id
string | steps_number
int64 | system_prompt
string | user_prompt
list | ground_truth
string |
|---|---|---|---|---|
shape(step:9)_65
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is Colorize the top layer of the original shape with the color green.\nthe 3th action is Stack the original shape on top of the {'layer1': 'RbRbRbRb'}.\nthe 4th action is Cut the right side of the shape\nthe 5th action is Stack the original shape on top of the {'layer1': 'RcRcRcRc'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'CgCgCgCg'}.\nthe 7th action is Stack the original shape on top of the {'layer1': 'RcRcRcRc'}.\nthe 8th action is rotate the shape clockwise 90 degrees\nthe 9th action is Colorize the top layer of the original shape with the color cyan.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_364
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color cyan.\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is Stack the original shape on top of the {'layer1': 'SySySySy'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'CyCyCyCy'}.\nthe 7th action is Stack the original shape on top of the {'layer1': 'SySySySy'}.\nthe 8th action is Colorize the top layer of the original shape with the color cyan.\nthe 9th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_263
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color red.\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is Cut the right side of the shape\nthe 7th action is Stack the original shape on top of the {'layer1': 'ScScScSc'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'SwSwSwSw'}.\nthe 9th action is Stack the original shape on top of the {'layer1': 'WcWcWcWc'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_240
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAgAAAAIACAYAAAD0eNT6AAAJoElEQVR4nO3d0Y7bNhCG0U3QV/RT+iETCKBQo822lkxK5PznXGcl3zD4MEPvfn0BAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABwkR+Px+PXVS8D5vN8Pn/c/RmA6/284Z0AwM0EAAAEEgAAEEgAAEAglwCBf3ExEOozAQCAQAIAAAIJAAAIJAAAINBf7/7Dx+Mx9pMAwz2fz7s/AjAJEwAACCQAACCQAACAQAIAAAIJAAAIJAAAIJAAAIBAAgAAAgkAAAgkAAAg0M93/+63XyEKAHWYAABAIAEAAIEEAAAEEgAAEEgAAEAgAQAAgQQAAAQSAAAQSAAAQCABAACBBAAApAaAvwcAAFlMAAAgkAAAgEACAAACCQAACCQAACCQAACAQAIAAJIDwO8CAIAcJgAAEEgAAEAgAQAAgQQAAAQSAAAQ6FQA+CYAABQKgHe/CggArM0KAAACCQAACCQAACDQ6QBwERAACgWAi4AAUJ8VAAAEEgAAEEgAAECgjwLARUAAKBQALgICQG1WAAAQSAAAQCABAACBPg4AFwEBoFAAuAgIAHVZAQBAIAEAAIG6BIB7AABQKADcAwCAmqwAACCQAACAQN0CwD0AACgUAO4BAEA9VgAAEKhrAFgDAMAaTAAAINBbAeAeAADUYgIAAIG6B4B7AABQKACsAQCgDisAAAg0JACsAQCgUABYAwBADVYAABBoWABYAwDAvEwAACDQ4QBwDwAA1jd0AmANAABzsgIAgECnAsAaAADWNnwCYA0AAIUCwBQAANblDgAABLokAKwBAKBQAFgDAMCaLlsBmAIAwDzcAQCAQB8HgDUAAKzn0gmANQAAzMEKAAACdQmAI2sAUwAAuJ8JAAAE6hYALgMCwDpumQBYAwBAoQAwBQCANdx2B8AUAADu4xIgAATqHgC+EggA8zMBAIBAQwLAFAAA5mYCAACBhgWArwQCwLymmABYAwBAYAAAAIUCwGVAAJiTCQAABBoeAKYAADAfEwAACHRJAJgCAMBcTAAAINBlAWAKAADzMAEAgECXBoApAADMwQQAAAJdHgCmAABwv+knACIAAIoEgD8VDAD3mn4CsDEFAIAiAWAKAAD3WWICsDEFAIAiAWAKAAChEwBfCwSAwAA4SgQAQJEAsAoAgMAAOMoUAACKBIApAAAEBsBRpgAAUCQAjk4BRAAAFAiAjVUAAAQGwFGmAABQJACsAgAgMAAAgNAAMAUAgMAA2LgQCACBAXCUKQAAFAkAqwAACAyAjQgAgMAAAABCA8AUAAACA2AjAgAgMAAAgNAAMAUAgMAA2IgAAAgMgDNEAAAUCAC/JhgAAgNgYxUAAIEBsBEBABAYAGeIAADSlQgA9wEAIDAANlYBABAYABsRAACBAXCGCAAgUbkAcB8AAAIDYGMVAACBAbARAQAQGABniAAAUpQOgDP3AUQAAAlKB8BGBABAYABsRAAABAbAxtcDASAwAM4wBQCgqqgAsAoAgMAA2IgAAAgMgI0IACBdZABsRAAAyWIDYCMCAEgVHQAbEQBAovgAOEsEALAyAfDBLwkSAQCsSgA0IgCAJALghQgAIIUA+AcRAEACAfAHIgCA6gTAN0QAAJUJgP8gAgCoSgD8DxEAQEUC4A0iAIBqBMCbRAAAlQiAA0QAAFUIgINEAAAVCIATRAAAqxMAJ4kAAFYmAG6KACEAwJ0EwE0R0H6274cBgDcJgA5EAACrEQCdiAAAViIAOhIBAKxCAHQmAgBYgQAYFAG+IQDAzATAQKYBAMxKAAwmAgCYkQBYIAKEAAC9CYAFIqD9fL8PA0A8AXAhEQDALATAQt8QaD8vBAD4mAC4iWkAAHcSADcSAQDcRQAUiAAhAMBRAqDAvYD2jH4fCIDyBMBETAMAuIoAKBYB7Rl9PgwAZQmACVkJADCaAJiYlQAAowiAkJWAEADglQAIWQm05/T5QAAsTwAsxDQAgF4EQGAEtOf0eAwAixIA4SsBIQCQSQAsrOc0QAgAZBEAi+s1DWjP6vEYABYgAIowDQDgCAFQSO9pgBAAqEsAFNQrAtqzhABAQQKgqJ7TgPa8Xo8CYAICoDjTAAD+RAAEGDENEAIAaxMAQYQAADsBEKhnBLTnCQGAxQiAUL2nAe2ZQgBgEQIgnBAAyNT1P37W93g8fg167ojHctC7YdY7CoH5mABwyX/8pgIAcxEAXLIWeHm2EACYgADgW0IAoC57Pm6/H/Dy/JGPxx0A4IUJAFNMBNrzTQUALqLymXYi0N4x+hVRTACAnQkA004E2jtMBQAGUPksNRFo77niNSWZAAA7h5xlQ6C966pXlSAAgJ1DzlBiYC4CANg55JQLgfa+K1+3DAEA7BxySodAe+fVr5yWAAB2DjlRMdDe+5VKAAA7h5zYEGjv/koiAICdQ8407gyBl8/wVZkAAHYOOVOaIQYqBoEAAHYOOdObJQYqRIEAAHYOOUuZLQZWiwIBAOwccpY0awjMHgUCANg55CxvhRiYJQwEALBzyClntSC4MhAEALBzyClt9RjoHQwCANg55MRIiIFeBADU55ATSxB8TwBAfQ45NILgbwIA6nPI4RvJQSAAoD6HHA5IiQIBAPU55PChilEgAKA+hxwGWD0KBADU55DDxVaIAwEA9TnkMJkZAkEAwFd5vwHJWfS7MnzkUgAAAABJRU5ErkJggg=="
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color cyan.\nthe 2th action is Stack the original shape on top of the {'layer1': 'WuWuWuWu'}.\nthe 3th action is Stack the original shape on top of the {'layer1': 'SbSbSbSb'}.\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is Stack the original shape on top of the {'layer1': 'RyRyRyRy'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'WbWbWbWb'}.\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is Cut the right side of the shape\nthe 9th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_109
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is Cut the right side of the shape\nthe 3th action is Colorize the top layer of the original shape with the color purple.\nthe 4th action is Cut the right side of the shape\nthe 5th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\nthe 6th action is Colorize the top layer of the original shape with the color purple.\nthe 7th action is Stack the original shape on top of the {'layer1': 'RyRyRyRy'}.\nthe 8th action is rotate the shape clockwise 90 degrees\nthe 9th action is Colorize the top layer of the original shape with the color blue.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_357
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'WgWgWgWg'}.\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is Colorize the top layer of the original shape with the color yellow.\nthe 4th action is Cut the right side of the shape\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is Stack the original shape on top of the {'layer1': 'RrRrRrRr'}.\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is Cut the right side of the shape\nthe 9th action is Stack the original shape on top of the {'layer1': 'WuWuWuWu'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:9)_247
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is Stack the original shape on top of the {'layer1': 'CrCrCrCr'}.\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is Colorize the top layer of the original shape with the color cyan.\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is Colorize the top layer of the original shape with the color white.\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is Stack the original shape on top of the {'layer1': 'CrCrCrCr'}.\nthe 9th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_448
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAgAAAAIACAYAAAD0eNT6AAARkElEQVR4nO3dXWod2RUFYHfTE7jjyGwCFchbhpa3QAoym4wjQ+hw3Hbbkq6k+1Onzv75PhDCSBT1Yq+1F8L68gUAaOeX1S8AAJxn27bfx2cFAAAaBf93CgAANAr+7xQAAGgU/MO+77/8du7rAACrgv9nFgAAaBT84/ofny0AANAg+F+zAABAk+D/fv0PFgAAaHDxv2YBAIAGwf/z9T9YAACgwcX/mgUAAIoH/+vrf7AAAEDxa/8aCwAAFA7+a9f/YAEAgAYX/2sWAABIFvzbto3L/uHrf7AAAECi4B9uCf/PKAAAkCT47/HR9T8oAACQKPiPuP4HBQAAClz891z/gwIAAEmC/6jrf1AAACD5xX/v9T8oAACQIPiPvP4HBQAAEl/8j1z/gwIAAMGD/+jrf1AAACDpxf/o9T8oAAAQOPhnXP+DAgAAAYN/5vU/KAAAEDT4Z13/gwIAQHtbsOCfff0PCgAAbUUO/pnX/6AAANDOFjj4z7j+BwUAgDayBP8++fofFAAAyssS/Gdd/4MCAEBZGYN/P+H6HxQAAMrJGPxnXv+DAgBAGdmDfz/p+h8UAADSyx78Z1//gwIAQMvQjxb8Z17/gwIAQCrVgn/F9T8oAACkUDn495Ov/0EBACC0ysG/6vofFAAAQuoS/PuC639QAAAIpUvwr7z+BwUAgBA6Bv++6PofFAAA0gf/t+d8qWifcP0PCgAAS3QP/pXX/6AAAHCq7sEf4fofFAAATiH441z/gwIAwFSCP971PygAAEwh+ONe/4MCAMChBH/8639QAAA4hODPc/0PCgAATxH8+a7/QQEA4CGCP+/1PygAANxF8Oe//gcFAICbCP461/+gAADwIcFf7/ofFAAArhL8da//QQEA4AXBX//6HxQAAL4S/H2u/0EBAGhO8Pe7/gcFAKApwd/3+h8UAIBmBH8cq67/QQEAaOCo0P/2rKMeVdYe/PofFACAwgQ/71k2PQAwj+CPf/3vC+f/wQIAUIjg51YWAIACBH8Me5Lrf7AAACQm+HnU8gYCwP0Efzx7out/sAAAJCL4OUqIFgLAxwR/bHuy63+wAAAEJviZJUwTAeAHwZ/HnvD6HywAAIEIfs4Sqo0AdCX4c9qTXv+DBQBgIcHPKuEaCUAHgj+/zNf/YAEAOJHgJ4qQrQSgGsFfy578+h8sAAATCX6iCttMADIT/HXtBa7/wQIAcCDBTxah2wlAFoK/h73I9T9YAACeIPjJKnxDAYhI8PezF7r+BwsAwB0EP1WkaCkAqwn+3vZi1/9gAQA4IfS/Pe/Ix8FT0jQVgLMIfqpf/4MFAOAbwU8nqdoKwAyCn27X/2ABANoS/HSWrrEAPEvw0/36HywAQBuCH35I2VoA7iH4udde/PofLABAWYIf3pe2uQC8R/DzjL3B9T9YAIAyBD/cLnV7ARgEP0fZm1z/gwUASEvww+PSNxigH8HPDHuj63+wAABpCH44TokWA9R2dPB/e+bRjySxvdn1P1gAgLAEP8xTpskAdQh+zrQ3vP4HCwAQhuCH85RqM0BOgp9V9qbX/2ABAJYR/LBOuUYDxCf4iaDz9T9YAIDTCH6Io2SrAWIR/ESzN7/+BwsAMI3gh7jKNhtgHcFPZK7/P1gAgLCh/+25Mx4L7ZVuN8B8gp9MXP8/WACAhwh+yK18wwGOJfjJyvX/kgUAuIngh1patBzgcYKfClz/b1kAgKsEP9TWpukAtxH8VOP6v84CAHwl+KGXVm0HeEvwU5nr/30WAGhK8ENv7RoPdCf46cL1/zELADQh+IGfKQDAQwQ/kbn+P6cAAHcR/FCDAgDcRPBT7frvTgEAPiT4qWpvPP8PCgBwleAnI9f/7RQA4AXBT4fw35tf/8Ovq18AADifAgBAeq7/+ykAANCQAgBAaq7/xygAANCQAgBAWq7/xykAANCQAgBASq7/5ygAANCQAgBAOq7/5ykAANCQAgBAKq7/YygAANCQAgBAGq7/4ygAANCQAgBACq7/YykAANCQAgBAeK7/4ykAANCQAgBAaK7/ORQAAGhIAQAgLNf/PAoAADSkAAAQkut/LgUAABpSAAAIx/U/nwIAAA0pAACE4vo/hwIAAA0pAACE4fo/jwIAAA0pAACE4Po/lwIAAA0pAAAs5/o/nwIAAA0pAAAs5fpfQwEAgIYUAACWcf2vowAAQEMKAABLuP7XUgAAoCEFAIDTuf7XUwAAoCEFAIBTuf5jUAAAoCEFAIDTuP7jUAAAoCEFAIBTuP5jUQAAoCEFAIDpXP/xKAAA0JACAMBUrv+YFAAAaEgBAGAa139cCgAANKQAADCF6z82BQAAGlIAADic6z8+BQAAGlIAADiU6z8HBQAAGlIAAFhy/bOWAgDAEub/tRQAAA7h+s9FAQDgdK7/9RQAAJ7m+s9HAQDgVK7/GBQAAJ7i+s9JAQDgNK7/OBQAAB7m+s9LAQDgFK7/WBQAAB7i+s9NAQBgOtd/PAoAAHdz/eenAAAwles/JgUAgLu4/mtQAACYxvUflwIAwM1c/3UoAABM4fqPTQEA4Cau/1oUAAAO5/qPTwEA4FOu/3oUAAAO5frPQQEA4EOu/5oUAAAO4/rPQwEA4F2u/7oUAAAO4frPRQEA4CrXf20KAABPc/3nowAA8Ibrvz4FAICnuP5zUgAAeMH134MCAMDDXP95KQAA/Mn134cCAMBDXP+5KQAAfOX670UBAOBurv/8FAAAXP8NKQAA3MX1X4MCANCc678nBQCAm7n+61AAABpz/felAABwE9d/LQoAQFOu/94UAAA+5fqvRwEAaMj1jwIAwIdc/zUpAADNuP4ZFAAA3uX6r0sBAGjE9c93CgAAV7n+a1MAAJpw/fMzBQCAN1z/9SkAAA24/nlNAQDgBdd/DwoAQHGuf675Zdu2369+BYB2XP99WAAAoCEFAICvXP+9KAAA0JACAIDrvyEFAAAaUgAAmnP996QAAEBDCgAANKQAADTnP4Tr6bdbv/Ff//zv3DcBpvr7P/5y0/dd/vrv6e/COf73n7+tfgUCswAAYAVoSAEAKMqaw0cUAAC+sgL0ogAAFGYF4D0KAAB/sgL0oQAAFGcF4BoFAIAXrAA9KAAADVgBeE0BAOANK0B9CgBAE1YAfqYAAHCVFaA2BQCgESsA3ykAALzLClCXAgDQjBWAQQEA4ENWgJoUAICGrAAoAAB8ygpQjwIA0JQVoDcFAICbWAFqUQAAGrMC9KUAAHAzK0AdCgBAc1aAnhQAAO5iBahBAQDACtCQAgDA3awA+SkAAHxlBehFAQDgIVaA3BQAAP5kBehDAQDgYVaAvBQAAF6wAvSgAADwFCtATgoAAG9YAepTAAB4mhUgHwUAgKusALUpAAAcwgqQiwIAwLusAHUpAAAcxgqQhwIAwIesADUpAAAcygqQgwIAwKesAPUoAAAczgoQnwIAwE2sALUoAABMYQWITQEA4GZWgDoUAACmsQLEpQAAcBcrQA0KAABTWQFiUgAAuJsVID8FAIDprADxKAAAPMQKkJsCAMAprACxKAAAPMwKkJcCAMBprABxKAAAPMUKkJMCAMCprAAxKAAAPM0KkI8CAMDprADrKQAAHMIKkIsCAMASVoC1FAAADmMFyEMBAGAZK8A6CgAAh7IC5KAAALCUFWANBQCAw1kB4lMAAFjOCnA+BQCAKawAsSkAAIRgBTiXAgDANFaAuBQAAMKwApxHAQBgKitATAoAAKFYAc6hAAAwnRUgHgUAgHCsAPMpAACcwgoQiwIAQEhWgLkUAABOYwWIQwEAICwrwDwKAACnsgLEoAAAEJoVYA4FAIDTWQHWUwAACM8KcDwFAIAlrABrKQAApGAFOJYCAMAyVoB1FAAA0rACHEcBAGApK8AaCgAAqVgBjqEAALCcFeB8CgAA6VgBnqcAABCCFeBcCgAAKVkBnqMAABCGFeA8CgAAaVkBHqcAABCKFeAcCgAAqVkBHqMAABCOFWA+BQCA9KwA91MAAAjJCjCXAgBACVaA+ygAAIRlBZhHAQCgDCvA7RQAAEKzAsyhAABQihXgNgoAAOFZAY6nAABQjhXgcwoAAClYAY6lAABQkhXgYwoAAGlYAY6jAABQlhXgfQoAAKlYAY6hAABQmhXgOgUAgHSsAM9TAAAozwrwlgIAQEpWgOcoAFDc3//xl68f0J0V4KXfXv0ZKELo02UF+N9//rb6NVKyAEAxLn54nxXgBwsAFCH06coK8BgLACTn4of7WAH+YAGApIQ+/GAFuJ8FAJJx8cPzNiuABQCyEPrwMSvAfSwAEJyLH+bYmq8AFgAISujD/awAt7MAQDAufjjP1ngFsABAELNCf9/3X7r/Q0cvVoDbKABQPPiBj23b9nvHvy8KACwi+GEeK8DnFAA4meCHeLaGK4ACACcR/HAuK8DHFACYTPBDDluzFUABgEkEP6xnBXifAgAHE/yQ19ZoBVAA4CCCH2KyAlynAMCTBD/UsjVZARQAeJDghzysAG8pAHAnwQ/1bQ1WAAUAbiT4ITcrwEsKAHxC8ENPW/EVQAGAdwh+qMcK8IMCAK8IfqDDCqAAwDeCH3qwAvxBAaA9wQ90XAEUANoS/NDXxQqgANCP4AfuVXEFUABoQ/ADP7s0XwEUAMoT/MARtmIrgAJAWYIf+Myl8QqgAFCO4Adm2QqtAAoAZQh+4BGXpiuAAkB6gh8401ZkBVAASEvwA0e5NFwBfl39AvBI8At/YPUK8CU5CwBpzAr9QfADl2YrgAJAeIIfiGhL/rMACgBhCX7gbJdGK4ACQDiCH8hiS7wCKACEIfiBCC5NVgAFgOUEP5DZlnQFUABYRvADUV0arAAKAKcT/EA1W8IVQAHgNIIfyORSfAVQAJhO8AMdbMlWAAWAaQQ/kN2l8AqgAHA4wQ90tSVaARQADiP4gYouRVcABYCnCX6AfCuAAsDDBD/QxaXgCqAAcDfBD5B/BVAAuJngBzq7FFsBFAA+JfgB6q0ACgDvEvwAdVcABYA3BD9A/RVAAeBPgh+gzwqgACD4ARquAApAY4IfoO8KoAA0JPgBzhVxBVAAGhH8AMe5JF8BFIAGBD/AeluwFUABKEzwA8x1SbwCKAAFCX6AmLZAK4ACUIjgBzjfJekKoAAUIPgB8tiCrAAKQGKCHyCGS8IVQAFISPAD5LYFWAEUgEQEP0Bcl2QrgAKQgOAHqGdbvAIoAIEJfoBcLolWAAUgIMEP0MO2cAVQAAIR/AD5XZKsAApAAIIfoK9t0QqgACwk+AFquiRYARSABQQ/AKtXAAXgRIIfoI9L8BVAATiB4Acg2gqgAEwk+AF6uwReARSACQQ/ANFXAAXgQIIfgCwrgAJwAMEPQLYVQAF4guAHIOsKoAA8QPADkH0FUADuIPgBqLICKAA3EPwAVFsBFIAPCH4Aqq4ACsAVgh+A6iuAAvATwQ9AlxVAARD8ADRcAVoXAMEPQNcVoGUBEPwAdF8BWhUAwQ9AFJfFK0CLAiD4AchuO3gFKF0ABD8AkV0WrgAlC4DgB6Ci7cAVoFQBEPwAZHNZtAKUKACCH4AutoNWgNQFQPADUMFlwQqQsgAIfgA62w5YAVIVAMEPQFWXk1eAX78kCX7hDwAvV4AvVReAmaE/CH4Auq4AIQuA4AeAuT8LEKoACH4AuructAKEKACCHwDOXQGWFgDBDwBrVoAlBUDwA8DaFeDUAiD4ASDGCnBKARD8ABBrBZhaAAQ/AMRcAaYUAMEPALFXgEMLgOAHgBwrwCEFQPADQK4V4KkCIPgBIOcK8FABEPwAkHsFuKsACH4AqLEC/Boh/EfwC38AOHYFCPu7AIQ+AKxZAW5eAI7k4geAtSvAqQuA0AeAGCvAKQuAix8AYq0AUxcAoQ8AMVeAKQuAix8AYq8Ahy4AQh/ym/n7x4E4DlkAXPwAkGsFeGoBEPoA0GgBcPEDQO4V4K4FQOgDQKMFwMUPALVWgA8XAKEPADVdLQCCHwBqrwAvCoDgB4AvLfwfFDlLFEcsxRIAAAAASUVORK5CYII="
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'SrSrSrSr'}.\nthe 2th action is Colorize the top layer of the original shape with the color purple.\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is rotate the shape counterclockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'RbRbRbRb'}.\nthe 8th action is Colorize the top layer of the original shape with the color white.\nthe 9th action is Stack the original shape on top of the {'layer1': 'RbRbRbRb'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_320
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAgAAAAIACAYAAAD0eNT6AAAP2UlEQVR4nO3dW25bRxBFUTvIFNtARhjAHGQCO1Fiy6LEx+3bXXXWAvznB2FArKNNSvo8xvjrE8C/LpfL59WPAZjvNx/sAJDnt9UPAABYNABUAADIogAAQPIAUAEAIIcCAADpA0AFAIAMCgAABPplAKgAANDf78/+BZc/vx7zSICpxh9fVj8EYPeXAO6pAJ5UAKAe7wEAgEBXB4AKAAB9KQAAEOjdAaACAEBPCgAABPpwAKgAANCPAgAAgW4aACoAAPSiAABAoJsHgAoAAH0oAAAQ6K4BoAIAQA8KAAAEunsAqAAAUJ8CAACBHhoAKgAA1KYAAECghweACgAAdSkAABDoqQGgAgBATQoAAAR6egCoAABQjwIAAIEOGQAqAADUogAAQKDDBoAKAAB1KAAAEOjQAaACAEANCgAABDp8AKgAALA/BQAAAk0ZACoAAOxNAQCAQNMGgAoAAPtSAAAg0NQBoAIAwJ4UAAAINH0AqAAAsB8FAAACnTIAVAAA2IsCAACBThsAKgAA7EMBAIBApw4AFQAA9qAAAECg0weACgAA6ykAABBoyQBQAQBgLQUAAAItGwAqAACsowAAQKClA0AFAIA1FAAACLR8AKgAABA4AACA0AGgAgBA4AAAAEIHgAoAAIEDAAAIHQAqAAAEDgAAIHQAqAAAEDgAAIDQAaACAEDgAAAAQgeACgAAgQMAAAgdACoAAAQOAAAgdACoAAAQOAAAgNABoAIAQOAAAABCB4AKAACBAwAACB0AKgAABA4AACB0AKgAABA4AACA0AGgAgBA4AAAAEIHgAoAAIEDAAAIHQAqAAAEDgAAIHQAqAAAEDgAAIDQAaACAEDgAAAAQgeACgAAgQMAAAgdACoAAAQOAAAgdACoAAAQOAAAgNABoAIAQOAAAABCB4AKAACBAwAACB0AKgAABA4AACB0AKgAABA4AACA0AGgAgBA4AAAAEIHgAoAAIEDAAAIHQAqAAAEDgAAIHQAqAAAEDgAAIDQAaACAJAucgAAQLrYAaACAJAsdgAAQLLoAaACAJAqegAAQKr4AaACAJAofgAAQCIDQAUAIJABAACBDIB/qQAAJDEAACCQAfADFQCAFAYAAAQyAF5RAQBIYAAAQCAD4A0qAADdGQAAEMgAuEIFAKAzAwAAAhkA71ABAOjKAACAQAbAB1QAADoyAAAgkAFwAxUAgG4MAAAIZADcSAUAoBMDAAACGQB3UAEA6MIAAIBABsCdVAAAOjAAACCQAfAAFQCA6gwAAAhkADxIBQCgMgMAAAIZAE9QAQCoygAAgEAGwJNUAAAqMgAAIJABcAAVAIBqDAAACGQAHEQFAKASAwAAAhkAB1IBAKjCAACAQAbAwVQAACowAAAgkAEwgQoAwO4MAAAIZABMogIAsDMDAAACGQATqQAA7MoAAIBABsBkKgAAOzIAACCQAXACFQCA3RgAABDIADiJCgDATgwAAAhkAJxIBQBgFwYAAAQyAE6mAgCwAwMAAAIZAAuoAACsZgAAQCADYBEVAICVDAAACGQALKQCALCKAQAAgQyAxVQAAFYwAAAgkAGwARUAgLMZAAAQyADYhAoAwJkMAAAIZABsRAUA4CwGAAAEMgA2owIAcAYDAAACGQAbUgEAmM0AAIBABsCmVAAAZjIAACCQAbAxFQCAWQwAAAhkAGxOBQBgBgMAAAIZAAWoAAAczQAAgEAGQBEqAABHMgAAIJABUIgKAMBRDAAACGQAFKMCAHAEAwAAAhkABakAADzLAACAQAZAUSoAAM8wAAAgkAFQmAoAwKMMAAAIZAAUpwIA8AgDAAACGQANqAAA3MsAAIBABkATKgAA9zAAACCQAdCICgDArQwAAAhkADSjAgBwCwMAAAIZAA2pAAB8xAAAgEAGQFMqAADvMQAAIJAB0JgKAMA1BgAABDIAmlMBAHiLAQAAgQyAACoAAK8ZAAAQyAAIoQIA8CMDAAACGQBBVAAAXhgAABDIAAijAgDwjQEAAIE+jzH+Wv0gANi/CtKLAgAAgQwAgGAqcC4DAAACGQAA4VSATAYAAAQyAABQAQIZAAAQyAAA4DsVIIsBAACBbv5OgF+/fp3/aIBpvny57Wc7XP70sd7NvT/Xw3cHzKAAADRn1PEWAwCAn3gvQAYDACCACsBrBgAAv1AB+jMAAEKoAPzIAADgTSpAbwYAQBAVgBcGAABXqQB9GQAAYVQAvjEAAHiXCtCTAQAQSAXAAADgQypAPwYAQCgVIJsBAMBNVIBeDACAYCpALgMAgJupAH0YAADhVIBMBgAAd1EBejAAAFABAhkAANxNBajPAADgOxUgiwEAwENUgNoMAAD+owLkMAAAeJgKUJcBAMBPVIAMBgAAT1EBajIAAPiFCtCfAQDA01SAegwAAN6kAvRmAABwCBWgFgMAgKtUgL4MAAAOowLUYQAA8C4VoCcDAIBDqQA1GAAAfEgF6McAAOBwKsD+DAAAbqIC9GIAADCFCrA3AwCAm6kAfRgAAEyjAuzLAADgLipADwYAAFOpAHsyAAC4mwpQnwEAAIEMAACmVwAvA+zHAACAQAYAAA9TAeoyAAAgkAEAwFNUgJoMAAAIZAAA8DQVoB4DAAACGQAAHEIFqMUAAIBABgAAh1EB6jAAACCQAQDAoVSAGgwAAAhkAABwOBVgfwYAAAQyAACYQgXYmwEAAIEMAACmUQH2ZQAAQCADAICpVIA9GQAAEMgAAGA6FWA/BgAABDIAADiFCrAXAwAAAhkAAJxGBdiHAQAAgQwAAE6lAuzBAACAQAYAAKdTAdYzAAAgkAEAwBIqwFoGAAAEMgAAWEYFWMcAAIBABgAAS6kAaxgAABDIAABgORXgfAYAAAQyAADYggpwLgMAAAIZAABsQwU4jwEAAIEMAAC2ogKcwwAAgEAGAADbUQHmMwAAIJABAMCWVIC5DAAACGQAANCiAnAfAwCAFrwMcB8DAICtqQBzGAAAtKEC3M4AAGB7KsDxDAAAWlEBbmMAAFCCCnAsAwCAdlSAjxkAAJShAhzHAACgJRXgfQYAAKWoAMcwAABoSwW4zgAAoBwV4HkGAACtqQBvMwAAKEkFeI4BAEB7KsCvDAAAylIBHmcAABBBBfiZAQBAaSrAYwwAAGKoAP8zAKC5L1++fP8FnakA9/v9gT8DFODow/UKcLlcPn8KpwBAM89+xj/++PL9F1SjAtzn862vh3z96j8WEj/j96RKNbcO2Et4BfASABQ3O/W/PJkaAtCLAgBFrXqN3xCgAhXgYwoAFLP6zX2KAPSgAEARqw//NYYAu1IB3qcAwOZ2PfwvFAGoSQGATe1++K8xBNiJCnCdAgApX8736glu1rdEVQSgBgUAwg7/2d8b3RBgNRXgbQoAhB7+179PEYAsCgCEHv5rFAE6UgF+pQDAyXY9/K//HkUAelMA4CS7H/5rFAG6UAF+pgDAZFUP/+t/RxGAXhQAmKT64b9GEaAyFeB/CgAcrOvhf6EIQA8KAByk++G/RhGgGhXgHwoAPCn18L9QBKAmBQAelH74V1UBQ4AjDBVAAYB7Ofxrq4AiAMdQAOBGDv/jFAF2NMIrgAIAH3D4n6cIwH4UALjC4Z9HEWAXI7gCKADwisM/nyIA6ykA8C+Hfx1FgJVGaAVQAIjn8K+nCMD5FABiOfz7UgQ42wisAAoAcRz+/SkCMJ8CQAyHv65ZRcAIILkCKAC05/DXN6sIqAEkUwBoy+HvSxFgZQW4NHkOUABox+HvTxFgpTHGXx2eDxQA2nD4cykCHGmEVAAFgPIcfhQBzjYaVAAFgLIcfq5RBHjWCKgACgDlzDr8HT6g+YciwBlG8QqgAFCGw8+jFAEeMZpXAAWA7Tn8PEsRYJZRuAIoAGzL4WcWRYBbda4ACgDbcfiZTRHgSFUrgALANhx+VlEESKwACgDLOfyspgiQWAEUAJZx+NmVIkBCBVAAOJ3Dz+4UARIqgALAaRx+KptRBQyBWkazCqAAMJ3DTwczqoAi0M8oVAEUAKZx+OlMEcg0GlUABYDDOfwkUASoXgEUAA7j8JNMEcgxmlQABYCnOfygCFCvAigAPMzhh+sUgd5GgwqgAHA3hx8+pggwNq8ACgA3c/jhcYpAP6N4BVAA+JDDD89TBDKNjSuAAsBVDj/Mowj0MApXAAWAXzj8MJ8ikGNsWgEUAP7j8MM6ikBdo2gFUABw+GEDikBvY8MKoAAEc/hhX4pALaNgBVAAAjn8sD9FoJ+xWQVQAII4/FCXIrC/UawCKAABHH6oTxHoYWxUARSAxhx+6EsR2NMoVAEUgIYcfuhPEahrbFIBFIBGHH7IpQjsYxSpAApAAw4/oAjUMjaoAApAYQ4/cI0isNYoUAEUgIIcfuAjisD+xuIKoAAU4vADj1IEzjc2rwAKQAEOP3Dkx/pRY0ARqF0BFICNOfxApSpgCNSqAArAhhx+oOL7BBSBWhVAAdiIww+spAhkVQAFYAMOP7ADRSCrAigACzn8wM4Ugd4VQAFYwOEHKlAEelcABeBEDj9QmSLQqwIoACdw+IEOFIFeFUABmMjhBzpTBGpXAAVgAocfSKAI1K4ACsCBHH4gmSJQqwIoAAdw+AEUgWoUgCc4/ADXKQJ7VwAF4AEOP8DHFIG9KQB3cPgBHqcI7FUBFIAbOPwAz1ME9qIAvMPhB5hHEfi0tAIoAG9w+AFqFoGKI2AVBeAHDj9AjyJQaQiMRRVAAXD4AdoVAe8P+Fh0AXD4AfaVVATGggoQWQAcfoD9KQJzRRUAhx+gru5FYJxcASIKgMMPUJ8icKzWBcDhB+irYxEYJ1aAlgXA4Qfo78fn42fHwAgsAq0KgMMPkO2oKnBZOATOqgAtCoDDD8CR7xMYAUWgdAFw+AHoWATGCRWgZAFw+AG4hSLQpAA4/ACkFIExuQKUKAAzD/83jj9ABkWgSAFw+AFILgJjYgXYsgA4/ACc4RJcBLYqAA4/ACuNDYvArAqwRQFw+AHYwSWoCCwtAA4/ADsbmxSBGRVgSQFw+AGo4NK4CJxaABx+ACobC4vA0RXglALg8APQwaVREZhaABx+ADobJxeBIyvAlALg8AOQ4FK4CBxaABx+AJKNE4rAURXgkALg8APAp1JF4KkC4PADwPlF4IgK8FABcPgBoHYRuKsAOPwAsEcReLYC3DwAZnL4AUgyTrq92w4Ahx+AZOOEG3zt1i75WQAOPwB8Ouw9Ao84tQA4/ABw3ayb/Nb9PaUAOPwAcN+9nP0J+tQC4PADwCZfOfDqJk8pAA4/AOz9PoFDC4DDDwBzPXO3f7zThxQAhx8AahWBpwqAww8Aa917x19u90MFwOEHgNpF4K4C4PADwN5uuevf7vlNBcDhB4BeReDdAuDwA0Bt1+78mwPA4QeAXl7f+58GgMMPAJ9ae7n7fwPdOLMj3b4oWAAAAABJRU5ErkJggg=="
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is Cut the right side of the shape\nthe 4th action is Stack the original shape on top of the {'layer1': 'CwCwCwCw'}.\nthe 5th action is Cut the right side of the shape\nthe 6th action is Colorize the top layer of the original shape with the color purple.\nthe 7th action is Stack the original shape on top of the {'layer1': 'CwCwCwCw'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'WrWrWrWr'}.\nthe 9th action is Stack the original shape on top of the {'layer1': 'WgWgWgWg'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_70
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAgAAAAIACAYAAAD0eNT6AAAGdUlEQVR4nO3YSw2DABBAQWgwUA3VBCKLJjQgobXAhU/yZs6b7B5fdhgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAC4yDjP8++qZcDzres63n0DcL7XBTsAgIcRAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAiajg5+vu9zLwFOtS373ScAD+IDAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABB09HBbdnPvQQAuIwPAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIaeP3YgCzC+NJnZAAAAAElFTkSuQmCC"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'CrCrCrCr'}.\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is Colorize the top layer of the original shape with the color blue.\nthe 4th action is Stack the original shape on top of the {'layer1': 'CcCcCcCc'}.\nthe 5th action is Cut the right side of the shape\nthe 6th action is Stack the original shape on top of the {'layer1': 'SbSbSbSb'}.\nthe 7th action is Stack the original shape on top of the {'layer1': 'CwCwCwCw'}.\nthe 8th action is Colorize the top layer of the original shape with the color blue.\nthe 9th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_29
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAgAAAAIACAYAAAD0eNT6AAALLklEQVR4nO3d3W0bRwBGUctIAylOBtJJSkgnAaziUoKDAA4SWJbEJfdnZu45z4bAt+/O7JJ++gRM7fn5+duef+/l5eVpz78HjOmXqz8AcOygA/yMAICTGXhgBAIADmDkgdEJAHiQsQdmJABgA2MPrEIAwBuMPbAyAQDfGXygRACQZfCBMgFAhsEH+I8AYGmF0f/j1683/bvf//py+GcB5iEAWM7so3/roAM8QgAwvdkG38ADIxAATGmG0Tf0wMgEAFMZdfiNPTAbAcDwRht9Yw+sQAAwpFFG39gDqxIADGOE0Tf4QIUAID38Bh+oEgDkht/oAwgAAqNv8AFeEwAsOfxGH+B9AoBlht/oA9xOALA7ow8wPgHAdMNv9AEeJwCYYviNPsC+BAB3M/wA8xIADDf8Rh/geAKAmxl+gHUIAC4dfqMPcA0BwJsMP8C6BACvGH6A9QkAThl/ww8wFgHAYcNv9AHGJQDiDD9AkwCIMvwAbQIgaO/xN/wA8xEAIYYfgH8JgADDD8CPBMDi9hx/ww+wDgGwKKd+AN4jABbk1A/ARwTAQgw/ALcSAIvYa/wNP0CDAJicUz8A9xAAE3PqB+BeAmBChh+AR31++C9wKuMPwB7cAMTG3/AD8A8BMAGnfgD2JgAG59QPwBEEwMLjb/gBeIsAGJBTPwBH8y2AwRh/AM7gBmAgrvwBOIsAGIBTPwBnEwAXc+oH4AreAbiQ8QfgKgLgIsYfgCt5BHAyww/ACNwAnMj4AzAKAXAS4w/ASDwCGHz8DT8AR3ADcDDjD8CIBMCBjD8Ao/II4ACGH4DRuQHYmfEHYAYCYEfGH4BZCICdGH8AZiIAdmD8AZiNAHiQ8QdgRr4FcMH4G34AruYG4E7GH4CZCYA7GH8AZicANjL+AKxAAGxg/AFYhQC4kfEHYCUC4AbGH4DVCIAPGH8AViQA3mH8AViVAHiD8QdgZQLgJ4w/AKsTAD8w/gAUCID/Mf4AVAiA74w/ACUCwPgDECQA7mT8AZhZPgDuOf0bfwBmlw4A4w9AVTYAjD8AZckAMP4A1OUCwPgDQCwAjD8ABANgK+MPwKoyAXDvj/0AwIoSAeDqHwBiAWD8ASAWAMYfAIIBsJXxB6Bi2QDYevo3/gCULBkAxh8AYgHg634AEAyArZz+AShaKgBc/QNALACMPwDEAsBzfwAIBsBWTv8A1E0fAK7+ASAWAMYfAGIB4Lk/AAQDYCunfwCYPABc/QNALACMPwAEAwAAiAWA0z8AxALA+ANAMAAAgFgAOP0DQCwAjD8ABANgC+MPAAsEgJ/7BYBYALj6B4BgAAAAsQBw+geAYABsYfwBYIEA8OIfAMQCwNU/AAQDYAvjDwALBICrfwAIBsAWTv8AsEAAOP0DQDAAtnD6B4AFAmDL6d/4A8ACAeDqHwCiNwC3cvoHgAUCwOkfAK4zxQ2A0z8ALBAATv8AcK3hbwCc/gFggQDwtT8AuN7wNwAAwOQB4PQPAGNwAwAAQacFgNM/AIzDDQAABJ0SAE7/ADAWNwAAEHR4ADj9A8B43AAAQNChAeD0DwBjcgMAAEFDBIDTPwAsEgD+y18AGNcQNwAAwAIB4OU/ABibGwAACNo9AJz+AWB8bgAAIOiyAHD6B4BFAsBX/wBgDpfcADj9A8AiAeD0DwDz8BIgAATtEgC++gcAc3EDAABBpwaA0z8ALBIAXv4DgPl4BAAAQacFgOt/AFgkAFz/A8CcTrkBcPoHgLF4BwAAgu4OANf/ADCvw28AXP8DwCIB4PQPAHPzDgAABB0aAK7/AWCRAHD9DwDz8wgAAIIOCwDX/wAwLjcAABC0KQA8/weANRxyA+D6HwDG5hEAAATdHACu/wFgHbvfALj+B4DxeQQAAEE3BYDrfwBYixsAAAjaNQA8/weAObgBAICgDwPA838AWM9uNwCu/wFgHh4BAECQAACAoHcDwPN/AFjTLjcAnv8DwFw8AgCAIAEAAEFvBoDn/wCwrodvADz/B4D5eAQAAEECAACCBAAABP00ALwACABre+gGwAuAADAnjwAAIEgAAECQAACAoFcB4AVAAFjf3TcAXgAEgHl5BAAAQQIAAIIEAADUA8ALgADQcNcNgBcAAWBuHgEAQJAAAIAgAQAAQQIAAIIEAACUA+DWrwD6BgAAzM8NAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAA1QDwGwAA0OIGAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAj67P8BAIAeNwAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAEPR06y8BAgDrcAMAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEFPV38A4By3/urny59fj/8wwKGef/vy4b9xAwAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQU9XfwDgHM/Pz9+u/gzAONwAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAA4FPP3yTm9P4svc67AAAAAElFTkSuQmCC"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'SySySySy'}.\nthe 2th action is Stack the original shape on top of the {'layer1': 'RpRpRpRp'}.\nthe 3th action is Stack the original shape on top of the {'layer1': 'CgCgCgCg'}.\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is Stack the original shape on top of the {'layer1': 'CbCbCbCb'}.\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is Stack the original shape on top of the {'layer1': 'CrCrCrCr'}.\nthe 9th action is Stack the original shape on top of the {'layer1': 'RpRpRpRp'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_151
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is Colorize the top layer of the original shape with the color red.\nthe 3th action is Stack the original shape on top of the {'layer1': 'CuCuCuCu'}.\nthe 4th action is Stack the original shape on top of the {'layer1': 'SwSwSwSw'}.\nthe 5th action is Cut the right side of the shape\nthe 6th action is Colorize the top layer of the original shape with the color green.\nthe 7th action is Cut the right side of the shape\nthe 8th action is Cut the right side of the shape\nthe 9th action is Colorize the top layer of the original shape with the color yellow.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_170
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'WpWpWpWp'}.\nthe 2th action is Stack the original shape on top of the {'layer1': 'RbRbRbRb'}.\nthe 3th action is Cut the right side of the shape\nthe 4th action is Stack the original shape on top of the {'layer1': 'WcWcWcWc'}.\nthe 5th action is Stack the original shape on top of the {'layer1': 'SySySySy'}.\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is Colorize the top layer of the original shape with the color yellow.\nthe 8th action is rotate the shape counterclockwise 90 degrees\nthe 9th action is Colorize the top layer of the original shape with the color white.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABAAAAATICAIAAAANxCANAABQaklEQVR4nO3deZSddX0/8MlGSAKEAJGw/UARhVAkgooGWvQgyo5EZgDFqsX9IFpba2m1oMeq1doq1YrFBVAITCCUHWUVZRFEluCCBAQBWQIMBLJCMr8j4xnSuXdm7tz7LN/l9Tr9p88M9z4ziU8+78/7ufeO6+/v7wIAAPIwvu4TAAAAqiMAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIxMrPsEoFJLly7dfPPNV65c2fSr73vf+0455ZTKTwqAjpx11llj+v7xL5g4ceLkyZOnTp268cYbz5w5c/PNN58wYUJp5wgBGdff31/3OUB1vve97x1zzDHDfXWTTTZ55JFHJk2aVO1JAdCRcePGdf4g66233l/8xV/stttur3nNaw4++OAtt9yyiFODEAkA5GWfffa56qqrRviGiy666MADD6zwjAAIIgAMecA999zzPe95z7vf/e6JE90uQWq8BoCMPPTQQ9dcc02xPTIA6env7//Zz372vve9b6eddurt7a37dKBgAgAZmT9//tq1a0f+nvPPP3+4VwgAkJvFixcfccQRH/jAB1avXl33uUBhBAAy8sMf/nDIkRkzZgw58swzz1x88cUVnhQAoTvllFP222+/5557ru4TgWIIAOTiV7/61e233z7k4Fe+8pXGmzvPPvvsCs8LgFL0j2jNmjWrV69++umn77///muvvfa//uu/Dj/88KlTpw73aFdfffVxxx1X7U8AZfEiYHJx/PHHf+lLX1r3yEYbbfTYY48dcMABQ14WPGXKlMcee2yDDTao/BwBKOxFwG1MOM8+++zXvva1L3/5y88880zTb/jRj370lre8pa1zhIBoAMhCf3///Pnzhxx829veNnny5Hnz5g05vmLFigsuuKDCswMgCBtssMGnP/3pG2+8cbvttmv6DZ/97GcrPykongBAFn7605/ef//9Qw4eccQRAzGgcXXkvYAAsjV79uyLL7646e1A119//S9+8Ys6TgqKJACQhTPOOGPIkU022WTfffft6uraaqutXve61w356o9+9KOnnnqqwhMEICCzZ8/+1Kc+1fRLV1xxReWnAwUTAEjf6tWrFyxYMOTgvHnzBj/x97DDDmv8TxYuXFjVCQIQnI985CMTJkxoPH711VfXcTpQJAGA9F1yySV9fX1N7/8Z0PgyAHcBAWRus802mzNnTuPxxhtKIToCADm+/f/MmTPf9KY3Df6/O+yww8477zzke6666qolS5ZUcoIAhGiXXXZpPPj444/XcS5QJAGAxD399NONH+x1+OGHDyl2G0uANWvWnHPOOeWfIACB2nTTTRsPPv3003WcCxRJACBx55xzzsqVK4ccPPLII4cccRcQAK18ksBGG21Ux7lAkQQAsrv/Z8stt9xrr72GHJwzZ85LX/rSIQd/9rOfPfTQQyWfIACBavp2cDNnzqzjXKBIAgApe/DBB6+99tohB7u7u8ePb/I3v/G9gNauXdvb21vmCQIQrrvuuqvx4O67717HuUCRBABSduaZZ65du3bU+3+GCwDuAgLI1qpVq2699dbG43/1V39Vx+lAkcY1vb8N0rDrrrvecccd6x7Zdtttf//73zd+9O/Avn/LLbd89NFHhxy/9957G+8OAiAcTa/qHU44Z5xxxtFHHz3k4NSpUx966KGNN964k0eG2mkASNadd945ZPrv6urq6elp+u/En/7HMH78oYce2nj87LPPLucEAQjU6tWrv/CFLzQe/8AHPmD6JwECAMlqfPnvCPf/DPBeQAB0dXV94hOf+PWvfz3k4DbbbPO5z32upjOCIrkFiDT19/dvt912f/jDH9Y9+PKXv/zuu+8e4b967rnnXvKSlzS+7cNvfvObHXfcsZwzBSCgW4CWLVv28Y9//Dvf+c6Q4xtttNE111zz6le/ut1zhIBoAEjTtddeO2T67+rqOuKII0b+ryZNmnTggQc2HlcCACSvr6/vpJNO2nnnnRun/8033/zSSy81/ZMMDQBpev/73994Bb/jjjuafq77uhYuXPj2t799yMEdd9zxN7/5TdHnCECJDcD8+fNH+E/6+/tXrVq1fPnyRx555MEHH7z11lvvuOOOxjeO6+rq2nfffU899dQtt9yy0FOGOgkAJGjVqlWzZs0acifPTjvt1HhDZ6Ply5dvttlmK1asGHL81ltvnTNnTtFnCkABhnt3hw69+tWv/uxnP3vwwQeX8eBQI7cAkaCLL7648T7+kV/+O2jq1KlvfetbG4+7CwggH9OmTfvWt751yy23mP5JkgBAgs4444zGg6O+AGDkTwTzZqAA+Vi2bNmHP/zhrbba6thjj3ULKOlxCxCpeeqpp2bNmrVq1ap1D86ZM6fpBzo21dfX95KXvOT5558fcvzGG2/cY489ijtTAIK+BWjQ/vvv//Wvf32HHXYo9VmgMhoAUnPOOecMmf7HtP7v6uqaMWPGG9/4xsbj7gICyNOll176qle96t///d/rPhEoxsSCHgeC/vyvcePGjWl8nzlzZuPB3t7er371q+PHi80AERj1Hoe1a9cuW7bsmWeeeeihhx544IHbbrvtpptuuvrqq1evXt34zStXrvzkJz953333nXTSSf4hIHZuASIpDzzwwLbbblve3+prrrlm7733LunBAaj9g8CeeOKJU0899fOf/3zjm0kMOOGEE0488cQ2HhnCIcKSlDPPPLPUTOsuIIC0bbrppn/3d3/3u9/97k1velPTb/j85z9/ww03VH5eUCQNAEl51atetWjRovIef+bMmX/84x8nTnTvHECaDcCgVatWHXjggVdeeWXjl/bdd98f//jHnTw41EsDQDruuOOOUqf/rq6uJUuWXHXVVaU+BQAhmDx58umnn77JJps0funyyy9v5ZMlIVgCAIm//Ldw7gICyMSWW2557LHHNv3SJZdcUvnpQGEEABLR398/f/78IQenTZu2fPny/nadeeaZjU903nnnNX2DCADS84EPfKDp8euvv77yc4HCCAAk4pprrnnwwQeHHDzooIOmTJnS9mMefPDBjf/5U089ddlll7X9mABEZKutttp+++0bj7sFiKgJACTijDPOaDzY3d3dyWNusMEG+++/f+NxdwEB5GP33XdvPPjkk0/WcS5QDAGAFKxatercc88dcnDatGlNx/cx6enpaTx4wQUXLF++vMNHBiAKm266aePB4T4lAKIgAJCCiy66qPFafOCBB06dOrXDRz7ooIMaH2TZsmUXXXRRh48MQBQ22mijxoM+DJio+etLsu//0+H9PwOmTZt2wAEHNB4/++yzO39wAMK3dOnSFlMBxEIAIHp9fX2Nb8c2derUpoN7G4444ojGg5dccskzzzxTyOMDELIlS5Y0Htx6663rOBcohgBA9BYsWND4vpyF3P8z+FDTpk0bcnDlypX/+7//W8jjAxCym266qfHgTjvtVMe5QDEEAKJXxvv/rGvKlCkHHXRQ43HvBQSQvN/97nd/+MMfGo/vsccedZwOFEMAIG5/+MMffvrTn5Z3/88I7wV0+eWXexs4gLT953/+Z9PjBx54YOXnAoURAIjbmWee2d/fP+TgAQcc0HjTTicOOOCADTbYYMjB5557rvG9RwFIxq233vr973+/8fhee+3V9NPBIBYCAHEr+/6fAeuvv/7BBx/ceNxdQACpeuihhw4//PBVq1Y1fulTn/pUHWcEhREAiNhtt9125513Djk4ZcqUMprZpncB/eQnP3n00UcLfy4A6nXjjTfuscce9957b+OX9ttvv6YvDIOICACktv7ff//9i73/Z/BhG9/1ec2aNQsWLCj8uQCoy0033fTXf/3Xc+fOfeihhxq/OmvWrKY3BUFcJtZ9AtCmtWvXzp8/v4L7fwZMnjz5kEMOafzEsbPOOuvYY48t4xkB6EQrd2k+//zzq1atWrp06eOPP/7b3/72lltuuf/++4f75k022eSyyy6bNWtW0WcKVRvX+AJKiMJVV121zz77DDm4/vrrL1mypPEFu4W48MILDznkkCEHx40bd//992+zzTZlPCMArRg3blzZTzF79uwLLrjAa39Jg1uAiFXjMn7gRp2Spv+urq63vvWt06dPH3Kwv7//7LPPLukZAQjB0UcffeONN5r+SYYAQJRWrly5cOHCyu7/GbDeeusdeuihjce9FxBAql7zmtdcd911P/jBDzbccMO6zwUKIwAQpQsvvPDpp58ecnD99dcv+50Zmr4X0C233LJ48eJSnxeAKm2wwQbvfe97r7vuuptvvnnu3Ll1nw4UzIuAidKUKVNOOOGEIQf/3//7f2VvaN7ylreceOKJja+caUwjAARu3LhxEydOnDx58gYbbDBjxozNN99822233W233ebOnTtnzpyJE81IJMuLgAEAICNuAQIAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAIC2jOuKXHd3d92nQDoWLFhQ9ykAAJRrfMmPDwAABEQAAACAjAgAAACQEQEAAAAyIgAAAEBGBAAAAMiIAAAAABkRAAAAICMCAAAAZGRiV9JmzOut+xQIS9/CnrpPAQCgThoAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIADXrW9hT9ylAbbq7u+s+BQDIzsS6T4A/Z4AZ83rrPhGojtEfAOoiANRsxrzegQAgBpDh6L9gwYJazwUAciQAhEUMIGG2/gAQAgEgoBJgkBhADqO/9T8A1EIACJcYQAJs/QEgNAJAoCXAIDGAJEd/638AqIsAEAcxgFhY+QNA4ASACEqAQWIAaYz+1v8AUCMBID6DOUESIBC2/gAQEQEgshJgXQoBYhz9rf8BoF4CQPTEAGph6w8AkRIA4i4BBokBRDH6W/8DQO0EgKSIAZTK1h8AEiAApFMCDBIDCHP0t/4HgBAIAMkSAyiErT8AJGZ83SdAEyNM7fNP/dWYHqpvYU+HfQLZ6n5B698/8l9O638ACIQGIDJHvWfngTHrqPfs3Pp/pQ2g1K1/G38nAYC6CACxvhJADCCc0X9U1v8AEA4BIOISQAwgnNHf+h8AYiEApPB2QGIAVb7Gd6wvRLH+B4CgCADRlwCDxADqGv2t/wEgIgJAap8JIAYQwtZ/kPU/AIRGAEiqBBgkBlDZ6G/9DwBxEQBS/mBgMYBatv6DrP8BIEACQLIlQOcxQBJIQ6mjv/U/AERHAEi8BOjwo5oUAlGrZes/yPofAMIkAGRRAgwSAzJRzehv/Q8AMRIAMioBBokBCat36z/I+h8AgiUAZFcCDBIDElPx6G/9DwCRGl/3CdCqkmbu9kbAvoU9BTYSdKj7BSEs/gdY/wNAyDQAWZcAnVQB2oAQtDH3FzL6W/8DQLwEgHxfCTCEGBCXukb/UVn/A0DgBIBEdFgCDBIDkpz7ix39rf8BIGoCAE2IAQEKYfQHABIgAKRzF1BRJcAgMSAQQY3+I/99cP8PAIRPAGAUYkCNghr9AYA0CADxqbIEGCQGVCzM0d/6HwASIAAwBmJAtqM/AJAMASBKtZQAg8SAPEd/638ASIMAQJvEgHxGfwAgJQJArOotAYqKAZJALKO/9T8AJEMAoM4YkHMhEMvoDwAkRgCIWCAlwCAxINXR3/ofAFIiAFAwMSCl0R8ASI8AELfQSoBBYkAhc38Io7/1PwAkRgCgRGJA1KM/AJAkASB6wZYAmceANEZ/638ASI8AQEXyiQFpjP4AQKoEgBSEXwJkEgMSG/2t/wEgSQIANUgvBiQ2+gMACRMAEhFRCZBYDEh19Lf+B4BUCQDULN4YkOroDwCkTQBIR4wlQKQxIPnR3/ofABImABCQ8GNA8qM/AJA8ASApUZcAgceAfEZ/638ASJsAQKDCiQH5jP4AQA7G130CFGyEqbe9YbpenQzQfQt7Bv6v7UfofkFW07/1PwAkTwNAylVAe4VAJ0N/vKM/AJCJcV2RG3lWC+F94msxwto76tk0/BIj4V+v9T8ApEEDQF5tQHmiHv0BgHxoAJKVagkwKJwYkMPv0/ofAJKhASBWIbQBaYz+AEBWNAApS74EGFR9DMjqF2j9DwAp0QCQgirbgMRGfwAgNxqAxOVTAgwqLwbk+Ruz/geAxGgASE0ZbUCqoz8AkCGfBJyvcN5FpwzzT/1VIVN7UY8TrLT/GgAAjTQAiZsxr3eEu4CS10kbkPbc3yL3/wBAejQAWctk+zvWLX7yW//c/gIAAOvyIuAsjFwCZDLstjLy+lWsy/ofAJKkAQAAgIwIAFkYuQlxH0iGrP8BIFsCAAAAZEQAyIUSgEHW/wCQMwEAAAAyIgBkRAmA9T8AIAAAAEBGBIC8KAEyZ/0PAAgAAACQEQEgO0qAbFn/AwACAAAA5EUAyJESIEPW/wDAAAEAAAAyIgBkSgmQFet/AGCQAAAAABkRAPKlBMiE9T8AsC4BAAAAMiIAZE0JkDzrfwBgCAEAAAAyIgDkTgmQMOt/AKCRAAAAABkRAFACpMn6HwBoSgAAAICMCAD8iRIgMdb/AMBwBAAAAMiIAMCfKQGSYf0PAIxAAAAAgIwIALxICZAA638AYGQCAAAAZEQAYAyUAIHzBwQAjEoAYAx3ARE79/8AAAIAY2PHHCx/NABAKwQAhlICpMr6HwAQAGiHTXOA/KEAAC0SAGhCCZAe638AYIAAQDvsm4PijwMAaJ0AQHNKgJRY/wMAgwQA2mTrHAh/EADAmAgADEsJkAbrfwBgXQIA7bN7rp0/AgBgrAQARqIEiJ31PwAwhABAR2yga+SXDwC0QQBgFEqAeFn/AwCNBAA6ZQ9dC792AKA9AgCjUwLEyPofAGhKAKAAttEV8wsHANomANASJUBcrP8BgOEIABTDTroyftUAQCcEAFqlBIiF9T8AMAIBgMLYTFfALxkA6JAAwBgoAcJn/Q8AjEwAoEj206Xy6wUAOjeuu7u7gIcBAmD9z5i4/gPV809VCDQAAABUxOohBAIAJMJOBQBohQAAAEB1lAC1EwAgBdb/AECLBAAAACqlBKiXAAApcCUFAFokAAAAUDWrqxoJAJAIV1IAoBUCAAAANbC6qsvE2P9gRn7zkxnzeis8lyz0LewZ+Rvmn/qrroAd9Z6dUz35gf/BejsgitLbG/r1s6enJ+rzp2L+wrTxa+n8NzPq41MLDQBFCnyAjp1fLwAVK3uCD3/XnCQBgCLX/9TOlRSA1pVdfWRbrQROAKAw9tMV8EsGoGJKgPQIALTK+j8WrqQAtE4JkCEBgGLYTFfGrxqAiikBEiMA0BLr/7i4kgLQOiVAbgQACmAnXTG/cAAqpgRIiQDA6Kz/Y+RKCkDrlABZEQDolG10LfzaAaiYEiAZAgCjsP6PlyspAK1TAuRDAKAj9tA18ssHoGJKgDQIAIzE+j92rqQAtE4JkAkBgPbZQNfOHwEAFVMCJEAAYFjW/2lwJQWgdUqAHAgAtMnuORD+IAComBIgdgIAzVn/p8SVFIDWKQGSJwDQDlvnoPjjAKBiSoCoCQAAAPwfSoC0CQCM+f4f++YAjfqHYpUCQLGUAPESAAAAGEoJkDABgKGs/yOlBACgYkqASAkAAAA0oQRIlQDA/2H9HzUlAAAVUwLESAAAAKA5JUCSBABeZP2fACUAABVTAkRHAAAAYFhKgPQIAPyZ9X8ylAAAVEwJEBcBAACAkSgBEiMA8CfW/4lRAgBQMSVARAQAAABGoQRIiQCA9X+alAAAVEwJEAsBAACA0SkBkiEA5M76P2FKAAAqpgSIggAAAEBLlABpEACyZv2fPCUAABVTAoRPAAAAoFVKgAQIAPmy/s+EEgCAiikBAicAAAAwBkqA2AkAmbL+z4oSAICKKQFCJgAAADA2SoCoCQA5sv7PkBIAgIopAYIlAAAAMGZKgHgJANmx/s+WEgCAiikBwiQAAADQDiVApAQAXmT9nzx/xABUTAkQIAEgLyPf/wMuowCMiRIgRgIAf2Y3nAl/0ABUTAkQGgEgI9b/tMJlFIAxUQJERwDgT2yFs+KPG4CKKQGCIgDkwvqf1rmMAjAmSoC4CADYB+fIHzoAFVMChEMAyIL1P2PlMgrAmCgBIiIA5C6fTfBR79n5qPfs3Pn3JCOfP3oAAqEECIQAkPX6P5MRcKxjfT4xYOS/AC6jAIyJEiAWAgAp62SUzycGAEBllAAhEAASl+36v6jxPfkYoAQAoEBKgCgIAKSmjJE9+RgAAJVRAtROAEhZbuv/ssf0VGOAEgCAAikBwicAkIIqR/NUYwAAVEYJUC8BIFmZrP/rGscTiwFKAAAKpAQInABArEIYwUM4BwCIkRKgRgJAmtJe/4c2dod2Pu1RAgBQICVAyAQAYhLyqB3yuQFAgJQAdREAEpTk+j+W8TqW82xKCQBAgZQAwRIAyGWknjGvd8a8Ua4UC16QeQwAgMooAWohAKQmsfV/ZaN/YwzoPAnEmAGUAAAUSAkQpol1nwCUNT2PaehvaiADdDL1DvwUMUYvAKhGT09PqXN8d3d3IfV+SjQASUlj/d/5/TNjXfmPrPM2IK47gpQAABRICRAgAYCAhDb65xwDAKAyXglQMQEgC+Gv/0Me/TOMAeH/hQEgIkqA0AgAWdz/E7JYRv8MY8Bw7FEAKJwSoEoCQPqC3ebGOPrnEwOC/WsDQIyUAEERABIR1/o/9tE/nxgwHHsUAAqnBKiMAJC40Pa4KY3+yceA0P7yABA1JUA4BIAURLH+T3X0Tz4GDMceBYDCKQGqIQCkLJANbg6jf6oxIJC/QgCkQQkQCAEgeiGv/3Mb/VONAcOxRwGgcEqACggAyap3d5vz6J9YDFACAFAgJUAIBIC4Bbj+N/oPFwM6SQK1x4Dh2KMAUDglQNkEgDTVsrU1+o8q0higBACgQEqA2gkAEQtn/W/0zyEGDMceBYDCKQFKJQAkqMp9rdE/kxigBACgQEqAek2s+fmJdv3f+dxf3LlEbCADtL2HGPhTqH067+7u7vC1zgDx7pIpSU9PT6lzfHfG/3hpAFJTwSzY4e4525V/7G1A7TEDYKx6XlD3WdCcEqBGAkCU6lr/G/1LFUUMGE7mN1MCoTH6p8ErAUoiACSlvB2t0b8yIccAJQAQPqN/RJQAdREA4lPx+t/oX4uQY8Bwst2jAIEw+idJCVAGASAdhW9njf61CzAGKAGAABn946UEqIUAEJlq1v9G/6AEGAOGk+ceBaiR0T8HSoDCCQCJKGova/QPVjgxQAkAhMDonwwlQPV8DkBMSl3/e1//KAxmgPbWFRV8bkDOb6sMVMPcnyGfCVAsDUAKOpznbP1zKwQ6bwOUAEAtbP1TpQSomACQ+/rf6J9zDOgqR4Y3UwJlM/rjlQAFEgCi1/YutpM1sNE/jRjQyd8BJQAQy+jf+4LizohSKAGq5DUAOa7/O9z6F3gmFGggA7SxwCjjhQG53UwJhLnxNfMlxisBiiIAxG2sQ5vRP3lVxoD5p/6q+o8bA3Jg9M9Tb29vqff5lP34EREAcmH0z0pQbQBA64z+jEwJUAivAYj4/p8WpzT3+mergtcGjPCXMKtXUwGdc68/XglQGQ1AyjqZ+4s+F2qjDQACZ+vPmCgBOqcBSHP93/bW38o/VeW1AUoAoG22/jRSAlRAA5AaW39GoA0AAmHrTyeUAB3SAKSz/rf1p642QAkAtM7Wn1EpAcqmAUiBrT9t0AYAFbP1p0BKgE4IAHGv/43+dGjw6jbWJDAkBozwmQBpX0OBVhj9GSufCVAqASBWRn9CKAS0AcDIjP6URwnQNgEgvvW/0Z9gY4ASABhk9KdDSoDyCACRaftlviWcC8nqJAYAGP2pjBKgPd4FKETDrf/b4B1+qP7NgprydkCQA+/wQ7G8HVBJNADJMvdT75sFAVmx9acuSoA2aAASXP/b+hNmGyBFQJJs/SmVEqAMGoCkmPsplTYAWJetP4FQAoyVBiCR9b+tP1G0AcIDpMHWnyopAQonAETP6E8CLxEG8hn985y3KFvZb+jZndYCSwCIeP1v9CfGGJDYNRTyUdTob/qnDUqAYnkNQHwM/YTGawMgbYXsVmscsLL9sKfceCVA6wSAmNb/Rn/SiAEpXUMhbUZ/wuGDgQskAMTB6E8sBid7hQBEzehPjJQALRIAQl//G/1JshBI5hoK6TH6EywlQFEEgHAZ/UmAlwdARIz+JEAJ0AoBIMT1v9GfHGJAGtdQSIPRn1goAQohAITF6E/CtAEQIKM/6VECjEoACGX9b/QnwxiQwDUU4mX0J1JKgM4JAPUz+pMhbQDUyOhP8pQAIxMAamb6J2dRXz0hRkZ/0qAE6JAAAADpM/qTGyXACAQAAEiZ0d89h0lSAnRCAACANBn9413QUgglwHAEAABIjdE/0rGMMVECtE0AAIB0GP2N/qxLCdCUAAAAKTD6xziH0SElQHsEAACIm9Hf6M8IlACNBAAAiJXRP7rBi8IpAdogAABAfIz+Rn9apwQYQgAAgJgY/eOatKiAEmCsBAAAiIPR3+hP25QA6xIAACB0Rv+IRitqoQQYEwEAAMJl9Df6UxQlwCABAABCZPSPZZYiEEqA1gkAABAWo7/Rn5IoAQYIAAAQCqN/FMMTwVICtEgAAID6Gf2N/lSjRwkgAABAvYz+4U9LREQJ0AoBAADqYfQ3+lOLnuxLAAEAAKpm9A98PCJqSoBRCQAAUB2jv9GfEPTkXQIIAABQBaN/yPMQiVECjEwAAIByGf2N/gSoJ+MSQAAAgLIY/YMdgEieEmAEAgAAFM/ob/QnfD25lgACAAAUyegf5sRDhpQAwxEAAKAYRn+jP9HpybIEEAAAoFNG/wBHHFACDEcAAID2Gf1N/8SuJ78SQAAAgHYY/Y3+REEJ0EgAAICxMfob/UlMT2YlgAAAAK0y+hv9iZESYAgBAABGZ/Q3+pO2npxKAAEAAEZi9Df6kwAlwLoEAABozuhv9CcrPdmUAAIAAAxl9Df6kx4lwCABAABeZPQ3+pOznjxKAAEAAP7E6G/0J3lKgAECAAC5K+of7Lqmf6M/FKgngxJAAAAgX0Z/oz+56VUCCAAA5Mnob/SHbEsAAQCAvBj9jf5krjf7EkAAACAXRn+jP7Qo7RJAAAAgfUZ/oz+sqzfvEkAAACBlRn+jP7SnJ90SQAAAIE1Gf6M/jKA34xJAAAAgQVF/qpfRHwLRk2gJIAAAwFBGf8hBb64lgAAAAC8y+gPJlwACAAD8idEfMtSbZQkgAACQO6M/kFUJIAAAkC+jP9CbXwkgAACQI6M/kG0JkHgA6FsYVt4CoHZGfxqFtqAlMb2BlQCJBwAAGGT0B9qWUgkgAACQPqM/UK/ekEoAAQCAlBn9gaL0pFICCAAApMnoDwSlN5gSQAAAIDVGf6AkPUmUAAIAAOkw+gMh6w2jBBAAAEiB0R+oRk/8JYAAAEDcjP5ARHoDKAEEAABiZfQHatETeQkQfQDo7u6u/kkL+SNx6QeIbvo3+qeqrjBJnnrrLgGiDwAVM/oD5MnoD1Sp1BJAAGiV0R8gT0Z/ILESQAAYndEfIE9GfyDJEkAAGInRHyBPRn8g4RJAAGjO6A+QJ6M/kHwJIAAMZfQHyJPRH8ikBBAAXmT0B8iT0R/IqgQQAP7E6A+QJ6M/kGEJkHsAMPoD5MnoD2RbAuQbAIz+AHky+gOZlwA5BgCjP0CejP5ApIotAfIKAEZ/gDwZ/YGQ9VZbAuQSAIz+AHky+gNp6C6uBEg/ABj9AfJk9Aci0lthCZByADD6A+TJ6A8kqbugEiDNAGD0B8iT0R+IV29VJUBqAcDoD5Anoz+Qg+4iSoB0AoDRHyBPRn8gGb2VlAApBACjP0CejP5Ahro7LgHiDgBGf4A8Gf2BVPWWXwLEGgCM/gB5MvoDdHdWAsQXAIz+AHky+gOZ6C25BIgpABj9AfJk9AcosASIIwAY/QHyZPQH8tRbZgkQegAw+gPkyegPUFIJEG4AMPoD5MnoD9BVZgkQYgAw+gPkyegPUEEJEFYAMPoD5MnoD1BZCRBKADD6A+TJ6A9QcQlQfwAw+gPkyegPUEsJUGcAKOqq7eoPEJei/jFz/QfoGnsJUE8AMPoD5MnoD1B7CVB1ADD6A+TJ6A8QSAlQXQAw+gPkyegPEFQJUEUAMPoD5MnoDxBgCVBuADD6A+TJ6A8QbAlQVgAw+gPkyegPEHgJUHwAMPoD5MnoDxBFCVBkADD6A+TJ6A8QUQlQTAAw+gPkyegPEF0J0GkAMPoD5MnoDxBpCdB+ADD6A+TJ6A8QdQnQTgAw+gPkyegPkEAJMLYAYPQHyJPRHyCZEqDVAGD0B8iT0R8gsRJg9ABg9AfIk9EfIMkSYGIFV22XfoA8p3/Xf4AAS4DiPwl4XS79AHly/QcItgQoKwC49APkyfUfIPASoPgA4NIPkCfXf4AoSoAiA4BLP0CeXP8BIioBigkALv0AeXL9B4iuBOg0ALj0A+TJ9R8g0hKg/QDg0g+QJ9d/0lPUp15AFNoJAC79AHly/QdIoAQYWwBw6QfIk+s/QDJaDQAu/QB5cv0HSKwEGD0AuPQD5Mn1HyBJIwUAl36APLn+AyRcAjQPAC79AHly/QdI3tAA4NIPkCfXf4AcdHd3vxgAXPoB8uT6D5CVcf39/XWfAwAAUJHxVT0RAABQPwEAAAAyIgAAAEBGBAAAAMiIAAAAABkRAAAAICMCAAAAZEQAAACAjAgAAACQEQEAAAAyIgAAAEBGBAAAAMiIAAAAABkRAAAAICMCAAAAZEQAAACAjAgAAACQEQEAAAAyIgAAAEBGBAAAAMiIAAAAABkRAAAAICMCAAAAZEQAAACAjAgAAACQEQEAAAAyIgAAAEBGBAAAAMiIAAAAABkRAAAAICMT6z4BqM6qVatuvPHG66677re//e3ixYsffPDBZ599dtmyZWvXrp0yZcq0adO22GKLrbbaaqeddtp111333HPP7bbbru5TBgAo2Lj+/v6iHxPCsmrVqgsvvPC000674oorVq5c2fp/uMMOOxx++OHvfe97d9hhhzJPEIAxO+uss8b0/ePGjRs/fvyECRMmT548ZcqUjTbaaNNNN501a9aUKVNKO0cIlABAypYvX/7Nb37zK1/5ypIlSzp5nEMOOeTEE0989atfXdypAdCRcePGFfI4W2+99ezZs3fbbbe99957r7322mCDDQp5WAiZAECyzjrrrI9//OOPPvpoIY82fvz4j3zkI1/84hf92wCQUgBY1+TJk/fbb793vOMdhx122KRJkwp/fAiEAECCnnjiiWOOOeb8888v/JFf+cpXnn/++a985SsLf2QAag8Ag7baaqvjjjvuox/9qBuESJIAQGp+/etfH3LIIffcc88I3/OKV7xi991332mnnTbbbLMNN9xwxYoVTz75ZF9f36JFi2644Ya+vr4R/tvp06f/6Ec/2mOPPUo4dwCCCAADttlmmy9/+ctHHnlk2U8EFRMASMr111+///77L126tOlXt9566w996EPveMc7XvrSlw73CP39/YsWLfqf//mf00477dlnn236PdOnT7/qqqt222234k4cgOACwIDu7u6TTz55k002qebpoAICAOn4xS9+sc8++zSd/jfaaKPPfOYzH/vYx1q/p/Ppp58+4YQTTjrppKb/G9l6661vuummLbbYouOzBqCwADDyVPP888+vWbNm+fLlzz777JIlS+67775f/epXN998809+8pPhNkcDXvayl1188cU77rhjEScO9RMASMS999772te+9sknn2z80mtf+9re3t723tT/iiuuOProo5u+knjffff98Y9/3NbJAlBDABjO6tWrr7zyym9/+9sXXnjh2rVrm37PjBkzLr30Uvd/kgYBgBQsX7587ty5t99+e+OXDj300N7e3vXWW6/tB7/zzjv33nvvptHilFNOed/73tf2IwMQQgAYtGjRor//+78fbrmz8cYbX3XVVd4SmgQIAKTgmGOO+d73vtd4/JBDDjn33HMnTuz0E69vvvnmv/zLv1y1atWQ47NmzVq8ePG0adM6fHwAQggAA7797W8fd9xxq1evbvzSFltsccstt7j/k9iNr/sEoFNXXHFF0+l/1113PfPMMzuf/gduIvrMZz7TePyRRx45+eSTO398AMLxwQ9+8Morr5w+fXrjlx5++OGenp41a9bUcV5QGA0AcVu1atVOO+30+9//fsjxqVOn3nbbbTvssENRT/Tcc8/tvvvuixYtGnL8ZS972d133z1+vCwNkEgDMOCGG25485vfvHz58sYvffWrX/3EJz5R1BNB9UwtxO3kk09unP67urq+8IUvFDj9d3V1TZo06YQTTmg8fu+9915//fUFPhEAIXjDG97w3e9+t+mXTjjhhAcffLDyM4LCCABEbMWKFV/60pcaj++4447HHnts4U/3tre9beutt248ft555xX+XADU7sgjjzzqqKMajz/77LNN//WBWAgAROyHP/zhI4880nj8X//1XydMmFD4002YMOGDH/xg4/Grr7668OcCIAT/9m//NmXKlMbj3/3ud5v+AwRREACI2CmnnNJ4cPvtt3/b295W0jMedNBBjQfvuOOOZcuWlfSMANRom222+Yd/+IfG4ytXrjz11FPrOCMogABArO68886bb7658fhHPvKR8l6Su+uuu86cOXPIwTVr1tx1110lPSMA9frbv/3byZMnNx4//fTT6zgdKIAAQKzOP//8xoPjxo078sgjy3vScePG7bPPPo3H77777vKeFIAaTZ8+vWn9+5sX1HFG0KkC3iIdanHJJZc0Hpw7d+6WW25Z6vMeeeSRjW8zt+GGG5b6pADU6J3vfOe5557bePyKK67Yaaed6jgj6IjPASBKzz777MYbb9z4USyf+cxnPve5z9V0UgCk8zkA61q9evWMGTMaPxPgsMMOW7hwYRnPCKVyCxBRuvXWW5t+EOPee+9dx+kAkLL11ltvl112aTx+22231XE60CkBgCj98pe/bHp8zpw5lZ8LAOlr+u/Lfffd98wzz9RxOtARAYAo/frXv248OGvWrE033bSO0wEgxwDQ399/zz331HE60BEBgCg98MADjQdf9rKX1XEuAKRv9uzZTY//8Y9/rPxcoFMCAOkEgC222KKOcwEgfRtvvHHT4w8//HDl5wKdEgCI0uOPP954sPEjugCgEBtttFHT40uXLq38XKBTAgBRanwvtq6urilTptRxLgCkb/r06U2Pr1ixovJzgU4JAERp5cqVjQfXX3/9Os4FgPQN1wCsWrWq8nOBTgkAROn5559vPOhT7QAoSdMPn+nq6po0aVLl5wKdEgCI0uTJk1usBQCgc8Nt+pXPxEgAIEpNb/dv+sIAAOjccB/4NXXq1MrPBTolABClDTfcsPHgkiVL6jgXANL36KOPNj0+a9asys8FOiUAEKUtt9yy8eAjjzxSx7kAkL7h3u9/q622qvxcoFMCAFFqesG999576zgXANL3u9/9runxbbfdtvJzgU4JAETppS99aePBRx999Mknn6zjdABI3G9/+9vGgzNnznQLEDESAIjSq171qqbHb7/99srPBYD03XjjjY0Hd9111zrOBTolABCl4a65P/3pTys/FwAS9/TTT995552Nx+fOnVvH6UCnJnb8CFCD2bNnT58+/emnnx5y/Oqrr/6Xf/mXUp/6b/7mb4a83+h66613+umnl/qkANTo0ksvbfpBYPvuu28dpwOdGufDU4nUvHnzzjvvvCEHJ0yY8Mgjj2y22WYlPek999zz8pe/fMjB7bbb7ve//31JzwhAU+PGjWs8WNJU093dfc455ww5uPHGGz/22GM+CZgYuQWIWO23336NB9esWXPuueeW96SXX35548HGSABAMh577LHzzz+/8fgRRxxh+idSAgCxmjdvXtMr77e+9a3ynvSKK65oPLjLLruU94wA1Osb3/jGc88913j83e9+dx2nAwUQAIjVZptttv/++zcev/3226+++uoynnHFihVXXnll4/E999yzjKcDoHZPPPHE17/+9cbje+yxxxve8IY6zggKIAAQsQ9+8INNj//zP/9zGU935plnPvXUU0MOTpo06U1velMZTwdA7T75yU8uXbq08fg//dM/1XE6UAwBgIgdcMABc+bMaTx+ww03nH322YU/3Te/+c3Gg/vss88mm2xS+HMBULuLL774+9//fuPxPffc8+CDD67jjKAYAgBx+/SnP930+Ec/+tHHH3+8wCc655xzbr311sbj73//+wt8FgACsXjx4ne9612NxydMmPDNb36z6XsQQSwEAOL29re/vekdOEuWLHnXu961du3aQp7lqaeeOu644xqPb7/99oceemghTwFAOB588MF99923r6+v8UvHH3+8DwAmdgIA0fvGN77R9O2ALrvssk9+8pOdP35/f/+HP/zhhx9+uPFLX/ziFydMmND5UwAQjkWLFs2dO/e+++5r/NJf/dVfnXjiiXWcFBRJACB6s2fP/uIXv9j0S//xH/9x/PHHd/j4xx577FlnndV4/M1vfnN3d3eHDw5AOPr7+08++eTXv/71DzzwQONXt99++97eXnsfEuCTgElBf3//IYccctFFFzX96pFHHvmd73xn2rRpY33YZcuWfexjH/vud7/b+KUZM2bccccdW2+9dVvnC0BwnwR81VVXHX/88TfddFPTr26++ebXXXfd9ttv3/bjQzgEABKxdOnSN77xjU1fpzuwtvna17520EEHtf6A11577THHHLN48eLGL02cOPGyyy7bZ599OjhfAIIIAHfdddcFF1zwgx/8YNGiRcN9z3bbbXf55Zf73HeSIQCQjscee2yvvfa6++67h/uGPfbY47jjjjv44IM33HDD4b5n6dKlF1100UknnfTzn/+86TeMHz/+1FNPbfrWEADUGwDmz58/wn+yZs2a1atXL1u2rK+v75FHHlm8ePEvf/nLUd8y7g1veMO55567xRZbdHzKEAoBgKQ89thjhxxyyHCz+4D11lvv9a9//S677PLyl798+vTpkyZN6nvBH//4xxtvvHHRokUjvHfQpEmTTj311He84x3lnD4ArargjTjHjx//iU984gtf+ELTt5qAeAkApGbFihUf+tCHTj/99MIfefPNNz/33HP33HPPwh8ZgNACwOte97r//u//3n333Ut9FqiFdwEiNVOmTDnttNPOO++8WbNmFfiw73znO++8807TP0Dy5s6de8EFF/z85z83/ZMqDQDJWrZs2Te+8Y2vfOUrTzzxRCeP85a3vOWzn/3s61//+uJODYDgGoDZs2cfeuihRx999OzZs4t9ZAiNAEDiVqxYcd5555122mlXX331c8891/p/+IpXvOKwww5773vf+8pXvrLMEwSgogAwfvz4iRMnrr/++tOmTdt4441nzpy5zTbb7LjjjjvvvPPcuXM333zzcs4UgiMAkItly5Zdf/3111133V133bV48eKHH3742WefXbZsWX9//5QpU6ZNm7bFFltsvfXWO+6445w5c/bcc8/tttuu7lMGACieAAAAABnxImAAAMiIAAAAABkRAAAAICMCAAAAZEQAAACAjAgAAACQEQEAAAAyIgAAAEBGBAAAAMiIAAAAABkZV/cJAFCP7u7uuk8BQrFgwYK6TwGqowEAyJSJByBPAgAAAGREAADIlxIAIEMCAAAAZEQAAMiaEgAgNwIAAABkRAAAyJ0SACArAgAAAGREAABACQCQkYl1nwAAcfjSjN66TwHa9499PXWfAoRCAwBASyWA+QkgDQIAAABkRAAA4M+UAAA5EAAAACAjAgAAL1ICACRPAAAAgIwIAAD8H0oAgLQJAAAAkBEBAIChlAAACRMAAAAgIwIAAE0oAQBSJQAAAEBGBAAAmlMCACRJAAAAgIwIAAAMSwkAkB4BAAAAMiIAADASJQBAYgQAAADIiAAAwCiUAAApEQAAACAjAgAAo1MCACRDAAAAgIwIAAC0RAkAkAYBAAAAMiIAANAqJQBAAgQAAADIiAAAwBgoAQBiJwAAAEBGBAAAxkYJABA1AQAAADIiAAAwZkoAgHgJAAAAkBEBAIB2KAEAIiUAAABARgQAANqkBACIkQAAAAAZEQAAaJ8SACA6AgAAAGREAACgI0oAgLgIAAAAkBEBAIBOKQEAIiIAAABARgQAAAqgBACIhQAAAAAZEQAAKIYSACAKAgAAAGREAACgMEoAgPAJAAAAkBEBAIAiKQEAAicAAABARgQAAAqmBAAImQAAAAAZEQAAKJ4SACBYE7si193dXfcpkNHIAuvq7u72d6ZGIgRApg2Af32B6nW/oO6zCJ0SACBM0TcAAFUy9wMQu+gbACUAUA1b/zYoAQACpAEAGIW5H4CUpNAAKAGAktj6d04JABAaDQBAE+Z+AFKVSAOgBACKYutfOCUAQFA0AAB/Zu4HIAfpNABKAKBttv5lUwIAhCO7BmD73hl1nwJ1uqenr+5TICzm/lTNmNdb9ykQlr6FQiak2AC0smQy/wEDbP0rpgQACER2DQCAuR+AnKXWACgBgBHY+tdLCQAQAg0AkAVzPwAk2wAoAYB12foHRQkAUDsNAJCszuf+7Xtn2BcAkJg0GwAlAGSu863/9r0zvGtwSZQAAPXSAABJKWTrX9C5AECIkm0AlACQG1v/iCgBAGqkAQCiZ+sPAK1LuQFQAkDybP3jpQQAqIsGAIiSrT8AtCfxBkAJAOmx9U+GEgCgFhoAIBq2/gDQufQbACUAJMDWP1VKAIDqaQCAoNn6A0CxsmgAlAAQI1v/TCgBACqmAQCCY+sPAOXJpQFQAkAUbP3zpAQAqJIGAAiCrT8AVCOjBkAJAGGy9UcJAFAlDQBQG1t/AKheXg2AEgACYetPIyUAQDU0AEClbP0BoF7ZNQBKAKiLrT+jUgIAVEADAJTO1h8AwpFjA6AEgMrY+jNWSgCAsmkAgFLY+gNAmDJtAJQAUB5bfzqkBAAolQYAKIytPwCEL98GQAkABbL1p1hKAIDyaACAjtj6A0Bcsm4AlADQCVt/6r0+A9AeDQAwZrb+ABCv3BsAJQCMia0/VVICAJRBAwC0xNYfANKgAfgTJQCMwNafGikBAAqnAQCGZesPAOnRAPyZEgDWZetPOJQAAMXSAABFrvxt/QEgcBqAFykByFnnK39bf8qjBAAokAYAcmfrDwBZ0QD8H0oAsmLrT0SUAABF0QBAjmz9ASBbGoChlACkzdafeCkBAAqhAYBc2PoDABqA5pQAJMbWn2QoAQA6pwGAlNn6AwBDaACaUwIQO1t/UqUEAOiQBgBSY+sPAIxAAzAsJQAZbv0HVv6mfwKnBADohAYAUlDI3T4FnQsAEDQNwEiUAOSz9S/ujKAKSgCAtmkAaiZCpHf3fHTq/Usoe5CtvoU9dZ8C1Ka7u1uMr5EGYBRKAADKMGNeb92nALG+SR0d0gAAAFA6c384NACjUwIAUAYlAJmw9Q+NBgAAgFKY+8OkAWiJEgCAMigBSJWtf8g0AAAAFMbcHz4NQKuUAACUQQlAMmz9Y6EBAACgI+b+uGgAxkAJAEAZlADEy9Y/RhqAoPknoeKP3vQLL4OPO4VCLJjvAtWR7qNciwpm7o+XBmBslAAAlGHUBYT5lXDY+sdOAwAAQEvM/WnQAIyZEgCAMigBCJmtf0o0AAAADMvcnx4NQDuUAACUQQlAUGz9UyUAAABQ8OjvfatCJgC0SQkAQBmUACQw+pv+A+c1AAAAFHCvv7k/FhqA9ikBACiDEoCK2frnRgMAAJApW/88aQA6ogQAoAxKAMpm658zDQAAQEZs/dEAdEoJAEAZlAAUztafARoAAIDE2fqzLg1AAZQAAJRBCUDnbP1ppAEAAEiQrT/D0QAUQwkAQBmUALTB1p+RaQAAABJh608rNACFUQIAUAYlAK2w9ad1GgAAgIjZ+jNWGoAiKQEAKIMSgKZs/WmPBgAAIDK2/nRCA1AwJQAAZVACMMDWn85pAAAA0l/52/ozSANQPCUAAGVQAuSp85W/rT9DaAAAAEJk609JNAClUAIAUAYlQCZs/SmVBgAAIBS2/lRAA1AWJQAAZVACpMrWn8poAAAA6mTrT8U0ACVSAgBQBiVAMmz9qYUGAACgarb+1EgDUHMJAABtUALEy9af2mkAAACqYOtPIASA0i1YsKCQ/8EDwLpmzOvtWzjSmr/7qB7DYiAKWfkXdC4gAAAAlMboT4C8BqAKXgkAQBm8EiDte/3d6E9JNAAAAEWy9SdwGoCKKAEAKIMSICi2/kRBAwAA0ClbfyKiAaiOEgCAMigB6mXrT3Q0AAAA7bD1J1IagEopAQAogxKgYrb+RE0DAADQKlt/EqABqJoSAIAyKAHKZutPMjQAAAAjsfUnMRqAGigBACiDEqBwtv4kSQMAADCUrT8J0wDUQwkAQBmUAJ2z9Sd5GgAAgD+x9ScTGoDaKAEAKIMSoA22/mRFAwAA0D5zP9HRANRJCQBAGZQA1bD1J1IaADrStzCpf0Ji/HFG/WceoAzdR/XkPPvW/rNn/vunQwIAACRoxrzekZcanU+QAzVCbmNo7T+v9obOCQAAwJgtmN87MInmEwOCGv1rPxmiJgAAQJoqKAHWfaiEp9Lafy5bf4olAAAAHZUACceAen+W4eb+lH7D1EIAAIBkVVkCrPuYCcypYY7+UAgBAAAorARIoBAIfPSP7vdJgAQAAEhZLSXAkMePZWwNfPSHoggAAEBZJUAsMSCW0T/YXyBx8UnAAJC4cD4YuPuoHnvudfmFUAsNACXq7Q1uUdHT0xPXCY96zgCxlACxtAEVaG/oz/k3RrE0AACQvnBKgMyX33n+1IRGAAAAOtX2cjqfgbjDn9T6nwK5BQgAslD72wGN/NQJj7mZJBwiogEAAApQyOyeWCFQ1I+TZC6iRgIAAOQiwFcCpBoDEvgRSJgAAAAUY4RFdRtvsxbpDN3GaY/8y7H+p3BeAwAAGanrlQA9PT0DY+5Y39o4lvcMbS+rtPc7gQ4JAABAddKLAZ2M/lALtwABQF5KfSXACDP6ukN/7wtivymovfMZ8rOPnIXCzDzETgMAANQj3jbA1p+oaQAAIDshlACFtAGxfIDxcD+j9T+10AAAAPXr7e1t77WwlRUCbYcNi39CowEAgBwFVQJ0UgUMKK8N6KRqGPknsv6nLhoAACAgnbwzZrFtQCeJwtafkGkAACBTAZYAgbQBnTxCi2du/U+NNAAAQKCqbwNs/cmBBgAA8hVyCVBxG1DB1n+Q9T/10gAAAFm0AZ18w8hnBXHRAABA1qIoAQppA4rV9plY/1M7DQAAkFEbUNSzQ7w0AACQu7hKgBrbgM6f0fqfEGgAAICIVdMG2PqTEg0AABBrCVDNgF7Ug1v/EwgNAACQgjKqAIt/kqQBAABKLwFGUPjIXsjUXvgLDOp6yTI0EgAAgNJVfH9LJ+N7Le806v4fqiQAAABJlQBtj/Lljf7W/wRFAAAA6l9ylzcitzLWl7r1H/VHs/6nYgIAAFB/CQBURgAAABIvAWpk/U+ABAAA4P9QAkDaBAAAoDpZlQDW/4RJAAAAhlICQMIEAACgUpmUANb/BEsAAACaUAJAqgQAAKBqyZcA1v+ETAAAAJpTAkCSBAAAoAYJlwDW/wROAAAAhqUEgPQIAABAPZIsAaz/CZ8AAACMRAkAiREAAIBARVcCRHfC5EkAAABqKwFyux8mt5+XMAkAAEC4ItqpR3SqZE4AAABGpwToXD4/KYETAACAoEWxWY/iJGGAAAAAtEQJ0IkcfkZiIQAAAKELfL8e+OnBEOO6u7uHHgOgNQsWLOiKlus/UKOor5+x0wAAAEBGBAAAAMiIAAAAABkRAAAAICMCAAAAZEQAAACAjAgAAACQEQEAAAAyIgAAAEBGJsb+OZEjf4zc9r0zusJ2T0/fCF+dMa+3K2x9C0f68PPe3t64Pq09wBMe9Zxj/0vikyCD9aUZof/V+se+pP+nMT/08y9c91Ej/UI6v0SXev0f+cE7+TMd9dfiKkobNAAAQOjCXNCEcHrh72oJkAAAANRs1D13tj9jhl0QFRAAAICgBb7+H6AEICICAABAuJQAFE4AAADCvTcmivV/i6da3p1OSgDGRAAAAAiaEoBiCQAAQG2SWf8PUAIQBQEAACB0SgAKJAAAAPVIbP0/QAlA+AQAAIAIKAEoigAAANQgyfX/ACUAgRMAAADioASgEAIAAFC1hNf/A5QAhEwAAACIhhKAzgkAAEClkl//D1ACECwBAAAgJkoAOiQAAADVyWT9P0AJQJgEAACAyCgB6IQAAAAEIbH1f+0/lBKA4QgAAEBFyrvjJcPfiRKAtgkAAEDKm/KeF3T+PW1TAhAaAQAAqHnVXdKIPNaxvrwYMPIPqASgYhOrfkIAgJJ1MscP/LfJvCChu7t7wYIFdZ8FYdEAAADprP+L2uIX3gYoAQiHBgAASEEZd++k0QYoARhCAwAARL/+L+8lvAU+uBKAQGgAAICIlTr6J1MFKAFYlwYAAIhy/V/qe3eW9IxKAEKgAQAAIlPx3J9GG6AEYJAGAACIZv1f/da/8DNRAlA7DQAAEIFA5v6o2wAlAAM0AABA1cY0MXe+9R91O97h+nysZ1hSYFAC0CINAABQirbvZilw69/6TDzwnZ2cc1FtQPdRPeWN8koANAAAQNVaGZEL2fq3MUa391+1ceZKAGqkAQAAitf2Kr3KrX+wbYASgFJpAACA6owwE9e19S/v0Ub+iZQA1EUAAAAK1sbuPKjRv/GRO3nw9n60zl9BMdKDd3eX9+CETwAAACrSdOfd4eK/vNG/wCca7mdUAlALrwEAAIrU+uq6w7m/qw6dvDxgrC8M8EoASqIBAACqsO7g28nWv7KVf0nnMORnVwJQPQ0AAFCYUVfjMW79a2wDlACUQQAAAErX29ub0uhfeAzo/M1Pm55Yqa8kJl4CAABQjBHGzU5u+OmKweB5Fv4OSEoACuc1AABAiEK41z/20w7nTAiKAAAAFKDAu02CmqFD+BF8JgDFEgAAgFAkMPqH9uPUfgIEyGsAAICapT2kdvIq4Wp4JUBuNAAAQKfanm5D2JFXo8OftJP8kMlvmNZpAACAGuQ5lQbbBigBsiIAUKIy3tW4VNGdMEAIxjrO5jn6d/6eoZ28H6jPBGBdAgAAUJFaRv+QB9+gCgElQD68BgAAaF+Lw2st9/p3H9UTyGxd1C/HKwEohAYAACiRrX9EbYASIBMaAACgTSNPq7b+bRj1l6YEoHMaAACgSHVNmVHP/eG0AUqAHAgAAEA7GsdTo381bxbk7YDokAAAAHTK6J9SIaAESJ7XAAAAYzY4jNb1Ub6x3+vfhnV/1V4JQCc0AABAO2z9E24DlABpEwDoyIx5kW0R+hb2pPTjANTFm3tG/fv3SoDMuQUIqFN3d3fdpwBEIMMbfmrn+pwwAQAASHn0nzGvV8HbyCsBciYAADWzZAKaMvrXzvU5VV4DAACEpfO7fcz9rfBKgGxpAID6WTIBA2z9Q+P6nCQNAABQP1v/WigB8qQBAIJgyQTZsvUPnOtzejQAAEA9bP1DoATIkAYACIUlE+TD1j8urs+J0QAAANWx9Q+QEiA3GgAgIJZMkDBb/6i5PqdEAwAAlMvWP3xKgKxoAICwWDJBSjrf+pv+w+H6nAwNAABQvELWyUb/KikB8qEBAIJjyQRRK2rrb/oPkOtzGjQAAEAxbP1jpwTIhAYACJElE8TF1j8frs8J0AAAAO2z9U+MEiAHGgAgUJZMEDhb/2y5PsdOAwAAjI2tf9qUAMnTAADhsmSC0Nj6M8D1OWoaAABgdLb+WVECpE0DAATNkglqZ+tPU67P8dIAAHXavnfGPT19dZ8F0Jytf86UAAnTAAChs2SC6tn60wrX50hpAICaKQEgKLb+DFICpEoDAETAkgkqYOtPG1yfY6QBAOqnBIB62fozHCVAkjQAQBwsmaAMtv50zvU5OhoAIAhKAKiYrT8tUgKkRwMARMOSCQph60/hXJ/jogEAQqEEgLLZ+tMeJUBiNABATCyZoD22/pTN9TkiGgAgIEoAKJytP4VQAqREAwBExpIJWmTrT8Vcn2OhAQDCogSAztn6UwYlQDI0AEB8LJlgOLb+1Mv1OQoaACA4SgBog60/FVACpEEDAETJkgkG2foTFNfn8GkAgBApAaAVtv5UTwmQAA0AECtLJnJm60/IXJ8DpwEAAqUEgKZs/amdEiB2GgAgYpZMZMXWn4i4PodMAwCESwkAA2z9CY0SIGoaACBulkykzdafeLk+B0sDAARNCUC2bP0JnBIgXhoAIHqWTKTH9E8aXJ/DJAAAodu+d0bdpwCRcc8P1Vgw31+zKAkAQAosmWCA0Z/QuD4HSAAAIqAEgFEZ/amFEiBGAgCQCEsmsmX0J3Cuz6ERAIA4KAGgkdGfECgBoiMAAOmwZCIfRn/i4vocFJ8DELS+hd5et1J+4YHzmQDgzT1L4v3syYoGAEiKJRMJs/Unaq7P4dAAADFRApAncz9QIA0AkBpLJlJi609KXJ8DoQEAIqMEIBPmfqAkGgAgQZZMRM3Wn4S5PodAAwDERwlAqsz9QAU0AECaLJmIi60/+XB9rp0GAIiSEoBkmPuBimkAgGRZMhE4W3+y5fpcLw1AzbbvnVH9kxayN63xf7oLFixI6Y+DtikBiJrRPyjl/csCARIA8mL0Jzfd3d3+2gDAugSAXBj9Bx5B55gYJQAAjJUAkD6jvwVw5pQAALAuASBlRn9jXw6UAAAwJgJAmoz+Rn/WpQQAgEECQGqM/ua8DCkBAKB1AkA6jP5Gf0agBACAAQJACoz+BjuUAADQIgEgbkZ/oz+tUwIAgAAQMaO/SY4hlAAA0AoBID5Gf6M/bVMCAIAAEBOjv9GNkSkBAGBUAkAcjP5Gf4qiBAAgcwJA6Iz+ZjXGRAkAACMTAMJl9Df6UxIlAAA5EwBCZPQ3nNEJJQAAjEAACIvR3+hPNZQAAGRLAAiF0d80RoGUAAAwHAGgfkZ/oz+1UAIAkCcBoE5Gf+MX5VECAEBTAkA9jP5Gf0KgBAAgQwJA1Yz+5i0qowQAgEYCQHWM/kZ/AqQEACA3AkAVjP4GLOqiBACAIQSAchn9jf6ETwkAQFYEgLIY/U1UBEIJAADrEgCKZ/Q3+hMdJQAA+RAAimT0N0IRJiUAAAwSAIph9Df9EzslAACZEAA6ZfQ3+hMFJQAADBAA2mf0N/qTGCUAADkQANph9Df6EyMlAAAIAGNm9Df6kzYlAADJEwBaZfQ3+pMAJQAACACjM/ob/cmKEgCAtAkAIzH6G/1JjxIAgMwJAM0Z/Y3+5EwJAEDCBIChjP5Gf5KnBAAgZwLAi4oaCOqa/o3+UCAlAACpEgD+xOhv9Cc3SgAAspV7ADD6G/1hOEoAAJKUbwAw+hv9yZwSAIA85RgAjP5Gf2iREgCA9OQVAIz+Rn9YlxIAgAzlEgCM/kZ/aI8SAIDEpB8AjP5GfxiBEgCA3CQeAKL+VC+jPwRCCQBAShIPAB0y+kMOlAAAZEUAaM7oD6xLCQBAMgSAoYz+kCElAAD5EABeZPQHRqAEACANAsCfGP0BJQAAmcg9ABj9gdYpAQBIQL4BwOhPIwtgSEbfwp66TwEgUDkGAKM/0DYlAACxyysAGP0BAMhcLgHA6A8URQkAQNTSDwBGfwAAyCIAGP2BkigBAIhXmgHA6A8AAFkEAKM/UA0lAACRSicAGP0BACCLAGD0B2qhBAAgRtEHgFqmf6N/vPzaIRlfmtFb/ZP+Y18BHzDsQgTUK/oAUDGjP0CejP5AMgSAVhn9AfJk9AcSIwCMzugPkCejP5AkAWAkRn+APBn9gYQJAM0Z/QHyZPQHkicADGX0B8iT0R/IhADwIqM/QJ6M/kBWBIA/MfoD5MnoD2Qo9wBg9AfIk9EfyFa+AcDoD5Anoz+QuRwDgNEfIE9Gf4DsAoDRHyBPRn+A7AKA0R8gT0Z/gOwCgNEfIE9Gf4DsAoDRHyBPRn+A7AKA0R8gT0Z/gOwCgNEfIE9Gf4DsAoDRHyBPRn+A7AKA0R8gT0Z/gOwCgNEfIE9Gf4DsAoDRHyBPRn+A7AKA0R8gT0Z/gOwCgNEfIE9Gf4DsAoDRHyBPRn+A7AKA0R8gT0Z/gOwCgNEfIE9Gf4DsAoDRHyBPRn+A7AKA0R8gT0Z/gOwCgNEfIE9Gf4DsAoDRHyBPRn+A7AJAUVdtV3+ADEd/13+AmAKA0R8gT0Z/gOwCgNEfIE9Gf4DsAoDRHyBPRn+A7AKA0R8gT0Z/gOwCgNEfIE9Gf4DsAoDRHyBPRn+A7AKA0R8gT0Z/gOwCgNEfIE9Gf4DsAoDRHyBPRn+A7AKA0R8gT0Z/gOwCgNEfIE9Gf4DsAoDRHyBPRn+A7AKA0R8gT0Z/gOwCgNEfIE9Gf4DsAoDRHyBPRn+AHANAIVdtl36APKd/13+ALD4JeF0u/QB5cv0HyC4AuPQD5Mn1HyC7AODSD5An13+A7AKASz9Anlz/AbILAC79AHly/QfILgC49APkyfUfILsA4NIPkCfXf4DsAoBLP0CeXP8BsgsALv0AeXL9B8guALj0A+TJ9R8guwDg0g+QJ9d/gOwCgEs/QJ5c/wGyCwAu/QB5cv0HyC4AuPQD5Mn1HyC7AODSD5An13+Arpz8f/d28xgrHGSqAAAAAElFTkSuQmCC"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_382
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is Stack the original shape on top of the {'layer1': 'RpRpRpRp'}.\nthe 3th action is Cut the right side of the shape\nthe 4th action is Stack the original shape on top of the {'layer1': 'WbWbWbWb'}.\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is Stack the original shape on top of the {'layer1': 'RgRgRgRg'}.\nthe 7th action is Stack the original shape on top of the {'layer1': 'CgCgCgCg'}.\nthe 8th action is Colorize the top layer of the original shape with the color white.\nthe 9th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_313
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is Colorize the top layer of the original shape with the color purple.\nthe 3th action is Cut the right side of the shape\nthe 4th action is Cut the right side of the shape\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'CpCpCpCp'}.\nthe 8th action is rotate the shape clockwise 90 degrees\nthe 9th action is Stack the original shape on top of the {'layer1': 'WgWgWgWg'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABAAAAATICAIAAAANxCANAABgfElEQVR4nO3de7yldV0v8JlhYBiG23CJ4XZERxLGo6BU6GCZL8LkruYe0Ox0PJqWL6KyrLEytFdH5+Sp1LQss9CSgb1BAsFLIpgGEmYokFcGb6Bc1OE2wAzCPq/cvTb77LX22mut5/b7/b7v91/w7Jm1ntlrPd/n+/l9n2etpdPT00sAAIAYlnW9AwAAQHsEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgECWd70D0Kp77733gAMOeOihh/r+9BWveMW73/3u1ncKgErOP//8kf78sh9avnz5ihUrdtttt7333nv//fc/4IADdtppp8b2ERKydHp6uut9gPb87d/+7ctf/vKFfrrPPvvcfvvtO++8c7s7BUAlS5curf4gu+yyy3//7//96U9/+o/92I+deuqpBx10UB27BikSAIjl+OOPv/LKKwf8gcsuu+zkk09ucY8ASCIAzHvA44477n/+z//5i7/4i8uXu1yC0rgHgEBuu+22T3ziE/XOkQEoz/T09L/8y7+84hWvOPLIIycnJ7veHaiZAEAgmzdvfvTRRwf/mUsuuWShOwQAiObmm28+44wzXvnKV+7YsaPrfYHaCAAE8g//8A/ztqxevXrelvvuu+/yyy9vcacASN273/3u5z3veQ8//HDXOwL1EACI4j/+4z8+//nPz9v4lre8pffizgsuuKDF/QKgEdMDPfLIIzt27Ljnnnu+8Y1vfPKTn/zzP//zF73oRbvttttCj3bVVVedffbZ7f4LoCluAiaK173udZs2bZq7Zc8997zzzjtPOumkebcFr1y58s4779x9991b30cAarsJeIwO5/7773/rW9/6x3/8x/fdd1/fP/DRj370uc997lj7CAkxASCE6enpzZs3z9v4/Oc/f8WKFS984QvnbX/wwQcvvfTSFvcOgCTsvvvuv//7v3/ttdcedthhff/AG9/4xtZ3CuonABDCpz71qW984xvzNp5xxhkzMaB36chnAQGEtW7dussvv7zv5UDXXHPNv/3bv3WxU1AnAYAQ3v/+98/bss8++5xwwglLliw5+OCDf+InfmLeTz/60Y/efffdLe4gAAlZt27d7/zO7/T90RVXXNH67kDNBADKt2PHjqmpqXkbX/jCF85+4+8LXvCC3r/ygQ98oK0dBCA5r371q3faaafe7VdddVUXuwN1EgAo34c+9KGtW7f2vf5nRu9tAK4CAghuv/32O/roo3u3915QCtkRAIj48f/777//c57znNn/Pfzww5/85CfP+zNXXnnlXXfd1coOApCipzzlKb0bv/vd73axL1AnAYDC3XPPPb1f7PWiF71o3mC3dwjwyCOPXHjhhc3vIACJ2nfffXs33nPPPV3sC9RJAKBwF1544UMPPTRv45lnnjlvi6uAABjmmwT23HPPLvYF6iQAEO76n4MOOuhZz3rWvI1HH3304x//+Hkb/+Vf/uW2225reAcBSFTfj4Pbf//9u9gXqJMAQMluvfXWT37yk/M2TkxMLFvW553f+1lAjz766OTkZJM7CEC6vvzlL/duPOaYY7rYF6iTAEDJzjvvvEcffXTR638WCgCuAgIIa/v27ddff33v9p/6qZ/qYnegTkv7Xt8GZTjqqKNuuOGGuVse97jHfe1rX+v96t+Z9f6DDjrojjvumLf9lltu6b06CIB09K3qFTuc97///S996Uvnbdxtt91uu+22vffeu8ojQ+dMACjWTTfdNK/7X7JkyYYNG/qeJ/7zYFi27PTTT+/dfsEFFzSzgwAkaseOHW9605t6t7/yla/U/VMAAYBi9d7+O+D6nxk+CwiAJUuWvOY1r/nCF74wb+Ohhx76h3/4hx3tEdTJJUCUaXp6+rDDDvvmN785d+MTn/jEr371qwP+1sMPP/wjP/IjvR/78MUvfvGII45oZk8BSOgSoG3btv36r//63/zN38zbvueee37iE5942tOeNu4+QkJMACjTJz/5yXnd/5IlS84444zBf2vnnXc++eSTe7cbAgAUb+vWrW9/+9uf/OQn93b/BxxwwIc//GHdP8UwAaBMv/RLv9RbwW+44Ya+3+s+1wc+8IGf+7mfm7fxiCOO+OIXv1j3PgLQ4ARg8+bNA/7K9PT09u3bH3jggdtvv/3WW2+9/vrrb7jhht4PjluyZMkJJ5xw7rnnHnTQQbXuMnRJAKBA27dvX7NmzbwreY488sjeCzp7PfDAA/vtt9+DDz44b/v1119/9NFH172nANRgoU93qOhpT3vaG9/4xlNPPbWJB4cOuQSIAl1++eW91/EPvv131m677fazP/uzvdtdBQQQx6pVq/7yL//ys5/9rO6fIgkAFOj9739/78ZFbwAY/I1gPgwUII5t27b9yq/8ysEHH3zWWWe5BJTyuASI0tx9991r1qzZvn373I1HH3103y907Gvr1q0/8iM/8oMf/GDe9muvvfbYY4+tb08BSPoSoFknnnji2972tsMPP7zRZ4HWmABQmgsvvHBe9z/S8v+SJUtWr1790z/9073bXQUEENOHP/zhpz71qf/3//7frncE6rG8pseBpL//a+nSpSO17/vvv3/vxsnJyT/5kz9ZtkxsBsjAotc4PProo9u2bbvvvvtuu+22b33rW5/73Oeuu+66q666aseOHb1/+KGHHnrta1/79a9//e1vf7sTAblzCRBF+da3vvW4xz2uuXf1Jz7xiWc/+9kNPTgAnX8R2Pe+971zzz33j/7oj3o/TGLGOeec84Y3vGGMR4Z0iLAU5bzzzms007oKCKBs++6772/+5m9+5Stfec5zntP3D/zRH/3Rpz/96db3C+pkAkBRnvrUp954443NPf7+++//7W9/e/ly184BlDkBmLV9+/aTTz754x//eO+PTjjhhH/6p3+q8uDQLRMAynHDDTc02v0vWbLkrrvuuvLKKxt9CgBSsGLFive973377LNP748+9rGPDfPNkpAsAYDCb/+tnauAAII46KCDzjrrrL4/+tCHPtT67kBtBAAKMT09vXnz5nkbV61a9cADD0yP67zzzut9oosvvrjvB0QAUJ5XvvKVfbdfc801re8L1EYAoBCf+MQnbr311nkbTznllJUrV479mKeeemrvX7/77rs/8pGPjP2YAGTk4IMPXrt2be92lwCRNQGAQrz//e/v3TgxMVHlMXffffcTTzyxd7urgADiOOaYY3o3fv/73+9iX6AeAgAl2L59+0UXXTRv46pVq/q27yPZsGFD78ZLL730gQceqPjIAGRh33337d240LcEQBYEAEpw2WWX9dbik08+ebfddqv4yKecckrvg2zbtu2yyy6r+MgAZGHPPffs3ejLgMmaty/Ffv5Pxet/Zqxateqkk07q3X7BBRdUf3AA0nfvvfcOmQogFwIA2du6dWvvx7HttttufRv3MZxxxhm9Gz/0oQ/dd999tTw+ACm76667ejcecsghXewL1EMAIHtTU1O9n8tZy/U/sw+1atWqeRsfeuihf/zHf6zl8QFI2XXXXde78cgjj+xiX6AeAgDZa+Lzf+ZauXLlKaec0rvdZwEBFO8rX/nKN7/5zd7txx57bBe7A/UQAMjbN7/5zU996lPNXf8z4LOAPvaxj/kYOICy/dmf/Vnf7SeffHLr+wK1EQDI23nnnTc9PT1v40knndR70U4VJ5100u677z5v48MPP9z72aMAFOP666//u7/7u97tz3rWs/p+OxjkQgAgb01f/zNj1113PfXUU3u3uwoIoFS33Xbbi170ou3bt/f+6Hd+53e62COojQBAxj73uc/ddNNN8zauXLmyicls36uA/vmf//mOO+6o/bkA6Na111577LHH3nLLLb0/et7zntf3xjDIiABAacv/J554Yr3X/8w+bO+nPj/yyCNTU1O1PxcAXbnuuuv+x//4H+vXr7/tttt6f7pmzZq+FwVBXpZ3vQMwpkcffXTz5s0tXP8zY8WKFaeddlrvN46df/75Z511VhPPCEAVw1yl+YMf/GD79u333nvvd7/73S996Uuf/exnv/GNbyz0h/fZZ5+PfOQja9asqXtPoW1Le2+ghCxceeWVxx9//LyNu+6661133dV7w24tPvjBD5522mnzNi5duvQb3/jGoYce2sQzAjCMpUuXNv0U69atu/TSS937SxlcAkSuehfjZy7Uaaj7X7Jkyc/+7M/utdde8zZOT09fcMEFDT0jACl46Utfeu211+r+KYYAQJYeeuihD3zgA61d/zNjl112Of3003u3+ywggFL92I/92NVXX/33f//3e+yxR9f7ArURAMjSBz/4wXvuuWfexl133bXpT2bo+1lAn/3sZ2+++eZGnxeANu2+++4ve9nLrr766s985jPr16/venegZm4CJksrV64855xz5m38b//tvzW9QvPc5z73DW94Q++dM71pBIDELV26dPny5StWrNh9991Xr159wAEHPO5xj3v605++fv36o48+evlyPRLFchMwAAAE4hIgAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACGTpxMRE1/sAqZiamup6F6A9ExMT3vMAAS2dOQd0vRuQBM0QQcwr+975AKG4BAggkIkfmtf3z90IQIgAYO0HoHiLdvliAEAQJgAAhRvQ2fcuAIkBAFECgCEAQHnG7ubFAICCmQAAFGj4Dn7AApAYAFB4ADAEAChA7V27GABQGBMAgEKM3akPswAkBgCUGQAMAQBy1Fp3LgYAFGD5qH9h7eTqZvYE2rBlw9audwHqVFc7PjU1NfxDzfxJa0YAhVwCtGhB1z8BpKDzxfjOdwCA8bgHACAzDXXe463oiwEAJQQAQwCANCXbbSe7YwD0MgEAyEA7HXbFy/rFAICMA4AhAEAisuuqs9thgGhMAACK7aTH+Ny2AQtAU5snh38cMQAgv48BXfQj4bZs2OojQQGaUL11bqI+T7x4w0wGmHjxhlH/IT4zFCDj7wEAoOzWf9EFoFFjgK8OAMjmEiB3AgDkdcFP04PZuU3/1ObJkS4Kcl0QQCJMAAA6lsKq/9hfDGwaAFDaTcCGAADBV/3n6dvrmwYAZMQEAKADCa76jz0EeOyvmAYAlPExoIYAAMFX/ecZ3OKbBgAkzgQAoCXpr/pXHwI89ndNAwCy/iIwQwCA4Kv+8wzZ2ZsGACTIBACgQdmt+tc4BHjsQUwDALKbABgCAIyqvFX/eUZq6E0DANJhAgBQs9xX/ZsYAjz2aKYBALlMAAwBABZV/Kp/xSHALNMAgA6ZAADUoLBV/0aHAI89rGkAQOITAEMAgF7RVv3rGgLMMg0AaJkJAMCYyl71b2cI8NjjmwYApDkBMAQAsOpf+xBglmkAQAtMAABGEGrVv+UhwGNPZBoAkNQEwBAAiMmqfztDgFmmAQANMQEAWETkVf+uhgCPPaNpAEAKEwBDACAIq/7dDgFmmQYA1MgEAKAPq/7pDAEee2rTAIAOJwCGAECprPqnOQSYZRoAUJEJAMB/seqf/hDgsX0wDQBofwJgCAAUw6p/XkOAWaYBAGMwAQBCs+qf7xBglmkAQHsTAEMAIF9W/csYAswyDQAYkgkAEI5V//KGALNMAwAanwAYAgAZsepf9hBglmkAQLMBACB9Wv8mJL5qPmoGEAOAIOoJAIYAQLK0/jGHAGOPAsQAoHjuAQCK5Vr/sHcCVL8xwL0BQMGW1vhYi54DnErp3OBhlDN9MbT+w7zn63rDD/htj7H6nuxoQn0AimECABRF69++LIYAFacBBgJASeq8CdidAECHXOufoETuBKjr3gC3BwBlMAEAsmfVv3N5DQFmmQYAMdX8MaCGAECbrPqnL9khwCzTACAaEwAgS1b9U5PpEGCWaQAQR/1fBGYIADTKqn920h8CzDINACIwAQCyYdU/cbkPAWaZBgBlq38CYAgA1M6qf+4yGgLMMg0ASmUCACTNqn9eihkCzDINAMrTyATAEACozqp/YXIcAswyDQBKYgIAJMeqf9bKGwLMMg0AytDUBMAQABiDVf+yZT0EmGUaAOTOBABIglX/khQ8BJhlGgDkq8EJgCEAMAyr/qGUMQSYZRoA5MgEgDLJllmw6l+wCEOAWaYBSan9jecFojxLUzgUncJJpMVX5Vuj9U/hSGn6DT/gVR5v1bzsEYf6M7yksqUXjhyZAJABy/nFqOW0rfUnZaYBBff6w++h15HEtTEBMAQgl3ZfyW6O1j/gBCDsEGCWaUB57f7Ywr6mpMkEgO5Z4C+b1p+wTAMid/yD/6URXlxS1tIEwBCALJp+FbleWv8UdDsBMASYZRoQsOkP+xKTPhMAojf9NEHrD/MEnwZo+of85eT+QpOL9iYAhgAx5dX0q7zVaf1T0/kEwBAg7DRA019RXi83eTEBoBF59f3UQusPQyp7GqDvr/03mfgrTo5anQAYAhQv975fkR2P1j9lKUwADAEiTAP0/S1I7UUnXyYAlNn3b1rdv6XYuHXMcy19af0h+DQgwb5/vPq/0N9K6sRhJkCuEwBDgJJ02/cPKNYDDK7jSurwtP65SGQCYAhQ2DSg276/ifo/3mN2Hg+cthiPCQAZ9P1j12WaoPWHsNOA9vv+9Ot/3z1sLRWYCZDNBMAQIF+ttf7NVXwTgG7P/Q7tyBMAQ4CspwGttf5d1f9Gk0ZrecBZjCGZAJBE35/+Gk9wWn+IOQ1ooe+PUP/n/RubywMGAiQ9ATAEyEWjrX8nRd8EYFRa/9wlNQEwBMhoGtBo659g/e8qhzQ6HHBSYyEmALTa+kdY6SmG1h9iTgMaav3V/0V/LbWHgUQ+KooEdTYBMARIU/F9vwnAMLT+JUltAmAI0NU0YNFXvPi+P80JQJtjAec4ZpkA0FTrn1QxZUhafyh1GjBgPbj21l/9T3MsYCBAEhMAQ4AiW//E674JwEK0/qVKcAJgCJDONKDe1j/r+p/4ztc+Foh8vsMEILoaW//0SycL0fpD2GlALdT/dsz+nmtJAqYBwXU8ATAE6ErY1t8EYC6tfwRpTgAMAZKaBoytpPqf17+l3oFAtHMfJgAR1dX6Z1crmUvrD4WpMg0Ylfpf2EDANCCg7icAhgCt0fqbAGj9A0p2AmAI0JzmYkDB9T/rf1qNA4HOywLtMAGIonr3n3txROsPQdQ+DVD/4wwEJiYmZIAIkpgAGAI0Sus/V8wJgNY/spQnAIYATaueAeLU/5L+pbUMBFKoDzTHBKBkWn+0/hCT1j+4mZevSgxwY0DZUpkAGAIk1foXXPfjTAC0/mQxATAESK31D1v/C/6HVx8IJFIrqJEJQIGqdP9lV8AgtP4QVpXuX/0vWMWBgBsDypPQBMAQoDqtf/AJgNafHCcAhgC10PovKvIEoK5pQDpFg4pMAMoxdvcfp+oVTOsPkY3d/av/AVWZBhgFFCOtCYAhwHi0/pEnAFp/CpgAGAKMTes/PBOAGqcBSVUPxrBsnL9ESnT/YU38UJVHWDu5WvcP+dL9U9HY74Tqa090K7kJgCHA8LT+YScAVv0pbwJgCDASrf8YTAAGMAqIxj0Asbr/4AWuAFp/YLzuX/2niRsD3BWQqRQnAIYAg2n9Y04AtP4UPwEwBFiU1r8KE4BGpwEJ1hMGcA9AZnT/AbnWH9D905rx3jPuCshLogFg0RxZ8ZtuMzXGv3rT6knVP19af6IZUPwrfsFt7sb456v/jG28N48MkBH3AJTc+jezL7TBBT9Alda/mX0hljFuDJg5ebkcKH2JTgAMAebS/Ydi1Z/gDAHm0v3TOaOAIpkAlNb9K/35suoPVOn+1X+SGgWYA6Qs3QmAIcCWDVt1/0FY9Ye5DAEmXrxB909qRn2PVT+10RwTgERp/YOw6g/Mo/UnWUYBxUh6AhB2CKD7j8CqPwwQdgig+6fIUUBj+0KhASAg3X/xtP5AX7p/ciED5C7RbwKO+cXAWv/ivwnYBT+0L69vAg77xcBa/xb4JuAUvjY4/bIThAlAKnT/ZbPqDyxE90++jAIylUcAKP5OAN1/wbT+MLYIdwLo/smdDJAjnwKUWfev9GfEBT9Ajd2/+k8xnw7ko4E6l8cEoOAhgO6/SFb9oS4FDwF0/xRmpHepOUC3sgkARdL9l0frDwxD90+RZIBc5BQAChsCDL+3m1ZPqv7p0/pDQ8obAgy/2+o/2RnpTSsDdCWnAFCSkbr/hveFqrT+QEPdf8P7Ak2RARKXWQAoYwig+y+G1h/aUcwQQPdPHDJAynwKUKtc9F8Mn/ADjMRF/wS0afXkkB8NNHNW9dFArclsApD1EED3Xwar/tCJrIcAun/CcltwmvILAJnS/RdA6w+MQfdPcDJAgrIMANkNAXT/udP6QwpyHALo/kEGSJB7ABrnlt+sudYfGJtbfmG8bwv2VcFNy3ICkOMQYFGqf2qs+kOCchwCLEr9Jw7v9kTkGgByMWQOcTwkResPVDdkIFH/iWbI97wLgRqVcQBIfwig+8+O1h/Sl8UQQPcPA8gAncs4ACRO9x+N1h+YofuHRckA3co7ACQ7BND9h6L1h5alPATQ/cOQZIAO5R0A0qT7j0PrD8yl+4eRyABdyT4ApDYE0P0HofWHbiU4BND9wxhkgE5kHwCSovuPQOsP9NL9w9hkgPaVEAASGQLo/oun9YdctDwE0P1DRTJAy0oIACnQ/ZdN6w8JSuSLQnX/UAsZoE2FBIBEhgCUR+sPmer844AAklVIAOiW5f8iaf0h99WfFjKA5X+okSFAa8oJAF0NAXT/5dH6A8PQ/UPtZIB2lBMAOqH7L4zWH7LT1RBA9w8NkQFaUFQAaHkIoPsHiEn3D42SAZpWVABIkOoPUPydAH2p/1CFI6hRpQWA1oYAwzyO9y5AeYZJFOo/VDfMcWQIMJ7SAkA7dP8AMYcAun9okwzQkAIDQNNDAF8pABCT7xaANMkAoyowAKTA8g9AzDsB1H+ol2OqCWUGgOaGAC7+AYjJxT/QFRcC1a7MANAQ3T9AzCGA7h+6JQPUq9gAUPsQwKX/ADG59B9yIQNEDwCdsPwDEPNOAPUfmuYoq1HJAaDGIYCLfwBicvEPpMOFQHUpOQDURfcPEHMIoPuH1MgAtSg8ALT2xcAAAJCFwgNAdZb/AWIOASz/Q5oMAaorPwBUGQLo/gFi0v1DymSAisoPAI1S/QFifhyQ+g/dcgxWESIAjDcEcHsAQEw++B/KYAgQOgCMwcU/ADGHAC7+gVy4EGhsUQJA7R8HpPoDxKT+Qzocj+OJEgBG4uIfgJhDABf/QHkMAUIHgCGHAC7+AYjJxT+QIxcCjSFQAKiL6g8Q8+OA1H9Ik2NzVLECgC8GBqAvF/9A2QwB4gaA6kRMgJhDAPUfUuYIHUm4ALDoEACAaCz/QwSGAHEDQBXCJUDM1R/1H9LnOB1exAAw3mnAuwogJvUfijlaDQHiBgAAAnIJKCADhA4Ao54GLP8AxKT+Q14cs8MIGgAACMgQAFhiCBA5AAx/GhAlAWJS/yFHjtxFxQ0AAARkCAAsCT8ECB0AhjkNCJEAMan/kC/H72ChA8Ci4c+7B6A8Vn8gAh8JOkDoAAAAANHEDQCW/wFiUv8hCEOAhcQNAAAAEFDQAGD5ByAm9R9CMQToK2gAAACAmCIGAMs/ADGp/xCQIUCviAEAAADCEgDms/wDEJP6D6VydEcPAAGnPACo/8AAE8HqQ7gAAAAAkcUKAG7/AohJ/Yfg3AocNwAAAEBwgQKA5R+AmNR/wBAgaAAAAAAEgP9i+QcgJvUf4nC8xwoAcWY6AMyl/gPDm4hRMaIEAAAAIEoAcPsXQEzqPzDPJrcCBwkAAADADAHA8g9AUOo/xLQp/LFffgCIMMcBoJf6D4xnovTqUX4AAAAAZkUPAGZAADGp/xDZptgVoPAAUPwEB4C+1H+giomia0jhAWCw4OEPICz1H9gUuA6EDgAAABBNyQGg7NkNAAtR/4HqJsqtJCUHgMEiz30AIlP/geDVIG4AAACAgIoNAAVPbQAYQP0H6jJRaD0pNgAMFnbiAxCc+g/MFbMmBA0AAAAQU5kBoNR5DQCDqf9AvSZKrCplBgAAAKCviAEg5sVeAKj/QK+AlSFiAAAAgLAKDABFXqoFwKLUf6AJE8XVlgIDwGABpzwAqP/AAJuC1YdwAQAAACITAAAAIJDSAkB5F2kBMAz1H2jORFkVprQAMFi0C7wAmKH+A4NtilQlYgUAAAAITgAAAIBAigoAhV2eBcCQ1H+gaRMF1ZmiAsBgoS7tAmCW+g8MY1OYWhEoAAAAAAIAAAAEIgAAAEAg5QSAku7MAGB46j/QjolSqk05AWCwOHd1ADCX+g8Mb1OMihElAAAAAAIAAADEIgAAAEAgAgAAAASyLMJN2UHu5wAISP0H6rVpYN0o44OACgkAAADAMAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACKSEAOAz4ABiUv+BJmwq/ZNASwgAAADAkAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBAsg8AvgYSICb1H2jOpqK/DDj7AAAAAAxPAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhkee6fYzrYxq0but4FcrJlw9audwGoh/oPsJDlC/4EACAGiZFQXAIEAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABDIIl8EtnZy9ZKcv7p10+rJFveFEr7tJf33fJFfsTw1NdXWvhCF+k8v3/YFM3wTMNC9iYkJGQDoltBInMToEiCgceYqAJAOAQBIwsTERNe7AAAhCABAGwwBACARAgCQCkMAAGiBAAC0xBAAAFIgAAAJMQQAgKYJAEB7DAEAoHPLyu4nCv4AVyiVIQBDGvzdEeo/UMXGgTUk9++uyT4AAHkxBACAbgkAQHIMAQCgOQIA0DZDAADokAAApMgQAAAaIgAAHTAEAICuCABAogwBAKAJAgDQDUMAAOiEAACkyxAAAGonAACdMQQAgPaVEAB8GTAUzBCAAXwZMNCEjUV/DXAhAQDIlyEAALRMAABSZwgAADUSAICOGQIAQJsEACADhgAAUBcBAOieIQAAtEYAAPJgCAAAtSgkAPgkUMidIQDj8UmgQL02lv4ZoOUEACACQwAAqE4AAFJhCAAALRAAgJwYAgBARQIAkBBDAABoWpQA4D4wKIYhACNR/4HhbYxRMcoJABYOoQyOZUZVxodyAOmbKqXalBMAgDgMAQBgbAIAkBxDAABojgAAZMkQAADGEygABLmrA8pgCECN1H9gGBvD1IqiAoCOAUIxBKC8O/OAZE0VVGeKCgBASUR6AGiCAABkzBAAAEYVKwDEubQLymAIQF3Uf2CwjZGqRGkBQLsA0RgCUN7luUBqpsqqMKUFAKAwUj0A1EsAALJnCAAAwwsXAEJd4AVlMASgFuo/sJCNwepDgQFArwABGQJQ3kW6QCKmiqstBQYAoDyCPQDUJWIAiDblgSAMAViU+g/0ClgZIgYAIEeGAABQizIDgEYBYjIEoLxLdYFuTZVYVcoMAECRZHsAqC5oAAh4sRcEYQjAYOo/MFfMmlBsALBSCEVyaBNzXg90YqrQelJsAADCMgQAgAHiBoCYEx8ogCEAFan/QPBqUHIA0CVAWIYAwZU6tQfaNFVuJSk5AAClEu8BYGyhA0DYuQ9EYAjAAOo/sDFwHSg8AFgmhFI5ugk7uwdaMFV0DSk8ACwqcviD4hkCMID6D5FtjF0BogcAIF+GAAAwhvIDgBYBIjMEiKzsCT7QnKnSq0f5AWBRwWdAkDUJnyrUf4hpY/hjXwAACmcIAADhAsCia4SCIOTLEIAqc3z1H6LZuNhRX/z1P1ECABCcIQAAhAsA1gihYA5wgi/mAXWZilExogSARZkCQ9kMAViI+g9xON5nCABACQwBAGBIgQKAW4EhOEOAsNwKDLj9N2gAAMpmCAAAw4gVAAwBIDhDgLAMASA4y/9xAwBQNkMAAFhUuACgP4DgDAHCCrW8B4xkKlh9CBcAFmUKDFkT8hmb+g+lcnTPIwAA4RgCABBZxADgVmAomyEAC3ErMATk9t9eEQMAgCEAAGEFDQCGAFA2QwAWYggAoVj+7ytoAAAwBAAgprgBwBAAymYIwEIMASAIy/8LiRsAAAwBYvK6A8GFDgCGAFA2QwDGpv5D7iz/DxA6AAzDOQDKZjE4muFfcfUf8uX4HSx6ALBACGVzjAPQayrw8r8AMBQhEspmCBDHqK+1+g85cuQuSgCwQAiFc4wDMNdU7OV/AWBYoiSUzRAggvFeZfUf8uKYHYYA8J8sEELZHOMAzJgKv/wvADzGR4JCcIYAZavy+qr/kAsf/TkkAWAEzgGQL0MAqlD/IX2O0+EJAI/RH0BwhgAxX9mpzZNTmydb3B2gG5b/ZwkAoxEuIV9CPlWo/5AyR+hIBID/j/4AgjMECLj8P+8/gCJZ/p9LABiZiAn5EvKpQv2HNDk2RyUAjNMfeJ9BwQwB4pi36j/MEED9h9QMc1Ra/p9HAOjDGiEUzAEeyqhxzoVAUB7dfy8BYEwWgaBghgARjN3rq/+QDsfjeASA/lwIBAUzBAhivCDnQiDIhYt/xiYALEiLAJEZApRtcJfvQiAog+5/IQJAJRaBIFMSfvGajnDqP3TLMViFADCIC4EgMkOAUg2zwO9CIEiZi38qEgAWIQNAqQwBClZLeJMBIE26/+oEAIAFGQKUx/X9AALA4gwBoFSGAEWqMbYZAkBqLP/XQgAYigwAYRkCBF/+lwEgHbr/uggAdXIOgOwYAhSmq8Cm/kPTHGU1EgCGpUuAsAwBgl/977YByIXl/yEJACNwIRAUSbwvRnNRzYVA0C0X/9RLABiNDAAxGQLkrvoqvgwAXdH9104AaIRzAOTFEKAAiYQ09R/q5ZhqggAwMo0CxJRIf0mHF/G7GQDSZPl/VALAOFwIBOWR7bPWWjxzIRC0ycU/DREAxiQDQECGADmqfdleBoB26P6bIwA0yzkAMmIIkKk0g5n6D1U4gholADTeK3gHQ0nS7DVp+ar9IR9W/YfxDHnsWP4fmwBQiQwAhTEEyE5XkUwGgIbo/lsgAFQlA0A0hgC5aPpDe2QAqJ3uvx0CQA1kACiJIUAZYaydj+yUAaBGuv/WCAAAIzMEACBfAkA9DAGgJIYAWeh8+X+k51L/YTDL/20SAGojA0AohgDMkgGgIt1/ywSAOskAUAxDgMQlsvw/6pOq/9BL998+AaBmMgDEYQjAXDIAjEH33wkBoH4yAJTBECBZqS3/j/rs6j/M0P13RQBohAwAQRgCMI8MAEPS/XdIAGiKDAAFMARIULLL/7NkAFiU7r9bAkCDZACIwBCAXjIADKD775wA0CwZAHJnCJCU9Jf/Z8kA0JfuPwUCQCqcAyBfhgBUof4Th3d7IgSAhJYPN27d4MCABBkCJCKj5f9R90r9p3gjvckt/zdNAEiue3AOgBwZAlA9maj/lGqk97buvwUCQEtkAMiaIUDnslv+nyUDEJzuP0ECQHtkACibIQALkQEIS/efJgGgVWsnV490S0DDuwOMwBCgQ/ku/8+a2jw50i0BDe8OtGGki/51/20SADogA0CpDAEYTAYgDrf8pkwA6IYMADkyBOhEAcv/c8kARKD7T5wA0BkfDwpFMgRgUT4elIL5uM8sCABdclswZMcQoGWFLf/PclswRXLLby4EgI7JAFAeQwCGIQNQGN1/RgSA7o2aAZwGoFuGAK0pdfl/7Ayg/pOmUd+cuv/OCQBZ9hPOAZA4QwCGNGqSUf9JzajvSd1/CgSAVMgAkBFDgBYUv/w/SwYgX7r/TC3vegeY31Js2bB1pKNu0+qiToRQjImJCac6RsoAEy8etpdS/+mc1j9rJgDJMQqALBgCNCrO8v9cRgHkQvefOwEgRTIAlMGdAIxKBiB9uv8CCADlZACnAWiZIUBDYi7/V8kA6j/tGOPNpvtPkwCQrrWTq40CIHeGAIxhavOkUQCpGaP11/0nSwBInVEApMwQoE0Rlv/nMgogERb+yyMAlNlhOAdAOgwBRuLXVTHzqP/Ua4x3lO4/fT4GtMxPCPUhcdCatZOrRzo2GU+05f+xPyFU/acuWv+CmQCUPwqwGgSds6o9JL+oekcB6j/jGe/No/vPiAAQ4oJj5wBolDsBmhZ2+b/6L0H9p533jO4/Ly4BCnE5kIkwdM4XAy/K8n8TlwOp/wxP6x+HCUC4UYDVIGiCIUBzLP/XNQpQ/6n97aH7z5QJQLhRgNUg6IohwACW/1sYBaj/9Bo7FqpmWTMBiLvuaCkI6mUI0ATL/038ctR/Zuj+wzIBKIFRAOTCEKAvy/9jMwpgPFr/4EwAylFlFGA1CGphCFAvy/8tjALU/2iqvOi6/2KYABRl7FGA1SBojSHAPJb/ux0FqP9xVAl7qlZhTAAKVGUN0moQVGQIUBfL/y3/0tT/glV8cXX/5TEBoI/ZMmFBCJpgCDDL8n9SowD1vzDVE51KVSoBoDTjXf+zEHNhGMPaydX1HokBWf6vaGrz5NgZYIb6nzWtP4MJAOVoruFwGoDaGQJY/m9OxdZ/LvU/O1p/hiEAlKCdtUZzYRieIUAVlv9TaP3nUv/TV9f9G7r/IASAvHXSYVgQgloEHwJY/s+i9Z9H/U+Q1p8xCAC56nxx0YIQDGYIMB7L/2m2/nOp/ymo8SObtP4BCQD5qaWlmDnaa1mBsyAEYws7BLD8n2nrP4/63wmtP9UJAEFb/4ZigDMBzGUIMCrL/621/up/dur9lgatf3ACQNDWv3d7XQtyzgQwkoBDAMv/KbT+c/9b/U9Z7d/OFq3g0JcAELr17/0zNZ6Y59YsJwPCMgQYnuX/Nlv/3u3qfzoa+kpmrT+zBIB0tdb69/3z9S7RWRaCAUINASz/t9/6D/nuUv87p++nNQJAijpp/fv+9dpP1ZaFCMgQYBiW/zts/fv+LfU/66Z/htafhQgAaUmh9e99qIZW7JwMINoQwPJ/4q1/7yOo/9k1/TMi1BOqEABSkVrr3/dhmzt5z6uGAc8HlM0QYDDL/0m1/n0fTf1PvOOfoe9nSAJA91Ju/fs+SwtreBHOBxBtCGD5P6/Wv++Dq/+pdfyzyq4e1E4A6FJGrX/fZ2ztdN63kmZ6ViAsQ4CFWP5PvPXv+0Tqf4e9/lz6fsYjAHQj09Z/oR3oZGFvcM1N6vQAQyp4CGD5P/fWP3L977bF76vUQkFrlg4+dNdOrm5vX2Ioo/Uv+BzvPU+3FSDZo7uh4hB5+T/T1r/g+p++1F508mUC0J6yW/8U1oSgAEUOARSEslv/Gep/c9J8xcmaANCGCK3/PM4E0Jc7AYIv/xfZ+s+j/tcli5ebTAkAzQrY+g/YeScDCDgEcODHaf3nUf+DvNDkSABoita/l5MBGAIEXP4P2Pr3Uv+Lf4nJiwBQP63/MJwMIMIQIPjRrfXvS/0v+MUlFwJAnbT+tfyTw54PiMMQoPjlf63/kOLU/zivKVkQAOqh9a9R7++h4FMCFDwEiHnkav2rKKb+B38dSZ8AUJXWvwV9fz+ZnhVgRuQhQKnL/1r/mPXfC0eOBIDxaf27NfhXl9TpAQIOAUIdg1r/suu/F4jyCADj0Pqnb6Ffr6++Jh0xhwCFLf9r/RPktwqLEgBGo/UH2pTpECDC8r/WH8iXADAsrT9Qu2hDgDKW/7X+QO4EgMVp/YEOZTcEKHj5X+sPlEEAGETrDzQtzhAg6+V/rT9QEgGgP60/kI6MhgDlLf9r/YHyCADzaf2BlkUYAuS4/K/1B0olADxG6w8kK4shQDHL/1p/oGwCwH/S+gPdKnsIkNHyv9YfiCB6AND6A7lIfAiQ+/K/1h+II24A0PoDSSl1CJD+8r/WH4gmYgDQ+gOZSnwIkB2tPxBTrACg9QdSlu8QYKHrf5Jd/tf6A5FFCQBaf6AMhgAVaf0Byg8AWn8gIzkOAXJZ/tf6A5QfALT+QJEMAdps/f2qgfKUGQC0/kC+8hoCJL78r/UHKD8AaP2BCAwBGu3+/W6BspUTALT+QDFyGQIku/yv9QcoPABo/YGADAH60voDFB4AtP5AqdIfAqS2/K/1Byg8AGj9AQwBZmj9AQoPAFp/IIiUhwCJLP9r/QEKDwBaf4B5wg4BtP4AhQcArT8QU5pDgG6X/7X+AIUHAK0/wGBxhgBaf4DCA4DWHyDBIUAny/9af4DCA4DWH2AkBQ8BtP4AhQcArT9AykOANpf/tf4AhQcArT9AFSUNAbT+AIUHAK0/QBZDgBaW/7X+AIUHgLpOZuo+QO5DAK0/QOEBQOsPkNcQoLnlf60/QOEBQOsP0Jy8hgBaf4DCA4DWHyDTIUDty/9af4DCA4DWH6A1iQ8BtP4AhQcArT9A7kOAupb/tf4AhQcArT9AV1IbAmj9AQoPAFp/gGKGABWX/7X+AIUHAK0/QCI6HwJo/QEKDwBaf4DyhgDjLf9r/QEKDwBaf4A0tT8E0PoDFB4AtP4ABQ8BRlr+1/oDFB4AtP4AWWhhCKD1Byg8AGj9ASIMAYZZ/tf6AxQeALT+ADlqYgig9QcoPABo/QFCDQEGLP9r/QHKDwC1nFfUfYAChgBjdP/qP0CIbwKeS+kHyGsIsNDy/6jUf4BwAUDpB4j5nQDqP0C4AKD0A2Q6BKi4/K/+A4QLAEo/QMwhgPoPEC4AKP0AuQ8Bxlv+V/8BwgUApR8g5hBA/QcIFwCUfsrT0JeqQvpGWv5X/wHCBQClHyDmEED9BwgXAJR+gJjL/+o/QLgAoPQDxBwCqP8A4QKA0g8Qc/lf/QcIFwCUfoCYQwD1HyBcAFD6AWIu/6v/AOECgNIPEHMIoP4DhAsASj9AzOV/9R8glKXT09Nd7wMAANCSZW09EQAA0D0BAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAJZ3vUOQHu2b99+7bXXXn311V/60pduvvnmW2+99f7779+2bdujjz66cuXKVatWHXjggQcffPCRRx551FFHHXfccYcddljXuwwAULOl09PTdT8mpGX79u0f/OAH3/ve915xxRUPPfTQ8H/x8MMPf9GLXvSyl73s8MMPb3IHARjZ+eefP9KfX7p06bJly3baaacVK1asXLlyzz333HfffdesWbNy5crG9hESJQBQsgceeOCd73znW97ylrvuuqvK45x22mlveMMbnva0p9W3awBUsnTp0loe55BDDlm3bt3Tn/70Zz/72c961rN23333Wh4WUiYAUKzzzz//13/91++4445aHm3ZsmWvfvWr3/zmNzs3AJQUAOZasWLF8573vJe85CUveMELdt5559ofHxIhAFCg733vey9/+csvueSS2h/5SU960iWXXPKkJz2p9kcGoPMAMOvggw8+++yzf/VXf9UFQhRJAKA0X/jCF0477bQtW7YM+DM/+qM/eswxxxx55JH77bffHnvs8eCDD37/+9/funXrjTfe+OlPf3rr1q0D/u5ee+310Y9+9Nhjj21g3wFIIgDMOPTQQ//4j//4zDPPbPqJoGUCAEW55pprTjzxxHvvvbfvTw855JBf/uVffslLXvL4xz9+oUeYnp6+8cYb//qv//q9733v/fff3/fP7LXXXldeeeXTn/70+nYcgOQCwIyJiYl3vetd++yzTztPBy0QACjHv/3bvx1//PF9u/8999zz9a9//a/92q8Nf03nPffcc84557z97W/ve4wccsgh11133YEHHlh5rwGoLQAM7mp+8IMfPPLIIw888MD9999/1113ff3rX/+P//iPz3zmM//8z/+80MrRjCc84QmXX375EUccUceOQ/cEAApxyy23/PiP//j3v//93h/9+I//+OTk5Hgf6n/FFVe89KUv7Xsn8QknnPBP//RPY+0sAB0EgIXs2LHj4x//+F/91V998IMffPTRR/v+mdWrV3/4wx92/SdlEAAowQMPPLB+/frPf/7zvT86/fTTJycnd9lll7Ef/Kabbnr2s5/dN1q8+93vfsUrXjH2IwOQQgCYdeONN/7Wb/3WQos7e++995VXXukjoSmAAEAJXv7yl//t3/5t7/bTTjvtoosuWr686jdef+Yzn/nJn/zJ7du3z9u+Zs2am2++edWqVRUfH4AUAsCMv/qrvzr77LN37NjR+6MDDzzws5/9rOs/yd2yrncAqrriiiv6dv9HHXXUeeedV737n7mI6PWvf33v9ttvv/1d73pX9ccHIB2vetWrPv7xj++11169P/rOd76zYcOGRx55pIv9gtqYAJC37du3H3nkkV/72tfmbd9tt90+97nPHX744XU90cMPP3zMMcfceOON87Y/4QlP+OpXv7psmSwNUMgEYManP/3pn/mZn3nggQd6f/Qnf/Inr3nNa+p6ImifroW8vetd7+rt/pcsWfKmN72pxu5/yZIlO++88znnnNO7/ZZbbrnmmmtqfCIAUvDMZz7zPe95T98fnXPOObfeemvrewS1EQDI2IMPPrhp06be7UccccRZZ51V+9M9//nPP+SQQ3q3X3zxxbU/FwCdO/PMM1/84hf3br///vv7nn0gFwIAGfuHf/iH22+/vXf7//7f/3unnXaq/el22mmnV73qVb3br7rqqtqfC4AU/J//839WrlzZu/0973lP3xMQZEEAIGPvfve7ezeuXbv2+c9/fkPPeMopp/RuvOGGG7Zt29bQMwLQoUMPPfS3f/u3e7c/9NBD5557bhd7BDUQAMjVTTfd9JnPfKZ3+6tf/ermbsk96qij9t9//3kbH3nkkS9/+csNPSMA3fqN3/iNFStW9G5/3/ve18XuQA0EAHJ1ySWX9G5cunTpmWee2dyTLl269Pjjj+/d/tWvfrW5JwWgQ3vttVff8e8Xf6iLPYKqaviIdOjEhz70od6N69evP+iggxp93jPPPLP3Y+b22GOPRp8UgA79/M///EUXXdS7/YorrjjyyCO72COoxPcAkKX7779/77337v0qlte//vV/+Id/2NFOAVDO9wDMtWPHjtWrV/d+J8ALXvCCD3zgA008IzTKJUBk6frrr+/7RYzPfvazu9gdAEq2yy67POUpT+nd/rnPfa6L3YGqBACy9O///u99tx999NGt7wsA5et7fvn6179+3333dbE7UIkAQJa+8IUv9G5cs2bNvvvu28XuABAxAExPT2/ZsqWL3YFKBACy9K1vfat34xOe8IQu9gWA8q1bt67v9m9/+9ut7wtUJQBQTgA48MADu9gXAMq39957993+ne98p/V9gaoEALL03e9+t3dj71d0AUAt9txzz77b77333tb3BaoSAMhS72exLVmyZOXKlV3sCwDl22uvvfpuf/DBB1vfF6hKACBLDz30UO/GXXfdtYt9AaB8C00Atm/f3vq+QFUCAFn6wQ9+0LvRt9oB0JC+Xz6zZMmSnXfeufV9gaoEALK0YsWKIccCAFDdQiv9hs/kSAAgS30v9+97YwAAVLfQF37tttture8LVCUAkKU99tijd+Ndd93Vxb4AUL477rij7/Y1a9a0vi9QlQBAlg466KDejbfffnsX+wJA+Rb6vP+DDz649X2BqgQAstS34N5yyy1d7AsA5fvKV77Sd/vjHve41vcFqhIAyNLjH//43o133HHH97///S52B4DCfelLX+rduP/++7sEiBwJAGTpqU99at/tn//851vfFwDKd+211/ZuPOqoo7rYF6hKACBLC9XcT33qU63vCwCFu+eee2666abe7evXr+9id6Cq5ZUfATqwbt26vfba65577pm3/aqrrvqDP/iDRp/6f/2v/zXv80Z32WWX973vfY0+KQAd+vCHP9z3i8BOOOGELnYHqlrqy1PJ1Atf+MKLL7543saddtrp9ttv32+//Rp60i1btjzxiU+ct/Gwww772te+1tAzAtDX0qVLezc21NVMTExceOGF8zbuvffed955p28CJkcuASJXz3ve83o3PvLIIxdddFFzT/qxj32sd2NvJACgGHfeeecll1zSu/2MM87Q/ZMpAYBcvfCFL+xbef/yL/+yuSe94oorejc+5SlPae4ZAejWO97xjocffrh3+y/+4i92sTtQAwGAXO23334nnnhi7/bPf/7zV111VRPP+OCDD3784x/v3X7cccc18XQAdO573/ve2972tt7txx577DOf+cwu9ghqIACQsVe96lV9t//e7/1eE0933nnn3X333fM27rzzzs95znOaeDoAOvfa17723nvv7d3+u7/7u13sDtRDACBjJ5100tFHH927/dOf/vQFF1xQ+9O9853v7N14/PHH77PPPrU/FwCdu/zyy//u7/6ud/txxx136qmndrFHUA8BgLz9/u//ft/tv/qrv/rd7363xie68MILr7/++t7tv/RLv1TjswCQiJtvvvkXfuEXerfvtNNO73znO/t+BhHkQgAgbz/3cz/X9wqcu+666xd+4RceffTRWp7l7rvvPvvss3u3r1279vTTT6/lKQBIx6233nrCCSds3bq190eve93rfAEwuRMAyN473vGOvh8H9JGPfOS1r31t9cefnp7+lV/5le985zu9P3rzm9+80047VX8KANJx4403rl+//utf/3rvj37qp37qDW94Qxc7BXUSAMjeunXr3vzmN/f90Z/+6Z++7nWvq/j4Z5111vnnn9+7/Wd+5mcmJiYqPjgA6Zienn7Xu971jGc841vf+lbvT9euXTs5OWndhwL4JmBKMD09fdppp1122WV9f3rmmWf+zd/8zapVq0Z92G3btv3ar/3ae97znt4frV69+oYbbjjkkEPG2l8Akvsm4CuvvPJ1r3vddddd1/enBxxwwNVXX7127dqxHx/SIQBQiHvvvfenf/qn+96nO7Ns89a3vvWUU04Z/gE/+clPvvzlL7/55pt7f7R8+fKPfOQjxx9/fIX9BSCJAPDlL3/50ksv/fu///sbb7xxoT9z2GGHfexjH/O97xRDAKAcd95557Oe9ayvfvWrC/2BY4899uyzzz711FP32GOPhf7Mvffee9lll7397W//13/9175/YNmyZeeee27fj4YAoNsAsHnz5gF/5ZFHHtmxY8e2bdu2bt16++2333zzzf/+7/++6EfGPfOZz7zooosOPPDAyrsMqRAAKMqdd9552mmnLdS7z9hll12e8YxnPOUpT3niE5+411577bzzzlt/6Nvf/va111574403DvjsoJ133vncc899yUte0szuAzCsFj6Ic9myZa95zWve9KY39f2oCciXAEBpHnzwwV/+5V9+3/veV/sjH3DAARdddNFxxx1X+yMDkFoA+Imf+Im/+Iu/OOaYYxp9FuiETwGiNCtXrnzve9978cUXr1mzpsaH/fmf//mbbrpJ9w9QvPXr11966aX/+q//qvunVCYAFGvbtm3veMc73vKWt3zve9+r8jjPfe5z3/jGNz7jGc+ob9cASG4CsG7dutNPP/2lL33punXr6n1kSI0AQOEefPDBiy+++L3vfe9VV1318MMPD/8Xf/RHf/QFL3jBy172sic96UlN7iAALQWAZcuWLV++fNddd121atXee++9//77H3rooUccccSTn/zk9evXH3DAAc3sKSRHACCKbdu2XXPNNVdfffWXv/zlm2+++Tvf+c7999+/bdu26enplStXrlq16sADDzzkkEOOOOKIo48++rjjjjvssMO63mUAgPoJAAAAEIibgAEAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACWToxMdH1PkAqpqamut4FaI/6DxDTMh0PQDQTP9T1XgDQjeUdPS8AHdD3A/Cf9wAYAgAUz6o/ADNMAAAKp+8HoM+nABkCAJTHqj8AvUwAAAqk7wdg8e8BMAQAKIBVfwAGMwEAKIS+H4CRvwnYEAAgR1b9AWhwArB2cvWofwXSsWXD1q53AerUXN+v2hOq/nvDE+o9//9NAIYZAuifAFJg1R+A8bgHACAz+n4Aqpg/ATAEAEiWVX8AqjMBAMiAvh+ABicAhgAA6bDqD0C9TAAAElW97187udp6DQBDTQAMAQCyXvVfO7naxxoC0JcJAEBpq/417QsAwSYAhgAAbbLqD0A7TAAAOmbVH4BUJgCGAACNsuoPQPtMAAA6YNUfgEQnAIYAAPWy6g9At0wAAFpi1R+APCYAhgAAFVn1ByAdJgAADbLqD0CWEwBDAIBRWfUHIE0mAAA1s+oPQAkTAEMAgEVZ9QcgfSYAADWw6g9AgRMAQwCAXlb9AciLCQDAmKz6A1D+BMAQAMCqPwBZMwEAGIFVfwDCTQAMAYCYrPoDUAYTAIBFWPUHIPoEwBAACMKqPwDlMQEA6MOqPwClGnMCYAgAlMqqPwBlMwEA+C9W/QGIYPwJgCEAUAyr/gDEYQIAhGbVH4BoKk0ADAGAfFn1ByAmEwAgHKv+AERWdQJgCABkxKo/AJgAACFY9QeA2iYAhgBAyqz6A8BcJgBAsaz6A0BTEwBDACApVv0BYCEmAEBRrPoDQEsTAEMAoFtW/QFgGCYAQPas+gNANxMAQwCgZVb9AWBUJgBAlqz6A0ASEwBDAKBpVv0BoAoTACAbVv0BIMUJgCEAUDur/gBQFxMAIGlW/QEggwmAIQBQnVV/AGiCCQCQHKv+AJDfBMAQABiDVX8AaJoJAJAEq/4AkP0EwBAAGIZVfwBokwkAZRovWw5oQxdNs4zBqj+QSP0f8LfUGcqzNIVzvEOLMSQ1PhIPRqX1T/9I8RsmWUnVf0cKOR4pJgBkIKlaP3w7KxU00fc73UIo6df/vnuoTJG4NiYAhgAUVu7HFjkSaP27YgJARgqu/w4o2mcCQNIKrviDm+AgeUDrDywkTv2f9y9V0wgxATAEIGzRH1KRYUDrnwITAFKj/s/jWKMhJgAkQdEfslcuIAxo/YG51P8hfznqHqVNAAwBYlL0K8ouDGj9U2MCQFfU/4ocg1RkAkDb1P3a++n0k4DWH1D/m/hNKozkPQEwBCieut+CBJOA1j9lJgC0Q/1vgaOSkZgAEK7ub1o92Xf7xq0bxvhbi/7FsDMBrT8Ep/63yUyAurQdAKampgZ3DFs2bPW2zkW3dX9AsW7/6To5PXSbBLT+EJn63239lwSoyASADOp+y7W+rj1s7azQchLQ+kNY6n9q9V8SYDwdBABDgHy1VvrTr/hj/CtaOB/MHFnNxYDqrb9DGzKl/ide/2deIDWWIZkAkETdL6PiJ3I+aGIgoPWHmNT/vOq/gQBJBwBDgFw0WvojFP0h//kNnQxqGQho/SEm9T/r+m8gwGAmALRa+oMX/U5OBmPHAK0/xKT+F1P/xQCSCwCGAGlS9zs3+7uq90ww0nVBWn8ISP0vtf67LoheJgA0VfoV/TSXhQYPBLT+EJD6H6T+GwiQRAAwBCiy9Kv7WSwL9cYArT8EpP4HrP9iACYA0dVY+tX9HM8EtXyivxMJ5Ej9D17/xYDgOg4AhgBdUfpzN/Nr7/wL6h2ekB31P3c11n8xICwTgHDqKv3qfsF3jA3DCQOyo/6XpMb6LwYE1H0AMARojdJfsDYHAo5HyI76X7C66r8YEEr3AYBcqr+6n76mBwJODJAj9T+Cuuq/VdcgkggAhgCNUvoDqn0g4ACEHKn/AVWv/0YBESQRAGiI0h9cXTHAaQCyo/4HJwaQRwAwBEiq9Kv7Jak+F3YagIyo/8xS/0k9AJBI9Vf6C1ZxQUgIh/Sp//Sl/pNuADAEqE7pp9HTgKUgSJb6z6LUf1IMAHRV/ZX+gCqeBpwDICnqP8NT/0kuABgCjEfpp+XTgKUgSIT6z3jU/+CWdb0DVKX6U9HY74S6vloIGI/6T0Xqf1hpTQAMAUai9FMXS0GQF/Wfuqj/MSUXAGi0+iv9NHQacA6A1qj/1E79jybFAGAIMJjST4KnAUtB0AL1n0ap/3G4ByAzqj/tGO8946pQaI76TzvU/wgSDQBTU1OD/0DM99kY/+pNqydVf8Yz3psn5rEJTVP/aZP6X7wULwGirtLfzL4QyxgTYeNgqJH6T1fU/4IlOgEwBJhL9adzloKgE+o/nVP/i2QCkLpRjyKln6SWgqwDwdjUfxKh/pcn3QmAIcCWDVtVf1Iz6ntsjLcxoP6TIPW/JCYAiVL6SZalIGiU+k+y1P9iJD0BCDsEUP0pcimosX2Bcqj/pE/9L0DqASAg1Z9cOAdAvdR/cqH+5y6DS4DifDGw0k/x42CfEAd9qf9kR/3PmglAKlR/8mUpCKpQ/8mX+p+pPAJA8XcCqP7kzjkAxqP+kzv1P0cZXAJUvJGOBKWfksbBZsEEp/5TBvU/O3lMAAoeAqj+FGakd2mmhy3UQv2nMOp/RrIJAEVS/SmScwAsSv2nSOp/LnIKAIUNAYbf202rJ1V/8jLSmzavIxeqU/8pmPqfhZwCQNjq3/C+QFOcA6CX+k8E6n/iMgsAZQwBVH/icA6AudR/4lD/U5ZZAMjdlg1bVX+iGekc4DRAqdR/AlL/k5VfAMh3COCWL8JyWxjBqf+Epf6nKb8AkCnVn+CcAwhL/Sc49T9BWQaA7IYAqj84BxCT+g/qf4J8E3DjXPQJ431bpK+KJHfqP8xS/5OS5QQgxyHAolR/4vBuh7kcEcTh3Z6IXANALobMIY4HohnyPZ9dkodZ6j/0pf6nIOMAkP4QQPWHAZwDKJj6DwOo/53LOAAkTvWHRTkHUCT1Hxal/ncr7wCQ7BBA9YchOQdQGPUfhqT+dyjvAJAm1R9G4hxAMdR/GIn635XsA0BqQwDVH8bgHEAB1H8Yg/rfiewDQFJUfxibcwBZU/9hbOp/+0oIAIkMAVR/qMg5gEyp/1CR+t+yEgJAClR/qIVzANlR/6EW6n+bCgkAiQwBAAAgcYUEgG5Z/oEaWQQiI+o/1Ej9b005AaCrIYDqD7VzDiAL6j/UTv1vRzkBoBOqPzTEOYDEqf/QEPW/BUUFgJaHAKo/NMo5gGSp/9Ao9b9pRQWABKn+UIUjiHx590IVjqBGlRYAWhsCDPM43rtQ3TDHkUUg2qT+QzvU/+aUFgDaofpDm5wDSIf6D21S/xtSYABoegjgfQZpcmzSNO8xSJNjc1QFBoAUWP6BejmmyIX3KtTLMdWEMgNAc0MAw1/oikEw3VL/oSvqf+3KDAANUf2hW84BdEX9h26p//UqNgDUPgTwroJcOFqpl3cU5MLRGj0AdMLyDzTNUUaavDOhaY6yGpUcAGocAhj+QjoMgmmT+g/pUP/rUnIAqIvqD6lxDqAd6j+kRv2vReEBoLUvBgYAgCwUHgCqs/wDabIIRNPUf0iT+l9d+QGgyhBA9YeUOQfQHPUfUqb+V1R+AGiU6g/dcgzSFe896JZjsIoQAWC8IYDgCGVwLDMq7xkog2M5dAAYg+Ev5MIgmHqp/5AL9X9sUQJA7R8HpPpDOhyPtMn7DdLheBxPlAAwEmERyuO4ZhjeJ1Aex3XoADDkEMDwF3JkEEx16j/kSP0fQ6AAUBfVH9Lk2KRp3mOQJsfmqGIFAF8MDME5xlmI9waUzTEeNwBUJ2JCyhyhNMe7C1LmCB1JuACw6BAAKJtFIHp5V0AEjvS4AaAK4RLS5zilCd5XkD7H6fAiBoDxhgDeVZCLRY9Wi0CM9H5Q/yEX6v+QIgYAAOcAZngnQDRbHPVhA8CoQwDLP5AXxyx18V6CvDhmhxE0AABYBMJ7AGLaEv7YjxsAhh8CiJKQI0cu1XkXQY4cuYuKGwAALAJF5tWHyLbErgChA8AwQwAhEvLl+KUK7x/Il+N3sNABYGJiYvAf8O6B3PlIOPry0Z9QPPV/gNABAAAAookbACz/QxAWgZjH8j8Eof4vJG4AAACAgIIGAMv/EIpFIGZZ/odQ1P++ggYAAACIKWIAsPwPAVkEwvI/xKT+94oYAAAAICwBYD7LP1AqRzeDeYdAqRzd0QPAotf/AGEFnAKH4vUFFrIlWH0IFwAAACCyWAHA7b8QnFvBwnL7LwSn/scNAAAAEFygAGD5H7AIFJPlf0D9DxoAAAAAAeC/WP6BOBzvzOX9AHE43mMFAJ/+CQwvzhQ4Aq8mMLwtMSpGlAAAAABECQBu/wXmcStYEG7/BebZpP4HCQAAAMAMAcDyDwTl2Md7AGLaFP7YLz8AuP0XGE+EKXDZvILAeLaUXj3KDwAAAMCs6AHADAgiUwEi8+pDZJtiV4DCA4Drf4Aqip8CF8xrB1SxpegaUngAGCx4+APUgbC87sCmwHUgdAAAAIBoSg4Arv8Bqit7ClwqrxpQ3ZZyK0nJAWCwyHMfYC7VIBqvOBC8GsQNAAAAEFCxAcD1P0BdCp4CF8nrBdRlS6H1pNgAMFjYiQ/Ql5oQh9camCtmTQgaAAAAIKYyA4Drf4B6lToFLo9XCqjXlhKrSpkBAAAA6CtiAIh5sRcwmMoQgVcZ6BWwMkQMAAAAEFaBAcANAEATirwMtDBeI6AJW4qrLQUGgMECTnmAIakPZfP6AgvZFKw+hAsAAAAQmQAAAACBlBYA3AAANKe8y0BL4tUBmrOlrApTWgAYLNoFXsCoVIlSeWWBwTZFqhKxAgAAAAQnAAAAQCBFBQA3AABNK+wy0GJ4XYCmbSmozhQVAAYLdWkXMDa1ojxeU2AYm8LUikABAAAAEAAAACAQAQAAAAIpJwC4AxhoR0n3gZXBKwK0Y0sp1aacADBYnLs6gOpUjJJ4NYHhbYpRMaIEAAAAQAAAAIBYBAAAAAhEAAAAgECWRfgIoCD3cwA1Glw3ivkgiAIMfi3Uf2BUmwLU/0ICAAAAMAwBAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIpIQD4DFCgCRE+CS53PgMUaMKm0ut/CQEAAAAYkgAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABBI9gHA1wADzSn+yyCz5muAgeZsKrr+Zx8AAACA4QkAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgSwf/Dn6udu4dUPXuwCULPePgi74n6b+A43aknORXFp2AAAAAOZyCRAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCDLB/947eTqJTl/Ddum1ZMt7gt58P2g1GhqampJtgZ/EaT6T3nUf2q0NuciuUgAgGg0DcyjY4Ag1H/i1H+XAAEAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCDLyv4WhoI/wBVoweAakvW3gBVA/Qeas3FgDUn/W8AKDwAAAMDwBAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEBKCAC+DBJogq8BTp/6DzRhY9FfA1xIAAAAAIYkAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAghQQAnwQH1MtngOZC/QfqtbH0zwAtJwAAAADDEAAAACAQAQAAAAIRAAAAIJAoAcB9YMDwVIySeDWB4W2MUTHKCQBl3JQNpM9HAKVG/QfasbaUalNOAAAAABYlAAAAQCACAAAABBIoAAS5qwOoSK0oj9cUGMbGMLWiqABQzJ0ZQLLcAZwm9R9o2tqC6kxRAQAAABhMAAAAgEBiBYA4l3YB41ElSuWVBQbbGKlKlBYASro8C0iNGwBSpv4DzVlbVoUpLQAAAAADCAAAABBIuAAQ6gIvYCTqQ9m8vsBCNgarDwUGgMIu0gIS4QaA9Kn/QBPWFldbCgwAAADAQiIGgGhTHmAYKkMEXmWgV8DKEDEAAABAWGUGgPIu1QK65QaAXKj/QL3WllhVygwAAABAX0EDQMCLvYAB1IQ4vNbAXDFrQrEBoMh5DdAJ1//kRf0H6rK20HpSbAAAAAB6xQ0AMSc+QC/VIBqvOBC8GpQcAEqd2gBtcv1PjtR/oLq15VaSkgMAAAAwT+gAEHbuA8xSB2LyugMbA9eBwgNAwbMboAWu/8mX+g9UsbboGlJ4AFhU5PAHqACRefUhso2xK0D0AAAAAKGUHwDKnuAAzXH9T+7Uf2A8a0uvHuUHgEUFnwFBWI59vAcgpo3hj30BAAAAAgkRABad4wiCEM2iR73rf8qg/gOjHvVrS7/+J0oAAAAAYgWACGEOqIvl/5Ko/8Dw1saoGFECwKJMgSEOxztzeT9AHI73GQIAAAAEEigAuBUMcPtvTOo/4PbfoAEAAACIFQAsAkFwlv/DUv8hOMv/cQMAAAAEFy4AhIp3wEgs/5dN/QcWsjZYfQgXABZlCgylcnQzmHcIlMrRPY8AAAAAgUQMAG4Fg4Dc/ov6DzG5/bdXxAAAAABhBQ0AFoEgFMv/zFL/IRTL/30FDQAAABBT3ABgEQiCsPzPPOo/BGH5fyFxAwAAAAQUOgBYBILiWf6nL/Ufimf5f4DQAWAYzgFQ9vE7MTHRyr6QH/Uf8uX4HSx6AIgc/gAiU/8hsrWxK0D0ADAMIRLKPnINAViI+g85cuQuSgCIHgEBwlL/Iaa14Y99AWAooiSUfcwaArAQ9R/y4pgdhgDwnwRBgJjUf4hmraNeAJjlI+GgGOMdrYYAYan/UAwf/TkkAWAEzgGQPscpTfC+gvQ5TocnADxGKITgDAHCUv8hAkf6LAFgNMIlpMwRSnO8uyBljtCRCAD/H9EQgjMECEv9h7I5xucSAEYmYkK+x6YTAFWo/5Amx+aoBIBx+gPvMyi4+zcECEv9hxxZ/RmDANCHdwkUfFw7wBnA2wPK47juJQCMySIQFHw8GgIwgPoP6XA8jkcA6M8gGAoe/loNYgD1H3Lh4p+xCQAL8o6ByMeyIUBk6j+UwbG8EAGgEotAkOkx6KxAReo/dMsxWIUAMIhBMEQe/hoCRKb+Q8pc/FORALAI5wAotfo7NzCY+g9p0v1XJwAALMgQAIDyCACLswgEpS7/WCJiMPUfUmP5vxYCwFCcAyBs9TcECE79h3To/usiANTJOQCyO8qcKqiF+g9Nc5TVSAAYli4Bwh6thgDBqf+QC0frkASAERgEQ5HDXycMFqX+Q7dc/FMvAWA0zgEQs/obAqD+Q1d0/7UTABrhHAB5HVPOHNRF/Yd6OaaaIACMTKMAMY9NQwDUf0iTY3NUAsA4DIKhvOGv8wfDUP+hTS7+aYgAMCbnAAhY/Q0BUP8hZv0vjADQLOcAyOgIciKhRuo/VOEIapQA0Hiv4B0M4xny2Gm5azcEQP2HmPW/JAJAJc4BUFj1dzphSOo/NET33wIBoCrnAIhW/Q0BmKH+Q7T6XwwBoAbOAVBS9XdeYXjqP5RU/+MQAABGZggAQL4EgHpYBIKSln8sLzE89R9Kqv9BCAC1cQ6AUNXfEIBZ6j+Eqv8FEADq5BwAxVR/pxlGov5DMfU/AgGgZs4BEKf6GwIwl/oPcep/7gSA+jkHQBnV3/mGUan/UEb9L54A0AjnAAhS/Q0BmEf9hyD1P2sCQFOcA6CA6u/EwxjUfyig/pdNAGiQcwBEqP6GAPRS/yFC/c+XANAs5wDIvfqnsA/kSP2H3Ot/wQSAVDgHEEd573ZDAKoo74iAhXi3J2J51ztQvrWTq7ds2Dr8UbFp9WTzOwUZlP50ln+GP4phLvUfcq//pTIBaMNI72PhmFKVXf0NAehL/Yfi63+OBICWOAcQXO7VP8FdIhfqP8HlXv+LJAC0xzmAsIJUf0MAFqL+E1aQ+p8dAaBVaydXD//mdg6gDMO/k0c6QNqX8r6RPvWfgIqp/+URADrgHEAcI1X/JfkzBGAw9Z84otX/vAgA3XAOIILyqn8u+0nK1H8iKK/+F0YAyOMc4DRAXkZ60xZW/Q0BWJT6T8Ei1/+MCABdclsYRSr7lq/sdpg0qf8Uqez6XxIBoGPOARRG9TcEYEjqP4VR/zPim4Az+5JR3xZJskZtUPKt/r4YmLqo/5QhTv0vhglAEkY9EiwFkRrVfx5DAIak/pM79T9HAkAqnAPIV8DqX8A/gXSo/+QrYP0vg0uAEjJzVBgHkxGlf4CJiYmpqamu94I8qP9kR/3PmglAciwFkYvg1b+wfw4pUP/JRfD6XwABIEXOAaRP9R+GOwEYlfpP+tT/ArgEqJCPGTEOpjVjNBylVn8fB0QT1H+Spf4XwwQgXWsnV1sKooCFn+DV3xCAMaj/JEj9L4kJQOosBZEICz99GQLQHPWfRKj/5TEByMAYR5GlIOql+ldhCMDY1H86p/4XyQSgzE+IsxREXZT+RRkC0Cj1n66o/wUzASh/KchqEOMZ782j+vdlCEBF6j9tUv+LJwBkZryjyzmAdt4zYat/2H84bVL/aYf6H4FLgEKMg02EGZ7S3xBfDEx16j+NUv/jEABiXXbsNEATK4WqvzsBaJP6T+3U/2gEgHBLQU4D9FL622EIQF3Uf+qi/sfkHoDsjX0EujCUGap/XfxCaJn6T0Xqf1gmACWwFMR4lP72GQJQL/Wf8aj/wQkA5Rj7EmSngYCqrP+p/gO4E4BOqP8MT/1HACjN2EtBTgNxKP2dMwSgCeo/i1L/mSUAFKjKGqTTQMEqXvWr+g/JEIAOqf/0pf4zjwDAoErhTFCA6nf7Kf21MwQgzVGA+l8Y9Z+FCAClqXfp0YJQ1pT+rhgCkHsMUP9zp/4zmABQjuYaDqeB7Cj96TMEoAViQEDqP8MQAErQzlqjuXD66vpsb9W/OkMASno3qv/pU/8ZiQCQt046DAtCCVL6c2QIQEajgBnqf4LUf8YgAOSq88VFC0IpqPHrPJX+2hkCUHYMUP+7pf5ThQCQn1paipl1x4mJieoPZUGoE0p/GQwByDcGqP9dUf+pTgAI2vo3FAOcCTKq+0p/CwwBiBMD1P+mqf/USAAI2vr3bq8lBjgTZFH3lf6kGAJQRgxQ/xui/tMEASB0699cDJhXs5wMUij6M5T+lhkCEC0GqP/Vqf80TQBIV2utf98/X2MSsCw0EnU/IEMAUjBbJZr4Qkn1fxjqP60RAFLUSevf96/XGwMsC7Vc9Gco/Z0zBCD4QGCG+t+X+k8nBIC0pND6txADZgQ/GTRa9Gco/RkxBCBIDJih/jf9FOo/gwkAqUit9e/7sA0lgd5qWOT5oIWKP0PdT5AhAJlq6LqgudT/Gqn/DEkA6F7KrX/fZ2kuBhR2Pmit4s9S+rNmCEDYgcBc6v941H9GIgB0KaPWv+8ztpAEBlTSpM4K7df6udT9LBgCUIAWBgLzqP+Dqf+MRwDoRqatf+dJYPiaW/vpodsS35e6Xx5DAHLRfhKYS/1X/6lo6eDWzTusdmW0/gvpJAlE46gsuwK0eXSr/9TIgKsFjkrqOipNANpTduufwkygbOp+EIYAZKrbmUDZ1H9qJwC0IULrP48kUBd1vzDuBKB4kkBd1H+aIwA0K2DrP2DnhYEhKfrBGQJQXikTBoak/tMOAaApWv9ewsAAin4chgAEJAwMoP7TPgGgflr/YQgDij4DGAJQMGFA/adzAkCdtP61/JMLzgMqPjMMAaBvVSz4uFD/SYoAUA+tf416fw+ZRgLlnioMAQiot2xmGgnUfxInAFSl9W9B399PUqlArWdUhgAwdnVN6thR/8mRADA+rX+3Bv/qao8HSjztMwSAMQpy7fFA/ac8AsA4tP7pW+jX66tPSYchADRhoUo++HBT/wlFABiN1h9okyEAALUTAIal9QdqZwgAQPsEgMVp/YEOGQIAUC8BYBCtP9A0QwAAWiYA9Kf1B9JhCABAjQSA+bT+QMsMAQBokwDwGK0/kCxDAADqIgD8J60/0C1DAABaEz0AaP2BXBgCAFCLuAFA6w8kxRAAgHZEDABafyBThgAAVBcrAGj9gZQZAgDQgigBQOsPlMEQAICKyg8AWn8gI4YAADSt5ACg9QeKZAgAQBVlBgCtP5AvQwAAGlVaAND6AxEYAgAwtnICgNYfKIYhAADNKSEAaP2BgAwBAIgYALT+QKkMAQBoSK4BQOsPYAgAQIgAoPUHgjAEACB6AND6A8xjCABAmQFA6w/EZAgAQLgAoPUHGMwQAIBCAoDWH8AQAIAQAUDrDzASQwAAcg0AWn+AXoYAABQYALT+AFUYAgCQTQDQ+gMsyhAAgLosW9KdLRu26v4B6jIxMdH1LgCQgW4mAHWtY2n9gTgMAQDIMgBo/QGa404AABIKAFp/gIoMAQDIIwBo/QFaYwgAQJcBQOsPUC9DAAASDQBaf4CuGAIA0GoA0PoDNMoQAIBUAoDWHyARhgAANBsAtP4AbTIEAKCzAKD1B0iTIQAANQcArT9AhwwBAGgvAGj9AbJgCABA1QCg9QdIhyEAAA0GAK0/QI4MAQAYOQBo/QGSZQgAwKiWDf5xLeeVqR+q/jgAjGFiYqLrXQCg6G8CnkvfD9A0QwAA6pwAjM2qP0A6DAEAaHACoO8HaJkhAADdTACs+gMkyxAAgDonAPp+gG4ZAgDQ0gTAqj9ALgwBAKg0AdD3Ux4LqDDL4UAo3vCEMs4EwKo/QKYMAQAYbQKg7wcAgBATAKv+AGUwBAAIbvEJgL4fAABCTACs+gMUyRAAILL+EwB9PwAAhAgAWn+ACAwBAMJ6LABo/QEAYEnp/h8K89T6o30/gAAAAABJRU5ErkJggg=="
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_472
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAgAAAAIACAYAAAD0eNT6AAAGdElEQVR4nO3YywmDABBAQQ02kNYCWmQEW7OEpAUvfuDNnBd2j48dBgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAC4yzvP8u2oZ8Hzruo533wCc73XBDgDgYQQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAgqajg+/P99xLgFPt23L3CcCD+AAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQNB0dHDflnMvAQAu4wMAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAoecP9RMLAepr/sAAAAAASUVORK5CYII="
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'RuRuRuRu'}.\nthe 2th action is Stack the original shape on top of the {'layer1': 'RwRwRwRw'}.\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is Stack the original shape on top of the {'layer1': 'WbWbWbWb'}.\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'CgCgCgCg'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'CuCuCuCu'}.\nthe 9th action is Stack the original shape on top of the {'layer1': 'WgWgWgWg'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:9)_435
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is Colorize the top layer of the original shape with the color purple.\nthe 3th action is Cut the right side of the shape\nthe 4th action is Cut the right side of the shape\nthe 5th action is Cut the right side of the shape\nthe 6th action is rotate the shape counterclockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'CyCyCyCy'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'SuSuSuSu'}.\nthe 9th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_105
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is Colorize the top layer of the original shape with the color blue.\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is Colorize the top layer of the original shape with the color green.\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is Colorize the top layer of the original shape with the color red.\nthe 7th action is Stack the original shape on top of the {'layer1': 'CrCrCrCr'}.\nthe 8th action is rotate the shape counterclockwise 90 degrees\nthe 9th action is Stack the original shape on top of the {'layer1': 'WyWyWyWy'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:9)_325
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is Stack the original shape on top of the {'layer1': 'CpCpCpCp'}.\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is Stack the original shape on top of the {'layer1': 'WbWbWbWb'}.\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is Cut the right side of the shape\nthe 7th action is Colorize the top layer of the original shape with the color purple.\nthe 8th action is rotate the shape clockwise 90 degrees\nthe 9th action is Stack the original shape on top of the {'layer1': 'WgWgWgWg'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:9)_468
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'SrSrSrSr'}.\nthe 2th action is Cut the right side of the shape\nthe 3th action is Stack the original shape on top of the {'layer1': 'WcWcWcWc'}.\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is Cut the right side of the shape\nthe 6th action is rotate the shape counterclockwise 90 degrees\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is rotate the shape clockwise 90 degrees\nthe 9th action is Stack the original shape on top of the {'layer1': 'RgRgRgRg'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_354
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is Stack the original shape on top of the {'layer1': 'WpWpWpWp'}.\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is Colorize the top layer of the original shape with the color red.\nthe 5th action is Stack the original shape on top of the {'layer1': 'RcRcRcRc'}.\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is Stack the original shape on top of the {'layer1': 'WbWbWbWb'}.\nthe 9th action is Stack the original shape on top of the {'layer1': 'WbWbWbWb'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:9)_396
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'SgSgSgSg'}.\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is Cut the right side of the shape\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is Colorize the top layer of the original shape with the color cyan.\nthe 6th action is Stack the original shape on top of the {'layer1': 'WbWbWbWb'}.\nthe 7th action is Colorize the top layer of the original shape with the color purple.\nthe 8th action is Stack the original shape on top of the {'layer1': 'SwSwSwSw'}.\nthe 9th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_474
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color purple.\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is Cut the right side of the shape\nthe 6th action is rotate the shape counterclockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'WpWpWpWp'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'SySySySy'}.\nthe 9th action is Colorize the top layer of the original shape with the color red.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_283
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'WbWbWbWb'}.\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is Colorize the top layer of the original shape with the color red.\nthe 4th action is Cut the right side of the shape\nthe 5th action is Colorize the top layer of the original shape with the color green.\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is Colorize the top layer of the original shape with the color blue.\nthe 9th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_482
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color white.\nthe 2th action is Colorize the top layer of the original shape with the color yellow.\nthe 3th action is Cut the right side of the shape\nthe 4th action is Colorize the top layer of the original shape with the color cyan.\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is Stack the original shape on top of the {'layer1': 'RcRcRcRc'}.\nthe 7th action is Stack the original shape on top of the {'layer1': 'SrSrSrSr'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'RwRwRwRw'}.\nthe 9th action is Colorize the top layer of the original shape with the color cyan.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABAAAAATICAIAAAANxCANAABwAklEQVR4nO3debhkdX0n/ttNszR7Ax32EUUi4CgoSVBwYnwIRnY11gWMmYyj0cSHkIwzTtqZOGiejDJxMpM4OjFjTNBEGuqCDAguEcFoQIIxKBDjgriBAq02WwMNQv+en5WUd27VrVt1tu/2ev3Bo3VvV51bdepbn/fnc86pVdu2bZsDAADKsDr0BgAAAN0RAAAAoCACAAAAFEQAAACAgggAAABQEAEAAAAKIgAAAEBBBAAAACiIAAAAAAURAAAAoCACAAAAFEQAAACAgggAAABQEAEAAAAKIgAAAEBBBAAAACiIAAAAAAURAAAAoCACAAAAFEQAAACAgggAAABQEAEAAAAKIgAAAEBBBAAAACiIAAAAAAURAAAAoCACAAAAFEQAAACAgggAAABQEAEAAAAKIgAAAEBB1oTeAOjU/fffv++++z7yyCNjf/rqV7/6Pe95T+cbBUAtF1100Uy/v/pH1qxZs+OOO+6888577rnn+vXr99133+222661bYSIrNq2bVvobYDu/Nmf/dmrXvWq5X6611573XXXXdtvv323GwVALatWrap/JzvssMO//Jf/8tnPfvZP/dRPnXbaaQcccEATmwYxEgAoywknnHDNNddM+IUrr7zylFNO6XCLAIgiACy5w+OPP/7f/Jt/8yu/8itr1jhcgtw4B4CC3HnnnZ/85CebnSMDkJ9t27b9zd/8zatf/eojjjii3++H3hxomABAQTZu3PjEE09M/p3LL798uTMEACjNbbfdduaZZ77mNa959NFHQ28LNEYAoCB/+Zd/ueSWdevWLbnlgQceuOqqqzrcKABi9573vOdFL3rRY489FnpDoBkCAKX4h3/4hy984QtLbnz7298+enDnxRdf3OF2AdCKbRM9/vjjjz766H333ffNb37zU5/61P/6X//rZS972c4777zcvV177bXnnntut38BtMVJwJTijW984/nnn7/4lt133/2ee+45+eSTl5wWvHbt2nvuuWfXXXftfBsBaOwk4AoVzoMPPviHf/iHv//7v//AAw+M/YWPfexjL3zhCyttI0TEBIAibNu2bePGjUtufPGLX7zjjju+9KUvXXL7ww8/fMUVV3S4dQBEYdddd/2d3/mdG2644ZBDDhn7C295y1s63yhongBAET796U9/85vfXHLjmWeeOYgBo60j1wICKNaRRx551VVXjT0c6Prrr/+7v/u7EBsFTRIAKMIHPvCBJbfstddeJ5544tzc3IEHHvgzP/MzS376sY997N577+1wAwGIyJFHHvnbv/3bY3909dVXd7450DABgPw9+uijCwsLS2586UtfOvzG35e85CWj/+SDH/xgVxsIQHRe97rXbbfddqO3X3vttSE2B5okAJC/D3/4w5s3bx57/M/A6GkAjgICKNw+++xz9NFHj94+ekApJEcAoMTL/69fv/4FL3jB8P8edthhT3/605f8zjXXXLNp06ZONhCAGD3jGc8YvfF73/teiG2BJgkAZO6+++4b/WKvl73sZUsGu6NDgMcff/ySSy5pfwMBiNTee+89euN9990XYlugSQIAmbvkkkseeeSRJTeeddZZS25xFBAA03yTwO677x5iW6BJAgDFHf9zwAEHPO95z1ty49FHH/3kJz95yY1/8zd/c+edd7a8gQBEauzl4NavXx9iW6BJAgA5u+OOOz71qU8tubHX661ePWbPH70W0BNPPNHv99vcQADi9eUvf3n0xmOOOSbEtkCTBAByduGFFz7xxBMrHv+zXABwFBBAsbZu3XrTTTeN3v6zP/uzITYHmrRq7PFtkIejjjrq5ptvXnzLk570pK9//eujX/076PcfcMABd99995Lbb7/99tGjgwCIx9hVvWaF84EPfOAVr3jFkht33nnnO++8c88996xzzxCcCQDZuvXWW5dU/3Nzc/Pz82M/J/7/N8Pq1Wecccbo7RdffHE7GwhApB599NG3vvWto7e/5jWvUf2TAQGAbI2e/jvh+J8B1wICYG5u7vWvf/0Xv/jFJTcefPDBv/u7vxtoi6BJDgEiT9u2bTvkkEO+9a1vLb7xqU996le/+tUJ/+qxxx77iZ/4idHLPvzjP/7j4Ycf3s6WAhDRIUBbtmz5rd/6rT/90z9dcvvuu+/+yU9+8lnPelbVbYSImACQp0996lNLqv+5ubkzzzxz8r/afvvtTznllNHbDQEAsrd58+Z3vOMdT3/600er/3333fcjH/mI6p9smACQp1/91V8dXcFvvvnmsd/rvtgHP/jBX/zFX1xy4+GHH/6P//iPTW8jAC1OADZu3Djhn2zbtm3r1q0PPfTQXXfddccdd9x0000333zz6IXj5ubmTjzxxAsuuOCAAw5odJMhJAGADG3dunW//fZbciTPEUccMXpA56iHHnpon332efjhh5fcftNNNx199NFNbykADVju6g41PetZz3rLW95y2mmntXHnEJBDgMjQVVddNXoc/+TTf4d23nnnX/iFXxi93VFAAOXYZZdd/viP//hzn/uc6p8sCQBk6AMf+MDojSueADD5G8FcDBSgHFu2bPn1X//1Aw888JxzznEIKPlxCBC5uffee/fbb7+tW7cuvvHoo48e+4WOY23evPknfuInfvjDHy65/YYbbjj22GOb21IAoj4EaOikk076oz/6o8MOO6zVR4HOmACQm0suuWRJ9T9T+39ubm7dunU/93M/N3q7o4AAyvSRj3zkmc985n//7/899IZAM9Y0dD8Q9fd/rVq1aqbyff369aM39vv9P/iDP1i9WmwGSMCKxzg88cQTW7ZseeCBB+68885vf/vbn//852+88cZrr7320UcfHf3lRx555A1veMM3vvGNd7zjHT4ISJ1DgMjKt7/97Sc96Unt7dWf/OQnn//857d05wAE/yKw73//+xdccMHv/d7vjV5MYuC8885785vfXOGeIR4iLFm58MILW820jgICyNvee+/97//9v//KV77yghe8YOwv/N7v/d5nPvOZzrcLmmQCQFae+cxn3nLLLe3d//r167/zne+sWePYOYA8JwBDW7duPeWUUz7xiU+M/ujEE0/8q7/6qzp3DmGZAJCPm2++udXqf25ubtOmTddcc02rDwFADHbcccf3v//9e+211+iPPv7xj0/zzZIQLQGAzE//bZyjgAAKccABB5xzzjljf/ThD3+4882BxggAZGLbtm0bN25ccuMuu+zy0EMPbavqwgsvHH2gyy67bOwFIgDIz2te85qxt19//fWdbws0RgAgE5/85CfvuOOOJTeeeuqpa9eurXyfp5122ug/v/feez/60Y9Wvk8AEnLggQceeuiho7c7BIikCQBk4gMf+MDojb1er8597rrrrieddNLo7Y4CAijHMcccM3rjD37wgxDbAs0QAMjB1q1bL7300iU37rLLLmPL95nMz8+P3njFFVc89NBDNe8ZgCTsvffeozcu9y0BkAQBgBxceeWVo2vxKaecsvPOO9e851NPPXX0TrZs2XLllVfWvGcAkrD77ruP3ujLgEma3Zdsr/9T8/ifgV122eXkk08evf3iiy+uf+cAxO/++++fMhVAKgQAkrd58+bRy7HtvPPOYwv3Cs4888zRGz/84Q8/8MADjdw/ADHbtGnT6I0HHXRQiG2BZggAJG9hYWH0upyNHP8zvKtddtllyY2PPPLI//2//7eR+wcgZjfeeOPojUcccUSIbYFmCAAkr43r/yy2du3aU089dfR21wICyN5XvvKVb33rW6O3H3vssSE2B5ohAJC2b33rW5/+9KfbO/5nwrWAPv7xj7sMHEDe/uf//J9jbz/llFM63xZojABA2i688MJt27YtufHkk08ePWinjpNPPnnXXXddcuNjjz02eu1RALJx0003/fmf//no7c973vPGfjsYpEIAIG1tH/8zsNNOO5122mmjtzsKCCBXd95558te9rKtW7eO/ui3f/u3Q2wRNEYAIGGf//znb7311iU3rl27to3J7NijgP76r//67rvvbvyxAAjrhhtuOPbYY2+//fbRH73oRS8ae2IYJEQAILf2/0knndTs8T/Dux296vPjjz++sLDQ+GMBEMqNN974r//1vz7uuOPuvPPO0Z/ut99+Yw8KgrSsCb0BUNETTzyxcePGDo7/Gdhxxx1PP/300W8cu+iii84555w2HhGAOqY5SvOHP/zh1q1b77///u9973tf+tKXPve5z33zm99c7pf32muvj370o/vtt1/TWwpdWzV6AiUk4ZprrjnhhBOW3LjTTjtt2rRp9ITdRnzoQx86/fTTl9y4atWqb37zmwcffHAbjwjANFatWtX2Qxx55JFXXHGFc3/Jg0OASNVoM35woE5L1f/c3Nwv/MIv7LHHHktu3LZt28UXX9zSIwIQg1e84hU33HCD6p9sCAAk6ZFHHvngBz/Y2fE/AzvssMMZZ5wxertrAQHk6qd+6qeuu+66v/iLv9htt91Cbws0RgAgSR/60Ifuu+++JTfutNNObV+ZYey1gD73uc/ddtttrT4uAF3addddX/nKV1533XWf/exnjzvuuNCbAw1zEjBJWrt27Xnnnbfkxn/xL/5F2x2aF77whW9+85tHz5wZTSMARG7VqlVr1qzZcccdd91113Xr1u27775PetKTnv3sZx933HFHH330mjVqJLLlJGAAACiIQ4AAAKAgAgAAABREAAAAgIIIAAAAUBABAAAACiIAAABAQQQAAAAoiAAAAAAFEQAAAKAgAgAAABREAAAAgIKs6vV6obcBgDAWFhZCbwIAXRMAAEonBgAUYlD5OwQIoPS6v/cjoTcHgBYtXurXtPlAACRj8MFgGgCQmdEWjwkAQLlGy33TAIBsjF3SFxYWTAAAWMo0ACBpk1s5JgAARZtQ5ZsGACRn8tI9WPNNAACYxDQAIAnTt2xMAABKN01xbxoAEK0pl+jham8CAMC0TAMAolKtNbPCF4H1+/0amwTRmZ+fn/BTOzxF7fNL6vhZP0XEAICA6izaJgAAVGEaABBE/QMynQMAwFzlUt65AQCdqbzkLlnhTQAAqMs0AKA9jfdZTAAA+Cc1K3jTAIBmNbKujq7tJgAANMk0AKC+VvspJgAA/NiEwr2/bv3092MaAFDNrOvn5MV57KpuAgDAVOY3bxp8zMxv3jTlPxl+hhkIAKxo1r7JrGvykAAAwP9jYWFhha+Imf0jx3FBAI2X/itabtUVAACYeQggBgDEUPpXaP8LAABUGQIMiQEAUXX9hyYsswIAABWHAENiAED3pX+19r8AAEDdIcCQGAAQtus/NHldFQAAaGAIMCQGAHRQ+ldu/wsAADQ5BBgSAwA67voPrbiQCgAANDwEGBIDgJL1Wiv967T/BQAA2hoCDIkBQGl6nXf9h6ZZOQUAAFocAgyJAUAJOij9a7b/BQAAuhgCDIkBQK564br+Q1MulQIAAB0NAYbEACAnvQ5L//rtfwEAgK6HAENiAJC6XgRd/6Hp10YBAIAAQ4AhMQBIUS9E6d9I+18AACDkEGBIDABS0Yup6z8002IoAAAQeAgwJAYAMesFLf2bav8LAADEMgQYEgOA2PSi7PoPzbr6CQAARDQEGBIDgBj04ij9G2z/CwAAxDgEGBIDgMJL/xVVWO4EAAAiHQIMiQFAyaX/fKPtfwEAgNiHAENiAFBa6b+iauubAABAAkOAITEAaFxv9r5GZ6V/4+1/AQCAlIYAQ2IAkH3pv6LKC5oAAEBiQ4AhMQDIu/Sfb6H9LwAAkOoQYEgMAPIr/VdUZwUTAABIeAgwJAYAmZX+8+20/wUAAHIYAgyJAUAGpf+Kai5ZAgAAmQwBhsQAIPXSf7619v/c3Nzq9u4agLxFXi5X+Ajv/Ug7mwN0rdo7uh9B9d/22msCAECGQ4DKowDTAMhAtSTfj2DV6qD9LwAAkOGZAEuIAVCO1Ev/FTWyKAkAAOQ8BGgkBkgCEL9sSv/5ltv/AgAARQwBasYAAwGIWTal/4qaWoIEAABKGQIMiQGQh/xK//n22/8CAADFDQGGxABIV36l/4oaXHMEAABKHAIMiQGQloxL//lO2v8CAABFDwGGxACIX8al/4qaXWQEAABKHwIMiQEQpxJK//mu2v8CAACNSX0IMCQGQDxKKP1X1PiqIgAA0LqEhgBDYgCEVVTpP99h+18AAKBJ2QwBhsQA6F5Rpf+K2lhGBAAAupDiEGBIDIBulFn6z3fb/hcAAGhYfkOAITEA2lNm6b+iltYNAQCAjiQ9BBgSA6BZhZf+8523/wUAAJqX8RBgSAyA+gov/VfU3kIhAADQnTyGAENiAFSj9A/Y/p+bm1s9l7j5+fnQmwDAUkWVtv1166vVJb0faWGLIF7VdvvK77J0LbS5iuYwARhkgH6/H3pDAChuCDBkGgATVM66WS4XYdv/OQSAfr8/CABiAADBiQGwhNI/QskfArTE/I+E3goAJtWyAfte3XBQENTZn0s44Gd+4jLYdi8g+QnA4iHAkGkAAMGZBlAsXf/I5TYBWMw0ACCskocAQ6YBFEXXP/72fyYTgLFDgCHTAACCMw0ge7r+Ccl5ArCYaQBAEIYAi5kGkCVd/7Ta//lMACYPAYZMAwAIzjSAbOj6J6qUCcBipgEAXTIEGMs0gKTp+qfb/s9qAjDlEGDINACA4EwDSI6ufwZKnAAsZhoA0AFDgMlMA0iCrn8e7f/cJgCzDgGGTAMACM40gGjp+mcmtwBQxzA5SAIAjVtYWFiuhpjfvEmVMCQGEBWlf37t/zwDQLUhwGIGAgCEJQYQnNI/Y6WfAzCB0wMAmuVMgFk5N4AgHOufd/s/2wAwoXm/sHG2vr4YAEBYYgCdUfoXIsNDgCbrnT0/yAC9s2co6x0UBNAIZwKEOijIcUFM5oCfctr/OQeAFc8EEAMAKCcGOD2A5Sj9C5TnIUCTLS76Fzb2HRQE0CVnAtRX53ALxwUx5ICfMtv/OU8AZrockGkAAMkxDaAyXf/ClTgBWK7WNw0A6IYhQINMA5iJrn+X4mz/Zz4BqPadAKYBACTHNIAV6fpT+gRgxRLfNACgVYYAbTANYCxd/yDmY23/5z8BqPnFwKYBACTHNIAhXX/GKncCMH1lbxoA0AZDgFaZBhRO1z+s+Yjb/0VMAGoOAYZMAwBIjmlAaeokN3V/OYqeAMxa0JsGADTLEKAbpgElqPNK6foX1f4vZQLQ1BBgyDQAgOSYBuRK159ZlT4BqDAEGDINAKjPEKBjpgE50fWP0Hz07f+CJgCNDwGGTAMASI5pQOp0/anDBKDWEGDINACgMkOAUEwDUqTrH7P5FNr/ZU0A2hsCDJkGAJAc04BU6PrTFBOAxoYAQ6YBALMyBAjONCBmuv5JmE+k/V/cBKCDIcCQaQAAyTENiI2uP20wAWhlCDBkGgAwJUOAeJgGxEDXPy3z6bT/S5wAdDkEGDINACA5pgGh6PrTNhOA1ocA9acBBgJAIQwBImQa0CVd/0TNJ9X+LzcABOysz5oBBsQAAAISA9qm9KdLhQaAUEOAyqOAATEAyJ4hQMzEgDYo/VM3n1r7v9BzAEKdCVD/xIABpwcAEJBzA5riWH9CMQEIMwQYMg0AWMIQIAl1ClDTgJrPgOo/HvMJtv+LngDEMAQYMg0AoKhRQLHTgJrJR+lPI0wAwg8BhkwDAAYMARJS8zD0cqYB9bv+qv/YzKfZ/i99AhDVEGDINACA5JgGTKDrT2xMAOIaAgyZBgCFMwRIkWnAErr+GZtPtv1vAhDpEGDINACA5JgG6PoTOROAeIcAQ6YBQJkMAZJW7DRA178E8ym3/00AEhgCDJkGAJCcoqYBuv6kwgQgjSHAkGkAUBRDgDw0Mg2IeSCg61+U+cTb/yYAqTINAKC0aUCcAwFdf1JkAvBPJtTEsQ0BhkwDgBIYAmSmfrc7kmmArn+Z5tNv/5sA5MA0AIDkpDsNqJ891P0EZwKQ9hBgyDQAyJghQK7SmgbUfyxd/9TNZ9H+NwHIjWkAAMmJfxqg609mTADyGQIMmQYA+TEEyF6c0wBdf/Jr/5sA5Mw0AIDkxDMN0PUnYyYAeQ4BhkwDgGwYApQj7DRA15+82/8mAKUwDQAgOd1PA3T9KYQJQP5DgCHTACB1hgAF6mYaoOtPOe1/E4ASmQYAkJz2pgG6/hTIBKCsIUBT0wADASAUQ4CSNTsN0PWnzPa/CUDpKk8DDAQASH0aUH8bIFEmAOUOAepPA5weAARhCEDA7ruuf1Hmc2z/CwDhxZMlxAC6Z7ehZLJKcuW40r9B9v+wBIDwQ4De2fNiAKWxt1BTHkOA+c2bEtramLVdmiv9y9zt5zNt/zsHILyFjf1B9T/4b+Xiu1nODaA9i+t++wkl669bPygvBv9VX8ZwbsBy90kjFr80ntiwTADiOhPANICM2SvoTCr9xUTbopFrqluv61/47j2f2gbPRAAIb7TIFgPIzNg9QfufmpKevw+M1pcp1klxqlO+K/0bNHaXzuDpXUh8/REA4r0ckBhABrz6hJJ0GS0GNGXWUl7p36Ckd+P5ZLd8SgJAFCbU1mIAiZr8imv/00ETLomP8AnlZtL1U1SmKeuV/g2avOvG/zzPr/S+S7397yTgafX7/eVKmd7Z8x2cuesUYVIh5kGznCJMKuTVhJgAxGKa4t40gJhN/7JKgDQo7yHAkGkAMZt+/4w/ys4X0P43AUhpCLD44Qb/I4aBgGkAuv7QfWkSfxVFIeTSRJkARGTWgj6egYBpQLEqvHwiH40rZAiwmIEAwVXYCeMPrvNltP8FgDQuBzSZGEAQXjIITgwgCDteBgSAuFQuoMUAOlPnZdL+pyUFDgGGVGN0ps7Opv0fFQEghyHA4m2IYTPEgFx5aSBaYgCtsoNlRgCITv1Te8UAGtfIy6H9T6tKHgIMqdJoXCM7lfZ/bASA3IYAQ2IAjfASQHLEABphR8qYABCjCeXyrBlaDKCyWZ/2yTun9j8dyHsI4EpBdGbWnWeF9V/7Pz4CQGJDgPnNmyp8XXlUMaDyvxUDYi79++vWKzUgwvVfDKDt0t/6nyIBIFIrFsrpxoA6owAxIM7Sf+Vf0/6nK3kPAYa/IAYQSek/za/NxW2+vPa/AJDqEODHmyEGEEfpr7aADtRc/8UA2ij97VQpWhN6A1jWwsb+lJX64H040ztwcM/1rzhU02ADKgeSQcGqu1xHhRw1a83hBaJjCwsLvV5v8oE0c3Gb/piKCuv/4JfjfxJoW4XCfeb1P/rdbL7I9r8AUEu/31+ueOqdPd9qbT32A6zwGKDQDFj6a/9AZ5pa/8WAkjVY+lv/E+UQoKhVKM2LPSjIcUGtPlEV9qt/+odSGSGUcCbA2H/ioCAaf8Wrr//Rx8v5Utv/AkAmZwKMEgOa26KstFH6qx6gY42v/2JACdoo/e026RIAYlenGhYDmtui5HXZ9f/xPWj/E06ZQ4DF/1YMoPuu/+J7mIvbfMHtf+cAZHgmwKjK5wYEPz2g5rkBzhLu4DRf5QIE0d76P/zl+As4wp7ma/1PmglAAhqpwqul+RgGAqYBaXX9f3xXZecuYlD4EGDxnVS4HwOBpAXp+i++q7m4zZfd/jcBKGUIUKcbFMnFgpqaBhSig4t7plI/Qa66Wf9dLCg5HVzc0/qfAROANDRbfJc8Dche2K7/j+9T+584GAKM3ptpQK7Cdv0X3+dc3OaLb/8LAPlfDmgCMSAzHZf+qgEIruP1XwyIVselv90gAwJAMloqeau9/8WAqFQ7yaG9Jo32P1ExBGj2bsWAqFR7OVpc/7X/EyEAFD0EqNkGEAPSLf1rrtE+/iESodZ/MSDd0t/6jwCQmFYrXTEgLaFK/5UfQvuf+BgCrHjnYkBCQpX+0zzEXNy0/4dcBajQywE1e5mIbK4UFL/K1zJqcF32eQ9RCb7+u1JQ/Kd8BN8GYiMAMIYYEKEYSn9I18LCQq/Xa7uGzoAYEKEYSv8MaP8v5hCg7jRSkk6orRvP5Q4KikTlLzJrY+A7eTdz/A+0Z8LbOZ7130FBzar8fAZY/4WNpAgADcuvABIDAoqq9IfUZXAmQMfEgICiKv0zoP2/hADQqeSGAENiQMfiLP21/6GcIcDiBxUDuhRn6a/9nxkBoHmTy6Dg1XAdYkCxpT/kwRCgMjGg2NI/A9r/owSAJAUZAuQRA2IWeemv/Q/FDgEWP7oYUGDpr/2fHwGgFRkPAYbEgHJKf8iJIUB9YkA5pX8GtP/HchnQVC1s7C9XRnd5PbuaFwwNfs3Q4FK5uKf2P8Sjv279cm/JJNb/4T8pvH5N5eKe2v9ZMgFoSwlDgEb6EMUOBHT9IRRDgAbVWZGKHQjo+ndG+385AkDCwp4JMEoMyLX01/6H2IQ9E2CUGJBr6a/9nysBoEVFDQGGxICcSn/IlSFAG8SAnEr/DGj/T+AcgLRFciZAg8eGDqNRTucGVD7QP4b+ivY/xCmSMwGaXf8H/yr4utegOqkm+POg/Z8xE4B2lTkEGDINqNzy1/WBthkCtMo0oM5fYf2vT/t/MgEgebGdCTCqzBiQR+mv/Q8xi+1MgFFlxoA8Sn/t/7wJAK0rfAhQYAzIo/SHEhgCdKOcGJBH6Z8B7f8VCQA5iH8IUEgMyKz01/6H+MU/BCgkBmRW+mv/Z08A6IIhQPYxILPSH8phCNCx/GJAZqV/BrT/pyEAZCKhIUBmMSDX0l/7H1KR0BAgsxiQa+mv/V8CAaAjhgD5xYBcS38ojSFAKOnGgFxL/wxo/09JAMhHikOARGNA9qW/9j+kJcUhQKIxIPvSX/u/EAJAdwwBMogB2Zf+UCZDgODijwHZl/4Z0P6fngCQlaSHAJHHgHJKf+1/SFHSQ4DIY0A5pb/2fzkEgE4ZAqQYA8op/aFkhgDxiCcGlFP6Z0D7fyYCQG7yGAIM1Vk9BzGgThKoU/on2izR/od05TEEaGQJHRTudf7qmv88w/U/wb+ICdZM+iEt6Pf7E2rK3tnzEyr4Mg0WnToL8SADTP/E1in6ByyUkKKFhYVer7fcT+c3b/LWTm79H/zb6V+4+knJThKE9v+sBIAMLWzsL9f2TvcDrKkYMFnhpb/2P6Suv279cm/kktf/af5t4aW/9n9pHAIUgDMBKov5kMqYtw2YkjMBohXzGhvztpVA+78CASBPmZ0JEPlSG9v2VKP9D3nI7EyAyNfb2LanGu3/AgkAYRgC5LHsxrANQLMMAeIXw9obwzag/V+ZAJCtvIcAwZfgzJZ+7X/ISd5DgCHrfyO0/8skAARjCJDocpzZ0g+MMgRIiPW/ZNr/lQkAOStkCNDZ0pzr0q/9D/kpZAgwZP2vRvu/WAJASIYAzWrve+AX33+Wn53AEoYAKWqjTM+19M+A9n8dvgegXOleEzr4J/HwETN4AtUxUKBs1v+Wvjdg8f1kzPpfMhOAzIcAGX+vcAz9+Bi2oVWO/4HlxP/Gz75+ba9zr+sf//4T/xswcgJA0RJ9/0RYc0e4SdNIcZuhM3kfP1DI23/WUr6c0j/7HSDv9299AkDpQ4CEloD42+3xb+FiK26n9j9MFv+bfXItG//2N2Wasr6c0n+q9T/up6KcXbc9AgAJSKiqTnSDgbE0ESFF3rkrEgCiYAiQ7uYluuXa/5D923zAEIAltP8RAIhaBn30DP4EKJxWIqTFe3YaAkAsDAHarpsP7a87tL9umt9Z8ddSjwHa/9CgqN7dYxkCMKT9z4DvASDbt3edOn7Jv/3a/Ob625P3hbchYwsLC71eL/RWACvT/p+SCUBEDAHqb8awhd9sF7+pu43hSdb+h8bF8NaezBAA7X8WMwEghzd24wftTPNY1cYCgz8z8kUWWMIQAOKn/T89E4C4FDsEqPzQbRyy38FDh3qqtf+h2N6kIUDhtP9ZTAAg1Xd1wNK/kc2wlkFaNBchZt6hMxEAolPaEKDCI0ZS+tffpI6fbe1/aFX8qd4QoFja/ywhAJDSWzrC0r/m5lnUICFajBAn781ZCQAxKmEIMOul8SMv/etsajffEqD9Dx2IP9IbAhRI+59RAgBpNP7nUmMUAFnSaITYeFdWIAAkKY8hQGaN/5g3XvsfOhPP+rkcQ4CiaP8zlgAQqYwLsunfzJFUzzVN/1dY5iAJ2o0QD+/HagSAVCU6BCit+o8hA2j/Q8fiD/OGAIXQ/mc5AkC88ivLpnwnx3PkTIOm/6OsdxA/TUeIgXdiZQJAwtIaAkxf/c/lq/sMoP0PQcSf5A0Bsqf9zwQCQNSyKc5U/0PmAJAHrUcIy3uwDgEgbWkNASYrofrv+C/V/oeA4o/xhgAZ0/5nMgEgdhmUaNO8jcup/qf/ey1/EDkNSAjFu68mASB5kQ8BVP+hMoD2PwQXf4w3BMiS9j8rEgASkG6h5j1cn+cQYqYNCd3zvqtPAMhB5EOAycps/7f9t2v/QyTiz/CGAJnR/mcaAkAaUizXHPwzDScDQOo0I6FL3nGNEAAykeIQQPXf0vOg/Q9RiT/DGwJkQ/ufKQkAyUiraPMebpbnE2KmJQnd8F5rigCQj3iGAA7+CXggkPY/RCj+DG8IkAHtf6YnAKQkm9JN9T/KcwJJ05iEtnmXNUgAyEr9IUD9dC7Bt2fF59aTD9FK/e2Z+vZnL/UXKPXtT44AkJi2hwCTjwJqhFZ3wGcmmyESRCj19mTkx4dQ+Oub+vsrNgJAbmIYAhCElwYil/qbNPXtz1jqL03q258iASA9MQ8BVnwPa//XfH7qrJLa/9C21JuUqTeJyfWVTf2dFSEBIEOGAAXyokASUn+rpr79WUr9RUl9+xMlACQpziGA9n/MQwDtf+hG6q3K1FvF5Peapv6eipMAkCdDgKJ4OSAhqb9hU9/+zKT+cqS+/ekSAFIV5xBgAu3/gM+V9j90KfWGZeoNY3J6NVN/N0VLAMhWx0MAIb5Li59tzzwkJ/W3berbn43UX4jUtz9pAkDCEhoCaP8HfMa0/6F7qbctU28bk8frmPr7KGYCQM6cCZA9LwEkKvU3b+rbn4HUX4LUtz91AkDaIhkCeBt3b8rnXPsfQkm9eZl685jUX8HU30GREwAyF8MQwPE/EX4pGBBc6m/h1Lc/aak/+alvfwYEgORFMgQgQtr/EFbqLczUW8glS/21S/29Ez8BIH8xDAEAyG/9TH37E5X605769udBAMiBIQCjtP8hBqk3MlNvJJcp9Vct9XdNEgSAIrQ9BJjACQB1ePYge6l3Q1Pf/uSk/oSnvv3ZEAAyYQjAYtr/EI/U25mpt5NLk/rrlfr7JRUCQCkCDgEAyLgnmvr2JyT1pzr17c+JAJAPQwAGtP8hNqk3NVNvKpcj9Vcq9XdKQgSAghgCAMQp9c5o6tufhNSf5NS3PzMCQFZiGwI4h7W+WZ9D7X+IU+qtzdRbyyVI/TVK/T2SFgGgLIYAAHFKvT+a+vZHLvWnN/Xtz8+qXq8XehsgFnGOLL42vzn0JpAn/bbu+cyFsSxHHVvT9QNCxJTaANC9FLPxQsqhxSFAANCRpCsGIBsCAAAAFEQAAIDuGAIAwQkAAABQEAEAALqT4smOQGYEAAAAKIgAAAAd0f4HYiAAAABAQVb4IrB+vz8Xt/n5+Qk/XdgY+/Ynp3f2pCd8CV+s273437NEtUgSVfu/v259nfuf37xp8i/U/Exccf2vuf1tm/z8JL3xMCvfBAyxh5a8EwvQTQHadkcs8gI6df1169sOeNRseqbFIUDMION3Qja0e6HMo//b7hBb/+PnNWJ6AgAt0rquz3MIJdD+Z0WeZBokADAtrYVUGAJAbLT/6YZXiikJAAAQkvY/U/JU0xQBgKloKqTFEADiof1Pl7xeTEMAAIBgtP+ZiSecRggAtNtOcA5rHXWePUMAiIH2P93zqpF/AJj8tUfeAx3QjQCoRvufCjzt3ehNrCEXFhbmUpZ8AKBtQlS6DAEgLO1/QvHaMZkAQC36EAF58iFp2v9U5smnJgGA1lsITgMI+LwZAkAo2v+E5RVkAgGABjoQWhHdGzznnnlIlPY/NXkJqEMAYFmaB3kwBIDuaf8TA68jyxEA6KL34CigWU3/jGkCQXK0/2mEF4LKBACaaRtYhro067NtCABd0v4nHl5NxhIAqKJCuW8I0N5zJX1BQrT/aZCXg2oEAABoTOrtf6AEOQQAXwbcuMlP2nL9hhX7EIYA01jxWRr7PK/45DsKCGIQf/u/2vpPQCu+KAqhCnpZfw1wJgEAAGKg/Q8kQQCgyfaPIUCQ9v+KPxowBICwtP9piSEAsxIAAKAB2v9AKgQAum7/GAK098wYAkC0tP9plSEAMxEAaJgPifZ4biFa2v9AQgQAArR/DAHae04MASBC2v90wBCA4gKAK4FGZZqPChlg1mfDBzBES/sfctLL/Rqg+QQA6mu2/aNabdZMz6chAERF+5/OGAIwJQGAYAwBBjwPkDTtfyA5AgBttX8cCBTw4B9DAIiE9j8dMwRgGgIAgZWcAUr+2yEPbbf/AdpQSgCQd4O0f7SO6qv8HBoCQHD118DJx/9o/zOWIUAdvTKenHwCwOQLARGKA4GW48o/kDrtfyjNQhaXAMoqABBt+0cGCFX9GwJAQNr/BGQIwGQCALEoJwOU85dCxrT/gXQJAEXrrP0z5V2VUBlP+Tc29eQbAkAQ2v8EZwjABAUFADt6WDJA99U/0BLtf8hSr5haMasA4DzgyNs/02eA/GLA9H9U48+8IQB0TPufSBgCNGshlzOAcwsAxG/6z5WcMsD0f4vPXYif9j+QOgGgUAHbP6VlgBiqf0MA6Iz2P1ExBGCssgKAvTw5SR8OlPTGA2Np/0OueiVVibkFAKcBJNH+mfUhUiyjZ93mtp92QwDogPY/ETIEaMRCRicAzM3NrQm9ARS9Hk3+qButpw/tr5uLXmylP9AU7X8gD7lNAEir/VNhFBDzNKDC5nX5hBsCQKu0/4mWIQClBwC7eGwqfOREGAOqbZKPWwCIQa+w+jDDAOA0gMpC1aPVHjeSGFB5M4I82yIHtHT8T/zt/8ksDtnzEtexkNcJAHkGAFIMuJUXpoAxoM5DR7sQOwoIchXt+k8k7CFFKfEk4N7Z8223UlIUvCSd9bTgxYaFeAdnCdfMGzE8z9WeZCiZ9j8ZsP4vp1de+CkxABQrif275vK0uDpvMAw0NWRI4lN2fn7ecXSQmSTWf4LTIS1HngGg3+87kiHdwrSpFsWSqn2mPNDGYUXxPMmaQDAT7X+yYf2vYCG7EwCyDQCk3v6pczhQzZo+79J/SoYAkJO01n/CMgQoRKEnAVsNkyhP++vWR7ttqf8JcW4VREj7n8x40ZcosybMNgDoX2azc6e7VKW75S4HBNlIev0nCPtM9sf/5BwAyKlIjbaPnvQGx7+FEJz2fx7mN29a8ZjSaX4nG+W89Cyn3ABQTsCd8JemWFXHvM3xb+ESkzfVEABSl836X9msZX05MWDyDqBGyl7OAcBRQLmKsMiOcJOAmvJu/2evTilfTgygzON/Mg8A5N3+iaHdHsM21GQIALnKeP3vpnzPPgYYApSs6MuAutZVZktYZyt13p+dgPZ/otr4FBjcp2U/S72CQ07mE4DCjwIqtv3TqvyeOkMAyE9p63/b3fpcpwGGAGUe/5N/AFhR4Tt3NrpcmnP9GACGtP8TYv2nml7ZFWDpASBjhbR/Qi3HmX0MGAJATqz/WT5uSwwBypR/ACj8KKCMxbAEx7ANQLO0/+MXw9obwzbQnoWsj/8pIgCsKMt0m3f7J7ZlN7btqcYQAPJg/S95e6opcAjQy/GPmknRVwEiOTGvs64UARnQ/o+W9R8aVMQEYMWjgDILglm2f5rqsrT9+Zp0N8gQAFJn/Q8ole0cq6ghQG+lPyf7439KCQAkrcHSf5rqv5GTRpL+GIBiaf8Xvv438hJY/0lCKQGgnFOBM2v/dLn0D/X/Wc3HTfEzwBAA0mX9r7/+D36/fhLIb/3PbAhQePvfOQA/5luBY1N/9az/gg4yQJ2q14GhkArt/3jEsP4P7qFO1Wv9j1M5SWYyASArebR/Ylj6S44B/XXrJ7wE8/Pz5czTICHW/zbW/9JiwOT1X6s0JwUFgH6/P7mGs2cHF9vSX3IMgKK03f6fzEdP5Ot/aTEgY07/LTEAlCz+RSfmpb/AGDC5CQTMKuAbKvLVJqH1v5AYYP0vRCknAZdwPdBEN77+BRMaOWFrJvVPEU76MhFOBSYzGbT/rf+dqf+ISa//ie5pA9r/i5kA5C/aZkMqXZ8ypwGaQNAU7f/81v+8pwHW/xKUNQHI+HqgaYXyFLs+yylzGmAIQDa0/zuW0/pf5jQgrf1tegsltf9NAPI/FTi27kLqXZ+ipgGaQFCf9n/263+W04D81v9cc0tlAkAOktitc136s48By3E9UDKg/d+NEtb/LGNAIa3SMpUYAMq5Hmgk60gJS3+uMSC/JhB0Sfu/tPU/pxiQ0/rv9N9RJQaAzMTc/ilt6c81BizHEICkaf+3quT1P6cYkH2rtFiFBoAShgBhF46Sl/7MYkBOTSDoUrHtf+t/NjEgj/Vf+3+sQgNANiJs/1j6Rw3b5JWTQPCPgeUYApAo7f82WP8n/EWVX69o1/8MWqUlKzcA5D0ECLJSWPrbHgiE+hjIowkEXSqt/W/9b3sgYP2vRvt/OcV9D0BO4mn/5HRd5/i/OiC260b7TgCSo/3fIOt/l39sbOt/PPthS6tBxsqdAGQ8BOiyQ6DrU8g0IPUmEHSpkPa/9b+QaUC6638G+aQ9RQeAaUSbAYLv1vVbPs1tS8LSigHLboYzAUiH9n991v8CY0DGZVKv1yvwQKDSA8CKQ4DkdLAWWPrLjAHpNoGgS3m3/63/ZcYA639+nAOQQK8lnk2qefRhUQd6lnZuQGZBmlxp/5e5/vfOno/wozybcwMifG5n3aReeWcClD4ByGwI0N6nl65PZ2KeBmgCwWQT3iBtL4PW/1Rq00SnAdb/zJgApLeCdLwxSXd90pXiNCCbIE2uwrb/G2H9z6nrn9M0IKqnutrG9AobApgA5DMEaPzTK+muTx4inAZoAkEJ7f+k1/+oitGcpgHW/5yYAPyTFbutkSwo3WxG0l2f/CQ0DcggSJMr7f8S1v90u/4ZTAMieebrbEavpCGACUAO17pq8NMr6a5P3uKZBmgCQZbt/6TX/0iqz+ynAZGv/3nvBs0SAFI6EKjVPTvppb8cw1FAtX21gwvG+U4AIqT9n/H6X07NN3yeq/3JHaz/MfdJpwwwvWK+E0AAyGHnrvl+TnrpL1adgUD9j4HIm0DQsXTb/0mv/+WU/g0OBDJe/4vdH6pxDsD/I+bOZUt7drrHelLz9ID2VvDIJ2mURvs/v/U/v2P9O34J2lv/Y35dBm/2Fd/yvTLOBDABSH4IUPnTq+bSX/nfEs80oE4rKNomEHQsxfZ/uut/zPVlWtOAzNZ/O8asTACWmqaf2v1+1uwj1rksgK5/ftOANi4TYQhAEgps/6e7/uv6t/HStLH+x1kjLX6z91N447fNBCDJs4Er78Tpdn2IcBoQYRMIOp7mJ9T+T3f9V/dHOA1Ia/2f9c3SK+BUYAEgkwOBMl76SeWgIEhLOft5uut/U6X/4LVOqGBN7qCg5HaSflIBpg0OAUrgQKDlHmjKd2m6A1/iPyhowk6YyhiNjGXQ/i92/W/qgJ/+uvXJVbSpHBQ04YkNXiAtVm0H6OV+KrAJQA4HAi2nzrrf9LYQjGkAjMp+x053/W+261+40qYBoyb8Cf2yhwAmALV0kHGrtX8qd320/HPV3jTAEIA4Fdv+T3f91/VPbhoQdgjQ9kP0sh4CmADUHQLEdjJAul0fOmAaABnvyemu/7r+HchsGtDIwT/9gocAJgBRnwwwU/sn3a4PqU8DDAGITWnt/3TXf13/1KcBQYYA7R36X84QwAQgB+l2fQjINIAyZbbrprv+N1X3N7EtxclsGlBHv9QhwKoVviO9UpswP9MUSY0vptO0f9Jd+gOavOQVu89Xa9VPuTcW+6xG/srmeqHrFT7XatcukbT/013/Q5X+Kz5jwZ+Z5K6kGeQLMRpv/8+vuGPkuFSaAKR6MkC6Sz85DQTy6waRtzz21XTXf13/nAYCQdb/Ng7+6Rc5BHAOQJMaPNxtQvsn3WM9yfX0gME+6UwAYpD30f9Jr//1PyId6N+qajvJiut/B6VR23o5nglgApDY1wJUXvpb2BayVWcaANFKvXZMd/1vpPRvaFtocRoQg2q7Sr+8IYAJwAw6uyJQgxk3hq4PpV0saKwY8jPZy7j9n+j6X/8iP7r+QTS783RWGrW3q/SyGwKYACR/MsByYtgGSr5YEESlqCIyhvVf17/kiwU1roPqv1/YEMAEoBV13i3132kxdH3ITCPTACmCVgVs0cXT/o9h/df1z0wjO1XYuqgRvbyGACYAqZ4MMFbwdZ+8mQaQqEaqyci7gzGs/7r+GYtnGtDentMvaQhgAhDXyQCV31oxdH0oRJ1pgPBAS0pu/8ew/uv6F6LOztZeXdTZntPLaAhgApD8yQDB133KZBpAKjJu/8ew/uv6F6izaUD31X+/mCGACUC7Znp7zPpeiqHrQ+EqTANkBhpXYPs/hvVf179wFXbCVouibvRyGQKYALR+MkDjc4Dgiz4sYRpAtDJr/0ey/uv60/Y0YMo7bGNH6pcxBDABqGXK3uc0+/E0vxNDywfqTwNEBRpUSPs/kvVf15+a+2dTFVHAGNnLYghgApDGHCCGdR+mMcwAqnyCy6P9H8n6n3TXP/iLWIjhvtrBRT9b3Z36BQwBTACimANM+FEkXR9odiAgHtB2K67tcrOD9n8k63/SXf/5zZuyr+QiNHnXrVYOLdbB7tSf+BAZDAFMAOIVw7oPNTk9gKSFqh0jWf91/cn4qwMKZwIQfggwemMkXR9odRogFVBTlu3/SNZ/XX+aMnaXnrIcGquz/aqf9RDABCCukwFiWPehJaYBpKXjIjKS9V/XnyDTgNiq/+yZAASeAwz/dyRdH+hyGiAMUFlO7f9I1n9df9q2eFcfWwtN1v3e1c93CGACEH4OEMO6Dx0zDSBy3VSTkaz/uv4EnAZEW/3nzQQg8BwgktUfgpj1W4Qhm/Z/JOu/rj9JnCIcsPrvZzoEEABi/4IwADpWQlmp9Ce4+Kv/jAkAbZEBANqQR/s/IKU/MUio+u/nOARwDkDyXxIMQIMyri/r1/1z4WT8uhQooeo/VyYA7TIHAGiQ9n+Qrn/Aln+DXf+FhYUmNocSq/9+dkMAE4BYmAMABJdfm1nXX+kfFR3PSAgAsRwI5LpAAJNp/89E6a/0T3eHjKr9P9Bft37Cbtnr9dLa2QSAuDKAUQBAKNm0/5X+Sv/YpF7958c5ADFe79yADGAJ7f9pONZ/UPqr/qOSTfXfz+hMABOA7pgDAEQr9fa/rr+uf5yyqf4zIwAEmANMf0qADACg/T+Z0l/pn8HOmUrp38/lTAABIPbTguP/7AFIXaLtf6W/0j9m+VX/OXEOQOynBDgfACic9v8ox/o71j9yGVf//SzOBDABCMblQQFikFb7X9df1z9yDvpPgglASC4NBDCZ9v+Qrr+uf/wKqf776Q8BTAACc2kggICSaP/r+iv6k1BI9Z8HASC8WTNAhH0pgDZo/yv9lf5JmHVHzaD67yd+OSABIL0MYBQAkH37X+kfef1EydV/BpwDkOT5AE4JALJXbPvfsf4O9E9IydV/P+UzAUwAUv2aMIcDAWTW/tf1V/cnpOTSPwMmANExCgAorf2v66/rnxbVf+pDABOAGDklAKCQ9r+uv7o/Oar/DAgA+WQAhwMBeSik/Z906d9I9a/0T06FnTb4jtq2fpqXAxIA8jklwCgAIIn2v9I/zpKIyTT+cyIAxM4oACCb9r/SX+mfIo3/OkOAODkJOMPTgp0ZDKQr5tPmakr3NN9GzvR1mm+iVP9ZrmkmADkfDmQUAGSjqZJiuSq21dWyZuk/F5Suf7GU/hkPAQSAnA8HEgOAtMTZKgtS+sdQSCn9i1Vtv41hp41TL75TgQWA/DOAk4OB1KXY/lf6N7QtdE31X8IQQAAo4nAgowAgftm0/5X+DW0LXVP6lzMEEACKGwWIAUBaEmr/K/0b2ha6lvSuG49+OkMAAaC4UYAYAEQo9fZ/0vWT0r9kSe+6aenFNAQQAAodBTgxAEhC/O3/pOsnpX/hkt5749RPZAggAOTAKABIWqLt/6SLJ6V/4ZLee9PVi2YIIADko84oQAwAIhRt+z/p4knpX7ikv5UiCf0UhgACQFYqjwLEACCUtNr/Sv+GtoUAlP4x6MUxBBAAMlR5FCAGAPGIrf2v9G9oW0is9I9kH05LP/ohgACQpzqjgMUrhSQAtCqJ9r/Sv6FtIbG6P5J9OD+9CIYAAkDOasYAAwGg8Pa/0r+hbaFrSv/g+nEPAQSA/IkBQJxibv8r/RvaFtIr/RfvRTHsz1nqhR4CCAClqHNiwIDjgoAS2v9K/4a2hSTr/iXEgFyHAAJAQeqPAgYMBIAs2/9K/4a2hRxK/8XEgPyGAAJAcZqNAZIAkEH7X+nf0LaQVd2/hBiQ0xBAAChUUzHAQABIuv2v9G9oW8i59F9MDMhjCCAAFK3xGCAJAKm0/5X+DW0LSdb9gx2gchQXA1IfAggANBkDJAEg/va/0r+hbSHJfv/iHUAMKHYIIADQSgxYsmYJA0AM7X+lf0PbQpIH+Sy3A4gBBQ4BBADGxIBmk4CxABBD+79aURVDWVOzdFD3p6Ljun/sr4kBhQwBBAA6GggMGAsAQdr/FcRQyij9s9fqGb0VdgAxoJAhgABAgBgwIAxAaYIf/T+lGMoXpX/GOriMT80dQAzIfgggABDsuKAJq6E8AEWJp/0fQ8mi9M9PZxfubPbVFwMyHgIIAMQyEFhMHoD8xNz+j6RGUfpno/tL9bf36osBWQ4BBABiHAhMs5JKBZCHsO3/SOoSpX+6wn4tV2cvvRiQ2RBAACClJDD9miseQFQibP9HUoso/eMXtsSP6nUXA7IZAggAJJ8EUlmvgUja/5HUH0r/2MT/wRHJiy4GZDAEEADIPAkAwcXT/o+k5lD6k8ErLgYkPQQQAGiFJABE1f6PpM5Q+pPZyy0GJDoEEADoKAkIA1Cm4O3/SGoLpT8Zv9BiQHJDAAGA7ggDQJft/0jqCaU/hbzEYkBCQwABgDCEAShBqPZ/JDWE0p8CX1wxIIkhgABAXGFAHoAStNf+j6RuUPpT+GsqBkQ+BBAAiD0PiASQqI7b/5HUCkp/vI5DYkC0QwABgCQjgVQA6Wq8/R9JfaD0L5MXbkViQIRDAAGArFLBkHgAJbT/I6kJlP558wI1+zRWWxwyjgFBhgACAGXFg8nBYHKoAOpr8PM7hlJA6Z8WT3jqA4H8YkA/0BBAAAAgt2v/d0DpD3WIAWGHAAIAAB3J4wNb6Q9NEQPmAg0BBAAAmpRx+1/pD20QA7ofAggAAHQh6U9opT+0reQY0O98CCAAANCY/Nr/Sn/oUskxoMshgAAAQOtS/EhW+kMoBcaAfrdDAAEAgGZk0/5X+kMMCowBnQ0BBAAA2pXQZ7DSH2JTTgzodzgEEAAAaEDq7X+lP8SsnBjQzRBAAACgRfF/6Cr9IRXZx4B+V0MAAQCAQin9IUXZx4AOrO7iQQDI2nKfxNF+ys5v3lSn+l/4kUa3COjubThfbwVo1YRls8EjLU0AACiIrj/kxDSgGhMAAIpo/+v6Q64ymwb02x8CmAAAkLmadX+j2wK0xTRgeiYAAGTb/q/T29PyhxTlMQ3otzwEMAEAIE91Sv+mtwVIaRrQj6OF0R4TAABya/9XbuPp+kNOKr+j5yMYBbQ6BDABACAfuv5AU9OA+XxPDDABACCH9r+uP5DZNKDf2hDABACAtOn6A1MyDRgwAQAg1fa/rj+Q9zSg384QwAQAgPTo+gM1LRQ8DTABACCl9r+uP1DUNKDfwhDABACANOj6Ay1Z+OdVYtaSOtFpgAkAALG3/3X9gW4sVFo02p4GND4EMAEAIF66/kAqpwfMpzMNMAEAIMb2v64/ENZCTNOAZocAJgAAxEXXH4jHQo7TABMAAGJp/+v6A3FaiGAa0OAQwAQAgPB0/YH4LeQyDTABACBk+1/XH0jLQrhpQFNDABMAAMLQ9QfStZDyNMAEAICu2/+6/kAeFjqfBjQyBDABAKA7uv5AfhZSmwaYAADQRftf1x/I20JX04D6QwATAADapesPlGMhhWmACQAAbbX/df2BMi20PA2oOQQwAQCgebr+AAuxTgNMAABosv2v6w/QwTSgzhDABACAZuj6AyQxDTABAKBu+1/XH6D7aUDlIYAJAADV6foDJDcNMAEAoEr7X9cfIPg0oNoQwAQAgNno+gMkPQ0QAACYtv2v9AeIMAYstzj3er2xy68AAMBUKlT/6n6AbmLATJwDAMCPzfrBsxwH+gPEsH6OXdVNAABokrofINQ0YEomAAD8k5qfNLr+AM1qZF0dXdtNAACoS90P0MEa29RAwAQAgOqfK7r+AJ2pvOQuWeFNAACoQt0PkOjpAataOrcAgIQq+Jk+C5T+AJGotnqbAAAwLaU/QAbTAOcAAJRumk8Ox/oDRGvKJXq42psAADCJuh8gs2mACQBA0SZ8VOj6AyRn8tI9WPNNAABYSt0PkPE0wFWAAAq1sLAw+hGg9AfIjG8CBmA8pT9AIdMAEwCA0in9AQoxqPxXbdu2LfSWAAAAHXEVIAAAKIgAAAAABREAAACgIAIAAAAURAAAAICCCAAAAFAQAQAAAAoiAAAAQEEEAAAAKIgAAAAABREAAACgIAIAAAAURAAAAICCCAAAAFAQAQAAAAoiAAAAQEEEAAAAKIgAAAAABREAAACgIAIAAAAURAAAAICCCAAAAFAQAQAAAAoiAAAAQEEEAAAAKIgAAAAABREAAACgIAIAAAAURAAAAICCCAAAAFCQNaE3ALqzdevWG2644brrrvvSl75022233XHHHQ8++OCWLVueeOKJtWvX7rLLLvvvv/+BBx54xBFHHHXUUccff/whhxwSepMBABq2atu2bU3fJ8Rl69atH/rQh973vvddffXVjzzyyPT/8LDDDnvZy172yle+8rDDDmtzAwGY2UUXXTTT769atWr16tXbbbfdjjvuuHbt2t13333vvffeb7/91q5d29o2QqQEAHL20EMPvetd73r729++adOmOvdz+umnv/nNb37Ws57V3KYBUMuqVasauZ+DDjroyCOPfPazn/385z//ec973q677trI3ULMBACyddFFF/3Wb/3W3Xff3ci9rV69+nWve93b3vY2nw0AOQWAxXbccccXvehFL3/5y1/ykpdsv/32jd8/REIAIEPf//73X/WqV11++eWN3/PTnva0yy+//GlPe1rj9wxA8AAwdOCBB5577rm/8Ru/4QAhsiQAkJsvfvGLp59++te+9rUJv/OTP/mTxxxzzBFHHLHPPvvstttuDz/88A9+8IPNmzffcsstn/nMZzZv3jzh3+6xxx4f+9jHjj322Ba2HYAoAsDAwQcf/Pu///tnnXVW2w8EHRMAyMr1119/0kkn3X///WN/etBBB/3ar/3ay1/+8ic/+cnL3cO2bdtuueWW//N//s/73ve+Bx98cOzv7LHHHtdcc82zn/3s5jYcgOgCwECv13v3u9+91157dfNw0AEBgHz83d/93QknnDC2+t99993f9KY3/eZv/ub0x3Ted99955133jve8Y6x75GDDjroxhtv3H///WtvNQCNBYDJVc0Pf/jDxx9//KGHHnrwwQc3bdr0jW984x/+4R8++9nP/vVf//VynaOBpzzlKVddddXhhx/exIZDeAIAmbj99tt/+qd/+gc/+MHoj376p3+63+9Xu6j/1Vdf/YpXvGLsmcQnnnjiX/3VX1XaWAACBIDlPProo5/4xCf+5E/+5EMf+tATTzwx9nfWrVv3kY98xPGf5EEAIAcPPfTQcccd94UvfGH0R2eccUa/399hhx0q3/mtt976/Oc/f2y0eM973vPqV7+68j0DEEMAGLrlllv+w3/4D8s1d/bcc89rrrnGJaHJgABADl71qlf92Z/92ejtp59++qWXXrpmTd1vvP7sZz/7r/7Vv9q6deuS2/fbb7/bbrttl112qXn/AMQQAAb+5E/+5Nxzz3300UdHf7T//vt/7nOfc/wnqVsdegOgrquvvnps9X/UUUddeOGF9av/wUFEb3rTm0Zvv+uuu9797nfXv38A4vHa1772E5/4xB577DH6o+9+97vz8/OPP/54iO2CxpgAkLatW7ceccQRX//615fcvvPOO3/+858/7LDDmnqgxx577JhjjrnllluW3P6Upzzlq1/96urVsjRAJhOAgc985jM///M//9BDD43+6A/+4A9e//rXN/VA0D1VC2l797vfPVr9z83NvfWtb22w+p+bm9t+++3PO++80dtvv/3266+/vsEHAiAGz33uc9/73veO/dF55513xx13dL5F0BgBgIQ9/PDD559//ujthx9++DnnnNP4w734xS8+6KCDRm+/7LLLGn8sAII766yzzj777NHbH3zwwbGfPpAKAYCE/eVf/uVdd901evt//a//dbvttmv84bbbbrvXvva1o7dfe+21jT8WADH4b//tv61du3b09ve+971jP4AgCQIACXvPe94zeuOhhx764he/uKVHPPXUU0dvvPnmm7ds2dLSIwIQ0MEHH/wf/+N/HL39kUceueCCC0JsETRAACBVt95662c/+9nR21/3ute1d0ruUUcdtX79+iU3Pv7441/+8pdbekQAwvp3/+7f7bjjjqO3v//97w+xOdAAAYBUXX755aM3rlq16qyzzmrvQVetWnXCCSeM3v7Vr361vQcFIKA99thj7Pj3H38kxBZBXQ1cIh2C+PCHPzx643HHHXfAAQe0+rhnnXXW6GXmdtttt1YfFICAfumXfunSSy8dvf3qq68+4ogjQmwR1OJ7AEjSgw8+uOeee45+Fcub3vSm3/3d3w20UQDk8z0Aiz366KPr1q0b/U6Al7zkJR/84AfbeERolUOASNJNN9009osYn//854fYHABytsMOOzzjGc8Yvf3zn/98iM2BugQAkvT3f//3Y28/+uijO98WAPI39vPlG9/4xgMPPBBic6AWAYAkffGLXxy9cb/99tt7771DbA4AJQaAbdu2fe1rXwuxOVCLAECSvv3tb4/e+JSnPCXEtgCQvyOPPHLs7d/5znc63xaoSwAgnwCw//77h9gWAPK35557jr39u9/9bufbAnUJACTpe9/73uiNo1/RBQCN2H333cfefv/993e+LVCXAECSRq/FNjc3t3bt2hDbAkD+9thjj7G3P/zww51vC9QlAJCkRx55ZPTGnXbaKcS2AJC/5SYAW7du7XxboC4BgCT98Ic/HL3Rt9oB0JKxXz4zNze3/fbbd74tUJcAQJJ23HHHKccCAFDfcp1+w2dSJACQpLGH+489MQAA6lvuC7923nnnzrcF6hIASNJuu+02euOmTZtCbAsA+bv77rvH3r7ffvt1vi1QlwBAkg444IDRG++6664Q2wJA/pa73v+BBx7Y+bZAXQIASRq74N5+++0htgWA/H3lK18Ze/uTnvSkzrcF6hIASNKTn/zk0RvvvvvuH/zgByE2B4DMfelLXxq9cf369Q4BIkUCAEl65jOfOfb2L3zhC51vCwD5u+GGG0ZvPOqoo0JsC9QlAJCk5dbcT3/6051vCwCZu++++2699dbR24877rgQmwN1ral9DxDAkUceuccee9x3331Lbr/22mv/y3/5L60+9L/9t/92yfVGd9hhh/e///2tPigAAX3kIx8Z+0VgJ554YojNgbpW+fJUEvXSl770sssuW3Ljdtttd9ddd+2zzz4tPejXvva1pz71qUtuPOSQQ77+9a+39IgAjLVq1arRG1uqanq93iWXXLLkxj333POee+7xTcCkyCFApOpFL3rR6I2PP/74pZde2t6DfvzjHx+9cTQSAJCNe+655/LLLx+9/cwzz1T9kygBgFS99KUvHbvy/vEf/3F7D3r11VeP3viMZzyjvUcEIKx3vvOdjz322Ojtv/IrvxJic6ABAgCp2meffU466aTR27/whS9ce+21bTziww8//IlPfGL09uOPP76NhwMguO9///t/9Ed/NHr7scce+9znPjfEFkEDBAAS9trXvnbs7f/5P//nNh7uwgsvvPfee5fcuP3227/gBS9o4+EACO4Nb3jD/fffP3r7f/pP/ynE5kAzBAASdvLJJx999NGjt3/mM5+5+OKLG3+4d73rXaM3nnDCCXvttVfjjwVAcFddddWf//mfj95+/PHHn3baaSG2CJohAJC23/md3xl7+2/8xm9873vfa/CBLrnkkptuumn09l/91V9t8FEAiMRtt932y7/8y6O3b7fddu9617vGXoMIUiEAkLZf/MVfHHsEzqZNm375l3/5iSeeaORR7r333nPPPXf09kMPPfSMM85o5CEAiMcdd9xx4oknbt68efRHb3zjG30BMKkTAEjeO9/5zrGXA/roRz/6hje8of79b9u27dd//de/+93vjv7obW9723bbbVf/IQCIxy233HLcccd94xvfGP3Rz/7sz775zW8OsVHQJAGA5B155JFve9vbxv7of/yP//HGN76x5v2fc845F1100ejtP//zP9/r9WreOQDx2LZt27vf/e7nPOc53/72t0d/euihh/b7fX0fMuCbgMnBtm3bTj/99CuvvHLsT88666w//dM/3WWXXWa92y1btvzmb/7me9/73tEfrVu37uabbz7ooIMqbS8A0X0T8DXXXPPGN77xxhtvHPvTfffd97rrrjv00EMr3z/EQwAgE/fff//P/dzPjT1Pd9C2+cM//MNTTz11+jv81Kc+9apXveq2224b/dGaNWs++tGPnnDCCTW2F4AoAsCXv/zlK6644i/+4i9uueWW5X7nkEMO+fjHP+5738mGAEA+7rnnnuc973lf/epXl/uFY4899txzzz3ttNN222235X7n/vvvv/LKK9/xjnf87d/+7dhfWL169QUXXDD20hAAhA0AGzdunPBPHn/88UcffXTLli2bN2++6667brvttr//+79f8ZJxz33ucy+99NL999+/9iZDLAQAsnLPPfecfvrpy9XuAzvssMNznvOcZzzjGU996lP32GOP7bfffvOPfOc737nhhhtuueWWCdcO2n777S+44IKXv/zl7Ww+ANPq4EKcq1evfv3rX//Wt7517KUmIF0CALl5+OGHf+3Xfu39739/4/e87777Xnrppccff3zj9wxAbAHgZ37mZ/73//7fxxxzTKuPAkG4ChC5Wbt27fve977LLrtsv/32a/Buf+mXfunWW29V/QNk77jjjrviiiv+9m//VvVPrkwAyNaWLVve+c53vv3tb//+979f535e+MIXvuUtb3nOc57T3KYBEN0E4MgjjzzjjDNe8YpXHHnkkc3eM8RGACBzDz/88GWXXfa+973v2muvfeyxx6b/hz/5kz/5kpe85JWvfOXTnva0NjcQgI4CwOrVq9esWbPTTjvtsssue+655/r16w8++ODDDz/86U9/+nHHHbfvvvu2s6UQHQGAUmzZsuX666+/7rrrvvzlL992223f/e53H3zwwS1btmzbtm3t2rW77LLL/vvvf9BBBx1++OFHH3308ccff8ghh4TeZACA5gkAAABQECcBAwBAQQQAAAAoiAAAAAAFEQAAAKAgAgAAABREAAAAgIIIAAAAUBABAAAACiIAAABAQQQAAAAoyKperxd6GwAIYGFhIfQmABDAmhAPCgAAdG3Q+hcAAAAgc4uP+hEAAAAgW6MH/AsAAACQoeXO9RUAAAAgK5Mv8yMAAABAJqa5wqcAAAAAyZv+4v4CAAAAJGzW7/USAAAAIEnVvtJ3hQDQ7/erbg/EaH5+fsJP7fCUts8DUFTpP2ACAAAARZT+AwIAAAAUUfoPCAAAAFBE6T8gAAAAQBGl/4AAAAAARZT+AwIAAABkVfqfv66/YfOyV4ETAAAAIJ/Sf8XfEQAAAKCI0n9AAAAAgCJK/wEBAAAAiij9BwQAAAAoovQfEAAAAKCI0n9AAAAAgCJK/wEBAAAAiij9BwQAAAAoovQfEAAAAKCI0n9AAAAAgCJK/wEBAAAAiij9BwQAAAAoovQfEAAAAKCI0n9AAAAAgCJK/wEBAAAAiij9BwQAAAAoovQfEAAAAKCI0n9AAAAAgCJK/wEBAAAAiij9BwQAAAAoovQfEAAAAKCI0n9AAAAAgLkSSv8BAQAAgKL1iin9BwQAAAAK1Sus9B8QAAAAKE6vyNJ/QAAAAKAgvYJL/wEBAACAIij9BwQAAAAyp/RfTAAAACBbSv9RAgAAABlS+i9HAAAAICtK/8kEAAAAMqH0n4YAAABA8pT+0xMAAABImNJ/VgIAAABJUvpXIwAAAJAYpX8dAgAAAMlQ+tcnAAAAkAClf1MEAAAAoqb0b5YAAABApJT+bRAAAACIjtK/PQIAAAARUfq3TQAAACAKSv9uCAAAAASm9O+SAAAAQDBK/+4JAAAABKD0D0UAAADyV7nWXFhYaHpbUPoHJgAAAFQsVcWDWSn9YyAAAAA0Wc5KBW3U/Ur/BgkAAADtFrslRwKlf4QEAACATovgQvKA0j9aAgAAQLDKOMswoPSPnAAAABBMZmFA6Z8EAQAAIApJhwGlf0IEAACAeOvp+JOA0j85AgAAQLxiTgJK/0QJAABA6RY2LluD9s6en4tDVElA6Z80AQAAoEo2CBUPwiYBpX8GBAAAgCbjQWepoOMkoPTPhgAAANBiKuggDwxK8/ZiQP3SX90fFQEAACCHPNDGQEDpnyUBAAAgTB5oKQw0MhBQ+mdMAAAAyDAMVI4BSv/sCQAAABGFgWaTwEzHBSn9CyEAAADkPxaYPBBQ+hdFAAAAKGUsMBoDlP4FEgAAAMpKAo1c0V/pny4BAAAgsSQQ5BuIF1P6J00AAABITEtnDE9D6Z8BAQAAIFVdDgSU/tkQAAAA0tb2QEDpnxkBAAAgE40PBJT+WVodegMAAGjSwsb+4i8TqEz1nysTAACADNU/LmjD5v//H4oB+TEBAADIWc2BwCAGkBMBAAAgf3ViwIbN82JATgQAAIBS1IwBTW8OYQgAAABlqRwDjALyIAAAAJTIKKBYAgAAQKGMAsokAAAAFK1ODGhhc2idAAAAQMUYYBSQIgEAAIB/YhRQAgEAAIAGRgHtbA7NEwAAAGggBjgcKBUCAAAA4xkFZEkAAACg4VFAa5tDAwQAAABW4HCgnAgAAACszCggGwIAAADTkgEyIAAAADADGSB1AgAAAO0eDuSUgKgIAAAAVGEUkCgBAACAimSAFAkAAAB0ejhQm5vDygQAAADqkgESIgAAANAAGSAVAgAAAAEOB5IBQhEAAABokgwQOQEAAICGyQAxEwAAAAicAcSALgkAAAC0wmnBcRIAAABoiwwQIQEAAIAWyQCxEQAAAGiXy4NGRQAAACC6UQDtEQAAAIgrAxgCtEoAAACgOzJAcAIAAACdkgHCEgAAAOiaDBDQmpAPztzc/LzdOiJeju71+04Io1C9Xi/0JvBjvbOt/2GuCzTNM79h8/z563xYNMkEAACAMMwBghAAAAAIRgbongAAAEBIMkDHBAAAAAKTAbokAAAAQEEEAAAAwjME6IwAAABAFGSAbggAAADEQgbogAAAAEBEZIC2+SbgHN4ATG/yNw56wtvg+zWhAstR46z/aa3/U35JMNWYAAAAEJ1pUpkhQDUCAAAAMZIBWiIAAACQMBlgVgIAAACRcnpGGwQAAADi5UCgxgkAAABETQZolgAAAEAOZIApCQAAAMTOyQANEgAAAEiAA4GaIgAAAJAGGaARAgAAABREAAAAIBmGAPUJAAAApEQGqEkAAAAgMS4KVIcAAABAhgwBliMAAACQHgcCVSYAAACQJAcCVSMAAACQLUOAUQIAAACpciBQBQIAAAAJcyDQrAQAAAAyZwiwmAAAAEDaDAFmIgAAAJA/Q4AhAQAAgOQZAkxPAAAAoIgMYAgwIAAAAFCKDTKAAAAAQDYcCDQNAQAAgIJsKH4IIAAAAJAPQ4AVCQAAAJRlQ9lDAAEAAICsGAJMJgAAAJAblwSdQAAAAICCCAAAAGTIEGA5AgAAABREAAAAIE+GAGMJAAAAUBABAACAbBkCjBIAAACgIAIAAAA5871gSwgAAAAUbUNhRwEJAAAAUBABAACAzDkVeDEBAAAACiIAAACQP0OAIQEAAAAKIgAAAFAE1wMdEAAAAKCgo4AEAAAAKIgAAABAKRacCiwAAABAUQQAAAAKslD8qcACAAAAFHQUkABALb2zM3+HRM7zD4Ri/QnL808da2r9a/jnNcg0rWOWfiA4638Q1v9GLGzsl/xMmgBQy3Dd7509X/IbqUuLn2qfu0Ao1v/uWf+7tCHro4BMAGiSblCrfMQC0bL+t8r634aFgocAAgDNv398DDRrueXJMwyEZf1vm/WflggAtMWYsr5iOxNA0qz/9Vn/Y7Bh8/z56/Lch50DQAMmL/EOD61gxSfNxyoQA+t/46z/XVoo9ck0AaAj5sJT8mEJZMb6PyXrP50xAaAZU67sukGNPDk+R4F4WP/rs/5Ha0Om1wIyASAA3aAlfCgChbD+L2H9D26hyGsBCQAEewv5GKi24pT8jAFxsv7PyvpPWAIAgZX5MVBgswFgCes/SdiQ47WAnANAkyqv4+UcG1rzLy3tkxJIhfV/RdZ/4mECQETyvnR0IZ9wABVY/wloobzTAEwAaFgja3dmDaGm/pwsPxeBbFj/R1n/iZMJAPHK4PDQnD7GADpj/ScqG7I7DcAEgOZNWLIrrOaJdoMqbPbkJyfpD0KgEBNWqgr1Uznr/+Qnx/rfgYXCnmQTADrVO3t+8B6bdXFMpRtU58puKX7OAczaQ531m5XyXv+rPSdQkwBAGPnFABd1BphGfjGgTukPQTgEiFZMWKMXL5QLG/sZHBRUbXuW/O2T7yHOzzyAmdarxUX/+ev6GRwUVG17lvztk7OQ9T8SG/Ka0pgAEF660wBdf4AypwG6/vlZKOlioAIAAd5IwzMBmooB3X8SNFv6a/8Dhaz/Y6+mUicGpLL+L1f6a/8ThABAJvm7s4ZQ5faAdRxggvPX9asdZRH/+q/xT2wEACIaAgz/VeV1tr2Pgfa+v137H8jPrEOA+pfEiXP9n1z6a/+nZUNG3wYgABCpeGJAe6U/ADHHgPZKf+K0UMxpAK4CRBSXA5rwzyuv4/UvFlHnHqbccu1/oPDLAS2n2mWCYlj/p9xy7X8CMgEgAd1PA3T9AcqcBuj6UwITAGIfAnQ8Deig67/4sSbfW7XNAMhjCNDxNKCDrv+Q9j9hmQBQ3DSgzi9M3ioAYp4G1PmFyVtFITbkch6wCQApDQEW32EkNXflLdH+B0rQ1BCgkWlAsypvifZ/zBbKeP5NACh0GtDUowOQ1jSgqUeHdJkAkOoQYPE9d1yL139E7X+gHI0PAQJOA+o/ovY/MTABIBPdTAMszQBlTgN0/cmJCQA5DAGmeYh47lz7HyhNe0OAbgr0pu5c+59ICADkpo0jguI55xiALo8IiuecYzqzMPETP9SZJ80SAIhFs0fvNFWyN176F/Id4wDTa7aiaqpkb7z0z6NwJA8CAJ1K6GzdIF1/cwYgVx2vb3XK9yBdf+s/XRIAiEhL3fFZS/n2Sn/tf4Auu+OzlvLtlf7a/0RFAKBrk2vr9krkacr6Vrv+K/5p2j9A3kIdWj1NWd9q13/FP836T8cEAAAAKIgAQEFDgIC0/wEKub7KEtr/REgAAACAgpKqAEAYRQ0BtP8ByimtFtP+J04CAAAAFEQAIJhChgDa/wBlDgG0/4mWAAAAAAURAAgp+yGA9j9AmUMA7X9iJgAAAEBBBAACy3gIoP0PUOYQQPufyAkAAABQEAGA8LIcAmj/A5Q5BND+J34CAAAA5J9OhwQAEpDcECC5DQaIU3JlVnIbTJkEAKJQ2jy0tL8XYDmlrYel/b3ESQAgDQn11BPaVID4JdRTT2hTKZwAQCzKaYqU85cCTKOcVbGcv5TICQAkI4nOehIbCZCWJDrrSWwkDAgARKSE1kgJfyPArEpYG0v4G0mFAEBKIu+vR755AOmKvL8e+ebBEqt6vd7S2wAowMLCQuhNKJrPXwoX/0ikl29fb03oDQAAoDgZl9fxcwgQAAAURAAAAICCCAAAAFAQAQAAAAoiAAAAQEEEAAAAKIgAAAAABREAAACgICt8EVi/H/uXtKVufn4+6S/J6/5rQWo+J5Pvv9U7b+QhUpT3V73Ev0hOXmSIlrVi1Pnraj0nGzbPh7rzAa9pZhZS/jJ13wRMSiJfPRc29vNe7Ap8TbP/AINU1CzQ23b+uv40GYD8KulEOQSIiJRQaZXwNwLMqoS1sYS/kVQIACQj/lZxKhsJkJbI2/8JbWScer1e6E0ojgAAAAAFEQCIRaun53ZpxU01BQaYflVMqLO+4qZa/5djCNAxAQAAAAoiABCFbNr/A4YAAKW1/wcMASozBOiSAAAAAAURAAgvs/b/gCFAHia/TPF/CxhELrP2/4AhQGWGAJ0RAAAAoCACAIFl2f4fMAQAKK39P2AIUJkhQDcEAAAAKIgAQEgZt/8HDAEASmv/DxgCVGYI0AEBAAAACiIAEEz27f8BQwCA0tr/A4YAlRkCtE0AAACAgggAhFFI+3/AEACgtPb/gCFAZYYArRIAAACgIAIA0cms/Z/xH5U9XwMMHcus/Z/xH9UNQ4D2CAAEYOI5ynMClMBaN6rY50Q0CkgAoJROee/s+RUX2Wl+pzJDAIAg5eCGzfMbNs/X/53KVLqVGQK0RACgaxMq7JZK5FnL+vZiwOQ/sNgmEFCICatcSyXyrGV9ezFg8h9Y7PovGoWyJtgjQ/vqLKmDf6ttD5CiOnX84N+qTSPR6/UWFhZCb0VuTADIs/3fVBe/8WmAIQBQps7a/0118RufBhgCjCVoBWECQG7aWENNAwDi18bRO6YBMTAEaJwJAFm1/1vtoDR154YASXANUEir/d/eKbwN3rkhwFjyVfdMAMhEN+umUQBAbFot/Zc8ilI1FEOAZpkAkHz7v9Vrd7b0iIYAQDnaa/+3eu3Olh7REGAsyapjJgAkLOxCaRoAEErHdf/YR1ezdswQoEEmACTZ/u++69/4lhgCACVovP3ffde/8S0xBBhLoOqSCQCJiXNlNA3ITJy7GRQukrp/CdOALhkCNMUEgJBmqpjbPvK++7MRBIZEuQQQ1DdTxVy/69/2+j/rFgoMY3laOmMCQALN1Pr3MP3KPvjNGL5CuHf2vIQAJK3+6l2/69/l+t/UNMD6P4EhQCMEAIKZZnXrsvQPEgMWNvYdbQKUZpoSucvSP0gMOH9dP86DmsLytHRDAKBdldfQUKV/VNMATSAgXZUXz1Clf1TTAOv/BIYA9QkAhDFhXYuh9O8yBhgCxMbLAa2aUBPHUPp3GQN0u8fytHTAScC0qMKiWf8035ZaJoN7rnPn1f40xWhsnAEMLa1d9U/zjXb9r/anWf8n6PV6oTchbSYABDB2GW37Cj8xNISWGwUYAgCFGNsLb/sKPzGs/8uNAnS7x/K0tE0AoC3TL5F1at9Qh0i2EQMm/L4jQYGETL821inyUlz/Zz0xwPo/gTMB6hAA6NritSzF0r+lGGAIEAmvArRnceGbYunfUgzQ7R7L09IqAYBWrLgmpl76dzwN0ASKhBMAYEUrLoapl/4dTwOs/xMYAlQmANCpmn3umBfBRmKA9jOQq5oN3VzX/2EM0O0e5WlpjwBA8yYsgpUL3JiX/rHb2fgVkDSBgPhNWMcqV3IlrP+Tnxzr/wSGANUIAMQu0VWv/tWj6Z7XC6Ji/ccQoCW+B4CGNbjktXdR5840+yf4OAnLCQAwmfV/Met/Z3wnQAUmAMQo9XV/Cd0ggClZ/1nCEKANAgARyWzdX8LHQOS8NBCQ9Z86nAkwK4cA0aQ65/jmvfo39Zf6/ADiZP1fkfW/sum/Oo0pmQAQWCHr/hK6QclxAgA0zvpPgwwBZiIA0JhZl7Myl/7614xzPTggNtb/WVn/Z+VMgGYJAARQ7Pq1HA2h4Dz50A3r/xLW/wYZAkzPOQA0Y8rFq5xjPSuY/snxUdExx//ABNb/+qz/03AmQINMAOiIdX9KukFAZqz/U7L+12cIMCUTABowebXS9algxSfNJ0SDPJlQmfW/cdb/CQwBmmICQFss+vXpBsXA8T8wK+t/fdb/ygwBpiEAUNfo8mTp7+ZiESVfDgKIgfW/bdb/US4H1AgBIKT5+dz24GLXo25oCLXB8wmNsP63Ksv1f8Pm+ZYO6TEEWJFzAKhluBg50LMzi5/qzD4MIuT4H1iO9b971v8BZwLUZwIQTDbtf+t+EFl2g7rnCYQ6rP9B5LT+GwKEYgJALVb/sDz/QCjWn7AKf/4NAWoSAMLIpv0PGXP8D0Db2jujt9frtXTPGRAAgELlMUAHKJMhQB0CQADa/wAAA4YA3RMAgBKt2P53/A9A5AwBKhMAuqb9DwCwmCFAxwQAgKW0/wGSYAhQjQDQKe1/iIHTfwFiYwjQJQEAAIBUGQJUIAAAZXH6L0BpDAGWEAC64/gfAIDGjwIyBJiVAAAURPsfoEyGAIsJAB3R/gcAmMwQoBsCAMA/0f4HyJghwJAA0AXtf4iBq38CxM8QoAMCAAAARTAEGBAAWqf9DzFw+i9AKgwB2iYAhLSw0W4KANCdniGAANA27X+IgfY/QFoMAVolAASj/Q8AFCtgIdQrfgggALRI+x9ioP0PkCJDgPYIAGFo/wMAhTMECEUAaIv2P8RA+x8gXYYALREAAtD+h2745i+AyBkCBCEAtEL7H5Kg/Q8QOUOANggAXdP+h25o/wMkwRCgewJAp+1/1T/EQ/sfIBKTCyRDgMYJAECGtP8BmEavyCGAANAw7X9IgvY/QFQMAbokAAC5celPAKbXK28IIAA0SfsfgnPwD0CiDAE6IwAAZdH+B6DwIYAA0BjtfwhO+x8gaYYA3RAAgIJo/wMwVlFDAAGgGdr/EJz2P0AGDAE6IAAApVT/2v8ATFDOEEAAaID2P8RP9Q+QCkOAtgkAQPIc/ANAI3plDAEEgLq0/yEsB/8A5McQoFUCAJA51T8A0+sVMAQQAGrR/oewHPwDkCtDgPYIAECqHPwDQBt6uQ8BBIDqtP8hINU/QPYMAVoiAAAAQEFDAAGgIu1/CEj7H6AQhgBtEACAxKj+AehAL98hgABQhfY/hOKyPwClMQRonAAA5Eb7H4BG9DIdAggAM9P+h1Ac/ANQJkOAZgkAQBpU/wB0r5fjEEAAaIz2P7THof8AhWup0Dq/yCGAANDY8T9AWNr/AMWqfBRQmUMAAaAZ2v/QHgf/AGAI0CABYAba/9A91T8A0zAEmN6aGX6Xztv/jnvumCc8Nl4RimXn75gnPBULG/ttvFjnr+u3mh9iYwIwLe1/6NiUS7z2PwADhgBTEgDqcvQ/tEH1D8BYzgSoTwCYivY/dEn1D0A1hgDTEABq0f6Hxqn+AZjMEKAmAWBl2v8AAKkwBFiRAFCd9j80TvsfgGkYAtQhAKxA+x86o/oHoBGGAJMJABVp/0OzVP8AzMQQoDIBYBLtf+iG6h+AZhkCTOCbgAMnzhgmCfW/US+hsmzFUBfDK1Ia1T9lWlhYCL0JZZlcsaXV9K1Z2ub0SeeLgasRAIpu/xdV+hMn1T/ArAZxpXKFOlh4c4oBy9mweb69aNfr9dKN8QLAzPJ4wyj9iYHqH6AyMWDAEKACAaC49n/NN4lSjKao/gHqEwMmMwQYSwCYTdLvEKU/8VD9AzSo8BhgCDArAaCI9r/Sn6i0sUwDUHgMWI4hwCgBYAYpviWU/qS7Q9r9ACooMwYYAsxEAMi2/a/0Jzaqf4DOlBkDlmMIsIQAMK2E3gNKfyKk+gfoXlExwBBgegJAVu1/pT9xUv0DBFRUDFiOIcBiAsBU4t/plf5ksHPaDwHaU0IMMASYkgCQfPtf6U/MVP8AUSkhBizHEGBIAFhZtHu50p/Iqf4B4pRxDDAEmIYAkGT7X+lP5Bz0DxC/jGPAcgwBBgSAFcS2Wyv9iZ/qHyAh+cUAQ4AVCQDJtP+V/iRB9Q+QomFfvFqNG2EMWM4GQwABYLJI9mOlP0mYdUe1ZwJkNhCIJwYYAkwmAETd/lf6kwrVP0BO8ogBy9lQ/BBAAFhW2B1X6U9CVP8AWUo6BhgCTFB6AIiw/a/0JyFKf4DsJR0DlrOh7CFA6QFgOUH2VKU/aVH9A5QjxRhgCLCcogNAPO1/pT/JUf0DFCjFGLCcDQUPAYoOAMvpctdU+pOcCjutHRUgJwnFAEOAscoNAMHb/0p/UqTxD0ByMWA5G0odApQbAJbTwb6o9CdFGv8ApBgDDAFGrR5zG22qswv2f6TRzYGpqP4BmOD8df3KrfQ2qvNI9Hq9uSgVOgFY7vifVjNozdK/0W2BaSn9AWh7GtD2KGDCEGBDjaOA0h0CFBoAOla59FdIkdx+a6cFKFy0MSCIXpRnApR4CFCX7f/e2fOVqyiFFAGp/gEIclBQ5dppsgll3oYaXfz2ziFulQlAW3T9SZTSH4CmmAbMRTkEKC4AdND+V/qTKLsuABnHAGcClBsAWqV+IlF2XQAKiQFBxDYEKOscgPba/471J12qfwAKOTfAmQADJgB1KZ5Il70XgCAKnAb0YhoCFBQAGm//K55Il2+lAKDMGLDgTICiAkCDlP6kS+kPQFSGNfesBXRy04BeNEOAUgJAU+1/pT/pqnnopH0YgAgHAhViwELxQ4BSAkB9Sn8SVf+UKfswAPnFgJKHAEUEgJrtf6U/iVL6A5CotmPAQtlDgCICQGVKfxKl9AcgA1lOA3oRDAHyDwDV2v9Kf8qs+wfsxgBkHwMWCh4C5B8AZqX0J0VKfwDyltM0oBd6CJB5AJip/a/0p9i6324MQIExYKHUIUDmAWBKSn+So/QHoFgZTAN6QYcAawpv/yv9KbbutxsDkLRGYsBCkUOAnAPAZEp/iq377cYAZCPdaUAv3BBgTYHtf6U/ZRb9A3ZjAPJTMwb0ChsCZBsAmi2q1Ex0Rt0PAN3HgKKGAGuKav9XoGyiA60uPfZhAIpSLQYsJ8shQJ4BoBHKJlrVQb/BPgxAsZqNAZkNATIMAPXb/8om2tDZhNEODAANxoAN2Q0BMgwAlSmbaFb3xxTahwEguWlAr/MhQG4BoFr7X9lETQHPH7IDA0DbMWBDXkOA3ALArFROJFHij2XvBYA8pgG9bocAa4pt/yueSKXQX8KuCwA1nf/P7fzpk0BOQ4CsAsCU1E+kyH4LABkPBHodDgHWFNX+V0KRHDstAEQSAzbkMgTIJwBMpooiIXZXAChwGtDragiwJvv2v1qKJNhRASD+GLAhiyFAJgFgLBUVkbOLAkCczg80DehmCLAmy/a/uoo42TMBIPUYsCH9IUAOAWAxBRbxsDcCQAbO73Ya0MEQYE027X/FFgHZ/QCgnBiwIfEhQPIBQO1FN+xmAMD5nUwD2h4CJB8AlGU0yO4EAKyocvs/kiHA6oCPDQAAjOr1enOtEQAAACClGUJNAgAAABQ0BBAAAACgoCGAAAAAAAUNAQQAAAAoaAggAAAAQEFDAAEAAAAKGgIIAAAAUNAQQAAAAICChgACAAAAFDQEEAAAAKCgIYAAAAAABQ0BBAAAAChoCCAAAABAQUMAAQAAAAoaAggAAABQ0BBAAAAAgIKGAAIAAAAUNAQQAAAAoKAhgAAAAAAFDQEEAAAAKGgIIAAAAEBBQwABAAAAChoCCAAAAFDQEEAAAACAgoYAAgAAABQ0BBAAAACgoCGAAAAAAAUNAQQAAAAoaAggAAAAQEFDAAEAAAAKGgIIAAAAUNAQQAAAAICChgACAAAAFDQEEAAAAKCgIYAAAAAABQ0BBAAAAChoCCAAAABAQUMAAQAAAAoaAggAAABQ0BBAAAAAgIKGAAIAAAAUNAQQAAAAoKAhgAAAAAAFDQEEAAAAKGgIIAAAAEBBQwABAAAAChoCCAAAAFDQEEAAAACAgoYAAgAAABQ0BBAAAACgoCGAAAAAAAUNAdZM/u35+fmWtwciYocHKNOGzdZ/CmICAAAABQ0BBAAAACiIAAAAAAUNAQQAAAAoiAAAAAAFDQEEAAAAKIgAAAAApej1egIAAADMleP/A5Eyia2+8JnIAAAAAElFTkSuQmCC"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_51
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is Cut the right side of the shape\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'CuCuCuCu'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'WrWrWrWr'}.\nthe 9th action is Stack the original shape on top of the {'layer1': 'CpCpCpCp'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABAAAAATICAIAAAANxCANAAB0g0lEQVR4nO3dC5RlZXkn7uqmARsQaLTD1RFtjYCjoiZBwYlxEYyo4CWeljFmMo5GE5cxGWecxJk4alZGmTiZSRydmDEmaiJoleh414hgNCrRGBSI8UJ5BUVabUFuDUL/11Dzr3Tq1OWcs2/f977Ps7KylqeLql2n9tn79/vevc/ZtHfv3jkAACCHzUNvAAAA0B8FAAAAElEAAAAgEQUAAAASUQAAACARBQAAABJRAAAAIBEFAAAAElEAAAAgEQUAAAASUQAAACARBQAAABJRAAAAIBEFAAAAElEAAAAgEQUAAAASUQAAACARBQAAABJRAAAAIBEFAAAAElEAAAAgEQUAAAASUQAAACARBQAAABJRAAAAIBEFAAAAElEAAAAgEQUAAAASUQAAACARBQAAABJRAAAAIJEtQ28A9Or6668/8sgjb7nlllX/9VnPetbrXve63jcKgEbe8pa3TPX1m++0ZcuWAw888KCDDjr88MO3b99+5JFH7rfffp1tIxRk0969e4feBujPn/7pnz7zmc9c61+POOKIa665Zv/99+93owBoZNOmTc2/yQEHHPDP//k/f8hDHvITP/ETZ5111jHHHNPGpkGJFAByOf300y+66KJ1vuA973nP4x73uB63CIAiCsCKb3jaaaf963/9r3/pl35pyxaXSxCNewBI5Oqrr/7IRz7S7hwZgHj27t3713/918961rNOPPHE+fn5oTcHWqYAkMj5559/xx13rP8173znO9e6QwCAbK688sqnPvWpz372s2+99dahtwVaowCQyF/8xV+seGTbtm0rHvnhD3/43ve+t8eNAqB0r3vd6x7zmMfcdtttQ28ItEMBIIu///u//9znPrfiwVe+8pXjF3e+9a1v7XG7AOjE3nXdfvvtt95663XXXff1r3/9ox/96P/8n//zKU95ykEHHbTWd7v44ouf//zn9/sbQFfcBEwWL3rRi84999x9Hzn00EOvvfbaxz72sStuC966deu11157yCGH9L6NALR2E/AMCeeGG274gz/4g9/7vd/74Q9/uOoXfPCDH3z0ox890zZCQUwASGHv3r3nn3/+igef+MQnHnjggU9+8pNXPH7zzTe/613v6nHrACjCIYcc8tu//duXXHLJ8ccfv+oXvOxlL+t9o6B9CgApfOxjH/v617++4sGnPvWpSzVgfOnIewEBpHXSSSe9973vXfVyoE984hN/+7d/O8RGQZsUAFJ485vfvOKRI4444owzzpibmzv22GN/6qd+asW/fvCDH/zBD37Q4wYCUJCTTjrpN3/zN1f9pwsvvLD3zYGWKQDEd+utty4sLKx48MlPfvLyJ/4+6UlPGv9P3v72t/e1gQAU57nPfe5+++03/vjFF188xOZAmxQA4nvf+963e/fuVa//WTJ+G4CrgACSu/vd737yySePPz5+QSlURwEg49v/b9++/VGPetTy/7zvfe97//vff8XXXHTRRbt27eplAwEo0QMe8IDxB7/73e8OsS3QJgWA4K677rrxD/Z6ylOesmKwOz4EuP3229/2trd1v4EAFOpud7vb+IPXXXfdENsCbVIACO5tb3vbLbfcsuLBc845Z8UjrgICYJJPEjj00EOH2BZokwJAuut/jjnmmEc84hErHjz55JPvda97rXjwr//6r6+++uqONxCAQq36dnDbt28fYlugTQoAkV111VUf/ehHVzw4Go02b15lzx9/L6A77rhjfn6+yw0EoFxf/OIXxx986EMfOsS2QJsUACI777zz7rjjjg2v/1mrALgKCCCtPXv2XHrppeOP//RP//QQmwNt2rTq9W0Qw4Me9KDLLrts30fuec97fvWrXx3/6N+l9f5jjjnmO9/5zorHv/KVr4xfHQRAOVY9qjdMOG9+85uf/vSnr3jwoIMOuvrqqw8//PAm3xkGZwJAWFdcccWK9D83N7dz585VzxP/98WwefMTnvCE8cff+ta3drOBABTq1ltvffnLXz7++LOf/WzpnwAUAMIav/13net/lngvIADm5uZe8IIXfP7zn1/x4D3ucY/f+Z3fGWiLoE0uASKmvXv3Hn/88d/4xjf2ffA+97nPl7/85XX+q9tuu+3HfuzHxt/24R/+4R9OOOGEbrYUgIIuAbrxxht/4zd+40/+5E9WPH7ooYd+5CMfefCDHzzrNkJBTACI6aMf/eiK9D83N/fUpz51/f9q//33f9zjHjf+uCEAQHi7d+9+1atedf/73388/R955JHvf//7pX/CMAEgpl/+5V8eP4Jfdtllq36u+77e/va3//zP//yKB0844YR/+Id/aHsbAehwAnD++eev85/s3bt3z549N9100zXXXHPVVVddeumll1122fgbx83NzZ1xxhlveMMbjjnmmFY3GYakABDQnj17jjrqqBVX8px44onjF3SOu+mmm+5+97vffPPNKx6/9NJLTz755La3FIAWrPXuDg09+MEPftnLXnbWWWd18c1hQC4BIqD3vve949fxr3/777KDDjro537u58YfdxUQQB4HH3zwH/3RH33mM5+R/glJASCgN7/5zeMPbngDwPqfCObNQAHyuPHGG3/1V3/12GOPfd7znucSUOJxCRDR/OAHPzjqqKP27Nmz74Mnn3zyqh/ouKrdu3f/2I/92I9+9KMVj19yySWnnHJKe1sKQNGXAC0788wz//AP//C+971vpz8FemMCQDRve9vbVqT/qZb/5+bmtm3b9jM/8zPjj7sKCCCn97///Q984AP/23/7b0NvCLRjS0vfB4r+/K9NmzZNFd+3b98+/uD8/Pzv//7vb96sNgNUYMNrHO64444bb7zxhz/84dVXX/3Nb37zs5/97Kc+9amLL7741ltvHf/iW2655YUvfOHXvva1V73qVU4E1M4lQITyzW9+8573vGd3e/VHPvKRRz7ykR19cwAG/yCw733ve294wxt+93d/d/zNJJa85CUveelLXzrDd4ZyqLCEct5553XaaV0FBBDb3e52t3/37/7dl770pUc96lGrfsHv/u7vfvKTn+x9u6BNJgCE8sAHPvDyyy/v7vtv3779W9/61pYtrp0DiDkBWLZnz57HPe5xH/7wh8f/6YwzzvjLv/zLJt8chmUCQByXXXZZp+l/bm5u165dF110Uac/AoASHHjggW9605uOOOKI8X/60Ic+NMknS0KxFACC3/7bOlcBASRxzDHHPO95z1v1n973vvf1vjnQGgWAIPbu3Xv++eevePDggw++6aab9s7qvPPOG/9B73jHO1Z9gwgA4nn2s5+96uOf+MQnet8WaI0CQBAf+chHrrrqqhUPPv7xj9+6devM3/Oss84a/89/8IMffOADH5j5ewJQkWOPPXbHjh3jj7sEiKopAATx5je/efzB0WjU5HsecsghZ5555vjjrgICyOOhD33o+IPf//73h9gWaIcCQAR79uy54IILVjx48MEHrxrfp7Jz587xB9/1rnfddNNNDb8zAFW4293uNv7gWp8SAFVQAIjgPe95z/ix+HGPe9xBBx3U8Ds//vGPH/8mN95443ve856G3xmAKhx66KHjD/owYKpm9yXs+/80vP5nycEHH/zYxz52/PG3vvWtzb85AOW7/vrrJ2wFUAsFgOrt3r17/O3YDjrooFWD+wye+tSnjj/4vve974c//GEr3x+Aku3atWv8weOOO26IbYF2KABUb2FhYfx9OVu5/mf5Wx188MErHrzlllv+z//5P618fwBK9qlPfWr8wRNPPHGIbYF2KABUr4v3/9nX1q1bH//4x48/7r2AAML70pe+9I1vfGP88VNOOWWIzYF2KADU7Rvf+MbHPvax7q7/Wee9gD70oQ95GziA2P7H//gfqz7+uMc9rvdtgdYoANTtvPPO27t374oHH/vYx45ftNPEYx/72EMOOWTFg7fddtv4e48CEMall176Z3/2Z+OPP+IRj1j108GgFgoAdev6+p8ld7nLXc4666zxx10FBBDV1Vdf/ZSnPGXPnj3j//Sbv/mbQ2wRtEYBoGKf/exnr7jiihUPbt26tYvJ7KpXAf3VX/3Vd77zndZ/FgDDuuSSS0455ZSvfOUr4//0mMc8ZtUbw6AiCgDRlv/PPPPMdq//Wf624+/6fPvtty8sLLT+swAYyqc+9al/9a/+1amnnnr11VeP/+tRRx216kVBUJctQ28AzOiOO+44//zze7j+Z8mBBx549tlnj3/i2Fve8pbnPe95XfxEAJqY5CrNH/3oR3v27Ln++uu/+93vfuELX/jMZz7z9a9/fa0vPuKIIz7wgQ8cddRRbW8p9G3T+A2UUIWLLrro9NNPX/HgXe5yl127do3fsNuKd7/73WefffaKBzdt2vT1r3/9Hve4Rxc/EYBJbNq0qesfcdJJJ73rXe9y7y8xuASIWo0vxi9dqNNR+p+bm/u5n/u5ww47bMWDe/fufetb39rRTwSgBE9/+tMvueQS6Z8wFACqdMstt7z97W/v7fqfJQcccMATnvCE8ce9FxBAVD/xEz/x8Y9//M///M/vete7Dr0t0BoFgCq9+93vvu6661Y8eJe73KXrd2ZY9b2APvOZz1x55ZWd/lwA+nTIIYc84xnP+PjHP/7pT3/61FNPHXpzoGVuAqZKW7dufclLXrLiwX/2z/5Z1ys0j370o1/60peO3zkz3kYAKNymTZu2bNly4IEHHnLIIdu2bTvyyCPvec97PuQhDzn11FNPPvnkLVtkJMJyEzAAACTiEiAAAEhEAQAAgEQUAAAASEQBAACARBQAAABIRAEAAIBEFAAAAEhEAQAAgEQUAAAASEQBAACARBQAAABIZNNoNBp6G6AUCwsLQ28C9Gc0GtnnARLatHQOGHozoAjCEEmsOOzb8wFSHf+3DL0ZAAwT/RcWFpb+59L/VwMAkhz/t+x7DgAgqg2P82oAQJLjvwkAQN7oP74ApAYAxD7+Lyws/L8CYAgAEM/MB3Y1ACDw8d8EACB19F9nAUgNAAh2/F86pP9jATAEAAig9SO5GgAQ7PhvAgCQPfpPsgCkBgDUfvxfPob/kwJgCABQo94O3WoAQIDj/9QTgPlt22f4MVCInbt3Db0JUGL0n2oBSA0AqO74v+9Be8u054Cdu3fpAACDG3xgqwYAVHr8dw8AQGU6iv6zXQWqBgBUca/XBgXAEACgTIOv+q9FDQCo6OBvAgBQgX6if8O3glADAAo8+I8fllcvAIYAAIUodtV/LWoAQOEH/83dfWsAmhjdqcl3mGGlZp3gvmN+W58bD5DTaMrj5/oH51WP6mteAmQIADCU5tG5i+Pz4s7dS6eZxZ27p/1FDAQAWj/4T3tMXuYeAICClBD9N1wAmuGU47oggNaj/4bWOuquVwAMAQBSRf/JhwBqAEAJ0X+G5X8TAIDhFRj9J387IDUAoKhV/2XrHGY3KACGAACpov9UQ4BlagBA/9F/tuV/EwCAYZQf/Wf4TAA1AGDYVf9l6x9XNy4AhgAAqaL/bEOAZWoAQA/Rf+blfxMAgP5UF/2bfDCwGgDQ86r/sg0PpBMVAEMAgFTRv+EQYJkaAGQ26iz6N1n+NwEA6Fbt0b/JEGCZGgBkM+p91X/ZJEfOSQuAIQBAqujf1hBgmRoAZNBD9G+4/G8CANC+YNG/lSHAMjUAiGo03Kr/sgkPlVMUAEMAgFTRv/UhwDI1AIhk1GP0b778bwIA0I7Y0b/dIcAyNQCo3aiAVf9lkx8bpysAhgAAqaJ/d0OAZWoAUKPRENG/leV/EwCA2aWK/h0NAZapAUAtRiWt+i+b6mA4dQEwBABIFf17GAIsUwOAko0Gjf5tLf+bAABMJ3P073oIsEwNAEozKnLVf9m0R79ZCoAhAJBQ5ujf5xBgmRoAlGBURvRvcfnfBABgY6J//0OAZWoAkDz6b2iGw92MBcAQAMhA9B92CLBMDQAyR//FVpf/TQAAVif6lzMEWKYGANmi/4ZmO77NXgAMAYCQRP8yhwDL1ACghCP/jr6if+vL/yYAAP9I9C9/CLBMDQDCR/8NzXxAa1QADAGAGET/uoYAy9QAIHb0X+xg+d8EAMhO9K93CLBMDQDiRf8NNTmCNS0AhgBApUT/GEOAZWoAECz6L3az/G8CAGQk+scbAixTA4AA0X9DDQ9ZLRQAQwCgFqJ/7CHAMjUAqD36L3a2/G8CAGQh+ucZAizbMb9t2jOoGgCRzHaA2lFA+l9f82NUOwXAEAAoluifcwgw8yhADYAAao/+i10u/5sAAJGJ/j0ofAiwRA2APGqP/htq5aDUWgEwBADKIfqXoJAhQCs1QBOA8oWJ/osdL/+bAADRiP79q2II0LAGGAhAycJE/w21dQhqswAYAgADEv0LVNoQYJkaADHEi/6L3S//mwAAEYj+g6trCLBMDYB6xYv+G2rxmNNyATAEAPok+pev2CHAMjUA6hI4+i/2svxvAgDUSvQvTaVDgGVqAJQvcPTfULsHmfYLgCEA0CnRvzrlDwGWqQFQpgzRf7Gv5X8TAKAmon/hah8CLFMDoBwZov+GWj+qdFIADAGAdon+tatoCLBMDYBhpYr+iz0u/5sAAKUT/esSZgiwTA2A/qWK/hvq4jDSVQEwBAAaEv2DqXEIsEwNgH7kjP6L/S7/mwAAJRL9qxZvCLBMDYDu5Iz+G+rouNFhATAEAKYl+sdW9RBgmRoA7Uoe/Rd7X/43AQBKIfpHEngIsEwNgOaSR/8NdXeg6LYAGAIAGxL9U4kxBFimBsBsRP8Bl/9NAAhr5+5d7R6PnKe7IPoH1sMQYKgTZ4vCz0kq4iDfmxjRf7H7tYxO98nOC4AhAEVF/Jmtvxs7c0xL9M+srRPnjvltAToAJDHzYb/A6D9X3realgkAFeg567d1XNMKOlrvFP0BKiL6F2hTIX97Z3Qqivszy1wJRP8CX1A97JDr/N3bOrVHOiUzoMzH5+7Ejv47mm3k+seurndIEwCGFzjxr38oTHK+Ef0Bsokd/QPoaQJgCEDa0D+hkGVA9C/BsBMAQwBqEfIgPIg80X9Hgw0edvnfBIBeCf0THjEDnIdEf4Bs8kT/APqbABgC5CT0N1RdGRD9SzP4BMAQgCpUd7AtSs7ov2PWjR98+d8EgK7I/a0fVcs/OYn+ANnkjP4B9DoBMAQIT+7vQYFNQPQvWQkTAEMAylfgobVwov+OmX6REpb/TQAIm/vXOjCt/9Kq4pOAi5oJiP5UxMfuJlfCMTMG0T+AvicAhgCRDJv7ZzsAzVwAmnzbrg3y00X/WhQyAShkCKADZLb+Dq8eTEL0b/hLFbL8bwJAHbm//HP2sJ8E3PNMQPQHyEb0D2aACYAhQL16i/7dJf6OJgDNf3QVP6j58+OlnXkCYAjAsEwAZiP6t/ULlrP8bwJAKbk/wym5t48B7mIgIPoDZCP6BzbMBMAQoBadRv9BQv+AE4Chen/Dby76166oCYAhAAMyAZic6N/6L1vU8r8JAH1Hf+fd/j8GeOmbz/BtRX+AbET/ZaPRKHAtHKwALCwsrL+T7dy9S3ron9w/uI7u6J3q24r+DHLwX9y5u5UMsWN+24aLbQ5KsILov6z140Npy/8mAHQY/Z1fyxwLrD8QEP0BshH9E0aXIQuAIUDI6J/nxVP1WGC8Boj+9MYQAAoh+i/r7oBQ4PK/CUB2LUZ/p9Iam0BbfzXRH6Auon/yADNwATAEGIroX7uZb+1tl5cnszEEgKGI/st6OAKUufw/fAGg3ujvxFmCnj8DeF+iP0BdRP9lo/QZZvgCYAjQG9E/sD4HAl6PtMIQAHoj+i/r8yW/WOryfxEFgFrSv9Nk+boeCIj+AHUR/ZeJMcUVAEOATon+CbU+EPACpAuGANAd0X/ZIK/xxYKX/0spAHRE9E+urRog/QPUosmJW/TPo5QCYAhQVPT3gomk+XVBS7uTFyBdMASAtoj++xr2Rb1Y9vJ/QQWAQtK/s2BgDQcCSjhAmUT/fUkyk9g8V4wNc0m7H1gb0s7du2Z+lkZ3anuLKE6TP3STHQxmOPg3jwITRpwSFuSg50P6jvltRaX/xZ27G77kC0kyi8Uv/5sAhNIk+re9LUSeBhgFAAzOqv++JJmKJwCGADObeV22kK7MUGbeAYwCaJchAEzOqn/JSWaxhuV/E4AILPzT0Gg0MgoAKJ9V/32JMXEmAIYAU7HwT1uMAhicIQCsw6p/FTFmsZLlfxOAis0c/TvYFrLfGGAUANARq/77EmPCTgAMATpacy22LlOa2XYVowCaMwSAfVn1ryvGLNaz/G8CUB8L/5R8Y4BRAEBzVv33JcNkmQAYAqzFwj9VjAK62RxSMAQgOav+lWaYxaqW/00Agkf/braFXGa4MWBpdzUKAJicVf99yTBJJwCGAPuS/hmcUQC9MQQgG6v+la7617v8bwJQgWlTVHUvG2KPAswBANZi1X9fAkyfyp0AGALM8LYqXjx0bdp9zLsDMQNDAMJruM5dVPrPuepf9fK/CUC5RH+KZRQAMLOG5+vSon/D7yC9DKXoCUDaIYD0T8hRQGfbQkCGAMTTfNW/nPSffNW/9uV/E4ASSf9E/awAcwAgJ6v++5JbSrBprgYb7isxUoXo34P1A6undDbTLnLEeMEGOLCUvDq14UuyrUi0YZpxWAhj/R2+o5eD6F/1q2mhwV5R+AHWBKAU0j/1MgoAWEH035fQUprS7wFIcieA9E/t3BJAF9wJQI1c6x/vWv9plX/cMAEY3lRJKOGriKjvDmQOAARj1X9fEkvJ6pgABB4CSP8EM9VeWunLlj4ZAlAFq/77yrnqX9cRwwRgSNI/IU11S4A5AFC1MKv+rTRqWaUW1UwA4g0BJt/a5E2aGk2109b1yqV/hgCUKcyqf/Mlf1mlumOFCUAF6b/jbYHhRwHmAEAtmp+XC8n9Vv0zq2kCEGYIIP2ThzkArTAEoATNF7mt+se2UM9RwgSgVy76J6Gp5gA+JgwokFX/FUSU2lU2Aah6CCD9k5a3BqI5QwAGYdV/Bav+MY4PJgA9kf5JzlsDAXWx6r+CcBJJfROAGocA0j+YA9CcIQD9sOq/glX/DVV3ZDAB6JxbfmG2Tws2BwB6ZtV/BckkqionADUOATbkNUYe9nZmZghAR6z6r2DVf3I1HhNMALo1YQ/xGiObCW8JMAQAyldI7rfqT/wJQBVDAOkfmu/5g7+QKY0hAOWItOq/tOQvk0yr0qOBCUBXpH/YkDkAUKlCcn8rvVcUSajiCUDJQwDpHyZkDsAMDAEYULxV//a2KJ2Fao8DJgDtk/7rfWWu+vX+Ul0zBwCqUEjut+pPc5vm6rfhTtxnaJD+81Rwf8RB/og6QIsHpXrXrjZ8DbYV1DaMWY4DFWmyw4v+OS2su89UfQg1AWiT9N+PQl5y45vhL9uEOQBQINGfkCJMAAoZAkj/GUL/5PyhZ2MO0LqcEwBDAJrv8KI/CyYArE/670LVL619N97ffXLmAExuYWHBi4suiP6EtyXJaUBcqEXVoX8tygD0b3Hn7lZi3I75beuHMD0kEtGfJIIUgGFZ/m8uZO5f/ze1P6zFEIDJrR++2+oAZFDOriL604M4BWCoIYD030Se3D9OE1iHDkBRDAHoh+hPb+r+ILDBSf8zW7jT0FtRBE/FqnxAGBNa/+XT1ueCQad8pBc9izMB6H8IIP3PQNJdi4HAOHMAymEIQEes+jOIUAWgQF6Wg0f/c7fN7/s/f2v3zsm/eMOv7+6JsudM1QFIzp0A1Ej0Z0DRCkBvQ4BJlv+9MvvM/ePZvdNv23UxMBCYqgMYAtADQwDaIvozuGgFoB/S/+DRv6O432QDOqoEBgI6AJMwBKAKoj+FCFgAuh4CuOlwqOg/eOiffPNaLwNqwCR0ALpmCMDMRH+KErAAlCDtq7T16F946O+5DGSuAW4GYEOGAJRJ9KdAMQtAd0MAF/+spd1wVmnuX/93aasJpK0BLgSiBIYATE70p1gxC0BHpP+u03+k3N91E8gZMnQA1mcIQCFEfwoXtgC0PgRw6X930T927u+uCaQdBWxIB6BThgCsQ/SnCmELwCBSvWibR/9sub+jJpCtBrgZgPUZAjAU0Z+KbJ6La5JLBSb8Vi7+WaFhAjt327z03+4TkioTT/JaM7KjUxu2iFQvSRZ37m6Y/kd3am+LYAMmABuT/tuN/u1tSzRLT87M04BUowA3A7AOQwB6Y9WfSgUvAL19MHAGTaK/3N/bdUGpagAMyJ0AyYn+VC3yJUCtsPzfMP272mdmTZ66DJcfuBCImV8CzaMbmbnghwDiF4AmdwJI/03SpOjfipmfRh1giQ5Ad9wJkI3oTxjxC0Cnwr+MF+40w38o+rdr5g4QPn+Efw0yM0MAWiT6E0yKAjDbEMDCoYX/ohgFzMxrme4YAoQn+hNSigIwAxf/zHDSEv17MNuTHDuCuBCItRgC0IToT2BZCkCLnwmwJPBLeobrRkT/ns3whMe+HCjw65HyGQLEI/oTXpYCMJXMi4WzLfx3sy1swChgKplf15kZAjAV0Z8kEhWACYcAmS/+sfCfZBQwF5ELgRiQIUAAoj+pJCoAbYn68p4h/Xe2LUxHB4j92qQhQwC6JvpTnVwFoPU7AWKY9upwC/8FmvaPEvuWgHXkfI3TA0OAnER/KpWrADQX73Vu4T8So4B4r1BaYQhA60R/qpauAMRLPE1I//HoABsyBKAjhgBJiP4EkK4ANBHsBe+yn6hmuBxoLpBgr1PaYghAc6I/YWQsALPFneTpv8ttoRM6wDoMAeiIIUBUoj/BZCwASP9JZO4AG9IBEjIEYAaiPyElLQDTZp1IL/7Jf3eX/QQw1R8xUgeI9JqlLoYAYYj+BJa0AKQ1VfrveFvoT84OsCFDgIQMAZiE6E94eQvA5EEnzFFA+s8sYQcI88qlOoYA9RL9SSJvAchG+idhB9iQIUBChgCsSvQnldQFYJKUE+NwIP2TswPEeP1SI0MAoGSpC8CG4SBGepD+2ZcOsIIhQEKGAEByqQtABtI/47J1ABiEIQBQrLwFIMPyv/TPWlJ1AEMAxhkCAJnlLQAsk/5z8neHrhkCAGVKWgAs/y+TAjOb8K8fIKMYAjDOEABIK2kBCE/6Z0J5OgAMwhAAKFDGAhB++V/6ZypJOoAhAOMMAYCcMhaA2KR/ZpCkA8AgDAGA0igA0Zb/JyH9k3OvyPDqZlqGAEBC6QpA7AQwyTJShpzHbCbZN2IvVboKiI4YAgBFSVcAApP+aU4HICFDACCbXAUg8O2/Mhl9qnd/cyswQzEEAMqRqwAkZ/mfSdhPSMgQAEglUQFIvvwv1TG52BcCGQIwFEMAoBCJCkBU0j9diN0BYJwhAJCHAlD38r8ExrAq3QMrfb0TgCEAUIIsBSDz+d7yP7PJvOe4CignQwAgiSwFICQX/9A1FwJB6wwBgMGlKACBb/9dn/RPc1H3IrcCsypDACCDFAUgJEtElMPeCFMxBACGpQBUufzv4h/6FPVCoBpf+/TAEAAIL34ByHmOl/5pV849ylVAdMcQABhQ/AIQj7MCZbJnEoYhABBb9gIQcj6Qc7GWroXcr0IeAaiFIQAwlOAFIN7ZfcPzQciURiE23Lvi5RVXAaVlCAAEFrwABKsH8dIV8VS3l1Z3HCASQwBgEKkLQDyW/+mafQyWGAIA9YpcAIIt7FkHohbB9lVXAaXVz55sCAD0L3IBSFUPLM3Sm3h7WryjAf0wBAAqlbcA1MUKEHWxxxKDIQAQUtgCkG1JL96iLCXLtr+5Coi1GAIANQpbACLVA2/9SYGCvSVoXccE+mQIAMSTtAAAQCsMAYDqxCwAkRbzLP9TrGBDgPW5CigzQwAgmJgFAAB6YwgA1CVjAYg0H7D8z7Ai7YGRjgy0zhAAiCRjAaiIYz21sw+ThCEAUJGABcAyHtAFtwEkZwgAhBGwAISpB27/pQqRbgWu6PhAgQwBgFqkKwAAMBtDACAGBaBWlv8ph70RlhgCAFWIVgDCTPAt8BBJmP3ZbQAYAgABRCsASeqBBVdKE2afDHOUYCiGAED5chWAWljaIR57NWEYAgC1UwAAoE2GAEDhQhWAJLP7MNdaEEySPdNtABgCALULVQBi1AMHdKKqZd+u5VhByQwBgJIlKgAA0BZDAKBeCkBlklxlQaXsn7DMEAAolgJQFms5xGYPJxJDAKBScQqAy3aBfrgPmAkZAgBlilMAMtQD11dQvhh7aYwjBj0wBABqlKUAAED/DAGAAikABbGEQwb2c4IxBACqowBUI8aVFWRgX4V9GQIApVEAAKARQwCgLkEKwPp37LmfD5jW+scNbwTEVAwBgKIEKQABWLkhD3s78RgCABVRAOrgomrqYo+FFQwBgHIoAADQAkMAoBYKAAD0wRAAKIQCUAQLNmRjnyckQwCgCgpABVxOTY3stzDOEAAoQYQC4D1AgS54J1BmYAgAlC9CAQCAWhgCAINTAACgTYYAQOEUAADolSEAMCwFYHgWacjJnk9ghgBAyRSA0nkrFepl74W1GAIAA1IAAKB9hgBAsRQAABiAIQAwFAUAADphCACUSQEAgGEYAgCDqL4A+BhgoDs+DJiGDAGAAlVfAACgXoYAQP8UgIFZlSEz+z8ZGAIApVEAiuZt1KmdfRg2ZAgA9EwBAIBuGQIARVEAAGBghgBAnxQAAOicIQBQDgUAAIZnCAD0Zkvsd8qvfanjt3bvHHoTgPX4KIABxTt/9dMBaj8zdsTTQipbht4AKIjG1T8nXQDomUuAAAAgEQUAAAASUQAAACARBQAAABJRAAAAIBEFAAAAElEAAAAgEQUAAAAS2eCDwOa3bZ+r+WM4y/+cyPU/BencbfM9bksWPu2LFvkgs2KVf/ynqFdr2h1mw4PYjvlt/XzKtcNpn3wSMPwTSlfPjav8k65zEpDZ4s7dzTvAjvltk3QAeuMSIACApMpZhSlnSzJQAAAAWFMri/etXEpEWxQAAIC8yll6L2dLwlMAAABYjyFAMApA0bxfDbWzDwOUr5yl93K2JDYFYGB2dDKz/wPUwhAgEgUAACC7clZkytmSwKovAOt/VJk38AaaWP8Y4ggDpGIIEEb1BQAAgEhL7+VsSVQKAAAAEzEEiEEBAACgrKX3crYkJAUAAIBJGQIEoACUztuoUy97L0B1yll6L2dL4lEAhmf/Jid7PkClDAFqpwAAAFDiAk05WxKMAgAAwHQMAaqmAAAAUOjSezlbEkmEAuDDgIEu+BhggHUYAtQrQgEIz1upUCP7LUDVyll6L2dLwlAAimDPJhv7PEAAhgCVUgAAACh6saacLYlBAQAAYEaGADVSAOrgcmrqYo8FiKGcpfdytiQABaAUdmvysLcDRGIIUJ0gBcA7gQLt8h6gAKWt2pSzJbULUgAAABiKIUBdFIBquKiaWthXAYIpZ+m9nC2pmgJQEPs0GdjPAUIyBKiIAgAAQDXLN+VsSb2yFIAYd+y5soLyxdhLYxwxAHpmCFCLOAVg/TcCAmiLegDkVM7SezlbUqk4BSAGOzSx2cMBYjMEqIICUJkY11cQlf0TILZy1nHK2ZIaKQAAALTGEKB8iQpALZftarREVcu+XcuxAiD5wbycLalOqAKQ5D5gV1lQpiR7pnoAsCFDgMKFKgAAAORZei9nS+qiAJTI3kw89mqAVAwBSparAISZ3Se51oKKhNknwxwlAJIs65SzJRWJVgDC3AZgbyaSMPuzegAwOUOAYkUrAHmEWXAlAHsjQELlLO6UsyW1UAAAAOiEIUCZ0hWAiib4G9ZZy66UYMP9sKKFmYqODwAlqOgIT/ACEOY2AKAo6gFAsUMAVSR7AYjE3kzt7MMAsTnO1yhjAYi0jOcqIIYVaQ+MdGQAKIohQGkyFgAAANoieVcnZgGIdBuAW4EpVqTbfzdkPgDQhCFAUWIWAAAAeiN51yVpAahrMc8QgAIFW/6v65gAUCNDgHKELQCRrgKahA5An7Ltb+oBwIYk74qELQDBeFFRF3ssAOMMAQqRtwDEW9LLtijLUOLtafGOBgCDkLxrEbkABLsKyIuKWgTbV9UDgBYZApQgcgFIKN7SLKWxjwGwDsm7CqkLQHULe15UlK+6vbS64wBA7QwBBhe8AAS7CshbgjKsYG/9OQn1AGBa8c4F8QQvADnP7joAXQi5X4U8AgCUzxBgWNkLQI3szZTJngnAEmeEwsUvAPGuAkq7WMuAcu5R5gMA3TEEGFD8AhDyHD/J3pwzsdGFSfalGo+wNb72AWpR43khDwWgVl5XlMPeCMAMDAGGkqIAbHgVUNSFQEMAmou6F234qo96WADojeRdrBQFICoXAtG1qBf/AFAIQ4BBZCkAOW8FXqIDMJvMe47lf4BWSN5lylIAop7vva4YVqV7YKWvd4CQDAH6pwBUz4VAdMHFPwC0wsmiQIkKQOBbgXUA2hU7/bv9F6A0hgA9S1QA0AGYhP0EgHZJ3qXJVQCSDwGgLfXub5b/AcpkCNCnXAUgNhcC0Vzsi38AGIpzR1HSFYDY7weqA9CE9G/5H2BAhgC9SVcANpQhAegA5NwrMry6AYoleZdDAUj66sqQ9pjchPuDYzcAnTIE6EfGAhD4VuAlOgBTSZL+3f4LMLjaTyVhZCwAGegATChJ+gegFoYAPUhaAMIPAXQAJpEn/Vv+ByhEgHNKAEkLAPvSAXLydwegTIYAXctbAAwB9iULZjP5XzzA8dHyP0BRApxZape3ACShA5A8/QNQI0OATqUuABmGADoAydO/5X+AAsU4xdQrdQGYRIxwoAOwRPqP+psC61i409BbwdQMAbqTvQBsOAQIQwcgW/oHEP1L5lwzoOwFYBJhjh06QGYJ0//kr9wwvzKwTPSPwRCgIwpAoiGADpBWwvQPpCX6V8RJZygKwEQiHUqm6gBqQO2m+iNGOhBP+5qN9LtDWqJ/SIYAXVAA0g0Bpt3LdYB6TfW3y3bsAyIR/evl7DMIBSDXW4Iu0wHCy5z+Z3u1BnsSIAnRPwNDgNYpAFNI3gHUgFpM+8cKdsgL9joF1iL6hxHsNFQFBSDvhUAzvOR0gPJN+zdy2N2XZwOqIPonZAjQLgVgOvGOODpAJNJ/vFcosC/RP6p456PCKQDZhwBLrzqXAyW87MfRdlWeFiiT6I8hQIsUgKlFPQAZBdTLwv/kr82cJR+SR/8d89s2jH0MLuq5qUwKwCz5QAdYYhQwuBn+BFGPsC2m/6hPEVRH9GeQIUAGCsAqMq8RzhB9dIChzPDMZ462y6/rzC9wqIXon1MhJ6lRGZvRqS1Db0CtFhYWou4fS7/XVEfepSR67rb5LreLfyT6dz2UG41GUQd9ULjmLz25P7bFnbub/4l3zG9rZZhQLxOA1WW+EKjJKMA0oGuzPcnS/4pXtCEAFMiqP+WcsEZlbEZ3FIA1iQiz7f1qQEdmfmLDH8U6ei173qA3oj9TcSdAcwpAI7GHAE3eLFIHaNfM0T98ip35NajhQwlEf8YVcuYalbEZHVEA1uNCoCVGAQOy8D/g+35meA5hKKI/TRgCNKQAbEAHaJiE1ICZNXnqMiTX5unfEAAGIfpTy1lsVMZmdMG7ANHhuwMtWw6y3iloQw37UuCj1SC8HRC0yDv80CJvB9SECcDGDAFavKzcQKC7JyfDFf+tX/xjCAD9sOrPtAo5o43K2IzWKQAT0QHafT2oAa0/IVGPUINc+p/5uYXWif50x50AM3MJUJsCfzpYu1cELXFdUCstKM8u11HTnt+2fefuXe1+T8AFP4S5CHNUxma0SwGYlJTQUQ1I2ATamn5ki/6Ta/3CnpBHf+iO6E9v3AkwG5cATcGFQF0n0aUrYaJeHdTub5cz/Xd08Y87AaAtLvihXYWc7EZlbEaLTADanwOkuhCo3VFAyJlA630m4d41yKX/KxgCwPqs+jMUQ4AZKACdyNkBWq8BK9JzRWWgoyFGzp1qSdfh2zV+MDPRn04Vsv4yKmMz2qIATE1Q6L8GVFEGOr1yKXP0L+dKnmBHf2hO9KcQhgDTUgBm4UKgAWvAWmm750rQ240KyfeiPi/+0e1hcqI/fSpk/WVUxma0QgGYkQ4woeVnoOvXzFqJvGExGOqOZHtOIZf+Bz76w2xaeQlI/7TOEGAqCkC3dIB+BgItJvjB34PIDrOvnncYQwBYh+jPgApZfxmVsRnNKQCdZwUdYJCBQHXsJOMm3El6fhPPMEd/mJzoTxUMASbncwAamTB5iAvjRncaeiuK4KkoKv37TABo9339vbU/bSnkXDkqYzMaMgFoyhygicwDAftDdWv/ywwByCDSqn+GBV2WGAJMSAFogQ7QXJ4mYB8oP/27E4DkRH+K1dv6y451O0CAZSAFgHLzce2vrmVCfzwBjv4wTvQngFaGAOEpAO0wBOhC1WXAH7rS5f/l728IQCqiP7UwBGiFAtAaHaBTVZQBf9kY6X9CtR/9YYnoTzyGABvatH5kKeREW5EJVw0lxXYNksP8EcOn/0k+7K+vbWHqF6BX6IZE/33ZYYLtvW3tmYvr7lr1ngVMAFpmDjCItZ7MVl6Z/lI50/8kDAGolOhPeIYA6zMB6IQ5QL1nPn+U/pWc/g0ByjTJ69RreVWi/1rsMNUxBGjCB4F1wgeEQYD0PwmhgVpE+kivxZ27LfyzITvJOhSArugAECD9F1s8MlO6piX6E1Jvh4Id6+75lR6RFIAO6QBQdfqfUKVHfzIQ/UnOPrMWBaBbOgDUnv5L2AaWqVsTEv3JwBBgZgpAKXQA8oi3t9d49Ccq0b+j54RKaY+r8jagnZv8I0WXDk+SBIFNdQ4uZ+ndBwMXwuFxfd7hZ5zcH54PBp6NAlBcevARAURVafqfUHVHfyIR/cd5PbLMZwKMcwlQT6ZKMw5bxFN7+i9wk7KxMrIqF/yMc8FPNu4EmIEJQH/MAUir9vQ/IUMA+mTVf5wXIGsxBFjBBKBX89u2Tx5uHMiIYfI9eaoXSP9K3rbwLIjsy6r/OKv+yRkCTMsEoPTbgivamaBh+p+rnyEAnbLqP84rjgkZAuzLBGAY5gBkEC/917KdwVgHseq/Kqv+7MsQYComAIPx9qAEluSi/1UZAtAuq/7jvMSYjSHAMhOAIXlrIEKKnf6r2+DaZV77sOo/zqo/6zAEmJwJwMC8NRDBxE7/EzIEoCGr/it4QdEWQ4AlCsDwpu0AtZRLspn2DF1v+vfBwL1Z51i3/qdy1kv0X0H0Zyo+GHhCCkCVecIogNLkSf8TKv/oT2lE/xW8gujIoiGAewDKMW0ecmSkHAnTf4Bfofbl/7lAXOu/ggv9acKdAJMwASguUrgciIokjP6TMwRgQ1b9V/CSoR+L6YcAJgDFMQqgFsnTf7BfpzThl/+t+q9g1Z8WGQJsyASgRG4JoHzJ0/+EDAEYZ9V/Ba8RBrGYewigAMTpAIV3TcKY4WwdNf17O6CORF3+jxT9W0n/oj/d8XZA61MA4twSYBRADyz8T6vYoz99Ev1X8KKgBIuJhwAKQOmMAiiEhf9VGQL0qcZTtei/guhPtiFAmdwEXIEZUpQjLO2S/ptQyHM+XZFu823lTl+3+VKgxe6De5nHNBOAyJcDFbvbURHRf0OGAP0oJAdPwqr/CnI/QzEEWIsCEDxnqAHMbLaDZrb0PyF3Akyo9oOV6L+C3Z7yLXZ/J0CBpwCXAFVmtnRV2m5H+aT/qaT9xXtTTiZeiwt+VnDBD4Uo5DMBSmMCkOJyIKMAJif651kBKk2lByir/ivYz6nOYr4hgAKQ67JjNYB1zHxskv7dCdCpcsLxCqL/CkXlG1jmToBxCkC6UYAawDjRvx+lrQAVpa4jkui/gh2b2i0mGwK4B6B6MyewcvZChiX9t8UT0oVyUvIS1/qv4Fp/quBOgBVMACIwCmA2on//iloBKkcVRyGr/ivYkwlmMdMQQAGIY+ZLkNWAhJocgKT/dbgToF2FxGXRf4VCEgxMxZ0A+1IAQpl5FKAG5CH6D66cFaBClHzYEf1XsOsS22KaIYACEFCTNUg1ILCGRxzpf0KGAG0ZNjeL/iuUEFmgIUOAZQoAq1h+eWgCATQ/2In+UVeASlDgQUb0X8G+SiqLOYYACkA07S49GghUTfQfiiFApQFa9F9h8IwCrTMEWKIAxNFd4FADqiP6l6+EFaDBlXNUaetvUUj6F/2hicUEQwAFIIJ+1hpdF1S+to4m0n9zhgC1xGjRfwXRn/BGhgAKQO0GSRgGAgUS/Ws0+ArQsAY/hoj+K2TeGyHbEEABqNXgi4sGAiVo8dgh+rfOEKDYPC36ryD6k80o/RBAAahPK5GixVV8A4FBiP4xpB0CDHXEEP1XyLn7wSRiDwEUgKTRv6MaoAl0rd0jhejfNUOAaXV3uhX9VxD9SW6UewigACSN/uOPtxXcNYEutH6QEv3LkXAI0PPBQfRfIdv+BjNbjDsEUABSR//xr2nxxLzvD1UGZtDREUH075khwORaP9GK/iuI/rCvUeIhgAJQrt6i/6pf325kNxaYnNyfUKohQG8HgUif6tUwOuTZu6B1i0GHAApAiQaJ/qv+562fqo0FVtXpK1/0H5whQEVRu7TtEf2hU6OsQwAFoCwlRP/xb9VRUk9eBno44oj+FUkyBKjilS76A+GHAApAKUqL/qt+2+5O3iu2vIqUMK3eXttyf4EMAarI3IVshugPfRqlHAIoAMMrOfqv+lN6SOcx+kD/p2HRv2rhhwAlv5BFfyDVEEABGFJF0X/VnzjszXxFhYlhz7tyfxUMAcoM36I/MMo3BFAAhlFp9F9rAwbJ4uv/+p3evlwIuT+ewEOAohr7EtEfSDsEUAD6FiP6l/8unzM/RaU9t+Pk/noZAhSSwkV/xnk+6UchQwAFoD8ho3/5TSAMuT+JkEOAcg4Ioj8ws0hDAAWgDxmi/wqaQFvk/mAMAYaK46I/UIgdBQwBFIBuJYz+KyR/s//ZCP3JBRsCDP7CF/2BtixGGQIoAF0R/ccpA+sQ+vMwBOgtl4v+QJl2DD0EUADaJ/pPQhkQ+skwBBjq1S36Ax1ZDDEEUADaJPpn/tivSUj8LDEE6O70KfoDVdgx6BBAAWiH6N+i8eeh0kog7pN8CNDzK1f0B/qxWP8QQAFoSvTvQfmfBCzrM63MQ4DWT5yiP1CjHcMNARSA2Yn+w+r5k4BFfPpX9RCgn4ou+gODWKx8CKAAzEL0L99aT+/6oUTKp085hwAtnjJLSP+if0U822HWCEp47dc+BFAApiP6A32qdAhQ1BV6HRH9oflLYLZjxdKrL1IN6P8UoABMSvQHWpdtCBDjhC36Q1vUgLmBhgAKwMZEf2BA1Q0BAi//i/7QBTWg/1OAArAe0R/oWp4hQNVnaNEfupa5BuzofQigAKxO9AfKUdEQIN7yv+gPfcpcA/o8BSgAK4n+QM8yDAFqPCWL/jCUhDVgR79DAAXgH4n+QLGqGAKEWf4X/aEECWtAb6cABeD/Ev2BYcUeAlR0Dhb9oTR5asCOHocA2QuA6A/UovAhQO3L/6I/lCxPDejnFJC3AIj+QFGiDgHKP+mK/lCL8DVgR19DgIwFQPQHKlX4EKA6oj/UKHwN6EGuAiD6AyWrdwiw1pm42LOs6A+1i1oDdqw9BGhxDShLARD9gRgMARoS/SGSqDWga/ELgOgPVKTGIUAty/+iP0QVrAbs6H4IELkAiP5ASIYAfUZ/TzXUIlgN6FTMAiD6A/WqawhQ+PK/6A/ZxKgBOzoeAkQrAKI/kIEhQKfp33MLyWvAjgI6QKfiFADRHwijliFAscv/oj/QpAYsFjAK6HQIEKEAiP5AQoYAqxL9gUg1oCN1FwDRH4iq/CFAacv/oj8QrAbs6GwIUGsBEP0BDAGWiP5A4BrQhfoKgOgPJFHyEKCQ5X/RH4hdA3Z0MwSoqQCI/gArpB0CiP5AnhrQujoKgOgP5FTmEGDY5X/RH0hVA3Z0MAQovQCI/gDryzMEEP2Bjiz8/0eJaZtApdOAcguA6A9Q4BBgkOV/0R8oeSCw2HENaH0IUGIBEP0BphJ4CCD6A/1bKLIGtKisAiD6A5Q8BOhz+V/0B4a1UFINaHcIUEoBEP0Bmog0BBD9gXIslFQD2jJ8ARD9AaoYAvSw/C/6A2VaKKAGtDgEGLIAtHUyc9wHqH0IIPoD5VsooAa0YpgCIPoD1DUE6G75X/QH6rIwXA1oawjQdwEQ/QG6U9cQQPQH6rVQ8zSgvwIg+gNUOgRofflf9AdiWOi9BrQyBOijAIj+AL0pfAgg+gPxLNQ2Dei2AIj+ALUPAdpa/hf9gdgW+qoBzYcAXRUA0R9gKKUNAUR/II+FGqYB7RcA0R8gzBCg4fK/6A/ktNBxDWg4BGizAIj+AIUYfAgg+gMslDoNaKcAiP4A8YYAsy3/i/4APdSAJkOApgVA9AcoU/9DANEfoIppwOwFQPQHCDwEmGr5X/QH6L8GzDwEmKUAiP4AVehhCCD6A1Q3DZiuAIj+ABmGAJMs/4v+AIPXgNmGAJMWANEfoEZdDAFEf4CqpwEbFwDRHyDVEGCd5X/RH6DAGjDtEGCDAtDKecVxHyDAEGCG9O/4D9BPDRj4k4D35dAPUNcQYNoTz1oc/wH6rAFTrQF1VQAc+gFyfiaA4z9AaTWg8wLg0A9Q6RCg4ZnG8R+gwBowvgbUZgFw6AfIOQRw/AfozvIxtq2BQDsFwKEfoPYhwGznFcd/gPIHAivWgJoWAId+gJxDAMd/gEqvC5q9ADj0E09HH6oK5ZvqROL4D1BdDdh3DWiWAuDQD5BzCOD4DxBgGjBdAXDoB4hnkjOH4z9A7TVgeQ1o0gLg0A+Qcwjg+A8QbBqwcQFw6AcIbJ1TheM/QLAasLQGtF4BcOgHyDkEcPwHCFwDVi8ADv0AGYyfGxz/AWLXgNFotLIAOPQD5BwCOP4DJKkBm5b/h0M/GbT1GdoQieM/QKogtGnv3r1DbwkAANCTzX39IAAAYHgKAAAAJKIAAABAIgoAAAAkogAAAEAiCgAAACSiAAAAQCIKAAAAJKIAAABAIgoAAAAkogAAAEAiCgAAACSiAAAAQCIKAAAAJKIAAABAIgoAAAAkogAAAEAiCgAAACSiAAAAQCIKAAAAJKIAAABAIgoAAAAkogAAAEAiCgAAACSiAAAAQCIKAAAAJKIAAABAIgoAAAAkogAAAEAiCgAAACSyZegNgP7s2bPnkksu+fjHP/6FL3zhyiuvvOqqq2644YYbb7zxjjvu2Lp168EHH3z00Ucfe+yxJ5544oMe9KDTTjvt+OOPH3qTAQBatmnv3r1tf08oy549e9797ne/8Y1vvPDCC2+55ZbJ/8P73ve+T3nKU57xjGfc97737XIDAZjaW97ylqm+ftOmTZs3b95vv/0OPPDArVu3HnrooXe7292OOuqorVu3draNUCgFgMhuuumm17zmNa985St37drV5PucffbZL33pSx/84Ae3t2kANLJp06ZWvs9xxx130kknPeQhD3nkIx/5iEc84pBDDmnl20LJFADCestb3vIbv/Eb3/nOd1r5bps3b37uc5/7ile8wrkBIFIB2NeBBx74mMc85mlPe9qTnvSk/fffv/XvD4VQAAjoe9/73jOf+cx3vvOdrX/n+93vfu985zvvd7/7tf6dARi8ACw79thjn//85//ar/2aC4QISQEgms9//vNnn3324uLiOl/z4z/+4w996ENPPPHEu9/97ne9611vvvnm73//+7t377788ss/+clP7t69e53/9rDDDvvgBz94yimndLDtABRRAJbc4x73+L3f+71zzjmn6x8EPVMACOUTn/jEmWeeef3116/6r8cdd9yv/MqvPO1pT7vXve611nfYu3fv5Zdf/r//9/9+4xvfeMMNN6z6NYcddthFF130kIc8pL0NB6C4ArBkNBq99rWvPeKII/r5cdADBYA4/vZv//b0009fNf0feuihL37xi3/913998ms6r7vuupe85CWvetWrVn2NHHfccZ/61KeOPvroxlsNQGsFYP1U86Mf/ej222+/6aabbrjhhl27dn3ta1/7+7//+09/+tN/9Vd/tdbK0ZJ73/ve733ve0844YQ2NhyGpwAQxFe+8pWf/Mmf/P73vz/+Tz/5kz85Pz8/25v6X3jhhU9/+tNXvZP4jDPO+Mu//MuZNhaAAQrAWm699dYPf/jDf/zHf/zud7/7jjvuWPVrtm3b9v73v9/1n8SgABDBTTfddOqpp37uc58b/6cnPOEJ8/PzBxxwwMzf/IorrnjkIx+5arV43ete96xnPWvm7wxACQVg2eWXX/7v//2/X2tx5/DDD7/ooou8JTQBKABE8MxnPvNP//RPxx8/++yzL7jggi1bmn7i9ac//el/8S/+xZ49e1Y8ftRRR1155ZUHH3xww+8PQAkFYMkf//EfP//5z7/11lvH/+noo4/+zGc+4/pPard56A2Api688MJV0/+DHvSg8847r3n6X7qI6MUvfvH449dcc81rX/va5t8fgHI85znP+fCHP3zYYYeN/9O3v/3tnTt33n777UNsF7TGBIC67dmz58QTT/zqV7+64vGDDjros5/97H3ve9+2ftBtt9320Ic+9PLLL1/x+L3vfe8vf/nLmzfr0gBBJgBLPvnJT/7sz/7sTTfdNP5Pv//7v/+CF7ygrR8E/ZNaqNtrX/va8fQ/Nzf38pe/vMX0Pzc3t//++7/kJS8Zf/wrX/nKJz7xiRZ/EAAlePjDH/76179+1X96yUtectVVV/W+RdAaBYCK3Xzzzeeee+744yeccMLznve81n/cE5/4xOOOO2788Xe84x2t/ywABnfOOef8y3/5L8cfv+GGG1Y9+0AtFAAq9hd/8RfXXHPN+OP/5b/8l/3226/1H7fffvs95znPGX/84osvbv1nAVCC//pf/+vWrVvHH3/961+/6gkIqqAAULHXve514w/u2LHjiU98Ykc/8fGPf/z4g5dddtmNN97Y0U8EYED3uMc9/sN/+A/jj99yyy1veMMbhtgiaIECQK2uuOKKT3/60+OPP/e5z+3ultwHPehB27dvX/Hg7bff/sUvfrGjnwjAsP7tv/23Bx544Pjjb3rTm4bYHGiBAkCt3vnOd44/uGnTpnPOOae7H7pp06bTTz99/PEvf/nL3f1QAAZ02GGHrTr+/Yc7DbFF0FQLb5EOg3jf+943/uCpp556zDHHdPpzzznnnPG3mbvrXe/a6Q8FYEC/8Au/cMEFF4w/fuGFF5544olDbBE04nMAqNINN9xw+OGHj38Uy4tf/OLf+Z3fGWijAIjzOQD7uvXWW7dt2zb+mQBPetKT3v72t3fxE6FTLgGiSpdeeumqH8T4yEc+cojNASCyAw444AEPeMD445/97GeH2BxoSgGgSn/3d3+36uMnn3xy79sCQHyrnl++9rWv/fCHPxxic6ARBYAqff7znx9/8Kijjrrb3e42xOYAkLEA7N27d3FxcYjNgUYUAKr0zW9+c/zBe9/73kNsCwDxnXTSSas+/q1vfav3bYGmFADiFICjjz56iG0BIL7DDz981ce//e1v974t0JQCQJW++93vjj84/hFdANCKQw89dNXHr7/++t63BZpSAKjS+Huxzc3Nbd26dYhtASC+ww47bNXHb7755t63BZpSAKjSLbfcMv7gXe5ylyG2BYD41poA7Nmzp/dtgaYUAKr0ox/9aPxBn2oHQEdW/fCZubm5/fffv/dtgaYUAKp04IEHTjgWAIDm1lrpN3ymRgoAVVr1cv9VbwwAgObW+sCvgw46qPdtgaYUAKp017vedfzBXbt2DbEtAMT3ne98Z9XHjzrqqN63BZpSAKjSMcccM/7gNddcM8S2ABDfWu/3f+yxx/a+LdCUAkCVVj3gfuUrXxliWwCI70tf+tKqj9/znvfsfVugKQWAKt3rXvcaf/A73/nO97///SE2B4DgvvCFL4w/uH37dpcAUSMFgCo98IEPXPXxz33uc71vCwDxXXLJJeMPPuhBDxpiW6ApBYAqrXXM/djHPtb7tgAQ3HXXXXfFFVeMP37qqacOsTnQ1JbG3wEGcNJJJx122GHXXXfdiscvvvji//yf/3OnP/rf/Jt/s+L9Rg844IA3velNnf5QAAb0/ve/f9UPAjvjjDOG2BxoapMPT6VST37yk9/xjneseHC//fa75ppr7n73u3f0QxcXF+9zn/usePD444//6le/2tFPBGBVmzZtGn+wo1QzGo3e9ra3rXjw8MMPv/baa30SMDVyCRC1esxjHjP+4O23337BBRd090M/9KEPjT84XgkACOPaa6995zvfOf74U5/6VOmfSikA1OrJT37yqkfeP/qjP+ruh1544YXjDz7gAQ/o7icCMKxXv/rVt9122/jjv/RLvzTE5kALFABqdfe73/3MM88cf/xzn/vcxRdf3MVPvPnmmz/84Q+PP37aaad18eMAGNz3vve9P/zDPxx//JRTTnn4wx8+xBZBCxQAKvac5zxn1cf/03/6T138uPPOO+8HP/jBigf333//Rz3qUV38OAAG98IXvvD6668ff/w//sf/OMTmQDsUACr22Mc+9uSTTx5//JOf/ORb3/rW1n/ca17zmvEHTz/99COOOKL1nwXA4N773vf+2Z/92fjjp5122llnnTXEFkE7FADq9tu//durPv5rv/Zr3/3ud1v8QW9729suvfTS8cd/+Zd/ucWfAkAhrrzyyl/8xV8cf3y//fZ7zWtes+p7EEEtFADq9vM///OrXoGza9euX/zFX7zjjjta+Sk/+MEPnv/8548/vmPHjic84Qmt/AgAynHVVVedccYZu3fvHv+nF73oRT4AmNopAFTv1a9+9apvB/SBD3zghS98YfPvv3fv3l/91V/99re/Pf5Pr3jFK/bbb7/mPwKAclx++eWnnnrq1772tfF/+umf/umXvvSlQ2wUtEkBoHonnXTSK17xilX/6b//9//+ohe9qOH3f97znveWt7xl/PGf/dmfHY1GDb85AOXYu3fva1/72oc97GHf/OY3x/91x44d8/Pz1n0IwCcBE8HevXvPPvvs97znPav+6znnnPMnf/InBx988LTf9sYbb/z1X//117/+9eP/tG3btssuu+y4446baXsBKO6TgC+66KIXvehFn/rUp1b91yOPPPLjH//4jh07Zv7+UA4FgCCuv/76n/mZn1n1Pt2lZZs/+IM/ePzjHz/5N/zoRz/6zGc+88orrxz/py1btnzgAx84/fTTG2wvAEUUgC9+8Yvvete7/vzP//zyyy9f62uOP/74D33oQz73nTAUAOK49tprH/GIR3z5y19e6wtOOeWU5z//+WedddZd73rXtb7m+uuvf8973vOqV73qb/7mb1b9gs2bN7/hDW9Y9a0hABi2AJx//vnr/Ce33377rbfeeuONN+7evfuaa6658sor/+7v/m7Dt4x7+MMffsEFFxx99NGNNxlKoQAQyrXXXnv22Wevld2XHHDAAQ972MMe8IAH3Oc+9znssMP233//3Xf61re+dckll1x++eXrvHfQ/vvv/4Y3vOFpT3taN5sPwKR6eCPOzZs3v+AFL3j5y1++6ltNQL0UAKK5+eabf+VXfuVNb3pT69/5yCOPvOCCC0477bTWvzMApRWAn/qpn/pf/+t/PfShD+30p8AgvAsQ0WzduvWNb3zjO97xjqOOOqrFb/sLv/ALV1xxhfQPEN6pp576rne962/+5m+kf6IyASCsG2+88dWvfvUrX/nK733ve02+z6Mf/eiXvexlD3vYw9rbNACKmwCcdNJJT3jCE57+9KefdNJJ7X5nKI0CQHA333zzO97xjje+8Y0XX3zxbbfdNvl/+OM//uNPetKTnvGMZ9zvfvfrcgMB6KkAbN68ecuWLXe5y10OPvjgww8/fPv27fe4xz1OOOGE+9///qeeeuqRRx7ZzZZCcRQAsrjxxhs/8YlPfPzjH//iF7945ZVXfvvb377hhhtuvPHGvXv3bt269eCDDz766KOPO+64E0444eSTTz7ttNOOP/74oTcZAKB9CgAAACTiJmAAAEhEAQAAgEQUAAAASEQBAACARBQAAABIRAEAAIBEFAAAAEhEAQAAgEQUAAAASEQBAACARDYNvQHQstFoNPN/u7Cw0Oq2QNgXCwTj+E8qW4beAJiCvAItWlhY8JoCSGXpsK8AUCKhBACgo3ClADAwWR8GZAgAEN74cV4BoG/SBgDAgKFLAaBzEj+UzBAAIJ71D+wKAO0TJgAAio1hCgDtEPqhXoYAAAFMfiRXAJidxAAAUF0kUwCYjtAPIRkCANRotkO3AsBEKkoGO+a3rfOvizt397gtEMr8tu1DbwLMbufuXUNvApSSzRQAasr964d7oNMhwM7du3QAgADxTAGgxNAv6AMAdBTSFACGz/3iPhTCEAAgQ05TABgg+kv8AABD5TQFIK8+c7/ED7UwBAAIH9UUgHT6yf0SPwDAUGltftv2dd75SgHIoofcL/RDDIYAAFVH/w2/RgGIr9PoL/QDANQS/ZcoAJF1F/3lfojNEAAgZPRfogAE1FHuF/oBAKqO/ksUgFC6iP5yP+RkCAAQL/ovUQCCaD36y/0AAMGi/xIFoG5yP9AdQwCAYNF/iQJQq3ajv9wPABA++i9RAFJHf7kfWJ8hAECk6L9EAaiJ6A8AUIVRkdF/iQKQK/rL/cC0DAEAwkT/JQpA6UR/AIAqjIqP/ksUgODRX+4HmjMEAIgR/ZcoACUS/QEAqjCqKvovUQDKIvoDZTIEAAgQ/ZcoAKF2I9EfAKBro2qj/xIFIMJuJPcDPTAEABhVHv2XKAADE/0BAMo3ChH9lygAgxH9geoYAgAJjQJF/yUKQH17kugPANCDUbjov0QB6JvoD1TNEADIYBQ0+i9RAPoj+gMAFG4UOvovUQBK35lEf6A0hgBASKME0X+JAtA5C/8AACUbpYn+SxSAbln4B0IyBABiGCWL/ksUgK6I/gAAxRqljP5LFICCdinRH6iIIQBQqVHi6L9EAWiZhX8AgDKJ/ksUgDZZ+AdSMQQAaiH670sBaIfoDwBQINF/3OZVHmNK0j+Q1sLCwvpfsHP3rr62BeCfGN2pyXeY37Y9Xvo3AWjBDDuW6A8A0B2r/utTAGZn4R/AnQBAUUT/SSgAM7LwDwBQDtF/cgpAH3uY6A/EZggADEj0n5YCMB0L/wAAhRD9Z+NdgKYg/QOsxdsBAX3yDj9NmABMymU/AACDs+rfnAKwMQv/AJNwJwDQKdG/LQrABiz8AwAMS/Rvl3sA1iP9A0zFnQBAu1zr3wUTgDVJ/wAAQ7Hq3x0FYBWiP8DM3AkANCT6d00BWEn6BwAYhOjfD/cA/BPSP0Bz7gQApuVa/z6ZAPyjqXY70R8AoDmr/v0zAfh/pH+AFhkCABuy6j8UE4D/S/qPZ3Hn7qE3AeiWCkFRi9BkOw7M11w8shcA0b9eIj4UztsBAZQpdQGQ/msh6wMAtCVvAZD+iyXuQxiGAAAFSloApP+iSPwAAL3JWACk/xII/ZCEIQBAadIVAOl/QEI/AMDgchWAydO/6N8WoR8wBAAoSqICIP33Se4HAChTlk8Clv77sbhz99L/Db0hQFl8MDBAOVJMAKT/rhWY+Nf6o2+YQoAY5ufnh94EyrJz5851/tUOw7T7TNXiFwDpP2ru97HtUBd3AgAUIngBkP5j5H5ZHwCgLZELgPRfb/SX+CEkQwCAEoQtANJ/Xblf4gcA6EfMAiD9VxH9hX5IyBAAYHABC4D0X3L0F/oBAIYVrQBI/w3J/UDXDAEAhhWqAEj/RUV/oR8AoEBxCoD0X0j0l/uBDRkCAAwoSAGQ/geP/nI/AEAVIhQA6X8Goj8wLEMAgKFEKAATkv7bjf5yPwBAjaovABPGUOlf9AdKYwgAMIi6C4D032f6l/sBAAKouABI/xMS/YFiGQIA9K/WAiD9T0L0BwAgQgGQ/ruO/nI/0BtDAICe1VcApP9O07/oDwAQW30FYBJp07/oD9TIEACgT5UVACG1i/TvWQUAyKOmAuDin7WI/kDtDAEAerN5rhLS/1qkfwAAok0ApP9Vif5AJIYAAP2oowBMQvqfhOgPAJBcBQVgksyaKv2L/kBUhgAAPSj9HgDpfwXpHwCAsAVAbG2e/kd36mZzANq3sLCw/hfs3L2rr20BiKmCS4DWl2T5f7bo3822AABQsXInAC7+WSb9A6kYAgBknABI/zOnf9EfAIDKJgAi7JLFnbulfyAnQwCAdBOADYVf/hf9AQBIMQFw8Y/0DzDJEACACAVA+pf+AQDoVEGXAAmyoj/AVB8MDED1E4DMy//SPwAAiQpA8ot/pH+AVbkTACDmJUDS/+RfLPoDABBhApCW9A+wPkMAgGgFIPPyv/QPAECuAiD9T2J0p443B6BchgAAoSYAOU2V/jveFgAAEhmyAKRd/pf+AaZlCABQ/bsA5Uz/LvoHAGBY5V4CJP13uS0A9TEEAKi4ACRMt9I/AABJC0DCi3+kf4BWGAIABPkk4Njc8gsAQN4JQMLl/wlJ/wCTMAQAiHYTcLD0P+Hyv/QPAEDAApAt5kr/AF0wBACoowBku/hH+gcAoEAFXQIk/QMwIUMAgNLfBShV0pX+640Iq/5R5AyA6uzcubP518/Pz7e3RVCQUt4GNMzyv/Q/iE4z+lp/LMUAoLqg38o3VwyoXR8FIE/Ylf77UUjyHv87FrJhAFF1GvebbIZKQF2KmADEWP6X/jtVRbbe949bxQYDlK+Q0D/5RioDlK/zArBh3pX+WUvVGVoZAIgd+teiDJC9AMi7TCtkVlYGAGKH/rUoA5Rp4EuALP+TLRYv7wZ5fmWAbLl//d9UEyByAUiSd6X/JjKHYE0AyCxP7h+nCZB6AhBg+V/6n5nUu2L38IQASWSO/qs+FWoAcQpAhsgr/c9AzF2LgQAQm9y/FgMBEk0AAiz/T0L6XzZUrj132z85nv7W7p2Tf/GGX98FAwEgmKGi/4pT8PrH1RI+2sVAgLoLQIa3/pxk+V/67/MAOp7dO/22XRcDAwGgdr3l/o7OtkN9DLyBAFk+CKw60v8kOj1EdhT3m2xAR5XAQACoTqfRf/DTa2+zAgMBaioA4Zf/J7z0P7OODoWDh/7JN6/1MqAGAJmj/+Chf8APe1ED6IIJwFzCQ1V3Wj/wFR76ey4DagCQJ/pXeibtqAyoARRdACz/13vMaqjdVFpp7l//d2mrCagBQODoH+kc2vrdXGoAbTEBmIL0v5a2Dm2Rcn/XTWA0GukAQJj0H/vs2W4T2Llzpw5AQQUg9vK/S/9X1cqxLHbu764JGAUAtUf/2Lm/uyZgFEBDJgBtSnUga547s+X+jpqAGgBUF/1TnS67awJqADPbPNcSy/+pDmcN4+a52+al/3afkFS7H1Bv+h/dqb3NqV7zJ8RHLDMDE4CNSf/tRv/2tiWapSdn5mmAUQBQePRvb1uiaXgANwpgmAIQe/mfJU2Spdzf23VBagBQVPSX+3u7LkgNYIBLgKKy/L9k5kDpap+ZNXnqMuyTQOHp39U+M2vy1LkiiFIKQL3L/9J/k/Qv+rdi5qcxw54JdG22NCn6t2Lmp1EHoI9LgDK/yMP/7k0W/tveltTO3TY/wxVBLgcCBln4b3tbUpvtU19cDsT6XAK0Jm/8b+G/KEYBQG8s/BfFKIDiCkDU239d/DND+hf9ezDbkxx7XwXaNUNqFP17MNuTrAOwKm8DOqPAR7rZon8320JrbxjqciCgo+jfzbbQ2sHc5UC0PAHIvPwflfRfEaMAoEXSf0WMAmjIPQArZb74Z9r075qfwc3wJ4i69wJNTJsOXfMzuBn+BDoAfRSASpf/NxT1kDdD+u9sW5iODgD0nP472xamowPQ9z0AIV//OS/+Ef0T3hXglgBA9I9h2uO5WwLocAJg+b8W0n8kRgHA5KT/SIwC6KMAhDwKJFz+l/7j0QGASUj/8egATM5NwHkPf1Olf/f7VmTaP1awHRtoN/m537ci0/6xdIC0ZikAId/9c8Pl/+Tpv8ttoRM6ANBK+u9yW+iEDsCGTAAyXvwj/SehAwArSP9J6AD0XQBqXP5PdRCcPP277CeAqf6IkfZzoEnOc9lPAFP9EXWAbKYuAPGOCKmW/6dK/x1vC/3RAYCp0n/H20J/dABW5RKgRIdC6T8zHQAyk/4z0wHovABUd/1PnuV/6R8dAHKS/tEBaFQAEh4aYvzK0j9LdADIRvpniQ5AVxOAeMv/MY6G0j/70gEgD+mffekALHMPQHDSP+N0AMhA+mecDsDUBSDYASLD8r/0z1p0AIhN+mctOgBtTgCqu/6HZdJ/Tv7ugPSfk787m3PuK5b/l0mBmU341w/wcoBUJly49dLObMK/viFAVO4BiEn6Z0I6AAQj/TMhHSCzzQmv/wm//C/9MxUdAMKQ/pmKDpDWRAXAkaIi0j8z0AEgAOmfGegAObkEKOORUfpnnL0CMshwjmNa9oqEWigAwa7/Cb/8L+fRZN9wnoAyTbJA6/VLk33DECASE4A4pH+a0wGgRtI/zekAqWxOdcgIfPvv5J/5Bc3V+0qBeGQy+mR/i2Fzqut/krP8zyTsJxCP0s4k7Cd5JLoEKPnyv1TH5FwIBLVw8Q/tciFQEhsUAEeN8kn/dEEHgPJJ/3RBB8ig0QQg0vU/lR4iXfrPsCp94UAAEhjDsgdWLcslQLHf/XN9lv+ZjT0HaqeiMxt7TuoC4M9fOBf/0DUXAkGZXPxD11wIFFuKCUDg23/XJ/3TnL0IahT1vEaf7EWBzV4AIt0AUCNX/1MOJwnok2VXymFvrFSKCUC87OLiH/rkQiAoh4t/6JMLgdIVgDCHj5y3/0r/tMseBbUIc/qmEPaokGacALj+Z0Au/qFMThLQNUuts1m40yRf4ww7G3tmdbbM5RYyslispQvnbpv/rd0O8VC0kCe1aTUM8eP/uWd1NBqpRsEELwDxrv/Z8BUo/TNgB3CSgAEXWTPn1E6PPPt+87RP8oaH9507d87PSyCVF4Ak+3d1v6ZoRfl0AOiCSyxW1f/RZvknVhcheqADBJ8AuAGgWJb/6ZoLgaBMqfJoCasMCZuA9Z1IIr8NaLDrf7zqqEWe0yH0w/L/sgLv0y1wkwZkX61F8HsAUmUUy//0wxAAShPvjLZC+Qk7yUDAECDyBCD2vlsprzfq4jACbUm+pFrd+np1G9y65Hts2EuAarkBINj1Pxuy/E+f7G9QjsB9u94kXe+WZ97fUol8D0CY3ddbf1KgDfe6ul5lUKa0b/0ZYB09wK8w815nCFC+vPcAAACl6SI0Ly1YrH/z0vKiRrv3OC39OlF7GvWKWQAiXf9j+Z9i+Vww6FTC5f+2jhhNzowr/ttW+sDCwkKwP5bPBYtWAILtoABAhvTf0XLYvt+2SRmI1wGo2paQdwCvL9Ir0PI/w/KWoDCUSOeyJtG/z/Ngw8uEgl0OZMZbtaQ3AdfCS4vahTnVQc/y3EY585nu3G3zQ62CNfnRec7sefbhGgUsAJFuAACAwGZLwwNG/1Y2I08HoFgBC0CY9Ui3/1IF7wcKrUty++8MObiQ6N98k2J0AO8HGqQAxDigAACFmzYBFxj9G25ejA5A/AlAjDuAwyj5OEg29kboU+2rddN+Qlbh0b/Jpgb4sLDa98a0ol0CFOYGgNqPCLAvZwiYXOyrJmZY+J+rjVFAnv25XtEKQJIUUuMBkdjsk9CPMCeySAv/wTZ+Wnn2yUhyFYBaxF4MICdnCJhE7OXSyc9uMdLz5L9F7PN+7L26+gLg9AwAdCRb+l+iA1D3BKCKO4DD3ACQ58hIJPZM6Fq9S3UTptuQV85M/kvV2wHq3TPTSnQJUC17Z72vf4jxGoShRL1SYvL0PxdX+A6Qc9+uV6ICAAD0TPpflrwDUBQFoDIZDpHUy/4J3Qk8Q8tz6Aj8mwbeP0NSAMqi9xObMwSkukZikpNa4Ew88+8bMgyE3MPrFacAJLkDGACqIP2vJW0HoLgCsP6yXBVvAZRh3THngZK62EuhC9WdxeTXhM9hdXtpZnEmAABARTKvF2T+3SmBAlCQ6ro+zMASEYS/PNrFP5NIeCFQsP28agpANRwrqYV9FdoVrzY7SkR9HuLtq1EpAABAa4ItWg/O80kXNmd4CyB9FAB64OKfaSW8EIgSBCkAAXh5k4dODmkvjJb+kz8nqfb2kikAdUh1dCAAeywkLMxWsrpT0XNb0R6bvQCE/xAAAGBwlgbW4pmhZyYAAACQiAJQhIpGe9AKM2IIdkn0hicyi9wNn58wUSHMPl81BaACDprUyH4LzanK1Mh+W74IBcB7gALAgCz/tyLPEIDBRSgAAADAhBQAAKBDlv8n57miHwoAADA716X0ybNNKxSA4Xkxk5P7cyDD26FY0p5Whmcsw55fOAWgdBkOBERl74UmlGTqZe8tnAIAAMzIELt/nnOaUwAAgE4YA87G80bXNq8/o9kxv63zTQAAAPpiAgAAAIlUXwB8DDAADMLF6EPxzJO9AAAABXIhexOePTqlAAxMiSczMzoy81boZGb/H5YCUDQLANTOPgyzUY+pnX24ZAoAAAAkogAAAEAiCgAA0PI9bC7/a27959A9hDShAAAAQCJbmrzLfvlq78e/tds98kBXYt+iV/t7jDh/EV7tL9Kdu3fNRS0AkIozFkBONR7/a2+JDMglQAAAkIgCAAAAiSgAAACQiAIAAACJKAAAAJCIAgAAAIkoAAAAkIgCAAAAiWzwQWA75rfNlW39zyou/3Mu1/8Uj3O3zfe4LVnU+Gkv0L/5bdvnav4Yzvn5+ao/BtX5qwuO/0Wp/UW6UPMHsfkkYKjgpFU1Z1ygCgUe/9c/ftbeEhmQS4AAACARBQAAmNr6y89Gf83VvvxPyRQAAABIRAEAAIBEFICiGaFSO/swzMbdk9TOPlwyBWBgruEjM6cHMiv/PRChO/b/YSkAAED7DACb8OzRqeoLwPofVWZ9EQA6Yog9FM882QsAAAAwuc3rr5Ev7tw9xTcDAADKZgIAAHTCheyz8bzRNQUAAJiRi9H75zmnOQWgdJYBqJe9F5rwPhbUy95bOAVgeKo8OTk9QIa3QrcQMK0Mz1iGPb9wCgAAMDvLWH3ybNMKBQAA6FCGJe22eK7ohwIAAACJRCgAPgwYAEq+LsXC9iQ2fJZc/0NbIhSA8Bw3qZH9FpqzhkWN7LflUwCKoNOTjdMDBHs7FEOAhvIs/4fZ56umAAAAQLICsP5S3OLO3T1uDwAQkyHAWjwz9MwEoA4ODdTFHgsJr5cLc41KgSp6bivaYzNTAEpR0WsbGnJ6gLSXRFsdSP6cpNrbSxakAHgnUACoYjErVd5t5dmwREjrghQAAKAE0mq7PJ90QQGohiUTamFfhXbFm2M7SkR9HuLtq1EpAAXR8snA6QHCXxjtQqBJJLz4J9h+XjUFAAAYQOYOkPl3p6ACEP6jAGIsOjpeUD57KXShurNYsKXrQVT3HFa3l2YWZwKw/hsBAQB9ciHQWhJe/ENp4hSAGLzgic36EKS6PFoHGJc2/Yfcw+ulAFQm24GSutg/oTuB+3OeQ0fg3zTw/hmSAgAAdGXCxezAyXja3zHk8j+lSVQAaummXvlEVctrEIYS9RoJHUD6j7pvxy8AVbwRUJL7gGMfIqmXPRO6Vm+LnrwDxDuSTP5L1Zv+690z0/rHAuCPBwB0ZPJ0G6kDTP671Jv+qVGiS4Aq4ihAPJYYYBKxr5TI1gGk/wx7daVyFYAwESTGkZFI7JPQjzAnstiXA1W98dPKs09GEq0AhLkNIPZiANk4PcDkYi+XTnt2qzFGT7vNsc/4sffnFAWgivuA86jxmEhU9kboU+2NenSnkKvp027qtE9FgWrfG9P6JwXAXxEAKHMUUHINmGHzao/+VC3aJUAbqqjkbHhoKPlQSB4b7ocVveiglqsmYrysZkjABdaA2TYpRvrfcD90/U+xAhaAMLcBAEBss+XgQmrAzJsRI/1TtYAFIBLHCGoXY50S+pdn6XTmM92ANaDJj85zZs+zD9doy1Rfvbhzd4D19YWFhTAvv9/avfPcbV5gDKaERTjIKdK5bOkXmW29YPko1MPZsOERL8zfa4n1nVAFINIBBQCoxWg0apIp903nLZaBtpY5hCsqngDUYsf8tjBvWrrhAdEQgKG4/Rc6NT8/v3Pneq+yeGt2DTvAWkenqc6SXQw2g/2Z3P4bQMwCAABkuxyoYaYX/ckj6U3AdS1Mej9QCmT5H3qQ5P1AQ35CVoBfYS2W/zMWgFourQlws/JUdAD6ZH+DckTtAFUvn9e75Zn3t+wFwJ+2QIEPJYTkMAJtSb6YWt06enUb3Lrke2wt8t4DEO/eKXcD0w/L/1CaeGe0FZZ/u2IXF2I//8uKff6ZVuR7AIJdBZTk4EIAzhDQLkuqJa+vF7hJA7KvRp4AxPg4sJAMAeia5X8oU/ghQGkDgTzP9jKLO/EnAEn+xtX9mgkPN1SnupcVVMHC6jqr732eHPv/iRWxl1Yk+D0AkT4RbInPBWNA3voTBpTwc8Emt+8v3vqBKO2zui9v/RlM8AKwoZCHSx2ALrj4B8oX8qQ2rfFnYKpK4AkcZ3EnnhlvAg62rF4XxybK5AwBXbPI2ul1O67tmZk9M04BCHMuz3m/ssVa2mWPglqEOX1TCHtUSJHfBjTwnj3JEoXERlsm2ZdqfB1B1KVWr0faMsm+ZPk/VwFwFdCwjCkph7QBfZK3KIe9sVIpJgAbXgUUNb4YAtCcvQhqFPW8Rp/sRUkLgD984VwIRNdc/ANlciEQXXPxT2wpJgBpbwVeogMwG3sO1E4HYDb2nPAaFYBItwFUuq+7E4BhVfrCgQAsvjIse2DkAuDsXj4XAtEFF/9A+VwIRBdc/JNBlkuAYt8KrAPQLukfaqED0C7pP4mmBSDSVUDh6QBMwn4C8egATMJ+ksfmVHtD8iEAtKXeVwrEYzmWPtnfYkh0CVB4LgSiORf/QI1cCERzLv5JpYUCUNdVQLHfD1QHoAnpH+qlA9CE9J+NCUDG46MOwDh7BWSQ4RzHtOwVCU1UAOwZ8W4GkPaYYX9wKICSTbhA64XMDPuD5f9g2pkABLsKqPaDow7AVKR/CEMHYCrSf1ouAYpJB2BC0j8EowMwIek/s0kLQLAjRfghgA7AJKR/CEkHYEPSf3KtTQDqugqIfekAOfm7AzpATv7ubE67uxgC7EsWzGbyv3iAFwIkNPnCrdd4NpP/xS3/B+YegOB0AMZJ/5CBDsA46Z/2C0B1VwFlGALoAKwg/UMeOgD7kv6ZsQAkPEDE+JV1AJZI/5CNDsAS6Z8OLwGKNwQIQwdA+oecdACkf1ZwD0CiA6IOkJn0D5npAJlJ/7RQAOIdGvIMAXSAtKR/QAfISfqnpwlAdVcBZTsaTtUB1IDaTfVHjLSfAw07gANC7ab6I0r/2bgEKN0QYKoOYBRQtan+dk72kMFUOc9hoV5T/e2k/4Q2d7FX1TgESPKWoMt0gPCkf2BVOkB40j8bMgGYS3scnLYDqAG1mPaPFWzHBlrvAI4StZj2jyX9pzVjAQh5LMh2IdC0HcAooArT/o1CvpaB1pOfY0X5pv0bSf+ZdTUBqPEqoJxHQB0gEukfmJwOEIn0z1S2zM1qYWFh2uxYvh3z26JWl3Us/R0nP3Yspcxztzl2FET0B2awlAJ37pzuvcLinf2rJvpT1j0AUZN01ORkFFAv6R9owiigXtI/s3ET8Cx3AkQ99s3QAdSAYc3wJ4i69wI9dwAHk2HN8CeQ/mmnAIR8P9CcdwMvm2GwqwMMZYZn3gkbaDEdOqQMZYZnXvqnnXsAkgt5C8RstwS4K6B/oj9Qwi0B7gron+hPEZcAZR4CxE5Us40CTAO6NtuTHHtfBUoYBTjOdG22J1n6Z1XuAVhT5guBlsy2oqMGdGTmJ9ZZGegnNaoBHZn5iZX+6bAAZH61h//dR3ea4T/UAdo1c/QPv4sCHZm/0wz/ocNOu2aO/tI/A08AKr0KyIVAy4wCBmThHxiQUcCALPzTHZcAbUAHWDLzDV5qwMyaPHUZ9kmgHzOnSTVgZk2eOumf/t4FaMO3xFncudsl9QnfHWjZcpD1TkEbatiXnG6BEt4daPyg5J2Cuj6Ai/5MztuAbmzH/LYNr2IK/K6gLdYAbxi6PtEfiFoDvGHo+kR/ar0EKOr7gS5xIdAKDY/grgtq/QlJtfsBA2qYNV0X1PoTIv0zAxOANuWZAzQfBbguqK33SnIqBeoaBbguqK1Dt+hPEQUg9p0Ak1wIlFDzGpCwCbQ1/RD9gaprQMIm0NZxW/SnIROAKbgZYC2j0aiVg1rsJtDuVU/SP1CC+fn5hh0gQxNo94gt/VNcAYg9BNABuh4FhGwCrd/tIPoD8UYBIZtA64dr0Z+2mAB0ImcHaL0GrEjPFZWBjm5xFv2BJDVgxRGvolNqRwdq0Z/SC4AhAK3XgCrKQKfvayT6AzlrQBVloNNDtOhPF0wAZuFCoAFrwFppu+dK0NvbmIr+QHU6qgFrHRV7Ptv2dlgW/amsAIQfAugAk1t+Bro+Yq6VyBsWg6E+r0DuB2q3nF87agIbHjAbnoKHOg7L/fRgU0ffd5JXXe0dYMILgXSAfcm1G/IU0Zv1j07z27bPlW3n7l3r/KsUVZqua0AAdtq6dtqFms/XXV0ClGHxe8KbATI8FQUOBKrjCQFi620gUB25n/5tnhtOgFtpJxxiyHbjRncaeiuCfA48QEXm7zT0VhTBU0HAm4CTrHybAzSReSCQ8FcGWJZ5ICD0k/1dgALcDawDtCJPEwj/CwJMJU8TkPvJUgBEXqa17w4TJiuH+UUA+snHYcqA0E+udwHa14YdIMAQwJsCda26DF3dBpOQdwGiCtWVAfteGDu9C1CnXAhEjMlAsRsGUK8qJgNCP3XpowDkibw6QD/Gn71Bkre4DzB4zh6kEoj71K6ICUCYIYAOMJS1nsxWMrqgD1CstbJ4K8VA0CeqngpAqryrA5Rj1Wd4/UAv7gMknBXI+qQy5AeBxftcsGU+IAwAILBRzcu4/RWAScKuDgAAAHEmANnCrg4AABDVqNohQEGXAMUbAugAAABkLwDZLgSanA4AAFCXUZ1DgOImAPFM/vamC3fqeHMAAEhtgAKQcAgw1Ucc6AAAALUYVTgEGGYCkDDj6gAAAJSg3EuAgg0BdAAAgJBGtQ0BBisACS8EWuoAU90S0PHmAACQzpATgJwdYNrbgjveFgAAcg0Byr0EKDYdAACAjAUg7RDA24MCAEQyqmcIMPwEQAeYkA4AAECEApCcDgAAEMOokiFAEQUg8xBghg6gBgAAUHcB0AGm6gBGAQAAZRrVMAQopQBMSAdYpgMAAFB3AZBop/qYMJcDAQAUaFT8EKCgAuBCoCVGAQAAZCkAOsASHQAAoF6jsocAxRWACekAK7gcCACAWguAIDvbLQGeOgCAQowKHgKUWABcCLQvowAAgNLMb9s+V61CC4AO0KQDGAUAAAxuVOoQoNwCMKE8HcAoAACgHPPVDgGKLgDyayujAE8jAMAgRkUOAYouAC4EaqUDqFIAAF2Yr3MIUHoB0AFauRzIKAAAYBCj8oYAFRSACaXqAE1GAWoAAEDmIUAdBWDCzJqwA6gBAACFGxU2BKijAOgA65itA7gxAAAg5xCgmgKgA6zDKAAAoGSjkoYANRUAi9bdjQI8sQAASYYAlRWACSUcAjQcBagBAABJhgD1FQAXAm1o5g6gBgAAhB8C1FcAdICuRwHLNUATAACINwSosgDoAP3UAAMBAIB4Q4BaC4AOMDk1AACgEKMChgAVFwAdYCoNO4DrggAAYgwB6i4AOkDPo4AlagAAQL1DgOoLwOR0gC5qgCYAAFDXECBCAZg8g+oArdcAAwEAgLqGABEKgA5QTg3QBAAA5sseAgQpADpAITVAEwAAKHwIEKcA6ABF1YB9m4AyAABkM1/wECBUAdAB2qoB7TYBYwEAgHKGANEKgA7Qli5qgLEAAJDHfKlDgIAFQAcovwYsUQYAgORGQwwBtswFtbCwMOETurhzd3cZN4bl56e7vrSiAwz+ARkAAM3Nb9u+c/euucKELQA6QBeWnqUexib6AACQxGg06vlqiMgFQAeodyCwwqqvCq0AACjffHlDgOAFQAcI1gT2tX5XVg8AgFqM+h0CbJrLYfI4qAM0EeCmanckk8f6B8Zi37xiWWkrakAq81MeJDc8ZPWZQGK+C9A47wtU9ccIAADENurx4oUsBUAH6JkmAABQ5lg1UQGYtgOoAe02AWUAAKCEIUCuAjDt9VU6QLuUAQAgrflihgDpCoAOUAhlAABgkCFAxgKgA5RcBvQBACCq+TKGAEkLgA5QUR9QCQCAPEbdDwHifxBYK58R5mPChrXqM6+VAQDVmS/gg4FTF4DlOcDkHxXsk8LKsf4fQj0AACo16viDgbMXgCVGAfGs8zfSDSCGQS6lbWXdzieOD6L2j74mkvmhhwB57wFYwS0BAKxj5+5dzU/YC3dqaYuAyEZd3gmgAMzeAdQAgAxEf6B1ww6dFIB/Ytqjsw4AEJjoD4QcAigAK+kAAIj+QOAhgJuAm741kHcHAojEbb5A+LcDMgFYk1EAQCpW/YEkQwAFYD06AEAGoj+Q6k4ABaD9DqAGANRC9AcSDgEUgE6O7DoAQOFEfyDtEEABmJRRAEAMoj+QfAigAExhhmO9DgBQDtEfqFS7QwBvA9rtO4QudQDvEAowLG/uCZRsftv2Vg5TEzIBmIXLgQBqYdUfiGHU3hBAAej1ciA1AKA3oj9Qkfke7wRQAPo+K+gAAF0T/YGQRi0NARSApowCAMoh+gP1mu9rCKAAtGC284QOANAi0R/IYNTGEMC7AA327kDLHcB7BAE04R1+gDDme3k7IBOAIkYBpgEAM7DqDyQ0ajwEMAEoYhTg4wIApmLVH4hqvvshgAlAJ4wCADpi1R9g1GwIYAJQ4ijAjQEA46z6A0nMdzwEMAHo1sxnGtMAgGVW/QFaHAKYAJQ7CnBjAIBVfyCn+S6HACYAPTEKAJiKVX+AjoYAJgDVjALcGAAkYdUfYK7LIYAC0Dc1AGAtoj/AVEaj0QwHPZcADaPJ+clFQUA8LvgBGDe/bftcB0wAqhwFmAYAYVj1B+h5CKAADEwNANIS/QEGuRNAAYhTAzQBoBZtncykf4C56YcA7gEoSPMzmdsDgAzX+rvcH0hlvu07AUwAQo0ClrguCCiQVX+AQoYACkCJ1AAgEtEfoKg7ARSAFDVAEwAGIfoDFDgEUABS1AADAaBnoj9AsUMABSBjDdAEgO6I/gCFDwEUgIw1wEAA6ILoD1DFEEABqE/rNUATABoS/QEqGgIoALVqsQZoAsDMRH+A6oYACkDdlk+ZmgDQM9EfoNIhgAIQRLsDAU0AWIfoD1D1EEABCKX1GqAJAPsS/QECDAEUgIBavy5oRRNQBiAh0R8gzBBAAYisi4HAEmMByEP0Bwg2BFAA4uuuBhgLQGyiP0DIIYACkEVH1wXtSxmASFpJ/6I/QIFDAAUgnR6awIoyoA9AQqI/QLFDAAUgr36awBJ9APIQ/QEKHwIoAHR7k8Cq9AEISfQHqGIIoAAwwEBg/T6gEkB1RH+AioYACgAr7buL9F8G1qoESxQDKI3oD1DdEEABoNCxwFTFYF9KAvRD9AeodAigAFBlE2hYEoAmRH/iaetTL6AKCgD1XSAEDEX0BwgwBFAAmJ0yAHmI/gBhKAC0QxmAqER/gGBDAAWAzuOCPgCVEv0BQlIA6Jw+ANUR/QECDwEUAPqmD0DJRH+A8BQASkwbWgH0T/QHyGA0GikA1BREFAPogugPMJfJ/wd1w/zAUAGxEgAAAABJRU5ErkJggg=="
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:9)_272
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'RyRyRyRy'}.\nthe 2th action is Cut the right side of the shape\nthe 3th action is Cut the right side of the shape\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is Stack the original shape on top of the {'layer1': 'CyCyCyCy'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'WcWcWcWc'}.\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is Cut the right side of the shape\nthe 9th action is Stack the original shape on top of the {'layer1': 'SpSpSpSp'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:9)_148
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is Cut the right side of the shape\nthe 5th action is Cut the right side of the shape\nthe 6th action is Colorize the top layer of the original shape with the color blue.\nthe 7th action is Colorize the top layer of the original shape with the color green.\nthe 8th action is Stack the original shape on top of the {'layer1': 'WpWpWpWp'}.\nthe 9th action is Stack the original shape on top of the {'layer1': 'RyRyRyRy'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:9)_115
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'CcCcCcCc'}.\nthe 2th action is Cut the right side of the shape\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is Stack the original shape on top of the {'layer1': 'WcWcWcWc'}.\nthe 5th action is Stack the original shape on top of the {'layer1': 'WyWyWyWy'}.\nthe 6th action is Cut the right side of the shape\nthe 7th action is Stack the original shape on top of the {'layer1': 'WuWuWuWu'}.\nthe 8th action is rotate the shape clockwise 90 degrees\nthe 9th action is Colorize the top layer of the original shape with the color purple.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_182
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is Stack the original shape on top of the {'layer1': 'CrCrCrCr'}.\nthe 3th action is Colorize the top layer of the original shape with the color green.\nthe 4th action is Colorize the top layer of the original shape with the color yellow.\nthe 5th action is Cut the right side of the shape\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is Colorize the top layer of the original shape with the color green.\nthe 8th action is Stack the original shape on top of the {'layer1': 'CrCrCrCr'}.\nthe 9th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:9)_337
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAgAAAAIACAYAAAD0eNT6AAARPElEQVR4nO3dC24c1RaG0WAxAQbXke5MegieSaR4cAyBqxMI2E673d1Vp85+rCWBRB52A0nq359N+O10Ov31BeAfLy8vv61+DcB8T36yA0Af4/Aff/y++oUAAPO9L/5P408qAADUvvjff7kCAAAFXfscv3H4P73+i8NeFQBw6MX/ngIAAAXc+l/1/Tz4ny59IQBQ6+J/TwEAgIQeeei/PvSfrn0lAFDj4t+9ALx8+771TQAHOP3v6+qXAGyw9aH//sB/uuUbXX1BflEBgPAX/3s+BwAAAtrzoX/psH+65xt/RAUAgP2u/SP+R30KAAAsNvOB/9FB//TId7pEBQCA+xx17V+iAADAwbY+9J//+P7l/Ofnh/e1Q/5py3d+TwUAgHkX/3jw3/rw/4wCAAAJLv57fXbAP+3xRl5TAQBg34v/tT2u/0EBAIACF/+9h/vTnm/sJxUAgI5OEy7+Gdf/oAAAQPKL/5GD/WnGGx1UAACqO02++Gdd/4MCAACJL/5HD/WnmW9cBQCgktOBF//M639QAAAg6cX/6IH+UAG4952oAABkdVp08c++/gcFAAASXvxbrv+HC8C970wFACCDU4CL/4jrf1AAAGjvlOzi33r9byoA975TFQCAaKJd/Edd/4MCAEA7p8QX/x7X/+YCcO87VwEAWCnyxX/k9T8oAACUV+Xi3+v636UA3PsiVAAAjpLl4j/6+h8UAADKqXjx73n971YABhUAgNUyXvwrrv9BAQAgveoX/97X/+4DYLyoW/8ljArw8i3PP3AAaj30oz34j7z+BwUAgFSqPfhXXP+7fg7ATz4XAICIH9+P8DH+KNf/oAAAEFrni3/W9T+lAAwqAABbVb74V1//gwIAQCgu/vnX/7QCMKgAANyjy8Uf4fofFAAA0l/8Q6YH/+rrf2oBGFQAAGZe/Bmv/gjX/6AAAHAoF//66396ARhUAACG7hd/pOt/UAAAmMrFH+/6P6QADCoAQD8u/rjX/6AAALArF3/86/+wAjCoAAC1ufjzXP+DAgDAJi7+fNf/oQVgUAEA6nDx573+BwUAgLu4+PNf/4cXgEEFAMjJxV/n+h8UAACucvHXu/6XFIBBBQCIz8Vf9/ofFAAA3nDx17/+lxWAQQUAiMXF3+f6HxQAgOZc/P2u/6UFYFABANZx8fe9/gcFAKAZF38cq67/EANg/M3f+oNxVICXb37AAax66A8e/Pmv/xADAIB5PPgJ+TkAP/lcAICYH98ffIx/zvW/Mv8PCgBAIS5+UhWAQQUAeJyLP4Zzkut/UAAAEnPxk74ADCoAwG1c/PGcE13/gwIAkIiLn5IFYFABAH7l4o/tnOz6HxQAgMBc/LQpAIMKAHTn4s/jnPD6HxQAgEBc/LQuAIMKAHTi4s/pnPT6HxQAgIVc/KwStgAMKgBQlYs/v8zX/6AAABzIxU8UoQvAoAIAFbj4azknv/4HBQBgIhc/UYUvAIMKAGTj4q/rXOD6HxQAgB25+MkiRQEYVAAgMhd/D+ci1/+gAABs4OInqzQFYFABgChc/P2cC13/gwIAcAcXP1WkKgCDCgCs4OLv7Vzs+h8UAIADrv3BQ59I0hWAQQUAslz7g4s/t3PB639QAAD+4eKnk5QFYFABgL24+Ol2/Q8KANCWi5/O0haAQQUAHuHip/v1PygAQBsufihSAAYVAPiMi597nYtf/4MCAJTl4ofCBWBQAYDXXPxscW5w/Q8KAFCGix+aFYBBBYC+XPzs5dzk+h8UACAtFz88rkwBGFQA6MHFzwznRtf/oAAAabj4YT+lCsCgAkA9e1/8g4c/na//QQEAwtr7oT948EPRAjCoAJDbrIvfw59Lzg2v/0EBAMJw8cNxShaAQQWAPFz8rHJuev0PCgCwjIsf1ilbAAYVAGJy8RNB5+t/UACAw7j4IY7SBWBQAWA9Fz/RnJtf/4MCAEzj4oe4yheAQQWAY7n4icz1/zcFAAh77Q8e+jBHiwIwqACQ59ofXPzM4Pr/jwIAPMTFD7m1KQCDCgDbufjJyvX/lgIA3MTFD7W0KgCDCgD3cfFTgev/VwoAcJGLH2prs3S2/OL28s0vWOS3umh58LOK6/8yBQCYyoMfYmr3OQA/+VwAmMvH+InA9f8xBQDYlYc+5NC2AAwqAOzHxU80rv/rFABgEw99yKl1ARhUAHiMi5/IXP+fUwCAu3joQw3tC8CgAsDnXPxUu/67UwCAqzz0qeqlcf4fFIB/qADwloufjFz/t1MAgDc89Onw8H9pfv0PCsArKgAAXRgAAKTn+r+fAfCOCgBABwYAAKm5/h9jAFygAgBQnQEAQFqu/8cZAB9QAQCozAAAICXX/zYGwBUqAABVGQAApOP6384A+IQKAEBFBgAAqbj+92EA3EAFAKAaAwCANFz/+zEAbqQCAFCJAQBACq7/fRkAd1ABAKjCAAAgPNf//gyAO6kAAFRgAAAQmut/DgPgASoAANkZAACE5fqfxwB4kAoAQGYGAAAhuf7nMgA2UAEAyMoAACAc1/98BsBGKgAAGRkAAITi+j+GAbADFQCAbAwAAMJw/R/HANiJCgBAJgYAACG4/o9lAOxIBQAgCwMAgOVc/8czAHamAgCQgQEAwFKu/zUMgAlUAACiMwAAWMb1v44BMIkKAEBkBgAAS7j+1zIAJlIBAIjKAADgcK7/9QyAyVQAACIyAAA4lOs/BgPgACoAANEYAAAcxvUfhwFwEBUAgEgMAAAO4fqPxQA4kAoAQBQGAADTuf7jMQAOpgIAEIEBAMBUrv+YDIAFVAAAVjMAAJjG9R+XAbCICgDASgYAAFO4/mMzABZSAQBYxQAAYHeu//gMgMVUAABWMAAA2JXrPwcDIAAVAICjGQAALLn+WcsACEIFALqR/9cyAADYhes/FwMgEBUA6ML1v54BAMBmrv98DIBgVACgOtd/DAYAAJu4/nMyAAJSAYCqXP9xGAAAPMz1n5cBEJQKAFTj+o/FAADgIa7/3AyAwFQAoArXfzwGAAB3c/3nZwAEpwIA2bn+YzIAALiL678GAyABFQDIyvUflwEAwM1c/3UYAEmoAEA2rv/YDAAAbuL6r8UASEQFALJw/cdnAADwKdd/PQZAMioAEJ3rPwcDAICrXP81GQAJqQBAVK7/PAwAAD7k+q/LAEhKBQCicf3nYgAAcJHrvzYDIDEVAIjC9Z+PAQDAL1z/9RkAyakAwGqu/5wMAADecP33YAAUoAIAq7j+8zIAAPiX678PA6AIFQA4mus/NwMAgB9c/70YAIWoAMBRXP/5GQAAuP4bMgCKUQGA2Vz/NRgAAM25/nsyAApSAYBZXP91GAAAjbn++zIAilIBgL25/msxAACacv33ZgAUpgIAe3H912MAADTk+scAKE4FALZy/ddkAAA04/pnMAAaUAGAR7n+6zIAABpx/fOTAdCECgDcy/VfmwEA0ITrn9cMgEZUAOBWrv/6DACABlz/vGcANKMCAJ9x/fdgAAAU5/rnkt9Op9NfF78GgHZc/30oAADQkAEAwA+u/14MAABoyAAAwPXfkAEAAA0ZAADNuf57MgAAoCEDAAAaMgAAmvMbwvX0+63f8Pv373NfCTDV16+3/Xawz3/4uV6F3wKYaxQAAFSAhgwAgKLUHK4xAAD4QQXoxQAAKEwF4CMGAAD/UgH6MAAAilMBuMQAAOANFaAHAwCgARWA9wwAAH6hAtRnAAA0oQLwmgEAwEUqQG0GAEAjKgA/GQAAfEgFqMsAAGhGBWAwAAC4SgWoyQAAaEgFwAAA4FMqQD0GAEBTKkBvBgAAN1EBajEAABpTAfoyAAC4mQpQhwEA0JwK0JMBAMBdVIAaDAAAVICGDAAA7qYC5GcAAPCDCtCLAQDAQ1SA3AwAAP6lAvRhAADwMBUgLwMAgDdUgB4MAAA2UQFyMgAA+IUKUJ8BAMBmKkA+BgAAF6kAtRkAAOxCBcjFAADgQypAXQYAALtRAfIwAAC4SgWoyQAAYFcqQA4GAACfUgHqMQAA2J0KEJ8BAMBNVIBaDAAAplABYjMAALiZClCHAQDANCpAXAYAAHdRAWowAACYSgWIyQAA4G4qQH4GAADTqQDxGAAAPEQFyM0AAOAQKkAsBgAAD1MB8jIAADiMChCHAQDAJipATgYAAIdSAWIwAADYTAXIxwAA4HAqwHoGAAC7UAFyMQAAWEIFWMsAAGA3KkAeBgAAy6gA6xgAAOxKBcjBAABgKRVgDQMAgN2pAPEZAAAspwIczwAAYAoVIDYDAIAQVIBjGQAATKMCxGUAABCGCnAcAwCAqVSAmAwAAEJRAY5hAAAwnQoQjwEAQDgqwHwGAACHUAFiMQAACEkFmMsAAOAwKkAcBgAAYakA8xgAABxKBYjBAAAgNBVgDgMAgMOpAOsZAACEpwLszwAAYAkVYC0DAIAUVIB9GQAALKMCrGMAAJCGCrAfAwCApVSANQwAAFJRAfZhAACwnApwPAMAgHRUgO0MAABCUAGOZQAAkJIKsI0BAEAYKsBxDAAA0lIBHmcAABCKCnAMAwCA1FSAxxgAAISjAsxnAACQngpwPwMAgJBUgLkMAABKUAHuYwAAEJYKMI8BAEAZKsDtDAAAQlMB5jAAAChFBbiNAQBAeCrA/gwAAMpRAT5nAACQggqwLwMAgJJUgOsMAADSUAH2YwAAUJYK8DEDAIBUVIB9GAAAlKYCXGYAAJCOCrCdAQBAeSrArwwAAFJSAbYxAABoQQV4ywAAIC0V4HEGAABtqAD/MQAASE0FeIwBAEArKsDfDAAA0lMB7mcAANDOSQUwAACoQQW4jwEAQEun5hXAAACgDBXgdgYAAG2dGlcAAwCAUlSA2xgAALR2aloBDAAAylEBPmcAANDeqWEFMAAAKEkFuM4AAIAv/SqAAQBAWSrAxwwAAGhYAQwAAEpTAS4zAACgYQUwAAAoTwX4lQEAAA0rgAEAQAsqwFsGAAA0rAAGAABtqAD/MQAAoGEFMAAAaEUF+JsBAAANK4ABAEA7zyqAAQAAHSuAAQBAS8/NK4ABAAANK4ABAEBbz40rgAEAAA0rgAEAQGvPTSuAAQAADSuAAQBAe88NK4ABAAANK4ABAABf+lUAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlYAAwAAGlaA32/9zl+/ft39BQHxnP/0cx06UAAAoGEFMAAAoCEDAAAaVgADAAAaMgAAoGEFMAAAoCEDAAAaVgADAAC+9PN/Q+c52ew4Zd4AAAAASUVORK5CYII="
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'CyCyCyCy'}.\nthe 2th action is Stack the original shape on top of the {'layer1': 'SgSgSgSg'}.\nthe 3th action is Colorize the top layer of the original shape with the color yellow.\nthe 4th action is Stack the original shape on top of the {'layer1': 'ScScScSc'}.\nthe 5th action is Stack the original shape on top of the {'layer1': 'CbCbCbCb'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'CbCbCbCb'}.\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is Cut the right side of the shape\nthe 9th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_79
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is Stack the original shape on top of the {'layer1': 'RgRgRgRg'}.\nthe 3th action is Stack the original shape on top of the {'layer1': 'RuRuRuRu'}.\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is Stack the original shape on top of the {'layer1': 'SySySySy'}.\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is Stack the original shape on top of the {'layer1': 'WyWyWyWy'}.\nthe 9th action is Stack the original shape on top of the {'layer1': 'RyRyRyRy'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:9)_25
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is Stack the original shape on top of the {'layer1': 'CcCcCcCc'}.\nthe 3th action is Stack the original shape on top of the {'layer1': 'SwSwSwSw'}.\nthe 4th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is Cut the right side of the shape\nthe 9th action is Stack the original shape on top of the {'layer1': 'CbCbCbCb'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_293
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color white.\nthe 2th action is Stack the original shape on top of the {'layer1': 'CbCbCbCb'}.\nthe 3th action is Stack the original shape on top of the {'layer1': 'WcWcWcWc'}.\nthe 4th action is Colorize the top layer of the original shape with the color green.\nthe 5th action is Stack the original shape on top of the {'layer1': 'RpRpRpRp'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'WyWyWyWy'}.\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is Cut the right side of the shape\nthe 9th action is Colorize the top layer of the original shape with the color cyan.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:9)_144
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color white.\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is Colorize the top layer of the original shape with the color white.\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is Stack the original shape on top of the {'layer1': 'CwCwCwCw'}.\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is rotate the shape clockwise 90 degrees\nthe 9th action is Stack the original shape on top of the {'layer1': 'CcCcCcCc'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_30
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color red.\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is Colorize the top layer of the original shape with the color purple.\nthe 4th action is Stack the original shape on top of the {'layer1': 'CcCcCcCc'}.\nthe 5th action is Colorize the top layer of the original shape with the color blue.\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is Colorize the top layer of the original shape with the color white.\nthe 8th action is Colorize the top layer of the original shape with the color blue.\nthe 9th action is Stack the original shape on top of the {'layer1': 'CpCpCpCp'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_319
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'SySySySy'}.\nthe 2th action is Cut the right side of the shape\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is Stack the original shape on top of the {'layer1': 'WgWgWgWg'}.\nthe 5th action is Cut the right side of the shape\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is Stack the original shape on top of the {'layer1': 'WyWyWyWy'}.\nthe 9th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_174
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAgAAAAIACAYAAAD0eNT6AAALtUlEQVR4nO3dQYokxwGGUY3QBXQO30bQBu98NO8MGvBtfA4fYUyAEgkzY1XVZFZGxPfeuhlqE8PHH1Hdnz4+Pr78AACk/Hj3BwAA3k8AAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIOinR3/wn//497WfBLjU3/7+l4d+zlmHxnm3AABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACDo08fHx5e7PwQA8F4WAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAI+unRH/z5l1+v/STA5f7zr78+9HOfP3/+dPmHAW5lAQCAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEE/PvorPx/9FaIAwPwsAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAEA1APw9AABosQAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAAFAOAL8LAAA6LAAAECQAACBIAABAkAAAgCABAABBLwWAbwIAwEYB8OhXAQGAtbkCAIAgAQAAQQIAAIJeDgAPAQFgowDwEBAA9ucKAACCBAAABAkAAAj6rgDwEBAANgoADwEBYG+uAAAgSAAAQJAAAICg7w4ADwEBYKMA8BAQAPblCgAAggQAAASdEgDeAQDARgHgHQAA7MkVAAAECQAACDotALwDAICNAsA7AADYjysAAAg6NQBcAwDAGiwAABD0UAB4BwAAe7EAAEDQ6QHgHQAAbBQArgEAYB+uAAAg6JIAcA0AABsFgGsAANiDKwAACLosAFwDAMC8LAAAEPR0AHgHAADru3QBcA0AAHNyBQAAQS8FgGsAAFjb5QuAawAA2CgArAAAsC5vAAAg6C0B4BoAADYKANcAALCmt10BWAEAYB7eAABA0HcHgGsAAFjPWxcA1wAAMAdXAAAQdEoAPHMNYAUAgPtZAAAg6LQA8BgQANZxywLgGgAANgoAKwAArOG2NwBWAAC4j0eAABB0egD4SiAAzM8CAABBlwSAFQAA5mYBAICgywLAVwIBYF5TLACuAQAgGAAAwEYB4DEgAMzJAgAAQZcHgBUAAOZjAQCAoLcEgBUAAOZiAQCAoLcFgBUAAOZhAQCAoLcGgBUAAOZgAQCAoLcHgBUAAO43/QIgAgBgkwDwp4IB4F7TLwCDFQAANgkAKwAA3GeJBWCwAgDAJgFgBQCA6ALga4EAEAyAZ4kAANgkAFwFAEAwAJ5lBQCATQLACgAAwQB4lhUAADYJgGdXABEAABsEwOAqAACCAfAsKwAAbBIArgIAIBgAAEA0AKwAABAMgMGDQAAIBsCzrAAAsEkAuAoAgGAADCIAAIIBAABEA8AKAADBABhEAAAEAwAAiAaAFQAAggEwiAAACAbAK0QAAGwQAH5NMAAEA2BwFQAAwQAYRAAABAPgFSIAgLotAsB7AAAIBsDgKgAAggEwiAAACAbAK0QAAEXbBYD3AAAQDIDBVQAABANgEAEAEAyAV4gAACq2DoBX3gOIAAAKtg6AQQQAQDAABhEAAMEAGHw9EACCAfAKKwAAu0oFgKsAAAgGwCACACAYAIMIAKAuGQCDCACgLBsAgwgAoCodAIMIAKAoHwCvEgEArEwAfMcvCRIBAKxKAPxGBABQIgD+QAQAUCEA/ocIAKBAAHyFCABgdwLgG0QAADsTAP+HCABgVwLgT4gAAHYkAB4gAgDYjQB4kAgAYCcC4AkiAIBdCIAniQAAdiAAXiACAFidAHiRCABgZQLgpggQAgDcSQDcFAGDCADgLgLgBCIAgNUIgJOIAABWIgBOJAIAWIUAOJkIAGAFAuCiCPANAQBmJgAuZA0AYFYC4GIiAIAZCYAFIkAIAHA2AbBABAwiAIAzCYA3EgEAzEIALPQNgcGVAABnEAA3sQYAcCcBcCMRAMBdBMAGESAEAHiWANjgXcAgAgB4hgCYiDUAgHcRAJtFwCACAPgzAmBCrgQAuJoAmJgrAQCuIgAiVwJCAIA/EgCRK4FBBABwEAALsQYAcBYBEIyAQQQAtAmA+JWAEABoEgALO3MNEAIALQJgcWetAYMIAOgQAJuwBgDwDAGwkbPXACEAsC8BsKGzImAQAgB7EgCbOnMNGEQAwF4EwOasAQB8jQAIuGINEAIAaxMAIUIAgIMACDozAgYhALAeARB19howCAGAdQiAOCEA0HTqf/ys7+Pj48sV/+7Pv/x6xT/Lkx4Ns7OjEJiPBYC3/MdvFQCYiwDgLdcCByEAMAcBwDcJAYB9uefj9vcBB+8ErucNAHCwADDFIjBYBQDeR+Uz7SIwWAXOZQEADhYApl0EBqsAwDVUPkstAoNV4HUWAODgkLNsCAxi4DkCADg45FxKDMxFAAAHh5ztQmAQA18nAICDQ87WITCIgd8JAODgkJOKgXoQCADg4JCTDYFiDAgA4OCQM407Q6ASBAIAODjkTGmGGNgxCAQAcHDImd4sMbBDFAgA4OCQs5TZYmC1KBAAwMEhZ0mzhsDsUSAAgINDzvJWiIFZwkAAAAeHnO2sFgTvDAQBABwccra2egycHQwCADg45GQUYuAsAgD255CTJQi+TQDA/hxy+I0g+J0AgP055PAN5SAQALA/hxyeUIkCAQD7c8jhO+0YBQIA9ueQwwVWjwIBAPtzyOHNVogDAQD7c8hhMjMEggCAH7b3X2Fd8m8W5tTAAAAAAElFTkSuQmCC"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'RuRuRuRu'}.\nthe 2th action is Stack the original shape on top of the {'layer1': 'SwSwSwSw'}.\nthe 3th action is Colorize the top layer of the original shape with the color purple.\nthe 4th action is Stack the original shape on top of the {'layer1': 'RuRuRuRu'}.\nthe 5th action is Cut the right side of the shape\nthe 6th action is Colorize the top layer of the original shape with the color yellow.\nthe 7th action is Colorize the top layer of the original shape with the color blue.\nthe 8th action is Stack the original shape on top of the {'layer1': 'RyRyRyRy'}.\nthe 9th action is Stack the original shape on top of the {'layer1': 'CpCpCpCp'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:9)_95
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is Stack the original shape on top of the {'layer1': 'RrRrRrRr'}.\nthe 3th action is Colorize the top layer of the original shape with the color red.\nthe 4th action is Cut the right side of the shape\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is Stack the original shape on top of the {'layer1': 'SuSuSuSu'}.\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is Stack the original shape on top of the {'layer1': 'WbWbWbWb'}.\nthe 9th action is Colorize the top layer of the original shape with the color red.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:9)_314
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is Colorize the top layer of the original shape with the color blue.\nthe 3th action is Stack the original shape on top of the {'layer1': 'SySySySy'}.\nthe 4th action is Colorize the top layer of the original shape with the color yellow.\nthe 5th action is Stack the original shape on top of the {'layer1': 'WpWpWpWp'}.\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is Cut the right side of the shape\nthe 9th action is Stack the original shape on top of the {'layer1': 'WpWpWpWp'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_392
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is Stack the original shape on top of the {'layer1': 'SbSbSbSb'}.\nthe 3th action is Colorize the top layer of the original shape with the color white.\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is Stack the original shape on top of the {'layer1': 'SuSuSuSu'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'RgRgRgRg'}.\nthe 7th action is Colorize the top layer of the original shape with the color red.\nthe 8th action is Stack the original shape on top of the {'layer1': 'SrSrSrSr'}.\nthe 9th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:9)_200
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'RuRuRuRu'}.\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is Stack the original shape on top of the {'layer1': 'CuCuCuCu'}.\nthe 4th action is Colorize the top layer of the original shape with the color blue.\nthe 5th action is Stack the original shape on top of the {'layer1': 'WrWrWrWr'}.\nthe 6th action is Cut the right side of the shape\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is rotate the shape counterclockwise 90 degrees\nthe 9th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABAAAAATICAIAAAANxCANAABSkUlEQVR4nO3deZidZXk/8EkIhBAgBIiE7SeKKMQqKCoaaNELUdkVnYG61FrcL0Rray2tFvWyarW2SrVqcQEXlhkIZUdFcGMRF1YXZBEEZAkwbAESIPO7dHrFOGcyOXPOuzzPc38+f9l3Jue82jP3e3+f+3nfM2NsbGwAAACIYWbbJwAAADRHAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhkVtsnAI26//77t9hii0ceeWTSn77xjW885phjGj8pAPpy4oknTuv3Z/7BrFmzZs+evcEGG2yyySYLFizYYost1llnndrOERIyY2xsrO1zgOZ8+ctfPuyww9b000033fT2229fd911mz0pAPoyY8aM/l9kvfXW+7M/+7NnP/vZz3nOcw444ICtttqqilODFAkAxLLXXnudf/75U/zCmWeeud9++zV4RgAkEQAmvODuu+/+13/9169//etnzbJdgtK4B4BAbr311u9+97vVzpEBKM/Y2NgPf/jDN77xjTvttNPw8HDbpwMVEwAI5IQTTli5cuXUv3Paaaet6Q4BAKK57rrrDjnkkDe/+c0rVqxo+1ygMgIAgXz961+fcGT+/PkTjjzwwANnnXVWgycFQOqOOeaYl73sZY8++mjbJwLVEACI4uc///kVV1wx4eAnPvGJzs2dJ510UoPnBUAtxqb0+OOPr1ix4r777rvpppu+//3v/9d//derXvWqDTbYYE2vdsEFFxxxxBHN/jeAurgJmCiOPPLIj33sY6sf2Xjjje+888599913wm3Bc+bMufPOOzfccMPGzxGAym4C7qHDefDBBz/1qU99/OMff+CBByb9hW9+85sveclLejpHSIgJACGMjY2dcMIJEw6+/OUvnz179sEHHzzh+MMPP3z66ac3eHYAJGHDDTd83/ved8kll2y33XaT/sIHP/jBxk8KqicAEMIPfvCDm266acLBQw45ZDwGdC4deRYQQFiLFi0666yzJt0OdNFFF/3kJz9p46SgSgIAIXzjG9+YcGTTTTfde++9BwYGtt566+c973kTfvrNb37z3nvvbfAEAUjIokWL3vve9076o/POO6/x04GKCQCUb8WKFSMjIxMOHnzwwau+8fcVr3hF5z9ZsmRJUycIQHLe/va3r7POOp3HL7jggjZOB6okAFC+s88+e3R0dNL9P+M6bwOwCwgguM0333yXXXbpPN65oRSyIwAQ8fH/CxYseNGLXrTq/9xhhx2e/vSnT/id888/f+nSpY2cIAApesYzntF58K677mrjXKBKAgCFu++++zq/2OtVr3rVhMFu5xDg8ccfP/nkk+s/QQAStdlmm3UevO+++9o4F6iSAEDhTj755EceeWTCwUMPPXTCEbuAAOjmmwQ23njjNs4FqiQAEG7/z1ZbbbXHHntMOLjLLrs86UlPmnDwhz/84a233lrzCQKQqEkfB7dgwYI2zgWqJABQsltuueX73//+hIODg4MzZ07yye98FtDKlSuHh4frPEEA0nXNNdd0Htx1113bOBeokgBAyY4//viVK1eudf/PmgKAXUAAYS1fvvyyyy7rPP4Xf/EXbZwOVGnGpPvboAw777zzlVdeufqRJz7xib/5zW86v/p3fL1/q622uuOOOyYcv+GGGzp3BwGQjkmrep8dzje+8Y3Xvva1Ew5usMEGt9566yabbNLPK0PrTAAo1tVXXz2h+x8YGBgaGpr0OvH7P4aZMw866KDO4yeddFI9JwhAolasWPGRj3yk8/ib3/xm3T8FEAAoVuftv1Ps/xnnWUAADAwMvPvd7/7FL34x4eC22277oQ99qKUzgirZAkSZxsbGtttuu9/+9rerH3zKU55y7bXXTvGvHn300Sc84Qmdj3345S9/ueOOO9ZzpgAktAVo2bJl73rXu774xS9OOL7xxht/97vffdazntXrOUJCTAAo0/e///0J3f/AwMAhhxwy9b9ad91199tvv87jhgAAxRsdHT366KOf/vSnd3b/W2yxxTnnnKP7pxgmAJTpTW96U2cFv/LKKyf9XvfVLVmy5JWvfOWEgzvuuOMvf/nLqs8RgBonACeccMIU/2RsbGz58uUPPfTQ7bfffsstt1x22WVXXnll54PjBgYG9t5772OPPXarrbaq9JShTQIABVq+fPnChQsn7OTZaaedOjd0dnrooYc233zzhx9+eMLxyy67bJdddqn6TAGowJqe7tCnZz3rWR/84AcPOOCAOl4cWmQLEAU666yzOvfxT3377yobbLDBS1/60s7jdgEBxDF37tzPfe5zP/3pT3X/FEkAoEDf+MY3Og+u9QaAqb8RzMNAAeJYtmzZ2972tq233vrwww+3BZTy2AJEae69996FCxcuX7589YO77LLLpF/oOKnR0dEnPOEJjz322ITjl1xyyW677VbdmQKQ9BagVfbZZ59Pf/rTO+ywQ63vAo0xAaA0J5988oTuf1rL/wMDA/Pnz3/hC1/YedwuIICYzjnnnGc+85n//u//3vaJQDVmVfQ6kPT3f82YMWNa7fuCBQs6Dw4PD3/yk5+cOVNsBsjAWvc4rFy5ctmyZQ888MCtt9568803X3755ZdeeukFF1ywYsWKzl9+5JFH3vOe99x4441HH320CwG5swWIotx8881PfOIT6/tUf/e7391zzz1renEAWv8isLvvvvvYY4/98Ic/3PkwiXFHHXXUBz7wgR5eGdIhwlKU448/vtZMaxcQQNk222yzv/u7v/v1r3/9ohe9aNJf+PCHP3zxxRc3fl5QJRMAivLMZz7zqquuqu/1FyxY8Lvf/W7WLHvnAMqcAKyyfPny/fbb7zvf+U7nj/bee+9vfetb/bw4tMsEgHJceeWVtXb/AwMDS5cuPf/882t9CwBSMHv27K9+9aubbrpp54++/e1vd/PNkpAsAYDCb/+tnF1AAEFstdVWhx9++KQ/Ovvssxs/HaiMAEAhxsbGTjjhhAkH586d+9BDD4316vjjj+98o1NPPXXSB0QAUJ43v/nNkx6/6KKLGj8XqIwAQCG++93v3nLLLRMO7r///nPmzOn5NQ844IDOf37vvfeee+65Pb8mABnZeuutt99++87jtgCRNQGAQnzjG9/oPDg4ONjPa2644Yb77LNP53G7gADi2HXXXTsP3nPPPW2cC1RDAKAEy5cvP+WUUyYcnDt37qTt+7QMDQ11Hjz99NMfeuihPl8ZgCxsttlmnQfX9C0BkAUBgBKceeaZnbV4v/3222CDDfp85f3337/zRZYtW3bmmWf2+coAZGHjjTfuPOjLgMmajy/FPv+nz/0/4+bOnbvvvvt2Hj/ppJP6f3EA0nf//fd3mQogFwIA2RsdHe18HNsGG2wwaePeg0MOOaTz4Nlnn/3AAw9U8voApGzp0qWdB7fZZps2zgWqIQCQvZGRkc7nclay/2fVS82dO3fCwUceeeR///d/K3l9AFJ26aWXdh7caaed2jgXqIYAQPbqeP7P6ubMmbP//vt3HvcsIIDi/frXv/7tb3/beXy33XZr43SgGgIAefvtb3/7gx/8oL79P1M8C+jb3/62x8ABlO0///M/Jz2+3377NX4uUBkBgLwdf/zxY2NjEw7uu+++nZt2+rHvvvtuuOGGEw4++uijnc8eBaAYl1122Ve+8pXO43vsscek3w4GuRAAyFvd+3/Grb/++gcccEDncbuAAEp16623vupVr1q+fHnnj9773ve2cUZQGQGAjF1++eVXX331hINz5sypYzI76S6g733ve3fccUfl7wVAuy655JLddtvthhtu6PzRy172sklvDIOMCACUtvy/zz77VLv/Z9XLdj71+fHHHx8ZGan8vQBoy6WXXvpXf/VXixcvvvXWWzt/unDhwkk3BUFeZrV9AtCjlStXnnDCCQ3s/xk3e/bsAw88sPMbx0488cTDDz+8jncEoB/d7NJ87LHHli9ffv/99991112/+tWvfvrTn950001r+uVNN9303HPPXbhwYdVnCk2b0XkDJWTh/PPP32uvvSYcXH/99ZcuXdp5w24lzjjjjAMPPHDCwRkzZtx0003bbrttHe8IQDdmzJhR91ssWrTo9NNPd+8vZbAFiFx1LsaPb9SpqfsfGBh46UtfOm/evAkHx8bGTjrppJreEYAUvPa1r73kkkt0/xRDACBLjzzyyJIlSxrb/zNuvfXWO+iggzqPexYQQKme85znXHjhhV/72tc22mijts8FKiMAkKUzzjjjvvvum3Bw/fXXr/vJDJM+C+inP/3pddddV+v7AtCkDTfc8A1veMOFF1744x//ePHixW2fDlTMTcBkac6cOUcdddSEg//v//2/uldoXvKSl3zgAx/ovHOmM40AkLgZM2bMmjVr9uzZG2644fz587fYYosnPvGJz372sxcvXrzLLrvMmqVHolhuAgYAgEBsAQIAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBAZgwODo6MjLR9GgAAfRkcHKzvxTVLlBYAxv+TTzZAEOOVX9knI7U291XxN0UuZkz4o/LZBSiYgk/ismj0p8vfGqkHgHE+qQCFUepJTZG9fvf8AdJyAFjTH6GPJkABVHgSEbzjn5o/SVIJAON8IgEypbbTLh1/z/yF0kQAWOtfqQ8iQEaUdFqh46+Jv1naCQDjfP4AEqeY0zBNf8P8/VJlAOj+b9gnDyBBajiN0fQnwp8zzQWAcT5zAIlQvWmApj9x/rTpMQD08Oft0wbQIkWbumXU9w/PXzDFT4dGl/b8b9f6z5Piz5y1mjXQH18nCdCKjNoycpTaB2ytDXoKJ5BISFj1/zvtGd1OAPr5m/c5A2iAKk3BTX99jX6fE4D63roZ/vypcgKwOtMAgLKbM4rU4ker9XX9tv5rNh8JjAVYywSgklrg4wWQVH+mLJNC699ix9/iBGCtms8DCkJwVU4AVmcaANA/q/7k/rkKssZf7f9KDeQBA4HgZky3Onxs/vA/jg5N6z18tgDqbtGmLs7qMI31/cl2/ClPAFKYD6gSoUw7AIxfZgYGBqYbA3y2AGpq/ddak5XfyBro+1PungsIAA2HAeUidACYegiw6j+LAQDttv7jLP/TcOufS8dcWABoLAyoG2XrJQBMuOqIAQAttv6W/2my9c+xUS41ADSQBFSPiAGgyyHAKmIAQMOt/zjL/9Ta92fdHEcIAA2EAZWkMD0GgDVdhMQAgCZbf8v/1Nf6F9MThwoAtSYB9SRKAJjuEGAVMQCg7tZ/nOX/4Cpv/ctrhWMGgPqSgMISOgCs9ZokBgDU2vpb/o9M3z9dYQPAKpIA0wgAPQ8BVhEDACpv/cdZ/g+o2tY/QuM7TgCoKQkoNeECQPeXKDEACKum1t/yf0AVtv6h+t1xAkCtSUDBKTAA9D8EWEUMAOKor/UfZ/k/Dq1//wSANREDAuo3APRwxRIDgOLV3fpb/o+jqtY/coM7TgBoLAmoP+UEgAqHAKuIAUB5Gmj9x1n+L57Wv1oCQJfEgAgqCAD9XMDEAKAYjbX+lv+LV0nrr6OdQABoJQkoR9kHgDqGAKuIAUC+mmz9x1n+L5XWvz4CQG/EgCJVEwAquZ6JAUB2mm/9Lf+XSutfNwGgH2JA6ABQ6xBgFTEASF8rrf84y//l6b/717+ulQCQQgxQo0oLANVe3sQAIFkttv6W/8vTZ+uvbe2eAJBOElCp8gsAzQwBVhEDgHS02/qPs/xfDK1/wwSAyokB+aoyANR0tRMDgNal0Ppb/i+G1r8VAkBNxIAoAaDhIcAqYgAQtvUfZ/k/ePevSe2HAJBsDFC+sg8AdV/8xAAgZutv+b8AWv92CQANEAMKDwBtDQFWEQOAOK3/OMv/+dL6p0AAaIwYEDEANHYtFAOA1ru0RMqdylZk968lrZYAkEsMUNCSDgCtDwFWEQOAglv/cZb/c2ThPykCQPOMAmIFgOYvjWIAUGrrb/k/Uxb+UyMAtMUooLQAkM4QYBUxACip9R9n+T8vWv80CQDtEgNCBIAWr5RiAFBM62/5P0j3r/tsgACQbwxQ6JILAAkOAVYRA4CsW/9xlv9zYeE/cQJAIowCCg8AKVw4xQAg39bf8n9GLPynTwBIilFA9gEg5SFAzxnAhwyCd2bply81KhFa/1wIAAkSA8oMAOlcRMUACCjr1t/yfxZ0/xkRANIkA2QcANIfAqwiBkAEubf+4yz/l/cx02W2SAAoLAYog0kHgASvqT3HAJ82SF8Zrb/l/8RZ+M+RAJA4o4AsA0BGQ4BVxAAoSTGt/zjL/8my8J8pASALRgHlBICUL7FiABSgsNbf8n9JHzZtZToEgIJjgKrYZgDIcQiwihgAOSqv9R9n+T9BFv5zJwDkxSighACQxRVXDICMlNr6W/5Pk+6/AAJAdmSAbAJA1kOAVcQASFnBrf84y/+pse2nDAJApmwHyjsA5HUBFgMgQcW3/pb/U2PhvyQCQL6MAjIIAGUMAVYRAyAFEVr/cZb/02HhvzACQO6MAnINAJlej8UAaFGc1t/yf1J0/+URAAogAyQdAAobAqwiBkCTQrX+4yz/J0L3XyQBoAwyQJYBIPfLsxgADQjY+lv+T4TWv2ACQEnEgEQDQKlDgFXEAKhDzNZ/nOX/1un+yyYAFEYGyCwAFHO1FgOgQpFbf8v/KdD9F08AKI8MkGIAKH4IsIoYAP0I3vqPs/yf0YdQp5gpAaBU04oBKmqbAaC8i7cYAD3Q+o+z/N8u3X8QAkDBZIC0AkADQ4Ce226A/lVSyiz/t0j3H4cAUDYZYFpmDbTkH0eHylvGA5guqxht0fpDScb/SLuMAYN/+POPHANmtn0CANA03T8UaVp/rYM9bUMtQ+0BYIp0Zd0LCM7u/1bo/qFgMkA3TAAACET3D8WTAZIIAIYAAJ0s/zdP9w9ByABTMwEAIATdP4QiA7QfAAwBAFZn+b9h3V/dh+cv0P1DGab15zwYKQOYAABQuGl1/zWfC9A0GaDNAGAIADDO8n+TdP+ADJDKF4E1Y/7BvmuMPzG6ZKrGyweG6X5mSJzuHxg3PH9B918TNlL6QkyjW4AMAQAs/zdG9w+szhxgFfcAAFAg3T/QSQZoJwAYAgCRWf5vhu4fWJNhGcAEAIDC6P6BqQ2HzwAtBABDACAmy/8N0P0D3RiOnQFMAAAohO4f6N5w4AzQTgAwBACisfxfN90/MF3DUTOACQAA2dP9A70ZDpkBWgsAhgBAHJb/a6X7B/oxHC8DmAAAkDHdP9C/4WAZoM0AYAgARGD5vz66f6Aqw5EygAkAAIXT/QPdGA5TK1oOAIYAQNks/9eny0W4OFd0oH/D3VWM3IcAJgAA5Ef3D9RkOEAGaD8AGAIApbL8XxPdP1Cr4dIzQPsBAAC6p/sHGjBcdAZIIgAYAgDlsfxfB90/0JjhcjNAEgEAANZK9w80bLjQDJBKADAEAEpi+b8tun+gWsMlVpVUAgAAlLTABoQymFWNSigAGAIAZbD8Xzmbf4AWDRe3ESihAAAAnXT/QOuGy8oAaQUAQwAgd5b/q6X7BxIxXFAGSCsAAMB06f6BZgyXUm2SCwCGAEC+LP9Xq5uFtGKux0AWhruoOekPAZILAACg+weSNZx/BkgxABgCADmy/F+hxK+dAFnXsRQDAACsleV/oC3DmdefRAOAIQCQF8v/FbL5B0jfcM4bgRINAADEpPsHcjGcbQZINwAYAgC5sPxflTSvlACFVbZ0AwAAdLL8D6RjOM+KlHQAMAQA0mf5vyo2/wA5Gs5wI1DSAQCAIHT/QL6Gc8sAqQcAQwAgZZb/K5HUdRGg+FqXegAAAMv/QOKGs6pRGQQAQwAgR5b/u2TzD1CG4Xw2AmUQAAAole4fKMlwJhkgjwBgIQ3Ii6oFQLLyCAAAlMfyP1Ce4RyGANkEAMtpQC7Uq27o/oFSDSefAbIJAAAAQKwAYFENSJ9K1Q3L/0DZhtMeAuQUAAAogO4fiGA44QyQWQCwtAakTI2qhO4fKMNwqtUsswAAQNZaf/YFQFJaqYr5BQALbECaVKe1svkHiGY4yY1A+QUAAAAgVgCwzAakRl1aK8v/QEzD6Q0BsgwAAJRH9w+Uajix+pZrALDYBqRDRVor9/4CpFMncw0AAOTC5h+A4ZQ2AmUcACy5ASlQi/qn+wciGE6m1s1q+wSiG10y1PYpQGtGlwzNP3i47bOgXjb/AHRvcHCwgXWljCcAZSy86X6IaXTJUBnpt4Aq1Lp0lsQAglS8vAMAkJ1iWn+6YfkfIMHKKQC0zxCAILT+JLsYBhCq7gkAQO20/jGtdRErhasgQPPWWv3qHgIIAEkwBKBUWv+wbP4BSLaKegoQUAt9P1Oz/A9ENjx/wdDo0rbe3QQgFYYAFMOqP5b/AVKupSYAQGX0/XTJ8j/AcHtDABOAhBgCkC+r/qxi+R8g8YpqApAZy2Z9anG/Xan0/UyXOgbQ7hDABCCzIYD+lXRY9aeTR38CpP9IUBMAYNr0/QCQLxOA5BgCkDKr/kzB8j9AFkMAEwCgK/p+ACiDCUCKDAFIilV/umH5HyCXIYAJALBG/ff97X7TIQDQyQQgUYYA5L7qPzx/gRXfOCz/A2Q0BDABAKpf9a/oXACA6pkApMsQgIZZ9ac3lv8B8hoCmAAAVv0BIBATgKQZAlA3q/70yfI/QHZDABMACMqqPwDEZAKQOkMAKmfVn8b4nAAkWDlNACAQq/5Uq/JvpwdgrQYHB0dGRgb6YAKQAUMA+mfVHwAYJwBA4bT+1MTtvwCZ3gosAOTBEIAeaP0BgE4CABRI60/dLP8D5DsEEACyYQhAN7T+AMDUPAUICuEJP6TDZwmgf8PzF9S0vGsCkBNDACZl1Z+GefonQNbV2AQAMmbVnwT5UAEkPgQwAciMIQDjrPrTFsv/ALnXZBMAiLXkb4EWAIIzAciPIUBM/S/5W/Wnf57+CVDA80BNACB1Vv0BgAqZAGTJECAIq/7kxScNIIvqagIAKbLqT4Lc/guQpsHBwZGRke5/3wQgV4YApbLqDwDUygQAUmHVn6z57AHk8oUAJgAZMwQohlV/0mf/D0AxVdoEANpk1Z8y+BACZDQEMAHImyFAvqz6AwCtMAGApln1Jzv2/wCU9CwgE4DsGQKEWvUfX/LX/ZMUH0iAvOqtCQA0oZLdPhWdC0yP5X+AwoYAJgAlMASIsOpf3RkBAKGZAEBdrPoTgU8pQHbPAjIBKIQhQFKs+lMM+38AyqvbJgBQJav+AEDiTADKYQjQLqv+BOQTC5Bj7TUBgH5Z9QcAMmICUBRDgIZZ9adsbgAAKLJ6mwBAL6z6g88wQKbPAjIBKI0hQN2s+gMAWTMBgG5Z9ScU+38ASv1KYBOAAhkCVM6qP0zg8wyQbx02AYCpWPUHAApjAlAmQ4D+WfUnMvt/AAqu5CYAMJFVfwCgYCYAxTIE6IFVf+iGDzlA1tXYBACqoSUCALJgAlAyQ4BmWPWnMG4AACi7npsA0BcRovX/EWQPGuYjB5D7VwKbABTOEAAAgNUJAAAAEIgAUD5DAKB7bgAAKL6qCwAAdMsNAAAFVGYBIARDAAAAxgkAAAAQiAAQhSEAsFZuAACIUNsFAAC64gYAgDLqswAQiCEAAAC+CZgabT88fyAx1w+N5nXCaz1nAIBpMQGIxRAAACA4AQCA33MHMECQCi8AhGMIAPTAHcAAxVRpAQAAAAIRACIyBAAACEsAAACAQASAoAwBgNW5AxggTp0XAABYC3cAA5RUqwWAuAwBAAACEgAAACAQASA0QwAAgGgEAIDo3AEMEKraCwDRGQIAU3MHMEBhFVsAAACAQAQADAEAAAIRAAAAIBABgN8zBAAACEIAAACAQAQA/o8hAMQ09TNAPQIIIC9T1+3xmi8AAABAIAIAf2QIAABQPAEAAAACEQD4E4YAAABlEwAAACAQAYCJDAEAAAomAAAAQCACAJMwBIAgfAkAQMCvAhAAAAAgEAGAyRkCAAAUSQAAAIBABADWyBAAAKA8AgAAAAQiANDXEAAAgLwIAAAAEIgAwFoYAgAAlEQAAACAQAQA1s4QAACgGAIAAAAEIgDQFUMAKM/g4OAUPx2ev6DBcwGgSlPXcAEAAAACEQDoliEAAEABBAAAAAhEAGAaDAEAAHInAAAAQCACANNjCAAAkDUBAAAAAhEAmDZDAACAfAkAAAAQyIyBor/JEqBWIyMjA9lSP4EW+brxug2NLl3Tj2bV/uYAANB1e0rdbAECAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAgk+28CJuVvEt1+eP5AYq4fGs3rhNd6zll/Ey0p//2m/yWdU3+L0MfmDw+k7R9Hh6b46fyDUz//0SVDeZXTmur/1C+bxf8r2/qQ0CLfBAwAUJfRJUORM0DWqwy5m2KVxBYgAIAeJTjrgLUSAAAAamQnDKkRAAAAemcIQHYEAACAehkCkBQBAACgL4YA5EUAAAConSEA6RAAAAD6ZQhARgQAAIAmGAKQCAEAAKAChgDkQgAACGpkZKS3r5AEemYIQDOmruECAABANQwByIIAAADQHEMAWicAAABUxhCA9AkAAACNMgSgXQIAAECVDAFInAAAANA0QwBaJAAAAFTMEICUCQAAQMmuHxq9fmh0ID2GALRFAAAAytRu628IQLIEAACgNMmu+k9gCEArBAAAoBxJtf6GAKRJAACIa2RkZIqfDo0ubfBcoKjWv3uGAFRu6uo9MjIiAAAAeUu59TcEIEECAACQq5Rb/+4ZAtAwAQAAyE9Grb8hAKkRAACAnGTU+nfPEIAmCQAAQB7ybf0NAUiKAAAApC7f1r97hgA0RgAAAEpu/ecfPDz/4OGBthkCkA4BACA0XwVAsopp/btnCEADXwIwMDAwq4L3AQCoTv+7fdLs+7cfnl/8RiayYAIAABS11z/N7r9LhgA0wAQAAGhfJUvj6bf+hgCkQAAAANoUpPXv3uiSoZL+65AgAQAAaEfM1t8QgNYJAABMZWh06fD8BW2fBaWJ2fp3zxCA3nT56DY3AQNEN/WTQCHN23yz7o99JwDtVnsTAACgCVb9p8UQgPoIAABAvbT+ndwJQIsEAACgLlr/fhgCUBMBAIC1cB8wPdD6r5UhAK3cAewmYAB+z33AVMttvlXxxcDUUedNAACAhITq+w0BaIUJAACQBKv+kzIEoHImAABAyyL3/YYANM8EAIAq7y2DabHq3w1DAKqt0gIAAL/nPmAapvVfxRcD03CFFwAAgEZp/XtgCECF3ANAjbLb1JjdCQPkJdm+X/0nFBMAACB0958LQwCqYgIAQFd8HzA90/pDUs9pMAEA4P+4D5jK2e5fLUMAKqntJgAAQPX0/ZAsEwAAoEpW/WtlCED/TAAA6JbbAJiavh+y+KJGEwAA/shtAPTGqn+TDAHos6qbAAAAvdP3Q3ZMAACAXlj1b5EhAP0wAaAvdgtANG4DYFxhrX9h/3WIY2j6NwCYAAAwkWAPUHY9FwAAACAQAQCAJibOACRSjQUAAAAIRAAAYCK3AQAUXMkFAAAACEQAAGDa3AYAkG8dFgAAmIRdQACl1nABAAAAAhEAAOiFXUAAmVZgAQCAydkFBFBk9RYAAAAgEAEAgB7ZBQSQY+0VAAAAIBABAIA1chsAQHl1WwAAoHd2AQFkV3UFAAAACEQAAGAqdgEBFFaxBQAA+mIXEEBe9VYAAGAtDAEASqrVAgAAAAQiAADQL7uAADKqtAIAAGtnFxBAMVVaAACgAoYAALnUWAEAAAACEQAA6IpdQABl1GcBAIBq2AUEkEV1FQAAACAQAQCAyqbMhgAA1VprXe1hf6YAAAAAgQgAAEyDW4EBcq/JAgAAVbILCCDxiioAADA9hgAAWVdjAQCAihkCAKRcSwUAAAAIRAAAYNo8DxQgu6d/riIAAABAIAIAAL0wBADIcflfAAAAgFgEAAB65HmgADnWXgEAgLrYBQSQYOUUAAAAIBABAIDeuRUYIKPbf8cJAAAAEIgAAEBfDAEAMlr+FwAAACAWAQCAfhkCAOSy/C8AAABALAIAABUwBADIYvlfAAAAgFgEAACqYQgAkP7yvwAAAACxCAAAVMYQACDx5f+BgYFZlb8iAExhaHTp8PwFbZ9F6kaXDLV9CrH4H5xWtLUmYgIAQJXqWKwCiGmknooqAADQNBuBAIbaq4QCAAAVMwQASLmWCgAAtMAQAIhsqNUaKAAAUD1DAIBkq6gAAEAtPBIUIJ1Hf65OAACgNTIAEM1QAnVPAACgLjYCASRYOQUAAKIvhgGEqni+CRiAGo2MjAwODrZ9Fin62Pzhtk8hln8cXct3/fqCauIMTk0AAGhZIktiAEFqnQAAQPsLWulcFwHq0E2Va+y+KQEAgNq5GxggnTopAACQBEMAoFRDidU3AQCAJtgIBMQ0lNLmn3ECAAAABCIAANAQQwAgmqH0lv8FAAAa5W5ggNarogAAQFoMAYAyDKVazQQAABplIxAQwVCSm3/GCQAANE0GAMo2lHD3LwAAAEAsAgAALTAEAEo1lPbyvwAAQGtkAKA8Q8l3/wIAAADEIgAA0BpDAKAkQzks/wsAALRMBgDKMJRJ9y8AAJAHGQBI2VBWNUoAAKBliSyJAQSpdQIAAO2zEQjI11A+m3/GCQAAJEEGAHI0lFv3LwAAkBkZAEjHUJ4VSQAAIBWpLZIBFFnZBAAAEmIjEJCLoQw3/4wTAABIiwwApG8o2+5fAAAAgOnJfQ1CAAAgOckumwEUUMcEAABSlPK1E4hsKOfNP+MEAAASlfgVFAhoKP/uXwAAAIAQW/9XEQAASFf6C2lAEEPddf9ZVC0BAICkZXE1Bco2VFD3LwAAkIFcrqlAkYbK6v4FAADykNGVFQhoJKsaJQAAAEDhN/6uTgAAIA95LbABBRgqbvPPOAEAgGxkd5UF8jVUaPcvAACQmRyvtUB2hsrt/gUAAPKT6RUXyMVQ0d2/AABAlvK97gKJGyq9+xcAAAAgUPcvAAAAQLFP/JyUAAAAQHRDXXf/uS//CwAAAEQ3FKn7FwAAAAhtKFj3LwAAABDXULzuXwAAACCooZDdvwAAAEBEQ1G7fwEAAIBwhgJ3/wIAAACxDMXu/gUAAAACGQrf/QsAAABEofsfJwAAAFA+3f8qs/74HwGgFP84OtT2KQAJ0f2vzgQAAICS6f4nEAAAACiW7r+TLUAAAIRu/Qcidf8mAAAAFEj3PwUBAACAouj+pyYAAABQDt3/WgkAAAAUQvffDQEAAIAS6P675ClAAADkTes/LTOm9+sAUJbBwcHuf3l4/oI6z4U2e0T/z82X7n+6bAECILRpdQPT6jOABuj+eyAAABDddDOAGAApmO4fo+5/FQEAAKbdGcgA0K7p/g3q/lcnAADA78kAkAvdf5/cBAwAvd8W7ObRjLgJuABa/0qYAADAnzAKgDTp/qsiAADARDIApEb3XyEBAACqyQBiANShhz8u3f/U3AMAAFNxS0Ax3AOQI61/HUwAAGAqRgHQCgv/9REAAKD6rkIGgH708Bek+++eLUAA0C3bgbJmC1AuLPzXzQQAALplOxDUyrafZggAAFD7diAxAOr4M9H998YWIABoYjuQTSatswUoWVr/hpkAAEAvjAKgfxb+WyEAAECPeutCZADo529B998/W4AAoIXtQPacNM8WoHRo/dtlAgAArY0CTAOIpuePve6/QiYAAFAZo4CUmQC0TuufCBMAAKiMUQBMysJ/UkwAACCVUYB16FqZALSi53Cr9a+PCQAAVK/n3sU0gGL082HW/dfKBAAAamQUkA4TgCZp/VNmAgAANTIKIBoL/+kzAQCApEcBFqerYgJQt34iq9a/SQIAADRHDGiRAFAfrX9ebAECgOb00+vYFESC+vxY6v5bYQIAAJmNAixX98YEoFp9xlGtf4sEAABojRjQJAGgKlr/3AkAAJB3DNC8dkkA6FP/O9C0/olwDwAAtKz/rsjtAdSqkg+Y7j8dJgAAUM4owEr2FEwAelBJsNT6p0YAAIC0iAE1EQCmRetfMAEAAIqNAfra1QkA3ahqL5nWP2UCAACkSwyokAAwNa1/HAIAAESJAcHbXAFgUhXePq71z4UAAAB5EAP6JABMoPUPSwAAgKAxIFrXKwCMq/aJsVr/HAkAABA9BgRpf4MHgMq/KULrny8BAAAyJgl0L2YA0PfTSQAAgOxVHgOKbIhDBYA6vhla618MAQAAClFHDCipM44QAOro+7X+5REAAKA0NSWB3LvkUgNATU2/vr9gAgAAlKm+GJBpu1xYAKiv79f6F08AAICS1RoD8mqdCwgAtTb947T+EQgAABBCA0kg8TY60wDQQNOv749GAACAWJpJAgl21bkEgGY6/nH6/pgEAAAIqskkkEKTnWwAaLLjH6fvD04AAIDQmo8BbfXc6QSA5jv+VbT+CAAAQPtJoJkuvK0A0GK7v4q+n9UJAABAimGg8u687gCQQqO/Ok0/ayIAAADZJIF+Ovh+AkBqzf0U9P2slQAAABSVBGLS99M9AQAAmB5hIBGafnojAAAAvRMGGqbpp38CAABQDWGgJpp+qiUAAAC1kAd6puOnVgIAANAEeWAKOn6aJAAAAC0Ingd0/LRIAAAAUlFkKtDrkxoBAABIXRbBQKNPLmaMjY21fQ4AAEBDZjb1RgAAQPsEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhkVtsnAM1Zvnz5JZdccuGFF/7qV7+67rrrbrnllgcffHDZsmUrV66cM2fO3Llzt9xyy6233nqnnXbaeeedd9999+22267tUwYAqNiMsbGxql8T0rJ8+fIzzjjjuOOOO++88x555JHu/+EOO+zwqle96g1veMMOO+xQ5wkCMG0nnnjitH5/xowZM2fOXGeddWbPnj1nzpyNN954s802W7hw4Zw5c2o7R0iUAEDJHnrooc9+9rOf+MQnli5d2s/rHHjggR/4wAee9axnVXdqAPRlxowZlbzONttss2jRomc/+9l77rnnHnvsseGGG1byspAyAYBinXjiie9617vuuOOOSl5t5syZb3/72z/60Y+6NgCUFABWN3v27Je97GWvfvWrX/GKV6y77rqVvz4kQgCgQHffffdhhx122mmnVf7KT3va00477bSnPe1plb8yAK0HgFW23nrrI4444h3veIcNQhRJAKA0v/jFLw488MDrr79+it956lOfuuuuu+60006bb775Rhtt9PDDD99zzz2jo6NXXXXVxRdfPDo6OsW/nTdv3je/+c3ddtuthnMHIIkAMG7bbbf9+Mc/fuihh9b9RtAwAYCiXHTRRfvss8/9998/6U+32Wabt771ra9+9auf9KQnrekVxsbGrrrqqv/5n/857rjjHnzwwUl/Z968eeeff/6zn/3s6k4cgOQCwLjBwcHPf/7zm266aTNvBw0QACjHT37yk7322mvS7n/jjTd+//vf/853vrP7PZ333XffUUcddfTRR0/6N7LNNttceumlW265Zd9nDUBlAWDqruaxxx57/PHHH3rooQcffHDp0qU33njjz3/+8x//+Mff+9731rRyNO7JT37yWWedteOOO1Zx4tA+AYBC3HDDDc997nPvueeezh8997nPHR4e7u2h/uedd95rX/vaSe8k3nvvvb/1rW/1dLIAtBAA1mTFihXf+c53vvCFL5xxxhkrV66c9Hfmz59/zjnn2P9JGQQASvDQQw8tXrz4iiuu6PzRQQcdNDw8vN566/X84ldfffWee+45abQ45phj3vjGN/b8ygCkEABWueqqq/7+7/9+TYs7m2yyyfnnn++R0BRAAKAEhx122Je//OXO4wceeOApp5wya1a/33j94x//+M///M+XL18+4fjChQuvu+66uXPn9vn6AKQQAMZ94QtfOOKII1asWNH5oy233PKnP/2p/Z/kbmbbJwD9Ou+88ybt/nfeeefjjz++/+5/fBPR+9///s7jt99+++c///n+Xx+AdLzlLW/5zne+M2/evM4f3XbbbUNDQ48//ngb5wWVMQEgb8uXL99pp51+85vfTDi+wQYbXH755TvssENVb/Too4/uuuuuV1111YTjT37yk6+99tqZM2VpgEImAOMuvvjiF7/4xQ899FDnjz75yU+++93vruqNoHm6FvL2+c9/vrP7HxgY+MhHPlJh9z8wMLDuuuseddRRncdvuOGGiy66qMI3AiAFL3jBC770pS9N+qOjjjrqlltuafyMoDICABl7+OGHP/axj3Ue33HHHQ8//PDK3+7lL3/5Ntts03n81FNPrfy9AGjdoYce+pd/+Zedxx988MFJrz6QCwGAjH3961+//fbbO4//67/+6zrrrFP5262zzjpvectbOo9fcMEFlb8XACn4t3/7tzlz5nQe/9KXvjTpBQiyIACQsWOOOabz4Pbbb//yl7+8pnfcf//9Ow9eeeWVy5Ytq+kdAWjRtttu+w//8A+dxx955JFjjz22jTOCCggA5Orqq6/+8Y9/3Hn87W9/e3235O68884LFiyYcPDxxx+/5ppranpHANr1t3/7t7Nnz+48/tWvfrWN04EKCADk6rTTTus8OGPGjEMPPbS+N50xY8Zee+3Vefzaa6+t700BaNG8efMmHf/+8g/aOCPoVwWPSIdWnH322Z0HFy9evNVWW9X6voceemjnY+Y22mijWt8UgBa95jWvOeWUUzqPn3feeTvttFMbZwR98T0AZOnBBx/cZJNNOr+K5f3vf/+HPvShlk4KgHK+B2B1K1asmD9/fud3ArziFa9YsmRJHe8ItbIFiCxddtllk34R45577tnG6QBQsvXWW+8Zz3hG5/HLL7+8jdOBfgkAZOlnP/vZpMd32WWXxs8FgPJNen258cYbH3jggTZOB/oiAJClX/ziF50HFy5cuNlmm7VxOgBEDABjY2PXX399G6cDfREAyNLNN9/cefDJT35yG+cCQPkWLVo06fHf/e53jZ8L9EsAoJwAsOWWW7ZxLgCUb5NNNpn0+G233db4uUC/BACydNddd3Ue7PyKLgCoxMYbbzzp8fvvv7/xc4F+CQBkqfNZbAMDA3PmzGnjXAAo37x58yY9/vDDDzd+LtAvAYAsPfLII50H119//TbOBYDyrWkCsHz58sbPBfolAJClxx57rPOgb7UDoCaTfvnMwMDAuuuu2/i5QL8EALI0e/bsLscCANC/Na30Gz6TIwGALE263X/SGwMAoH9r+sKvDTbYoPFzgX4JAGRpo4026jy4dOnSNs4FgPLdcccdkx5fuHBh4+cC/RIAyNJWW23VefD2229v41wAKN+anve/9dZbN34u0C8BgCxNWnBvuOGGNs4FgPL9+te/nvT4E5/4xMbPBfolAJClJz3pSZ0H77jjjnvuuaeN0wGgcL/61a86Dy5YsMAWIHIkAJClZz7zmZMev+KKKxo/FwDKd8kll3Qe3Hnnnds4F+iXAECW1lRzf/CDHzR+LgAU7r777rv66qs7jy9evLiN04F+zer7FaAFixYtmjdv3n333Tfh+AUXXPAv//Ivtb713/zN30x43uh666331a9+tdY3BaBF55xzzqRfBLb33nu3cTrQrxm+PJVMHXzwwaeeeuqEg+uss87tt9+++eab1/Sm119//VOe8pQJB7fbbrvf/OY3Nb0jAJOaMWNG58GauprBwcGTTz55wsFNNtnkzjvv9E3A5MgWIHL1spe9rPPg448/fsopp9T3pt/+9rc7D3ZGAgCKceedd5522mmdxw855BDdP5kSAMjVwQcfPGnl/dznPlffm5533nmdB5/xjGfU944AtOszn/nMo48+2nn89a9/fRunAxUQAMjV5ptvvs8++3Qev+KKKy644II63vHhhx/+zne+03l89913r+PtAGjd3Xff/elPf7rz+G677faCF7ygjTOCCggAZOwtb3nLpMf/+Z//uY63O/744++9994JB9ddd90XvehFdbwdAK17z3vec//993ce/6d/+qc2TgeqIQCQsX333XeXXXbpPH7xxRefdNJJlb/dZz/72c6De+2116abblr5ewHQurPOOusrX/lK5/Hdd9/9gAMOaOOMoBoCAHl73/veN+nxd7zjHXfddVeFb3TyySdfdtllncff9KY3VfguACTiuuuue93rXtd5fJ111vnsZz876TOIIBcCAHl75StfOekOnKVLl77uda9buXJlJe9y7733HnHEEZ3Ht99++4MOOqiStwAgHbfccsvee+89Ojra+aMjjzzSFwCTOwGA7H3mM5+Z9HFA55577nve857+X39sbOxtb3vbbbfd1vmjj370o+uss07/bwFAOq666qrFixffeOONnT/6i7/4iw984ANtnBRUSQAge4sWLfroRz866Y/+4z/+48gjj+zz9Q8//PATTzyx8/iLX/ziwcHBPl8cgHSMjY19/vOff/7zn3/zzTd3/nT77bcfHh627kMBfBMwJRgbGzvwwAPPPPPMSX966KGHfvGLX5w7d+50X3bZsmXvfOc7v/SlL3X+aP78+VdeeeU222zT0/kCkNw3AZ9//vlHHnnkpZdeOulPt9hiiwsvvHD77bfv+fUhHQIAhbj//vtf+MIXTnqf7viyzac+9an999+/+xf8/ve/f9hhh1133XWdP5o1a9a5556711579XG+ACQRAK655prTTz/9a1/72lVXXbWm39luu+2+/e1v+953iiEAUI4777xzjz32uPbaa9f0C7vtttsRRxxxwAEHbLTRRmv6nfvvv//MM888+uijf/SjH036CzNnzjz22GMnfTQEAO0GgBNOOGGKf/L444+vWLFi2bJlo6Ojt99++3XXXfezn/1srY+Me8ELXnDKKadsueWWfZ8ypEIAoCh33nnngQceuKbefdx66633/Oc//xnPeMZTnvKUefPmrbvuuqN/8Lvf/e6SSy656qqrpnh20Lrrrnvssce++tWvruf0AehWAw/inDlz5rvf/e6PfOQjkz5qAvIlAFCahx9++K1vfetXv/rVyl95iy22OOWUU3bffffKXxmA1ALA8573vP/+7//edddda30XaIWnAFGaOXPmHHfccaeeeurChQsrfNnXvOY1V199te4foHiLFy8+/fTTf/SjH+n+KZUJAMVatmzZZz7zmU984hN33313P6/zkpe85IMf/ODzn//86k4NgOQmAIsWLTrooINe+9rXLlq0qNpXhtQIABTu4YcfPvXUU4877rgLLrjg0Ucf7f4fPvWpT33FK17xhje84WlPe1qdJwhAQwFg5syZs2bNWn/99efOnbvJJpssWLBg22233XHHHZ/+9KcvXrx4iy22qOdMITkCAFEsW7bsoosuuvDCC6+55prrrrvutttue/DBB5ctWzY2NjZnzpy5c+duueWW22yzzY477rjLLrvsvvvu2223XdunDABQPQEAAAACcRMwAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCAz2j4BqNjg4GDP/3ZkZKTScwGgOeo/dGlWt78ImRd3APKl/kOFBABSpNADxKT+QwMEAFqm1gPEpP5DWwQAmqbiA8Sk/kMiBABqp+IDxKT+Q5oEAKqn4gPEpP5DFgQAqqHoA8Sk/kN2BAB6p+gDxKT+Q9YEAKZH0QeISf2HYggAlFb3pz5V3/UIMC3qP5RHACCnup/a+QCUKrV6m9r5QNYEAFIssimcA0A0KdTeFM4BiicA0H7NVe4BWqT+QzQCAC3UXxUfIAXqP8QkAMTVZBVW8QHSof5DcAJAOM3UYhUfIDXqPzBOAIiigYqs6AMkSP0HJhAAyldrXVb0AZKl/gOTEgBKVl91VvcBUqb+A1MQAApUU3VW9AESp/4D3RAAilJHjVb3AdKn/gPdEwAKUXmZVvcBsqD+A9MlAORN3QeISf0HeiYA5KraSq3uA+RC/Qf6JADkp8Jire4DZET9ByohAORE6QeISf0HKiQA5KGqeq3uA+RF/QcqJwCkTukHiEn9B2oiAKSrkpKt7gNkR/0HaiUApEjpB4hJ/QcaIACkRekHiEn9BxojACSk/8Kt9APkSP0HmiQAJKHPwq3uA2RK/QeaJwC0TOkHiEn9B9oiALRG6QeISf0H2iUAtKOf8q30A+RL/QdaJwA0TekHiEn9BxIhADRH6QeISf0HkiIANKTnCq70A2RN/QdSIwDUzsIPQEzqP5AmAaBeFn4AYlL/gWQJAHVR+gFiUv+BxAkAteitiCv9ALlT/4H0CQAVs/ADEJP6D+RCAKiShR+AmNR/ICMCQDWUfoCY1H8gOzPbPoESqP4AMan/QI5MAPrVQx1X+gEKoP4DmRIAemfhByAm9R/ImgDQIws/ADGp/0DuBIBeTLeUK/0AZVD/gQIIANNj4QcgJvUfKIanAE2D6g8Qk/oPlMQEoFvGvgAxqf9AYQSAtbPwAxCT+g8USQBYCws/ADGp/0Cp3AMwFdUfICb1HyiYALBGqj9ATOo/UDZbgCah9APEpP4DEZgATKT6A8Sk/gNBCAB/QvUHiEn9B+KwBajHaq70AxRD/QdCMQH4P6o/QEzqPxDNjIHMqcVUaGRkpO1TALql/lMh9Z9Qsp8A+IsFAIBAAQAAAIgVAAwBAAAgUAAAAABiBQBDAAAACBQAAACAWAHAEAAAAAIFAAAAIFYAMAQAAICpzRoIZnh4uO1ToE1DQ0NtnwLQhPkHq/b8idEl6j+UOAHoZgig/wMAILLSAgAAABArABgCAABAoAAAAACsSdAAYAgAAEBMBQaAwcHBtk8BAAASNTNs928IAABAQEUFAGv/AAAQJQD00P0bAgAAEE0hAcDaPwAARAkA/XT/hgAAAIRSQgAAAACiBID+N/8YAgAAEEfeAcDWf4CY1H+AiAGgy+o/+AdT/44hAEBGdP8AEQNA991//ecCQHMUdoCIAaCH7t8QAKAAun+AiAHA2j9ATAo7QNAA0PNFwhAAAAAyCwCWfwBiUv8BIgaA/jf/GAIA5Ej3DxAxANj6DxCTwg4QMQBU2P0bAgBkRPcPEDQAdMNFAgAASggAlazrT+uXDQEAUmBlByBiAKi8+wcgC2o7QMQAUF/1NwQASJnuHyBoAOiGiwQAAJQQAOre/GMIAJAmmz8BIgYA1R8gJvUfIGIAaKyyGwIAJEVnDxA0AHTDRQIgJvUfoLQA0PDw1xAAIBE2/wBEDACqP0BM6j9AYxIKAG1VdkMAgHbp7AGCBoBuuEgAxKT+A5QWANod/hoCALTF5h+AiAFA9QeISf0HCBoAUmAIAABABO0HAMs/ADGp/wARA0BS1d8QACBm/QcIpf0JAAAAECIAJLj8YwgAELP+A8TRWgBQ/QFiUv8B2pXuFiBfDAwQk+4foMAAoLgDxKT+A0QMAOkPfw0BAGLWf4AI0t0CBAAAZB8Acln+MQQAiFn/AYqX3ARA9QeISf0HKDAA5FXcDQEAYtZ/gLI1FwAMfwFiUv8BkpLQFqAEq78hAEDM+g9QsFnNvI3iDhCT+r8mo0ssIQGxJwDJXiEMAQBi1v+6zT94uO1TAIJqIgCELe4Awan/AAlKYgKQ+BXCEAAgZv2vmyEAUGYAWGtxD179AUql/gNEDADFFHdDAICY9b9uhgBAuC1ArhAAMan/AAUGgMKKuyEAQMz6XzdDACDQBMAVAiAm9R+gwABQZHE3BACIWf/rZggAFPhNwJ1cIQBiUv97Mzx/QdunkLeh0aVtnwIUPQEo+NFvhgAAMet/60MA/StQ1BeBAQAAzag+ABS//GMIABCz/tfNEABohgkAAAAEUnEACLL8YwgAELP+180QAGiACQAAAARSZQAItfxjCAAQs/7XzRAAqJsJAAAABFJZAAi4/GMIABCz/tfNEAColQkAAAAEUk0ACLv8YwgABBe2/tfNEACojwkAAAAE0kQAKHv5xxAAIGb9r5shAJBuAFDfAWJS/wFyZAtQBQwBAKiDIQCQYgBw+xdATOo/QKZMAKphCABAHQwBgLQCgOUfgJjUf4B8mQBUxhAAgDoYAgDZBADLPwAxqf8AZQYA9b2TIQAQgfrfPEMAIIMJgMsDQEzqP0CZAUB9XxNDAKBs6n9bDAGAqrgJGAAAAuklAHj629QMAYBSqf/tMgQAKmECAAAAgVQfACz/GAIAMan/DTAEAFoIAOo7QEzqP0AZbAGqiyEAAHUwBADSCgDWhwBiUv8BygwA6vu0GAIAxVD/k2IIAKQyAXB5AIhJ/QfIiHsA6mUIAEAdDAGAJgKABR6AmNR/gJJUNgFweVgTQwCgbOp/WwwBgHoDgPoOEJP6D1AY9wA0wRAAgDoYAgCtBQDrQwAxqf8AZQYA9b1/hgBAjtT/9BkCANNlCxAAAARSQQCwPtQlQwCgMOp/IgwBgGkxAQAAgEDWHgAs8FTIEADIiPqfEUMAoLkJgMsDQEzqP0CmbAFqmiEAAHUwBACqCQAWeABiUv8BStXXBMDloTeGAEDu1P80GQIA3bAFCAAAApkqAFjgqY8hAJAy9T9fhgDAWpkAAABAIL0HAOtDfTIEADKl/ifOEACYmgkAAAAEssYAYIGnAYYAQILU/wIYAgDVTwBcHgBiUv8BcmcLUMsMAQCogyEAsCYCAAAADEQPACa8TTIEANKh/pfEEACobALg8gAQk/oPUABbgJJgCABAHQwBgE4CAAAAxA4AJrytMAQAWqf+F8kQAOh3AuDyABCT+g9QBluAEmIIAEAdDAGA1QkAAAAQiACQFkMAAOpgCACsMQDY4gkQk/oPEMT0JgAuDw0wBAASpP4XwBAAGGcLEAAABCIApMgQAIA6GAIAAgAAAAQOALZ4psMQAGiS+h+HIQAwjQmAywNATOo/QElsAUqXIQAAdTAEgOAEAAAACEQASJohAAB1MASAyP4YAGzxBIhJ/QcIpdsJgMtDWwwBgHap/6UyBICwbAECAIBABIAMGAIAUAdDAIhJAAAAgEAEgDwYAgBQB0MACEgAAACAeAFg6gVmj4BIgSEAUAf1H0MAiMYEAAAAAhEAcmIIAEAdDAEgFAEAAAACEQAyYwgAQB0MASAOAQAAAAIRAPJjCABAHQwBIAgBAAAAggUAD4HOjiEAUAn1nwkMASACEwAAAAhEAMiVIQAAdTAEgOIJAAAAEIgAkDFDAADqYAgAZRMAAAAgEAEgb4YAANTBEAAKJgAAAEAgAkD2DAEAqIMhAJRKAAAAgEAEgBIYAgBQB0MAKJIAAAAAgcycevF4rUvLJMIQAJgu9Z9uGAJAeUwAAAAgEAGgHIYAANTBEAAKIwAAAEAgAkBRDAEAqIMhAJREAAAAgEAEgNIYAgBQB0MAKIYAAAAAgQgABTIEAKAOhgBQBgEAAAACmeG7HmGVkZGRtk8BmqP+wyrqP6GYAAAAQCACAAAABCIAAABAIAIAAAAEIgDAH7knEiAm9Z9QBAAAAAhEAAAAgEAEAAAACEQAAACAQGblfk/M1F/dNzw83OC5kIGhoaG2TwHykHv9n39w6vV/dMlU5Wh4/oIGzyWEodGlbZ8CpMIEAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACCQmVN/lfrUPwUgX+o/QEwmAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABAsAIyMjEzxG1P/FIB8qf8AAZkAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAvADgUdAAMan/ANGYAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAg3QYAD4IAiEn9Byg2ACjxADGp/wCh2AIEAACBCAAAABCIAAAAAIFMIwDYJAoQk/oPUGwAUOIBYlL/AeKwBQgAAAIRAAAAIBABAAAAApleALBJFCAm9R+g2ACgxAPEpP4DBGELEAAABCIAAABAILPaPgEAgBoNjS5t+xQg8wmATaIAMan/ZGdodKnuH7oKAEo8QEzqP8XQ+sMUbAECAMqh74e1EgAAgBJo/aHGpwCZEQPEpP6TJht+oIIAoMQDxKT+kxetP/TAFiAAID/6fuiZAAAA5ETrD+18E7AZMUBM6j8tsuEH6g0ASjxATOo/CdL6Q4VsAQIA0tV/3z//4OGBgYHRJUMVnRFE3QJkiQggLPWfXFb95x88PN79A6szAQAAylz1B6Y9AbDGAxCT+k9brPpDA0wAAID2WfWHDO4BsEQEEJb6T4Ws+kNaAUCJB4hJ/acBWn9ohS1AAEDTbPiBXLcAWSICCEv9pzdW/SGDAKDEA8Sk/lMtrT8kwhYgAKBeNvxAUVuALBEBhKX+08Cqv+4fKmcCAABUr/++X+sPbU4ArPEAxKT+0+Kqv+4f0t0C5AoBEJb6z+q0/pAFW4AAgH7Z8AMFTgCs8QDEpP4zNav+EHQLkCsEQFjqf1hafyg/ACjxADGp/0yg9YesuQcAAOiWvf5QgMq2AFkiAghL/Y/Aqj8EnQCMjIwMDg7WdjJQo6GhobZPATKm/kdm1R8KU/EWIFcIEqT1hwao/0XS+kOR3ANAybT+AL3R+kPBph0ArPGQBa0/VE79D0LrD8WrfgLgCkG7tP7QFvU/d1p/CMIWIMqh9QfojdYfQplZx+PePA+Ohg39QdtnAeVT/8vj4Z4QkAkAedP3A/TGqj+E1WMAsNGT1mn9oRXqfwG0/hBcXRMAVwjqo/WHlKn/KdP6Az3eAzDORk9y3OuvL4H+qf85stcfaOIeAItAJLXq79MIjVH/k2LVH5jATcCkTusP0ButP1DxFiDPgyOLDT+6f6iD+p84G36AKZgAkCKr/gC9seoP1DsBsAhE5az6Qy7U/9RY9Qe6ZAJAKqz6A/TGqj/QdADwtAf6pPWHTKn/rdP6A4lOAFwhWBOtP5RN/a+P1h/omS1AtEPrD9AbrT/Q8k3A49wKRvfc5gslUf+b5DZfoBImADTHqj9Ab6z6A8lNACwCMTWr/lAw9b9WVv2BypkAUC+r/gC9seoPpD4BsAjEBFb9IQ71v3K6f6A+JgBUz6o/QLu0/kBDEwCLQFj1h7DU/0TY7g+slQkA1bDqD9AufT/QzgTAIlBAVv2Bcep/W6z6A9NiAkDvrPoDtEvfDyQxAbAIFEH/q/66fyiS+t8Yq/5AfhOAkZER/V+O+u/7tf4QnPrfJ30/kGgAUN/Lo/UHuqH+10frD2R/D4CLRC60/kC11P/p0voDeQQA9b0AWn+gB+p/hbT+QGlPAXKRSJbWH6iV+r9WWn8gywCgvudI6w/0T/3vh9YfyO8xoKvzSLiAD/d01QfU/954uCcQ5YvALBS1zqo/0Ar1fxV9P1BUAFDfU6b1B+qj/ndD6w9EnAC4SLRC6w+kIHL91/oDJQeAyPU9QVp/oDHq/5ro/oHoEwAXiWZo/YEEqf8ART0FaFpPe/BEiPp4wg/QFvUfIO4EwBpPK6z6A61T/wHSkdAWoHEuEhXS+gMZUf8BStsCNM4guBk2/ACpUf8BEpHcBIA+WfUHACChCYBFoPpY9QcSp/4DxJ0A2OhZLav+QC7Uf4DWpbsFyEWiG1p/oDzqP0BpW4DGGQT3yYYfIFPqP0DQAOAa0DOtP5A79R+gReluAaKTDT8AAGQ8AbAI1D2r/kBh1H+AoAHANWCttP5AqdR/gFbYApQuG34AAChwAmARqJNVfyAI9R8gaABwDVhF6w9Eo/4DNCyzLUAFfzuMDT8AMes/QNwAELa4a/2B4MLWf4DQW4BiDoJt+AGIWf8BWpRWAIhzDdD6A8Ss/wCtS2gLUJB5sQ0/AP3It/4DJCLFAFBqcdf6A8Ss/wBJSW4LUJGDYBt+AGLWf4AEpTgB6H4dKP1rgFV/gJj1HyBZ6QaA3Gn9AQBIUNIBINPNoFp/gJj1HyALSQeA7K4BWn+AmPUfICOpB4BcrgFaf4CY9R8gOxkEgMRp/QEAyEgeASDNRSCtP0DM+g+QtTwCQGrXAK0/QMz6D1CAbAJAItcArT9AzPoPUIycAkC71wCtP0CLZACAoAGgFVp/AACKkV8AaHIRSOsPkA5DAICgAaCZa4DWHyBBMgBA0ABQ6zVA6w+QMhkAoE8zB7I1MjJS7QsO/UH/r+PKBJBX/QcIJdcJQLXrQJX0/Vp/gMaYAwAEDQD90/oDABBK3ACg9QcAIKCIAUDrDwBAWLECgNYfAIDgogQArT8AAIQIAFp/AACIEgA81x8AAAIFgD5p/QEAKIwAMDmtPwAARRIAJtL6AwBQMAHgj7T+AAAUb2bbJwAAADRHAPijkZGRtk8BAADqZQvQnxgZGbERCKAAo0uq+RIYgPKYAExkDgAAQMEEgEnIAAAAlGpWtJ6+yx0+479vOxAAAIUpfwIw8ger/5/T+rf1nBQAALRjZpzWf/Xj03qRSk8KAADaNDNU67/6L0zr1ao4KQAAaN/MaK3/6r85rZft46QAACAVMwO2/qv/k5p+GQAA0lTCU4D6ac2n9bQfjwYCACB3M9o+gVRMq62XAbJW4f0hQAHU/zjUfyhtC1CfbAcCiEn9B6IRAHq/BrgMAJRB/QdCEQD+RK23EQOQLPUfiEMAmMg1ACAm9R8IQgCoYLxrHAxQBvUfiEAAWCNLQQAxqf9A2QSAqbgGAMSk/gMFEwCqvwa4DAAUQP0HSiUA1FLTXQMACqD+A0USALplKQggJvUfKIwAMA09FHTXAIACqP9ASQSA6TEOBohJ/QeKIQD0wjgYICb1HyiAANDoONhlACB36j+QOwGgd70VdNcAgNyp/0DWBIB+WQoCiEn9BzIlAFSgt2ruGgCQO/UfyJEA0PI42GUAIGvqP5AdASCJpSCXAYCsqf9ARgSAivVczV0DALKm/gO5EABqYSkIICb1H0ifAJDiUpDLAEC+1H8gcQJAvXou5S4DAFlT/4FkCQC166eUuwYA5Ev9B9IkADTEUhBATOo/kBoBIJulIJcBgEyp/0BSBICmuQwAxKT+A4kQANrRTx13GQDIl/oPtE4AaE2fddxlACBT6j/QLgGgZS4DADGp/0BbZrT2znQYHBxs/RUimPqS6YIKNE/9b4b6D+NMABLSf+mxIASQI/UfaJIAkJZKKrjLAEB21H+gMQJAilwGAGJS/4EGuAcgdVVt67Q9dBV7QIEsqP+VU/9hnAlA6qpayLEgBJAX9R+oiQlATipcxYm8IGQFCMiO+l8J9R/GmQDkpMJVHAtCABlR/4EKmQDkqtolnFALQlaAgKyp/z1T/2GcAJC3ygt3hCuBCwBQAPW/B+o/jBMACuFK0D0XAKAk6n/31H8YJwAUpY6qXd6VwAUAKI/63w31H8YJAAWqqWQXcyVwAQBKpf5PTf2HcQJAyeor2VlfDFwAgOKp/5NS/2GcAFC+Wot1jlcCFwAgCPV/AvUfxgkAUTRQqXO5GLgAAKGo/6uo/zBOAAinmTKd8sXABQCISf1X/2GcABBXkzU6qeuBCwAQnPrfw0+hJAIALVTndq8HLgAA49T/7n8KJREAaL8oN/zWLgAAq1P/u/kplEQAIMVxba3n4AIAMCn1v763hqQIAKR+Maj8fFwAANZK/YeCCQBkeSXo51RdAAC6p/5DeQQAir0S9MYFAGBS6j8UQwCgd0VeDFwAANZK/YesCQBUo5iLgQsAwLSo/5AdAYDqZX0xcAEA6Jn6D1kQAKhdXtcDFwCAqqj/kCYBgKYlfj1wAQCoifoPiRAAaFlq1wMXAIBmqP/QFgGAFLV4VXABAGiR+g8NEADISQMXBhcAgASp/zBQnf8PyAJ2yZXImn4AAAAASUVORK5CYII="
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_231
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color red.\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is Cut the right side of the shape\nthe 6th action is Stack the original shape on top of the {'layer1': 'SuSuSuSu'}.\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is Colorize the top layer of the original shape with the color purple.\nthe 9th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:9)_217
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color white.\nthe 2th action is Colorize the top layer of the original shape with the color red.\nthe 3th action is Cut the right side of the shape\nthe 4th action is Cut the right side of the shape\nthe 5th action is Colorize the top layer of the original shape with the color green.\nthe 6th action is Cut the right side of the shape\nthe 7th action is Stack the original shape on top of the {'layer1': 'WcWcWcWc'}.\nthe 8th action is Cut the right side of the shape\nthe 9th action is Stack the original shape on top of the {'layer1': 'CbCbCbCb'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_476
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is Stack the original shape on top of the {'layer1': 'RgRgRgRg'}.\nthe 3th action is Stack the original shape on top of the {'layer1': 'RcRcRcRc'}.\nthe 4th action is Stack the original shape on top of the {'layer1': 'WyWyWyWy'}.\nthe 5th action is Colorize the top layer of the original shape with the color yellow.\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'RrRrRrRr'}.\nthe 8th action is Cut the right side of the shape\nthe 9th action is Colorize the top layer of the original shape with the color white.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABAAAAATICAIAAAANxCANAABEHklEQVR4nO3de5RdZX344UkyIeRCLkBMCOEHGlESikRQ0UCLLkS5BkEygGLF4n0hWlvrotWCLqtWa6tUKxYvAYXAcCt3FEgQBSKIXAIqEhAEJBBgSMgdkvktm640nXPmzMw5e5+99/t9nuU/7gnnvJnMfuf97Hefc4b19vZ2AAAAMQwvegAAAED7CAAAAAhEAAAAQCACAAAAAhEAAAAQiAAAAIBABAAAAAQiAAAAIBABAAAAgQgAAAAIRAAAAEAgAgAAAAIRAAAAEIgAAACAQAQAAAAEIgAAACAQAQAAAIEIAAAACEQAAABAIAIAAAACEQAAABCIAAAAgEAEAAAABCIAAAAgEAEAAACBCAAAAAhEAAAAQCACAAAAAhEAAAAQiAAAAIBABAAAAATSWfQAoK1Wrlw5ZcqUdevW1f3q+9///rPPPrvtgwKgJRdccMGQ/vzw/9bZ2Tlq1KgxY8ZMnDhx8uTJU6ZMGTFiRG5jhBIZ1tvbW/QYoH2+//3vn3zyyf19dfvtt1+2bNnIkSPbOygAWjJs2LDWH2Sbbbb5sz/7s3322ed1r3vdkUceOW3atCyGBmUkAIjloIMOWrhwYYM/cNVVVx1++OFtHBEApQiAPg+4//77n3TSSe9973s7O90uQWq8BoBAnnjiiZtuuinbfWQA0tPb2/vzn//8/e9//8yZM7u7u4seDmRMABDIggULNm3a1PjPXH755f29QgCAaJYuXXrcccd98IMf3LBhQ9FjgcwIAAL50Y9+1OfIpEmT+hx54YUXrr766jYOCoCyO/vssw855JAXX3yx6IFANgQAUdx///333HNPn4Nf/epXa2/uvPDCC9s4LgBy0dvQxo0bN2zYsGLFikcfffTmm2/+93//92OPPXbMmDH9PdqiRYtOPfXU9v4NIC9eBEwUp5122pe//OWtj4wfP/7pp58+7LDD+rwsePTo0U8//fS4cePaPkYAMnsRcBMrnFWrVn3961//yle+8sILL9T9Az/+8Y/f9ra3NTVGKBE7AITQ29u7YMGCPgff8Y53jBo16phjjulzfO3atVdccUUbRwdAKYwbN+4zn/nM4sWLd9ttt7p/4HOf+1zbBwXZEwCE8LOf/ezRRx/tc/C4447bnAG1l468FxBAWLNmzbr66qvr3g506623/vKXvyxiUJAlAUAI5513Xp8j22+//cEHH9zR0bHzzju/4Q1v6PPVH//4x88//3wbBwhAicyaNevTn/503S/dcMMNbR8OZEwAkL4NGzZcdNFFfQ4ec8wxWz7x9+ijj679Ty699NJ2DRCA0vnoRz86YsSI2uOLFi0qYjiQJQFA+q655pqenp669/9sVvsyAHcBAQS34447zp49u/Z47Q2lUDkCgIhv/z958uS3vOUtW/7v7rvvvueee/b5MwsXLly+fHlbBghAGe211161B5955pkixgJZEgAkbsWKFbUf7HXsscf22dit3QTYuHHjxRdfnP8AASipHXbYofbgihUrihgLZEkAkLiLL7543bp1fQ4ef/zxfY64CwiAwXySwPjx44sYC2RJABDu/p9p06YdcMABfQ7Onj375S9/eZ+DP//5z5944omcBwhASdV9O7jJkycXMRbIkgAgZY8//vjNN9/c5+C8efOGD6/zk1/7XkCbNm3q7u7Oc4AAlNcDDzxQe3DfffctYiyQJQFAys4///xNmzYNeP9PfwHgLiCAsNavX3/XXXfVHv+Lv/iLIoYDWRpW9/42SMPee+997733bn1k1113/f3vf1/70b+br/dPmzbtqaee6nP84Ycfrr07CIDyqDurt7jCOe+880488cQ+B8eMGfPEE09MnDixlUeGwtkBIFn33Xdfn9V/R0dHV1dX3d8TfzoZhg8/6qijao9feOGF+QwQgJLasGHDF7/4xdrjH/zgB63+SYAAIFm1L/9tcP/PZt4LCICOjo5PfvKTv/71r/sc3GWXXT7/+c8XNCLIkluASFNvb+9uu+32hz/8YeuDr3zlKx988MEG/9WLL774spe9rPZtH37zm9/sscce+YwUgBLdArR69epPfOIT3/3ud/scHz9+/E033fTa17622TFCidgBIE0333xzn9V/R0fHcccd1/i/Gjly5OGHH1573CYAQPJ6enrOPPPMPffcs3b1P2XKlGuvvdbqn2TYASBNH/jAB2pn8Hvvvbfu57pv7dJLL33nO9/Z5+Aee+zxm9/8JusxApDjDsCCBQsa/Ce9vb3r169fs2bNsmXLHn/88bvuuuvee++tfeO4jo6Ogw8+eP78+dOmTct0yFAkAUCC1q9fP3Xq1D538sycObP2hs5aa9as2XHHHdeuXdvn+F133TV79uysRwpABvp7d4cWvfa1r/3c5z535JFH5vHgUCC3AJGgq6++uvY+/sYv/91izJgxb3/722uPuwsIII6xY8d++9vfvvPOO63+SZIAIEHnnXde7cEBXwDQ+BPBvBkoQByrV6/+yEc+svPOO59yyiluASU9bgEiNc8///zUqVPXr1+/9cHZs2fX/UDHunp6el72spe99NJLfY4vXrx4v/32y26kAJT6FqAtDj300G984xu77757rs8CbWMHgNRcfPHFfVb/Q7r839HRMWnSpDe/+c21x90FBBDTtdde+5rXvOZf/uVfih4IZKMzo8eBUn/+17Bhw4a0fJ88eXLtwe7u7q997WvDh8tmgAoY8B6HTZs2rV69+oUXXnjiiScee+yxu++++/bbb1+0aNGGDRtq//C6des+9alPPfLII2eeeaZfBFSdW4BIymOPPbbrrrvm91N90003HXjggTk9OACFfxDYs88+O3/+/C984Qu1byax2emnn37GGWc08chQHhKWpJx//vm5Nq27gADStsMOO/zN3/zN7373u7e85S11/8AXvvCF2267re3jgizZASApr3nNa5YsWZLf40+ePPmPf/xjZ6d75wDS3AHYYv369YcffviNN95Y+6WDDz74Jz/5SSsPDsWyA0A67r333lxX/x0dHcuXL1+4cGGuTwFAGYwaNercc8/dfvvta790/fXXD+aTJaG0BACJv/w3c+4CAghi2rRpp5xySt0vXXPNNW0fDmRGAJCI3t7eBQsW9Dk4duzYNWvW9Dbr/PPPr32iyy67rO4bRACQng9+8IN1j996661tHwtkRgCQiJtuuunxxx/vc/CII44YPXp004955JFH1v7nzz///HXXXdf0YwJQITvvvPOMGTNqj7sFiEoTACTivPPOqz04b968Vh5z3Lhxhx56aO1xdwEBxLHvvvvWHnzuueeKGAtkQwCQgvXr119yySV9Do4dO7bu8n1Iurq6ag9eccUVa9asafGRAaiEHXbYofZgf58SAJUgAEjBVVddVTsXH3744WPGjGnxkY844ojaB1m9evVVV13V4iMDUAnjx4+vPejDgKk0P74k+/4/Ld7/s9nYsWMPO+yw2uMXXnhh6w8OQPmtXLlykFUAVSEAqLyenp7at2MbM2ZM3YV7E4477rjag9dcc80LL7yQyeMDUGbLly+vPTh9+vQixgLZEABU3kUXXVT7vpyZ3P+z5aHGjh3b5+C6dev+67/+K5PHB6DMbr/99tqDM2fOLGIskA0BQOXl8f4/Wxs9evQRRxxRe9x7AQEk73e/+90f/vCH2uP77bdfEcOBbAgAqu0Pf/jDz372s/zu/2nwXkDXX3+9t4EDSNu//du/1T1++OGHt30skBkBQLWdf/75vb29fQ4edthhtTfttOKwww4bN25cn4Mvvvhi7XuPApCMu+666wc/+EHt8QMOOKDup4NBVQgAqi3v+38223bbbY888sja4+4CAkjVE088ceyxx65fv772S5/+9KeLGBFkRgBQYXffffd9993X5+Do0aPz2JmtexfQT3/606eeeirz5wKgWIsXL95vv/0efvjh2i8dcsghdV8YBhUiAEjt8v+hhx6a7f0/Wx629l2fN27ceNFFF2X+XAAU5fbbb//Lv/zLOXPmPPHEE7VfnTp1at2bgqBaOoseADRp06ZNCxYsaMP9P5uNGjVq7ty5tZ84dsEFF5xyyil5PCMArRjMXZovvfTS+vXrV65c+cwzz/z2t7+98847H3300f7+8Pbbb3/ddddNnTo165FCuw2rfQElVMLChQsPOuigPge33Xbb5cuX175gNxNXXnnl3Llz+xwcNmzYo48+ussuu+TxjAAMxrBhw/J+ilmzZl1xxRVe+0sa3AJEVdVejN98o05Oq/+Ojo63v/3tEyZM6HOwt7f3wgsvzOkZASiDE088cfHixVb/JEMAUEnr1q279NJL23b/z2bbbLPNUUcdVXvcewEBpOp1r3vdLbfc8sMf/nC77bYreiyQGQFAJV155ZUrVqzoc3DbbbfN+50Z6r4X0J133rl06dJcnxeAdho3btz73ve+W2655Y477pgzZ07Rw4GMeREwlTR69OjTTz+9z8H/9//+X95XaN72tredccYZta+cqa0RAEpu2LBhnZ2do0aNGjdu3KRJk6ZMmbLrrrvus88+c+bMmT17dmenNRLJ8iJgAAAIxC1AAAAQiAAAAIBABAAAAAQiAAAAIBABAAAAgQgAAAAIRAAAAEAgAgAAAAIRAAAAEIgAAACAQAQAAAAEMmzevHlFjwEAoEgXXXRR0UOA9rEDAAAAgQgAAAAIRAAAAEAgAgAAAAIRAAAAEIgAAACAQAQAAAAEIgAAACAQAQAAAIF0Nv5y96TJ7RoJtENXz/IGX/UDT7Sf+QacDiSm6XMB0mMHAAAAAhEAAAAQiAAAAIBABAAAAAQiAAAAIBABAAAAgQgAAAAIRAAAAEAgAgAAAAIRAAAAEIgAAACAQAQAAAAEIgAAACAQAQAAAIEIAAAACEQAAABAIAIAAAACEQAAABCIAAAAgEAEAAAABCIAAAAgEAEAAACBCAAAAAhEAAAAQCACAAAAAhEAAAAQiAAAAIBABAAAAAQiAAAAIBABAAAAgQgAAAAIRAAAAEAgAgAAAAIRAAAAEIgAAACAQAQAAAAEIgAAACAQAQAAAIEIAAAACEQAAABAIAIAAAACEQAAABCIAAAAgEAEAAAABCIAAAAgEAEAAACBCAAAAAhEAAAAQCACAAAAAhEAAAAQiAAAAIBABAAAAAQiAAAAIJDOogcAuejqWZ7tf9U9aXJrIwJKcZoDIACoqjb/7m/8dPIA2q970mQNANAEAUAFlP93fN0RqgIAoIQEAKVT/uV+038RSQDZsgkA0AQBQPHi/P7u8zfVAwBA+wkAihFn0T/Ib4IYgObYBAAYKgFA+/gl3YAYAADaQwCQL4v+JogBGBKbAABDIgDIhV/GmX8nlQAAkAkBQJas+/OjBKABmwAAgycAyEAJf+/2t0pu+vO8yvN3VALQnAXz7y96CBTphJP2LHoIUBYCgOYVuyZu8/K38dMV8q1QAjCkTYATTtpTAwAIAJrR/sVu+Re4dUfYtm+UEgAABk8AMARtW9GmsZDt87dow3dv81Ok8d2DJtgEABgMAcDA2rByjbBmbVsP2BAAABoQABS29A++PN36r5/T99mGAAHZBAAYkACgvpyWpBaj7Y8BGQAAbE0A8H9Y9xduy/cq238L9wURh00AgMYEAHkt/S00y7ktYEMAAIITAGS89LeyrMS2gAwgbTYBABoQAKFluPS3lKxiCcgAAAhoeNEDoBhdPcuzWv13T5psBdl+GX7bM/xhgPIY8AQ54aQ92zUWgHKxAxBOhuv+TB6HkmwI2A0AgCDsAASS1YVel/xLKKt/FLsBpMQmAEBddgCiaH1VZ9EfZ0Ogq2e5f24ASJUdgPS1fk3XJf/Kaf2fzFYAabAJAFDLDkDKXPUPbvM/Xys/Bl4YAADpEQBpav2Sf3ZjofL3BckAKs1nAgD04RagBLWy+ne3T8Ja/Md1RxAApEEAJKWV+7Yt/YNo5R/aCwOoKK8EANiaAEiHpT9ty4CshwMAtI8ASEHT12Ut/YNr+gfAVgCVYxMAYAsBEPrCf9ZjoZJsBQBAKAKgwlz4Jyu2AojAJgDAZgKgqiz9KVUG5DAcACAXAqB6mrvmaulPrj8qtgKoBJsAAAIg0IX/HMZCymwFAECqBECVuPBPJbYC8hkOZMMmAEBn0QMgx6V/PmMhls0/SEP6Cdz8h/0EAkA52QGoAKt/CmcrgJTYBACCEwBlN9RVlHt+yEkTP1oaAABKSACUVxNvq2LpT96aaAAZQAnZBAAiEwAl5cI/pWUrAAAqTQCUkQv/lJ8GoOpsAgBhCYDSsfqnKjQAAFSRACiRod4t7bYfCjfUH0IvCaBUbAIAMQmAsnDhn+qyFQAAFSIASsHqn6rTAFSUTQAgIAFQPLf9EPZ2oDyHAwDUJwAqtvrPcyyQAQ1A5dgEAKIRAEWy+idJGgAAykwAFGbw6x63/VA5Q/qh1QAUziYAEIoAqMDqP+exQF40AACUkAAogNU/cWgAqsImABCHAGirIX0KktU/ARtABgBA3gRA+3jJL2F5WTCVYBMACEIAtInVP8FpAAAoCQHQDlb/oAGoBJsAQAQCIHfe7hO28PagAFA4AVAWlv7E4aedMrMJACRPAORrkJcwrYeIZpA/8zYBACBzAiBHVv/QgAagtGwCAGkTAHmx+ocBaQAAaD8BkAurfxgkDUA52QQAEtZZ9AASZPUPQ9I9afJgzpqunuXOGlIiIYCi2AHImNU/NME+ACVkEwBIlQDIktU/NE0DAEB7CIDMWP1DizQAZWMTAEiSAMiG1T9kQgMAQN4EAAD0yyYAkB4BkAGX/yFDNgEAIFcCoFVW/5A5DUCp2AQAEiMAWmL1DznRAACQEwHQPKt/yJUGoDxsAgAp8UnA+bL6hzZ8SDCkZ0b3pKKHkJqHunqKHgKUhR2AJg1mUWL1D60bzHkkEmgDmwBAMgRAM6z+oZ00AABkSAAMmXUGlJNzk7zZBADSIABy4fI/ZMs5BQBZEQBD4+YfKIobgSgDmwBAAgTAEFj9Q7E0AAC0TgAMllUFVIWzlVzZBACqTgBkyeV/yJuzDABaJAAGxc0/UB5uBKJwNgGAShMAA7P6h7LRAADQNAEAAENmEwCoLgEwAJf/oZxsAgBAcwRAI1b/UGYagGLZBAAqSgC0xOofiuUcBIChEgD9cuEQ0uBcJj82AYAqEgD1ufkHqsKNQAAwJAKgSVb/UB7ORwpkEwCoHAFQh4uFkB7nNQBsJgD6cvMPVJEbgSiQTQCgWgTAkFn9Qzk5NwFgMATA/+ECIaTNOU5ObAIAFSIAhsYlRigzZygADEgA/C+XBiECZzo5sQkAVIUAGAIXF6H8nKcA0JgAGOxFQasKqIoBz1abAOTEJgBQCQLgT6wGIBpnPQBhCYBBcfkfqsU5S1FsAgDlJwBcCISgnPsAxCQABuZSIlSRM5ei2AQASi56ALgECJGZAQAIKHoADMhFRKgu5y9FsQkAlFnoAPDWn5A8bwkKAH2EDgAAyIlLSEBpxQ0Al/8hCJsAALC1uAEAALlyIQkop6AB4PI/hGITAACiBwAAtIHLSUAJRQwAl/8hIJsAABA3AACgbVxUAspGAPRlpoZUObsBIGIA2OUH+mN+ICfiEyiVcAEAAACRxQoAL/+F4LwUmKL4/QKUR6wAAACA4AIFgMv/gE0ACuS3DFASgQIAAAAQAP/DhRmIw/lOUfzsAWUQJQDs6QODZ8YAIGFRAgAAysAmAFC4EAHg5b9AH14KDEBYIQIAAMrDVSegWALARAxBOfcBiCn9ALCPDzTH7EF+9CdQoM4in5zqS2yFVMW/jmUEADAk6e8ANGbxBJGZAQAIKPEAqOIFXaA8zCEApCfxAGjMxT/APABANKEDAAAAokk5AOzdA60zkwCQmJQDoDH7/sBmZgMAQokbAAAAEFCyAWDXHsiK+QSAlCQbAI3Z8Qe2Zk4AIA6fBEyOuru7O0qmq6urWgMecMwAAEOS5g6A/XogW2YVAJKRZgAAAAB1RQwAN/sCtcwMAAQRMQAAACCsBAPArbpAHswtAKQhwQBozC4/0B/zAwARhAsAAACITAAAAEAgqQWAm3SB/JhhAEhAagHQmBt8gcbMEgAkL1YAAABAcAIAAAACSSoA3J4L5M08A0DVJRUAjbm1FxgMcwUAaQsUAAAAgAAAAIBABAAAAASSTgB4ZR7QHmYbACotnQBozKv6gMEzYwCQsCgBAAAACAAAAIhFAAAAQCACAAAAAhke4U05vJ4PGKrG84Y3AgKguhIJAAAAYDAEAAAABCIAAAAgEAEAAACBCAAAAAhEAAAAQCApBID3AAXy4J1AAUhSCgEAAAAMkgAAAIBABAAAAAQiAAAAIBABAAAAgQgAAAAIRAAAAEAgAgAAAAIRAAAAEEjlA8DHAAP58WHAAKSn8gEAAAAMngAAAIBABAAAAAQiAAAAIBABAAAAgQgAAAAIRAAAAEAgw+bNm1f0GIDm+bCLvHmzf4jgoosuKnoI0D6dbXwuIHuWpwDAkLgFCAAAAhEAAAAQiAAAAIBABAAAAAQiAAAAIBABAAAAgQgAAAAIRAAAAEAgnVX/kNHGn4JU/vFX3QDf/+7ujpLp6uqq1oAHHDPFKv8k0/RHxVX9r7Zg/v0d5XbCSXs2+OqM7kkdwTzU1dP4D7Q4RZtLYQufBAxJKf+irXJ81jKUQTkv0EBFuQUIkmK1CiR5+R/IkAAAAErN5X/IlgCA1NgEAAAaEAAAQHnv/3H5HzInACBBNgEAgP4IAACgMC7/Q/sJAEiTTQAAIM0AaPyu59ZAQCt81CDkyuV/KETlAwDojwAGAGoJAACgAC7/Q1EEAKTMJgAA0IcAAADazeV/KJAAgMTZBAAAtiYAoNq8EQ1QOS7/Q7EEAKTPJgAAsIUAgMqzCQBUiMv/UDgBAAAAgaQQAD4MGAbcBHAiNMHHAEObufwP7ZFCAAAACdz/A7RHZ5ueB8hZ96TJja9Yd/Usd9EaCHj5v6urK6dHhooSAABAwZf/c1r9W/pDXQIA0mETAGAzS39oQAAAAOlc/rf0hwEJAEiKTQAgLEt/iPUuQN4JFMiW9wCFal3+t/qHwbMDAKmxCQCEYukPQyUAAIBKXv639IfmCABIkE0AIG2W/tAKAQAAVObyv6U/tC6RFwEPyOuAiWbAC/xOigZ8c6CEuv5b0aOAFKQTAO5nANrDbAOtG9Ll/9aX/jO6J7Xyn0Ni3AIEyfJKAKC09/8MUuuX/C39oZYAAABKd/nf0h/yIwAgZTYBgMpd/rf0h7wFCgALHWAwvAIYirr8b+kP7ZHOi4C9Mg/q8nZA2TLPQE6X/1t/ma/VPwxSoB0AAKCEl/+9ww+0mQCA9HklAFDOy/+tLP2t+6FpsQLAKgdozA1R0J7L/5b+UKDOaFc6ISabAJnwLYLWL/9b+kPhUgsAAKCEuru7Lf2hJJJ6FyCgAW8HBBR4+b/p1b+394HMhdsBcJ8D0B8JBKVi3Q85SXAHwPoe+uPsaIXvHuT00b+1XPWHXIXbAQAasEUGFMu6H9ogYgBY4hCZd8rqj28LFMi6H9opYgAADShkoJ33/1j6Q/sl+BoAt+pCY06QJvimQebc6A9FsQNAjlp5y+dCVG7AObEJAOR6+d+6H4qV5g7AgNzsS3DW932YE6A9XPWHMkg2AKxvoBUWxFszn0Drl/8t/aE83AIEQXk7IKA9rPuhbJLdARiQpQ80vrAd5xyJ8zeFNl/+d9UfyinlHQAXOIHWuf8HhsqiH0ou7g4AYBMAyPbyv0v+UAkp7wAMyHsdAiIHMmHdDxWS+A6A9T0MyCZAA+YQGPDyv6v+UDmhdwBsAkBwwfMGWmTdDxUVPQBoURXzKcM1XxX/+k28Yl4nA7Ws/qG6Er8FKKUlGiXU1bPcJeSEmT0ASFL6ATAgCzhalEYGBHwlQJJ/KQAYkACAbKSRAQBA8kIEwID7+NZtZKXSGRBqE2DAv477fwBIVYgAgMHLZNlX6QwAANIWJQBczGPwuidN3vy/Fh+nig0QahOgATMGAAmLEgADirOyYfBazwBbAeXkHwWAyAQADCBaBtgEAIC0BQoALwWmFdEyIGFe/gtAcIECAFoXJAOsgAEgYbECwCYAmQiSAf2p7shd/geAcAEAGUo7A6yDASBV4QLAsoZspZ0B/ancgAfJ/ABABOECIOzKhlwlmQHprYbL9h0GgEIIAMhMkhnQn6qMEwDoI2IAeCkwuUopA1LaBPDyXwCIGwDQBillQH9KPjwAoK6gAWATgPZIIAPSuC7u8j8ARA8AaH8GtLLELDwD+lPOUQEADcQNAJsAtF9FM6DqV8dd/geArcUNAChKRTOgP6UaDAAwoNABYBOAAlUrA6p7jdzlfwDoI3QADIYGIFfVyoAGw+gopdIODAAKFD0AXPyjDCqRAUmeLEn+pQCgsegBMBguItIelciABs/eUTIlHBIAlIEAcAmQcilzBiR2siT21wGAQRIAg+JSIm1W5gxo8KQdpVGqwQBAqQiAP3EhkHIqYQYkc7Ik8xcBgKESAP/DW4JSWiXMgAbP1VEC3voTABoQANVb3BBTeTKg5Ktn5ykANCYAKrOsgS0Z0PTPaht2A8q//namAxCcAEhtcUMQxWZAadfQzlAAGJAAqMayBvLIgKyHk/sjt845DgACIKnFDTE1nQGtbAWUcCXt3ASAwRAAzSxrrDMooUIyoMFjZvuAmTxjCaMFANpPANRhlUB1tTMDqnWmVGu0AJAfAdAkmwCUWal2A9qgimMGgKIIgPrcCEQC2pABDR6/VJ8+5vI/AGwhAPplxUAaou0G1HIuA8DWBEBL0lgeEUF+GVDsJoBzEACGSgA04kYgEpPYboCbfwCgCQJgABqA9GSeAYVsAlj9A0BzBAAEldhuAAAwSAJgYDYBSD4DmiiBPhnQ5k0Al/8BoGkCYFA0AMnLJAPaw+ofAFohALKkAYicAe3ZBHCWAUCLBMBguaBIHE1nQEc5OFsBoAEBMARuBCKUpl8lnN+p4eYfAGidABgaDUA02WZAK6z+ASATAiAXGoDEZJIBrZwXzikAyIoAGDKXGAmrPLsBdZV5bABQHgKgGW4EIrJWMqC588LNPwCQIQHQJA1AcG3bDbD6B4BsdWb8ePxfjd8cHapu84/3kFp3SCeFiiash7p6ih4CkCw7AM0b5CLGCobk5bQbMMhzR2MDwJAIgJZoAGgiAwZzRlj9A0BOBECrNADUZkCL63KrfwDIjwDIgAaAWo0zoMHpYPUPALkSAEDcjw4AgIAEQDZsAsBQM6Du6eDyPwDkTQBkRgNAi7sBVv8A0AYCIEsaAIaUAVufC1b/ANAeAiBjGgCa2A2w+geAtvFJwNnrnjR5kG9zbjVDcEP6IGHnC4lZMP/+9j/pCSft2fqDVPRkdOkNthAAudAAMEhW/9AekZf+QB8CIC8aAAZk9Q9tYOkP9CEAcqQBoAGrf8ibpT9QlwDIlwaAuqz+IVeW/kADAqAsNABxeCke5MfSHxiQACjLJsCWVZFpl4QNaenvXIAhsfQHBkkAlKsBbAWQMKt/yImlPzAkAqBNNADBWf1DHiz9gSYIgPbRAIRl9Q+Zs/QHmiYAyvu5pxqAaKt/P/AwGJb+QIsEQNlfFmyOptKs/iFDlv5AJgRAMTQAEVj9Q1Ys/YEMCYDCeHtQEuamf8iKpT+QOQFQJC8LJklW/5AJS38gJwKgYBqAxFj9Q+ss/YFcCYDiDbUBTOsksPT3Ywx1WfoDbSAAqtcAtgIoIat/aJGlP9A2AqAsNADVZfUPrbD0B9pMAFT1Y8LcDkQZWPpDKyz9gUIIgNKxFUBVWP1D0yz9gQIJgDLSAJSf1T80x9IfKJwASKcB/EqgnEt/P5mwmaU/UBICIJ2XBNgKoA1c+IcmWPoDpSIAys5WACXhwj80wdIfKCEBkGAD2Aogc1b/MFSW/kBpCYCUbwfyy4PWWfrDUFn6AyUnANLfCvCLhLYt/f2wEZylP1AJAiD9BnBHEE2w+ochsfQHKkQAhLgdyFYAg2fpD0Ni6Q9UjgAItxXgNw3ZLv39RBGWpT9QUQIg3FaADKCWpT8MiaU/UGkCIOhWgBcGsIXVPwyepT+QAAGQAlsBNMfSHwbP0h9IhgBIRytbAX4tRdP00t+PCgFZ+gOJEQBJaXorQAbEYekPg2fpDyRJACSo6a0AGZC2Vpb+fiqIxtIfSJgASFMrWwFb/4d+eyWgxXW/HwOisfQHkicAUtZiBtgQqDpLfxgSS38gCAGQPhkQkKU/tH/p78QBqkIARNHKCwM2c19QhHX/Zv6JicPSHwhIAATS+lbAZjYESsjSH4bK0h8ISwCEk20G+OWXxrrfvyOhWPoDwQmAoLLKABsCRbH0hyZY+gMIgOgyzwC/Fyu07vePRSiW/gBbCACyzAAlUIl1v38dQrH0B+hDAJBLBvR5KL84y7Do38y/BXFY+gPUJQCo/3su29WnbYHBs+6HTPhUL4D+CADatCGwmW2Bdi76N/N9hiY4cYCECQAKyIDNgsdArov+sN9VaJ0TB0ieAKCw+4K21ueRk/wF3IYVf8LfPWgD5w4QhACgLBsC6fVA21b8Vf9GQeGcO0AoAoAybgj0UfeJSvULu/1r/dJ+K6BanD5AQAKAKpXA1ho/aea/1Itd4tdl4QKtcAYBYQkAKl8CdTU9kvL8Ffpj1QItchIBwQkAEi+BZFiyQOucRwACgLwogaxYr0AmnEoAWwgA2vdLVwwMkpUKZMgJBdCHAKB9xEAD1iiQOacVQF0CgGKIAasTyI+TC6ABAUDpflUn3AMWJZA3ZxnAgAQAFfj9XdEksBCBdnLGAQySAKCqv9dLVQVWHlAgJyDAkAgA0vyVn3keWGFACTkxAZogAIi1LGgcBhYTUCFOWIDmDG/yvwMAACpIAAAAQCACAAAAAhEAAAAQiAAAAIBABAAAAAQiAAAAIBABAAAAgQgAAAAIRAAAAEAgAgAAAAIRAAAAEIgAAACAQAQAAAAEIgAAACAQAQAAAIEIAAAACEQAAABAIAIAAAACEQAAABCIAAAAgEAEAAAABCIAAAAgEAEAAACBCAAAAAhEAAAAQCACAAAAAhEAAAAQiAAAAIBABAAAAAQiAAAAIBABAAAAgQgAAAAIRAAAAEAgAgAAAAIRAAAAEIgAAACAQAQAAAAEIgAAACAQAQAAAIEIAAAACEQAAABAIAIAAAACEQAAABCIAAAAgEAEAAAABCIAAAAgEAEAAACBCAAAAAhEAAAAQCACAAAAAhEAAAAQiAAAAIBAOht/uatnebtGAsXzAw9bOB0AUmUHAAAAAhEAAAAQiAAAAIBABAAAAAQiAAAAIBABAAAAgQgAAAAIRAAAAEAgw3p7e4seAwAA0CZ2AAAAIBABAAAAgQgAAAAIRAAAAEAgAgAAAAIRAAAAEIgAAACAQAQAAAAEIgAAACAQAQAAAIEIAAAACEQAAABAIAIAAAACEQAAABCIAAAAgEAEAAAABCIAAAAgEAEAAACBCAAAAAhEAAAAQCACAAAAAhEAAAAQiAAAAIBABAAAAAQiAAAAIBABAAAAgQgAAAAIRAAAAEAgAgAAAAIRAAAAEEhn0QOA9lm/fv3ixYtvueWW3/72t0uXLn388cdXrVq1evXqTZs2jR49euzYsTvttNPOO+88c+bMvffee//9999tt92KHjIAQMaG9fb2Zv2YUC7r16+/8sorzznnnBtuuGHdunWD/w933333Y4899n3ve9/uu++e5wABGLILLrhgSH9+2LBhw4cPHzFixKhRo0aPHj1+/Pgddthh6tSpo0ePzm2MUFICgJStWbPmW9/61le/+tXly5e38jhz584944wzXvva12Y3NABaMmzYsEweZ/r06bNmzdpnn30OPPDAAw44YNy4cZk8LJSZACBZF1xwwSc+8Ymnnnoqk0cbPnz4Rz/60S996Ut+NwCkFABbGzVq1CGHHPKud73r6KOPHjlyZOaPDyUhAEjQs88+e/LJJ19++eWZP/KrX/3qyy+//NWvfnXmjwxA4QGwxc4773zqqad+7GMfc4MQSRIApObXv/713LlzH3rooQZ/5lWvetW+++47c+bMHXfccbvttlu7du1zzz3X09OzZMmS2267raenp8F/O2HChB//+Mf77bdfDmMHoBQBsNkuu+zyla985fjjj8/7iaDNBABJufXWWw899NCVK1fW/er06dM//OEPv+td73r5y1/e3yP09vYuWbLkP//zP88555xVq1bV/TMTJkxYuHDhPvvsk93AAShdAGw2b968s846a/vtt2/P00EbCADS8ctf/vKggw6qu/ofP378Zz/72Y9//OODv6dzxYoVp59++plnnln3HJk+ffrtt9++0047tTxqADILgMarmpdeemnjxo1r1qxZtWrV8uXLH3nkkfvvv/+OO+746U9/2t+Vo81e8YpXXH311XvssUcWA4fiCQAS8fDDD7/+9a9/7rnnar/0+te/vru7u7k39b/hhhtOPPHEuq8kPvjgg3/yk580NVgACgiA/mzYsOHGG2/8zne+c+WVV27atKnun5k0adK1117r/k/SIABIwZo1a+bMmXPPPffUfumoo47q7u7eZpttmn7w++6778ADD6ybFmefffb73//+ph8ZgDIEwBZLliz527/92/4u7kycOHHhwoXeEpoECABScPLJJ3//+9+vPT537txLLrmks7PVT7y+4447/vzP/3z9+vV9jk+dOnXp0qVjx45t8fEBKEMAbPad73zn1FNP3bBhQ+2XdtpppzvvvNP9n1Td8KIHAK264YYb6q7+99577/PPP7/11f/mm4g++9nP1h5ftmzZWWed1frjA1AeH/rQh2688cYJEybUfunJJ5/s6urauHFjEeOCzNgBoNrWr18/c+bM3//+932Ojxkz5u677959992zeqIXX3xx3333XbJkSZ/jr3jFKx588MHhw7U0QCI7AJvddtttb33rW9esWVP7pa997Wuf/OQns3oiaD+rFqrtrLPOql39d3R0fPGLX8xw9d/R0TFy5MjTTz+99vjDDz986623ZvhEAJTBm970pu9973t1v3T66ac//vjjbR8RZEYAUGFr16798pe/XHt8jz32OOWUUzJ/une84x3Tp0+vPX7ZZZdl/lwAFO74448/4YQTao+vWrWq7m8fqAoBQIX96Ec/WrZsWe3xf/qnfxoxYkTmTzdixIgPfehDtccXLVqU+XMBUAb//M//PHr06Nrj3/ve9+r+AoJKEABU2Nlnn117cMaMGe94xztyesYjjjii9uC99967evXqnJ4RgALtsssuf/d3f1d7fN26dfPnzy9iRJABAUBV3XfffXfccUft8Y9+9KP5vSR37733njx5cp+DGzdufOCBB3J6RgCK9dd//dejRo2qPX7uuecWMRzIgACgqi6//PLag8OGDTv++OPze9Jhw4YddNBBtccffPDB/J4UgAJNmDCh7vbvb/5bESOCVmXwFulQiGuuuab24Jw5c6ZNm5br8x5//PG1bzO33Xbb5fqkABTo3e9+9yWXXFJ7/IYbbpg5c2YRI4KW+BwAKmnVqlUTJ06s/SiWz372s5///OcLGhQA6XwOwNY2bNgwadKk2s8EOProoy+99NI8nhFy5RYgKumuu+6q+0GMBx54YBHDASBl22yzzV577VV7/O677y5iONAqAUAl/epXv6p7fPbs2W0fCwDpq/v75ZFHHnnhhReKGA60RABQSb/+9a9rD06dOnWHHXYoYjgARAyA3t7ehx56qIjhQEsEAJX02GOP1R58xSteUcRYAEjfrFmz6h7/4x//2PaxQKsEAOkEwE477VTEWABI38SJE+sef/LJJ9s+FmiVAKCSnnnmmdqDtR/RBQCZGD9+fN3jK1eubPtYoFUCgEqqfS+2jo6O0aNHFzEWANI3YcKEusfXrl3b9rFAqwQAlbRu3brag9tuu20RYwEgff3tAKxfv77tY4FWCQAq6aWXXqo96FPtAMhJ3Q+f6ejoGDlyZNvHAq0SAFTSqFGjBrktAACt6+9Kv81nqkgAUEl1b/ev+8IAAGhdfx/4NWbMmLaPBVolAKik7bbbrvbg8uXLixgLAOl76qmn6h6fOnVq28cCrRIAVNK0adNqDy5btqyIsQCQvv7e73/nnXdu+1igVQKASqo74T788MNFjAWA9P3ud7+re3zXXXdt+1igVQKASnr5y19ee/Cpp5567rnnihgOAIn77W9/W3tw8uTJbgGiigQAlfSa17ym7vF77rmn7WMBIH2LFy+uPbj33nsXMRZolQCgkvqbc3/2s5+1fSwAJG7FihX33Xdf7fE5c+YUMRxoVWfLjwAFmDVr1oQJE1asWNHn+KJFi/7xH/8x16f+q7/6qz7vN7rNNtuce+65uT4pAAW69tpr634Q2MEHH1zEcKBVw3x4KhV1zDHHXHbZZX0OjhgxYtmyZTvuuGNOT/rQQw+98pWv7HNwt912+/3vf5/TMwJQ17Bhw2oP5rSqmTdv3sUXX9zn4MSJE59++mmfBEwVuQWIqjrkkENqD27cuPGSSy7J70mvv/762oO1SQBAMp5++unLL7+89vhxxx1n9U9FCQCq6phjjqk7837729/O70lvuOGG2oN77bVXfs8IQLG++c1vvvjii7XH3/ve9xYxHMiAAKCqdtxxx0MPPbT2+D333LNo0aI8nnHt2rU33nhj7fH9998/j6cDoHDPPvvsN77xjdrj++2335ve9KYiRgQZEABU2Ic+9KG6x//hH/4hj6c7//zzn3/++T4HR44c+Za3vCWPpwOgcJ/61KdWrlxZe/zv//7vixgOZEMAUGGHHXbY7Nmza4/fdtttF154YeZP961vfav24EEHHbT99ttn/lwAFO7qq6/+wQ9+UHt8//33P/LII4sYEWRDAFBtn/nMZ+oe/9jHPvbMM89k+EQXX3zxXXfdVXv8Ax/4QIbPAkBJLF269D3veU/t8REjRnzrW9+q+x5EUBUCgGp75zvfWfcOnOXLl7/nPe/ZtGlTJs/y/PPPn3rqqbXHZ8yYcdRRR2XyFACUx+OPP37wwQf39PTUfum0007zAcBUnQCg8r75zW/WfTug66677lOf+lTrj9/b2/uRj3zkySefrP3Sl770pREjRrT+FACUx5IlS+bMmfPII4/Ufukv/uIvzjjjjCIGBVkSAFTerFmzvvSlL9X90r/+67+edtppLT7+KaeccsEFF9Qef+tb3zpv3rwWHxyA8ujt7T3rrLPe+MY3PvbYY7VfnTFjRnd3t+s+JMAnAZOC3t7euXPnXnXVVXW/evzxx3/3u98dO3bsUB929erVH//4x7/3ve/VfmnSpEn33nvv9OnTmxovAKX7JOCFCxeedtppt99+e92vTpky5ZZbbpkxY0bTjw/lIQBIxMqVK9/85jfXfZ3u5ss2X//614844ojBP+DNN9988sknL126tPZLnZ2d11133UEHHdTCeAEoRQA88MADV1xxxQ9/+MMlS5b092d2222366+/3ue+kwwBQDqefvrpAw444MEHH+zvD+y3336nnnrqkUceud122/X3Z1auXHnVVVedeeaZv/jFL+r+geHDh8+fP7/uW0MAUGwALFiwoMF/snHjxg0bNqxevbqnp2fZsmVLly791a9+NeBbxr3pTW+65JJLdtppp5aHDGUhAEjK008/PXfu3P7W7ptts802b3zjG/faa69XvvKVEyZMGDlyZM9/++Mf/7h48eIlS5Y0eO+gkSNHzp8//13velc+wwdgsNrwRpzDhw//5Cc/+cUvfrHuW01AdQkAUrN27doPf/jD5557buaPPGXKlEsuuWT//ffP/JEBKFsAvOENb/iP//iPfffdN9dngUJ4FyBSM3r06HPOOeeyyy6bOnVqhg/77ne/+7777rP6B0jenDlzrrjiil/84hdW/6TKDgDJWr169Te/+c2vfvWrzz77bCuP87a3ve1zn/vcG9/4xuyGBkDpdgBmzZp11FFHnXjiibNmzcr2kaFsBACJW7t27WWXXXbOOecsWrToxRdfHPx/+KpXveroo49+3/ve9+pXvzrPAQLQpgAYPnx4Z2fntttuO3bs2IkTJ06ePHmXXXbZY4899txzzzlz5kyZMiWfkULpCACiWL169a233nrLLbc88MADS5cuffLJJ1etWrV69ere3t7Ro0ePHTt2p512mj59+h577DF79uz9999/t912K3rIAADZEwAAABCIFwEDAEAgAgAAAAIRAAAAEIgAAACAQAQAAAAEIgAAACAQAQAAAIEIAAAACEQAAABAIAIAAAACGTZv3ryixwBlcdFFFxU9BGgf8z9sYf4nFDsAAAAQiAAAAIBABAAAAAQiAAAAIBABAAAAgQgAAAAIRAAAAEAgAgAAAAIRAAAAEEhn4y93T5rcrpFAO3T1LC96CFAN5n8SY/6HLewAAABAIAIAAAACEQAAABCIAAAAgEAEAAAABCIAAAAgEAEAAACBCAAAAAhEAAAAQCACAAAAAhEAAAAQiAAAAIBABAAAAAQiAAAAIBABAAAAgQgAAAAIRAAAAEAgAgAAAAIRAAAAEIgAAACAQAQAAAAEIgAAACAQAQAAAIEIAAAACEQAAABAIAIAAAACEQAAABCIAAAAgEAEAAAABCIAAAAgEAEAAACBCAAAAAhEAAAAQCACAAAAAhEAAAAQiAAAAIBABAAAAAQiAAAAIBABAAAAgQgAAAAIRAAAAEAgAgAAAAIRAAAAEIgAAACAQAQAAAAEIgAAACAQAQAAAIEIAAAACEQAAABAIAIAAAACEQAAABCIAAAAgEAEAAAABNLZUXFdPcuLHgIABTD/AwTdAeieNLnoIQBQAPM/QNAAAAAAYgWAi0AAMZn/AYIGAAAAECsAXAQCiMn8DxA0AAAAgFgB4CIQQEzmf4CgAQAAAMQKABeBAGIy/wME+iTgoVow//6ih0CRTjhpz6KHABTD/B+c+R/S3AEYzEUg5z9Aksz/AEEDAAAAiBUALgIBxGT+BwgaAAAAQKwAcBEIICbzP0DQAAAAAGIFgItAADGZ/wGCBgAAABArAFwEAojJ/A8QNAAAAIBYAeAiEEBM5n+AoAEAAADECgAXgQBiMv8DBA0AAAAgVgC4CAQQk/kfIGgAAAAAsQLARSCAmMz/AEEDAAAAiBUALgIBxGT+BwgaAAAAQKwAcBEIICbzP0DQAAAAgODCBYCLQAAxmf8BggYAAABEFjEAXAQCiMn8DxA0AAAAIKygAeAiEEBM5n+AoAEAAAAxxQ0AF4EAYjL/A8HFDQAAAAgodAC4CAQQk/kfiCx0AAAAQDTRA8BFIICYzP9AWNEDAAAAQhEALgIBBGX+B2ISAAAAEIgA+BMXgQBiMv8DAQkAAAAIRAD8DxeBAGIy/wPRCAAAAAhEAPwvF4EAYjL/A6EIAAAACEQA/B8uAgHEZP4H4hAAAAAQiADoy0UggJjM/0AQAgAAAAIRAHW4CAQQk/kfiEAAAABAIAKgPheBAGIy/wPJEwAAABCIAOiXi0AAMZn/gbQJAAAACEQANOIiEEBM5n8gYZ1FDyA6v0IAYjL/A0WxAzAAF4EAYjL/A6kSAAAAEIgAGJiLQAAxmf+BJAkAAAAIRAAMiotAADGZ/4H0CAAAAAhEAAyWi0AAMZn/gcQIAAAACEQADIGLQAAxmf+BlPgk4FLr7u4uegip6erqKnoIAAOb0T2p6CGk5qGunqKHAGVhB2BoXAQCiMn8DyRDAAAAQCACYMhcBAKIyfwPpEEAAABAIAKgGS4CAcRk/gcSIAAAACAQAdAkF4EAYjL/A1UnAAAAIBAB0DwXgQBiMv8DlSYAAAAgEAHQEheBAGIy/wPVJQAAACAQAdAqF4EAYjL/AxUlAAAAIBABkAEXgQBiMv8DVSQAAAAgEAGQDReBAGIy/wOVIwAAACAQAZAZF4EAYjL/A9UiAAAAIBABkCUXgQBiMv8DFSIAAAAgEAGQMReBAGIy/wNVIQAAACAQAZA9F4EAYjL/A5UgAAAAIBABkAsXgQBiMv8D5ScAAAAgEAGQFxeBAGIy/wMlJwAAACAQAZAjF4EAYjL/A2UmAAAAIBABUPBFIACSZP4HSksAAABAIAIgdy4CAcRk/gfKSQAAAEAgAqAdXAQCiMn8D5SQAAAAgEAEQJu4CAQQk/kfKBsBAAAAgQiA9nERCCAm8z9QKgIAAAACEQBt5SIQQEzmf6A8BAAAAAQiANrNRSCAmMz/QEkIAAAACEQAFMBFIICYzP9AGQgAAAAIRAAUw0UggJjM/0DhBAAAAAQiAArjIhBATOZ/oFgCAAAAAhEARXIRCCAm8z9QIAEAAACBCAAAAAhEAAAAQCACAAAAAhEAAAAQiAAAAIBABAAAAAQiAAAAIBABAAAAgQgAAAAIRAAAAEAgAgAAAAIRAAAAEIgAAACAQAQAAAAEIgAAACAQAQAAAIEIAAAACEQAAABAIAIAAAACEQAAABCIAAAAgEAEAAAABCIAAAAgEAEAAACBCAAAAAhEAAAAQCACAAAAAhEAAAAQiAAAAIBABAAAAAQiAAAAIBABAAAAgQgAAAAIRAAAAEAgAgAAAAIRAAAAEIgAAACAQAQAAAAEIgAAACAQAQAAAIEIAAAACEQAAABAIAIAAAACEQAAABCIAAAAgEAEAAAABCIAAAAgEAEAAACBCAAAAAhEAAAAQCACAAAAAhEAAAAQiAAAAIBABAAAAAQiAAAAIBABAAAAgQgAAAAIRAAAAEAgnY2/3NWzvF0joY6urq6ihwAEZf4v1kNdPUUPAUiWHQAAAAhEAAAAQCACAAAAAhEAAAAQiAAAAIBABAAAAAQiAAAAIBABAAAAgQgAAAAIZIBPAu6eNLmjyp9VuWD+/R3ldsJJezb4and3dxvHEoIPV4ZBMv8XO//P6J7UxrGE4MOVYQs7AAAAEIgAAACAQAQAAAAEIgAAACAQAQAAAIEIAAAACEQAAABAIAIAAAACEQAAABCIAAAAgEAEAAAABCIAAAAgEAEAAACBCAAAAAhEAAAAQCACAAAAAhEAAAAQiAAAAIBABAAAAAQiAAAAIBABAAAAgQgAAAAIRAAAAEAgAgAAAAIRAAAAEIgAAACAQAQAAAAEIgAAACAQAQAAAIEIAAAACEQAAABAIAIAAAACEQAAABCIAAAAgEAEAAAABCIAAAAgEAEAAACBCAAAAAhEAAAAQCACAAAAAhEAAAAQiAAAAIBABAAAAAQiAAAAIBABAAAAgQgAAAAIRAAAAEAgAgAAAAIRAAAAEIgAAACAQAQAAAAEIgAAACAQAQAAAIEIAAAACEQAAABAIAIAAAACEQAAABCIAAAAgEAEAAAABCIAAAAgEAEAAACBCAAAAAhEAAAAQCACAAAAAhEAAAAQiAAAAIBABAAAAAQiAAAAIBABAAAAgQgAAAAIRAAAAEAgAgAAAAIRAAAAEIgAAACAQAQAAAAEIgAAACAQAQAAAIEIAAAACEQAAABAIAIAAAACEQAAABCIAAAAgEAEAAAABCIAAAAgEAEAAACBCAAAAAhEAAAAQCACAAAAAhEAAAAQiAAAAIBABAAAAAQiAAAAIBABAAAAgQgAAAAIRAAAAEAgAgAAAAIRAAAAEIgAAACAQAQAAAAEIgAAACAQAQAAAIEIAAAACEQAAABAIAIAAAACEQAAABCIAAAAgEAEAAAABCIAAAAgEAEAAACBCAAAAAhEAAAAQCACAAAAAhEAAAAQSGfRA6CRrq6uoocAQAEe6uopeghAsuwAAABAIAIAAAACEQAAABCIAAAAgEAEAAAABCIAAAAgEAEAAACBCAAAAAhEAAAAQCA+CbhgC+bf3/4nPeGkPVt/kO5JkzsqqKtnedFDAPgT83+bmf9hCwEQS+SpHyAy8z+whQCIwtQPEJP5H+hDAKTP1A8Qk/kfqEsApMzUDxCT+R9oQACkydQPEJP5HxiQAEiNqR8gJvM/MEgCIB2mfoCYzP/AkAiAFJj6AWIy/wNNEADVZuoHiMn8DzRNAFSVqR8gJvM/0CIBUD2mfoCYzP9AJgRAlZj6AWIy/wMZEgDVYOoHiMn8D2ROAJSdqR8gJvM/kBMBUF6mfoCYzP9ArgRAGZn6AWIy/wNtIADKxdQPEJP5H2gbAVAWpn6AmMz/QJsJgOKZ+gFiMv8DhRAARTL1A8Rk/gcKJACKYeoHiMn8DxROALSbqR8gJvM/UBICoH1M/QAxmf+BUhEA7WDqB4jJ/A+UkADIl6kfICbzP1BaAiAvpn6AmMz/QMkJgOyZ+gFiMv8DlSAAsmTqB4jJ/A9UiADIhqkfICbzP1A5AqBVpn6AmMz/QEUJgOaZ+gFiMv8DlSYAmmHqB4jJ/A8kQAAMjakfICbzP5AMATBYpn6AmMz/QGIEwMBM/QAxmf+BJAmARkz9ADGZ/4GECYD6TP0AMZn/geQJgL5M/QAxmf+BIARAxlO/2R+gcsz/QCgC4E9M/QAxmf+BgKIHgKkfICbzPxBW3AAw9QPEZP4HgosYAKZ+gJjM/wDhAsDUDxCT+R8gXACY+gFiMv8DhAsAUz9ATOZ/gIgB4FNdAGIy/wMEDYAWmfoBYjL/AwkTAPWZ+gFiMv8DyRMAfZn6AWIy/wNBCID/ZeoHiMn8D4QiAP7E1A8Qk/kfCCh6AJj6AWIy/wNhxQ0AUz9ATOZ/ILiIAWDqB4jJ/A8QLgBM/QAxmf8BwgWAqR8gJvM/QLgAMPUDxGT+BwgXAKZ+gJjM/wDhAsDUDxCT+R8gXACY+gFiMv8DhAsAUz9ATOZ/gHABYOoHiMn8D9CE4R0VZ/YHiMn8DxA0AAAAgMETAAAAEIgAAACAQAQAAAAEIgAAACAQAQAAAIEIAAAACEQAAABAIAIAAAACEQAAABCIAAAAgEAEAAAABCIAAAAgEAEAAACBCAAAAAhEAAAAQCACAAAAAhEAAAAQiAAAAIBABAAAAAQiAAAAIBABAAAAgQgAAAAIRAAAAEAgAgAAAAIRAAAAEIgAAACAQAQAAAAEIgAAACAQAQAAAIEIAAAACEQAAABAIAIAAAACEQAAABCIAAAAgEAEAAAABCIAAAAgEAEAAACBCAAAAAhEAAAAQCACAAAAAhEAAAAQiAAAAIBABAAAAAQiAAAAIBABAAAAgQgAAAAIRAAAAEAgAgAAAAIRAAAAEIgAAACAQAQAAAAEIgAAACCQzsZf7upZ3q6RAFAi5n+AVNkBAACAQAQAAAAEIgAAACAQAQAAAIEIAAAACEQAAABAIAIAAAACEQAAANARx/8HMvd+VwlrRpIAAAAASUVORK5CYII="
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_371
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color white.\nthe 2th action is Stack the original shape on top of the {'layer1': 'WyWyWyWy'}.\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is Stack the original shape on top of the {'layer1': 'RyRyRyRy'}.\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is Cut the right side of the shape\nthe 7th action is Stack the original shape on top of the {'layer1': 'ScScScSc'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'WrWrWrWr'}.\nthe 9th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:9)_291
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'RwRwRwRw'}.\nthe 2th action is Cut the right side of the shape\nthe 3th action is Colorize the top layer of the original shape with the color purple.\nthe 4th action is Cut the right side of the shape\nthe 5th action is Stack the original shape on top of the {'layer1': 'CuCuCuCu'}.\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is Stack the original shape on top of the {'layer1': 'RcRcRcRc'}.\nthe 9th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:9)_153
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color yellow.\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is Stack the original shape on top of the {'layer1': 'CpCpCpCp'}.\nthe 4th action is Stack the original shape on top of the {'layer1': 'WpWpWpWp'}.\nthe 5th action is Cut the right side of the shape\nthe 6th action is Cut the right side of the shape\nthe 7th action is Colorize the top layer of the original shape with the color blue.\nthe 8th action is Cut the right side of the shape\nthe 9th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:9)_250
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'RbRbRbRb'}.\nthe 2th action is Stack the original shape on top of the {'layer1': 'WpWpWpWp'}.\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is Colorize the top layer of the original shape with the color white.\nthe 5th action is Cut the right side of the shape\nthe 6th action is Stack the original shape on top of the {'layer1': 'CpCpCpCp'}.\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is Stack the original shape on top of the {'layer1': 'CpCpCpCp'}.\nthe 9th action is Stack the original shape on top of the {'layer1': 'SuSuSuSu'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_378
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color yellow.\nthe 2th action is Colorize the top layer of the original shape with the color red.\nthe 3th action is Cut the right side of the shape\nthe 4th action is Stack the original shape on top of the {'layer1': 'WuWuWuWu'}.\nthe 5th action is Colorize the top layer of the original shape with the color purple.\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is rotate the shape clockwise 90 degrees\nthe 9th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_352
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color cyan.\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is Stack the original shape on top of the {'layer1': 'SuSuSuSu'}.\nthe 4th action is Stack the original shape on top of the {'layer1': 'CbCbCbCb'}.\nthe 5th action is Colorize the top layer of the original shape with the color white.\nthe 6th action is Stack the original shape on top of the {'layer1': 'CgCgCgCg'}.\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is rotate the shape counterclockwise 90 degrees\nthe 9th action is Colorize the top layer of the original shape with the color red.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABAAAAATICAIAAAANxCANAAB6zklEQVR4nO3de5jkV1kn8JnJJCEXkkwg5soSaJAkLBBABRJW5MEgt4SL9BAQ12VBUB5El13Wh11Z0McFV9ZdZWHFRRRQEugmsNxBQoIgEEEMEEQuGa4JhAQYEnKbhGT2Me22Y1d3ddXv+p7zfj6Pf0h1puvXVae+57zvOVW1de/evVsAAIActo19AQAAwHAUAAAAkIgCAAAAElEAAABAIgoAAABIRAEAAACJKAAAACARBQAAACSiAAAAgEQUAAAAkIgCAAAAElEAAABAIgoAAABIRAEAAACJKAAAACARBQAAACSiAAAAgEQUAAAAkIgCAAAAElEAAABAIgoAAABIRAEAAACJKAAAACARBQAAACSiAAAAgEQUAAAAkIgCAAAAElEAAABAIgoAAABIRAEAAACJKAAAACCR7WNfAAzqmmuuOfroo2+88cZ1f/qMZzzj1a9+9eAXBUArb3zjG+f677fdZvv27QceeODBBx98xBFHHHXUUUcfffR+++3X2zVCIFv37t079jXAcP7kT/7k6U9/+kY/PfLII6+44or9999/2IsCoJWtW7e2/yUHHHDAv/yX//J+97vfj/3Yj5155pnHHXdcF5cGESkAyOVhD3vYBRdcMOU/eOc73/noRz96wCsCIEQBsOYXnn766f/m3/ybX/iFX9i+3XEJauM9ACRy+eWXf/CDH+x2HxmA+uzdu/ev/uqvnvGMZ5x88slLS0tjXw50TAFAIueee+6tt946/b9529vettE7BADI5tJLL33Sk570zGc+86abbhr7WqAzCgAS+fM///M1t+zYsWPNLT/4wQ/e9a53DXhRAET36le/+hGPeMTNN9889oVANxQAZPF3f/d3n/70p9fc+LKXvWzycOeb3vSmAa8LgF7sneqWW2656aabrr766q997Wsf+tCH/tf/+l9PfOITDz744I1+24UXXvjc5z532L8A+uJNwGTxghe84Hd+53f2veWwww678sorH/WoR615W/BBBx105ZVXHnrooYNfIwCdvQm4wQrn2muv/f3f//3f/d3f/cEPfrDuf/C+973v4Q9/eKNrhEDsAJDC3r17zz333DU3Pu5xjzvwwAOf8IQnrLn9hhtuePvb3z7g1QEQwqGHHvobv/EbF1100Yknnrjuf/Cbv/mbg18UdE8BQAof/vCHv/a1r6258UlPetJKGTDZOvJZQABpnXLKKe9617vWPQ700Y9+9G/+5m/GuCjokgKAFN7whjesueXII48844wztmzZcvzxx//ET/zEmp++733v+/73vz/gBQIQyCmnnPLrv/7r6/7o/PPPH/xyoGMKAOp30003LS8vr7nxCU94wuo3/j7+8Y+f/CdvectbhrpAAMJ59rOfvd9++03efuGFF45xOdAlBQD1e/e737179+51z/+smHwbgFNAAMnd8Y53PPXUUydvnzxQCsVRAJDx4/+POuqohz70oav/8+53v/s973nPNf/NBRdccNVVVw1ygQBEdK973Wvyxu985ztjXAt0SQFA5a6++urJL/Z64hOfuGZjd3IT4JZbbnnzm9/c/wUCENQd7nCHyRuvvvrqMa4FuqQAoHJvfvObb7zxxjU3nn322WtucQoIgFm+SeCwww4b41qgSwoA0p3/Oe644x784AevufHUU0+9y13usubGv/qrv7r88st7vkAAglr34+COOuqoMa4FuqQAoGaXXXbZhz70oTU3Li4ubtu2zsif/CygW2+9dWlpqc8LBCCuL3zhC5M33v/+9x/jWqBLCgBqds4559x6662bnv/ZqABwCgggrT179lx88cWTt//kT/7kGJcDXdq67vk2qMN97nOfz3zmM/vecuc73/krX/nK5Ff/rvT7jzvuuG9/+9trbv/yl788eToIgDjWTfWWK5w3vOENT33qU9fcePDBB19++eVHHHFEm98Mo7MDQLU++9nPrln9b9myZefOnevOE//wYti27bGPfezk7W9605v6uUAAgrrpppte8pKXTN7+zGc+0+qfCigAqNbk23+nnP9Z4bOAANiyZcvznve8z33uc2tuvNOd7vRbv/VbI10RdMkRIOq0d+/eE0888etf//q+N97tbnf70pe+NOVf3XzzzT/yIz8y+bEPf//3f3/SSSf1c6UABDoCdN111/3ar/3aH//xH6+5/bDDDvvgBz943/vet+k1QiB2AKjThz70oTWr/y1btjzpSU+a/q/233//Rz/60ZO32wQAqN7u3btf/vKX3/Oe95xc/R999NHvec97rP6phh0A6vSLv/iLkwn+mc98Zt3vdd/XW97ylp/92Z9dc+NJJ53093//911fIwA97gCce+65U/7J3r179+zZc/31119xxRWXXXbZxRdf/JnPfGbyg+O2bNlyxhlnvPa1rz3uuOM6vWQYkwKACu3Zs+eYY45Zc5Ln5JNPnjzQOen666+/4x3veMMNN6y5/eKLLz711FO7vlIAOrDRpzu0dN/73vc3f/M3zzzzzD5+OYzIESAq9K53vWvyHP/0t/+uOvjgg3/mZ35m8nangADyOOSQQ/7wD//wk5/8pNU/VVIAUKE3vOENkzdu+gaA6d8I5sNAAfK47rrrfvmXf/n4449/znOe4wgo9XEEiNp8//vfP+aYY/bs2bPvjaeeeuq6X+i4rt27d//Ij/zID3/4wzW3X3TRRQ94wAO6u1IAQh8BWvXIRz7yD/7gD+5+97v3ei8wGDsA1ObNb37zmtX/XO3/LVu27Nix46d+6qcmb3cKCCCn97znPfe+973/+3//72NfCHRje0e/B0J//9fWrVvnWr4fddRRkzcuLS393u/93rZtymaAAmx6xuHWW2+97rrrfvCDH1x++eXf+MY3PvWpT3384x+/8MILb7rppsn/+MYbb3z+85//1a9+9eUvf7mJgNI5AkRVvvGNb9z5znfub1R/8IMffMhDHtLTLwdg9C8C++53v/va1772t3/7tyc/TGLFi170ohe/+MUNfjPEoYSlKuecc06vNa1TQAB1u8Md7vDv//2//+IXv/jQhz503f/gt3/7tz/2sY8Nfl3QJTsAVOXe9773JZdc0t/vP+qoo775zW9u3+7sHECdOwCr9uzZ8+hHP/oDH/jA5I/OOOOMv/iLv2jzy2FcdgCox2c+85leV/9btmy56qqrLrjggl7vAoAIDjzwwNe//vVHHnnk5I/e//73z/LNkhCWAoDK3/7bOaeAAJI47rjjnvOc56z7o3e/+92DXw50RgFAJfbu3XvuueeuufGQQw65/vrr9zZ1zjnnTN7RW9/61nU/IAKA+jzzmc9c9/aPfvSjg18LdEYBQCU++MEPXnbZZWtufMxjHnPQQQc1/p1nnnnm5D///ve//973vrfx7wSgIMcff/zCwsLk7Y4AUTQFAJV4wxveMHnj4uJim9956KGHPvKRj5y83SkggDzuf//7T974ve99b4xrgW4oAKjBnj17zjvvvDU3HnLIIesu3+eyc+fOyRvf/va3X3/99S1/MwBFuMMd7jB540bfEgBFUABQg3e+852TWfzoRz/64IMPbvmbH/OYx0z+kuuuu+6d73xny98MQBEOO+ywyRt9GTBFM3yp9vN/Wp7/WXHIIYc86lGPmrz9TW96U/tfDkB811xzzYxVAZRCAUDxdu/ePflxbAcffPC6C/cGnvSkJ03e+O53v/sHP/hBJ78fgMiuuuqqyRtPOOGEMa4FuqEAoHjLy8uTn8vZyfmf1V91yCGHrLnxxhtv/L//9/928vsBiOzjH//45I0nn3zyGNcC3VAAULw+Pv9nXwcddNBjHvOYydt9FhBA9b74xS9+/etfn7z9AQ94wBiXA91QAFC2r3/96x/+8If7O/8z5bOA3v/+9/sYOIC6/c//+T/Xvf3Rj3704NcCnVEAULZzzjln7969a2581KMeNXlop41HPepRhx566Jobb7755snPHgWgGhdffPGf/umfTt7+4Ac/eN1vB4NSKAAoW9/nf1bc7na3O/PMMydvdwoIoFaXX375E5/4xD179kz+6Nd//dfHuCLojAKAgn3qU5/67Gc/u+bGgw46qI+d2XVPAf3lX/7lt7/97c7vC4BxXXTRRQ94wAO+/OUvT/7oEY94xLpvDIOCKACorf3/yEc+stvzP6u/dvJTn2+55Zbl5eXO7wuAsXz84x//1//6X5922mmXX3755E+POeaYdQ8FQVm2j30B0NCtt9567rnnDnD+Z8WBBx541llnTX7j2Bvf+MbnPOc5fdwjAG3Mckrzhz/84Z49e6655prvfOc7n//85z/5yU9+7Wtf2+g/PvLII9/73vcec8wxXV8pDG3r5BsooQgXXHDBwx72sDU33u52t7vqqqsm37DbiXe84x1nnXXWmhu3bt36ta997U53ulMf9wjALLZu3dr3XZxyyilvf/vbvfeXOjgCRKkmm/ErB3V6Wv1v2bLlZ37mZw4//PA1N+7du/dNb3pTT/cIQARPfepTL7roIqt/qqEAoEg33njjW97ylsHO/6w44IADHvvYx07e7rOAAGr1Yz/2Yx/5yEf+7M/+7Pa3v/3Y1wKdUQBQpHe84x1XX331mhtvd7vb9f3JDOt+FtAnP/nJSy+9tNf7BWBIhx566NOe9rSPfOQjn/jEJ0477bSxLwc65k3AFOmggw560YtetObGf/Ev/kXfHZqHP/zhL37xiyffOTNZjQAQ3NatW7dv337ggQceeuihO3bsOProo+985zvf7373O+2000499dTt262RqJY3AQMAQCKOAAEAQCIKAAAASEQBAAAAiSgAAAAgEQUAAAAkogAAAIBEFAAAAJCIAgAAABJRAAAAQCIKAAAASEQBAAAAiWwd+wKgY4uLi43/7fLycqfXAsBw5D/MaPus/yEUHu4AlEv+Q4cUAEQk6AFykv8wAAUAI5P1ADnJfxiLAoChSXyAnOQ/BKEAoHcSHyAn+Q8xKQDonsQHyEn+QxEUAHRD6APkJP+hOAoAmhP6ADnJfyiaAoD5CH2AnOQ/VEMBQG25v3zu0pSfLj5554DXAlA8+Q/1UQBQUu5PD3cAuiL/oWIKACKGvqAHGJ78hyQUAIyf++IeYETyH7JRADBC9Et8gAjkP+SkAMhryNyX+ABxyH9ITgGQzjC5L/EBopH/wAoFQBYD5L7QBwhI/gNrKADq12v0C32AsOQ/sC4FQM36i365DxCZ/AemUABUqKfcF/oAwcl/YBYKgKr0Ef1yHyA++Q/MTgFQic6jX+4DFEH+A/NSAJRN7gPkJP+BxhQApeo2+uU+QCnkP9CSAiB19Mt9gILIf6ATCoCSiH6AnOQ/0CEFQK7ol/sAZZH/QOcUANGJfoCc5D/QEwVA5dEv9wGKI/+BXikAIhL9ADnJf2AACoBYRD9ATvIfGIwCoKr0F/0AJZL/wJAUADVEv9wHKJT8B4anABiZ6AfISf4DY1EAjEb0A+Qk/4FxKQDKS3/RD1Au+Q+MTgEwNNEPkJP8B4JQAAxH9APkJP+BUBQA0dNf9AMUTf4D0SgAeqfxA5CT/AdiUgD0S+MHICf5D4SlAOiL6AfISf4DwSkAAqW/6AconfwH4lMAdEzjByAn+Q+UQgHQJY0fgJzkP1AQBUA3RD9ATvIfKM62sS+gBtIfICf5D5TIDsAI6S/6ASog/4FCKQCa0/gByEn+A0VTADSk8QOQk/wHSqcAGCL9RT9AHeQ/UAEFwHw0fgBykv9ANXwK0BykP0BO8h+oiR2AWdn2BchJ/gOVUQBsTuMHICf5D1RJAbAJjR+AnOQ/UCvvAZhG+gPkJP+BiikANiT9AXKS/0DdHAFah+gHyEn+AxnYAVhL+gPkJP+BJBQA/4z0B8hJ/gN5OALUMP1FP0A15D+Qih2AfyT9AXKS/0A22xJ+S0vLXyL9gQ7zh8bkPzCWxcLzf3s1z8Hy8nLjfzsj0Q/UEf3VkP/AwBaryP/idwBWc3/xNnP9W+kPzGvfqGm27qQr8h8Y0mJF+V/DDkCzbpD0BxJ2fSom/4GeLFaX/8XvAKwb95t2g6Q/MLt1I6X09k8d5D/Qq8VK87+2HYBZukHSH0jb9UlC/gMtLVad/zXsAEwvxdaUbtIfmMX0RnIF7Z9qyH+gW4sJ8r/mHYB9+YpHYEZ1d30Skv/AjBbT5H8lOwDdFmTSH3Ka8cNk6mj/1ET+Ay0tJsv/LDsAs5P+kFCerg9TyH9IaDFl/ldVACwvL7d8FqU/pNIgMapp/1RG/gNzWcyd/1UVAC1Jf8gjZ8uHjch/yGNR/tf0HoD6ijOgDw2+NXaVhInMswNMJ/9X2QH4J4tP3rny/2gFQZV0fdiI/Ie6yf/KdwA6KdEWn7xzdTIAknd9am3/VEn+A2vI/3XZAdjQyhygGwRF0/WhAfkPFZD/uXYApj/f844G3SBI0vWZ/h/X1/6pkvwH5H/GHYBNn+/Vj4qb6+nUDYKCzL3Omz8TCEj+A/I/YwHQoNozDUBNmkX/phLODcWR/5Cc/J/L1i21aLPX0+DZNQ0UavqGfq2v8wxaRv/0p97ACE7+Mwv5Xyv5n3cHoOX7PHSDoFw9dX2qT/9qyH9IS/6n3gFolv4b/SvdoLrpANWkq+jP2f6pg/xndvK/JvK/pUp2ADqkGwTx9d31yZD+TJL/EJ/878TWzJu/s3xkxLy/0zQQnA5Q6TqP/rTtnwrIf+Yi/0sn/ztU9g5A31/xoBsECbs+SdK/dPIf8pD/nSv4i8Bm/fymjbN4xme3wZdI+/oYGPcrXZJ/vlv15D8kIf97sj1D+i+fu9Q+jnWDIEPXZ1XyuSEy+Q8ZyP9ebc/Z+5n8Ysi57to0ABVEf4aIr4/8h+rJ/wFsT5L+nTSB1lyDaQAq6/qsMjfEJP+hbvJ/MOUVALOYK2fnbQKtMg1Ahxq8DNtEf5KIT0j+Q3Hk//AKKwBaPd+dNoFWmQagrOjflLkhJvkP9ZH/Y9me8+hnV02gVaYBKCj680R8NeQ/VEb+j2t7qvTvqQm0yjQAhXZ9VpkbApL/UBP5H8H25L2fDptAq0wDEDn6U0V8BeQ/VEP+x1FGATCLGdOz7ybQKtMARIv+TZkbCiX/ITj5H00BBcAsI6CT0OywCbTKNAChoj9bxJdO/kPp5H9M2xOm/2BNoFWmAdKKE/2bMjdEI//7vC7onfyPLHQBMPw46KMJ1H4aMBNQooDRnzDiyyX/5T/lkv/xbdtSuGbJOGKeNvzSmSfvHLhrBY0t3qbBv9oyHnNDieQ/RCP/SxF3B2Cwo59DNoEat4L+8R/aFya2Nl+q2recEV8o+b/OP5T/xCb/y7I9bfoPfxJ0DdMANYkc/ZsyN4Qi/6f9Q/lPPPK/RBELgNHHxABNoFWmAUpXRPSnjfjiyP+Z/qH8Jwb5X66IBcAsuvnct7GbQKtMA5SoiOjflLmhOPL/H/+h/Gc88r904QqAsY5+jtgEWmUaoBRlRX/miC+L/Jf/xCf/67A9efrHaQKtMg0QWVnRvylzQxzyX/4TnPyvSaACINoQGaUJtMo0QDSFRn/yiC/F6ONkDfkP+5L/9QlUAMyil899i9cEWmUaIIJCo39T5oayyP9Z/6H8pzvyv1ZRCoAgRz9DNYFWmQYYS+nRL+KLIP+nkP+MRf7XLUQBMHr6R24CrTINMKTSo39T5oYg5P8s5D9Dkv8ZhCgAIgvSBFplGqBXjUd7qJfJChFPS/KfVOR/KuMXAKO3f0pkGqBzNUU/pZD/Dch/Oif/E9o67t2HSv8pu8CRh3jjMjfnNDB9rz9nz6DK6J/+VOZ8oqOR/+3J/7nI/0nyP63xdwBoSTeIxqqMfshD/tOY/E9uzB2AUO2foptAq3SDNqUDlCH6tX/ik/+dk/+bkv8r5D9j7gAETP8K6AaRPPopgvzvg/xnU/Kf8XcANh1MY4VR6U2gVbpB68rcAUoS/do/8cn/vsn/dcn/If/hKOR/9B2AssZToXSDyBb9FMGgGoD8Z5X8J8oOQPzN32qaQKt0g9J2gLJFv/ZPcPJ/ePJ/lfzv+x+OS/7PxacApaAblFC26AfWJf8Tkv+E2wGI3/6ptQm0Knk3KEMHKG30a/8EJ/9HJ/+rjwj53+CnOYXbAagjZSLTDapY2uinDuKlb/K/YvKfuDsApbR/qm8CdVITx3mm5lJrB0j0a/8EJ/+jkf/VpIT8l/+hdwDKSv8kGneDNITiEP3EJ/8Dkv8VkP8UsAMQ9oOfkzeBsnWDauoAif5V2j/Byf/g5H9xQSH/V8n/0DsA9Q24+lTZDZoe9zMO1IDxIfopiFEXn/yX/2Qz0A5Aie2fhE2gcrtB8wZ9J0aZGET/JO2f4OR/WeT/LOR/EPI/9A5AxSOvVsG7QaPE/SwDu9esEf2UyPArjvyfhfyndEPsAJTb/sncBIrWDQoS+rPrcDIQ/VNo/wQn/4sm/5uR/8OQ/6F3AEpPf0bsBhUX+huN/IaPXov4zhD9xCf/Syf/m5H/ZN8BqOaj35I3gYbsBhUd+l09hqJ/Rto/kcn/ysj/9uR/h+R/2d8EXET6M0A3qPrcnwzodR9G0U8e8r8s8r89+U+KHYBq2j8rNIH66Ablyf1NH0nRPy/tn8jkf93kf1fkfzPyv+wdgILSnz66QawQ/SQk/4sm/7si/6ltB6Cy9s8KTaCNqLaHZ8g1/il9k/+peLkNz5Br/FPG3wEoLv3pqRvUt6WlfzbSdu7cOft/vOl/P4rk0U8F5H9NQuf/jqP2/Z87d181+3+86X8/CvlP6B2Aij/6TRNoU2NNA5Nr93XNWwA0+z09McZWaP9EJv8zGy3/J9bu65q3AGj2e3pijK2Q/5V8ChD1GaYbNPtKfbAL6LUkEP1AfAPl/8wr9cEuoNeSQP5Txg5Axe2fFZpAm+op/TtZ9He1A9DmXhozwLR/gpP/9JX/XSz6u9oBaHMvjRlg8r9bdgDoUucvv9E7/e0vu8NioP0HxgEUk/9jd/rbX3aHxYD8J/QOQPXtnxWaQH1Hf3/r/mF2ABrc9bxyjjTtn8jkf85XZff539u6f5gdgAZ3Pa+cI03+d8sOAB3o6oVXaL9/3r+uk0pgeXk55xwA1Jn/Zfb75/3rOqkE5D+xdgCStH9WaAJ1GP1DrvtH3AGY1EklkGe8af9EJv+zvR47y/8B1/0j7gBM6qQSyDPe5H/n7ADQUPvXW939/sH2BBwMBcrL/6r7/YPtCch/Gtu2pSOp2j/T/5wMlWjLv3HpNt1dTvHaPyDVjzrtn8jkf6qh2Db/dxxl9d/tA1L9qJP/fbADwNBL/+6upTYrD07j3QCtICD40r+7a6nNyoPTeDdA/jPOewCytX9yngRtE/1x1v2h3gMwXZtzQZUNP+2fyOR/9S/AtvkfZt0f6j0A07U5F1TZ8JP/0Y8AUbfGrzGnfRpr89DJRGD8/Hfap6k2D538J0oBUGv7J89J0GZ/i6V/Jxo/jNWMQO2fosn/pPlv6d+Fxg9jNSNQ/od+D0Blm0101fjv+lpSW1paanAiyKlQ+mZ0VaxN47/ra0ltacdRDU4EyX+mcwSorYqbQBr/oeTcCtD+ITL5v4bGf09ybgXI/9AFQNq3f1WvwUvL0n8AzR5kQUkf5H+tmuS/pX//mj3I8p912QHoQGVNoOXbzPVPLP0H1uABb/C0jk77h/jkv6X/wBo84PKfjgsA7Z/6NGv893MtbMJWACOS//Vp1vjv51rYhK0AWrID0I06mkAa/0m2AraUQPuHUiTNf43/MrcCtpRA/pddAGj/lKXB6r+3a2E+tdYAlEv+l6XB6r+3a2E+tdYAxP0mYPu/1XwxZKqlf0HfBNzAvB8VGnZYav8EJ//z5n/JS/+Cvgm4gXk/KjTssJT/Ze8AJEz/QqVa/VfPVgARyP9SpFr9V89WAEMUAGELx3EVdxLU6r8+FdQA2j/Byf+k+W/1H14FNYD8H4w3Aec11wvJ+30LMu+TJVIhm/ny3/t9yzHvkyX/02pSADj92Uyol9m8q/8+r4VeFFoDxLkS1iX/KxjY867++7wWelFoDRDnSjKwA9CxIiY/q/8kCq0BSr9I0qow/63+i1VoDVD6RaYuAIpIwMzDd/ZrcOynAnM9iaOPz9EvgJbkfz3579hP+eZ6Ekcfn6NfQDZzFwDe/tVyChx3iM+1+u/5WhhOETXApndtehid/M+S/5b+FSmiBpD/w3MEKBGr/8yKqAGAnlj9Z1ZEDUDZBYD937BNIKt/ItcA2j8VkP815L/Vf6Ui1wDyv4ACwP5voaz+iV8DEJz8L5TVP/FrAMreAdD+idkEsvoneA2g/VMB+V98/lv9JxCwBpD/Y/EegMpZ/VNEDQB0zuqfImoAohcA9n+LawJZ/RO/BtD+KYL8rzn/rf6TiVMDyP8adgDs/5bL6j8nzztdkf/lsvrPyfPOrAWA9k9xTaAZf7lVYGYzPvv9DVTtnyLI/2rz3yowsRmffflfK+8BqJPVP6XUAEC3rP4ppQag+ALA/m+oJpDVP0XUANo/dZD/Rea/1T+j1gDyv4wCwP5vQaz+acA+ABuR/wWx+qcB+wA5OQKU4uMg1rD6Z/RRof1DEuHy3+qfsUeF/K+kALD/G8csrxmrf9qMDbnMvuR/Yflv9U+LsSH/a2IHoJ4mkNU/pdQA2j+kEiX/rf4JUAPI/2IKAAdAi+AFw5CMtyTkfxG8HhmS8VaHtjsA9n8LOgmq/U+EcaL9Uw35X1L+a/8TYJzI/zgcAaqBwz90y5sBoBQO/9AtbwZIYpMCwP5v/CaQ1T8F1QDaPwWR/5Xkv9U/MWoA+V/PDoD939F5tTAuIzAt+T86rz7GZQQWzRGg+k+Cav8TZORo/5DcCPmv/U+MkSP/SyoA7P8G5/APffNmgLTkf3AO/9A3bwaomx2AmptAVv/EGUXaPzBo/lv9E2YUyf+qCgAHQMfl1UIcRmM28n9cXnHEYTQWyg5AkU0gh38o6yCQ9g8Mmv/a/4Q5CCT/CysAHAAtmtU/3TKiUpH/RbP6p1tGVJW2N/tn9n/bWz53afHJOzf86fLyRnNwqFp5584N/wQGsHPnzjhL840GrfZPZeR/e3XkP6yS/8VxBKhCQ64I46w+s9l5myHv0XMN8WnW0gfjqj4KgMJOgm5aK1ulVW/4pf/so2tyfGr/wHD5b5VGbzYdXfK/hgLAAdCYYr5UlBwZlv6lj1JmJ/9j8soiPqO08h0AB0DDfia0tXit4iz95xpj2j/1kf9x81/7n57NNcbkf3COABUj8ktF4ZFh6V/HWIUSeU1RCmO1FAqAeppAVuGVCbv0n3Gkaf/AcPmv/c8gZhxp8r/IAsAB0IDiv1SUHxmW/jWNWNYl/wPyaqIsRmydOwAOgMZsAll/16GUpX/78WaGKJH8D5r/2v8MqP14k/8ROAJUgyCr/yCXUahSlv6rPN0QgdU/wzPq8n4TMAN/MWQ1Ru8gBnyQy1r3d0L7BxLmP8j/OOwAFC9UI3bTizHJFd31jzz2ICGNWMZi7NVWAHgHWObuOIMpfenfhvZPWPJ/RPKfDOR/qTsAEiqagC1YmwCplv4BRyA9kf/RaMEyLiOwaI4AxWKKrVhlS/9mtH9gI/Kfusn/UBQAdM8mwBqW/gBAHAqAgptATl9kWPrHbwrOPg61f6Cz/Hf6ggBmH4fyP3QB4B1gdMUmQCdL//irf6oh/wHymGMHwFpkMLM81Nr/kdf92Zb+s4xG7Z+ilTUg689/7X/CmGU0yv+AHAGiL9k2ATo56F/c0h8AKI5vAi6S9n8onbzBt/R1/9LSkjc6wwC0/4lmacdRO3dfNfZVMB87ABFV0xqvfhNA1392jpjDLEpPRZgk/0PvAHh6YHa6/tRE/gOkMusOgJVKHGWd/6lvE0DXv46RyezqG6vlcv6HmIzM4ngPQDjFLYjz0PVvaXFx0WdBwBTyn1rJ/2i8B4DeVbAJoOsPAFTDDkBhnLIYmK7/XHwWEPTHKQsi81lAZbEDEEv8XnieTQBd/z54sykUFIPQIfkfih0AWEvXHwCofwdgellmKRNE0ed/itgEaN/1X2n5Z37JFD1Kc5L/RXD+h/iM0oLYAYBuWCcBAEXwHoBAIrTAe1XEJkADyVv+83IMFKpJP5iL/I9DAVAMJysCsvRfl7EK3XKyglIYq6VQADCoajYBLP0BgEJ5DwDMx7ofACiaHYAoSul8Z94E0PXvimOgUEToQefkfxAKgDI4VD0uS/95GbHQFYeqKYsRW0wB4EOgGVhBmwCW/tRN/gMk5D0AsD5LHwCgSo4AhRCn4T2YyJsAuv4DcAwU0uY/ycn/CBQABXCcejCW/h0ybqE9x6kpkXEbnwKA0UTeBAAAqJUCAAAAElEAMCabAAAAA1MAAABAIgqA8SVvctsESMsHQYB8Iyf5PzoFQHQ+SoVyGb3Qho9SoVxGb3AKAMZnEwAAYDAKAAAASGTb9GNYvhSJYdgEgOHJf4Cc7AAAAEAiCgCisAkAADAABQAAACSiABiZrva+bAJk46OgyUygkZn8H5cCIDQfo07pjGFoxseoUzpjODIFALHYBAAA6JUCAAAAElEAEI5NAACA/igAAAAgke3Tf6zVOq6dOz3+g45MAx5WeTmMa+fuq8a+BCBrAQAEp0oEaE/FRSqOAAEAQCIKAAAASEQBAAAAiSgAAAAgEQUAAAAkogAAAIBEFAAAAJCIAgAAABLZ5IvAls9dGupKkpr+XZtLS0tFfwtVwPEz/QFvfMG+M5X6BHz95sr/HUcNeC1Z+LYvWOGbgGEg8cu5nviuYqAIiq7OqbjCcgQIOqBXCgCUQgEAA9EIBwAiUABAN2wCAABFUADAcGwCAACjUwCEZr1YFpsAk4xhaMa7JymdMRyZAmBklozZWBDva3l5eexLgNHIfzKT/+NSAECXzOgAQHAKABiaTQAAYEQKAOiYTQAAIDIFAIzAJgAAMBYFAHTPJgAAEJYCAMZhEwAAGIUCIDrLxELZBDB6oSUfo065jN7gFADjs1JMK/n62IdAg/wnJ/k/OgUA9MXUDgAEpACAMSXfBAAAhqcAgB7ZBAAAotk+9gXAQBafHLTXvnPnzqUldQIAMBA7AAVwSqSlxSfvHHH1n3YTwLiF9nyUCiUybuNTAISQdo1Y99J/dgnXyj4CAlbIf7KR/xEoAKhTqKW/CR4AiMN7AKhNnHX/XLwTAAAYhh2AMiQ8IlJ61z/5JoARC11xnJqyGLFFUABEkW2BmGfpP7s8i2YHQGFf8p885H8QCgDKVtDS3xwPAETgPQCUqpR1/1y8EwAA6JsdgGLkOR9SU9c/5yaAsQrdcqiaUhirpVAABJJkdZhz6T+76lfPDoDCJPlPBvI/DgUAWZb+S7fZMjbTPAAwLgVASarvDde99E/yRBd98RCWkxXEZ5QWxJuAiav9aZ+Y6/7lc5eqP8gEAIRlByAW50M6POsfc/WfvI/uAChsRP5TN/kfigKgMLWuCztf+gdf/dc601c/PmFEzlcQmfFZFkeAiKKTUzHB1/1z8Z0AAEAf7ACEU2tveIokXf81Ej7R9n9huoSxQBLyPxoFQHlqOmWRc+lf63Nd1tVCiZyyICYjsziOADEOB358HBAAMAo7ABHVvQus65+zrW7/F2ZRd/6Tk/wPSAFQpEIXhZb+FU/2hY5JKI6zFkRjTJZIARBRfcdCLP3bqGNtvbi4OPYlQAHqy3+Q/wEpAEpVyqLQ0j/DJkApoxHqoOFKHEZjoRQA4dTU/rH070odK2xNIMiT/7Av+R+NAqBgdSwKN5Jq6V/0JkDd4xBi0nYlAuOwXAqAWLR/si39s62zNYFgI/Kfusn/UBQABJJ56V/0JgAAUBAFQNntnzq6wsmX/kU/3Q0uSRMIusl/py8YVYMRKP/jUAAwMkv/VTYBAIABKACKP/0ZsCs8I0v/0p/uxhejCQTd5L9NAEbSeOzJ/yC2j30BZBR23e9NeABA9ewAFLDu3LRcDtUVLnf1X4ogT3fLy9AEgm7y3yYAg2s56uR/BAqASgRZFE7nzE81ihhvkIQagCEZb3VQAJTR/im9XLb0z7b+XrzNpv/NUJcDQWXIf7KR/0VQANQj5qLQ0r8+MUcaZKYpyzCMtGooAIo5/VlcuWzpn3YVvjpWNYEgZ/6TlvwvhQKgKkEWhZb+FQsyxoA1tGbpmzFWEwVASR/+EL9ctvQfUsy1+JpRqgkESfIf5H9BFACFCfuRoJb+GWw6uqQ59MdHgjKiTUeX/C+LAqDUz36OUwNY+o9oyOe6v+/9NW2QTY/5rwagqO/9lf9j8U3A5VlcXFxeXt4SQ3FL/6WlpekL2eL+ojjkOKTKf1gl/4tjB6C29k/k0+GUq+/v/TV5kEfv+W8TgKK+91f+j0IBUKRZXi1qALoyy1iS4BAo/9UAdGSWsST/S6QAKLX94/VGHLOMRk0gkP/UR/4XSgFQM5sAtGcUQYlsAtCeUVQxBUDBpz8dBKKswz+aQCQ3dP5bvRHm8I/8j0YBUD81AM0YOVA6NQDNGDnVUwCU/eEPKmbGNe8I1AQiLflPZeR/0RQAxXMQiD745B+Iz0Eg+uCTfzJQAETR5rWkBqCg1b9pA4bOfzUAMVb/8j8OBUCU/d8BqAEoYpyYIajP+PmvBqCEcSL/B6MACKH9iPeaYUgtx5vhCqvkP2WR/3VQANTT/nEQiGqO/pshqEmU/B+7uUtwQY7+y/9hKADG1+FYVwNQyupfxMMI+a8GIMDqX/5HoABIcfpzDTUA8UeFGYI6hMt/NQDhR4X8H4ACoLZRPuMvjLbaY1wzjoduh6uIJ7nR8j/Yao9xzTge5H9lFAC9G779owYg/uo/5j1ClvxXAzDe6j/mPWajABhTf+NbDUARq38RT1rj578aIL1xV//yf1wKgGpPf6oBKLf3H+Guof78VwMkFrb3H+GuM1AAjCbOyFYD5BTkeY/zQoCEw14NkFOQ5z3OCyEhBUDNH/4w+0sryFqQwcz+jI8e0KNfAFSe/zHWggxm9md89Pgd/QIqpgCofEyrAYi/+hfxpBIx/9UAaURb/cv/sSgAqm3/rFIDEHn1X9aVQLX5rwZIINrqv6wrqYwCYASRP05LDVC3sKt/EU8SofNfDVC1sKt/+T8KBUDl7Z9VagDCrv4LvSSoMP/VAJUKu/ov9JIqoAAYWhGfqKUGqE/81b+Ip3pl5L8aoDrxV//yf3gKgEHbP6MPcTVATvFX/7Pc++gvH8iS/2qAisRf/c9y76O/fOqjAEhnrhpAGVC6uZ5ECQt1m6sGUAaUbq4nUf5nowBI1P5pdiVqgHLN9dwFGZ+aQJSrwvxXAxRrrucuyPiU/0NSACSlBqheiat/YABqgOqVuPpnYAqAdO2fxjWAMqAU8z5Z0QanJhAlqjn/HQcqx7xPVrTBKf8HowBIbd7XkhogvnmfI3kKOc2d/2qA8OZ9juR/ZgqApO2fVWqAmlSz+tcEoixZ8l8NEFg1q3/5P4ztA90Pga28nJaXl+daZS4tLfV8XWRc+gOh8/+2VebSjqN6vi4yLv0Zkh2A1O2ffdkKKFeVq39NIEqRMf9tBYRR5epf/g9AAUCrGkAZMK4GT4HoBDqpAZQB42rwFMh/VikAOlBB+6fNBasBxtLgkS9rQGoCEV/2/FcDjKTBI1/WgJT/ffMeANoeCfWugOFVv/QHisl/7woYVvVLf4ZhB6Ctmto/7bcC7Ab0rdmDXO5Q1AQiMvm/yomgATR7kMsdivK/VwoAOn51KQN60viBlZLAQPmvDOhH4wdW/rMRBUArtbZ/Vi3epsE/VAN0q/HSv4JxqAlETPJ/I2qAbjVe+lcwDuV/fxQAbM5WwIg0/oER2QoYkcY//VEANFd9+6eTv0gZ0Fibh66yEagJRDTyfxbKgMbaPHSVjUD53xOfAkSPnw6xanUh65OCNtWyXpKGQKz8//8LWZ8UtKmW9ZL8Z3Z2ABpK1f7p8FihDYH+Hpw6TnxuRBOIOOR/MzYE+ntw5D/zUgDQRMvXmzKg8wdEAgJl5L8yoOsHRP7TwNbp42b5XAc21pG2/TOp2Y7wGgOfC5q+1B7yYjqpglINuenjrZPRmIr8b0D+d5z/w54Lmr7UHvJiOqmCUg05+d8t7wFgtIOhad8h0NXuR6roB+rM/2TvEOhq90P+05IjQHPT/unvD185CVPr6aBu/7qcg81JUMYl/3vM/9tOwtR6Oqjbvy7nYJP/3bIDQKBWUJV7Ap3XM2IOqDn/K9oT6Lyekf90RQHQGS/LzqeBNavngoqBnjYxjLGVB8FZT6Lx2uwl//dZPRdUDPS0iWGMyf9uKQA62/9lRX8vzuDFQK0nl8pieqA/8n/M/I9dDNR6cqks8n8uCoBuKM0Hfg/+5Go71EcJ9foIG2xSnlC8JIfO/4nVdqiPEuqJ/F8h/7uiAJiD9s9GIrwaN1qRtywMAvb1TQPTmR7og/zfSISX20Yr8paFQcC+vvyfTv7PTgHQgcwvxfivtHlX8AFX/OtKPg1IeYJI+xosI//nXMEHXPGvS/7HH3vx+RjQWWn/rLF8m7GvIjvPwrrSzov0RP6vIXki8CysS/7PyA5AWwmHWvvEWf2GUdNqJ72cnN0gTSBGl+1FJ/87J/+bkf/tbfVV8LPw5S+dR/8aCWeCdR/M9sPJgJzxp2w6WuT/Cvm/Qv53SP63J/9bsgPQSp4XW3/Rv+an1c8Es2SWbtCMNIEYUZJXmfzvkPzvkPxvyQ7A5pK3f/qO/imqmQyaPYa6QbPQBGpD/m9K/rf9DfJf/vdG/rdhB6C56l9dI0b/5D8vbjLo4NH7/7+h8UjL0A3SBGIUdb+s5H9L8n8Y8r8NOwCbyNn+GT36pws7GfSaRC3HW9rhanqYQv5PJ/8b/gb53zX5vxH535gdgIZqfTkFj/6N7mKUKWHgZGnZzqm4G6QJxMCqfB3J//kuQ/7HIP8bswMwTar2TxHRP69OJoaA4aIbtIYmUDPyfwr5P99viDda5H8f/zwg+d+MHYAmKnv9VBn9zXpFpSSFbtAamkAMpqYXjvz/Z/99IRki/9eQ/80oAMo7aNihiqM/A9PAjEwPzEv+z/Qb5P945P+M5P9GFABzq+MFI/qrYRpYIeUZQAWvFPlfE/m/Qv43oABI1/5p+SKR+zGZBqYzPTA7+b/hP5f/Icn/6eT/uhQA8yn6FSL6q5d8GpDy9Krcl4b8z0D+y/+5KABStH9EfyrJp4GNmB6Yhfxf+8/lf1Hk/7rk/yQFwBxKfEmI/rRyTgNSnp4U91qQ/5nJfzalAKi2/SP6STsNbMT0wHTy/x//ufyvgvzfl/xfQwEwq4JeA6KfzNOAlKdzpQx++c8k+c+6FABVtX9EP1OkmgY2YnpgI/K/u2shHPkv/9dQAMwk/qAX/cwowzQg5elQ8NEu/5md/GeVAqD49o/op4EM08BGTA9Mkv/kIf+3oACYRdhRLvppqeJpQMrTiZjDW/7TnvxPTgFQZPtH9NOhiqeBjZge2Jf8Jy35n5YCYBPRhrXopyf1TQNSnpZCjWf5T3/kf0IKgGLaP6KfIYdZsygPOA1sxPTACvkPK+R/KgqAaYKMY9HP8NpEeZxpQMrTWIQBLP8ZhfzPQAEQuv0j+hlXHdPARkwPyH/YiPyvmwJgQ+MOXNFPHEVPA1KeBuQ/rJD/tcpeAARs/4h+Yip6GtiI6SEz+Q8zkv/1yV4AbGSUkSr6ia/EaSB5yjMv+Q/rkv81SV0AxGn/iH7KUuI0sBHTQ07yH5qR/3VIXQBsZMihKfopV0HTQOaUZy7yH2Yh/0uXtwAYvf0j+qlDQdPARkwP2ch/6IT8L1feAmAjA4xF0U994k8DaVOe2cl/aED+l0gBMLQ2Q1D0U/c0MHorCHol/6mY/C9L0gJgo/3fXsef6CeJxtNA362gKU0g/aE85D/0R/6XImkBMLDGA0vuU66w0wAMSf6TkPyPL2MBMGT7R/STXLRpQBMoOfkPg5H/kWUsAIYh+iHsNAC9kv+wSv7HlK4AGKD9I/oh8jSgCZSW/IexyP9o0hUAvRL9UMo0AN2S/7Ap+R9HrgKgv/aP6IeCpgFNoITkPwQh/yPIVQD0QfRDY7pBFE3+Q2Pyf1yJCoDO2z+iH8qdBjSBUpH/EJP8H0uiAqBDoh/6e1nNG+i6QQxJ/kPn5P/wshQAXbV/RD/0rVmgN/hXmkBJyH8ohfwfTJYCoD3RD1VOA7Ap+Q9Dkv8DSFEAtGz/iH6odRrQBKqe/IdCyf9epSgAGhP9EIFuEMOT/xCB/O9J/QVAs/aP6Ick00DyJlDd5D/UQf53rv4CYF6iHyLTDaI/8h8ik/8dqrwAmKv9I/oh5zSQuQlUMfkPVZL/nai8AJiR6IcS6QbRnvyHEsn/lrYnb/+IfihdJ9NA2iZQreQ/ZCD/G6u5AJhO9ENNdIOYnfyHmsj/BrYnbP+IfqhVy2kgYROoSvIfEpL/c6m2ANhIs2dR9EOSaYCKyX+onvxPXQBs1P5pQPRDobrd3q21CVQf+Q/I/6QFQCdEP1Qg+SlPmpH/UAH5n6sAaN/+Ef1QmU6mgSqbQJWR/8Aa8j9LAdCY3Ie66QaxEfkPdZP/lRcAzdo/oh/yaDMN1NcEqon8B6aT/9UWAPMS/ZCTbhDyH3Jalv+VFQBztX9EP7Dazpl9JqisCVQN+Q/MZTl3/ldVAMxI9ANraAglIf+BNXLm//ZU7R/RD7SfBmpqAtVB/gMtLSfL/3oKgOlEPzCjnN2gisl/YEbLafJ/e/XtH9EPdD4NVNMEqoD8B7q1nCD/KykA1iX6gZbydIMqI/+Blparzv/tVbZ/RD/Q9zRQRxOodPIf6NVypflfQwGwL9EP9KTublAF5D/Qk+Xq8n97Ne0f0Q8MPA1U0AQqmvwHhrRcUf4XXwCIfmB49XWDCiX/gYEtV5H/27YUTvoDYym6/VMB+Q+MZbnw/C++AAAAAGanAAAAgEQUAAAAkIgCAAAAElEAAABAIgoAAABIRAEAAACJKAAAACARBQAAACSiAAAAgEQUAAAAkIgCAAAAElEAAABAIgoAAABIRAEAAACJKAAAACARBQAAACSiAAAAgEQUAAAAkIgCAAAAElEAAABAIgoAAABIRAEAAACJKAAAACARBQAAACSiAAAAgEQUAAAAkIgCAAAAElEAAABAIgoAAABIRAEAAACJKAAAACARBQAAACSiAAAAgEQUAAAAkIgCAAAAElEAAABAIgoAAABIRAEAAACJKAAAACARBQAAACSiAAAAgEQUAAAAkIgCAAAAElEAAABAIgoAAABIRAEAAACJKAAAACARBQAAACSiAAAAgEQUAAAAkIgCAAAAElEAAABAItun/3jxyTuHuhIAApH/ALWyAwAAAIkoAAAAIBEFAAAAJKIAAACARBQAAACQiAIAAAASUQAAAEAiCgAAAEhk6969e8e+BgAAYCB2AAAAIBEFAAAAJKIAAACARBQAAACQiAIAAAASUQAAAEAiCgAAAEhEAQAAAIkoAAAAIBEFAAAAJKIAAACARBQAAACQiAIAAAASUQAAAEAiCgAAAEhEAQAAAIkoAAAAIBEFAAAAJKIAAACARBQAAACQiAIAAAASUQAAAEAiCgAAAEhEAQAAAIkoAAAAIBEFAAAAJKIAAACARBQAAACQiAIAAAASUQAAAEAi28e+ABjOnj17Lrrooo985COf//znL7300ssuu+zaa6+97rrrbr311oMOOuiQQw459thjjz/++JNPPvk+97nP6aeffuKJJ459yQAAHdu6d+/ern8nxLJnz553vOMdr3vd684///wbb7xx9n9497vf/YlPfOLTnva0u9/97n1eIABze+Mb3zjXf79169Zt27btt99+Bx544EEHHXTYYYfd4Q53OOaYYw466KDerhGCUgBQs+uvv/6Vr3zly172squuuqrN7znrrLNe/OIX3/e+9+3u0gBoZevWrZ38nhNOOOGUU0653/3u95CHPOTBD37woYce2smvhcgUAFTrjW9846/92q99+9vf7uS3bdu27dnPfvZLX/pScwNATQXAvg488MBHPOIRT3nKUx7/+Mfvv//+nf9+CEIBQIW++93vPv3pT3/b297W+W++xz3u8ba3ve0e97hH578ZgNELgFXHH3/8c5/73F/5lV9xQIgqKQCozec+97mzzjpr165dU/6bH/3RH73//e9/8skn3/GOd7z97W9/ww03fO9739u9e/cll1zysY99bPfu3VP+7eGHH/6+973vAQ94QA/XDkCIAmDFne50p9/93d89++yz+74jGJgCgKp89KMffeQjH3nNNdes+9MTTjjhl37pl57ylKfc5S532eg37N2795JLLvk//+f/vO51r7v22mvX/W8OP/zwCy644H73u193Fw5AuAJgxeLi4qte9aojjzxymLuDASgAqMff/M3fPOxhD1t39X/YYYe98IUv/NVf/dXZz3ReffXVL3rRi17+8pev+xo54YQTPv7xjx977LGtrxqAzgqA6auaH/7wh7fccsv1119/7bXXXnXVVV/96lf/7u/+7hOf+MRf/uVfbtQ5WnHXu971Xe9610knndTFhcP4FABU4stf/vKP//iPf+9735v80Y//+I8vLS01+1D/888//6lPfeq67yQ+44wz/uIv/qLRxQIwQgGwkZtuuukDH/jAH/3RH73jHe+49dZb1/1vduzY8Z73vMf5T+qgAKAG119//WmnnfbpT3968kePfexjl5aWDjjggMa//LOf/exDHvKQdUuLV7/61c94xjMa/2YAIhQAqy655JL/8B/+w0bNnSOOOOKCCy7wkdBUQAFADZ7+9Kf/yZ/8yeTtZ5111nnnnbd9e9tvvP7EJz7xr/7Vv9qzZ8+a24855phLL730kEMOafn7AYhQAKz4oz/6o+c+97k33XTT5I+OPfbYT37yk85/UrptY18AtHX++eevu/q/z33uc84557Rf/a8cInrhC184efsVV1zxqle9qv3vByCOZz3rWR/4wAcOP/zwyR9961vf2rlz5y233DLGdUFn7ABQtj179px88slf+cpX1tx+8MEHf+pTn7r73e/e1R3dfPPN97///S+55JI1t9/1rnf90pe+tG2bWhqgkh2AFR/72Md++qd/+vrrr5/80e/93u8973nP6+qOYHhWLZTtVa961eTqf8uWLS95yUs6XP1v2bJl//33f9GLXjR5+5e//OWPfvSjHd4RABE86EEPes1rXrPuj170ohdddtllg18RdEYBQMFuuOGG3/md35m8/aSTTnrOc57T+d097nGPO+GEEyZvf+tb39r5fQEwurPPPvvJT37y5O3XXnvturMPlEIBQMH+/M///Iorrpi8/b/+1/+63377dX53++2337Oe9azJ2y+88MLO7wuACP7bf/tvBx100OTtr3nNa9adgKAICgAK9upXv3ryxoWFhcc97nE93eNjHvOYyRs/85nPXHfddT3dIwAjutOd7vQf/+N/nLz9xhtvfO1rXzvGFUEHFACU6rOf/ewnPvGJyduf/exn9/eW3Pvc5z5HHXXUmhtvueWWL3zhCz3dIwDj+nf/7t8deOCBk7e//vWvH+NyoAMKAEr1tre9bfLGrVu3nn322f3d6datWx/2sIdN3v6lL32pvzsFYESHH374utu/f3+bMa4I2urgI9JhFO9+97snbzzttNOOO+64Xu/37LPPnvyYudvf/va93ikAI/q5n/u58847b/L2888//+STTx7jiqAV3wNAka699tojjjhi8qtYXvjCF/7Wb/3WSBcFQD3fA7Cvm266aceOHZPfCfD4xz/+LW95Sx/3CL1yBIgiXXzxxet+EeNDHvKQMS4HgJodcMAB97rXvSZv/9SnPjXG5UBbCgCK9Ld/+7fr3n7qqacOfi0A1G/d+eWrX/3qD37wgzEuB1pRAFCkz33uc5M3HnPMMXe4wx3GuBwAMhYAe/fu3bVr1xiXA60oACjSN77xjckb73rXu45xLQDU75RTTln39m9+85uDXwu0pQCgngLg2GOPHeNaAKjfEUccse7t3/rWtwa/FmhLAUCRvvOd70zeOPkVXQDQicMOO2zd26+55prBrwXaUgBQpMnPYtuyZctBBx00xrUAUL/DDz983dtvuOGGwa8F2lIAUKQbb7xx8sbb3e52Y1wLAPXbaAdgz549g18LtKUAoEg//OEPJ2/0rXYA9GTdL5/ZsmXL/vvvP/i1QFsKAIp04IEHzrgtAADtbdTpt/lMiRQAFGnd4/7rvjEAANrb6Au/Dj744MGvBdpSAFCk29/+9pM3XnXVVWNcCwD1+/a3v73u7cccc8zg1wJtKQAo0nHHHTd54xVXXDHGtQBQv40+7//4448f/FqgLQUARVo3cL/85S+PcS0A1O+LX/ziurff+c53HvxaoC0FAEW6y13uMnnjt7/97e9973tjXA4Alfv85z8/eeNRRx3lCBAlUgBQpHvf+97r3v7pT3968GsBoH4XXXTR5I33uc99xrgWaEsBQJE2ytwPf/jDg18LAJW7+uqrP/vZz07eftppp41xOdDW9ta/AUZwyimnHH744VdfffWa2y+88ML/8l/+S693/W//7b9d83mjBxxwwOtf//pe7xSAEb3nPe9Z94vAzjjjjDEuB9ra6stTKdQTnvCEt771rWtu3G+//a644oo73vGOPd3prl277na3u6258cQTT/zKV77S0z0CsK6tW7dO3tjTqmZxcfHNb37zmhuPOOKIK6+80jcBUyJHgCjVIx7xiMkbb7nllvPOO6+/O33/+98/eeNkSQBANa688sq3ve1tk7c/6UlPsvqnUAoASvWEJzxh3eT9wz/8w/7u9Pzzz5+88V73uld/9wjAuF7xilfcfPPNk7f/wi/8whiXAx1QAFCqO97xjo985CMnb//0pz994YUX9nGPN9xwwwc+8IHJ208//fQ+7g6A0X33u9/9gz/4g8nbH/CABzzoQQ8a44qgAwoACvasZz1r3dv/83/+z33c3TnnnPP9739/zY3777//Qx/60D7uDoDRPf/5z7/mmmsmb/9P/+k/jXE50A0FAAV71KMedeqpp07e/rGPfexNb3pT53f3yle+cvLGhz3sYUceeWTn9wXA6N71rnf96Z/+6eTtp59++plnnjnGFUE3FACU7Td+4zfWvf1XfuVXvvOd73R4R29+85svvvjiydt/8Rd/scN7ASCISy+99Od//ucnb99vv/1e+cpXrvsZRFAKBQBl+9mf/dl1T+BcddVVP//zP3/rrbd2ci/f//73n/vc507evrCw8NjHPraTuwAgjssuu+yMM87YvXv35I9e8IIX+AJgSqcAoHiveMUr1v04oPe+973Pf/7z2//+vXv3/vIv//K3vvWtyR+99KUv3W+//drfBQBxXHLJJaeddtpXv/rVyR/95E/+5Itf/OIxLgq6pACgeKeccspLX/rSdX/0P/7H/3jBC17Q8vc/5znPeeMb3zh5+0//9E8vLi62/OUAxLF3795XvepVD3zgA7/xjW9M/nRhYWFpaUnfhwr4JmBqsHfv3rPOOuud73znuj89++yz//iP//iQQw6Z99ded911v/qrv/qa17xm8kc7duz4zGc+c8IJJzS6XgDCfRPwBRdc8IIXvODjH//4uj89+uijP/KRjywsLDT+/RCHAoBKXHPNNT/1Uz+17vt0V9o2v//7v/+Yxzxm9l/4oQ996OlPf/qll146+aPt27e/973vfdjDHtbiegEIUQB84QtfePvb3/5nf/Znl1xyyUb/zYknnvj+97/f975TDQUA9bjyyisf/OAHf+lLX9roP3jAAx7w3Oc+98wzz7z97W+/0X9zzTXXvPOd73z5y1/+13/91+v+B9u2bXvta1+77kdDADBuAXDuuedO+Se33HLLTTfddN111+3evfuKK6649NJL//Zv/3bTj4x70IMedN555x177LGtLxmiUABQlSuvvPKss87aaO2+4oADDnjgAx94r3vd6253u9vhhx++//77777NN7/5zYsuuuiSSy6Z8tlB+++//2tf+9qnPOUp/Vw+ALMa4IM4t23b9rznPe8lL3nJuh81AeVSAFCbG2644Zd+6Zde//rXd/6bjz766PPOO+/000/v/DcDEK0A+Imf+In//b//9/3vf/9e7wVG4VOAqM1BBx30ute97q1vfesxxxzT4a/9uZ/7uc9+9rNW/wDVO+20097+9rf/9V//tdU/tbIDQLWuu+66V7ziFS972cu++93vtvk9D3/4w3/zN3/zgQ98YHeXBkC4HYBTTjnlsY997FOf+tRTTjml298M0SgAqNwNN9zw1re+9XWve92FF1548803z/4Pf/RHf/Txj3/80572tHvc4x59XiAAAxUA27Zt2759++1ud7tDDjnkiCOOOOqoo+50pzuddNJJ97znPU877bSjjz66nyuFcBQAZHHdddd99KMf/chHPvKFL3zh0ksv/da3vnXttdded911e/fuPeiggw455JBjjz32hBNOOOmkk0499dTTTz/9xBNPHPuSAQC6pwAAAIBEvAkYAAASUQAAAEAiCgAAAEhEAQAAAIkoAAAAIBEFAAAAJKIAAACARBQAAACQiAIAAAASUQAAAEAiW8e+AOjY4uJif798eXm5v18OQBvyH2akAKAkvYZ7V0wSAJ2T/9AhBQARFRH08zIxAGxK/sMAFACMrMqsn51ZAUhL/o99CeSlAGBoyRN/OvMBUDH5P4X8Z0gKAHon8RszHwBFk/+NyX96pQCgexK/J+YDIDj53xP5T7cUAHRD6A/MZAAEIf8HJv9pTwFAc0I/CJMBMDD5H4T8pxkFAPMR+sGZDICeyP/g5D+zUwBQW+4vLO2Y8tNdO3c3/reb/vNQzARAJ+T/LP88FPnPphQAlJT7mwb0plpOAO3vYnhmAqAB+d/5XQxP/rMRBQARQ7+TIB5rAmh218MwGQBTyP9R7noY8p99KQAYP/d7jd04E0CoKcFMAKyS//KfbBQAjBD9A+ds2Alg9PnANADJyf9V8p9UFAB5DZn74wZrKRPAiPOBmQBSkf+Rr1P+MwAFQDrD5H6oJC10AhhlPjATQMXkf4mXLf/pgwIgiwFyP3J6VjABDDwZmAmgGvJ/hfyfkfzPQAFQv16jv5TErGwCGGwyMA1A0eT/vuT/XOR/3RQANesv+ksMylongAFmAtMAFEf+T5L/Dcj/WikAKtRT7hcdjhkmgAEmAzMBBCf/p5D/bcj/yigAqtJH9FeTiakmgF5nAtMABCT/NyX/25P/1VAAVKLz6K8vCnNOAP3NBKYBCEL+z0j+d0X+V0ABUDa5P6+0E8AqMwHUQf7PS/7Lf1YpAErVbfRnCL4VJoCeZgLTAAxG/jcj/1fJfxQAqaM/Vd6tMAH0OhOYBqBX8r8N+T9J/qelACiJ6G/PBLAR0wBEJv/bk/8bkf8JKQByRX/mgFthAhhsJjANQCfkf1fk/6bkfx4KgOhEf7dMADMyDcDo5H+35P+M5H8GCoDKo1+irWECGGUmMA3AXOR/H+T/vOR/xRQAEYn+/pgAmjENwDDkf3/kfzPyv0oKgFhEf99MAG2YBqA/8r9v8r8N+V+ZbWNfAF2m/8LSDhFGfzoZYJ1/exFUQP4TnPyvjB2AEFq+JIT+7HSA4jSEtIJA/g9J/ndI/pdOATAy0T8wE0DnTAPQjPwfmPzvnPwvlwJgNKJ/FCaAnpgGYHbyfxTyvyfyv0TeA1Be+jvoSUAth6WDoeQh/6mM/C+RHYDCor/Ta8lIByh4N0griIrJ/3HJ/wHI/1IoAIYj+iMwAQzGNACr5H8E8n8w8j8+R4Cip78NXwrVZujaEaYm8p9s5H98dgB6p/ETig7Q8LSCSEv+hyL/hyf/w7ID0C+NH9AKIif5D/I/LDsAEaO/62vhn+gAFdoN0gqiIPI/Jvk/Lvkfih2AQOmv60P1Gg9yrSBKIf9hXfI/FDsAHdP4CU4HKAitIOoj/4OT/0HI/wjsAHRJ4wdmpBVEZeQ/zEj+R2AHYOTo7+FamEYHqJpukFYQQcj/Usj/gOT/WOwAdED6QxtaQZRL/kMb8n8sCoC2GoxCe77QyYvCHMC45D+0J/9H4QhQcxo/JbIFHJztYIog/0sk/4OT/0OyA9CQxg/0QSuI+OQ/9EH+D0kB0MS8o030Q98vGXMAw5D/0Cv5PwxHgIZo/PRzLTRhC7j6HWHbwfRE/pdO/pdF/vfKDsAcpD8MzHYwQch/GJj875UCYFa2fWEUtoMZnfyHUcj//jgCtDmNn5rYAi6X7WCGJ/9rIv/LJf87ZwdgExo/EIRWEAOT/xCE/O+cAqDj9O/tWoB/YA5gGPIfopH/HVIAbEj6Q0zmAPom/yEm+d8V7wFYh+ivmDOgmU+FOhLKpuR/xeR/TeR/S3YA1pL+UAqtILol/6EU8r8lBcA/I/2hLOYAuiL/oSzyvw0FQMOR4dMeIIh5X4zmACbJfyiR/G9MAdAw/fu8FmBu5gAak/9QNPnfgALgH0h/qIA5gAbkP1RA/s8r+6cAif5sfApEBnN9OoSPhkhL/mcj/zOQ/zNKvQMg/aFKWkFsSv5DleT/jPIWANIfKmYOYAr5DxWT/7NIWgBIf6ieOYB1yX+onvzfVMYCQPpDEuYA1pD/kIT8ny5dASD9IRVzAKvkP6Qi/6fIVQDM/uz6nheoxlwv52xzQB7yHxKS/xtJVADMlf49XwswNHNAZvIfMpP/eQsA6Q+YA3KS/4D8z1gASH9ghTkgG/kPrJD/uQoA6Q/syxyQh/wH9iX/sxQA0h+YZA7IQP4Dk+R//QWA9Ac2Yg6om/wHNrIg/ysuAKQ/MJ05oFbyH5huIX3+11kASH9gFuaA+sh/YBYLufO/wgJA+gOzSz4HVEb+A7NbSJz/tRUA0h+YV+Y5oCbyH5jXQtb8r6oAkP5AM2nngGrIf6CZhZT5X08BIP2BNnLOAXWQ/0AbC/nyv5ICQPoD7SWcAyog/4H2FpLlfw0FgPQHupJtDiid/Ae6spAp/2soAGYk/YFZyIr6eE6BWSykyYriC4AZi7A8zyjQ3oyJUUETqGjyH+jcQo78L7sAkP5AT5LMAeWS/0BPFhLkf8EFgPQHepVhDiiU/Ad6tVB7/pdaAEh/YADVzwElkv/AABaqzv8iCwDpDwym7jmgOPIfGMxCvflfXgEg/YGBVTwHlEX+AwNbqDT/yysAZiH9gW5JlVJ4poBuLdSYKoUVAMUVWEAqMqo/HlsgssWiMqqkAsDmLzCiWjeCiyD/gREtVJf/xRQA0h8YXX1zQBHkPzC6hbryv4wCQPoDQVQ2B8Qn/4EgFirK/zIKgFlIf2AY0iYazwgwjIVa0qaAAmCWQqqa5wMowiyZU0QTKDj5D0SzUEX+Ry8ApD8QUx1zQGTyH4hpofz8D10ABH/sADYlx5rxuAGlWwycY6ELgFlo/wBjkT/j8vgDY1koPH/iFgA2f4H4KtgIDkj+A/EtlJz/QQsA6Q+Uoug5ICD5D5Riodj8j1gAxHykANqQbLPwKAH1WYyXbBELgFlo/wBxSKQhebSBOBbKTKRwBYDNX6BE5W4ExyH/gRItFJj/sQoA6Q+Uq8Q5IA75D5RrobT8D1QAhHpcAHoi6yZ5TIAMFsNkXaACYBbaP0BkMqo/HlsgsoWiMipKAWDzF6hDcRvBo5P/QB0Wysn/EAWA9AdqUtAcMDr5D9RkoZD8D1EAAAAAWQoA7R+gPqU0gcYl/4H6LJSQ/yMXANIfqFURc8CI5D9Qq4Xw+T/+DgAAAJCiAND+AeoWvwk0FvkP1G0hdv6PVgBIfyCD4HPAKOQ/kMFC4PyPewRI+gN1kGbz8ogBdViImmbjFADZ2l0A0+VJxTx/KUDYVByhALD5C2QTeSN4SPIfyGYhZP7HPQIEAAAUXwBo/wA5xWwCDUn+AzktxMv/cDsA0h+olXybzuMD1GohWL4NWgDU3dwCaK/WnKz17wIoMSeHKwBs/gIE3AgegPwHWIiU/4GOAEl/IANZN8ljAmSwECbrBioA6mtoAfSnpsys6W/p1q6du8e+BBiN8T9uZkbZAYhTEgH0TeLtK/OjsWvnbssgskk+7BdiJN4QBYD2D0DO5Kzjr+h7HZB8PUQe+w71IOvgtMkZYgfAIACykXsrPA6rlAFUzPCOlnvbRi9iIjwKAMPbNP1Kb5/L/01NPgLWSVRm3SHttb8wdv73WwCUPnsBjKvcFC33yiNQBlABwzhyio58BEgJCGSWOQMz/+0zPg7WTxRq+tD12o/wOPRYAGj/AOTM0hKvOSxlAGWNVcO1iCwdcwdACQiQMwlz/tVtHg3rKiKbfXx67Qd5NPoqALR/AHImallXWxYdVqIxIAtN1NF2AJSAADnzMNvf28djYtXF6BoMQq/9OI9JLwWAj34DKOsj4boi/4ekDGAUBl4F+R/ii8AAILnGpZHVGINpM9gU/6F0XwBo/wDk3ASQ/yNSBtArA6yy/LcDAAAhtC+QrNLoXCeDSvEfTccFgPYPQM5NAPkfhzKAThhIFee/HQAAKGARMO/0b/VGY/MOnumDU/EfUJcFgPYPQM5NAPk/gOXl5cXbzPWvlAH0vfRfXFxcXl7u86KyWBgw/7d39YsAgPYWlnZMX4GtLALmWnKt/EJlGFPMWyjOuBg16irfAdD+Aci5CSD/B7Pvot9uAON2/Vf/p/Z/iflvBwAACtsEWGU3gMYaVIPzrj4Ns8p3ALR/AHJuAsj/ga271rcbQN/P/kZjTPu/0Py3AwAABW8CrLIbQISu/yrjKrIhPgbUCADImZx1/BXRTF/i2w2g767/Ku3/cpOzgwIgzk40QB4RsjfCNVSszSJAGUCvS/9NKf6DZ68jQABQ5HcC9HcoyAKuDr0e+NH+L1rbHQBv/wLI+VZg+T+ATh7DZt1cGwJFG6Xrv8prP37+2wEAgGo3AdrsBniXcImGeZuv9n/qHQDtH4CcmwDyfzDdPpJ2Ayo2btd/ldd+EflvBwAAUmwCrLIbUJkhP9xT+78OPX4MqIwAyJmlJV5zwsez2RLQbkAozZ6O/nYOvfZLeTybFwA+/Q0gguHTWP7H0bIX2/gEiDKg3KV/y9ev9n8ojZ/NvnYAlIAAORO1rKstRa+PqjKgLGMt/TfltV/Qo9qwAND+AYhjyEyW/9F01ZFVBgS38jiPu/TX/g+o2ZPrTcAAQKv3B3uLcK8a11fKdTaydcv8fPobtcaooUvRi4ABmnPyP+wY6GOp13hExRwGJeZ/qKX/9PEQ8wGsxq6u898OAACwDrsBIwq19Kc+3b8J2AseoA/x0zX+FZZuyiPc3/6P9wYMrPHj1uvbfLX/x9X5Izx3AaCyBIip73yW/5kpA9Iu/SnCvAOgxy8CAwAq2ARYpQzIufTX/q9Px+8BMAgA+rOwtCPsKkr+5+G9AR1y1p9R8n++HQCjDSCy/lJa/scx7iZAV7sBYUvZwQTv+q/S/i/FXKOiyx0AgwAg5yaA/E+r8W5A5g0BXX9Gz3/vAQCAwgTZBOikJ51qN6CUrv8q7f9azVEAqDsB4usjq+U/s1AG1LT0p0SzD5XOdgBUgQDDiJa30a4niWibAKuUAV294WH0pb/2f0BdPeyzFgCqT4BSdJvY8p8GlAFt/orRl/6Ua8aR4z0AAFCksJsAycuAOpb+2v916+ZTgIwDgJyfBST/2VSeTwpq86oMsu4nSf7PtANgUAKUpavclv/Bxd8ESLIbUEfXf5X2f9FmGU4dfxMwAECe3QBdf0rUwXsAor0UATKIkL0RroGCNgEq2w2orOu/Svs/vvbPgh0AAGAE5e4G6PpT/w6AkQpQovbpLf9LUeImQKG7AbV2/Vdp/9dh05HWdgfAUADI+VlA8p9UuwG6/tSU/74HAACKV/QmQPDdgOq7/qu0//PYpAAoaNQC0GGGy3/GEqcMyLP0pz7Th1+rHQC1IMC4xsph+R9QHZsAq9qsnlcW7m0qgZb/vMSlv/Z/cdo8KT4FCACo7Y0Bzd4e0H73oMSlPwltbTOIlYMUZ3q4G9KUaNMlS4P1k/yvcjwUvTaNv4lR8cPr9V5f/tsBAADq3w3oT9FLf3Jq/h4A5SBABMOnsfyPrLJ3AgR/Z22062lG+79cjZ8dOwAAQEki7AZUsO4nsw13AIxsgDrMm+fyv3R1bwKM3n2vo+u/Svu/bhuN1YZHgAwIgDiGzGT5TyhDLscrW/pTh2aZ7JuAAaA2STYBBlua17r01/5Py3sAAICy9V3VrP7+KssAElp/B8D4BqjJ7Kku/zOoZhNg+f+r+B77U8dfQbNUb7IDYEsIIJqFpR3tv8R0lnvp+y4oa0ikXblWvyfgxV73i917AAAgnQhr6AYCdt8DXtIsSrxmOuQ9AACQsS+4vLxcSvc6/mq1rA2BTR9P7f/qrbMDUMTYBWAus2S7/Cea4vrrxV0wGUxm+9xHgBSFADH1nc/yv0TTn7XgS9Xgl1folWv/V2neZ80RIAAglsgL6Ln+BLtqxORNwABQs7I2Afo4QrO046ilHUfN8t9s+p+VfiJI+58VdgAAgBC6Wiu3Wcev+bc7d1/V/noKer81SXcADFCAWk1PePlfsSI2AVpexmoLv9sufle/NsKDrP2f2ZqEn28HwMgAyPndT/Kf/rRZHHd+aGeW+2q2LeBdAcTJf+8BAID6hd0EaHzXfRzZH+Cux3qotf/ZlwIAABhHs9XwiEv/Ti4jwnEgklMAAEAK0TYBGtxjkKV/+0sa+NHW/mdaAeBcGkDdNsp5+c/A5l0BB1z6t7w8+wAMbN+cn2MHQHUIEF8fWS3/qxFhE2Dej8YPvvRvc6nDfEuA9n8eCzM/lY4AAQBxG/9bSmMrgPgUAACQSIRNgMoa/5EvXvufdSkAAIAhzF5dBFk9tzT7XxGn7iJdAeAdYAAZTKa9/M9mlE2AbKv/CDWA9j8bpf2sOwCGCEApuk1s+U97M65u45yc6dDsf5R9AAZLbEeAACCdITcBZl/9b6nX8DWA9j9TKAAAgL5Y/a+yD0AcCgAAyCjOxwFlWP0P/Jdq/zOdAgAA6MUsVUSe1f/sf69NAPqmAACApHrdBLD6H6sG0P5n1gJg+mfAGSgAZZme2/tmvvynD3rY7XkM6S//7QAAQF4jvhMgZ/u/779d+59ZKAAAgC45/DMLbwZgRAoAAEht+E0Aq/+eHgftf2akAAAAOqNp3S2PJ31QAABAdl1tAjj8M+JBIO1/ZqcAAAAGYvU/yWPC8BQAAEAHTWiHVfqz6WPrwWfuAsCHQAPk/Cho+c+QT7dW94iPjJdzKgub5b8dAABgc3rMYXlqmJcCAABo2yTedA2q/d/y8Wmzytf+Zw0FAAAwE53mgDwpNKAAAABatYq1/yNvAmj/M0kBAADMSr85FE8HzSgAAIAeG8ba/yM+Vtr/rEsBAAA07zprQg9p30fbI09jCgAAoK+2sfb/iI+Y9j8bUQAAAPPRex6dp4A2FAAAQMPmsWXo8GZ8zLX/mUIBAAD0sgx1/ifgl4LBPxQAi4uLU36sfAQo1/QMl/9MZwyUy3PHwtQxYAcAAGhCHxoKpQAAANankVwizxqbUgAAAN3zBoA2PHr0SgEAAGxIO7ksni9moQAAAIBEFAAAwDSayqXwTDEjBQAAACSiAAAAOm4tew9re/M+htr/zE4BAAAAiWyf/uNdO3cPdSUwvhIHvJYPPSnx5UAcO3dfNfYlpOM1O7CFkuffrdO/Ch4AAKiJI0AAAJCIAgAAABJRAAAAQCIKAAAASEQBAAAAiSgAAAAgEQUAAAAkogAAAIBEtlf8JWeM8kWDS0tLWwLbuXNnrRcP3Yqf/9PjaPnc0C/nEi0+eY4IWtpx1JZ46v5+YmN+3DFfVQEAcwm+gC7d0tLSpjXAjid4Cjq2+y07K14lA5GLlrorltItlJz/jgAxByuJ0lerAM1U3AqthueI2SkA6Iz2/wA8yEARtK7b8xjSHwUAs9L+L4VNAKBbWsul8EwxIwUA3dCZHoyHGgBoQwHATLT/y2ITAOiKpnJZPF/MQgFAB/SkB+YBBwAaUwCwOe3/EtkEAMZtJ3sPaxttHj2bAGxKAUBbutGj8LAPo/QvAajb9MffGmgAi4uLY18C0IQCgE1o/5fLJgDQhiKqXJ47ptu2vLw85ccWf0ynDz0iDz6bmp7h8p82tP9H5MFnU9Mz3A4A01gBlM4mADBiC9nbAEZ83GwCMIUCgOZ0oEfnKQDG7UBrRQ9v5TH3yNOGAoANaf/XwSYAMC/N4zp4HtmIAoCG9J6D8EQAA5ur9+wU0Lxmf8RsAtCYAoD1af/XxCYA0F/b2DJ0SPM+2jYBWJcCgCZ0nUPxdACDabDctwnQ32Ol+qIZBQAAACSiAGDu8z/6zQFt+qQ4BdSArwGOz5cBd276g7ZRv3nTPrRNgFls+iit+zhv+uB7ITBJAQAAAIkoAFhL+79QNgGAUdr/s/zUJkBP7f9Nf/SP/4FNAP45BQAAACQrAJaXl6f8Fz4OMhXt/6LZBGD2l/NK8st/Omn/z8gmQH+PjE0A5sp/OwAAQAd8JGV/PLZ0SwHAP9H+r4BNACBm+3+FTYD+HhObAMxOAQCwDp8BWgqfBBrKLKWCGmDeR0P7n84pAPhH2v/VsAkAjNj+t1rt1lyPp00AZqQAAAAGZRNghceBsSgA+Afa/5WxCQCMePrfQaARD//YBGAWCgAAYASZa4DMfzuBCgAfBZ2Z9n+VbAK0UcGDM8uXAEz+//P+niLod47y4T/eCdBe48fQJkByu2bIfzsAAPPxEUDReEZichBoIz75h9EpALLT/q+YTQBg3M/+VwOMtfq3CcB0CgAAYEx5aoA8fynBKQBS0/6vnk0AYNyv/p3xV2VYGc/4N3b14NsEYAoFAMA/oyiqj4XOuNQAw6/+oZsCoIIPgmAN7f8kbAIkfL9pt4ldRP4X8bwkbP/P+zt37r6qvjJg9j+q80feJkBCu2ZL7G0zfhIcAHWYTHv5zwBmX93WVAPM/rfo/TOA1bR3BCgp7f9UbAIAI7b/09YAEVb/NgFYlwIA4J+ohWpllVOcoo8DFX3xZKAAyEj7PyGbAJ1w0Dwyz07w9n+zuyhxGT3vNff9sNsEYNL2LTPbtXO3eAUIro/37Mp/Ol+Pzv7Ok5X19NKOo7aEF23pTza7Zs7/f7YD4H1gGWj/p2UTgCk5L/8zGL393+bugh+qaXB5Qz7gNgHY8s9z3hEggH+kBKqbJU40DVbAAcuAZpek98+4FAD8E+3/6nmK23AGJj7PUWNjrUeb3W+QMqDxZYzyaCs52JcCIJcivtCHEWmBQ63CboA0XpiOWAa0ueuwC/GwI4TxCwDLx4rpDSfhia67+OkvpevIf0ucmEvSxdu0WYsPUwm0vK82f2YdTzS9miul1xYA3gdWsTrmb/pWxzqYdU1PePlfsSIqn5bL09XVebfFQFe/tojFdxHjhGbWJLwjQPwDXeFUPN0NOFxeCs9U0QvTri5m31X7vAv3Nv82/oMc50oo5nsAKJr2P7Pb/ZadO56gSIBKlNXWnfdbAmYx4zq+j3NExS24F5+8c/lc+V8/OwDoB2fkSV/Dwac8yloN9y3s8nT04/IV/wkxr4roBYBGcok8a8zLgrjEUyV9v9JLSZJSnq9hFF3wlLtULffKSx8zae2aM5/XKQC8DyyVPJ3gnbdp/99UI89Tz+zZLv9TKWKRGraPXvQFx79CujWZ7Y4ApS4KkywB513W5ykDpg+APJsAef5SsjU4p/ylJa6qI19z/CtcY/ql5nmNpOVNwNSszTp+5d8mqZGYwnmSEi0s7SjlwBKjv0W4pYIW/dBqB0CqFiRt+7+rLn71uwE2AaoxTDLL/4JU0/6P2W6PcA0t2QSoRoNkXn8HYHl5uegxTWZ9rNftBlQsSZEze8c0Sf77rMM6rI7VwfYEMrw6qMy6rw7vAahZtvZ/3936WncDbAJM4fxPuZI/dxW3/0dU30NnEyAt7wGgBkOuy+0G1CR5eZOcTYA6DPl+gJX7qq8MIKGGOwCOgcaXpP0/Vle+st0AmwClGzKT5X98Sdr/y7fJc789sQlQumaZvGEBUNPgpkoRluARroH+VHOGZN48ryb/q3kGCbgEj3ANsKmNRqn3ANSp7vZ/tGV3tOtpJuEmQJV/FHOpsrtZd/s/2rI72vU0YxMgoebvAdi1c7fmCgOLvM723gDGMvyZHPnP8CKvs703gOLy3w5Ahaps/3fVZe971VL0bkCqTYBN/xwL3Dps+jxW1t2ssv3fVZe97/d8F70bYBMgm2kFQLnjmJp0uPSfZUm34wlLycsAKtMsyeU/lS39Z1n9d1IhFF0GUJkpQ9EOQG0qa/8PufRfteMJSyv/1/J+S6wBUm0CTKH9X5M8z2Zl7f8hl/5r/vv2lUCJNYBNgFRafQ+AY6D0p/3quf3gXKkB2qx6vTEgppoqmbE+lLOm/PeFANG0Xz13sIK/7Te0WfV6YwCR839bfSVsZnW0/9ufn5m35T9d+92Ask4E2QSoSZsMl/9lqaP93/78TCf9+w5/W1kngmwC1GT6wPNNwAQSoeu/EbsB1fD234QWlnZMb5XZBBhdhK7/9N9sN4CatC0AatoFrlj8RWfkpX/CMmBpaamgLYvMxv1SXvlfhPiLzshL/4RlwOLiYkFbFpntapf/m78J2DgoxbhLgWoO/Mwi26Ggmk4BpWr/d7Cuqij/6/480EIvPtqBn2HusaxDQXWMtISWNxtjjgDVL2yzuZSuf87dAJsAUIGwzeZSuv45dwNsAmTQQQFgFziCstr/pS/985QBG9n9lp2dfGFCNHHGVSmv+rLyf9N3AhSqrKZs6Uv/PGXARrxhJoL2UWYHoHLRlpU1Lf2rLwPq2wQo+vASA6hsZRNtWVnT0r/6MsAmQPVm+iIwgyC4InpaJZ71n1eq9wZYTAfXVW7L/+CKaP+XeNZ/XqneG1DEqMtseYaBtC3PAjShIO3kDEv/WsuAIEOoE5W9/TdO6sa5klnU/VbgfQVpJ2dY+tdaBgQZQvSUuo4AFS/y7FvrgZ+0h4KSvBMAShG5XKn1wE/aQ0F1n5dLaNYdgCD1KLMbd+GYretf8W5A5Aokbft/4MSuLP8zbAKMu3DM1vWveDcgcgXCRmYcM9tzfhZENQK2/zN3/TeyWgM03hAIuxtgE2AU0V748n8UAQuVzF3/Tf+ixs9X2N0AmwBF5/+2tE2guo2yUtT173tDYKzdgICFx1y0/2P+zhHVvQkwykpR17/vP3Cs3YCAhQdTzD5IvAegYHG6gLr+Q749INpugE0AGF6cEkXXf8i3B0TbDbAJUK5uPgUo2no0uSGXhrr+SXYD4tQb86qv/R8zaWNeVcJNgCGXhrr+SXYD4tQb7OouaefbAVheXjYOghh9um2/7u/uWgpWx25A2E2AhF9W0N+yIGH+h+1ujl6ctF/3d3ctBatjNyDsyySh5XlemNsqW5UywFqwZe85bcu/9N2A0cuMPhQ3FCNnbORrq+PZ39QAa8GWvee0Lf/SdwNGLzPY0nXGeg9AkcaaaHX9e1X0bkDATYCE7X8ydDfHav/r+veq6N2AgC8Tut8BqOyzICrT3+JP138wkXcDKtsEqG9M9p3P9eV/TWOgv8Wfrv9gIu8G2AQIbt6nvuMjQCXuAhdn4EfY0n8UkcuAIjruoS4mT7rGv8ISD9yPeDGW/qOIXAYU8TKp0q6u09URoHp03p114Gd0AQ8FLS0tjfvNxF0xPlmxsLSjgrql8+6sAz+jC3goaHFxsb5twLSa7ABs+vRXEKZhDfPY6vqHUtBuQJC+e30f/TnLa3+YibnK/C/lI0GHuQxd/1AK2g0I8jKp0q4e8t8OQCW66vLq+ocVZzcg+CZAkCKEykR+m2NXXV5d/7Di7AbYBKhGwwIg4QdCR9Bra83SvwirWwHNlrkDfFJQwI8DyjBWh5ySq8z/+AeBem2vWvoXYfVxbjYYBvikoMh1csWWG71+u38T8IrgSVqZlus5B36ynQtqfygo7McB1dr+LytRy7ra0k84tFzPOfBTojYPe/tDQfXV/zkTtXkBYA+ojhFg6Z+5DNiSbxVe5YgdPo2rzP/IY6On2sPSP3MZsCVTnVyx5aZPZV87ABU3gaJp3Itt0wa29K+jDGgzBgJuAkQuPLJlaYnXXOLipnEvtk0b2NI/lMZPR5sxYBOggiz1JuCMI6Bl17/DKyHCu4T7eGPA8O8EmOUPN3pp/06A4U85d1t1tOz6d3glRHiXcC+fFuqdACVotQNQ5efBlWXeRZuuf/WG3A0IuAkwRaGjN8inf+bJ/4LGybyLNl3/6g25G2AToPT8twOQha5/KqF2AwZQ6+EfYiquwanrn0qo3QDC2tr+V2w6ViwfeyoBZ1ylWfrPVVIH/wjLIRfH7QfYMA9mxYd/wrb/q8//WbYvhlkZb7SMm3GVZum/xvRlcX1/cuPzY+0HWB0P5uLUB7DXfOs7/+0A1KzNaZ+ur4XRZNsNmGQ8U9/XAmyqzWmfrq+F0dgNoMdPARq9BVW3Zu3/xmf9HfSvVX/vDZgyFAc4mZP58E+E7I1wDRV/IlCz9n/js/4O+teqv/cGTBmK0T4yqzLLrbN3iB2AXTt3W1MORtefPLsBFR/+KfdNtNXkf8xPBJpO158p7AYUZFf/+d/j9wAwcPtf15+xdgNG2QSoe/VPBLOMn/7anHO1/3X9GWs3wCZAobrZAVheXp5eGpbbBCqCrj8NVLYbUJn4b/9dJf/HpetPA3YDIhsm/+0AlN3+1/Wnk92ABhsCa8bewJsA2v/UvQkwS/tf15+WVkZCg8GwZuzZBChRZwVArV8KE5alP93qpAwYRvWr/4La/xnyf9yDQOuy9KdbnZQBlJX/Pga0vPa/Az9EOxe0eihoo8G5+y07u/pOgMwf+0NkHb4heEr734Efop0LWj0UtNHgjPZeebo/AlR3EygIXX8i7wZsiaHo0V5c+z9D/gcZUbr+RN4N6Odyctk1YP57D0BEHc6Ulv4M/2FB/XXuqz/8Q1iDHQTq8DSRpT9BBo93AgTUcQFQdxOoLJb+BCwD2siw+i+0/Z8k/wO+GWAjlv50wkCqOP/tAITTfo609CdmGdBmE8DRf0rRpgZoXz9YsdG5TgZVkNqYHguA6ptAkVn6k2Q3YF2lD/6i2/9J8j/yGLP0p1cGWGX5bwcglsazo6U/RZQBzRr5GQ7/UIr+DgI1bpFamTGYNoPNJkAovRQA1TeBQrH0p+7dgCSr/wra/3nyP86bASz9GYWBV0H+j7YDUMEcMPpjYulPiWXAXJsASY7+Z8vDJH/vXDXA3B++bgXG2BoMQpsAcfKwrwKglGZViVbW/Zb+VL8bMOPqP8NroaxELetqm5lx1HW+3FlZcln6E4cBWWiijvkegCRNoA4fDet+6igDZlnZ51n950zCCv7qDmuAWf4byywim3182gQIkoQ9FgAZmkCDsfSnrDKg5YZAntV/rVla4jWH3Qew9KcUdqgKytKRPwWogiZQ34+DpT+Fml4GTFnip1r9Z87AOv729jXAlB9ZS1Go6UPXJkCEDOy3AEjSBOqJpT8VCP7VAfGVm6LlXnkElv5UwDCOnKK97wBk+Ei4liYfAUt/MpQB63b6tf9rWkMnyf82mwCTN1ozUZl1h7RNgF1j53+ILwKrYw7ohKU/mXcDrP4TquNx6OTNAJb+VMzwjpZ7QxQApTexhhkElv4kLAP2XfGnWv3nSc46/oqeaoDV/9/aiCT2Heo2AcZNzhA7AEGKobFY+pPQmt2AbKv/zIlX8aPRoAaw9Ceh5MN+V4zEG6gAyNMEmlc1CxpoYKUGyLb6z5aZNf0t3dYAmddAYPyPm5lRdgDilETAkBKu/mVd3Y/JWF8SDMS3K0zWbQtV0MR5XIABWP0naZlny381ABA8/wfdAahvVgMaS7j6z5yTtf5dG1EDAJFzMtARoPqaQMBGcq7+5Vuqx0cNAITNt6ELgGwbwUDj1X9lQm3+jkL+b0QNAHXbFS//tw95Z0Bycy39K2v/k9DC0o4ZSxqfCwQMaYQjQJpAkFPm1X/A9s8oEub/XCPZVgDUZ1fI/B/nPQAZ5jlgX5lX/7PIk4p5/tJVagAgWiqGexNwrU0gyCz56l+azau+R0wNADntippmoxUACTeCIafZV/8LSztyrv6zNcVz5v9cw1sNABXYFTj/x9wByDkHQCpzrf63VCdy+o8rbf6rASCJ4Pkf9wgQULrkq39YlxoAGN3IBUDaJhDUbfdbdlr9B2//jC5z/s9VAygDoDi7wuf/+DsAmecAqFLyt/yWkv4RZM5/bwuGWu0qIf/HLwCAmlj9w4zUAEDqAiBzEwhyHvupe/VfRPsniOT5P28NoAyA4HYVkv8hCgBzAJRurqW/1X+E9I8jef7P+1pQA0BYu8rJ/ygFwIwqngOgXFb/q2RUfyp+bNUAUIFdRWVUoAIgSEkE9Hrsp+LV/4xk3SSPybwvDceBoETLYbIuUAFgIxjKovFf7uZvQPLfVgCUa1dp+R+rADAHQCms/ktP/4DkvxoASrSrwPwPVwDMqPo5AKo59mP1T7eqf7Qb1ADKABjLrjITKWIBEK1IAlY1WPpXv/qfkWSbhUep8QtHDQBhLcdLtogFgI1gCEjjv6bN38jk/ypbARDcrmLzP2gBYA6AUOZd+lv9x0//yOR/m9eRGgCGsavk/N++pXC7du5Oss6AUVj6T5FkDRpWkvxf+RvnGmwrNcDyuUt9XhdQsLg7AJHLJsigwZmfVKv/GcmxZjxunWwF2A2AES0HzrHQBYCNYBhLg6V/ttV/0Zu/RZD/nby+1AAwiuXY+R+9ADAHQCmNf6v/stK/CPK/kxearQAY2HL4/C+gAJhRqjkA4iz9szX+pU1A2Z6RxlsBygCgpAJgxkIq2xwAEZb+Vv+Ftn9KIf+7fekpA6BvReR/GQWAOQD602zpn7Dxb/U/Fvnf+WtQDQA9KSX/iykAzAHQOY3/uVj9j0j+b8RWAMSxXE7+l1QAlPXIQpVL/5yN/9nJqP54bHvaClAGQMKMKv6LwDJ/Oww00Hjdn3zpn7C1XKi0+d/g+8JW+eIwyKawHQAbwTBK19/qv772T4nkf6+vU7sB0Fhx+b91S5kWFxdn+c8yL1lotjjY8YTaemBtFv0rkr+OrP6jkf/DVEFVbghMr3Cq/JNpY3G2krjE/C9vB2CFPhD03fJP+2bffVn9ByT/h3nx2hCAivO/1ALAHABTWPp3wuo/LPk/I2UA9Gq52PwvuAAwB8C6635nfjph9R+c/B/yFb1SBqgEoJr8L7sAMAfAik7W/Rr/q6z+iyD/h39pKwOgDnV+DOi60n42HBXrZNG/wqtjlfVifeR/+48K3ddqDeBds1Co4ncA5mrCmdepRlctf13/ximh/R+B/B/3JW9DAApVQwFgDiCPrk75r7D0X8Pqv0TyP0gZoBKAglRSAJgDqFu3635L/3VZ/ZdL/geJApUAlKKq9wAsLy/P+AUxzoMSX4fL/X0Z+euy+i+d/I/w3oBV+9YA3icAAVVVAJgDqIB1//Cs/usg/1tafUy63SfxjmEIqLYCwBxAiXpa9K8wyKez+q+J/I+5IbDCtgDEUWEBYA6gCL0u+lcY25uy+q+P/A9eBqxQDMC46iwAzAHkXPGvMJ5nZPVfK/kf/1zQvta8aVg9AAOotgAwB5Bnxb/KMJ6d1X/d5H9ZGwL7Ug/AAGouAMwBVLzW35ehOy+r/wzkf6EbAmus+6GiqgJoqfICwBxAHUv8dRmuzVj95yH/a6oE9jX9qwaUB7CprVtymHEOsKjKoPRvAjJE27D6T0j+D6P0aIV5FT1NZCkAzAGUPksZlu1Z/acl/4dUaMbCvIqeKRIVAOYASpycDMWuWP0nJ/+HV1bYwryKnixyFQBzzQGmgVrFn5MMvBGf8aIDnenk/4jiBy/Mq+j5Il0BYA4g5jxkpPXE6p99yf8IYoYwzKvoKSNjAWAOSC7O3GNo9c3qn0nyP5Q4gQzzKnrWSFoAmAMyG3G+MZCGZPXPRuR/WOoBCrJc8sSRtwAwB6Q12ARjzIzI6p/p5H8plASEtVzy3JG6ADAH5NTHdGJshGL1zyzkf7lUBUSwXPL0kb0AWGEaSKXZzOF5L4KlP/OS//VRHjCM5ZInEQXAPzIH5DF9bvDklsvqn2bkfx7yv1byf17b5v4XlZprNOguQDTSn8bkPxRN/jegAGg+B5gGIIJ5X4zSn0nyH0ok/xtTALQaGeYAGNe8r0Hpz0bkP5RF/rehAFjLHAClkP50S/5DKeR/S94E3M3bwrx5qCDeBFYB0U+v5H+t5H8F5H8n7ABsSCsIYpL+9E3+Q0zyvysKgGnMARCN9GcY8h+ikf8dUgB0PweYBqAPDV5c0p825D8EIf875z0As3IktBrOgJZI9DMi+V8N+V8i+d8HOwCz0gqCUWj8MDr5D6OQ//1RAPQ7qswB0EaDV5D0pw/yHwYm/3vlCFATtoOLZgu4FBo/BCT/iyb/SyH/+2YHoAnbwdAr276EJf+hV/J/GAqAQbeDTQPQx8tE+jMk+Q99kP9DcgRo6O1gm4yjswUcluinLPK/OPI/LPk/MDsAbWkFQXsaP5RI/kN78n8UCoAONBuF5gBo81qQ/kQg/6EN+T8WR4BG3g625zg8W8BxiH6qIf+LIP/jkP/jsgMQohWkG0Q2jYe99Ccm+Q8zkv8R2AHohVZQZDpAoxP9VEz+Ryb/Ryf/g7AD0AutIFiXxg/Vk/+wLvkfih2AiK0gfYhe6QCNovHiRvRTKPkfkPwfhfwPyA5AvxqPXd0gqtFmMEt/yiX/Qf6HZQdgIFpBcegADUn0g/yPQ/4PSf5HZgdgIFpBZKPxAyvkP9nI//jsABTTCtKc6IoOUN/aLFlEPxWT/6OT/32T/6VQAIzDNDAiE0B/RD9sSv6PSP73R/6XxRGgcbQZ6zaFCajlsJT+5CH/qYz8L5EdgIJbQdoVzegAdavlckT0k5b8H57875b8L5cCIATTwJBMAF0R/dCe/B+S/O+K/C+dAqCeaUB4zcgE0FL7EwiiH9aQ/8OQ/y3J/2p4D0Ag7V8VjofSq04GmPSHSfKf4OR/ZewA1NkK0smYQgeogU4WFqIfNiX/eyX/G5D/VVIAxGUa6IkJYC6iH4Yn/3si/+ci/yumAEgxDci1fZkAZtHVWQLRD43J/87J/1nI/wwUAGUwDXTIBDCd6IdQ5H+H5P908j8PBUDGaSB5zJkA1tXh2wdFP3RO/ndC/q9L/iekACiPaaAlE8Aaoh9KIf9bkv9ryP+0FACl6nAayJZ6JoAV3X5ioOiHwcj/xuT/CvmPAqBs3U4DSeIv+QTQ+SeFi34YhfxvQP53+wvlf7kUAJUwE8wu5wQg96FW8n928r8T8r8CCoCqdD4NVBmIqSaAPr4ZVPRDQPJ/FvK/JflfDQVAhfqYBmpKxgwTQB+5L/ohPvk/nfxvTP5XRgFQs55mgtJTstYJoKfQl/tQIvm/Lvk/L/lfKwVA/fqbBgqNy8omgP5yX/RD6eT/GvJ/dvK/bgqALHqdBsqKzgomgF5Df4Xoh2rI/1XyfxbyPwMFQDoDzATBY7TQCWCA0Jf7UDf5L/+nkP+pKADyGmYmCJiqpUwAwyT+CrkPqcj/4Jcq/+mbAoBBZ4IIIRt2Ahgy8VfIfUhO/u9L/pOHAoDRpoGxMjfOBDB84q8S/cAq+b9C/pOHAoBAM8EwKTzWBDBi3K+S+8AU8n+U+x2G/GdfCgCiTwadp3PfE0CEoN+X0AcakP+d//7hyX82ogCgyJmgTYK3mQCihfsUch/ohPyf5d+GIv/ZlAKAameCnOQ+0BP5H5z8Z3YKAJozGQQh9IGByf8g5D/NKADohslgYEIfCEL+D0z+054CgO6ZDHoi9IHg5H9P5D/dUgDQO/NBYxIfKJr8b0z+0ysFAEMzH0wh8YGKyf8p5D9DUgAwsuTzgcQH0pL/Y18CeSkAiKjKWUHWA2xK/sMAFACUpIiJQdADdE7+w5bu/D9IFdZ4Our9/QAAAABJRU5ErkJggg=="
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_94
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color red.\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is Cut the right side of the shape\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is Cut the right side of the shape\nthe 9th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_441
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is Stack the original shape on top of the {'layer1': 'CcCcCcCc'}.\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is rotate the shape counterclockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'SpSpSpSp'}.\nthe 8th action is Cut the right side of the shape\nthe 9th action is Stack the original shape on top of the {'layer1': 'CgCgCgCg'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_60
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is Stack the original shape on top of the {'layer1': 'SySySySy'}.\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is Stack the original shape on top of the {'layer1': 'CuCuCuCu'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'SgSgSgSg'}.\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is Stack the original shape on top of the {'layer1': 'CbCbCbCb'}.\nthe 9th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_140
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAgAAAAIACAYAAAD0eNT6AAAGbElEQVR4nO3YwQnDMBBFQSekRblIN+mUkENAa3gzZ4H+8bHHAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAwCavXR8Bs9Za9/QG4Dne0wMAgP0EAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAII+0wOAZ7mua3oC8KfzPH++cQEAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBIAABAkAAAgKDX9ABgj7XWPb0BeA4XAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAggQAABw9X4VmCQd25UVNAAAAAElFTkSuQmCC"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is Colorize the top layer of the original shape with the color purple.\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is Stack the original shape on top of the {'layer1': 'CcCcCcCc'}.\nthe 5th action is Stack the original shape on top of the {'layer1': 'CcCcCcCc'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'SgSgSgSg'}.\nthe 7th action is Cut the right side of the shape\nthe 8th action is rotate the shape clockwise 90 degrees\nthe 9th action is Stack the original shape on top of the {'layer1': 'CrCrCrCr'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_330
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAgAAAAIACAYAAAD0eNT6AAAGc0lEQVR4nO3YsQ2DQBQFQWzRDfUQkFEamStyPXYJDizdIe1MfNK9cPWXBQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAgEEeoz4C5tr3/TN7A3Afz9kDAIDxBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACC1tkDgHt5Xe/ZE4A/Hef2840LAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAErbMHAPdynNvsCcAALgAAECQAACBIAABAkAAAgCABAABBAgAAggQAAAQJAABYer6jaQfwr41cwgAAAABJRU5ErkJggg=="
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is Cut the right side of the shape\nthe 3th action is Stack the original shape on top of the {'layer1': 'SuSuSuSu'}.\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\nthe 7th action is Colorize the top layer of the original shape with the color white.\nthe 8th action is Stack the original shape on top of the {'layer1': 'RcRcRcRc'}.\nthe 9th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:9)_349
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is Stack the original shape on top of the {'layer1': 'SuSuSuSu'}.\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is Colorize the top layer of the original shape with the color green.\nthe 7th action is Stack the original shape on top of the {'layer1': 'RyRyRyRy'}.\nthe 8th action is rotate the shape counterclockwise 90 degrees\nthe 9th action is Stack the original shape on top of the {'layer1': 'RyRyRyRy'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:9)_171
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is Stack the original shape on top of the {'layer1': 'SwSwSwSw'}.\nthe 3th action is Stack the original shape on top of the {'layer1': 'ScScScSc'}.\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is Cut the right side of the shape\nthe 6th action is Stack the original shape on top of the {'layer1': 'WpWpWpWp'}.\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is Stack the original shape on top of the {'layer1': 'SuSuSuSu'}.\nthe 9th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:9)_162
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is Colorize the top layer of the original shape with the color red.\nthe 3th action is Cut the right side of the shape\nthe 4th action is Stack the original shape on top of the {'layer1': 'SwSwSwSw'}.\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is Colorize the top layer of the original shape with the color cyan.\nthe 7th action is Colorize the top layer of the original shape with the color white.\nthe 8th action is Colorize the top layer of the original shape with the color yellow.\nthe 9th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_403
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'RrRrRrRr'}.\nthe 2th action is Stack the original shape on top of the {'layer1': 'CbCbCbCb'}.\nthe 3th action is Stack the original shape on top of the {'layer1': 'CwCwCwCw'}.\nthe 4th action is Cut the right side of the shape\nthe 5th action is Colorize the top layer of the original shape with the color green.\nthe 6th action is Stack the original shape on top of the {'layer1': 'RbRbRbRb'}.\nthe 7th action is Colorize the top layer of the original shape with the color blue.\nthe 8th action is Cut the right side of the shape\nthe 9th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABAAAAATICAIAAAANxCANAABNeUlEQVR4nO3deZhddX0/8MlGSAKEAJGwFRRRCEUiqGigog+i7EgkAypWLe4PorW1PrRa0Meq1doq1YrFBVAIzEAoO8oqyiKILAEViQgCsgQYCGSFZH5PO/1Nx7l37szce9bv5/X6zzOTew9Izvm8v5/P95wJ/f39XQAAQAwTyz4BAACgOAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIJPLPgEo1PLly7fccsvVq1c3/en73ve+U089tfCTAqAjZ5999rh+f+L/mDx58tSpU6dPn77pppvOnj17yy23nDRpUm7nCBUyob+/v+xzgOJ873vfO/bYY0f66Wabbfboo49OmTKl2JMCoCMTJkzo/EM22GCDP//zP99jjz1e9apXHXrooVtvvXUWpwZVJAAQy3777Xf11Ve3+IWLL7744IMPLvCMAKhEABj2gXvvvfd73vOed7/73ZMnG5cgNfYAEMjDDz987bXXZttHBiA9/f39P/vZz973vvftsssuPT09ZZ8OZEwAIJBFixatX7++9e9ccMEFI+0QACCapUuXHnXUUR/4wAfWrl1b9rlAZgQAAvnhD3847MisWbOGHXn22WcvueSSAk8KgKo79dRTDzjggOeff77sE4FsCABEcffdd99xxx3DDn7lK19pHO4855xzCjwvAHLR39K6devWrl37zDPPPPDAA9ddd92///u/H3nkkdOnTx/p06655prjjz++2H8CyItNwERxwgknfOlLXxp6ZJNNNnn88ccPOuigYduCp02b9vjjj2+00UaFnyMAmW0CbqPCee655772ta99+ctffvbZZ5v+wo9+9KM3v/nNbZ0jVIgOACH09/cvWrRo2MG3vvWtU6dOXbBgwbDjq1atuvDCCws8OwAqYaONNvr0pz9900037bDDDk1/4bOf/WzhJwXZEwAI4ac//ekDDzww7OBRRx01EAMal448CwggrLlz515yySVNx4FuuOGGX/ziF2WcFGRJACCEM888c9iRzTbbbP/99+/q6tpmm21e85rXDPvpj370o6effrrAEwSgQubOnfupT32q6Y+uvPLKwk8HMiYAkL61a9f29vYOO7hgwYLBN/4eccQRjX9k8eLFRZ0gAJXzkY98ZNKkSY3Hr7nmmjJOB7IkAJC+Sy+9tK+vr+n8z4DGbQCmgACC22KLLebNm9d4vHGgFGpHACDi4/9nz579xje+cfB/7rTTTrvuuuuw37n66quXLVtWyAkCUEW77bZb48EnnniijHOBLAkAJO6ZZ55pfLHXkUceOayx29gEWLdu3bnnnpv/CQJQUZtvvnnjwWeeeaaMc4EsCQAk7txzz129evWwg0cfffSwI6aAABjLmwQ22WSTMs4FsiQAEG7+Z+utt95nn32GHZw3b96LX/ziYQd/9rOfPfzwwzmfIAAV1fRxcLNnzy7jXCBLAgApe+ihh6677rphBxcuXDhxYpP/8hufBbR+/fqenp48TxCA6rrnnnsaD+65555lnAtkSQAgZWedddb69etHnf8ZKQCYAgIIa82aNbfddlvj8de//vVlnA5kaULT+TZIw+67737nnXcOPbL99tv//ve/b3z178B6/9Zbb/3YY48NO37fffc1TgcBUB1Nr+odVjhnnnnmMcccM+zg9OnTH3744U033bSTT4bS6QCQrLvuumtY9d/V1dXd3d30PvHffxkmTjz88MMbj59zzjn5nCAAFbV27dovfOELjcc/8IEPqP5JgABAshq3/7aY/xngWUAAdHV1feITn/jVr3417OB22233uc99rqQzgiwZASJN/f39O+ywwx/+8IehB1/60pfee++9Lf7U888//6IXvajxsQ+//vWvd95553zOFIAKjQCtWLHi4x//+He+851hxzfZZJNrr732la98ZbvnCBWiA0CarrvuumHVf1dX11FHHdX6T02ZMuXggw9uPK4JAJC8vr6+k08+edddd22s/rfccsvLLrtM9U8ydABI0/vf//7GK/idd97Z9L3uQy1evPhtb3vbsIM777zzr3/966zPEYAcOwCLFi1q8Uf6+/vXrFmzcuXKRx999KGHHrrtttvuvPPOxgfHdXV17b///qeddtrWW2+d6SlDmQQAErRmzZo5c+YMm+TZZZddGgc6G61cuXKLLbZYtWrVsOO33XbbvHnzsj5TADIw0tMdOvTKV77ys5/97KGHHprHh0OJjACRoEsuuaRxjr/19t9B06dPf8tb3tJ43BQQQBwzZsz41re+deutt6r+SZIAQILOPPPMxoOjbgBo/UYwDwMFiGPFihUf/vCHt9lmm+OOO84IKOkxAkRqnn766Tlz5qxZs2bowXnz5jV9oWNTfX19L3rRi1544YVhx2+66aa99toruzMFoNIjQIMOPPDAr3/96zvttFOu3wKF0QEgNeeee+6w6n9cy/9dXV2zZs16wxve0HjcFBBATJdddtkrXvGKf/mXfyn7RCAbkzP6HKj0+78mTJgwrvJ99uzZjQd7enq++tWvTpwoNgPUwKgzDuvXr1+xYsWzzz778MMPP/jgg7fffvvNN998zTXXrF27tvGXV69e/clPfvL+++8/+eST3QioOyNAJOXBBx/cfvvt8/uv+tprr913331z+nAASn8R2JNPPnnaaad9/vOfb3yYxIATTzzxpJNOauOToTpEWJJy1lln5ZppTQEBpG3zzTf/m7/5m9/+9rdvfOMbm/7C5z//+RtvvLHw84Is6QCQlFe84hVLlizJ7/Nnz579xz/+cfJks3MAaXYABq1Zs+bggw++6qqrGn+0//77//jHP+7kw6FcOgCk484778y1+u/q6lq2bNnVV1+d61cAUAVTp04944wzNttss8YfXXHFFWN5syRUlgBA4tt/M2cKCCCIrbfe+rjjjmv6o0svvbTw04HMCAAkor+/f9GiRcMOzpgxY+XKlf3tOuussxq/6Pzzz2/6gAgA0vOBD3yg6fEbbrih8HOBzAgAJOLaa6996KGHhh085JBDpk2b1vZnHnrooY1//Omnn7788svb/kwAamSbbbbZcccdG48bAaLWBAASceaZZzYeXLhwYSefudFGGx144IGNx00BAcSx5557Nh586qmnyjgXyIYAQArWrFlz3nnnDTs4Y8aMpuX7uHR3dzcevPDCC1euXNnhJwNQC5tvvnnjwZHeEgC1IACQgosvvrjxWnzwwQdPnz69w08+5JBDGj9kxYoVF198cYefDEAtbLLJJo0HvQyYWvOfL8k+/6fD+Z8BM2bMOOiggxqPn3POOZ1/OADVt3z58jGmAqgLAYDa6+vra3wc2/Tp05sW7m046qijGg9eeumlzz77bCafD0CVLVu2rPHgtttuW8a5QDYEAGqvt7e38bmcmcz/DH7UjBkzhh1cvXr1f/3Xf2Xy+QBU2c0339x4cJdddinjXCAbAgC1l8fzf4aaNm3aIYcc0njcs4AAkvfb3/72D3/4Q+Pxvfbaq4zTgWwIANTbH/7wh5/+9Kf5zf+0eBbQFVdc4TFwAGn7t3/7t6bHDz744MLPBTIjAFBvZ511Vn9//7CDBx10UOPQTicOOuigjTbaaNjB559/vvHZowAk47bbbvv+97/feHyfffZp+nYwqAsBgHrLe/5nwIYbbnjooYc2HjcFBJCqhx9++Mgjj1yzZk3jjz71qU+VcUaQGQGAGrv99tvvuuuuYQenTZuWR2e26RTQT37yk8ceeyzz7wKgXDfddNNee+113333Nf7ogAMOaLoxDGpEACC15f8DDzww2/mfwY9tfOrzunXrent7M/8uAMpy8803/+Vf/uX8+fMffvjhxp/OmTOn6VAQ1Mvksk8A2rR+/fpFixYVMP8zYOrUqYcddljjG8fOPvvs4447Lo9vBKATY5nSfOGFF9asWbN8+fInnnjiN7/5za233vrAAw+M9MubbbbZ5ZdfPmfOnKzPFIo2oXEDJdTC1Vdfvd9++w07uOGGGy5btqxxw24mLrroosMOO2zYwQkTJjzwwAPbbbddHt8IwFhMmDAh76+YO3fuhRdeaO8vaTACRF01LsYPDOrkVP13dXW95S1vmTlz5rCD/f3955xzTk7fCEAVHHPMMTfddJPqn2QIANTS6tWrFy9eXNj8z4ANNtjg8MMPbzzuWUAAqXrVq151/fXX/+AHP9h4443LPhfIjABALV100UXPPPPMsIMbbrhh3k9maPosoFtvvXXp0qW5fi8ARdpoo43e+973Xn/99bfccsv8+fPLPh3ImE3A1NK0adNOPPHEYQf/7M/+LO8Vmje/+c0nnXRS486ZxjQCQMVNmDBh8uTJU6dO3WijjWbNmrXllltuv/32e+yxx/z58+fNmzd5shqJZNkEDAAAgRgBAgCAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAmLFy4sOxzgKro7e0t+xSgOK7/MMj1n1B0AAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgkMmtfzxrQU9RZwJF6FvcXfYpQD30zJpd9ilAlrr7lpV9ClAVOgAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQyOSyTwBy0be4u+xTAKAE3X3Lyj4FqDoBgLpS4gPEpMSHDgkA1IBaHyAmtT7kQQCgcpT7ADEp96EYAgDlU/EDxKTih1IIAJRD0Q8Qk6IfSicAUBxFP0BMin6oFAGAfCn6AWJS9ENlCQDkQt0PEJO6H6pPACBL6n6AmNT9UCMCAGnW/T09PU2Pd3dX7lQB6quCdf+i0+5uevzt79m18HOBihIAqGvdP1KJD0Dadf9IJT4wRgIANaj71foAMet+tT7kQQCgiqW/ih8gZumv4ocCCABUou5X8QPErPtV/FA8AYDSSn9FP0DM0l/RD+USACi09Ff0A8Qs/RX9UB0CAH9C3Q8Qk7of4hAAyKv0V/QDxCz9Ff1QcQIAGZf+6n6AmKW/uh/qQgAILcPSX90PELP0V/dD7QgAQSn9AWJS+gMCQDhZlf7qfoCYpb+6H+pOAAhE6Q8Qk9IfGEoAiKLz6l/dDxCz+lf3Q2IEgPQp/QFiUvoDTQkAKVP6A8Sk9AdaEADS1GHpr+4HiFn6q/shAgEgQZ1U/0p/gJjVv9If4hAAkqL0B4hJ6Q+MnQCQjrarf6U/QMzqX+kPMQkAKVD6A8Sk9AfaMLGdP0SVqP4BYlL9A+3RAagxpT9ATEp/oBMCQKzqX+kPELP6V/oDgwSA+lH6A8Sk9AcyYQ9Azaj+AWJS/QNZ0QFIvPpX+gPErP6V/sBIBIB6UPoDxKT0BzJnBKgGVP8AMan+gTzoAKRW/Sv9AWJW/0p/YIwEgOqy8A8Qk4V/IFcCQEVZ+AeIycI/kDd7AKpI9Q8Qk+ofKIAAUDmqf4CYVP9AMYwAVYjSHyAmpT9QJB2AqlD9A8Sk+gcKJgBUguofICbVP1A8I0A1q/6V/gAxq3+lP5AVHYCSqf4BYlL9A2URAMqk+geISfUPlMgIUA2qf6U/QMzqX+kP5EEHoByqf4CYVP9A6QSAEqj+AWJS/QNVYASoUIb+AWIy9A9Uhw5AcVT/ADGp/oFKEQAKovoHiEn1D1SNAFAE1T9ATKp/oILsAcidLb8AMdnyC1STDkBVqP4BYlL9AwUTACqx/K/6B4i5/K/6B4onAORI9Q8Qk+ofqDIBIC+qf4CYVP9AxQkAuVD9A8Sk+geqz1OASq7+u7vH8YRQAKpM9V8db3/PrmWfAlSXAJAxa/8AMan+S6HQhzYIAFlS/QPEpPovhnIfMiEAZEb1DxCT6j9Xin7InACQDdU/QEyq/zwo+iFXAgAAUD5FPxRGAMiA5X+AmCz/d07dD8UTADql+geISfXfCXU/lEgA6IjqHyAm1X/blP5QOgGgfap/gJhU/21Q90N1CAD56rD675k1O7tzYRy3bYAOqf5LL/1nLehpY9kOIhAA2jSW64i1f4CY6wiq/yLr/mGFPjAqAaAdqn+AmFT/pZf+yn3onAAwbnqIADGZISyr9Ff0Q7YEgFxY/geIKezyf+alv6If8iMAjI/hH4CYDP8UU/qr+6EAAsA4qP4BYlL95139q/uhSALAWBn9B4jJ6H9+pb+6H0ohAGTJ8j9ATKGW/zsv/dX9UC4BYEwM/wDEZPgn2+pf6Q9VIACMTvUPEJPqfyilPyRDAAAA8ir91f1QQQLAKCz/A8Rk+b/D6l/pD5UlALSi+geISfXfSfWv9IeKEwA6ovoHiCn56t/CPyRMABiRB/8DxOTB/xb+IW0CQHOGfwBiMvzTRvWv9Id6EQDapPoHiCnh6l/pD0FMLPsEqsjwD0BMkYd/VP8Qhw7AcIZ/AGKKPPwz3upf6Q+1pgMwbqp/gJhU/wNU/1B3OgB/wvAPQEwxh3+U/hCTDsD4WP4HiCm95X/VP4QlAPwfy/8AMQVc/lf9Q2RGgMbB8j9ATIkt/4+r+lf6Q3p0AMa6/K/6B4i5/K/6BxIjAPw3wz8AMUUb/lH9A0aAxsryP0BMKS3/j736V/pD2nQALP8DBBVq+V/1DwwSAEZn+R8gpmSW/1X/wFDRA4Dlf4CY4iz/q/6BYaIHgFFZ/geIKY3lf9U/0Ch0APDoT4CYgjz6U/UPNBU6AABAqlT/wEjiBgDL/wAxRVj+V/0DLcQNAAAQnOofYgoaACz/A8Rk+X+Q6h/CChoAACBJqn9gVBEDgOV/gJiSX/5X/QNjETEAAEB6VP/AGAkAw1n+B4ip7sv/Y6H6ByIGgFHnfwCIOf+T/PK/6h8IGgAAIDGqf2BcYgUA238BYkp4++/Y3/kFEDEAAEBAlv+BoAHA8j9ATMGX/1X/QNwAAAApUf0D7REA/pflf4CYarr8b/QfaFuUAODpnwAxpf30z9Ys/wOhAwAAJMPwD9CJEAHA9l+AmBLe/tua6h+IHgAAIBmm/4EOCQCW/wGCquPyv+EfoHPpBwDbfwFiirn9V/UPjCr9AAAAaTD8A2QiegAw/wMQUx3nf0Zl+R8Yi8QDgPkfgJjSm/8Zdflf9Q+MUeIBoDXL/wAx1W753/APkKHQAQAA0mD5Hxi7lAOA+R+AmBKb/7H8D2Qr5QDQmvkfgJhqN/8zKsv/wLjEDQAAUH2W/4HMJRsAzP8AxJTY/M+oLP8D45VsAGjN/A9ATPWa//HoTyAPQQMAAADElGYAMP8DEFNK8z+W/4GcpBkAAACApiIGABsAAGKq1waA1iz/A22LGAAAoOI8/RPIT4IBwAYAgJhS2gAAkJ8EA0Br5n8AYqrR/I/tv0CuwgUAAACITAAAgDqx/A90KLUAYAMAQEzJbACw/RfIW2oBoDUbAABiqtEGgNYs/wOdixUAAKDKLP8DBRAAAAAgkKQCgA0AADElswGgNfM/QCaSCgCt2QAAEFNdNgCY/wGKESgAAAAAAgAA1ID5HyArAgAAlM/8D1CYdAKAHcAAMQXZAQyQlXQCQGt2AAPEVJcdwK2Z/wEyFCUAAAAAAgAAlM8GAKBIAgAAVJr5HyBbAgAAAAQyMcIjgOwABoj5CKA0dgADZCuRAAAANWUDAFAwAQAAqssGACBzAgAAAAQiAAAAQCACAACUxgYAoHgCAABUlA0AQB5SCACeAQoQk2eAAgQNAAAAwBgJAAAAEIgAAAAAgQgAAFAOjwACSiEAAEAVeQQQkBMBAAAAAhEAAAAgEAEAAAACEQAAACCQ2gcArwEGiMlrgAGCBgAAAGDsBAAAKIGXAABlEQAAoHK8BADIjwAAAACBCAAAABCIAAAAAIEIAAAAEMiEhQsXln0OUBW9vb1lnwIUx/UfBrn+E4oOAAAABCIAAABAIAIAAAAEIgAAAEAgAgD8H3siAWJy/ScUAQAAAAIRAAAAIBABAAAAAhEAAAAgkMmtfzxrQU9XtfUt7m7x056eqp9/d3fL8581u6vauvuW1e6/n9b/zQB1uf7UXR2vn3Xn+g8DdAAAACAQAQAAAAIRAMhxSECzFQCgagQAAAAIRAAAAIBABAAAqBwjlEB+BAAAKIEHrQJlEQDIl0UsAIBKqX0AaP2qlNav2SITFrEAAGqk9gEAAAAYOwEAAAACEQDInW0AAADVIQCQAdsAAADqQgAAgCrSPgVyIgBQBLcxgEbap0ApBACy4TYGAFALAgAF0QQAAKgCAQAAAAJJIQB4GXBdpoA0AQAASpdCAACAJFk3AfIgAJAlTQCAcfEEBaB4AgAAAAQiAFA0TQAAgBIJAGRMOxsgQxZNgMwJAJTA/QxgkHUToGCJBABPAq3dzUwGAAAoRSIBgKqxoAUAUE0CAKXRBAAYC1dLIFsCAHkxCAQwRrqmQJEEAEomAwAAFClKALAPuBTWtAAyYa0EyFA6AaD1g4Aoi0EgAIBKSScAUFkyAMCotEyBwggAVIUMANCCiySQFQGACq1sub0BAOQtUACwD7hcMgBAa6aAgGIkFQDsA04mA4gBAI1cG4FMJBUASGl9y30OACAPAgBFkwEARmIKCChArABgG0DtGAcCGMolEehcagHANoAkl7jc8IA4NAGAvKUWAKiLnlmzx3WT0woAGOBiCHRIAKBmrQB3PgCAToQLALYBJNDsFgOA4BdG10CgEwkGANsAggy8igEAAG1IMAAQatObGAAkyVZgID8RA4ApoDS2BTfGAEkAiMMVD2jb5Pb/KOSgZ9bs7r5lmdwRDYMBAETpAKj8ai2rxvdgW0BzAKgjW4GBnOgAUN3bXietgEbulAAAyXYARmUbQPK7AgASoAkA5CHZAGAKKBkyAEALMgAwXskGAFKiFQCE5eoHZC5uADAFVNMY4F4IMIwmADAuKQcAU0CpEgOAUFzxgGylHABIm4YAwCBNAGDsQgcAU0BpkASA5LnEARlKPACYAoqZBNwpgfR4JCiQlegvAuvu7u7pERJC3Cmzfa0YQAX1Le628gVE7wDAIJ0BoO5cxIBMpB8ArIUAEIdBIGBU6QeAUdkKDEBKTQAZAGhNAACAOjEIBHQoRAAYdQpIEwCAlGgCANEDAACkxCAQ0IkoAcBWYACikQGA0AFgVKaAAKgROwGAtgkAAFBLBoGA9gQKALYCA5AYGQBoQ6AAAAAxyQBA3ACgCQBAYmwGAMYrVgAAgPQYBALGJVwA8DxQANIjAwBjFy4AjMoUEACpkgEAAQAAYm0GkAGAiAHAVmAAkiQDAGMRMQAAQKpkAGBUQQOAJgAAqZIBgNaCBgAAQAaAmOIGAE0AAFI19reDyQAQUNwAAAAJkwGAkYQOAJoAACRMBgCaCh0AxkIGAKC+ZACgUfQAMGoTAABqTQYAhokeAMZCEwCAWpMBgKEEAE0AANInAwCDBIAx0QQAIFQGEAMgYQLAf9MEACCCsWcArQBImADwvzwSFIAIZABAABgHGQCAgBlADIDECAD/xyAQAEGMKwNoBUBiBIDx0QQAIA0yAIQlAPwJTQAA4uiZNds4EAQkAIybJgAAKdEKgGgEgHaaADIAAMEzgBgA9SUANGEQCIBoxpsBtAKgvgSANmkCABB8S4BWANSUANCcQSAAYmqvFSAGQI0IACMyCARATG1kADEAakQA6IgmAABJamMcaIAMANUnALRiEAiAyLQCIEkCwChkAAAiay8DiAFQZZPLPgEAoAYZoLtvWRt/djAD2FkH1aEDMDpNAABoe1fAAA0BqA4BYExkAADoZCJogBgAVSAAZEkGACB5HbYCBmOAJABlEQDGyvAiAGQYAyQBKIsAMA4GgQBgqM4zwABJAIokAIyPDAAAmbcCBkkCUACPAc1Fd3d3T4+RIQCi6ORRoU0NzQCmcCFbAsC4zVrQY2UCAAqIAQOEAciWAJBXBtAEACCmnGLAgMb7r0gA4yUAtEkGAIAWBjcG5JQEBo10OxYMYCQCQL46zAB5XzQBoNYNgRbM68JIPAWofWNcWvBQIAAYeFhQhs8LAtomAHREBgCAcREDoHQCQKdkAAAYLw0BKJEAkAEZAADaIwlA8WwCBgDKNzQDeAYG5EoHIBuaAACQeVtAZwDyIABkRgYAgMwJA5A5I0BFvx3MC8IAoD2NGcCwELRBAMiYDAAAhRmpLSAYQAsCQMkZQAwoniksgOSNt1fQ29ub8xlBhdgDkAv7AQAAqCYBIC8yAAAAFSQA5EgGAACgagSAfMkAAABUigBQFTIAAAAFEACq0gQYyABiAAAAuRIAqpUBtAIAAMiVAFAQGQAAgCoQAIojAwAAUDoBoFCzFvSMa0tAzqcDAEA4AkAJZAAAAMoiAJRDBgAAoBQCQGk8HhQAgOIJAGWyLRgAgIIJACWTAQAAKJIAUL7xZgAxAACAtgkA9csAWgEAALRNAKgKGQAAgAIIAHV9TZhxIAAA2iAAVI5WAAAA+REAqkgGAAAgJwJAOhlADAAAYFQCQDpbArQCAAAYlQBQdVoBAABkSABIMANoBQAAMBIBIOVxIDEAAIBhBID0WwFiAAAAgwSA9DOAiSAAAAYJACHGgbQCAAAYIACEawWIAQAAkQkA4VoBYgAAQGQCQO21lwFsDAAAiEkASIFWAAAAYyQApKOTVoAYAAAQhACQlLZbAWIAAEAQAkCC2s4AYgAAQPIml30C5JgB+ha3WcoPZoCenvazBAAAFaQDkLJOJoIGaAgAACRGAEifGAAAwCAjQFHMWtDT9kTQAHNBAAAJ0AEIpPNWwAANAQCA+tIBCKfD/cGDNAQAAOpIByCorLoBGgIAAPWiAxBaVt0ADQEAgLoQAMgyBkgCAAAVJwCQSwwYmgSEAQCA6hAA+BODGwMyTALaAgAA1SEAUFBDYIC2AABAuQQASogBA4QBAIDiCQCUNhc01LAHicoDAAA5EQCoSkNgKHkAACAnAgBVbAgM0/RFY1IBAEAbBADqlASGav36YfEAAKApAYDaJ4E24gEAQFgCAIknAQAAhhIAyIUkAABQTQIABSUBYQAAoAoEAIojDAAAlE4AoBzCAABAKQQAqhUG5AEAgFwJAFQ9D4gEAAAZEgCoZSSQCgAA2iMAkFQqGCQeAAA0JQAQKx60Dga9vb25nREAQCVMLPsEAACA4ggAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIFMbv3jvsXdRZ0JABXS3bes7FMAIBc6AAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgUzo7+8v+xwAAICC6AAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEMrnsE4DirFmz5qabbrr++ut/85vfLF269KGHHnruuedWrFixfv36adOmzZgxY6utttpmm2122WWX3Xfffe+9995hhx3KPmUAgIxN6O/vz/ozoVrWrFlz0UUXnX766VdeeeXq1avH/gd32mmnI4888r3vfe9OO+2U5wkCMG5nn332uH5/woQJEydOnDRp0tSpU6dNm7bJJptsvvnmc+bMmTZtWm7nCBUlAJCylStXfvOb3/zKV76ybNmyTj7nsMMOO+mkk175yldmd2oAdGTChAmZfM622247d+7cPfbYY999991nn3022mijTD4WqkwAIFlnn332xz/+8cceeyyTT5s4ceJHPvKRL37xi+4NACkFgKGmTp16wAEHvOMd7zjiiCOmTJmS+edDRQgAJOjJJ5889thjL7jggsw/+eUvf/kFF1zw8pe/PPNPBqD0ADBom222Of744z/60Y8aECJJAgCp+dWvfnXYYYf97ne/a/E7L3vZy/bcc89ddtlliy222HjjjVetWvXUU0/19fUtWbLkxhtv7Ovra/FnZ86c+aMf/WivvfbK4dwBqEQAGLDddtt9+ctfPvroo/P+IiiYAEBSbrjhhgMPPHD58uVNf7rtttt+6EMfesc73vHiF794pE/o7+9fsmTJf/7nf55++unPPfdc09+ZOXPm1Vdfvccee2R34gBULgAMWLhw4SmnnLLZZpsV83VQAAGAdPziF7/Yb7/9mlb/m2yyyWc+85mPfexjY5/pfOaZZ0488cSTTz656d+Rbbfd9uabb95qq606PmsAMgsArauaF154Yd26dStXrnzuueeWLVt2//3333333bfccstPfvKTkVaOBrzkJS+55JJLdt555yxOHMonAJCI++6779WvfvVTTz3V+KNXv/rVPT097T3U/8orrzzmmGOa7iTef//9f/zjH7d1sgCUEABGsnbt2quuuurb3/72RRddtH79+qa/M2vWrMsuu8z8J2kQAEjBypUr58+ff8cddzT+6PDDD+/p6dlggw3a/vC77rpr3333bRotTj311Pe9731tfzIAVQgAg5YsWfK3f/u3Iy3ubLrppldffbVHQpMAAYAUHHvssd/73vcajx922GHnnXfe5MmdvvH6lltu+Yu/+Is1a9YMOz5nzpylS5fOmDGjw88HoAoBYMC3v/3t448/fu3atY0/2mqrrW699Vbzn9TdxLJPADp15ZVXNq3+d99997POOqvz6n9giOgzn/lM4/FHH330lFNO6fzzAaiOD37wg1ddddXMmTMbf/TII490d3evW7eujPOCzOgAUG9r1qzZZZddfv/73w87Pn369Ntvv32nnXbK6ouef/75Pffcc8mSJcOOv+QlL7n33nsnTpSlARLpAAy48cYb3/SmN61cubLxR1/96lc/8YlPZPVFUDxVC/V2yimnNFb/XV1dX/jCFzKs/ru6uqZMmXLiiSc2Hr/vvvtuuOGGDL8IgCp43ete993vfrfpj0488cSHHnqo8DOCzAgA1NiqVau+9KUvNR7feeedjzvuuMy/7q1vfeu2227bePz888/P/LsAKN3RRx/99re/vfH4c8891/TuA3UhAFBjP/zhDx999NHG4//0T/80adKkzL9u0qRJH/zgBxuPX3PNNZl/FwBV8M///M/Tpk1rPP7d73636Q0IakEAoMZOPfXUxoM77rjjW9/61py+8ZBDDmk8eOedd65YsSKnbwSgRNttt93f/d3fNR5fvXr1aaedVsYZQQYEAOrqrrvuuuWWWxqPf+QjH8lvS+7uu+8+e/bsYQfXrVt3zz335PSNAJTrr//6r6dOndp4/IwzzijjdCADAgB1dcEFFzQenDBhwtFHH53fl06YMGG//fZrPH7vvffm96UAlGjmzJlN27+//h9lnBF0KoNHpEMpLr300saD8+fP33rrrXP93qOPPrrxMXMbb7xxrl8KQIne+c53nnfeeY3Hr7zyyl122aWMM4KOeA8AtfTcc89tuummja9i+cxnPvO5z32upJMCIJ33AAy1du3aWbNmNb4T4Igjjli8eHEe3wi5MgJELd12221NX8S47777lnE6AKRsgw022G233RqP33777WWcDnRKAKCWfvnLXzY9Pm/evMLPBYD0Nb2/3H///c8++2wZpwMdEQCopV/96leNB+fMmbP55puXcToARAwA/f39v/vd78o4HeiIAEAtPfjgg40HX/KSl5RxLgCkb+7cuU2P//GPfyz8XKBTAgDpBICtttqqjHMBIH2bbrpp0+OPPPJI4ecCnRIAqKUnnnii8WDjK7oAIBObbLJJ0+PLly8v/FygUwIAtdT4LLaurq5p06aVcS4ApG/mzJlNj69atarwc4FOCQDU0urVqxsPbrjhhmWcCwDpG6kDsGbNmsLPBTolAFBLL7zwQuNBb7UDICdNXz7T1dU1ZcqUws8FOiUAUEtTp04dY1sAADo30kq/5jN1JABQS03H/ZtuDACAzo30wq/p06cXfi7QKQGAWtp4440bDy5btqyMcwEgfY899ljT43PmzCn8XKBTAgC1tPXWWzcefPTRR8s4FwDSN9Lz/rfZZpvCzwU6JQBQS00vuPfdd18Z5wJA+n772982Pb799tsXfi7QKQGAWnrxi1/cePCxxx576qmnyjgdABL3m9/8pvHg7NmzjQBRRwIAtfSKV7yi6fE77rij8HMBIH033XRT48Hdd9+9jHOBTgkA1NJI19yf/vSnhZ8LAIl75pln7rrrrsbj8+fPL+N0oFOTO/4EKMHcuXNnzpz5zDPPDDt+zTXX/OM//mOuX/1Xf/VXw543usEGG5xxxhm5fikAJbrsssuavghs//33L+N0oFMTvDyVmlqwYMH5558/7OCkSZMeffTRLbbYIqcv/d3vfvfSl7502MEddtjh97//fU7fCEBTEyZMaDyYU1WzcOHCc889d9jBTTfd9PHHH/cmYOrICBB1dcABBzQeXLdu3XnnnZffl15xxRWNBxsjAQDJePzxxy+44ILG40cddZTqn5oSAKirBQsWNL3yfutb38rvS6+88srGg7vttlt+3whAub7xjW88//zzjcff/e53l3E6kAEBgLraYostDjzwwMbjd9xxxzXXXJPHN65ateqqq65qPL733nvn8XUAlO7JJ5/8+te/3nh8r732et3rXlfGGUEGBABq7IMf/GDT4//wD/+Qx9edddZZTz/99LCDU6ZMeeMb35jH1wFQuk9+8pPLly9vPP73f//3ZZwOZEMAoMYOOuigefPmNR6/8cYbzznnnMy/7pvf/Gbjwf3222+zzTbL/LsAKN0ll1zy/e9/v/H43nvvfeihh5ZxRpANAYB6+/SnP930+Ec/+tEnnngiwy8699xzb7vttsbj73//+zP8FgAqYunSpe9617saj0+aNOmb3/xm02cQQV0IANTb2972tqYTOMuWLXvXu961fv36TL7l6aefPv744xuP77jjjocffngmXwFAdTz00EP7779/X19f449OOOEELwCm7gQAau8b3/hG08cBXX755Z/85Cc7//z+/v4Pf/jDjzzySOOPvvjFL06aNKnzrwCgOpYsWTJ//vz777+/8Uevf/3rTzrppDJOCrIkAFB7c+fO/eIXv9j0R//6r/96wgkndPj5xx133Nlnn914/E1vetPChQs7/HAAqqO/v/+UU0557Wtf++CDDzb+dMcdd+zp6bHuQwK8CZgU9Pf3H3bYYRdffHHTnx599NHf+c53ZsyYMd6PXbFixcc+9rHvfve7jT+aNWvWnXfeue2227Z1vgBU7k3AV1999QknnHDzzTc3/emWW255/fXX77jjjm1/PlSHAEAili9f/oY3vKHpPt2BZZuvfe1rhxxyyNg/8Lrrrjv22GOXLl3a+KPJkydffvnl++23XwfnC0AlAsA999xz4YUX/uAHP1iyZMlIv7PDDjtcccUV3vtOMgQA0vH444/vs88+995770i/sNdeex1//PGHHnroxhtvPNLvLF++/OKLLz755JN//vOfN/2FiRMnnnbaaU0fDQFAuQFg0aJFLf7IunXr1q5du2LFir6+vkcffXTp0qW//OUvR31k3Ote97rzzjtvq6226viUoSoEAJLy+OOPH3bYYSPV7gM22GCD1772tbvttttLX/rSmTNnTpkype9//PGPf7zpppuWLFnS4tlBU6ZMOe20097xjnfkc/oAjFUBD+KcOHHiJz7xiS984QtNHzUB9SUAkJpVq1Z96EMfOuOMMzL/5C233PK8887be++9M/9kAKoWAF7zmtf8x3/8x5577pnrt0ApPAWI1EybNu30008///zz58yZk+HHvvOd77zrrrtU/wDJmz9//oUXXvjzn/9c9U+qdABI1ooVK77xjW985StfefLJJzv5nDe/+c2f/exnX/va12Z3agBUrgMwd+7cww8//Jhjjpk7d262nwxVIwCQuFWrVp1//vmnn376Nddc8/zzz4/9D77sZS874ogj3vve97785S/P8wQBKCgATJw4cfLkyRtuuOGMGTM23XTT2bNnb7fddjvvvPOuu+46f/78LbfcMp8zhcoRAIhixYoVN9xww/XXX3/PPfcsXbr0kUceee6551asWNHf3z9t2rQZM2ZstdVW22677c477zxv3ry99957hx12KPuUAQCyJwAAAEAgNgEDAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABDKh7BOAjC1cuLDtP9vb25vpuUCyf1kgMa7/hDK57BOAcVCvAAB0SACgihT6AAA5EQAomVofAKBIAgBFU/EDAJRIACB3Kn4AgOoQAMieih8AoLIEALKh6AcAqAUBgPYp+gEAakcAYHwU/QAAtSYAkFrd39PT0+Kn3d3dBZ4L1NisBa3+KkHt9C12/Yf/JQBQp7q/dXEPAMCoBACqWPQr9AEAciIAUH7dr9wHACiMAEAJpb+KHwCgLAJAXEXW/Sp+AICKEADCKabuV/EDAFSTABBFAXW/oh8AoPoEgPTlWvor+gEA6kUASFl+pb+6HwCgpgSABOVU9yv6AQASIAAkJY/SX90PAJASASARmZf+6n4AgCQJAPWm7gcAYFwEgLrKtvRX9wMABCEAhC791f0AANEIAHWi9AcAoEMCQKzSX90PABCcAFB1Sn8AADIkACRe+qv7AQAYSgCoIqU/AAA5EQCqRekPAECuBICkqn+lPwAArQkAKZT+6n4AAMZIACiZ0h8AgCIJAKVR+gMAUDwBoH7Vv9IfAIC2CQBFU/oDAFAiAaA4Sn8AAEonAFS9+lf6AwCQIQEgdxb+AQCoDgEgXxb+AQCoFAEgL0p/AAAqSACoUPWv9AcAIG8CQMYs/AMAUGUCQJYs/AMAUHECQDaU/gAA1MLEsk8gBap/AADqQgeghOpf6Q8AQFkEgPZZ+AcAoHYEgDZZ+AcAoI4EgCKqf6U/AAAVIQCMj4V/AABqzVOAxkH1DwBA3ekAjJWxHwAAEiAAjM7CPwAAyRAARmHhHwCAlNgD0IrqHwCAxAgAI1L9AwCQHiNATSj9AQBIlQ7AcKp/AAASJgD8CdU/AABpMwLUZvWv9AcAoI50AP6X6h8AgAgmB3xLV+e6u7uL/1IAYFR9i92jIfUAAACEosSHDgkAAEBFqfUhDwIAAFAJyn0ohgAAAJRDxQ+lEAAAgOIo+qF0AgAAkC9FP1SKAAAAZE/RD5UlAAAAmVH3Q/UJAABAp9T9UCOJB4CeWbPLPgWqpbtvWdmnAJCOCtb9PT09TY93d1fuVKEsiQcAACCxun+kEh8YIwEAAKho3a/WhzwIAABAVUp/FT8UQAAAAEqr+1X8UDwBAAAotPRX9EO5BAAAIPfSX9EP1SEAAADqfghEAACA0DIv/RX9UHECAAAElW3pr+6HuhAAACCcDEt/dT/UjgAAAIEo/QEBAABCyKr0V/dD3QkAAJA4pT+QTgBYuHBh2acAAIlX/+p+SEyNA4DqHwBaUPoDSQUA1T8AjETpD6QWAFT/AJBH6a/uhwjqFwBU/wCQefWv9Ic46hcAAIBhlP5AsgHA8j8AZFX9K/0hpjoFANU/AAyl9AfaMLGrJlT/ADCU6h9IuQOg+geAQUp/IP0AAAB0Uv0r/YE6BQDL/wCg9Aei7AFQ/QOA6h+I0gFQ/QNAe9W/0h+oZQAAgOCU/kCgEaCxLP+7xgGQMNU/EKgDoPoHILjxVv9ui0CNA4DRfwAis/APhAsAY+FKB0CSLPwD4fYAGP4BICzVPxAuAKj+AQhL9Q8Uo0IjQEb/AYhJ6Q/E7QCMyiUPgMSo/oGgAcDwDwABqf6BoCNAqn8AAhpX9e8+CKTWAQCAUFT/QNwAYPkfgGhU/0DcESDVPwDRjL36dwcE0uwAAEAcqn8gdACw/A9AKKp/IPQIkOofgDgM/QPVUd0RIJc/ANKg+gcqZWJll/8BIAGqf6BqSggAhn8ACEL1D1RQJd4EDADpseUXqKaiOwCW/wFgKHc9IPomYNdBAOIs/7vrAYkHAHt/AYhA9Q9UWXEBwPAPABGo/oGKq9AIkEshAHWn+geqr6AAYPgHgOSp/oFaqEoHwNUQgFpT/QN1UUQAsPwPQNpU/0CNVKID4IIIQH2p/oF6mVj68r8LIgD1pfoHaiffAGD4BwAAKqXkESArIgDUl+V/oI5yDACW/wFImOofqKkyOwCuiQDUlOofqK+8AoDlfwBSpfoHaq20DoDLIgAJc5sDYgUAj/4EIPLyv9scUGWVeBEYANSC6h9IQPYBwPI/AJFH/wEqTgcAADJjkQsIFwAs/wOQJMM/QDJ0AABgFKp/ICVZBgDL/wCkx+g/kBgdAADolBUuIGIAsPwPQHoM/wDp0QEAgOZU/0CSsgkAlv8BAKAWdAAAoAnL/0CqiggAro8A1IvqH0jYxALmfwAgMap/oL6MAAHAn/DgfyBtnQYA238BSInhHyB5OgAAMA6qfyB0ALD8D0BKDP8AEegAAMB/M/wDBJFjAHCVBCAl7mtA9ADg6Z8AJMPwDxBHXh0AyyQApMR9DYgeACz/A5AMy/9AKDYBA8AoLP8D0QOAp38CEGf5300NSIwOAABxGf4BAso+AFgpASAZbmpAesYdAGz/BSANlv+BmIwAAUBzlv+BJGUcAFwrAagFy/9AWOMLAOZ/AAjCkhaQqiw7AK6VANSCR38CkdkDAAAAgYwjAJj/ASABlv+B4DLrALhcAgBAOgHA8j8ACbD8D2APAAAABJJNALBeAkD1Wf4HGGsAMP8DAABpMAIEAP/N8j8QRAYBwBUTgATmfwCC0AEAAIBARg8ANgAAUHe2/wJk1gFwxQQAgBoxAgRA4iz/A4wjAJj/AQCAlHTUAbBkAkDduZcB0RgBAiBlnv4JMI4AYP4HAAASowMAQLJs/wXIMgC4aAIAQO3oAAAQlJUsIKYRA4ANAADUmu2/AFl2AKyaUDvdfcu6+5aVfRYAiejulq+griaXfQKQC7U+0JqVrKwygH+TUDsCAOlQ9AODzP/kraenZyAAiAGQSACwAYAaUfcD46VazZwYAInvAfDXm+rM9Kv+AcrSWA90/4+STgcYKyNA1I+iH2jN/E+5BjOAFUOoJu8BoDYs+QOZUJUW9i9TQwBq0wGwAYCqUfQD1JftAVD7DoC/wBRM9Q+Mi/mfgo2xMNANgOqwB4DqUvoDmbOMVS7dAKgCewCoojxm/Wct6Jm1wC0HIHvjLeh1A6BcOgBUTlalv3IfAjL/UyO6AVCVAGAHMLWu/hX9AOW+GHi8xACoegfA30+qWfqr+4GxcBerLK8OgCLZA0C9q3+T/QAVkUntbnsAFMAeAOpa/av7gWFsAEiGuSDIlQ4A9av+rfoDbVBNlvsvuY3rtm4AFNEBsAOYilf/6n6Amupb3D1wDR9vo0Y3AMocAfJ3jwwp/QFiEgOgdEaAKIHqH8icDQAV0aJGH/r/UXvDnIaCIBM2AVNpSn8gE1aOq0k3AEqhA0B1l/9V/wAJNwEy6QZoCEBHAcAOYAqg+gcg28u+GAB5dQA02iis+veUT2C8bACoexOg8+u/GABjZwSIylX/+Z8LEIs1rHoRAyBvAgBFUP0DRNNeE2CQGAD5EQCoCtU/AMOIAZAHAYBKLP+r/gHS02ETYJAYANkSAMiX6h/Imx3AQXQYA7I+Hah/AGj9DFDbpyjmjb8AmXMLS6MJMMiT4qBzOgCUzHUcgPESA6ATAgB5MfwDQB5NgEFiALRHAKA0rtoAdE4MgPESAMiF6X8ACmgCDJIBYOwEALJn+AcoTOvy0Q7gULQCYIwEAErgAg1ATg9yFQNgVAIAGTP8A0Dp3RgxAEYJAF4CQJFckQEo5m1uYgA0pQMAABSh9ZJifm90FgNgGAGAQud/XIIBAMolAAAAiTcBgKEEADJj+R8omGeAArRBAAAAiqMJAKUTACiI5X8AgCoQAMiGx/8DMEaaAFAuAYAiWP4HAKgIAQAAKJomAJRIACAD5n8AAOpCACB35n8AaKQJAGWZuHDhwhY/9hBlAABIiQ4AAFAOTQAohQBAp2wAAErhNcAA7REAyJcNAAC0TRMA8iAAAACl0auB4gkAAEB1aQJA5gQAAKBMmgBQMAEAAKg0TQDIlgBAjo8AsgMYgLHQBIAiCQAAQNVpAkCGJrR+EzCE0tvbW/YpQHFc/2GQ6z+h6AAAAEAgAgAAAAQiAAAAQCACAAAABCIAwP+xJxIgJtd/QhEAAAAgEAEAAAACEQAAACAQAQAAAAKZ3PrHPT09XdXW3d3q3eA9s2Z3VVt337IWP1102t1d1fb29+za4qezFlTxvx/vk4exqObf37H/Xa77/av61/+Cbyid/zfp4g+DdAAAgKqrfiKFGhEAAICqL/8DGRIA6EjrJrV+KwCds/wP2RIAAAAgEAEAAChTHZ8nAbUmAFSamUiAmFz/gfwIACWr/oNKAchD9R9UWgzL/1A8AYB82QcMAFApAgCdCvi2GqAKWq8Nt37NFhVh+R9KIQAAAEAgE3t7e1v82AoKAJAHy/9QFh0AcmcbAABAdQgAZMA2AADGxfI/lEgAqDqPggaIyfUfyIkAUL4IrwIwBQTQKOyrACz/Q7kEALJhCggAoBYEAAqiCQCA5X+oAgEAAAACEQAobgpIEwDIlpcBJ8byPxRDAKgBD4IAiCm96396/0RQRwJAJSTzICBNAIBxCfsgoCKX//sWd7v7wFCT/+R/AQAUvvyfU/Wv7ocROwC9vb1dIzNDSbZcjgHIm1V/aMEIUD3UaGjSCwEAYl7/K7L8r/SHUQkAVZHMNoCxcGkGGGQbQFaU/jBGAgDlNAFco4FMeBJoLRSw/O+2AmMnAJALg0AAFMPCP4yXAFAbyYyBDnK9Bohw/c9v+V/pD+0RACoksW0ABoEAxsg2gPFS+kMnBABK5goOkLDMl/+V/pBZAPAqgFqoXRfYTgCgdGncwmp3/c+D0h+yogNAvgwCAXnL6SWyVOf/tc5L/0Wn3W1NCgYJANWS2DaAATIAQMxtAJ03LpT+kAcBoGYS7gLLAABBrv9jWf5X+kN+BACKMMZLsAwAkIy2E4vSH/ImAFROklNAMgBQorrsA05yCmhcy/9Kf6hWAKjL1TOC+naBx54BxABgXILsA67R9b+NU1X6QwkBoPWTQCETY786ywAAQaJah+s+Sn8YLyNAVZTqFNAAGQAg7SmgsS//d1L6D9T9Sn9ogwBQSzXqAnfIOBCQiWQGWWt9/R+6/N956Z/deUE4AkBFaQIMJQMAcbYB1L0JMGpEUfpDnQJAMssnaaj1IlAbF3GtAIBaX/9nLehR+kMVA4B9wFS/FSAGANQxnCj9oTqMANV4Cqimi0DDtHFZFwOANtSojz3qFFAa1/9RKf0hJwIA5Wvv+i4GAKluA6ipDGOJ0h9yJQBUWtpbgYdq+0IvBgBJqvtW4LYp/aFyAaBG/dMgUuoCd3LRH4gBkgAQ5y6W0vXfQ/2hYJOH/e/e3t6FCxcWfRbw/y067e5O7mpDM4BhAIDCtH3pVvRD8YwAVV2QrcB53AwG2wKaAxBHSsk/+a3AlvyhKh0AqIKBW0K29zYZACAn471cq/uhXDoANRCwCTDA4hAQfBtAek0AF3aoZQCo16UzjtrdA8bOrQIIOwVUi+v/GE9A6Q+VDgDeB1xBcZ4H2pTbBhBWAs8DdQ2HqjEClI7SF4Hy5iFxQCbSa2WXeP1v/dUu2lBNAkBtBG8CDOWOAoSaAqpdE8B6DSQYANJbO0lG8k2AodxgAMq9/jd+qcsy1DgA2AZQTZoATUkCQPIrWdVvArgOQ40YAaqZsI8EHVcScBMCEpsCquAjQQe/zlUXaseLwBL09vfs6lrc+G8gcjQCGnV3d1d/Wb3i13/3GojVAahd8zQlBoHaozkA1F2lEovLKSQYAGwDqDWr3QDpTQGNhes/MCp7AJJtArgHAKTXzR5LE8D1H8grANTxupkSg0AAMVVqEAioIx2AlFkEAoIbdQoo1cUs13+gzQBgG0DFGQQCiMkgENAJHYD0uQcAkcXcCjzA9R/IPgCk2jmtETsBADpU03uZnQBAXgHAFFD1GQQCiMkgENAeI0ApkAEAYm4FlgGAEgJAfS+aAbkHAMTk+g+MLwCYAqoFmwEAWgjeBAAYyghQOgwCAcRkEAgoOgDUd9UkPTIAQMzngcoAwNjpAETkHgAQcz3L9R8YawCwDSC9zQDuAQCJGeNmANd/IJsOQIRVkxqRAQCibQUeIAMAY2EEKE0yAEBMMgCQWQAwBVQ7MgBAwCaADAAU1wFI4IoZlnsAQEyu/xDTOAKAJkDCbwdzDwDi0AQYyvUfArIHIHEyAEBMMgBQRABIYMkkSTIAQMAmgAwAZBMATAHVlAwAMF4yAJCqjEeA0rhcJkkGABhXEyAZMgAwjD0AgcgAADFXtWQAoKMAYAqo1mQAgIBNABkAyLcDkMx6SarGlQHcBoDgUrqpjSsDuP5DwowARTT2DGApCEhbqCbAuDKA6z8krJ0AMOoUUErrJamSAQBCPRJ0kAwA6ADENd4M4DYAhBU8A7j+Q2LaDAC2AgfMAJaCgFRFGwQabwZw/YfE5NUBSGyxJGEyAEDM+5oMAGG1HwA0AZLRM2u2cSAguIBNgIEMYBwIAspxD0B6iyVp0woAiHlf0wqAaGwCpqMM4DYAhGoCyAADXP8hbgDwPND0jDcDWAoCUhJzEKi9DOD6D/WlA0CnWwIsBQGhJLy2Nd4tAa7/EDQAaAKkqr1WgNsAUHeRB4E6aQW4/kON6ACQZQZwGwASEHkQqO0M4PoPsQKA54EmrI1xoAHuAUDa0m4CtDcONMD1H6qviA5A8lfJ5GkFANEYBBqgFQBJMgJEjhnAbQCoLxmgkwzg+g/pBwBbgSNoexxo8DbgTgAQahzI9R+qSQeA4mKABSGgXjQBsooBrv+QZgDQBAilkwzgNgDUiAwwTCcZwPUfKmJy2SdAvTNAd9+ytj9h8B6w6LS7szsvgBJ0d3d3WBnXyMA/aSexx/Uf0hkB0gQIqMOJoAEmRIEq81qAPCaCBrj+QynsASADnWeAAe4EQDUZBBpJVn0P13+ocQDQBAgrk1bAIHcCoGpkgFxbAYNc/6EA9gBQrY0Bwwy9BxgVBaov1GaAbDcGDOP6D3UKAL29vQsXLmzxC2EvjnFkHgMGuBkA5Zq1oKdvccQ1/hJjwADXf8iWDgA1iwEDGrvDbglARTKAda6cYsAA13/o3ISufLRuAmS4baj19SXDqXQ6lFMSGFXjjaH1aOmo+1ggGa0v1B5908JY+gDBM0AVtka4/kPlOgAWSKLJtSHQgp1kQCnc5oppCLTg+g9FPwZUjKbFw4J0ZoBaG2N7JOZDgVo/LEgogujvAXBljEwMAGpNBmibGAApBwBNAEalIQDUlwzQCQ0BiPsmYJdFBkgCQB3JAJ2TBCC1TcCjvhMAhhmaAcp6cBAAxRuaAUQmqHcHYNRBIH/JGbUtoDMAVJYmQK5tAZ0BSPZFYJ6Vxqh0BoC6vyHYza49OgNQywBgEIhsNTYERAKgXDJAMRr/7YkEUNcOgGsiHRppRkgwAAojA5RipH+ZggGUHwA0ASiFXgFQJBmgOpr+G5YKoBKPAR3KX0sA6s6eYKD6igsAY3kvmAsiAHUnAwAVV2gHwLuBAYhABgCqrEIjQANcDQFIgAwAVFbRAcAgEAAM5a4HRO8AAECoJsBABhADgJQDgCYAAEGMPQO49wGJdwDsBgYgCBkAqJrqjgC5CAKQBhkAqJTSAoBBIADimLWgZ1xbAnI+HSC0MjsAMgAAocgAQBVUdwQIANIjAwDRA4AmAADReDwoEL0DIAMAEI1twUDoAAAAAckAQOgAoAkAQEDjzQBuhUA6AUAGACCmcWUAt0IgqQAwRi58ACRGBgDiBoCxNAEAIPhrwowDAekEAINAAESmFQBEDAAyAACRyQBAxAAwRi55ACSpjQzgngjUPgDYDABAZOPdEmBdDKh9ADAIBABaAUCsACADAMB4M4A7I1DvAAAAtDcOJAYAdQ0ANgMAQNutADEAqF8AkAEAoO0MYCIIqGUAkAEAoO1xIK0AoJYBAADovBUgBgB1CgCaAADQYStADADqFABkAAAYpr0MYGMAUJsAIAMAwDBaAUDiAUAGAIBsWwFiAARUswAAAGTYChADIKD6BQBNAABoqu0MIAZAKJO7aqi3t3fhwoVlnwUAVDQD9C1us5QfzAA9Pe1nCaDi6tcBGKAPAAB5TAQN0BCAhNU1AMgAANCaGACkFgBkAAAYVYcZYDAGSAKQjHoHAACggFbAADEA0lDLTcAAQMH7gwfZKAx1pwMAAIFk1Q3QEID60gEAgHCy6gZoCEAdCQAAEFSGMUASgBoRAAAgtGxjwNAkIAxANQkAAMD/PS00wySgLQDVJAAAADk2BAZoC0B1CAAAQEExYIAwAOUSAACAQueChhr2IFF5AAogAAAAZTYEhpIHoAACAABQlYbAME1fNCYVQIcEAACg6klgqNavHxYPIHoA6O5bVvYpAECyyk0CbcQDIP0AAADETALASAQAACAzkgBUnwAAAOSYBIQBqBoBAADIlzAAlSIAAADFEQagdAIAAFB+GJAHoDACAABQxTwgEkBOBAAAoDaRQCqAzgkAAEDtU8Eg8QDSDwC9vb2ZfM7ChQvH/steM15rXhIJEDAetA4GWZUTUAsTyz6BqhjX33wVJAAANSUAtJ8BxAAAAGpHAOioAygDAABQLwLAcDIAAAAJEwCa6P0fY/9940AAANSFADAirQAAANIjALQiAwAAkBgBIPsMIAYAAFBZAkD2WwK0AgAAqCwBYKy0AgAASIAAMA5tvCdcBgAAoFIEgPExDgQAQK0JAO0wDgQAQE0JAIWOA4kBAACUSwAodBzIRBAAAOUSADqlFQAAQI0IAOVkAK0AAABKIQCUPA4kBgAAUCQBoBKtADEAAIBiCACVaAWYCAIAoBgCQC60AgAAqCYBoIqtADEAAICcCAD5ai8DiAEAAOREAKhuK8DGAAAAMicAFEQrAACAKhAAatMKEAMAAOicAFA0MQAAgBIJAOVoOwOIAQAAdEIAqGUrQAwAAKA9AkDJxAAAAIo0udBvYwQDGWDhwoXt/fHBDNDT05PpeQEAkBodgArppBUwQEMAAIDWBICkJoIGiAEAAIxEAKgiMQAAgJzYA5DsxoABtgcAADCUDkCIboCGAAAAA3QAAnUDNAQAANABiNgN0BAAAAhLByBuN0BDAAAgIAGgrjKMAZIAAEAcAkC9DU4ESQIAAIyFAJCIbBsCkgAAQKoEgKRkHgMkAQCAxAgACcp8LmjA0KcGCQMAADUlAKQsj4bAAG0BAICaEgDSl18M0BYAAKgdASCKnOaChhIGAACqTwAIp4AkMCwMyAMAANUhAMRVTBIYIA8AAFSEAEC+mwSakgcAAMoiAFBCQ6B1HhAJAADyIwAwYhIoJQyMFAkGCAYAAB0SAKhoW2BcwWAoIQEAoAUBgFomgQ5DAjCqvsX+KgGkSQCgfgNCAAC0TQCgfcIAAEDtCABkQxgAAKgFAYB8w4A8AABQKQIAuZMHAACqQwCgaPIAAECJBACqlQcGSAUAADkRAKhNKhAMAAC6Ovb/ALl+dA43ehv9AAAAAElFTkSuQmCC"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:9)_46
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color red.\nthe 2th action is Colorize the top layer of the original shape with the color blue.\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is Cut the right side of the shape\nthe 5th action is Stack the original shape on top of the {'layer1': 'RyRyRyRy'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'WgWgWgWg'}.\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is Colorize the top layer of the original shape with the color purple.\nthe 9th action is Stack the original shape on top of the {'layer1': 'SgSgSgSg'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:9)_87
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is Colorize the top layer of the original shape with the color yellow.\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is Colorize the top layer of the original shape with the color green.\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is Colorize the top layer of the original shape with the color red.\nthe 7th action is Stack the original shape on top of the {'layer1': 'SpSpSpSp'}.\nthe 8th action is Cut the right side of the shape\nthe 9th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_47
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is Stack the original shape on top of the {'layer1': 'CgCgCgCg'}.\nthe 3th action is Colorize the top layer of the original shape with the color yellow.\nthe 4th action is Stack the original shape on top of the {'layer1': 'CuCuCuCu'}.\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is Colorize the top layer of the original shape with the color yellow.\nthe 9th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:9)_49
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAgAAAAIACAYAAAD0eNT6AAAGc0lEQVR4nO3YsQnDQBQFQdmoAQcuTSpSrSlQCXYJDgx3gp2JD+6Fy18WAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABnmM+giYa9u2z+wNwH08Zw8AAMYTAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAhaZw8A7uV4vWdPAP60X+fPNy4AABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIAgAQAAQQIAAIIEAAAECQAACBIAABC0zh4A3Mt+nbMnAAO4AABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAAGDp+QLfRwk8SDa9QAAAAABJRU5ErkJggg=="
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'SySySySy'}.\nthe 2th action is Stack the original shape on top of the {'layer1': 'CbCbCbCb'}.\nthe 3th action is Stack the original shape on top of the {'layer1': 'RcRcRcRc'}.\nthe 4th action is Colorize the top layer of the original shape with the color white.\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is Stack the original shape on top of the {'layer1': 'RwRwRwRw'}.\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is rotate the shape counterclockwise 90 degrees\nthe 9th action is Stack the original shape on top of the {'layer1': 'RpRpRpRp'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_286
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color purple.\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is Colorize the top layer of the original shape with the color cyan.\nthe 5th action is Colorize the top layer of the original shape with the color red.\nthe 6th action is Stack the original shape on top of the {'layer1': 'SpSpSpSp'}.\nthe 7th action is Stack the original shape on top of the {'layer1': 'CwCwCwCw'}.\nthe 8th action is Cut the right side of the shape\nthe 9th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_229
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is Stack the original shape on top of the {'layer1': 'CyCyCyCy'}.\nthe 3th action is Stack the original shape on top of the {'layer1': 'WuWuWuWu'}.\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is Stack the original shape on top of the {'layer1': 'CuCuCuCu'}.\nthe 9th action is Stack the original shape on top of the {'layer1': 'CyCyCyCy'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:9)_334
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color cyan.\nthe 2th action is Colorize the top layer of the original shape with the color red.\nthe 3th action is Colorize the top layer of the original shape with the color purple.\nthe 4th action is Colorize the top layer of the original shape with the color blue.\nthe 5th action is Stack the original shape on top of the {'layer1': 'RpRpRpRp'}.\nthe 6th action is Colorize the top layer of the original shape with the color cyan.\nthe 7th action is Stack the original shape on top of the {'layer1': 'RgRgRgRg'}.\nthe 8th action is rotate the shape clockwise 90 degrees\nthe 9th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_439
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAgAAAAIACAYAAAD0eNT6AAAMb0lEQVR4nO3czY0dxxmGUbbBBByHsjFAAdopNO8MeABlozgUggxZsk1T5PSdO/1TVc856wF0N+rveWvB7dOnT79+APjDy8vLdvdvAM73lwv+GwDAYAQAAAQJAAAIEgAAECQAACBIAABAkAAAgCABAABBAgAAgj4++od//ds/z/0lwKl++en7u38CMBAvAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAj6+Ogf/vLT9+f+EgDgMl4AACBIAABAkAAAgCABAABBAgAAggQAAAQJAAAIEgAAECQAACBou/sHcJ1Pnz79+ujf/uPvP5/7Y7jcDz9+99Dfvby8+C5AgBcA/sTxB1ifAIh4y/oHYH0CgP9j/QM0CIAA6x+ALwkA/sv6B+gQAIuz/gH4GgHAv1n/AC0CYGHWPwDfIgCw/gGCBMCirH8AXiMA4qx/gCYBsCDrH4A9AiDM+gfoEgCLsf4BeIQAiLL+AdoEwEKsfwAeJQCCrH8ABMAirH8A3kIAxFj/APxGACzA+gfgrQRAiPUPwH8IgMlZ/wA8QwBEWP8AfE4ATMz6B+BZAiDA+gfgSwJgUtY/AO8hABZn/QPwNQJgQtY/AO8lABZm/QPwLQJgMtY/AEcQAIuy/gF4jQCYiPUPwFEEwIKsfwD2CIBJWP8AHEkALMb6B+ARAmAC1j8ARxMAC7H+AXiUABic9Q/AGQTAIqx/AN5CAAzM+gfgLAJgAdY/AG8lAAZl/QNwJgEwOesfgGcIAAAIEgATP/9b/wA8SwAAQJAAGIz1D8AVBAAABAmAgVj/AFxFAABAkAAYhPUPwJUEAAAECYABWP8AXE0AAECQALiZ9Q/AHQQAAAQJgBtZ/wDcRQAAQJAAuIn1D8CdBAAABAmAG1j/ANxNAABAkAC4mPUPwAgEAAAECYALWf8AjEIAAECQALiI9Q/ASAQAAAQJgAtY/wCMRgAAQJAAOJn1D8CIBAAABAmAE1n/AIxKAABAkAA4ifUPwMgEAAAECYATWP8AjE4AAECQADiY9Q/ADAQAAAQJgANZ/wDMQgAAQJAAOIj1D8BMBAAABAmAA1j/AMxGAABAkAB4J+sfgBkJAAAIEgDvYP0DMCsBAABBAuBJ1j8AMxMAABAkAJ5g/QMwOwEAAEEC4CTWPwAjEwAnPf8DwMgEwAmsfwBGJwDewPoHYBUC4GDWPwAzEAAPsv4BWIkAOJD1D8AsBMADrH8AViMADmL9AzATAbDD+gdgRQLgANY/ALMRAK+w/gFYlQB4J+sfgBkJgG+w/gFYmQB4B+sfgFkJgK+w/gFYnQB4kvUPwMwEwBesfwAKBMATrH8AZicAPmP9A1AhAN7I+gdgBQLgD9Y/ACUf7/4BM7H+mdEPP353908ABiQAHlz/jj+zcfiB1wgAWIzDDzwiHwDWP6tw+IG3yAcAzM7hB56RDgDrn5k5/MB7pAMAZuTwA0fYPkRZ/8zm7MP/8vKS/R5AkRcAGJzDD5wh+T++9c8MHH7gTF4AYDAOP3CF3IfA+mdUDj9wJS8AcDOHH7hD6sNg/TMShx+4kxcAuJjDD4wg86Gw/rmbww+MxAsAnMzhB0aU+HBY/9zB4QdG5gUADubwAzNY/kNi/XMVhx+YiRcAeCeHH5jR0h8W658zOfzAzLwAwECH39EHrrLsx8b652gOP7ASLwCww+EHVrTkx8f65wgOP7AyLwDwBYcfKFjuY2T98yyHHyjxAkCeww8ULfVxsv4Z5fg7/MDovACQ5PADdakAsP5x+AEWC4BHnv/pcvgBFg2APdZ/k8MPsHAAWP98yeEHCATAHuu/w+EHiASA9c9vHH6AWADssf7X5vADBAPA+u9y+AHCAbDH+l+Pww8QDwDrv8XhBzjWtAGwx/pfg8MPcI4pA8D6X5/DD3CuKQNgj/U/L4cf4BrTBYD1vyaHH+Ba0wXAHut/Lg4/wD2mCgDrfx0OP8C9pgqAPdb/+Bx+gDFMEwDW/9wcfoCxTBMAe6z/MTn8AGOaIgCs//k4/ABjmyIA9lj/43D4AeYwfABY/3Nw+AHmMnwA7LH+7+XwA8xp6ACw/luH39EHuM7QAbDH+r+eww+whmEDwPofi8MPsJZhA2CP9X8Nhx9gTUMGgPV/P4cfYG1DBsAe6/88Dj9Aw3ABYP3fw+EHaBkuAPZY/8dy+AGahgoA6/86Dj9A21ABsMf6fz+HH4ChAsD6P5fDD8CQAbDH+n+Oww/AsAFg/R/P4Qdg+ADYY/0/zuEHYIoAsP6P4fADMFUA7LH+X+fwAzBdAFj/z3P4AVj2BcD6/zOHH4CpA8D6fxuHH4DEC4D1/zuHH4BlAsD63+fwA5B7ASivf4cfgCUDwPr/OocfgPQLQG39O/wALB8A1v//OPwA3GmoF4DC+nf4AUgFQH39O/wAjGSYF4BV17/DD8CIhgmA1Tj8AIxsG+H5f6X17/ADMAMvAAdx+AGYyekHZvX17/ADMCMvAIMcfkcfgCudenRWXP8OPwAr8AJw0/F3+AG402lHaKX17/ADsBovAK9w+AFY1SlHafb17/ADsDovAJ9x+AGoOPxIzbj+HX4AatIvAA4/AFVbcf07/ADUpV4AHH4A+N1WWP8OPwCEXgAcfgD4um3F9e/wA0DoBcDhB4DHbCusf4cfAEIvAA4/ADxnm3H9O/wAEHoBcPgB4BjbDOvf4QeA0AuAww8A59hGXP8OPwCEXgAcfgC4xjbC+nf4ASD0AuDwA8A9tjvWv8MPAKEXAIcfAMawXbH+HX4ACL0AOPwAMKbtjPXv8ANA6AXA4QeAOWxHrH+HHwBiLwBHHH9HHwCutb1n/b+Xww8AoX8J0OEHgHttV65/hx8AQi8ADj8AjGU7c/07/AAQegFw+AFgbNuR69/hB4DQC4DDDwBz2d6z/h1+AAi9ADj8ADC37S3r3+EHgNALgMMPAGvZXlv/Dj8AhF4AHH4AWNv2+fp3+AHgQ8K/AIXba6kCawIPAAAAAElFTkSuQmCC"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color white.\nthe 2th action is Stack the original shape on top of the {'layer1': 'SbSbSbSb'}.\nthe 3th action is Colorize the top layer of the original shape with the color white.\nthe 4th action is Cut the right side of the shape\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is Stack the original shape on top of the {'layer1': 'CcCcCcCc'}.\nthe 7th action is Stack the original shape on top of the {'layer1': 'WgWgWgWg'}.\nthe 8th action is Colorize the top layer of the original shape with the color blue.\nthe 9th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_133
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAgAAAAIACAYAAAD0eNT6AAAKKUlEQVR4nO3d62ocVxCFUTn4FWXIEwaih0ywc1NkSd0zc7q7qvZavw0zYEx9+xjLT08AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACc5MtZH0RNz8/Pf1z9HQA43y8XfCYAcDEBEMz6B8glAAAgkAAIZf0DZBMAABBIAASy/gEQAAAQSACEsf4B+E4AAEAgPwkwyC3r/+W334/9Mpzu+ddvu36d33vI+PPuBYCfOAAA8wmAEP7uH4DXBAD/Y/0DZBAAAax/AN4SAPzL+gfIIQCGs/4BeI8A4AfrHyCLABjM+gfgIwIA6x8gkAAYyvoH4DMCIJz1D5BJAAxk/QOwRQAEs/4BcgmAYax/APYQAKGsf4BsAmAQ6x+AvQRAIOsfAAEwhPUPwC0EQBjrH4DvBMAA1j8AtxIAQax/AP4hAJqz/gG4hwAIYf0D8JoAaMz6B+BeAiCA9Q/AWwKgKesfgEcIgOGsfwDeIwAasv4BeJQAGMz6B+AjAqAZ6x+AFQTAUNY/AJ8RAI1Y/wCsIgAGsv4B2CIAmrD+AVhJAAxj/QOwhwBowPoHYDUBMIj1D8BeAqA46x+AIwiAIax/AG4hAAqz/gE4igAYwPoH4FYCoCjrH4AjCYDmrH8A7iEAACCQAGj8/G/9A3AvAQAAgQRAMdY/AGcQAAAQSAAUYv0DcBYBAACBBEAR1j8AZxIAABBIABRg/QNwNgEAAIEEwMWsfwCuIAAAIJAAuJD1D8BVBAAABBIAF7H+AbiSAACAQALgAtY/AFcTAAAQSACczPoHoAIBAACBBMCJrH8AqhAAABBIAJzE+gegEgEAAIEEwAmsfwCqEQAAEEgAHMz6B6AiAQAAgQTAgax/AKoSAAAQSAAcxPoHoDIBAACBBMABrH8AqhMAABBIACxm/QPQgQAAgEACYCHrH4AuBAAABBIAi1j/AHQiAAAgkABYwPoHoBsBAACBBMCDrH8AOhIAABBIADzA+gegKwEAAIEEwJ2sfwA6EwAAEEgA3MH6B6A7AQAAgQTAQax/ACoTAAc9/wNAZQLgANY/ANUJgBtY/wBMIQAWs/4B6EAA7GT9AzCJAFjI+gegCwGwg/UPwDQCYBHrH4BOBMAG6x+AiQTAAtY/AN0IgE9Y/wBMJQAeZP0D0JEA+ID1D8BkAuAB1j8AXQmAd1j/AEwnAO5k/QPQmQB4w/oHIIEAuIP1D0B3AuAV6x+AFALgRtY/ABMIgL9Z/wAk+Xr1F+jE+qej51+/Xf0VgIIEwM717/jTjcMPfEYAwDAOP7BHfABY/0zh8AO3iA8A6M7hB+4RHQDWP505/MAjogMAOnL4gRViA8D6pxuHH1gpNgCgC4cfOEJkAFj/dODwA0eKDACozOEHzhAXANY/VTn8wJniAgDSDv/Ly8uXH5/jP7wCUgPA+ifx8AM8pQcAVODwAxXEBID1z9UcfqCSmACAqzj8QEURAWD9cwWHH6gsIgDgTA4/0MH4ALD+OYvDD3QyPgDgaA4/0NHoALD+OZLDD3Q2OgCg2+F39IGzjA0A65/VHH5gkrEBAKs4/MBEIwPA+mcFhx+YbGQAwCMcfiDBuACw/rmXww8kGRcAcCuHH0g0KgCsf6ocf4cfqG5UAMBeDj+QLioArH8cfoBhAbDn+Z9cDj/A0ADYYv1ncvgBBgeA9c9bDj9AQABssf5zOPwAIQFg/fOdww8QFgBbrP/ZHH6AwACw/nM5/ADBAbDF+p/H4QcIDwDrP4vDD7BW2wDYYv3P4PADHKNlAFj/8zn8AMdqGQBbrP++HH6Ac7QLAOt/Jocf4FztAmCL9d+Lww9wjVYBYP3P4fADXKtVAGyx/utz+AFqaBMA1n9vDj9ALW0CYIv1X5PDD1BTiwCw/vtx+AFqaxEAW6z/Ohx+gB7KB4D134PDD9BL+QDYYv1fy+EH6Kl0AFj/WYff0Qc4T+kA2GL9n8/hB5ihbABY/7U4/ACzlA2ALdb/ORx+gJlKBoD1fz2HH2C2kgGwxfo/jsMPkKFcAFj/13D4AbKUC4At1v9aDj9AplIBYP2fx+EHyFYqALZY/49z+AEoFQDW/7EcfgBKBsAW6/8+Dj8AZQPA+l/P4QegfABssf73c/gBaBEA1v8aDj8ArQJgi/X/OYcfgHYBYP3fz+EHYOwLgPX/M4cfgNYBYP3fxuEHIOIFwPr/i8MPwJgAsP63OfwAxL0AJK9/hx+AkQFg/b/P4Qcg+gUgbf07/ACMDwDr/z8OPwBXKvUCkLD+HX4AogIgff07/ABUUuYFYOr6d/gBqKhMAEzj8APwlB4AW8//k9a/ww9AB14AFnH4Aejk8ACYvv4dfgA68gJQ5PA7+gCMCYCJ69/hB2ACLwAXHX+HH4CRATBp/Tv8AEzjBeATDj8AUx0SAN3Xv8MPwHReAF5x+AFIsTwAOq5/hx+ANNEvAA4/AKm+Jq5/hx+AdFEvAA4/ACwOgMrr3+EHgKAXAIcfAA4MgGrr3+EHgKAXAIcfAE4KgArr3+EHgKAXAIcfAC4IgKvWv8MPAEEvAA4/AFwcAGeuf4cfAIJeABx+ACgUAEevf4cfAIJeABx+ACgaAEesf4cfAIJeABx+AGgQAKvWv8MPAEEvAA4/ADQLgEfWv8MPAEEvAA4/ADQOgFvXv8MPAEEvAA4/AAwJgD3r3+EHgLAXgBXH39EHgEIBsLX+H+XwA0DQTwJ0+AGgaAAcsf4dfgAIegFw+AGgQQCsWv8OPwAEvQA4/ABQ25eV69/hh7qO/lc9QOALgMMPAI0D4NaF4PADQNALgMMPAEMCYM/6d/gBIOgFwOEHgIEB8NH6d/gBIOgFwOEHgNm+vl7/Dj8APEX4E81OZjH41NuaAAAAAElFTkSuQmCC"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is Cut the right side of the shape\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is Stack the original shape on top of the {'layer1': 'WrWrWrWr'}.\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'SuSuSuSu'}.\nthe 8th action is rotate the shape clockwise 90 degrees\nthe 9th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:9)_35
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'RcRcRcRc'}.\nthe 2th action is Cut the right side of the shape\nthe 3th action is Stack the original shape on top of the {'layer1': 'SySySySy'}.\nthe 4th action is Stack the original shape on top of the {'layer1': 'RpRpRpRp'}.\nthe 5th action is Stack the original shape on top of the {'layer1': 'CcCcCcCc'}.\nthe 6th action is Cut the right side of the shape\nthe 7th action is Colorize the top layer of the original shape with the color cyan.\nthe 8th action is Stack the original shape on top of the {'layer1': 'RuRuRuRu'}.\nthe 9th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABAAAAATICAIAAAANxCANAABUOElEQVR4nO3dCZRcZZk/4M5GSMIWIBK2AUUUwiARVDQwogdRdgSpQBRHHNwPouOM42FGB/Q46ug4o4yOOLgEFALdLMOOsoqyCCJLQEUigoDsBAIBEiD9P9r+29hVXV1ddZdveZ7j8ejt7qqvO9233t/7fvfWhMHBwT4AACAPE+teAAAAUB0BAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGRkct0LgEotW7Zso402evbZZ1t+9D3vec8JJ5xQ+aIA6Mmpp546rs+f+EeTJ0+eOnXq9OnT11tvvVmzZm200UaTJk0qbY0QkAmDg4N1rwGq853vfOeII44Y7aPrr7/+Aw88MGXKlGoXBUBPJkyY0PuDrLHGGn/913+94447vupVr9pvv/022WSTIpYGIRIAyMvuu+9+2WWXtfmE8847b5999qlwRQAEEQBGPOAuu+xy+OGHv+td75o82XYJUuMaADJy3333XXHFFcXOkQFIz+Dg4E9+8pP3vOc92267bX9/f93LgYIJAGRk0aJFq1atav85Z5999mhXCACQmyVLlhxyyCHve9/7Vq5cWfdaoDACABn5/ve/P+LIzJkzRxx58sknzz///AoXBUDoTjjhhD333PO5556reyFQDAGAXNx2220333zziINf+tKXmjd3nnbaaRWuC4BSDLb1wgsvrFy58oknnrj77ruvvPLK//7v/z744IOnT58+2qNdfvnlRx11VLXfAZTFRcDk4uijj/7CF76w+pF11lnnoYce2nvvvUdcFjxt2rSHHnporbXWqnyNABR2EXAXFc5TTz31la985Ytf/OKTTz7Z8hN+8IMfvPnNb+5qjRAQEwCyMDg4uGjRohEH3/rWt06dOvWggw4acfyZZ54555xzKlwdAEFYa621PvnJT1577bVbbrlly0/49Kc/XfmioHgCAFn48Y9/fPfdd484eMghhwzFgObWkXsBAWRrzpw5559/fsvtQFdfffXPfvazOhYFRRIAyMLJJ5884sj666+/xx579PX1bbrppq95zWtGfPQHP/jB448/XuECAQjInDlzPvGJT7T80CWXXFL5cqBgAgDpW7ly5cDAwIiDBx100PA7/h544IHNX3LmmWdWtUAAgvOhD31o0qRJzccvv/zyOpYDRRIASN8FF1ywdOnSlvt/hjRfBmAXEEDmNtxww7lz5zYfb95QCtERAMjx9v+zZs164xvfOPx/t9566+22227E51x22WUPP/xwJQsEIETbb79988FHHnmkjrVAkQQAEvfEE080v7HXwQcfPGKw2zwEeOGFF04//fTyFwhAoDbYYIPmg0888UQda4EiCQAk7vTTT3/22WdHHDz00ENHHLELCIBO3klgnXXWqWMtUCQBgOz2/2yyySa77rrriINz58598YtfPOLgT37yk/vuu6/kBQIQqJa3g5s1a1Yda4EiCQCk7N57773yyitHHGw0GhMntvjNb74X0KpVq/r7+8tcIADhuv3225sP7rTTTnWsBYokAJCyU045ZdWqVWPu/xktANgFBJCtFStW3Hjjjc3HX//619exHCjShJb72yANO+ywwy233LL6kS222OK3v/1t81v/DvX7N9lkkwcffHDE8TvvvLN5dxAA4Wh5Vu+xwjn55JMPO+ywEQenT59+3333rbfeer08MtTOBIBk3XrrrSOq/76+vvnz57d8nfjDH8PEiQcccEDz8dNOO62cBQIQqJUrV37uc59rPv6+971P9U8CBACS1Xz5b5v9P0PcCwiAvr6+j33sY7/4xS9GHNx8880/85nP1LQiKJItQKRpcHBwyy23/N3vfrf6wZe+9KV33HFHm6967rnnXvSiFzXf9uGXv/zlNttsU85KAQhoC9Dy5cs/+tGPfutb3xpxfJ111rniiite+cpXdrtGCIgJAGm68sorR1T/fX19hxxySPuvmjJlyj777NN83BAAIHlLly497rjjtttuu+bqf6ONNrrwwgtV/yTDBIA0vfe9720+g99yyy0t39d9dWeeeebb3va2EQe32WabX/7yl0WvEYASJwCLFi1q8yWDg4MrVqx4+umnH3jggXvvvffGG2+85ZZbmm8c19fXt8ceeyxcuHCTTTYpdMlQJwGABK1YsWL27NkjdvJsu+22zRs6mz399NMbbrjhM888M+L4jTfeOHfu3KJXCkABRru7Q49e+cpXfvrTn95vv/3KeHCokS1AJOj8889v3sff/vLfYdOnT3/LW97SfNwuIIB8zJgx4xvf+MYNN9yg+idJAgAJOvnkk5sPjnkBQPt3BHMzUIB8LF++/IMf/OCmm2565JFH2gJKemwBIjWPP/747NmzV6xYsfrBuXPntnxDx5aWLl36ohe96Pnnnx9x/Nprr915552LWykAQW8BGrbXXnt99atf3XrrrUt9FqiMCQCpOf3000dU/+Nq//f19c2cOfMNb3hD83G7gADydOGFF77iFa/4j//4j7oXAsWYXNDjQNDv/zVhwoRxle+zZs1qPtjf3//lL3954kSxGSACY+5xWLVq1fLly5988sn77rvvnnvuuemmm6677rrLL7985cqVzZ/87LPPfvzjH7/rrruOO+44LwTEzhYgknLPPfdsscUW5f1WX3HFFbvttltJDw5A7W8E9uijjy5cuPCzn/1s880khhxzzDHHHntsF48M4RBhScopp5xSaqa1CwggbRtssME//MM//PrXv37jG9/Y8hM++9nPXnPNNZWvC4pkAkBSXvGKVyxevLi8x581a9bvf//7yZPtnQNIcwIwbMWKFfvss8+ll17a/KE99tjjhz/8YS8PDvUyASAdt9xyS6nVf19f38MPP3zZZZeV+hQAhGDq1KknnXTS+uuv3/yhiy++uJN3loRgCQAkfvlv4ewCAsjEJptscuSRR7b80AUXXFD5cqAwAgCJGBwcXLRo0YiDM2bMePrppwe7dcoppzQ/0VlnndXyBhEApOd973tfy+NXX3115WuBwggAJOKKK6649957Rxzcd999p02b1vVj7rfffs1f/vjjj1900UVdPyYAEdl000232mqr5uO2ABE1AYBEnHzyyc0HG41GL4+51lpr7bXXXs3H7QICyMdOO+3UfPCxxx6rYy1QDAGAFKxYseKMM84YcXDGjBkty/dxmT9/fvPBc8455+mnn+7xkQGIwgYbbNB8cLR3CYAoCACk4Lzzzms+F++zzz7Tp0/v8ZH33Xff5gdZvnz5eeed1+MjAxCFddZZp/mgNwMman59Sfb+Pz3u/xkyY8aMvffeu/n4aaed1vuDAxC+ZcuWdZgKIBYCANFbunRp8+3Ypk+f3rJw78IhhxzSfPCCCy548sknC3l8AEL28MMPNx/cbLPN6lgLFEMAIHoDAwPN9+UsZP/P8EPNmDFjxMFnn332//7v/wp5fABCdt111zUf3HbbbetYCxRDACB6Zdz/Z3XTpk3bd999m4+7FxBA8n7961//7ne/az6+884717EcKIYAQNx+97vf/fjHPy5v/0+bewFdfPHFbgMHkLb/+q//anl8n332qXwtUBgBgLidcsopg4ODIw7uvffezZt2erH33nuvtdZaIw4+99xzzfceBSAZN95443e/+93m47vuumvLdweDWAgAxK3s/T9D1lxzzf3226/5uF1AAKm67777Dj744BUrVjR/6BOf+EQdK4LCCABE7Kabbrr11ltHHJw2bVoZk9mWu4B+9KMfPfjgg4U/FwD1uvbaa3feeec777yz+UN77rlnywvDICICAKm1//faa69i9/8MP2zzXZ9feOGFgYGBwp8LgLpcd911f/u3fztv3rz77ruv+aOzZ89uuSkI4jK57gVAl1atWrVo0aIK9v8MmTp16v7779/8jmOnnnrqkUceWcYzAtCLTnZpPv/88ytWrFi2bNkjjzzyq1/96oYbbrj77rtH++T111//oosumj17dtErhapNaL6AEqJw2WWX7b777iMOrrnmmg8//HDzBbuFOPfcc/fff/8RBydMmHD33XdvvvnmZTwjAJ2YMGFC2U8xZ86cc845x7W/pMEWIGLV3Iwf2qhTUvXf19f3lre8Zd111x1xcHBw8LTTTivpGQEIwWGHHXbttdeq/kmGAECUnn322TPPPLOy/T9D1lhjjQMOOKD5uHsBAaTqVa961VVXXfW9731v7bXXrnstUBgBgCide+65TzzxxIiDa665Ztl3Zmh5L6AbbrhhyZIlpT4vAFVaa6213v3ud1911VXXX3/9vHnz6l4OFMxFwERp2rRpxxxzzIiDf/VXf1V2h+bNb37zscce23zlTHMaASBwEyZMmDx58tSpU9daa62ZM2dutNFGW2yxxY477jhv3ry5c+dOnqxGIlkuAgYAgIzYAgQAABkRAAAAICMCAAAAZEQAAACAjAgAAACQEQEAAAAyIgAAAEBGBAAAAMiIAAAAABkRAAAAICMCAAAAZGRCo9Goew0A1GBgYKDuJQBQAxMAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIyOT2H+7v769qJVCF+fPnt/moX3hy+50HIEMmAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZmVz3AgBiNX/+/P7+/rpXka9Go1H3EkjHwMBA3UuA6ggAAOM2f/78upcAAF0SAAC6LP21/wGIkQAA0BFdfwDSIAAAdFP6a/8DECkBAGBUuv4ApEcAABh36a/9D0C8BACAv6DrD0DaBACA8ZX+2v8ARE0AAND1ByAjAgCQry7qfu3/WAws8i/FX2gskPPhTwQAIEda/gBkSwAA8tJL6a/9D0ACBAAgF7r+ACAAAFkopPTX/gcgDQIAkDJdfwAYQQAA0jTe0n/RwtsWHL7daB/V/gcgGQIAkJouSv++vr421T8ApEQAAHIv/cek/Q9ASgQAIAU9lv7a/wDkQwAA4lZS13+Y9j8AiREAgNxLf+1/ALIiAADxKbvrP0z7H4D0CABA1qW/9j8AuREAgDhU1vUfpv0PQJIEACDf0l/7H4AMCQBAuKrv+g/T/gcgVQIAkGnpr/0PQJ4EACAsNXb9h2n/A5AwAQCIsu7vsfTX/gcgWwIAkFfpPybtfwDSJgAA2ZX+2v8A5EwAAGoQWtd/mPY/AMkTAIC8Sn/tfwAyJwAAuZT+Y9L+ByAHAgCQUemv/Q8AAgCQRek/Ju1/ADIhAAC5lP7a/wAgAABBlP41Nv6HaP8DkA8BAMii9Nf+B4AhAgCQeOk/Ju1/ALIiAADpl/7a/wAwTAAAUi79x6T9D0BuBAAg8dJf+x8AVicAAMmW/mPS/gcgQwIAkHLpr/0PACMIAECapf+YtP8ByJMAACRb+mv/A0AzAQBIsPQfk/Y/ANkSAIBe6/4wS3/tfwBoSQAAUiv9AYA2BADIXZKlf/v2v/0/AORMAIB8JVn6AwDtCQCQo7RLf+1/AGhDAIC8pF36AwBjEgAgF5mU/tr/ANCeAADpy6T0BwA6IQBAynIr/bX/AWBMAgCkKbfSHwDokAAAqcm29Nf+B4BOCACQjmxLfwCgcwIApEDpr/0PAB0SACBuSn8AYFwEAIiV0n+Y9j8AdE4AgAJK6pTK5Yqll0agQ40F8wcWSadADSbW8aQAhdH+J16NBfMbC7LoOwBBEQAAoAbD7X8xAKiYAABETPufZIgBQGUEAACoR/M1AGIAUAEBAIiV9j+pEgOAUgkAAFCbNjcCEgOAkggAQJS0/8mEGAAUTgAAgDp18m4AYgBQIG8EBsRH+588DWcA7yAG9EIAgD/zmloGbUsY08Ci/nH9pQx9slMW0B1bgIDIaP/DEPuCgO4IAABQv67b+WIAMF4CABAT7X9oSQwAOicAAEAQet/TLwYAnRAAgGho/0MnxACgPQEAACIYAixaeNu4HkoMAEYjAABx0P4ncwsO327RwtvEAKB3AgAAxHQlgBgA9EgAACKg/Q8j/hDEAKBrAgAAxHo7IDEA6IIAAIRO+x/a/zmIAcC4CAAAkMJ7AogBQIcEACBo2v8wrj8KMQAYkwAAAKm9MbAYALQxud0HAWql/Q9t3hNgzE8b+pz2f0cjDGeAXuIHEDgTAAAIVCFVeBfTAAMBSJsAAARK+x/aGFdfXwwAVicAAEC4it2KIwYAAgAQKO1/KHwIMEwMgMwJAAAQtJKux+0iA4gBkAYBAAiO9j+UPQToZRQgBkDsBAAACF2pN+UUAyA3AgAQFu1/qHIIMEwMgHwIAADAn4gBkAMBAEiwlwlZ7QIq/A9HDIC0CQBANOz/gSqJAZAqAQAIhfY/hDMEGCYGQHoEACAIY5Yv2v9QIzEAUiIAAEA0ahkCDBMDIA0CAFA/7X+IiBgAsRMAACAm9Q4BiooBkgDUSAAAaqb9D/HqOgYYCECNBAAAiEwgQ4BhYgDERQAA6qT9D8kQAyAWAgAAxCe0IcAwMQDCJwAA4dL+h0iJARAyAQAAohTsEGCYGABhEgCAQGn/QxrEAAiNAAAAsQp/CDBMDIBwCABAiLT/IUliAIRAAACAiEU0BBgmBkC9BAAgONr/kAMxAOoiAABA3GIcAgwTA6B6AgAQFu1/yJAYAFUSAAAgelEPAYaJAVANAQAIiPY/IAZA2QQAAEhBGkOAYV1ngOEYIAnAaAQAIBTa/0BRo4AhYgC0JAAAQCISGwIMEQOgcAIAEATtf6DUGAAMEwAAIB1JDgGGiQFQCAEAqJ/2P9A5MQB6JAAAQFLSHgIMEwOga5O7/1Lo65s/f77ebY0aC+a3eaWPhV8hiFFKWQJyYwJAr+b/Ud2ryI6bWgBtZDIEALpjAkBP+vv7h6r/of/Wyq3A6nW/9j8AMF4CAEUSA0ql5Q8UYsHh29k9DzkTAChsCDBMDKim7k+g/Q+UZ2BRv64B0JIAQFmGU4Ek0DUv3kBJDAEgZy4CpgDtS3xXCZdxja/2PzCm9icKVwNDtkwAqIh9QR3S9QcASmUCQDE6rOxNAwq5s6f2P9AhQwCgmQkANTANGEHXHwCojABAibcDak8M6K7u1/4HCrwdUElXAwd4hbFxBwwTAKhZnjFAyx8AqItrAChS13V8PtcGdL7RvyXtf6ALrgQAVmcCQEDSfusAXX8AIAQmABSskNo9sYFAj13/Ydr/QNcMAYBhJgCEK4HLA3T9AYDQmABQvDYlexf3hYh0GtBF17/9D0f7H+iRIQAwxASASg3fb268rzSxTAO6a/l39zMBAOiCCQD1WLTwtsSmAd1t9O/u5wDQHUMAwASAGt4UbPU3nUljGtBL139Y+x+C/T8AQFFMAKhfvNMAXX8gOoYAgAkANQ8BhvUyDah+IFBI13+Y9j8AUBkTAMLSdWu8soFA1zf11/UHAmEIAJkzASCgIUDvt8Qp7/KAXu7o37701/4HAKpkAkCgetkoX+w0oJf38bXdHwiTIQDkzASAEIcAgUwDyuv6D9P+BwAqZgJABKqfBuj6A8kzBIBsmQAQ+hCg4mlABV3/Ydr/AED1TADIaxrQ/hN0/YGsGAJAngQAqtCm9d7dC0w4BXfXK9H+BwBqIQAQsXpjQDghBKBrhgCQIQGAWIcANRbivT+j9j8AUBcBgERUEwN0/YH0GAJAbgQAUhgCDCu1Oi/qwbX/AYAaCQCkpowmvcY/kDZDAMiKAEAoin2BKapkL7z09zoKANRLAKBSnbwVV4F6Kd9r6frb/wOESfMCUiIAkP4LzHhL+fJKf6+gQLA0ICAfAgBhDQHKK5E7KetL7fqP+a159QVCpoUByRAAAIA/0IaATAgAZDQEqJH2P5CAJM/PkCEBAAD4E80IyIEAQD2yGgJo/wPJSOz8DHkSAACAP9OSgOQJANQmkyGA9j+QmGTOz5AtAQAA+AsaE5A2AYA6JT8E0P4HkpTA+RlyJgAAACNpT0DCBABqlvAQQPsfAAiQAAAAtKBJAakSAKhfkkMA7X8AIEwCAADQmlYFJEkAIALRDQGiWzAAkA8BgAh2AaVHUw2IhfMVpEcAIA4R9dQjWioAkCEBgFDkMwTQTgPi4qwFiREAiEYUnfUoFgkA5EwAICA5DAE00oAYOXdBSgQAYhJ4fz3w5QEA9PX1TWg0GnWvAYAaDAwM9MXM6xcFiv3PAcbFBAAAADIiAAAAQEYEAAAAyIgAAAAAGREAAAAgIwIAAABkRAAAAICMCAAAAJARAQAAADIyuf2H+/v7q1oJ/MH8+fPbf8Kihbf18vgLDt+urgcfMrAou7+pxoJ2/6ZOMrX/TaUqw7+1ev+Wiz2dlqGTUzRkwgSAmAT4ihLR8gAABADCkkOrclwtNIBAOHdBSgQAohFFfz2KRQIAORMAAIB2tP8hMQIAcez/iaizPuZSvZQCADUSAACAUelZQHoEAIKQTPt/iCEAABAsAQAAaE23ApIkAFC/xNr/QwwBAIAwCQAAQAv6FJAqAYCaJdn+H2IIAAAESAAAAEbSoYCECQDUKeH2/xBDACBJCZyfIWcCAADwF/QmIG0CALVJvv0/xBAASEwy52fIlgAAAPyZrgQkTwCgHpm0/4cYAgDJSOz8DHkSAAAAICMCAMFJsr2U5DcFpKf9QNKpDNIgABDc/p882QUEAFRDACAs5bWXFhy+3YLDt+v9c7qmcwYETvsfMiEAEFD7v6RXl/GW9eXFgPbfoCEAAFCByVU8CdSklzp+6Gt1vIBMaP9DPkwASLP9X1QXv/BpgCEAAFAvEwBSU8buHdMAIG3a/5AVEwCSav+XdwlvgQ9uCAAA1MgEgESUWvqPeBbNMCAl2v+QGxMAom//l3rvzpKe0RAAAKiLCQARq7jub/nsemNA1LT/IUMmAETZ/q++61/4SgwBAIBamAAQmUDq/hFMA4AYaf9DnkwAqNO4Xl167/r39/e3/4SBRWN8QrEr9OIKAFTPBIA69/9U1vUfs/QfkQF62YFT1DSgsWB+j4EEoA3tf8iWAEBtOnl1qbL0ryUGLFp4W5ibmgCAVAkABNr+r6v0D2oaYAgAlET7H3ImAFCPNq8uIZT+VcYAQwAAoEoCAGG1/8u+zLdrw534rpPAgsO366KpZggAFE77HzInAFCDlq8uwZb+BQ4ERhsFGAIAAJURAKi//d9L7VtZ3V9BDBiNIQBQIO1/QACgaqu/usRY+pcUAwwBAIBqCADU0/6PvfSveBpgCAAUQvsfEACoWo997tBK/8JjgCEAAFA2AYBK2/9dF7ghl/5F3Syo/Q/HEADokfY/MEQAIHSxlP6Fv3sAAEAZJpbyqGSs67f+bdb/R30xG1jUX2DbXpwASqL9D1kxASBEsdf9I5gGALVzCgKGCQAEJLG6fwQxAAiT9j/kxhYggtj/k8Bun2o2BckPQBecOoDVmQBQs0zq/hFMA4BAaP9DhgQAamv/51n6937PUPcDBcalll6DdzWBkAkA1EDpP4KBAFAL7X/Ik2sAqLT9n89e/1IvDxAVgA45XQDNTACoiLq/Q6YBQDW0/yFbJgCU3v7X9S9jGiAhAGNqc6JQ/UPOTAAoi6K/d6YBAEDhBACKb/8r/au5WZDbAQFtaP8DoxEAKJLSv1QGAgBA71wDQDHtfxv9a7k8QBgAWtL+B9owAaBX6v5amAYAAN0RAOiJ6r9ergEA6mr/1z5J8GbD0DUBAACIidIfeiQAAEA60t79r/SHQggAAEDolP5QIAEAABKRZPtf6Q+FEwAAgJRLf7dNgxEEAABIQWLt/0Kqf7dKg5YEAAAgqdJf3Q/tCQAAEL002v9Kf6iGAAAA1EzpD1USAAAgWeG3/5X+UD0BAADiFun9bZT+UBcBAADSFGz7X+kP9RIAACBicbX/lf4QAgEAABIUWvtf6Q/hEAAAIFZRtP+V/hAaAQAAUhNI+1/pD2ESAAAgSiG3/5X+EDIBAACSUm/7X+kP4RMAACA+Abb/lf4QCwEAANJRS/tf6Q9xEQAAIDLhtP+V/hAjAQAAElFl+1/pD/ESAAAgJrW3/3ss/dX9UDsBAABSUEH7X+kPaRAAACAadbX/lf6QEgEAAKJXXvtf6Q/pEQAAIA4Vt/+V/pAqAQAA4lZ4+1/pD2kTAAAgAtW0/5X+kAMBAAAiVlT7X+kP+RAAACDr9r/SH3IjAABApu1/pT/kSQAAgBzb/71U/0p/iJoAAAB5tf+V/pA5AQAAcmn/K/0BAQAAsmj/K/2BYQIAAKRM6Q+MIAAAQGT7fzps/yv9gZYEAABITdelv7ofciAAAEA67X+lPzAmAQAAUqD0BzokAABA3O1/pT8wLgIAAMRK6Q90QQAAgPja/0p/oGsCAADEROkP9EgAAIA42v9Kf6AQAgAARKC76l/pDzQTAAAg9PZ/F5T+wGgEAABIitIfaE8AAIBE2v9Kf6ATAgAARE/pD3ROAACAiNv/Sn9gvAQAAIiS0h/ojgAApdx/A6C8k4/SH+iFAAAAcVD3A4UQAAAg9Pa/0h8okAAAAOFS+gOFEwAAIMT2v9IfKIkAAABhUfoDpRIAACCU9r/SH6iAAAAA9VP6A5URAACIT6PR6Eul/a/0ByomAABAPZT+QC0EAPiz/n4vxhCBBNr/qn+gRhPrfHIAAKBaAgAAMUmj/Q9QIwEAAAAyIgAAEA3tf4DeCQAAAJARAQCAOGj/AxRCAAAAgIwIAABEQPsfoCgCAAAAZEQAACB02v8ABRIAAAAgIwIAAEHT/gcolgAAAAAZEQAACJf2P0DhBAAAAMiIAABAfO3/RQtvq3YtAOkQAAAAICMCAAAh0v4HKIkAAAAAGREAAAiO9j9AeQQAAADIiAAAQFi0/wFKJQAAAEBGBAAA4qD9D1AIAQCAOPb/AFAIAQCACGj/AxRFAAAgFNr/ABUQAAAInfY/QIEEAACCoP0PUA0BAICgaf8DFEsAAKB+2v8AlREAAAiX9j9A4QQAAGqm/Q9QJQEAgEBp/wOUQQAAoE7a/wAVEwAACJH2P0BJBAAAaqP9D1A9AQCA4Gj/A5RHAACgHtr/ALUQAAAIi/Y/QKkEAABqoP0PUBcBAICAaP8DlE0AAKBq2v8ANRIAAAiF9j9ABQQAACql/Q9QLwEAgCBo/wNUQwAAoDra/wC1EwAAqJ/2P0BlBAAAKqL9DxACAQCAmmn/A1RJAACgCtr/AIEQAACok/Y/QMUEAABKp/0PEI7JdS8AgHyV1/5vLJhf0iMDxM4EAIByaf8DBEUAAKAedv8D1EIAAKBE2v8AoREAAKiB9j9AXQQAAMqi/Q8QIAEAgKpp/wPUSAAAoBTa/wBhEgAAqJT2P0C9BAAAiqf9DxAs7wQMQJTt/xAmCQsO366XLx8YGChuLQCdEgAAKFgO7X+lPxAvAQCAioTQs++d0h+InQAAQJESbv8r/YE0CAAAVCHq9r/SH0iJAABAYdJr/yv9gfQIAACULsb2v9IfSJUAAEAxkmn/K/2BtAkAAJQrova/0h/IgQAAQAFib/8r/YF8CAAAZN3+V/oDuREAAMiU0h/IkwAAQFn7f4Jt/yv9gZwJAABkROkPIAAAkEX7X+kPMEQAACBxvZT+6n4gPQIAAMm2/5X+AM0EAADS1HX1r/QH0iYAAJBa+1/pD9CGAABAOpT+AGMSAABIof2v9AfokAAAQNyU/gDjIgAAEGv7X+kP0AUBAID4KP0BuiYAABBT+1/pD9AjAQCAOCj9AQohAAAQevtf6Q9QIAEAgHAp/QEKJwAAEGL7X+kPUBIBAICwKP0BSiUAABBK+1/pD1ABAQCA+in9ASojAABQZ/tf6Q9QMQEAgHoo/QFqIQAAUHX7X+kPUCMBAIDqKP0BaicAAFBF+1/pDxAIAQCAcin9AYIiAABQVvtf6Q8QIAEAgOIp/QGCJQAAUGT7X+kPEDgBAIBiKP0BoiAAANBr+1/pDxARAQCA7in9AaIjAADQTftf6Q8QKQEAgPFR+gNETQAAoNP2v9IfIAECAAAd6aL6V/cDBEgAAGDs9v94Kf0BgiUAAFAkpT9A4AQAAIpp/yv9AaIgAADQK6U/QEQEAAC6b/8r/QGiIwAA0A2lP0CkJhR1wwcA4q3gx/VaoPQHiJoJAACdUvoDJEAAAMhdJ+1/pT9AMgQAANpR+gMkRgAAyFqb9r/SHyBJAgAAIyn9ARImAADkq7n9r/QHSJ4AAMAfKP0BMuF9AAByp/QHyMqEwcHButcAAABUZGJVTwQAANRPAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIiAAAAAAZEQAAACAjAgAAAGREAAAAgIwIAAAAkBEBAAAAMiIAAABARgQAAADIyOS6FwDVWbFixbXXXnvVVVf96le/WrJkyb333vvUU08tX7581apV06ZNmzFjxsYbb7zppptuu+22O+ywwy677LLlllvWvWQAgIJNGBwcLPoxISwrVqw499xzTzzxxEsuueTZZ5/t/Au33nrrgw8++N3vfvfWW29d5gIBGLdTTz11XJ8/YcKEiRMnTpo0aerUqdOmTVtnnXU22GCD2bNnT5s2rbQ1QqAEAFL29NNPf/3rX//Sl7708MMP9/I4+++//7HHHvvKV76yuKUB0JMJEyYU8jibbbbZnDlzdtxxx912223XXXdda621CnlYCJkAQLJOPfXUj370ow8++GAhjzZx4sQPfehDn//85702AKQUAFY3derUPffc8+1vf/uBBx44ZcqUwh8fAiEAkKBHH330iCOOOPvsswt/5Je//OVnn332y1/+8sIfGYDaA8CwTTfd9Kijjvrwhz9sgxBJEgBIzS9+8Yv999//N7/5TZvPednLXrbTTjttu+22G2644dprr/3MM8889thjS5cuXbx48TXXXLN06dI2X7vuuuv+4Ac/2HnnnUtYOwBBBIAhm2+++Re/+MVDDz207CeCigkAJOXqq6/ea6+9li1b1vKjm2222Qc+8IG3v/3tL37xi0d7hMHBwcWLF//v//7viSee+NRTT7X8nHXXXfeyyy7bcccdi1s4AMEFgCGNRuP4449ff/31q3k6qIAAQDp+9rOf7b777i2r/3XWWedTn/rURz7ykc73dD7xxBPHHHPMcccd1/JvZLPNNrvuuus23njjnlcNQGEBoH1V8/zzz7/wwgtPP/30U0899fDDD99111233Xbb9ddf/6Mf/Wi0ztGQl7zkJeeff/4222xTxMKhfgIAibjzzjtf/epXP/bYY80fevWrX93f39/dTf0vueSSww47rOWVxHvssccPf/jDrhYLQA0BYDQrV6689NJLv/nNb5577rmrVq1q+TkzZ8688MIL7f8kDQIAKXj66afnzZt38803N3/ogAMO6O/vX2ONNbp+8FtvvXW33XZrGS1OOOGE97znPV0/MgAhBIBhixcv/sd//MfRmjvrrbfeZZdd5pbQJEAAIAVHHHHEd77znebj+++//xlnnDF5cq/veH399df/zd/8zYoVK0Ycnz179pIlS2bMmNHj4wMQQgAY8s1vfvOoo45auXJl84c23njjG264wf5PYjex7gVAry655JKW1f8OO+xwyimn9F79D20i+tSnPtV8/IEHHjj++ON7f3wAwvH+97//0ksvXXfddZs/dP/998+fP/+FF16oY11QGBMA4rZixYptt932t7/97Yjj06dPv+mmm7beeuuinui5557baaedFi9ePOL4S17ykjvuuGPiRFkaIJEJwJBrrrnmTW9609NPP938oS9/+csf+9jHinoiqJ6qhbgdf/zxzdV/X1/f5z73uQKr/76+vilTphxzzDHNx++8886rr766wCcCIASve93rvv3tb7f80DHHHHPvvfdWviIojABAxJ555pkvfOELzce32WabI488svCne+tb37rZZps1Hz/rrLMKfy4AanfooYcuWLCg+fhTTz3V8tUHYiEAELHvf//7DzzwQPPxf/u3f5s0aVLhTzdp0qT3v//9zccvv/zywp8LgBD8+7//+7Rp05qPf/vb3275AgRREACI2AknnNB8cKuttnrrW99a0jPuu+++zQdvueWW5cuXl/SMANRo8803/6d/+qfm488+++zChQvrWBEUQAAgVrfeeuv111/ffPxDH/pQeZfk7rDDDrNmzRpx8IUXXrj99ttLekYA6vX3f//3U6dObT5+0kkn1bEcKIAAQKzOPvvs5oMTJkw49NBDy3vSCRMm7L777s3H77jjjvKeFIAarbvuui3Hv7/8ozpWBL0q4BbpUIsLLrig+eC8efM22WSTUp/30EMPbb7N3Nprr13qkwJQo3e84x1nnHFG8/FLLrlk2223rWNF0BPvA0CUnnrqqfXWW6/5rVg+9alPfeYzn6lpUQCk8z4Aq1u5cuXMmTOb3xPgwAMPPPPMM8t4RiiVLUBE6cYbb2z5Roy77bZbHcsBIGVrrLHG9ttv33z8pptuqmM50CsBgCj9/Oc/b3l87ty5la8FgPS1fH256667nnzyyTqWAz0RAIjSL37xi+aDs2fP3mCDDepYDgA5BoDBwcHf/OY3dSwHeiIAEKV77rmn+eBLXvKSOtYCQPrmzJnT8vjvf//7ytcCvRIASCcAbLzxxnWsBYD0rbfeei2P33///ZWvBXolABClRx55pPlg81t0AUAh1llnnZbHly1bVvlaoFcCAFFqvhdbX1/ftGnT6lgLAOlbd911Wx5/5plnKl8L9EoAIErPPvts88E111yzjrUAkL7RJgArVqyofC3QKwGAKD3//PPNB72rHQAlafnmM319fVOmTKl8LdArAYAoTZ06tcOxAAD0brROv+EzMRIAiFLL7f4tLwwAgN6N9oZf06dPr3wt0CsBgCitvfbazQcffvjhOtYCQPoefPDBlsdnz55d+VqgVwIAUdpkk02aDz7wwAN1rAWA9I12v/9NN9208rVArwQAotTyhHvnnXfWsRYA0vfrX/+65fEtttii8rVArwQAovTiF7+4+eCDDz742GOP1bEcABL3q1/9qvngrFmzbAEiRgIAUXrFK17R8vjNN99c+VoASN+1117bfHCHHXaoYy3QKwGAKI12zv3xj39c+VoASNwTTzxx6623Nh+fN29eHcuBXk3u+RGgBnPmzFl33XWfeOKJEccvv/zyf/3Xfy31qf/u7/5uxP1G11hjjZNOOqnUJwWgRhdeeGHLNwLbY4896lgO9GqCN08lUgcddNBZZ5014uCkSZMeeOCBDTfcsKQn/c1vfvPSl750xMEtt9zyt7/9bUnPCEBLEyZMaD5YUlXTaDROP/30EQfXW2+9hx56yDsBEyNbgIjVnnvu2XzwhRdeOOOMM8p70osvvrj5YHMkACAZDz300Nlnn918/JBDDlH9EykBgFgddNBBLc+83/jGN8p70ksuuaT54Pbbb1/eMwJQr6997WvPPfdc8/F3vetddSwHCiAAEKsNN9xwr732aj5+8803X3755WU84zPPPHPppZc2H99ll13KeDoAavfoo49+9atfbT6+8847v+51r6tjRVAAAYCIvf/97295/F/+5V/KeLpTTjnl8ccfH3FwypQpb3zjG8t4OgBq9/GPf3zZsmXNx//5n/+5juVAMQQAIrb33nvPnTu3+fg111xz2mmnFf50X//615sP7r777uuvv37hzwVA7c4///zvfve7zcd32WWX/fbbr44VQTEEAOL2yU9+suXxD3/4w4888kiBT3T66affeOONzcff+973FvgsAARiyZIl73znO5uPT5o06etf/3rLexBBLAQA4va2t72t5Q6chx9++J3vfOeqVasKeZbHH3/8qKOOaj6+1VZbHXDAAYU8BQDhuPfee/fYY4+lS5c2f+joo4/2BsDETgAgel/72tda3g7ooosu+vjHP9774w8ODn7wgx+8//77mz/0+c9/ftKkSb0/BQDhWLx48bx58+66667mD73+9a8/9thj61gUFEkAIHpz5sz5/Oc/3/JD//mf/3n00Uf3+PhHHnnkqaee2nz8TW96U6PR6PHBAQjH4ODg8ccf/9rXvvaee+5p/uhWW23V39+v70MCvBMwKRgcHNx///3PO++8lh899NBDv/Wtb82YMWO8D7t8+fKPfOQj3/72t5s/NHPmzFtuuWWzzTbrar0ABPdOwJdddtnRRx993XXXtfzoRhttdNVVV2211VZdPz6EQwAgEcuWLXvDG97Q8jrdobbNV77ylX333bfzB7zyyiuPOOKIJUuWNH9o8uTJF1100e67797DegEIIgDcfvvt55xzzve+973FixeP9jlbbrnlxRdf7H3fSYYAQDoeeuihXXfd9Y477hjtE3beeeejjjpqv/32W3vttUf7nGXLlp133nnHHXfcT3/605afMHHixIULF7a8NQQA9QaARYsWtfmSF154YeXKlcuXL1+6dOkDDzywZMmSn//852PeMu51r3vdGWecsfHGG/e8ZAiFAEBSHnroof3333+02n3IGmus8drXvnb77bd/6Utfuu66606ZMmXpH/3+97+/9tprFy9e3ObeQVOmTFm4cOHb3/72cpYPQKcquBHnxIkTP/axj33uc59reasJiJcAQGqeeeaZD3zgAyeddFLhj7zRRhudccYZu+yyS+GPDEBoAeA1r3nN//zP/+y0006lPgvUwl2ASM20adNOPPHEs846a/bs2QU+7Dve8Y5bb71V9Q+QvHnz5p1zzjk//elPVf+kygSAZC1fvvxrX/val770pUcffbSXx3nzm9/86U9/+rWvfW1xSwMguAnAnDlzDjjggMMOO2zOnDnFPjKERgAgcc8888xZZ5114oknXn755c8991znX/iyl73swAMPfPe73/3yl7+8zAUCUFEAmDhx4uTJk9dcc80ZM2ast956s2bN2nzzzbfZZpvttttu3rx5G220UTkrheAIAORi+fLlV1999VVXXXX77bcvWbLk/vvvf+qpp5YvXz44ODht2rQZM2ZsvPHGm2222TbbbDN37txddtllyy23rHvJAADFEwAAACAjLgIGAICMCAAAAJARAQAAADIiAAAAQEYEAAAAyIgAAAAAGREAAAAgIwIAAABkRAAAAICMCAAAAJCRCXUvAArWaDTKe/CBgYHyHhwAoAICADEptbgvipAAAIRMACBEURT64yUYAAAhEACoWZK1fuekAgCgYgIAVcu84m9PHgAAyiYAUDoVf9fkAQCgcAIAxVPxl0QeAAB6JwBQDEV/xYQBAKA7AgDdU/QHQhgAADonADA+iv7ACQMAQHsCAKnV/QOL+tt8tLFgftdfO+aXB0USAABamtz6MARZ949ZoIewgEBCwvC/nSQAAKxOACDEor/2Qr+MxdcVDFb/BxUGAAABgPrr/qjL/V6+zeojgbEAACAAUEPpn0nFP96fQ5V5YOgfXQwAgAwJAPmqsu5X8YeZBwwEACBDAkB2qqn7Vfxx5QFJAADyIQDkooK6X9Ff2Y+3vDAgCQBA8gSA9JVa+iv6Uw0DLhIAgFQJACkrr/RX94dj+N+ijCQgBgBAegSABJVU9yv6sx0L2BcEACkRAJJSRumv7o9RSWMBAwEASIAAkIjCS391fxrKSAJiAABETQCIm7qfupKAfUEAECkBIFbFlv7q/nyUlATEAACIhQCQdemv7s9ZsUlADACAWAgAMVH6U4ahXwYxAAAyIQDkVfqr+6lgICAGAEDIBIDQKf2JdCAgBgBAmASAxEt/dT/1DgTEAAAIjQAQIqU/iQ0ExAAACIcAEBalP2ESAwAgGQJAUtW/0p8oYoAMAAA1EgBSKP3V/cR1eYBRAADUSAComdKfePU4EBADAKAWAkBtlP6kQQwAgLgIAPFV/0p/kowBMgAAVEMAqJrSn4T1EgOMAgCgGgJAdZT+ZEIMAICQCQChV/9Kf/KMATIAAJRkYlkPzP/X+KPuvlb1T+y6/h3u5Q8HAGjDBKBcSn8wCgCAoAgAZVH6QyExwFUBAFAsASCg6l/pT/J6iQEyAAAUwjUABet647Lqn3x099vuqgAAKIQJQJGU/tAhowAAqIsAUAylP1QWA1wVAAC9sAWoAKp/qGVHUAlrAYD0mQD0qosqROkPRY0CzAEAYLxMALrX3SWJqn8o8K/DlcEAMF4mAF1S+kMZjAIAoGwCQBXVv9Ifyo4BMgAAdMgWoNL3G6j+oTvj/duxHQgAOiEAjINtPxDFVQHlrAUAEmELUKc0/qEWtgMBQLFMAMZm2w/UznYgACiKCcAYlP4QCKMAACiECUA7qn9IYBRQ2loAIEoCwKhU/xAmGQAAemELUAtKf0hsO9DQH7XtQABgAtCC6h9iYRQAAF0QAP6C6h/iIgMAwHjZAtRlZaD0h3i3A9kLBEDOTAD+RPUPURvXX6U5AAA5iz4AFPJCrvqHBMgAAJDLFqBe7u+h9IdstwO5NRAAeYp+AjD84t34o3F9reofkmQUAAApB4AROo8Bqn9ImAwAACkHgOYJ/pgxQPUPyZMBACDZADCa0WKA6h8yIQMAQLIBoM1lfCNigOofsiIDAECCdwHqhLf4hWyN99ZA7gsEQNoSmQAUey8/1T+kp/O/a3MAANKWTgAoiuofUiUDAEBqAaD3IYDqH9ImAwBAUgGgR6p/yIEMAEDmUgsArt4DxiQDAJCz1AJALxoL5g/9p+6FAKWTAQDIVoIBoPchgBgAOZABAMhTggGgKGIAJE8GACBDCQaA9q/TixbeNr5HEwMgaTIAALlJLQCM+Qq94PDtFi28TQwAhskAAGQlqQAwrtdmMQAYJgMAkI90AkDnr8oLDt9u+H+LAcAQGQCATCQSAHp8PRYDABkAgEykEAC6eCVefQgwTAwAZAAAkpdCACiWGACZ6zwDAECMog8AXTfhWg4BhokBkLMOM4AhAAAxijsAlP3qKwZAtmQAAFIVcQDo8HW3zat4+yHAMDEA8iQDAJCkiTlU/4Xs6BUDIEMyAADpmZhn73+8Q4BhYgDkRgYAIDETM6n+i72thxgAWZEBAEhJfAGgE+Mq98c7BBgmBkA+3BsUgGREFgB6abCV9PotBgDDDAEACN/EPLf+FzUEGCYGQPJsBAIgDROzqv7LHuKLAZA2GQCABEzMvPdf4BBgmBgACZMBAIhdHAGgwFflyq7kEwMgVS4IBiBqEQSAThpphbweFzgEGCYGQJI6OecYAgAQpokZVv/Vd+/EAEiPDABApIIOANW/dpYxBOg9BkgCEC8ZAIDQBB0Aymvn17iFd7wZYIgYAAFyMQAAMQo3AFS29b/KIUDXo4AhYgCExkYgAKIzMdvqv/bWnRgAaZABAIhLiAGg9lfKCoYAw8QAyETtZzYACDcAVNa/r30IMEwMgKiFczIBgPgCQF1b/2scAgwTAyBeNgIBEIuJmVf/AfbtxACIlAwAQBQCCgChvS7WMgQYJgZAqkI71wGQm4ACQF0N+wCHAMPEAIhLyOcTAAgrAASy9T+oIcAwMQAiYiMQAIELIgDUXv1H0bQTAyAWMgAAIQsiAIQskCHAMDEAAIC4A0Dt7f8YiQEQOEMAAIJVcwAIp/pv8yyhDQGGiQEQMhkAgDDVPwGgR2IAAABxBIBw2v/xDgGGiQEQIEMAAAJUWwAIrfpPgxgAoZEBAAhNuFuAaqn+ox4CDBMDICh6GQAEpZ4AoN1VATEAIuKsCEDKASDwzT9pDAGGiQEQAhuBAAhHuFuAKJAYAABAPQEg8PZ/kkOAYWIA1MgQAIBABDcBqL36T54YAHVxfgMguwAQUXMr1SFAUTFAEoCSRHSeBCBS1QWAKDb/5KbrGGAgAN2xEQiA2gW0BSi06j/5IcAwMQByPtcBkJvJ1TyNhlbaWSKZDJDMNxIR1XBLjUZjYGCg7lUAkKZQJgBhFgH5DAGAKoV5xgMgE1UEAO1/gPFy5gQg5QlAyM0wQwAgt/MeAGmbWHsTy6sgkKcxz36GAADEFwDSePUyBADqksZZFICg1LwFSPsfyJlzIABJBYCUGleGAEBdUjqXApD7BEDrC8CZEIBEAkB6LStDAKAu6Z1RAUj/nYCbaXp1wk+p4vf69QMvg/dXHtPAon4/JQDingCkeutPQwCgJG4JCkBebwQGAABUo/gAkGr7f4ghAFASQwAAqmECAAAAGSk4AKTd/h9iCACUxBAAgAqYAAAAQEaKDAA5tP+HGAIAJTEEAKBsJgAAAJCRwgJAPu3/IYYAQEkMAQAolQkAAABkpJgAkFv7f4ghAFASQwAAymMCAAAAGakiACTZ/h9iCACUJOEzJwDRBwCTaIDqOfcC0B1bgHplCAAAQEYBIM/LfwEq4FJgAMpgAlAAQwAAALIIANr/AKUyBACgcCYAxTAEAAAg9wCg/Q/QO+dSAEIJAObOIxgCALVwNgYgiAmAlhVAUZxRAag/AGg4tWQIANTCORmAzrkIGAAAMtJNAHD3z+4YAgBdcz9QAIpiAlAw4QcAgLwCgAq4DUMAoGvOrgDUEwBMmXt8kZYBgJI4PwPQCVuAAAAgIwUHABPqIYYAQBmcYwGoOgCYLwOEzFkagEonAFpTqzMEAMrgTAtAj1wDAAAAGRlHADBZHi9DAKB6ztUAVDQBMJUGqIbzLQBVBAAtpe4YAgDVc8YGoA3XAAAAQEaKCQDm0W344QCFc2IBoNwAYJoMEBfnbQBGYwtQFfTqAABIJwCobgGq59wLQHdMACripRoAgDgCgI2kADFy9gaglAmAxnbn/KyAYjmrANAFW4AAACAjYwQAE+RiadcBVXIOB6DgCYByFqBezsMAjJctQFXzag0AQKABwOwYIHbO5ACMYAJQA0MAAADiCwCqWIAQOBsDMC4mAPXwgg0AQFgBwLZRgDQ4nwNQwARAA7t3afwMGwvm172ErPn5k9L5BIBqTK7oeUi9BlV/VEzpDwB0xzUAdUqgaB7+FhoL5itJq7H6jzqBXyEAIIgJgA2jdMc0oFQiFl1rNBoDAwN1rwKAaCcAyjva/z6YBhRr6OfZ/CP1l8jq/D4A0CHXAFAW21R6J0cBAIVzDQAFaF/iGwh0YcwfmlgFABQ2AXABAGVweUCHhCVK4jIAALqcACjg6OUXwzSgkB+OP0Na8osBQCdcA0ANTANGEIoAgMoIABRmYFH/uApZMaC7uj/nnxgA0DsBgJrlGQO0/AGAUK4BcAUwvei6js/n2oAev9PckhLFcoYHYNwTAMUHpUr7rQMySTjEtRMPgAx5HwAKVkjtnthAoKhvJ8lcBABUzDUAhCuBywNSijEAQBpMAChem5K9i2o+0mlAF8tu/8OJOggBAIFOAFwfRtkaC+YPFbLjLY5jmQb0cmfPGHMO0fF+wACMYwtQ+LUXEUkvBripP4FwHTAA7dkCRCna1LWrlyYDi/oT2BTU3XpGfO/tH0FOAACK4iJg6hfvNEDXHwCIjgBADfsQhq8EKCoGVF9VF1v6a/8DADVsAXIFMCEI/72Eu34idTyBcLYHyFyn1wCoXSjvSoDmrwowBgw9ctelf3c/Cn96dMevDQBt2AJEoHq5M2axlwf0kijUYQBAaNwFiHJ13fkOYRrQyyN0uHLtfwCgYiYARKD6aYCuPwCQKhMAQh8CVDwNqKDrv/pztX+07pYBANCGCQDZTQN6+YT2qwIAiGYC0P6ucIobAhkCrP6Agfxadr0S7X9K1f5XyJ1AAXJmAkCm04Cinh0AIC6uASDWIcDqj1xxLd77M2r/AwB1MQEgEdVMA5TmAEDsTABIYQjQyVOE8+Da/wBAjUwASE0ZowBFOQCQDBMAQlF4yV5I1V74BQZ1XbIMADBEAKBSEV2tW8udRo0aAIAqAoA3ASAQJXXHx1vKl1f6a/9TJW8FAEBLJgAEVpSUViJ3UtaX2vUf81sTtgGACggAAACQEQGAjIYANdL+BwACIQAAAEBGBADqkdUQQPsfAAiHAAAAABkRAKhNJkMA7X8AICgCAAAAZEQAoE7JDwG0/wGA0AgAAACQEQGAmiU8BND+BwACNLHRaLT5sAIFIF7O4QA0MwGgfkkOAbT/AYAwCQAAAJARAYAIRDcEiG7BAEA+BACCkNt+mNy+XwAgHAIAcYiopx7RUgGADAkAhCKfpng+3ykAECABgGhE0VmPYpEAQM4EAAKSQ2s8h+8RAAiZAEBMAu+vB748AIC+vr4J7d8JGKBURiJlk0uBcRkYGKh7CZROAAAAgIzYAgQAABkRAAAAICMCAAAAZEQAAACAjAgAAACQEQEAAAAyIgAAAEBGBAAAAMjIhLoXAHXyRngQ75s0t3+T45kHhb5+Rlh65vxSfyfb/8KU+uBDFi28revHX3D4dmN+Tne/82P+2EnS5LoXAHXyhufkTAAmIoEn0oFF/Z1kgK4tWnhbJxkgzx8+o2nzO2kLEABQsxz60GVX8N39DM3K8iQAAABBi6IDXfYie9lB1KNShxvUQgAAAEiBIQAdEgAAgHDL1ija/x0utcddQIYAFEUAAABIhCEAnRAAAIDaJNP+H2IIQBQEAACAdBgCMCYBAACoR2Lt/yGGAIRPAAAASIohAO0JAACZav9O2Fp9lC3J9v8QQwBq1/5fSgAAAEiNIQBtCAAAQNUSbv8PMQQgZAIAAECCDAEYjQAAAFQq+fb/EEMAgiUAAACkyRCAlgQAAKA6mbT/hxgCECYBAACAv2AIkDYBAAAIQmLt/2q+qTGHAN3tAuqEIUC8BAAAoCLlFaPx6nEXUHkMARImAAAAKXfKGwvmj9mr7uRzumYIQGgEAACgCm3K0JJK5PGW9eXFgPbfoCEAFRMAAPI1MDDQ5qN6e8Srl1K+1GlASQwB6PwfZWBgQAAAANJp/xdVvhceAwwBCIcAAACkoIzOfUTTAEMAOicAAADRt/9LrUGLenBDAAIhAAAAEaumSR/FKMAQgA4JAABAlO3/6ovy3p/REIAQCAAAQGTq7ceHPA0wBKATAgAAEE37P5ziu+uVGAJQOwEAIGveCoBYhFP6B74qQ4DMNcZ6EwABAACowbja/70X2WN2r8csmotdYUnvfFw2Q4BkCAAAQCl67zQXUvp3WLYuWnhbxTGgvF1AhgC0JwAAAJXqpP9dZelfSwwwBKBGAgAAULyue8x1lf5BTQMMASiVAAAAVKdN5zuE0r/KGGAIQF0EAADa0cyjC110l4Mq/ZtjQC9JoLtvzRCA8n7yAgBA7trfCRQK1LLn3WPjv7zSf4ReYsBo36MhALWc7QUAAKBInfeVeyn9h+r+6ivRMmLAaAwBKIkAAABUYfVud++lf1+tCowBhgBUTwAAAAozZkc59tK/4mmAIQBlEAAAGINXcXo3sKg/pdK/2BhgCEAhOv/7EgAAcB0wxWjTS06y9C/qZkHtfziGABR+nhcAAIAQxVL6F/7uARGJ8R8IAQAAKEaBXeRIS//yYkAFQ4DyGAIESAAAAEKRQOkf6TSg6/yW0r9XPgQAAMamh0ep6rqpf1YxwBAgbY3x/JAFAAD+wHXA1NU/TrXuLzYG9L4LaEyGAPmc4QUAAKAG+ZT+4UwDDAEYIgAAAJV2jvMs/Xu/Z6ghAEURAACAiij9ax8IGAIgAADQKS/e9NIzVvoXEgMMASjk/CwAAPAnrgOmDFGU/gsO366C2jqQaYAhQG6az+0CAABQSrc4itI/uhhQyArbP4UhQPIm170AACApsVeBQxV2vXfuH3r22tNIGRoL5g8sivs3JAEmAAB0yvie9n3i6Fr+UUwDmqOIIQA9npkFAAD+zGUAdCel0j+0GFD7uwcUTiuh9rO6AAAAjNtwhzjV0j/wGGAIQC8EAACgGzmU/oHHgHgZAtRLAABgHLxsMySr0j/MGFDB4xgCpHpOFgAA+AsuA4BYYkDUdBNqPJ8LAAAA+cYAQ4AMCQAAjI++HaQXA2rhZFLXD1AAAADIOgYYAuRGAABgJJcBkJui7mgUdQyohSFALWdyAQAA4M8xoPckEGMGMATIigAAwLhp2pG23mOAUUDnnE+q/7kJAAC0YBcQ5BYDDAHyOYcLAAAAo8otBtTCEKBiAgAA3fCCTVYyiQFFvcHwCIYAoZ2BBQAAWrMLCPKMAYXvAuqEnkKVZ28BAABgHNKOAYYAORAAAOiSjh05SzsGjMYQIAS9/6AEAACALiUZAwwBkicAADAqlwFAtjFgNIYACZy3BQAAuufVGpKMAYYAaZ91BQAAgMKkFANGYwgQOwEAgHbsAoI8Y4AhQMJnbAEAgJ5o10H7GNBLyVt7DBiNIUAtivrJCAAAjMEQAHoUaQwwBEj1XC0AAABUIdIYMBpDgHgJAAD0yks1pBoDDAGSPNMKAACMzS4g4rX0zPml9qpziAGjMQSI9CwtAABQAC/VBCjM0j+6GGAIkN45VgAAAFITfukfXQwYjSFAjAQAADpiFxBRiKv0jyUGGAIkdn4WAAAohl4d9Yq39I8lBozGEKBshf8QBAAAIG5plP6BxwBDgJQIAAAUNmXWq6Ni6ZX+gceA0RgC1Pjtd7E/UwAAAOKTdukfZgwwBEiGAADAOLgUmNrlU/o3x4Cua+UKpgGGABGdkwUAAIrkdZry5Fn6j1BvDDAESOOMKgAAMD6GAFRP6V9sDOgrhyFALGdjAQCAgnmdJqjSf2BR/8CiNBvMXceAXkYBhgAJnEsFAAAgREr/kGPAaAwBoiAAADBu7gdKqZT+gccAQ4BI7/45bHLXXwkAEFr/OLe6v2UN3cWPcSgDlFTZF6ixYH7m/8SFMAEAoBuGABRL1z+uaUCbqNDLv6MhQAXtfxMAAKBmuv4lSXUaYAjQOxMAALrkfqD0SNc/6mmAIUC8514BAICy2AXEaJT+Od8pqHdpn1sa5X93AgAAUB2lf0oxwBAgUgIAAN1zKTCdU/oHIo1pQKrnlrIv/x3iImAAoFwu8w3QcAYY77/OiEuEFy28bbRUsPTM+V338mce1F/qe4plzgQAgJ4YAtCGrn+qA4EQpgHpnVsalbT/TQAAgFLo+udwz9DhaYAhQFxMAADolSEAq9P1z3Aa0FeTlM4tjara/yYAAEBhdP0zfwexlgwBAmQCAEABDAEyp+ufnq5vFlSxNM4tjQrb/yYAAEBPdP3TVsg0wBAgNCYAABTDECA3uv75CHwaEPu5pVFt+98EAAAYN13/PPUyDTAECIoJAACFMQRIXu9df9V/7MKcBsR7bmlU3v4XAACoWryv05krqvRX/WcbA3r5/QkwckR9PhQAAChSGc0q6qX0J4ppQJLNhYFyzqgCAABVS/J1OklKf4qNAYYAgZwJXQQMQMEGBgYajUbdq6AnhVxzqe7PynCBXuMFu40F81P6rRsobaBqAgBADQwBgqXrT6kDAUOAEM6BAgAAxXMlQIyU/iRweUAyzYWBMs+iAgAApXBL0Igo/akyBhgCNOq49efqBAAAaiMD1E7pT3rTgMBPLI0AlicAAFAWG4FCpvSnxhhgCFDvmVMAACD3ZlhulP4kPw0I9sTSCGNhbgMKQIncEjQobu5JIHrMADMP6q/xZqMJDE5NAACoWSAtsbTp+pObAE8sjWCWJAAAUH9DK5zXxfQo/UlSdFcCNDo4y1V23ZQAAEDpXA1cC6U/mYurszBQ4XlSAAAgCHG9VAdO6U8OIhoCNAI7vwkAAFTBRqBqKP0htLNKI6TNP0PcBQgAUuAOP2Qo4dsBlcoEAICKGAKURNcfgj2rNMJr/5sAAFApbwtQLF1/iH0IMFDHPRJMAAAIiyFAJ3T9IfyzSiPUs5kAAEClbATqkdIforgdUCPIzT9DBAAAqiYDdEfpD12r+JTSCLj6dw0AAETAXn9I+0qAipkAAFADQ4AO6fpDUSo7pTTCbv8LAADURgZoT+kPMV4J0Ai++rcFCACCY8MPlKSxYL4/DRMAAOpkCDCCrj9EPQRoxND+FwAAqJkMMETpD9VolHY+iaX6FwAAiEPCGUDpDwkMARpRnaMEAABqFkhLrHpKf8iqWB8I5lwnAABQv9w2Ain9IaUhQCOezT9DBAAAgpBJBlD6QwgaxZ1Moqv+BQAAIhNvBlD6Q3pDgEacZyQBAIBQhNYkK4rSHwLUqKp2D/DMJgAAEJDENgIp/SHhIUAjws0/QwQAAMKSRgZQ+kP4Gj2cSeKt/vv6+ibXvQAASErvdf9Q6V/EWiBrMw/qL+TvMcYeRHsmAAAEJ9i2WXu6/hCdRmmlfMjnMRMAAEI0MDDQaDT6IqHrD/kMARoxb/4ZYgIAQKACfwUdousPWQ0BGvFX/yYAANAlXX/IbQjQiHzr/zATAADCFWYjTdcfEtPooLLvsPoP86w1ggkAAEEL6mIAXX/IcwjQSKj6NwEAIAIhvKbq+kPaGqOX+IlV/yYAAMShxjmArj8koLz3BIiu+hcAAGBUSn/ISmPB/OY/2GQu/F2dAABAHKocAij9IT1dDAEayW3+GeIaAACiUcGrrL3+kLPGahV/qtW/CQAAkSlvDqDrD8nrfAjQSLf6FwAAiE/hGaCoSwNV/5CARseb/iOt/gUAALLOAEp/yM3Mgm4HFG/1LwAAkCmlP5Bn9S8AAJAdpT9kbmbJ7wkQPgEAgFwo/YHexd7+FwAAyILSHyhkCDAQf/UvAACQOKU/UJSBJKp/AQCAZCn9gQKHAAOpVP8CAABp8q5eQIEGEqr+BQAAaEHpDzmY2dkQILHqXwAAgL+g9AeSJwAAwB8o/SFDM7N8TwABAIDcKf2BNhqNRmK7gCbWvQAAAKjNzIOyawEIAADkrrEguw0AwLg0Go2+hNgCBAB/yAA2AuUsw13g5MwEAAD+wBwAyGQIIAAAwJ/IAEAOBAAAUjbw/3X4+Y0F88UAIO0hgAAAQJpG1P3juoufDAAkTAAAIDWjtfxlAKBHaQwBBAAA0jHmbh8ZAEAAACAFnW/0lwGAzIcAAgAAcRvXNb7DX9L5J8sAQGIm1L0AAOhGo9EYb93f8kE6/2TvFBY1QY5iDfR8/qmRAABA1mSAfLTPAP5xM0l3AzEX7kWxBQiArNkOBFFT/XdhcjdfBAAJGRgY6HwOMFRt6BZD7cYbyFX/w0wAAGDclYFRANRL9d8LAQAA/kAGgFio/ntkCxAA/EWVYDsQBEvpXwgTAAD4C0YBECbVf1EEAAAYSQaA0Kj+C2QLEAD0emsg24GgPF0EbNV/eyYAANDawB+N60uMAqD2xr/qf0wmAADQjlEA1ELjvzwmAABQfFVhFAC9UP2XSgAAgLHZDgSVse2nbLYAAUCnbAeCUmn8V0MAAIASM4AYAOVNzFT/3bEFCAD6KthvYEcQFNv4V/13zQQAALphFAC90/ivhQkAAHSpuyrEKACGqP7rYgIAAN0bqkWMAmBclP71EgAAoIbtQGIAeep6Aqb6L5AtQABQgK4vSbQjiHx03fhX/RfLBAAACmMUAC1p/AdFAACA+q8KEANIldI/QAIAAIQyChADSEkv29tU/6VyDQAAlKKXjcsuDCDnxr/qv2wmAABQIqMAcqPxHz4BAAACvSpADCAuSv9YCAAAUAUxgIQp/eMiAABABDuCxADC1OP1Kqr/WggAABDNKEAMIBxK/3gJAABQAzGAeCn9YycAAEDcMUASoBq9351W6R8IAQAAIr4wYIiBAKUq5I0pVP/hEAAAIPpRwBAxgMIp/ZMkAABAKMQAwqH0T5gAAADJxgBJgFrqfqV/4AQAAEg2BhgI0Dmlfz4EAADIJQZIApRX9yv9IyIAAEAuMcBAgNUp/bMlAABApjFAEshTgXW/0j9SAgAAZBoDJIGsFFv3K/2jJgAAQHyGay9JgPbU/TQTAAAgYsUOBCSBZBRe9yv9UyIAAED0Co8BkkCkyqj7lf7pEQAAIBGF7wtqrimFgXyKfnV/wgQAAEhNGQOBIcYCOdT9Sv/kCQAAkKbyYoCxQJJF/xClfw4EAABIWUn7glYnDMRe9Kv7cyMAAEAWKkgCzdWqPBBsxT9E3Z8nAQAA8lJNEvjTU8gDgVX8Q9T9mRMAACBTpV4k0JI8UFfFP0zpjwAAALmrciAwZh2cZCSosdwfpu5ndQIAADCyRqw+DLSvlaMIBiEU+qtT9DMaAQAACGgs0HVtXWpICK24b0Pdz5gmjP0pAED2AkkCjEbdT+cEAABgfISBQCj66Y4AAAB0TxiomKKf3gkAAEAxhIGSKPoplgAAAJRCHuiaip9SCQAAQBXkgTZU/FRJAAAAapB5HlDxUyMBAAAIRZKpQK1PaAQAACB0UQQDhT59kfh/fkrHXPNLx3gAAAAASUVORK5CYII="
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_124
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'RcRcRcRc'}.\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is Stack the original shape on top of the {'layer1': 'CpCpCpCp'}.\nthe 4th action is Stack the original shape on top of the {'layer1': 'WrWrWrWr'}.\nthe 5th action is Cut the right side of the shape\nthe 6th action is rotate the shape counterclockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'ScScScSc'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'SwSwSwSw'}.\nthe 9th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:9)_279
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is Colorize the top layer of the original shape with the color white.\nthe 4th action is Colorize the top layer of the original shape with the color purple.\nthe 5th action is Stack the original shape on top of the {'layer1': 'SpSpSpSp'}.\nthe 6th action is Colorize the top layer of the original shape with the color blue.\nthe 7th action is Colorize the top layer of the original shape with the color yellow.\nthe 8th action is rotate the shape counterclockwise 90 degrees\nthe 9th action is Stack the original shape on top of the {'layer1': 'WuWuWuWu'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABAAAAATICAIAAAANxCANAAByhElEQVR4nO3de5jkZXkn7p5hADnISQlHVxSNgKuiJkHBjfEiGE/gIdaIxmx0NZp4GZN11w3uxlVzZZWNm93E1Y1ZY4Imgk6LrmeNCEajEo1BAY0HPIMiqCPIaUCY3yWdXznp6q6uqu/pfZ/nvv9JrBm6v9NV9an3eT7V3Zt27ty5BAAA5LB56AsAAAD6YwAAAIBEDAAAAJCIAQAAABIxAAAAQCIGAAAASMQAAAAAiRgAAAAgEQMAAAAkYgAAAIBEDAAAAJCIAQAAABIxAAAAQCIGAAAASMQAAAAAiRgAAAAgEQMAAAAkYgAAAIBEDAAAAJCIAQAAABIxAAAAQCIGAAAASMQAAAAAiRgAAAAgEQMAAAAkYgAAAIBEDAAAAJCIAQAAABIxAAAAQCIGAAAASMQAAAAAiWwZ+gKgV9dee+0hhxxy0003rfmnz3zmM1/72tf2flEANPKmN71prr+/+XZbtmzZc88999577wMOOODggw8+5JBDdtttt86uEQqyaefOnUNfA/TnL/7iL57xjGes96cHHXTQlVdeufvuu/d7UQA0smnTpuYfZI899vjX//pfP+ABD/iZn/mZU0899fDDD2/j0qBEBgByOfnkk88///wpf+Fd73rXox/96B6vCIAiBoBVH/Ckk0562tOe9mu/9mtbtni7BNH4HgASueKKKz70oQ+12yMDEM/OnTv/7u/+7pnPfOaxxx67bdu2oS8HWmYAIJFzzjnntttum/533v72t6/3HQIAZHPZZZc96UlPetaznnXzzTcPfS3QGgMAifz1X//1qlsOPPDAVbf88Ic/fPe7393jRQFQute+9rWPeMQjbrnllqEvBNphACCLz372s5/5zGdW3fiKV7xi8s2db37zm3u8LgA6sXOqW2+99eabb77mmmu+/vWvf/jDH/7f//t/P/GJT9x7773X+2gXXHDB8573vH7/BdAV3wRMFi984QvPPPPMXW/Zb7/9rrrqqkc96lGrvi14r732uuqqq/bdd9/erxGA1r4JeIETznXXXffHf/zHf/iHf/jDH/5wzb/w/ve//+EPf/hC1wgF0QCQws6dO88555xVNz7ucY/bc889n/CEJ6y6/cYbb3zHO97R49UBUIR99933937v9y688MKjjjpqzb/w0pe+tPeLgvYZAEjhIx/5yNe//vVVNz7pSU9aGQMmV0d+FhBAWscdd9y73/3uNd8O9LGPfewf/uEfhrgoaJMBgBTe+MY3rrrloIMOOuWUU5aWlo444oif+7mfW/Wn73//+3/wgx/0eIEAFOS444773d/93TX/6Lzzzuv9cqBlBgDiu/nmm5eXl1fd+IQnPGH8G38f//jHT/4nb33rW/u6QACK85znPGe33XabvP2CCy4Y4nKgTQYA4nvPe96zffv2Nd//s2Ly2wC8CwgguTvf+c7HH3/85O2TbyiF6hgAyPjj/w8++OCHPexh4/95z3ve8973vveqv3P++edfffXVvVwgACW6z33uM3njd7/73SGuBdpkACC4a665ZvIXez3xiU9cVexOlgC33nrrW97ylu4vEIBC3elOd5q88ZprrhniWqBNBgCCe8tb3nLTTTetuvH0009fdYt3AQEwy28S2G+//Ya4FmiTAYB07/85/PDDH/KQh6y68fjjj7/b3e626sa/+7u/u+KKKzq+QAAKteaPgzv44IOHuBZokwGAyC6//PIPf/jDq24cjUabN6/xyJ/8WUC33Xbbtm3burxAAMr1hS98YfLGBz7wgUNcC7TJAEBkZ5999m233bbh+3/WGwC8CwggrR07dlx00UWTt//8z//8EJcDbdq05vvbIIb73e9+F1988a633PWud/3qV786+at/V/b9hx9++He+851Vt3/lK1+ZfHcQAOVYM9UbnnDe+MY3PvWpT1114957733FFVcccMABTT4yDE4DQFiXXnrpqtP/0tLS1q1b13yd+PGTYfPmxz72sZO3v/nNb+7mAgEo1M033/yyl71s8vZnPetZTv8EYAAgrMlv/53y/p8VfhYQAEtLS89//vM/97nPrbrxLne5y+///u8PdEXQJm8BIqadO3ceddRR3/jGN3a98R73uMeXvvSlKf/VLbfc8lM/9VOTP/bhn/7pn4455phurhSAgt4CdP311//O7/zOn//5n6+6fb/99vvQhz50//vff9FrhIJoAIjpwx/+8KrT/9LS0pOe9KTp/9Xuu+/+6Ec/evJ2JQBAeNu3b3/lK19573vfe/L0f8ghh7z3ve91+icMDQAx/fqv//pkgl988cVr/l73Xb31rW/95V/+5VU3HnPMMf/0T//U9jUC0GEDcM4550z5T3bu3Lljx44bbrjhyiuvvPzyyy+66KKLL7548gfHLS0tnXLKKWedddbhhx/e6iXDkAwABLRjx45DDz101Tt5jj322Mk3dE664YYb7nznO994442rbr/ooouOP/74tq8UgBas99MdGrr//e//0pe+9NRTT+3ig8OAvAWIgN797ndPvo9/+rf/ju29996/9Eu/NHm7dwEB5LHPPvv86Z/+6ac+9Smnf0IyABDQG9/4xskbN/wGgOm/EcwPAwXI4/rrr//N3/zNI4444rnPfa63gBKPtwARzQ9+8INDDz10x44du954/PHHr/kLHde0ffv2n/qpn/rRj3606vYLL7zwhBNOaO9KASj6LUBjj3zkI//kT/7knve8Z6efBXqjASCat7zlLatO/3Ot/5eWlg488MBf+IVfmLzdu4AAcnrve9973/ve93/8j/8x9IVAO7a09HGg6N//tWnTprmO7wcffPDkjdu2bfujP/qjzZuNzQAV2PA9Drfddtv111//wx/+8IorrvjmN7/56U9/+hOf+MQFF1xw8803T/7lm2666QUveMHXvva1V77ylV4IqJ23ABHKN7/5zbve9a7dPao/9KEPPfShD+3ogwMw+C8C+973vnfWWWf9wR/8weQPk1jx4he/+CUveckCHxnKYYQllLPPPrvTmda7gABiu9Od7vQf/sN/+OIXv/iwhz1szb/wB3/wBx//+Md7vy5okwaAUO573/tecskl3X38gw8++Fvf+taWLd47BxCzARjbsWPHox/96A9+8IOTf3TKKaf8zd/8TZMPDsPSABDHxRdf3Onpf2lp6eqrrz7//PM7/RQAlGDPPfd8wxvecNBBB03+0Qc+8IFZfrMkFMsAQPBv/22ddwEBJHH44Yc/97nPXfOP3vOe9/R+OdAaAwBB7Ny585xzzll14z777HPDDTfsXNTZZ589+Yne9ra3rfkDIgCI51nPetaat3/sYx/r/VqgNQYAgvjQhz50+eWXr7rxMY95zF577bXwxzz11FMn//Mf/OAH73vf+xb+mABU5Igjjjj66KMnb/cWIKpmACCIN77xjZM3jkajJh9z3333feQjHzl5u3cBAeTxwAc+cPLG73//+0NcC7TDAEAEO3bsOPfcc1fduM8++6x5fJ/L1q1bJ298xzveccMNNzT8yABU4U53utPkjev9lgCoggGACN71rndNZvGjH/3ovffeu+FHfsxjHjP5Qa6//vp3vetdDT8yAFXYb7/9Jm/0y4CpmocvYX/+T8P3/6zYZ599HvWoR03e/uY3v7n5BwegfNdee+2MUwHUwgBA9bZv3z7549j23nvvNQ/uC3jSk540eeN73vOeH/7wh618fABKdvXVV0/eeOSRRw5xLdAOAwDVW15envy5nK28/2f8ofbZZ59VN950003/7//9v1Y+PgAl+8QnPjF547HHHjvEtUA7DABUr4uf/7Orvfba6zGPeczk7X4WEEB4X/ziF7/xjW9M3n7CCScMcTnQDgMAdfvGN77xkY98pLv3/0z5WUAf+MAH/Bg4gNj+1//6X2ve/uhHP7r3a4HWGACo29lnn71z585VNz7qUY+afNNOE4961KP23XffVTfecsstkz97FIAwLrroor/8y7+cvP0hD3nImr8dDGphAKBuXb//Z8Ud7nCHU089dfJ27wICiOqKK6544hOfuGPHjsk/+t3f/d0hrghaYwCgYp/+9KcvvfTSVTfutddeXTSza74L6G//9m+/853vtP65ABjWhRdeeMIJJ3zlK1+Z/KNHPOIRa35jGFTEAEC09f8jH/nIdt//M/6wkz/1+dZbb11eXm79cwEwlE984hP/9t/+2xNPPPGKK66Y/NNDDz10zTcFQV22DH0BsKDbbrvtnHPO6eH9Pyv23HPP0047bfI3jr3pTW967nOf28VnBKCJWd6l+aMf/WjHjh3XXnvtd7/73c9//vOf+tSnvv71r6/3lw866KD3ve99hx56aNtXCn3bNPkNlFCF888//+STT1514x3ucIerr7568ht2W/HOd77ztNNOW3Xjpk2bvv71r9/lLnfp4jMCMItNmzZ1/SmOO+64d7zjHb73lxi8BYhaTS7jV96o09Hpf2lp6Zd+6Zf233//VTfu3LnzzW9+c0efEYASPPWpT73wwgud/gnDAECVbrrppre+9a29vf9nxR577PHYxz528nY/Cwggqp/5mZ/56Ec/+ld/9Vd3vOMdh74WaI0BgCq9853vvOaaa1bdeIc73KHrn8yw5s8C+tSnPnXZZZd1+nkB6NO+++779Kc//aMf/egnP/nJE088cejLgZb5JmCqtNdee734xS9edeO/+lf/qusNzcMf/vCXvOQlk985MzmNAFC4TZs2bdmyZc8999x3330PPPDAQw455K53vesDHvCAE0888fjjj9+yxRmJsHwTMAAAJOItQAAAkIgBAAAAEjEAAABAIgYAAABIxAAAAACJGAAAACARAwAAACRiAAAAgEQMAAAAkIgBAAAAEjEAAABAIptGo9HQ1wClWF5eHvoSoD/yH8bkP6ls9ogHyGZ0O/kPkDP/twx9GQD0x9YfIKdd8//H3wNgCQSQZOuz6kb5D5Aw/zUAAMHZ+gPkNFon///5pwBZAgEk2fqvIv8BsuW/BgAgIFt/gJxGM+T/T34PgCUQQJKt/yryHyBV/msAAIKw9QfIaTRn/v+L3wRsCQSQZOu/ivwHyJP/czcANkxUzSmHYPrMZPlP1eQ/wYwaZPLmeZ8enj8AMbb+q8h/gCT573sAACpjEw+Q06il/F/dAFgCAeTZ+q8i/wEy5L8GAKACtv4AOY06yP81GgBLIIA8W/9V5D9A+PxfewAAIED06w0AajTqOP/XHQAsgQCqjv6FP4L8B4id/74HAKAgzXf2tv4ANRr1mP/T3gJkCQSQZOu/ivwHCJz/GgCAgdn6A+Q0Gij/N/gmYEsggCRb/1XkP0DU/NcAAAzA1h8gp1EB+b/xjwG1BAJIsvVfRf4DhMx/DQBAoq0PAP0rLf9n+kVglkAAMbY+85L/APHyXwMAkGjrA0A/Ss7/mRoASyCAGFufBch/gGD5rwEASLT1AaA7teT/rA2AJRBAgK3PYuQ/QKT81wAAJNr6ANCuGvN/jgbAEgig9q3PwuQ/QJj81wAAJNr6ANBc7fk/XwNgCQRQ9danCfkPMAqR/xoAgERbHwAWEyn/524ALIGAnGJsfRqS/0BCo3D5rwEASLT1AWB2UfN/kQbAEghIIt7Wpzn5D2QwCp3/GgCARFsfAKbLkP8LNgCWQEBUsbc+rZD/QEijNPmvAQBItPUBYFK2/F+8AbAEAsLIs/Vpi/wHYhilzH8NAJBatq0PACsy53+jBsASCKhXzq1Pi+Q/UKlR+vzXAADpZN76AGQm/9tpACyBgIrY+rRL/gO1kP+70gAAKdj6AOQk/ztpACyBgJLZ+nRK/gPFkv/r0QAAYdn6AOQk//toACyBgKLY+vRJ/gPlkP+z0AAAodj6AOQk/wdoACyBgGHZ+gxI/gMDkv/z0gAA1bP1AchJ/g/fAFgCAT2z9SmH/Af6JP+b0AAAVbL1AchJ/hfXAFgCAV2z9SmW/Ac6Jf/bogEAqmHrA5CT/C+9AbAEAlpn61ML+Q+0S/53QQMAFM3WByAn+V9ZA2AJBDRn61Mp+Q80JP+7pgEAimPrA5CT/K+7AbAEAhZg6xOD/AfmJf/7pAEAimDrA5CT/A/VAFgCAbOw9QlJ/gMbkv9Dqb4BWF5edsdDpWrf+sgfgJz5X7stg79ANn8FXVkjeRxARWqPftvrQvIfqE7t+R9D9Q3AaDRaeSU2BkD5WnmGlnP0FzgAefI/ki3BlkDGAChTgOi39V+AEgAIkP/xVN8A7FoCjBkDoBxRj/4SBiB8/ke1JfASyBgAwwoQ/bb+zSkBIKEA+R9bhAZgzRJgzBgA/Qt/9BcpAFHzP4MtSZZAxgDoR4Dot/VvnRIAMgiQ/3kEaQCmlwBjxgDoTp6jvwwBCJb/2WxJuAQyBkC7AkS/rX+S/AfaFSD/c4rTAMxYAowZA6C52qN/gXO/0AAIkP/JbUm+BDIGQM7ot/LvX2n5D+TMf6I1APOWAGPGAMgT/U2O/lICyKz2/GfIAaDYJdD4WOChCWtq/tTwRv/kis1/IHb+E7wBWLgE2JVCAIJFfytHf5kAJFR7/lPQAFDFEsgYAAGi39a/NFXkPxAg/8nVAEwvAc48cNsZ27fO/qGMAaSV7eg/PRyEAJBH7flPuQPAUEugM7ZvPfPAbSv/z+z/lTGAVBIe/efNBJpQAkCxas9/UjcAs3wngDEA4kX/Ykf/DXnWA+HVnv9UMwAMXgIYAyBM9Dc8+lv/90wJAOWoPf9ZQNgGYK4fB2QMILPao7+jrf+YpzkQVe35T60DQAklwJgxgGxqj/62jv7W/4NQAsCAas9/GorcACz2OwGMAWRQe/R3vfUf87wGgqk9/wkyABRVAowZA4iq9uhv/ehv/T8gJQD0qfb8J9QAUPIvBjYGEEnt0d/b1n/MExmIofb8J+YAUGYJMGYMoHa1R393R3/r/8EpAaBTtec/kQeAkkuAMWMANao9+vvf+o955gJVqz3/STEAFF4CjBkDqEXt0d/D0d/6vxBKAGhX7flPogGgihJgzBhAyWqP/gG3/mOeqkCNas9/Mg4AtZQAY8YASlN19C8wojc5+lv/F0UJAJnzn9QDQF0lwJgxgBJUHf09H/035LkJVKTq/GcoZQ0A1ZUAY8YAhlJ19A919Lf+L5ASAFLlP8MqawCotAQYMwbQp6qjv7St/5gnI1C+qvOfEhQ3ANRbAowZA+ha1dE/+NHf+r9YSgCInf+Uo7gBoPYSYMwYQBeqjv7Bj/4b8uwDilV1/lOaEgeAACXAmDGAtlQd/eUc/a3/C6cEgGD5T5lKHADClABjxgDSRn85R/8NeboBpak6/ylZoQNApBKg+RjgCZxW1dFf4NHf+r8KSgCoPf8pX6EDQLwSYOzMA7ctcApRCGRTdfQv9uQaavG/wpMLKETV+U8tyh0AQpYAC1cBK4wBGVQd/SUf/a3/K6IEIKeq85+6lDsABC4BVhgDiBT9JR/9N+TZBAyr6vynRkUPAIFLgDFjALVHfxVHf+v/6igBSKLq/KdeRQ8A4UuAMWNAWlVHfxVH/w15+gCDqDr/qV3pA0CGEmDMGJBK1dFf19Hf+r9SSgCiqjr/iaH0ASBPCTBmDAiv6uiv6+i/Ic8XoE9V5z+RVDAApCoBxowBIVUd/ZUe/a3/q6YEIIyq8594KhgAEpYAY8aAMKqO/kqP/hvyBAF6UHX+E1UdA0DOEmDMGFC1qqO/9qO/9X8ASgDqVXX+E1sdA0DmEmDMGFCdqqO/9qP/hjwjgO5Unf9kUM0AkLwEGDMGVKHe6F94Ei7qabLC+j8MJQAVqTf/SaWaAYBdGQOKVW/0Rzr6A/Sv3vwnoU1LVdnwudHkyTPlAFTyEWfhNWfOoJl+zG3yTrB6oz/k0X/68yLVg3/K/Vv+Wx97y38ykP9ks7z+o1oDUD1twODqjf6QR3+A3tSb/yRXWQOgBJhOG9DzBqje6I999Lf+D9kAKAFoSP6TzbIGIAltQG/qjf7YR3+ArtWb/1BxA6AEmJE2oKMNUL3Rn+Tob/0fuAFQAtBE5vwnp2UNQELagNbVG/1Jjv4AHak3/yFOA6AEmJc2oOEGqN7oz3b0t/4P3wAoAVhYtvyHZQ1ActqAhdUb/dmO/gDtqjf/IWwDoARYWPI2YPYNUL3Rn/bob/2fpAFQArCYDPkPu9IA8BPagA3VG/1pj/4AyfMfsjQASoAB24B6M67rlaej/1Cs/1M1AEoAFhA1/2E9GgBabgNSFQIzcvQHyMlLIdWpuwFQArQoSRvQxQbI0X9w1v8JGwAlAJnzH2ahAWBj2oAFOPoDC1teXk4Ym2G47xry+B9W9Q2AEqALgduAtjZAjv7lsP5P2wDUXgKMv/4lX2Qkted/GB75vdEAMB9twBSO/kArRqPRyvM6fGyG4T5qqN2ftUr2BkAJ0KlgbUCTDZCjf4Gs/5M3AGFKgCqutnY15n8YHuqD0ACwOG3AUP+EJq9VGY7+EKkEiBebYbgvungt81UdXJAGQAnQjwBtwLynakf/kln/zyJ8AxCvBKjismtURf5H4rE9OA0A7UjVBjj6A4OUAPXGZhi+5p2+lvnyliBOA6AE6FmlbcAsJ2xH/ypY/88oQwMQuASo4vpr4evctRkjxRe5NxoA2heyDXD0B4oqAcqPzTB8bft5IfN1LsTmpUBmDNDFTHnINtmF1+7MA7ctfAZdvt1SYk2+Ak2+8gFY/9Nn/pcWGjH+LcTgAVkpDQAtCNkGdMrWH5i3BNhVzuSk9hcyj9hyhGoAlADD0gbMwta/Oet/MpcAOZOTonjgBaABoGXagPXY+gMtlgBJkpOi+GVqYURrAJQAhdAG7MrWv0XW/0yRsAQInJwUxQMsGA0AHdIG2PoDPZQAwZKTorRy7veYLE3ABkAJUJqcbYCtfxes/9lQ5hIgQHJSFA+kwGIOABQozxjg6A8sbMocu23btsDJSVHmffBMf3DazhQo7ACgBChTk9Nt+S9mDa/Q0X8663+SlwBbt27ddrtgyUntR/9t27Zt3erwUxnfA0BN3xhQ7DtcG76+OvoDs38nwMoMMNeRq8zkpOoXshlnUY+6MoVtAJQAhWv4XpdydlrNt/5O/7Ow/mcugUuA8f+vDWDYrf/4f1r/10gDwJCqbgNs/YHBfxyQNoA+X8XmnTk9zIoVuQFQAqRqA/pca9n698z6nwVkKAHGtAF0fe+v9xiz/q+UBoAgbUA/ay1bf6DY3wmgDaCErf+Yx1XJgjcASoDqNN+Od7HWal4y2PovzPqfhaUqAca0AXS99R+z/q+XBoASldMGNH9RdO4H+v/FwNoABtn6j3kgFS5+A6AEqNewbUDzlZitf3PW/zSUswRo3gZU+mWhh63/mPV/1TQAlK7/NsDWHwhQAjRpAxQCtRtk6z/mYVO+TUtpbPhwbPJ4nfJMcxZsUfmliru7Rdb/rZiSTnm2vJ3mf9em3E0LnNgW29qW/PWZ3fQHfIx/Y29H/+kPpDBfzMAPBg0AudqA7jj6A8WWAGPagMCG3fqPeZxUIcX3AKzwnQBhlPbe+tKuJwbrf1qU/DsBWvneAD8sKO17/Sd5938AiQYAginh2F3CNQDhdTTxLnb+MwYUZbG7o4vF/wrbmVrkGgCUAPEMdQR39O+U9T+tUwK0uwY2BtR79G94+rf+j8H3ABBBn98b4NwP1P6dAK18Y4DvDRjKYo+E7rb+Yx4JFcnVACgBYut6K2/r3w/rfzqiBJhOG1C4hX9FQ/Ot/5j1fxgaAKLpog1w7geS0AYUqOEvhIZJ6RqAAZdASoA+tbWtt/XvmacJnaq6BJhytm59L6sNKMTCX88Wt/5jfvZ/JBqAmt6mSZ9tgHN/gbzAQJ+0AQOy9adTGRsAJUA2827xbf2H4glCD5QA89IGZN76j1n/B6MB6LsEOGP7VofLYtsAd03Jp38vMDAgbUAPbP3pTdIGoPYlEAA583+QEmBMG5Bq6z9m/R+PBqATSgCYi/U/VEQb0CJbfwaRtwGofQkEQM78H7YEaKsNKPkr3I/Ct/5j1v8haQC6ogSAGVn/Q8I2IHMhYOvP4FI3ALUvgQDImf+FlACt7KRTtQG1bP3HrP+j0gB0SAkAG7L+hzC0AVPY+lOU7A1A7UsgAHLmf2klwJg2oK1veBhq6z9m/R+YBqBbSgCYwvofotIGNJlkbP3pmgag+iUQADnzv9gSIHkb0OTKB9/6j1n/x6YB6JwSANZk/Q9J5GkDbP2phQYgwhIIgJz5X34JkKQNiLH1H7P+D08D0AclAKxi/Q85xWsDbP2pkQYgyBIIgJz5X1EJEKwNCLb1H7P+z0AD0BMlAIxZ/wNVtwG2/tROAxBnCQRAzvyvsQSotA2IuvUfs/5PQgPQHyUAWP8DlbYBtv5EogEItQQCIGf+V10CFN4GhN/6j1n/56EB6JUSgOSs/4GK2gBbf6LSAERbAgGQM/9jlACtHKBXdvZN7qyG/3mNp3/r/1Q0AH1TApCW9T/QWxWwWCHQfMCr8ehPQhqAgEsgAHLmf7ASoK230c+yzm/+LQR1vd1/Fev/bAwAA5j+RNpwSwo1sv4Hoh6vS742WJMBIOYSCICc+R+yBCj2qF3a9SzG+j8hA8AwlACkYv0PBDt2l3ANsDADQNglEAA58z92CTD4ETzY0d/6Pyc/BWgwMX4cULCyosZ/TvmPE+t/oOSfFDTv54IANACRl0AA5Mz/JCVAb1v5YFv/Mev/tAwAQ/KdAIRn/Q/0potjetSjP8kZAIIvgQBYWNT8D1kCtH5kD3/0j/0wYDoDwMCUAARm/Q8DSv78anJ8D3/0n0Xyx094BoDUSyAAcuZ/ku3vvEf5PEf/JA8A1mMAGJ4SgJCs/2Fw059leY6Asxzr8xz9Z7nr5XN4BoDsSyAAppP/QDAGgCIoAQjG+h8KoQRgFet/DADzsQQCyEn+A5H4TcCliPGLgVc556zPLhXmyU+7d10XvOE1F8j6Hyp6fdm6dWue975j/c8KDcB8LIEAcpL/QBgGgIL4TgACsP6HAvlOAKz/2ZUBYG6WQAA5yX8gBgNAWZQAVM36H4qlBEjO+p9dGQAWYQkEkJP8BwIwABRHCUClrP+hcEqAtKz/WcUAsCBLIICc5D9QOwNAiZQAVMf6H6qgBEjI+p9JBoDFWQIB5CT/gaoZAKqkBKAoHpBQESVAKtb/rMkAUOgSyBOSSDyeiUcJANTLAFArO1cK4aEI1VECJGH9z3oMAE0pAWA6j2SiUgIAlTIAVMzmlcF5EEKllADhWf8zhQGgBUoAWI/HMLEpAYAaGQDqZv/KgDz8oGpKgMCs/5nOANAOJQBM8uglAyUAUB0DQPVsYRmEBx4EoAQIyfqfDRkAWqMEgF153JKHEgCoiwEgArtYeuYhB2EoAYKx/mcWBoA2KQFghUcs2SgBgIoYAIKwkaU3HmwQjBIgDOt/ZmQAaJkSADxWyUkJANTCABCHvSw98DCDkJQAAVj/MzsDQPuUAGTmUUpmSgCgCgaAUGxn6ZQHGKSlBCicO4i5GAA6oQQgJ49PqLcE8PyNzf3LrgwA0djR0hEPLUjOjrlY7hrmZQDoihKAbDwyYYUSgNK4Z1nFABCQTS2t86ACbJrL5E5hAQaADikByMNjEnalBKAc7lMmGQBisq+lRR5OwJh9c1HcHSzGANAtJQAZeDTCJCUAJXBvsiYDQFi2trTCAwlYxda5EO4IFmYA6JwSgNg8DmE9SgCG5X5kPQaAyOxuachDCFiT3fPg3AU0YQDogxKAqDwCYTolAENxDzKFASA4G1wW5sEDTGEDPSBffBoyAPRECUA8HnswCyUA/XPfMZ0BID57XBbgYQNsyB56EL7sNGcA6I8SgEg86mB2SgD65F5jQwaAFGxzmYsHDDAj2+ie+YLTCgNAr5QAxODxBvNSAtAP9xezMABkYafLjDxUgLnYSffGl5q2GAD6pgSgdh5psBglAF1zTzEjA0AiNrtsyIMEWIDNdA98kWmRAWAASgDq5TEGTSgB6I77iNkZAHKx32UKDw9gYfbTnfLlpV2bzIsAAJCHBgAAABIxAAAAQCIGAAAASMQAAAAAiRgAAAAgEQMAAAAkYgAAAIBEDAAAAJCIAQAAABLZMv2P/Z7gri0vL1f99Z9+/eec9dmlwjz5afeu64I3vOZVzjxw28Kf6IztG/+q+cUek9MfJ7P8Bbow/d6sPX+O3nZgj9eSwpe3bp/+F7ZtWzx/erB169aoF1/yc1b+l0kDALQwPDRU5usWMLvCD9C1C/zllf+DMABAKLNs8ZtYbFUj3yH8+p/BlblKl/9lMgAAP6EEABYQeD9djsBfZPnfPwMARKMEANpl/V8LJQAzMgAA/4ISAJhL4M10aQJ/qeV/zwwAEJASAGiL9X9dlADMwgAArKYEAGYUeCddpsBfcPnfJwMAxKQEAJqz/q+REoANGQCANSgBgMzb6JIF/rLL/94YACAsJQDQhPV/vZQATGcAANamBABy7qHLF/iLL//7YQCAyJQAwGKs/2unBGAKAwCwLiUAkG0DXYvAd4H874EBAIJTAgDzsv6PQQnAegwAULejtx3Y6cdXAgB5ds91CXxHyP+uGQAgPiUAMDvr/0iUAKzJAADVUwIAvQm8da5R4LtD/nfKAAC0QAkAwOzk/7AMAJCiBGj4LiAlACQx/f0/gffN9drwTinzXUCzkP/dMQAA7VACADA7+T8gAwAEoQQAGrL+r5QSgHkZAIDWKAEAmJ38H4oBAOJQAgALs/6vmhKAuRgAgDYpAQCYnfwfhAEAQlECAAuw/g9ACcDsDABAy5QAAMxO/vfPAADRKAGAuVj/h6EEYEYGAKB9SgAAZif/e2YAgICUAMCMrP+DUQIwCwMAUBD5DpCT/O+TAQBiGrwE6G7J5EUC2mL9H5ISgA0ZAICyyHeAnOR/bwwAEJYSAJjC+j8wJQDTGQCA4sh3gJzkfz8MABCZEgBYk/V/eEoApjAAACWS7wA5yf8eGAAgOCUAsIr1fxJKANZjAAAKJd8BcpL/XTMAQHxKAGDM+j8VJQBrMgAA5ZLvADnJ/04ZACAFJQBg/Z+TEoBJBgCgaPIdICf53x0DAGShBIDkrP/TUgKwigEAKJ18B8hJ/nfEAACJbFgCNKQEgEpZ/4cX+C6W/wswAACtvQuoO/IdOn3/DxT7LiD53wUDAOSiBADy7IZJckfL/3kZAIB/QQkA8Vj/MwslQB4GAEhHCQBk2AqT6u6W/3PZMt9fh3k8+Wn3XqpKdRfckTO2b93wED+I0WhU7IIKimX9z+yWl5fLPEnL/3ZpACAjJQAQex9Mwjtd/s/OAACswXcCQAzW/8yr2EW7/G+RAQCSUgJAcoE3watsvV3zvxNG4Lte/s/IAAB5TZ8BlAAQeP0f+AjY5FifZwyY/gBQAoRnAAC6ogQAhtLkKJ9nDAhJ/s/CAACpKQEgqrTr/7aO7+HHACVAZgaAIRX77IK2KAGA3nRxZA8/BoQk/zdkAIDslAAQT7b1f9fH9KhjgBIgLQPAYIp9XkG7lABAjKN51DEgJPk/nd8ETK4nWLtnza5/kmZvjt524JR9oV8MDHVJsv4f6iy+8nnDfCW3bds25SvpFwNHpQEYhkdtDF/eut0v2ZmFEgAItokv4RqYTv5PYQCApmKMAb4TAGKIvf4v7dhd2vUsxncCJGQAGECxzyWaiDEGdEcJAEQ9apd8bcnJ//UYAKBNVY8BSgCoXcj1fy3H61quc01KgGwMAH0r9lnEypa6le92rXoM6I4SABjkSH30tgM3/JkNo9slHwNCkv9rMgDA2mNA80mgxhlACQD1Crb+7+3oPzkGNI+UGmcAJUAqBoBeFfv8YU3NxwBVwCpKAKCHJfrKub/JT2puPgaoAsoh/ycZAGAD2cYAJQDUKMb6v62jf1vXk20MUALkYQCAmWQbA7oz4O8U8yIBxSrt6J95DAhJ/q9iAOhPsaMzs0syBgz7G44XfqbId6hx/V/y0T/hGFD+A2ZN8n9eBgCYW5IxoLt3ASkBoF2V5kktR/+EY0DIVab835UBoCdVP2dIOAYoASCAYre5NR7984wBxT5sppP/czEAQCOxx4D1KAGgHHUFSO1H/zxjQMiFpvwfMwD0oepnC2nHACUAVK20PW6ko3/4MaC0B8+M5P/sDADQmpBjwHqUAFCCKhIj6tE//BgQcq0p/1cYADpX9fOE5GOAEgAqVcgGN8PRP+oYUMhDaF7yf0YGgCENuAGla5HGgPUoAWBYJUdEtqN/1DEg5HJzJP8NAF2r+hlCcwHGACUAVGfY3W3mo3+wMUAJEJgBYDDW/9nGgCb3+OBjwHqUADCUAjPB0X+9MaBJ2gw+BoRccY7S578BoENVPzfoQqVjgBIAKjLI1tbRf0OVjgFKgKgMAMOw/s+s0jFgPUoA6F85IeDon2EMCLnoHOXOfwNAV6p+VtCDusYAJQBUoc99raN/kjFACRCSAWAA1v9UOgasRwkAfRr8Wd/wALpy7s959K93DAi57hwlzn8DQCeqfj7QvyrGACUAFK6HTW0rR/9Wr6h6VYwBSoB4DAB9s/4v2RnbtzZfZsceA9ajBIB+DPU0d/TvVBVjQMil5yhr/hsAen0mOP1XwRiwnq5fv6f/w5UAMMiO1tG/NyWPAUqAYAwAsDZjwLwG/HI150WCKvT8vHb0H0TJY8B6lADVMQC0zPo/GGPAKkoAKFDr21lH/8EVOAYoASIxAMDGjAEzUgJAd/p5Ijv6F6XAMWA9SoC6GADaZP0fmzFghRIAitLWXtbRv1jljAFKgDAMAFDfGLDwJNBDG6AEgC50+sx19K9oDFg4pnpoA5QAFTEAtMb6P5Vhx4CGhUDzMUAJAIVouJF19K/RsGOAEiAGAwDkHQOWuqEEgHZ19Gx19M88Bix1QwlQCwNAO6z/M6t3DGhSBSgBYHAL72KbrIEd/WOMAU0eA0qAAAwA0I6cY8B6lADQlnafno7+IQ0yBqxHCVAFA0ALrP/JOQYoAWBA825hHf3D63MMUALUzgAArf2otZxjQEheJIjE0T+VotqAGo1y5L8BoCnr/3iMAbOPAVNOBq3825UAJLfeM3HG/aujf1o9jAFTHoQlvwtI/q/Y8s//F1grI5qn2Mo5eMBpcOVTL3AcXzl5pD0BjEajkl/DYLom5/62r4X6XshWHj+Vvs+nuVGC/NcANGL9H542YMM2QAkARa3/F976W/lH1V0boASolwYA5giLhommDahLhiUQkdj6M4U2YC6j6PmvAVic9X9CrRQC8doAJQAMu/639WeoNkAJUCkDAMzNGJDnJwV5kaBwjv4swE8KmkXs/DcALMj6n0hjwAIP2lVjgBIAel7/O/rTyqvYAjG46rGnBKiRAQAaiTEGLFwIZGgDkr9IUCBHf9rVyhgQ0ihu/hsAFmH9T0djwNLQmowBSgDoev3v6E+ZY4ASoDoGAChoDCihCmgyBiwFlflFgnI4+lPyGLAU1Cho/hsA5mb9z3TJx4D1KAGg50Ha0Z/BfwfOCiVAgQwA0AljQDBpXySokaM/BY4B9RpF/CIYAFrjkMQkY0DPJcDCQuY7Cdf/jv6UOQYoAUpjAIjzCKZYxoAYz9CcLxLUwtGfTiVvA0bh/u0GgHYUfiqiBMYAJQB0sf539KeKF7KSV6ijfPlvAAjy2KUWxoCuKQHIw9GfQeRsA0ax/slbhr6ACLo7Bhk5YudIk/t3ZQYY/Ai+cgFzDSRnbN/a/LLPPHBbF1PQaDTypKOK9b9zPzW+kC0vLxd7jB4ly38NwKxSPSzohzagI0oAYq/8nf4pR6o2YBToX2oAaKqocw81SjgG+E4AmHf979xPjBeyktepo0z5bwBYqv3xSgzBxoDBB2MlAGE4+lPXC1nshBxF+dcZABoZ/JRDMGHGgA0LASUAbLj+d/Qn5GtZyUvVUZr8NwBsrORHKiHlGQM6pQSgXo7+BBC1DRiF+EcZABZn/U/hXWrhY4ASACbX/47+BLPmC1nJq9VRjvw3AGyg5McoScQeAzqlBKAijv4EFqwNGNX/bzEALMj6n56FHAOUAGQ2Xv87+pPwhazkBesoQf4bAKYp+dFJTiHHgE4pASiZoz8JxWgDRpX/E/wm4EW0eHApoUlofiLs+WlgMGv4i4QL+S3CLV6DXwxMjRz9yazwA/Qoev5rANYV+45vax/c8xy/fLvePl3hwrQBXVMCANC6Uc35bwCYWwl70+YSHv2jDg/GgBW+EwCAFo1C57+3AK0t5ElxRfNz/1Jt90XgezPem4I6sry83N1DN3xTDECw/DcAzKfqE5Kjf3jJxwDfCQBAi0Zx898AsIZ4d7ajfyrJx4D1KAEAaN2ozvw3AMyhxiORo39aOccAJQAALRoFzX8DwGph7mZHf9KOAetRAgDQuhrz3wAwq4rOQI7+ZB4DlAAAtGgUMf8NAP9C7Xewoz9TpBoD1qMEAKB11eW/AWAm5R96HP2ZUYYxQAkAQItG4fLfAPATld61jv4sIMMYsB4lAADJ898AsLFiTzmO/jQUeAxQAgDQolGs/DcA/LO67lRHf1oUeAxYjxIAgMz5bwDYQGnHGkd/OhJvDFACANCiUaD8NwD8WBV3p6M/PRg/Thb74hc4BqxHCQBA2vw3AExTyDnG0Z+6CoFyxgAlAAAtGkXJfwNA0WdNR3+GFWMMWI8SAICc+W8AWNewBxdHf8pR9RigBACgRaMQ+Z99ACjwLnT0p0xVjwHrUQIAkDD/sw8A6xnkpOLoT/lqHAOUAAC0aFR//qceAMq58xz9qUuNY8B6lAAAZMv/1APAevo8mjj6U6+KxgAlAAAtGlWe/3kHgMHvNkd/YqhoDFiPEgCAVPmfdwBYTw9nEUd/4il/DFACANCiUc35bwDoW5MjiKM/sceAwauAjlT9IgFAvPzfvJTSendGp+ePM7ZvXfj0P7rdUo+WbzfsR6BSCz9cmzxHZjHlCd7ksdr/ZA5ACUbV5r8GoA9Nzv1LvbP1Z9g2oJBvDEiyBAIgYf5nbAD6XP8vvNHsf+Vv60+GNkAJAECLKs1/DUBXsm39Lf6ZQhtQ7BIIgIT5n64B6GH9n23rb/FPXW2AEgCAFtWY/xqANtn6w4YytwEFLoEASJj/uRqA7tb/tv5QURugBACgRdXlvwagKVt/WFjCNqC0JRAACfM/UQPQ+vrf1h/qbQOUAAC0qK781wAswtYfWjd+dsz7YKuuDShqCQRAwvzP0gC0tf639YeuLfZkWeC5qQQAoEUV5b8GYFa2/lD+twfU0gaUswQCIGH+p2gAGq7/bf0hahugBACgRbXkvwZgGlt/KEHINqCQJRAACfM/fgOw2Prf1h+StAFKAABaVEX+awBWs/WHkkVqA0pYAgGQMP+DNwBzrf9t/SFnG6AEAKBF5ee/BuDHbP2hRgHagMGXQAAkzP/Nydf/tv5Qu1baACUAAC0qPP/zNgC2/hBJvW2AEgAgp9Fw+b8l4frf0R+iajgGrBcOy8vLCz/9ne8BchoVnP9hB4D1LPyGn6XeOfpD/2PAIEp+kQAgXv7H/B6AFr+U3usPlWr3yes7AQAIk//pGoDZ2fpD2jagf0oAgJxGQ+R/wAag+RfR1h+CaeVJrQQAIEb+awCGv4ds/aEfhbcBSgCAnEa953+0BmCxL98gK39bfxhEk+e7EgCAAPmfvQGw9YecymwDlAAAOY36zf9QA8BcXzhHf2CcA7M/p/xOgFp8eev2oS8BoND8DzUAzMjRHyi2ECjtRQKAePkf53sAZvmSea8/0DwifCcAAFXnf5YGwNYfqKUNUAIA5DTqK/+DNABTvli2/sACpkeHEgCAevM/cgNg6w9U2gYoAQByGvWS/xEagMkvk60/0KI1I0UJAECl+R+tAbD1B2K0AUoAgJxG3ed/9Q3A+Atk6w/0YNeoUQIAUGP+R2gAbP2BkG2AEgAgp1HH+V/9ADDU1r+QDwLUmz/O9w3Jf6pbu0Ih+V/9ANAz0Q+kepFgTP4DYfLfADAr0Q+0zvm+CvIfCJb/BoCNiX5gQIaEAcl/IGT+GwCmEf1A15zvyyT/gcD5bwBYm+gHymFI6JP8B8LnvwFgNdEP9Mz5vhDyH0iS/waAnxD9QLEMCZ2S/0Cq/DcA/JjoB4blfD8U+Q8kzP/sA4DoB2phSGiX/AfS5n/eAUD0A0Vxvu+N/AeS53/GAUD0A5UyJDQk/4FKtZv/uQYA0Q+UzPm+O/IfKNmo3/zPMgCIfiAGQ8K85D8Qw6i9/I8/AIh+oCLO9y2S/0BFRj3mf+QBQPQDIRkSNiT/gZBGLeV/zAFA9AP1cr5vQv4D9Rr1lf/RBgDRD2RgSJgk/4EMRm3kf5wBQPQDYTjfz0X+A2GMesn/CAOA6AcSMiTIfyCnUeP8r3sAEP1AVM7308l/IKpR9/lf6wAg+gFyDgnyH2DULP/rGwBEP5BEzvP9FPIfSGLUcf7XNACIfoCcQ4L8B2gx/+sYAEQ/kFOS8/0U8h/IadRl/pc+AIh+gJxDgvwH6Cj/yx0ARD9A4PP9FPIfYKnL/C9xABD9ADmHBPkP0EP+lzUAiH6AwOf7KeQ/QG/5X8oAIPoBcg4J8h+g5/wffgAQ/QCBz/dTyH+AQfJ/89Jwlm/Xysdp43IA6jYajZYqIf8BBsz/YRqAtiJb9AN5xCgB5D/A4Pnf9wAg+gFyDgnyH6CQ/O9vABD9AIHP91PIf4Ci8r+PAUD0A+QcEuQ/QIH53+0AIPoBAp/vp5D/AMXmf1cDgOgHyDkkyH+AwvO//QFA9APkLAHkP0AV+d/mACD6AXIOCfIfoKL8b2cAEP0AOUsA+Q9QXf43HQBEP0DOIUH+A1Sa/4sPAKIfIGcJIP8Bqs7/RQYA0Q+Qc0iQ/wAB8n++AUD0A+QsAeQ/QJj8n3UAEP0AOYcE+Q8QLP83HgBEP0DOEkD+A4TM/809pPby7Zp/HAAWMBqNFviv5D9A1PzfYABoSPQDlHm+75r8Byg2/7saAEQ/QM4hQf4DFJ7/7Q8Aoh8gZwkg/wGqyP82BwDRD5BzSJD/ABXlfzsDgOgHyFkCyH+A6vK/6QAg+gFyDgnyH6DS/J/vNwHvSu4Tj0c1zMIzhXg8qkllkQbA1gcgZwkg/wEC5P98DYDcB8hJ/gOkawBsfQBylgDyHyBY/m/cAMh9gJzkP0C6BsDWByBnCSD/AQLn/9oNgNwHyEn+A4S3egAQ/QA5SwD5D5DBaDT6yQAg+gFykv8AqWzauXPn0NcAAAAU/IvAAACAShkAAAAgEQMAAAAkYgAAAIBEDAAAAJCIAQAAABIxAAAAQCIGAAAASMQAAAAAiRgAAAAgEQMAAAAkYgAAAIBEDAAAAJCIAQAAABIxAAAAQCIGAAAASMQAAAAAiRgAAAAgEQMAAAAkYgAAAIBEDAAAAJCIAQAAABIxAAAAQCIGAAAASMQAAAAAiRgAAAAgEQMAAAAkYgAAAIBEDAAAAJCIAQAAABLZMvQFQH927Nhx4YUXfvSjH/385z9/2WWXXX755dddd931119/22237bXXXvvss89hhx12xBFHHHvssfe73/1OOumko446auhLBgBo2aadO3e2/TGhLDt27HjnO9/5+te//rzzzrvppptm/w/vec97PvGJT3z6059+z3ves8sLBGBub3rTm+b6+5s2bdq8efNuu+2255577rXXXvvtt9+d7nSnQw89dK+99ursGqFQBgAiu+GGG1796le/4hWvuPrqq5t8nNNOO+0lL3nJ/e9///YuDYBGNm3a1MrHOfLII4877rgHPOABD33oQx/ykIfsu+++rXxYKJkBgLDe9KY3/c7v/M53vvOdVj7a5s2bn/Oc57z85S/32gAQaQDY1Z577vmIRzziKU95yuMf//jdd9+99Y8PhTAAEND3vve9ZzzjGW9/+9tb/8j3ute93v72t9/rXvdq/SMDMPgAMHbEEUc873nP+63f+i1vECIkAwDRfO5znzvttNO+/OUvT/k7P/3TP/3ABz7w2GOPvfOd73zHO97xxhtv/P73v799+/ZLLrnk4x//+Pbt26f8t/vvv//73//+E044oYNrB6CIAWDFXe5ylz/8wz88/fTTu/5E0DMDAKF87GMfe+QjH3nttdeu+adHHnnkb/zGbzzlKU+5293utt5H2Llz5yWXXPJ//+//ff3rX3/dddet+Xf233//888//wEPeEB7Fw5AcQPAitFo9JrXvOaggw7q59NBDwwAxPEP//APJ5988pqn//322+9FL3rRb//2b8/+ns5rrrnmxS9+8Stf+co1nyNHHnnkJz7xicMOO6zxVQPQ2gAw/VTzox/96NZbb73hhhuuu+66q6+++mtf+9pnP/vZT37yk3/7t3+73uZoxd3vfvd3v/vdxxxzTBsXDsMzABDEV77ylZ/92Z/9/ve/P/lHP/uzP7tt27bFfqj/eeed99SnPnXN7yQ+5ZRT/uZv/mahiwVggAFgPTfffPMHP/jBP/uzP3vnO9952223rfl3DjzwwPe+973e/0kMBgAiuOGGG0488cTPfOYzk3/02Mc+dtu2bXvsscfCH/zSSy996EMfuuZo8drXvvaZz3zmwh8ZgBIGgLFLLrnkP/7H/7jecueAAw44//zz/UhoAjAAEMEznvGMv/iLv5i8/bTTTjv33HO3bGn6G68/+clP/pt/82927Nix6vZDDz30sssu22effRp+fABKGABW/Nmf/dnznve8m2++efKPDjvssE996lPe/0ntNg99AdDUeeedt+bp/373u9/ZZ5/d/PS/8iaiF73oRZO3X3nlla95zWuaf3wAyvHsZz/7gx/84P777z/5R9/+9re3bt166623DnFd0BoNAHXbsWPHscce+9WvfnXV7XvvvfenP/3pe97znm19oltuueWBD3zgJZdcsur2u9/97l/60pc2bzZLAwRpAFZ8/OMf/8Vf/MUbbrhh8o/+6I/+6PnPf35bnwj659RC3V7zmtdMnv6XlpZe9rKXtXj6X1pa2n333V/84hdP3v6Vr3zlYx/7WIufCIASPPjBD37d61635h+9+MUvvvzyy3u/ImiNAYCK3XjjjWeeeebk7cccc8xzn/vc1j/d4x73uCOPPHLy9re97W2tfy4ABnf66ac/+clPnrz9uuuuW/PVB2phAKBif/3Xf33llVdO3v7f/tt/22233Vr/dLvtttuzn/3sydsvuOCC1j8XACX47//9v++1116Tt7/uda9b8wUIqmAAoGKvfe1rJ288+uijH/e4x3X0GR/zmMdM3njxxRdff/31HX1GAAZ0l7vc5T/9p/80eftNN9101llnDXFF0AIDALW69NJLP/nJT07e/pznPKe7b8m93/3ud/DBB6+68dZbb/3CF77Q0WcEYFj//t//+z333HPy9je84Q1DXA60wABArd7+9rdP3rhp06bTTz+9u0+6adOmk08+efL2L33pS919UgAGtP/++69Z//7T7Ya4ImiqhR+RDoN4z3veM3njiSeeePjhh3f6eU8//fTJHzN3xzvesdNPCsCAfuVXfuXcc8+dvP2888479thjh7giaMTvAaBK11133QEHHDD5q1he9KIX/f7v//5AFwVAnN8DsKubb775wAMPnPydAI9//OPf+ta3dvEZoVPeAkSVLrroojV/EeNDH/rQIS4HgMj22GOP+9znPpO3f/rTnx7icqApAwBV+sd//Mc1bz/++ON7vxYA4lvz9eVrX/vaD3/4wyEuBxoxAFClz33uc5M3HnrooXe6052GuBwAMg4AO3fu/PKXvzzE5UAjBgCq9M1vfnPyxrvf/e5DXAsA8R133HFr3v6tb32r92uBpgwAxBkADjvssCGuBYD4DjjggDVv//a3v937tUBTBgCq9N3vfnfyxslf0QUArdhvv/3WvP3aa6/t/VqgKQMAVZr8WWxLS0t77bXXENcCQHz777//mrffeOONvV8LNGUAoEo33XTT5I13uMMdhrgWAOJbrwHYsWNH79cCTRkAqNKPfvSjyRv9VjsAOrLmL59ZWlrafffde78WaMoAQJX23HPPGWsBAGhuvU2/8pkaGQCo0ppv91/zGwMAoLn1fuHX3nvv3fu1QFMGAKp0xzvecfLGq6++eohrASC+73znO2vefuihh/Z+LdCUAYAqHX744ZM3XnnllUNcCwDxrffz/o844ojerwWaMgBQpTUD9ytf+coQ1wJAfF/84hfXvP2ud71r79cCTRkAqNLd7na3yRu/853vfP/73x/icgAI7vOf//zkjQcffLC3AFEjAwBVuu9977vm7Z/5zGd6vxYA4rvwwgsnb7zf/e43xLVAUwYAqrRe5n7kIx/p/VoACO6aa6659NJLJ28/8cQTh7gcaGpL448AAzjuuOP233//a665ZtXtF1xwwX/9r/+100/97/7dv1v180b32GOPN7zhDZ1+UgAG9N73vnfNXwR2yimnDHE50NQmvzyVSj3hCU9429veturG3Xbb7corr7zzne/c0Sf98pe/fI973GPVjUcdddRXv/rVjj4jAGvatGnT5I0dnWpGo9Fb3vKWVTcecMABV111ld8ETI28BYhaPeIRj5i88dZbbz333HO7+6Qf+MAHJm+cHAkACOOqq656+9vfPnn7k570JKd/KmUAoFZPeMIT1kzeP/3TP+3uk5533nmTN97nPvfp7jMCMKxXvepVt9xyy+Ttv/ZrvzbE5UALDADU6s53vvMjH/nIyds/85nPXHDBBV18xhtvvPGDH/zg5O0nnXRSF58OgMF973vf+5M/+ZPJ20844YQHP/jBQ1wRtMAAQMWe/exnr3n7f/kv/6WLT3f22Wf/4Ac/WHXj7rvv/rCHPayLTwfA4F7wghdce+21k7f/5//8n4e4HGiHAYCKPepRjzr++OMnb//4xz/+5je/ufVP9+pXv3ryxpNPPvmggw5q/XMBMLh3v/vdf/mXfzl5+0knnXTqqacOcUXQDgMAdfu93/u9NW//rd/6re9+97stfqK3vOUtF1100eTtv/7rv97iZwGgEJdddtmv/uqvTt6+2267vfrVr17zZxBBLQwA1O2Xf/mX13wHztVXX/2rv/qrt912Wyuf5Qc/+MHznve8yduPPvroxz72sa18CgDKcfnll59yyinbt2+f/KMXvvCFfgEwtTMAUL1XvepVa/44oPe9730veMELmn/8nTt3/uZv/ua3v/3tyT96+ctfvttuuzX/FACU45JLLjnxxBO/9rWvTf7Rz//8z7/kJS8Z4qKgTQYAqnfccce9/OUvX/OP/uf//J8vfOELG3785z73uW9605smb//FX/zF0WjU8IMDUI6dO3e+5jWvedCDHvTNb35z8k+PPvrobdu22fsQgN8ETAQ7d+487bTT3vWud635p6effvqf//mf77PPPvN+2Ouvv/63f/u3X/e6103+0YEHHnjxxRcfeeSRC10vAMX9JuDzzz//hS984Sc+8Yk1//SQQw756Ec/evTRRy/88aEcBgCCuPbaa3/hF35hze/TXVnb/PEf//FjHvOY2T/ghz/84Wc84xmXXXbZ5B9t2bLlfe9738knn9zgegEoYgD4whe+8I53vOOv/uqvLrnkkvX+zlFHHfWBD3zA730nDAMAcVx11VUPechDvvSlL633F0444YTnPe95p5566h3veMf1/s611177rne965WvfOXf//3fr/kXNm/efNZZZ635oyEAGHYAOOecc6b8J7feeuvNN998/fXXb9++/corr7zsssv+8R//ccMfGffgBz/43HPPPeywwxpfMpTCAEAoV1111Wmnnbbe2X3FHnvs8aAHPeg+97nPPe5xj/3333/33XfffrtvfetbF1544SWXXDLlZwftvvvuZ5111lOe8pRuLh+AWfXwgzg3b978/Oc//2Uve9maP2oC6mUAIJobb7zxN37jN97whje0/pEPOeSQc88996STTmr9IwNQ2gDwcz/3c//n//yfBz7wgZ1+FhiEnwJENHvttdfrX//6t73tbYceemiLH/ZXfuVXLr30Uqd/gPBOPPHEd7zjHX//93/v9E9UGgDCuv7661/1qle94hWv+N73vtfk4zz84Q9/6Utf+qAHPai9SwOguAbguOOOe+xjH/vUpz71uOOOa/cjQ2kMAAR34403vu1tb3v9619/wQUX3HLLLbP/hz/90z/9+Mc//ulPf/q97nWvLi8QgJ4GgM2bN2/ZsuUOd7jDPvvsc8ABBxx88MF3uctdjjnmmHvf+94nnnjiIYcc0s2VQnEMAGRx/fXXf+xjH/voRz/6hS984bLLLvv2t7993XXXXX/99Tt37txrr7322Wefww477MgjjzzmmGOOP/74k0466aijjhr6kgEA2mcAAACARHwTMAAAJGIAAACARAwAAACQiAEAAAASMQAAAEAiBgAAAEjEAAAAAIkYAAAAIBEDAAAAJGIAAACARDaNRqOhrwFKsby8PPQlQH/kP4zJf1LZ7BEPkM3odvIfIGf+bxn6MgDoj60/QE675v+PvwfAEgggydZn1Y3yHyBh/msAAIKz9QfIabRO/v/zTwGyBAJIsvVfRf4DZMt/DQBAQLb+ADmNZsj/n/weAEsggCRb/1XkP0Cq/NcAAARh6w+Q02jO/P8XvwnYEgggydZ/FfkPkCf/524AbJiomlMOwfSZyfKfqsl/ghk1yOTN8z49PH8AYmz9V5H/AEny3/cAAFTGJh4gp1FL+b+6AbAEAsiz9V9F/gNkyH8NAEAFbP0Bchp1kP9rNACWQAB5tv6ryH+A8Pm/9gAAQIDo1xsA1GjUcf6vOwBYAgFUHf0LfwT5DxA7/30PAEBBmu/sbf0BajTqMf+nvQXIEgggydZ/FfkPEDj/NQAAA7P1B8hpNFD+b/BNwJZAAEm2/qvIf4Co+a8BABiArT9ATqMC8n/jHwNqCQSQZOu/ivwHCJn/GgCARFsfAPpXWv7P9IvALIEAYmx95iX/AeLlvwYAINHWB4B+lJz/MzUAlkAAMbY+C5D/AMHyXwMAkGjrA0B3asn/WRsASyCAAFufxch/gEj5rwEASLT1AaBdNeb/HA2AJRBA7Vufhcl/gDD5rwEASLT1AaC52vN/vgbAEgig6q1PE/IfYBQi/zUAAIm2PgAsJlL+z90AWAIBOcXY+jQk/4GERuHyXwMAkGjrA8Dsoub/Ig2AJRCQRLytT3PyH8hgFDr/NQAAibY+AEyXIf8XbAAsgYCoYm99WiH/gZBGafJfAwCQaOsDwKRs+b94A2AJBISRZ+vTFvkPxDBKmf8aACC1bFsfAFZkzv9GDYAlEFCvnFufFsl/oFKj9PmvAQDSybz1AchM/rfTAFgCARWx9WmX/AdqIf93pQEAUrD1AchJ/nfSAFgCASWz9emU/AeKJf/XowEAwrL1AchJ/vfRAFgCAUWx9emT/AfKIf9noQEAQrH1AchJ/g/QAFgCAcOy9RmQ/AcGJP/npQEAqmfrA5CT/B++AbAEAnpm61MO+Q/0Sf43oQEAqmTrA5CT/C+uAbAEArpm61Ms+Q90Sv63RQMAVMPWByAn+V96A2AJBLTO1qcW8h9ol/zvggYAKJqtD0BO8r+yBsASCGjO1qdS8h9oSP53TQMAFMfWByAn+V93A2AJBCzA1icG+Q/MS/73SQMAFMHWByAn+R+qAbAEAmZh6xOS/Ac2JP+HogEABmPrQxPLy8seAFCp2vN/ufL82TL4F6j2ryCQMPopJP9XagQPBqhI7fm/HKK91AAA/WkltZ32WDEajVZeiY0BUL4A+b+8y9G/9sDpYwBQAgABop/C898YAGUKkP/LIbb+u9IAAN0KEP2UXwKMGQOgHFGP/qP6E6anAUAJAAkFiH4qzX9jAAwrQP4vh9v670oDALQvQPRTbwkwZgyA/oU/+o9CREp/A4ASADIIEP0Ey39jAPQjQP4vh97670oDALQjQPQTrwQYMwZAd/Ic/UdRMqTXAUAJACEFiH6S5L8xANoVIP+X02z9d6UBAFJHP3lKgDFjADRXe/4vz3/ujxQaW3IugYDk0U//Sst/YwDkzP/llCv/VTQAQK7oJ6q5SoAxYwDkyf8mR/9RrJQYYAAobQkEzKj5E9NTO7li8398LPAQhZD5b+u/igYAiB/9JLFYCbArhQAEy/9Wjv6jcJkwzABQ7BIICBb9lKaK/DcGQID8t/WfQgMAxIx+cppSApx54LYztm+d/UMZA0gr29H/zKnhEDIEBhsAqlgCQU61Rz+FGyr/z9i+9cwDt638P7P/V8YAUkl49F+aMxNi0AAAcaIfZvlOAGMAxMv/xY7+G4r6rB9yAFACQDlqj37qMngJYAyAMPnf8Oh/Rr71vwYAqD76ocmPAzIGkFnt+d/R1n8s8NN84AFACQADqj36qVoJJcCYMYBsas//to7+Z6Rc/w8/AACDqD36oYvfCWAMIIPa87/rrf9Y7Of18AOAEgD6VHv0E0lRJcCYMYCoas//1o/+Z2Rd/xcxAAD9qD36oc9fDGwMIJLa87+3rf9Y+CdyEQOAEgA6VXv0E1iZJcCYMYDa1Z7/3R39z0i8/i9lAAA6Unv0w4AlwJgxgBrVnv/9b/3HMjxzSxkAlADQrtqjnzwKLwHGjAHUovb87+Hof0bu9X9BAwDQltqjHwosAcaMAZSs9vwfcOs/luSpWtAAoASA5NFPWrWUAGPGAEpTdf4vMKI3OfqfkX79X9YAAOSMfqirBBgzBlCCqvO/56P/hkZpnptlDQBKAEgV/VBvCTBmDGAoVef/UEd/6/8SBwAgSfRDjBJgzBhAn6rO/9K2/mOpnozFDQBKAIgd/RCvBBgzBtC1qvN/8KO/9X+5AwAQNfohdgkwZgygC1Xn/+BH/w2Nkj37ShwAlAAQLPohTwkwZgygLVXnfzlHf+v/0gcAIEz0Q84SYMwYQNr8L+fov6FRvqdboQOAEgBqj35YTKQSoPkY4FmcVtX5X+DR3/q/jgEAkqs6+qFk/ZcAY2ceuG2BU4hCIJuq83+xJ9dQi/8VOZ9c5Q4ASgByqjr6oRUhS4CFq4AVxoAMqs7/ko/+1v81DQCQTdXRDxUZsARYYQwgUv6XfPTf0Cjrs6noAUAJQBJVRz90IXAJMGYMoPb8r+Lob/1f3wAA4VUd/VCvwUuAMWNAWlXnfxVH/w2NEj99Sh8AlABEVXX0Qw8ylABjxoBUqs7/uo7+1v+1DgAQT9XRD2GUUwKMGQPCqzr/6zr6b2iU+/lSwQCgBCCMqqMf+peqBBgzBoRUdf5XevS3/q97AIAAqo5+iKrAEmDMGBBG1flf6dF/Q6P0T5A6BgAlAPWqOvphcDlLgDFjQNWqzv/aj/7W/xEGAKhR1dEPSZRcAowZA6pTdf7XfvTf0MgzoqIBQAlARaqOfihN8hJgzBhQhXrzf+FJuKinyQrr/zgDAFSh3ugHqmAMKFa9+R/p6M+MNi1VZcPnhmijScw1eSdAvdFPbFMe1eW/9aW3/J/ypSj5iLPwmjNn2sj/JEf/6c+LVA/+5fXvXw0ANFVv9ANV0wYMrt78D3n0J2wDoASgqA1QvdFPHmEaACXAdNqADcn/DEd/6/9daQCgZfVGPxCSNqA39eZ/7KM/wRsAJQDDboDqjX5yitQAKAFmpA1YU+b8T3L0t/5fRQMALag3+oFUtAGtqzf/kxz9SdEAKAHoeQNUb/RDsAZACTAvbUDa/M929Lf+n6QBgAXVG/0A2oCc+Z/t6E+iBkAJQNcboHqjH2I3AEqAhSVvAzLkf9qjv/X/mjQAMId6ox9gCm1A4PxPe/QnXQOgBGABXa88PeQoTcgGQAkwYBtQb9BFzX9Hf+v/9WgAoHOZIwbI0wakKgRm5OhPdepuAJQAlLAB8hijZFEbACVAi5K0AZHy39F/zPp/Cg1AuZaXl5M/OqvmvmvI4x9KoA1YgKN/Q2ds31raJaVSfQNQewkwfiaXfJGRtLUBcn815JHfm8ANgBKgC4HbgNrzP9LRv60Ls/6fTgNQrtFotHL3pF2iVMd91FC7P2sPaJc2YApH/4Z2fVyVdm3ZRGgAwpQAVVxt7ZpsgNwvDXmoDyJ2A6AE6FSwNqDG/A959F9h/d8DDUAdJUCeJUp13BddZJCvKhROGzDUP6HJrFL+0b/Ai0woSAMQrwSo4rJrNG+q+vo35LE9uPANgBKgHwHagCryP/zRf4X1fz80APWVAPGWKNXxNe/0ZcyXF+qSqg1w9G9o+uOktKvNKU4DELgEqOL6a+HrXMhrmC9ybzI0AEqAnlXaBhSb/2GO/jM+MKz/e6MBqLsEqHeJUh1f235ew3ydoWoh2wBH/yZmfzAUddmZbV4KZMYDdO2W/39DXwj8Mw9IYuf/lKNhk1147c48cNvChzmh0eQr0OQr37oztm/t+Vlg/d8KDUBlJUAVexTyWOAFzCMWIgnZBnQq4da/zOtPLlQDkKcE2JU9CoPwwKM0SoABaQNmYevfyqee8qfZhskmNAB1lwDJ9ygMosZfpgP0QBuwnsxb/zL/IURrAHKWAAn3KAzCA4zCKQFKoA3Yla1/u9cw5U+jTo8d0QDEKQGS7FEYRCsvyR6TkIc2wNa/2H8RMRuA5CVA4D0Kg/BAoi5KgKLkbANs/btg/d8uDUBlJcA5Z332yU+7d7Y9CoOY9wVs+oPTgxDSytMGpN36T8//ov5pRG4AApcAT37avc8567PnnPXZJHsUBjHvA2blMTnXaArdUQKUqckpsPxXsYZXWO/Wv5/8t/5vnQag1u8EWJkBtAEMvvWf5a951AENq4BiX8UaTiZFHf27yP9y/oGkaABilwDj/18bwLBb//H/tP6nKEqAkjV8m3s5r2LNt/6FHI4X2/qP/6f1f400ABF+HJA2gIUt8Oo178zpYQYEawNibP0X+OLPm/+F/EuZtGkpug3ToeTTyZSIWe9JuMAgXvJXoOfU9qWYbrFHXaqval13dCFr1Erzf8pXz6FnXs2bk1nuylby39F/rvxv/u+1/m9iysNVAxDtdwJoAyhh6z/mcQV03Qb080Lm6F/pP5mkDUDCEmBMGzApeQPQxdHf+r9wmRsAJUCNumsDFsv/5k+TwEd/6//CaQCS/mJgbQCDbP3HPJCAetsAR/8A/3ZSNwCZS4CG36Rf8pdlMQkbgE6P/tb/5UveACgBqtZuGzB7/jv6z8L6v3wagLwlQJM2QCFQu0G2/mMeNkB1bYCjfysK+SIwRZYGQAmwq8xtQJIGoJ+jv/V/FTQASoAYyv8dC6mO/tb/VdAAVK+VEmBMGxDYsFv/MY8ToLQ2oDupjv61fDXI+5uAE/5i4Lks8FuEi/oVjDS/axZ7DKzwq3+piF8MHEY5vz23qOuZ91f5Fp7/1v890AAkLQHGzjnrsws8k7UBRVnsgdHF4meFBwYQvg0o4dy/8Behu/wv5MvChhI1AEqA1tcA2oDBLXYXNFn8rLD+pzpKgHiG2r7Xu/WvIv+t//uhAahJRyVAk28M0AYMpbSt/5hHAhC1DSjh3F/g1r+0rw+zSPRTgMb8OKDu5vuSv3QxfgpQw98K1wo//KcufgrQrvw4oNi6GwNKuAcX/tf1lv9++E9p/BQg5qMNKFAJR3+AbG2Aoz8hZWwAlACZ24AaG4Cijv7W/9XRAPSW/9O/niWcI1NpPgaUcJcVdfQfdv3vJWYBGgAWpw0YUFFHf2DAb9OizzbA0b9AjhPtStoAKAHStgG1NABlHv2t/2ukAZikBMhm9sN0CfdRmUd/6/8aaQBohzYg7dEfaF4CnLF9awnny4RmaQNKuGvKPPr3wOm/f7l+D0CY3wkw5ZnQww9o93sDOrLw16f5z3WehfU/YVSd/4S02A/1LyT/S5idmJcGgAVpA1pk6w9hKAGYS9qt/5j1/yDyNgC1L4GGLQHaagNK/gr3o/Ct/5j1P8FUnf/EUPjWf8z6PyQNAEO2AZkLAVt/iEoJwHS2/mPW/0NJ3QDUvgQqpARoZSeRqg2oZes/Zv1PSFXnP5WqZes/Zv0flQaAlmkDprD1hySUAKxi6z/J+n9A2RuA2pdApZUAY9qAtr7hYaitz5j1P4FVnf9UtPKva+s/Zv0fmAaADmkDmpweAm99IAMlQHILr/yT5L/1/7A0ANUvgYotAZK3AU2ufPCtz5j1P+FVnf+UaeGVf0X5b3ytnQaAnuRpA2z9gRVKgGxs/Wdk/T84DUCEJVD5JUCSNiDG1n/M+p8kqs5/ChFj6z9m/R+eBoABxGsDbP2BNSkBwrP1n5f1fwk0AEGWQBWVAMHagGBb/zHrf1KpOv8ZSrCt/5j1fwYaAAZWbxtg6w/MQgkQj63/wqz/C6EBiLMEqrEEqLQNiLr1H7P+J6Gq85/eRN36j1n/J6EBoCDltwG2/sAClAAB2Po3Z/1fDg1AqCVQ1SVA4W1A+K3/mPU/aVWd/3Qn/NZ/zPo/Dw0AhSqnDbD1B5pTAtTI1r9F1v9F0QBEWwLFKAFaCdCVnX2TO6vhf15j+lv/k1zV+U8hW/+Q+W9ADUYDQOQqYLFCoPkLfI3RD3RNCVC+Jof+FfJ/Tdb/pdk09AWUa8PHYskP1imvMVVnU/klRuAvb8kPeBZLA8vs/vN/+tfcAFD44T5t/jd/ZBoABjElcLwFiJqU/N1UJV8bUIjpp5yuT6h0RP5P5/RfIANAzHeCBvtOgMKjtrTrWYz1P8TIf/qUIf8VUyEZAKhVCbFbwjUAdVECxCD/Z2T9XyYDQNglUOwSYPAIDhb91v8QKf/pVKr8t/6PygBABH3GcbDoB/qnBKiU/J+X9X+xDACRl0BJSoDeojlq9Fv/Q7z8p10589/6PzADANF0EdNRox8YihKgFvJ/Ydb/JTMA5F0ChSwBWo/s8NEf+2EADUXNf2Yh/wnMABBc8vG6SXyHj/5ZJH/8QKeUAMWS/83f/2P9XzgDQOolUJLpf94ozxP9SR4A0ETU/GdN8p8kDADxTR+y80TALLGeJ/pnueutZ6BrSoByyP9dWf+HZwCYlSUQQE7yHwjGAJCCEoBVrP+hEEoAemb9jwFgPpZAADnJfyASA0AWSgDGrP+hKEoAemP9zwoDwHwsgQBykv9AGAaARJQAWP9DmZQA9MD6nzEDwNwsgQBykv9ADAaAXJQAyVn/Q7GUAHTK+p9dGQAWYQkEkJP8BwIwAKSjBEjL+h8KpwSgI9b/rGIAWJAlEEBO8h+onQEgIyVAQtb/UAUlAK2z/meSAWBxlkAAOcl/oGoGgKSUAKlY/0MYSgDqWv9TJgNAI5ZAADl1l/8GciLxeC6TASAvJUAS1v8QjJ0rM7L+Zz0GgKaUAAA5KQFgOo/kYhkAUlMChGf9DyHZvLIh63+mMAC0QAkAkJMSANbjMVwyA0B2SoDArP8hMPtXprD+ZzoDQDuUAAA5KQFgkkdv4QwAKAFisv6H8GxhWZP1PxsyALRGCQCQkxIAduVxWz4DAD+mBAjG+h+SsItlFet/ZmEAaJMSACAnJQCs8IitggGAf6YECMP6H1KxkWXM+p8ZGQBapgQAyEkJAB6rtTAA8BNKgACs/yEhe1ms/5mLAaB9SgCAnJQAZOZRWhEDAHNQAhTOHQRp2c4m13X+e4AFYwDoRL0lgPE9NvcvdE0JQJkavv9nQx6fdTEAMB875mK5ayA5O9q0rP+ZlwGgK0oASuOehX4oASiN9T+rGACYm01zgdwpgE1tTtb/LMAA0CElAOVwn0KflACUw/qfSQYAFmHfXBR3BzBmX5uK9T+LMQB0SwlACdyb0D8lACWw/mdNBgAWZOtcCHcEsIqtbRLW/yzMANA5JQDDcj/CUJQADMv6n/UYAFic3fPg3AXAmuxuw7P+pwkDQB+UAAzFPQjDUgIwFOt/pjAA0IgN9IB88YEpbHADs/6nIQNAT5QA9M99ByVQAtA/63+mMwDQlD30IHzZgQ3Z44Zk/U9zBoD+KAHok3sNyqEEoE/W/2zIAEALbKN75gsOzMg2Nxjrf1phAOiVEoB+uL+gNEoA+mH9zywMALTDTro3vtTAXOx0w7D+py0GgL4pAeiaewrKpASga9b/zMgAQGtspnvgiwwswGY3AOt/WmQAGIASgO64j6BkSgC6Y/3P7AwAtMl+ulO+vMDC7HerZv1PuzaZ5wAAIA8NAAAAJGIAAACARAwAAACQiAEAAAASMQAAAEAiBgAAAEjEAAAAAIkYAAAAIBEDAAAAJLJl+h+X/3uCl5eXp/zptm3beryWFLZu3eC3hZ9z1meXqv1t6lVffMnP2enP01n+Al2Y/mgp87FEk+fRmQemfk08Y/vWevO/UrO8bMn/QWgAaJMA7VTgL6+zJnQt+emfYsn/QRgAaHP9z+DKXKXId8j53AfKZACgNYH30+UI/EU2JEB3rP8pmfzvnwGAWVn/16LMRaB8h2zPeqBYBgDaEXgzXZrAX2pDAnTB+p/yyf+eGQCYifV/XcpcB8p3yPN8B0pmAKAFgXfSZQr8BTckQLus/6mF/O+TAYCNWf/XqMyloHyHDM90oHAGAJoKvI0uWeAvuyEB2mL9T13kf28MAGzA+r9eZa4G5TvEfo4D5TMA0EjgPXT5An/xDQnQnPU/NZL//TAAMI31f+3KXBDKd4j67AaqYABgcYE30LUIfBcYEqAJ63/qJf97YABgXdb/MZS5JpTvEO95DdTCAMCCAu+e6xL4jjAkwGKs/6md/O+aAYC1Wf9HUuayUL5DpGc0UBEDAIsIvHWuUeC7w5AA87L+Jwb53ykDADAY+Q7zsv4HmjMAMPf7fwLvm+u14Z1S76HBkACzs/4nEvnfHQMAMCT5DrOrd5KHSfJ/QAYAVrP+r5QSAJKz/ice+d8RAwAwMPkOs6h3hof1yP+hGAD4F6z/q6YEgLSs/4lK/nfBAAAMT75D1OkdppP/gzAA8BPW/wEoASAh639ik/+tMwAARZDvEG9uh1nI//4ZAPhn1v9hKAEgFet/MpD/7TIAAKWQ7xBpYofZyf+eGQD4Mev/YJQAkIT1P3nI/xYZAICCyHeAnOR/nwwAWP/HpASAAKY/T63/yUb+t8UAAJRFvgPkJP97YwDIzvo/MCUAVM36HybJ/1YYAIDiyHeAnOR/PwwAqVn/h6cEgEpZ/8N65H9zBgCgRPIdICf53wMDQF7W/0koAaA61v8wnfxvyAAAFEq+A+Qk/7tmAEjK+j8VJQBUxPofZiH/mzAAAOWS7wA5yf9OGQAysv5PSAkAVbD+h9nJ/4UZAICiyXeAnOR/dwwA6Vj/p6UEgMJZ/8O85P9iDABA6eQ7QE7yvyMGAH7C+j+8wHexFwlqZ/0Pi5H/CzAA5DL9/T9Q7LuA5DtATvK/CwYA4u+GSXJHe5GgXtb/0IT8n5cBIBHrf2ahBACgKPK/dQYAgm+FSXV3e5GgRtb/0Jz8n4sBIAvrf2anBACgKPK/XQYAIu+DSXine5GgLtb/0Bb5PzsDQArW/8xLCQBAUeR/iwwA2QXeBK/y5Kfd+8lPu3fzvxNG4LveiwS1sP6Hdsn/GRkAUq//Ax8Bmxzr84wB0x8ASgAAiiL/22IAILImR/k8Y0BIXiQon/U/dEH+z8IAEFza9X9bx/fwY4ASAICKyP9WGACIposje/gxICQvEpTM+h+62zHJ/w0ZACLLtv7v+pgedQxQAgBQEfnfnAGACPo8mkcdA0LyIkGZrP9hhRJgKAaAsJKs/4c6jgcbA5QAAFRE/jdkAKBWJRzBS7gGpvMiQWms/2FXSoBBGABiir3+L+3YXdr1LEYJAEBF5H8TBgBqUvJRu+RrS86LBOWw/odJSoD+GQACCrn+r+V4Xct1rkkJAEBF5P/CDABkOVJvu930vzO6XfIxICQvEpTA+h/WowTomQEgmmDr/96O/pNjQPPIqHEGUAIAUBH5vxgDAIVqvkRfOffPdfRfpfkYoAoohxcJhmX9D9MpAfpkAAglxvq/raN/W9eTbQxQAgBQEfm/AAMABSnt6J95DAjJiwRlsv6Hrsn/VQwAKZS//i/56J9wDCj/AbMm+U6xiq3OIMYzRf7PywCQ4v0/Javl6J9wDAh5lPEiQWms/6Ef8n9XBoD4it3m1nj0zzMGFPuwmU6+U6CqZ2bomRKgHwaAIOpa/9d+9M8zBoQ80HiRoBzW/9An+T9mAAiutD1upKN/+DGgtAfPjOQ7Ral6WoZBKAF6YACIoIr1f9Sjf/gxIOSxxosEJbD+h/7J/xUGgMgK2eBmOPpHHQMKeQjNS75TiKrnZBiQEqBrBoDqlbz+z3b0jzoGhDzceJFgWNb/MJSR/DcABDbs7jbz0T/YGKAEgIQTMgxOCdApA0DdClz/O/qvNwY0iaTBx4CQRxwvEgzF+h+GfSKM0ue/ASCmQba2jv4bqnQMUAJAqtkYCqEE6I4BoGLlrP8d/TOMASEPOl4k6J/1P4wpAYZiAAioz32to3+SMUAJAEmmYiiKEqAjBoBaDb7+b3gAXTn35zz61zsGhDzueJGgT9b/sIoSYBAGgGh62NS2cvRv9YqqV8UYoASA8PMwFEgJ0AUDQJWGWv87+neqijEg5KHHiwT9sP4fyhnbt56xvZTvmmOSEqB/BoBQutvROvr3puQxQAkAC0/CTv+DcPSvxfQniBKgdQaA+vS8/nf0H0TJY8B6lABAORz9mdEoZf4bAOJofTvr6D+4AscAJQCsx/q/EI7+lVIC9MkAUJl+1v+O/kUpcAxYjxIAGJCjP4sZ5ct/A0AQbe1lHf2LVc4YoASASdb/w3L0j0EJ0Jst/X0qyl7/N/99Xu1dCxun2GI5uHIvd3qCX15erjdqR6NR1SUGJOTcTytGyfJfAxBBw/OcrX+2QqB5G6AEgF1Z/w/C1j8kJUA/DADZ1/+O/pnHgKVuVL1E8SIB5XP0pwujTPlvAKjewrvYJmtgR/8YY0CTx4ASAFZY//fJ0T8DJUAPDAAZ1/+O/iENMgasRwkAtMvRnx6M0uS/AaBu825hHf3D63MMUAKA9X8PHP0TUgJ0zU8ByqLhe/1bvRY6t5JxC0RkDz8mqArZfhwElKmtc//CkUhCoxz5rwGo+P0/M57SbP3T6qENmPIgLDlALYFohfV/+Vv/hr9BhQEpATqlAYisybm/7WthMNqAxSRZAkHsrT8sYJQg/zUAMdf/C2/9rfyj6q4NUAKQk/V/62z9WUUJ0B0NQDS2/kyhDZhLhiUQlMDWn9KMoue/BiDO+t/Wn6HaACUA2Vj/t8XWn+mUAB3RAERg688CtAGzCL8EgqG0de5v41ogXf5rAOpe/9v608rabIEX0VWPPSUAeVj/l7D1t/LPQwnQBQ1ArWz9KaEQyNAGxF4CQZ9s/anLKG7+awDqW//b+tOdJm2AEoAMrP8XZuvPwpQArdMAVGbho38H10JYTdqAkAIvgaCWo39L1wLziZr/GoCa1v8LsPWnkGVbyQHqbMGMrP/7f7u/rT8rlADt0gCE5dzPsD8sKJioSyDoiK0/YYwi5r8GIOD639af1rWyhCs5QB01aML6f1e2/tT1RBulfLAZAEJx9KdTyV+VM//bKXyCLYSjP1GfoaNwD0sDQJD1v6M/vWnyCl3yESpevtMP639Hf3qjBGiLAaB6jv4MIuerdcJ/MuXPrsNy9KccSoDZ+Sbgitf/zv3U+C3Cy8vLxcZoyO/0olOZ1//Bvs038A8yDubMA7e18hvlkue/AaA+zv2UJtVPCsr2IkGex3bgo797MI9Od0yjQPlvAKhp/e/oT4wxQAlADAnX/47+lEAJ0JwBoA6O/tRi/OoeOEZTvUjgvl7h6E8tlACzMACUvv539CdkIaAEoHZ51v+O/hRICdCQAaBcjv4EEPXbA/K8SCSX/F529KdSSoANGQBKXP87+pNhDFACUK/w639Hf8qnBGjCAFAWR38CC9YGJHmRyCzn/evoTwxKgOkMAKWs/x39STgGKAGoUdT1v6M/1VECLMwAMDxHfxKK0QZkeJFIK9U96+hPSEqAKQwAA3P6J7Ni1/8x8p0uBFv/O/rXEkftfh0iPYyVAIvZvOB/B0BthwZmFPuFf8UZ27c2PDaNbrfUl+Xb9fbpCtfwi9/83q9Fp4+ZUc35bwAAiJnvtC7G3jTh0T/q8GAM6PSJOQqd/94CBNBI+KY4m8D3ZvNz/1Jt90Xge7Otb6laeVTEGG7X5DsB1mQAAIiZ77Sr6hOSo394yccA3wkwLwMAQFOBXySyiXc/OvqnknwMWI8SYJIBACBmvtOiGo9Ejv5p5RwDlABzMQAAtCDqi0QqYe5BR3/SjgHrUQKsYgAAiJnvtKWiM5CjP5nHACXA7AwAAO0I+SKRR+33naM/U6QaA9ajBNiVAQAgZr7TivIPPY7+zCjDGKAEmJEBAKA18V4kkqj0XnP0ZwEZxoD1KAHGDAAAMfOd5oo95Tj601DgMUAJMAsDAECbgr1IZFDX/eXoT4sCjwHrUQKsMAAAxMx3GirtWOPoT0fijQFKgA0ZAABaFulFIrwq7ilHf3owfpws9sUvcAxYz7ISwAAAEDXfaaKQc4yjP3UVAuWMAUqA6QwAAO0L8yIRW8n3kaM/w4oxBqxnOX0JYAAAiJnvLGzYg4ujP+WoegxQAkxhAADoRIwXicAKvHcc/SlT1WPAepZzlwAGAICY+c5iBjmpOPpTvhrHACXAegwAAF0J8CIRVTn3i6M/dalxDFjPcuISwAAAEDPfWUCfRxNHf+pV0RigBFiTAQCgQ7W/SIQ0+D3i6E8MFY0B61nOWgIYAABi5jvz6uEs4uhPPOWPAUqASQYAgG5V/SJBi5ocQRz9iT0GDF4FZMv/zUNfAEDd+j+Z0cR6L8adnj/O2L514dP/6HZLPVq+3bAfgUot/HBt8hyZxZQn+HKDx2q9+a8BAMi7BKJrTc79S72z9WfYNqCQbwzIkP8aAICm6l0CZdPn+n/hjWb/K39bfzK0AUqAXWkAAPIugehCtq2/xT9TaAOWisx/DQBACypdAqXSw/o/29bf4p+62gAlwJgGACDvEoi22PrDhjK3AaPC8l8DANCOGpdAeXS3/rf1h4raACXACg0AQN4lEE3Y+sPCErYBo5LyXwMA0JrqlkBJtL7+t/WHetuAM5UAGgCAzEsg5mXrD60bPzvmfbBV1waMisl/DQBAm+paAmXQ1vrf1h+6ttiTZYHn5pnpSwANAEDeJRCzsPWH8r89oJY2YFRG/msAAFpW0RIovIbrf1t/iNoGnJm7BNAAAORdArEeW38oQcg2YFRA/msAANpXyxIotsXW/7b+kKQNODNxCaABAMi7BGJXtv5QskhtwGjo/NcAAHSiiiVQYHOt/239IWcbcGbWEkADAJB3CYStP9QoQBswGjT/NQAAXSl/CZR5/W/rD7VrpQ04M2UJoAEAGJISoH+2/hBJvW3AaLj8NwAAdMj5vqj1v6M/RNVwDDhjnXBYXl5e+Olfcv4bAAAGVvKLRCQLv+FnqXeO/tD/GJAq/30PAEC3Cn8naDAtvpR6rz9Uqt0n73LE7wTQAAAMTwlQFFt/SNsGJMl/DQBA54pdAgXT/EXU1h+CaeVJvRyuBNAAABRBCTCgoV6hbf2hH4W3AaPe818DANCHMpdAkSz28jnIyt/WHwbR5Pm+HKsE0AAAlEIJ0Cdbf8hpVGQb0HP+Bx8Atm4d7Oc6AazifN+dub6wjv7A6P/PgdmfU5F+J0DwAQCgLqW9SATj6A8UWwj0mf++BwCgPwW+EzSAWV4yvdcfaB4Ry1G+E0ADAFAWJUC7bP2BWtqAUV/5rwEA6FVRS6AAprxY2voDCxhNjY4YJYAGAKA4SoCGbP2BStuAUS/5rwEA6Fs5S6DaTb5M2voDLRqtFSkBSgANAECJlADzsvUHYrQBo+7zXwMAMIBClkBVG79A2voDPRjtEjW1lwAaAIBCKQE2ZOsPhGwDRh3nf/UDwFBbn0I+CDWO3bDC+b4h+Q9Umj+jofO/+gGgZ6If6NPgLxKMyX8gTP4bAGYl+oHWOd9XQf4DwfLfALAx0Q8MyJAwIPkPhMx/A8A0oh/omvN9meQ/EDj/DQBrE/1AOQwJfZL/QPj8NwCsJvqBnjnfF0L+A0ny3wDwE6IfKJYhoVPyH0iV/waAHxP9wLCc74ci/4GE+Z99ABD9QC0MCe2S/0Da/M87AIh+oCjO972R/0Dy/M84AIh+oFKGhIbkP1CpdvM/1wAg+oGSOd93R/4DJRv1m/9ZBgDRD8RgSJiX/AdiGLWX//EHANEPVMT5vkXyH6jIqMf8jzwAiH4gJEPChuQ/ENKopfyPOQCIfqBezvdNyH+gXqO+8j/aACD6gQwMCZPkP5DBqI38jzMAiH4gDOf7uch/IIxRL/kfYQAQ/UBChgT5D+Q0apz/dQ8Aoh+Iyvl+OvkPRDXqPv9rHQBEP0DOIUH+A4ya5X99A4DoB5LIeb6fQv4DSYw6zv+aBgDRD5BzSJD/AC3mfx0DgOgHckpyvp9C/gM5jbrM/9IHANEPkHNIkP8AHeV/uQOA6AcIfL6fQv4DLHWZ/yUOAKIfIOeQIP8Besj/sgYA0Q8Q+Hw/hfwH6C3/SxkARD9AziFB/gP0nP/DDwCiHyDw+X4K+Q8wSP5vXhrO8u1a+ThtXA5A3Uaj0VIl5D/AgPk/TAPQVmSLfiCPGCWA/AcYPP/7HgBEP0DOIUH+AxSS//0NAKIfIPD5fgr5D1BU/vcxAIh+gJxDgvwHKDD/ux0ARD9A4PP9FPIfoNj872oAEP0AOYcE+Q9QeP63PwCIfoCcJYD8B6gi/9scAEQ/QM4hQf4DVJT/7QwAoh8gZwkg/wGqy/+mA4DoB8g5JMh/gErzf/EBQPQD5CwB5D9A1fm/yAAg+gFyDgnyHyBA/s83AIh+gJwlgPwHCJP/sw4Aoh8g55Ag/wGC5f/GA4DoB8hZAsh/gJD5v7mH1F6+XfOPA8ACRqPRAv+V/AeImv8bDAANiX6AMs/3XZP/AMXmf1cDgOgHyDkkyH+AwvO//QFA9APkLAHkP0AV+d/mACD6AXIOCfIfoKL8b2cAEP0AOUsA+Q9QXf43HQBEP0DOIUH+A1Sa//P9JuBdyX3i8aiGWXimEI9HNaks0gDY+gDkLAHkP0CA/J+vAZD7ADnJf4B0DYCtD0DOEkD+AwTL/40bALkPkJP8B0jXANj6AOQsAeQ/QOD8X7sBkPsAOcl/gPBWDwCiHyBnCSD/ATIYjUY/GQBEP0BO8h9gKZP/D1P2imNdwqKaAAAAAElFTkSuQmCC"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_169
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is Colorize the top layer of the original shape with the color blue.\nthe 4th action is Stack the original shape on top of the {'layer1': 'RyRyRyRy'}.\nthe 5th action is Stack the original shape on top of the {'layer1': 'RpRpRpRp'}.\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'ScScScSc'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'WpWpWpWp'}.\nthe 9th action is Colorize the top layer of the original shape with the color yellow.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_183
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'SpSpSpSp'}.\nthe 2th action is Stack the original shape on top of the {'layer1': 'RbRbRbRb'}.\nthe 3th action is Stack the original shape on top of the {'layer1': 'WbWbWbWb'}.\nthe 4th action is Stack the original shape on top of the {'layer1': 'WyWyWyWy'}.\nthe 5th action is Stack the original shape on top of the {'layer1': 'CpCpCpCp'}.\nthe 6th action is rotate the shape counterclockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'WrWrWrWr'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'CbCbCbCb'}.\nthe 9th action is Stack the original shape on top of the {'layer1': 'WcWcWcWc'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_304
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'SySySySy'}.\nthe 2th action is Stack the original shape on top of the {'layer1': 'RwRwRwRw'}.\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is rotate the shape counterclockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'CpCpCpCp'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'WcWcWcWc'}.\nthe 9th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:9)_55
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is Stack the original shape on top of the {'layer1': 'WgWgWgWg'}.\nthe 3th action is Cut the right side of the shape\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is Stack the original shape on top of the {'layer1': 'RcRcRcRc'}.\nthe 6th action is Cut the right side of the shape\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is Cut the right side of the shape\nthe 9th action is Stack the original shape on top of the {'layer1': 'CuCuCuCu'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_125
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is Stack the original shape on top of the {'layer1': 'SySySySy'}.\nthe 5th action is Stack the original shape on top of the {'layer1': 'WuWuWuWu'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'RyRyRyRy'}.\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is Stack the original shape on top of the {'layer1': 'RuRuRuRu'}.\nthe 9th action is Stack the original shape on top of the {'layer1': 'CgCgCgCg'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:9)_208
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color green.\nthe 2th action is Colorize the top layer of the original shape with the color blue.\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is Stack the original shape on top of the {'layer1': 'SwSwSwSw'}.\nthe 5th action is Stack the original shape on top of the {'layer1': 'WrWrWrWr'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'RuRuRuRu'}.\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is rotate the shape clockwise 90 degrees\nthe 9th action is Stack the original shape on top of the {'layer1': 'RcRcRcRc'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:9)_190
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color cyan.\nthe 2th action is Cut the right side of the shape\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is Colorize the top layer of the original shape with the color purple.\nthe 6th action is Stack the original shape on top of the {'layer1': 'CgCgCgCg'}.\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is Cut the right side of the shape\nthe 9th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:9)_460
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is Colorize the top layer of the original shape with the color white.\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is Cut the right side of the shape\nthe 8th action is Cut the right side of the shape\nthe 9th action is Colorize the top layer of the original shape with the color purple.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABAAAAATICAIAAAANxCANAAA8V0lEQVR4nO3debReVX038HszEDKQCWJCCCVMQkKBACoQqMhCkClhkECKWEtBUBaipaWWVgq4LFCprVKoWEQBZUoYygwSEgSBCGKARGQI8xQIEBIy3UBy3/X2dt03732e3Nx7n/M855z9+3z+abufm3O2a9m993f/9jmnubW1tQkAAIihV94dAAAAGkcAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACKRP3h2AhlqyZMnIkSNXrlxZ9dcTTzzxsssua3inAKjJdddd162/7/U/+vTp069fvwEDBgwdOnTEiBEjR47s3bt33foIBdLc2tqadx+gcX72s5+dcMIJ6/p1+PDhCxYs6Nu3b2M7BUBNmpuba7/IBhts8Kd/+qe77rrrpz71qUmTJo0ePTqLrkERCQDEst9++82cObOTP7j99tsPOeSQBvYIgEIEgA4X3Guvvf7yL//yK1/5Sp8+jkuQGs8AEMgbb7xx//33Z1tHBiA9ra2tv/nNb0488cRx48ZNmzYt7+5AxgQAArn22mvXrFnT+d/ccsst63pCAIBo5s+ff8wxx5x00kmrVq3Kuy+QGQGAQH75y192aBk2bFiHlg8//PCOO+5oYKcAKLrLLrvswAMP/Oijj/LuCGRDACCKP/zhD08++WSHxgsvvLDycOf111/fwH4BUBetnVq9evWqVasWL178yiuvPPDAA//xH/9x1FFHDRgwYF1XmzVr1mmnndbY/wRQLx4CJoozzzzzggsuWLtl8ODB77zzzsEHH9zhseD+/fu/8847gwYNangfAcjsIeAerHCWLl36wx/+8Pvf//6HH35Y9Q/uueeeAw44oEd9hAJRASCE1tbWa6+9tkPj4Ycf3q9fvyOPPLJD+4oVK2699dYG9g6AQhg0aNB3vvOd2bNnjx07tuofnHvuuQ3vFGRPACCEBx988JVXXunQeMwxx7TFgMqtI+8CAghr/Pjxd9xxR9XjQA8//PDvfve7PDoFWRIACOHqq6/u0DJ8+PD999+/qalps802+8xnPtPh13vuueeDDz5oYAcBKJDx48d/+9vfrvrTjBkzGt4dyJgAQPpWrVo1ffr0Do1HHnlk+xd/jzjiiMp/ctNNNzWqgwAUzimnnNK7d+/K9lmzZuXRHciSAED67rzzzkWLFlU9/9Om8jEAp4AAgttkk00mTJhQ2V55oBRKRwAg4uv/R4wYse+++7b/n9tuu+0OO+zQ4W9mzpy5cOHChnQQgCLacccdKxvffffdPPoCWRIASNzixYsrP+x11FFHdSjsVhYBVq9efcMNN9S/gwAU1MYbb1zZuHjx4jz6AlkSAEjcDTfcsHLlyg6NU6dO7dDiFBAAXfmSwODBg/PoC2RJACDc+Z/Ro0fvvffeHRonTJiw5ZZbdmj8zW9+88Ybb9S5gwAUVNXXwY0YMSKPvkCWBABS9vrrrz/wwAMdGqdMmdKrV5X/5le+C2jNmjXTpk2rZwcBKK5nn322snG33XbLoy+QJQGAlF1zzTVr1qxZ7/mfdQUAp4AAwmppaZkzZ05l+2c/+9k8ugNZaq56vg3SsPPOOz/11FNrt2yxxRYvvfRS5ad/2/b7R48e/fbbb3dof/HFFytPBwFQHFVH9RpXOFdfffVxxx3XoXHAgAFvvPHG0KFDa7ky5E4FgGTNmzevw+q/qanp6KOPrjpP/N//Z+jV67DDDqtsv/766+vTQQAKatWqVeedd15l+0knnWT1TwIEAJJV+fhvJ+d/2ngXEABNTU2nn376008/3aFx8803/+53v5tTjyBLjgCRptbW1rFjx7766qtrN26zzTbPP/98J//qo48++sQnPlH52oc//vGP22+/fX16CkCBjgAtW7bsW9/61k9/+tMO7YMHD77//vt32WWXnvYRCkQFgDQ98MADHVb/TU1NxxxzTOf/qm/fvoccckhluyIAQPIWLVp00UUX7bDDDpWr/5EjR951111W/yRDBYA0ffWrX60cwZ966qmq33Vf20033fTFL36xQ+P222//xz/+Mes+AlDHCsC1117byT9pbW1taWlZvnz5ggULXn/99Tlz5jz11FOVL45ramraf//9r7jiitGjR2faZciTAECCWlpaRo0a1eEkz7hx4yoPdFZavnz5JptssmLFig7tc+bMmTBhQtY9BSAD63q7Q4122WWXc889d9KkSfW4OOTIESASdMcdd1Se4+/88d92AwYM+MIXvlDZ7hQQQBwDBw788Y9//Pjjj1v9kyQBgARdffXVlY3rfQCg8y+CeRkoQBzLli37+te/vtlmm5166qmOgJIeR4BIzQcffDBq1KiWlpa1GydMmFD1g45VLVq06BOf+MTHH3/coX327Nm77757dj0FoNBHgNoddNBBP/rRj7bddtu63gUaRgWA1Nxwww0dVv/d2v5vamoaNmzY5z73ucp2p4AAYrrrrrt22mmnf/3Xf827I5CNPhldBwr9/a/m5uZuLd9HjBhR2Tht2rQf/OAHvXqJzQAlsN4zDmvWrFm2bNmHH374xhtvvPbaa0888cSjjz46a9asVatWVf7xypUrzzjjjJdffvmiiy4yEVB2jgCRlNdee22LLbao33+r77///n322adOFwcg9w+Bvffee1dcccX3vve9ypdJtDn77LPPOeecHlwZikOEJSnXXHNNXTOtU0AAadt4443/5m/+5rnnntt3332r/sH3vve9Rx55pOH9giypAJCUnXbaae7cufW7/ogRI958880+fZydA0izAtCupaXlkEMOue+++yp/2n///X/1q1/VcnHIlwoA6XjqqafquvpvampauHDhzJkz63oLAIqgX79+V1111fDhwyt/uvfee7vyZUkoLAGAxB//zZxTQABBjB49+tRTT63605133tnw7kBmBAAS0draeu2113ZoHDhw4PLly1t76pprrqm80c0331z1BREApOekk06q2v7www83vC+QGQGARNx///2vv/56h8ZDDz20f//+Pb7mpEmTKv/5Bx98cPfdd/f4mgCUyGabbbb11ltXtjsCRKkJACTi6quvrmycMmVKLdccNGjQQQcdVNnuFBBAHLvttltl4/vvv59HXyAbAgApaGlpufHGGzs0Dhw4sOryvVuOPvroysZbb711+fLlNV4ZgFLYeOONKxvX9ZUAKAUBgBTcfvvtlWPxIYccMmDAgBqvfOihh1ZeZNmyZbfffnuNVwagFAYPHlzZ6GPAlJr/+pLs+39qPP/TZuDAgQcffHBl+/XXX1/7xQEoviVLlnQxFUBZCACU3qJFiypfxzZgwICqC/ceOOaYYyob77zzzg8//DCT6wNQZAsXLqxsHDNmTB59gWwIAJTe9OnTK9/Lmcn5n/ZLDRw4sEPjypUr//u//zuT6wNQZI8++mhl47hx4/LoC2RDAKD06vH+n7X179//0EMPrWz3LiCA5D333HOvvvpqZfvuu++eR3cgGwIA5fbqq68++OCD9Tv/08m7gO69916vgQNI27//+79XbT/kkEMa3hfIjABAuV1zzTWtra0dGg8++ODKQzu1OPjggwcNGtSh8aOPPqp89ygAyZgzZ87Pf/7zyva999676tfBoCwEAMqt3ud/2my44YaTJk2qbHcKCCBVb7zxxlFHHdXS0lL507e//e08egSZEQAosSeeeGLevHkdGvv371+PymzVU0C//vWv33777czvBUC+Zs+evfvuu7/44ouVPx144IFVHwyDEhEASG37/6CDDsr2/E/7ZSvf+rx69erp06dnfi8A8vLoo4/+xV/8xcSJE994443KX0eNGlX1UBCUS5+8OwA9tGbNmmuvvbYB53/a9OvXb/LkyZVfHLvuuutOPfXUetwRgFp05ZTmxx9/3NLSsmTJknffffeZZ555/PHHX3nllXX98fDhw+++++5Ro0Zl3VNotObKByihFGbOnLnffvt1aNxwww0XLlxY+cBuJm677bbJkyd3aGxubn7llVc233zzetwRgK5obm6u9y3Gjx9/6623evaXNDgCRFlVbsa3HdSp0+q/qanpC1/4wpAhQzo0tra2Xn/99XW6IwBFcNxxx82ePdvqn2QIAJTSypUrb7rppoad/2mzwQYbHHbYYZXt3gUEkKpPfepTDz300C9+8YuNNtoo775AZgQASum2225bvHhxh8YNN9yw3m9mqPouoMcff3z+/Pl1vS8AjTRo0KDjjz/+oYceeuyxxyZOnJh3dyBjHgKmlPr373/22Wd3aPyTP/mTeu/QHHDAAeecc07lkzOVaQSAgmtubu7Tp0+/fv0GDRo0bNiwkSNHbrHFFrvuuuvEiRMnTJjQp481EsnyEDAAAATiCBAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAE0px3BwDIx5QpU/LuAhTF9OnT8+4CNI4KAEBQVjwAMQkAAAAQiAAAEJciAEBAAgAAAAQiAACEpggAEI0AAAAAgQgAANEpAgCEIgAAAEAgAgAAigAAgfTJuwMAlMPW04bl3QXouReOXpR3F6AoVAAA6FIRwPoJIA0CAAAABCIAAPC/FAEAIhAAAAAgEAEAgP9HEQAgeQIAAAAEIgAA8P9RBABImwAAAACBCAAAdKQIAJAwAQAAAAIRAACoQhEAIFUCAAAABCIAAFCdIgBAkgQAAAAIRAAAYJ0UAQDSIwAAAEAgAgAAnVEEAEiMAAAAAIEIAACshyIAQEoEAAAACEQAAGD9FAEAkiEAAABAIAIAAF2iCACQBgEAAAACEQAA6CpFAIAECAAAABCIAABANygCAJSdAAAAAIEIAAB0jyIAQKkJAAAAEIgAAEC3KQIAlJcAAAAAgQgAAPSEIgBASQkAAAAQiAAAQA8pAgCUkQAAAACBCAAA9JwiAEDpCAAAABCIAABATRQBAMpFAAAAgEAEAABqpQgAUCICAAAABCIAAJABRQCAshAAAAAgEAEAgGwoAgCUggAAAACBCAAAZEYRAKD4BAAAAAhEAAAgS4oAAAUnAAAAQCACAAAZUwQAKDIBAAAAAhEAAMieIgBAYQkAAJSSCAHQMwIAAGUtArxw9CIxAKC7BAAASmnracPa/hcxAKBbBAAAUngSQAwA6CIBAIDSFwHaiQEA6yUAAJDa64DEAIBOCAAAlFhlEaCdGABQlQAAQMrfBBADADoQAABItgjQTgwAaCcAABDlw8BiAIAAAECUIkA7MQAITgAAIFARYO3biQFATAIAAOGKAO3EACAgAQCAoEWAte8rCQBxCAAAhC4CrE0MACIQAABonMIWATr0oQjdAKgTAQCAEEWA7tYHxAAgVQIAACGKAC8cvWjracPEAAABAICkrHeJLwYAwQkAAAQqArT/72IAEJYAAEBqur6yFwOAgAQAAIIWAdqJAUAoAgAACerBNwHEACAIAQCAfBSqCNBODACSJwAAkKZaPgwsBgAJEwAAyE0xiwDtxAAgSQIAAMmqpQiw9kXEACAlAgAAeSp4EaCdGAAkQwAAIGWZFAHWvpoYAJSdAABAzspSBGgnBgClJgAAkLhsiwBrX1YMAMpIAAAgf6UrArQTA4DSEQAASF+digBrX18MAMpCAACgEMpbBGgnBgClIAAAEEK9iwBr30gMAIpMAACgKBIoArQTA4DCEgAAiKJhRYC17ygGAEUjAABQICkVAWqPAZIAUA8CAACBNL4IUOOtxQAgcwIAAMWSZBGgx6WANmIAkCEBAIBYciwCtHdADAByJAAAUDgJFwHaiQFAXgQAAMLJvQjQTgwAGk8AAKCIIhQB2okBQCMJAABEVJwiQDsxAGgMAQCAggpVBGgnBgD1JgAAEFQBiwDtxACgfgQAAIorZhGgnRgA1IMAAEBcRS4CtBMDgGwJAAAUWvAiQDsxAMiKAAAApSEGALUTAAAIXQToZD1d2BWzGADUQgAAgFISA4CeEQAAKAFFgHURA4DuEgAAoPTEAKDrBAAAykERYL3EAKArBAAASIoYAHROAACgNBQBuk4MANZFAACAZIkBQCUBAIAyUQToATEAWJsAAAAhiAFAm+b//Z8AUB5Tpkzp/A96ttJt08lit5bLFkqd6iTl/Y+83soSpEQFAADC6XE1QEEAEiAAAFA+ngTIhBgAMfXJuwMAQJ7aMkDPVvNt/6qAh4KEE+iEZwAAKCtPAmSudM8GZLXQ9wwAoagAAADlqAbY14dMqAAAUGKKAMlXAxqz6FcBIBQVAACgWNUAO/1QVyoAAJSbIkAa1YB8F/0qAISiAgAA5FYNsNkPjacCAEDpKQKUrhpQtHW/CgChqAAAAA2tBgD58iVgAErPh4HL9RVhIF8qAABADtWAertg2LS1/8+/X3R0fn2BYvEMAACJ8CRAvvKKAR0W+uvSeQDwDAChqAAAAKWpBnRxuQ90QgUAgHQoAuSrTqv/TBb9KgDQTgUAACjc0t9OP9SPCgAASVEEKPXSv37rfhUAaKcCAADkvPq33w+NpAIAQGoUAcqy9G/kul8FANqpAAAADV362++HfPkSMACp8WHg+qnxP+MFw6ZZ/UPuVAAAgEYs/bPrC1ATzwAAkCZPAhRh6V+cdb9nAKCdCgAAkP3qvzhLf6ADzwAAkCZPAtSuZ/9ZHPSHglMBAAA6svEPCVMBACBZigA9Y+Mf0qYCAADUtPq37odyUQEAIGWKAF33wtGLutttu/5QRgIAAGDjHwIRAABInCLAetn4h1AEAAAIrQer/7r1BWgEAQCA9CkCZHLo38Y/pEEAAICIbPxDWAIAACEoAqzN6h8i8x0AAIilu8d+6tkXIAcqAABEUdciQOMv2zNW/4AAAAAZ6OQUUHFY/QMCAACxRC4CdL0P3vYDaRMAAKARRYB8M0C3Vv917guQMwEAgFjyKgLkyOofWJsAAAApFwGs/oEOBAAAwolTBLD6ByoJAACQZhHA6h+oSgAAIKLkiwBW/8C6CAAAkFoRwOof6IQAAEBQyRcB1svqH2ISAAAgqSJAFy9u9Q9hCQAAxJVeEcDqH1gvAQAAEikCWP0DXSEAABBaMkUAq3+giwQAAEj2dUAdWP0DAgAApFAE6EoPrf6BNgIAAJS7CGD1D3SLAAAAJS4CFLZjQGEJAACQ+JMAtv+BtQkAAFDWIoDDP0APCAAAUMoigNU/0DMCAACUrwhQnJ4ApSMAAECaTwLY/geqEgAAoGRFAId/gFoIAACQWhHA6h/ohAAAAGUqAhShBAGUmgAAAKUpAjj8A9ROAACAkhUBOmH1D6yXAAAA5SgCFDZ1AOUiAABAIkUA2/9AVwgAAFCCIsB684bVP9BFAgAAFL0IUMBqA1BeAgAAlP6bALb/ga4TAACg0EUA2/9AtgQAACh3EcD2P9AtAgAAFLcIYPsfyJwAAAAlLgLY/ge6SwAAgBI8CVCV1T/QAwIAABS3CACQOQEAAEpZBLD9D/SMAAAAOVMEABpJAACA8hUBbP8DPSYAAED+FAGAhhEAAKCURQCAnhEAAKBkRQDnf4BaCAAA0A2KAEDZCQAAUKYigO1/oEYCAAB0jyIAUGoCAACUhu1/oHYCAAAUpQigdAA0gAAAAACBCAAAUI4nAZz/ATIhAABAITj/AzSGAAAAPeR1QEAZCQAAUALO/wBZEQAAIP8igFoB0DACAAAABCIAAEDRnwRw/gfIkAAAAACBCAAAkHMRwAMAQCMJAABQaM7/ANkSAAAgA74JAJSFAAAAAIEIAACQZxFAZQBoMAEAAIrLAwBA5gQAAMiMJwGA4hMAAAAgEAEAAHIrAigIAI0nAABAQXkAAKgHAQAAMuZJAKDIBAAAAAhEAACA7CkCAIUlAAAAQCACAADUhSIAUEwCAAAUkVcAAXUiAABAbkUAgMYTAAAAIBABAADqSBEAKBoBAAAAAhEAAKC+FAGAQhEAAAAgEAEAAOpOEQAoDgEAAArHRwCA+hEAAKARFAGAghAAAAAgEAEAABpEEQAoAgEAAAACac67AwAQy5QpU/LuAh0pzhCKCgAAAAQiAABAQ9lsBvIlAAAAQCACAAA0miIAkCMBAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAKA4mltbW/PuAwAA0CC9GnUjAAAgfwIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABNIn7w5A47S0tMyePfuhhx565pln5s+f//rrry9dunTZsmVr1qzp37//wIEDN910080222zcuHE777zzXnvtNXbs2Ly7DACQsebW1tasrwnF0tLSctttt1155ZUzZsxYuXJl1//htttue9RRRx1//PHbbrttPTsIQLddd9113fr75ubmXr169e7du1+/fv379x88ePDGG288atSo/v37162PUFACAClbvnz5JZdccuGFFy5cuLCW60yePPmcc87ZZZddsusaADVpbm7O5DpjxowZP378rrvuus8+++y9996DBg3K5LJQZAIAybruuuu+9a1vvf3225lcrVevXqeccsr5559vbgBIKQCsrV+/fgceeOCxxx57xBFH9O3bN/PrQ0EIACTovffeO+GEE2655ZbMr7zddtvdcsst2223XeZXBiD3ANBus802O+20077xjW84IESSBABS8/TTT0+ePPmFF17o5G8++clP7rbbbuPGjdtkk0022mijFStWvP/++4sWLZo7d+4jjzyyaNGiTv7tkCFD7rnnnt13370OfQegEAGgzeabb/79739/6tSp9b4RNJgAQFIefvjhgw46aMmSJVV/HTNmzNe+9rVjjz12yy23XNcVWltb586d+1//9V9XXnnl0qVLq/7NkCFDZs6cueuuu2bXcQAKFwDaTJky5dJLLx0+fHhjbgcNIACQjt/97nf77bdf1dX/4MGDzzrrrG9+85tdP9O5ePHis88++6KLLqr6/yNjxox59NFHN91005p7DUBmAaDzVc3HH3+8evXq5cuXL126dOHChS+//PIf/vCHxx577Ne//vW6do7abLXVVnfcccf222+fRcchfwIAiXjxxRc//elPv//++5U/ffrTn542bVrPXuo/Y8aM4447ruqTxPvvv/+vfvWrHnUWgBwCwLqsWrXqvvvu+8lPfnLbbbetWbOm6t8MGzbsrrvucv6TNAgApGD58uUTJ0588sknK3867LDDpk2btsEGG/T44vPmzdtnn32qRovLLrvsxBNP7PGVAShCAGg3d+7cv/3bv13X5s7QoUNnzpzpldAkQAAgBSeccMLPfvazyvbJkyffeOONffrU+sXrxx577M/+7M9aWlo6tI8aNWr+/PkDBw6s8foAFCEAtPnJT35y2mmnrVq1qvKnTTfd9PHHH3f+k7LrlXcHoFYzZsyouvrfeeedr7nmmtpX/22HiM4666zK9gULFlx66aW1Xx+A4jj55JPvu+++IUOGVP701ltvHX300atXr86jX5AZFQDKraWlZdy4cS+99FKH9gEDBjzxxBPbbrttVjf66KOPdtttt7lz53Zo32qrrZ5//vlevWRpgEQqAG0eeeSRz3/+88uXL6/86Qc/+MHpp5+e1Y2g8axaKLdLL720cvXf1NR03nnnZbj6b2pq6tu379lnn13Z/uKLLz788MMZ3giAIthzzz0vv/zyqj+dffbZr7/+esN7BJkRACixFStWXHDBBZXt22+//amnnpr57Q4//PAxY8ZUtt98882Z3wuA3E2dOvXP//zPK9uXLl1adfaBshAAKLFf/vKXCxYsqGz/53/+5969e2d+u969e5988smV7bNmzcr8XgAUwb/8y7/079+/sv3yyy+vOgFBKQgAlNhll11W2bj11lsffvjhdbrjoYceWtn41FNPLVu2rE53BCBHm2+++d/93d9Vtq9cufKKK67Io0eQAQGAspo3b95jjz1W2X7KKafU75HcnXfeecSIER0aV69e/eyzz9bpjgDk66//+q/79etX2X7VVVfl0R3IgABAWd1yyy2Vjc3NzVOnTq3fTZubm/fbb7/K9ueff75+NwUgR0OGDKla/v3j/8ijR1CrDF6RDrm48847KxsnTpw4evTout536tSpla+Z22ijjep6UwBy9KUvfenGG2+sbJ8xY8a4cePy6BHUxHcAKKWlS5cOHTq08lMsZ5111ne/+92cOgVAOt8BWNuqVauGDRtW+U2AI4444qabbqrHHaGuHAGilObMmVP1Q4z77LNPHt0BIGUbbLDBjjvuWNn+xBNP5NEdqJUAQCn9/ve/r9o+YcKEhvcFgPRVnV9efvnlDz/8MI/uQE0EAErp6aefrmwcNWrUxhtvnEd3AIgYAFpbW1944YU8ugM1EQAopddee62ycauttsqjLwCkb/z48VXb33zzzYb3BWolAJBOANh0003z6AsA6Rs6dGjV9rfeeqvhfYFaCQCU0rvvvlvZWPmJLgDIxODBg6u2L1mypOF9gVoJAJRS5bvYmpqa+vfvn0dfAEjfkCFDqravWLGi4X2BWgkAlNLKlSsrGzfccMM8+gJA+tZVAWhpaWl4X6BWAgCl9PHHH1c2+qodAHVS9eMzTU1Nffv2bXhfoFYCAKXUr1+/LpYFAKB269rpV3ymjAQASqnqcf+qDwYAQO3W9cGvAQMGNLwvUCsBgFLaaKONKhsXLlyYR18ASN/bb79dtX3UqFEN7wvUSgCglEaPHl3ZuGDBgjz6AkD61vW+/80226zhfYFaCQCUUtUB98UXX8yjLwCk77nnnqvavsUWWzS8L1ArAYBS2nLLLSsb33777ffffz+P7gCQuGeeeaayccSIEY4AUUYCAKW00047VW1/8sknG94XANI3e/bsysadd945j75ArQQASmldY+6DDz7Y8L4AkLjFixfPmzevsn3ixIl5dAdq1afmK0AOxo8fP2TIkMWLF3donzVr1j/90z/V9dZ/9Vd/1eF9oxtssMFVV11V15sCkKO77rqr6ofA9t9//zy6A7Vq9vFUSurII4+8+eabOzT27t17wYIFm2yySZ1u+sILL2yzzTYdGseOHfvSSy/V6Y4AVNXc3FzZWKdVzZQpU2644YYOjUOHDn3nnXd8CZgycgSIsjrwwAMrG1evXn3jjTfW76b33ntvZWNlJAAgGe+8884tt9xS2X7MMcdY/VNSAgBldeSRR1YdeX/84x/X76YzZsyobNxxxx3rd0cA8nXxxRd/9NFHle1f+cpX8ugOZEAAoKw22WSTgw46qLL9ySefnDVrVj3uuGLFivvuu6+yfa+99qrH7QDI3XvvvfejH/2osn333Xffc8898+gRZEAAoMROPvnkqu3/+I//WI/bXXPNNR988EGHxr59++677771uB0AuTvjjDOWLFlS2f4P//APeXQHsiEAUGIHH3zwhAkTKtsfeeSR66+/PvPbXXLJJZWN++233/DhwzO/FwC5u+OOO37+859Xtu+1116TJk3Ko0eQDQGAcvvOd75Ttf0b3/jGu+++m+GNbrjhhjlz5lS2f/WrX83wLgAUxPz587/85S9Xtvfu3fuSSy6p+g4iKAsBgHL74he/WPUEzsKFC7/85S+vWbMmk7t88MEHp512WmX71ltvfdhhh2VyCwCK4/XXX99///0XLVpU+dOZZ57pA8CUnQBA6V188cVVXwd09913n3HGGbVfv7W19etf//pbb71V+dP555/fu3fv2m8BQHHMnTt34sSJL7/8cuVPn/3sZ88555w8OgVZEgAovfHjx59//vlVf/q3f/u3M888s8brn3rqqdddd11l++c///kpU6bUeHEAiqO1tfXSSy/dY489Xnvttcpft95662nTptn3IQG+BEwKWltbJ0+efPvtt1f9derUqT/96U8HDhzY3csuW7bsm9/85uWXX17507Bhw5566qkxY8b0qL8AFO5LwDNnzjzzzDMfffTRqr+OHDnyoYce2nrrrXt8fSgOAYBELFmy5HOf+1zV53Tbtm1++MMfHnrooV2/4AMPPHDCCSfMnz+/8qc+ffrcfffd++23Xw39BaAQAeDZZ5+99dZbf/GLX8ydO3ddfzN27Nh7773Xd99JhgBAOt5555299977+eefX9cf7L777qeddtqkSZM22mijdf3NkiVLbr/99osuuui3v/1t1T/o1avXFVdcUfXVEADkGwCuvfbaTv7J6tWrV61atWzZskWLFi1YsGD+/Pm///3v1/vKuD333PPGG2/cdNNNa+4yFIUAQFLeeeedyZMnr2vt3maDDTbYY489dtxxx2222WbIkCF9+/Zd9D/efPPN2bNnz507t5N3B/Xt2/eKK6449thj69N9ALqqAS/i7NWr1+mnn37eeedVfdUElJcAQGpWrFjxta997aqrrsr8yiNHjrzxxhv32muvzK8MQNECwGc+85n//M//3G233ep6F8iFtwCRmv79+1955ZU333zzqFGjMrzsl770pXnz5ln9AyRv4sSJt956629/+1urf1KlAkCyli1bdvHFF1944YXvvfdeLdc54IADzj333D322CO7rgFQuArA+PHjDzvssOOOO278+PHZXhmKRgAgcStWrLj55puvvPLKWbNmffTRR13/h5/85CePOOKI448/frvttqtnBwFoUADo1atXnz59Ntxww4EDBw4dOnTEiBGbb7759ttvv8MOO0ycOHHkyJH16SkUjgBAFMuWLXv44YcfeuihZ599dv78+W+99dbSpUuXLVvW2trav3//gQMHbrrppmPGjNl+++0nTJiw1157jR07Nu8uAwBkTwAAAIBAPAQMAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEEhz3h2AjE2ZMqXH/3b69OmZ9gUAoHD65N0BaNDiHgAAAYCCstAHAKgTAYCcWesDADSSAECjWfEDAORIAKDurPgBAIpDACB7VvwAAIUlAJANi34AgFIQAOg5i34AgNIRAOgei34AgFITAEht3X/BsGmd/Pr3i45uYF8AAApHAKBM6/7OF/cAAKyXAEARF/0W+gAAdSIAkP+633IfAKBhBAByWPpb8QMA5EUAiKuR634rfgCAghAAwmnMut+KHwCgmASAKBqw7rfoBwAoPgEgfXVd+lv0AwCUiwCQsvot/a37AQBKSgBIUJ3W/Rb9AAAJEACSUo+lv3U/AEBKBIBEZL70t+4HAEiSAFBu1v0AAHSLAFBW2S79rfsBAIIQAEIv/a37AQCiEQDKxNIfAIAaCQCxlv7W/QAAwQkARWfpDwBAhgSAxJf+1v0AAKxNACgiS38AAOpEACgWS38AAOpKAEhq9W/pDwBA5wSAFJb+1v0AAHSRAJAzS38AABpJAMiNpT8AAI0nAJRv9W/pDwBAjwkAjWbpDwBAjgSAxrH0BwAgdwJA0Vf/lv4AAGRIAKg7G/8AABSHAFBfNv4BACgUAaBeLP0BACggAaBAq39LfwAA6k0AyJiNfwAAikwAyJKNfwAACk4AyIalPwAApdAr7w6kwOofAICyUAHIYfVv6Q8AQF4EgJ6z8Q8AQOkIAD1k4x8AgDISABqx+rf0BwCgIASA7rHxDwBAqXkLUDdY/QMAUHYqAF3l2A8AAAkQANbPxj8AAMkQANbDxj8AACnxDEBnrP4BAEiMALBOVv8AAKTHEaAqLP0BAEiVCkBHVv8AACRMAPj/WP0DAJA2R4B6uPq39AcAoIxUAP6X1T8AABEIAP+X1T8AAEFEPwJk6Q8AQCihKwBW/wAARBM3AFj9AwAQUNAAYPUPAEBMEQOA1T8AAGGFCwBW/wAARBbrLUBdX/1b+gMAkKRAFQCrfwAAiBIArP4BACBKALD6BwCAKAHA6h8AAKIEAKt/AACIEgCs/gEAIEoAsPoHAIAoAcDqHwAAogQAq38AAIgSAKz+AQAgSgCw+gcAgCgBwOofAACiBACrfwAAiBIArP4BACBQAOgiq38AAOgVZPvf6h8AAEofAKz+AQAgSgCw+gcAgCgBwOofAACiBACrfwAAiBIArP4BACBQAOgKq38AAEghAHT9m18AAEC5A4DDPwAAECUAWP0DAECUAGD1DwAAgQJAV1j9AwBACgGgK9v/Vv8AAJBCALD6BwCAKAHASz8BACBQAOgK2/8AAJBCAHD4BwAAogQAq38AAIgSABz9BwCAQAGgK2z/AwBACgHA4R8AAIgSAKz+AQCgrgoUABz9BwCAQAGgK2z/AwBACgHA4R8AAIgSAKz+AQAgUAAAAACiBADb/wAAECUAWP0DAECsCgAAABAiANj+BwCAKAHA6h8AABqvuEeArP4BACCRANCV7X8AACCFAODwDwAA5KW4R4AAAIDSBwDb/wAAkKPCVQCs/gEAIJEA4NlfAACIEgAc/gEAgNwV6AiQ1T8AACQSABz+AQCAIihKBcD2PwAAJBIAbP8DAEBBFKICYPsfAAASCQDr3f63+gcAgEQCgMM/AABQKDkfAbL9DwAAiQQA2/8AAFA0eVYAbP8DAEAiAcD2PwAAFFBuFQDb/wAAkEgA8OpPAAAopkJ8CAwAAGiM7AOA7X8AACgsFQAAAAgk4wBg+x8AAIpMBQAAAALJMgDY/gcAgIJTAQAAgEAyCwC2/wEAoPhUAAAAIJBsAoDtfwAAKAUVAAAACKQRAcD2PwAApBMA1nv+BwAAKAhHgAAAIJBaA4DHfwEAoERUAAAAIJCaAoDtfwAAKBcVAAAACKSOAcD2PwAApBMAvP0TAABKp14VANv/AACQTgCw/Q8AAGXkIWAAAAikJwHA2z8BAKCkVAAAACCQ7AOA7X8AAEgnAHj8FwAAyssRIAAACCTjAOD8DwAApBMAnP8BAIBSy7ICYPsfAAAKzjMAAAAQSDcCgPM/AABQdplVAJz/AQCAdAKA7X8AAEiAZwAAACCQbAKA8z8AAJBOAHD+BwAA0uAIEAAABJJBAHD+BwAAykIFAAAAAll/APAAAAAAJKPWCoDzPwAAUCKOAAEAQCDrCQDO/wAAQEpqqgA4/wMAAOXiCBAAAATSWQBw/gcAABKjAgAAAIH0PAB4AAAAAEpHBQAAAAJZZwDwAAAAAKSnhxUA538AAKCMHAECAIBABAAAAGiKHgA8AAAAAEnqSQXAAwAAAFBSjgABAEAgAgAAAMQOAB4AAACAVHW7AuABAAAAKC9HgAAAIBABAAAAAhEAAAAgcADwBDAAACSsexUATwADAECpOQIEAACBCAAAABCIAAAAAFEDgCeAAQAgbd2oAHgCGAAAys4RIAAACEQAAACAQAQAAAAIGQA8AQwAAMnragXAE8AAAJAAR4AAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgXgDo/B2gXgEEAABpUAEAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBgAcBHAAAAIAgVAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAik15QpUzr5+YJh0xrYGQAAoL5UAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgkD6d//z3i45uVE8AaKjOvwQPyZs+fXreXYB8qAAAAEAgAgAAAAQiAAAAQCACAAAABNLsITBYm2fCiMP4D2sz/hOHCgAAAAQiAAAAQCACAAAABCIAAABAIOv5EvAFw6Y1qifQIL5vDV1h/Cc9xn9oowIAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEEiv6dOnd/Kzj2YDpMr4DxCTCgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAECwDTp0/v5C/+ftHRDewPAI1j/AcISAUAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAADiBQCvggaIyfgPEI0KAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAATS1QDgRRAAMRn/AZINAJ2/CQ6AVBn/AUJxBAgAAAIRAAAAIBABAAAAAulGAPAcGEBMxn+AZAOA58AAYjL+A8ThCBAAAAQiAAAAQCACAAAABNK9AOA5MICYjP8AyQYAz4EBxGT8BwjCESAAAAhEAAAAgEAEAAAACKTbAcBzYAAxGf8Bkg0AngMDiMn4DxCBI0AAABCIAAAAAIH0JAA4BgoQk/EfINkA4BgoQEzGf4DkOQIEAACBCAAAABBIDwOAY6AAMRn/AZINAI6BAsRk/AdImyNAAAAQSM8DgCowQEzGf4BSUwEAAIBAOgsAjoECxGT8B0iYCgAAAARSUwBwDBQgJuM/QLIBQBUYICbjP0CqHAECAIBAag0AqsAAMRn/AZINAKrAADEZ/wGS5AgQAAAEkkEAUAUGiMn4D1BGKgAAABBIlwKAY6AAMRn/AdKTTQVAFRggJuM/QOk4AgQAAIF0NQCoAgPEZPwHSExmFQBVYICYjP8AyQYAm0AAMRn/AVLiGQAAAAgkywCgCgwQk/EfINkAoAoMEJPxHyAZGR8BsgkEEJPxH6AsPAMAAACBdDsAqAIDxGT8B0hD9hUAVWCAmIz/AKXgCBAAAATSqx5VYJtAAEky/gMkQAUAAAAC6WEA8CgYQEzGf4Cyq1cFQBUYICbjP0CyAcAmEEBMxn+AUqvjMwA2gQBiMv4DFJmHgAEAIJCaAoD3wQHEZPwHKC8VAAAACKTWAGATCCAm4z9ASakAAABAIBkEAO+DA4jJ+A9QRo2oAKgCA8Rk/AcoIEeAAAAgkGwCgEfBAGIy/gOUjgoAAAAEklkAsAkEEJPxH6BcVAAAACCQLAOATSCAmIz/ACWiAgAAAIFkHABsAgHEZPwHKAsVAAAACCT7AGATCCAm4z9AKagAAABAIHUJADaBAGIy/gMUX24VAHMAQEzGf4A0A8B6N4EASJLxH6Dg8nwGwCYQQEzGf4A0A4BNIICYjP8ARZbzW4BsAgHEZPwHSDMA2AQCiMn4DxC3AuCVcAAxGf8BiqkQHwIzBwDEZPwHSDMAKAQDxGT8ByigQlQAbAIBhGX8B0gzANgEAojJ+A9QNEWpANgEAgjL+A+QZgDoyiaQOQAgPcZ/gLgVAIVggJiM/wDFUaAjQG1sAgHEZPwHSDMAKAQDxGT8ByiIwlUAAACApAKATSCAmIz/AHErAJ4GA4jJ+A+Qu+IeAbIJBBCT8R8gzQCgEAwQk/EfIG4FwBwAEJPxHyBHxT0CBAAApBYAbAIBxGT8B4hbATAHAMRk/AcIGgAAAIBYAcAmEEBMxn+AoAHAHAAQlvEfIGgA6CJzAEBMxn+ABAOA78MDxGT8BwgaABSCAcIy/gMEDQDmAICwjP8AQQNAF5kDAGIy/gMkGAAcBgWIyfgPEDQAKAQDhGX8BwgaAMwBAGEZ/wGCBoAuMgcAxGT8B0gwADgMChCT8R8gaABQCAYIy/gPEDQAmAMAwjL+AwQNAF1kDgCIyfgPkGAA6OJhUHMAQGKM/wBBA4A5ACAs4z9A0ABgDgAIy/gPEDQAeDEcQFjGf4CgAaCLbAIBxGT8B0gwACgEA8Rk/AcIGgDMAQBhGf8BggYAcwBAWMZ/gKABwBwAEJbxHyBoADAHAIRl/AcIGgDMAQBhGf8BggaArjMHAMRk/AdILQB0/esw5gCAlBj/AYIGAHMAQFjGf4CgAcAcABCW8R8gaAAwBwCEZfwHCBoAzAEAYRn/AYIGAHMAQFjGf4CgAcAcABCW8R8gaAAwBwCEZfwHCBoAzAEAYRn/AYIGAHMAQFjGf4CgAcAcABCW8R8gaAAwBwCEZfwHCBoAzAEAYRn/AYIGAHMAQFjGf4CgAaC7c4BpACAZxn+AoAGgW3OArSCAlBj/AYIGAHMAQFjGf4CgAcAcABCW8R8gaAAwBwCEZfwHgosbAMwBAGEZ/4HIQgeAtjnAqyEAAjL+A2FFDwBtbAUBxGT8BwISAP6XOQAgJuM/EI0A0PM5wDQAkAbjPxCKANDzOcBWEEAyjP9AHAJAR+YAgJiM/0AQAkCtr4ZQDgZIhvEfiEAAWCdbQQAxGf+BtAkAnTEHAMRk/AcSJgBkPweYBgASYPwHUiUAZH8k1FYQQBqM/0CSBICushUEEJPxH0iMAFDHOcBWEEAajP9ASgSA7lEOBojJ+A8kQwDoCeVggJiM/0ACBICGloNNAwBlZ/wHyk4AaGg5WEUYIAHGf6DUBIBa2QoCiMn4D5SUAJDPHGArCCABxn+gjASAnMvBpgGAUjP+A6UjABRiK8g0AFBqxn+gRASAQmwFqQgDlJ3xHygLAaAubAUBxGT8B4pPACjiVpBpAKC8jP9AwQkA9dWzOcA0AFB2xn+gsASA4m4FORgKUGrGf6CYBIAGsRUEEJPxHygaAaA0W0GmAYCSMv4DhSIANJppACAm4z9QEAJAPno8B5gGAErN+A/kTgAo5VaQaQCgvIz/QL4EgJyZBgBiMv4DeWnO7c5UmDJlSo1XuGDYtIz6krLOp8xa5mOAnjH+N4bxH9qoABRI7UOPDSGAMjL+A40kACRVEW5jGgAoHeM/0DACQBGZBgBiMv4DDeAZgPQPhrZxPLSdM6BAKRj/M2f8hzYqACF2g2wIAZSO8R+oExWAiLtBwTeE7AABpWP8z4TxH9qoAETcDbIhBFAuxn8gQyoAZZXhblC0DSE7QECpGf97zPgPbQSAcst2GggyE5gAgAQY/3vA+A9tBIBEmAm6zgQApMT433XGf2gjACQl82kgyZnABACkx/jfFcZ/aCMAJKge00BKM4EJAEiV8b9zxn9oIwCkrE4zQdknAxMAkDzjf1XGf2gjAKSvftNASWcCEwAQhPG/A+M/tBEAoqjrNFCuycAEAIRi/G9n/Ic2AkA4DZgJCj4ZmACAmIz/xn9oIwDE1ZiZoIDzgQkACM74X5XxnzgEABo6ExRhPjABALQx/q/N+E8cAgC5TQN5zQcmAIC1Gf/bGP+JQwCgQDNBY6YEEwBAVcb/+t0aCkUAoOiTQeYTgwkAYL2M/5AwAYBSzgS1TBImAICuM/5DegQAkp0JesYEAFCV8R+SIQDQc0lOBiYAgPUy/kOpCQBkI5nJwAQA0C3GfygdAYDslXoyMAEA9JjxH0pBAKDuyjUfmAAAsmL8h2ISAGi0gs8HJgCAOjH+Q0EIAOSsaPOBCQCgMYz/kBcBgCLKcVYwAQDkyPgPDSAAUCYNmBhMAAAFZPyHpuz8H4J7YmhZXvwkAAAAAElFTkSuQmCC"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:9)_139
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is Stack the original shape on top of the {'layer1': 'RuRuRuRu'}.\nthe 3th action is Stack the original shape on top of the {'layer1': 'CgCgCgCg'}.\nthe 4th action is Stack the original shape on top of the {'layer1': 'CuCuCuCu'}.\nthe 5th action is Stack the original shape on top of the {'layer1': 'RcRcRcRc'}.\nthe 6th action is Colorize the top layer of the original shape with the color cyan.\nthe 7th action is Cut the right side of the shape\nthe 8th action is rotate the shape clockwise 90 degrees\nthe 9th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_410
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAgAAAAIACAYAAAD0eNT6AAAJEUlEQVR4nO3dS24bOxBAUTt7lBcpLzIPGeQFiX+S1R+S95x5GhqwgYsqtvP8BCRcLpefWz/z9fX1eetnAsfw8kLEHgFwL8EA4/AyQsQIAfAVgQDH8bJBxAwB8BlxANvyQkHE7AHwHlEA3+flgYgVA+A9ogBu40WBiEoAvEcUwFteCogoB8C/BAEIAMgQAB8TBBQ59BAhAG4nCChwyCHi1gC4Xq83P/Pl5eVpdWKAVTnYELFHANxr9mAQA6zEYYaIEQJgtUAQBMzM4YWIGQJg5jAQA8zGgYWImQNgpigQAszCQYWI1QJghigQA4zM4YSIQgCMHAVigNE4kBBRDYARg0AMMAKHECIEwHhBIAQ4k8MHEQJg3BgQApzBoYMIATBHEIgBjuKgQYQAmCsGhAB7c8AgQgDMGQNCgL04WBAhAPYhBpiVwwQRAmCdGBACbMEhgggBsF4MCAEe8eOhfw3AhyG1d0z9irpbww7+pR4hwgRg/amAiQD3MAEAWGQqYCLAPdQiRJgA9KYCJgJ8xgQAYNGpgIkAnxEAAAMQAhxNAACEQmCXBzMl+yGIcAdgXnvcE3A/ABMAgOBUwFoAAQAwCSHAlgQAwGT2CoFNH8jwBADApLYOAdOAFgEAMDkhwHcIAIBF7BECmz2M4QgAgMWYBnALAQCwINMAviIAABa2ZQiYBqxFAAAEbB0CmzyIUwkAgBDTAH4TAAAxpgH8IgAAorYKAdOAOQkAgDjTgCYBAMCm04BNfhC7EwAA/M9KoEMAAPAX04AGAQDAbiEgAsYlAAD41BYRIATGIwAA+JKVwHoEAAA3sRJYiwAA4C5WAmsQAADczTRgfgIAgG8TAfMSAAA8RATMSQAAcPpKwL2A4wkAADZjGjAPAQDApkTAHAQAAEOuBDb9QbwhAADYjQgYlwAAYFciYEwCAIChVwK+ENiHAADgMKYB4xAAABxKBIxBAABwOBFwPgEAwClEwLkEAACnEQHnEQAATP2FwOY/KEIAADAEEXAsAQDAMETAcQQAAEMRAccQAAAMRwTsTwAAMCQRsC8BAMCwRMB+BAAAQxMB+xAAAAxPBGxPAAAwBRGwLQEAwDREwHYEAABTEQHbEAAATEcEPE4AADAlEfAYAQDAtETA9wkAAJIRUCcAAEhGwCU+BRAAACxBBNxHAACwDBFwOwEAwFJEwG0EAADLEQFfEwAALEkEfE4AALAsnwh+TAAAQHAKIAAAWJpVwPsEAADLEwFvCQAAEkTA3wQAABkuBf4hAABIuTcCLotOAQQAADlXESAAAKAYAQIAgKRr/D6AAAAg6xpeBQgAANKu0QgQAABwpxUiQAAAkHcN3gcQAADw1FsFCAAACEaAAACAB8waAQIAAIL3AQQAAARXAQIAAIIRIAAAIEgAAEBwCiAAACAYAQIAAIIEAAAEpwACAACCESAAACD4R4IEAADsZOQpgAAAgOAqQAAAQJAAAIDgFEAAAEDwQqAAAIADjDYFEAAAEFwFCAAACK4CBAAAHGiUKYAAAIDgFEAAAEBwCiAAACA4BRAAAHBCBJw9BRAAAHCSMyNAAABAcBUgAAAgOAUQAAAQnAIIAAAITgEEAAAEpwACAACCnwUKAAAIEgAAEJwCCAAACBIAABCcAggAAAgSAAAQnAIIAAAIEgAAEJwCCAAACBIAABCcAggAAAgSAAAQ/I+CBAAADGyvNYAAAIAgAQAAwcuAAgAAggQAAASnAAIAAIIEAAAEPwkUAAAwiS3XAAIAAIJTAAEAAMEpgAAAgCABAADBTwIFAAAECQAACF4GFAAAMKFH1wACAACCBAAABNcAAgAAgmsAAQAAwSmAAACAIAEAAME1gAAAgOAaQAAAQHAKIAAAIEgAAEBwDSAAACC4BhAAABAkAAAguAYQAAAQJAAAIHgPQAAAQHANIAAAIEgAAEBwDSAAACC4BhAAABAkAAAguAYQAAAQJAAAIHgPQAAAQJAAAIDgPQABAADBNYAAAIAgAQAAQQIAAIL3AAQAAATvAQgAAAgSAAAQJAAAIHgPQAAAQPAegAAAgCABAABBAgAAggQAAAQvAgoAAAheBBQAABAkAAAgSAAAQJAAAIDgRUABAADBi4ACAACCBAAABAkAAAgSAAAQvAgoAAAgeBFQAABAkAAAgCABAABBAgAAggQAAAQJAAAIfQnw+1NAAQAAQQIAAIIEAAAECQAACBIAABAkAAAgSAAAQJAAAIDg3wIQAAAQJAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAECQAACA4P8HIAAAIEgAAECQAACAIAEAAEECAACCBAAABAkAAAgSAAAQJAAAIEgAAEDQ89k/ADjG5XL5efZvAMZhAgAAQQIAAIIEAAAECQAACHIJEMJcDIQuEwAACBIAABAkAAAgSAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA8HeU/96ryxn0HAQAAAAAASUVORK5CYII="
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is Cut the right side of the shape\nthe 4th action is Stack the original shape on top of the {'layer1': 'RgRgRgRg'}.\nthe 5th action is Cut the right side of the shape\nthe 6th action is rotate the shape counterclockwise 90 degrees\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is Colorize the top layer of the original shape with the color blue.\nthe 9th action is Cut the right side of the shape\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABAAAAATICAIAAAANxCANAABQlElEQVR4nO3deZiddXk//kkIhBC2AJGwfUERhVAEQUUDFb0QZUeQCYxi1eJ+IVpb60WrRb2sWq2tUq1YXACFgRmWsqOsoiyCyK4iiyAgS4CwhZCwzO/S6S/GOSczZ855ts/nfr3+45nJOQ/JzP3c7+f+fJ4zZWRkpA8AAIhhat0nAAAAVEcAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACGRa3ScAlXriiSfWX3/9Z555pu1X3/ve9x5zzDGVnxQAPTnppJMm9f1T/2TatGnTp09fbbXV1l577dmzZ6+//vorrbRSaecIDTJlZGSk7nOA6nzve9879NBDV/TVddZZ54EHHlh55ZWrPSkAejJlypTeX2SVVVb5q7/6q+233/5Vr3rVPvvss+GGGxZxatBEAgCx7LrrrhdffPE433D22WfvtddeFZ4RAI0IAGNecKeddnr3u9/9rne9a9o0yyXIjT0ABHLfffddeumlxc6RAcjPyMjIz372s/e+971bbbXV0NBQ3acDBRMACGRwcPCFF14Y/3vOOOOMFe0QACCa22+//aCDDnr/+9+/dOnSus8FCiMAEMgPf/jDMUdmzZo15siTTz55zjnnVHhSADTdMcccs/vuuz/77LN1nwgUQwAgiltuueWGG24Yc/ArX/lK6+LOk08+ucLzAqAUI+N6/vnnly5d+vjjj999992XXXbZf/3Xfx144IGrrbbail7tkksuOfzww6v9P4Cy2ARMFEccccSXvvSl5Y+sueaaDz300J577jlmW/CMGTMeeuih1VdfvfJzBKCwTcBddDhPPfXU1772tS9/+ctPPvlk22/40Y9+9OY3v7mrc4QGMQEghJGRkcHBwTEH3/rWt06fPv2AAw4Yc3zx4sVnnnlmhWcHQCOsvvrqn/rUp6666qrNNtus7Td89rOfrfykoHgCACH89Kc/vfvuu8ccPOigg0ZjQOutI88CAghr7ty555xzTtvlQFdcccUvfvGLOk4KiiQAEMIJJ5ww5sg666yz22679fX1bbTRRq95zWvGfPVHP/rRY489VuEJAtAgc+fO/eQnP9n2SxdeeGHlpwMFEwDI39KlS4eHh8ccPOCAA5Z94u/+++/f+kdOO+20qk4QgMb58Ic/vNJKK7Uev+SSS+o4HSiSAED+zj333IULF7Zd/zOqdRuAVUAAwa233nrbbbdd6/HWBaWQHAGAiI//nz179hvf+MZl/7nFFltsvfXWY77n4osvXrBgQSUnCEATbbPNNq0HH3744TrOBYokAJC5xx9/vPWDvQ488MAxg93WIcDzzz9/yimnlH+CADTUuuuu23rw8ccfr+NcoEgCAJk75ZRTnnnmmTEHDz744DFHrAICoJNPElhzzTXrOBcokgBAuPU/G2644c477zzm4HbbbffiF794zMGf/exn9913X8knCEBDtX0c3OzZs+s4FyiSAEDO7r333ssuu2zMwf7+/qlT2/zktz4L6IUXXhgaGirzBAForltvvbX14A477FDHuUCRBAByduKJJ77wwgsTrv9ZUQCwCgggrCVLllx33XWtx1//+tfXcTpQpClt17dBHrbddtsbb7xx+SObbrrp7373u9aP/h2937/hhhs++OCDY47feeedrauDAGiOtlW9xw7nhBNOOOSQQ8YcXG211e6777611167l1eG2pkAkK2bb755TPff19c3f/78tteJP/4yTJ263377tR4/+eSTyzlBABpq6dKlX/jCF1qPv//979f9kwEBgGy1bv8dZ/3PKM8CAqCvr+/jH//4r371qzEHN9lkk8997nM1nREUyRIg8jQyMrLZZpv9/ve/X/7gS1/60ttuu22cP/Xss8++6EUvan3sw69//estt9yynDMFoEFLgBYtWvSxj33sO9/5zpjja6655qWXXvrKV76y23OEBjEBIE+XXXbZmO6/r6/voIMOGv9PrbzyynvttVfrcUMAgOwtXLjwqKOO2nrrrVu7//XXX/+8887T/ZMNEwDy9L73va+1gt94441tP9d9eaeddtrb3va2MQe33HLLX//610WfIwAlTgAGBwfH+SMjIyNLlix5+umnH3jggXvvvfe666678cYbWx8c19fXt9tuux177LEbbrhhoacMdRIAyNCSJUvmzJkzZiXPVltt1bqgs9XTTz+93nrrLV68eMzx6667brvttiv6TAEowIqe7tCjV77ylZ/97Gf32WefMl4camQJEBk655xzWtfxj7/9d5nVVlvtLW95S+txq4AA4pg5c+a3vvWta6+9VvdPlgQAMnTCCSe0HpxwA8D4nwjmYaAAcSxatOhDH/rQRhttdNhhh1kCSn4sASI3jz322Jw5c5YsWbL8we22267tBzq2tXDhwhe96EXPPffcmONXXXXVjjvuWNyZAtDoJUDL7LHHHl//+te32GKLUt8FKmMCQG5OOeWUMd3/pG7/9/X1zZo16w1veEPrcauAAGI677zzXvGKV/z7v/973ScCxZhW0OtAoz//a8qUKZNq32fPnt16cGho6Ktf/erUqWIzQAImXOPwwgsvLFq06Mknn7zvvvvuueee66+//uqrr77kkkuWLl3a+s3PPPPMJz7xibvuuuuoo45yISB1lgCRlXvuuWfTTTct76f60ksv3WWXXUp6cQBq/yCwRx555Nhjj/385z/f+jCJUUceeeRnPvOZLl4ZmkOEJSsnnnhiqZnWKiCAvK277rp///d//9vf/vaNb3xj22/4/Oc/f+WVV1Z+XlAkEwCy8opXvOKmm24q7/Vnz579hz/8Ydo0a+cA8pwALLNkyZK99trroosuav3Sbrvt9uMf/7iXF4d6mQCQjxtvvLHU7r+vr2/BggUXX3xxqW8BQBNMnz79+OOPX2eddVq/dMEFF3TyyZLQWAIAmW//LZxVQABBbLjhhocddljbL5177rmVnw4URgAgEyMjI4ODg2MOzpw58+mnnx7p1oknntj6RqeffnrbB0QAkJ/3v//9bY9fccUVlZ8LFEYAIBOXXnrpvffeO+bg3nvvPWPGjK5fc5999mn944899tj555/f9WsCkJCNNtpo8803bz1uCRBJEwDIxAknnNB6sL+/v5fXXH311ffYY4/W41YBAcSxww47tB589NFH6zgXKIYAQA6WLFly6qmnjjk4c+bMtu37pMyfP7/14Jlnnvn000/3+MoAJGHddddtPbiiTwmAJAgA5ODss89urcV77bXXaqut1uMr77333q0vsmjRorPPPrvHVwYgCWuuuWbrQR8GTNL8+JLt8396XP8zaubMmXvuuWfr8ZNPPrn3Fweg+Z544okOUwGkQgAgeQsXLmx9HNtqq63WtnHvwkEHHdR68Nxzz33yyScLeX0AmmzBggWtBzfeeOM6zgWKIQCQvOHh4dbnchay/mfZS82cOXPMwWeeeeZ///d/C3l9AJrs6quvbj241VZb1XEuUAwBgOSV8fyf5c2YMWPvvfduPe5ZQADZ++1vf/v73/++9fiOO+5Yx+lAMQQA0vb73//+pz/9aXnrf8Z5FtAFF1zgMXAAefvP//zPtsf32muvys8FCiMAkLYTTzxxZGRkzME999yzddFOL/bcc8/VV199zMFnn3229dmjAGTjuuuu+/73v996fOedd2776WCQCgGAtJW9/mfUqquuus8++7QetwoIIFf33XffgQceuGTJktYvffKTn6zjjKAwAgAJu/7662+++eYxB2fMmFHGZLbtKqCf/OQnDz74YOHvBUC9rrrqqh133PHOO+9s/dLuu+/edmMYJEQAILfb/3vssUex63+WvWzrU5+ff/754eHhwt8LgLpcffXVf/M3fzNv3rz77ruv9atz5sxpuygI0jKt7hOALr3wwguDg4MVrP8ZNX369H333bf1E8dOOumkww47rIx3BKAXnazSfO6555YsWfLEE088/PDDv/nNb6699tq77757Rd+8zjrrnH/++XPmzCn6TKFqU1o3UEISLr744l133XXMwVVXXXXBggWtG3YLcdZZZ+27775jDk6ZMuXuu+/eZJNNynhHADoxZcqUst9i7ty5Z555pr2/5MESIFLVejN+dKFOSd1/X1/fW97ylrXWWmvMwZGRkZNPPrmkdwSgCQ455JCrrrpK9082BACS9Mwzz5x22mmVrf8Ztcoqq+y3336txz0LCCBXr3rVqy6//PIf/OAHa6yxRt3nAoURAEjSWWed9fjjj485uOqqq5b9ZIa2zwK69tprb7/99lLfF4Aqrb766u95z3suv/zya665Zt68eXWfDhTMJmCSNGPGjCOPPHLMwf/3//5f2Xdo3vzmN3/mM59p3TnTmkYAaLgpU6ZMmzZt+vTpq6+++qxZs9Zff/1NN910++23nzdv3nbbbTdtmh6JbNkEDAAAgVgCBAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIFMqfsEoGD9/f1d/9nh4eFCzwWANOr/hFwgyIkAQEpKLe7qO0DY+l8IFxFSIQDQRHUVerUboF5JNPqT5eJC0wgA1KxRtV6NBohZ/6vnikONBACq1uSKrxwDxKz/tXMBokoCAKVLqOKrvwAx63/TuB5RKgGA4qVb8RVcgJj1v+FcniiWAEAx8ij6KixAzPqfEJcqeicA0L38ir6qChCz/ifKZYvuCABMTt5FXyUFiFn/M+ASRucEAHKr+8ODQ+N8tX9g/nh/VvUESLb+Dx57yzhfHXj31l3/2Qn/eKO4ljGhaRN/C4E1re6P39wDkGv9n7BBb8IJNCQkLPu3kwRYEQGAJhZ9jT5AzPpfe6NfxsnXFQyW/wcVBlieAED9dV+7DxCz/ifd7vfyv1l9JDAWYHkCADWUfh0/QMz6H6Tjn+zfQ5V5YPQfXQwITgCIq8q6r+MHiFn/dfzNzAMGAsEJAOFUU/d1/AAx67+OP608IAnEJABEUUHd1/QDxKz/mv7K/nrLCwOSQCgCQP5KLf2afoCY9V/Tn2sYsEkgAgEgZ+WVfn0/QMz6r+9vjmX/FmUkATEgbwJAhkqq+5p+gJj1X9MfdixgXVCuBICslFH69f0AMeu/vj9FJY0FDAQyIwBkovDSr+8HiFn/9f15KCMJiAHZEADSpu8HiEnfT11JwLqgDAgAqSq29Ov7AWLWf31/HCUlATEgRQJA6NKv7weIWf/1/ZEVmwTEgBQJACnR+gPEpPWnDKM/DGJAQAJArNKv7weIWf/1/VQwEBADUiEANJ3WHyAmrT+JDgTEgOYTADIv/fp+gJj1X99PvQMBMaDJBIAm0voDxKT1J7OBgBjQTAJAs2j9AWLS+tNMYkCWBICsqr/WHyBm/df6k0QMkAEaQgDIofTr+wFi1n99P2ltDzAKaAgBoGZaf4CYtP6EHQiIAbUTAGqj9QeISetPHsSAdAkA6VV/rT9AzPqv9SfLGCADVE8AqJrWHyAmrT8Z6yUGGAVUTwCojtYfICatP0GIAakQAJpe/bX+ADHrv9afmDFABqiAAFA6N/4BYnLjn8gGj73FKKCxBIByufEPEJMb/2AU0FgCQFm0/gAxaf2hkBhgFFAeAaBB1V/rDxCz/mv9yV4vMUAGKJwAUDA3/gFicuMfStoYYBRQOAGgSG78A8Tkxj90yCigCQSAYmj9AWLS+kNlMcAooChTC3ulwHT/ADHp/qEX3f0u9PKAXUaZAPSqi59CrT9AzPqv9YeiRgHmAL0QALrnxj9ATG78Q+2bgy0H6oUA0CU3/gFicuMfymAUUCUBoIrqr/UHiFn/tf5QdgyQAbogAEyOG/8AMbnxD41dEWQ50GR5CtAk6P4BYtL9Q8W6+A3ydKDOmQB0yrIfgJgs+4FaWA5UHgFgYm78A8Tkxj/UznKgMggAE3DjHyAmN/6hIYwCCmcPwHh0/wAx6f6haSb7W2ZLwDgEgBXS/QPEpPuHZpIBimIJUBtaf4CYtP7QcJNdDmRLQFsmAGPp/gFi0v1DKowCeiQA/AXdP0BMun9IiwzQC0uAuvzJ0PoDxKz/Wn9IdzmQtUCjTAD+j+4fICbdPyRtUr+V5gCjBIA/0v0DxKT7hwzIAJMVfQmQ1h8gJq0/hF0O1B/+0UChJwC6f4CYdP+QJaOADsUNALp/gJh0/5AxGaATQQOA7h8gJt0/ZE8GmFDEAKD7B4hJ9w9ByADjCxcAdP8AMen+IRQZYByxngLU+b+u1h8gZv3X+kPYRwMNh3kuUKAJgO4fICbdP0TW+e91f5g5QJQAoPsHiEn3D8gAEQOA7h8gJt0/MEoGiBUAdP8AMen+geXJAFECgO4fICbdP9BKBsg/AOj+AWLS/QMrMigDZBwAdP8AMen+gfENhs8AeQYA3T9ATLp/oBODsTNAhgFA9w8Qk+4f6Nxg4AyQWwDQ/QPEpPsHJmswagbIKgDo/gFi0v0D3RkMmQHyCQC6f4CYdP9ALwbjZYBMAoDuHyAm3T/Qu8FgGSCHAKD7B4hJ9w8UZTBSBsghAHRI9w8Qk+4f6MRgmFqRfADoMITp/gEy02H9j3NFB3o32FnFSH0IkHYA0P0DxKT7B0oyGCADJBwAdP8AMen+gVIN5p4BUg0Aun+AmHT/QAUGs84ASQYA3T9ATLp/oDKD+WaA9AKA7h8gJt0/ULHBTDNAegGgE7p/gJh0/0CxBnOsKokFgOQCFgCFUP+BJutPqkalFAAs/gGIyeIfoEaD2S0ESiYA6P4BYtL9A7UbzCsDpBEAdP8AMen+gYYYzCgDpBEAOqH7B4hJ9w9UYzCXapNAAOgkSOn+AfLTSf3P5noMJGGwg5rT/CFA0wOA7h8gJt0/0EyD6WeARgeAhv/dAVAS9R9IXX+D61ijA0An3P4HiMntf6Aug4nXn+YGAIt/AGKy+AdovsGUFwI1NADo/gFi0v0DqRhMNgM0MQA0828KgLKp/0B++ptX2ZoYADrh9j9ATG7/A80xmGZFalwAsPgHICaLf4AUDSa4EKhZAUD3DxCT7h9I12BqGaBBAaBRfy8AVEb9ByLob0yta1AA6ITb/wAxuf0PNNlgUjWqKQHA4h+AmCz+AfIwmM5CoEYEAN0/QEy6fyAng4lkgEYEAAAAIEoAcPsfICa3/4H8DKYwBKg5AOj+AWLS/QO5Gmx8Bqh/AgAAAIQIAG7/A8Tk9j+Qt8FmDwFqCwC6f4CYdP9ABIMNzgDNXQKk+weISfcP5GGwqdWsngBQ+95nAGqh/gPUXhVrCAAW/wDEZPEPEM1gIxcCNXcJEAAAkHwAcPsfICa3/4GYBps3BGjcBED3DxCT7h/I1WDD6lulAcDeL4CY1H+A5tTJ6gKAxT8AMVn8AzDYpIVADVoCpPsHiEn3D0Qw2JhaN62atzH8BYhJ/V+RgXdvXfcp8Gf+OSJ3w43S398/PDwcZQLg9j9ATJoAII7BZlS8KgKA2z8AMan/AA2snI2YALj9DxBTQ26GAYSqe1NrDzG6f4AsTVj/m3AVBKjehNWv7CFAuQHA8BcgJvUfoLFVtOYlQG7/A8Tk9j8Q2WCtNbDEAOD2D0BM6j9Ak2tpnRMAt/8BYnL7H2CwvkpYVgBw+wcgJvUfoOEVtaJPAm7l9j9ATG7/d2LzoVl1n0Ju7pi/cJyv+guv/u+cvj/Vw1o+hbqUCYBHfwLE5NGfAM1/JGgjPggMAACoRvEBwO1/gJjc/gdIYghgAgAAAIEUHADc/geIye1/gFSGACYAAAAQSJEBwO1/gJjc/gdIaAhgAgAAAIEUFgDc/geIye1/gLSGACYAAAAQSDEBwO1/gJjc/gdIbghgAgAAAIFUEQDc/geIye1/gAZWzgICQOGfTgxAEtR/gBRrryVAAAAQSK8BwPZfgJhs/wVIdCuwCQAAAATSUwBw+x8gJrf/AdIdApgAAABAICUGALf/AWJy+x+gybW0+wDg6W8AMan/AElX47ImAG7/A8Tk9j9AwytqlwHA7R+AmNR/gNRrsk3AAAAQSDcBwNM/AWLy9E+ADJ4HagIAAACBFB8A3P4HiMntf4AkquukA4DtXwAxqf8AedRnS4AAACCQggOA9T8AMVn/A5BKjZ1cADD/BYhJ/QfIpkoXOQFw+x8gJrf/ARKqtPYAAABAIJMIAOa/ADGp/wA51erCJgDW/wDEZP0PQFr1ttMA4PYPQEzqP0BmFdseAAAACKSYAGD9D0BM1v8AJFd1OwoA5r8AMan/APnVbUuAAAAgkAICgPU/ADFZ/wOQYu01AQAAgEAmDgAWgALEpP4DZFm9e50AWP8DEJP1PwCJVmBLgAAAIJAJAoD5L0BM6j9ArjW8pwmA9T8AMVn/A5BuHbYECAAAAhkvAJj/AsSk/gNkXMlNAAAAIJDuA4ANAAAx2QAAkHQ1NgEAAIBAVhgALAAFiEn9B8i7nk/r7uWs/wGIyfofRt0xf2HdpxDaHfMXbj40q+6zoH6Dx94y8O6tJ/unLAECACZN91mXO+YvlL7oUZcTAAAAqqTvpyjtJwAWgALEpP7TOUOAyrjrT7FVvZslQDYAAMRkAwBUTOtPGZXZHgAAoEuGAOXR+lMeewAAABpE30/Z2kwALAAFiEn9pwuGAAVy159qavuklwDZAAAQkw0AUB6tP1XWZ3sAAICeGAL0QutP9ewBAABKNzRU8wqC+fPn9zWMvp+6mAAAAKUPARrYf9fIXX+aFQDsAAOISf2HCmj9aUKFn9wEwA5ggJjsAGZChgDj0/rTnCptDwAAQIn0/TSNPQAAQDEMAcZw159mEgAAABrX+tf+3CSiBAA7wABiUv8piiFAIa2/7p9S6/wk9gDYAQwQkx3AMKFClvro++nF4LG3DLx7606+0xIgAKBI0YYAhSz0d9efKnkKEABAN9z1J1EmAABAwbIfArjrTyYTADvAAGJS/6Fz7vqTrv7+/uHh4UlMAOwABojJDmC6k98QwF1/sqnY9gAAAIzHXX8yYw8AAFCKDIYA7vqTJRMAAICx3PUnYyYAAEBZUhwCuOtP9kwAAAD+yF1/Yk0Axn8GnEcAAeRq/PrvEUAEGQL0ftd/9Ja/7p/ajV+3R2u+CQAAQPc0/STHHgAAoFxJDAG64JY/iTIBAACYHH0/STMBAABKl80QwF1/MmACAAAwMX0/2TABAACqkO4QwF1/MmMCAADQnr6fbCcAPgQAICYfAkDFEhoCuOtPxh8FYAIAAPBn+n6yZw8AAFCdJg8B3PUnCBMAACA6fT+hmAAAAJVq8hAAIhAAAAAgEAEAAKiaIQDUSAAAAIBABAAAoAaGAFAXAQAAAAIRAACAehgCQC0EAAAACGRqf3//OF8eHvS5GAB5Gr/+Dx57S4XnQlyGAFCG8Wu4CQAAAAQiAAAAdTIEgIoJAAAAEIgAAADUzBAAqiQAAABAIAIAAFA/QwCojAAAAACBCAAAQCMYAkA1BAAAAAhkyvifBAmhDA8P130KUB31H6iRjxsv28C7t17Rl6aV/uYAANBxe0rZLAECAIBABAAAAAhEAAAAgEAEAPgzeyIBgOwJAAAAEIgAAAAAgQgAAAAQiAAAAACBTPBBYMODQ1WdCVSkf2B+3acACWj+h3SO/ylCQ0NNv37Nnz9eLdp8aFZfs90xf2Faf//j/4V3fcLjv2wS/5R1/ZBQI58EDABQljvmL4ycAZK+y5C6ce6SWAIEANClBs46YEICAABAiayEoWkEAACA7hkCkBwBAACgXIYANIoAAADQE0MA0iIAAACUzhCA5hAAAAB6ZQhAQgQAADJ8iPiEH88E1TMEoCEEAACAAhgCkIqpw8PD43y5f8AdFIA8jV//x/kISaBrhgBUY/wabgIAAFAMQwCSIAAAAFTHEIDaCQAAAIUxBKD5BAAAgEoZAlAvAQAAoEiGADScAAAAUDVDAGokAAAAFMwQgCYTAABIlQ8DphPz/6SveQwBqIsAAADkqd7W3xCAxppW9wkAABSsmbf8W90xf+HmQ7PqPgvCMQEAAPLRqAU/hgA0NwAMDw+P8x39A035LQKgWOPX/4F3b13huUBWrX/n7ASgcONX7+HhYRMAACBtTW79DQFoIHsAAIBUNbbvnxQ7AaiYCQAACfMk0LCafNd/DEMAmsYEAABISSp9/6QYAlAlEwAAIA0J3fUfwxCARjEBAACaLtG+f1IMAaiMCQAAkPNd/82HZjWhsTYEoHEBwEcBAMSU/UcBRLhznKtsWv/O+UwAKvgQABMAADJ/EBApyrX1NwSgIewBAACymtg0sPXvnJ0AVEAAAADqF6T1HxoasiyN2gkAAECdgrT+nTMEoGz2AACQOTdc836ufzOX+4/DTgCSCQAeBAQQUxIPArIPODkxW//OeRwQpVbsqR0+CQ6AXKn/VEnrbwhA7dXeHgAAoArW+k+KnQCUxx4AAPJnG0C93PVvZQhAjUwAAMjB4LG3JLFdIRp3/XthCED9EwD7gAFi0ljTBXf9J2QIQF21+i8CgH1gADGp/xRL618UjwOijDpvDwAAIdgGkIpQrb8hALUQAADIhE8DSF2o1r9zhgAUTgAAAGoWufU3BKDpAcA+YICY8tgHbBVQA0Vu/TtnCECxVXpsALAPDCAm9Z+Kaf2XMQSg4gpvCRAA+bANIAla/y4YAlAgHwQGAFSksX2/5WGEYgIAQCD6vBo1tvtPhSEAtQUA+4ABYkplH7BVQA1kzQ80qj63CQD2gQHEpP5TOK1/sQwBKKS2WwIEQCxWAVVD6w+NJQAAkBurgOql9S+VIQD1BADbAABiSmUbAHXR+kMSlbl9ALAMFCCmIPXfKqDCaf2rZAhAj1XdEiAAMmQVUGW0/pAcAQCAiAwBeqf1r5EhADV8EnD/wPzhwaGe3hmABA28e2s318nvU70y+98hjoGutmZNDb4MFIBc67+gAgQ3vIJ6bgkQAEFZBQTE1H0A8DBQgJg8DBQg6WpsAgBAtiZcBWQIAAQ0NcIyUAAmRf0HyLiSmwAAkDNbgQGKDAC2AQDElNM2AKuAgGh1eIIAYAoMEJP6D5BrDbcECIDM2QoMUGQAsAoIIKacVgEBhKrAEwcAU2CAmHKq/4YAQBzDE1VvS4AAACCQAgKAVUAAMaW1CsjzQIE8DPRce00AAOCPrAICgpgabRkoAJ1T/wHyq9vFTACsAgKIKbNVQIYAQISqawkQAAAE0mkAMAUGiCmz+m8IAGSsw4pd2ATAKiCAmNJaBQSQrqLq7dSwN4EAiFn/DQGA4LXaHgAAAAikyABgFRBATMmtAjIEACJX2qmRp8AAdChg/ZcBgFyrdMFLgAwBAGLKbwgAkGuNtQcAANozBACyNOkAEHAKDECW9d8QAIhZn4ufAFgFBBBTcquAOmEIAORXXS0BAiAuQwAgoKllTBkMAQCyNGH9T3EI4JGgQJNNWFe7WJ9pAgAAE5ABgJx0GQDy2woGQNj6byEQEKomlzUBsAoIIKYUVwF1whAAyKaidh8AsrwJBEDM+m8IAMSpxiXuATAEAIjJEACgybXUJmAA6HQIIAMAGegpAHgeKEBMWT4P1EIgIO+nfy5jAgAAk2AIAKSu1wBgCAAQU+QhgAwApHv73wQAAMayEAjIWwEBIMvnwQEwocj13xAASLf2VjEBsAoIIKZEVwFZCATkXTktAQKANmQAIFfFBABbgQFiynUrMECW239HmQAAQHuGAECWCgsAhgAAMeU9BJABgMxu/5sAAEABZAAgIUUGAEMAgJgMAQBSuf1vAgAAE7MQCMhJwQHAEAAgpryHADIAkM3tfxMAACiSDAA0X/EBwBAAICZDAIDm3/43AQCASbAQCMhAKQHAEAAgpuyHADIAkPrt/76+vml9NekfmD88OFTXuwNQl4F3bx1hLc38+fOHhrq/zN0xf2Ghp8ME/IVTi7ruiZS1BKiMsAJA80Wo/x0GGHMAoJkVtc49ABYCAcQUZCGQDAA0sxKWGAAi3AQCIGz9lwGARGtpzU8BMgQAiCmDIYAMACRaA8sNAEFuAgEwhvoP0NgqWvoEwCNBAWKK8EhQQwAglUd/Nu6DwGQAgJhkACCagQbUvSoCgEEwQExx6r8MACRUORsxATAEAAirCTfDCiEDAKlUvCmVvVN/f//43+CDgWlC2oxzwxKaU/9z+mDgDq/uvXxIMF0bP33l9HNIYw3Uvfq/WRMAQwCAsBpyS6wQ5gBA82tddQGgk0AjAwDkp5P635zrYu9kAKC7KlfZMoRKJwAWVwDEFK3+ywBAk+tkg5YAjTIEAIgppyGADAA0ub5VHQAsBAKIKdpCoM7JAJC3gSYt/mnoBAAA8tD5U2Xm/0nJpwNQXwAwBACIKeAQYFJPlpQBID8Dzbv9X9sEINpuMADC1n8ZAGhaVWzuEiBDAICYMhsCyAAQ1kBTq1ltAcBCIICYAi4EGs0Ak9oSUPLpAEEX/9Q/AZABAGKKmQEmuy245HMBgnb/jV4CBAD5kQGA2tUcAAwBAGIKOwTweFDI3kCzb//XHwBkAICwZIAOyQCQkIHGd/+NCAAAEJAMAIQOAIYAADFFHgJ0kQHEAGi4gRRu/zclAMgAAGHJAJP6fhkAGmsgke6/QQGgQzIAQEwywDIyADTQQFI1qkEBoCGRCICKqf+T+pgwy4EgUcONqXUNCgAWAgGEFXwh0CijAEjUQDqLf5oYAGQAgLBkABkAUjSQWvffxADQIRkAICYZYAzLgaBGA2lWpCYGgKaFJACqof53tyXAKACabLh5la2JAcBCIICwLARaxigAGm4gwcU/jQ4AMgBAWDJA1xnAKAAqM5Bs99/oANAhGQAgpjgZwCgAmmYg8frT6ADQ2NgEQKnU/0JGAWIA1Gi4wXWs0QHAQiCAsCwE6j0DWBEEZRhIefFPGgFABgAISwbofTmQUQAUayD97j+NANAhGQAgplAZoJdRgBgAPRrIpdqkEQA6DFIyAEBmOqz/2VyVSx0FiAHQi4HO6kzzb/8nEwBkAICwZIAV6S4D2BgAwbv/lAKADAAQlgywIkYBUIGBvLr/xAJAWn+zABRI/S9pFCAGQMAalVgA6JAhAEBMAYcAPY4CxAAIWFXSCwAWAgHEZCHQhLrOAGIABFn8k2oAkAEAwpIBSh0FLIsBkgD05dv9pxoAZACAsGSACmKAgQAM5Nv9JxwAZACAsGSADokB0J2BrLv/tAOADAAQlgzQuR4zgHVBRDOQe/effACQAQDCkgGqHAWMEgPI3kCA7j+HANA5GQAgJhmgjBggCZCfgTC1IocA0HkIkwEActJ5/Y9zXa8sBhgIkJmBjqtE6rf/MwkAMgBAWDJAQ2KAJEDSBiJ1//kEABkAICwZoAkxQBIgXQPBuv++vr4pfXnp7+/v8DuHB4dKPhcaavwEmM3vNkTTef0vsOXNSUnpaGioQVfb8cOJH4yYBuJ1/1lNAEaZAwDEZA5QyDSg8CbYWIAmGwjZ/Wc4ARhlDsA4TAAgY+YARSk1JtU1FjABYHkDUbv/bAOADMA4BADImwxQoAqmJVWGAQGAZQYCd/85BwAZgBURACB7MkDhKls3VWoeEAAYNRC7+888AMgAtCUAQAQyQBmq3z5RbB4QAND9hwgAMgCtBAAIQgYoT70bqbtOBQIAuv8oAUAGYAwBAOKQAcrWwEcqjRMPBIDgdP+xAoAMwPIEAAhFBgibBCbLD0DedP85fw7Aivh8AICYfD5A0h8jAIXQ/QcNADIAQFgyQJUkAZpG9x93CVAXs2DLgXJlCRDENKn6r38tVhLJyj968B+84UgNQKAJQBf/ukYBADHrfxINa4pjAU02ldH9jyNcAJABAMKSAZpAGKACuv/xhVsCtIy1QGFZAgTBWQvUWPWGLv/W2dD9TyhuAJABwhIAABkgFVVGAv/QedD9dyJ0AJABYhIAABkgaSWlAv/KGdD9dyh6ABglBoQiAADLiAH56Toe+PdNmtZ/UgSA/yMDxCEAAMuTAeIYv0f0j5su3f9kRXwKUFseDQQQk0cDQdJ0/10QALrPAGIAQMwMIAZAE0z2l1H3v4wA0NNPhgwAELP+ywBQr8n+Dur+lycAjCUDAMQkA0AqdP89sgm4mG1hdgYnxCZgoNj6b/NoKmwCzoDWvxAmACtkFAAQk1EANJPuvygCwHhkAICYZABoGt1/gQSA4jOAGAAQMwOIAVCGLn65dP/jEwAmNvwnk/ojMgBAzPovA0Cxumj9df8TEgA6ZRQAEJNRANTCjf/yCADl/lTJAAAx678MAL3o4jdI9985AWByLAcCiMlyIKiMZT9lEwC6YTkQQEyWA0GpLPuphgBQ6XIgMQAg5nIgMQDK+DXR/XdHAOhed/MmGQAgZv2XAWBFumv9df9dEwB6ZRQAEJNRAPTOjf9aCAAF6O6nUAYAiFn/ZQDo5XdB99+7KQW8Bv+//v7+Lv7U8OBQCedCl9FLWQEqq/+Dx95SwrnQZbvpn6NKWv96mQA0YhRgGgAQcxRgGkA0Xf/Y6/4LJAAUrOstKTIAQMz6LwMQR9etv+6/WAJAKYwCAGIyCoC23PhvFHsAmrgq1MaAUtkDADS5/luJXh57AGrRdbh1RS6PCUC5uv7ZNQ0AiFn/TQPIRi8/zLr/UgkApetl4ZoMABCz/ssApK6X1l/3XzYBoCJGAQAxGQUQjRv/zWcPQDKrQm0MKIo9AEBy9d/y9ELYA1C2XiKr62+VBIB6iAE1EgCAGokBNRIAyqP1T4slQPXo5WfdoiCAmPXfoiAaqMcfS91/LUwAEr4VZBrQHRMAIIP673Z1F0wAitVjHHXBrZEA0AhiQJUEAKA5xIAqCQBF0fqnTgDI5zIgCXRIAADyq/+a104IAD3qfQWai2xD2APQIL3/VtgeABCz/tseQKkK+QHT/TeHCUCet4JMA8ZhAgDkXf/dyV4RE4AuFBIsXVubRgBoLjGgJAIA0HBiQEkEgEnR+mdMAAhxGZAElicAAKHqv752GQGgE0WtJXM9bTIBIA1iQIEEACAhYkCBBIDxaf3jEAAiXgaCJwEBAIhc/yO3uQJAWwVuH3cNTYUAkB4xoEcCAJAoMaBHAsAYWv+wBIBUFXgZiJYEBAAgacXW/1BdrwAwqtgnxrpupkgASFuxl4EgSUAAADJQeP2P0P4GDwCFf1KEK2a6BIBMSAKdEwCAnEgCnYsZAPT9tBIAslL4ZSDLJCAAAPkpo/7n1xCHCgBlfDK0S2Q2BIAMlXEZyCkJCABArkqq/9l0xhECQBl9v4tjfgSAnJV0JUg9DAgAQPbKq/9Jd8m5BoCSmn7XxIwJAPkr7zKQaBIQAIAgSq3/KbbLmQWA8vp+V8PsCQBRlHoZSCsMCABAKBXU/1Ra5wwCQKlN/yjXwQgEgHAquBI0PAwIAEBM1dT/JrfRiQaACpp+l79oBIC4qrkSNDAPCABAcFXW/0Z11akEgGo6/lGuejEJAFR6JWhCHhAAAOqq//U22Y0NAFV2/KNc7IITAKjtMlBXHhAAABpS/yvuuZsTAKrv+JdxmUMAoFlXgmoigQAA0Nj6X2oXXlcAqLHdX8bVjeUJADT9YlB4MBAAAJKr/4V052UHgCY0+stzRWNFBACSvBL0EhIEAIAs6/+EHXwvAaBpzf04XMiYkABAtleC7qibADHrf+pcv+icAED3srwYKKAAMet/ilyz6I4AQDGyuRgopgAx638qXKfonQBA8ZK+GCisADHrf5O5NlEsAYDSpXU9UGQBYtb/RnExolQCAFVr+PVAzQWIWf/r5epDlQQAata064ESDBCz/lfM5YYaCQA0UY1XBRUZoEZZpgJXFppGACAlFVwYlGmABkoiGLiCkIopIyMjdZ8DAABQkalVvREAAFA/AQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACmVb3CUB1lixZctVVV11++eW/+c1vbr/99nvvvfepp55atGjRCy+8MGPGjJkzZ26wwQYbbbTRVlttte222+60006bbbZZ3acMAFCwKSMjI0W/JjTLkiVLzjrrrOOOO+7CCy985plnOv+DW2yxxYEHHvie97xniy22KPMEAZi0k046aVLfP2XKlKlTp6600krTp0+fMWPGmmuuue66686ZM2fGjBmlnSM0lABAzp5++ulvfvObX/nKVxYsWNDL6+y7776f+cxnXvnKVxZ3agD0ZMqUKYW8zsYbbzx37tztt99+l1122XnnnVdfffVCXhaaTAAgWyeddNLHPvaxBx98sJBXmzp16oc//OEvfvGLrg0AOQWA5U2fPn333Xd/+9vfvv/++6+88sqFvz40hABAhh555JFDDz30jDPOKPyVX/7yl59xxhkvf/nLC39lAGoPAMtstNFGhx9++Ec+8hELhMiSAEBufvWrX+2777533HHHON/zspe9bIcddthqq63WW2+9NdZYY/HixY8++ujChQtvuummK6+8cuHCheP82bXWWutHP/rRjjvuWMK5A9CIADBqk002+fKXv3zwwQeX/UZQMQGArFxxxRV77LHHE0880farG2+88Qc/+MG3v/3tL37xi1f0CiMjIzfddNP//M//HHfccU899VTb71lrrbUuvvji7bffvrgTB6BxAWBUf3//0Ucfvc4661TzdlABAYB8/OIXv9h1113bdv9rrrnmpz/96Y9+9KOdr+l8/PHHjzzyyKOOOqrt78jGG2989dVXb7DBBj2fNQCFBYDxu5rnnnvu+eeff/rpp5966qkFCxbcddddt9xyyzXXXPOTn/xkRXeORr3kJS8555xzttxyyyJOHOonAJCJO++889WvfvWjjz7a+qVXv/rVQ0ND3T3U/8ILLzzkkEPa7iTebbfdfvzjH3d1sgDUEABWZOnSpRdddNG3v/3ts84664UXXmj7PbNmzTrvvPOs/yQPAgA5ePrpp+fNm3fDDTe0fmm//fYbGhpaZZVVun7xm2++eZdddmkbLY455pj3vve9Xb8yAE0IAMvcdNNN//AP/7Cimztrr732xRdf7JHQZEAAIAeHHnro9773vdbj++6776mnnjptWq+feH3NNdf89V//9ZIlS8YcnzNnzu233z5z5sweXx+AJgSAUd/+9rcPP/zwpUuXtn5pgw02uPbaa63/JHVT6z4B6NWFF17YtvvfdtttTzzxxN67/9FFRJ/+9Kdbjz/wwANHH310768PQHN84AMfuOiii9Zaa63WL91///3z589//vnn6zgvKIwJAGlbsmTJVltt9bvf/W7M8dVWW+3666/fYostinqjZ599docddrjpppvGHH/JS15y2223TZ0qSwNkMgEYdeWVV77pTW96+umnW7/01a9+9eMf/3hRbwTV07WQtqOPPrq1++/r6/vCF75QYPff19e38sorH3nkka3H77zzziuuuKLANwKgCV73utd997vfbfulI4888t577638jKAwAgAJW7x48Ze+9KXW41tuueVhhx1W+Nu99a1v3XjjjVuPn3766YW/FwC1O/jggwcGBlqPP/XUU22vPpAKAYCE/fCHP3zggQdaj//rv/7rSiutVPjbrbTSSh/4wAdaj19yySWFvxcATfBv//ZvM2bMaD3+3e9+t+0FCJIgAJCwY445pvXg5ptv/ta3vrWkd9x7771bD954442LFi0q6R0BqNEmm2zyj//4j63Hn3nmmWOPPbaOM4ICCACk6uabb77mmmtaj3/4wx8ub0vutttuO3v27DEHn3/++VtvvbWkdwSgXn/3d383ffr01uPHH398HacDBRAASNUZZ5zRenDKlCkHH3xweW86ZcqUXXfdtfX4bbfdVt6bAlCjtdZaq+3499d/UscZQa8KeEQ61OLcc89tPThv3rwNN9yw1Pc9+OCDWx8zt8Yaa5T6pgDU6B3veMepp57aevzCCy/caqut6jgj6InPASBJTz311Nprr936USyf/vSnP/e5z9V0UgDk8zkAy1u6dOmsWbNaPxNg//33P+2008p4RyiVJUAk6brrrmv7QYy77LJLHacDQM5WWWWVbbbZpvX49ddfX8fpQK8EAJL0y1/+su3x7bbbrvJzASB/ba8vd91115NPPlnH6UBPBACS9Ktf/ar14Jw5c9Zdd906TgeAiAFgZGTkjjvuqON0oCcCAEm65557Wg++5CUvqeNcAMjf3Llz2x7/wx/+UPm5QK8EAPIJABtssEEd5wJA/tZee+22x++///7KzwV6JQCQpIcffrj1YOtHdAFAIdZcc822x5944onKzwV6JQCQpNZnsfX19c2YMaOOcwEgf2uttVbb44sXL678XKBXAgBJeuaZZ1oPrrrqqnWcCwD5W9EEYMmSJZWfC/RKACBJzz33XOtBn2oHQEnafvhMX1/fyiuvXPm5QK8EAJI0ffr0DscCANC7Fd3pN3wmRQIASWq73L/txgAA6N2KPvBrtdVWq/xcoFcCAElaY401Wg8uWLCgjnMBIH8PPvhg2+Nz5syp/FygVwIASdpwww1bDz7wwAN1nAsA+VvR8/432mijys8FeiUAkKS2BffOO++s41wAyN9vf/vbtsc33XTTys8FeiUAkKQXv/jFrQcffPDBRx99tI7TASBzv/nNb1oPzp492xIgUiQAkKRXvOIVbY/fcMMNlZ8LAPm76qqrWg9uu+22dZwL9EoAIEkrqrk//elPKz8XADL3+OOP33zzza3H582bV8fpQK+m9fwKUIO5c+eutdZajz/++Jjjl1xyyb/8y7+U+tZ/+7d/O+Z5o6usssrxxx9f6psCUKPzzjuv7QeB7bbbbnWcDvRqig9PJVEHHHDA6aefPubgSiut9MADD6y33nolvekdd9zx0pe+dMzBzTbb7He/+11J7whAW1OmTGk9WFJX09/ff8opp4w5uPbaaz/00EM+CZgUWQJEqnbffffWg88///ypp55a3ptecMEFrQdbIwEA2XjooYfOOOOM1uMHHXSQ7p9ECQCk6oADDmhbeb/1rW+V96YXXnhh68FtttmmvHcEoF7f+MY3nn322dbj73rXu+o4HSiAAECq1ltvvT322KP1+A033HDJJZeU8Y6LFy++6KKLWo/vtNNOZbwdALV75JFHvv71r7ce33HHHV/3utfVcUZQAAGAhH3gAx9oe/yf//mfy3i7E0888bHHHhtzcOWVV37jG99YxtsBULtPfOITTzzxROvxf/qnf6rjdKAYAgAJ23PPPbfbbrvW41deeeXJJ59c+Nt985vfbD246667rrPOOoW/FwC1O+ecc77//e+3Ht9pp5322WefOs4IiiEAkLZPfepTbY9/5CMfefjhhwt8o1NOOeW6665rPf6+972vwHcBoCFuv/32d77zna3HV1pppW9+85ttn0EEqRAASNvb3va2titwFixY8M53vvOFF14o5F0ee+yxww8/vPX45ptvvt9++xXyFgA0x7333rvbbrstXLiw9UtHHHGEDwAmdQIAyfvGN77R9nFA559//ic+8YneX39kZORDH/rQ/fff3/qlL37xiyuttFLvbwFAc9x0003z5s276667Wr/0+te//jOf+UwdJwVFEgBI3ty5c7/4xS+2/dJ//Md/HHHEET2+/mGHHXbSSSe1Hn/Tm97U39/f44sD0BwjIyNHH330a1/72nvuuaf1q5tvvvnQ0JD7PmTAJwGTg5GRkX333ffss89u+9WDDz74O9/5zsyZMyf7sosWLfroRz/63e9+t/VLs2bNuvHGGzfeeOOuzheAxn0S8MUXX3zEEUdcffXVbb+6/vrrX3755ZtvvnnXrw/NIQCQiSeeeOINb3hD2326o7dtvva1r+29996dv+Bll1126KGH3n777a1fmjZt2vnnn7/rrrv2cL4ANCIA3HrrrWeeeeYPfvCDm266aUXfs9lmm11wwQU+951sCADk46GHHtp5551vu+22FX3DjjvuePjhh++zzz5rrLHGir7niSeeOPvss4866qif//znbb9h6tSpxx57bNtHQwBQbwAYHBwc5488//zzS5cuXbRo0cKFCx944IHbb7/9l7/85YSPjHvd61536qmnbrDBBj2fMjSFAEBWHnrooX333XdFvfuoVVZZ5bWvfe0222zz0pe+dK211lp55ZUX/skf/vCHq6666qabbhrn2UErr7zyscce+/a3v72c0wegUxU8iHPq1Kkf//jHv/CFL7R91ASkSwAgN4sXL/7gBz94/PHHF/7K66+//qmnnrrTTjsV/soANC0AvOY1r/nv//7vHXbYodR3gVp4ChC5mTFjxnHHHXf66afPmTOnwJd9xzvecfPNN+v+AbI3b968M8888+c//7nun1yZAJCtRYsWfeMb3/jKV77yyCOP9PI6b37zmz/72c++9rWvLe7UAGjcBGDu3Ln77bffIYccMnfu3GJfGZpGACBzixcvPv3004877rhLLrnk2Wef7fwPvuxlL9t///3f8573vPzlLy/zBAGoKABMnTp12rRpq6666syZM9dee+3Zs2dvsskmW2655dZbbz1v3rz111+/nDOFxhEAiGLRokVXXHHF5Zdffuutt95+++3333//U089tWjRopGRkRkzZsycOXODDTbYeOONt9xyy+22226nnXbabLPN6j5lAIDiCQAAABCITcAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgUyp+wQAqEd/f3/dpwBNMTw8XPcpQHVMAACC0vEAxCQAAABAIAIAQFyGAAABCQAAABCIAAAQmiEAQDQCAAAABCIAAERnCAAQigAAAACBCAAAGAIABDKt7hMAIA1Ds2bXfQrQvfkLF9R9CtAUJgAAdDQE0D8B5EEAAACAQAQAAP6PIQBABAIAAAAEIgAA8GeGAADZEwAAACAQAQCAv2AIAJA3AQAAAAIRAAAYyxAAIGMCAAAABCIAANCGIQBArgQAAAAIRAAAoD1DAIAsCQAAABCIAADAChkCAORHAAAAgEAEAADGYwgAkBkBAAAAAhEAAJiAIQBATgQAAAAIRAAAYGKGAADZEAAAACAQAQCAjhgCAORBAAAAgEAEAAA6ZQgAkAEBAAAAAhEAAJgEQwCA1AkAAAAQiAAAwOQYAgAkTQAAAIBABAAAJs0QACBdAgAAAAQiAADQDUMAgEQJAAAAEIgAAECXDAEAUiQAAABAIAIAAN0zBABIjgAAAACBCAAA9MQQACAtAgAAAAQiAADQK0MAgIQIAAAAEIgAAEABDAEAUiEAAABAIAIAAMUwBABIggAAAACBCAAAFMYQAKD5BAAAAAhEAACgSIYAAA0nAAAAQCACAAAFMwQAaDIBAAAAAhEAACieIQBAY03rS1x/f3/dp0CglgUAIHUmAACUwhAAoJkEAAAACEQAAKAshgAADSQAAABAIAIAACUyBABoGgEAAAACEQAAKJchAECjCAAAABCIAABA6QwBAJoj+U8CHt+sA4bqPgWaZeFp8+s+BQCAOpkAAFAFQwCAhhAAAAAgEAEAgIoYAgA0gQAAAACBCAAAVMcQAKB2AgAAAAQiAABQKUMAgHoJAAAAEIgAAEDVDAEAaiQAAABAIAIAADUwBACoiwAAAACBCAAA1MMQAKAWAgAAAAQiAABQG0MAgOoJAAAAEIgAAECdDAEAKiYAAABAIAIAADUzBACokgAAAACBCAAA1M8QAKAyAgAAAAQiAADQCIYAANUQAAAAIBABAICmMAQAqIAAAAAAgQgAADSIIQBA2QQAAAAIRAAAoFkMAQBKJQAAAEAgAgAAjWMIAFAeAQAAAAIRAABoIkMAgJIIAAAAEIgAAEBDGQIAlEEAAACAQAQAAJrLEACgcAIAAAAEIgAA0GiGAADFEgAAACAQAQCApjMEACiQAAAAAIEIAAAkwBAAoCgCAAAABCIAAJAGQwCAQggAAAAQiAAAQDIMAQB6JwAAAEAgAgAAKTEEAOiRAAAAAIEIAAAkxhAAoBcCAAAABCIAAJAeQwCArk3r/o8CAN0SUYC6mAAAkCRDAIDuCAAAABCIAABAqgwBALogAAAAQCACAAAJMwQAmCwBAAAAAhEAAEibIQDApAgAAAAQiAAAQPIMAQA655OAAaBxZh0wVPcp5GbhafPrPgVoChMAAHJgCADQIQEAAAACEQAAyIQhAEAnBAAAAAhEAAAgH4YAABMSAAAAIBABAICsGAIAjE8AAACAQAQAAHJjCAAwDgEAAAACEQAAyJAhAMCKCAAAABCIAABAngwBANoSAAAAIBABAIBsGQIAtBIAAAAgEAEAgJwZAgCMIQAAAEAgAgAAmTMEAFieAAAAAIEIAADkzxAAYBkBAAAAAhEAAAjBEABglAAAAACBCAAARGEIACAAAABALAIAAIEYAgAIAAAAEIgAAEAshgBAcAIAAAAEIgAAEI4hABCZAAAAAIEIAABEZAgAhCUAAABAIAIAAEEZAgAxCQAAABCIAABAXIYAQEACAAAABCIAABCaIQAQjQAAAACBCAAARGcIAIQiAAAAQCACAAAYAgCBCAAAABCIAAAAf2QIAAQhAAAAQCACAAD8H0MAIAIBAAAAAhEAAODPDAGA7AkAAAAQiAAAAH/BEADImwAAAACBCAAAMJYhAJAxAQAAAAIRAACgDUMAIFcCAAAABCIAAEB7hgBAlgQAAAAIRAAAgBUyBADyIwAAAEAgAgAAjMcQAMiMAAAAAIEIAAAwAUMAICcCAAAABCIAAMDEDAGAbAgAAAAQiAAAAB0xBADyIAAAAEAgAgAAdMoQAMiAAAAAAIEIAAAwCYYAQOoEAAAACEQAAIDJMQQAkiYAAABAIAIAAEyaIQCQLgEAAAACEQAAoBuGAECiBAAAAAhEAACALhkCACkSAAAAIBABAAC6ZwgAJEcAAACAQAQAAOiJIQCQFgEAAAACEQAAoFeGAEBCBAAAAAhEAACAAhgCAKkQAAAAIBABAACKYQgAJEEAAACAQAQAACiMIQDQfAIAAAAEIgAAQJEMAYCGEwAAACAQAQAACmYIADSZAAAAAIEIAABQwxAAoC4CAAAABCIAAEApDAGAZhIAAAAgEAEAAMpiCAA0kAAAAACBCAAAUCJDAKBpBAAAAAhEAACAchkCAI0iAAAAQCACAACUzhAAaA4BAAAAAhEAAKAKhgBAQwgAAAAQiAAAABUxBACaQAAAAIBApvX39/fla+Fp8+s+BYCGyrv+p871CyiPCQAAAAQiAAAAQCACAAAABCIAAABAIAIA/Jk9kQAxqf+EIgAAAEAgAgAAAAQiAAAAQCACAAAABDJt/C8PDQ31Ndv8+eN9VuKsA5p+/lTMh2tCh4Zmze5rtvkLF4zzVdcvxlD/YRkTAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAADL8qLLxP2YLIDIBAAAAApk6PDw8zpfdQQEAgJyYAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAACp8mHAAF0QAAAAIBABAAAAAhEAAAAgWAAYHh4e5zusoQQAgGyYAAAAQCACAAAABCIAAJAwTwIFmCwBAAAAAhEAAAAgEAEAAAACEQAAACBeAPBRAABkySUMYAwTAAByfhAQAGMIAAAAEIgAAAAAgQgAAAAQiAAAQObsAwboJgCongA0ln3AAN0EgPGfBAoAAGTAEiAAAAhEAAAgfxayAiwjAACQA9sAAIoPAG6fAABAVgHAPmAAAMibJUAAhGCODTBKAAAgE7YBAHRCAAAAgEAmFwDMTwFIl6sYQJsAYB8wAABkzBIgAPJhGwDAhAQAAAAIRAAAIBDbAAAmHQCUTgCazCoggEkHAPuAAQAgV5YAARCLUTYQnAAAQG6sAgIoOAC4dwIAAFkFANsAAMiYO1lAZJYAAZAhq4AAVkQAACAiQwAgrC4DgLoJAABZBQDbAABImlVAAG1ZAgRAUKbZQEzdBwB1EwAAkmMCAEDcVUBuZgEBjRcAbAMAAIDMmAAAkDNbgQGKDAAmpwCkzrUMiGaCAGAVEAAA5MQSIAAyZyswQJEBQNEEAICsAoBVQACkzhAAYBlLgAAAIJACAoC7JgA0n+eBAowyAQCAP3I/CwiiowBgGwAAAOShmAmAuyYANJ+twACWAAEAQCydBgCrgADIgCEAQGETABUTAACyCgCGAABkwBAACM4eAAAACKTIAOCWCQBJMAQAIptcALAKCIAgZAAgVwUvAVIuAchjCACQK3sAAKA9d7WALE06AFgFBEAeDAGAmIqfALhfAkA2XNSA/FgCBEBchgBAQN0EgAlXAblfAkAqPBIUiMYEAAAmIAMAOekyANgKDEA2LAQCQilrAuBmCQA5cV0DstF9ADAEACAbhgBAHCXuAXCzBICcuK4BebAJGAA6HQLIAED0AOB5oADkxEIgIAITAACYBPe2gOgBwBAAgJxYCARkzwQAAP6ChUBA3goIAJ4HCkA0hgBAuqqYAKiSAKTFQiAgY5YAAUAbMgCQq2ICgK3AAACQBBMAAGjPEADIUmEBwBAAgPzIAEB+TAAAoFcyABA0ABgCAJAfHwsAZMYEAAAmYCEQkJOCA4AhAABZkgGAbJgAAEBhZAAgYgAwBAAgSzYDAHkwAQCATlkIBGSglABgCABArmQAIHXT6nrj+fPnDw0N1fXuANDky9zC00QIILUlQBMOAQAg780A5gBAM9W5B0BlBCBRMgCQrhIDgCEAABmTAYBE1fwUIGURgHTJAECKyg0AhgAAABBrAuCRoABkzBAASE4jPghMWQQgXTIAkJYqAoCFQADkTQYAEtKICYCaCEDqZAAgFRV9EvDw8HB/f3817wUAtRiaNXv+wgUdfkhwL58TTHekL2jWBMCvJQAZMAcAmq+6ANDJTgAFEYDUyQBAw1U6AbAbGIAIZACgyRq0BGiUaghABmQAoLGqDgAWAgHA8lz1gOgTAAAINQQYzQBiAJBzADAEACCIzjOAax+Q+QTAbmAAgpABgKZp7hIgRRCAPMgAQKPUFgAsBAIgjqFZsye1JaDk0wFCq3MCIAMAEIoMADRBc5cAAUB+ZAAgegAwBAAgGo8HBaJPAGQAAKKxLRgIHQAAICAZAAgdAAwBAAhoshnApRDIJwDIAADENKkM4FIIZBUAOqTwAZAZGQCIGwA6GQIAQPCPCbMcCMgnAFgIBEBkRgFAxAAgAwAQmQwARAwAHVLyAMhSFxnANRFIPgDYDABAZJPdEuC+GJB8ALAQCACMAoBYAUAGAIDJZgBXRiDtAAAAdLccSAwAUg0ANgMAQNejADEASC8AyAAA0HUGsCIISDIAyAAA0PVyIKMAIMkAAAD0PgoQA4CUAoAhAAD0OAoQA4CUAoAMAABjdJcBbAwAkgkAMgAAjGEUAGQeAGQAACh2FCAGQECJBQAAoMBRgBgAAaUXAAwBAKCtrjOAGAChTOtL0PDwcH9/f91nAQC5WZYBhoaG6j4XoCzpTQBGmQMAwPLmL1wwf+GCwl7NQADylWoAkAEAoIzW/y9eWQyAHCW5BGgZa4EAiKykvn/su1gXBHlJOwAAQEzVtP5tk4AYAKkTAAAgJbW0/n9xAgYCkDgBAAACtf6jO+gKWUBrIACJEgAAIFDrX1IMkAQgIQIAAARq/VuPF/U4DUkAUiEAAEC41r/1ewp8qt7yTw4VBqCBBAAACNr6t/3+Yp+vbSwADSQAAEDo1r/tHy/8Y3aMBaA5BAAAqF8TWv/Wlyrp0zaFAaiXAAAAdWpa69/2ZUtKAmPCgDwA1RAAAKAeTW79275LeTFgGXkAKiAAAEDVEmr9275jBUmgbR4YJRVAjwQAAKhOoq1/7UlgwlSwjHgA0QPAwtPGqxEAUJk8Wv9GJYEu4gGQfwAAgNpl2fo3PwkAKyIAAEBZIrT+Y0gC0HwCAAAUL2DrP87JCwPQKAIAABRJ699KGIBGEQAAoBha/04IA1A7AQAAeqX1L+R/WR6AaggAANA9rX+BWv8eRAIogwAAAN3Q+leg7d+PVAA9EgAAYHK0/vUa/69OPID8A0BRBXRS9cLHjCfNh0QCXdP6N5+/XpjQ1Im/JYZJ1QsdJEA08xcu6L37H/6Tgs4IIOoEoEDDw8OdzwFGM4BRAED23PUHMmMC0FOBNgoAyJi7/kCWBICxZAAAtP5AxiwBamO0XlsOBBCQBT9A9kwAVsgoACAUd/2BIASA8cgAABFo/YFQLAEq8tFAlgMBpMWCHyAgAaD4LQGjMUAGAGgyrT8QlgDQKaMAgDxo/YHg7AEot9zbFQDQHNb6A5gATJrlQAApctcfYBkBoBuWAwGkQusPMIYAUFEGEAMAKqb1B2hLAKh0OZAVQQAV0PoDjEMA6JVRAEBzaP0BJuQpQH11XSo8IAigQJ7wA9AhE4CalwMZBQD0yF1/gEkRAGpeDiQGAHRN6w/QBQGgEaMAm4MBJkXrD9A1AaAURgEAJdH6A/RIAGjiKEAMAGil9QcohADQxFGAGACwPK0/QIEEgOaOAmwMAND6AxROAKiIUQDApGj9AUoiACQzChADgCC0/gClEgCqJgYArIjWH6ACAkBiK4LEACBLWn+AyggASY4CxAAgG1p/gIoJADUTA4CwtP4AtRAA8okBkgAQqvXX/QN0RwDIZGPAKAMBoOG0/gC1EwCyGgWMEgOABtL6AzSEANBEYgCQE60/QKMIACFigCQA1ELrD9BAAkCIGGAgAFRM6w/QWAJAxBggCQDl0foDNJwAEDEGGAgAZdD6AyRBAEhP4TFAEgB6pPUHSIgAkKoCY4AkAHRN6w+QHAEgbcsumZIAUDGtP0CiBIBMFDsQkASAcWj9AZImAGSl8BggCQDL0/oDZEAAyFDh64LGJAFhAALS+gNkQwDIWRkDgVHGAhCH1h8gMwJA/sqLAcYCkDetP0CWBIAoSloXtDxhAHJSSPev9QdoIAEgnAqSwJgwIA9AQFp/gMYSAOKqJgmMkgcgDq0/QMMJAJS7SaAteQCypPUHSIIAQA0DgfHzgEgAydH6AyREAGC8C3n1YWBFkWCUYABNo/UHSI4AQEPHApMKBssTEqAaWn+ARE2p+wRITEOSQHn0NMTR9a+zXxOApJkAkN4CIaAuWn+ADAgAdE8YgDi0/gDZEAAohjAAudL6A2RGAKD0dkEegERp/QGyJABQOnkAkqP1B8iYAEDV5AFoMq0/QPYEAJrYbUgFUD2tP0AQAgApNSKCAZRB6w/QF8n/Bym/KmAw5iwMAAAAAElFTkSuQmCC"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_209
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is Stack the original shape on top of the {'layer1': 'SwSwSwSw'}.\nthe 3th action is Cut the right side of the shape\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is Cut the right side of the shape\nthe 6th action is Stack the original shape on top of the {'layer1': 'RuRuRuRu'}.\nthe 7th action is Stack the original shape on top of the {'layer1': 'CbCbCbCb'}.\nthe 8th action is Colorize the top layer of the original shape with the color blue.\nthe 9th action is Stack the original shape on top of the {'layer1': 'CcCcCcCc'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_92
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color cyan.\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is Cut the right side of the shape\nthe 4th action is Colorize the top layer of the original shape with the color cyan.\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is Colorize the top layer of the original shape with the color green.\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is Stack the original shape on top of the {'layer1': 'WuWuWuWu'}.\nthe 9th action is Stack the original shape on top of the {'layer1': 'SbSbSbSb'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABAAAAATICAIAAAANxCANAABsUElEQVR4nO3dDbSkdX0f8N1lARcQWJTwakXRCFgVNQkKNsZDML6BShykxjS1Gk08xqS2Nsc2Vs1JNY1Nm1htTI2Jmgi6K1jfNSIYjUo0BgVifAFfQRHUFWSBBWF79HrGzZ25c2fmefv/f7/P5/T0xGd3732Yeeb7/F5m7t24e/fuDQAAQA6bhj4BAACgPxoAAABIRAMAAACJaAAAACARDQAAACSiAQAAgEQ0AAAAkIgGAAAAEtEAAABAIhoAAABIRAMAAACJaAAAACARDQAAACSiAQAAgEQ0AAAAkIgGAAAAEtEAAABAIhoAAABIRAMAAACJaAAAACARDQAAACSiAQAAgEQ0AAAAkIgGAAAAEtEAAABAIhoAAABIRAMAAACJaAAAACARDQAAACSiAQAAgEQ0AAAAkMjmoU8AenXDDTccdthht9xyy9Q/fcYznvGa17ym95MCoJE3velNC/39TT+0efPmfffdd7/99jv44IMPPfTQww47bK+99ursHKEgG3fv3j30OUB//vzP//zpT3/6Wn96yCGHXHPNNXvvvXe/JwVAIxs3bmz+RfbZZ59/+S//5YMe9KCf+qmfOv3004888sg2Tg1KpAEgl1NPPfXCCy+c8Rfe+c53Pvaxj+3xjAAoogFY9QVPOeWUf/tv/+2v/MqvbN7s7RJE4zMAJHL11Vd/8IMfbHePDEA8u3fv/tu//dtnPOMZxx9//LZt24Y+HWiZBoBEzj333DvuuGP233nb29621icEAMjmiiuuePKTn/zMZz7z1ltvHfpcoDUaABL5q7/6q1VHtm7duurI9773vXe96109nhQApXvNa17zqEc96rbbbhv6RKAdGgCy+Md//MdPf/rTqw6+/OUvn3xz55vf/OYezwuATuye6fbbb7/11luvv/76r3zlKx/60If+9//+30960pP222+/tb7aRRdd9NznPrff/wLoig8Bk8ULXvCC3//939/zyIEHHnjttdc+5jGPWfWx4C1btlx77bUHHHBA7+cIQGsfAl6iwrnxxhv/6I/+6A/+4A++973vTf0L73vf+x75yEcudY5QEBsAUti9e/e555676uATnvCEfffd98wzz1x1/Oabb37729/e49kBUIQDDjjgd37ndy6++OJjjjlm6l94yUte0vtJQfs0AKTw4Q9/+Ctf+cqqg09+8pNX2oDJ0ZGfBQSQ1gknnPCud71r6tuBPvrRj/793//9ECcFbdIAkMIb3/jGVUcOOeSQ0047bcOGDUcdddTP/MzPrPrT973vfd/97nd7PEEACnLCCSf89m//9tQ/uuCCC3o/HWiZBoD4br311u3bt686eOaZZ45/4+8Tn/jEyX9y/vnn93WCABTn2c9+9l577TV5/KKLLhridKBNGgDie/e7371jx46p7/9ZMfkxAO8CAkjurne964knnjh5fPINpVAdDQAZf/z/oYce+ohHPGL8P+9973vf9773XfV3Lrzwwuuuu66XEwSgRPe73/0mD37rW98a4lygTRoAgrv++usnf7HXk570pFWL3cklwO233/6Wt7yl+xMEoFB3uctdJg9ef/31Q5wLtEkDQHBvectbbrnlllUHzz777FVHvAsIgHl+k8CBBx44xLlAmzQApHv/z5FHHvmwhz1s1cETTzzxHve4x6qDf/u3f3v11Vd3fIIAFGrqj4M79NBDhzgXaJMGgMiuuuqqD33oQ6sOjkajTZumXPmTPwvojjvu2LZtW5cnCEC5Pve5z00efPCDHzzEuUCbNABEds4559xxxx3rvv9nrQbAu4AA0tq1a9cll1wyefxnf/ZnhzgdaNPGqe9vgxge8IAHXHrppXseufvd7/6lL31p8lf/rsz7jzzyyG9+85urjn/xi1+cfHcQAOWYmuoNK5w3vvGNT33qU1cd3G+//a6++uqDDz64yVeGwdkAENbll1++qvrfsGHDWWedNfU+8YMXw6ZNj3/84yePv/nNb+7mBAEo1K233vrSl7508vgzn/lM1T8BaAAIa/LjvzPe/7PCzwICYMOGDc973vM+85nPrDp4t7vd7Xd/93cHOiNok7cAEdPu3buPOeaYr371q3sevNe97vWFL3xhxr+67bbbfuInfmLyxz780z/903HHHdfNmQJQ0FuAdu7c+Vu/9Vt/9md/tur4gQce+MEPfvCBD3zgsucIBbEBIKYPfehDq6r/DRs2PPnJT579r/bee+/HPvaxk8ctAQDC27Fjxyte8Yr73ve+k9X/YYcd9p73vEf1Txg2AMT0q7/6q5MJfumll079ve57Ov/883/xF39x1cHjjjvun/7pn9o+RwA63ACce+65M/7J7t27d+3addNNN11zzTVXXXXVJZdccumll07+4LgNGzacdtppr3vd64488shWTxmGpAEgoF27dh1++OGr3slz/PHHT76hc9JNN91017ve9eabb151/JJLLjnxxBPbPlMAWrDWT3do6IEPfOBLXvKS008/vYsvDgPyFiACete73jX5Pv7ZH/8d22+//X7hF35h8rh3AQHksf/++//Jn/zJJz/5SdU/IWkACOiNb3zj5MF1PwAw+zeC+WGgAHns3Lnz13/914866qjnPOc53gJKPN4CRDTf/e53Dz/88F27du158MQTT5z6Cx2n2rFjx0/8xE98//vfX3X84osvPumkk9o7UwCKfgvQ2KMf/eg//uM/vve9793pd4He2AAQzVve8pZV1f9C4/8NGzZs3br1537u5yaPexcQQE7vec977n//+/+P//E/hj4RaMfmlr4OFP37vzZu3LhQ+X7ooYdOHty2bdsf/uEfbtqkbQaowLrvcbjjjjt27tz5ve997+qrr/7a1772qU996uMf//hFF1106623Tv7lW2655fnPf/6Xv/zlV7ziFW4E1M5bgAjla1/72t3vfvfuruoPfvCDD3/4wzv64gAM/ovAvv3tb7/uda/7vd/7vckfJrHiRS960Ytf/OIlvjKUQwtLKOecc06nPa13AQHEdpe73OU//If/8PnPf/4Rj3jE1L/we7/3ex/72Md6Py9okw0Aodz//ve/7LLLuvv6hx566Ne//vXNm713DiDmBmBs165dj33sYz/wgQ9M/tFpp53213/9102+OAzLBoA4Lr300k6r/w0bNlx33XUXXnhhp98CgBLsu+++b3jDGw455JDJP3r/+98/z2+WhGJpAAj+8d/WeRcQQBJHHnnkc57znKl/9O53v7v304HWaAAIYvfu3eeee+6qg/vvv/9NN920e1nnnHPO5Dd661vfOvUHRAAQzzOf+cypxz/60Y/2fi7QGg0AQXzwgx+86qqrVh183OMet2XLlqW/5umnnz75z7/73e++973vXfprAlCRo4466thjj5087i1AVE0DQBBvfOMbJw+ORqMmX/OAAw549KMfPXncu4AA8njwgx88efA73/nOEOcC7dAAEMGuXbvOO++8VQf333//qeX7Qs4666zJg29/+9tvuummhl8ZgCrc5S53mTy41m8JgCpoAIjgne9852QWP/axj91vv/0afuXHPe5xk19k586d73znOxt+ZQCqcOCBB04e9MuAqZrLl7A//6fh+39W7L///o95zGMmj7/5zW9u/sUBKN8NN9wwZ1cAtdAAUL0dO3ZM/ji2/fbbb2rhvoQnP/nJkwff/e53f+9732vl6wNQsuuuu27y4NFHHz3EuUA7NABUb/v27ZM/l7OV9/+Mv9T++++/6uAtt9zy//7f/2vl6wNQso9//OOTB48//vghzgXaoQGgel38/J89bdmy5XGPe9zkcT8LCCC8z3/+81/96lcnj5900klDnA60QwNA3b761a9++MMf7u79PzN+FtD73/9+PwYOILb/9b/+19Tjj33sY3s/F2iNBoC6nXPOObt371518DGPeczkm3aaeMxjHnPAAQesOnjbbbdN/uxRAMK45JJL/uIv/mLy+MMe9rCpvx0MaqEBoG5dv/9nxZ3udKfTTz998rh3AQFEdfXVVz/pSU/atWvX5B/99m//9hBnBK3RAFCxT33qU5dffvmqg1u2bOliMzv1XUB/8zd/881vfrP17wXAsC6++OKTTjrpi1/84uQfPepRj5r6wTCoiAaAaOP/Rz/60e2+/2f8ZSd/6vPtt9++ffv21r8XAEP5+Mc//m/+zb85+eSTr7766sk/Pfzww6e+KQjqsnnoE4Al3XHHHeeee24P7/9Zse+++55xxhmTv3HsTW9603Oe85wuviMATczzLs3vf//7u3btuuGGG771rW999rOf/eQnP/mVr3xlrb98yCGHvPe97z388MPbPlPo28bJD1BCFS688MJTTz111cE73elO11133eQHdlvxjne844wzzlh1cOPGjV/5ylfudre7dfEdAZjHxo0bu/4WJ5xwwtvf/naf/SUGbwGiVpPD+JU36nRU/W/YsOEXfuEXDjrooFUHd+/e/eY3v7mj7whACZ761KdefPHFqn/C0ABQpVtuueX888/v7f0/K/bZZ5/HP/7xk8f9LCCAqH7qp37qIx/5yF/+5V/e+c53HvpcoDUaAKr0jne84/rrr1918E53ulPXP5lh6s8C+uQnP3nFFVd0+n0B6NMBBxzwtKc97SMf+cgnPvGJk08+eejTgZb5EDBV2rJly4te9KJVB//Fv/gXXU9oHvnIR774xS+e/OTMZDcCQOE2bty4efPmfffd94ADDti6dethhx1297vf/UEPetDJJ5984oknbt6sRiIsHwIGAIBEvAUIAAAS0QAAAEAiGgAAAEhEAwAAAIloAAAAIBENAAAAJKIBAACARDQAAACQiAYAAAAS0QAAAEAiGgAAAEhk42g0GvocoBTbt28f+hSgP/IfxuQ/qWxyxQNkM/oh+Q+QM/83D30aAPTH1B8gpz3z/wefATAEAkgy9Vl1UP4DJMx/GwCA4Ez9AXIarZH/P/opQIZAAEmm/qvIf4Bs+W8DABCQqT9ATqM58v/HvwfAEAggydR/FfkPkCr/bQAAgjD1B8hptGD+/7PfBGwIBJBk6r+K/AfIk/8LbwBMmKiaKodg+sxk+U/V5D/BjBpk8qZFXx5ePwAxpv6ryH+AJPnvMwAAlTGJB8hp1FL+r94AGAIB5Jn6ryL/ATLkvw0AQAVM/QFyGnWQ/1M2AIZAAHmm/qvIf4Dw+T+9AQAgQPTbGwDUaNRx/q/ZABgCAVQd/Ut/BfkPEDv/fQYAoCDNZ/am/gA1GvWY/7PeAmQIBJBk6r+K/AcInP82AAADM/UHyGk0UP6v8yFgQyCAJFP/VeQ/QNT8twEAGICpP0BOowLyf/0fA2oIBJBk6r+K/AcImf82AACJpj4A9K+0/J/rF4EZAgHEmPosSv4DxMt/GwCARFMfAPpRcv7PtQEwBAKIMfVZgvwHCJb/NgAAiaY+AHSnlvyfdwNgCAQQYOqzHPkPECn/bQAAEk19AGhXjfm/wAbAEAig9qnP0uQ/QJj8twEASDT1AaC52vN/sQ2AIRBA1VOfJuQ/wChE/tsAACSa+gCwnEj5v/AGwBAIyCnG1Kch+Q8kNAqX/zYAAImmPgDML2r+L7MBMAQCkog39WlO/gMZjELnvw0AQKKpDwCzZcj/JTcAhkBAVLGnPq2Q/0BIozT5bwMAkGjqA8CkbPm//AbAEAgII8/Upy3yH4hhlDL/bQCA1LJNfQBYkTn/G20ADIGAeuWc+rRI/gOVGqXPfxsAIJ3MUx+AzOR/OxsAQyCgIqY+7ZL/QC3k/55sAIAUTH0AcpL/nWwADIGAkpn6dEr+A8WS/2uxAQDCMvUByEn+97EBMAQCimLq0yf5D5RD/s/DBgAIxdQHICf5P8AGwBAIGJapz4DkPzAg+b8oGwCgeqY+ADnJ/+E3AIZAQM9Mfcoh/4E+yf8mbACAKpn6AOQk/4vbABgCAV0z9SmW/Ac6Jf/bYgMAVMPUByAn+V/6BsAQCGidqU8t5D/QLvnfBRsAoGimPgA5yf/KNgCGQEBzpj6Vkv9AQ/K/azYAQHFMfQBykv91bwAMgYAlmPrEIP+BRcn/PtkAAEUw9QHISf6H2gAYAgHzMPUJSf4D65L/Q7EBAAZj6gOQk/yPvAEwBAKmMvXJQP4Dk+R/CWwAgP60EtlyH6A68j/XBsAQCGhrYGPqUx35D8j/AtkAAN0y9QHISf6n3gAYAkFOpj7If8hJ/hfOBgBon6kPQE7yvwo9bQAMgSAJUx8myX/IQP5XxAYAaIepD0BO8r86/W0ADIEgKlMf1iX/IST5XykbAGB5pj4AOcn/qvW6ATAEgjBMfViU/IcY5H8ANgDAYkx9AHKS/2EM0ABs37599nO/7l8ABtHKyKelc6FK8h8qJf+DsQEA1if6AXKS/yH1/RmAFd4JCrVo/jZNb/RkT/IfaiH/A7MBAKYz9QHISf6HN8wGwBAISmbqQ6fkPxRL/idhAwD8mKkPQE7yP5XBNgCGQFAUUx/6JP+hHPI/IRsAyM7UByAn+Z/WkBsAQyAYlqkPA5L/MCD5n5wNAGRk6gOQk/xn+A2AIRD0zNSHcsh/6JP8Z8wGALIw9QHISf5T3AbAEAi6ZupDseQ/dEr+M5UNAERm6gOQk/yn9A2AIRC0ztSHWsh/aJf8Z102ABCNqQ9ATvKfyjYAhkDQnKkPlZL/0JD8ZyE2ABCBqQ9ATvKfujcAhkCwBFMfYpD/sCj5z9JsAKBWpj4AOcl/Qm0ADIFgHqY+hCT/YV3yn1bYAEBNTH0AcpL/RN4AGALBVKY+ZCD/YZL8p3U2AFA6Ux+AnOQ/iTYAhkCwwtSHhOQ/yH+6ZgMAJTL1AchJ/pN3A2AIRFqmPiD/yUn+0xsbACiFqQ9ATvKfnpW7ATAEIg9TH1hF/pOE/GcQNgAwJFMfgJzkPwMqegNgCERgpj4wm/wnKvnP4GwAoG+mPgA5yX8KUfoGwBCISEx9YCHynzDkP0WxAYA+mPoA5CT/KVAFGwBDIKpm6gNNyH/qJf8plg0AdMXUByAn+U/h6tgAGAJRF1MfaJH8pyLynyrYAECbTH0AcpL/VKSaDYAhEIUz9YHuyH9KJv+pjg0ANGXqA5CT/KdSNW0ADIEojakP9Eb+UxT5T9VsAGAZpj4AOcl/AqhsA2AIxOBMfWAo8p9hyX/CsAGAeZn6AOQk/wmmvg2AIRD9M/WBQsh/eib/CckGAGYx9QHISf4TWJUbAEMgemDqA2WS/3RN/hOeDQCsZuoDkJP8J4mNG2q27svM65CeR4MuOSq65quelMt/FiX/yWb72te8DQC0Q/QD5CT/qU6tnwFY4Z2glMB7PaF/8p8SyH8qVXcDEIBbVNVEf0OufzJz/VdN/jfk+h9W9Q1AgCHQ9h8a+ixYjOhvyGVPc/KfQcj/hlz2JfAZgIGNRqOVl8HK/y9Tyuc5amjP3Pdgkpn8r47nqCH5X47qNwAxhkBj2uKSmfo05PKmdfKffsj/hlzepbEBKGgINGYaVBrPRUNTc9+jCvK/fJ6LhuR/mSJsAIINgca0yyUw9WnIZUzX5D8dkf8NuYxLZgNQ6BBozDRoKB7zhmbnvocXVsj/AnnMG5L/5YvTAGzfvn32JbXuXyiZ20CfPM5NmPfQP/lPWzzOTcj/isRpAAIPgcbcBrrmse0n+j3OsCf5XwKPbRPyvzpBPgMQ+J2ga72pLsZ/CzG4IBmc/IdBuCArFaoBqN2ibbFXHYNb4iI0/oFJ8p/qyP+qRWsAkgyB9uQ2wCBceJRG/kM/XHgBRGsAard0c+zVSG+aXGzGP7AW+U/55H8YARuAhEOgMbcBOuUCo3Dyf+izICwXWDABG4DaNW+RvUppXSsXlfEPzCb/KZD8DylmA5B5CDTmNkArXEjURf572dIWF1JgMRuA2s1olLeeuW2hL+XVy9IWvXhmX5zGPzAP+U8J5H94YRuAqEOgHeeftfXMbW4DlBb9W8/ctuP8s7o8KZiX/N+T/Gch8j8Jvwm41l8MuXIPWOgl5xdJsq5FC4U5axFXHcxP/jMI+Z9K2A1A7CHQ+P82DWLYqc/4fxr/UBT5P5X8Zyr5n5ANQMVDoDHTIJa2RDWwaM3hMoNFyX96IP8zi7wBSDIEGjMNoutnf61rzPiHAsn/2eR/ZvIfG4AgQ6Ax0yBKmPqMua5gOfKfLsh/UmwAsg2BxkyD6HrqM2b8Q7Hk/5zkfwbynz3ZAAQcAo2ZBjHI1GfMhQRNyH9aIf/JuAFIOwRqPg2q9GGhh6nPmPEPhZP/8j8z+c9abACCD4GaTIMMhGo3yNRnzGUDzcl/liP/mS3FBsAQqMk0yNtDa9Tp1GfM+IcqyP8V8j8J+c88bAASDYHGTIMCG3bqM+Y6gbbIf+Yk/5lflg2AIdAk06Bg+pn6jBn/UBH5v4r8D0b+s6hEDUDtOmqpl3v9uw0UZbmno4vBzwrjH2iX/Gct8p/l5GoADIHaHQO4DdQb/Q3T3/iH6sj/qeR/veQ/TfgMQN53grbyxlDvDR3KcldCd1OfMVcCdEH+Myb/aS7XBsAQaF2mQYVb+kd0N5/6jBn/UCn5P5v8L5z8p0U2AExhGlSghr8QFGAe8r9A8p/WpdsA1D4EmpGtrfflpkGFWPrxbHHqM+dl5t5P4eT/nOR/IeQ/HbEBYB2mQQMy9QEGJP8HJP/pVMYNgCHQEkyDMk99xox/CED+L0r+90z+0wMbABZgGtQDUx+gQPK/B/Kf3iTdABgCNWEalGrqM2b8Qxjyf2nyvyPyn57ZALAk06AWmfoAFZH/LZL/DGLjhtzWjaGSc2pGavScC03GTj0/wrOjtv+nu5boN/6p14xrLPlEVv63Qv4vTf4z4DVmA8CQ06DMA6Faoh9gBvm/BPnP4PJ+BmCFd4K2qMk7EVO9PbTw93pOMv4hJPnfIvk/J/lPIWwAaJlp0AymPkBg8n8G+U9Rsn8GYIV3guZ5b+gg7wFtMtwq/Eks+aXBCp8BmE3+d0T+z/NNZyv8SSz5pcEKnwFgGKZBVUc/wNLkv/ynZNk/A7DCO0E7lfO9oU3OfKj3ek4y/iE8+d8p+b8o+U8/bADoSZ5pkKkPwJ7k/zzkP32yAfgRQ6B+xJ4GxZj6jBn/kIT874f8X4v8p382AAwg3jTI1AdgHvJ/T/KfodgA/JghUM9iTIOCTX3GjH9IRf73TP7Lf4ZlA8DA6p0GmfoANCH/YSg2AP+MIdBQ6poGRZ36jBn/kJD8H4r8L4r8T8IGgIKUPw0y9QHogvyHPtkArGYINLgyp0Hhpz5jxj+kJf8HJ/+HJf/zsAGgUOVMg0x9APok/6FrNgBTGAKVo0mArsxsmjxZDf95jelv/ENy8r8c8r9n8j8VGwAij4KWGwg1v8HXGP0ApZH/0JGNXX3h+q2bFyV3wzMirOpsKn+IFfjhLfmCZ7k0KHmYPSz5XyD53yn5H9KMNLABINc0qDtVRz9A4eQ/tMhnANbknaDFKu2HKpR2Pssx/oEx+V+s0vK2tPNZjvxPyAaAWpUwDQqQ+wDVkf/QkA3ALIZA5Rtq+hJj6jNm/AOryP/yyf9WyP+cbACIoM9pUKTcB6id/Icl2ACswxCoIl1PZYJNfcaMf2Aq+V8R+b8c+Z+WDQDRdDENCpn7AMHIf5iTDUDwIdAMIYdArU9rok59klwG0JD8r5H8n1Psy4DZNADBJd/fNYnv8NE/j+TXD1Qt+etX/jeU/PoJTwMwF0Ogqi0a5XmiP8kFAE3I/6rJ/+QXAGvRAGRv4vNEwDyxnif653nqjX+gdvJ/hfxfRf6jAcg+BAJgNvkPBKMBSMEQiFWMfyAJ+c8q8h8NwGIMgQBykv9AJBqALAyBGDP+gVTkP2PynxUagMUYAgHkJP+BMDQAiRgCYfwDOcl/5D970gAszBAIICf5D8SgAcjFECg54x9IS/4nJ//ZkwZgGYZAADnJfyAADUA6hkBpGf9AcvI/LfnPKhqAJRkCAeQk/4HaaQAyMgRKyPgHkP85yX8maQCWZwgEkJP8B6qmAUjKECgV4x9gTP6nIv+ZSgPQiCEQQE7yH6iXBiAvQ6AkjH+AVeR/EvKftWgAmjIEAshJ/gOV0gCkZggUnvEPMJX8D0/+M4MGoAWGQAA5yX+gRhqA7AyBAjP+AWaQ/4HJf2bTALTDEAggJ/kPVEcDgCFQTMY/wLrkf0jyn3VpAFpjCASQk/wH6qIB4AcMgYIx/gHmJP+Dkf/MQwPQJkMggJzkP1ARDQA/YggUhvEPsBD5H4b8Z04agJYZAgHkJP+BWmgA+DFDoACMf4AlyP8A5D/z0wC0zxAIICf5D1RBA8ACDIEK5wkCOiJeCucJYiEagE7UOwSyH4zN8wtdk/+UyfPLnjQALMaMoVieGqBTQqZYnhoWpQHoiiEQpfHMQj/kP6XxzLKKBoCFmTQUyJMC9EDUFMiTwhI0AB0yBKIcnlPok/ynHJ5TJmkAWIZ5Q1E8HUBvBE5RPB0sRwPQLUMgSuDZhP7Jf0rg2WQqDQBLMnUohCcC6JnYKYQngqVpADpnCMSwPI8wFPnPsDyPrEUDwPLMHgbnKQAGIXwG5ymgCQ1AHwyBGIpnEIYl/xmKZ5AZNAA0YgIxIA8+MCARNCAPPg1pAHpiCET/PHdQAvlP/zx3zKYBoClziEF42IHBCaJBeNhpTgPQH0Mg+uRZg3LIf/rkWWNdGgBaYBrRMw84UAhx1DMPOK3QAPTKEIh+eL6gNPKffni+mIcGgHaYSfTGQw0URSj1xkNNWzQAfTMEomueKSiT/KdrninmpAGgNSYTPfAgAwUSTT3wINMiDcAADIHojucISib/6Y7niPlpAGiT+USnPLxAsQRUpzy8tGujfhEAAPKwAQAAgEQ0AAAAkIgGAAAAEtEAAABAIhoAAABIRAMAAACJaAAAACARDQAAACSiAQAAgEQ2z/5jvyeYVbZv3z77L2w9c9uGan+betUnv+LYbVt7OZdErjxrR5NXRMlmJ3z5+T/7wfda6Pm1UHuEVn3yJb9m1w3JqlO0XjYAtKnwAK2dhxcoloDqVOCHt8y+JTwNAAvQpgcY0QEsQbaUr8x7tPq+TBoAWhN4PlEODzJQINHUg8APsiahfxoA6h4tMMmgDmiXVKlFmXdq9X2BNAC0I/BkojQeaqAoQqk3gR9qTULPNABUPFRgLcZ1QFvkSV3KvF+r70ujAaAFgWcSZfKAA4UQRz0L/IBrEvqkAaDWcQKzGdoBzUmSGpV511bfF0UDQFOBpxEl87ADgxNEgwj8sGsSeqMBoMpBAvMwugOakCH1KvPerb4vhwaARgLPIcrnwQcGJIIGFPjB1yT0QwNAfSME5meAByxHetSuzDu4+r4QGgCWF3gCUQtPATAI4TO4wE+BJqEHGgAqGx6wKGM8YFFyI4Yy7+Pq+xJoAFhS4NlDXTwRQM/ETiECPxGahK5pAKhpbMByDPOA+UmMSMq8m6vvB6cBYBmBpw418nQAvRE4RQn8dGgSOqUBAACgV+r7YWkAWHhjGHjeUK91nxQ7fWAes7NC/hdo3SelzHcBzUOT0B0NAAAAfVPfD0gDwGrG/5WyBAAaMv6vlCUAi9IAAAAwAPX9UDQA/DPG/1WzBACWZvxfNUsAFqIBAABgGOr7QWgA+DHj/wAsAYAlGP8HYAnA/DQAAAAMRn3fPw0AP2L8H4YlALAQ4/8wLAGYkwYAAIAhqe97pgHgB4z/g7EEAOZk/B+MJQDz0AAAADAw9X2fNAAY/8dkCQCsy/g/JEsA1qUBAABgeOr73mgAsjP+D8wSAJjB+D8wSwBm0wAAAFAE9X0/NACpGf+HZwkATGX8H54lADNoAAAAKIX6vgcagLyM/5OwBABWMf5PwhKAtWgAAAAoiPq+axqApIz/U7EEAMaM/1OxBGAqDQAAAGVR33dKA5CR8X9ClgCA8X9OlgBM0gAAAFAc9X13NADpGP+nZQkAyRn/p2UJwCoaAAAASqS+74gGgB8z/gnPUwxMJRzCC/wUaxKWoAHIpd4dH/3wLiCIyqubSisE9X0XNADEnw2wJ080sIpYSCLwE61JWJQGIJFim3uKYkwI8XhdU3WdoL5vnQaA4FMBJnm6gTGBkErgp1uTsBANQBbFtvUUyLAQIvGKJkC1oL5vlwaAyPMA1uJJB0RBToGfdE3C/DQAKRTb0FMsI0OIwWuZMDWD+r5FGoDsAk8CVtlx/lk7zj+r+d8JI89TDyQPAfmf56nXJMxJA5C6lQ8cAU1iPc9tYPYFYHAItZvxKpb/rfz9es2+ACwBwts89AlAh5rk+Mq/TXKPBAhG/qc1Go2KbWDKYQMQXNrxf1tTnPDTIEsAiCrt+F/+z8kSIDMbAKLpIq9NgwDKJ/9ZYQmwLhuAyLKN/7ue1kSdBlkCQDzZxv/yfzmWAGnZABBBn7lsGgRQDvnPVJYAs9kAhJVk/D/UVCbYNMgSACJJMv6X/62wBMjJBoBalZC/pkEA/ZP/zMMSYAYbgJhij/9Lm76Udj7LsQSAGGKP/0vL29LOZzmWAAnZAFCTknPWNAigO/KfJVgCrMUGIKCQ4/9apiy1nOdUlgBQu5Dj/1pytZbznMoSIBsbAErXVp6uxMTsFDt229ZWKl3TIIBy8n+ebJ/nHjEP+V8aS4CpbACiCTb+byX9Rz80/98/dtvWlf/X8PvWOAqyBIB6BRv/txKhi4b5yv2i+Vw5Xv4XW0NbAizHBoBCNU/P5qHQfCFgFATQf/43n+A0XwjI/3JYAkyyAQglxvi/+dsoW5nfjDXfBtT1xlBLAKhRjPF/87RsZX/b4t0kUv4XW0NbAizBBoCClDD1X4ttAEDsqf9abAMCsARYRQOQQvmhU3Lpn7AN2HrmtopGVsAMhadN4aV/wjag0vxX3y9KAxBHpZd+LaV/wjZgLVeetaOf2y0wp0rfm1dL6Z+wDVjL9u3b632/jSZhTxqA+IpNmRpL/zxtQKVDIGBPZcZLpaV/njag0vxX3y9EAxBEXRd97aV/njZgLZYAUI66xv+1l/552oC1WALEoAEIrrRYiVT6h28DKh0CASuKypNgpX/4NqDS/Fffz08DEEEVl3vU0j98G7AWSwAoQRXj/6ilf/g2YC2WAAFoACIrJEcylP5R24BKh0BACQGSpPSP2gZUmv/q+zlpAKpX8oWerfSP2gasxRIAhlXy+D9b6R+1DViLJUDtNABhDRscmUv/YG1ApUMgyKz2/K+39A/WBlSa/+r7eWgA6lbgJa70n3EzW7oTGPw2sBZLABhKgeN/pf+MO9rS9+ti898SoGoagJgGSQqlf9cLgaFuA5UOgSCnSvM/Xunf7kJA/i9Efb8uDUDFyrm4lf4Z2oC1WAJA5vG/0j9DG7AWS4B6aQAC6jMalP5J2oBKh0CQTV35n6r0r7cNqDT/k9f369IA1Grwy7phHKSt+6tuA9ZiCQCpxv8N819c1NgGrMUSoFIagGh6yAKlf842oNIhEORRfv4r/SttAyrN/8z1/bo0AFUa6oJW+neqijZgLZYAEHv8r/TvVBVtwFosAWqkAQiluxe/0r83JbcBlQ6BIINi81/pH6MNqDT/09b369IA1KfnS1npP4iS24C1WAJAsPG/0n8QJbcBa7EEqI4GII7WX+1K/8EV2AZUOgSC2ErLf6V/yDag0vzPWd+vSwNQmX4uYqV/UQpsA9ZiCQC1j/+V/kUpsA1YiyVAXTQAQbT18lb6F6ucNqDSIRBEVUj+K/0ztAGV5n/C+n5dGoCadHr5Kv2rML7FLtcJ9DANsgSA6sb/Sv8qjO+zyxUDPeS/JUBFNAARNHw9K/2zLQSa3wYqHQJBPMPmv9K/uoVA2vzPVt+va9P6f4UydHThNnkZj36o1dNhMcdu27r0Dbi7BB/815RCMB29ppqEQJPwoRVNbsHd5X/VRfYoU0ljA1C9pfv4hqX/0v+WcrYBTUZBlQ6BIJJB8l/dH2MbkDD/LQH2pAGoQ7uXrNI/pEHagLX4JACUOf5X+oc0SBuwFp8EqIIGoG6LvmiV/uH12QZUOgSCGPrMf6V/FfpsAyrN/zz1/bo0AFko/VMpahsADEvpn0pR24AajXI0CT4EXIG1LsQ5X6U7zj9r6fT3Md+qLf0pvfmvmRkXoY8CQ3NrvY56yH8f863a0rfvVvK/5AJaVbPCBiCyJnV/2+fCYGwDIKEmdX/b58JgbAOWM0qwBLABiDn+X3rqY+QfVXfbAEsAKGr8v3T+G/lH1d02wBKgXjYA0Zj6M4NtAARm6s8MtgELGUVfAtgAxBn/m/oz1DbAEgCGHf+b+jPUNsASoFI2ABGY+rME2wAIwNSfJdgGzCP2EkADUPf4X+lPQ+MiYNFOYNVtYMbPhPZLwaCL8b/Sn4bGlcCiZe78+V/yLwUbha7v16UBqJXSnxIWAqmmQVAIpT8lLAQy5P8obpOgAahv/K/0p9g2wBIAOh3/K/0ptg2wBKiLBqAyS3/Mt4NzIawmbQDQkaU/5tvBuRBWkzYgpFHQJsFPASpRi5ean/DD0tr98SB+HBD0/ErxE34opHgouYAeZa2RbADCSntNU8gPCwKGou5n2B8WFMwo4hLABqA4zS8yU39a18ooURcBXb9GTP1pXStFRckF9ChlyWQDEErOi5je2AZAsdT9dCr5NmAUbglgA1CWpS8vU39602TEqHmA1l8dpv70pkmxUXIBPcpXQdkAVC/hVUsJbANgcOp+BpFzGzCKtQSwASjIoheWqT+DW2L0qGeA5q8LU38Gt0QRUnIBPUpWUNkA1CfbNdqWknOndrYB0A9FP6VJtQ0YBVoC2ACUYp5Lysh/Odt/aOiziG/+kaRWARZ9RRj5U7L565OSb8ejTCWWDUAdUl2ULSo5aKIa1yiqfGiFup/qapXAN99RlCWADUARZlxMpv7LMfUf3OyBpfYA1n0tmPpTqdmlS8l351GaissGoFx5rsJ2lZwsCfl4ACxB3U8AUT8eMAqxBLABGN7kZWTqvxxT/2JNHWTqCmDyVWDqTzBTS5qSb9ajHAWYDUBZklx2rSs5ShizDYAZ1P0EFmwbMKp/CWADMLDxBWTqvxxT/+rsOeDUDJDZ+Po39SeJPUudku/dowT1mA3A8DJcZ10oOTtYl20AmPqTU4xtwKjyJYANwMBU/0sw9Q9D9UNmrn8yK7z+GZV9es1pAKiJ0p/ShL9JABAv/zUAZCn9NQ8AQIb6fl0aAEqn9KdwsW8SAMTLfx8CplzNq3Z1PwCQ85O+M9gAUCJTf+pS7xAIgIT5bwNAWUz9AYBCjIIuAWwAKIWpP1WrdAgEQML8twFgeKb+AECZRhGXADYADMnUn0hqHAIBkDD/bQAYhqk/AFCFUbglgA0AfTP1J7DqhkAAJMx/GwD6Y+oPANRoFGsJYANAH0z9yaOuIRAACfPfBoBumfoDAAGMAi0BbADoiqk/aVU0BAIgYf7bANA+U38AIJ5RlCWADQBtMvWHuoZAACTMfxsA2mHqDwCENwqxBLABoClTf6h3CARAwvy3AWB5pv4AQDaj+pcANgAsw9QfYgyBAEiY/zYALMbUHwBIblT5EsAGgHmZ+kO8IRAACfNfA8D6lP5QY74D0J1RzfmvAWAWpT8kv0kAEC//NQBMp/SH2vMdgE6Nqs1/DQCrKf2hdfXeJACIl/8aAH5M6Q+R8h2Aro3qzH8NAK0V7kp/iHeTACBe/msAsmur9Ff9k1yB+Q5AD0YV5r8GIC+lP/SsxpsEAPHyXwOQkdIfMuQ7AP0Y1Zb/GoBclP4wrOpuEgDEy38NQBZKf8iW7wD0ZlRV/msA4lP6Q1HqukkAEC//NQCRKf0hc74D0KdRPfmvAYhJ6Q8lq+gmAUC8/NcARKP0h8EVku8A9GxUSf5rAOJQ+kNFarlJABAv/zUAESj9oTQl5DsA/RvVkP8agLop/aFeVdwkAIiX/xqAWin9oXCD5zsAgxgVn/8agPoo/SGM8m8SAMTLfw1ATZT+UBf1PUBOo7LzXwNQB6U/RFX4TQKAePmvASid0h+qpr4HyGlUcP5rAMql9IckSr5JABAv/zUAJVL6QyTqe4CcRqXmvwagLEp/yKnYmwQA8fJfA1AKpT8Epr4HyGlUZP5rAIan9AeKvUkAEC//NQBDUvpDHup7gJxG5eW/BmAYSn+gipsEAPHyf3Of34yVqr2QL8KkK8/aMfQpENloNPLi7Y2XM1COUWH5bwPQH1N/YF2WAAA5jXrMfw1AH5T+wAr1PUBOo5LyXwPQLaU/UPVNAoB4+a8B6IrSH5hKfQ+Q06iY/NcAtE/pD4S5SQAQL/81AG1S+gPzUN8D5DQqI/81AO1Q+gMhbxIAxMt/DUBTSn9gCep7gJxGBeS/BmB5Sn8g/E0CgHj57zcBL8Nv841KvUXmXwxZnUFesPK/XhKecoyGzn8NwGJEP5DqJsGY/AfC5L8GYF6iH2id+r4K8h8Ilv8agPWJfmBAmoQByX8gZP5rAGYR/UDX1Pdlkv9A4PzXAEwn+oFyaBL6JP+B8PmvAVhN9AM9U98XQv4DSfJfA/Bjoh8oliahU/IfSJX/GoAfEP3AsNT3Q5H/QML8z94AiH6gFpqEdsl/IG3+520ARD9QFPV9b+Q/kDz/MzYAoh+olCahIfkPVKrd/M/VAIh+oGTq++7If6Bko37zP0sDIPqBGDQJi5L/QAyj9vI/fgMg+oGKqO9bJP+Biox6zP/IDYDoB0LSJKxL/gMhjVrK/5gNgOgH6qW+b0L+A/Ua9ZX/0RoA0Q9koEmYJP+BDEZt5H+cBkD0A2Go7xci/4EwRr3kf4QGQPQDCWkS5D+Q06hx/tfdAIh+ICr1/WzyH4hq1H3+19oAiH6AnE2C/AcYNcv/+hoA0Q8kkbO+n0H+A0mMOs7/mhoA0Q+Qs0mQ/wAt5n8dDYDoB3JKUt/PIP+BnEZd5n/pDYDoB8jZJMh/gI7yv9wGQPQDBK7vZ5D/ABu6zP8SGwDRD5CzSZD/AD3kf1kNgOgHCFzfzyD/AXrL/1IaANEPkLNJkP8APef/8A2A6AcIXN/PIP8BBsn/TRuGs/2HWvk6bZwOQN1Go9GGSsh/gAHzf5gNQFuRLfqBPGIsAeQ/wOD533cDIPoBcjYJ8h+gkPzvrwEQ/QCB6/sZ5D9AUfnfRwMg+gFyNgnyH6DA/O+2ARD9AIHr+xnkP0Cx+d9VAyD6AXI2CfIfoPD8b78BEP0AOZcA8h+givxvswEQ/QA5mwT5D1BR/rfTAIh+gJxLAPkPUF3+N20ARD9AziZB/gNUmv/LNwCiHyDnEkD+A1Sd/8s0AKIfIGeTIP8BAuT/Yg2A6AfIuQSQ/wBh8n/eBkD0A+RsEuQ/QLD8X78BEP0AOZcA8h8gZP5v6iG1t/9Q868DwBJGo9ES/0r+A0TN/3UagIZEP0CZ9X3X5D9AsfnfVQMg+gFyNgnyH6Dw/G+/ARD9ADmXAPIfoIr8b7MBEP0AOZsE+Q9QUf630wCIfoCcSwD5D1Bd/jdtAEQ/QM4mQf4DVJr/i/0m4D3JfeJxVcM8vFKIx1VNKstsAEx9AHIuAeQ/QID8X2wDIPcBcpL/AOk2AKY+ADmXAPIfIFj+r78BkPsAOcl/gHQbAFMfgJxLAPkPEDj/p28A5D5ATvIfILzVDYDoB8i5BJD/ABmMRqMfNwCiHyAn+Q+Qysbdu3cPfQ4AAEDBvwgMAAColAYAAAAS0QAAAEAiGgAAAEhEAwAAAIloAAAAIBENAAAAJKIBAACARDQAAACQiAYAAAAS0QAAAEAiGgAAAEhEAwAAAIloAAAAIBENAAAAJKIBAACARDQAAACQiAYAAAAS0QAAAEAiGgAAAEhEAwAAAIloAAAAIBENAAAAJKIBAACARDQAAACQiAYAAAAS0QAAAEAiGgAAAEhEAwAAAIloAAAAIJHNQ58A9GfXrl0XX3zxRz7ykc9+9rNXXHHFVVdddeONN+7cufOOO+7YsmXL/vvvf8QRRxx11FHHH3/8Ax7wgFNOOeWYY44Z+pQBAFq2cffu3W1/TSjLrl273vGOd7z+9a+/4IILbrnllvn/4b3vfe8nPelJT3va0+5973t3eYIALOxNb3rTQn9/48aNmzZt2muvvfbdd98tW7YceOCBd7nLXQ4//PAtW7Z0do5QKA0Akd10002vetWrXv7yl1933XVNvs4ZZ5zx4he/+IEPfGB7pwZAIxs3bmzl6xx99NEnnHDCgx70oIc//OEPe9jDDjjggFa+LJRMA0BYb3rTm37rt37rm9/8ZitfbdOmTc9+9rNf9rKXuTcARGoA9rTvvvs+6lGPespTnvLEJz5x7733bv3rQyE0AAT07W9/++lPf/rb3va21r/yfe5zn7e97W33uc99Wv/KAAzeAIwdddRRz33uc3/jN37DG4QISQNANJ/5zGfOOOOMK6+8csbf+cmf/MkHP/jBxx9//F3vetc73/nON99883e+850dO3ZcdtllH/vYx3bs2DHj3x500EHve9/7TjrppA7OHYAiGoAVd7vb3f7gD/7g7LPP7vobQc80AITy0Y9+9NGPfvQNN9ww9U+PPvroX/u1X3vKU55yj3vcY62vsHv37ssuu+z//t//+/rXv/7GG2+c+ncOOuigCy+88EEPelB7Jw5AcQ3AitFo9OpXv/qQQw7p59tBDzQAxPH3f//3p5566tTq/8ADD3zhC1/4m7/5m/O/p/P6669/0Yte9IpXvGLqa+Too4/++Mc/fsQRRzQ+awBaawBmVzXf//73b7/99ptuuunGG2+87rrrvvzlL//jP/7jJz7xib/5m79Za3K04p73vOe73vWu4447ro0Th+FpAAjii1/84k//9E9/5zvfmfyjn/7pn962bdtyP9T/ggsueOpTnzr1k8SnnXbaX//1Xy91sgAM0ACs5dZbb/3ABz7wp3/6p+94xzvuuOOOqX9n69at73nPe7z/kxg0AERw0003nXzyyZ/+9Kcn/+jxj3/8tm3b9tlnn6W/+OWXX/7whz98amvxmte85hnPeMbSXxmAEhqAscsuu+w//sf/uNZw5+CDD77wwgv9SGgC0AAQwdOf/vQ///M/nzx+xhlnnHfeeZs3N/2N15/4xCf+1b/6V7t27Vp1/PDDD7/iiiv233//hl8fgBIagBV/+qd/+tznPvfWW2+d/KMjjjjik5/8pPd/UrtNQ58ANHXBBRdMrf4f8IAHnHPOOc2r/5U3Eb3whS+cPH7NNde8+tWvbv71ASjHs571rA984AMHHXTQ5B994xvfOOuss26//fYhzgtaYwNA3Xbt2nX88cd/6UtfWnV8v/32+9SnPnXve9+7rW902223PfjBD77ssstWHb/nPe/5hS98YdMmvTRAkA3Aio997GM///M/f9NNN03+0R/+4R8+73nPa+sbQf9ULdTt1a9+9WT1v2HDhpe+9KUtVv8bNmzYe++9X/SiF00e/+IXv/jRj360xW8EQAke+tCHvva1r536Ry960Yuuuuqq3s8IWqMBoGI333zz7//+708eP+64457znOe0/u2e8IQnHH300ZPH3/rWt7b+vQAY3Nlnn/2v//W/njx+4403Tr37QC00AFTsr/7qr6655prJ4//tv/23vfbaq/Vvt9deez3rWc+aPH7RRRe1/r0AKMF//+//fcuWLZPHX/va1069AUEVNABU7DWvec3kwWOPPfYJT3hCR9/xcY973OTBSy+9dOfOnR19RwAGdLe73e0//af/NHn8lltued3rXjfEGUELNADU6vLLL//EJz4xefzZz352dx/JfcADHnDooYeuOnj77bd/7nOf6+g7AjCsf//v//2+++47efwNb3jDEKcDLdAAUKu3ve1tkwc3btx49tlnd/dNN27ceOqpp04e/8IXvtDdNwVgQAcddNDU9e8//dAQZwRNtfAj0mEQ7373uycPnnzyyUceeWSn3/fss8+e/DFzd77znTv9pgAM6Jd+6ZfOO++8yeMXXHDB8ccfP8QZQSN+DwBVuvHGGw8++ODJX8Xywhe+8Hd/93cHOikA4vwegD3deuutW7dunfydAE984hPPP//8Lr4jdMpbgKjSJZdcMvUXMT784Q8f4nQAiGyfffa53/3uN3n8U5/61BCnA01pAKjSP/zDP0w9fuKJJ/Z+LgDEN/X+8uUvf/l73/veEKcDjWgAqNJnPvOZyYOHH374Xe5ylyFOB4CMDcDu3buvvPLKIU4HGtEAUKWvfe1rkwfvec97DnEuAMR3wgknTD3+9a9/vfdzgaY0AMRpAI444oghzgWA+A4++OCpx7/xjW/0fi7QlAaAKn3rW9+aPDj5K7oAoBUHHnjg1OM33HBD7+cCTWkAqNLkz2LbsGHDli1bhjgXAOI76KCDph6/+eabez8XaEoDQJVuueWWyYN3utOdhjgXAOJbawOwa9eu3s8FmtIAUKXvf//7kwf9VjsAOjL1l89s2LBh77337v1coCkNAFXad99951wLAEBza036LZ+pkQaAKk19u//UDwYAQHNr/cKv/fbbr/dzgaY0AFTpzne+8+TB6667bohzASC+b37zm1OPH3744b2fCzSlAaBKRx555OTBa665ZohzASC+tX7e/1FHHdX7uUBTGgCqNDVwv/jFLw5xLgDE9/nPf37q8bvf/e69nws0pQGgSve4xz0mD37zm9/8zne+M8TpABDcZz/72cmDhx56qLcAUSMNAFW6//3vP/X4pz/96d7PBYD4Lr744smDD3jAA4Y4F2hKA0CV1srcD3/4w72fCwDBXX/99Zdffvnk8ZNPPnmI04GmNjf+CjCAE0444aCDDrr++utXHb/ooov+63/9r51+63/37/7dqp83us8++7zhDW/o9JsCMKD3vOc9U38R2GmnnTbE6UBTG/3yVCp15plnvvWtb111cK+99rrmmmvuete7dvRNr7zyynvd616rDh5zzDFf+tKXOvqOAEy1cePGyYMdVTWj0egtb3nLqoMHH3zwtdde6zcBUyNvAaJWj3rUoyYP3n777eedd1533/T973//5MHJlgCAMK699tq3ve1tk8ef/OQnq/6plAaAWp155plTk/dP/uRPuvumF1xwweTB+93vft19RwCG9cpXvvK2226bPP4rv/IrQ5wOtEADQK3uete7PvrRj548/ulPf/qiiy7q4jvefPPNH/jAByaPn3LKKV18OwAG9+1vf/uP//iPJ4+fdNJJD33oQ4c4I2iBBoCKPetZz5p6/L/8l//Sxbc755xzvvvd7646uPfeez/iEY/o4tsBMLjnP//5N9xww+Tx//yf//MQpwPt0ABQscc85jEnnnji5PGPfexjb37zm1v/dq961asmD5566qmHHHJI698LgMG9613v+ou/+IvJ46eccsrpp58+xBlBOzQA1O13fud3ph7/jd/4jW9961stfqO3vOUtl1xyyeTxX/3VX23xuwBQiCuuuOKXf/mXJ4/vtdder3rVq6b+DCKohQaAuv3iL/7i1HfgXHfddb/8y798xx13tPJdvvvd7z73uc+dPH7sscc+/vGPb+VbAFCOq6666rTTTtuxY8fkH73gBS/wC4CpnQaA6r3yla+c+uOA3vve9z7/+c9v/vV3797967/+69/4xjcm/+hlL3vZXnvt1fxbAFCOyy677OSTT/7yl788+Uc/+7M/++IXv3iIk4I2aQCo3gknnPCyl71s6h/9z//5P1/wghc0/PrPec5z3vSmN00e//mf//nRaNTwiwNQjt27d7/61a9+yEMe8rWvfW3yT4899tht27aZ+xCA3wRMBLt37z7jjDPe+c53Tv3Ts88++8/+7M/233//Rb/szp07f/M3f/O1r33t5B9t3br10ksvPfroo5c6XwCK+03AF1544Qte8IKPf/zjU//0sMMO+8hHPnLssccu/fWhHBoAgrjhhht+7ud+burndFfGNn/0R3/0uMc9bv4v+KEPfejpT3/6FVdcMflHmzdvfu9733vqqac2OF8AimgAPve5z7397W//y7/8y8suu2ytv3PMMce8//3v93vfCUMDQBzXXnvtwx72sC984Qtr/YWTTjrpuc997umnn37nO995rb9zww03vPOd73zFK17xd3/3d1P/wqZNm173utdN/dEQAAzbAJx77rkz/sntt99+66237ty5c8eOHddcc80VV1zxD//wD+v+yLiHPvSh55133hFHHNH4lKEUGgBCufbaa88444y1avcV++yzz0Me8pD73e9+97rXvQ466KC99957xw99/etfv/jiiy+77LIZPzto7733ft3rXveUpzylm9MHYF49/CDOTZs2Pe95z3vpS1869UdNQL00AERz8803/9qv/dob3vCG1r/yYYcddt55551yyimtf2UASmsAfuZnfub//J//8+AHP7jT7wKD8FOAiGbLli2vf/3r3/rWtx5++OEtftlf+qVfuvzyy1X/AOGdfPLJb3/72//u7/5O9U9UNgCEtXPnzle+8pUvf/nLv/3tbzf5Oo985CNf8pKXPOQhD2nv1AAobgNwwgknPP7xj3/qU596wgkntPuVoTQaAIK7+eab3/rWt77+9a+/6KKLbrvttvn/4U/+5E8+8YlPfNrTnnaf+9ynyxMEoKcGYNOmTZs3b77Tne60//77H3zwwYceeujd7na344477r73ve/JJ5982GGHdXOmUBwNAFns3Lnzox/96Ec+8pHPfe5zV1xxxTe+8Y0bb7xx586du3fv3rJly/7773/EEUccffTRxx133IknnnjKKaccc8wxQ58yAED7NAAAAJCIDwEDAEAiGgAAAEhEAwAAAIloAAAAIBENAAAAJKIBAACARDQAAACQiAYAAAAS0QAAAEAiGgAAAEhk42g0GvocoBTbt28f+hSgP/IfxuQ/qWxyxQNkM/oh+Q+QM/83D30aAPTH1B8gpz3z/wefATAEAkgy9Vl1UP4DJMx/GwCA4Ez9AXIarZH/P/opQIZAAEmm/qvIf4Bs+W8DABCQqT9ATqM58v/HvwfAEAggydR/FfkPkCr/bQAAgjD1B8hptGD+/7PfBGwIBJBk6r+K/AfIk/8LbwBMmKiaKodg+sxk+U/V5D/BjBpk8qZFXx5ePwAxpv6ryH+AJPnvMwAAlTGJB8hp1FL+r94AGAIB5Jn6ryL/ATLkvw0AQAVM/QFyGnWQ/1M2AIZAAHmm/qvIf4Dw+T+9AQAgQPTbGwDUaNRx/q/ZABgCAVQd/Ut/BfkPEDv/fQYAoCDNZ/am/gA1GvWY/7PeAmQIBJBk6r+K/AcInP82AAADM/UHyGk0UP6v8yFgQyCAJFP/VeQ/QNT8twEAGICpP0BOowLyf/0fA2oIBJBk6r+K/AcImf82AACJpj4A9K+0/J/rF4EZAgHEmPosSv4DxMt/GwCARFMfAPpRcv7PtQEwBAKIMfVZgvwHCJb/NgAAiaY+AHSnlvyfdwNgCAQQYOqzHPkPECn/bQAAEk19AGhXjfm/wAbAEAig9qnP0uQ/QJj8twEASDT1AaC52vN/sQ2AIRBA1VOfJuQ/wChE/tsAACSa+gCwnEj5v/AGwBAIyCnG1Kch+Q8kNAqX/zYAAImmPgDML2r+L7MBMAQCkog39WlO/gMZjELnvw0AQKKpDwCzZcj/JTcAhkBAVLGnPq2Q/0BIozT5bwMAkGjqA8CkbPm//AbAEAgII8/Upy3yH4hhlDL/bQCA1LJNfQBYkTn/G20ADIGAeuWc+rRI/gOVGqXPfxsAIJ3MUx+AzOR/OxsAQyCgIqY+7ZL/QC3k/55sAIAUTH0AcpL/nWwADIGAkpn6dEr+A8WS/2uxAQDCMvUByEn+97EBMAQCimLq0yf5D5RD/s/DBgAIxdQHICf5P8AGwBAIGJapz4DkPzAg+b8oGwCgeqY+ADnJ/+E3AIZAQM9Mfcoh/4E+yf8mbACAKpn6AOQk/4vbABgCAV0z9SmW/Ac6Jf/bYgMAVMPUByAn+V/6BsAQCGidqU8t5D/QLvnfBRsAoGimPgA5yf/KNgCGQEBzpj6Vkv9AQ/K/azYAQHFMfQBykv91bwAMgYAlmPrEIP+BRcn/PtkAAEUw9QHISf6H2gAYAgHzMPUJSf4D65L/Q6l+A7B9+3ZPPFSq9qmP/IEwvJYrNeAoYVTzNbMpwBBo+w81/CJAn2qf+oideVgCAJSp+g3AaDRauYWs/P9Vd2MQXiuv0MGn/oWcCQAUugHoeQhkLAdlamVgb+pfHUsAgAJVvwHYcwkwZhsA5Qg29R+TMABUalPgIZBxHQzL1B9LAIACRdgATF0CjNkGQP+iTv3HRAoA9dqUZAhkjAf9MPVnkiUAQFGCbABmLwHGbAOgO+Gn/mMyBICqbUo4BDLeg3aZ+lNL/gMQagMw5xJgzDYAmqt96r9E0Sk0IKRjt20d+hQozpVn7dgQ1KbkQyBjP8g59ffa719p+Q+QVqgNwKJLgDHbAJhfwqn/mJQAIIABGoDt27fPvomu+xe6Lgvc42GqVkb+G4ZjwDy4YvMfIJVoG4CllwB7shCAVZT+g/8nAECtnwGo6J2g3iIMrbxN34/3obr8B4gt4AZg9hJg65nbdpx/1vxfyjaAtLJN/WeHgxAAIIxN2YZAO84/a+uZ27aeuW2hf2WISCrZpv4rmbDQaIAmLAEAhhVzAzDPJwFWegDbAEg+9Z/nr3nVAxDJYBuAYZcA4//bNgAyT/3H/9P4v2eWAAADCrsBWOjHAdkGkJmp/2xe5gAEM+QGoJAlwJhtANkkn/qPGf8PwhIAYCiRNwDL/U4A2wAyMPWfk9c1APEMvAEobQkwZhtAVKb+qxj/D8gSAGAQwTcADX8xsG0AkZj6L8oLGYCQht8AFLsEGLMNoHam/msx/h+cJQBA/+JvABouAcZsA6iRqf/SvHIBiKqIDUD5S4Ax2wBqYeq/LuP/QlgCAPQsxQagrSXAmG0AJTP1b85LFYDAStkAVLQEGLMNoDRVT/1XXh1dT/3HjP+LYgkA0KcsG4DWlwBjtgGUoOqp/xIvzC6m/mNemwDEVtAGoMYlwJhtAEMJMPVf6J80mfqPGf8XyBIAoDeJNgDdLQHGbAPok6l/F7wYAQivrA1A1UuAMdsAumbq34Txf7EsAQD6kWsD0MMSYMw2gC6Y+nfKqw+ADIrbAMRYAozZBtAWU/9WGP8XzhIAoAfpNgB9LgHGbANowtS/H15uACRR4gYg2BKg+TbAxCstU/92Gf9XwRIAoGsZNwCDLAHGtp65bYkqxEIgm2xT/wEH/yu8uADIo9ANQNQlQMMxp21ABtmm/j0M/lcY/1fEEgCgU0k3AMMuAZb+YMAK24CoTP2H4tUEQCrlbgBiLwHGbAMw9e+B8X91LAEAupN3A1DCEmDMNiAtU//BefkAkE3RG4AkS4Ax24BUTP17Y/xfKUsAgI6k3gAUtQQYsw0Iz9S/HF4vACRU+gYg2xJgzDYgJFP//hn/V80SAKAL2TcAZS4BxmwDwjD1L5AXCAA5VbABSLsEGLMNqJqp/4AKeQnThCUAQOtsAEpfAozZBlTH1L9kXhEApFXHBsASYMw2oAr1Tv1XrpOqp/7FvnhZmiUAQLtsAKpkG1Cseqf+S5dQpdX9AECQDUDXQ6AZVVexc0TbgKLUPvVf4h8WOPWf82WrB66OJQBAi2wAqmcbMDhTfwCgIjVtACwBZrANGISpf5mM/0OyBABoiw1AKLYBvTH1BwAqVdkGwBJgHrYBnTL1L5zxf2CWAACtsAEIyzagdab+AEAA9W0ALAEWYhvQClP/Whj/h2cJANCcDUAKtgFLM/UHAIKpcgNgCbAc24CFmPpXx/g/CUsAgIZsANKxDViXqT8AENjGDTVbt8xqUofNqKXCVEtNFhqVdgJdjwaV/kMx/l/i2qh6Ut5p/hPS7Av+2G1bezwX6nDlWTuqDpkZ17wNQGpLbwNSLQTmpPQHAKpQ62cAVvgkQCuavPM758cDVvFe/8EZ/yfkkwAAS7MB4EdsA5Zg6g8sbfv27QljE1ZcedYOb7saUN0bAEuA1tkGzMnUvxzG/2kFWAKkik1YceVZO2a/t54e2AAwhW3ADKb+QCtGo9HK6zp8bMKKPet+4/9hVb8BsATojm3AKqb+BTL+Ty7AEiB2bMIKU//S2ACwDtuAof4TmpQC4et+CLYEiBebsGJq3W/8P7gIGwBLgB6k3QYMMvVv8ohlmPqPGf8TbAkQIzZhhal/yWwAWECqbYCpPzDIEqDe2IQVs+t+4/8SBNkAWAL0Kfw2wNS/Csb/xF4C1BWbMB75m/pXwQaAJYXcBpj6A0UtAcqPTVh35L8n4/9CxNkAWAIMIvw2oFOm/ksz/ifVEmBVaMT4byEGI/9K2QDQgpDbgE6Z+gOLLgH2lDM5KcoSdb/xfzlCbQAsAYZlGzAPU//mjP/JvATImZwUxdQ/ABsAWmYbsBZTf6DFJUCS5KQoTep+4/+iRNsAWAIUwjZgT6b+LTL+Z4aES4DAyUlRTP2DsQGgQ7YBpv5AD0uAYMlJUVqp+43/SxNwA2AJUJqc2wBT/y4Y/7OuzEuAAMlJUUz9A4vZAFCgPG2A0h9Y2ow+dtFwqCs5qbr0n31xGv8XKGwDYAlQpibVbfk3s4ZnqPSfzfif5EuAHeeftcSMoPzkpPbSf+uZ2xQ/1fEZAGr6YECx73BteH9V+gPzfxJgiRQtMzkpyqLv9pnzzmX8X6awGwBLgMI1fK9LOTOt5lN/1f88jP9ZSOAlwPj/tg1g2Kn/+H8qe2pkA8CQqt4GmPoDg/84INsAlrbEB3wXvXMZ/xcr8gbAEiDVNqDPsZapf8+M/1lChiXAmG0AXf94n7WuMQVPpWwACLIN6GesZeoPFPs7AWwDKGHqP2b8X7LgGwBLgOo0n453MdZqvmQw9V+a8T9LS7UEGLMNoOup/5hSp142AJSonG1A85uiuh/o/xcD2wYwyNR/zPi/cPE3AJYA9Rp2G9B8JGbq35zxPw3lXAI03wZU+rDQw9R/TJFTNRsAStf/NsDUHwiwBGiYohYCVRtk6j9m/F++jRvSWDfFmsTcjIBWC7ao/HmDp7tFxv+tmJFOeaa8neZ/19q9vyyXoiU/PvObfcGHqVn7Kf1nX0hJHsxR8a+LGde8DQC5tgHdUfoDxS4BxmwDAht26h+v+o8txWcAVvgkQBilvbe+tPOJwfifFiX/JEBbqeWzATnf6z9JYRNAogaAYEoou0s4ByC8jjre5eJLG1B76d/pytr4vxa5GgBLgHiGKsGV/p0y/qd1lgDtRpk2oN7Sv+HNS0kTg88AEEGfnw1Q9wO1fxKgrQj12YBBLFH393PzMv6vSK4NgCVAbF1P5U39+2H8T0csAWazDahi5D/I1H9MMROGDQDRdLENUPcDSdgGhBn5u3kxQ7oNwIBDIH1zn9oaeJj698zLhE5VvQToc8lsG1CI5Ub+Hd28kvzs/yRsAGp6myZ9bgPU/QUyXIQ+2QYMyNSfTmXcAFgCZLPoIMTUfyheIPTAEmBRtgGZp/5jxv/B2AD0vQTYcf5ZistiR1memgGtW76YJsKAbAN6YOpPb5JuAGofAgGQM/+H/XFztgGppv5jxv/x5G0AOjV71OF9DrCK8T9URBuQp/QnqtQNQNVDIABy5n8hv3OmYRtQ8iPcj1pKf+P/kFI3AJ2yBIA5Gf9DvZoUo2nbgFpKfwLL3gBUPQQCIGf+F7IEGNMGRC39jf+jyt4AdMoSANZl/A9haAMilf7EpgGoewgEQM78L20JMKYNmKz7Ky39jf8D0wB0yxIAZjD+h6i0AUvX/SWU/oSnAah+CARAzvwvdgmQvA2IUfob/8emAeicJQBMZfwPSeRpA2KU/mSgAYgwBAIgZ/6XvwRI0gYEK/2N/8PTAPTBEgBWMf6HnOK1AcFKf5LQAAQZAgGQM/8rWgIEawOilv7G/xloAHpiCQBjxv9A1W1A1NKfPDQAcYZAAOTM/xqXAJW2AeFLf+P/JDQA/bEEAON/oNI2IHzpTyoagFBDIABy5n/VS4DC24A8pb/xfx4agF5ZApCc8T9QURuQp/QnGw1AtCEQADnzP8YSYKxJ9bzSBjR5spqU/g1PfijG/6lsHvoE0hmNRjMiacf5Z9WYGjAP439gISs3xCbdy8oNd/5saVL0r3ATpwo2AAGHQADkzP9gS4C23kszzzag4ci/9vf8GP9nowEYgE8CkJDxPxC1vC753GAqDUDMIRAAOfM/5BKg2FK7tPNZjvF/QhqAYVgCkIrxPxCs7C7hHGBpGoCwQyAAcuZ/7CXA4CV4sNLf+D8nDcBgLAFIwvgfiFGOByv9yUwDEHkIBEDO/E+yBOitNI9a+hv/p6UBGJIlAOEZ/wO96aJMj1r6k5wGIPgQCIClRc3/2AOmtkr28KV/7MuA2TQAA7MEIDDjfxhQ8tdXk/I9fOk/D+//iU0DkHoIBEDO/E8yYFq0lM9T+ie5AFiLBmB4lgCEZPwPg3N/mb+sz1P6z/PUG/+HpwHIPgQCYDb5DwSjASiCIQ3BGP9DIdxfWMX4Hw3AYgyBAHKS/0AkGoBSGNIQhvE/FMX9hTHjf1ZoABZjCASQk/wHwtAAFMSQhgCM/6FA7i8Y/7MnDcDCDIEAcpL/QAwagLIY0lA1438olvtLcsb/7EkDsAxDIICc5D8QgAagOIY0VMr4Hwrn/pKW8T+raACWZAgEkJP8B2qnASiRIQ3VMf6HKri/JGT8zyQNwPIMgQBykv9A1TQAVTKkoSguSKiIJUAqxv9MpQEodAjk/RJE4nomHksAoF4agFoZ0lAIlyJUxxIgCeN/1qIBaMoSAGZzJROVJQBQKQ1AxQxpGJyLECplCRCe8T8zaABaYAkAa3ENE5slAFAjDUDdDGkYkMsPqmYJEJjxP7NpANphCQCTXL1kYAkAVEcDUD1DGgbhwoMALAFCMv5nXRqA1lgCwJ5ct+RhCQDURQMQgSENPXPJQRiWAMEY/zMPDUCbLAFghSuWbCwBgIpoAIIwpKE3LjYIxhIgDON/5qQBaJklALhWyckSAKiFBiAOQxp64DKDkCwBAjD+Z34agPZZApCZq5TMLAGAKmgAQjGkoVMuMEjLy79wniAWogHohCUAObk+od4lgNdvbN7/w540ANGYAdARlxYkJwSK5alhURqArlgCkI0rE1ZYAlAa439W0QAEZBJA61xUgCgokyeFJWgAOmQJQB6uSdiTJQDlMP5nkgYgJvMAWuRyAsYEQlE8HSxHA9AtSwAycDXCJEsASmD8z1QagLBMBWiFCwlYRSwUwhPB0jQAnbMEIDbXIazFEoBhGf+zFg1AZGYDNOQSAqYSDoPzFNCEBqAPlgBE5QqE2SwBGIrxPzNoAIIzIWBpLh5gBhExIA8+DWkAemIJQDyuPZiHJQD9M/5nNg1AfOYELMFlA6xLUAzCw05zGoD+WAIQiasO5mcJQJ+M/1mXBiAF0wIW4oIB5iQueuYBpxUagF5ZAhCD6w0WZQlAP4z/mYcGIAszA+bkUgEWIjR646GmLRqAvlkCUDtXGizHEoCuGf8zJw1AIiYHrMtFAixBdPTAg0yLNAADsASgXq4xaMISgO4Y/zM/DUAu5gfM4PIAliZAOuXhpV0b9fQAAJCHDQAAACSiAQAAgEQ0AAAAkIgGAAAAEtEAAABAIhoAAABIRAMAAACJaAAAACARDQAAACSyefYf+z3B1dm+ffvsv7D1zG0bEpv929Q9OOv+neUyYd3Lct2/QBdmP5vyn2D3l6rzv7t87pr8L5MNQC6FBxxpL48y71vA/NxfOhX44ZX/g9AAhKKNpsxrTL5D7dxfylfmcyT/y6QBSCTw/IC2WAIAS3B/6UHgB1n+908DEEeZrT/xWAJANu4vtSjzmZL/BdIAZBF4ckC7LAGAhbi/9CbwQy3/e6YBCKLMpp+oLAEgD/eXupT5fMn/0mgAUgg8M6ALlgDAnNxfehb4AZf/fdIARFBmu09slgCQgftLjcp81uR/UTQA8QWeFtAdSwBgXe4vgwj8sMv/3mgAqldmo08GlgAQm/tLvcp87uR/OTQAwQWeE9A1SwBgBveXAQV+8OV/PzQAdSuzxScPSwCIyv2ldmU+g/K/EBqAyAJPCOiHJQAwlfvL4AI/BfK/BxqAipXZ3JONJQDE4/4SQ5nPo/wvgQYgrMCzAfpkCQCs4v5SiMBPhPzvmgagVmW29eRkCQCRuL9EUuazKf8HpwGIKfBUgP5ZAgBj7i9FCfx0yP9OaQCqVGZDT2aWAADMT/4PSwMQUOB5AEOxBIAkZjfz7i8FWvdJqXdoKP+7owGoT72vZGKzBABgfvJ/QBqAaIxn6IglAIRn/F8pSwAWpQGoTL2vYTKwBABgfvJ/KBqAUIxn6JQlAARm/F81SwAWogGoSb2vXvKwBABgfvJ/EBqAOIxn6IElAIRk/B+AJQDz0wBUo97XLdlYAgAwP/nfPw1AEMYz9MYSAIIx/g/DEoA5aQDqUO8rlpwsAQCYn/zvmQYgAuMZemYJAGEY/wdjCcA8NABAQeQ7QE7yv08agAoYz1CgAYdMbhLQFveXkCwBWJcGACiLfAfISf73RgNQOuMZimUJAFVzfwnMEoDZNABAceQ7QE7yvx8agKIZz1A4SwColPtLeJYAzKABAEok3wFykv890ACUy3iGKlgCQHXcX5KwBGAtGgCgUPIdICf53zUNQKGMZ6iIJQBUxP0lFUsAptIAAOWS7wA5yf9OaQBKZDxDdSwBoAruLwlZAjBJAwAUTb4D5CT/u6MBKI7xDJWyBIDCub+kZQnAKhoAoHTyHSAn+d8RDUBZjGeomiUAVMr9JbzAT7H8X4IGAKiAfIeG6n2PB8mvEPnfBQ1AQYz/CcASAKrj/pJE4Cda/i9KAwDUQb5DvOEuRSn2OpH/rdMAlML4nzAsAaAi7i+pBH665f9CNABANeQ7RBrrUqBirxb53y4NQBGM/wnGEgCq4P6SUOAnXf7PTwMA1ES+Q4yBLsUq9pqR/y3SAAzP+J+QLAGgcHnuLzvOP2vH+Wc1/zthBH7q5f+cNABAZeQ7zGlGmx24BGxS1udpA2ZfAJYA4WkABmb8T2CWAMBQmpTyedqAkOT/PDQAQH3kO6wr7fi/rfI9fBtgCZCZBmBIxv+EZwkA9KaLkj18GxCS/F+XBgCoknyHGbKN/7su06O2AZYAaWkABmP8TxKWAECM0jxqGxCS/J9NAwDUSr5D5vH/UOV4sDbAEiAnDcAwjP9JxRIACFaCl3AOzCb/Z9AAABWT75Bq/F9a2V3a+SzHEiAhDcAAjP9JyBIAiFpql3xuycn/tWgAgLrJd4g9/q+lvK7lPKeyBMhGA9A343/SsgQABimpRz/U/O+EbwNCkv9TaQCA6sl3iDf+7630n/z7zSOlxh7AEiAVDUCvjP9JzhIA6GGI3ryOb94GWAWUQ/5P0gAAEch3kosx/m+r9G/rfLK1AZYAeWgASlFRQEOll7qbBBSrtNI/cxsQkvxfRQPQn2JbZ4jxSpHvUON0qeTSP2EbUP4FM5X8X5QGoAiVvt5gOZYA0K5KB0y1lP4J24BgV9oK+b8nDUBPqn7NQM8sASD2dKnG0j9PG1DsZTOb/F+IBmB4lb7SoAlLAMg5YKq99M/TBsS43lYp5MopgQagD1W/WmAQlgAQbLoUqfQP3waUdvHMqcDLo1gagIFV+hqD5iwBIMmAKWrpH74NqPqqW0vhF1JvNACdq/p1AgOyBIDap0sZSv+obUAhl9CiKrpahqUBGFKlry5oiyUARB0wZSv9o7YBNV576xrVeV21SwPQrapfITA4SwCobrqUufQP1gZUOqYMcPH0QAMwmEpfV9AuSwAIM2BS+q/1X9TkP2rwNqCiK3B+o1iX2RI0AB2q+rUBhbAEgPKbaqX/uiptAyodVsa+llqhARhGpa8o6IIlANQ7YFL6Z2gDyr8OlzBKc9VNpQHoStWvCiiKJQAU2E4r/ZO0AZWOLHNeWvPTAAyg0tcSdMcSACoaMDUsQJu/LT6GutqAYq/GJkaJL0INQCeqfj1AgSwBoIRGupXSv9Uzql4VbUClg0sX2wwagL5V+ioKYJ6ULGSgkpMlAJQ8YFL6d6qKNiDk0HOU9bLUAPT6SlD9D2LRZNQGDGX2C8QSAGbo7v6i9O9NyW1ApQWMa28tGgAia5KG2oBU3CSoQs+jVqX/IEpuA9ZiCVAdDUDLjP8L0VYCagN6ZgkAS2j9/qL0H1yBbUClZYxLcSoNANF0kXragAzcJChcP0NWpX9RCmwD1mIJUBcNQJuM/4fVddJpA/phCQALaev+ovQvVjltQKXFjCtz0uYpx6A2fdblK9+r0hBkttFoVPUQi8A6vTKb/z6v9s6F9R/n5S6GHm5e27dvr/diGCXLfxuA1hj/D2KoqbxtQKcsAWBODe8vpv41avKwN795VVrSuFBX0QBQqxJK8BLOgXa5SVCgjgaTSv/MbcCGblQ9RB9luqQ1AO0w/s9cdpd2PjFYAsC6lr6/NEktpX9Rln46mlwDlRY2rts9aQCoScmldsnnxkLcJChKuyNVpX9Ig7QBa7EEqIIGoAXG/z2opbyu5TyrYAkAMyx6f1H6h9dnG1BpeeMyHvNTgChdW/X0yst+dtU4z9+Zh58UVLtsPw6C2Bq+17/Vc6FzS9/I3LlS5b8NQFPG/+VP0xcdirQ167INaM4SgOTWusjnvL+Y+qfVwzZgxkVYcgHtql5hA0D8qX+Tf2sbkFaSIRBRNan72z4XBmMbsJxRgvy3AWjE+D/M1L/rr2MbsDRLANJabvy/dNoY+UfV3TbAEqBeNgCUooSp/7pfs2GiJZ+pVCfDEIhITP2ZwTZgIaPo+W8DsDzj/6hT/66/hW3AoiwBSGih8b+pP0NtAywBKmUDwJDaqvvbOJeFv6NtQAbhh0DUztSfJdgGzCN2/tsALMn4v4Qp+LCzK9uAPlkCkMo8439TfxpauRKWuBhWXXuWADWyAaBvlU7912IbEF7sIRA1MvWnhBtZhjvXKG7+2wAsw/h/abVP/bveBrR0OjFZApDEjPG/qT/dabINsASojg0ANZX+G8rWfBuQYaBSo8BDICqydOnfwbkQVpNtQEijoPlvA7Aw4//+3+Ze1+yq+dn6YMBaLAEIr8VSo67kpCjtXjwlF9CjrK8RGwA6lGHqvxbbgGCiDoEIqd7kpCitfMgtgFHE/LcBaI1CLfPUfy22AbW80AJcbATQvMiIkZwUpZWLquQCepTyJaMBiHMFF0LpP0kbEOMVGuyyJJh4yUlRkl9go3D/7RqAdhj/K/3XpQ1oiyUAITX5EIurl340udhKHqGO8r2CNABBrt1hKf3npw3omiUAeeRJToqS88IbxfpP1gC0IPP4X+m/HG1AQ5YAJG9ccyYnRVniIix5kDpK9oLyU4AiXLWDqO4n/BT4DPpJQR3Zvn17d1dXyB8HQS2y1Sht8ZrtTqqfFDQKlP8agKYS1l5K/3ZpA5az8ltRW/+ykfKdWsxzySn9l+PlXNqNrNMBTUOjTPmvAZhLngtiNqV/d7QB7bIEIIxiq6XCeZEOeK0GfvBHUfJfA9BInmJL6d8PbcBCLAEIYMbFpvRfjtdv4fcyS4ASaADWl+RSWIvSv3/agFZYAlCvYsujwnlVFiXqxwNGIfJfA7C88NWV0r/2XWqGNsASgKpNXmZK/+V4wdbVBlgCDE4DsI4MF8EkpX+kIUqGNmAtlgBUpNh6qHBehlUItg0Y1Z//GoAlRS2nlP7F0gasxRKASo0vMKX/crxCq76RWQIMSwMwS/inf09K/ypoAxZlCUDJii2ACud1V7UY24BR5fmvAVhGsPpJ6V8dbcAqlgDUSPW/BC/JMAq//kfR818DsKbYT/wKpX/VtAFzsgSAALzQKM2o5vzXACwsRsGUsPRf+QqFjxyWoA1YYQkAUcl/BjEKnf8agOkCP+UNi6T+A7St6I9NGzCbJQDUSP5TuFG1+a8BWEzVFZLSP7zkbYAlAIQh/ynBKG7+awCmiPdkK/1TSd4GrMUSAKog/6nLqM781wAsoMaSSOmfVs42wBIA6iX/KdAoaP5rAFYL8zQr/UnbBqzFEgDKJP+p2qjC/NcAzKuiGkjpT+Y2wBIAKiL/Kd8oYv5rAP6Z2p9gpT8zpGoD1mIJAIWQ/0Qyqi3/NQBzKb/oUfozpwxtgCUAlEz+U51RuPzXAPxYpU+t0p8lZGgD1mIJAEOR/wRWV/5rANZXbJWj9KehwG2AJQAURf5Tu1Gs/NcA/EhdT6rSnxYFbgPWYgkAvZH/5DGqJ/81AOsoraxR+tOReG2AJQAMS/4TzChQ/msAfqCKp1PpTw/G18lyD36BbcBaLAGgO/KftEaV5L8GYJZC6hilP3UtBMppAywBoGfyn9hGUfJfA1B01ij9GVaMNmAtlgDQIvkPFeW/BmBNwxYuSn/KUXUbYAkAXZP/pDIKkf/ZG4ACn0KlP2Wqug1YiyUANCH/odL8z94ArGWQSkXpT/lqbAMsAaB18p/MRvXnf+oGoJwnT+lPXWpsA9ZiCQALkf8QIP9TNwBr6bM0UfpTr4raAEsAaE7+Q5j8z9sADP60Kf2JoaI2YC2WADCb/Idg+Z+3AVhLD7WI0p94ym8DLAFgCfIfQua/BqBvTUoQpT+x24DBVwEdqfomQVryHwLnf9IGYK0no9P6Q+lPEku3AV2vAmYsAZq8C6jYfIflyH8In/9JG4CeLV3691/3i37CtwGDqPcmQSryH5Lkf8YGoM/xv9Kf5EprAywBYCr5D6nyP2MD0I9spb/0p6I2YBCV3iQIT/5DwvxP1wD0MP5X+kPJbYAlAKyQ/9CKGvM/XQPQKaU/1NIGDKLGmwQhyX9Inv+5GoDuxv9Kf6ioDbAEIC35D12oLv9zNQBdUPrD0hJuA6q7SRCG/IdhjUrK/0QNQOvjf6U/1NsGWAKQh/yHHoyqyv9EDUCLlP7QuvGrY9GLrbptQF03Caom/6Eoo2LyP0sD0Nb4X+kPZS4ElmgDLAEITP5D/0b15H+WBqA5pT+EbAMGUdFNgurIfyjZqIz8T9EANBz/K/0hahtgCUAk8h8GN6ok/1M0AEtT+kMJQm4DarlJUAX5DxUZFZD/8RuA5cb/Sn9I0gZYAlA1+Q+lGdWQ//EbgEUp/aFkkbYBVdwkKJb8h3qNhs7/4A3AQuN/pT/kbAMsAaiL/IfCjYrP/+ANwJyU/lCjANuA8m8SFEX+QxijQfN/c/Lxv9IfatdKG2AJQOHkP9RlVHb+R24AZlP6QyT1bgMKv0kwOPkPUY2Gy//NCcf/Sn+IqmEbYAlAUeQ/VG1UcP6HbQDWslz1r/SHJG3AIEq+STAI+Q9JjAbK/5gNQIsPpdIfUrUBa7EEoB/yHyIZlZr/MRuAVij9IYB224CENwl6I/8hp9EQ+R+wAWj+ICr9IZhW2gBLADoi/yGwUZH5H7ABqKvuF/3Qm8K3AWXeJOiU/Ac2DJH/0RqA5R4+pT/k0aQNsASgLfIf8hiVl//RGoBFKf0hpzK3AQXeJGid/AcGz/9QDcBCD5zSHxjnwPyvKUsAlib/Ia1RYfkfqgGYk9IfKHYhUNpNglbIf6Co/I/TAMzzkCn9geZtgCUA85P/QIH5H6cBmE3pD9SyDSjqJsHS5D9QbP4HaQBmPFhKf6D1NsASgBnkP1B4/gdpAKZS+gOVbgPKuUmwEPkPVJH/ERqAyYdJ6Q903QZYArAn+Q9UlP8RGoA9Kf2BGNuAQm4SrEv+A9Xlf/UNwPgBUvoDPbcBlgDJyX+g0vyvvgFQ+gNRtwEl3CSYSv4DVed/9Q3AINW/6Aea54/6vkbyH2hu8PyvvgHomegHUt0kGJP/QJj81wDMS/QDrVPfV0H+A8HyXwOwPtEPDEiTMCD5D4TMfw3ALKIf6Jr6vkzyHwic/xqA6UQ/UA5NQp/kPxA+/zUAq4l+oGfq+0LIfyBJ/msAfkz0A8XSJHRK/gOp8l8D8AOiHxiW+n4o8h9ImP/ZGwDRD9RCk9Au+Q+kzf+8DYDoB4qivu+N/AeS53/GBkD0A5XSJDQk/4FKtZv/uRoA0Q+UTH3fHfkPlGzUb/5naQBEPxCDJmFR8h+IYdRe/sdvAEQ/UBH1fYvkP1CRUY/5H7kBEP1ASJqEdcl/IKRRS/kfswEQ/UC91PdNyH+gXqO+8j9aAyD6gQw0CZPkP5DBqI38j9MAiH4gDPX9QuQ/EMaol/yP0ACIfiAhTYL8B3IaNc7/uhsA0Q9Epb6fTf4DUY26z/9aGwDRD5CzSZD/AKNm+V9fAyD6gSRy1vczyH8giVHH+V9TAyD6AXI2CfIfoMX8r6MBEP1ATknq+xnkP5DTqMv8L70BEP0AOZsE+Q/QUf6X2wCIfoDA9f0M8h9gQ5f5X2IDIPoBcjYJ8h+gh/wvqwEQ/QCB6/sZ5D9Ab/lfSgMg+gFyNgnyH6Dn/B++ARD9AIHr+xnkP8Ag+b9pw3C2/1ArX6eN0wGo22g02lAJ+Q8wYP4PswFoK7JFP5BHjCWA/AcYPP/7bgBEP0DOJkH+AxSS//01AKIfIHB9P4P8Bygq//toAEQ/QM4mQf4DFJj/3TYAoh8gcH0/g/wHKDb/u2oARD9AziZB/gMUnv/tNwCiHyDnEkD+A1SR/202AKIfIGeTIP8BKsr/dhoA0Q+Qcwkg/wGqy/+mDYDoB8jZJMh/gErzf/kGQPQD5FwCyH+AqvN/mQZA9APkbBLkP0CA/F+sARD9ADmXAPIfIEz+z9sAiH6AnE2C/AcIlv/rNwCiHyDnEkD+A4TM/009pPb2H2r+dQBYwmg0WuJfyX+AqPm/TgPQkOgHKLO+75r8Byg2/7tqAEQ/QM4mQf4DFJ7/7TcAoh8g5xJA/gNUkf9tNgCiHyBnkyD/ASrK/3YaANEPkHMJIP8Bqsv/pg2A6AfI2STIf4BK83+x3wS8J7lPPK5qmIdXCvG4qkllmQ2AqQ9AziWA/AcIkP+LbQDkPkBO8h8g3QbA1Acg5xJA/gMEy//1NwByHyAn+Q+QbgNg6gOQcwkg/wEC5//0DYDcB8hJ/gOEt7oBEP0AOZcA8h8gg9Fo9OMGQPQD5CT/ATZk8v8BScp5/S129k4AAAAASUVORK5CYII="
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_222
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is Cut the right side of the shape\nthe 3th action is Cut the right side of the shape\nthe 4th action is Stack the original shape on top of the {'layer1': 'SpSpSpSp'}.\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is Colorize the top layer of the original shape with the color blue.\nthe 9th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_129
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is Stack the original shape on top of the {'layer1': 'WyWyWyWy'}.\nthe 3th action is Colorize the top layer of the original shape with the color cyan.\nthe 4th action is Stack the original shape on top of the {'layer1': 'CcCcCcCc'}.\nthe 5th action is Stack the original shape on top of the {'layer1': 'SuSuSuSu'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'SpSpSpSp'}.\nthe 7th action is Stack the original shape on top of the {'layer1': 'RpRpRpRp'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'WbWbWbWb'}.\nthe 9th action is Stack the original shape on top of the {'layer1': 'WgWgWgWg'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_308
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is Stack the original shape on top of the {'layer1': 'SrSrSrSr'}.\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is Cut the right side of the shape\nthe 6th action is Stack the original shape on top of the {'layer1': 'SpSpSpSp'}.\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is rotate the shape clockwise 90 degrees\nthe 9th action is Stack the original shape on top of the {'layer1': 'RyRyRyRy'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABAAAAATICAIAAAANxCANAABj4klEQVR4nO3de5xkZXkn8J5hYBiG23AJw21FkQgzq6AkQQc3xg/ByF2NPdDGbHA1mvghJOuuG9yNi+aT1dm42U1c3Zg1JqOJNMyALAheIoLRgARjUC7GC+INlIs63AYYEGY/sXcrk67q6qo6t/d9n+/3P04PVaerz3nO+3ueU1VLtm/fPgUAAMSwtOsdAAAA2iMAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABLKs6x2AVj3wwAMHHHDAo48+OvCnr3nNa9773ve2vlMAVHLhhReO9e+X/tiyZcuWL1++22677b333vvvv/8BBxyw0047NbaPkJAl27dv73ofoD1/9md/9upXv3qhn+6zzz533XXXzjvv3O5OAVDJkiVLqj/ILrvs8i//5b98znOe81M/9VOnnXbaQQcdVMeuQYoEAGI54YQTrr766iH/4IorrjjllFNa3CMAkggA8x7w+OOPP/vss3/lV35l2TK3S1Aa7wEgkDvvvPNTn/pUvXNkAMqzffv2v/mbv3nNa15z1FFHbdq0qevdgZoJAAQyOzv75JNPDv83l1122ULvEAAgmttuu+3MM8987Wtf+9hjj3W9L1AbAYBA/vIv/3LellWrVs3b8uCDD1555ZUt7hQAqXvve9/74he/+PHHH+96R6AeAgBR3HrrrV/84hfnbXzHO97Rf3PnRRdd1OJ+AdCI7UM98cQTjz322P333/+tb33r05/+9P/8n//z5S9/+W677bbQo11zzTXnnntuu78BNMWbgIniTW9604YNG3bcsueee95zzz0nn3zyvLcFr1ix4p577tl9991b30cAansT8AQrnIceeugP//APf//3f//BBx8c+A8+/vGPv+hFL5poHyEhJgCEsH379tnZ2XkbX/KSlyxfvvxlL3vZvO2PPPLI5Zdf3uLeAZCE3Xff/Xd+53euv/76ww47bOA/eOtb39r6TkH9BABC+MxnPvOtb31r3sYzzzxzLgb0t458FhBAWGvWrLnyyisH3g503XXX/d3f/V0XOwV1EgAI4YMf/OC8Lfvss8+JJ544NTV18MEH/8zP/My8n3784x+/7777WtxBABKyZs2a3/7t3x74o6uuuqr13YGaCQCU77HHHtu8efO8jS972ct63/j70pe+tP9/+dCHPtTWDgKQnNe//vU77bRT//Zrrrmmi92BOgkAlO8jH/nIli1bBt7/M6f/bQDuAgIIbr/99jvmmGP6t/ffUArZEQCI+PH/+++//wtf+MLefx5xxBFr166d92+uvvrqe++9t5UdBCBFz3zmM/s3fv/73+9iX6BOAgCFu//++/u/2OvlL3/5vMFu/xDgiSeeuPjii5vfQQASte+++/ZvvP/++7vYF6iTAEDhLr744kcffXTexrPOOmveFncBATDKNwnsueeeXewL1EkAINz9PwcddNDzn//8eRuPOeaYpz71qfM2/s3f/M2dd97Z8A4CkKiBHwe3//77d7EvUCcBgJLdcccdn/70p+dtnJ6eXrp0wJHf/1lATz755KZNm5rcQQDS9ZWvfKV/47HHHtvFvkCdBABKdsEFFzz55JOL3v+zUABwFxBAWNu2bbvxxhv7t//sz/5sF7sDdVoy8P42KMPRRx9900037bjlKU95yje+8Y3+r/6d6/cfdNBBd99997ztt99+e//dQQCkY2BVr7jC+eAHP/jKV75y3sbddtvtzjvv3Hvvvas8MnTOBIBi3XLLLfNW/1NTU+vXrx94nfjHk2Hp0jPOOKN/+0UXXdTMDgKQqMcee+xtb3tb//bXvva1Vv8UQACgWP1v/x1y/88cnwUEwNTU1Bve8IYvfelL8zYeeuihv/u7v9vRHkGd3AJEmbZv337YYYd9+9vf3nHj05/+9K997WtD/q/HH3/8J37iJ/o/9uEf/uEfjjzyyGb2FICEbgHaunXrb/3Wb/3pn/7pvO177rnnpz71qWc/+9mT7iMkxASAMn3605+et/qfmpo688wzh/9fO++88ymnnNK/3RAAoHhbtmx55zvfuXbt2v7V/wEHHPDRj37U6p9imABQpl/91V/tr+A33XTTwO9139GHPvShX/zFX5y38cgjj/yHf/iHuvcRgAYnALOzs0P+l+3bt2/btu3hhx++66677rjjjhtvvPGmm27q/+C4qampE088cePGjQcddFCtuwxdEgAo0LZt21avXj3vTp6jjjqq/4bOfg8//PB+++33yCOPzNt+4403HnPMMXXvKQA1WOjTHSp69rOf/da3vvW0005r4sGhQ24BokBXXnll/338w9/+27Pbbrv9wi/8Qv92dwEBxLFy5co//uM//vznP2/1T5EEAAr0wQ9+sH/jom8AGP6NYD4MFCCOrVu3/vqv//rBBx98zjnnuAWU8rgFiNLcd999q1ev3rZt244bjznmmIFf6DjQli1bfuInfuJHP/rRvO3XX3/9cccdV9+eApD0LUA9J5100h/90R8dccQRjT4LtMYEgNJcfPHF81b/Y7X/p6amVq1a9XM/93P9290FBBDTRz/60Wc961n/7b/9t653BOqxrKbHgaS//2vJkiVjLd/333///o2bNm36gz/4g6VLxWaADCx6j8OTTz65devWBx988M477/zOd77zhS984YYbbrjmmmsee+yx/n/86KOPvvGNb/zmN7/5zne+04WA3LkFiKJ85zvfecpTntLcUf2pT33qBS94QUMPDkDnXwT2gx/8YOPGjb/3e7/X/2ESc84///y3vOUtEzwypEOEpSgXXHBBo5nWXUAAZdt3333/3b/7d1/96ldf+MIXDvwHv/d7v/fZz3629f2COpkAUJRnPetZN998c3OPv//++3/3u99dtsy9cwBlTgB6tm3bdsopp3zyk5/s/9GJJ574V3/1V1UeHLplAkA5brrppkZX/1NTU/fee+/VV1/d6FMAkILly5d/4AMf2Gefffp/9IlPfGKUb5aEZAkAFP7239q5CwggiIMOOuicc84Z+KOPfOQjre8O1EYAoBDbt2+fnZ2dt3HlypUPP/zw9kldcMEF/U906aWXDvyACADK89rXvnbg9uuuu671fYHaCAAU4lOf+tQdd9wxb+Opp566YsWKiR/ztNNO6//f77vvvo997GMTPyYAGTn44IMPP/zw/u1uASJrAgCF+OAHP9i/cXp6uspj7r777ieddFL/dncBAcRx7LHH9m/84Q9/2MW+QD0EAEqwbdu2Sy65ZN7GlStXDly+j2X9+vX9Gy+//PKHH3644iMDkIV99923f+NC3xIAWRAAKMEVV1zRX4tPOeWU3XbbreIjn3rqqf0PsnXr1iuuuKLiIwOQhT333LN/oy8DJmsOX4r9/J+K9//MWbly5cknn9y//aKLLqr+4ACk74EHHhgxFUAuBACyt2XLlv6PY9ttt90GLtwncOaZZ/Zv/MhHPvLggw/W8vgApOzee+/t33jIIYd0sS9QDwGA7G3evLn/czlruf+n91ArV66ct/HRRx/9P//n/9Ty+ACk7IYbbujfeNRRR3WxL1APAYDsNfH5PztasWLFqaee2r/dZwEBFO+rX/3qt7/97f7txx13XBe7A/UQAMjbt7/97c985jPN3f8z5LOAPvGJT/gYOICy/Y//8T8Gbj/llFNa3xeojQBA3i644ILt27fP23jyySf337RTxcknn7z77rvP2/j444/3f/YoAMW48cYb//zP/7x/+/Of//yB3w4GuRAAyFvT9//M2XXXXU877bT+7e4CAijVnXfe+fKXv3zbtm39P/rt3/7tLvYIaiMAkLEvfOELt9xyy7yNK1asaGIyO/AuoL/+67++++67a38uALp1/fXXH3fccbfffnv/j1784hcPfGMYZEQAoLT2/0knnVTv/T+9h+3/1Ocnnnhi8+bNtT8XAF254YYb/vW//tfr1q278847+3+6evXqgTcFQV6Wdb0DMKEnn3xydna2hft/5ixfvvz000/v/8axCy+88JxzzmniGQGoYpS7NH/0ox9t27btgQce+P73v//lL3/585///Le+9a2F/vE+++zzsY99bPXq1XXvKbRtSf8bKCELV1999QknnDBv46677nrvvff2v2G3Fh/+8IdPP/30eRuXLFnyrW9969BDD23iGQEYxZIlS5p+ijVr1lx++eXe+0sZ3AJErvqb8XM36jS0+p+amvqFX/iFvfbaa97G7du3X3TRRQ09IwApeOUrX3n99ddb/VMMAYAsPfroox/60Idau/9nzi677HLGGWf0b/dZQACl+qmf+qlrr732L/7iL/bYY4+u9wVqIwCQpQ9/+MP333//vI277rpr05/MMPCzgD7/+c/fdtttjT4vAG3afffdX/WqV1177bWf+9zn1q1b1/XuQM28CZgsrVix4vzzz5+38V/8i3/RdIfmRS960Vve8pb+d870pxEAErdkyZJly5YtX7589913X7Vq1QEHHPCUpzzlOc95zrp164455phly6yRKJY3AQMAQCBuAQIAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBAlkxPT3e9DwAAQEtMAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgkGXDfzy78da29gTaMHP22iE/dcAT7ZgfwulAYdR/oplZ+Jg3AQAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBAsg8AM2ev7XoXgKDUn255/YGuzGRef5ZNlfI3mN14a9c7AkSRe+kvhvoPtGymiPqf/QSgV/dnzl5bxp8ESNmOpca6s1vqP9CmmYLqfwkTgB3pBgENscRMnPoPNGSmuPqf/QRgYLnXDQJqNLCkWGimQP0HGjVTaP0vbQKwI90goCJLyUyp/0BFM0XX/xImAMOrvG4QMIHhpcPKMh3qP1CvmQD1v+QJwI50g4ARWTIWRv0HRjQTpv4XMgEYsbjrBgHVS4SlZGrUf6CimWD1P8oEYEe6QcA8loZBqP/APDHrf1EBYHbjraP/FV0GgAnqvqKRJvUfGMtM7PpfVACYgMsAxBSz5cOO1H+IaUb9L+k9AHMmK+XuDYU4qpzvFospU/+B4dT/nugTgB0V8/XOwEDWeSxE/Yeyqf+FTwBqKd8aQlCYWk5qS8P0qf/APOr/QCYAC3J7KBTAYo4JqP9QAPU/1gRgeNXesGrTWA+lGwSZGvfkHV4crAVzof4D6v+iwk0Aztuyfu7PfN6W9aP/X7pBkJFxF20T1ARypP5D8dT/6AFg0c+EdhmA8kxW+hflrM+L+g8Bqf9jKTYAjNIEchmAYlQs/QHbPzGp/1Ae9X8CJQeA0b8Y0mUA8tVQ16fHaZ4j9R8iUP8nVnIAGLEJ1OMyADFLf8z2T1jqPxRA/a+o8AAwehOox2UA0td016fHeZ0v9R+KpP7XovAAMG4TqMdlAIKU/rDtn8jUf8iR+l+j8gPABE2gHpcBCNj16XEi5079hzKo/7UrPwBM3ATqcRmAUkt/5PZPcOo/ZEH9b0iIAFClCdTjMgARuj49ztwyqP+QKfW/USECQPUmUI/LABRT+oO3f1D/IU3qfwuiBIBamkA9LgNQZNenx6laEvUfcqH+tyZKAKixCdTjMgA1mmCJVqX0a/+g/kMi1P/2BQoA9TaBelwGIK/SvyjnZnnUf0iT+t+VQAGgiSZQj8sAZFT6tX/oUf+hE+p/t2IFgIaaQD0uA5Bp16fHyVgq9R8Sof6nIFYAaLQJ1OMyACmXfu0f5lH/oR3qfzrCBYCmm0A9LgOQWulflLOvbOo/dEX9T024ANBOE6jHZQCSKv3aPwyk/kND1P80RQwArTWBelwGCCud0r8op1sE6j+0Rv1PWcQA0HITqPplIOahSe4SLP3aPwyh/kNd1P/0LZ0KqcN6OtkhPnP22pa7VjCxyQ7Xrho/c6yx4lD/oTnqfy5MAFptAk3cCppjLkziJlumtFP6tX9YlPoPE1P/8xI3ALR/J+g8LgOUJOXSvyhnUzTqP9RI/c9R3ADQbROox2WA3GVR+rV/GJH6D6NT//MVOgB03gTqcRkgR1mU/kU5fWJS/6EK9T93oQNAIk2gHpcBcpFX6df+YSzqPwyh/pchegBIpwnU4zJAyvIq/YtyvkSm/sNY1P+SRA8AqTWBelwGSE2mpV/7hwmo/7Aj9b88AkCKTaAelwFSkGnpX5QTBPUfhlP/SyUApNsE6nEZoCu5l37tHyam/hOc+l82ASD1JlCPywBtyr30L8oZwRz1H+ZR/yMQAPJoAvW4DNCoiVdCSZ0mc7R/qEj9JxT1PxQBIEsuA9SupNIPBVP/qZ36H9DSrncgFUNqYrI5csOqTZOdezNnr01/5E1rJj4eJj4CWzD8tLUGYkfqP2Gp/2GZAGRPN4iJ6fpA1tR/Jqb+B2cCkHcTqEc3iLEU2fXp0f5hXOo/caj/mACURjeIRen6QJHUfxal/tNjAlBOE6hHN4iAXZ8e7R8mo/6r/wVT/9X/eUwAiqUbRI+uD4Si/tOj/jOQCUCZTaAe3aDggnR9erR/qEL9n6P+l0H935H6P48JQAi6QQHp+gDqf0zqP4syASi/CdSjGxREtK5Pj/YP1an/86j/eVH/B1L/+5kAhKMbVDBdH2AI9b9g6j9jEQAGm91460Ln0nlb1hdwtlS8DLgSpEbp1/6hLur/QtT/NKn/6v8EBIDQJr4MaAilQ+kHJqD+F0D9Z2LeAxDuTtB67/xze2iHwt7r2U/7h3qp/6NQ/zuk/veo/5MxAehYGdcS14CWFdP1KeOGCsidaUBG1H9qIQB0fCfohlWbysgAtKOk0t/OQ1mXMJni3wnQTwxInPo/7kM5IIcQACAPSj/QAjEgQUXW/9T2LRoBYBGGAHSuyNLfzmNaiFBFwCFAjxiQCPV/4sd0BA4nAECB76yIUPqBpokBXSm+/qe2kwEJAIszBKBlxZf+dh7cyoPqIg8BesSANqn/tTy4Q25RAgAkROkH0iQGNC1O/U9tb2MSAEZiCEDT4pT+dp7FUoO6GALsSAxoQjH1v7VljPpfnQAAHSum9Ov6QxBiQF2Kqf+jHwxJ7XZkAsCoDAGoXTGlv/2lv/YPbTIEGEgMqKKY+t/+ukX9r4UAkJnNswmd9jmankkiYhVT+nX9ITgxIGz9n+CPntT+B7e06x3IyZAiVdcaaNFzI5H1KxObOXttlc91Tqp6nrdlfSerf+0fiqz/WatSnapUxbwUU/+7Kv7qf41MAKAlxXR9rHiAgUwDiq//VYp/Ur8IJgDjMQQgcten28ZPbweG/LTU1QMpMAQYkWlAkfW/8+Kv/tfLBAAaVEzXxxIHGItpQDH1v5bin9RvhAnAJAwBCNX1SaTxM0f7h24ZAowr5jSgmPqfTvFX/2tnAgA1K6brU8uaZvPsJnkVgoszDSim/o/7xxpe6pP61ZhjAjAJQwCa6FclVSKrN342z26q91NrtX9IgSFAJyUu/WlAMfV/3OI/V+qbXpOo/7UzAYAaVLwypVP66+r617QvQFGqjAKSnQYUU/8n6Prn9QuyIwEg4y8Gnp5Zb6XVuWJKf+JLf+0f0uGLgSsqJgYUU/8rLv21/3MkAED00p/40h8oUtYxoIz6P8GLP26pT+Q3pZ8AMDlDgLDKKP0ZLf21f0iNIUBSMaDNOlBG/a9x6a/9nykBAMKV/oyW/kAEFWNAOwOBMup/C13/1H5lBhIAKjEECKL6p08kVQfzWvpr/5AmQ4AgMaCY+t/E0l/7P18CAIQo/Tku/YGA0okBxdT/Nrv+qf3uLEQAqMoQoFTFlP6sl/7aP6TMEKDUGFBM/W906a/9nzUBAIot/Vkv/QHajwHF1P9Ouv6pvQgMsWR6enrIjwWs6iWjrtNg0ZPZKi2FjkVSVS+Rpf/w13zIK6b9U4uJFzRe4XTqP1l80XKopf/EhX1E6n/T1ckEAIoq/Ukt/QHSmQYUX/+77fqn9mownABQD+8EiCypYlfM0l/7h1x4J0DkGBBz6e/u/wIIAJB96S9s6Q+QfgxIpP5P9iI0V+0TeVlYlABQG0OAUJKqceUt/bV/yIshQKgYEHzpr/1fBgEAsiz9pS79AZKNAYnU/9S6/qm9PoxCAKiTIUDZkiptBS/9tX/IkSFA2TEghb/gxL9djdVe+78YAgDkUfrn1HJ5S3bpD5BaDEih/qew9KcwAkB7DAFylELpD7X0T+fDPaBGhgA5xoAU/mRJLf27/ex/6iUAtDcFJi8plP5QS/9RmP+SMvW/mBiQQv1PaumfAvW/XgJAqwwBspBC6Y+59Nf+oWCGAFnEgBT+Rmku/bX/CyMAtN0Ecg1IWTp/mmhL/1F+Ze0f0qf+5xsDUvjTpLn0b4H63z4BIFeGAKUKuPQHCC7xpX/T7X/aJwA0QhOICURe+mv/UAz1n5KW/i1Q/zshAGTMEKAYkZf+ADHlsvTX/i+SANAUTSBGYemv/UN51H/KWPq3QP3vigCQN0OAfFn6A0ST3dJf+79UAkCDNIEYyNJ/R9o/FEn9J/elfwvU/w4JANkzBAi19PenBAhS9jsv+Nr/BRMAmqUJxBxL/8lo/5Av9T+4rJf+LdD+75YAUAJDgJRZ+gOEUsbSX/u/bAJA4zSBwrL0r0j7h9yp/9GUsfRvgfZ/5wSAQhgCJMXSHyCUwpb+2v/FEwDaoAkUh6V/XbR/KIP6X7zClv4t0P5PgQBQDkOAbln6A4RS6tJf+z8CAaAlmkAFs/SvnfYPJVH/y1Pq0r8F2v+JEACKYgjQMkt/gFCKX/pr/wchALRHE6gklv7N0f6hPOp/AYpf+rdA+z8dAkBpDAGaZukPEEqcpb/2fxwCQKs0gbJm6d8C7R9Kpf7nKM7SvwXa/0kRAApkCFA7S3+AUCqW/RxrvvZ/KAJA2zSB8mLp3ybtH8qm/qdPzW+I9n9qBIAyGQJU5zIAEEfwmq/9H83SrncgouExt3oNoqLztqyvPvzN+krQCe0fIlD/i6TmD6f9nyATgGIZAkwgeAcIgIA1X/s/IBOAbmgClUcHqArtH+JQ/8ug5o9I+z9NJgAlMwRoh9cQII7Car72f0wmAJ3RBCqADlAttH+IRv3PVFI1f/jCPRHa/8kyASicIUBDvGgAcSRV82tc+mv/h2UC0CVNoEwldSXInfYPMan/uUit659F43+O9n/KTADKZwhQu1799boBlCqpCt/Euj+jLEHtTAA6pgmUtblmjBoKTED9T5auf/X7f7T/E2cCEIIhQNPmqrPXECBrSZXxRtf9WlfBmQB0TxOoGAYCwFjU/3SE6vov+uDa/8UTAKJY9GS2bK2RGADABFw+aIcAkARNoCIp4sCi1H9aXvpr/yMAxGII0D69HACGc6WgfQJAKjSBUjD9/9X8sIo7sDD1P6z2rw7a/8zxKUCx+DigEc3LAJs3b67hMb22APyYrhDdMgFIiCZQ+pOBisMBFR8YSP2Po8OZsPY/PSYA4RgCVNTLAJONBXxjAEBMekCkwwQgLZpAGakyEHAZAOZR/wuWwjvBtP/ZkQAQkY8DSiEGeJEBipfC0h/6CQDJ0QSKEwNcFYAdqf8lqb7037SptptFtf+ZRwAIyhAgkRjgdQYoTC1L/xpX/9BPAEiRJlCoGGBADPSo//maK+YJLv21/+knAMRlCNAoowCAIGrp4+j60yYfA5ql87asr5jXaS0D1PIlYgBz1P+k1NK7aXTd33n7nzSZACSqnXmZIUBSowCvNuB+iVzo+o/I8ZwmASBXMndGZACgRup/tzJa+mv/sxABIF2GADHfGewFBzRN05TR0j8RjuRkCQAZk7yzIwMAtVD/W5bj0l/7nyEEgKQZApRHBgBGoXWaiByX/olwDKdMAMib/J2jCb4zGGAe9b9pWS/9tf8ZTgBInSFA2AzgNYfgNFC7kvXSPxGO3sQJANmTwjMlAwAVqf+1K2Ppr/3PogSADBgCROZlh8i0UTNa+s+t+yN3/Xsct+kTAEogi2fKmwGAitT/FCS17tf+ZxQCQB4MAUrlRiBgOM3UlCW19E+EIzYLAkAhJPJ8mQMAVaj/nUhz6a/9z4gEgGwYAkTmZYfItFSTkubSPxGO1VwIAOWQy/PlRiCgCvW/HYkv/bX/GZ0AkBNDgIK5EQgYQmO1W4kv/RPhKM2IAFAU6bxsohewEPU/+NK/6QuEA6wwAkBmDAEKZggADKG92rJclv4jqnj/z6Icn3kRAEojowPEpP6HXfpr/zMuASA/hgCRhwBedohMk7Vp2S39R6T9zzwCQIEkdYCY1P+AS3/tfyYgAGTJEKBghgDAEFqtjEv7n34CQJnkdYCY1P9QtP+ZjACQK0OAgvk4IGAIDVdGp/3PQAJAsaT2gsldwBDqfxDa/0xMAMiYIUDBDAGAIbRdGYX2PwsRAEomuwPEpP5TkUOobAJA3gwBwvKaQ3Carwyn/c8QAkDhJPh8uQsIqEL9Z2IOnuIJANkzBACISQuWhWj/M5wAUD45HiAm9Z8JOGwiEABKYAgQkxcc0Iiln/Y/ixIAQpDmM+VtAEBF6j9jccAEIQAUwhAAICbtWHak/c8oBIAoZHqAmNR/RuRQiUMAKIchAEBMmrLM0f5nRAJAIJI9QEzqP4tykIQiABTFECDa+4C91MAcrVm0/xmdABCLfA8Qk/rPEA6PaJb4nEFoVPVTbPPmzTXtCwCAAAAAAJG4BQgAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIJBlw388u/HWtvYkqJmz1w756ebZTS3uSwjTM+ube8GHP3ijNqza1M5XwasJhRWZIfyty/tb11Io8jW8xG3aNOGLs379+gJedvU/Wk1YJAAAo9s8u2nRDDBZxlj0Yc/bsr76NWbDqk2jXAOAHGWxDC1SLfW5aep/NG4BglZNNiVIZxY0cTsZaJRzsysTjw6y4xgriQAAdepwpV5L8yb9NhUwAad2t7JorjtIQhEAIA+GAMBCnJXdMgQgOwIAtL1Sb+69woYAQD8ndQoMAUiKAADZMAQA+jkfU2AIQF4EAKifIQCQCKdzOgwBSIcAADkxBAB25ExMhyEAGREAoBGGAEDnnMipMQQgEQIAZMYQAJjjHEyNIQC5EACgKYYAQIecwmkyBCAFAgDkxxAAcPalyRCALAgA0CBDAKATTt6UGQLQOQEAsmQIAJE571JmCED6BABoliEA0DKnbfoMAeiWAAC5MgSAmJxx6TMEIHECADTOEABojRM2F4YAdEgAgIwZAkA0zrVcGAKQMgEACl+pGwJAHE7VvBgC0BUBAJIw8V1AhgAQh7MsL4YAJEsAgH8yPbO+udvxDQGARjlJc2QIQCcEAGgvBgzPAIYAwBDOrxwZApAmAQA6mAa0zxAAyub0zJchAO0TAKDVGGAIAEzAmZUvQwASJABAlGmAIQCUyomZO0MAWiYAwKjqygCGAMBYnFO5MwQgNQIABBoFGAJAeZySZTAEoE0CAHQQAwwBgBE5m8pgCEBSBACINQ0wBICSOBlLYghAawQA6CYGFD8EACDmEID0CQAQbhrQzhDAFBiqG34e6cWWp4whgPqfPgEAamufjxsDGurWGwIApMkQgEQIAPDPbJ7d1HIMGPI4U40xBID0af/HZAhACwQA6DIGGAIAhGIIQAoEAEh3GmAIAGFp/0dmCEDTBADoOAYYAgCEYghA5wQAGCMGVFlVT9bONwSAgLT/MQSgUQIAjKdKDFhoFGAIABCKIQDdEgAglRgw5N9PNcYQAFKj/c8cQwCaIwBAEjHAEAAgFEMAOiQAQAbTAEMACEL7nx0ZAtAQAQBSiQGGAAChGALQFQEAUvmwoOFtfkMAKJ72P/0MAWiCAACJfntAjdLZEwB2ZAhAJwQAyCYGGAJAwbT/WYghALUTACDENKDzHQBgIEMA2icAQKAYMJwhAHRF+5/hDAGolwAAOcWAKncBJR4/AMIyBKBlAgB0INlpgCEAtE/7n1EYAlCjZXU+GDCOXgYYq69f5RsDNs9uavSdxACZWr9ebSQQEwCiGPE7dzuR1EDAEADapP3P6AwBqIsAQPlSXvpPFgO8EwAAmJgAQMlyWfqnNg0wBIB2aP8zLkMAaiEAUKYcl/5jxQBDAABgMgIApcl96Z/INMAQAJqm/c9kDAGoTgCgHCUt/ftjQH8SMAQAACYgAHRJ/K1LqUv/bgcChgDQHO1/qjAEoCIBgLwFWfovFAMMAQCAcQkAnRF8Kwq49G9/GmAIAE3Q/qc6QwCq8E3A5Cfyun+eihnAFwMDzJG7CMUEoBsi72SCd/07YQgA9dL+JxT1P00CAFGW/htWbXJl7eedAAAQjQDQAWF3LJb+nTMEgLpo/xOQ+p8g7wEgXdXv9nE1HYV3AgBAKCYAbRNzR6HrnxpDAKhO+5+w1P/UmACQFl3/ThgCAEAcJgCtEnCH0PVPnCEAVKH9T3Dqf1JMAOiern8KDAEAIAgTALqk65+XdoYAEI2TgiAc6ukQANpjtrUjS/8EJfKdAM4UyuOohlE4U1ojANA2S/+sGQJAvZwOhOKAT4QA0BKh1tI/C4YAUDvHM4zO+dIOAYA8lv7aBukwBIC6OBEIyGGfAgGgDZHjbF1Lf/WiNYYAUCNHMozLWdMCAYCmWPoXzBAAqnMKEJaDv3MCQOMCBllL/9wZAkAtHMMwGedO0wSALpW3wLX0j8MQAKpw8BOcU6BbAkCz4kRYS//CGAJARY5eqMIZ1CgBoDPFrHQt/cMyBIDJOOzBidAtAaBBxYdXS/+yGQLAxBy3UJ3zqDkCQDdyX/Ja+jPHEADG5YCHHqdDVwSAppQaWy39QzEEgAk4YqEuzqaGCAAdyHTta+nPQIYAMDqHOszjpOiEANCIwgKrpX9khgAwFscq1Ms51YRljTwqC8trEVx93Z/Or1xLo5qBztuyvvpfecOqTf5GlC2RYhjQKLVl7t/4G3VC/W+fCUCrUTWjylJS1/+8LetVliyGAMOPFk0g0ldG/S/JuPXf9aIr6n/LTACYT9efroYAACnUf9MAimcCULOs2z+6/izEEADKrv8lqav+u460TP1vkwkA/0jXn+oMAYDy6r9pAEUyAYje/tH1Z0SGAFBY/S9J0/Xf9aUd6n9rTADi0vWndoYAQMH13zSAYpgARGz/6PozGUMAyL3+l6Sr+u+60yj1vx0mALHo+tM0QwAgQv03DSBrJgBR2j+6/tTCEACyq/8lSa3+p7Y/ZVD/W2ACUD5df1pmCACEqv+mAWTHBKDk9o+uP00wBID0639Jcqn/uexnFtT/ppkAlEnXv9/sxltVjdYYAgB51f+6rhGmAWRBACit/WPpv1BZp0abZzfVcqQtasOqTUMOg5mz1/rj0qHU6n9Juqr/YkA61P9GCQDlsPTvpzp0yBAAyLT+iwEUTwAoof1j6d/P0r9phgAEl0j9L0lq9V8M6Jz63xwBIG+W/v2Ug3QYAgC51//eY1ZMAmIASREAcm3/WPr3s/RvmSEAYWn/B6z/tQwExIBxqf8NEQDyY+k/j5M/ZYYAQEn1XwygDAJATu0fS/95LP07ZwhAQNr/FRVQ/8WANqn/TRAA8mDpP4+zPSOGAECR9V8MIF++CTj19k9J3+ZbS/Wf3XhrOtUfXwxMNNr/Eyu1/teyV75CeDj1v3YmAEnT+N9RgnWfERkCQGQR6n/1aYBRAG0yARhbRu2fRBr/521ZX7H6p9n1occQgCAyqv+JiFb/q+9t9VesVOp/vUwAypTIpShC14cRGQJAKJHrv2kA6RMAapPIiZrIbkQu/TEl8nFAELnwJkL9nyMG1E79r5EAMJ6UZ0yJ1Ailnw6HAD4Pjpj1PxHqfz8xoDXq/1gEgHp0e2YmUheU/uAMAYgpkQrcLfV/ODGgLup/XQSAvNs/idQCpZ8RGQKQqQTrfyLU/9GJAU1T/0cnANSgk1MxkfO/sNLfTgOb6jSBSEQipbgThdX/1ogBFan/tRAA8mv/JHLOK/1MxhCA7KRT/xOh/lcnBjRE/R+RAFBVm+deIue50k8KNIHoXCI1uU3qf73EgMmo/9UJAHm0fxI5t5V+amEIQEY6r/+JUP+bIwbUS/0fhQBQSQsnWyLns9JPgjSB6FAixbkF6n87xICxqP8VCQDptn8SOYeVfppgCEAWgrf/1f/2iQG1UP8XJQBMrrmzK5HzVuknfZpAdCKRKt0c9b9bvVdv4iQQIQao/1UIAGm1fxI5V5V+WmAIQOJitv/V/5IGAhFiwELU/+EEgAnVfjolcn4q/WRHE4iWJVKua6f+J0sMWIj6PzEBoPv2TyLnpNJP+wwBSFao9r/6nwUxYFzq/xACwCRqPH9SOBWV/kx/kYoLlBSOvbpoAtGakk4c9T9HYsA86v9kBIDQ7R+lP2suAyPSBGJc6v8onFYdUv9HpP4vRAAYWxknjNJfDJeBOZpAtKCAM0X9L4n6P0f9n4AAEK79U/EkUffT5DIwnCYQo1P/F+IkSpP6P5z6P5AAMJ6szxClv3jBLwOaQDQq31ND/Y9A/Vf/xyIAhGj/KP2hBL8MLEQTiFGo//M4a/Ki/g+k/vcTAMaQ4ymh9IcV8zKgCURDsjsX1P/I1H8WJQAU2/5R+gl7GViIJhDDqf9znCZlUP93pP7PIwCMKqNzQOkn8mVAE4ja5XLwq//0U/8ZSAAoqv2j9DNEqMvAQjSBWIj6X9++kBz1X/2fRwAYSfoHvdLPiCJcBjSBqFHiR7v6z+jUf3oEgOzbP0o/E4hwGViIJhD91H/iUP+nEABGkexRrvRTUcGXAU0gapHm4a3+U536H5wAkGX7R+mnRgVfBhaiCcSO1H/CUv/DEgAWkdphrfTTkPIuA5pAVJTU8az+0xz1PyABIJv2j9JPC3rHyWQnRYKXgYVoAjFH/Yc56n8oAsAwiRzHSj95NYTSuQxoAjGxFA5g9Z9OqP8RCABJt3+UfrpVxmVgIZpAqP+wEPW/bALAgro9cJV+0pH1ZUATiAmo/zBH/S9V9ACQYPtH6SdNWV8GFqIJFJn6DyNS/8sTPQAspJMjVeknfTleBjSBGIv6DwOp/yUJHQDSaf8o/eQlx8vAQoI3gcJS/2Ey6n8ZQgeAhbR5aCr95Cujy4AmECNS/2EU6n/u4gaAzts/Sj9lyOgysJDITaCY1H+ohfqfr7gBYCEtHItKP+VJ/zKgCcSi1H+YgPqfIwGgbVUOQaWfsi8DnbeCoFHqPwVT//OydCqkhQ7QRo+/87asn7j6z268VfUnFxMfrlXOkVEMOcE7vyeE1qj/0Bz1PxcmAG2oUvfr3hdIvRuUyI2hUAv1n4DU//RFnAC02f6ZONFq+VCG1LpBmkDBqf/QGvU/ZSYATdH1gR7dIEJR/6FH/U9TuAlAC+0fXR9IuRukCRSW+g9dUf9TYwJQJ10fWJRuEEVS/2FR6n86Yk0Ammv/6PpARt0gTaCA1H9IhPqfAhOAqnR9YGK6QWRN/YeJqf/dCjQBqL39o+sD+XaDNIFCUf8hTep/V0wAJqHrA7XrnR3j1l/dINqk/kPt1P/2RZkA1NX+0fWBpk12skxwbmoCBaH+Qy7U/9aYAIxK1wfSvz1UN4gmqP/QJvW/BSEmABXbP7o+UGo3SBOoeOo/ZEr9b5QJwDC6PpAC3SDap/5DCtT/hpQ/AZis/aPrA0G6QcGbQGVT/6EM6n/tTADm0/WBlOkG0Rz1H1Km/teo8AnAWO0fXR+I2Q2K3AQqmPoPRVL/a2EC8I90fSBHukFUp/5DjtT/ipYGb//o+kDuaukGhW0ClUr9hwjU/4nFnQDo+kBJdIMYnfoPJVH/J7AsYPtH6YdSVbwMLFQcZs5e6/TPiPoPAan/Yyk2ACxk4oFvA/sCJHcZoGDqPxRP/Q/9HoAa79lyrydkqt6Tt+A7QQuj/gPq/6LCTQBGp+5D2G4Qwan/UAD1P9YEoPpfWtcHClPLSe0qkj71H5hH/R/IBOCfKPpQNt0gFqL+Q9nU/8InAJP9abV8II4q57uLR8rUf2A49b8n+gRA3YeYdINQ/yGmWfW/sAAw1t9S6Qd6dWD06lHqZ0LnTv0HxjIbu/4XFQBGVMwfD6iLhlAQ6j8wT8z6X857AEb5y7nXE6heIqJdJ9Kn/gMVzQar/1EmAOo+MKKY3aCCqf/AiGbD1P9CJgBD/lS6PsAEhpeOCJeHXKj/QL1mA9T/kicA6j5QUZxuUGHUf6Ci2aLrfwkTgP6/ja4PUKOBJaXUq0Je1H+gUbOF1v/SJgDqPtCQsrtBBVD/gYbMFlf/s58A9P4Yuj5AC3YsNSVdDHKk/gNtmi2o/pcwAVD3gZaV1w3KlPoPtGy2iPqf/QRA9Qe6ov50y+sPdGU28/qTfQAAAABGJwAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCACAAAABLJkenq6630AAABaYgIAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABDIku3bt3e9DwAAQEtMAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAJZ1vUOQHu2bdt2/fXXX3vttV/+8pdvu+22O+6446GHHtq6deuTTz65YsWKlStXHnjggQcffPBRRx119NFHH3/88YcddljXuwwAULMl27dvr/sxIS3btm378Ic//P73v/+qq6569NFHR/8fjzjiiJe//OWvetWrjjjiiCZ3EICxXXjhhWP9+yVLlixdunSnnXZavnz5ihUr9txzz3333Xf16tUrVqxobB8hUQIAJXv44Yff/e53v+Md77j33nurPM7pp5/+lre85dnPfnZ9uwZAJUuWLKnlcQ455JA1a9Y85znPecELXvD85z9/9913r+VhIWUCAMW68MILf+u3fuvuu++u5dGWLl36+te//u1vf7trA0BJAWBHy5cvf/GLX/yKV7zipS996c4771z740MiBAAK9IMf/ODVr371ZZddVvsjP+MZz7jsssue8Yxn1P7IAHQeAHoOPvjgc8899zd+4zfcIESRBABK86Uvfen000//+te/PuTf/ORP/uSxxx571FFH7bfffnvssccjjzzywx/+cMuWLTfffPNnP/vZLVu2DPl/99prr49//OPHHXdcA/sOQBIBYM6hhx76+7//+2eddVbTTwQtEwAoynXXXXfSSSc98MADA396yCGH/Nqv/dorXvGKpz71qQs9wvbt22+++eb//b//9/vf//6HHnpo4L/Za6+9rr766uc85zn17TgAyQWAOdPT0+95z3v22Wefdp4OWiAAUI6/+7u/O+GEEwau/vfcc883v/nNv/mbvzn6PZ3333//+eef/853vnPgOXLIIYfccMMNBx54YOW9BqC2ADB8VfOjH/3oiSeeePjhhx966KF77733m9/85q233vq5z33ur//6rxfqHM152tOeduWVVx555JF17Dh0TwCgELfffvtP//RP//CHP+z/0U//9E9v2rRpsg/1v+qqq175ylcOfCfxiSee+Fd/9VcT7SwAHQSAhTz22GOf/OQn/+RP/uTDH/7wk08+OfDfrFq16qMf/aj7PymDAEAJHn744XXr1n3xi1/s/9EZZ5yxadOmXXbZZeIHv+WWW17wghcMjBbvfe97X/Oa10z8yACkEAB6br755n//7//9Qs2dvffe++qrr/aR0BRAAKAEr371q//sz/6sf/vpp59+ySWXLFtW9RuvP/e5z/2rf/Wvtm3bNm/76tWrb7vttpUrV1Z8fABSCABz/uRP/uTcc8997LHH+n904IEHfv7zn3f/J7lb2vUOQFVXXXXVwNX/0UcffcEFF1Rf/c/dRPTmN7+5f/tdd931nve8p/rjA5CO173udZ/85Cf32muv/h9973vfW79+/RNPPNHFfkFtTADI27Zt24466qhvfOMb87bvtttuX/jCF4444oi6nujxxx8/9thjb7755nnbn/a0p33ta19bulSWBihkAjDns5/97M///M8//PDD/T/6gz/4gze84Q11PRG0z6qFvL3nPe/pX/1PTU297W1vq3H1PzU1tfPOO59//vn922+//fbrrruuxicCIAXPe97z3ve+9w380fnnn3/HHXe0vkdQGwGAjD3yyCMbNmzo337kkUeec845tT/dS17ykkMOOaR/+6WXXlr7cwHQubPOOmtmZqZ/+0MPPTTw6gO5EADI2F/+5V/edddd/dv/y3/5LzvttFPtT7fTTju97nWv699+zTXX1P5cAKTgv/7X/7pixYr+7e973/sGXoAgCwIAGXvve9/bv/Hwww9/yUte0tAznnrqqf0bb7rppq1btzb0jAB06NBDD/0P/+E/9G9/9NFHN27c2MUeQQ0EAHJ1yy23fO5zn+vf/vrXv765t+QeffTR+++//7yNTzzxxFe+8pWGnhGAbv3bf/tvly9f3r/9Ax/4QBe7AzUQAMjVZZdd1r9xyZIlZ511VnNPumTJkhNOOKF/+9e+9rXmnhSADu21114Dx7//8GNd7BFUVcNHpEMnPvKRj/RvXLdu3UEHHdTo85511ln9HzO3xx57NPqkAHTol37ply655JL+7VddddVRRx3VxR5BJb4HgCw99NBDe++9d/9Xsbz5zW/+3d/93Y52CoByvgdgR4899tiqVav6vxPgpS996Yc+9KEmnhEa5RYgsnTjjTcO/CLGF7zgBV3sDgAl22WXXZ75zGf2b//CF77Qxe5AVQIAWfr7v//7gduPOeaY1vcFgPINvL5885vffPDBB7vYHahEACBLX/rSl/o3rl69et999+1idwCIGAC2b9/+9a9/vYvdgUoEALL0ne98p3/j0572tC72BYDyrVmzZuD27373u63vC1QlAFBOADjwwAO72BcAyrf33nsP3P69732v9X2BqgQAsvT973+/f2P/V3QBQC323HPPgdsfeOCB1vcFqhIAyFL/Z7FNTU2tWLGii30BoHx77bXXwO2PPPJI6/sCVQkAZOnRRx/t37jrrrt2sS8AlG+hCcC2bdta3xeoSgAgSz/60Y/6N/pWOwAaMvDLZ6ampnbeeefW9wWqEgDI0vLly0ccCwBAdQt1+g2fyZEAQJYG3u4/8I0BAFDdQl/4tdtuu7W+L1CVAECW9thjj/6N9957bxf7AkD57r777oHbV69e3fq+QFUCAFk66KCD+jfeddddXewLAOVb6PP+Dz744Nb3BaoSAMjSwIJ7++23d7EvAJTvq1/96sDtT3nKU1rfF6hKACBLT33qU/s33n333T/84Q+72B0ACvflL3+5f+P+++/vFiByJACQpWc961kDt3/xi19sfV8AKN/111/fv/Hoo4/uYl+gKgGALC1Ucz/zmc+0vi8AFO7++++/5ZZb+revW7eui92BqpZVfgTowJo1a/baa6/7779/3vZrrrnmP//n/9zoU/+bf/Nv5n3e6C677PKBD3yg0ScFoEMf/ehHB34R2IknntjF7kBVS3x5Kpl62ctedumll87buNNOO91111377bdfQ0/69a9//elPf/q8jYcddtg3vvGNhp4RgIGWLFnSv7GhVc309PTFF188b+Pee+99zz33+CZgcuQWIHL14he/uH/jE088cckllzT3pJ/4xCf6N/ZHAgCKcc8991x22WX9288880yrfzIlAJCrl73sZQMr7x//8R8396RXXXVV/8ZnPvOZzT0jAN1617ve9fjjj/dv/5Vf+ZUudgdqIACQq/322++kk07q3/7FL37xmmuuaeIZH3nkkU9+8pP9248//vgmng6Azv3gBz/4oz/6o/7txx133POe97wu9ghqIACQsde97nUDt/+n//Sfmni6Cy644L777pu3ceedd37hC1/YxNMB0Lk3vvGNDzzwQP/2//gf/2MXuwP1EADI2Mknn3zMMcf0b//sZz970UUX1f507373u/s3nnDCCfvss0/tzwVA56688so///M/799+/PHHn3baaV3sEdRDACBvv/M7vzNw+2/8xm98//vfr/GJLr744htvvLF/+6/+6q/W+CwAJOK222775V/+5f7tO+2007vf/e6Bn0EEuRAAyNsv/uIvDrwD59577/3lX/7lJ598spZnue+++84999z+7YcffvgZZ5xRy1MAkI477rjjxBNP3LJlS/+P3vSmN/kCYHInAJC9d73rXQM/DuhjH/vYG9/4xuqPv3379l//9V//3ve+1/+jt7/97TvttFP1pwAgHTfffPO6deu++c1v9v/oZ3/2Z9/ylrd0sVNQJwGA7K1Zs+btb3/7wB/99//+39/0pjdVfPxzzjnnwgsv7N/+8z//89PT0xUfHIB0bN++/T3vec9zn/vc73znO/0/Pfzwwzdt2qTvQwF8EzAl2L59++mnn37FFVcM/OlZZ531p3/6pytXrhz3Ybdu3fqbv/mb73vf+/p/tGrVqptuuumQQw6ZaH8BSO6bgK+++uo3velNN9xww8CfHnDAAddee+3hhx8+8eNDOgQACvHAAw/83M/93MD36c61bf7wD//w1FNPHf0BP/3pT7/61a++7bbb+n+0bNmyj33sYyeccEKF/QUgiQDwla985fLLL/+Lv/iLm2++eaF/c9hhh33iE5/wve8UQwCgHPfcc8/zn//8r33tawv9g+OOO+7cc8897bTT9thjj4X+zQMPPHDFFVe8853v/Nu//duB/2Dp0qUbN24c+NEQAHQbAGZnZ4f8L0888cRjjz22devWLVu23HXXXbfddtvf//3fL/qRcc973vMuueSSAw88sPIuQyoEAIpyzz33nH766Qut3efssssuz33uc5/5zGc+/elP32uvvXbeeectP/bd7373+uuvv/nmm4d8dtDOO++8cePGV7ziFc3sPgCjauGDOJcuXfqGN7zhbW9728CPmoB8CQCU5pFHHvm1X/u1D3zgA7U/8gEHHHDJJZccf/zxtT8yAKkFgJ/5mZ/5X//rfx177LGNPgt0wqcAUZoVK1a8//3vv/TSS1evXl3jw/7SL/3SLbfcYvUPULx169Zdfvnlf/u3f2v1T6lMACjW1q1b3/Wud73jHe/4wQ9+UOVxXvSiF731rW997nOfW9+uAZDcBGDNmjVnnHHGK1/5yjVr1tT7yJAaAYDCPfLII5deeun73//+a6655vHHHx/9f/zJn/zJl770pa961aue8YxnNLmDALQUAJYuXbps2bJdd9115cqVe++99/7773/ooYceeeSRa9euXbdu3QEHHNDMnkJyBACi2Lp163XXXXfttdd+5Stfue222773ve899NBDW7du3b59+4oVK1auXHnggQcecsghRx555DHHHHP88ccfdthhXe8yAED9BAAAAAjEm4ABACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAlkyPT3d9T4AAAAtMQEAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgECWDf/x7MZb29oTaMPM2WuH/NQBT7RjfginA4VR/4lmZuFj3gQAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAhEAAAAgEAEAAAACEQAAACAQAQAAAAIRAAAAIBABAAAAAsk+AMycvbbrXQCCUn+65fUHujKTef1ZNlXK32B2461d7wgQRe6lvxjqP9CymSLqf/YTgF7dnzl7bRl/EiBlO5Ya685uqf9Am2YKqv8lTAB2pBsENMQSM3HqP9CQmeLqf/YTgIHlXjcIqNHAkmKhmQL1H2jUTKH1v7QJwI50g4CKLCUzpf4DFc0UXf9LmAAMr/K6QcAEhpcOK8t0qP9AvWYC1P+SJwA70g0CRmTJWBj1HxjRTJj6X8gEYMTirhsEVC8RlpKpUf+BimaC1f8oE4Ad6QYB81gaBqH+A/PErP9FBYDZjbeO/ld0GQAmqPuKRprUf2AsM7Hrf1EBYAIuAxBTzJYPO1L/IaYZ9b+k9wDMmayUuzcU4qhyvlsspkz9B4ZT/3uiTwB2VMzXOwMDWeexEPUfyqb+Fz4BqKV8awhBYWo5qS0N06f+A/Oo/wOZACzI7aFQAIs5JqD+QwHU/1gTgOFVe8OqTWM9lG4QZGrck3d4cbAWzIX6D6j/iwo3AThvy/q5P/N5W9aP/n/pBkFGxl20TVATyJH6D8VT/6MHgEU/E9plAMozWelflLM+L+o/BKT+j6XYADBKE8hlAIpRsfQHbP/EpP5DedT/CZQcAEb/YkiXAchXQ12fHqd5jtR/iED9n1jJAWDEJlCPywDELP0x2z9hqf9QAPW/osIDwOhNoB6XAUhf012fHud1vtR/KJL6X4vCA8C4TaAelwEIUvrDtn8iU/8hR+p/jcoPABM0gXpcBiBg16fHiZw79R/KoP7XrvwAMHETqMdlAEot/ZHbP8Gp/5AF9b8hIQJAlSZQj8sAROj69Dhzy6D+Q6bU/0aFCADVm0A9LgNQTOkP3v5B/Yc0qf8tiBIAamkC9bgMQJFdnx6naknUf8iF+t+aKAGgxiZQj8sA1GiCJVqV0q/9g/oPiVD/2xcoANTbBOpxGYC8Sv+inJvlUf8hTep/VwIFgCaaQD0uA5BR6df+oUf9h06o/92KFQAaagL1uAxApl2fHidjqdR/SIT6n4JYAaDRJlCPywCkXPq1f5hH/Yd2qP/pCBcAmm4C9bgMQGqlf1HOvrKp/9AV9T814QJAO02gHpcBSKr0a/8wkPoPDVH/0xQxALTWBOpxGSCsdEr/opxuEaj/0Br1P2URA0DLTaDql4GYhya5S7D0a/8whPoPdVH/07d0KqQO6+lkh/jM2Wtb7lrBxCY7XLtq/MyxxopD/YfmqP+5MAFotQk0cStojrkwiZtsmdJO6df+YVHqP0xM/c9L3ADQ/p2g87gMUJKUS/+inE3RqP9QI/U/R3EDQLdNoB6XAXKXRenX/mFE6j+MTv3PV+gA0HkTqMdlgBxlUfoX5fSJSf2HKtT/3IUOAIk0gXpcBshFXqVf+4exqP8whPpfhugBIJ0mUI/LACnLq/QvyvkSmfoPY1H/SxI9AKTWBOpxGSA1mZZ+7R8moP7DjtT/8ggAKTaBelwGSEGmpX9RThDUfxhO/S+VAJBuE6jHZYCu5F76tX+YmPpPcOp/2QSA1JtAPS4DtCn30r8oZwRz1H+YR/2PQADIownU4zJAoyZeCSV1mszR/qEi9Z9Q1P9QBIAsuQxQu5JKPxRM/ad26n9AS7vegVQMqYnJ5sgNqzZNdu7NnL02/ZE3rZn4eJj4CGzB8NPWGogdqf+Epf6HZQKQPd0gJqbrA1lT/5mY+h+cCUDeTaAe3SDGUmTXp0f7h3Gp/8Sh/mMCUBrdIBal6wNFUv9ZlPpPjwlAOU2gHt0gAnZ9erR/mIz6r/4XTP1X/+cxASiWbhA9uj4QivpPj/rPQCYAZTaBenSDggvS9enR/qEK9X+O+l8G9X9H6v88JgAh6AYFpOsDqP8xqf8sygSg/CZQj25QENG6Pj3aP1Sn/s+j/udF/R9I/e9nAhCOblDBdH2AIdT/gqn/jEUAGGx2460LnUvnbVlfwNlS8TLgSpAapV/7h7qo/wtR/9Ok/qv/ExAAQpv4MqAhlA6lH5iA+l8A9Z+JeQ9AuDtB673zz+2hHQp7r2c/7R/qpf6PQv3vkPrfo/5PxgSA/0c3aKFuSoK/l64PUCP1PyPqP7VYMj09PeTHTukhZ1rB51KVFlfix0yN/apOflOlv5/2T0PHjJdO/S/smBl+LiS+8+r/QOr/xMeMCQAD6AZNdl41+lsr/UAL1P8Eqf/UzgRgcTGbQKV2g1q7Y7XG313pH0L7Z1EmAFWo/xP/vwkePzlOANT/IdT/RZkAMDndoOpn3WSvQJWsEqH0A01T/7ui/tM0E4CRBG8CldQN6vwzK0Z5HZT+EWn/jMIEoCL1P0j9z2Inh3NApvbX7JwJAPXQDapu+DfpKP1AmtT/pqn/tMkEYFSaQGV0gzqfACz0aij949L+GZEJQHXqf4T6n+yODecI7Kd29ZgAUD/doLoo/UBe1P+6qP90xTcBjyrOF0OOxbdIdqW8b3Mci/YPbVL/B1L/q6jyCqj/Q36q/o/IBIAaFNMN6r8jbvPmzVOJiVz3gdQUU/9bo+tPCgSAMcxuvHWh8/a8LeudlkVeBhZ6k0wnwcAxNkf7h/ap/wHrf+0s/atT/+siAFCzIJeBlmcFSj+QviD1fwKW/qTGpwCNzcdBZP1JEcOr8PDTYXQNhQEHmPbPBHwKUI3U/4LrfydPOpyDah71f1w+BYhuhO0G7RgkagwDc6+kSwKQvrD1v8fSn5T5FKCx+TiIcQX/pIjp/6+uBzxvy/qwR5r2D91S/8cVs/77hJ8mqP/1MgGgJbpBvQxQy0zA+w6BXMSp/7r+5MIEYBKaQJ0UuHy7QQ3NBKKNArR/SIH6P7Gy63/FPbT6H079r50JADm1grLrBrUwE/DGACAXRdb/islE9aYTJgAT0gSqqOJtjul3g8ZSfSBQ/FGn/UM61P+Kiqn/1bv+Vv+jUP+bYAJAl4rsBk1sLgNMPA0wCgAyknX91/Und74HoBKfCV2j6p2zUQ7Xdr4HoBZV7gsq7PDT/qnC9wA0RP0vrP6PeMBb+rdM/a/C9wBQfjeo84ZQUgMBnxEEZCSL+m/pT0m8B6ASd4LWrvo9kencHtrt2wOKOQK1f0iT+h+k/s89pnv9O6H+N8cEgBRl0Q1q0/T09ASjAO8KALKTTv2vniWUX5JlAlCVJlC0blBXYo4CtH9Imfpfav2vfu3Q9a9O/W+UCQCpS6cblO8bA7wlAMhR+/Vf158gfApQPXwcRDuabqol9SlAi5rgpqC8jkbtn1r4FKCmqf/tSH+o4s9dI/W/6erkFiByYqhaMa6kfwUFyK7+p7xvMJAAUA93grZJqa3yxoBcDkjtH3Kh/keu/6ntTxnU/xYIAORK2e0pNQMAJFv/U9gHmJgAUBtNoE4owZONAs7bsj7lw1L7h7yo/6Hqv+tOo9T/dggAlEA5nmMUAETTZv13raEYAkCdNIG6pTSXkQG0f8iR+l92/Xd9aYf63xoBgNIo0xPcDtTk7gBkXP9dUyiSANAey6w2KdmZZoB09gRq5MDOsf67jrTMadImAaBm5lNJCV6+M80AQzi/SJnjs5j6H/zakSbnV70EgFZlscYqT+RSPtbtQJ0fn53vADTH4Z1F/Y98veiWE6RlAkDbIdUh3pXIZT2LDLDoU2v/kD71P9/6H/ka0Tn1v30CAISQRQYAAFogADRCE4gEpZwBtH8ohvoPY1H/OyEAQCApZwAAoB0CQFM0gUhTghlA+4fCqP8wIvW/KwIAhJNgBgAAWiMANEgTiGSlkwG0fyiS+g+LUv87JABAUGN9TRgAUAwBoFmaQBSQAZo7ULV/KJj6D0Oo/90SACC0zjMAANAyAaBxmkAkrqsMoP1D8dR/GEj975wAAJgDAEAgAkAbNIFIX8vvCdb+IQj1H+ZR/1MgAABjZADrFQDInQDQEk0gstBOBtD+IRT1H3rU/0QIAMDYLFkAIF8CQHs0gchC028G0P4hIPUf1P+kCADAfN4MAAAFEwBapQlE8Ayg/UNY6j/Bqf9JEQCAyVm1AEB2BIC2aQIR9s0A2j8Ep/4TlvqfGgEAWJA3AwBAeQSADmgCEXAOoP0D6j8xqf8JEgCAqqxaACAjAkA3NIEIdSOQ9g/0qP+Eov6nSQAAuv92MACgNcvaeyr+udmNt86cvXahn563Zf2GVZumkqdZ1a3NmzenszRf6KDV/oF51H+qy+I4Uf+TZQJAJelXn1Jt/rE2nzGdpAGkQP3vynlb1ktfVCQAdMmdoGSx9B89A/QftNo/MJD6T/FLf/U/ZQIAVWkCRVj6jy6jixNQkfrfmryW/qRPAOiYJhB5Lf3HuhFI+weGUP8peOmv/idOAKAGmkARlv6jy/FaBUxG/W9Opkt/siAAdE8TiLyW/iMOAbR/YFHqP0Uu/dX/9PkYUOqxYdWmrKtVUtJc94/FwQBxqP818krSDhOAJGgCkXjXv/aPBNX+gTnqP2V0/Xu0/7MgAFAbd4JGWPr3+FoAoEf9r6KYpT8ZcQtQKsr4YshFbdrU8W+xfn1yRTavdX8ttH9gR+p/2Ppf3rpf+z8XJgDUadGrVIL1t0PZdf3nMQQAetT/sej60y0BICHuBI0j96V/Fdo/0E/9j6Pgpb/2f0YEAGqmCRRq6W8IAPSo/2GX/mRHAEiLJlDBClv6T0b7Bxai/hcswtJf+z8vAgD10wSax9IfCEL9D7j0J0cCQHI0gUpSfenf+edm1HgXkPYPDKf+l6T60j/9+t+j/Z8dHwNKN18MuX79+oxK2wSqt/zLfn2AUqn/1aNa2a8PKRAAUhTkM6GLVMutPtmV/unp6UV/ce0fGIX6n69aRjTZ1X/t/0wJADQlWhMo5tIfoF+0+h926U++BIAsaQIlxdJ/xCEAUJ36nxRLf29NyZQ3ASeqjHlZ8R8HUcvH+2z6sanSDbmrAdiR+h/n430i1P8yjufymADkShOoW7r+QFfU/27p+vdo/+fLBCBdZYTm8ppAuv4L8a3AUBf1P026/jGP5CKZAGRME6hluv4VzZy91sUAaqH+t0zXv5/2f9ZMAJJWxmqpgCaQrj/QMvU/Ebr+wY/hUpkA5E0TqGm6/mPxWUDQGvW/abr+Q2j/584EIHVlBOgcm0C6/k3wWUAwOvW/K7r+1ZVx9BbMBCB7mkC10/UHsqD+107XfxTa/wUwAchAGTE6iyZQ9a7/XMun+Oo/hM8Cghqp/xl1/dX/wo7bspkAlEATKAWKPtA+9T8Foeq/9n8ZTADyUEaYzqIJNAEtn7F4GwCMRf1Pmfpf6hFbPAGgEBJ5J5T+gdwFBG1S/zsRs/472IohAGSjjEhdTBMoZukHOqH+J0X9L/5YjcB7AMrhTtB2qPtAatT/dgSv/9r/JTEByEkZwTrfJpCuT128DQDGpf53S/2Pc5QGIQAURTpviNI/Lm8DgJap/w1R/+c4wAojAGSmjHidURNI6QcSof63TP0PeHzG4T0ApXEnaF3UfSAv6n9d1P95tP/LYwKQnzJCdspNIF2fFngbAExA/W+a+h/5yAxFACiQpD4xpb9G3gYA7VP/J6b+L8RBVSQBIEtlRO2Um0AAaVL/SU0Zx2Q0AkCZ5HWAmNR/auRwKpUAkKsyArcmEMC41H/SUcbRGJAAUCypHSAm9Z9aOJAKJgBkrIzYrQkUlg8Cgomp/6SgjOMwJgGgZLI73fJBQNAV9Z+KHEJlEwDyVkb41gQCGJf6T7fKOALDEgAKJ8EDxKT+MzEHT/EEgOyVEcE1gQDGpf7TlTKOvcgEgPLJ8QAxqf9MwGETgQBQgjKCuCYQwLjUf9pXxlEXnAAQgjQPEJP6z1gcMEEIAIUoI45rAkXjqwCgOvWfNpVxvCEARCHT0wlfBQCdU/8ZkUMlDgGgHGWEck0ggHGp/7SjjCMNASAWyR4gJvWfRTlIQhEAilJGNNcEAhiX+k/TyjjGmCMAxCLfA8Sk/jOEwyOaJd6iB1lL/xTevHlz17sAAPwTAQAAAAJxCxAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAQCDLhv94duOtbe0JtGHm7LVd7wL/jCKT7DHvT1Pe33rDqk1VHv+8LetH/8ebNlV6riasX7++iR0e/rAMoch0WBMWCQAQimIElKri6p8qpqenp0LavHlz17vAYG4BAoDsNT3eHKv9H0qCsw5YlAAAAIXT/u+WRjipEQAAIG/a/90yBCA7AgAAlEz7PwWGACRFAACAjGn/p8AQoJ/MkzIBAACKpf2fDgviHfnYvW4JAACQK+3/dBgCkBEBAADKpP2fGkMAEiEAAECWtP9TYwhALgQAACiQ9n+aDAFIgQAAAPnR/k+TIQBZEAAAoDRNt/83z1rmTs4QgM4JAACQGe3/lBkCCDnpEwAAoCja/+kLvj72JQCdEwAAICfa/+kzBCBxAgAAlEP7PxfBhwB0SwAAgGw03f6nLoYApGxZ1zsAAKTS/h9+/0+m7f/16xO9qWnz5s3T09Nd7wURmQAAQB60/8e1/se6evawQwB3N6XPBAAASqD9n0XXf56AQwAfAZQCEwAAyID2fxZd/3nCDgFInAkAAGRP+z+jrv88AYcAdM4EAABSp/2fUdc/+BDAGwCyYAIAAHmL3P5Pdt0/ljhDAG8ASIQJAAAkTfs/u65/8CEA6TMBAICMBWz/57LuH0ucIQApMAEAgHRp/2fa9Y85BPAGgFyYAABAruK0/zNd94+l+CGANwCkwwQAACi56795dlMKSSbIEIAsmAAAQJb3/xTf/q/e9e/8Vwg1BHD/T0YEAAAgLaUu/Tdt2hThXibSJwAAQIpitv9rWR+nufqPMAQYwhsAkiIAAADdC7L0L3UI4P6fvAgAAJCcUO3/IEv/0ZU6BCAdAgAA0I2YS/9ShwBDuP8nNQIAAKQlQvs/5tK/1CGA+3+yIwAAAO2x9I85BCApAgAAJKTg9r+lf8FDgCHc/5MgAQAAaJalf8FDAPf/5EgAAIBUlNf+t/SvoowhwMzZaw0BUiMAAAD1s/SPMATQ/s/U0q53AAAorf1ffV27eXZT2av/UCvs4cc27TMBAAASEmrdn/UQoIxwEpMJAACU3/7PYs2t61/wOtsQICkmAABQvuH3/3Qu8ro/6yEAmTIBAICORW7/6/pnOgSYYJcMAdJhAgAAhUuz/W/d32MIQMtMAACgSwHb/7r+uQ8BJt4ZQ4BEmAAAQMmSav8nu+7XgCcUEwAA6Eyo9n+yq/9cJDIEqLgbhgApMAEAgGIl0v639C9GIiGEigQAAOhGhPZ/Ckv/6ZkkUlAtNm/ePD09PZWwueN2ePKcOXvt7MZbW9wp5hMAAKBMQxZhLazLLf3Lo/1fDO8BAIBw7f/iP+RnemZ9qav/lFfhveN20QPYOwG6ZQIAAAXqpP3f+bpf1z9m8GBcJgAA0Lby2v+6/m1Kcy0+77g1BEiZCQAAlKbN9n/n635d/xQiR46pNTITAABoVTHtf13/IEOAiZ/LECBZJgAAUJR22v8pLP1rfsC0P14zZRmlVuaYAABAe4pp/3cobNc/x1GDIUCaTAAAoBzdfvZ/06z7E1z9S605MgEAgJZo/09M1z9Noxy0hgAJMgEAgEIU2f637u9Kmh82Si1MAACgDdr/XXX9N6za5OXt9uYfQ4DUmAAAQAkKa//XtfSvY1/C0fsvngAAAI3T/m9z6e/1bMG4L/KGVZuGZNS5c2R2462V94uRCAAAkL0y2v+W/inwyT8RCAAA0CVrKUv/IKv/RYcAtEYAAIBmdfgGx/Tb/5b+6ej81n93AbVGAACAztSyeM20q2rpn6OKr7khQCIEAABokPZ/P0v/BCVy678hQDsEAADoRsD2v6V/mtpc/RsCpEAAAICmaP/3WPonq/Nb/+cxBGiBAAAAHYjT/rf0L2D1X++fwBCgcwIAADRC+9/SP3GdrP5HYQjQNAEAANpWfPvf0j993a7+DQG6JQAAQP3Ctv8t/bOQbO+/xxCgUQIAALSq1Pa/pX8uEnnXryFAhwQAAKhZtPa/pX+Rq//O/yiGAM0RAACgPYW1/y3985La6t8QoCsCAADUKUj739I/O6mt/kdhCNAQAQAAWlJG+7/i0j+dxWUoya7+DQE6IQAAQG3Kbv9b+mcq2dX/KAwBmiAAAEAbsm7/Z730D95gTn/1bwjQPgEAABpv/ze9tGqu/W/pn7X0V/+9Zx/yxzIEqJ0AAAB5aHk5a+kf58P+E7zzh0YJAABQg5La/5b+uctx9W8I0CYBAAAy0M661tK/ADmu/mmZAAAAVRXQ/rf0j7b07/yv1s8QoDUCAACkrtEFrqV/GXJf/dMmAQAAgrb/Lf2LUczq3xCgHQIAACStoZVuldW/pX86iln60yYBAABitf8t/YtR5OrfEKAFAgAApKveJa+lf9ilf+d/QZIiAABA+e1/S/+SFL/6NwRomgAAACWz9J9bLA5JaxkpfulPOwQAAEi0/b/QCnjE9r+lf0l94gmW/p3/HaswBGiUAAAApZl46d/5etHSv66lfwp/TZIlAABAOe1/S/+Slv4BG/87MgRojgAAACWw9C9sOajxT3MEAADIu/1v6W/pn87ftF6GAA0RAAAgV8GX/oUt/qqs+1P4m5IRAQAA8mv/W/pPFcTSfwhDgCYIAACQE0v/qYJUXPqn8GclRwIAAOTR/s936V/L6r+kpX/1dX8if9Z2GALUTgAAgAxMtvpPYY1o6V/vuj+RPytZEwAAIPX2f6ZrREv/etf96fxl22cIUC8BAACKksIC0dK/9nV/In9ZyiAAAEAl6bT/U1ggBl/6177oT+cvm/gQgLEIAABQ6f6fFKSwQAy79G9o0c9Y3AU0FgEAADJu/1v6R1juz73CKfytu2UIUBcBAACybP+nsBwseOmfYF9fDBjOEGB0AgAAZNb+T2EJWN7SP8EV/0DBY4AhQC0EAADIo/2fyJqvvKV/joLHgIUYAoxIAACA1Nv/iazzLP3rNfdqVEmYMWOAIUB1AgAApNv+T2RtZ+lfo3kvhRhQL0OAUQgAAJBi+z+R9Zylf12Gvw5iwFgMASoSAAAgrfZ/Ims4S//qxn0FxIBaGAIsSgAAgFTa/4ms2yz9u/3de48wcRKIEAMMAaoQAACg+/Z/Ims1S/+kfuuKA4EIMWAhhgDDCQAA0GX7P5H1maV/sr+pGLAQQ4CJCQAA0E37P5E1maV/Fr+XGDAuQ4AhBAAAGFWN66cUlmKW/tn9ImLAPIYAkxEAACCtz/5vgaV/1sSAERkCLEQAAICRlLFgsvQvhhgwxxBgAgIAAIRo/1dcJFn3p0kMGM4QYCABAAAWl/UKydK/eMFjgCHAuAQAACi2/W/pH0rwGLAQQ4B+AgAALCLHJZGlf1gxY4AhwFgEAAAoqv1v6U/YGLAQQ4B5BAAAGCajNZClP5FjgCHA6AQAAMi+/W/pzxChYsBCDAF2JAAAwILSX/RY+jOiCDHAEGBEAgAA0WXa/rf0ZwIRYsBCDAF6BAAAGCzZVY6lPxUVHAMMAUYhAAAQWl7tf0t/alRwDFiIIcAcAQAABkhtWWPpT0PKiwGGAIsSAACIK4v2v6U/LegdJ5OdFAnGgIXMGAIIAADQL5F1jKU/eQ0E0okBhgDDCQAABJVy+9/Sn26VEQMWMhN+CCAAAMA/0+3CxdKfdGQdAwwBhhAAAIgowfa/pT9pyjoGLGQm9hBAAACAf9LJSsXSn/TlGAMMARYiAAAQTjrtf0t/8pJjDFjITOAhgAAAAP9Pm0sTS3/ylVEMMAQYSAAAIJbO2/+W/pQhoxiwkJmoQwABAACm2lmLWPpTnvRjgCFAPwEAANpQZQli6U/ZMaDzUUA0S7veAQBoz0ILlEbXH+dtWT/x6n92461W/+Ri4sO1yjkyiiEn+EzX9wR2wgQAAJpSZd1f975A6tOARN4YEIEJAABRtNn+n7ijqeVPGVKbBhgC7MgEAADqpOsPPaYBaTIBACCEFtr/uv6Q8jTAEKDHBAAAqtL1h0WZBqTDBACA8jXX/tf1h4ymAYYAc0wAAGASuv4wMdOAbpkAAFC42tv/uv6Q7zRggyGACQAAjE7XH2rXOzvGXX+bBkzMBACAktXV/tf1h6ZNdrJMcG5uCD8EMAEAgGF0/SH9tweYBozFBACAYlVs/+v6Q6nTgA2xhwAmAAAwn64/pMA0oCEmAACUabL2v64/BJkGbAg8BDABAIB/pOsPKTMNqJEJAADR2/+6/hBzGrAh6hDABACAuHT9IUemARWZAAAQsf2v6w+5q2UasCHkEMAEAIBYdP2hJKYBExAAAIjS/rf0h1JVjAHnLVAcZs5eW+TpLwAAEMLEN/w0sC9AcjEgFO8BAKAcNd6z615/yFS9J+9Mie8EMAEAgH/Guh/CTgOCMAEAoBDVr/S6/lCYWk7qmeJShAkAANFZ9EPZTAPmMQEAoASTXdq1/CGOKuf7TFnhwQQAgIis+yGmWdMAAQCAAox1Lbf0B2b/fx0YvXqU9J0AAgAAURRz8QbqMhtyIOA9AADkbZQrt3v9geolYqaUnGACAEDJrPuBEc2GmQaYAACQsSGXal1/YAKzQ0tHGfHABACA0lj3AxXNFj0NMAEAIFf912Zdf6BGs4NKSgGpwAQAgBJY9wMNmS1uGmACAECWehdjXX+gBbM7lJrcw4AJAAC5su4HWjZbxDTABACALFn9A12Zzbz+CAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQiAAAAACBCAAAABCIAAAAAIEIAAAAEIgAAAAAgQgAAAAQyJLp6emu9wEAAGiJCQAAAAQiAAAAQCACAAAABCIAAABAIAIAAAAEIgAAAEAgAgAAAAQiAAAAwFQc/xcDgx2+SqSbjgAAAABJRU5ErkJggg=="
},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:9)_119
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is rotate the shape clockwise 90 degrees\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is Colorize the top layer of the original shape with the color green.\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is Stack the original shape on top of the {'layer1': 'SgSgSgSg'}.\nthe 9th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:9)_181
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'WbWbWbWb'}.\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is Colorize the top layer of the original shape with the color purple.\nthe 4th action is Stack the original shape on top of the {'layer1': 'RwRwRwRw'}.\nthe 5th action is Colorize the top layer of the original shape with the color yellow.\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is Colorize the top layer of the original shape with the color white.\nthe 8th action is Stack the original shape on top of the {'layer1': 'WrWrWrWr'}.\nthe 9th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_86
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is Colorize the top layer of the original shape with the color cyan.\nthe 4th action is Colorize the top layer of the original shape with the color cyan.\nthe 5th action is Cut the right side of the shape\nthe 6th action is Cut the right side of the shape\nthe 7th action is Cut the right side of the shape\nthe 8th action is Colorize the top layer of the original shape with the color yellow.\nthe 9th action is Stack the original shape on top of the {'layer1': 'RcRcRcRc'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
B
|
shape(step:9)_211
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is Stack the original shape on top of the {'layer1': 'WuWuWuWu'}.\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is Cut the right side of the shape\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is Stack the original shape on top of the {'layer1': 'SpSpSpSp'}.\nthe 8th action is Cut the right side of the shape\nthe 9th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_77
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color blue.\nthe 2th action is Stack the original shape on top of the {'layer1': 'WbWbWbWb'}.\nthe 3th action is Colorize the top layer of the original shape with the color white.\nthe 4th action is Colorize the top layer of the original shape with the color green.\nthe 5th action is Stack the original shape on top of the {'layer1': 'CyCyCyCy'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'WpWpWpWp'}.\nthe 7th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\nthe 8th action is rotate the shape counterclockwise 90 degrees\nthe 9th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_128
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is Cut the right side of the shape\nthe 3th action is Colorize the top layer of the original shape with the color purple.\nthe 4th action is Stack the original shape on top of the {'layer1': 'WuWuWuWu'}.\nthe 5th action is Cut the right side of the shape\nthe 6th action is Stack the original shape on top of the {'layer1': 'CwCwCwCw'}.\nthe 7th action is rotate the shape counterclockwise 90 degrees\nthe 8th action is Cut the right side of the shape\nthe 9th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
D
|
shape(step:9)_1
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is Stack the original shape on top of the {'layer1': 'ScScScSc'}.\nthe 3th action is Stack the original shape on top of the {'layer1': 'WgWgWgWg'}.\nthe 4th action is Colorize the top layer of the original shape with the color blue.\nthe 5th action is Cut the right side of the shape\nthe 6th action is Cut the right side of the shape\nthe 7th action is rotate the shape clockwise 90 degrees\nthe 8th action is rotate the shape clockwise 90 degrees\nthe 9th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_276
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape clockwise 90 degrees\nthe 2th action is Stack the original shape on top of the {'layer1': 'RcRcRcRc'}.\nthe 3th action is Cut the right side of the shape\nthe 4th action is Stack the original shape on top of the {'layer1': 'CuCuCuCu'}.\nthe 5th action is rotate the shape clockwise 90 degrees\nthe 6th action is Stack the original shape on top of the {'layer1': 'RgRgRgRg'}.\nthe 7th action is Stack the original shape on top of the {'layer1': 'CbCbCbCb'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'CpCpCpCp'}.\nthe 9th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_388
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is Stack the original shape on top of the {'layer1': 'ScScScSc'}.\nthe 3th action is Stack the original shape on top of the {'layer1': 'RcRcRcRc'}.\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is Stack the original shape on top of the {'layer1': 'RpRpRpRp'}.\nthe 6th action is Stack the original shape on top of the {'layer1': 'CcCcCcCc'}.\nthe 7th action is Stack the original shape on top of the {'layer1': 'ScScScSc'}.\nthe 8th action is Stack the original shape on top of the {'layer1': 'WwWwWwWw'}.\nthe 9th action is rotate the shape clockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_270
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is rotate the shape counterclockwise 90 degrees\nthe 2th action is Cut the right side of the shape\nthe 3th action is Stack the original shape on top of the {'layer1': 'WcWcWcWc'}.\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is Colorize the top layer of the original shape with the color green.\nthe 7th action is Cut the right side of the shape\nthe 8th action is Colorize the top layer of the original shape with the color yellow.\nthe 9th action is Stack the original shape on top of the {'layer1': 'SrSrSrSr'}.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:9)_267
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Colorize the top layer of the original shape with the color white.\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is rotate the shape clockwise 90 degrees\nthe 5th action is Stack the original shape on top of the {'layer1': 'RcRcRcRc'}.\nthe 6th action is rotate the shape counterclockwise 90 degrees\nthe 7th action is Colorize the top layer of the original shape with the color white.\nthe 8th action is rotate the shape counterclockwise 90 degrees\nthe 9th action is Colorize the top layer of the original shape with the color purple.\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
A
|
shape(step:9)_258
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Stack the original shape on top of the {'layer1': 'RwRwRwRw'}.\nthe 2th action is Cut the right side of the shape\nthe 3th action is rotate the shape counterclockwise 90 degrees\nthe 4th action is rotate the shape counterclockwise 90 degrees\nthe 5th action is Cut the right side of the shape\nthe 6th action is rotate the shape clockwise 90 degrees\nthe 7th action is Cut the right side of the shape\nthe 8th action is Stack the original shape on top of the {'layer1': 'WgWgWgWg'}.\nthe 9th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
C
|
shape(step:9)_254
| 9
|
You are a player of the game Shapez, and your goal is to transform a set of raw shapes into a target shape through a series of operations.
First, I'll introduce the game's shape notation:
Each shape is represented by two characters, where the first character denotes the color, and the second character denotes the shape type. The color and type correspond as follows:
C: Circle; R: Rectangle; W: Windmill; Fan; S: Star; r: Red; g: Green; b: Blue ; y: Yellow; p: Purple; c: Cyan; u: Uncolored; w: White; --: Empty (No shape or color)
A single layer's shape code consists of the shape codes for four quadrants, in the following order: 'Quadrant 1, Quadrant 2, Quadrant 3, Quadrant 4'
For example, 'Su--Ry--' indicates that Quadrant 1 'Su' has an uncolored star, Quadrant 2 '--' is empty, Quadrant 3 'Ry' has a yellow rectangle, and Quadrant 4 '--' is empty.
A shape can consist of multiple layers, with each layer represented by a shape code of up to four quadrants. The layers are arranged from bottom to top, as follows:
{'Layer 1': 'Shape code for Layer 1', 'Layer 2': 'Shape code for Layer 2', 'Layer 3': 'Shape code for Layer 3', 'Layer 4': 'Shape code for Layer 4'}, the layer with the larger number is on the top.
Note that not every shape has a fixed number of layers; some shapes have only one layer, while others may have two, three, or four layers. Note, each shape has a maximum of four layers.
The whole shapes follows specific physical rules:
1.If a layer contains only one quadrant with a shape, that quadrant must have a corresponding shape in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' is the only shape in Layer 2, so quadrant 3 of the layer below (Layer 1) must also contain a shape, which in this case is 'Ry'. Conversely, in {'Layer 1': 'SuRy----', 'Layer 2': '------Wp--'}, quadrant 3's 'Wp' in Layer 2 is not supported by a shape in the corresponding quadrant of Layer 1, which is blank ('--'). This does not comply with physical laws.
2.If a layer contains two non-adjacent quadrants with shapes, those two quadrants must also have corresponding shapes in the layer below. For example, in {'Layer 1': 'Su--Ry--', 'Layer 2': 'Sb--Wp--'}, quadrants 1 ('Sb') and 3 ('Wp') are non-adjacent shapes in Layer 2. Therefore, quadrants 1 and 3 in Layer 1 must also contain shapes, as seen in 'Su' and 'Ry'. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'Sb--Wp--'}, quadrant 1 in Layer 1 is blank ('--'), which does not conform to physical laws.
3.If a layer contains two adjacent quadrants with shapes, then at least one of those quadrants must contain a corresponding shape in the layer below. For example, in {'Layer 1': 'Su------', 'Layer 2': 'SbWp----'}, quadrants 1 ('Sb') and 2 ('Wp') are adjacent shapes in Layer 2. Therefore, either quadrant 1 or quadrant 2 in Layer 1 must contain a shape, as shown by 'Su' in quadrant 1. Conversely, in {'Layer 1': '----Ry--', 'Layer 2': 'SbWp----'}, both quadrants 1 and 2 in Layer 1 are blank ('--'), which does not comply with physical laws.
4.If a layer contains three quadrants with shapes, then at least one of those quadrants must have a corresponding shape in the layer below. For example, in {'Layer 1': '--Su----', 'Layer 2': 'SbWpCb--'}, quadrants 1 ('Sb'), 2 ('Wp'), and 3 ('Cb') are the three shapes in Layer 2. Therefore, at least one of quadrants 1, 2, or 3 in Layer 1 must contain a shape, as seen in quadrant 2 with 'Su'. Conversely, in {'Layer 1': '------Ry', 'Layer 2': 'SbWpCb--'}, all quadrants in Layer 1 are blank ('--'), which does not comply with physical laws.
Next, I’ll explain the available operations and the rules for each, please remember that all shapes obtained after operations must follow the laws of physics.:
Cutting (removes shapes in Quadrants 1 and 2 from each layer of the input shape, as well as cut the right side of the shape, such as {layer_1: 'SuSuSuSu'} will be cut as {layer_1: '------SuSu'});
Rotate clockwise by 90° (rotates all shapes clockwise by 90°, so Quadrant 1 becomes Quadrant 2, Quadrant 2 becomes Quadrant 3, Quadrant 3 becomes Quadrant 4, and Quadrant 4 becomes Q uadrant 1), such as {layer_1: 'CgScScCg'} will be rotate clockwise as {layer_1: 'CgCgScSc'});
Rotate counterclockwise by 90° (rotates all shapes counterclockwise by 90°, so Quadrant 1 becomes Quadrant 4, Quadrant 4 becomes Quadrant 3, Quadrant 3 becomes Quadrant 2, and Quadrant 2 becomes Quadrant 1), such as {layer_1: 'CgScScCg'} will be rotate counterclockwise as {layer_1: 'ScScCgCg'});
Stacking (stacks one shape on top of another, such as stack {layer_1: 'SuSu---—'} on the top of {layer_1: 'RbRbRbRb'}, the result will be {layer_1: 'RbRbRbRb', layer_2: 'SuSu---—'});
Coloring (input a shape and a color; change the color of every shape in each quadrant of the top layer to the given color, such as colorize {layer_1: 'SuSu---—', layer_2: 'RbRbRbRb'} with color 'p', the result will be {layer_1: 'SuSu---—', layer_2: 'RpRpRpRp'});
Great, now you have become a Shapez master. From now on, you will answer my questions, and you should output the letter corresponding to your choice, and why you choose it as detailed as possible.
|
[
{
"image_url": null,
"text": "This is the original shape, with its image:.",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAgAAAAIACAYAAAD0eNT6AAAPwklEQVR4nO3dUY7cyLVFUamhCWhqAuhBKgFPrYbQRtjORqqkyiKZQTLinrV+3o/dT4DVuJuHLOnrsix/fwHY4Xa7fb361wDs899/eUUAcAbBAOMQAMAwBAKc559/2UQAMDJxAH0JAGBaogD2++VfHhEAzE4UwDoCAChPFMDvfvuXQgQA1QkCEAAAgoBIf/xNLwKAZIKABC8HwPcfP7v+goBjvP37X6v+c8uyrP5n3m63L9WJAar68De2CIBajgiArWYPBjFAJd+u/gUAOT6Li9ED4f2DkSBgZk9/81oBoI4RFoC9Rg+DRgwwGwsAMLw/RcloUXB/YBICzOLT36hWAKhh5gVgrdGiQAwwMgsAUMZoS8HjA5QYYDSrfkNaAWB+CQvALCuBGGAEFgAgyvvAuSIIfC/ACFb/5rMCwNwsAOOuA0KAK1gAAC5eB3wrwBU2/UazAsC8LABzrQNCgKNZAAA2htEZMeA7AY62+TeWFQDmZAGYfxkQA/RkAQCYZBmwCtDTrt9EVgCYjwWg3jIgBHjFXy/9twH4MKSOjqn2MLblgQwe7a5HKwDMxQJQfxWwCLCFBQCgyCpgEWCLl2rRCgDzsADkrQIWAZ6xAAAUXQUsAjzzch1aAWAOFoA5WAQ4iwUAIGgROOQfzJS61KAVAMZnAZjXEauANQALAEDgKuD7ALoVoBUAxmYBqMMiQA8WAIDJHLUIdP0HMryuxWcFgHFZAOrqvQhYAzJYAAAm13sR8H1Ahr+uqsa1TyMAXBcC3f5hDMcCAFCMNYBLAsAKAHA9awCfsQAAFNYzBKwBtRwSAFYAgNoh0OUfxKUsAABBrAEcHgBWAIAxWQNoLAAAoXqFgDVgTocGgBUAYHzWgEwWAAC6rgFdfkHMHwBWAIB5eCWQwwIAwC+sARlOCQArAEBmCIiAcVkAAHiqRwQIgeAAsAIAzMsrgXosAACs4pVALacGgBUAYH5eCdRgAQBgM2vA/E4PACsAQB0iYF4WAABeIgLmtPppvLct/4N///Hz2F8MBFi7qPX6c+HJdLvdXv3vX3aX0lgAAOjGGjCPywLAtwAANYmAOVgAABjupwREQPEAsAIA1CYCxmUBAOBQImBMQ3xt6ScC4Hh+CoDZf0rATwj0ZQEA4DTWgHEMEQC+BQDIIQLGMEQAAJBFBFxvmACwAgBkEQHXGiYAAMgjAq4zVABYAQDyvPKHBomAIgEAQC4REB4AVgCAXCIgOAAAyCYCggPACgCQTQSEBgAAiIDQALACACACAgMAABoREBgAVgAAGhEQFgAAcCcCwgLACgDAnQgICgAAeCQCggLACgDAIxEQEgAA8J4ICAkAKwAA74mAgAAAgJ4RkG6qALACANArApbwFWCqAACAj4iA4gFgBQDgIyKgcAAAwDMioHAAWAEAeEYEFA0AAPiMCCgaAFYAAD7jRwQLBgAAHGEJWQGmDgArAACf8SqgYAAAwBoioGAAWAEAWEMEFAsAAFjLR4HFAsAKAMBREbAUXQFKBAAAbLGIgDoBYAUA4EhLsQgoEwAAsMUS/j1AqQCwAgCwxRL8KqBUAADAVktoBJQLACsAAEdbCkRAuQAAgK2WwO8BSgaAFQCArZawVwElAwAA9liCIqBsAFgBADjDMmkElA0AANhjCfkeoHQAWAEA2GMJeBVQOgAAYK+leASUDwArAAAEBgAA7LUUXgEiAsAKAMBeS9EIiAgAACA0AKwAAOy1FFwBYgIAAF6xFIuAqACwAgDwiqXQHxIUFQAAcKZl4BUgLgCsAAC8osqrgLgAAABCA8AKAED6ChAZAACQ/kFgbABYAQA402grQGwAAEDyq4DoALACAJD6KiA6AADgbKOsAPEBYAUAIHEFiA8AAEhcAQSAFQCAwBVAAADABRFw9QogAP7PCgDA2a6MAAEAAIGvAgTAAysAACkrgAAAgMAVQAC8YwUAIGEFEAAAELgCCIA/sAIAUP3HAgUAAAQSAB+wAgBQeQUQAAAQSAA8YQUAoOoKIAAAIJAA+IQVAICKK4AAAIBAAmAFKwAA1VYAAQAAgQTASlYAACqtAAIAAAIJgA2sAABU+YuCBAAADOyo1wACYCMrAAAVCAAACPwYUADsYAUAYHYCAAACVwABsJMVAICZCQAACPyRQAHwAisAAGfq+RpAAABA4AogAF5kBQBgxhVAAABAIAHQgRUAgNl+JFAAAEAgAdCJFQCAmT4GFAAAMKFXXwMIgI6sAADMQgAAQOBrAAHQmRUAgBleAwgAAAhcAQTAAawAAIxOAABA4GsAAXAQKwAAI78GEAAAELgCCIADWQEAGJUAAIDA1wAC4GBWAABGfA0gAAAgkAA4gRUAgNFeAwgAAAgkAE5iBQBgpO8ABAAABL4GEAAnsgIAMAoBAACBrwEEwMmsAACM8BpAAABAIAFwASsAAFe/BhAAABBIAFzECgDAld8BCAAACCQALmQFAOCq7wAEAAAEvgYQABezAgBwBQEAAIEEwACsAACc/R2AAACAwO8ABMAgrAAAnEkAAEAgATAQKwAAZ30HIAAAIPA7AAEwGCsAAGcQAAAQSAAMyAoAwNEEAAAEfggoAAZlBQDgyA8BBQAABBIAA7MCAHAUAQAAgQTA4KwAABzxIaAAAIDADwEFwASsAAD0JgAAIJAAmIQVAICeBAAABH4IKAAmYgUAoNeHgAIAAAIJgMlYAQDoQQAAQCABMCErAACvEgAAEEgATMoKAMCenwS4/yigAACAQAJgYlYAAPYSAAAQSABMzgoAwB4CAAACCYACrAAAbCUAACCQACjCCgDAsuHPAhAAABBIABRiBQBgLQEAAIEEQDFWAADWEAAAEEgAFGQFAOAzAgAAAgmAoqwAADwjAAAgkAAozAoAwEcEAAAEEgDFWQEAsiwr/z4AAQAAgQRAACsAAO8JAAAIJABCWAEAeCQAACCQAAhiBQDgTgAAQCABEMYKAEAjAAAg0LerfwFcswIsy/L3mv+sFQCgJgEA/OJ2u139SwBO4BVAqC3fAgBQjwAAgEACIJgVACCXAACAQAIgnBUAIJMAAIBAAgArAEAgAQAAgTz5QZC1fwIkUJ8/CRD4zfcfP6/+JQAvWPPHuHsFAACBBAAABBIAABBIAABAIAEAAIEEAAAEEgAAEEgAAEAgAQAAgQQAAIT9KYCNAACAQAIAAAIJAAAIJAAAIJAAAIBAAgAAAgkAAAgkAAAgkAAAgEACAAACCQAACCQAACDs7wG43W5fBQAABBIAABBIAABAIAEAAIEEAAAEEgAAEEgAAEAgAQAAYX8GQPu/AgAAAgkAAAgkAAAgkAAAgEACAAACCQAACPkJgEcCAABC3H8EsBEAABBIAABAIAEAAIEEAACEfQDYCAAACPsAsBEAABBIAABAIAEAAIEEAACEfQDYCAAACPsAsBEAABBIAABAIAEAAIEEAACEfQDYCAAACPsAsBEAABBIAABAIAEAAGHv/xsBAABh7/8bAQAAgQQAAAQSAAAQ9v6/EQAAEPb+vxEAABBIAABA2PzfCAAACCQAACDs/X8jAAAgkAAAgLD3/40AAICw+b8RAAAQSAAAQNj83wgAAAib/xsBAACBBAAAhM3/jQAAgEACAADC3v83AgAAwub/RgAAQCABAABh838jAAAgbP5vBAAAhD39NwIAAAIJAAAIm/8bAQAAYfN/IwAAIOzpvxEAABBIAABA2PzfCAAACJv/GwEAAIEEAABM9vT/6vzfCAAACCQAAGAiPZ7+GwEAAEEf/90JAAAIe/pvBAAAhD39NwIAAAIJAAAI+dG/RwIAAAIJAAAIe/pvBAAABBIAADCwI57+GwEAACE/+vdIAABAIAEAAEEf/90JAAAIJAAAIOzpvxEAABBIAABA2NN/IwAAIJAAAICwp/9GAABAIAEAAGFP/40AAIBAAgAAwp7+GwEAAEX/wp9nBAAAXOzsp/9GAABA2NN/IwAAIOzpvxEAABD29N8IAAAIe/pvBAAABPzY33sCAACCpv87AQAAJ7v66b8RAAAQ9vTfCAAACHv6bwQAAIQ9/TcCAABOOv6jPP03AgAATjDS8W8EAAAETf93AgAAgqb/OwEAAIEEAACEPf03AgAADjLq8W8EAACEfPj3SAAAQND0fycAACDs+DcCAAACCQAACHv6bwQAAIQd/0YAAEAgAQAAYU//jQAAgLDj3wgAACj6h/08IwAA4AUzPv03AgAAgqb/OwEAAF+yjn8jAACI9xby3v+RAACAjWZ/+m8EAADR3sKm/zsBAECst9Dj3wgAACK9Bb73fyQAACDs6b8RAADEeQue/u8EAABRHP//EQAAxEh/7/9IAAAQYc/xvxV9+m8EAADlOf6/EwAAlOb4/5kAAICw498IAADK8tHfxwQAACWZ/p8TAACU4/h/TgAAUIrjv44AAKAMx389AQBACY7/NgIAgOk5/tsJAACm5kf99hEAAMQd/1v4038jAACYkuP/GgEAwHQc/9cJAACm4vj3IQAAmIbj348AAGAKjn9fAgCA4Tn+/QkAAIbm+B9DAAAwLMf/OAIAgCE5/scSAAAMx/E/ngAAYCiO/zkEAADDcPzPIwAAGILjf65vJ///A4Buf52v47+fBQCAyzj+1xEAAFzC8b+WAADgdI7/9QQAAKdy/McgAAA4jeM/Dj8FAMDhHP7xWAAAOJTjPyYBAMBhHP9xeQUAwFCHv3H8j2cBAKArx38OAgCAbhz/eXgFAMDLHP75WAAAeInjPycBAMBujv+8vAIA4PTD3zj+1xIAAGziqb8GAQDAKp76a/ENAACfcvzrsQAA8JTJvyYBAMAfeeqvTQAA0P3wN47/2AQAAP/w1J9DAADgqT+QnwIACOf4Z7IAAIRy+LMJAIAwvQ5/4/jPSwAABPHUz50AAAjgqZ/3BABAYQ4/HxEAAAX1PPyN41+PAAAoxlM/awgAgCI89bOFAACYnMPPHgIAYFIOP68QAADhh79x/PMIAIBJOPz0JAAABufwcwQBABBy9BuHnzsBABBw+BvHn0cCAGAADj9nEwAAF3L4uYoAACh09BuHnzUEAMBJHH5GIgAAJj76jcPPHgIA4AAOP6MTAAATHf3G4acHAQAwwdFvHH56EgAAGzn6VCAAAAY7+o3Dz9EEAMAgR79x+DmLAAC48OA3jj5XEABAtKuOfuPwcyUBAES58uDfOfyMQAAApY1w8BtHn9EIAKCMUY79naPPyAQAMKXRjv2do88sBAAwvFGP/SOHn9kIAGAYMxz6R44+MxMAwGlmO/DvOfhUIgCA2IO+hqNPVQIAiDzszzj6JBAAQDwHn0QCAIjj4IMAAAI4+PA7AQCU4tjDOgIAmJZjD/sJAGAKjj30JQCAYTjycB4BAJzGgYcvw/gPPP6HhRGtWI0AAAAASUVORK5CYII="
},
"text": null,
"type": "image_url"
},
{
"image_url": null,
"text": "If you perform 9 operations on this shape, what will the resulting configuration look like? The operations are: the 1th action is Cut the right side of the shape\nthe 2th action is rotate the shape counterclockwise 90 degrees\nthe 3th action is rotate the shape clockwise 90 degrees\nthe 4th action is Cut the right side of the shape\nthe 5th action is rotate the shape counterclockwise 90 degrees\nthe 6th action is Cut the right side of the shape\nthe 7th action is Colorize the top layer of the original shape with the color cyan.\nthe 8th action is Cut the right side of the shape\nthe 9th action is rotate the shape counterclockwise 90 degrees\n. Please select the correct answer from the options below. The options are: ",
"type": "text"
},
{
"image_url": {
"url": "data:image/png;base64,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"
},
"text": null,
"type": "image_url"
}
] |
B
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.