35EvrQ20c7sLcVuCOt3wmy7dvGnLmKxOBtrZ9px4oHLZz6Dp9qWTx+xKHoeRipEknx/H58lHvAqZdLX82qCK94ZgpOIk6Vqb2ZqspyUCM/uErl8oiZ+PkUqQpLX3JiwN3rRFnNNzuFsDbcg+jGRHknIlaMeqElXIxs8DSm3I3bAbI5UkSZEqSbvj32/4rb6T82xZ7B7whvYkae+Ruu97LSopmR4X4rlsqW4GRnIgSR0eRi94WX5sQMacVJugFR+6Y6RSJOmf8e89pq1uh+7qUErm+bxPF4xUmiRNvbfdRtMyIiR7v+t0x/b1l2CkMiQpafIp3YzZvkGzE70+JU7quhgjOZKkH2nvz6oevvGb1OXxmvFTWoowUlmSdN9/C/ropTR495PPoYknPtXBSOVIUv1j637z7z4hZM3iLYcPlZvaHyOVJ0lPcja+aFlliv+Wt/HNExM8vmCkCtQbbo2Y0NB1p+eM9Ed/1z1XaytGqkiSji8rM6jRsC4hqXG2fzz7ZS74yZVI0rNyD6a2KD/Vb/XHP4Mufqj8EyM5kaSdH/v0rZVWJPhX/x7PioS9uYCRKpMkda7N7Z7Vh/mkDVqA3ol9UAsjVSFJpwZ9dPh6qp14vneLO+Ui6ydjpKokaVeDpXcvvD8fsCy8yIFHj+8Ox0jVKLHp97tdWmy2JMOvumrpzVhwzludJG0/9nhEYMc3nmkT7w597pL5AiPVIElbam1f4Dr3uyR34+WGjrm/vMNINUmSeEdjhx6V7vuu7j+i2KGJZZwxUi2S1O9Ccr30J5W8p9tvKn38ea9vGKk2Jdj13RqPfjInWBeRsUn2MqsxRhKRpIj+SlWa6wqfCTGSrRNWzO2FkeqQpLP9zt4KXf5Bsq3qfqfqgyePwEjOJMn/XMijxW/HSjJrODpdjF/RiuXHAD0ET7b/+aVRer26vvtiX2tVy4YlCuDH1OFSbJWiduXMP3rSa+H6uyNO10hZQh/Y4zVcrVBFQrqDcJ1DNyDvEJE9h7DNPyg5jJUqFJjqIjsdGNkihKnWoK/GniVEEoz13TGfHY0/jvc3gBRaguqmeNMaheT1ICJeBO4N+afGxlRf7rtsnkvVKc120KedmNeCSOhxkC4o4gEAioTGOSajSOt4kyaBtAqVYaKBT7mOlEWoYtUqrRwP2GPvJ1fgA2MoORFJsT2iFAwnjYCi2HvUma6eOxcEb/ac5Hxa8xe9iUxJ/fewExfySIJHPFxwieGByzneKuZX2Jg7v6IZudAi89iFl8jGSofKRJjbAo6OB0u1MkIRwHss+bbfJO06MmSOrO3HacnnHjGCfeRjIXPlKYrg3PtACrsntJqxggQIOyvpwETg6vSQaeLk2CepA3YZE0goWOs/u84s936SZHH8lhZzB7XYSweLeiYbLD3FEmA15QULE3XS/jhzHgjWLjJ05uay6K6lipcdRtr50n6VoxfZxk0UKFNGx8Ww7VAJDox32ehvpSyRFORHRWBgYA8QRUkj4lQaTNmolNF4Aa4C/wJX8otIulYUIVWKBstE2ni1WiHHODRYhRGx+4lHxivBraCGVwkmiCnwGcr4RVeRJEaqjJbh/O0b3F+kpk7w8GwlVXS0wqB3FvYZ0D8rFhMCI20j06/nhY0lE8wPGMtwBEVmAYZXksDOKp+iSLxpttLIfn3XYv8Zd6T/1qAFh0NbujTtGi6gsWRqIHONpR2KzAAITYFq/0wUmWCasXSmySM5rhtvXkcAhn0UCtnNzud8WyVdDpn7cFZS39a73tLPADjEgrouuKLAUBnNi0p84dhEg3NPw+nHpozVaukXJQJ5ZU3xVUznllxrqBdc3FzdRKNE7q5ujaAsWzI8Zd4B6eCgma9djm3uNeszIwtP/yBIFl4ezRKsG8rLOqm1ujN8yTc1iVYVUqJbKhh2LY8C6p2wAlD2/PNy9cKNNT8E7wjv3qbd4XTGpsy0tijmMsVGQmgZ+NFjNQnQMialRjYIB8YKQyRBRthFE4CxCXKJGHteHDLBt6ra4+4dBX2bRj6YvU2jCJYAZzQvOPHxpmVHNiSsVJ4FNwWdy3EZCy6HjvHY9ueRrlMeXzlI36Lo83rYW5Q8kiUQGsqLkFTvt9Xl8ttOLpAGfm9X2WfMylolntZN3k/3RvG+hmGegcYHDlB6W1HSE8Z2iFHYXzG/K8mw9yambEl5Bb4X6bqNNMpxYkY94e/N9qIpirEYd0WR4NEYxn9D07q+oYjraAv0H+14dv6CgAp7xduf129epYaPuzlte5kJldORu14pHYImHurUvC06qI+5nlIvFAkczZmcm4si6Ghoz1EuQ1wFB4iSC5dIuYbIA4Qb2xOL1ntN6DPe99e17Z416/hrKfqy9KRuZi/LPFJ+gJ32POd65/whn8zgiedsJp2rKABgbXkBwySqUJwowmaAz7RAuP68YjlVVEYZdFYpzkserbr+Su59ybzpQbr7mWgrmwX3y/spMU2JMcNruFqDbcENnlVcjIa59GpkngPMYK3j7Y6vf3sYIp41ovGtDil/9ROAtfV4WVutkFgL84+ndRG4x+0xpWp11tlUjx0tlAvb/qiYXXg9bu0lhE7aBM1Wwna92BIjDWM9LsOIXqx8I6HNVo8NfQdUyeyxL5D2ayqCjJU4EPr0lEdFyTQyDApIj3+u4oHmElUsBjmRN4M/JjLvMfjmkJiwDQJLoBLMKIvIPOzL/4VZ7IB+yljQPVHknwQM9MfQeoODKHIzwdyp3OJAA1BAuEGllmmAtwHKLggZ14I6OWpkgob0g7UgGq1KlEXCjUj3vlXfDrlU1XN28uBYee1Gf9N1TA981DJbx5DX881Rull9oO8udy9d58MdxzSst81cHROIIk8BzLYoLHt/PA6zuSHh+gbs10e3IlRKrSwiHhcPfBI8PItx0r39gb9PC1oy6n7847vfzzNqiPTPZW9/aUTBVcJVErZ+MNh0JSQANlIl1OdSCafL1H3r3loVlP7mZYDrn6O96EUFoTK1Qhohw8vzILqAy2FuRt0Hsnq1BlWehJAnyuNiRCpsm6IxXhMwz/Z53pNd/EAjm9DldFsCZ5dTWwmyyOy17wSMmpaqEdWXxUIBuL5x0/XJJzb7zHtyPErT+O0NuvuMP4jtPhOX81vOzFwGAbp3bkkgk5LYLsNiFFmdwOk+G4lcdT1yGpqoAdGCwmcf+ankiwW/itPrvOx/onirsjT4SpECAj/SoVMFX8UYWot40ZqZUKAOFvWirDT+unxp/MDJjZZpINUa5ipuJ9xAAsZij8A21UkEq+GammGYzFkk5vK1rIRYBWA8DpuvtSVgFZgUCKsSjGOLF4/h0k+KPrxIeKTyVEj2+hH+M2olX/qrU+vljIMJ8KsgBxP4ZUtAsYgXipl6Q9XA6tO+mdpSmLRvWbUpp8u7ufiuWt0kXLM0/pgAad+aBL607yF6yBtaPeTMjDphIA99tufLtayfIXu2NyuxrUenSwJA/nciH+QXEynIXQTL5XSkIC+AXE5I6iWVywlJvaRyOSGpl1QuJyT1ksrlhKReUrmckNRLKpcTknpJ5XLuvNTg3HDvqeKFEeH3a8zutZuV8gaEFyp9zKRNAVLeGnHx3zngSLMbm+29V9lGDr78pCyd/xWIYD+tuzjbKS/OsdqcveXKSPxwgGp/rqZ6ops0hI+ZqJrvK7LAgX3IhFYkz8H5wFVo7PoQipw17Zi/un72ANnmnOhxzp0XpHJc2gy9XjVoY/OZoZ7dEgabc9bGUEjMYzxzFRK2L3wWT5rdVyyFNAlTV+wDfz6sKulTIgyxgqI0P37Z8MbdOwTM2C1vFCZvvUTAtIjU7sHvT6wc7r1GNcE3A006JABKZ3lR2h9vWveEpvpZA/hiwzEzmDigzz3jPirR1OwkLbrI1jf1Y+2AnKgBOYV5nnudFCL4gRyYvGXieW5j/ekhgIiAJ1IVCzKfMAtE001QcBZ8+TEweXLJwL21GzQfsyYyxBpOLTGQrvCCdNbEc936rIkMeSKDHyxyKyjt14wNPWWDxeNnvT+wuc7g4YU/hgFD5zAvOrv0Z7qNuQyjFY6JZJZlWGBMZMcEvjGRDdgBKPOPaWt+qerqu/16wMoVNR5dHPOMvr0RbkwkU8UJUPHePoFv/qEbPObEBZYxYyLb+b/f+/Pea3SGzcrAiTvf0AdWCDMmUmiXIAaXGh6YakAi7eYdoTHPmgt1TCQuI5xjIhvo98RNuPSQpOGZ5u3SbgUu8V76Oq5d1ZrMOHSsVC0i4jSQeDmXa96QuI867cHrUqQipSwRXJJp5BGkgTRKLTFLwnjeEBYpNyAbiyvmOfVNPo5n50B88iISpEOySYqqDH4MRQR3sdeB/sqmN8YfO3rjUWDOePRtxvPGs+guEv4AtotEXM5vzTGr48xdcwiK9AbwrIeuudkoEpJsUjZJaeJ9SJmAopOzVjak+UeNX0b0X2f/iQ9/ymizgd/PPv0jr+eHz6F9948/PTXOX7cmrEvDoMEvBMDHixcfTHwKI8PADk/cSCCA6Igw/7DTRvhycUuHSzXRsjg+pu2zv/tx9p3KwTu6fqheJzSV3uq0OHE/m2nkdcGVJcYVd16uNLQqrrw6QHHFJPPliCs8tSySVL5QxqS1H+jVzOZo4O457TrVe+Q/ks6YIPx+NmPI64IzpoyEUCcgzMjerzpLEP9k0zZk1fUY4BsLhTw/PFLfZM16Vv0+On1H2N3Jf9+LoGfVSogHsLNqKYIlEOnAi0jTZMquN+Wy65umB7zr26G9X/q773F2h68zihKIbzQ+GaajfodBN+CixBh5RAzmVoLaQqkW2+kaZMWQ5t+4zQezuhv2vmyZJK6bkCdaMpnME2Vnv2BXv44w9wS8BulqAGMvV0Yo4iNBWa6IeBPoDy/+64aRv54MD9mDdI44OHh3NF34uBwbPaGgjX8vFCkBMHSDprbMxTE0SWN1DCYlypOQKMNCLZAPpCXiAzHy6Bjw33k+pSg5GN7Jk2nP6aJEfA1blMjrgi/mdyRgVaCAlZYAwMjF3MzqD66Y0mTMwZWNKF8hZR5zCHBydX0E38nVBT3mrlyYB+/0PncSOSLR9anaQf7Uvxy94UpQvCJOrlbII/CyMOPbp1YPwvwBzDzFYXcqRLG0pxilJ5n9LPhei90Hhk43oUtxt5Fkl2J24OYQ5tCOhLRNpewJpG0q+CZm21Sutqg2HHQh26Jy6aaa3nINpnP0Pf7p/IL3929VTfRm9oSAde0yi6Yd9ej3L9orM5sp9nly5ZZv47F+2eGr/I8HLqwkQHvlkJFke2Vogo7XyOOMlqR8INUKk0Wo8NG6xqPUyS3JPW7VOo/Jl2rk/NO3yH06SigbJTRflNoPexG8uHGs74RZLl8GDas2SQCUOvCi5D6S1XKSN9uFaBUNHCMjAGJmvRd6N2pcYj5BA02fcaRIfdr8P6ZPmU2ACkif7kzm06dLk/+nT0n+LJ64+1J21b9990zwfB+V0numAPqU2dxJAE2xPZlPU6xLtrQ+vbHj+59ZK68HrOvZceq19s92CqBPmUECAVBayovSnGQL6lOmDS10fYpLDKc+Xarf4LtZ/Z6AuZyESWZrZVP19WSJ2nPHe4+YTRcnhwqwJUhI5tsSKPWQuwuWzFaWgrwAktkgnfMoVQ/pnEcls0E651HJbJDOeVQyG6RzHpXMBumcRyWzOd/5Z09p+8+SfbV2PBzyyPOWQTKbx80pSy6PbOSd/f2b9vEvmgMGjQn9A2PnfR0S5btn9J0aDV33XWPluYEPwQ+OGJ36BMhz+0Uw0XAoQNH4dz0rIQ0cKbiZmQIsnthy8YTZIlEAnrTg4sn83Nu9x9//5Lc7d/vuzUPv0KsDi3WVKmUKdn9gLnXoIhapwR1kWxjQ6VWkVMXJiJZEYKITMXMHHuRj9niEvIoxOtIhLEKjUihCgZ0DF/MKRV91YejPoyu3DQ199817USPxEt2dtbW49Kddd61ME469PvW19T1V8YMVIMMLex+8XVCkPI787ZhfAs5G7upWMlhSjEvtqsXI30mY2m0nQXTjJfZBUk20XBkoi6KZTQficqg8OoZ2vSRxPVylNrxK192+GVrxsL+SjjviIHbVgGrDODnxViWot4ItKI000U8ZCZp1UfDalAQXwYGNwSXcwwdpNfpLpcJALwqpQgI6SBmYL7zXv/7vtj01UrX+HlJUW1q9MWd2HBUowMeUfwGseWneAF8xfYCvldVjzmzlar1B1aLD+TD/qi8HaC2YmSzIxvuQHr2UmYT06KXMJKRHL2UmIT16KQ+qw9h0pw/bbDxmB8yZe812UGvjG+8zu/sKYEHbcLGrZNichJXxQzxznn+StRGteUPvfEeeCQZh/9Jg+tD4hoHVqNNEpShELVP6BIpiyWcYd1bI7GLM+1rshnyMDxgr/9hm7bAOHORIEOQ8a9NmI0HW6Finh3wZFDUJ+aUaU4LuAvGgg2eMVIlZMugPf3xd2sBlUXefDWlNh7WJqLqQflboSTyBfVZIEYSfOIMihwAkq7lyKvbpCiWnolgEBq1eM0yaNOmnKX0ARXTGgNZT8QqpBj+CVAAfBcobxeahNdy6xHlNKb7wdKx3A3tGf1XyIZD+qhTFEtzJ5eXOVmvgDqaNfpqSeFTbK1auxTsaR9DYRKkQ+HlDq2v3h7o39U0t8lvRP5Kf0nM27YgnQuK7eRRLMGcjL3PWWANzAH8MmVM0H+a0EceCr8R5gr2OFrtVpoxIIvoxdhKp1NJhoH2jO/63vE/AV9TS7c6/RM9/ic6YFdL82bNtpekl7uEGz2eXuNOolmBeNi/zFhcO84zosWmbDwc75XFQGyNXJikxTxdjH8YupUoJWIf9l0KViBPBX90AKVY6nLgA5eOGj/N9Ry1+5jNv26fw4BQnRr1hWAwsY5q8bAnOzefl3KxC5xy4CRy2mJRFU54IVcuV0fyKMKf6vC/dei8Sj2/xzAVZfWkOXRFy+kx5FME5UlpC+BBgW3GC5VbVwd0q0k9ty+WnVrVNDju0513IAbucBw1aJzelH+IRc3lEXTWyBLkske6mAky5kt4aikFDIq1BxAfvLRstU8XK4jRJIjXxQK2jH5Ho5acMlSnJTQq388qcs8H3ruwDRzq9TA/sX2qVJo6YXUh9ymjsJ6LIfYD9XOhBZFEJco3t0lK7YOiW14fCBq+pxN/RKI9etyM8qNXMpp7jFM9KNzhSqRdj3jb5VMi8bYqS32a49C9FHzg8eOI/e2L9NV7nQsubuxmegiL3AHIeUD2yH0Vu6kzKga8UbuDCiFQJMo1GzjHO4q5z/dG5PxsF7Rqv/dzNbuZE85cwAyumjhAAq2u8WF0sWJ1LBStLkFsu8CHg7NxYcuOnnYz0+KiLqBv6sxhu25hW1Y7aGFAfBf9fytDtod+h326341Jj/+vP/6/68zPHExVUf35dqVSe/vy6b2zdKUB//k0H+g+rfDAoJGvrkQNlnu1BBSxEF1pH2qE6h1Sedua64qkF0p9fMXlP66GDlSE587oNOd/N40xh9+fX2fCi8q3QPVDDY6XC6c8/9PPC3NH9LvmPa/5uZm6jmS+tpT+/7qOOj3VvCod1Bd6ff+/Wuk3TNi/1nD5qmLpyrxtbCrc/P6FluBqsAy1TcP35G697eD7knm/uJf8uvc6sZxRzFEZ/fkLZcIKDKZuC68+vW7EpukS3fT4ZaamXA163eGANnS4whPA1zYnQG/32sz2X3+YlbtzkZ6eL4tU3a625sOhlC3qLAby+T61SYBad7bPZceDcKu+IRJ53P9kmA0Nco4qPjsF8OK0MD9WY0uaBObKR823ZDREMiMbie/CgbheQQKkEBF2Y+DaU6LJTza25qpj3WthVEgvoTy/WLv1B43HHQrJjNwxpens+vfDxX431YrhQG0r7qmyib/vPnNnubUO/w0XNdaF0B3W5AL3aEph0zkF1W01zoUoRyzdSFq2Rwf3L338+Hjz51knJ+PM3X3cp0jyDUTyF3wgpniKuC746sd+/kff3r0ktbGdJL5kmOErgleWqSHkET9ubYq06ld0k/eG7VvziWYs/7zHOk6gHsGVVT7EEM7J5mbG4cJjBdH8QU04sXAOUqjjMfEkjQOzUxa0TtmXFdhaxTUXunSJiVJrIpqJfOmmHaeLwv8C91aW/VnLp3Vzrs6Rs3VXzT+46Tbdr4AvC4pIUkNGYeSRLMGs+L7NmWcXKAY8yyVutlBfoVsZrBmt5VtCh5NUrez++5ZV7v8+EdPeYbuZslc1lRwsJochBFeh5Fju8JZc2m+ilkpqcx9varsg9cu7bCvGGimMGOvRt07Nwt70YAOsoAK5CAACqxSRPlDJl3P0n0A+d6vUfrwvcevjqmJ/X+0wo3DrgFhJkER8AjeekUo5mh/9YPg5z0neB5eN8TuXLx7nF9iwFzsexKf6zx8sRvb2nHneICnII+W4F+TifUvlON98WjtKnJxVoMZfe8vk4Y2pPyY36Wc5rRcLx4fd2tjpsFfk4L3i588QauFMg+Tjf135NPFV/g3/2SdWknt2WZFlFPs59XubcsgbmIIWZj1PrwgAb/z+r+hxofqUhsi+3vlXl41znZd6lQnd2rSgfp3SW13KPZYHeuZml7q3+kNy7kPNxzvNy7nShc86i+TgDvIJiLw6+KN5epnKJomuvtbaKfBzch+DMx7ml91M7/l/Ix7Gt79Z49JM5wbqIjE2yl1mNCzkfp9oYvnwcxzEFk4+zzlPZUe4wLXCN+mjsx9pPSwuej8PcmwuQY1J1DF+OScUxlsrHyZHOu31F1zRge9vaJ+8M77JB8Hwcpo4QACtHXqzsx/x/lY/TiUuNDTsgbyIPXivZuT9E8eh+X/optEO3eFAg6aORqmPYZaQmHF/U85Rr1aBETH+ak9SMKCUVSUE7vWjwDVDJi+ivVKW5rvCZECPZOmHF3F6c78c+yTEksuSvZBimwkIM660gUsksbjJSKvVPg/TnnAJK+pwk4B+6VJa/WwRtPXnE8dJhMgXGMFmkH6bXh1OPw9lKsLIzFyuXZE2O/8f/k8/sYU7a+ROb0tu8FPcGSQNxbEvE6VYTN4i0mLYjRgDGa4Gpx8dXxagUkaBDHUiFisI/h7sBcdJorXHzSBilYcUDVRFDZZH6m2Cvzg5jEdeNVQkuKDIP1PYVgSYzFZcgScMhHWkARMB/hXSkAf8wO9IEj7vZOez4M4+xp7fp7F6HXGR2pEnruXT0dXU/37kHl8x7OHdSZ4pOVdr96441zC+GdKzh4rQDKI0m2Qjl1sH2U0rsuy3x2dJyTkDnHw3/NodbwjtzbigyB/B1IVTVr0SRycMLZRafAxh5N1CL/QZldJ7Zy/s7vuVIdmsfOhLSOIeLV+W981YbZgji4jVwg33RvY9d800DPTZF99cWO3nIj5dlJSTEkyDtX0mCJZiWxsu0pIJlGrUnsg2UEAoV3DJav+5x3lBrlMvIOXuS04DlSq1Mg2cbYV9BU5hQXs2JnJ20c8B18YQ7+1Y4O/+azuRViaD4OOlghb46H2EE+cG3urGrp93ybX/0L80bH1NVvEyVDWe1P+LtKU8Ku4xoPgEFj9kDglfQbYGmY08uwK8KLuLlJYReOiiGDf+uhdsb0qR34TLp3e7dCimhOOezeNf+IqN31Emn5wiGxcij4kRg1CbdrAN7xTXmt3pIVBRwwaQKBTmRUg5miYF+xq7wth6MGWxcrwAp3zcWqSUoMgoM4QtHYZb5LooMSDQ3f6Y0PpAUW5ta8MLQH9o8KuFGI11RrzU/NW861HtP3w/acvzE/MduM+ZQm7vGslEkBWA1VwxbYztRRJNoWrYMwUEVLhXw7nRnBrT7XrSP37KjL1yqLtwoYoXSoowDxtz1hP3yGN5fjkmJFYTRTM2TcQBNVPj66gTXrLLdc/8zdF1fJ0eHif98ossluLug4A/nhd+/cOBnZcaYO7uYWBEgyxP7JVCOMIeQ/ktNYS5HvpCq4KAHzMAgErAgSAPjwWVgepzMeTGlQU3vKdoXxY59bEo3l6WJfj8iItJnfMPS+sQNYGMfoVKA3SzIWQQjkMGCEGnxpxq3UTz9Y/PStzeueOlu1W9yv+VvH3jejz0Yh0Y2FtUMVKcAybLzocboMqrrpzN/m6je1d7Va9we7zRFjXIPpA7n8mtcKtg20YjGplxcrYgHJPAWMyCVgeAilGnjbZtH28yoGLDfJm2HyvHzI/r68IGl3RJX8zOmSe32Za+ICpGMWZjytNWje2b3P56E6oYCXp+A6rQVqC6q0OtU9EqBvkfkiL9x8a6yn8HKAxsTOc5LN3jILbn9SOWV7ZKZk0TVem8vEsO//7AjV9m/2oEcU6pWZ51N9djRQrmw7Y+K2QIwVMrLUGzxcuzozEPSHYrk6N6vkgbuOxk0rsiTZifqHtllHJLubCTd80WyfOmxyzsHFglcXs2nrcS2htl+JoZkT14kQ3WsvZyJzcMcCcWMWVoeXcIs2MtnM0xAyFYvYS5ujYS3wC9I/QHf4hWVAHEjLbD4v2qBKz2ruelXr/NBk0u9XOR8acr0grDAiCaVxwIjg1P/Z4H5LfDBxrWQPgP3ec3c2qZ+7MO+CVZsgZFhqTxqBlFYRW4EghSoBW50ru2xSXeOoNPX6qL7jVW0tKAFZpY5CsDQaF6GYou3AC1wd9n3FV72IZ6z7q2L+nJ9X5QFLfCPM+8jdrW+Ebx63cytNo0+OgiAZH9eJHulFogFZtZ7WZkFJvQHlwUG4kZaYJTLAl+f4Dztb5cAr7kXcz+trevlRI9wdo1XKIjBv+yzUzzIKiGmn4coFUl60YDW3OJPkpLzwPFpsQlSjVwWlwQ0OpXhY1w2+u7PXz2+bkzySpXMjalddd0grldm147n0YyFuCKKoABiBwksYecYirRh56DzRfUrdqUA0MqkmogYUZRGBZc8v8jQ9peuID6bXl39cvlt86rmlGBbWO3VQBFxKme+SQqKdGQXMZoYwjZIdIrBtJ4aYyQ8YBi7WvV3wtqkkNTZLr9dTVSsEjyx6YDuUxXJNc+ALS9fXbGrdHSKAOC14QXvl1TT5u1VJ0QMc3n7+vQXRRALFEhc36794TPfGLqb7uSSK5xjSTHIgqu4m6RopcDQ0ZWRANEyqazKzVNOIKBvSIPBgqdygO42ao1qCLVfADOtMQThe9vRT8dNrHREvH6ZjTimgv1QupRRX8GWMj3FEkC14QXqF70tkHDZgsyLe8rZ76kekhr9pVH8tHb0QyB7/Qx4yFhRWw60nb2Gx2mkEUQLAf1sei3Q+WSnIuNUfpnucVeeXdsevDV01IaPuqVuXG/GVvl5NGORHIMiM0aTGctslX8dRUaOtkTfnzUeLi+27i7ln+N7qFzu6MGuAvb9ETrQlI4iWQChV2IEMt0mG0fIJJVFQoSBookjRAR+GFdi8YCBw6uHTG/V9M0fDWVxjMM4cDckrx2/LPh6e0NicB7qoBaXIONHm6aYHAkM9IsEisCZHwOLb7R77Lnxn5gXua+/+9MQKIrJOuv34xct8etH8v567WhK23hyaZtnPYIDbZt/lsxafsZ7aYhfH+ZBkhLSTYNLz9TRjy8Gkxzyeo0lqkzqnBH3rE1MiLqhZOHuCTe/7g1OZ78S27UHV42FbRCqE4OQ2RmoanmH6lqb1lKsLPjyfJfNpfQ/R7aY1zhoTRGbou/+HkWv3nTA1weHdacR89Mykx/dqFys+37fLWEl/R2WZjc0V8vEoDoPAFZXqGO0GtV1gHdg5EyowcHiX18vkndeO1j6efC4azc0s8/WuEov9NfbEnahfx4p3w4ixwaserMhwj9rZvUrU17VaScATK15YXLXmaaMSxFCJYuO5aoTY4bbjV0mwuuh4hJCRjZBLVE5CYCG1ENe/4d2wAfPiWcsn+zvN+7Owt4TlTHvLbsD1tXS8eyAdRVM01nG74DvONdKWHi5mPfYU7Murm91p5GAO2CmJ2H+Jk5Xk7sDagqqq8LWVZbaAdv/GNMzvIZWMnVl8Bs/9+BG/4EdMJAhHvDKmKjBTN4BM02Xde2ACdHi2tgB0SqEHXCNYiWaxce8DpzVpNLNQRKnU9awAybEiBOoMnpb4P1/yBb0qTsu5t6q33z3DVyy4+zJ6nUsHA29O5ovGnrGtK2x8bagxcot389UOBe48dS6dZFF4ocJaAuYeyoBAnq3R/MF9C6PLjBb0Do5o+3pSwck06c+/PJZ+8bjP2ALgAzxgHfIxNCCybaA6Z9bly0gRIszyHfZxKCDMLagoetrx+Lvg7y2V5QMGN++5iprsAWEGHECdUgfn/DhsgVlvgcfvze6WeCkXxv166H5WoG+FwwGyhMcnBtffdAwHIiGlKgn1A//BoVSItA/WZkgVcgj5XFJUIwrBl7rYK/9GbRF07Xo6QdBozjehr0z1ZOMxS4QRd6NxLC7Dc1A2YIiF0eapORLgS/HG8HLOFKKnR2rj72Y85skw+WfvR26KOhHXbbQn0Vcze9UWrz83NTi/V9J0m/07D/2asfV5mqncBR5M5LzwHUMDo1J2qki6KYtkkcR4iDXigC3oBgh8lX2Vz85BY6tf+i55+352xkNswGTvRXSaEgE3IAm+Do7RQKihqrrohLk8UjTFFJlJiB+xLKAp8dpbg+r733Xe8PYZc9SPTovoqtq8k4OWBhkSyBzkxcZpqgUyQeZRmK8DixeqhBF5lGpZkzEsEsQCuQ4Xij6x8pvLy98CNnYdXHJBVcnr6AHAQ2+jx0ENCRaAqdTvDgdHElpal8uTd1xZNPT28SxgSv3TW+1z6XbHoaXAwLDwSpImVhRDqjrdZVpQEWwiKyuECll0UTrYZfgkHAR9t+yRvB6sfo+a5u0bGHvN8v+ScPvix1Xw98E4m+RFGNRm4YiDUYdx9NkkNss1A6hSJVRJuno0ij5S/FSHOhPW9s69cDtOW38Zp4q5bVq2NXjtJ9mI2YnDYnzdR6ZOs1c9TwTReoBVNzEQEUzUVmMo2KSei6DKQmZRisDqyxZPBKecHDr57hd68v57vjZtOamaUWy6QlBRJcgdj04eV3w5XSdhOATFILPOATkcvL7rybllhlYx14+rZPPxPkxyKvZIUMsn5QbhyKJANVcqEv0EEV6jvpfUi5/Um7rvdN2RJT5FrR61IKva/3f0jOpzUnKZa4/c5UItmWIH0W2x4LWcQ8dZaVJuSbmP5qUlDvzZ+b+4fM3eqQ/alknZ1lWVyGTcs3VeRjHpLwcw1ZnAWbdNm9wxuXPZwPEU56tvxw+qYvCglm3/7xcvXBjzQ/BO8K7t2l3OD1RANkP4kVSMqpAsm7Fj1q6Vp2e4buqxOnaaS9udLGqrNsfpIKAbwIdJEDcSBPrz2ViRdF1d2RMnoDOOLw+cN7nXcn0cGaoTCFNoptWE1GuIBYlyjUykQY8idwcwJFm7JAhL8IeNp+vTva4OWXJ5ZGNvLO/f9M+/kVzwFy53IgiS0aScqljyeVlFJmr3yQEWD3kFacjd71SOgRNPNSpeVt0UB9hIGcuGQEgXzSKD/LZeikP5ILcPTv0aN+cNd6rsx1PHxr1fjb9l/poVPFqOuSlKMhRlWFzMvwS0SMaXKJav8G4UEssigbPxV0SjVSrjVGp1TINyQ9tET9PCjBmQA0jUZ4WcxeHkSijwfQ9MVJRBB5swki21HcxWG7n5zmQxhngOUOFxf9cyKPFb8dKMms4Ol2MX9EKAiFbWBg8RigeE+wK+m8EPLOdOl05vmZd4ExXmwZTHZXDLBrw7JvCF/DskCJwwLOl+N3DOpfOSg7cXOYsKbJIJljA0/HPuNNeC3T+c9I/VtkxaMAEAQKevVP4Ap4YNBYKeN5ZPmTW2SolPBeO61vppOLADasJeOKAcIarQlIsGPDs2+nd3KiDsZ7bWq/r3mfW6gVWFvD04kWGKSoWDnheEQejO1bOEmc9Hyluf+/wWSsKeLrz4tQwhTKswdYf8CxW23b7yUmnAmfenrLe7qw414IBz8kpfAHP0abpaCMCnhUrruhj+3Cjdy6SMuB8ds0BAgQ8mTpNgIBnZgpfwHO0ierZmIBn+dkNH8Q/rohODXfsdOyCbf1CD3jiEHAGPEfrl1PIfzXg2cFl0J9fQ9Vo1rMhL1s1GDbR8gHPQShyJ4VMVGe7RK9Q5LeU/wU8+QOeCfbzG52PK+Wftdzjr9wTTusFC3gy15/5CeTIrRTOAakrUeRSihUHPHEvwgIBT9XdFUFjp1fzW9HxxMHba8WDrSngiXHsNC/HfitYjlHvbxeepJYZ/nhngy24a4BMo5QpXMFntK4+vgPD8GbAxjQKtnVv7t66ACO4V/yT/8i5lRow1/NboHaQpoYFI7hCR8ow0djJKxobUgokgvvXjycrz3i4howLLnl0SUKSl1VFcG0lhMaD72rLSsD6IX2GrlYfTmRu+a02gls8hS+c+COZgryb1UPeftiL4MWNY30nzHL5MmhYtUnCQM5cMgJAbssbNP+ml/LQ/2QElxkhNIjgMrelBhFcpjNtEMFlLiWDCC6T5SZEcANj530dEuW7Z/SdGg1d910TIIIbxsUup7uTPcu3/12ytNW9AzknEj1p31Xr0E6+/8FHnJQj5h/B+MT/OHviRhNegBy1xMQin7ugIsR/C5RNTIVnCnQs/uX3+X9r0fSuMaRnwcNksmfBQTEpJuFcYvJj3JbsCq626I5+VeavVAfRcwEd/eh/6HJhn69cMO+HCALzIxycZ34M6owwPgPl7dl+Z2+FLv8g2VZ1v1P1wZNH8P5e9vha5gfyU+TMro1GKnJO5k5BdWmgsGmKIXO7C6ayGxegyh5d5orjN3lkyOak6llTZowabaCyZ9WV2K9rWsVrX0+HrncSZ98wUNl3nwc3rvyLHZrZu2XXtmX3bjRQ2aXfVraLCV8XnIo08b74+a/zBip7yHJtjt2XEcEz+mz77Z+cgT0xUjGS5PPj+Dz5iFchk66WXxtU8R44xStOkq61ma3JeloiMLNP6PqFkvj5GKkESVp7b8LS4E1bxDk9h7s10Ibsw0h2JOnhEdvZS2wzvDbtXHayya1aGzBSSZLU4EQNx10r2vnOGlYCPfy03UqMZE+S0kptnCw7eF2yLGbXkqPXM50wkgNJWrUh4ukvG9Z5rBg1LaPFwskajFSKJLXwivsRsrIZOuXSzpoT3+FmrzRJ6tQv8reU5DS/uT+2aDrcalIGI5WhjOWBlAEdjrfx3h9d+97+y92LYiRHkvTSpn2nsUXmB0/1UEX+/jMjEiOVJUklnx7P6l+vlveSxtMa/pZ7/wFGKkeSdvsm7OlVPx6dFpg1Jufy5aMYqTxJet7SbnWDJclBW8uMSTlrW3EdRqpAkvzsFJN39q3uu/z0xA0Vnq76ByNVJElLe62qGH/piHjTpM+vFPY/62CkSiTpWbkHU1uUn+q3+uOfQRc/VP6JkZxI0upu1QdFdz2IzttX9nC15i27YaTKJKlOs3kTxies8JnWb0ubEKeEJxipCknqu/BG7onJjYIXrvdZf6V/NfBdVUnSqZtzGtnZFfFcUeRki8ql/DIwUjWSNG3HpHO9qy72Xhb6V0SpxqMTMFJ1kqRx/OvkqTY30PlTvkw9MO/QD4xUgyS5zdt1oEhOJ8nGe1vvdn73AshhTZK0NfrgpvT3ezx+Vd3r7HTfsytGqkWSvte9OKN/v4DArUW7fY+Lig7FSLVJUtHTFfY/i3DzH5PYInezV9IjjCQiSW2GPz/dyDnGY6pHMU38pL4AjTokaeqlmqV83OsH7/zrWOuYyTevYiRn6nd1vO+0+dLGkD2umdNaJvw6jOXcAD0E1awPdHMqTFtU3n9Kz9+dPMW7swRwbnpwKbZKUbty5h896bVw/d0Rp2ukLKFP8fEarlaoIiEtQ7gOpxuQd4jIRkQiOShx0sZKFQpMdZHtD4zsG8JUa9BXYw8YIgnGOvQiVHcJjPUrDq2+vInqTrGHR/J2D8lrTES8CDzv29fV6/AZr5CxL//ZWL5XM3o9nHl9iYSeEemC6i4CgCKhwY/JqO539oxIvukUrUJlmGjgo68jZRGqWLVKK8ej+Nj7yRX4FBlKTkRSbOMoBRNLI6AoLq807sapyn+J5w6IHyG590cgPZtB/z3sbIY8kuBhEBdcYnjgOlqwYyIpB4g51MLG3KEWzciFFpnHLrxuNlY6VCbC3BZwnjxYqpURigA+h0R0cN3jsbGS7Zfb5kzdNY1RSBtGPhYybJ6iCM69D6Swe0JLHCtIgLCzMhFMBK5OD5kmTo59kjp1lzGBhI+lCvzYvsSkpiE7lGsSW2UfYQx/p57JBktPsQRYp3jBwkSdtD89OU8JaxcZOnNzWXTXUsXLDiPtfOm7CC+yt5soUKaMjoth26ESHBjvstHfSlkiKUiaisDAwB4gipJGxKk0mLJRKaPxqlwF/gWu5BeRdK0oQqoUDZaJtPFqtUKOcWiwCiNi9xOPjFeCW0FhrxKMFVPgg5Xxi64iSYxUGS3D+ds3uL9ITR3r4SlMquhohUFDLewzoKlWLCYERtpGpl/PCxt788X4gLEMR1DkJ2B4JQnsAPMpirw0zVYa2cRvR5Ssz11bbcBO//fRU5+cfCKgsWRqIHONpR2K/BhD7irZ2j8TRT6bZiydafJIzvDGO9oRgGEfhR9uz2/V+dClw35byi/e87VxvVj6wQCHWFDXBVcUGCrveFF5WTg20eAw1HAksimztlr6RYlAsllTfBXTuSXXGuoFFzdXN9EokburWyMoy/Y4Fduu21DXM3XOvP5L5zqVZKTm6R8ESc3Lo1mCdU95WffAWt0ZvoycmkT/CinRQhVMwJZHAfVOWAEoe1bEdChya6fYa8ecM0FvApvRm6Wa2CvFXKbYSAgtAz+PrCYBWsakfMkG4cBYYYgkyAi7aAIwfYfOnBAhkvrnblvgfHehkg5MCfLB7G0aRbAEOO94wXk5xrSUyYaElcqz4KagE+I622tGyca+C73aZ3bz602vSyipT/Zhb1HySJZA6CkvQg/0flsvLr/t5AJp4Pd2lX3GrKxV4mnd5P10bxRvdhjmGWh84ACl9xolPWFshxiF/RXzu5IMG3JiypaUV+B7ka7bSKMcJ2bUE/7ebC+aohiLcVdU99d4DOO/oble31Dd6fEWaErqp736afvX++LU2lenRyyeozSnly/DUyoaOvNQaK2HntsPLuvqfvtwP3M9pV6o7vp4zozdXFR3aTy0ESmXIa6CA0TJhUukXEMkB8KNLVJn1dlR3/39svZeW5cR3mYrfVl6Ujezl2UeKT/AwmKqXomfvUO8vUbH+13mnRsuAGDneQHDJKpQnCjCZoDPtEC4/rxiOVVUmhl0gCnOSx6tWrz3dOTT+utBM/eW91rj9OJ5eT8lpikxZngNV2uwLbjBs4qL0TCXXo3Mc4AZrH3s3vqietTmgOxhy7cN2f3U7JFFGGuP8bL2t0JiLcw/ntZF4Ma3890Wyeuu1/jvmfeo+Eu7FHo1VoE2vrWXEDppEzSFqZIELDHSMPbmMozoxco3Etps9djQd0CVzB776DHJiiCNJQ6EPj3lUVEyjQyDAtL4n6uioLlEFYtBTiTT4I+JzHsMvjkkxm6DwBIoDzPKIjIP+/J/YRY7oJ8yFnRPVLc2DQP9MbQI4SCqW55m7qhucaABKCDcoFLLNMDbALUYhIxrQfEcNUdBQ/rBWhCNViXKIuFG5MD7IhMaT2vr/2uPvXb7DoevpeuYHvj8ZbaOIa/np2P+bPxl1YsrOo9lSTX2vN/39XdzdUwgqlsDYLZFYSn943GYzQ0J1zdgvz66FaFSamUR8bh44OPh4buIi/u2I5V6iNeU6iV/33azjlFYpH8ue/tLIwquEq6SsPWDwaYrIQGwkSqhD5dKOF2m7lv31qqg9DcvA1z/HO1FrzQIlakV0ggZXrMH0QVcDnMz6j6Q6qs1KP0khDxRHhcjUmHbFI3xmoB5ts/znuyKCBrZhDbYU9I4W5/aSnRpZq99J2DUtFThqL5WFgpAUJbjvZsH1SFTvJdn1noepaC7z/iD2O4zcTm/5czMZRCgvfNkgNwyqMuwGNVlpHG6z0YiV12PnIYmakC0oPDdD1CevB7+Gt1c5Hz9zBjH2zT4SpECAj/SoVMFX8UYWmm8aI1KK1AHi3pRVm5/Xb7cfuDkRss0kBIOcxW3E24gAWOxR2Cb6iSC1VAuMw2TOYvEXL6WlRCrAMzMYfO1tgSsApMCYVWCcWzxijJc+knRh1cOP6los3ely+ug8buHDtu7wP4Z42AC/CrIwQR+2RJQpPFCMUpvqPpafS44U1sKkwseqZK0O/79ht/qOznPlsXu6WR+LrguNo0nF1wn10Pez+ohZ2bUCQP54/41qvffkey/wGnCmwsz75vdBnwjitQfy5d+X2csBXl/wXI5HSnICyCXE5J6SeVyQlIvqVxOSOollcsJSb2kcjkhqZdULick9ZLK5YSkXlK5nLPcWm1ZtHy8ZJVjzN9lqp+LYKW8AeGFSh8zaVOAlLcBXPx3DjjS7MZme+9VtpGDLz8pS+d/BSLYT2s5znbKi3OsNmdvuTISPxygeqKrqUbpJk3mYyaq5vuKLHBgHzKhP0kToNeuQmPXh1CkOtsr54tdV9cPJCB7nxONz7nzgoKmN82YW2KBn86zOtpxc0KQgHMJmMd45iokbF/YmDK7r1gKaRKqc4b74VxYVdKnRBhiBUWpXfiQeUGrfgavfbfq3If/1951wDWN/v3KEBQB9xYriifqIbhx0rSMQhkC6jnOs0KFaim1LSjOIrK3WxQFBXErbsWBe3vuPXFvxb3fpEuaPElbmpb6f+/uc8M8TZp+f8/z2+PNcAaJaRGxA/3eH10+wWNlZLJXEhSznwSUmhGiVA/gfCDS0zoqBxBID5sUswpjCJS5Z/ihEs60yWvj+i323LThvPWRmpGTqzKee02+icABuep0ioOWamx7ZfQQgUgGT2hkBJL5BEsgFd4EBKf47OkDj5o0855xqp2v9cuifsYQtYRBohKC1CxOu7iuA2ZMw68tIw0s4jOoTXMPW09ZPxJabjs4PeFY4buqn80Ao9OQEJ06Sl30HzzBaISzI9FlGXqYHRkYRzQ70lM7UadZmJb2JT47v+UOjzlmvbszT9L262l2JJrFkTAUcUAc0VBElnayTpPZkVMulXeZF+LoFWcT1639kP1d9DA7kmyVIFy6awhggrQUdupDaOhYc5XOjpTuEdzZkZ5KPjQSjw/R/zjZyTXuNivPI/+N2LVJC7QfOoItoMr8NAB/OZ5q/ofsPkW0R1qXwqbyOeORSxwhN0QuIDViS+iSMII3BHnKKyxriiusOZXFH5Fm5wB0chM65Vy8VozKRhqGkjl34dcB/sqdY77ZzE255DdrQPMF63bZogxl6QOwKpLssrozh66O0/XMUSDKXQSeNcAzNxei3IjXKpvEWvY+8j0BROdS1LNdFqdm+eZ0d0gbk17jNKr3hvR+bPRPfl0dPt4D+rRvvXyT7xrXdzdbdnNIIQGfy4T4wNunKjIMLKWJG9EyIPpQ0H9h00aIcnGtg9nCMI6YiGiln82WBd2t7pO8b0K316ws1YNbXXY/lmjy66QzS5gqpwipctSoqPJ6r4IqWokvWynDE3BC5cwXXBBHW36PVlLbPa8wxemk6wbVJpzVfaX3Ywkjv046YWzoMnaCuBmx9qo9XXI1XjuDrJkSA6lhweOqw2P31+JdJ+pwWenltzP2Brmq4mFBlz0Am1WrWNAHIucIETker5DrbDy5vmGmz7thvXsxE959F1seuPZWlcayb9Q8GaaP0sJQFeDU8eHckHBYrURqC9ki2NKtkBUjF/+aGR/o6m7Q+2L3pOy65nmilB3x8jxRbPYLfHUjVq5rGQFvLlc1EGHP5YfwokKRslyq7E2AP5x/58KFW0v3s5Y+7buEzu1vpbr58BQb5YKhhf9fEGU7gqEzMLVlvhRDrThWHz/5jmLIdlTFQi0kH0gk8w+Ec8PCkf//pVNSJ/mB23ui5bnqVpJ9DXYrya+TfpjfyQFrDATMmo4AJj/Mo4w+cIXeTZoErqpR1W5SdJiDhGBhfjxRsDBXiXkIHuZ+2zxOH6McpEuGNunNfepdR+Wn2vhG8cRcAY8bIi0L07ynajNfWB+AxZMYvpNHjVB5ikZ8Et3Pgui1MKRArWvRuvhmgrx1MdZxsx9WaBMAvVQV8gTQSxX5JnQvVbxeqdVw1snslYrHm1p4cIUwz1E2/lelF5A+f/naXP9++KTf5vK9zF5JYtWm3Zr1XEZ3WLzJW3Zkb89FHptsLb/SigIhEnou30iQ91wGJehQLiccQfUpJQLJLogTEimdt6s5Sj02ht070P04c7FXo4Jjy9aq9jOqBmFRgtSi9OqIt0nslkyf1Z2stq8sj9tEAkrnCFE6lYDpQ0mY7SLrH40oRhoAhM56r/IW1dId8wnoaPosRUrOT0N/M36KbgJkGH4qsSHipxLT//ipgj4DMpt5vBsX5bn6agcWg3r9KAn8FN3cSXdOIbEm4hQSS73zU8+ww9HTq7G9s9yfen+KtcgmgZ+inQQkoGRKiNKPeD3yU7QMrWp+KtsxePwUQUrOTzlGbxOgjxM5yWzdqjV5k04XMLa+dwvfcCE9kAST4BWhSfBMaRKMJi2ZrbYCcgMkswE65ylYPaBzniKZDdA5T5HMBuicp0hmA3TOUySzATrnKZLZ7O8+L7Gu+Zm+227rwzGPGLcrJLM5Zi4Q/x2b6r/j8833pWVf+ldoTLi4k2fMpYc9fVasWbPhUtn7a5g8N+RD4AJdVKc+EvLcwkjbGlYG3BqV61kJaOCogBudKYChiRkeTdAtEkmgSTgeTXK23xmSeP8Tc+f2LTuLx95VrQ40D2DzOTxsy2A8dtiORhUgd8jbwiDdXqn8SDFH1pIIGfMkG8QDdvKhezwCXkUTHmkVFCKM5PECETmHXPxVKPq6P4p/2h2nOOSsKXHb0z66/aXWQxzx+KflQBFHGAy/vuJrHRiRUaN4SIYX/D7SdkGhXLH8t8N6CRIbKZMsR5HEHI/tjqRJWiFs15VOkSTSa/qyhWFcPoszWkVsWskuB3LDwlWu15BdD44UVLyqyrudb4bTpsFfYSsFMUCIVBuKubK3slC8FehACdnjmfxQpFmXAt5qNZCLSMCmwiWpho+k1Sgv1QpCelGweXSkg1QF8SUdAKD8s9lgIVugvEe+VblGL8zRHUdJcvCh9z8Jqem9iaQ5pYdSmo8xeszRrVyN1qlK6U5YDtBZWQ4wljQxachu/IAevQoxCejRqxCTgB69CjEJ6NGr0KAGltXg7Ho63zMv5XHp3TlxUZp340d39yVBgvLwyFUjaF708qgxjPUvPnF6UFeWq3a+k8cEfeF/CWF+qHnDwKaKaCKf6i/g8D1Z1Aj5MzSLFaK7GBO+FrYhH+oDmu7/TzTJxyQkkEOnUM5gjLZqdMnNJEz0kCiDooVs/yoaUyLdBaKQDp7hbD4syYA/vL2TPaNr0kXGXudbCY3Kch6qxgoZsidgY4WKBfLH0ECSD0nypv2gnArJm6QqyakwD4GhVXKG+Pj4n9r0AaSqEgZpPRXFYwulIUgeoqMAabNnZ9+evTYep+d2v2i2ZXIP1QoByyD5QwD9VRUr+qDOc0LqPDIG6sDc6Kc2iUct3SO4ImlH4xAVMilYCJA4F9d3ZiTduuiZ6HTlqWT6p/mqxJE9EeDf/bWiD+KUERLnpjEQB6FPReKYqiFOD1oE8pVSmsCvI4Jv5fBDYmT9GPtSIwXscUj7Rhfpn359AnyiusSd3eRTMMlt8cnc77umjX+vWuIeXOH52BJ3lVV9EO8KIfHOVw3xNOixaaaGgn1/UVAUzuXH8GFNFyYfTC5+JB8hHfx/vMjx0kXkj87IUgR7guwCkI4nihi7wgbSoKJ2bdzZDV7eRjVKCwdlTMsv64Nypwkpd6zKKYfchARbtMqiqStzVXP5YcSMcFUhg5PHbu6+6+LmZc1W9lJtWmeJqzP9WiGdItZ0mQ6BmBVHMWpVK6laJddTI/D01CZmk4L2l7zz32u5/kHb7pM6qgbxZLN5qAFCTjSXM15VTUUwxUt6+4OGNCQSVfD4SHvLhnEiIzhiYQxVIHugyJYpS/Ri8gM5fLmRgq+8oudsEL0rNuCoum4zCP6XIFIolg00VHxKY+xTIEnj5CPStC1AINKULrFOxk2IA5q8ngpspDWV0nfUSKMfPnCoqah8HS1zS0vuynCeqqvWUvFUwBBuxYo6Y7j9XyvHSMp7e220EzEHpd1aoKsxnAFJGiHIuQH5yB5IUjdZqxz4BsEVVBhqZDRHKOTijLNIKc+aGhv12Hcjz+r26I7nD+l+hNGRPxSPIAEra0KsLJMNynMVzkoLucmFfAhRdm7m3fxpyZFrfIqLkDP001wq29BS1VJhGCg+ivy3VkW1R/UOpbnNx2Nj//Xnr1R/fvR4IoP156clE/Xnd8HyThL68wd7nxorSLgPFdu3smlavQGZhehk80hLiOKWTNTOvDeWR+qjP3+19nddX1328ygouFnsv8ZftYlSVfTn706IiothuSGh7aBdTRB5/fm7NKpZ6LImhJUUtPi92fHOM42mP39HQtL9UTWkM3h//rissnpPz3+DNpd9+HF7ptkeVDjT0P35pVwGt8E6zGUM1p//3esR977v2MjcMWiEf7Obu5sbQX/+7oTguCQbsD9//cVndofPYnrPcv5o1fxIc9XgYtX15+9IiBB8puV6WySe3uZOa9/hZ98LtBW37FaeW/xKtW7eSlrfJ4jkwRIdq7NZ4uDc7VeIhPvrfnmbDBhxYWRUWDisw4k4UleNNm0e0CMbcd8W2xChwqKm+JaWUl4i+LLpiNMFje8fdMpVfBNTw5qr+r9eC74qxwL407/84fBXtLO1+8wZg5JmvWxboPtYL5QKNa5/64aB7/huhXEmo8zfXR2oqwolKaW8QNBrSQftznkQ5bF2KlQt2fEN5YQJOWD9soNfXgdRrUceW0PsFhWsKVXtK1qdIb0RUDwlu0766YR//z3C33+rypUl5c7UQlFCXpkbGcoNIWh7Q3/w5G3uYq5v0ijK0yacQeGqe1XxAOxeVa7ogxhXCYlxwTjUH4o2EQsnH36kGBZf7BDEd9rOuS9sssKWRURHqkvfkPBIYWhHaue+onFCsfQPYG11cWqI6+srk9wyLxxYPce9WXdVuYZ8QZA4hgcYjflrSR/E+peQWMeN4uQgj9JKW23wy9HNjxKOEhGcoFe7+nf962VNn6X9C1wmRrT11sVU1pUcXegyRo5UgZ7BkMODPvChllqqnJMTaFuiBYvORQxb7JMZc+3JF8mTaVVr9sIA3FEAcAUAAMJatNJEFaIMv//EqI8r7+X/7eRWdObMIl749WVVWwfchS45RwTAqhNKRVPwm+XjoCd9Gywf588Uonycein6zsep1uZHhOPrB4z5tTY9ZbVtPcUI8nE6phBFN/9IMYKkgrFjxxogH8fuS2nYgBqBPjuHbMjpxLvZwSjycewJqdPCGKhjkHycxHevkx5njGPmLMp9KTw457BR5OM0JiROPWMgDqUq83EYNYL5HQaYQsvdFi5oHnLqqVHl49gQEq9G1RDPOPNxlpz90n5W39eMzF6zAuqF3Xhfxfk4ZoSU+2kUZore8nF+uH0KPf7soduGtrsnlXoPf2AU+ThSHQI3HwdmhHI9ddz/Qj6O6Yl6e56FOHtPH99le7F7zKMqzsfxSyHKx6FjVVq95OMEDWU82TTnPGPeyc9zBI3915Kej4O2zUnIMfFNIcox8UrRVz6OVdG6zrkOXh6Jl2PWFpZftSc9HwfNI0jAik6IVT/DSsuqzscR4rGxcXu5Hbh+q+jb9vjzHt0f9ko1UjIgCimQ9BSyBeHYMlItwhdtGFyRACkRU0ZzYv6UlZJS2Ug7vTDkG8BddCa8OOFoH+6W6WYujEobNgD3/bCRnIqLmP1XIwhmYf4V660AuxJd3KThrlQ+DZtPI5mIlPQ1pCP/qO5KVg8KFAKvWgdxeEhPhFAmzNcnKB4nJauMlCI8UuZlp0c99/7kOXdcQ1FOSse/VX1BHkjSgBgriXDVatkNVBHM7WQjAKNEiKiXjq8Kj+SFIh3qkFSo0dLPSdUAMTtMpBHvRZeGVWdFhozlhCpvAr061o0lu64pS2gHUWKR2j4TYDJTdTpl3AxARxoEIkR/BXSkQf5Bd6Txi7/VL+jIM7cZJzZLLN/4X0B3pIkbnD/tmmC41/zSvAUP56f1U6wrKu0q3bEG/cWAjjV4lLZCSqPlZARSyyV5RudVHZ+zUsJnms9w8ozXhVrkK3POEEWC0HURkNUvhyiTZlTJLD4rZOTdPyL4N/DDfom9X3+WmhyTnHsFTgE0zsGjVV2PX6cNFgTiKCFYYMdPP1vnxNRbHukdV40v+ePOeEKSWdBlTwK0f5Uv6INo0YREG2dYoilsIjMWXcZQkVumKc+9lDaKM4on5OwZ8mnAXL6II5RmG8FfocIwgbT6u7ZdjX5/rWCtGTjDUVy0xgdNKwvfKDF7FE9ZnU9BOfmRb3XGVk87q21/VEnxRkRUHiFRw2Zg2h8R9pSXb3aOrPkE2AWK6gFBuNHNEE6HnVwgvUr6Fq9Ll/GlUhpo+LedVN7IRboYT6QPuHfb34J32nPJjj0m07a2SlDNEQwK544WU5FRm6piHZFXeGN+m/mPHo2oYGweTz6RkovMEkP6GTsBAUbPYMN7BUD5vqZI5UGSt8iMh2AIJJnLIMk9naf2WksHksJnU4S8MPCHbtwrvnZpSgRrQ5ex6Q1Hv1btkG2G8xPVGjboOdS6nrECSFKOYDWfBjpj2yDJC+zMFMJsGRkFI6W7AojLUstGRY0arPBe0vL0p4aRD4sxrrTRmgGj63mCf/ljwl9+z7Azd0nKk7FCmqgQ9dWxGvksYOnEbj7b+Z0H5pycNEh1XyJ3Gwr+W4TwX60a+DGZMbrOLpadCCTLE/4l4MalqCGkleQUulLki5wVlLqBBAyFjhwIuYCJwhMwg46tf5nRtoVHhuil+eGPHVXFpbWs3w9V5unTvGGpg+wGxLAPieQh1iySs4iMQEYOBFUkfapmhuKZK6dqc1ie3vPXdE443pjei+D9sINxVJY1RTUJouQjtZo5QGF0CaJkJ+luJgp29HJyjy/xiOM1r/OAbXVaXeNS0sxEDRqb4lG1vtQhIW0xg6QyyKgIJNpgXsyzAfUOu8XNvTawr+u+b6rnwxOUdiu7qk6YxrjuLigc7U+fvmjy026P7qXpKkzTIEoeQuujQJ5WCFEWGkWlNIWiYocoNgmAp+HRrhGzwslDDBOulJbOQPLF+PdJm9K8Bm2T2NHK77HDa2L7w1J+yiplgeQ4L+a2XiP0LlnwqPory8ndSCDoXEKCwocXx6LTDUkXIJIrL3m0XDO5lBYXvXJgauZdqmZIumCRdFHf8LdmvW2HNyzxzmgy6tOtOnPOkoBkGiGSiUkYW07L5mG2MsYMS1oCXoIu2FNjDMsgxLKXoHbOjuRL4Jdy/gE28UzpyHaTS+Do31UCN8jrc9zcro5f4THTsuefu/xtCAksWZ5MIIElc5P/k8DEErhJ3u2i7ReHuC1a1CVi48NmjY1YAksKkwnYjCTPKHIjKBSDSuDGSz52rXch2TcjZrxvLVGTbD1KYHSZIwkEXUhIUPjwGlAC16XVXzfvuCM0dzvnTW3+rVw9SuChroufMx0d/edtFS6bPt3WlwQkswmRTEs2iARG13sZmQSW8Q88CYxsN7kEHo8nga8l22fdaOfjPv/C9k+rWrs3VPVwBkTxeLLBv9jYqdTJSpdNP/fn82KUWwNYcyt9Els+D1w6LTaaLeRyxDEIR1dk+GiWjX7xnX/ALNsf9BRm0f4lG/tuwXtlbO34rzVNIa4PSaIRiK3ooISdw5BkrHZNIOoHKAAQcdjCkHDqaGEkeOd9jL3/uWmbpv4lAcvyhx9qfFKXEmw9s73mkCQKv//LZEgiwBYxaunCrpDoFA5zPQFMSLDD8E3Q9BGxZ7b5pywtYwm+vqeRnti0V/KpMf0qw2fjq9eXLRscyiABvLGE4I1O1m7eXjPZFoNV3mGef1NDZAcU2XHDAv4GQobm3apKrvyE4xwp1DLpLO6WfGtNBqEjsaEjW0ursipnBleGgLIhDQyLNJUD6W4jEEaOUdgLyExrGEEgZEWNbGsM8yqgbS35+u2976V7qrtM8RXYXaZc0QdQYwmBGq2UBRPwZEHqhZI6NUua+ceGfXGMynK1VmWsyhnwgLGiZjho27tPEAvZIbIWAsrZ9CKE58s7FWnG8pceLO788q9O7iWZ2+LC+n88jvdmWJb/a01TJKdDlB+J8oxlLMu/BlHeJuqj78/0HV7Vel8o9VzTOp5VvY9YdWKabn1/yHY0JUCU7whCr2kUwHSbAilCWrEsOUQwKEKxbIsAIfKacPVk2pqPnpINvV1Lx3o8RgXjkLsBee3Sy6Sft3I5BmeACmp1OuVTonaMyVaGgfKQABF4tmz43ag/Cmh5vAaWzi6DVRuImcJ7HfP7pRf18evfEv76l4kKbhODx22eDfJjmXX6TJ+z7KRHvj9zKDqQxAd008DjM62U44uRSQ6/eo2Nj9Sqc8bmcg/T5PglbiXWZ11rmpdNw74SVrVHrmoK20iIEo24zE4CWcs7iDIW22GciLXURr5c7bFJ2frFPHqrC1QyeGfZtfkthqhmkUrPB450V1lUx2VqRa63Lfzrtt8O7/EB63evfKsrlwmHKFEIWAFAxQjmzoIkYMY3bkKNFCzi87Xgc+qcpJFUZsKQ5Sa5sQ/6qhb6K2UJttD/15I6mGac9eEG7NrJWuvo/zakZVkcCTCNJYRpdJJ2zLiWbFNxwiLw6sTQ7nZNjwn5fAjmNNI9sgEoierQEWjkfGji/5AFPCavzML12RdWSmrA7qvQnwL9WsCUoCQCC5jipR3P0twC/my9ae2S4A0+S2iDeblxl+uTaAGjNQndjThKYBKBEUfxxfIqfVnAce4n7fd0O+8ff69ldEzsxDa/gQWM7CEC8OhacjCtLWC06DIuC1i2tfAMO2RrVYEFHLioQe+1lwf5ldC7LWElFp03BgtYto1wgaIrZcGk/yFZIFm8sdv4PkdZ+Wbfh292uZ+qZ2+oA5EskDTVlyzoUNYydUubEyzJv5xpDW1cQ0mUBWibigSHXhsidiZpaThZ0Ovs6FUPF4h8im80tC/z7ND4N5AFyB4iAK+BvmUBWj83Llkg21q4Tr6WVSILXto6rak7+BMziXpkVdrz4y2NQRbIthEuUA2UsmAyniyw+e535N60P1lpuY7DBwm/1lO1Bf0Q5okEzjWvPvgjGNkabFk9oXL4N1IoRUX6J/Oj2TxuKFccA8R43ZJalwUHUr3n552v8+agYDPO22AtU+WSptixIIkT4tu5A8xA2QhJ7LTzf9ZCvlzaCJ6Dk1LsmLbNMauOuefSWt0zz+512K5qTwJ/luyquqj0+1rFP490eO25dNzK4oljmUt15U7BkOTPRNyA63QpNFpxp/pIN20qd7RsO3BFVIRaQIx62rY+SP/gSovrF2zHOVjcB9UwGyGyB48dBvCAV1gj/ZwdlwMiALJrU7qknZZe0EZoQJiyYwGuzjmwxXfd0I6e86I2rrxwJj9PlVXL78SBBbWsD2RaEyKD3iomapBxpEnrwKLYPGror1VFMybZsEvEFYgTXkgevNzlnnM3j12Wp/dPW+RnquoErPB9WCdgxUV94NSEEKf6Sk/yFDxO3WdKxxObaRGs5btndtvdbkAJSstBHMN+kYAyMVMcqNsEcIRIRTBVXl1B5XPCZK2H2/n5B1Ph/+c4guvFeL1u9fpyfZV/seusI37Nzu4EvwlA35KvaIpaFiTxRFBLg1G7g0FtPyRx045HW0PyXyotxQH+tPT8ns8Dg83dZr6Z3SrBY5qPyk+rRsMmDdHUKo9onqYre54NSTwQVJxpCItGo7JEiopW7NkGZhIcoYiDnLJJtClAXG707rXsWodL9M07F/NfpriptsqvLusShK0Hl18n/Thdk0PwCQjBZykE8uM09XdNyu0zYd6la663mUtj1lwd/nPeLv0n5YohigBBdTtQJXoIUUYm/peUS5yUa1Kr0b9/NnaEdl49Nf5VYnkEaUm56POnKxOBTYbIRHl7LGAd95hEI03K1TL/Uauk3Jun1xZ9SD/gmZTzMO3vLO+5ZCbl6srzYIpxCCkGn04DZt0+PP/v4bhaIp8ZFjcnP4+dNUePWbeF4b1Nbm+juW+dd9K3nPWnMwl7fxghkoMSDZJ120aYtn4j+7Nn7uqpddJHNDAzqqzbH3IGATYCrejIdpOL2Gl4IpYa1nprUnoyNOvAGtaCzzsmqbozAzk8doyqaNUS5Xo06niukEMVIk+SGwdApNEWMuBFsMPm1fJkx8wF4r9jU/13fL75vrTsS39d9+U6SGKm2JcSzL68BEkoSsglRg+5aeDs/YF2DxlbSpcGuNw5MJwcyNFHhgTI4wghn6aEPBYPcpeCwEPD1q/0WFFge2L/1PdzVX+ppzAySqAKeS0F5FBkxeZk0kuyHtHIJUXrNxAV7GjUMOS5UpVEyBaJwiMFAo5QTg+RCZOhAAztUIOXFJoW2oqDlxRCA617wkumFLCzCV4yky+hSW7JZPyjQhlEcwZulqw+9xsWX1znX+KUmtU1OnccAELsZkHRmKKgsYxc038Ph6fVraJBQ4ZcgZJrR84ue/dXvD4dnpRRCQQOT0pgAskOz7xvnIwu90f55XSa3mVFcQ8+aQ7PMV+aHxo68JpbfMblicwj3Yt0d3hS2AkEDk8EGj05PG9/cxwVlDyQPq/me+tXns8KjcXhKQMEz11FGZ6gR4enbW6N3FsLh0Mzbs8NZlvQHhuXw5MymBAZ9FbRs8MzcsnDrQc6rKfN/rlqzLlLh3ONx+FJ8SXEyStBIVjjjN/h+c/akU3PvdjiOXsZQ+y4fpBEfw5PyqQEAocnRawdj9bA4dnqe0jXj2bbvOKX1Unv7nu7OQkOTzRP093hSZmYQODwRFAh3eH5NvP9t5yBHTxz7+cPMk9gPapqh6cMAjyHJwKB/DjN+F0dns/te95ItWvMWFtrx53iFcuW69/hORKiFCbIE9WxKtFriDIn4T+HJ7HD0+1qZORgD5ZPYkhNkWRA9hPSHJ7o80dCAnlBAu6A1OUQZUmCETs8pVqEHhyezQYy2i6q6eO7cZPFqWUmNKNyeMIUyyGk2BzDUkzx/pbBMQJOxR9vX8EEd/LhCPkcnhPyGZGTp9c/QdJmwJo0CjZz6eTS3YAe3KuDn+SWtnDzKfq+r2S0uKSuHj24ZHvK4K2RRbg1UhMM4sGlMz/VKONaM4vy2vbwGNStt1F5cM3oMo4Htmpr05HzI9cZ4o3enYg2+Y3Vg0vplkDgTqS4KCFPMHrIXx3xNondkumzupPV9pXlcZvIgRx9ZEjw4G4lglyyUQl54m/pwUV7CCt4cNFmaQUPLlqZruDBRR+lCh5cNMk19+Au7uQZc+lhT58Va9ZsuFT2/hoJHtwkPHI1LEtn1O31Lz2/272964+OZ6h8F3X/NuK/wUNO6sgmIIHGNqp7YE3ZrVq9hHzgEhoRtfcB50qquwmcjYpifdqBiKGl+jsqK9+UijI2jCuxR07+BgiRcfJNk4y3aX7Ebyyo52QGbR3eOGe5wFfV0VqbifpLdZPUVLtJMA8AbArMZ3A2AeZzwJpo9IeARM682KKWp4uD37brh7uHp9+6QvyjMUTFfkIdd0e3ctSQu+PSOA2ibEcy3GdXpHFKpRiDaVlKjrZnH7kHQEnkMg7xkCUQvZDrQBL5z2r3vLb9JWZ+sYuNLb2QiXlnbK8D5CLppykHojRJlTtslUin/q6+pK4HA0/FbQll7Qhf0qzeqkH+BkmeG5omT57bSgckz/1MBfiSGsBr9ShAX1Jdiv59SYp1UzXrZmrWzdWsV1ezbqFm3VLNeg016zXVrFupWa+lZt1azbqNmnVbNeu11azXwVk3Ll/h+LePPqfMfe2+fPWKieEDjt0nzVeYu7GFG+vnn1454geN8r48MichQWxIGlGCWHCaMfgKTSkGTY6829w/22tMmVfqeknyoaPc7sbkK4Qp5k9IMe80QyZHfunBmlyQLvHbcadd02H900306FrbP4Z3tnl6tnfJ+P0m7zvWtSNh77sTIummgqQpaUh2BudIBr7s2Sz1kFf+pKefeNvH2WiGZGcskp3VIukb1bpG/houY0tX0/yevXtdIQHJ3oRIdldB0ow0JLsAkSxJmHul0VxPaBP1wNpq1SKHaoZkFyySXdQiGTQ6Nu76P23pKWt/jszMe/CNBCRdCJHsqIKkOWlIdgX3IpgSNv142k63+eMbJjMDLE9phmRXLJJd1SJZ8/hKbtutgW6bZt+vE5BFtSQByT8IkbRXQbI6aUh2AyKZuCe9afWBi6DsbqH1j19s0l8zJLthkeymFkmHHjUCjj565L5nSEnOU6t9gSQg2YIQycYqSFqQhmR3IJKddkdvnz26xDvX3elI8dfcu5oh2R2LZHe1SNpy2wen13hBn9M0JXnoiMm1SECyHiGSNipIWpKGZA9w9tl+AW/+t6a+607dzBk3OaZUMyR7YJHsoRbJSR8Ct0w8P9Nr+59Xp559+45LApI1CJE0U0GyBmlI9gQief2O6ZaVt6PpRUsuhxSuYrfTDMmeWCR7qh9zOa4H577ZVq/4+enWk1wZHUhA8mcqEZJfUisiWZM0JF3BmbQtmnVs43XRL802IeqJ+PUNzZB0xSLpqv505wS29Q0Reizmzmpz59KO2iQg+Z4QydcqSFppj2RjHM0cbMUwrlNW1/6a7j3r8qs3ngPWvSGGsoZCNceaMSYu6icvXOX4bnEyNfXMmPj847YUvs7TV2EwnxGC+VAFzFrkgQm2c44WNrpZ8nYHs5AWVTDmfflmDcHEGjomLuotHUlc/qpld3pDiQJWqytZ0fVIAPMuIZg3VMC0Jg9MsKnj6fA4Q2wXzdpUs07mbs+xauxrJZhYW8fERb2x02mk9ffVB495bEu2XDvDerIFCWBeJgTznAqYNuSBCbZ2og7FWt/njmMWfp3X8PPUR2rKE5VgYs0dExf19o7v4h4t9wUvZqQ+bv9PzsOpo0gA8xQhmEdVwLQlD0ywwfN4bdnPmv7OnusbjTzNahOkRk1Xgom1eExc1Js8sWMeFf1NLaAVvWUM7VpcBJEA5gFCMPeogFmbPDDBNo/fiJOem+pO9c0RX67p4d1zg4ZgYo0eExf1Vo91Z9MHVg+eeM9NcVjpfjqwLglg7iAEc7MKmHXIAxNs9qxdE/PYYcA++h5uQvmZXs3VJGApwcTaPSYu6g2fSgY3icBcTwjmqlSDZLFNsz87PyBwBz0pPbZsWlyTlZXOYnPRTx2y1BePZLFtxsTVrOiIni6PVqb9lvk9MevPr43vMZVRbLF/xtYn3vYV8nvQseEK+T3oAGeF/J5Zd0pHuiU5s2b7DmWMmN7ynwr5Pa99J7/Y/GStz+r+z2feZxYwNc/v4fvO/Oo6WOCVaRbc6snF0EIS8nvSTWUhDAy5YiynFO2fXY22h3F/ecOfz2qZsrijFGtLviT80+Hw44AGkzYHv+pH+aLyHk1lMXlqgJATzeWMpyLduMdzuGHhoGEeeOWcLVEPGc8Vh1d8Erj5/MkWCxzfrKVnuO7cvyqVF67pa2EwI/isDXJBECkUy840Hsq4J0kASWYi7GYnhDRMx54kyZRUTHGRgt2oac8ZSRXI3lej4Pyyf+8tzc1390nY9aD31H3/XiC9XSeaoenKqCdAkmwEuelARr0bkqSlYnqdEs2DbxYczlEgRhWFs0MRxhDNEQq5oeAiraY/rcaeeeDmv53+4VrTcyPQDFn6BGwxkvw66SwZhiOREI7pqQYNj5rLX9QilDt6dJSIo+DNk99RflpyIrgikRx75KIDk/LTXBQOHyvkSnUFT6Lc6W8pEnBConhsFd5eSwy/mgimLYcfEqN6BwxkBZor6jzxaN4Kobk4HKYRH5bbivpOaSZuKFck4LHB9eFOU70dvuecoc15YLasXu8eHFV9JljxPGx9+K8l0oOtMP2nENJ/gmHpDwiPV6CSW0UqmaqhUv8gjrRtrhgpV5b+V8rdYOojZ1Q6ykkkkwhsPpU9ShTJg9GCCRjB4SObDFw9+kxS71/e+520GQePP3BqeEKoyu9o8qdg+Z1yRR8nWERIQX7VUNBCXpn7i7HLVIUMPM1ujEnm5RrVTvrszT4zI2pc/dEq0MpGoTAUxMEWCuPN2WmvnLMTqmgczObzI8WyYmE2L5IfRpXN4AETfMBfMbPFY9J9di8o9RS3G9qf6K0wZEeta0rSmZCEmX0EmawMqmX8AUlcszHSXWGaAaW78g2oo9gijvTXaiTda39+3K/QncaUXLp01+5G02cWvmyBQF7mpDBVKj9KBSXp/V8H3D7VZRN95oshbOruXQ91lfRzIYlXNq5JdhqS0LOBXc3x+InNLxSRKn8gYKxpgS/3WZ5krLjcv2hv3bhY9YAFw4/CAia9qg6wVzzK2LxxLaHVHaHgvQ+7eZAAWD9CwOBtZ0hOonhRTQruqrmgBbiGpBRxJ4L1tFM/bY5YZ7gw4se+jam94Osc9aQMgh8FMKWRq+pIudRsRpM1h/Np2S0XDug/4n1zEkjZlZCUnQxLShyxfu325GbwS/aXi4ZMPNHwZdSwI11qFvkW7jb9Tgn/PktVZ2Zx+GHicM17R9j5ctiiKCFHqrXxpDdXHO8I3A0r+iWFHLXf4rnw1YL+pnc21Qa9AVZrl13XPO1YMjZLnnaM7RhxDpKEZmk3a005xjFC9oPBv6z9vW59HXcwNswUnJnptTKHxCmOZNtukyHJmCz5FEds54RFUoC0GxwmQ0i2B4DozI8/Ztfd4iVrHeXYvnzxTro2dCdf13sqB8ASAgFQnY4AID9LWb9run95br28w1lrPGYtsh9bdHBKb4Ok+/fPIEr3v5/+X7r/f+n+/5/T/Z8PWRkSsHMQI/ZDWflUwTfVGhwjS/fvl0EUh3HNqGrFpwrS/Xe7vsw7Nm6Kz/T3q5ktnKwDjSzdvyshxTplGDLdf+SGb3uY2067L+1y6Mf3tIznekz3r+nb/cPZXHuv9d5X+o9oc+EUCXu/PSGSDhmGTPdPHT33rO38th6b20+0dxu1YYge0/2TDhwauPeeNWvNjLLsnk8+kZEySCVEslmGIdP9ha3b120iWERfUBC7/YL/p+16TPfv/O+yH0WjfdyL6qcOy69xLYEEJBsSIlknw5Dp/tFne/ZtN7WYtWxXQq/NH8xS9Jjuf6HePPclwxnui3aMsB4w7uxTEpCsRYikRYYh0/2vDXlLO53lxFi3fYIZb1/fE3pM9382rX6nWS26uyUlfoylvV9dQAKSJoRIfk83ZLo/g5U0Z0Feqnfy85YTtvRy/1eP6f7Vhwz8SM/f47754ZGkMcHr+SQg+SmdCMm36YZM9y+P/NFH/GC/59yVP46nnUser8d0/xaRC3c2t4tzy865WJe2uyWPBCRfEiL5JN2Q6f7tn1iWj+/gT0vv137CoGvLRHpM958TnXcouJUNtFe4qOO34f7LSUDyPiGSt9MNme7fOP3KVx+Hxf45XbJnRz2ZrSatWqd0f7tjR6x9AvJ8kqrda7J94JQHJCB5jRDJi+kGTfdf1HZS+od1nu6FJ8zaDq1+fIpe0/2b3GVntwyJ95395N85zvbMDySAeYYQzBPpBk33vzvXbMW27SY+ey4xL9vFz2XpNd1/xc8Bh36mbnTb+6De8s/eoStIAPMwIZj70g2a7p/X9t/h4gMTfVZ0nfG1w+qv3fSa7r9q3QyLTqVdmStOFvSy72R+gAQwdxGCuS3doOn+w1ZEOS62+OZXeNvhQV4hf6Ne0/2v32mbmzHUiplIpRcluPaLIgHMjYRgrk03aLr/dasRe3af7+23qbPPs6szWN/1mu7PaZpxoq5zO6+iFR2ChflRh0kAcwUhmMvSDZru33edf+PgjHW+GUGBD1ZtuTtCr+n+oZF01yPfbzJX3F3/bGlESV8SwFxMCOaCdIOm+1/5OOuwrelzz1WbKI4fm/vU1Gu6f9ujzW13FLp6zRlnAR146kqGkjmbEMzMdMOk+xe/GdG90wr/pdVT25WHsrKNLd1f6ovHTfeH9XR5tDIbL1qZl50e9dz7k+fccQ1FOSkd/1b9PR6Rwgg2YGoEHqY9ZDdQRZERHNmMnygRlx9GFfDYIZzwSF6oNITJD0Wm/sCfEyNrYnYYOE/867Lpg4rGUn3Wrvy0oPXGaFPQq2FDw7LrmkLYDlbBM2EITeigTLDqdMrxTN272vvF3+oXdOSZ24wTmyWWb/wvoEOTcYPzp10TDPeaX5q34OH8tH6kdbVHfzEqdEWU3GmFZEjJyQSkTtkG82Mnps/2mmW64+EQx5ID2lCH/KPgDFGuInRchMcvLmQabWqVBXWSc6/AKVRUvIqIOnU9fp2fkCieGC/3ZHaLVR2GrEjwzKhmc8LyVkRHFSJZ0GV3YqikXNAHmf4lJNNxw5JJET00Y9FlLBG5ZRpFJXaoyHXDy3GxR94SSQLi8kUcoRiRy/BXqLA8cBnM3U+XadRxUFadpGZ32/rdViNapN+iWcQQJZvP7DzSKqzLE/ri94MuFj0TfNRVNsNEPERIxNJMjGwmnDAj38ywJMbN+2y3lZNktWAMa0dd80N1hvMCK5/jqesWrkuXcRpwp3g7qcSQC92ZeEK308wpMS16/fDIHtgtlbJwyDzVQWb+fA7VP5ojpP6lecpdPXpkhABJr4+Eb0bKY6gTwHl2X76vitubIfaYw/efd9js4Xy8r8bOUPu1pk3NZqa86TA23+4CbHxkapVvZyXTf/HnM70Z+eNBp2elfskvPVY14xzrqppqNwi5D5tqJ7usLo/i5YqpU+MelbJWHn3JGd1h6nZdD9F0iLIOweYxMNVuiRQb7VLtZCeOAB00H6jaKU3P5QAApzRJzOkIAPJzNOs3VF7Xne/+48/6lsxdrIJvVGGxuZ6U17mEymvCf8orWJy8qPfWmXJnqmdx+sM0my5pUVWuvM4hFKhZxqu8mkt1Vz2oruO61Ps3vrmDX+KxpQkv7FnhRqC6phISKeH/j+qafIJ2ZMXpAVD2spR3Gxt4n9Ob6kq21IWJGEtIxMnkq65LM3eaNBtxwn9en2NzH1V/UbdKVdc5hKprglLkzsYTuYRjA6qN0HZoQLURgJEB1UbgDAyoNgJEhGojgLj/uHtl5Kb4aO+CfstMXGsdaYt6U+x2HKGPQQGSW1noQQFzSK8cINJqNKscACJY6+lY/+qsTO/4at3m1H2TPkr/lQJJEKUlUlaVA4E0mksQxTb7vyGTxJnkH0/P35Lv4eCdf6zn3NjkBQ1JyyQ/MvJgrYLhXT33fJBcdRud9V5XXpwGUewQWh+lgXhxIURpUuUldMrjrqrekJPOAs7ByP5y8Nj3EX97Lds152aGWbsQMjPJ0TWRKMFEAkHrExIUPrwGTDTvtGB63N0vo/wXiW7U+ZRbOFaPieZo7xQJSNYkRNI82yDRL3QBtFGNbHwp5x9gbcaUjmw3ucSdiydxk6/POcFhb6Uvog022TXsTQ9VI0M+EFxV1hJx6T/kn8QK21EVZ4uDpS2avwLfBWvwKBbUsW+0OqTrHi2AKG+z5GNF0f6bK7GXodPPs4yqLcY8vD3w6ubaPh3sarBmZdlkTvg4comq09CXIwzjqO4AIuu2hfTzMPlHRcG/BaG81JGkTX1ms+2m23NDnd0X+JQ0YXmdqVadFRkylhOqvAnwflinpvSy5hNiJc+ROPJ+mJRLMXHkXZBkYQZA60JqM5EkBoDWhSSKoLUuPK2qslrXf/WZxl2fSZZWXJOilVyzZvw6bziKgcsfzBO+6d39Nth/6WA+av8P9AHTxJsBSNNkGL4gTQBJniEHdwNQT8iAJA9VSlaq6QgnODezjuOp0iG+RawFV2rfqG+T9LAycAISNRmGr0qD4bxLCOcNTKWkLnCCszOXXShYGfeqxLvEu8vk+zPtm1QGTkCqJsPwpWkwnJcJ4TyHKZfUBU5wfmbJ5O+dy9PKmZKNq850vrd/YmXgBCRrMgxfnwbDeYoQzqOYmkld4ARnaC7akdW69VIbv+npNkWzSz0DKwMnIF2TYfgiNRjOA4Rw7sEUTuoCJzhHc9WDC9us3Vu4FTdoQy0WDTOvDJyAhE2G4SvVYDh3EMK5GVM9qQuc4Pq0boWv10ZTdkLrY7avsLsdVl4ZOLHVaiYMw5erwXCuJ4RzVQa6hFIXOMFFasMmduoxbncybfUT81dTKIFzKgMntmTNhGH4mjUYzkJCOPMy0HWUusAJrlQ77FHXTDwx2Du7OH7U9faRrMrAia1bM2EYvnBNIDUJCeCcm4EuptQSThsVNR7sKp3fZ3XrxgPWeG1d1ebVkZcdvLXD00Kmx2M9p6aMKqhegxHNJkQ0LQNdVKkTomDLaGt3l/3it429F04TiId0L6RWClGsaQQjavgSNhjRREJEp2egiyt1QhRsHE3IFbbaPGqae/xfQSwLZpuySiGKtY5gRA1fxwYjOoUQ0QkZ6ApLnRAF20eml3N+uvTI8d7Swmen66JmByqFKNZAghE1fDEbjKiIEFF+BrrMUidEwSbSlTaD3s3bI2bkhhcP3vFsh5ZySY4o1kaCETV8RRuMKJcQ0dAMdK2lToiCraTuf48btaTuUP/UTx6PX/UziasUolgzCUbU8GVtMKL/ECI6NANdcKkTomBDKb34fWb1zj89N7b+8SrDY+zASiGKtZRgRA1f2wYjOpAQ0YAMTHRPy0CprSxrF4k/RCCRALC15FhaPtDC3yOTlvzXH7FBZ7CYqmnIa/Cc4Qtyf2cfJH0LE6h4K9VK5eGe+XjhHq3n2yihN8B8G3RvzgrzbdBhIcw4GuTXgscihF2/PrTOAf95gxusnX2AUo+EcTQLfpdgGnq+j0GCadXTiYJpW9L+C6b9F0z7XwmmFdxhf+av8PFbdY7ZNoH1wdVwwbT9Y3hnm6dne5eM32/yvmNdOxLEsnk6kVimpOs/mNY1YD3tQ+Fg5qzCuLg7PVYuNFwwzTeqdY38NVzGlq6m+T1797pCApxf04jg/JCm/2Da7JiZguHlOz037Jrac+TTLeMNF0wLGh0bd/2ftvSUtT9HZuY9+EYCnG8I4Xyepv9g2sfSe4c5NxOgDWXcL22o+ysV6q1cMK3m8ZXctlsD3TbNvl8nIItqSQKcjwjhLEvTfzDtZNaVXiHudn5rO8+rM/5Q6STDBdMcetQIOProkfueISU5T6326ZywCMN5kxDOK2n6D6ZNXtyPdtBhoV92wdUb1ZmfLhsumGbLbR+cXuMFfU7TlOShIybXIgHO84Rwnk7TfzAtqN2q3Dun97mnz1r9yGLirkGGC6ZN+hC4ZeL5mV7b/7w69ezbd1wS4DxGCOfBNP0H0yJm3cmnRFx3myHuuqT5nxOnGS6YNmxcD859s61e8fPTrSe5MshIk9lLCOfONP0H02jlPRdF13Lwyji96XO2V0NLwwXTbHMC2/qGCD0Wc2e1uXNpR20S4NxCCOeGNAME01jT3pTHvBf4JJmZd3tZh0czZDDtKsd3i5OpqWfGxOcft6XwW5GA6GpCRJenGSCYNpozaUv0o13u8WMCAzZfH5RiyGCaJC5/1bI7vaFEAavVlazoeiQgmk+I6KI0AwTTftYJm0n3d4OyLLd7pV7YfN2QwbROI62/rz54zGNbsuXaGdaTLUhAdB4hojPTDBBMu+K8qlaZT5Rn0oATvc5t9TtpyGCa7+IeLfcFL2akPm7/T87DqaNIQDSdENGkNAME0za8K2xsybrms+dujSm3abPuGTKYFjvmUdHf1AJa0VvG0K7FRRAJiMYRIjo1zQDBtGatPpc8mbKbMTcvpAubBw03ZDDNurPpA6sHT7znpjisdD8dqHOJHIxoDCGi4jQDBNMkdOHLi+dLaQnR1eqtSt1W15DBtPZ/rRwjKe/ttdFOxByUdmsBCYhGEiI6Js0gwbQXg9Y8uiVY75Pq8Ork4AlBz3+LYJrU34kbTIO1Unm4Jwcv3EMNa701KT0ZmnVgDWvB5x2TVMMpgRweO0Y13KNllWI9mmzqtxB5kjxeBoQf3SgC8CLYGJf6+Yqo7p+6btZ1kCQsU97VVILZrJcgSYiyAcNCPMiNfbxgn7o3bo6J+8xM3Pn6OX9M5wME70feeMEAxVhPbNOAhxDFLeu/pgHETQMOft7T9EFLJivj77cxu6b3Uq2D1aVpQFb+zr2J5/d7ZZk7Cl412E3GGA//LKK+wN5VU3WqvmmAPsfPzfr0qPGXDxv8th/b4HAlKdXMyMbPuRNSDD6dBuwK0Gau57q+Aa+9Zlk+u1qyPGutHrsCkD+dl9KbEMnuWQbpCoCeI29UXQF+yBkEuCuAFR3ZbnIRuwhPxBpTVwA0AyW5K0DHG/sfuUVv8V5ez3VCt977p+reFUBiSdQVgG9iXF0BcvH2AGGfK9OyhDnadrpC7gH0ukIu43S7QpZA+wm5DtwraGJi3hlrsiEX9dH1qjwT3fVqMR7STZ7XG/rk/jX6Xs5nZ4cvicdRCmN4pBD+PjGVBe8Yzc+cW1C4kMsfizlxPPgpIqTjHTKaXqR4tnxGPTsikh8G/xFei9BI1801//Qs9tpe5nLvHpzOXWwXEGaXqf4UgO6rshws5Eb4RoZyKnJsTQ9hT4gSiOD/DkI63gEUYk8t+4Ii36RrChpI4UWeq1bhVX4A78ma5ThVw9kpLRC4qe1k/6Y5OiKbI1LAEbKlzZSBZBdzG6W9uNsGmsmOcZz0ass+dba+dMtXpLUt6jsxm8FSsaRWyUAn8erKwN0gygBk7wwHKhlFEIWVqWEWlEaAQxoBXuPb1gblZnu9CiwaB9bvQEvSDXAIH3BIPeBoRw8JgHsSAg5hW1LiKMh4iDemhY6BJQys1fFU9x04UN37advve7JoeXc9SmP9Fz7Rzjuow9YmQ/eT7t3mICgldenI3q0IZTWyoIRwoHQo7nQ7b/om+vpCn485wV1X6gCldpuWDCg9CaGElJ6qJUbvHMzd2MKN9fNPrxzxg0Z5Xx6Zk+Mc9J/V7nlt+0vM/GIXG1t6IZME5+DwVCLn4F+pCsjz8CD/Eb+xoJ6TGbR1eOOc5QLfQpQGmJKjCriCcxNprSk5QK01JQdXa03JAWutKTlA6jRf/KfT7q8jfLfTO30UTdzhgXlngNYKX1RHnte+k19sfrLWZ3X/5zPvMws0JQ+RUuuVilZq8/EIgXYXqpptTL6YE4b2zxJNPmiHa0JyZY+iyvxPYBsSDQXwZbA2pGLB0AcBtiGdUnFsyPknL0MR7ZQHYWklDwLafNPkIOjdfNv56u0B9vpdPtPFu/7h7Xv9qbLmGzkuWIKDQGmF6Wm8DI8Qfts8Th+jHKRLhjbpzX3qXUflR9n4RvHEXAGPG8JGfoPmTY2b+bIRIw2+K4TNo0aoPAWI7dCEAas3H3/BjN/+boZT1EsK0WtgYEata7qPsyBKGgJUGtAM2w9RYkFxCSRMI83eNpwZRnbcoYUHVwgrJlwxJwIZwqAJfZY6NZK0+cx0K6x5dOpBRrNo1WbdNKz7laZWUX8y4NjJJYumQUuajQ1oM+FQJ13Z0myIkoqQ0xkYaV4CURIM69pSqHSWwTECTkVs7CvUGDr5cIR8Ds8J+YzIydPrnyDp9AZNJjuYOTl37oYy9YiobhfECYnkh2pF9kzXxOsP4tf67T7ZOX5cjc+QKtkhLNkhtWSfH3/MrrvFS9Y6yrF9+eKddBLIHktI9sn/g2TXZgZC4wrpERocdLMZTdYczqdlt1w4oP+I982rNgfimvxMI0OIqBgW/VlKermEK6iUqlGtvbaKRrX2oIkI7fEmIrQHTkRoD8R+xQnvQTVvbaZldno97Zv7xNmoN8WetvZqlQt0h2gSlAt2Nlq5KKykkz5xtvZO+sTZQC0vcTaulpc4G6zlJc4GEgEtljDvDNDy4Iv6cNIXYNS45ZXUp9FIa6JP6x1pp7dmcbcXbWVk1M+y4vs+OFFZpMnRK4i2fAmGEEV4hNC6fYEVRSF29N++YEW/pJCj9ls8F75a0N/0zqbaFdoXoBVweMkEB1B4yVS+hCYhpukBYiQAif92TfCo9PCPzPxLF2x948tm6tL04P8A
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38
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38
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38
20
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27451
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40
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28165
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31
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31
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31
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27085
31
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70
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27382
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11
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11
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31
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41
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78
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61
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61
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27041
22
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122
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122
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47
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47
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26994
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78
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27034
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24
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- Raise 2 to the power of N.
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- 00000000-0000-0000-0000-000000000000
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 3
-
255;255;255;255
- A group of Grasshopper objects
- 0b9f480b-88da-4856-9c83-6d1d5314a585
- 1
- 0208315a-ac5c-4218-a12b-42c843878280
- Group
- ⦿✺⦿✺⦿
- e9eb1dcf-92f6-4d4d-84ae-96222d60f56b
- Move
- Translate (move) an object along a vector.
- true
- a4283709-82ce-4012-a8b5-950c46998f27
- true
- Move
- Move
-
6803
-4032
201
44
-
6940
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- Base geometry
- f417dbe0-4a39-4dcf-9737-e57f0d97ada0
- true
- Geometry
- Geometry
- true
- 97a5f791-e1a9-4f20-b7bf-bca497bdd92b
- 1
-
6805
-4030
123
20
-
6866.5
-4020
- Translation vector
- 0617d7e2-44db-444c-9bff-d35d80e4d831
- true
- Motion
- Motion
- false
- 0
-
6805
-4010
123
20
-
6866.5
-4000
- 1
- 1
- {0}
-
0
0.5
0
- Translated geometry
- 121da76f-3b82-40b0-a2b6-62365e4ed90d
- true
- Geometry
- Geometry
- false
- 0
-
6952
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50
20
-
6977
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- Transformation data
- 1aa7ddc8-2b2d-47b6-b898-3fd430caa004
- true
- Transform
- Transform
- false
- 0
-
6952
-4010
50
20
-
6977
-4000
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 6f1a16f5-76e8-400f-b6d6-b31f775ca595
- 32f809c0-d4e4-46b1-918c-88686e051997
- ecc4fafa-b694-4673-82b0-7ce4302cfe80
- 3
- 2dd6b27d-0ff2-44b8-9abd-26174c019846
- Group
- f31d8d7a-7536-4ac8-9c96-fde6ecda4d0a
- ΘᗩΘ
-
5L0HWBPL9/gdkCZdRYooRkVERZoFUVFCEkIgoSvYiRAgGoqhKFZAehMBpUm3UKUoHQEFFcWCgr1XbIiIvcB/J8wqgYD6fvHq73m9j17Yz5bZc2bOnDMzZ1aI4GLr4UR3du9G/vBgMBh+5K+4K9PDgeG82pPOcmO4OANkihwGGPwRBKeg1xnQaXZ0FjiFH2JhFJEJ4PBw5JBdY1T+iVNvKbnKhw8ovzonImjKonsy6BsAF0a4gIUjchc7CXiYSndztPRypQM8DD5YDDJjF5YTjQmIInI0LS2tG73Kgs6k27rT7VDGYDC6pQh0e4Yzwx15C1OWiyud5c6gu6G3BX/5CDR39nOEkF8O33cK2RV4U0iEQHezZTFc3eHLgyJi+IxpTnT0t7Zh1gYkVdUHxfHPk4ORfx/E5iP/3o8tvB97hP0D+9cj+8G/uyLY/0be37X7+5lNccbg52g/cIc94JIHe/d9//l+TPT9mN3fT7sfm/X9bj2n9dzkeexhcDzeh+PR6LWwSJBmcRYv6cdzQxLYJ4cN9nNC9vcbwn/hkUGvYv8M34j9xF4FyPpeNlhOtNg/zmHTnneED2W/O5Qq+w5QPui1/SXZI2Eo7Z4HoYqAeoF341AfFC9bs6qqJAPr4eZIDQNNwQ1tJuCPGHoU7+LR04CGoU0AqWxrkcoI6w8vPCxgSWM50NlnKiC/ViN/aQjjW+bi4oS2oHNnKTr8S5Dq/P1R4O9wcITjMeAoHzjKrpvoA3DOto4u7NY4nn2g4BgmfjFJvOcw2e3H89k35qjSPOoc5cipxS0abm7rSqF5uXi4935tYRLLxcO13zuLkgxwFMYaFo0FmxgPLBg/x6ngiGDPeV7sIsPLJXFubnSnNUwvfQ8ms3e5cKYe9vZ0lj3DzVEFu6THIunMVFUH/6lg8R5Mdw8WXceZ7uHOojFVsKYea5gMWyO6l6XLOrqzjjNyNwn01kt+2DNwZ0F4FwGchzuUGjgsRmXYOtLoTKwpy8uFxUu2Q61Y2tOksas1llDyBXYyup4Kb+IQn/CPYgoO8Bz0tXl+5bUXGHg40Zx/vLGGqpbqzP/5jeFd+rwxptdLpnwOWD395FPT0ZuPWLYvxHzmeEl+dqH6vh+/BnJPDfTteH/l7SysXJj2LJoTiUVzc3N0cUUsM97FydXFGek23Hq/9FCoWYOrmqVhEbDmdDc6jWWL1C6ys61qL1GsVJnEs8Q+nJJ7z36yn+z6exyiGAEv/1HsvmL5Xs2H/YpEFunRnR2Qfs+9dyWfOSSVfCaXt++t8r5/ON4T0++1RvzoU03WACv3vbWPRd5SpOcYR5sHxwV6jrMfjZov0uIfLoLGPvMTy/Oz9DP3STQe3/ZuD2e9Y5uc4XgXZ3caw7nH3XjC03MXAT0XFvRAULsogHdhuniwUEcA/J9bl66AwzqA+2Jd7LG9KiLWpeeteMkEUFpQOBl14ezS09f1wmepHAlRNh2DIB6IzpWRUvSzokkleqTDh3TvLEEQL0Qa+69nP5pXqhctrLvpbpkGCUHDIFomltHWka9s4n+0u1aUriSMID6Imu6llSgt2aZ/NMdrhsgwT3kE8UNEp7aNoJXYk/ePkt53YJKdGIIEILIZ7XPw09cvpJLOtDK30fnGCBJEC69VI3yzfraBf9ryWdbp2tMRJATRfv0qEYalvNH+Kpzk9tsrKQgaDtHI7NH5iY7hpLKnZ9Wut189hCBhiE7lXpV5ZuVMqnE4dcGQr/E0gkQgOsSvSX8REqhXI+O/Zmpd2EoEiUK0sdbVWFBtKdVfbIRNXZtTNoLEICpV75gmo9hkXNTo2ZbxefF2BIlDVNe9kUV1vkWtPvGeEmgdcRxBEhC9tKgPXa9vQDhCjMl+umbaOwRJQpRmw2x9czYA77tlO8Uj1SAWQSMgWiTGsNBq0iZnax6lrPSV+ICgkRBtltWWkrsiQqmUzp1zvanNE0GjIPpyg/B5EeESrlhZW11iInM9gqQgMta2Vdtid8copzRIMtT3XSOCRkO0xjX+AHFhE66C7+0u2QiCB4KkIdoWnZ90qbrLqGzzzkSxOmcgeRmIqoX3nJ+Zfs8wLSOIHrTT+RmCZCHiL/WUTMlMMInRSPQf11ynjyA5iEa9uHFzvUA7OcpMvCXqMIGJoDEQFbcJ5p4wfUMI3lvttvb+A10EyUOUzsLGjckhk/epVu885y7zBkFjIWp8qz3tm/9XkvcEDaKixcjbCBqH3vAheYnVDHfdkgqCwZe1PhcRpAARM8ttvs5EKj4qOODyuzWUGASNhyiPdEbSRqaauHO5TGNqxeodCMJClIhbH+V38aFhTU1ts/6hqiMImgCRbmCN9tUmA+MD+60tm0zLhiFoIkSrFfTtZ+Bf4UNZRF6+eyWjEDQJIteHEuOn7EwzjKnSWtcheD0IQYoQLaWcmCtz/7bevgbi3WqHazkImgzRXUlTvdcqVKOUq8+oYve+2SJICaKgBxtssgnL9TOnTP2K1SYBCzAFFZSQs6eWVDUuy9Rxb4mYMrAAyhCpPwhbVKvwjZB35PM3ic4EYFKmQuT5RVN2tFIDJaPiBnNlyS4sgqZB5LHt3FWs53ODAsv9Cfsd3x9A0HSIXrdEYgjLDAwPCj+xmvvQl4EgFYiWRz1ijfW0Jla6hCVIa18DhZ8B0edjs45Gm6bqlimdL33x4A0fglQhak+NXCEwVhifs/fr+ZvHz99HkBpajJLay9OKQ/V2+bRIZV+PW4ggdYhSW+2vncktNvAW1JJ2mtYMSqgB0eWMz7enyckRD8YLPha4nbIUQZoQifKdfVQcdtQo4kBd0ZMd908haCZEjy7pqugcj6ME+0U8oTlLxCFoFkTapxonbj90nRj6VlTISPwoaF+zIfoYFGL7lsJHKQyY43n6s/0VBM2BKK7G40y7Ht6w5Cqe99XFrH0I0oLok+PDBUSDS4T8MAtnnUpfUA/nQlR+2tm+202WvPP49tOPSm8bIEgbom7fSz4RvktwubOKcU7b4vcgaB5EWz94BA1vbKf6Wyk+vI5hhSNoPkR6n18nXtVcg6t8n3n6oUp1FIIWQJRZPG1yfqYH+YC1TMj+dW32CNKBKKAluYE+oZyYYhmH979bkoWghRDt23du9rig2cbllzcbvPUVBYZoEUQKUgoOLZ4fSDuj7vDFJtovQ5AuRBQ3s5RWO5JBBi1WaqXduwoE4SB6xj/2rGn9TlIJn0zHzc6lGgjSg+iqaPfbVXQ/UpC/j8J8u/JXCMJDJHnN8Kqr9kRCXObC8nmBMzoQRIBocV3EnhVrcihRyjIEns/x5QgiQrSqrprizmNMKh1F2dVdfmMGgvTRKlpz84rX3idkXz93/1cudUBfJIi+CT7RvbH9GvWg2alhPoHFoAIYoGY52mV94Mds4+L6hrnTdW8SEUSGyMFDJG/GG1G9DJf42y1ZCqAYhuh7xbqUuMR+NoryM3+2I2nMBgQZoY3Idtfkt5rDTXapUF6OxUZfRRAFojLW0S9TSfdJcbhRoq5hrucRRIXoCeuSgpBIKb5kEf9eXoHgYgQZo0avcv5EZlCAbqVrzdiVz8zVEWQC0YsnV9qxt2NNSoSPLUgwuliHIFOISu4+u3DwUJd+pFj8SZqV0mMEmUF0Pm/2gsbLz8lZTuKVJ5Kej0aQOUQGDrSdMV63qdFzAud2DLt1B0EWEMk8kz2QuzrZpMTfMvyD7qKvCLKEKHh8eaytahY1s2ll6Zqv5cBiL4bozV37rw/CO/HxSUKshTbzSxG0BKKV9Htaj/xqjfJqX0jv0VEehyArtAtI60jVaCkz8L/2ysGxvc4cQdYQufCqjncsTDP0KUvZsDdi3xMELYXo6duVGJLWIqPimPNN2407AhC0DCKih/SGxNp4QqC3laRdGdkaQcshkn+wO9zFeDMpN1on9fKdygsIWoE2WL8m/esNIwxyC+PWJq//8BxBKyFacFfFYdlyKb1wv9NmSqsaqhC0CqLruU92Xzmjr1e65i1jRfNXPIJWQ3Tl3Sz6JW1p/eRpFa0f5enBCLKBCNsSF9i29wQxW3zttI1NIIgg0CCKKXebZnPfjXI4J3fOmGXTgMVeg1qbr/pU3vjllB05WuvCNTf5IsgWosjs/Wvx+4opkTsPE/Cht7sRZAdRoHEM48Tj6aQiw0+n3LIS3BFEh4h0PebJZEkSMac1em3VjXHAfNmjtndtxAwR76ekGEylrbOz6lgEOUCk9nn7m5Z39brFeVtMXrIqgd1wRG0v741Yt6+ryEdDrq/4cMshCUEM1BBNi4412nGVkPBlsaG+8+5LCFoLkb7ARKdPE28YpVTFfy1acF0QQesgaq3N9l5OTMMdqfM2dnujsRFBTIh27yhlOdnJ4DLGBLaa6voCQ+SEvteYeqUAwgnq7sTUeS1Wr4Hr6Iyq0p502UmryiQ1ll+9dIE8DUEuaPsaHrvpwUdvoveVuze+tOiCVukKUZhVasqsyPXEo8PFLIY3nQG+zXr0lePGJb+99hhfsaI6+7Rb2WQEsdBnjcK4vdtRo7tHe7xBwMu1wDi4QaRKlXebR/AmlCTpvfp4SRa0SneI1KMeT9m2ylo/b0NT9RrxMYYI8oDIvG74+wlflE2KTi5e3/qyVRxBnhAZvc/EjTkgQ95du97ff8Yh4M5tgGgcXWbZs+cLcH47GypHdbESELQRovhRY9doBvMRY/0XNdpOvgA8Ii+ITk5xnBUl3mG4U0Jc/V7hDWBFN6EmhcK/SVsx1agkYVXE8vMlwLfZDNH0FVvzaekNxmn7cYu8rosCu7EFNQ4zfIOEy8xJAdKO1rnbxwJ9bUXr/OlwlXX8xZRqkl3HnnGBjgjahr5XEbncXekbJYw2Jv7Up5ugwW6HqCn56TEL5n5q1dm80XuzTxYiyBsij/Rjpy65sEiV9rwB7w6dAZXNB6IVTL6o3GMmuAq7aO0QbYoNgnwhurM3TVBLj06Nz4t/KHxyBRVBOyCq19e+08zMpfhturPkxWrycgT5QbS+QyjrXsVpYpLZvJy1plKhCPKH6D7/CEa422G9Q/PNIvg/h7cgKAAiC/u7n2/ZLSfnz69lGqe93YWgQIiyDSNuNwtpkWKXOqxiHiOAZh4E0Yhbihbqb3aQUu+OsYsyo4EIMRiiqG0yyxce6iSXeih5MguagGceAtFatav+F5h8uPLgo4Ssc+4goAuFKF97pmrD2g1Gfj4eW8e+nOCHoDDUVJ4wpq8KtTcsXTxx+bCUUcAsh0Nk9umU2BnPBIL314K1svPLZiMoAqKpPq21U3nHU8OxBHr0h/fAM98J0beR4xMDadNM4q7KWndbJgGnIhKiSvyUvDtvtI3DDlTdOXetBgQIuyDinZUp/fRaulFJc4WWgYVpE4KiUMu2xqdB6aUA1Vvx9hXDT83A1Y+GiIeatuPhoSukI4oxZXlndUGEGANRkNT9YWd5xuqG1F0rIS39Boz5bogO6UTIfDujQIx9WLl1l8t1YCr3oHXjhM5e07vL8eXMF236r06oISgWopII84t3+LRMdjTKS2Eoee8RFAfRJ1p+ln59Kjku8eHZKQ2XVyMoHqLt46qXjr98yShbyWp26LWyqQhKQI3eWAcG61UpNZ9c0NYZWSOHoESIGDN1yebND4i+lu3RIU4r0hC0FyKrvVarX57VJ8Urnu18X/QS1N4k1BBNXeiXdew5OVSnxqEivfMogpJRGYq2L5zZMF336HyyivIeW9C+UiBKiSkz/GJSSi1ac0laf99Z4H2lQnSs+MvDzQGniHkvKqa/b+GfiaA0tG5se6RMkb5iWLX/0OuZI10/Iygdopa1o/fMNhahRn87JLFmixQw5hkQDdfhactPvWWQKaU9btErJeDP70O7GyxLd9gnX4MiNXO1LyuHA7uxH6Ikbd+rAW1H9IO+hNEJE+tA0zsA0Zoq4Ye8UpcND7w8PmwBz2oQth9Em4PM7WO69zeZFM40mGzz8RoIsjLRpkc37DwzbiIlL1Dm4/6wc80IykJV6XvxdFXxeOP9+/eu+EY8z0JQNkQnnmZ1XPQKwe99N7FU6Yg2MMs5EBkoLd5xgWZiFDH1foXW2KA8BOVCFHfKU2eMiQAxt5hvHaZoBvD08iBSVhG95nVlnv4+x2a/LLsUEGQdgmi/Rl791OVNRG/c2ulWdnNBM89HpVHvtnfRNkW9wOuzgkb4VQB7WADRZHxJSiWWaZLOXyx7bDILGL1CiGTLl5P3nNcnpgTsxgVW4kDdKELt/Bn+qbIXrXUjSmMM4uznrEDQYbSlqAh6rBT8Ss3EUzXSnnZYIegIaipfj3eqpx/Gx5+fLKewYzewAMUQKRwwPKi96b5RzO11Cu0KK6URVAIRn9vbfZkfThsFzXg83hX3yRJBpRCp77TUlP/K0i2+3Oh0elHENgSVQSS913THaFY2qVhopuyslIBOBJVDhJ2otu1Y1UJcplmelab8RuAtV0DkqsoXYN46TS/4SXsUefszZQRVQlRUFnva8FCe8X6ssEZZmiUY0qmC6PkbpQ9PUmmEspcyYdIPTgH/8ChEq+c8CMpeMk//qKLm0bZnlcAJrIboTCvz4QtrTWrwWTXSLhE1EPnWQHRxd6b6/PLd+qEHBT/h9lfFI6gWraLvovgEuoKpR/w7DaR5yp4i6Biq5VcySyaf/qBfwajP8uk6Cwp/HLUbnnn1rwUyKNFSJawLi03BDesganR4HZsl4mIS7WQ3S1raaRWC6iEa1tl4ddJ5PlKa150dzpV1wEs5AdH8tTs9jtIIetWGs6bWK4eBUceTEG2IMB95V8qeWODgySrOC9dF0CmIak6cHktd6aybapBU76B1EISBDRDZ0/2qOiqekNOzlxVfqjxVhKDTED2YGLn/gWEUIWHx1vqzM48D83UGogDtF0t8XviQIx3rth86SwMxbCNq58feVp79IYGQphr+Yaxd3VkEnYUoIfNrd5b9W1yo7ES1FZNFQbB/DiLamzUErRWJhJBDxkl5u+tAD3seIi+19tGrAl309+D4m92X7AIhzAWIXnt8sM2XizTKWBE/+4mKImjLTRDd9We1tzO7dHeeuZHrYSMJRiouQjT34fSFwRXbDP0C893Oby4GYfsliKqYY32uRG0z2i25LaEjqQn4Uc0Q7eRXcE56kasfv2zjgohPslsQ1AKRnJe++Kk9HykRY1drPIuaByKpyxAlexlefdH6wSBk39mVvJvPlSDoCkRLvWaubF1OpiRaqpcfMFsB/PmrqKl8O3POp45gXJz+DKXVcmTQjV5DVSmeFEQaU0IuCbS+vv3RZNC1XYfo2li76erLT5P3Jgd+UdOdwI+gG+gNP+8JE24M0au6u2Nf025D0JZvooJSUro78/ATSqBKC+aQ9rwMBN2CKMtsVARxlAYpOklVcKTGXDDodBuid7vlVrjpxRrGP+H9irvcCWrvHbRV1rqFdiiwqJEL7iu/GpvngKC7EDkyE19a81zRzxNpHvf1KA3YjXsQ3SwzuHzc9iY5bbTJY5OKMOAe3IfooH5HPGm0INFf/c6k4aQ3oP96gNooRaFNSRfrjYMb9gu+2F4J4pSHaN1oWbdl3sEThsHphXcbiG+AcXgEkaaKwp66cwd1Dze0Xh/VLgjq/GOIMOZxUynN3SYBmSVUVa/twLd5AtGx5kt7R8d44PemrqAb3sAAV6QVIoFLURnnji/VK4hw379y0XEpBD2FKOPghWTTRW8My6sPJPLJtwC78QwiQVWs+Ywtjwx2HbU4T3zN2oSg5xA9GfbB9UxHLLVc56WttXlNIIJeQKQkczl0o0KbYYiucr1NswNoRC9RAztewUh/82ZK4bXWxXcwiWEIaoNotNWJxc8vMEzi8ZNUO3hOFSDoFUTTw11H5NYUGIQ9/7RydDYTjKW0o2358abirFJDQrlZ5a4lG3XWIug1ajduqMlTVS4Q/SIFp15hulxHUAdEylGB1Ywb03XTkzLDhFYZAo/oDURfgv22mtfIEUsbNalXn5aDKLsTov37ykLup4UaVH8Yv4E/Whe4xG8hIsi/mmybutigTG7s8MXfVoJg5B1E+KxuXaqxrNE+ZxfvS5IhDxH0HtWyxD7CBNpEQvbpO0rtxhlgpOIDekOX9sfrDKOpvlLt4acSKkDs8BGiHRkyNJcARfJu/jfTmecuAVfkE0QFpzcnPRHUJ0eMlH68Xi0UiPczKqjP0U8XaRnrFt/gfxnb9GQ+gr5ANO5Kub6n2DATb5VjAW1OPKAefoXoyqIHk7e22Ontt9qqsOhoO+gQv0G0a/SS/fZW74jZrbalmfHXvRDUBRG/g//sCwoORgHSKu6yylqKCOqGiHlogWyeBIVQzNtdMdpuK2hfYDYNIJzSLvnGVDXqvvjdO5O/fQJOBQ9ExnyHL4nyZ5MC/MdG7jy+l4wgXojC89ZrSnTUE7PLk+sb47BgwGQYRO9UfQ4IzpllUq1oNsNc5uEZBPFBJNay59SKE+sIebQWR2UrN+D28EM0XeRAUFpSPGX3Y5IKY43lbgQJQFQ4xUizeNU0asqwHbj4scogNBOESFusUHLu+iCjUmZpZ4zpXDAqIgRR58wA8aSDktT97a1n955KBf78cIjwc9Ra6oYdwYUaqMTTbvh9QZAwRGGacidsTsrj/D42bI7YfiIdQSIQFWcLOJutn6Cf3+V43VS84y6CRCEKMnNa1blhMtk/4SFmhMs84MGKQZT0sKXsVlm0XtLde+aUBEcw2iMOUaXT3viiIldqmQZLdtfqPPAsCbQYXw5/oCQbG+/Zpzjv/bue+S+IrhCGL3o1gkkN0B0XunJ4ClDKCIhubLLFfjOTwVfxv/duPO8ILPZIiLA13aztK01NilRGNAttXvEJQaMgSikKOPX0+BRSQqZ3SJ24GxjEkILoWujlG3PeB1PTNf08woaZ5iNoNERb91nGH5YoIEdWXcLulgsEYynSEI0oe7OR2nyKGvb1mc+rPS/BVKYMRJO8fTcHtzUbRUiqkrbo5gAkC1HUNFGl0tXVlMyp9tUdkfG1CJKDqItPeZfmkYv4PWefVstJugI/agxElw/NiJEXX6MXWXV+m7/sKlA35CG6a7ImOXxhF6FASmrbJ35jUwSNhSjQYmrFJe0aXOKG5rYKewHQHMZBVD37qeVGh2mGmWc2lBRMu5SCIAWImBvnPhYpFNMtc9h0+fS2dmAcxkOkpndC1nHkdGKenWZ3mAABTOxiUVUunvHZK2eefhifVMMbjLMkgiZAFP9owXrrwhpcUnfivAsjzoMgayJEIUdW1j2NMTLxjquh3MiTBAHdJIgkVWdMIcW+MDg0YpmBsuBoYG0UIfpqxbI8JbOUUOPDR/TrVADO0mSI3m5njSi+oEFIUHi3xjp5C6hsShA1TXw6XiG0yvDA9G2zjZ9VtiNoCkQ75k5dedtjsm50ysEjVRU3QDNXhmjTlpN2p2+r6ucz9r5Y2K6RiqCpEJnOOTiu2pGK2/th2Izgu4J2CJoGESEuyZGX9zAu6bSe6hMrR1kETUeb+U25heeei1GSnTKTeacKT0SQCqrlT2M87p46Z1zC4NNQ0VMHMewMiNaN8Bgl88SesH/ZVbUZzYb1CFKF6FvkC7nFYyPw8VuuiJbQHgFvWQ01emvPejEXihmGLTYtSt30FnTZ6hBtX/RuA/O8lklZooha3SQqGJ3TQCv2uM9fw1Y3GR8O3v3BgtcWzIBrovbwvq569Xuqkf/dz1fbFRccRNBMiJzG2IZmr8/SK81XXR889zN45VkQnbMvqvP/zNJLux/ula53BNje2RA1Yj/lv39x2tCfnF0X9MEpE0FzIFp4e46gcl44qYwf+4zOyl+AIC2IaIzbtIijS00K83gKD/iqArdnLkSjL7xK2mrrg8vZOjL75AlpMFitDZFlSkkpf6GIns/xgLRVw415ETQPogabBJt3c4+Tc7fyMRVenwPGYT5E1BeXz7rxCxtWCorRZ7W1gAa7AKIHspVf8Zs/U3fP5f8s3P5IAEE6ECVWfXq43dHIwFfBZbpuNgWM3C6EyEbmzMGChQ/JJRVtjQIpMh8RtAiiM/fJezs7ZxqlL3nfaOQbABxOXfS9plauSzyYZ1RJOfzugrAhkAYOomOL5q64GJxBjZRI9g89TwHzDnoQ0VcKLSAxEg2D71y3Db778gGC8BDNpOwZTngnRiq6OU3T8rwwiIkIaNd208tjrEoRdc8l9TntD9OBi0WESLTyZHN4+yqTSJ8m5s1jnYcRpA9R1vvkTiNtd3JBrN4TnHgjGHMgQbRUfGr2ef5Yg4rIJo/F02zAIKEBRHt9S663XRSkeq/2Eg1/cAK4B2SIMgMeL8dHL6D6rKrPMb9ISEaQIWpFr6z+ulU5Q7cgW8ZCZm2FBIKM0L7yjUSi6MkIfb/Rz+fMmVLOnv+CqO6aUGDyyFG4oILre7znn5mAICpEExcZz9dsnWBc0iw2+f2FF1MQZAyRQetGceLDMkKZ6Nov5lnRYLDaBKKrAa+TpTXj9XyClytoj5CbiyBTVBp8ux7WMO8apCkLxCs9WSSEIDOIJqQ6m1+WXUXI30Kaq7Z2PhCUOURjIu2rlG/Owx+5fvGSW6cJ6BAt0M63+Wq3YeZUYrro1DKLq/dBv2wJUcAhiVxia5XBoezbOvaKoaCKLkZr74TAENqpJaTUiGsrtPHnxiNoCUT8H1dvCJ77jpK+uUY6NTwCxLBWELUaN40/uYPXIMMb27R+/TzQBVhDlL2swLehLsWotFgs+72IMhgJXAqRSlODQY7sXMNU0Tmibrn6YPp+GdoTLbXf8IZ4ixAQFrrkRUMDsPPL0cLfn3fFsfaqnt+XB1Uf1yyPRNAKiBLSpfXvOc3QL7vCOqIrMQX4GyshktkVbPtpykNd7+2TeJbofgMz+6sg8nVQGXPNrIhUmjFBq2iWrgWCVkNkt7fyyWqzEJz/FjmRba1SWxFkg3Y3rUlFb63J1JLuJL2xTp6gAtBQU/k4uyMj96NhlKZ08yX1BG8ErYFo2a3UnNsjy8k1CUVeY8eXgiFTW4i0Nq2ymHCAiQsfRSiKaE4FAbgdquW6ZaSqneHGmQuXOlStuBCBIDpEl05orZIZ8x6f3j3BvUBW7zKC7CEye8Ov7+JG0c/ymn3elXzYBkEOEFXcse72V3ijV+z/0eytiQgwsI6oUnAJEjaRmQa5CdYylbfjwIAkA7XztzqOXLz0Ub+IsWGS6iwmiPXWQrSmlaZ7q/wxoTgpP+qy71ngpq5Da9QzmXPLdhwlhPiqjY3fSgPrAZionU9bELi6IUrP59iF9Ade+6MR5ASRI6PymfKbu8ZHakY03/OrEEGQM0Q8G5NEz+yyMKmW58UlWYqCeXMXVIYd1mJMbzv98uI5R4elH9ZDkCtEp7NNAy+6nCcneQd0piqog2etR+uGx55DGyLnEcvreROEJFcDC8CCaE9rF8ZDv82ohn9p0nPsxdcIcoPozcKFI1pVlEk1q07y6GRQwfiGO0SHF05nyrafMDksX21bkL5QAUEeqCH6olMgv4hpuO+zzErryQ6gEXlC9EHd8sWFDDXjlIhOr6bDq8G46AaIdqYRVQ+N+kwMSmZmu82bB/rKjRDpKsniPfbJkguIwRt0NZauQZAXRJ42BmlaJsOJO6SkCWpUEdCbb4JINSvj2063sfreZg8url/droOgzRC9zw1QnHtjFCFC4sH4EpV2EPlugajqmshBzOEiw50zFDCBN+1AgLAVIqEDWsrPC7L0j44qoz5/9xDMwmxDLXb+3DdOj44RshavDd+T0gHqxna0pdSOwsi3CRodqbp0zuqMOXhlb1Tyk2jUd3E++ASNEhruzDwgQx+IHiqGteXEFxMPXPGPE44xBPryhSgnep0ez9cP1JTCqPHdNvXghjtQV+RwW/MkPnXD/AstLybbJYLpDz+IpFr2ns7lmWGSv0XunmBOF4h8/dF+OfVxUssaTaPyje3vGo5nP0JQAEQ1Z913iAu80t2VdFIRrynsgqBAiDZq3X0kpTCTvHduUK7VvHhXBAWhyKpcbYRTJ8mXpjtOYrcoGIILhujxhMUKp8LOGEfuGEHSjLYCw+khEM1/t7idl76flBC5j3+iIA3M3oZC5K5iTnQViybsS+p49ElgJeiywyAyeXCKT1zC0yAz4cH8rKe1YElYOOoSH/aOFj0tQg04fTdGWtkBLIGIQD2HTTW+89fwEqvCtVvK/bVBx7ETomQL1855a8PJpR5mVL/bHeCqSIgs3kbs27D8Au4QP211lPLKmwjahfYOiuo18lQJk6So69LhYYnAmEdBpMCKmJJxU8kgfszR5w2fXIFLHI1KY6JEeKXpQkqRZXnigkdzQU8UA9Ej800WMce7DNNP+uSu/OI7CUG7IWohNx/nP6BJijGLimq43gjGAfZAVBl+5oPAtCqDqvd+VW2q08CUeixEEQl21l/ml+Or6wkXkwNzvyEoDqKpjBDhVuXJusnpuZ3mpSag6cVDNHfbDouRD0/gQ+pqW28xx4OlOAlouGTLP+/je0F8CmGpbUyUI1hxlwjRScwV6mPrYEL6nbnLLtPMQJe9F6I5S9rcHntOMC6bfe/uvrxq0N0koc28jdn4gG8dJcq79ZncJBPgBCZDNCtwStk1Cz7DIxFj/BpMLUBLSUFDmEcthaZWo6gl+Funl1TtBCPSqRC5zTVV49002yhw3pE12R/mgRKmQfTxza0G63uTdaMqNpBKXZp8EJSOdgGMSGmbl/XEuOCK2MT2AlBFMyAKnZ2YpxE3y3inx+3Eb212wBDtg+h58/Fi4utgvZyc6EuhXl9uIGg/RIIHvlpr3t9jkL/Rl5myWh+EMAcgUkrJJ1pg9+AqrltsICr57EfQQbTaXLt8edwBft09n0+ssKrKW4SgTIjGCb16QN/2mlIhpNCo9NEPLEDNQuOvK0ZvVlyZYrjvesSMplWHQXPIhmiyko23VstXkr9k6NHd0xuAMc+BKEn19aHPLZGGZc7fIjGyisMRlAtR17xndw8LtOpWm9oFasU/A1U0D3VFkvnNFk2sIaQlnM5PoymDZn4I7dr4VP0yFe7qZRMZk/d1GooiKB/1RR/r7Dtqw0sMfv1o/ufPLQAVoM3BbPpWw/S3JO9LGtMtEqeCAeRCiAiv3BU2t2oY+p70F4rtzgVz2UVob76KtnZSBp4QtWv/PKlXVmBu9DDqYr17zPcs4LNJjvh8nqbZU8CKuyOoWW4+dnwfZQWhYJLGJX/sIhByFqOGiBJanrM2iLzz4417uWrPgbNUAtF1n9feF7M6TPKGm7TMT5ZTQlApRDe3p2zpcrQgel86QNNRLQbvVQYRa8Pdp4HjZukXOR+0cTLvAouuyyES+eB+geexAGmPgFxDZ+h5HgRVQFQ80/HGNIcDesHv/S7G3jYBNaoSdczCJwnUedCMfRJiVJ8csABhexXaL19ePenUYsRYfJsx5oXyKND0jkJUe6DM8+IbbePDrPpCgcp7YBC+GiJpHiY5bHcbKdYzRGjV8oPAqahBe6J7fC+3v8g1jFcavYlXrh3M+dZC9ACT/T79HZkaI/KlfLrgcmCIjqGq3F3lvXajL74ioX5EjbA5cImPo1GAWebdsmmL8akzltIXOV8Dq7jrIGJG3r3+TLbVILBs8qS19RWgRtWjdT5BRUsy9xW5cI9I9jVtITDodAKis8F6pwTbWOT8ta8fhWbfBx3iSYga39xPaRM5QigVefXy2X2cCYJOQbRfqjpeuEiBGn/nmGeeXJEZghogyhjZFalVWWJYuMUowkdeC4ScpyES3/JEaGdaEzFnpNRyhxJLMO9wBiJF8Xzfgg3P9PxXfZIolpMCg06NEL2+sausYLIoJSnqSZfqxBww83gWIhdS96fn+6yoh7+eumnGMxW4+ufQakO3ydNL79T1oba5F6vhQed7HqLYrLXqC0ctIu07gO2+UtCqhaALqG8T2FS1GfvKMLHBmrL+XDPoK5vQjsOz/N3+3bHkauyGG6pjh4NJrosQ2frfttBMEiTs50uSJYVMAp75JdSK2td776i/aZCsUalYsbUL1KhmVFByb0a2Hbei7JotcdnvQzwYPWiBaJgbdQwu4aRuzgLeJ0GUJOARXYZo5prHxClz5uICpnQ1EiWHgbpxBW16Rl6bz2m4kQ6RpDKevWavJLwK0VGe2SXjThob7vUXu+yj+AZEiNfQpnd3qcB7srxxWIHXlXWX4kFvfh0iXu+77Ska8w0OGYuPmlE84haCbkAk8dqfp8J+MjlcO4uOu/IBODA3ISIHiQhODLpFPPo2+HVCuQ+w87fQBtuBD+WzFdLbGb9reXq0OFhvcxuihslvwwts35tEex65bf8tD8REdyAaaftyTMQIql7S1DNdy/Pe5Qoh8RdHLs1d5ERRsrObO83Zlk7yYHzP4vFZfMN4WFaRbuC1K0tUpL8ZcEmgETJm2K7jSO4Rxrm7sxhrPNx7UvYw8A9M1uHBDFWyjhjmv0vWcaZGfdG2cjXYyWc54dllO9BV8kCk6nDz5rIRdSaxVqPzYuowYH0cmqzzzOz02ZS92/VS5NeZKm5kLwhCk3Wk914nK3dVEPMTxad/fZIExjDQZJ0vGb5LDq7DGuVlfYyfVOQJ5lrRZJ1DzXO6ZkgJkaso+75iWYX8/TQJUne4anJLsarEgfkVxmFdTU0VQQ52Q6BJ3iHT5Iz/UJPR5s+3LH3rYByi9kL18zOPPb002W1z4/Ld24pGMWaFq+POnhHupUnW5i6Vp+oihPwz+S/lC4xG99LkgwnzaLWqoZSc9ByNNrqEci9NFp7CeX6WlzWoeXJv51zJCXd6abLz8oOy9FFPKalPWlf6WeeAhBw07SqlaqbU5W+ipKM8vGXbFOKAlUfTrlzzKck5EvOI3tIROPLkbWBmFE278n1fhRGv5jMpqJrLc7GUBIL24RAF1Z1YXPNQjJLr92DX3GcfwUQmmnblXDLj+clnh4jZ93JstJXLwfQMmnY1rHLdZX7tLt3Utqh7RWpLwcAHmnYVsm3y17Yra/R3i5m2vTWVB6t70bSrje+kJ0x3jTPK2BYqmPgxGCz6QdOuvj5QnHeubbZhqbbFjPVpNm95f6RdfavAJS3bnUFIGN59MeO6HxibQ9Ouxo9Pagyfdd9gV3JDfRHpMxhWQNOu4o1eUGpz5lKiSqaPTV5mpsL7I+2qLUN0bMEdSZMiGzO72/ITweg8mnY1Yfix6epGHbgyy6+1u/ilwRAhmnY1ZoVr0kitdvJuvnKR9eJk4BygaVd3nr89GO4nbXDo2LpHkrmJwJlD066eTiGe/BK5CF+ZiFOz3foerMRC0662h8cJNbR/0w9Sac4/s98HzBOjaVf2oy0+8QRs0Q/kKWU5TzACvjKadmUSV+a7cZgxLn21w8gXQuxpQjTt6pTHzFlvtnlTq+7sv35ZyAtEDmja1fk50RuijjcZFow8WIk96TON90faVZx/S+nnJCdcXscEcTvnBFCj0LSr6HpGwEiZOGLkG6LmcYrOC94faVcLLo1viU6uwe3fkuvrtG4zCOfQtKvtdzKXHvSfbeJj33oLg4kBXRQWomSGU8yRDFXifv6Ea1VdS8D6kgkQ2Sy2kJOuHUUt2LXdaML2F8BvQNOuPod0+BYkHtU9MlU1YtXomWDWHE276tSeUXvzhTYhU2P8dAWtWIDQtKsjZP8lQllIAKO9ycekgl3472lXNlt5P516Yhxb8hF/uoW4up+lVBrIUu5gXeC/XsNrUFNCDb9XS+MbAks5bMgsJe0/tJQzLctiv5Kv4jMXPdPClV5y72UpXY+MyxcQdCLmX1WZHez7fEUvS5mTf/6Qb9tdo6I1kjZtYoske1lKn8XG7xoObNTPcgk2CNLzOt7LUj56WZ7SQSLrBU+fuhNjgH3Uy1Iezj/WZVC8lBKuEPq6MbZWopelXGw59pSCVTcuvm5W6nDLb297WUrLBXJOAYovTEKNed7uEDP63MtSbiW5u6zdr0Gq5G32uyta09nLUiZON1bQ/7LKuNAtMfHgNJ/CXpbyc9xGQjYZQyqSDtVp3bH4TS9LGR1EnNUkv1k/fV4G8Un94Um9LOXr7SNGXAigGiQajD9iOWPq+16WUpg65/3FpIkG+YbXFq1SbDnXy1I2mb4pmNFKJWZNSlcQ03BT7WUpQ6ZneMmbUkiRXgnyRZfMK3pZytL4ekF5QRblgNUVBcHL9Ut7WcqpR240dLx7YRSW1qFmYSUT08tS8uoURW0q32ay58N8Hc2g7pZelvL4S9M3YySmGcWrJCUJH9TP62Up3+Uv0RfO1zUqn6Q2wsF8UV4vS3lzNZZRcdncYO+EZvMrqytTelnKkLW4j2FnU8iFXp2jUh9RN/aylJiHDlqmxa/1IhU72leGLbjay1JiLJa21rZkGBY1y5Xzh94Y2ctSms/RiRtlMR13ZEWwofLONr9eljJQboN8wuGzRqGbaTL1L9die1nKJR6r8TPrvYwOC+oUSL1lTeplKSnnZU8mlY3QT67dbj/6sGZ3L0v5ViOaqN3x2uAwPrWiZaWiUy9Lyf8q2AO3NMQgyAy3/JyLgW4vS5nbaXJA66MioVi48M0xn2hWL0s56f2Zl7oTjpH2CuRi/a35RvWylNrTqihqeC39wlPkObh1RTt7Wcp1+hqLBQ6n6PmI+Ydtu316dC9LSbH0W5Gzl08/fs37AzKVmxb1spRHJ7TvsQmUxQWcirmmc+hoTS9L6a0cmT1JYZde5dQKy9hl98H4G5qguo1SvOyUU6Z+qZNWYoTVeBneHwmqM25i4+0+6hBDtZJk5lm5gWehCarrrC6JJ3pONUw4KKn0rH5RCO+PBNXdI7qN59htoSa9mNh5040Kwl40QTVjRkH0NdVg3XCsZYBp/U4w4IAmqCpk6JxpdHLUP5Jx6HoSZjYIYNEE1SweM8UGigU+4FLCasEFIiBtHE1QPRklKbCw4y71wL6ke8bnjoIpGDRBVTgg/aSoWLvhATNVSWvDiWDVBJqg+kVu9r5Vmta6R9M+PKScVgFhL5qg+uHjo4Pnxr42CFjofDFy4qXNvD8SVM+o1Ek3Doug1gS/m/BCaGQi748E1f3+WirJy6/rFSm4S55RaAH9PJqg+mRTqe/tc26GuRQZcoPdJjDugSao7p3nem/ODS/9I0yh0p1PikDkgCaoWrYoTVxVt4IUMaKo0eh9FMjXRhNU3Xg9ZIzHSRpGFb4tXNtZyp6gh+jBTL5Rw29XUiNSYtYqmxjM4f2RoPrWXM6GSJ2ET6ZI3mkdEQ4Wb6AJqtt2250fX3baIKjyWNKuFC8wC48mqMp+vrZDQ0zcMLTUccGZGj5gKtEEVYx5SbO8hZhxoL3e2m6fLeCV0QRVvnNZCsQdocScJyUZ7en7wIADmqCac+ZIpw5hPungsLxxaaRUMO+MJqhqeypEnhBcQvR/uk/p0unnwHyhCapZwaYmpgGWumHzthqlhniAUQVdtOPQmvDx5sGbRpUqc+btCC4HFgCHGljXnHOZpS9wwVolWa163mB5CZqgekGsxnnm29u4/GgL1ds8s0F3gyaomlc0nw+ZkoCPSkq80qWYB6oNmqA6t0XVao7UeP3gpx91bG2qG3h/JKgepaV3fQyJ1z18YsOrIh41YLHRBFXHxTe01IOwuDjqvoSss+vAkio0QTVS99MCTfoLw+hx2nFLZdrm8f5IUL0xHLPANbcTt+vRnhiL7MUjeH8kqMo4jSPkTBxlsqO93DIt8BGYx0QTVCesCssYnjCf7H1x+hcRxmLgs6MJqmUbcNdO8uGMiqadLzJPpgI/Gk1QXaf4XObYuCvkPeRXoa5Z78E0Fpqgeob/64fVuFlG1VI88tbJWmCkGk1Qnf/G5f2hUVcMEuiHxNylFoBxezRBVTcsQMd5Yi4pziPnZvO+BJDxiiaoGnZvEX7y6jxlz41NRzeMkgcJWWiCalVGZvlKiiqlVLIq/ZPrXDCIjSaoYrbcsnJvrDTa5SO/S/jeY2Ac0ARVmzt3VzzMxlIOOs5s83bMBDnUaILq/LYpuyvFRXA5qlfOWJfMAStd0QTVWl3yJcz7vbphz+qGrdYeCcbt0QTVqQ/MEiMUSoyyU1nE5CBxMEeAJqhetDxdOm24FyVJaWkM48VqUEXRBNXUq9svKinv1Q/Z+y42a+6wMt4fCapSnZ1fTzKYJum2z0LmFQZX9vNSQboqVy/V/2CrNU7ptIHPs1NhwhJbxYfASwW+GFcv9Sj9QLbzt0ZKuMqJw+qskSs5njUc78HypIGtZDg9VeC+AT+Nmw86n+hJY3rQ3OlYd0c61ha9AXBJaexf6ViaO/KjmyvdlmHPoNthXWks5JnudJaqgAHDzo7ujG4Pw8NVOn390wFK3E9CP1AfUX3fbUsP0Y4d+9Ak9oGvepjUkScQ9xCxH956/KYMTxe28nq2ylqIx6RKnhBhl341w9nVg71XjSAUMjfRjMCzX9/dBUuHMuI+nNP+bNrLmHRy2HIRzcXpb3041c++R7+Xg4dN2M/r2e6Oh/1OFkjYYAvyfbl66SI9uN9GYb8qIQwe4w0kZIBI6DWur4Tk8JjIERwS4vmJhCabonUB6+IMa4udixNS8X4qtaiNk/J1jBYY5V2+UiETN47FWS2+37d/tfiBfia9LqtdzKeiCfqBw7xVFywJPDIE0kNq0CDSK5A4IdojPRcPd1jBBAYR32hTF4az+w/RIQ1ts/tWruKSXx59a4+GqW6xxP0x+peXWnBWMvZ9+leynsP9xMRNDlxM0oByMIS1aAEih9S+cvCm4TH3RnDKgecncpD53tSxnojxc2ENJgm7B0ICFHwoJY28cO6+jqYXv29P/ohEdEcMJhGk3nBIhPfXJWLLYNkyB60bjVZXuw0OHKNm05iv6qUe6P4jEsFIDiYRG4kTsK8DvRPXvk61dc2Er6yPRjFLW66pZWZLcbyXKIHhybCjY9mGtH93JziAYKfCy9C+DWkgiKFa70FjYpl0Zwd3R6wb3QFsbur2S51b3xGWgYvYT/oc9FfF2qWH0RVDxPqeaxc3G6mGIr/VxUl87+Ls2KXh+pKLkjwCrz8RNfALrM6OINd3/cMdHA8egwXywXKrdpjRiOES5drB8Q4gn5HGHk5rQO9m/71ecBVR08YRNkpy7sZJwk/OzdsUeLCPiMDrcBER+/DPROQveGtmnUOLUQFrzazh1YlGQyCieyKDiQipQuKmYE9AN3fkfQk0d9r3NoDpu9tnz/gnCxEH2FLkezPufxKfKc3dEX3zYZvVt/KR3elOGMyPXYcFnNmiRi/CAo300hRqMQfSlIyFK5Ph/l1LwF6uYziv466umWdm8iVvHk+uDP/cKr0+ZCmnuozAdf3V1XN4yC0loo9U4cH0gRH+K/oQXOPiwqTTvhtATD/XBjUsAjhbW7qbW+/bc7U1wOCBnSaxrsAv4a6ZpFs0gcyrd3DpM/kfE+0Mqzk0I8B2aPqrBj0+5LrBQXOygmsvtoJtTvp5Or8plomWNGcHRLHQ9WHXXLtfkFTxWHpmslEobgf1atDuCsP7HJISgjftL6sf5E9Ii21ZBpQWYln6eUG/Ka1JPyIOEF3Qf1lcfYOBPpv7onftL7De7E+IjN34BxQZ0vihm4Qav35uUsrmPZdfPV2Hz8yb+u38Bc3LXLpnTv9IaBD5ToFnugEPyYXJ7NnkGvR/SKWhsxi2PX7Tr3lHfXv3IXQc+g6U/q+9oiLSln3qemK72j6KIO3QwT897VkHFSE4kCLWKAdMSuCr1i22VpTNbrwuzfG6EgS6rQsiI5aHrTsWx7Lt77LyD6CS+eZ05BXonj0jNGtobnSsK5PmTFfBsmh2DA9EU852yF8H5vfYG4zdOGNpLNtfG6HpO+E3aLn7KazvCb8qcWE8pkkGqfpnubqyKggd/Vuu7Fjk2VgkdMT3xEvApf1RMK7vfafE+7l8xzL98rWakUST+lsc7z2M27uyD/6savYNx/7XqimKxxQAQaXiMBjXfoKSZgvqt4Yd5PW+1yF2VemRW0+cyVVQGRd4Mm+qb9SvGL9o9BS3xHGctpN9N1Nwt/62sxcbcts5F8rFmqvjZIHHSMr85jCEeU97+iWZEIqrjleH3iaExFzR3LZB5AOno9Jzp/6OCjz+J2ThKj2YLPrWkZ8NQGBxvQ2KMvIXGBuas9tUKB6uQhEqOzmK720+/lB7kvvz1+85d1TnZ9+yv8HvOfwnRKI+ejCRREqhXavQQBZdLWqr17h5Xfq7Fs8OxSQujeWs+CZI+zHxRDwR6/7GfNgAch0F9pNHyo51AY0PXLzx14x036UXAxWlfxv8wX5VdCOQznABIroCRHT3+oluAeKzzP8t0yxCBmf1OGxcXy6xdUTXiUOLTbJlTmletaD1Gd1cAq7rX296Dv/MGvddD/C/WuNReIwNkM1TXH9HAeM9gS2b37LGoibs0waRzgu7dXKiy0abFOt63pjZfC+hj6mhu3kw+48uoMeHvF0ZQAF85CoAK7YAYLsaPlC7Wl/DmM4wzsaXVpswWx8tb+d4IxEzD+RdwIIoV0fOhjUc81uxgiKB4Yb0cl5g9oruDuyW1ww0aAD+rQN4AleJ913MNGD5+omdA/aT/XALF5a7Se/VYlxqbN/FSL9YY7/fra/CHiGt2OAE21NA/nIq7I35Yz3KO9IJMfTjSmRnO/pG9Hbg/1CVwgOp8sUSYwqf2if87oyz+mkm5GUcouKjIKrrbxz5BlDYBDyLDmYiaVgmcjp2Dd19A53ujHXf4AIju18zlX3Xm/UvUj+1sY/+hueqrgU9V/V+DhkF6Wxn/5Z5lAQPxyLvwXLveU+ubzVVbu8DnudpxPAVvjldYodlOeukBftq7vNAHPBn9rLvRNMQeK+SQFimXLthJcRvmfNbU47ibGHRkZBnYFE9Kl4468iMR3pZF5fQzAu0wzgnRIjItdwF1Qv9TEx9XeIhEBNSawYRk/rs3+xWeipVz3AoVyk5OnkZmN8uxufVqPD6rw+c9KvNZOi7FGtYRwpwYBi078vbskUD7ZDIQHbodCKN8k1bhuR7QEHw+aTNnAOHQmxhWBAovx5163HaIihIJKa0R361w67x6t1gVbDucBAPxOI9E0mqW3/JWPVdAcu93P2H8VDyqzIWwGMczyMyvsU13DZF6Lk/YLQspc/lWS5aTfR3ENmidlVYn9OxY9ul/o5dz+GftUDZmkIJCQeSbmGubq26N1X9f22BQniMNRCQK9cWqIrHCJ3/rakjWbaA0HqhbMdg9YylTeUqqO2OMrRMyhtiaLzBqCNTTUU4TRYBvbi/yfqBfiYwm5qjnfKVK/T9HmQuFX+tdWAIBFZ2bjCBITXqr0wk9Qykg3NmYgb683pR38klNAjkGsCwddnTrrknKlyinar1KiNWCBp8CppQLDmS7OxOZyHKIG50ZSGuaq978c6w5nTgKezb9nfg4fGfqbXvuushUKvsoGptOPu35wfRj60BNQ5xp2hd4dP6RvGpcdjtj1pye5bs+Xud4gpojwq4Dvs5sJsX7BRFMQN0ikvG866LKZTUK09jts/fKsSZMyrxfeVfT0379UUU5TzfL+VYI2hLZ4EbYO1pPYt4mC7ODliGuxvaI8IHQe6GtaU5I04+1s3D1ZUJVhaucUEgA10N5eEMLgUdqjP7m7CMTcgp7IOqWLwjsKvsAfHlxit/LEkEw77uLg5g6Op79ICcAyIIJxc7+i8GEH1TTwYVW/8B8T4n/KrCkTgN+/xEz5Rv/x6ahMdgn/2J5YvyVZ0eHmoSFN9nhTlelZeThnCS5vha5sWx4bsMKzcc532nMlLhfzVNT/UwkkBCEVxny2TwmNpn/browdYMTOSoj1h7MOLLlhkUGHIqV5GJC5hGWJUeIe7i0z9TE+Jr87/Z8//VUCBScX02mFSQevMPGezfWdQxi2yPtWR50FXYrZhTWwy33nZBWV1VHbsNq6Gqzt2/Esyhp2YlKpH98o5KpSnP+sg5fGr8/Ub9h097sT+huqang6nO++k/sfaD57d62XE9y1qRLgFo7cfC8UH8p6jbPsMi5asNc2POV5vTXnBOnf7Hy1vBzNFzuMy3vwPEZFuZ35pXUuJc4fFbglHXbpktNUUSn3xteP21lCbOYX9BeON+ovkO/oRw2MZmQOFgn/3eRNOUnl7qRw/+O9Kx2xgbM2x2BSWz4Pht0lTviKFYRD4EEmK36QElhLRp6LeJYQbw24i4adO7dVpwmXcUsi4lt8/kHOtjxxauLkykR+/vswkNIOfZ6HiGM1jzil5vBzs8d0eWi4eD44+R8t8Zb+2bjjtgafuPTPaCvyrfOD1MQSciXxriJmX2c5O88BibN/3cJHTFyy9OHEj9KNZPVhXZdFyUs8zeqB/B51FHLrkayjl6swTxhxnIA/uP3nwnP3OhLMbLnHuq1EhIe5p6Yx5hVN3/6kLt1cOkAumNx3PrccbhMaadv+VCifY0Xzu6A4vO3b88lyquJLQhmhh6KjnmcVfnNE5nicC+sL+zBI8PeetE3h8z6PsXvPnbztL3mvkbjhIoMsPFDl2exVURuVGFqkfnlRFL1j70rrB59pizrqI36F9Xv5M/oQyksQ6iDMm/o4x+S197q2LYT1ShauTs4o50XzRbBhL9KqvrICErElk4qWA1dGwdXVh2KlhNHbf1LHf2L9y91SAF4aAtycsIAY0a9x0ju09y9mvgARbuXlzWUvRCf0JZtR2DKcu1419oOeBWv5eE1TNRDpTl7MFa4zZIC4r8IOW3YOFrwx0P5J2f7VC48b+Eyv+jOrx98T2GXBYxaE393Iww/OLZnb/npUJLPoi3NTd/jnr16vPUneanqTLqR8z/atgLBND0BgrgGhcBANPyW54o2pWxlzxxFcCGQhGPOcZKxP3xI5Z+FLn7uk9Xxr6QS1fWc/xPCOBjxyACyA7pQB1Nccz/ubXDfXdrGcJhqb7NeAjWDs/9eIL72mGTQzp4uSsfUEVIDKQIrMOkkqDwYL3oulxK/KfyzZyva05n0ry4K6KPSztQrzQKh93AYNGxLHAnuMEQV7n3XX3CpSD95M6D/anM+65h+l9lPhWPeb0QZs1496v8OkhvtBCVueRAMh9uEet5wGMtIb/tI10Lm8UZt0jAeImK/MNi0Ji/Pjo+5kekZeJKdyZRsE7wHr8WTvXdcWjQYvUffe5zwq8K9IEexvoxsCZI997UL6xCgtqyh/3CqsHcoHE9W2CB1g/CeTuGvb2HGx1r60hzdqYzub749RmzH9TditOtylx1fpOS/mnOsQ5Czx36j3WgYMg9nid6GAMgkkyukTzi8Xx89Fc8Hn7EuLp831zsw4cP3b8TsWE5FQPGWTyYNBbWkeHgyET+cjcLjau/XQg67kM9+PXbbvnArjrO4MEC3qR/8PCd/AntZD4aTDvW/4J2ursx3b8TyI0nOjHc3BiIH2LLoSbUhHBVjsu+3OQruWlGR0R9Xij4PaniVE7PHbmsHfhB/oRyhAZVDmJN/r5ygH5+J7TTwjmBR7J1ghQHifFYdGdbr57JBx2siyttPZir0GD/9uMM7i3KLOEma5yyPGVn8PZvroXzHTlTxy173b9/6jgH/RPKc3w4mPJk/47yuE4o3eOYUOL7iQZ1fmjQzZHh7OWMuE6I+hB1ObuAjCoN5CemywY2BL+qA+RE29hzgPuwCvXq3qutH/TC8yZ8iGd1O/RZ4uTIbckAPPwnNNfwYDDNbXzwtzUHLrLD/GaMPvJHjD6oIUymEM30JwgQyo6UdDSv38fPaQgH9Jl+kCHXyGp8jw8B/NSGfm6VG9sQQj91BGYAP1WOb7PF8cq3JjVC+Y+V5mxW4XgrcbyHm7uLE9aURfdk0DdwuqlApgNlokzBMZGa7gZnvcE92BOpDnQXJ7o7ywvr2nNDNwmysy3Tw45OdjanO8OV6wM7r333xBysrP300IeLL0H+cXVhueszmO49Dxb+HdnL4DFBrSfYMwZc1mkvxmOuPRlwpoBrDEVCZePugornlzx6Id7t+aeeKZEC8pk5I0fNjOKsluhd+1fL7+S/Xmghh1gKIDldrnZEA49Rbv2ttZCjLXu5MOy0J9ZAm42M006Ye0+6g1y+X2+l5qQ+0c//pybcR1Z9bcQQyAqpR4PIKujJf2pz+WFBBWHIBU4Czs7t1NvdQnTo8aEH9dT1uvnZfVvfXlUIDQzQU8H/RXu7PZxXYNCt60YOZMb+0XC771a9/1m4jYmpHyTc9g6v/8PhdsbBMW73QkcaxIenPRZ+fjT+Hwi3a6PrB3FevKPq/37MUFBQ8B+E20/3Emtu2YzX3/34fhndffrzfyLc1t01mHYwkf+Adv6TcPvKh3RJ2qM2vK9QStL2rbdN/4lwuzZi0KYT/g8oB/M3w+2nIa0SGdgn+MLPDc8912qG/FPhtm7YoC0r9K8o798Mt+PI2ievTpytV7hYwkS9dtW6vxxu1wYP2uyC/rbm/mi4HXZu8svZV4bjMzo0RYUkxAv+iXCb7UMMGG4jhhD6qaMw/6fCbe5bT/f9mMRfDrdr99YPEm5jEvq5tH8k3F5qJ6K2YKUOece4m0snyxUeHvJwmzQpVzH/Shkl/JPe2vZQX/wQhJDeQHIDhpC6ifV/KNwubdLewbz4iJTFnOlCmfZq1ZCH231txBDICqlHg8iqNu4/tbl/O9yWGsiM/aPhdt9v3Pxn4bbrt8Fmt5u+/OnZbeGggy2RS63wMSbRXRO38KT9A+G2zbfB5gokv/0DU3R37tz5D8JtzTjl/XPNppjsdNAcdnr2y4p/Ityu/TqYdly//gPa+U/C7atxFPnC/BRyzIubXg8sJ4j8E+E2dlDlINbk7ysH8zfDbWFy0cQWK2FcjPfEOwVXuwz/qXDb+8tgylP/O8r7N8Ptm3MzJLsqlfA+6uFFihLjcv5yuH3v82Cai/z8tzX3R8NtiemTJmgrWhuFhlTuWuDllvVPhNtsH2LAcBsxhNBPHY35PxVuc3de+36F8S+H25ndg81uf+z6b2a39abjY9eaexlGJNo019yVaxvycLvvUvAhCCHjugebsTXo/lOz261Rt0e5u1saHr4a9EWiZOHtIQ+3+9qIIZAVUo8GkVVm1/+vZrelBzJjuC5Pt5fu28iHHcZ3mbJsQvvEtd8/58NlW0vwmIG2RBxHYNEQM2aOvIQLts9dfjE9t+/3YQUoLrbr6HbfLxq0pFwicM4TfrUijcZjaqvrkUqkx213EyuEVvQbHUT3++S+VyQ7WwfY9x8lYu/oiUTj7G0/f0k4XWpyu9YXMPCpy5SNvTAzZw0qnH/rWzdgewggUe5bBoJRw6O/NWo4zoLm5MoEXggiNTeGuxcanZEG3Ce1bGH7w6ezRQnRI1ldcs9jzgwqPUFCz225jHFAMOT+CSIiTNVgIkIq3T/gMbLr+G9sRyZuYUtjsvduH3gL28lSAfYTG3caZRkGG1jVT5YcvGKzb8jFkWcf/lnF7vuV6aGo2OWDVuyyf0FrDMz3XkEGM0Cv4PGpamZRqqVR/DfrFcHzk4M4HUYCw4HhjrWwZYFkORZnpzBYS51k7OHEzqdzg5eyzaAbg71le08huW9X0FdTg1aKPsX7payvgRqsEHoXcBDtwwXYD/ieugZ2MRNAnGN7xsYfj+AHO+Z/35BYhF35POx7nQL3AUdFZo8+EdOjuV+tc956GJtCpM5twvevc6/MffTkTAvRiUPZgZSNn3JWTXvHXUqqflqHu7Yc52cSxMzpTjRXbM/3xNx+/fusU3qug1rt+V4dDetM3wAOsStBT8LqL/V2fT/6PkgJ+6mbE//GpmZBQQNuamaGxwQF/tamZuJsbYMQhQWKw/2jfOUsJ9Kys6SsbfcyguPq7gzhbvIYi6WttS0ZhkXNcuX8oTdGDsGOZhuBeNK5mTrvsXiMctBvhSJiPeUZLIlZeOJs5waSK6novdFNO5yaEGcSc8/1/ZOY4fGfyce0svm55NlzlH2eKaZmn6pHDYF8rgUOJh+k+vyNrkCIvUOMZ48gFmD6/vm9Xc7ELGksB7r7YEp7v9LsULm5lFG5FXFlxM5Ozo0cBXqu7680ePxPbFs2d1CtPA34N7XyW8NyEmyD50q3g8aXq2KMzF4bNr67QYlhGi0+NG0PZ/aPAJV9fX/FwONDrpiV+B5zAsbj+n+heD1ig4N+b1MI+e8yAPtw2jIZP5PH5608IsanT1DCv71zIM671MEZAeB7btA/AkDBn5BIUOBgEpEMREco5TAD9OsFUUZvl8+fRw54+81dqO4G5xbd8Im//gWYBd83FufswLEbHBm2jli6s62LkyvNzQ18pQLLRFoQ8PNh9/9rAT/moYOWafFrvUjFjvaVYQuucitv/zrZc/w3thO/5g+3E+//iRhdPMbR/3/dhWssdDVAZ8/oGaUFm8P2lITrizOflwhPWGxpkuK+ocBkmudRzso3kGPzHfzXnb8QHtMAZKiux+VLKhgFtgx/y2ItQOOCni1HOLbAZbpsoLv17E8P5sLBzz98SuxmY+6flu7bn//VHU/ApzXYApPlKrDVbIHBxjxmoMb8z2y00bc2DdFGG5PWnZR9M9fBsGwPY4JtttvSIdhoI3XTYBttYDehMpf/52Xed6/0IZK5GN/npBJjEi72fcp2mQ1eD4dA5rWNg8ncuxGV+diBZG5cqn/+NKYe771Mbj7jueEIztCeCuYbXZkMW/YOh/07r4EkLU9FfDDEJXBHrmRinTju8kt9U6DcBvmEw2eNQjfTZOpfrsUOVqz+M2ic/FfFOQaPcT2GiDOM60zZTETYtSfEvu8IinqraB8uzP54GYcuwZME2YfJdmgdWGrXEMFTM5xQ8UqGKjZ9VBPKeQbgIj2f/epXR4R6jg98457ysIsLThksWB6nz2Ahdp6BuMnsESJOfXHVj6qgH31byW79hKjRj6d6ruT8kDkPrn/rwPVrHTx9Wse49mO3YpWiyHvXOa47tD4r/X9tHUh8YQPUqY7jFn1MQFy6Yyd6CelnIbOCBfhMqN1vSckpUXlL1N1nJgfDX4a01zhzbk7Fo9dfSno/lVK97QL7bfnBuilRh9xiltdnDoGUkGo9iJRca//TGA0tqJCllyu9t2wmkliIt+vogvj/LFUjOsuZzlQF57ipkgxW97hmXJfGuC+CTeh7UxjMNZLtWWMBfOlf0G9fg/53v7i3CFZ48MW9fp9H8jZmKxp2B+MwA3QHCWX3lgY++kiuKCuuKFx3n9Jng20aIvX+39obqMko47Cu4Ipeqyuwzi7u9J6vNbjTN8KvGXL30innZf8fe98B1kTW/T0qSscGgotiwN4Qu1ghQycUARHLqoEEiAaCIQhYARsiKCo2VOwNsSsgdkXsHV17Wwvq7op11bV8cyczITOZGZJlINn/9/I8+74yJzNMfufcc869p5WsKmzolnNsWrjF3m4/KV5FBVuIClX0SDkAcJEoGeWDSGvLeXdkGyOrZrzpo6M2hdwQ0AYoDIbECqVByOvjf7a1iyQuVCwEG9+wcegkBYFIhn13RGmAhfMkaROJj4rjbTIfT3ChTHuEj46IAZ8NG/nwpRGiaJ4wnCAUxvLLASBXVfm6ofx6kCRG+SpRGMoDTnAnzbM/VR8F0V8qiQFthuVvpY+/lTxBFlzC497GIMbsGS0ADYkVOsAQXASrWekSan7FWDhdbuNBBqyIL4bBcA0Fa+oFypA9bpTid72hUn5MheKTi6oNnajqjLf4oesiV8e35R574TVFpb+2imLJWyTLPwveokN3Jm9xVzdcPbTQeczJ41pZwpw8rZkFzK80ZcLcvymOOYcO864bAk6N2LnVbcuG+udPTP1IHDVU110qiYshYm6CY86VKI8QrUW3qil8HWdOBHguMINKZhdjSGxtTxccsOC40XD34kTvvfoDdpl/kLZESLgnS5ZfhFQbI5FXDEKqA1HP4UVIehjpZ7+2d9/esHTe1ujFrNpPL5obeLqMJnAGaFTq3kvv/Tb1/tzKZb/R7nfHkxdJKSBUNSUkHkM4j+XssqVjlw5ZUMcOh3hd4N5uu0979nIet2c+6xZUZf0U97v361L+Ju6umHGPhvx1ubOWLOgeLhQTeQqdQVxdFnQvd2V45H/DgtrRiarOaPNxbl2H1Nu7mptsOjN96v2zFixpc7L8s6DNY8RM2rx8HK7NW+o85rygGSO3rdRzWx76aZPlwYmDWML8X06lZvRafBm9Fh8c81Z0mH8NHXG6u9Fmn42H63yHIr8vompIrn5gxsZHyI8FWYTocbl81hRiJ7EJd+qFXg7bvlkyZraV86zTWbcG7Dh8VJMW6eoiVx+GnNyLIaiQMvTSD9kOwiqZlIyTXBVz4qLkAFB+s5OzFruGxOf7pXV/5j5up4DkDOtUYmRDBAK3YhDvowoTcFCANBsbWWlr/J61mr7NgGNc8j86Re4qzdBua3wwKxAFwIAyThKCAoCtrdZ0a0tHz4+T2mXmtrRZwD3Yviho6fDHVjV0fly4j+n82GDf/86PMf7sGNdqy8IJya5bRrgcfFUQF8DC+fHihj99ewkm+6x6bff+bqzPYBZORrfsYzoZDdlHdX5MB9K/OT+ea/3Qz3HgHtdtm1IsokbGWrFwftzB/mWdrt+7cxef9AnZseBjDgsoGTCiVLj3VPUdwJJjBlo/gEUlhvYAFkEK06dt6PSpzviHU3n7h5+O2uJWENV7xbyhLSzV8Q8pNo/V7x62+5vJPSz7hEPeVuchHzf0mtmKCe29sjc3aPOyeFAaO5BHRiV6BNzfD28/2qn2zPGzW7IR6XdkjPQ74pC303nIyUaDHcjJbh4LkBvkMUF+ZhsOeXs6yC3CD+zMPnXWdWXek4nnm01eQ0x6ck2IEUsEFHMi69Ig3Aa7A9/3yDPOY6P4aJ0BNjpdzUS0RQGvJg/7EOGb1uW1/deXcUsoX001HwsjqAviBy7kX7cETUmjcM+cYeizXsm/2w8J5S9C+d1+N3ez9Nt31S1/9rBPX3u7rmBxP8R2vetnLuQBABJQputaIQu7bokmPVZ6BggR0UDbeAiEIFtREisCdA7yfiIxB5EUhZxw+FIwG14SJQqjRPFyvbe166/zdsueM/NU414RRAkxVPwd1UF3FSTWrT0CFyIxDHBd0SvRhamEqkOZcalWM8GyM7bQBBXskkXyZZwo/jghJy4GPQcJ5YO2RrQT8bbUGd06Z1us9/IGmyPmzs1rQGqcgz2WonEOTmGdez6wXNhdKLknRIVdJQVaQ+Bs8fGteIWkkAwkJVgrOh0Km5ER4J39QhpisyOdGK34V8NiWQALFXVasBBRx+xPB4jG/gS3qD0ua3cD7oG14jf9phgQSxPqu4IwBkh3pjuNo+szdqCW4lbcEiGiifwTAQPktmJT4PliSXQEsveKxU5n7IlT4mM5YXyQB8uJjYtBdhwIh0IlCBG5X/7IuGhwK4i5KM2SRy/ac+BIMEQb5e8I31+VJlQjlkEmiQC1dsoJtrJ4CScKHOKrZxt/jrlz4+H9Vt5Zg3ePXnbhnBEjbKpV2KQPaFCOtbJeCV05ljsMNaunka1sWGErsRei/LJju7nWd7u50mM7zzr+tx3FDVk0lmQNxELFURZAaB7lkrCEIXE9jYylHUEesXgfwAwDjG4HPED27dO4Kdd8dt/wKwrpPyBIuyeKCCoujKggcqOjTZMqq77q4RnOCZKCzlZgFRO5JYpV1gtoI6ypoAEW9dTe4IXpE2cXDuEd2NLn2/pPV64TWGbkq3iQCtuUadXBug91mVh3oa6OujNMx0nN/cFQdmAS8DZ/onCg3hnO6OPOXu1aL+e9Z/K96AOhx1JJgTH0eapKSH6ZdaYEwnIt40FZ4i5GtYxGhVptgoCxQhCZIJTbRQ2AafqzzhX7Dudct2ZNhbLmvibtILEHq27TcEJ1gOPCCE4zEji1KwGnrdxKVVhwTdDxmr9358n6UZ4ZtR+kJ3RvsJi4RVEc+6tuUSpI1YEQuqZpEULWNOa3dYRo/LazK/i8746W7imbbPRftZx0hOiN8hAfjRPowlP/4ICrqGsD+Q24J4zsEMORXxG/K5GDYCuVcWLAikKULSavwPfCXLcpajlO0kk/OpU5GLvsPLfzD+td3hbU763qReMUDSrcYnqVyCvcVF0lfxgq76nZsQL6AkoYUDfr2dPfsW9jF4/cRX8N4R+edYnUpgPcTdGmA71cmaekH90vEWrgy8vtmt17UnLaBBbK1yIBQDGUQmgPQ069VDwlpkR8KxQgXC7aCURS+QBpamP7W+7Kp+mmyW5JjfnDC8uf7CMuSxf8ZtVlWUGq9Ey71ekWjeO9XbJGXQ88tzHLjAXArBgBQyRKK06U3GaAz3SH6H5US9qZOtQYo7xk0KrSGUWyNqFv3edYRDeZOP2kUSO0dBthhmtCjFSo6OKFOrXO3MB2Ie2r5gCTWBu1a87RhFPWbjPMxq0wailLZqOUsycTa9doibVU/nGmZnXwJjwlfU7JTHND/U5ts9u4LG46e8eQtoeIMzn0eFQ9QuVXWTeMIzGdtMsZ8ILMhwh0iWGGsRNEYxi5pZb3J/Te67R9xCirucGHiYme5iB0IANHn6AxtxC0ihNqUPzdBZZEIZDLAxjoYwQVj0E3hxU13wJESNSyiE9s+/KP2c/lbVu3reufwvrtKn9hFXZQfkpd0OvAUKv6JehOgyIhqRsM/WGmYik1rAV35imBAo4bQGIm8DYk0Zx2eB0zgh5qWNF/yXVaLDiNlsQLBdRGpDRujvlNB75PwdJ+bQ9kd+1A1DFoSxiKSnnsemU6JsutQwfvwIEei1/4dT0/0rF7VXVMXcTxBTDrUWX1JFmgMFf1SLi1EvsVp1thkuhYYVgcKh4gy4H6dDP+fjvou1dHbs7hQM+RSUv7E7A0rniu6vaXQGRdJQzEYBtJCdswFDZMJXSmUwnnzVq+79pL4jPr3Rtv++vTXMl9k2LE/DAhxzdOLKbQBXQOc2f8vmhwH5BZUfQEvlgkkAt5vAjkHyLbFKn6mmD3aecJX62tPI4+fzS/TwPbBwzvSdXfSYmsLrp/caExZgi6xpTBt2AYMqjy2m8CjBraBUIGuhYAJQkQo06suXTyct41L7fF6Sc2DPvwwpPoPqMPUnWf5ZcrW84pnw5BZkf0/HYd6lPraoH7hqou53dcKAQgR91ExxaGHMxo3Wc1kbNWICcliBoQLersupLHsxMhntve0/rtSwfN/Urs2o4JCHVIh0hlfRUjaBkwovXItEYdLNpy1pZM5azAyY0g1LPiOFRVcTdBDSRgLPIIZFOdKGc1JZfJhqkqi6SqfA2F5augnCrNDPTncTDT7CDMSl4yDHwF1Fbhoi+g7m/i493mel6m14645LU3wz+TGkKg34oiMIFerg4oDBihQEQcM1T2kK7n35C1JTv5N+TcNRbyb/qYljDk31gpIO+i85Cnnjw15Ojvpry8GU8W9Hn5uSM7kE/61sa3673JPoeG1jrkn2tZxgLkj2yYID9mg0PuQAe5xpWT9XHIa6BykrwbU6qcJLtnSpWT7288KVzXuIy35vmLX2eEbHupVDm5+lB38xvfTdwP16pdONVm2VelysmYnbycbfX7uiY1mefs2XpqPEKqC1G7KwipHkYiCwpC0sdIy5pHOzyYHukx2yqvc62npQ9USjGB8FJKX3R+51clL3e45j7aNsax3YEvLJRidqXjv513cef7u43cNusJQm++bEDkf2P5YT8slsQCdxEN4KjfbtXOTQQKMCNBxaL8AeiWEuwzNSoEqnNw3I26jj+c1vy58NGeLsNuVPqKKuBQfUjdRaYPQ5/1kUV2i/LsujsMJehrdHZtLY+2oYMhJGhRswRkBdLnBXVIvVzyWBTtt2u5qYnhL42nVSXWRlJI5DBeVRWSIQyV62NmV7VDoBUM7dOn9MPpsLJQpEQoY0XdPFLQt355t7aei5YOHeUYXveeDtdUGaIyw4BSf33VwwcmP62TP76u0MWGYoYvObDVw3PP6EMlUfEG5U05B/zyR2cODQ9uZqnNeO4gTIioA3IhMHRGXzM3toMiegggksOD9YlELBBBN1F3sBkb0uSf2H8815nLfrt4zTNKF6KWCEhrGEFK0NcsrtvaRST/5oqjqgqRkTcspVVQuSc5N7+usPYpqr/YwnHKklbEKCL+XNUoooJSHej4M6LTTh93jLpBNIbxdbAvT6/LF3jx+gtua/08h6sexKtaQrrJI7bEeK4i1S1egp2yqmcI06a2/vbnzVC3xab+f37wt6Z4JerYgLqwGcEQxxCB7QJlcR7oGGlQDWHarfria79EZXC35K5sdf7B2BTiYScaj6Ux6wRipWEqkoqrqhY3QXY0ACzqyQptECVmoJGtM0PBEiIrjR6q7Drem/Y5DnFbsvBjw/dBx6OJmsgVuZcaKCVSTbsEJqjUMMC0xkAzY1d5CK2rw4cOfs9WeOWsrLW91o/z4doLoYVgMgJCaCrFblAYCg2mh7rT6SHdn4SQ8LGJbceYZd7rp87VX/F5ztDqn4TwiAtNti1Bq4kpfPIgGPrG0UhRqTMJ4c3Hx8Z2Ay857fm8pVF9l4bNWJyE8L3IedXwxetdsg1/Xl1/e4ZBVdfcUy4kA/DkUa655jDEs9Uom0SNSQjNJb040rp8r+TGt4f0Db2Tx+okhJst237iOfdw3tG8R/GBl9J7LODTihEfRHx0suc+y5MQ2nSeM+nn3E0u84tq6dk2ntlau5MQEK6Ucpi4kqdTXCk/inOF/UkIQQeP3+fqP3ZON3AURvVp91i7kxDGwHJ1Qt33XwZDfWw125BpPAmh1wC4ZMvgZNf5G2ctiN3elFT8WPOTEMagKoIBkWMc3K73gGjs+n9tEsK3J636Xvyzp1eBY2Dn8WvHfKimSQgOnBKGSQifW1Q1Aq75JIQLI52uSnyCXQ92z90qOH72b5YnIbBt/A2Q3S3AkHYSAoKhlichkO251ichoIDRTkJAAMMWc0+6xawzgSuyNLHUsYwc5mAhciVrwRS5ClJg3osOcx3tqtSixarzGT0eeyzIOVO8x/3rIqbXYrGr0qHOJQxdlQSdS/7XVUnOnyuJxX3uFF1xnzmgm1k9scMLFroq3VxxZt4j21Z+K7/VvrdzTP0qn5k0g6F9gJ20/YLSO5dUc1elReK119Zf3OS7Y0KefYce4S4sdFXy19/i0qNxiPO6N2Y//K99fsUCSgJGlPp3Lqm+rkrkrHetd1VCJYa2qxKCFKZPe//H9Oly79e8Y9v68Bbmd2yWM3xwpxrSp2V2TPo00+5/+hTjz+Of3T5dvpfmtnlp16Tdj4u2sqBP/1xv0mzXgwZ+e8YMFty3titmQVM8smPSFIV21a1Pg8fP95zAjXNJ62lTe13fzpNY0KcWrb7K7g82ctsx+cAD37pCExZQymREKdKuGvUp2YZqXZ+iEkOrTxGkMH3ah06f6syegLycdLZ/1yNbpi3BMVscckc6yDVOZmuIQ14DyWzkMIlSMhv5bEUpmY28oVNKZiPvNJSS2chGUymZjSwNSslss3te4aQeeAIv9LkpDHLeWKaUzHYyO6Xx/olC9+l1n98adHjKPwjJACNlGLzzf2jh7pt/yvHuzuy5zRCSIUZafNC20ZV9Ir+MOyErfqk/54VKChwa0KOSWVvD4x0dvN86FwZ9O7agbpM+LKTA9WVNaoxrUGrIfd+UpIbc9kZJasgpc0pSQ04iUOGJHh1PfhkZs6pR7zeei/UOGI8381zKAk/60fFEhyZElLV1LfkncxB8cIVzl7Apnx5TvArLM5bW2UbNEtxJc17s9DSpz9rEHdqbsSS2LKnmGUuWIsuS/8SEiP50oqozdn5axjKDM2++u6V2ur7z3MbkSJbO/sjyz4KhL7ViMvT7rHBDP0DnMQ+3CPxSa9Zkt9m1CqTRtt6punveuqYhE+ZJDXHMB9JhrrGZNIVqzkw+ePVhc8aMJh47jo972iBvxVYlM0mWXyUzSV4xSmaSzFgl5yppf6eHZ1qed80tWXqpn72duZJztXcrN22n7wPejsi/26/Y1GOuinEFWp9SkPyWFaYk1PF1Xjc6otFrgxn/sGBcB9Fx0jBw6YRNcWNddv75Wdibs/UdsV8eFkn0Qf5HiqhK9dsM/oLHIKM5fjHCaHceJwp7hnoRxtNx3Xu8m5rkc+jBxts3DBKTGV9LtY0f6QPqLo0nXKjMqQTNu4auqJz1BMKQlZNKzJEp76K5XLTxdpagJ0Ec6PsZyY9GjBzlF48VjQ4c3lvATR/vMipK1uoJMcLoIn+CaoQRJ7C++33OhR4BSLbQZWIUOmklE6NuGAKtQmmUl5f/1KR7IIfIGNCwKk7Ml6KBSzFwXyh5s+zkjmXxOf18ji6z+Kfnu217SV1ZsYdQdGXFKdXBnUxG7kTqAncQbfRTk3SlFq5Roli0D3IYgU24CqFkzr4hMQXlI+b6JZ90cLE+uW0ykTnyJ1KcCldQqoM5TozMsdIF5gD+KDMHt0x0zOntHAX+JMoT5HVikVuF0WGJ8i6OAziSGP540PSxK/pbxSeoV9Tb8xuG7U34xt3Y+6+2j/b2JDZWMAlSer5qYTyBWh3MKx/ExLwzg3Sn8xCxM6deJRwcUMHB2EhRdGI04gQj7EPYFS2JBqxD/iWWxKNE8KsDIEXxE+QXKPkoWtyi7+CNv/vOPXlvtSTY7QqpvVokVZ41drk6OLeGkXMJWuccuAmEaDTKvWkkP+AWRUcwK0L7u2FHVorsPVMjJ7V6ebbjR6IipPWZKiisc2Q0LPchwI7jjIpbFYsqQsxPdYJo/NSmepMCTxz84HfUYOezNr0mkUJ/sPwgx18qnCASxhPdVIApXapcW2fQxihW6TAI7UgbIZRECWXSRE6M/IGx9T3l6WGe0QHCaGz/Qu+8Xuq1KH7hiSteuxptPsgpSe7A9K6qYUoi3SwY+Z8YiVTmJhLL5H+Yyt2nxd4ShvS4CPbLKMOXQ2Aoz5k2jY5yN+yOY4NWYqLvqJZH3ym34aqCpGZ+M25cTZv2ag6xkNkAf6qqWCoole2TfeJaGq7NE7ns71FnbZ9+fW9VdZ/cFIa+OSPIOVHqka4wVOqsUea8RZCSC8ORTBBKpSKaIRiWxt6jTGx/c91oUvfM9JM7Gld9CZOwIusIFrDKY8RqhnON6lz8HFMf23KBDwFn5/6a+z8NhJjHh1/kOnB/1kVtG9mqGuAbA/yj4P9NlN0e4h2K7bYznRr7X1f/f9XVf9nM0oKvq6Kct7+1NRNEZ39lhI3Nrv4CmKmr/1NudXT1L4KXjU25f8KrqI5f+9VQ86cslq+zrSPLuNBImKkJeg+4Rrr6N2+4J//g3RXw9LGWu9MORHlrvau/CSMqiNzozN5Bs0oi9rr6J0cOarw+o6HHNodVzi+98n7Vma7+h7hMrMvSDutqvKt/3efTt545Yu6yvPx8s8vH/+xPinTWdFd/VMvQtmVHtEyNdfWfNerMt3vNkty3c4scV2bMIWYjaKervwkjOIiyqbmu/odvOJw4klvC3VJ3pc+2jzdu60J/DAQhdE3TIoSsacxv40I0fpurc4eOPweUOm95YLP1Ws4bYm8/Y7QqMEYiRiy6qs9mQINzz4oQiajifqy5BoK4VBIXEYn4cLFC9KhGk+YQi4pFsxpZLnPNfOfa7QRvwGvat1Vto6BEVBdfZGuZ5YHgy4fBoQsZ30QY+sO9qpVa5hWvhVzFsKD86vodOmx+PDXQc3Gs5/SNJV3Kqj4MjORCecy9GzM+eb5HZt+fg391bLW2qi7USi6UDtBrAVNZnOYwJPDQyIXChqoLhBFSIbV/aTrLeFF2yAevGZdumhgXlbYglVyhN1KUXMmvs746ke/fn/H7m3to21lSSKYGjhJ4ZZFEIApjaJYTNDnUuPO3fO9kq+Ssx70c6xJlFX+AqqwqKNXBDGSxMjCj2F0n3B9Ik4iFvXe0RIaYL34YODtt5zAA2bIiO4uoTpyuA8IiJVJBJ063AbHjpTL0F2pv9WrvF2a70h9z552NuZrk7DGdaNfAHwiUJYopBmpWkKqDWSsZmSXTDrNIKwc8SiNv1aLioDs6Thoay7CCOp7tVcgJdoAXFC85MH7Gb39XZatcRXYkpcByRQ5qR6+ouBnp8LZgD828VEyTM3hbPiGNePXs5vntHvlw/7mY0j1a3fYCAFrhANyiAACoFo08UdyU0XetSPym5z7mkz1v6+V+/1g3GZSu1ephAEChOwMAwcnuuKMJQ/+tfJz+11qULso56rxxcl5K1LhJuTWWj/OHF1M+TjOv6s7HiX/e0OJy6A6nfZ/eLVgZn+mtA/k4T72YopuHvHQgqeDmzZs1kI8zbcOfzqa3tvusfuIj6P5zXF+dyMfJYuSOWBe4UyP5OLeKa7U9YxTLy5r6s/XQtk8P6kQ+jgsjc5rpAnMgbebj7NbvXWvh72Oc91pbOf9uPailTuXjfPBkYt4FT207uzqUjyPJ3BP8PryfX2GGf/ioWyOstZyPs4GRc5O1zrlqzcdZGuWTDb/s6jlfNPUa1+FsmU7k46A+BG0+DqIIMT/VBfo/kI8z7cGWYZtn9vRLDn9xD4KyQrWcj/PBmykfZ6V3zeTjhDf3WSSzHOE04+2y37gLQjNZz8ch781ZyDH5w5spx6TYu7rycXjTlvEm1I9zOrDcx6e1nUkd1vNxyDqCBaxWMmIl8/7/Kh/HlU6NjT8q6ijyzYULjviJXzwd8YYYKRkcB2on3aX8mEjVClMNwhetXESxMaB6TBHNSewsrzLl8EETvgjwFyglL0cUlbVvvb3rxrrZtw79CM6nfT/VSI4yUUX+DAMRFeanXIpFIZXkuic1pVLxNIp8mm/NEalsAoP/iFL5LuAZSjUNFIoRhgkFnoheT8Afh7JVzko3OlZqXJPWSSHb1V+TVj89se+Mng25R4rrF/TxrT1XqSYt/f37Zkm3b7vPiHw+onlLfT+lmrT5Xd/yubnuvtvs/2nbQM92qVJN2vmQIu87nZZw918Jz2h3sctcpZq0+Q182i91z3Rb1+r26Oxuh38q1aRd+nXMPddWn/xyv0yd08jlThelgv++vtdOL2lT7JE5dLB0afPZO5UK/uc/5pcE3Ylx3Slu0rcocGtXpYL/5c0fW4fP7s/NTZTcX7Wm3Valgv9ul9f/2Bzu7brZfO6ItYZ3ZiEkI4x0NPb6gzijUp85OVemdj3deA9CMsZICx3jni2a9NBzAX9hn8ZtYt0QkglGatTIrnWPWhyvnTNfXPcMHzUHIZlipFlGQeMGeQvccx8U/xLr4ngVIZlhpNGjOZufBXZ3WzBvzdRXEy4vREj1MZLjBe9Ds739fVM7xlj+Oun4eITUACO13x4efrv7Ra+dtet5rQ754YOQGmIk+1OPDrfqetIpfWJQ6PWVKy4ipEYY6UrzDqn54+65TR/4+Zdr6UaTEVJjjORR5JGwvDzCY+fjuObLat85gJDMMVJMi26mvlf3OS87Wn5t5LAmEQjJAiM9Czz68+51Q+eDNqKuX7yOjEJITTBS2MWbhu3XZbsebvFn+5l/OU5HSJb4y19/Gu456zsvbWBvyOXXU8EIyQoXthDztCPL9Z0Ldl96XjI4/BlCaoqRegzxMx532Ml377Qf61YlZ/MR0i8YyTRsvfmFqaHuR1J2nF+o134mQrLGSK+6l38Z8/qR79rkBwWn/ef1QUjNMBJX0uNzzutIl+TMlvvefNkTipCa41y+I/xydf4xbo7+1NdTj51JQ0g2GKnrNbMmCW+K/NaXdJ7yi8mLvxBSC4yU183y9ckbdbmZdj2iLT+eB9+Lg5HK4GLzslNLuHl9xz6vbXFYipBsMdKIVJuy/f0/e+zL/jjy6+E9XgjJDiNlrb+xJzB/GS+p45B057dj1yKklhjpxP6Eia8d+nL3lb3fv37CXiC9rTDSWKeTe7c2fOy7qO5vjgOu/D1OpbCzNURT2Lm8Uc/mZVYv4NlO5r+8GX5xFAuFne506tAi/MDO7FNnXVfmPZl4vtnkNcSDS9eEGLFEQJGtQDdVtQ12hyK/FO0THxvFF4sRhYe14FczPYGsDClfTfVMFSOo6wN94EIGg0uALqfytJ1haJe/ZhMsKrI35S9C+d261TXJ72Rdxpv7/kKY0eDxP1hM3mTbof6MOIcAIAFlrpsVDN3y1yjzoGcA4pxJ0XNCgRD0GJbEitB0DeT9RGIwMVohJxzEW+PwwfYujBLFZ2HNLg0cthSebmva/pbjNDtiuFXxd1TDrRUk1nfNCFyIxDDAleqvE7Fx1dRADWeedsYWmqCCXbJIvgzZK40TchBnRzFDij4u++OpjaTw5kbvrI9/P7YddCqBdDKPPZbiZB6nsM49H1gu7C6U3BOiwq4SndUQOFs8iQg/IBeSgaQEK8Bif/7H7Gvc9ObHJq6d9Dmy6ilLLICFijotWIioY/bHA/pfpQOblQ7k3UCNVTqIA5gqHf4YXB2VDg9nJGxKuJHqkV+3jU2L1lZTWTSWZA3EQqWDIIApMbx/QI1UOqydL+qwer3Id/+sriFPLLqt1nqlgzkjKojc6GhUpuYqHWbe2dmp4Gmi1/z1WWarLwau0plKh+LBTKxbqR3W1Xilw4smJdFLt7WB0zxP1F28/sRVLVc6oFqGNlUd0TI1Vulwenr2Np9vBi6L7nxo5fAipI0OVDqYM4KDKJuaq3QYG7yp/dDEr9ychHoPTPr9Qew3or1KB3RN0yKErGnMb/OEaPy2syv4vO+Olu4pm2z0X7WcdITojaID9wJdeOofHHCJ8y4xTxjZIYYjvyJ+V6LyUEhE2WLyCnwvzHWbopbjRD4rpX5vVS8ap2gwl6ZNCjaXRtVV8oeh58nVMBhTMnN2G+sBEu7Gwt9bbOBsbksK6IO7KQL66OXKPCXzo8XDMjts9Nh2KGfR4FM3klkYOmMHAIqhFEJ7GDJL0ShOZ4UChMtFO4FIiogvQqc2tueHb0s2mmzvmjmiOPRe6+PEBseGLvjNqsuyglQZYOVvU7vu22fNXTbg80fphKV2LAD2NZkJMESitOJEyW0G+Ex3iO5HtXzUgIGXxigvGbQqd+7uPzJ7JrgetI04vnVf+N+N0MIfhBmuCTFSoSJMiDq1ztzAdiHtq+YAk1grrT8/43nTOT7zuj//9drgXQdZYO01RtYe0RJrqfzjTM2m11U+fNXdwfS3us87cVPr1/X43G1okvaGr47EdBIYvhqjorQj0CWGGUYviMYwckst70/ovddp+4hRVnODDxPbEJuD9p4ycPQJMn+FIBYt1GBkWxdYEoVALm8yij5GUPEYdHNYMalNgAiJWhaRHCKs/IVV2EH5KXVBrwNDmSNK0J0GxQS3bjAUMqKqdYHOPCVQwHEDaBsMvA1JNKcdPn0MQU9eMAj+JddpseA0WhIvpKn2ue7Wzrp7yGK3eS12pon3+9Qn6hh0kCvFfDvseqW5HmbBlj0N+sO7+3b6vkHao1tVdUxdGEoFMOtxKWaWJVmgMFf1SLi1EvsVp1thkuhYYVgcKh5g/gX16Wad3KiEgFEn3XfegIcs4F8MI2YwVDxXdftLILKuEgZisI2khG0YChumErzpVMJ5s5bvu/aS+Mx698bb/vo0V/K04xgxP0zI8Y0Tiyl0AZ3D3Bm/LxrcB2RWFD2BLxYJ5EIeL5JFciTINkWqviYgZwQwvCfVVGYlsrro/sWFdg1H0DWmDL4FI+gOr+rabwKMGjq7UQZmDQIlCRCjBGDPiQ0TIsqu+y78c6L7mSf1jhHdZ/RBqu6z/HJly5mcAVHV5fyOC20ByK2jPJexhaGk4bTus5rIWSuQkxJEDYgWJXyL3dbGPbp4yfOQuT0v/vifr4hp4ZiAUId0iFTWVzGCVggjWg7Da9TBwl/UICgxRqiMQ0ul/CB7b8SlFYrtwWdi7d09RgMnN0IoJWUkg5+qKu4mqIEEjEUegWyqE+Wspk5UJhmmqiySqvI1FJavgnJnKsd5PLoKNDoIs5LPYAW+AmqrcNEXUEKR4tLN6J6RG1x4aJ80YukUPVJgAnwrisAEerk6oAhhhAIRccxQ8SAaQ6UzPfLJ2pKd+UPV0CJ/3zCmFvlZw3DIfXQecnIeHjuQWx3s3Lb0Z7j36ltzzLt9ufCUBcgFo5kgdxmNQ+5LB7nGGaD1cchrIAOUImETzwClSNjEM0ApEjbxDFCKhE1FBqhqwiaeAUqRsIlngFIkbOIZoKM87F5ZHHzutEnA4w81nzdbJeUNCC+l9JFTPVlIefOj47+dd3Hn+7uN3DbrCUJvvmxA5H9j+WE/LJbEAncRDeCoOuX1aFabnZsIjAeKBPN05A9At5Rgn4mlIagX3ient1b6iirgUH1I3UWmD0MXApFFdovy7Lo7DPECNTq7tpZH29DKEwlgDYIH8gt9XtBD7rRrtllznGYv4Y85feLCpqrE2kgKiRzGq6pCMoSh4kDM7JarKCSQ7hVI6YfTYWWhSIlQxooSpduGO2c+vGfnOpM36VnU290Qi2kRyUN8P57ZlOC2VTLHI5WbeIIFlHiMKDUI1GzCfCd/fF2hiw3FDF9yYKuH557Rh0pmfSvqxxc+dF1hG3W6QY7stjbjuYMwIaIOyIXA0MpAzdzYDoroIYAoTKk/BrBABN1EnVjp/OrU5ZV5HjP5x6/Vn1K+QBeilghIMkaQeIGaxXVbu4jk31xxVFUhMmhgkV5BGf84ffjGhMuey5e6/36ds57Y3c8Af65qFFFBqQ50WjGi8y0Ad4z8IRrD+DrYl6fX5Qu8eP0Ft7V+nsNVD+JVLaEeDbi2xHiuItUtXqJRizpyMYe6sQF1YTOCoadBCGwXKOsseTCUHlQNYdrEbkMb10vcyz2Yrrfveof5J4iHnWg8lsasE4iVaXGyiquqFjeBoXsALH9KGWuD7IaCNLJ1ZihYQmSl0UP1ven50izLXU5Lnjf2WTFITJwqb+iK3EsNlBKppl0CE1RqGGASBGlm7CoPof0VPO/UgWGZbsnXW4hvtvX+qL0QWggmIyCEpjIGGQpDocH00GA6PQS3vdDFcfpD3hq3tW9ljk2bk8+ho/gxHPk5DcV5OZ1r3lZ+Hx7tQetS+JxoYTy4JJSKwjADqZZaIheSMbwh1Um5ElldXB9xoVvRJeiceQqfPAiGQqI1UlRmaBhKfriLvA7lt5zYcefpayXbPddsbHt+6ebeDkQXCX2Aqoskv1zZmiPX1FV1zT3lQlcAPHl03SO2RGuUTWIqfx+mpmJTVszaffX8YueDSa4ll0LqDCNG/+T3q0b/sOuV4VO65exU4dI5boebv+yV+jRazAI+SYz4IOKjjQwDAzRxY4IciP4Q+UezruOmQXxphFDGxLSeq5pmDxq83qfAsuG6eNeDpLQQ+f2qTMOus64sEa44MHLFQKe4Un4U54pG5qs+qvBihAJM+VIypsOlAXf3f1npkWHln2M9w2slkTE+6P2qjMGus86YMbBcnYBjRtX9qgyGsqI125BZKzBANxZiUWV4nDnZYrjf20kuKVaGMTHP60wgZtXC8geoZtXihOpAJIQRkWbRuF0PgGjs+q6F3h9G9OvrOevDd5nByTvviTyW/0X1k2H6K3YYRAPOiY8UhUUibiWoLeTHxoLuCYqsGMz8q7f5INeEU72vqkzKr2uQJ5oeheWJqma/OMFQUFRVI+DNMFcDGHuRvCEOKGGSvwn1ZNlVbsYz//rpsmZYlwuHc9OIhl+fzrFREGra+BvA0AyAoQNVjgZkg2Kokcbq74tJlLwFKKFQC+QDxcrPB0DbQfDvCp+SM8l3CiWiZHuu1Q6kYF+LAmZFCdhoFDBsMQfSLWadCVyRpYmledrkMAcbM8zFTJGrfWIc8yA6zH0L3C6dhYrhpOFN+4leeTUkdqhCZ9fHiEVhaFmYqiKlQ9raB/EHEPMkQ+4Uc6IIT1FLT5K7YDC9lmrjLCJdXTiRfVDkJATOdMqDm+4w1GBSianiNBL3nHB7YuQJdCmBl+Av6aOXPQW4DAwTnJlX66ihS9Fflj6mHRtfwem1aOjGfqh6UZERA/l1+gfL3wd9XfARpo1bczeRFNE5IDsBTWYi8ouSP0+X/Xo98OMxz5k5nqHjnk8jDhqs5ay6OpxVVkct0uroYxLS/6RDX8+tfccujHjeRlbV1dEMhsYAdjpQZS+ABJ0+k0qUQKrsZMkmUBgmQTS0JigNa5d25OunOJdcj6/v12xbfo2IElcVJW6lKPVrtS1r1e2bngfcdg/YA+eksYBSA0aUyiaWYDKokCXGbBd5b0LgGKkBEDnrnWjD5I9StWHY9eo48EYl5jPVQVOSL4oUpk+H/Mf0Kbl1UE3p0xhGfRrzP32K8aeRwYkDac3n+K77NLj/qpsRZSzoU3JLKDb0aQyjPo2pbn26lrdpetPS186rny1bUnh02EoW9GndFR4wN/mQ0+agD+NLp5QuYUOfMqJUJqlGfUq2odrXpzGM+jQG16fBdPpUZ/YE5OXETjJbz1pN32bAMS75H50id5VmBLCRzCZhTGaT4JAPpYNc42S2BjjkNZDMRtFvD1f1FP328GQ2in57eDIbRb89PJmNot8ensxG0W8PT2Z7WV5W9KHDKqes4Vt/MfhePFwpmU2mtyPgFO8MN5N355+tV6OaK7Uz9Mgolf7ustcrr86ZEZIt606r5LmBD1EKJrm/Hwt5biGsiYZxDYrGv+t0SdH2EYebnCmgwhM9Op6QGyuywJNhdDzJLnw0bPbTz55FhfuLdo97TKwOrOvPjxaKVVvI0qnDds6cGHCHUh9sTrREJpS3JJIJE2QceftYyq9N7gxJ8Srq6EjjwDCpRCwOAHYOXFQeGUvSn/l3U27yh43lHj13ynHIt9pf6fSnwZBYoTQIeX38z7Z2kcSFikGGF+hVC9oFCUQy7LsjfgmIjTxJ2kRiCd5MWEXtnuBCx4SI2nWEoaTZsJEPXxohiuYJwwlm01h+OQBMFVG+bii/HiSJUb5K1N3lASe4Mw8JS+qjIPpLQbWhTCR/K338ragWlJQf7xktAM26cHhrGYKLIGCjdAn18MVY42P5NgLMKhHxxTDoIKVkvmRSIT9K8bveUCk/RnEPJqrD6URVZ4w5uU8pSwd8ZPlnwZq3imCy5noRuDUfofOYkxvA6u6hKjSGCfNHinKAkXSYa2wmTaGaM5MUnX1xM0nR2Rc3kxSdfXEzSdHZF/egXps0zA4dmOMxryk/pEXw+FIlD4q3JGuZXZCdx/q/RwyBl7ZzVDGuQOtTChK5XTALxvVXOk7q6FA0clvkGhuK1mc201C0K7OqeyhaYMdTqSeedvTJnmDRdn/BDGJ7Vu0MResxm2nEDGe2Dkx2Kisrq4GhaC//3Bu6YOcv7kv7LBh9pHzPbp0YimbCyJ3Ps3SAOzUyFC3mWtDAFt86OWfXy+Z3sfl+QSeGoj2dxcScK7rAHEibQ9EOvJ/3ckbsa7hw7HirT1kXiJnK2h6KdoiReVu0wzzdHIp2fEj3Ng/OL4d3NN1xKMJzLjEOWPND0bIYOZekdc6Bm6ptKNqg/KYvfjk9ET60+Zh5q57bif3stDUUDfUhaIeiIYoQ81NHQTR+6n9pKBp5cIeWh6KVzGYaipY9u4aGon1c3L/L7S+e612TjEoMUj+xPhQtMDx5+t3RbeC07T/HzF/z7BsLg75OzGYa9LVjdnUNRZv8toC7sOl4nxmr4u6OWdLiBetD0cg6ggWsshmxmlWzuwRtD0UbTafG/te6/1+17ifPO6qx1v0TUpla9/dKrY7W/fkNY5v1zZ3tnRbR2q50ZiMuizXqbOvIMi4kTWXqdD4qtUZa9xsuSndZveWBVy6UUnpnQoS91lv3ezGigsiNzuwdNCsXYq91/1/fmh9uavO7z9zrAzovNj57Wmda99sxss5MO6yr8db9lvdEjWIP73OfF/rDpvn1Qb9puXU/qmVoe68jWqbGWve7W5tl3z0+2D1PPPVAqdkXonbWTut+L0ZweqXWYOv+Wmb3f5pLPL3T7XYmXLAZsV8XmmAgCNkxIoSsacxvGwPR+G2uzh06/hxQ6rzlgc3WazlvuhO7D6ClfzESMWLRVX02Axqce1aESEQV92MdNBDEpZK4iEiOYqytJh0gyDMgad9WtVeCElFdfJGtpdNcBF8+DA5dyPgmwtAfaVUtxzKveC3kKoYF5Vc3uXrRe6zLYbddv67lX1y52LLqE79ILlSsVZ2JQfHxzmlR9/f3WnuGX1UXaiUX6g/QawFTWZzmMNRurkYulIl8+QqEEVIhtX9565/LSz9+FfvsnL9jb+rKftGkuir0Roq6Kvl11lcn8v3NGb8/NFfbzpJCMjVwlMAriyQCURhDR5xJe5ZPb/fC1GfpjPc3xhaVCYmyij9AVVYVlOpgBrJYGZhxK00n3B9Ik4iFvXe0RIaYL34YODtt5zAA2bIiO4uoTpyuA8IiJVJBJ063AbHjpTL0F2pvNXtn7pWcLi/9NncvPtA6ouM2ol0DfyBQliimmJpZQaoOZhUzMmuXdphFWjngURp5qxYVB93RcdLQWIYVdAdaXs/seS3fI38e7ZT/uV1aVbbKVWRHUgosV+SgQPSKipuRDg+xnauZl4ppcgZv6wzvoLhJv3XumzbVnXQ7OnCSVre9AAADHIBbFAAA1aKRJ4qbMvrWFDvu9rO8dqeLe9b3X32yJ8vakkxZzZYIAwCupTEAkJufhjuafOi/lY9DHh1eY/k4aelM+Th26dWdj/P389BR/5QN8i2oP6EW78i8wTqQjzMrnSm6KU3XgaSCy5cv10A+TuZv+5aPcAvz3OQ/rKf5hQt+OpGPM4qRO166wJ0aycdp9ffiodErazktWtPltJtp+G6dyMfpxcgcO11gDqTNfJyGkv2DIwzNPLae9YjUuzDwV53KxzFjZN5XrW8TdSgf5+HigI42Rw+5zd++Z+DiiaW9tZyP83wuE+euaZ1z1ZqPM6e34GBC/ye8LcZdImbNmrNVJ/JxUB+CNh8HUYSYnxoK/R/Ix8nrZvn65I263Ey7HtGWH88HazkfxyyDKR/niapLWy35OI23GdwIeeDjvWLAH5ZbHrZawHo+DnlvzkKOiVEGU47Jp/TqysdxWD7zt5D5y1xW78leNWKP1TvW83HIOoIFrJ6kM2F1qWZdHW3n44TRqbHxR0UdRb65cMERP/GLpyPeECMlg+NA7aS7lB8TqVphqkH4opWLKDYGVI8pojmJneVVphw+6LQXAf4CpeSVwcXmZaeWcPP6jn1e2+KwlPb9VCM5ykQV+TMMRFSYn3IpFoVUkuue1JRKxdMo8mlKIxGpbAKD/4hS+S7gGXfmlcgS00ChGGGYUOCJ6PUE/HEoW+WsFNCxUuOatE4K2a7+mrQmmTZXW398xku508a/0+eUd0o1aS3m+45u38XUa2vjHvX/3NL6h1JN2s2f3986ddvjullaK2xFYOYRpZq02GD+pYb6xd4HB/uF5pTFT1SqSdt700MyvKiHT87Y2xFwH1++Uk3aw00Z7p87/ek3/aE7J3H14z+UqvonQJKCT2bDefvm1raqe27tXqWq/r6Lz7Z+tmWW0/Zn9bZaJGR5K1X1Z/kNvB15/aXb4gNXCsP8TmQgJEOMVNp4qevqkS6uKw+MMh08/uorhGSEkXwOLXo39oGf76ZP0vsbzvvbIiRjjORh9FPKd+C7ZqyXdnQc924tQjLBSEaNfs36Z9cY730nXFKKo25vRkimGGnGlLtTxw3O4m7d06R40ownoAzPDH/DsIx6IQ0LXNaLG5q8+ZpkipDqY6QOqcNGRrTc470h4dQ8j9XdJiGkBhhpzjDZfe/YhX5zn9kEmJ2xBxg2xEh3V/QdH5473Huj5cjOs1cYLUNIjTDSiTNjD7YpHOa5KTaB4yi+DbjcGCMNje/Z8huvmUeShbvePPcGLRGSOX5X/uPAtd+D3dbeDxqx5ZoMIG+Bke7bj9G/uRxyWbS+X9o/rRfPQEhNMNL8+UsfdP27qfcOM4c54rJx8QjJEiMVfJ6T9uRMf/e1RUE+KSO2zUZIVhjpasc5LaS/nICLnrzi+Z4/k4mQmmKkSQOSLE8J+3AP+bU/uyH2/iCE9AtGmvXKv12vse9d0tZ06bfd8q97CMkaI110kQTc+VHktqSB9aY1B9xaI6RmGGln8LqV19L+cFo51TaobMlFIGzNcYmqJ57/5F6s04wmg7/1+dEhASHZYKR1ZasG9JzR0nN7o7+5k6bOiEFILTDS87W3IxNcv/gWdAgbsGBdCuhJwcFIpo5bJ3e6d8O1KLFJxJFRL98gJFuMdHv5pD5HGvbxTc3oJBs1cl5thGSHkb61KWiQ++6t757jlm/qrGqij5BaYqRlxWPjjun35a4Zdafg9P564G+1wkhbQpf33Zd13T3PNmlAwvlpJiqFna0hmsLO3LQVf96zTfBN+XX5/IePsx6yUNgppFOHFuEHdmafOuu6Mu/JxPPNJq8hHly6JsSIJQKKbAW60altsDsU+aVoM/jYKL5YjCg8rM++mukJZGVI+WqqZ6oYQV0f6AMXmjqvBOhyKk/bGYYC5mk2pqIie1P+IpTfrd6Al0X2OZ3g9Ze2d7O1Ochm8ibbDvVnLjQRACSgzHWzgqHweRplHvQMQJwzKXpOKBCCRsKSWBGaroG8n0gMxkIr5ISDeGscPtjehVGi2G7oruEPTj7kFi6JbD6pTZ0PxHCr4u+ohlsrSKzvmhG4AhjhGjhPJ2LjqqmBGg427YwtNEEFu2SRfBmyVxon5CDOjmJQFH1cdnKTi2Uz3/f32TWrVePnI1zMSSfz2GMpTuZxCuvc84Hlwu5CyT0hKuwq0VkNgbPFk4jwA3IhGUhKsLb++Dx8R8g53tw9F1zPFrbcVfWUJRbACmAECxF1zP6EQzT253+VDv+q0oG8G6ixSocO85kqHV5pZivVrHTonGjxlCtb4Fl4o22jdh/cPFk0lmQNxEKlQ5v5TInhjebXSKWD1UK3voeazXA6kBLyl2fWd3+tVzr8mMeEyivt2EQ1ojI1V+mQ/LjDPzs7FnDzpc3bLGw+dJDOVDrcZGTdCV11Z1iudBB45zkYJV33nC19vqv9K0GylisdUC1Dm6qOaJkaq3S4PmyiV/ZXG681JftfFPdoeVgHKh1QZUMLzqt5NVjpYB9i1F1wOcN9a8bwPf90LidOX9ZepcNNRoROKPy2CIjGbzu7gs/77mjpnrLJRv9Vy0lHiN4oOlUv0IWn/sEBlzjUEvOEkR1iOPIr4nclKk9+RJQtJq/A98JctylqOU7ks1Lq91b1onGKBsNnoC3Y8BlVV8kfho5trobpl5vXzTz1LbPMd0ZSn9vzii69IQX0wd0UAX30cmWe0h6HwsA/+kz2XhHSc4vLowmrWZgs820zAlAMpRDaw1DZZo3idFYoQLhctBOIpIj4InRqYxs0alB5QfceXvOb/d3y78Rm2cRl6YLfrLosK0iVAXbWL6jFqcddndaZBj3ua8K/wwJgpYyAIRKlFSdKbjPAZ7pDdD+q5aMGDLw0RnnJoFV5VyaPfdvhrt/yv66cm7bm95eN0MIfhBmuCTFSoSJMiDq1ztzAdiHtq+YAk0cIDnEeaLOL55IZ1SXIblLrFiywNo+Rtcu0xFoq/zhTsxF1lU9YfZlZ2327xXu3A9uG9Xv9UmqmvQmrIzGdBCasxqgo7Qh0iWGGMRKiMYzcUsv7E3rvddo+YpTV3ODDxDbE5qC9pwwcfYLMXyGIRQs1mMvWBZZEIZDLm4yijxFUPAbdHFaMYxMgQqKWRSSHCCt/YRV2UH5KXdDrwFD6ohJ0p0Expq0bDMUsqmpdoDNPCRRw3ADaBgNvQxLNaYePGEPQkxcMgn/JdVosOI2WxAtpqn0eT525flyvQteiJJOx566m3yLqGHRaK8UQO+x6ZTqmVf2PHUd/683dcDvD5lDBequq6pi6MJQKYNbjUgwmS7JAYa7qkXBrJfYrTrfCJNGxwrA4VDzAkAvq083cwVkNj/1e332O3pp5Q15CxO7txhXPVd3+Eoisq4SBGGwjKWEbhsKGqQQRnUo4b9byfddeEp9Z795421+f5koeaRwj5ocJOb5xYjGFLqBzmDvj90WD+4DMiqIn8MUigVzI40WySI4E2aZI1dcE5IwAhvekGr2sRFYX3b+4UCeArjFl8C0YuVrltd8EGDV0QKMMDBQEShIgRjOV8qJ/z3uGzjNb+Ib2zvH9k+g+ow9SdZ/llytbzuQMiKou53dcqB1Abh3luYwtDJkvonWf1UTOWoGclCBqQLQo4Uv5rbNRasA139z7TYfGW3ZfREwLxwSEOqRDpLK+ihG0IEa0/lhYow4W/qIGQYkxQmUcWirlB9l7Iy6tUGwPPhNr7+4xGji5EUIpKSMZ/FRVcTdBDSRgLPIIZFOdKGc1dcUGyTBVZZFUla+hsHwVlDtTOc7j0VWg0UGYlXzQKvAVUFuFi76AEgoD0yWxP3xf8g4K9/rfNX/5mBSYAN+KIjCBXq4OKCBGKBARxwzVWIjGUOlMj3yytmRnyFA1tMgvXMjUIn+LAvJxOg85OQ+PHchbXZj2JbrRDzj5YfKax08mV3mnjEButJgJ8q9ZOORiOsg1zgCtj0NeAxmgFAmbeAYoRcImngFKkbCJZ4BSJGziGaAUCZt4BihFwiaeAUqRsIlngM6uM9udn3vD5ciOKw0tnl76VSXlDQgvpfSRUz1ZSHmLouO/nXdx5/u7jdw26wlCb75sQOR/Y/lhPyyWxAJ3EQ3gqDrl9WhWm52bCIwHigTzdOQPQLeUYJ+JpSGoF94np7dW+ooq4FB9SN1Fpg9DN0F46Rbl2XV3GFoyX6Oza2t5tA2tPJEA1iB4IL/Q5wU1lQbnzh0Z67SnrHhqkxFd+lcl1kZSSOQwXlUVkiEMXZuPmd1yFYVkBUP7VAP+TFhZKFIilLGiRMn48j/+esEh8KL8RvNz6mY3YzEtInmI78czmxLctkrmeKRyE0+wgNISRpQS5ms2Rr6TP76u0MWGYoYvObDVw3PPGEIl33pM+JFyxDPfpXvKbI6oWJvx3EGYEFEH5EJg6IiG8dwOiughgChMqT8GsEAE3UQJzvypfVtnv97gvFBkbsexbjxaF6KWCEi5jCAtma9ZXLe1i0j+zRVHVRUigwYW6RVU/C/Pg1cY3+OlhoVcnXd8+SViFBF/rmoUUUGpDnRSGNGJno87RtEQjWF8HezL0+vyBV68/oLbWj/P4aoH8aqWUI8GXFtiPFeR6hYv0ahFHbmYQ93YgLqwGcGQVyYC2wXKOkseDNlkVkOY9pLjTL8j9kN9l9541qifXmtSm0A0Hktj1gnEyrQ4WcVVVYubwJAbAMufUsbawFC3TI1snRkKlhBZafRQORkujhrucZq3gXd5QpH9uiFETeSK3EsNlBKppl0CE1RqGGAyytTM2FUeQtt96fPEyYtauqU+eJX64WjzptoLoYVgMgJCaCqzjqEwFBpMD0no9BDc9kIXx+kPeWvc1r6VOTZtTj6HjuLHcOTnNBTn5XSueVv5fXi0B61L4XOihfHgklAqCsMMpFpqiVxIxvCGVCflSmR1cX3EhZrklKDD5Cl88iDEY1+lkaIyQ8NQ8sNd5HWoWxIMsMjS+94Xnt0wYp/HwBHEb1kXfYCqiyS/XNmaI9fUVXXNPeVCjQA8eXTdI36s0iibxFT+PkxNxToE/8x78dLGOevKuCGth6xbRYz+ye9Xjf5h1yvDp/EvlgYDnl7kbSz6NqL+7IEOLODzahUTPoj4aCPDwABN3JggB6I/RP7RrOu4aRBfGiGUMTFN7HRqe99bP50K9d5/31KvPakTnPx+VaZh11lXlghXTjByZYdOcaX8KM4VjcxXfVThxQgFmPKlZIxsscXRieZpnoe/PV57c02oNZExPuj9qozBrrPOmDGwXJ2AY0bV/aoMhj6s0mxDZq3AAN1YiEWV4WEWGX5p/JILznkQ/9SfrvMTiVm1sPwBqlm1OKE6ELm5igmRwlW4XY+BaOz6roXeH0b06+s568N3mcHJO++JPJb/RfWTYfordhhEA86JjxSFRSJuJagt5MfGgu4JiqwYzPyrt/kg14RTva+qTMqva5AnOnYVlieqmv3iBEO+qnZdwwh4M8zVAMZeJG+IA0qY5G9C+cWnuk9J8vL0dN/c9PGdEXetiIFcfTrHRkGoaeNvAEPhAEMHqhwNyAbFUCON1d8Xkyh5C1BCoRbIB4qVnw+AtoPg3xU+JWeS7xTqNjoke67VDqRgX4sCZkUJ2GgUMGwxj6dbzDoTuCJLE0vztMlhDjYiV6sYI1crccyldJj7FrhdOgsVw0nDm/YTvfJqSOxQhc6ujxGLwtCyMFVFSoe0tQ/iDyDmSYbcKeZEEZ6ilp4kd8Fgei3VxllEurpwIvsg8w0InOmUBzfdYahsfYmp4jQS95xwe2LkCXQpgZfgL+mjlz0FuAwME5yZV+uooUvRX5Y+ph0bX8HptWjoxn6oelGREQP5dfoHy98HfV3wEaaNW3M3kRTROSA7AU1mIvKLkj+HT9ldPPk+wG2TdOFqK6tJxJTUWs6qq8NZZXXUIq2OXvlNBmd6OfqkNbOb5XGs1+Sqro5mMNQAsNOBKnsBJOh8W1+iBFJlJ0s2gcIwCaKhNUHJYfuGNcZ9m3Dzjsz07nc5dyARJa4qStxKUZoxKXncn7s/O22arz/I0+dnSxZQQsSaAaXS9SWYDCpkiTHbRd6bEDhGagC0/u7ROatOHPJJ+SOvyZSfQcRWrfXkj1K1Ydj16jjwRiXmM9VBU5IvihSmT2P/Y/qU3DqohvTpzRwmfZqb8z99ivGna4Hhy6JuF51zs4etm3OrmS0L+pTcEooFTXEth0lTHMmpbn26rPHTGdv2LPQokDatN3ZLrfYs6NP+T943WXYqyHVDgIFDRvfNbiyglMuI0pKcatSnZBuqdX2KSgytPkWQwvSpjE6f6syegLyc2Elm61mr6dsMOMYl/6NT5K7SjAAWtgQhOUxbAg8F5HF0kGuczNYAh7wGktko+u3hqp6i3x6ezEbRbw9PZqPot4cns1H028OT2Sj67eHJbK+HSDdtCO/M3XHFW3Ax61qMcjLbS1PZhlqHnDL+Thq09FzGHqV2hpMlYyWnr7z33bPurceEz6FNVfLcwIcoBZPc34+FPLcJrImGcQ2Kxr/rdEnR9hGHm5wpoMITPTqekBsrssCTeDqeZBc+Gjb76WfPosL9RbvHPSZuxer686OFYtUWsnTqsJ0zJwbcodQHmxMtkQnlLYlkwgQZR94+ljrHh9QZkuJV1NGRxoFhUolYHADsHLioPDKWpD873bBJanevj3tq6pvp3kNXN6XTnwZDYoXSIOT18T/b2kUSFyoGGV6gVy1oFyQQybDvjvglIDbyJGkTiSV4M2EVtXuCCz3NRtSuIwwlzYaNfPjSCFE0TxhOMJvG8ssBYKqI8nVD+fUgSYzyVaLuLg84wU17kl1SHwXRXwqqDWUi+Vvp429FtaCk/HjPaAFo1oXDW8sQXAQBG6VLqIcvxhofy7cRYFaJiC+GQQcpJfMlkwr5UYrf9YZK+TGKezBRTaATVZ0x5uQ+pSwd8JHlnwVrvnAFkzVPWYFb80Sdx5zcAFZ3D1VDGMsBPBbjmE+kw1xjM2kK1ZyZpOjsi5tJis6+uJmk6OyLm0mKzr64B3VrzfIBH2bv5e5Ib6wXxdfvo+RB9SiXNjQ23upysHznuELr32qrGFeg9amHV5LaBbNgXCfRcVJHh6KR2yLX2FC0hO1MQ9EabK/uoWjvV5l96H12n196j5H/5KYMX6cDQ9Fk25lGzIzZrgOTnR49elQDQ9FWZPn8Wjx/mfNK99dxRc8S/tGJoWg8Ru700QXu1MhQtANfGye9Cd/hs8/k1c3BA9sTk161NRStFSNzGugCcyBtDkW7MdD12L6C2s7ZMzN+7ozw2KdTQ9G+5TExryxPd9oLaX0o2rcjUZftSmf5bN7j33XNpfAULQ9FK2Xk3DGtcw7cVG1D0Xb+arf8+MVPnnvHNH+x//0uPZ0Yiob6ELRD0RBFiPmpkyEaP/W/NBSNPLhDy0PR6u1gGop2R9WlrZahaF0XnwuQmPi5Fs0o7DuvNPoO60PRjM5tFbXJD3Dam/W0oX8mx4CFQV+1dzAN+vpre3UNRRu+It908KbGfrMNOo2y2LhuE+tD0cg6ggWs7mxnwqqkZl0dbQ9Fm0Knxv7Xuv9fte4nzzuqsdb9+TuYWvdP2FEdrftLFrR/yK0X5Vbwx7jPa4PmEwfCV61GnW0dWcaF9uxg6nSes6NGWvcHz+lwtsnGRh5zBguMGs3tX1/rrfvTGFFB5EZn9g6alQux17q/kXHGlsGeXq55UblNx22IJB7ba7N1fygj63y1w7oab93fPaiZa8QIf58Uw5wPjQ6Hwlpu3Y9qGdre64iWqbHW/QuyedaTn2Z7FA2v92VJw1Jimy3ttO5PYwRnwo4abN1vPsvuS4MhK3wz/K9+7C4tIzbh0V7r/lBGhJA1jfltUyEav83VuUPHnwNKnbc8sNl6LecNqfsAWvoXIxEjFl3VZzOgwblnRYhEVHE/1kEDQVwqiYuI5CjG2mrSAYI8A5L2bVV7JSgR1cUX2Vqe2I3gy4fBoQsZ30QYit5d1XIs84rXQq5iWFB+9S/rVzeuL+rnufhl5MHSK0OIecD/auIXyYXqPWFEnkPKAaeDTfMvfG5wLLiqLtRKLnQEoNcCprI4zWEod7dGLpSJfPkKhBFSIbV/eTal74m3t57B61ItjtxZX+5OqqtCb6Soq5JfZ311It9/CeP3T9mtbWdJIZkaOErglUUSgSiMoSPOwC2e0+f4Bnplmct8krZlzSXKKv4AVVlVUKqDGdGMzBiuHWaQ3R9Ik4iFvXe0RIaYL34YODtt5zAA2bIiO4uoTpyuA8IiJVJBJ063AbHjpTL0F2pvNXD6jVslZ1u6Lhj24mX57bMSol0DfyBQliimmJpZQaoOZrkxMqubTqwc8CiNvFWLioPu6DhpaCzDCkq5b2zRJdQPnnFwzSL/d71aV2WrXEV2JKXAckUOCkSvqLgZ6fCQ9bs181IxTc7gbZ1oMkdgYPjEuSB9Zn4/j88ztbrtBQCk4QDcogAAqBaNPFHclNG3pnA5+rTBrIN+LnP33h6+p/ngX7RaIgwACGICILfPbtzRnAb9t/JxyKPDaywfp3wPUz5O6p7qzsfhbIuftP/oLe76Z8f/eHNrykkdyMf5Yw9TdPPWHh1IKjh9+nQN5OPcGV2rsNeQUS7b78r2mkT8laAT+TjFjNzZpQvcqZF8nKN+0Jg2fqYec1sk7bJd/utwncjHWcnInFRdYA6kzXycwVcznx07DXsnrek+98CuHQY6lY8jY2TeGO0wTzfzcbqYWD+vn1fCm/77M9u0Q459tZyPw2PkXB+tc65a83E6bRLchH/LcV+cO29V5q97V+pEPg7qQ9Dm4yCKEPNTk6D/A/k4z9fejkxw/eJb0CFswIJ1KZO1nI8j28uUj+Oxt2bycZIur5yadXqNe3pC1jBxQbetrOfjkPfmLOSYxOxlyjEZube68nHmFXuveBI30i1/Q0TbH3WObWE9H4esI1jAyoMRqx57/7/Kx0mmU2Pjj4o6inxz4YIjfuIXT0cQh/8aD44DtZPuUn5MpGqFqQbhi1YuotgYUD2miOYkdpZXmXL4oNNeBPgLlJJn6rh1cqd7N1yLEptEHBn1kv79VCM5ykQV+TMMRFSYn3IpFoVUkuue1JRKxdMo8mnEKxGpbAKD/4hS+S7gGTdt7MoS00ChGGGYUOCJ6PUE/HEoW+WsTKFjpcY1aZ0Usl39NWmLxn+Nr9M82HdFes7A5GmnBynVpJ3pufDQQ3135+29LN707rf1L6WatPrhc8wMzl1wntO3S+bL7q2SlGrS3Pr+PP7H1+0+qxoVzLufPChWqSbtkeX5MVH7OjjnHm/V7vPyrD1KNWmtJf3e1p4+zXnNgkJR2NHfXylV9bfa+Vzv+qdz7hmzj3y7Utp3vVJVv0X2db/kG6O9Zh/0/pF75Es3par+gyYTygsHnHXdN+j3drz4xB4IyRAjvZ5m3mVR815OqbP/Tnb+uG0DQjLCSP9M//zNo1cWvOhA5+cH/vYIQ0jGGKnRKZvy5PzNvLl6N9wHDbm9AyGZYKRz2Yv0/+ku8Jgn1D/855oedRCSKUb64nXPa+i0XK/d+ru3nju97zxCMsNImWvKbp2S3vBYlyp49Ifp9ocIqT5GMhRtyEk58s1v9b69z/Zevw9eowFG+usXt03zjqV4rRl1r97vyzuBv9UQI7V9YZBX/0iu16LuM4RLMx9EIqRGGOlUoNlv5T3OOW1tKC4bfmV5FEJqjJFGp29MgwZ05h46+ibjQUC73xCSOUaSul94sN13Jne3d/0lAV8aN0BIFhjp7IUTK2XnWntmPjna8fXqNaEIqQlGqhvV72h55i73LVY2RROO9AtHSJYYaWS7OStGLVnht3bpnWjLUx/OICQrjPRx6frBn9999MvJ8+gcMKJZGUJqipHcHw094X1ji+esh71Pf3Tc1w8h/YKRNpd3Sd49Z4N78qofyx3ah4G7rDHS/EJjg255l32nPxvbZ9TIM2YIqRlGeis68OZ1v3OuKWndu238PscdITXHSL9bm9ncuVHOndXRdu+g142OISQb/Ht1nd73Y3GK874uMyw6hEQsQUgtMFJvh/tDreOtfBdM6vf6zv07SxESByNxn0UlSVdc8Js5bVuHg3dbXERIthjJ+NyBOx+Tp/isil50vUlMQg5CssNItU6n1Z2b2MM9KeRqox3e61IQUkuMtNpwUUrXWqM8Z4rbD01tOecSQmqFkdYPSfbxvNOUm36zTr3jMkEvlcLO1hBNYefK8m4PLTIeOS8Ia9GtbPH7ThQqStPCzul06tAi/MDO7FNnXVfmPZl4vtnkNcSDS9eEGLFEQJGtQDc6tQ12hyK/FG0GHxvFF4sRhYf12VczPYGsDClfTfVMFSOo6wN94EL2+SVAl1N52s4wVDtfszEVFdmb8hehzv3PXGy0scjRd8fly1HZ617ls5i8ybZD/ZkLdQAACShz3axgqEm+RpkHPQMQ50yKnhMKhKCRsCRWhKZrIO8nEoOx0Ao54SDeGocPtndhlChuc3bcuMpa6lvUQ79o2e3Jd4nhVsXfUQ23VpBY3zUjcNVmhOuv/ToRG1dNDdRwsGlnbKEJKtgli+TLkL3SOCEHcXYUg6Lo47IlM3lnj7db57zzOXfNW67LUtLJPPZYipN5nMI693xgubC7UHJPiAq7SnRWQ+Bs8SQi/IBcSAaSEqzaCxp0ulu3ns9yP6jw5kV+3aqnLLEAVm1GsBBRx+zPDIjG/vyv0uFfVTqQdwM1VulwJZ+p0iFTM1upZqXDxWflVncN7Xxyvvbv3dzkvBmLxpKsgViodLiQz5QYXqiZsfy3lQ63ml1KLOshdl/RQTz0xJ9RJ7Re6bCBERVEbnQ0KlNzlQ5LNi749OHjcLes37OPSf6JJ57haLPSYTIj6yK1w7oar3QYnt0kVuxelzen5XCjuXkv+mi50gHVMrSp6oUUXkp1VTq0tuE1TI/lOR2ecPenSbCBWAcqHTYwgpOZX4OVDk3iu3Sdcu+e+4Ie+y8YL9A7rCOVDpMZEULWNOa3zYRo/LazK/i8746W7imbbPRftZx0hOiNolP1Al146h8ccIlDLTFPGNkhhiO/In5XovLkR0TZYvIKfC/MdZuiluNEPiulfm9VLxqnaDB8JvMyNnxG1VXyhyH/y9Uw/fIJd5r4xvhtvjPrnlkxquidFSmgD+6mCOijlyvzlIQhOy/fjIlzOrIx44aA/5sVC5Nl0gFAMZRCaA9DCZc1itNZoQDhctFOIJIi4ovQqY1t7mnX/OQpU+CZx72vrr97ZwpxWbrgN6suywpSZYClbWixrq3+cd+tj84cevPB5yILgAkYAUMkSitOlNxmgM90h+h+VMtHDRh4aYzykkGrxlrIRqc+t+fuXGt969vV528aoYU/CDNcE2KkQkWYEHVqnbmB7ULaV80BJrE20GMr9Gv/Iu+9N906RM/ycWKBtf0ZWdtOS6yl8o8zNRtRV/mE1ff6gVkrjV3cZzh1sVtuUuCnvQmrIzGdBCasxqgo7Qh0iWGGcRZEYxi5pZb3J/Te67R9xCirucGHiW2IzUF7Txk4+gSZv0IQixZqMJetCyyJQiCXNxlFHyOoeAy6OawYxyZAhEQti0gOEVb+wirsoPyUuqDXgaFdB0vQnQbFmLZuMJR1sKp1gc48JVDAcQNoGwy8DUk0px0+YgxBT14wCP4l12mx4DRaEi+kqfY5d3LjZM7ZdK8VV4WrO3qPfkbUMei0Voohdtj1ynSM/rcfesKvw13mO7/t/+Sxa5VzPerCUB6AWY9LMZgsyQKFuapHwq2V2K843QqTRMcKw+JQ8QBDLqhPN70bvzxpAW/wWt1A4GqfOrIxMYOh4rmq218CkXWVMBCDbSQlbMNQ2DCVMJtOJZw3a/m+ay+Jz6x3b7ztr09zJY80jhHzw4Qc3zixmEIX0DnMnfH7osF9QGZF0RP4YpFALuTxIlkkR4JsU6TqawJyRgDDe1KNXlYiq4vuX1zIF6BrTBl8C4Yhuyqv/SbAqKEDGmVgoCBQkgAx6gQuv1VOf6wf5ryk1s9j/9iInhPdZ/RBqu6z/HJly5mcAVHV5fyOC3kB5NZRnsvYwlCvg7Tus5rIWSuQkxJEDYgW9STG6b8/eXZjuvvCe4EfnX8WfSWmhWMCQh3SIVJZX8UIWnaMaJkdrFEHC39Rg6DEGKEyDi2V8oPsvRGXVii2B5+JtXf3GA2c3AihlJSRDH6qqriboAYSMBZ5BLKpTpSzmpLLZMNUlUVSVb6GwvJVUO5M5TiPR1eBRgdhVvJBq8BXQG0VLvoCSijar9GL2iiZ6bk8vzBwWsLqnaTABPhWFIEJ9HJ1QGHHCIWZwlClQjSGSmd65JO1JTtDhqqhRX5JEVOL/PwiHPI5Og85OQ+PHcjfiLNyDA2GwfuefB3TtsuIDyxA3ukwE+TNDuOQp9FBrnEGaH0c8hrIAKVI2MQzQCkSNvEMUIqETTwDlCJhE88ApUjYxDNAKRI2FXOdVBM28QxQ+0eDBmSMv+W2a8SspKaDfZxVUt6A8FJKHznVk4WUt7l0/LfzLu58f7eR22Y9QejNlw2I/G8sP+yHxZJY4C6iARxVp7wezWqzcxOB8UCRYJ6O/AHolhLsM7E0BPXC++T01kpfUQUcqg+pu8j0YWhGAbLIblGeXXeHIZcCjc6ureXRNrTyRAJYg+CB/EKfFzRtX/Nzo4vNfFM8drbYe2hbVlVibSSFRA7jVVUhGcJQUgFmdstVFJIVDIUWUPrhdFhZKFIilLGizgFZtzu/o/dmt7QzE9969jWcxmJaRPIQ349nNiW4bZXM8UjlJp5gASUXRpTaFGg2Rr6TP76u0MWGYoYvObDVw3PP6EMlwZnnci62ne++/cF4T+uXj99oM547CBMi6oBcCAyJCzRzYzsooocAojCl/hjAAhF0EyU4q3rzfnvX75jvshtJGa6r+8zWhaglAlIII0guBZrFdVu7iOTfXHFUVSEyaGCRXkEdWy56XOgQ5Vn46ZB5+qVLU4lRRPy5qlFEBaU60HFgRKdZAe4YpUM0hvF1sC9Pr8sXePH6C25r/TyHqx7Eq1pCPRpwbYnxXEWqW7xEoxZ15GIOdWMD6sJmBEMmhQhsFyjrLHkw9EgzU6demHZuL69NF8YJeGsv+5c6unByiIedaDyWxqwTiJVpcbKKq6oWN4EhAwCWP6WMtYGhD5rZOjMULCGy0uihCsm27Z/hF+yS8mjM/syWvYlZr4auyL3UQCmRatolMEGlhgGmCxoau8pDaIcvB977py7svcrRZs9ohw7m2guhhWAyAkJoKrOOoTAUGkwPZdDpIbjthS6O0x/y1ritfStzbNqcfA4dxY/hyM9pKM7L6VzztvL78GgPWpfC50QL48EloVQUhhlItdQSuZCM4Q2pTsqVyOri+ogLNSopQYfJU/jkQTB07ZRGisoMDUPJD3eR16FuavR5yoWI5Z+4683OixdvGNCI6CKhD1B1keSXK1tz5Jq6qq65p1zIDMCTR9c94uspjbJJTOXvw9RUzP7xh1mb2z922bxin964vEaXidE/+f2q0T/semX47B391rO8z1WPJF7iqNmLhH+zgM/zU0z4IOKjjQwDAzRxY4IciP4Q+UezruOmQXxphFDGxDR3Q1Gsz8SbzkcfxnTpeXHBFSLT5PerMg27zrqyRLhyhJEruTrFlfKjOFc0Ml/1UYUXIxRgypd6O2Z7tHarcYbOq8fcvLdwaT1i/LeeD3q/KmOw66wzZgwsVyfgmFF1vyqDofJTmm3IrBUYoBsLsagyPJ6XjJEc+KMhL9XstWGb3n2IpW36sPwBqlm1OKE6ELl2igmRfadwuz4PorHruxZ6fxjRr6/nrA/fZQYn77wn8lj+F9VPhumv2GEQDTgnPlIUFom4laC2kB8bC7onKLJiMPOv3uaDXBNO9b6qMim/rkGeaPQpLE9UNfvFCYYCVO26hhHwZpirAYy9SN4QB5Qwyd+E8otbz7ndqmDjWl7qz5jP+Sbribnu+nSOjYJQ08bfAIbGAgwdqHI0IBsUQ400Vn9fTKLkLUAJhVogHyhWfj4A2g6Cf1f4lJxJvlMoESXbc612IAX7WhQwK0rARqOAYYt5Pt1i1pnAFVmaWJqnTQ5zsBC5anCKKXIFKTDPpMPct8Dt0lmoGE4a3rSf6JVXQ2KHKnR2fYxYFIaWhakqUjqkrX0QfwAxTzLkTjEnivAUtfQkuQsG02upNs4i0tWFE9kHfTuPwJlOeXDTHYaunC8xVZxG4p4Tbk+MPIEuJfAS/CV99LKnAJeBYYIz82odNXQp+svSx7Rj4ys4vRYN3dgPVS8qMmIgv07/YPn7oK8LPsK0cWvuJpIiOgdkJ6DJTER+UfJnE99os1HOc7f9m68YJtuLexH4U8tZdXU4q6yOWqTVccrz72cm8/S4R/amGexuX5Je1dXRDIY+A3Y6UGUvgASdp+dLlECq7GTJJlAYJkE0tCYodd3olDJr2lLP7WN3LV7JnxlKRImrihK3UpR+G1zW2jb4ncvCosHWmcHXb7CA0hVGlA6dL8FkUCFLjNku8t6EwDFSAyBy1jvRhskfpWrDsOvVceCNSsxnqoOmJF8UKUyfLviP6VNy66Aa0qebzjDp04ln/qdPMf6kHfNcXX5piOeu1dZuFh9vtGZDn5JaQrGgKdadYdIU885Utz6dIVr/Z/+u09wX/97UwsKjqyML+vRb8UC3D/ZrfdZN+6V09dEPZ1hAaSIjSuFnqlGfkm2o1vUpKjG0+hRBCtOnC+n0qc7sCcjLiZ1ktp61mr7NgGNc8j86Re4qzQhgYUvQ7AzTlsDk/7F3HWBNa188ICKICDIEFLEiKg4Q91basClDwD0rFKgWiqUobkSfouhzIyruvZ4bERUUBfdeuBFxoSLurf/cNCltmgT6CG3f+z++z++THJKmv3PuOefes2SQL6KCXOVkNlMccjUks5H028NVPUm/PTyZjaTfHp7MRtJvD09mI+m3hyezkfTbw5PZPtXu1hj+ctNt2Y9Vl2pMqh8vl8wWnjJpWOv5m+AE3Wle1gevnpFrZ7jetuj2oV2WfoeN6hxv0LVOolKeG/gjUsEk9vdjIM9tMWOiYaRG0fh7nS5J2j7icBMzBZR4okfFE2JjRQZ4soSKJ8szCgbMLPrinZlxIHPPqEeK1YHVA3nRfKFyC1kqdejIZsWAO+T6YLOiRRK+tCWRhB8vYUnbx5J+bWJnSJJXqYiONAoOFYuEwiBg58BF+ZGxBP1Zcsb8vEOBr9viBVd/uJxtRZl/bdAnli8OQV4f/9gmbqK4EUKQ4QV61YJ2QWECCfbdEb8ExEYKEzYRWII3E1ZSu8c40OUcRO12gaGEmXBNP544QhDN5YcrmE0j6eUgMFVE/rqh9HqIKEb+qqLudvE6zrlwMSfPBAUxUAyqDSUC6VvVwN+KbEGJeWO9o8NAsy4cXh1DcBEEbOQuoR6+EGt8LN1GgFklAp4QBh2k5MyXRMznRcl+1+sn5sXI7sFENYVKVLXGmBP7lDJ0wEeUfwas+ZgTdNY8/ARuzZdqPebEBrDae6i6gbYcYLGsHCCVCnOVzaQxpD4zSdLZFzeTJJ19cTNJ0tkXN5MknX1xD8pgYXbx8iX7OLPffrzYruh2PTkPqsXI5PTjeSU+GUVBvaMvv3FQMq5A65MH3AntghkwrsuoOKmlQ9GIbZHVNhSt6w26oWhXr1f1ULTUpjcMBm7+w2tvx+BRfxY1XKkFQ9E63qAbMWN/QwsmO92+fVsNQ9ECxgbdaiR8FzD9+MpZ40UzjLRiKFptWu58u64F3FHLULQluhn9r0y+6Jv1o8OlyOA7o7RiKNrT63TMuaoNzIE0ORQtSqc0LTgs0y/7xcLxkYsOTdOqoWhZtMzbphnmaedQtGv3C71+fPcKSBfe+XRp/YTVGh6KlkLLuUSNcw7cVGVD0diha4xCWko8k353bWlh0xfWiqFoqA9BORQNUYSYn7ocovBT/0lD0YiDOzQ8FO30DbqhaGk31DMUjVUnaPTn+EPuu75BHkHcYcsYH4rWpJNh4Olnz9yzBhxeXmx0vNKRBhsYOnmDbtDX7htVNRQt+9dDB8/iJh7LSjcPvuzVZwXjQ9GIOoIBrNJosUpS7y5B00PRVlCpsf9a9/+t1v3EeUdqa90ff5OudX/nm1XRun+04+9DPyxD/Ga3vJX7InyrYupZ5WrUmdaRzzmQ5CZdp/PhN9XSur/wZ/Pw9FYWfvuMp031M9nUTOOt+7m0qCByozV7B9XKhZhr3T/o8WobqGekT/rAvXvtq7dqqTWt+x1oWWeqGdapvXV/dGpsvRpza7kuGHT30Kr2h1M13Lof1TKUvdcRLaO21v2t81Y3K7jan7Nw8ZSNC8ek62tB634uLTidb6qxdX9JTYvBCwT5rllje2RtnnRtpzY0wUAQcqBFCFnTmN+WBlH4be7sFi1/97jO3vLAbuvVVW/aKXYfQEv/YkRCxKIr+2wGFDh3KAuRCMruxzpoIIiLRXERkSzZWFtVOkAQZ0BSvq1yrwQ5YkXxRbaWTW8j+PJgcOhCxHccsr3Pr2w5lkXZayFXMSxIv/rxdl/0W556DC8cedGvTY3tirMZ/9bEL4IL1XKX49iWN+p473+Z7vWRM9Cisi5UGgeyB+g1hMksTgMYqn1bJReqlnT5hvEjxHxy/9LS6U7BU/c1nJlGm45nPkteR6irQm8kqauSXmd8dSLf/1s+3fd/mq9pZ0kmmSo4SuCVBaIwQShNR5yl255wMxO++KXxfQsbvuvbSFFW8Qcoy6qMUhXMuErLjCzNMIPo/kCqRCycfaNFEsR88ULB2amjSw9ky4rsLKJasdr0CI0UicNasdr2iB0tlqC/kHurhjvTb/uMme06fVjLmXrjvXsr2jXwAcGScUKSqZllpKpg1jZaZqVoxcoBj1LJW7UsO+iOjhOPiKVZQXG/GrYcOmOt/2Edw+Ljt7oUVGarXEl2JCTCUkUOCkQvK7kZc+A+NW6r5qVimpzG2zoq0Bu/sekm76OWtxs2Skvoq9FtLwCgJB8DIJ8EAKBaVPJEcVNG3ZrCPnrZlIi61V2TXcxOhnFbFGm0RBgAkEEHwLa0fNzRXAn9s/JxiKPD1ZaP0/MOXT7OzdtVnY9z+2XeiJ13grzWvG5woO7u8WZakI/T9Q5ddLPpHS1IKsjOzlZDPs4o+6PLl0wI5WYWI275yzV5WpGPY0bLnV+3tYA7asnHSbRNMr8dcNptn4dg9T7uIQOtyMcpvk3HnJvawBxIk/k4UNHnyFtfhvqtenlPR2AyeJ5W5ePk0DLvL80wTzvzcfq6dE7847DEMz3bOP5nN+diDefjLKfl3AyNc65K83Eso9p3H52X6bq6/5iel/jdeVqRj4P6EJT5OIgixPzUVdC/IB+nk8v9fvXHWvsvmNDt5Z37d5ZqOB8n5w5dPk7KHfXk41yq+9cDt417vJOyM+fM6ic+z3g+DnFvzkCOSdYduhyTbXeqKh9n4JGbVq02zfZeZXv7VqeCj2cYz8ch6ggGsEqhxSpRvbsETefjrKZSY6OzBS0F/tvgg1kBwmdFgxQ72hv1jgO1k55iXkykcoWpCuELBzdBbAyoHpNFc8Y5SatMWTzQaS8CfAKp5HGeRCWIV5wP+GPK9haH7za8QPl+ypEceaKS/BkGIyosQL4Ui0QqiXVPFZRK2dNI8mmEJxGprAuDf4pS+S7oCWfeqJN5xsF8IcIwfpg3otfj8cehbJWycg0VK1WuSXOSyXbV16QNDq3T/Vl4rvuCgvfn1rddz5OrSWN9vxb44IOZ52qbNtu8v/95UK4mzdho6tibvyTs1YNHdqw9vZ5EribtrxOW936l5XstWrfbbnJO/yC5mjSbYYc7j+6e5jmz68TDAqF9tlxNGrt/zPP7a9195hY6H5jcKTdCvqq/VczmhLiJbovtOlUfuXCMu1xVf7/aL1/vaFvss6xf/4zbCyfclKvqN9j14/x+HYFvpk1Cg81Z/b8jJEOMpD+gz2d4bZb7/qenkkaG7IpGSDUxUvP7/quezBobsHHNrx+DSlqeQkhGGKlB82/v370d4TF9pesw49pvXiOkWhjpQeG7jbGfQ92XBhsN3fOgLWhJYIyRuE+eDd66Ybr/jnMbU3TPR95FSLUx0syA2i53PfPYmUv0old8qH4NIZlgpPH6uSmJ7Y95pC24wDowaF8LhGSKkTq9yBs3MjjUf9Pe59+ad2ntg5DqYCQdE/cd9+vt9JzqaZV/vXBrHkIyw0hNvAYUmnrMDlge3czHP7PObYRkjpHudhyX3a7vWHjG8KDkVo1XnkVIFhjpyaHlf+TOM/ae+rrRiberqh9ASJYYac+lAzPqJbV3X5byMrG7/nPwletipN5ntj2fLmnkcyB+w8vciVwnhGSFkR53HNPN9Zaf+976My0Mmx+YgpCsMdLLSyFeI6r15mSubvbL9bwICJsNRqo18d2L1N5T/GYfazHyfPqMjQipHkbanWI2OvbSZt/pw/TWvk+sC0j1MVLDyHtdexq39V/bJuWPnBu54LNsMZLn9ENN993x8vuzvuU+w+rr9BBSA4xkvSuiZHvOet9tu7+cqWfZLRUh2WEk+PGs+I3Td8AbrZ16HKzTaw9CaoiRNknq1vm49E+f+ZJl9ua6W8BrsDDS1r3F93659+eum5vs2HNd15MIqRFGqpswqm2H3o5e6cvX2VrZ1dNHSPa4gtP/a+yNeTkBqzzOZH6eEj8LITXGSNlrM749jgnymSZe+CzxY/o2hOSAkXKcjvttvPMwYGGnB2nGX6avRUhNMFJ3yGNSr8XN3f/cdr1O06Z1uyrVfDaFKGo+wyysjV0uPfRbOHzI1gt9W0eSaC9Vaz7XUmlKy/BDu5bnnnFP21E4/pztRMUYeQ33+BihKIwkkYFqqmpT7A5Z6inaJz42iicUIroQa8FfwcwFop4kfTXl41aMUFH36AMHWncvD6h5MiecDUNj7qk2waIssVP6IqTfbSiHG2QVpsve8JBj3qxHk5cM5nUy7Wt/4UCrAEBhpGlw1jA0+55KSQkdghC/TYweIYbxQY9hUawAzeRA3k8gBBOjZXLCQhw5Fg/s/EJJUQx9/NF1d66Bf2rekOeu934EKkZiZZ+jHIktIzG+oUbgGkML14h7WhE2V84aVHHmqRO20MLK2CWJ5EmQbdQoPgvxg2QzpKhDtsHN1+f8sMzz/evyjf6LCnN6Eg7tsceSHNrjFMa55wdLhd2NlHt8VNiVArcqAtcIzy/Cz875RCDJWx+ZTlyov+kzO/3icqh/36fzK5/NxABYY2jBQkQdsz/roP+KIJgsgiBuFNRWBOF1n64IwuB+VRRBlD6QjFzx+53X4fpbzGrEDopk0FgSNRADRRBu9+lyxl3uq6UIwrvw3YLeK2+57Z87ocmJ8WFLNZoNAlCxpUUFkRstDdiorwhixvSibb2t9/ol9PnQa2/UuxytKYL4cI+OdQXa6s4wXATRLODr+0lpNh6Z7VbUv/xm9RANF0GgWoYyix3RMmorglj/M8r+w+a/4LkNaqfZPpioeCypmSIIW1pwDO6rsQiibb2vc8902uB5eKq1hb7/qF9aUgSBrmlKhApkftt6iMJvO7OCx/3ZxcozcZNdjeLGE7IUvVF04F6wG7fiBwccxXmXmCeM7BDDkV8Rv2uc/FBIRNli8gp8L8x1m1Qhx4l4jEr+3speNE5RYS7NkU/YXBplVykQhiZ+qoLBmC9CHX//1SHFa5rPqw7zan47S4j1g7tJYv3o5fI8pc6S9/e7zx/ks6ru5WO+J83bMDB0JgMAFEMqhM4wtOGTSiE8axQgXC4cwwRiRHwROrmxLeDcvrn/wy3uFi5vmv70yBLFZemG36y8LMtI5QH27v4+gzUZbTjZPrfPnz1+fwIDgM2nBQyRKI04UVKbAf6mHUT1o1xZakDDSyOUlzRa9fTKU5O5008E7Jt2fdGsWqJsM7QmCGGGe3yMmC+LIKJOLZsT7Ni/eeUcYAJr+02/b24b/sw9zS2n17Snz78wwNpIWtaGaIi1ZP7xfNWm15U/fLV4StPUZu3veM8aIgnaNTcqQXPDVwdjOgkMX41RUtoR6BLDDOMGiMIwcq5b3R/TaZ/rzkFDrZP7HlXsUGwBOn9KwNEnSArmgzA1X4WRba1hURQCubT/KPqYsLLHoJvDskltYYiQVMgiEqOH5b+wEjtI/6qioFeDoaeP8tCdBskEt7YwdPZRZUsG2Vw5UMBxA+goDLwNUTTLEZ8+hqAnrSUE/5PqtFhwGi0ay6coBKof2/rYnjZHOItrZv8crtdXoKhj0EGuJPPtsOvl6Zhk7u0PP8a0Za97/Pb+0u09B1VWx1SHoUIAsx6HZGZZgiUKc2WPhJvIsV92uhUqio7lh8ah4gHmX5Cfbq45Uc245PIsj62HD8+9PH1YB8XkhrLnKm9/FYiMq4SeGGyDSWEbgMKGqYSNVCrhXO3G79t0FPnNePfG1/naFHfitOMYIS+Uz/KPEwpJdAGVw+yE3xcN7gMyK4gewxMKwqRCPlYgiWSJkG2KuOKagJgsQPOeZFOZ5cgVRbeEA0kAukakwbe+MORV6bVfFxg1dHajBMwaBEoSIEae8sw5vSH1V3vukvtfThW49GQrus/og5TdZ+nl8pYzMTmissv5HQeKAcitIz2XaQRDgx9Rus8VRK6+DDmxgqgB0SKFb8C0+i71Hu0NSB4xZ+3EGU3HKmaMYwJCHtJRpDK+ihG0vGjRav9IrQ4W/qIGIeNi+PI4NJZLHXL2RVxavtAZ/E2ss6fXMODkRvDFhGRl8FNZxV0XNZCAscgjkE31OCmrSblMNEyVWSSV5esIWLoKStlkjvNodBWodBBmLZ3BCnwF1Fbhoh9GbrSepL9L2HnTY77RRruTBU+SCYEJ8K1IAhPo5aqAwosWivYyQ7UJojBUWtM+n6gtmZk/VAXd898V0HXPLyzAId+s9ZATU/SYgZyvO3S/+bdSz0S9y3ku6bp7GYC8tJAO8oJCHPItVJCrnBxqgkOuhuRQklxOPDmUJJcTTw4lyeXEk0NJcjnx5FCSXE48OZQklxNPDiXJ5cSTQxelnbuRyh3i+df4L37C4NF1lFLegPCSSh8xC5SBlLetVPy39z3pdH9PTY/NemEjbr4wVeS/ufSwHxaKYoG7iAZwlJ1yfYrVZu8hAJODIsGoHekD0C0l2GdiaQgVC+8TM1/LfUUlcMj+qKKLrAYMfQERlHzSs+t2MJShWpi/vjTahhaliABrEDyQX6jzgvrVKZ0cxOH4bb97KDpgzaf8ysTaCAqJGMarrEIyhKEP9zGzW6qkkKxh6KZywJ8OK0tZSoQ8VqQondQTTn3ovDBg28/tpuFtC20ZTIuY2sf/4+lN8R5bRbO8kjjjchhAKYMWpeX3VZsw3yoQX1foYkMxw5cc2OrhuWfUoZLkqKMtlvjA3MR7cfyJ0dOdNRnP7YUJEXlArj9i1VSM57aQRQ8BRKFyrTOABVLQTaTgmEw/07Vnwm9405oHViusfIy0IWqJgHSeFqQMFeO6TdwE0m8uO6oqExk0sEitoFpFrO0RmN/Lc0Odfit3t3DXU4wi4s9VjiLKKFWBzgZadObfxx2jbRCFYXzZ15+r1/orvGT9eY+1Ad4DlQ/ilS2hHgW4jRTjubJUt7EilbrXEes8KhobqChsNWEo9QEC23nSEkwuDAkfVEGY9j7vZG8dD6HHvvhXkmHpSeaKh51oPJbCrCsQyz1CJqi4ymrxWjC0GIAVSCpjTWEo4YFKtq42ChYfWWnUUMX76npNfL7aPbvZ5uamzScMU9RE7si95EDJkdTtEtRCpYYGpv4PVDN25YfQDp64mdruWrLfHzqHXEqO1RNqLoTWH5MREEJTGoMMhaLQYHpoO5Uegpudb91l2kPuGo+1byVdbBoQz6GjeDEs6TkNyXk5lWveTHofHu1B61J4rGj+WHCJLxaEYgayQmqJWGNG84ZkJ+Vy5IriWsCBTr/MQ+fMk/jkITCU9FIlRVUbDUNJD3eR1yH9lt9edEnabBPrmbLAuc3DPb8IgyPRByi7SNLL5a05YrldZddcEQc6CeDZQdVYYvdLlbJJjKXvQ9dvbFTa6Klbkjf4LL4UbZCV3HK0YvRPer9y9A+7Xh4+M387P9u45ZfbottFKf53+m5iAJ80WnwQ8dFEhoEBmrgxRgpEd4j4o1pDcuMQnjiCL6Fj2l3bkhEtHqX5Ld7c+iD8uvEWRaZJ71dmGnadcWWJcEVCy5XhWsWV0mycKyqZLxNU4cXwwzDlS8qYBVMLbjlEDONuX7J0yJY/68UpMsYPvV+ZMdh1xhkzHJaqE3DMqLxflcDQppeqbcjqyzBANxZCQXl4PA8v6uTxOpvzRx4nv3XcVVfFrFpY+gDlrFqcUBWIJNEiMvIlbtd3QBR2ffdC3w+DunX1nvHhp8TgxJ33ijyWfmLFk2G6y3YYigacNTZSEBqJuJWgtpAXGwsaK8iyYjDzX7HNB7FcnOx9lWVSel2FPNF6L7E8UeXsF1cY+lVc2Qi4LeZqAGMvkPbKASVM0jchH1r1qIlN3C9jj+VTihZt3G1xVFH4qBwbGUHdxt8AhuoCDF3IcjQgOxRDlTRWd39MoqTdQRUKtUA+UKz0fAB0JAT/L/MpWRP8J5GLEsGea7Q5KdjXooBZkwI2DAUMW8w7qRaz1gSuiNLE0KhtYpiDgcjV6WK6yFWGDPO/qDD3P+hx8Qx0Ek4YaNNNUOxTR7F5FTrWPkYoCEXLwpQVKRXS9f0QfwAxTxLkTiErSuEpFdKTxAYZdK+l3FNLkV5ROJF90I53CJxzSA9u2sFQwrs8Y9lpJO454fakpjfQpQq8BJ9UA73sHYbLwICw03/qZBu6ZZZY+Rm3NL+M03Uo6EYBqHpRkhED6XXqB0vfB31d8Cd0G7cGHgIxonNAdgKazKTIL1L+hCx025Kis8J3+sGTpyeE11cUGx228upgK60OHcLqWPXnE5sjZ1sEZA66bjdAb3hAZVeHLQxtAex0IcteAAk6i9/lyYFU3smSXTA/VIRoaFVQKmw28mNW/Z1uf65YlF58udhYESWOMkqcclHSv55a8oPn6L29fkebtE0fGjGAUgItSsJ3eZgMymSJNttF2rYQOEYVAIiY9a5ow6SPUrZh2PWqOPBGJeYL2UFTgj+KFKZPd/3D9Cmxq5Ca9GnKKzp9OvLVf/oU48/Ejf3+8n6/13fJvWETfrSYWMSAPiV2i2JAUyx8RacpJr+qan0aNbpxWuOsnpyUmzHR+T2c/mJAn7roZtX7I7qP65GoVvt/D39RaZ/MFhVrGpT6vqpCfUq0oRrXp6jEUOpTBClMn+6m0qdasycgLidmktk66Ni8nQvHuKV/dI3cfX1upSdmIluCWq/otgQ/ZGcqe6ggVzmZzRSHXA3JbCSt+HBVT9KKD09mI2nFhyezkbTiw5PZSFrx4clsJK348GS2L8a775fyAz3Wn5qVG7W5dJRcMptjw66xUc10PZZ+DGxk0L/rbLlOh9dGDni4o8EmnxWm0xPPthDEK+W5gT8iP38mtP5jIM9tL2OiYaRG0fh7TTBJOkLicBMzBZR4okfFE2LPRQZ4so+KJynPP6506jOHe+hswHHP32vsFZt8lFWvKjKGLlJVt6zRUTToJIU9oKZyJWwdj4AgP3aIo/0El65Bk+xbBTSvkDdK7DupzxWFjuKHyW6i+grKfUrKaBXVkCc50LciREN2hClORx8UkXilehhcJF4p6ugQvNLUnwmZaxf0907fvNXf9UnLu0x5nbStusuwYI3hiQW8EULyTKPeMR3OLl2Y6Zq+Cjbq8OxMJj36fbFHsQKU3auAct0rYkPQytq30xzoUxHmXikfM17jAO4R3Ss6L9SizL0qE3RS1G6MsrF/Hwe57Z3U9N7NPZ/e0aJG5WqRHRJW1stKgqWQHHMlKyechQo0pkP2U+mQ5RkFA2YWffHOzDiQuWfUI8UK4+qBvGi+ULlDNZX6cGSzYsAdcm32WdEiCV/a1kzCj5ewpN2pyaWT0HiW5FUq4mcZBYeKRUJhEPCVwcWyYvPSXgQZ9W9tecVmX6jr7gXrOF0m7N9HJaMGfWL54hDk9fGPbeImigMrI1QIWmGDlmNhAgn23ZG9DYivFiZsIvAR71WuxMccDnTkKcLHLjCUMBOu6ccTRwiiufxwBaEwkl4OAkOL5K8bSq+HiGLkryoKQ2lQDifj8NM8ExTEQDGoWJYIpG9VA38rMqMs5o31jg4DDf9k0m4ILoKgr9wl9JRAiPVVlyp/MApJwBPCoAudjDX6wRIxnxcl+12vn5gXU6ZApKJ6gEpUtWZDQGyDzFCQgCj/DOwIwp7R7QhCnuHqIV3rMSeaE+0NzLg9psO8/WMc84NUmKvsateC1OdqkzQOx11tksbhuKtN0jgcd7VJGofju7DxX4u3Fa6fxj1c0P7Kmc3eW5W8cKBRSaWF2HKcAS88g4pdWjpYkdhaXW2DFTv/oBusePl7VQ9WDGti3X7aqTcBO9rWCLnXoRpfCwYrtv9BN6aK9UMLpsNduXJFDYMVmw1ckR423dwvzaL/O1vr5TO1YrBiLVrufPmuBdxRy2DFWh+e9Kj28IT7H1eTHx5apqc4ilpTgxWLvtMx57I2MAfS5GDFxLON2v8cAvln5Tqvq5O2UbF1oqYHKx6hZd4WzTBPOwcriq5dWFt62QTOsuJ/DHSwbqbhwYqLaTmXoHHOgZuqbLBi0a3kc+/nPfI74DNn6uQxI69rxWBF1IegHKyIKELMTz0EUfip/6TBisThPxoerJj3g26w4vIf6hms2NKSC7f0+e6+JTnUusMaluLEcCYGK5oIWoTMNXwNL6k3e9bAoRNrMTAsMOcH3bDAv35U1WDFgwfWFYTeXuh25FTnUgM7kV7llzABK6KOYACr5bRYzVDvLkHTgxUzqdTYfzM+/taMD+LMNLXN+Bjzk27GR8efVTHj4+WjY2fefevsmx7ea87Zt6sKGWxmwbSOfM6BxD/pRiIM/amWGR/uPiUB317Ncz36esftLDMHxdbympjx4UOLCiI3WrN3UK2ukLkZH2lf5pyde07Hf87UiV8P1xs0XmtmfNjTsq62Zlin9hkfE06ZtTH+fomb2GBojNHMibU1POMD1TKUQxoQLaO2GR9T55tc23Vwqvcmvectal5g39OCGR8+tOB0/KnGGR/QyN4lX2dtdVvdM91r/gSrdG3oloMgZE+LELKmMb/tMETht7mzW7T83eM6e8sDu61XV71pp9imBK0RjhEJEYuu7LMZUODcoSxEIii7H2u1gyAuFsVFRLJko7FVaRVDnCNL+bbKTVXkiBXFF9laNoROQRAPBocuRHzHwVDx78rWbVqUvRZIE5JiQfrVux0Nd1qZ+BDOWjc2v63ouGIf0r81GpDgQhU7OtieN3/ht8JnGW9Cl56TK+tCpXGgBgC9hjCZxWkAQ+bQKVVcqFrS5RvGjxDzyf3LwGdtkgpfVXNP+146sLtzSS6hABO9kaQAU3qd8dWJfH9D2u//67emnSWZZKrgKIFXFojCBKE0rbOOOF3YnuWSFDDNa/27ceOG2CjKKv4AZVmVUaqCGchipWHGTc0wg+j+QKpELJx9o0USxHzxQsHZqaNLD2TLiuwsolqx2vQIjRSJw1qx2vaIHS2WoL+Qe6v35/SMKBpxwH3ngOQ4n521DivaNfABwZJxQpLxumWkqmBWDi2z/tKKlQMepZK3all20B0dJx4RS7OCXqS/fTZk4kKfqb3W7ypO3nu0MlvlSrIjIRGWKnJQSX5Zyc2YA283gU6p5KVimpzG2ypl+XrmOO4ImH12kvvmR8F/aHTbCwCohgOQTwLA7xe/VfNEcVNG3cNmx64f6y412uO+3Day5HLTEnOCKVNvLwEAwOXfedQAbNv/G3c0j0D/rHwc+PGs+I3Td8AbrZ16HKzTa4/a8nE2oRJFlY8jVvSNcM3CYD7O5l9+xV61q/su9HFu+9b0fagW5ONsAJBQRjeXQ6c0n1SQkZGhhnycwr5fxQOX5fuvjO/zLO2rn4lW5OPMp+XODG3gjlrycdqVwnMCS474blySkx/1ad84rcjHmUjLHLE2MAfSZD7OhuCL2//yn+i9oMG6VNeodY+0Kh8nkpZ5QzXDPO3Mx3mdcVhUfWhz18TCnNc7Ov5eo+F8nBBazvlonHNVmo/DmiNKfDKKy1lZp1H2UB+bVK3Ix0F9CMp8HEQRYn7qUehfkI+zSVK3zself/rMlyyzN9fdslHD+TjPAfaU+ThXlV3aKsnH6f2g5vHFve67bxmd16tvD24/xvNxiHtzBnJMngLkKHNM7ikflDKUj/ORbTelbr+zfnOXvFkc+iNtG+P5OEQdwQBWV2mxOq1enavpfJwsKjU2OlvQUuC/DT6YFSB8VjTojWKkpHccKJD0FPNiIpXLSFUIXzi4CWJjQImYLJozzklaSsrigZacEeATSCVv697ie7/c+3PXzU127Lmu60nK91OO5MgTleTPMBhRYQHy9VYkUvk3i6BlTyPJp7EFff/qwuCfolS+C3rCWV2vOM84mC9EGMYP80b0ejz+OJStUlZmU7FS5cIzJ5lsV33h2Wb39vUtnK/DS2ImhR7UcUuTKzy7mZq+Z+JVsfv+A5z4wrCkQrnCsxumc4WzbV67HXnLF/dMO9lDrvDMr83j4DUtFrsvOzh958DCjAZyhWdJ41ZNGTCN5TfntPOwdh+6f5dr/9HgRW6KIK++e/Zhw7tTi3dclmv/0XHJEojbeJ/31qP9515+58mRa/8xN2vgeNZZT/+dE5ZGjD9854Nc+48G4es7N966znO3baN3iTWrPURIhjhJtCLT1m6a64LlN8zYRxsKEVJN/OVthl6OehLtt9klZKtk5l1ThGSEkf4KfuXx8fg4/6SNw773/DYoGSHVwkj9hor+/JI+lr2Ox+28UbQfdLwwxkhrVzrcm7K+r9u0lJbN/OqZRSKk2hjpnt/8sQd7HOX+MfzmA9MO83oiJBOMZLXv9PWEwNteyYN2PGh7bIs5QjLFSKJay4+e6NGZvaF5ROOPe2zrIqQ6GOltdA/TlXEDPdbvK/ExM729HSGZYSQo1dEvP0TfY+OJk8kB/WYMQUjmGGm7zuIJMTU+BOyp39RrV/oTB4RkgZG6rq6TO6/FHP+598Ivfpvk9xghWeKv8agXa+xrO7f9STVC7/Y4vBsh1cVIv8Md3zQZuYU9Y8ZEn9dDhV4IyQojHeVBS9ed6+A1O6jhU/8uCV8QkjVGGjVl4qhdh+J8Z+6eM6TgyY2uCMkGI3V48npXgk+23+yBM9quzXn+AiHVw0jJoyX+g6fV4f4xMG7HwsTUAIRUHyMd1y++VCPBgru3/XeDmhmj8xGSLUayGO5j367LNo8jPwvEjQRuixFSA4w0OXtyRsp8oc+iEydtzhacBcjb4fwS2G5ovOGW95Fqp36zC3yBADTESBe8Ak8IP3z2T7IfbSMKSVqKkFgY6fG0F/GTiw3ZK0+fz7JPvuOBkBphpH1T3fWdb2/wOfLslUNcaGN7hGSPkZoavffYEX7Rb15x5NX5kVEA3sYYqfTz+dcTXov9d6bmLGm88ulzhOSAkRJHFUvadPRyX7vc+f6ocN8YhNQEIznHTPj+oLSH1xKXLcN2GnY7olTz2RSiqPlMu7jCyClxqs/2O98HX/pt/I5Ee6la83mMSlNahh/atTz3jHvajsLx52wnKu4Oa7jHxwhFYSSJDFTjl5tid8hST9GBErFRPKEQ0YXYrI4KZi4Q9STpqykft2KEirpHHzjQTp1TQM2TOeFsGFqqo+SE0466KUvslL4I+TakxaKhP3lmfn+ksoaxDt7qyWBeJ9O+9hcOorAQgMJI0+CsYWitjkpJCR2CEL9NjB4hhvFBM3JRrADN5EDeTyAEo+VlcsJCHDkWD+z8QklR5KW9yHHf+hFOFT4QVb9ju0wxEiv7HOVIbBmJ8Q01AtdSWrjm6mjkiKP8rEEVhyM7YQstrIxdkkieBNlGjeKzED9INmyOZl7YIYugft/vuh1t36dlp6J77oRDe+yxJIf2OIVx7vnBUmF3I+UeHxV2pcCtisA1wvOL8LNzPhFI8qnKfe2gHR1X+c95aPKwa6NiduWzmRgAayktWIioY/bnOPRfEQSTRRDEjYLaiiB0dU/RFEEUqmYrK1gE8f7T8Pj312/4L7hxzfNwY7PnDBpLogZioAgCAghR5ox/Us1Y/t0iCDFcyzv5qb/7vLs1whcFzmqs8SKIVzp0qBRqxiZWIGCjviKIX2vjFo7sVRtOr33/wKMV8xy0pggin5Z1F7XVnWG4COJaH9sBBrFjvI7Mb91i+7k/p2u4CALVMpRZ7J9IvJSqKoL4cymst3LATE4Wa5CwQ8oqxb4NmimCQJUNJTiFBHCqtAiiu90Y/+Qbez1m6w2oUdI3frCWFEHk0yJ0Uea35UAUftuZFTzuzy5Wnomb7GoUN56gyHUDdDJnsBu34gcHHMXBuJgnjOwQw5FfEb9rnPz0WETZYvIKfC/MdZtUIceJeIxK/t7KXjROUWGAVdfap6QDrJRdpUAYqldbtWOFCk3QNavR6pwgejdn/enVSzKrB9YhxPrB3SSxfvRyeZ7SpQIjZwtHW86quB7P9o2p2Y+B6VSdAUAxpELoDEPOtVUK4VmjAOFy4RgmECPii9DJja137tGeLzbsZq9s9zz7rFtajuKydMNvVl6WZaTyACOe/zEAmAMtYIhEacSJktoM8DftIKof5cpSAxpeGqG8pNGq7Kd3Awb3PemZ6t1qod3Ewg9maE0Qwgzl9s76bE6wY//mlXOACazd/+PX6pKnbI/lWT0Tbox3uMAAa01pWauvIdaS+cfzVRtzWf6UZon945ED7W08VxsEbbJ3zczW3JTmwZhOAlOaY5SUdgS6xDDDeAKiMIyc61b3x3Ta57pz0FDr5L5HFdsQW4D2nhJw9AmSgvkgTM1XYbZja1gUhUAubTKKPias7DHo5rBspGMYIiQVsojE6GH5L6zEDtK/qijo1WCok94p6dZZuZl5WxhqrkeZBVPBEzc2Vw4UcNwA2gYDb0MUzXLExxQi6ElrCcH/pDotFpxGi8byKQqBvH1uubeMimen2MRL3rd7ozgIWh+d+EwyCBO7Xp6O+TTu6IWoHzPgxT1cRjT7sex9ZXVMdRjqAGDW45C12LZEYa7skXATOfbLTrdCRdGx/NA4VDzAoBzy083w7l06NbT4FrBy9YpJRnlZisPyjMqeq7z9VSAyrhJ6YrANJoVtAAobphJOUqmEc7Ubv2/TUeQ3490bX+drUxSPuY2D+DFCXiif5R8nFJLoAiqH2Qm/LxrcB2RWED2GJxSESYV8rEASyRIh2xRxxTUBMVmA5j3JxrfLkSuKbgkHMgDoGpEG3/rC0LtqlV37dYFRQ4e8SsBQUqAkAWLklS1G1meLPuhyD325HT6DP6atovuMPkjZfZZeLm85E5MjKruc33EgfYDcOtJzmUYw9KMapftcQeTqy5ATK4gaEC1S+FLMPNfUnV/dd+m2QyE9Bm4bopgxjgkIeUhHkcr4KkbQQiSJBq3n1dTqYOEvahAyLoYvj0NjudQhZ1/EpeULncHfxDp7eg0DTm4EX0xIVgY/lVXcdVEDCRiLPALZVI+TspqUy0TDVJlFUlm+joClq6CUTeY4j0ZXgUoHYdbSYc3AV0BtFS76YaRQvMmasSTar8Tr4NuCF7amVxoSAhPgW5EEJtDLVQEFKuKUUCAijhmqXIjCUGlNj3yitmRmUFkVtMjProblzpO2yD8ogzxP+yEnpOgxA3n7tyPSJhwy81m5uteHsyb86QxAvlePDvJtMnfsFBXkKieHmuCQqyE5lCSXE08OJcnlxJNDSXI58eRQklxOPDmUJJdTlhyqnMuJJ4eS5HLiyaHCwNOXDWvWg9f6RM+o94X7QSnlDQgv+SaUkAXKQMrbaSr+2/uedLq/p6bHZr2wETdfmCry31x62A8LRbHAXUQDOMpOuT7FarP3EIDxQJFgno70AeiWEuwzsTSEioX3iZmv5b6iEjhkf1TRRVYDhgaC8FI+6dl1OxjqqqvS2XV9abQNLUoRAdYgeCC/UOcFfQvXP7Fa5OCWcWRE55zo0oGVibURFBIxjFdZhWQIQ/11MbNbqqSQrGHIW5fUD6fCylKWEiGPFSlKgz6Mz76kI2ZnPk5rGnDwsC6DaRFT+/h/PL0p3mOraJZXEmdcDgModaVFqaWu8uEDnZ/WKhBfV+hiQzHDlxzY6uG5Z9ShkoifzXplpTVzT7zUYYWRr4OJJuO5vTAhIg/I9Ychf13V3NgWsughgChUrnUGsEAKuom8ZtS/dafvV/f6ZDTdvlqHO2aeNkQtEZDcaEHqqqtaXLeJm0D6zWVHVWUigwYWqRXUGPPeowZcXeS3ve3B5B/uToqD8wzw5ypHEWWUqkDHhRadprq4Y3QGojCML/v6c/Vaf4WXrD/vsTbAe6DyQbyyJdSjALeRYjxXluo2VqRS9zpinUdFYwMVha0mDK0BsJ0nLcHkwtBs1UxdxcK0WcmDrt28/dRjn3OfWOvFrWopHnai8VgKs65ALE+LE1VcZbV4LRhaBcAKJJWxpjC0WDVbVxsFi4+sNGqoHo7cP7yGRZ73qtxhj//6lDdfURO5I/eSAyVHUrdLUAuVGhqYElQ0duWH0PYdb2oVFdItYIHB7rPGHbPjNBdC64/JCAihKc1Lh0JRaDA9dJZKD8HNzrfuMu0hd43H2reSLjYNiOfQUbwYlvSchuS8nMo1bya9D4/2oHUpPFY0fyy4xBcLQjEDWSG1RKwxo3lDspNyOXJFcS3gQA0MT4HmTWQ+eQgM/TRQSVHVRsNQ0sNd5HVIv+X4S63reuSvd507Wmdl5s5doxVdJPQByi6S9HJ5a45YblfZNVfEgeoDeHZQNZaoY6hSNomx9H3o+o25TwrkXV60lpsVOobvYZ9UTTH6J71fOfqHXS8Pny5+owt/pn30O9Tj3rnUnJdvGcCnBi0+iPhoIsPAAE3cGCMFojtE/FGtIblxCE8cwZfQMe3buEUBuzI8/BYEfTFOS32umEquL71fmWnYdcaVJcKV9wZ0XHmhVVwpzca5opL5MkEVXgw/DFO+5J1RUsf17xjlw5m2Tr+/cXvoiCJj/ND7lRmDXWecMcNhqToBx4zK+1UJDNUyVG1DVl+GAbqxEArKw+Prx47G/dm1fZN+fXSya92+kWJWLSx9gHJWLU6oCkR+GtAhUmKA2/VzEIVd373Q98Ogbl29Z3z4KTE4cUcxcoR9YsWTYbrLdhiKBpw1NlIQGom4laC2kBcbCxoryLJiMPNfsc0HsVyc7H2VZVJ6XYU80VwDLE9UOfvFFYYOKtt1FSPgtpirAYy9QNorB5QwSd+EfHv75Gt155JantuC2V/uLdugeBpbg8qxkRHUbfwNYOgEwNCFLEcDskMxVEljdffHJEraHVShUAvkA8VKzwdAR0Lw/zKfkjXBfxIpokR7rtHmpGBfiwJmTQrYMBQwbDGfp1rMWhO4IkoTQ/O0iWEOBiJXSwzoIldzZZhfoMLc/6DHxTPQSThhoE03QbGPYnp3bXR2fYxQEIqWhSkrUiqk6/sh/gBiniTInUJWlMJTKqQniQ0y6F5LuaeWIr2icCL7oCa1EDjnkB7ctIMhk1qnjGWnkbjnhNuTmt5AlyrwEnxSDfSydxguAwPCTv+pk23ollli5Wfc0vwyTtehoBsFoOpFSUYMpNepHyx9H/R1wZ/QbdwaeAjEiM4B2QloMpMiv0j5M6qjVV71K0+58/vctXl6IG2qAn902Mqrg620OnQIq6NZzbVvoIaj/Vbd7xWafan0RGVXhy0MNQbsdCHLXgAJOja1TsmBVN7Jkl0wP1SEaGhVUApZ38qiY8An/3mLb65pF3vFTREljjJKnHJRWhsxyrHYM5y7sntkdZNDn9YwgJIJLUrVa53CZFAmS7TZLtK2hcAxqgBAxKx3RRsmfZSyDcOuV8WBNyoxX8gOmhL8UaQwfXrxH6ZPiV2F1KRPZxnS6dNYw//0KcafPh4nR/5h19njoMcY00vDBogZ0KfEblEMaIqZhnSaYpJhVevTrkYrnebfmuS7PHLQlm6r9KIZ0KdjmvnE6i5zhlcPvXTaeMDDStfd2KJiTYOSwLAK9SnRhmpcn6ISQ6lPEaQwfXqJSp9qzZ6AuJyYSWbroGPzdi4c45b+0TVy9/W5QQxsCdwN6bYEPWSQX6aCXOVkNlMccjUks5G04sNVPUkrPjyZjaQVH57MRtKKD09mI2nFhyezkbTiw5PZZr1t9fbGymTfRCenLYN2jHeXS2bjz9b5FhHWx+fAYEnps5BNJXKdDmcVugc3bn/Jdbvr/a7RHSIHKeW5gT8iFUxi6z8G8tyuMCYaRmoUjb/XBJOkIyQONzFTQIknelQ8IfZcZIAnV6l4sjyjYMDMoi/emRkHMveMeqRYHVg9kBfNFyp3l6VSh45sVgy4Q65FNitaJOFLWxJJ+PESlrSzLOnXJjaNJHmViuhIo+BQsUgoDAJ2DlyUnyZL0J/Tm6f4P3I44T9n4dyFRwvePqPSnwZ9YvniEOT18Y9t4iaKGyEEGV6gjS1oFxQmkGDfHfFLQGykMGETgSV4n2EltZvDgW7rI2q3CwwlzIRr+vHEEYJoLj9cwWwaSS8HgYEj8tcNpddDRDHyVxV1d0xkDmd2vv4pExTEQDGoNpQIpG9VA38rsgUl5o31jg4DzbpweHUMwUUQsJG7hHr4QqwnsnQbAcaYCHhCGHSQkjNfEjGfFyX7Xa+fmBcjuwcT1WtUoqo1xpzYwpShAz6i/DNgzavXoLPmP/Vxa35d6zEn9obV3kPVe7TlANdl5QA3qDBX2UzWgtRnJkma/uJmkqTpL24mSZr+4maSpOkv7kH18nT1Lh2Y7JF5vdBq+eqI9UoWFGhUUmkhtgtmwILepGKXlg5FI7ZFVttQtChTuqFoXUyreijagWbzj16e6O+1KOi0RNRvDksLhqKNMqUbMcMz1YLJTmfOnFHDULQXr+CaJhte+WSe6Z16cFJbR60YitaPljt+2sAdtQxF+/Fkn3frk7U99piU9uKnZipmOWpqKBpMy5wu2sAcSJND0daduzExaHVvv2W611IiPye10aqhaK1pmddEM8zTzqFoU14kz9Ef8NB92q8BzxqvzIM0PBStPi3n6micc+CmKhuKdizX06F+fR3v7DWjVzTkvuqiFUPRUB+CcigaoggxP/UWROGn/pOGohEHd2h4KNp+U7qhaKuUXdoqGYqm17pu0ezNJ9iJdbceXL/jqWKqMBND0SZ8Cjow/tpCrwyn25OvvP8gYGDQ115TukFfW0yraihasWnfZJPHIp/Nd2oXLti6dybjQ9GIOoIBrFbRYrVYvTpX00PR8qnU2H/9+f9Wf37ivCO19eevVYeuP/8rZd3JQH/+mJ7eLc82u+SbfrClaHe2914GC9GZ1pHPOVDNOnTtzKE6aunPf/SLbVZNdhPfbSYdWyw7lK7Yf1YT/fk/mdKh8krjHqh8WEkz/fnjHo5/PUTYirv6yrRBbRr3U+zJocn+/IW0rMvXDOvU3p+/3YoS8341Z3ksyuZFhCd1tdZwf35Uy1A2WEe0jNr68ydvrnGnro4Jd/XN+QWGGT0staA/P6psKMFBlI36+vNPFW14tFi3gWfCoV0bepnGntKGThcIQoW0COXLtp+3IQq/zZ3douXvHtfZWx7Ybb266k07xRYDaH1fjEiIWHRln82AAucOZSESQdn9WJsMBHGxKC4ikiUba6tKmwfiDEjKt1VuiCBHrCi+OzhQrBmCrz8MDl2I+MbAkLdZZWuuLMpeC7mKYUH61S+/DW8f4bMl4MCpMw5jT19RnGH3t8Z6EVyoA2/v5t8wXspe2MswOKjbsLWVdaF2c6DRAL1aMJl02sFQhJlKLlQt6fIN40eI+eT+ZWy9Dl31wx+6Zp57eGjUphqKRyn6buiNJMVT0uuMr07k+w+h/f7BZpp2lmSSqYKjBF5ZIAoThNK0vTHIGTq2VfQX//UWV16dneBwX1FW8Qcoy6qMUhXM8KZlRi/NMIPo/kCqRCycfaNFEsR88ULB2amjSw9ky4rsLKJasdr0CI0UicNasdr2iB0tlqC/kHurui8zTfXHbPbaJal2R/zkKKxo18AHBEvGCUlGY5aRqoJZHWiZ1VIrVg74UclbtSw76I6OE4+IpVlByUZbfmW81/U92MG01UrOCfvKbJUry46JsFSRgyrQy0pbh5nw9lAz1bxUTJPTeFsXnF8+M8vwDZgTOjAmx6KhoWa3vQgA/XAA8kkAAKpFJU8UN2XU/ScuZB9u1+jOGZ+Mafrf7T9mLSOYMjXXASMAdKcDoK+zGe5o3oH+Wfk4xNHhasvHqWZOl49zSdmzZDgf54HehYv15nXx2LzlzSaX/WPCtSAfR8ecLrr5WTNKXzGpYPfu3WrIxzH55HD7jUlXv81fkzxCw0c+1Yp8nNdmdNx5rA3cUUs+TuyEN603nFwbkLapw6Dunw1aaEU+zm1a5lzSBuZAmszHyby7KmO4c4nrTHMj09LnuxO1Kh8nl5Z5hzXu7GpRPs4rvYDvCUZmbn+k1f1xbqPhBw3n4+yh5dxmjXOuSvNxXvsMisyNP+uTbHGoMPVDj3ZakY+D+hCU+TiXZH7qXehfkI9zwSvwhPDDZ/8k+9E2opCkpRrOx/E0p8vHaWOunnycpsvygltNGeaecrNl0cm91dIZz8ch7s0ZyDFxN6fLMelmXlX5OL2Nmr4eUNLVJ8smqctBQ/YHxvNxiDqCAaza0GLVzPz/Kh/nHpUaG50taCnw3wYfzAoQPisa9EYxUtI7DhRIeop5MZHKZaQqhC8c3ASxMaBETBbNGeckLSVl8UA7vQjwCaSS93jai/jJxYbslafPZ9kn3/GgfD/lSI48UUn+DIMRFRYgX29FIpXE4qYKSqXsaST5NIGgZ1ddGPxTlMp3QU848wIMThkH84UIw/hh3ohej8cfh7JVysr7VKxUufCslUy2q77wLP2aY6OfNyZ7rHVOOf/xzZJRcoVnq3uebGU1vxrnMM9+x2NbX2u5wrPJYxJZnfS7es/itP0rkxsilCs8K35mdKjF4u+e+16G+Uz40LRUrvBs8Oqmpiybrb6zf1Yr9L/wSiBXuu/569QywfjSgDn5Ztv8LB6PlCvdv90pRbyguAY3eWDQjjQ4brlc6f62x7PW+u/ey97VL96laWzAUbnS/R5RW6ZNflfsuW7i1dwmpnqpCMkQIy0ZsyY3pFFtTrY4rdWPwQGbEFJNjORhtXlr6zXfPVJnJF/Z8WBJAEIywkgNJNbt394Ss5PuV7Pc79sRVKvXwkidra7pmF8Vc/ea94yxfDrfAiEZY6Tecz1Kh8acdM/ot/Tb5t+9kxBSbfx72V1d5uX9wH/rWV0Hi+K67RCSCUaKf+C40X2yFTvj0eLvTxccOImQTDHS1RWTfhsfTPJIMuaFmA9wmYGQ6mAk0/zuE/jzdQOyD4THSWqdfIyQzDDSmzdPaz/fYAAv6FBa9+2qhj8RkjlG8veJXDNle6z/2htRz+ddO3IRIVlgJNem7gFP2yxl7xoypKNeeMhthGSJkV7WeTKvndk87y2fr/ld/2T1GyHVxUhml6cWz3lxPGBhv/vTBUd8qyEkK4y0eHPX3ENdWnDXWu7UHWqssxohWWMk5+lz1o848dtr9psMTuefVzciJBuMNKDX67YS+3YeS+bc+zn3qCXgcj2MNC2odluzvRZe2wYtdbxWU/IVIdXHSF6LxKdPP13tOeO1wcx7tmfPICRbjBTiYFJb9N6HffDWoSN1IWuAYQOMtLR2Xs/OM9p7Znycd1gYUS8CIdlhJO81XV8tzWofsKA0K2jM0L8WIKSGGKlQ32SyRaQ3e7lEd1CzI1HjERILI124OmxJ7+pFftvZhz33Ld0ahpAaYaRftW9kfVhg6Tm9pWX/ttfbv0VI9hjp7O3Fxq9P3PNZIf5wbsEJ+CNCaoyRus5rsXLHz1Zua9vvT3Fq2uQaQnLASH63zK6mn2nuP6/xk8DO56yclAo7m0AUhZ0O/JvPtjtf8E8YcvTagOzXsxko7HxApQ4tww/tWp57xj1tR+H4c7YT1ygeXLrHxwhFYSTZClTzUZtid8jyS9GO77FRPKEQUXhYM/0KpicQlSHpqymfqWKEivpAHzjQF4tTQJeTedpsGCq0UG0WRVn2pvRFSL/bynElQ8U6I11TohZNbDrB2rQyEakqdqi/cKBPAKAw0lw3axh6ZaFS5kGHIMQ5E6PnhGF80C1YFCtA0zWQ9xMIwexnmZywEG+NxQPbu1DyeqKNMcfOc0s4Kycf5zXuPuqOYrhV9jnK4dYyEuO7ZgSuQlq48i20IjaunBqo4vRSJ2yhhZWxSxLJkyB7pVF8FuLsyKZBUcdlz+rfjhvNbem996VD3Xp9WrMIJ/PYY0lO5nEK49zzg6XC7kbKPT4q7ErRWRWBa4QnEeEH5HwikOQTYAv2W5lPOeh2tP/STXrbB66rfMoSA2AV0oKFiDpmfx5C/1U6MFnpQNwNqK3Swc2SrtLBwbIqKh10kqbenLh/LXv/Sm5mP8eNexg0lkQNxEClA8eSLjG8s6VaKh2OLTVvMuRdXfdpfTf36PNrTrzGKx2caVFB5EZLozLqq3S4nO4++nrkbN8j936seDnv9m6tqXSoR8s6U82wTu2VDpv7hX84NHWc+67JTxYlLZ1PGMuk9koHVMtQpqojWkZtlQ7dIMGI9MQu3Kml+xPaNT6nGMHXTKWDMy04DpZqrHRYZPKGFc6J8N1fx2TCJX8LPS2pdKhHixCypjG/rQCi8NvOrOBxf3ax8kzcZFejuPGELEVvFB2dF+zGrfjBAUdxciXmCSM7xHDkV8TvGic/3hFRtpi8At8Lc90mVazmgXBWSv7eyl40TlFhwsxTFjZhRtlVCoShPFYVjLg887x3Q/OWd1xn61S/2pRn1YkQ0Ad3kwT00cvleUpTOoe3b7UhzzN1GN/s2c2eZgyMjykCAMWQCqEzDN1hqRSns0YBwuXCMUwgRsQXoZMbWxe453mL93E+RxY2fBnYM+hPxWXpht+svCzLSOUBZnnTuT6n1N896cNKttWOqHgGALtMCxgiURpxoqQ2A/xNO4jqR7l81ICGl0YoL2m06vWAq3aXfzu4LRCvi/vc0O6ZGVr4gzDDPT5GzJeFCVGnls0JduzfvHIOMIG17NGm7UYPbOA+//PqOZIRT/wZYO0RWtbu1RBryfzj+arNoSt/jOr7IafHzogvdd/RtsW86oFObTU3RnUwppPAGNUYJaUdgS4xzDA+gigMI+e61f0xnfa57hw01Dq571HFXsMWoIenBBx9gsxfPohF81UYvtYaFkUhkEs7iaKPCSt7DLo5LJu5FoYISYUsIjFEWP4LK7GD9K8qCno1GAq1OoXuNEhmsbWFoT5Wla0LZHPlQAHHDaA3MPA2RNEsR3yOGIKetGAQ/E+q02LBabRoLJ+i2mfgtyaLvtpsZS/Q/ZHb7+Kde4o6Bh3JSjKpDrtero65+ceT11sOuG7PuFdrql38tsrqmOowxAMw63FIpo8lWKIwV/ZIuIkc+2WnW6Gi6Fh+aBwqHmCSBcXwu6Y3g3U7dfbbksd/WPhwZAfFDIay5ypvfxWIjKuEnhhsg0lhG4DChqmEQiqVcK524/dtOor8Zrx74+t8bYo7cW5xjJAXymf5xwmFJLqAymF2wu+LBvcBmRVEj+EJBWFSIR8rkESyRMg2RVxxTUDMCKB5T7L5ynLkiqJbwoFaAnSNSINvfWHIstJrvy4waugURgmYGgiUJECMFIDOtz37GfZcyN5Wx/SAf227xoruM/ogZfdZerm85UzMgKjscn7HgZoD5NaRnss0gqGGVpTucwWRqy9DTqwgakC0yOPW296OerSS5T9DN36k84fAKYpp4ZiAkId0FKmMr2IELUtatIys1Opg4S9qEDIuhi+PQ2O5/CBnX8Sl5Qudwd/EOnt6DQNObgRfXJHCSRUVd13UQALGIo9ANtXjpKwm5TLRMFVmkVSWryNg6SooZZM5zqPRVaDSQZi1dJoq8BVQW4WLfhgpFJesa9eeclfMXjgz363P6eq/CIEJ8K1IAhPo5aqAwpIWCiOZoXoMURgqrWmET9SWzEwSqoI++C/r0vXBf1wXh7xI6yEn5uExAzmv0W+/hqOmeG730reu38b1BgOQQ9Z0kH+RSfkTKshVzgA1wSFXQwYoScImngFKkrCJZ4CSJGziGaAkCZt4BihJwiaeAUqSsIlngJIkbOIZoIUrGn5vu7eF34ZBEedmH/BzVkp5A8JLKn3EVE8GUt6eUvHf3vek0/09NT0264WNuPnCVJH/5tLDflgoigXuIhrAUXbK9SlWm72HAMwAigRDc6QPQLeUYJ+JpSFULLxPTG8t9xWVwCH7o4oushowtA7EB/JJz67bwVCiamH++tJoG1p5IgKsQfBAfqHOC/p2Jtan/xZrr00FLhOe+OQOqUysjaCQiGG8yiokQxhaY4mZ3VIlhWQNQwuUA/50WFnKUiLksSJFKeqwV/HrHTvhDHNP8869tzZiMC1iah//j6c3xXtsFc3ySuKMy2EApURalGItVZsV3yoQX1foYkMxw5cc2OrhuWfUoZKQayeXub0d6ZU6NHxG/1f3JmgyntsLEyLygFx/GEpRMZ7bQhY9BBCFyvXHABZIQTeRRy19g90e/GHIndrcbd7Fblt/aUPUEgFpDi1IiSrGdZu4CaTfXHZUVSYyaGCRWkE96f2txagnLfx2mXtd+bFqVYJiFBF/rnIUUUapCnTiadGJlsV0n0EUhvFlX3+uXuuv8JL15z3WBngPVD6IV7aEehTgNlKM58pS3caKVGpRRyzmqGhsoKKw1URceADbedI6Sy4M3VDN1FUsTJtyslQyo+M0z1XLB9pwr918oHjYicZjKcy6ArE8LU5UcZXV4rVg6AUAK5BUxprC0EPVbF1tFCw+stKooeqTu6zOkVX9PY5KdnixzjgqGjlDd+RecqDkSOp2CWqhUkMD0zkVjV35IbTA8fn8xOG5nG216y+z4bxbpLkQWn9MRkAITWmgMRSKQoPpoedUeghudr51l2kPuWs81r6VdLFpQDyHjuLFsKTnNCTn5VSueTPpfXi0B61L4bGi+WPBJb5YEIoZyAqpJWIhGc0bkp2Uy5ErimsBB7pnewqdGE/ik4fA0BFblRRVbTQMJT3cRV6H9FvaNVw9eJHTZ+8ZwTmiW8Pvpim6SOgDlF0k6eXy1hyxpq6ya66IA90B8Oyg6h5x2ValbBJj6fvQNRWbU21W33UvJvvuCypu4/FovI5i9E96v3L0D7teHj4xvcZfWdX+oFuyuc+KA40eRTGATx4tPoj4aCLDwABN3BgjBaI7RPxRreu4cQhPHMGX0DGta058s7sn9P22Xo0Tr+wz5bUi06T3KzMNu864skS4speWK1u0iiul2ThXVDJfJqjCi+GHYcqXlDEdZ29/4l5tIeegUebmgmMjeYqM8UPvV2YMdp1xxgyHpeoEHDMq71cliAm3VW1DVl+GAbqxEArKw+PM4YffUtyKPY5+zR1t1vxXa8WsWlj6AOWsWpxQFYgcoUVkpy1u119AFHZ990LfD4O6dfWe8eGnxODEnfeKPJZ+YsWTYbrLdhiKBpw1NlIQGom4laC2kBcbC7onyLJiMPNfsc0HsSac7H2VZVJ6XYU80en1sTxR5ewXVxgaU7+yEXBbzNUAxl4gbYgDSpikb0L6xd3vPb43MuyV6/ySereqWx1SnM1eg8qxkRHUbfwNkL0/wNCFLEcDdLhFMFRJY3X3xyRK2gJUoVAL5APFSs8HQNtB8P8yn5I1wX8S+bAWgj3XbAdSLgaYNSlgw1DAsMVcTLWYtSZwRZQmhoZmE8McDESuguvTRa58ZZi/pMLc/6DHxTPQSThhoE03QbFPHcUOVeiA+hihIBQtC1NWpFRI1/dD/AHEPEmQO4WsKIWnVEhPErtg0L2WcuMsRXpF4UT2Qd/tEDjnkB7ctIOhJ3anjGWnkbjnhNuTmt5AlyrwEnxSDfSydxguAwPCTv+pk23ollli5Wfc0vwyTtehoBsFoOpFSUYMpNepHyx9H/R1wZ/QbdwaeAjEiM4B2QloMpMiv0j5E/rNdU19i05+a7m9H+cF7p6lwB8dtvLqYCutDh3C6hgwXbfdX38a+B60iOvrPWT268quDlsY+grY6UKWvQASdN7YnZIDqbyTJbtgfqgI0dCqoHRk0aq9jd79dp0/zWHiJXiNYgaiDkcZJU65KPnx3yc7rXJwn990ad1ij/BpDKD0hBalu3anMBmUyRJttou0NyFwjCoAEDHrXdGGSR+lbMOw61Vx4I1KzBeyg6YEfxQpTJ+++ofpU2LrIDXpU/cGdPq0dYP/9CnGn41jHBa0c2RxZ5/r3kQkeDWSAX1KbAnFgKaAG9Bpii4NqlqfvljuLvhzUhJ3YdtpY21yt81iQJ/OKhCeeDxygNfctaX7fR+diGYApda0KDVpUIX6lGhDNa5PUYmh1KcIUpg+fU2lT7VmT0BcTswks3XQsXk7F45xS//oGrn7+twgBrYEug3otgTfZGcqJVSQq5zMZopDroZkNpJ+e7iqJ+m3hyezkfTbw5PZSPrt4clsJP328GQ2kn57eDKb/aNXh41rfoWP2qU/HfnM7aFcMtuVV0/e9+g6kz372ebWb93a3pJrZ/gx3GrByWVr2PPr2vXZ4Gg1SCnPDfwRqWAS+/sxkOf2hjHRMFKjaPy9TpckbR9xuImZAko80aPiCbGxIgM8KaXiyfKMggEzi754Z2YcyNwz6pFidWD1QF40X6jcQpZKHTqyWTHgDrk+2KxokYQvbUkk4cdLWNL2saRfm9gZkuRVKqIjjYJDxSKhMAjYOXBRfmQsQX/65rs6GdRI5MzbMa4wx6W3OZX+NOgTyxeHIK+Pf2wTN1HcCCHI8AK9akG7oDCBBPvuiF8CYiOFCZsILMGbCSup3RwO1L8eona7wGDaTk0/njhCEM3lhyuYTSPp5SAwVUT+uqH0eogoRv6qou4uDcrhNO1X75QJCmKgGFQbSgTSt6qBvxXZghLzxnpHh4FmXTi8OobgIgjYyF1CPXwh1vhYuo0As0oEPCEMOkjJmS+JmM+Lkv2u10/Mi5Hdg4nqWypR1RpjTuxTytABH1H+GbDmi+vRWfM59XBr/k7rMSc2gNXeQ1V72nKAetY45u+pMFfZTNaC1GcmSTr74maSpLMvbiZJOvviZpKksy/uQW1Iadg6diXH41BorUCDBZGlShYUaFTynQyhJzADFvQDFbu0dPIZsfex2iaf2TWmm3xWbF/Vk898fr0wf3S5L3vVyjnOjZxWx2nB5DPbxnRzZMwaa8H4ppycHDVMPvPcbpOT+sWMs+PUtryeoz0JM2U0NPnMgJY7v+y1gDtqmXw2OcZ594EPNz12uEzclfvrUJhWTD77YE/HnGJtYA6kyclnln8uO/XjeLpH1oYjZ6+1/TFMqyafFdAy76ZmmKedk8+6zMy9afDKkz3v8q1WH2JvHNPw5LPztJzL0TjnwE1VNvlsfLvus0vz+/lvmDfxWcMnETW0YvIZ6kNQTj5DFCHmp36EKPzUf9LkM+J0Dg1PPhvemG7ymU9j9Uw+69D+62rOiTD/JfOWbl9fclUx3M3E5LNBozvxi/TSvf5InWs8oYtbSwameQ1tTDfNK6RxVU0+y63bhOvwYYbHhijd6ser7dhY+SVMwIqoIxjAyocWK1f17hI0PfnsE5Ua+68//9/qz08caqS2/vx7GtP151+grDsZ6M+/N+f0uJkhnVynXvAsmJKYu4TBQnSmdeRzDrSrMV07843KOrIq+vPfbeUUMjXe2/VQg5Grfs2eqNh0URP9+VfQorJAM2cmpHsH1WqCmOvP3yDu6KrBnuv9ZolTm/smXhurNf35Z9KybpJmWKf2/vxPTIrsp04YyJmTo79y3d6gnhruz49qGcoG64iWUVt//l+vYgdPDP7quaSwlU3O5VvZWtCffwUtOAsaq7E/fzWPRqmvh3oErF3Ya02dBdGHtKHTBYLQTFqEkDWN+W2fIQq/zZ3douXvHtfZWx7Ybb266o3i0a8RWt8XIxIiFl3ZZzOgwLlDWYhEUHY/1iYDQVwsiouIZMlm16rS5oE46JHybZUbIsgRK4ovsrXUaYLgy4PBoQsR33EwdMuhsjVXFmWvhVzFsCD96rP2Wl8wuVDCmXHeYJdOsWFJ5cd6EVyowoHNmv5atyFg2nG2cMJ5k++VdaHSONBvBwS9hjCZxWkAQx8dVHKhakmXbxg/Qswn9y9/bc7V8XVk+67vGrtmxWeXc4TiKfRGkuIp6XXGVyfy/V/Sfv9HDpp2lmSSqYKjBF5ZIAoThNK0vckPZuVszNPxO+oz86RjRuvBirKKP0BZVmWUqmDGLVpmXNAMM4juD6RKxMLZN1okQcwXLxScnTq69EC2rMjOIqoVq02P0EiROKwVq22P2NFiCfoLubfKW7p02NvONf1TpwQ8bng6P1jRroEPCJaME5KMxiwjVQWzTtAy65BWrBzwKJW8Vcuyg+7oOPGIWJoVdDA3ybX6m0ueu16tsz3x6FPtymyVK8mOhERYqshBFehlJTdjDrz9rYNqXiqmyWm8rSV8qzdnXdZysg8dCezducddjW57AQBPcADySQAAqkUlTxQ3ZdT9J7g3ru26OiHV/8C26kWnn1ztq9E6YADAWToA+h5xwB3NL9A/Kx+HOB9cbfk4s5vQ5eP0bVLV+TiLL93MPWfm5L3fxXNUgPeohlqQj5PUhC66ObmJFiQVbNmyRQ35OKuXmq4I7h3kdfhGmt+mRz1OaEU+joSWOyO1gTtqyccJmDCu7a74+977Bn+efexdtwNakY8znJY5fbWBOZAm83Hu5BxquAzK9JqVd6wwLmBrX63Kx+HSMo+jGeZpZz6O26d5n7PS+roeHNHfI+/e7CUazsfpTMs5Z41zrkrzcYJnvi4U9FvmmtKk3uGhpgN/aUU+DupDUObjIIoQ81O/Qv+CfJxCfZPJFpHe7OUS3UHNjkSN13A+zvkmdPk46coubZXk47QcVNq369Rd3LTBmeYTbXTHMZ6PQ9ybM5BjcrYJXY7JsSZVlY8za+3lexm3l7DnX90w5OjnBTmM5+MQdQQDWKXTYrVDvTpX0/k436jU2OhsQUuB/zb4YFaA8FnRoDeKkZLecaBA0lPMi4lULiNVIXzh4CaIjQElYrJozjgnaSkpiwfa6UWATyCVvAtXhy3pXb3Ibzv7sOe+pVvDKN9POZIjT1SSP8NgRIUFyNdbkUglsbipglIpexpJPo0h6NlVFwb/FKXyXdATTolB/VPGwXwhwjB+mDei1+Pxx6FslbLyOxUrez9+GFBDeNFz9aEs3SnpjRRzhGoizk24hAXmclV8JmD9gPBwwC+eUIiNrxKAwSOg+WHFTk1SG0S7PJgW6TXTeoeTTtH1B1SvRFL7V9GVbg9DR0zzICiEQ5ajBMNQd9O8SgbfjNFpZoh5iQUvTPpFza8n9t4xK8pv/6XjBj0P12tDbJhN+hXL1Ypj7ztCP31aclYdDfYenLC0e2W1ogMM7QdYpbLJDsydYGiOIlblhtqkHBShUkKKy4642gu7jg6FN9XdZdT61YSbSn54eMWAqazHh3zzMNpvjkiJFvjgqgbZjEAFNl1RfovP3T5vNu3ptS4xo0uz1hdjFOUS3K0u+C1o4X9lohH4lcJqlR18KF0RIEUE+SakHJnwo6l/m3sT/Y700zkSuM3q+d/UFJXlSACmCo65ko2mDkIXBGZwfkD/HIMz1Mu+2PLwU9dNYVxeP4s/Z1aNwTk5hM7guA1Rg8GpvjLFvN5vH3heh2s746/Ua8SMwam2LSo+aOgJz1034D4LeBdCGTA4R4bQrfvFQxg2OLMGRfiM6iv22VW9z+KsZwszNGhwhLTfHJGSf6PB8Xx9u3raAyu/OcNg0clFNVpozuDY0sL/YfD/i8GxPuzU7PrvcN/V+bMs2n49X6Q5g4OqAkqDgywIzOD8hP45BmdmtZmevG033LL+ulzHsujikKoxOP0X0xkc68VqMDgHmjYwLjzQwXVu23Eu1dZH3WLG4GzrvbjOsccmnrP01vzZ5wV0iAGDE7KYbt27LmbY4JT87tVt5sDv7D0+F099PhReokGD04r2myNS8m80ODV5M1o98kjyP+QSPcKk3VYNGhw9WvhLF/2/GByH81O+Rpv9gqc+nLrmUeHEhpozOKgqoDQ4yILADM4viMLgrFkwN+6VzxfPlNF1Y5fPbqWo3fU9QB2ORDm4Qxmplt7AihVF8VlhiASw4mJB9AydCB8pEoaBoQ+gujAc/Ts0sibhRcRWyBD97tbs7tsbVuztZs9m6BZdsNDnikJH8cNkN5G9unJmmPR6RSH+woFcG+YiXxgms0z9EW3bIFe5yTOACISESZo8g3/EJs/+fzzoGXzqpev0c/sTDN4GXCc2eZ7Wb+2UOzGDvVKPrVn2NHVOT5yuC1WyCTTxg0maQFNqLdBtEGMjKbdeZhhHcVv3cMv6tMThdcvVoyvDLeaXzg8OxAJ8TSONnjSBoQS7XHUqM/xFjaLjhMJhsch3iI6QfVn9st9RkzvBpWvQJJJe1FS8MvMoW22hcUJJnJg8BnYkYE/pxX1/es5ImH1tScD1tbQsqwFLn0QyUQkjVAXTChrQMQ1ZjJqwQHpcWKpQwS1TZOse5Q2+RqmMjT14S+mcoVi+GC3gQz5CQWGS8mpi/+CX0Pks9yU7h/leN7FuS+RVDb84CW+EkC8Dn5A3Cz7VRdlKuZTbUbx6yaw49oDZXkm92YMuiLxcK+vPIkxdY0vHVMg2l9hRnHZMIybsfGk/V/K5DHsim9a0tuVOGxa1qf+NsNW0gq4HNJ3yMFD0KuMiHgZL9dIxNplJj0FFHDPpv6F/vknf+EenVqsG3ebstZOYnrW7nqQmkw6F0Jl0KOg/k07Krc31No5fcDDRbUbDY565PdN7ap1JLwimtQ7B/38mPYFdtGTaeBZ33Snd+Tkb73O10KSvCaLV/kH/NyZd/5WkoWvnVvBUp/GzU9NXX1ebSeeGTB+8PU3PY9mIT5usDo/vxYBJH96bjqnHAhk36Se73RuylLeJsztmVEGfkktOWmXSUb1EadIREcdMOkDgn27S923lzN7l/4D7V+Tn5is2tU9Wk0nfbZ5HY9JdzPP+M+mkRV/ffrvDA/gBG3nXsk6n7F+gdSZ9C+Ar9S7dXK1Hjlph0gfHb5pSx3aSx/ar1Y/NHcyto4UmvT8t01zUyzRNmvQJswauysxt45v0MuBlC8hosNpMerhl8FedGRM9ZuocFEc38k1iwKQb0DK1wCyPaZO+rlHUjLA7s9lLXIsSOq8d95dWmXRUL1GadETEMZOu8y8w6dyUxan2IfZe6z8P6gMvdeyiJpNewKMz6cN5/5l0Um7NiDV+nD/N3H99r2fzr8UM66V1Jj2fR6dIdvP+/0z6nbZrR140T+Ss+6o308/9dhMtNOlJtEwbrl6madKkh479GN1KX5c7fUl+y/yo+TfUZtLn9LeYnbWsBvvgnotP83qHP2HApHemZaopj3GTnn438SZvwEhO9tncLn1+6H7TKpOO6iVKk46IOGbSdf8FJr19qbiOkdFWt8Olu0Zl1L+lqyaTPj+FzqQHpvxn0km5Vbrl6NGRBad8U4N8J+ZO6mimdSZ9TgqdIolP+f8z6TfnxLq5H9P3WHDOR7zswbmPWmjSw2iZFqhepmnSpFs1ObFrV8Ztrxm8Ef0+CdNuq82kX2k5q6G4Xg6cWVjM9T93ej4DJr07LVMdUxg36a1u2CU43uvsmZT0Zppvv9U2WmXSUb1EadIREcdMerV/gUlvMTI5/XheiU9GUVDv6MtvHNRk0s9m0Zn02Vn/mXRSbpk0Ee0eV9qMO69NhmV43asrtM6k52XRKZK9Wf9/Jt10atvuBulNODP5D0Yb9wpsrIUmfRUt02arl2maNOmdji2Z2uiFKGDPA8GXPX8Mqqc2k/5x6freX959DFi1w8spaJDtcwZM+hhapo7IYtykl5wxP+9Q4Ou2eMHVHy5nWxVrlUlH9RKlSUdEHDPpev8Ckz7+a/G2wvXTuIcL2l85s9l7q5pMengRnUlvWvSfSSd3wJYNv/dtwUbOIvO6btVOientgyZM+ogiOkXiX/T/Z9Kd8wPtf32b7rVhUKuh392Ke2uhSe9Ky7Sm6mWaJk366HtbJ/+CCv1mdIrenLGkp73aTPrLSyFeI6r15mSubvbL9bzoIAMm3YyWqb8eM27S/VtbXrHZF+q6e8E6TpcJ+/dplUlH9RKlSUdEHDPp1f8FJr2Xp6t36cBkj8zrhVbLV0esV5NJT6x+isakj6h+6j+TTjp84PDJd0VdO7r+MdJxcLdxd49onUlPAHylVCRjqqu1BaBWmHRem4vFiTw3TvLEiQvYOU3pq0Q1Y9KFtEwboV6madKkr2g7/v6Gd9v9M33YdtdDM2epzaSPmjJx1K5Dcb4zd88ZUvDkRlcGTHp/Wqb6Vz/FtEmf3jzF/5HDCf85C+cuPFrw9plWmXRUL1GadETEMZOu/y8w6RtSGraOXcnxOBRaK9BgQWSpmky6yJrOpAdY/2fSSbnFF9qFbL6c7pXlebzNmwaH5mqdSY+yplMkodb/fyZdIuzdwbHfcbd9s531fzoNHqSFJn0ALdMC1Ms0TZr0K1kvzY8+W+OdfPRWydn+j43VZtL/ZidjOqa60zK1mzXjJt0339XJoEYiZ96OcYU5Lr3Ntcqko3qJ0qQjIo6Z9BpUJl0Le5s5F/TqMXd0vsfuQTP+x96VB0LVd+EpS1LRQqmkCYmopH21zFiGsWtXloylhCxFK6HsSYrImmQrJSq7hKRNEu1p165dm747Y/i4M/cXde+409v3/fG+772Guc85v/P8znOee6/ncENdVWyebeZcAHq2mVIBB55tNtpH+5QRz3g9z5rhETe+iaH0ME2dIc/OiJKStOMGWqlP9DMdgsKzzRwKQI+YWlqA8rPNdFymjNUd0KB7zO5I6aEK6Xs9+GwzDeCVQ1nyNz7brHSixUTSZzXdwBjTJT97333Rc882kwDCL9gz8PfAs83e2IfH9hVYQsp+8NV83KRlH3ru2WaMUlCigvBsM2hBMAlHgIsIZ/f+89ciqcs1j2xo1rU3XjsIG8JJfAAiHMsHHCCcy2UuVryVj7W8ffgf+5/4NhEdwok/wzPgdbW/Rmp+fnC1j9k0FAgn9gFo3Qc8QJlwgqOGxv38tlDTX1fn/CYzM50eJJx1wCuHsuRvJJwRUR/5Pn26pemnOOfO/LP3V/Qc4egB4Z/dM/D3AOHQeq/IHvK1SXMbb3WF4oneWT1HOIxSgEg40IJgEk5fLiIce4PK6r6CI0gJ2g7bRzRTP2BDODt5zwIIx5EX8X1n6BHO4OypxbIS2dppl01Wf59ATUCHcKznzpoxWuSrfkxc9OZ+FUXaKBBOMB0rxHXvzcvyhrM/fF2AyFRSw9UjmhFxS9P59WqiepBwPIBXDmXJ30g4eyyGWcaWvKKkGB4fu6up7/OeIxwaEP5lPQN/DxDO1LeW+zfmDtaOiVP+UCVM8+k5wmGUAkTCgRYEk3AEuYhwHkSP/qaUNV43aZnN+YAc3YnYEE7FMBDhJA/jAOHk6ZYbS2xQoOxZzxM8/lhjNjqEs06mzrj3jJm6KRW0ew/urUKjwykbBlr3ecNQJpz5qxeWzZ11QS+Kb8PrOH3TDz1IOEeBVw5lyd9IOIbJckH7r/dTL56sPDtdJNC05whnPxD+sJ6BvwcIx2LMT93Rq7dqpmvxi42crHKt5wiHUQoQCQdaEEzC6YdEOOeiLag/Zg3T3JYs0ee51Maizq/JpUIMQzQmU7tON2okZ5qFK43BMNBnXWg2a6BkIFrRrKH/tCJaehAhOJ1diU6Odg6uCkQIWhv6ebpVw57mYONqO3Fzl1hp/2ynhuk3PTSy7QVO7nySNYn992Z9vW/bma5izEMiNAeUEwiNbKnJGDrrXw6nJtDUcCDjC3TAgO3VjQyJvdEcPUrz8KKgOsGFzf6wkkv/NJt3wTMO/4qPYm5b8KfU31VNnML3WN1Ku+hP+YiPRGikA+TDdqwqQyJEBpR35xXPYgyA2vJC1srOGUpf6Lwc+wd/C/9cuHn0fVKRUJ3pR/ePUzsB1Zfc9mEWsDqc+hVgOeK0lFidQFVv3Xq/PXna91EATAsIGJRRPUJj6yBAHBkLfAoB6X9Nyt2iNkYsW9c12/Cdadmz1aKit86eH+ubn1/bXNHZO0BlfJDVq8M8jno9hSKT4g+KzOIeisz/Nxj/f092UzELz/ETAKRG7VCO2T+G8tiGgiK1+SqRWmMXfI7L14OTmgOrA6f1KOpxMGOWlKOq7HhtFWOFMHmtPxKvEfPqT7he3qV6aKHk0AMOioc6Z5aRoytEUl1ntdGtH4BYrXWREC2c6d8Zoi2ihbudS9caKZNaGckVZ0w1QwZlndf5FKbB7iuxJnvr8a5Cx08inNoPQXebLV2pQ2eju0dXC1uvF2qcnBlfhO2VPTnl+3WUxTeK1wrjR9tf3TfsfGWtv4L1ypjHf1V/rR4I8FNJgdQEyvyZSW+rX/xp/RWAVjkdIjK7Ve4pC63y/WwJC7GzZEQIOsBIBbb4ZJvNTxGN9SV7lT7OuKwR2afz0lKFPsa6tBhHf4UNfM2igI0AEBtY+tB/kQABmQBG/h8bBxt7GlHWzgHaCto402gu7Pn8W4aE8tuvm3Xy3o7zCh+926zzxkeV/ktYNz6th3+FlVHe1UsB46JIYTHRdS3Sh0ciYrXAhUZu/Y7t67kb+NlGg/ATi8YPg7DplEAMItRaiayYJZBt+MyLC9+PzDfV8HmQskSoaUbynxWCP+URQ+ZK51VjwyOeFoxsZvLIACQeWXgu83WIzCiNEJfXfBWfFTo79gYYu0Ldzhqihp29K82ZlU6QlsXY1g+4QHyy0tHevnUjSnS0JjIWFdQd0H9r17zq58JNXnu8cFJPlL/+5NW7Jk3A92MBvvPprqI6lESovAuhGsWWYuZBZ+/8+etWnHJnT1T3zdfwthcf9Nii3yW4Ux3uREfNqQ7/YDec6iIUByuaOz2MmvS9QmsU2QZN/NHD3UkeT6jpo7YJUN7mw143qMluH9B69Fc1zmNWYdJBa33Stv2bnk97+jDoT/lADFoj9FhXstV8pKFqd7en61l7UehsU2+zQsM0H6TYDaN0WHl0b7QdI5aKbMM36fy4FquXL/T37gzLtdlyshxsgRZgrrLfMkEvzvN6+k66US/oTvOM4XsX7kUhoGLAgEKLF8FU/mdITmaLpORBw/mnNiWpxoaEXi04FmLYNSQnsyI5+ZdITtgVobzqS4VKkbwrz+5N/cVQQNL9DghJ2Tss70RBmFkgQSncWpghygXUktJV9lfEg3dp568v7f1RYbDEL/z4rRCylhdjWUU59BmYwqwf7F3mCxjpxmRgISQG/jh48erp+a66Ed+Xjp60Xn1C5/mTgZu9PZHk5ryOxnrzGC8CruKMD0HcS/8YEfqUI/QfLm7O1hYraV1r5S7obj5clyCg6fuyUG3SeNt4oK+/w3dkwb3Dua5iOoBEUKmmYwrxryILpqokQuhllhavLfHY9i+Mv07v8Jyg78J+AiRlqGm28pLKjoSFO+seHlYFXi4f+ytlHv4Vg6Fd8IRJBEU6WmJsNR1JEqHhMku3B0JrsHFrnhBdbaHaRkeMfcsX2M8i5vnjK5oh2xbMtQ9M0Qbf4sT8pay3OLWd+BVsxZ7NYqQbZJ2sN031AqLlISjABqURADaVy+WIcxZ2uI1qzTI6YFA9Y6w5V1ta26pjC6H1D5l92Sll+omrxM++c4vZimbW/Wlh02WmVRNU2Igsi9CUgR6zsAlza2uRNLVJVkaQohJerkYIOF7syJHWQmVjGaC1UHEp+9daAFuLuMa0O6/nR6jvvLPzTbLcmMt4bi1KNpQB9k8q7mX/vdZixo+CxHM3D+rH3v527Jiq6VIMWwvlfnur0k1qKNESI1XfDwocjEZA3YABdSnjYGvB07vQ6sdPde2I64vigl1F5DFsLXqpDT99OPaYVoS4zxvbox5JaCDpBETSoYwTrcUpOy+X7+5OOmmalAFWo0SS8NZaMOoHYmsBpRuTgQei21rQ6Re71uLk5RnbY+O3UILHfYg70fjuNdathE0ZoJUosSjrzrSoC60Eqe8poetfh+sF6dWutJ3edBTF1gHtggbtgUusy0B7YKuy7gyKuto6HDAStVgybR417MQFT/Poc33x3ypAaQKCyaysW4OG32gV4BW4h1sDRtogtgYQWszCNAhxem0jdcIv2F9t95kM6r4vuRs7X48Rzd7Co3NN6mb5H6JKXG/nTCM6038T0bF1lM726XawNcXmi7AAS/hlCnot0PtYmeyukeror+Wn5lH6pykoByXZojI63PQXZLPrGxa0QT4Y95BrSmVIZ9adogZ/UVv1JnAbCR3I4VyOAuSEbSDICV5tkA9BgnxyklH5ssxUjZQk4fOlWz7u7Xylms6Obk6dIe/XBrmao7NVZ8ctP8nRHroi+iFp6D8ZP80mChKqRBv672W0Us4WLi62jk5ONGdmPFx6U8htgMG7X+hU2+YfTtHQqbbdLHy9QKd4mKfgcRWgkM06wU/fU7DNCK3X7i5ECT/VRIdHTdHz3JewwYk1I2CBJLQFsjUmIkgxidu499rrxtWklMNyPy5dVrrGppJ2jgnomTPjmD/JqkbY0KCP261s3Sd1TY74YDTcXF1XihRLHXj36aDgbX10LZycmE8ralt4KO4mVks/H3Z6VB1lL+V1oFPqp3l/umCGQ0uiopRACFCj71k7LxhpD3VSddrhUmZwRJGCI/RD7+zDrROoQTFypgudvw3p7HbUo+//6O1s131N40xoLq5QcBhPUKPfHUJ/0BaR/mgoIvRPO4d1FvZ2VnauHl0KkBR/kG50xSEdb+sTy2oCRpxF+HasXsz2U90w6h1NLicQGtjqRPLQ2YPdcjn1p/9x+rYV+sPsi7L1/jHUuGPDqfkB+3nPln4d1VlWYXtZrUd/1TuivRvrQyLEJyNOXIYwoOnWbkzExNmNRrSzbk0POxeiHtLWfgnPsVktaadUDpYstEzzENzcuXNhBFnD3sKG1evU8Rzq27EZTECc2G5PoT7RILkzIL1+AcgwOCCU1mXCFpOz2c6pOqpLVSI3BNy9u/3Fvs4aKvOTCLDATmOBDAGIDDxVev8CGTlVxpOw3CzsiVb/P0sv9/T9eyvF0q3vCC7CV0N9+afui9fLuTX/pHLV8vxOWHX8eyxIdTqJBU7mB0E4DTzYpvUPRarcczcrnM9WXUNNLgybVihr2PnaBBiirp4jm7v6eBCgljagOdOfiUhk3vxCdKDZtBrtZPX0TYjQv9PkuqY3KK4Uqy+clUYJez3OTc7x7Rf234z1Roq2M11FcQSUT2kQikEQig0sKE6B9uhp3arZA9SYV864c4rtpa1JfE8R+pxCzrO3v1k4hdbQ6dJ6qbJKfaq/3BXAa9yflmtxqDrRUVFUZd0VEDzHMFDpnksPKho0ZxcafdVtVN3MFhe4lA8zItNc3OzZPCGTeRz15aXMhKCZLQR6DAiYy2sYt47SVo187K21aabqbrmEqdO2LXblyCht/7wKwChNfN6fv/Xl7x6lTX25IayPR5bK9pX20R8SDlnieZQWTo814rzAfh4eHv1DIHB0lOZnTozyc6LqFf40i6ladHgrhqM0kb59FMZFyZD3DN9xZMG4gtUoBJQMDCi0eDk4Srt1MnDy1snyWkXPp177bvPwDoajtD3vTaS15yVqHHvVWPFpXLEACkh+mAtC8sJcllezYDFK03WT6puQYUfOmcqTMHPO7Ot4G6Ux6gfiKA1KNyYDi6E7SsPWpedybPyqhBovnZ1Xkz6OunVtAYddep4zKgCjNdkZiA/t+83R2u6b7xbmPFhFTTlT4UnI2XAXQ5ce2gVPmERwp6OFOEMymMHy2D40XHrZpwYpiFZt1ox9Ry1rqKwO4j6XniwQNsKMCqxdehuiCm2cxBM04yWPrb/t+mUkzlx6jLRCHMVB6DEL23BubS0eXj9aLjT2kXbmS21/s0bBxxxpLRSbQDcAKb75dwMQuLXQHXbX/WKRvd6Og+LhOqlzQ/DcWhCbQHc5VL/5D94AVLH9gITzugUqvvm95pavqJPFsLUIu+PFEzqySDsj/FKRkcWLoSgE1PMNKKDQ4uVga7HSUuP+CW1DrQLvkJLPU78bYNhaXJvjaePndForft4dZWM/43gUkGx4DUIy9DVHbgAyHj3sYqPMeXJCY/zN2eQhZ/DWWjDqB2JrAaUbk4FHIDHwTX/J0NuyOuqRtaea06TUh7LZthvQn6TD2lowxp4ke0cXmourvoO9R3tqsANbhtlvMJ7KQ2R0G+ssnO1orh6tA2tHiM6cPbrWeUiuHxhuZduglzTmQJDilcq7SF8ZodNgnOsqxK8hGn5VTr9Qdp3GNGjv/LJbwrqIQRsALjQL55W2RGtnR/aZl/tp6Ni9p9eRizeL62q9Sev8oF8+9hfIPPwrHkO77L1TIzS9hEBSYbtTHkQixL9EvA2oi48NG6LJTJFfNR2n0pRHW0fdpmSleoy+uUPTAzZxYf4WNhOXtjOcbjMg8AyA4BFedm9IMbI1xaAt7zLN5cSVrQuUnnHLDJazhQxeuztvcpkrHGFJwU6jXuKgXp6RWpvYPvPBnJFa3RowK5LtWhEgWtJc19NoDnRYGE9Is3N1ITo5O65q6xfo/RmEIFvI+ovWTbgrdlE/fkR9ldXaWJXOWdb2J1izrP0MFkAZAIGC0ojJBSO5tRvztvxWUr3ylWqx/xlBn/ijkzjSjZlogAY9ter/Bj3gbmzR95qbkmK6ukWecuSzZ4Y/wXM3RtUAqdnSGv/BQc+DnClfz94+rB25qTlbtp9cLIbdGN8T79TKIhHyvqbz4pdPv5qLQkC/q4MCCi1eDnZj7zXPf5If7qF+pN7+7pqHESEYdmM/Rr0zoMkMVNkxzjNl0sgN8iggmQFE0kedI4MercBbTmu9dmqFzv5puHyWdALeujFG/UDsxqB0YzKw+F/UjZ0JHSAyJ2OFZnqNe9X7peN3YNyNfSdXALqxJDLL3AelbszyoY7oBhftxE/lRk8vxseg2I2hXfaghuIDHSTEhuICGXHcg3Y31qCkuvkk/xJdz5FCkWOnzbjGDd1YEhC8TWTWoQ+q3Ri8duOsG2OkFmKTcQGGDme6sZRgobCVAgtJ+TI/iwa/FbuGi24sCQgUlEZMLhjFrd1Yfq71mt7LHXS8n5qbL+OLLeJIN1bjC+rGwnz/dWPgbiyquDYwKtVapejbqB3R32mn8dyNXfIFbTnzfP+D3Zj8/J8SH2Mu6IRMrOTP/lzyFcNuTFNxQD3fEwU1P2E+rWalRZ4oBDQZGFBo8XKwGzvzbOON62+DNTIeZX5bXi6tiGE3ts9v7UGeMDHK0elb1snIHOyDApJbgEiu8uVIN2Zs7eV9y0yGFHD4p/nO+Mff8daNMeoHYjcGpRuTgSWQGBiPtjsvxbm9+I1yqBlp0lddL63U4bDt7sg2kO1u2za0bXcKa7Yui3bQ0s0VWDlJJLM4AUPbHdoFT5hESNsG8o/t3YaJ7S6HqnhvUN0lncw5z8xnOk9/yH22u21A2By2YW676/84yH9rQy0pYW7/Vc++DWrAme2OkVaItjsIPWZhG82trYWZ1K6lVhmH9E+8XCSy39TtHEdai5kBoNai2f9fawFuLTSKzn37sOiy+tGiXQt4Ytxf4rm1mBoA2j8RA/6DrUV1xCvJh2kfyPHb3Md4nt2rjWFrMey23WCXwmzNEMsWiVFXletRCGh/YEChxcvB1mKqWnDlkqb95KAVu/qHL5pyF8PW4vHAHye0b67U3k9QUyMt6vUKBSQf+YOQrPbnSGvhIsazwWT9etWANXdypidUWuCttWDUD8TWAko3JgMT/6JBj9oe48fWJZka8bcc9mx+OyQF40FPkD9o0GPuj9GgZ8iBzeMNJVVVI2ZOWiknX7kexUEP2mXvnRrBzx80q3D159ig527u/R/538uoJ9XTtbb13ujEDYMecyB4VH+MBz3w2o2zQQ8jtRDnF67+PTHoUfnmfWvV62X6/s+l5GNnmBjjYtBjDgSK2s4FY7i1G9txfO39hs0/tHaYLi7SW1RwniPd2Mt0UDeWkf6vGwN3YyOKavXTJlzVzPDdOLaX79LZeO7GGtOBLq30/2A3tu+h6RbZm3304tSPD/k+S2sIht3Ys9DemodF32vkpi+Z8+KZsxAaD9gGBhRavBzsxgyXxMp8Mp6i75Vm6LnzhO9zDLuxr6bxjkOWOlOyy16PFtWquocCkpFAJH3SOdKNCVal2smcMFI5Hv5okEEoUQBv3RijfiB2Y1C6MRlYkpsGPXETd5nOV1LT9DnK26ciROwxhwc9iSmgQc+6FLQHPa6q9x5ba4xR8xQhVBTfXrsFw0EP2gVPmESITQFNLAJSMBn05BvN3V4hE0UNKP3wjODavzf3DXrWAWGzTMF80BMw/quJ5PUKff9FV+Ne6O+ZgLNBDyOtEAc9EHrMwibFra3FWeWJelLJJ9QTXiwxnprqycuR1qL6KKi1CD36r7UAtxalCTukBiuv1NspfPdxtKSnEZ5biwtHQfunU0f/g62FLY9yhIxUNjkksaUxWJ5HC8PWYoqJuLrNMgPdbX1jPwwutCShENAkYEChxcvB1uJ+38KEc9bXKIeb++68XNZvD4athcnuUekyyavV073fPHtc09SEApKbgEjaHuVIazFj3bIMxW25KvnDT1xoHliyEG+tBaN+ILYWULoxGVj6Lxr0eDht+ZmcJKh7rIL/Y1wImYL18xWOggY9tZkYDXooATbJ0Uc/U7w87+j48phtQnHQg3bZe6dG+J4JmlU0ZnJs0JPZskZQ8vEt/cS84pS6g7viuGHQUwsEryQT40EPvHbjbNDDSC3E+UVjZk8MeiaPNo/zHfBc44hU5oyLltXSuBj01AKBgtKIyQVjkbigKDlofsqPTO2ckrkmlfkund/3xK/H2BR25gHQhn0S4vtfrO0dLVztHGyYbNC622S/nI/PGNN869AtnXyF6bO9/XOJ7L4S69PKmcd/tZTnvHP8dGRInVYU7cgAV5G56n+6lKFtSfzVMgJBS431YeZ3eOeRnvap6em3mvIT2v4XqsJMBxl00wFp4aGSDkZ5Vy8FjIsihcVE17VIHx6Jajp8MrCviVjzU+9gyEdv86S7I1BIB7GIcvbpcFF+Hkk5Z2/bI0/GIcXAeHvmXdkF29U8N81rPHWz3outZsb+1WRsX9Lxy3cyMdWorskjcC5EWdHT/rlJ8MnrS9S9NzcUrh8ysgaFgFTHIARE6PA8Etk2pi0gskgBCazNHySYP1Lfy+arnFvorAGdN5/qEI8wmNCl628NlVR3d3W2WOnKEANp0C9gLAMXelCY+nzXtsUDZOJuKYg9VU1XfDLUd0rVDaRvxrot/v+5riI5hEQwuAohmcJWgKe/1KGmW48dG9QuwNPob/RAeklMpd1+8dL9TfrRbgO+vht7vAlF0X1xntfTd9KNekF3mmcM37tw75/mmiiJoHIV8R3x0gyEurWtY0IEgeLs2poibCFy/Foyy9iwXGvf8n0Or2IEO4tffMb0T7NC1HoY9T2JDhODanZNPGExidBU072HYwm3YtC+SNgi8NI8uSXKkU834LFgv355Eys6IcAD5TrL9TMOYnH1UIwBV29Q01Zt5JCqzYuFelTeSV9Iew5c0EjQpyztLGVSofLS9TozhuRMoyunFkR76Mfbt7+u6x2ZFadrZUZh1Kshm8x6q8ZQA59XPcicyfqVWOUP+tGuwiZIIlTehGC7wLa0UCFOvdmt0jKQ/sd/uWwiRz8x5dEdrB2cJm/u1Fer85uJ+zHWB0IH1Onkr6oMMWLggwfhxjqhA/Lc9Dfry/xplelPIpyig2XAtnmUIRFsb7I82RAElhADLPD6enFy9eDbT+rI4fJ3+6yvMet880vfdi5hfdPf/0/9CiZK4JaoWzMfqe2sp2Vkj9q8EAWYxIAwVd7oXjHu35pUNJs1NASUJuyKUF71pUKlSN6VZ/em/mJdXSbo16HFzBw5ypaJVjKgYdah8X+RSuj9Yd2GK+o8lOINeZISTdPTMVYJF18HPYU1pR6jp7CGv46U+ilgRN53LNflR82eUBRVQvhOAgWhS+s66EGizfUcewqrA7XMyWZerkb84FFnnpxPbeEGlRDKIQB4i+sxfgornLpwphIyUgtR/Gqu74mnsGodn3Tk9lEJ8p7F6dOinm/Bx1NYGWmECBSURkwukP+LuEC7OTya//QR8p6Ut+Yh0/neYcwF1ddAXEC8hhEXrFw8O7K33HzdHLdPQWI3hqPJBfCeCoVyVnINVM6crnGMCzaHj1k0wCBOPa1J1qLB6v52buACIhC86lqMuQC+P8cZFzBSC7HEQanVA1wgc2eI7TTnYF1PM397cTeH3rjgAiIQKCiNmFygwH1qqP2zgNyEZBO9jK/LfV3nCqVhrIbaz6wAqKEiM7tlEuiiGupjcqgy7eISzYAf+cpFvIq3cPyKN1ESwWomoldUmoEQFmqopdd7S123UfqRa8jbGpxve/SwGsrAAFEPnDuze6PsLqmh5Ys/vlvwY6F29FXN9Y/672vqQTVUBHj1L9vfxjaBi9TQA+oTtsZcylA75tCPusKo8jAGamjjnAqAGho6p1ulpWtq6KUr1tUiu0x0/J/tqc9QmI2VGlq3WoKXv3Kv7qGSGbvjdmm8RUHma6CDhSjznZrD4kP6UzVUvzhLYfGdLP1Qyyb9gwcefcdADf2Sf8tH+dQk6s7r+eOcTV+fQQGmUCBMtnO6V4x/rYbC3+zbo2ooI0cQ1VAIGmYdmvgXdcDjBs4y33lymH5E/RzziD0CXhh3wI9mgzyTQbMx8kzGKUznacp4rxsg1nBTzFjZCsUOGL6TQKGJuz0bZPvLns0xz6RWzrf9auttdPJWR/crjRkTwA0dcBAQPKvZGHsm4dSFsw6YkVqIjV327J7wTD6dPS4tr/GARvK1/tkXeRcsxEUHHAQECkojJhdM+ou44EF/d9KEkHPa6f3KP4+Okz6MMRekzAJxgcEsjLhA6eECQ40RNO2Thk7yQS2xo1HkAnhPhUI5i58FKmfuszjGBebDs/ZZrRbUOdB8/8q0wjCu8M8bAMGTnYUxF8D35zjjAkZqIZY491k9wQXuk9ZJP6CZ6QXUn3vtErfAExdcYAAECkojJhcoInHB5CSj8mWZqRopScLnS7d83Nu55Gg6O7o5daaBfm2LWM3R2er/N1wyDpEc7aEroh+Shv6T8dNswiGhSrSh/17GfbHOFi4uto5OTjRnoiPjm7r0ppDb1h3cHgqd6sU8Bbd0Qafabk2EuyigUzzMU/ChmgCFbNYJfrr0wjb653Zmmx4X6qfm+3nSyzeXaZlscGIJPTyQhLZAtsZkMlfGBC5Sd4gJXFjqEBN4L9chJnBq73pMimcNOKN/fpJ2sst3KZWo6q8oxESJ+6YGfcquLd52ewo5repW+Y6PYWMwnhrM9QZNDQZ6YzE1uD5i4b2BO2VIaUs/r7LWC7iI4yfUi5IIM71BUwMIISymBmKKvSYJTPbQLlpz4Z50n0mePTw1YGCAqJtLe2MwNXAdIqR0TvCtWny66sIDX66r9+DUYCDw6r+3P0x+ChdNDSbwZM33EBmktl/M53JpQeByDKYGX31AU4NLPhhMDXZO/1qSq/lIL3BYyH2Fs+lyGE0NPjx9Fj9o6BWtAvezoRviJP/4MbX9SYRPPiA5/IEP6lMDHWtbGeem/pqZHmpbG/e83YfB1GByoFrMgg3TyTuthlzj89h9GAWYLgFhyvNBe2oAfzFRj04NGDmCODWAoGHWoal/kVL0cWlfqRYjKinEv/8yMV/B1RgrRe4+IKWI2r2a1XWlyEwqzJL8hqaRpL5+aNkZ5akoKkXwnQQKYoerD0jsMGetVVgpRcJvtqxZeeKR+q4tAgdV1fyCuUEpogLBm9nNCtZtpQhOXThTihiphSiAmPv0hFIkbnn7UcrwDWrZtQ5XjH0a7+JCKaICgZrZzgXT/iIuWGBIPfSVx14t9ZgDT8jB0d8w5oKb3iAuONK91rjrXJC+LCD37dTNlExhS1nnlSk0FLkA3lOhUM7qvEHlrNSbY1ww0NjFIix3oGb+6VF9MqX0XnMDFxwBghfVTWmh21wA35/jjAsYqYVY4kq7KTqgwwVz7Lc92pE4WG3n9HsLc+znKOOCC44AgYLSiMkF07lSoYYLoh0UariI0UGhhvcNHRRqOI10XaHu1dvtyrP9AnqRvgnj36zzf4aCQj2D+xTqZXpPBE09VTWO3pxysyHCfQPWT/lIBSnU0qlYKNSPhoun9V2yRneHoenguIfhdjh+tLYotBdMBSnUEEJYKNR3L6rVjlv8Tq9o9NeC6gaz1B5WqBkYIGq0M1MxUKgt5c2/5q2Q1ty3ftylsnMx9T2oUEsDr35gahsDzOQihXr2ivuP3IMbdXct21J0ZatKlx9f0A2FWigdpFA/SMNAof5Se36wsf073cNi1LOVVz++w0ihfjJWXWq6XKDGsUt9P0xMtBiOgvQqmA6SXj+loa5QDxxlfHj1tumkzLfR3j5jG7dgoFDnEE5euTnLWD9glWZuWcum/ijABGUNAKZLaWgr1PA3qvSoQs3IEUSFGoKGWYdm/UWqxEYlvR+nP+RqH9fabKZ/4KIG1i99TAO+9LF7NavrqsTkIQXxcQWz1PJeU17UkRcJoqhKwHcSaLz0MQ340kfWWoWVKnGnephH/OPtaoG9TvXfSHm8ihtUCXMgeNRuVrBuqxJw6sKZKsFILeSXPqb1hCohIjrAv+b8C9L2C2P7CxSvvIYLVcIcCBS1nQtm/0VcEBlCcnfMG6+b6/90rgl591eMueB1KogLSrvXGnedC16/LP9pO6VJL1u38UdMaPN8NO9xgvVUKJSz56mgclaXyjEuyLMLtTBQG6rht6X5QZbcCVlu4IJSIHhHuiktdJsL4PtznHEBI7UQS1xdN0UHdLhA2tXEYFHBO73g2JSPsYuVV+OCC0qBQB1p1yfmcKVCDRdEOyjUcBGjg0IN7xs6KNRwGum6Qi2Zoik/PT9H88i2RVeuHns5AgWFei5STPD+5rS6rYdcL/Z/Szm6YJAtQWFtJuD7offmtNqroDenhV/99+Y08JvTki8GP5terq25/bmDdLqUjjye35xWfRX0eqiCq//BN6f1578t1d92jWrGru06W3geP8XwzWnv+xiH7+9H1vRRmSS5r/9JfRQCmgIMKLR4OfjmtGktzaqH8wTIMd+k+r0ss+2H4ZvTVDSOTxpHitWPHarlflRY6o9tIRCSnkAk7a9y5M1pY2f0Nah8+lS9aEl+1PN+p43w9uY0Rv1AfHMalG5MBp7HrQw892rgpcH1vcgRZHeXytNr0jnCwErXQQz8rv4fA4MZeH6f/W93bbpPTnOM67fjW2AfPDPwxOugMjPi+n+QgfcIfqyQfblOO+l5nEwwX5IfhgzsEOkyok9wf5Vdy27lxk7Nj0QhoPzAgEKLl4MMXDj3fcWEjIP6EdX9/SfK+y7AkIFpOpZloSsSVEL9Z2vtLl7eFwUk79aDkKyq5wgDy2fKrpe/NoiS/eKE1ke1pSJ4Y2BG/UBkYCjdmAw8/y/SqMNcBvFslhysk9kk3V9luBrWbyXYVA989ko9Rhr19SOkub29gjUDd7ryqx5fdRxFjRrtsvdOjeBeD3yUVD3HNGqzqatlwo+L6ufafuBx50k+zg0atQEQvLn1GGvU8NqNM42akVrIj5eq7wmNOma7j0Kai7lGasi2xzKuCeW40KgNgEDNbecCZSQuwK9jt09foYIBe631igeGyNStuuyB9M1QcuxKXgE5dj9VY+HYfTNrfyx1mqtKzsezEmrUrRNQdOyiLTSJkggSV0COXQghLBy7VU+llbdOUlHxi9m+exdtImxsy3HHLgMDRM+q4BUMHLtiapvSEo/I629fu/PtkCS9kh507EIxBlz9g+q2aqOCVG1w6NjVWXRVYoOuiMqOV/quudml2Rg4dodeBTl2n9dg4NgtefC9+ow0RT/2SsH+DfcvF2Pk2N1Yf1Mg09ZTLTbqwvGVg95uRsGKOvgqyIraUoO6Yzeuri7Br6w/NTbE3nNQlLErBo7d5PD5C+esGq7utVL887cJF0kowARlDQCmuhq0Hbtwub1HHbuMHEF07ELQMOuQ6l/UAVOne+ckp22k5OwjZD455DoP4w44oAbUAa/oXs3qegfcuFvgnWACv65XoWNNC180mk+ihu8kUGjitteAmjhn1lqFVQcsmz3kZnqEECngyg9S1aKnW7mhA14BBE+7mxWs2x0wnLpw1gEzUguxsXOu6YkO+LzZ58joF2O0CpdZ/9x17OIMXHTAK4BAabdzgdpfxAXDh9+d1ihkQzkhVqXyKnmaMMZcUHsFxAUpVzDiArWzQze5ra8lR4ycJj9+6dCfaD5fCNZToVDOqq+AylnBFc5xQYPT2WeiIZoJX4YJP9Y/kssNXJACBC/8CsZcAN+f44wLGKmFWOIKuik6oMMFY2uUzYpr76puv1/ZX8o/5AAuuCAFCBSURkwuICFxAa4du3BBtINjFy5idHDswvuGDo5dOI103bE7a0jfcwOeF+hHnQxx3vFNKZUNTt117JK51S/EW8tXKxIrqhJY+uXM89jqCo74hTZ8BfmFZn/95xcC+4VShygJDrhgRz146t2W+jQJ2H36+PILrfsKMkVYfv0P+oUElRbHXX+1VCPs3cYlDyPP7MPQL/R8q0zkuKk3Kf7LXY0yg9f88aMooYDqAQMKLV4O+oViplGaKdkvdOPWeK1c6jrKFkO/kD1PjvGK4bFaiePLXU01f8qjgKQMEMnBXzniFxK2G28S3PcVac+IAP+lKzb1x5tfiFE/EP1CULoxGVidWxn48d4F11+X/tTxqhE9rhijVMQRBhb5CWLg2pZ/DAxmYLkr7iuLd8prnOizxThb/9BJPDPwwJ+gMvO95T/IwJ/K+gmluZ4jHfrQ0sj3IrYWQwbeeHbw5AHfLlO3jVrh1G/Hpj9++BgU0MYWUEChxctBBm6OEF7s2me3qvfbzRct9IZYYcjACXuu2OvIbtXd4Ww6c1awSiIKSJYAkcxo4QgDP5eVFr8w5JlutPY+i42z5m/BGwMz6gciA0PpxmRgjb9Ioz5TnHhq3S559ZChiu8nyIgoY6xRr2gBadRKLRhp1LLufZZbnh+vkVoT83rXhxdJKGrUaJe9d2qEpS0gmVWjhWMatadElHP+bgv1rBjzOzPEZ2znBo1aCQieRAvGGjW8duNMo2akFqL0qtHSExr10C8jPh2XEFM9stXS7YbCmihcaNRKQKAk2rlAE4kL8OvY5Q2cejmW7zUpp6hQMPGY20CMHbuRn0GOXfvPWDh2Iz6orjRUUVQ/vs5kHq9Esz2Kjl20hSZREiH8M8ixCyGEhWN3YjFthPH0Jr0Dn4QUi7e86JyfnHfsMjBA9Kx6fsbAsfvzweic1FUvqMWXXSUFBt/x7kHHrj3w6hd/bqs2WkjVBoeO3aA3Mdd5rcV0Q/KHjw4ZeHgZBo7doC8gx675Fwwcu49/XK3ze36InLhk4Vdbz/eGGDl2vy96TRtx4YZuwNCTcw4KRT5CwYrq9wVkRXX9grpjl3dxodiEM5P1T20iV53yV+p8Zwg6jt2LX/g/8RqMUk9/WMIrn3htHwowmQNhon5B27ELl9t71LHLyBFExy4EDbMOUf6iDniQ42NJl9SXVK/7Zw0aSQ1yGHfAhC+gDri2GaMOeKqAxrbFSySooQ/9TtonTruDYgcM30mg0MR9bwY1cY3NHOuAl0luP2Qg25sSPuSmlEzagSvc0AHXAsEraca4A4ZTF846YEZqITZ2jc090QHf6L/rZb3gDd3DngGjc09r3cFFB1wLBApKIyYXaP9FXNDw0/xlXMJoNf8Lb6+ET6oaiTEXaDeDuEACKy54FK0lLnnISDtRO/2ZxHviLBS5AN5ToVDONIDlTIlzXFCQsLKoVuOQSlxCQ5A1z/0IbuACCSB4glhzAXx/jjMu0ACWOKUe4YJbs3ar7yu4p5nnu+KrsPbt27jgAgkgUILtXKDDrd6U9/Mjlsy6G6abVs7ne+ez9wqOeFMuCZ8FeFOOCJ/9500BelNiIm8GrEiwU01/0sRv8E2jc0HGmTflAj3WiAP4UuGz/z1vykO58ev5F3zXjN6SWh36ocgNQ2+Kq+TDVUslh2vGCRglS6rkFaMQ0FPAgEKLl4PelPnG0/YuWHVOJ+n6gnElW++pY+hNIb7J2d5X5gr1UBb/rvFn89B4nmsSEMko4bOc8KZs/GSUs+FqmNapCTe2XHn/wQ5v3hRG/UD0pkDpxmRgKrcycMbawLfCDot1ghIHzqUNy7vOEQYmDAYxcMOgfwwMZmDN9LrUs1cJ6gXTXy2bdLqFD88M3DIIVGY+DPoPMnDIgMlO1q5RmtnRm56N/nnMAEMGnhL9esgiQX+N3cUWNtZ+s8VQCOhzYEChxctBBj5MPf+YeGIAKaWOwL/U8lwvDBnYK6237a3hx3S3P5yh9Xb3yV0oIFkHRPLCII4wcM7bW9evDYhQDVPua2w0xywBbwzMqB+IDAylG5OBdf8iPTTATDl7X04wdeeTa1/Om2cOwVgPjaNDjKiH+kN5iIkeav1u8MHPE26q7ZkQfrmU+jEART0U7bL3To0QQwcJUdLb3RkkLPXQKD/76SKHTElZ5W+kNXY86ssNeqg/ELytg85iq4fCazfO9FBGaiHKfLth6HBGD61+UV2ds1eY7Okn8q5/wuwUXOih/kCgtrZzgR4SF+DXHXpCtmjVZ4q8SpCg8mbZYrIh0jdDyR26TegsyB0q1K2S30V36Pp5p3eKC7zWCl51f1kj38HO9zz8mTsUbaFJlETwpCOE7A4V6l7J6qI7dPJZj34ZzyNV017G9WtROfagh92hDAwQ/ZHrhLpXmLrkDtXIWmd66cM5zf2l92uq+g+c0pPuUODVWwq1VRt9pGqDQ3fotIvf+AvSP2rsyW9Y9U7fRpD1K/2xO3QTXTJDdIdaC3ertHTNHSo9fsdO3oPj9OJeJ92e1bDCHyN36P7Jd/dFhKmr5ia8ss7YpimKgu1xAx0sRNujkzDLrvJP3aG3lvunq75YTj51b2KDu/uRpxi4Q137vZ1t9C1Wc88Rk1mX+vD/8ZtP+jOyBgCTqXD3ivGv3aFwub1H3aGMHEF0h1q3a9AGf1EHHPIjz/7iJmOtxCm3fO/w3vDAuAOeLgzqgIndq1ld74AXpFr4bJ56n5KhYLCzPvNJIIodMHwngUITN1UY1MSNZ61VWHXAfm4OxndGq+sUHhAINB5oPYcbOmAiELyh3axg3e6A4dSFsw6YkVqIjd144Z7ogAXi7acrVu8l7TGcpnTWLpaEiw6YCARqaDsXGP5FXNBrfeA03pIxKtFJvYbsdtObgDEX3BICcUF591rjrnPBzpp8WSXlpSr5Tw4MXLHYdzSKXADvqVAoZzeEQOXsshDHuIBn46qTfPw+mv6DBIdLTBz9khu4oBwIXn43pYVucwF8f44zLmCkFmKJu9xN0QEdLsjhD/M0vbGP7Ck4/qR0VkYwLrigHAhUfrs+YcSt3hQp4p1oz3tL1XIT1cKLoh2zAd8PPW/KWkmQN8VQ8p83BexNSRMuFHnWR4OcdfFtjOT86s949qY4SoIG8DTJ/6A3JXWkpoGOyWyVYNuCmQpjR2DpTXm/vHL9dvcm9Qyl8Tv5DCYooRDQZcCAQouXg96UZ0SZmknFiWqeoZOqRxEVT2PoTRkv8k0va9Z3crJ71hWvBWojUEBSE4jkPEmOeFOWrZ1Be8R7Qss3MnjAxllkebx5Uxj1A9GbAqUbk4GNuZWBm1IsieeKd6ltDz+2WbnifjRHGHiTNIiBTaX/MTCYgUXLrWRXETV1j6s5e1YIb9mOZwbeIA0qM07S/0EGzq0xNpIfJ6IRuyz+fpHiSFMMGfix8CNJr41L1YJK+WMSs4z++KVfUECtgQGFFi8HGVjIZJrtFt+5WlkH+/tcEXgwG0MGTl2sQH3ubaay//vHerJT1nUUkDQCIqklzREGfrB0nExLYpK+92lV+40XhL/hjYEZ9QORgaF0YzKwyV+kh5L1+IaYFvPqp7jUbtWfs70WYz1UXBqkh/JLY6SHWp4JmB7Km0AKUbqdJ2Z9dwKKeijaZe+dGmGENEjSGyjNMT30tITpGl/iRLWADxNyN/uWB3KDHsoPBO+7FMZ6KLx240wPZaQWoswHpVYP6KFFCqtiGm581dghWXvZbMN3cVzoofxAoKA0YnLBAiQuwK87lPjCdNrVad+0C6WXfNg03zYIY3eo/BiQO1R0DBbu0C2rezVd2SKrER1XMSU0VFwWRXco2kKTKIkgNwbkDoUQwsIdanz9ey/eUF61A3kfH92NXU/uYXcoAwNEf+ToMRi4Qy32bJq9vWWq/qFdVRfvPBhn2oPuUFHg1fcb01ZtFiJVGxy6Q18kJDXNtqukZN56uPK50PODGLhDR0qC3KF8khi4Q1c0jZq8I/y8aqrcmdP3svIUMHKHnklNLkn1e6Yelq3fT3bRVn0UbI/DJUG2R2FJ1N2htNHOcS4keZ3c7XJmokY60zFwh/YeOpYmcJ9XP2tNwT0R0sQIFGDiA8L0rZvF+NfuULjc3qPuUEaOILpD+do16EV/UQcckKE47lVIhlpStOilgct2RWHcAV8bA+qAi7u3Hep6B7zq7gK5rW/mUINPTXghf27CcRQ7YPhOAoUm7uoYUBN3bgzHOmCf9ZFXq6c5a4THiL+wVTxtzw0dcDEQvJxuVrBud8Bw6sJZB8xILcTG7lw3N5ooOYLOeBu6qivoR4b1qVVdX3ENFx1wMRConPY96eK/iAskar0fjLp7kFwYNvrUo7draRhzwQYgF1hhxQX+PD6edseEdFISrfd9HBvpgSIXwHsqFMqZO7CcOXCOC1xfbg9MOf+VGvDiyIqPi8c+5wYusAKCtxRrLoDvz3HGBe7AEufQI1yQMP3e8ScLF6r7bmtRfBNheRoXXGAFBGppOxcs6dXqkWDhAlGlXoffr7ypETj00pyPu+NLeKh2lu1X3BgjbjZ5ITWTf6ddS6Pghk5XzFSz1K3sXBEFU36EgKzuJJjSf0ObYurQppjSp76rHRxdiRbraM4WNjQXBcYPM3/OwoEI/ZPm7ORob+FKs2J+pNMhV1tnRzcb267Ri1uO54Xvpw00TjneXbs3cdjLX1wpS5BZf6SrMWxRI3i+KyMQPrF1wkBk4/m6rDtkM7pdh7WhscHXmu3lrxGb7D1rxSvVmB8t80VcJPlQVGW9Fuh9rEx210h19NfyU/Mo/dPS2YtEUKHjRVSjK7NwvERJBPOmMjjv0NMQaT7+tRfFmmji7EZTgJLP3oMFMWYauhBlXZygrKNBX0aOaOEM/VBrCkOZJvtbiSk3QBD6yxoW9i7Qn7aA9iid/mqnP7De1g7aNdDWukE/zPiCLlAciBZr6BgSLVoPtf6hldAKdHa0b/s1svZ2q2lEI1s7B8dxLozsNIC2bdBPrVkDVT859s/rMbH2kal+rxucwDt/aoPo0c65oEPHgjUXWg+jXuB6MdIfEOz4l2U9YR3qY+noaE+z6FBU4GTdtkS7uNURU+9cBNsjyl7AjSuv1/9gq150VVaCvE55QWd3BkKJajuOBQsxVqQpWxYyhTbRb8tY6Lqb+EiYWDjYQBEmroO4zNGZsSw7rBf2z7aRvcz/QVmK4n9vV1MxjTKtM18zfyErTv8/gwVSJW9ASEHJ3gmp3t1HanS7a5JIn8PRugRV6vQxAh8WftE45nhr3foL2stg3VXbb2QzeOxwDpPEegVMrJdlzO3NUqRWV+7HMLEjRB71HLWmbzQJm/rOUwEqVDeIVJqDjast6+aFBwHhUbo0Cxc3qEDTF6k948Otk1576Ld1bbvRx2nbnH59dPR9I/LnK+VMe4j4rVhnFR1Odue9W80QjqUQjg0sVXQCVEU/sWwxutmq9VWzcKExAGB7vZI/Vfxs3xlSfeV06z7tF6qHS+kurE1G69Ff7S7glfBPdxdCJAKRDlWkKt1vBk+5YQyoEGs9295fj2EyZfiyIRJxgbYCRCpbjGqPrpYSyx+ln/J+a+IXI56+gyn0TQN07eruTs5QCDr8Up7FEyZ3rvkI2dJ2HPWlOYuJk5YaG5wI2gycmEtzGdLSFPqhd/bh1gnUoBg504XO3zo//rCvHl22ofMu68LkQ8B6nAm9KbUgWkHbAAbaRGtHZ6ID/RdB/7RzgOqhHVQIPbq0RF/Ne1IqHhShv93gwIwii1kbEb4d64ys/VRXseSDsHwAYdnAtgOQh87e7VYH0J/+x+kNAPSH2S9HnoSVa29b9SId/5Qdzx+9pvMjunjZXlbr0V/5Y4/PGNN869AtnXyF6bO9/XOJf7oc+5AIDffLkKyfQxjQdEsnEaHv9Il2rYuRaOdCpEeLLUZvHUPHvmtxVk2Iyi3oW/ZhZ2dKZARZw97Chg0ldjiH+rqbwQTEia1wtABadw2sey0QIMPggFBalwlbTIr7OVxPuRxDzj0mtOQmaUN1Z9GI+UkEWGCnsUDG/B4IGXiq9P4FMnKq0AJyd4V6LqLV/8/SCzmd9x0ZtY1uSkAwOp23LBpuorlAPfiW70lJouXUzhTf4e+xUnzHk5hk0G1gBt1qq9ymSJV77maF89mqa6jJhWHTCmUN82F6K92ioufo2vUdlTTUwkGleg2R2VYRHWg2Fgy0ZfX0TYjQv9PkuraxajktapwztVA//IJYXy+pEfPZfzM2SjDzTFdRHAHlUyOEYhDbLdUUKBefdKtmD1BjXjljz8720uRW1utVTgkjhxpI3JiktGBzp0vrpcp6O4PqL3dP8Br3p+VaHMqtpxAqimx3T2MYqHSrXAtBRQNqLWj0VbdRdTNbXI7vIyvELcjSzcvpRcl7wTuu88bIiObiZs8a8LbjqC8vZSYEzWwh0GNAwFxey5GWF95vF2xYeXYNX+9LWl4ryh7b3X5vy5HbBZ16lYNeJtFS9u92QeDtglXuGy7mD55LSlg7IHhqsgB6N+zD1x8K90QZ0GONeE/UUUL5f+92wfGTTb3Vn+3WP/nWi6x/eoIEhrcLwhtRFAI6kAAKKLR4OXi74NlbLfc8eCtVQvnnPlXIPhaA4e2CaLdDEJLxP8oASJp/L+PE7YKTRcYrbdKYqbEt9Nrj8vnHTX77dsHJ2NwuyKgfyC+TaGlj4BVIDFyUHDQ/5Uemdk7JXJPKfJfBna+nVdLpTL2gIj2J+ZOs3Gtt7wjtcx1smBaZ1grDXqL17XN7yhmbWp2jzpZT+xZF67D7SqzbHObxXz5GEhbQP01UKBXje5ezl4feSs8jzbjXq6drOD+h7X+hKsx0MENKh6EPgsmDZ18mJUx7WJxZCbsjo3fpyc6p0Fa8BpHcXFwd17BJCOgjgq0nYb9IiHkUFkboDLu8gg6zTRVt3cnpFg8zVBN8kgu+y+iJwr8uS5rQj/3uOmyHFp4Do0kExRPlrY1miSoTYnMkiFt8s5KGTORVO2EqFpXspNv5noRelM4IC/4S4V4UNgD3oiDg24vCDt5eFLbonlqver2CV1Una/ylLKNYXQXYN2XlCcovl1/pKvsr4sG7tPPXl/b+qDBYoovLDwR9fAMceovfy+5Lqd3O7kup7LL7UipSdl9KZZvdl1LZ4r9a+vmw06PqKHsprwOdUj/Ng39d1uyGjmGR3YTEUhjElkgQE22kTvgF+6vtPpNB3fclt7OYzGdEs7fw6IxyN1l7iCpxvZ0zjehM/01MbYoteHsb3Q6T1/joHf3hddHI1yWVzRdhwY/wy/w9Zefl8t3dSSdNkzLAapRI0p/ShxwE7qozrWN/TxZ1BWr3CJZnmJCv/K2CwpLVv64oGGd1Fd/3z2aqU3WKRHqNXBw7Q/H3shoWF3i0UagrhHlnYElv9Vt1hedBRFB3Cwv9M2xiQD+MEAT6KXZRoB9nG4Y57xw/HRlSpxVFOzLAVWSuOst3Zr3zkH4Qi/KicqUMhjTtt3KdFelfJzsHkLY7K7L4+atQUu7tVSGfxnhu/l2kYSkP3yajkPKefeBUav2bKR+Q0P2UD0hgG4iABMRABCSwD0RAAvvd4s9Ngk9eX6LuvbmhcP2QkTUs35lNIKCDmDBqLBxpm99MeTjSXUl5zJFWCdo+z0EyQzPSLf3W1aSoS7+LNDrmdFAgquPhgbD9zd4oqfu9URLb3igJsTdKYt8bJbGNQcGBlNzl1InUkwMLEr84zZwC/7pseqMkTHK9MhAOsd3vbWXgEHdhK4MtxIRNtxe5ns/X2eU1cpdgw2PS70EMS3KjvKuXAsZFkcJioutapA+PRCHJVaLgEVj1W0nOW3qy+xIA40NsosA4jhAHxjl2kWCcYBuLYIF3BvdENfVOlM+6lRkVKM76xVllOcZRLFJ+v1QFDPDVv5fylG7rAdBH2KU8BUkRgM6wTXkKe03ga8DbbUejC1Wy5SaGrBCd8hD+dVlTnvJrVUDXTapvQoYdOWcqT8LMObO7+rA54FZmPjwC9kgRwLc7y/zuPdOHaUTqIdsprzxtU4IRvh1K7qzd5SB3Vlg5uu6s2P2rhqUTSORMM7OCzdlR1qi5s+QeGEaHSJzQSYt3Vo/1E2pGwZ01cDei0j6EAQ1G7qy8pGN7BaTstZIHls5bbMfXeeDQk+4sBiCI3poSGCC9fgFIt9xZVcse9/tqHaYVWbtKyMFyDez27h53ZzmFgZCBpwrG7qzmApPyuAGh2mnDdA49LSLr4sidVb0LhJPnrnJm5V6DVLnx686a82rcnnyhfqrpE+uqFp+YvoH9N0PFnXU0vBzgzlIJ71bN7oI7i5dPbPI+KRfN7bW9v1FnkspQcGfBaxwK7qx4OiqI7iwIFdTdWUPTtfeM8iSQIwbwR0513r+kx91ZDAgQ3VkQBMzl5YC0vPDuzipRodQQPu1XCXp2hsds1uB07N1ZwiSCQQSE6im2WyR16Oze8n/uLKA7a4/7eJWLYw+T8tMU/G/39ZdDzZ0FX39/WkQGQWuEHmsiW4IaSyI07e3pyT6CO0uA+RewcGepblHWu35ORSMis+hG4OQd8Wi6s/605kERi98LipgBZyPW9v0FTDycaB0vXlLT2cLFxdbRyYnmPFGH5uxAs59I/xmXiZpaZhBkdg42/ejtopkL49//n/H//+9WDDloJhsWlusxeMd0tUP3Vi/b5dy8FEMzGdrdG5QXBGBeHN1Tzgkz2ScD+5qINT/1DoZ89DZPujvit81kyhiYyQyZ5Y59i7ucsXiYGwZHpA3D75nJkDZdqJjJ4LmEqpkMLrGjYCbTCkIwkxVvnkd6/SiwLQZO3KlmVcn+0H954JV+QeWpVwsshTdjqmaZl4PULPMylNUs69xjM0yzyTqZeze9pcmvXoWamjXmCe/5mNNOKt7zm2UO6uc2oqBmGZSD1CwIGozUrLoJ2cMyv91QzSm9MWDT+EZ+3KhZDEAQtQhCOYZqFrWo9njiFyo5uE5A4y3p5SKcqVlHy0DIwFMFYzUreKIqzfrmKu2AiTvef0x+uARHatZAIE4lZ9oq91ouVLNiz2jwXX2jkrT6C7FXr4bTGKpZTRUgNcuzAm0166G88Y3vxpF6KbtnfF4wTnc9CmoWvMahca9hBUjNglBBXc1qOmzeJ3jXAU2/OU83qn0OUe1xNYsBAaKaBUHAXF7O3KpmPYpZfC2qhEj2kavSSg8UncIRNcv9HEjNcq/8p2aB1aw+lKlKWblK5IyNZTNdi99KoaZmwdcfCj2w7TlQDyx2Dsdq1p+LGuzVrJM0lUs/N57VSkzRPrc3OEcHZ2pWZSUoYtDq5KD+MzDsxxJR+f66e+qtrkxPvdofQ/1n5LLdt/dONlDJEb4/QuPaEmMUcl8WiOT1sxzRf5ZnLBrzYN8qlb1f/HkDz0oE4epmQkNmgUDUf6B0Y1KsCxLF4ubmD3jHjM7NH/C7zVC4+aOktBxw84dnaRvkrriHXKz4mLCwjabKsQyVEkVPXUV0IIcvGRQgP1oFgtypqg1yNyTIJycZlS/LTNVISRI+X7rl497OV6rp7Ojm1Bny/m2Qqzk6W/2f6xiHSI720BXRD0lD/0n/J9uHQqoSbei/l7El+f/sgBkPl94UchtgcIENOtW204J3cdCpNtKA7z2hUzwE9uITdIqXeQoecgEK2axTZOg7Z7bJEl+/9YqM7H6NgP0fI1Jn8pxiAyFrssBiTGiLcWu41nGnIGrWGFObZ/2MGjiw5NznTzn+mAqiYnkgQVQsF2VB9GWFg0JKwTpq3hdVtejViZ6oCaI3swK+1U5o0s22Sck4udJaDAVBVCAPJIhC0GAkiPLss7wwliKmeypivJxK/xQibgRRBiCIctapXAwFUW0ff38lOSdKzNRqnyVPF4TjTBC1zQUhA08VjAVR5YYJvZSEqjWyBtbfySSJ++BIEK08BcLJ/VQb0a7nPkHUvnKgkfjR2Zr5628afpjzNRhDQTQyHySIyuajLYhKjE20KZdYQw0i9Qmqk/fTRkEQhdc4FARRv3yQIAqhgr69T6av3vlrE0mJ+S/S3T6N0+lxQZQBAaIgCkHAXF7u3CqI7rSpE7E5o6jly/fE0qJpfyz2gqggiaBYVN76Ok/WLZI2dLbwnyAKFkRrNl27wWuZpr7HsmlY3y2mi1ATROHrD4XXbBKLmF4LtqJQdSGOBVGs7H2z7GN2zazWUU+/GzN9xo/TH/EkiEIR8ywERUyRsxHD2t7HO3nS5OkcVHitjjyWcrjcTzPleXqa6yzxGRgqvGgraVBqNBSAUiO0gCMKr+YG8Qz/FZ7qhfL7HHUKzyTiSuFdyKx47LtcS8b6Ye4ZPHAvN8IlANwqvLYnQXKj7Mk2yDfgHvKylXOtt2T6q8SFHXEJX1aWgg7k8CWDBuTFQMiL2yDfyJUKL1wx7KDwwtvSDgovfDPdQeGFL6UOCi885F1XeK+YnDs5vq8HNUZmSbjdC7NwFBTeTdyp8Ibv1mgaknZKOyZspo/REkdhTBVek8kVAIW3VrECXYVXO2/sUoXty3VyM977OQ2VMUNN4f2yN5UvauYnNU9HAaNavZbbKCi8VDo0iAovBA1GCu/++J0PFY4bavi87WtKCR/ViBuFlwEIoj4nPbkCO4XX+a7SyO3Dh1J2Tzl5TPr8OU2cKbzfFUHIwFMFY4V37pg9GUP7epMCV4wIN98VugpHCm8GECcfxQpm5d7MfQrv7DhekyyprVoJmnNWBfW6W4OhwiuuVAFQeB9N7lbN7oLC+zl+nk7c43DVYy01g5e4LdmCgsILr3EoKLwidFQQFd5Hk7tXrrui8Lpe3PH4XYSs3om5y4aJndq/occVXgYEiAovBAFzeW3hVoVX9Inuij3XX6mk16u6+j1am4q9witMIphPqQBYXhuUKv4pvECFN+pC1BKK4WdK+gTPnalVA3aipvDC1x8Ktr/F9Fgj2v4Up1TgV+H9c5WPvcK7V+Oh3NLtylr765rzcg1vHcSTwgtFTAAYMWh1clAQvSvQp8ohd456lhy1iUCQvIahIOp27spk/tj3FK/bDrmWJX7KKOT+KSUQkqFKFZwQRIVStEOerErVCFqlrC0tqFuMK0HUkFkgEC2vULoxKXYr7tU5eMeMjjoHf6oiCuocr2IFQJ17NKkNck/cQ97HYY4HYaAeNW1y1IyNXgHr0IEcvmRQgPz7FBDkt6e0Qe7FlYIoXGDrIIjCu7gOgih879lBEIUvpQ6CKDzkXRdE38+aUHLrxSxyyuTR8hIzIh6iIIhu405BNLff0hrithnkI5aPdPUL31diKoj6yIEEUV45lAXRhnPyVYdW2KvsMu+tZOQizIeaIDr2mrDYh50P1XMP2bhnOFj/QEEQ3SQHEkQhaDASRA8WzJV7zT9bI0j95YHMQfODcCOIMgBBlLNM5DAURH1X25OHbd1Mzfywq25h6EtDnAmiCkBk4KmCsSDaYhoipBgZSfLOXjB9xeOC/jgSRG/LgnDKlm0jWm/uE0Szoi6ITxYeQYnvfcD24mXllRgKotTxIEFUZDzagqjP9YpRt1UvaG/LEXYcqr10AAqCKLzGoSCIkseDBFEIFdQFUdPJLkfj563VLHzcp/5iRKFxjwuiDAgQBVEIAuby8uFWQdTqme675SVz1HY9vyEaEC47nCOW1/3yFQDLq7j8P0EULIhefnPhrNdDLb3AZyW+7wd5LEdNEIWvPxRccuH0WCO65OzlcSyIYmV5fRPx3oCgeFelWCxUMmH2bFw90RKKGBkYMXHORuxvs7wWe6s39pviqOMVRjoQM8R6AYYKL9pKGpQaH8aDUuPCeI4ovHv7yujqzdtHDSOqbPlxoWE9rhTehcyKh2h5hdYPc8/gi3u5ES4B4FbhVZEGyY1E6TbIt+MecoM+KeSpQxarJr4RajGoaX6ODuTwJYMC5LIKIMgFFNog38GVCi9cMeyg8MLb0g4KL3wz3UHhhS+lDgovPORdV3j35I8ZXJ1tpx98c3H0CGH/pygovH7cqfDKPOOnvg0vUY3T0JK8e9VaCFOFd+pWkMKbvQVlhXda9Hm/wdKD1E9Wb7/Dq+11DTWF1702OCyUn1d9z2GnSfcL42+hoPAqbAUpvBA0GCm81s+zjywqvkXKfn7wUJro9Ou4UXgZgCDrmFsxVHivDXDw3HT4sPbJ3aG+O6VHZuBM4b29BahcbuGowhu18PqxoZdkNQNTRswY/PL4aBwpvEFAnKy2tBGtP/cpvFMvuQcXFFbpHpdJ5NdpGPsIQ4X3+1aQwlu2FW2Fl3piKc+JqgvUHbZ7FJRXjeJHQeGF1zgUFN4PW0EKb9lW9BXeMc9vnXlbSdXfv/X18pBeT5p7XOFlQICo8EIQMJdXALcqvCOq3+x2jT6gljx82333R2omHLG8xnuCLK/mnv8UXrDCe2XLbOu8yzu009YqyYZM/8iDmsILX38o2P72e4Jsf36eOFZ4/1zlY6/wzhibd/9msaj+UeWty1f4lA7Hk8ILRcwVGDFodXJQEM1JaWkM8m/UO7bspcFTCqkCQ0H06dAKh4h0GVIApZRvz4HSKyjkPhWI5ExPjgiis6/6Zw1PnaIfuTzg1g0H3/O4EkQNmQUC0fIKpRuTYgNxr87BO2Z01DlX3iNG5dRKtVDqzW+pV9aMQkGde7QZpM6VbW6DPAj3kIsUly0JHX9QK70gdrdh+TUvdCCHLxkUIH/tCYL8bnuWB3OlIAoX2DoIovAuroMgCt97dhBE4UupgyAKD3nXBdHwA9eyjE9EUj3lFwSpvl2VgIIgGsKdgujNiX7uatL3VQp1XtkN1tuSiKkgSnABCaKezigLopIKNtviw3VVciL3OTguNeiLmiDq3BwmmBjzkhI74GXjyguLLVEQRJudQYIoBA1Gguj0jRf4GpUGq+esHVwWvp2wDjeCKAMQRDmr2hlDQVS1fvSpWCUdrZhF0+x6xf2UwJkgmgJEBp4qGAui02a7a6+J4NPIvvDZT8qk9z0cCaKLgTgpOrcR7U7uE0Rzl14feLL0nG4M342dd+KjeDEURCtdQIJoqAvagmjvCZduT5jpTUoIi52iNnLPGRQEUXiNQ0EQLXEBCaIQKqgLooQ+8YrBBKr6/vcHKk2ukx71uCDKgABREIUgYC6vUG4VRJfN3fh1bd5TjazdvLzvn/J+4ozl1QNoefX4J4iCBdFQQtrbmpAqSk6LZ5W5p1QYaoIofP2hYXn1AFpePXAsiGJleR3h/Nk4unc49XjUdxU5N28RPAmidMsrMGLinI3Y32Z5pd63T53yhah+/IZAdc5+RWkMFV60lTS65dUdaHl154jCq+pq/4z3caNmnLOP9fJFenq4UngXMisesuXVo23PsAv3ciNcAsCtwhu5FiQ3uq9tgzwM95DPkU4Pj7lRR8nVODYvixQbgA7k8CWDhuV1A9DyuqEN8t1cqfDCFcMOCi+8Le2g8MI30x0UXvhS6qDwwkPedYVXK7jW+SH5uHYGT+Uyx5TEsygovOFI4Rr6IJg8ePZlUsK0h8WZlevJnYts6Un6/zvHq41GB5HcXFwd17CJB/Njgq0/wOYXCjHPwDu+1rPsQsw8xf4Jc7DCw+4SWLtL5vHfZYr2LSd8DY2GuGAtU7wpUWXCvwcJ/hbfrKQhE3nVTpiKRSU76R7s9N15KBRKZ+wFf4k9/TNsgKcfRkCdfood5PTj7HtLP4nGnLnNWtlRH02/FmZps3xnFrAZB39VzIytvbxvmcmQAg7/NN8Z//h7F4sZKBBTt8MDsZc7Jx17jFwDjZ6Kax6YvNt5mb7Ne0wnHVEHQZOOpQdRnnQs9nIS9c0U1Trkk77yYcy+JehNOnIuR0UVOmqmHmn68KNOdSQKk469B0GTDggajCYdr+0+Rjg5XVbfIz1ryc6B6Rm4mXQwAEHUqbcdxHDSsfSo5bq1bz5rRI5efPj+xcIXOJt0OACRgacKxpOO2v7CPlq9HdR2fK3SdeI7KY6jSYcGECelg20bzgjum3Sk3lr+frrPVvVAkVehJhuU9mI46Wg5CJp0POheze7CpOOZdO0a4TlTNHeLDQtVUF43F4VJB7zGoTDp+HoQNOl40M1y3ZVJx7W7s10vTFXWPTDf19jFOntAj086GBAgTjoetC+vSG6ddNx0fz9ohAC/RvK0Xj88TKac5oz1Oxlo/U7+N+kATzoSQiLeDrXyonitFLw65+UIRdQmHfD1h4b1Oxlo/U7G8aTjz9Vu9pOO7dJBW48bpusfOlzmciZcdBKeJh106zcwYtDq5OBgYLjyDX2tD1SNI5OVF1lT7bMwHAxY6WQoCnpepexwfnJU7rmVFxrWbyCSM5M5MhgY/eTB5XpvCjklJeWEi/fnebgaDBgyCwSy9Tu5jWL34V6lhnfM6KjUO54NcE3qVaAS/NlTOaIqOAsFlfpdEkilfpDUBnkU7iHPUjxl/HLmJp3oxdNSyA3r4tCBHL5k0LB+J4Mgv9ue5dFcORiAC2wdBgPwLq7DYAC+9+w4GIAtpQ6DAXjIuz4Y+C5zcmDau7d6WaeHveGJGdoHhcHAfu4URHddu+p5wfMJKWrFsTcjFsQrYSqIyiSCBNEnCWgLolc27V43ZLT6rjrpw4kJhyagJoiOeh5BjFPVJx+ZunRvs7xaOgqCqGQiSBCFoMFIEP04wHDq5x0eKjmvplUuHrD7DW4EUQYgiHKWUCKGgugZsW1nh50W1YoNnu4iuaHEDmeC6NcEEDLwVMFYEH2ftSFxtWGeVt5q25fBKaJvcSSI1gBxKkpoI9oY7hNEXX9QLM7W6VAOJt1KH2QWguXr3wISQYKoQyLaguja/UniyRoS1O3DTpydN+bQUxQEUXiNQ0EQ3Z4IEkQdEtEXRGfoTPBr9lyiHTmhyejiUB/HHhdEGRAgCqIQBMzlFcutgujID2qBdUEN2qkTqCmbf0ipc8T6rXQAZP1+l/hPEAULolUfBlQH7wzVPDrA4NZj6clmqAmi8PWHglt04gGQW3TEARwLolhZvy1s1muN7b9bNy6MZHosVyccT4IoFDF+YMSg1fnP+v37Cq+HUNqnoJnrqUU/U2fUW1rwY6jwoq2kQalxNxGUGlWJHFF4Z12Zviz7E0ktf/uhpWGEa2K4UngXMiseovX7XfueIQ73ciNcAsCtwrspASQ32rd3QfG4h9xno9fqV8eaVZJ39lGm6P6UQgdy+JJBAXL3AyDIbQ+0QZ7AlQovXDHsoPDC29IOCi98M91B4YUvpQ4KLzzkXVd4Nzmucjxb/V4vK/Gt1rpmy+EoKLyJSOECWr8FWv3R3Td/t3+QjQu5/RyCFbn9PLtQt59kCxy8BLG/GFZpof0MFkbw2W1STrv/+ABSMIBGcF7KbzjBGR9iEwTGcYQAMM6xA59xgi3wN/ZtnFk0aKaeX7CC6wrTkN6sX5yNWt0VP7hgVaqdzAkjlePhjwYZhBIFUPCDm2bA45HEneMPnlEvP57VK1aLe3j0Y2DG6EOYjj+cLoLGH4oXUR5/jJUgq0RtP62VyLd000zCspGojT8+GfLcDlziTYqpv/2BZwNJC4Xxh/1F0PgDggaj8cfpdTEJ0zel6hSlnBtTfP+yAW7GHwxAEMXrxRcxHH9kJ74ek5K6TuvQdNsCBd/DBjgbf5CByMBTBePxh/j+S/1DhwZp70vZvSQ+OdYMR+MPcSBOAhfbdqEHuW/8sVnrsHXc6kX6B9a8N3vz9uxDDMcftRdB449T3avZXRh/9L0g+cYvZ7Ne9Fc7wXGrn71GYfwBr3EojD+qL4LGH6e6Wa67Mv4YVp91LfqJvb6311qFmzE1Pf8ocAYEiOOPU+3LK5lbxx8xY+ZGLqYWqqfXFwzffMJpE0f84Osugfzg0y/9G3+Axx8bQmacCTB6qrN350j1bR+uoPeyR/j6Q8ET63wJ5IldcQnH448/l8DZjz9KXCaQbhTu1o7ZeGDrzRcRo/E0/oAipg2MGLQ6OTgtiD/5aV2krozmMcUzNUNC3a5hOC1YGjXUxV6Tj+ovtVQwMOPpTBRyXxKIpNAljkwLvKvsiUFpUap5rxLiwvq8moOraYEhs0Ag+sGhdGNS7CHcS9fwjhkd6dp672azSaHJJM/e3lpiJ2vOoSBdV14ASdenLrRBnoJ7yGmLMy/XObmpFB0MvmZlUS+GDuTwJYMC5GWXQJBnt2d5KldOC+ACW4dpAbyL6zAtgO89O0wL4Eupw7QAHvKuTwt6nQ3gC/SYqum5+MrgIzqJ21CYFqRxpyBaalMq8ahstHbonOCYDzq3QzEVRAWqQIJo5TmUBdGlC48m7Io/QA3ZmS8/vZ/IfdQE0YgpFd7LHZwoSSduKxCqPt9FQRDlrQIJohA0GAmikVKHePvRdpMPCE45avJCvQE3gigDEEQ5q+kchoKox9gxk1IOi5J3PosxDo+p8cGZIHr7HAgZeKpgLIhecDi8MX1GtmZuk/E7R+1phTgSRLOBOMWfayPadO4TRFfrL791N+4E5eCEArdp2QemYyiI2leBBFGDKrQF0S3eKwycqkJUT/CqushWDviGgiAKr3EoCKK2VSBBFEIFdUF06st7j5d5EfQK5eWLf9ybe77HBVEGBIiCKAQBc3llcKsgWt2rgFoUpqyX4m5x7VD0yQ0c8YOLnAf5wWur/gmiYEFUYJyh5I2GaLVIoccNX6qs3FATROHrDwUL6cDzIAvp9yocC6JY+cEbzlSc/THtATnsVl2vQb33+OFJEIUi1lgFilgtZyP2t/nBKUZpyxaU9NU/fr68xnxDaQuGCi/aShqUGiXA1Mio4ojC+26JwqErcV7aAVKxR6dlvHqBK4V3IbPiIfrBa9v3DIdxLzfCJQDcKrwm50ByI7m9CzqCe8jrDRvHjln4jhyWZzgydOHVa+hADl8yKEC+9DwIcu3zbZBncqXCC1cMOyi88La0g8IL30x3UHjhS6mDwgsPedcV3gPij27kZorq5vcbdHrU7EFoKLxHkcIFtCDzUX7Hg9z6KTYm5NYTCC7k1pPswtt6hi1S/apyb3702qwb47D76lAn91g2354FKebhX62tsTP6GlQ+fapetCQ/6nm/00YoOJHn1sKdyMeQwgK06Qu2+de7b9Tv8FE2AepwFiFKHX6CXag6nGYbLzhHIF0Wq2Lb4RwWpn3ec/DQZHHnTGRDPf8nEcI4yv/Yuw6wJrKuPSoIAooVsAARFbBQFAW7JEMLXYpiN0KAaEhiAipiQVTAimJBERUb9oq9rw177733VVR0dW3/1JBMI1kmEP/n83t2v3VOMpl5z73nnHvOe8/dM62lW9CZpGM6rYmElTDVROqWsFwT+eFm8DLB5xF/ac1qvz1NfXJZq4k8/123f4FvK68dn4Yedd/h0ouFmkhwCVNNBIJGRzWRDfXqtPgkfBZwYOCW3hv316+lNzURBBDajHbnEh3WRPoVdu3TKNPdb3KbnVs2mb1vrWc1EXtGZIhDRcc1kS1tsxyO1Evi72x/7KjMbd1DPaqJ/PrEhNPrT3hoWvjn1UQOjjlyp++OL4FTjDk5Fyac3abDmsjOEqaaSK52NluDmsijwowBa3ucC9rX5cHLH482nWWhJkK0cSzURLaVMNVEcrU015rUROZeWVHvctVs3tLW9pyjneb2qvSaCAIBbU0EggCbXtv/1JpI/XMF1gPvugas/rQk5pgo7VKFkMSjPjORxK0+/68mwlwT6bDptGmnuJ6+OesG3Jq4rqsxazUR4vxjgSgb8ZmJKOv5WY9rIuXPi1PXRBKbHz3XckZ04AbxkDZ3fwYO1qeaCKSxNowag2ZnBZYQBp18VW/h+6EBOTnBrrt9t2zVYQnBIeTbp7F5DX32ui1qfPH90gEsjH0DRiSLSyqkhPDW5O/Ms6Hjg9O+vLVd7t/2u16VEHpiBoKWJA4NN8zF7tD7fDZxxcxOPtvRtrMiwaGqT87n0KbGUZ2nspDPXvOJKZ+9QLlo2Kn3kHdM/HSv66x+/kssLh4OOFavLTuQE6cMC5Dv/cwE+TrlKN/1R5YQiAk2lRICcRWnUkIgxp4qJQTiVFIpIRBVrnkJ4dCy3f8+kYX5T5Rnv0j7vHMdCyWE3X9mQrSBaWTC1xN9Aw+9WzTsQv7bkzpNiFoUMyVEr79nOSFaB1i8qQX/sucim/sT9hll7mctIRod4VTdNNjJc//2oQsig53KfSyXEQjULWZKiELQ6CghOrb+DNH2LpG8OYWelw/aDd6nNwlRBBDadNav9zpMiCbsflwYN/iiz+pRrTqHxVv81rOE6Ov3TMgQh4qOE6Inl/Y1eVLjL5+pLtni4dU699ejhOgRRpw2vccd7Z4/LyG6OPLci6ioDp6Te//Oa5HhXl+HCdHRxUwJ0YHFbCdETwzck+0u6+6dUWv37UNzP99kISFKtHEsJERHFDMlRCFUWE+ICq6fnxbZ/Bxv6pJ3PjvvHRhc6QlRBALahCgEATa99v6pCdHrwh+FJlnNgzM8Pg+9s2Bwmwohidt9YCKJPy7+X0KUOSHquzPsxEpFo4D0k3ULb1VNvsVaQpQ4/1jgldp8YOKVmnzQ44Sorkji8pzHVy3SQH5mxwZGM54ppulTQhTS2JdiJo1Bs/N/JPH/nuHtP2t5XJXcdv47fz4cnFZikaTDDC/bmTRoaJxnHBp7iyskw+vZ1+Tzqa4NAxbcGbwv4+pIJ73K8PbCLB4tSfyxMmbYp/fpRmIKQG8zvEPeM6Ubw5SroP16D3n1qwve/RA48tc3dm+YV1DSlB3IiVOGBcjFH5gg7/8Bh/zAH5nhJWYMVTK8xGWpSoaXGEyrZHiJU0klw0tUueYZ3itD+zzYYF3gv6j2pLTTrUSjWMjwHqRTFyMb2ayUmqs9H1ntyxSMZDU5DSdZ7TOUiVTVD1CCSTRL9C9IwlRdqgtucslbIjf5EJ2iGNn81fn/ic6PfY1COZiERi2YlEohmIj6kMfqm0ZeyzoSssTn1N5/xo+aQvUK5DQAXzNSv7moVcSMGn+D8xpNndJ34BgzFkj9xf8StXP4zyyUTLdtl/xkfAJ3U1XLgkzbTJ5OCyXPzIoYCiXHzYrYLZQ8fBb2ePjgr36Hnh5ZmjnC+xVrhRL5VqvAO2lvfabaTpMsubukNQuFkicwNLSFEggaHRVKNgmXnW0cvQ/MHPT+XHBsyUC9KZQggNCmuW8RAGG1UPI4xeRau4H1uLPCxj/P/vdtuJ4VSi4wIkMcKjoulEzOe2pebfpP31VZWR2LNuV31aNCyT5GnLaaFWGW+68/r1CyZ9WaRdkntgdN9FyaMLFHbzcdFkosaxYxFEpq1NTKZmtQKBFH5dQ2vf45YN7kFrK9T9dGs1AoIdo4FgolDWBUaAslECqsF0pabzess6dlZsCuU+d6KpZucKn0QgkCAW2hBIIAm15H/tRCSaeSa16KuLbcg8vM+vJu1k7TfaHEHATiYVRpmeN+NYv+VyhhLJRMemIY86jaOTA7sOuMv9P3LWetUEKcfyywZ2NhXdOyZ/vXLNLfQkn5k+XUhZIiyxWnOz1aGXSw56ZPMd1WrNSnQgmksTBGjUGzswLrCu23z9x7v9Ccu63kYM3v2XXX6rCucCWySR9jxQi//bNcWq0/M3MSC2O/OyOS7aGwogLqCl3a7SnKGd/If0pOqIHvs+lCvaor9MQMBC1z3E/pYo/qfZKbuGJmJ8ktnFrl37iYSP8d/ROLX0QUvGMhyT3brIghyT1FuWg4pveQX3ho6lzfsQlvSVK3F4UjTHqzAzlxyrAAeVZNJsgzlKP8+B9ZVyAm2FTqCsRVnEpdgRh7qtQViFNJpa5AVLnmdQV7008+G2LPB2W9jr88Kz5hCwt1hRN/ZkJ0aJDLkOXmUm7hi9Dp1dqYVdFpQtTPhCkh6mjCckK0RuzwwUsdG3jNPsJL23jL4TdrCdH5kTOLUpJDfAqNDIZLPYdNYyEh6mPClBCFoNFRQrSDgezf2g+TffPmmC3+bb8rT28SogggtOmsriY6TIi6JfxzNkl4xjvPssetwIOzpupZQrQdIzLEoaLjhKjt92oPuz2bzd+f/VqR8GPITT1KiNow4lTfBHe0RX9eQvRi8fbH+8KDQ9a34TS3PZLD02FCtI8pU0I0wJTthGimxbl+DfzaBKV+eLHt3N+zB7KQECXaOBYSor1NmRKiECqsJ0Qv3Rh6Z9qV5txpfpzajjUMHCs9IYpAQJsQhSDAptfJPzUhWtBPNnNKW2fungTxWlGg5GCFMMc3wqjSMsdnmP4vIcqcEJWv7uhmu8/FNz+mJMbrw3tb1hKixPnHAtl0PaxrWrLpMlM9Tojqijn+492bSPfbH3xnju/IMa6dvU+fEqKQxnIYNTajYjX2/405bjFozdCjr3O89kqudjGp3mahDjO8bGfSoKExkXFoJJtWSIa32ytn89rF1QLybNKibx8MPKhXGd5emMWjZY7PUMYMp/Q+3UhMAehthvddDaZ04/MaOOSn9R7yZXHDHF/7xgYu7hpvaL7nSz47kBOnDAuQXzRlgvykcpSf+SMzvMSMoUqGl7gsVcnwEoNplQwvcSqpZHiJKtc8wzvlsXd4s/YXPNd73uss6RDfj4UM71k6dTEyx2upUqe1544Tvk5BUCZ8goaoTPgU5SpU/SPUh7gSDBTTq5LwJcp1wSM/WKOIwFQ+R6c2Rh65Ef+/Ecnx71EoChfRaAgXU6kGl1HqpHCCd3XnWyv997942zwpupkd5XuQlKEUlGUgU76E7Rh9Jdtvt9OtcZc+lYhYoJN/NCcq6fyfWT1p8gCofz21yHN7+4SxmQuS1+u0erLclql6kmbLcvVk6ZbC6PO1nwROPh2bXi2gXgBr1ZPaRXPbGxzdGLik8EKKyPlFVxaqJ/m2TNUTCBpdVU9if664sy0oZGeq19rv0cLrelM9QQChzX3Pt9Vh9WSjnbxdscg/eMGk7cYFd6L26ln1ZDojMsShouPqidWcGY4teR24c4Qjzv4z0UChR9WTUYw4SWzxIPbCn1c9sf5et+fL2NnBe39mNfrV4pRCh9WTq7ZM1ZMT2tlsDaonF4tzg47PfOs/MR183xNwfcpG9YRg41ionly2ZaqenNDSXGtSPYnLOOsv39iIP6GXXeHlFtNjKr16gkBAWz05oZxeF//U6smlC41KDDcH8A91GbPox5rRt3RfPTEHgRYcJjq5Ied/1RPm6smVffP3WVXt5rv09oL8rAc9DVmrnhDnHwuU2mYcJkptQ44eV0/Kn0Gnrp4AYVOyGo7z89xWlDsgaEWBlz5VTyCNmTNqDJqdFVhscHDM8LwypaHX/uLg8zvb3L2kw2LD6t6xJXsmJHtvHvdsTmbOrOEsjP3vtkxIfrCtkGKD79U7V6/PjfSec+1mpv3Mfe56VWzoiRkIWjo5NNwwF3tJ7zPfxBUzO5nvS2+fferWOYM79cVqlw9e7W6wkPkOtmXKfPsoo5rLeg/5+I6x7dusPOG7YJCw7ovr3euyAzlxyrAAeSCHCXIv5Si/8kcWG4gJNpViA3EVp1JsIMaeKsUG4lRSKTYQVa55seH0rbk1/z5613+RvOTM7KPgZxaKDVf/zIRo7MzM49/3bg3aFO09ZPSc97V0mhCtbsOUEH1uzXJCNHZ4qmj/7jVeu+9Z3LHrZt6RtYRowssg296Nv/IX9dl+t97OlDYsJEQNbJgSohA0OkqIjnMs5BjcPhmUbmf45HRyRozeJEQRQGjTWf9a6zAh6nv756VJ27YHr/t6Kc1pjdRTzxKixdZMyBCHio4TohFVqpTkTrsEFkzo3W/QHeNxepQQvcuI02Vr3NFe+/MSoi+8ZuVnnd0VnPW5oMHAOqZLdZgQ7WjDlBBtZcN2QjS96fB566535BVunzH1vsmroSwkRIk2joWEqLsNU0IUQoX1hKjb2pd1bpxb6Z/7qmr3jCZz61Z6QhSBgDYhCkGATa/rf2pCNMXCOrnW8WYhMx49a3/9cWSe7hOiJiAw3YaJTi62+V9ClDkhWrL798T3d3YHFxb3nPPwQrYlawlR4vxjgYE61YaJgZpqo8cJUV3RyU+dLh4z23qR75xGBWZ9/uk2Wp8SopDGRjBqTFyxGvv/Ric3mbJ3UmTAfN9ZD8GDTetXTddhhpftTBo0NIYwDo0omwrJ8I6NH+967ONzz5wOv7jxA8I/6VWGtxdm8Wjp5GJlzHBD79ONxBSA3mZ4N1gzpRtXKldBN/Ue8iDhp2lOS5p7z7LPsXjtEzuRHciJU4YFyDfbMEG+WjnKb/2RGV5ixlAlw0tclqpkeInBtEqGlziVVDK8RJVrnuH9HGs5+9jCfO4sC5vIlY6WbNDJb9Opi5FOXludQ609oZx0AwqmMukzNJRl0ueohgLpQ9R0EYKpYn5pEtbkT7BOLrcBgSTY+CWq8pbv0CmRkVxuzP+P7HLlFymUppTRKEspp1KSUkipnF+1rh0smd3Ad1LrBlHtrrb/QP0y5PyQUlKW1ew33EP41GCn3+QFM2qmdPLStMM0ra5sQWCpHZFjfpc1+9i6Au3jq8P9gu/Uvho8s5HFvSSL4nYq9vHas8V3+9Zw4h96G2XzfeLTRqoVsP0uMy62mxI0eUtiboOjUQdU7KPn2IR7YYVbvLZNyLC73ueTrYp9PLwjbmnJxUVe2am733h+P/ILEhliIt9fRQtFo4tDpt+suy6o/pOhkKg6JrrlMV8++7VR4LS+YRvywKRcSGSEidY9mbIseMs27ubeo1ztFSHwYxhjomdhhVeApdbBa2/1eOm49OoOSFQDE9mcKqoZEJofkFnlScPdkWOfQSITTPSU0/FIXKu/vSefHX1wxg/7K5DIFBPtOLn97I864X5rP5zvtaiPhSUkMsNEyzemjm3xnBu4Pn+AUwvpic2QqCYmEucOXp2W2cpninF7cczoMW8hUS1M1PNqL5uiwOVeB+7fib69Q5oBicwx0biDhd9D2rcLXlkQ7JiwJ6ofJKqNie4sT3Dx2WHGX9Va1Hj4COs6kKgOJjrfw+HB61+tA3bsaHZ1zpvj8yFRXVxf76w6Ltq2Knj/+Bm9Wjb6vBcS1cNEzfo/Dep6dXbIvGUB56bOngsfx1EfE/FPR818VrgS3H7dsEdK3wNekKgBJnpT51mWW90s/pp/rgRd/WL5GxJZYKKq69buGPW9fmD+2LlyoWvoWkhkiYlWHgl5lz6wU+C05mkXb44b3wUSWeGqLMoM5343BzfuqcarNsbrb0jUEBOd6jkxo82mA4EzPZb1kI6OagyJGmGi6KlXJ932vMmbccPvXozJcB9I1BgTlXQreRxZfULgvnozfw/795EYEjXBRI+XFkicrMx428XiY6cDDeDDSazxG8rOzu+46Kb3iiHDgsNfToBf2QYfAJaR7V2yGgaunlKl2rOTrnGQyBYTuR6IiNksPOC3eJV7j+hU0TVIxMFED0d2vBZ03QicW+u81dC2a25CoqaYqIE847RVQt/A/c/mrvuWavQYEtnhyH9dsL+Wg5l3Wn5Eyer0jjCGzTDR4tNXkwQdv3qtuWbYqNqu5XxSkAHbBUozW2WDM3/jqHe+W3ZJl2QM+HSLhSDjHp3NaxC7Z3Pu8VPeeRsejz7TZIz6Zkoj71EysTRGqHkR2R77BpwnTZKPEEIr80QpR5EgEIshq6YQxiUIJYkKzaoRRItH+Wjk/UyYQNPAuoQH/LAvgg02NDxIy0cuCDy316oWURtE3ht6ayH6IJTv9tH/pMPPc4v8D611jc7q9Wu6uoqRW5DeDLtclg/ddTzT0/D9Bd/Nb5c3OfroS63yrjy+8oB/YYBiqJIQqVYgUKwOEF4zpVuYdQgTQkNDIYJAihFGSxNkUoUIyaZDzycSc6CRohwnHAG0gBNAMYwomhLFqm+7PLa8/Jyfw/XfNa+WTUt1loHyd8gsg1IR6+kICK7njHDdta+UBKwRVh0snXPEUhI+qgkLbLqB7oRNtJhSdSXGCxI5CYJhQg4U0cB13iEChRA1BNSddXwz0nyPtvJamWSWVhwVsIGQicNuS44nlRLWtRcEooPdi1J7QmSwkxgCWgLXtJdQniiCPolXw4VEICnB6rzdMeju1+s+hV1CQ4LfNm6iDhZ+TzJYSokuwHrOCBY01DH/c5+2WmdbddjcrbV5e5aJ33cZa+yn9lbm3nBBFy7NBAolcYnxZD9kRIPxnirKr+KeSACTm6IhMKAbcGIF0YlSOWRspJI4jggaumLkB5yxH8LkCk60QMIZIuQokmQysQjS0BApJIS+j94ySQJ/VSCJ4UikcsjHiUZDH0EuOnPAeIEkTojot1/wAI4ML68h1CJpXJwYmh3CxJFCoQT5TOJIKScBGgQa+kZiyM8IG2lMED+gqcKf8oAQB0jhDUCqQqIvCLg4aOUr65T6SuyBqGl1MxotsOoT5remyaq5+eOdb7HoLIkWqLzO8iUPCIIRmkk5JSxBAHTQylnaqY1HhJGHDj0MMOijlJB9cbSaMUo0KmDetY+TPFz3qbeurE4zLPDrrBsKCJVOjKhA46aSi5LVAfzPwx6qCsJ5TnQKas+P5cAksDbILFbXlkihahccXZ1dOeM4bZ1dW1Kq7O3eMyKHxe38Fjc1DN6Vt41ImVPeiIIyVyrThepaMKquceWoruxwhokZYx0qhRYmsEuAtaaQCaNFsbB5R70ApXqWT39w5sWJ6mCuxLBRktMFQr0CuR/ZCKGXWVdKOIhaGeq6oBixMlrxGO0jYGcFITJCiPpFLYA5m+vw/eqwG0G7BsyoPrF1Q3WqnhF2Y/IyDRfoApxOjOC4OGhHZXRAvVSpB9cGneqHYqqlzRgZlLaifurOzaZS9SWKknRDXqKUinSBUAtGhKA5jcVtD+jitlOLBIE/O1n6phXYGL1ulqLeFNM4EIrROOFegZonDnigXIhGa2L4u1gkDK0QY6G/QnFXMkwWlSdyZPCMgowtNl7h2AsL3cZqth2VkBClfm5yFI1LNMW4OgjkukEY36XkXIWCwGg37dIKyAOoYED5dpI32wXdZVO9p3Xrs/LVCdlwdSMVDn+bbKTQy2VFSmf2xu+/4Tk6aFpampWJmXOz8kZKxiCwwI2WSesMAjPdSJESE5fLCgEIHxeOMSI5StKjdrZjT9Sw+dIn3Td94HmPi4s3cNSnpRf+ZfK0LBWVBVjuJs73Lk/MuXO3Xn7+beZSUxYAm8QIGDSiKiWIQn0G/Bk3gO5PMSmowuleVLo0RXTJYFU/dOges+VbUdDyqiMiO9cdYFGXL4EsJaQM71EyObQEV7lXdS4v3DGqZfkCYIJqN0QaNepYGOuzaWiIBMwL/MmCamWMqo2tJNVSxcezemgVapkFqthzas6LL1c+eshTcPqiWY5S85Mj1LmV8NfJVCLkKuuOsT9mk7ZQUonikCmGOcaHdI6Rd9Xy3giPQs+N/QZaTet1IFDtberDdJJEOPXpJYqNFcqFEBQKzZn+LqA0AYIcJbUgt4kpvQ2yOITdpyIRTizB27g08ojEOmDZD0xSB+WnNAW9GggMa1mErDQoNgO0A4EBLUmekoYLRDcGuYEqoMDpBqlMKIejDXiPBDrGFfAmN8SxIv+F2jQFnI2WjhTGUDuR9tsXXnYfBHpv7bbnUNqAv/uo25he8F4EMlb49bJsjIPHxZIf2Y9CluZ12djk10FxeW2MIQiIYJgNeFTU+gYIzOVNCbdQUb8yuxUtlSiE0UnI8IC3SVFnN4f9DAyzml4zeN1NyawLy7uo22vT0vuSl79qQtZNQncMtv6UsPVBYMNMwiM6k3CmVrNPbd2lQekf3wc4Xxnvrc74DxPKxIJoIbKXjsIW0AXMTvj3YMqtQmWLJjrIR4oS4zlSaJki19wSEMv+DM9J3pmgJtYU3Xc8wA1G15Sy+NYLBKzLPfctYKemwDd0Kve0Up+iaSl9pjixKGC7947ruc32XlUPn5EbkcNn9HJZ05lIcyjvdP7IA9rCyC2nzMs0BQGHlrThs4bINVYiJ1cbavDQooRvQl7q14WtLvtsXSCu+s/C4/XV4DPDBgh1SUddyvoshtCyZkSrXssKDbDwByVx7JsxcezhIDdOKKfYSlFew22BOEhYsdAtoEV1Mqpq6o4pBMdUnklSXr0OAdFZUMylCpyHI7NAq0SYVTCCLbKzCxn92NCn3tGriCxoNnVPYsDOTZP38b06E46PQ96KojCBXNYFFNaMUNRTOqrHdI5KbzjZRGvJDid73oj84xFNa/EOyfPa/OgfUsACJ/uDIxMn+5UjDvkTvYecSLZjB3L3xBwXQ+8Qv1mxZvN3zo2yZqORfUvGRvbKUf6UNZqnOQ55BdA8KViZOM2TgpWJ0zwpWJk4zZOClYnTPClYmTjNk4KVidM8KViZOM3zxPeGb9aZdgictQS4zj+QEk2ivMGDl3L0EfmcLFDentHp3y7gmNO9rSY+qw1ihlx/VVtd//XQZD8olirgcBEp4JCD8uo0s83ORySJQYoD0dgNkCUlvM7EaAialfeJHNYyH5EEDtWHtOgbshquD9ykzF27gUCGdmX+xmi1DQokZXIp0vhBCrMC6XlBE1McpmZsdfNeOHO2YVrerkflqbURDBKxjFdeg1QDBFY5YG63mGSQrEBgPrngz4RVAyUlQhUr6qMNimPG9N202m9vxtpC/xrDLrBIi5gQGfz5ZMEon7XSKX6ZvOQjLKCUwYjSKAftWhu0CcXnFTLZEMzwKQcv9XDuGX2ppP/07gF//xrvv+VN+K3G3DnHKrOe2wMbRNQFuSgQWKRlPbeVsnoIQ4TCEyNNgJlPkAdSs02U4Kxv1vlhcfzagHTxfA/g0MN8fahaQiDNZgQpQ8u6bgsvEfrmylRV6ZBBCov0BurakuUrxsaNCFqeVDRpRYfrNdSriPh9yVVEpUQX6IxlREehrOk+p3OMb3oFBxq4fAPnrTjrsyyE35eciCd7QgMacJuq13OVVLeRUizLqpkjJO7Y0LQ2oEVrjHcOWGsMcgIqEARuaufqNCvTTrUev6fJw0L/nMwWGyZtv3RcPdmJ1GNp3LqasCwrTjRxLGxHfwuDFUo5xuxB4LF2vq4WApYQmmn0UHl7ulyNNu3OTx9+K+dA4opkdUvkDX2XGigVUUWHBGbIqGGA6byWzq7sElq/djN4Qc3k3lM/ihZ1OZ8dWXkltChsjMAlNA5pQkUj0GB26AWdHQIdzrp0mvggMN9n2YfETg2tiXnoBIGMg+ZpKPLldKG5A/o9vNqD7EsRcCTCkfAloVwUjTlIjcwScbcYwxNSZcpVxJri+pAH2DkXIa2zKGLyCBCo6qyVoaqFlKHQ5C70OJRv2SNkQL3gLl28d9SKcTX4aEMIw5EbkEMk9HKZvbMIG+fKO+ee8gAODM8GyjlnDQIWzlqxSWqiz4ONCWoOws9xhUW308FVVbb32O74Ub0BJ/a65Oofdr0sfH4ceZWdYxnru6DnvO0WzqsbsYCPGSM+0PCpDIaBMULcGIEC0RUg/iHTRpi4uDUjBPI4YSKT0jK4pzcNtn/Gnz88qPf1zBGE07PR75OVhl1n3VhCWvnqxKSVd076pJXiQ7hWtHJf5ojBkwljMONL3RWto7d9Vkic1+IQ+8zJDpPGqCsmCPk+WTHYddYVMxhEzQmcZiSvVxNBoI6zdguyxkoMkIWFWFQWHuN2XLjXevUH/5y0YidZtU6v1Vm1IHoDMqsWF+gCkaqMiHxywv36Szq/viU7oKRfl8789JKficZHb39S1zH6i5qTYboqVxjqDpwzMl4UHQ+FlfDeQoECWumqsGIw96/Z4oO48ZvqecljEr2uBU/0ohPGEyWzXzxB4IhTeSvgTbBQA3b2Ikm0OCkG3pbLQZ+Eul2af/3ev82PBGac7TMvVfTKTH3w0QU2SkFFO39jKKSGMXSl4mjA/TogDLWyWF2DsRHlhY4o1Y1aMB9IgeYH4kVx8fB/l8aUnJRg6jabRH+uPpTQnyEPJew665M5EAPMihKwQQhg2GR+pfeFK+Jo0qRwVYVT5iAlljlYqFwtc2KqXC1UYv6aDvPgXT7nTwHHwNS+DbuIXvvXUT91NShJnCiSiUXRyLYwzXubNg6C4gHIPSVC3xRzEtTuopGdJLa6YHos8mGw6nJtWgi7YS2EyYkbNxCwc6PoaYr7E4qepvAvEXua0vUsrUIjZ7NnKZ1tsvYRySGbo2zQr64vSv188jCxHeMZ4j+na7VGRzI+bvwPvY+JnQ7Pt2oZ8tHayT9rzO0S2XaXcDZ6H7thvY8pCTpt3IoI/UKZQLIJF0ZLIQutDUpBXzr4Tj55yDO9INXjtceuHuoo8cgo8cpE6eerh8aXxoWETOkoXWh/zsiTBZTsGFGyciP1g2Rku6B9nOHASAOAiKz3ym8V7Ya1iiYlmuBW0XZKrvabP8yeEvsDVZA9XeXCZE+zXP5nTzH9RDe1m8FtnOS/NMKzw6fidREs2FNi3ycWLMUKFyZLsdBF1/a0mvVqj2NVxnluEL8X2bkP7MmCPW077siK5y2k/nNfprv9ip/XhAWUshhRmuyiQ3tK9KGVbk+REUNrTyGkMHv6Vu/XBMTpxA6ZrUOVhh9mgDKvnZ8947dcnRHGwpKgmzPTkqCDMw7536yR2ergkFcAmY2iqR5u6ima6uFkNoqmejiZjaKpHk5mo2iqh5PZKJrq4WQ2u0dv99U0+QYesNn5fOgLrwcqZLbr1+xuh45b4ZN2eN5jz4FT7VV6Fg5aFFvnM/eV/9zzf4Vkpiw2V+lZaNys64ht09Z75tzPaNpg0Oq7JAocUtCjGrPE/n4sUODesTZqTCtw1Py3TpcUbR/xUUMkEZB0YkCnE2JjRRZ08p5OJ7m7H/bJePqVv3f3jr1bhz1S3zhoGCqQCMXkHr90ltKRy5HB38A6xsB9YDkSaaIQ7VYEn8yEnpVDnf8jdoakeBRNzKdpeLRcKhaHwS4Qvli6h7S4B8G0Wv/aM831s1NgzqL5z2v3LWlPZ1qNIxVCeQT0+PjPtvCSJg0Rw+Qv6HmQTkIxokTs3aGQBS6bPE4tIKjEkM4iH+YBuW0gi9wJBFIzQJMggTxOJAkUxqp5VFP0cpgoLl7teg30eoRUpnpV3ayHPvmL13RhmyJzBMRQObwRMVGEPpUR/lRUE0ouGMmXxMB9vHB4q9SAL8K1HJVLSPAPM26Ul8zC4TYVAjEIN5dS8WxIj37l3w16ywUy5XewoVqs936e2KeUpdwfcfyz4OivtmFy9Gfb4I7+g95jTmwAq7/51tqtmDA3boVj/pE1N1mRDfMpOvvibpKisy/uJik6++JukqKzLx5ceX4fOOZJQbeg1NgGGXxPRbHmDfOJPYFZ8KCf6NRVIzxnREHSUK/Nf38VenDWflRvioeVC4Ogf8khe6h5L8FGeKFRwgmRCSW+gZwE7B6alRGJvY8ZH4vcq4/wAU3H/2MecLtDEUKuBi6SEjrhIFDQgVRYZCJXWKPjF+9ZCTceSIKbe8YLJJAno+4ssKjX8qEWj8G0NuP3cBxGCNTLiF7oHchlRFzA+hL3OQ+4CUOyho5ucb5DpdAtDKMhaJWWYe/evb+1aRHIUVcM3JUqSSyQI9VJMRyjUDcIfCDcO3hsTc91104aPuftuUNovYrdhKL1Ki7RhXaOMWpnrz5oB7JGv7XhJNl6J4gUSLPjaDU14SaEUjlrL1536bAqxm/T+oc+U9PMWqkrB70jReq3VKIL5WxhVE6BPigH1o+qcqqVoRwPbgL8k4hOoMdRQF8VSqKT0VaN3ThSmWA43NmxLfK30k9QzyhZ//QTB1e2957SLfNep+ILfPXd7xEq9yfvfleT6kJ5eYzKy64c5WnQftOgDA12K9WgIl4kSZZAkS6kPkhdEqkEVh30X2LpSEQI/9UVFiUIRqEXKPV4+/Kcv65/vOK75MNN68PtqzkReqjFU5Gpscu60Fwmo+bGVbrm4C/BdRitCDZ10Sy2SBLHbAh3FnEuLsy/6bl20JR+X9c0v6ZuCGljplIJ6xoZBKIxBLysOEkKqxSIIcTi1BK6OLWhQUr4kX0lIYeMNz+zdycc8oad2sMJlQtHiIQj1cNUGFM6PpwDF+5VpFDJ+CBtZ+OE0gRhojyZI0NvqDDnoxwwviRMKMEWKfTBK/F0DqZnJdci1eW1ekH/kknlieiZg/inNMbeEgSauEPYL6CsUUaCQHV3Wq4c5ZLXF8cG2W6JPKNGEb2Hg8318UvDvA+tjnzSyODQA8I52dhdKc7JxiVlLYbNc8Psg6LlPktEc5o/vL6ndnkXww1BoBGMnCelHWkLLZXdtaLHN4hQCWE40hFCuVxEc9LFrVpT0m7WCvLf8uzm1qmTTkeXfwoTsCLaCBawqs6I1Y+Ktbl4stIIW3LBH4KDnXv5934bC7GID7/Ic+X9NkR8G9GrGuMLA/yj8P+bqYY96t9QLrc/05mx/7Xu/0+t+4mHGlVY6/5J7kyt+2PItpOF1v2XOjT8sX5eAm9psqtzvsCQ0NehXHvU2baRL3lAmjtTp/NRZBupi9b9Xgvmpn9dE+g/9Vb/jYE7/X9Xeut+CSMq0LjRm7WDdtuF2Gvdn3Ix663X2u6+E6/HtCtYVeWi3rTu78uoutDKUV2Ft+6vavj1wqMFLYOzfp5duG5F6spKbt2PWBna3uuQlamw1v1O4aNcoCCYu733a8GF3Kbqp5BVTut+CSM4Me4V2Lr/r7Fzt3Aa7fZZYeNzPmKiga8+NMGAEOrLiBA0p7G47Qtd3ObNbdX6d7er3DX3bdZeXvLeTb37ALL1TyYVQx6dHLMZ0+DcobREIir9PtZBA0JcLk2Ki4diOIUQSdVo0wGCeNAj7dOSeyWoCDXFF1pa7vKA8BWAcNKFiG8yCMzwKO92rPqljwVdxbCgfPUlXiabh6b/65/xJsI+YHKC+jas/3TiF/GQ8qVVvrcZ3Zi/uKje6jm/em4vbwiVxwN2wOjZglQexxoE1ntoFUKZodM3RhgnF1LHl+9cxq6rkzA0ZEKdH5M73UrbQ9hXhXyRYl8Vep312Qm9/zLG98/xqOxgSTkytQiU4EcWSWNE0QwdcbbvzaozqqO9167g4UPc7LPuqo9V/AbksaqU6EIZMxiVMbFylEEMfwBtKhbOARJpIuS+BNFw7tTRtRu0ZIVWFgltOG27RcdL5TFtOO26KYbLE5G/UEerNx+7bJjVO9J72aCGfc6//6zeXqMG/APhicliilMzS0W6UFYyo7KkejFz4FtpFa02KE10S5LkQxQMM+hi6JGfdmGxPrtmvuqT+2vdp/IslcupjtQ0EDXk8AbRi6QwYzq4frWHdlEqZskZoq1GNe0PvQ78h5t15PUzScaXhpW67IUBWIQDcJMCANi0aBWJ4q6MvjXFheySEbt5Z0MWrX782eToxKOVukUYBiCVCYBecg880PznD+PjEM8HrzA+jk9HJj5O3Y665uPcu73+VJ75HP6S49WXBQXNcdMDPo5XR6bqZueOekAqWLZsWQXwcfp79PhqImjGXZFz8uG03/326wUfx5VRO/b6oJ0K4eP8TGzCrXXenZ+aLQuvc+iAg17wcZowKqeuPigHqEw+znvJpEMfh63yzHB56jPn1T//6BUfx5hReb8qPdjVIz7OvgKX8Rm1V4ccKsly7G79akgl83FKPJg097rSNadTPs4/4lZ5Lw0e8eZdKjxh0tKYqxd8HCSGoOXjQIYQi1O//n/g47geiIjZLDzgt3iVe4/oVNG1SubjZHZk4uPIySGtTvg4EY2rtjCNMApa/WjMfOPBHauyzschrs1Z4Jikd2TimIzpqCs+TiowJ2jq6vfgpNupWVfeXV/FOh+HaCNYwErOiFV8xYY6lc3H+UZnxoYfErUWBa8Ddx0MEb942u+9eqWkZxK8QdJXLpDFk7eRalG+aO4lUsjgLWLKak6yE7qVlCOAO+3Fwb9AOfIejux4Lei6ETi31nmroW3X3KR9PnIlR1VIGn81wiETFqK634piVBI3N2k4KpV3o+DTBMDtvCxA+B/1URnx5Cnvrb9TUc1woRhSmDCGD9n1UfjtELWiqvyXTpX5s2ckvfX/6jt/uIUid2qbAeq5IB+YNJBI9kS0YTX6BY4Csnbo6YBJCtjVIydbxUvFMXDzOpgKFYt8DgkDEgVxCs2ODyVsDaseKI0eJoxRfonq0clpLPS6pibhKw8ogPf2VaUkM0VBxrUVRbMaGCI4fqVoVgP/Q2xWEzz5fvfwojeek85sTzX+EHKV2KxmYu9l42/L+vstOJy/8PmC6d1xOb7T7j83syH+MEUzGzpNm8JbozE1UicZv6cP93ibwVswZ/LF46ue/y6PttgP5n7wgJWwXvMoTX0LEMhtVSnH9JnCp+ENUkDvIIkrdXulf0eWHCmuncPGUvTUodNVXZ/S2QY5gsQkObXDtmrWaXWrC8P85tw2sr/vsNOZUWVGIHonis6wmEAXSpvFqLT0ilUaviYyCARRgwp/Zbxy3iO6weconZOz88IOChZJFEI5wjaCfkLNYFLqatmtqKDm1xp6LfJdtaDdo4bLiLoyCkpKFAwRK3fnA4QkP/yrruTd065ldkb6j+6NSaljGJUqb0XqjMTYbh4b7EK0+QQleMQeEIwD3QC2dORDDZCrrA/xGBC1S4e5VOeCy5Ahjrn073QuveeTByFG4vO+S/ccrDp+Z9N0dY5geLwoNpEDn8Kp+QnAjUNiY+EQTCAWY4dViuBjxuBWx5oVQojHtdE9EsV2fk2RswOBU/B5fRE8Kk8NgsDach/wWxM5uxSaqwr4gSlfdPool2rvp4/0TVsiC6uR5LiCeDwG5SuWudAhHlld3jnXHASKYKwWcKlq4E4gcIB8pC8jewbVoBQZJZS47P0Uau/c9Jfv2hePajd55zSHlFqL1QyY8s4v6M0LGd98bcUez0uTVkNGoBa1BlO4qQpTn5037eYtrD3nivfK7LfVs38aqp+5ibRkqSj4lzLCP69y4CcxZcp7zDE6I2DWJ/QmlBohnlf6Hy1FeTUSgpmCw55UDicMmRCYw/lB53B6ndr8bqa9tc9MxTvDE/+0UXefNdH+Pxw086d5b9MW6BfghX60VAyvbmEOI3xaMjwhOArkrpotHPOCozpLr2zzmZS+L3dDVOZ0hucjn6GjJtYUVWit7gTv3cyldEbdQKBmh/IvG2V7Ojt7T97nM1HcpM4zgen5snqcsrZs1KAHKp1W6yMJCqTlDExtQLVIqbSz5qdbnPO9xN2yuX4T09RF6j0rDXypaLjo1bKcaXKnAytXxYaAaXljXnd48WR6eZ2pFQi0hnV9ktKmQRavqV7snAYAtXUJPkgobBqd7iz5KjMPXqiIEF26Unf9aG058+q6rp4ZWVMazGgztTvzesQYm2X/aUWS4MuVjx7yFJy+aJaj1PzkCBYUasmoUGjy0qzwyodkW0okD/ZxG+d20sZ36bBGnwwnvpdphmRbMpJty0TSM8clu8GpWSFp4dVXdZCU1GMByWqMSH5rT1rbadlMzBw1zJCnZbAlxA18ZSyOUQjJ5iXc0bUl+x6Yj9kP6iVfJDLcMA/880/1wKsvdPGNP9XPe57XkrQVpk37VYgHdvdg8sAWHv/zwMweGIhLrBFwa7TPAnPzyO4z51bTZw/c3oPJzLTSC64EAFSoB14/OLRk8rYawVPCOA4eQXkJOvTAxG2PLCiUw6hQaPJWoAfetPxIQa8Xo4Imf6veuLnxV2sdemDfjHz+9YBU31zDCRM/XQNrsICkGSOSVT0qxAMT93/pmwdG7AetB7ZQMtB/0Xng21PsZt11DPBecHX313XNvC3UM5yhSWIxekYwuZaKJF1B9KD0EIk4WTk0KPfgIncSYEeHIwfLjhDIRcLEZNii44wfzZKy01umZTvkB3vvaVfD0uHamES6RybvJS+VaQrxOx5wH95NagpSEXg6gMBJ7ZpC1A/FAVAIBfLoeE6sXEo98p6u7vFvH1FecPblNaJqftJz5dmSrWOz95EH3KXvB1MHBC6T+0JomcJWIT7FQ1ZPBimSOmH45dXzpOSmy30mXE0ePOH05hmsE50OpX61Am95BWx7X3zDuMHxmSyAd5IRvIPu2h3N1xgdYlDI2893ACcanaDwiOsXOoASMqLtVg9ysRlOM6UIYtZNHBdEh9YYKnRSByNDS6ttVq5eIhQBZYMaCBaE2gF3u5HJpUPx9QJ8/DWEICVk18fJDqw2zwXXm/4SbX/eR6o+yvCfII8ypUQXQJ1kBOqgctv7bzpfMO3qvjom+xqHTIj7t2XSrE411Q2r8rh4ihNIDWjQtvMelSgXRKMtBZTH2Ctgm491LtLM5PN+cdL4iSu98hcNXZgRMn8l3ZORTX6pTFMk64HACzeMwUw2+T1A4JKbLvoAtSxc1gyM4oZs+n5vVHB2dicW+wCxnWhqAALPYISKuQDFCfbNEYS0MlkYRBAo8kR0iFBCFDNyzZLwmynchc/eLU9s1XckoRgHf5uC545cZn2+BWAYXKQKUGGC1R037QyTOYqBcpJQImA5tfarZ/kngvZnm/YMneOlPkiqQWOd9P7IRV28/SXGty9SHi0HmxpKa/OmV3Cggcs3cN6Ksz7LQvh9iYUkCUV3DTo701R50jF8skNp77GRUq06aZzuYic4treH174zhbl+VuPHkR+JHNrDVzWFzQQEbrSHYDtLaVoCQeCv9lqZltrwj5c5bQqjfs+N/2t9cPpJTweTXTFh6qxSZH7QeHc1YVlWpu3VlYEPTVN9c04szghv/bh6ea2MGQhcg8EKpQyM7EHgTHtKBjgdWLUQsJjn19GWC3OCWr3x3Gjv6HK871f1pUUNpS8hb/wvFZUFk3tmtUzDHQKvA+uu3NlrJCp3rtoMGTUMMO1qr50xNkMHlTAugW7fGDHdruk0Yd8ORWFjZAulJ4pGoMHsUBU6O/QHroCXxq1OvnahxHtF+kfBudd5l3W8Ap7dnmkFnKKdzdJ8BfzZ4H12+Mfp/ju6d43v3fD+VxZXwMRIgoVFXFZ7pkXcZLKt0tUKeMtwp1nRd3eHTF5yb2tg9Ibqf8IKOIURvOFaWjCtV8BE16VnK2BkaNEu7Ca3r4wVcOc8helZi3f+S1fmV50sSRHqxQo4hRGo4UpfUPX/kS+I4RW/8zccGLDnjXXAgr39a+vYF7gz+gKOrnyBaOXKqFNvHQOnyrrPnfHkuDWLvoC4pmLBnLVnNGetKs4XNBDtPRLT/VnQ6sS/e3/KlS79E3wBhxE8C137AmJ8rme+oD2jiWtVKb7g0dkNAWfm/M1L7/Mp531Uxr964Qs4jEBZKH1BNTpfUOtncNGT8U6B0xe37N9L/l19INQIho0nXDjXfDeCQwQ8NATo/kLlOeHwxikO3E9ZMkIgFsWIEpM1MvubZvXNa703n7dgr8t4ofX6NjRPR16pKkWaYmkIAnvbQlg+pGSktAaB3LZaGX0z+MeRRvFCGoqxoG/T3H1mjb13TvG3bjWzfY76+pLytdCrZVWps7Jv3Hk0ZjF3Y57bqxppfuvLa62MQGB3W9oCbD0EGq2sVX242zZHFIsOD5GCA2uLuhtS8+Sot7f2ee6xv/3in9anFhMaasNK9hEL4igy4ioy1uedBwaIjNJ8R4LAprbaGShLIiB8dJpQMw7vG47eMtXDK6P2kM3zBqWpL4trYt+kgYUg1gUyKxmRIQ6VqmUg05KL7BNLEog5MaVSvFkTehgmnBqkKTdMaZ4Vtb3fRO7BWpHT3swNVy/6qf4eOSmoKtQFTrMYcUpvi1tuAzrL3XVsmzPbuQmBBQeyOxxw7LmPEPXAieJgKcU2smo0UDcPFcrhHcMcbLcFRyKMQ1sTOwaHRHCg/xa21CxYH/5wZI9lH3sF7DQc8/LFy6Qn1E9GEY9hEk1RbAQCb2EUp0MoPiSh6AYC97Wz2TV52JsjW3UoX20Fp5PA91vLoIOWu1NieTOaqr1aFS6ZVMQtM7gk2rjymusmIPAaRsWVC5tsYlTQFEFFK3NdCzIaQrlCCM+6FO5YSlyynnX89uWOiDsr7eZK4OfG1+qEIbSrEHn/OHad9enVA4PgKyUEwQgE2PQypJte+k7adTcenDCk2VffRXLr+p67m77RPWnXHAS6tYNQ3U0ZInmDgHW7/5F2mUm7U/aOMgkT1fCZ7dJ88ZFJVgaskXaJ86+8RgRag3Zph7XTotz33badnpJ2teRHakXa3ehz71hHsbnn8v5Hz5w06neNTdJueW0epDEHRo1Bs7MCWbkXU5aO6++/OGiBX/S++sO+2OiQlbt8+oMzL05UB3Mlho2SnC6ksDD26zEiWaNdhbByrwmF9bu/rB8we+R8+/emL+31ipXbEzMQ1IvCAchww1xsdToXy4lrtjNzxhTenKMbAhd+25Oinu4ME4oFyequVUuU63E5I0VyIUcO3wlbLFBHL4QVM8WDkA+nL9MmX79mdzt03AqftMPzHnsOnGpf3nHZEgRi22LjMpU0LruBwEBlVGOk95Cf2Ru//4bn6KBpaWlWJmbOzdiBnDhlWIB8QjsmyJOVo9yYDvK2K8OO99u81mfNSvMzR8Z9nq/+pr5yaZJMHXIzHHKeVLWZGXIJ7SkNX8JbxVFpwYbLiYPvi4QkcoFCES+VyYRyTB+KqnwvHDBigg0S4ZEWcRUHiXCnQYw9IVE1gDr5BIkMMBFR5cZ8r0FqmoEjZ8rBYtys64ht09Z75tzPaNpg0Oq7FBCSBwtBxwCuY1RdNf7MhOjacwlPguY0CSzs2nnZ30/3L9ZpQtTdlSkhauHKckK03W3nK8WdXoKFfRZHLBv3cwlrCdGxtwtsE/tLQ2ZWrd9tw7MRu1hIiLZ3ZUqIQtDoKCF6efSp7puP7vc/0KrKZrvgxiv1JiGKAEKbzmrlqsOE6I19jV72izrqv/PuWI+H8Ute6VlClMOIDHGo6Dgh2j6+Rp2gzwP4s8S842bT7FP1KCFqxohTVVfc0Zr8eQnRj6tnOPqNdQ/at+S6OPR0aKwOE6LxrkwJ0b7a2WwNEqKXVk541ehOtt+efkfzu0jc/VhIiBJtHAsJ0VhXpoRoXy3NtSYJUfc+aQMNz7/nLXq7rGEzJ6/oSk+IIhDQJkT7KqeX6Z+aEM3m1aw1qstvz11N1yy4M8TbQfcJURMQ2O+KEd3JIZI/COS5/i8hypwQLbhzy806OCp4888n06t14GxhLSFKnH8sEND3utIeuNoCBLa46nFCFIkqdJAQnb+vx4nMX6O5848Uu8e1+umjTwlRSGMFjBrLq1iN4c9vHJEsE6q+vJ3KEt05QCiXCMXO8GcUzr5+g8KR5sKaNB42aOvS1r0CM7w2c6e5uvRxCVrd8/D3kvHu8TrM8LKdSYOGRjbj0Mh0rZAMb90GHWwKGo/32rjUquWq/RPKgLCCM7y9MItHvcodgswfLGYw0/t0IzEFoLcZ3rsuTOnGqy445DX1HvKfrx4aXxoXEjKlo3Sh/TkjT3YgJ04ZFiB/4MoE+Q3lKK/1R2Z4iRlDlQwvcVmqkuElBtMqGV7iVFLJ8BJVrnmGd9Ci2Dqfua/8557/KyQzZbE5Cxleczp1WTye4VW38wVwWYcnhzafHKl+knzdI7uI/6M+JqUOeoYSVUN/8i1M0A+X8UPYsUzE96T4JOU5AuSPUXd1IBitsl6fhDvVZ/6r91GGscR5aQ0CDeFiVyoP9kCYSmvTqfTX5G0r6zkb8Hb2t8otkAWpH2ZUg4//UdekSZmaLP0mhQJLhTR6K/0AlbpKpdR7GuQZp60S+gbufzZ33bdUo8c0b0RO9JeKyjKlxL6LGppSWpXZgkC/DlgOT6myOqwZTacKNJpnFo4+GXXlb/+M1St8302bG6piNLvMnpUo9ujhu/N9l1YvJkWuUzGa/udn8oOK73pldTDvXPf3p+MqRnP5Doem7n2Kg2ffyT5/59xyExWjeW5I0aW1YVN9CywHBPEs91lDIkNM5PuraKFodHHI9Jt11wXVfzIUElXHRLc85stnvzYKnNY3bEMemJQLiYww0bonU5YFb9nG3dx7lKu9IuQAJDLGRKdODO7gV6+9z9zsb95jraqNhUQ1MFHDR4LZttGTg+a+ujDP1Y7/BRKZYKJH/i7/nD0Qyt2asysrqcsRDiQyxUSd/v385WvRZe+d71ssTBgwJAoSmWGia++yH2/ZPC5w2pNFS3eveVUFEtXERDYHH98sLpjHm9Cuf5WibYsjIFEtTOTVd9yFOoWPAtdfGtF9/+wg2CeZY6I6HW3cR36+6F0oWtVp1NxV9yBRbUwUZz/4U+i4W96LnnccO3jNtqmQqA4mSn7S1rSem3Fg5qvrS7c2awBXOOtioovnEqoletTi5ri2+NQ3+dVrSFQPE/XNmeZ3pmkT3uLLB4PcMrrDovqYKK+66a/vdWRB2WeDQztOudoeEjXARG/qPMtyq5vFX/PPlaCrXyx/QyILTBQaN8PH8t3nwOwRE/mXooo2QCJLTDTshnXUxsuZngfWDuf/0+XOeUhkhYls7c4v6rVgoe++v9Y0HzRrTR4kaoiJLo/LzBwQ3tZnXVurjItdLz6CRI3wEdV6UUlq7W2+uauHTqnlVG0JJGqMifrVMqx+sskev/XxY39/a3T+PSRqgolcXpu71x8xx2dmisNImaJDCiSyxkS/hmyca37ygV+O6/BzvT9Zv4VENphovDw5Zu343gGzbLZ/2HGkV09IZIuj8WxD/pS7F7lzu5ze0aUQvAiJOJgIvHS9yDf3HT/PaljAuO+rrCBRU0w0/KtBySP3QM8V10f0HlR313hIZIeJ7A8fG3/GvAd/1sXkvzwjDw+DRM0w0ZPzv8626dA0cOvrKenXX/6zChI1x0QFKzdtqjos0nv9w+Ur2vAizkKiFphoXuLF/oe61fTNne0x1OBs71OkeMUeoIlX1hQZhc+zkARtHDfgwamQku8sxCt16Sxlg9g9m3OPn/LO2/B49JkmY/LVD/rxHiUTS2MouojQ1aPtsW9wsN5E0CIf3pqYIBCLIVuIdUTQsJUI0U5SPhr5DCJMoGmMXsIDXnUqgs081YZMLghc6aRdQ5HSXkXog1C+279Hf1gO8N4JTu2tmLbm5/xPLLYqYvsYya884AUMUAzlRjArELjXSasTQzqECaGhgZyOHSOMlibIpAoRkpiHnk8kRg6awccJRwCtBQXwoabRlCg61JXtfMixD1qV3zLIbVaTi+pxjPJ3yHFMqYj1zAYE1xVGuE510otzLqqU95wLJ2yixZSqC9lKmyAYJuRAcRBcMh4iUAhRQ0DdoLGbecqCXpYB839ELclKuz+ckNTDbktxHj0uYV17QSA62L0otSdEBjuJbKAlcE17CeWJIuiTeGFdSASSupfHudCsYU2eBC2/kXHaevnN1upg4fckg6WU6AKsK4xgQUMd8z/1aAt/tlWHzd1am7dnmfh9l7HG6iVec2+s3RsnUCiJS4wn+yEjGoz3VFF+FfdEApgnFQ2BAd2AEyuITpTKIWMjlcQhG3XFyA84Yz+EyRWcaIGEM0TIUSTJZGIRpKEhUkgIfR+9ZZIE/iq811cCnzwmRs5eRi46c8B4gSROiOi3X/AAjgyv1CEsJWlcnFilxxb0GbjPVgI0CDT0jcSFAiNspDFB/ICmCn/KA7p2LkK611HUJH1BoElnXfT1G7dz5MMdO6y8V+1Y/Kh1QJVAFp0l0QKV11m+5AGdYYRmUk4JSxBw7ayVs7RTG4/YMd9IkzsUMOijlJDJfhaJEpN7cHc/7yPL7dL4hXqun2ZY4NdZNxQQKvaMqEDjppLrm6qnJmtz/FZ7fiwH5pO1QWaxurZEClW74Ojq7MoZx2nr7NqS+gjOh5YPvq79yc1LXSWJehqrvp3UJFh5Iwr2XalMF6qry6g648pRXdnhDBPJxhptaSFAu6rCh2SLYmHzjnoBSvWcG1klp7FXoddqm6bGT44ZqJ+WrGX7lPIqJRxErQx1iVGMWBmtKJH2EbCzghAZIUT9ohbApJv2TE25dyQkVeCzf/fyoep9ZYywG5OXabhAF+DYM4LTpLN2rEgH1EuVenBt0HluHrQlEUzjFhrsKfw9dedB9SWKkr9DXqKUinSBUF1GhKA5jcVt9enitlOLBIE/O1n6phXYGL1ulqL+XsZI/8Nwr0DNEwc89fajWCQMrRBjob9CcVeyao9OyNhi4xWOvbDQbaxGgRMxjUr93OQoGpdoinF1ENjkDWF8l5K+FQoCM7110Ke0r2/ACIHb2KCcEM9Dz71lWeVp70uIlCziZcAWbwVv4oRfpvLH0WB5IyVjENjgTUvKdQaB5d6UvUnpHLEVAhA+LhxjRHKU70ftbG0Do+rlNF3mtfyUwqHX5ac71KelF/5l8rQsFZUFGDH/xwJgCxgBg0ZUpQRRqM+AP+MG0P0pJgVVOHOM8kxTRJcMVvWNQUHYhduvAuda3x0WkbKmbV2+BLKUkDK8R8nk0BJc5V7Vubxwx6iW5QuACao9uj97XOtAG96etfzkWdwxjVlQ7SRG1Y6uJNVSxcezerDcCzep6PiCLEf34AOLat0xyXi/u/J64fbHbNIWSlZSHDLFMMfYgM4x8q5a3hvhUei5sd9Aq2m9DqgvVuvDzJREOPXpJYqNFcqFEBQUZwHQbRpwAaUJEOQoPwa5TUzpbZDFIXoyN5xYgneEaeQRidXDsh+YpA7KT2kKejUQGNa1CFlpUOwraAcCA7qW9/RubqAKKHC6QSoTyuFoA95ugY5xBbxfDj9aQY7FwQo4Gy0dKYyhdiIXX/WObzw5339J/9oDei2u003dxvRCjmQm2xjselk2prPzZYOlNxM8C+593yWQ1fMur40xBAERDLMBj4ql3wCBubwp4RYq6ldmt6KlEoUwOgkZHsgJ8pRYrnxxsb3Bx3u8JYl3/3E5eOw9Ye+Q8r7k5a+akHWT0B2DrT8lbH0Q2DCTYEFnEs7Uavaprbs0KP3j+wDnK+O91TcPhAllYkG0ENmWR2EL6AJmJ/x7MHtXobLbEx3kI0WJ8RwptEyRa24JiGQBhuckb3JQE2vRDdWtK2031F4gYF3uuW8BOzUFvjdUuT2WEoBOF9KXdkm3C9j1UXI95aTfMvXwGbkROXxGL5c1nYnkCBa6fLaFkVtOmZdpCgIOXWnDZw2Ra6xETq421OChRQnfgomLC8DLDb2zlq0+tTU+1lQNPjNsgFCXdNSlrM9iCC1rRrTqda3QAAt/UBJdvxkTXR8OcuOEcopdGeU13BaIg4QVC90CWlQno6qmbltNcEzlmSTl1esQEJ0F8DE65MB5ODILtEqEWQUj2CKbxJDRjw196s3BNXIKM1bY9uBOnnJRYJfUs5BQmIDfiqIwgVzWBRTWjFDUUzoqS72ndxOtJTv0bptTRTUDQvMDMqs8abg7cuwzFujdH7ow0btfdcEht9J7yIkUPXYgz70dNu/781Sf7L3Cz3n89BYsQG7UjQny38pR3pA1cqg5DnkFkEMpuJw4OZSCy4mTQym4nDg5lILLiZNDKbicODmUgsuJk0MpuJw4OdTJcu3ODudFvnvGv4q3req8kUR5gwcvdf9rAguUBcpbIzr92wUcc7q31cRntUHMkOuvaqvrvx6a7FfrQk4OyqvTzDY7H5EkBikO4G3SZXjvdK0O6yMyX8t8RBI4VB/SogXJXLg+cJMyd+0GAonalfkbK88owNqho73Q6XlB24eaW879tNn7UMHk3/dmvX7I4lEFxDJeeQ1SDRDI7oy53WKSQbICgYnkgj8TVg2UlAhVrChRmvA7+qDAZZRv/tRHmwIDj7dnkRYxITL488mCUT5rpVP8MnnJR1hAKZERJWFn7boktFGeSYBMNgQzlZMJlNwz+lKJGe9O7ZmTd3mtapqWc7JD/XaVWc/tgQ0i6oJcFAhkalnPbaWsHsIQofDESBNg5hPkgdRsEyU4jSJvOzdaZeY3d4uZ+3Trsfv1oWoJgTSOEaRELeu6LUgnN5QOGaSwSG+gxOab5sRsvumz+cSmHLsffZ5X/nENEDpDGdEZrKzpNqZzjHp4nCRxn4cOjpO82ZnpOMkj2rk6zcq0Q6tMK+r4d0OfJR2TBEnV8211dJwk0cSxsLP9ememcxLPaufrNDlOUnSDc8U1xM9zfvuc6FPj7NXXR+wcJ8l2SGCGjBoGmHZr6ezKLqG5Hbj0fuj2t565p740bPa7T+dKPU4SGSO0x0keUdqhJnR2CHQ469Jp4oPAfJ9lHxI7NSTloRMEMg6ap6HIl9OF5g7o9/BqD7IvRcCRCEfCl4RyUTTmIDUyS8Q9ZgxPSJUpVxFriutDHmDILUK6cFHE5BEg8MxTK0NVCylDocld6HEo3/LV4aRV5/26cidFeN30HZxACMORG5BDJPRyWXOOuN2uvHPuKQ+oBsOzgXLOWYPAN0+t2CQ10efBxgR1tjtje+Z6+0n+GxsGdQueFnWD0E4D+T65+oddLwufu18c8n9uecJLm1aTd1qe5cMCPu89mfCBhk9lMAyMEeLGCBSIrgDxD5k2wsTFrRkhkMcJE5mUBp7bd+SIWwqY3WFNvM/Ys+rupDr6fbLSsOusG0tIK3cYtXJJr7RSfAjXilbuyxwxeDJhDGZ8qc8+cQrkJqwe4j1zfSQ/MiiCMJuCkO+TFYNdZ10xg0HUnMBpRvJ6NREESjy1W5A1VmKALCzEorLwMDgcM6Pp8mCv5S17vysq2DFInVULojcgs2pxgS4QeebJhMh1T9yvW9P59S3ZASX9unTmp5f8TDQ+elt90yP2i5qTYboqVxjqDpwzMl4UHQ+FlfDeQoECWumqsGIw96/Z4oO4XZzqecljEr2uBU+00BPjiZLZL54gsIrs17WsgDfBQg3Y2Ysk0eKkGHhbLgd9Emp2pMQgnTt1DP9Qp8XjPT069FcffHSBjVJQ0c7fGAS2whi6UnE0ABsEQ60sVtdgbER5oSNKdaMWzAdSoPmBeFFcPPzfpTElJyWYumMn0Z+rDyX0Z8hDCbvO+mQOxACzogRsEAIYNplt9L5wRRxNmhSuqnDKHKTEMgcLlatJnkyVqzFKzG3pMA/e5XP+FHAMTO3bsIvotX8dtVetFZQkThTJxKJoZFuY5m1SGwdB8QDknhKhb4o5CWp30chOEhtkMD0WSRUEuRbdiF+DWDdicuLGDQSughTtUXF/QtEeFf4lYntUuvanVWjkbLY/pbNN1j4iOWRzlL3+1fVFqZ/iL6EHO33w8FqfuLRB5ChDw//QRpnYNPGW29TzT5Ifh+Ty1l2qdW7KKhbaKL8EsTbKlASd+2ARofUoE0g24cJoKXIEr+Yojf/bMWvvTDfP9FSJLLXOU/Xu91V4ZJR4ZaLUZ/bqbclx1QPmX17kOPOiWblJX02QYc2A0mmQ1FqSke2CtoSGAyMNACKy3iu96zQyYr5SJZrgrtMQUpg95fxh9pTYVaiC7GkMl8meBnP/Z08x/VQr6cNf3eZuSPaIjq9eHBowngV7SuwWxYKlGMJlshRRXF3b06t9d63vHsnz3uluydmzLDeaBXva/faVHZ2O9Q3Y0+Vdo/vZq7eygFIwI0peXB3aU6IPrXR7iowYWnsKIYXZ06Z6vyYgTid2yGwdqjT8MAOUee387Bm/5eqMMBaWBBwu05LASgm5HWtktto45BVAZqNoxYebeopWfDiZjaIVH05mo2jFh5PZKFrx4WQ2ilZ8OJnN7tHbfTVNvoEHbHY+H/rC64EKma34r/GRP16OCMp5P2NQtm/bKSqdDnkNDgdd+3bYc3ejWq53T9qPJPHckOor5QZdQus/FnhuzVgbGqYVODT+WxNMio6QONxEpgBJJwZ0OiH2XGRBJ83pdJK7+2GfjKdf+Xt379i7ddgjQiubUIFEKCZ3BKYzh45cjgz+BtYWBm4Ty5FIE4VoSyL4JCf0bB3qJB+xaSTFo2hiI03Do+VSsTgM9nPwxdKNosU9CPYzrN1X+6F1vHwy+oyxPMqtS3sYuXGkQiiPgB4f/9kWXtKkIWKY4QU9D9IuKEaUiL07FJfAtZHHqQUElRjSmd0jPGB8D8jsdgKB1AzQJEggjxNJAoWxam7TFL0cJoqLV7teA70eIZWpXlW33W36HeGljOtRZI6AGCqHdxsmitCnMsKfimpCyQUj+ZIYuFkXDm+VGvBFuGCjcgmJ8GFajfKSWTjci0IgBuEOUiruC+npr/y7QW+5QKb8DjZUW+i9Mye2MGUpwUcc/yx48109mLz55h64N7fXe8yJvWH1N6naknE7QNNuOOYOrLnJimywT9H0F3eTFE1/cTdJ0fQXd5MUTX/xCOqemdPA2Q41+QVWE9aONXn0l+YN9ontglnwoI506qoRnjOiIGmo1+a/vwo9OGs/qne+w2qCQdC/5JA91LxhYCO8mijhhMiEEt9ATgJ2D81qhcS2yIyPRW7IR/iApuP/MQ+w9StCGNTARVLWJhwE3viSqodMDAprdPzijSnh7gJJcAfPeIEE8mSUL57RYqJ71zUR/H0nB3p/uHL6s3qt0Au9A7lWiAtYX8c+5wHWMCRr6DgV9fwqhVNhGA1Bq7QM27Zt+61NH0COumLg1lNJYoEcKUGK4RiFUjfBsVbNo6yfBWbVGTN+Xo+ORwj9VbGbUPRXxSW60E4NRu389tUD7UDW6Lc2xCNb7wSRAuloHK2mJtyEUJ8suyHAYlZg14Dc5TdqSo3Oqrc9MUbvSJHfLZXoQjmffZmU80YflAPrR1U51cpQjgc3Af5JRCfQ4yigrwol0cloP8ZuHKlMMBxu39gW+VvpJ6hnlOWgu99HZ7cMmn/Q45t8wpAQ9S3uESr3J29xV5PqQnmPGJV3o3KUp0GPTYMyNNitVIOKeJEkWQJFupD6IHVJpBJYddB/iaUjESH8V1dYlCAYhV6g1uOaJBfLWyn8A7t7rfmyZM0tQqO0eCrGNHZZF5o7x6i5o5WuOfhLcLFFKxZNXTRVLZLEMRvCv4JF1o0CYwOmWV5Yktqj8VZ1Q0gbM5VKWNfIIBCNIeBlxUlSWKVADCEWp7aki1MbGqSEH9lXEnLIePMze/cUQhEPPdSHEyoXjhAJR6qHqTCmdKQ3By7ckEihkvFBesvGCaUJwkR5MkeG3lBhzkeJXnxJmFCCLVLog1fiwR1Mz0ouOKrLa/WC/iWTyhPRMwrxT2mMvSUICGDsF1AWIiNBIMCPlhBHueT1xbFB9lQiz6hRRD9vTX0PjzWzPFdtsf34pW7DroRztbG7UpyrjUvKWgzfEgbtcK5WzXfm6Lf/7JoqaVrexXBDEBgEI+dJaUfagkCkn1Yc+AYRKiEMRzpCKJeLaI6zaPt6fk+3Yn7QomPWvXZx2/8s/xQmYEW0ESxgFcCIFbdiVwl4stIIW3LBH4KDnXv5934bC7GID7/Ic+X9NkR8G9GrGuMLA/yj8P+bqYY96t9QLrdb0Zmx//Xn/0/9+YnnHVVYf/5tfkz9+bPJtpOF/vy76tg2XnDyQfCiv3dPTncqUT+op3wb0dm2kS95wBY/pnbmBWQbqYv+/J9mXptWV2rrmerdbH7rO6Y5ld6fP48RlezKyZlQrh202xPEXn/+BieajvrVsCt3u/eBE7UjH5npTX/+TEbVjasc1VV4f37Ddr18pzW9zZ3pUiflYWzH+5Xcnx+xMrQN1iErU2H9+bnjc/66Unev3zp+QxG4rk01PejPn8cITrZfBfbnj7pw4e69mBqBKxpvcb8k+ZCtD50uIIQyGRGC5jQWt7Wmi9u8ua1a/+52lbvmvs3ay0veu6m3GED298mkYsijk2M2YxqcO5SWSESl38faZECIy6VJcfFQDKcQIqkabdo8EM+ApH1ackMEFaGm+EJLSzN/CF8BCCddiPgmg8Bjfnn3XNUvfSzoKoYFNdk39H6nOwuzAtfe3XL29b1/L5f/WC9CCLWsMK7j6B5XfbPeHf5HFLm+3M3K83iACYyeLUjlcayhq/5ahVBm6PSNEcbJhdTxZe8DRr3vW3QI3hzztvjg8mvqR69U90K+SLF5Cr3O+uyE3v8Ln+n93/IrO1hSjkwtAiX4kUXSGFE0Q9sb39zCD9bhL/xnXqvT+eKRZqfVxyp+A/JYVUp0oYzHjMq4WTnKIIY/gDYVC+cAiTQRcl+CaDh36ujaDVqyQiuLhDactt2i46XymDacdt0Uw+WJyF+oo9UfVdxc3Pc89C2o6dlpXfd3/dT9GvwD4YnJYoqjMUtFulDWeUZlHdOLmQPfSqtotUFpoluSJB+iYJhBVS98XznzkafPgs6Hbfq0E3Ysz1K5nOpITQNRQw7vAr1ICjOmg+t/8LWLUjFLzhBt/bzwdVWCvyB4Xq1OUU8WPHau1GUvDEAxHwPgJgUAsGnRKhLFXRl9/4lFLg/98j+neW2abHxVartEVKn7gGEArjEB0KuIjweabf4wPg7x6PAK4+NM82fi4/T21zUfJ6RZwcbkr0Xe2cMH5O16HBCvB3ycKf5M1c3x/npAKli4cGEF8HEmHbzRLT3pNH/PqWE/p558vVEv+DhJjNoZpg/aqRA+Tu2CC4IxIwx529+aDWnUb6SPXvBxBIzK6a0PygEqk4/zxrFvovndvn7zvwzrImo266Ne8XGCGJUHVo7y9JOP83Llw8Z96l0Kym+aPz3+tfvtSubjdGLUnEula06nfJy1var17uMr99uwwu5c2sHZm/SCj4PEELR8HMgQYnGq0/8HPs6bZxvyp9y9yJ3b5fSOLoXgxUrm45zzZ+Lj7CKHtDrh40TuyjLxeATy182qvrmVW/wn1vk4xLU5CxyTM/5MHJO/yIlSlvg4/9xuHRhpuMd70cfh4JoxxqNY5+MQbQQLWO1ixGpjxdrcyubjONOZseGHRK1FwevAXQdDxC+e9iOck9czCd4g6SsXyOLJ20i1KF809xIpZPAWMWU1J9kJ3UrKEcDt9OLgX6BusHnpepFv7jt+ntWwgHHfV1nRPh+5kqMqJI2/GuGQCQtR3W9FMSqJm5s0HJXKu1HwadrCPbssQPgf9VHp2u8Zr4urZ1HNcKEYUpgwhg/Z9VH47RC1oqp0oVNl/uwZSW/9v/rOH26hyJ3ahlDW8IFJA4lkT0QbVqNf4Cgga4ceAZikgF09cnxVvFQcA3eog6lQscjnkDAgURCn0Mj2EreGVQ+URg8Txii/RPXo5DQWel1Tk/CVB2TCe/uqUpKZokAgvhtFRxoYIjh+pehIA/9D7EgTPPl+9/CiN56TzmxPNf4QcpXYkWZi72Xjb8v6+y04nL/w+YLp3XE5vtPuP3esIf4wRccaOk2bwlujMTVSaqtZ+g3fUS2qBRzoP//UcsX2LuXRFvvB3A8ekA7rNY/S1LcAgTHdKuUsPlP4yLtBCugdJHGlbq/078iSI8W1c9hYisY5dLqq61M62yBHkJgkp3bYFo5DjQd5zfdeOCqjRa/wqb0YVWYEoneiaP+KCXShNDmj0uIrVmn4msggEEQNKvyV8cp5j+gGn6N0Ts7OCzsNWCRRCOUI2wj6CTWDSakrj1lZB02FbrxtfWfXvhL6PoWoK6OgpETBELFydz5ASPLDv+pK3j3tWmb7o//o3piUOpBRqRHdSO2PGHvKY4NdiDafoASP2AOCcaAbwJaOfHIBcpX1IR4DonbpMJfq8G8ZMsQxl+5K59J7PnkQYiQ+77t0z8Gq43c2TVfnCIbHi2ITOfBRm5of89s4JDYWDsEEYjF2IqUIPksM7mesWSGEeCYb3SNRbOfXFDk7ELgHHz0ZwaPy1CAIHCj3Kb41kQNKobmqgB+Y8kV3/+x+ye7vLf4rJp7yzh53XT1/a0DzimUudIjnUpd3zjUHgTswVgu4VDVwJxC4RD63l5E9g2pQiowS6nSOWbTJV4fj3nnPeqTu+WT3hpRai9UMmPLOL+jNixjf/EDFnsFLk1ZDRqAWtQZTuKkKU5+djTtOOn2pFh2yYoHRUPHcHrPVxyX87YqCv5AR/rWVAz+JKVPes4zRGQGzPqE3odQI8VDS/2gpyquREMwUHPakcjhhyITAHE5b2u05pza/m2lv7TNT8c7wxD9t1N1nTbT/DwfN/GnewLQF+gV4oR8tFcOrW5jDCB+JDE8IjgK5q2YLR6n1m5ZJXnX5K/i/+I3PfVjA8Hzkg3LUxJqiCq3V5fBu2lxKZ9QNBMJ8y79slO3p7Ow9eZ/PRHGTOs8EpufLamTK2rJRg0andFqtjyQokJYzMLUB1SKl0jhnOzv3WmXolfvAK+DCzwOe6vPDl4qGi14ty5kmdzqwclVsCJiWN+Z1hxdPppfXmVqBgAzW9UlKmwZZvFi92DkNAGrrEnyQUNg0Ot1Z8lVmHrxQESG6dKVUX+bYgsBuk+97LjwaFvHR6N+FzOsRY2yW/acVSVLR8QVZju7BBxbVumOS8X43Cwrtz6hQaPLSrPDKh2RbSiRXnkj2+LY/m5/5es7tdsX/NtIMybZkJNuWieTW5hH7j4Q68pc+BnZtb3Ww3AdlQ0j6MSLZ3Ze0ttOymZg5apghT8tgS4gb+MpYHKMQks1LuKNrS/Y9MB+zH9RLvkhkuGEeuN2f6oFPV92/to3tbzDTvVn6v3nTD1eIBx7LZ/LAA/j/88DMHrjOxDdF7i2WeW6ecdbx+U+7K/rsgVP4TGZmuF5QugGgQj3wq/pHC3b9fgUeuDaan23bK16HHpi47ZEFhcYxKhSavBXogXfMdubyfp4K2LQkusPVfsvv6NADt1xZPercQEnI1h/g5cLLEX1ZQDKcEUk+v0I8MHH/l755YMR+0HrgAUoGuhudB749xW7WXccA7wVXd39d18zbQj3DGZokFqMHAZNrqUjSFURPQw+RiJOVQ4NyDy5yJwF2PjhyeuwIgVwkTEyGLTrO+NEsKXvo/qaUTrdzuJMLhhVYJO9sSPfI5L3kpTJNIX7HA6xhiE1BKgJPBxByrVo1hagfigOgEArk0fGcWLmUeuT1myX6bDTT2qcgOeVj6+MN15VnS7aOzd5HHtCYT8s/qQMCdfiktKyWKWwV4lM8ZPVkkCKpE4YDQu7WfpcwLWTqe9MbyblbXrFOdDqU+tUKvOUVsO198Q3jBsdnsgCeESN4P/20O3+vMTrEoJC3n+8ATjQ6QeER1y90ACVkRNutHuRiM5xmShHErJs4LogOrTFU6KQORoaWVtusXL1EKALKBjUQLAi1A+52I5NLh+LrBfiMawhB6oPVe24/tvLCCu8J3U+cya9yrLX6KMN/gjzKlBJdAGXECNRP5bb39nS+YNrVfXVM9jUOmRD3b8ukWZ1qqhtW5ZnwFMeMGtCgbec9KlEuiEZbCijPqlfANh/rXKSZyZ945Xjy68m2/JU9+np3mTwsn+7JyCa/VKYpkvVAoI0PxmAmm/weIGDho4s+QFXa2bh6/TzoszynsM/EZqFs9gFiO9HUAARawQgVcwGKY+qbIwhpZbIwiCBQ5InoEKGEaNP54SYWrsFeBQXjN9w5vnEaoRgHf5uC545cZn2+BWAYXKQKUGGCFcdHO8NkjmKgnCSUCGxLTprRulFjn3XtxrQ8muOtvrStBo110vsjF3Xx9haMb2/mg1ubDnTW5k2v4EADl2/gvBVnfZaF8PsSC0kSiu4adHamqfI4Y/hkh9LeYyOlWnXSCPnmvzhtzv+x9x1wTWRd36OioKDYsKwt9o4g9gqZJLRQBMSCihECREMSExARey/YGyL2rliwo4u69q6r7q66uvay9l5WXb+5U0Jm5s6QLBOI7/fs89t9dE4ymfmfc0+7557T1m/Xrw9uVo3Z7Ml+JLZrD66aC1spFKkOUmZnoapFjiIl2B3H+VRLWfDjeS6bXU33JzYNypKOHXX+7slnskn0qlJ8fXBYdxoxLy3z29u9lSedWijf0NhhkXhd7TL51TJOKPITACsY6hg1QJGy3tAKcM4CGxws/vVVruzDDqqkFtLF79quL677QF9fJY22hH3wP5eUF0wbXYcEd7txRrr/+JTrLfqvchMAphK8MH21UBk7EUKljI3nOjfGTLebu0yE10M9SRnZBrVEUTg0pB5q838oAi6eXjr52prbknlXN99SbHeQWjkC/l3GFwEfsswdMj8CrlL/Sep0F4n3wraRv+ju3TkuYATM9CQECOKuyPiCuNOyAouAM47+GvNuaBP57rf77r/e6rXjR4iAD/GCt9tCDWZxBMw0XTYWAeOixRnYnbbQ0RQmAvZ06f1k49efgpa1zRravN11f5uIgA/xArXb6JO2/T9kCx45b5xXsvNW7z1HFiTE3uq0xMq2IIXXFiitZQvCshY1Vkl3e+880PTZmmWOgwS0BcyYSgB1lsyrzrQFZwvGZj5LqTlJEnAgc4LWATWU+BFsgZIXvAhr2wKmf25jtiCZV8VpC8UWrCzpbF98awnxvJS/Ho/TiXrbhC1Q8gIVYbQF7bhsQZlvgSfujWouT13SuE+4/ksFeiwYCJQn2Dg3/zRCwzAgGgrifKFxGDg4OCUC/ZQ1QxRqVbQqIdkstX8mxb5NjecV/FYvSnKR1Kn8D8fTsSNVI8lcLIujyHQJhuVtaEVKUxSJl1ik9J3Aj+ON4pUcJcatoroEH7pXzmfD+OTqSfsYpy7soK9FXM1rl7ry1EshK1M2yjIePVg3bF+R6fnVVvYoMk3CuQFbAYfGIm1VEXTbFqliCPFQGUSAW1CMvox986SquId022m/2dXuvLvJaKgNmCxTK2IhGXETmuDrri0JiA6qvrujyBiJZQqqMhMQX2KZwCsOl5Y6rB0cIlt3O+tDfHZpL7rqJr/JAQuDbA1kkniRYYpK0TyQaeyFnxNLVKhF0blUqlkTMQwTpAY5thuW1jqc3irQXT6m2IjBfjsm0WeUmv4eOyloSrQGTlG8OPWSUJq7PZfm7jSi2ZmdXvHytTlzWuc06raf4fWARHGgFnKMrBgH1PWClXpwYlhEnrYQaZSxRGviRoFBYSLsz8rG5jnrHzq6bTq5+jfPva2U24qVbTUW/mQQf4ykmIviTyhyEKCYiqF4m4WiB4pkWaazS4vJN8eP6kBf7XiReVnLff6Rbl40fN247+Pq0V6tiBe7qMgrT+eSqePyq66ro0gOQMXNC6hspldQG0fFInVdBlMaSr1BCVZditcIKC4OUYumjTlZ1u+A9uKwvl9GNKcXDBFdhdjnx8nrgi+vriQEn6AQBOIQkMurw49atDt/RqkmvTe18936duKMlSMDx/I8n0BFu84oUlaKoboX6iJJUeSV5H9Fu/xFu9U9hjZ7k9ZGmu56Ie13xafnghXtMtdffpUIFoOWkZLttKDnvu2kNlq0a2F9pEVFu7E3vk/Yc2ubPDNgZ8s5TbqUErJoN786D+PYPxI+jmGrswCrcrVH/TdXvn1SMnbSohbpioiDVqzKPZdUZGE1yQ7Jupq1He4dtesrgOw/5EXyhqRAqnI7u6/944PTKs+sYJ/5U67OsrOpqtxupIKAB4V9cXEjTWxHLhMriq27e/L0KeK5RzLliz5n0yegFQ9RqhXJdNNqIcoVvERJKr1SpAd3IoMF+KhXRsQMeRD2cPo8dfKrX0Z1//p4SMDCl9Mj53i7T8mvXDZGkfaUXI5myWVnFHE3Qt7J5iGvFKdDtkkN4nFj/nXU341ChYGcuWQEgLytlA/yFlIK8s5ckLuvDjkWsXWDbP1q5zOHR75fQH9Tb702UUeH3ImCXKw1bWaGXyJ6SoNLVKs4GBdqeoliwX1xl0SvMBjitDqdUk/yw1DUV0IBxkywYSTK02JGcRiJMhpM3xMjFUPgySeMZEeSmCx38JVE0jgDPGeosDQ4dHTUGeeuvrMuJv/i2f3QIAiEbGFh8BiheEywq8uPmRA9fiftVelTAUFz63n7uny8E2bVhOg7MV9C9IpY4IToHvmETu0XbQlanFM1ULNheQfBEqKeyBxNyQS5f9bBYI+MMWJnARKib8R8CVEMGislRDV3VcpRjzV+6XPrFd3vPLK+zSREcUA401mPxVZMiO5/1OlMkPqGbNw09zd/ucV1sLGE6F+8yDBFxcoJUd+NQ+qHj/zgv2lD/LrPAy8/s6GE6GlenA6JKUPb9cdLiLouW938z5JXvTOL13xeul73dlZMiDZA+RKiVVChE6IN5nSc8/rxrKBdJ+ruP5ctqyBAQpSp4wRIiNZD+RKiGCqCJ0TLZVW4qR1eRpolWxJ02vnZxEJPiOIQcCZEMQjI5eX5oyZEL4lbZ3W9G41mT17dpHaDeyesnxAthSLDULLQne0i+aFIb/R/CVH+hOj3IyW21fxaz3Oi77ENNbo6rhMsIcpcfwIUoA9FOQeu1kcRDWrDCVHcq7BCQjR16/DzK+4G+exAsx60XLm7my0lRDGORfNyrHfBcox6foewZJ3S9OXrmITorv5KvUapdgWfMbh6+0SG4s2FzWk8bOfewr1NAWZ4a1TrqvpXNTVwUoLHQM2xqSWtmOEVOpOGiUYwr2jI0ALJ8LYYN7nyu22Z4oWf2laJfvdvHm24CjjDG05qPHiUOwBfP6TP4GXz6UZmCsBmM7zpYr504xxjFCS2ech7zV63PTm2hP+CS4sbzbjoNEIYyJlLRgDIl6B8kM83Sjn6Q2Z4mRlDkwwvMyw1yfAynWmTDC9zKZlkeJksNz/DK3Y5FPDb50Oee38q43bjZIMkATK8Ei52Vbo7XVK+wwV0Ret7B7eeTJLQfqvi4T3s/8EHpZQjpijB/F/YTUoRH8/zx8jhTMy3hX4W6nzDPggFnam+8gaCxQP4p/6rLTI6tcxVWg1FRgHFOFkM7BHJYCkXg/+dsH11BVc78e4+VdLX6gLW0JOkvsZ/6GwtlSdbTb4KYaYJlYOFJp+AMc6EDGXX4E927+60kXuu+n1Ij8jye0ZxvRY792tCy0u/MpsxmqlfOTlXC0WWe5OJPSPnZIJp0mYFqEnXT92Y3Xl5utfyQX+/re56/YSJJlW5+9RX13nhl7a8glSTVe2SiSatcLLtNanLZWnana07nj+55GGiSa+Nn3jjt6V7AzceqlTJNaNMWRNNGjns+zLvx9OlWYdWnm57JfMPjFScJHn/e2KRatiroNSr5TcGVLw3ECOVoG7YdoF+9hN7+bTeIZkZaGI6RrInSRvvTVkRuG2719YeQ90aGIJyMJIDSULuT9Br5drAnEH9c2bufPgnRipJvfL3bse+T9vuefBBhbWf/aLXY6RSJOmAbOCxYZ47JQfqbJp12T++EUZyJEnVxy6ulP1dFbAnsWn89WJ+KozkRJL6Rc2XxTwpIl8zePyRo/N+OoaRSpOk154x3SakV/ccfebZoLe9m+/GSGVIUsljSdtbJff1WzZTsuXfoX47MJIzSXp/bufVdbHfpZPTa4++WPteF4xUliRtOjS2+Om6iZKfZw0+vvL0nxMwUjmS9O/Ohxuf3BziPVudHdxX4fweI5UnSaNH671bvGoasKR7kUOilMA4jFSBJHXxvPy8dcOnvhOePP1j0lv7bRipIknqeFXeds9PdeSLo24fKz3rrxIYyYUkPS33YKZH+Zm+6z9eDrjyofJ3jFSJJIn+WtxFluIq3njoYZdnp3wHYaTKJGn4loaltFnXPFd+ju/XpV+zZxipCklau77h+7jB1aWLT3fptyJhfnGMVJUk1fllwqSbkr/E2Xt/Wzlrzn0gUT+RpH+u93q16I8Bsv0Xah6fP7iuHCNVI0nz1nul+zxwk2W/fGCI63rgMEaqTpLcfjk3rqM/xsrMtolfNzUFYlODEuxLT65etO8i3lDi3xHzNy8fipFqkqTQUIP8ffsy4qnZq476XBsFxKYWJaIZiPJT0+4BC5ueqdts1qd1GElEkpbUnLk8K+WFfGPRZjuy767fipFqk6SyS1xnHWw+V75jtajvxF2vh2CkOiQpU+nzxr/6H/K0qUET3n0uMRoj1SVJJxOnJP+1pj069sLTwNY7spIwUj2StGKl//BW7exk00p9etKranowy1Opj3B4KkuKFW15y76/ZGziO7815zy+COCpeHOpQ5eY7K3px05JMzLvDjtTfTi9IZC9dKhOrY2G9A/h2oluQH5DRHYlwsJ7cCgxXqFWYwqP7IVgZhMRpjKEPhp7+hBJMNc7fydGpPITQJfDjmJ6oUgLuWWtRHK7FBEPAu+HO/Hpx0bvZb4Hy2VNmev16y8CNikSeoDkJzGCAoCioUfAqqBIe7lFs0Jahygx0cDnYkcro7TxOq1BhafksedTqfERM5SciBRYFKgA40yj4Ed267Z3fNbnu9+Bfg2rrTaEFKeXKhh/h12qkEsSPKeBwdWCF676cpuYcFEkvxMumpMLLTqXXfgh2njFIKUIc3bAZvEAhUFJKAL42asGjqePp5YJyro/JSi5fEU1I51H3hYyiZ6iCM69AJQQdgmUe0pc2FllBhYCVztcqU9QYZ+kttSVTCChYH2blObi/Vkt29t29vkjtUYXpYNF3ZMNlpFiDbBa8IKFiTppf3w4t/xqFR00L6usOHuF+mXHEQ4+tLdylpKN3kRypSY2IY5th+w5MM4uYvwqZYkUoEIqCgMDu4EoRhGVoNVjykaricWP6KrxH3Alf4ikG0RRCo1ogFJkSNTp1CqMQwO0GBH7PnHLRA34KjjlqwEzx9T41GX8oqsIjVNoYpU4fyMC+4p01B4dXp+kjY1Vm3TXwj4DOmzFY0Jgpm1kRgO8sLFkgvkBcxl+X4ykAYa7oLDdSG8UGWqZrTSzo1//euf8L4QPES9w2r2k2/g9HgIaS6YGyq+xfCxGFgCEZkCXRGUUSbXMWNahySM54Btvb0cAhn0UClmkfY2JQQ26STNqtwgvntgxhp7l5xAL6rrgigJDZSwvKkMLxyaa7Gyazku2ZPBWK98YEagka4avYjq3VAZTvdDIzdVNNFLk7urWGMqyheKUowESVLyn6LKO7Rva0Rvulgo03ghSd5dLswbrNLysi7ZVd4avvKYG0cxCQfRTBeOxVTFAvRNWAMqe4f2aLjn6vFHg/kYzy7bZVFOcn8Yp+WVKKEpoGfjmohrXMhYVQzYIA8YKQ2SIkrCLFgATsbZjlcNd+3uP+atMx+jPr+vSwzTyxuwwjSJYA5yxvOAMlVtWD9mQsFK5FtwSdO506T7or78zvNNbfNpeUZ1F771W0li5ww5RcknWQEjDi1C00W/z5fLbTi1WyL+1r+w9dm1N+yd1Uw7QvVG882GoRG5+4kBMbzxKesJYhBiD/RXzu5JNu3NiypaUV+B7ka7bCLMcJ2auFP7cbC+aopiLcQkUadkTw/gGtHArGEXK97RCh9L1mh3v38xZEXjwdtf+CTfv381PY1+Gp/Rx6sLVWYc3BmzcMDWxIjrPIb+ekgOKuPXkLMd1RZEGPaFdSbkMcRUcIEouGkWr9ESlH9zY9lrczrv+s4N+mZvdRBdSV6+gL0sJ9WX2sswl5QXY4rot47dueSud8cfA+AZ3xzcTALDqvIBhElUoThRhM8BnPBCuf16xnCqqZgw6zRTnJY9WjT/yTyP1748ks6KOKXdOGjK0vK8G05QYM6RDdXosBDe5VwkvcWijno3z5wAzWDvhau2JWYcVfpOvBTy6s7z4PgFY68DL2n972I5/PKurwF1wK8yq7rZ4o5NsxsvFOyde7lG+8Lrg9iF10jZoPVIsvsRIw+jHZRjFVyrfHNJ2h+fmiH5VpoXnyOk73qAmJQGkPiWqmBilXolBAZkCwHVcoAWqjccgJypj8NtE594GDw6JmdwgsQTOgpllEZlbhHk/MHuLHvYpc0EvhiJHAk/gkQbkREFLFNkVmN+53V5yE1BAukGrU+qBtwEOWhAybgAn5aihCnrSDzaAbLQ2SRkNNyK1f9s5t1ixTOkKl8Cc03Ma9qPrmHB8GDNbx5DX89IxXRv87qa18xOnb67c7vmsoiH51THFUeQXALOdGFaf74LDnN+UcH0T9huzW1FajUEZlYiLBz47HorljqrrpD2+XA9autVpqs+1JpGMU0PG+7LDXxpRcJXQhYStDxS2XjhspErw51IJZ8rUfeveRhsw8c1Lf9fLo+hdpkuHKHVqRZQSP5AH0QVcDnNz6nugbtdgcs6TEPIkVUKcSIuFKXrzNQGzIoDnOdnHG2hkC/qgzgnk7IMajiLD8732KwGjZqBOhRoPxkIB8FnRuqpfh2+ee3c2GzE4eRh9P6I4fiO2+0xczms5MysgBOjvOQsgtxKal6mNIhMDOd1nM5GrZkROTxM1IFpQ+H6/ViI1oUx44Lp6yIqSu+fSJ684kQIC39KhUwVfxRhaw3nR0gcWqINFPSirUL8uX6E+cHJjlXrIeYz8Ku5KuIEEjMVugQXVyQSroVxmGqb8LJL88nUASqwCMECH7TgPxleBRYmwKoE4tvjxMFz6SdGHHwsuan9zS/DTpWj2kPHz3pYN78PYmABvBdmYwC9bA4rhvFDojYZKbvOF3UxtKUxhd9U7itm1oiYEzPv7wny3Or4fBCjsDgzkK+yWGSEPsHnImXV4wkDezT9uctMItWS6+5b+1T7e3yUA5G2C+CB3DaIgDxSsAtSZgrwAKkAhBZtUBSikYJOqAIUUbBorQNkFm1QFKKRgk6oAhRRsUhWgkIJNqgL0TcW/R92qkSldPPejf4Ulhj9ZJW9AeKHSxyz1FKDkLYiL/3X8jza/mVVKts4uesDvf5el878Ckeyn9R9nO+UlOFZbHZlKE41vDlAN0nVU13SLxvQxy1vzfEQWOLAPWdB85BnYH7gKzV17oMhZy7b5qxmnE5CN0Iku6Nx1QedlNT7dW6v3XOy2/GSFWPFjAYcUMLfx8quQSqLIEzlpdl+xFFIVFPmTveHPh5WLsSTCFCv46chuS92DW070neGq+H7k/Z1AAcsixnQPfH9y7VDZBu0Un8ni5MMCoHSWF6UcuWX9EZoZpxHgiw3HzGQmgbH2jHurxDHpvdPOyyX9fw5U9qjuftyrMPdzu5JCBN+Q64kity3cz21i3D0EEBHwRGvjQeUTZoFougkeCPu1Tsrci0pnXd5b6+i4i862sGuJgfQ7L0hnLdzXrc+a2ZArMvjGIreCun+oVbFGsVelG2/sXVLGb9Ojwh/UgKFzmBedvcY93WAuw2iDgySZhzmsMEjSNYBvkGSVACts0w46P/q3QbLm8vXjMo+ElbjY0kqDJJkqToAz7c0C+CYk1gkQfJDkONHp1T6BIun2CbWPNNsaccoKgySFdgmccKnhgalMgNCDJEedKzapwzNpwJRi+/+dIG/RqPC20HqSMsI5SBKDhtRD3bj0ENrwbIv2427Jl8tWvE5oX7UGMw8dr9CJiDwNJF/O5Zo3JL5H7fbg51IUIo0yCVxS6lVRpIE0Sy0xD5LxPCEsU25CNhfX22KkV+gJvP8WxCcPQ5H2oRYpqjL4NhSR3MUeB/qWO9sd2jTpTpfATS3XH1aWLUUfTVccvwHbRSIu57XmmGfq8rvm7ouRHgCeTOiaq4EiAaEWVZOUJp6HlAkoOj00KQ6KLyf8FlRIv3x6ayMNo5EG/n327h95PS98XFaNjNxW8rXsZ5eOqnqXWx8SAB+UFx9MfAqjwsABL9wYQgDRCWH+wy4b4avFLR2m0McqE/iY5nn285rIXzd5bfm4yyutdCZ9i6IE8X0208jrgitLjCsteLlS36a48uogxRWLzJczrvB0ymhS+UIZ82JMj5xo5x3S9R49Pdq4fWxFZ0wA/n02Y8jrgjOmP0qoE5BmZMerCSjiE2pZQFbNiAEeWKhVeeExWblwWdWLPQLHHUjU+X8JoEdg9ihxA3ZVLUWwBiLteRFpEkrZ9RAuu75tjv+7iI4dfCe++5bgcOT6WzqPiV80vximkzHCoBtwUVKcKioOcyvB2UKFAYt0TapiSPNvXvDBPBMOe162TBLXLagTtQ8l60TZ1S+eKPI5JL874NVJVwMYe5UmSp0YDY7liogngY/a8VEpwmsX8ZpbyqGJXZ2hWrrwcTk2RkJBG38HFCkOMHSD1WggNXEMLdJYnQJJiZIQEmV6UAvUAxmI/ECcKjYO/DnXpxSlBMJ7dTLtOV2UiJ9hixJ5XfDFLCcBqwIFLBIHjFzMoTa/ccWUJnM2roqI8hRS5jaHADtXV0P4dq4uGjEP48I8cI/s/CnkKDq6d9WOqid+5WivWiYgUZ2g0qlVUfixMPMbpFYLwPwBzDwlYN9Ui+JpdzFLTzK7YPA9FosVDLoFfYhbh5N9iNmJGw8UqRUOaYxK2RNIY1TwS8zGqFyNT4tw0IVsfMqlm2rIVHpM5xi7/NP5BeWPwbHagSTP0v6b2110uVap49b/0ECZ2S5xxQfPoM79bgX+3GKn45bW5/Pdlq46iniEkw2UoQU6jcNPMJqO8oFUM1QZpcWH75qP0qItJRc033VakunsN738rXL0Ec9FxGyUxHmi5JghvmG/NUycWfeQw9L0fY8EQKkWL0ou4aymkrzVLkQzaOAYmQEQs+q90PtN4xLzCZZoAv2mMaRIfdr9B9OnzNZBBaRPd4Xy6dNlof/TpyR/PiskEauj2ohXlBr3/vc29psE0KfMllACaIodoXyaYkOotfVpptdB/fKlpwPGHeif4nt100UB9GlLZZ2nKxvHSMbfjrn49e+fPgmA0jJelOaHWlGfMm1ooetTXGI49ekyY4AfbvMxAXM5CVPM1rpI1dfTUZ1k93vPuG1Xpuf7SAYWEiSE8oUEaiPkPQQrZitLQV4AxWyQfnuUqof026OK2SD99qhiNki/PaqYDdJvjypmg/Tbo4rZ6tx5tr90qc9oTs3dDwc+ktwyKWYr43T86dl7Tl7Latxq0PxgRF2Tdoa/Xi6bun+MVnag7JTWI2dMcGfVuYEPQQWT2d9PgDq3noKJhmMBisZ/63QJaftIwc2sFGDxxI6LJ8zGigLwpBcXT9L33u416f4n3317d+3LGnSHfjqweLBCo1SzOwFzqcNGXiId+AbZFgb0gxVptAlKoiURmOFETNWBJ/mYnSEhj2KOjnQMjdJr1eoQYOfAxdyDoq+6MvTnw+KOV//J9pTt617h3LiFxxO49KdDd4NSH4Y9PvWz9SXaxAFqUOGFPQ/eLihalUC+O+aXgL2Ru6PXMlhSnEvtHhYjjbtharc9ioyehJYKUOhjVRq5MoZmNh2JyyGq2Dja9ZLE9TCtzvQqXXfPenpYPLVRtxPOOIjBenDaMEFFPJU99VSwBaVXJPlqokGzLgreIiXBRbBhY3IJ9/BBWY3xklMo6EWhUKOgg5SJ+cK7+Rv/btdDr9AZv0OKam+bN+bMPqUCJfiY8i+ANR/Qjc+a9+5GWfMIm8ec2QDWdpOqPXmPAwQbjwP0EcxMFmRrfUhnX8pMQjr7UmYS0tmXMpOQzr6UBxX/NK1p1S9q8cZz/j1uLUh7b35rfWZPYAEsaF8udpUMXThkbeJAydbnn5RtRRve0DvfkXuCAdh/9Jg+NL9h4E/UbqJGFKRTarzlonjyHubtFTJ7H/M+FrshH+MD5sr/XTEysPcJvIIaucjK2oSiSJverN1DvgqKGoT8Uo0pQXeBRNDBM06hwSwZPG1arsvMUc/2ytKyE1r2+tmnJn2vUELcgb1XSBEEj2MfipE4AMl6rpqKfr0LpaaieBQGrVEzbNq06bslfQBFdMaA1lOJaoUe34JUAx8FypumI971Tpf4+I/u/ardn/ebVmf0VyVvAumvSlGswZ0wXu742QJ3MG303ZLCo1rSeJUB72gcRWMTpUKgzKn4+I6H+t4BnzGLat519s5xpTOHuCMkv5tLsQZzPHmZ08YWmAP4Y8qcYnkwp61XPPhJnCfY4xiwryo1UclEP8bOIq1OMRi0b3TH/5b7CfiKqne/eZukY9380xxbPpw0ZAj9xK9TmMn92UfcaVRrMK8ZL/PqFA7zzOixaZcHBzvnctAQp9IkazBPF2Mfxi6NVgNYh/1JrU3CieCvboAUrxhKXIDH/N9fuS/z9wjcPHDXPdkzH3r7uuKhcbCKafKyNThXhZdzZQqdc+BLYLPFoiqa8kSqWqWJ5VeEfjunb9xxaYHPwk0nd3Wdlq6gK0JOnymXIjhHIlHChwBhxUmWW2XAFSHpp/bj8lOr2qWEHt7/Luigw9YHDdqkNKNv4hHTe0TBeuUQlTKJ7qYCTLmK3hp6gYZEBpOMD95bNlapjVcm6JNFOuKGBmdfotDLVxOi1JBBCrfzypzOwfes7A1HOr1MOPYfnVafQEwnpD5lNvaVUSQTYJ8G3YjsjiIL2C4tFQVDQ15vChv8TCX+jGZ59Pu0Ts+/hcTKZgyOq7KwQu0njIna5F0hE7UpSl7B8OhxKzauut1RPEknr3111pAK+Q2Gq6LIRoCcJ1SPuKPI8t4W1cC7hJm4MCLtEKVer+IYZ9G22tjUI62Wy9eNGKYYOGnfoPwvYQZWTB0hAFYLeLFKLVidSyUr7cmQC3wIODs3l9/87qAkPT7qothN/L04btuYVtWBCgyoj4L/dzJ1e+jfMIbbkVxq7H/9+f9Tf37mUKMC68//rTdff/6bbN0pQH/+eb0aRf86pqfPuhpeKSuHht4W8CC60DrysRj50puvnflrto60Rn/+5c4rF6ydfj5o244uoccdU/wKvT//I15Ubha6B2q6rVQ4/fnbNe+3aXDWDHTnsrTRatdokc3057/My7pThcO6Au/P311z/PP46ymy1JE1Jw4M6vu8kPvz41qGs8E6pmUKrD//sKUrFp5t8nNgRt1hokObwulHDwqnP/8jXnBu9i7A/vwlFg5cJo4/6zV2fraH1z4p/SRv4fXnv8yL0Clj+Nmfy2+TejVp+r3zFa/1f9XccGnpS3qfe0f8fJ9Oq8YsOttnc+DAuXXuFokq9/tkmwwMcb02MTYO8+EMSjxVY0mbB+agR86nZTdEMCGaiy8WWvbog+GrQEHShYlvMoo075PfM1cVcx8Lu0piAX11+bHr5y+feBEwFo1YOvtBn6P5H+vFHGd+tdj0UNcX/vN+Onb98cr2Afl1oTLESHeAXi0UZnFqoIh/H4tcKCdi+UYrY/VKjmTdw0uVxpSt6L877nOle0OWTGIcnsK/CDk8RVwXfHVi7+/F+/5t+xS2s2SUTAscJfDIKm20Koqn7c3DVSdnGEY0l+3T5KwpUbuEji6r1A3YsmqkWIMZzXmZUbdwmMF0fxBLdixc/TXaBMx8KaJA7rSRW2csZMUii/hmIvfOUXFafXQzUcvOhsH6BPwvcG/V/ZdvoRv6f/Pa0DO7SOLg34bT7Rr4gdCEZDVkNGYuyRrMqsrLLGebWDngVhZ5qy65iW5Non6AgWcFjakzYt+syrWDZi7RXp/TtuOr/ITK+WTH6LEoocjBKdCLLDcjFd3k3ccyL5XU5Dze1qe2gcvOuPr57U+SLiu21q5XoYa9AICOFABXIQAA1WKRJ0qZMu7+E0dkTeIjlk/3WVjut1UHqhSVFOo5YACAiA+A8PJ9KEdT8YPV4zDngxdYPc7vffjqcVayPUuB63EWr07+qdSMvl5rKq92Lf31bAMbqMe50odvd/N04Sh9elHB7NmzC6Ae50n/Rd0P1VsbMP+gYlfnbm332UQ9ziFe7uy2Be4USD3OXMnAiR2m3w6cu8Lj3wFXwkJsoh4nk5c5K22BOUhh1uOMRyeu/rbpkmd69bcbO0+Y2NWm6nHSeJk3o9CdXRuqx/G/6Tlju4+Dd+o/nd60vL34SCHX44zn5dywQuecdetxKpSa9NeZxr6rrk5z27iox182UY+D+xCc9TgrjX7qgP8L9TjXMhDlp6bdAxY2PVO32axP6wq5HqdKX756nKJ9C6Yep3yn6Z+2bo0Wpx2qWWlr9O51gtfjMGNzAWpMKvXlqzFx6mutepw944pfXOHQPmD8SV1j/2GvZghfj8PQEQJgVZQXq08Fq3MLux4nikuNDT6oaqoK3IjuORCkfnQ/4iV9p6RbIjgg6a1X6OLYx0gt2L6oJ1EZdOCImHE3J7k5cZRUpADt9GLBL0Alb0nNmcuzUl7INxZttiP77vqtnM/H3skxJbLkr2QopsKCTM9bQaSSebjJTKk03g1ST/MnONJXCQX/0qVyztMH4qDr3U6UDlWqMYYpo30xvT6Uuh3OVoKV0VysXD57euIzv0/eCwZXMqRPbdaXnguSgaKBBLYl4nSriS+IDJi2I0YAJhqAqcfHV8Vp1dGgQx0ohYrBP4e7AQmKWINZupd5NKyEXBs1SBlt/BLs0dlpLOK6uSrhkxh5Ac72FYUWM/VEkfNBkI40ACLgv0I60oB/mR1pAif81SX0xFPP8Wd2jnZ4HXSF2ZFmXI8Vo67r+vikHVq+6GFaaheKTp20+88da5g/DOlYw8VpR3A0mmQjlFsDHdsvPXbzjtfScQGj+ntKE/LDLeGdua9i5BngawZU1ddHkbtBhTKLzxGMvIs0YO+gic01e7l/x0OOFLcOISMgjXO4eFVelrvaMEOQkKiHG+x+6JSMWvfq+mxq2jRD+XjNL7wss0eJO0Hav5IEazDtKi/Tzhcs06iYyE6OEgoVfGWUcd3jvKHWKJeRqyMhpwGrNAalHq82wn6CpjChvLKfv0AeO66O98q0y9OP/ry0G5NX9gGJCYoBauPpfISR5Ae/6sY+Pe2WZ/uj/2je+Jh6lJep+4JY7Y94e8qTwq4kmk/At5AZPSB4Bd0OaDr25AL8quAiHo0SeumQF2z4tw4XcdKkK7lMerd7t4Ls1ee9l2UfKDpqd+2J9BrB0DhVTIIIjNo0f8xvtaCYGOCCKdRqciKlCswSA/2MzdsIYc5k43okyHF+c5GrgwU6ALkwMcxSoyjyId9TfEvjA0qxtWoADwwvqW1U+d7OLY7emySvM5q+n0NvWmzH8Yp5BjrMudT5XXP1UKQiwCrNC7YH3hxFSgVZVj1DcFCLSwkUlw57fnv+UbTFf1fpteXD68dWYaXWYswDJr/rC3tzhPfNPxTsDF6OtBougRbsNTiCpip8fXaO1SnhKE6V+OysNeXkzLO76MN+8JYsBQX/s0A++O8WDvysSpn8zjImVgSo+sTeBMoR5lDS/6gp8suRIFIVHPKEGZwQfEGQBieG83jOqa0vZjSoIZtheFH8+MdmdPNZmuj/IyIyf+Y3MK1PfAEE+lFaNYhuQQ0jGIkMFoTIgN/VvMCx3Nfgmx987skX/Fox+su0WXKe52MPyqGRzUUVi9VzemGopkONUWcUWdIr/2GjLruDq3TCftk4dfVyDxSO5/NqZCpY2GhGo1MurlbEExR4yxlQ2kBwEcq0Vyk7D3/qccF/6+x/pyxeqw6nrw9vWBkucTUvY5rcPmf1mpggdGzG8CetH91Lza8xrYIi+wGvT0J1GqbxsnrZgklBEFpcQgkJRKdx8a6yr8nKA4GKCuelG5R9h/3L9HjTwc93dvWm3vUzz+/gj0ccyFX2nyKSCrOquy3e6CSb8XLxzomXe5QXgKHreBmKLV6OCC9/SLpDkdzdYNy/I1c7yDIftEx6E9pYZx6S7mwk3fNEMr0Z2kYx+oF0f8uDIePW/l5SACTn8iI5pRcrtrOwmZgzoZgxS8ujS5gH+PIIjgkI2eoltJFbY+EtsC+pP+AhX3dc3EgLHPujWuBht07p2yWuDJhyYnj7un/vulEgFvhkBJ8FXh/xPwvMb4EflFSODIn97j9h/oAFaV8CZ9iyBT4ewadmfo74/9ACt/h1hbds/SH55Et3ddL1v4qtaIGZxx4FYOh2XoZii7cALXDL4Umq5V82yuf5Zg7LnPmloxUt8NgvmdX+2VvGa26J51mdnIq+FwDJpbxIzosoEAvMPP9laxYY1x+cFhgTN9ICx3FZ4OtT6sy60chfmnZl76eNdaWV6BnO4ES1mhgEzN5LxZOuKDENPUijTjaKBvQMLn4nBTkfHJ8eO0ShVykTkoFGpyp+zEvKHkj53rqMx1Pp2pGdFA83H93B9cjss+S5NHMhfiFG4gDEjiisgKc1ioREWNQUomIwBYBBqdBHxYli9Fq45CX10VQOSKrmN2bbo18/RZ16kZ8j2VZWe2/ESEwEZ/1JORTpE8FKy1qYwjYpfIrDtJ4OYyQ8YRiTMnq3ZOPOoB2rGsnrHLVrJXih08HRn6qg1yT+21+++sPB5dgMAcAL4QXPJ8Ky+XvVCBHDXN4I776iKGKBAomLCO4LhYypu+lOLrnCOZYUgyy4ivNCCdEaDkNndH9ctCw6ZuUmUREIGBvUYLDgpR2g241Orx1IxQtgxjWGILyT4RqP/UvLX0NnDt2ZM6V0cUaVJ/UTbCkzUqwBVAgvUD5GW6DisgXTruwvV2p/taAxsf80TpzVvjRdsRpnwkPGjNpxoF1HOjRBr4giWgoYZ9UbgM4nOxeZp/J3NJ4fuu/BAHTcxzf2/ad9ncf1ZGyVn0szF8kKKJLUk6xgZqv8riii6GmNPkBT12zfcrtGkPfCZzNLad/3fyxgHyChE00uKJIIEHrlhUDG1NfDEbJIZZEQYaDoEwgRgW9/D7mcnN35e+Dy0fpdX2adkzE248C3IXXu+GXB15s/icFFmIMKCqwG9bRMMTkTGBgXCRSBPsWrOu0Q+fpsQbpNH7f0+WwaAsUwWWe9P37RGm+v4H37Hj0pbTOQS9s8DQ+U27X4jM5fdVa2Isi3N3MjSQPprsGlZ2obxxmDyQ65vceStBZ10mh5I/C+dsbBwMkOI+ThX4/1ZD8S27UHV82FrRSKxIKU2VmoapGjSLdeFqmWsuDH81w2XTU3hlyZVclz6fjUbYa5S7/Qq0rx9cFh3WnEvLSMtuq62NPfVN4ru97J6nuvSL/8ahknFFECsIKhjlEDFInoBa0A5yywwcHiX1/7no3/9+DanZ67Xld9WF4+PZV+8N9oS9gH/3NJecE05aj69eAPXWS7op+eeL9gRIoAMHXjhcm7l2XK2IkQKmVsPNe5MWa63dxlIrwe6knKyDaoJYrCoSH10KD/QxHwzlr+ms31Ngfsyalf41Oby1+sHAHX7sUXATtaprPMj4AnrlrcZ+n97t77ylex6+8xWSxgBMz0JAQI4mr14gviXNi6yloRcOdJrZRV58+Vbm5Sda5LxXqTf4QI2JEXvCIWajCLI2Cm6bKxCBgXLc7AzqVXYUTAKx72H9Zh7kPvZW/vrVkb8u2DTUTAjrxAFTHaAvX/IVsg6R+/t6pXpHR+rZSf7eY0VFrZFhzvyWcLtlkWGptvC2rJE44s79EkcOGTalf7/vnuvoC2gBlTCaDOjvbkU2f7ehaYLdj96PmVwRVaBiwLkg28UvPuzB/BFmzjBW+thakFi20B0z+3MVuAixanittnYdJBGFuwsdHvwzacOBOQGZIY0fyLwyybsAXbeIFaa8xPxHPZgjLfAk/cG9VcnrqkcZ9w/ZcK9FgwEChPsHFu/mmEhmFANBTE+ULjMHBwcEoE+ilrhijUqmhVQrJZan/thXcXFxxOR/euu3hmUuNrxziejh2pGknmYlkcRa6GY1jehlakNEWRveEWKX0n8ON4o3glR4nx0NSMyR6jLqFTDMf/rV1r/0J6fAl9LeJqXrvUDVolaFqfzvBcduXFOfdpW17kV1vZo8jv4ZwbsBVwaCzSVhVBt22RKoYQD5VBBLgFxcjxfHSt57tTgpZ0LrZ997Y2DxkNtQGTZWpFLCQjbkITfN21JQHRQdV3dxQ5G26ZgqrMBMSXWCbwyMc/K7Hrd3u/8b4JAY+LhcTTVTf5TQ5YGGRrIHOYFxmmqBTNA5nGXvg5sUSFWhSdS6WaNRHDMEFqkGO74f1WX9e9tZLlE1/c8Wvbswy9c67p77GTgqZEa+C0hRen1eGU5tZwae5OI5qd2ekVL1+bM6d1TqNu+xleD0gUB2ohx8iKcUBdL1ipByeGReRpC5FGGUu0Jm4UGBQmwv6sbGyes77J+4X4/PEK8injd3oPeHxgOvzJIP4YSTEXxZ9QpFQPDMVUDMXbLBQ9UOSrZTq7tJh8c/yoDvTVdEOPtO/YfL3f/q91EsO7ja5Fe7UiXuyiIq88nUumjsuvuq6OIg4AFTcvoLKZXkFtHBWL1HUZTGko9QYlWHUpXiOguFx4/eGXComvfNKkP99yH7gzgl4wRHQVYp8fJ68Lvry6khB8gkIQiENALi/tj1q0+3LuhDSP7NL+2elJyZePLnrG83wCFe06o0gEQHUv1EWSokjHHv8r2uUv2u10RusVnHHBP3Vq09XP44+vFaxol7n+8qtEsBi0Vw+ynRb03HdQDxst2rWwPtKiot0N12YPz7YLla29fur9+Nc1o4Us2s2vzsM4JuXlGLY6C7AqNzb28xNd3Aqffa8VZY4v3IdYsSp3eL+mS44+bxS4v9HMsm021RQLIPvuvEg27FEgVbkr+k7d5TP/imxpy01T3h861MGmqnK7kQoCHhT2xcWNNLE6LhMriq27e/L0KeK5RzLliz5n05NQxUOUakUy3bRaiHIFL1GSSq8U6cGdyGABijQzYoY8CHs4fZ46uYzT8adn7zl5Latxq0HzgxF18yuXjVFkfDgpl6NZctkZRYYbvZrBNg/5x6kLV2cd3hiwccPUxIroPAdhIGcuGQEgH9uDD/JhRinXc0HuvjrkWMTWDbL1q53PHB75fgH9Tb312kQdHXInCnKx1rSZGX6J6CkNLlGt4mBcqOkligX3xV0SvcJgiNPqdEo9yQ9DUV8JBRgzwYaRKE+LGcVhJMpoMH1PjFQMgSefMJIdSWKy3MFXEknjDPCcocKSqfR541/9D3na1KAJ7z6XGA2BkC0sDB4jFI+DSBB+yIRoO+eVsV+CwoM2l51VZtWRDlqrJkR7hfElRNuHCZwQXTBg1NyqsfbSpd9u1o0JTo0RLCHqNvZCP5cS6332PWiidn8Vc0KAhGiPML6EKAaNlRKikXuc/vr87bhXxqX0bmlniiy2mYQoDghnOisgzIoJ0b2OX64ubvPNN2OC73D0j7qtbCwhivIiwxQVKydEk9bsPVnxTYZkDjqse52jVdrZUEK0BS9O9cMoQ5vw4yVENW/ftr69Y5rP9LSa6izPemusmBCdFsaXEB1hmc42IyGqn35DJK062TPjk/JfB+caZwVIiDJ1nAAJ0SlhfAnRERaqa3MSoul7Imu/9viKrhkR1Wzm0WYlCz0hikPAmRAdYVxeiT9qQrRX5smeh/sc9VuWLft6TtWzh/UToqVQ5FYYWejOdpH8UORg2P8SovwJ0Tq/tO23uWc3ydoqH39q+2TxSMESosz1J0AB+s0wzoGr9VHkcpgNJ0Rxr8IKCdFRY0Z1PLazTlDOseQVd0ODJbaUEMU4doqXYwcLlmPU8zuEJeuUpi9fxyREd/VX6jVKtSv4jMHV2ycyFG8ubE7jYTv3Fu5tCjDD26HclWYBnz1kGx3WPfs1/fo8K2Z4hc6kYaKxi1c0NoUVSIZ3XH0Pw8b97WTrjn90T3H70temMrzhpMaDR7kD8PVD+gxDbD7dyEwB2GyG93soX7rxYygFeZLNQ+6YIb5hvzVMnFn3kMPS9H2PhIGcuWQEgPxxdz7Ib3enIB/6Q2Z4mRlDkwwvMyw1yfAynWmTDC9zKZlkeJksNz/D++vlsqn7x2hlB8pOaT1yxgR3ATK8yVzsqnR3uqR8hwvoitb3Dm49mUQfsFrp8B7Y/+CjUsoRc5Qg/OG4TSniC2b8IDmiifnOHJ+GiQjHR6HwMxWZOZCw+MH1uf9qmYwuLmQS0H2gJmeIgXUi2T2Mi93/Tti+uoKrnXh3nyrpa3UB9OSLo2/uP3Qel8qTx6bfhTDWlMzBTdOPQBtHm9ChfCu7xHXWweZz5TtWi/pO3PV6COe7sdN5psS8lC6zQ6OZSpeTgTVR5Ck4xJRgysAUwdRr8wJUrwlzq4/yfdzLc6nL2xmfl2VfMlGvW1aN7tYxp6f3z71+aekq6xlmol5vHnzbpp39a0nmreg/n9q/3WyiXj0mN/Rwtisly7l74F6DBrV3m6jXAJcK0Qs2fg1Y1KPlo4fS2WBvrThJ8v73xCLVsFdBqVfLbwyoeG8gRipBkq61XaCf/cRePq13SGYGmpiOkexJ0sZ7U1YEbtvutbXHULcGhqAcjORAkproNvZMaNXJb2nXtx7nv1WchpFKUt/aMt6+xaFWvuvPru5Qp0XxIxipFEnqfChjfdOjx4M2BsnLlJsXORojOZKkKVtyyuu2uPhlZ6xXXd7isAUjOZGk8L9lh4aVbROw+wqy9mbsefCt0iSpukvFr2P6f5OuTFa/Uhz9PAkjlSFJzrVmDvj1Y1HZipQ73Vd4XnLHSM4kCfnW+sXqyTd8lo+6VnphzPhojFSWQr6I++jJ2X7ohvoTF3a53H0iRipHkmqfbljFP3iWX8bt0auj55wCu5rlqd+S+g4ovSBNvuXlubNfyl0+jJEqkKSPJaJadPYrEbRVWn9iRJc6URipIklqejxp6y/dfP231F/+okvRSuCGLiTpabkHMz3Kz/Rd//FywJUPlb9jpEokyanppVVV9o71338gKvjn8q8WYqTKJOlT69MzNx8LFC9Cy7h+lqa2x0hVSFLJD2OdR9bWSLKPHryQETenL0aqSv3WbrvpLw1NpVvOdc068KHWGIz0E0n6Vjv484Xyf/tkxj85uspxxAWMVI0kfXfS/Bpas7TXkoDaD09k1R6KkaqTJNcq6/4MkV7w2V1kr0vYzjdjMVINknR20JrFna9d8Vz34Umm/ta9dhipJkkakB0uafTdIyi78bojg0O7hWOkWiTppz9qxbRtOCxoZ8aElIGp3/wwkogkbW+nbV1vdhfpzGmiU/GSDIB8beq3plXyK/XzWPneyuMfeYd8v4eR6pCkSZlb6t7y+i5ZuC2n9euV595ipLokaULJXnMuf1olSx+BtvXcF9wSI9UjSY6VVzkX2zQ5aOeO0k32D/c7gJHqk6STz3TTpkaPRxf1epumvzn7IsuzaYBweDZD9t14LgubI9kpuaeV1Pz+XgDPZjiXpnSJyd6afuyUNCPz7rAz1Ycvp48Ekg7VqbXRkH4jXDvXDchviMguRiIVOB9liFeo1ZguJHsnmNl0hKknoY/GnlZEEsz15t+JkQf9TgA1Dzu66YUiF/pZ1nokt6sR8SDwpkaiIuPTl6/xTp08YoNd/ahqAjY1Enrg5Ccxcg8AFA09MlYFRa71s2i2SOsQJSYa+BztaGWUNl6nNajwFD72fCo1PpKGkhORAosaFWD8aRQUxeGbyr8cM+lfr52bmoY/u+KVRC9tMP4Ou7QhlyR4DgSD6wIvXMf62cREjCL5nYjRnFxo0bnswg/dxisGKUWYHwQ2lwcoDEpCEcAHAIads6s8frx4987Ifv0G3G3DSP+Rt4VMrqcognMvACWEXQLlnhIXdlZZgoXA1Q5X6hNU2CepLXglE0goWLN3aO1/PlocnXjB+ddRR9e2pYNF3ZMNlpFiDbAu8IKFiTppf0ZwbhHWKjpoXlZZcfYK9cuOIxx8aG/lLCUbw4nkSk1sQhzbDtlzYJxdxPhVyhIpQEVVFAYGdgNRjCIqQavHlI1WE4sf6VXjP+BK/hBJN4iiFBrRAKXIkKjTqVUYhwZoMSL2feKWiRrwVXAqWANmlKnxKc34RVcRGqfQxCpx/kYE9hXpqD09vJ5JGxurNunGhX0GdOSKx4TATNvIDBR4YWPJBPMD5jL8vhjpGnkC73MH2b30RpFakdboABha5e63Zce7SkbvHdh28J6YaAGNJVMD5ddYPhYjnSPJPAN7SVRGEY9Ii4xlHZo8kgPB8XZ4BGDYR6GQnV8lejDrp+3i1X9HvbM/luhE3xXgEAvquuCKAkOlMS8qmNwU8k6o6XxlSwZ1tfKNEYHKs2b4KqZzS2Uw1QuN3FzdRCNF7q5ujaEsk0WVPNB/ddmA6ZM2BcQOOvUHo07PeCNInV4uzRqsc+FlnWPhsC5vd4avHKcG0fxCQfRfBeO0VTFAvRNWAMqes3P8OkwZM1KSdTbnTom1Y5rnp9FKfpkSihJaBr4Zqca1jEXFkw3CgLHCEBmiJOyiBcDcSesye+tbndeqXQeVffcNaEQP08gbs8M0imANcBrzglMr0rL6yYaElcq14JagU2tSu/RxPVoE7cp4Ovt4v5Nu9BDFWOnDDlFySdZAyIUXIWxNk37bSC6/7dRihfxb+8reY9fWtH9SN+UA3RvFOyWGSuTmJw7E9EalpCeMRYgx2F8xvyvZtJsnpmxJeQW+F+m6jTDLcWKmUeHPzfaiKYq5GJdAkd2DMIxvQAu9glFkwSArdDRN/63Xi2WRPWRZNTMl9xNWFctPI2CGp+QRvv/YQp9+3lkxLRzrT6o+P7+ekgOK7BzEWb7riiIbB0G7mHIZ4io4QJRcNIpW6YnKQLixLX/gRTnxxuW+B4ov/H1fnSg7+rKUUF9mL8tcUl6AMfN/AgC2nBcwTKIKxYkibAb4jAfC9c8rllNF1ZhBN7FwXvJo1crn2w0eMuuudIto1r7UPzacL++rwTQlxgzpUJ0eC8FN7lXCSxzaqGfj/DnADNbmtCn7t6H1Pp/da+p26qe99JMArE3lZe3YQmItzD+e1VXgrrmRz1e/kDfZhy6s++5d2cOruhde19w+pE7aBq1fisWXGGkYR3EZRvGVyjeHtN3huTmiX5Vp4Tn02aQVQQ1LAkh9SlQxMUq9EoMCMjWA63hBC1Qbj0FOVNLgt4nOvQ0eHBIzvEFiCZwdM8siMncP835gFjugnzIX9GIoskpxAo80ICcQWqLIfEV+53x7yU1AAekGrU6pB94GOJhByLgBnKyjhjDoST/YALLR2iRlNNyINL5k6N7n+jbPtLWxbrd9PFbSdUw4PryZrWPI63npGNf7o4MOppQW76rtJv8l4rdl+dUxxVFkBYDZTgyr53fBYc5vSri+CfuN2a0orcagjErExQOfNQ/Fsn6rIn3rJJ33W7hFs7XOrJIBjFNGxvuyw18aUXCV0IWErQ8Utl44bKRKGM2lEs6UqfvWvY02YOKbl/6ul0dJ6ccMQpQ6tSJKiR/gg+gCLoe5OfU9UOdrMDkXSgh5kiohTqTFwhS9+ZqAWSzA85zs4xA0sgV9UwcpOPumhqNI93yv/UrAqBmoU6TGg7QcJ3CSHDKmnkOXZ0sPX/BXeNLdZ/xGbPeZuJzXcmYWRwjQD1QFkFsJzcvURpFIBaf7bCZy1YzI6WmiBkQLCl/74A4XLxcP85//4vdZL54eH0GDz4kUEPiWDp0q+CrG0OrOi5a/okAdLOpBWYX9dfkK+4GTG6vUQ85v5FdxV8INJGAsdgssqE4mWA3lMtMw5WeR5JevA1BiFYCBO2zHeTC+CixKhFUJxLHFj5Ph0k+KPvwY8fbUzbPuv5wUuKXKy/Ir+gUPY2xMgLeCbEzgl60BRXdeKPyNhmqMzReCM7WlMIXg6793O/Z92nbPgw8qrP3sF71egELwxgq+QvDaRsjH2jzkzBI9YSBfkrb0+fNqbWVruxzsMF3SId8TtjDI0wbwQT5rAAX5OMGKQ50pyAugOBRSy0kVh0JqOaniUEgtJ1UcCqnlpIpDIbWcVHEopJaTKg6F1HJSxaFpo3q3jHvxq9/e5dPrLO3w6QOr5A0IL7xDLaMKVICSt/Fc/K/jf7T5zaxSsnV20QN+/7ssnf8ViGQ/rV852ykvwbHa6shUmmh8c4BqqK6juqxbNNaPWfma5yOywIF9yIJmJYvB/sBVaO7aA0VSLNvmr2acZkA2Tie6pnPXBX3/fGx3iSmBvvv6qo/lOF8MEnCoAXMbL78KqSSKLIokze4rlkKqgiJT2Rv+fFi5GEsiTLGCouQQsrbBhZsv5Ht1p6rdObq3g5A1hN0D359cO1S2QTvFZ7I4+bAAKKXwoqSOtKyfQjPj9AJ8seGYmcwwMNae8cxMjC3t6RA5VTzV/cGCdF3H6oW5n9uVFCL4hlxPFJlp4X5uE+PuIYCIgCdaGw8qnzALRNNNUHASNY9W3H5aPGC3y/SUu7dKu9jCriUG0gRekFIs3Netz5rxkCsy+MYit4IaU+3p5vNf+/pP3NnI+Zo86l3hD3bA0BnMi06scU93ApdhtMHBk8xzHlYYPHk7km/w5GnLTJ1527RHJUrFkZgM/9XB506Xa1FsjpUGTzJVnABn4P+K5JuoeMUyW2fO4Mkt6lP/dNImeU+JCpnT4+m2ZCsMnhTaJXDCpYYHpkMWGru8t9CS467WjZh+XzLL7uIQ3wS0RqEOnsRlhHPw5GmjHprIpYfQhmdbtB93S75ctuJ1QvuqNZh56HiFTkTkaSD5ci7XvCHxPWq3Bz+XohBplEngklKviiINpFlqiXnGjOcJYZlyE7K5uN4WIzdjTuD9uiA+eRiK5MRYpKjK4NtQRHIXexzoW/5jr7xy7+BKn3FHz7SO/v4zvbVEcfwGbBeJuJzXmmMet8vvmrsvRv4E8GRC11wNFPk1xqJqktLE85AyAUXnUkWD68CV52S7HdVO3kO60mcik6/L3v0jr+eFT4+WI98MTOngN7XE5Q9XDzpLBcDnBC8+mPgURoWBA164MYQAohPC/IddNsJXi1s6TKGPVSbwMS3ufMnO8hotxQd3ua1+VOsRfTpQCeL7bKaR1wVXlhhXdvByZYNNceXVQYorFpkvZ1zh6ZTRpPKFM6aDKhZ5G+KzZdydM5F1Q3fQGROAf5/NGPK64IzpjxLqBKQZ2fFqAoqcjbEsIKtmxAAPLNSqvPA4P6xxxI33RbxXBB4adOqG5iO9qhYlbsCuqqUI1kAkhxeRLTGUXZ/EZde3zfF/F9Gxg+/Ed98SHI5cf0vnMfGL5hfDdDJGGHQDLkqKU0XFYW4lOFuoMGCRrklVDGn+zQs+mMfFYc/LlkniugV1otNiyDpRdvWLJ4qMYNt1C3fAq5OuBjD2Kk2UOjEaHMsVEU8Cnzkyv2fx0qIA/2ktzw6pkawtSxc+LsfGSCho4++AIlMAhm6wGg3QOWJEjGUOd6dAUqIkhESZHtQC9UAGIj8Qp4qNA3/O9SlFKYHw3p5Me04XJeJn2KJEXhd8MctJwKpAAYvEASMX82Sb37hiSpM5G1dFRHkKKXObQ4Cdq94xfDtXIUbMp3BhHrhHdv4UchQd3btqR9UTv3K0Vy0TkKhOUOnUqij8WJj5DVWrBWD+AGaeErBvqkXxtLuYV1PPaJDB91gsVjDoFvQtvq8i+xazEzceKHJeBWmkStkTSCNV8EvMRqpcjVKLcNCFbJTKpZtqyFR6TOcYpwLQ+QX3rbIbJk19WUK20OEPZ6fU/fSTZeY1XGa2V2yiGp3t9mGRz8xt26fMkDa9LUDD5bsqsuEytEDnquoEo0kpH0g1Q5VRWnxYr/koBXYfGbR42nh0h1Qb/+XmtVV0lMRslMR5oqSuknF3+JlIz62P+3n2X3DCUwCUzvOidFTFakLJW+1CNI8GjpEZADGr3gu9PzUuMZ9giSbQnxpDitSnU38wfcrsKlRA+rRtLJ8+rR37P31K8mf7tKsbRH90Cprp2+zptJEligigT5ndogTQFK1j+TRF01hr69OqI+O6hnWtELhxy6BxYY0WrxdAn9Ya6H/hgLy8bGLdA2EdzoobCoBSbV6UKsdaUZ8ybWih61NcYjj1KYYUqU+n2XxMwFxOwhSztS5S9fV0VCfZ/d4zbtuV6SEChASfeEOCV8aQIFWwYrayFOQFUMwGacVHqXpIKz6qmA3Sio8qZoO04qOK2SCt+KhiNkgrPqqYrc6dZ/tLl/qM5tTc/XDgI8ktk2I2u3WGVvM3yMRrzu1b3OFZ4N8mnQ7/cVh8+PdaMT5p7WvWH3f9m4hV5wY+BJ9hx2j9J0Cd23TBRMOxAEXjvzXBhHSEpOBmVgqweGLHxRNmz0UBeDKDiyfpe2/3mnT/k+++vbv2ZQ26Qz8dWDxYoVGq2X2DudRhIy+RDnyDbAsD2sWKNNoEJdGSCMx8IqbwwJN8zKaRkEcxR0c6hkbptWp1CLBz4GLuQdFXXRn6M7VqxfXic58Cd0nXHu34sOs9Lv3p0N2g1Idhj0/9bH2JNnGAGlR4Yc+DtwuKViWQ7475JWBv5O7otQyWFOdSu4fEyPRoTO22R5HRk9BSAQp9rEojV8bQzKYjcTlEFRtHu16SuB6m1Zlepevu0pt+EV9PjT7hjIMYrAenDRNUxFPZU08FW1B6RZKvJho066LgLVISXAQbNiaXcA8flNUYLzmFgl4UCjUKOkiZmC+8+7/x73Y99Aqd8TukqM60eWPObGEqUIKPKf8CWPOj0XzW/OdoyprPsnnMmb1hbTepuo/3OMB243GA2YKZyYJsxQ9p+kuZSUjTX8pMQpr+UmYS0vSX8qDOV5j+Sr9okdeqLR0Ui/qllTS/FT+zXbAAFnQOF7tKhi4csjZxoGTr80/KtqINb+id78g9wQDsP3pMH5rfMPAnajdRIwrSKTXeclE8eQ/z9gqZbZF5H4vdkI/xAXPl/64Yqao5gVdQIxdZWZtQFHkQz9o95KugqEHIL9WYEnQXSAQdPOMUGsySwY8D2r8L+HPKBfmitDIeWvf1P9P3CiXEHdh7hRRB8Dj2oRipDCBZz1VTUVpTKDUVxaMwaI2aYdWqVd8t6QMoojMGtJ5KVCv0+BakGvgoUN6seVVtX6Ubib7rXJxnHPqyoTSjvyp5E0h/VYpiDe4U4+XO53gb4A6mjb5bUnhUSxqvMuAdjaNobKJUCDxHUTuozO1i/j4Hvh7pGTOmiYbOHOKOkPxuLsUazHkZz8ecB7bAHMAfU+YUy4M5bb3iwU/iPMEex4B9VamJSib6MXYWaXWKwaB9ozv+t9xPwFfUr82KvNr9wFOc/thbNqr/wL30I+5hJvdnH3GnUa3BvD95mfdr4TDPjB6bdnlwsHMuBw1xKk2yBvN0MfZh7NJoNYB12J/U2iScCP7qBkjxiqHEBSgfYxo63B+1v5Ff+qglPaurXOj9v4qHxsEqpsnL1uDcCV7O5RQ658CXwGaLRVU05YlUtUoTy68I36084zZjf5ug3R5v7Me+W0XvZezA6TPlUgTnSCRK+BAgrDjJcqsMuCIk/dS5XH5qVbuU0MP73wUddNj6oEGblGb0TTxiuI8oWK8colIm0d1UgClX0VtDL9CQyGCS8cF7y8YqtfHKBH2ySEfc0ODsSxR6+WpClBoySOF2XpmDO/ielb3hSKeXCcf+o9PqE4hphtSnzMa+MopEAOzToBuR3VFEquEsiIOGvN4UNviZSvwZzfLoK01fsGZQwtjAVcXuqxyayPYxJnCTd4VM4KYoeQXDLfqX/rbp6CnZnikOm8eXHm6f32C4Kor0Ash5QvWIO4oEaSyqgXcJM3FhRNohSr1exTHO4udywapmlV8G7hYPWtT0j8xr+V/CDKyYOkIArKS8WHUs2CiBSlbakyEX+BBwdm4uv/ndQUl6fNRFsZv4e3HctjGtqgMVGFAfBf/vZOr20L9hDLfncamx//Xn/0/9+ZnzjgqsP3+mhq8/fypbdwrQn//Bq1V27R73lh680jorfbI3Y2xnvg6iC60jH4uRjRq+dubL2TrSGv35P3lMezDiz/aSmdWfP307bXD9Qu/Pv4AXldTCyZlAYwfLzgQJ158//qPPpaEZs8Q/l6uw3zf9/Tab6c8/lpd1QwuHdQXen792s2j9hAN+QQumvXh0uphhJWM7s6D78+NahrPBOqZlCqw//yLR9uNLJk1AR1/oPGhfyxIfbKA//wJecFI1Bdiff3/R+h5tn62VLR74b8mOidvW2UKnCwyhsbwIYWua9Nvmc/ltUq8mTb93vuK1/q+aGy4tfenBGPMKzvfptGrMorN9NgcOnFvnbpGocr9PtsnAENdrE2PjMB/OoMRTNZa0eWDOgOR8WshQ2lyiufhioWUJHYavAgVJFya+yShyQ5vfM1cVcx8Lu0piAX31EwpR17IzDsgmlAxuOmvSX9fzP9aL4UKdqtEuNsz5oGzTbxcuRW7QqfPrQmWIETuAXi0UZnFqoMg/WotcKCdi+UYrY/VKuH/pPPHapYy/dnju6lBkrm/FqmmMw1P4FyGHp4jrgq9O7P1fafne/6G2sJ0lo2Ra4CiBR1Zpo1VRPG1vdvnX8hypivFZsPlM9B+/edGjGgfqBmxZNVKswYwbvMy4VDjMYLo/iCU7Fq7+Gm0CZr4UUSB32sitMxayYpFFfDORe+eoOK0+upmoZWfDYH0C/he4t/pzqnhCy5WxshmrXNYe/FzxK92ugR8ITUhWQ0Zj5pKswayTvMw6YBMrB9zKIm/VJTfRrUnUDzDwrKBLLwdIZyQ+Ctpx61S71znL0PyEyvlkx+ixKKHIwSnQiyw3IxXd9EFrmZdKanIeb6tf/LA9ak18wPb9Y+56FetRslDDXgDAEy0JwFUIAEC1WOSJUqaMu/9ExYe/XN6maCkZ2/bx84drXNswTFnBngMGAFzgAyD8Fy3laC74wepxmKPDC6weZ4KOrx6nm87a9TjlQiJjB65dLs+uMSltyZjOv9lAPc44Hd/uZrLOBooKpk6dWgD1OE23bmv1cscV+ZhaJ882rfjHIJuox9HyckdpC9wpkHqcrVVGDGt2LlU69mbG77/kSP6wiXqcCF7mdLMF5iCFWY/T6HH80touVaTLW9fZ/fFr8mubqsfx5mVe58Jhnm3W47i1elLtadEv6CQ/b7Rd3PkqhVyP48HLucaFzjmr1uNsruk8PS5zZeCm93s+z6v5z0ebqMfBfQjOehxMEZJ+6sL/C/U4P/1RK6Ztw2FBOzMmpAxM/eZXyPU4J3R89ThZbJfWKvU4R+OHvQnse9w7Z1LbKp19AlYIXo/DjM0FqDE5puOrMdmvs1Y9TubroCfz5/kHrDnQas7fNzwXC16Pw9QRAmCVxYvVuoLVuYVdj5PGpcYGH1Q1VQVuRPccCFI/uh/xkr5T0i0RHJD01it0cexjpBZsX9STqAw6cETMuJuT3Jw4SipSgHZ6seAX4L0x2mlb15vdRTpzmuhUvCTjMOfzsXdyTIks+SsZiqmwINPzVhCpZB5uMlMqjXeD1NM4ggP6lVDwL10qnTfdFzuXijlROlSpxhimjPbF9PpQ6nY4WwlWLuJi5fLZ0xOf+X3yXjC4kiF9ajP6GbsSMlA0kMC2RJxuNfEFkQHTdsQIwEQDMPX4+Ko4rToadKgDpVAx+OdwNyBBEWswS/cyj4aVkGujBimjjV+CPTo7jUVcN1clfBIjwVEY+EWhxUw9UcQtCtKRBkAE/FdIRxrwL7MjTeCEv7qEnnjqOf7MztEOr4OuMDvSjOuxYtR1XR+ftEPLFz1MS+1C0amTdv+5Yw3zhyEda7g47QiORpNshHKr25ia9X8elO0z8cDnGUtG3f2YH24J78x9FSOBgK8ZUFVfH0UkUYUyi88RjLyLNGDvoInNNXu5f8dDjhS3DiEjII1zuHhVXpa72jBDkJCohxvsz9tHxDSJni5b+XBN2XrpXZvxssweJe4Eaf9KEqzBtA68THMrWKZRMZGdHCUUKvjKKOO6x3lDrVEuI1dHQk4DVmkMSj1ebYT9BE1hQnllfyU2fkO2p3hj+9e+gy4Wvc7klX1AYoJigNp4Oh9hJPnBr7qxT0+75dn+6D+aNz6mNuBlavUoVvsj3p7ypLArieYTUPCYPSB4Bd0OaDr25AL8quAiHo0SeumQF2z4tw4XcdKkp3OZ9G73bgXZq897L8s+UHTU7tr0TpilQuNUMQkiMGrT/DG/1YJiYoALplCryYmUKjBLDPQzNm8jhDmTjeuRIMf5zUWuDoq0Bqfww8QwS42iiMuA/NbTlMYHlGJr1QAeGPqile+GHfH654zP/AqKUb0CStBPYNtxvGKegQ5zLnV+11w9FPEAWKV5wfbAm6NI4wGWVc8QHNTiUgLFJbrM1htZAWv8lpQ82rzhXxUesFJrMeYBk9/1hb15Ld43x6TEBtJquARasNfgCJqq8PXZKTpz/aRaF5f4bYor5jG771P6IWy8JUtBwe/IC3+RwoGfVSmT31nGxIoAVZ/Ym0A5whxK+h81RX45EkSqgkOeMIMTgi8I0uAs5jyec2rrixkNashmGF4UP/6xGd18lib6/4iIzJ/5DUzrE18AgX6UVg2iW1DDCEYigwUhMuB3NS9wrFf15Ow/XrkEra5e7caBhTM78Twfe1AOjWwuqlisrganadOhxqgzisjj8x826rI7uEon7JeNU1cv90DheD6vRqaChY1mNDrl4mpFPEGBt5wBpQ0EF6FMG9HryZoKq55Kl/x203lMl67z6evDG1aGS1zNy5gmt89ZvSYmCB2bMfxJ60f3UvNrTKugyEDA65NQnYZpvP42cXIaQWhxCSUkEJ3GxbvKviYrDwQqKpyXblD22T0erhpu5+yz7Na0AYcUxR7wxyMO5Cr7TxFJ5PPVL+RN9qEL6757V/bwqu4CMDScl6HY4uWI8PKHpDsUycdNvF7bdVrqldm6hbzes+l+5iHpzkbSPU8kjyjqNenco37Anm8NO9e7pX0oAJJiXiTbxbNiOwubiTkTihmztDy6hHmAL4/gmICQrV5CG7k1Ft4C+5L6Ax7ydcfFjbTAGT+qBY5wvlwseucVnx1zXhVr/7lBpQKxwElaPgvcQ/s/C8xvgUdX9v6na/J5z3nJZy+Urj7zoC1b4EQtn5oZZBMl3QhSoBZYlG0XFfj+iE+GU79K119tamNFC8w89igAQxW8DMUWbwFa4AHl1NUHjzot2eJeu5qkd+vZVrTA50pNO/fH9gM+u9DSt8ooSvoKgGQAL5KotkAsMPP8l61ZYFx/cFrgHsYK9CVcFvj6lDqzbjTyl6Zd2ftpY10p3cKVCk5Uq4lBwOy9VDzpihLT0IM06mSjaEDP4OJ3UpDzwfHpsUMUepUyIRlodKrix7ykbPuBV8d97zhDPqPzyYZ/Dxwn53pk9lnyXJq5EL8QI5UBxI4orICnNYoUYZ925MvyVwymADAoFfqoOFGMXguXPNcN8UGLvoR6H7zpWvHLugm6/BzJtrLaeyNGXLSc9SflUMSRfajRwhS2SeFTHKb1dBgj4QnDwPUjQnpVeuCVtuOfh0nnNv8peKHTwdGfqqDXJP7bX776w8Hl2AwBwCvCC95HjWXz96oRIoa5vBHefUVRxAIFEhcR3BcKGVN3051ccoVzLCkGWXAV54USojUchs7o/rhoWXTMyk2iIhAwNqjBYMFLO0C3G51eO5CKF8CMawxBKGS/7B/fPaVjBb9l4dNFo+e8pm8LOFA/wZYyI8UaQBXhBeqj8dj7Ui5bMO3K/nKl9lcLGhP7T+PEWe3pyfZSxpnwkDGjdhxo15EOTdArooiWAsZZ9Qag88nORWYecV/Uelz2zeo+U0PXNS5+zjGI68nYKj+XZi6SFVCkgZqsYGar/K4oUlZtjT5Ad8pc+P651a2ASa8m7260rbpMwD5AQieaXFCkHkDolRcCGVNfD0fIIpVFQoSBok8gRAQK0dxnZU9ENcoIyGg+46tXtWUVGJtx4NuQOnf8suDrzZ/E4CLMQQUFVj+pLVNMzgQGxkUCReBewIl5X08t919SxT00yPljIxoCxTBZZ70/ftEab1+W9+1LqClts4xL2zwND5TbtfiMzl91VrYiyLc3cyNJA+muwaVnahvHGYPJDrm9x5K0FnXSqKEeHrDw/G++iycnbl7Wc9sk9iOxXXtw1VzYSqFIJZAyOwtVLXLMx2R3HOdTLWXBj+e5bHbNG7pNGqoMmGOoOanP0akSelUpvj44rDuNmJeW+Xhm8NsxF1L8MtCge29CpzrmV8s4oUhFAFYw1DFqgCKl4qEV4JwFNjhY/Otrx5G5Z4be/lU8pmd6p5yeu+gFwiWNtoR98D+XlBdMD70PR6yNW+09q1efX5x9PX4WACaEF6YPFipjJ0KolLHxXOfGmOl2c5eJ8HqoJykj26CWKAqHhtRDy/8PRcDj3TWtPm+87TP2xcGAyGyv0laOgC+q+SLgfZa5Q+ZHwCPSl+7sfE7ukzo0dL+v4dtjASNgpichQBB3Xs0XxB1VF1gEHF9yx77qCfLAzd1FfZc18vb+ESLgfbzgbbNQg1kcATNNl41FwLhocQZ2Ry10NIWJgBVBqHjComK++5OPtTzvYNfSJiLgfbxAbTP6pCv+D9kCzedhlcYPauy3eEHrdvcXnlda2RYk8tqCSGvZgu6H5FW94i94z17oPXv73tHjBLQFzJhKAHVm4FVnqoKzBX0mHzrd9LpOOuVGg41Zw5sJ34bdCrYgkhe87ta2BUz/3MZsgYFXxakKxRYU/dIy/XnET9J9U2uk282+cMgmbEEkL1DdjbZgJZctKPMt8MS9Uc3lqUsa9wnXf6Fnm0oGAuUJNs7NP43QMAyIhoI4X2gcBg4OTolAP2XNEIVaFa1KSDavR7ruZQ1DJ1dp5spKJ/d3v3yB4+nYkaqRZC6WxVFk0kAMy9vQipSmKBI70CKl7wR+HG8Ur+QoMd79/beeF5Y1C1rWrZg6cbPOgR5fQl+LuJrXLnXxoDXf/Sa285l3Z5N87sl/YvKrrexRZMJAzg3YCjg0FmmriqDbtkgVQ4iHyiAC3IJiNG7Hy5ottv3qP65V53hx4tQIRkNtwGSZWhELyYib0ARfd21JQHRQ9d0dRVIGWqagKjMB8SWWCRSTDVUuP3qlOyvftW7C2Hfrvkynq27ymxywMMjWQGYwLzJMUSmaBzKNvfBzYokKtSg6l0o1ayKGYYLUIMd2Q9+ffj9fX7fdZ2mLIBfZrpN6elLQ5PfYSUFTojVw6suLU+hASnOv4tLcnUY0O7PTK16+NmdO65xG3fYzvB6QKA7UQo6RFeOAul6wUg9ODIvI0xYijTKWaE3cKDAoTIT9WdnYPGe90cGE1V3SnMTb38S0eTC+mCP8ySD+GEkxF8WfUCQboJiKoXibhaIHimyyTGeXFpNvjh/Vgb7alYNd+m++3RJdnTXAYbPHp9G0VyvixS4q8srTuWTquPyq6+oosgeg4uYFVDbTK6iNo2KRui6DKQ2l3qAEqy7FawQ8+15xypLZHZwCcuwanww/OimDXjBEdBVinx8nrwu+vLqSEHyCQhCIQ0Aur9U/atHutZedFosroLK0S0tnfJlSbp71i3adUaTUIAzVvVAXSYoiTwb+r2iXv2j3c0KT4LE1fw+aFvxtX89djrcFK9plrr/8KhEsBnUYRLbTgp77/negjRbtWlgfaVHRblTO93/bajegc+bErbr+WoEIWbSbX52HcezdQD6OYauzAKtyDWUdi9zqnhBwoMX5d7OfLNxnxarcs3P8OkwZM1KSdTbnTom1Y5oLIPu3eZH8fWCBVOV+7drBpX3mDckMyYKRJR40u2BTVbndSAUBDwr74uJGmtg1XCZWFFt39+TpU8Rzj2TKF33OTqGnO0OUakUy3bRaiHIFL1GSSq8U6cGdyGABijQzYoY8CHs4fZ462W6dodX8DTLxmnP7Fnd4Fvh3fuWyMYp4UHI5miWXnVGkqRHytTYPuUf4/mMLffp5Z8W0cKw/qfp8YSBnLhkBIHcfxAd540EU5Ou4IHdfHXIsYusG2frVzmcOj3y/gP6m3nptoo4OuRMFuVhr2swMv0T0lAaXqFZxMC7U9BLFgvviLoleYTDEaXU6pZ7kh6Gor4QCjJlgw0iUp8WM4jASZTSYvidGKobAk08YyY4kMVnu4CuJpHEGeM5QYZmUuaXuLa/vkoXbclq/XnnuLQRCtrAweIxQPCbYtf7HTIi2ujXq7D+pG6QLvhdd9KbFZa6nEyYh+iKOLyF6Pk7ghOjhmc+OD7yc473hUcLK2y0+3hAsIbr7RIu9Dql/SrPDc34/VGxIviNsexR5FseXEMWgsVJCdE5Pj9Zrd25AV0a5TflH3CbHZhKiOCCc6ay7cVZMiJb4cK3L88hVnjvK/dp2wYPgGjaWEL3KiwxTVKycEL31/9i7Drgmsue/KgqCiqICFjSioiginu3sJEuvCtj1NEKAaCAxARERDdLFXrH3hgW7oGLBgu3seuqdvfeu2M7/1pDdfbskxwLx//n5+9z9zp3dzdvvzJuZN2/eTGqyQ93KbV235L59HqKuNNOAAqJHOXHaG04a2g2/XkDU4URCfNji2l7TT3X5NNBR/awUA6ICKVdA1ELKd0B0gTorMTi+jXNa5e1xqg3z+vMQEKXrOB4Coo2kXAFRBBXeA6LtK071/GfTLPf0+KZxge8HZZR7QBSDgDUgikBATK+sXzUgeixqS8UGFeu4JXd9/KHx9eedSj8gagpDUVIi0Z3pInnBUJD0fwFR7oDogGa3Zm/d3c9j7oVGTwsvPFrDW0CUPv94SEBXSlkbrjaHoXCpAQdEMa+iFAKirTcsqxH/PN5tSsNetV9OHfHWkAKiCMf+4ORYUNlyjBy/SVCsQqL98bZaS3RHb4kyUiJzRO9RObp7DAvEigvrUnjYqF3bdp3KMMJ7St7E8sIokShpp92oALvGvqUY4eU7koaIhhenaDhLyyTCe/3EiCsO24+4rbB/M2t5v3mnDCrC24/QeOBV7ghs/hA+w0aDDzfSQwAGG+FNDOMKN8aFkZBvMnjIZdaL740/Pcw5+8kfzsPnFTjzAzl9yvAA+XwpF+TTNVK++ZeM8NIjhloRXvqyVCvCS3emtSK89KmkFeGls1z3CO9Xk0X5VxuHemR2adQ88cYPAQ8R3i1s7LK8N9XFous5eEXH+wezT8RQT4pa5+8B/w/cLKUW3kkJwCHWF5nij+j0o0SjJvqXs94PEhXWm8GVIWkqTTdwGLxhv/O/2imNwwsoohSOKs05ItRWEczPZmP+v8nbV9d2NBLtHmK9cK3Cl7rgqOap9YfKcNNiGU55GMBkCp2FsZR7wFF0rT/gIhIZll6m+yf55FglPXYP+Hmf/QOZ7Q4p1OI0Mb1so46amJWPNjC0ED3lqtbm41bedK5DGercxpnLa5/p7i1av3qQa82+76pq6VyJ09mK+Rf8RZkeKwZd3iTpoqVz2+2OSK3cU+mzx7R/qNOJUzu1dO7xk6cffvSs7TZNMv3Vp1z/HVo6N/y2+8HYP+1dUu/db5dgnLkGIVUmSO7/FiyQjnvjP+WaRZZvnfsjEVIV0ox2nqec+czYJ2NQwKbFcPRChGRMkLLup6/w27pdmN1/rJOdyj8PIZkQpBe1ekQ1ed7QZ6o0XjRjSmFLhFSVIP19x27JtEFmnqkCeF1Kl57RCMmUII1uvFMWee+UaF2XC23XfT10DCGZEaTXl45smbq5jnvezxHWdy1ljgipGkGa3Cou91SQwmXfwTHPOx1eWwchVSdIzk3OuZwOWeC/9PSb713XbeuLkGoQpG22fx3bmy3xysnYMv1m1SYVEZI5QXpwDXqw7eIWr20O/XyqOO9ahpBqEqTTeX367uqX7pv24fWQ7pkJ3gipFkGyvPJheMLTIy6Tqu2b37bdpZMIyYIgpc0PmWm/6bPPtmXC4c9Fe4cgpNoE6ceTOVaDLylcsk5At5tcehWIkOoQpM+F+V/s2hk5r5UPKQjYcREVm7oE6Xmth9PbW0z3XP/5ku/lT1Y/EZIlQXrZTrRk++Z44bJTDu/9Gsy+hpCsCFLTPj3nwC+6eucuOfX6tuQEyi9rgrQ6uvlBmwFecFqHJ032NDCLR0j1CNLVkDZLrRadgzekzanwqV6/SQipPkE6srJ91BWPENHWjeNjodbzEhBSA4LUSzHqnV16oteBBj/G7bOdcRohNSRIYxxWD9/svcx1nuqbjbCxeS5CsiFImwaO9oif0chrs2Xfdl+T5qBMaUSQpKp/zptcXOM8S3li+cQK+1DZaEyQKn4wdWt3ajS8JmZNd4uENrcRkoAgdepvlj888JRwm8m4XSOz6g1HSE0Ikm2PNx3v9hzpuvDsi/v1ah9ZjpBsSX5dOzPIx/lveMnKpKDTEe+HIqSmBGn9999WnB5s5b2wwlzPZ8nHXiOkZgSpbs5hRVuxucv8d8lJfR3yMhk+TXOIxac51sNLeKD7DdfE81UEf1ayP8uDT7ONTR3WDc3NXnjspOviTffGnW44fjm1GZDrWIVMHgKoNMK2Z21HPCEg6hcJpOjJKFWEWCZDFB5RNUHHciN0ZQgcGrNPEUHQ1Y//IIIaKwtQXQ46tCmEoapK/YqOFNUzwgcC/LY/Xtl2MBkwE15ps0c0f2jz5zyWM+K71WShCLJBAQoBHhZDnKjaSr26inQMkCCigXXQDpEEyyMUcpUUC94j45PKsGY0pJwIxMh6UYw2Pg0Govj024np7vFt/GbutLQe99s9X2pSg+Z3mEkNRSTeox8IXFU54fo52iB6YVQoaS+MNsRECyliF3bcNkI8SiJAnB10W3mEWCXBFQG4GuGkeGhL6J9+B+tkOm4afX4gLfBHvBbQs56k8M49XxgXdhcg9ySYsDMSEvQErkk/iTJKitxJbr5L6EACwZpwdp6RZ16Y39qsxwe2LJkeTgWLfCcTLA2lNMCqygkWIuqE/dnOujnYuOKoOdtqinJXyF53izfxoHyVuStREk7gI4kMiwpn2iFjFoxzK2geJS2RGM2lCkbAQF4gCBUHR8mViLKRR4Zhh3ll2A84Ej9E0FWCYHGkYIREoIpWKGRShEMj5AgReR5/ZXQk+ih6HjgS7U4mw/ozYxcdBXC4ODJMgvF3sN9QgYLczcMymeRhYTKtOlzIPWgtrghECHS0jfTVACdsDJmg36Arwx+IICXK8LowaN/SHYYC9LOVOtb+a92hvtlYlyivjOFzN7scvWHCo7Gka6CSGssnIkiBIjQNOCWsYChUP2NpS5FHohU4VggPBwy5Fdyk+celDo2rf/NPHzP3xdcDgjfU/QAWsSCv864oEFSGcKKCyE0574Fqd1bWp0VXB89QAZpz5oDNYiq3pCptvdDSydFJMEHQztHJHsiyhd0W7PP4GS3Knb3LKkHa+B0tQ0/zIkCGXhGtNFjnwcm6nuXDuuLdGa5EHBu87IUYr7yKNtKWhqLqHbcC4MIX8RWX73EY6pV44bvg9/qJ1FohepZYKSlTAmFcy4C3IWWYltErbdIuCDVWCCJjJLhd1AOYrjEOFtNqZjovXtBdvjN8UwF1mUa8mLlMIwmlAc4QTnAClPplTrbArVSRBdcHnaHGm01tPnoLZ8ovBY19IrCnLlE0OT7MJUoRqTQQ8uBECJnThN+2g81vO7lI7POji5X7pLWNjJ81jTtA9UaxGomBLj66Bw5E1BKlhCeMrBBDkb8iflesdh1PRNkS8or6XoTrFq+T40SPlYLHzfSiSYquGFeBoZUTEIz/AaZ49YahSRNKoZbpFUX1kfGSSa6LLv7V+uAmU2q+qJ4lgGme0uiAgdGTati6Tg1PX7D067NeJfWUTGBo+QTWxF1HGJo3AVi/lM0QW2MAkXLRMkSqxHMCwcZ23hinI0MvVhOp4yPvRU/aPIA6LV3Ih5nTsohUbCXTzblmd59vEi5tvujMF/jvOB4Am8IJGCJR5eJE4TYDvac9xPbnDcOpIrPLgH1PMV5yaNVe8+d+E1Z391m/7Ivbjs5PF1p4RiKaEmGG61iFElmCa72rilAU2HKAfckcYBprW1fy/Jy++JB/Tp/OJ63uzN3EA2vHcrI2spxYC/KPZ/TiuV4ufLllnY1/NvZKNw36/Ll2q9/Lr17uEEInbQVmLoVhU4wwjDvZDKPostXNMZ13OG8e/Id1Rr88avuVOmj2ShQa+nSRhoZKlBIECkC/ALaDBW1heQQCOZ5Dg70mpOg12OIQ796NBpbQU2M6WUT6FmHxA2awA3iXrqBXgqFZUQXYSgNw9uA3GEqKKmmHb6GPFihouEGukChRbwM9koHLuAo9U0e2X1ASfrAKjUbLYyQhYCOycv/+xAu/L/I9aOE+ve3XB9T251X6YW2bmTqGuF6cjvEMONlxY2534coXn7ZeHRdY4ubglWFoBgqzkQiUyV8Xg7mkIeHmWuzXRLeC5ZEqSXA0Jh5Yl3kglq+v1lUoW+S55drFJ1hmr6Xm8ZgVvZe5/KUQeVcJPQnYhgBhG4jBRqiEXWwq4XSNpu/bdZL7prx77e14aaIr9YBBgEQhEwdLsKN7AF3A5jC3IZ9DM3xVWidCcSGPkUaFC+TIMkWpuyagZwRwjJN5EIJC1qNi6qAo1oqp/WDIpcRz3xI1airy/KjmCC0QgOykq10a7DojOqjy9fjQcNBVqvuMvYjpPuOXi5vO9AwIHiqBDkCRWwmMyzSBIb8oVvdZR+QaaJBTUkQNFS0gfKGC3GPnQ019d04e7F496tAf1AwiQkDAWzpUKu+zGEHLhROtrlFl6mCRA2Wk9DflSulHndwwiRJwcqOkitsSM5AoY5FXIIvqWJzVQC7TDVNJJklJ+ToCxmcB2mqH6TiPxmaBXoEwaz8MW+wgGSb9hOiDDxDHP0gM7TD6rfPMvQV7vu/I+ULbmEC/CrAxgV0uDShcOKHoqjFUuw0+BZyuLflJAc/akmTc9lAHz/VnVne1bVv5CA8p4NZRXCngNTWQ7zF4yOl5ePxA3lPi183hwG8us5LHf3hpkf+aB8hTo7kgnxhNQp7DWwaoOQl5GWSAAhI2yQxQQMImmQEKSNgkM0ABCZtkBiggYZPMAAUkbJIZoICETTIDdKT/mfstzTv6zLpx6dnrC5sXM1LeUOEFSh891ZOHlLdcNv7beh9tc3Obqds6o5ARV5/WpPK/Nh7sp1QqZzrlVVhmm62bNDIE2xwgS6kryPrqejX0o6e3FjtEBjigm/QoU3IK3R+4Boxdt4ehLP22+Rto+hgQJdPxeunseUHugccHnjw4xDPTzWdBw8uVxvHYzoC+jVdShVQVhk4oCbP7hqGQrGEol7nhz4VVXU1KhDZWQJQm3bMuMF9cyWtSg/5763U/GM9jWkRCX7+PJ9aOddsgT/dIE8Xm84BSFidKi5T6VVJw0PQtwCYbhplW9wJN7hn7Voll/09jYp0cvFe6tn5+L/1cUHnu5/YihAi8ITcAhg7ouZ/bSrN7iEKEwxMij0AznxALRNFNQHC2thx3pP3LyW4LxdseTrapVtkQdi0RkHZygpSl575uc0Z3hyKRwTYW2RVU4bXCDuc7ZTjPTxBurZw9Q1b+LR0QdJZzojNPs6e7l80wGmDLSfphjlJoOVlLxdVy8pue2d86bdNe7ZtY3+9qHa+d+/faxn/vfr2UWk7SVRwPp9/NVVy9FCureG85ebCl57p5B5f4LRd2WerVLGlZabSc5NklqIZJDQdMb/U0dsVvoc1uNj2t+qBv8JZ/uvc+k17XulxbTmIywtpy8ptGD+1j00NwizNtuyTe9lnutuJtVJd6NvQ4dIRYIcDjNIB4OZtr3gJ/jtztwc6liAWRkhj0kkQpDSYMpE5qiX6QjGOEoEi5FllXXO+IoLzYAqxSF8AnD4KhJbF6Kaoa2DYUHtxFhgP8SruG6Q22Jw7w2nm94ysL434jqC4S9gKmi4RfLm7O0c/UlXTOPRBB+1B4NgHnnA0MbYvVK5ukOj4eQiaA6Cx7cHJ0qKMnvLttl9DkRm3/pZXcwJ5n7v4R14vDp05GWnCvW54+0/aHbjp3MWE+D/is48QHEZ/yyDAwwRI3xuBAdIfof5hpI1y5uNWDxMowSRQX06TXvrT6MneAMCmxkYlr9SvUgs1V8OeZTCOu864sEa7M5uRKukFx5c1Bkit6mS9zTOEpJCGE8gUyZnWh4/VKN+Ocd3Ue/mD+DQ/q3lEVX+x5JmOI67wzZjiMqxM0zMhcr0bB0KZY/RZkDTQYYAsLmbQ4PHJPtn74KeeF1+5qXrEj24RRy1wbw/gLmFm1JKE0EFnCici0WNKu72ez61tneX8Y3K2rZ8qHH1EmR25QqzETv6h7Mkx3zQqDasAFMeHS4HDErUTPFopVyEpXKyuGMP+6LT7oZ8JB42XKJH5djzzRUbFEnigz+8UZhoYy7bqeO+ANCVcDNfbSyGBZdAh6LFeAjwT44Yc2D7K6JXnvsXnkgCpn8r5SkzGM2RwbDaGsjb8JDElRDJ1AORpQIwxDvTRWdz9ColxwidI+qIXmA6nw+EC4NCwc/e8in1IQ5weu6km351RRwn+GKUrEdd4nsw8BmDUQsGEYYMRkzjP4jSu6NOmycVVBUKyQ0rc5eNi56h7LtXPVQYP5ATbM/fa4nT0JHYXVg+p1kz7zqkX51Bq+0bIoqUImDcaOheleSrWBL+IPIOYpCnlSJoigvEUnPUmvgsE1LAYraHQ9KhavGU9ULGYGbtrD0PTxgBKqpD0BlFBFf4leQpWtRGoFFjqfJVLZdJONm1SJ6BxNPwAqv4D8UQ5dkvD8mIvfTmM7k0RP4Z//odQyvbDiwq4/2j+evACePXX9o5SK1d7wUGp51Xii1DIwQWfB+AJaeVIukBoFSoLlWJte3VEa10kg2PakvuuOYfGxs4ZIf1JREjFREhWL0i3ZqyWt7Ed55P7WNEbU10TBA0rTOVFKHs8oP8mZ7YKXjUYdIx0Aome9l3tlakxiCkGBJrQyNYIUoU8P/mL6lF46qIz0qfU4Ln1acdz/9CnBH0jsGL3O6In/CtHXwGnNPy7nQZ/SS0LxoCksx3FpimrjSlufvqrUr3JK16Ne21ts8DuWHLGOB33q3ueOSVpFc7+9PtO65Cw1usQDShU5USqMLUV9Sreh5a5PMYlh1acIUoQ+PWTwawL6dOInma1jhXpvp8IKl90fncO3Xp4awMOS4BrnkuC8ZklwmLdktpok5GWQzAaot0eqekC9PTKZDVBvj0xmA9TbI5PZAPX2yGQ2QL09MpnN9u6LfdVNv8B5jXY/GvnY5bZWMlvFh+1P5M7M8VmXXXvQCafYS1rlDKEGAnvfoyK3lJHXOjTpMLweI88NvQkomPT6fjzkueXzJhpmZSga/63SJaDsIwk3PVOAwRMjNp7QCyvywJMjbDxZmHNnYOqDQs+9Obv2bht1l3o6sHJvcaRExqwXzKYOWwoFCvQJoiwMWhdWECmPkuAlidBuT3j/HXCQj14ZEjAUXXSkWWCwUi6TBaB2Dr1YdFD0TS+a/qz8dVLknMKFvovM76TNuwyNZtOfJn1VEmUQMnzyZ5u7yKNHyNAML2Q8WLmgEGkU8e2IX4LujdxTr6WxpDKb2s0XQfExiNrtAkPqVNjUV6wMk0b6SEIpZtMMvxwgDQunXK+KXw+SK7SvUnV3LWG+yHR8TIE5BmJvJXraMEqKj8qYHBVoQinFMZ6RIWixLhLeClXRi+iGjdYlzMNH02o0l6oForUoxDIYrSClZb6wuv+avxv1V4oVmmcIUT1q8MacXqeUpwAfXf55sOY7Yris+cYY0pofM3jM6QVgDTeouoHzOMAKzXGA47yZybIswg+o7EuaSUBlX9JMAir7kmYSUNmX9KBS59uNuNNytWjnbROvh8KMVboX4afXBObBghawsatq4Pwxa6NHumS/LJR0FmyglskyJ/YEfZF/KRF9qHvBwPrkbmKkwF8hiXT3EUQQ79Btr5Be+5hzWMyCfLQbdJX/eyIoQl2AZVBD5xlRm0AYClQzdg+5MihscPklC1Oi1QWi0Qqe4eJIxJKB6/4L5i0/tOqJm7pntX/7bJ5N7Txj7IK/gblXSBJ4X8c+EkEyFJL1bDkVYepyyamoHIxAq9EMixcv/qlPHUABlTFo6alomViJbUHKUB8FyBuv+dHjQ8P2+K8btD7ryUtxJVp9VeIlgPqqJKU0uDOCkztDDYE7iDb6qU/iUWPXCKkKq2gcTGETqULAlahMrp4e17aXT+r3+rLsMxU2U5mDvxEQ3y2ilAZzBnAyJ9AQmIPyR5s5lYphTmdhBPqTGE+Q4aiQRyWRwbF4PcYeArlCPBot39gO+1vRHSyJtlYXrg+aEOG398OB1FhVAvXEb7Ugrfczj7hTqKXBPD9O5nmWD/N0qLFpVAwHexRxUBUujYyNRDxdhH0IuyLlkSjrkP+SyWMwIvpXJ5QUIR6LXwDycWB8o6vB1ntc052hc4qD8uO0QmnhoIxp4nJpcM6Fk3O9yp1z6EPoZoteWTQWeKhaGhnGrQhtGk4Z1Ci1p/e2f43uHtvvkEtVhKw+UxGFd44Mg3EfAl1WnGC4VSpMERJ+6gk2P7WeUVxg/r4P/gdNsh/adYpzoG7i4V18BL2VkjFSSQzVTUUxZUt6ayFECxKptCI+WG3ZMIk8QhKljBUo8BeqzD3xRC/PyABJJLFIYXde6d05uMbK3HCk0mv0Q/6lkCuj8D6G5F06Y28FQ9NQ7DOBG5F9YSiR6dKSq2DgktedxAY7U4mNUSeP/twcyyvbBwx0nzx7gkTUYzW1zoUJ+VZA722SUtxi2Hdp58aHg5a6ZDxpNWzhowkjSroYrgdDU1HknIF6pB0Mpan1yoGvG6TlwgjkYyRKpZSlncWP3Zfi5o0fIExyLdxUIHJbVPIpTMOKriN4wCqRE6sJZatzyWClMbHkQm9CnZ2by2/+NJEQHh95UeQk+lkZs210q2pCLgzIW9H/r6bt9lCf0Cy3T7Kpsf/V5/9P9fnpTY3Kqj6/ereaoz6/ei1Td/JQn/+ba4Pwr/FHhNm51kMXfW2xkseD6HzryCci9S41Rzlz9VamjiyN+vyzdl7f0/8PhXBu3b3ZUbWz95d3fX71Rk5U1pa7B6q9rVQ+9fmHPo3P6VloLczs5Fcn5cqaW4ZSn1+9gpN1i8uHdWVen3//9uP5FSzPeu/eemxNm88SWu2+sq7Pj2sZtgLrqJYps/r890w9nFT3f7ou8Nvkd1NYw7/86/PjyoYVnLXqMqzPP6Nj4pJa8+e7bZuxZdOoprWaGEKlCwShFZwILdYsP0+x+W2uwlatf/a4LFx/q9GGi0tft6eWGMDO9ynkMsSiM302ExacOxZtkUiLnifKZCCIK+XRYeGID6eSYKEafco80Bs9so6WWRBBi6grvpkidXACgq8YRoMudHxjYbVfQknPXNUpGhZylcAC+Okjbxw2d/hjgFua3dy8U9O7UWsd/ae2XjQXqqrwnx39R3Vxn3nD/sGc2c/dSupCLRapR6DoNYZBFscGVg9N0MuFqoZP3xBJmFIC9i/3/GtjO/fYMP/Fxj32Be/5pqQdnsIeBByewq/zPjuR7x/A+f2BCeXtLGkkUw9HCR2yVB4iDeYoe1PjyYvHbhIf94V1ttSNvdCOegLAhHwBU1Y1lNJghh8nMzzLhxl09wfSZ8fC0TtSHoWYL3EwGjtt6dQDWbIiK4sIB0G7HsHhcmWIg+C3HqrRyijsL2BvdVHesJEWj/52n+dssm2x5MYhql1DfyAwKlYGaI1ZRCoNZrlwMquXQcwc9FV6eat1iwLdkdHKESqOGTTxaYX0jLTVcILLHaXL90BRSZbKJWSHehKMK3L0FOh5hpsxBb4yOEE/L5XQ5Bze1vNbn0furdjNd/aDfcaDVNsLynXZiwLQlwTgGgAAVLXo5YmSpoy9/oSiw6F/4DsdPFKT/9zS9mTvLjRTVrbngBEAIA8uAFoJE0hH8/Qvlo9D7w9eZvk4qxK48nHSmZ4lz/k4/dZa1Q1KnCnaIfz70Ph/V8UbQD7OygSu3c0l5aP0qUkFkyZNKoN8nH0z79zOm37Lb8bb1a5XxvqYG0Q+TiYnd2YbAnfKJB8nJvXUvKDEg6LUVrmfjj0b2MYg8nGmcTIn3RCYA5VnPs6adce9/T//EO5a8HDv3buJLQ0qHyeJk3kTy93ZNaB8HJf+Hh3CQrKc1174fOXg4OS/yjkfZxwn56LLnXOlmo+zQpj3sFWHu94bkyTJo59cDzCIfBzMh2DNx0nX+Kln/j/k41T8YOrW7tRoeE3Mmu4WCW1ul3M+ztEErnycXPZgKa/5OL38rhc+2vpMOOvJElOjWcta856PQ1+b85BjciSBK8fkADNQylM+TlKrK39N9M3zmlcraM3gj+Oa856PQ9cRPGCVy4nVzrLVueWdj/MnmxobfVDaWuqXBe854C97/GDwa+pOSZ9o9ICku1KsCGceI9Vj+6KZi1SlQI+IaXZzYtvgR0kFYrScXhj6C0DJ69TfLH944CnhNpNxu0Zm1RvOOj7mTo42kSF/VQMRFeavfd4KIJX0w006SqXmbYD6nM/HIlJpCaP/UKWytvChaNCzsQXVAyUyhGGSEE9Er48lX4exFWflWTZWLp85NfqFV6H7vNGWqoWTHYZSY0FuaNJAFNMSsbrV+AMCFaLt8BaA0SrU1GPtq8LlshC0Qh2aChWK3Ye5AVHiMJVOupd+NKyKjzx4lCRE8xBo6MwwFn5dV5VQKIJ6jUHArwhMZhoAQ43HACrSoBCh/iugIg36D70ijV/yrZ6BBc+dk07vVJu89b9Mr0iT2H/FxBuKIR6Zh5YveJQ5pSdJJ0/a/eeKNfQfBlSsYeO0GXo0mmAjkFtzTuYePFrY03nvDuG56stFT0vCLf6due8iqAfK18VAVd8chtqPKZdefGZoy7thKuQbIsOKzF7R37ElR5xT14B4QOEcNl5ZuBXNNsQQREUrwQb7Sr+BTo4BCzwnjV2zojAmS8bJMmMYfxOg/CtBKA2m2XMyrXHZMo1cExn5wLhCRR+ZqJn3GG/IOcpm5GxdiG7A0kiVRIllGyE/QVGYQF7J2zfPq//vV9+8vtWeDxjp3IHOK2Pf6CjxCJnmdD5EC/Kjv+rEPD3tVGz5o/9o3riYWpeTqWZjGOWPOGvKE8IuwYtPAMGj14DgFHQjVNMxOxdgV3kX8RAY10uHhKDm3wpMxAmTfo7NpPe5f9vfWHbWfVnugYoTdzdJoeYIBoZLQ6MEaKtN3dv8NvAPDUVdMLFMRnSklKK9xNB6xrpthNB7srENCXCcX1fkbGGoGXoKP0gEstQwDBlFlzSfpjrWoBSZqyp0wMAP9W0UGvGjbqB/8uHu7tJaXtSeRUYsn1jsQofel7qkc64ZDNmiWGUKQXvgbWDIOlq/7Bmcg3JMSsCH85v0OXS1yXWfPQmxL/6pu+YNI7QWqhswJZ1fyJfX4PxyREoMIKyGSaAeew1maFEVrjo7rk2rZA2eMdRj6sH07s37ff1AlUv06bKC/2sUF/xvyrYFMgk/I1OmpL2M8RmBZn0iXwLkCL0p6X/UFCXliD+hCg45gwxOADYhCINznvV4zsnsV9PsbNymqV5VPv7ZgWo+q+P1fwR45E/3AqbN8QfQhX6wXIaubtEcRrQlMjohBCrsrbotHN0lt4P6Wvb23dI360J3izs3OcbHbJRDIeuKqiWstkSTZxcCjVEPWF1FXfJloyK3q6Nr8j63RFnDWg/FZmeLK2TK27JRh0KnbFytgwUosJIzaGoDzkUg0zp+ezNTaL0F3tV3r3G9qHFTqfPDHZSGi18tzpjGdslbvSbUH560ePyzjo/vTympMbWG1XVRXp8A6rRmsLpmuZ9b0SgF6pqRJR7HxjsrT62Zhy5UpBgvncB7or4N49LjtrglDps5ymV1ld+51yMmxCz7TysS+HLLOhv/bOyVbhr0+XPtVr/zwFAzToYik5dlhVcyJNsBkdzZoHarhAFWooWm/X/fevSmQjck2zGRbFcskj6bU+/Zf3J23XPWpu0/C1/JeUCyAheS0JeJjLWdnsXEzHHFjFhaDl1CP8BXzOIYh5CpXgJbOtnzb4E9Cf0BXvL1xcSNsMAXflULvCgppebJyt+8M448bhE6z2hsWVhgqGEChwWGqiX8zwJzW+AmiTk3xy/+7LHIwvxO17sRDQ3YAkMNErjUjKVB5EpAUJlaYPPljsPr3fruMy+4zZc2ZkfCS9EC04898sDQWpwMRSZvGVrgswte+jq/SPLYZWJ++Mzzj1VL0QKvufVk9MDOC7zWxBmp4w+PKHGJCQRJY04kKyaUiQWmn/8yMAuM6w82C4yKG2GBL7JZ4BvptjP+aentmnk5pzCrqaslNcLZO1omwxsBM/dSsaArjHdD94+UxWpEA3gGF3uTmOgPjnWPHSNWSiVRsahGJzN+dAvKdh6fONHM6pFrToFrckADcQ22ITPPkhfRdIX4lQh6gTo5ZjAogacjDN3VryhEnd4kACqJWBkcLghVysGSN9ax262rh+c7Z6yZ92z1lDeHS3Iku5TV3jsR9Jy9HkwtGHrErAuhZwhbK/EpHNF6CoSR4IChZVbzpQlxhS4HrNY3qd68TTzviU4H1YXW8HUX7+2v3/xlUvfYNB7Au8sJ3j9q/frvNcBFDHF5B7sPFQTjExSVuMG9h4KXvDTdTXVyiRnOMqVoZN5VnBDGRWs8CB31cEy09Dpm5eQixRHQFKhBYMFSO9BqNwqlfCS5XkB7XCMIAiH7CR/Ll3h/8Fk2Z3Mth/nXT1CljPwJppRpKKUB1F1OoP7RrMYusdmCjMv7apnua+CfEPbVPnpGl+pUxarpCQ9oM2rEgrat69gopTgYLymg6VWvQnU+UblIN5Vf+ciGZqoRh3wylA9vmnWJ6MA2MqbKL6LpimRtGHo8gchgZqr8XjB0YUJp1AFaNmSI6/HHjd2SUuuc/OvSRir4JasDxHegqS4MPUQReiOEAG3qm2EI6aWyCIgQUJRRuIgAIXo93zc6K2q6587JQQ8FFY3TaJtx6NOAPHfsMu/zzZvA4DzIQUUTrP6eoJ9iMscx0EwSIALXxn9uXzeiBrz90uNRrwSyPhQEKiGyzvh+7GJpfP0Fzq8vmEBqm8ts2uZ5Pz8fo7Zf4Lmrzrit8PccRN9IigRU12DTM0007YzRzg5Ftcdi5HpV0ri/3tv91JenXtPbmfgYdZkuYA6J6dqjV3WFzRSG/pqIwHYGqFp8YOjwRL1US030x4udNgtu9z5w5Wai11q3lb2gyxO2ULNKsfnBYt0pxOK0zPtNVRa3rhDpNsko7I1fyoe5JdUy1WDoCgpWb6BjZAdDpycCM8BZE2wwsLjnl6pGrcKMNsmeMyx/3l/S6SxVAKpqbAnz4H8RqTiY/N/ceOlWLdkj18xJdKrO7yVWxtUwqeGAac9E/ZRxNVyoJGERbOfG6OF2XacJ/3poACEjW4GWKBiDhtBDV/4frYD/SatXq/2gyT5zPr02TmlyYUkpr4BnTuRaAcfpp7N0XwH3HFLxQMOhxj4ZE2se9Jc2z+JxBUz3JHhYxE2fyLWIS2bqqtJaAd9p1b/nX/evu6SJT09O9ziY/iusgOM4wRutpwbTewVMN10GtgLGRIt1YZc8sTxWwLN3SjsvvGPnPfv3Sn3uZSR/N4gVcBwnUKM1tuDq/yNbcMeowtVPL7q6LK2pNN3l1epQKduCTpy2QFBatuD1xi1jH51q4D7PPj70i1rSkkdbQF9T8aDOOnCqs1ZlZwv2vPa/+SFgnGjR4+j3V04r+v8KtkDACZ5ladsCun9uYLagA6eKa1UutqBW6oshOUkWXuv2L/rbZHV0R4OwBQJOoCw1tuAvNltQ44dfwf2JbXymLLEf0k/5rTZ1LeiHKk9041z30wgtglDREOPnCzXNwNGDUwK0nnLkGLFMGiKNitVJ7btcvysu+Hjff5eLW93fZ4ydzjI65kpVQ9IVy8ow5BGPYHkHmJHSGoZaxuul9KuhP44VipewpBj/FrXI/tI3Y5/13xq2huLC7lPXl8DPwq8Wt0stj7B/2NStr3C5Q+GeZadiS9y10hiG3OJZN2BrY9Dopa3qoNW2BdJQXDykKgHKLSBGS69aTT3q5+K9ISLf88R6sT2toDbKZDeZOAwQEdei8T7vOhOAKIDquy8MdY/XT0FZ0QHxxKcJEJMTRrd8wo/vQmZsrcofB9lNoapu4kkWWGjk0kDmN05k6KJSsRhk7IXYObFosUwQUkQlizXhzTDR0CDLdkPD1/Uazr3r672qV1bc4I1vmlKDglq/xwwKahNLA6dGnDjViSc19zU2zd093uH0TmGEz9q8WR3zWvbZR/N60ECxnxxwjKwSC9TNekuU6IlhAXHaQhApCcNLE7f08w8SIP8tsdfNWX/mOK9f7wW9fJeMX/9038gM+tqcGBnAHyMouqJYH4bGoShOQVC8w0CxPQzJ9NPZ1UXEl2NHdcBdbEb02fTjxCGX7K/fCpo+9KWCXkHITCoSFutc0nVcSdV1Qxgai6LiJERVNt0raIKhope6roEoDYlSJUFnXZwwHogLNHtU+uIr71wXyqZvW/ij92xqwhBeVYh5fpy4zvv06kVAUAiEwA+DgJhe13/VpN1K8SqbdYdqea2YNc0hdHs7S47x8ZS0aw5Dp1FUc4AukisMbYz/X9Iud9Ju+wcbOn9qetZZ/W/X9QEbv4XxlrRLn38lVSLIGvRkPFFOC3ju+2C8gSbt6pkfqVfS7pNRMw65J72G18+IH7wx16uYkwr6Je2WVOchHNvFyTFkdpZhVm6HzCXbApMbuewP7WOkDvjpU4pZuY/iKy7f4zDUK/HCd8Hv9RP38iD7KziRnB9fJlm5hTmmF8zybYT733X4507XnwsMKiu3D6EgwIvCoZi4ESb2BpuJFYQ13Z02NV00+8gmnwVfcuOo4c4AiUwcSzWteqJcWyiIkSolAiX6JmKxAC7XQVsxAwbCbE5frE6u+LD9idyZOT7rsmsPOuEUe6mkcmkPQx/GE3KpZshlDxh6MZ6E/G+Dh3x0wMDoSTVsXaeGpy9Y+vVZL34gp08ZHiB/F88F+TONlP/DBnm71QHHBmdvcFu/2vx0/oSP86hf6q6URyuokFcjIRfJtYuZYZfwmtLoJbJUHIgLjYSCMPS9mEuiFKtU4XKFQqIk+KGq6OlCAkYPsCEk0tOir+IQEmk06L4nQqoEgYNPCMmIINFZbuLpMozCGdRzBgpL2rUzg3yc/4aXrEwKOh3xfigAQqaw0HgMkTzG2XXz1wyItpp4XHm37Xe3pW0qWPS1OTOxVAOi2XFcAdHpcTwHRM9sGWNx96OdMPNjXkUTm7gLvAVEk+PazOp3KMs1bdi9oCfqjy95CIhujuMKiCLQlFJAdG6rV4dNet1229NDXRhguVlqMAFRDBDWcNaquFIMiL57OWi+cUGk/676zTqOa7p2h4EFRBdwIkMXlVIOiEKrzkBH2vRzzRnax0e8VOJlQAHRZE6c4uJIQ3vr1wuI7prXLTXx/WznKV8eSGbPr3yoFAOid+O4AqKX9NPZOgREF24OK7waYeea4Zj3dUWLHQoeAqJ0HcdDQPR2HFdA9JKe6lqXgOiRgsC9z34XeB7s2XlS3VcfDpR7QBSDgDUgekkzvW7/qgHR0OMjPgWPWS+aFOo5qHPvydNLPyBqCkMdxxOJ7kwXyQuG6o7/X0CUOyCaP69PK6MOA0S7V5z8fUc9tyO8BUTp84+HBPT241kbrjaHIfvxBhwQxbyKUgiIHs+7MPpC9zm+e0PzWl6IWd3AkAKiCMcac3KsbtlyjBy/SVCsQqL98bZaS3RHb4kyUiJzRO9RObp7DAvEigvrUnjYqF3bdp3KMML7x9i14/6tOcQ5z3OqPPhRUkEpRnj5jqQhomHGKRoVxpdJhHfmjDHRG92/+WxtnOT7uvGLQQYV4e1HaDzwKncENn8In+GOwYcb6SEAg43who/jCjcOH0dCftfgIb8le7Wklf0oj9zfmsaI+poo+IGcPmV4gHwAZ1C9t0bK7/2SEV56xFArwktflmpFeOnOtFaElz6VtCK8dJbrHuGFGgjsfY+K3FJGXuvQpMPwejxEeO+zscvy3lQXi67n4BUd7x/MPhHjQvmt+vl72P4HbpdSC++lBOpPyv4qU/whHX+YaNdE/36OJ4DtUtlvB3eYoik3XWFi8Inr3v9qtTTuL6CynMc4omD9ISEhCg/YROHf5O2razsaiXYPsV64VuG7hhY61P5D5b5psdynPg1gOPUGFh5TbwLGaCh3ADlp2+NNx7s9R7ouPPvifr3aR5ZzfCUgQEohF6ee6bUcdVTPrOxsCKvboAU/krTZ+ZA3RexQhor4zy7J/a/77nff2vv0phzT7CAtRfx5n22rszFNnDdIOwhbdd8/VksR9xncfnhAgJlLQv2sb3+P9P1DSxFvmrkhzz73rPPG6R1NHgTeeKOliPtHd+uqzKzmv+XwsdSHKyu7IaTKBMn934IF0nFv/Kdcs8jyrXN/JEKqQpCud56nnPnM2CdjUMCmxXD0QoRkTJCy7qev8Nu6XZjdf6yTnco/DyGZEKSrJh87znfe6j/jhpnP0z+PfkFIVQmSpP600xZOLT3WrW8dpFwRfRwhmRKkiSn9AzYsynHbmRU08HDjFU4IyYwgee4d+ehulyzhmt7+xwZEhC9FSNUIkjh6+tNbyS1cV/wM21q3y70LCKk6QTJLNfO/22A4nNPn8BM/5fVEhFSDIM1rYNvj/CWB2+o6U1v4f57TEiGZE6TN3Z51v3yyit/Wqk9GXsv3XIeQahIkm0eep2ROHvCBDcNa5b0YgsJbi8Swx79p4x59Fa4YmGH0diRUByFZEKT3YxKW7J7axXfbCb8H9mevmyKk2gRJVCXYvEH0LPe1Pdr/Pb5+8yYIqQ5piXeE7ixs0chjV0y132zXdg1ASHUJ0vNaD6e3t5juuf7zJd/Ln6x+IiRLghTxce+0FpuXe2fMnf1wzbHFwxCSFUHqed1kTfLR3sK5W9qv//vsux0IyZogXRT8s3n9SgvPhJzpz+bcmpSPkOoRpBp/Ob9q9D7IeavDi9g6d91ECKk+QTJ9LX+j9N4gyp40qurEMDgWITUgSIfPjkh7v+yl29xrfx9MPpXkhZAaEqQXQZNHpqza45HUcu6Iht+/90RINgRJDb2rOFc+0zl76PidLt0/tkFIjQjSyB1vxOaVlnnM9hCdXuHYphFCakyQ0s46rq0y8opw84auvT+fuCRFSAKCpBrvJhavrOc58/HI878fX3YQITUhSF9X7re7dW6KT2bt10mPvSbsQki2BKlvqzFbbXoP9FvSULDCf8i3qwipKUF6YttI2X3VSuc1matcvkfYLEBIzQjSSeW/9g0D2/ttlngsVzZxiGQ4Os0hFkfn/bBunzN7V/GfNcjpm82e4Yd5cHQesanDuqG52QuPnXRdvOneuNMNx1P1vrHrWIVMHgIoP8K2kW1HPCEgihoJpOhxKVWEWCZDFB5RSkHHGiR0ZQgcGrN5EUHQ1bn/IFKvmlSA6nLQSU4hrM6cpF8lkqIiR/hAgN+2en4rgWzNNI+lD2+v+qyosZ/HGkd8958sFKlXogCFAE+QWcPqJZP0ajXSMUCCiAbWVjtEEiyPUMhVUiyij4xPKsM61JByIhAji0gx2g01GIhiRrMmf9lb3/XYaXPkfUaFAdQ+OVU1v8PMdCgi8R4SQeDK5IRr9iSDaJBRoaQNMtoQEy2kiF3YGdwI8SiJAHF20L3mEWKVBFcELL12NuZYJwV5LjAKW3Fo7gRfWjSQeC2gkT1J4Z17vjAu7C5A7kkwYWdkKegJXJN+EmWUFLmT3JGX0IEEgqWevbLGy6/fPdPP/9brzGtfamkGE/KdTLA0lNIAK5MTLETUCfvzmHXHsHHFUXO21RTlrpC97hZv4kH5KnNXok6cwEcSGRYVzrRDxiwY51bQPEpaIjGaYBWMgIG8QBAqDo6SKxFlI48Mw074yrAfcCR+iKCrBMHiSMEIiUAVrVDIpAiHRsgRIvI8/sroSPRR9JBwJNqyTIY1bcYuOgrgcHFkmATj72C/oQIFucWHpTfJw8JkWsW5kHvQAl0RiBDoaBvpqwFO2BgyQb9BV4Y/EEF/ogyvC4M2M91hKE8/W6ljQUDrQWZ/d3g90X/hqcujfEccn8ijsaRroJIayyci6AyK0DTglLCCoQL9jKUtRR6J/uBYdTwcMORWIGR21om/jRz+wm/troFzNi0XmFI3CVjEgrzOu6JAUMnnRCWvfGyi1saodrtlffp2dfAMFaCJaA7YLKZyS6rS1gstnRydBBME7Ryd7IEs67pqeURar26+2RlTIiu3GRRDS9vTvAiQtldEKw3W5XCyboehujNc2Tk2eC0MMV6OFe2uLQ1F1TtuBYDs+Za2v1djt8muO2emTTBKrELNQtCz7kpJmRII41oGvDcpw7SMXrmUdkGosUIQGSPB7aIewITtHb1pUHqq/yy37Wvvj3jcm7pMI17MXKaRhNIAJ58TnLxJ+qVTtsCtVJEF1wed1WvPh3eo1N55Rr22H5ol3qeur6tqEn+YS5QiUmkglMOJ0A6N3/aEzW87uUjs86OLlfuktY2MnzWNo+aumWCFEwNdfHQPHIiodUsJTxhZIYYif0X8rljt4p6IsiXkFfW9CNctXifHiR4rBY+b6UWTFF0xrgJDE9IQjP8B5n31hqHItFIocLrjZHvXjxs+uWav7GwTPev8ipLUBaZ5SrMtAmd/fHrTc5L76Plj33o7lNRTMoGh+DTWbF5HGBqbBixqymaIrTGASLloGSJV4omCYGOb1sBzaKww1nXpo0Vu2+y3Uzd1qrqQDzOnZRGpOMC8zrVIFk8fIsru9zRrcKWsUB4AU3EChkhUuThRuM1A72kPsf15w3CqyJQzYDNUjJccWnXLwEEtKu9sJ9onn+VjmqH8aeEZiWhKhBmuYxVKZAmu9a4qQlFgywH2JXOAaaxN76kSpzw857EzYEONqdtL3kEbYa2Uk7Uh5cRakH88oxfPRXQ7fb4wM+Xiau/V47PdF1gd8ym/IrpDCJ20FZjOFIZNMcIwPmUzjKLLVjfHdN7hvHnwH9YZ/fKoX1MHTWmJQkOfLtLQUIlSgkABaCLAdtqgLSyPQCDHE2uw14QUvQZbHOItvdHAEnqUTCeLSN8iLH7ADHYA79IV9EqIu5pYgK00AAcSfoOhQ4klbfst9NECBQ03yBUSJeptoOc0cBlXoQftyJ4MSsIPVqHRaHmMJARsRK52cl3w7eVer3UjPtf8tLFHAVXH9MN6OTN1DHG9OB3T/eb3gBo+rV1T260f1jxA1LqkOqYyDB1HYTYSgdL762IwlzQk3FyL/ZroVrA8UiUJjsbEA2s9D87Mf2h3flbiv34L2iuaSB5nZ9AOHWney1z+Uoi8q4SeBGxDgLANxGAjVMIzNpVwukbT9+06yX1T3r32drw00ZWaWxEgUcjEwRLsPB9AF7A5zG3I59C0X5XWMVFcyGOkUeECObJMUequCegZARzjZOaAUMh6lFHdlchaRrUfDGWVeO5bokZNRR4q1ZyrBQJww/3nghCjBX5zf1bb4mbyKIrqPmMvYrrP+OXipjM9A4KH8qA7UeRWAuMyTWAoO5HVfdYRuQYa5JQUUUNFCwjf5nkSc8nnPP9ZbTscuS6ZSe1jUY0QEPCWDpXK+yxG0MriRGtNYpk6WORAGXn+Tbny/FEnN0yiBBznKKnitsQMJMpY5BXIojoWZzWQy3TDVJJJUlK+joDxWYD232E6zqOxWaBXIMzaD8MWO12GST8h+uBTxfLhmSdXZw+G8+zslvxsP0BI25hAvwqwMYFdLg0osjihWKMxVM8NPi+cri35yQv/+47dkmmDzDxTBfC6lC49o0ueF66em8iRF66eqYH8hcFDTs/D4wfyl799H1212iu3HVcm19rewcuCh1R8iySuVPwaSSTkL3nLADUnIS+DDFBAwiaZAQpI2CQzQAEJm2QGKCBhk8wABSRskhmggIRNMgMUkLBJZoB+7Lnm2LCB6W5JlfYkh8eu3cZIeUOFFyh99FRPHlLeXrHx39b7aJub20zd1hmFjLj6tCaV/7XxYD+lfDnTKa/CMtts3aSRIdjmAFlfXUEWXderyx89vbXYITLAAd2kR+2SL+j+wDVg7Lo9DD3Vb5u/gaa5AVFHHS+izp4XtOO5XaVb0T2E6yb4rko7nZlRkr02mkKib+OVVCFVhaHCSYTZfcNQSNaw+g1zw58Lq7qalAhtrMAdmTuLHdWD3sHpvZ64VmlY+wCPaREJff0+nlg71m2DPN0jTRSbzwNKTzlRujtJv/IKDppmBthkwzDTammgyT1j3yqpdDF93pUjfVzXfNw4LGWY4Gp57uf2IoQIvCE3AIbe67mf20qze4hChMMTIo9AM58QC0TRTeC+Zr41fe7tv+uy7pjdjpNBW1MMYdcSAekVJ0hP9dzXbc5o+VAkMtjGIruCel0zfnl14UfPpIHjvGq9bEzLxSuPPg8IOg840bmt2dN9zWYYDbAPJf0wRyn0oaydyNWH0oQZgCr5Nm2OcPF4k2YtXLZNHvTlUp1T1KRH/vpQ0lUcD0fiLRK5GixWB8ec2MDSpQ/lb/c3Hres/9NnRdKYDR2tvO6VQh9Kvl2CapjUcMBUCRBpL9kW2ri0TV0tsh74bgmd89vSiUculd8W2gBCRlj7UJpo1sRv2PQQ3OJM2y6Jt32Wu614G9Wlng09Dh0hVgjwOA0gXs7mmrfAnyN3e7BzKWJBpCQGvSRRSoMJA6mTWqIfJOMYIShSrkXWFdc7IsgmpQAr3wXwyYOQuZeil6KqgW1D4cFdZDjAr6y5707h7aPhzgtiA07E1n73g+oiYS9gukj45eLmHP1MXUnn3AMR1BCFZxNwztnAkFWKXtkk1fHxEDIBnnOz067/tPLwSqxd8GjEel9qBwvic5m7f8T1Ymu1N1nmFjh/nm9mQvgzp9Xqf3jAx4ITH0R8yiPDwARL3BiDA9Edov9hpo1w5eJWDxIrwyRRXExb2ixXbf63mc9Or8ivsQrfJCrT8OeZTCOu864sEa6YcHKlkkFx5c1Bkit6mS9zTOEpJCGE8gUyJn323F5nNsFwcv6ufstiv1AtWBVf7HkmY4jrvDNmOIyrEzTMyFyvRsHqOin6LcgaaDDAFhYyaXF4fNnx9XZ86yVeefPjQ+9XbHSHmlUL4y9gZtWShNJApDonIpVTSLv+ls2ub53l/WFwt66eKR9+RJkcufGeymP8F3VPhumuWWFQDbggJlwaHI64lejZQrEKWelqZcUQ5l+3xQf9TDhovEyZxK/rkSf6IZnIE2VmvzjD0Mvkku6ANyRcDdTYSyODZdEh6LFcAT4S4Idvn9n396pDOwjn1R4Cffh9MLWtuTGbY6MhlLXxN4Gh9yiGTqAcDagRhqFeGqu7HyFRLrhEaR/UQvOBVHh8IFwaFo7+d5FPKYjzY+l9RLPnVFHCf4YpSsR13iezDwGYNRCwYRhgxGR+Z/AbV3Rp0mXjqoKgWCGlb3PwsFn4TzLXZuE1Debv2TD32+N29iR0FFYPqtdN+syrFuVTa/hGy6KkCpk0GDsWpnt91Qa+iD+AmKco5EmZIILyFp30JL0KBtewGKyg0XUvY6yemEqUMWYGbtrD6qhUQF1V0p4A6qqiv0Svq8pWN7UCC53PuqlsusnGTapEdI6mSQCVX0D+TMtvnaxy3OY94/6l09/OX6IWztKt/jK92uKNiwmvErbau8+ckdgo+3GXpSWvv6yekErUXwYl6KhjUwtoNUu5QGoUKAmWY717dUcpNmZTYrdtbTwOrJ21bnJh65NUlERMlETFotT2aEeTrPwmnikdO/XO3G4VwQNKUZwoyVMZNSk5s13wWtKoY6QDQPSs9/IuV41LTCEo0KT2w5Ai9OmHX0yf0ksHlY0+hQJSOPQp5J7yP31K8Cfosc33B2OcRNtDblh6RiwP40Gf0ktC8VDPvk8Kh6aAfFJKW5+2bXHmrk2s0m3mvvFb3kRPs+FBn4acKngNvw33nzx285Bd1lsr84CSOydKopRS1Kd0G1re+hSXGDZ9iiJF6NOPBr8moE8nfpLZOlao93YqrHDZ/dE5fOvlqQE8LAlapXAtCew0kH/iLZmtJgl5GSSzAertkaoeUG+PTGYD1Nsjk9kA9fbIZDZAvT0ymQ1Qb49MZrO9+2JfddMvcF6j3Y9GPna5rZXM1u5kn+SjT/d7bVY8vxLUveCsVjlDqT30bHXdfM8Fd65UsHW4EM7Ic0NvAgomvb4fD3lun3kTDbMyFI3/VukSUPaRhJueKcDgiREbT+iFFXngSSEbTxbm3BmY+qDQc2/Orr3bRt2lng6s3FscKZExSwizqcOWQoECfYIoC4PWhhVEyqMkeEkitAUU3pQHHOSjV4YEDEUXHWkWGKyUy2QBqJ1DLxYdFH3Ti6Y/wzOqt/qr81O3A3diOkSuW8h6bNakr0qiDEKGT/5scxd59AgZmuGFjAcrFxQijSK+HfFL0L2Re+q1NJZUZlO7+SL1SzSHuAsMqVNhU1+xMkwa6SMJpZhNM/xygDQsnHK9Kn49SK7QvkrV3dWs80WeyE+YYyD2VqKnDaOk+KiMyVGBJpRSHOMZGYIW6yLhrVAVvYhu2Ghdwjx8NK1Gc6laIFqLQiyD0QpSWuYLawag+btRf6VYoXmGENUvBm/M6XVKeQrw0eWfB2vuxBngc9AE+L4aPOb0ArAGG1SFmnIeB2isOQ7wjTczWZaV+QGVfUkzCajsS5pJQGVf0kwCKvuSHtTNhi5Bu6Mt4ZXSxRnNXLvt070yP70mMA8W9Dsbu6oGzh+zNnqkS/bLQklnwYZ31Mp3xJ6gL/IvJaIPdS8YWJ/cTYwU+Cskke4+ggjiHbrtFdJrH3MOi1mQj3aDrvJ/TwQtTEc3cmAIOs+I2gQiBi6dsXvIlUFhg8svWZgSrS4QjVbwDBdHIpYM+OGP5tqL128b75v5+Lpt9W05j6l7hS74G5h7hSSB93XsIxG0AIVkPVtOxZz0csmpqByMQKvRDHPmzPmpTx1AAZUxaOmpaJlYiW1BylAfBdw5bfTYlvnXm/pv6S+9XDtlNnVjxiSQeAmgvipJKQ3uTOfkzmRD4A6ijX7qk3jU2DVCqsIqGgdT2ESqECBzDu3vuv728rvuCcJY067LalB7JZrgbwTEd4sopcGcZE7mqA2BOSh/tJlTqRjmdBZGoD+J8QQZjgp5VBIZHIvXY+whkCvEo9Hyje2wvxXdAZ5R78Kb9K16psB9zddll0TDTK2oR9yDtN7PPOJOoZYG8+I4mTemfJinQ41No2I42KOIg6pwaWRsJOLpIuxD2BUpj0RZh/yXTB6DEdG/OqGkCPFY/AI4hN+09fdnj+6Idp17EJPt/WQOrVBaOChjmrhcGpwbzck5WblzDn0I3WzRK4vGAg9VSyPDuBXhsZyBZ77KHrrvbB54bWljxQSqImT1mYoovHNkGIz7EOiy4gTDrVJhipDwU3+w+an1jOIC8/d98D9okv3QrlOcA3UTD+/kI+itlIyRSmKobiqKKVvSWwshWpBIpRXxwWrLhknkEZIoZaxAgb9QZe6JJ3p5RgZIIolFCrvzSu/OwTVW5oYjlV6jH/IvhVwZhTc3JO/SGXsrGNqHYp8J3IjsC0NbmS4tuQoGLnndSWywM5XYGHXy6E9uCX3Vvm4bt5SBN/u7HK9zhtaQm3groCE3SSn2kOXIx+uGClYL1713GdRh27oSN2qoB0N7UeScgXqkHQztStcrB75ukJYLI5CPkSiVUpZ2FnvefsoWPpwmTBzw78joMMWfJZ/CNKzoOoIHrLZyYrWxbHUuGaw0JpZc6E2os3Nz+c2fJhLC4yMvipxEPytjto1uVU3IhQF5K/r/1bTdHuoTmuX2v2xq7H/1+f9TfX56U6Oyqs+vvp/OUZ9ffYmpO3moz5/x+a+r81IcfVZVvbXsbpovNU+6hAfRedaRT0Tqe+kc5czVN5k6sjTq8w/46quYsTfefaY4vkuj9mc+lnd9fvU1TlQulbsHqr2tVD71+T81ffDYJLYVnDhm8cnvvgpqy6ZyrM+vPsvJupPlw7oyr8/fsVbztt+2R3nPqtekpvjxrmXlW58f1zJsBdZRLVNm9flfLkhr9HzoM9eUJZJ679eFvi3/+vy4smEF51J6Gdbn72uafva0VSv/lJjZA/t5L3U2hEoXCEJnORE6qVl+/mTz21yFrVr/7HFZuP5Wow0Xl75uTy0xgJ3vU8hliEVn+mwmLDh3LNoikRY9T5TJQBBXyqPDwhEfTiXBQjX6lHmgN3pkHS2zIIIWUVd8M0XqGZMRfMUwGnSh4xsLq+Mml/TMVZ2iYSFXCSyAnx48KfLP3Gr73VLXjQ03XTWcWuvoP7X1orlQz1w/2olS7H1ybL2SB7S65lJSF2qxSD0dRa8xDLI4NrB68mS9XKhq+PQNkYQpJWD/cvHogKDgzGjhgZ/H+563yKSetq/igj0IODyFX+d9diLfn8z5/erJ5e0saSRTD0cJHbJUHiIN5ih7Y+nWTRlxf6HrmlkmJyZW7E6TVfIFTFnVUEqDGXGczBhTPsyguz+QPjsWjt6R8ijEfImD0dhpS6ceyJIVWVlEOAja9QgOlytDHAS/9VCNVkZhfwF7q9OsX/25vtorr701e2zam/GwAdWuoT8QGBUrA7TGLCKVBrNGczJLZhAzB32VXt5q3aJAd2S0coSKYwb9XefrlM4tmnsduPI244MR7cSJnkvlErJDPQnGFTl6CvQ8w82YAl9Jm6yfl0pocg5vq8/9Pc+3D1/nOztX6KoMMDpdrsteFIBJJADXAACgqkUvT5Q0Zez1J8RHPvZM7/XAZdeZUb1vVvhtTLmeA0YAgKK5AGgVOZl0NNEdiV8pH4feH7zM8nHOT+bKx9nN9Cx5zsdJvVqhuo2/pfeW1gHN653uOcYA8nHOTeba3TxVPkqfmlQwbty4MsjHCYY6vLK7/MR/fsqWwkz7Jp4GkY9zjJM7hwyBO2WSjzP1QxuzGTVai5L2DjBJ/GS3yCDycfZxMme3ITAHKs98nJ0jzT3335vgP3s1vPPJwpTKBpWPs42TeZvK3dk1oHycefPH2bWYHegy9cyoT0OeNi0s53ycdZycW1nunCvVfJw9+atuvUkPEu1M8BkbWrtrnEHk42A+BGs+zm6Nn1qBzU/9lfJx0s46rq0y8opw84auvT+fuCQt53yct5O58nEesQdLec3Hsd4wI8F39G2fxYN216l70iaE93wc+tqchxyTN5O5ckyeMwOlPOXj/B5wIlfc20iY0HH9xjuCKSre83HoOoIHrB5xYnW3bHVueefjVGRTY6MPSltL/bLgPQf8ZY8fDH5N3SnpE40ekHRXihXhzGOkemxfNHORqhToETHNbk5sG/woqUCMltMLQ38BKHmq8W5i8cp6njMfjzz/+/FlB1nHx9zJ0SYy5K9qIKLC/LXPWwGkkn64SUep1LwNkE+zAz3SZwmj/1Clsqb1Q9EYhFo9UCJDGCYJ8UT0+ljydRhbcVZWYmPl8plTo194FbrPG22pWjjZYSg1FuSGJg1EMS0Rq1uNPyBQIdoObwEYrUJNPda+KlwuC0Er1KGpUKHYfZgbECUOU+mke+lHw6r4yINHSUI0D4GGzgxj4dd1VQmFIsgfPdtXEZjMNACGeiUBKtKgEKH+K6AiDfoPvSKNX/KtnoEFz52TTu9Um7z1v0yvSJPYf8XEG4ohHpmHli94lDmlJ0knT9r954o19B8GVKxh47QZejSaYCOQW09WHbGYevmVaPZR2YL9uSNcS8It/p257yLID+XrYqCqbw5Dnknl0ovPDG15N0yFfENkWJHZK/o7tuSIc+oaEA8onMPGKwu3otmGGIKoaCXYYI96OuPd3p9VfZPkH9u6iU9+4GSZMYy/CVD+lSCUBtNcOJnWq2yZRq6JjHxgXKGij0zUzHuMN+QcZTNyti5EN2BppEqixLKNkJ+gKEwgr7ISz1ZrfmWI3/RDOfVvLOi/jc4rY9/oKPEImeZ0PkQL8qO/6sQ8Pe1UbPmj/2jeuJjalZOpHZMY5Y84a8oTwi7Bi08AwaPXgOAUdCNU0zE7F2BXeRfxEBjXS4eEoObfCkzECZNuxGbS+9y/7W8sO+u+LPdAxYm7m1D75pgGhktDowRoq03d2/w28A8NRV0wsUxGdKSUor3E0HrGum2E0HuysQ0JcJxfV+RsYfV7tOdDkAhkqWFYfb/EXXyrYw1KkbmqQgcM/NCZT3bvOl/fxX9V8kOvd+FXetB7YAA/sdiFDr0vdUnnXDNY/Q7FKlMI2gNvA6tfMnuocGbP4ByUY1ICxCWlt/m5x/0h953tHX8POdPvGiO0FqobMCWdX8iXP+H88vtl24OXJayGSaAeew1maFEVrjo74ujqydJTBZ7Tmz+xthtZ82+qXKJPlxX8tzjhv14+8DMyZUrayxifEWjWJ/Il4IxYWlPS/6gpSsoRf0IVHHIGGZwAbEIQBqcym8HpdzL71TQ7G7dpqleVj392oJrP6nj9HwEe+dO9gGlz/AF0oR8sl6GrWzSHEW2JjE4IgQp7q24Lx+kbUgZNXJHvnNJmmHCda7dFHONjNsqhkHVF1RJWw2jy7EKgMeoBq9unl3zZqMjt6uiavM8tUdaw1kOx2dniCpnytmzUodApG1frYAEKrOQMmtqAcxFcrD4/5WefV87uM59Vql+70hnqppqROygNF79anDGN7ZK3ek2oPzxp8fhnHR/fn1JSY2oNq0Uor08AdRqi8XqU+7kVjVKgrhlZ4nFsvLPy1Jp56EJFivHSCRz8jbra9PTLRu5JbmP8vro8fMS9HjEhZtl/WpF0+nxhZsrF1d6rx2e7L7A65sMDQ3/nZCgyeVlWeCVDsh34TEnncwd3PnP2yH13tEZKmGuebki2YyLZrlgkoTO11hwa+bv/jrYTflQwVeTxgKQjJ5L26Yy1nZ7FxMxxxYxYWg5dQj/AV8ziGIeQqV4CWzrZ82+BPQn9AV7y9cXEjbDAVX5VCzwqJ65nz/WvvXILHnyOW3jqz7KwwJDnZA4LDHWZ/D8LzG2Bj7yrd+F8aqFP7o5zn10q1Uw0YAsMeUzmUDMQbBC5EhBUphZ4/e/JM7NvvXRNCPh6emXNuE+laIHpxx55YGhPToYik7cMLfCzcze9z495AqfFjTT/eqxJSCla4PiRYX+MyDjotisoc2PGOuFJHpDswIlk28llYoHp578MzALj+oPNAqPiRlhgYzYLfCPddsY/Lb1dMy/nFGY1dbWkRjh7R8tkeCNg5l4qFnSF8W7o/pGyWI1oAM/gYm8SE/3Bse6xY8RKqSQqFtXoZMaPbkHZBL9K279+qe6RMFU64Leov4+wDZl5lryIpivEr0RQPRRiMxiUwNMRhmowE3i4ovx1epMAqCRiZXC4IFQpB0tepEPLixWcsnw3uMzue2VjV2qzTT2PZJey2nsngqzZ809qwVBtZq6OniFsrcSncETrKRBGggOGQ9On7rvsMNd7Y8qQnz2O7LzCe6LTQXWhNXzdxXv76zd/mdQ9No0H8Gpwgld1sn799xrgIoa4vIPdhwqC8QmKStzg3kOBkNF1N9XJJWY4y5SikXlXcUIYF63xIHTUwzHR0uuYlZOLFEdAU6AGgQVL7UCr3SiU8pHkegHtcY0gCITsePd22es3BrrNM8sf91KwvQ9VysifYEqZhlIaQNXgBKqqxhaYsNmCjMv7apnua+CfEPbVPnpGl+pUxarpCQ9oM2rEgrat69gopTgYLymg6VWvQnU+UblIN5XvOXnaDnhuQ3i/qkqb2OsedmwjY6r8IpquSNaG1cvTiAxmpsrvBavnppVGHaC2fkvHOX395DzbYsU1xaYHp3isA8R3oKkurF6GIvRGCAHa1DfDENJLZREQIaAoo3ARAUL0+eDJoFnLqzhP7vdleb3Wi0Npm3Ho04A8d+wy7/PNm8DgPMhBhQbA6oVp+ikmcxwDzSQBIuDq92WDWdIh4cqHL+d3kFlNpiBQCZF1xvdjF0vj6+dyfv2MNFLbVGXTNs/7+fkYtf0Cz111xm2Fv+cg+kZSJKC6BpueaaJpZ4x2diiqPRYj16uSxvb7f4lPdpwHp5t5Jb08VXclc0hM1x69qitsprDaGg2ZnQGqFh9YXV2/EmM10R8vdtqsShhyVfzXa/dVAyoLQ/0ujaBmlWLzg8W6U4jFaZmwvsbhay4ecJ7l31NuM3i4d0m1TDVYbYWC1RvoGNnBagtwRUbWBBsMLO759WhlxIzvXfY6z+4fY54x3+Q29eC/xpYwD/4XkYqD6cEWq5gDxgecZww8nmze3fwFDzBV54TJJF0/ZVwNFypJWATbuTF6uF3XacK/HhpAyMhWoCUKxqAh9JDp/6MVsMWCn48KG2V7ZAraJiraHblduitg9cc0jhWw+pl+7pDuK+B76nXyxn5OHlkhX4/P62z6hscVMN2TKPkiTv0hjWMRp36dVmYr4DuKW30aqo+L9lVcndb9qtnpX2AFjMoQB3gP9XQn9V4B002XYa2AcdFiW9iholUOK+DfQ5Pd+j256H7wdTeXxFsP6hjCChgXI1agHmp8UrP/R7ZgRtUtZnsSL7pO6fDjhf/Iwd9KORp6gssWQHmlZQvS2oU/f3f7oldOlz1fX73zWMyjLaCvqXgI6BVwqTMov+xswY6zb5TXVzl4TA1xP9yoqseFX8AWoDLEAV5OadsCun9uWLYAFy3WIF9+udiCEdNm9ZJNueEyc9+WCDg4pKUh2AJcjFiBytHYgmpstqDGD7+C+xPb+ExZYj+kn/Jbbepa0A9VnujGue6nEVoEoaIhxs8XapqBowenBGg95cgxYpk0RBoVq5Paz58juXr4x3HfHf7P+pqNONSFZXTMlaqGpCuWlWHoQiqC5R1gRkprGDqcqpfSr4b+OFYoXsKSYnzy6xrnD32G+qbtuXgu8m0V2voS+Fn41eJ2qTM3ek/abntHpH5nbLVddDuzpNrKGIbOp7JuwNbGoNFLW9VBq20LpKG4eEhVApRb4B2IBbV7DH7h7J/919+Xe/z791VaQW2UyW4ycRggIq5F433edSYAUQDVd18YOp2qn4KyogPiiU8TcJHxCa1Pvq9TKJz884DtoWGVoqmqm3iSBRYauTSQOc6JDF1UKhaDjL0QOycWLZYJQoqoZLEmvBkmGhpk2W6w6hn9xsHore/Wqq6N3yy7YEQNCmr9HjMoqE0sDZz2c+K0J5XU3NXZNHf3eIfTO4URPmvzZnXMa9lnH83rQQPFfnLAMbJKLFA36y1RoieGBcRpC0GkJAwvTdzSzz9IgPy3xF43Z/3ikU5+C9p4ekxL231ia/AeY/DIAP4YQdEVxfow9AxFcQqC4h0Giu1h6L5+Oru6iPhy7KgO8NPOznCNy5k73W+Hg+h71urmWyifVkHITCoSFutc0nVcSdV1Qxh6iqLiJERVNt0raIKhope6roEoDYlSJUFnXZwwHojLBePvkX9Mues8Qzb+Q3wVGzE1YQivKsQ8P05c53169SIgKARC4IdBQEyvGr9q0u6w/vUKDuVv8N1pXqeSSadKXTjGx1PSrjmstkDdzRygi+QKqyum/S9plztp91TDdUaJh9e6HDi3YmklswxT3pJ26fOvpEqkFqyulUaU0wKd+1ZXSzPQpF098yP1StrtV/PD0iFbq3jtP3YsFY7cPpnPpN2S6jyEY8acHENmZxlm5f5h0f0vlzOW8MIJb44rJKc6lmJW7re0/b0au0123TkzbYJRYpUjPMj+j1QuJAtTyyQrN6Oe0vnktA3+i76lH2/64n2CQWXl9iEUBHhROBQTN8LEmrOZWEFY091pU9NFs49s8lnwJZdaRbBygEQmjqWaVj1Rri0UxEiVEoESfROxWAAiTV8xAwbCbE5frE5ud7JP8tGn+702K55fCepecLakcmkPQ+tIuVQz5LIHDK3SeDU1DR7y2RaBsz8+vek5yX30/LFvvR34gZw+ZXiA3C6NC3JbjZTXYoO83eqAY4OzN7itX21+On/Cx3nUL3VXyqMVVMirkZCL5NrFzLBLeE1p9BJZKg7EhUZCQRj6XswlUYpVqnC5QiFREvxQVfR0IQGjB9gQEulp0VdxCIk0GnTfEyFVgsDBJ4RkRJDoLDfxdBlG4QzqOYM7MLUas9Wm90C/JQ0FK/yHfLsKgJApLDQeQySPcXZZ/JoB0Q73b02yPN/Rbc26P2ZvCfAQlmZAVG3EFRBVf0jhOSA6QjVfer3Xfd+DzT9kp0VYVeItINrKPcP4++IpXnuOnk6d/m+7ZiUPiKorcQVEUWhKKSBa5/KWjIG7LT2WmI2tsXPoq32GEhDFAWELZ6n/TSnFgGj71cImZv9U8NskH7dkwDbzJMMKiKq/pHAhQxeVUg6IqiesbC6dOM19XVcz+/GFAW8MJyCqfs2J07MU0tDW/vUCoiZTex1Orf3ZX51yfWjvWT37lV5AVG3DFRBVW/IeEFVU2PrHl3eT/OdbPOpz4mq1NB4ConQdV/KAqLohV0AURYX3gGi/5Scy2oZ6eCSezIqcuzzjdXkHRHEI2AKiKATE9KrzqwZEE7wP2/pNTfDO+2Z2J37Y5+ulHxA1hdXuqUSiO9NF8oLVnVP/FxDlDojW2/Cs0a2TOR5ZHp9WDbc0681bQJQ+/3hIQHdLZW242hxWC1MNOCCKeRWlEBC1jDQ/Nju7oXte1EPLIHnN+YYUEEU41p2TY53LlmPk+E2CYhUS7Y+31VqiO3pLlJESmSN6j8rR3WNYIFZcWJfCw0bt2rbrVIYR3m3NluZfGNLZeeXdLve2SO5JSzHCy3ckDRGN3zhFo03ZRHhreO25XDlkk8/spm02zOicfdmgIrz9CI0HXuWOwOYP4TPUNfhwIz0EYLARXkUKV7hRplkFWRo85G2PdjTJym/imdKxU+/M7VYR/EBOnzI8QD6QM6jeVyPlVr9khJceMdSK8NKXpVoRXrozrRXhpU8lrQgvneW6R3il9tCz1XXzPRfcuVLB1uFCOA8RXms2dlnem+pi0fUcvKLj/YPZJ2JcKL/VMH8P+//ADVNq4d2UAFzifJkp/pjOP040baKjwPkMSHQ4HwAyh67mdAeMwTPuu/+rDdM4w/TZXQeG/kAV6koRascIwajHJhj/Jm9fXdvRSLR7iPXCtQrfNdSeWp6UP1RRMC1WFGiPA5hPu4OF3bS7wOEJyh8gS7+u3G9369wUn8zar5Mee03YxfWpzPZhNHpxOpte4FFHnc3K1fqwehB6HnayNlfr86adHcpQOyvvdrgcnqv2WvEu88LT2NRmWtq5zoQbye2m7/bOGR88IWHvh7+1tPPA0wd7br90wmely/gt56CvnbS0c5eLUdt9e9z0nCXetnX7pJk9tLSz0VnhsMiVP31nmVaPm5Qbl4yQKhMk938LFkjHvfGfcs0iy7fO/ZEIqQpBut55nnLmM2OfjEEBmxbD0QsRkjFByrqfvsJv63Zhdv+xTnYq/zyEZEKQcmBR93qw3H/Llz+qbc7ZvBchVSVIIXK4S8GPm57r72Y/XxmxDx2hKUHaf7TpxwFLq8KzovxdVq5Qz0ZIZgSp26OwRa8tkrzT5idU8F3zqS9CqkaQXqR+dJ6xvosot1s1icvLQb0QUnWCNP3+rgrKDsH+qw84zjLv2nw5QqpBkGKnnlLPnufhOy/GtTBmSu9lCMmcIP2b+PFP+aN3nlN6PdmQOq2DACHVJEgPvLaLHr8W++19+iUg5kRhE4RUiyA1P77xsFffdP8Ny7Yfya81fShCsiBIT7O3vOpgPc1r+/votjFjnL8ipNrkCHcEp7dw3OMyO+XxP03PNtqBkOoQpIKVNYbbj+7lnxBldOH5b5noJ9clSM9rPZze3mK65/rPl3wvf7L6iZAsCdKez4MGN0qs6LfEq9/zioHvLiIkK4KkyKlwp3+D0e6JwxeJ7kY8bISQrAnSqeGfzb6d6iJc6Nb+bq2Q5nEIqR5ByrVbce/ix/PeK4MqHnz85N5YhFSfFJsh50wSI1bDaZ4N5CtuRaD7wA0I0q7jT8b5dH/nkjj53qiXLTNeIaSGBGl7o12LHDN/wDlbrrYwz/ntA0KyIUjC3a3M+tV94LF+6LjK+ZNr2CKkRgRpyMW4ZilP67rNMt1aveDlgO8IqTEp2M2dWk18Ot9PHZy2VfJ6ZiuEJCBIwUMj5YmOa9zTw+Ed6WsyByCkJgTpzyF/3g5Y9QneWe+AZYMRU8chJFuC5HXW//Gy90lwRkNzy8vRazoipKYEafXWPy7POTfDI+vYqqhF2yaaIqRmBGnuogMh+xLe+W++v2KMzUhrO4b30xxi8X4+/fxqn9KsqUdexFuVfOXoGB68nwZs6rBuaG72wmMnXRdvujfudMPxy6ltg1zHKmTyEEBNErbd7f9j7zvgmsi6viOgIILYG5aIFQuCioqVZOhdwF4DBIiGBJOgsrbYGwgqKCAqVuy9Y1t7X127rr2Xta2uXb+5M5PAzNyZJJsJxPd7fH67zzo3M5n8z7mn3VMaE3fwiU5HfAmooVImiKRSVOAR/RX0bExCFYbQV6NPNCIW9LX43wt5J2YeB7IcVt4JaqpmGtaepLDzEf4icBsqYHxCvOMyv6XZTWvOarmDPGPFuMZHXA+l/CTkHQcAxUDLymogvEMzDZo/4h4uRlkDm7UdI46WJyTKlRIszI++n0SKja3R8AlfhHqWIjAiNRqKYp+xZ8K8di4I2eyV4nRacZPcuqas9nvo6Q+FS5zHSVC49rHCtWumWUzNKGXs1IyWxEaLKSQXVpibIBoq5qPGDjiAjhIpxbgggHd28uu4SRQ2JnS+uMPH9FHnnlBChMRjIdPtNSucUy8YwZndC0o9McbstNQFA4Gr31OsUEnQT2qO6cVUIKFgrfvsklHxQwqyOGlLm6zBbfaSwdI8kw6WdsUUYO1jBQtldUL/1GY8RqxnMTRjcwXh7iXS153G2PiRfpWDN9E8jh8klsWp4ul6yJoB492ltLdqNJEIZF1Fo2CgD+DHiqJVcgUqbOSyOKzsV4p9gQvxRcS6kh8tkvGjxHxlUmKiVIJSKEqOLqL3449MkoFbQeWwDMwxk2KTnLGLLnwkXiSLE2P07RcygJ+oOffDcp7kcXHSIh270M+Arl0JKBPoqRup3gArbDSeoH5AX4I/FKrfAoJXRWAnnL6I+p5hulLPLoHXE15OPjJga/CCw+Ftm7YIi+RQWVIlkLHK8qlQ/QYgNAu6Jaoj6heGKUsnEj8SQ8Oxlnk4YOhHoZDd7nrOzz35SmjW48zkfu12/0M+OWBgC811zgUFispjVlTulYxOLHJaWnQGsyHDvNr6x/JBdloLbBeTqSVRFpULTV1dXPlj+W4urs5QkuWNHJ19QBQVnPG26bHNvTM/U3L5tA+C5PIVrpmCdH+xku6quZozbCk7dfAGGSK8RysYuS2JBeId1wJQ8rx8vSp3Q51/Q3ZE9mjvcXgKxSkzrBmLsUSJQHApAz+wlGJSxqAEy8aRQFmhiAwX43rRAGBKBTeNnnReEDrdr2ai5/17UrKbRjyY7qZpFkwBzmNWcO7NNCzHsgmupQo1uCHoXFFNW3AlfILntotHwmY9vXqQ7KJos4HoLkrhkikQ+osVoatau60Ok912coEo6LtHdd8JK+taP28waj/ZGsW6KUZ4BekfOBCSm5kSljDqIcaif0XtruSiHT9RYUvwK7C9CNNtjF6GEzVWCn9vuhWtWdEX4zKI+vpsFOO/oMlgYYj65GwTdD3tfDZnQWDlvYLtfzdqVaO2r5sxzYKpaZhzePe9R3cKnnGoS6sOwsF9jbWUbBD1tdmMKb4uiPribGinUyZFXAMDSMMXTWMkCjx7EK5sTyxa5z2971S/hWs8XrTsvNCOvC29NDfTt2Xhki7AsqpmBu1O3em9eWOzjPBLu6pwANg5VsBQjioRIwrXGeAzbXhMf97QjCpNHhp0QipGSxapuu7qrodI9pxg9cOZQvdSCx5W8pehkhIlhvfIRAXqghd5VhmBMKJpb2fjDGAKaR3udn77++NQQeZvze50Gn2zPwekPcJK2gMlRFqYfZzejePOusdk8lWzz4733NFGltvhR5XlJddZtz8hkzZBc5zisC1GKMa6TIpReKn6reHtt3qu7zewxsye+4JIv6YKyHNRgdCnlyQ2VqwQo1BAJgswlSC0QuQJKOR4tg32mJjCx2DOIT7nGwSWQH2ZXhqRekSo+4Vp5IB+Sl/QLRF1/dTjwNOAVSm0RtS1Uo2dBS4IKgIKCDfIE8UKYG2A4g2cx5Wg+k4zqEFB2MFKEI2WjxDHwJVIj341/xlyuabXvFFRCZJ6zn+RZUxPbMAzXcYQ13VmNt12HOS3281b3fVw5wlNGm4zVsaURtR8ALOVEJbzXxWD2diQcKMi5NdGt6LlMqU4OgljD2wePTz3MeXB/qA/0oPzxj5Menr/+3lKJZL2uXT3l7TIuUjoSsDWHwpbHww2QiTUYxIJp8s3+MetnTx4yrvXgS4Xx3mTSxHCxYlSUbQYK/KDyAImg7ml5j6QC6wsUjuKM/kIiSqeL0fdFIX+koCaEcDynvSSCdKyAb1VLVIZe6v2RHgfU4zd+9WAUlNqKk21xbZQAG5s2HQj9cRm3+xnx2MVzf65RTafsQfRzWf8sq7tTM2A4KBnaKlUIpWJHpepj/C+pTCaz3oi56hFTkFiNcBaUPhsYz6VfbVgoWBK/dcDTpRxr0CCz45gEPiRDnmV812MooVyEgta71KK1cDSvCgt+b8BW/I/MHLjxApIjYexgrsapiABYdFHoE51Mk5quKSmKCZjNomxdI1C8F0AhvLQDedh2C4wKBBWIwTDFis5w7ifYH14qfEY2anQ5et+C5hbd9Tlm13aLaMcTIBfBTmYwC6bAgqMxRmhQFmcUFR8s08Wp0pLbpLFxbVmna7k2tQvf1XzSMWSpGPGJ4ur/0phSRZXX9NCXt/sIafm4XEDefiLgi/XZ/8MLdje0npbzy6XOcjPj0ply88fqDXHnDjLAHXQQF4MGaCQhE1NBigkYVOTAQpJ2NRkgEISNjUZoJCETU0GKCRhU5MBCknY1GSA7rzc+NxInzRBbnTkw9rzeu+hpbwB5oVyHzXVk4OUtwZM9HcKPNLy1mZbn3yrmKgrzyqQ6V8ZD/aTeprTjfIyDLvNyUcii8EOBzRN1xM1ndgNGv1HTW/V+Yo0cGAfMqChSR0g165BY9dtELU93Spni107aiceEM3V8c7qzHlBcoclLYU3agZvaJUR7tV9eJQxZ20UgUQ9xjNWIJVF1LU1avcNTSDVQHhV4XY4E1ZVtSkRRbGCopSTtHRksx6dAufukThHSNrlcZgWMb5HyIcTK0f6rJZP95smTD7EAUr2rCiVSTGs50IL7YQDbLNhmBWZc6DNPWM+KlHU6SKyXGTlN/5jvcCNsQM3luR5bjeCieAHcmDel4FmbDPt6SGACIcnRp4AMp9QDUSSTVBwFnz5MWhUatmgvfUat5qwOibUHE4tUZAqsYJkn2LYuW4j2hyIQpbBDhaZBZTy67T1vcRRgqmZHw5srh81suSHP6Do2LCiY6m1RRsyKUYzHE5JLebgfjglr0sKy3BKXmvDVJ1+x7R1vtR08dt+I3DlitpPLk14QXZvuBtOSRVxxtfJ8zqnsExd5LU3TNfpM5zSI+DD3p8P3grnlloZNGPnO/JYDG6GU3JtEthhXMMCU0sDlZ3uI7TTXudc7p0/5DszZMa5UinnqpTcEVpvgkeYhlMCaAg51IhJDiFNzrTymHgnKM9nyVuVR8061Dh0giiRj8dpIPFyJtO8CX6f5rQHq0sR8WXiEeCSWCGJJhSkXmKJWkjG8oawSHmRZX1xvSvkxacdx4YcQGzySITXO80gQVUeO4bCg7vo60B/ZYtbU48dvfUkaONU4T/T/m6WSTaRsAfQTST8sq49R62pM3bPPRTy4gA866B7rg7Ci0ozKJvEHn8fgieg6GxcIx7S6qPCf1rczbMvkyKfU5pzYPfTT/+I67rwObTv4fHnpyYHqFdHdGsSHPWKA3wGsOKDsk9JZBjYYIkbw3EgOvOof+hpI2y5uPaRIkWcWMVGtH229z/Ou1c9ZEfYv471w8eTG6aWwe+nE424zrmwRKkSwUqVELOiypsDGqoYpL4cMIGXKI4hhC+UMBM7DvJuWepo0J75Hl0aPgkYQyZMMHY/nTDEdc4JMxjBxQkIM9L9VRWiHpRmmEPmqMUAcyykEl14jH83O/OF40PhnB0R91P/ehBNzqpF8AfQs2o1C6ZApDcrImFpGr3emEmvb5oT+L5fp47+U95/V9kcvkEpSsC/Uf9kmM5aD4OswPkj4iXR8ahZCWoLRUrU0y2SFUOof/2cD2pNOOx96TyJX9c/T5TXLY3IE6Vnv3givA50vW7gCXhtwtQAyl4ii5YmxYCyXD7+JtAfXmbh+jELT0aGFvC6Rh+M2hNHZj4mw0a7UNzK3wbhdQUYusJyNHh1MQwNklidQwiO8sI5qmihFsgHUuLxgXhJXDz470Kbkj8qBN7/k6rPyayEfw2dlYjrnG/mIAKwGlDABmGAEZu5idkfXFG5SZ+Dq1J8nUxKPebg4LCwSRrbYWEDLeZNmTAP2elz7iTvCKLuW7OT5HlARXKbluAkqUqSKJVEY2Vh+jdddQxG7QFUPanQO6X8BNJT9JKT1C4YbK9F7x5DXjdg2NvNdKK3MT1w0wbhnU+HNFvV6BNIs1XwTdRmq0zNVEsxrHPZTJVJNtXxkShQmaOdHECmF3xKgHst/rt50wPXesy0nHjUs/9/aMpMbcHY99nVO37NJvkvj8wPOB6UW5WDKXU30ommzNAEncvpxymNTNlAqhshjpZjA331R6mLa7KbKn+tZ+rl2htf9rN4SEZJSEdJqBOljsNehSxuluA3PbPpl8HDaqVwgNJ5VpROp9MaVbJmu+ANpoFhpAdA1Kz3ku5hjXPMJ1igCQz1Q5Ei5KnzLyZPqa2Dikmezktjk6cz0/4nTwn6LJ6x5/Lymn/5FUz3+hA7uk8GB/KU2hKKA0mRmcYmKdLTTC1Pb+34fnH2yhuBa3t1Trve8cVODuRpjxGCHtv/eu63/ttvuyqtSCjLAUozWVGakmZCeUrVoSUuTzGOYZSnM7X2aTOz9wmo24mbZDb3UjXfpiKJXjs+eMZvupQazoFLkMTqEgzTQt6cs2S2ChrIiyGZDdJvTyPqIf32NMlskH57mmQ2SL89TTIbpN+eJpkN0m9Pk8zmdO9lgb3tZ2Rf3R2PhzzxulMkmc3z9qy8K2OcfZZ//6Z82lpxoEg7w4CghOyvQ2L9Csbdq93EZd91Wp4b+BD84IjS34+DPLcWnLFGuWJkjf/W6RLS9lEDNzVTgEYTKyaaUBsrckCTlkw0ydl1t8/Uh5/89+zavmfz0Hvk6sDSYSKZWErvKswkDpsK+IngDqItDOgPy5fJVWK8JRGYC4VP6oEH+aidISGvoo+MLBcRrZBLpeFAz4GLhYWib7pR5OfRlduGhr//5rPIWZCnvremLpP8tOmhFCsi0dfXfG0jL3lSlBRkeKHvg7ULipGoiN+O2iXgbOS+eiWFJKWZxO5BIW/QLFTseiA89VTENlikiJPIgsSxJLVZDr8cLomLJ10vi1+PlCcWvUqW3dP7/C68OXDWcQcMxDAFqDZUSfC3sta8FWxDKUQj/GUxoFmXBt5SZcFFcGBT5BJm4YO0Gu0luwjQi0IkRUAHqSLqC5sQoP27VS+FKFF7D8GqLmavzKl9SjkK8FH5n4PU9N9nsaWm75ul0eatzB5zagNY8w2qJrGVA6iHacsBXDlTk8XZrh/S2VejJiGdfTVqEtLZV6MmIZ19NRZUp0lTqv27rZTnvMD5WdetBrfTv10/tScwBxrUjYlcZSPmD1+ZNMRr49+fxO35q9+RO98RZ4LB6L8UqDzUv2FgLc1poowfmiiW+QbxE4hn6HdWSO19zPpa9IZ8lA/oy//3heoPc45jGdS887SoTQSivjmHdnrIlkFRB+dfTWNK0F0gCXTwjBfJUE0G/eFPb4gaN13Uw3f9xBbD2kfXzCWfFXrhT6CfFWoWOPdjHwvV7wEkqxhyKtSv55RITkXpaBRarWRISUn5aUgfQD6ZMKD1VJJUpMCOIKXARoHSRrp5aG3XbirvWWVyTyf4NLal9FclHgLpr6pZMQV1nrNS55E5UAeVRj8NSTyq550gUWIdjaNJZNKIEPh5g/v1h0PdWviNt/jd8sKo5+ScTRv8iZD4buGKKYhzl5U4N82BOIA+RYljqYM47QUJ4CsxmqCvo0RvFcuik/F+jF348kTRMNC+0Q37W+En4DtqyXan1nE5r4VzM0NbvXixzZ5c4h5Z5Pn0EnfSqimId4WVeBdKhnh69Ni00kHBLoUUVMZLZMky1NJFyYeSSyaXAdKh/yWVj8AWwV9dwVKCaCR+AUrH9R9z/MYufuGbve1TZMjoapR6w4h4WMY0cdkUlDvDSrnjJU45cBM4bDEoi6YSHqqWyOLYBeFGx+wv3fssEkxt86Ipb9Xl+WRByGgzFa5wTpFBCG5DALfiBM2sUmKCkLBTWzPZqTWtRkUcKngfesBm46PG7Ua1IB/i4dN8+GEK8XCJeATZTAWYMiW9NRGAhkTKIhEfrLdsnFieIFYpkvmJ+AOVDv54ope/LFwsI5wUZuOVOp2D7V3pB47k9fI90X8lyhUqfOKh5lN6Y18dUVebi2KfBT2I7IGoy81lTIiDury+GmywmkrsHfWy6NU7IoPdM1p4TZa+sG98pGpvypRu4qmQKd2aFV3OsH1ry0flHj0LmDej0Wrvc+GVjHWGayLqqgA5T6gccUPUFeYalANfNbKICcOXDxcrFBKGcRb3nRqN2/XTOXj3VOXn7jYZM4zfwhSsqDKCA6zKsWJVZm6xylxNsNKacLnAh4Cxcyvv1k8bMWHxaS4KXYU/S2O6japVbTSOgeaj4P/tipo95Du07nYbJjH2v/78/6k/P3WoUXH15+d1m8vSn5/Xii47OejPv+nAgGHVDwaHzt565ED5FwVCDgvRuZaRT4W8rnNZ2pnzPOgy0hT9+aWpBe2GRslCN2Z3H3K+u+eZku7Pz2vLikqr4pWGrL6DYTVB3PXnH/o5d9e4/pcDJrd6n7HLOeO1ufTn5zVjJV2jkiFdsffn37u1QYuJm5d4zRk7LLF671tbSrY/Py5lmBqsAylTfP35m619fD70gd+uywHdep9ZRynmKIn+/LiwYQSn1dxi7M+vXrEpzrr7Pt9pE8dfCXzb5pE5dLpAEWrGihC6pwm7rS2T3eYtaNb8Z5dLglW3667+c9HrNuQWA1h9X6Jcimp0us1mw4Cze+ERiaTwfqJNBoq4Qp4UF4/acEoxFqoxpM0DddAj49vSGyIUWdQXX9S1fAnwFSEg6ELFNxnhXWV2MfWsuapS+FroVQIL6E8v7THlUbPJx0KXJ6wf0uJuDrnw8T+N9aKYUOvt/eSl4u4GZGR4/NPE/7ClsSZUrpD3AqBXD4FpnDoI77FhJpQdvn1jxHEKMdy+/OPn06jUOyeRqedvv+1m0WoapXgKuxFSPIVf53x3or//Huvv/6vEjSUtZxpgKIFXlshjJNEsbW9Ku3epsEn0w2+N4NWLNhcfUM6TNA+g86p2xRTEuMpKjD/Nw/zhGXJi4RIok6tQ9SWKBrHTpq5dUJcV9SwSWvDdukTHyxUxLfituyiHKVTYX+DW6pKFVZv2aaX0zavQID/n5O7TZL0GviBClSyFjMYsXDIFsc6yEuuEWewc8CiDrNWqhYFuWZIiSsmygw6NWrWyz9M73rse9p0+xS2+uzGuspHkUE9AcEEOqkDP08yMFKTHQwOtVEKSs1hb26W7jpz7tkKwvsqEQeX6te9Vom4vAOC2BoBrEACAaDHIEtWoMub+E8J/uzQcMFUdtPXwtQk/b/SdXqJ1wCgA6vNsAKw5qTU03X+xfBzqfPBiy8dpnsGWj1Mxw9T5OKXK/Oz5+rc+PmnHy8UGlwv9bgb5OM0y2E43G2WYQVKBEjXpTZ+PM6HerF2xPyt6rxh+fOSDne6HzSIfh89KHUdzoE6x5ON8X/N1xKlG6wOWn5Sn9OqeN9ss8nGqsRKnojkQh1eS+Th1/xxYKuBiTd8Dra424e3b1cis8nHsWIlnXTLEM898HPvZ3ss8lwb57Jpp92DVv6P6lHA+jgUr5b6bhZtisnycgd7BCZeiLgm2l69ubbnmejuzyMfBbAjGfBxUEBJ2arv/C/k4Vo1cm417Nj9EHT1tk/j17GYlnI8TlMGWjyOgm7QmycdZ6yXrLCmXHrQ68WjCx3rP7TnPx6H65hzkmARmsOWY+GSYKh9noyj77lV1i8DtHeqdvDey23rO83GoMoIDrASsWHUuXm1Z0vk47ZnE2LADkuaSkDXIzv2h0icP+5FPoct1TwIFkr4KUWI8vYzUgOOLhl4SZSIoEdOe5iS3xEtJ+SLQTi8OfAOU86IHyOQTXVb4To9Htk5fkdWb8f3oJzlFF2n8VzYCFWGhReutIFxJLW7Skyu1T6Pn06h/gJK+agj4h8yVKX0eCpXoqn2EWIoSTBzjj8r1kZrHYWTFSdmBiZR5s1OTXgZ88p03rJoyZ0YLcpuXMj4gaUBF10SMZjV+A1+JSjt8BGCSEqh6bHxVvFwaAzrUgVSoWOxzmBmgEsUp9ZtHQikNKxMkjx4qjtHeBHt1ehgLv66vSPgkVB8EtX0W0GSm3oh6UyqkIw2ACNivkI404B9qR5qQybe7Rhx/4Tnp9Da1zdvQS9SONBN7LRl3I7G/X9bBvOzHWSldNeuaSrv/3LGG+sWQjjVMlC4HSqMJMkKpdbDjLOt9dxHfLW3nB3b90eQvY6jFvTH3Tag+AOiaCxX1jRD1ntQSmcVXDoy8G6REf4MsrlDtFf4dczlGuXYMHwNpnMNEq0o+hbsNVQSqJAVcYV9y62vTatMgz01xA5SlTx7yZyWZNYI/CdL+lVgwBdG2sxJtU/ESTeMTWQUhuEAFt4zT7nuMNpo9yqTknLyIacASmVKswLKN0K8gCUworebHzEveOfCGYPq9fSucnBZOodLKOjhJJYqSaqvzeZQgP/hWV3r1tKvO9kf/Ub2xEXUtK1FXptLaH7H2lCeYXYw3n4CCR+0BwcroVkDS0ScXYFc5Z/EYBJdLBwWw4d+JGIsTKt2DSaV3f3An1Fp6znfx7v0W43bUn0LOEYyIl8Sq+GDUpv5jfh1DY2OBCSaSSomJlBIwSwz0M9bvIIQ6k43plSDl/Poi54So/QFykUKYpkYQtYfRE7ztsQGl6F5VgheG/tBWscNvOastvVf/VLzr1PAD2T+0YviJusdwU+ZSG7vnGiJqP4BVlgB2Bt4SUSOphmXP4BSUY1wC71Z3ZqDHd8u+/kuPvmpaM3cDnxZai9UPGGP3F/rLu7L+co+SUSFG5s2UA01V2PrshNSpsd1r/wvh2n7VHMrNePmJzJfg7uKCvy0r/K1KBn5apoyxs4zxHQGyPtFfAqUIdSjpf5QUxlIklBAFBz1hCicc2xCEwunIpHB6ntz4albjOj6zlK9KH/vYgqw+7fH+P3w88qd/A9NG+A3A0Y+WS4F3C3IYwUhksCH4Suyp+jmOp39sXvLPrave6juNmj9s+/u/LO9HH5RDWtYXVdRXXwxqN3OgyqgLwkubY7zbmLi7o4v35AKfidLaFR+Jyp3T1ciUM7dRj0anTFStggUosJYzILUBpyKUaFOtWsWVmlslcH+piTvkDp+fkPeHLywNF7+qS5kme+xbviI2FJmQO/q5+5MHRvdDroHwFgFan4DKtIYIL9ssKqd5PJJfomESiExjol11/yI7DzgqEoyWrvAQ3KiOY2RXtyMZKfxafbZbxLP7IzbELvtPHskxmXzV7LPjPXe0keV2+FFlOQcEzWAlKLp5GTw845B0gyI5rs+b5EH7TgZPtnjW8kSDI7v1Q9KNjqSbTiQr2U9a1jXIImhZLd8OiFVto+1MFMkZrEhOnkPz7QxsJuaAC2ZU07LIEmoBnw7nGIeQLl4imro6c6+B/Qn5AXf5emDsRmjgTr+qBq76os6mhd7ng1PtXi9yujxrTnFoYPXyuSwaWJ0x938amF0DH2xWl9d30D7vjK3tGyU87jfcjDWwetlcFjGjXmQWuRI8XrFqYOdzHY6l3DsinLNGHdd/krStCTUwteyRA4JmsxIU3bzFqIF7iL+v8LYN9cp8sDb2y419sSbUwD/OfIje3e5WyKq1GVtLOX8sxwGSaaxIzphbLBqYWv9lZhoYlx9MGhiwG6GBOzNp4BvTndL/ahronXVp16c1DbyrkSOcYUlSKT4ImH6WigVdEXwaeqhMmqxlDWgNLvYkETEfHJseO1ykkIhVyUCiazJ+9AvK7vn81fPrhmTv8UhWfL2aawczvTK9lrxwTV+IXwnVKgBxOQSWwOOOqCWGNYWoEqYBQCkWKaLj+bEKOZzz/GPCO16+yvPd9Obalyv/tKppTEm2icXeO6FaydwPpiKiltGLGg0MYRdJfIpHpV4iSkh4wDBhlfyv4WuSQ8fPa/r7tRHSfM4TnQ6oP9VArnsFbnn95qpN1aOzOABPwgpezFzD5u854iyGmrz9fAfwo/ENCjiuX9gA+Aw4iuwmG7nEDmfYUpRlzkWcAMFZazQMHfVgjLUMKrNy9ZLgCGgb1KCwYKkdoNtNokI+ROMvgBnXKIJw33bc88kzqh4RrFtaShBf2XYomcs0X0HnMu2KKYCSsAIVo9UFXZh0wcxLBRVtCxxDx8d9cU5K9yAfAtlqZ8JDxoxaMaDt5D1SpRBF4y0FtLPqlUDmE52L9BP55Xuorr64vj1ka/jY9R/VS1yZ3owu8gvX9EWyMsL7NpvIYKaL/G4I7+1sU/QBWu3Z9NXWPXYBG/0OVdw1LsqFwz5AXAeaqiK8rwChNwIeZEx9Qwwhg0QWAREKikKFswj8MM568cBBIx1D57i3eHehiVhFOYwDd0Py3LHLnO+3QAKD8zADldcb4f072zDB5IBjoN0kUATO/BhUZoPNU68NL+Nf7Xr7PYCEgCXK67Tfj100xa9/y/rrX87WSJuuTNLmRc+QIKtWn5HMZWd8loT696UeJMkg3TWY5Ex97ThjMNmhsPfYCLlBnTRUL9rHhyY2QXL3TL/9dW/IFPor0U17cFVf2GwRngqEzM5ARUsQwpPQO46ziZYK4Mt1bpvLUy6OaZPdLHi1RSnL93+NJVdzlsP2B4N2Jy3qkjKpT25VL91jv9+WiLIB5ZYsb2KslLFDeEoAVhjUMGqM8GRzoBngjAk2GFjs++vVqJ3XD9r/HTL5+i3FvLO1r5EL/7W6hF74X7iks6PIsYH579ZHB8zOcLw66019Dw5gkrDCFDPHMGFshzOVOC6BqW6MGm7Xd5twL4d6EzyyCaqJojFoCDnU7f+QB3zwnGDustQA/8n3cvvMkMV/MK0HzOs+h8UD5vkYJrP094DvOdUdnnultM+kU5mX1rnfc+bQA6ZaEsY7cbywOSxOHC+QLqtM5QHb/pjQK7K2EklbGfLO3y3E+RfwgAEPsYAnMFCCGewBU1WXeXnAOGsxOXaAtUrAA65d2rplUvzboMzmVW8PRqqdMgcPGGcjRqAEWl3g+X9IF/RtMDn+Qf7vfvsG5e04e9KxvomjoQ3YdIG6hql0QZuVW76fqXwuaMOptWtjLJKGcagLqD4VBwE9JzZxpq5TfLqg3ahpHU5fPoDMSXv85bPynecvoAsAD7GAV9nUuoBqn5uXLsBZizHIV6dEdEETl7cOZT4Ee2+vggyc2rFOvjnoApyNGIGqrNUFAiZdUP57yPEH41oGpSx07t9T8bUy2RcMAcITHJzrX43QJBKwhgivL9QOAweFU3zQT1k2XCSVxEhUyXqJ/SpB1zvZKn8Gb1GEWZ5+FDyW4e3onqp2SV8sSyPqFiDWcxeakdIcUdc2LB5qB74caxQvZkgxdnJwnHRp4+/ItKYv93bqJiUffVlBfxZ+VdcptWDZubQyA94gU271GjDpWudVxkora0TdfDbjAWxlDBqDpFUV0G2bL4nF2UOi5ANqQTHiSfJtr32qFjSp0aG/ve7mbKc01AZE9pGK4iAR8SJrnO+79gQgiVDx3QNRNzYwKlqdCog/vk3g6XKKu8Ma+dz3WT9p6Yvxnl0XkUU3cScDLJRlUyBTnxUZKqtY6EDGWYDViSWJpPyYwlVNsyZ8GCYIDTIcN1heWPnt9Z//hm4IW1x2wbXUFeSgYJHvowcFiy6aAqfqrDhV0kaWhUySu/OYFqe3CRKCVu6b476vafcCitUDAsUhckgZmSUD1A3DxApQMcwnqi34MnEc3pq4aUhoJB/9b7GzfsZ6I981zdu2sfXPtH3W5Ptih1XwN4PYY8SKvijWQtTeAMUUFMW7NBTbIOquhslseyHxy7FSHehPW9Nu/IG789v7Z5yy884fdu046aeVEtCTigQ6jUuqjDNWXNdG1F4AFVcBENlUq6A+hopB4ro8KjTECqUY7LpRgjHwhIQ7PyfvXlfRb8fPFnU2pVssJycM4V2F6PXjxHXOt1c3AoJPUAhCMAiI7YX8qkm75QfVt5Wkd/GdkRPPezMvdIjpk3YdEJ4MoLoLaiJ5I7yBs/+XtMuetNtub/qO6PLfgleNXfB1TcA/5ExrY5J2qfvPWCFSEeElzCbaacHqvnnxs800adfA/EiDknYzfs7cPzJng+eUJ23rb1w6O4zLpF1jZR5KsWhWiqG7sxizcls1PtP04ouBglkv1l2JTOkmNWFW7svXq3I31Pk3ZEdkj/Yeh6eM4ID3+7AiGTm7WLJyBU/autScM80v3/p0vYmvbnUzq6zc7oSAgDuFAzB2I1SsF5OK5cc12DEtdbpw7uF1Qdmfd48ihzvDxVJRMlm1GohyZQF/hEQh5ivAkwhnAY40xWOGvAh9OL1Omex5e1belTHOPsu/f1M+ba04YCxfOiNqCw1fqml82QVR/0jXQO5t9pBXmcO77z26U/CMQ11adRAO7ssN5NQtwwHk41khH6Plch8myN2Whx/tt3G1z6rlDqcPjf0wj/xLfRXypEQy5HYayIXyos3MsEt4T2lwSdMqDkaFugJ+HHguZpIoREplvDwxUawg6KG08PfSAEYNsKFLGkuL6sWhSxqlQbU90SVLHjz4hC5Zab6LQnIbf69BJMoAyxnKLAHnQp8s/mcSMrO2Q7VLSSvcIRDSmYVCY56Gxji5fH/NgOjyal2uHl+9NijDpVTjNAfZMFMGRHmD01kCorywdI4Dom0F7x/Xv3wWOXB7qRNisUjMWUDU4aLqtPcCdcD8KR9r7Bg8cLrxAVHeoHSWgCiAxkQB0XvLhmSerWHtlTu5X9WT0gO3zCUgigPCFM7i9U03YUC0X5f3WbEHE7y2tVvbo2/mqgXmFRDl9WBFhsoqJg6IXhWECHeszBTM/nuMoOODw2fNJyDKC2TFyUdr2/j9egHR0vWstp9MORWUcXfWOpuzgl2mC4jyktNZAqI8hWEyW4+AaJUqK/paPd7gs4s3euD55XUGchAQpco44wOivJHpLAFRgArnAdFK85o8SnpaRZgW6dDl2J9WjUo6IIpDwBQQBRAQ28v/Vw2Idmo6+OLX8ETh7BdDXrs3HjbD9AFRW4S3LJ1IdKebSAEIb276/wKi7AHR4bY5zudVdgGzl3ne3HWi2jrOAqLU/cdBAvrSdMaBq40Q3sJ0Mw6IYlaFCQKi8vsrgifNqeW/ovOJg3fXCKLMKSCKUiyLlWJzi5dimve3iUxOFBf98U5FXHSXQLFCJpa6gM8oXXz9BkVgzYX1aTxs5dbKrV0xRnivBoy6sPHO+MAsr29BysGK2iaM8HIdSUNZYxYra0xPL5YI780fz1ae8XQJnRxS9mje8GRvs4rw9iQkHtzLjcL2D2EzBJh9uJEaAjDbCO++NLZw4+40DeSBZg95x2GvQhY3S/Cbntn0y+BhtVK4gZy6ZTiAfFs6G+SbtFwe9EtGeKkRwyIRXqpbWiTCSzWmi0R4qVupSISXSnIDIrxBCdlfh8T6FYy7V7uJy77rHER4g5nIVe1+qleljn8gS9wfHNh4YoQX6bvqHtrJ9j/4yJSK+DwlGJ3YH2eL32jACxCjm6hY6LgLykLst0DJRBV4hkBHo5+uz/9XjaY1jek9D9Tr04ieBwcFBJuEMLHJj8lblld2sRLu6F8jZ2ViMDl30MGf/IfMF7Y6+YJ6P4QRqB9hoDz1Y1BjhPIZKG3P9j97J3zZv8i2mvurOUal/sb6e+njcKkf0CXIqV0f9RTkjMStifB2gGT4WUWJG8qZyG5RjCJ7XPmrDt8kMaGbkx1nz5o7dlwRkZ3ZALFd26KG975e5cLujZh3q4jIvv93SLPqrW2EM/u0DetQYe+GIiLb/p/qNvGRa0PG85r7XPp883wRkT1kmXKjzZffQub23fb7y42DeqFLpYkl3x/HsyW/vQlNuVZpTXCVB+CUrwyxdL39PMXs59ZBM/uGr8tFknLQJWtiac2D6UtCNm0RbOw10rWxMnQfumRDLD0+YjUvz2qa96adS082v1N3PbpUllhqfKK2w+4VHn6Zw6yFh597rESXbImliXYbUsUHbyBL43fnHb0xsxq6VI5Yyl8f/bz1+rWeK8amT2uTm6pAl+yIpTbeqh+hK1sKZ13eWWfGe0zt2RNLXfrH/D561ET/rB9bFJ3uNC+PLpXXKMsDowd2Ot7eZ39cvQf7r/SwRJcciKXXpTp2mWSRE5LmKY/54+e0GHSpArFU9vnx2QMa1vXJa5be5PddDx+hSxWJpT1+wwt6N0oSpgfNnrDxypWj6FIlYunvtjarGueNCt5afsLos1ZV1qJLlYklfxtp6s5+jn7LTs9YX/l5/kt0qQqxtKR3fpWky0cEm1I+v5Ha/qyPLlUlll5UfJTWplKa/6qPF4Mv/Vv9J7pUjVha1d1xcFzYQWH2vgqHa7Vq2x1dqk4s1W+ZPX3q8BW+6f23tA+tNvwZulSDWOqXe2vXiVTnkNx1vuuuDqgFvqsmsXTq9nxnGxsLrxUWJ9tUt/Ofhi7VIpbSd6Sc61Nzsc/S8JvRds3GDUeXHIklhcPNk6fa3xLmzPqSdiD70A90qTax5Jq9+4DFxi7Ihgdb73d9/wrwYR1iaWvcwU1TPhR4LpQ/6FrtoVcYulSXWPre4NLcAf0Dg7Zadv+uio0LR5fqEUuWpyvvfxHtGjBhRJtdm72Tn6BLfGKp/ci/Tzs7xXumeZZWJKX0A2jUJ5bSLtex83VrFLLz5rF28am3r6FLTprf1flhtc2XN4QWuMxMbzt8IeCoBsTS5odlLj+Z7Oab9ULSsWyz5/boUkNiSf71xbfyg/yCNzfztI76s95omknUiMdgEj1Sz6+cvqhSwKxef1TzEuyZzYFJFMYkDqvG7t6Yc/Skd+66+7+drj06jzxLyHtkolQeA2lUwnTk3Zi4g0+0P+JLQGGVMkEklaICj2i6oGe3EqowhL4afcwRsaCvG/BeyLPJPA5kOazmU4DwvtNHWLL2LClsh4S/CDyb3M/F+/AZ79BJr19uqNS7JbkKz7huSFxPqvwk5FkDgGKgtWY1EJ5FpkFDSdzDxShrYAO4Y8TR8oREuVKCxf7R95NIsVk2Gj7hi1B3UwTmpkZDUVxWdfKtU9VvCrIGJv2GPLgQRM6J0H4PPSeicInz4AkK1/cMNrg+lcxoZ+oojVLGjtJoSWy0mEJyYdW6CaKhYj5q7IBT6SiRUowLAvj0E/7BtU8nJSDbr3TYmLY7nVK+G0E8FjLyXrPCOfWCEZzZvaDUE2PMTstnMBC4+j3FCpUE/aTm7F5MBRI+HCvoY0frlBahO2SrR7gvP0IZQa95Jh0s7YopwMJYnRGsT9rJy90ZzxbrWQzN2FxBuHuJ9HWnMTZ+ZN/Dm+goxw8Sy+JU8XQ9ZM2A8e5S2ls1mkgEUrGiUTDQB/BjRdEquQIVNnJZHFYLLMW+wIX4ImJdyY8WyfhRYr4yKTFRKkEpFCVHF9H78UcmycCtoJxYBoabSbHxzthFFz4SL5LFiTH69gsZwE/UHAZiiVDyuDhpkTZe6GdAK68ElAn01I1Ub4AVNrrLRvmAvgR/KFS7gd1RFYEde/oi6vqZpmgduCNW3Pe+lTJwZ8CHuLRnJ59xqCypEshYZflUqHbNJHxR+paojqibG6YsnUj8SEwSx/ro4YChH4Ufiee4dz10+bD/lkqLC742a5hAPk5gYAvNdc4FBYpKY1ZUUL4p4SPUooOZDZnw1dY/lg9S1lpgu5hMLYmyqFxo6uriyh/Ld3NxdYaSrKBa6e3q9Q28xs/PHrAkq1pZSoKf9kGQBL/CNVOQrjYr6aqXDOl0mzNseTx18K4ZIrxxK5jDLYkF4h3XAlDyrIjvZHFnp8B7x/wzwe+CWpJbtBrYocVYokQguJSBn2JKMSljUNZl40igrFBEhotxvWgAMP2GZkyP5osCdm1b4HQ/V0YGxpp4MN1N0yyYApzGrODUzzQs8bIJrqUKNbgh6IS6zPOeW7aZX653x5nd/fuQqx3KalOE6C5K4ZIpEKrNihC6pwm7LZzJbju5QBT03aO674SVda2fNxi1n2yNYi0WI7yC9A8cCMkdTglLGPUQY9G/onZXctE2oKiwJfgV2F6E6TZGL8OJGiuFvzfditas6ItxGUR9JwfF+C9ohlgYov4jxwStUP2V1z5t//pQML7etTnRi+fLjOkgTLGULMMzDoXXfey1/eDSMLe7h/sbaynZIOrbOYx5vy6I+noOtP0pkyKugQGk4YumMRIFnlIIV7a8+vlnx34P8J+99/raaZHtt5K3pZfmZvq2LFzSBditmvU29DlVRZiZIbn41Do6jwPALrEChnJUiRhRuM4An2nDY/rzhmZUaZLToGNTMVqySNUyfebwPq27EZyxt5L36mqv/q7kL0MlJUoM75GJCtQFL/KsMgJhRNPezsYZwBTSPnVrdylx7ObA5cOWbRuy57nRg5JQ0p5iJe3REiItzD5O78Zxu90c10WSBusUAQXZT8q8thlNrvEq1na7/QmZtAma+BSHbTFCMUYwKUbhpeq3hrff6rm+38AaM3vuI8ckq4DkFxUIfXpJYmPFCjEKBWTcAFNdQitEnoBCjqfgYI+JKXwM5hziw79BYAkUnemlEalHhLpfmEYO6Kf0Bd0S4TWedxx4GrDShdYIr948YweEC4KKgALCDfJEsQJYG6CiA+dxJSjJ00xvUBB2sBJEo+UjxDFwJXLgg8X0ZukdAhb23Guz73DkGrKM6YlNfabLGOK6LhlzsdmX/FdX1Z5Lk2sXfNj39Q9jZUxphNcIwGwlhBUCVMVgNjYk3KgI+bXRrWi5TCmOTsLYAxtSD/ciLu3bzqvaU7DarrfkQ4fNakp5kva5dPeXtMi5SOhKwNYfClsfDDZCJEQyiYTT5Rv849ZOHjzl3etAl4vjvMn1CeHiRKkoWoxV/kFkAZPB3FJzH0gQVhYpKMWZfIREFc+Xo26KQn9JQM0IYHlPeh0FadmAhqvl5zE2XO2JqC2N3vvVgFJTaspPtRW4UACCZzs8uH0wMXSWz7KZdf+OlZLNZ+xBdPMZv6xrO1MzIDhoJGoPkFsKjcvUR9Q28xjNZz2Rc9QipyCxGmAtKHwPA2Unb0S+FW62ON9oZrzDXRJ8dgSDwI90yKuc72IULUtWtH4UbxRL86K0ioAGbBUBwMiNEysghR/GCu5qmIIEhEUfgTrVyTipoVSmKiZjNomxdI1C8F0AJvXQDedh2C4wKBBWIwTDFqtDw7ifYH14/fGzKqX2rmz6NnjqnqHD9i6wfUE5mAC/CnIwgV02BRSWrFD80AZ1eph9BjlVWnKTQR4jRzyOf7/lv+rexhdLEwq6GJ9BznuXyZJBznulhbyn2UNOzcPjBvKnA2o7DtgxKmBBtenv/sx4aHTzcWdE3WseW9J+hNYc68VZBqiDBvJiyACFJGxqMkAhCZuaDFBIwqYmAxSSsKnJAIUkbGoyQCEJm5oMUEjCpiYDNNPVfcuiZVORfIf4v8o7noumpbwB5oVyHzXVk4OUt95M9HcKPNLy1mZbn3yrmKgrzyqQ6V8ZD/aTGp3TjfIyDLvNyUcii8EOBzSd2BM17dkNmgdITW/V+Yo0cGAfMqDt8wAg165BY9dtEHWwYcf8jtoxCETHdbzdOnNeUPCcFtOyrBf4q70chZ03Dw/mcBoC9RjPWIFUFlH3zyTU7huaQKqB8HrQD/zZsKqqTYkoihUUJY/IIdnB+T9D1rzPP/fv2/5eHKZFjO8R8uHEypE+q+XT/aYJkw9xgFIwK0o+mYY1YmihHXuAbTYMsyLDD7S5Z8xHJeJxo9dP7LrId+umi/bHbeWjS/I8txvBRPADud6ozjPwPLeZ9vQQQITDEyNPAJlPqAYiySYoOJsvnDv8pKZjwKSzTYPtX+V3NYdTSxSkcFaQgg08121EGw5RyDLYwSKzgNo675j9mI2DhSsdeqVOObnifclPhEDR8WNFB9Haon2YFKMZTqykFnOYYGLliEy2iZVSw1Sdfse0gi+TZy+pt9sn06pTO/8zgkMmmlhJFXEcFM8Pz2QbxTjMMF2nz8TKMVfetZkf7ew3sfxE92Z9DrUxwcRKrk0CO4xrWGCKM1DZ6T5Ci4iveTVp3g7B9tqdH3bLPjeyRCdWYjzCOLFSqpVDfZnkENLkTCuPiXeC8nyWvFV51KxDjUMniBL5eJwGEi9nMs2b4PdpTnuwuhQRXyYeAS6JFZJoQkHqJZaohWQsbwiLlBdZ1hfXu0L14KzjWKMviE0eiajDsgwSVOWxYyg8uIu+DvRX7hnyrfy8GVdC5navnb1hrwPFUcYeQDeR8Mu69hy1ps7YPfdQqB4E4FkH3XN1EHXfLIOySezx9yF4AorOlaQXe63Pzg3OadcoZUhq2XOUjh3Y/fTTP+K6LnwCundu1mDl1uB1Hu9v1XNvNIMDfHqw4oOyT0lkGNhgiRvDcSA686h/6GkjbLm49pEiRZxYxUa0g5+tlkXcKxM4/feR7m+C0skbtwx+P51oxHXOhSVKlUBWqviYFVXeHNBQxSD15YAJvERxDCF84QVxgpUPBAUVvPNWzHA547GJ3MqzTDB2P50wxHXOCTMYwcUJCDPS/VUVwuudZZhD5qjFAHMspBJdeOz7unnv6YqSoNR3d2YdiPAg42GN4A+gZ9VqFkyBSBgrIv5ZGr3ej0mvb5oT+L5fp47+U95/V9kcvvEPmcb4N+qfDNNZ62GQFTh/RLwkOh41K0FtoUiJerpFsmII9a+f80GtCYe9L50n8esG5Im2zyLyROnZL56I2pWu1w08Aa9NmBpA2Utk0dKkGFCWy8ffBPrDZXcvXbq99FDQ0uddFiOSbuXIzMdk2GgXilv52yDqdgBDV1iOBq8uhqFBEqtzCMFRXjhHFS3UAvlASjw+EC+Jiwf/XWhT8keFwJuCUvU5mZXwr6GzEnGd880cRABWAwrYIAwwYjP3N/uDKyo36XNwVYqvk0mpxxwcHBbys9gOC2trMR/AhHnITp9zJ3lHUGu2ZifJ84CKpJ9aPjhJqpIkSiXRWFmY/p1YHYNRewBVTyr0Tik/gfQUveQktQsG22vRSEFZN6Dh8b1souExPXDTBuFdyYZ0YNXoE0gHVvBN1A6sTB1WSzGsc9lhlUk21fGRKFCZox0nQKYXlD69g8vf/H7sTMi2dwf8O05TkVt/69epmdqX8ZZ02fEDHXJ9tjrYfBXkhws56NR8N5vo1AxL0OHdzD5O6W7KBlLdCHG0HJvyqz9K7bfEPTjc7pT/Ir/qy08uW0/uglRKSEdJqBOl18cDLMZvTwtc26rcrtXvJm7lAKUrrChdyKZ1r2TNdsG7TgPDSA+AqFnvJd7YGuOYT7BAE2hsjSJFyNOBv5g8pbYOKiZ5mprFJk8nZP1PnhL06Z7m6PN+WJLv2uvNg7z4N09wIE+pLaE4kBQpWWySYmqWqeWpb9yx4RNKiQLSvZ8HfBpvPZsDefrpa41Bro1G+6642GTd4+9923GA0gRWlMZkmVCeUnVoictTjGMY5ekErX06yOx9Aup24iaZzb1UzbepSKLXjg+e8ZsupYZz4BLIWF2CIVrIB3OWzFZBA3kxJLNB+u1pRD2k354mmQ3Sb0+TzAbpt6dJZoP029Mks0H67WmS2ZzuvSywt/2M7Ku74/GQJ153iiSzOadlqwaMnxm6+/OtDwfvf+lWpJ3hola+yVcedwhctW7dpiv3P9yg5bmBD8ELdCn9/TjIcxNxxhrlipE1/lunS0jbRw3c1EwBGk2smGhCbazIAU2imGiSs+tun6kPP/nv2bV9z+ah98jVgaXDRDKxlN5omEkcNhXwE8EdRFsY0COWL5OrxHhLIjAsCh/fAw/yUTtDQl5FHxlZLiJaIZdKw4GeAxcLC0XfdKPIz7qneI1y1hV47m82vNmVBn2cmeSnTQ+lWBGJvr7maxt5yZOipCDDC30frF1QjERF/HbULgFnI/fVKykkKc0kdg8JeeHzUbHrgfDUUxHbYJEiTiILEseS1GY5/HK4JC6edL0sfj1Snlj0Kll2u1odEs7uPv+4AwZimAJUG6ok+FtZa94KtqEUohH+shjQrEsDb6my4CI4sClyCbPwQVqN9pJdBOhFIZIioINUEfWFjQ3Q/t2ql0KUqL2HYNVos1fm1D6lHAX4qPzPQWp6wny21HTJfI02jzF7zKkNYM02qKqOZy0HiNGWA4g5U5PF2cMf0tlXoyYhnX01ahLS2VejJiGdfTUWVI/7ZcV7n2f55s14evBe5sQk/Xv4U3sCc6BBY5nIVTZi/vCVSUO8Nv79Sdyev/odufMdcSYYjP5LgcpD/RsG1tKcJsr4oYlimW8QP4F4hn5nhdTex6yvRW/IR/mAvvx/X6j+uuA4lkHNO0+L2kQg6nsLaKeHbBkUdXD+1TSmBN0FkkAHz3iRDNVk0B/ezMXJq+20y14HXG9PqX4/5zH5rNALfwL9rFCzwLkf+1io/rKAaPUPzan4sKBEcipKR6PQaiXD5MmTfxrSB5BPJgxoPZUkFSmwI0gpsFGgtNm/p0uHjltOIQvbXbbaPro9uULAJoJ4CKS/qmbFFNR5w0qdF+ZAHVQa/TQk8aied4JEiXU0jiaRSSNCoMS5vLG117Tbl32nulx7rp7wKYtMHPyJkPhu4YopiPOYlTj3zIE4gD5FiWOpgzjtBQngKzGaoK+jRG8Vy6KT8X6MXfjyRNEw0L7RDftb4SfgO6rNxAtbA5eP8lx0ZuH3veNGfCCXuEcWeT69xJ20agri/cVKvKslQzw9emxa6aBgl0IKKuMlsmQZaumi5EPJJZPLAOnQ/5LKR2CL4K+uYClBNBK/AKXj6XyvvXE9BML8pg29RVVf3aE0SouHZUwTl01BuT9ZKXe2xCkHbgKHLQZl0VTCQ9USWRy7IFyzwkucJ6rtvffytmWOqzuSm9bZMNpMhSucU2QQgtsQwK04QTOrlJggJOzUOCY7tabVqIhDBe9DD9hsfNS43agW5EM8fKIPP0whHi4RjyCbqQBTpqS3JgLQkEhZJOKD9ZaNE8sTxCpFMj8Rf6DSwR9P9PKXhYtlhJPCbLxSp3OwvSv9wJG8Xr4n+q9EuUKFj0HUfEpv7Ksj6tq5KPZZ0IPIHoi6Yi5jQhzU5fXVYIPVVGLvqJdF379HX0vluw2CtO31JKvjpeRQrY3mqZDR3ZoVXc5ws96rh6jfdfLbUlfp3zPldraxznBNRO0IkPOEyhE3RF0t16Ac+KqRRUwYvny4WKGQMIyzmPEufez4pKfBW6Tl7sS2uHjU+C1MwYoqIzjAqiIrVna5xSpzNcFKa8LlAh8Cxs6tvFs/bcSExae5KHQV/iyN6TaqVrXROAaaj4L/tytq9pDv0Lrb8Uxi7H/9+f9Tf37qUKPi6s/P885l6c/Pc6fLTg7680cGnB2aOOWhcLNT/fK1ylTlshCdaxn5VMjzymVpZ87rRpeRpujPX6rZPY/XV0N8li+/tTl0XSi5iVIJ9OfndWRFxb14pSGr72BYTRB3/fnbVLdd4bYuOmhaxKIPVqdazzGX/vw8V1bSNS8Z0hV7f/6J6fcrP7/4Tbjt/r8/7syx2k85zizm/vy4lGFqsA6kTLH153//ZuCD77u3+O/uOTDU8da+2iXfnx8XNozguOcWY3/+KovO74uf6x8w1/VjudrHa5MPF0usPz++pxkRQvc0YbdJmOw2b0Gz5j+7XBKsul139Z+LXpPr5sth9X2Jcimq0ek2mw0Dzu6FRySSwvuJNhko4gp5Ulw8asMpxVioxpA2D9RBj4xvS2+IUGRRX3xR1/IdwFeEgKALFd9khHeL2cXUs+aqSuFroVcJLKA//UuTRr2Hu9p7z5nUc9rcV42XGz/Wi2JCDevWoFr4e5nniokWUaXfX+9hrAmVK+S9BejVQ2Aapw7Ce2mYCWWHb98YcZxCDLcvm4fkNVfaPfHZEV03d/m6g+S+omW8sBshxVP4dc53J/r7n7D+/vslbixpOdMAQwm8skQeI4lmaXuDPHr2z8JFkuBpUbznNcU948m8qnkAnVe1K6Ygxi1WYlwzD/OHZ8iJhUugTK5C1ZcoGsROm7p2QV1W1LNIaMF36xIdL1fEtOC37qIcplBhf4Fbq4tmRnu8uTbKM+3S4bWZ3o7tyHoNfEGEKlkKGY1ZuGQKYl1kJdY5s9g54FEGWatVCwPdsiRFlJJlB73e261t71e2gUu7LXf7LaFxgDGuspHkUE9AcEEOqkDP08yMFKTHcwOtVEKSs1hbyuzcPxP6LQpMS77x7Iv62bgSdXsBAA81AFyDAABEi0GWqEaVMfefiPq4+sGSAS6e+efP50rjby4r0TpgFAD1FTYA1vyhNTSH/GL5ONT54MWWj+O2kC0fp/pCU+fjlGr4I8H5zSOvLLutz4MaNxhjBvk4rgvZTjebLzSDpIKhQ4cWQz5O3S8H47qXDQ/c02dTTivpreZmkY/TmJU69c2BOsWSjzP1/ZtpT2cN88/JXfhKcSTzmFnk49RmJU51cyAOryTzcbzKRsqad7cUrvRckF07+uxzs8rHqcRKPPuSIZ555uMsvvCl2dwub7zSOs4Nqxz314cSzsexYaWcZYlTzqT5OD88P8WcevHYc1PjfaMOBvR/ZBb5OJgNwZiPgwpCwk4d+n8hH8fydOX9L6JdAyaMaLNrs3fykxLOxwlfyJaP40s3aU2SjxPR1+vZ1syLXvPPfM5MrBG6nvN8HKpvzkGOSfeFbDkmQQtNlY9TLn9D64WN/HymXk1ev+LddSfO83GoMoIDrHxZsRIWr8wt6XwcKZMYG3ZA0lwSsgbZuT9U+uRhv9fkk5LuSaBA0lchSoynl5EacHzR0EuiTAQlYtrTnOSWeCkpXwTa6cWBb4B30Rn592lnp3jPNM/SiqSUft0Z349+klN0kcZ/ZSNQERZatN4KwpXU4iY9uVL7NEg+zUdQ0lcNAf+QubKN1SPhs3/nH7ePEEtBeVmMPyrXR2oeh5EVJ2UCEynzZqcmvQz45DtvWDVlzowWA8ixIB+QNKCiayJGsxq/ga9EpR0+AjBJCVQ9Nr4qXi6NAR3qQCpULPY5zAxQieKUesleamlYmSB59FBxjPYm2KvTw1j4dX1Fwieheiuo7bOAJjP1RtTL5kE60gCIgP0K6UgD/qF2pAmZfLtrxPEXnpNOb1PbvA29RO1IM7HXknE3Evv7ZR3My36cldJVs66ptPvPHWuoXwzpWMNE6XKgNJogI5RabtMntV7T4mXQjPg5pSe5+E42hlrcG3PfhOotgK65UFHfCFGvn1cis/jKgZF3g5Tob5DFFaq9wr9jLsco147hYyCNc5hoVcmncLehikCVpIAr7MkTLlQ8Pfa2T2qLNSMKmtwdwUoyawR/EqT9K7FgCqKtYiXasuIlmsYnsgpCcIEKbhmn3fcYbTR7lEnJOXkR04AlMqVYgWUboV9BEphQWg2oULds196rgtb1mOSsyl8XSKWVdXCSShQl1Vbn8yhBfvCtrvTqaVed7Y/+o3pjI+oiVqJmz6O1P2LtKU8wuxhvPgEPgVJ6QLAyuhWQdPTJBdhVzlk8BsHl0kEBbPh3IsbihEqXMan07g/uhFpLz/ku3r3fYtyO+lPIOYIR8ZJYFR+M2tR/zK9jaGwsMMFEUikxkVICZomBfsb6HYRQZ7IxvRKknF9f5JwQXgBALlII09QIwuto9BRfe2xAKbpXleCFoT90ywHVjStjEoI2tRmaWi32DbljthXDT9Tp6FDnUhu75xoiPH+AVZYAdgbeEuF50ef2smbP4BSUY1wCxWWpTfX86lVXBSyud+5TNfnjzbTQWqx+wBi7v9Bf3o31l3csGRViZN5MOdBUha3PTrnBL8KW/uYeuEvWukfOmVE9yXwJ7i4u+N1Z4XctGfhpmTLGzjLGdwTI+kR/CbyRKWUo6X+UFMZSJJQQBQc9YQonHNsQhMKRMymcnic3vprVuI7PLOWr0sc+tiCrT3u8/w8fj/zp38C0EX4DcPSj5VLg3YIcRjASGWwIvhJ7qn6O4/lrZyuIg3wDsta1nnKqBtKR5f3og3JIy/qiivrqK0DtZg5UGXVBeJkLjHcbE3d3dPGeXOAzUVq74iNRuXO6Gply5jbq0eiUiapVsAAF1nIGpDbgVIQSrZc0+UX3ysc8J8670aOLx+/fyPvDF5aGi1/VpUyTPfYtXxEbikzIHf3c/cmDFGOVaQ2EtxzQ+gRUpqESb7FZVE7zeCS/RMMkEJnGRLvq/kV2HnBUJBgtXaHkSw7tnDKmdlnBVpVzuZCnjd6w+yM2xC77Tx5JjusiSYN1ioCC7CdlXtuMdueAoDmsBEU3L4OHZxySblAkV1/xqbdu9EHBxOGre8xMu8fXD0k3OpJuuhsA21beeWzT4oBZNaM+3a6YeYEDJNNZkZy5gObbGdhMzAEXzKimZZEl1AI+Hc4xDiFdvEQ0dXXmXgP7E/ID7vL1wNiN0MCJv6oGrprX+VTpuhVDVpy0vP/yc5sBxaGB1WtyWTSwOif3fxqYXQPXzLuTv+tyH8/c3DYJWx471jBjDaxencsiZtTLzSKlm8crVg1cY/HHtpUvTQ+elTwi2E5Zc7YJNTC17JEDgi5mJSi6eYtRA1cSVNkw/5SzcN4u8dsKstsLTaiB+3oseunv7Bw6f4di2YQJDsEcIJnJimR6brFoYGr9l5lpYFx+MGlgwG6EBh7GpIFvTHdK/6tpoHfWpV2f1jTwrkaOcIYlSaX4IGD6WSoWdEXwaeihMmmyljWgNbjYk0TEfHBseuxwkUIiViUDia7J+NEvKHv5fWjYXIcfyAz//EOLt3TZzvTK9FrywjV9IX4lVP8GIC6HwBJ43BG13LCmEFXCNAAoxSJFdDw/ViGHc97H8Q8/12pYK7QgbNmS/kdrnDGmJNvEYu+dUJ3M3A+mIqJW0YsaDQxhF0l8ikelXiJKSHjA8G3EhIHjz+8MnbH0flDi1w8CzhOdDqg/1UCuewVuef3mqk3Vo7M4AE/OCt6QXMPm7zniLIaavP18B/Cj8Q0KOK5f2AAoZFTZTTZyiR3OsKUoy5yLOAGCs9ZoGDrqwRhrGVRm5eolwRHQNqhBYcFSO0C3m0SFfIjGXwAzrlEEoZDlV3co289vuWBHwddvH4KvPCBzmeYr6FymXTEFUHJWoIZodYGCSRfMvFRQ0bbAMXR83BfnpHQPe7Jg1c6Eh4wZtWJA28l7pEohisZbCmhn1SuBzCc6F+kn8pce2dz6Ve9W3gVpOyfGdft4iunN6CK/cE1fJCsjPAtNR0G6yO+G8D7mmKIP0ITdfqU6XTrou67B5KAynVXkCWrG9QHiOtBUFeGVAgi9EfAgY+obYggZJLIIiFBQFCqcRaAQ+Y28fiZl3Udf9aZOHgeH+jylHMaBuyF57thlzvdbIIHBeZiByuuN8L7lGCaYHHAMtJsEisCLZf3vJTVZLsiTVrVxdetFbihmifI67fdjF03x61Eas/z6dzkaaaNkkjYveoYEWbX6jGQuO+OzJNS/L/UgSQbprsEkZ+prxxmDyQ6FvcdGyA3qpLHtnY/l9MmLPQvsL3jYlr4/jv5KdNMeXNUXNluE9xtgmjNQ0RKE8OT0juNsoqUC+HKd22bGji+lh+9wExb02nP/RladPuSsUmx/MGh30qIuKWMn3+iwovedkN0BI8I27lv9j7FSxg7hJQOwwqCGUWOEp1oAzQBnTLDBwGLfX9mfZ2ZOG8z3n9JnpcXC8Y+6kAv/tbqEXvhfuKQLpkkXAiVhe/cErXcO/Se63v2JHMAkZ4VpyALDhLEdzlTiuASmujFquF3fbcK9HOpN8MgmqCaKxqAh5JDq/5AHPCTvvrXHiy9BM2aG7bsubJloWg+Y12sBiwfMCzJMZunvAX+237p+ceSmwMWCXtKFE69W4dADploSxjtxvJ4LWJw4Xne6rDKVBzzR+4zTfveLoZMf1BuePP63hr+ABwx4iAU8XwMlmMEeMFV1mZcHjLMWk2MHWKsEPODw3Kqd1l/tGVKAuC8Ompp/0Rw8YJyNGIHy1eqCpP9DukC9aIv7iM4ngpZYfe+/ze3hTBNHQ53ZdIG6rql0QfP79WZub3g6SP2HeFy18h4xHOoCqk/FQUCvKZs4UzcoPl3Q8ULsmsfZysDNf1Vzuu/bvMYvoAsAD7GAV9PUuoBqn5uXLsBZizHI16BEdMErB5d1lXp98p/GP74m5eWpeuagC3A2YgSqplYXDGfSBeW/hxx/MK5lUMpC5/49FV8rk33BECA8wcG5/tUITSIBa4jw+kLtMHBQOMUH/ZRlw0VSSYxElayX2N+w2O5q4uGZAVl5Fyu+PZK4jeHt6J6qdklfLEsj6tYg1nMXmpHSHFE7GRYPtQNfjjWKFzOkGDun7HROr1jad6ldu7QLBxrtIvuX0J+FX9V1Sv3BbvPP483f+C4dtnrzb0P9lxorrawRtVsO4wFsZQwag6RVFdBtmy+JxdlDouQDakEx6uDQ4Ajyr4dgYtfIuuIjmztTGmoDIvtIRXGQiHiRNc73XXsCkESo+O6BqFsYGBWtTgXEH98m8Gqdw9uDN/Rt4Ts/acvqS+eX5JFFN3EnAyyUZVMg04QVGSqrWOhAxlmA1YkliaT8mMJVTbMmfBgmCA0yHDdM77XS7YGru89em3OHxuWGWJKDgkW+jx4ULLpoCpzqsOJUQxtZHsEkuTuPaXF6myAhaOW+Oe77mnYvoFg9IFAcIoeUkVkyQN0wTKwAFcN8otqCLxPH4a2Jm4aERvLR/xY762esSzve7vjl5prQzR5zj4c4XtgDfzOIPUas6ItiLUQdCFBMQVG8S0OxDaL2Mkxm2wuJX46V6kB/WuqSDi/DI0t7znmbUX+Kz7hA0k8rJaAnFQl0GpdUGWesuK6NqAMAKq4CILKpVkF9DBWDxHV5VGiIFUox2HWjBGOguPzVqeOyG82vINv2LJK9muFJbq1fBu8qRK8fJ65zvr26ERB8gkIQgkFAbK+Rv2rSbueR86/c8LjjvzR53fX+P+fvNX3SrgPCUwFUd0FNJG+EF5Pzv6Rd9qRdC7vqf7Ss4Szcc/3siNdT3yVwlrRL3X/GCpGKCE+ZQ7TTgtV982Q5Zpq0a2B+pEFJu7fOrc//N/Ww77ScxykD0gPmcZm0a6zMQykmYaUYujuLMSv38cU/jk20UwZOsr41+uX4uZkmzMpdEd/J4s5OgfeO+WeC3wW1dOWA9wexItk3p1iychsqUjZuEX32Xbh2bMXUgVWtzCortzshIOBO4QCM3QgVm8ykYvlxDXZMS50unHt4XVD2592jyOHOcLFUlExWrQaiXFnAHyFRiPkK8CTCWYAiTfWYIS9CH06vUyY7p2WrBoyfGbr7860PB+9/6WYsXzojahsNX6ppfNkFUVtpIf/N7CG3DM84FF73sdf2g0vD3O4e7s8N5NQtwwHkU1khn6iFfBQT5G7Lw4/227jaZ9Vyh9OHxn6YR/6lvgp5UiIZcjsN5EJ50WZm2CW8pzS4pGkVB6NCXQE/DjwXM0kUIqUyXp6YKFYQ9FBa+HtpAKMG2NAljaVF9eLQJY3SoNqe6JIlDx58QpesiCUqyW38vQaRKAMsZyizpHd+WG3z5Q2hBS4z09sOXzgMAiGdWSg05mlojJNr9K8ZEC13O79nnz7XhNMryDPuv+892aQB0btZbAHR81kcB0TzvolntXkYFZLTakKbVZvbyzgLiA75Uvto3x43PCfPuvqb//F2+RwERO9ksQVEUWhMFBC98805KmJ6D2S+7Qf7174vVphNQBQDhDGcdSPLhAFRh4VlF95e0F846c68SJG14KmZBUQvsyJDZRUTB0Tlix/vONx8oyDj55ohf145ttCMAqKnWXE6lqVRtGN+vYDooPWDa/3593bfjGVeKueNPdWmC4jyxmWzBER5I7O5DojW/x7d9qPVTr/Jyyqmtgu+U5uDgChVxhkfEOWNzWYJiAJUOA+I/pP24VtOj+a+Cx8u6Vl6StCTkg6I4hAwBUQBBMT2GvurBkRfOnX4a2bdGl7r7Xbf3bxq2UrTB0RtEd7qbCLRnW4iBSC87Oz/BUTZA6Ke1+XyXj5BgVOjbZXq7rOfcRYQpe4/DhLQV2UzDlxthPCWZZtxQBSzKkwQEHXs4dU41zYweMtW67PLLARmFRBFKbaIlWLZxUsxzfvbRCYniov+eKciLrpLoFghE0tdwGeULr5+gyKw5sL6NB62cmvl1q4YI7zXez1beLCOZ2D+998LYlUFlUwY4eU6koayRgYra6RlF0uEF/H/VPa+xN4/P69xe5+e7p3MKsLbk5B4cC83Cts/hM0wzuzDjdQQgNlGeLdmsYUbN2q9ILXZQ/76eIDF+O1pgWtbldu1+t3ErdxATt0yHEC+J5sN8h1aLh//S0Z4qRHDIhFeqltaJMJLNaaLRHipW6lIhJdKcv0jvIta+SZfedwhcNW6dZuu3P9wg4MI7wQmclW7n+pVqeMfyBL3Bwc2nhjhRfou/qGd7P+DD02piE9Ugo2B1PVAW/xWg16CGOBERUTnfdA5lbpugmevUkSfYSDSaKn7jv+q37SGMuSYdwkQtpuEQMcRTDORiWl+TN6yvLKLlXBH/xo5KxODyYHXCv6UP2QmsdXJJLQHQJiC9hkGJqB9DlpTTf0QlMhpl+vY+bo1Ctl581i7+NTb19h/NI2o9E/oku7UVpB6SndGGtdAeHtBhnxGURpP+k+CwfL+jBxD9z64B0JJcJmBeGAJRi9wHUqi0LlNX1ZwuuK/ZLNbeQdkhT/tnem9EsBFzndTPUS9YjERwNUiPflXjSW1PRJ+duL2mKDd8YsdK6/pGVocyXXqx3lEct0OhJ5cp56ZB4klVUXXKvOgsaRKPNPHkjTrljrWrXSsl9axXkbHurWOdRsd62V1rNvqWC+nY91Ox7q9jvXyOtYddKxX0LFekWHdvGKFI/558nnGvDfeK9eu+i2++8mHnMUKF26p4xn0s6VfjupR9bwvT0obn0CmfpTHkkCmvptnDrFCS16xJk/eqx0622/Ifb+ZG9XTj56QtDOnWCFKsZusFLuSV5zJk1/aB41enqoO2X23aa1+3VItTBhaOzREeqF26uyAghGHLD60qFSXA96/wIrkGRKSlpwh2RqeQxn+qoPjzKN+S0Y9/yTdNay8fki2piPZWieSwUkNyi5ZJ/Ha3tZySYdOHa9xgORxViQPkZC04gzJNlAkC6bMu1Z9nq9wK//w+lKl5H31Q7INHck2OpGMiB0/8eagxsiM9T8Hp+U9+sYBkvtYkdxFQrI0Z0i2hfcyGBM34VTKHs+sEdWm+4fZnNUPybZ0JNvqRNL21GpJ4x3hnlszHlYMS+fbcIDkVlYkN5CQLMMZku5QJKfuT61VpkeucLZ7TJVTl2t20w9JdzqS7jqRbNS+bNiJJ0+89/cpyHle7vdwDpBczYrkchKS1pwh2Q6KZKt9w3dlxBYELPR2Ob7568J7+iHZjo5kO51IOkiaRaaW/RvJrDVjet+Bo+04QHIxK5I5JCRtOEOyPTwb7VCiNOtbreANZ2/lDBudfFA/JNvTkWyvE8lR/4Zv/+3iHL9dLa+PvfDPewkHSGayIplOQrIsZ0h2gCJ5867l9tV3hiP5i69Gr1gjaqofkh3oSHbQPTZzWHvxQ6sdfpOzUu1HeXg15wDJmaxITiEhacsZkh7wzNo6ji0a+l0OSXGYkvRM9eYv/ZD0oCPpoXt354Q3Do5W+CySzG1498ruChwgOZ4VydEkJMsZjmQNBssc7sV43eStrfA1NWDu1ddvfbtveMsOZVmNaU53YyzcdE9uuC4O3u5iaek767eXH3fOkBk9zRUFcwQrmAoSmHbcgQn3c06sqH6r4J/d/isEScuHfHi3TU8w6Y6OhZtuT0c9ccmaZXc7CacmBtW/lj68MgdgJrCCGU8C0547MOGujm+jp7NUdYcHbbWtmLbPd6gO/1oLJt3XsXDT7ey0Gmz/fe2Rkz47p9usn2Q/2poDMKNZwRxIArM8d2DCvZ2ko+PtH0qG+a/4Or/a57FPdJQvasGkuzsWbrr9neBF7ev9HrnIa+bTZoNyHo+N4gDMPqxgRpLAdOAOTLjD83T9/Z+2oa6+G6sPPhfUMEKHma4Fk+7xWLjpdnnGD3mSP4C/XJD/j1fftpvzhRyAGcoKZgAJzArcgQn3eUIGnvHdWmlscI7qqq1PQIdNeoJJd3os3HR7PfatLR+Ve/QsYN6MRqu9z4VX4gBMb1YwPUlgVuQOTLjbs35d8tNG3X9H9kumvDvfsbaOBCwtmHS/x8JNt+PzHw832cDsxApmu7xiyWIb53QhKyx8NzItdfz9cRNrrv7PWWztTVKnjMfiQRbbNtq52gDMTidOK6f8kvk9yRsvrp/cfqzXZutDk3Y8C3Aqkt9DPRsukt9DPeAskt8z9+7BwZ7TXIMygvt6DZxQb1CR/J43waP/3vZsfeDabi/nPPRf7q9/fo8seM5Xj16JfmlWkfWfXY5ZwUF+z1RL/AiDRq5kmzH5hzJKCfZ7PVxZ7ecLO8sgSZRmbfGXKYOaH3saVnXUtsjXXXlfSO9RCz+T54cpxMMl4hF80M17hFgSFw8bBsJU7lmP8pARElV80SfBm9efqZPt/HY9Mstjz6E1M6Xx+r4WDTOWz5YHFxLlChW+p5lQZtxJ5RFefbCT9gjB1BBIxb9dHq24SCNudLT3lPMT8ffV63B+2R8Pli5c4h04Ze+jTmN//+MS5+0+qQLNWEFdAeHxAXITYIJa7YrwHPNovVLZ5sk7RsaLNYjxlfGiGCAYhosVCkkMvEir1s9yQ88/8gzdhfx7o9afA6kCGXsCvRiJuM65SEbhqMYKR8XiPR4tTbyodYwkNjZJKdbI5tHveT9txAkSpZLAHlxs5M/7WVoZj24rcKWMRibx7nazUSaKo5OkIpJst1Ohr6ZEaSuWRSeT70CBLEJzTd0nE83rA5qr4lEayVC9ran3xDJxYyTKRKkoGUp5l7EBjb7nnBdkPrJaVrlTezHZnonUPI9eL164xPlhawVMVLDQ37rEj8cLqfSmW1EqWeqgUrcIMdZ2VwXKl7H/x6QbSn2wR7FRUEpcI4hkfFGUUi5F0UIJmCCWASZzgY/DUVf+Q/phj2DSkVOPXKqdVpDlnYB4Cl3eaVdMsYMtWCn4fXGJUNCaqNQtFOy4qTCNybIbYpF2tWypM4EHZp+flDSsSiwJWnyUipeGOGQTAJhETHN6mmnn9MRoGg+LZDK5Ci8eFknlsjg+PsMHTvDuvZMzVENSA/dlH/RVNe3bje2taGSnrOtLUkeEd2UFStJp0FrG7gjv2Aqadte4ZlDtrn0DfpRIKcZ+rV7avcLnp11XeAv81Veu3Kv7V60X1sGixESizEnjqvz3USwUTR/6JuzO2TZbkTl/9xHx9+19bKymr4PwLq9gdMk8EN75FdCu6EzypHwhiqDqHwpY0LjwV7/bnPFadbVb/oFKE8frBiwSfRQdMOyqLsBeS3lD84bVE65tIYw88NjdhwPATrMChrJdcUoSzYvqU3BXyo2qwPUkpVLyG9xOO/uz/HH7WW5ek4f+k1wh+2umblJGoI+CuNLgqi5SLrWaVHPdsSWC2fUWdO828ENtDkj5Oysp9xYvKRnU+o07ox3Rl+xGqIbpTKrhS1S/421s84NX7LP8zov/PpdsMweJZXGqeP17SdQNFouUSQoxZrVJsZsNHg+5quu06BNO230XvM7uZnl3awXYG9GtePy6AT0+Py0n0pDpHSQ6Iby3yw2b3aYdC5mAAwD/Zc0euHdx3u21aU7i+Tl+q3M4nArJtS9XEeF9XE5MhaR1UuDxMYAMG0SGI4TzBBSdrMkn67azfhW0gXfy9yWqPYghdOfe9vMlALARwgDojQFA7K0Zv2r6/7uFlfOOpa/zmZvrNDT/yJhOxZL+f3opW/p/4tL/pf//L/3//+f0/5d9VkeH7enpNf7f++/GJn4j1+SYWfr/qaVs5zJHl5a0IVQC6f/7PF7lnRw2JnDCh7X+dVzsw80s/f8gK8UKlhZn+v/gTd/2++885720zdEf31NmvTRh+r9tcLt/Lyx08tsYcK3bwIaXznLA+ztYkdy8tDjT/2fGzrvgkNXYZ1uz35w8ozb1MWH6/7TDR3sceGAftG7S/dkdnn3iIoVwHSuS+UuLM/1f0aBZpZqJuUj28vG7LoV+2mXC9P/Wfyz7kR8b6J1fZWa/JWVvTOEAyaWsSC5cWpzp/8MvdPh/7J15IFTtF8cp0qZEpRRNkpC9VVKYGetYQqvINpZiyJZIqQhFZV8ra1mikn0vRfu+r1qlTXvaf/eO4R135t4s984Mv/rjfWsuM3e+53nOc55zzvO5alIbj5DSK7fNK/zCsx3D9v9rQnHEfSsJxOQyS/5Fay+/REHJeEQlo9JY2f5/Z/lHjQu75Qn5pT48zsfUzmLY/v9q02iFKNHZ6iHBXzdrfM7NQEHJnYhKhqaxsv2fQAqJSUjZoRf6epJP0TziRQzb/wctX/wVn1pNLHzeELLa7BAFBSUDEZXclMbK9v8Prr/nez47rh2b/ftM2JXQdRi2/4u6JpVPFNuqHpF4XVCjapIzCkr6IirplcbK9n+Z5sEf1k030ghfIOOz5E66B4bt/zHeKSfNJo/QrHFPlv250mg/Ckq6ISq5Jo2V7f/jwm/90J+61yhxRkS0V3P0X9qse9X+L3a6gV/fOEU/hPvJ+NLF/s9QUNIeUUnrNJa2/ydL+oV/ydcmZp7lkVwx6Iw/pu3/4x9ZR0yyDTKIbr4Yoyiu+wUFMVciirk0jaXt/49iebJKSgfoV9/QvSkWFEvCtP0/68+ik392FKjXPBPa/03PLgsFMU0QxTRIY2n7f4rkxZWedb76WTMDf0zP/TEL0/b/nPxAPoXambpZ5zLmiSvw1qEgpg6imPg0lrb/m2d5Se/l+2mY+XDqs5RMSgGm7f93GyX37FwxTDcYhz+wTWWBFwpiLkAUUyWNpe3/d4dZVlddVTU8qqz/6nYg6Rem7f9kkZ1nBRWldA5kTTdzT/WqR0HMmYhiKqSxtP1fLd9onNnOfIOdpibPcooeWWLa/m/nildp+HVfN+vRoVdpLhVqKIgpgyjm1DSWtv/f+hpVP3Lga+2co1zSXyfqD8W0/V/y1MSRZZkqOjFr+TTrXqqgEWTiEMWckMaa9v8j7y1nK2QZpQ3aIfXBjhTBae3/1Fw8bPs/EKfTqpU74KqVKRHhXq/1WrVj1471SNwua9H5+2i5urtYM3mqBJymc9p+Aefh6kJueyaQl4cTxQHn5mxtS3Z0dbajljApduBTgoCf8wSveVo7dK1w+SN9y5IDa3D6edmtCVMKvAcyu1XGUnHb612VtFUzwB4sAA/AM+sUW4YPWJLRe+q9YdCDBaYNr9QDzxYGDH5vdA1aqty6NHXTHbeVOvG1KQnP48MWoEa9h34wpJSF1Pw5DOygopmNqXUeH+Y9fXZLtE7UwLLny6Ur6rpjHfSnxk/NADJox2Q4/2GVwbGtV3w4P8V5Jv44SP0KyTqCWv/NJ1svZ0+4XpRo0Zzpy7O2ae/kHnF28AMX2U5G4sO3/SaDlTouYGEmc0QzLWGtmdqriTwkfJuLBH9lE1enWmJ7Lxxcz4s4eJdgU5ATxYPs7gmu08BHdHKBzI/JPGq9qYFbq7l7VMiER5KGD/+y1FA/pWsVRMhafam8YbLDjGb83s9Lrh945fa1t2s1YMRFiEYkZTCs1YhPoKENZmBlhu0LlSomhwxLWE0qE+Q9OWqls0nPe0B7O4Tt8G2ehjlJ3o06hGmLcBjcIqwQ6b9edN5vrYjFs3ZwJS2P6/zgMyMKGWfkTXbHLet6S54Q3tXFDWy/dwV+GTw+g/PpWh/e9185W2t2emrFUIzi6nmex8PdCuMz2P671p0znhk0SDFjP958YHPSvX68YW3xMfzznN5b/X6m8KrWMPStVs4E8umZnVvxloC/x9iK1/by3/os3mZt3Li1qZaUfeot2X76xtLeTiohfMA8UJsXzFrxwAfdz+xuK17bDERQB+oX2PtUJx2aAMyf6rSUKgBtXoX3g+A2/+rs33KjB+tWkjJ+4tyP8GIU3IojBreC/4Jb5svNG6GPilyNG7WPhD8PGzEjzIvtwe1kxAV3IucGt7zU2BaD0HbtDKGLQROnGgafTtv2RpzkyAGhrTCikQT/f0Lb0LMaDVkXFmlGpG//VDBG7wpmoS3aqzBgRH5EIw5GP7RN21U+YILlWaO4+adjmwa9EWRraDsZMbQV7FiCd8ItwYiPHeC27O5DB7gtmTxygNsS5oED3JbMjMBtyVT3349uWR0N8tbLWJA+QGV4gyTkThmHoyUWDxrgWpMJfdDArr560mD4yzVGg0i79IK4Z8UIvg+3wf6kwVh8QC6oX6ImswhHDR+QlPnvoZXInehfL8QXpWpN1Us9PTd2c2jCWNQ60RusTgzPWDlTu/pLwG11+92fe+ubx+EDckBbn9Jgdk5bAh+QyfYjeR3Tv3O4g047DPMejojvJ07/srTQSa+Mub+TR8oWzU506BlLyEKFgkFTEA0KTF4WNqorJGzZ+ui7jVGyx71RrXsy12DYqA7NZqGgZCyikhGZLKmeQQ9Uc9QjIHVp/oN5dLOYOtxoK/BuuBU49G7MWbJ1MT5ZY+mASvP3czpvOmgPGO+89iJ56Wm0n2RcfG3on1XOPMiG+lem98K4AWq/8Df3DQ2PejtGgVHon0l7TCk0v6NcpIb3Xcce9w2H2YiAGwMt9/PmTxcbQoraPWKXz1erfZ2TigZkdwdy5xGAtNsVpf48YH4bL+C7gJanJpq6E3VNKB1YusdOkZigXzGepHOJexDJ1XYN2a7jl5jcH2PSk/pyN544uz4dMOVxwJRpDHVoRTyXVDqTqAs82wk2QTCJusBGE2jUBRdV9TTq+ne+k7PPd6IVFQ/l6ta6xk/4b77BBAZK03TPGoTPNjws/n06r83x39AJ1pXsBpM2TwLrD7SNwHP5gBP3MLM4gWs8nssjvQESu/ZGTua9naOkz9cuNzhASrglcG/0iJDnPZGTSaMngfWn2gA5KYhyOqVDA9jeyMm8uzP9Wkb21pYKvQq9GRueRoqP74mcTFo9Caw/2gbIaYco56p06HHL3sjJvL+zYsMv5Q9hH3QDCnIuKT857tsTOZk0exJYf74NkHMFopyL06FnLnsjJ/MOz+Sy3VOmpI0w3BI+4kB0rbZJT+Rk0u5JYP0hN0BOY0Q59dOhBy97IyfzHs+cZ9dK+Imi6kfGSOCOeJjz9kROJg2fBNafdAPk1EKUUyMdevqyN3IyP982K/NdnjdXueah9aVZYg8dPvRETsbTbgMIrD/uBsg5H1HOOenQI5i9kZP5ITdzX4U5a6tCNXKbeVv8uUxieiIn45G3AQTWn3kD5FRGlFMuHXoOszdyMj/pVq8lyOPpa6YXcSTI5q6MK6kncjKeextAYP3BtxHULSGCnFPSoYcxuynniE5hPPNUafz83CnjFh3UKc6RaGl4O12ve3rytcXxjJnTgQQ2nH4DFBVDVHR8OvRQZq8UZb4zKp6tdNzz4zi9pE1unstnZ+J6pCjj1ghQlPVH4ABFRyMqOjIdejizV4oy3xz57HGfXGiziRi0zJTEpyvxuEeKMu6OAEVZfw4OUHQooqK86dATmr1SlPn+aODNxD9KcxL1ikT1y1WSJ9T1SFHGDRKgKOsPwwGKciEq+oPhmGavFGW+RbolseRTXLUnYY/jkaVlr8q6uS7RFGXcIwGKsv5EHKDolzQkRd8znNXslaLMd0mzLdba7BNcYbSjVetFy4IBW3ukKOM2CVCU9cfiAEVfIyraxHBgs1eKMt8ohR/5vGuQ8h/tgim/W3ZqrVncI0UZd0qAoqw/Gwco+hhR0fuMZ+O6WSgd2dbVC9YfXMBKAPPdknTth8V8Rlq7NEKXTdtseolR078AflneUzyflu+cD7ZzQQsVAfrUqJRW7omEK/d0+3k5HdKz4Hk5ULYn3fNyoGUhhsfbgN+W+WMWHO7eXTGqzihu6Zi86DouIRQebxPVV4pp0OcFsaSYFpWKVEzTTP1XTPtXTOsvxbSMRutvlCx9w5wrupLbSF9UWFdMO77a+fLE8Ai9inXHB3yWFRRDYVmOTEValsNTsS+mzTQ+pPElc6luVObWrY1zspNYV0wz8JoyJPWgE6Fo5sDUuarzbqEgZwiinFtTsS+mRa+PdFv5oVz7cOXGuVYvi9axrphmar95691VkvjteX+sdqU8+4mCnBsR5Vyfin0x7Wvtk3ry/W2ahx87fZfAHe9RqbdnxbShZ7KdJItN1I9GPx1lvBs3GAU5PRHldE3Fvph2bvetebZEMcM85bhR607W+rGumDZ1zhDjU01NxOrlFYkvhx3rdcMiIOdqRDnJqdgX0zbsXaBxYmqSYUTG7XuDdFtvsq6YNtJJxix8yBt8jMj20BWWG4ajIKcVopzmqdgX00ylcvY0XjhGDI/KbeLzrVzCumKa3xeTIt+rkTqlcrc3Xv74yQkFOZcgyrkoFftimktUYyqXy131QM+Z+ybK+W5iXTHNfO0c8lOeYp2g+HB+PxUCGm0yJEQ5tVOxL6ZpfJib7D18qs7OC0e/ReiMHcy6YtrIRBNJA1t3rb1OURKNN8oEUJBTE1FOtVQWFNNIm95/WP/ZTT+Eh3fW21HOGqwspt0mGxTJDxyovdP39deS7ZTJKCg6F1HRGaksKKbZk/2KvJsqiUGrTYwL7y7ZzspiWsDW1Jz0RlXNYDfS5Fu7vYVQUFQeUVHpVBYU0/6McojEG6lr7h5cqrPjWuFdVhbTFKz4f+WeOK1VEjo4L5B/Ax8KikogKjoplQXFtFuKOcMf63tphyw6O+9KseE5VhbTDPbOmXTMbC9hxwuZVYnPN9qgoKgIoqJjUllQTDv8KXPcYNId/epHQ/wfakQ9YWUxbfPqpgMWuAyNAx8JK2YeOaCJgqICiIoOS2VBMW3C5G8Vzf5VhNgU2xnWzporWVlM41ce+GzYs2a92O1Ts4kXTHp9RA5QdBCiotypLCimBeDd316/WquxzZtbKGdHiSAri2kyy7JXB3xQ1SkQ89BdEvYgAQVFf6YgKfo1hSXFtDdLDjY9cDukv2Nqy7mlPqav+0QxjZrvhC2mAVEprdwTDVfuwTlMKQ4JD9WMqjtISvhW5te5nGJCdrZe37nc081TikIabU8RdwffiVYvYyo/FBzB5EYYa1x/fz4jhB7a28Eqjef6lE6jogYwDFY1PNe7jvplDJzknA4NmC947/7qrd90g8vfvaasVq5DuD/0Hk94r/2xoIzQACI+4BwKWKT+DQ048a1a5NkkXdJOi4/rK7fM63wOtjfQgN2p5TXBV4/r7OaVdmsZU4XGY0DuZiBxhW+wh8rzd2gAlo+vi2ptGvf9y2HD0tOHp94K2cHDYY+vu4xoMWB2spAKIBGrna9m/E4navCr2xX7d+dhSAVA/+m+AQ2ISh5nhBlhQQWAPpeeo6gAi2gOgjkVwII63GhLbCzcEstJVACoA0WZCiB773iTuneR3n4hFZ9Zqsc39p4KwBWdgUAFSAxnj3+GowLEwY0BRO7VwMfbYrpLvgJ/hwn7CnwZhn4FXmI2nsDXmY4VqDEZ7plxywa+iAUFa1MGlIIVD6f0+NdCK5qf3sHXkL8pTv0efAYSMDq6ugOf54kjASOm63NO3dTR3YmyhmHGOQPv4gES8MBH3Xu0vzftmffWLq4UB+CfwDWXLsW6e3hbX22+U6O7X28OWXnGyATE7rLOX4VJ7Nvpspm7k4uBqx2Z3mN3dRJy4QMegNuMT4D+iswC4qvMeA4IATH4Sb1tQWMW8ILv+9eAt+MH4N65az1O3DAjRRSUGyfV9l8NaWlwcLi6kd2tqfBlpmb3dBIOe/NIQjPSer20X0vRsb/t9alDnt7WIyGfyTAYBrdf+muQAW3i7a0DH4APuA+OnZXMgowAIMi41VWkQJcE1+yS4EN+Fo/5wFOjk8E3zmT0dI2Q3gmuCS+45t8FhyZ6UBD8KqLgF9K7msCCU3ycht1qYIUBojrnzuOOeaFa9aXkr+rdGimPtGo3GyU1dy872IuhjUbsRx27E5lKaUcdu/RScqMlpSaMlFOPKDxM2XIUfyhT/2ui2czsXkjZvUGLhpRXEaW80JGpSuD45OCeAlF10h85nUTPZ8Ip35t40UkOGkVJvRYQv6GbekRpxEh8pi4KycHmfUjJwWf72iVPhJP8d1BBhpA8j2bxynGJ+90MMiER4PbEzoK3e26kqHV7ItOodXsibNS6PZF51Lo9kal1Ju6Vk6/6YWlQilf46uFbpsVwz0yiVuDFv5nnncGGN4XNefq5C19HPtXN6Kp5kILa6/ugQW0SnCGg6cLO2zZdiifZAZqfRQpnpWC3kE5tb4Vryz8x30NCpWB6M4x7yPYLrJ4IwB6yfB/MHjLhDrCHPLqPE3J81HduGwbJPZyP0F1kV+Yj5rvI8paPddaHKvW3eFaucj72rrWnu0h0MsEI8zEgj2GTuQfOEIYlWhdOc53AB6wYr+r0Um9Upy81wsDL2dPJzdnJ1hr8Dl0vm0wwsAb3isBv2Vo741w6vUuXNpArti3KLTzzRjeo9FOgvNdbLqTbYpAdcr2r00sEHzAOBDeGMd0dzsAH8DNjLLc/rIaFu0O0yyGiWk7uQLzkBExr8FkREHsxZ7nLCwdIfNNVzxx6auMJwgTvzkxxDcassMZf9w/Ni06f25e8SXPfhDXGEj4nFXrrLSfiA4RBcyoyK4CDD5oRZC2Hsz3SHGy23o1Mr4043dFHeX2yO4XsLA/+jIe8ts4qU+pDJrryAAoeeUXlWZAdKJLVxUzJtq4Uu26ZfZdK8N1nQXmGVeeUg9YO+abZ2eyajGbX/KvZ44NOi83me0vK5zp9LNWzHI+C2fkRzT64H5q9O49qGEfXtdGFic4TOP5gfapGxKSkRQstP09kb2vGQtqcBp+dhIO66ABDqulpK97eHoUe3DLdDTy4ZZg9uEEG7sENMkwf3CDDVPuss3pLhj4o1Nil8G7TT6JvNOROGWebzF+DDSi4GoVg4w3Dcx329bB2EBzd/dpBcDTTqC84GjbqC45mHvUFRzM1AnRZYrhnJlEf8CIWtQMlBqVTehhfQ5XuSnyNudLyH3m2PkwuJuwcvXsYxeDZ2Z4qjU5cgTTktRkMkQpniG5TFYZxtS872FMVshaE2J4SL9JOaklYOLDxqAAdVQEagAOXBsAIClwaSLsENSEDiwGsozA1/seDZjbhjl91U29cG2kQ9DgSBRZDGmo2EWGhTc6Xau/Tyo7SLtbUPpqv/mAJnU2UMm/nPJ1Xohk1VN33YamSNp1NVvCnv3l/SMooqOpP7XCy5FA6m1xqTC2WXLJRqyp3vdywgd4TgEvttAKywZtR1sX2uplCYzP2T7HjBy61gwqsxmw+8O3nD+3ij6mlHmMOGQKX2hkFwnNqht49MUsnKNV85rI0lenApXY8QaZW5TAnswn6mZUaApvuW5CAS+1kAsGcMYeSHMO1S1+cU7jdcjMfuNQOJWg4eFO4eSlFu8ah4aIez9nTwKWhtEv5vMrkV9uDNWuEg2yk68IsgEvtKAKfWjdDPoXlBkH8o6zq3rjkAJfaKQQliu9lhCUuGRac9X6T/n3xJuBSO4Cg7o+PuwHlnkH1yS+k4GU7jwOX2tkDC/mdTOdcUtHNUa4iWWwZ+RW41I4d8BunMnr8jWGkirEHZ9++9MYbuCRAu/TjDuH7QsIVjSIpFcWR4s5rgUujaJdem57YsVZLh1BIjM55YSPzGbgkSLuUauXc9OHcNvyWDZtIXik6cQwTRQhuoggrDs0pOX1bM3ymbOF2KWMRFCZK+sC2MJVhouS+HJPDvUxEM3tOzcMM7x12A0lONu3XLGSncC+xDycdbLSfGjhubWPn3NlSEg7vakdmzBiAg4jpBCGCvR5gqWupq7M9EMbiSNYUBy9rBzLOFnijLiUNoFOH6S0xpvNoF7oYgzbqErmMY05yce1n1lWpTgKuRp/szsNdZcwcmXxpso+bO9nDA0xmeroC/yLbAjfGvJZi9WmqzPg16umPhnhlxwku7tyiSATeh7HFiPrq3xbO7IUWV8Ydr9SMrzCuUh1yKLa3OzM9Ipc6KBzYgfQOujOrBa6e6iwcNxfyRkYMFM4ZbGagtS20i0ikOABDjqlYOuUuPPXX1fUq9C7PvrOgfHBnsUjAmzGKRX0V9fY/PepAQVDjVtTJbj0Hdygohzt148X0q4+vH31bJ6bRKPnurJYXZ3Uo7N3JGdAGQyuzbXorcPVddOev/7fRIAt+fWBD31b4Am9aFmcNPrYWBw52WWqGw45s4+UAjA0HpgIFi4Yd4RpSqx9/ebmsb9TPBT2fSCiIkxKNJI4xRJwBGEyVC+QVrWsvhGjHPA95PO7Zh8AeTxU05OBClONw1EnaUpYBF/Nx+4fwkIxH6BSkcb8cf265eOfHf1Mfk2vq5uzE5KnJPDCaKlB/vu2hyeAzL8GKkysOUNXBBRiGHrRnKHuQQTt5urp37ZAANMSDu03Gp5T/d62Lsr4DfExIHCArgVm+uxZYyG7FdmshG0G9BUADD/Au5Jl+v6VcwqKJd69qZvMU6dZFK1p24Rmgfy84Qz1bLxcqAX0ilw8ojBuz8RYCXJWKY7pQwWVax5i2DwKcrSPwF1vwRAlzfZaf/5K7XX654V4yRSLU8OfzzvbveB+PrqjUy2kHygCMAAQZQmJPcurTmLllGdbO9qHb1YaWtpWP+qxz6kO02yc2U7udGsw96bT7Ct3ccYTmYC6lT11aXNG3WYABbejWqjNJkB42oFqU5ioz4VxlYmnj8uCnrbrlpUXlR9Y8InXeYRhbU8jOjO0psAV6DZwb+BvU9deWmijCUVyBr0F9oDxVWYQmb+i2lsmtdE1VW3dXZ2cTMM0NvjiIq/3Pu4Vwig9e7EF2Bx1S+/sWDteytnHy8tCaN8/LAwjR1cRp/zb3scA5OHkDXwlcWanfBtzmg/9o+wmcvRelrS9BS8pHmqqENSACRY5CdgBuyRsMWKydcdbuDl7gCMP5yIur8g81sAZu2sPKlOypQbtAvUdz2qfKKlkAP2S6HrCDjy6l7RHvwEe0X7ZQ8xNv/z0PY/DJzO4UcbkFfqv8/cFfA960Y0B1vKOfIfDj7k62WrTblQXbqMA2LH/wo/iHEoCL3tQbNqesojVBWHR84Dw1ZUspCk6KMl1JWkFZGteujrIlBTfFQhJ8AykZR09PN495Cgou/9WH5YHPsF1D9gFcI8WBLG/r6qJgraA0Q3nmLBlp/qFuruvI7kb2ZutcFwEfCnwI7XOBf1lISmo6eWpQ7MwpshQ5JQs1NUXwQ9o/FxDFieLkud6C+ivugF3M/eSUZJWoX6bDdKsWGlKbFxZZKKjq2psrzlczIQMGlZTUdQH+B7ylLP0dEMgUVxcnCuiCgasWsgaAIwGGgnnHyAANSaHI+lioalk7e5CB+3X6b5SAd2ft7mTtQTBXtFBTUu34V4eaC41dPZxAgYFfbL9moWbq5QKoKCW1Bie1Rk5JWg4UGfg/VWXaT62xUABeWwNIP1nWb42sIiiIP/AaID7wk1TrAeYGvi7wxsZOZFvyOicPsrmfn7Kcj6zPAiV/f9m22/vvbsGfNHC183IGfgzYitqqGQP/cQI3pMA3kfVQU5JdD4jjqwYMJborsh2qy1Jk3WTXynq6Osuu8wd+rk1c3/lqyrLgnfhayK5VW+Tl6ukEDFBzX1ll0CpSMrZAvO5Opj53HWfm6EU2ANY6srkFbp2TpyN1Rjm5uDmTwUFNHe1AzIXr6pCaqzJjlpKMNHAf/73xWsDCSsCXAUaPKvWu5JRxay3AWwHuW01J0VJKDvzuoIBLHZ0AKXwXANKqyWk5uwIjwAQwNrABcKW0fwULVTdgElBUfeXUlBTcVNdRbUxwNV/XbkwXi+luOF/cOtBYLoCxVN0UAD38XGQp1FG5Xm2d3Hrg/8A9ath4mK+zmA/+b70FDlRRExhba8wtqHfXSXQPXNtPyYK3Sr38aPcR6kfXHzBVU5oNvhAd9Sg6Rs1P1wUYraZOvmS5BTgtYBWV1fBwA5YCqmMEXlJSUJota2DtY0K29XIH31sO+LrGzq6exq5AcOsB/sR0YCCSXB3Mgbe2UAD/omwhjQNdysu4o2p+4I10jCAZZRngRiwswKvgm5gDPyLr5wMMTiV/2fZ0j3nbrVFv29Cc4a2pX5a6spu0jQpz/qFmrm2vgH8FvZM5OHA73q+TNKCfswW+i7Xteuqn/zc6O/5GHfbgbWk5g16SYm4CjhlzRVnqbYD/8Qd+RJZaVwcfcg/+w0/cD/ClOHFxWXH/9r/g2v8iY0n9mwwwesT9LSALNy/Mwp2iQeSyWnGSKyAfz1U7jQA4f3dgY0Yi23dak4a1vWzi5ODY6fUhba+bubrRv9p59ddJ1yCGW6w4OZK6ahq7g53lwOSj3gJf+10xS2a7W6/Tpdg52f5XFuEeAr4Ixml0L1F7boAtZkfPLvdwU2BsOVk7g8m1/0oqtGNvHf/mWepu7dbxO7TYZD9cbML1sNVg1uwqYszzbzib2GMCnQKC4SbtngNYthlpyrwwIcrC9l+zdnbGuYLDhQyEIR7gGm6NA+eHk72TbecgsM0fWQOBjCPZvUsbO2gWHv7GGQKaTlcFaHPTm0x7tUPILoaIxjpELp2wk2DozSR/eQkIEXV2dGvbJ9S+7fvvrALzvU0hd+ESS+4w3ZQf16Vv3N3h0IW9X9urf9v/LZsfM/XynRGEdPXFQwqWqU7s5f7PDVBoLqhQNLMebzA192JHt/Z/o7Xahw2gEm11Yy5RCG7/qhNzTmgWjmre+dzpYUFnibScKHaMElFfRTs9CWoQvwNJA2CUcOrmb1DbukdvogF/GcSL2gX8b4r/ZyvqbJfH6drjbJytKWtkmTgKLeBngBdtwFDexdWbbAdj34lyJqPU/hjtUH/56Hqe5q/OFQrajGasULRf+FsvVZ7tG5eAX8KahW6qBcYxpr3FbYKDoHU70iDI2t69HLXIf71HVH9KExjUmzmmOP6OpNQuft3S4swWoWi7GWzNWe82pPkFMA/JcIQ6xIg6J2gL2AG4BWzqUyGcUPBjzf3WRRt9Agd2PkI9DFizbAEXCmwwmJTO4NyLON1vtaUj/0tC0oTu0hIFrQbD3hqD4vQXu1FGOxwKiJnFLPtoTCJycYWe7HW3rWHQgwWmDa/UA88WBgx+b3QN2m0Lvd7lblvoL0K6bZFWA6G2bttO8QRTe5SdDNITnpqls7VWpc7D8dzqzrnAjjWFsdmWMQOCRrUqBbTWKWa5wFNgLSuUY5cDHnA56EZj7GhaY+zfLXRZIPdU8J1V+JAVvEGxt/kOwViIsS+WiYUgrhzap4BC8ZUL0YCHQzjWgNzd6m+VhyRuAVuCXwr8NxjRA6s0mEdATudCF1K2rjsCBrTJx7TrdbAh1bK0dScLbt25uUrM904JQTPN+v0de2vdzv1VQ43BHBcojzLjsjMQRmcRE2snDzJOub2k6Nb+HobyXVpuoB1GcHfEWOr671oXFVTXB3bX2062HSFsZGgKBxabd0FM9zxwLmJYG1mHmutl+uW48Rpq8eqW6mVziIu/V0ZDWsyWgL/Xg0LXXYX9qycMkNGtwi+2FdOV6G2hywqQxXgbrVoAPVDGtVufKkt/6pXnVu5WtDq8zesgmDl/U5lXokCj1r7aJDPetL3SbCr7qBsgGdLNgGpImofI7nepFWg/IttSKynAfumdB+iombWG7QbNsBab1IpRYaSA+uhSQsCI6I3D3pyqRi21Ai3A9dLj1AIKXQIV2sJsRwmGIYoeGKVWPCROZKxWWqpdIbrM6V7MmmNsS62AGux2R9IAGCWcGorxUksLzDIrcBZiUWYlx83hSuRvonr6D4eBFdsWO6OcWfEbMvaqreV+zVhL+8VNpodyUZgHxmuRxsBhN44dA91cRbub84Fmc9kaexsb0hwW05yPjhF1stJW1pw+mPOBNuxjmvO5BPp3CiDmMmY5n3dAGH7J+f8855PZOmFq2mcz/QylVyHxBlcl2JjzAfsDBUBrpTBLGYC7AzcXjvVRPOA6hUnOJzpNlNg8rF4rXHuO5tpzP+6gmPORUtde6LqrEJ92XHPa9w0jLvdykQENCEwoBAMqOnOsAblnsjrnA13i2bSXA5v0qNOOaQtfowHVprQVJxduxZH4emMa94EgYoLC3Did7TWdjzkMIbk6WLsDgZdL15M90nhXF8AYZKqOmtYeZDklRZxz+/u07eeo2+Su5X6gh8Fg7o9B7v8udSPzE+CHlPlJ8UU38yP+ZHramKJXxELui9M/F7XaoJP5Wfl6gdWoFm2DfNVXy5XV6vehkPmx8kPK/ACy9KfMD4+SovJMlJM/ZxzyE29NddYIO5zSVDktT56NyR94W4LJH8CWNIdxsK86DOgRUcwcBrhovttCOxXB4DDAUxEBWxgcBlLo91eHYSldZSJou9Mg8F2G5Lwlx8/30GGg0O3fuIXW7c8wisBuf+B79yePgHou2IwsYvpu1hidsqiLmdmrJGTYeASAakim7gCMLgBD0txBHpw7mDQtKPl76D7DfXo3lw0QHH6uM/uf4ORNba/s+lmpMZ14YHa03+/SzIeeAGd+K4wI0PYr3QgUXgTSAgWGvSkYKMwN7Fbudjw4kMFUF/ht7cg4qbb/U+yYE1H9PKQcS89KkUpECydPuHXq+9+AWn8PGaDLEwohw61A2rhiupsICWRI3SIJJAoRiJr3p6rk4erOXCTpqy13D8bN0t+sYf4rUvHJlb/hp/4uEnTSoiDSXESRXmztZsfUf6d62w+VtI9sphJBS4RsDEo6RgvDLgYMSgCZaF4oH84LdZvT0cHJZQGnA7qFYSA4gJ/K1ERQcAUKBIdDfVJCaPKx6xJCAR8oSHgYTsIeEmvhJnTviLXQtiCUibXQejYKGah3YF2aGbF28jYSccmObe1e4AhqxxHBX8LmOCIU6ILBcUSIQaDnSuEMwnBacSrB1cvGmYyzdQbuh4oQsXPypH13W0AtIIR/HLC/i6dTArSJXIcTweAID9ySJganU4aHaRMJuYl943RKAdxQ5Riw+5Q19eM+zHXQK411mmyb47EcHbD7UIPZXy7vEdc5pHdroaXEtfMogN1xrrSQmynYPYXS7h2O9p2+NijaCeO+NoHVSNlNRSd0s5sC2nH5k11GEg+NdiWs8ZrAh052E4rXQiEKf+eElN0EZOlXuQxFlHMZ0EoUG3cR8IYEdxGAIWkeohDOQ/D4ciXfvvRUZ096UqpmpUHnxygMM/Wy8QSJHEzTGXDTZFyndIbHf2/RJQcB5czB3hBjzZ3uYjdchLEPUl7jnXfva+7spJrD5hfaau7U1jkgtgMDPjpLMbWM9uJfO0OUy3Vyi5sS45fdftH9JAy0pBvEd29GncM1/cPuNjOHVCfpo+DZFH2Q8gu7153sAQO8OyL9uPxKPuCEpl6FTf68fc1vV3c/CcPQXIWB+/dGEsnYu5+5/+7Uysf814/1N1NDq45sXAY6Rj3TZBJgbtoyUNQntvHQEY/yNh7KJEVhG69oC7ONP7idRNRxtWnXvxhOf69vlTMKUsz0E34tWxmqujek8xM9CE4OwPa0bV8MNQNSdW0KDVmD86D9apsLAyYHsPdFsgBUIqTbYQSt47o+xge3v0v7skpVmPoBHfs9kFs7yNidbO/k899H8JpY27X9m7pToVrZy57uR2jxdvtI7fyHu8v9JgRg0VgFGNcXz+gtkysJxAHBq9qNW8LxG99xenrDJ2+MMsh+/jXl64FTquhsfPUXvdM7+/kOKdpZf3G+TKwDChtfqzykjS8ur13yUtQyu6yEWNu4JewnLrikUc7zKWLcToIXHcR6Y9ShPVeqf+uX+u1K4q+jkOgg1tVDYy/MSGvUS00PIYfsojTTQax5S7wF9mUlGkUrJQWJXq3TooNYC726c3ftoBbdyEUjrkUeJTjTQayL3vAdPGn8gRCaXO2x+tFjdTqIdZo7Ll4kV1c3Q75613lP4Q90EOuzn1RkfgX91A6YrESUMBW8TwexLnqiu2SpnKd6cTlB58fqzZfpINbO2R6qauIG+MjQbdc/25Ci6SDWedpnBKyEq4m7zIXPppSv2koHsU7SWBsZePmJXk1N7VWt/MpCOoi1enCNys1LOob7M5eZXTIuHUgHsV4lpmUvh3+L3+FOHMDTWCxEB7F+KGCs+U7WQH/fzWYD/sZftnQQ65DH66xyCOZaWdOkf+JUtEXoINZnB1O854yu1sg2dkwu5pdaQgexdnsyctK0Xal60ZVz1rznux1CB7FeTjo5V/jRfc2MU8SH1Q63crsOsTZUsVXYYPdAP7ckRGDHls9nUcjflw3sHxBr6NTBDGL9WrQeAWLtLFrPSoi16apyPoHCH/g9tmtdMyKrOz8gujcQ6zMPbrwqjK3B14RcF+UjVMmhcI76KSgcLLY5q7Nw3FzI0XhPyLxF9WSLp4nXdUoP3BEQD3SAUGJYDLF2RlRDUbQeVYh11J8kyouZK7UT4o/PCJTi+sZ2iDV1MMCCiSshX/9vo6H3EOt5oatM6w3ECaU5l1bweL0O6flEQkGcaERxnCHiDMBgqkyRE3/m/XSTwR6+Yo+0EcKEHk8VNOQgIMoxUbSetpSVw8V8fQRiDQ3xMIZYj55UjwCxrhTr1kLWFYh1tYLXUdFdb3WzxjfWSZhbuaICsYZ6NhQg1sNBYWDpzU/FmC5UcFuwbkCsFyQMS3Wxvqmz64+M73Kv70vZDLEGRgCCDNFi9Rx7BobFEOsANenXPg/26Efa2Usd3fZMjI0drNShyzTdB3awAhalucoK1LpGsINYQ7e17IRYl/yDWP+DWP+DWP+DWP+DWHMcxNrQvHcYawsO4Fjv1gAiquH1GHKsnyVqEKdFDa/vE52ClXDhSZ+FLUET8WzlWKuPr0fgWNeO69bOr8uwpav5wyZPDHqhtdd/xXzBGYIeqMGWNKf6+V+OkiZWz9adPiloSxMaHGtQIVh8r8D4bm0Buw5bqoqpURq0c4Z+ikW1t3WB/F62cqxfjEPSABglnLr/41yOtZTLwQXniy8YHsm4v/on1+PObaC9py1t/O0W/2hNgU7l1PhHpxt+XUBhIsQjDgK3cd1LU3eXaVTgUuvktsNfv9p87vHraTmNbE1bUznW4+sRONbAnKAtYFVwCxgHM42gBWHMOdafhOsRONbJwvX/30yjV/sfJe0+VmGYHV54UTFYq3OrDes51q9Ba8FikE8Ic+xygB3HumTPixj5yvXErYb3z/Oq7fOGsVBPejuhrQoo1F+TEQ3oybkGZD3HGrqQsp1jTZ18sBxrwLK0dae675z3gTYZYXzehzS2HuG8z+ixTPc8PT7vk29Qtfaz1zhCylnVxogGr0HonPfR2e928VnJfI3yEG3Ncc9bClFo+CaMrUc47wPI0q8avtFml4QWOxvPEOY3itHYbOadcF+PjY3e8IYEG70BQ9I8RE2/S61AWxLZyrE+N6oegWNNGoVNamX2ftVv5de1NWK/bZ/2Lf/iUNRSK9AaHAr83hOgQrD83uRRGKVWDl3ao8U9/Id2SWOUi2DgYVW2pVZADTwRNQBGCaeGYhzLsa7cIDnk5JlrRlvrrqrEvK4oRzmzQt7q4RxwU1E90WT4KK11N1RRmAcSiGPgpwDHjgGMOdbQbC7bOdZUhwXLsQYmK21lre2DOR9ozz7mHOuVAvUIHGsegf/znI/KhIIavqFvieULckfU82lnspljbQZaCxaDLMu5Pgo7jvXMXBNJz7pPRpXS/mSC90o40nhPcj6iLi1fpAK4dBOm3RUJlBCyReH4IQ+iAe+N5FgDsp5jDV3i2cixpk47pl18IMcasCltxTkGt+JwOpYWeh4MU471YSGkzI+PELqZn42K336fdDyof6RhUei7p2d2oZP5WbS9Nlwo6oRR3JnGN5Wa1TwoZH6yhJAyP4As/SnzgwXH+lmk8Q7VA55aW06orpC4d8GTjckfeFuCyR/AljSHcbyvOgzoKVFMOdbRo+sRONYrRzM4jF5xrD8I25bdP6OqFf1gqPsSScC998xhoNDwHza6HoFjDXzv/uQRUM8F60x9M2L5zB1GqXdxVQ+ic4XZeAqAakim7gCMLgBD0txBHZw74CCONfQQOIYc691j6hF4T3PHdCt3202O9afokLjQ8IsGVbGa2wYK4x71nmMNXZ5QCBlCxtQj0IGsxjCkblHmWK+d8s3ux7nl+lsH7U2M+Pquc7aiRxxr6KRFg2ONKJLAmG52THWTYw0tEbIxKOkYLcw51mPavdAJOC/E0RBm6Bam6xBmKLsCBYjDyT4pITT52HUJoYwPFCSsh5OQowBY0LYglAFY0Ho2ChkoO7AuzQyAVbCDRDyi2FGXbkDtRCL4S9icSIQyXbDnWEOPlrKPYx2CA4MjPEYc672btYmTgnB943TKqb7TZAVFDWHcZGU2EinVNnEkuqm2LYUEq3B9f4OdO7dMJMXiZdFJtUFxTyiEhKSRSKm2iazNwmO+sUYbqgwti7AxpIU3JBjSAoakeYjTcB6C46DKUO4Z5lDlp4JIm+wwwd4XgPsJVPnh8LGCLxRe4ct0L2dIawrc5kio8j1BpM1uoWA9xlBl1UN/1iTxyeADfo89/jJHS777GQGoSBi4/zBEkewE+5n7xwiqDC2BsXEZ6Bj1TDMbgLlpy8CZPrGnhI54lPeUUEYmCntKrhEwe0o1YA3Zf46/Xf+zcPpzGFQZKlHfhyoP5aL/0y2osjF/PXOoslwBgRhl2GHcc6jlvFhJ+PX+oTxujOQpUnr5HWeL4ggcHeHXa+P5mzjvlzqHzTITMx2/7Kcj/L67tpuLsEJH78DQ50vnPtniREf4NY986j7RexmxwjUscazKLVs6wu/3YzOrooxT1EslL5S8evyBh47w25Kye+WgiUPxuck/L9w9fuERHeHXq7j2ukzRDs2IzddG59yOX0BH+E1psr915mCRTgDfnLEuMlf30xF+r6d/vy8zfjzxQALfs0H39y2nI/wO5zn3tCisSn/n/rqC51sfNdARfp9eUZdVOx5PCg3c+dyaMjKejvCr0nBWfFP+beKOT8MH64+oOktH+G0N2W77icRDOrJttvfp7/Y36Ai/8TVeZ1o08XrFN/ED3l7OzqAj/P7ZcmXzzi1LNA7OLNJw2ZgQS0f49f/qFTLkbItB0FKJJ7e53MPpCL+a398l3VS20aj4knX6iWx1JB3h95vjk/lEnSuEQ2GmFLWKLVvpCL9lpyn2fzzG6e46vun005L7Ol0n/Co+DltYK/aLkFf4/dfIj4keKGQ2zw/sH4Rf6NTBjPAb6IJE+OVxYSnh14RnoqQ0bp5Geku97C7XlM7PzusN4Xfq1qH4jG2fdcI+LQkUGzasBoUTphtckJi26i6YE37v7XMea1jbYBg+/lJs+v5qJbYSfnkQ1TjljC7h19Dw4cPomhEGSXXCjxWv7JjBdsIvdTDAUlvNXFhN+M1z8bhcLPiHuNVyv/v0gt1kthJ+ZRHF4XHBnvArvGga+euOVGIlfufSF6+Tw9hK+L3njCRHoXN7zHcBLubrI4RfaIiHMeH3IAWJ8GtGQZ3we8CmVdBfK5cU09KyB2cueAgVwi/Us6FA+M2gIKFtN1CwIvweXkXWn/7CRXtP7Z4/JWdmmrKZ8GuGKIMshXNPB7CY8GuoVn25UUnYoGLTce8H861XsrG3jzp0meaeqCcHKO2u8iJq9XTsCL/Qbe0/wu8/wu8/wu8/wu8/wu8/wm9/JPzeW4kl4VcrUYNof2dl3+ihugQXnvRZDA00Ec9Wwm+yExLhd6ITNhga7wUL+RzEBYyyt5XzEWZqiXdh+9c1DE3gqXvbFDWrdBNtWv9kLNldggLYNNoJCWzq7IQRhmaqa2yr0RIJ9WT/2cpFd06dZCvhl4CoATBKOHX/x7mE3zJe26n+i5x1DpyUwJ2eVDkVZQ6Ng49GfsJDX8293EdeLtpjlo3CRPjkiDQIzjliS/g1sFv/aeJoUdLObySxX/zLI9hO+KX6BVjCLzAnaAvYZbgFjINpL9CCMOaEX2NHJMJvq8P/Oe1l89SaMfq37mkkFOz6PbRobBCbCb86jkiAWJwjxy4H2BF+bS3XxUV/JhuGnj7jy/1JYiaKtBdoqwIK9VdgQiEY8JIDxxqQ9YRf6ELKdsIvdfLBEn4By9LWnSt95/AJtMkI48MnWfZIh0/c7NE9fJLB/zGu9EGM0XZ5jQmk3+c7l/J6fPiEZ92bUlt7bt3EyN+v3kXfHotC93GKPdLhE0CWftV9jDbVoeC79c+7q7N1qp+b+jw6ePQDmyo/YNcxvCHBrmPAkDQPcbXfpVagLYlsJfxK2SARfrOssUmtxH5ee5lH4wAhfYXknuh3gfaopVagNTgUyKY4GySyaas1RqkV77hzzRMW++nv2X1hcHbefj22pVZADS5ZI2kAjBJODcU4lvArr2bvMZinmBgp/GoNz9r7PChnViQGLR575Fy0ds1V9SxFMZs3KMyDAMQxsIxzxwDGhF9oNpfthF+qw4Il/AKTlbayXuuDOR9ozz7mhN9SKyTCr5XV/3nOJ23tYNlrbjZGEREJtgqS063YTPg9bIUEiA2x4lgfhR3h95PF6jNXJy00LJt6YcOXeh8lFHM+he9C5jd8MyNkH3hyuzHubG8XGdCAVogGnMu5BmQ94Re6xLOR8Euddky7+EDCL2BT2opzHW7F4XRgJ/Q8GKaE3+F2SJmfa7boZn5wSrVL7IY1EWqaZpdaheZVoJP5IeGJmeUzZfTCv33g8SNN9kYh88Njh5T5AWTpT5kfLAi/LpJFl6qK8UaJ5x3P3c5ZO52NyR94W4LJH8CWNIdxo686DOgpUUwJv+/skAi/pXboEn6/Z93fO/FSjtZehw3ruBRn3e+hw0Ch4f+FHRLhF/je/ckjoJ4LfheqMmWFxhZS2MH5kdaNBevZeArgBaw7AKMLwJA0d3ATzh1wEOEXeggcQ8LvazISfCiajCXhN/i6o6RJSJ5+iYLZn4QTAjq9J/xClycUQoanZCRUTSUZa8Jvq/HQSS2mSwiBr0/k3NRJ75xI6RHhFzppURApGlEkZzK2hF9oiZCNQUnHaGHKwQFkonmhW3BeiKPxtNAtTNfxtFB2BQoQh9t9UkJo8rHrEkIZHyhIeAdOQo6iMUHbglCmMUHr2ShkoArtYWhMlcCi+npLR136LmonErEj/EKZLtgTfqFHS9lH+B3thiXh9+A2beJQQbe+cTrlXt9psoKihjBusjq8CvFhWqvQTbUty7BwoXy+gs9SeDLUUkD/LDqpNijuCY2Haa1CfJjWqv61sUab8Asti7DzSVqwhqQ+SWtV+2J2H85DcBzhF8o9w5zwq26LtMl+YfOP8EuzzJ5bD1euvL5Fa5eLIdchL2+n7mcEWED4nWuL+DgbW6wJv4J2q5OHxyvrBJm4nKeIGZC6nxGAioSB+39hgyRSrU0/c/8YEX6hJTA2LgMdo55pZgMwN20ZeNAn9pTQEY/ynhLKyERhT2lsCbOnJAWRiOfFLNv1fwinP4cRfqES9X3C72gu+j/dIvxmWMAQflVLCMS6FIt24zailvNiJeF327W9p8iTy4j7zOLxQQ+Ls+kIvxkZ52eJhswyLLvup/Npy/C1dIRfsdFiDte8v2rvinzAE5dkv4KO8EvyWLSvyU5bJ906brSF3edyOsJvM+/Ec8YndmkX8wi/v/txuRId4ffm8D+fLMmB2iFBm8VU7cre0hF+BW7p3XRTESfEZy0omxcs956O8Lu4bmfsSptcUqSUMIH7e0IZHeHXsq6a5MltqF0iRIr4U3ZHjo7w+73m7o31yc91twR6Br11rcugI/z+4nuufmfTLYMDixoGbg4uOktH+P0R5bo2uDXHsOjEqbnT1e8S6Qi/Dl7D8uQ+DNdMd024fy1brIyO8HszzrXYNe67fmSgSfPWPSLr6Ai/z92viA0eVoIvXsibPGBQaBEd4TevQlXcOWSbeoVbzUSLZhNFOsLvq+c3WnD344yKhx6bn6h/uY6O8GtuGzH1k/IQowhZ0uuJuKibdITfUveqH9Laj7TjNYSGu4W5Xeg64TerSGbqoSwv3f3LhLdnrnljj0Jm89HA/kH4hU4dzAi/YUlIhF9SEksJvy1qYTde7XxruOP+YLkTYnsmoUb49ba2m7aRNF89eOooY0+F9z4onDANSUJi2q5Owpzwm2XJ/6NxcyVp51fzs1dyh4uylfBLQlRDPgldwm/SRK0qcpQ54eCxyA82tw8osJ3wSx0MsNRWzyRWE37PWu7xXnXLgFBVPOuAh8nncWwl/FohikNKwp7w65C90WZV9Q31qlyXy4/+7B/Y46mChhxzEeWQSGqP+R7DxXx9hPALDfEwJvwOTUYi/D7o3kLWFcLvnhlLR3y47Eoqmx6UelgkWQUVwi/Us6FA+B2UjIS2/cB8oYLb9nWD8Js1SWW/Zm6ORmHsxPf47XWqbCb8PkhCkuFMEueeDmA14VfaaN8sq3r8vknDzimvbX3Jxt4+6tBlmnsCe/sedLjKJ6jV07Ej/EK3tf8Iv/8Iv/8Iv/8Iv/8Iv/8Iv/2R8CsQhSXhVzoe+IiRUX2jh+opXHjSZzE00EQ8Wwm/bglIhF/FBGwwNCcnWZ2h8EwjZuerh3E5me1ADUNjtHXaj0cBo0i7N8tQRG8UkVAAmzonIIFNlyVghKGxJ7wwbp2hZhi00sfvWIpSK3sJv4gaAKOEU/d/nEv43XKp1cLA7xwp3eyEj+KraZ2RkL3n0Ii4xrbMkivQiWqRyY3SGKSGwkSYiDgIBidgS/h1fh0baSFwTf/Az7QXz7Zmd21njSXhl+oXYAm/wJygLWDP4BYwDqa9QAvCmBN+z8QjEX73xv+f016eNOMvNS/01qyaqc9zscqxcwMz6wm/9fFIgNiCeI5dDrAj/H6TP3LWUWi+7mGxx88qn71xRpH2Am1VQKH+uhfRgNs514CsJ/xCF1K2E36pkw+W8AtYlrbuPO87h0+gTUYYHz75Eod0+OROHLqHT943HZ28Jr8Kn2Q5oTAmeW9nfHGPD5/YeFuIEceOISQveVee7XpoEQrdxx/ikA6fALL0q+5jtKkOOueF1r+xtTWMnhwReNw6ZQGbKj9g1zG8IcGuY8CQNA/R1O9SK9CWRLYSfotjkAi/3jHYpFamuOip21qV6GUbfKOsvnfrF2qpFWgNDgWyaUEMEtl0bwxGqZVLY/ifjrr5Sb9gzqKTL93Or2dbagXUYDuiBsAo4dRQjGMJv3Wrn6049a5VJ89jzADZCwdsUc6suJonPD5xJoKQe6eiar4N8RMK88AGcQwYcu4YwJjwC83msp3wS3VYsIRfYLLSVtYXfTDnA+3Zx5zw+zsaifB7Jfr/POcTp+i3y+uWoG6F3H4cjvcaDxtzPmCL4PdoJEDs82iO9VHYEX4zrPc8/34lhhQlcGagxr3cXBRzPo2Se4nvWubqRu/XWz9zwBphFM7CXUE0YDXnGpD1hF/oEs9Gwi912jHt4gMJv4BNaStOM9yKw+nATuh5MEwJv1mxSJmfsFiUMz+/W20PPWjCbw2oNZdtLVuETubny6CWTZ/Mbuvst/PgWy14ZDQKmZ+MWKTMDyBLf8r8YEH4bZBI+aVXf1AjovrCiVS+0zVsTP7A2xJM/gC2pDmMl33VYUBPiWJK+BWJQyL8/mZ0GL0i/N6hJMy+sGaGfuaiKpsxc0L3sI/wOzYOifD7u395BNRzwQ/Kt+66OdCEkKRPOMO9o8aNjacAxsLmgsHo4neHO3gF5w44iPALPQSOIeE3vr1ExBQ+5My8RAQ3YLpJ+NUmDOEyqUvWKxi9vGElWa9z/qpHhF/o8oQGvLZ9XDHdTQTEYU74dR1yehgxjpBhMkR6U8Puzs887hHhFzppURDJGVGkZXHYEn6hJUI2BiUdo4UpB8e5oyL1Gs4LcTSeFrqF6TqeFsquQAHi8KZPSghNPnZdQijjAwUJ38JJyFE0JmhbEMo0Jmg9G4UM1Ih4GBrTgB0kotrnDi/QgtqJROwIv1CmCwsIv5Cjpewj/F5KxpLw2wx8xNoLyX3jdMq7vtNkBUUNYdxk5RuNlGqzjEY31TZd4fzKCw1RusXSr6TX7FGejk6qDYp7QiEk9I5GSrVZsjYLj/nGGm3CL7QswsaQFt6QYEhr2ZGYfw/nITiO8AvlnmFO+NWMRdpkj439R/ilWUbuyvU54yzcNY9YlR68tG0oP0cSfhfEIm12ZWKxJvyucZF5EpjAZRj788nBzUM+lXc/IwAVCQP3PxZRpAH9LK+KFeEXWgJj4zLQMeqZZjbGduRXP/SJPSV0xKO8p4QyMlHYU56JgtlThu8C9pRHotr1/winP4cRfqES9X3CrxgX/Z9uEX49o2AIv/5HCER59w7jfkIt58VKwu+FvFnzz15/qZvtMqLi5J6XY+gIvzoO1rui1983iJodPPf9wHsP6Ai/ws3j9h9ctdeoOMgs/Kv6wp90hN/QSWVxtvLZBlmXLEpsfpZF0xF+Pzy0//k4/CM+Yc9g9wVWqiV0hF8LcuOcp4G1+nm1r8bGqkmJ0hF+nVPfpyhdK9UJuvXWwbGlzoSO8Os6QH6S45FUvc2l+9Yl78x4Tkf4ffHJgkt7zkL9ougLlzYZvt9GR/gleo1dl1SbQAgOWCpgV6q7jI7wO+FxTLiroZ/2wSi1lOsPKi7SEX7/BF7Sun1qlM7BI/Gr9679+pKO8Dv/oazDCvPRmuGBpxdJWp6qpCP83j74PObGGS3NEptPTiuv/sTTEX6jyzxkrB55kI7mHpwtskLGiY7wW/ZTy2BAgjlpa+6cNeHKvlvoCL+7czJX4zOKSLt3HSXgd9z/Q0f4vfF5JvmKylitvTLlTa0TyKF0hF/ctfjgN8kniTkjVsv4XLKV7zrht/hh88UD+b+1dvMn1FsvlXyGQmbz88D+QfiFTh3MCL+Vx5EIvxuOs5Twu2Znqc3a02MIe2eOfLsgJrUzu7I3hF9i+VW/9xrztaqC707SkpZ9gMIJ09LjSEzbxOOYE34H3Dluvk9uqPYBhf3Rx3RwnR8EzWrC7wZENSyPo0v4NQne+pjbQp1U5rhLXvO5S2uXwmMsCb/UwQBLbc04zmrCb8iKMU07Z50l1KTrVGaZ7M1iK+F3N6I4G45jT/glOswj5BUGqB8cMWDU40cJ1Wwl/DoiymF2vD3m+wIX8/URwi80xMOY8LugDonwK1iHOuE384NgRWzyQv2KsdpRSw1qIdjoHhJ+oZ4NBcLvvDoktK1kHVaE35WzeYdpGVXrRH0Uu7Hxs1cVmwm/gogy/D7OuacDWEz4HV3NozyxaJ32AfOl9YZjZBaysbePOnSZ5p7A3j7AojRX+RW1ejp2hF/otvYf4fcf4fcf4fcf4fcf4fcf4bc/En4by7Ak/DbHaxCDHpT1jR6qVrjwpM9iaKCJeLYSfk1qkQi/grXYYGhMlZedurtJ2Si39te3pti9S1DD0Ey6u2B6/Lxm3YjS+vWHt4ZOQwFsaliLBDadV4sRhiarJmbKtYWROqWOycut4+d0flw5qwm/kogaAKOEU/d/nEv4LZO+emT4IEeDvTV73PiPR3bOgPSeQyMVr6lsd9VRPWJwydvhC7mHozARftcgDYKXNdgSfpMO7DkeZ2SusevZgkIz55tdO6+CJeGX6hdgCb/AnKAtYN/gFjAOpr1AC8KYE34P1iARfgNq/s9pL2VZgnV1mX564duGzyRprurMJGM94TerBgkQG13DscsBdoTfqj3nfic4meskNsiG3bAZPRrGQj1pNIS2KqBQfw1ANKAz5xqQ9YRf6ELKdsIvdfLBEn4By9LWne995/AJtMkI48Mnt6qRDp9UVqN7+KTw5j0fvOVzwm7RgN95a+ceRefwyb3qyqbt0raa2/MSFry5a3kVhe7ja9VIh08AWfpV9zHaVIcGH+GUsMVF6umy+TfHzDn9i02VH7DrGN6QYNcxYEiah/jR71Ir0JZEthJ+4yuRCL/LKrFJrbiXk0NVzeS0CyZ/IMpfv3sGtdQKtAaHAtk0uhKJbBpQiVFqxXDzJ0/LY6rEfCnC56rHWRPZSvh1RtQAGCWcGopxLOH36jpRsgKhSj/SP3xCkSHfbZQzK3v3XE1fSRY32lYxIabOZwsa84CAOAYUOXcMYEz4hWZz2U74pTosWMIvMFlpK+vPPpjzgfbsY074baxAIvwWVvyf53xkrXdKzA4/QzqspWj9ZaXyCTYTfu9VIAFiT1VwrI/CjvB7/dCOqisx3EZ5131eDchXn4Nizke5dJbgAYNKvaLHE0+8uN0chMJZuEJEA6ZwrgFZT/iFLvFsJPxSpx3TLj6Q8AvYlLbi/IJbcTgd2Ak9D4Yp4Xd7FVLmh1KFbuZndlTJBmWSpVb8rNOXLT6feYVO5kdst4Ty5Ff8GmHndKyvNU2NQCHzs60KKfMDyNKfMj9YEH795/5q/FMep1v+piXtVARlCRuTP/C2BJM/gC1pDuN3X3UY0FOimBJ+f1YhEX4bGR1Grwi/Vz3m+gY9faKXoSMgan7poBn7CL+tVUiE38b+5RFQzwXffqPB5/nkrm5oVOCiQ8NXxbHxFEArrDsAo4vGDnfwB84dcBDhF3oIHEPCr297iYgpfMiQeYkIbsB0k/ArZ+9VaO5K0o38udLNUS+i8/MlekT4hS5PaJDK2msMTHcTNtVYE36/WgSlNBaQNEvf/xm803deS+8Jv9BJi4JIhogizavGlvALLRGyE4dWDbeLAYMSw46KFOg10EF1sBJPC93CdB1PC2VXoABx4O6TEkKTj12XEMr4QEHCAXASchSNCdoWhDKNCVrPRiED9akahsakFkgi8t7p8AID4fTnIMIvlOmCPeEXerSUfYRf8RNYEn4XBmsT83En+sbpFB64ocp5TVZQ1BDGTVYrK5BSbeoV6KbazuIt/TZRFmqHj5p5v+45vgWdVBsU94RCSLisAinVps7aLDzmG2u0Cb/QsggbQ1p4Q4IhrXpHYp4XzkNwHOEXyj3DnPArUYW0yW6t/Ef4pVkmqVE6P2PmEsNdH1ujlEKsDDiS8IurQtrsDq/CmvBbskNtZiR3nVHJiaULtgfo2fWe8IuB+2+tRBLpKWs7fbB3/xgRfqElMDYuAx2jnmlmo7WjI2hQn9hTQkc8yntKKCMThT1lfjnMnvJ8CIn4Jaa8XX8+OP05jPALlajvE36luOj/dIvwu6wchvBbWU4gflnSYdzBqOW8WEn41b4d/XyqgDYxtylqdeUdUR06wu/w1TvlhgW80I7mqrClUOQn0hF+Fb5v+nDt8wn1orwNRq/dK1bQEX5VBtyJ8/hpqVu1/fbKr/cc9tARfjNkouL0t94kJP5YrKdFiblCR/jVGiTu8k38jv6+yoSfBfNv89ERfptqcwLMiakahXUBhh4flHzoCL8xW0vcXeyENdJFgpuM1bco0RF+tUVOSG4jnDSISUqZd23puxw6wu98e+3rLnMqjVLieBVL5k+wpiP8vhoS5/u4NYAYcOPhnR/X1IvoCL9hS1P2zdy9llg1hN90yKUz9+kIvyrxons/3XqGL19ZnXPao3QqHeF3vhCXx+etNeqxKpN0tr1efZOO8GtSN+TL5B9SRgX1i9c2vW4aQUf41f+SpSGyX1g3pnZtUJBcvjMd4VeULLyi+eV8jcBdpyqEfrsn0hF+5Q0meMwjBBCK92i+bb0ybgwd4Vcx8tm0jZbLtPLWXaq2GSGi13XCb7BhtNPJZ9O1C/S+NXhkJ3qikNkcwtM/CL/QqYMZ4XfwSyTC76lmlhJ+1ddOaMiqXqhe8Hpbhr/AnaeoEX6VTU43yhs/04oade/xXInzDSicMOV5icS0fd6MOeE39GjsBnOxRp0tU91sLqqcmcJWwi8wUBDUyGlGl/D7+VnB4gOyx/GHvuakjX5227NL4TGWhF/qYICltr5rZjXhd6ZX6ae6SYcIUetwPHVak/aylfB7rxlJnFPN2BN+Dxmu0l1h62y4V7thdYmbdWOPpwoachQiypHS3B7zDYWL+foI4Rca4mFM+N34Eonwa/ISdcKvxg3xkWOnGunlJ97RN3+VkoEK4Rfq2VAg/Pq+RELb2r/EivArVSoy5/MHfY2d5pnT6w4bdz4vzHrCrwmiDAtecu7pABYTfrPH1kwjzdpMqhRI5q9ZPGc5G3v7qEOXae4J7O0DLEpzlcNQq6djR/iFbmv/EX7/EX7/EX7/EX7/EX7/EX77I+F3ySMsCb8X92gQ7y1+1Dd6qIbDhSd9FkMDTcSzlfAb1oRE+CU1YUT4nS7obyqyRj9t5W3VETNP26CGoWlep7SDOzpQ96DT5tLMonFjUACbhjQhgU09mzDC0HBX894Zu2akUWVoksCnEXez2Ur4tULUABglnLr/41zCL++oxPO2N6L0ql/9mR8yp+4eyhyaUeYecyIrY4kRFj+LypdMlEJhIsxFHAQSTdgSfqFVCLYTfql+AZbwC8wJ2gLGD7eAcTDtBVoQxpzw+/w5EuG3/Pn/Oe1laVm4fdi3X1pRokNri0W1IP3iLCf8Pn6OBIi98JxjlwPsCL9FdwcfVf0wXv2orv4Iu7xTojAW6kmjIbRVAYX6azmiAfdzrgFZT/iFLqRsJ/xSJx8s4RewLG3dGdF3Dp9Am4wwPnwi+Bzp8MmXZ+gePhE99Ojp2F/CuqHTwwOjFurloXP4ROXnt2XOgTE6NVe3XS/bvdwdhe7jEc+RDp8AsvSr7mO0qQ5Lz83k/pm1XPvQjRlXZfYM3MDGrmN4Q4Jdx4AhaR5iZL9LrUBbEtlK+L3yBInwG/kEm9TKnD9qJZmb6gyCvWqvuwdPfIRaagVag0OBbHrhCRLZtPwJRqkVEYOvl5bcv2CQcPBX2fyKW81sJfzuR9QAGCWcGopxLOHXdeIRvanGOqSAFp1G51nKvihnVjL9v755OVueGLY3ovam6JSLKMyDjYhjYDXnjgGMCb/QbC7bCb9UhwVL+AUmK21lFeiDOR9ozz7mhF+RJ0iE37eP/89zPnLjbsRdj32KjyZeJoRdEopgY84HbBEc+wQJEDuAc30UdoTfE9bzIyyWHTE4UjmNR2GEQzSKOZ9PWmejxbaLEApxuPjRI26FoXAWDphQCAa885hjDch6wi90iWcj4Zc67Zh28YGEX8CmtBVnFNyKw+nATuh5MEwJvyeeImV+sp6im/lZ7RAm+cpGVO9geN66hbdGnEYn87PFZMv4GaOnqx8lnTxZHRGhi0Lmp/YpUuYHkKU/ZX6wIPzenffz6yEvH6Mqy5Ejp3nb1bAx+QNvSzD5A9iS5jAE+6rDgJ4SxZTwO/sZEuFXhDFV3CvCb0Trz6N6vC34yIUyQx2avZrYR/hVfoZE+BX5lwtGtOPcnyo4y4kW6gk8JpVOb7YsZeMpAKohmboDMLoQ6cgFC8G5Aw4i/EIPgWNI+C18hgQfCmFeIoIbMN0k/D46/jbq5hcF7YPkr6e2z21S6T3hF7o8oRAyHG4fV0x3E8nPsCb85lslZLeY1+gk6v8x0Andf7P3hF/opEVBpBBEkTyfYUv4hZYI2RiUdIwWphyckA4vNLpP4mmhW5iu42mh7AoUIA5j+qSE0ORj1yWEMj5QkHBsn6AxQduCUKYxQevZKGSgFJ/D0JhEw0jE/LEdnSvCfYDwC2W6oH4ikcEg0KOl7CP8ar7CkvA7eIs20Vr9Vd84nTKu7zRZQVFDGDdZxT5GSrX5PkY31XbVPPuBexZJpzpTzGPypYFf0Um1QXFPKISEkY+RUm2+rM3CY76xRpvwCy2LsDGkhTckGNL6diTmx/cZwi+Ue4Y54dfyKdImW/npP8IvzTIH+V9EznyZZpC6w+5Kw+gFUt3PCLCA8LviKdJmV+sp1oRfoydHXO+eF9aNHXlz2IUtcvG9J/xi4P6VEUUS61+VFswIv9ASGBuXgY5RzzSzodxRbhHpE3tK6IhHeU8JZWSisKd8/QhmT5kFrCH5Vx616z+hjxB+oRL1fcKvMhf9n24RfqMfwRB+owoIxPyoDuNORC3nNb7Ds2Kf86qf5jgzcsR7vV0jRyg2Hrlzlo7we4HE66sikaJfnGi50/xCsQgd4Xf6Sv9D1mmnDFMzNRauvz38Jx3h94PclpChpSba28Y6Lju4aaISHeE3+nS47BreIlK1tt37WNFgRzrCr36Bbpmn5C9SmLVIQsO3uxfpCL+X9r44ZuqcaVB5Lm9Mck79ETrCr1fasYYrru7aFfYDtn3OP3OFjvC70pkn8uAxI41yuyiV7SokKzrC74PkVL45mmSDhLyEJ0PrVxrQEX5PaKk8uOp8kBTo+2DJq1W65nSE37XvB2c3lp8m7lk0L3e18egddITfR7yjnMI9jmrmqy7ayfs9/Bod4XfUPQlTxQ9btVMeithFLrLWpiP8Rm4UNl+Q/1G3xEvS2/nwpQ90hN/VCjeDLjrzaJSFVhGyz3tOpyP8mto//H7Pzlz3kGqts2Hqpwg6wm+O3s77VwfP0Y5b7mDpfIywhSF9CfJ+mc73BKGJNsqhPMS4oIVnbadeFEIhfSnaTzC+0PmBGcY3anADAsbXY3ADKzG+K3MLBl3TytSNMxiSO2P33M5Nhb3B+Ebdkno78PMnvaTvwlXPTRcMQ+EYaQQoHCy4dktn4bi5kOO/nrBJF36rOpe7i18z6MUYUXlhv1y2Ynw9ENWwG9yAKsbXJHjYWA17V+3De8su7vdXeMd2jC91MMCiWYMhX/9vo6H3GN8jw9T2frtoTcie57JdNGG0I1sxvv6I4nhAxBmAwVRZs3vgyvM50ZoF+zJSjBWNBdmK8XVClGPV4AbaUibWxzG+0DgOY4zvLVBWWIzv8e4tZF3B+OJ3CEfNER2mHpS3brfb7fU8qGB8oZ4NBYzvDVAYWH7tOeYLFdzerhsY36I7vyZsU4zUS9jw7PmbKyadH7LMeozvcUQZSgc3cOwRABZjfOe/GjTveZ623nYHIV7XD7ZKbEowgQ181KHLNMEENvAd73CVk/rdYW7oTpetnDx3vgYETp4JX7dca5cPc6eEXuFZrJKuXmIccXOPwiw51A5zx425/uBi+l71/cs25F/+ePswCngwN1AhWDyYPV+3fGzXD3PzuZ6Pq3JM0Np1+t7M9G+JkC0Aizl5KxE1AEYJpzpYzuXkfTx2YFzVuKU6+5aQHZYkmsmifJo7yq98+1j+zfjS8y7XK8+fSEFhIuggDoIFfN3bB3b3zPTVTNVx1x9+NNrsalDN/Yu4l637QpCTR/ULsJw8YE7QFjBcHzwzDc24Ys7JmwSKCcvJG8LX8P99ZnqS+sN3u96aaQQIN5Q0LZohw2ZOnihoLVjMmhDnLgfYcfIME/jXXDTI1ih43/q+ad2FZhgL9aRcD60FoJDgHIJowD+DONaArOfkQRdStnPyRNvXHaacvCEd687kvtPCCa3iYdzCWTSoAaGF88AgpnueHrdwbtx2Injtwq/E6Gsu5S9Wz+h86L7HLZxnfh6YVZzlRzp6qdyeoPTTF4UenqODGhBaOA+w1in0ubORXELB3hvuVhEj18ZUjVkmNJmNvTvwhgR7dwBD0jyEeL9LrUBr/mzl5MXwNiBw8rx4sUmtDLGMC/ea66abVBVz1Vb4uQhqqZXqB2NWrZn1WWOfXOW5R1UB81Dgg0WBCsHywUJ5MUqtzBEeMiLa19gwZ1LLiI0/lmSylZO3CVEDYJRwaijGsZy8gHt1eafDtxhtI6tIzfgYfR3lzMrIsuHrhsYvMtrnEv1zYbntExTmwRrEMWDNuWMAY04eNJvLdk4e1WHBcvKAyUpbWaf0wZwPtCkOc06eCigmLCdvCu//ec5n2Xoxd6c7Z/XTlUn8nssXJrGZkzcHtBYsZk2Oc30Udpy8l2fMDlWOPm+YXmLCHz2j5SSKOR8TgYiH3xYP067SvjdY/9qEySh0lE9BNOB4zjUg6zl50CWejZw86rRjWiYHOXlTOlYcib6KvYI2XGPKyRuBmPnhQjnzk7k6zH7Uqm+a+8X8Nt9RGmqHTuYnKMwq/FvrOs2A5evX8l/7lIBC5mc4YuaHq39lfrDg5N0bwyN2NOuLQemfwocCi3ZLsDH5A29LMPnD1ZH8mdpXHQb0GAamnDztQQ0InDwVRofRK05eoLKaot5TW8MUW9f6LQFXitnHySMOakDg5Kn0L4+Aei7YdHFK9fFVMUZVny1x30Wtr7DJHYBtdkRYdwBGFyod7kCyD3DyoKesMOTkbWsPFJge4XdjHijADZhucvLOT1pdHfd8v2YKRUPiupjW5t5z8qDLEwohQ2D7uGK6m/AdxJC6RZmTF5T89OeE/Rpa5TXJ2la1xzJ6z8mDTloURHJDFMl+UDc7prrJyYOWCNkYlHSMFqanyd06vNC0Pgl5g25hug55gx4OReGUpFSflBCafOy6hNBDtChIKN0nmAbQtiCUmQbQejYKGagToBdgxjSwDyQR/Us6vIBMH+DkQQ9NY8/Jg57dYB8nT30IGBzhMeLkXQzXJl5cOKShT3DypvedJivoWX6Mm6y+8iCl2pp50E21OQs5NubiC3UOya6y/XE7PxadVBuUp4BCSPiZBynVBsjSrzbWaHPyoGURNoa08IYEQ1rAkDQPIdtnOHlQsAjmnLy7vEib7JMoFID7CSdvhp0K6YjpUsKuQ0ttX5dWLuRITt5tXqTN7kXeBow5eQFBY+fFODob7kzW+/r4dsuR7mcEoCJh4P5PIopUwdoiLPbuHyNOHrQExsZl4DZsfRZcBk521Gfl+sSeEjriUd5TQiFUKOwp03hg9pQfQkhEv5iOZVi+j3DyoBL1fU7efC76P93i5HmDxmXGyXtWTiB+8eowrgJqOS+RDs+Kfc5rwklDsuUOe72SxeLmA/cJmdBx8hZ9a+A/451ICPh5ePU41dJZdJw86c1NtdIDJhmE4wjkqK9fCuk4eb8EJyUFW8sYxd8ct+yP2Z5yOk5eBX5a3oMPKoZh+ysfnL9Vc5mOkzdgZtbYF7fS9Iuvls/RMTW+RMfJC7bZfEry9SCDAIn7N/S+XR1Ix8njNkjd+iT/hnahRHRp3jn1TXScvJDRjwae456ovr3uVrH28l+VdJy8fLWdwr/OiBHjnlT4R7je9qTj5D04qZZs/NAcX+b86o3W25MKdJy84p0mlx/wzDHaenbCaC5S3hc6Tt43a8C6J1J045OenJt26voqOk7eJtHq5ZOuX9HPkVw6a8etUmk6Tt7S5KWrXp/T0k6QOPfxS8FrAzpO3nzpBYHZx17q7lCrcShP+1hFx8kLHt6yYMap6epVqrqyUrG2F+k4eU0THZzc35YYHNI9/Obj7prxwCVB2iWnGeq6JlcfE7eYtURtd1mZypDZFOKCyWweUpkhf2r1Ov3AzV7+E19PDkQhs6nYTxB60KmDGUKPTwQJodc0nqUIvSL3wwe973wilUp9qEnh5luEGkLv7j5TXiLumlHRvCK7P5923EfhhCmvCBI07st4zBF6ItJceyNWLdaN97/lnjR1a+dUAasResBAQVDj1nh0EXo8IeNerBI6b1D8dWnkkiP+kV0Kj7FE6FEHAywW7cd4ViP0Zm5Wfnj2JsXoyInaiteDRv5gK0Lv/XgkcZrGY4/Q23qshCKpO8igyuDMuOvKy2+xFaF3H1GOq+PbYz6lPo7Qg4Z4GCP0NEWQEHqyIqgj9Jwb6j4KZh82yi0vKXBPXdkZEddThB7Us6GA0FMXQWLHzRbBCqEXLZB3IOiXjOahV5E1crj4zg/9ZD1CTxZRBnERzj0dwGKE3oYMxwo7Hj39tOJpywPkJUPZ2NtHHbpMc09gbx9gUZqrVEatnj4YYez3rp4O3daiXk9/txA2EwItmJcM17K2cfLy0Jo3z8sDCNHVxGn/NvexwDk4eQNfCVxZqd+mvROr7Sdw9l6UtoSblpSPNFUJa0AEihyF7ADckjcYsFg746zdHbyoR4N85MVV+YcaWAM37WFlSvbUoF2g3qM57VNllSyAHzJdD9jBR5cCvCdY4HGltF+2UPMTb/89D2BKAS6HIi63wG+Vvz/4a8Cbdgyojnf0o6WntGi3K0sCZra1jTPZH/wo/qEE4KI39YbNKato2T2Ljg+cp6ZsKUXBSVGmK0krKEvj2tVRtqTgplhIgm8gJePo6enmMU9BweW/kpQ88Bm2a8g+gGukOJDlbV1dFKwVlGYoz5wlI80/lFrPNrI3W+e6CPhQ4ENonwv8y0JSUtPJU4NiZ06RpcgpWaipKYIf0v65gChOFCfP9RbUX3EH7GLuJ6ckq0T9Mh2mW7XQkJp3W2ShoKprb644X82EDBhUUlLXBfgf8Jb/Y+8s4KLauj48oqBiB2UgNilhSw7M0AMIioGoCKgoJR2CQ3eIpIBSSiiItIhiAXaLChZiJ3brN4Mw33ic2S/IPpw5XPi9771eBnBYa++11v7vtZ4jyfwOSJa2djZWtvQQTHvVVJJCCyS0pWDCWBl0R9raSrqZyqubWTta0t6v1f+vEvq7M3OwMnMkmciYKsrKM/6LYU1lAztHK7qBad/Y/pqpopGzDc2KoqIbRUQ3SsmKSdGNTPt3q5XbvmqjqTTtcxtppp8o6blRUoZuEC/a52jGp31lq/do7qb9urQfbGBlaW7pauVoaeLpKSflJummJOvlJfn77f3/u6V/JcXOwtma9mW0o6i5ogHtH61thbTfRNJRUVbSnWYcD0XaUmJ6RZJhdUlbSXvJTZJOdtaSrl60r/ttXA8FRTlJ+jvxMJXcpLjQ2c7JirZATTwk5eheERU3p9Xr7aPfi9Y7W1Jouc7SxPR37yd9R1nZ2Fu3jga3rnZazSXS0SU1b/7M2bLiYrT38f8/eBPNw7K0X4a2euRb35WUnMgmU/pbob1vRVmZlaJS9N+dbsAl661opvBQoplWUUrd2o62AgxpzqYdAOxs238FU3l72iawlfeQUpSVtpd3bfUxyc7Etd2ZNqYS9iIeIq50Z9nQnCVvL02zh6eNpG3rqnRXdJVyp/2b9h6JaxxNXE0V6P9yNxWhW1GVtrY2mpi2vrs/jO4o8vurJOlvtfXl1hl82r9/Yw7pn4jd1hQbp+ipZUNbrUZWHpZSSiLqtCwqSaQzNpxaAyPtU7LSsnMkKWZubZwLWoSi/boG1nZOBna04taR/hUStIWoa7fOhPajTaXpf5AzFROhh5RnCcWKnvQ3wlhB4nLitDdiakp/lf5DTGhfIunpRlucsl6S7XKPye+31vq29Uz++tGtv2xrZm8bxDcZwrvI7vdn6H+kRycT+ncO4WX8xD+MQ490dFyAmbl769///+uT8Sfawqf9j/7O1K3pgdLWxJC+bExkJFvfCf0fXvQvaL2oVKcF2tavnuRJC6cikyZJTvJq/4NI+x/EV7b+SZy2gCZ5mXawhyqaSCZc5asjUAvUCEemk1DooapJJJJXXOHDRw/VzB6HoUEK8ZgSfvsKgQi/zYLoYGhCl25ZdTjgom7O2CYxLxOj7R04/nUMQ7PjvKirV5YcOeqsvji/cN97EMCmfYRAYNNPgihhaBYUbhn0lj+LfPDCmDKLHScRKlQ3E35fCoJsQFslnHr+41zC78XMFMV1ma76KSTlW5mTFiPuTbrMoWni8iPEh+iqBJSc8R3nvtkOwka4CVwEFwTRJfzmax+dPNLMXyWpuTLHZP2Ad5gTfvu0S5EsCb+0PdGWwGbhkPaCvBBGnfBbKAgi/G4X/I/TXlyGFD6y41umG3+JxzN3tcIgjAm/BYIgQGwW56YD9Ai/tc83tew5N1Z1a+6YI56NcS4QaS/IVgUI96/bgQ6M5lwHdj/hF5lIMSf8tm4+toTf7Yy8Mxs/wyfIJiOUh0/UBUHDJ/NYn3n+efjk0nXS1V8zdPR2WIybsGLb4D8jwz8PnzxL57VRnVerHbJiyPuUV+dvQeg+JgmChk/mdW9QwB3VYVKmWuTTY4dVMq4OiJB91G8dhl3H7B1J7zqex4gQc3qctIJsScSU8DtNAET45RFAR1pxUVuRpX6iiRxzPcDvvHP1VGjSCvIODgLZdIoAiGw6RgAlaYUqkDnF+/Ys1fLGIzu0paXqMSX8DgfagLZKOLUU41jCr0zqMJ8a8kXd0JOueZHSzl8gKyvWV6i1l889UYvkE0jkWaa9D8I++M4PWgNv+Tl2DaBM+EWquZgTflsDFlvCL22ztmXWuTjUfJA9+6gTfk/zgwi/Jfz/cc1nptjH57GNCZq+BwOOzz2u8wtjwu9JfhAg9jDnxij0CL8GlSse1WU76+04GLngievQbxA1H3XeQ6b9sg3UQ+RDjzwenpYLYRauBOjAPM51YPcTfpEpHkPCb+u2Y9nFRyf80nzalnHm4RXYiZwHQ5Xwu1MApPxsZX0k+2flpyWL+u1doKL2trtZNSeUmsbAUX4eiQ+WyByup79H787i/APBBRCUn1QBkPKztXvPIGgrP2gQfuf5r34VVjCSlCK0eK6Lu/g4DMUf9r6kiz9bGSXqfLwGDOSUKKqE3xsCIMLv6b8DRpcIv2F9s3TzqgZoVlyI95WbXsWHHeG3XgBE+D3dsyICdC24JO34ktnra1RCv1+1SZq/XwvDKYB6tuGAXl2cZoSDBXgg/CKGwFEk/Aq0XxGxhA/16VxbXCcJvwIviwXSeHm0dmWrvim/9CS764RfZHqCUDLwtd8xsDxNDPq7Kw4y4fdjYZNTHc96SvTdVXclsvr/2Q70T4Rf5KaFYKQ+QCN9EkCX8Iu8IsSwKGGsFpYcnD6MGyl5XOJpkUeYjuNpkewKCBAHBVyaECk+dtyESMYHBBMq4oLGhGwLgkxjQt5nQ1CgjATZ0Jh2hOmSvdQZUUAJB4RfJNMFhYlEhEOQo6XYEX4zxqBJ+I3w0SCnpI/Bx3SKMn6arJCoIZSbrIL5QVKbBz9cqa0i1XTAg+pS3WRqXWrEShtPOFIbEvcEoSQM5AdJbR7dq8KjfrCGTfhFXotgWNKydyS9pPVgCPMquCH8IrlnqBN+rQVAh2xjgV7Cb5tnIh7MsrGdVqoWl5wkZ/xJJ4gjCb8bBECH3dUCaBN+xQ37XrQPXK4TZLtkn3cfxTldJ/yiEP6NgUbS7WG6KlqEX+QVGIZpgLHqWSobxgx9lYiLMyVyxUM+UyIZmRDOlLL8bM6UYrQc4jiFkYZVcUL4RZoI/4RfdQLzR6cIv9z8bAi/44tI5Hf9GM5VwyXh92jpt2bPwDpy/vNKiY9XuWcyE369H4jq8tdrV+0qaJk50v4rE+H36ga++Nl6gyjbfhQMW7N5tBsT4XegYp+X+9JuaeaMnj9e+dW0RCbCr7SIg0rfL76aRdKG0t9MB8oyEX5T5/teD3xZoh78LdySNOl4GBPhd00VbzPX6Gvau18c66vQZ9UnJsLvBoHbR1WaPPT3z9ScuvrzDUcmwm+epfa70+Mn6eYHCXzeFX7uChPh94vvpVNVpRP0du1KWfGDfN6BifBb8yT3zSX3ULWUD5PKp5XMH8pE+NWcttjvgpm+TqRYU+XcccH5TITfxDoXxTH6POS9pf02EoqkZJgIv6KSg2+41y9Qz1p/xT/XYmcTE+F3qlrZzoMi1voZ3KWCR6c6rGYi/AoeMNGKP69O3hkYRww6SGQm/J4/zS0meGmpSmR5rGbi2jkrmAi/u2TzT4iZXCRTiRsklljMe8tE+E094Zii7D1FNejmrOAR/pV/P7uMLeF3Z2yF9jf9ckrRmsv86llnpSAom6QeQvhFbh3UCL9VkiDCb4pk9xJ+HeeW2evnaWwb8p5fx5T7CTTCL/c2R8nT6yik7KTF1TFzskUgTJhWSoKYtnskUSf87h0tvtZ8wCxVH3HyQaW3PH8+Xr27Cb8pQGtESMIl/PKun2WXPeWceoQLsTJuY+18zAm/rYuBLbW1ULK7Cb8h38n9BDct0wg3p97wEX72DFPC726gcVIk0Sf8bg05/3ie1XGiP69uv4HviaX/vFVgmCMGaI5gyfaaj4x3wi+ixEOZ8PtJEkT4bepcIusI4TfFYN99kfCTGinv1y9NbVzypxzzr4RfZGSDQPj9IAlC2z5nnajYHfs6QfitX7kj6iv1knb5UZedzV9dhmFM+G0CmuG6JOdOB3Qz4XeOzcwBE6MnkKMHiQvxximswbC3r3XpstSe6L19TYxQqY4Dwi/yWNtL+O0l/PYSfnsJv72E317Cb08k/FJF0ST8GqYQyYpbRPHRQ6XR4zA0SCEeU8LvPgkQ4TdKAh0MjVFNo1jwDgmif/bLjZIWFlodOP51DEPT6LzsLM87M71KpalHRvYTWwIBbJovAQKbZkqghKExKdmsUHA1TL9A04Ya40xFPLCtmwm/SUAb0FYJp57/OJfwSzlekZj7/Qcx666lul/52RrIHJolp4Kqr0kFqcfkZ7vuE7zsCWEjBAAXgacEuoRfd7XvfXnDFCiBadGWIk1vr2NO+G2NC2wJv7Q90ZbANHFIe0FeCKNO+F0hASL8qkv8x2kv1rGB630vf1GJklbbsOeXeTjGhN/lEiBArAHnpgP0CL+zzHwcsuceVY/cLD3XaorNaIi0F2SrAoT7V3WgAxU414HdT/hFJlLMCb/L2/MOS8KvOiPvaOFn+ATZZITy8MlbcdDwyQNxuMMn6QsH+D/t+0MnxXjd4wMrH/6AM3yyn2fWXs8CLTU/a2OjBzWRsRC6j1vEQcMnNLP0qO5j2FSH9CX8E1J516nn+saFCX3gmoPRzQ+965i9I+ldxzRHtkUI7R4nrSBbEjEl/F4WAxF+i8TQkVYCfZL0t556plloYbaNz9NZG5q0gryDg0A2vSgGIpvWiqEkrZQdX39qno6BVuKYgw63lro0YUr4rQLagLZKOLUU41jC75efiiEtpqs105ev3Crk2VwEWVl5F8y9XIX3ukrs/NHnfN58SYawD3KAa2AH564BlAm/SDUXc8Jva8BiS/ilbda2zKqDQ80H2bOPOuHXRQxE+F0t9h/XfNL7uW6Kf8xPjjPfwvf9uO4nDDUfeougkxgIELuBc2MUeoTfFbHruE/xLdQoi0zSTno9QRmi5hO8nPo9gN9ZIy9vK9+0q5ppEGbhVgMdaMy5Dux+wi8yxWNI+G3ddiy7+OiE39WMjKOLV2Anch4MVcKvDlD5UYSs/JyMvUmtrL5Gyf9wsajgiakDHOWH//GP8wVKgqrhdevneL2b6whB+dECKj+KPUv5QYPw6xq+Z7/O1ADtEJ0zu5e/eDcBQ/GHvS/p4o8iQ/yh4DVgIKdEUSX8+ouDCL8ufweMLhF+P2dZjpmqPVYvtCKIOzGsRhQ7wq+vOIjw69KzIgJ0LZjHxeCQX2KeVtqdVS93izqlYDgF4Ms2HNCrCxdGONDDAeEXOQSOIuH3eHuhwBI+lM+6UGC3YDpJ+FUzbbQ8cni0/vY5dUNbxuT++aidfyL8ItMThJLhaPu6YnmaKBdHm/BrrNmgemjTZNWy+TPrl70ypnad8IvctBCMlA80UqY4uoRf5BUhhkUJY7Ww5ODkM6KQPi7xtMgjTMfxtEh2BQSIgwEuTYgUHztuQiTjA4IJF+KCxoRsC4JMY0LeZ0NQoH6Js6ExSUTpkle8ZUQBQxwQfpFMF/QJv8jRUuwIv0uk0CT8jgzQIM80lsLHdIoRjpqsEKghlJusZomBpLZprLsf/vnkvP/rvF0Fzkbq4d4ynmu/LnWGI7UhcU8QSkI5MZDUNq17VXjUD9awCb/IaxEMS1r2jqSXtNMYwvwi3BB+kdwz1Am/gsBDNpd4L+G3zTPFlhaSluZFaskXsu3W9N1wjCMJv/zAw+5gcbQJv7oHNz9Lso7T3TuM+LzfzS/ZnVcEkEZCIfxzAY30uaeFf5QIv8grMAzTAD9Q2eBinGkW4+JMiVzxkM+USEYmhDPlbVE2Z8oyP13y8oui7fY3xgnhF2ki/BN+DQjMH50i/O4XZUP4zSslka8WMpy7BJeE3xMtE2xOWBarJZ2fKiTsF1fCRPgV3q2dPd+jSSf29kbh18Km/EyE336O77NyPp3SCZZ6OMGe+GURE+FXJmqR3NjvDiql187YnFKO9GYi/PKnGPjxOeRplA6YKThrZ+A7JsKvyCRp76NVSsSchflL5Ma6HWci/NrP6Bdo+FhcNeTR6xitLU9FmQi/RRUJp7QL8vV2ifDKVqQvcmEi/D57O+3TozQzUsULgXD++3XPmAi/q+bcD84zXqB+aIrcoZdPD6oxEX5PP7Zufr5UjhJyVlpj6yDp3UyE30txOTLyB+LUw7L7fyHuqkpiIvxu+BDTj+dnCKUk4J0mf5+KJ0yE39RXAsZTT31Sr7Q6kevz86woE+G377sz1yef76eR7n7Hz/bg8etMhF/5DVHOh8xIqoe1Z4mdEA3nZSL8ukYajrw7ei25cJ2LQ2l+hAoT4fexS/6JFp5M3W2jyxwuLDZIYiL8nlnXkpA7yE5/m43FLH5+m5UdJ/wWSPZ3Nu3/nZKjRpFNf/JmCQRlc2kPIfwitw5qhN+jyiDCb7pytxJ+I4Z+nBmsQVYLO/CxeeI6ezNohF+3Me5X3xVL6cVuLRkYT7nW1dMAfcK0WhnEtC1URp3we2J1/1dTnthoVdgNSFZ4ILwDU8JvOtAaMcpwCb9Su8ljZikr6fnK2xUnZYo0YE74bV0MbKmtpcrdTfidEldY3+B+SSX75z1v6ZG6tpgSfvcAjZOujD7ht5F33nO7vhUaeSZXNZ+GvfDDlPCbADRHhHJ7zbcM54RfZImHMuH3uzKI8Puoc4msI4TfY3NuPom55aCbZ5kclLt1VR8ohF9kZINA+P2qDELbtrBOVOyOfZ0g/LqNdqw5Uq2r5bPSz9jUOODPc3/3E34fAc1wS5lzpwO6mfD7XVX3wSjjIPKeQt9hJg1hnzDSnui9fa1Ll6X2RO/te8QIlctxQPhFHmt7Cb+9hN9ewm8v4beX8NtL+O1phN80IpngJ48m4bdlF5E8z1ceHz1UJj0OQ4MU4jEl/BYrgQi/25TQwdA0q62Rsj93Sz82P0tUp2lpbAeOfx3D0AwZGnpZZpWCTmWEWWZ6UXI4BLDpfiUQ2DRbCSUMjYPCfN0rrgGUGKJ57uiUrMOYEn5TgTagrRJOPf9xLuHXaIhZ2a7Vz0k5hF/BS7ZcGQeZQ/NgXN3TdTff6iTXeBgTlQSvQNgIIcBFsEUJXcKvc/AtWR3HTSpFVz+suaesKYA54bc1LrAl/NL2RFsCW4FD2gvyQhh1wu9qJRDhV1vpP0572R6kOziRR0OtWOeVrcotzz/zZfcTflcqgQCxizg3HaBH+FXyzwmZ5rVCv0SA0pK30nYyRNoLslUBwv2rNtCBKpzrwO4n/CITKeaE35XteYcl4VebkXdM8TN8gmwyQnn45KMiaPjkiSLc4ZPmS3dHfeaiELN3frUYNj9vHZzhk5ydmnHzzZtUdk7Vyo02XHIHQvfxe0XQ8AnNLD2q+xg21aHh/vAJOUdWaUSNC3th8O5VI4Zdx+wdSe86pjmyLUKs7HHSCrIlEVPCb70CiPBbpoCOtFLl3v8mpfAK5VC+x5PVgiuWQZNWkHdwEMimVxVAZNPTCihJK2LjQsvlZq/VObTFhkuW0H87poTfI0Ab0FYJp5ZiHEv4vbQo4951i1jVfS8umlEMY2MhKyvK9Z4r7589q5K0sfhdqIJvHIR9sBe4BjI4dw2gTPhFqrmYE35bAxZbwi9ts7Zl1lU41HyQPfuoE349FECEXwuF/7jmcya64dLu1Gzt9JCtw2/6lqZhqPnQWwTdFECAWFvOjVHoEX5/mdckpDWMUk3jnzSxb8GzZRA1n2JlhTv3Y70paU77r05fRT4FYRbOAujA5ZzrwO4n/CJTPIaE39Ztx7KLj074tWBknNV4BXYi58FQJfzqA5UfImTlp7wy+PCopr1qxSKLNh2dfMIAjvLjM/ugy9PCb6Ts2ctmqe/0qYWg/FCAyg+xZyk/aBB+Vxz7OXa1MrdGsF1eYu4m52gMxR/2vqSLP0SG+GOG14CBnBJFlfAbrAgi/Hr8HTC6RPitJ6inecrtVM/P/zxM7v7OKdgRfgMVQYRfj54VEaBrwYafZZ8Jxbwkls/tv0P46pGvGE4BBLINB/TqwoMRDtbggPCLHAJHkfBb114osIQP7WddKLBbMJ0k/KZJv314Tolbw9fRTGCy7IrqrhN+kekJQslQ076uWJ4mDiqiTfgt+Znz1N/ivEo2/6hhmnrZWV0n/CI3LQQj7QcaKVsRXcIv8ooQw6KEsVpYcnD2M6KQOS7xtMgjTMfxtEh2BQSIgwUuTYgUHztuQiTjA4IJLXFBY0K2BUGmMSHvsyEoUFxKbGhMp4J1yYs+MKLAWhwQfpFMF/QJv8jRUuwIvyYqaBJ+SyI1yLLLVfAxnbIOP01WSNQQyk1W8xRAUps46+6Hfz45PzaqHlncvEAj68vG70s137+HI7UhcU8QSsI5CiCpTbx7VXjUD9awCb/IaxEMS1r2jqSXtOIMYX49bgi/SO4Z6oTfccBDNo9iL+G3zTMj7oSP3vDEX3d3jrt2s7nGZ44k/I4BHnaHK6JN+FUjPVoT7TdKM6VKasZO/Z3Xuk74RSH88wCN9L2nhX+UCL/IKzAM08AYoLLBwzjTWOHiTIlc8ZDPlEhGJoQz5T15NmdKgwhdsv4V+Xb7b8AJ4RdpIvwTfpcTmD86RfgtkWdD+CVVk8gXihnO3YhLwu9aS/+qN5WPtDLylpdePlhXxET4vT8petd97RjS9sVeJ87OPEZhIvwGzn9u7PPcRyt6/fEtBWfNNjERfvuMuy06+9N2UvqMiE/jLI6fZSL8bs/5/it37XtimOAk6RVTB9czEX7N3q4hzV2RTAot0EvNjzvuy0T4dZd+zbcyyE49nsh9xcl4azkT4bfF+ZP5PqFoncwVSbMfSU7JZyL83g1weP3a+qdK1OmGvc6rh9cxEX7nNUsohVR6a/sH7XM871m6lonwW2U9zqc+xlsnbrj39jepF8cwEX6juIVtU5/vVU9a7qYQ+UVwMxPhV8hdfWhd/GfdyHGrZJ/GLBjPRPjd4a59/fnjT5qhWWdNuTzPlTERfquHpgZrjCnTKgtaenPLg6kfmQi/N8ZZSMiYnNJK2RH0TVplIjcT4XfN1/hw3jOhqlV3/bIuxmkvYiL8LnOfafrYREs3eZHMgd0LV4xjIvyueT9zzpc3IcREdalpq4S0+nac8Ftdc2ocxdRWJU0z9cS6udmvICib1j2E8IvcOqgRfr8Yggi/Nw27lfArb6/x4v5OGa2KkRbPR4qv2giN8OvTv2CK1PKtaiEGa28OVJ87E8KE6SdDENP2iSHqhN98szoBnfPfKXmJB8ZlCA/bjCnh9ybQGqcN4RJ+Rb3PcZee/66XNm+Mod2NbUaYE35bFwNbautLw+4m/FK1Z1eezXmmGev4fPz45HdymBJ+m4HGuWmIPuHXOsJEK/v0YfWwmd8fq54z3osp4fcC0Bw1hu01nw3OCb/IEg9lwu8sIxDhV9gIOuHXUGLXvPLVVuSC2kNjp0w89yey818Jv8jIBoHwK2cEQtuKGqFF+P34ZtTqd8buxHhnz9tTbp4cgTHhVxhohtFGnDsd0M2E37qCAdErRG/qh+UUNj6UHhiCYW9f69JlqT3Re/toHm0LlbY4IPwij7W9hN9ewm8v4beX8NtL+O0l/PY0wm80kUw4r4cm4Zc3iUjWP6eHjx4qux6HoUEK8ZgSfn8sBBF+by9EB0OTdjr90afVKcTSpIlN6dfN3kLD0OhfsX3bNMZXPYirSO6OloAJBLDpt4UgsOmbhShhaCQzp1erLK9V8V1+6lbINJGhmBJ+HwNtQFslnHr+41zC7zD7Zz/l3rxX30X4rDLYkPtP/3adQ/NFdW1j7I1ivco7n++c+NjnCYSNcAW4CE4tRJfwOzBKepitz2nigbKN9Saq5UKYE35b4wJbwi9tT7QlMHsc0l6QF8KoE37zFoIIv7EL/+O0F5krZ0IMDLgoRVO9T7vwBitgTPjNWQgCxO7g3HSAHuHXPENotB15jUbFg7eFPGr20hBpL8hWBQj3r7FAB4ZyrgO7n/CLTKSYE35z2vMOS8JvLCPvbMLP8AmyyQjl4ROVhaDhEznWZ55/Hj4pC3u6jdS8nRigOEzvkZv5MTjDJ0pWynn5MqaUfTzHjy7fe76rCCh697HSQtDwiVz3BgXcUR28cueY1x1zVk//unLLvQep5zG6+aF3HbN3JL3rWI4RIRx6nLSCbEnElPArYgAi/BIM0JFWXB+mTF8Qr69Z+sx8rduRKGto0gryDg4C2VTYAEQ2HW2AkrTyIc554LM19apRM4387QpvLcJMWqHbgBdoA9oq4dRSjGMJvwpVErZ7U6maVRu+VJJUnm2DrKzMv2h5wfrkWg2qd7KjJNeFgRD2wUd90Bp4oc+xawBlwi9SzcWc8NsasNgSfmmbtS2zOuJQ80H27KNO+D2hDyL8Fuj/xzUfefmnFi83vCcGzdNZUKp3xQVDzYfeInhMHwSIreDcGIUe4XdV87eKhz5X1eKzLz6YZxM5FqLmM4mQGml25K6u36eB83Y0mjhBmIUrADowi3Md2P2EX2SKx5Dw27rtWHbx0Qm/NJ+2ZRwnvAI7kfNgqBJ+kwxAyk8Y6yPZPys/V3ffN/D+flwjQXqi3VppVTU4yk/hAx6zI3Fc2ofTSn21+lXdgqD8JBiAlJ+w7j2DoK38oEH4PXtk3kfqk3St1ACTvg9r6igYij/sfUkXf8IYJaozXgMGckoUVcLvZQMQ4ffE3wGjS4RfW/PrX6eSijRDEhpbROMvKWFH+L1oACL8nuhZEQG6FjwxYHcfwRGSOtn+ffonLvwyHsMpgItswwG9ujjBCAcuOCD8IofAUST8jmi/ImIJH/rWOe22k4TfRz6Cr+e73df2H3Kpyv7SUASq5l8Iv8j0BKFkGNZ+x8DyNMH9d1ccZMJvyyrNSnFJspr/tF2u14ZL/0nC+CfCL3LTQjDSNwOQkd4YoEv4RV4RYliUMFYLSw7ON0YUcsUlnhZ5hOk4nhbJroAAcXDDpQmR4mPHTYhkfEAwoTsuaEzItiDINCbkfTYEBYqykA2NqTlMl2ytwriX9sAB4RfJdEGf8IscLcWO8BtrhCbh94KPBrlimxE+plM88dNkhUQNodxk5asPktqc9OFKbesVAieaji3X3NHIryUtFkGCI7UhcU8QSkKqPkhqc+peFR71gzVswi/yWgTDkpa9I+klrRNDmN+MG8IvknuGOuF3rQHokG1g0Ev4bfPMhI9cBZfejdQM+zV/5bmtHz5xJOHXAnjYXW6ANuE3yHr44NULt5Ai06NWWbvFR3deEUAaCYXwbwA0knoP01XRIvwir8AwTAOMVc9S2TBgKBteuDhTIlc85DMlkpEJ4Uwpoc/mTGlHyyHWwow07I0Twi/SRPgn/FoQmD86Rfj9pceG8LuyiER+8VOv3blbcEn4zV04KpI8SlZjW+qM/iNl5/VjIvx+iBNa4aiaoJ30iOs78dq7lUyE32dHHMPeCDtQohWaRF+Ny1/HRPhdb538YmmfevX8QVfGfz9k5s1E+G2s0Lx2zLxRK51P/6F+ZfgWJsJvtvqbJA2+/uQAmTuTB2q8/cpE+O03ZYBH6qUTeiEnd/V/vuVgf2bC79WNmxdk12iHZOy/e5L89hkT4VdOUjj++LlsleKTj2+Oet2/iInwSzBMFNO98ks/MKeMMsN9y0Umwu/RK5dT+GKd1VLSVlhqNxCcmAi/PJdjMs8dW6ZaGOm0y1T52Ggmwm9m9oUdBspvtQ8c3p3cb+zVJ0yE3/4zRAylNj/Q3HrI6Dy5xcGDifArMkFYR93TU3f/jceL7xCSw5kIv3xLahY/u2Cln6Q2ecabPnWFTIRfiQj7EXurCzXDn30x5cuzdmUi/D7q+8n+9JsEygHFF+ZLDauDmAi/0wSuhbkJv9QOVRE9sfrKuvqOE37vTpt2d2bxI90gyauEgvkLMiEom9QeQvhFbh3UCL/PLUGE3zOW3Ur4DbKfvM7EJl3/4MVJAur+E0WgEX4f3U/imRA6VSXLNfaV1mJnewgTpk8tQUzbBkvUCb+JKQum6225opp2a872wmXlf04BdDfh9wzQGlWWcAm/6QJ3NtjfD9LeccdAZv8X+0TMCb+ti4EttfWuZXcTfqc2L53NN8uMUvE+wbalYJ45poTfa0DjnLFEn/Bbxud995flGI2dgfzjHo4Xuowp4fco0Bzllu01nw/OCb/IEg9lwu+0tSDC7/C10Am/822UQwI+C5LLh85bQA6O+VNN/FfCLzKyQSD8TlkLQtuOWYsW4Ted96J6XXmzfnbQi8iUDb/eYUz4HQ40A89azp0O6GbCr6GEvu3sU+H6Bxrlvmt/Py+LYW9f69JlqT3Re/toHm0Llb44IPwij7W9hN9ewm8v4beX8NtL+O0l/PZEwm+aGaqE32Qi+fhOM3z0UPn1OAwNUojHlPB7zgJE+M23QAdDo5/3vf/qbU6kTKmLt8bbV97rwPGvYxgar3dbqq2FArR25Z9ZR+aVzYQANj1jAQKbHrVACUOzI6eU9P6Cp2bW3s1XHD2q/ryc6m7CbznQBrRVwqnnP84l/M5Kdn77/eEMtQCpkLjv/BHPIHNoRt++n3GgVIVYzK/5ccyq9QcgbIRM4CJIskCX8LtRZkB4sZkbMWNxwpGUrGEDMJWt6YTf1rjAlvBL2xNtCcwfh7QX5IUw6oRfDwsQ4dfC4j9Oe9n46FCalsw3crHPhsqJJT65GBN+3SxAgFhbzk0H6BF+xT+8ectnOEu1eoHCuIN3NpLYeOhfGg2RrQoQ7l8tgA5czrkO7H7CLzKRYk74dWvPOywJvxaMvBOAn+ETZJMRysMnwy1AwydcrM88/zx8MrRv/ysDfO9pZc0f5vTO/sIyOMMnEvtMTvTJ8NWqPv1gKnlYPsuo3snu46EWoOETru4NCrijOpzcPm7lzk+NKoE/TQ/nCK1aj2HXMXtH0ruOuRgRIrDHSSvIlkRMCb8ta0CE34tr0JFW9kkGGGxQ7adWsOfCsvjhMnLQpBXkHRwEsumrNSCy6YM1KEkrKzR1tpXwbNTLepz6w+flT1VMCb8NQBvQVgmnlmIcS/jd8vnA7VFOn8iJKwIK5p+1VoesrJi2WFfHlMxWKSx5P0hTpnEvhH1QC1wDVZy7BlAm/CLVXMwJv60Biy3hl7ZZ2zJrEA41H2TPPuqE39g1IMKv95r/uOaTIfV0xZ66MvWDoXK7pXWOZWKo+dBbBGPWgACxwZwbo9Aj/N6cW002GnieEms/Qmp2aeJPiJrPkH0LQ7QOOOgfzJq6j/ToQ1fvsegO9AY60IlzHdj9hF9kiseQ8Nu67Vh28dEJv96MjBOMV2Anch4MVcKvlTlI+TExh6v8PFlIrX4aIqtbuW602GZvk6FwlJ9zkwUGDrd6p1H0cGW/90M+GEBQftaZg5Qfmll6kvKDBuF329ITZ0XLrTQPaQ0LuSvitQ5D8Ye9L+niD82XbQEjBK8BAzkliirhN8McRPiN/TtgdInwuyhwwTSrt/1J6bo+7y8P7GuJHeE3zRxE+I3tWREBuhbMVx1yf27/KGLyorDNJ7h2NmA4BZDGNhzQq4tYRjgIxQHhFzkEjiLht6m9UGAJHzrDulBgt2A6Sfi1J3r7X/QyVyuQGh12tfLln9XnPxF+kekJQslwt31dsTxNXDNHm/D7jMdEhCzNpRZMPqmeWKj65zOo/4nwi9y0EIx0Bmiko+boEn6RV4QYFiWM1cKSg3OGEYXCcImnRR5hOo6nRbIrIEAcwnFpQqT42HETIhkfEEwYgQsaE7ItCDKNCXmfDUGBmmDBhsb0OEKXfHck4146EgeEXyTTBX3CL3K0FDvCb/BaNAm/V/w0yGVBa/ExnRKFnyYrJGoI5SYrwzUgqY3Euvvhn0/O1MuC9mfFTxL9jR//EGq8/QmO1IbEPcFAPK4BSW2k7lXhUT9Ywyb8Iq9FMCxp2TuSXtKSGMJ8NG4Iv0juGeqE3znAQ7aIeS/ht80zTktr94kfPUaOuGZ1xunIlrLOKwLdQPidBTzsipujTfj12Nt41vvwFtWIUYM3jr31tW/nFQGkkVAI/yJAI/H3MF0VLcIv8goMwzQwC6hsiDCUja24OFMiVzzkMyWSkQnhTPnDjB3h11eX3NBi1m7/GJwQfpEmwj/h15bA/NEpwu9lMzaE3zUlJPLySwznbsMl4Xdtg/RYiuQFsn90f7F6a7ubTIRf0Zigw1YNEioZqTnhA1ZqpzMRfr+F+HsZVguRy8/IUa4/OTCDifC7K6sitCk9TPPwpwmu3NtUJJgIv6Sxr6aapy3WrBAaN3DxD9P1TIRftdxfKhQ9QZ0sWzvq5eGhzUyEX7lhWaSJZpNIeafuTHutl/mIifBLsnv9cKP2Norv6NcRddsrTZgIv36ZAmZ2gVO04rjfSlifu+zIRPgtPOWZ+qi/ulbkSP6Hm6TDwpkIv32+bnuiPFdPpbSB+0XCxUfyTITf8fUH1F2G9NWnSh4NfGnT5xkT4bde+f5Ur6sWqruWeAkrH3p9nInwu5XPeNfaJR/IeY/Ny3OSbrozEX6J07aOPZMmTclKiova8ePLISbCr16/4suDufM0AgPGRUcdS9FiIvxG5G+SG/bmBDnvwI4TZxJFQpgIv9zrAmZfEF6nE8gv6SQoOncKE+HXukBBMH+YLqmU61cln4WXd8cJv30eepTmlmuTDiw8uNXYTXEDBGUztocQfpFbBz3CrxuQ8OvWrYRfXavPn+zyf2ns0JlyZvesDF9ohF/leU7fHldqUSokNxmJPD4rB4Pw6wYk/LqhTvj9oq0/dWYUQa9shNWz6gSTIdgSfoHWqHKDS/gVn7vpkaFfhWbkocpvzYoVHetGQpXw6wYk/Lp1N+FXVWicQ6Nxqn5BWGS9vs3qRf++kWAQfoHGOeOGPuFXSmic2fXlSfp7g5NqayTf2mNL+AWao9ytveaLwznhF1nioU34dQcSft2hE34zDPT2bnp/V+3AxlHvvm7fGgWF8IuMbDAIv+5Awq87WoRf1cOup26l+5ByEvg33wt9eQZrwi/QDDzunDsd0M2EX9/DP09Kj1MhJfu4N2QSlz7FkvDrDiT8ureHyngcEH6Rx9pewm8v4beX8NtL+O0l/PYSfnsi4bfQCU3Cb9FOInnRPid89FAl9DgMDVKIx5Twe8sVRPitckUHQ1Mvnp6Tz7tA97DKAQNX7rGLoWFomo+/TWpoSVTfKfzQYYVbcRMEsGmDKwhsetEVJQwNaeO9G3MvGqpGFjV/WaU2SABTwm8t0Aa0VcKp5z/OJfwueez4KdUgQJ+6fNXacIdsO8gcGrWB5+pqpvVVyRuTYX1SIPMhhI1QBFwEOa7oEn4Tj/juqvkho1W46fid1Kux3pjK1nTCb2tcYEv4pe2JtgSWiEPaC/JCGHXCb4griPDr6Pofp72Y3PhyaYTEMa3MMVIDdTeUYk34DXIFAWK9ODcdoEf4bfgZf//mR2ON/Mxb3Mab9ixi46F/aTREtipAuH91BDrQinMd2P2EX2QixZzwG9Sed1gSfh0ZeScJP8MnyCYjlIdPJriChk9GsD7z/PPwieOHbVvkZ1PU/biHLqs/L3oNzvDJTq1v0tOnShMrvw8+Zbw/QBFC9/F4V9DwyYjuDQq4ozo8jmoZei9GXGXrvYM1o1ouPMew65i9I+ldxyMYEWJ7j5NWkC2JmBJ+fzmDCL93ndGRVjZvvG8ndSZat6KWnG2dn3sSmrSCvIODQDb94Qwim75zRkla2bTFQqwpKlYn7GlemdyP/RMwJfw+BdqAtko4tRTjWMJv+b2UUt7Ty3RDCSlTz3M9fgtZWckbqLHO5USsWkDfY49vXnh8E8I+uAZcA2c4dw2gTPhFqrmYE35bAxZbwi9ts7Zl1mQ8aj6Inn3UCb+ZziDCb4Tzf1zzMfMqXmZon6y9u4w4Io5rwFiMCb/pziBAbALnxij0CL/DUgcaOyflqMS4HNC2XP1jNkTN59bXUTzXAz8SK5xKZhnvCunqA/roDowAOtCPcx3Y/YRfZIrHkPDbuu1YdvHRCb8RjIyTgldgJ3IeDFXCr5sLSPnZ4AJX+Tk3avMzv4uD1IvjfNZmKN8Uh6P8pLvPrSz1E1LfueTpLcGMoywbFzup/Li4gJQfmll6kvKDBuH3UX1wVsAWP6346Y1JxyXyyjEUf9j7ki7+0HzZFjBS8RowkFOiqBJ+97uACL+ZfweMLhF+n0+ZTowYGqQRX5cucWDrnUTsCL/7XECE38yeFRGga8GNJjEaikNukLavMZnpm1UxF6NwQJ8C2Mc2HNCri0xGONiBA8IvcggcRcJvS3uhwBI+1MC6UGC3YDpJ+B3/Ocx5RyOXnv+h7x+i6+q0uk74RaYnCCXDq/Z1xfI08cAFbcJv1mx3wVyKvMr+fqVf1Uq//znA+0+EX+SmhWCkBqCRLrqgS/hFXhFiWJQwVgtLDk4DIwrtxCWeFnmE6TieFsmugABxSMOlCZHiY8dNiGR8QDBhOi5oTMi2IMg0JuR9NgQFStqVDY0pyleXvGkS4146AweEXyTTBX3CL3K0FDvCb4g7moRfz2AN8opgd3xMp2Tip8kKiRpCucnKzBkktRmx7n7455PzhfMNP8aOMaXsri9PiRI1DYYjtSFxTxBKwlXOIKnNqHtVeNQP1rAJv8hrEQxLWvaOpJe0RgxhPgs3hF8k9wx1wi8ZeMiWdukl/LZ5ZuqV4eN+Ttugnb4lIitJ48FtjiT8qgEPu/Nd0Cb8rmtIPzd2qIdq8ZhXE0QfK0h0XhFAGgmF8C8NNNLUHqarokX4RV6BYZgG1IDKhjRD2diFizMlcsVDPlMiGZkQzpRDnNmcKUcG6ZKtCYw0vBsnhF+kifBP+HUjMH90ivDb5MSG8Mt7gER+cc+p3bnZuCT8DrkaX7eiZiMp3+zqetEljvuZCL8Sg3YHp6cm6cY91JC0WrMojonwu3+6jlzpSnHKzr5+xKRxoleZCL/zh+wfPm9TsE65dfm7WIN5mkyE33czA4emZg+n7Hr9+GxKXdoqZsLvHOmrx/uWEMM0JZPMGvy/MRF+w+WEalbXjiX6fz7pGbmlJoOJ8Fuax2O7cNNE9X0/1980GPrmLhPhN3ihzcp3rlO1ArY3E0bYLfjERPhNbb5acatim2rq3XuGutvX/2Ii/B60SUkqKrKnVMg6CG5dlZ/BRPgN/1b8SXeHnl581pQFHz+If2Am/JIGKr8aYU0JVBkfZjpwpxYT4bfBw1zkx0IBtSruj9Qz59dnMhF+b4Rda5jzMYSSIefvHN7XYB8T4dcra1FS8bBCreiqyyJxQkFTmQi/IyreulGu1FHCvz/1eRX/YggT4Vek+pfDFlMD/SLJEVcGeK74wkT43VkUWPfk2HSN7TnU0ONDHbU7Tvj9MMNnd/85s/QPT1koZSjQfBqCspnTQwi/yK2DGuE3OQBE+A0L6FbC79K1E50G3LLUi+8TO4Hw5qcYNMLvgZdH3zxVrNA9qGkzb+GB+3YQJky3BwCYttSYANQJv1snUs+WHN+unR66z74yveXP40B3E37DgNbwC4BL+L0h6kQsOfeVlOWYcnZcrkLHLv7QJPy2Lga21Na4gO4m/AZZ+dc7fE7Q2Pog92XGmx38mBJ+o4HGCQtAn/C7+0ND8gKVlVoJlyxXOgpn+2NK+A0EmsMnoL3my8U54RdZ4qFL+KVWBAAIv9T8ziWyjhB+pb3UVo1PPqZd7mwn4H5/aQYUwi8ysnWd8EstDwCgbalFrBMVu2NfJwi/ay8cF1+dq6YdxXOzOfTHpqHYEn7pKwBghpwAzp0O6GbC77un9zelzdisH1BbuMOZizIDI+2JSmlbuiy1p0JKq0fbQmUeDgi/yGNtL+G3l/DbS/jtJfz2En57Cb89kfBr64cm4VdvO5H8ycYPHz1Ue3ochgYpxGNJ+KX2CwAQfqnv/dHB0Lj2Pz5x3MDzWlsPbyne0zC9Iw946RiGpu/H/mYXzEJVfJINDjoHVQt3HWxK7RsAAJtSf/qjhKEZL3f8+uRQX7WISX1DBWao/NkA1M2EX+oXf5ANaKuEU89/nEv4TZh/vt+Sz4dJB0TchGyfX/yzWa3rHJpnpZv0xfdKqPsbb9Nc9L15OYSN8Bq4CJ75o0v4XaPhnXS37IfG1lnpY0R9hn7AmvD7Oy6wI/zS90RbAtuLQ9oL8kIYdcJvoz+I8HvR/z9OewnYclaX/9VUYoQYQX20asqfU83dT/ht8AcBYq9xbjpAj/A7fST/Hf2fo3UOaVQnnRY07gOR9oJsVYBw/3oR6MAznOvA7if8IhMp5oTf1s3HlvB7kZF38vEzfIJsMkJ5+GS3P2j4ZCfrM88/D5+kJTkrvQ/g0cufQdl37pfpn+S0fx4+sY1zWhoUm666tUaxZfqkAGcI3ce7/EHDJzu7Nyjgjupwx1qhKng0r0Zcueecl1dErTDsOmbvSHrX8U5GhCjocdIKsiURU8Ivvz+I8MuDkrQy9blKU0LOO0r6l/Ufstc/g0f4Rd7BQSCb8vmDyKbD0ZJWciWyq7anG+j5bPUzLfAZOAUzaYVug0FAG/BwbinGsYTfvkqhxyKH6JITLxUnDxHxzYasrGzJ5koTEZyjWvROfdCumtFXIOyDPsA18N2PY9cAyoRfpJqLOeGXz5+d5kMn/PIwMus+HGo+yJ591Am/T/xAhN/bfv9xzWfJw0ne/RWf6JatddzXOOfMK4wJv4/9QIDY+5wbo9Aj/OaPv1l4n2+iyu6rwQN5PheXQ9R8xsYEJe7UJZF9PqTsmC9WGgFhFu420IE3ONeB3U/4RaZ4DAm/rduOZRcfnfBL82lbxinEK7ATOQ+GJuGXaghSfqg6kJWfb+7H3VxmOGrt2G22UOXkqUtwlJ+Va/eSuPwUNCNd6ygD7X3yuq78UBeClB+6WXqS8oMG4TcjdnqYSPUn/eoFK8j5ru4jsRN/AL60p7T6si1g7MdrwEBOiaJK+LXzBxF+1/8dMLpE+HW6XX507jI+zfhjWlWblde+/ceAAYHwa+sPIvyu71kRAboWHD90g83WpcYqAU590nIFv1zDKBzQCb+2bMMBvbpYzwgHRTgg/CKHwNEj/FIj2wsFVvAhql/ntNtOEn6lBUXeygofUd//0923bMZWta4TfpHpCULJENG+rlidJqjBf0u3kAm/lc5n+UY8+6jtu+V28DvioD/n+P6J8IvctBCM5Ac0kndnO6Y6SfhFXhFiWJQwVgsrDg7dTG1RqBiXeFrkEabjeFokuwICxKEElyZEio+dIPwiGB8QTFiKCxoTsi0IMo0JeZ8NQYEq8GdDY5KI0CUHZDOiQBkOCL9Ipgv6hF/kaClmhF/q0wA0Cb8j/TTIW2h/BS6mU8rx02SFRA2h3GRV5wdqsjriB1dqyxXYeenlzp+6SRMHmU+3Il6GI7UhcU8Qmqxq/QBSG90sPepgDZvwi7wWwbDJir0j6U1WRxjCfAVuCL9I7hnqhN/5oEM2YQaEpv8eQvh1rirOjnodpre9btK8udaN6ziS8DsPdNglzPRHm/A7mtTP7J7HIVL0bd2lhuVPvbpO+EUh/M8AGkmsh+mqaBF+kVdgGKaBeSBlg+7utjRwABdnSuSKh3ymRDIyIZwpU/3YnCmLfHTJ/vGMNFyJE8Iv0kT4J/z6Epg/OkX4DfJjQ/jdXUwinwhkOPcgLgm/MeKDp5WvOqybI7b28JvopCNMhN+f/US3ypVcUos/++Sw0HB7USbC77UCqdixQ9eoRled9w4QXMlM+L2rv2ZHhNJPUuHo0d5fuPUMmAi/QUZilZfnVxOTXa+8rFzL481E+D08+8kit3Xi2jmnXcsKxS/vZCL8WrvNezho/xCVinUe1055vzZhIvxKq9YIrh8pQc63kPsVzkMay0T4DV8s9dV9zwL18H6jT74l2A5nIvwmPVDYtHR/NTH1V/KCCyPOuzERfkNLTI8/idXRpyZW6zbkD5diIvwOnyE1XSPhuWbBiOWaov35wpkIv9+XOCyqE1hGqvbpR/Z/J+zLRPh9v8VhROkFWdJ24Q9rlu7YnMFE+PXYXGtx6vYM9X1WKc+VXsumMRF+DeZkjz+8nkJM+dRXKuRufwsmwi8pMXU9F1cxMfWU6oxHS9YLMhF+L056MkE4rEp7t4T3bL2nB18zEX795omZ3naeqrJtZ3ZJVWVDSMcJv5Opvp4hL6/oRA6fobFZZc8QCMpmVQ8h/CK3DmqE3+ZIEOH3SmS3En6HbuMl2Aov1s56e2lLiMO169AIvy8fVZMS7xPIBQ+H+h4Yk74CwoTp/UgQ07YhEnXCr6tifXFZvbp22tCQnKmXWowwJfxeAVrjTCRcwq+QSeWH3bxc5NiquPt7SAErMCf8ti4GttTW25HdTfgtP1p/qeLzdnLK/C9DAlPGGGJK+L0BNM6VSPQJvxu2lG2YUhhHCnMaWrTXbqruP28VGOY4DzTHqcj2mu8Qzgm/yBIPZcIvIQpE+P3QuUTWEcLvsxUjKjI+VpCThrp6e40jzIdC+EVGNgiE31+RILTtV9aJit2xrxOE3zFPDWUp90M1Ig6uGJJQrMeNMeH3A9AMLZGcOx3QzYTfQyqb4lXzbqpFJgw/O3p0WMd4EOgQfluXLkvtiU74/cAIlYdxQPhFHmt7Cb+9hN9ewm8v4beX8NtL+O1phN80Ipl6OxxNwu9U2l/hRfsrcNFDVd3jMDRIIR5Lwi9hQySA8EtY3rmTX4cxNJseLJHc91qPtJsw+tuvQctfQ8PQ2CR9ayITHPTTqvRsh88cWNZ1sCnBKhIANiVYdO4I2HEMzfFvG8QSbfqpho11P9Yg5fAMS8IvYRXQBss59/zHuYTfDe+nN73eUqWe5OU4VpNb+89Byq5zaAi7tyyJNNymWp39YvbGOXyVEDbCYuAiMOikTN1Z2su4x41eL9WNyWnHFcbfVW/xwlS2jtZriwvsCL/0PdGWwI7gkPaCvBBGm/BLVY4EEH6psyL/47SXGdMHhw4iXdUvdrq0hsvq9UNsCb9UpUgAIJY6n3PTAXqE32lkox2bP5qRCw+MMhm/ZmEMGw/9S6MhslWh6/ev9A0FcKA05zqw+wm/yESKNeH39+ZjR/ile7Yt7xzFz/AJsskI3eET6uhIEOdlCOszzz8Pn0TLKBVYh2zSzor6Ybf4o9GfHKh/Hj7x7duo1FK3TbtiXOOEgKjJCyHMI49qvzBgyXkZ0r1BAXdUB4WMTK8ozxxSxCjJRDkjAT0M56nZO5I+Tz2EESGO9ThpBdmSiCXhl+ofASD8Up0i0JFW1jb8knE+eE1zf7TYnbFeJXzQpBXkHVzXyaZUvwgA2ZTqHYGStMJlFP81OsOCsu1Klf7E1a+rsCT8Ut2BNqCtEk4txTiW8HstOmDU+fJPuoELPYP2CP+Ug6ysXEiLfrSgcLZaSrzlm6iJJ4wg7AM74BrYwLlrAGXCL1LNxZrw+ztgsSP80jdrW2Y9jkPNB9mzjzbhl2ocASD8UnUi/uOaT9TNm/7bJ30lx+vnaC7c4CyFLeGXujgCAIilGnBujEKP8DvD3chV+MMa3XCxl6crxr/6DlHzeVZ5vHrv5kX6YUslEvfvndm367Nw9A0FcKA65zqw+wm/yBSPHeH397Zj2cV3j9Lq07aMcwKvwE7kPBiahF/C0QgQdqSS9ZHsn5WfB2Zrkg+6iJDjN6TtfFw05AMc5Sda9OM4geeROol6Jtk5j6jyEObOj0QAlB+6WXqS8oMG4Xettp9W+vVsvYCi7JzkU9v5sBN/AL6kj5xXMgJGDV4DBnJKFE3CL/V2BIDwS63/O2B0ifC7/cCkWV/jyFr7Fo63d5t+qBEzwi/1VgSA8Ev/vXtSRICuBVvzf8xzHyWgFROtuv1ebroAhlMAt9iGA3p1Uc8IB7U4IPwih8DRI/wSfrQXCizhQ287p912kvDLTdw6eeIIYZWoNZWhM2OWHO064ReZniCUDN/b1xVLVM2nv6VbyITfm8RpMR7pQurbTUXGKw4sb+464Re5aSEY6S3QSC8j0CX8Iq8IMSxKvrM9xdCLkreMKFSHSzwt8gjTcTwtkl0BAeJwEpcmRIqPHTchkvEBwYSncEFjQrYFQaYxIe+zIShQ4yPZ0Jh++uqShwgw7qVP44Dwi2S6oE/4RY6WYkf4lYtCk/D7NFiD7Ej7K3AxnXIGP01WSNQQyk1Ws0FSG3UGZKmNa2B/5yxNY419NRa7I0nikB6mhcQ9QWiymgWS2uhm6VEHa9iEX+S1CIZNVuwdSW+ymsEoac/ihvCL5J6hTfilZoMO2dQUCBfAPYTw+1RxjJrjSAcNn9kT5O0fKu7hRMIvdTfosEtNj0Cb8JvlGa63/1SVRl5m/aghDeP8u074RSH8pwCNlNDTwj9KhF/kFRiGaWA3SNmgu7stDZzDxZkSueIhnymRjEwIZ8rBEWzOlCFBuuSBPAz7n8cJ4RdpIvwTfsMJzB+dIfxSP4azIfx6HSCRtWivtjn3Ai4Jv9e+jHG+W3dOr8yqn6ykqsxMJsLvxhHOowQerSXtWn5dWuqK9gkmwu+P6OdCi8dFqiVtrh9cZvbgOhPhl7jhrLu10hDt8MUGRWke752YCL9blD+4Wp+fq1+RPEj6+GSKNRPhd8T4r9/DV13UKw6J+2TEZW7KRPiNaFKROfyRohNw9+v111MUspkIvzZjzMPyNuWqlu+bsSlk3ldBJsLvubVFxwO+OqimN0W4Z6iWHGIi/J4R+bLv4/NT2gFaeceDP9nkMBF+lW7P6S+aH6FRwS3y1NJhnwIT4dfM6rZZ5KFl+vvz++zf7TujPxPhl+/Cq1Qvcx/iHq+RebU1/FZMhN9FO8vKufcPUvU5Fpi+cqAeFxPh977gwe9qnl8pcfO4v/K+fsDDRPhNrvrSvGW9jqavsJ2ESp5uKRPhd7XA6exCpWatssqXZ3h2CnxmIvyeXL199Yd5x7T2evWzFm45p81E+KU8v3bWkZtX+2D/IZazXl490nHC7/5GIaVzz4bo7rDJ2cElxjsJgrJ5sYcQfpFbBzXC76BEEOH3W0K3En43VTfNs0x6pRlsdTr/W0D0n8eArhB+6/udPj/8qL9GcLDWVIFdscMgEH55E0FMW65E1Am/yk8uf//E90V1t6G7S8jBOD9MCb+0hQKwxrsEuITfBYm1oy6KSmsFDHkmadhHSb1D5TGahN/WxcCW2sqd2N2E3/tz85ePWxCqvWvQnvrh5rEjMCX8EoDG+ZaAPuGXMtNubG7JF53ABSOCeIc+W48p4fdjAsgcbxLaa75LOCf8Iks8lAm/ookgwu/4ROiE38hhB4YNTB6tsmvAhP3xZUNmQCH8IiMbBMLv9EQQ2nYS60TF7tjXCcJvotloHcPyvvq5Lx69539yThpjwu94oBkEEzl3OqCbCb9ak27r1El800xdoLbqyaxqKYy0J3pvX+vSZak90Xv7aB5tC5WXcUD4RR5rewm/vYTfXsJvL+G3l/DbS/jtiYRfQjyahF/eTCJ5Ae2vwEUP1ZUeh6FBCvGYEn7DE0CE382dkzA7jKG5/3ZweQhBR9P/ZPngR0ciTkLD0Hw78c0q9uRUncJVaQJFTwffgQA2DUsAgU0DE1DC0KzTyMkc/XqydrJNy56rPz7/2SLY3YRfH6ANaKuEU89/nEv4jb/EM+FZ3BHNgKnmlpMXyNyHzKEJNZhpfrePnW7lvWQ3Zz/vxRA2gitwETh0UqbuLO3lePJ622Gh09RiyZt/kbP3bsKc8BvWLkWyJPxuZkiRV3FIe0FeCKNN+CWYJQAIvwTjhP847aVMrVwupsCRtFdaQvTHCM8/NfhuJ/wSVicAALEEE85NB+gRfptU798LHTZAJ1v8+k2Z/sNGQaS9IFsVINy/GgMduJBzHdj9hF9kIsWa8Pt787Ej/NI925Z3ruFn+ATZZITu8AlhbgKI8yLD+szzz8Mnfg9XpXp4X9SP3W3HF1N7408ixT8PnySlmdxKrh2nETHaLFy+T8l8CPPIcxJAnBeZ7g0KuKM6FMmGHXzCH0wprGk4avp8HYbDJwBH0uepZRgRor7HSSvIlkQsCb+E7HgA4ZeQEI+OtOK5+nvJa4U7xP0u/e57NMe9gSatIO/guk42JeyOB5BNCenxKEkrxV8Vbz0xd1HbM79o9wEe/dNYEn4JKUAb0FYJp5ZiHEv4fSI1s/bocnW1kttOeQJJFfyQlRX7n9ZfModUaaYMGqa4Liz6A4R9EANcAxGcuwZQJvwi1VysCb+/AxY7wi99s7Zl1us41HyQPftoE34J7vEAwi/BNv4/rvlIn5rDw+W1lnhI+OW0rw9XT8WW8EtwiwcAYgmOnBuj0CP8blU9cFiRx5qU0PySmhZ9igJR8/Fbev/UFG5ljTBpDd+8hdcLuj4LR99QAAdaca4Du5/wi0zx2BF+f287ll189yitPm3LODfwCuxEzoOhSfilNseDsCO3WB/J/ln5iR7LV/sqN0AvJyMq7Bl/yDA4yg//0adevt7+qtEX9kft9zYNgzB3fj8eoPzQzdKTlB80CL8vn8ocdQw20454PWrpD0+ebxiOnLP3JX3k/BYjYNzEa8BATomiSfglEBIAhF/Cl78DRpcIv9vsl4varAvSS7MMNRjsvoDyjwGj6w3/hF/xAMIv/ffuSREBuhZcPSVv4YltHqrFVpk5vh61JhiFAyqlzZEswwG9uvjCCAcNOCD8IofA0SP8Uie0XxGxhA+N7lxbXCcJv5sVTF0J9vkah40jGiYLn1fqOuEXmZ4glAzC7XcMLFE1Qn93xUEm/GrekTPkqtqiG+bvbSYh/4a364Rf5KaFYKTRQCMN62zHVCcJv8grQgyLEsZqYcnBGc24kWrEJZ4WeYTpOJ4Wya6AAHG4hUsTIsXHjpsQyfiAYMLbuKAxIduCINOYkPfZEBQolQQ2NKbmAF1y7XxGFLiDA8IvkumCPuEXOVqKGeGXYJKIJuH3SpgG+e3yRHxMp9zFT5MVEjWEcpPVUpDURlgIWWpL/qFqSySeIO72zx2hdPBTNRypDYl7gtBktQQktdHN0qMO1rAJv8hrEQybrNg7kt5ktZBxsL6HG8IvknuGNuGXcDoecMgmVEO4AO4hhF+lsUd3vxRz0Eu+rjd+pMuk/ZxI+CWcigccdgkn4tEm/GqlDlCZRL6h6StzRmjgmmbpzisCSCOhEP6rgUaq7GnhHyXCL/IKDMM0cIrt/Sw9DVQz0kATLs6UyBUP+UyJZGRCOFNKx7M5U9qF6pJPiDLsfx8nhF+kifBP+I0nMH90ivArFM+G8LuyikTuJ8RwbjM754qsm1wWHBGiuu34Xt2kLwc8/zwWGFpam7mz0bz+hEOxbeYiirj+Bg3SflKbrMV6iihrQsb0/kf1cu+drHr9nnKOxRv5h/OJm7jJSe26bNXd13Tnj78ZntbVyTAxNYL22drfNRkVmaAIimqEBWdr20z+gONNfkp/0YSaJlmVjCGLmhYMNmuAY/L8YctsXNbdpSQOWHnmmbZ6l4fxaCZXjQGZXC6m3eQPOd7kVxcTlYQLdUnRNtKLJnlOnQDH5JmN1SGpx6oovi/28nv9WrQfhsmzgSbPbjf5I3ZEZD6TtQ8tFlxXKbzpniUSHPGKmYiM/PjDCkLq1lb2IubODi6WIk52rmYOFrREbU/H6vx9zGM3SjOu9WeYsfwpHdOCEk9scD7Sf4Fq2sqG8rpSns0dfIt/OY/9l3bUGRdVCbxba1ud8vecDMFSjXA6urYzStEQK1sXSwen3++JdYr9MCKlvq/RNPWiyjqBCG9FzT+LnNbvd2QxH9D+wv9argWbM5VmBimr+H940BQlJSje1eV6VZXAQ7fQHVbzAdSJaoS30bXdeWro0/ZG+6+xs7O2NPv/ldaZYZ1BrV/1e6mwdFLGIlEeAb9mHf+TfdSvidl8QOjrLFdj26ehc2dpHrgTDfLAaWw8wKtmZ+dgQcfQtZpgJovY0/7RGQBKm29adxBL31RxHxp+XmQdqXTkhsbpB73+fAQxtxr9+/72ze9P/6/Ns//8Z4/N2yarB995Fvy+erwQhM1TBnRdRnRt5zTK318GsI6EhMo1j8bpGlElqQPMz54a2RXrdHXlblL7HTtaiCxGVgjU1pXbluoe99BUV6IVYDwgN55YOd/DR79S8TmmqS6cF5TqBvPCTnW1sxv4xUPPkfM+cxkl1qhs5PxU588L2q0reHtgqntRUfreZrQLKXXygsXhk6f5Y5zqZgE9MBgbD2CV6iofT7FVMTukETMgQ0NNZrA/xFQnK/NeXP9hsvaOlD75fX6eWQth8zwYCHJd1UDYqS5/Uuy5i7ynKKU8iup8Aw50qRCAkOpaYwfbVEdbuW2p7gnHH6R5p9RNGOWqQ4pdecXo9K7YoXAO0kEy5o4fzvJoxFg9ifjAN+8khIN0+GDQQdp6cLvJn/bQ6uJYqZvHc5kFqiVP3pVmuhQHYlpdrDYGVRf3FsOuLlb4ly1PuhGlVTr7kKDmr/gyzq8ulhqDAqSMcQ+sLua+15DaeHuD6oHG5/VCpPWWGFcXA4AeoK3R/1J14XIywObISUfSwQ3lmhs9beQgVhevjCNrDiyLVve5MsG6frpOVykVdNdVLAa5Lnox7OpiUvhwdYPsbToZIa/6Ji0a3wfj6qI1drCtLmgrty3VPeP46qLlTbBsSclY1UTFzx8cXBImwakujrmRo/aEm+gFXhizaNEuvtcQqotbS0HVRdXSdpM/76HVxc6B23xl+6zUCrAWWxI8OeQ8ptXF2QpQdRFeAbu6WG8fFHjo+V2NbU53XUS8BzlwfnVxsgIUIEsqemB1kXtnlGKlzRI9qszoRknvD1jL9GlAD4Rj4wGsqovM5c/lmnKVVPJNiYvNsu0UIFYXhy4Y3frGraaTOl+4aJWM+GgIm8cN6DqLCtjVhdC4p4fP7HiiG73L5p7YhZPGGFcXrbGDbXVBW7ltqe4Fx1cXyKYUONXFiQvJFk4hldqFlnHCTf2KZkCoLvpVgqqL9wfaTf6yh1YXx6SOUnY13NWPmXsnZchn/3RMqwvVu6Dqgusu7Opi1U+Czd7gQnJC/90Ogc+zuDi/ulC6CwqQ4nd7YHWRQq5P3PBgtXbgQIntMbzT+2BcXfADPcCFjQewqi7GReWtjHAsJR80ina7Mr3UFGJ1UX68PnHmlTBKQJ8DMq+OjLGGsHle3QG5ruEO9JsRrrkTP2+W1StYXy/+0cajEePqojV2sK0uaCu3LdW94vjq4u3t4gFpFbKq1do3z54+epvVG/mH6kJmcNOKi40BqjHUJ5ahlDNfIVQXO+6BqovIe+0mf91Dq4uWT2dfer500MtPPBY3OfXRE0yri59cdYDq4g5Xp4ZRO1Bd2FpPytzx5bhO0f6J2cePqDhxfnXxnW4h9i2GXN06mNQ91UWfwVsdMjZbE8OOJBimLajcjnF18QTogTvYeACr6iJeX3mScNxare3pQsYDKy+fgVhdFB+dJmCzSF5/64DC00PmVDtD2DxXga47zdU5zs//ri5mqAQI8ivzacbvU86uOvN6JsbVRWvsYFtd0FZuW6pr4fjqYoa957c7LYqacTI5q/IHylfBqS5yNy5Zef2lu0pJ7mbR69Zy1RCqi4S+dYDqIqpvu8nf9NDqYkGUeOreH5Kk9Fkl8VLTpl7BtLpQ4gdVF8L8sKuLl7EhtVz5L9SCNxs1G31v+sH51YUCPyhAyvH3wOpi5nNqw3zhYL0Qy6nKH4XOZ2BcXYgCPSCMjQewqi6OP15aqPT6LbkoIEv8YT+3FxCrCwOPG5a+q2tU84aOTRJSfbsNwuYZDXQdLz/s6uJ27XZ9haxXqhncfBVeJamLMK4uWmMH2+qCtnLbUt1bjq8u+OpnjFVt0SMHv08lCuy1cYNTXbhptQhe5nclxzyoUB31wPsahOriJD+oujjCMPm7HlpdaH1OrBo6fTDZN23R++zAebmYVhfzRUHVhZAo7OoihSqSf6VvNLFo+pvpu26KXOb86mKuKChASon2wOpCOuvWTZWDrhq7y9YeyGn218S4upgM9IAQNh7AqroYv4uo590nTTU+9YGg7J2L5yFWFyZyEaqUyQ7k0LdWyfLnY7r6VHe664YBXcctCru6sH/LvXnW2S+kdNXsxQt3WztgXF20xg621QVt5baluvccX11sLxD5Jt88jBi7//KjL5E7B8GpLkxCTk68bSlMrLKbEOE/6toYCNXFWVFQdXGCYfIPPbS6aD7/86zk7Im6+5+FBNY/+bQL0+pipjyouhglD7u6UJcftqGFuoeyY3q/UnGpHe85v7qQlQcFyOnyPbC6ULKR3PdA7L124M8krref7kVjXF2MB3pgFDYewKq6iDh9/Ju/RwulLOmzzm4b8VyI1cXMQ5debyh5obL91Eehyb+WLYCweQYCXfdrAezqQoq76mw/13E6sas+zn7xUX0ZxtVFa+xgW13QVm5bqvvI8dVFnNPFFdWKQzS2b527od/ZJafgVBfjjs26b/hzomY0tWR21qiNiyBUFyXyoOpiL8Pkn9iZXOU0OdbxrJlm1uLR5gPWrV+M+E3NbNexeDgru6fdjFFzsKQ/l9VMxIH+jXQOYxv9r2O1wukmrZR372bqZBh/PKPjG9iPxZv5ez23frqjJtMmE07uqaFtUFUWHN4jFDJBcE9NZx5yJUCys6GZpu03bWUgtv7qLH+9Qe/mC+YkjtLIXHTMO+/WrKY/QZ6/f1I3gDxFaEaooBthHqtIRSezrt9Tg0WSGUAnazq4/P5NFQjIjxblzjxlZ5he68prBaw6Wdqzrs+eXj/92pQSp1EuM8SRuDmr7s8FZ0T/vn/Y57dvyT8xqr2s4iNvoZE/WDumi/uc7i9BoL9O5tX8lVnabYMIjezMNdwQsWNZ2kv/KJd4y0lvSpnWYorgz8mbOrJBUXjSl17bAj6iQvibRFuo12qutsD3mV3gs1sjcfaX7QBKopioqzHPtj9L8wFkOpW9Uw+mlm//FhEzWxFLN3sHmtHpLNrWpzuZiay1tnSzWsPAodIN7WLmYGVG+1QHgyOf2MGNydn5Ogd1iz9c4NVWYP2G/34eWPsrnXgeXs4+mnFnqbI4JqXp0l4tqPkbVU4PkvS0wAJVTv8/ElW+eaB11THrFI3SvH1J38olgpGo8sQf1Mr0rUu1yrJz9VQeSjS2v87F5vXuQJnzk//fq/TnirTZlaWzHKYLj4+X99QOdV/SZGVT8frPx0/8/w/6h+hiaTpAQcMqWTvkzk3zkLsv7ncxusjQ/J1I97cMkUV0oT//UHNfDQuYOTsrjWKyUvsKZ930tLo5eMagAq196nZPgoSEv/9pIuO2bxVZ+jf3d+n/ZJkj4xQEG30uANmItieYbPS/jj0dtpHU6n76EYNKKOXjy6vOahwewcZG+n/bSP9/2uj1Q1fSMN8XpLhrkgOM9t+dBcFGS4E2GlBQ0xlC+ggmI/1+DhxLE40yolJ9Hcs19xe3zE8tT/1zAKv76OirKW3biJ6T/jr/RFNal0hbTvqCEzr3UeV5Ky6FZFKih+0ICDuvGwh6O/igc//50Rk6N8E+pYY1nVuxgkSO35jS7tyv0B7nNQDgU9EuPc4LmUJQeJwXW1cjn9dV1kdmxmwJUSlZsZXquvr6hqIyMyT0xeXEl4pJi8qJi8pKkFeKirZ+Qur3679fFFtJ/xYpUVmp1v+W+Ps12sfvH0v7GYifzPSjpdj+bAnwz+7gE8QKyWSCwV7a0lnWunRQeILYtioy+ab+3hpcPEHsG36eIDZTN34g6cMQjaJGcblF53lfofwEMYO0GgL7J4jd2/mXLAHUVf/XE8QkBI66js0t0U/LvbOs1iQI8RzJf32CGDJhQHiEjEpaDeAJYjSzQH7mFrIqwvBhK+x/dfrDVmi/etue+o6bZ259aHR3HidZRIm/LDPndXNGPerP3NLMaNtULJ+5lZjO4iD733zm1mHqM8Kpbf11/RpdzgjvaSFy5DO35mXUAB4n9SSd1TGV3UL+l2dunXtuyh/8/pnGnjs+ClEiy/p2/Zlby4aK5Z3nTtCsjL7ovFh8tQYEI9EWNcBImundquwyqj68PXMrM49SMLjBTDP2wsKlVmtcD2KYBhirnuUzt2jubksDP6A9Cns4w/noPwobeeVDe6k9dH49z9dYsddKu2SazKT5WY2+tJfa5T+kFkp7qS+BdQ1Ce6kfgbVyRnuJu+0lZLFHe4mn7SVk0qK91L/tpdyPO97pzHfSKkxQfUQcemYo7aUBbHb2X4/4pn8Ry6U3+GDtlYjXK/WjfS5aNx59VwzhEd8/cfCIaaQt0X/ENFI5wu4R00uL6GUK7YBYiMYjpptCNcjzFxXh44D4CxdPDkTubshPDoR8jqI/OfBGag3rJweK+euSN9mntmcReicg5zcKpPiW3Xx5qT+Fusp9cMT9mmeoNAoYiNUCGgU+i/4FaYLWKDCAJ6r/pkPLdSuiftoQThccwrBRQJNuBLYXzyJimFCA/qlRgJ1nOtQo4GOauyp9dplWZfXUVdoJlEA4jQK35hbwz6aoaPuqKAuk/jSqgtAoQFuWAH9dFMXEXzy/N3f7N7UqMd3Sr2BaXFb7uSReJUmnZZN8ydyx2PUrtO4jtv0KNK+1xd8+7OIv7voVcgIfmqhtU6D4rDyxx/ASaQeK/QrzJGoB/QoV4rW9/Qr/o1/h0qa6Z171TvqVj/kT8zKrVkHsV5j/dljy4NpIdX++Z3PmTD9wHcI9swzd3+zvmSVq0ehXSMl4pBdyUUw9W8TI7c1jcX2Y/QrIOAXBRvfEQTai7Qk0+hVWDt+YJCwmQIoU3bRZdcvOoTD7FZLzv+nczclWL5A+wj1gepeHHeg2igbaaL14LQr9CvJrPB/xf7lG3uf6QMFCY/ZPDPsVWrcR234F2hJpy0lc7HISh/UrxNSv+u4lmqlSmCdgJLChchj++xV4CcwfnepXiJ1Yy7pf4WkFifwiZmK7c/uycy4H9SsgU0hvvwJq/QpHyGTCWXqtilq/Qs0JMtnztFgtLuSofux2B+f1Kxy/MSBox8hRxODCm/FU+dMTUe5X2Dy5FtCvQJrMEmH9z/0KiQvXSkf4iOvuO0ioldYoU4XTr4BMGBCu35wm1wL6FWhmgdyvgKyKMLyoYv+r0y+qaL96257iZrenOK5fYZKynrzc44l6ZVeGTP144fl01PsV3KbUAvoVRKawOMj+N/sVojxOZjs1J2tuXUIMvTFIIYkj+xXsp9SCruKnsDqmwuxXGF+697Gh/QjVxODYwsJDEyd3vV8ht9/W5mrru5rpojxJ0x4pD4BgJBGgkT5P7lbBErf9CmUNvygH+yZq7SI2xFwed9kfwzTAWPUs+xVo7m5LAzzs0gBH9ysgb5461q+A1EKZ+hWQNQhTvwLy2MPUr4As9pj6FZBJi6lf4Xpgyw5+uSRVnxAT4fkjhOYx9Ssgd3bH+xU0H7sNJTdXkCoGb/hmmLttO4R+hf7QzqTo9SsgbYl+vwJSOcKuX8FashbFfoWIMA1ylpUkPg6IA9gtVY7qV0Dubsj9CpDPUfR+Bc1Jtaz7Fa7565JX8E1qzyIDcdGvMDHN1vCa4ErSvs0a86Q3yCOfcA6nXyHYHdSvIOOOXr/CJIW9i186l+pWRQXxyJ9/nIZhvwLVHXT/vdT9P9Kv4LRiTvOE0ltqsSZukfeqZV3h9CtYzb0YbBlhp7M9/qLMg0HityD0K8gA/TUAG39h1q8w4+fDdcOGLaH4BRbGm0nUaGLXr9C6j9j2K9C81hZ/eXtMv8KY6LVVoo0L1EpuXrrs+E7/A4r9CvaeoH6FFo/efoX/1a9w0P/nYJlzH1VLpodmjVXUHAyxXyGwYNhe8uMqzYK824prp4QdgXDPvN4TdM+s4olKv0L86zf8gTnrdbNmTG2udT01Gma/AjJOQbCRINBGtD2BRr/C5YYt2X5DiinbRM89icqI2wizX4FXa/A+66r72n4iodpu1ZuKIdjopAfIRmkeaPQrHBKNKxC3M1YP8CMckHj0YgCG/Qqt24htvwJtibTlpEE46VcIvnL9l3aOGDljsFiF0fWmu/jvVxhNYP7oVL/ClE1s+hUel5PIMydvanfuYBz0KyBTSG+/Aqr9Cnvd0exXOHycTJ65xx0fctQQ/PQrUCYGhZrVGWukRd5YMV/t3ASU+xUGO4L6Fa46wO1XaLpzZ3DGm4PE4G3r72cOWh8Dp18BmTAgXL/1cwT1K9DMArlfAVkVYXhRxf5Xp19U0X71tj01FDf9CtyfV7mGzPugm+FZzZ8WEbkJ9X4FghOoXyHHsbdfoc0zDhduOEwsU6bsOdBvidf2K4P+j72zDmjq7eL4SBFQUARpwcCkTAQDFowaoKCoGKSElKSBOlpKuktKBKRBQUpRBBsVu1ABW7Gx320M3nHZLvjj3o0p/PN7313F7Xuec77nec7n3o1IXqHbBWwU3+ICN69gHG693TOiDBVxV2PTufQcl+HzCvNamjXyhZW0DvIu5nU5om4OgUiHQUXCu4zyCkPhFaIuhptv/vgBFccTuty+wmcuA22gb9VT5RUI4SbbAB9T8grAydPQeAXgWSgFrwDsQSh4BeC2h4JXADZ7FLwC0LQoeIW8DcXezafStI9VjMv7zDNLhIJXAGb20HmFp7otU874sGpk4qVatm9XNoaAV+BnAl4BqCX8vALw5IhxvEKWJ5y8QnAQFrMxw5M5NogTmIJXAGY3xLwCxPso0vMVttPgFa756GDCsvuOryYyBa8QsH6rx3vMPbR/SPDal83NsrDwChvTQXmFdPh4hVDrrluvz5SjSkXvnJ6k8hPHQF5hXTrY/Bud/o/wCgvSd087mFujmsdh1hITp74EGl5haYL7DCE9AXSYxr6XAW+Of4GCVwCNlzhj4sUwXuFmpZ7TEeNVSJ9HiUfaNWcDv7CHjrwCKY9o8wrpvfVX4K/hFfwfKd+wPnET6fv9cU23mXE4jLyCcgYYr/AtfZRXGIxXeCsccHHP21bVgikPESbPLiEh5BUmRwSaf535RBW/bxrLWtWfKyCYMy/OAJszT82AhVc4rlSEa0AXqoWsDfXaY6/xGEpeAVinINBoPKhGhJyAg1dQNMpW4JSZiA3NrX501T6WBUpeIV/uYgP3EglcWE6AptCuJ+8h0KgzHUyjq+lw8Aq7A6fazI/8op3hetHtAtcCBAN5BVIa0eQVvvV50iQm4RUSM4TU2+xl1StvOJer8s38wvy8giSC8uePeAWdFBq8wrdKNOaRVkpvcAWZgFcAWsgorwArr7ArHU5e4cppDAa3M505jqOEmIdX8LaaJ3prVSn2WKb0ktKFqgYw8worUsF4hamp0PIK7PVRFs4TgtDZZTtvmiZh2KHhFYCGAcH4TTkVjFcgyAIxrwDsihg4qKL90YmDKsJHJ+fUZKbhFSySqzu3rApS8/MU4dn7dNIe2HmFmlQwXiE8dZRXIEcm55HQscVZSRo126Omi/+4mjsieYXKVLBRfFYq3LzCqYvxb5UDo9WqJ47dYJ59x2P4vMKGewfz70+s0qxPLN0pPuXYbAhECgcVyTN1lFcYCq9QuuFxZWawul7cLU+5qs1HnzLQBvpWPVVeIbzPBoSZklcATp6GxisAz0IpeAVgD0LBKwC3PRS8ArDZo+AVgKZFwSvs68h7l3mkWytyvtC1qwqJeApeAZjZQ+cV+J+mlH5cp4k7+jsFKW7vPhMCXkGECXgFoJbw8wrAkyPG8Qo3MuDkFRKDsRi+1gzm2CCKMgWvAMxuiHkFiPdRRF7hUAoNXuGRrw6GL6Tv+EqMKXiFJbs2G0gfslMLFUCXHrh2sAkWXkGrGYxXkGyGj1dYfYuHc7zYVb2j/hcL4s6d+8BAXkG9GWz+Pb/5H+EV9p9gF2hXEtSslC+4c+zpRi1oeIVlH32nnNplrF4kevh62u8djhDwCpKg8eJmTLwYxiskX/tufEd2oma6xWLV78fLixjHK5DyiCavQIgauf6K/zW8guipDdiasFDdwyvWW9VsvHwARl5hxVkwXuFX8yivMBivsOBBLQtuVqxexIIPBc5nbrFCyCuses+h7uiio567c9ElJ80yEwjmzMpnwebMMmdh4RVSfIU+d5fdQVVseBxz9bDXByh5BWCdgkCjiaAaEXICDl6BvyVqfP2+Mo0Sl3HGmKQyUSh5heIbOh0fa1aiDldcn6ZueFkPAo1eNINpdKMZDl4h22DK5AbpDrSXYvF38eerdjOQVyClEU1e4VefJ0kwCa9wtXHJ5smin1EZv6Vdi4WR15mfV5iFoPz5I14h6DQNXmH7MTSmNvB0b3AlmYBXAFrIKK8AK6/g2Qwnr7CU8E/I7W5mjuOoKczDKxx/sO63n+R7ZIVf96qPejy1MPMKuxrBeIXNjdDyClqvt+92RbxDpzho3TF+bcIPDa8ANAwIxm/ujWC8AkEWiHkFYFfEwEEV7Y9OHFQRPjo5p6SYhleYp5bIZxJ+WONI4rrJ1ffjg2HnFbobwXiFC42jvAI5MsY30KrlZlG4tHeqBW6i3vojklf42Ag2im9rhJtX2Lup+V1oSiC29p4Qu+vSMbuGzyvgnk++uMGnFh3kLS+esMc0EgKRLoCKVNk4yisMhVcwV5nxSuKQO+bAu12Pcn+IVTDQBvpWPVVe4UKfDUgzJa8AnDwN8fkKgLNQCl4B2INQ8ArAbQ8FrwBs9ih4BaBpUfAKZk9NVe9VdaArUooir3tfiKHgFYCZPXReYcK9d+VXrnarl9p4TJNbaNcCAa8wlQl4BaCW8PMKwJMjxvEKD87CySvwB2Ex0ffOMscGcRpT8ArA7IaYV4B4H0XkFdpP0+AV1vnoYDrP9R1fTWcKXuFi+rKALc2RSK+TlzMe78yOgoVXKHwLxit4v4WPV2Bdy9b+IXKy+oEIudv1MraLGMgr5L0Fm3/Hvv1HeAXNTVf3NahN0DzOLj5Xcv/rkxDxCj8OvA2bqawWdFCv8KcuNw4CXsEbNF4OjIkXw3iF01kWK4Ub6jXinmmOvbR1mzjjeAVSHtHkFQhRI9ffGX8Nr2BtU/181vuHuuX1E661+R7ngZFXyOgC4xXMukZ5hcF4hRlXXiv71tRoHtbH3HxjovUQQl5hybt14+zwFupVFYtr2TLKkBDMmVO7wObMQV2w8Aryt7I8X5WVa9UYSuUaN5pUQckrAOsUBBq5g2pk1gULr3Bj5a4PR7L9MHi1BNeg9B2tUPIKN5rus21G+SO9Ww/8Dm1MbIRAI11QjZS74OAVFFBPhY3wPOr+1YvGy67T+8xAXoGURjR5BcISIXuSDJPwCiw7UnjPRRjo1YmxqqUY8mYxP68wH0H580e8wvGXNHiFH1VozKSql73BnckEvALQQkZ5BVh5hVtv4eQVbjZiMHY33jLHcdQs5uEVzubpB1xxvKSZgvf/cFBSIQpmXuHQKzBeIegVtLyC7XXteWdfsSJzrhz6nJSbLwMNrwA0DAjGbxmvwHgFgiwQ8wrAroiBgyraH504qCJ8dHJOzWYaXmGyW2yhR7gypuo0ayIX/5absPMK01+D8Qrdr0Z5BXJkGpHLFF9dm4TzW5eIkL8o5j0ieQWp12CjeN7XcPMKT5uF5bC3vNQD4jK3LfXX9x4+r1C2Yq6d8NtGvTKxOvPijBWSUHxpxiswkdpfjfIKQ+EVItN/HE77JaAZcDpkdTfmuDwDbaBv1VPlFbr7bGAOU/IKwMnT0HgF4FkoBa8A7EEoeAXgtoeCVwA2exS8AtC0KHiF9ytWTHg6bxa2fvMZluWZOE8KXgGY2UPnFWKf/kK4qb/WrudYn/JC6koXBLzCXCbgFYBaQr4nHdCtAk+OGMcrIN/BySscDMFiJqm+Y44N4jym4BWA2Q0xrwDxPorIK0x6RYNXeOqng0F96zu+kmUKXiHy+/JisZV2WlnfJm9aN8NqOyy8wg6eJhBewYynCTZeYdLYV/apJ7XQMRcjb80tPXOWgbyCO1EEmvNvO56mf4NXeLGrO3/77Cc6R1du5LASCZsJDa9QLZ3AG3H0NzJA9XHzBK65uhDwCmag8VrHmHgxjFe413I73zJnilp4lrN5+xjxAMbxCqQ8oskrEKJGrr9yfw2v8EXB8OXlTHndtAMfdraUbXkPI6/wniguTV7hKk/TKK8wCK+wYjenjxPrZb20V++dN5Z0ikLIK6jKCKPcsoQ1izGBHqqK680gmDN3EeNNc87cydMEB6/wu/SUktcdHdSBD7LnlqvMEoOSVwDWKQg0ugeq0dV+GkHGK6zEXxdqtZHXyPN/cS3SxiYUSl5hXkq5gtViVeT+bdtQfKzhrhBo1AyqUR2hw4OeV2Add5LVLMhSrXT+/NBE8TtRDOQVuno9iSqvcLXPk+SZhFcIS8fIFQp8w+xPtctzUVYWZn5eoX9v+0e8wqGxTdR5heBKNGZr9tje4CowAa8AtJBRXgFWXiGRWBdg4xXMTmMwexJ4mpjiOEqReXgFdxON9CV6YzE+k4TQ8jgeV5h5BTHuJhBeYRz3gNORYfEKgVICARkFdegoDcXdd69EQvR9EEDDgGD8JsLdBMIrEGSBmFcAdkUMHFTR/ujEQRXho5Nzaj7T8ApyuZk/w1zE1fGrHl/ZvuXtcth5hQ29SUWVV0BzU9nI/pu8goTOW5EJ5wPVgu/XzHlx7/rkEckrrOtNCKpncbrc1LapUPIKRjNtFp0siEd6nTk+adbHZUXD5xW4Di2Z9aI4V71WoBL34tMTXwhEQoOKpMxN1wNLpuUVSo4pLEiqXq1Te9p2qtScL8cYaAN9q54qr4Dus4EFTMkrACdPQ+MVgGehFLwCsAeh4BWA2x4KXgHY7FHwCkDTouAVam7x5CDKSrXCZCURAXctvlPwCsDMHjqv8PmI/3SlOwLoA3yPpxyd97YYAl5hIRPwCkAt4X++AvDkiHG8Aoq3CUZeQT4Yi8EgeZljg7iIKXgFYHZDzCtAvI8i8gpXicdX1HgFF18dzM/GvuOrxUzBKyQXKb23bz+Jzl1jGxqb9i4GFl7hgzgYr3BfHD5eYX3udEfOIBWNsoDUhehU83wG8grvxMHm30/F/xFeITy1Ve7cOJRObvSGs/Ht839BwytofBQtL2VtxSQcPO5dffAKDwS8wn3QeF1jTLwYxiuYh8tzj507FulTIGI23/YrlnG8AimPaPIKhKiR6++Sv4ZX2HdCACH2eox2ec3Vi0bnVsPJK9hLgPEKOIlRXmEwXqGCxeqsvh8rpmAaywoVjnFpEPIKT6aHvM5PqMAcuuEXzx2tdROCOfM2CbA5s6kELLxC8Gdfy8D6RO2Yie+5QnOn0Xp2wH/iFYB1CgKNjEA1wknAwitYIhae8KlSwcY/e4phubn5MpS8gt2uufL3Xs3A4c0vbJ413v8BBBqhQDVaKgELryAjqzpvzBX10rmPs3dK/nRnIK9ASiOavAJhiZA9SYlJeIXYaaa4T/FeqETFo6Zq55QlmZ9XUEdQ/vwRr/BdlAav0HEUjTn0TbQ3uEuZgFcAWsgorwArryAgASevgCT8E+cmSjDHcZQy8/AK+VHbkCw/vuDSSiKn/DY5/R5mXsFJDIxXMBODlleYUnMwavYcHZ2q3dJdCneqpkHDKwANA4Lxm4MYGK9AkAViXgHYFTFwUEX7oxMHVYSPTs4pFabhFULLXl+bxq6gVXS59eUMiyR52HmFot6kosorJIiN8gq99eBZ1ARvzTd62VLVs0KbTgmPSF6hQAxsFJ8pBjevcBFdIP1EAqVZukLyhPmVWxnD5xXqL7j6jOd8oxqRcmY6aj73cL/AlihSAqhIYWKjvMJQeIUim51fxC6Mw4U0Cc5ViX8QykAb6Fv1VHmFhD4bWMaUvAJw8jQ0XgF4FkrBKwB7EApeAbjtoeAVgM0eBa8ANC0KXiHpYEdKq9l87aodbz81N+S1U/AKwMweOq8wqTX57BEWWb0iT5G2Mfm/OiHgFZYzAa8A1JIOvALg5IhxvEK9BJy8QmAgFhNdxyQbxBVMwSsAsxtiXgHifRSRV5glRoNXuOKtg8GI9bnISqbgFXYsedg+SXKBZrLS/iNGyglOsPAKzfJgvEKpPHy8QutLPzEBhJNG3JRPyCTUjd0M5BXOyIPNv2vk/xFeIVnd78TDpfZa/vkLeRvyjZOh4RXSjrPf3f8hDJNo+axk9uPZbyDgFUpB43WYMfFiGK8wdfJVu1Wcmtq5V01+XZ+IzWEcr0DKI5q8AiFq5Pqr+tfwCjuMquQn2H/AepuqSvDF8BbAyCsgFcB4hakKo7zCYLyCxuNfFrs+3sEl33fTYv2VvBlCXkHl05q3rJbZ2MTwLI6pY0zvQzBnVlUAmzMvVoCFV+DEfn/n/kxcJ7C0UjTv8cybUPIKwDoFgUbzQDWaqgALrxDEt+j6Z4kujei5HXuWLV1+BUpeIfyJvkLlD3f1nIZrIstNnoRCoJEwqEbjFeDgFY6sXDx/XZKUWoJ1+626rjW8DOQVSGlEk1cgLBGyJ6kxCa/QIb1GsinknG64zwTs/CgjBebnFfQRlD9/xCuUyNLgFRrr0BitYtne4CKZgFcAWsgorwAbr1CMwSAeysPJKyQfx2BEH8gzx3EUinl4Bdd5qzFO46LQWSnv2r9ybnoMM68wXQ6MVxCSg5ZXeGKb9ijmWzEK/3RmzczMfQLQ8ApAw4Bg/DZVDoxXIMgCMa8A7IoYOKii/dGJgyrCRyfnFJppeAW9x03s4/ncNQ4nPlbJfXZiP+y8gnlvUlHlFXByo7wCOTKSQevbx05JQ/mwP3p16URb6YjkFUzlwEbxRnJw8worQ/IecfNd1Tz6ZFHnaecG9PB5hVQDpw/KtqGax9xW4Xzvv4uGQCQcqEgouVFeYSi8QvRY/1qVHWM04gzNSrVQDRMZaAN9q54qr4DrswEMU/IKwMnT0HgF4FkoBa8A7EEoeAXgtoeCVwA2exS8AtC0KHgFwV313ipmrJia0KWtVX5LH1LwCsDMHjqv8KMMH8V7lgfnf/ZhtNAsq2gIeAV1JuAVgFrCzysAT44YxytkK8DJK+SFYjE+WQrMsUHEMgWvAMxuiHkFiPdRRF7hviwNXuFIkA6ms6Xv+EqDKXgFg48HsjyML6sVcphuiZy16S4svEI6EoxXCEbCxyvUTFjt0F4RgIqbfdOHc/r4nwzkFdKQYPPvGOQ/wis4ccx13HA/SXt/hIdrzcX9StDwCuN2xlRbmO3GZlWedp4qe9ALAl4hGDReXoyJF8N4hYC5+tijZuWY8IVb8yWangozjlcg5RFNXoEQNXL91fxreIWn0xXqxXB8eimRt4VCQ5JkYeQVxFBgvMJ35CivMBivwGd6T9Q55hoqTEA4pXYVyx0IeYWOqXyh1fordEoNq5KWtStNgWDOLIICmzPzoWDhFSxsk9/7rritnbnkjZyprUcnlLwCsE5BoBEHqEaEnICDV1DdWz1z/cGX2rFPL183Pa6dDCWv0JGX6Leoq1CtcJNv88LCKeoQaPQOCabRUyQcvMKWsZL5lThh3dqi72FtytVXGMgrkNKIJq/wvc+TtJiEV5B0PjAz866MRoJo7Yvmr04WzM8rbEBQ/vwRr9CgSoNX0CJcvXNStTe42kzAKwAtZJRXgJVXKEXCyStI12Aw3CVI5jiO0mEeXqF99S6D6IZfWhlnvI5s+u49DWZeYaEaGK8gowYtr8CZtOUqf6KIaoynQ5t+uaM7NLwC0DAgGL/NVwPjFQiyQMwrALsiBg6qaH904qCK8NHJOYVjGl6hVfNaA8eh+djoVZGRzbfP74SdV3DpTSqqvMImtVFegRyZZJX1vG1ZE7RLcnkqOHdzRo5IXmG7Gtgo3koNbl7hbqbiB/m9YmoBZT9P7mz4IDl8XmG2TRD301kzVFMzjnxYfUwPii/Q2QQqkoHaKK8wFF4h6aDKsUPfs1TDkLUyE+fUBjLQBvpWPVVeYVOfDegyJa8AnDwNjVcAnoVS8ArAHoSCVwBueyh4BWCzR8ErAE2Lglc4kGix7rtKFaruNPpKasCRnxS8AjCzh84rVIee+8I5p0aj5rNvzWu5OXkQ8Ap6TMArALWEfE86oFsFnhwxjldwRMHJK3R4YzGtDijm2CDqMwWvAMxuiHkFiPdRRF7hrSoNXkExRAfj/rjv+GoVU/AKSnt9DCY+aUQFnTrx9J7dFAwsvMKLNWC8Qusa+HiFuGQppeSJX1H1XWbJgQ3jlzKQV3i2Bmz+/WDNP8Ir8M14bdaKa8JmOvDPywuNOQgNr8B1faYC91F7bV92vs6HscUTIOAVWkHjdY4x8WIYr4DydCpY93u6VlKpztT8LKONjOMVSHlEk1cgRI1cf1f/NbxCnTmHcvfnMag09Hrz6EjrfBh5BYu1YLwCeu0orzAYr5CbPuGgZtxRlL+JYkXlz5MREPIKi9e+dulwl9atXNT2MKugbg8Ec2aztWBz5nVrYeEVJr/77hvhnKeaUt2kuNfmQyqUvAKwTkGgkS6oRui1sPAKeTfco94fz0WXZF4OlBKawg4lr3DIWOHV28IlyMMqqU/P66jvhEAjZVCNFNbCwSu846+1nvfpsGaw2I/VSQpOdxjIK5DSiCavQFgiZE8yYBJe4QziBq5jXSA644HShuumqz4xP69ggaD8+SNeQciQBq9QeAyN8RM07A2uIRPwCkALGeUVYP0+CK61cPIKG05jMIpj1jLHcdQa5uEVVF/bnX/Mvk0nEv/0ucg0vW6YeQV/QzBeYYchtLwCIlXRplq/TuvI3ht2ix7GnoGGVwAaBgTjN19DMF6BIAvEvAKwK2LgoIr2RycOqnb0Oc5apuEVFgbMrLxlwK5VfkDUt1nfQBJ2XqGxN6mo8gpFhqO8AjkymLEXdMU3zkX57QlYr3v2xbkRySucMgQbxVcZws0ruD9tMUn5slbtuGLa7fvql7HD5xW6399rXtc2QzXyuAf2mGPLcG+wIopUBCpStuEorzAUXuFB2cIiX6NnqkWI6RPSxpayMtAG+lY9VV6hqM8GjJiSVwBOnobGKwDPQil4BWAPQsErALc9FLwCsNmj4BWApkXBK7go6cuz7lqkHaBcbpb3RTmfglcAZvbQeYWW9tYSfSMB3FHUvbNra8JwEPAK65iAVwBqCf/zFYAnR4zjFarXwskr6AZhMajjTLJBXM8UvAIwuyHmFSDeRxF5BZQhDV4hwkcHI764z0U2MAWvMMEmXMjk1WlMfODxuKS3xQqw8ArPrcF4hWvW8PEKZfq4024l3LjoNPMl5Vt5OhnIKzy1Bpt/37f+R3gFeWF8HS4hDrNfOTIzd5FBCzS8gtj0vfcDj47FRam6swodPCcNAa9wDTReZxkTL4bxCs0Z/D4KNcKYsqjIa02mutMZxyuQ8ogmr0CIGrn+Gv81vELwoqQCxfiFumFu95N+vrYwg5FXsLEB4xU0bUZ5hcF4BZH55zMX/3qLrl5ce6OwMu0jhLzCmEM/1s1/FKtRtMPbLm2L+gII5sxWNmBz5k02sPAKTxe0cr8LzMT6zgy81JCybQOUvAKwTkGgkQGoRpo2sPAK0Xy2IZ8McDrH5C8tLl5kpwglr7DEnLWtRKhKHb8qge+giOB7CDRaCarRIhs4eAVb9LhpHp1oXFpE/q5uh3gxBvIKpDSiySsQlgjZkzYyCa/w4lpDBaYrEJmfH3U1eOf3O8zPKzggKH/+iFdgt6LBK5SXozHL2ax6g7uJCXgFoIWM8gqw8gqCNnDyCmGEfyJxkg1zHEdtZh5eQSatCGMgFat2/LaBB0bGKxtmXmG7FRivYG4FLa8g/uycyuv17Kp1zWe8Wgqdg6DhFYCGAcH4zdEKjFcgyAIxrwDsihg4qKL90YmDKvM+x9nCNLyC5K3r1yUOcajGfmvcaFRTsBJ2XqG4N6mo8gqJVqO8AjkyxnujgmblLdeOPoVc5WbGv2pE8gqFVmCj+CwruHmFgke5woG31mGD55yswMxcwDl8XmGGjAl+SesPrB9/cG3M3GZPCERKBBUp3GqUVxgKr6DK2/1lIi8H8jBXzprW4y83MdAG+lY9VV4hsc8GTJiSVwBOnobGKwDPQil4BWAPQsErALc9FLwCsNmj4BWApkXBK+jf0H6/8cZMrazbB2RbNpftp+AVgJk9dF5BguvNY8u9XTrHuSTPy3T7ukHAK5gyAa8A1BJ+XgF4csQ4XuGaDZy8wroALGbrVSbZIJoxBa8AzG6IeQWI91FEXkHBigavkEzohFun9bmIOVPwCilyXYXfWsO1Kh1+hiOEp4+FhVc4tRuMVyjYDR+vsDCED7FIwwYbO1tzXsRGcR4G8gond4PNv4/t/kd4BUybd7NljqwmfrKUh7RD+n1oeIWpUpeLpo9dhK4xLtoe6mqQBAGvUAAar0zGxIthvELgZ/luu7e/UUVSuTaeyWXpjOMVSHlEk1cgRI1cfy3+Gl7hl/Lzh2WcT1Xr9C0CliQ8nwIjr7DcE4xXkPAc5RUG4xXwKS3HrJ64qh69OKvN8LvdeAh5BWt2Od/Dkg+ReRibGVkftGh+7dofzJlVPMHmzIqesPAKG+QbN+O4VmAzFDu2V3rvuA0lrwCsUxBoNBNUIwlPWHiFuD1zmp4s3a3jg/ogtJFXcAGUvMLj9EneiZ+EMUn5r3Jymt7VQqCRAKhGYz3h4BU8DKrxO6U6dcIkL6je8UTxM5BXIKURTV6BsETInmTJJLxCYirHqpVT69HpiWeL0k1nFTA/r7ADQfnzR7xC504avEIH4eq5jp29wd3KBLwC0EJGeQVYvw+iczecvEJNDQbT3bGbOY6jrJiHV1jasTyr1oQVE9jVrvLtWysvzLyCwS4wXgGzC1peYcevKyLLanzRAVYeD/aLruaEhlcAGgYE47dVu8B4BYIsEPMKwK6IgYMq2h+dOKgifHRyTlkzDa/QsWruHq2Mj1j8VcW5BkmzN8POK0T2JhVVXsFz1yivQI7M5FOiOa6vKjUy2WJ/e76+tHZE8grhu8BG8f674OYVmvT9pnW/NdZNLRT5mNy2pWv4vELApw725/7f9PLHq7C0LJqZC4FInqAiOe8a5RWGwitUC3aed4w/rXoU8fTM4h0uJgy0gb5VT5VX8OyzARum5BWAk6eh8QrAs1AKXgHYg1DwCsBtDwWvAGz2KHgFoGlR8ArzNpvaTstEoSMjspUnvTG6TMErADN76LwC+o2r5O6nilreZ/y44n4fWQQBr2DLBLwCUEv4eQXgyRHjeIVYTzh5BT8fLOZUjCdzbBC3MQWvAMxuiHkFiPdRRF5BYBcNXuFiiA5mK2efi9gxBa+w79rJhiydjejiaYpX/aRWToWFV+AJAOMVEAHw8Qr74jbWJ81y1KsPM9uffmJrAQN5Be4AsPk3R8A/wiu4LFq/ufGmvW6W1+vXjc58btDwCpEOZWYd9auwCcf2laG61tpCwCsgQOP13f/f4hXO58jcltBR0k6QffBbvvE5O+N4BVIe0eQVCFEj11/7v4ZXUNEJrsq33a8Z1n2n7Yj8CwMYeQWNADBeQSlglFcYjFfojnFDr9F4phm3yf6z1Q4rRwh5hbv70jx/WRtg8FcPmS6Xq4CCV8AGgM2ZkQGw8Artd/dKNk1r0a4NHCP4ICFiK5S8ArBOQaDRclCNlAJg4RWsvrAUHDiyEp18dUZpNTuPNpS8QuecpaLcy19reKXslL/EO88cAo0WgGokFwAHr8BtdanjpGC7upeeTrWj6x1vBvIK2F5PosorKPV5kgOT8Aq3vbrwV3Lf6RWM1WtVSRWRYX5ewRtB+fNHvIKcPw1egbsEjTkp698bXEcm4BWAFjLKK8D6fAXJADh5hSenMJhvEgHMcRzlxDy8grPHw2cBEgvVSx1yTOxX/yqEmVfY7A/GKxj5Q8srdH71Pe7t5qdz8OfvBVVCq92h4RWAhgHF17H7g/EKBFkg5hWAXREDB1W0PzpxUGXU5zjbmYZX4PniepmlgxMbyynS/CH4EgvsvMK+3qSiyiu4+o/yCuTInLmmPHXL2tlqEUdlGhviXSeNSF5hrz/YKH6nP9y8wrFpgefZleSw1fZGui/vJbMMn1cou75lWhMhY2N+yoq+nCUAxRfouIKK5EjfA0um5RXOqE2xveseo179tcJ35ndTWQbaQN+qp8oruPbZgDNT8grAydPQeAXgWSgFrwDsQSh4BeC2h4JXADZ7FLwC0LQoeAX+0Gmcp9xMdb0So+U6Dxm8peAVgJk9dF6hYoH1nTlWh5CBn32vxN3XuwMBr+DCBLwCUEv4eQXgyRHjeAW3ADh5hUIfLOaRK5NsEF2ZglcAZjfEvALE+6guLQwe7U+DV/gcooOZsKLPRdyYglc4cajS/cr7pbplzqdLOKvbrODgFfBbwkF4BbxhOHy8wp4Sr8cixp+xtQtFEx7khTQxjlfAbw4HmX/j14f/I7zCIyNdpWT13+o5agWNoR/dZaDhFTQqjQT0OSLUM/gNuI6XPQsYPq9AXJYg8dJjTLwYxiuInzu0PlviELZO2dFbT7DgHsN4hZ48osUrEKNGrr/ufw2vIMRipxkS8xob5x7Etdk4Bwkfr4BPDgfhFfAh4aO8wmC8wr31WVm6y7eqZbnNrSvhkq+CkFd4jMj7nPFJExfN871q7hjjncOfM+OTwkHmzPjYcFh4Bd07NTe9Isaoh5i4n+eZUqQOJa8ArFMQaBQBqlFIOCy8QtrXxgJjxy2qPkFSZz9GdW2EkldAeJ04Zf3lhVb0xMI1r1+aPYBAowBQjbzD4eAVutH27ofGdGLTLc7oLpKJiGAcr9CTRrR4BeISIXuSB5PwCk/a2F/te3lEK0FGcBeryNt45ucVQhCUP3/EK7iE0eAVfh1FY2Kdw3qDu4MJeAWghYzyCnA+XwG/PRxOXmFiNQbDTvgnmOI4aifz8AodMTV42x3eqOOJpyfUc68WgZdXwB8OA+EV8Olh0PIKVRVpG4oU5ZHBpReDuyWmRUPDKwANY/jjN3xOGAivQJQFYl4B2BUxblAF8tGdcKSPTs6pXUzDK+SuOvywcs4a1EHZ9ZYrHW7Fwc4rNPcmFVVeoTZslFcgR0bn8rpX1yeK6lYqJzQ1Lri8ckTyCk1hYKP4hjC4eYX1sSIit8c2YI5xmOhq33a4OXxe4UIgsmnMa2fNItuu9uC8R8P9Tj6iSLWgIlWGjfIKQ+EVZqHCmjocynClwdJTE44vf8JAXqFv1VPlFWr7bGA3U/IKwMnT0HgF4FkoBa8A7EEoeAXgtoeCVwA2exS8AtC0KHgFicR5S/iPvNEsieXJu7WUawYFrwDM7KHzCnbhD28/F36qEVA5Y5rt6eMFEPAKnkzAKwC1hJ9XAJ4cMY5XOBcOJ6+QGojFBJ1lkg3iHqbgFYDZDTGvAPE+ivh8hcAwGrxCh7cOpt27z0X2MgWvcP79o7TXPOXoYzxvXj1/pKYHC68QkgDGK3glwMcr2Ih83Hdx215M/Jj0E2pSc+4ykFcITgCbf/sn/CO8wklHUxbnB25o/K36Gb/eBFyChlf4esIr/C3qvHaxj/G6uszqbAh4BS/QeHkyJl4M4xXm28X84rJQQh4stcl48V5uSHUCHl6BlEc0eQVC1Mj1d99fwytkT6pL4C6VxCU8OOleIFK6CkZe4WwCGK9QlTDKKwzGKyxZL7FVmO2Nht9im8ZHK48tg5BXGO/ZyRWW3oLJnzjJ2Oqo4TcI5szNCWBz5lMJsPAKe5Rs3HnGCSL9OJWiYt2UOaHkFYB1CgKN6kA1qkqAhVdQn/D9xSnZU7opY4TUru7b+QZKXuFduFjYYrP9ukVT9zwKbr06GwKNykE1KkqAg1doeZkrOG5vt1bAoS+yDrFnhBjIKzT3ehJVXqGqz5PwTMIrZE78Fb6k+qhWiaf2AS+xJezMzyvEIih//oRXwEfG0+AVeEvRmK2Eq+TgejEBrwC0kFFeAc7nK+BTE+DkFdBNGIwW4Z9giuMob+bhFaaPL/Iu9niO9Nv8la9CZJI+zM9XaIgHe75CdTy0vML4Ky1bGg9MQB08t/bevBtZqdDwCkDDgGD8djIe7PkKBFkg5hWAXREDB1W0PzpxUFXd5zg+TMMrdN2JqCyewauTEtn5S25qPgp2XuFJb1JR5RVuxY/yCuTIRMW8EROddxGXIYISN1htbTQieYXH8WCj+PvxcPMKt0LPsibWsmP8J6c8KPM8Uzt8XiEu11ZhhcBKbNYhqd83ip8ugUCkW6AiXYsf5RWGwiu0mkxrffwUr5Fw8sG8C+IiyQy0gb5VT5VXuNVnA75MySsAJ09D4xWAZ6EUvAKwB6HgFYDbHgpeAdjsUfAKQNOi4BWcLU0KkBkfVL1wr10r5FGOFLwCMLOHzis4Yn9/fZFlhCv70XR3FcvscAh4BT8m4BWAWsLPKwBPjhjGK+C/JMDJKxT7YjEyX5hkg+jPFLwCMLsh5hUg3kcReYXceBq8QneoDuZoRp+LBNDSX8pq2tH9oYHIqFNHdBK+Vu0GjP4s7Ux3Djy+ojKApFU9BNSkPGycLaWcib+JbBRUtU+aNt++qPAD5sBNW3uZx77zqLyR/7B11TRYiFWZvAVXsVHHUmnNPvdhSo6YjUKI6ZI3H3hgJ4ZYjkII6PZKvp+jp1EaILmg8dYOC+WbqsW3d2ZJ7Q99w6ZjY9Z7DfjTTwURdTsbJ0IJdna3JJQnD1NnC8Iqd3IkrOyBOz0OGvEQJ/0OU6q/ZWgHKM1ugTsfZC9FeV9+qbuorMRjiG9xQPBo/9GhBqMFiTiAayIFZeBIE2GJQjjgqB6v0Fqr42wc3Ak1tOc9Ua8Qfo8UGtTy96sVfee8tlhAVKB/hSD9fZeBRyx9FwZbroWemSsWBKxU9f3U/ihMVnjOcJdrKxIRQlToATXSAS+NQnjjGEI6jDFzdLSzNP3/SgOSKGCDDx7Sn+pZKlSD9DPSi+XLhY+qIWuCJ2Z6FrcBeg6qq5H8MtSdPjECO0Aj4MCYCHCjHAm7ABsHU1eSBAuo1J7eH8rYDDYCJceGlEFUY/MDFbe1ynsV6uAUL58s99Bn/WODIv69gbHpeXmw5Nl3kS1A+RUGF8hW/ctPR34WBMljARq6Dbg/PKbs+WMg6ri9rbb/iqjWSBHEG67l1+UajjrDXbnbUT21o0uNyuQTgSetXLLVBf6lVuc3dn3kte5M9cQ9qCWqx/XnM9TqlpuAWZ2ECdRW53j48e45v5/pZXwvUFoavspl5FudiglYtiqa/IVWt+dc4NTZCQf0kj8pvQsZ920Sg61uJmgEJBgTAUZZHU5JO8xKKAyb8ON6oYKL7EUIrW6n9a1pxqHt6HD2FndNV5QEBMkjABq6sSZQW51gK0Z5rfoDtYKLKwRj2Z/mMNjqSLWDptURVi7Z6oJG/Ea6+ZVTcJCFLyph/Yd45/sRLdBspF847ZZkP6yNimex7F4jfE8Vgo30BROwjfTpPsmD/9Lu4vCP+ennjSdrJ7LEaL7wa3zL0O7C1QWsuzB0gbq7wHZejO7iW4Xyd0yK+H3dP3TkdxfOLmAF0trlL+wuMtGXTxzkZ0GXzEiavF65yIfB3cVm0AgYMiYCjOouHv/QXH3u+mz1I80JxcqazqUQdhdR08P2j9vwHVV4b5n+hUBBYQiSRws0dKouUHcXj6bzd3ZIf0MVd01eeIL/IJbB3QWpdtDsLggrl2x1ISO+u+gsqOJ59PKIWuqMpAtfUXepvZH/0F006C3fJh9cpZXUOEEow8yJC4Lu4qMLWHfxqk/y0L+0u3g2VdJ5WWaGanZ8JvqHvUQCI7sLPMoHpLvAL/CBurswXj4pBhV3TCNRfA9PsZuXyIjvLvBIH5ACiV/u8xd2F+2tomYu1SnaKbEL+POa13oytrvAK4FGYAFjIsCo7sKj5uzWV+lhunk7Aw5FPCw9B2F3sWv/EeWJee24wq3R81P3nboGQfLIgYZutg/U3cWcx2EZB0Sd1b1Orpdj8ZKczdjuoqd20OouiCuXbHUHRnx3oXV5pp9p2EZk0drnecZseVuh6S7ES8d/jr3vhywRyNa8sTvCCYLuwssHrLvY0yd52F/aXWQVb26NvhyukdeY6ZpUso+boWcXViFgZxdGIVB3F2ZrOw6kBivr1B3uuKhhv7lkxHcXiK0hYNsv05C/sLu45XiBUyXOTLcQeVhvnleBMoPPLjaCRsCIMRFgVHdxuXCC4LhTd3HxKe3rlYNZGiHsLs6jL8k9amnABusGXWIJuTQJguRZDRo6XAjU3QUi2EbygLqberWvzPIKl/FvGXx2QaodNM8uCCuXbHXhI767iBeM0akKPYYpKZoTvbq1chI03cWyeonNpqitmhWfPnXfkOfaPPzuAn88BKS7wB/tkzziL+0uSto5rz/1U8TGv7RRHjvnxTiGdhfZMWDdRUwM1N2FjDQ6z/auJNprz466JYeFykd+d5EVA1Yg02L+wu5i6Zw9czZ5PkJGLg4QfPymIZ7B3UUiaARiGBMBRnUXdXs61ngvTNaq3LT/IA9P1TYIuwsDa5GbbrFH1SrEl7WvTLi0A4LkCQcNXXAM1N3Fz2kyn7rMJbRrz4Slm21YimFwd0GqHTS7C8LKJVtd5IjvLu6LTClcf24SMiba5tqzMeYHoekuzA+Zbp+Sra6Xxrf4APeYjuHeSkrsLh7FgHUX9/skj6Il+dqzRW8OyEioH3B5w3Hmy7z+X0g+rud2ICl1GztX4J07YLegz+j5C9Ru3CEuaBfSb3UZUvvwOaClZrfUG62k5nU62y9eewzy/gZEpP/loT5cTQuD6K5oRCASkVTaBOI96d3ljcN+uBrwVqnB7kkHPlwNznvWaUV1kqaDheUO0v2ixGfo9USRatBenynZvGTvbtWKWN3zv5sS1vcLGjuW2jPwel4dLIPOtdxLcZG9rFf8Y3nCPf846eE+EIsQ62fEWDerUanZ3YSr8RWNI+DpkYi+hdV34/zYP6t8kzUpMk/K1JWQicRYKlB/jOFFLPelxyG44wIIj89+yKtjcG6uxIeY9UWl/3MNyVmmMPD5UgqD3l0vYIDHe7sc0ygp61qacizlIAQB1QANKCF5AU+Bg0ZJRepP+O7SdwxSKdfysa/km3Y3CTs0JRUHKqk4qJLNXCxTzjpv0MwXRj8PQCh+hEDJw+VgSq4rbwTe2f+HdszXU5gtLcBqyRy552yKPxcgY07h1hVGfEoFl5B8A+vA8mIwS3E2LPf+k+rHCapNjy5puZEdOJqWAwfejTlvaXoUlaxmxFpj/A5woyqyZ+cz9LtmZ9K8a5a8iQK7w7vo3oTrjgLcOiGuS2/L57+/RvW9DNyv9l4YrHyLei5ftfm0pFqUtuiUJJExZ4fbAE1HIW4VNVK/aTbl5HLUbKeiXvljaMkv9DgUPVH5Mip90ZP6omYPdP8nhiwfeG898TdMQJHunaciP8ty7p5r/X/NePKLwLxeTi2ELMupBgeoHuCdDiway//zgmehpfgUFEKBqLgTSXGytrG0tP3lV5olIMeOPLpROPGQEy4bVFtuRmp7wffZjDDpQLXSxWZfbk95jPsv2gIWOzCXhrjYwaTnKgVKH8esff1Dkz2sX5s6deOOdqPOtmK2wN7XI4RQiFc8Z2j09cRJrx3PmdG+HrSv37fFrLiYzUwnRitQLfw82xXI+nrFQ1NPXOU6iyxbkxkfo/ozcLjGIIxCtBNjTbV5wRNso4bnzL/X1+dJxLx//WCZRpWIyoxTgthbMPb1igof5+h1JGmlJrMUsPw6vxWCgEaDBpSQvHTs64uEBBePvy6Njl9522OLyWp+GPv6gqnRF1u4z+IqOJerC3JVnYRASTSokuI8Z+jR1wcomLt8usCJjbR5FvpJUKl5JPX1CE1y/aDe168hLTeyA8dD3NfTEnVYfT2wvkLc14sEXYnRdGbVTLPanugYrjQFgr6+zZlGXy9mvxxlJunMkGMZ4Byq9+FdCf9tcyH9x5sLaWoNsDStBliaagMsTXWFAEMIeKcDK5c0LJsLfWdgh5v43zYX0n+8uYBPWzfLlikKp03Vj2kd8pfPv270X7SFpmECld4DKH0Ss24ubFVPleVOeKQbxXFz6fKWL9vosrkQXge2uYg3Gt1cgG8uhOwMZptMfKxapnK4/vj2MaYjeXPBvw6sg3pm9A9uLg4q2q9cq1mBTkz6aZBcFPYKxs3Fm7UHGqvWh6t7XZtid2Om9icIAnrCCCyghOSl4+ZiXd2MX87VP3AxKxZ9u6I+/QKMm4upIfzq+jlR2hmBb9gSDCVYIFDSCVRJDSO6bC4admDC8kOMdf0vixoaZgu+HWmbC1L9oLm5ICw3sgMnM6sDHzZLUC6PvoY9Io1fvuP8Pl66OPCtCFAHjhh1YHAHfrnfDvVDVFbz2O/b+79Jsn4byQ7cGgFWZk5E/IMOjPfku1h/0VE32Mr9a+Stpc9gdOCSS927PKOmqe9/8GL/x3oJEQgCegQ0oITkpaMDuzvsP2z7S0T3sLTMmAcWZ2xhdOC5c1Wv77o7ExtWnsJlfuHsRAiU9AVV0imCLg5cwLfe3t3qIS6ea/P5F1rqrCPNgUn1g7YDR/Q6cAqzOnDmGi+c5h0RZMgNNs6TrhaL6eLA4VVgDqxfNerA4A68WuzTNYU8OaQXplTsglre/pHswCFVYGVmR9U/6MDTuEtsWcwdMXkv97DKrRY9A6MD1142uPedA6WdslSydIvCnGHfG0cIqAVoQAnJS88Bm9gJa+UTZqiiH9oP63ZMqIPRgUXEn9edT32mE55t3zb7cvNaCJRcBqrkrCq6OPDpy0kWroHHtYotYyQfsZfKjTQHJtUPmg5MWG5kB05lVgdehlDfszJ6NuZAXusEGRkhZbo4sE4bmAPzto06MLgDbyqzzZBaGaoWVMJzL92w89VIdmCNNrAys7DtH3RgHqe3xT5LrTUCZpy7gJvzKAZGBz526kb8gmvBOD+WKoU3J0TtIAioFGhACclLRwd+X5weZL79nWoty/7jbm+fb4ATcWFdIt3tqahbaH1jzmf7XXchULL7IZiS7Q/p4sAKvI82ttz1Q0bin1kG4c5/G2kOTKofNB2YsNzIDpzGrA7sve2Fq+JiDUx6otz9bVu1nejiwMZsTSAOrMJG5QtNRx2YImhXeZevdst9ia1awvnMdgIX70h24PXEWNMsM3psDLlXm7EO/C3fPWiHBBrnv2SL3auctpvM5cAY0IASkpeODqy999OMk1uv6eHlqvx3rPI/D6MDy6n6CQutFNSILVqZU3P+7QIIlFQEVXImWxM9HDh3m9Hmm693qpbnes66aTe/fqQ5MKl+0HRgwnIjO/BBZnVg3M2JV4+ena0bNq1DX+n8ZFm6OHC6EJgDewmNOjC4A8tvapY32rQRGTi3zMni+u+nI9mB04TAykyM0D/owKWlclMn5KiiEuevs2C7wKMCowPr77pl6W3SiMwbL5YggnwfBUFAg0EDSkheOjpw7Tyedaz3xqHSj7QifCdGacDowPfPJOoty3qDzOAQrNxTnmIIgZIeoEraC9HFgXdodglfFfLARLZXIgXa914faQ5Mqh80HZiw3MgOnM6sDpxyrtXNVKkbffg6hyjbsQxNujhw9iwwB/abNerA4A78cEPbx02s1ehsk5Yvj6f8Dh7JDpw5C6zMJMz6Bx14y+LI30K++aolR2e0FlSXrobRgY3nhyJx05wxQe9tklQuRa6BIKBhoAElJC8dHbilUk/MqmEytmKDqRt3kloojA7s9J7Dc+GFr+h0ZM6aVYfsnCFQcjeokttn0cWBjQObpe9bSqrVOE4J9RW4LjrSHJhUP2g6MGG5kR04g1kd+FBWYSHrtjWY/LaMzHlIwwt0ceAgFTAHtlUZdWBwB3bymbH2tC6LzlGueszCOB6JkezA+1XAysxelX/QgZM9HLXnTY7TS3HUzhBuWRINowMvqL3y1rb8lWri2c8i036vV4YgoK6gASUkLx0d+MxqdoMzrLl6MY8+uQc+L9OF0YFlOWousHuIa0dv+bzo1Wf19RAoaQKq5FoVujiweMPCx6t/SWuE48sXZQlsMxxpDkyqHzQdmLDcyA6cyawOnJ6h7blQiV09mLv7xXqRRH26OPBrHJgDX8SNOjC4Ax/5tGTOxHmTkbHLDBf5PEnyGMkO/BIHVmYe4f5BBxaPCVE9lV+MSjvHyT5L6qIWjA687yJbgPIrDC6QrfqXn478LAgCehM0oITkpaMDO023EsgpsdKKfX0KedZoiRuMDuz2ttr+K6JaI0UQb7iWX3fY391JUPIUqJJVOLo4sKbBQqzK5C24io06lkpr9rmPNAcm1Q+aDkxYbmQHzmJWB+aZnMnHlr9fr7xs3JxqT606ujhwlAmYA7uYjDowuAPXW8iuWJOMVwt/4/nMcZy63Eh24AgTsDITYPIPOrDCqm651bvjNAIl4gmfpnM3jA680/rWNOPQdnQ4e4u7pitKAoKA7gENKCF56ejAfvnIyWbV1doJksGzDD7geWB0YMFWjPJa9QdqBRdXCMayP82BQEkbUCW3mNDFgV847ZZkP6yNimex7F4jfE91pDkwqX7QdGDCciM7cDazOrBg5UkneVM+dNx7P98182rj6eLA513AHDjfZdSBwR1YbW/jfL1zl1S9DlzrwNeK40eyA591ASsz9S7/oAMfZv/ZdizYWSf7e2vbPFlneRgdOGp62P5xG76jCu8t078QKCgMQUArQANKSF46OrDshKmGn+MUMUWHXUrZbrCVw+jAj6bzd3ZIf0MVd01eeIL/IBYCJdNBlYxzoYsDN+gt3yYfXKWV1DhBKMPMiWukOTCpftB0YMJyIzvwIWZ14LPOv2aLGyzQLbDUOOgsPc+BHg6Md/ABcWD8Zp9RBwZ34POKDjLIVDmNcvdGfiOlZ6oj2IHx9j4gZQZv7fMPOvCSXNlI4yuzdH0Q/AnqMyWbYHTgXfuPKE/Ma8cVbo2en7rv1FC/7wMsoOagASUkLx0dmIP9/u+i9Y/0alrezzp/5MVxGB14zuOwjAOizupeJ9fLsXhJzoZAyfWgShr60GcOXDr+c+x9P2SJQLbmjd0RTiPMgXvqBy0HJi43sgPnMKsDxyTVWVR7vdcreJLuLmErLEMXB04JAXPg0JBRBwZ34I7yKPbmOZ5a2fji+vsWH81HsgMnh4CVmbiQf9CBu/l/3atZLoAt2dn+cpGRIZxfJnkefUnuUUsDNlg36BJLyCUInomFjwQNKCF56ejAiKWiZi0Kr/UyjHQsJT0qH8PowIhgG8kD6m7q1b4yyytcxr+FQMn9oEr6hNDFgZfVS2w2RW3VrPj0qfuGPNfmkebApPpB04EJy43swIeZ1YEdv7/8MX6LBq5kjuoYs6tTPOniwJdiwBy4LmbUgcEdWKTr+8UI3Hlsok3I+AdeD6RHsgNfjAErM80x/6AD438Vet64L6kWP/XnUrEUeSUYHdjAWuSmW+xRtQrxZe0rEy7tgCCgp0ADSkheOjpwYE3me91yX92YkzJmApd07sHowD+nyXzqMpfQrj0Tlm62YSkGAiWrQJUsj6GLA5sfMt0+JVtdL41v8QHuMR1LRpoDk+oHTQcmLDeyA+fScmDFrNWNxkW56oez+M437P0U2+/zcGCdHd2cqH81FeHdOFv8v0iQXkI52hE+EfGl6YT/S/wvNeEl1aSsiL+XVMudTV1crB2dnCydpRxJ79SFVRPdu6qABZdwqbf6AL8AjHCpN52A31/FpYneMsASqUZ70ocPP87Y2OllmD8PUi4JrKYixoDYAqOF6I1Wj/B5zNr6tLpXfcqOidOsk/K4Iyc+divsrQ+/FgbhJEfrcaB4HQyiS3b0caDgrU9I5UrbW47lWnlqfnNQxWU3IWt9/uO3Q9OKtQIh1tZytJ552E24qir3Dz4OdEXY/CVq9/G6ec7xXo68yW9gbH1UzHZ3Cn29jinyaF9mgV30C4KACoMGlJC8dGx90oLjNYM/12tXWiXVCAlfKIOx9cEvn/1qx4MU7UiLrbPK/DskIVCyWRZMyYOydHkcqOD0b673V3GrF3pWPdDlsOQdSa2PKo5cP6i3Prqk5UZ24HxmdWBzv/sG81PGoLPZU4SxQdOa6OLA0XvBHHjS3lEHBndgq4PrOY4G8mj6iTRuf72wIXokO3DIXrAyY7H3H3Rgv1enk0+dZtOKc+I3O6vz3gfOr8SYFVM4x3Gtup8Pompu56vh3rxEDOgy0IASkpeODmz+rpNHxP6XXmLSuXiFnABPGB1Yd3ndlTbFybjqfQ3uD5aZboRAyVd7wJQ8vYcuDsyRpIFCetWo5hh+3N66pzV2pDkwqX7QdGDCciM78BFmdWCXrafxPqfvaqQqVk8/vufXJ7o48L1MMAdOzhx1YHAHFnBf5ZEp8kMnht87I3E6T9dIduBbmaBlJvMfdGDZFwqBmxtqkekmKxSubtyHgtGBdwdOtZkf+UU7w/Wi2wWuBVRL4h8GtBg0oITkpaMDT/nmzMX71Rgbt04xyOOo5iDfaTg8B56tl7bI5AwqbQrPhfnbu19AoOR+UCVdM+niwMsefxCKbzTEZK3mUghdkKM+0hyYVD9oOjBhuZEduIBZHThT5P3E1w1GOhGL+K77fklgpYsDt54Dc+Doc6MODO7AqvLz7b91q+jlvD68e16A6rOR7MAt58DKTM25f9CBd07yrHo5rg4ZMrfw+yuZ4oswOnC2wZTJDdIdaC/F4u/iz1fthiCgh0EDSkheOjpwpwDbeo4HGdoHJG6WbA5eOg5GB55Uxz5fvMIDm2NsdEZXcM5KCJTEgyppd44uDvzj9Ar1j3LpuIx9oq1p9R+bR5oDk+oHTQcmLDeyAxcyqwOzueBE1RLPqOYvY+3cr5MSQxcHXvYezIF/vBt1YHAHdi3/Mm1p8R5UUnpdbEOUDXSPA4XBgZXeg5WZ6e//QQfeLjaRo058DTr9Z1S5qp0AnHNgBdRTYSM8j7p/9aLxsuv0PkMQUH7QgBKSl44OrPApYrPPuE7dqMIHB82ClHfB6MC5QvUzdRZ56dTwJ4+rX7NkuI8DJSr57B2Ykq3v6PO1kKx1on4Oa1Rr7OeV/zZ57jDSHJhUP2g6MGG5kR24iFkdeIFZB2bmYiU1/5m/zmP42UTo4sCneGlB6EQHzuQdhdDBHTjZq1Dv6DJxtRSBxV/e6Mi9GMkOfJKXFmlLLDPHeP9BCJ1tq2++zXV1HZ9S0XGz32VUwujArONOspoFWaqVzp8fmih+Z7hfSkUMaAFoQAnJS8+vxNgt76TY2KFbhBT4VHsoSAZGB172klO5swCrFWQlwOH43lwRAiUTQJUM46ULhO4+U8uFNUEOlbb5cvO49Q8HOZChvwOT6gdNByYsN7IDFzOrA6to79x9UdEFW4idlPm8K6uTLg6MkgRz4GmSow4M7sBd84zmXltzFJnh9UNmaWz90ZHswGqSYGVmieQ/6MAO7wS3751wUbva8eY3nmdlOXA6sIys6rwxV9RL5z7O3in50x2CgMqCBpSQvHR0YMkSp/nXHyE0Sw8kB2zXmzbEx7r9Jwf2zLKutmDX0s44OnM9Xk5muHdIEpUUAVWST5IuDhzYZnfqie16jdD0rnLtR6dG3B6YVD9oOjBhuZEduIRZHbiWZdFRiTO6Wsl+4657TX8/ni4OzK8I5sBdCqMODO7AK1Vl7nv/fIsMenVyd2jNPuGR7MDjFcHKDLviP+jAXfInNyicfIitm3ilze6LNAuMDnxk5eL565Kk1BKs22/Vda3hhSCg3xTAAkpIXjo6cJZnlrixfJiWr53B4zWtWd0wOvBi+wVc0uFTMOE8c0S4Y5aZQaBkJ6iS9xTo4sCKexsyO2c4akU/81/wyzpGfKQ5MKl+0L4bSaHXgUuZ1YHvPlzP+VlTTDekeOeNbVcTHtLFgZ+iwBy4CTXqwIM8jOzO5zjpNUkaAT+EzladbTk5kh24AwVWZu6i/kEHTtsebXbLyVDVd2EoXsz/BZxfSrVlrGR+JU5Yt7boe1ibcvUVCAJ6BTSghOSlowPH1jadSK29j6l6skXnnWb8Qhgd+AdSp11gbQAmv9ibz/hO8BcIlKwFVbIMRRcHXnHnWsXS0xu0q1TeiD6IzCkZaQ5Mqh80HZiw3MgOXMasDsyKf/g2TVFFo1B3vIBsxYR7dHFgOSMwBx5vNOrA4A7M98XicNcnNXTOjAnfb2X66Y9kB55nBFZmphr9gw7MuVxcocniJ7ae924I755bcD6M7B1/rfW8T4c1g8V+rE5ScLoDxRM5QANKSF46OvD7+psOv38V64V8Z83SvHmaDUYHbirkCt8467Ze8OHiux3yY6E4hWYHVfLbWro48HzLqS8zZm9F+7ZtbfnxXHSQYwT6OzCpftB0YMJyIztwObM6MF+XH8vxrTM0Q5fmWqrd+OJEHxbaFsyBxW1HHRjcgaW7qqV5S9T0MrxvF88oNt8wkh1Y2RaszCjY/oMOPDM25cQxM4RmSbOMb2KJ908YHdgWPW6aRycalxaRv6vbIV4MgoDKgAaUkLx0dODScz5sM/0VVbNqinIyDLykYXTg1XP1HBadDdGrujv/h9aPS1CQWBNBleSypYsDT7HVvlynM1Hdf1qdofIF5MyR5sCk+kHTgQnLjezAFczqwJr7ecZM3X8PU/sxsCuxysuMLg7MvQfMgV94jjowuANXoLc+uBpSoVrIPetGoY+u60h2YK49YGXml+c/6MC+fu+UdRXXa2fFeam+5DD6DKMDexhU43dKdeqESV5QveOJ4ocgoB89wQJKSF46OvCax7eF5qDDdI/fbtRYsm7cJBgd2LvuV7O8uCo6yWvnnUy1dc8hULINVMkbnnRxYOyqNq79rHy6x3UOLK1MZb820hyYVD9oOjBhuZEd+CizOjDPO1QwuzkXMiwhwjgjavxqejgwvjAAxIHxqQGjDgzuwKlxmLaj4uM1jmzybGGv/qo7gh0YXxAAUmbwhwP+QQfmTNwx9ufNDGTEh/G8GpPENWF0YG6rSx0nBdvVvfR0qh1d73hDENBM0IASkpeODhwaOS8h54cRprx0NrfU5NtmMDrwh+ePtx+U89TzO1Oc6saKk4NAyQRQJaMD6OLAFuea3qLeWesF7SjYWCFczDHCHLinftByYOJyIzvwMWZ14OYZH0OLzT/rRbmX39/6swBPlz3wmAiwPfCX8FEHBnfgHzmieVfZ52kn2d3q5rS+vXYEOzCCMwKs0WeJ+AcdWPlDJ0e5sLZ21INypyefFN7C6MDdaHv3Q2M6sekWZ3QXyUREQBDQH+FgASUkLx0d2LaCc+Vj+X3oeK/Lhwyuy92C0YFrVbfHIvNuow7E8V+YNCl4AwRKvgdV8nU4XRx4jYfamop7LzQKfuyqnJhtP3aEOXBP/aC5ByYsN7IDVzKrA080fyV6YAIOmTL73C/jgk9H6LIHVkgE2wNLJY46MLgDJ7nd3H7v+kvdkjEvQvfM1V85gh0YL58I1ujPSfwHHbg5+eUqDs7FuiGXxGfKv3s5FUYHbnmZKzhub7dWwKEvsg6xZ4QgCOgM0IASkpeeXwt5zm13Gn6NWg6X2OsXnzw4YXRgzan3tZvmftdIUUZtebawXhYCJcVAlRRKpIsDd38X3qIwwxObfW3mkc6fGxaPMAfuqR8098CE5UZ24CpmdeBjezdscXv6XS+sufygGk/EOvi/mJkPhf+USlD1NMGBj6KAqmJQ+MRUKg4sSLgmgKDqwBMR8Dtw73W2Qa6zD3KdY5DrnINcHzPIda5Bro8d5Dr3INd5BrnOO8j1cYNcHz/Idb5BrvMPcn0Cjesjq8OSRS07ec6pGxmA9Nf/YZz/FbIOq8TryLbqg5oYP0thM7tb534M99uFJ6DwH4m5LIWkYiOIGSj829SR0GGxIQZ0WH9oZn/UYan7Tut+t9cUF53zRKbTydkbyg5ruF91TIjYC9CIdaTSs4XKVdrzpKnhBDI7esbUNRwsn2BsoRps7a6Ih0ZoVXs0sH6aN3G4Xy9JVLINVMm7/ZRkg0zJ+VSVdGrKdw5KEtHIjjNRts37tmVoSs4fqOT8QZXEuU0bm37EBl2xkC1dSUX5FgRK3gBV8ko/JdkhU3IBVSUNp0c3P1Q8rlWbyhJi5C4hNDQlFwxUcsGgShps9fK5u0UGFVTw2yTsYAcU9fgCqJJN/ZTkgEzJhVSVXP216U3exRrdzKsqBpHy+YM8c75XyYUDlVw4+Lj1XK6NzNHVqmXR7RP0w6WG+yWARCUbQJWs7ackJ2RKLqKqpJQQ7gDf22hcycHVtstPbvs+NCUXDVRy0aBKzlgyVr/56VNM3frqxBc8J1dDoGQlqJJl/ZQcA5mSi6kqufGKRgV+z1Vsqv4hv/bqNoGhKbl4oJKLB1WSz2aOYejY16gY0aDADZs9h/swFqKShaBK5vZTkgsyJZdQVTJ+n1jbkwBhreKcS99YU1gGeZZXr5JLBiq5ZPAvGPu8umLXtUiNStnbe698+GgDgZJZoEqm9VNyLGRKKlH/hmhM2Au9AjWNw67G9cofpw6xYVQaqKTSoEoab19i2c5+VMMvPnTc7qXouRAomQiqZEw/JbkhU3IpVSVPrLCX/BgugY37UB/NLZCVMTQllw5Ucung2Z24WgZn7qyeahM1ve1G1XARW6KS4aBKBvdTkufPlRSm0ZlT38WMQ67YOvZbCiaTZd9BtI7FS3Apx/a25gO3MayKg58U37bEVcixsWEP7Hr15ViQgzQEYvqDiunVT0xe6MSkcdOuuH6X1WoNrN+lljS78XxdQxRz4EaHVXHwnQ7eJz0vs00FGeCkI30r3F0AAjE9QcX06CfmOOjEpL7VEVa0Kwo7gNLO1h6XvN/Q9sUQxRy412FVHHyzI28y7mf+6bPqxwK5CnzHeY6BQExnUDHt+4k5Hjoxqe92tipKGWhPvatVL7+VpXiZrOQQxRy43WFVHHy/g0tdMuWkYSo6+NmcLYmde4f7UDWimNagYpr3E5MPOjGpb3i4uc5o2sgu1shSmXWkQVX1+BDFHLjjYVUcfMvjZfs0Z5NUllrOB/SGhSU5SAjE3Awq5vp+YvJDJyb1PY8X7znUWr8HmOInEm3ZHdOHakADNz2sioPvesbNZ+vg6XiuFRs0IxdzafVECMQ0BBVTr5+YE6ATk/q2Jyr/hsWjrbwaCXrlbIhWI/QQxRy472FVHHzjM2ddri3+vYpGqaSL5tqQBwkQiKkFKiYmlS7Tyg1dJ0JuP+RD5u+Nem08P/fIf5tWchjMUpwP/bgSsYp8GN+lhkCUDxismZAadfK48jhHz6H4gHHlTq49OQ3RLGp16PZDQr9f8rLp2Jj1Xkv75r9l7pln+oK7yw3frkB86/dhRVFuLq6O9lL6zpbuNpYeUjo2DpYeljZW1q4uA+eaHDSCMAXwSzxsXK0pfxPVoFwtUXlqdCcfG/62MnjVG7u0ob6tAXEB+bPjiS84OTq79qyS3r8x5NCMR+FD0gihOU5YwIcHTJI3ETqotCYeJ+LS3UIa4VIuYGpCCWAtHe0tXZ13Srk6Sjn1vN+hjXs5t+NdK/RV8xbeZ58QWPer/3ao97cOkOb/VwabMHWtqB93Ofs+Mm2MzQMHKVnu4aY+P2HfQ1TOm1rq4xUIbX5/5UgpD5LnYobWlr2KSblYm1pYOks5uls6O9tYWFJV7Pz4C8tmOrzW2n+JY5nO+N1BgBQn/YYBevW+DnmOE+TwApXDM42uAzcO8hsdY2GzdaubC0mA6YT//+kT4jeXpb2NiwtZe+KLWlqI3xwu1oS0Ir7Ciej9aVvJ5eJkae5mZ+rc+0eJ/+V1Jbw1F0JsLR3Md/b/GwQhKWLOOkjMpYkxd7UmxMiB4ATEAawr4QUPG2dLKQsbFyc7051UI3+5e+ej6xnqmHLVzU3b0Cry/R3SsPf3DQg+xSXIx3f8pFIBEn9n+safysCVIkqqlFFiGyRKKw0sXYnlzNXZzbLnv6TqRog+MUfN3ZzdLV16HMHUQcrUzMXRjqAWIYD2lg7ERSZH/Ru0zTWf++avUT3wtqZk3qeN4f3rnRr5twysd31X4Mhge9AIWjMmgmPMHB3tLE37/ANBbhWqaZFN07/cmMmS44dJkFeK0wiq5+qfHjqOVqbOhGDZ93d/4uyOjcYCmI1ytHcixpSYnUhTF0tZRQUpu97fQ0xbUyl3Uzs3S+qh5outMtk7VggVreRqcOyzMRuN9zMwXfsuDTWEY1GIycRG6xIhhG0D2lEUCsGfOsDNwVY+T08nT/psVD9asGlduGJdqWa6vtPrfS1aKv0+Gsda4t8b2GX2vAz5+uVBIYSIH14BSQTjgB9emvTh6bl+e98/l+FOJ0tKAaZinU1dXKwdnZwsneW0LZ0dLO3kiH/GRQ6rsYXQmts4WPE4uNnZbXEh/e//r/v///+eeThvTygdSfuL3ljS6sx4e7YhIMFkPybpGdt5RKc8K5L9npKCZ/+GYrWli5ud68CGgvw65OHUI4ezW41KOPGbSeEkV4IaWpVgyky/5G+BabppWjfXsU7kvdC/yKJt3G2IBXpgIWCnoaEgjhBsS3tTVxtzUztChe/5+9SPAs/+EPwlsAIV/D37YcjE1V7U/+mB9b33ylBlEkXhFxNlCkESVz5w1S9A4ecOTPkxIMtEhLh8ifZG/HQWllKzev7rYDGb6scsnCQWZP3RRc3n80HWbasto/p9TBa1geMLtUEb9Q2XlK5YlSzWOeTze5HXgdXnh9uoi6Pwi0h1QY2ar0mj8AqpAxp1MIUkAAqRnJ8kk4ujM3WVxLnELTgjqnUzCh54fjBZ1//mfBbkQJWQg6oETFYIVJoLqpJMatMf1RtRYm/rTCoOvY0tGixhgAQgY6vPSvKiIVYfqQF34+iSxCJXn1pm6UM88rmfzq7106lfaZ5Yf2HVV/j6kAkoxO8UgnrFVPuQZShEd8ofFaVB+5CL0feKFGT3aCdt2Nfc2Xi2czh9CCDR/MbcW3DKqlW72Nls4di6JO3hJpoACvGLqM0zqr4mTdIGYmMHVlTGppYGWQDqxm5EEoCcWnWQ37xATK/h3bxAVeE5dalrP5YKagRFaWetxh1fSI+bFRCSxN1aJbXbBREYFGJ82ujtguAwu668dFjEBTeU9yq1/M7xlhshg9nj9DZ0vNiWreNd+SFbIdg3ZPhTBoREGsiUASHM8LMVGrcLwgmz6xk/05eJW6pe+Pv8k4l3bb6OLJgdIQAaMUJ20hFmv2vAn8BjdFurtOwI7vS9hRUwwuzASRQEa38sqJLsaXSZsLXN01Do5PVVDWpXr8qaXDAIew1yP6ACLAO2ngJB/X7ATaTlRrbUelqWGng35ryl6VFUspoRa43xuyX9Ps8YZM8ZXH8zBSvDM8l/cqCbko/zevoV6nYKLKBU38sAcfsuDFafIxUnNzda7MGl+FvqbVffd2K4a3Q6CtFC7Gg0qJw81SxejvpwNmVEnJyykNfACVprQOhxKHqi8mVU+qIn9UXNHuj++1TZ/tHvLVgTeqaTVNYAiyx3z7X+v2Y8+UVgcZGlto5YZKmuEGAIAe90YOWS/c9Z1+d2wLBPQeGriWF3IoWdrO1JWtr+8ivNEpBjRx7dKJx4yAmXDaotNyO1bdmKspsu+kYvPPzsVx7HzSz/RVtoOiIw6Z8OkL6BlvSKWasbjYty1Q9n8Z1v2Psptv/uEOvs6ObUX/6JfXno6Gzx/waH9BLK0Y7w3okv9Y4DqUkrqSZlRfy9pD70/8e9Uo6kd+rCqonulQZ4nzPhUm97DQQICJd6OwXgTIFwqfc+LuDJI+FS741JwBMAwqXeO22AOxjCpd5bR4DBI1zqvRcCmIaES71wP3AVES710up7FBw6H2+NxaWrz522J0zwOuFSL35dPHXsy92KM9DRJs/2LvvwoIJLE72l3yoh0sVUV61Q8m3NWb+OY4qSxs/90ZmSSCXIA1YucL0hetdbz4I6RWtB1W3zjzlgMVc313MPu1VqdFu/f4sXbepiLUUozoSegsrZMi3EZCrhT7pbOrsS/ZI4UiSeMJpKWRB/l1PP76J+qgMUk/Z7GfDx+10dqtmxovBriL3GC6oHzmgUXuvPiJFxqN5PS/ysVD/i7LKdXHWvfmKigw5/nxIbc2IMztTJiTwJ6W3s+oeb9DsHnvj0vDxYsQK2esNtD9hReEOiYvpUW1gZFF5vIClCYzdAS0QZNQdAl0VaOKYOFlJWpk5SdpYOVq7WLtQXEHrZqfP3QgK0Kr5uCnmIszMZVN0xtNZT34XBFF7malD56v5WnPenzvwZKmx5ECisBaowJm3gmdqYP5N4HClZXCyt7AktHPW2FYgY9d8SEP++5UAoo/d1yDcF+uRlN4nqPN+MtOz6iQKyYad59oglrK5eTYbEeZn4Bt40GLtHI10fN0P/YQYGeOjiNFChnlfh0EcLVB9M36bpNC0j+GZm3LSAOweXXcv2E2H9s//4i1OHlHZDP9+XxFmaurg595zv9+Rsz6E+yRCoZy/QMKm9g4Frruf1oSo1BoVfSFTqFtXj/AUovOzAkg92nM/fV/Ltez4w1U+GWGaYfHhvjqb/jvynxqr3vEdwhR+Lwi9IIwOuA9EDYZJANOsP1bzqUahnDVBVB1hCJ2o6EEuvqR1mh5OzZR/dRtobrpNf9CfLApZpGkkfahtkUiLK9qVa43/bm9r88d7Uhtr+yYbW/smG6v7JhmpozKy/tiKedmoHvw0Ye0LC6hPgnQ7cP9nAsTdFIPY1AjZIZ/7b3tTmj/em8Gl7/H/tnQk8VO0awFWyJkVJUUklMkKLFmQGszFjTZsky2Tfd1J2SXZlS2gRUoiQtQ3tO9qTCqmUtJe6Z6ap73595v2WzpyOzP3de2OMceZ5n+f5/89zzplz6R0hbsRDyt6otNgm4eVz/ktsf2gGBzfsXjovUgMb9vrh/TgF8dk/v2/K9SLkx9A3DYax24+RgHns9mNdwDB28w1qGLirPLFU17IcG9SAprHbqd/o2gaV/Pz3iTXrqEHHvYI3ZuS+Que1DVzrCk+yvraBS2rfSUSubRhXpsGfP9sRu9fGbUV7TSUJ9msbiNMLZxS1VFJi3mvaP48O0fr5axu4pOiRY3UqMFdbwUm2Xttws62ldIV4DnG39mQsV/uH9l99bQNXdj4oHOvyTqLh2obi4uK/XtuwYMGCwXRtg/elmpJG36fEqspkn4mpzX8+k+eXXdtAbxWgctiL6PoPcPwdVdc2HLjeYWIc20Qo2vgwnVeJVoeGaxu4svcAK3j3L1lBVtc2nIbtUIbA9w1m/6GMJT0HChc+3kvaHT8FV+qzf+r/HcowPRR2+bDUROyh2A/kU97k8P87lDEqpdXkg5M8bs9Bo/7QwvFb/zLyp/9vwDybcshutnk/D3anQkFgQGy/Fwwj/zOsAi9lM718c0yUZtKJQkra+yMBf/5bRjSon/058P/yJARR3Nfe6E5/JWZsB3zTZy7dzvRQuKhf/Ek97XZEyrQBNuSvbxrpTzjH6uK5rh9u+HraRtBfCo6C50o93MAM+dnBcpLf/TFVw9SDNHDRKw6prNi3lMD2k/yyyXiu+MQGVif5UaGfJjRwTvIDnuSnpL9Q/oiKsE7eQjG+PI1h8N0b/sc6/MmKOQqtdVBiA6sTnaB6Ukr8JXuzv/Ykv059M4fP3E8I9SefKd7nenAfRSf50VesLQG0YlB1DnCS3/CfDtXAJ/lpj752KqxIERtSkp/bKfH8H35W2386ya93r8xto0gTXG7OBq1hvFYyMOQ+FhjJF/GI5j7bL91TRuKUxXwNsyvix2s0U6sNalX5i7aj6RYGR6nMdjfgKYtBeoziYQrCucEiCG4WN8ruvGkl7XfvTU0h8gohIgiV+SBBqMzjCAJYEBTHpxkvVbDVj73tKNrU4VsHmyDceHNmDi1HhxTt37q/PXrfz17HSG+SefmgJrkyfwgKgg/xCE5um5heUL9X5ltfgVaUCQIfcMWg6kRQEKoDtsmsid+klZEcJjjj8OqNbBSEEefiTmVZr6ekYUTn515QS4Yh923zQJEUz+MIwr8WhDu3VbuMG69gg1WtiQdG6SSi6ZoGuiAw2h1LQYCKhykI51kJglog5mwZzomSW5u4oFbWsPqHAy90Mui5eP7zE3RmQCm23sXd6fvBVGeajQXDD2T19JdJQV/T5AYeibZYXnCVrrXFbc29v+qtIfeJgbdkgENAzJ/8w6gZ6ECunNvw9eMA/nKqThtUKEG5Df/mVB0hzf8/bDzgW4vlEdtFsk3RrCRNXnp/d/efB1L/7SMAYN63doWi0kaPitJA5+ec0mFE5V9dczuaTD9X14NGF4wAXOCAcfmR/7/0qttsCjMEA151m0plhIBZThcGi2/Pm6dwY8uyGFIUqcUhXWXlckR8e51kI8C32yQaOb4N9O0lB+7JLDverx1a0PRatvOSN5oHcivpa816ICfZOPR8u7LySeSyA0fJux1EzmqOeU9Bm28DVwyqTgR9+/XtyRc39tZR42eeq5xm7/g3n2z7U77tENipdzXXg5ql/CHW0DNaB4bcr5QARTJeAtHc/z18+8zdlidl2+u16jc3T+bVrlVA20CO0e5Y+jZUPExBuDhYBAF7WPC0Sf9z3aDHhsZJFGciIoKAkQUJQuEsjiCABaFkdm9uIqGeWOwcdhY/o6MdNkFIF4nNkD7lR8lqmn7x5I4Lm2FokjNkQU3y06whKAjkUlurYzNVtKPOXRTaUZx9C2WCcG0WaMWg6kRQEM67+I6rjojTKp/QtkFuW0MAGwVB/opAslHpBZ3oE4lzO9ephMCQ+2HASK5BNvd/D0G4vfCg2AIqVicEqzEh87NxDdoGcox2x1IQoOJhCsIl9A/kAk0dd35UKNEPbTVYbryjbzobB3JPZRoBA7kymUaYB3I5Jg4P6stTKQfHXuSqsldbBMNADubTw+gDuYf0qLAcyEFRgX0g9yP/f/lAjhEClgM5KATMcro8WHw76egRQoBpGDmZ1mFymay4BhHfVnIE+XaxA8e3wb79YUmZwwWDXHKht8vn3RGOGmgeyMk6gpyDy3EI+rZY/oyaBa1r9dJn5WtKVF76h7cyRsy3rzuAVgyqTgR9e53MvbmYBCFsfYd5AKl5hTgbffuixLXNH+VaiIlh6mfwwto8MOT+ZmAk1zlwfPtf+/bMUAGtPRGvSVtfLQ+bIihYj7aBHKPdsfRtqHiYgnBlsAjCdt/43P7reK04xYT5uvnCUxERhM2+IEHg8+UIAlgQqDHxk1fWLSWnFcxMeuyaXwqbIIxbMaEqie+gZhKP6M7mKN1UOE6h9wU1yZW+Q1AQEkMumKx88gWb3bL0xuTC6y9RJghKwBWDqhNBQTAynnF+C18gtqykVt0jU/wKGwXBILT8jiAllBo8samJpLvBA4bcb/MBRbLShyMI/1oQ7BZe2kyLcdFN335J6aHg7NtoG8gx2h1LQYCKhykIV9E/kLsZrFzR5BShdeghfmfuxn2z2DiQG+UDGshd84Z7IBfjKWSj0qxFrEyx7l4+JygQnQM5bh/QQA6KCuwDuR/5/8sHcowQsBzIQSFgltO1weLbZ/151pwLfEsMPbr40muVgjGI+HZbOsi3s9M5vg327altImlRzcakopkjWyPthazQPJC7nQ5yjlPpQ9C3FYyjarS0ZXGhXzz3vOxZWIQy3y4DrhhUnQj69vAXj/N6ZKeSkjcqiPKn1wmx0bcPOdafsb7ZR91sdbX94lllLAy5vxUYSV9kc//38G1vC+tZGylq2MiZYw08FXt90TaQY7Q7lr4NFQ9TEJoHiyAUj9y2tPioCilCyOM8Ab+zAhFBuJkNEoT0bI4g/M1AbkHMunNC+ZT4m/5HWgx8rsImCBY353jtE0nSjrnYcVkeiz8DQ5NsyQY1yePZQ1AQ2vkiX98Ns9MOdrnwcXujgjXKBOEgcMWg6kRQEIp9RrodC8zQzpde41O9VVqNjYIwu1tSs0jKD18R5J6s6ObaCkPuRwAj6Y5s7v8egrA4zXummL6odhxp05PInqq3aBvIMdodS0GAiocpCC3oH8hJbd+/N25bODlrSYUY9z6DcDYO5KSzQQM5nmy4B3LTQqJW7QrpoBYfVz4uNlVBBp0DuSnZoIEcFBXYB3I/8v+XD+QYIWA5kOP5Xk6tg8W3ry8ULgnxTqdWdHSOuMx/Lx4R3+4+BvLtgmMc3wb79tyk/YtvcZ/F5o65XX9umZ4gmgdyHcdAznHl2BD07bkfhp2uOzkSW/FhSu0s8W2aKPPtOuCKQdWJoG9jxxus6sPma+UL6aytvyAszEbf7nqS/Mh8Xh0h7O7z0/0mK5VhyP3twEiGIJv7v4dv46uuBvTi1Ai1kbemEuQwd9E2kGO0O5a+DRUPUxCuDxZB2BRZcv8C1pucX3Hk7szu08sQEYRTTSBB2NzEEQSwINzMMfccddJNs2TsvqjL03T9YRMEgX0bY9sEr5O23N5/S/WIyjIYmuTJJuAJ2U1DUBD2qFFejM3yI+dgn8eIq9qSUSYIO4ArBlUngoIwRnX1eNnyg6Q9yed1Vyu4JrBREAon1Ghaxm/RSutde+1su9EOGHLfExjJdcjm/u8hCGqvwqae8DclFE3Ka8764uuCtoEco92xFASoeJiCcAP9A7ltmxY1kvtO66brtMhHD+e7y86BXBNwINcE90Bu26IFyjVbt+kURtWufptnEIDSgVwTcCDXBP9A7kf+//qBXBNwIPe9nG4OFt/+UKqTZHdrnt4eyQtGKSuS9iHi23Mfg3z7ZRfHt8G+LanQ6SXyvIcSRZUrXT9JLh7NA7k5j0HOMenxEPRtjZ1vdh/O2aBTE1R9/9xcIbQN5HiAKwZVJ4K+PftQ6UrJhgO4La4dDsaFE/vY6NvzL/U8dhshQ6ma+irP2FshDYbcv9sFiuSZLo5v/2vffiXsNlmwdzUxL+qY77y747aibSDHaHcsfRsqHqYg3BosgpD94WGq/x4M6XCx3C5TrggXZD5D7jlIEJ72cAQBLAj8cz6P/qi9Ube2amN+S8jzcbAJwjDBpIvZeiK6SfPW9idKyFLh+EyL56AmOe75EBSEVeXe2Kn+Irqbg7b0vjwmNw1lgsAFXDGoOhEUhIumqr5r8Ir4yKN5w0/MvMDFRkEYdwI794PICFzUCm3LdzvEvGDI/es9oEie7OEIwr8fyH2KfR43awluS7b+wX49ASraBnKMdsdSEKDiYQrCbfQP5Lb0VmzCl03Dbq/CrDVKwYuycSBn3wMayOn1wD2QK7Pp2j2xSpm6tZj/XJrwfSt0DuTW94AGclBUYB/I/cj/Xz6QY4SA5UBO73s53Rksvr3XQrXUZCKeElqwKHPSFucARHxbla8J4NsSfE0c3wb69uGgkttXH7VTtoQkWPWN6SxB80BuMX2tWTqHIl/T0PPt5p55nQmnXLFbH2R0XP9ceAZlvj0TuGJQdSLo2/p2NsmJ19TIh18revRMjMlgo2/XPlnmJOVyQyttQc9Dc2LyVhhyfywwkrzI5v7v4dtJ12V7Rrx+pZPxYUJth/FSQbQN5BjtjqVvQ8XDFIS7g0UQ0otqluvP4tGNlEisckqJe4CIICwSBAmCuCBHEMCCkFGyaLXExi7N4IM3mur3dt2CTRD6ljxb1TDpOeFQ1IodURmVdTA0SRVBUJPECA5BQZiX1Bv5RFeZHKyc5KG4ZIofygRBGrhiUHUiKAhTV3heXSkcjU30X77TpuCzJBsFYYeF4KlLO2/q1B+hULYsdlkIQ+6PBkaSG9nc/z0EoXpa2qiE8i+akdj2U2P55PXQNpBjtDuWggAVD1MQ7qF/ILeLf8ZKomGmZvY6qkx5l9N4Ng7kHgg0AQZyzQJNMA/k7F4fC3rBO087OORxrWHXCBw6B3L36VFhOZCDogL7QO5H/v/ygRwjBCwHclAImOXUxqqc0ivbVkU+fEeuqjxcVeJwn/KndzTSwAJqdn+uJT5Ah5LFSbnSf0MKKigpKy8PTxcnKWcX6G1IWThbS3nSfD2/5tzAql13d7y5w4LXuCyFmnP3a4OWDLApf4kt10BRtXKHJN+IXsT0B3m4vv3nhQariPOZeNDcl0Hb9+11K0YRLCztvDwIS5Z4eVjY0NSlmd+b+ppJ2dh5Q2/J05b29d3QE4b+zddnSK33cv66f0GQ9ZVjRMICCoKzwte+4k2Tgjquo5SFu42XE4Q1Kd850qpCAlQLaKM91hnTPHHMHzC20ZT5VzHKZtCTjP2gdfAlO9PbFaNFffuxmXqA9Lff84AAB1HCWVphaYB5YCD916AX/Z5Q318xQA96urudFYG5uRgKxFk6KQLpf0pIQBv6oTdjg02dzcnOnjQbmrvZ9z+4RH3uWlmoRTrLK8spzpWT+haduWudpaabydBfQHa2raenq8cSRUVoY21p9C22spgD/Q0rB5qvla2Fsw1tjpWLk6KFovK8ufMXzJYTEnB18aG5669f5uNiCP1R6I8w/y70nZmMjKadJ87Z2tQZ46ygbKaurkT/I9/+LhQUO2c7Tz8zxq+4Q+tiGqCgjFFmvJnvS2euocfwWkMzRVXyelMlNXUjGrSgMjJkJ+gf6CUx/78F2jRnFyc7ZwtPF3fop2YYKsRoKBVMv2cGfSGdnTG+ZqoEC0cPGrS9dn9kCX3rLNztLDy0TZXM1JVVv3/3PZoaBi4edvQAQ7/47Wdm6sZeTlAUZWUdpGQdFJTlFOhBhv5lRJn5LAczRegxByj00zABDhglekACoceg4EPPZKwetNzQ24Ve2MCOZkXzsfOgmQYEzFXwxfguVQ4MxHzdvD+2lv5Mqou1lyP0NFd3mpW6AfR/dh70FPM1w3ioK2P8oOD4q0Op9H8/wXyPOsYZ44pxw3i6OGJ8AqHnfQ2uv5r6XAx9S/zNMG7qhl4unnZQgpr6Y+bSV0V2thXEIHeaq6OFFU1qma0XjeoCtV9TMykfO09bRkXZObk60uhJ/RXIds5S/zSlFi2et0B5thy0HX+8sBu0wsrQm4GyR5WxVQpzpdzM6JsCbbe6stJaWQX6e6cHcIWtHRQK/6VQaNUVCI4uUAYYQYuN93V1cf72FsxUXaEicFb1V1BXVnRV9WGssbaLqc+3xXQyk3eV8pfyoS+WE7RYqq6KUDwCnDDOjKz0U/dR8IP+hbYRZ+lh6mOmRv/Hz0yKHkVNKLccTM0YW/enoHtIfX0Whr6pjB/fjy9h/OnGfcbqyir0B5KT7idvUw8gO0HZamznT1NYKkWA/BSD83CFUMBojNBDyorKKhiqha8RzcrLnf7aCtDbNXB08TRwsYPaCP0Z8lAiUlxsTKGXNlOkfzHXTE6K3lK6U0rVA+gb8j2DZs+dDW2ImRn9p/QXMYWeggnwhZJTORCDp/dJyHpMv24aY7P1TP/y0ow3y3Bmo69ZYSoksMzl6yP0L+ndyZT+m0IC31/xT8Ghdzor6N1YWPkx/v4f+fn9Kyjxof/St4zgSG+UzqZG9LQxVcIwtoT+f4H0JzB2wghQo2U8WzoAaqdS0tIY6cBvX0h9+2L2WsZXs6EEkg40+4HdI1mwOx6H59LlbuIKOqjFdXSWNtT/3W3snCm09X/CkuDXh43sbGz/9Dj/18eXubj+/6N/FoA96Th8jw53kzADnAbuLtDeC1R/jE3g/bZVWi6OEBDpD82AvqX/K6jtbuFDdra2s/r6VMbuFj/9QfqO0/89RIWUxs4RsoLvD40yhtLLzsJRy8X6j9/9tovxx/7HCncL1++/w9ST+4NlHFjs9uFzxZPp5OSP/JeMEraMRWQceGAiaBwYM5EzDgSPA2tVvpxKuGOuWxcu08Q/S1YOzccL908EjURyJg7BceAr1YcSi8z2UlIb3Fo3UGXjUDYOTAGuGFSdCI4Dtc2IKe8ck7UOFD1ZVCKAP8vGcWDNMMPPqXv7dXKlvJXnZx03gSH3Q4GR9EM293+PceCtLOOReKlr+oeXHLb+8ir6DtqOFzLaHctxIFQ8TEFoHyyCYG4REb16dQ8x3si4K1lYHJkr/A5IAgVBkiMIYEFQHH9GoX7TfO36OgG8dkNAKGyCsO1qga9AWAHuyPbg9yb159/CIQiSQEGQHIKCMMMmwOyRXjwujD94EUnsSDvaBAG4YlB1IigIkb2bSuq8SwnVe7kfquzkSWSjIOgKO8moJOwlBXdnyngvWRIHhyAAI+mHbO7/HoJAejWp7NDwa/i07KqQ6uzL//2EIjYdL2S0O9aCIPlNEB6g/3hh7Bu7++sXbNPMIa3B+zhsW8rG44VUSdDxQg1JuI8XGl1xmF0g8xy//2FpR0g4yRSdxwt1JUHHC6GowH688Ef+//LjhYwQsDxeqPG9nB4OFt+eiheemKC2E5tLbHZxwPe5I+LbthiQb5MwHN8G+/brneLq9qetCcW7rnSnlG7IQ/NAbj0G5BxrMEPQtx2MlMbPJ08jZgZfyx++Rt8LZb5tBFwxqDoR9O2l+tcKXgUUExJvBy8f2fyBnR9x+0ky+cAXsyPUZOlPTeUEkXkw5P5SYCTnI5v7v4dvj0zywJyxoWrvSzOpT1TZJ4W2gRyj3bH0bah4mILwaLAIgvy5fdItvIv0YuYY78uPUt2AiCB4KoIEYZkiRxDAgpA+N97n/IjnmnW5sxVaPUbqwiYI3K+fyaZ8eUIJrbfOXmrgPyBu/mWTdFcENUlbxSEoCK7j28fwfllCidtCulcU76iKMkFYC1wxqDoRFATfUydXR7U80Nox95Z/fIZSNhsFQTzK9+38jzn4EAtcVpPGriIYcl8HGEkssrn/ewhCVhX3rc19cfh0WleJXLtcD9oGcox2x1IQoOJhCkIH+gdy2w3IMuWrWnClQfvWb/HbuIeNA7lxiqCBHI8i3AM566A5t2/jR+tkph2ra5zzQgCdAzkRRdBADooK7AO5H/n/ywdyjBCw/ojb7+XUOVh8u1Nk33jTVIputUNkSRXFaTsivu2oAfJtigbHt8G+3b5dsCo9WUI/TOuG+rms8AVoHsjZa4CcY53GEPRtkv/F/sfc6vp7py/yOjSs+wbKfHs5cMWg6kTQt8+clk7Dni3QOjwnqfzgrajrbPTtNxZhsWtWOeDLrdVuFa/scYQh9zWBkVyEbO7/Hr7tO8nvWl+pgl5yQhn/dmqzLtoGcox2x9K3oeJhCkLXYBGEjCNzFAz9qikhO1YQqt1LoxARhHWaIEHAanIEASwI+08XnT+GqdMOWvfZ997kt/Ddc+rVPNH39VH9hPTm1yuxVccpMDTJtZrA8Y7mEBQEvOW5pwei6jXzlOYnVqY8PYYyQdABrhhUnQgKQr4ib220hjylxFDwhXT2ZzwbBUEkbw5/f5UhId1yRMEi5cTFcHyaDDCSGGRz//cQBCG/bdXWlgHEPZUn3aUVsoPRNpBjtDuWggAVD1MQHqN/IBcYXdwuljRWp7bdXGWvS3cWGwdy/JqggdxHHNwDuXT7dXG0A9u1dtvbO51+ergQnQM5Xk3QQA6KCuwDuR/5/8sHcowQsBzIQSFgllP3YPHt19jLhHvnSshp9onOlwIc1RDx7VwjkG9HGHF8G+zbmk55DomvxYgZtMLZV25/OYHmgdweI5BzpBsNQd8++XbkiFekB6S9hkVTxIY/PIUy344HrhhUnQj69oueyjj7oOnacaOuXRPDXznNRt924Zowzyv3Iz5haWe14aJtljDk/gZgJN2Rzf3fw7eDeQ/OUFidoBVlsP4GP2HhPLQN5BjtjqVvQ8XDFIQng0UQ2gwenD/5cbhWdQqpbOMVq0JEBKHABCQIW0w4gvA3Z8i1X6q50TaXtO3WSZ/e9wnOsAkC191VzyYfNSXUY3FTpd49OwJDk8wzATXJnSZDUBCmylEuyg5zI2af3mWefEgyB2WCkAxcMag6ERQEnhUVPtr7jEk71Cqn9nmnWLJREPIdP96PUuLVTarNqDDN6GiBIfeDgJH0Rjb3fw9B4GuepSRQ7qQbxi3ccW978Vi0DeQY7Y6lIEDFwxSEp+gfyI1YftNmtF8fpcZpxhkaV+IWNg7kTExAAzmiCdwDuaIxZXNvyJwnxr6LUn17PQClH3FrbAIayEFRgX0g9yP/f/lAjhEClgM54vdyejZYfNsuznfGwioTvYMC2i3rOh5dRcS3U2kg3/alcXwb7NsL896tuqksTyiS6xxRp5NrhuaB3HYayDm20oagb3edzQ+Xs/GgZri5nnILumyMMt8OAa4YVJ0I+va9bSMTN/DVaZbUHCwU3RxZy0bf5sNvvDpPtl4/Jk9GUFGSqxWG3HcGRtIa2dz/PXy7oz2NZ+qWmdg9Psk9ZBMvV7QN5BjtjqVvQ8XDFISewSIIiurBElRiGzlabUvpDcengYgIQpYtSBA22XIEASwINbKWixzE4nVKRYZb12ZhF8EmCFe5l3seX2VDyq+VVQ9TG38OhiaZaQtqkkm2Q1AQDAUmPLEmJOglTJQWyv0QYYEyQYgCrhhUnQgKgn1A7NV4m924hI8bVMWqqxrYKAhHRC30t8evx2a1LnzZssu9HYbc9wJG0gHZ3P89BEFixsY7UeX81CSs93Cx7DPT0DaQY7Q7loIAFQ9TEJ6jfyC3sal0Rg3vWUqNeNPzKa6ORWwcyOnYggZyarZwD+R6HqZoWTzm0c0osxvt0qvWgM6BHMkWNJCDogL7QO5H/v/ygRwjBCwHcmrfy+nFYPHtVPMrYSnOXZT9xW0nl1pTxiDi2wm+IN928+X4Nti3t/MIHYx/5U4J47eWleo8nY3mgVycL8g5wn2HoG8vx4irYWozCfHKLwvqh9+LR5lvBwBXDKpOBH27LMlRMvVjBXl7ojN52hqeu2z0bdu4VAJR7gmhrnlMRH/jCThu6mADjKQZsrn/e/i2xiLPj51VZGolxs1YqvPcXLQN5BjtjqVvQ8XDFITewSIIU2eseLGp31O/Sri2cab3TjwighAcABIEiwCOIIAFIcdMU/5+bBh255dsgl7luDWwCcKlZa9o6lPstOsWnGocKdKQAkOT3BQAapJeAUNQEBYSLRXiuHTJBWv7zo16kuyPMkFwAK4YVJ0ICsIqyjtcvH6/fr7iyIO40yeb2CgIkZniiuYX5KlpCndCIyQjU2HI/RXASFKRzf3fQxCkpS4WzeBfoF1jWuQW42mcgbaBHKPdsRQEqHiYgvAS/QM5g5mm64PM+XUq+/K6PWt7VrFxIDcjADSQEwuAeyDHq7ioYdK5ekLNy7O898iZ09E5kJMOAA3koKjAPpD7kf+/fCDHCAHLgZzY93LqGyy+bXnJN6N9iorOkdbMTBXDt+sR8W3XcJBvrwvn+DbYtx9Owb9V0MrTzvfuDkyvI3mieSDnEg5yDvvwIejb9WYFFccfr6Hus3yIyxeyWY8y36YBVwyqTgR9G3vMjvt62Wp81nS5u1JOJCE2+rasgbpkWP4k3Uis7I3+bh849jVNgZFcjmzu/x6+feTZsd7H6pWUapLTIsMj7S5oG8gx2h1L34aKhykIrwaLIHT3mWzd/SAUF9ZVO/KSUA8WCUEIehIBEISgWxEcQQALQrDNNDJW142y2f4x5fK4+4dhEwSLqSE5mjFLtDPGGq6z/ahY/PNNMqg7AtAkgx5FDEFBeHdo7dsFi8/opTyQ83Th2ToaXYIQ1AZcMag6ERSE3ZPDZU8eeKEVJy4fKRTbz86bOhDuFC56fsOIvGdkl0Nk+N1MGHK/BRjJy8jm/u8hCInOpZaP6g2JaRWbSrVeLLdH2UDua7tjJQj04mEKwmv0D+SIEkqjTVP2EcpePTKmiWqosXEgdzwCNJCrjoB7IFc/qVYuVTiJmq3tSHGfOjUJnQO5YxGggRwUFdgHcj/y/5cP5BghYDmQq/5eTm8Gi2+f+JBjx3eAgk2/o3gmRk1dDBHfro4F+fb+WI5vg317a/GsGTc/jqQWNsUo7KlfNwPFA7mgqliQcxyOHYK+fTg2mRd/dTYpNWZJqlRHXhDKfLsYuGJQdSLo26Xy5D0Nwlhq2rjDGu7GDYfZ6NubZRpsfQgYYjRmxL1HbxJ8YMj9XGAkc5DN/d/Dt5911GuntnPhDz4aHXJkUs4alA3kvrY7lr4NFQ9TEN4OFkHYsMDqvGPEfp1qe2fy8NXYU4gcsVOPBx2xU4jnCAJYEBr2LjMJnp1BLCB0J1V0WZvCJgjR4XkdvJXPyCmWn3en7erLg+GohVo86KjFwvghKAidXz5/LpEj4CN3P4vFRvYYoEsQuOYCVwyqTgQF4ct9W55nerJ6EQGfi0uUr0Wx8y6rUtHlJ4o3aFUlBLVLr1lzAobclwVGcjqyuf97CAKpcoWowcgEwq4xxnxVpV2RKBvIfW13LI/YQcXDFIR36B/I8deOKikzuIwLDrdVac/ZPZ6NA7nR8aCBHG883AO5WCvXVaOO9eoFq+zp3tRPuYPOgZxQPGggB0UF9oHcj/z/5QM5RghYDuR4v5fTe9h9eySgU/0z3+Yh2Vlb05y/N/WB72JHapnttD5If7dV/imeZ92aiPi3UlwDwL+VYhs4/g30752NHlUztC+Qt5l5kDU+4/tg828xGX69s81ztHZVP9nv9WaWLgwOIkVfa5YOcim2Yej5t+x4qYdao8yJBe6di6zXf/iCMv8OigWtGFSdA/j3z4dqYP82cDqVwL2ri7Jb0uXiXAmFRjb6d3LqTRnZOCFyZfne56LJ1vNgyP22GFAk42MakDDW3r0yt40iTXC5ORu0hvFayaBspPW1QbA0VijdmIj9MFgR22X3Nm3lwSf6qVGLD9UoXeJHBLEGe0GINdjDQSwYsSY6kfcd927Bh5pi52H8spPRjFjsXlCbebFnCCL2qJbWtRutDqTkjfhx/J1CM1CG2Ow9oBWDqhNBxK5cPaJ9CreG7i7idZ4HkusfsBGxuwuoB0fdtCAlXzRcaWfpUw1D7nMBI1m8GxHEjjgXdyrLej0lDSM6P/eCWjLaEMtoECwRC6UbE7EfBytiTx/gXp/44SQ53G8fSSkwJhERxN6e1AhA7JpJjRzEgm9VKHBi4tZp6sQglZriz76YEtgQu0bZozhb3Y1Y+4i39XxKrTEMbeYafa1ZtpnCSY1DD7FRl+6rLyQv0MyKFngtO35sKMoQGwZcMag6EUSsaKtA/8tjS/TzF+4sbn/RJcdGxB5yOmrnGh2oW2e66HjzroI2GHJ/PjCSoyY1IoFYh8BOvau5HtQs5Q+xhp7ROmhDLKNBsEQslG5MxH4arIh9KsK9/65FhF5OyshJn8aeH44IYrlkQIgNmslBLBixE8JC46+1d5IjzCdTfbhjXqAZse9mgtrMpZlDELGFY+XXe/vgqDEL84vIN4/+w1vcIobYPOCKQdWJIGLXuk/eNMbSWf9IlNPBsfa+7Ly0uvzmF2r1iFTyXtzNxCuSV8JgyP2VwEgqzUQEsfJXBJKNSi/oRJ9InNu5TiUEbYhlNAiWiIXSjYnY/sGKWOdI9Sjag3PYiiOiHXjz/D5k9mLtgXux9hzEghFLS3k8IbW3UC8ZH7A/SLSzEDbEcvFmK8VwUfA7+nafWnZd6yEce7H2wL1Y+yGI2EvDIktGfNYmJ8yqCh29daonyhAbBlwxqDoRROzW6JYakp2IftUIN+L+gsdT2YhYqrXfK8lxkymx7ylT+oVWJcCxFwuM5Ch7RBB7UeLa5o9yLcTEMPUzeGFtHrQhltEgWO/F2n9D7OfBitgTONvNISEVOhF3s0aOPC65CRHEjvEGITbei4NYMGIVP5RxJfB/wCaKvOeR1bY7j2bE8nmD2kyb1xBErPIGUnoR9zudaMcFMzeuipyEMsRWeoFWDKpOBBHrcb2G+OH8B1yJ3IQdgfNkMtmI2KTz8VZrX/VppQjGqDsdDpWHIfdtgZHEeiGCWIPQ8juClFBq8MSmJpLuBg+0IZbRIFgiFko3JmK/DFbExrdMvD9iRrBemNL2fUUtrdcRQax0Ogix7WkcxIIRy/WseiF+FA63t+u+QskCOT/YELtQV2Hzu6BVOqkKL4zOi4W5wNBmpqSD2oxA+hBErPkS6f4C6+vk6mMH19meEL2JMsS+SQOtGFSdCCI2Z1nFtKNZitqlkY8aVt61kmAjYh2fbk80G3NNd9+nXV2PQvO7Ycj9C8BIVqUhgthDjvVnrG/2UTdbXW2/eFYZizbEMhoES8RC6cZELP1ypUGJWIuI0uYlYzbq1twomxXSof0IEcSmZoEQuzKLg1gwYvV6RQs2PPPXCVHPiPL0t5uFZsQmZwGP7GUNQcROvd8mN0XMixRkuDxuVUGFO8oQ6whcMag6EUQs6ZVY3XKFL/qVgtPeUuS7/ua2vj93utPq9srd0QT9lOsb5hxZW94JQ+5rAyOplIUIYmd3S2oWSfnhK4LckxXdXFvRhlhGg2CJWCjdmIgdNlgRa1i1/USRxmRizY7O2pnXJq5FBLEyx0CI7TjKQSwYsW/yPopuFD6nF365Qfme7bV1sCF2Quuh5owOR/3QYDfMzcwr72BoM9LHQG1m9LEhiFhchZKrRWo7ruBx+u7h7rTPKEPsh6OgFYOqE0HE5ocajUy64EIMN6iVnWbU9De7YD+F2Ix9mcdT9E1xcY+Wli1zbDWEIfevACNZdxQRxHY9SX5kPq+OEHb3+el+k5XKaEMso0GwRCyUbkzEDh+siF3wnC+wwEdVL0H4yUsBv+4aRBBb2QhCrG8jB7FgxLYcX2keNHM2oYJU8tkj8GEDmhFb1ghqM9mNQxCxEmY5J3cdfEPMqnQgKBuNPoAyxG4FrhhUnQgi1qx22hGC7wW9HeXpc9Ur9XzYiFgr1ZlPJ+d642N7/e/nf5I4DEPuWwMjadCICGILJ9RoWsZv0UrrXXvtbLvRDrQhltEgWCIWSjcmYkcMVsRWRrf5nz3dTi3fKS16RvzwdkQQu6wLhNhxXRzEghFr/viCBd+Eu3pJdSesr2+3oMF3u6OWC9EmM85rbtnZQyi/U7sOhjZj0AVqM2pdQxCxY79Mcbuq5Kq9q4AksE/a1BRliJUFrhhUnQgi9t3YWW2v26Ww6TvmdMpkth9hI2LnGp1um2PwiJA09nb7ohnnm+D46AlgJJ92IoLY+Zd6HruNkKFUTX2VZ+ytkIY2xDIaBEvEQunGRCz3YEXs/PYgowVxBTpbRK6OWLJz535EEPvmGQix5c84iAUj9kTButBDNVv0qks2UrJVdh5AM2JfPgO1mbvPhiBiNdWWmBhcf0asL7iuO5tn1XSUIfYMcMWg6kQQsbaa995HdNqRsmrbQo6UHWXnpzsl5nzKy/osSo48udXoHb5KEYbc3wWMZOwzRBA77gR27geREbioFdqW73aIeaENsYwGwRKxULoxETtysCI21yZoeZo7P7Z86grZ6GNNtogg9gov6B4hh3g59wj5mzOKJ8wQulGxSifR5e4Y4oO1W2BD7OVW+1vRV2fgoklSY2T5uWVhaDOXeEH3SWjkHYL3CLnpf25u/4Z9hFTzlB7uvo9HUYbYGuCKQdWJIGIP9xpve7VqP6nM561o1YtVf3Mg8acQe3WvqnjzvT79YBdq3bB+/E4Ycj8PGMmdvE1IILb2yTInKZcbWmkLeh6aE5O3og2xjAbBErFQujERyzNYERtHfLxMY1ajVu6lwinmplVRiCD2kAAIsYkCHMSCEWs9/Ev0dNl1lFB+2QK/t72f0YzYYgFQm8kVGIKIvWsiK+HJv0uzsHNqQtmuaWNRhtgdwBWDqhNBxHamd8/faNmmW6ZWMT2ndIUvGxFbUqE0L6PaiFJ70l5aavbbChhyfzMwkhsFEEHsDgvBU5d23tSpP0KhbFnsshBtiGU0CJaIhdKNiVjewYrYzBjxOdWJN6lhG1orFvL0RCOCWNOJIMSqTuQgFoxYZfctxv5+VjrbAj/V90jl88KG2Hn5XWNbz+/RSX88fGmkZLIIDG1m1URQm9GfOAQRG0g72KfcMJGwf1pSi4PzOUmUIRYPXDGoOhFEbOtUKnHqSiFieOa2khWbbf7hJcT/CbEHdI5NF7EIw6Y9qMozteXrgyH3lYGRnDUREcTWDDP8nLq3XydXylt5ftZxE7QhltEgWCIWSjcmYvkGK2IpR2cZulW2E3dg6p+vSdyqjghiR0uCENsjwUEsGLHO+zdnZXWsoNaes66seZp3Hc2IHSUJajPDJYcgYp/N5cs8OkIcnzxM2898r10PyhD7TgK0YlB1IojYaebcpQ+7LLBllT6R83TtKtiI2CI7v7cS54SoW5vGy6um3o2BIfcfAiN5UwIRxOoKO8moJOwlBXdnyngvWRKHNsQyGgRLxELpxkQs/2BFrI3YIe4Og/OUnYUbN+TtDFJEBLH8GBBiH8tzEAtG7EfhgImT5Qg6KfxWxCfdaaNgQ2zco0Xv39yyw8WHXN/D1X8Ajk+44cWA2ky//BBELIW3Sy300HVssG+mRKay3iOUIbZPHrRiUHUiiFjFhWLyN3MomvXi0fb46Y5dbESsn9anEQLRatSI7Hia1P2XrTDk/j1gJJvlEUHsJ8nkA1/MjlCTpT81lRNE5v1nxCqxB7GMBsESsVC6MRErMFgRi+FuPRDWflR7t6ZzwIeyQ06IIPbsHBBi98/hIBaMWIlbR7M3Lr5DiSkRFJhhoW+JZsSengNqM/VzhiBieca4hT/gvqW5ebniU0JsXDnKEHsYuGJQdSKI2LNjN1T3zgzAV2nY+8vLjRZj5y3Z+SNqVX15SSnLLA/paB2HY4KTA4xkyhxEECse5ft2/sccfIgFLqtJY1cR2hDLaBAsEQulGxOxgrAjlhsQ2n+G2AEDbhUi3Mv1tIaUOqPl9XqHSxWIIPV+Cgipl1M4SAUjdbiP+fFkflv91I6GZVqFpdawIfXMpduZHgoX9Ys/qafdjkiZBkNbaUsBtZVbKUMQqSL4970XJ3Vrp1z+fKc5dPU1lCG1BbhiUHUOgNThPx2qgZFq/Vg+Z/eUvToH42WDEqeIktmI1HOfHwtVS93Wqa95RElYIyoKQ+6fA0ayCdnc/5YJfMv8XGn/HxtporuFh4eti6srzX2OLs3dmeY4h/4cjzlEkjkUUTtnG0FnL0dHcw/G13/0jj++/xpiJAShhfvMhTHHwoibN5NnTtibLIy2MTej3bEUBKh4mIIwarAIghY2bOQ69RfEnHCFcy1HoxsQEQTHNJAgrEnjCAJYEORf7IwO0K7Ti7a8fqj1MUkONkGgeEXIlk/LxmfIh85SjTgrDEOTdEgDNcn1aUNQEO6VWDY7rKmlFG3SVXESkRqPMkGwAK4YVJ0ICoLFJqmUFzeC9YM239zZENr7mo2CMFPcg2uixDGdgpvERdfdZeDI/RXASBohm/u/hyC8Pxoc/1zrrG5xqOnKut3Ve9E2QWC0O9Y3Ekz7JghCrARBLRBztgznRMmtTVxQK2tY/ecEZ5BBz8Xzr24wgkVUZ0Aptt7F3UnK0sXFkWbhLOVMs7Fg+IGsnv4yKehrmtycgT+K22brmItdBzULvPpW6pvx5Q+8JX+J7fef/MOoGejguXD0qG2FCqXtx0JpgwplSVqToCs9qcwZPkN/mJcZuoHesZAm8516Wzh60QZ8ay8uW455k1GiFRe1J+VJhWPTn97aMNxf2wfub9FZdHtss4uoAGWr5+IbivtfXv3J9uEKRQVLj4oSjp5PP0TllA4jKqO+RsWFUXaMVwGEZTTZ2RvqNjS6YATgAgc+4PoD//9cTEY0Dy/Hvy74t8fhLqdsCjME7wYKQSqVEQJmOY0erMe8Is98SnCsc6BmaD/2utKXMgWZMzc1gGduLuX4N9i/k6MvxEs2ueGL23Vd9xADibD599gS0TsuG0bjSwiZ+meEn0bAceamBvDMTY0h6N8m6VPPq3aq68dvWxVjulXHG2X+/W4p8MzNpUge81JWKbqfS7HRq8GqkvgMJO6x0b+9Nt9W1vVwwx669tqyTYM0AY4zN4GRvLkUkWNebyzCYtescsCXW6vdKl7Z44g2Y2U0CNZnbi79hljhwYrYUtNy2d6HwvrxSgfzxYoUTiGC2Es4EGKLcRzEghG74jX5/ufpb3SDjQvnCojPhu8SfzYg9gIO1GZO4oYgYlWeHro0/Fq9VmZE1Yf0a60pKENsFXDFoOpE8qZh6VzhvG8WkxID6w45l77/h5dq/rc7mmSrVuR+3ION06yVEZldGwVD7ucCI7kDhwhiRfLm8PdXGRLSLUcULFJOXIw2xDIaBEvEQunGROyYwYrYtEmWotHPVbRqjLMNml/cTkYEsYZGIMQqG3EQC0asKk9unyGPMXH3ss+kpvHHnWBD7MXeN8dEvV6QUvE195Tty0xhaDP6RqA2gzcagog9EEW+QdXNxqY+vhxr81I2FGWIVQWuGFSdCCI2b5L9i31RNbppX6b4NJQaHmYjYvnjFIWdg8/gjpQ7tJhqVkyEIfdnASM52QgRxLpwTZjnlfsRn7C0s9pw0TZLtCGW0SBYIhZKNyZixw5WxL4Zffx65G5z4uarnRlFo9pGIILYGSYgxHKbcBALRuzIBkdtee8scswTvYL9JDH4TtRgA2KlTUBtRtxkCCJ2o3pfAhfBErtvTrLIyE89E1CG2NHAFYOqE0HE9l0trn97vpBaTZ6AST54joeNiL1bOr8obEUXtohrxtgs/kPDYcj9D8tAkXyxDBHE5jt+vB+lxKubVJtRYZrR0YI2xDIaBEvEQunGRKzIYEUsn4e4aFKAOnUXrlCtRvkeBRHEKtNAiB1L4yAWjNjXPTgerY7NeqGF94I75e71w/cpOsNjyLcLE4lRgdMDjPtWR8PQZhRpoDYzkzYEEbsnfJLvyplXcNsCn00ac7lsFMoQKwFcMag6EUQsbqOT9ZRdqwmVLiqK6i+Mv7ARsQ5KfFtLLXxxu0xSju7YI8wHx8dbACPZb40IYvnwG6/Ok63Xj8mTEVSU5GpFG2IZDYIlYqF0YyJWdLAi1vi1p/au4wm6QamZrevclC8gglhJWxBiP9lwEAtGLPeaMcEihQ+IodsiEu8XXktAM2In2YLazBjbIYhYF/covd23aOTCSV/GHhyxOBpliOUBrhhUnQgiFj/ZoES56q1WmF/zXRWNGyQ2IhY76t1bkVEjNfP49plcq3piBscN82xAkeyyQQSxR0Qt9LfHr8dmtS582bLLvR1tiGU0CJaIhdKNidhxgxWxU1U+ZOqPz9Xd2zTdN2sR8RgiiF3kC0KsuC8HsX8zKDbpv3CnREU35p1LPI/NOmnYEHuiybiqe5EUuX7pwpDxPa/qYGgzKr6gNoPxHYKIPd+dUC6ceEMrY+ziCw3SKyeiDLHSwBWDqhNBxJa6e29T0UzULJP44tC+vTmMjYhNPRqyt6FfiVzsduJu5rXkjTDk/mhgJLl9EUGsbVwqgSj3hFDXPCaiv/HEf/+4dTYhltEgWCIWSjcmYscPVsT6xsq3elGSqVtvyxuPvSG5HBHE9voDP1XHn4NYMGJfSKygKRwI1Ym4fDipwVjyDJoR+9wf1GYe+Q9BxFaedwipr47RDT8RkSu4NvgyyhB7C7hiUHUiiNi04bJPBC+FUePGCucI4Ub+zU0lfwqx1eM7zrqknsSWc3U2qvh6wHHb9yZgJGv9EUFsZKa4ovkFeWqawp3QCMnIVLQhltEgWH8Ojf83xIoNVsTm59huWtu8kLhlzIqJHVWC9YggViUchFiZcA5i/+ZY7I7bu7fhqzRjnbbGtYj47YANscuzT0UrrieRQk8XOG/Ljn4OQ5tZEA5qM0rhQxCxK0NPqHkdekGsOpUW7l+dXoAyxMoDVwyqTgQR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- Raise 2 to the power of N.
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- Power of 2
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- Translate (move) an object along a vector.
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- A beta fill and stroke preview in Rhino.
WARNING: This does not reflect most of the graphic settings in Graphic Plus.
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- Applies Stroke properties to a Shape
- true
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- Stroke
- Stroke
-
-6025
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212
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- A Graphic Plus Shape, or a Curve, Brep, Mesh
- 5c93d15f-c585-4d0a-86aa-e5c51605af29
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- 23a0297b-ed98-4bd0-ba8b-8cd6c9188e69
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- The stroke color
- f1e150bd-749c-4f85-bd23-9bdea7a32669
- Color
- Color
- true
- fb5e6000-65f6-4083-bb75-66522d7a800d
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- The stroke weight
- ee015750-1b36-42fa-a542-c758a2bdf3ff
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- 49b99293-9239-4d70-ac77-3ddc2b030bf1
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- 361a594e-1a81-409a-8175-56f37d97a253
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- Pattern
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136
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- The shape to be used at the end of open path
- 8791ee90-8038-48a9-a37c-24def1a9ba6e
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- End Cap
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-
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136
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- 89ec55d9-9acd-4778-b1b1-303743c452af
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-
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48
100
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- 071c3940-a12d-4b77-bb23-42b5d3314a0d
- Clean Tree
- Removed all null and invalid items from a data tree.
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- 1d5c4f6d-33b9-4a05-bb48-6bc9bf3bcc4e
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- Clean Tree
-
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135
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- Remove Nulls
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83
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- Remove Invalid
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- Remove empty branches from the tree.
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- Drawing Viewer
- Preview a Drawing in canvas.
Note: Right click on the component to save the image or svg
- true
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- Drawing Viewer
- Drawing Viewer
-
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- A list of Graphic Plus Drawing, Shapes, or Geometry (Curves, Breps, Meshes).
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- Drawings / Shapes / Geometry
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- c2f20982-683c-4cca-a3cf-8f2484184be0
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- The PPI (Pixels Per Inch) resolution for the image which must be greater than or equal to 72.
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- Resolution
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- Applies Stroke properties to a Shape
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- Stroke
- Stroke
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- The stroke color
- 544e9f0f-0517-4ba7-8771-8ad5e7eb6a31
- Color
- Color
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- 971f16c6-2031-4660-bd7d-1784e4a6c0d9
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- The stroke weight
- 4a80ecf0-e637-4c44-bbb7-78164464e728
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- Weight
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- 49b99293-9239-4d70-ac77-3ddc2b030bf1
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- The shape to be used at the end of open path
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136
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- Removed all null and invalid items from a data tree.
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83
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83
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83
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- Spotless data tree
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- Evaluate Length
- Evaluate Length
-
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149
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71
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- Length factor for curve evaluation
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- Length
- Length
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71
20
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Normalized
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71
20
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- Point at the specified length
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- Tangent vector at the specified length
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50
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- Create a polyline connecting a number of points.
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- PolyLine
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106
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- Vertices
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40
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- Close polyline
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- Closed
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40
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- Resulting polyline
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- Polyline
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38
40
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- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- f7b81817-49e9-4681-80c7-db50b00040a6
- PolyLine
- PolyLine
-
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3387
106
44
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- Vertices
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- 60158ae8-cf8c-438c-8c3c-14ba849a03b2
- 1
-
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40
20
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- Close polyline
- f046a1db-bedb-479c-986f-d4a4ef10c49a
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
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40
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- Resulting polyline
- 2a519291-539a-48a2-9e4d-a2d835b74781
- Polyline
- Polyline
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-
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3389
38
40
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- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
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- Merge
- Merge
-
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90
64
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Data stream 1
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- Data 1
- D1
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-
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- Data stream 2
- a994094a-2e0c-4d33-bd70-ab048da589ff
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- Data 2
- D2
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- a55f5b2b-59dd-4127-af45-fb2940b84e66
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- Data 3
- D3
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- Result
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
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- Evaluate Length
-
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149
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- 706e6595-4fb3-421b-996a-354bb8e28c9b
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71
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- Length factor for curve evaluation
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- Length
- Length
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71
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Normalized
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71
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- Point
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- Tangent vector at the specified length
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50
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- Curve parameter at the specified length
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50
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- Create a polyline connecting a number of points.
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- Close polyline
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38
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- Create a polar array of geometry.
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- Polar Array
- Polar Array
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132
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-
0
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1
0
0
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- Number of elements in array.
- e228660b-0381-4064-b83d-8ca570d2b8ed
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- Count
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- a36a42bd-2f18-4380-938f-847c2f934c7b
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132
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- b2942652-4e75-4d30-be8c-77cf436e1982
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- Angle
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- false
-
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- Geometry
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50
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- Transformation data
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- Transform
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50
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- Cull Duplicates
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- Cull points that are coincident within tolerance
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- Cull Duplicates
- Cull Duplicates
-
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180
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- Points to operate on
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113
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- Tolerance
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113
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- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
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- Create a polar array of geometry.
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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- Cull Duplicates
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-
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- Proximity tolerance distance
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- Culled points
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- Number of input points represented by this output point
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
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-
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- Data matrix to flip
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132
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- Number of input points represented by this output point
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-
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- Curve to explode
- c3ccf7ec-ba9f-499c-81a1-9d1dc74b42f4
- true
- Curve
- Curve
- false
- 83c38d86-bdbd-4063-9828-467d22d7cc98
- 1
-
16599
-1065
57
20
-
16627.5
-1055
- Recursive decomposition until all segments are atomic
- 0f9cb2f4-802a-4cb2-82c8-2656e9252490
- true
- Recursive
- Recursive
- false
- 0
-
16599
-1045
57
20
-
16627.5
-1035
- 1
- 1
- {0}
- true
- 1
- Exploded segments that make up the base curve
- 1b904cf9-6d07-4371-8794-c811f80ea402
- true
- Segments
- Segments
- false
- 0
-
16680
-1065
49
20
-
16704.5
-1055
- 1
- Vertices of the exploded segments
- 4452f4d1-91d8-4946-88d6-5888c9faa279
- true
- Vertices
- Vertices
- false
- 0
-
16680
-1045
49
20
-
16704.5
-1035
- ccc7b468-e743-4049-891f-299432545898
- Curve Middle
- Get the point in the middle of a curve
- true
- a98d7f24-e9a1-4711-acc6-2d87a7568bd0
- true
- Curve Middle
- Curve Middle
-
16750
-998
117
28
-
16794
-984
- Curve for mid-point.
- 9dad8727-e2b7-4175-a52c-cda81aebda87
- true
- Curve
- Curve
- false
- 1b904cf9-6d07-4371-8794-c811f80ea402
- 1
-
16752
-996
30
24
-
16767
-984
- Point in the middle of the curve
- 716c171e-2e0d-4bde-81a6-268ef5a60530
- true
- 1
- Midpoint
- Midpoint
- false
- 0
-
16806
-996
59
24
-
16827.5
-984
- 11bbd48b-bb0a-4f1b-8167-fa297590390d
- End Points
- Extract the end points of a curve.
- true
- b7292e2d-a04b-41d3-a7b1-6e70cd4b600d
- true
- End Points
- End Points
-
16746
-1126
84
44
-
16790
-1104
- Curve to evaluate
- 07aaae07-05f0-46e9-9bb2-3521d8036832
- true
- Curve
- Curve
- false
- 83c38d86-bdbd-4063-9828-467d22d7cc98
- 1
-
16748
-1124
30
40
-
16763
-1104
- Curve start point
- 179bff57-cd4a-493a-863d-25b9a179d84c
- true
- Start
- Start
- false
- 0
-
16802
-1124
26
20
-
16815
-1114
- Curve end point
- 4b7f86fb-520a-49f8-ab98-37b47b50d332
- true
- End
- End
- false
- 0
-
16802
-1104
26
20
-
16815
-1094
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- f598445f-c9bb-4632-ae5a-5ced170ec13e
- true
- Merge
- Merge
-
16901
-1112
106
84
-
16946
-1070
- 4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- 64df2663-8991-4145-9111-913541e81ca2
- true
- false
- Data 1
- D1
- true
- 179bff57-cd4a-493a-863d-25b9a179d84c
- 1
-
16903
-1110
31
20
-
16918.5
-1100
- 2
- Data stream 2
- 269a8b4a-e4c3-4863-bf1f-0deb0d87ac67
- true
- false
- Data 2
- D2
- true
- 716c171e-2e0d-4bde-81a6-268ef5a60530
- 1
-
16903
-1090
31
20
-
16918.5
-1080
- 2
- Data stream 3
- 16cd3125-c7cc-4272-b383-8acadd92fcfe
- true
- false
- Data 3
- D3
- true
- 4b7f86fb-520a-49f8-ab98-37b47b50d332
- 1
-
16903
-1070
31
20
-
16918.5
-1060
- 2
- Data stream 4
- 6e98d805-d129-410e-9208-7e959562de1b
- true
- false
- Data 4
- D4
- true
- 0
-
16903
-1050
31
20
-
16918.5
-1040
- 2
- Result of merge
- d41ee257-f83f-44a4-b288-3bff9e9da672
- true
- 1
- Result
- Result
- false
- 0
-
16958
-1110
47
80
-
16973.5
-1070
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- a1cd0866-6775-4e14-9c95-510db4b8326d
- true
- PolyLine
- PolyLine
-
17038
-993
116
44
-
17102
-971
- 1
- Polyline vertex points
- ec7c6dab-9b0d-40fc-8bdc-62f65e696227
- true
- Vertices
- Vertices
- false
- d41ee257-f83f-44a4-b288-3bff9e9da672
- 1
-
17040
-991
50
20
-
17065
-981
- 1
- 6
- {0}
-
0.230849276451111
-0.197502004087453
0
-
0.0662562057590903
-0.223755241522163
0
-
0.0663636407279125
0.199099878871604
0
-
0.609184501908787
0.20516461549513
0
-
0.605827517736367
-0.203827499272069
0
-
0.401731366034673
-0.194413499441869
0
- Close polyline
- 05860923-c6b2-4151-b8ba-800a16aab90b
- true
- Closed
- Closed
- false
- 0
-
17040
-971
50
20
-
17065
-961
- 1
- 1
- {0}
- false
- Resulting polyline
- 99adb399-bb0d-42f7-995a-6b1d6ba6e352
- true
- Polyline
- Polyline
- false
- 0
-
17114
-991
38
40
-
17133
-971
- cc14daa5-911a-4fcc-8b3b-1149bf7f2eeb
- Point List
- Displays details about lists of points
- true
- 47957213-cdcf-4228-a22d-1459dac03b4a
- true
- Point List
- Point List
-
17052
-889
74
44
-
17112
-867
- 1
- Points to display
- true
- f53fe761-7495-41bb-984a-5d00113338bb
- true
- Points
- Points
- true
- 7dfed2fb-2c2d-43fe-80f7-67d25a4cb30d
- 1
-
17054
-887
46
20
-
17077
-877
- Optional text size (in Rhino units)
- 48a722bc-723e-4c9a-8aee-6d0321f04616
- true
- Size
- Size
- true
- 0
-
17054
-867
46
20
-
17077
-857
- 2576f657-2f0d-4e3e-9dfb-c79eb4cd13d7
- 4442bb24-c702-460c-a1e4-fcdd321eb886
- Loop Start
- Start the loop with this one. Double click to rerun.
- true
- dfbb98ef-98e2-40fb-9c5f-4322dc449848
- true
- Loop Start
- Loop Start
-
16552
-1312
118
64
-
16617
-1280
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 3
- 6cc73910-22ac-4eb4-882b-eb9d63b8f3c2
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Number of repeats
- dd387923-9b22-4629-bdb1-d0a610793581
- true
- Repeat
- Repeat
- true
- 0
-
16554
-1310
51
20
-
16579.5
-1300
- 1
- 1
- {0}
- 64
- 2
- If you want trigger loop to restart
- 85885200-e9ee-4621-a0fd-ea1c8eb9e686
- true
- Trigger
- Trigger
- true
- 8922d579-58bd-4f83-b1d2-2f7c1c847b74
- 1
-
16554
-1290
51
20
-
16579.5
-1280
- 2
- Data to loop
- f9b4de04-ed90-4a16-a896-ee43d05682a9
- true
- Data
- Data
- true
- 55e2b44c-7595-4da6-bdc2-27211f29bd8b
- 1
-
16554
-1270
51
20
-
16579.5
-1260
- Connect to Loop End
- 688aaa76-c5c0-437f-bb7b-d2fb2d647152
- true
- >
- >
- false
- 0
-
16629
-1310
39
20
-
16648.5
-1300
- Counter
- 150a773a-5aa8-4e0b-abca-14a9d8ff6e48
- true
- Counter
- Counter
- false
- 0
-
16629
-1290
39
20
-
16648.5
-1280
- 2
- Data to loop
- d5cadfaa-7751-4509-a208-173c2c13ffa1
- true
- Data
- Data
- false
- 0
-
16629
-1270
39
20
-
16648.5
-1260
- 15483310-2ce2-48c6-b803-9dee8cb7cc9b
- 4442bb24-c702-460c-a1e4-fcdd321eb886
- Loop End
- End the loop with this one. Double click to pause the loop.
- true
- 0088c44a-a145-4779-89de-19b000b39a60
- true
- Loop End
- Loop End
- 0
- false
- Constant & Record
-
16959
-1372
104
64
-
17008
-1340
- 3
- 6cc73910-22ac-4eb4-882b-eb9d63b8f3c2
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Connect to Loop Start
- 062f1d0d-2835-4808-a2e1-68ed71c83de0
- true
- <
- <
- false
- 688aaa76-c5c0-437f-bb7b-d2fb2d647152
- 1
-
16961
-1370
35
20
-
16978.5
-1360
- Set to true to exit the loop
- 446153a1-e5fe-4b51-9c06-03f3c8269142
- true
- Exit
- Exit
- true
- 0
-
16961
-1350
35
20
-
16978.5
-1340
- 1
- 1
- {0}
- false
- 2
- Data to loop
- 27320839-2dfa-4799-87b2-f5a27c549120
- true
- Data
- Data
- false
- 613432b1-7d77-4615-b262-15d13c6fc293
- 1
-
16961
-1330
35
20
-
16978.5
-1320
- 2
- Data after the loop
- 869cc8ba-3a74-4469-ae82-c452fd20180b
- true
- 1
- Data
- Data
- false
- 0
-
17020
-1370
41
60
-
17032.5
-1340
- dc6f76a5-ffd3-4a50-b42b-fcb46a544902
- c6c19589-ab63-4b60-8d7c-2c1b6d60fac7
- True Only Button
- When clicked, the button object only raises recomputation one time.
- False
- True
- 8922d579-58bd-4f83-b1d2-2f7c1c847b74
- true
- True Only Button
- True Only Button
- false
- 0
- neutral,N
-
16390
-953
148
22
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 83c38d86-bdbd-4063-9828-467d22d7cc98
- true
- Relay
- false
- 79cee91b-b321-4230-985a-2ae1ec2ad0ef
- 1
-
16693
-1186
40
16
-
16713
-1178
- 7a1e5fd7-b7da-4244-a261-f1da66614992
- Power of 2
- Raise 2 to the power of N.
- true
- a42b481f-1cac-406c-915c-78cd5dc17db5
- true
- Power of 2
- Power of 2
-
16568
-1443
103
28
-
16626
-1429
- Input value
- d2e297c3-b80c-4014-b980-9a8c29f5fcfe
- true
- Value
- Value
- false
- 0
-
16570
-1441
44
24
-
16592
-1429
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_String
- false
- 16
- Output value
- 853f787d-d612-40ed-957d-502a109f80c4
- true
- Result
- Result
- false
- 0
-
16638
-1441
31
24
-
16653.5
-1429
- 4d2a06bd-4b0f-4c65-9ee0-4220e4c01703
- Scale
- Scale an object uniformly in all directions.
- true
- dd01be7a-f004-4f2e-8f95-86bd6510ab44
- true
- Scale
- Scale
-
16526
-1535
201
64
-
16663
-1503
- Base geometry
- 7adec163-1f97-4ba6-9387-2030d32702d0
- true
- Geometry
- Geometry
- true
- d5cadfaa-7751-4509-a208-173c2c13ffa1
- 1
-
16528
-1533
123
20
-
16589.5
-1523
- Center of scaling
- 3b53ddef-ed80-4109-8689-e13f03a7db64
- true
- Center
- Center
- false
- 0
-
16528
-1513
123
20
-
16589.5
-1503
- 1
- 1
- {0}
-
0
0
0
- Scaling factor
- 4deef344-5568-4030-965e-c677619704f7
- true
- Factor
- Factor
- false
- 853f787d-d612-40ed-957d-502a109f80c4
- 1
-
16528
-1493
123
20
-
16589.5
-1483
- 1
- 1
- {0}
- 0.5
- Scaled geometry
- 6830d610-5ef3-4e8b-95f3-a34e4424f6f9
- true
- Geometry
- Geometry
- false
- 0
-
16675
-1533
50
30
-
16700
-1518
- Transformation data
- 937023b7-428d-448e-b8ce-626e522bf593
- true
- Transform
- Transform
- false
- 0
-
16675
-1503
50
30
-
16700
-1488
- 4d2a06bd-4b0f-4c65-9ee0-4220e4c01703
- Scale
- Scale an object uniformly in all directions.
- true
- efd5b6f1-8a95-4da6-a382-798344be96a6
- true
- Scale
- Scale
-
16873
-1516
217
64
-
17026
-1484
- Base geometry
- d8eb3162-4f16-4420-bdb4-08565b3f2b85
- true
- Geometry
- Geometry
- true
- 99adb399-bb0d-42f7-995a-6b1d6ba6e352
- 1
-
16875
-1514
139
20
-
16952.5
-1504
- Center of scaling
- 83ecda89-b6c1-42f0-91b3-f8e168213f81
- true
- Center
- Center
- false
- 0
-
16875
-1494
139
20
-
16952.5
-1484
- 1
- 1
- {0}
-
0
0
0
- Scaling factor
- ce9b475d-ee91-4782-9281-c7430f998752
- 1/X
- true
- Factor
- Factor
- false
- 853f787d-d612-40ed-957d-502a109f80c4
- 1
-
16875
-1474
139
20
-
16952.5
-1464
- 1
- 1
- {0}
- 0.5
- Scaled geometry
- 613432b1-7d77-4615-b262-15d13c6fc293
- true
- Geometry
- Geometry
- false
- 0
-
17038
-1514
50
30
-
17063
-1499
- Transformation data
- 114d69b3-2bae-4eda-9527-28f1b502a88d
- true
- Transform
- Transform
- false
- 0
-
17038
-1484
50
30
-
17063
-1469
- 2162e72e-72fc-4bf8-9459-d4d82fa8aa14
- Divide Curve
- Divide a curve into equal length segments
- true
- 1cff164a-3135-4ae3-a5e4-0381ab2b137c
- true
- Divide Curve
- Divide Curve
-
16951
-808
139
64
-
17021
-776
- Curve to divide
- a7bc0aa0-0e3b-44c5-890d-3ecd63a3928b
- true
- Curve
- Curve
- false
- 79cee91b-b321-4230-985a-2ae1ec2ad0ef
- 1
-
16953
-806
56
20
-
16989
-796
- Number of segments
- d491ebe7-c4d7-4c83-bec9-1f5b25370ad0
- X-1
- true
- Count
- Count
- false
- b62af334-f12b-4c33-a2b7-43592a10d8d0
- 1
-
16953
-786
56
20
-
16989
-776
- 1
- 1
- {0}
- 10
- Split segments at kinks
- 974ce49c-d65c-4c95-8ecb-7d37f65946f8
- true
- Kinks
- Kinks
- false
- 0
-
16953
-766
56
20
-
16989
-756
- 1
- 1
- {0}
- false
- 1
- Division points
- 7dfed2fb-2c2d-43fe-80f7-67d25a4cb30d
- true
- Points
- Points
- false
- 0
-
17033
-806
55
20
-
17060.5
-796
- 1
- Tangent vectors at division points
- fd7f89c6-9b02-4ce7-b568-7d86e954cf39
- true
- Tangents
- Tangents
- false
- 0
-
17033
-786
55
20
-
17060.5
-776
- 1
- Parameter values at division points
- b174f96b-e9d4-4e21-872d-c1ad6297b1eb
- true
- Parameters
- Parameters
- false
- 0
-
17033
-766
55
20
-
17060.5
-756
- ad013215-63f3-46da-8b16-ce3bf593a0c0
- 1c9de8a1-315f-4c56-af06-8f69fee80a7a
- Curve Edit Points
- Extract the edit points on a curve at knot averages, the points an interpolated curve interpolated through.
- true
- c1604d20-1e74-4275-a566-65b937656418
- true
- Curve Edit Points
- Curve Edit Points
-
16599
-807
123
64
-
16653
-775
- Curve to get the edit points of
- da149e96-5071-4803-bb0b-729c3e0c978d
- true
- Curve
- Curve
- false
- 79cee91b-b321-4230-985a-2ae1ec2ad0ef
- 1
-
16601
-805
40
30
-
16621
-790
- If True, only the edit points at knots (span ends) are extracted (the points an interpolated curve interpolated through)
If False, all edit points are extracted which equals the same amount as the curve control points (like Rhino's EditPtOn command)
- d47fd754-782f-4f1f-ae61-b568debe71da
- true
- Knots
- Knots
- false
- 0
-
16601
-775
40
30
-
16621
-760
- 1
- 1
- {0}
- false
- 1
- Edit points on the curve
- a06159f5-0b11-4e74-bd9d-86eaa907ae3b
- true
- Points
- Points
- false
- 0
-
16665
-805
55
20
-
16692.5
-795
- 1
- Tangent vectors at edit points
- 35af92e7-36f2-44b1-836b-2f48870d8c76
- true
- Tangents
- Tangents
- false
- 0
-
16665
-785
55
20
-
16692.5
-775
- 1
- Parameter values at edit points
- b9fdd5cd-f966-4ab6-8462-edac2f3ca86a
- true
- Parameters
- Parameters
- false
- 0
-
16665
-765
55
20
-
16692.5
-755
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 79cee91b-b321-4230-985a-2ae1ec2ad0ef
- true
- Relay
- false
- 6830d610-5ef3-4e8b-95f3-a34e4424f6f9
- 1
-
16607
-1172
40
16
-
16627
-1164
- 1817fd29-20ae-4503-b542-f0fb651e67d7
- List Length
- Measure the length of a list.
- true
- 5f8620a3-97e4-4943-93ec-621d31085efa
- true
- List Length
- List Length
-
16765
-790
97
28
-
16798
-776
- 1
- Base list
- 0edfa1db-55c6-4759-a9c2-8e38c20fab36
- true
- List
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- Remove Nulls
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83
20
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- Remove Invalid
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83
20
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- Remove empty branches from the tree.
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- Data tree to clean
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- Spotless data tree
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80
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- 177ebf54-672d-4201-9e7e-88a2174b5ff2
- Evaluate Length
- Evaluate Length
-
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149
64
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- Curve to evaluate
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71
20
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- Length factor for curve evaluation
- 46bc8c22-474f-49f1-b450-e269dacf0b1b
- Length
- Length
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4312
71
20
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- If True, the Length factor is normalized (0.0 ~ 1.0)
- eb593801-031c-40f0-8db8-091e757e5ec4
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71
20
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- Point at the specified length
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50
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- Tangent vector at the specified length
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50
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- Curve parameter at the specified length
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50
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- 71b5b089-500a-4ea6-81c5-2f960441a0e8
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- Create a polyline connecting a number of points.
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- PolyLine
-
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106
44
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40
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- Close polyline
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40
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38
40
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4313
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
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- Create a polyline connecting a number of points.
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- PolyLine
- PolyLine
-
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4359
106
44
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40
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- Close polyline
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40
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38
40
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- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
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- Merge a bunch of data streams
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4319
90
64
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31
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31
60
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- Create a polar array of geometry.
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- Polar Array
- Polar Array
-
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210
101
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- Base geometry
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132
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- Polar array plane
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132
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132
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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132
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50
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50
49
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- Cull Duplicates
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- Cull points that are coincident within tolerance
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- Cull Duplicates
- Cull Duplicates
-
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180
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- Points to operate on
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113
30
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- Proximity tolerance distance
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113
30
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- Culled points
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- Points
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39
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39
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- Number of input points represented by this output point
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39
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
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- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
- Flip Matrix
-
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78
28
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- 2
- Data matrix to flip
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25
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- 2
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4285
25
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- Evaluate Length
- Evaluate Length
-
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4399
149
64
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- Curve to evaluate
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71
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- Length factor for curve evaluation
- dadde2e7-02b0-4b9a-a1ce-4765be8dd176
- Length
- Length
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71
20
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Normalized
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-
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71
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50
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- Tangent vector at the specified length
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50
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- Curve parameter at the specified length
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50
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- Polar Array
- Create a polar array of geometry.
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- Polar Array
- Polar Array
-
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4399
210
101
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- Base geometry
- 85a3d78e-d56f-4116-91fd-86d3810607b6
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132
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- Polar array plane
- 676b7b59-00e0-40d2-af96-5dc6039143cb
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132
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-
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0
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0
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- Number of elements in array.
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132
20
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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132
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- fd011762-3520-48d2-a6fd-14f37f6d119a
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4401
50
48
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50
49
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- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
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- c021a3bf-0177-4b65-aa95-b18ca93e291f
- Cull Duplicates
- Cull Duplicates
-
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4396
180
64
-
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4428
- 1
- Points to operate on
- a09bce55-f62d-4ecd-9500-4a2edf22ee4b
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- 1a9d7e15-c1be-43de-b0db-779afbd0a4dd
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-
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4398
113
30
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- Proximity tolerance distance
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- 0
-
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4428
113
30
-
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- 1
- 1
- {0}
- 1.1641532182693481E-10
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- Culled points
- 40e9a704-1897-40c9-a62f-c1ca756c1129
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-
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39
20
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4418
39
20
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- Number of input points represented by this output point
- 9ac7a65a-d317-4483-a0c1-a1a696a79822
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-
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39
20
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
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- Flip a matrix-like data tree by swapping rows and columns.
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- 5723f52f-3856-490b-bb74-1bed6c50fdc9
- Flip Matrix
- Flip Matrix
-
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4411
78
28
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- Data matrix to flip
- c2ec5213-befc-4d81-8e58-70acd9a580bf
- Data
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- fd011762-3520-48d2-a6fd-14f37f6d119a
- 1
-
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25
24
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- 2
- Flipped data matrix
- a2b0532f-503c-41b6-87ab-030285f5949d
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-
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4413
25
24
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- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
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- Merge a bunch of data streams
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- 1017d33b-cbb5-459d-b84c-254beedb00ed
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- Merge
-
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90
64
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Data 1
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- 96f72f95-50c1-4167-a4ee-9dd0f5c4d8e3
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31
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- Data 2
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31
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-
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31
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- Result of merge
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31
60
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- 071c3940-a12d-4b77-bb23-42b5d3314a0d
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- Removed all null and invalid items from a data tree.
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- Clean Tree
- Clean Tree
-
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135
84
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- Remove null items from the tree.
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-
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5660
83
20
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- Remove invalid items from the tree.
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-
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5680
83
20
-
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- Remove empty branches from the tree.
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- false
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5700
83
20
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- The shape to be used at the end of open path
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- Flip a matrix-like data tree by swapping rows and columns.
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- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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101
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132
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180
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- Removes duplicate lines in a list
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- Flip a matrix-like data tree by swapping rows and columns.
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- Create a polar array of geometry.
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- Removes duplicate lines in a list
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- Clean Duplicate Lines
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- The value will be false if the line was removed.
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- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
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- Create a polar array of geometry.
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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- Removes duplicate lines in a list
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- Clean Duplicate Lines
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- The value will be false if the line was removed.
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- Flip a matrix-like data tree by swapping rows and columns.
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- The stroke color
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255;21;0;255
- The stroke weight
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- The shape to be used at the end of open path
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100
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- Removed all null and invalid items from a data tree.
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- Remove null items from the tree.
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- Length factor for curve evaluation
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- Tangent vector at the specified length
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- Create a polyline connecting a number of points.
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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- Cull points that are coincident within tolerance
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- Cull Duplicates
- Cull Duplicates
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- Number of input points represented by this output point
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
- Flip Matrix
-
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- Data matrix to flip
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- fa6723e9-51f0-4cfa-88f2-e3b098ebf179
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- The value will be false if the line was removed.
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
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- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
- Flip Matrix
-
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94
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- Data matrix to flip
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41
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- Create a polar array of geometry.
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- Polar Array
- Polar Array
-
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210
101
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- Base geometry
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- Number of elements in array.
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132
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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- Removes duplicate lines in a list
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- Clean Duplicate Lines
-
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- Distance check tolerance
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- The value will be false if the line was removed.
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
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- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
- Flip Matrix
-
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- Applies Stroke properties to a Shape
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- A Graphic Plus Shape, or a Curve, Brep, Mesh
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- The stroke weight
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- The shape to be used at the end of open path
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136
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- Removed all null and invalid items from a data tree.
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- Clean Tree
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- Data tree to clean
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- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
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- Evaluate Length
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- Curve to evaluate
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71
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- Length factor for curve evaluation
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- Tangent vector at the specified length
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- Curve parameter at the specified length
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- Close polyline
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40
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38
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- 71b5b089-500a-4ea6-81c5-2f960441a0e8
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- Create a polyline connecting a number of points.
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40
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- Close polyline
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- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
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- Merge a bunch of data streams
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-
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-
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210
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- Base geometry
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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- 1
- Cull points that are coincident within tolerance
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- Cull Duplicates
- Cull Duplicates
-
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39
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- Number of input points represented by this output point
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-
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
- Flip Matrix
-
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25
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
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- Evaluate Length
- Evaluate Length
-
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149
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- Curve to evaluate
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71
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- Length factor for curve evaluation
- add03b20-f3b4-4a76-a814-884b7804ed5e
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- f8c79933-13ba-44cb-aa67-0e8cf579350a
- Data
- Data
- false
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- 1
-
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10190
25
24
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- 2
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- 45dd2659-3327-4e21-90b2-ecdb137cd833
- 1
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- Data
- false
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-
-9918
10190
41
24
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10202
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- e697eefb-87ad-422d-a21d-1137b7c1e972
- Polar Array
- Polar Array
-
-10927
10305
210
101
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- Base geometry
- ae94b400-3755-400d-ad35-1bbcb11b03bc
- Geometry
- Geometry
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- 30b06e4d-8646-4a7c-970f-d0368cb36430
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-
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132
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- Polar array plane
- 391dbf1e-6125-4ab4-a209-461987e3f0d5
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132
37
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0
0
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1
0
0
0
1
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- Number of elements in array.
- 5715e9a2-c1ad-4c08-a5c1-b2064df88696
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
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10364
132
20
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- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 68fdcded-66fe-483d-b0e3-a958f1e182c7
- Angle
- Angle
- false
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- false
-
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132
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- {0}
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- Arrayed geometry
- 521c3438-9d00-49a4-9c55-e44ff84f69c2
- Geometry
- Geometry
- false
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-
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10307
50
48
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- Transformation data
- 9448579d-23fa-4302-9786-54d3209f6b39
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- Transform
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50
49
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- dc8aee5e-da26-45f0-b2c8-612fcf84157e
- 08b214d9-388c-4ad0-940b-716633b47e45
- Clean Duplicate Lines
- Removes duplicate lines in a list
- true
- 56cf12cb-93cb-4799-97c1-5b4da8f18c3a
- Clean Duplicate Lines
- Clean Duplicate Lines
-
-9260
10314
176
64
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10346
- 1
- Lines to check for duplicates
- 406058b1-d198-4e31-b684-c49d1fdbdef4
- Lines
- Lines
- false
- 9878c493-eeff-4143-9e82-fe72a838b843
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-
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113
30
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- Distance check tolerance
- a00024cf-762e-4c59-b724-712c5638305b
- Tolerance
- Tolerance
- true
- 0
-
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113
30
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10361
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Filtered lines
- bc879567-85d4-4dad-80d0-78d6e3a37c55
- Lines
- Lines
- false
- 0
-
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35
20
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10326
- 1
- Mapped Indices
- 1db72078-1077-497d-aa43-9eb502e38cfe
- Indices
- Indices
- false
- 0
-
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10336
35
20
-
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10346
- 1
- The value will be false if the line was removed.
- c66bf3ec-c734-4149-94e0-d50bd08f4c4a
- Status
- Status
- false
- 0
-
-9121
10356
35
20
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10366
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- d9c3671f-0dae-46ba-b548-bc0c391248e7
- Flip Matrix
- Flip Matrix
-
-9969
10317
94
28
-
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- 2
- Data matrix to flip
- c76f9827-3168-4b5b-86cb-8bd0494d4802
- Data
- Data
- false
- 521c3438-9d00-49a4-9c55-e44ff84f69c2
- 1
-
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25
24
-
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- 2
- Flipped data matrix
- 9878c493-eeff-4143-9e82-fe72a838b843
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- Data
- Data
- false
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-
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41
24
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- 030b487b-a566-476f-96a4-a0ae2ad283af
- a48ac930-c378-48dc-84da-26b2af9d8302
- Stroke
- Applies Stroke properties to a Shape
- true
- 9bf9cad7-6250-4710-920c-44347225fcc7
- Stroke
- Stroke
-
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212
104
-
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- A Graphic Plus Shape, or a Curve, Brep, Mesh
- 26476845-3463-4e30-b838-14d451ac743b
- Shape / Geometry
- Shape / Geometry
- false
- 0d69f67e-72dd-4b79-81cb-d8c17722633e
- 1
-
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9938
136
20
-
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- The stroke color
- 4422378c-96ec-4899-86be-fb32f65e295e
- Color
- Color
- true
- 214c99d0-6148-4a47-a6bb-b3e15350f20b
- 1
-
-5973
9958
136
20
-
-5905
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- 1
- 1
- {0}
-
255;21;0;255
- The stroke weight
- 298bb8fa-6ede-46e9-9981-2fde047ca04e
- Weight
- Weight
- true
- 49b99293-9239-4d70-ac77-3ddc2b030bf1
- 1
-
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9978
136
20
-
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- 1
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- {0}
- 9
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- The stroke pattern
- 2e29f14b-7f71-4105-b927-c9ce8b7e4b0e
- Pattern
- Pattern
- true
- 0
-
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9998
136
20
-
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10008
- The shape to be used at the end of open path
- 5b8f120e-18c7-4010-b508-1f173fc33f7b
- End Cap
- End Cap
- true
- 0
-
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10018
136
20
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10028
- 1
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- A Graphic Plus Shape Object
- true
- 8e672fa7-2874-48a8-83dd-23c69a49627d
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- Shape
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-
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9938
48
100
-
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9988
- 071c3940-a12d-4b77-bb23-42b5d3314a0d
- Clean Tree
- Removed all null and invalid items from a data tree.
- true
- 4d0acd62-42f9-4f30-ab24-7bf6079d0af1
- Clean Tree
- Clean Tree
-
-6809
9912
135
84
-
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9954
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- cb95db89-6165-43b6-9c41-5702bc5bf137
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- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Remove null items from the tree.
- 323ae7c9-455f-4087-b80f-487adc139f90
- Remove Nulls
- Remove Nulls
- false
- 0
-
-6807
9914
83
20
-
-6765.5
9924
- 1
- 1
- {0}
- true
- Remove invalid items from the tree.
- 19cbc24c-5e81-454c-9512-06c638f45ce8
- Remove Invalid
- Remove Invalid
- false
- 0
-
-6807
9934
83
20
-
-6765.5
9944
- 1
- 1
- {0}
- true
- Remove empty branches from the tree.
- aaf93b03-12d0-4145-919f-122ae9fac3e3
- Remove Empty
- Remove Empty
- false
- 0
-
-6807
9954
83
20
-
-6765.5
9964
- 1
- 1
- {0}
- true
- 2
- Data tree to clean
- d3a7193f-33f9-47c4-9741-a77b2498bc77
- Tree
- Tree
- false
- 46be9080-af03-498e-8aea-1db208e11c1c
- 1
-
-6807
9974
83
20
-
-6765.5
9984
- 2
- Spotless data tree
- 0d69f67e-72dd-4b79-81cb-d8c17722633e
- Tree
- Tree
- false
- 0
-
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9914
24
80
-
-6688
9954
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 835e1481-19b2-462a-92d8-b19bb04ba708
- Evaluate Length
- Evaluate Length
-
-11820
9878
149
64
-
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9910
- Curve to evaluate
- 40ae8545-0d31-4cf9-b0b0-133e6b9914ac
- Curve
- Curve
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- aaeded99-67a6-45ba-a830-e6f67d3af730
- 1
-
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9880
71
20
-
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- Length factor for curve evaluation
- c87f4ff8-55ee-4c08-b2da-bcf939eab6eb
- Length
- Length
- false
- 0
-
-11818
9900
71
20
-
-11782.5
9910
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 37fa8fc6-7112-4255-8656-cf368d912b98
- Normalized
- Normalized
- false
- 0
-
-11818
9920
71
20
-
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9930
- 1
- 1
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- true
- Point at the specified length
- df366672-ce88-4283-8d28-f80d442da29e
- Point
- Point
- false
- 0
-
-11723
9880
50
20
-
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- Tangent vector at the specified length
- be0819a2-3d92-4efe-87bc-eab4bb139328
- Tangent
- Tangent
- false
- 0
-
-11723
9900
50
20
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- Curve parameter at the specified length
- 38112c29-5bd3-42c1-8332-73781e56c94e
- Parameter
- Parameter
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- 0
-
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9920
50
20
-
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9930
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- c3f75100-e08f-4b19-8731-6fb588572721
- PolyLine
- PolyLine
-
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9924
106
44
-
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- Polyline vertex points
- 5fb43496-a355-4eaf-8463-49a7c59e1c8f
- Vertices
- Vertices
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- 2138d5a5-a00b-43ff-a0ad-aa4822db0145
- 1
-
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9926
40
20
-
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9936
- Close polyline
- f3ebc787-5bcb-42d0-8e75-5106d2b7d125
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
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9946
40
20
-
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- 1
- 1
- {0}
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- Resulting polyline
- 80936a9d-c0ce-4517-8e5a-e3072c18e9a5
- Polyline
- Polyline
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- 0
-
-8128
9926
38
40
-
-8109
9946
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- 762fd39a-467b-4f24-af75-53d880aee254
- PolyLine
- PolyLine
-
-8194
9995
106
44
-
-8140
10017
- 1
- Polyline vertex points
- 8e958efb-6ca0-4048-9e91-7c57b8dc0b40
- Vertices
- Vertices
- false
- 9b4bc001-60b6-4360-bcbe-ee42a7f1e22e
- 1
-
-8192
9997
40
20
-
-8172
10007
- Close polyline
- d8106ca5-1244-4d75-b520-7ac01868ed06
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8192
10017
40
20
-
-8172
10027
- 1
- 1
- {0}
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- Resulting polyline
- 30657e92-cc69-4c53-b2df-8c7ee85b4e4a
- Polyline
- Polyline
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- 0
-
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9997
38
40
-
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10017
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 66cd0c34-b22e-4d50-81c8-586358999c73
- Merge
- Merge
-
-7433
9952
90
64
-
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9984
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Data stream 1
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- Data 1
- D1
- true
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- 1
-
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31
20
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- 2
- Data stream 2
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- Data 2
- D2
- true
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- 1
-
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31
20
-
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9984
- 2
- Data stream 3
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- Data 3
- D3
- true
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-
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9994
31
20
-
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10004
- 2
- Result of merge
- 46be9080-af03-498e-8aea-1db208e11c1c
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- Result
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- 0
-
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9954
31
60
-
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9984
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 5a53701a-7b84-4254-9fc0-20b9e62fc9c4
- Polar Array
- Polar Array
-
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9878
210
101
-
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- Base geometry
- f363b1f5-3025-4e9e-a9c5-13c334f8bf9e
- Geometry
- Geometry
- true
- df366672-ce88-4283-8d28-f80d442da29e
- 1
-
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9880
132
20
-
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- Polar array plane
- 08ea3d69-382b-485b-b890-f4fc791f0a31
- Plane
- Plane
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-
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9900
132
37
-
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9918.5
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- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 0f87e8b2-2ebf-487c-b244-4d5366e6565b
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10925
9937
132
20
-
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- 1
- 1
- {0}
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 3e06e523-8157-41bf-b347-c355666837f5
- Angle
- Angle
- false
- 0
- false
-
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9957
132
20
-
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- 1
- 1
- {0}
- 6.2831853071795862
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- Arrayed geometry
- ac53c8e5-84ec-447a-a023-b73d81c9e8ec
- Geometry
- Geometry
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- 0
-
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9880
50
48
-
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9904.25
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- Transformation data
- a5341e3b-f366-4b9f-bed7-9bc13fe9d343
- Transform
- Transform
- false
- 0
-
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9928
50
49
-
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9952.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- b0b6dace-83ff-4665-9cd5-b6088764a19e
- Cull Duplicates
- Cull Duplicates
-
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9887
180
64
-
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9919
- 1
- Points to operate on
- 6e1247df-8680-4a2b-bf5c-cf110b2b7a7c
- Points
- Points
- false
- 29d90faf-b068-4670-badb-8456709db8a1
- 1
-
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9889
113
30
-
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9904
- Proximity tolerance distance
- 7a698892-07b7-40b6-ae78-53d7c75fda67
- Tolerance
- Tolerance
- false
- 0
-
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9919
113
30
-
-9203.5
9934
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- 2138d5a5-a00b-43ff-a0ad-aa4822db0145
- Points
- Points
- false
- 0
-
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9889
39
20
-
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9899
- 1
- Index map of culled points
- cbb6dc8d-cdd7-4f8f-8a92-03bfaac778d1
- Indices
- Indices
- false
- 0
-
-9123
9909
39
20
-
-9103.5
9919
- 1
- Number of input points represented by this output point
- 82c5849d-ada1-40d6-bfb0-b619cee41fc6
- Valence
- Valence
- false
- 0
-
-9123
9929
39
20
-
-9103.5
9939
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- 9c55da62-3de4-48e9-be17-8e9539c901b9
- Flip Matrix
- Flip Matrix
-
-9969
9890
78
28
-
-9930
9904
- 2
- Data matrix to flip
- b2830708-1294-4943-ac9b-cbfaca80efa0
- Data
- Data
- false
- ac53c8e5-84ec-447a-a023-b73d81c9e8ec
- 1
-
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9892
25
24
-
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9904
- 2
- Flipped data matrix
- 03e022f8-3fe1-4c18-aef5-bfd78f21620a
- Data
- Data
- false
- 0
-
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9892
25
24
-
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9904
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- eacefcda-50a5-4ae1-ab4a-ee70d2a4029e
- Evaluate Length
- Evaluate Length
-
-11820
10006
149
64
-
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10038
- Curve to evaluate
- d6c571ea-12ae-4f30-83ea-ecb22ecee090
- Curve
- Curve
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- 461d5dae-ee94-476e-b507-0690ab55e79f
- 1
-
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10008
71
20
-
-11782.5
10018
- Length factor for curve evaluation
- 09ce81bd-82a4-424a-8ff1-2d8e07e49acc
- Length
- Length
- false
- 0
-
-11818
10028
71
20
-
-11782.5
10038
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 3b23ca22-49a1-4f93-ae2e-2c63cb2680b2
- Normalized
- Normalized
- false
- 0
-
-11818
10048
71
20
-
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10058
- 1
- 1
- {0}
- true
- Point at the specified length
- 3e957476-4dfc-455d-af84-e5ac1d3751d1
- Point
- Point
- false
- 0
-
-11723
10008
50
20
-
-11698
10018
- Tangent vector at the specified length
- 660b823b-b006-4bb2-9bc4-95b919079c00
- Tangent
- Tangent
- false
- 0
-
-11723
10028
50
20
-
-11698
10038
- Curve parameter at the specified length
- c4e5db6e-a9a1-405a-b053-dcf0b7ecff88
- Parameter
- Parameter
- false
- 0
-
-11723
10048
50
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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- Removes duplicate lines in a list
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- Clean Duplicate Lines
-
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- Distance check tolerance
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- The value will be false if the line was removed.
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- Status
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
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- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
- Flip Matrix
-
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- Data matrix to flip
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- Flipped data matrix
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- Applies Stroke properties to a Shape
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-
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- A Graphic Plus Shape, or a Curve, Brep, Mesh
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- b6749caa-7b90-4824-bc78-e5c27b47f95d
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136
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- The stroke color
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- Color
- Color
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- 1597fcb6-8f36-4207-a151-eb0d7474c548
- 1
-
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11118
136
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255;21;0;255
- The stroke weight
- 262e4331-5d26-4c86-86b5-2ec94cd2f9d9
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- Weight
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- 49b99293-9239-4d70-ac77-3ddc2b030bf1
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- The stroke pattern
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136
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- The shape to be used at the end of open path
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- End Cap
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- A Graphic Plus Shape Object
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11098
48
100
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- 071c3940-a12d-4b77-bb23-42b5d3314a0d
- Clean Tree
- Removed all null and invalid items from a data tree.
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- Clean Tree
- Clean Tree
-
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11072
135
84
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Remove null items from the tree.
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- Remove Nulls
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-
-6787
11074
83
20
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11084
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- Remove invalid items from the tree.
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- Remove Invalid
- false
- 0
-
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11094
83
20
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11104
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- Remove empty branches from the tree.
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- Remove Empty
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83
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11124
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- Data tree to clean
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- Tree
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83
20
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- 2
- Spotless data tree
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11074
24
80
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11114
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 55db54fd-35cb-4494-b22e-8b00243041c5
- Evaluate Length
- Evaluate Length
-
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11038
149
64
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11070
- Curve to evaluate
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71
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- Length factor for curve evaluation
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- Length
- Length
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-11798
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71
20
-
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11070
- 1
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- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- a3cb0976-96a3-43b9-a506-a078bec8f622
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- Normalized
- false
- 0
-
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11080
71
20
-
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11090
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- Point at the specified length
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- Point
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11040
50
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- Tangent vector at the specified length
- 787996d9-49cb-4ed1-bee2-703c65ce4736
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- Tangent
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-
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- Curve parameter at the specified length
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50
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- 71b5b089-500a-4ea6-81c5-2f960441a0e8
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- Create a polyline connecting a number of points.
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- PolyLine
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106
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40
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- Close polyline
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40
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- Resulting polyline
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- Polyline
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-
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11086
38
40
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11106
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- 8000371a-c674-4938-8be1-9853ca521f5f
- PolyLine
- PolyLine
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11155
106
44
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- Polyline vertex points
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40
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- Close polyline
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- Closed
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- 1
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40
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- Resulting polyline
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- Polyline
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38
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- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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- Merge
- Merge
-
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11112
90
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- Data stream 1
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- Data 1
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31
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- Data stream 2
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- Data 2
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31
60
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- fca5ad7e-ecac-401d-a357-edda0a251cbc
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- Create a polar array of geometry.
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- Polar Array
- Polar Array
-
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210
101
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- Base geometry
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- Geometry
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132
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- Polar array plane
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132
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0
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- Number of elements in array.
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- Count
- Count
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- a36a42bd-2f18-4380-938f-847c2f934c7b
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11097
132
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 3aacda92-a77b-45dd-9f44-f56a6b37a14b
- Angle
- Angle
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- false
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132
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- Arrayed geometry
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- Geometry
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50
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- Transformation data
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- Transform
- Transform
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-
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50
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- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
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- Cull Duplicates
- Cull Duplicates
-
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180
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- Points to operate on
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113
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- Proximity tolerance distance
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- Tolerance
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- 0
-
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113
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- 1
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- {0}
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- Culled points
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- Points
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-
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39
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- Index map of culled points
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- Indices
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-
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39
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-
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- Number of input points represented by this output point
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- Valence
- Valence
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- 0
-
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39
20
-
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- 455f0762-2713-4463-9220-4134b05d4f57
- Flip Matrix
- Flip Matrix
-
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11050
78
28
-
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11064
- 2
- Data matrix to flip
- 2523c816-93d0-41ff-984f-d483c8d06d39
- Data
- Data
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- 4841119b-6919-43e0-9f72-21da2df86cd2
- 1
-
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25
24
-
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- 2
- Flipped data matrix
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- Data
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-
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25
24
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
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- Evaluate Length
- Evaluate Length
-
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11166
149
64
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- Curve to evaluate
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- Curve
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-
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71
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-
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- Length factor for curve evaluation
- 41621117-2021-49ba-b487-d4aedbf29fcc
- Length
- Length
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- 0
-
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71
20
-
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- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 6fde47c3-b049-48e7-8b58-c109b354b541
- Normalized
- Normalized
- false
- 0
-
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11208
71
20
-
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- 1
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- Point at the specified length
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- Point
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-
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50
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- Tangent vector at the specified length
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- Tangent
- Tangent
- false
- 0
-
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50
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-
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- Curve parameter at the specified length
- 40681e3e-d54e-4273-8f43-cb3b1e82e2a7
- Parameter
- Parameter
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- 0
-
-11703
11208
50
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-
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- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- c18ab1b9-2a48-4a82-ad16-5826ac595810
- Polar Array
- Polar Array
-
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11166
210
101
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- Base geometry
- 70d7df57-4bbf-4f78-a202-18f595656711
- Geometry
- Geometry
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- 6d5abb8c-34bb-4407-a45c-9ce18f00de6a
- 1
-
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11168
132
20
-
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- Polar array plane
- b77e7644-9474-45f8-8d72-86b458c1342c
- Plane
- Plane
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- 0
-
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132
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-
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- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 5ef9e7db-f254-4c4e-b867-db39b0fadee0
- Count
- Count
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- a36a42bd-2f18-4380-938f-847c2f934c7b
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-
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132
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- Clean Duplicate Lines
- Removes duplicate lines in a list
- true
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- Clean Duplicate Lines
- Clean Duplicate Lines
-
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176
64
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12640
- 1
- Lines to check for duplicates
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- Lines
- Lines
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-
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113
30
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- Distance check tolerance
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- Tolerance
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- 0
-
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12640
113
30
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12655
- 1
- 1
- {0}
- 1.1641532182693481E-10
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- Filtered lines
- 8b5e702e-fe66-451c-9d6f-7d420bedd33f
- Lines
- Lines
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- 0
-
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12610
35
20
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12620
- 1
- Mapped Indices
- 9011f340-ae92-43f4-a4fb-968ae4580415
- Indices
- Indices
- false
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-
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12630
35
20
-
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12640
- 1
- The value will be false if the line was removed.
- da5155c9-1172-46c4-b4a9-07b1097720a4
- Status
- Status
- false
- 0
-
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12650
35
20
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12660
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- cf17a6b1-9c69-4bea-8df9-aad3926d8a47
- Flip Matrix
- Flip Matrix
-
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12611
94
28
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12625
- 2
- Data matrix to flip
- c9416a33-92e7-4e2a-80fe-f44883ffe9a1
- Data
- Data
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-
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25
24
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- Flipped data matrix
- 6f6badfc-3548-443d-9915-3e528056c5b5
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- Data
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-
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12613
41
24
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- 030b487b-a566-476f-96a4-a0ae2ad283af
- a48ac930-c378-48dc-84da-26b2af9d8302
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- Applies Stroke properties to a Shape
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- Stroke
- Stroke
-
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12230
212
104
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- A Graphic Plus Shape, or a Curve, Brep, Mesh
- 34b44bad-c225-4b90-b038-e617f66ae7fc
- Shape / Geometry
- Shape / Geometry
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12232
136
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12242
- The stroke color
- d912eabb-dfeb-4a6a-b312-3f8c3bf774ab
- Color
- Color
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- 6b1ee9b3-d527-4f0a-92bd-29a66feb6eb4
- 1
-
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12252
136
20
-
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12262
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- 1
- {0}
-
255;21;0;255
- The stroke weight
- 4f659f4c-b3dc-4f09-8c77-586f57958c2d
- Weight
- Weight
- true
- 49b99293-9239-4d70-ac77-3ddc2b030bf1
- 1
-
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12272
136
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12282
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- {0}
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- The stroke pattern
- ef45aa1c-d7c6-4913-b5e1-161fe8dcf0ef
- Pattern
- Pattern
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-
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136
20
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12302
- The shape to be used at the end of open path
- e2318e1e-0fc0-4106-b936-440f351dc506
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- End Cap
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-
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12312
136
20
-
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12322
- 1
- 1
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- A Graphic Plus Shape Object
- true
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- Shape
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-
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12232
48
100
-
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12282
- 071c3940-a12d-4b77-bb23-42b5d3314a0d
- Clean Tree
- Removed all null and invalid items from a data tree.
- true
- 8d6e19cf-5301-40e0-9013-0f3c19973e8d
- Clean Tree
- Clean Tree
-
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12206
135
84
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12248
- 4
- cb95db89-6165-43b6-9c41-5702bc5bf137
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Remove null items from the tree.
- 37690dac-ffe2-4835-91c1-6066f9d76ce6
- Remove Nulls
- Remove Nulls
- false
- 0
-
-6827
12208
83
20
-
-6785.5
12218
- 1
- 1
- {0}
- true
- Remove invalid items from the tree.
- 5f89493f-76d6-4ac4-adc7-86ed0ddc2372
- Remove Invalid
- Remove Invalid
- false
- 0
-
-6827
12228
83
20
-
-6785.5
12238
- 1
- 1
- {0}
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- Remove empty branches from the tree.
- 23999a55-d9d8-4b4a-a9ee-dbc53c88822f
- Remove Empty
- Remove Empty
- false
- 0
-
-6827
12248
83
20
-
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12258
- 1
- 1
- {0}
- true
- 2
- Data tree to clean
- 5ed0643b-cc55-4597-aa6e-00dabf7f5245
- Tree
- Tree
- false
- 86daba70-2a3b-4a1c-a39a-106f8460fa2c
- 1
-
-6827
12268
83
20
-
-6785.5
12278
- 2
- Spotless data tree
- d9b8d3cd-38bf-4578-839b-0a5ece250025
- Tree
- Tree
- false
- 0
-
-6720
12208
24
80
-
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12248
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 1d88f662-fdb9-46e3-aba0-0600f05c556e
- Evaluate Length
- Evaluate Length
-
-11840
12172
149
64
-
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12204
- Curve to evaluate
- 71194947-2b03-49f9-ab5d-65d964bcd2b9
- Curve
- Curve
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-
-11838
12174
71
20
-
-11802.5
12184
- Length factor for curve evaluation
- d94423ca-039f-488d-9398-40cffcfd5922
- Length
- Length
- false
- 0
-
-11838
12194
71
20
-
-11802.5
12204
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 31c42d3d-1753-4b35-943e-43531dc22aa7
- Normalized
- Normalized
- false
- 0
-
-11838
12214
71
20
-
-11802.5
12224
- 1
- 1
- {0}
- true
- Point at the specified length
- 191da902-2fe2-4d59-8b2c-16c5826ea944
- Point
- Point
- false
- 0
-
-11743
12174
50
20
-
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12184
- Tangent vector at the specified length
- 07a10d0e-6b2c-44ef-8a93-6203590c3610
- Tangent
- Tangent
- false
- 0
-
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12194
50
20
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12204
- Curve parameter at the specified length
- 7e2d691f-777b-4ec3-aae8-d55f21baabc7
- Parameter
- Parameter
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-
-11743
12214
50
20
-
-11718
12224
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- a4cfa61c-6315-48e5-9748-41e6bff9dd13
- PolyLine
- PolyLine
-
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12218
106
44
-
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12240
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- Polyline vertex points
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- Vertices
- Vertices
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- 1
-
-8212
12220
40
20
-
-8192
12230
- Close polyline
- ab68209f-a1ff-4f85-b7ea-656a5a0329f4
- Closed
- Closed
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- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
12240
40
20
-
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12250
- 1
- 1
- {0}
- true
- Resulting polyline
- cd6a97f5-0587-4a71-8611-22fa2aaa3840
- Polyline
- Polyline
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- 0
-
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12220
38
40
-
-8129
12240
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- a3b55592-fb58-4505-8d3e-ab1d2a9afc89
- PolyLine
- PolyLine
-
-8214
12289
106
44
-
-8160
12311
- 1
- Polyline vertex points
- 3874fd28-3057-4ffb-ba94-3127f375a64f
- Vertices
- Vertices
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- b85a0de9-2fc9-4d83-b473-65417e5818a7
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-
-8212
12291
40
20
-
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12301
- Close polyline
- b26490d5-64cf-465f-828d-9f73b4aaa9fd
- Closed
- Closed
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- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
12311
40
20
-
-8192
12321
- 1
- 1
- {0}
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- Resulting polyline
- 76e975c9-0859-4963-aa3d-d26213287614
- Polyline
- Polyline
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-
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12291
38
40
-
-8129
12311
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 11da8026-3f02-41e4-9eb5-39a041af1bc2
- Merge
- Merge
-
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12246
90
64
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12278
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- Data stream 1
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- Data 1
- D1
- true
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31
20
-
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12258
- 2
- Data stream 2
- ba5eb681-4804-4efe-99dc-e0aba500cae3
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- Data 2
- D2
- true
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- 1
-
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12268
31
20
-
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12278
- 2
- Data stream 3
- 1462617e-c980-43e5-aaaf-c5eb62f9d386
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- Data 3
- D3
- true
- 0
-
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12288
31
20
-
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12298
- 2
- Result of merge
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- Result
- Result
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- 0
-
-7396
12248
31
60
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12278
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 46c45a5b-1d60-4374-9874-2f46a8395bfd
- Polar Array
- Polar Array
-
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12172
210
101
-
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12223
- Base geometry
- 79e27294-499c-48b8-b416-6eb8a231dc2d
- Geometry
- Geometry
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- 191da902-2fe2-4d59-8b2c-16c5826ea944
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12174
132
20
-
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- Polar array plane
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- Plane
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12194
132
37
-
-10879
12212.5
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- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- b0a02c9a-7404-49e4-aeb1-880997243f13
- Count
- Count
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- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
12231
132
20
-
-10879
12241
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 6b988194-31d4-4a16-bff3-69f35e94bfb3
- Angle
- Angle
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- 0
- false
-
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12251
132
20
-
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12261
- 1
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- {0}
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- Arrayed geometry
- 5f8c5ef7-ad16-42a2-9646-930141e9f464
- Geometry
- Geometry
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- 0
-
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12174
50
48
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-10764
12198.25
- 1
- Transformation data
- 07080f9d-e2dc-4146-85a8-d6b8d2c26ccc
- Transform
- Transform
- false
- 0
-
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12222
50
49
-
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12246.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- f2a326c1-b3a7-4936-920d-cbeb331af976
- Cull Duplicates
- Cull Duplicates
-
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12181
180
64
-
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12213
- 1
- Points to operate on
- 7dd1da8a-1ac4-405f-ba33-3ffa8d49bced
- Points
- Points
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-
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12183
113
30
-
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12198
- Proximity tolerance distance
- 516ab31e-150a-4206-ac59-d027de7e7dc9
- Tolerance
- Tolerance
- false
- 0
-
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12213
113
30
-
-9223.5
12228
- 1
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- {0}
- 1.1641532182693481E-10
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- Culled points
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- Points
- Points
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-
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12183
39
20
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12193
- 1
- Index map of culled points
- 03482fd5-7707-4c90-a892-c48c8986bf4d
- Indices
- Indices
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-
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12203
39
20
-
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12213
- 1
- Number of input points represented by this output point
- bb151dbc-c2c0-4200-900b-e7f3fda48e26
- Valence
- Valence
- false
- 0
-
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12223
39
20
-
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12233
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- a8d83d35-138a-41e7-93a1-22679fbc2439
- Flip Matrix
- Flip Matrix
-
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12184
78
28
-
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12198
- 2
- Data matrix to flip
- 6a2d23e5-4524-4315-aa03-8d7a304f84df
- Data
- Data
- false
- 5f8c5ef7-ad16-42a2-9646-930141e9f464
- 1
-
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12186
25
24
-
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12198
- 2
- Flipped data matrix
- 260ef8d4-4714-4379-8975-e217a4b3e16f
- Data
- Data
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- 0
-
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12186
25
24
-
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12198
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
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- Evaluate Length
- Evaluate Length
-
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12300
149
64
-
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12332
- Curve to evaluate
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- Curve
- Curve
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- 1
-
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12302
71
20
-
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12312
- Length factor for curve evaluation
- d8d5579c-f745-42c3-a9d0-85590e33ca5d
- Length
- Length
- false
- 0
-
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12322
71
20
-
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12332
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 27bdb2b4-cd9c-4657-bef0-d7aca6df4452
- Normalized
- Normalized
- false
- 0
-
-11838
12342
71
20
-
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12352
- 1
- 1
- {0}
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- Point at the specified length
- e4bc4020-8141-4a7d-b4cb-85d0f43fc123
- Point
- Point
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- 0
-
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12302
50
20
-
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12312
- Tangent vector at the specified length
- c6d2c933-7f36-46d4-89e5-f4c6e5ecc676
- Tangent
- Tangent
- false
- 0
-
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12322
50
20
-
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- Curve parameter at the specified length
- 5d82cdc3-80d2-4fed-911b-2b37c1ba5ff5
- Parameter
- Parameter
- false
- 0
-
-11743
12342
50
20
-
-11718
12352
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 656f3f38-f138-4399-bd8e-f76e210d93db
- Polar Array
- Polar Array
-
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12300
210
101
-
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12351
- Base geometry
- 74d9afb7-f715-4f56-9e7c-4befd1ec6bec
- Geometry
- Geometry
- true
- e4bc4020-8141-4a7d-b4cb-85d0f43fc123
- 1
-
-10945
12302
132
20
-
-10879
12312
- Polar array plane
- 13e96852-2bc7-42aa-bea0-f7014624b7ad
- Plane
- Plane
- false
- 0
-
-10945
12322
132
37
-
-10879
12340.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 1900298c-8c94-443b-a46c-64ab0635c3ec
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
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12359
132
20
-
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12369
- 1
- 1
- {0}
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- c8109293-a159-4ec9-803f-8c4aebce2c29
- Angle
- Angle
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- false
-
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12379
132
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-
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12389
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- a0c3207e-4300-4c24-9bfe-549b0e7ca683
- Geometry
- Geometry
- false
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-
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12302
50
48
-
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12326.25
- 1
- Transformation data
- 1495dbc3-4e89-4e94-b07f-ff833ead1c24
- Transform
- Transform
- false
- 0
-
-10789
12350
50
49
-
-10764
12374.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- ef20db35-fd60-4f9e-8053-80f3336e480b
- Cull Duplicates
- Cull Duplicates
-
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12297
180
64
-
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12329
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-
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13790
- 1
- Mapped Indices
- 2b1d52f6-8468-482f-93ae-9a4fb9d1dfc6
- Indices
- Indices
- false
- 0
-
-9141
13800
35
20
-
-9123.5
13810
- 1
- The value will be false if the line was removed.
- 5ad77074-97fc-4dbb-b9e4-b3d9597dd378
- Status
- Status
- false
- 0
-
-9141
13820
35
20
-
-9123.5
13830
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- ca92eeb5-0c1f-4fdb-8882-fcb7e9eed882
- Flip Matrix
- Flip Matrix
-
-9989
13781
94
28
-
-9950
13795
- 2
- Data matrix to flip
- 6fe0510d-52f1-4682-b8e2-55283346ca39
- Data
- Data
- false
- 3fc82d5e-7989-4464-a1f2-e35bc71b39be
- 1
-
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13783
25
24
-
-9974.5
13795
- 2
- Flipped data matrix
- 476dc671-a77d-48fd-b913-946bc603a6d2
- 1
- Data
- Data
- false
- 0
-
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13783
41
24
-
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13795
- 030b487b-a566-476f-96a4-a0ae2ad283af
- a48ac930-c378-48dc-84da-26b2af9d8302
- Stroke
- Applies Stroke properties to a Shape
- true
- d9bae896-445c-4f81-909c-3e75cff0dee7
- Stroke
- Stroke
-
-5995
13400
212
104
-
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13452
- A Graphic Plus Shape, or a Curve, Brep, Mesh
- 5227eb0b-46ca-49c2-aa4a-62b85816bf74
- Shape / Geometry
- Shape / Geometry
- false
- 986a4ea2-6d71-45b5-9958-cb0ff67dcc00
- 1
-
-5993
13402
136
20
-
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13412
- The stroke color
- 4cab67c0-dd40-4838-90b1-7d135e74022f
- Color
- Color
- true
- bb795819-a6c6-4e55-a863-d50b1c8f2040
- 1
-
-5993
13422
136
20
-
-5925
13432
- 1
- 1
- {0}
-
255;21;0;255
- The stroke weight
- 1692da24-7c26-4ac1-b9d4-5a848ee2e055
- Weight
- Weight
- true
- 49b99293-9239-4d70-ac77-3ddc2b030bf1
- 1
-
-5993
13442
136
20
-
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13452
- 1
- 1
- {0}
- 9
- 1
- The stroke pattern
- ee818197-99d6-4bff-9b99-ad9871e7514a
- Pattern
- Pattern
- true
- 0
-
-5993
13462
136
20
-
-5925
13472
- The shape to be used at the end of open path
- 36c8692e-b4aa-40d8-80ef-840011193383
- End Cap
- End Cap
- true
- 0
-
-5993
13482
136
20
-
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13492
- 1
- 1
- {0}
- 2
- A Graphic Plus Shape Object
- true
- 17e7981a-444d-404f-8e9c-f8a208a76a17
- 1
- Shape
- Shape
- false
- 0
-
-5833
13402
48
100
-
-5817
13452
- 071c3940-a12d-4b77-bb23-42b5d3314a0d
- Clean Tree
- Removed all null and invalid items from a data tree.
- true
- 1699dbef-9b40-4a59-89b2-d575c6368831
- Clean Tree
- Clean Tree
-
-6829
13376
135
84
-
-6732
13418
- 4
- cb95db89-6165-43b6-9c41-5702bc5bf137
- cb95db89-6165-43b6-9c41-5702bc5bf137
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Remove null items from the tree.
- 82022d82-52cb-4ae7-a2a4-6cb10355572a
- Remove Nulls
- Remove Nulls
- false
- 0
-
-6827
13378
83
20
-
-6785.5
13388
- 1
- 1
- {0}
- true
- Remove invalid items from the tree.
- 425eefb3-38bd-43a4-b684-54e7df9d61c7
- Remove Invalid
- Remove Invalid
- false
- 0
-
-6827
13398
83
20
-
-6785.5
13408
- 1
- 1
- {0}
- true
- Remove empty branches from the tree.
- 087a5d61-135f-4c98-8922-7c44e9c1852b
- Remove Empty
- Remove Empty
- false
- 0
-
-6827
13418
83
20
-
-6785.5
13428
- 1
- 1
- {0}
- true
- 2
- Data tree to clean
- 95c1bf20-b4f3-4e52-a270-b8458219a044
- Tree
- Tree
- false
- 89600b18-6607-4de2-a6a1-41f9e72185f2
- 1
-
-6827
13438
83
20
-
-6785.5
13448
- 2
- Spotless data tree
- 986a4ea2-6d71-45b5-9958-cb0ff67dcc00
- Tree
- Tree
- false
- 0
-
-6720
13378
24
80
-
-6708
13418
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 2a568e96-3e71-4a50-9fd1-3e4ce13e70f5
- Evaluate Length
- Evaluate Length
-
-11840
13342
149
64
-
-11755
13374
- Curve to evaluate
- 4c239629-3b78-433c-9285-5438917e626c
- Curve
- Curve
- false
- 609b5d6e-7b75-4e1a-8a12-faf652c3c682
- 1
-
-11838
13344
71
20
-
-11802.5
13354
- Length factor for curve evaluation
- 6feaf1a9-b8e6-4c02-b75f-cc8982d91726
- Length
- Length
- false
- 0
-
-11838
13364
71
20
-
-11802.5
13374
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 573b8081-cb2c-4cd2-b6be-ed5a8fbd352b
- Normalized
- Normalized
- false
- 0
-
-11838
13384
71
20
-
-11802.5
13394
- 1
- 1
- {0}
- true
- Point at the specified length
- f9679928-c7a3-4d10-94a2-003b0737b7c6
- Point
- Point
- false
- 0
-
-11743
13344
50
20
-
-11718
13354
- Tangent vector at the specified length
- 2efa796c-48c3-4be3-92b6-4fe5af425c3b
- Tangent
- Tangent
- false
- 0
-
-11743
13364
50
20
-
-11718
13374
- Curve parameter at the specified length
- 95fd76a4-439d-4d69-852d-8097fac143e9
- Parameter
- Parameter
- false
- 0
-
-11743
13384
50
20
-
-11718
13394
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- 962f300e-d13a-4cfb-8775-3332be224a3b
- PolyLine
- PolyLine
-
-8214
13388
106
44
-
-8160
13410
- 1
- Polyline vertex points
- eb63dc90-64a2-4093-83ed-e8aeacb0a275
- Vertices
- Vertices
- false
- d88c6a85-1583-416c-834b-da43cc4b6ff9
- 1
-
-8212
13390
40
20
-
-8192
13400
- Close polyline
- df21ddec-7724-4a3d-a7a2-7cc64268a33c
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
13410
40
20
-
-8192
13420
- 1
- 1
- {0}
- true
- Resulting polyline
- 22e94c20-c8b5-422f-ad04-0b643f130e29
- Polyline
- Polyline
- false
- 0
-
-8148
13390
38
40
-
-8129
13410
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- 543bb0df-8039-457a-aa73-cedeb032ee5c
- PolyLine
- PolyLine
-
-8214
13459
106
44
-
-8160
13481
- 1
- Polyline vertex points
- a4af2146-6a13-4cc3-9bcc-8866e2bf66c1
- Vertices
- Vertices
- false
- 302ea92b-a67e-4cda-af4d-800b4f829f22
- 1
-
-8212
13461
40
20
-
-8192
13471
- Close polyline
- be2b82c1-1411-4f86-9681-02d93a113ff2
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
13481
40
20
-
-8192
13491
- 1
- 1
- {0}
- false
- Resulting polyline
- 660bf03b-9848-4309-bb76-41f35d76729e
- Polyline
- Polyline
- false
- 0
-
-8148
13461
38
40
-
-8129
13481
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 18c4dff3-a6c4-4b00-a9d7-b6caf73180f0
- Merge
- Merge
-
-7453
13416
90
64
-
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13448
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- a1d0bbe6-b200-40ce-bbea-0fac78383987
- false
- Data 1
- D1
- true
- 22e94c20-c8b5-422f-ad04-0b643f130e29
- 1
-
-7451
13418
31
20
-
-7435.5
13428
- 2
- Data stream 2
- d6695219-64fc-4e9d-9bd2-d27ff3ece270
- false
- Data 2
- D2
- true
- 660bf03b-9848-4309-bb76-41f35d76729e
- 1
-
-7451
13438
31
20
-
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13448
- 2
- Data stream 3
- 1852818a-0863-4c53-838f-65738bb00e53
- false
- Data 3
- D3
- true
- 0
-
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13458
31
20
-
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13468
- 2
- Result of merge
- 89600b18-6607-4de2-a6a1-41f9e72185f2
- Result
- Result
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- 0
-
-7396
13418
31
60
-
-7380.5
13448
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- eded538d-9e14-4b3b-8511-012d710a4202
- Polar Array
- Polar Array
-
-10947
13342
210
101
-
-10801
13393
- Base geometry
- 25ef12c1-95e7-4f96-82d7-df17d6607e32
- Geometry
- Geometry
- true
- f9679928-c7a3-4d10-94a2-003b0737b7c6
- 1
-
-10945
13344
132
20
-
-10879
13354
- Polar array plane
- 2b96e6d5-9614-40b1-acf2-34b19ce4ca4f
- Plane
- Plane
- false
- 0
-
-10945
13364
132
37
-
-10879
13382.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 58eccda3-d61f-4806-9e7b-4cac97b391c3
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
13401
132
20
-
-10879
13411
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- b9d8fa57-8017-48c7-b39b-951608e6d413
- Angle
- Angle
- false
- 0
- false
-
-10945
13421
132
20
-
-10879
13431
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- 99daf0cc-a43f-450a-b90f-272d1153ba8a
- Geometry
- Geometry
- false
- 0
-
-10789
13344
50
48
-
-10764
13368.25
- 1
- Transformation data
- 7768115b-1c42-4ff7-b6fe-8ba943768f3e
- Transform
- Transform
- false
- 0
-
-10789
13392
50
49
-
-10764
13416.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- 53dadc15-5b5d-4d86-a82b-9c99c687e599
- Cull Duplicates
- Cull Duplicates
-
-9282
13351
180
64
-
-9155
13383
- 1
- Points to operate on
- d5a21377-8e13-40ca-87b6-c3ce316d4284
- Points
- Points
- false
- 7a082c6f-007d-4f4d-88ae-98d6d5d1f17a
- 1
-
-9280
13353
113
30
-
-9223.5
13368
- Proximity tolerance distance
- ea47d601-9b7a-485a-aafe-60fe26ddaae6
- Tolerance
- Tolerance
- false
- 0
-
-9280
13383
113
30
-
-9223.5
13398
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- d88c6a85-1583-416c-834b-da43cc4b6ff9
- Points
- Points
- false
- 0
-
-9143
13353
39
20
-
-9123.5
13363
- 1
- Index map of culled points
- cd46575f-a154-4a06-a33b-9c164ea46ccc
- Indices
- Indices
- false
- 0
-
-9143
13373
39
20
-
-9123.5
13383
- 1
- Number of input points represented by this output point
- 52a6aaa7-6e75-4b91-9c70-46767f1da2b5
- Valence
- Valence
- false
- 0
-
-9143
13393
39
20
-
-9123.5
13403
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- 39875cab-f112-4d5e-8493-bea84926f5e6
- Flip Matrix
- Flip Matrix
-
-9989
13358
78
28
-
-9950
13372
- 2
- Data matrix to flip
- 3d6273bb-a233-47ac-b046-6c1b482618bd
- Data
- Data
- false
- 99daf0cc-a43f-450a-b90f-272d1153ba8a
- 1
-
-9987
13360
25
24
-
-9974.5
13372
- 2
- Flipped data matrix
- b8290ff5-cc18-4aed-b419-0380c7314516
- Data
- Data
- false
- 0
-
-9938
13360
25
24
-
-9925.5
13372
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 9646f763-5f33-4816-a637-889100b707fe
- Evaluate Length
- Evaluate Length
-
-11840
13470
149
64
-
-11755
13502
- Curve to evaluate
- 7d56b35b-39f2-4ff4-9691-a2043e2af748
- Curve
- Curve
- false
- 68ed2259-a880-4020-a4fa-5102d6548b24
- 1
-
-11838
13472
71
20
-
-11802.5
13482
- Length factor for curve evaluation
- ace16953-c438-4ca0-ba26-fc3f7c426e21
- Length
- Length
- false
- 0
-
-11838
13492
71
20
-
-11802.5
13502
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- d0d762db-efb7-4e56-a6cc-c8251bf47a0a
- Normalized
- Normalized
- false
- 0
-
-11838
13512
71
20
-
-11802.5
13522
- 1
- 1
- {0}
- true
- Point at the specified length
- 3224f531-fcc0-4069-98d6-72111ade37c7
- Point
- Point
- false
- 0
-
-11743
13472
50
20
-
-11718
13482
- Tangent vector at the specified length
- ebb51016-99ab-421c-be6c-e0ccc7108e15
- Tangent
- Tangent
- false
- 0
-
-11743
13492
50
20
-
-11718
13502
- Curve parameter at the specified length
- e3ea3454-734c-453f-8949-03fc9323b976
- Parameter
- Parameter
- false
- 0
-
-11743
13512
50
20
-
-11718
13522
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 6477d210-711d-4699-93a8-6bde781c3f7a
- Polar Array
- Polar Array
-
-10947
13470
210
101
-
-10801
13521
- Base geometry
- 5494aaf9-a934-4696-bab5-ff2557ead832
- Geometry
- Geometry
- true
- 3224f531-fcc0-4069-98d6-72111ade37c7
- 1
-
-10945
13472
132
20
-
-10879
13482
- Polar array plane
- 2e21f5f8-44c0-43a3-ab9f-91911709aba1
- Plane
- Plane
- false
- 0
-
-10945
13492
132
37
-
-10879
13510.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- f3bae605-ca2c-4b34-9ab3-182d03df58f9
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
13529
132
20
-
-10879
13539
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- e4f278f6-967a-45ed-8b63-cbdd1fa95005
- Angle
- Angle
- false
- 0
- false
-
-10945
13549
132
20
-
-10879
13559
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- a2b0bb3c-0097-402a-a4da-133df59b5297
- Geometry
- Geometry
- false
- 0
-
-10789
13472
50
48
-
-10764
13496.25
- 1
- Transformation data
- 9bd95ff5-7cf4-41aa-bb33-086c3c6f832c
- Transform
- Transform
- false
- 0
-
-10789
13520
50
49
-
-10764
13544.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- 19ab8151-885d-4701-9426-377b97fa68f9
- Cull Duplicates
- Cull Duplicates
-
-9282
13467
180
64
-
-9155
13499
- 1
- Points to operate on
- 444c54dc-822b-4c33-b7f8-eaebc591c3a8
- Points
- Points
- false
- 7bb1462d-d332-4e9e-bc1f-eed4c3dc7d71
- 1
-
-9280
13469
113
30
-
-9223.5
13484
- Proximity tolerance distance
- fbe566d9-1562-406e-89f1-8b8d3b53cc0e
- Tolerance
- Tolerance
- false
- 0
-
-9280
13499
113
30
-
-9223.5
13514
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- 302ea92b-a67e-4cda-af4d-800b4f829f22
- Points
- Points
- false
- 0
-
-9143
13469
39
20
-
-9123.5
13479
- 1
- Index map of culled points
- fd1d8802-5c55-41dd-8bc4-19864163e1ef
- Indices
- Indices
- false
- 0
-
-9143
13489
39
20
-
-9123.5
13499
- 1
- Number of input points represented by this output point
- 31bd5227-a6b1-4246-adbb-e85cd52b5f32
- Valence
- Valence
- false
- 0
-
-9143
13509
39
20
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- 99f710a2-4a47-432f-bbf7-db034f59fc42
- 1
- Data
- Data
- false
- 0
-
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14862
41
24
-
-9925.5
14874
- 030b487b-a566-476f-96a4-a0ae2ad283af
- a48ac930-c378-48dc-84da-26b2af9d8302
- Stroke
- Applies Stroke properties to a Shape
- true
- fab76d4a-5a00-4349-a6d7-5aac9c9035c4
- Stroke
- Stroke
-
-5995
14479
212
104
-
-5845
14531
- A Graphic Plus Shape, or a Curve, Brep, Mesh
- f96b899f-6d17-4937-8f63-a809a943d375
- Shape / Geometry
- Shape / Geometry
- false
- 69102192-8a57-4804-a0d3-0f12214359c7
- 1
-
-5993
14481
136
20
-
-5925
14491
- The stroke color
- 37088d6f-cb86-472e-b59c-298e8c3b88e8
- Color
- Color
- true
- 90b10fb7-d93e-4fe9-a16e-d27f72355c55
- 1
-
-5993
14501
136
20
-
-5925
14511
- 1
- 1
- {0}
-
255;21;0;255
- The stroke weight
- 5d3df0ae-99af-4eb3-8f55-5439e25d08bb
- Weight
- Weight
- true
- 49b99293-9239-4d70-ac77-3ddc2b030bf1
- 1
-
-5993
14521
136
20
-
-5925
14531
- 1
- 1
- {0}
- 9
- 1
- The stroke pattern
- 7c3d7436-8f2d-4740-9a2c-123b15572ae8
- Pattern
- Pattern
- true
- 0
-
-5993
14541
136
20
-
-5925
14551
- The shape to be used at the end of open path
- b4e90716-dda7-4592-9911-55d9d9fd3a41
- End Cap
- End Cap
- true
- 0
-
-5993
14561
136
20
-
-5925
14571
- 1
- 1
- {0}
- 2
- A Graphic Plus Shape Object
- true
- 96d02cee-1dd7-497e-bef2-a5e5a52e14e3
- 1
- Shape
- Shape
- false
- 0
-
-5833
14481
48
100
-
-5817
14531
- 071c3940-a12d-4b77-bb23-42b5d3314a0d
- Clean Tree
- Removed all null and invalid items from a data tree.
- true
- d15949ac-a1da-47b3-86a8-9f28d03b5c04
- Clean Tree
- Clean Tree
-
-6829
14455
135
84
-
-6732
14497
- 4
- cb95db89-6165-43b6-9c41-5702bc5bf137
- cb95db89-6165-43b6-9c41-5702bc5bf137
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Remove null items from the tree.
- 4d4dedc4-2352-41a1-8350-e1cc1bf20efd
- Remove Nulls
- Remove Nulls
- false
- 0
-
-6827
14457
83
20
-
-6785.5
14467
- 1
- 1
- {0}
- true
- Remove invalid items from the tree.
- 0f1d3e8b-05d6-45ba-bbf2-139486b34e72
- Remove Invalid
- Remove Invalid
- false
- 0
-
-6827
14477
83
20
-
-6785.5
14487
- 1
- 1
- {0}
- true
- Remove empty branches from the tree.
- 3e272bff-968f-4253-8a11-2d7cb50d412a
- Remove Empty
- Remove Empty
- false
- 0
-
-6827
14497
83
20
-
-6785.5
14507
- 1
- 1
- {0}
- true
- 2
- Data tree to clean
- 3610081d-8934-446f-92dc-991628c7f4f7
- Tree
- Tree
- false
- 1156a5b5-586e-4002-90e3-56fd218dc983
- 1
-
-6827
14517
83
20
-
-6785.5
14527
- 2
- Spotless data tree
- 69102192-8a57-4804-a0d3-0f12214359c7
- Tree
- Tree
- false
- 0
-
-6720
14457
24
80
-
-6708
14497
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 4ece2bad-44ab-4c65-9d83-11d636649fbe
- Evaluate Length
- Evaluate Length
-
-11840
14421
149
64
-
-11755
14453
- Curve to evaluate
- 0ae644e7-2700-4121-a09c-3b824092af2d
- Curve
- Curve
- false
- 589e948c-d0d2-4b05-9c56-6855d5c435b4
- 1
-
-11838
14423
71
20
-
-11802.5
14433
- Length factor for curve evaluation
- 139ce10c-5675-48e2-adef-f0796c46b695
- Length
- Length
- false
- 0
-
-11838
14443
71
20
-
-11802.5
14453
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 59dc6693-6391-4968-aae0-add876133636
- Normalized
- Normalized
- false
- 0
-
-11838
14463
71
20
-
-11802.5
14473
- 1
- 1
- {0}
- true
- Point at the specified length
- 8b3658f2-d9eb-4ff3-b6d5-fb133de62fd5
- Point
- Point
- false
- 0
-
-11743
14423
50
20
-
-11718
14433
- Tangent vector at the specified length
- 5e197156-76d9-43cf-b626-93ee38784c34
- Tangent
- Tangent
- false
- 0
-
-11743
14443
50
20
-
-11718
14453
- Curve parameter at the specified length
- 57204c6e-0312-4149-962d-bf94a514fd6e
- Parameter
- Parameter
- false
- 0
-
-11743
14463
50
20
-
-11718
14473
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- 44683d76-8a35-44ed-949b-30141fdf9139
- PolyLine
- PolyLine
-
-8214
14467
106
44
-
-8160
14489
- 1
- Polyline vertex points
- bc3381be-1c43-4988-a4a2-1b7183e7605d
- Vertices
- Vertices
- false
- 7d3159e2-523c-4dad-9669-e5097446dc9c
- 1
-
-8212
14469
40
20
-
-8192
14479
- Close polyline
- 3781906a-5d20-4be8-9143-adc5210374eb
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
14489
40
20
-
-8192
14499
- 1
- 1
- {0}
- true
- Resulting polyline
- 9fc4e560-6e7f-46af-bebe-161db37b149c
- Polyline
- Polyline
- false
- 0
-
-8148
14469
38
40
-
-8129
14489
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- e13f38a0-10b9-4295-9d8b-bf9e69299e2c
- PolyLine
- PolyLine
-
-8214
14538
106
44
-
-8160
14560
- 1
- Polyline vertex points
- 1efe0a7d-5261-4210-b5a9-0e5d96d0ae22
- Vertices
- Vertices
- false
- 86f52d0b-8cb1-4fb8-a748-317c08627eed
- 1
-
-8212
14540
40
20
-
-8192
14550
- Close polyline
- 652f2e02-6e5e-4c66-9318-5bba8a2b2634
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
14560
40
20
-
-8192
14570
- 1
- 1
- {0}
- false
- Resulting polyline
- 5a89161b-d07b-4559-aad8-0c85fd87afc4
- Polyline
- Polyline
- false
- 0
-
-8148
14540
38
40
-
-8129
14560
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 5690b6d3-0968-4fb0-8da8-d12b7a6a3897
- Merge
- Merge
-
-7453
14495
90
64
-
-7408
14527
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- 8b1c5b0e-e5eb-465d-9702-1093981df655
- false
- Data 1
- D1
- true
- 9fc4e560-6e7f-46af-bebe-161db37b149c
- 1
-
-7451
14497
31
20
-
-7435.5
14507
- 2
- Data stream 2
- 03a65eea-a460-4b1e-9b61-c36549e42e97
- false
- Data 2
- D2
- true
- 5a89161b-d07b-4559-aad8-0c85fd87afc4
- 1
-
-7451
14517
31
20
-
-7435.5
14527
- 2
- Data stream 3
- b507d38b-ef29-4a0c-979a-2c3398d21215
- false
- Data 3
- D3
- true
- 0
-
-7451
14537
31
20
-
-7435.5
14547
- 2
- Result of merge
- 1156a5b5-586e-4002-90e3-56fd218dc983
- Result
- Result
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- 0
-
-7396
14497
31
60
-
-7380.5
14527
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 3cbb6bd3-1171-4d43-aac6-9a7e1e1fb4fb
- Polar Array
- Polar Array
-
-10947
14421
210
101
-
-10801
14472
- Base geometry
- 6ccaf25d-7140-4e9c-a0a6-f3c4c8a0c919
- Geometry
- Geometry
- true
- 8b3658f2-d9eb-4ff3-b6d5-fb133de62fd5
- 1
-
-10945
14423
132
20
-
-10879
14433
- Polar array plane
- 1ffb22d4-e7b0-4fe5-955a-cad72ce9a392
- Plane
- Plane
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- 0
-
-10945
14443
132
37
-
-10879
14461.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 92e5f868-11e5-48fa-8de8-acff82ca7778
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
14480
132
20
-
-10879
14490
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 70c31ff3-400e-4319-96a7-b438dcd589b7
- Angle
- Angle
- false
- 0
- false
-
-10945
14500
132
20
-
-10879
14510
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- c945af59-6bd4-4bbb-a72f-3179c172e355
- Geometry
- Geometry
- false
- 0
-
-10789
14423
50
48
-
-10764
14447.25
- 1
- Transformation data
- 5d5a0247-2f57-4e08-b0e9-ad6b237ec22c
- Transform
- Transform
- false
- 0
-
-10789
14471
50
49
-
-10764
14495.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- 82907fbc-f2b6-47b2-9250-f01eb07b4cd0
- Cull Duplicates
- Cull Duplicates
-
-9282
14430
180
64
-
-9155
14462
- 1
- Points to operate on
- e53103ee-684d-4f00-a313-bfb1b013f471
- Points
- Points
- false
- 50866164-631f-4e5d-97a6-38052c2a1f58
- 1
-
-9280
14432
113
30
-
-9223.5
14447
- Proximity tolerance distance
- 8f4fadfa-d919-47fc-a4a8-6a1a41c1cd3f
- Tolerance
- Tolerance
- false
- 0
-
-9280
14462
113
30
-
-9223.5
14477
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- 7d3159e2-523c-4dad-9669-e5097446dc9c
- Points
- Points
- false
- 0
-
-9143
14432
39
20
-
-9123.5
14442
- 1
- Index map of culled points
- 2f7f49f5-cec2-4013-99eb-ae1add62cfae
- Indices
- Indices
- false
- 0
-
-9143
14452
39
20
-
-9123.5
14462
- 1
- Number of input points represented by this output point
- 31775788-8e35-466b-9c61-4bd7db70d4d2
- Valence
- Valence
- false
- 0
-
-9143
14472
39
20
-
-9123.5
14482
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- 887c7df8-f58a-477f-a647-9f7f4df65452
- Flip Matrix
- Flip Matrix
-
-9989
14433
78
28
-
-9950
14447
- 2
- Data matrix to flip
- e161da66-411b-49e5-a5c4-241e250daa13
- Data
- Data
- false
- c945af59-6bd4-4bbb-a72f-3179c172e355
- 1
-
-9987
14435
25
24
-
-9974.5
14447
- 2
- Flipped data matrix
- 6bce306e-3a53-4b29-ad04-d2586045e5e4
- Data
- Data
- false
- 0
-
-9938
14435
25
24
-
-9925.5
14447
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- f0566591-ad31-4f9b-8266-088bd2369cfb
- Evaluate Length
- Evaluate Length
-
-11840
14549
149
64
-
-11755
14581
- Curve to evaluate
- b55f07b5-dd49-4738-9a2d-0eadabe5b2bf
- Curve
- Curve
- false
- 0ba93922-a608-4ac3-8ad6-de58e4e01a8f
- 1
-
-11838
14551
71
20
-
-11802.5
14561
- Length factor for curve evaluation
- 35207d3d-0e24-4aa4-94dc-55c0c7dce157
- Length
- Length
- false
- 0
-
-11838
14571
71
20
-
-11802.5
14581
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 451b4f84-441d-437f-bbc9-09be16c9b9e2
- Normalized
- Normalized
- false
- 0
-
-11838
14591
71
20
-
-11802.5
14601
- 1
- 1
- {0}
- true
- Point at the specified length
- 8a32f9b6-c5ff-4b22-a7ce-4daf530718c6
- Point
- Point
- false
- 0
-
-11743
14551
50
20
-
-11718
14561
- Tangent vector at the specified length
- 88e55a93-6497-4929-8829-74d77865bdd2
- Tangent
- Tangent
- false
- 0
-
-11743
14571
50
20
-
-11718
14581
- Curve parameter at the specified length
- b3381614-7d25-460c-9f4a-5a095ffe7c5b
- Parameter
- Parameter
- false
- 0
-
-11743
14591
50
20
-
-11718
14601
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- f812766a-18a1-4288-8d6e-7dcd02316302
- Polar Array
- Polar Array
-
-10947
14549
210
101
-
-10801
14600
- Base geometry
- 2a420b45-7129-4afd-8394-4bb24cd94bc2
- Geometry
- Geometry
- true
- 8a32f9b6-c5ff-4b22-a7ce-4daf530718c6
- 1
-
-10945
14551
132
20
-
-10879
14561
- Polar array plane
- f6b5b82e-1c7b-45b4-b48e-eaba2f79ef21
- Plane
- Plane
- false
- 0
-
-10945
14571
132
37
-
-10879
14589.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 9dc6bcca-bb46-4c8c-acec-2d144c59a035
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
14608
132
20
-
-10879
14618
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 8145af6d-c7ef-42bc-9049-9e286624e582
- Angle
- Angle
- false
- 0
- false
-
-10945
14628
132
20
-
-10879
14638
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- 0cf31f4b-5998-48de-89ee-310044622439
- Geometry
- Geometry
- false
- 0
-
-10789
14551
50
48
-
-10764
14575.25
- 1
- Transformation data
- 4501ab18-2ebe-4371-9271-3c94f76f3856
- Transform
- Transform
- false
- 0
-
-10789
14599
50
49
-
-10764
14623.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- 438847c3-266b-464a-b75f-f7f717333f9f
- Cull Duplicates
- Cull Duplicates
-
-9282
14546
180
64
-
-9155
14578
- 1
- Points to operate on
- 84319d3c-f942-4ab8-800d-a053b27f4f8f
- Points
- Points
- false
- 2c9cd1a3-de48-4ce5-be20-36b483914987
- 1
-
-9280
14548
113
30
-
-9223.5
14563
- Proximity tolerance distance
- aecc6dd9-a2ff-4422-843d-1ea3dba089c9
- Tolerance
- Tolerance
- false
- 0
-
-9280
14578
113
30
-
-9223.5
14593
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- 86f52d0b-8cb1-4fb8-a748-317c08627eed
- Points
- Points
- false
- 0
-
-9143
14548
39
20
-
-9123.5
14558
- 1
- Index map of culled points
- 7f4c1da7-cf48-4f2b-84d1-b59c02c7b8a4
- Indices
- Indices
- false
- 0
-
-9143
14568
39
20
-
-9123.5
14578
- 1
- Number of input points represented by this output point
- 2cff57af-6ab2-48bb-a829-85522e937e81
- Valence
- Valence
- false
- 0
-
-9143
14588
39
20
-
-9123.5
14598
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- 52d631d9-d9d0-4b66-ab7b-8f3bebae1b5f
- Flip Matrix
- Flip Matrix
-
-9989
14561
78
28
-
-9950
14575
- 2
- Data matrix to flip
- bc99306f-722d-43b7-8a49-f99d3689965d
- Data
- Data
- false
- 0cf31f4b-5998-48de-89ee-310044622439
- 1
-
-9987
14563
25
24
-
-9974.5
14575
- 2
- Flipped data matrix
- dff4cfd5-06dd-4644-a8fa-9833eff92395
- Data
- Data
- false
- 0
-
-9938
14563
25
24
-
-9925.5
14575
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
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- 592109e0-df36-4b5c-94a0-cbd7baf26a6b
- Color
- Color
- true
- 6c6fb177-f0ba-4860-8ebe-5a36c08f4a14
- 1
-
-5993
15544
136
20
-
-5925
15554
- 1
- 1
- {0}
-
255;21;0;255
- The stroke weight
- fd4f3b5f-203a-4333-b50e-b9209eee2034
- Weight
- Weight
- true
- 49b99293-9239-4d70-ac77-3ddc2b030bf1
- 1
-
-5993
15564
136
20
-
-5925
15574
- 1
- 1
- {0}
- 9
- 1
- The stroke pattern
- 5ae57219-d11a-4fc8-b9fd-b79e756353f0
- Pattern
- Pattern
- true
- 0
-
-5993
15584
136
20
-
-5925
15594
- The shape to be used at the end of open path
- 35002325-80cb-42cd-ab96-b47be73fd80b
- End Cap
- End Cap
- true
- 0
-
-5993
15604
136
20
-
-5925
15614
- 1
- 1
- {0}
- 2
- A Graphic Plus Shape Object
- true
- 9e12c21c-2e26-4f4c-9f08-61fe6812af57
- 1
- Shape
- Shape
- false
- 0
-
-5833
15524
48
100
-
-5817
15574
- 071c3940-a12d-4b77-bb23-42b5d3314a0d
- Clean Tree
- Removed all null and invalid items from a data tree.
- true
- 34879ece-4417-40d3-aeed-ab5ce1ef32db
- Clean Tree
- Clean Tree
-
-6829
15498
135
84
-
-6732
15540
- 4
- cb95db89-6165-43b6-9c41-5702bc5bf137
- cb95db89-6165-43b6-9c41-5702bc5bf137
- cb95db89-6165-43b6-9c41-5702bc5bf137
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Remove null items from the tree.
- 09ff579e-ffeb-4ffc-aa55-759e5e193f50
- Remove Nulls
- Remove Nulls
- false
- 0
-
-6827
15500
83
20
-
-6785.5
15510
- 1
- 1
- {0}
- true
- Remove invalid items from the tree.
- d0961bf5-04f9-4781-a961-e55a0a67b97d
- Remove Invalid
- Remove Invalid
- false
- 0
-
-6827
15520
83
20
-
-6785.5
15530
- 1
- 1
- {0}
- true
- Remove empty branches from the tree.
- 0a9d932d-83ff-428b-86a5-943c1d0e8dd5
- Remove Empty
- Remove Empty
- false
- 0
-
-6827
15540
83
20
-
-6785.5
15550
- 1
- 1
- {0}
- true
- 2
- Data tree to clean
- 9950c6f4-47d2-4cdc-b0d7-7d1f51ee7e3c
- Tree
- Tree
- false
- 5f0869c0-9bc2-45ba-b9bc-7bd6ce42b320
- 1
-
-6827
15560
83
20
-
-6785.5
15570
- 2
- Spotless data tree
- 30e8295c-3a26-49df-aef1-101d48a13c2b
- Tree
- Tree
- false
- 0
-
-6720
15500
24
80
-
-6708
15540
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- a1ee8a14-8a22-497a-8572-ee31d0c10743
- Evaluate Length
- Evaluate Length
-
-11840
15464
149
64
-
-11755
15496
- Curve to evaluate
- 7ff01179-ea77-4869-ad68-0c9536995559
- Curve
- Curve
- false
- b7cf406c-d92d-4328-9b8e-d0e00d9cb12a
- 1
-
-11838
15466
71
20
-
-11802.5
15476
- Length factor for curve evaluation
- b3590d82-b7a8-40b8-adec-cee0fef3d24e
- Length
- Length
- false
- 0
-
-11838
15486
71
20
-
-11802.5
15496
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 80ea4189-9088-46a2-9b7e-85ab6608bc9b
- Normalized
- Normalized
- false
- 0
-
-11838
15506
71
20
-
-11802.5
15516
- 1
- 1
- {0}
- true
- Point at the specified length
- 8139e3a6-7ad0-46d9-9244-0ef47834cdd8
- Point
- Point
- false
- 0
-
-11743
15466
50
20
-
-11718
15476
- Tangent vector at the specified length
- fabfec87-a549-4543-a177-dfd67fb18d4d
- Tangent
- Tangent
- false
- 0
-
-11743
15486
50
20
-
-11718
15496
- Curve parameter at the specified length
- aa5bc4ba-a857-4868-b36d-46b8926f3f6d
- Parameter
- Parameter
- false
- 0
-
-11743
15506
50
20
-
-11718
15516
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- 34133586-fdfd-447f-8e4c-9fc9bdf5f0e4
- PolyLine
- PolyLine
-
-8214
15510
106
44
-
-8160
15532
- 1
- Polyline vertex points
- 96f12eda-fc94-4baf-bb18-9e67bc34d3d0
- Vertices
- Vertices
- false
- 3fe4e5ef-c18f-4e75-b445-569590545a8e
- 1
-
-8212
15512
40
20
-
-8192
15522
- Close polyline
- 13e0205c-351a-499d-b36c-dd55a61bf7c2
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
15532
40
20
-
-8192
15542
- 1
- 1
- {0}
- true
- Resulting polyline
- 8db4425b-83e2-40c4-87be-14b2cc962742
- Polyline
- Polyline
- false
- 0
-
-8148
15512
38
40
-
-8129
15532
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- 54552803-fcb7-47e3-85b6-f8522ddca3a7
- PolyLine
- PolyLine
-
-8214
15581
106
44
-
-8160
15603
- 1
- Polyline vertex points
- a7f94eda-da8a-4121-a5d9-4d6fec2c6da4
- Vertices
- Vertices
- false
- 374bcae9-a010-466e-9d02-a93c7753a60d
- 1
-
-8212
15583
40
20
-
-8192
15593
- Close polyline
- 39f77415-45d3-4a69-b629-5b6a3423aeff
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
15603
40
20
-
-8192
15613
- 1
- 1
- {0}
- false
- Resulting polyline
- 1292e96a-373f-4615-878b-73b06199438a
- Polyline
- Polyline
- false
- 0
-
-8148
15583
38
40
-
-8129
15603
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 55428555-7510-47e7-b34a-f9e35f2c711d
- Merge
- Merge
-
-7453
15538
90
64
-
-7408
15570
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- df518e4a-92c8-4acf-b41a-3c852981d346
- false
- Data 1
- D1
- true
- 8db4425b-83e2-40c4-87be-14b2cc962742
- 1
-
-7451
15540
31
20
-
-7435.5
15550
- 2
- Data stream 2
- 330680e9-fb57-4a38-8d98-f9a023615dc6
- false
- Data 2
- D2
- true
- 1292e96a-373f-4615-878b-73b06199438a
- 1
-
-7451
15560
31
20
-
-7435.5
15570
- 2
- Data stream 3
- b6c59f4a-7a29-43c4-9880-663646ed73c7
- false
- Data 3
- D3
- true
- 0
-
-7451
15580
31
20
-
-7435.5
15590
- 2
- Result of merge
- 5f0869c0-9bc2-45ba-b9bc-7bd6ce42b320
- Result
- Result
- false
- 0
-
-7396
15540
31
60
-
-7380.5
15570
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 16f260a6-3bfa-4177-9700-dbd2b19bd644
- Polar Array
- Polar Array
-
-10947
15464
210
101
-
-10801
15515
- Base geometry
- 8ca529ad-ddb5-459f-b521-fa1dfb48965c
- Geometry
- Geometry
- true
- 8139e3a6-7ad0-46d9-9244-0ef47834cdd8
- 1
-
-10945
15466
132
20
-
-10879
15476
- Polar array plane
- 82ce54f1-9164-4aad-accc-a41175a73316
- Plane
- Plane
- false
- 0
-
-10945
15486
132
37
-
-10879
15504.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 3a48ed06-c501-413e-8978-b8dc1375db5e
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
15523
132
20
-
-10879
15533
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- fcc69342-30ed-45ed-8833-c6aba74d4db8
- Angle
- Angle
- false
- 0
- false
-
-10945
15543
132
20
-
-10879
15553
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- 1ff37f60-11fa-4998-b09a-100ed37fa4b5
- Geometry
- Geometry
- false
- 0
-
-10789
15466
50
48
-
-10764
15490.25
- 1
- Transformation data
- a6adc338-b316-4e18-a5aa-0992c712727d
- Transform
- Transform
- false
- 0
-
-10789
15514
50
49
-
-10764
15538.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- f9de9d1c-9d35-4a4f-981b-2fa481c0d868
- Cull Duplicates
- Cull Duplicates
-
-9282
15473
180
64
-
-9155
15505
- 1
- Points to operate on
- f2f14759-281c-41b9-82df-a03f03285868
- Points
- Points
- false
- e87642af-d7f4-4c8a-badf-e9466bf0b858
- 1
-
-9280
15475
113
30
-
-9223.5
15490
- Proximity tolerance distance
- 0353c331-b4a5-43b1-a20e-7a0b43bfd2e5
- Tolerance
- Tolerance
- false
- 0
-
-9280
15505
113
30
-
-9223.5
15520
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- 3fe4e5ef-c18f-4e75-b445-569590545a8e
- Points
- Points
- false
- 0
-
-9143
15475
39
20
-
-9123.5
15485
- 1
- Index map of culled points
- 9fde27e7-a677-4304-a18f-c2676737d8b0
- Indices
- Indices
- false
- 0
-
-9143
15495
39
20
-
-9123.5
15505
- 1
- Number of input points represented by this output point
- 6f6bcb5e-d048-436c-aa76-f32f093b621e
- Valence
- Valence
- false
- 0
-
-9143
15515
39
20
-
-9123.5
15525
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- af6b5adb-149b-4459-9dbf-137428ec716c
- Flip Matrix
- Flip Matrix
-
-9989
15476
78
28
-
-9950
15490
- 2
- Data matrix to flip
- 4728b728-dde9-45ad-a962-6b8d3dc26dd4
- Data
- Data
- false
- 1ff37f60-11fa-4998-b09a-100ed37fa4b5
- 1
-
-9987
15478
25
24
-
-9974.5
15490
- 2
- Flipped data matrix
- 82f35a99-14e7-47ff-900d-a54c896b2c78
- Data
- Data
- false
- 0
-
-9938
15478
25
24
-
-9925.5
15490
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- e5d41782-59e3-422f-8dc1-39d1a4c31f64
- Evaluate Length
- Evaluate Length
-
-11840
15592
149
64
-
-11755
15624
- Curve to evaluate
- fdab1e59-e8a6-4ca8-a6fb-ffc5e907e94c
- Curve
- Curve
- false
- 11ceca9b-30b2-4213-b35d-85e5be45643a
- 1
-
-11838
15594
71
20
-
-11802.5
15604
- Length factor for curve evaluation
- 5e598139-29f5-4d32-9b67-673c1e882f4e
- Length
- Length
- false
- 0
-
-11838
15614
71
20
-
-11802.5
15624
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 2e3a9590-1657-41a4-b518-a093017be771
- Normalized
- Normalized
- false
- 0
-
-11838
15634
71
20
-
-11802.5
15644
- 1
- 1
- {0}
- true
- Point at the specified length
- 473b46fc-6cd7-4a94-8ca5-b05277cc1d8b
- Point
- Point
- false
- 0
-
-11743
15594
50
20
-
-11718
15604
- Tangent vector at the specified length
- 52a87992-e8a0-4f0f-8c05-55153f97d863
- Tangent
- Tangent
- false
- 0
-
-11743
15614
50
20
-
-11718
15624
- Curve parameter at the specified length
- b130efa6-1671-4814-8eb7-15fed1ab4d7d
- Parameter
- Parameter
- false
- 0
-
-11743
15634
50
20
-
-11718
15644
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- e09ba9cc-f215-4476-a87b-f3262cdad00d
- Polar Array
- Polar Array
-
-10947
15592
210
101
-
-10801
15643
- Base geometry
- 08a3a0e5-ab76-4f85-9791-6ef4be0b9757
- Geometry
- Geometry
- true
- 473b46fc-6cd7-4a94-8ca5-b05277cc1d8b
- 1
-
-10945
15594
132
20
-
-10879
15604
- Polar array plane
- 4437a4ce-48b8-4487-86a8-909e6464789d
- Plane
- Plane
- false
- 0
-
-10945
15614
132
37
-
-10879
15632.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- cecf5e04-5877-483f-b076-ffa1ae57d765
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
15651
132
20
-
-10879
15661
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 7ec85d43-0d12-4cf3-9654-7e21d2143d62
- Angle
- Angle
- false
- 0
- false
-
-10945
15671
132
20
-
-10879
15681
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- 81827009-40cb-4a9d-81cd-2bdaedb2032c
- Geometry
- Geometry
- false
- 0
-
-10789
15594
50
48
-
-10764
15618.25
- 1
- Transformation data
- 1dfc6ef3-24e3-4422-8c65-70641f970550
- Transform
- Transform
- false
- 0
-
-10789
15642
50
49
-
-10764
15666.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- fe0fc6e9-e5f7-4110-a364-f3890ca938b3
- Cull Duplicates
- Cull Duplicates
-
-9282
15589
180
64
-
-9155
15621
- 1
- Points to operate on
- a3e211f7-c4ad-4867-8204-98cdbb3340d2
- Points
- Points
- false
- 0156a723-76fc-4a7c-8320-97d012f1e76e
- 1
-
-9280
15591
113
30
-
-9223.5
15606
- Proximity tolerance distance
- f068b07d-0de1-42d7-8d2f-b5669a2a9a29
- Tolerance
- Tolerance
- false
- 0
-
-9280
15621
113
30
-
-9223.5
15636
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- 374bcae9-a010-466e-9d02-a93c7753a60d
- Points
- Points
- false
- 0
-
-9143
15591
39
20
-
-9123.5
15601
- 1
- Index map of culled points
- a878cb80-e1bb-449d-8caf-1900890ade4e
- Indices
- Indices
- false
- 0
-
-9143
15611
39
20
-
-9123.5
15621
- 1
- Number of input points represented by this output point
- 7f3f23e9-8b29-441d-86b2-02da645e2b58
- Valence
- Valence
- false
- 0
-
-9143
15631
39
20
-
-9123.5
15641
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- e35cce34-d103-45dc-93d5-42459738908e
- Flip Matrix
- Flip Matrix
-
-9989
15604
78
28
-
-9950
15618
- 2
- Data matrix to flip
- 091a163d-9635-43b4-a769-1e708bfc0749
- Data
- Data
- false
- 81827009-40cb-4a9d-81cd-2bdaedb2032c
- 1
-
-9987
15606
25
24
-
-9974.5
15618
- 2
- Flipped data matrix
- 535c49a7-eac1-4cc0-b695-b51aef04808e
- Data
- Data
- false
- 0
-
-9938
15606
25
24
-
-9925.5
15618
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- b7cf406c-d92d-4328-9b8e-d0e00d9cb12a
- Relay
- false
- 55870985-56ce-4fce-8489-d8cae772ce2d
- 1
-
-12721
15483
40
16
-
-12701
15491
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 11ceca9b-30b2-4213-b35d-85e5be45643a
- Relay
- false
- d5ac0a7f-71d1-455e-9221-37229abd3ab6
- 1
-
-12721
15631
40
16
-
-12701
15639
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- b7cf406c-d92d-4328-9b8e-d0e00d9cb12a
- 11ceca9b-30b2-4213-b35d-85e5be45643a
- 2
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16775
136
20
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16785
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- A Graphic Plus Shape Object
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- 1
- Shape
- Shape
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-
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16695
48
100
-
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16745
- 071c3940-a12d-4b77-bb23-42b5d3314a0d
- Clean Tree
- Removed all null and invalid items from a data tree.
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- Clean Tree
- Clean Tree
-
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16669
135
84
-
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16711
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- cb95db89-6165-43b6-9c41-5702bc5bf137
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- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Remove null items from the tree.
- 6782aa1f-a2bf-49dd-b7f4-cc4138a697d5
- Remove Nulls
- Remove Nulls
- false
- 0
-
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16671
83
20
-
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16681
- 1
- 1
- {0}
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- Remove invalid items from the tree.
- ee053123-99d9-4c17-9a85-9dd25085669a
- Remove Invalid
- Remove Invalid
- false
- 0
-
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16691
83
20
-
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16701
- 1
- 1
- {0}
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- Remove empty branches from the tree.
- 6c263a19-fcf7-42c1-a05f-6297b0615acd
- Remove Empty
- Remove Empty
- false
- 0
-
-6827
16711
83
20
-
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16721
- 1
- 1
- {0}
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- Data tree to clean
- 0786fe94-2693-4e2f-a530-ba3f25454d65
- Tree
- Tree
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- 1
-
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16731
83
20
-
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16741
- 2
- Spotless data tree
- bc172503-953b-42d6-9f6c-01e9cdbf6da9
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- Tree
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-
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16671
24
80
-
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16711
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 02737097-b8b1-41db-98c1-fc50380663f5
- Evaluate Length
- Evaluate Length
-
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16635
149
64
-
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- Curve to evaluate
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- 2f545125-747a-4904-9cb7-05bc0727e11d
- 1
-
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16637
71
20
-
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- Length factor for curve evaluation
- 97db9dfb-d83f-43bc-aa6c-74315e99c866
- Length
- Length
- false
- 0
-
-11838
16657
71
20
-
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16667
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- b97a0607-d9c4-424b-bf06-962419323acb
- Normalized
- Normalized
- false
- 0
-
-11838
16677
71
20
-
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16687
- 1
- 1
- {0}
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- Point at the specified length
- f264c5ca-1559-4c36-92b0-2d97232c46ad
- Point
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- 0
-
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16637
50
20
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16647
- Tangent vector at the specified length
- 8a1eee52-af70-4242-b077-63631f092dd9
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-
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16657
50
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- Curve parameter at the specified length
- 2f54eb4c-185e-4cf1-a1fd-9e1135d4fa77
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-
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16677
50
20
-
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16687
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- e0561d63-9b13-44a4-b9ea-99a9cb1c13e2
- PolyLine
- PolyLine
-
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16681
106
44
-
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16703
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- Polyline vertex points
- 528e6586-6ecf-40b3-a743-0d6f9fe0bfbb
- Vertices
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- 1c9cf092-7009-4949-8f7f-f9236794e9fe
- 1
-
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16683
40
20
-
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16693
- Close polyline
- d00b5e18-77f2-45e7-9369-4182df4cb587
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-
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16703
40
20
-
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16713
- 1
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- {0}
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- Resulting polyline
- ced6c00c-4ac4-4fb8-8f0e-7f436ffdab13
- Polyline
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-
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16683
38
40
-
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16703
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- dbe88505-9526-40fb-9e1b-1d78e902c27b
- PolyLine
- PolyLine
-
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16752
106
44
-
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16774
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- Polyline vertex points
- 1c49aba5-694f-462f-a831-11170af53bec
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- 9349eef4-58b8-408a-a0c5-e579ddf40767
- 1
-
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16754
40
20
-
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16764
- Close polyline
- 8233a329-2e4f-44bd-96f8-223124a1bc74
- Closed
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- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
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16774
40
20
-
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16784
- 1
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- {0}
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- Resulting polyline
- 1207f491-dbbb-4093-b3ad-3c374a18a952
- Polyline
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-
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16754
38
40
-
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16774
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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- b45fdf0c-87e6-4bba-86a6-8fed07429172
- Merge
- Merge
-
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16709
90
64
-
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16741
- 3
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- Data stream 1
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- Data 1
- D1
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- 1
-
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16711
31
20
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- 2
- Data stream 2
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- Data 2
- D2
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- 1
-
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16731
31
20
-
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16741
- 2
- Data stream 3
- 038257c2-b3a0-4434-aaa7-dda6c93c1836
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- D3
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-
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16751
31
20
-
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- Result of merge
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-
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16711
31
60
-
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16741
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 7c40bd65-f93b-4501-8448-a9384bf4ddce
- Polar Array
- Polar Array
-
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16635
210
101
-
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- Base geometry
- 09e1489a-38c3-4586-a46e-83107b7f002a
- Geometry
- Geometry
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-
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16637
132
20
-
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- Polar array plane
- 764fb3a2-368f-4b97-93ef-08ec580daf72
- Plane
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-
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16657
132
37
-
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- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
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- Count
- Count
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- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
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16694
132
20
-
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16704
- 1
- 1
- {0}
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 6800c134-8e8f-44a1-9722-8a746870d50a
- Angle
- Angle
- false
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- false
-
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16714
132
20
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- 1
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- {0}
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- Arrayed geometry
- 23d7f84a-bc05-46db-b2ea-0f7b23826746
- Geometry
- Geometry
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-
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16637
50
48
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- Transformation data
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- Transform
- Transform
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-
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16685
50
49
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16709.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- 9887bd44-97bb-4024-9f89-c1252834018a
- Cull Duplicates
- Cull Duplicates
-
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16644
180
64
-
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16676
- 1
- Points to operate on
- e79e43c6-1e2b-46be-8454-f2a5d0a9e7a3
- Points
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- d3503a0a-25d4-40f9-b392-12c89e516f16
- 1
-
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16646
113
30
-
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- Proximity tolerance distance
- 26c15905-27a6-4859-83f1-faa8fec300f6
- Tolerance
- Tolerance
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- 0
-
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16676
113
30
-
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16691
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- 1c9cf092-7009-4949-8f7f-f9236794e9fe
- Points
- Points
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-
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16646
39
20
-
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- 1
- Index map of culled points
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-
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16666
39
20
-
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16676
- 1
- Number of input points represented by this output point
- a8c0bb0c-fdc4-47b0-b658-845db3b475f1
- Valence
- Valence
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-
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16686
39
20
-
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16696
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- b5d93ecd-2ef1-4b68-b74f-be0a5cca1d2b
- Flip Matrix
- Flip Matrix
-
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16647
78
28
-
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16661
- 2
- Data matrix to flip
- 32e8694b-97fc-455a-9d25-12c6106e2bec
- Data
- Data
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- 23d7f84a-bc05-46db-b2ea-0f7b23826746
- 1
-
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25
24
-
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- 2
- Flipped data matrix
- 6de70eee-64cc-4d17-ad90-5e27d252e6e5
- Data
- Data
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-
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16649
25
24
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16661
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- e44419a3-3e7b-451b-ad2b-befe815a1642
- Evaluate Length
- Evaluate Length
-
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16763
149
64
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- Curve to evaluate
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- Curve
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- 1
-
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16765
71
20
-
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- Length factor for curve evaluation
- 7d649dc5-fa68-41b5-aa84-d93b3189a6d1
- Length
- Length
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- 0
-
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16785
71
20
-
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- 1
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- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 39b0d8c4-19df-4207-ad20-b62f10657d75
- Normalized
- Normalized
- false
- 0
-
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16805
71
20
-
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16815
- 1
- 1
- {0}
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- Point at the specified length
- e2dea9a1-a097-4340-b25a-e37176bd7740
- Point
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- 0
-
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16765
50
20
-
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- Tangent vector at the specified length
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- Tangent
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- false
- 0
-
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16785
50
20
-
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- Curve parameter at the specified length
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- Parameter
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- 0
-
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16805
50
20
-
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16815
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- af57175f-b87d-4d4b-865c-8de67eb6f48c
- Polar Array
- Polar Array
-
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16763
210
101
-
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16814
- Base geometry
- f22d30c8-4b4b-4cea-9ec0-0edbc8672688
- Geometry
- Geometry
- true
- e2dea9a1-a097-4340-b25a-e37176bd7740
- 1
-
-10945
16765
132
20
-
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16775
- Polar array plane
- 99756a04-f589-4b3d-9f05-522affd1de67
- Plane
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- 0
-
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16785
132
37
-
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16803.5
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- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 840959dc-1048-4e82-9559-88d1802886bb
- Count
- Count
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- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
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16822
132
20
-
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- 1
- 1
- {0}
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 31487356-e2ba-44a1-a310-e5120d4ff151
- Angle
- Angle
- false
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- false
-
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16842
132
20
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16852
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- 90282863-2ca2-4350-a4f0-8ba50b257398
- Geometry
- Geometry
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- 0
-
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16765
50
48
-
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16789.25
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- Transformation data
- b7364e57-5ffd-4559-9ef0-07aedc662109
- Transform
- Transform
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-
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16813
50
49
-
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16837.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- a2446556-35a4-42a2-992b-4c5465def5ca
- Cull Duplicates
- Cull Duplicates
-
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16760
180
64
-
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16792
- 1
- Points to operate on
- 176aa800-b998-4c0a-9503-57c602bcda9e
- Points
- Points
- false
- 4dfda7fb-90ae-4f9e-9305-08baf23c2d50
- 1
-
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16762
113
30
-
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16777
- Proximity tolerance distance
- cb095ab5-a871-4ea2-ae23-443a1fbeee58
- Tolerance
- Tolerance
- false
- 0
-
-9280
16792
113
30
-
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16807
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- 9349eef4-58b8-408a-a0c5-e579ddf40767
- Points
- Points
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- 0
-
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16762
39
20
-
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16772
- 1
- Index map of culled points
- 26dd8312-d3ae-477c-9e0c-1009f60f5c95
- Indices
- Indices
- false
- 0
-
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16782
39
20
-
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16792
- 1
- Number of input points represented by this output point
- c419d320-3140-47d8-8d0d-fc6df26eece9
- Valence
- Valence
- false
- 0
-
-9143
16802
39
20
-
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16812
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- 14074e3a-0c4f-43d3-8ef6-6d6fa0d55c7b
- Flip Matrix
- Flip Matrix
-
-9989
16775
78
28
-
-9950
16789
- 2
- Data matrix to flip
- 4bf40f1b-5da2-40d3-a958-12d3c3d9ad5e
- Data
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- 90282863-2ca2-4350-a4f0-8ba50b257398
- 1
-
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16777
25
24
-
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16789
- 2
- Flipped data matrix
- 87fdae07-bcf5-489b-89b1-aec57ffa9c17
- Data
- Data
- false
- 0
-
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16777
25
24
-
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16789
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
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- A wire relay object
- 2f545125-747a-4904-9cb7-05bc0727e11d
- Relay
- false
- 598eec7f-8923-45a9-bb06-9d39462f5b42
- 1
-
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16653
40
16
-
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16661
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
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- A wire relay object
- 29946d34-0db3-4cc0-bbb0-27c79f7c8eb9
- Relay
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- 5307cc5a-5b6c-4d5a-a89d-43ca13f2f506
- 1
-
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16801
40
16
-
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16809
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 2f545125-747a-4904-9cb7-05bc0727e11d
- 29946d34-0db3-4cc0-bbb0-27c79f7c8eb9
- 2
- 0d584a9b-bb53-4bf2-ba3f-1146f1cf993e
- Group
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 39efa66c-03c8-4671-9b59-f399b410e8a9
- Merge
- Merge
-
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16840
106
84
-
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16882
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Data stream 1
- dc7177b2-1d07-4d1a-a04d-b20518108921
- false
- Data 1
- D1
- true
- e8350921-bce9-4dab-befe-7c6e8c133aeb
- 1
-
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16842
31
20
-
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16852
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17772
83
20
-
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17782
- 1
- 1
- {0}
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- Remove invalid items from the tree.
- bfa076b6-fb4b-40d6-be9f-67fb884e8d6c
- Remove Invalid
- Remove Invalid
- false
- 0
-
-6827
17792
83
20
-
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17802
- 1
- 1
- {0}
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- Remove empty branches from the tree.
- 329824a3-1ac9-4d57-9735-a29b88f515c5
- Remove Empty
- Remove Empty
- false
- 0
-
-6827
17812
83
20
-
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17822
- 1
- 1
- {0}
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- 2
- Data tree to clean
- a38d6fc8-c43a-4b4a-9553-733995115f34
- Tree
- Tree
- false
- 625c9542-af93-4f62-aed4-573bb02b38ee
- 1
-
-6827
17832
83
20
-
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17842
- 2
- Spotless data tree
- 60a0df0e-bd21-4cdf-a3f4-16fb4176c3ae
- Tree
- Tree
- false
- 0
-
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17772
24
80
-
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17812
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- fd943d99-68a3-4898-b506-68be67cd4cf2
- Evaluate Length
- Evaluate Length
-
-11840
17736
149
64
-
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17768
- Curve to evaluate
- 21446a6b-2f2d-4abc-a8c3-b71cb39432c9
- Curve
- Curve
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- 1504e2b4-e091-439c-ace1-a3e70d52839d
- 1
-
-11838
17738
71
20
-
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17748
- Length factor for curve evaluation
- 80653072-e8be-483c-a4a2-f30d6bd332e8
- Length
- Length
- false
- 0
-
-11838
17758
71
20
-
-11802.5
17768
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- ced79bb1-e361-42a4-89f7-a85a93ea6d28
- Normalized
- Normalized
- false
- 0
-
-11838
17778
71
20
-
-11802.5
17788
- 1
- 1
- {0}
- true
- Point at the specified length
- 7b21e7c4-e20e-484d-818d-a663768d8508
- Point
- Point
- false
- 0
-
-11743
17738
50
20
-
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17748
- Tangent vector at the specified length
- c4a0d5f8-e9f9-4097-afb7-0f148a2fc879
- Tangent
- Tangent
- false
- 0
-
-11743
17758
50
20
-
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17768
- Curve parameter at the specified length
- 74969c75-1dd5-4e4d-ad34-4225f6ae85e0
- Parameter
- Parameter
- false
- 0
-
-11743
17778
50
20
-
-11718
17788
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- a2436e8a-9975-43b5-8abc-89e175cb9bcd
- PolyLine
- PolyLine
-
-8214
17782
106
44
-
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17804
- 1
- Polyline vertex points
- 5062ab4b-7936-4329-a512-9a867699e9d8
- Vertices
- Vertices
- false
- efa1592b-bbf9-4d3b-9415-7562319eaad4
- 1
-
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17784
40
20
-
-8192
17794
- Close polyline
- e11365c4-bde5-47cf-845b-e1c75c83629b
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
17804
40
20
-
-8192
17814
- 1
- 1
- {0}
- true
- Resulting polyline
- 4713e6bd-a9c4-4e05-984f-ea9377a0e684
- Polyline
- Polyline
- false
- 0
-
-8148
17784
38
40
-
-8129
17804
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- fb1f3eff-3a65-4bda-9df9-54842bb38cd9
- PolyLine
- PolyLine
-
-8214
17853
106
44
-
-8160
17875
- 1
- Polyline vertex points
- 4bd91e38-4208-49d6-bc7c-3b81596309b1
- Vertices
- Vertices
- false
- ffd681a6-6a65-4c1f-9085-7033988b0b32
- 1
-
-8212
17855
40
20
-
-8192
17865
- Close polyline
- 02d0af90-446c-49a4-af64-6a50853b6df9
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8212
17875
40
20
-
-8192
17885
- 1
- 1
- {0}
- false
- Resulting polyline
- d0ac4694-9cbb-408e-a7c4-fe13ed702009
- Polyline
- Polyline
- false
- 0
-
-8148
17855
38
40
-
-8129
17875
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- a8f9a73d-06ad-4ff7-a9f6-5af2990ec6f6
- Merge
- Merge
-
-7453
17810
90
64
-
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17842
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
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- 2
- Data stream 1
- 9acadea0-bd13-47ca-b3be-42b06838ca1e
- false
- Data 1
- D1
- true
- 4713e6bd-a9c4-4e05-984f-ea9377a0e684
- 1
-
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17812
31
20
-
-7435.5
17822
- 2
- Data stream 2
- 8a35825f-12c6-4369-b4a8-095ea5853786
- false
- Data 2
- D2
- true
- d0ac4694-9cbb-408e-a7c4-fe13ed702009
- 1
-
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17832
31
20
-
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17842
- 2
- Data stream 3
- 2ace1d5c-cb95-4db9-8c22-afa659881bf5
- false
- Data 3
- D3
- true
- 0
-
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17852
31
20
-
-7435.5
17862
- 2
- Result of merge
- 625c9542-af93-4f62-aed4-573bb02b38ee
- Result
- Result
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-
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17812
31
60
-
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17842
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- c605e62b-d6b6-4e76-91bb-368d21f313f5
- Polar Array
- Polar Array
-
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17736
210
101
-
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17787
- Base geometry
- 9e87d25c-f926-4f0e-9456-35e638186c1d
- Geometry
- Geometry
- true
- 7b21e7c4-e20e-484d-818d-a663768d8508
- 1
-
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17738
132
20
-
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17748
- Polar array plane
- 697e3b87-e310-46b2-807a-5dab2983da65
- Plane
- Plane
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-
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17758
132
37
-
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17776.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- 50e55b22-9ec1-4670-b88a-e1f7bcdf83c0
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
17795
132
20
-
-10879
17805
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 574e6b39-ce22-4257-b82d-a817ecf2b838
- Angle
- Angle
- false
- 0
- false
-
-10945
17815
132
20
-
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17825
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- 2b5ab43a-bf29-46b7-97f8-b9a1e5f5505d
- Geometry
- Geometry
- false
- 0
-
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17738
50
48
-
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17762.25
- 1
- Transformation data
- 9d851bcf-7c36-4420-a968-df9aea2eeabe
- Transform
- Transform
- false
- 0
-
-10789
17786
50
49
-
-10764
17810.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- 22c8303a-ab41-4056-b0f0-d75617008c03
- Cull Duplicates
- Cull Duplicates
-
-9282
17745
180
64
-
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17777
- 1
- Points to operate on
- db3726a7-ccba-464a-9d6c-4365a485eaa6
- Points
- Points
- false
- 3b0f4ca8-63aa-4144-82ce-e47ac4bbb7e5
- 1
-
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17747
113
30
-
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17762
- Proximity tolerance distance
- 10e85b55-fe13-40a0-b8a2-043f1dddde10
- Tolerance
- Tolerance
- false
- 0
-
-9280
17777
113
30
-
-9223.5
17792
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- efa1592b-bbf9-4d3b-9415-7562319eaad4
- Points
- Points
- false
- 0
-
-9143
17747
39
20
-
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17757
- 1
- Index map of culled points
- 3aca07e1-b1b8-44f0-81b1-8d23b1d0bb0f
- Indices
- Indices
- false
- 0
-
-9143
17767
39
20
-
-9123.5
17777
- 1
- Number of input points represented by this output point
- 50ed2f1f-0e8b-46b5-b32e-bdbe742f4fc2
- Valence
- Valence
- false
- 0
-
-9143
17787
39
20
-
-9123.5
17797
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- ddafa6fc-5d20-4aaa-86d7-657fc631898f
- Flip Matrix
- Flip Matrix
-
-9989
17748
78
28
-
-9950
17762
- 2
- Data matrix to flip
- 4a24e956-c5f1-4b2a-9f10-68d207dcd243
- Data
- Data
- false
- 2b5ab43a-bf29-46b7-97f8-b9a1e5f5505d
- 1
-
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17750
25
24
-
-9974.5
17762
- 2
- Flipped data matrix
- 7e35038d-d7b3-4169-a2e1-ee147c9aa897
- Data
- Data
- false
- 0
-
-9938
17750
25
24
-
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17762
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- b06ef032-a6e7-4452-9651-12a4aa2e7cec
- Evaluate Length
- Evaluate Length
-
-11840
17864
149
64
-
-11755
17896
- Curve to evaluate
- 2c14f2cf-46ba-4918-8f1c-b3272ba74995
- Curve
- Curve
- false
- 587de0b9-9f06-4d87-bf93-b93668a84499
- 1
-
-11838
17866
71
20
-
-11802.5
17876
- Length factor for curve evaluation
- de6d2a10-b91a-4a82-a095-c0c9229e0510
- Length
- Length
- false
- 0
-
-11838
17886
71
20
-
-11802.5
17896
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 32924ee0-ca83-49e6-845a-57621ca8781b
- Normalized
- Normalized
- false
- 0
-
-11838
17906
71
20
-
-11802.5
17916
- 1
- 1
- {0}
- true
- Point at the specified length
- ab1cebea-9440-45d3-b22a-729e57d3f393
- Point
- Point
- false
- 0
-
-11743
17866
50
20
-
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17876
- Tangent vector at the specified length
- c4f283c6-130d-4973-b31d-0b4e1e300c93
- Tangent
- Tangent
- false
- 0
-
-11743
17886
50
20
-
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17896
- Curve parameter at the specified length
- f8e517ea-def4-4d7a-b176-d494f464103b
- Parameter
- Parameter
- false
- 0
-
-11743
17906
50
20
-
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17916
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 613d5bca-f997-48a6-99da-2794f7a3babf
- Polar Array
- Polar Array
-
-10947
17864
210
101
-
-10801
17915
- Base geometry
- 863bdee8-d814-4028-a927-080f2ae9d329
- Geometry
- Geometry
- true
- ab1cebea-9440-45d3-b22a-729e57d3f393
- 1
-
-10945
17866
132
20
-
-10879
17876
- Polar array plane
- af140e57-5203-44d4-b935-2c282782fc2f
- Plane
- Plane
- false
- 0
-
-10945
17886
132
37
-
-10879
17904.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- f07b7b89-6eed-4d38-bbd7-03d43ae2b722
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
-10945
17923
132
20
-
-10879
17933
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- 4334bf6d-2032-41a4-94b1-ab89a78e6cb8
- Angle
- Angle
- false
- 0
- false
-
-10945
17943
132
20
-
-10879
17953
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- 5b1d4834-80d0-4db9-ac90-af4511687158
- Geometry
- Geometry
- false
- 0
-
-10789
17866
50
48
-
-10764
17890.25
- 1
- Transformation data
- e5d1d1bc-46cb-4015-8dfd-098bb74775d3
- Transform
- Transform
- false
- 0
-
-10789
17914
50
49
-
-10764
17938.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- 7da63af0-39d5-4057-9777-ed62661c16b2
- Cull Duplicates
- Cull Duplicates
-
-9282
17861
180
64
-
-9155
17893
- 1
- Points to operate on
- 38f185c5-7c31-409b-abb8-cca7ff4ae1ac
- Points
- Points
- false
- 7415449f-d53b-4906-8899-d2695a78b338
- 1
-
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17863
113
30
-
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17878
- Proximity tolerance distance
- a1c113c7-5886-4257-a65f-cc641c5d5e71
- Tolerance
- Tolerance
- false
- 0
-
-9280
17893
113
30
-
-9223.5
17908
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- ffd681a6-6a65-4c1f-9085-7033988b0b32
- Points
- Points
- false
- 0
-
-9143
17863
39
20
-
-9123.5
17873
- 1
- Index map of culled points
- b9843477-48d7-4054-b06a-b93861e7f600
- Indices
- Indices
- false
- 0
-
-9143
17883
39
20
-
-9123.5
17893
- 1
- Number of input points represented by this output point
- 37d80b0c-37cc-4b41-8b86-0405fac43c2d
- Valence
- Valence
- false
- 0
-
-9143
17903
39
20
-
-9123.5
17913
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- d3afd561-a88c-4672-82f5-740dd875dd98
- Flip Matrix
- Flip Matrix
-
-9989
17876
78
28
-
-9950
17890
- 2
- Data matrix to flip
- f0fd6251-e51b-4d26-a996-a53e51e57a84
- Data
- Data
- false
- 5b1d4834-80d0-4db9-ac90-af4511687158
- 1
-
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17878
25
24
-
-9974.5
17890
- 2
- Flipped data matrix
- eb27fc67-93d3-4155-93e7-01f56e95a084
- Data
- Data
- false
- 0
-
-9938
17878
25
24
-
-9925.5
17890
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 1504e2b4-e091-439c-ace1-a3e70d52839d
- Relay
- false
- 56e8bb2d-4b74-4665-8007-49becf882746
- 1
-
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17757
40
16
-
-12701
17765
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 587de0b9-9f06-4d87-bf93-b93668a84499
- Relay
- false
- 4106a4b6-ae1e-4c1a-aa13-89f01b1f0d6e
- 1
-
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17905
40
16
-
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17913
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 1504e2b4-e091-439c-ace1-a3e70d52839d
- 587de0b9-9f06-4d87-bf93-b93668a84499
- 2
- 653f1ce8-71ff-4bd6-8b5b-9fd09ed2f5ac
- Group
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 876934e9-655e-4c18-8ecc-1f5a9916c57f
- Merge
- Merge
-
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17941
106
84
-
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17983
- 4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 2
- Data stream 1
- 912d9e7e-269b-48bb-baac-202efe744be9
- false
- Data 1
- D1
- true
- 0e15a768-0ee5-4b2c-8524-5d790cc8917d
- 1
-
-5152
17943
31
20
-
-5136.5
17953
- 2
- Data stream 2
- 41de7089-d912-48dc-aeae-85a770be608d
- false
- Data 2
- D2
- true
- a56d7112-93f7-4bfb-b9b3-f40bc8813cf0
- 1
-
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17963
31
20
-
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17973
- 2
- Data stream 3
- a1195511-5814-4cbf-adde-46e1a4233c0b
- false
- Data 3
- D3
- true
- 659efc47-65df-4ea8-8eae-843b8943b7ff
- 1
-
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17983
31
20
-
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17993
- 2
- Data stream 4
- 53d2ea73-4a80-433a-b6de-1f11e4c7df02
- false
- Data 4
- D4
- true
- 0
-
-5152
18003
31
20
-
-5136.5
18013
- 2
- Result of merge
- 3833a314-af2b-4fa7-85ba-2d7ce04deabd
- 1
- Result
- Result
- false
- 0
-
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17943
47
80
-
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17983
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
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18954
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- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
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- Evaluate Length
- Evaluate Length
-
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18878
149
64
-
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- Curve to evaluate
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18880
71
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- Length factor for curve evaluation
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- Length
- Length
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-
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18900
71
20
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- 1
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- {0}
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Normalized
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18920
71
20
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- 1
- 1
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- Point at the specified length
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- Point
- Point
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- 0
-
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50
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- Tangent vector at the specified length
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- Tangent
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-
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50
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- Curve parameter at the specified length
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- Parameter
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18920
50
20
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- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
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- PolyLine
- PolyLine
-
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18924
106
44
-
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- Polyline vertex points
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- Vertices
- Vertices
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- 3606ae1a-a45f-48d1-a992-4ac71a0775e4
- 1
-
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18926
40
20
-
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18936
- Close polyline
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- Closed
- Closed
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- 1
-
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18946
40
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-
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18956
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- {0}
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- Resulting polyline
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- Polyline
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-
-8148
18926
38
40
-
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18946
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- c34fa604-6cdc-4331-84e4-5f9370955b30
- PolyLine
- PolyLine
-
-8214
18995
106
44
-
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19017
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- Polyline vertex points
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- Vertices
- Vertices
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- 1
-
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18997
40
20
-
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19007
- Close polyline
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- Closed
- Closed
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- 1
-
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19017
40
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-
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19027
- 1
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- {0}
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- Resulting polyline
- 5d541f70-e0c5-4828-8290-1655d1ce11b3
- Polyline
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-
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18997
38
40
-
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19017
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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- Merge
- Merge
-
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18952
90
64
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18984
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- Data stream 1
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- Data 1
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31
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- Data stream 2
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- Data 2
- D2
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31
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- Data stream 3
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- Data 3
- D3
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31
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18954
31
60
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- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
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- Polar Array
- Polar Array
-
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210
101
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- Base geometry
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132
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- Polar array plane
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132
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-
0
0
0
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0
0
0
1
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- Number of elements in array.
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- Count
- Count
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- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
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18937
132
20
-
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- 1
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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- Angle
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- false
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18957
132
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- 1
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- Arrayed geometry
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- Geometry
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18880
50
48
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- Transformation data
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- Transform
- Transform
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18928
50
49
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- Cull Duplicates
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- Cull points that are coincident within tolerance
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- Cull Duplicates
- Cull Duplicates
-
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18887
180
64
-
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- Points to operate on
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- Points
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-
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18889
113
30
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- Proximity tolerance distance
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18919
113
30
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- 1
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- {0}
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- Culled points
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- Points
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-
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18889
39
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- Index map of culled points
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39
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- Number of input points represented by this output point
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- Valence
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-
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18929
39
20
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- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
- Flip Matrix
-
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18890
78
28
-
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- 2
- Data matrix to flip
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- Data
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25
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- 2
- Flipped data matrix
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- Data
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-
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18892
25
24
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
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- Evaluate Length
- Evaluate Length
-
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149
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- Curve to evaluate
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- Curve
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71
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- Length factor for curve evaluation
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- Length
- Length
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- 0
-
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71
20
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- 1
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- If True, the Length factor is normalized (0.0 ~ 1.0)
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- Normalized
- Normalized
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-
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19048
71
20
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- Point at the specified length
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- Point
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-
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50
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- Tangent vector at the specified length
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- Tangent
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-
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50
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- Curve parameter at the specified length
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- Parameter
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-
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19048
50
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- Polar Array
- Create a polar array of geometry.
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- Polar Array
- Polar Array
-
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19006
210
101
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- Base geometry
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- Geometry
- Geometry
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-
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19008
132
20
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- Polar array plane
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-
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19028
132
37
-
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- 1
- {0}
-
0
0
0
1
0
0
0
1
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- Number of elements in array.
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- Count
- Count
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- 1
-
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19065
132
20
-
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- 1
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
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- Angle
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- false
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19085
132
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- Arrayed geometry
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- Geometry
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19008
50
48
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- Transformation data
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- Transform
- Transform
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-
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19056
50
49
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19080.75
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- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
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- Cull Duplicates
- Cull Duplicates
-
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19003
180
64
-
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19035
- 1
- Points to operate on
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- Points
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-
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19005
113
30
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- Proximity tolerance distance
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19035
113
30
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19050
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- {0}
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- Culled points
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- Points
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-
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19005
39
20
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- Index map of culled points
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- Indices
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-
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19025
39
20
-
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19035
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- Number of input points represented by this output point
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- Valence
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- 0
-
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19045
39
20
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19055
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
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- Flip Matrix
- Flip Matrix
-
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19018
78
28
-
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19032
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- Data matrix to flip
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- Data
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-
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19020
25
24
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- 2
- Flipped data matrix
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- Data
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-
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19020
25
24
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- A wire relay object
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40
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- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
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- A wire relay object
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40
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255;255;255;255
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- Merge a bunch of data streams
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106
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- Data stream 1
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- Data 1
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31
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- Data stream 2
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- Data 2
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31
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31
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- Result of merge
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47
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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255;255;255;255
- A group of Grasshopper objects
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- Normalized
- Normalized
- false
- 0
-
-11818
19998
71
20
-
-11782.5
20008
- 1
- 1
- {0}
- true
- Point at the specified length
- 76a0f0fe-0d66-42f8-84a0-61224197b028
- Point
- Point
- false
- 0
-
-11723
19958
50
20
-
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19968
- Tangent vector at the specified length
- 8b18daa3-1b76-4ec0-b2e9-6de883f749c7
- Tangent
- Tangent
- false
- 0
-
-11723
19978
50
20
-
-11698
19988
- Curve parameter at the specified length
- 55d774ca-491f-4294-bd97-13198245ddf9
- Parameter
- Parameter
- false
- 0
-
-11723
19998
50
20
-
-11698
20008
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- 2fd4876b-2721-4121-a279-9c4c5558b830
- PolyLine
- PolyLine
-
-8194
20002
106
44
-
-8140
20024
- 1
- Polyline vertex points
- b1cbd185-844c-4008-9e80-dbc0909efc1d
- Vertices
- Vertices
- false
- 4d2cbf50-a1ba-45ad-8198-b44691eec9ac
- 1
-
-8192
20004
40
20
-
-8172
20014
- Close polyline
- 68a6997b-caf3-4e33-8736-296cd8e09c26
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8192
20024
40
20
-
-8172
20034
- 1
- 1
- {0}
- true
- Resulting polyline
- a59b4080-0aca-4cc9-833a-09ee0d215583
- Polyline
- Polyline
- false
- 0
-
-8128
20004
38
40
-
-8109
20024
- 71b5b089-500a-4ea6-81c5-2f960441a0e8
- PolyLine
- Create a polyline connecting a number of points.
- true
- f560aaac-123d-465c-8191-c1047fd222d3
- PolyLine
- PolyLine
-
-8194
20073
106
44
-
-8140
20095
- 1
- Polyline vertex points
- 94cccdca-5b21-43a4-bf74-1c39615093e7
- Vertices
- Vertices
- false
- 7f9add94-d346-4753-bd0f-0f76292ea708
- 1
-
-8192
20075
40
20
-
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20085
- Close polyline
- b9854ef1-54b9-4e60-844b-4397346b7628
- Closed
- Closed
- false
- bf9476b7-1f42-4ee8-b1f2-94078732ec74
- 1
-
-8192
20095
40
20
-
-8172
20105
- 1
- 1
- {0}
- false
- Resulting polyline
- 94c19071-e38a-4b13-9af9-048665b18ff3
- Polyline
- Polyline
- false
- 0
-
-8128
20075
38
40
-
-8109
20095
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 9d8d2ca2-b660-4198-b1cc-d185509419f4
- Merge
- Merge
-
-7433
20030
90
64
-
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20062
- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Data stream 1
- ebd2a01f-0058-4a26-bfa7-d294b761a2b8
- false
- Data 1
- D1
- true
- a59b4080-0aca-4cc9-833a-09ee0d215583
- 1
-
-7431
20032
31
20
-
-7415.5
20042
- 2
- Data stream 2
- dc550c28-69e7-492f-afa3-dee2b54b6cda
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- Data 2
- D2
- true
- 94c19071-e38a-4b13-9af9-048665b18ff3
- 1
-
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20052
31
20
-
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20062
- 2
- Data stream 3
- 8a1bbe8e-fbd2-48a8-831c-0f3b667b7d92
- false
- Data 3
- D3
- true
- 0
-
-7431
20072
31
20
-
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20082
- 2
- Result of merge
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-
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20032
31
60
-
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20062
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- f218f49d-a862-449e-84b9-4eaa9005b11a
- Polar Array
- Polar Array
-
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19956
210
101
-
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20007
- Base geometry
- b6ac27b7-2397-40da-8194-9a6481b951da
- Geometry
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- true
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- 1
-
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19958
132
20
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19968
- Polar array plane
- 54e10d4f-e95b-4bd4-bb8a-69a7ede39828
- Plane
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19978
132
37
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19996.5
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- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
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- Count
- Count
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- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
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20015
132
20
-
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20025
- 1
- 1
- {0}
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- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- af352af0-8742-4442-b18c-8c0ea7e1912a
- Angle
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- false
-
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20035
132
20
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20045
- 1
- 1
- {0}
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- Arrayed geometry
- 82b41a8a-209f-4fd4-bd04-159ba3336e94
- Geometry
- Geometry
- false
- 0
-
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19958
50
48
-
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19982.25
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- Transformation data
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- Transform
- Transform
- false
- 0
-
-10769
20006
50
49
-
-10744
20030.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- 93442037-38d0-4883-a028-e3db395ca18a
- Cull Duplicates
- Cull Duplicates
-
-9262
19965
180
64
-
-9135
19997
- 1
- Points to operate on
- 8a9ad42a-9e11-4bd7-b911-d24abcbb1b83
- Points
- Points
- false
- 5bc2b19d-ee68-47a6-82eb-a318b39d70ea
- 1
-
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19967
113
30
-
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19982
- Proximity tolerance distance
- 3211bf5c-517d-4abf-802b-0e550d8948fa
- Tolerance
- Tolerance
- false
- 0
-
-9260
19997
113
30
-
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20012
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- 4d2cbf50-a1ba-45ad-8198-b44691eec9ac
- Points
- Points
- false
- 0
-
-9123
19967
39
20
-
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19977
- 1
- Index map of culled points
- 0c092b8c-b525-44ab-8eff-01847e540346
- Indices
- Indices
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- 0
-
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19987
39
20
-
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19997
- 1
- Number of input points represented by this output point
- 9e98a26a-639e-4238-aa0b-5f21eece5005
- Valence
- Valence
- false
- 0
-
-9123
20007
39
20
-
-9103.5
20017
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
- true
- 62cb6685-6943-4d70-9dad-7d319fa18b07
- Flip Matrix
- Flip Matrix
-
-9969
19968
78
28
-
-9930
19982
- 2
- Data matrix to flip
- ea5c434e-83f4-4f78-8167-2ef51e2516ba
- Data
- Data
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- 82b41a8a-209f-4fd4-bd04-159ba3336e94
- 1
-
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19970
25
24
-
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19982
- 2
- Flipped data matrix
- e319d54d-2de8-490c-a8cd-087587455e2a
- Data
- Data
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- 0
-
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19970
25
24
-
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19982
- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 6f0fe1aa-c584-42d6-9c71-b78c74adf532
- Evaluate Length
- Evaluate Length
-
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20084
149
64
-
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20116
- Curve to evaluate
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- Curve
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- 1
-
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20086
71
20
-
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20096
- Length factor for curve evaluation
- 2264bcbc-ecba-4504-876c-993616b278e3
- Length
- Length
- false
- 0
-
-11818
20106
71
20
-
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20116
- 1
- 1
- {0}
- 1
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 2a2e2d18-bfce-4fd3-8edc-8e7fe87e7fcd
- Normalized
- Normalized
- false
- 0
-
-11818
20126
71
20
-
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20136
- 1
- 1
- {0}
- true
- Point at the specified length
- 59ed0548-dad9-4044-87cf-7f6e19440ac6
- Point
- Point
- false
- 0
-
-11723
20086
50
20
-
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20096
- Tangent vector at the specified length
- 851d8e75-5343-4769-bda4-4292fe509ae2
- Tangent
- Tangent
- false
- 0
-
-11723
20106
50
20
-
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20116
- Curve parameter at the specified length
- 26e0ff5f-501e-4993-941d-95ca9955229c
- Parameter
- Parameter
- false
- 0
-
-11723
20126
50
20
-
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20136
- fca5ad7e-ecac-401d-a357-edda0a251cbc
- Polar Array
- Create a polar array of geometry.
- true
- 9609a713-0277-4bbc-948a-0184566a74fe
- Polar Array
- Polar Array
-
-10927
20084
210
101
-
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20135
- Base geometry
- 2ff31a93-ec8c-468a-a25a-292730cb10fb
- Geometry
- Geometry
- true
- 59ed0548-dad9-4044-87cf-7f6e19440ac6
- 1
-
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20086
132
20
-
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20096
- Polar array plane
- a656c790-d5b5-4f87-a651-7e130d661606
- Plane
- Plane
- false
- 0
-
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20106
132
37
-
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20124.5
- 1
- 1
- {0}
-
0
0
0
1
0
0
0
1
0
- Number of elements in array.
- e6b374d6-08a2-4a89-b3c7-2b6e6228c7e0
- Count
- Count
- false
- a36a42bd-2f18-4380-938f-847c2f934c7b
- 1
-
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20143
132
20
-
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20153
- 1
- 1
- {0}
- 4
- Sweep angle in radians (counter-clockwise, starting from plane x-axis)
- cdf25ec3-5566-4a3a-851c-9ce37ce198c7
- Angle
- Angle
- false
- 0
- false
-
-10925
20163
132
20
-
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20173
- 1
- 1
- {0}
- 6.2831853071795862
- 1
- Arrayed geometry
- 6787462c-549e-463a-b031-5a0b2929d662
- Geometry
- Geometry
- false
- 0
-
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20086
50
48
-
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20110.25
- 1
- Transformation data
- 0d10a4e0-a051-4841-97f8-7bc7550defdf
- Transform
- Transform
- false
- 0
-
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20134
50
49
-
-10744
20158.75
- 6eaffbb2-3392-441a-8556-2dc126aa8910
- Cull Duplicates
- 1
- Cull points that are coincident within tolerance
- true
- 5af0002f-4d74-4c49-bf53-a9761afd014b
- Cull Duplicates
- Cull Duplicates
-
-9262
20081
180
64
-
-9135
20113
- 1
- Points to operate on
- ecfd6858-0615-46ed-8488-18102c5e6e15
- Points
- Points
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- 2998955a-933e-4961-9baa-e06be20d8f29
- 1
-
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20083
113
30
-
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20098
- Proximity tolerance distance
- 42819980-e3a4-408c-9d13-01724d95a9b7
- Tolerance
- Tolerance
- false
- 0
-
-9260
20113
113
30
-
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20128
- 1
- 1
- {0}
- 1.1641532182693481E-10
- 1
- Culled points
- 7f9add94-d346-4753-bd0f-0f76292ea708
- Points
- Points
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- 0
-
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20083
39
20
-
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20093
- 1
- Index map of culled points
- 15b4b02e-e0bd-4b88-9c1e-2553dd0b20f4
- Indices
- Indices
- false
- 0
-
-9123
20103
39
20
-
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20113
- 1
- Number of input points represented by this output point
- 4986a7c2-0250-4af8-a89c-0b84d96f4b29
- Valence
- Valence
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- 0
-
-9123
20123
39
20
-
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20133
- 41aa4112-9c9b-42f4-847e-503b9d90e4c7
- Flip Matrix
- Flip a matrix-like data tree by swapping rows and columns.
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- e98c1e8e-dc86-4ad9-b410-a3cc1e4fe19f
- Flip Matrix
- Flip Matrix
-
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20096
78
28
-
-9930
20110
- 2
- Data matrix to flip
- ebbe8ba7-cb3f-4fd0-ad47-e14bf5872344
- Data
- Data
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- 6787462c-549e-463a-b031-5a0b2929d662
- 1
-
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20098
25
24
-
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20110
- 2
- Flipped data matrix
- 1f6fa5f9-d23b-4441-ba83-963964a3f192
- Data
- Data
- false
- 0
-
-9918
20098
25
24
-
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20110
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
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- A wire relay object
- e5799d89-59d5-4c14-8936-50c8d6fbe19d
- Relay
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- 5d1e2520-a8eb-4564-87c3-e2eb2695c71b
- 1
-
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19978
40
16
-
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19986
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 7518ba3b-c967-42a5-94df-67473f997574
- Relay
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- 1
-
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20126
40
16
-
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20134
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
- e5799d89-59d5-4c14-8936-50c8d6fbe19d
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- 2
- 2dc18481-206c-487a-8196-ae80e51e7dfb
- Group
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 7f27bbcc-b3b9-47c3-988a-b50cb5780213
- Merge
- Merge
-
-5134
20161
106
84
-
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20203
- 4
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 1
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- Data stream 1
- 96e04837-099b-4b7a-a0dd-8ee341de2fc7
- false
- Data 1
- D1
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- 5a47da9d-e9df-4d2e-8b10-98dbda99f0d0
- 1
-
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20163
31
20
-
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20173
- 2
- Data stream 2
- f01a0789-e2e8-4e9d-ae66-96b4e2c37191
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- Data 2
- D2
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- dd6cbd33-19fb-49e7-b2f7-cf489642eec4
- 1
-
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20183
31
20
-
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20193
- 2
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- 3e7cb10f-d70b-4cd6-987c-c4e6acf3b8b5
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- Data 3
- D3
- true
- 0628ad87-5dcc-4767-950d-bc21545fad58
- 1
-
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20203
31
20
-
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20213
- 2
- Data stream 4
- 5875c811-a062-4660-a357-a9215b7e7d7e
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- Data 4
- D4
- true
- 0
-
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20223
31
20
-
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20233
- 2
- Result of merge
- e464753a-4326-447b-a5d6-2dcdd58beadb
- 1
- Result
- Result
- false
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-
-5077
20163
47
80
-
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20203
- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
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- ee92d79b-a7b3-4909-b884-23e9ecc9c8c7
- Merge
- Merge
-
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665
112
344
-
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837
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- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Data stream 1
- 9f12dd9c-e621-4af5-ac33-5da96b852939
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- Data 1
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- 706e6595-4fb3-421b-996a-354bb8e28c9b
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-
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667
37
20
-
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677
- 2
- Data stream 2
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- Data 2
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- a924444c-3e6d-436a-8dd2-27f6ad4945f9
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687
37
20
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697
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- 70ee9a2d-1670-4371-a11f-92861c159727
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- Data 3
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707
37
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- FabiusF::usage="FabiusF[x] gives the value of the Fabius function F(x) for a non-negative real argument x.";
Macros`SetArgumentCount[FabiusF,1];
SyntaxInformation[FabiusF]={"ArgumentsPattern"->{_}};
SetAttributes[FabiusF,{NumericFunction,Listable}];
Derivative[n_Integer][FabiusF]:=2^(n (n+1)/2) FabiusF[2^n #]&
(*https://mathematica.stackexchange.com/a/13245*)
powerOfTwoQ[n_]:=IntegerQ[n]&&BitAnd[n,n-1]==0
FabiusF[Infinity]=Interval[{-1,1}];
FabiusF[x_?NumberQ]/;If[0<=Re[x]&&Im[x]==0,powerOfTwoQ[Denominator[x]],Message[FabiusF::realnn,x];False]:=iFabiusF[x]
ariasD[0]=1;
ariasD[n_Integer?Positive]:=ariasD[n]=Sum[2^((k (k-1)-n (n-1))/2) ariasD[k]/(n-k+1)!,{k,0,n-1}]/(2^n-1);
tri[x_]:=Piecewise[{{2-x,x>1}},x]
iFabiusF[x_]:=Module[{prec=Precision[x],s=1,y=0,z=SetPrecision[x,Infinity],n,p,q,tol,w},z=If[0<=z<=2,tri[z],q=Quotient[z,2];
(*can replace ThueMorse[] with the implementation in https://mathematica.stackexchange.com/a/89351*)If[ThueMorse[q]==1,s=-1];tri[z-2 q]];
tol=10^(-prec);
While[z>0,n=-Floor[RealExponent[z,2]];p=2^n;z-=1/p;w=1;
Do[w=ariasD[m]+p z w/(n-m+1);p/=2,{m,n}];
y=w-y;
If[Abs[w]<Abs[y] tol,Break[]]];
SetPrecision[s Abs[y],prec]];
ᐱ=1;
ƧS=16;
ᔓᔕ={ImageSize-> Full,AspectRatio-> 1/16,MaxRecursion->0,PlotPoints-> 1+2^(Log[ƧS]/Log[2]) };
ꗳ={Abs[FabiusF[x*2*ᐱ]]};
Plot[ꗳ,{x,0,1},Evaluate[ᔓᔕ]];
N[(Log[ƧS]/Log[2])];
StringReplace[
ToString[
Table[
N[
Evaluate[SetPrecision[SetAccuracy[ꗳ,Infinity],Infinity]]
]
,{x,Flatten[Range[0,ƧS]/ƧS]}]
,InputForm]
,{"{"-> "","}"-> ""," "-> "","*^"-> "*10^"}]
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- Replace Text
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- true
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- Optional fragment to replace with. If blank, all occurences of F will be removed.
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- Replace
- Replace
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- Concatenate
- Concatenate some fragments of text
- true
- a2c862c4-001b-450b-bfa3-c672c7aeacf9
- true
- Concatenate
- Concatenate
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5622
-2272
- 3
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- 1
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- Index of Gate stream
- 3a46a533-d39a-4446-b923-8921005cb645
- true
- Gate
- Gate
- false
- 0
-
5570
-2302
40
20
-
5590
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- 1
- 1
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- Input stream at index 0
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- true
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- Stream 0
- 0
- true
- 0
-
5570
-2282
40
20
-
5590
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- 2
- Input stream at index 1
- 0d26362b-b98e-4fd1-9f2e-069c5b52ef3a
- true
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- Stream 1
- 1
- true
- 20eec82c-3638-4068-b8ec-f7754f44d1d0
- 1
-
5570
-2262
40
20
-
5590
-2252
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_String
- false
- 1
- 2
- Filtered stream
- aa6e20b3-ed69-4615-8194-b0e2c46ede90
- true
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- Stream
- S(1)
- false
- 0
-
5634
-2302
24
60
-
5646
-2272
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 2d1fa5b0-bc84-4c71-a356-02c3ae09bc4c
- true
- Stream Filter
- Stream Filter
-
5568
-3204
92
64
-
5622
-3172
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 4263c740-37b0-49a0-abf2-6d797694626c
- true
- Gate
- Gate
- false
- 25de4f3d-bbbe-4d69-a2f8-eafb39ed11c3
- 1
-
5570
-3202
40
20
-
5590
-3192
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 403a03e8-2056-460d-811a-7288a41cfbaa
- true
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- Stream 0
- 0
- true
- 0
-
5570
-3182
40
20
-
5590
-3172
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_String
- false
- 1
- 2
- Input stream at index 1
- b0bfffc4-ceeb-44e9-b31c-fb638dd0a66c
- true
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- Stream 1
- 1
- true
- 8e2c479f-1986-4a29-ac9c-d76908386441
- 1
-
5570
-3162
40
20
-
5590
-3152
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_String
- false
- 1
- 2
- Filtered stream
- 7ec9447f-503b-4550-a46d-b2f1773da413
- true
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- Stream
- S(1)
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- 0
-
5634
-3202
24
60
-
5646
-3172
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- de03810f-58b7-4c2c-89d6-49cb00614695
- true
- Gate Not
- Gate Not
-
5574
-3099
80
28
-
5609
-3085
- Boolean value
- a0efc076-2674-4a8e-966a-cd6ff8b2cfb5
- true
- A
- A
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- 0
-
5576
-3097
21
24
-
5586.5
-3085
- 1
- 1
- {0}
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- Inverse of {A}
- 25de4f3d-bbbe-4d69-a2f8-eafb39ed11c3
- true
- Result
- Result
- false
- 0
-
5621
-3097
31
24
-
5636.5
-3085
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 88726205-2a30-44c4-8e25-19521cf91261
- true
- Stream Filter
- Stream Filter
-
5568
-2219
92
64
-
5622
-2187
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
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- Index of Gate stream
- 0b8d4ebb-ff0a-438f-873f-ac724eb994b3
- true
- Gate
- Gate
- false
- 0
-
5570
-2217
40
20
-
5590
-2207
- 1
- 1
- {0}
- 1
- 2
- Input stream at index 0
- e1375ca2-bad5-46e1-83e4-8bcf1f144b8e
- true
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- Stream 0
- 0
- true
- 0
-
5570
-2197
40
20
-
5590
-2187
- 2
- Input stream at index 1
- d7733ad1-9026-423d-8042-4e6431d6e982
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- Stream 1
- 1
- true
- 051df130-9b07-4484-aee6-c11038f9920f
- 1
-
5570
-2177
40
20
-
5590
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- 2
- Filtered stream
- 20eec82c-3638-4068-b8ec-f7754f44d1d0
- true
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- Stream
- S(1)
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- 0
-
5634
-2217
24
60
-
5646
-2187
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- e84dba12-64d4-4086-bd66-0d891880a38b
- true
- Stream Filter
- Stream Filter
-
5568
-3038
92
64
-
5622
-3006
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 1
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- Index of Gate stream
- cde52939-d91f-48c0-852f-d1d931c679d1
- true
- Gate
- Gate
- false
- 0
-
5570
-3036
40
20
-
5590
-3026
- 1
- 1
- {0}
- 1
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- Input stream at index 0
- 30fb0819-1aec-45bd-86ad-db3341956079
- true
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- Stream 0
- 0
- true
- 0
-
5570
-3016
40
20
-
5590
-3006
- 2
- Input stream at index 1
- fb00641f-71e1-43db-ad33-197aac2070b3
- true
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- Stream 1
- 1
- true
- 26b600f6-cf65-413e-ae98-aa04c9baea3f
- 1
-
5570
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40
20
-
5590
-2986
- 2
- Filtered stream
- 8e2c479f-1986-4a29-ac9c-d76908386441
- true
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- Stream
- S(1)
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- 0
-
5634
-3036
24
60
-
5646
-3006
- 7a1e5fd7-b7da-4244-a261-f1da66614992
- Power of 2
- Raise 2 to the power of N.
- true
- 722c82cf-9886-4262-9816-99e5cd56678c
- true
- Power of 2
- Power of 2
-
5599
-592
49
28
-
5628
-578
- Input value
- ee9c09b1-533c-4d4a-be2d-82b761176c38
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- Value
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- 0
-
5601
-590
15
24
-
5608.5
-578
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_String
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- 4
- Output value
- c24a11ca-4b56-465e-a295-4d23379c5a82
- true
- Result
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- 0
-
5640
-590
6
24
-
5643
-578
- 2b69bf71-4e69-43aa-b7be-4f6ce7e45bef
- Quick Graph
- 1
- Display a set of y-values as a graph
- 6dde463b-8ec4-4fed-8469-a81cead81ceb
- true
- Quick Graph
- Quick Graph
- false
- 0
- 67a89d9d-9c53-46e9-9e3f-3e39885aabe6
- 1
-
5545
-3668
150
150
-
5545.936
-3667.635
- -1
- 2b69bf71-4e69-43aa-b7be-4f6ce7e45bef
- Quick Graph
- 1
- Display a set of y-values as a graph
- a13feeb8-9203-4a56-91d0-bffa77e0adec
- true
- Quick Graph
- Quick Graph
- false
- 0
- c392a01f-be44-46c9-b4b8-97692db5ba6a
- 1
-
5544
-2734
150
150
-
5544.146
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- -1
- d5967b9f-e8ee-436b-a8ad-29fdcecf32d5
- Curve
- Contains a collection of generic curves
- true
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- true
- Curve
- Curve
- false
- 7fd0d788-1237-49d2-b610-14b9cdecf740
- 1
-
5856
-861
50
24
-
5881.943
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- 6b021f56-b194-4210-b9a1-6cef3b7d0848
- Evaluate Length
- Evaluate a curve at a certain factor along its length. Length factors can be supplied both in curve units and normalized units. Change the [N] parameter to toggle between the two modes.
- true
- 293ffb2b-17b1-499c-ab83-ca4b6b12d7cc
- true
- Evaluate Length
- Evaluate Length
-
5992
-1067
158
64
-
6086
-1035
- Curve to evaluate
- cae78a03-2530-469e-8072-6dc15a29e5de
- true
- Curve
- Curve
- false
- 13394695-7838-4186-a49f-10abd5475f71
- 1
-
5994
-1065
80
20
-
6042
-1055
- Length factor for curve evaluation
- c6389f43-3849-4238-a5f7-cd2e422f9150
- (((1-X)+.25)%1)*0+X
- true
- Length
- Length
- false
- ef28f44c-dbc6-4685-a989-6732ef0bb7c2
- 1
-
5994
-1045
80
20
-
6042
-1035
- If True, the Length factor is normalized (0.0 ~ 1.0)
- 92dc2b87-a073-4931-ae5c-34b2de2739af
- true
- Normalized
- Normalized
- false
- 0
-
5994
-1025
80
20
-
6042
-1015
- 1
- 1
- {0}
- true
- Point at the specified length
- 7591450a-f055-4d21-a585-f8ae56edcd48
- true
- Point
- Point
- false
- 0
-
6098
-1065
50
20
-
6123
-1055
- Tangent vector at the specified length
- 17858ac8-32f7-44d6-b6f8-2d508ecaa5fd
- true
- Tangent
- Tangent
- false
- 0
-
6098
-1045
50
20
-
6123
-1035
- Curve parameter at the specified length
- 49590bed-a20e-4773-8468-19bcd687b41d
- true
- Parameter
- Parameter
- false
- 0
-
6098
-1025
50
20
-
6123
-1015
- d27b55c6-9d5f-4d05-be7b-b91009aad383
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- DotDisplay
- Show points as round dots
- true
- 7eb88e78-1c37-4abe-86a2-1d9a5462c467
- true
- DotDisplay
- DotDisplay
-
6260
-1030
55
28
-
6301
-1016
- Points to display
- 1269a20e-0305-403a-89e4-6ce870afc658
- true
- Point
- Point
- false
- 7591450a-f055-4d21-a585-f8ae56edcd48
- 1
-
6262
-1028
27
24
-
6275.5
-1016
- b6236720-8d88-4289-93c3-ac4c99f9b97b
- Relay
- 2
- A wire relay object
- 2b49245c-cda0-4c54-82f2-915c2c2d3104
- true
- Relay
- false
- c392a01f-be44-46c9-b4b8-97692db5ba6a
- 1
-
5856
-1105
40
16
-
5876
-1097
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- a032b96c-6401-439f-b3f3-904dda76193d
- true
- Shift List
- Shift List
-
5971
-796
85
64
-
6023
-764
- 1
- List to shift
- 59903599-7e96-4aa6-bbc0-1dd19bc6b732
- true
- List
- List
- false
- 7685ddf3-078a-480f-99b7-862e703168f0
- 1
-
5973
-794
38
20
-
5992
-784
- Shift offset
- fa55991b-de79-429a-9f60-49f921ce5b6c
- true
- Shift
- Shift
- false
- 8b406b6e-1939-4eca-b757-fee45c7bdd1a
- 1
-
5973
-774
38
20
-
5992
-764
- 1
- 1
- {0}
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- Wrap values
- 87a68ae4-9a06-4490-a950-0b2e160b1389
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- Wrap
- Wrap
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- 0
-
5973
-754
38
20
-
5992
-744
- 1
- 1
- {0}
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- 1
- Shifted list
- 23a6c8c0-0b37-4d13-a7e3-8809dcbe6e24
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- List
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- 0
-
6035
-794
19
60
-
6044.5
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- 9c85271f-89fa-4e9f-9f4a-d75802120ccc
- Division
- Mathematical division
- true
- 7763af33-af48-446f-a61a-b14eef73d6b4
- true
- Division
- Division
-
5903
-1211
85
44
-
5943
-1189
- Item to divide (dividend)
- e8d7559e-d7e9-47c0-a40f-d442f2b00caf
- true
- A
- A
- false
- 2b49245c-cda0-4c54-82f2-915c2c2d3104
- 1
-
5905
-1209
26
20
-
5918
-1199
- Item to divide with (divisor)
- 4d7f72d4-79ff-494e-9a40-70f92811487e
- true
- B
- B
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- 0
-
5905
-1189
26
20
-
5918
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- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_Integer
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- The result of the Division
- 7685ddf3-078a-480f-99b7-862e703168f0
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- Result
- Result
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- 0
-
5955
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31
40
-
5970.5
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- Subtraction
- Mathematical subtraction
- true
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- true
- Subtraction
- Subtraction
-
6107
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85
44
-
6147
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- 2
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- First operand for subtraction
- 0b42fc02-1e42-476d-82b8-58fa966fb336
- true
- A
- A
- true
- 0
-
6109
-762
26
20
-
6122
-752
- 1
- 1
- {0}
- Grasshopper.Kernel.Types.GH_String
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- 1
- Second operand for subtraction
- b2d244ff-2a5e-40ff-b002-3fd8100dfaa7
- true
- B
- B
- true
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- 1
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6109
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26
20
-
6122
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- Result of subtraction
- c1a886a6-a389-4bef-92a8-675272355ed7
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-
6159
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31
40
-
6174.5
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- 3cadddef-1e2b-4c09-9390-0e8f78f7609f
- Merge
- Merge a bunch of data streams
- true
- 9ae96cdd-eee0-4568-afce-7d59699d1545
- true
- Merge
- Merge
-
6271
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106
64
-
6316
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- 3
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Data stream 1
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- Data 1
- D1
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- 8ac10f4f-35e5-4926-b1ad-69680a469255
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6273
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31
20
-
6288.5
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- Data 2
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6273
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31
20
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6288.5
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-
6273
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31
20
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6288.5
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-
6328
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47
60
-
6343.5
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- 059b72b0-9bb3-4542-a805-2dcd27493164
- Cloud Display
- Draw a collection of points as a fuzzy cloud
- true
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- true
- Cloud Display
- Cloud Display
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-
6352
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119
64
-
6457
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- 1
- Location for each blob
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- 2
- Points
- Points
- true
- 7591450a-f055-4d21-a585-f8ae56edcd48
- 1
-
6354
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91
20
-
6417.5
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- 1
- Colour for each blob
- ca51359a-3873-47c3-bcac-fb0729baa349
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- Colours
- Colours
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- 0
-
6354
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91
20
-
6417.5
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- 1
- 1
- {0}
-
255;0;244;124
- Size for each blob
- a73e21b3-0789-4f1e-be52-243347a3b340
- X/64
- true
- 2
- Size
- Size
- true
- 0
-
6354
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91
20
-
6417.5
-1015
- 1
- 1
- {0}
- 0.5
- 1817fd29-20ae-4503-b542-f0fb651e67d7
- List Length
- Measure the length of a list.
- true
- 9483e01d-cc2a-4b34-994f-82c856e1d0e7
- true
- List Length
- List Length
-
5962
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97
28
-
5995
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- 1
- Base list
- e4e028de-6ac2-4ea2-ad4f-de1511a6e7cd
- true
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- false
- 2b49245c-cda0-4c54-82f2-915c2c2d3104
- 1
-
5964
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19
24
-
5973.5
-914
- Number of items in L
- 8b406b6e-1939-4eca-b757-fee45c7bdd1a
- X/2
- true
- Length
- Length
- false
- 0
-
6007
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50
24
-
6024
-914
- 4fdfe351-6c07-47ce-9fb9-be027fb62186
- Shift List
- Offset all items in a list.
- true
- f13a9bd2-16c5-46cb-924c-9eb2b0358e00
- true
- Shift List
- Shift List
-
6112
-927
101
64
-
6180
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- 1
- List to shift
- 61a7c0c9-36be-4685-8035-d3e562eb30e0
- true
- List
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- false
- 7685ddf3-078a-480f-99b7-862e703168f0
- 1
-
6114
-925
54
20
-
6149
-915
- Shift offset
- eb28a822-0c31-4a3a-b65d-4fefe766f6f2
- -X+1
- true
- Shift
- Shift
- false
- 8b406b6e-1939-4eca-b757-fee45c7bdd1a
- 1
-
6114
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54
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100
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237
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170
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92
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40
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24
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92
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40
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24
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92
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40
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40
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40
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24
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92
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40
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255;255;255;255
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- Filters a collection of input streams
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- Stream Filter
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64
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20
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20
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40
20
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24
60
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- Filters a collection of input streams
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- Stream Filter
- Stream Filter
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92
64
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20
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40
20
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20
-
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- Filtered stream
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- Stream
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60
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-
255;255;255;255
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- Group
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- Filters a collection of input streams
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- Stream Filter
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64
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20
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20
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- Input stream at index 1
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40
20
-
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- Filtered stream
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24
60
-
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- Filters a collection of input streams
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- Stream Filter
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64
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20
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40
20
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- Input stream at index 1
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40
20
-
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- Filtered stream
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- Stream
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24
60
-
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- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Group
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- Filters a collection of input streams
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- Stream Filter
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92
64
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40
20
-
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40
20
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- 2
- Input stream at index 1
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40
20
-
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- 2
- Filtered stream
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24
60
-
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- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
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- Stream Filter
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92
64
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40
20
-
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40
20
-
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- 2
- Input stream at index 1
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40
20
-
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- 2
- Filtered stream
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- Stream
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24
60
-
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Group
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- Filters a collection of input streams
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- Stream Filter
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92
64
-
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- Index of Gate stream
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40
20
-
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40
20
-
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- Input stream at index 1
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-
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40
20
-
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- 2
- Filtered stream
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24
60
-
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- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
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- Stream Filter
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92
64
-
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- Index of Gate stream
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- Gate
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-
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40
20
-
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- {0}
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- false
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-
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40
20
-
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- 2
- Input stream at index 1
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- false
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- 1
- true
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-
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40
20
-
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- Filtered stream
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24
60
-
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Group
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271
155
-
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-
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196
20
-
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- An optional frame for the drawing. If blank, the shapes bounding box will be used
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-
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110
196
71
-
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145.5
- The width of the output drawing
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- 0
-
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181
196
20
-
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- 1
- 1
- {0}
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- The height of the output drawing
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- Height
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- 0
-
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201
196
20
-
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211
- 1
- 1
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- An optional background color
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-
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221
196
20
-
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- {0}
-
0;255;255;255
- A Graphic Plus Drawing Object
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-
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47
75
-
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127.75
- The bounding rectangle
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47
76
-
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203.25
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92
64
-
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- Index of Gate stream
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- Gate
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-
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40
20
-
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40
20
-
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- 2
- Input stream at index 1
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- true
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-
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40
20
-
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- 2
- Filtered stream
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24
60
-
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- eeafc956-268e-461d-8e73-ee05c6f72c01
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- Stream Filter
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92
64
-
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- 2e3ab970-8545-46bb-836c-1c11e5610bce
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- 1
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- Index of Gate stream
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- Gate
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-
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40
20
-
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- 1
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- {0}
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- Input stream at index 0
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- true
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-
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40
20
-
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- 2
- Input stream at index 1
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- Stream 1
- 1
- true
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- 1
-
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40
20
-
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- 2
- Filtered stream
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- Stream
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-
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24
60
-
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- 2
- 14b30f5b-f7e1-48df-a27f-19c0ea0559a6
- Group
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 2afd3edb-d771-40ba-9e12-ae84a3d2c52b
- Stream Filter
- Stream Filter
-
-11227
12608
92
64
-
-11173
12640
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
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- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
12610
40
20
-
-11205
12620
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- dc35d3b8-24b9-4476-aa26-4045c6111021
- false
- Stream 0
- 0
- true
- 0
-
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12630
40
20
-
-11205
12640
- 2
- Input stream at index 1
- 42c2fd41-52b1-46a2-b9eb-39d5d4b30ba9
- false
- Stream 1
- 1
- true
- 0f7d41df-0b88-413c-bf09-4b93aebfd26f
- 1
-
-11225
12650
40
20
-
-11205
12660
- 2
- Filtered stream
- c275b6a1-118d-4ab6-9708-51c158efd69c
- false
- Stream
- S(0)
- false
- 0
-
-11161
12610
24
60
-
-11149
12640
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 97dc2833-b406-498f-8847-89d4d247ff99
- Stream Filter
- Stream Filter
-
-11227
12481
92
64
-
-11173
12513
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- f67731f9-a091-40ee-aac8-252fde956cc9
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
12483
40
20
-
-11205
12493
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 664f2c9c-c93a-4673-b7c2-0db2519483c4
- false
- Stream 0
- 0
- true
- 0
-
-11225
12503
40
20
-
-11205
12513
- 2
- Input stream at index 1
- 2a419803-185f-4277-895c-31b5e3a9ab90
- false
- Stream 1
- 1
- true
- 360e3c71-f39a-4344-9b0b-f76f6040e9a5
- 1
-
-11225
12523
40
20
-
-11205
12533
- 2
- Filtered stream
- f71f118e-dff3-449b-8eb8-77a6b5272af6
- false
- Stream
- S(0)
- false
- 0
-
-11161
12483
24
60
-
-11149
12513
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 2afd3edb-d771-40ba-9e12-ae84a3d2c52b
- 97dc2833-b406-498f-8847-89d4d247ff99
- 2
- 7fe95677-b648-4e7c-af60-2ac98b6280e5
- Group
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- c319f1fd-9a2f-4e3e-b41a-462b6183ff1f
- Stream Filter
- Stream Filter
-
-11227
13778
92
64
-
-11173
13810
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- c744c5fd-cb6e-4fef-8386-ddde37a92a96
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
13780
40
20
-
-11205
13790
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- bc4c971e-516e-458d-9bd8-d9e361610a32
- false
- Stream 0
- 0
- true
- 0
-
-11225
13800
40
20
-
-11205
13810
- 2
- Input stream at index 1
- 49be4b2e-7253-4819-a896-eca1a5b70d13
- false
- Stream 1
- 1
- true
- 68ed2259-a880-4020-a4fa-5102d6548b24
- 1
-
-11225
13820
40
20
-
-11205
13830
- 2
- Filtered stream
- 27bc95ad-0ae8-4000-9aff-03a94c23bb45
- false
- Stream
- S(0)
- false
- 0
-
-11161
13780
24
60
-
-11149
13810
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- b23a953e-f5fe-490d-b4e1-4836f77bf220
- Stream Filter
- Stream Filter
-
-11227
13651
92
64
-
-11173
13683
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 2b1b6ad2-d1bc-4881-bdc4-6b4113ab2662
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
13653
40
20
-
-11205
13663
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 6f575b6a-e190-4cac-aaeb-3ba7716f3380
- false
- Stream 0
- 0
- true
- 0
-
-11225
13673
40
20
-
-11205
13683
- 2
- Input stream at index 1
- dccef9cf-5d4b-443b-be87-4160cd59f0f9
- false
- Stream 1
- 1
- true
- 609b5d6e-7b75-4e1a-8a12-faf652c3c682
- 1
-
-11225
13693
40
20
-
-11205
13703
- 2
- Filtered stream
- d3e6f2a9-2986-4d0e-9d6d-14be9dfd713f
- false
- Stream
- S(0)
- false
- 0
-
-11161
13653
24
60
-
-11149
13683
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- c319f1fd-9a2f-4e3e-b41a-462b6183ff1f
- b23a953e-f5fe-490d-b4e1-4836f77bf220
- 2
- f2403d64-acca-4fec-8df9-48668cb8aada
- Group
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 21885950-be69-465c-9d96-960f153c1764
- Stream Filter
- Stream Filter
-
-11227
14883
92
64
-
-11173
14915
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- e55bda3b-8bbe-4404-9461-64492dce29bb
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
14885
40
20
-
-11205
14895
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 5aa6f597-e792-4a71-975e-df7a2cd6a126
- false
- Stream 0
- 0
- true
- 0
-
-11225
14905
40
20
-
-11205
14915
- 2
- Input stream at index 1
- bceaa58d-d972-4d19-8468-d1e80f9fb6ef
- false
- Stream 1
- 1
- true
- 0ba93922-a608-4ac3-8ad6-de58e4e01a8f
- 1
-
-11225
14925
40
20
-
-11205
14935
- 2
- Filtered stream
- 367d9c37-ecf5-4adb-a85a-2bdcd57e2092
- false
- Stream
- S(0)
- false
- 0
-
-11161
14885
24
60
-
-11149
14915
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 269cc0bb-67ab-43ed-a590-db3e7b6ab08f
- Stream Filter
- Stream Filter
-
-11227
14756
92
64
-
-11173
14788
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 4dc57c65-7ba5-4cd5-a06e-202a19c48e94
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
14758
40
20
-
-11205
14768
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- ee9327d4-ebf1-4450-8c01-edff53e474b5
- false
- Stream 0
- 0
- true
- 0
-
-11225
14778
40
20
-
-11205
14788
- 2
- Input stream at index 1
- 2c4e6896-5d80-416c-a893-d11cea4c865d
- false
- Stream 1
- 1
- true
- 589e948c-d0d2-4b05-9c56-6855d5c435b4
- 1
-
-11225
14798
40
20
-
-11205
14808
- 2
- Filtered stream
- a6314d11-f0d5-419c-bc82-24c2862d0c35
- false
- Stream
- S(0)
- false
- 0
-
-11161
14758
24
60
-
-11149
14788
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- 21885950-be69-465c-9d96-960f153c1764
- 269cc0bb-67ab-43ed-a590-db3e7b6ab08f
- 2
- b718a122-9098-4399-a42f-a974dc783cd7
- Group
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- a740a9fc-8b55-4c5c-a871-f76e1efb3a41
- Stream Filter
- Stream Filter
-
-11227
15907
92
64
-
-11173
15939
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 1bac5d72-7374-401e-bbea-792f52769d0f
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
15909
40
20
-
-11205
15919
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 7fdefbf2-2487-451b-99fe-444e9f9a1b96
- false
- Stream 0
- 0
- true
- 0
-
-11225
15929
40
20
-
-11205
15939
- 2
- Input stream at index 1
- ecac3ee8-866c-4c84-adc9-06193c3e68a8
- false
- Stream 1
- 1
- true
- 11ceca9b-30b2-4213-b35d-85e5be45643a
- 1
-
-11225
15949
40
20
-
-11205
15959
- 2
- Filtered stream
- c0cb4ede-8eab-4fd5-9c53-b62df174b453
- false
- Stream
- S(0)
- false
- 0
-
-11161
15909
24
60
-
-11149
15939
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 074a7f4a-bb6e-4134-9cbd-8a3674cd6458
- Stream Filter
- Stream Filter
-
-11227
15780
92
64
-
-11173
15812
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 21e3aca0-77dd-499a-99b5-265b7782e734
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
15782
40
20
-
-11205
15792
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 1c62efb8-aa5e-432e-a3ce-d919a2e82c28
- false
- Stream 0
- 0
- true
- 0
-
-11225
15802
40
20
-
-11205
15812
- 2
- Input stream at index 1
- 84fe6fe7-3c54-4b99-a392-fae62be28538
- false
- Stream 1
- 1
- true
- b7cf406c-d92d-4328-9b8e-d0e00d9cb12a
- 1
-
-11225
15822
40
20
-
-11205
15832
- 2
- Filtered stream
- bec1d112-916e-46f3-aec4-8d3439e35c7f
- false
- Stream
- S(0)
- false
- 0
-
-11161
15782
24
60
-
-11149
15812
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- a740a9fc-8b55-4c5c-a871-f76e1efb3a41
- 074a7f4a-bb6e-4134-9cbd-8a3674cd6458
- 2
- d0cbf364-bbd3-443f-baf9-ddf9faa06c95
- Group
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- ca8ca783-f945-428f-a2f3-e0f01c9d6b16
- Stream Filter
- Stream Filter
-
-11227
17087
92
64
-
-11173
17119
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 90ecef0b-9236-441c-a23f-6a5ab3009534
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
17089
40
20
-
-11205
17099
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- f0caa3d9-32b1-4924-902e-592380384fda
- false
- Stream 0
- 0
- true
- 0
-
-11225
17109
40
20
-
-11205
17119
- 2
- Input stream at index 1
- e2dae74c-9f51-441d-a4fb-3cd6933b04c7
- false
- Stream 1
- 1
- true
- 29946d34-0db3-4cc0-bbb0-27c79f7c8eb9
- 1
-
-11225
17129
40
20
-
-11205
17139
- 2
- Filtered stream
- c1a066d8-bd60-41c5-aa56-6f9a6e46db6f
- false
- Stream
- S(0)
- false
- 0
-
-11161
17089
24
60
-
-11149
17119
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 5a1f7027-0875-4c99-9a72-e52c18b199e4
- Stream Filter
- Stream Filter
-
-11227
16960
92
64
-
-11173
16992
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- b6110d43-b2e8-4417-b027-d4c7f9597bc7
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
16962
40
20
-
-11205
16972
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 9560843a-4de3-4059-a942-481ddeac3fbb
- false
- Stream 0
- 0
- true
- 0
-
-11225
16982
40
20
-
-11205
16992
- 2
- Input stream at index 1
- 800847d4-b720-4cb9-97f6-f12f98eb114e
- false
- Stream 1
- 1
- true
- 2f545125-747a-4904-9cb7-05bc0727e11d
- 1
-
-11225
17002
40
20
-
-11205
17012
- 2
- Filtered stream
- 5f27d6a1-8003-43a4-bbbb-1f5ca0d473f0
- false
- Stream
- S(0)
- false
- 0
-
-11161
16962
24
60
-
-11149
16992
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
- ca8ca783-f945-428f-a2f3-e0f01c9d6b16
- 5a1f7027-0875-4c99-9a72-e52c18b199e4
- 2
- 1c15b9f5-09dc-4725-ac96-59ef9df1e148
- Group
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 677fd46b-d68b-4325-99d3-40ba2c3fc641
- Stream Filter
- Stream Filter
-
-11227
18184
92
64
-
-11173
18216
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- e77c1f91-65fa-4900-a828-555611124af4
- Gate
- Gate
- false
- 17741e82-4e3d-4b9f-9969-9d69c7808425
- 1
-
-11225
18186
40
20
-
-11205
18196
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 0042b91f-33d6-4545-8c19-912f2f51caeb
- false
- Stream 0
- 0
- true
- 0
-
-11225
18206
40
20
-
-11205
18216
- 2
- Input stream at index 1
- 8eb2df1d-fcea-4dc5-93d2-59e30a899241
- false
- Stream 1
- 1
- true
- 587de0b9-9f06-4d87-bf93-b93668a84499
- 1
-
-11225
18226
40
20
-
-11205
18236
- 2
- Filtered stream
- e3599a80-f9c8-4366-b990-b219b6a91609
- false
- Stream
- S(0)
- false
- 0
-
-11161
18186
24
60
-
-11149
18216
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 1a53acd3-457c-4985-ad35-d636350ac9ca
- Stream Filter
- Stream Filter
-
-11227
18057
92
64
-
-11173
18089
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193
101
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35
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35
40
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84
44
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30
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26
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116
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116
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38
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196
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136
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136
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136
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32
100
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135
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80
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166
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90
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90
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48
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116
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35
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84
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116
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26
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- Create a polyline connecting a number of points.
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116
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38
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- Merge a bunch of data streams
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136
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136
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100
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83
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83
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83
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83
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35
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26
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50
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38
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26
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38
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196
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90
64
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31
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31
20
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19587
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19537
31
60
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19567
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40
16
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19556
196
104
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19608
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19558
136
20
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19568
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19578
136
20
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19588
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0;255;255;255
- The stroke weight
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19598
136
20
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19608
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- The stroke pattern
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19618
136
20
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19628
- The shape to be used at the end of open path
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19638
136
20
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19648
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19558
32
100
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19608
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19512
135
84
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- Remove null items from the tree.
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19514
83
20
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19524
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- Remove invalid items from the tree.
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19534
83
20
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19544
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- Remove empty branches from the tree.
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19554
83
20
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19564
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83
20
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- Spotless data tree
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19514
24
80
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19554
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2724
70
22
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255;255;255;255
- A group of Grasshopper objects
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40
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255;255;255;255
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- Stream Filter
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92
64
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- Index of Gate stream
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40
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40
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40
20
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24
60
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3052
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- Stream Filter
- Filters a collection of input streams
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- Stream Filter
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92
64
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4063
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40
20
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40
20
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40
20
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24
60
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- Stream Filter
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- Stream Filter
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92
64
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40
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40
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40
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24
60
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4975
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- Stream Filter
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5969
92
64
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6001
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40
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40
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40
20
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5971
24
60
-
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6001
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- Stream Filter
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7115
92
64
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40
20
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40
20
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40
20
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7117
24
60
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7147
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
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92
64
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40
20
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40
20
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40
20
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24
60
-
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- Stream Filter
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92
64
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40
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40
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40
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24
60
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- Stream Filter
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92
64
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40
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40
20
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40
20
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24
60
-
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- Stream Filter
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11677
92
64
-
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- 92dfb677-4945-46c1-ba10-6d9d2f3a170e
- 1
-
-7075
11679
40
20
-
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11689
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 381db23c-40f2-4021-afd3-85010a193c00
- false
- Stream 0
- 0
- true
- 0
-
-7075
11699
40
20
-
-7055
11709
- 2
- Input stream at index 1
- f24880ec-3c8b-4ef8-8553-fadec6b85d96
- false
- Stream 1
- 1
- true
- c6e722f2-92b0-4558-beb1-fba620419e63
- 1
-
-7075
11719
40
20
-
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11729
- 2
- Filtered stream
- aeb61ff0-bd0a-4098-9475-efec72c7673e
- false
- Stream
- S(0)
- false
- 0
-
-7011
11679
24
60
-
-6999
11709
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- f0e96c3f-e779-44a4-9862-315edd179c43
- Stream Filter
- Stream Filter
-
-7017
12915
92
64
-
-6963
12947
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 1e78bad0-2df3-443c-b14f-9b6f48e3a96d
- Gate
- Gate
- false
- 92dfb677-4945-46c1-ba10-6d9d2f3a170e
- 1
-
-7015
12917
40
20
-
-6995
12927
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 29b9ee40-fa7c-434a-8169-183398e57a15
- false
- Stream 0
- 0
- true
- 0
-
-7015
12937
40
20
-
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12947
- 2
- Input stream at index 1
- 47b12ec4-d344-4d33-b2d9-05e633a6fdca
- false
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- 1
- true
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- 1
-
-7015
12957
40
20
-
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12967
- 2
- Filtered stream
- 4b0cab58-d257-4fb7-b9a9-1b04f696e2d2
- false
- Stream
- S(0)
- false
- 0
-
-6951
12917
24
60
-
-6939
12947
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- b017d256-9aa7-4060-98d9-5e784a0a7cd9
- Stream Filter
- Stream Filter
-
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14088
92
64
-
-6943
14120
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
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- Gate
- Gate
- false
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- 1
-
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14090
40
20
-
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14100
- 1
- 1
- {0}
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- 2
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- false
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- 0
- true
- 0
-
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14110
40
20
-
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14120
- 2
- Input stream at index 1
- ceb29de5-b1a3-4559-8146-d37078b28f88
- false
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- 1
- true
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- 1
-
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14130
40
20
-
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14140
- 2
- Filtered stream
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- false
- Stream
- S(0)
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- 0
-
-6931
14090
24
60
-
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14120
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- b664df6a-5160-42e7-87b8-af9f0ea1ee2b
- Stream Filter
- Stream Filter
-
-7012
15164
92
64
-
-6958
15196
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
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- Gate
- Gate
- false
- 92dfb677-4945-46c1-ba10-6d9d2f3a170e
- 1
-
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15166
40
20
-
-6990
15176
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 0b82203c-37e3-4e34-a3b8-904d9d892742
- false
- Stream 0
- 0
- true
- 0
-
-7010
15186
40
20
-
-6990
15196
- 2
- Input stream at index 1
- f8052ad8-4ad0-41de-a504-d9e881240d73
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- 1
- true
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- 1
-
-7010
15206
40
20
-
-6990
15216
- 2
- Filtered stream
- d9c00061-44f3-4e23-ba0c-cc1b7e5671df
- false
- Stream
- S(0)
- false
- 0
-
-6946
15166
24
60
-
-6934
15196
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
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- Stream Filter
- Stream Filter
-
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16167
92
64
-
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16199
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
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- 1
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- Index of Gate stream
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- Gate
- Gate
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-
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16169
40
20
-
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16179
- 1
- 1
- {0}
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- 8014dc77-ab2a-45db-86b8-56d8e2730d32
- false
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-
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16189
40
20
-
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16199
- 2
- Input stream at index 1
- 0e3e51de-66ab-4127-b872-4ef8c2ef2b67
- false
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- 1
- true
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- 1
-
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16209
40
20
-
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16219
- 2
- Filtered stream
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- false
- Stream
- S(0)
- false
- 0
-
-6887
16169
24
60
-
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16199
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 94d38037-9a7a-4ac3-a117-fac9adb58793
- Stream Filter
- Stream Filter
-
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17296
92
64
-
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17328
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
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- Gate
- Gate
- false
- 92dfb677-4945-46c1-ba10-6d9d2f3a170e
- 1
-
-6960
17298
40
20
-
-6940
17308
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 40d0ebce-b00e-4be8-aaf8-1eb5645b63d0
- false
- Stream 0
- 0
- true
- 0
-
-6960
17318
40
20
-
-6940
17328
- 2
- Input stream at index 1
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- false
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- 1
- true
- be615a1b-b5ca-456f-9216-7ca55cad191c
- 1
-
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17338
40
20
-
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17348
- 2
- Filtered stream
- e232eef0-15de-49e4-b844-a2a662441091
- false
- Stream
- S(0)
- false
- 0
-
-6896
17298
24
60
-
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17328
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- ae977cc2-007b-4819-aab1-607bc574da3d
- Stream Filter
- Stream Filter
-
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18452
92
64
-
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18484
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
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- Gate
- Gate
- false
- 92dfb677-4945-46c1-ba10-6d9d2f3a170e
- 1
-
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18454
40
20
-
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18464
- 1
- 1
- {0}
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- 2
- Input stream at index 0
- 2f671999-2df2-49bd-a78a-0968fb4e4704
- false
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-
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18474
40
20
-
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18484
- 2
- Input stream at index 1
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- false
- Stream 1
- 1
- true
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- 1
-
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18494
40
20
-
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18504
- 2
- Filtered stream
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- Stream
- S(0)
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- 0
-
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18454
24
60
-
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18484
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
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- 40d0d220-c1df-41fe-a4ac-5d725e326324
- Stream Filter
- Stream Filter
-
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19591
92
64
-
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19623
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
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- Gate
- Gate
- false
- 92dfb677-4945-46c1-ba10-6d9d2f3a170e
- 1
-
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19593
40
20
-
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19603
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 64c59ebc-ffa2-49d1-8621-423b5b4f03a6
- false
- Stream 0
- 0
- true
- 0
-
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19613
40
20
-
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19623
- 2
- Input stream at index 1
- 286cdb93-f769-441f-a32f-c56ca6656fde
- false
- Stream 1
- 1
- true
- df097d69-a4f5-4ef7-ab1f-1a0727ff6f06
- 1
-
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19633
40
20
-
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19643
- 2
- Filtered stream
- 7c3b70d3-ffab-4356-a42b-31da084be03a
- false
- Stream
- S(0)
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- 0
-
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19593
24
60
-
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19623
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 3
-
255;255;255;255
- A group of Grasshopper objects
- 38e33091-5805-4830-b960-f7b95e820fd2
- 1
- a1ac0900-3dd8-44d2-860f-83352b920fda
- Group
- ᗱᗴ
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- Panel
- A panel for custom notes and text values
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- Panel
- #
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- 0
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- 1024
-
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156
160
100
- 0
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-
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156.4436
-
255;255;255;255
- true
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- true
- false
- false
- true
- 3e8ca6be-fda8-4aaf-b5c0-3c54c8bb7312
- Number
- Contains a collection of floating point numbers
- e2d5421d-793a-4786-9e3b-7530f182e59f
- Number
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- false
- 0
-
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86
49
24
-
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98.35362
- 59e0b89a-e487-49f8-bab8-b5bab16be14c
- Panel
- A panel for custom notes and text values
- 1e42e4ee-225b-427d-95a0-827d03bae077
- Panel
- ⊚
- false
- 0
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- 1
-
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764
147
55
- 0
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-
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764.59
- 2
-
255;255;255;255
- false
- false
- true
- false
- false
- true
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- 35cc33c8-2ec6-4de4-82f7-cbdc643d1827
- Null Item
- Null Item
-
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11580
128
64
-
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11612
- Item to test
- a17212d0-4c05-4c33-8e3d-389e5333f6de
- Item
- Item
- true
- c6e722f2-92b0-4558-beb1-fba620419e63
- 1
-
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11582
24
60
-
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11612
- True if item is Null
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- 1
- Null Flags
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- false
- 0
-
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11582
76
20
-
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11592
- True if item is Invalid
- bf5046cf-2155-4f6e-aa97-c7c55ce87f98
- Invalid Flags
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- false
- 0
-
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11602
76
20
-
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11612
- A textual description of the object state
- a10398c8-44c9-4840-97e2-4a47e8b317c9
- Description
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- false
- 0
-
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11622
76
20
-
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11632
- 7c9d9882-545d-434b-9850-2f3c6b01296b
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- Min / Max
- Extract the minimum and the maximum value of a list of numbers
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- Min / Max
- Min / Max
-
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11580
115
44
-
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11602
- 1
- Set of Numbers
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- Number
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- 1
-
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11582
39
40
-
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11602
- Minimum
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- Minimum
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- 0
-
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11582
48
20
-
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11592
- Maximum
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- Maximum
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-
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11602
48
20
-
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11612
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
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- Gate Not
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-
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11584
70
28
-
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11598
- Boolean value
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- A
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11586
11
24
-
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11598
- Inverse of {A}
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11586
31
24
-
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11598
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
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- Stream Filter
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-
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11719
92
64
-
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11751
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- Index of Gate stream
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- Gate
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- 1
-
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11721
40
20
-
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11731
- 1
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- {0}
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- Input stream at index 0
- 4ef35a03-9705-4eb0-9f68-1816dc541ae1
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-
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11741
40
20
-
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11751
- 2
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- 1
-
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11761
40
20
-
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11771
- 2
- Filtered stream
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11721
24
60
-
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11751
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
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- Null Item
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-
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2953
128
64
-
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2985
- Item to test
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- Item
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- 1
-
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2955
24
60
-
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2985
- True if item is Null
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- Null Flags
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-
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2955
76
20
-
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2965
- True if item is Invalid
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- Invalid Flags
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-
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2975
76
20
-
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2985
- A textual description of the object state
- 9127bce0-f88e-4b9b-8325-b682b0d2be9a
- Description
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- 0
-
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76
20
-
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- 7c9d9882-545d-434b-9850-2f3c6b01296b
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- Extract the minimum and the maximum value of a list of numbers
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- Min / Max
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-
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115
44
-
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2965
- 1
- Set of Numbers
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- a70c3c9f-2f96-442b-beec-394a2663079b
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-
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39
40
-
-7575.5
2965
- Minimum
- 330c5023-18e8-4911-af46-8bb9d7a1fdf4
- Minimum
- Minimum
- false
- 0
-
-7532
2945
48
20
-
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2955
- Maximum
- 0b1b7c6e-4ca1-4bcd-b0f9-21d2409f20bd
- Maximum
- Maximum
- false
- 0
-
-7532
2965
48
20
-
-7508
2975
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- 189dd2a9-82f7-49c4-878c-0e52bb36583f
- Gate Not
- Gate Not
-
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2961
70
28
-
-7434
2975
- Boolean value
- 901f909c-7bb2-417a-97ff-4963637a9801
- A
- A
- false
- 0b1b7c6e-4ca1-4bcd-b0f9-21d2409f20bd
- 1
-
-7457
2963
11
24
-
-7451.5
2975
- Inverse of {A}
- 538bcd17-2e47-46da-b7c8-d30390ab8c9c
- Result
- Result
- false
- 0
-
-7422
2963
31
24
-
-7406.5
2975
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- ac4eb0e1-0629-423d-86d3-698fe1fbe3be
- Stream Filter
- Stream Filter
-
-5795
2997
92
64
-
-5741
3029
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 33978c7b-0a2d-46eb-b2d9-63c16f7a391c
- Gate
- Gate
- false
- 538bcd17-2e47-46da-b7c8-d30390ab8c9c
- 1
-
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2999
40
20
-
-5773
3009
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- e146e615-c617-4312-a7d2-08ee2a1b3ab3
- false
- Stream 0
- 0
- true
- 0
-
-5793
3019
40
20
-
-5773
3029
- 2
- Input stream at index 1
- 64d60379-b575-4112-bc03-90d913bcd4c1
- false
- Stream 1
- 1
- true
- cc39f9f6-c9c7-4df2-b57d-b44bce6c64c0
- 1
-
-5793
3039
40
20
-
-5773
3049
- 2
- Filtered stream
- 75fc82ae-e535-43d8-8cea-21b2a580a62e
- false
- Stream
- S(1)
- false
- 0
-
-5729
2999
24
60
-
-5717
3029
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- a8094a18-bafe-447f-a1e5-d50f443f6c8d
- Null Item
- Null Item
-
-7219
3929
128
64
-
-7181
3961
- Item to test
- 82a62292-6bc5-47d6-b336-1369d94ba43a
- Item
- Item
- true
- bf02b6a7-2c32-4838-9324-0fa547efef5e
- 1
-
-7217
3931
24
60
-
-7205
3961
- True if item is Null
- c3a4ae0a-d5e9-483b-a4dc-2ea16ff547d4
- 1
- Null Flags
- Null Flags
- false
- 0
-
-7169
3931
76
20
-
-7139
3941
- True if item is Invalid
- 86d204a4-ec45-4555-ad20-960e96e72291
- Invalid Flags
- Invalid Flags
- false
- 0
-
-7169
3951
76
20
-
-7139
3961
- A textual description of the object state
- 1a0611c8-0f02-4920-bb42-ecae33d37518
- Description
- Description
- false
- 0
-
-7169
3971
76
20
-
-7139
3981
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- be452c49-8669-4366-becd-7b6bb0edf3ce
- Min / Max
- Min / Max
-
-7055
3929
115
44
-
-7002
3951
- 1
- Set of Numbers
- fe9cc553-c348-415d-a674-35ca07f8cb3f
- Number
- Number
- false
- c3a4ae0a-d5e9-483b-a4dc-2ea16ff547d4
- 1
-
-7053
3931
39
40
-
-7033.5
3951
- Minimum
- 8208d769-9be0-477f-8940-4b5859bf4c22
- Minimum
- Minimum
- false
- 0
-
-6990
3931
48
20
-
-6966
3941
- Maximum
- d598ed14-f257-4d9b-a5f3-99946b1fbb4d
- Maximum
- Maximum
- false
- 0
-
-6990
3951
48
20
-
-6966
3961
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- d646942a-7636-44c6-98e1-f72444dfd831
- Gate Not
- Gate Not
-
-6904
3933
70
28
-
-6879
3947
- Boolean value
- 8ab5f103-6967-4002-8173-15d9a6fe2d8e
- A
- A
- false
- d598ed14-f257-4d9b-a5f3-99946b1fbb4d
- 1
-
-6902
3935
11
24
-
-6896.5
3947
- Inverse of {A}
- 5fa81d7b-ae98-4e4a-bfdb-9ada698cf631
- Result
- Result
- false
- 0
-
-6867
3935
31
24
-
-6851.5
3947
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 2df6c65e-08c7-4660-9cc8-f4a18301d889
- Stream Filter
- Stream Filter
-
-5777
3985
92
64
-
-5723
4017
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 16406ef3-d8bd-4150-be29-dead03773ad7
- Gate
- Gate
- false
- 5fa81d7b-ae98-4e4a-bfdb-9ada698cf631
- 1
-
-5775
3987
40
20
-
-5755
3997
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 93e1a8fc-06ec-42ce-b0ab-e189211ba4d3
- false
- Stream 0
- 0
- true
- 0
-
-5775
4007
40
20
-
-5755
4017
- 2
- Input stream at index 1
- 120144d8-961e-4ffc-87b7-f4de9a43fe62
- false
- Stream 1
- 1
- true
- b67db8b0-4ac4-430d-be27-39be205c7d61
- 1
-
-5775
4027
40
20
-
-5755
4037
- 2
- Filtered stream
- 9fcffae3-3a3f-4651-a205-1f89243e9353
- false
- Stream
- S(1)
- false
- 0
-
-5711
3987
24
60
-
-5699
4017
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- d7f3135f-1177-4b0f-8b05-6ce46940feb4
- Null Item
- Null Item
-
-7147
4863
128
64
-
-7109
4895
- Item to test
- 7a5e3346-84c6-4356-96e0-47a3a51f957e
- Item
- Item
- true
- 9aa9fdf5-c248-4bf6-afe3-b324ca007251
- 1
-
-7145
4865
24
60
-
-7133
4895
- True if item is Null
- 53617fcd-cb0c-43ea-a0e9-9a35a5ee4099
- 1
- Null Flags
- Null Flags
- false
- 0
-
-7097
4865
76
20
-
-7067
4875
- True if item is Invalid
- b78284f8-37d3-4341-ad05-89a04047fe05
- Invalid Flags
- Invalid Flags
- false
- 0
-
-7097
4885
76
20
-
-7067
4895
- A textual description of the object state
- 058b65a1-c2e5-4625-8df7-3570ebf8e99f
- Description
- Description
- false
- 0
-
-7097
4905
76
20
-
-7067
4915
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- 00ceb525-9e87-4db3-9802-667580ba1078
- Min / Max
- Min / Max
-
-6983
4863
115
44
-
-6930
4885
- 1
- Set of Numbers
- c3315609-f58f-4506-b8ef-5b499ee91f26
- Number
- Number
- false
- 53617fcd-cb0c-43ea-a0e9-9a35a5ee4099
- 1
-
-6981
4865
39
40
-
-6961.5
4885
- Minimum
- 6eecbe0a-786e-4500-9023-e0036260ce84
- Minimum
- Minimum
- false
- 0
-
-6918
4865
48
20
-
-6894
4875
- Maximum
- 93be164d-631d-4706-aaa0-61f1c643d2e6
- Maximum
- Maximum
- false
- 0
-
-6918
4885
48
20
-
-6894
4895
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- f3c88c5d-9ab5-4a48-8e2b-b86ef9537f38
- Gate Not
- Gate Not
-
-6832
4867
70
28
-
-6807
4881
- Boolean value
- 9af6d155-d97a-4a53-a1e5-d55dcbf2dca3
- A
- A
- false
- 93be164d-631d-4706-aaa0-61f1c643d2e6
- 1
-
-6830
4869
11
24
-
-6824.5
4881
- Inverse of {A}
- fbb890a1-5183-4102-944f-95013c6261bd
- Result
- Result
- false
- 0
-
-6795
4869
31
24
-
-6779.5
4881
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 17755101-7062-42de-ba3b-de5fe2af1944
- Stream Filter
- Stream Filter
-
-5677
4913
92
64
-
-5623
4945
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- f49fe484-3cfc-47b0-aadd-80e2434a514a
- Gate
- Gate
- false
- fbb890a1-5183-4102-944f-95013c6261bd
- 1
-
-5675
4915
40
20
-
-5655
4925
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- b0223655-9b78-4e47-ace1-2cc5ed775f3a
- false
- Stream 0
- 0
- true
- 0
-
-5675
4935
40
20
-
-5655
4945
- 2
- Input stream at index 1
- e1e8c4b5-f1e0-4114-a673-f363d5af642c
- false
- Stream 1
- 1
- true
- 25d8da2c-a18b-475a-87f0-e332861fb3b3
- 1
-
-5675
4955
40
20
-
-5655
4965
- 2
- Filtered stream
- e49badfa-457c-44b7-a041-d1654e42fc37
- false
- Stream
- S(1)
- false
- 0
-
-5611
4915
24
60
-
-5599
4945
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- 6cb3cdab-825d-4a25-b6d7-c8ce93e6b860
- Null Item
- Null Item
-
-7063
5875
128
64
-
-7025
5907
- Item to test
- 05d22590-dfa4-487b-b9fc-40746c5187e9
- Item
- Item
- true
- 14273b4c-e52e-48ca-b8ab-682e73fe2600
- 1
-
-7061
5877
24
60
-
-7049
5907
- True if item is Null
- 9f954724-61fd-4f30-bf3b-5be741d2ad38
- 1
- Null Flags
- Null Flags
- false
- 0
-
-7013
5877
76
20
-
-6983
5887
- True if item is Invalid
- e5ac74b2-2304-49c2-ab3b-e514ffb5d702
- Invalid Flags
- Invalid Flags
- false
- 0
-
-7013
5897
76
20
-
-6983
5907
- A textual description of the object state
- 3f775720-99c8-4d87-8082-1a114e50fb73
- Description
- Description
- false
- 0
-
-7013
5917
76
20
-
-6983
5927
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- 072e65b2-2f5a-4a67-ba98-de57ff321e0a
- Min / Max
- Min / Max
-
-6899
5875
115
44
-
-6846
5897
- 1
- Set of Numbers
- 3ee8b196-b2a7-43bd-87fa-c9d70c55996f
- Number
- Number
- false
- 9f954724-61fd-4f30-bf3b-5be741d2ad38
- 1
-
-6897
5877
39
40
-
-6877.5
5897
- Minimum
- f4b55248-208f-4228-ab11-054e59d08b2a
- Minimum
- Minimum
- false
- 0
-
-6834
5877
48
20
-
-6810
5887
- Maximum
- e4b0b066-26b0-448e-a5c8-f4e5c3b4bcc8
- Maximum
- Maximum
- false
- 0
-
-6834
5897
48
20
-
-6810
5907
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- 01823b6f-3915-46e2-bb6c-45ee2f0b1d75
- Gate Not
- Gate Not
-
-6748
5879
70
28
-
-6723
5893
- Boolean value
- 0927c3b9-4aa8-43e1-9078-1096f8ec3895
- A
- A
- false
- e4b0b066-26b0-448e-a5c8-f4e5c3b4bcc8
- 1
-
-6746
5881
11
24
-
-6740.5
5893
- Inverse of {A}
- d3d8423d-b76c-460e-8176-3ebcb3be397d
- Result
- Result
- false
- 0
-
-6711
5881
31
24
-
-6695.5
5893
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 87135cf1-b079-4cb3-bf64-3722c5ca823e
- Stream Filter
- Stream Filter
-
-5593
5925
92
64
-
-5539
5957
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 204e91b7-8b54-469d-8ad1-fb4ff58123c3
- Gate
- Gate
- false
- d3d8423d-b76c-460e-8176-3ebcb3be397d
- 1
-
-5591
5927
40
20
-
-5571
5937
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 453b8df4-ff60-46ce-88f0-6efb394b4562
- false
- Stream 0
- 0
- true
- 0
-
-5591
5947
40
20
-
-5571
5957
- 2
- Input stream at index 1
- 3b3e7dd0-c139-49fb-a308-7abf58d2d736
- false
- Stream 1
- 1
- true
- 51de33f0-e511-4a37-8537-cce5e8deb152
- 1
-
-5591
5967
40
20
-
-5571
5977
- 2
- Filtered stream
- e9c7e654-d046-48b6-9a42-23807c78b8a8
- false
- Stream
- S(1)
- false
- 0
-
-5527
5927
24
60
-
-5515
5957
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- 4f25cec0-7e3f-43b9-a363-1b7cd2747a9f
- Null Item
- Null Item
-
-7060
7022
128
64
-
-7022
7054
- Item to test
- f993cfcd-d680-46b8-a928-2bfb242ea0d7
- Item
- Item
- true
- 43c898bd-1523-42e9-9485-b3cd42382016
- 1
-
-7058
7024
24
60
-
-7046
7054
- True if item is Null
- 71caca59-5a1d-4b88-9d15-ba7633f6f69a
- 1
- Null Flags
- Null Flags
- false
- 0
-
-7010
7024
76
20
-
-6980
7034
- True if item is Invalid
- dfc56233-4395-44f5-be6e-afcaff8f8714
- Invalid Flags
- Invalid Flags
- false
- 0
-
-7010
7044
76
20
-
-6980
7054
- A textual description of the object state
- 3b681b16-66d2-4e3b-b309-b5b35b58583d
- Description
- Description
- false
- 0
-
-7010
7064
76
20
-
-6980
7074
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- 4bec467c-e348-430f-a67d-ad4288ebf902
- Min / Max
- Min / Max
-
-6896
7022
115
44
-
-6843
7044
- 1
- Set of Numbers
- 3bb95461-355d-431f-b4d5-6a0dcee3139d
- Number
- Number
- false
- 71caca59-5a1d-4b88-9d15-ba7633f6f69a
- 1
-
-6894
7024
39
40
-
-6874.5
7044
- Minimum
- 1fd4fb0a-fd07-4924-a15e-e0cb43abe349
- Minimum
- Minimum
- false
- 0
-
-6831
7024
48
20
-
-6807
7034
- Maximum
- 1a36e77a-f207-41a8-8a48-ef7fb3367cdd
- Maximum
- Maximum
- false
- 0
-
-6831
7044
48
20
-
-6807
7054
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- a97852d9-a598-4352-8c86-7221c33fc96a
- Gate Not
- Gate Not
-
-6745
7026
70
28
-
-6720
7040
- Boolean value
- 772cd3dd-b907-4181-aa81-efc2848f1411
- A
- A
- false
- 1a36e77a-f207-41a8-8a48-ef7fb3367cdd
- 1
-
-6743
7028
11
24
-
-6737.5
7040
- Inverse of {A}
- d7a5e523-7978-46d0-9ffe-8254a2b71250
- Result
- Result
- false
- 0
-
-6708
7028
31
24
-
-6692.5
7040
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 2c24899b-2b57-4192-8893-96e535b58ccd
- Stream Filter
- Stream Filter
-
-5537
7082
92
64
-
-5483
7114
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
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- Gate
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7084
40
20
-
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7094
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7104
40
20
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7114
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7124
40
20
-
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7134
- 2
- Filtered stream
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- Stream
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-
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7084
24
60
-
-5459
7114
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- 37488903-bcf2-4b36-a4bf-5cc30a0b9a3c
- Null Item
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-
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8147
128
64
-
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8179
- Item to test
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- Item
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8149
24
60
-
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8179
- True if item is Null
- ddaf865a-6a4f-4207-8f3b-9c3d651c3962
- 1
- Null Flags
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-
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8149
76
20
-
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8159
- True if item is Invalid
- 7665f0dc-1418-4dc5-8995-e4ea104a0578
- Invalid Flags
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8169
76
20
-
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8179
- A textual description of the object state
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8189
76
20
-
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8199
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
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- Extract the minimum and the maximum value of a list of numbers
- true
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- Min / Max
- Min / Max
-
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8147
115
44
-
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8169
- 1
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- Number
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8149
39
40
-
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8169
- Minimum
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48
20
-
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8159
- Maximum
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8169
48
20
-
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8179
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- true
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- Gate Not
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8151
70
28
-
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8165
- Boolean value
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11
24
-
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- Inverse of {A}
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8153
31
24
-
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- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
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- true
- 204e7fe9-7a7e-479a-b489-4892b355619f
- Stream Filter
- Stream Filter
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8207
92
64
-
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8239
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- Index of Gate stream
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- Gate
- Gate
- false
- b16f4576-fb27-4f10-9fe6-0e4da0596c1a
- 1
-
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8209
40
20
-
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8219
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8229
40
20
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8239
- 2
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- 1
- true
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- 1
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8249
40
20
-
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8259
- 2
- Filtered stream
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-
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8209
24
60
-
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8239
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
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- Null Item
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-
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9353
128
64
-
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9385
- Item to test
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- Item
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-
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9355
24
60
-
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9385
- True if item is Null
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- 1
- Null Flags
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-
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9355
76
20
-
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9365
- True if item is Invalid
- 0d2c0dc8-f3ea-431e-9788-c6837d202db8
- Invalid Flags
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- 0
-
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9375
76
20
-
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9385
- A textual description of the object state
- bdb6013c-1541-4765-a267-1cf5d8d4a3ad
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9395
76
20
-
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9405
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
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- Extract the minimum and the maximum value of a list of numbers
- true
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- Min / Max
- Min / Max
-
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9353
115
44
-
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9375
- 1
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- Number
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- 2b4a67fb-ae7c-4ba1-bc65-027125293f34
- 1
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9355
39
40
-
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9375
- Minimum
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- Minimum
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-
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9355
48
20
-
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9365
- Maximum
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-
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9375
48
20
-
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9385
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
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- Gate Not
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-
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9357
70
28
-
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9371
- Boolean value
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- A
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11
24
-
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- Inverse of {A}
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- Result
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-
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31
24
-
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9371
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
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- ccbe8cdf-717b-4b38-a4b0-d2265f7b5b4d
- Stream Filter
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-
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92
64
-
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9445
- 3
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- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
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- Gate
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- f95d28f9-5c1b-4737-880d-d56ef8853fd9
- 1
-
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9415
40
20
-
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9425
- 1
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- Input stream at index 0
- 893def05-ac6b-49ca-9d84-5f626fe4fcf6
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-
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9435
40
20
-
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9445
- 2
- Input stream at index 1
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- false
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- 1
- true
- ad549466-4ec2-4830-aced-c029153ed38a
- 1
-
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9455
40
20
-
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9465
- 2
- Filtered stream
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-
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9415
24
60
-
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9445
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- ef845926-e270-4238-9c31-7826bcd7dc35
- Null Item
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-
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10521
128
64
-
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10553
- Item to test
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- Item
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-
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10523
24
60
-
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10553
- True if item is Null
- f24a96ec-f551-424d-b26a-072846e268de
- 1
- Null Flags
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-
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10523
76
20
-
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10533
- True if item is Invalid
- 0663b653-456a-4146-93ca-64ca58e64262
- Invalid Flags
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- 0
-
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10543
76
20
-
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10553
- A textual description of the object state
- f8cb1f09-78c3-4b9f-94af-5b7bb63e1fb9
- Description
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-
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10563
76
20
-
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10573
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- bfeb3fd9-9103-4fd0-95ac-022b5a5f48c1
- Min / Max
- Min / Max
-
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10521
115
44
-
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10543
- 1
- Set of Numbers
- e6f63a9c-2422-4f1b-ab10-3931a44cbea1
- Number
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- false
- f24a96ec-f551-424d-b26a-072846e268de
- 1
-
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10523
39
40
-
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10543
- Minimum
- ea7d8250-db50-42c3-b883-81505d9a4d09
- Minimum
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- 0
-
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10523
48
20
-
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10533
- Maximum
- 5a85cc1f-6412-43ab-9da8-073b8bf971a4
- Maximum
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- false
- 0
-
-6794
10543
48
20
-
-6770
10553
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- 192df5d3-f93a-4aef-a40e-cbad90f6d75b
- Gate Not
- Gate Not
-
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10525
70
28
-
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10539
- Boolean value
- 1505cf56-234b-45ad-bc75-ef43fab88efb
- A
- A
- false
- 5a85cc1f-6412-43ab-9da8-073b8bf971a4
- 1
-
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10527
11
24
-
-6700.5
10539
- Inverse of {A}
- 6aa859da-faad-431e-8679-ca71bf8af6fe
- Result
- Result
- false
- 0
-
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10527
31
24
-
-6655.5
10539
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 25c75de0-e074-469e-af87-ed42c1e4189a
- Stream Filter
- Stream Filter
-
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10581
92
64
-
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10613
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- c9427943-f9a8-4d48-8a43-7797e98aa96a
- Gate
- Gate
- false
- 6aa859da-faad-431e-8679-ca71bf8af6fe
- 1
-
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10583
40
20
-
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10593
- 1
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- Input stream at index 0
- 7a2c1e3d-a216-4034-9974-967db57e4d3f
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-
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10603
40
20
-
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10613
- 2
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- 9979f7c5-ee42-4ff1-91fe-d3b6929249b4
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- 1
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- 0de2eaa7-c2bc-4cbc-b548-271df3bcf16a
- 1
-
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10623
40
20
-
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10633
- 2
- Filtered stream
- ba724b87-59f4-42c1-b032-80d0e7a043b6
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-
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10583
24
60
-
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10613
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
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- true
- 6fe9ab0f-7fbf-4f24-b49d-8304568d8891
- Null Item
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-
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12802
128
64
-
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- Item to test
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- Item
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24
60
-
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12834
- True if item is Null
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- Null Flags
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-
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76
20
-
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12814
- True if item is Invalid
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-
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12824
76
20
-
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12834
- A textual description of the object state
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-
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12844
76
20
-
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12854
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- a5b1c0c0-ed53-4928-9e19-8b13e166f8f5
- Min / Max
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-
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115
44
-
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12824
- 1
- Set of Numbers
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- Number
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- 82ba3565-15cc-43a6-bdb7-bb0c8ae0ea70
- 1
-
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39
40
-
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12824
- Minimum
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- Minimum
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-
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12804
48
20
-
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12814
- Maximum
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- Maximum
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-
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12824
48
20
-
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12834
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- f7ba651d-d70d-496b-a389-a5b02e0b590b
- Gate Not
- Gate Not
-
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12806
70
28
-
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12820
- Boolean value
- 84082a0b-436f-4eff-9826-68e040df03b5
- A
- A
- false
- 95d42b9f-4d49-4210-81a8-27c77c8defdb
- 1
-
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12808
11
24
-
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12820
- Inverse of {A}
- 7e03e96a-60c3-44b8-8508-4a0249f6e5a0
- Result
- Result
- false
- 0
-
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12808
31
24
-
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12820
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- d7bbe7be-7e27-4e12-8d82-e69c3c3513bb
- Stream Filter
- Stream Filter
-
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12862
92
64
-
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12894
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 406127bb-7c1f-41d0-8cb8-dcbdb5d6ffe8
- Gate
- Gate
- false
- 7e03e96a-60c3-44b8-8508-4a0249f6e5a0
- 1
-
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12864
40
20
-
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12874
- 1
- 1
- {0}
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- 2
- Input stream at index 0
- 606a32c4-23ff-47c3-9b3e-eed9a14b7088
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-
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12884
40
20
-
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12894
- 2
- Input stream at index 1
- 74a2c323-ef25-41bc-8530-9c13e7708302
- false
- Stream 1
- 1
- true
- 1bebc86d-5784-4955-910d-2d5169d1baac
- 1
-
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12904
40
20
-
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12914
- 2
- Filtered stream
- e53053d4-d564-44a6-beee-0050818b6f00
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- S(0)
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-
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12864
24
60
-
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12894
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- ee7da382-815b-415a-9861-1675753f8b17
- Null Item
- Null Item
-
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13991
128
64
-
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14023
- Item to test
- c4b9f8a6-2632-4dff-9be8-b7e2d47fa350
- Item
- Item
- true
- 87166262-f90e-4df6-bfdc-8d5ff0afe20e
- 1
-
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13993
24
60
-
-7002
14023
- True if item is Null
- 1648d712-ddcb-484f-86a6-3bf455dc71bf
- 1
- Null Flags
- Null Flags
- false
- 0
-
-6966
13993
76
20
-
-6936
14003
- True if item is Invalid
- 46a8e847-c729-4b2b-a671-abcb1f8f1882
- Invalid Flags
- Invalid Flags
- false
- 0
-
-6966
14013
76
20
-
-6936
14023
- A textual description of the object state
- 58a3745f-6e95-4031-9372-871e1a3230e4
- Description
- Description
- false
- 0
-
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14033
76
20
-
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14043
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- 2c4de2de-7fd1-4247-920b-e4e4d985f902
- Min / Max
- Min / Max
-
-6852
13991
115
44
-
-6799
14013
- 1
- Set of Numbers
- a3dbc77a-bf20-4311-b2ed-f205798a4147
- Number
- Number
- false
- 1648d712-ddcb-484f-86a6-3bf455dc71bf
- 1
-
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13993
39
40
-
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14013
- Minimum
- 644f30e6-cd45-4fa5-bcb1-d2f3ec0088c0
- Minimum
- Minimum
- false
- 0
-
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13993
48
20
-
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14003
- Maximum
- f554aac2-085e-4c30-b33b-9feebb9269ae
- Maximum
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- 0
-
-6787
14013
48
20
-
-6763
14023
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- 869a7ab1-6d37-4602-997f-d7610372f50e
- Gate Not
- Gate Not
-
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13995
70
28
-
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14009
- Boolean value
- 32e3041b-5ee5-409a-b83f-7f221bf3158f
- A
- A
- false
- f554aac2-085e-4c30-b33b-9feebb9269ae
- 1
-
-6699
13997
11
24
-
-6693.5
14009
- Inverse of {A}
- f5241e2f-e3b9-4b92-a0a2-bb5535a30bc5
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- false
- 0
-
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13997
31
24
-
-6648.5
14009
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 2dc62a4f-fa9a-4d00-9304-565cbbb21053
- Stream Filter
- Stream Filter
-
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14054
92
64
-
-5383
14086
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- f9a060e6-874f-4dc4-a2a6-f1c341a55364
- Gate
- Gate
- false
- f5241e2f-e3b9-4b92-a0a2-bb5535a30bc5
- 1
-
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14056
40
20
-
-5415
14066
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- a3bbb5c5-ecca-4e4a-88e8-6a12ec936b83
- false
- Stream 0
- 0
- true
- 0
-
-5435
14076
40
20
-
-5415
14086
- 2
- Input stream at index 1
- 62df6a11-051f-4b24-9ace-aa4802a9bda6
- false
- Stream 1
- 1
- true
- 429f2160-9c55-4489-9f07-6fc421633a0f
- 1
-
-5435
14096
40
20
-
-5415
14106
- 2
- Filtered stream
- 371e8722-687f-4b56-97c4-03bfd4ba7a21
- false
- Stream
- S(0)
- false
- 0
-
-5371
14056
24
60
-
-5359
14086
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- bc8a43f9-69f8-416a-97c3-5e6fb9733f5e
- Null Item
- Null Item
-
-7036
15064
128
64
-
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15096
- Item to test
- 0ea97718-8927-4b3b-b427-e9da7cd6e334
- Item
- Item
- true
- 55a9b8da-f51b-46f7-9956-1cfce98363c7
- 1
-
-7034
15066
24
60
-
-7022
15096
- True if item is Null
- c72b0ed7-9c5d-47da-a98f-4953bbef1271
- 1
- Null Flags
- Null Flags
- false
- 0
-
-6986
15066
76
20
-
-6956
15076
- True if item is Invalid
- a1cf6f25-d078-429b-9e50-5d148274fe7b
- Invalid Flags
- Invalid Flags
- false
- 0
-
-6986
15086
76
20
-
-6956
15096
- A textual description of the object state
- 7accc688-6afc-4a9b-8d14-e2ce628d350e
- Description
- Description
- false
- 0
-
-6986
15106
76
20
-
-6956
15116
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- acfba1bb-b50c-4af6-a793-334e02358a94
- Min / Max
- Min / Max
-
-6872
15064
115
44
-
-6819
15086
- 1
- Set of Numbers
- 7304bb6d-12d4-4be8-9f55-d2a0ee349bc6
- Number
- Number
- false
- c72b0ed7-9c5d-47da-a98f-4953bbef1271
- 1
-
-6870
15066
39
40
-
-6850.5
15086
- Minimum
- e705aece-6cd6-4c26-9f72-1b586d5c7a5e
- Minimum
- Minimum
- false
- 0
-
-6807
15066
48
20
-
-6783
15076
- Maximum
- 0b7e60b9-9058-4d68-80e5-3d388446894a
- Maximum
- Maximum
- false
- 0
-
-6807
15086
48
20
-
-6783
15096
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- 1b86b70a-3104-4e2b-9ea8-e7b621f91e72
- Gate Not
- Gate Not
-
-6721
15068
70
28
-
-6696
15082
- Boolean value
- 143deb72-368b-4a20-bf86-6ab0afed5bcb
- A
- A
- false
- 0b7e60b9-9058-4d68-80e5-3d388446894a
- 1
-
-6719
15070
11
24
-
-6713.5
15082
- Inverse of {A}
- 1cc96b60-6c9d-4b5a-952b-d87e0f026373
- Result
- Result
- false
- 0
-
-6684
15070
31
24
-
-6668.5
15082
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 7a50b3ba-d956-42c7-85ae-020294238131
- Stream Filter
- Stream Filter
-
-5377
15051
92
64
-
-5323
15083
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 6c3c0a55-54ee-48bc-933d-5f10e406781f
- Gate
- Gate
- false
- 1cc96b60-6c9d-4b5a-952b-d87e0f026373
- 1
-
-5375
15053
40
20
-
-5355
15063
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- afb7c341-6a0d-49ee-9fe7-8bfe8897afe5
- false
- Stream 0
- 0
- true
- 0
-
-5375
15073
40
20
-
-5355
15083
- 2
- Input stream at index 1
- eab2eb72-06e3-4ad5-b3a5-80d0b1552cfd
- false
- Stream 1
- 1
- true
- 498b7dc4-3bbe-40d4-94f3-8a7fd2ddd8cb
- 1
-
-5375
15093
40
20
-
-5355
15103
- 2
- Filtered stream
- 7be70df7-f6d7-45a4-acba-b061356bcd53
- false
- Stream
- S(0)
- false
- 0
-
-5311
15053
24
60
-
-5299
15083
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- 69a6a8b7-8a4c-461d-a8e3-38b25f1090de
- Null Item
- Null Item
-
-6974
16069
128
64
-
-6936
16101
- Item to test
- 8e171002-c9c5-40fa-94a1-1001311e625d
- Item
- Item
- true
- 1149d574-8501-435b-a0b2-df2ba22f96e8
- 1
-
-6972
16071
24
60
-
-6960
16101
- True if item is Null
- d86c8275-c6b6-49f3-8e58-8b6a74aacae9
- 1
- Null Flags
- Null Flags
- false
- 0
-
-6924
16071
76
20
-
-6894
16081
- True if item is Invalid
- f3ff0523-ef2a-4496-9a34-d44373395db9
- Invalid Flags
- Invalid Flags
- false
- 0
-
-6924
16091
76
20
-
-6894
16101
- A textual description of the object state
- b75efb85-ddd2-4c87-9141-e5f4c1331f1e
- Description
- Description
- false
- 0
-
-6924
16111
76
20
-
-6894
16121
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- df4df02e-61f8-4247-b4ae-e627c2119ddb
- Min / Max
- Min / Max
-
-6810
16069
115
44
-
-6757
16091
- 1
- Set of Numbers
- 180b7c54-6a7e-486f-9082-88a8b1879e13
- Number
- Number
- false
- d86c8275-c6b6-49f3-8e58-8b6a74aacae9
- 1
-
-6808
16071
39
40
-
-6788.5
16091
- Minimum
- dc5521b1-348f-45e2-815d-692347349b5c
- Minimum
- Minimum
- false
- 0
-
-6745
16071
48
20
-
-6721
16081
- Maximum
- 51b0ebbf-b611-45ce-9ca3-e7db982d471a
- Maximum
- Maximum
- false
- 0
-
-6745
16091
48
20
-
-6721
16101
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- 4d572279-4b57-4ccb-9b17-4cf6a61cddfb
- Gate Not
- Gate Not
-
-6659
16073
70
28
-
-6634
16087
- Boolean value
- db135412-13b1-494a-9e44-f2a298e2a893
- A
- A
- false
- 51b0ebbf-b611-45ce-9ca3-e7db982d471a
- 1
-
-6657
16075
11
24
-
-6651.5
16087
- Inverse of {A}
- e5221d87-c7c5-441c-b2a0-f5d656b5e19f
- Result
- Result
- false
- 0
-
-6622
16075
31
24
-
-6606.5
16087
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 8c75690a-9909-4a23-b4bd-03ea933c5c1b
- Stream Filter
- Stream Filter
-
-5315
16056
92
64
-
-5261
16088
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- 4b34dd7b-a876-46ea-bcee-2d2e42db6605
- Gate
- Gate
- false
- e5221d87-c7c5-441c-b2a0-f5d656b5e19f
- 1
-
-5313
16058
40
20
-
-5293
16068
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 8e44a545-9b16-42f4-a5bf-929298a5975b
- false
- Stream 0
- 0
- true
- 0
-
-5313
16078
40
20
-
-5293
16088
- 2
- Input stream at index 1
- a8e94b10-1280-48b2-8c43-a75c4c94a665
- false
- Stream 1
- 1
- true
- 17cd7088-f1b9-4fd0-a76a-67c8e527f68b
- 1
-
-5313
16098
40
20
-
-5293
16108
- 2
- Filtered stream
- ff5ee03c-6fb6-4999-ba11-3c9add44a863
- false
- Stream
- S(0)
- false
- 0
-
-5249
16058
24
60
-
-5237
16088
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- a3813988-9a7d-44cb-bb48-1e51bfd8122c
- Null Item
- Null Item
-
-6991
17200
128
64
-
-6953
17232
- Item to test
- 02fb06c2-1fc1-4719-a1c0-19e6f6320810
- Item
- Item
- true
- be615a1b-b5ca-456f-9216-7ca55cad191c
- 1
-
-6989
17202
24
60
-
-6977
17232
- True if item is Null
- 54d595a2-8560-4ac7-b251-1c1614234d33
- 1
- Null Flags
- Null Flags
- false
- 0
-
-6941
17202
76
20
-
-6911
17212
- True if item is Invalid
- 3ca9f52a-60ea-41dd-8091-248edad96e5b
- Invalid Flags
- Invalid Flags
- false
- 0
-
-6941
17222
76
20
-
-6911
17232
- A textual description of the object state
- 248cb7c4-9def-47e7-a8b6-793822c6f00d
- Description
- Description
- false
- 0
-
-6941
17242
76
20
-
-6911
17252
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- 595f90c7-3ca3-4d10-8958-7f8fa2e74a29
- Min / Max
- Min / Max
-
-6827
17200
115
44
-
-6774
17222
- 1
- Set of Numbers
- 32637777-e83c-4c23-b669-258135f86f6d
- Number
- Number
- false
- 54d595a2-8560-4ac7-b251-1c1614234d33
- 1
-
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17202
39
40
-
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17222
- Minimum
- 00364658-7a30-463d-9002-9917505e5b1a
- Minimum
- Minimum
- false
- 0
-
-6762
17202
48
20
-
-6738
17212
- Maximum
- 26c41fcb-0fcc-4ec1-9bd4-79abb98e013c
- Maximum
- Maximum
- false
- 0
-
-6762
17222
48
20
-
-6738
17232
- cb2c7d3c-41b4-4c6d-a6bd-9235bd2851bb
- Gate Not
- Perform boolean negation (NOT gate).
- true
- 3b77b2f4-e654-4020-829d-ef86cca75bcf
- Gate Not
- Gate Not
-
-6676
17204
70
28
-
-6651
17218
- Boolean value
- e6521ab1-bd41-4cfc-81e4-9e57473d1419
- A
- A
- false
- 26c41fcb-0fcc-4ec1-9bd4-79abb98e013c
- 1
-
-6674
17206
11
24
-
-6668.5
17218
- Inverse of {A}
- 56f940ac-dac3-4e7c-ae76-4c5d06f6a203
- Result
- Result
- false
- 0
-
-6639
17206
31
24
-
-6623.5
17218
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
- 4ed3b515-31a0-4a8a-ac08-7a94b811e048
- Stream Filter
- Stream Filter
-
-5332
17187
92
64
-
-5278
17219
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- 1
- 8ec86459-bf01-4409-baee-174d0d2b13d0
- Index of Gate stream
- b677065e-0f8e-4e53-838f-96e373aa2f38
- Gate
- Gate
- false
- 56f940ac-dac3-4e7c-ae76-4c5d06f6a203
- 1
-
-5330
17189
40
20
-
-5310
17199
- 1
- 1
- {0}
- 0
- 2
- Input stream at index 0
- 0463558b-f3ba-4e8e-9375-4a54ed58ee17
- false
- Stream 0
- 0
- true
- 0
-
-5330
17209
40
20
-
-5310
17219
- 2
- Input stream at index 1
- fbebdd51-24e2-4e04-8bad-2a46a7d9649c
- false
- Stream 1
- 1
- true
- a9429e5a-d32c-4087-b07f-09998c87b547
- 1
-
-5330
17229
40
20
-
-5310
17239
- 2
- Filtered stream
- 659efc47-65df-4ea8-8eae-843b8943b7ff
- false
- Stream
- S(0)
- false
- 0
-
-5266
17189
24
60
-
-5254
17219
- c74efd0e-7fe3-4c2d-8c9d-295c5672fb13
- Null Item
- Test a data item for null or invalidity
- true
- b579c9d7-271d-457f-bd33-499bb0a04854
- Null Item
- Null Item
-
-6952
18329
128
64
-
-6914
18361
- Item to test
- bcb8b65d-4922-46cf-956d-7c4a16ea0146
- Item
- Item
- true
- 424c8d2f-e0fa-482b-81a1-f7c2a6375ff5
- 1
-
-6950
18331
24
60
-
-6938
18361
- True if item is Null
- 06fb23ec-2d77-4414-bf96-2c966bd4481f
- 1
- Null Flags
- Null Flags
- false
- 0
-
-6902
18331
76
20
-
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18341
- True if item is Invalid
- 27a182c5-33a4-4ae8-a00c-055fbca81d40
- Invalid Flags
- Invalid Flags
- false
- 0
-
-6902
18351
76
20
-
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18361
- A textual description of the object state
- f6de43bf-fbd7-4dc2-b04d-73e10e35dd7e
- Description
- Description
- false
- 0
-
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18371
76
20
-
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18381
- 7c9d9882-545d-434b-9850-2f3c6b01296b
- 08bdcae0-d034-48dd-a145-24a9fcf3d3ff
- Min / Max
- Extract the minimum and the maximum value of a list of numbers
- true
- c9f59e7d-070e-45e7-80a2-b3cf2f76059b
- Min / Max
- Min / Max
-
-6788
18329
115
44
-
-6735
18351
- 1
- Set of Numbers
- 700e0c9e-2f13-4861-85cf-58b1b9754642
- Number
- Number
- false
- 06fb23ec-2d77-4414-bf96-2c966bd4481f
- 1
-
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18331
39
40
-
-6766.5
18351
- Minimum
- a982f350-8b27-46fc-b540-5f37dd61b480
- Minimum
- Minimum
- false
- 0
-
-6723
18331
48
20
-
-6699
18341
- Maximum
- 6579c37f-0561-44a5-9af6-273f490a6245
- Maximum
- Maximum
- false
- 0
-
-6723
18351
48
20
-
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42
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42
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24
40
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77
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25
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25
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25
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94
44
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42
20
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42
20
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24
40
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77
64
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25
20
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25
20
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25
20
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24
60
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255;255;255;255
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94
44
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- 2
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42
20
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- Path of flattened tree
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42
20
-
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4383
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24
40
-
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4373
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77
64
-
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4273
25
20
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25
20
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25
20
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4273
24
60
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4303
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4505
94
44
-
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- 2
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42
20
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- Path of flattened tree
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4527
42
20
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24
40
-
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- eeafc956-268e-461d-8e73-ee05c6f72c01
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77
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-
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25
20
-
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4437
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25
20
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25
20
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- 2
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24
60
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94
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- 2
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42
20
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- Path of flattened tree
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42
20
-
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24
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77
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25
20
-
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25
20
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25
20
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24
60
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255;255;255;255
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94
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- 2
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42
20
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- Path of flattened tree
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42
20
-
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24
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77
64
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25
20
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25
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25
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24
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94
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42
20
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42
20
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24
40
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77
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- Index of Gate stream
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25
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25
20
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94
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24
40
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77
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25
20
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25
20
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25
20
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24
60
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255;255;255;255
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- Flatten a data tree by removing all branching information.
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94
44
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42
20
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42
20
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24
40
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77
64
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25
20
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25
20
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- 2
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25
20
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24
60
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255;255;255;255
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- Flatten a data tree by removing all branching information.
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- Flatten Tree
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94
44
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42
20
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42
20
-
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24
40
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7871
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77
64
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25
20
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25
20
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25
20
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24
60
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255;255;255;255
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94
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- 2
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42
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42
20
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24
40
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77
64
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8743
25
20
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25
20
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25
20
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24
60
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94
44
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- 2
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42
20
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- Path of flattened tree
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42
20
-
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24
40
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77
64
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25
20
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25
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25
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94
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42
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42
20
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24
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77
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25
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25
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24
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42
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- Path of flattened tree
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42
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10130
24
40
-
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10150
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10048
77
64
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10080
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10050
25
20
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10060
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10070
25
20
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10080
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10090
25
20
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10100
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10050
24
60
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10080
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255;255;255;255
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- Flatten a data tree by removing all branching information.
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11116
94
44
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11138
- 2
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11118
42
20
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11128
- Path of flattened tree
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11138
42
20
-
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11148
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11118
24
40
-
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11138
- eeafc956-268e-461d-8e73-ee05c6f72c01
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11036
77
64
-
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11068
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11038
25
20
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11048
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11058
25
20
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11068
- 2
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11078
25
20
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11088
- 2
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11038
24
60
-
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11068
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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255;255;255;255
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- Flatten a data tree by removing all branching information.
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- Flatten Tree
- Flatten Tree
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11288
94
44
-
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11310
- 2
- Data tree to flatten
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-
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11290
42
20
-
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11300
- Path of flattened tree
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11310
42
20
-
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11320
- 1
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11290
24
40
-
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11310
- eeafc956-268e-461d-8e73-ee05c6f72c01
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- Stream Filter
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11208
77
64
-
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11240
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- Gate
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11210
25
20
-
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11220
- 1
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11230
25
20
-
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11240
- 2
- Input stream at index 1
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11250
25
20
-
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11260
- 2
- Filtered stream
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- 0
-
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11210
24
60
-
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11240
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Group
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- Flatten a data tree by removing all branching information.
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- Flatten Tree
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-
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12241
94
44
-
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12263
- 2
- Data tree to flatten
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12243
42
20
-
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12253
- Path of flattened tree
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- Path
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-
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12263
42
20
-
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12273
- 1
- 1
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- Flattened data tree
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-
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12243
24
40
-
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12263
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
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- Stream Filter
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12161
77
64
-
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12193
- 3
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- Index of Gate stream
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- Gate
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- 1
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12163
25
20
-
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12173
- 1
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- true
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- 1
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12183
25
20
-
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12193
- 2
- Input stream at index 1
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- true
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- 1
-
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12203
25
20
-
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12213
- 2
- Filtered stream
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- false
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-
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12163
24
60
-
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12193
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Group
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- Flatten a data tree by removing all branching information.
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- Flatten Tree
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-
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12424
94
44
-
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12446
- 2
- Data tree to flatten
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-
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12426
42
20
-
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12436
- Path of flattened tree
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- Path
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-
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12446
42
20
-
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12456
- 1
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- Flattened data tree
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- Tree
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-
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12426
24
40
-
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12446
- eeafc956-268e-461d-8e73-ee05c6f72c01
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- Stream Filter
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-
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12344
77
64
-
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12376
- 3
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- 1
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- Index of Gate stream
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- Gate
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-
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12346
25
20
-
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12356
- 1
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- true
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-
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12366
25
20
-
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12376
- 2
- Input stream at index 1
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- 1
- true
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- 1
-
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12386
25
20
-
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12396
- 2
- Filtered stream
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-
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12346
24
60
-
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12376
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Flatten Tree
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13432
94
44
-
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13454
- 2
- Data tree to flatten
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-
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13434
42
20
-
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13444
- Path of flattened tree
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-
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13454
42
20
-
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13464
- 1
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- Flattened data tree
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-
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13434
24
40
-
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13454
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
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- Stream Filter
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-
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13352
77
64
-
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13384
- 3
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- 1
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- Index of Gate stream
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- Gate
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-
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13354
25
20
-
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13364
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- Input stream at index 0
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25
20
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13384
- 2
- Input stream at index 1
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- true
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13394
25
20
-
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13404
- 2
- Filtered stream
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13354
24
60
-
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13384
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- Group
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-
255;255;255;255
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- Flatten Tree
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13592
94
44
-
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13614
- 2
- Data tree to flatten
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-
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13594
42
20
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13604
- Path of flattened tree
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-
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13614
42
20
-
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13624
- 1
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- Flattened data tree
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13594
24
40
-
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13614
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
- true
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- Stream Filter
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-
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13512
77
64
-
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13544
- 3
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- 1
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- Index of Gate stream
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- Gate
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- 1
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13514
25
20
-
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13524
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- Input stream at index 0
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- true
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13534
25
20
-
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13544
- 2
- Input stream at index 1
- fa07e38b-ec06-4ace-a2ba-c11d932ecbc6
- false
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24
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25
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25
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25
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25
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25
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24
40
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17851
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- Stream Filter
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77
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17781
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25
20
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25
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25
20
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24
60
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17781
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255;255;255;255
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- Flatten a data tree by removing all branching information.
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- Flatten Tree
- Flatten Tree
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94
44
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18008
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42
20
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17998
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18008
42
20
-
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18018
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17988
24
40
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18008
- eeafc956-268e-461d-8e73-ee05c6f72c01
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- Filters a collection of input streams
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- Stream Filter
- Stream Filter
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17906
77
64
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17938
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17908
25
20
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17928
25
20
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17938
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17948
25
20
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17908
24
60
-
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17938
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Group
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- Flatten a data tree by removing all branching information.
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- Flatten Tree
- Flatten Tree
-
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18962
94
44
-
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18984
- 2
- Data tree to flatten
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18964
42
20
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18974
- Path of flattened tree
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-
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18984
42
20
-
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18994
- 1
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- Flattened data tree
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18964
24
40
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18984
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
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- Stream Filter
- Stream Filter
-
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18882
77
64
-
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18914
- 3
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- Index of Gate stream
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- Gate
- Gate
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18884
25
20
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18894
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18904
25
20
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18914
- 2
- Input stream at index 1
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18924
25
20
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18934
- 2
- Filtered stream
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- Stream
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-
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18884
24
60
-
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18914
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Group
- f80cfe18-9510-4b89-8301-8e58faf423bb
- Flatten Tree
- Flatten a data tree by removing all branching information.
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- Flatten Tree
- Flatten Tree
-
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19129
94
44
-
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19151
- 2
- Data tree to flatten
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- Tree
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-
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19131
42
20
-
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19141
- Path of flattened tree
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- Path
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-
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19151
42
20
-
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19161
- 1
- 1
- {0}
- {0}
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- Flattened data tree
- 32061fa5-7a54-428f-be02-8eaafc8d8662
- Tree
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-
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19131
24
40
-
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19151
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
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- Stream Filter
- Stream Filter
-
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19049
77
64
-
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19081
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
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- Index of Gate stream
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- Gate
- Gate
- false
- d4a3053e-492d-459f-b24d-a486603f6732
- 1
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19051
25
20
-
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19061
- 1
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- Input stream at index 0
- 05ff72f2-5cf8-4016-ac15-7b6330bd588a
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- true
- 62d6ed83-3071-4687-a5e0-09c3b2be03ec
- 1
-
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19071
25
20
-
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19081
- 2
- Input stream at index 1
- 25778b5d-605f-45f6-a0e0-7b632cbf9e6f
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- Stream 1
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- true
- 32061fa5-7a54-428f-be02-8eaafc8d8662
- 1
-
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19091
25
20
-
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19101
- 2
- Filtered stream
- 4fef4eb8-0fc3-486e-9c41-26f4afe1b295
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- Stream
- S(1)
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- 0
-
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19051
24
60
-
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19081
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
- 1
-
255;255;255;255
- A group of Grasshopper objects
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- 39af6b88-659d-4ff1-88ad-9ea16c55755d
- Group
- f80cfe18-9510-4b89-8301-8e58faf423bb
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- Flatten a data tree by removing all branching information.
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- Flatten Tree
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-
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20052
94
44
-
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20074
- 2
- Data tree to flatten
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-
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20054
42
20
-
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20064
- Path of flattened tree
- 1af30164-93f9-45d1-b1bd-6169588f5a33
- Path
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-
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20074
42
20
-
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20084
- 1
- 1
- {0}
- {0}
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- Flattened data tree
- d48f93fe-314f-4c4b-a271-24cb32e5ba46
- Tree
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-
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20054
24
40
-
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20074
- eeafc956-268e-461d-8e73-ee05c6f72c01
- Stream Filter
- Filters a collection of input streams
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- 4e533fe9-5c49-49ae-8e02-7883753e1fda
- Stream Filter
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-
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19972
77
64
-
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20004
- 3
- 2e3ab970-8545-46bb-836c-1c11e5610bce
- 8ec86459-bf01-4409-baee-174d0d2b13d0
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- 1
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- Index of Gate stream
- 268f54e2-f757-408b-9020-e2d77e2d6b8c
- Gate
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- d4a3053e-492d-459f-b24d-a486603f6732
- 1
-
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19974
25
20
-
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19984
- 1
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- {0}
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- Input stream at index 0
- 8a244879-5668-4533-9862-ec5cf431b1d0
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- true
- e319d54d-2de8-490c-a8cd-087587455e2a
- 1
-
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19994
25
20
-
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20004
- 2
- Input stream at index 1
- 25ca9235-fcfb-473b-b3e9-841046a34612
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- true
- d48f93fe-314f-4c4b-a271-24cb32e5ba46
- 1
-
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20014
25
20
-
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20024
- 2
- Filtered stream
- 5bc2b19d-ee68-47a6-82eb-a318b39d70ea
- false
- Stream
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- 0
-
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19974
24
60
-
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20004
- c552a431-af5b-46a9-a8a4-0fcbc27ef596
- Group
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-
255;255;255;255
- A group of Grasshopper objects
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- Group
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- Flatten Tree
- Flatten a data tree by removing all branching information.
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- Flatten Tree
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-
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20208
94
44
-
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20230
- 2
- Data tree to flatten
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-
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20210
42
20
-
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20220
- Path of flattened tree
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-
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20230
42
20
-
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20240
- 1
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- Flattened data tree
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-
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20210
24
40
-
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20230
- eeafc956-268e-461d-8e73-ee05c6f72c01
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- Filters a collection of input streams
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- Stream Filter
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-
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20128
77
64
-
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20160
- 3
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- Index of Gate stream
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- Gate
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-
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20130
25
20
-
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25
20
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- 2
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- true
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20170
25
20
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- 2
- Filtered stream
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24
60
-
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20160
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-
255;255;255;255
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130
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- Text format
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8270
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78
20
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8309
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- Formatting culture
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8270
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78
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8309
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8270
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78
20
-
8309
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- Formatted text
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8372
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24
60
-
8384
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149
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- Curve to evaluate
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71
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- Length factor for curve evaluation
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- Length
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-
8261
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71
20
-
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- Line SDL
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- Line SDL
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- true
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- Deconstruct a point into its component parts.
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-
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- 6576c2b8-5338-4770-afcf-f2e26ea21e0e
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8889
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- 01b0fd73-cd51-437c-b81e-6e1acd6aa2b7
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- c552a431-af5b-46a9-a8a4-0fcbc27ef596
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255;255;255;255
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- 0
- If activate Then
Dim i As Integer
Dim aryText(4) As String
aryText(0) = "Mary WriteLine"
aryText(1) = "Had"
aryText(2) = "Another"
aryText(3) = "Little"
aryText(4) = "One"
' the data is appended to the file. If file doesnt exist, a new file is created
Dim objWriter As New System.IO.StreamWriter(filePath, append)
For i = 0 To data.Count - 1
objWriter.WriteLine(data(i))
Next
objWriter.Close()
End If
If clearFile Then
Dim objWriter As New System.IO.StreamWriter(filePath, False)
objWriter.Close()
End If
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- filePath
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- a8b97322-2d53-47cd-905e-b932c3ccd74e
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255;255;255;255
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- 1
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Dim i As Integer
Dim aryText(4) As String
aryText(0) = "Mary WriteLine"
aryText(1) = "Had"
aryText(2) = "Another"
aryText(3) = "Little"
aryText(4) = "One"
' the data is appended to the file. If file doesnt exist, a new file is created
Dim objWriter As New System.IO.StreamWriter(filePath, append)
For i = 0 To data.Count - 1
objWriter.WriteLine(data(i))
Next
objWriter.Close()
End If
If clearFile Then
Dim objWriter As New System.IO.StreamWriter(filePath, False)
objWriter.Close()
End If
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- A
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- a8b97322-2d53-47cd-905e-b932c3ccd74e
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- true
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- Merge
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