diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..ab9b8ed --- /dev/null +++ b/.gitignore @@ -0,0 +1,2 @@ +tensorboard/* +models/* \ No newline at end of file diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..d867224 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,5 @@ +{ + "[cuda-cpp]": { + }, + "C_Cpp.errorSquiggles": "disabled" +} \ No newline at end of file diff --git a/CUDA/kernel.cu b/CUDA/kernel.cu deleted file mode 100644 index 22c229d..0000000 --- a/CUDA/kernel.cu +++ /dev/null @@ -1,86 +0,0 @@ -#include "setting.h" - -__global__ void Collision(int *flag, LBtype *pres, LBtype *vell, LBtype *f0, LBtype *forc) -{ - GLOBAL_INDEX() - - if(flag[k]==0) - { - LBtype P,Ux,Uy; - LBtype M[9]; - LBtype g[9]; - - LBtype Fx=forc[k*2], Fy=forc[k*2+1]; - - for(int kk=0;kk<9;kk++) - g[kk]=f0[k*9+kk]; - - Ux=(g[1]+g[5]+g[8]-g[3]-g[6]-g[7]+0.5*Fx)/rho; - Uy=(g[2]+g[5]+g[6]-g[4]-g[7]-g[8]+0.5*Fy)/rho; - P =(g[0]+g[1]+g[2]+g[3]+g[4]+g[5]+g[6]+g[7]+g[8])/3.0; - pressure[k]=P; - - M[0]= g[0] +g[1] +g[2] +g[3] +g[4] +g[5] +g[6] +g[7] +g[8]; - M[1]=-4*g[0] -g[1] -g[2] -g[3] -g[4]+2*g[5]+2*g[6]+2*g[7]+2*g[8]; - M[2]= 4*g[0]-2*g[1]-2*g[2]-2*g[3]-2*g[4] +g[5] +g[6] +g[7] +g[8]; - M[3]= g[1] -g[3] +g[5] -g[6] -g[7] +g[8]; - M[4]= -2*g[1] +2*g[3] +g[5] -g[6] -g[7] +g[8]; - M[5]= g[2] -g[4] +g[5] +g[6] -g[7] -g[8]; - M[6]= -2*g[2] +2*g[4] +g[5] +g[6] -g[7] -g[8]; - M[7]= g[1] -g[2] +g[3] -g[4]; - M[8]= g[5] -g[6] +g[7] -g[8]; - - M[0]=1.00*( 3*P -M[0]); - M[1]=1.20*(-6*P+3*rho*(Ux*Ux+Uy*Uy)-M[1])+(1-0.5*1.2)*6*(Ux*Fx+Uy*Fy); - M[2]=1.20*( 3*P-3*rho*(Ux*Ux+Uy*Uy)-M[2])-(1-0.5*1.2)*6*(Ux*Fx+Uy*Fy); - M[3]=1.00*( rho*Ux -M[3])+(1-0.5*0.0)*Fx; - M[4]=1.20*(-rho*Ux -M[4])-(1-0.5*1.2)*Fx; - M[5]=1.00*( rho*Uy -M[5])+(1-0.5*0.0)*Fy; - M[6]=1.20*(-rho*Uy -M[6])-(1-0.5*1.2)*Fy; - M[7]= nu*(rho*(Ux*Ux-Uy*Uy) -M[7])+(1-0.5*nu)*2*(Ux*Fx-Uy*Fy); - M[8]= nu*(rho*Ux*Uy -M[8])+(1-0.5*nu)*(Ux*Fy+Uy*Fx); - - f0[k*9] =g[0]+( M[0] -M[1] +M[2])/9.0; - f0[k*9+1]=g[1]+(4*M[0] -M[1]-2*M[2]+6*M[3]-6*M[4] +9*M[7])/36.0; - f0[k*9+2]=g[2]+(4*M[0] -M[1]-2*M[2] +6*M[5]-6*M[6]-9*M[7])/36.0; - f0[k*9+3]=g[3]+(4*M[0] -M[1]-2*M[2]-6*M[3]+6*M[4] +9*M[7])/36.0; - f0[k*9+4]=g[4]+(4*M[0] -M[1]-2*M[2] -6*M[5]+6*M[6]-9*M[7])/36.0; - f0[k*9+5]=g[5]+(4*M[0]+2*M[1] +M[2]+6*M[3]+3*M[4]+6*M[5]+3*M[6] +9*M[8])/36.0; - f0[k*9+6]=g[6]+(4*M[0]+2*M[1] +M[2]-6*M[3]-3*M[4]+6*M[5]+3*M[6] -9*M[8])/36.0; - f0[k*9+7]=g[7]+(4*M[0]+2*M[1] +M[2]-6*M[3]-3*M[4]-6*M[5]-3*M[6] +9*M[8])/36.0; - f0[k*9+8]=g[8]+(4*M[0]+2*M[1] +M[2]+6*M[3]+3*M[4]-6*M[5]-3*M[6] -9*M[8])/36.0; - } -} - -__global__ void Streaming(LBtype *f0, LBtype *f1) -{ - GLOBAL_INDEX() - int neighbor,nex,ney; - int e[9][2]={{0,0},{1,0},{0,1},{-1,0},{0,-1},{1,1},{-1,1},{-1,-1},{1,-1}}; - - for(int kk=0;kk<9;kk++) - { - nex=(x+e[kk][0]+NX)%NX; - ney=(y+e[kk][1]+NY)%NY; - neighbor=ney*NX+nex; - f1[neighbor*9+kk]=f0[k*9+kk]; - } -} - -__global__ void BounceBack(int *flag, LBtype *f0) -{ - GLOBAL_INDEX() - int neighbor,nex,ney; - int e[9][2]={{0,0},{1,0},{0,1},{-1,0},{0,-1},{1,1},{-1,1},{-1,-1},{1,-1}}; - int opp[9]={0,3,4,1,2,7,8,5,6}; - - if(flag[k]==1) - for(int kk=1;kk<9;kk++) - { - nex=(x+e[kk][0]+NX)%NX; - ney=(y+e[kk][1]+NY)%NY; - neighbor=ney*NX+nex; - if(flag[neighbor]==0) - f0[neighbor*9+kk]=f0[k*9+opp[kk]]; - } -} \ No newline at end of file diff --git a/CUDA/setting.h b/CUDA/setting.h deleted file mode 100644 index 8268929..0000000 --- a/CUDA/setting.h +++ /dev/null @@ -1,9 +0,0 @@ -#define LBtype double -#define Pi 3.141592653589793238 -const int N_thread=256; -int devicenum=0; - -#define GLOBAL_INDEX() \ - int x = threadIdx.x + blockDim.x * blockIdx.x; \ - int y = blockIdx.y; \ - int k = y * gridDim.x * blockDim.x + x; \ No newline at end of file diff --git a/CelerisLab/__init__.py b/CelerisLab/__init__.py new file mode 100644 index 0000000..b15069c --- /dev/null +++ b/CelerisLab/__init__.py @@ -0,0 +1,3 @@ +# CelerisLab/__init__.py + +from .driver import FlowField \ No newline at end of file diff --git a/CelerisLab/__pycache__/__init__.cpython-310.pyc b/CelerisLab/__pycache__/__init__.cpython-310.pyc new file mode 100644 index 0000000..76dc357 Binary files /dev/null and b/CelerisLab/__pycache__/__init__.cpython-310.pyc differ diff --git a/CelerisLab/__pycache__/compiler.cpython-310.pyc b/CelerisLab/__pycache__/compiler.cpython-310.pyc new file mode 100644 index 0000000..a0e6c00 Binary files /dev/null and b/CelerisLab/__pycache__/compiler.cpython-310.pyc differ diff --git a/CelerisLab/__pycache__/driver.cpython-310.pyc b/CelerisLab/__pycache__/driver.cpython-310.pyc new file mode 100644 index 0000000..d584503 Binary files /dev/null and b/CelerisLab/__pycache__/driver.cpython-310.pyc differ diff --git a/CelerisLab/__pycache__/preprocess.cpython-310.pyc b/CelerisLab/__pycache__/preprocess.cpython-310.pyc new file mode 100644 index 0000000..155cbe6 Binary files /dev/null and b/CelerisLab/__pycache__/preprocess.cpython-310.pyc differ diff --git a/CelerisLab/__pycache__/utils.cpython-310.pyc b/CelerisLab/__pycache__/utils.cpython-310.pyc new file mode 100644 index 0000000..8f19ede Binary files /dev/null and b/CelerisLab/__pycache__/utils.cpython-310.pyc differ diff --git a/CelerisLab/compiler.py b/CelerisLab/compiler.py new file mode 100644 index 0000000..c51cbe5 --- /dev/null +++ b/CelerisLab/compiler.py @@ -0,0 +1,87 @@ +# CelerisLab/kernels/compiler.py + +import subprocess +import re +import os + +from .utils import FlowFieldConfig, CudaConfig + + +def kernel_path(file_name: str) -> str: + current_dir = os.path.dirname(os.path.abspath(__file__)) + return os.path.join(current_dir, "kernels", file_name) + + +def read_lines(file_path): + with open(file_path, "r") as file: + lines = file.readlines() + return lines + + +def write_lines(file_path, lines): + with open(file_path, "w") as file: + file.writelines(lines) + + +def modify_macro(lines, macro_name, new_value): + pattern = re.compile(rf"(#define\s+{macro_name}\s+)(\S+)") + for i, line in enumerate(lines): + if pattern.match(line): + lines[i] = pattern.sub(rf"\g<1>{new_value}", line) + break + return lines + +def modify_const(lines, const_name, new_type, new_value): + pattern = re.compile(rf"(__constant__\s+)(\S+\s+{const_name}\s*=\s*)([^;]+)(;)") + for i, line in enumerate(lines): + if pattern.match(line): + lines[i] = pattern.sub(rf"\g<1>{new_type} {const_name} = {new_value}\4", line) + break + return lines + +def compile_kernel(): + subprocess.run( + [ + "nvcc", + "-ptx", + kernel_path("kernel.cu"), + "-o", + kernel_path("kernel.ptx"), + ] + ) + +def config_kernal(config_cuda: CudaConfig, config_field: FlowFieldConfig): + lines = read_lines(kernel_path("macros.h")) + lines = modify_macro(lines, "MULT_GPU", config_cuda.multi_gpu) + lines = modify_macro(lines, "NT", config_cuda.threads_per_block) + lines = modify_macro(lines, "X_1U", config_cuda.unit_dimensions[0]) + lines = modify_macro(lines, "Y_1U", config_cuda.unit_dimensions[1]) + lines = modify_macro(lines, "Z_1U", config_cuda.unit_dimensions[2]) + + if config_field.data_type == "FP32": + lb_type = "float" + else: + raise ValueError(f"Unsupported data type {config_field.data_type}.") + lines = modify_macro(lines, "LBtype", lb_type) + lines = modify_macro(lines, "UX", config_field.field_dim_in_U[0]) + lines = modify_macro(lines, "UY", config_field.field_dim_in_U[1]) + lines = modify_macro(lines, "UZ", config_field.field_dim_in_U[2]) + lines = modify_macro(lines, "NX", config_field.field_dim_in_U[0] * config_cuda.unit_dimensions[0]) + lines = modify_macro(lines, "NY", config_field.field_dim_in_U[1] * config_cuda.unit_dimensions[1]) + lines = modify_macro(lines, "NZ", config_field.field_dim_in_U[2] * config_cuda.unit_dimensions[2]) + lines = modify_macro(lines, "DIM", config_field.dimensionality) + lines = modify_macro(lines, "NQ", config_field.lattice) + lines = modify_macro(lines, "VIS", config_field.viscosity) + lines = modify_macro(lines, "U0", config_field.velocity) + + write_lines(kernel_path("macros.h"), lines) + +def config_object(n_obj: int): + lines = read_lines(kernel_path("macros.h")) + lines = modify_macro(lines, "N_OBJS", n_obj) + write_lines(kernel_path("macros.h"), lines) + +def config_sensor(n_sen: int): + lines = read_lines(kernel_path("macros.h")) + lines = modify_macro(lines, "N_SENS", n_sen) + write_lines(kernel_path("macros.h"), lines) \ No newline at end of file diff --git a/CelerisLab/driver.py b/CelerisLab/driver.py new file mode 100644 index 0000000..133a740 --- /dev/null +++ b/CelerisLab/driver.py @@ -0,0 +1,282 @@ +# CelerisLab/driver.py + +import pycuda.driver as cuda +import numpy as np +from typing import List, Tuple, Union + +from . import utils +from . import preprocess as preproc +from . import compiler + +FLUID = 0b00000001 +SOLID = 0b00000010 +GAS = 0b00000100 +INTERFACE = 0b00001000 +SENSOR = 0b00010000 + + +class FlowField: + def __init__( + self, + field_config: utils.FlowFieldConfig, + cuda_config: utils.CudaConfig, + device_id: Union[int, List[int]] = None, + ): + self.field_config = field_config + self.cuda_config = cuda_config + cuda.init() + + # Sanity checks + if cuda_config.multi_gpu: + if device_id is None or isinstance(device_id, int): + raise ValueError("Multi-GPU support requires a list of device IDs.") + # self.devices = [cuda.Device(id) for id in device_id] + raise NotImplementedError("Multi-GPU support is not implemented yet.") + else: + if isinstance(device_id, list): + if len(device_id) > 1: + raise ValueError( + "Single-GPU mode does not support multiple device IDs." + ) + device_id = device_id[0] + elif device_id is None: + device_id = 0 + utils.check_cuda_device_availability(device_id) + self.device = cuda.Device(device_id) + self.context = self.device.make_context() + + utils.check_cuda_capability(field_config, cuda_config, device_id) + + # Config kernel + compiler.config_kernal(cuda_config, field_config) + compiler.config_object(int(0)) + # compiler.config_sensor(int(0)) + + # Set constants + if field_config.data_type == "FP32": + self.DATA_TYPE = np.float32 + else: + raise ValueError(f"Unsupported data type {field_config.data_type}.") + + self.FIELD_SHAPE = tuple( + size * unit + for size, unit in zip( + field_config.field_dim_in_U, cuda_config.unit_dimensions + ) + ) + self.FIELD_SIZE = np.prod(self.FIELD_SHAPE) + self.LATTICE = field_config.lattice + self.DIM = field_config.dimensionality + if field_config.lattice == 9 and field_config.dimensionality == 2: + self.E = np.array( + [0, 0, 1, 0, 0, 1, -1, 0, 0, -1, 1, 1, -1, 1, -1, -1, 1, -1], + dtype=np.int32, + ).reshape(9, 2) + self.OPP = np.array([0, 3, 4, 1, 2, 7, 8, 5, 6], dtype=np.int32) + self.WW = np.array( + [4 / 9, 1 / 9, 1 / 9, 1 / 9, 1 / 9, 1 / 36, 1 / 36, 1 / 36, 1 / 36], + dtype=self.DATA_TYPE, + ) + else: + raise NotImplementedError( + f"Unsupported lattice type {field_config.lattice} in {field_config.dimensionality} dimensions." + ) + + # Compile kernel + compiler.compile_kernel() + self.ptx = cuda.module_from_file(compiler.kernel_path("kernel.ptx")) + self.step = self.ptx.get_function("OneStep") + initflow = self.ptx.get_function("InitTubeFlow") + + # Initialize memory + self.ddf = np.zeros(self.FIELD_SIZE * self.LATTICE, dtype=self.DATA_TYPE) + # self.velo = np.zeros(self.FIELD_SIZE * self.DIM, dtype=self.DATA_TYPE) + self.flag = np.ones(self.FIELD_SIZE, dtype=np.uint8) + self.indx = np.zeros(self.FIELD_SIZE, dtype=np.int32) + + self.delta_curve = np.zeros(0, dtype=self.DATA_TYPE) + + self.ddf_gpu = cuda.mem_alloc(self.ddf.nbytes) + self.temp_gpu = cuda.mem_alloc(self.ddf.nbytes) + self.flag_gpu = cuda.mem_alloc(self.flag.nbytes) + self.indx_gpu = cuda.mem_alloc(self.indx.nbytes) + + self.objects = {} + self.action = np.zeros(0, dtype=self.DATA_TYPE) + self.obs = np.zeros(0, dtype=self.DATA_TYPE) + + initflow( + self.flag_gpu, + self.ddf_gpu, + block=(self.cuda_config.threads_per_block, 1, 1), + grid=( + int(self.FIELD_SHAPE[0] / self.cuda_config.threads_per_block), + int(self.FIELD_SHAPE[1]), + int(self.FIELD_SHAPE[2]), + ), + ) + cuda.memcpy_dtoh(self.flag, self.flag_gpu) + cuda.memcpy_dtoh(self.ddf, self.ddf_gpu) + + def add_cylinder(self, center: Tuple[float, float, float], radius: float): + x_c, y_c, z_c = center + + if ( + x_c - radius <= 0 + or x_c + radius >= self.FIELD_SHAPE[0] - 1 + or y_c - radius <= 0 + or y_c + radius >= self.FIELD_SHAPE[1] - 1 + ): + raise ValueError("Cylinder is out of bounds.") + + index = self.delta_curve.size if self.delta_curve.size > 0 else 0 + if self.DATA_TYPE == np.float32: + id_object = np.int32(len(self.objects)) + else: + raise ValueError(f"Unsupported data type {self.DATA_TYPE}.") + for x in range(int(x_c - radius) - 1, int(x_c + radius) + 1): + for y in range(int(y_c - radius) - 1, int(y_c + radius) + 1): + if (x - x_c) ** 2 + (y - y_c) ** 2 < radius**2: + k = x + y * self.FIELD_SHAPE[0] + self.flag[k] = SOLID + delta_temp = np.zeros(11, dtype=self.DATA_TYPE) + delta_temp[0] = id_object.view(self.DATA_TYPE) + for i in range(self.LATTICE): + x_neb = x + self.E[i][0] + y_neb = y + self.E[i][1] + if (x_neb - x_c) ** 2 + (y_neb - y_c) ** 2 >= radius**2: + self.flag[k] |= INTERFACE + x_i, y_i = preproc.find_circle_intersection( + x, y, x_neb, y_neb, x_c, y_c, radius + ) + d_neb = np.sqrt((x_i - x_neb) ** 2 + (y_i - y_neb) ** 2) + delta_temp[i] = d_neb / np.sqrt( + self.E[i][0] ** 2 + self.E[i][1] ** 2 + ) + if self.flag[k] & INTERFACE: + delta_temp[9] = (y_c - y) / radius + delta_temp[10] = (x - x_c) / radius + self.delta_curve = np.concatenate( + (self.delta_curve, delta_temp) + ) + self.indx[k] = index + index += delta_temp.size + + self.objects[id_object] = { + "type": "cylinder", + "center": center, + "radius": radius, + } + + if hasattr(self, "delta_gpu"): + self.delta_gpu.free() + self.delta_gpu = cuda.mem_alloc(self.delta_curve.nbytes) + + self.action = np.zeros(len(self.objects), dtype=self.DATA_TYPE) + if hasattr(self, "action_gpu"): + self.action_gpu.free() + self.action_gpu = cuda.mem_alloc(self.action.nbytes) + + self.obs = np.zeros(len(self.objects) * self.DIM, dtype=self.DATA_TYPE) + if hasattr(self, "force_gpu"): + self.obs_gpu.free() + self.obs_gpu = cuda.mem_alloc(self.obs.nbytes) + + cuda.memcpy_htod(self.delta_gpu, self.delta_curve) + cuda.memcpy_htod(self.flag_gpu, self.flag) + cuda.memcpy_htod(self.indx_gpu, self.indx) + + compiler.config_object(len(self.objects)) + compiler.compile_kernel() + self.ptx = cuda.module_from_file(compiler.kernel_path("kernel.ptx")) + self.step = self.ptx.get_function("OneStep") + + def add_sensor(self, center: Tuple[float, float, float], radius: float): + x_c, y_c, z_c = center + + if ( + x_c - radius <= 0 + or x_c + radius >= self.FIELD_SHAPE[0] - 1 + or y_c - radius <= 0 + or y_c + radius >= self.FIELD_SHAPE[1] - 1 + ): + raise ValueError("Sensor is out of bounds.") + + id_object = len(self.objects) + for x in range(int(x_c - radius) - 1, int(x_c + radius) + 1): + for y in range(int(y_c - radius) - 1, int(y_c + radius) + 1): + if (x - x_c) ** 2 + (y - y_c) ** 2 < radius**2: + k = x + y * self.FIELD_SHAPE[0] + self.flag[k] |= SENSOR + self.indx[k] = id_object + + self.objects[id_object] = { + "type": "sensor", + "center": center, + } + + self.action = np.zeros(len(self.objects), dtype=self.DATA_TYPE) + if hasattr(self, "action_gpu"): + self.action_gpu.free() + self.action_gpu = cuda.mem_alloc(self.action.nbytes) + + self.obs = np.zeros(len(self.objects) * self.DIM, dtype=self.DATA_TYPE) + if hasattr(self, "force_gpu"): + self.obs_gpu.free() + self.obs_gpu = cuda.mem_alloc(self.obs.nbytes) + + cuda.memcpy_htod(self.flag_gpu, self.flag) + cuda.memcpy_htod(self.indx_gpu, self.indx) + + compiler.config_object(len(self.objects)) + compiler.compile_kernel() + self.ptx = cuda.module_from_file(compiler.kernel_path("kernel.ptx")) + self.step = self.ptx.get_function("OneStep") + + def run(self, num_steps: int, action_target: np.ndarray): + if ( + action_target.size != len(self.objects) + or action_target.dtype != self.DATA_TYPE + ): + raise ValueError("action data type or size does not match the objects.") + + weight = 0.1 + stream = cuda.Stream() + action_pinned = cuda.pagelocked_empty_like(self.action) + action_pinned[:] = self.action + obs_pinned = cuda.pagelocked_empty_like(self.obs) + self.obs[:] = 0 + for i in range(num_steps): + action_pinned = (1 - weight) * action_pinned + weight * action_target + cuda.memcpy_htod_async(self.action_gpu, action_pinned, stream) + self.step( + self.flag_gpu, + self.ddf_gpu, + self.temp_gpu, + self.indx_gpu, + self.delta_gpu, + self.action_gpu, + self.obs_gpu, + block=(self.cuda_config.threads_per_block, 1, 1), + grid=( + int(self.FIELD_SHAPE[0] / self.cuda_config.threads_per_block), + int(self.FIELD_SHAPE[1]), + int(self.FIELD_SHAPE[2]), + ), + stream=stream, + ) + self.ddf_gpu, self.temp_gpu = self.temp_gpu, self.ddf_gpu + cuda.memcpy_dtoh_async(obs_pinned, self.obs_gpu, stream) + cuda.memset_d32_async(self.obs_gpu, 0, self.obs.size, stream) + self.obs += obs_pinned + stream.synchronize() + self.obs = (self.obs / num_steps).astype(self.DATA_TYPE) + + def apply_ddf(self): + cuda.memcpy_htod(self.ddf_gpu, self.ddf) + + def get_ddf(self): + cuda.memcpy_dtoh(self.ddf, self.ddf_gpu) + + def __del__(self): + self.context.pop() \ No newline at end of file diff --git a/CelerisLab/kernels/D2Q9.cu b/CelerisLab/kernels/D2Q9.cu new file mode 100644 index 0000000..395d8ed --- /dev/null +++ b/CelerisLab/kernels/D2Q9.cu @@ -0,0 +1,101 @@ +#include "macros.h" +#include "const.h" + +__device__ void Index_lattice(int &x, int &y, int &k) { + // Only for D2 + x = threadIdx.x + NT * blockIdx.x; + y = blockIdx.y; + k = y * NX + x; +} + +__device__ void CollisionKernel(LBtype* g, LBtype* m) { + // Only for D2Q9 + LBtype p, u, v; + LBtype niu = 1.0 / (0.5 + 3 * VIS); + + u = (g[1]+g[5]+g[8]-g[3]-g[6]-g[7])/RHO; + v = (g[2]+g[5]+g[6]-g[4]-g[7]-g[8])/RHO; + p = (g[0]+g[1]+g[2]+g[3]+g[4]+g[5]+g[6]+g[7]+g[8])/3.0; + + m[0]= g[0] +g[1] +g[2] +g[3] +g[4] +g[5] +g[6] +g[7] +g[8]; + m[1]=-4*g[0] -g[1] -g[2] -g[3] -g[4]+2*g[5]+2*g[6]+2*g[7]+2*g[8]; + m[2]= 4*g[0]-2*g[1]-2*g[2]-2*g[3]-2*g[4] +g[5] +g[6] +g[7] +g[8]; + m[3]= g[1] -g[3] +g[5] -g[6] -g[7] +g[8]; + m[4]= -2*g[1] +2*g[3] +g[5] -g[6] -g[7] +g[8]; + m[5]= g[2] -g[4] +g[5] +g[6] -g[7] -g[8]; + m[6]= -2*g[2] +2*g[4] +g[5] +g[6] -g[7] -g[8]; + m[7]= g[1] -g[2] +g[3] -g[4]; + m[8]= g[5] -g[6] +g[7] -g[8]; + + m[0]=1.00*( 3*p -m[0]); + m[1]=1.20*(-6*p +3*RHO*(u*u+v*v)-m[1]); + m[2]=1.20*( 3*p -3*RHO*(u*u+v*v)-m[2]); + m[3]=1.00*( RHO*u -m[3]); + m[4]=1.20*(-RHO*u -m[4]); + m[5]=1.00*( RHO*v -m[5]); + m[6]=1.20*(-RHO*v -m[6]); + m[7]= niu*( RHO*(u*u-v*v) -m[7]); + m[8]= niu*( RHO*u*v -m[8]); + + g[0]=g[0]+( m[0] -m[1] +m[2] )/ 9.0; + g[1]=g[1]+(4*m[0] -m[1]-2*m[2]+6*m[3]-6*m[4] +9*m[7])/36.0; + g[2]=g[2]+(4*m[0] -m[1]-2*m[2] +6*m[5]-6*m[6]-9*m[7])/36.0; + g[3]=g[3]+(4*m[0] -m[1]-2*m[2]-6*m[3]+6*m[4] +9*m[7])/36.0; + g[4]=g[4]+(4*m[0] -m[1]-2*m[2] -6*m[5]+6*m[6]-9*m[7])/36.0; + g[5]=g[5]+(4*m[0]+2*m[1] +m[2]+6*m[3]+3*m[4]+6*m[5]+3*m[6]+9*m[8])/36.0; + g[6]=g[6]+(4*m[0]+2*m[1] +m[2]-6*m[3]-3*m[4]+6*m[5]+3*m[6]-9*m[8])/36.0; + g[7]=g[7]+(4*m[0]+2*m[1] +m[2]-6*m[3]-3*m[4]-6*m[5]-3*m[6]+9*m[8])/36.0; + g[8]=g[8]+(4*m[0]+2*m[1] +m[2]+6*m[3]+3*m[4]-6*m[5]-3*m[6]-9*m[8])/36.0; +} + +__device__ void ParabolicInlet(LBtype* f, LBtype* f_neb, LBtype y) { + LBtype p, u, v, yy; + LBtype feq1, feq5, feq8, feqn1, feqn5, feqn8; + + p=(f_neb[0]+f_neb[1]+f_neb[2]+f_neb[3]+f_neb[4]+f_neb[5]+f_neb[6]+f_neb[7]+f_neb[8])/3.0; + yy=(y-0.5*(NY-1))/(NY-2.0); + u=U0*1.5*(1-4*yy*yy); + v=0.0; + + feq1=(2*p+RHO*(2*u*u+2*u -v*v) )/ 6.0; + feq5=( p+RHO*( u*u+3*u*v+u+v*v+v))/12.0; + feq8=( p+RHO*( u*u-3*u*v+u+v*v-v))/12.0; + + u=(f_neb[1]+f_neb[5]+f_neb[8]-f_neb[3]-f_neb[6]-f_neb[7])/RHO; + v=(f_neb[2]+f_neb[5]+f_neb[6]-f_neb[4]-f_neb[7]-f_neb[8])/RHO; + + feqn1=(2*p+RHO*(2*u*u+2*u -v*v) )/ 6.0; + feqn5=( p+RHO*( u*u+3*u*v+u+v*v+v))/12.0; + feqn8=( p+RHO*( u*u-3*u*v+u+v*v-v))/12.0; + + f[1]=f_neb[1]-feqn1+feq1; + f[5]=f_neb[5]-feqn5+feq5; + f[8]=f_neb[8]-feqn8+feq8; +} + +__device__ void PressureOutlet(LBtype* f, LBtype* f_neb, LBtype y) { + // Edit to Parabolic Outlet temporarily + LBtype p, u, v, yy; + LBtype feq3, feq6, feq7, feqn3, feqn6, feqn7; + + p=0.0; + + yy=(y-0.5*(NY-1))/(NY-2.0); + u=U0*1.5*(1-4*yy*yy); + v=0.0; + + feq3=(2*p-RHO*(-2*u*u+2*u +v*v) )/ 6.0; + feq6=( p+RHO*( u*u-3*u*v-u+v*v+v))/12.0; + feq7=( p+RHO*( u*u+3*u*v-u+v*v-v))/12.0; + + u=(f_neb[1]+f_neb[5]+f_neb[8]-f_neb[3]-f_neb[6]-f_neb[7])/RHO; + v=(f_neb[2]+f_neb[5]+f_neb[6]-f_neb[4]-f_neb[7]-f_neb[8])/RHO; + // p=(f_neb[0]+f_neb[1]+f_neb[2]+f_neb[3]+f_neb[4]+f_neb[5]+f_neb[6]+f_neb[7]+f_neb[8])/3.0; + feqn3=(2*p-RHO*(-2*u*u+2*u +v*v) )/ 6.0; + feqn6=( p+RHO*( u*u-3*u*v-u+v*v+v))/12.0; + feqn7=( p+RHO*( u*u+3*u*v-u+v*v-v))/12.0; + + f[3]=f_neb[3]-feqn3+feq3; + f[6]=f_neb[6]-feqn6+feq6; + f[7]=f_neb[7]-feqn7+feq7; +} \ No newline at end of file diff --git a/CelerisLab/kernels/IO.cu b/CelerisLab/kernels/IO.cu new file mode 100644 index 0000000..e69de29 diff --git a/CelerisLab/kernels/__pycache__/compiler.cpython-310.pyc b/CelerisLab/kernels/__pycache__/compiler.cpython-310.pyc new file mode 100644 index 0000000..d4121d9 Binary files /dev/null and b/CelerisLab/kernels/__pycache__/compiler.cpython-310.pyc differ diff --git a/CelerisLab/kernels/const.h b/CelerisLab/kernels/const.h new file mode 100644 index 0000000..e21bcc3 --- /dev/null +++ b/CelerisLab/kernels/const.h @@ -0,0 +1,10 @@ +// CelerisLab/kernels/const.h + +#ifndef CONST_H +#define CONST_H + +__constant__ int e[9][2] = {{0, 0}, {1, 0}, {0, 1}, {-1, 0}, {0, -1}, {1, 1}, {-1, 1}, {-1, -1}, {1, -1}}; +__constant__ int opp[9] = {0, 3, 4, 1, 2, 7, 8, 5, 6}; +__constant__ float w[9] = {4/9., 1/9., 1/9., 1/9., 1/9., 1/36., 1/36., 1/36., 1/36.}; + +#endif \ No newline at end of file diff --git a/CelerisLab/kernels/kernel.cu b/CelerisLab/kernels/kernel.cu new file mode 100644 index 0000000..fc73105 --- /dev/null +++ b/CelerisLab/kernels/kernel.cu @@ -0,0 +1,190 @@ +// CelerisLab/kernels/kernel.cu + +#include +#include +#include + +#include "macros.h" +#include "const.h" +#include "D2Q9.cu" + +extern "C" +{ + __global__ void OneStep(uint8_t *flag, LBtype *f, LBtype *f_temp, int32_t *indx, LBtype *delta, LBtype *action, LBtype *obs) + { + __shared__ LBtype f_share[NT * NQ]; + __shared__ LBtype obs_share[(N_OBJS * DIM > 0) ? N_OBJS * DIM : 1]; + + int x, y, k; + LBtype g[NQ], m[NQ]; + Index_lattice(x, y, k); // Only for D2 + int totalCells = NX * NY; + int id = indx[k]; + + for (int i = 0; i < NQ; i++) + { + f_share[threadIdx.x + i * NT] = f[k + i * totalCells]; + } + for (int i = threadIdx.x; i < N_OBJS * DIM; i+=NT) + { + obs_share[i] = 0; + } + + __syncthreads(); + + for (int i = 0; i < NQ; i++) + { + g[i] = f_share[threadIdx.x + i * NT]; + } + + if (flag[k] & FLUID) + { + CollisionKernel(g, m); + + for (int i = 0; i < NQ; i++) + { + f_share[threadIdx.x + i * NT] = g[i]; + } + } + else if (flag[k] & SOLID) + { + if (x == 0) + { + for (int i = 0; i < NQ; i++) + { + m[i] = f_share[threadIdx.x + i * NT + 1]; + } + ParabolicInlet(g, m, y); + } + else if (x == NX - 1) + { + for (int i = 0; i < NQ; i++) + { + m[i] = f_share[threadIdx.x + i * NT - 1]; + } + PressureOutlet(g, m, y); + } + + for (int i = 0; i < NQ; i++) + { + f_share[threadIdx.x + i * NT] = g[i]; + } + } + + __syncthreads(); + + for (int i = 0; i < NQ; i++) + { + int x_neb = x + e[i][0]; + int y_neb = y + e[i][1]; + + if (y != 0 && y != NY - 1) + { + if ((y == 1 && y_neb == 0) || (y == NY - 2 && y_neb == NY - 1)) + { + f_temp[k + opp[i] * totalCells] = f_share[threadIdx.x + i * NT]; + } + else + { + int k_neb = ((y_neb * NX + x_neb) + totalCells) % totalCells; + f_temp[k_neb + i * totalCells] = f_share[threadIdx.x + i * NT]; + } + } + } + + __syncthreads(); + + if (flag[k] & SOLID && flag[k] & INTERFACE) + { + LBtype Uw, Vw; + int id_obj = *reinterpret_cast(&delta[id]); + Uw = action[id_obj] * delta[id + 9]; + Vw = action[id_obj] * delta[id + 10]; + + int x_neb, y_neb, k_neb; + for (int i = 1; i < 9; i++) + { + x_neb = x + e[i][0]; + y_neb = y + e[i][1]; + k_neb = x_neb + y_neb * NX; + if (flag[k_neb] & FLUID) + { + LBtype q = delta[id + i]; + int k_neb2 = (y + 2 * e[i][1]) * NX + (x + 2 * e[i][0]); + LBtype temp = 6 * w[i] * (e[i][0] * Uw + e[i][1] * Vw); + f_temp[k_neb + i * totalCells] = (q * f_temp[k + opp[i] * totalCells] \ + + (1 - q) * f_temp[k_neb + opp[i] * totalCells] \ + + q * f_temp[k_neb2 + i * totalCells] + temp) / (1 + q); + f_temp[k + i * totalCells] = temp * Uw; + k_neb2 = (y - e[i][1]) * NX + (x - e[i][0]); + f_temp[k_neb2 + i * totalCells] = temp * Vw; + + temp = f_temp[k_neb + i * totalCells] + f_temp[k + opp[i] * totalCells]; + k_neb2 = (y - e[i][1]) * NX + (x - e[i][0]); + atomicAdd(&obs_share[DIM * id_obj], -temp * e[i][0] + f_temp[k + i * totalCells]); + atomicAdd(&obs_share[DIM * id_obj + 1], -temp * e[i][1] + f_temp[k_neb2 + i * totalCells]); + } + } + } + if (flag[k] & SENSOR) + { + LBtype u, v; + u = (g[1]+g[5]+g[8]-g[3]-g[6]-g[7])/RHO; + v = (g[2]+g[5]+g[6]-g[4]-g[7]-g[8])/RHO; + atomicAdd(&obs_share[DIM * id], u); + atomicAdd(&obs_share[DIM * id + 1], v); + } + + __syncthreads(); + + for (int i = threadIdx.x; i < N_OBJS * DIM; i+=NT) + { + atomicAdd(&obs[i], obs_share[i]); + } + } + + __global__ void InitTubeFlow(uint8_t *flag, LBtype *f) + { + __shared__ LBtype f_share[NT * NQ]; + __shared__ uint8_t flag_share[NT]; + int x, y, k; + LBtype u; + Index_lattice(x, y, k); + int totalCells = NX * NY; + + flag_share[threadIdx.x] = flag[k]; + for (int i = 0; i < NQ; i++) + { + f_share[threadIdx.x + i * NT] = f[k + i * totalCells]; + } + + __syncthreads(); + + u = U0 * 1.5 * (1 - 4 * (y - 0.5 * (NY - 1)) * (y - 0.5 * (NY - 1)) / ((NY - 2) * (NY - 2))); + if (y == 0 || y == NY - 1 || x == 0 || x == NX - 1) + { + flag_share[threadIdx.x] = SOLID; + for (int i = 0; i < NQ; i++) + { + f_share[threadIdx.x + i * NT] = 0; + } + } + else + { + flag_share[threadIdx.x] = FLUID; + for (int i = 0; i < NQ; i++) + { + f_share[threadIdx.x + i * NT] = w[i] * RHO * (3 * e[i][0] * u + \ + 4.5 * e[i][0] * e[i][0] * u * u - 1.5 * u * u); + } + } + + __syncthreads(); + + flag[k] = flag_share[threadIdx.x]; + for (int i = 0; i < NQ; i++) + { + f[k + i * totalCells] = f_share[threadIdx.x + i * NT]; + } + } +} \ No newline at end of file diff --git a/CelerisLab/kernels/kernel.ptx b/CelerisLab/kernels/kernel.ptx new file mode 100644 index 0000000..69e8dd4 --- /dev/null +++ b/CelerisLab/kernels/kernel.ptx @@ -0,0 +1,1410 @@ +// +// Generated by NVIDIA NVVM Compiler +// +// Compiler Build ID: CL-32688072 +// Cuda compilation tools, release 12.1, V12.1.105 +// Based on NVVM 7.0.1 +// + +.version 8.1 +.target sm_52 +.address_size 64 + + // .globl OneStep +.const .align 4 .b8 e[72] = {0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 255, 255, 255, 255, 0, 0, 0, 0, 0, 0, 0, 0, 255, 255, 255, 255, 1, 0, 0, 0, 1, 0, 0, 0, 255, 255, 255, 255, 1, 0, 0, 0, 255, 255, 255, 255, 255, 255, 255, 255, 1, 0, 0, 0, 255, 255, 255, 255}; +.const .align 4 .b8 opp[36] = {0, 0, 0, 0, 3, 0, 0, 0, 4, 0, 0, 0, 1, 0, 0, 0, 2, 0, 0, 0, 7, 0, 0, 0, 8, 0, 0, 0, 5, 0, 0, 0, 6, 0, 0, 0}; +.const .align 4 .b8 w[36] = {57, 142, 227, 62, 57, 142, 227, 61, 57, 142, 227, 61, 57, 142, 227, 61, 57, 142, 227, 61, 57, 142, 227, 60, 57, 142, 227, 60, 57, 142, 227, 60, 57, 142, 227, 60}; +// _ZZ7OneStepE7f_share has been demoted +// _ZZ7OneStepE9obs_share has been demoted +// _ZZ12InitTubeFlowE7f_share has been demoted +// _ZZ12InitTubeFlowE10flag_share has been demoted + +.visible .entry OneStep( + .param .u64 OneStep_param_0, + .param .u64 OneStep_param_1, + .param .u64 OneStep_param_2, + .param .u64 OneStep_param_3, + .param .u64 OneStep_param_4, + .param .u64 OneStep_param_5, + .param .u64 OneStep_param_6 +) +{ + .reg .pred %p<98>; + .reg .b16 %rs<12>; + .reg .f32 %f<393>; + .reg .b32 %r<250>; + .reg .f64 %fd<116>; + .reg .b64 %rd<108>; + // demoted variable + .shared .align 4 .b8 _ZZ7OneStepE7f_share[4608]; + // demoted variable + .shared .align 4 .b8 _ZZ7OneStepE9obs_share[56]; + + ld.param.u64 %rd27, [OneStep_param_0]; + ld.param.u64 %rd28, [OneStep_param_1]; + ld.param.u64 %rd29, [OneStep_param_2]; + ld.param.u64 %rd30, [OneStep_param_3]; + ld.param.u64 %rd25, [OneStep_param_4]; + ld.param.u64 %rd26, [OneStep_param_5]; + ld.param.u64 %rd31, [OneStep_param_6]; + cvta.to.global.u64 %rd32, %rd28; + cvta.to.global.u64 %rd1, %rd29; + mov.u32 %r59, %ctaid.x; + shl.b32 %r1, %r59, 7; + mov.u32 %r247, %tid.x; + add.s32 %r3, %r1, %r247; + mov.u32 %r4, %ctaid.y; + mul.lo.s32 %r5, %r4, 1280; + add.s32 %r60, %r3, %r5; + cvt.s64.s32 %rd2, %r60; + cvta.to.global.u64 %rd33, %rd30; + mul.wide.s32 %rd34, %r60, 4; + add.s64 %rd35, %rd33, %rd34; + ld.global.s32 %rd3, [%rd35]; + add.s64 %rd36, %rd32, %rd34; + ld.global.f32 %f39, [%rd36]; + shl.b32 %r61, %r247, 2; + mov.u32 %r62, _ZZ7OneStepE7f_share; + add.s32 %r6, %r62, %r61; + st.shared.f32 [%r6], %f39; + ld.global.f32 %f40, [%rd36+2621440]; + st.shared.f32 [%r6+512], %f40; + ld.global.f32 %f41, [%rd36+5242880]; + st.shared.f32 [%r6+1024], %f41; + ld.global.f32 %f42, [%rd36+7864320]; + st.shared.f32 [%r6+1536], %f42; + ld.global.f32 %f43, [%rd36+10485760]; + st.shared.f32 [%r6+2048], %f43; + ld.global.f32 %f44, [%rd36+13107200]; + st.shared.f32 [%r6+2560], %f44; + ld.global.f32 %f45, [%rd36+15728640]; + st.shared.f32 [%r6+3072], %f45; + ld.global.f32 %f46, [%rd36+18350080]; + st.shared.f32 [%r6+3584], %f46; + ld.global.f32 %f47, [%rd36+20971520]; + st.shared.f32 [%r6+4096], %f47; + cvta.to.global.u64 %rd4, %rd31; + cvta.to.global.u64 %rd5, %rd27; + setp.gt.s32 %p1, %r247, 13; + @%p1 bra $L__BB0_7; + + max.s32 %r63, %r247, -114; + add.s32 %r64, %r63, 127; + sub.s32 %r7, %r64, %r247; + shr.u32 %r65, %r7, 7; + add.s32 %r66, %r65, 1; + and.b32 %r238, %r66, 3; + setp.eq.s32 %p2, %r238, 0; + mov.u32 %r239, %r247; + @%p2 bra $L__BB0_4; + + mov.u32 %r68, _ZZ7OneStepE9obs_share; + add.s32 %r236, %r68, %r61; + mov.u32 %r239, %r247; + +$L__BB0_3: + .pragma "nounroll"; + mov.u32 %r69, 0; + st.shared.u32 [%r236], %r69; + add.s32 %r239, %r239, 128; + add.s32 %r236, %r236, 512; + add.s32 %r238, %r238, -1; + setp.ne.s32 %p3, %r238, 0; + @%p3 bra $L__BB0_3; + +$L__BB0_4: + setp.lt.u32 %p4, %r7, 384; + @%p4 bra $L__BB0_7; + + add.s32 %r241, %r239, -512; + shl.b32 %r70, %r239, 2; + mov.u32 %r71, _ZZ7OneStepE9obs_share; + add.s32 %r72, %r71, %r70; + add.s32 %r240, %r72, 1024; + +$L__BB0_6: + mov.u32 %r73, 0; + st.shared.u32 [%r240+-1024], %r73; + st.shared.u32 [%r240+-512], %r73; + st.shared.u32 [%r240], %r73; + st.shared.u32 [%r240+512], %r73; + add.s32 %r240, %r240, 2048; + add.s32 %r241, %r241, 512; + setp.lt.s32 %p5, %r241, -498; + @%p5 bra $L__BB0_6; + +$L__BB0_7: + bar.sync 0; + ld.shared.f32 %f392, [%r6+512]; + ld.shared.f32 %f391, [%r6+1024]; + ld.shared.f32 %f390, [%r6+1536]; + ld.shared.f32 %f389, [%r6+2048]; + ld.shared.f32 %f388, [%r6+2560]; + ld.shared.f32 %f387, [%r6+3072]; + ld.shared.f32 %f386, [%r6+3584]; + ld.shared.f32 %f385, [%r6+4096]; + add.s64 %rd6, %rd5, %rd2; + ld.global.u8 %rs1, [%rd6]; + and.b16 %rs5, %rs1, 1; + setp.eq.b16 %p6, %rs5, 1; + mov.pred %p7, 0; + xor.pred %p8, %p6, %p7; + not.pred %p9, %p8; + @%p9 bra $L__BB0_9; + bra.uni $L__BB0_8; + +$L__BB0_9: + and.b16 %rs6, %rs1, 2; + setp.eq.s16 %p10, %rs6, 0; + @%p10 bra $L__BB0_15; + + setp.eq.s32 %p11, %r3, 0; + @%p11 bra $L__BB0_13; + + setp.ne.s32 %p12, %r3, 1279; + @%p12 bra $L__BB0_14; + + cvt.rn.f32.s32 %f176, %r4; + cvt.f64.f32 %fd67, %f176; + add.f64 %fd68, %fd67, 0dC06FF00000000000; + div.rn.f64 %fd69, %fd68, 0d407FE00000000000; + cvt.rn.f32.f64 %f177, %fd69; + mul.f32 %f178, %f177, 0fC0800000; + fma.rn.f32 %f179, %f178, %f177, 0f3F800000; + cvt.f64.f32 %fd70, %f179; + mul.f64 %fd71, %fd70, 0d3F8EB851EB851EB8; + cvt.rn.f32.f64 %f180, %fd71; + mul.f32 %f181, %f180, 0fC0000000; + mul.f32 %f182, %f181, %f180; + fma.rn.f32 %f183, %f180, 0f40000000, %f182; + add.f32 %f184, %f183, 0f00000000; + cvt.f64.f32 %fd72, %f184; + mov.f64 %fd73, 0d0000000000000000; + sub.f64 %fd74, %fd73, %fd72; + div.rn.f64 %fd75, %fd74, 0d4018000000000000; + cvt.rn.f32.f64 %f185, %fd75; + mul.f32 %f186, %f180, %f180; + mul.f32 %f187, %f180, 0f40400000; + mul.f32 %f188, %f187, 0f00000000; + sub.f32 %f189, %f186, %f188; + sub.f32 %f190, %f189, %f180; + add.f32 %f191, %f190, 0f00000000; + cvt.f64.f32 %fd76, %f191; + add.f64 %fd77, %fd76, 0d0000000000000000; + div.rn.f64 %fd78, %fd77, 0d4028000000000000; + cvt.rn.f32.f64 %f192, %fd78; + add.f32 %f193, %f186, %f188; + sub.f32 %f194, %f193, %f180; + add.f32 %f195, %f194, 0f00000000; + cvt.f64.f32 %fd79, %f195; + add.f64 %fd80, %fd79, 0d0000000000000000; + div.rn.f64 %fd81, %fd80, 0d4028000000000000; + cvt.rn.f32.f64 %f196, %fd81; + ld.shared.f32 %f197, [%r6+2556]; + ld.shared.f32 %f198, [%r6+508]; + add.f32 %f199, %f198, %f197; + ld.shared.f32 %f200, [%r6+4092]; + add.f32 %f201, %f199, %f200; + ld.shared.f32 %f202, [%r6+1532]; + sub.f32 %f203, %f201, %f202; + ld.shared.f32 %f204, [%r6+3068]; + sub.f32 %f205, %f203, %f204; + ld.shared.f32 %f206, [%r6+3580]; + sub.f32 %f207, %f205, %f206; + ld.shared.f32 %f208, [%r6+1020]; + add.f32 %f209, %f208, %f197; + add.f32 %f210, %f209, %f204; + ld.shared.f32 %f211, [%r6+2044]; + sub.f32 %f212, %f210, %f211; + sub.f32 %f213, %f212, %f206; + sub.f32 %f214, %f213, %f200; + mul.f32 %f215, %f207, 0fC0000000; + mul.f32 %f216, %f207, %f215; + fma.rn.f32 %f217, %f207, 0f40000000, %f216; + fma.rn.f32 %f218, %f214, %f214, %f217; + cvt.f64.f32 %fd82, %f218; + sub.f64 %fd83, %fd73, %fd82; + div.rn.f64 %fd84, %fd83, 0d4018000000000000; + cvt.rn.f32.f64 %f219, %fd84; + mul.f32 %f220, %f207, %f207; + mul.f32 %f221, %f207, 0f40400000; + mul.f32 %f222, %f221, %f214; + sub.f32 %f223, %f220, %f222; + sub.f32 %f224, %f223, %f207; + fma.rn.f32 %f225, %f214, %f214, %f224; + add.f32 %f226, %f214, %f225; + cvt.f64.f32 %fd85, %f226; + add.f64 %fd86, %fd85, 0d0000000000000000; + div.rn.f64 %fd87, %fd86, 0d4028000000000000; + cvt.rn.f32.f64 %f227, %fd87; + add.f32 %f228, %f220, %f222; + sub.f32 %f229, %f228, %f207; + fma.rn.f32 %f230, %f214, %f214, %f229; + sub.f32 %f231, %f230, %f214; + cvt.f64.f32 %fd88, %f231; + add.f64 %fd89, %fd88, 0d0000000000000000; + div.rn.f64 %fd90, %fd89, 0d4028000000000000; + cvt.rn.f32.f64 %f232, %fd90; + sub.f32 %f233, %f202, %f219; + add.f32 %f390, %f233, %f185; + sub.f32 %f234, %f204, %f227; + add.f32 %f387, %f234, %f192; + sub.f32 %f235, %f206, %f232; + add.f32 %f386, %f235, %f196; + bra.uni $L__BB0_14; + +$L__BB0_8: + ld.shared.f32 %f48, [%r6]; + add.f32 %f49, %f392, %f388; + add.f32 %f50, %f49, %f385; + sub.f32 %f51, %f50, %f390; + sub.f32 %f52, %f51, %f387; + sub.f32 %f53, %f52, %f386; + add.f32 %f54, %f391, %f388; + add.f32 %f55, %f54, %f387; + sub.f32 %f56, %f55, %f389; + sub.f32 %f57, %f56, %f386; + sub.f32 %f58, %f57, %f385; + add.f32 %f59, %f48, %f392; + add.f32 %f60, %f59, %f391; + add.f32 %f61, %f60, %f390; + add.f32 %f62, %f61, %f389; + add.f32 %f63, %f62, %f388; + add.f32 %f64, %f63, %f387; + add.f32 %f65, %f64, %f386; + add.f32 %f66, %f65, %f385; + div.rn.f32 %f67, %f66, 0f40400000; + mul.f32 %f68, %f48, 0fC0800000; + sub.f32 %f69, %f68, %f392; + sub.f32 %f70, %f69, %f391; + sub.f32 %f71, %f70, %f390; + sub.f32 %f72, %f71, %f389; + fma.rn.f32 %f73, %f388, 0f40000000, %f72; + fma.rn.f32 %f74, %f387, 0f40000000, %f73; + fma.rn.f32 %f75, %f386, 0f40000000, %f74; + fma.rn.f32 %f76, %f385, 0f40000000, %f75; + add.f32 %f77, %f392, %f392; + mul.f32 %f78, %f48, 0f40800000; + sub.f32 %f79, %f78, %f77; + add.f32 %f80, %f391, %f391; + sub.f32 %f81, %f79, %f80; + add.f32 %f82, %f390, %f390; + sub.f32 %f83, %f81, %f82; + add.f32 %f84, %f389, %f389; + sub.f32 %f85, %f83, %f84; + add.f32 %f86, %f388, %f85; + add.f32 %f87, %f387, %f86; + add.f32 %f88, %f386, %f87; + add.f32 %f89, %f385, %f88; + sub.f32 %f90, %f392, %f390; + add.f32 %f91, %f90, %f388; + sub.f32 %f92, %f91, %f387; + sub.f32 %f93, %f92, %f386; + add.f32 %f94, %f93, %f385; + sub.f32 %f95, %f82, %f77; + add.f32 %f96, %f388, %f95; + sub.f32 %f97, %f96, %f387; + sub.f32 %f98, %f97, %f386; + add.f32 %f99, %f385, %f98; + sub.f32 %f100, %f391, %f389; + add.f32 %f101, %f100, %f388; + add.f32 %f102, %f101, %f387; + sub.f32 %f103, %f102, %f386; + sub.f32 %f104, %f103, %f385; + sub.f32 %f105, %f84, %f80; + add.f32 %f106, %f388, %f105; + add.f32 %f107, %f387, %f106; + sub.f32 %f108, %f107, %f386; + sub.f32 %f109, %f108, %f385; + sub.f32 %f110, %f392, %f391; + add.f32 %f111, %f110, %f390; + sub.f32 %f112, %f111, %f389; + sub.f32 %f113, %f388, %f387; + add.f32 %f114, %f113, %f386; + sub.f32 %f115, %f114, %f385; + mul.f32 %f116, %f67, 0f40400000; + sub.f32 %f117, %f116, %f66; + mul.f32 %f118, %f67, 0fC0C00000; + cvt.f64.f32 %fd1, %f118; + mul.f32 %f119, %f53, %f53; + mul.f32 %f120, %f58, %f58; + add.f32 %f121, %f119, %f120; + cvt.f64.f32 %fd2, %f121; + mul.f64 %fd3, %fd2, 0d4008000000000000; + add.f64 %fd4, %fd3, %fd1; + cvt.f64.f32 %fd5, %f76; + sub.f64 %fd6, %fd4, %fd5; + mul.f64 %fd7, %fd6, 0d3FF3333333333333; + cvt.rn.f32.f64 %f122, %fd7; + cvt.f64.f32 %fd8, %f116; + sub.f64 %fd9, %fd8, %fd3; + cvt.f64.f32 %fd10, %f89; + sub.f64 %fd11, %fd9, %fd10; + mul.f64 %fd12, %fd11, 0d3FF3333333333333; + cvt.rn.f32.f64 %f123, %fd12; + sub.f32 %f124, %f53, %f94; + cvt.f64.f32 %fd13, %f53; + neg.f64 %fd14, %fd13; + cvt.f64.f32 %fd15, %f99; + sub.f64 %fd16, %fd14, %fd15; + mul.f64 %fd17, %fd16, 0d3FF3333333333333; + cvt.rn.f32.f64 %f125, %fd17; + sub.f32 %f126, %f58, %f104; + cvt.f64.f32 %fd18, %f58; + neg.f64 %fd19, %fd18; + cvt.f64.f32 %fd20, %f109; + sub.f64 %fd21, %fd19, %fd20; + mul.f64 %fd22, %fd21, 0d3FF3333333333333; + cvt.rn.f32.f64 %f127, %fd22; + sub.f32 %f128, %f119, %f120; + cvt.f64.f32 %fd23, %f128; + cvt.f64.f32 %fd24, %f112; + sub.f64 %fd25, %fd23, %fd24; + mul.f64 %fd26, %fd25, 0d3FFF400000000000; + cvt.rn.f32.f64 %f129, %fd26; + mul.f64 %fd27, %fd13, %fd18; + cvt.f64.f32 %fd28, %f115; + sub.f64 %fd29, %fd27, %fd28; + mul.f64 %fd30, %fd29, 0d3FFF400000000000; + cvt.rn.f32.f64 %f130, %fd30; + sub.f32 %f131, %f117, %f122; + add.f32 %f132, %f131, %f123; + cvt.f64.f32 %fd31, %f132; + div.rn.f64 %fd32, %fd31, 0d4022000000000000; + cvt.f64.f32 %fd33, %f48; + add.f64 %fd34, %fd32, %fd33; + cvt.rn.f32.f64 %f133, %fd34; + mul.f32 %f134, %f117, 0f40800000; + sub.f32 %f135, %f134, %f122; + add.f32 %f136, %f123, %f123; + sub.f32 %f137, %f135, %f136; + mul.f32 %f138, %f124, 0f40C00000; + add.f32 %f139, %f137, %f138; + mul.f32 %f140, %f125, 0f40C00000; + sub.f32 %f141, %f139, %f140; + mul.f32 %f142, %f129, 0f41100000; + add.f32 %f143, %f141, %f142; + cvt.f64.f32 %fd35, %f143; + div.rn.f64 %fd36, %fd35, 0d4042000000000000; + cvt.f64.f32 %fd37, %f392; + add.f64 %fd38, %fd36, %fd37; + cvt.rn.f32.f64 %f392, %fd38; + mul.f32 %f144, %f126, 0f40C00000; + add.f32 %f145, %f137, %f144; + mul.f32 %f146, %f127, 0f40C00000; + sub.f32 %f147, %f145, %f146; + sub.f32 %f148, %f147, %f142; + cvt.f64.f32 %fd39, %f148; + div.rn.f64 %fd40, %fd39, 0d4042000000000000; + cvt.f64.f32 %fd41, %f391; + add.f64 %fd42, %fd40, %fd41; + cvt.rn.f32.f64 %f391, %fd42; + sub.f32 %f149, %f137, %f138; + add.f32 %f150, %f149, %f140; + add.f32 %f151, %f150, %f142; + cvt.f64.f32 %fd43, %f151; + div.rn.f64 %fd44, %fd43, 0d4042000000000000; + cvt.f64.f32 %fd45, %f390; + add.f64 %fd46, %fd44, %fd45; + cvt.rn.f32.f64 %f390, %fd46; + sub.f32 %f152, %f137, %f144; + add.f32 %f153, %f152, %f146; + sub.f32 %f154, %f153, %f142; + cvt.f64.f32 %fd47, %f154; + div.rn.f64 %fd48, %fd47, 0d4042000000000000; + cvt.f64.f32 %fd49, %f389; + add.f64 %fd50, %fd48, %fd49; + cvt.rn.f32.f64 %f389, %fd50; + fma.rn.f32 %f155, %f122, 0f40000000, %f134; + add.f32 %f156, %f155, %f123; + add.f32 %f157, %f156, %f138; + mul.f32 %f158, %f125, 0f40400000; + add.f32 %f159, %f157, %f158; + add.f32 %f160, %f159, %f144; + mul.f32 %f161, %f127, 0f40400000; + add.f32 %f162, %f160, %f161; + mul.f32 %f163, %f130, 0f41100000; + add.f32 %f164, %f162, %f163; + cvt.f64.f32 %fd51, %f164; + div.rn.f64 %fd52, %fd51, 0d4042000000000000; + cvt.f64.f32 %fd53, %f388; + add.f64 %fd54, %fd52, %fd53; + cvt.rn.f32.f64 %f388, %fd54; + sub.f32 %f165, %f156, %f138; + sub.f32 %f166, %f165, %f158; + add.f32 %f167, %f166, %f144; + add.f32 %f168, %f167, %f161; + sub.f32 %f169, %f168, %f163; + cvt.f64.f32 %fd55, %f169; + div.rn.f64 %fd56, %fd55, 0d4042000000000000; + cvt.f64.f32 %fd57, %f387; + add.f64 %fd58, %fd56, %fd57; + cvt.rn.f32.f64 %f387, %fd58; + sub.f32 %f170, %f166, %f144; + sub.f32 %f171, %f170, %f161; + add.f32 %f172, %f171, %f163; + cvt.f64.f32 %fd59, %f172; + div.rn.f64 %fd60, %fd59, 0d4042000000000000; + cvt.f64.f32 %fd61, %f386; + add.f64 %fd62, %fd60, %fd61; + cvt.rn.f32.f64 %f386, %fd62; + sub.f32 %f173, %f159, %f144; + sub.f32 %f174, %f173, %f161; + sub.f32 %f175, %f174, %f163; + cvt.f64.f32 %fd63, %f175; + div.rn.f64 %fd64, %fd63, 0d4042000000000000; + cvt.f64.f32 %fd65, %f385; + add.f64 %fd66, %fd64, %fd65; + cvt.rn.f32.f64 %f385, %fd66; + st.shared.f32 [%r6], %f133; + st.shared.f32 [%r6+512], %f392; + st.shared.f32 [%r6+1024], %f391; + st.shared.f32 [%r6+1536], %f390; + st.shared.f32 [%r6+2048], %f389; + st.shared.f32 [%r6+2560], %f388; + st.shared.f32 [%r6+3072], %f387; + st.shared.f32 [%r6+3584], %f386; + st.shared.f32 [%r6+4096], %f385; + bra.uni $L__BB0_15; + +$L__BB0_13: + ld.shared.f32 %f236, [%r6+516]; + ld.shared.f32 %f237, [%r6+4]; + add.f32 %f238, %f237, %f236; + ld.shared.f32 %f239, [%r6+1028]; + add.f32 %f240, %f238, %f239; + ld.shared.f32 %f241, [%r6+1540]; + add.f32 %f242, %f240, %f241; + ld.shared.f32 %f243, [%r6+2052]; + add.f32 %f244, %f242, %f243; + ld.shared.f32 %f245, [%r6+2564]; + add.f32 %f246, %f244, %f245; + ld.shared.f32 %f247, [%r6+3076]; + add.f32 %f248, %f246, %f247; + ld.shared.f32 %f249, [%r6+3588]; + add.f32 %f250, %f248, %f249; + ld.shared.f32 %f251, [%r6+4100]; + add.f32 %f252, %f250, %f251; + div.rn.f32 %f253, %f252, 0f40400000; + cvt.rn.f32.s32 %f254, %r4; + cvt.f64.f32 %fd91, %f254; + add.f64 %fd92, %fd91, 0dC06FF00000000000; + div.rn.f64 %fd93, %fd92, 0d407FE00000000000; + cvt.rn.f32.f64 %f255, %fd93; + mul.f32 %f256, %f255, 0fC0800000; + fma.rn.f32 %f257, %f256, %f255, 0f3F800000; + cvt.f64.f32 %fd94, %f257; + mul.f64 %fd95, %fd94, 0d3F8EB851EB851EB8; + cvt.rn.f32.f64 %f258, %fd95; + add.f32 %f259, %f253, %f253; + cvt.f64.f32 %fd96, %f259; + add.f32 %f260, %f258, %f258; + fma.rn.f32 %f261, %f260, %f258, %f260; + cvt.f64.f32 %fd97, %f261; + add.f64 %fd98, %fd97, %fd96; + div.rn.f64 %fd99, %fd98, 0d4018000000000000; + cvt.rn.f32.f64 %f262, %fd99; + cvt.f64.f32 %fd100, %f253; + mul.f32 %f263, %f258, %f258; + mul.f32 %f264, %f258, 0f40400000; + mul.f32 %f265, %f264, 0f00000000; + add.f32 %f266, %f263, %f265; + add.f32 %f267, %f266, %f258; + add.f32 %f268, %f267, 0f00000000; + cvt.f64.f32 %fd101, %f268; + add.f64 %fd102, %fd101, %fd100; + div.rn.f64 %fd103, %fd102, 0d4028000000000000; + cvt.rn.f32.f64 %f269, %fd103; + sub.f32 %f270, %f263, %f265; + add.f32 %f271, %f270, %f258; + add.f32 %f272, %f271, 0f00000000; + cvt.f64.f32 %fd104, %f272; + add.f64 %fd105, %fd104, %fd100; + div.rn.f64 %fd106, %fd105, 0d4028000000000000; + cvt.rn.f32.f64 %f273, %fd106; + add.f32 %f274, %f236, %f245; + add.f32 %f275, %f274, %f251; + sub.f32 %f276, %f275, %f241; + sub.f32 %f277, %f276, %f247; + sub.f32 %f278, %f277, %f249; + add.f32 %f279, %f239, %f245; + add.f32 %f280, %f279, %f247; + sub.f32 %f281, %f280, %f243; + sub.f32 %f282, %f281, %f249; + sub.f32 %f283, %f282, %f251; + add.f32 %f284, %f278, %f278; + fma.rn.f32 %f285, %f278, %f284, %f284; + mul.f32 %f286, %f283, %f283; + sub.f32 %f287, %f285, %f286; + cvt.f64.f32 %fd107, %f287; + add.f64 %fd108, %fd96, %fd107; + div.rn.f64 %fd109, %fd108, 0d4018000000000000; + cvt.rn.f32.f64 %f288, %fd109; + mul.f32 %f289, %f278, %f278; + mul.f32 %f290, %f278, 0f40400000; + mul.f32 %f291, %f290, %f283; + add.f32 %f292, %f289, %f291; + add.f32 %f293, %f278, %f292; + add.f32 %f294, %f286, %f293; + add.f32 %f295, %f283, %f294; + cvt.f64.f32 %fd110, %f295; + add.f64 %fd111, %fd100, %fd110; + div.rn.f64 %fd112, %fd111, 0d4028000000000000; + cvt.rn.f32.f64 %f296, %fd112; + sub.f32 %f297, %f289, %f291; + add.f32 %f298, %f278, %f297; + add.f32 %f299, %f286, %f298; + sub.f32 %f300, %f299, %f283; + cvt.f64.f32 %fd113, %f300; + add.f64 %fd114, %fd100, %fd113; + div.rn.f64 %fd115, %fd114, 0d4028000000000000; + cvt.rn.f32.f64 %f301, %fd115; + sub.f32 %f302, %f236, %f288; + add.f32 %f392, %f302, %f262; + sub.f32 %f303, %f245, %f296; + add.f32 %f388, %f303, %f269; + sub.f32 %f304, %f251, %f301; + add.f32 %f385, %f304, %f273; + +$L__BB0_14: + st.shared.f32 [%r6+512], %f392; + st.shared.f32 [%r6+1536], %f390; + st.shared.f32 [%r6+2560], %f388; + st.shared.f32 [%r6+3072], %f387; + st.shared.f32 [%r6+3584], %f386; + st.shared.f32 [%r6+4096], %f385; + +$L__BB0_15: + bar.sync 0; + add.s32 %r23, %r3, 655360; + setp.eq.s32 %p13, %r4, 0; + @%p13 bra $L__BB0_52; + + setp.eq.s32 %p14, %r4, 511; + @%p14 bra $L__BB0_52; + + setp.eq.s32 %p15, %r4, 510; + ld.const.u32 %r74, [e+4]; + add.s32 %r24, %r74, %r4; + setp.eq.s32 %p16, %r24, 0; + setp.eq.s32 %p17, %r4, 1; + and.pred %p18, %p17, %p16; + setp.eq.s32 %p19, %r24, 511; + and.pred %p20, %p15, %p19; + or.pred %p21, %p18, %p20; + @%p21 bra $L__BB0_19; + bra.uni $L__BB0_18; + +$L__BB0_19: + cvt.u32.u64 %r84, %rd2; + ld.shared.f32 %f306, [%r6]; + ld.const.u32 %r85, [opp]; + mad.lo.s32 %r86, %r85, 655360, %r84; + mul.wide.s32 %rd39, %r86, 4; + add.s64 %rd40, %rd1, %rd39; + st.global.f32 [%rd40], %f306; + bra.uni $L__BB0_20; + +$L__BB0_18: + ld.const.u32 %r75, [e]; + add.s32 %r76, %r23, %r75; + mad.lo.s32 %r77, %r24, 1280, %r76; + mul.hi.s32 %r78, %r77, 1717986919; + shr.u32 %r79, %r78, 31; + shr.s32 %r80, %r78, 18; + add.s32 %r81, %r80, %r79; + mul.lo.s32 %r82, %r81, 655360; + sub.s32 %r83, %r77, %r82; + ld.shared.f32 %f305, [%r6]; + mul.wide.s32 %rd37, %r83, 4; + add.s64 %rd38, %rd1, %rd37; + st.global.f32 [%rd38], %f305; + +$L__BB0_20: + ld.const.u32 %r87, [e+12]; + add.s32 %r25, %r87, %r4; + @%p14 bra $L__BB0_24; + + setp.eq.s32 %p24, %r25, 0; + and.pred %p26, %p17, %p24; + setp.eq.s32 %p27, %r25, 511; + and.pred %p28, %p15, %p27; + or.pred %p29, %p26, %p28; + @%p29 bra $L__BB0_23; + bra.uni $L__BB0_22; + +$L__BB0_23: + cvt.u32.u64 %r98, %rd2; + ld.shared.f32 %f308, [%r6+512]; + ld.const.u32 %r99, [opp+4]; + mad.lo.s32 %r100, %r99, 655360, %r98; + mul.wide.s32 %rd43, %r100, 4; + add.s64 %rd44, %rd1, %rd43; + st.global.f32 [%rd44], %f308; + bra.uni $L__BB0_24; + +$L__BB0_22: + ld.const.u32 %r88, [e+8]; + add.s32 %r89, %r23, %r88; + mad.lo.s32 %r90, %r25, 1280, %r89; + mul.hi.s32 %r91, %r90, 1717986919; + shr.u32 %r92, %r91, 31; + shr.s32 %r93, %r91, 18; + add.s32 %r94, %r93, %r92; + mul.lo.s32 %r95, %r94, 655360; + sub.s32 %r96, %r90, %r95; + ld.shared.f32 %f307, [%r6+512]; + add.s32 %r97, %r96, 655360; + mul.wide.s32 %rd41, %r97, 4; + add.s64 %rd42, %rd1, %rd41; + st.global.f32 [%rd42], %f307; + +$L__BB0_24: + ld.const.u32 %r101, [e+20]; + add.s32 %r26, %r101, %r4; + @%p14 bra $L__BB0_28; + + setp.eq.s32 %p32, %r26, 0; + and.pred %p34, %p17, %p32; + setp.eq.s32 %p35, %r26, 511; + and.pred %p36, %p15, %p35; + or.pred %p37, %p34, %p36; + @%p37 bra $L__BB0_27; + bra.uni $L__BB0_26; + +$L__BB0_27: + cvt.u32.u64 %r112, %rd2; + ld.shared.f32 %f310, [%r6+1024]; + ld.const.u32 %r113, [opp+8]; + mad.lo.s32 %r114, %r113, 655360, %r112; + mul.wide.s32 %rd47, %r114, 4; + add.s64 %rd48, %rd1, %rd47; + st.global.f32 [%rd48], %f310; + bra.uni $L__BB0_28; + +$L__BB0_26: + ld.const.u32 %r102, [e+16]; + add.s32 %r103, %r23, %r102; + mad.lo.s32 %r104, %r26, 1280, %r103; + mul.hi.s32 %r105, %r104, 1717986919; + shr.u32 %r106, %r105, 31; + shr.s32 %r107, %r105, 18; + add.s32 %r108, %r107, %r106; + mul.lo.s32 %r109, %r108, 655360; + sub.s32 %r110, %r104, %r109; + ld.shared.f32 %f309, [%r6+1024]; + add.s32 %r111, %r110, 1310720; + mul.wide.s32 %rd45, %r111, 4; + add.s64 %rd46, %rd1, %rd45; + st.global.f32 [%rd46], %f309; + +$L__BB0_28: + ld.const.u32 %r115, [e+28]; + add.s32 %r27, %r115, %r4; + @%p14 bra $L__BB0_32; + + setp.eq.s32 %p40, %r27, 0; + and.pred %p42, %p17, %p40; + setp.eq.s32 %p43, %r27, 511; + and.pred %p44, %p15, %p43; + or.pred %p45, %p42, %p44; + @%p45 bra $L__BB0_31; + bra.uni $L__BB0_30; + +$L__BB0_31: + cvt.u32.u64 %r126, %rd2; + ld.shared.f32 %f312, [%r6+1536]; + ld.const.u32 %r127, [opp+12]; + mad.lo.s32 %r128, %r127, 655360, %r126; + mul.wide.s32 %rd51, %r128, 4; + add.s64 %rd52, %rd1, %rd51; + st.global.f32 [%rd52], %f312; + bra.uni $L__BB0_32; + +$L__BB0_30: + ld.const.u32 %r116, [e+24]; + add.s32 %r117, %r23, %r116; + mad.lo.s32 %r118, %r27, 1280, %r117; + mul.hi.s32 %r119, %r118, 1717986919; + shr.u32 %r120, %r119, 31; + shr.s32 %r121, %r119, 18; + add.s32 %r122, %r121, %r120; + mul.lo.s32 %r123, %r122, 655360; + sub.s32 %r124, %r118, %r123; + ld.shared.f32 %f311, [%r6+1536]; + add.s32 %r125, %r124, 1966080; + mul.wide.s32 %rd49, %r125, 4; + add.s64 %rd50, %rd1, %rd49; + st.global.f32 [%rd50], %f311; + +$L__BB0_32: + ld.const.u32 %r129, [e+36]; + add.s32 %r28, %r129, %r4; + @%p14 bra $L__BB0_36; + + setp.eq.s32 %p48, %r28, 0; + and.pred %p50, %p17, %p48; + setp.eq.s32 %p51, %r28, 511; + and.pred %p52, %p15, %p51; + or.pred %p53, %p50, %p52; + @%p53 bra $L__BB0_35; + bra.uni $L__BB0_34; + +$L__BB0_35: + cvt.u32.u64 %r140, %rd2; + ld.shared.f32 %f314, [%r6+2048]; + ld.const.u32 %r141, [opp+16]; + mad.lo.s32 %r142, %r141, 655360, %r140; + mul.wide.s32 %rd55, %r142, 4; + add.s64 %rd56, %rd1, %rd55; + st.global.f32 [%rd56], %f314; + bra.uni $L__BB0_36; + +$L__BB0_34: + ld.const.u32 %r130, [e+32]; + add.s32 %r131, %r23, %r130; + mad.lo.s32 %r132, %r28, 1280, %r131; + mul.hi.s32 %r133, %r132, 1717986919; + shr.u32 %r134, %r133, 31; + shr.s32 %r135, %r133, 18; + add.s32 %r136, %r135, %r134; + mul.lo.s32 %r137, %r136, 655360; + sub.s32 %r138, %r132, %r137; + ld.shared.f32 %f313, [%r6+2048]; + add.s32 %r139, %r138, 2621440; + mul.wide.s32 %rd53, %r139, 4; + add.s64 %rd54, %rd1, %rd53; + st.global.f32 [%rd54], %f313; + +$L__BB0_36: + ld.const.u32 %r143, [e+44]; + add.s32 %r29, %r143, %r4; + @%p14 bra $L__BB0_40; + + setp.eq.s32 %p56, %r29, 0; + and.pred %p58, %p17, %p56; + setp.eq.s32 %p59, %r29, 511; + and.pred %p60, %p15, %p59; + or.pred %p61, %p58, %p60; + @%p61 bra $L__BB0_39; + bra.uni $L__BB0_38; + +$L__BB0_39: + cvt.u32.u64 %r154, %rd2; + ld.shared.f32 %f316, [%r6+2560]; + ld.const.u32 %r155, [opp+20]; + mad.lo.s32 %r156, %r155, 655360, %r154; + mul.wide.s32 %rd59, %r156, 4; + add.s64 %rd60, %rd1, %rd59; + st.global.f32 [%rd60], %f316; + bra.uni $L__BB0_40; + +$L__BB0_38: + ld.const.u32 %r144, [e+40]; + add.s32 %r145, %r23, %r144; + mad.lo.s32 %r146, %r29, 1280, %r145; + mul.hi.s32 %r147, %r146, 1717986919; + shr.u32 %r148, %r147, 31; + shr.s32 %r149, %r147, 18; + add.s32 %r150, %r149, %r148; + mul.lo.s32 %r151, %r150, 655360; + sub.s32 %r152, %r146, %r151; + ld.shared.f32 %f315, [%r6+2560]; + add.s32 %r153, %r152, 3276800; + mul.wide.s32 %rd57, %r153, 4; + add.s64 %rd58, %rd1, %rd57; + st.global.f32 [%rd58], %f315; + +$L__BB0_40: + ld.const.u32 %r157, [e+52]; + add.s32 %r30, %r157, %r4; + @%p14 bra $L__BB0_44; + + setp.eq.s32 %p64, %r30, 0; + and.pred %p66, %p17, %p64; + setp.eq.s32 %p67, %r30, 511; + and.pred %p68, %p15, %p67; + or.pred %p69, %p66, %p68; + @%p69 bra $L__BB0_43; + bra.uni $L__BB0_42; + +$L__BB0_43: + cvt.u32.u64 %r168, %rd2; + ld.shared.f32 %f318, [%r6+3072]; + ld.const.u32 %r169, [opp+24]; + mad.lo.s32 %r170, %r169, 655360, %r168; + mul.wide.s32 %rd63, %r170, 4; + add.s64 %rd64, %rd1, %rd63; + st.global.f32 [%rd64], %f318; + bra.uni $L__BB0_44; + +$L__BB0_42: + ld.const.u32 %r158, [e+48]; + add.s32 %r159, %r23, %r158; + mad.lo.s32 %r160, %r30, 1280, %r159; + mul.hi.s32 %r161, %r160, 1717986919; + shr.u32 %r162, %r161, 31; + shr.s32 %r163, %r161, 18; + add.s32 %r164, %r163, %r162; + mul.lo.s32 %r165, %r164, 655360; + sub.s32 %r166, %r160, %r165; + ld.shared.f32 %f317, [%r6+3072]; + add.s32 %r167, %r166, 3932160; + mul.wide.s32 %rd61, %r167, 4; + add.s64 %rd62, %rd1, %rd61; + st.global.f32 [%rd62], %f317; + +$L__BB0_44: + ld.const.u32 %r171, [e+60]; + add.s32 %r31, %r171, %r4; + @%p14 bra $L__BB0_48; + + setp.eq.s32 %p72, %r31, 0; + and.pred %p74, %p17, %p72; + setp.eq.s32 %p75, %r31, 511; + and.pred %p76, %p15, %p75; + or.pred %p77, %p74, %p76; + @%p77 bra $L__BB0_47; + bra.uni $L__BB0_46; + +$L__BB0_47: + cvt.u32.u64 %r182, %rd2; + ld.shared.f32 %f320, [%r6+3584]; + ld.const.u32 %r183, [opp+28]; + mad.lo.s32 %r184, %r183, 655360, %r182; + mul.wide.s32 %rd67, %r184, 4; + add.s64 %rd68, %rd1, %rd67; + st.global.f32 [%rd68], %f320; + bra.uni $L__BB0_48; + +$L__BB0_46: + ld.const.u32 %r172, [e+56]; + add.s32 %r173, %r23, %r172; + mad.lo.s32 %r174, %r31, 1280, %r173; + mul.hi.s32 %r175, %r174, 1717986919; + shr.u32 %r176, %r175, 31; + shr.s32 %r177, %r175, 18; + add.s32 %r178, %r177, %r176; + mul.lo.s32 %r179, %r178, 655360; + sub.s32 %r180, %r174, %r179; + ld.shared.f32 %f319, [%r6+3584]; + add.s32 %r181, %r180, 4587520; + mul.wide.s32 %rd65, %r181, 4; + add.s64 %rd66, %rd1, %rd65; + st.global.f32 [%rd66], %f319; + +$L__BB0_48: + ld.const.u32 %r185, [e+68]; + add.s32 %r32, %r185, %r4; + @%p14 bra $L__BB0_52; + + setp.eq.s32 %p80, %r32, 0; + and.pred %p82, %p17, %p80; + setp.eq.s32 %p83, %r32, 511; + and.pred %p84, %p15, %p83; + or.pred %p85, %p82, %p84; + @%p85 bra $L__BB0_51; + bra.uni $L__BB0_50; + +$L__BB0_51: + cvt.u32.u64 %r196, %rd2; + ld.shared.f32 %f322, [%r6+4096]; + ld.const.u32 %r197, [opp+32]; + mad.lo.s32 %r198, %r197, 655360, %r196; + mul.wide.s32 %rd71, %r198, 4; + add.s64 %rd72, %rd1, %rd71; + st.global.f32 [%rd72], %f322; + bra.uni $L__BB0_52; + +$L__BB0_50: + ld.const.u32 %r186, [e+64]; + add.s32 %r187, %r23, %r186; + mad.lo.s32 %r188, %r32, 1280, %r187; + mul.hi.s32 %r189, %r188, 1717986919; + shr.u32 %r190, %r189, 31; + shr.s32 %r191, %r189, 18; + add.s32 %r192, %r191, %r190; + mul.lo.s32 %r193, %r192, 655360; + sub.s32 %r194, %r188, %r193; + ld.shared.f32 %f321, [%r6+4096]; + add.s32 %r195, %r194, 5242880; + mul.wide.s32 %rd69, %r195, 4; + add.s64 %rd70, %rd1, %rd69; + st.global.f32 [%rd70], %f321; + +$L__BB0_52: + bar.sync 0; + ld.global.u8 %rs11, [%rd6]; + and.b16 %rs7, %rs11, 10; + setp.ne.s16 %p86, %rs7, 10; + @%p86 bra $L__BB0_58; + + cvta.to.global.u64 %rd76, %rd25; + shl.b64 %rd77, %rd3, 2; + add.s64 %rd78, %rd76, %rd77; + ld.global.u32 %r200, [%rd78]; + cvta.to.global.u64 %rd79, %rd26; + mul.wide.s32 %rd80, %r200, 4; + add.s64 %rd81, %rd79, %rd80; + ld.global.f32 %f323, [%rd78+36]; + ld.global.f32 %f324, [%rd81]; + mul.f32 %f37, %f324, %f323; + ld.global.f32 %f325, [%rd78+40]; + mul.f32 %f38, %f324, %f325; + shl.b32 %r201, %r200, 3; + mov.u32 %r202, _ZZ7OneStepE9obs_share; + add.s32 %r33, %r202, %r201; + add.s32 %r203, %r247, %r5; + add.s32 %r204, %r203, %r1; + mul.wide.s32 %rd82, %r204, 4; + add.s64 %rd83, %rd1, %rd82; + add.s64 %rd105, %rd83, 2621440; + add.s32 %r243, %r204, 655360; + mov.u32 %r242, 655360; + add.s64 %rd104, %rd78, 4; + mov.u64 %rd103, opp; + mov.u64 %rd102, w; + mov.u64 %rd101, e; + +$L__BB0_54: + ld.const.u32 %r38, [%rd101+8]; + add.s32 %r205, %r38, %r3; + ld.const.u32 %r39, [%rd101+12]; + add.s32 %r206, %r39, %r4; + mad.lo.s32 %r40, %r206, 1280, %r205; + cvt.s64.s32 %rd84, %r40; + add.s64 %rd85, %rd5, %rd84; + ld.global.u8 %rs8, [%rd85]; + and.b16 %rs9, %rs8, 1; + setp.eq.b16 %p87, %rs9, 1; + mov.pred %p88, 0; + xor.pred %p89, %p87, %p88; + not.pred %p90, %p89; + @%p90 bra $L__BB0_56; + + cvt.u32.u64 %r207, %rd2; + ld.const.f32 %f326, [%rd102+4]; + mul.f32 %f327, %f326, 0f40C00000; + cvt.rn.f32.s32 %f328, %r38; + cvt.rn.f32.s32 %f329, %r39; + mul.f32 %f330, %f38, %f329; + fma.rn.f32 %f331, %f37, %f328, %f330; + mul.f32 %f332, %f327, %f331; + ld.const.u32 %r208, [%rd103+4]; + mul.lo.s32 %r209, %r208, 655360; + add.s32 %r210, %r209, %r207; + mul.wide.s32 %rd86, %r210, 4; + add.s64 %rd87, %rd1, %rd86; + ld.global.f32 %f333, [%rd87]; + ld.global.f32 %f334, [%rd104]; + mov.f32 %f335, 0f3F800000; + sub.f32 %f336, %f335, %f334; + add.s32 %r211, %r209, %r40; + mul.wide.s32 %rd88, %r211, 4; + add.s64 %rd89, %rd1, %rd88; + ld.global.f32 %f337, [%rd89]; + mul.f32 %f338, %f336, %f337; + fma.rn.f32 %f339, %f334, %f333, %f338; + shl.b32 %r212, %r38, 1; + mad.lo.s32 %r213, %r39, 2560, %r212; + add.s32 %r214, %r243, %r213; + mul.wide.s32 %rd90, %r214, 4; + add.s64 %rd91, %rd1, %rd90; + ld.global.f32 %f340, [%rd91]; + fma.rn.f32 %f341, %f334, %f340, %f339; + add.f32 %f342, %f332, %f341; + add.f32 %f343, %f334, 0f3F800000; + div.rn.f32 %f344, %f342, %f343; + mul.lo.s32 %r215, %r39, 1280; + add.s32 %r216, %r38, %r215; + add.s32 %r217, %r243, %r216; + mul.wide.s32 %rd92, %r217, 4; + add.s64 %rd93, %rd1, %rd92; + st.global.f32 [%rd93], %f344; + mul.f32 %f345, %f37, %f332; + st.global.f32 [%rd105], %f345; + mul.f32 %f346, %f38, %f332; + neg.s32 %r218, %r38; + sub.s32 %r219, %r218, %r215; + add.s32 %r220, %r243, %r219; + mul.wide.s32 %rd94, %r220, 4; + add.s64 %rd95, %rd1, %rd94; + st.global.f32 [%rd95], %f346; + ld.global.f32 %f347, [%rd87]; + ld.global.f32 %f348, [%rd93]; + add.f32 %f349, %f348, %f347; + mul.f32 %f350, %f349, %f328; + ld.global.f32 %f351, [%rd105]; + sub.f32 %f352, %f351, %f350; + atom.shared.add.f32 %f353, [%r33], %f352; + mul.f32 %f354, %f349, %f329; + sub.f32 %f355, %f346, %f354; + add.s32 %r235, %r33, 4; + atom.shared.add.f32 %f356, [%r235], %f355; + +$L__BB0_56: + add.s64 %rd105, %rd105, 2621440; + add.s32 %r243, %r243, 655360; + add.s64 %rd104, %rd104, 4; + add.s64 %rd103, %rd103, 4; + add.s64 %rd102, %rd102, 4; + add.s64 %rd101, %rd101, 8; + add.s32 %r242, %r242, 655360; + setp.ne.s32 %p91, %r242, 5898240; + @%p91 bra $L__BB0_54; + + ld.global.u8 %rs11, [%rd6]; + +$L__BB0_58: + and.b16 %rs10, %rs11, 16; + setp.eq.s16 %p92, %rs10, 0; + @%p92 bra $L__BB0_60; + + cvt.u32.u64 %r221, %rd3; + add.f32 %f357, %f392, %f388; + add.f32 %f358, %f357, %f385; + sub.f32 %f359, %f358, %f390; + sub.f32 %f360, %f359, %f387; + sub.f32 %f361, %f360, %f386; + add.f32 %f362, %f391, %f388; + add.f32 %f363, %f362, %f387; + sub.f32 %f364, %f363, %f389; + sub.f32 %f365, %f364, %f386; + sub.f32 %f366, %f365, %f385; + shl.b32 %r222, %r221, 3; + mov.u32 %r223, _ZZ7OneStepE9obs_share; + add.s32 %r224, %r223, %r222; + atom.shared.add.f32 %f367, [%r224], %f361; + add.s32 %r225, %r224, 4; + atom.shared.add.f32 %f368, [%r225], %f366; + +$L__BB0_60: + bar.sync 0; + @%p1 bra $L__BB0_67; + + max.s32 %r226, %r247, -114; + add.s32 %r227, %r226, 127; + sub.s32 %r43, %r227, %r247; + shr.u32 %r228, %r43, 7; + add.s32 %r229, %r228, 1; + and.b32 %r246, %r229, 3; + setp.eq.s32 %p94, %r246, 0; + @%p94 bra $L__BB0_64; + + mov.u32 %r231, _ZZ7OneStepE9obs_share; + add.s32 %r244, %r231, %r61; + mul.wide.s32 %rd96, %r247, 4; + add.s64 %rd106, %rd4, %rd96; + +$L__BB0_63: + .pragma "nounroll"; + ld.shared.f32 %f369, [%r244]; + atom.global.add.f32 %f370, [%rd106], %f369; + add.s32 %r247, %r247, 128; + add.s32 %r244, %r244, 512; + add.s64 %rd106, %rd106, 512; + add.s32 %r246, %r246, -1; + setp.ne.s32 %p95, %r246, 0; + @%p95 bra $L__BB0_63; + +$L__BB0_64: + setp.lt.u32 %p96, %r43, 384; + @%p96 bra $L__BB0_67; + + add.s32 %r249, %r247, -512; + mul.wide.s32 %rd97, %r247, 4; + add.s64 %rd107, %rd4, %rd97; + shl.b32 %r232, %r247, 2; + mov.u32 %r233, _ZZ7OneStepE9obs_share; + add.s32 %r234, %r233, %r232; + add.s32 %r248, %r234, 1024; + +$L__BB0_66: + ld.shared.f32 %f371, [%r248+-1024]; + atom.global.add.f32 %f372, [%rd107], %f371; + ld.shared.f32 %f373, [%r248+-512]; + add.s64 %rd98, %rd107, 512; + atom.global.add.f32 %f374, [%rd98], %f373; + ld.shared.f32 %f375, [%r248]; + add.s64 %rd99, %rd107, 1024; + atom.global.add.f32 %f376, [%rd99], %f375; + ld.shared.f32 %f377, [%r248+512]; + add.s64 %rd100, %rd107, 1536; + atom.global.add.f32 %f378, [%rd100], %f377; + add.s64 %rd107, %rd107, 2048; + add.s32 %r248, %r248, 2048; + add.s32 %r249, %r249, 512; + setp.lt.s32 %p97, %r249, -498; + @%p97 bra $L__BB0_66; + +$L__BB0_67: + ret; + +} + // .globl InitTubeFlow +.visible .entry InitTubeFlow( + .param .u64 InitTubeFlow_param_0, + .param .u64 InitTubeFlow_param_1 +) +{ + .reg .pred %p<8>; + .reg .b16 %rs<5>; + .reg .f32 %f<59>; + .reg .b32 %r<31>; + .reg .f64 %fd<92>; + .reg .b64 %rd<9>; + // demoted variable + .shared .align 4 .b8 _ZZ12InitTubeFlowE7f_share[4608]; + // demoted variable + .shared .align 1 .b8 _ZZ12InitTubeFlowE10flag_share[128]; + + ld.param.u64 %rd3, [InitTubeFlow_param_0]; + ld.param.u64 %rd4, [InitTubeFlow_param_1]; + cvta.to.global.u64 %rd5, %rd4; + mov.u32 %r4, %ctaid.x; + shl.b32 %r5, %r4, 7; + mov.u32 %r6, %tid.x; + add.s32 %r7, %r5, %r6; + mov.u32 %r1, %ctaid.y; + mad.lo.s32 %r8, %r1, 1280, %r7; + cvt.s64.s32 %rd6, %r8; + cvta.to.global.u64 %rd7, %rd3; + add.s64 %rd1, %rd7, %rd6; + ld.global.u8 %rs1, [%rd1]; + mov.u32 %r9, _ZZ12InitTubeFlowE10flag_share; + add.s32 %r2, %r9, %r6; + st.shared.u8 [%r2], %rs1; + mul.wide.s32 %rd8, %r8, 4; + add.s64 %rd2, %rd5, %rd8; + ld.global.f32 %f3, [%rd2]; + shl.b32 %r10, %r6, 2; + mov.u32 %r11, _ZZ12InitTubeFlowE7f_share; + add.s32 %r3, %r11, %r10; + st.shared.f32 [%r3], %f3; + ld.global.f32 %f4, [%rd2+2621440]; + st.shared.f32 [%r3+512], %f4; + ld.global.f32 %f5, [%rd2+5242880]; + st.shared.f32 [%r3+1024], %f5; + ld.global.f32 %f6, [%rd2+7864320]; + st.shared.f32 [%r3+1536], %f6; + ld.global.f32 %f7, [%rd2+10485760]; + st.shared.f32 [%r3+2048], %f7; + ld.global.f32 %f8, [%rd2+13107200]; + st.shared.f32 [%r3+2560], %f8; + ld.global.f32 %f9, [%rd2+15728640]; + st.shared.f32 [%r3+3072], %f9; + ld.global.f32 %f10, [%rd2+18350080]; + st.shared.f32 [%r3+3584], %f10; + ld.global.f32 %f11, [%rd2+20971520]; + st.shared.f32 [%r3+4096], %f11; + bar.sync 0; + setp.eq.s32 %p1, %r1, 0; + setp.eq.s32 %p2, %r1, 511; + or.pred %p3, %p1, %p2; + setp.eq.s32 %p4, %r7, 0; + or.pred %p5, %p3, %p4; + setp.eq.s32 %p6, %r7, 1279; + or.pred %p7, %p6, %p5; + @%p7 bra $L__BB1_2; + bra.uni $L__BB1_1; + +$L__BB1_2: + mov.u16 %rs3, 2; + st.shared.u8 [%r2], %rs3; + mov.f32 %f58, 0f00000000; + mov.u32 %r30, 0; + st.shared.u32 [%r3], %r30; + st.shared.u32 [%r3+512], %r30; + st.shared.u32 [%r3+1024], %r30; + st.shared.u32 [%r3+1536], %r30; + st.shared.u32 [%r3+2048], %r30; + st.shared.u32 [%r3+2560], %r30; + st.shared.u32 [%r3+3072], %r30; + st.shared.u32 [%r3+3584], %r30; + bra.uni $L__BB1_3; + +$L__BB1_1: + cvt.rn.f64.s32 %fd1, %r1; + add.f64 %fd2, %fd1, 0dC06FF00000000000; + mul.f64 %fd3, %fd2, 0dC010000000000000; + mul.f64 %fd4, %fd2, %fd3; + div.rn.f64 %fd5, %fd4, 0d410FC02000000000; + add.f64 %fd6, %fd5, 0d3FF0000000000000; + mul.f64 %fd7, %fd6, 0d3F8EB851EB851EB8; + cvt.rn.f32.f64 %f12, %fd7; + mov.u16 %rs2, 1; + st.shared.u8 [%r2], %rs2; + cvt.f64.f32 %fd8, %f12; + mul.f64 %fd9, %fd8, 0d3FF8000000000000; + mul.f64 %fd10, %fd9, %fd8; + ld.const.f32 %f13, [w]; + cvt.f64.f32 %fd11, %f13; + ld.const.u32 %r12, [e]; + mul.lo.s32 %r13, %r12, 3; + cvt.rn.f32.s32 %f14, %r13; + mul.f32 %f15, %f12, %f14; + cvt.f64.f32 %fd12, %f15; + cvt.rn.f64.s32 %fd13, %r12; + mul.f64 %fd14, %fd13, 0d4012000000000000; + mul.f64 %fd15, %fd14, %fd13; + mul.f64 %fd16, %fd15, %fd8; + fma.rn.f64 %fd17, %fd16, %fd8, %fd12; + sub.f64 %fd18, %fd17, %fd10; + mul.f64 %fd19, %fd18, %fd11; + cvt.rn.f32.f64 %f16, %fd19; + st.shared.f32 [%r3], %f16; + ld.const.f32 %f17, [w+4]; + cvt.f64.f32 %fd20, %f17; + ld.const.u32 %r14, [e+8]; + mul.lo.s32 %r15, %r14, 3; + cvt.rn.f32.s32 %f18, %r15; + mul.f32 %f19, %f12, %f18; + cvt.f64.f32 %fd21, %f19; + cvt.rn.f64.s32 %fd22, %r14; + mul.f64 %fd23, %fd22, 0d4012000000000000; + mul.f64 %fd24, %fd23, %fd22; + mul.f64 %fd25, %fd24, %fd8; + fma.rn.f64 %fd26, %fd25, %fd8, %fd21; + sub.f64 %fd27, %fd26, %fd10; + mul.f64 %fd28, %fd27, %fd20; + cvt.rn.f32.f64 %f20, %fd28; + st.shared.f32 [%r3+512], %f20; + ld.const.f32 %f21, [w+8]; + cvt.f64.f32 %fd29, %f21; + ld.const.u32 %r16, [e+16]; + mul.lo.s32 %r17, %r16, 3; + cvt.rn.f32.s32 %f22, %r17; + mul.f32 %f23, %f12, %f22; + cvt.f64.f32 %fd30, %f23; + cvt.rn.f64.s32 %fd31, %r16; + mul.f64 %fd32, %fd31, 0d4012000000000000; + mul.f64 %fd33, %fd32, %fd31; + mul.f64 %fd34, %fd33, %fd8; + fma.rn.f64 %fd35, %fd34, %fd8, %fd30; + sub.f64 %fd36, %fd35, %fd10; + mul.f64 %fd37, %fd36, %fd29; + cvt.rn.f32.f64 %f24, %fd37; + st.shared.f32 [%r3+1024], %f24; + ld.const.f32 %f25, [w+12]; + cvt.f64.f32 %fd38, %f25; + ld.const.u32 %r18, [e+24]; + mul.lo.s32 %r19, %r18, 3; + cvt.rn.f32.s32 %f26, %r19; + mul.f32 %f27, %f12, %f26; + cvt.f64.f32 %fd39, %f27; + cvt.rn.f64.s32 %fd40, %r18; + mul.f64 %fd41, %fd40, 0d4012000000000000; + mul.f64 %fd42, %fd41, %fd40; + mul.f64 %fd43, %fd42, %fd8; + fma.rn.f64 %fd44, %fd43, %fd8, %fd39; + sub.f64 %fd45, %fd44, %fd10; + mul.f64 %fd46, %fd45, %fd38; + cvt.rn.f32.f64 %f28, %fd46; + st.shared.f32 [%r3+1536], %f28; + ld.const.f32 %f29, [w+16]; + cvt.f64.f32 %fd47, %f29; + ld.const.u32 %r20, [e+32]; + mul.lo.s32 %r21, %r20, 3; + cvt.rn.f32.s32 %f30, %r21; + mul.f32 %f31, %f12, %f30; + cvt.f64.f32 %fd48, %f31; + cvt.rn.f64.s32 %fd49, %r20; + mul.f64 %fd50, %fd49, 0d4012000000000000; + mul.f64 %fd51, %fd50, %fd49; + mul.f64 %fd52, %fd51, %fd8; + fma.rn.f64 %fd53, %fd52, %fd8, %fd48; + sub.f64 %fd54, %fd53, %fd10; + mul.f64 %fd55, %fd54, %fd47; + cvt.rn.f32.f64 %f32, %fd55; + st.shared.f32 [%r3+2048], %f32; + ld.const.f32 %f33, [w+20]; + cvt.f64.f32 %fd56, %f33; + ld.const.u32 %r22, [e+40]; + mul.lo.s32 %r23, %r22, 3; + cvt.rn.f32.s32 %f34, %r23; + mul.f32 %f35, %f12, %f34; + cvt.f64.f32 %fd57, %f35; + cvt.rn.f64.s32 %fd58, %r22; + mul.f64 %fd59, %fd58, 0d4012000000000000; + mul.f64 %fd60, %fd59, %fd58; + mul.f64 %fd61, %fd60, %fd8; + fma.rn.f64 %fd62, %fd61, %fd8, %fd57; + sub.f64 %fd63, %fd62, %fd10; + mul.f64 %fd64, %fd63, %fd56; + cvt.rn.f32.f64 %f36, %fd64; + st.shared.f32 [%r3+2560], %f36; + ld.const.f32 %f37, [w+24]; + cvt.f64.f32 %fd65, %f37; + ld.const.u32 %r24, [e+48]; + mul.lo.s32 %r25, %r24, 3; + cvt.rn.f32.s32 %f38, %r25; + mul.f32 %f39, %f12, %f38; + cvt.f64.f32 %fd66, %f39; + cvt.rn.f64.s32 %fd67, %r24; + mul.f64 %fd68, %fd67, 0d4012000000000000; + mul.f64 %fd69, %fd68, %fd67; + mul.f64 %fd70, %fd69, %fd8; + fma.rn.f64 %fd71, %fd70, %fd8, %fd66; + sub.f64 %fd72, %fd71, %fd10; + mul.f64 %fd73, %fd72, %fd65; + cvt.rn.f32.f64 %f40, %fd73; + st.shared.f32 [%r3+3072], %f40; + ld.const.f32 %f41, [w+28]; + cvt.f64.f32 %fd74, %f41; + ld.const.u32 %r26, [e+56]; + mul.lo.s32 %r27, %r26, 3; + cvt.rn.f32.s32 %f42, %r27; + mul.f32 %f43, %f12, %f42; + cvt.f64.f32 %fd75, %f43; + cvt.rn.f64.s32 %fd76, %r26; + mul.f64 %fd77, %fd76, 0d4012000000000000; + mul.f64 %fd78, %fd77, %fd76; + mul.f64 %fd79, %fd78, %fd8; + fma.rn.f64 %fd80, %fd79, %fd8, %fd75; + sub.f64 %fd81, %fd80, %fd10; + mul.f64 %fd82, %fd81, %fd74; + cvt.rn.f32.f64 %f44, %fd82; + st.shared.f32 [%r3+3584], %f44; + ld.const.f32 %f45, [w+32]; + cvt.f64.f32 %fd83, %f45; + ld.const.u32 %r28, [e+64]; + mul.lo.s32 %r29, %r28, 3; + cvt.rn.f32.s32 %f46, %r29; + mul.f32 %f47, %f12, %f46; + cvt.f64.f32 %fd84, %f47; + cvt.rn.f64.s32 %fd85, %r28; + mul.f64 %fd86, %fd85, 0d4012000000000000; + mul.f64 %fd87, %fd86, %fd85; + mul.f64 %fd88, %fd87, %fd8; + fma.rn.f64 %fd89, %fd88, %fd8, %fd84; + sub.f64 %fd90, %fd89, %fd10; + mul.f64 %fd91, %fd90, %fd83; + cvt.rn.f32.f64 %f58, %fd91; + +$L__BB1_3: + st.shared.f32 [%r3+4096], %f58; + bar.sync 0; + ld.shared.u8 %rs4, [%r2]; + st.global.u8 [%rd1], %rs4; + ld.shared.f32 %f49, [%r3]; + st.global.f32 [%rd2], %f49; + ld.shared.f32 %f50, [%r3+512]; + st.global.f32 [%rd2+2621440], %f50; + ld.shared.f32 %f51, [%r3+1024]; + st.global.f32 [%rd2+5242880], %f51; + ld.shared.f32 %f52, [%r3+1536]; + st.global.f32 [%rd2+7864320], %f52; + ld.shared.f32 %f53, [%r3+2048]; + st.global.f32 [%rd2+10485760], %f53; + ld.shared.f32 %f54, [%r3+2560]; + st.global.f32 [%rd2+13107200], %f54; + ld.shared.f32 %f55, [%r3+3072]; + st.global.f32 [%rd2+15728640], %f55; + ld.shared.f32 %f56, [%r3+3584]; + st.global.f32 [%rd2+18350080], %f56; + ld.shared.f32 %f57, [%r3+4096]; + st.global.f32 [%rd2+20971520], %f57; + ret; + +} + diff --git a/CelerisLab/kernels/macros.h b/CelerisLab/kernels/macros.h new file mode 100644 index 0000000..8f783cf --- /dev/null +++ b/CelerisLab/kernels/macros.h @@ -0,0 +1,34 @@ +// CelerisLab/kernels/macros.h + +// cuda parameters +#define MULT_GPU False +#define NT 128 +#define X_1U 128 +#define Y_1U 32 +#define Z_1U 1 + +// flow parameters +#define LBtype float +#define UX 10 +#define UY 16 +#define UZ 1 +#define NX 1280 +#define NY 512 +#define NZ 1 +#define DIM 2 +#define NQ 9 +#define VIS 0.004 +#define RHO 1.0 +#define U0 0.01 + +// constants +#define PI 3.141592653589793238 +#define FLUID 0b00000001 +#define SOLID 0b00000010 +#define GAS 0b00000100 +#define INTERFACE 0b00001000 +#define SENSOR 0b00010000 + +// variables +#define N_OBJS 7 +// #define N_SENS 2 \ No newline at end of file diff --git a/CelerisLab/kernels/preproc.cu b/CelerisLab/kernels/preproc.cu new file mode 100644 index 0000000..c2b25c5 --- /dev/null +++ b/CelerisLab/kernels/preproc.cu @@ -0,0 +1,2 @@ +#include "macros.h" +#include "const.h" diff --git a/CelerisLab/preprocess.py b/CelerisLab/preprocess.py new file mode 100644 index 0000000..69aadc1 --- /dev/null +++ b/CelerisLab/preprocess.py @@ -0,0 +1,40 @@ +# CelerisLab/preprocess.py + +import math +import numpy as np +from typing import Tuple + +FLUID = 0b00000001 +SOLID = 0b00000010 +GAS = 0b00000100 +INTERFACE = 0b00001000 +SENSOR = 0b00010000 + + +def find_circle_intersection(x, y, x_neb, y_neb, xc, yc, r0): + dx, dy = x_neb - x, y_neb - y + a = dx ** 2 + dy ** 2 + b = 2 * (dx * (x - xc) + dy * (y - yc)) + c = (x - xc) ** 2 + (y - yc) ** 2 - r0 ** 2 + det = b ** 2 - 4 * a * c + + if det < 0: + return None + + t1 = (-b + math.sqrt(det)) / (2 * a) + t2 = (-b - math.sqrt(det)) / (2 * a) + + if 0 <= t1 <= 1: + return x + t1 * dx, y + t1 * dy + elif 0 <= t2 <= 1: + return x + t2 * dx, y + t2 * dy + else: + return None + +def find_sensor_area(radius): + area = 0 + for i in range(np.floor(-radius), np.ceil(radius)): + for j in range(np.floor(-radius), np.ceil(radius)): + if i ** 2 + j ** 2 <= radius ** 2: + area += 1 + return area \ No newline at end of file diff --git a/CelerisLab/utils.py b/CelerisLab/utils.py new file mode 100644 index 0000000..7a93009 --- /dev/null +++ b/CelerisLab/utils.py @@ -0,0 +1,256 @@ +# CelerisLab/utils.py + +import pycuda.driver as cuda +import subprocess +import json + +from typing import NamedTuple, Optional, List, Tuple, Union + + +class CudaDeviceInfo(NamedTuple): + name: str + compute_capability: str + multiprocessors: int + total_global_memory: int + max_shared_memory_per_block: int + max_threads_per_block: int + max_blocks_per_multiprocessor: int + device_interconnect: Optional[str] = None + + +class FlowFieldConfig(NamedTuple): + data_type: str + dimensionality: int + lattice: int + field_dim_in_U: Tuple[int, int, int] + viscosity: float + velocity: float + boundary_conditions: Tuple[str, str, str, str, str, str] + + +class CudaConfig(NamedTuple): + multi_gpu: bool + gpu_connection: str + required_cuda_capability: str + threads_per_block: int + unit_dimensions: Tuple[int, int, int] + + +def check_cuda_device_availability(device_id=0): + if cuda.Device.count() == 0: + raise RuntimeError("No CUDA device is available.") + + if device_id < 0 or device_id >= cuda.Device.count(): + raise ValueError( + f"Invalid device_id {device_id}. Must be between 0 and {cuda.Device.count() - 1}." + ) + + try: + subprocess.check_output(["nvidia-smi", "--version"]) + except subprocess.CalledProcessError: + raise RuntimeError("nvidia-smi is not available or not installed correctly.") + + +def query_cuda_device_info(device_id=0) -> CudaDeviceInfo: + check_cuda_device_availability(device_id) + + try: + output = subprocess.check_output( + ["nvidia-smi", "-q", "-d", "TOPOLOGY", "-i", str(device_id)], text=True + ) + if "NVLink" in output: + device_interconnect = "NVLink" + elif "PCIe" in output: + device_interconnect = "PCIe" + else: + device_interconnect = "Unknown" + except Exception as e: + device_interconnect = None + + device = cuda.Device(device_id) + + return CudaDeviceInfo( + name=device.name(), + compute_capability=f"{device.compute_capability()[0]}.{device.compute_capability()[1]}", + multiprocessors=device.get_attribute( + cuda.device_attribute.MULTIPROCESSOR_COUNT + ), + total_global_memory=device.total_memory(), + max_shared_memory_per_block=device.get_attribute( + cuda.device_attribute.MAX_SHARED_MEMORY_PER_BLOCK + ), + max_threads_per_block=device.get_attribute( + cuda.device_attribute.MAX_THREADS_PER_BLOCK + ), + max_blocks_per_multiprocessor=device.get_attribute( + cuda.device_attribute.MAX_BLOCKS_PER_MULTIPROCESSOR + ), + device_interconnect=device_interconnect, + ) + + +def load_flow_field_config(config_path: str) -> FlowFieldConfig: + try: + with open(config_path, "r") as file: + config = json.load(file) + + required_keys = [ + "data_type", + "dimensionality", + "lattice", + "field_dim_in_U", + "viscosity", + "boundary_conditions", + ] + if not all(key in config for key in required_keys): + raise ValueError("Missing required configuration items.") + + if config["data_type"] not in ["FP32", "FP64"]: + raise ValueError("Data type must be either FP32 or FP64.") + + if config["dimensionality"] not in [2, 3]: + raise ValueError("Dimensionality must be either 2 or 3.") + + if config["dimensionality"] == 2 and config["field_dim_in_U"][2] != 1: + raise ValueError( + "Field dimensions must be 1 in the third dimension for 2D simulations." + ) + + if config["lattice"] not in [9]: + raise ValueError("Lattice must be either 9 or 19.") + + boundary_conditions = tuple( + condition + for key in ["x", "y", "z"] + for condition in config["boundary_conditions"].get(key, []) + ) + if len(boundary_conditions) != 6: + raise ValueError("Boundary conditions must contain exactly six elements.") + + return FlowFieldConfig( + data_type=config["data_type"], + dimensionality=config["dimensionality"], + lattice=config["lattice"], + field_dim_in_U=tuple(config["field_dim_in_U"]), + viscosity=config["viscosity"], + velocity=config["velocity"], + boundary_conditions=boundary_conditions, + ) + except Exception as e: + raise RuntimeError(f"Failed to load or parse the flow field configuration: {e}") + + +def load_cuda_config(config_path: str) -> CudaConfig: + try: + with open(config_path, "r") as file: + config = json.load(file) + + required_keys = [ + "multi_gpu", + "gpu_connection", + "required_cuda_capability", + "threads_per_block", + "X_1U", + "Y_1U", + "Z_1U", + ] + + if not all(key in config for key in required_keys): + raise ValueError("Missing required configuration items.") + + return CudaConfig( + multi_gpu=config["multi_gpu"], + gpu_connection=config["gpu_connection"], + required_cuda_capability=config["required_cuda_capability"], + threads_per_block=config["threads_per_block"], + unit_dimensions=(config["X_1U"], config["Y_1U"], config["Z_1U"]), + ) + except Exception as e: + raise RuntimeError(f"Failed to load or parse the CUDA configuration: {e}") + + +def check_cuda_capability( + field_config: FlowFieldConfig, + cuda_config: CudaConfig, + device_id: Union[int, List[int]] = None, +): + SAFE_FACTOR = 0.8 + + if cuda_config.multi_gpu: + if device_id is None or isinstance(device_id, int): + raise ValueError("Multi-GPU support requires a list of device IDs.") + raise NotImplementedError("Multi-GPU support is not implemented yet.") + else: + if isinstance(device_id, list): + if len(device_id) > 1: + raise ValueError( + "Single-GPU mode does not support multiple device IDs." + ) + device_id = device_id[0] + elif device_id is None: + device_id = 0 + device_info = query_cuda_device_info(device_id) + + if device_info.compute_capability != cuda_config.required_cuda_capability: + raise ValueError( + f"Device {device_info.name} has compute capability {device_info.compute_capability}, but {cuda_config.required_cuda_capability} is required." + ) + + field_size = sum( + size * unit + for size, unit in zip( + field_config.field_dim_in_U, cuda_config.unit_dimensions + ) + ) + if ( + device_info.total_global_memory * SAFE_FACTOR + < calc_field_memory_consumption( + field_size, + field_config.dimensionality, + field_config.lattice, + field_config.data_type, + ) + ): + raise ValueError( + f"Device {device_info.name} does not have enough memory to store the flow field." + ) + + if ( + device_info.max_threads_per_block * SAFE_FACTOR + < cuda_config.threads_per_block + ): + raise ValueError( + f"Device {device_info.name} does not have enough threads per block to run the simulation." + ) + + block_size = cuda_config.threads_per_block + if ( + device_info.max_shared_memory_per_block * SAFE_FACTOR + < 2 + * calc_field_memory_consumption( + block_size, + field_config.dimensionality, + field_config.lattice, + field_config.data_type, + ) + ): + raise ValueError( + f"Device {device_info.name} does not have enough shared memory per block to run the simulation." + ) + + +def calc_field_memory_consumption( + field_size: int, dimensionality: int, directions: int, data_type: str +) -> int: + if data_type == "FP32": + data_size = 4 + elif data_type == "FP64": + data_size = 8 + else: + raise ValueError(f"Unsupported data type {data_type}.") + + return ( + field_size * directions * data_size * 2 + + field_size * dimensionality * data_size + + field_size + ) diff --git a/SB3/__pycache__/env_pinball.cpython-310.pyc b/SB3/__pycache__/env_pinball.cpython-310.pyc deleted file mode 100644 index ebd9c6f..0000000 Binary files a/SB3/__pycache__/env_pinball.cpython-310.pyc and /dev/null differ diff --git a/SB3/env_pinball.py b/SB3/env_pinball.py deleted file mode 100644 index bb7d0d9..0000000 --- a/SB3/env_pinball.py +++ /dev/null @@ -1,74 +0,0 @@ -import gymnasium as gym -import numpy as np -from gymnasium import spaces -import ctypes -from collections import deque - -lbm = ctypes.cdll.LoadLibrary('./lbm_sens.so') - -S_DIM, A_DIM = 6, 3 -action_amp = 5 -action_weight = 0.5 -sample_interval = 200 -max_steps = 320 - -class CustomEnv(gym.Env): - """Custom Environment that follows gym interface.""" - - metadata = {"render_modes": ["human"], "render_fps": 1000/sample_interval} - - def __init__(self, devicenum=0, Ccost=0.2): - super().__init__() - self.action_space = spaces.Box(low=-1, high=1, shape=(3,), dtype=np.float32) - self.observation_space = spaces.Box(low=-5, high=5, shape=(6,), dtype=np.float32) - self.fifo_rewards = deque(maxlen=50) - lbm.SetDevice(devicenum) - lbm.InitAll() - lbm.CoreSolver.argtypes = (ctypes.c_int,ctypes.c_float,ctypes.c_float,ctypes.c_float,ctypes.c_float) - lbm.CoreSolver.restype = ctypes.POINTER(ctypes.c_float) - self.temps_init = lbm.CoreSolver(100*1000, 0.0, 0.0, 0.0, 0.0) - self.s = np.array([0.0] * S_DIM, dtype=np.float32) - for i in range(S_DIM): - self.s[i] = self.temps_init[i] - lbm.InitCPUMemory() - self.max_steps = max_steps - self.current_step = 0 - self.Ccost = Ccost - - def step(self, action): - assert self.action_space.contains(action), "%r (%s) invalid"%(action, type(action)) - lbm.CoreSolver.argtypes = (ctypes.c_int,ctypes.c_float,ctypes.c_float,ctypes.c_float,ctypes.c_float) - lbm.CoreSolver.restype = ctypes.POINTER(ctypes.c_float) - action = action_amp * action - temps = lbm.CoreSolver(sample_interval, action_weight, action[0], action[1], action[2]) - for i in range(S_DIM): - self.s[i] = temps[i] - observation = np.hstack(self.s) - cd = self.s[0]+self.s[2]+self.s[4] - cl = self.s[1]+self.s[3]+self.s[5] - reward = float((1-self.Ccost)*np.exp(-np.abs(cd)/3)+self.Ccost*np.exp(-np.abs(cl)/3)) - self.fifo_rewards.append(reward) - terminated = bool(np.mean(self.fifo_rewards) > 0.9) - truncated = bool(np.any(self.s > 3) or np.any(self.s < -3)) - self.current_step += 1 - if self.current_step >= self.max_steps: - terminated = True - info = {} - return observation, reward, terminated, truncated, info - - def reset(self, seed=None, Ccost=0.2): - lbm.ResetAll() - for i in range(S_DIM): - self.s[i] = self.temps_init[i] - observation = np.hstack(self.s) - info = {} - self.current_step = 0 - self.Ccost = Ccost - return observation, info - - def render(self, episode=0, numstep=0): - lbm.OutputFlow.argtypes = (ctypes.c_int, ctypes.c_int, ctypes.c_int) - lbm.OutputFlow(episode, numstep, sample_interval) - - def close(self): - lbm.Finalize() \ No newline at end of file diff --git a/SB3/jupyter.ipynb b/SB3/jupyter.ipynb deleted file mode 100644 index d778b16..0000000 --- a/SB3/jupyter.ipynb +++ /dev/null @@ -1,148 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using cuda device\n", - "Logging to ./tensorboard/PPO_1\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Process ForkServerProcess-2:\n", - "Process ForkServerProcess-1:\n", - "Traceback (most recent call last):\n", - " File \"/home/frank14f/anaconda3/envs/pycuda_3_10/lib/python3.10/multiprocessing/process.py\", line 314, in _bootstrap\n", - " self.run()\n", - " File \"/home/frank14f/anaconda3/envs/pycuda_3_10/lib/python3.10/multiprocessing/process.py\", line 108, in run\n", - " self._target(*self._args, **self._kwargs)\n", - " File \"/home/frank14f/anaconda3/envs/pycuda_3_10/lib/python3.10/site-packages/stable_baselines3/common/vec_env/subproc_vec_env.py\", line 35, in _worker\n", - " observation, reward, terminated, truncated, info = env.step(data)\n", - "ValueError: not enough values to unpack (expected 5, got 4)\n", - "Traceback (most recent call last):\n", - " File \"/home/frank14f/anaconda3/envs/pycuda_3_10/lib/python3.10/multiprocessing/process.py\", line 314, in _bootstrap\n", - " self.run()\n", - " File \"/home/frank14f/anaconda3/envs/pycuda_3_10/lib/python3.10/multiprocessing/process.py\", line 108, in run\n", - " self._target(*self._args, **self._kwargs)\n", - " File \"/home/frank14f/anaconda3/envs/pycuda_3_10/lib/python3.10/site-packages/stable_baselines3/common/vec_env/subproc_vec_env.py\", line 35, in _worker\n", - " observation, reward, terminated, truncated, info = env.step(data)\n", - "ValueError: not enough values to unpack (expected 5, got 4)\n", - "Process ForkServerProcess-4:\n", - "Traceback (most recent call last):\n", - " File \"/home/frank14f/anaconda3/envs/pycuda_3_10/lib/python3.10/multiprocessing/process.py\", line 314, in _bootstrap\n", - " self.run()\n", - " File \"/home/frank14f/anaconda3/envs/pycuda_3_10/lib/python3.10/multiprocessing/process.py\", line 108, in run\n", - " self._target(*self._args, **self._kwargs)\n", - " File \"/home/frank14f/anaconda3/envs/pycuda_3_10/lib/python3.10/site-packages/stable_baselines3/common/vec_env/subproc_vec_env.py\", line 35, in _worker\n", - " observation, reward, terminated, truncated, info = env.step(data)\n", - "ValueError: not enough values to unpack (expected 5, got 4)\n", - "Process ForkServerProcess-3:\n", - "Traceback (most recent call last):\n", - " File \"/home/frank14f/anaconda3/envs/pycuda_3_10/lib/python3.10/multiprocessing/process.py\", line 314, in _bootstrap\n", - " self.run()\n", - " File \"/home/frank14f/anaconda3/envs/pycuda_3_10/lib/python3.10/multiprocessing/process.py\", line 108, in run\n", - " self._target(*self._args, **self._kwargs)\n", - " File \"/home/frank14f/anaconda3/envs/pycuda_3_10/lib/python3.10/site-packages/stable_baselines3/common/vec_env/subproc_vec_env.py\", line 35, in _worker\n", - " observation, reward, terminated, truncated, info = env.step(data)\n", - "ValueError: not enough values to unpack (expected 5, got 4)\n" - ] - }, - { - "ename": "EOFError", - "evalue": "", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mEOFError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[1], line 24\u001b[0m\n\u001b[1;32m 16\u001b[0m vec_env \u001b[38;5;241m=\u001b[39m SubprocVecEnv(env_fns)\n\u001b[1;32m 18\u001b[0m model \u001b[38;5;241m=\u001b[39m PPO(\n\u001b[1;32m 19\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMlpPolicy\u001b[39m\u001b[38;5;124m\"\u001b[39m, \n\u001b[1;32m 20\u001b[0m env\u001b[38;5;241m=\u001b[39mvec_env, \n\u001b[1;32m 21\u001b[0m n_steps\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m64\u001b[39m,\n\u001b[1;32m 22\u001b[0m tensorboard_log\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m./tensorboard/\u001b[39m\u001b[38;5;124m\"\u001b[39m, \n\u001b[1;32m 23\u001b[0m verbose\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m)\n\u001b[0;32m---> 24\u001b[0m \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlearn\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtotal_timesteps\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m128\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m1000\u001b[39;49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/anaconda3/envs/pycuda_3_10/lib/python3.10/site-packages/stable_baselines3/ppo/ppo.py:315\u001b[0m, in \u001b[0;36mPPO.learn\u001b[0;34m(self, total_timesteps, callback, log_interval, tb_log_name, reset_num_timesteps, progress_bar)\u001b[0m\n\u001b[1;32m 306\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mlearn\u001b[39m(\n\u001b[1;32m 307\u001b[0m \u001b[38;5;28mself\u001b[39m: SelfPPO,\n\u001b[1;32m 308\u001b[0m total_timesteps: \u001b[38;5;28mint\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 313\u001b[0m progress_bar: \u001b[38;5;28mbool\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[1;32m 314\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m SelfPPO:\n\u001b[0;32m--> 315\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlearn\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 316\u001b[0m \u001b[43m \u001b[49m\u001b[43mtotal_timesteps\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtotal_timesteps\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 317\u001b[0m \u001b[43m \u001b[49m\u001b[43mcallback\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcallback\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 318\u001b[0m \u001b[43m \u001b[49m\u001b[43mlog_interval\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlog_interval\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 319\u001b[0m \u001b[43m \u001b[49m\u001b[43mtb_log_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtb_log_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 320\u001b[0m \u001b[43m \u001b[49m\u001b[43mreset_num_timesteps\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mreset_num_timesteps\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 321\u001b[0m \u001b[43m \u001b[49m\u001b[43mprogress_bar\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mprogress_bar\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 322\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/anaconda3/envs/pycuda_3_10/lib/python3.10/site-packages/stable_baselines3/common/on_policy_algorithm.py:277\u001b[0m, in \u001b[0;36mOnPolicyAlgorithm.learn\u001b[0;34m(self, total_timesteps, callback, log_interval, tb_log_name, reset_num_timesteps, progress_bar)\u001b[0m\n\u001b[1;32m 274\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39menv \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 276\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mnum_timesteps \u001b[38;5;241m<\u001b[39m total_timesteps:\n\u001b[0;32m--> 277\u001b[0m continue_training \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcollect_rollouts\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43menv\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcallback\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrollout_buffer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mn_rollout_steps\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mn_steps\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 279\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m continue_training:\n\u001b[1;32m 280\u001b[0m \u001b[38;5;28;01mbreak\u001b[39;00m\n", - "File \u001b[0;32m~/anaconda3/envs/pycuda_3_10/lib/python3.10/site-packages/stable_baselines3/common/on_policy_algorithm.py:194\u001b[0m, in \u001b[0;36mOnPolicyAlgorithm.collect_rollouts\u001b[0;34m(self, env, callback, rollout_buffer, n_rollout_steps)\u001b[0m\n\u001b[1;32m 189\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 190\u001b[0m \u001b[38;5;66;03m# Otherwise, clip the actions to avoid out of bound error\u001b[39;00m\n\u001b[1;32m 191\u001b[0m \u001b[38;5;66;03m# as we are sampling from an unbounded Gaussian distribution\u001b[39;00m\n\u001b[1;32m 192\u001b[0m clipped_actions \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mclip(actions, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maction_space\u001b[38;5;241m.\u001b[39mlow, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maction_space\u001b[38;5;241m.\u001b[39mhigh)\n\u001b[0;32m--> 194\u001b[0m new_obs, rewards, dones, infos \u001b[38;5;241m=\u001b[39m \u001b[43menv\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstep\u001b[49m\u001b[43m(\u001b[49m\u001b[43mclipped_actions\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 196\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mnum_timesteps \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m env\u001b[38;5;241m.\u001b[39mnum_envs\n\u001b[1;32m 198\u001b[0m \u001b[38;5;66;03m# Give access to local variables\u001b[39;00m\n", - "File \u001b[0;32m~/anaconda3/envs/pycuda_3_10/lib/python3.10/site-packages/stable_baselines3/common/vec_env/base_vec_env.py:206\u001b[0m, in \u001b[0;36mVecEnv.step\u001b[0;34m(self, actions)\u001b[0m\n\u001b[1;32m 199\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 200\u001b[0m \u001b[38;5;124;03mStep the environments with the given action\u001b[39;00m\n\u001b[1;32m 201\u001b[0m \n\u001b[1;32m 202\u001b[0m \u001b[38;5;124;03m:param actions: the action\u001b[39;00m\n\u001b[1;32m 203\u001b[0m \u001b[38;5;124;03m:return: observation, reward, done, information\u001b[39;00m\n\u001b[1;32m 204\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 205\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstep_async(actions)\n\u001b[0;32m--> 206\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstep_wait\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/anaconda3/envs/pycuda_3_10/lib/python3.10/site-packages/stable_baselines3/common/vec_env/subproc_vec_env.py:129\u001b[0m, in \u001b[0;36mSubprocVecEnv.step_wait\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 128\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mstep_wait\u001b[39m(\u001b[38;5;28mself\u001b[39m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m VecEnvStepReturn:\n\u001b[0;32m--> 129\u001b[0m results \u001b[38;5;241m=\u001b[39m [remote\u001b[38;5;241m.\u001b[39mrecv() \u001b[38;5;28;01mfor\u001b[39;00m remote \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mremotes]\n\u001b[1;32m 130\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mwaiting \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m 131\u001b[0m obs, rews, dones, infos, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mreset_infos \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mzip\u001b[39m(\u001b[38;5;241m*\u001b[39mresults) \u001b[38;5;66;03m# type: ignore[assignment]\u001b[39;00m\n", - "File \u001b[0;32m~/anaconda3/envs/pycuda_3_10/lib/python3.10/site-packages/stable_baselines3/common/vec_env/subproc_vec_env.py:129\u001b[0m, in \u001b[0;36m\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m 128\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mstep_wait\u001b[39m(\u001b[38;5;28mself\u001b[39m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m VecEnvStepReturn:\n\u001b[0;32m--> 129\u001b[0m results \u001b[38;5;241m=\u001b[39m [\u001b[43mremote\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrecv\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mfor\u001b[39;00m remote \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mremotes]\n\u001b[1;32m 130\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mwaiting \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m 131\u001b[0m obs, rews, dones, infos, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mreset_infos \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mzip\u001b[39m(\u001b[38;5;241m*\u001b[39mresults) \u001b[38;5;66;03m# type: ignore[assignment]\u001b[39;00m\n", - "File \u001b[0;32m~/anaconda3/envs/pycuda_3_10/lib/python3.10/multiprocessing/connection.py:250\u001b[0m, in \u001b[0;36m_ConnectionBase.recv\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 248\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_check_closed()\n\u001b[1;32m 249\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_check_readable()\n\u001b[0;32m--> 250\u001b[0m buf \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_recv_bytes\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 251\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _ForkingPickler\u001b[38;5;241m.\u001b[39mloads(buf\u001b[38;5;241m.\u001b[39mgetbuffer())\n", - "File \u001b[0;32m~/anaconda3/envs/pycuda_3_10/lib/python3.10/multiprocessing/connection.py:414\u001b[0m, in \u001b[0;36mConnection._recv_bytes\u001b[0;34m(self, maxsize)\u001b[0m\n\u001b[1;32m 413\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_recv_bytes\u001b[39m(\u001b[38;5;28mself\u001b[39m, maxsize\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[0;32m--> 414\u001b[0m buf \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_recv\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m4\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 415\u001b[0m size, \u001b[38;5;241m=\u001b[39m struct\u001b[38;5;241m.\u001b[39munpack(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m!i\u001b[39m\u001b[38;5;124m\"\u001b[39m, buf\u001b[38;5;241m.\u001b[39mgetvalue())\n\u001b[1;32m 416\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m size \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m:\n", - "File \u001b[0;32m~/anaconda3/envs/pycuda_3_10/lib/python3.10/multiprocessing/connection.py:383\u001b[0m, in \u001b[0;36mConnection._recv\u001b[0;34m(self, size, read)\u001b[0m\n\u001b[1;32m 381\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m n \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m 382\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m remaining \u001b[38;5;241m==\u001b[39m size:\n\u001b[0;32m--> 383\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mEOFError\u001b[39;00m\n\u001b[1;32m 384\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 385\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mOSError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mgot end of file during message\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", - "\u001b[0;31mEOFError\u001b[0m: " - ] - } - ], - "source": [ - "import os\n", - "os.environ['MKL_THREADING_LAYER'] = 'GNU'\n", - "import numpy as np\n", - "import gymnasium as gym\n", - "from env_pinball import CustomEnv\n", - "from stable_baselines3 import PPO\n", - "from stable_baselines3.common.vec_env import SubprocVecEnv\n", - "\n", - "def make_env(gpu_id):\n", - " def _init():\n", - " os.environ[\"CUDA_VISIBLE_DEVICES\"] = str(gpu_id)\n", - " return CustomEnv(devicenum=gpu_id)\n", - " return _init\n", - "\n", - "env_fns = [make_env(i) for i in range(4)]\n", - "vec_env = SubprocVecEnv(env_fns)\n", - "\n", - "model = PPO(\n", - " \"MlpPolicy\", \n", - " env=vec_env, \n", - " n_steps=64,\n", - " tensorboard_log=\"./tensorboard/\", \n", - " verbose=1)\n", - "model.learn(total_timesteps=64*1000)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "vec_env = model.get_env()\n", - "obs = vec_env.reset()\n", - "\n", - "n_steps = 0\n", - "list_reward = {}\n", - "terminated = False\n", - "truncated = False\n", - "while n_steps < 500 and not terminated and not truncated:\n", - " n_steps += 1\n", - " action, _states = model.predict(observation=obs)\n", - " obs, rewards, dones, info = vec_env.step(action)\n", - " list_reward[n_steps] = rewards" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "pycuda_3_10", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.13" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/SB3/lbm_sens.so b/SB3/lbm_sens.so deleted file mode 100755 index 2e626e3..0000000 Binary files a/SB3/lbm_sens.so and /dev/null differ diff --git a/SB3/nohup.py b/SB3/nohup.py deleted file mode 100644 index fbedbfe..0000000 --- a/SB3/nohup.py +++ /dev/null @@ -1,216 +0,0 @@ -# %% -#!/usr/bin/env python3 -from env_pinball import CustomEnv -import os -import pickle -import random -import numpy as np -import torch -import torch.nn as nn -from torch.distributions.normal import Normal -from torch.utils.tensorboard import SummaryWriter - -env = CustomEnv(devicenum=3) -writer = SummaryWriter(log_dir='./tensorboard/DRL') - -# %% -class Policy_Network(nn.Module): - """Parametrized Policy Network.""" - - def __init__(self, obs_space_dims: int, action_space_dims: int): - """Initializes a neural network that estimates the mean and standard deviation - of a normal distribution from which an action is sampled from. - - Args: - obs_space_dims: Dimension of the observation space - action_space_dims: Dimension of the action space - """ - super().__init__() - - hidden_space1 = 256 # Nothing special with 16, feel free to change - hidden_space2 = 256 # Nothing special with 32, feel free to change - - # Shared Network - self.shared_net = nn.Sequential( - nn.Linear(obs_space_dims, hidden_space1), - nn.Tanh(), - nn.Linear(hidden_space1, hidden_space2), - nn.Tanh(), - ) - - # Policy Mean specific Linear Layer - self.policy_mean_net = nn.Sequential( - nn.Linear(hidden_space2, action_space_dims) - ) - - # Policy Std Dev specific Linear Layer - self.policy_stddev_net = nn.Sequential( - nn.Linear(hidden_space2, action_space_dims) - ) - - def forward(self, x: torch.Tensor) -> tuple[torch.Tensor, torch.Tensor]: - """Conditioned on the observation, returns the mean and standard deviation - of a normal distribution from which an action is sampled from. - - Args: - x: Observation from the environment - - Returns: - action_means: predicted mean of the normal distribution - action_stddevs: predicted standard deviation of the normal distribution - """ - shared_features = self.shared_net(x.float()) - - action_means = self.policy_mean_net(shared_features) - action_means = torch.tanh(action_means) - - action_stddevs = torch.log( - 1 + torch.exp(self.policy_stddev_net(shared_features)) - ) - - return action_means, action_stddevs - -# %% -class REINFORCE: - """REINFORCE algorithm.""" - - def __init__(self, obs_space_dims: int, action_space_dims: int): - """Initializes an agent that learns a policy via REINFORCE algorithm [1] - to solve the task at hand (Inverted Pendulum v4). - - Args: - obs_space_dims: Dimension of the observation space - action_space_dims: Dimension of the action space - """ - - # Hyperparameters - self.learning_rate = 1e-4 # Learning rate for policy optimization - self.gamma = 0.99 # Discount factor - self.eps = 1e-6 # small number for mathematical stability - - self.probs = [] # Stores probability values of the sampled action - self.rewards = [] # Stores the corresponding rewards - - self.net = Policy_Network(obs_space_dims, action_space_dims) - self.optimizer = torch.optim.AdamW(self.net.parameters(), lr=self.learning_rate) - - def sample_action(self, state: np.ndarray) -> float: - """Returns an action, conditioned on the policy and observation. - - Args: - state: Observation from the environment - - Returns: - action: Action to be performed - """ - state = torch.tensor(np.array([state])) - action_means, action_stddevs = self.net(state) - - # create a normal distribution from the predicted - # mean and standard deviation and sample an action - distrib = Normal(action_means[0] + self.eps, action_stddevs[0] + self.eps) - action = distrib.sample() - prob = distrib.log_prob(action) - - action = torch.tanh(action) - action = action.numpy() - - self.probs.append(prob) - - return action - - def update(self): - """Updates the policy network's weights.""" - running_g = 0 - gs = [] - - # Discounted return (backwards) - [::-1] will return an array in reverse - for R in self.rewards[::-1]: - running_g = R + self.gamma * running_g - gs.insert(0, running_g) - - deltas = torch.tensor(gs) - - loss = 0 - # minimize -1 * prob * reward obtained - for log_prob, delta in zip(self.probs, deltas): - loss += log_prob.mean() * delta * (-1) - - # Update the policy network - self.optimizer.zero_grad() - loss.backward() - self.optimizer.step() - - # Empty / zero out all episode-centric/related variables - self.probs = [] - self.rewards = [] - -# %% -total_num_episodes = int(5e3) # Total number of episodes -obs_space_dims = 6 -action_space_dims = 3 -rewards_over_seeds = [] -MAX_REWARD = 0 - -# Check if there is a saved state -if os.path.exists('saved_state.pkl'): - with open('saved_state.pkl', 'rb') as f: - i_seed, episode, agent, reward_over_episodes, rewards_over_seeds, MAX_REWARD = pickle.load(f) - os.remove('saved_state.pkl') # Remove the saved state -else: - i_seed = 0 - episode = 0 - agent = None - reward_over_episodes = None - -for seed in [1][i_seed:]: # Fibonacci seeds - # set seed - torch.manual_seed(seed) - random.seed(seed) - np.random.seed(seed) - - # Reinitialize agent every seed - if agent is None or reward_over_episodes is None: - agent = REINFORCE(obs_space_dims, action_space_dims) - reward_over_episodes = [] - - while episode < total_num_episodes+1: - obs, info = env.reset(Ccost=0.2+episode/total_num_episodes*0.6) - steps = 0 - done = False - terminated = False - truncated = False - reward_over_steps = [] - while not done: - action = agent.sample_action(obs) - obs, reward, terminated, truncated, info = env.step(action) - agent.rewards.append(reward) - reward_over_steps.append(reward) - steps += 1 - done = terminated or truncated - - avg_reward = np.mean(reward_over_steps[-64:]) - reward_over_episodes.append(np.array([avg_reward], dtype=np.float32)) - agent.update() - - if episode % 10 == 0: - # print("Episode:", episode, "Average Reward:", int(avg_reward)) - writer.add_scalar('Average Reward', int(avg_reward), episode) - - if avg_reward > MAX_REWARD: - MAX_REWARD = avg_reward - with open('saved_model_'+str(seed)+'.pkl', 'wb') as f: - pickle.dump((episode + 1, agent, reward_over_episodes, MAX_REWARD), f) - - # Save the current state at the end of each episode - with open('saved_state.pkl', 'wb') as f: - pickle.dump((i_seed, episode + 1, agent, reward_over_episodes, rewards_over_seeds, MAX_REWARD), f) - - episode += 1 - episode = 0 - MAX_REWARD = 0 - i_seed += 1 - rewards_over_seeds.append(reward_over_episodes) - agent = None # Reset the agent - reward_over_episodes = None # Reset the reward_over_episodes -# %% diff --git a/SB3/ppo_1.zip b/SB3/ppo_1.zip deleted file mode 100644 index 7e7d4de..0000000 Binary files a/SB3/ppo_1.zip and /dev/null differ diff --git a/SB3/ppo_2.zip b/SB3/ppo_2.zip deleted file mode 100644 index 6deabf3..0000000 Binary files a/SB3/ppo_2.zip and /dev/null differ diff --git a/SB3/saved_model_1.pkl b/SB3/saved_model_1.pkl deleted file mode 100644 index 6d9eb6a..0000000 Binary files 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b/configs/config_cuda.json @@ -0,0 +1,9 @@ +{ + "multi_gpu": false, + "gpu_connection": "NVLink", + "required_cuda_capability": "7.0", + "threads_per_block": 128, + "X_1U": 128, + "Y_1U": 32, + "Z_1U": 1 +} \ No newline at end of file diff --git a/configs/config_flowfield.json b/configs/config_flowfield.json new file mode 100644 index 0000000..f0ed50b --- /dev/null +++ b/configs/config_flowfield.json @@ -0,0 +1,13 @@ +{ + "data_type": "FP32", + "dimensionality": 2, + "lattice": 9, + "field_dim_in_U": [10, 16, 1], + "viscosity": 0.004, + "velocity": 0.01, + "boundary_conditions": { + "x": ["parabolic", "outflow"], + "y": ["noslip", "noslip"], + "z": ["none", "none"] + } +} \ No newline at end of file diff --git a/configs/config_gym.json b/configs/config_gym.json new file mode 100644 index 0000000..544b7b4 --- /dev/null +++ b/configs/config_gym.json @@ -0,0 +1,3 @@ +{ + +} \ No newline at end of file diff --git a/lbm_kernel.py b/lbm_kernel.py deleted file mode 100644 index 530edcb..0000000 --- a/lbm_kernel.py +++ /dev/null @@ -1,9 +0,0 @@ -import pycuda.driver as cuda -import pycuda.autoinit -from pycuda.compiler import SourceModule -import numpy as np - -with open('./cuda/kernel.cu', 'r') as file_k: - code = file_k.read() - -kernel = SourceModule(code) diff --git a/output.png b/output.png deleted file mode 100644 index 1ce14b5..0000000 Binary files a/output.png and /dev/null differ diff --git a/profile.nvvp b/profile.nvvp new file mode 100644 index 0000000..908c164 Binary files /dev/null and b/profile.nvvp differ diff --git a/scripts/__pycache__/gym_env.cpython-310.pyc b/scripts/__pycache__/gym_env.cpython-310.pyc new file mode 100644 index 0000000..cb8db48 Binary files /dev/null and b/scripts/__pycache__/gym_env.cpython-310.pyc differ diff --git a/scripts/d1a3o12.py b/scripts/d1a3o12.py new file mode 100644 index 0000000..239addb --- /dev/null +++ b/scripts/d1a3o12.py @@ -0,0 +1,57 @@ +import os +os.environ['MKL_THREADING_LAYER'] = 'GNU' +os.environ["OMP_NUM_THREADS"] = "8" +os.environ["MKL_NUM_THREADS"] = "8" +import torch +import numpy as np +from torch.nn import Module +import gymnasium as gym +from gym_env import CustomEnv +from stable_baselines3 import PPO +from stable_baselines3.common.vec_env import SubprocVecEnv +from stable_baselines3.common.vec_env import DummyVecEnv +from sb3_contrib import RecurrentPPO +from torch.utils.tensorboard import SummaryWriter + +current_dir = os.path.dirname(os.path.abspath("__file__")) +parent_dir = os.path.abspath(os.path.join(current_dir, os.pardir)) + +class Sin(Module): + def __init__(self): + super().__init__() + + def forward(self, x): + return torch.sin(x) + +if __name__ == '__main__': + + vec_env = CustomEnv(device_id=1) + name = "d1a3o12_c1" + + model = PPO.load(os.path.join(parent_dir, "models", "d1a3o12_a0"), env=vec_env, device=torch.device("cuda:1")) + + # model = PPO( + # "MlpPolicy", + # policy_kwargs=dict(activation_fn=Sin), + # env=vec_env, + # device=torch.device("cuda:1"), + # verbose=0) + + writer = SummaryWriter(log_dir=os.path.join(parent_dir, "tensorboard", name)) + max_reward = 0 + + for i in range(100): + model.learn(total_timesteps=480) + test_env = model.get_env() + test_obs = test_env.reset() + list_reward = [] + for step in range(480): + test_action, _states = model.predict(observation=test_obs) + test_obs, test_rewards, test_dones, info = test_env.step(test_action) + list_reward.append(test_rewards) + + avg_reward = np.mean(list_reward[-240:]) + writer.add_scalar('Reward', np.mean(avg_reward), i) + if avg_reward > max_reward: + max_reward = avg_reward + model.save(os.path.join(parent_dir, "models", name + ".zip")) \ No newline at end of file diff --git a/scripts/gym_env.py b/scripts/gym_env.py new file mode 100644 index 0000000..106442c --- /dev/null +++ b/scripts/gym_env.py @@ -0,0 +1,198 @@ +import gymnasium as gym +import numpy as np +from gymnasium import spaces +import ctypes +from collections import deque +from typing import Tuple +import sys +import os +import threading +from concurrent.futures import ThreadPoolExecutor +from concurrent.futures import ProcessPoolExecutor +import queue + +os.environ["OMP_NUM_THREADS"] = "1" +os.environ["MKL_NUM_THREADS"] = "1" + +current_dir = os.path.dirname(os.path.abspath("__file__")) +parent_dir = os.path.abspath(os.path.join(current_dir, os.pardir)) +sys.path.append(parent_dir) +from CelerisLab import FlowField +from CelerisLab import utils + +config_cuda = utils.load_cuda_config( + os.path.join(parent_dir, "configs", "config_cuda.json") +) +config_field = utils.load_flow_field_config( + os.path.join(parent_dir, "configs", "config_flowfield.json") +) + +S_DIM, A_DIM = 12, 3 +U0 = config_field.velocity +T0 = 1000 +SAMPLE_INTERVAL = 800 +FIFO_LEN = 120 +CONV_LEN = 60 +MAX_STEPS = 640 +if config_field.data_type == "FP32": + DATA_TYPE = np.float32 +else: + raise ValueError(f"Unsupported data type {config_field.data_type}.") + + +class CustomEnv(gym.Env): + """Custom Environment that follows gym interface.""" + + metadata = {"render_modes": ["human"], "render_fps": T0 / SAMPLE_INTERVAL} + + def __init__(self, device_id=0): + super().__init__() + self.action_space = spaces.Box(low=-1, high=1, shape=(A_DIM,), dtype=DATA_TYPE) + self.observation_space = spaces.Box( + low=-1, high=1, shape=(S_DIM,), dtype=DATA_TYPE + ) + self.fifo_states = deque(maxlen=FIFO_LEN) + self.target_states = np.empty((0, 6), dtype=DATA_TYPE) + self.force_norm_fact = 1.0 + self.sens_norm_fact = np.ones(6, dtype=DATA_TYPE) + self.sens_deviation = np.zeros(6, dtype=DATA_TYPE) + + self.flow_field = FlowField(config_field, config_cuda, device_id) + L0 = 20 + U0 = config_field.velocity + NX = self.flow_field.FIELD_SHAPE[0] + NY = self.flow_field.FIELD_SHAPE[1] + center: Tuple[float, float, float] = (10 * L0, (NY - 1) / 2, 0) + self.flow_field.add_cylinder(center, L0) + center: Tuple[float, float, float] = (40 * L0, (NY - 1) / 2 + 2 * L0, 0) + self.flow_field.add_sensor(center, L0 / 4) + center: Tuple[float, float, float] = (40 * L0, (NY - 1) / 2, 0) + self.flow_field.add_sensor(center, L0 / 4) + center: Tuple[float, float, float] = (40 * L0, (NY - 1) / 2 - 2 * L0, 0) + self.flow_field.add_sensor(center, L0 / 4) + self.flow_field.run(int(4*NX/U0), np.zeros(4, dtype=DATA_TYPE)) + + for i in range(FIFO_LEN): + self.flow_field.run(SAMPLE_INTERVAL, np.zeros(4, dtype=DATA_TYPE)) + new_state = self.flow_field.obs.copy()[2:8] + self.target_states = np.vstack((self.target_states, new_state)) + + self.flow_field.apply_ddf() + center: Tuple[float, float, float] = (30 * L0, (NY - 1) / 2, 0) + self.flow_field.add_cylinder(center, L0 / 2) + center: Tuple[float, float, float] = (31.3 * L0, (NY - 1) / 2 + 0.75 * L0, 0) + self.flow_field.add_cylinder(center, L0 / 2) + center: Tuple[float, float, float] = (31.3 * L0, (NY - 1) / 2 - 0.75 * L0, 0) + self.flow_field.add_cylinder(center, L0 / 2) + self.flow_field.run(int(4*NX/U0), np.zeros(7, dtype=DATA_TYPE)) + self.flow_field.get_ddf() + + for i in range(FIFO_LEN): + self.flow_field.run(SAMPLE_INTERVAL, np.zeros(7, dtype=DATA_TYPE)) + self.fifo_states.append(self.flow_field.obs.copy()[2:14]) + + temp_states = np.array(self.fifo_states) + self.force_norm_fact = 6 * np.max(np.abs(temp_states[:, 6:12])) + for i in range(6): + self.sens_deviation[i] = np.mean(temp_states[:, i]) + self.sens_norm_fact[i] = 5 * np.max(np.abs(temp_states[:, i] - self.sens_deviation[i])) + self.target_states[:, i] = (self.target_states[:, i] - self.sens_deviation[i]) / self.sens_norm_fact[i] + + + def step(self, action): + assert self.action_space.contains(action), "%r (%s) invalid" % ( + action, + type(action), + ) + + # barrier = threading.Barrier(2) + result_queue = queue.Queue() + + def run_flow_field(action): + self.flow_field.context.push() + U0 = config_field.velocity + try: + temp = np.zeros(7, dtype=DATA_TYPE) + temp[4:7] = np.array((action*8+[0,-4,4])*U0, dtype=DATA_TYPE) + self.flow_field.run(SAMPLE_INTERVAL, temp) + finally: + self.flow_field.context.pop() + # barrier.wait() + self.fifo_states.append(self.flow_field.obs.copy()[2:14]) + + def calc_reward(): + states = np.array(self.fifo_states) + forces = states[-1, 6:12] / self.force_norm_fact + cd = (forces[0] + forces[2] + forces[4]) / 3 + cl = (forces[1] + forces[3] + forces[5]) / 3 + sens = (states[-1, 0:6] - self.sens_deviation) / self.sens_norm_fact + + similarities = 0.0 + + def calc_lag(target, state): + target_mean = np.mean(target) + state_mean = np.mean(state) + + correlation = np.correlate(target - target_mean, state - state_mean, "full") + lags = np.arange(-len(target) + 1, len(target)) + max_lag = lags[np.argmax(correlation)] + return max_lag + + def calc_sim(target, state, lag): + target_mean = np.mean(target) + state_mean = np.mean(state) + target_std = np.std(target) + + aligned_state = np.roll(state, lag) + + if lag >= 0: + seq_target = target[-CONV_LEN:]-target_mean + seq_state = aligned_state[-CONV_LEN:]-state_mean + else: + seq_target = target[:CONV_LEN]-target_mean + seq_state = aligned_state[:CONV_LEN]-state_mean + + seq_diff = seq_target - seq_state + sim_cor = 10*(np.corrcoef(seq_target, seq_state)[0, 1] - 1) + sim_div = -np.abs((target_mean - state_mean) / target_std * 0.75) + sim_amp = -np.abs(np.std(seq_diff) / target_std * 2) + + return np.exp((sim_cor + sim_div + sim_amp) / 3) + + id_sens = 0 + target_seq = self.target_states[:, id_sens] + state_seq = (states[:, id_sens] - self.sens_deviation[id_sens]) / self.sens_norm_fact[id_sens] + lag = calc_lag(target_seq, state_seq) + similarities += calc_sim(target_seq, state_seq, lag) / 6 + + for i in range(1, 6): + target_seq = self.target_states[:, i] + state_seq = (states[:, i] - self.sens_deviation[i]) / self.sens_norm_fact[i] + similarities += calc_sim(target_seq, state_seq, lag) / 6 + + reward_cd = np.exp(-np.abs(cd * 80)) + reward_cl = np.exp(-np.abs(cl * 20)) + # reward_sim = np.exp(2 * (similarities - 1)) + reward_sim = similarities + reward = np.minimum(0.3 * reward_cd + 0.3 * reward_cl + 0.4 * reward_sim, 1.0) + # barrier.wait() + result_queue.put((np.hstack([forces, sens]), reward)) + + run_flow_field(action) + calc_reward() + observation, reward = result_queue.get() + + truncated = bool(np.any(observation > 1) or np.any(observation < -1)) + observation = np.clip(observation, -1, 1) + # truncated = False + return observation, float(reward), False, truncated, {} + + def reset(self, seed=None): + self.flow_field.apply_ddf() + return np.zeros(S_DIM, dtype=np.float32), {} + + def render(self, mode="human"): + pass + + def close(self): + self.flow_field.__del__() \ No newline at end of file diff --git a/scripts/jupyter.ipynb b/scripts/jupyter.ipynb new file mode 100644 index 0000000..9d36262 --- /dev/null +++ b/scripts/jupyter.ipynb @@ -0,0 +1,182 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "os.environ['MKL_THREADING_LAYER'] = 'GNU'\n", + "os.environ[\"OMP_NUM_THREADS\"] = \"16\"\n", + "os.environ[\"MKL_NUM_THREADS\"] = \"16\"\n", + "import torch\n", + "import numpy as np\n", + "import gymnasium as gym\n", + "from gym_env import CustomEnv\n", + "from stable_baselines3 import PPO\n", + "from stable_baselines3.common.vec_env import SubprocVecEnv\n", + "from stable_baselines3.common.vec_env import DummyVecEnv\n", + "from sb3_contrib import RecurrentPPO\n", + "from torch.utils.tensorboard import SummaryWriter\n", + "from collections import deque\n", + "\n", + "\n", + "\n", + "current_dir = os.path.dirname(os.path.abspath(\"__file__\"))\n", + "parent_dir = os.path.abspath(os.path.join(current_dir, os.pardir))" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# def make_env(gpu_id):\n", + "# def _init():\n", + "# os.environ[\"CUDA_VISIBLE_DEVICES\"] = str(gpu_id)\n", + "# return CustomEnv(devicenum=gpu_id)\n", + "# return _init\n", + "\n", + "# env_fns = [make_env(i) for i in range(3)]\n", + "# vec_env = SubprocVecEnv(env_fns)\n", + "\n", + "# vec_env = gym.make(\"CartPole-v1\", render_mode=\"human\")\n", + "vec_env = CustomEnv(device_id=2)\n", + "\n", + "# model = RecurrentPPO(\n", + "# \"MlpLstmPolicy\", \n", + "# env=vec_env, \n", + "# # n_steps=320,\n", + "# # tensorboard_log=\"./tensorboard/\", \n", + "# # log_name=\"Lstm2\",\n", + "# device=torch.device(\"cuda:1\"),\n", + "# verbose=0)\n", + "model = PPO.load(os.path.join(parent_dir, \"models\", \"d1a3o12_a0.zip\"), env=vec_env, device=\"cuda:2\")" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "test_env = model.get_env()\n", + "obs = test_env.reset()\n", + "\n", + "list_reward = []\n", + "list_action = []\n", + "list_cd = []\n", + "list_cl = []\n", + "list_sensor = []\n", + "fifo_states = deque(maxlen=60)\n", + "dones = [False for _ in range(test_env.num_envs)]\n", + "# while not all(dones):\n", + "for step in range(120):\n", + " action, _states = model.predict(observation=obs, deterministic=True)\n", + " # action = np.array([0.0, -1, +1], dtype=np.float32)[np.newaxis, :]\n", + " obs, rewards, dones, info = test_env.step(action)\n", + " list_reward.append(rewards)\n", + " list_action.append(action)\n", + " cd = [obs[0][0], obs[0][2], obs[0][4]]\n", + " cl = [obs[0][1], obs[0][3], obs[0][5]]\n", + " fifo_states.append(obs[0][6:12])\n", + " list_cd.append(cd)\n", + " list_cl.append(cl)\n", + " list_sensor.append(np.array(obs[0][6:12]))\n", + " # if step % 8 == 0:\n", + " # test_env.envs[0].save(numstep=step)\n", + "avg_reward = np.mean(list_reward[-60:])" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import pickle\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "\n", + "# with open('Sin_PB_Best6.pkl', 'rb') as f:\n", + "# data = pickle.load(f)\n", + "\n", + "# 偏移量\n", + "offset = np.array([0, -4, +4], dtype=np.float32)\n", + "\n", + "# 添加偏移量\n", + "list_action_offset = [action[0]*8+offset for action in list_action]\n", + "\n", + "# Sum 3 CD and CL to get the total CD and CL\n", + "list_overall_cd = [sum(cd) for cd in list_cd]\n", + "list_overall_cl = [sum(cl) for cl in list_cl]\n", + "\n", + "n_points = 640\n", + "plt.figure(figsize=(12, 12))\n", + "plt.subplot(3, 2, 1)\n", + "plt.plot(list_cd[:n_points])\n", + "plt.title('CD over steps')\n", + "plt.legend()\n", + "plt.subplot(3, 2, 2)\n", + "plt.plot(list_cl[:n_points])\n", + "plt.title('CL over steps')\n", + "plt.subplot(3, 2, 3)\n", + "plt.plot(list_reward[:n_points])\n", + "plt.title('Reward over steps')\n", + "plt.subplot(3, 2, 4)\n", + "plt.plot(list_overall_cd[:n_points], label='CD')\n", + "plt.plot(list_overall_cl[:n_points], label='CL')\n", + "plt.title('CD and CL over steps')\n", + "plt.subplot(3, 2, 5)\n", + "plt.plot(list_action_offset[:n_points])\n", + "plt.title('Action over steps')\n", + "plt.subplot(3, 2, 6)\n", + "plt.plot(fifo_states)\n", + "\n", + "plt.tight_layout()\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "pycuda_3_10", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.13" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/scripts/nohup.out b/scripts/nohup.out new file mode 100644 index 0000000..e69de29 diff --git a/scripts/nohup1.out b/scripts/nohup1.out new file mode 100644 index 0000000..e69de29 diff --git a/scripts/nohup_c.out b/scripts/nohup_c.out new file mode 100644 index 0000000..e69de29 diff --git a/scripts/test.ipynb b/scripts/test.ipynb new file mode 100644 index 0000000..d9ce659 --- /dev/null +++ b/scripts/test.ipynb @@ -0,0 +1,318 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from typing import Tuple, Union\n", + "from collections import deque\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import sys\n", + "import os\n", + "\n", + "current_dir = os.path.dirname(os.path.abspath(\"__file__\"))\n", + "parent_dir = os.path.abspath(os.path.join(current_dir, os.pardir))\n", + "sys.path.append(parent_dir)\n", + "from CelerisLab import FlowField\n", + "from CelerisLab import utils\n", + "\n", + "config_cuda = utils.load_cuda_config(os.path.join(parent_dir, \"configs\", \"config_cuda.json\"))\n", + "config_field = utils.load_flow_field_config(os.path.join(parent_dir, \"configs\", \"config_flowfield.json\"))" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "FIFO_LEN = 120\n", + "SAMPLE_INTERVAL = 800\n", + "DATA_TYPE = np.float32\n", + "fifo_states = deque(maxlen=FIFO_LEN)\n", + "target_states = np.empty((0, 6), dtype=DATA_TYPE)\n", + "force_norm_fact = 1.0\n", + "sens_norm_fact = np.ones(6, dtype=DATA_TYPE)\n", + "sens_deviation = np.zeros(6, dtype=DATA_TYPE)\n", + "target_deviation = np.zeros(6, dtype=DATA_TYPE)\n", + "flow_field = FlowField(config_field, config_cuda, device_id=3)\n", + "L0 = 20\n", + "U0 = config_field.velocity\n", + "NX = flow_field.FIELD_SHAPE[0]\n", + "NY = flow_field.FIELD_SHAPE[1]\n", + "center: Tuple[float, float, float] = (10 * L0, (NY - 1) / 2, 0)\n", + "flow_field.add_cylinder(center, L0)\n", + "center: Tuple[float, float, float] = (40 * L0, (NY - 1) / 2 + 2 * L0, 0)\n", + "flow_field.add_sensor(center, L0 / 4)\n", + "center: Tuple[float, float, float] = (40 * L0, (NY - 1) / 2, 0)\n", + "flow_field.add_sensor(center, L0 / 4)\n", + "center: Tuple[float, float, float] = (40 * L0, (NY - 1) / 2 - 2 * L0, 0)\n", + "flow_field.add_sensor(center, L0 / 4)\n", + "flow_field.run(int(4*NX/U0), np.zeros(4, dtype=DATA_TYPE))\n", + "\n", + "for i in range(FIFO_LEN):\n", + " flow_field.run(SAMPLE_INTERVAL, np.zeros(4, dtype=DATA_TYPE))\n", + " new_state = flow_field.obs.copy()[2:8]\n", + " target_states = np.vstack((target_states, new_state))\n", + "for i in range(6):\n", + " target_deviation[i] = np.mean(target_states[:, i])\n", + "\n", + "flow_field.apply_ddf()\n", + "center: Tuple[float, float, float] = (30 * L0, (NY - 1) / 2, 0)\n", + "flow_field.add_cylinder(center, L0 / 2)\n", + "center: Tuple[float, float, float] = (31.3 * L0, (NY - 1) / 2 + 0.75 * L0, 0)\n", + "flow_field.add_cylinder(center, L0 / 2)\n", + "center: Tuple[float, float, float] = (31.3 * L0, (NY - 1) / 2 - 0.75 * L0, 0)\n", + "flow_field.add_cylinder(center, L0 / 2)\n", + "flow_field.run(int(4*NX/U0), np.zeros(7, dtype=DATA_TYPE))\n", + "flow_field.get_ddf()\n", + "\n", + "for i in range(FIFO_LEN):\n", + " flow_field.run(SAMPLE_INTERVAL, np.zeros(7, dtype=DATA_TYPE))\n", + " fifo_states.append(flow_field.obs.copy()[2:14])\n", + "\n", + "temp_states = np.array(fifo_states)\n", + "force_norm_fact = 6 * np.max(np.abs(temp_states[:, 6:12]))\n", + "for i in range(6):\n", + " sens_deviation[i] = np.mean(temp_states[:, i])\n", + " sens_norm_fact[i] = 5 * np.max(np.abs(temp_states[:, i] - sens_deviation[i]))\n", + " target_states[:, i] = (target_states[:, i] - sens_deviation[i]) / sens_norm_fact[i]" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "force_list = []\n", + "sensor_list = []\n", + "cd_list = []\n", + "cl_list = []\n", + "# action = np.array([0.0,0.0], dtype=np.float32)\n", + "action = np.zeros(7, dtype=np.float32)\n", + "# action[4:7] = np.array([0, -4, 4], dtype=np.float32) * config_field.velocity\n", + "\n", + "for i in range(120):\n", + " flow_field.run(800, action)\n", + " obs = flow_field.obs.copy()\n", + " force_list.append(obs[8:14]/force_norm_fact)\n", + " sensor_list.append((obs[2:8]-sens_deviation)/sens_norm_fact)\n", + " # sensor_list.append(obs[2:8])\n", + " cd_list.append((obs[8]+obs[10]+obs[12])/3/force_norm_fact)\n", + " cl_list.append((obs[9]+obs[11]+obs[13])/3/force_norm_fact)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "flow_field.apply_ddf()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[,\n", + " ,\n", + " ,\n", + " ,\n", + " ,\n", + " ]" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(12, 12))\n", + "plt.subplot(3, 2, 1)\n", + "plt.plot(force_list)\n", + "plt.title('force over steps')\n", + "plt.subplot(3, 2, 2)\n", + "plt.plot(sensor_list)\n", + "plt.title('velocity over steps')\n", + "plt.subplot(3, 2, 3)\n", + "plt.plot(np.array([cd_list, cl_list]).T)\n", + "plt.title('cd and cl over steps')\n", + "# plt.show()\n", + "\n", + "plt.subplot(3, 2, 4)\n", + "plt.plot(target_states)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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JJ52EF7/4xTjwwANx9913461vfSue+cxn4o477ohaiqcttuiyWCzWAurBBx/E3nvvXQNAAMiy+iP5+uuvx/r167Hrrrti1113xZOf/GRcffXVdvvmzZvx/Oc/H/vttx9WrlyJxz/+8Tj99NPxwAMPtOYldV/j5vr1r38dv/d7v4c999wTj3vc46LpnnbaadiyZQs+97nP1bZdc801mJ2dxSte8QoAyl3r3HPPxdq1a7FixQr8+q//OjZu3Ihf/OIXrfm/99578b//9//GPvvsg9nZWRx22GH4y7/8S5Rl6cTbvn07LrroIhx22GFYuXIl9tprLzzjGc9wesCp6/Itt9yCo446CgDwB3/wB9a1+IILLsBHP/pRCCFw++231/Jz0UUXYWZmBvfdd19r3mOKuR9///vfx8tf/nLnXK+88sqkND/72c/iyU9+MmZnZ7F27VrHZY3FYrFY7SqQTe0DALvvvrvzaQJD34oqpWwcihKKHwpP1dVXX42TTjoJa9asccJPPfVUPOc5z8Hhhx+Ok08+GZ/73Ofwn//5n/jsZz/b6zhDiC26LBaLtYBav349/vqv/xpveMMb8IpXvAJPfepTMTMzE4z7Z3/2Z3j729+OF73oRTjnnHOwxx574Dvf+Q7uueceG+e///u/sX79erz2ta/FHnvsgR/84Ae4/PLL8du//dv49re/HU27z74vetGL8NKXvhRnnHFGI4i+7GUvw1lnnYUPf/jDOPnkk234Qw89hL/7u7/DC1/4Quy555745S9/ieOOOw4/+tGP8Ja3vAVPetKTcOedd+LP/uzP8O1vfxs333xz9EX8P//zPzjmmGMwNzeHt7/97TjooIPwD//wDzj33HPx3//937jqqqsAAOPxGCeddBK++MUvYuPGjXjmM5+J8XiML3/5y7j33ntxzDHH1NJ+6lOfimuuuQZ/8Ad/gD/90z+1bsT77bcf9tlnH7zxjW/ElVdeifXr19t9xuMxPvCBD+CFL3xh7eUfUlEUGI/HTlio8wMA7rrrLhxzzDE44IAD8Jd/+ZdYvXo1vvCFL+ANb3gDHnjgAbztbW+LHucf//Ef8fznPx/r16/HJz/5SRRFgU2bNuEnP/lJax5ZLBaLtXS09957I8/zmvV269atNaut0erVq4PxR6MR9tprr855uOeee3DzzTfjb/7mb1rj7rvvvjjwwAPx/e9/v/NxhhKDLovFYi2g3vGOd+A//uM/8J73vAfvec97MDMzg6OOOgonn3wy/uiP/gi77rorADVT4iWXXIJXvOIV+NjHPmb3P+GEE5z0zjjjDPtdSoljjjkGT3/603HggQfic5/7HJ73vOdF89J131e96lW48MILW89xt912w4tf/GJcf/312Lp1K/bZZx8AwMc//nFs377djuN997vfjW9961v4yle+Yt14jz/+ePz6r/86fu/3fg+f//zncdJJJwWPcfnll+PHP/4xvvKVr+A3f/M3AahxR0VR4P3vfz82btyIQw89FJ/4xCfwz//8z/jQhz6E1772tXZ/CuC+dt99dxx++OEAgMc97nE1V+LTTz8dl156KS6//HJ7bn/zN3+D++67D3/0R3/UWj5A2D05Nl7q7LPPxm677YYvfelL1rXthBNOwPbt2/GOd7wDb3jDG7DnnnsG9z3//POxatUqbN68GStXrgSgyumggw5KyieLxWKxgFIKlHL4Cfy6pLlixQqsW7cOmzdvxgtf+EIbbryzQlq/fj1uuOEGJ+ymm27CkUce2dgRHtM111yDffbZJ2keiQcffBA//OEPe7lHDyV2XWaxWKwF1F577YUvfvGL+OpXv4p3vOMdeP7zn4///M//xHnnnYcjjjjCug1v3rwZRVE4a9SFtHXrVpxxxhnYf//9MRqNMDMzgwMPPBAA8N3vfnfQfU855ZTk8zzttNMwPz+Pj370ozbsmmuuwYEHHojjjz8eAPAP//APOPzww/HkJz8Z4/HYfk488UQIIXDLLbdE0/+nf/onPOEJT7CQa/TqV78aUkr80z/9EwDgc5/7HFauXInXvOY1yXlv0x/+4R8CAD70oQ/ZsPe+97044ogj8Du/8ztJaVx33XX46le/6nxCFt1HH30U//iP/4gXvvCF2HnnnZ1yevazn41HH30UX/7yl4PH+MUvfoGvfvWreNGLXmQhF1AdEU2gz2KxWKylqbPPPht//dd/jQ9/+MP47ne/i7POOgv33nuv7bg+77zz8Pu///s2/hlnnIF77rkHZ599Nr773e/iwx/+MK6++mqce+65Ns7c3By++c1v4pvf/Cbm5ubw4x//GN/85jfxX//1X86xy7LENddcg1e96lW199XPf/5znHvuubj99tvxgx/8ALfccgtOPvlk7L333g6UL7TYostisViLoCOPPNJaMefn5/GmN70J73rXu7Bp0yZs2rQJ//M//wNAucvGVJYlNmzYgPvuuw9vfetbccQRR2CXXXZBWZZ42tOehkceeWTQfbv0yh577LE49NBDcc011+Ccc87Bt771LXz96193lrX5yU9+gv/6r/+K9io3jTN+8MEHg1ZJ4zb84IMPAlAuzmvWrAmOf+6rVatW4dRTT8UHPvABvPnNb8add96JL37xi/jABz6QnMZhhx0WnYyK6sEHH8R4PLYeACHFyumhhx5CWZbBdRFjayWyWCwWq66SjKcdOt0uOvXUU/Hggw/ioosuwv3334/DDz8cN954o+2kvv/++501ddeuXYsbb7wRZ511Fq688kqsWbMG7373u52O6/vuu8+ZkPGyyy7DZZddhuOOO87pcL755ptx7733BjuO8zzHt7/9bVx33XX46U9/in333RfPeMYz8KlPfQq77bZbp3McUgy6LBaLtciamZnB2972NrzrXe/Cd77zHQBqzToA+NGPfoT9998/uN93vvMd/Pu//zuuvfZavOpVr7Lhfi/sUPt2nbjiNa95Dd785jfj3/7t33D99dcjyzJnlsa9994bO+20U3Qpor333jua9l577YX777+/Fm4mgjL7Pvaxj8WXvvQllGU5KOz+yZ/8CT760Y/i7/7u7/D5z38ev/Zrv2Yn2BpSe+65J/I8xytf+cqodX/t2rXRfYUQwdk4YzN0slgsFquuUmYo5RRAt0eaZ555Js4888zgttA66scdd1zjuvUHHXSQnaCqSRs2bIjG22mnnfCFL3yhNY2FFrsus1gs1gIqBGdA5SpsLJIbNmxAnufRReCBCjz92RlTLIuT7Jsq4970gQ98AB//+Mdx/PHH215nAHjuc5+L//7v/8Zee+1lLdz00zSO9Pjjj8ddd91Ve3lfd911EELgGc94BgC13MGjjz4afPk3yZRLzCq+bt06HHPMMXjnO9+Jj3/843j1q1+NXXbZpdMxUrTzzjvjGc94Br7xjW/gSU96UrCcYhOK7LLLLvjN3/xN/M3f/A0effRRG/6zn/2sNmaLxWKxWKwdTWzRZbFYrAXUiSeeiP322w8nn3wyfuM3fgNlWeKb3/wm/vIv/xK77ror/uRP/gSA6mF9y1vegre//e145JFH8LKXvQx77LEH7rrrLjzwwAO48MIL8Ru/8Rt43OMehze/+c2QUuIxj3kMbrjhBmzevLk1H5Psm6rVq1fj2c9+Nq655hpIKe0kVEYbN27Epz/9afzO7/wOzjrrLDzpSU9CWZa49957cdNNN+Gcc87B0UcfHUz7rLPOwnXXXYfnPOc5uOiii3DggQfis5/9LK666ir84R/+IQ499FAAagboa665BmeccQa+973v4RnPeAbKssRXvvIVHHbYYXjpS18aTP9xj3scdtppJ3z84x/HYYcdhl133RVr1qxxZlT+kz/5E5x66qkQQkR714fQX/3VX+G3f/u3ceyxx+IP//APcdBBB+FnP/sZ/uu//gs33HCDHY8c0tvf/nb87u/+Lk444QScc845KIoC73znO7HLLrvg//2//ze1PLNYLNaOpAICBYafjGoaabIqsUWXxWKxFlB/+qd/ij333BPvete78LznPQ8nnXQS3v3ud+NZz3oW/u3f/g1HHHGEjXvRRRfhuuuuwz333INXvOIVeMELXoBrrrnGuqrOzMzghhtuwKGHHorTTz8dL3vZy7B161bcfPPNrfmYZN8uOu200yxIv+AFL3C27bLLLvjiF7+IV7/61fjgBz+I5zznOXjJS16Cd7/73dhvv/0aLbqPfexjcdttt+GZz3wmzjvvPDz3uc/FF77wBWzatMkZyzoajXDjjTfivPPOw2c+8xk8//nPx+///u/jS1/6kmNd9rXzzjvjwx/+MB588EFs2LABRx11FD74wQ86cV7wghdgdnYWJ554Ig455JBe5ZOiJzzhCfj617+Oww8/HH/6p3+KDRs24LTTTsP//b//107sFdMJJ5yAv/3bv8W2bdtw6qmn4uyzz8Ypp5wy6ORcLBaLxWItRQmZ4pTNYrFYLBbL0Q033IDnPe95+OxnP4tnP/vZi50dFovFYg2sbdu2YY899sCFX3kWVu46vCPsoz8f421H34yHH37YLh/HGk7susxisVgsVgfddddduOeee3DOOefgyU9+cnStXxaLxWKxWIsnBl0Wi8VisTrozDPPxL/+67/iqU99Kj7ykY90no2axWKxWMtLBaYznrYYPEUWFYMui8VisVgdRNcVZLFYLBaLtTTFoMtisVgsFovFYrFYES2ldXRZ6eLSZbFYLBaLxWKxWCzWDiW26AIoyxL33XcfdtttNx5rxWKxWCwWi8ViDSgpJX72s59hzZo1yLLlZ2crZIZiCtbXaaTJqsSgC+C+++7D/vvvv9jZYLFYLBaLxWKxdlj98Ic/xH777bfY2WD9iohBF8Buu+0GAPhtcTJm8hU2XJY79hLDImPr9XLXjl5HjbiuJkos4Z5hvobT13J8HshysXPQT4t9r/H9NJkW8l5Z4Dq+KO2C0DlKnQ8hAJGhXJnhX375f22be7lJQqCcwqzLcgppsiox6ALWXXlmxU4YiZlFzs3kYvdrFmsJaNquWUPe5wPndVGfQUsdABYRRqWc0rHLRYDVIc9loerrAPfZ4PfWUrxfBrxHetf5vnV6kno54X002P3dt/wJ7NZgW5YotSFpubZR2XV5eYpBl0jkGYTIF+6lN7SW4JiH5fpAWwhNrdHJmkgLVmcnaWD2tSb1OeYk5TGU1WspNsYXWgM0/gUwmXVpiGfWcrQ6p2ii+7nnvkNalad5jw11zbvWXZloK0vNX5fjdzhn2xbI88S0w/loPNcu924oG0kQntlzETncMshGECNGDtbCa1Fr3QUXXIALL7zQCVu1ahW2bNkCQN38F154IT74wQ/ioYcewtFHH40rr7wST3ziE2387du349xzz8UnPvEJPPLIIzj++ONx1VVX9fL/F6MRhAgUyXJsZC20W9VyLKNF1uAltqM2ICfVQtfNhQTDDufWCeBT43btXJuobPgZMxFodt23j3Vpgvwtt46/iTrE+uw7aUf2Yt0/g1pUAwSWkH5r3Up5d8oSjQuV+McIwmL4OLUr0wbUOclHx/d+7/vMQHjLc0F1phlwN4FC1d+lZ4vppFIKlHL4+2gaabIqLXr3yhOf+ETcfPPN9ndOerQ2bdqEyy+/HNdeey0OPfRQXHzxxTjhhBPwve99z/r4b9y4ETfccAM++clPYq+99sI555yD5z73ubjjjjuctJKU57obSmsaDeTFeNlME3oXAXCXupV4uTXYkrUYIL0EO1Amrn9d9k9t3KakmRInpbxT8z8NsCaSC1E3uuRrAe570ece7JKv1Lidobk9/mDWqGloiHdO3/o6xLGn+c6cWueLAauW9NuO32TVNdAWeszW0s3Ipp7gTI/TCLNZJA8B+ZbTFk3s1WEgO/WYpt6LDMh30LYRa0lr0UF3NBph9erVtXApJa644gqcf/75eNGLXgQA+MhHPoJVq1bh+uuvx+mnn46HH34YV199NT760Y/iWc96FgDgYx/7GPbff3/cfPPNOPHEE4PH3L59O7Zv325/b9u2TX3JMvVpAsMFbHhPDegGH+MzRZBe4lAb0kQ5XuwGHcvVQlpthoLMtjgt21sBcsL0k+MAiwsHS0He8yDp6dAFhlOeN1OC317QPuExO2nAOjRRp8xyrMuJ16W1DkjZbAWMHafp+I47LUm8aR9vm70iMeumSbaxHLJhLM3meJ3gNZv83km1I4kKdEVWTHbMRVaBDMUUzNLTSJNVadFB9/vf/z7WrFmD2dlZHH300bjkkktw8MEH4+6778aWLVuwYcMGG3d2dhbHHXccbrvtNpx++um44447MD8/78RZs2YNDj/8cNx2221R0L300ktrLtOAdl3OAkXS90WznCajWcwe65iW4wt+ocRAPB0tpLU2Ie5UobNp2yTHbQPpJMtye5TU401t36G0UO7ICe1gsYDg62ydhrdI13Kddl0Y8v240PW2Tx1NgNjGOXg6QmwUmv34bRAaCw+lnyVYXhu2ibbhAVlL2s5hetSJaXppkfpujTYZt1tYC69FBd2jjz4a1113HQ499FD85Cc/wcUXX4xjjjkGd955px2nu2rVKmefVatW4Z577gEAbNmyBStWrMCee+5Zi2P2D+m8887D2WefbX9v27ZNraObZ0BGuqmGtEykaim9DBd7f60FcVHcATSIheRXVBPXsaHddNviNOW3J4RGAbSpMTpN4E2F3T7PmaUAuG3qAxep+0Ta13TvwaB3YBjvo6RzQWInzJBaToacDtdG9LXENm0Lvd9IXAeaO0Ds1AEZaHBlTrSsJsQRQPdx9UmW547y7yHTGSAEIJZ3G4XH6C5PLSronnTSSfb7EUccgfXr1+Nxj3scPvKRj+BpT3sagLr7rpSy1aW3Lc7s7CxmZ2frG0a5C7ox9Z4hcaDKPGE6vRv1i205WQ6N00WU9KsuW33TNGm96nI/TepW3GiF7ZFuJLzXcXoDdnw3dbwEy3fXa7gcHyVdDZQp939D55jZktQ2XeLA2xXgFxx4mzQ0DPctW/1+SSq/VpANlG8kX/Z4PUE2GZCnZUEG0oBywvtVHSfRFbtNQ3hD0DD7DF9OPTusHUWL7rpMtcsuu+CII47A97//fbzgBS8AoKy2++67r42zdetWa+VdvXo15ubm8NBDDzlW3a1bt+KYY47pngEzRjekDi++QSyQiwGVvV20F8mispQaI0tVDLvtmrTjKHm86YR5GdIa2+M4USCN3P+N5dJUZJNAccv+QS2ntlcHSJFAmiWozcM0JZ3Ex0yqZRXAoG6V9ByHfCIuS0NMoC+/i6GtdVxpDGSBZpj170N9HGcqKXtsEhZI06lnbYDcA46BBEBu2JY0NjmkFNjvkt60RJ/B5LtcVg/bukpkKKdwDtNIk1VpSYHu9u3b8d3vfhfHHnss1q5di9WrV2Pz5s14ylOeAgCYm5vDrbfeine+850AgHXr1mFmZgabN2/GS17yEgDA/fffj+985zvYtGlT5+PLLIPMvQo3jRlGh9gPWNiJWjru07tHfIj7/VcdgJ2X2q94WXTRAtzDE7nrLhacxtLoesyGfRpX7Wi1gjdvTkqjR5oLLon0CWBgGvsJ1vCENnAroKYAuJRIXNVUgVfHRRP8Yzk/J0hqQdTn2TMgvMjal2Y11ofYEjoS0dmNa/UiVHdjQBsA5HB6qNKcBhwD8c6ZGCS3pZe6HT2GLk0Dfn0PTPqeEQIol/dkVKzlqUUF3XPPPRcnn3wyDjjgAGzduhUXX3wxtm3bhle96lUQQmDjxo245JJLcMghh+CQQw7BJZdcgp133hkvf/nLAQB77LEHTjvtNJxzzjnYa6+98JjHPAbnnnsujjjiCDsLcyflefqC3UZdYXOBLbWdG3hdQbNzA7Lf+Q/uSracO9CmNI6NRdSnfgzUKdYIil2tp0NAakc47ZqXvpbfIVyek9JJ0RDPpwEanq7lsiVPKUv+yJa0TBINr00RssI1pYVuYBqGrqXYUzG0Es+x6/siyQ09Vh9k+L6T4Wsa7Iwp62E1SJ7U2pucVmJ6RqkW1z7jeVv27QzPbWrbv8swHDsZ1SS9V4uvQgoUU3DjmEaarEqLCro/+tGP8LKXvQwPPPAAHvvYx+JpT3savvzlL+PAAw8EALzxjW/EI488gjPPPBMPPfQQjj76aNx00012DV0AeNe73oXRaISXvOQleOSRR3D88cfj2muv7b6GLqAmo/ItuiEthHVzmg3tnvt0Oo+Fyv8k+/XQ0M+jXnMzLFVIXyw36Slf/87XfIgxpT2sotF8huIPAKndgTYcHof3SHxgAPfmhDiTxO+ljgcJGZq6xM/Dx0ty8+3gEt0I3B2tUKHnZaqVOFlL3vzbUV5TqN19XJdnU7RoGiIM1qFJoGTg2oVAOQDJtXOYCI4TLcdISI+Ep6RbS98/Ri3NiLq+exdotmUAruty4zTbLNZ0JGTrgIsdX9u2bcMee+yBZz7h/4dRHpikCpi+pbPnPlO12A49k6zWNMCh/ZjcY9amTuPnlqEGqwNdkpnEetu0/wKDahdI7QTcjfEj4S3bhnB1tmktw3aZ6GLBG2psbeqjI/l4ielFj7NjP8t89S6vFuBpTDeyLVhXAkHBeAmQXMtTwvHCxwrDd2vasfC2ybRS0kjZ1nK8pGO3qct+qRMaZsC4nMM/fXsTHn74Yey+++798rYIMoxw+r+cgtldZwZPf/vP5/GB3/n0siuX5aIlNUZ30TVKtOg2aOquwsBU3YWTIbQDfHYqk74sMjDILjdPkiFm7R/cMrLM1PuaDzQZVR8X3qUAq2F359j+4eDOrtdogdA2L9lkN/O0aG3qWrcmuZ/rs693OW7ELdKxgiWkkwrbMQaIpZvcAO954ZYpHweznXIu2qofq28SaISeoIU9aBENxAvcFMJfZ1UCtWtZs+a2bAfqN2CC5TjuVu3myZ5bymRaTv4CdTTV6hs6npM2wsduiOsdrWFbgvznq/693CejkjJDOYXeT7Z0T1cMukQyF5ARd65WTXms6jStoFNp9CWm2fm8Jl4KZrLdl6qWTPtsoccPL9D1HLqzpq/VcRD3307jcxPDEDmnWNzobNAd0m6Ir/aJb2vbt1M6qerS4Wi/DHdnp8CzhBjE6mphewDIdtKtQUN6+stRnazzTUowyMfLP14ngrvkolY3Qo6DKZBct7C6dSA8GZXvwizd7JdAGzwP41bdDsn0eAAa4TU+Tt7B83CcHvWoizU4eTm6X+2+dNYiiUGXKhPx5YUC6tUA6uiGO7XZQqdh5R1ymRV77L4dD/12a9JycX9eVBfkZdSRMPH1HBKUBhynOqmFNRVYu8DqYON5u8YHJncfTzh+XzUdW4SsWZMcq+NjYZBlhxLTUukJknA/DeHZspRUs87XInRPs9VqH3NJjsFSKH7tGHVYDmVDeM9BH5BrAN0RjNUxmq3GNTAGkuDYHD8IpA2TdJF/XlpNlt92uHXKoum9nOLF0Uch75/l5irnqYBAMYXG5TTSZFVi0CWSWbNFd6KG8ZQtl4sFo9OwBi/GUiDL/Pnr6FfdBXlQ9RgfPular83Qlh7eya05dL9PaLntAquDjeuNpJ+0X8u+ndOaUEMyW2cADFiqwukmeu50suymx60dp88BdyAN1aEQtLbm8X18eA55BgRBuW1MrFe//M1dwRilu/RQikt12GoM+A+LOCDX46a4g0eBGYi/l2Tway2fXkg0L47aJrBqeVdKISDFMuoJZ+0wYtAlknlgHd1J05wy4E7FOpoQbWjAXagJqnYkoGUNoAmtuukdTP23d7aGLhS0drGupo7t7ZpuQ/zGfRL2Vfv3qB9L5RmT0Oj11ckbJBmG05NMTbP9eEvlIiysZPRHWH3G5iaPt/WZNfBcqgGyD5k+HC8yGAfj6HzV4wUAWccNuy/LarOvGDADSZ06ycuONaXVd1JQZ9bl5X1flhIop3AO05wEm8Wg60hmwl3gehL14OVpWTIXDUqTlllJTAvoBSVTe64u7+d1s5brQ3fa16Rj+pPM/ttnoqVOY2QTwXUa0DptwO27Lm/jsTqm06ahnkuDuOqmNoK7HK8DZE801CIEXf1T2+GU5n4e3TuynFN4nz7jcuvWU297RrfVXY4d62wLFNcsrj5wep0sanmiuiW2Zg8NlV8qIJN8BkHZKArMQNx1Wdaj1vJZ2ysWUyeUeHdFn8E7csOJtVTFoEs00WRURj13n9bMxEPPojypW2bntIAebt8d40e0XMbksgZW33s4pXNrEgvihNAaj5sIrhNCa7e4Ha3YTeU6KdxO43k7kLpCXR8X5tTj9YFg9TOt0Ha08bcLIVn7ElZ83G5437BVtxYrALbN6TRZWLtAsdru9rZ0geJgZkOW2IAHQiog27ghBUC5dR+bR/M1bjW2ir2zGjo/JtFyH1ZVTmnW5WmkyarEoEvU26I7wb073dmUEyMmAN2gUDq0JbpjutHj8bPmV0sDvHOH8pboA2rTWAJoYnCdEFqHnYQqvmkQuF0iVl0gHQIbo3V0MU7dfVK4bkuflabGWbIDY2qb9gsBcAiW28HW395iYXX2ldFt9dmZvc1NUBzaP2F8cdD1OGZ1lajHpfkMgHLksO5+MZUmbz3gOaSeN+Nyd11mLU8x6BLJrAPsDODiPM3xu0sWTFPT6gKdC2FFZy0fTfGydr9nJ0iv60RMU3FTDsWbEFynZZlu2adtW5q3SkKcrmkOoJR2Zy+LaId9Gsd7TpDuIPtNQ8vs9dHspqw0katyaAKqVrCV0e1N+/rjsBuB2rOmdoViyO5gDKTBsZ9ebXOTe7IMfiVpkh/BGZ/bXZuH9qJY9hZdCJRTOIdppMmqxKBL1Oq6PCAYDd1g7hN30MmpBnDbtGlNyY3bPUa//XpruTzHFqshucTLZxqdUsNacTvET4XXxQbXpWLdbdnfTWvpVuRwY7jjDd9oFfTTHibdSVUDpoW6REutKqSUcSxOkqtyCtj62xusrg7YpgNx3RKcbiVOgWL1rxmMgQQ4jqQHRCDZ2yek1nG5TmAzPMfSmGhW9CX8fGTtuGLQJWpbXmgw9TjENOBvKDgd1JI7BaDvnX5X8UN8h1KvupJ0v/RLY5BJmSay5HY5dmLcaQJ9yz5qv5aLsYxcmPs0QGsWlgHh1AWGXpkbRFNh6Imv+cK/K1KuQSxKbKbh1rBWq2zqtn5ATMG2HYgB58ImQLGOFo9DIrQta+TETYFkbx//GHbfJmj29g+pvnRUv3SAxDbnElYhBYopNCKnkSarEoMu0aCzLsfUB86m4Ma74HA6BADYtLoX4lSeI/xs2uE0UT2ZKuSmuwtHjzM05MaOP+H+g82y3BN+G/PQIY3e6fbU4O6HA7gtV0m5ANFLC+1tMuVnQUzTqCMi4FobPngkOGi9jUMlPW407YbfiwnEoX1ToJj8C6dBMpHs/RCx+Dbu4x2gEzQHMtfJ2hxJo8rL8m408WRUy1MMukQyV5+pqbeb7RSsuQsJp0NOdgV0LsdBGw7L+znNimjiOjJEB1Mf99ppQOViQjLSLdGN4T2O27pfhzR6x52CZPRHnwSaoyyku/JQ4wcX6t4f7HhNx40BRkpyHdyWVXiLN0ANDhPdj5uA2PseBcvWbREg9oA1BMR+NuLuzaE44TJLB9+4a/JkszGn7QtMBs6TrCTGYvUVgy7R1C26C2EBGBR0BwLUQa25ifG6pjuFY7OWhwZxIxzivpsm6E7B7Xgak1cttivzoM+qxPQWRR0bnJ1mdV4g2G21nsX2myZoThIP07X4xyQisBUPRLsF1Nu3ZlFuhFIZ3BYDyir9cNo0qBlq6+knjcUN5TsSJ5hOIN/x+PHOhW7g63U6JO8XChLJ+y17iy4EyincpDwZ1XTFoEvUadblruptze1yjLTIQ0Ll0gfdgR4g/BzaIbWQjd5JlrSZdLKmBYHXKVmd+8TvBcBN6aXun5jOklEHgJ2WtXYIy+xCGooW/P3ZIb1kNQCSPVwXC2+TFRYN1lsvrgPEk8Kwd5xeMNxpewMUB9JR8SKFnAS98X0CP4cH5ggsN547e+iyFkEMukTTBd1+b6lpvAiXJugmZmoxeseXS6OV1VkLXUeGtDQu2Jq3U3BRnnTMb2MaA++TvD3lGEtQU7HWLpBVdyE12HtzaACeghwopIpATCOMNf2OwOykMOyDMI0ag+GaZbsn8DbGqcVrgeNIutU+DTdPA/j2Aeb6PoFrgIZOMSmXvUVXYjrLCy33ZZeWuhh0iabqujxBsosGu0MB6iJZdBl0WakapK4McE8t9vJBizlhVZdjNR6vYZ9e7uEJ+3ZKZ6lpClCabKWVA5VXyvEmPc6UvTaS9l8gpVv16vFkw/YU62vU8tpp/zAIm39dZ2emSgVi+jVl1urGuNF9EkC54VhqvzRY7nou9XIUbNFlLYoYdKmmadEFFsh9OTXNBQRUBl3WctGE13rS+2EhJ26axrJCk+4/dRflSUA3VcvsedHJoJry2kiFV5mWXuwYbkC3/Xtf62mB6hIFYAt1/vEt9YSD6b61DWh2I+5keY2CbNu+zSCs4oZNqWGIQ00itHsH4PXTaDtef4ttP6ty05hk87V2HZY56JZySmN0l0oP1w4qBl0iKZYm6AKJYNrhOEOB5VIG3aEanPwM+hXUtD0wGoErsnEKcLlosy5PGVynARw73PhcoBNsJllpu1hoO5aTAw4DlvFCTVjYaxbwId+diQoCWjQgHOZ0dgTqWG+r7iQW4Q4QrYJF1Fobhb2eFtDQ8Z1oHcC19dgN+3az2ooEN3W3QDp1qrFYA4lBl2iprqMLTMuqO0xag6QzLbdAhl3WpOpx7Sf2mJjQtXdJAeyE5xKN26Y+aQ3wnFpOz4pBXYwToLnzxFNTgtughnoHLYD3QdL2ngpeokTLYqNbb8iqG4HhJiAdxqIb3zd2XD8NtSkOw/Rnm/XTjVsPb9onlK9g9E5W3nianazb0r2oy32MLq+juzzFoEs01cmofPVqPA+f/kJB6pBrUy7m8h6DzeLMWp4auKNlsAmVFgNipwHjTRoSFPpabnckq26q9TUVYBNAOPl4NuGE+NPQBO+r6bvft/cWTNIp0G4FrCfeZdxqG2w6cQQJF260aUFwW95a4S6wPQjEkX2j1uKGfdz94rvF9o3tVyuHQBpNZVqzqDPPsRZBXO2IDOguyEd03wdCfYZMHwKqFjR92tJKOFZSvpPLRKR/RIe4CR9zDZLKbSE/YsLPYud/uXxImSXfhw1xG9OKhAevVyhuICw136Fzn+gZJuofIF4fJy6PDueacu6d0xSAzOTS/LTUyaSy9e6HSe4Beh8M8iwaIq3U8xqkPna4drlszlOuPpOUn0nD+TjHkNVH56vM1cfJJ80ryZeTZuB7ME6groTqVknjet+d8wvEKf3zzML719II/A6mFUk/fh0a2iIN28pcfRrrSCC8zNPz3fhuaCrHDMtaZozuND5dddVVV2Ht2rVYuXIl1q1bhy9+8YuN8W+99VasW7cOK1euxMEHH4z3v//9zvY777wTp5xyCg466CAIIXDFFVfU0rjgggsghHA+q1evduJIKXHBBRdgzZo12GmnnfD0pz8dd955Z+fzG1Js0SVatBuxT+/r0NbPSSxPyWkkJDIli8mCuBNOeoxJBrAstgVpsY+/yBrkPhvAQtTXEju4FbbLvpOeX1MaDduaLbfNN+OyHa/b6hupFJ2EyElLNJ6fPUxjGgnHCcRvVJcyH+A6drG8Tjpevbeb85AKXIO4RVfW/rnWvyrjqZbe1u2ChAk3Wl+X5rb94W8LpRXZb2h35Wo30X6/RN2nm/2g26zawfJki+5g+tSnPoWNGzfiqquuwm/91m/hAx/4AE466STcddddOOCAA2rx7777bjz72c/G6173OnzsYx/Dv/7rv+LMM8/EYx/7WJxyyikAgF/+8pc4+OCD8eIXvxhnnXVW9NhPfOITcfPNN9vfeZ472zdt2oTLL78c1157LQ499FBcfPHFOOGEE/C9730Pu+2220Al0E0MulSmh2qRNK3xp8PB7gCgmpDEtBqRS37s3FLP346qoct90jo+aQM3Zf+FgNgOjfqpTlgFRFuE0x6v23qMBVSSezGAVhfjFh/JVkimG1JA2QlsyNcASuvQ7VCXJulA6nL/hINb92tVyzUQfrQEl143bkVEtWrVBsEhsOrhCl3LZwPA1vivo0uzn54TLdG12d/U11W5OT8RSK6drwxuC30XEovavh5CJaazjq5Jc9u2bU747OwsZmdna/Evv/xynHbaaXjta18LALjiiivwhS98Ae973/tw6aWX1uK///3vxwEHHGCttIcddhi+9rWv4bLLLrOge9RRR+Goo44CALz5zW+O5nU0GtWsuEZSSlxxxRU4//zz8aIXvQgA8JGPfASrVq3C9ddfj9NPP72pGKYmBl0ix6UuVVN48U4PeJcIqC4i7DJMsrqqN6hMUs+HtuI2HavrfgsIsH3GKQ41RrIxrYR9e8WbhlKtpgkW2EZYbgVcmkhD+iZ6bzijJNbfTabXtR8QYoM573I/xY7dU42THfl1x/vtBCdbVSv6dYAuBMBtafYF4Ib80v3t5gTQ7Qq0bVW4aShv6zE75qd+vp7J3M8UfV7sABbdaS8vtP/++zvhb3vb23DBBRc4YXNzc7jjjjtqMLphwwbcdtttwfRvv/12bNiwwQk78cQTcfXVV2N+fh4zMzPJef3+97+PNWvWYHZ2FkcffTQuueQSHHzwwQCU5XjLli3OsWZnZ3HcccfhtttuY9BdChrMdXmg+6DzxEc9G7L1406eziANxGlaTBh4WROqU73reT9M26W4dyN8gQF26hP8NKXVtg0JFrXEdAYTzVDLMUXtSzy9YPk1ALJoy4ffcE6xJLepK9xO+C4aDGR733dNvq3xTV0loz9MmHuw6OROHlQGIXiKABy10AaO6QU3Q3Dgd7BzIAa/bR1EMSVU92YX50gaKWGxMjPXwpa5tGOpWXH98Ic/xO67725/h6y5DzzwAIqiwKpVq5zwVatWYcuWLcF0t2zZEow/Ho/xwAMPYN99903K39FHH43rrrsOhx56KH7yk5/g4osvxjHHHIM777wTe+21lz1+6Fj33HNP0jGmIQZdoqktLzRpkh32H9ISOjGsTgrDKcfoktYE6bNYrRqirg4IsdF9Eyy0fa24E49XjB2rIXxQC2580yDeLvY4U3ruJI2LdTLScs5NEFv7Ut+v3bob3rwYbstUnTtEQvdCyr5tIBsqiBT4jeQpqjaAiylAv81LDAVglMYxENwFgOmBAvHMMVPdn90043H8w9j8N0WIAG0jiA4Aun1huZPFuqFTwYDv8l9eaLoW3d13390B3SYJzxAmpayFtcUPhTfppJNOst+POOIIrF+/Ho973OPwkY98BGeffXbvvE1bDLpUCzRGd6L7ZGjwmzasLgRQ943bJQ9LWBN45yXpV6lsBj3XITp6WtJbSJBNtSZNOp64cxpN4Who4/VJq/VZ1eNmnLTO0QZ6MuCKxmM3ArMPMqG8NIFxS7o0e1EN8cyb8B2ZBLKBsFaYbY2fcMzQfrV8DfdwbFyax/ktGyZ+agBSeyACwI1gRbcFKqx3rFh6rXFEOJ7ZnvKcFaF4kWOE9k1qY/WF5Q4W62D5+f+XcVtiqWjvvfdGnuc16+3WrVtrllSj1atXB+OPRiPstddevfOyyy674IgjjsD3v/99exxAWZCplbgpbwshBl2ixXKtmKrr7RCgmZDOtK2/ScfokNZgxxpYfdrJyxlEp61plc3g6XZprPaG0j77JIJsqpVrIIAdCl77TGDVeJyUdFPUZgntkBcnqvS/hNMPuyjH4TgKxj4ARbZF0w3lsXHD5Ops1U/qSBoOZpPdlxvrdsO2qOI9HGG4dQ/SPrOxjMyq7AGwb/0FYIxFQ8Av3SeWph+nFs9POxDfxOk7nKIRkP189IHlUPoJFl2ani2TpufKMtK0LbopWrFiBdatW4fNmzfjhS98oQ3fvHkznv/85wf3Wb9+PW644QYn7KabbsKRRx7ZaXyur+3bt+O73/0ujj32WADA2rVrsXr1amzevBlPecpTAKgxxbfeeive+c539j7OpGLQJVoy63x1vI+GAsDl4qq86A/LLsdfTIsia+E1af3tAGqDWGVTQHYSiO1yPpGofRrsnSexajhG73G9Kdu7qm96bQ3NJktsDI6bLLARKG4csxsDqJCG8mKZ4J00sZtxl46nFlDu5i0xTOGJUGWS3o8mS2/ymFoZ2BaBX5q/CGzFjxfolZHClqMPhK3WXeFuD0Jj0/0WU1do7AvLoTL1ztnuS89FumG2LOQSaV/vADr77LPxyle+EkceeSTWr1+PD37wg7j33ntxxhlnAADOO+88/PjHP8Z1110HADjjjDPw3ve+F2effTZe97rX4fbbb8fVV1+NT3ziEzbNubk53HXXXfb7j3/8Y3zzm9/Errvuisc//vEAgHPPPRcnn3wyDjjgAGzduhUXX3wxtm3bhle96lUAACEENm7ciEsuuQSHHHIIDjnkEFxyySXYeeed8fKXv3whi8gRgy6VwNKzBnZIa7m4Kw9SPtPqDBhaDK5LVo3jooa6bj3vlUGtpt6JDue2nBiGCJd0gOBoHoBh4bVreFNatTSGorNE0YxF8pjkohwD0kaIDZtyo0AcyUO0yKb4XO1s5W/tTOoQn6bfOZ0WGG4L7ygZG+Bds2T6GTX/q4jJEBuD3zZoRgW+7n40n1VYBXDhetwEwDWoDQBt0Io6QWdULe0UdbQm16A4Yt2ulS0t12UOukvBogsAp556Kh588EFcdNFFuP/++3H44YfjxhtvxIEHHggAuP/++3Hvvffa+GvXrsWNN96Is846C1deeSXWrFmDd7/73XZpIQC47777rBUWAC677DJcdtllOO6443DLLbcAAH70ox/hZS97GR544AE89rGPxdOe9jR8+ctftscFgDe+8Y145JFHcOaZZ+Khhx7C0UcfjZtuumnR1tAFACFlq/f+Dq9t27Zhjz32wG/88SXIZ1dO7ThTc2frGXdRgXWI/CWmM1H85aCFuoOXatkt9hNsqM6oviALdIfZJEBuz08nK+yUAXZB4HWIGW6nfR+l3A9NcSInHz31juGNDfGkvA9cgG1kkHwPNv9OttDGvsOD2ZT7NaRpdLi0XZMArKqsiHp4KK4/prYFVBv3Id8F4tva9q3FIccMbgvs2xbeBVqT1Vbdu97nCJdT6FqVjz6K/3jPW/Dwww8nT7q0FGQY4YQbT8fMLisGT3/+F3PY/OwPLLtyWS5iiy7Rorku93hvd3rXT9vCOom1YyCY7X0OSxHeurZDluI5LKSW6vkPac0FpmOZTQHgljSj+y0xgB0UXrt2WEQ0FTfSpuMnWHBjLsop7slR1+SYVdc//VhaTpwmV4zYPvFdgsl0ue6t91ginFLmi+3T+kxJsOpO5XkZsO76dSFQXxyrsLXWhuA3bMFtsiTGrL7BMaQ0q9aaSy27ZLsHva77rnTiuXVd1Mq+bWx7sltxFytvy/MhPD4f8XuT7iOq7VJU+5kyX+4WXQmgnMINtNh99Tu6GHSJlswYXWC4F/OAx50IWieF7QWylkzbxTmpXbtUwW25axpvk8Ea0OHMTWw5SokfzE/L72jeQi3H0AGWIMD2eH61gmqfe7ltn8AhW/PRALgiACCN+4SAONQwj8B3CgzX0gpsD2qSZ2fH6986RrcJUCeB2k7HSb8fW+O0lX9ouwOt9friHMzAZxP8+uDrhLnwmwS+BMxM3CBDxuCX7u9BcQ2SPQh24vg/gvepn6kGtd1LsbgpIF4D+Hr+7Fe/TJZK+5r1KyUGXSqBwSFjUcaGJhxz0aB1QqDtZsleev1kU60P00h8CZZhTannvdD3YkvZTWI1Cu7fFWg7A3Nao3nRALbPc6crwHY9t2loKHi2je2wBbfe6A0AcaQhrHeoh4ECgH8AeqxAfvuAb5v6vG/a7oNpQW0sfhfwDcX3N7eVSdPutfG4kbpF4wYB2IPfwCzJUfjtCL4uvJJ9BFzwpWBL8haDXycd7/yCXg3edandlrHrEtrQcg2ToDlk3W04P6d8aQcASWe5g+5SGaPL6iYGXSIpFhhMJzhW+gQok22fFhC3p9sTEnrkZUmrS2NuqUJp17LvehoTnnff3Xs9KyaFvYWG2VSQTQ2L7R86dks6jdsWC2BTKtNCPItarW8i/ZxDQBwA3BoIhxrTTljMwtdg6WrKJ5qLf5BO0g7349ShNhF8a+A64ThzATTUrzodhSaaqm3w4LS2/I9Arc768Ds5+Oo/TeBrTpHmOwK/zukG75d6WNTFP7C9nlBcydBMN9Y6ulDLa9S6TbcHLL7LVQy6y1MMukRLxnV5yAY00cTuwX3BteEJt1BjeDsdcwHV+vBfQnldMA11zokv1qnWhz4dSQlh0wbaXmN5hwLYHmC7aADbs6OvNd0+ahunG4NMf5ufXlN9dBrmATixhwuk1QbCfl4Timpq80203JONMx53AdsuUEtdYZvu71CHQJ/67CuSRG22Y+d3RUdBAPYBNwTGIauv1NdAA5cwUEwssw7E6u2O5darg1HwpUCXAr9w4/mnnOQ6HNleJRYJ94+Vsm/Eshwbb1wrB1LufvkuifY161dODLpUAtMBiwHS7NYbPXmcqYDrBI3CwSzY09o3pGk3zBajh3SpgHfKuXfM64JZdjs0pqcJtIPAbJcxgD2gszPAtm0Lxh/iHCazknWO38WyE7Ic2W0NANpgcZ0YgnW82tIzjcDbsG1SdahPrcv4DAm2ge2ibR8EQNYv5j71OKTAw09A1t2baV0wIEnDa1bWAEHSbQRCSWr230TW3jbwBdlO7oOahdaHX7qNfo11/iBQvLHLk/DMiF7aFngOuy9Lm2a0EwCoWc2xzEGXLbrLUwy6RMtp1uUu+03VTbhX47UtPxNuN8dJizY9TfDsStr1V/nZ2OXcEyvC1N41TfdC6j4TAG0t/sBpdwpDA7w27NP/GdkBlLs0/nt36A30VEqC4QYYbYJZ33JDw4aA4DYAJvvWQLiWv8AxuqpLR0sq1ALTBdsY1DrhkWMhnu2opTcmISFTxoi2uCxb+KVk6Ft+Q4AbswSHwNdaGUVVD+3/gOXW5CcEvgZsffCleYrAL/yvXudP4GtLIJLug9b3W+QetD9DIO/cix78NlnNWawFFIMulYDb49TUq7wA6m4pan/aLcqY275pNuzWmu4kcRdKDSc4cfutTwJLsYxS1XS+iec1xOknF3si0IVdm8MN22D8BsB14bdHgz4QFoTYvs+G6D4DgvK0QBhondRnaoPWbEO7nr70G6tOfBpm4nkA0QWCuwJwYB9JoSakJiBuUa8Zs7uCLf0+ANi2Qi11Z/az5+zbs86GFJidSgDOA0bWNpoNMVANwK+sW2Cjrs5SumGiOm67tRcu+IbcdGPgSzMcgV/nnGh5+HUfaAkIpNFvczyS0ynlhdP6FywXUs7eNViuYovu8hSDLpEULZaPoTRhA2cwN96W7YNbcvvmJeF8ez0npj07QlumOuS5c1YX4bk5zWf1xGOZU3q8UzPTV107igay0jZaaNuAtnbMRJAdupOu17OoA8TGwrsAwYTuy52taUSOVS2UjmnU+/mQwokfBeFUCPbHCTsN+gC0xlyXQ2FNHYNtQBxLs+92oB1saZwW8K2BqgOxPuzW03eCIkDrX/tQfesFugiyrhNG3ZlFCIBb4Ffqekqh1zmGb+0V4XScumzBrNqnydprs0YtlU463klF4JeeYmxcffBRULt3A3EiSoqacEzhf3HKpQqvga9xFc+m/pZlsWpi0KXK5NK4EXtBW3uUqVlzB0xvUjfr1uMupLo0XFui/qp3+CWffyxiw/7T7O/oVZ+bgDawvRfUdgXatjzE1GeMbdv2BbDoJoNsrLr1Pe+eih4vBK4gYOy5IDvn7cWpQTC1UjXBbyxuKL5/bKrUOjNpp1h0v8QOognh1gfbUFz7MwC1wtmvK+j2exiG3JdrKwvZ38Td2bq7RuDXgqcHihaaTRwZtvbK5nSqQkc79Jr9Qm7OAfClWQnCrz0B1OpsEIR9xZ49fd9nofT8fPlfSPHRMqLgS6F3ybTNekpKEXbVHyBd1vTEoEslML0bcYB0O90LKXH7wGvTfn3gtacVZDCr9kIrdrqJ+Zy2EbqLFuvZ3FgGbQ3+0Kam8+h6kqkXKPVeaQXSyLETobbXbLFO/HT4GxxeJ0h3KiAbYrO+5zypIm7CFhA8wKVxaxBs9/HTlmnwa9KKxW2LHzqvJg3xXGq7vl3uux5w22S1reLGwTYOu3Hw9bd3UdiiK73fBGZl/L8QipScKuHXGcfaq6NY0NVhwotfg1549SwAvagyEbT2okrDB18nT03wSw/tl2PoPm1R0isr9b3md4749zCgzp189+uwlCR8mU9GxVqeYtAlWvTlhfq+oBP2a31GNjbIImn2acT1SqthW8r2LscaQM0g1rJzy4Va9h1/jVCZlkTnSTUix01q0w0MI9G8B8GrYd9UQI1BbRtQO9sajtUY1u0ZkL49fk16gWVqgz8VZGNwHc9Z/Jgd1OS+bNunTgO1DsMWNOiODQA8GPz6GQnFD+4TUeuwkZZE2ur4FOA2FLcNbn2wDUFtDHqDv9FTQob7JQJwq75LZ3sMfH2Lr8OkASttyMV5Iui1x0Lc2kvimLKouTrD7Idauk55hSA4lKVJX0ttCUQ2N7lcW8ut3l+adISugxLLvv1SQqCcgvVkGmmyKjHoUglM8KRvSHMgdXq2TdCYXHSA7Zs3YHAw6aOJelQnbJ8thKb2suqYbrQsQumELA6J8QZRx/tgCBfkKNhG77sWoG3KU2vakfBYOnTzJPd87DbrBL1pxwxGix4nvaKFjh+yoAWPpSuSn4QBAvvbPxZpnNeswKRx78CvJGl40O3Ab/TZF4LYHg8bAy0p6nJfptxPAbhMtt4mwG0XsA1u804pawHfLgq5X5Z0O61vNcDtAL4ha28b9FL3ZhOfwm0T9KaM6yXb6t8j4GviIVBdAxBM5RT1NN5Z3qVMsTQHod6Ul4nLFl3WIohBl0iKRe5x6nvshP0mAsSuENsxPJ5OyxM8pbwWu6MsCmNNb7GGTannMy2X266apPzbOp2DoJrWgZAMyRP3nMc3BbPayWWSpjUg1IYa6U3ppZ6H2TREZ1Vbh1DHDrlBYTZm0e0K3Q1qK8PgGFyEoNUFYX8/SY8Vg98W8LX5jVl9m1yYU90zaPSuz5xJO36arLckXhPgNsEtDXdhNxaH5Ef/z5w8hr/Dxq0FJakMzb7sWHSr7waAzXMrBXyVt0FH6NX1wbjP2npo6mAIbvtCrw7rAr62bPz7wOyDhMfh0O+sgBrBWpA8ks4wScrRQO+yt+hKnnV5OWrJ9K9ceumlEEJg48aNNkxKiQsuuABr1qzBTjvthKc//em48847nf22b9+OP/7jP8bee++NXXbZBc973vPwox/9qF8mxBQ+WYdPS1rGtbr2EYGPnljLfCC8T+Z9mo7jpFt9oucZSyuSv2i+2soxpZyD5SgH/fS+/l336VTvAte46TOtej3Neyf1vP26L7xrGLp/AvU9WvdT7x2v/ofyFSyDwHeVb/2h18/Pm5F/j/llTMuuLZ5fzjq+yMhHoPpk7rbG51CkLvppCOF9asfw99cfgWDeaJ5smvR0hURWO2YJkZX18yfpZ5m0H7qvG47oPl0+TWlEj+tdF3NONr45b8CG1c5Vl61znUToOtAydq9B9B4I3muRewc9nzOheySUXi39Kp45l9C+VbmZ39U5i0DZmvIx181cK/86unFKe70EgFxI9clK5FmJjHzyTEY/M3lp9+n6UfvG03bzoD86n6aeVXH8+l3W6nPm3PPk/J06Wn9+mGeWc++bukqfhf4z0K97tD50fTaH6nXTuyr2Hgm+W9o/g7yXBT1n733nlaM5B+d+Y7EWSEvCovvVr34VH/zgB/GkJz3JCd+0aRMuv/xyXHvttTj00ENx8cUX44QTTsD3vvc97LbbbgCAjRs34oYbbsAnP/lJ7LXXXjjnnHPw3Oc+F3fccQfyPO+Uj0UfowtUD9BO+7RHabfodt/WyRIbjds9P73WP5yiWvMDJBsmGteDbDqvHtWm13E6KKlcEhQtk1BwWzkHt8vm7aHDTFJGqXWe/O48aRSNH4vbNQ5QtyR2udeBNOtlYtlOYhkOFlnwXOphfZdpiZ37pGNzm9IxFjGanypM6t9w4lC3Ztdyq/cjaUBUYzOp1bYKk0iy+JIrUh/tmfKCQ793Z0jBykG/V8eZhgU3ZKlttOjqtDInXpWfzMtPzLrrb+sj/1lNrbiudVf9L/0xuPo/tfhKKRxLrpQyauk1Y8yFFFU9NvVSxxGQVV0UDa7NArADTWthgFOBqaUXcOJJt6KHLb6B/dxwm9ggSnp/tUUit7ITZrJqvpvHiQH/ZSyedXl5atFB9+c//zle8YpX4EMf+hAuvvhiGy6lxBVXXIHzzz8fL3rRiwAAH/nIR7Bq1Spcf/31OP300/Hwww/j6quvxkc/+lE861nPAgB87GMfw/7774+bb74ZJ554YvCY27dvx/bt2+3vbdu2qS+0p24aGqAud7ofJoDbzu7EXYA1Cs4d027btpSUCGXBMkipkotRDgt0zGi9aIHaICC3Qm/DtiGUeJ/0mg3Za1jXvyduRwLQJsBeKF5tc6fnWftFaX3kJcKsitu+b98lW5rOe8hJqWhaoRmXDUTQ/SgAx+C3DXxdV2UfmHWakZtReFexFXxlPaimxI7Gxu2x+6MGtHHApckK0t5woZZ+DwMuhVs/bgxsXfil5Y1geB/5RUafYw7Mmjx5LssUfNug19RDAx9Cg6pN33NtpvWyqsOo6qestlvoBYFbEr8VemlhePAaBV+E4ydvG1qJHcA1t2tBdtX5pdC7nMWuy8tTiw66r3/96/Gc5zwHz3rWsxzQvfvuu7FlyxZs2LDBhs3OzuK4447DbbfdhtNPPx133HEH5ufnnThr1qzB4Ycfjttuuy0KupdeeikuvPDCWviSsOga9an3Cfs03k9DQGwkvBPE9r3nu76k+x6nz4umDbqalAjJU9NSfQbXWlXez7YXtW2b9wDivkrt5OkCtrH4oe0pYBtLFwEICxVdn2eMHy0pljleQpqJMBtLrw/Qpqc9GcDXMNBLL9WqW32v4tN41PIrHRiIgO80rL0GOGyASHs+plSohPus7T7pasVtG4PbBLi+9TYT9Lu/zYVsCrRNFt6uyrxnKW3Am29R+AUBXCGToFftW1l5XQjub+VVP0kd9+G2L/Sa704UWauvfmfPostevNh26Wx34NeAr1hC7WvWr5QWFXQ/+clP4utf/zq++tWv1rZt2bIFALBq1SonfNWqVbjnnntsnBUrVmDPPfesxTH7h3Teeefh7LPPtr+3bduG/fffX93MC/V8mfA4yR1AbS+uxkZpevjUQLanpWiq17Et7SBU+RSWcJy+bswLqWl6QLQp1BMeUwO4+uslxvZtdCtPUPI9kgqKTfDaAr5NFim1PQ60Qy6pEzxW6w6JsNx0+0wAvn2ANgi4kbxNalUzKj2YBTzIRB2CjWVMfXfjhcCXhjngi+q/BRJqvfSgV8Wl+QzfsK3W3hBY9FFbZ0fTPdMDcpusuNRF2bfgUust3RYD2zbr7qR1z7dM0WemgeAY/JZSICcAS629MeiVMHVRDGrllYbOJKmv1MrriFx3H3opxHpWzyaF4JfuO+m7qLc8SG/cTs5B0rJZxmLX5eWpRQPdH/7wh/iTP/kT3HTTTVi5cmU0nvBaEVLKWpivtjizs7OYnZ2t77dUe5yGtlT2gNsFBdkOgB1No8v+kygItaF4LVA2FBxPW52u7YDHnaR8UoG45SXe2PhIUdd6bbcPDLdNligvnagFC5Fbv+le7NGI7uTa3Hb8hvT6uhz3AdoQTLTnu73s/MZSHrHsGpUUar3jxMG2vr3V2ovqf1folbRxLOHWIeJ2reIiXMe6NCJTAVdlksQZDnJrv/X+dDI09bsZcENw64cBQEY7EiL1LFRnQ+6WuXDrWUkKz3a8ECtupgHX5BkgdYNYYH1LryRQbOqxsfJWdbJu5QWx0gpUdVKacpfCwnPl1ly9GBqtvCr3sCdTe+94748O4OsrvGrxAqkNtB3Ypd/lYPN2sFhdtGige8cdd2Dr1q1Yt26dDSuKAv/yL/+C9773vfje974HQFlt9913Xxtn69at1sq7evVqzM3N4aGHHnKsulu3bsUxxxzTPVNC9mqMDaa+YJCyX0oPYpf9UvOaCrJdIbYHrE9FQagNxZMt2+n+sdZ4yzGmoUmu85CqdQwEMkYbxE64DIeH0knpJOp7qn3KMgSvNE5XuG1onDvx/XRocPCebofCmCZ1l5z0OKljaFstu4G0U9YpjcNFMDiuIIzUj2NAJPd+q/gEbL19YuDrb7NQ0AC99L6zYENKsGonSxJGqdY73xD02hPvV78ax6knQm49TnfIDVlxqUtyCHCb4DZDtY2G+9+bwoxCsOtYbKlFVxeQgV8ffKnF11p3hWvpVd+NlVeXiYZbH3hdwIXz2/mOMPBCmO2yAl4NqzUrb1fopdvtz47vosWSbGgvajmeFz74LmOZejaNdFnT06KB7vHHH49vf/vbTtgf/MEf4Dd+4zfwpje9CQcffDBWr16NzZs34ylPeQoAYG5uDrfeeive+c53AgDWrVuHmZkZbN68GS95yUsAAPfffz++853vYNOmTd0zZZ5409JQaSemM9HsxF3yOgnMTguEaZQpP0Nqywe2QVkbsLZBcS2NAU8wtVHYqX70yomrGLyGttv2dqDcQ+mkALCfzpDyz6UNbml4YHsMbkNW2xDYRqG2Bm2oqQlah7oPu4Jx1zwljb8NpNUGtf7vEMimnFsMPGIWNiN/jVwDwRRmffgNga8/hjcFeqsKRyzDJo5n5aXQ6t7WJG+15Kt9Td6q864VS6uSZhdHO+Q6yYTAFxXA+r+bINcHWRrXh99MSAdua+BLQRd+HS3RKAGUnhtcyIpLv1uwDYCvgVoKvdXj3LXs+lbekFuzOucQ8KqXQdM4XsWvBHj1u0J6lc/kUDbSXAB6a++jQB1L6fReKHWA1Zr3k9DXnXmOtQhaNNDdbbfdcPjhhzthu+yyC/baay8bvnHjRlxyySU45JBDcMghh+CSSy7BzjvvjJe//OUAgD322AOnnXYazjnnHOy11154zGMeg3PPPRdHHHGEnYW5k8z6YEtInV09Uh4kfR42iwWzidaWxmMF46VFs2pItpafkMuS2dQExV2slJH0W+PG0h8qbk/rSedjxzoPQpacNgjuAsCx46cq5V5og1v6PQa3JE6SxQleXH87La4E4A3FS9Gk1l03re7HSh1LOynUho4TA9jUMvFdlQHPUmABV+j4XhwhHfiNga+BXjePzdBL3ZvhgYHNoQ+8IBAhq4hdrLwmb26ZIKqkzpiOt76I3kf1bb67stnfh1zHogt3nWcfcGncmHXXAK1fB9PG7Ja1TpaSwJwBYd+SGwLfGPRS9+ZmK68KM824GPDScbwV8ApIU15SVBZbUJitgNdaeT3grVl5awq9kGLqAL/T1oSHtesKL2NJ9Os4S0mXNT0t+qzLTXrjG9+IRx55BGeeeSYeeughHH300bjpppvsGroA8K53vQuj0QgveclL8Mgjj+D444/Htdde23kNXUDfiNNqqKeo74NkiOde7LynDbOpINslfzadAa9lw3FqbicN4OmcW2S/4IM0BGgxDf0ebCnHtMbhhNcitfMgBrJAHYL9/VIswNVRm/PbpK73hQjEiQHuJHAbaJDHGun+tqaw2P7TUMo935jHQFhXqFX7NB8zxaU5FK+zyP4V4LrwSgHYgd8I+LZBb/iGC4W3AC/JWwh4QYAlnLzp6HIvRud62LMDwjmMcx/Vr30oT3RMLnVXdrajDrkhC64Pvz7Yhqy7QN3CG1PpnYBryXU7WErUwbf0rLSZkChFJFxWk0nRbSVQA14Lw4AHvARQye9W4NXviaoGywp4yTulZuVNgd5onIZ9olEWCYapUtuOLNaUJaScRv/E8tK2bduwxx57YL93XYRsp/jEWINooW/0toZSLD/R8CkCbWLa0QZGCgNO2iuZcrdE4kTHYcTSbHhZLcRdO5HlfJr1vEN51crJj1Pb3p5mYx5S1Vb3ReB7CDo7Am4MbkMW25gVd5oW3S7qZTFu2JY6SVRXa20K1AaPHc1pfB+jpnFk/l40bmi8rhvmxvNdnE3a/nY7860XFvoNPx7ccDcuOS96zqGiGcoLI9AJ5NxvoXuN3FOxsbnUhdkAbMya2wa5NctuAHDj1t3qvFpdl4moC7MDunDrCP1vrb2gYdV3Ban1bcaSWxLotPGdOCCWW9j4tC76dZPWS1onQ/XRr4e2Dnp1WW2rh7mTU8FVqL62PfIWszWfcH+VjzyKH238Mzz88MPYfffdFyBTw8gwwv/3f89BvnN9IttJVfxyO/799/5y2ZXLctGStuguuASWbo9T10Zd23l0AdlY/GBYQiO4qVFv92uPE00/dIyBFDxeyBJoNtG2kLUw+ImauH46MvriorOVDq6eENsKHn2zGzMMwSuzQPnWyklIuPDblqnYOQ1Q9ilw68WbBHBjcBuy2obAts+Mw74W8/HaBIaxvE/DWpsCtU15TbHy0jgx6KUWXhtbSDfcWnZNmGvtjVl668+QultzddaVfUz9ckExNoY3ZN0FTP68pPW5LYilK3j+6RoKcn3rbiZKJxyAht9qO+C6wKdadAGg9M65sPXBg1nHkivJ98yx5FrrbcDKW+p8GrdmE9+38GYwdTXNpbn6LdBo4QVqMzWra6frIHFjjlp5dWhcobJviC+bN/dWahVIqfNT7vxksUJi0KUiPa+Lrj4PrJR9ms4vCo1p6bRaaHsAbRc35qbTH9K61OSqXGve2QYXhS2Tjh83ALYxCKbHHbLKNhRiH0v6IO6qXhqtnQcCdQCOwa8PvikdCBLDPSdq9wz9Phng2q8tgFv/XQfbRotu6Lww3Hqwk6qvO3PqZFFdwTZUXqljI/s8xyi40PuCLu1iZMY+ArCuof76psbGZycT8h5AGUmr7tpcEWgX4JWeu6oK1/FMA9+CiufOPCXYNWOPl4pikEsBF6Duy7IGt75Vt4tFF3CtutVkUyqtEPhGoRcZSlSwa8fsQtqxvMnAK0UQeOv1M7JUFiHINuCFhmb6Lq9NXkXeMenQi/h7h9b1FHWtskPBM73Vl6l4Hd3lKQZdqsW4ESc9XuqLtpEC09NOBs8Wq0cr0CZYPYLpNuVpINWOSR5SNI8ha6PzWotAcMgtOQjBzj6TV9zGRluw0R+L21z2XXMa7TwAai/5qpHiAXCtjJzmjXe8Do2PtsxSpXYkTQi4JrgJcNvgNga2NKup40x9NcUb8oWfmp/YMj7JLsYJkOofIgVsU4/fSR7c+uN1ffi1kEv29S29MStvKvCGwujyMLTTpjZ+17fuTgN2e1poKzzqn0ZMIWtubbsHuRRwVZxSQSKB2xj4umlX8OvPuAxRWsutD7Yh8PWht7LkGsB1rbwWbhOB14RT4C01rFIQhvA7Xtx6WQFwM/Dq2DqO2du8++vvH3dJrdqbrlb2NbV1ugY7yNuTbTxeimLtROY51iKIQZdqmqA7NHil5rMtXtRykBi3DWiDcZrTrW2uQXKHPDflq6caLbrkMBVs1UHYh+AaAAdeUM0MNWkDuGFTYl2IctyEZR/tPND5aCw70nHgdBZQ8PU6ERobH9Qt0gkPZLZJbfdABHDVtiqscQzuBIArvPRoQzrFZbnzGrA2sfa6UrZE6XrsWP1MtaoOAbZdoHZS2DX7l94zqOayDBd8U6CXWnnTgTfUwHdvKAkDtbJu3e0Du11FQZUQrLXq6jCzRquzq2f5pW6xXWXclmvhaIFe4VpxQ4Bbt+qGZ2LOQay8okDhLVVh6stIaMjV8BsC31JIFFIg03FLCM+Sq+tfBHgziZpLM82NuewmvJqwSlhPBFo/6TOzuk4VAAeB1xwsEXhVWL2jx3nv+AAbeu84PSleuE20Y6Vv6wDqWmfp8UWP/CwxGVf6aaTLmp4YdKkyqT5LVV3uhZYHSueJhkIdgzUATTgObTC3phdp/Dft0xA3HC9eTjHrkttoCR83aM31IdgD4Cb4tWnHHoiinpdUda0LQe4N1pl4hro08oKdB4Ati1rnQQP8uv30oYaHG6vZ2lul27uDrA1wSdpd3ZTbADcVbmPW3ZQlc6ahvG9ZB9Rn3G7qxFFd4TaUbhR2BxivoCxewv1N7iHzPQtsp9BbuTJX+7UBr1vvq0Z/BYV+WHXvmWdlCuwOqgjstsalwQEQnlRt1lwAQcj1Lbj+ZFUGaNvqcea9eGidKkinSmZnW3bhllp6jZXXWmQt2DYArxSq2SaqOuqsqSvTx++G3JmV/PpKOmI0/KYCL2R176e8d2rQa44Rg9y2+tV0b8Seh11BLPD+mqohaYFEx3IPnS5remLQpVqKN2KPxmPri7QpzVSYrDVym48zKdTWrUiJ+WwIb1NsPwqkNB9ueAhuAzDbBX7NPrH89q28TY19/3cC0A49C2+sjP0OBFp+ftnZRgftLCCdAynQaxrTVV4QLrumRkEIkmKdQfRUSViqFVcEv0egV6fhw20IbJMsmhNA70KOV2rKZ9Simxi/j5tzEHYjd/wQHQt+vy6FXwu2Aeg1Cll5Y8BbnQ8coCZnBHq/SXu/hV2ZU2DXseomyH9e1yPUYTdq1ZVCjd8M7UvO0UmsVibNcmdIlsHfNMyH3Bjg+jMyO1Zc77gQvncArJXXQHAJAWP9DUGvAl7pWHlLmQESUeA1xVWDWx3e5M7s11FTP6mbs+/OHB+/q066bRK1GvCieu/UJlBz2k5uRYyCr3Nwus373QeEU95zTe1E+4JhomMtvBh0qUhDcVGz0bedl5L3pjZ4AtCqeO3HplG6QG0b0Ka4TUbzmLCfr1AjKWbRreDWBWEfgDvBbzBT4ZObZA3o4CXtAbUpHRKN6QcU6kBQ4dUxHDdkmMZmGHxloBERanyo8DTopflJfYY0uvD7UGl/u3GFEyduxY1Cr04uBrg+3Da5MA82+ZSXzjTdutrynAq1sfChwLYPkCeJQKxNz2dP1KHXAAGdLMjmJQa8olqX1weK2gEJACTDbuu5xiOGLCpR6O0Cu+aQsnJfrlxf4+7Lpvz8604nC2sSHUfrW2/Ndgq5IcD1Lbq5l6aTL+HXIQK4AApRgW8JUbP0hqy8PvBSi60dw6snrbL5QLM7s627pI661l1zflX8ps4YWl/pDM10Swx4QVKKvnN8qI29d5pANPYQi1WjyCuvHq9ho/C+k/fPchZPRrU8xaBLpBqBi3XwCRuJCfluBIvI/n0miWoC2yYw6gq1bfHbwlMU2jdk0W2y5voA3Aa/TonWtoUvlWnw9VWq6/EknRLR43TIW6wToW5Br8C3stpW/33oDbo3S+/aRXrcQa5rL9XuFzjn1BdyY1Zc6qKcOXGa4da17tLOgrBSAawNZJ1ZgKegtsvWdaxsV7hNBdu28hyyo8GO14U3zhUENsxxSRjguopSmFBxRat1l8ItyRRqsAvz7CT7B6y6bUpxG6SdaiqgHXb9ePYZ7V0n/xnmbyshe7vrx6y51XYXcn3ANXBr6mjuzcJswkvvLrLhusAo+BYi837LCnghAJRR4C1rLrsl2tyZdazO1l2gqp9p7swmzLxHmoGXQqubUjr0Au57x11BwKtPNQss6vKrYCr0xvbxIHeSzngWq68YdKn0y3n6xxkwqdT8Nhyzy+y5XaA2lHYMbJugto9Vt2/j1VeoEe6AlxeWas2tu9Q1vVHcPISclwepUhOAbddOiVi8kPp0IgTdzALQS1/+nV3MTKRA4yNJEcCl5zUU5MasuDHA9eE2BLYp1skU+fu1ge/QFt6UfKdCbSx+G9x2AdvUck6JZ6G0KY7+70Ovb+Wlbs3UwuvMfAvU3JnbrGfuuF1vzK6FS+G4MFN1dV9ukjPG1gFs1GBXArYDzbgwVxbo6nyqzlJzzrBlSmfFtuVI8kOvX8q1NKKTUQFwINcH3DbYBYDc+03TLiEc8DVWXQAWemPAC1TWXArAdJbmkDszkGbdDXXI9Lfu+mGJwAvyznE6Sbz3W9N7R6cbes82eho1wW/TqcUUadIIA7zDProXXGzRXZ5i0CUSQkJ4Ywj6VMAhxk6lHSgxWlu8RFDs6sqaCkZ9ASqUx6HHC4bcxEJ1wjTs7IuJHLvJChkC35o7cxv4hl56PdQ27rm50yKtAyMW1pwv0rHg9WI3laVbjpHGB20YR1zMaOPDAd4qOZJ8vfHhnkzk3KcMub4Vl8ZJAVwfbptcmOHFjSkGrP6SN6F0FwN2u5znUGA7bStuKuRba60Jc28n/b0CBurSTCetSrGeQYThFjD3Qt2KCxsTNl4XS20V0FCvbL2sjmH36QC7Zh8Ku+6DhLo5k/M0v8n1yE1Z1jqLMmSiCG5zXZhlbfyt3aYh14FdM3lVC/H4SxBRy28G6Vh6qZW3BryCjuEVEQC2R0Jo7G7Iuut3yvS17tbH6gKovxT0rwjw6mOqbdUJuSl678BQ84BeZ6/NQRW1+oagN9b0aG6SVL/N+0lD7sSrQ7BYPcSgSyVQu2EXDFo7qpObZMM5xJLpCrWhfSYF2yaobRsL1zymLbopKH85k5D1NtQ4p/CbdgViscjLT4bOLX5C4TV5o9H7XZvU6xw4XqrVyU8z1JEQAlsfeg0Q07jJk4iQdmm9Ieoclpx0y/nF7qEGyKVpDwG5FGqd7/owPtzGXJhDv5tE4wbBVW8PbaNL4AyllGd9FytrG9x2KbtkK+5QDclI0dbG6hrojACvEYUJlc/KepYKuwDsvWwoJ+4h06BYvLb96XbheozAe+5IuLALqOeI1GBeWaHrsGvPhZRjKfVETQCEKUsplCsujKXUs6TbMldwWdj9MuSiqJ0eteb6kJuJ0sJtCuxmpEKUqMYHG+i1E55p6O0MvOR3yLobG7tLYZc+Q7rUTxO/aWx5OCwdeB23Zq8fpNbx61dbCTR1uLa6Ojv1PHBaTuYDikGukJ0nb15q4uWFlqcYdIkWdYxuF3VoTLadTrRxFwjvC7b+765g2wS19cZjLdsTd1bkzovBbewALgjTBpffGA+Br9tA6wa9Kj/184vNCl1LKVIuQ8Bt146JJuX+i53I9LADxnrSZM21R/fCSQPEwnB4RlcntSbgDR3WV8dONUHjeWXuXw8KvWbfGORmTpgLxUAdcENW3S4zA4eAxLpfBp5YUQtuLHwCTeIWPATYtlpwJwDZLOBy6qta49Q7TkMxl0AQeEMw4Vt3LUyQe8mHXcA8b7x7TYeb+7YK9H5H5DTy/fihYnbubXO/B4DXAq7OO1RDXy1BU8GuSdKH3bIEMkNUoppRuISC3aLMgKysYNaWF2wjvBQCkBlKMhY2EwhArwiO/w1BLgVcWpd8i3Bh51SGhWrqrp6JEqXMUBirM7HyZlJi3jhCyxIQupZYS23dnTnFumtj6nh0nHnNlRlu/fTX3QWqOmreOZWqThkaZt7T/oRqZg91vlVmg+N4/XMMQS/qcVQYyVOgfZAEvCmPHgK5oW3Lon3N2uHEoEvlNSCXoro+J1qBIgF2YmlN6sqaArapUJvqChiL26QQ3AIVuObCiyeq8T0x8C0jaZJAmoNovkJuSd1dg0NhzdeyDW5Tr6GK25w/vyMBQGNngulIiFlzSWr6f3itTrVJQ7DX8GgcS+Unr+MEw73zott9a64fL3T/hTqYukCuSTILbDPhgAtCTRbeoAL3kJGxEtVgeIEbSEkuvYH7sgluUy24XWE2BWAnSYu6ngKIXgsfeEMwodJzXUVj43ap1aw+YZNGRN/bQ3rOkbSBHitWWteair7OL2Hg9TrSpMJbG2J/mQ40hGFXCA28QqIo1YRLyEoHdoHqHiqFVMynMzLKSozLHKOsQCkExmUOZAY6lZU0gwHTwv5vkoHc2Bq7AJw0ShPPLCcEY5mugFcBaVn9hztpFbXuqtHAk8Gu3ynT6sqMqo6mL5MFVO8V72VB4oSAl04sGRrHW+1HDjkh9EaBtwvseu8r35pbO/YyFK+juzzFoEsksODtqc7qbJ1siZ86SVAXGPLjDwG3TVDbZi2ceDbSSMO85q4spAO/IfCl+/rQG3dxrl6KFKhCL7ZJeky7dFQ0wW3b9fPjtCloUTc979LtTHBcy0g8cuQI8HoNkATrrpT13aMulBM+WJzdvfKtA28Yek186q5chdUhl1pwfcD1rbv+91TRiXTcjLrWWmciJCde50N2Uht0drHato3breINB66xvKRKNfq9/GirbxPw+mN4m1xFY7My+7ALiFqD0EBEzarbIpuO2ccvmpQGfe0ZYoLNs9EFHgidUw0pjiuz3a+CXQAaeKvOu7LIkWelfv6Y7xIwIAx9nXWBBr9nwAxKFBocR9BWVVFZeI211YhadZ1ZmYk115+kqpCZfXZnMGmXerKpOvAal+Ym6+5I47hxXR6XeWfYtbFJ3CbYBZo7ZEx8Cf95ECLDnsCLant4PXc32c7QGwPeEOzS/f10Y5ArJmubsFiTiEGXKNY4XDLqkbe2h0uK+2osbpt1KfidxGkCI7W9nl4T1Na21U8hGK9NIbgFyLPeAVzZDL4B6A3NVuouteG1Gt2j16DXhLUpBkLV93q4D7ihDgofbhuvUeK1qANuuFwNaPqN6nongt8I8XvhXevuILAbUcia21XR+xiuNZfKhPswFoLcGOCG3JiBNKskdVOOAq9zMi1rvk5RsfKdBGybgHbizrmBVJ/kiICvcXMWEjWXc2HGkAJtrqIWdk1nlYhbdv1OqSZLSOqEVI5S4ofYJQC9rcALKIgQms/0eUphOqsqyKXfZalwK880IApAauAtpcAoK1EKgREUWJZCTeI0EgUlNqCsrMBAFZ5JCYgSJYSdTdkf12sgt5qRuV6X7bhcZMhRokDlFl+iGXjnZQ7fuqsGKHuuzFlhx+3O69SbYNefWM2HXUndl4l7txDSFp2KU9VRwK2/9fHl8CtIILwf8AIenAaaCI3eRhGgdd9tHuzS/Z0wArn+Jg2+S7p9nSBl0R2e2NmiO10x6FIJ2QsmF1Jde8XaHiypFt1QWJ/ZkVPhNgZHUeANHAMtYalqmjSHAi5QvYhC4EutFrDxXDCKWSQpzFKXZd9Vue7i166U6xoD3C5wm+LiGkZ5OPelv+xGtRRHGHq7TyDiNaSFvzQIBofdqGLllNARFdoecxM3QByCXgq5McB1lypJs0iqxmHmBpL8RcfmEqXaPmsurj2U8lyJjVv2y6TrWOBpTFbS5ZlIJzkioXqbdm0OZDFm3Y3CLiZrSFr35VDjHHDDfGuujMRrVaQcDcQaeLHPbQK8wlh4K+A1Fl6h2yMu7Er73ZRdpp93BngL0tE3FpkCXylQZgKlLFFmhZ7AqcRMVngXpPqeobr3c1GggDvBmJGB3NAKBQCQo9BjgksHekPAO0/2M9bdeeTKoqshfN64L3vjdmdQtsKusVyT0BrsAvX6SYsm5H3g7xPyJHLH6brjdf3O7E7ACzRbefUOUSsvBVqdFpAAu87peZArpK3fCBxquYqXF1qeYtAlWg6TUfVppPWx6obD4nFqsES+TwK3UeANhNXiRMqqrwsfUHdXDjVE6aQrKiPVmoj+8hC+K5TNo3fcFOAFIi+zgNqurw+wQBhyY4Abm8CIpuOHt6mpU8EvWzqBSBrwur+rxsciw26w0TRd+VZePyzkymxALjruNAKtxj2yuh88+J2g+EKzdcfUdxKqJqutv4xLn+P1jT+0wpZdE+ZaeGvXTLjWXbNHE+y2uTC7ljB9n3Z0X1Z59v+L8PaYRGCf0E4O9OpdBSAhLBQY3q2+C/vcUfEN+AJZpp5rpfmtn0t5pt4PeSYd4C0zYf+XEChlocFXoMi0pTYAu0aZMKCo8uqP5c2F68ZMZ1lW29VYYAO95rLlAhpmocG1sNbd+XIEa9UVwlp0Z7SrdbVPlelBYJdYcM1vdU6RcbsEIo1FuI9115+wyoQFZ9wndc6B3pCVl+7stROcCeQCUFuDXXr82juCxCOQS625UrTdUCzW8GLQpRLLw7WiD4w3nVeq+3KT1RaIA0wImrrCbSjtJqjt2rCk6/wFt/tA6/2mllvHPcoHYns8eL+HBV4gvVMkdQblkBW3CXBTr11bXpM7FTzobZsx04ddv2e9N+x2lON6XmucxfZxr1uKJd+UQ+ryWm0WTAq5MZfd2PeaCzK5Z8z6n+oY3cE3bH1MV9N+fcB2Usht0kLPOt1cts3A2zQusivsTtKBVF871/wX9bDYbxpe41zzUIQHD+a78A5HnkV2tj/zTBPEKiYsNJQFIPRYXSEkMg24BtLKUqLIRAW8ZYYiK5HLEkVZYpxlWCGLyrorMw29AqXIAMy7sFsCyMbqPSUzNcmUyIJr8NLZmY0lGFCW31KP2y0g1W8CpMa6awE2G1f3vswq67NQYTMopga7VWr6u37mmzoqnfpaf3dnZJ+QdVefVGN4DHghvXc/3cuD0RTgjVp3Y9AcOCcfct2N0pbDUjcktUliOlbppU8dy1sMukTLwaJL1RXKm2E3LX5XuKXf28bc1mApkHabG3PbuLi2MoutDViDLXi/a5baKj8UelOAl7rdWmukacTA9Pa7wBuajKoNvFIs9CHIDVlxmwDXv3YpLsxuxlxAolZ1v3zp8iUUeDOY66OPi3rnQRLswmscLJCcNpgH6T70+vuZJUiG6sSj7swUckP3aHzCJfc+ahZpTBPo9RurgG9p7K+oZToyzjYF7kP791FobHMtTmL9nNSyHC5vArwDwm59WRTaeu94T9Yst6Y1T8MS9nOyIcPhQOBhi+Bvab9Xlja7nrfQ3w38lrkF3VJICG3lzTKJMpMQeoKqPCsxyssa8JZSYCQzjMoSK/IxSikwq12aAaCAmq25ZukVegEhqcfdCuWeDLiQa+R8N+Ar4QBvjgxzGEFNOqWhUY/TnbHlmQ67uX0LNMOuynP1TjZ1Mzjzsge7QFVPY+N2zX7qAsbdlv1wUhv6AS/8eGR/kPIg77uadVe4913dewyu/PaDbk8LmHYD2KLLWhQx6BLRRvxyUXfY7ZZWE9gC7XCr4oTCXOhpcktuAqRYo7rNwtsWHpoFlob7y6Colx8BrwD00rSbgDfUQ+zDLlABr2/dtVnu0O7rA7n02jnfyX6x65wCQ74o2NAyNkBryscH3gywcWnD2YKw5xYZgl11DnDcI20HuKjC+ipk1bUAq/MnAa9xo3JRd1evWnaTPM/aoDFkway7NLccn2w291BLrsi+mbdlGMilappAKgS0TfV60rxVzxMPNgNltlCuzvR+DAJvwLrbFXZBn7ENVl1zf4rAtqAkwmDrhE0Az/6xGkV7gaUXrGhB6g439V3FE1kFviJzoTfLJDI9PrcosxrwlrlAQcbsrsjG1X8LvfpdZICXXiyh66JU1loIBZUWdmNj9fXEVgZ41X4lVoixAmd9mjOAHbfbBLuZedJr2C0lyJjx9tmYa67JqbAr3UmqALejGjasu3V3QYHXvt/arbsqnn8KstoHLuRW26qx5ctZPEZ3eYpBl8j0ji5H9YWalG2pcEt/x5YDioGPD1VNcf3GdOwY/vfQ75hClgsaTntpKfxWLk116G0DXuoOpc4v/NI0+1qkEdSi293a2BdyY1ZcH3Bj1y21M8KcL+1csOUmRA16Mw2vFnhJ+desRCDW3QDcqnwCvsUoVM7O+rqxU4m1cwDnGsZg18QzjSYDu2aH0P0rAaf+VTOdkrarcDtmTFibgrAHf1KrptmFPddkWaXVBL3O7L8Aamu9+vFDMJjQwdI0iVQT3Kacvz95TxG5b035xFy/6XmkWcjT1LcDytQlFRa27qbCLjxLWYaqnKhVt3YvIn4L1kT3lYGwWvyUNNMOLYLHEToLLkA4L3kNuFJDhcw0RGTasislZClRZqIGvKO8QJ6pjrPCAG9ZoswFVsixnrjKwC8BXQCluhhu760Acm3hzQOnU5uR2ZJYBrV+Lizsmm103K4aF+xadjMhYZYcyvV/A6/qfqNw2w67QHVPCSEd2LVhdE/a8Wxg137XZYWqEzq0DFHzpFT6VAPbugIvQDpkbTy6fxWp1bobUwRyBUzbgWxnsRZYoUn0fmVVTem//D7VOcjWT1M8QD2z6Aeo4CUEPnT/TLgWXEH2y5x41dqdwkvfuFsJ/T8TEiP937hNZqjSysm2EYlP9xmJEiNR2n0zSIxE0fqp4pZVGl769Dg23+ZYgXPKIudPy8aUn28Nj3UQ+LCa8kLx400CuQKq4U6vc+6VfwZVLv519cvSD/PDc/0x5UyvCT22/U3Kt9perSdLz6Gqy+FydHqpSVk5SoVcEybdbbbRbtolpPFto0vhNMZVT3PV40y/L6T8MauVdUdGPyaecYP273P63PGfE1V46XxC+fI/znZv/1B+/PpI67X7bCjs/jNZ4ZzrjCjtx89PqGz8vFX5rU8YRs9z0mvYJQ0aP3R9MnONveehEO719d8LJj3zHHTeT7VnV6ARnfAMtKL3oH/PyOaPKEX7pyCfcfVBAWAsgh8xn+mPqD5jlUYVL1P/5zPIsYAcZyjn1acYZyjGOcbzOcZj/SkyzBc55sc55sYjzBU5to9H2F6oz6PFjP6o33PlCI8UK7C9nMH2coRHyxlslyP9ewbzMse8zDEnRyiRYU7mKGWGAgKFP6O6rS+lclfWa/POiAIzYowVoiDhJWaEuo9mRGHX8DXvELVNTYBF/2eiJM+U6r6iv9vqJYBa3bRh5Dlk3it0Wybq70qzne7nvmvoOwdO/Ni2ajtp/wlp63zt/gB5Vznx6P5VJGd/Z2dP3j6OY4INq5/DslXLs2CiT0ddddVVWLt2LVauXIl169bhi1/8YmP8W2+9FevWrcPKlStx8MEH4/3vf7+z/c4778Qpp5yCgw46CEIIXHHFFbU0Lr30Uhx11FHYbbfdsM8+++AFL3gBvve97zlxXv3qV0PNFF99nva0p3U/wQHFFl2iVEBYLkqCnUh4qBEVgqIqfj1eFojvA5pvFWmz3sa2h+KqsH7LelTxq9klfVfkUvcsO9ZbohJ1K686ibqFN7iMAekhDo3bNRKoW3YR+N2kmHXVsSaLeh2gL/zQS7/r0jS+/OtFy9qWuZAQGuoyIa2V17cSGeuuidtndtcu4OjETal25FDWumssVnaTyp8EYJYhkVhaLmH0mlGrZfQ6O3mn96uZiMaN59wrnsts5XkRtyI3ya9vTc8XCtlGeaBOpz5zMrjPkBLCKT+zRAtQt/LWJveCtGmkKhVuQ+XtH9OPo367FjQVN27ZleS3se4a65hv1aVzFPjeGPXJpwRpYAr33ozdszTNhDghaBYOTJOw0P5UQlTJVJSkds709kwCpQlTv6Wx7mZQXRHawqtmX9YeMJlAmaunTCnV91IW1iOGujKXEFiBMQCodW31hSnNdwArxBhzElgBAKK63sF1dlFZcI11dwWAOVMfpK6/QrsuyxzIxnY2ZlW3iSeHLPVoXwNcqvakjFf3l8dyhgmQ5w613tL3kDka9coKjdtVaYY9soTz3gGot4K/rY+Ft5ayE4/uj6p+0v0jxegAMbzOYAK4Pgiz+utTn/oUNm7ciKuuugq/9Vu/hQ984AM46aSTcNddd+GAAw6oxb/77rvx7Gc/G6973evwsY99DP/6r/+KM888E4997GNxyimnAAB++ctf4uCDD8aLX/xinHXWWcHj3nrrrXj961+Po446CuPxGOeffz42bNiAu+66C7vssouN97u/+7u45ppr7O8VK1YMXALdxKBLNC3Q7brMy9BKeba0gW0orM09mYZPC3Drjc/hZz6NuS2b2WHNzLA+9Jr/1hWZNOiAugeYcWsyL8om2DX58V/iqbAbq3ehukIty+a4Icil18hArg+49Ho1Lb8Skut+q74ZqLVlLatlTEyYkMJxZ3bKF6hbcBKV3JEQa0gHE5WudRd14I3BLunyIAeud64M+cyJjeOtdTA1gR/9qbNLoS4FeJvy0kWx54Sff2qpptvdZ45bBmmuynU3bqCC3sLe+6Xj8h16Fph8pcBumht36Dq7YaqOhYFXx0iCXVOvzb1KXZhd130DuHR8oex+Txvopb/Jfwu3QZilYcJmgW4XNK4U7m96nEDygIEHVGNzBSD1TD8yg/Lc1d+rHgICvJL8l0CWSchcv3P0Jzfr7eYC0sKucm0uM7fDt9QvhBDwtsGuGbtbSLWCbolMhWnYNW7Q/mPMzvis4yoILXXnZH28bjXbswu+ziNSnVHtXjKxQzP+h2CXvrebhiCFXJnVBXahNu6yXF9+qAvw2nikaH3gbVuDNygBUMuy6otx227GurusJafkJdUxzcsvvxynnXYaXvva1wIArrjiCnzhC1/A+973Plx66aW1+O9///txwAEHWCvtYYcdhq997Wu47LLLLOgeddRROOqoowAAb37zm4PH/fznP+/8vuaaa7DPPvvgjjvuwO/8zu/Y8NnZWaxevbrTOU1TDLpEprO0SX1u06EalkPcXk0NwSj81Bp/4W0pgEvDfDhy/newBPozn8YAt20GWCrHUkEb06hbk9T/MPSa/Q3wGguv06iDa3lsg11TLqHZmIdU3W3XdTH0IdcHWceyK6RzvWLXtEmOtUvScbeZ08Fg4NYv59QxgG1WXYWd9cY0tRz57sdNcalE7S43gKsbK9KFXXOsLs8Y6Zxff5V2PFyz2iamcsI9mDXAa+8pAlK+BSZmaWzMWwu8xay3uVOf69vovm3HdkG0btE259wGu9HjNMBuX8Bti+tfJ/f6tMOuJOmYdENWXVXvzQRy1X0V64RKWgLMAVT/Pvb/E7A14TGwNdtIPLtvIF+CfLE8pAhCDdnX4SKTkJl+1mXq4wBvru/5TAJ5iVLmgCwV3OalnZBvlFfvHykFZvRMymr5IWrhVZmJA6/AjPaECsFuIRXY5qJ0YNcotxNbKdgtNPiWUCBcjYFV4JsJaa25Zt9SmvvQhdvSK+dQnQxNTuW/95Nhl7y71VHSVlPwa0HT+F1/exPwAl48kxaqePQdVIPeiIKQK1xrrj/sh1XXtm3bnN+zs7OYnZ11wubm5nDHHXfUYHTDhg247bbbgunefvvt2LBhgxN24okn4uqrr8b8/DxmZmaC+7Xp4YcfBgA85jGPccJvueUW7LPPPvi1X/s1HHfccfjzP/9z7LPPPr2OMYQYdDtqCn05E6uPFaOpYRza5q+9mQq4QFVmTVbcJgtuE+A2AVPMipTUOPfO17oKGmuFhaW6BdeuA+oBr00LzdZd89I05WDhS+fLvCynJf96dll3NQVwHQtvk6XPU0kaONSCZaC37DHhjbQdCq4Lc2xioF6SXsMhsg0wltlKtClCrbsGdqVuWKjxu+Zkm12ZF3t4Ruz+MzALoAa8fpcQhT+VZh2M0vPjxk0BWLrNDe/npWCBtQXwfdj1zyMV8IeSPyEYzYsKEzW3UB27EXZLUVm9CK5ACuFYdelzMjSsQ20kEX1ZAK0DrZCiEXA7wa33v/oeAGWabx1F6EjSwKwgn1JowJXa4lQdRwGvAHKpx+1nELmElBkybd3NzTYAUhrXeOG4MtswCBTG0ptpN2ZkWJnNAyVQBF4WMdilsm7MgQmqDLxmus6YyakyHdd3YS6krpdkFmZ7HOGDr/DyUdVVf3Kq2qz/qO65EOwCbkd1kyszTdMAb5sF16gz8AKOlbfNwuseq/rubLOQ7ENufQ6Y5Sx1D00nXQDYf//9nfC3ve1tuOCCC5ywBx54AEVRYNWqVU74qlWrsGXLlmD6W7ZsCcYfj8d44IEHsO+++/bIs8TZZ5+N3/7t38bhhx9uw0866SS8+MUvxoEHHoi7774bb33rW/HMZz4Td9xxRw3aF0oMukS0Eb7c1eWhEovbBLdqex1waXgK4Dr/UXd/9bfHrLd1CHYbqUDddTDFmmEa0jkZq1uYF5Z2nwpBrzq2B7xmhmCkwa6bVtVTbJTiOhvb3tUKmGLNpfEo5PqT+gB1WADq18eXadybBnUJ4VlyjeU8q8bpautuBoGxdp5zZq42HQlQsFvoLJiGZVMZBiW976bx4oT7rQf6Iwy+tFkvFeLWLLspGrKx0WccbPMMzNX40xjcxay7PvCqdMLXLWjFDXS4xKy3Ibg1++Rwn09NeVLjxhUo+B4hFPDp+YbKzN4PkfOdZCbmuBU+MOYyAL3+dXTTC8Mu7PNUfTfPGmvBJfet5UMPCqRs5lvotMPhAchtA9wQ3OoTspBbBuI4aXv50NkzllsIfW6lfvZnepspCKlPXH+XUs9HYF40Bn6l0JZdQCADpHJjNuUopYDMhbX0luZ7TutuVll49bhdZECpobuAUJZYKI+bGRSAGKNpzC4Ax4UZEiiQ6zDY8brUhbmUakxugcoSTGdhLmVeg9vOLszmHex1rPmW2xrsknpqjmphV9Zhllp31YVvB1p/acE24DXbkpYm8u/9APj6EzPWIVdvI9DLiuuHP/whdt99d/u7CQyFdzGklLWwtvih8FT90R/9Eb71rW/hS1/6khN+6qmn2u+HH344jjzySBx44IH47Gc/ixe96EW9jjWpGHSJdvQbse3cYpa7voBLw1KtuFnDdt+C2wa3MRfCtsab87Ij+7rQKdRagDHoJVBLgTdkwfBfniEX2/pSNpNbdWOwmzrWkUJuBbXNkFvFKRvHNwaPZyy6Op61LHhlboB3jLw6JwAjlDXYlag6GApSHk0T3rRJ0kYyCOT6ViMbwfvuHMb08sso1NZ2CcjAwtBKTTMUL9Sx4cMsANvIDcEu4LrJUqhrr0/h50Ib4NJ6TcHW/x0UsSIVZlyhNEtjaTdNa7kS1v2SepTQc2xyXU4B3BKiVg5tSvOIcTstANjr2Aa70lAq4LgwW7gNWHWr8YykId/1+WjhMwC51PLaBrj0vwZdUQoCu97+WrRYakZpA7vWmqvzKDTYZmRHCQ28lXXXentIdVJSAy5QWvdj48psyntUPT4V6FoX5gwr8rHdVsiqU3FWW3npBFXGBRrqaPqE1L8Y8BrlQgKy1J1BEoVUw3/UEOS6VVdZc6XtsDQWWt9luUnVPgGoJdu6wG5o3K4qD+8ZZMrJqdtx4LWdnwnAG9oWG8db9zQCQu8ex6grpBOnZtGNpLGcNK2VDEyau+++uwO6Ie29997I87xmvd26dWvNamu0evXqYPzRaIS99tqrc37/+I//GH//93+Pf/mXf8F+++3XGHfffffFgQceiO9///udjzOUGHSJdnTQpWpzR22CW3+7A75e2CRW3BTAbYNb17ISt+5SUeutkQFaoIJadZwKvij0Qr9wKfC2uuslPED9sbrmHEP7pjyQXUtIWt33oclcKx961TIrYcAdwqKbQdhyN2VOy3aEwlp3x2UWhF3aYLFlSxrR0QlvUiSFC7m08Uzi1PdDoEEgKtg132oNmHD5xT022sdb+9c1lk6b/M6T2LWmMKv2M2PwwrBrjk+tLvaYAdALQV1fwKVwm4lqSTGVRrwBb9w2lRuoAtpC6NlhvTVBfXCPWm298C5W3D6wG5K5ptStOnQdAdQsac56pkLWXJhN/fGtuvCeXzX3ZS+OVds9aOL4IKvDLcyWlaXUGAst4JaCfDfxq2yFYNdI6D82awKVidoAr6Ip9cWkE7DumqcGpCpmcw72TSnVjkJWoGSA11hypb4GypWZQq/ArHkHGiuvBt5CKpdmA72FzDAjjLuzXhe9oZpmonJxDll1C6msvb5V1x+ra9IyVtwi9FywzyP3uQK4LsyhiSB9i2wr7Dq/06y7Eqi9p9uAV6k610Yrr9MzG3iXRO4RJ56or5drrLrmHSL9dJebpIiWxcTpJmrFihVYt24dNm/ejBe+8IU2fPPmzXj+858f3Gf9+vW44YYbnLCbbroJRx55ZKfxuVJK/PEf/zE+85nP4JZbbsHatWtb93nwwQfxwx/+sJd79FBi0CWia8D2VZeew2mpzzk0NYab4nW14jr/WyCXuimHAdid/bTNsmuO6ea/3TrhWCXgWhSpNTfTrrTG0huCrzbYtb/tsb1ZggMPxBRADo0rCXms1LLrybfm02scteRq6KWA2zS2kR6HnttIl7Vv0fWBt4SwHQzjEoDMMMrKMOxSSBLuhDeQ9QZOcLkSU74SlTXXaVT7FqJIg9tJUMC2TqsSh7OUUORi+etq+/KXieoi/96k4UMpNuFSzI3ZHD843q7hPKrv4TG4TYBr1/Eka3va/3p90JAKqDpqADeD6gzLpLTAq3pdKtg1BJUy8VRfN+VU2A09L/1Oi9Ds0kGX88hz0T7vJPlOAIFadSn8+pAb6piq3b/ed2vNDUEuBVMSXkEvXAuuBlwLuTReA+RWmW34aKiV0HnOTPeXDi9hO8XUqQkY5DUhgLAu3rbKIdPjdDPrBQ2o59oor8bqGgB2xu3qmZkLZPVxuyUs5AJADjUFlQVewE5OpbZLvc0HVmrVNe9FDbkGeu37QddXMgOzOo7ufSDuy6FnR6yTyXfDD4FsX9h184AqfVsn6kAbAt6mOE1WXpVCvVJGnypOe8D8d12XjTWXujKzJtPZZ5+NV77ylTjyyCOxfv16fPCDH8S9996LM844AwBw3nnn4cc//jGuu+46AMAZZ5yB9773vTj77LPxute9DrfffjuuvvpqfOITn7Bpzs3N4a677rLff/zjH+Ob3/wmdt11Vzz+8Y8HALz+9a/H9ddfj7/7u7/DbrvtZq3Ee+yxB3baaSf8/Oc/xwUXXIBTTjkF++67L37wgx/gLW95C/bee28HyhdaDLpE1KLb1z1hUlCetlIauKFGa6P7ciC8CXJjE065ltq6FTcFcOOW3aqB5p+fcTf0ZcYY+WvpmnF0qhFWd2EuLaSUVRiBr5hrbWiJja4y9bb63xTXNPy6W3XrnRIu5I4ydf1GpuHvffc7MqIun6Y89PkUpHGRIXMAlwLvuMwBAQ24qMGuqRemh9k0fcwszJULXDPg6kSi5eus2QnyG4DTnqAWKL8A/DBZD0u5bjGPFYE0a65/bfwwaqUH2i30Tlq6MKox8dKzDDaP2TVxgOaOn/o5tFtxR1lRA9wZUSAXpf6twNb9X3+m2DGLuuE9L3MLvfPIUQpR9XJp8mjqOPXH5rouzWnPDqcDD1VDnqYzaSeGb6UHsijsuqBSHZvep75VV2igcGddDn+PKrS9CXINrKpsE6AV1XcTTuHWh9xYvjTQCuhHhh6Pa6y5EpV1mFBQHHZFA+yiYucSgJnLXur6pdw11ZhemQuMDOhaq65egki/+yoLr0CRZVgJgVJkmM2EheAVGKOAqCaqAgDSkeNbXTOU9v5RVls143umvSIo5Bq3ZWPdBVQdTDFCZBqC26y6tfG6DbDrpGPPB95vU2Zh667Jg7lOLsA2w2wciuvQq1R/doTgV5UH/S5tmOOyTN4ty991OeFZ0jPdLjr11FPx4IMP4qKLLsL999+Pww8/HDfeeCMOPPBAAMD999+Pe++918Zfu3YtbrzxRpx11lm48sorsWbNGrz73e+2SwsBwH333YenPOUp9vdll12Gyy67DMcddxxuueUWAMD73vc+AMDTn/50Jz/XXHMNXv3qVyPPc3z729/Gddddh5/+9KfYd9998YxnPAOf+tSnsNtuu3U7yQHFoBvRr4oLM9BsjWl1YQ6ETwtyqaW2CXBjyw7RxmdK4y2D68JsxtEBLnC5ywlVcGssvH7vsdEIRRB2YzPJNslhpgDkhjpu1IvU/qpehqiAPhWgTH59S64PuTP6P7WOmX1jHQ46eyiQYYSysiJY+HGBF8iArEApM4yRObBrG87alOG7RkrhWYhQb4tSS1GtdHRDuAa5pvz937X9abhJneSipSrQ60UbISFIpRb5VPn3p0lrCNdXk74Pu7410CgEuyY/rceJWHEBYCYrnPOkcEsB10CuDUepLbtl0KoJACUyzMmRepZAohAKeFEC8zLHTFYAJVAKYS1SpcwRkw+5NRdm31Ll5ctviJu0Uq9namcGdWs2bqQh2M3I+FzjwlyCgC3gWHVNh5RE1aAXQtjxhwaCASB4M/sKAWgMcg0AW9ANWHFL91ODZrhtf3u5RPVb2I4P2HmaKOyayahMmsa7xAK+FBClebZX4AupTYkGfEk+SpgxvOpZKaVATiy55h0RcmWuLLxVnaRjd9WnWoIoR6Ytt+7z3/dgoBZfPzzkvgwYCIX+HndfDr1rY1bdkAtzG+yaqtfXuusDr7lcXYDXlw+9TfFNh7gbJmtxTHjImquqw69Ou3raOvPMM3HmmWcGt1177bW1sOOOOw5f//rXo+kddNBBkC3E3bZ9p512whe+8IXGOIshBl0i3yIxTaX2uA+hrucUdncMA66/rQly/fSbIDdsMfTdXeuAG4PbUD4awcqTmQwDMBBYWPCtWRmDcBuGXdqwA1wrhm/Ralvyhr6IzPPIfzn5L0SAAm/1m8YvIZEHDl2zsnuWXeOuPBKlAw8GHHzYNeMa/Ua2aWzMoHDGNFbuni7wolQ95PNQDzgKu+a3aUSrDoqqfK3V07MaRZcuiZS/CjCfgFWXxvElaDxZD+vQ+UB3DW3zw5usuaHlc0L3fnhGXnOPKEtMIUUni6+TltcANcdMce2l+WtzVXYANyss0Fafsf2/glh2DexSlVCW2wICM1J5gMzLAvMyV66bGmbmtVUqg0Su1wZVDfgKaOkkbCbMfm95RsTAt255IhN8OY3s5rWTY4Ac6rwwsOvmJ+DCHPC+qO5V2A4pep/WGuYJkCuc+7I+LrcNckWBuhU3ALoVNAfyQEBXGotuqUHDTEbswa5Js+6uXEGyeZQIDcKi1PO2G7IC6bjT+SozAEWmQbdK00zIM8oLC7tBV2aZqU82j0K/F2fFGEUm7KzM1LprgZfIWHF9qWdIXk1Mhbr7clWn651Fvvty2/PE72QDqufQkLCr0g1bdwG48XU+UoBX/U7puI4/P9r2DY3LFag6VXcEi26jF8ak6bKmJgZdophrX5v6uDkvFFC3qe18mwDX394GuaExuV0hN2bZjbnBtllzmyaNcc6T9GSZl6I/ayoEXSYk7FY7X+YO7Lrr/ekxaLKyYtBxuXTcaExSihrkhmDXlw+7EGYm2PZ6GgKeTEjHkktdQEdZWZvAJwa5VLbxLUyDXzWU52VugXdcKqtYIZV1JQS7GYR1Y3ZmyiaNfWotSlpTl0CstebSbbEwVA1sO1GHqR/G6mKuO70WXodJqmpLhqF+/drTCN27LuTGZjyPaZIlcLqoC+SOstIF20yB7Uoxr/5n8xZyZ8QYM1DW3hxuh4BxVTYuyoWcx6NyBrlUMOv4M5YVuJZCu0ga8AjUQ2pJi8WJl4XbeKcNc5N2F0t945hoVGn6sFuvy+qZ2OR9Qa26knRIWWuulhDa6dIvlybwdeDWgGl4TG4Qcn24JfBbpSmjnVxSz6hs4VbvJswuNH/m8SB1PPOckdKGA9raDLL+NsgiZSHY1V/KTEBICSmVK3OeAzIzy7kBeVZZ02OuzGYJIt+V2UxSVUpl3bVjdr1nUSGF7SjqIvXs1t9JZ1FX+e8GB1IDnW4AOsGuyp+Sb90FADMzs4zF198p8PrqB73pom7L5jd1Wc6Eea8ujXYv61dLDLoDaDHdnNvcSfoo1uidFHJpXGdfArlOnAjk1l2Xm11h2yyGbbBbSAWwgGmo6TzSZUGMhdEDXiAH7TmeyQoHdlXe3IZdIevgFYMtM+GF6WWnkJsyTrfukqSbQsJ9ucoES6LtqDDX00KDmaCnglxj4e0yiY863/BEPvMyV50RGapy126gFHYzIa0VPRPKUkGtuhJ1a5Eqp7o1t1a+NOsUbink2oauqO0jtAlHmhat04KBG5Yo15XZLdvYfd5kzQ3fu/0gdxKrrlFs4qrgeXn3Oc17G+SuzOYxm2nAFXNYmc1jpZi3kLtSzCOHHrvrnXchhB2TOy9HmNNrgz6qCdZ0mBUaALKGG5Zacx13UVndH1Shcbd0a1U24Q4fe591sOo2yebD1uM47NIZ7Y33hXk2+vep65EBCLPmrH/awhBh5EaSVTT7n8KtjpMEuQWx4tr/0km3yld1eKGfTxIC9FEgyfHt45jCb+iUDDBbWJceDAttrdWRJICSuHtbEM5QGhfmvIS0gFtqa26BcZlhnGcosgxjmWGcjTHOM8zLDLNZjtlsbOvqbDa29X5GFCig1tpVbsfmPV3amtAkMztzaJwuVZdxuqEOo1g43Ra0/DbALuDDrQvAIXfmEPCadIwo9Ppzb4Rcliv1ex4HZ1s2/8lnuWPutJcXYk1HDLpEfcas9dVQrsvTBFt7jJZ9fMitxUW1PQSzfrqpkNu0lmUMbvvArjM5i7Hmavgt9ROezppKgXeknJ4day6F3epl5/Xyymo5jZhiD8cQ9MbTMNfNhV0DtqUUGsCq733ghF4bA7lmvKM/mY+K71rEZqBhVxTWQjZfjlwXS+LeqeTCbqbLdJQVGJfavU3XJd/1jDaEm4w/VTkS6KVwG4Ncv6FLJCDqsDuwYsMTUp9/9B5Vv+OQ25RmE+wmWdIT1bS0mNsp40LuSg23sxpsd8m2W8hVlt0xVooxZkSJGT02l4JuYdw4ITCPEnOiQCZnlCU3A4pSaBDOkEvzfNPPLwkCtFn1XwqMyVIudlIq2xkUtvyqcyXPMj2u0cRwy4TcEwHYTSvzelwL0agmFQvBLh2/azuiIGtWXTN5nBTeeFzozilRdSDRpcJqojv6nVD0fqXQq8fkWvClAFzAdVcupbuvXzQGXml29IPHcrmswvxng5Dm2UMAuOH5QePbtErbg+vArpSAyNQnK4GxzJBlUll3pUBRyk7WXTorc1kK1YEE9VyfEWN1L6CsuS3H3JibRMfrpqjm5RCw2MasujWgJfUtBLtA3bpbm3xKeNbdCPCGJq0y6dcht+ke7v7M9TtTTQq+Ndd0ULFYCy0GXSKBydqVXW7ihQLqSdQGuKHfNCzzHoDxNMgERj0gNwa4IZdY+9sD25gl0Y9LlzoBKhdaA7014IUaKwqZeYCrmm7OxFne8ht0EhZf7njcCmzDll26o+l6dZqENeCtZixVL9pSVuN0JWChtxQiqRlBr5O5Lv6stWb5CXsNdePb9PyXUuixXhIZBPJMWuDNRWkn9bFLtJhUhMSMGrgLlMayqyxG1Krrj4mmbpFR0W21BrL7na656TSigVrL17oV+lZdmM6JeJa6yjRI/LCYNdfvoOoLuUaTAG3XfaMuy8J9jlAr7koxj5XZPHbOtlewK+axUoyxUhQactX9kQH2flCGPokCEvPEZFfq9Z1zSKwQBebFSIEvEbXSFvq7+e9Dru++TNMwoo1g+ruqX/48sJVCsNs21jrqLUDy0QS7IU+XkPcFnTzOhClrbsc1r33R+9YApAkvq3vZgi397o/JLWXSkkK2Q80+EvQcyj7kun2SjY0WC7T0u03Ls+qa9EvhwK72pFZ1NxM2ISkFskwiy5RzbVlKa90tpcA405BLPQ9Q1WNr2ZWZHRpQQCjoDXTMAOQdQDwXUsfmq/Tik7s1WWy7KgV2garI7X2h93fA1QlT37sCr9XA7c7QXBDmfWIg11p0sTzava3aAU7hV00MugNqqLbnYt5HTefQBLm+y7KNE2n0+g1oP92+kOuvawnAWg0BF2gdK08T6JJSMeNlzL5mDV21zXOn1U3eGRTO+NH5MscMyppLrXHXoy569IUYksOwHvCqMFiYchp+Jl2hXdks5Kr/ZQlkhBcFSbfUMTPTAC8zU1AK7oVugOsGcSmksmtr8C+FwIy9jhXkmuvoT+ZjljMvhZ7QR6iGfiEyNZlPplyXASAz381MpTpf86WeuITWKdNw1mElaSzHACrYgPY7EmTov/8RbptDCn1JSCBt+ZrIXsO2D/SGvDHsb4Sg14Vcum8fyK2W7mh3f3UbtM0n2qXBS2XqQzUWl7gsE8jdJduOXcSchdxZUWClKDEjFNzmQjg2pxxAYcaXSgW86rmn63egeIxrPgDboC+lcv8cl7mF3HGZ11yX/XpJ3ZZpfRbkuWKuaWWRMlbegIW3p2U3WOZeh54KU7Drpq+eidW43LrVjE4aJ2yYAV4oS646cXUribR3rCDPTgCu5VZWIGvCjfsynPAA5IYOTq23cG99E1Drc2uCXA2xoe0WeKl12OZJB1LYNaxtksyAUrhjd6UUKPXY3aIUKPISM3mhLL4ywzjLMM4KArqmbqvZmctMoCyrsbvWywfVUl10eS6jvuNuu6oNgn2rLt0nBrtABaOm+B2vIlTgGnJnVvuHgVflyVUQfD1N4iFozsmHXOfdsSOALmvZiUGXqIvrXh+l9hZOG5j7pJ9iyU3Z3hTuW4qq8DrkmhlRY4BLLbe+O2zIPbZpBuaMvDIs6Fo32aqxb6DXWc9SW3eNwYLCbq4blBl5mZlGd1lr1dRl6pNrwSW/6fZIGnbGUr2vOlXVCjJjt6SQGmbVSeRZCSkkxgRwq+IboZSFXVrCbMsgFQhrwLQwDIncLjNRYkaMtfuna3lXjZsChchUQ0moZVpylJjXj7FMlJgvySPNg92yUBPgmPIOWXWl14A24/+UZcOzjjsFSawlpggJ5FprbkkA10tLNXiqFq+Qwp2gSoqpNhTqEFu/HwHXGgq4S3r56TSpC5jSZ2c1fKDfk5J6URhrrl0nNyswK8aVNTcAuTtn88qSC4kZAawwwxdofqEgt4Bak7mAdl+WmR6rm9sJqtQMzNVvs72UKv6YQO64zDDW28ZlZt1EaRk1jSN0zl8DcEk6KVVjlLo1e89FQbxZImN1Qx47vsxyUQAssNmx1tZ8CueZCMStumbyOCertvMuIA3Alnopbfgy2SGdVL7LsoVdAsHGXdmH3NDtQaHWQCWgrbpCOJBr0upc/b1niE1T6meNc3ANu6pHE7IknQR6P5EBQuaQpUSZlcgyCZnDdroY4B2XGcpRZdFVlt6x48o8Iws7brcQGWaysfXc8cfo0vkanPCeHV0xhcb8+1bZUMdnKuw62/W+Eq7XQ8ydGYgDr9nm/55m25aOzVXnVUEuteYu98moeIzu8hSDLlFX0O3q5tLnQTOJK80Qt05KnlOnnW9LMzbZVB/IbRr36U9SRcNi+TKqJsow4+JkDXrny5HKo7buGsilsJuJ0uCZY2X0J8ug8GXzQOLQmZUdt2XzHSDAWz83086zTcJSN2KEypu6dvq/hl3TE28amqZXfmQsTJlAKUtraSqyaiIvfcq2LDJRWostvRZ0qRaVUbW0kLKOC8zLETINuQqey7olF7Az12ZSjc1FqSzDIatukpknRQZwAduIdCCXArEnC7vUlTB0I0vqbl5v2KSIJtto5aW98gNBbqpq7rgRyO1qzaXQ53iFQDqzK9c/YzUWF5Urf6FvrALGXVnBbQnoSaiURXYOCmIflTPqU67Q31dgXo6wvZzBdjnCvMyxvRxheznCXDnC9mKEscwwp/8bLwpq0ZWy7rrsq9DnXcD1wMkgHeilwKtcmqvnZWnNe1UZGvfl0CzNMau90zlo7j3zAAq4MDsTU+ljpHRKBcfpdngz+oBKP+ZUfYutY+mNQS4tJmOtBUCJhzJnaAjDRPLTobDvHBgaeFWngNS9ojXgRQZZwrozl5lATpYdkgCKLLO/SykwzrPKwpuRd4e27pp7MeRFBejOIzI5oRG9D/xxvX29PlIUm4HZKOZe7Ft3gQp4Q9ZdGzcAvGpbM/RSUcDqY82tt+2qcAO5mfedxVpoMehOoElu2lSAnSZ49z3uEA+r0Li/+nZjdau7K1sLjJnQKAK4FG7NMQzU0gmo/HUvqWaAqldZoAIuZChR6omS3LGj89oiUioTiJ0RmEJvNUFS3MoYe3FSKy214oYgl1oaaz2Hpty1W5+EaRQqq4mZeTjLSkghqt7sUr248kxZeEWZqeWEshJ5Vqq1c3NliVqRjzEuc8zm42p8Fn0zG8OwkBZ66Xqk5jrN6LLP9fjGQgjksnJbdtIrFRTNaGsxMmjXOGW1U9bdqrzN8R335WiN0GVJyh72YzaICnIDrou0oazKn/wUVbxaY9SkTe8X8pvOkk3/p8p1favun5DqkzqlHafPc4reBxRyUxuureu/6nphXJaNNddMPGXCLdyZzgiTJwLg89r91sy0rP6PMCdzzEPNvPxoaWBX/d9ezuCX5Qo8Ws7gkWLGgdy5MsdcOcK4zFCUmYVdqa26AGyHkxGdLdw/T0G+SwK+BnqllA7wZhC6Q4gMM7EcVC/XLq7NxmoWg13bIeHNlG6XXxOuVddMShV0X6YmUWFOoq5oZxSFVA9inf9QllgaNwq55jeFXZq1aUCuc2xq4dVWXXN8CrvVyyEMvKWAyKTqMikV6Cp35gxFWVrrrh1jTiaoms9yjDP9fiDW3VyUFnhz8pw2opBL/1fbuxVWfYx7fygOWW2N2qy7QHV7xcG2Hl5to+cQBtjQ8yH1PeEvUefvb/Jm7s/c6Txb5qAbei4MlS5ramLQJbLjfSZQqgvCNBqFC9FbNnUA1tbc+ndZW4PVh1w6sRF1RwRgx34CFdTShnqTRVepsL3Ddn9kFnwV1JbINPCa/BvrbnWC0FZFgRwKvEJjR1NVG5dbs+yacLODW5/sT90YBETVS1/ol6iQKMucNB6JBSUrIZAjz0rkmcRYg24uJObKHCuyAmOZYUU2Do7PsuWfKatsjpG2EpZ63GM1VguAXm8xs1bdHMYSp/al5VyWqpOhKDPkssRIKGtwJgVGWaEaUaKy6tpJqUwSpPHcyU/QaxArK4/wrD1+etZpWTd4VQvSWf4jdH85DeFInBZVS1UQyBXud9+a64/JTbn3Y9bZVLVZcdtcdn1Rt2UzAZWx5q4QY7U2rhjrOlhquNXWI51kAVFZljTQ1v5rd+RCW3TntNVWWW4V7BoL7nb7PcejxQzGZYa5coT5QrkuF6WGaM+Sa947seVTqKXFlIm1uoB4jpBr7bhGeNbdKgwwD7W22dhD2816ujHYDU7WZ/PXbtU1YdLcP7pDz+Y/oQoKwH1++vc3/U7Cgu16ss0G+VZbuBZeIc0s+O15dRJIVRNAO7CrM2QeUjDAq8u2FGrZoUyqPJcCWV5C5qZT0J1UrchcrwTfujvKSuXGLNTY3iwAnqFnSIEs+KwZchb3FPkQC1TPKB92zbYm664NDwCvv63aXs9XDH5jAGvy23auNK6FXbjPmuVPdIkPjV7psqYlBt2B1QWUU6C4rQE5pBV3sRVynzRWpSZL7kw2tnCr1rGs4lK4NQ0tf/xn00RUVMqKKzAjyJhRjbY5Mv1dEvdmBVq1nmHSXjTgZay69PxD7rQGYk3j1p9puQa5pbBQRcftViJwJKrvsjSQK+wmiGptPFjoVUtNFJlybx5lJTINvTN5YS1Q4yzDWBbVpCS5CINOBuRST0CiOwioVTeHVHPWSmVBnmuY87k065OKzALvjChRikzDc/VCpuXt98DrUvIuhNdhYBu5OlyCLCNUh1z/tjaYK0xapn1pPoKkr9fCFKSB6vBuddl6qcmN2YmXCLmh8bVA/zG2qYBLt1M32yDEa3iylltUQx4KmWFeLxRmjm/H0yLXIEvB1oBupsfaZtaya77PyxzzZW6/z5UjzJc5tmvr7VxRWXHny1zdR6Uaz1vosblFSQFX3+OB8zelQy0t/mQx1PpigLcUAiNRWvgdZSV8V+ZaWQfcl4Ew5JpwCrsA7BjdUlbfqQuz6ZSCgOOBEbLq2rPXYZbTCK/WZ3mKiIKrjISbbd7p0ja+XxTmN73NYXJusiarNGQg/aACj/qonAeIF5/Crt0m3DjmNaMnsTLAW0o9yVSZocxLFGVZAa8GXTVmd97tCM3GKKBWMiiF0HXTnWDSsd4aq26tM0zU378N6tOecqAVrheW/y5xrLYEWP1tXYDXpNEEve5xms/FV9PzPTYszQCu474M2WpOYLGmIQZdopALbV+lPDDboHgSEF4MAJ5kNk7HmmRfZlVDmn7M0jQUcitrroLcFWLsWG7NuE+gcoutjuc+fv01dekL1box6zGjBnKBAnPIK+AVyqU2RzX7Mi0nM3aUglflLmgalNWYOqBeH1zABWSZ6Z5zA7hA5bosgg0wJd1IFvo7gSfr1mYbNFK7rOn/mX6ZZdKOzcqyDKNMNWjyTI/VJeO1YrLXHQqWM2lcl3WnBYyrMQFeDcG5HFWdBwZI9CzNM0Itd5Gj1I0m4ipu0ySNDQ8IWntba41cUoCkgepALgVYmAaublDK9LY3EAfbLsBLgb8Ko/dI3ZrbprYJpCYdLxd6xtXWvIQkcbPaOQFwnin+GrgGWB+VM8qTgFhuqXXWAViZWyuucmHWLpr6t1kSaL4kE06VOebK3P4vysz+n9cuywZsC3uf12dZj8lYNqvvlSU3y0oLvWVm5j3QE8dkppzUpEIUdul43VSrrnNN9LWisAtijTO/TecTAHemdEks0QGrbhXmui8LQZbtMfc3KT7HeBqA09j32u8AFAdB2WyDB7u0syt0eRNuw07NAAnYNbzbErLAawqoepBJCQd4kQvlzlyS8bqlgByp57KdqEqOHZfmkcyUdVeDLh064HaYecvPGZBG+PnSZt0NPle8DqVJ1ObKTI/TBrx2WwP0huI05Y0qtk+oned3qDmQa+/NYdrXi6bUTqY+6bKmJgZdohDo9n2w9XHl89X0UGhr2AR72xfJ+ttlnCB1Wzb/7ZhakLVXUU0aE1qeprLsunBbwW9guaFIf6NxPa5mf6wsu4XMLFAZq4QBXrVPIE3jvqyBtxozWiITWWuHizs+V1Quy1CAayDXWnNLVKALdHyoUgiGbRzKTEGu66qmZt2ULa7X/rmFJrDJpARK5dKcC2PBrWZnVtdSdRDYhqAdm6vW4y1FhkJPbDKTKet7occSlxraLPAS92WTR9MYcmeUrCxE0caf+U46GISB3LKKZy02pGglzLIdZl/PfVlKJ106IRUQhtumqxGrZxQCu3ZeNQFuSRqlzj7UCtLjrR9zg6ZL7IRk3JadCeekwDxGKMsMj+oBCdVsyCMHaH3LrBqDmDsQa5dRoW6aBHjH1h05s+NwKdyW2pJblhmkhP3vrJFNyrP2vCWdVf7wgyxT9SvXv82+pR5+UOrOKmTVfW1gd1zq7xrI3LGBVWObwm+oQ7NaS1f9MnAbc2E2Vt1SpxGy6qr5BQzkhtyXpU6/gnUpJNoXYOmoULWTqAGyierArqyeETDuy15DW8jm+1tFot873FsxwHbi0F5RLXMJ1dTYaj6HXM1gYZeoy1VHaJHrNXhNRyi5R2a1B8Q4KzAy69QLM2mjm7HK26KCXHqPVUNm3I42c1/G1HV4RUih/IZcmQF0Al6gbuWlaYXSa1PbxKGx0gh5ATlLC0H2epewWEOIQbdFfW/MFKhsSrsrBPex/g4FvrRhZScrmsC6a+S7ltoHJrHkUsg1VtxcqLAQ3NoZmBuAN65C/xVqAirtPgs9E7BxccxE6cwKHExJKOtIUWYWsow7LT13f8kMMwYvtKQQtdrKUqhedYnqv98o8dIWtD74xSFUQ1D7LuveeqjWba7WBC1zfSwAQggUQkCUAkIIa4EyDfsMubZ6Z8hKVWZZqS1rpZ7VNivxqJTKlVkYC66SuvYFCmOh042yQmTEoqvHT+qOCAM1ZqxuLjLbSAYq67n/3ykGCrshGYg1jQ4LvNV3QeJBFyfldUniS7K/49dYO64q44lmYSblQP+H5IOhrxDgWqsImq0j1bqqXqPLO/ko3DY0KjMRd6+txtIKPCpnbL4p1D5aqnGz8zK3QDuWmf0/LjO7xq2B1tjsyKW+ZjScgq2UxO2zFI7XRuskc1rG80J9B+zwg6zUY+ylBltl2S1KqOXDpIDU4+1RVt4lpt/OwG5JOoZK49Yswh0Lsc6GOvC6sOu7MJvnpTpvWbPqmvOmk1JBQ64wnYS0484psEi4H63rq43e/7HnLzzYNcZz+gwgx294FARHqDT+DuS38XmDhm3WL7x6T8gyhyhLSG3dNV5I6r7Q94AezmJmZS6hXeelUB2Wen3dGVGQteddUcjtoq4TUdH4teWFUJ9EMgS7ofAuwAtUl5ECL81j13dAE9iGyjtmAXbabSDzAQzcj7Tg8u7DQdNlTU2LCrrve9/78L73vQ8/+MEPAABPfOIT8Wd/9mc46aSTAKiX2IUXXogPfvCDeOihh3D00UfjyiuvxBOf+ESbxvbt23HuuefiE5/4BB555BEcf/zxuOqqq7Dffvt1zo+BKKq+PXptkNf2IO5qkZ0EfLu8FGIAG2tY00alcxyBiGNRoIErKkstdTFU4+nGdryuseJW43eruEHY9ZYbMmqCXgu5MC6xypXRjBk1Y4eMy3IuFKgZC6VNR1Qw5lp1672efrna8XiyckuWUD3o1qJrP3AA2I4bBdyHtiQutYD74BXmoxoupg1qIko9wYuwMF29rOmYYuejG//jUpXRWObIpFTWMZHjUTlSk1PJEo+WM8q9Eu6SQ9bFW4xtngsx1uMn9bguadxty5pVt5rNO7OWIqFbkMaiq2BXRBsqVTEEOgkcwBUu5NLy1Y1KW3IyYtW1VCPgjNP12Dt2L6oJbYZ5o8ZgkQIutd5SuG1zA3TBlIBUy7M4Cs5SWPgqiWcAoO5jO5YWAvNFbs/DWGq3lyOMZY7txci6GdM1belsyP5YWuNubMfVo3o2V/9hfxu4dYYieB4azlAEoAE4Kt4wY+rt0INMzZJbFgp6s0wiy9TSMCqP0gJIqYcfjLRll8LuuMzVxG4Wbtzyjak+U3O1BrkPu9Sl2bjP+8sNUatueFIqAvrWotsCvSYsUL4T30oS1czMJMxOlmWesfQeN+v5aMgNwq7wvtPnwlCQoQ9qO0ZD5WA6RqWo3JilmpEZoxISua7n1T1B3xPjLEMpx1ih19udhUCpV1Uo7fM6fAHouFzfmhuz7lb7BTrtBiq4WHsrFB4DXhOv5rpM0jNb+hoaYnDb1i4JxaWQy2ItlhYVdPfbbz+84x3vwOMf/3gAwEc+8hE8//nPxze+8Q088YlPxKZNm3D55Zfj2muvxaGHHoqLL74YJ5xwAr73ve9ht912AwBs3LgRN9xwAz75yU9ir732wjnnnIPnPve5uOOOO5Dn8YlqUjWkG52TbuTGb3qodrHI+g/KlLykPtD93kUj6/YmXauumjExBGwZMlGtsUrLms6I6ltzTa+uD7nGilvNlCpd2CVg67gsd7DqmuVv7KL10BPTiMxC7zxGdtzoHF36xpmESll6ZrRLlpl11AEvkUXrn7turoJb878GuSWcZW78caKqXRlZ41U3lqQFXN3yM1aSLF5mTWNyKPACBoyEtZxlpcS8KCzkzsiRnf1W2YP1RFUEdgsIrDAjd0WGEuOoVdd6C0i430U187K5GzJddO3WXA92SUPQKVv6WxejU+SlLmch61ZdiIqMYnkgZd7HsgvUQSTY8RYoixDg0g4OFZ5F91cwWj9+U15CDVY/PoXdQgpkUG7F5n4cw6zNqUBWwW1ml/ehcCulCELtuCCzIheZtsYqOC2lsPWhdvkI6Nrf5l6W1W/nO9kvBhruf7WerHoQq/tZmI/M9ZIwFfCWmUQuBaRU1l3khbXs+rBrry0pX2rVNevsVtejfm3tzMvEGqbCcgu+mUlXW3XNd9+qq777Sw157svmvx1bqqHMdAaYnidTxORn6Lv/37kU5DpVVt2KUs2h1eVS44fN8GTQ+z92re2BwsE+zLe95oU0M817acYA139nmHQMtAtyDnpGZWPdtasEjAq3Q5S4MpsZ+0e6s9IAL+2sNPKfLT7k+jLPp5D8+AsFvHRbkxtyqB3mQ6/dtyE/fvwY3IpIeG0ffTRq3aWfZS2ZcAP1TZc1NS0q6J588snO7z//8z/H+973Pnz5y1/GE57wBFxxxRU4//zz8aIXvQiAAuFVq1bh+uuvx+mnn46HH34YV199NT760Y/iWc96FgDgYx/7GPbff3/cfPPNOPHEE4PH3b59O7Zv325/b9u2DYDbME9dJiikJjhug+AuMBt6MPoa4nxiCj1oY7BrttEmThcXZ2PJNeNy7bq6BHJXENjNUGIFmaAKgAe70vlP85ACvBXoltUSIxp61URJogJtkl6pG1Zm7GghKOCWyBvg1kiCWoGqnn/YMbke5Jbkv4QdJ2p/q3ZkcJIk5Z6s09KAG61KQlrLEXVRCvXo0peev+TQfJljJi+qybxkUbkwQ+o1dM1yI6WFXTOW2nQ8FMhQCDUjrrHqVi/cqrzHJj+mLqB6Djj/beOj6eJ4GwmkCKAqf7ONFJ3MKgOSuSbStJ6tGaeerjQVwmtkp0JuU6+9Eb1PfXAJjb+NjUf1rSahZ4i6Fqbjq3TC/byE0or9BhTQjqDWsEYJjJEjK0e6kyVzZjymS/qMiTuxsdQaqDXuxUUhII2bcSkgCxEfPtAmC0QUcKv9nY6SkMx9KnTFM+tka9CtZsYFRCaBTEJkanmYMiuR57IaDq4fNjIrq0PSlYb091FW6vebsuqq8vcmABP16wmYa2qGIZhl24TtgIKAMyt6aLkhY9UNLzVUWXIVyKGCWqELjF4aCrnkpwXZSNzgb/iwK2udXXa7zpPM3OtuO7xQhUUlyHNaeOFEtn40ydvsQK6Tn/pM8vQYQr+XZC71MysDpBqaYzyTjMsytfICKnxUlta6W2QFZoSw8yzADiGq5A+ZaANf9znS3225i5oMDE1WXnPcUPsv1n5sy2UMXGNwGwJbP5+O+zJ5v7JYC60lM0a3KAr8n//zf/CLX/wC69evx913340tW7Zgw4YNNs7s7CyOO+443HbbbTj99NNxxx13YH5+3omzZs0aHH744bjtttuioHvppZfiwgsvbMxPHytIkvU0cLM3wW8q+LZZZVOAt9U9MyL/IRuCXdrDb/eDUG2kBtg1bsvGmluNyzVrXRZYKeatFXcGhQO41Zq6sga11XhdArmJwGtAVwGuAd0yDLqiBErtIq0bhdbKKDLrvjwWuTNpQ+jaS+clC9vDaN2YS1jIFYUG3lJZCAT9buDWfoTbeDE98ZmaYAq5qTsenQHV5Db0u/3trtVZe6EGyti4kmalrIBXlpiTOTJlr9XX1HWRzKEmDjLuzWpsb4kZMVbp6XCTj8oiYBrQyopuxuca92VqyXUAHpH2Jmmc0gaua9Fx40sBOyZPCHptK6uudV+2wBOvn/6kVKUHp31V6s6F2ORSlUt6VoNbU39DY3Spq1tJ6v8IFRzFALeex2bgnZM5MpFhTm8zLsjbx8p6O18od+T5IlPjY0nezWRQBmbLMlNDBoqsAtsi3MFUu+6Ic68DsjI8rCBWAtJsFNDDCvR4enUT6uEHwkKvzBXoIpcoMoksF4AsUWb6nHPtuuw7SOlnmfLaUeN1jQuzb9X1FWtYW+A1vT4BF+Zq7gZ3uSFj1TX/6RrY1XNJw64wY9oJEEooK7C+cUy4BVtT4PR/6Hvk4riwi3B9MLuWBK+Fuf8J7HqSft6cA1fbK8BvzmujvGdXbSZ5+OCu7gOpJz5TQ7npWF3jLi9skqUESjMrMwTKrHCsu6VwO4bLwLONPpMABF2W/aEUvkW4bZhFSF2HuzUZLGLbmlybadwuFtQ2620MbttguAmKl5tkwz04abqs6WnRQffb3/421q9fj0cffRS77rorPvOZz+AJT3gCbrvtNgDAqlWrnPirVq3CPffcAwDYsmULVqxYgT333LMWZ8uWLdFjnnfeeTj77LPt723btmH//fef+FxicNw6Q3IAAKNxWxp6KcA7DesuPWZGjlHCcx2U1EajmiqZqF5oxq2QyoKpfrkpq23pQO4K6spsxulquFWw7EJttaYufQhDb3PPK9S/a2wbhf5fQq2JOy/VWq3zepxupoFLNQpXWCtjod1rC5FhXqiJmUaiwLzInXOOjbV03ZZB3JV1q0YDr7CNbvXdAm6hGuDqP5zZgG3DKFM/pO+eTBtLGawFobKk0GUFqnMQBCzpRGOOdRAZRrqGlBDWqptJiaws7SzMuVST3qywgKoax4UoMYOxteoqqFEdI/NCjQP23ZcN4JpyN+N0ze+CnLYtAtFsVHGKS8Jac6tGbmUBUbeGtJZcqdv2pvHouC5bipF2m383T7qOLmCAtvDCTMdVGG59662ZTdifTZVOyGSU0TpDLLkKnBRRhRpRMagNukdLN55Zo3a+yJUVd6y+G7djZ0gAoDqU6Dj4orrnRKHvJfNfdyhZTwnzn6gRTkieK0DSnS0+aJA0qjSlvYelEPo/rIdGNZGctLPjylIBb6lnTxfGqisFcj07rpQCo5w0/nOoOfpy2Ae7cmd2rbpN43ZzlHYCucrLpw67ua4XZqZ0AO5yQxp4FFtVVt3qt37/CcB4nkgDYh74SQu4srrZBflNylvQ69hy3wndcQUJ69nhXE9BTluPyU1tBIdg1j4u6P9gxtrTr01WGIBcQcJtsuYBWKp6CLU+nL6nMjse3JwrHcPuLkGkvq+QY7WMncgwss/++FrNsQnxYt4gTZA7lDU3pibDRptrM81TXxfhJsDtAreh/ZqGo7BY09Sig+7/+l//C9/85jfx05/+FJ/+9Kfxqle9CrfeeqvdLrwWm5SyFuarLc7s7CxmZ2dr4V3HEKT28kUnhokoBXzb3Jb7WGfb4rdtD40d8d2VKewqS4BIcl82kGvAVUHt2IHclWLeWnvV/9IB2wp2TZok7ybMOaaobXfKQ59PIRUMlZCYQYF5bc2tXJfLKpGy+m+Wv5mROUohNPCWFrzoEi++7PqZ5LtqBwoCuNV3Uej2Bm2ME8i1DRQCudLk2T88BV0DuZm0jUc7n0pWEuCt3Aqt6yHoy9SdGKxa/zbTHQg5cowcF2ZTL0BczXKUahIwY9UVejIwawEIuy9Ty67Jl7HoWvhF1YB2WoakHJpajLQRaL+bcONaCgnhj82zDUdZNbh92DENRYQbPzTMt+76ltIgRJqv0n0eNQFuoRuWBbWKou6Z4Fv9zXI2QBl8NviNqTrs1t2kzTGNK/J8mWG+yDE/VoA7HivAlYUIT/pk7y31WxQKdEUJiDHpMIp0INHrTcvTyXqo6nj3XtNjkoKzmSDOWHJlhmqcfS4s9CpvDfVQpsArS+HMkluWAnmuZsY1HWyjXMNrAHbNM24mK5xxu2a4gRFdOg6AXYPch10687KBWkB3cnlWXeOubKy6lfuycJ5PtFOgep4JEma+mzIF4H2ErMJNmg740uvoAaGqE+4FFRDa+gnn+SD9+hNREHb18ykUlmrZjU08VYPcUtTruikcAX0hRWWhzqGfdRlKlJAyBx23C8Cuva7G7SrYHUk1e74BXmrVDY3ZVd/r3iTuM2Jyl+UhliOiirXzoi7KHduaofhNlljfLbnxOzUi0Akkl7MS78Ne6bKmpkUH3RUrVtjJqI488kh89atfxV/91V/hTW96EwBltd13331t/K1bt1or7+rVqzE3N4eHHnrIsepu3boVxxxzzNTz3gRnbVDYZZZkuvxCLB9dYLerVTcVmKNWZrPdZkDDru1drdzeSpkB2jVypJPLNbCaiaZWaLg1H2PVXWkno1LxV4jSgVr6GksB2hwG2EUtDKisuaohJlFAYh4SM5CYR4F5UWJGZniUPsWM67IQmM3UWD9jbVQzS1OX2rJWx5zrJgVpiOtGOKBdJn0LE5CNXcjNFJ1XoIsKconRsBJtEOrfQkOuaSP61tyQ23JTTzFVoSensWN1kdtZmM2FyiEBfd2ra2SWIiqr2bqlmZysmrXZF7U0FxLW/Vptc++nymIkAmXk3QfBBm7121xSoeP6gGvG9MUmMVoI+W6AvrvfmEItyNI6UjhjW0vpWmzMczDPFOCa5WzUtXAbdqGxXnXobl6bdqwtt+Miw/zcCMU4QznOgHGmLLROB4QLubZTSHtJZKazyO84oveWhOstYUTASdJ7CuR7l+tNITcjaRvrrQBkJizcmiEJshAafjUAGwtvISBH0GtjS9e6bZZ/kai+a+gt6WK6pGNvpK9Wa4emeUsIM8tyNRbf9L6Z9a+h70nfqmvuU8fDxPmN6t7VYBqCWAcKoW9rC4jCKXPHCgzV0SAiF6y6/6U7tEHoji5jig3d80SS5M3veIxac0OQ2/J6dyy5Jq/mneOdk/Ns8/cBYKzjwqwLXAJyBNKx5C7ppjpViuqwUmAG2sqbCZS6E3OUVZ3aWaAdErPSxjxAYvGaNDTk+kq19vrbus7TQH+nAG6Ta3JsTP6ylXPTDZwua2padND1JaXE9u3bsXbtWqxevRqbN2/GU57yFADA3Nwcbr31Vrzzne8EAKxbtw4zMzPYvHkzXvKSlwAA7r//fnznO9/Bpk2bOh/bTF5B1WfMKhC+qZvSCs2uV0uzAXhjrnx9LLtUoX1THlcilBe4sIsyA7JSAy5ZdiZwfsaia9xQjdty9RljRpSYEWbpIeshpfcPw6xzDKdhLZywTO9F05kh+xaQKFFiRkjMyxIrBJT1Ub+2nfG+mR6jWyq35ZlsjBmZYz7LMZIFRiLHdsRlrbnU6mQa08ZdklpyDeSOhfpfAmJcNdQd4CK9EraDmzSaZKbGv5llhpBVDUc1Y6vrvlytn1d3W6YzZppZtqlMXShlhnl9JTOprOSZLO14XQAo9Jjswru6qlFc9Sbn2s3NQJM/TlfFc2GK3pshi67QDd+k17iGJwo/JjnVUNY9DCZ5OyGVuU5kmaGUw3ncXUrXk4Fad83yQ2aYgXEZDll5qdWUzkRsYLdaXqdaYscAL10D2tSdcSkxyrRbbF4gJ9Rg7nvf5b0+1i6zMyPPl7mF27nxCOMiU67J8zmK+RzlfA7MZdoaW90n9hqZ62Ia7/49Ze6rQt1LBm5FIV1PiVTI9dtPIrCfyRO9vjWAQdRVWQGu+QgNtxp4SwFZeMArM6BQoFuOVLxS6sm37MRBhbK0oYIQwLyjxkAGff+pScDUhFLtrug5Sgu7gHFLrWZh9iemolZd88xRj0b3Nx2nG3NfNuN0TXma+5uWs6DXDd5vArz+q0yQe95Cof5tnipqHL6pgwp96xWB/PfrUO239OpbAHLJIWQXIPE65RzIpfcPyauQ0F4TUvUgAtqVWbkxm44++pywQx5yBbkzuZ6lORMYZQJlkTnPiZhCbshdx+WG2md9ILfreNXQ2rzO9gbwTcpPBFhj66u3WW8nyQuLNaQWFXTf8pa34KSTTsL++++Pn/3sZ/jkJz+JW265BZ///OchhMDGjRtxySWX4JBDDsEhhxyCSy65BDvvvDNe/vKXAwD22GMPnHbaaTjnnHOw11574TGPeQzOPfdcHHHEEXYW5kmVcpOmgmQqRLdBbxvwDgW7/j6xkohZk40KSaa8l3qCkKysYBfQDSJl1aVLlFDlkHoCqjFWZnMO5M6KAitEiRmhADQXQoNu+3kby2wBaeOXUiITwgmz52bGk8F/sajpkHIUKKCAbB4SGQrXqgu9vJDIMCdGFtyrpZSoe21L/TO9/rqnUY0NFE5D24HcwvymVidLeLaB7RzVb0QZiy8FWgK4uaBW3brbclVeBnDDnUK5qKy6tpxlCWBF5QKutcLkk0hZcqU9Ri6rXmozTtfkhS7rZAifui9bwJXumpyWUkk52e+Ba2X/k0YuLWY6CRVI0vG0IkSUILpXNf5WHdAMKzBlUZoGp84QHX8bWz+21L/LMnMncTLnCFjYyHO93AiAPCuttZfWn1HAEm9AeyzVONvQmNv5+Rzj+RGKuUzB7VyGfE5AzLv3SVUwBHTJduuabO6hAsjG0vGQEIVU/0vAWuxoQx8GQEUYeKFBlai23qqTVRfApB4z77osa3ilsJsDZU6B10Av+V0IyJHUrsxqmxiVdoyyGcdclKW63mY8Za7GUyqNAYzUtSPuzAZ2IdSSX6b+UeA1sGt73QQI4CrotfWDWnVFtdSQqkMaXu29q0BWkGpYc1+297ew4VLfj44FOFPXvoJigD4v6ZW011H1ClR1jGTBdCjaePS/jejWG/qxYSYdUhcciy9ImK1L9XpWG5fbIAvxOq7TyUM73Mw7RArbE21dmQHAdl+WMBHMKn2+F8EI1dCnUSZ0PXCHxVC5oFsfx991XO5CAG5svzbwBdrbpqF9fCsujRfzxkqB2x0BeO0rfwrpsqanRQXdn/zkJ3jlK1+J+++/H3vssQee9KQn4fOf/zxOOOEEAMAb3/hGPPLIIzjzzDPx0EMP4eijj8ZNN91k19AFgHe9610YjUZ4yUtegkceeQTHH388rr322kHW0E1VnwcM3S/F0hsD3qHcZWKTuhj5Z9jW2+k3SS0w2AQylEJilJUQ0liGct3YzlDK0oFdMwmVWTZoBoWF3J2zMVYKiRkAM0JgRmRBwC0grYuxyaMZX2uzZV+16qTVEDaBDAVyqImy1P9Mh2fKmmCPl2FWZJiXBXKhG2v2o5e+QYYVosC8KLBSzBGr7gh5WVrrZqjnVJUx7AQ50rZy4H4M7HquldkYyOZNuLRuy9K2ToRtVACoA665JHYdTsC34JrGpT/zsjmXUM97cPZl7cY+TzNkAbcOuzmqGa99VVBbOq7LoeMaKKeW3wLV+cB8p41lr1EcaugC5IVmXpgEgmx8gcqi7oAv6YXocdtTV2FjvaXfS11+gOuqTAHYeF7Q8bcxwC3MrMUGjGS1NqwzRjeTKIsMcqaAEBKjMoMYjTXcFhhlpQO5pYbrcamWAxqXer3bIsfceITt4xzz8yOM53MU8xnk9lzB7XaBbF4gmwOyeeF4M7gFVV0bH3BFIdU9REC3AlyprLultKDrXnzhTBAlc3PdCfQCbobaGkDCWOsqC6RxXbauypmGWOKiXOaAsIBLYDiHtt5q4C2AciTUpFUjWcHvSCArM5RlgdGommSs0DM023VQczV5kB2/68FuJgoUyCqXZS2/08VYc40Lc464VdcBXph7FTbcmRleCOWdIumSQ6isuuYe1DMG2zkLhFQdg7LaJ3bPRxUCWVHVPUnC7H+nnrjhFmIzEo/mzSwt5e3fz4JbTabn7O6/h+y9JGxk++jRk24py201nMqHXYnc20YOZay6gnaWZLbzo0nx5YXqsDuUFXdIpazgkQqXKUsE+emFIDfmAt01PyzWkFpU0L366qsbtwshcMEFF+CCCy6Ixlm5ciXe85734D3vec/E+QlZ0IZyXW5Kh8ZtsvKmwm6KVbdpnG4T5LY+/KV9e9rjAiDLtGgOk2SSGTKWKyvVTIohF+ZMyGriqayC3J2FxEohsFLkFkCNCqnGy5ZSjZ+dkxLzEpiHmiF5XmbVOrieFZkuS1SN+y2s1ZhC9YyZLZm6OMsMM8JYjHVjDQUKzNuJqOZlbi26M7pRn5XSupM21iMKuNqS6wBuCTsxTkYsucqaK21DH6gsEZQpHSuBXXdTqoahBl0I9d+6LQMEdgngQkZfln4PvHKdzVBNP6xg19aHCOyuQIHCNo/qHgFmds5QudaXGiKAq+MXBvqEat0643RNQ9Ors1IQS4YWhd0qomn0gTQkpd0mEdhnAFFLbiaqyeN8d2XrOgjiqkwAd1yQMbl61mIFuBXowv5HVXdN3RrpOpCVwAy0hUaNvQOAuTK3YDtf5M4yQI7ldpyjnMshteVWzAmMtgsFuXOqk8dAKoVc0g7XBVMBa2WtVfeNAl2p4HZe/9e/VeeRhLXIAzBWQpkpUFIAqieEykUFqSYuVSvowoVlm765ZwWx4AoLvZn5nQNypK27+iMKgXKk4Xiknh/lCGoMs7HwFgLFqNTjeDMFuKPKultIgSKjk4Jldh1U5GMLu6pzsyT3u3tvOjMy65vETEwVs+qa+1jSeq2XGrIdVBYMTQcV6agi5UrDZQY16ZbtgKLxyDPU+15ZgQPjdv2+EFnVRVUvTcUMgKsDseQDndeMWvals69KW9q0m/KUJGtGrs6DQm7VqScqi7idTdHsXz0/pT6JUgoIWYEUHd8/0pbdGQ27xuuDLk8GxOGqqXN/aCtuF6Uubdnk7TfEsdusuCqsfs/u0DBr6/EU0v0V1re+9a3kuE960pM6p7/kxuguNbXdtH3cllOgt8skUqmwS5U6GVUK5Da9FAry24KubnBIwHFdRglkIsdYlhhJ48Ks9s+1u6kZm7uLmMPO2Ri7CYmdsxwrxQgjMsXUGAUelWNslyV+UUr8Uub4hZzBL8tZPCpn8Av9f17mmJMj1UBHZmHXrMM7o8F6hSg0XM/XXKZXikKPEa7ANyOglUOgFMAMJGZQYiUKlGIecxpyjVXXuNRmonTAUOXHrYe2s5o2MCSqtXIVVxNLFCqLrrU8VQ0r31PcWp4y6Yz1gwCQV9ZcY/20bstZiUwo91MDiI41F9XLsm0GxgKq8Wsas2r5KbM8k8BKMXY6SQBoK7qC0qJlFs3Kulw6BUDz6CyNJEAay/WxfgpmJMy4WtVGjXRcSfe/MdY6L1LyXcjIuzC1UUS/GwuuVONz6X9jorYz5QIEVkQUcAsNtEWRVdZbPYOxLDLtPqFbuLoDxmRK5hqcABQjBdHGJfnn5SweGc/g0fEIj87N2BmSS7ME0FivXzsWEOMMYl4gnxMKaLer//l2DbjzshqjXpJyp5fJsI8BXcclWYPtWIFtNi4h5kuIcQlRlBCFBMrSDgcwY2VVvciAXANungEadJELB2ZiFy7mvlxZg/V/O6OyOnY5MsesYNYArtDjc8tCKOsuAV5RqLTKApAjCVEqK7DU3qRyBOWVUwo9hldb7UfaoltmKLQr8zjPlDszqnVQV2QKekdZoec6cN2YfTVZdStLnrqPzXwABnjCSw1VHhkVNGoYzKA6Zei6r1K/vzLdUeNBsK1LFmrVdU+Flvp1RS1dCrcWas2z2eTd5F+Qcbke5EoTNybzLAKsy3e0Ie6DugmjkOvNR2CejUJbcl3Tten9oo9BY90lhzWzf+v/IynUslZC/ZeSzsIcfo+G6lmtk39gyG0C0a51pe9ylinptHUSqG2/YpDLmpqe/OQnK4NBwqo6RRFfqi4mBt0J1ccCnAK9MVCNuTIP5cbsQGsgPAS4blhD4ia+bgBIUTVUpBRADoxLibHIMBY5yqxwJhfKtfuygswCOwuJ3bIRZsWMtahul/P4ZTmPn5Yl/l+5Ag8Wu+P/Fbvip8XOeLjYGT8rVuLnxSweKWbwSDGDcZlbN0gKucaitCIbYzYrMJuNsVM+h53zOeyaP4qdsznslj2C3fNHsbPYjt2zR7FzNq+ht3KjziGq2ZkBPSOzmlDLWKdzMaOgWrsvz5RFZZmArL0cq15t0/MtHEiyvenGuivhuF7SiXQAVA0gAl12tlbr7oiaNdeMzTXWXDM2l1pz6WRURk097LnwetbNJFSQ1vpdQlkLHcjV/32rbsiNOSYfygsSJoH/P3v/Hm1LVtYHw785Z9Vae+9z64vQTWvbNIoKYhwKBi8xMF4FgZEoykASEjPIIEQ/0JEWUfR1JDTKCwGNElFQCPHGEB3GaNBP/SQjQwLSiXkx4AW8RFtA6Kbt6+k+Z++1VtWc3x/P88z5zFmzaq219z7dfZr9jLPPqppVNatq1qxZz2/+nkuhLCNTlpOibDKlMmN44gMcLksdRj3HUcs7pQTnZeuVjBLkBlWulcnSrE9HUC4BbmRwewapnNoqSIorjmYcU/KIOb2ATRfgW7r/rvU4WFHwqE+tzuDg4gzhYgN7QCBW/Mqtp65opJ/ryZwV/blliAxu9KX1IWfNFJtKbR8S0JV3pQ+wK08TRCtPALfzMKseZtUDXQ/T9QRyVZQtYxjUOgfjLEJjYaxFcB6wlieTTASp+YOSawpxUDXpYcVzAMjrEbaYUwFZx2bEzsA2Ad4ZZnMB0zDg7QOB3N7ANAyGGwa1HtFcGY0sgyYwXEhRmb1BYBPmntle6iupz/ShQ2ctZpYCWHnL77LxaG2PBj3A+axLU2aRGqtrQ7L+ie9rSKyu/OaphtJYFaQptakykEAjB00K6rlkrK5MMCoQKuvy7pe/URSolGcZyu1Gyk1cjv2l9MVmYJuCkCXwngHcqWExDK9rdD/9W5H4LSom7eI1xG9XIPP2OONnilMksFuOi6JzBJBlTunfLwHKaN/134OHwkz5sBMix13XGGgd88kdA8SHded72MvgBT3Gej+N5dZbb43L//t//2+84hWvwHd/93fjK77iKwAAt9xyC/7dv/t3hwoyDJwA3WOXbYHvFIO7iQ/vcci6+ktAOwVwQ2VbKWQyZZgBZCVEbReQGaO4CgBl/9wd02HP9DhlLOamhYXBRb/EA2GF23uHj3dX4ePLq/GxxdX41OIs7lqcwn3LHVxYzkiJ7hy6jvwHJbCKFsNAzjkP5zzapses6bHbrrDbrHCqXeB0u8DZZoEr2os411zEObePK9wFnLUHOGP3ccqssGc7tPAxtZF46kqqJGt8BLuS+zdGJK6kFioaUS2nXyY+8gA6AnZ1gCpW+rnBxapMMQRIeTYjwEXG5hrrI8hNoHbI5qZ72ozFLVkdYnZJ+e1g0VhPrG6w8Da3CIAFnJoc8YHZx4ops5aBORYzQ2LGLPl0RVnOfP2sh+FrDD5ERigy4NzfSyVTHq+wtVG3VErhQEoluCgTML6JZFGWQZfbF+9t8slNPrhd7zIGN7KrkoM25nA2ib1lgGsl52wHWEnnYwz6eUAHh743uHDXHPM7HfZuDzh3nthTaZTc71SZjAvoZb/zzHe2C8yyqnvXkxGxEAxaQvK59SFnbQXcrjoCt6sOoesQ+h4xxLWxMM4CTQMT2Os5kFl/sIgsoeF+MnhcMdQsA1350+vpgdMhYgItzHFjI3tsGwa7jSUg2wQYRxMNgQGv94BpAmH1hp5baGis8B6cVxfwkmqop+3eG/LfFXPmngCvmKz7xo6yu7Fv8Yxbbwy5iIgp84SI2bJEYI5jTJFqyJvcnSKlGpJHFWB61Y+kTwirawKM5H01gPjzlqxuYn2RT27V+pk8N3nxY1m+HNRfBnht+RcKdhcJ5EZ/3TByHXrWR11HCXbXAF/9bqXJOpOD4YDBO5iAsInxMdCtAbsN0HWIjK5Teom3PgYflIn00pJoG1kHcGsuYtvKFDA9TH3b6ou1c2wDcjepb6r8RE7khhtuiMvPf/7z8WM/9mN4znOeE8v+zt/5O7j++uvxr//1v8Zzn/vcres/AbpKauxZKdvO7G0KVqdMjWvbambMJau7znx5SqQV1oHcMYAb96tWnpQ77wOszYGNRcDSUKTOXeeS+bIJzOj22DGANQYP+AXu9R4f7c7iTxafgz+58Jn4y/OfgdvuP4MLD+zAX2hgDhzcwpByzblkG0ad2Yc3KtCkDPoG6NqAg1lAaD3M3MPOesxmHXZmK5yeL3F6tsDZ2QGuml3EFc1FXNlewFXuAq5wF4nxtQcx9ZGOlt2DAlVRrtfAbHXPaZS0j64f/xCKMqGXZdI+FH9sPpalPCmqjYpSNYBNIJDLfzaCXA/L+U8lF6pmc7eV6J+L1IeEae+Y3V0Fj87YPGcnEMHuzCTTlh42+uvWInkD1K86qaKYoY6gFrmyHEGvZQaB289YYrei6aAFynydtTeypm9qiYp4PIB/DvF6ExZPIFfGidIvNyCxuRJkqmMGNwO4Yj6s2VvxxS3yOdseKSCU+IwHwLcGzQMGs/strvrTJXb//DaE+x8AVvxkZi3Mzg7CzgyYz+BnDcLcwTc2grrc/JjBb0/AUJqO2tFEU3cxGzYMJBEY3HY+/qLzMH0BbpcrhNUSYdUBYkrlHEzbAE0DlBMr+kGFAOPJvl0/81FQ2zNT7H3y/+V6Yr3OAsbAWAs0jtqksQjOIvQEvD1POnhPpsqGqozjgmcAF0IgkBeQWF1eNo5AseTWjf67HgSwe2L0QxOY5ffwramyu5KiaAby4Z3bDt5YtLbPoueOif6+ZROESKmGZL8AxIBygH6XZdlgGJQqkKlyAGA5zQ8vI5jI6pZsrgSLDp6eu4BMYXqzSRbdbWMdyvy8ALhZoCkFdhH/QgS/GaMrJ4mza7pvKsAdzRsQy6L5cnHIQEYm6Gqsbiw36TiLEbAr99vlYDfzWQEQAkVrD/w9Sv7ZCfBKcL3DyqakwFFB3VGOP85ja365U8c84sHsSB8/lnpPBADwR3/0R7jxxhsH5TfeeCM+/OEPH6rOE6C7pawL8T56nBoApgDt2PZNwe5RZAycToFcDXDL4yVnZqpHXzufkz+i3nMgHNfz9oDG9lj0DfommbO1podFwEEA/rYz+KvVo3DLA5+L//euz8Zf3341cMccs3stZvcDV1wMcAsyYRSGppxVBkRZIB803xj4FuhngJ8Z9HNDy3OLfg74ecD+jsf+zOP8TofZrMPufIkz8yXOzg9wxewirppdxJXNRVzVXMBVzQMK8K6i8uaDzUCYGGZt48OaboBmxMv7iut8z6L8R9ZKgauoWFlkgWkCR1tFBLoMcJntds5nJssSmVgDRR11eUzGUtnoVFPaF68zDj2kDekmevD1o8u8umKE4G3e1YCqspzl5bQeIVgGu4rVtUpBFgVXQC4D5AiMdbNoxW9EsgiprIxrk2qpsAaAxVxZrwsRLvfYq3c9aBa3ALh9bxPAZZBregVuZUJFm893CeS6JeAOAHcQ4FZ0z7MLHmc/+Cn4T96OXgaLvieWPBB6MM7BzFrYnTnMzg4waxFmLULbAI2NKYroJjDwbQ0K5Jbgk9hnD/QMRLVJsjC3XZeWVx1dl3MwTQMzmxGL2zgCu42LpssCRMVnFxpg62sIIYJz9ESnGv6NgJfZY+mbhs2k4Ryds3cwnYMRwOsdfAvYwLlxvYFvOYpAoA4X+BeBTNgt5zNNUbLBeXQZ53nDZsuIZurRvDlYhJ4jNLdizmzRNxZd7zBvu+iD3TmLLvSZz678UqyD9RqgsLv1bcOgVLn5spHBMbGsYpZsTHyfjfh21CItC/CVsVVArmUMqQBusCZNvBg1IRbHCpMAs0lANrNkGGVzZWJSgdzY1wvAOyrqo6AmjsZkK1wjGDvkRYKzCbtPMLsNgF6BXWeQooNx84cAH3issz5O1kk/MKovlLJpHJVLLQ8FWFzXHqlsnM19xIPcE3lQ5AlPeAJe85rX4O1vfzt2dnYAAIvFAq95zWvwhCc84VB1ngDdI8phgO86pnVs+1EY2sNI7VxTILcEuIl4MGrfVFeMwWICvA0MalJZYz12XIeFb2JanlVwuNvv4BPdlXjf+c/Df/vY52H552dx5lbgsz7ZY3bPAdz+ikwM+wB0fVQg40nZlw2WFWNrEVqHfu7g5w79jkW3Y9HtGHQ7Bv0OA9454Oe8PrPwc4f9eYPFvMWF+Rz3zXdw93wPd84PcMVsH1fNLuLq2QO4shGG9wCn7AKtIZaqD8mHVEcJrvmnbfwREVa3tntIOl15iDACnlONUIoRxOircAGm8cTmMsAVv1yr2FwxG4s+UtokeERj8pEGSWUCcH0wA8BLKYICVt6hsw7e5f3UG4O2YHXFdJlMmevMbpZDNzNlHs/LSSA3wLIvn7eGWF0OSoWouLIJpFGgd4tHmplAGvUgVZlmq0RKwJvSfwVWKpMuXIJcH4CudxGoiLm/7wjkoiOQa7oEciXSd1T6wb8lq7sEmv2A+XmP2fkezQMrtLd+Cv2dd9N1O4vQF+9B8AidR+hWwP4B7O4CZncHZncXmLfRF1bdrAxUqj2MPNS0X4ySHHJQ6T0B7a6j9b5PJsoAzKwlBtc5BrgNIIxqAXDFtJgYvuG4GgGvdkTUf3w9dC092W56BrsCcp0lwN22QEMBeQx/4ukNIxrXAoAN0boehsCFMQIstb829xN+nlYuyQvYpfaL6z1SCqJA1g1izux7C98mE+ZZY+vsLkfdb9iM2RUvSmleLxLdIyrmy3SbNfPlPChVZHUtd1xgYMIc/XanWF0BuTwGEBjm+RrZJ3A/DPIeC5M7BLYyPmexE4qyfBuD3GKMqKoncYJNIdvj0jNCakZggtX1I2C3l8kAk80BBiN91AHoEYKFcwCcBwW49AjBkRsNT2ykidKUG13kuHWrMTBdyjZWTw8WkBywuoXJ8lGu6bIHw0X/PdZ6TwQA8JM/+ZP4h//wH+L666/HF3/xFwMAPvShD8EYg9/4jd84VJ0nQPeYRZunTu43wd7K9k0G3pLV3TYo1bpzhEL5peU6yC0BrQa8GvgOfYI4z6GVvJukrDbW46BvsPQNFp4iJX98dTX+fP9a/NbHnojF71+Fa//nArt/8Tfwd9+LcLAgZdjzjL01iL5e1sA4xyDXRgbENA3MfAbMWtjdOfzeDLZrAN/ABFv4thr0HqTYzwG/MvBLA7+0WCwcVvMGF2cz3D+f476dHdw738Xds70M8ArY3bErAAR2V8Fl4Ev7kx7qw8BAKphcrykZ3rgvK0iRyW3ozzcBaATkBliX/JatpYmIGsjVf+vuwSvWRiuwnad0QitPQEv8tUUkt2q1/9rk6wsgRtPWIFdMdcvzZtUUyrIwQc4KPPQInhhdgNgEE8h/WVjdYAPAKVuoTyJnVoz6xqmygW/fAOxCKeqIbK6ePFqnRIkJsyh9+v2WXLhemNxOsbgrSwB3JSCX3wlR+IHBh1tY3WRRQKbLzUWP+R0XYf7mU+juvpfeWecQek+gUksRhEmb8BofEIzY2CrQGk2BgzzUYSPEfWj/0HtCJPKrIuyZtqGHKEGmBNw6i9C4uBwn0cRv1qrrlntQ1x/EV5dN341ifdO18rX0nq5xtSJm2ViYloB2AIN5a2C6ngMYGVAAOU99MhjyZbYEIoynYwSsGUOTESXY1U1pLDeLBywD3uCDArugoGSce9dH8EvA17dsLdDYUXa3tz2csZlZMj2y3LVhEynNl2t+9sEz6x7BoUkA0RoEhBhJOFpqMDqrsroMimX+TH4p93lIzLFiUBPQ1X8mTkDGnMeKzQWzuMGB/KU1yC3BLpAGf83cBiBBTV5WHxC698MDwXIoGrC6QB3sGgCdiXqNieMllUSwq1MQ2QDLjC5gIYEvnfUxkwNZ7ShXjQ3u4cEAaQ8lU1o99wkCO5EHWf7u3/27uPXWW/GOd7wDf/qnf4oQAl7wghfghS98IU6dOnWoOk+ArpKYaoRlzKdvo7q2ALzbgN1LxeqWZsdZ5NtsOR1TA7mjAFfKIMv5+Y0BehNICWpUWiHjsdcscZ/bxf39Dj5y/lr88YduwGf//zz2fv8v4M+fR7fqaLZdTBwBwFhaR5/KGmZgvEewlvzurCF2pHFK4UUKSNNRlNKwVHqB+Lr1RK7YlYOfWfilxXLm0C0dFssGF+cznJ/v4PzODs53c9w328WVzUWccQc47Q4wU8zuKrgsV2z8DfnvWhHNSys2WgodJ6YeaTiaqktsbmgooipaD9N4WNfDOY+m6eFMQON8nDHXIDf66SKBrXoURgtner43q8opx7GOiN0Fl7WB9QGN6VNgG3WzfbDYsWQmLqmGPLex7DsWnCpTqoON5sslqysA05kAsEIVQjJhNmJaKoyOQ/J11KbNisjOmFsggWCTUoXQRYb0x4p47ntYvbXYtvrOveoQAnQlwrIEm+o7B98b+JUjFrczsEvLPu/k+y5RlEsfRElPpRo4Kuy+IfeA0FiYrqOJKLrIBHLV+xwbUMQ5+lPA1yh/VmFhtZlvCirg4zFZWRk2noF3BLbKRJjArF0PbiWycwmyYQDPAMIEJvbkPg33EUaUbIECBqvGJAsaum4fJ1riPSlrXnFbkH0i2OJORpMUFOzLsI9uFkxJsXw20POzgZ8lzweE3iR3B/bN9j3InNmTObOA3KACVPXeYN6aLDJzZ3vMXIfGeDZjJvCipbT0yB9bHn25V+XCBhoeK2NgKn4kkImr4jmJ6XlgNjdLIVVM4sTgVNzXEShKtZiBR3vloE4UQa5RsRH4eFk3SG0cwS8DWqtAbjY+IJsEiz4rPGbQq6EAbgl2VTMcB+4ZZXUjqJZ5BgP0vGMvmRqAmI2Y3wFx+hEJIWTMrpHPi7dpkqPUq8prrH6vhgPrpQahm9Y/tt86N7nJOjOrJq+WP43Bb9F3j7XeE4myt7eHf/kv/+Wx1XcCdCekZqqxLfjdBPA+2CbJm0ruX5svbwJyvTcJ4EbAC/b7Khhe/hB7a+F7CmQCEJCYuR4HfYtb770aD/z+Z+Dz//PdwP/5a3hmXATkEkPRQljdCH6Z1Q0dsahm1tJHVALHtOLn5+BbR1FDVXAb4wNFiF0lxVAUGtORT6/pALNy8CsLv7JYLB1WS8r9ub9qcGE1wwPzOe6f7eCK9iLONgfYc4sYbVmA7iq4mKdU+lrW9qq9s2dlSBGTGe/JiJ/g2zAm5dZs+K8FQgv4NiC0BHJt4+GaHk1DILfRLC5HWG4Y8OpIy3q9FM/t2DNrkEVZDiaC3GXfRLArvrYA0BiPzjJTyzcYP8wMKlvbYSXnYzZX/oDE9I5JFuzG5KwuFKsLTwCE+jNROZKKiSYSAiRzSjAq4q68D9lzRPK3i2ARBISU8jrG5qbyIeDNVNiy/6j32RcRlXsxVV4ZmJWFWRrytV0BdsVB3jhlVbwHUfCdIZYpAgj2gWflOhgHhD2c/uuGwBz75Bpr8kjG7KMrYNc4A+MoXY+Yf2a+rV2H4BPQhUyCibmvV4AYIBAJ0DskAFrArVVmyOvArSwzsI2pg2qzD/HeeHItGOatbPyl3RjA2kDpiawjK4vZjK6L6zHiByyuGVm/ygNfZbhGFwsQU8v6uWafRBkHeb9ghoCXJgQN+ew2IbK+XU8TKd4ndndWiczcmB5NsGzGPB23YBN3oGxCKJj8PZJ3m5+ZuBgk/13kJsz6j82Zdd7daF4sgFf9Qs6jJlakr0TLGgG9kgNZ3inN7MaAgSEDvBIl38QcXOoZ86SKPEMjmFsAuC/AbolAc5y8nYSRZTkLI9cAgLxPTLx+0xs+jO+nY6sa0HNJ7j888WjZAsdQpTqtoXyb+jCMem6VdUu8tjVA8jjA3zZ1HBUATx5zgrrGRT7Ql6LeE4ny8z//8/ipn/op/NVf/RVuueUW3HDDDfjRH/1RPO5xj8M3fMM3bF3fCdDdUkrzqY2PW2NSvI1fbll2qYJSDZdHQNYEyPU8MIgPFy0b+hYpUy8EG6NT9i4Qg8Rgtw8G913YhfnAWdz4y7fBf/QTdN6+J6VUg93WMKigY41S+IK3EexiBjL3sxZoG4RZCz9vyEd3RsprkDoE1PaAg+TZNAgdYBoywfQrYkT7FRAWDv2cGN6DpcNq5bBYtTjoGlzsZrgwn2F/dhGn3AJ7bhn9SVfB4cC3xDyKf6oy0xt9xlLMbIUEQ6mOyQKejFHMmmFTZQK4vgkIswA0Aab1cI2PILd1fdVUuQS5m/Qv6scMXuI2uu+ld+i8w9I78sXlnK1y7EpM0aytvle9tdhBHswmMrrBTCrFWgTgiplbFgyqBLuO7iM4Bo7Op77uxJ9RcBczVBosGK7OioItIJfLZdIi5jJGNLski/zkgyiylpkIojym9zcyub3yx11yHlsBuUvALgwc56w1Cuh6Nn+XXKyhN3lwnZbaqJ8Dq1MG/bzBmTOngfvuZysMxF9aUWBXhP1iI0DVvqx9n0CurHMQp9D3GWMsptKG6zRNUzVLhmXTZFkmOj8Hty4HtkED3JxGR2x0WWfAq0FugCe211oCjRwRysih1qTxjc2p6fodX49cu/QrAeFyjMHoJ6kAuzSxR5GHIyCRfsuvgYC4DPD2oLRFvfLf5UBVnlO71djdECitXGstmkD5zGl8SabMui9v466jJ4ESyDUx1ZAwoMEKrhN0h2SJYUKcYEnmMWA20cT2IzaX3gkbDLwLWVcIJgUR1BNEBG4NNKsbx2thc3XAQA1ynYwPMimWgK7Mq8Rxgb/b4CcbwPclYFe/hkasD1L/WAt41zwWdRkQ/Boj5Ml416uqDNhvlwGvgF+eBPPGAL3+prAVhLcMcLkIiC4bgwnNCniVb+82PrXr/HTX1fVgmzGPfbc3Dop5IidyDPKWt7wF/+bf/BvcdNNNeM1rXoOev9VXXnkl3vjGN54A3QdTDmPivK3/7KWSMcA0NoRWE6grNlfvNwVyQ8ytqYAumwFDZpMBUvRXFqvOwvcODzywg9lf7OKG/+/d8B//ZGbWGAo3vowRKs0Q5TqF2W1JkQ0tpyqZN/AzS4FTWhOjWUrjmJ5+bQBMT4qQdWL6S8q9XRj4GSn/vnXoVwb9yuDiioL5LDuHRd/goGtxdraPs80Cc7uKH7BVcOgCm+yqv7WfN5P+gmHySzERQAK+0l29IwY3/s3kNyA0HmbWE8ht+whyW+fJN9ckE2UAGcCdMlfWIqyuDy4qGB7sr6dA7qp3WDHQ7dl/24wA3bKlXJHWaeUdM7kmnk9Y4fI9jpDDSNAfsM+u3mkE7AaDAAvjyfcvmjHLhI9jpRicz5Sry1KDMKiNZSYpsMLUjIHcMfPl2hOJvrmcQiiyuZrJ7RLIdQcGdsGRkxeAXQZKFSSTKw31LYCYXngGtjsG3R7Q7wD9TuB3JqA7bbD8rKvgPnl7VGqj1G7EmAzQ8U3EqMQZyA0+Mbji48oTY2Df1hjESgJKOfa1laBSJXurfw1onxLcMntP11teP/8Ie2UVYDQUHCkw+ArWMsC1CcRwFcEbkF8Fsd1GBcCK/sIck0DAeYzqyzmIpSxk11+5Zrn0kNJpScqyPPBSAXgZ3BpONxT9dz3YnNmga3N2NwSDvrGYsd/uzJKLggSnaiy9MAOwqyawNpnIStGXTQK8Viw0COyl9jD8mjMAFoskZnJ1YCqiEREjLsdlR0+OAsElkBgtyGX8FpArk0UxQCCD2gY5i8ssbwZyXYgA19jUZ/j1UWbvAta5GwnYFZpXfmOnRTpYL0+JKZbVJAldQ9olWhBkYNckkNqr69Jt1iMe5B2qYNcE8tvtPSK7m+11BMC7afCpo8hx1b8NY1uC3Ml4Gw9CGzzUYnS/PeZ6T4TkTW96E972trfhuc99Lv7tv/23sfwpT3kKXvGKVxyqzhOgewxC6Q2ODnYfqmjLU9GV0z7DspovbhBwWwO5kmuTgS5FYVXLoiSAPuK+tfD7Ds19Fp/53w+A//MxwAf2s2VtQhgN8WPzAcaBlNm2SdviRRMADn2PsOqYybFstmw5vRDPpNsEdqPfWlRIuTo2MY2z8JyeyM/o164s+qWB7ywWHfk7rnqHZU9A7qBtcapZYmY7vlQCtou+QecVIAum+gwyMMumcsZyag+T3XYCwhaJHWiNArqBQO4sADMP2xLIbZses6ZH43q0bK5csrflh78WiCqlEPJZWQS5/KdB7qJrsPKUlqTrbZxgMaCgUL1TvkPI2WRKU+KzKNY92AwaEpxq6l3MTR5tIBPtztsIdg0AWA9rDOlgPZnMOcemzI2BDxKBFoAXX3L22xWlTSm7+vmEaIqIqMwK0LUmDECuZqq0hJBHGa1PUFmKkMsAJIFcZa68YJC7oKjJbgE0B4FTeKV7aPY95ncv4M4fUC7cWYvVlbu48Jk7uHCdxf6jAL/nEfY6LM8Y3PP5O3jUH6jPEbdRKaHvIWmG8n35jxnb+kO10cgdbI4sADdjcDXAbVxkbaPfLQPdwCbCA3AbJ5bG0CIDRhCLCM9gwyAxhhLcKIINsP+s5bHORpN1QpcmM7dOAbL4Wh1fK1uqSCqx4JCNCdHaQ/piDfSGeBvUbXmCw8gyX07sx8zuUs5d8d815B7Bpsya3ZVAaDHvrqUxsbXkNtEF8s8HamA3TXyNfUsDW76U+WFj/C+TTJgFJAb5TwCWTYGpoqmyAr4mvt9U7h2T+lQxR7lObUn9RdosxUuIZssxfoIGuaAJM5cDXD1GUNccaudGvt1GmFz+bgjYjag4f+bBqJRMshP3kzjnZCpdxowo8yH/1f7NYsZM98AVyLvW52naUhXjYNeYAHiKuwDrUUadp3AKeX+aArzb5onfDmBeuro3v4YTJvdEHny59dZb8SVf8iWD8vl8jgsXLhyqzhOge0xyXGD3wZTDgOcylZCUjUZbHjC5DG4l3UiXUo5IChJRKCRS5bm/9Jj90Ufhl0s6x4rBlTUca4oZ3FW6KlrvommfsLvR1C8w6+M9xMyPQJ+h2XSbzC1F+aPjAOtDmpFWs9tkakZMVT8TZpeYsL4L6DryTbsgpqGeAO1B22LHrdCIWTwMA+GGGEhvVZsq3+Z4s4SSyH9MZqvTtcfnZAwzg6I8JZDbzwMpnrMAtB5u5tG2PWZth3nbEZtrPVrXZ/63m4rM9mqwG8syRsYOQO6SJweEbRQlo7cWQVH6OvewXFuPPks1RPl0bYzqLKbSMbVO5b3UkTkF7PpgKL1QMNEsrhSa7PGksEYrhpSzVKKIGu5P9CxzgBuDzRhSZg2bLFvDYNdSeqcawJVlHSG9vD79vgrI9T1NzIBz5JpVMld2DHLdAdDsE9htL3o0F3vYpYfxAe7+A5hP/i38/Q/Aq0BPTdPgyr++GrMvvg79rEV3FmjmPdpZh/se3+IznnAj8ME/5Yu3eXA5JRnIVZGLo79tenA0zjAIJLNSFVCq9MGVAFPaRLlkcNcA3FEWN2v4StEYEIg3rSq0jCyszbdrH2JnEaxlcG4juA0R7EKVIbK6eszTFiLV+xEmLqjtRgFfDaAtD7VswuybEAP6+RkQgqVURD6Zz/uWQW/TR8Dbuh7OeHTGjvv/a2Z3g++sTBDJuELPwkAiYEPdC8SEWQWmijl25T0DYvouqG9EBFXse0rMcIjtJ4GtsmBtCvCGJo0HvgH5vgvIlbHB+eTSwGOE3GP26AISIOfnFrxJYNfymMXflhReOj3nCG5r/ZYnDEZNS8aO4wbUGCsYxEk0/T02PT+rXt2DvJPAAOzGoFRAZso8xu4aDAHvFNg9CqO57rip7Q8nkPuIZ3W1znfc9Z4IAODGG2/EBz/4Qdxwww1Z+W/91m/hiU984qHqPAG6xyjbgN3xOjZjbyejNR8BSI/5546J1jMjiyvb2ISZTJTlD4nB7QwBXA5qY1cMeLv0oWsvBFzxJ/ejv/teqTSdW5k5xmV2UA0+/Rpr4nFSDoByUnLkzMhyKOUs/mlfNh7oJPiO6Tk9BzdEsBQ1um8D+plBv2CTTQ7a0/UO3hsccHuteotV77DbNGhdTylz2Hy39zYGphKz3djOcrvycedAP1GbygAukoLgWBFjkNvPyFfSt4CfB4SZh531aNoOLYPcmesxbygCqmZzS1nXX4ZgNyff5L61ubKA3K5zlN7Gp3NYZk21MlKaTXsYeKPSSIRkqiypJsYYoJhXVxUL2JUyDwV8OSBXlEZP/HhS5kWxFU1PfALlMLYg0OlCYKEU2aTAapA7lU6o9OEvJ6Vk8iDIRIJYX8hE1MrAdukdJZPlgOaAQG77QIfm3gXshQOY/QX8396JfsnuAcqFICwWCLd/CnurFa7YvRHLcxb9FQbztsPiugPc8WVn8Ji7PhP9xz9RBbhcYW7F4X0yYbaMpixNPgCyjZV9eqjMyilTXx1BWUx/NYsrE1/aRFkY0RqDuyXIJcDB24Sd5kkR9aDG6xQqUvxyrTDWhq5drr8pAK4OeGRryxiA3Wws1JdQMnNggOJlfKLHAY7EbHoCueK64nuaZKOsTmmS1LcmsbuOrClaR8zu2IRbzCCgrESmJObSZTAnrG6iqSsmzAHM6rKpb2Cwi+TDHP119bVxU0jbRHAs7VsAXUn35pvAk5NkugxHwb3EXNk4ynEeLT2ilUcCuXockC4lgJfMtUMGduP9FlYnicqn8iDnMCYaJmiJgFhwssmbVyaNowGDql5YXUKdNJkLVR/6VCZnjpBVhgEGu5RD29N7ixSUvMwpbgpQK4C3BnYfajlOkLsO3G563w+3NjqRy0u++7u/Gy972ctwcHCAEAJ+//d/H+985zvxute9Dv/hP/yHQ9W5MdD9m7/5G3zWZ33WoU7y6STHAXYfTjLqz5uxuOnjmbaDP/ZA9OUCKTWGzdgMg9pcgSYl2q4A2wXs3NPD3XYn+iKCMp0kTj3nZeW1ctCq6LMbwTDnzAQiONTmhsRwKL81IOaapOUA2wf2UeSorwCCY7C7Y9EtDFZLEGDw5I9JprMtDoS58BarmcXc9RFIega3K09AuPe5T/TgM2LSr8wtZBoHg1xhyim1C//NA4HcNpBfbttjNuuw03bYaTrMmy6aDWrWVCT2dw0IR/qNZloys2ZWSAXci7mygNyuI3YniD+34WO8gFyHBQPNxnrYPgHb3hqOvEkS2dsM8K5/ZzWz60Q5EvaAr71MgRKa9Lyiha02fDasXPpUFKwEm5EgMwR2ia0JsJzH2FqfzJZHrrnsJ9oiIAe56re3CeTyZFSMrrwC7CrALenXrgLsooe9uADuugf9+QegfWDlfSTASyytv+tunP3gKVx49GNw7xUtFjsrzHY63P9YYPcp1+Kcswi33UFpv9glwTQNMblSb9PANBKQSgFfY4ih7Xt6V3xILA49xMToGlNNExQaxeaaCsgV4KbbdYy5Kh6CMHhGgVnDncP0xIijDzDep18G9KbXfsbFk5X0Q8I2M0iPE3gRrBsV3CgHtcN1jINcfbuhvhx35eNNj5Rmy/P47w2x/p5cM8D+7D4AoU3sbmgNvPfwTY8ASoFVc6EQkaBzQAK81EXy5xQj79ZYXb4dsgIKsa6Yn9aThYyBtrJRs2DVdZrvNeKvL8fJuC3sd2Rx2dxbgV4CuzwuNAnkWs6VbHkSrAS6cj00BgQkiw7Ax+jxBYutn7e2HMocfQspJkeqb0ZqUroqBX5jkwX1x9/dgQmzSZOFwYS4n34fPT8rawP3J3pVeoyDXSCZMsvl1MDuYUyYj0uOA+ReKvPkGth9OGYWOZGHn/zzf/7P0XUdvud7vgcXL17EC1/4QnzmZ34m/v2///f4R//oHx2qzo2B7pOe9CS86U1vwrd8y7cc6kSfTrIJ2H24mC9vIto3tDRbLkVY3UTr8j1qwBsQQZ/thC1ikLsf0EZzSI/5HRfhz98fffPSiXzxqzUsk29nM8hBgKrgiV5AujYTlGKilI+I5SzYvJpM7wBidO3Kk+nmqocJgG8s/NzB7Tq4pcVqZTnXqIlT2T0aLLlt+2DQsR+sZh97b9GxmbOPJsyqwcU8jD/+VHXRr0SBClC+ucLmBvSzAD/3wLxHM+sxnxPI3WtXmLuO2dw+BqFK/UL6BFsXCEuLoUlyTUrrgT4wyGWAu2QWt+OgZBS5NR1jbAAaE1MICbvT2CZjnSWG7QBYK5Crmd1SLNMMg4+3ST5+FgbWBXQcLIv2S8OrvBc+BIQYjoYUMuND/kyjD17B2FhEcOucJzYXOZMdz8X3WOiT2T4a5Ppgoi9l9KXvTcqT24He004ACit6FvAzhzBv6Fx9n9wF+mRyod/f4APC39yGK//8KiyunmN/voN2b4XuXI/zj21gu0fj1BWnYO8/oPdaQChdeAo6RQ89vfsaDFoKBCblqW0ZDEoqnhLk8vYgDKk1CUjrYFNZYwLZqFhtcESrjwHAzVIjKZArAbX0fek8wXI/0g7yG++RAHpusqz/UPktQK5mrdVtCzChcyKN63EWJW2Pr7nlCU6V0ix9C+hdophhidEVU+YQDLyKzNw6DxdMjPw+xuxqVjeocmqqFFgrcNNpVjeAGds4xtKYE4SaNDQJQ/sBabqJEVu0sM+/KREIWtVXVFnO6IYc7ArIFXNl52Ebvv8NJ8CC0SA3wHsLa0MCuwxqY9RpMWEuWV353pTLyJezfTWIVdVJk4lQeyKxugrs5kA6gd0IzH2qO1pbwNL9QRl+TIFdbqNtwe7Dlc18MAGt3nYiJ3IYeclLXoKXvOQluPPOO+G9x6Mf/egj1bcx0H3ta1+Ll73sZfi1X/s1vPWtb8XVV199pBOfyOUnNXZ3zP+PCtVXL5BPY/S/kV9Pv8QaEVPU7Ae053vM7t6H/dt70R0shiBXM7kluyHpSMrLKXPrBg+sOlIsQyBlqzdREQOQFBIxKYV82A0pqJ4ADvkMediDFcyigw0BaBu4UzO45Qy2k0q1smzRo8EKrNTNOjTOUW7aqIwwGPOc7kWbg4soRaz2CCJYZwVB8uUKk+t3PDD3aOY9Zgrk7jQr7LgOM9cN8ljGSMXZSWmCR0/ijIFd3V90yp9VT6mEBNx3nSOQ2xkKjqQY3WADPD/7zoAAYBdI+VVog4JSUb5ikYzVLQC3XpdJKwG7VDYMUBJ9dm1AZwKst0DTAWhIydZxlriFAohBifeklMgIchs2V3akwDqXQK4zw3RCWmzR7sM0YCaafme+9L2yuhA3A7bAkPeVrtGg2yXfdpg9zD7VUAA4jnxOJ/XpfVTvbeg9dv76bpz+zGvR7bZYXWUBD6zOBDzwGId+fhrNwV5sEzo/WU7YpYddEfgzfQA6D+M9TOcRuj4HhiEAcJEZBiCIJgFcBr6DoFMDQKtSsLAlgfhAjs7+iX4pwJaXEUDXH8AsLXIWVwNclSYJQfIA0/0YgNhpgF0vDLti2OiKgUoAqmCR0tcocDUEuiaBCiAHu1JU3ruA3BDn30g4Un1MNcd9yXsAYtXA3wV6L8ncX+YAgjfwjWdLDo/G+SyXdxkAT489QX6L96GUPGo5gyihd7UJs+XtbEUgkaYysNsXYNcYiilhhl1L2jY+B3Zd0ObKA5DbeFgeFxLIDXECzFnxTc0nwQTACeAF/BDs1qJOG3nYitVdZ76cbUcGQAXgrpVQ/pn0PinwG8SPV3dSkw6Bv3Rgd1t5sFjg4wK4D0fw/lBIfAUuQb0nkqTrOvzu7/4u/vIv/xIvfOELAQCf/OQncfbsWZw+fXrr+jYGui996Uvx7Gc/Gy9+8YvxhV/4hXjrW9+Kr//6r9/6hCdy6eUwTLF+dw+dk7emRAyUIFWuFKIEeMkc0h10MA/sw5+/Hwg+BqCJZsiKLQKgppKLE2qADAa76vgQQlSYbUcsmrDN8XLFlEzy6roAdIAMT8Zbiii6tLDGwKw6YJ/YqGZ/F2Z1CsbPowKKzEfOwqNBxwCrb/qosKS2RArE5Ic+ZzUrstiufJkC3INFjLDczwP8TgBmHm7eYzZfYXe2wqnZEnvtEnvNEjPbY+66yIhG5ZFN/nyw6IokoaU1gzYhpD2GIDgESStkserZN7m38D0FRwqdJTQb1M0a8n317HPZdQ5Lk9IeiTIxs90oq1u7njHR4LmMJp0BXq/O03TVurywgz0xqdkDNFBMLiu00WQ5gVxrPbuc5oosTIi+zxYYRJbWJovks14AXXkfY0R0pFzSgZRf7wzCDqhPO6CfW8wb+pwMQG68r9QvQt8D957H6duuxvLcDPveITSA6Qz8HNi/imeXmPWyHUV4dssAtwjs3uDZfJpArl31MCtLgFeznzyJFc8d/XRNBLkJrExIoP8iKwUkIDvYNwfAhsEpvZfc+F7KvWJ0GeAyYEfvga4jF4vA6wBiQCqNmNhsWefNnQ5ApQBvwebqeAWRFSteDwXphqBFxnYv95/ayxgg9BQd3/NYaxi7i9WDzM6RiS2/m23qu97RBGBjDZy1cXIwmiLrR4ac3aXf4l4i6EtNCeQmzJHVFeCvJhjFhHkAdlVMAQGHRuZ+yjE6tr1KIdSEFIhKQG7DpsqNj5NfwuJK2jdqiyGgorYMMepyDzEKILAr/smT96sm5EZZXbWOcrscz7/V/qP6USTDC2Ab/zTj7MEmzCadj9tefPePA+wOLjNsZ8L8YJg8P1hRkx+uLPaJXJ7y0Y9+FM961rPwsY99DIvFAs94xjNw5swZvOENb8DBwQF+8id/cus6twpGdeONN+K//bf/hh//8R/H8573PDzhCU9A0+RV/MEf/MHWF3Ein6aiPoSyHIzMaFtg1sLs7AAXLmb+tdEMMvPNHRlohUWSU1ozBMl9D7vqETpKL0SAF1GzI53LpFQcMEkhMQJ2DUznYLsWZtnB7B/A3/8AzMEBfUAdR3N2DUV4bpLCCWMpTgv7olmX8qNmtydsYzCjtwsUM46iQDFgDw5kqjwjkBtmHnaHQO6OArmn2wV23Apz26O1fZaLNvm0WgCe/FL5WsfAIikLQ185UT51wK2uJ5Plvjc5yJWI3XJ/FgiwMdZZbwI6SwGsnPUwfRqbfOgH+TfTtiHQLVndKclhvmUT5sDBclz9IGMJU1q+eKUQiw+g9r1zTQ/nPBznMXY2KbS6jSFMAwx6eWWQmiyzwAji9807RJaNGV2PCELSxI+hqK+slPczg34H6PYMzl55FrjzLt6xALnRWV/JcoX23gV272wAWPiG8/KuAvm471J/NT0QlgaQwHEGCI5z+i49QkORzWENjOWgYJodDaGeU1sB3hRIKn/pDAzQh/RSCStc08rVOSKglXsXUFsBuQMfXP4NXRfZ3NB1iaHWaZHkmuVPAlEJo1uYK3sJSJUBXxRsrkkWLNK5ZZyObYMseFBEADWwq38FNPPwbXxgKxWoP8Ntx4A0aL9dT11VTJqdQe8DnDVwdjoa/CZBqfRNEBhBNGEemPTqG/aGo6MLFtTojN4zQyYWdN8BGbCWeqP1kAWZKzsADbsxNB5ggGuiZQf9CrOt26BsCwH5kgPYcxAqDXYB+haZXt1v/EanMqxjdTOAq7cjgtvIePD81QABAABJREFU6qruU30u3C+C7Kj7SNZvwBMp5Dud/HXB42vgnMYmWv9bm17TKbAr7Vcun4A8kk+bdhAl9VLUeyIAgH/1r/4VnvKUp+BDH/pQZjn8jd/4jfgX/+JfHKrOraMuf/SjH8Wv/Mqv4KqrrsI3fMM3DIDuiXwai5h5gWfI9ZcMMqNNynI560sfdo4EPLdYnWkAewotAHv//fALZb5cglztpyfrIzJIWcLsiVl2MK2DdTZjdePYbZQSYkDmzVb5bwULMbsjdriH6XqEixdhLu7Dzls0Mwc/s+g5d23Mb2kAwIq+i9AEGGcSPlftGm9TKUq6TMzDk3mvvv7A6YQY5M497G5H5sqzFU7NVhHknmqW2HUrNIZ8hh085541sLBYQQYPC88OVck3l5tWMyjKPLkMDhMABXLpl9hcFwMjwUsqKpPuTUxJjUEwFr0NsL1F5yyWXZOZM3pr4IOHNX7yg7xpxPPaMh0fuFUcOrWN9MQAa1z0BfQmwDtirJN9HT3vmEaIzRJrIFdMNkVCBLmIAXbq7gbyx2A3Y3MJ7EazU3YvSDdM7ykM4GdAtwN0pwOWZ4GLN57F3v8hwBkk6jGA0qoiStvAePLH9/cY2D5gdp7MklenHXwr5qyC2HMQStYJUmajYm2toUirneeBxSdgWRFJ6yL1GoCjewdi1qGGMcl5q0UPRTpCsga0uuHji07WJJrJRd8Te+t7YNVRvm8BvADl+nWO2tRxMC7HKZEaR3lzGwvfkO+xl0k1CWSUMbgjTK4sG8R2GXQjk8ZGDVoCu3Rku0o/0kO0PJoAcvPQ45acgMs9nyTAMkAxFOQtkJ+5c559d3M2sybR2KAYh2oSWV15l7jQQJswK7RPqChyuoHBYTAhWkcEw5+viNrU7XJ7i9ly9NN3IbkwKOsOPSZYNS5IapxybDL8MHoFeMGmyj0IIMYAVpbKxT/7UKwuW2OMsbqBhwgNdqW/TA3D2gqsxurGKMwylilgHS2zPbe1AryQRwhZHo/GbDAEd9JPaoCY6jOXJBXQgyGbANlPC7CbjVHHXO+JAADe97734fd+7/cwm82y8htuuAGf+MQnDlXnVij1bW97G77ru74LX/u1X4s//uM/xqMe9ahDnfSRLptEcD1qIKrLwtFfZsjlw6OCmiS/sEBRiltwRGJSlnzjsDplMW8tdv72DEzXZblwY5ogAb2ZCV/R/mz6XGV1QgAWS5jFDLZ1BD4bSncxALtQ182nIRM/+epb3r9F43fJerBxdI5VB7vo4A4aNDsW/YGJeRJJOQIE7IY+kCJnJQ9iPmGQLgZphrEAKYAoTiGP5NlyhOW5h90hkLs7X+L0fImz8wMCuW6JU80Cc9tFkAuA889a9IYU+BUAGwz7sY4wl0AV5GqAKwFmvE8my32ngk9Fn1HyFU2MLjPbDFRCb9B3Dp0lP11nLWyvrsuCgkYJGN3StKsGcONvtFFNgN96yvVp+pDtT8qkQ28D+j7A2sTUUx2kSJnCJ7exyi+R2ZrSH5Ham0E1sy6DSRKWIGWxHyGBXK/KRdRkj28oLVV3OmB1xiPMAu5+QoPTf/Ro9J+4Hcam1F6D9y54mNkM5uwZ9LstvGOQe7/H3sfOw/7tvQRku44AoLMwu7vw506jPztHv9ugn3NUZPB44egpWADeMKvrDLGxwSI5eiogWnv8Yuos48nYPmrbENwWwFZMpzNGl3/F71abJvc9WZ30ffTHFYBr2oYiTrctgdy2IZDbNgitQ2gdfGsRWga5LY9njViUGPb9lF8kNleZMMdnzc1Qfm54bisNS4z3hm2V/lLEaQY7bD3geTLABJqok9fMCGUMo5osmTPLZF8IJjKbomyXAdrGUmzJJU6JzKMavs8I7CUNj5XJDwPxnRa2MwWyCvHdCnKPEdnlYzWBWxR++hR0at3E11hwLh8MnNy35P327Bqg0F8IlgEveMINGVjd1lcXkf2WwF783QSSr7/uR/p5VL55Rl61OGYFBXrTdRAwDxAT5tjO0h4Mdj2E1aWrkNd9CuzKNUq1xwHwyjrWrdO1TQNnH+yDZr6czvlpAHZP5JKK9x59aXUJyvxz5syZQ9W5MdB91rOehd///d/Hj//4j+Of/bN/dqiTfTrIIyG10BgTNLVvdox83PVynAEnBcrYkPxUG2X1Zwj0drvEDKz2ZpjfcTXCXXfT9uA56IRFxuxGwKvaX9bF3Fn2A6JiSoxJD7PqYFYNbOvgOw560wcVKEVyJiIpJnyLvRiyeYOVt3RDgV6u6LMLkB/hsoc7sGhmdJ9iSuiiYm0RWja1tCGaw4lyUYmPkymT0UwQiOyzKK2+5VyVMwa5O0OQe6ZZ4FSzwJ5dDkyWbQhirQxvDBwMvAlwIHbSYhhpOYvWHcgPN6h1ArrIQW7PZoka5Er0X8nFHBVrViwtyPTcBfS9xco6lIGaQjCR8aDmMfxb/zBrJaEEuRrgJhDr+V5JuyOwG/J9+nRdnXEUAManCMgAIqui/e4a18PZgNb1VWVWfO7ivTJzU0pMCxb/kE2QmKAig6u+JFYXgPQlwM8panfY9XCnVnjgccBdX3UdrvrtB9Dfc18CuTogFQDjHNyVV6C/+gyWV7RYnSLzc7ffw3zqbvR33V2Jkn4vzB0N2iuvQHP1FejO7aDfbQjUxesiMGeMIYuIzsM4EFC0PoFLYVmj1owBoDU1t4i4bwFsNZBVZYP9YnAsRAAb20b7NVsDYwnEGskbbJW5cuMI3HIO4NASk+tloq618M5Q2zjKRZuD2zUgV5stK5CQ2gPRbFkYuZK1GzsumsLLMSHABpPGMQUhyJSUTkRKvZrHC5aDVxPTGjhyubWBLFdkQolPXfPNl7PR88jflTRuyGRaMlQ2oElIyTmLALIAsHxj/M3ITJkt7UMAt4iyHsfoEBld8dHXpsrWejRNzuK2auJrKt2STMBl47NibYMJMZgewDm/DU822PT6bs3qIi3HVExe7Qeodq2InLMU9foaD7I5Vt/AICbMLiRW17NfLI951I/YB9xbWEs7assYYAh2a+bM8ltjdS+lPJhgd9N7ekRHYo7j1CWo90QAAM94xjPwxje+EW9961sB0Hv8wAMP4FWvehWe85znHKrOjVFZ3/f4wz/8wxOQOyGbgtwpNvdSDQRr/ZPWHG+UYm0AlLPl9JuXDxQfE/hjnkyzfMM+o/NADNEusDoNLM8BiysNLlxncN8TroC78hz537HZnhF/PLVe+uLGcipI242lC7PM9nUdRV9e9TCrHnbZwwjYzVKqIEWKZmVPclL6xnC6HoNu16Dbdej3ZvCndhB256SUBmb3lp6D6oAD63BqpSXgluRvaJYWprOA+Kcy6At9MjWN5qb8FwEKEE0PKZWQBJ7yCDs9mSsXIPdse4Bz7T6uaC/iXLOPPbfEnl1ix66wY1doTR//RpWpkT6XBYLhdTFV7r1Bx5GWvTccWZrNeSXNjbS59hv1/EwU2wv25yWwbDl6s4u5iLtgsfJ8LgbdPhh0KoK0fjdr77O+dwGw1ni0tkdrPFrjMbeUd3hmO8xsj5nrsONW2G3ob+567LQd5m2HWdOhbShv8WzWoW17/uvQOI/W9Zg1PVpeFoW2deRz3Bj+U8F45P3U72wp2ldX/L+1+ejgEJks4bQn8b2dBZhZj93dJU49+gL+9snAA1/9uXCPKqLym/Qe2tOnEK48i+UVcyzPkG/u7ILH7l/dBc8gF0AR1MojLJfo77wLuONuNPdcRHNhBbfoU/5qAzbdNRHwxeUm5ceFY59c+ZNLDOTTa3oOBNWR+TBWHbBcwSxWMAdLmAX/7S/iH/YPgP0DhIv7CPsHCBcPEA4WCAcH9LdYIKxWCF2XTJFlIs46YNbGmARmdxfm1CmY06dhzp6GOXsGOHca4exphDN78Kf3EE7vwp/ZQX9mjv7UDP2plpjuvQbdjkO/69DvWPQ7hvyo2V1Cfn2DlJtV59aNwBfJhFn/aQBsUlkOeIZfk8TYIgJe24PHVzXWcp5myauu86ybFfllmxWPDStLk1urZAXSdZSOTMaAaDGi/vS8YPku1EQmnvg1iBOORixuDP8yUBWAKush+tiGGFQqtPmfn3le9kATgDbAtB62pcjKTUPjQtP0aF1PY0ZDY0DL48GM4ym0lvfhv8T20lih2V/t25usTcDpifh7LhOG8U+edeDnHZC+7zJZEvLYEPEvZOsCZHX/KsHzlMRxSh6ofC8yCxX+jvCEBP3x2CdBHkMaC4P6To1lmqilqxqT3NpGTbIUx5X1rFuv1Vk///GRL5vqp2X2ghM5fnnzm9+MG2+8ETs7O3jyk5+M9773vZP7v+c978GTn/xk7Ozs4HGPe9wgqNOf/Mmf4HnPex4e+9jHwhiDN77xjYc6bwgBN998M6677jrs7u7i6U9/Ov7kT/5k4/v60R/9UbznPe/BE5/4RBwcHOCFL3whHvvYx+ITn/gEXv/6129cj5aNGd13v/vdhzrBp4tcSib3oR4wONPAQDSLG91kTRG4Qz5aFpAp3ODSbLnMDvcWMA37dwb+6HEewXtmFqc+eQOaD/wZwqpDFt/HmsTatOpCVaRmY/MZTUkvZNqG9glegV0H2zoKcuMoMJSL/mxkpiWzulGfExDQGPRtgO0M+h0ymzW+pV1WxCjbznMEWQ/Xmug/l9nF8Qc6eAgtnDO7KiIzggBCZADcRDM4asPQhjy68nyJM/MlTs8WuGK2j7PtAc40B9izS+y5BVqTTEd03xazXBc8OjiaLZ7o+9psuZdfBriJ0TUR5EZFRPxytdlyQGG6nH6DBQEYngzorYG1NvrJWhOAnoJUgU3VajPv1oTRWfISMArIlXRGZfqlxgDOBDTBYGlSbl9jApx3cCagdwn0S75qE68ZA5NEx+BWA1gfDFk4Wo+OzaUJuwa2NpAJKFHokX4jyMXgzxTdLPprxneTlHjXENN8er7EXTcAt//ds3h0cyPOfug08Kk74fcPokWF3ZnDnDmD7swOulMO3hk0BwGnPnYR/Sduq3eiaIXhEfoe/t774ObsamAJtPqW31EDNh3liRD2O5SAUuQvSaph6BH9SbPAULxs1PLA1FgtR2aWHoZ0jnTtMegVLRtj2M+WyyXqszEUhE+VZSmPBLBb2i80KsAUmyXrYFO+YGv9ALwWLG4BPqpAQ9aFSZMydYwwf2OhEoTVlC5pgrBlmtej5XR++lZkzK58KwJRjt7xVn4+xoQI2ACTwOrExM+kCEMcmAGFBJkiVtDE6+HbKH4zFlffKsCgmECgsUEFokvuC856NI4mvRorZssJvG7C5nq23uhAtrteWZjYbJ2/7/x81rG6Meo0p1sKESSbZMxR9hGb2sKI/zKQrAXU9ZePRxtjDMYseQ7C6kbzZhOfR+A+KP1P++pGn13uJxRjYjw4lVzaFKs7xnKui768iQkzsBmzC2zvrjN2TVTX+PkOs+/lIHGy7hLUu4380i/9Em666Sa8+c1vxld91Vfhp37qp/DsZz8bH/7wh/HZn/3Zg/1vvfVWPOc5z8FLXvISvOMd78Dv/d7v4aUvfSke9ahH4XnPex4A4OLFi3jc4x6H5z//+fjO7/zOQ5/3DW94A37kR34EP/MzP4PP+7zPw2te8xo84xnPwJ/92Z9tZHp83XXX4YMf/CDe+c534g/+4A/gvceLX/xi/JN/8k+wu7u7XUOxmBBGInR8Gsn58+dx7tw5POe3X4z21Gz9AYVsA3IPw+aum9kbzAxmrJQZHBOKsmhmqpfVjJykY9ABPALSupj+xNlQSYETTMyZmLGPHHzHeAP0iOaomZlkk8AZAOz95Qw3/Je74P/81mSGzIyINnGU5YFvYMgHeDObkd9bCOT7Np/B7O4i7M4R9ubo94gh6XYd+h2Dbm7Qz5kNaU1SGgWr98Q+CFPbHHi0Fz2aiz3cfgd7QFFTQ+vgd1p0pxp0exarPYvVnqFz7JDfo58RCxsapMibLsTZ8AECUW2JkHzcKE1FIB+vmYebEcjdm69wer7AmdkCV8wu4myzwNlmH6fdIoJc8csFgFVosAoOB77FKjgsfIOFb+Ly0jfElAaLZe/QBWJNe2/RBf71NkZWJoA7BLle2NzOIKyIzTYrZrhXBjbmcTXq/hBZazHLNq2HnfWRBWldH9nRmomfBo36VxQHCWCVsbkjIFfn8NURqrtgsegbbiP6FZZZ2ke/fzqgjFXX7IprkfdXJhB0ffEZ9Nz23L59T/7Q0Tqgs9FiwKzITNyuDDNsbDKuXGYonVBAvxvQn/ZwZ5c4d+Yirtrbhw8GH7vjKrj/s4srPxJw7i8egLv9HoTz9yN0HczuDnD1lVg95iz2P2OGfm4wv7fHqQ99At1tnxq+q8rkOb28Fu7Kc8BnXAV/dhfdqRZ+Rua6GRAL4NzYnCO741/Jv8u5d6u5a9V69JWVfLacB1ibIjMNRiDWMpC1js2QLa1z3t4IZq1N+XsteJuJvzH3rY6cLMscDK+Moixp0MqcuNVoylMMLTAKMESfNgJ2+TflXZZ2p2Ubf0Papuqh8/L1N0hBCYV9nnE5j4u+AbGgbZ5XVtJxWZesGYwNGXDLLZHye9OaUGnxEC0fAPquCaMX9wPE/zaaxupJJO6Tuc+7TIrQsjDExvH7XfjilmPYzPZxXKA85z4bF0RkfJDc57WxWcp6z5YuysJGvucyAZlbEqV7jG4lRU5k/X2PFlFixu1VH9J9YkQGfZVZ4qC+x8GlSd7o/sMsc5xMcD4G/NN9xUrUahW9OjHdKWXTwHUEGHxDTLGeTagWN6r7ZQ0U1iZZa7JNsKvjAL3bAtjVhSV+4+v+I+677z6cPXv2yOd/sEQwwmP/n/8Hdmfn2Ov3Bwf46+//fnz84x/P2mU+n2M+nw/2f+pTn4ov/dIvxVve8pZY9oQnPAHPfe5z8brXvW6w/ytf+Uq8613vwkc+8pFY9m3f9m340Ic+hFtuuWWw/2Mf+1jcdNNNuOmmm7Y6bwgB1113HW666Sa88pWvBAAsFgtcc801eP3rX49v/dZv3bxRjlFOQiYfUg7D4B4HyH0wRXxPRsuNZnTT9DVPABNUMuzHhOIbFpDMmkLyf6V8dyClZd6jnXeYz1e4uNvh48ur8dn7C/Qf/yQpmz6ZJkdg6xwoOyAio0uKs4v+gqZpCeQCzNZ4ZlPYD85RPlyZmZakAyZQCiDjA0Vd1oq1J0UuKW9KOWUF1QRDSveqh11a2MbANYGjoFKKDKnPhJRPkoKvmOiHlHW9gBRpmS8yKrGSc3Hm0cw6zOcddmcrnJkvcKZd4OxsH1e0+zjbHOBcc5H8ck2PmUm5X5ehgYWHhYEzHqvgkjIV9bT6xy4LQoU0MVIFuVGZglKkwNFKk1JkdXohGKAPMbBN8CDzZWZ2vaW6k4LrANdDgrF4E8jXLaQoxXn/Xq84ZObLrGzqOhpDY4UNFhYBq0CMa+ctGuOx9A69sWidYlyk7goYb6zPALiX+jj6tQXdF3VB9asVci1yvhElMzJzwoQUDGDcj+s50y7wmKvvw990Fvf6HQR3Gmd2GrSfmsPefwFoGvidFr6xMIEmhtrzK4T7H0jvsPjblxcbyz2ZE7OJMYFWntySa5XbsWrFcQOwiUo2sgmLy8Ggsvy1bGocIoPLCqIlwGqcS0DWOQK2HA05AltryZ9WAdmNAK0wr2JiXDCxgxy4EeDWQa0AhCprK00lbVj59Aigi6+/TWycRNlNkfUn3h0NbAxXHMB+85RGygprKNeykotUzG4wiAw7PE/EevZUoTgPkqqN/tL3iuZQNlPU5fum/XVlljOA35HAEZmD3I+8NEB6/+SdlIrF/BkEtIzkyw4ZwHXM4IrLgmN3BXJbmHYn8UbGloDOO0qzBkBiLchEmg/EejvDlg8M6iKra9J4EFndaO5lUmAqS3GnY7Apk15dHZwKAYkVD3nfqg67qj+OMrzyHLg/Bf4+RlZX+ktM5xbUGCG+07w/juavG9u/Ul4ysJrZrbGgtTrLfaReYDPAq3XYw4LeRxpju1Y2mIw5dL0Arr/++qz4Va96FW6++easbLlc4gMf+AC+93u/Nyt/5jOfife///3V6m+55RY885nPzMq+7uu+Dm9/+9uxWq3Qtu3aS9zkvLfeeituv/327Fzz+RxPe9rT8P73v39joPtnf/ZneNOb3oSPfOQjMMbgC77gC/Dt3/7t+IIv+IKNji/lBOhuKccNcI9bamzuNjIGboGkFGgGeW3uQas++FHRCgRkZFvgD58BYFMahXbWYW9niXO7B7ju7Hl84qvO4a/b63DDu+YIf/lRUkBZhMWFD4rd9YWfX4gsiyisMdqptTDLFf1aC8umgi7eqosz1L4DMylhYH5FfmeJRcoGxZ5GSWMM7KKHE3NDR4G5yLSSFIoeSekTZQ7BxNRH1S4lCqz4h7UebubRtB3msw578yVOz5Y4N9vHufYAV7QXcbY5wBl3gNPuADtmiZmi7nrlwi9BLQTsapE+py0EMr+kYNQfolWA50jL3pOvFDEGNqUTinldFTPA7Zw6ICs5niIyBxci2KW6AwW6kjsybLIXTGbqa02ApF4ENvtwuwiMxbSYWVeuRfpObwJs4H3YZHllHDrr0fgenXeRadHtmLHLRpjjPD2SNT3dCz//0Keoswm8rxkHSjxZrGsQI24IiVmhfikTF9Z4fMbuA1g9yuL2zgJhBu92cWbmMLtrDtN5Brp8j/yuTBoWRZtJr4oo0JfYsJriVcvALl8zzXXwRInkLwbYbJm14r4HOpXSR8BuDGZngLblCTFibY0KDAXLqX6cRXAumhvDUsofCJBtKoBWfGXtENCWoHbSBLkGbmugVgPbot2qXUaDXH4PI9iVvqHAkNSjwVHGogZEQKKdYE3P2EP6l8lBluXout4QWPBkNIsAS5Yv2nzZAoZH0gR4Q/pOhXFAXjNnzlx0VFNJDmvddrJKXTsMmlUiGxOgJxZRAK4EoJNgU62V334AcJvI5Mq4k+5HLEo8DDy3cedpslIm+mQ8dtYjBMeANUCiL8t1ymOKEyECcksTZp3qx4LAvzdDsMvtYmQCQfWtCHjlWVT67VgfjWOBArb1ZTkXTzQEw2bLMoEf4nPVYFcuTMoE7BrkgLQEr9uAXRR11dalDDga4KV6cr12W+D7aQd4L5HUGN1S7rzzTvR9j2uuuSYrv+aaa3D77bdX67399tur+3ddhzvvvBOPecxj1l7bJueV39o+H/3oR9eeAwD+03/6T/jH//gf4ylPeQq+4iu+AgDwP/7H/8AXfdEX4Rd+4Rfw/Oc/f6N6tJwA3Qk5Dr/bTUDuNmzuOrPl45Lc/5ZnMdUYplldPgJAiD4ugAGsT5GKBVwKu6QBcKw0mQ81bY+d2Qqn50ucmx3g6vkF3HD6bvz5//Vo/PlnPAbXv/ssdv/fv4K//wHy242mygmoZSAXIKVUfOQAoG1hZ4aurWmI5Z21xMAApEB7CpQSVvSFFtM82yE380MOdO0yUFCVnswjTSdBbgIpd6zY2sagcUCw5HvnbIhKXwZ2YdJsYlRg0+RBnECQdBSth2s8ZvMV5m2HvdmK/HHn+zgXWdx9nHP7OOP2sWMo4JTjD1wfLBAQfTw3lcyfN6RgHtHsnU2YZVlArh+YxSGBXKX46Hyc5B7MDDvPVxhP/SD0lA/Z9xY9K7fe0zJAvq+dt2isT0ba3C2zT7wBo4YSYCbmFkgKhcPQfNCyImVDQGN6dMGhMZ7Mlxnw+mA41++wvUvAO2xzg85TXzEREDPYrT2kQNpqaY5pgsk6dOB2i6waBFiFpGRyHT4YrHoHHyz2miWu2XsA3aMd7vRnAczgmxlO7Tm0D3RkchujJRMQNPMZ/IWLGZgdXrc8+PQOS5AjiMKq+2tUiA29Mx7MH1XqDYFNlhnsCqvrmaWS/LXOply2DHCDE7bWAQ2ztM4mf9pYRlGhYWWiLDc7rjG0UObIteBQ2oQzAlkFcBPIDXVAOyW1CRAGCDG1kgK7MjZFsBFBEqL/5dh5DAJPPNC3JgIl7oPGmAh+vUHyvUYJdum/UEThpefP/usCvAM2mwiS+1cAWRokdcnUWEYaenRimLYlc2pMRlhvXR/9cGe2R8Ng1yKgsX3mPlGKBUXG74OpsrkhJDY3IF2PicshTVIE7oMR26qxQbej9EEQ6B0Du9K/ggnRlHkAeAcPQfVt1cYDkecOqa/C6gqY5jK5g6DOHa+B9R1nKI6IjLXyfEuwC17fBOzScxqCY32MXpe6tawDvPocm8hhgW9pkfSIE92vjrteAGfPnt3YpDvqsVJFCIOydfvXyo/jvNtem5bv+Z7vwfd93/fhB37gB7LyV73qVXjlK195AnSPKj7YYwG3wNEA7ti2hzooFQDUWN1UnsCufCyCVopYR0ofsRDLZYbcOo+GI0ruzChK7V6zxBXtRTx6dj8+d+8O3HrFp/C7N3wu7Bd/Pq79/QPM/+JT8PedBw4WyX8XgImmyMS0xGUBtYWi6hUDE1oHz5FafSMaGxj4iomlun8P9gNkoLvyxNoueo7WuqI0QyEg9I5mh62NSrBzITNPFAVWlDpS5gBWGUhhyAAuyNybI3U6juS7O1vh1GyJM7MFzrYHbKq8zyD3Is64A+yYFXbsEo6fRw8Dy/PXPSxcYJPciQG+ZHDLfLnC5sZtEumSg1IlP25ENjdLc8PAV5ajLikAN6RlirIZovmy4fQ9veE6+d6mwO420SESs5sAprC6EtwqLgczALw+GKx47Ims+IiCUlVwDJ87CJObK95HEc3GZcBJ78Pm5ytvsfQOewDOzvaBM4Qb78ZZBNeinzfYucfCLQMkeJvxwOp0g/bKc8Dd9yJPGVacSEVuRtsQ+AMIpIr7g553K8WALSbCcHM2YPE5HHJzZEnno1P7NPIOy18CtjFIlDXkb+8SsB340mqfWg12C19bGRdygBuGQFfdc5W5lc0KDOhfUymLkwkeEJNTANFEVbP+dB1pnMwArzGq0lR3BLsmUPA5E2AVwDcW5C9uEuMrY+IA7HKdITuBgbcM2IygHJOZMK/Txcr3qr7/+LunA2JpX1BnOPCUArjaD5dY3JzNdSb55sYxCDmAEkbXgtpR2FxrPBqeWBOQHIMpsTlzAr4pr25MJWhBIFZAbnymRrG6iMsR7AbuO77QB+RhhRzwAqmPlqxutj7W3rouBXLHWF0NgqlvJACvJ//XBafaBOxCH6vY3dwdbNyUuSybKpdziGwDeqne7YHv1HWfyOHlMz7jM+CcG7C3d9xxx4BJFbn22mur+zdNg6uvvrp6zGHOe+211wIgZlezxFPXVsrtt99eze7zT//pP8UP/dAPbVRHKSdA9xhlGxPlbUFuTaaCUB2X5IMyIqtLzJEo2now16oGL+uPXMYCy24ppYHjgBvztsNO03E6lg5z22HPLnFNey8eP/8U/s6pj+P9n/k5+B9f8liY//PZOPPXwOnbOszuXcEerMhvTyuuECXXTDIuA784a3IlMr/sDOCangFuF2CXPeyCg1BxKpKwXAHBw8zn9IFvLGxLvrq25QBADmwSTdGkJVgr5Jdnw/k7TCCXU1cIi9vOKHXN3nyJ0+0SZ2YHONMucK7dx5XNRZxrLuKMPYhM7o5ZRZPlHgaWtBKs1nwLy4+fDyk9jzZnFnArAVwSuyvbuMsImxvXpX0RFaDMfFKzR7KPBynXKgVTMMQeGyN8v1AKdbBbmu+XikxN9IdfWF1hx8WE2YYQo1YPAC8rpLoNAVJU3cg5e4VqRHm1xkYlxvC1Sz7RUSW+6NiaiUvghDcKaIo7A+CJBErlRAG2ds0KV84vAjw5fbc9C9+26PYsZvfz+yITGHBorz2H9u5z6O++Z+Qik9hZSwyrURdDsymkPNuxG10jYqfZNDCOlXfxs21cztpqgNsY+PjL44gAWx0kSgCuBrcR/BbA1qRlWBkT1DpSecZyxeV8Iq4qEcBW3q0wLAeAmJPUFDP0MvSXfcemiSnx2836l3xPPCIYAuc7NeyOQMCWn4cCuHEC0IACqRn2DZVqBSAJuJFo9RFg5YA3b5T1MpyHGR5bBr/SfvOO301nVZofBrhNZqacA9yWTZUlz3lpXSJCIJZ891feZfnO9cRYjFAdGVz+CyZec+aXqxGqDCy6+aR/WHpQGdiVdZlg4ElxQofIQGgEuGWzqmuZUpVMGHmaCvBqVldyIacJs2TCDKz319WRljXYBRCPmYrGXGN35Rio+o4KePW50vUdHviuA72PJHAbh4tLUO+mMpvN8OQnPxnvfve78Y3f+I2x/N3vfje+4Ru+oXrMV3zFV+DXf/3Xs7Lf+Z3fwVOe8pSN/HM3Pe+NN96Ia6+9Fu9+97vxJV/yJQDIt/c973nPxqmBnv70p+O9730vPvdzPzcrf9/73oev/uqv3qiOUk6A7hFlW3C57qU/rqBUY/tPmTrLkC6KeGm+HAKZj3mk8qEJc6pJjsnNgPI3Wj6k5J9EH/hZ02Pmesxdh5nrMLNdVOQdAq5yD+C65h58wfw2PO2KP8cHPuex+NBd1+Fjn7oC9s4dzO7dQ3MBaPYD7BJwKwKhUWnjSwyiFLNCFk2RtUlyof/oHK62T3l2LUL0HTV9IFPlFeXhNAdLyqV54SIobwFg2gZgk2bbs5lzG2B7wHO+WNuTsmu8UtbidauIo+yLq1ncvZZMlc+2BzjDTO45t88gdx9n3QH2zAI7dgUHalfN5A78cAuT5OSPS6bINd9wbbacRe32JirS0GwugyYjeYEL5RvIu1nc7jnoTGa+jAh2hdU1bPJqAwVmMYHMda1WYAyD0ZBOJoFv1omOVC1ikQCvJdoKHgYr8ZMLBm3osQou+tIBAmLH3SciM8BKrDZXHsudC0yA3biDUvqNKuMDI6AC4rMJ3sD3FN151Tss+wa+WWLXrdDsPEDvrQ24szmDfmeG7l6L5iIoZ2oH+BYwYY7Ti8+E8wH9fecRWV1lrgyArDRmMxjLqpmwuT0r1jz5sU5vCIYAUQS31iI0IGAr5RJAKgO1FqG148BWM7YjwHZQpthbMlUOAzNlaKBrAqI/vjYj1+BWP2cT8smMoH5ZkSefW3oHg3qnxFoiTkQlvV8vpPExgmQkpleB3sjkxXIOHIQEduV9j5OIAnht4PzpBJBsR+a3MYgcKA1MBLvx1SkAsJHAZdQuRvYwmPTZnQK2JSOcBYJTj0PeTydMboymngCuMx4z168FuI3tM8sRLWRmS/EBOu/Q2j7O7/nox08TY57Hi6B+ZQzxRkysTboPAZkw6VnquBvesKl4DnZjHxQ9IMiYn/qE8dJ/1Es8YoowmNzRIjqJArXRfBkmA9TS5w1fk4wrgLIQEZ3nEGA3Y8tDSj0kz63G7gLrAW92TKVsqryUmh57GP/e44jkfCLr5eUvfzm+5Vu+JfqxvvWtb8XHPvYxfNu3fRsA4Pu+7/vwiU98Aj/3cz8HgCIs//iP/zhe/vKX4yUveQluueUWvP3tb8c73/nOWOdyucSHP/zhuPyJT3wCH/zgB3H69OkIOted1xiDm266Ca997Wvx+Mc/Ho9//OPx2te+Fnt7e3jhC1+40b19/dd/PV75ylfiAx/4AL78y78cAPno/vIv/zJe/epX413vele27yZyAnS3lMOyppsA1W1A7jZs7rpzTwWg0ttL4CvXkR2vPvjRzEmzqoUiIf5JBojBN2aux7zpMHM9ZvyBdxxhVnxGT5kOVzcLXN+cxxftfBwfP3c1/uy6x+BPL1yDj91/Fe584BTufWCOcLGBWVjYJaVLMR3YLLZyo7UmUEpbBnI59YpdBdilobRCbUDDim/DY7+lmyaQJTNnbYvQNolZ1jPitWsShdaCUic0lEonRlRu+8ji7s5WON0ucapd4NzsAOfa/eiLS6bK+zhlFzhlltEvNz5npjpWyEGuBKUiUDsO+XIAnJstx7RUgz8khUMiYQqw9Sbp0/qveDb6zwTGSKKYa1aXgW5vDOAVPW7T25P869Iy9W8LCfw0pTDINmd8BLkpSnIPDwMHsl6g9EOWIlkHeodSWxPDKx21ZHnJukLYXA8r16oaSJTqgZRlDG4lNyj4cYhSm4FbDaa4vcRHt/MWi95h6R0WfYNdt8KpZhGZqZnrccfsNA52d9Ccd3D7Bm4B2KWhlDH2FE63N6D96N/C33kXQtcNXRFms+iKgBAoNVDnYZyl4G+y+xiry+CKzH0N0+3ksqC0VQRrgcZG94UIatmVYZKxjaA2lUVf2wLYxjzXmq3V62VaseJXTEqJSS2ejbxOxTtTTYEjk2li+h8YsDDwEN93wxNIWYVi2hkUUBXQ6smUNYIZK76SDHAVCM4kKJDL467tEU2YJZYYBa4iP1QYUJR2MGsMNq3tqcIIdmVQMQzMFNhNnQT1d0eV18CtBrZW7VempnHyzVO5cI0JawFuY/roGlF1k+BxoDfsBhG8MlmmcaKxPbxPQevkz5tk0m8NiqBUzOAbbiXDEabj2GDiOJIctLnVGewCbKnEGNMIo6oBZelbLaC3+iDio8qXp0S6qwLAkdU1Ed9ybJFkwgx9GVuAXaBirizVHBHwSt36mLEyXS6yzof2MOD3qEGtHvYSarMqx1TvFvKCF7wAd911F37gB34At912G570pCfhN3/zN3HDDTcAAG677TZ87GMfi/vfeOON+M3f/E1853d+J37iJ34C1113HX7sx34s5tAFgE9+8pORhQWAH/7hH8YP//AP42lPexp+93d/d6PzAuRju7+/j5e+9KW455578NSnPhW/8zu/s1EOXQB46UtfCgB485vfjDe/+c3VbQCB6r6vRiEZyEkeXaQcWc/8rX95qDy6U3IUgDu2rcbKloNS6TNZO7a2TyjXFXDJ1/P6BvtNXCuQz3Q79k2SGe1502HuOuw1S5xpFzjTHODK9iKubC7gUc39eJQ7j6vdBVxhl9gzgDMGyxBwn3f42/4UPra6Cn+zvBq3L8/ijsUZ3HOwh/PLOQ6WLRarBl1nszyimcKXAa/0a3pDfx0oz6gA3SXglqDfBefQXQRaPvBoDnrYRQ+7YoaXI3mE1sHPHPq5Qz+36Hcsuh3K1dvPkX5noPyRc8ob6Wcpv7Cb92jaDrMZBZvabVc4M1vgdLPAFbN9nGkOIot7hSMmV0Bua3gCgZlcHwyWINB1EFr68zNc8DMchBku+hkWvsVFP8OBb2P+3EXf8DLlzl36hlg979B78tvsehfzM/a9TemE+Bl4lccV0s4rA9uZmJ84LhfjWrBI+YZb+vUtEFoPSA7hxsM2KSel1aaCalkUT2NSGp8yT6UooEnx9FEBbVlBdfCRdZGJBKc++DJZIEA3/jLQ1RMGGvjSrz425ehdeWrzZU/PYuUdFl0T23/Z0fOg9udAYB21P3oDdJb6eSf93KS8qOIbzfqrgDY/49zFcw+722G+s8KpnSWu2N3Hudk+rpyRP3hjPRa+wd3LPdx28Rw+df9pPHB+F+GBBu6ihVsYuIsG7QPAzj0Be3d02LntAdi7ziM88ADCchUBr2kaYnR35sDOHGF3Dj9vEeYOvnUZy5pRcML6CksoUdElOBwQJ5zE15YAreU8zaleAaxemx1HgJvKMoAbQSwxtjHvpwa2wuQ6BoASPV3yq6o0NAbIogiXTGIpaZyGmmAa5jsXCwvxlY9pvtSv6Wmbzptr+/SuGk8TgTIhaNjyJVuPx/IzGbiY5JMHvqHJEN+CnnELzrkr7z8QmkDHNCFOIEB+TeD2BLdjpT2l7SrtWWNqS4Ar4FbvU+ZddQroyriyzgdXA9y2ALqZtQiSHqDHk87TuN6F5Fqgc3rLWK3H7Jh/m6OppzHbUIT8kGIsQCx0lFVOshYA9Rv9ba1Z65RlSMv8SOr9WgHcjOEVk/7CCiKbNDJAzKsr75kJ7CrEz0zlYbbZ+5Y/7/JZp+ef9BwggUsNMvU7W4LPwfrAIm7YMOPuNdOq/mGCR22bt3fxQIfffvbbLts8ujfe/NpLlkf31pv/78uuXS4XOWF0j1m2MTE+jJ/utiD3sFKyuMN1ArspEmXaT1/DmOKlPxARbJgUYbLhj7+OJulDAmIXwgxt8LDocMoAO8Zgx3mcs+dxXXM/7p3fhrv707irP427u9O4r9/Ffd0uznc72O9bHPDfsnfEqvUE1PpAqVJ69jn0waDrHIGD3sGvLEJngJUlMLY0zOga2IWBW4IU90WAW1i4pYNdBbhlUrQB+QAb+Bkp1P0M6GcJ5PoZgdx+TsDNzwP83ANtgJn3aNoes3mHebvCqdkKe+0SZ2cHONMscKY9yHxxr3AXccoucMbuY8d02DE9s4380Q0GK2OjUtEzc9vDwEfgNWRz+1D2OzuYPCmjLsf+Kwq2zJDyX5YTWCtCsl4TAWGBFfHoowvqpKyQJVZXfGTrJsxOzcjHX6S8nZLWZJ0kH92UX5f6PlknENaRujldCvvxwhDIFabXyTqzyuzQCIBYmuify790nlyBmpz7jGyMWlc+kbH51YS2tLm0b8/my4uuwbIhRboH+evuNCvs2SWzvEt8an4a9+7uYXFhhn7fwe1Y9DsG/Y5Bt9tgeeYsdu/cRXvPOdjzF4HFEmGxiBNFUXoP4ymnNiJTqLpQvB8CvpKz2+ic13Jf4qMfgVUF2CpQGyMoK0Abf0XJ1oytQ/K9VaBWlgXUwiVgaywr2DYFL7I2TIKrUnIXguQn773JfkPMZW3yCOi9vEv0Fwy3n/rueASyKpDU5Trnd2BWV6+L6agMKfq959X4Tus/CTinLGyC/rWgiRvuvyECGpNYRZjoGxrNVXkWJ1kq5d1MS4xMrNsdNGFbA7dixlqbRNPRkwXklhNoGuBKZPyBS0R8DjRpZk1PljnBx/GKfHKJarf8kpTmyz3SWBHNl0NidGNQKn5I0eda2HMgmS+LebKYMUt/sSFOtMQxRF5aAcgF6KXz1Z9HSTyW6k+coANy82XZoFjdwLRuDLYWwznk/rpS8RizCz5Mx30A6qyqZmpLU+PjYnnLc1eDVVX0xm1Z36nv4nEFej2RR6b8z//5P3H33Xfj2c9+diz7uZ/7ObzqVa/ChQsX8NznPhdvetObqimX1skJ0D2iHAZUHtZPdxOQe1SJHxVdNgF26RqGg5tTA7iuRy9bk5SDCHKtZ7DbZyAXoEBJy9Aw29jiIigNg/c95gaYGYOZMXAI2HELXGGXuNadx4W2xQU/x8UwxwVPf5qhXHmHhW+wYKZSZrwPesVadg2WvcNi1WDZOaxWDv3KoV869CuLblmA3qUhH0T+dasQGRBprmjC2LBi3RJ72/Ovn4X4F2YeZu5hZ+SHK8Gm9toVzrQHON0ucLZZ4Io2B7hn3D5OmSX27AI7pseO6eEQ1McZkdGlNrYEbmEjuI2somIeI8MIlSMXqUwCTwGENUurgsxsGcVvMMMZ/E0mjkPxB6qL0lpw31XnTuus+EMm+Q0TWuSrm0AvKZCxPwbK0Em/lvPlhpQ/t9gfQIxsrW3na4C3DxYWZOosZogWDHIlKhmDXa+RHUsyl64zB3HdpOc0MAMUdkTh32ybiDIR75gRWvYO+32LXbeCt0vs2B57zRJz2+G0W+DsbB93zM/grt1TuP/iHMu9Fv3FBv2uRb9rsTrlsDxjMb+6xezeXTQXOriLS5hlR3luAcBacgHg/LRkcpyCypGvfbr4BEkQ9dUUwdhE8KpBbTQ3LqMkF/61GbBl5iiytiYHu7Aj4FYB3JhuJv75GJlXgJSwgnJXU8prQJp4Sr8o0n1x+q+eTLdDMPA9t6UCvGUUbnQCpAU4MHiRtgmV3/iO8heHXz59C9nnQ0BPAPvjmwzsRta5J2QUVC5Xul4GXwYJ2HCApAhsBOwCVQoxBWqaZvUS4D08wJVtYwA3A7ri3lBMngHkhmIR4BjwOkiU5eGEWDRhDin6so/3beK90yQEtWV8hJGGFRCoHpyAXZ7cSOxuBfDy883K5flPiSl+y/4jdZR9ShSeONES5B9vM4LEOcduUdEI2KVlZN9Z3dZVUKlvpwC5AwCsbsQi17Vqvrz63Ou2adkW/B7F1/dyEJlwuxT1frrLzTffjKc//ekR6P7RH/0RXvziF+NFL3oRnvCEJ+CHfuiHcN111+Hmm2/euu4ToLuBHAdDelQT5k1BblnHUa695rurwa5c1xjgrZvVpG2lr5IE4rCsFDS2jx9xAljM6PoWF80cLnjAA71doUePFYMMthLEjglo7Qp76HDGLrEKF3AQGqwELDNgXgaHg0DAV+pfhAYX+xn2+xkWvsF+3+Ji1+JiNyMQ3DU4WLYEepcN+s4m0MtML5nfstltaQrKkinNDcg8uUE0UQ4tAVw369FybuEdDjZ1pl0QwG0PMjNlCTZ1xgrIXWHH9GiR2seDdEJ6bvxh5jbuGdD2sGxKm8oiqJV9FcClOvJcsHVWVykvmskRDKiBauxM6q/2UQgcPAeKaRRNg89rAinAY6wu7VpndUufK4qeXLmOCXHqwmXZmT7lKhY/YAG8pEYDwUdGl/YT6srDc9CwqVya5QTTIJ+dyZczEAMGNuV+IjJpw2ygRF9e9Dwx1DdY2AZz22FuVzjXXMSeI/P6sw3ldb5r9xTuvriLC7sEeA/2GnR7DqvTBosHHGZXWrQXWrQX53D7Hm7hYVcStYYBaGujD60wsoOI6UaxTgJMFcgNkblVoLYSNCoziRRQa4s6BdDG/RS4NSGZ0Tpmax37SjqfgdtGmdfXTF8tP/fyOcfHU5mQErDbyy9bsBDo9XDOou8DvDcwxsJbZniNBXrVFyKwCUBnIosb3z+XwEtwBBgi0xv0i5wAaOxP/Lx0n8vBULEsrC4PbsOo4Yba36eOHGwKUEjQpUDaE1KCXAkuVX7TxtwgNMC1xqNV/rgSZKqxPgLcNlrhcDohNZZEC5FiLIHx6bmLFUpAYnNlvOAynZYsM9EOCeSWrK60WQxMJSAwsrpABLtyaVDsLj/YUcDLh8uLO/V40rsdsn4zCngViI2THzBDpt9bwNJMzCZgV9qxZHeBccBbsreHYXnpPHXQq8+lj61tq22f2nfdMSULfSInUpMPfvCD+MEf/MG4/ou/+It46lOfire97W0AgOuvvx6vetWrToDuUaVU0o9a13HsO+bjugnI3bSuTUQHotKDbQ3wTtUhx0elQCtuCNFXSbZpSWC3wYFvYUGBNnpvsBKT3MARLItBtQWbRhuPVeiwE1ZYwsFbi4NAYHel2OKD0GLhmDn2M+z3LfZb+r3QzXDQt9iftdhftVjMGyw6h9WKAS//YUW+p9HvUXzbNJAzSVEODkATEBoyUbZtj0alC5JoyqeaZQZwzzgCuWfcPqUNir64K8xNjx3j0RoUIaYoRksPQ0w5LJZwWAYXAyRRJGDavvINsYsCfjEEtBrUlu8ST+CPSwF2B8ubirRtBLZgSpnMJ8tAWJrVFYXFgFhdicAsfUnuWZvSexPUr4kMLJkJpuBTWrQZM7EwYTj7EfOtKF4gAty0rM0RU/1D4DNgc1EogBrcMhNGfm3M4pUH6wIBC8p8edU7ekf6DnM3w9x3FOHbdGjtEjuG0oWdbfYpYNrsFO7Z3cP5gx3cvzvH8lSL7kyD1QWL5QWL5qJBc9Gi2Sc/eLcMlMarT/elU4PFoFA6qroAnwKsVvPZiplxBLNynI5+XNRpQ/RhjsHjykBSDGoRmdsAw+yt+I9bE9C4PnPpGANNGujWAr9on+40SUX9vxM/zsxlw6L3Hp2lOAa9DeS2YS2PUxw8r1eWAEztESjh70QEuPwbQDnKQwCczEEx2DVACoLFz1KBVL0M1AFv/JXIvwKmI8vMINdKWTpfBDZyejWRS++OTBApNhdDkKsjKNtsnRlcE9YGmhrz89cAtwS6QJowswBW6YXIwCyQwIYzAR3yMm0F0itwWxUGwDLpIYGpOEQVItiN7SzXwO9jye4a6TtIDzqoP4TN2F05VI9nNYnnVL+Brp3OYwCfonNLcCoBu8JwW5uqo0+IThdEfS9azWM7hlfvD+Sgt8byUr3joFfqqJ1vHfAd22/dMRmLDFPVWy8r0brbcdf7aS733HNPlmv3Pe95D571rGfF9S/7si/Dxz/+8UPVfQJ0j0EuhfnyFCjdFOQeFrTLuA8MQa0Gu/ocY764ImWABlEURCGQoByl8ubUeTxMBGDL4GBDS6wuwABsBYdAoLYycshsNwELoiZ6Vg5b02EVerjg0ZoOre84YFOP1nbYsS3mfYeZnWFmO+z3LXZci7mbJdPmGQX96bxlv14Lz0E8Qk9sV+Z/JI1twKyOJ2bHerRtj8b5mE94r11ijwHu6WYZAe5pdxBz4p61B9jjYFN7psPMeMwZ4DqlsfQhiLsdViH54PpgsQIB/h7JbHkV3MBsWae/keNFNMjN/HKBpMgosDk6yCulxfB6XFYT6tVDRRnmCsg3MwHuwGWBr1FYXcdMhQBgmV3X5ss+hEk/XemrZCqYgk+BFVQygU5mhxrsEjOjQC7/Sh0OCez2G3wcMyxbe0cjqJWmkuiqUGxY3tyqWZMw0PWe+gaZMDsc9E1kdQ98i9b0mBuPuV2hNcTynnYLnG0OcOVsH3fN9nDfzi7u3d/Bxb05FqdaLPYdVvsO7sDESM1uQS4BpqPARknTTNc9ALpVNrYOaCNQFeAKpHVmjDKwK2l+eOIqThgo82Ttd0tBbxJ765yPY6GzDHQZ2NYAk5i2lsFtyj5Z5rOO7zoMnAQashSwqDcBvfXovYXzAV0v4M6i70HuDDzxorGInDL6sSPEKOCeb1/ec+/Se0NmsbTO80oJtGbP0WR9rex3+jioc8UJxbidwUr5GqwZS0Q04NXmymMgV3/TShZXzJRzNjc3VS4BrgS2o/V8UqOH5RgClgCWGjOkf7jg0cFlE2O6//SVX9kWkMBdllEBiQWVgTkDu4MGDmkQLwFvBJx0TRr0DkDuBmA3TUSFvLwUAeCR3aVC7a/rwddoxcFFg16kCQHRl/h7YUzYCvACm4Fe/fQ3Bb1ArleOsb3l9WiZ0inX+f0eJtjViXz6yDXXXINbb70V119/PZbLJf7gD/4Ar371q+P2+++/f+Ocv6WcAN018mAzvNsC3LG6j+u6gXEGV7ZtIhmbixzkaoZX5wMtlTYJkETMa4ALAQc+oDcWO2YFbywD1vqsd6wHJpnjZp8PwMLDwWJmegDLZOerdnOKHW6Mx9I5HLiWog23DqvekbLP0YZ7T3fivR2wmjGPsChHjnyUJY/wjuuw06xwyi1xqlngtKO/M47A7Z5dRIC7Y1Y4xcx2a4AWBHAzf9wQsAKwCsAyWKyCHbC5vZpQkPyupdky1ZeUZyABPJEc4JrJvr1WFOgSvSnO2seTCDFgFIOANFsfhE1nkMtlosQIAI6maBnArZsvV/10WUXsmVEhgLuZCPDNyiLjmwf7ciC/u4y5keZSy2V5CqIz8jxU24ofLwClzA7BRmTHOLLzSnLqOjL7n7sZGs8mmKyoizK/Y1bYiYB3H/fO9nDPbBf37e7i/r05LhzMsFi0WB00WC0s7MLCMtAltwCatzL6eRt1jRqUxt+huXECtpUcnSYBWSpT6yi3h8jiZpF9VbTkMf9bZylWgc6rWvPrtIPxUvl8MyOnJU5IwcAHDx8MGmPQBQcfPJyxA8BrjKMIydxfehNgeu7dxkA8/WPvkvfHAT6wr2IAmYMT1qdrQT5J5MHvpVcAJ/ZDBYqsbu/iV19I9t6rP9U3siBE0qfVspYs6JRJEZqFzY3fMpObJ9eiKSf2dhitvTRTbm0XAa4Gt/I+O/j4/Ur++8yUB5qUEBatzIse6wmIwNfE9cApzMhPVwfq0ubLxH5KwC+BtzRAT4LdOOM4BLwwDCjj8yv6BJANPmPqR3r314Fck/aRn0DgHQjk622VD7e36f2u3F+I7ZTMmWPuXAV4hTEXQBzXUQe9hzFt1nWtA71SV3neUo5i0nycOulDJmG8zx213k93edaznoXv/d7vxetf/3r82q/9Gvb29vDVX/3Vcfsf/uEf4nM+53MOVfcJ0FUipozHIdvUsw4AbJsjt1Y2yLu75pyCJ0TKAVQPirXrrynaRq2Pglvjq4OpmMuufEPKRfA48C2ZLgtrAYtlcKQsMNgoZ76z+hhQCHiWKMOlWOPhAl3n3HapnK+78Q6N9egcpdfpJD0DK5fCCALIwJJuA1GMZrbHzHWY2R67boW57bDrljjtFthzC+zZJU7ZBTG3wt6qQFMtAlpDgbnKGeA+0Cx9LyAXNqYUWgUX2dxVaCKbG0Euktky3Ufun6tNmctAVFrWgl2twBZgw6jlbP+pKgtlN7G5CdgGI6xtisCcWRJwgDNZ3tR8GTEATJ3VXScCcEtmRsyWpb0zM8SRr3CNzU1BhTRIE+UzkNmyNKJMEqA4JmtnEyd0PAelWvUOB5bAbqNYKgEIAnhPuwMCvXYV8++emx3gvtkOLuzM8cBqhouLGQ6WLQWCWzp0Swt0yjWAU+IYDWxMfs0RLDHYXQtegbxPluUmrWc5bW2I6wJuKUVJiGlKygBTMeWVArlZzAJm+3Q0emt8ip6uRuzSZNCZPqajEmsDmswJlGPVBXSexrjOBFifGL9Vn+6v5zboE3cbH79MIIHBriyLv24enIfBrkH0rxXfcd1Vgwa42tR8k/d+rCyUX7dxSSmEEshN4zYSC78ByNU+uJrF1QxuBnYjk9vFdwXIU5U5qPHBWPSBLJbKr56DRwcbQe06f8myacsWK7MtJKuPNWBXJhlkHcgALw01CfQCBfAFMtQbdPnYDaj3N9TGx6B2ZPCpsi4PwW4wgE/fpAT+8wlEGYa468b20j68wDjLCxzetFmO3RT0AtPAV2RTvbYE648osHsil0Re85rX4Ju+6ZvwtKc9DadPn8bP/uzPYjZL6V7/43/8j3jmM595qLpPgO4R5Cgv7Sbs1rYAd6z8SEyaknLgFBkzW86YJLVegtwS8JaSzGUtRaTlGWoHn2lPHpYZWY9VaGi54rcmQgBOBVpic91VcDH6sBZnPFbBRVDe2F5tC1gZArw+kOmmKJWDdkEC9NqsrTUec9dhZjvMLfk0zk0XAe6OWeKUXWLHLnHKLIkJMx3mpseM/XCFxY1tF++1YHJBbK6kaxKAq5ncyOiiCESFgtktgLx+bmXZJhLZRCAHExxMyFgMlZsq8FL7CYMQzZX135DVHQSlEiUIwo7l5stizq2jL0cfWmFkFdgF8uBU/cS7LuIK0LtOyncp4tjYngLGFHBgZdBIW0dAIQoskAPjVH8IyMyXidF1aL0A3cRaibSGXAQcyJzZ8j7C8J5pDnB/t4ML3QwPzOfY79gvnqOfi4tA6A18bzkXLNLzzhpgGqDG/lZI3eRbtuV1G9nf6Oi8rNiqtEDOJEZQB5rSvrg1kFuyuBKErPa8RSxP0sCgCngBfke1pi1dtVKf4IweNrKiCAZoOHK4AFztnzusmpjc2Afp9TDF/nFiK/OThuqrmr2r3j5f9HpwW8+Vm/9pkKvzb+uxfBuQS64x/SiLK+9GSiVU+Z6ZNJHm4KuTtWMyMH03yWRZ+yWX5ssJ3CZWV1LyjILd+AiKdQG2cjPqJwJfOUz2qn1Tin6TbRqbtBqtYz3Y5S2QG6E20cx3qjLCXwX6YvCvEZYXOLxp82FAL9UxDnxLmXJXq537EWG6rHWK467301we9ahH4b3vfS/uu+8+nD59Gs7lVii//Mu/jNOnTx+q7hOgq+Q4g1Fp2QZornPW3wbgjp37KPc4NeDWBjJTbMtAbrGc1yXRlg0ak4NdYXVX0n090BsDz3lEZ+jRwwNwaRZ8BFRogJtMmhnsVvxPHZuDic+TN4aChgRiWVoYrLxDIykfitlTraBqH625XaGxHjt2RX6MlkGsXWHHLLFjVzjF5sk7ZsUmnz1a+AhyU9THAGcMVqwx9iCA65GD3IMIbpsYkIv+mozNlaBU0hbC5JamzDoQlYiOuFyWDTpKBkDyCLlgcDvwFy3AFpDrTTHQVEgMk2HFPLG7+Uy/+OcaIAtKZcLQlDmaL5shqyvPfyWGy0XQKFQmYTJf56LvXLJAHjyJkCmBenJB2l7MCBXIiPvLBgYqniP5rnqHlXVYWoeFddj3syyA1Jwj2Mn735oesIhKPlk0rLDftLjQzDn6+Sz6/q56h2Xv0PVkReGDygsrzx6pz62LJTAlY/5ttJ6XZ4GLzPo0NLUARkP2NqhxNO87tfGzZgJP7G5AhJwhHdugr4LdssXECjYEA+88QrBxAskEaSeVLgtD6xIrfSzmvMVwcgpI/cwgsbnKt7qccAnFeqpns+dueF8NVDSbq4NPSZn4UR8F5GpgK+BWWFxKJ5SYe/mm5VHYqd08++Ba8ORcxWR5bRusaStjJHJ7YnWxEdiNLZwGaQNERrcEvVKO/FCAx/LDSK1fbDqsyiQMj5V0udR/46Sg+jqJKbwGvBGAFsBPMlZsw/ICddNmfRz0OdXxY7rbNumBNgXC+pt52Md2Ip8+cu7cuWr5VVdddeg6T4DuMclhWdNNlNd1wPRSgdw4ATsiUzN0ptgvmi8rha1kIiLLWZzVBwuYPgJQYVZL8bBo0UOC/TgErAIzsZVrlFlwDXAJxOXMrkQm1mya+EdaBFIQ4QDL57Z1UKKBbk3hmZuOAl+ZDq0hRlf8FwncdhHkzjjglss+lvreAiSFkOTKXSmf3JWKMi0At8bqCpubWO4EdunZTP9uJLVdydYroakAMjUFmajq6jNWR0vJ4gijy8q4gfjpMoALZL7slGJSC0rl2Sw8mTLbmMtWs7oIPjNhzgJMTcg2rO06EXClRRRV0TGpMCiAQBGqo9cdpwnJ2thgXEkMKidrMFh6YnUP+pyBFCHf+h6tIQNsCriFDPDuWDLjX/gGi5YY4qWnFEZdILDbB/IxDYEsKuT5TU3AxGsoALHeHk3yx5s5NomIbncBtjkjmMcq0BGVoztDBLl5kL7ooznJqGzP6pHlAtXvTUDDY5wzAWBLlRBSEjlyUbCUBoZ9LIXFjZMetGMV7EazT29ifnETgxPlEynBmOhDnQKGJcCb2F7Vj0vAq/s6r5ts38IX1+SAViYmJPiUDhZ2VJBbMrgpby6bRUf/XJ0zN/noHrcIg6uzgAvQH5osB9QGYApWlcAuoBlQLSUIRgK9enNe+6Huiw5VFerJuvJ9CgWrCwH1AmeH7K60SQZwNwC8Y2bN61heueIxIKv9eaHPq/Ytj9fldL7t2rr0AY7+ykeYZHzYSDkRd5z1nsglkxOgOyLHZe6rZZsB47DgFhi/9m3Z4MNIqezp3xLkyjowPmso0oPMQMcCa8g+PUettSEpCGRunDMgWhEsAS6xmSZFHA7Kn7cSyRLGRrCrTQPTfuJbFaLiqgOQxKA8is2dKVDbmg5WlB/kqZP6OBsu7ajMlZlt9DAK6Dos4SLQXWamyyn4lDDaOZubcm9G08dgsl9q2xwsaMW4lDJHqzabzRRVNmskP0uT6yS8Uge76lctB24yzfjVglLFbQMml3PeTrC6YroMYwEPtLYHAgXzcWsAr4+KznpFVgceGg8Igghg9FsqfrrRX9eCtFvV/sGyMidtpUFuCSa4vQL3FUlZs+odlqYh5Z8tGeTdn5sOvaU+KulTABUd3YKjofc44FzXp92C815bdN7FX/GLH/TRkPuQl9GIY7kCxVqJrAHfKcncNvREHyoxCorxMAe1dZBbypQiGe9JKc9TQFjOlwISsRm/9XFiKHAgrRA84CjAFTG7Guzye9QAKJldg9TPPKKfbgaQ1b4h9kUFaidMmQVrx3MZ5D7YEeyqtEFxXYBJMjeX56VTPmWTFjI5cUiQOwS6XRXgxrFfvmcBNL6EIegtv3HrxDLQKst0QCqAx4qQGMwxVpeaPoFdWqdxNQa2i98vfiYF5h2wulD7HlWySZAwLMvOuR7sSsAuAfMDgKvWddCqnoGyfkI6p/EYy7sugFUp60CvrmdbnXAMGFvVP078c0/koZIToKvkyJFhWQ5jYrjpIHAYgLtN/aWkT9T0PqXUQO6YjCpoMCjNQXvl91iCYwsfgyaRr5LHCo78mkbAsfgzJXZ3CHJTsKsh+NDKQWN6Zp/JFy6/tqS0OvgByG1tx9vJx1h8sbQ/ow8WPZulAQCCZXAV0GP4oelZyRdGWoNbCdylQe5SMbol2BVT5hI80HUpcFBhxErJWAEoRcaIJqCWGWQF7dynIyojKcFAoeDGHVDsHLJlbb5cBqUSYCLsbRmUCkCV1QUcGk541aKPYFfMUjPAOyLbMLtlXuMp0UwVsQtIz0HAACtwJubECENG1zIIlvWoSCXWvJd0Q4GCsy29g+3bbOKpNxY7SK4HLfJ3R1IvtQCsDdQ/rcHcd+jBkYJBQFcmHXSU4XK97LvrAHGtf8v6JlKOgZkJ8gYAd1hfvc9MXY8GuXr/sj20GL4Wz9chTFQ0v7YEboMPMA7I/HUdvaYeAbbLwa4xNH9BbG76g0d0MwAwYHVLoCsgN60Xky8mDE2ckW8v2VwJGKZNz3VEbP2cdMAwHVX5MCBXAk7NeFJTQO5Y9gCHMOrXrydma9t0f9hGpA9oRheQ8YN93DXYZTCbwC6QAV4AQ5PmuAuvB31YtuuxSVmf/h6VEjAOdgFEdjeC8fSNyQGvgGGuSwHeTc2aqQzDskOAXqAOfMtjxqR2nDXJfeGRAnb5UV2Sek/k0skJ0N1Ajts3bpuXfZN9jwJwjzLwjB1ZDoilgqdNlvW++QBtM7BIIC9EVtebIbNrwUybArzAeORlEQG3aVn764qp7riCILlNiVUZMnUpZ2oCuTrAyKAufW3BwsJSyhB4IDR8HQE9R4Neoe6DXKZRisAVCfDmIHcYhEozupJzN/fRtQMAkOHKdf1LlIH4SwqrCck3FLzOLoUpYI3WkbQiW5PIMCGyk6K0Eas7/NJMBaUaY3VhRJmkngjui3SdxLwQPS2MzGZgdjy12HamizoqaEQSmdJv2CwgANYQiLEmNY8cbjRDlr7+ekIrMruK1W2MR2c9lp76MbHM3F/ZhFkAr+7TAnYpAjoF5WpdT3701qRfqFzP6r0WMLspCC6Pq03sZKB3zTdCT8pVAW82LvoMUMnx4vYATJst165J572We6hNjpTR0wf3YVIwrWDJZNlbVmct9Rk45a8LcQ1gsKv7GTO6YtGfzJeRs7oCEGRyxRQg1xUAWG2nCZkc0OaRsUs2V0B8GETFFnBbRsXWDG5jjwfkJjP+UP1OlJNgUwGo9CRuKdtMjmlT1AjQFJCTbWNgF8Ao4I0sL6TK4rrKy9wUGBxGvTH6Xa3vku6fgasAdzU7wy2jQO5mgBfg5xLqZs0SvAoYsrxZmcmnEdaB2HXZM7ad2ItWUBjPOX8iJ/JgyEMKdF/3utfhP//n/4w//dM/xe7uLr7yK78Sr3/96/H5n//5cZ8QAl796lfjrW99K+655x489alPxU/8xE/gC7/wC+M+i8UCr3jFK/DOd74T+/v7+Jqv+Rq8+c1vxmd91mdtdT2Sc+445LAActPj1qYkOkaAqydZ1x01BlzHwO86EWAVWTVw6hY2BdVgl4BuyAAvsF4JzVLmyKxpAXLFV3VK5BrHAsVIgJGsrNi3B6V+cLDoESB5fZdBtnMgEkMstWNf3VVWxxC0C8AlhraJKZVKkBv3DQ4r7xRg0GxuriyLlMxQmVookxJwibapgFSW4iaAvuACftXMasbYbNKtQzIjS6bLwuAhBbDSH+zAABfJZzdj+4y0izDuwvBarEBARZjdPiQlYIrVnVIO5LnQ8mZgV5SkLNAO/xe4LEQwwODWIvpfGgHFUCBXKlF1ahFz4M5btI6ZXW+xQAOLgKUJ0d7eGwNvDVr0sIHygNbYy2TGScGrJBo7gGxCSoLJAcgAcL6+HQCWti+ZsW3G02xcLMCtbC9dOjTILWVqfKsBXDlm9J4qoD6/fvGxTaCQPDgCYBmwsBGNgXyr1PsO6j/WmGSyLIBX3s2i68s7LpejTZcJ7IZYRn8hY3npl/sag9zUb8NobuMywvJakJvFX9ge5M5UWqFapOVJQKu2yTjeF89d94VNRJ5xDt6QATdAhotiP6N9c7m+EcBL21Rf08C3emEb38JaGQOz+lpGz8vdOppyR5DPYDjupvv/esBLbax8bYvTHoXlLUGv9ulFccw2Fo46+JSuV859XBaTJ3Ii28pDCnTf85734GUvexm+7Mu+DF3X4fu///vxzGc+Ex/+8Idx6tQpAMAb3vAG/MiP/Ah+5md+Bp/3eZ+H17zmNXjGM56BP/uzP8OZM2cAADfddBN+/dd/Hb/4i7+Iq6++Gt/1Xd+Ff/AP/gE+8IEPDEJUbyuXytRi23o3Skd0TPtk51XLhwG5h4lyKjOApd8jmNWNgEeBXUprwcqxArxU3wZ+jgXAjcsK5JbKsxYJDDJm3iMgV1jd0XsPxEf3Eag3fDyz0wyoyAeZTLNL07YIdMMwfdKSzZKFzRWmN/75JjK/AgbEBzKyufEvTzmU7mFDM9oSmArIQhEMiX9hAONZOVYgVY4NWR2FBBMBMqKyJYp4YnbHcur6MAxKBUjf8qoNkgnzyrvolws2o3eBAU1kdwGtxmSm6htoc5nfZYWhi82jJxYgCqyBmBsbE9SEgUlMmC/ArWpvuvSSLVNNHpK5bwDQeQtnLDpDKboWXn1+tHZmCeDJOx0VftU2tWUfiBGm9iAXAp+9C2o51NnfGvCVdq6V1cz3N5XaeFkDuOX9rmNzc/PkOsCVMn3Pukz7MY8yPWrSxFgPExz7c4NmIQK9xxR0nCBS4CBoxgDeBAK5vUlx2kICu8OT5qyumM5HM2ZlwpyXqT7KYBw2EKObmSljAHKjT+6GIHduu0sGcjd53hI8UUsGcotxekrKremZFwyumqGMHrlBgt2lfhLUEDQEvEBJ0wpw3EoOoW9M1zdSPHWekJsySzUDM+1y8idgME4L4K358QJDwEtl4DIMyoAh6TBqdrxB2+u6piLbP2JY3ahDXIJ6T+SSyUMKdH/7t387W//pn/5pPPrRj8YHPvAB/P2///cRQsAb3/hGfP/3fz++6Zu+CQDwsz/7s7jmmmvwC7/wC/jWb/1W3HfffXj729+On//5n8fXfu3XAgDe8Y534Prrr8d//a//FV/3dV+38fVsrKBvUM9RZNNZr03PcxRwW5Yf5c7WRd3Ts3+0nINeGL6XIsiPsGut6eGDywAvkD4G6TqSYqylBLh0rMmU5LTv5rPiU8C2D2L+auk6DXHRFgFkptwBFP+Ur8dnqZNKNlffx7rUSeJ7W4Jc+eu8jZMIms0tAZUAv7Dm/Sk/4qm8wiSa9MePPMFTY5hSQm5qEOspTlOeNiiUHNaYLiulJd6fQcbqkqWv4cjKGuAOwa4GuJQKhEzSXKGejJkrlgANGL7fpSl51tZ6OYLbEMFtCkrFIFeAS+3NF2ArbNmIeAV4+0C+utZbNMZjFSysd9TfFdgdvNPq+WSgT5s3K1eH1vSZwq+DyWn2V09eTQFf2j9neXWZtDtd/mZgohwPa/lwjxPgynrJ4pYm29o3ufwbk5iChy0uQjCAS+CH94oTWVFr75n5C6D+FgpGV727+t0OhgGsMleOwJdNmeFC3KcKcNnn1igWtzRX3hTkzmx3rEzuJgAXSN8hnQovs74Zee598Sy31X002M3LUQe7SIxtDfACJeiVCkNtaC722ex6L4msOXeaTC3ZXTm4BL91wEu7DP14B2bNmGZ5B+UmDJrXYPNxq2SGIfeq2Fyt153IiTwU8rDy0b3vvvsApHxJt956K26//XY885nPjPvM53M87WlPw/vf/35867d+Kz7wgQ9gtVpl+1x33XV40pOehPe///1VoLtYLLBYLOL6+fPn4/KlYnBLOYwJx4MNbLeRKTPlbSQHu7kpqJNgT8yOxSA/KlKRZbAogJfy3sp1sdlv4dubRacsTBLHmCC51nWyzj9YzuXAAJUB7wrg72DD4JaDbIUUoERSJ9VkLHXSKubITabLPUwEuVrBTbl0TYXNnWYQx0TAVTSDrTGJBatLpl6kKAWA0pmQBpXhqzCor9IPBd+G5Ker0wxp82XxxZWgVADWsrqiu/RquQS7ZIxeMPuGA6hx/RI9vCa6zbVp6lqGRllZENaj/eOibjsNSnTDxcrSMQKQ5XdMqcxBEwPeENCFABtsstRAbrYt7zTkfQ520qQ5HafOzfUJABb2V4DvYRhfuicLHycuzBBsmnTvNRmA3eIeNvHFrQFcOWdpWq3bX655CuTGSSykiR4f8u+XKOViJRBUv6CHoMAu518lbZrfZ54DEjbYhPR+isTTSR/V4NYIe6uY3BrIddMg17kEcnV05eNMIbQNyNXvf198o6QP0zO01YlXMV3OTJqrAHd4bMnoWUORgCUad3yUBWiL/cIo2Mr9J/rxVwAvldf7ehUAyzHr3o8HR51bb/6MBAD5A8gTrOX4qiuqlSG2YzQRLs4zxfKW+5ejaA34xtPKMUUfKn1yAXWv2bmOzzXwoRIzPad7pHpP5NLJwwbohhDw8pe/HH/v7/09POlJTwIA3H777QCAa665Jtv3mmuuwUc/+tG4z2w2w5VXXjnYR44v5XWvex1e/epXD8p9MJXPxbb3cfQXeVvw8GAC28OwutsCXwEMoux6mAI85Kagks82ziCCWWA5FmBWePrpllGVB+uZQmkGZUeReG3CRAfy7SyjSFMKFhsZ3jJ10rZpk7I0QjBYec3ojrO5pdlyVIyhmNAtWIIBqysQVMBu4JlwYXw9A14g0wcSUNOV56shyCw7okndmPmyM5hkdQHEHLleWGKTJmk02CVlVky4ErsblcoJsFtOstSiYJfPPypCJsQ4xlqBjb66otwIq8s+l2RSoRi4Uu8yDCT46x+DqVTe9wSS8j7TsRl+5110R4AFWo5YTefhAG8TYHeM5Y1lYtIMZuAje5qsOwTsUqRhw1YjmAS9MD4za26MGhtUO5QAoyZjoFaD/ilF8TAsrt5egtze2/hO630mv3EyiWLlW8izSVYnmjFpksSCAC8XJUa38NHkU6ZJrLQspsrRTFn9VkGuy0GuczmT+3AFuaULjozvOthULee7nrTUfeWwoMPwcx5G7eUHCBXjQIM7iHFIDniBIehNG9aA2amuOHV72+gk237jJ+qugV2dbkivq6Ok4up51gFe2iZjfjGBMThmKBG8FuUa+NbArl4/YXVP5KGUhw3Q/fZv/3b84R/+Id73vvcNtplixAohDMpKmdrn+77v+/Dyl788rp8/fx7XX3/9g+IsfxRgdJhjL8XQsi3YPewg52XKngFDDh6GpqCy7AOZhDphdpEUfWB8pjyedwTglkxuxqxtMUXSQ7HQhRIPgNlcZgANwJFeCPigSJsEoJY6ScCtnC9jaGEi0K2BXA1GVpybdIzN3eR9Gd1HmcwiqHUxm9Vg1xvqCqIAC+CtdStWfiPrGC+kcm0QwFrMPgeTBaXyIWd1AVIePNLETOcdGks9rYOFxMdOIHG8/8r7IZMaItX+qZ4B7ZP3x02YXWOEgcOQYYdJwWWszAQUbRkBR8gD+8RzjCuaKUAVvaedd3Auz0EsFhvrwC4YJNRY3irrCxpHHDO7et0KgJYJNmF6GfTq9GYeBjB9fLcsctAL5MBz4BenGnMb3zXxXRZZF2xKyvREyKYsrga5vbdcnp5fnBgq+5vqGyijeCP1uWANB6IKERgbfqdlMkpLUPWHOMEC5Y+rQK5BBLiZubICuQRww0MGcikXb+6Tu07G2Nw0+ZibLWd9QE1WbiPC4pbmyrl/buoHKbASMrCbm+8iA4Smck2j4LeQUVVwROfYWosq6tlGk5k8VwXs5mcYewO2A7xAneUdgN7q5MVwH301NbA7JnocuqzlBK9fdvKwALrf8R3fgXe961347//9v2eRkq+99loAxNo+5jGPieV33HFHZHmvvfZaLJdL3HPPPRmre8cdd+Arv/Irq+ebz+eYz+dHvu5L8dIets6H+t2bmtVbdxyAXPkX4W9oDKVfAN8SLPhAfpLWhAzwCsh1kb0ZD1BWzoQDOYjdFuSWwKVsmz6Mg92xCNL6fIN0RMW1lhGlI9D1DcQ/UcCt/u2CK0yWh2yuPo9WjjeRQboKQ8pOPDxWk8AumTUKwFWMjz6ntC0r23kKHHUBBUhOSrsKzhSI1TWBAJFmdSUCsw15H87aBWV/Bab6LzBu/aCZxNKkPAsmVPxuKhLpE4ZDf1lQ4C9RZ8q5AAG5AnBNyjs6CnC57WI/Mum3D5S6SecglnuYArsA2MphC7AYA/3koBcF4KU81f2A5RXASwC353VJPwV+Ww3VG1QqEDW2bBuYZeq92jTglN52ZJCLiQksFiMTTrSWwC5PtMCHHPDKhAofUq1fwK283wJ4NYsrTLH45LrcXNk6P4iu3Di/XWRl26tfArKSNq4GciWqdpknV4v2y62lDypjLUyxudpsuew7tUnLUsb6m2Znq9sY4A7ALtLwqwEvMAS9VGjGAeyYVMbOWhVH9dfV97H1sSPnjlGbUWd3s9zzlXKqvA549T41llf2qQHaMsCUthICNiM9TtjcE3mo5SEFuiEEfMd3fAd+9Vd/Fb/7u7+LG2+8Mdt+44034tprr8W73/1ufMmXfAkAYLlc4j3veQ9e//rXAwCe/OQno21bvPvd78Y3f/M3AwBuu+02/PEf/zHe8IY3bHU9l2rG6bjqPI6hYttrGRugtmV15dw1s5b1x02DBR9QANwEeHuunkxCVSqikmEplYEKuC2XN2Vxo+lxSGY8mskbA7swHn1wEfA6hAz0AuCoyz6eJ28zZLP/Ol2SsLhiEpuDXVKitOlyV5gqS1vU/HTXM4qIIDWLxhmVIpN+AUCBrSzVjWyqvRka5E5JkPRFYWC+TMVrWF2lIEiEcJmskeBUJdi1W744GuTmjPowWq4sr5METBN7K6wuq6hx8iH6kxlEFoLqAJLJMlR5ykeq78Gp5RKICatLJswUc7zn9xlQkwaV98QaH4HqWAoeIJ8UkndFQK3k6QUQ69eAV5/XGSTAK/UI4OVnLSBaXCkAROC7qWTAuFBEgdI3dxrklv1kE5AbTZcVyO29Ve4J6v1QEs3h9eSVCZkpvLCuNHEVYs5szeqOvdcAUsC0CHh5OQadQkx3FEFuJYVQo1ncI4Lc1vRwxldBbmt6iryvQO6mbK62zgEKl5Q1bG5tYqx6ji36pfTFOIVh6FllqYaC3gaU7C6VGf1IqUwWjgCMNgK3xwC8Yp2H1e9KpliB3bJsAGoLdjcDwlw6BXgJ2FK5NTloN8U3ja4jB7ybiPbTzXSfy1mKCfJjrfdELpk8pED3ZS97GX7hF34B/+W//BecOXMm+tSeO3cOu7u7MMbgpptuwmtf+1o8/vGPx+Mf/3i89rWvxd7eHl74whfGfV/84hfju77ru3D11Vfjqquuwite8Qp80Rd9UYzCvKk8VKYVx9XHLzVIL8FhCXa3mbkrgxV4VrLHWN0xZqwHpX/JAv0owBtZZiln6ddc5hi4BYYAd6zds/MVYDfWMwJ2dTAtDXjpzvPzRcYru6YK0A15qqSVdyowlYsK00opTIPZfwV4s4BMSvGh9dGmjRIfpcmBVfTFzXqY+rAzMItFtXMZdegYqzshEpTKsUKgWV0fKK+uB0+wBGQmzJEJjOuABFOjtknLY1KbUKkprbV0T1N1GUOAVjfZUEmSIEEMcAMDXmnLeGACGmKBrsHuOvGsrHu2U02R1cmEOfrtBk+5syfM/bNI6iPmzNq6QtKBybECdntwHmxmz2wBfvUkFMQFwajxIBAQFsAbj41tNt4eJQgeiw6ft6Ga3JoAuWX5FMjt1fo4yM39dcfSAcXJKwG52hQ+mMrElbbUqNQnv3oiKwJpYBhZmfu8ArnO0ZjrRkDuzPYDU2VrwlqQWwJdy5MlAnKdGYLcKRGfXGFy5XnruAs0djeTbG45MVaLnA9MM5Q1JrcErFJGY0l6gLKu2V0NeHUdY1cw1r2mZBNwu441HosuXat3Mu/vBqKvRetHJdjV29exu9sC3vLcYzrdYVhar8aLEzmRB1MeUqD7lre8BQDw9Kc/PSv/6Z/+abzoRS8CAHzP93wP9vf38dKXvhT33HMPnvrUp+J3fud3Yg5dAPjRH/1RNE2Db/7mb8b+/j6+5mu+Bj/zMz9z5By628qlmpR5uMyC1Qa3EuyW+5ah5gFEU0DZD8hBoWbFAIyCXTFNlrKUhiQBXp26pXausfssZVNwW9un9L/Mji3zqSq/4tHo0RugtRLc6mUd2KjzOSsgIFf8chOrqxWmnNnVgFd/yEbTT6jZfWgFipWj3IQ5KcVRaU7T/tnP8GQhbRfGB8I41Q+R6MvRBVgrENyPXfELAwZW6XnXJoh69Q7o5SmRfpc9p4rSKqJBSxkMTCKnxuYxuWIqrG4wkruYJyDSC6gOljrEfDnPR1reu74+B9VneF+5F1LvzXg6sQmwqwHuFNityRTYBdjtgevtg43vZwS7QAS8dI8aAKuxbGCSmhqrDEY1xf6WbG7ZB0omV5dvC3K9CkoVg8z5oY9u9r4rkBsnrwqQmwHeaK+M6Q+pKX4jqxtyFtckkGuVL65l82UNcpvI7K73x7UmjDK5JciNAJdB7rqUQbV87yXIXQYXQa6kh5PJzMOwuTU3lMOIZnWzMSWU4HcIeOn4Qq8oQfXG11HpPEVZDdxOTcxtymIOg0gdXsZNnIfRjCeBMFLbaZ1MzlEC3m3A7iZSXtPlLiZU50uOpd4TuXTykJsurxNjDG6++WbcfPPNo/vs7OzgTW96E970pjcd7Xpw6S0ILgVovVQDSDXxdwUs1gbTMdHby8GUTlpEGdUgSIHdxORSGQ3SOeCVMs+MZwIZWzQCxp/ZFNMiQgp0arNRM2YAOk2SBryHjR4NjKdHyhUho3xyrQo+VQauSUpRGUVXt9Om/TEHWQyq4vNmBTbWpdaVEj19ArUPg1ujc77q7RNSgtygyik4cciWJbfulEyljSnN5uvPqZ7uaVPRLK5h9jy+jxWwi0KJM0UbGiCCXdqejx+D3IsZwE3XL7mzE+gVSw3pF9uBXQAD1rcmU+9yNGEGIsCVd9Ax2K1OogVijfPYBTlLW/rq1p6hPv/UNQ8sL2AG5ZcC5AYBroWQok19K4JdVN7nmNMaxTtfVpi/y9qiQIKiSWC0eo7cBHKjT67ZLuiUM2HSXFlYXAdhbjeYzAp5KrHcTJmeZS2Cvo68LtHzx9jcVPdw3JY+sk7KibL4WEbAE63nYFeX0Yp+Xyrjy1FkAwa3PM/WfsEDmb7utax5tXy8ro1YX9T1sxpoHgO7pUgdmzRX2LKfPazlUoGEE6B7SeVhEYzq4SIlA/JQXsfDQaqKLUsJaGuD6RirK4quRQ4Q5FhSdljR1exYBnaB3JSZygXcChBOLC/itm1lHaCdiqDqlZKd7kMDWyXGRgZaB9Iaix69yTX1CpyuywtagtzML7cEvYrNBdIjKMFubfzOlB6ATBD1MxbFOIJZzRSFcTOC7CTlb2IeRREWBeIwStVhZrkF3OZpcYZBaaR++dXPqvSdHkv3tI0MWF1gAHYBqCXEdq214UZmy6Co1j4k82UKTiX5shPoRcj9dTcBuwAgPrvCiJVsak00e7ZOdARkcZcQYBv7R0j+8zXAG9tDAd/k0xsGrG75bEsri1I2BbkCZDXIDcW2EtxqkBuC+LoPfXZFYiRvFJNVev+QDehFBUOgW3unS1Pl44qsXIJcYWpb08NCRVDmZQAZmztg7JGCqJWTl5mpcgXkxvEAyWR5jM2VeqoWIJXldWAsMzMeAbA1YFuW0bkqzxcYn+zYRDYEjJuA3O2/Deuue7P6xsDtYScA1n0ya6B2m3NtaiX3cNCvT+TTT06A7jHIgw1ML/VgURu0asEIShZjG7ALjJswbwZ2gTq7K+V0BgBpO4jtpT02H8S3AQ5VRkYYJmwOeHV5GT0ayFMkAZUonQrcynoJmgAkf1xWgmsgtzRf1gqyPleI65u0VHHLRrG6igUCWDnWTE9NFy6bXTGLcZ2VYPpFwUQOWchtpfbeSFmM9JuxnNMAFwBqZuXiX12yuSVDMzZO1NKFZDkwK2BXtorodjWq7CiMiO6DZJlRvP+VVGKjYBdANWAVS+kf2W/xjk+J9v0dK88m9VhK1jg3OS5AkJrYKKU6KbUByM3LFbDFZiB3UmLfAgbBzYAC1KhxfOqdrrzPMQgamy4fB8ilFEAhA7kyOdVaBriggFIlwJ22bLKDPlluB8ZzoYtfrgQP9LxcY3NLCxDdT2S5JmNXb0zgYGsmKytZ3TGwC2Aa8AJ1sDrVz9aM29uC3HXfgTFT6/Xfj+3HmVqdx81ET113ZG/jt2wzUFsrv9yJSxPWdrVD13sil05OgK6SsMlH+whyucxmldeZMbcjgHdbsCv1SoqWQXkBdjOJChKgQW1icTkdSHBKqcyBRfK9mx5htomSWhNncqU1Z5Vy377E5nK7KZNrHT0aSIA9u9bC5FX/6jQTJYurFaKBT25NQVYz/1pRlrLyGqg8v9bMfC3bkINdKlKAV+1XkwzYqv1qANfwVytTkvU6UjmQm2vZskytyyRKuY+eXNHLNd/tfIJi6DudP5ehSbnIWrWLQUjdnzpEsBv3jZMNqS2kHfVxm04Y+GBimiEZDzSrC1BgqloqJmcQ95kEu0BWNgYwBoByC3a3FD3uyfMoQfDQl7tuokzXMKI8lu/qIUFuNEtWIFeXh5B/H0tzZWFz8wIFgOR1nuhLk6LeZ5Mtq/7G4NYYRFNlwyB1U5BrGdgmcKsArSn+BOCyuTKADOyW0gf6PqX3fbxfCcClZ1wHuTWzZQkqmPvmJjYXyCfBhpOUR/veDf1yxxlffd48ENNY5YdDA0c3R5Z6xs+/yXg3ZQp8lPPr+xuzrNm0CbbJCLBNs14uuu+JPDLlBOgqEXO6h1IearPlKb9cYDzcvAaplwbsAoggj4E1K7oEGorAL0adP7LGeeRlKtuygbYQa/wQKGfkRSVYTQF66Rrz6NFTMgWW6Pg6wNXrWknuQp051H+1c2/Uj03FTFYryDC5cjz1adXPtQC3tJzONwS4GuiSkixg1pgAq7Zr8CrrQ2DrM2XYGp+ZLevJFXm2tWBnU2blHgadT88sHrOB+aE0Uc7QBlWaggPJ8xGJoFcfp9qwPIe+HxPoCVruN5bZPdpO5svy3gurSz7p+aSX44rzCYIC7AJ1wFuWV0SDYB3UDdjOukNkG7CbXUdRvu5dPQrI1YBnaLI8ZHVFtMkyrU80RHmbJmAwE1NpihLYyrHlu2wVkyvvprOewG4F5JbvsOVtObj1yizZRzZXLGqyyaspH3BQWjgNdoE0xus+UQJc2R5Tv0Emv4YAdzhW2/Q+IU2MyDJQNyvdBpiUfrlT28sJztqxoyzvIeTBALlT5ynv9XiupVZWMrx1kKv1nxRPYZwx3pTN1TqKLhORLQ+1fntkCdjU+nz7ek/kkskJ0J2Qy+Wl3BSsbTJbN8rsxHMlIKr3LyP0yRFGlR0J7AJ1dpdPUrK4msHNTZcNtjFbPqzQNdiirAC+EYzX/Yh1SqRtAmhp5pbqMVxHzv5tC3JDsQwgU5bl+ss+tM17FFPPCisgjaQAb/1AOX6NUizrFZArCnIN5ApwzbeRgqy3Z8wPFDBWyyJivlgqlbVJiUnf6eKZjLE1w7YeUzIZ7IbUdlKPKY6v1bmNyLXn/qspHzFFGE/R1i1SWi46YRHIrfTVVUA1mvuvy1s6MBUu36PDg15gO7B7GDZ5ndRArrC5entQ/WfSL3eNTPaJsSbUw+QG73F8d9VElURWNiaBXP3u6jy5cXIqA7fMBquJKyB9+9blvwWkr3KcBQV26fgEeLMo2kh9VljcyNAWIFfyoad98lzoVF8+TgBqjClAry7bRPSEWebrH/LxZVuwK/sBxwN410kth22+vc7Grk9PdMQLm6x7/fi7DcgV/XBTE+VSxvpNUNsvF536RB5ZcgJ0lRzVdPlSsoPHIYcFxLWgVDXAW4JdIJkybwN2gSGcle1VFjRenFyw3G/ddHlTs+XDCgHuWj8qldYihZKUFsAXWB9EaxCBVYFb2T4FcGkfYQnHmSEgmceWDMAA4GJzkGuAYVAqrSytVSgSwKV1ZCBtHYsbl8Hmx9ZnINcpllfYoAzwaiXZ5KC21s/EP33qua3zna4FCCtBbv6Mxtotqav5xJUOCFZ5BFFZSm26qfhAJsviK5tdO892pGBUACDmzEMTZrqIwmcXAKUHUoCkBnpHRPu8l1HMdVlfAIYxKcHsmC9veT6p+zjZ3LLu0mQZyMHtWonHbLCvlkqTZX2o6Hc164EIbNU77OS3AnLFTNlpqwsGvNpkGUAEvEBiXuV3arKUIn4DkiMdSH0uSyEkMRgwnFip5s6GBrEJ5Eo+9JSCLJkq110d8rGiZOgfDNkU7Nb23UbGAOw6M+Kjmhkfl2xyDVXAq5ZrALdcLkHuttdQij5C97PDTg4+bOSE0b0s5QToKvFhmjQ6Lnk4zWrVTZXzdQ18J02W1basHJuBXTo4j8Y8vGC5kBRhuayX0pTwTah7KU2XNwWRW8vY4x00tfapHfoQ5yau63NC57k1ixQ1BYDS5dsqzDXTx3iLIwr1lJRKTsq1iwh2tVSVEA1wAZSmjbJtCuS6WJYzuWMgd+i3lwegkTItWY7ooonKSQl5ZjHwlHoGtQBhdGzOtus220Q0wE0gWJ7HZozGJDPC1yh9W/qKsLg2RlxOrO6YCfMk2AUwMGHewnwZqANcXV4DuWPgdfI86rmn8xmsY3MPA3I3eW/LfnMUNjfKJv1EK+Fxn+H7q5dr7gZ6kqoEuWNWF2NsLjD0tR8Tnb85lRlldTBsk2G05TrAzX4VyB2yvnpSRE2OZJNgdV/dbcbsTWWM1aX1hxfYTW4zabtcV23/qbrTdR+vQjlVX3kZZX/dBuRuwuau26OcSDlhdE/koZIToKvkUgejOqwc9po2GWSnzBpFNPC1xUdA9p0CvNqUufyYan62NFUeY3epcrmBCYYXyEEv6qbLMRLzsX2URoBz0dTltYwBcbq2kfurKMOlOVpfU3CUEhzLNlSYgdxkWbNCRxZDrG4GduWEsot+TnqOxCBjgfIP+zjI1ezsFMjN/iomyyLlOpCYSW3SXmuv2qTEJiC3ZHNLtn2jpjdD80Jtjjh1XBYUaESIma8B3HwZSKxuYnINtAmzBrtZIC+VomsU8AI50zsig0jmNWb3iCC3lG3Y3I3qmwC5tfc2YEs2d0wm+4teGQG3atsUwNWWGOKPa41ezv8aU5anyamSzdW/24qwujq4YNk/1kfKH4JcMVkWkCu+ufIrebazFGTFuFCyubU+V+snU5LGidx8eVuZArtHkRLEpvIczMq+eXCsPDftuv2PKtuA49pppwBuuV5zZ5vSg6QvT23XUoLch7vV4zpR827HXu+JXDo5AbpKHq5A97Cy7b3kg7epbpsCvTXAuw27O1ApFOAdVTcKwFuyvMBwcC7BbyyX6zyyHclY5NSh4jRkbuvXsI7RLZWVGriV/QaKT0i5FTdlhWr3VrJCGynMDGyBSOAOwa5sHKsiashhuGumENeV5FRPDnK1r5Kt7ju8sdjnlMkt4FP07ZG2GDM134RxXzcRsYnUcmCOpQTRbbCpaJCbvZsg82UfDIPbxOpKh+jV8hjYpZPU2F05Bhj45q5jTCudLmN2J0DuOiA63H/I5k6B3E3Z3NF7U4rnmBXGGJub77T5N2bKLJm2bwdwgfzd1O9vnKhSE1Z1VwOuZ8sxX9xorKGkb8LmSjA0J24J8fu0oT8v6gBXg1ttrqxBbhlluWqyXGFzZX2dJc5xgJTDAtnj8tPdFPBuwu5O7T9W75hsOpZOtVztezTG4tL+258fWD+2haJfSdnlDnJP5PKVE6CrxIeHPurygynlwFgPCDFUckvQOwl41TEa8NLx+flGuVmzht1FAV4L0CvnGjC7I4O7KLiHZngnD6sxsHUALFLz8RxLe1SaLAMYgNi0nPwNtaIMAFMgd9vZfqnvMArOFDOwqT9f/dhh4KlyuzVhoFjU2Fot9T6ezJWn8rWWjHtcXgdqNpiI2FSmmJm6/9b4NhEBuTK+OrUMIEZfFnCrr780YR4FuwCqpswAynzUIodhdamecYBbbp8qK8s1qB2TbUDu1Htbq3fTyantJ1D1yuEYXNmv5k9fgtwIatV2/d4mBtdPrm8iAnh1P4qgF1Bm82vqEf9xmMFyjcGtgVydE700WS77C5CP8ZvK4cbwzcHtg0U05CbTw/NfCsB7FDPmowDc+jHj20rdaB1YL5+Z7k+J0a3ve9lJwHqb7cPWeyKXTE6A7iHkcu2T5RAz9YGzxUAe6zCln01AyfJWTZdrZUjsbnZuuT59rQJkg4n+erou1PYFK7eViMb6/kcBb6FwbypjjLHUWQNKU+bTm8yElgpzWT4FcFN53Qx2E9PHGptbk41n5o1ietd9GysgtVwvGaEpGXt2m/aB+CwimzMEWdX9Mc64623lswKw1TMqZZ0iuj6yaMh+14nsFQEwFOjVwBbITJjHwG56x3N2V8YGHb18yKxt4KtbaZtNAW6tXPth0q/N3lnZNhY0rlb/NiB3kz6xsRTv6ZiiH/fFNMCV8ny5wuqiDnIjw4sc5EpdpavBpv63ALWfq9xXFiRRAdwsX/PI5EU1ldUIi9uH5IubAk8NQa5eLicwy3WRTSdEDiO6nmNnc7etr/Kca332uABv7Ri939j5jlvW1VsC8ZpuNPXsav2JyvP1yx7onshlKSdAV8lxTtY8lC/06MzbJsfy7wB8jjC7Y6BXA16v6qiVyXmjYlqA4ymTZr19lKVVt6KBbyrbJKrxNCiu7X8YxjgD11PMYUXpzQBTZXkdwNXbsrJDKsva7LEsPzapMERl+XGJBrADc3oDjKW/komPqYml2oQE/dZZO6n3MAzuuv01qwtMP6/hpEJ9/PEBcDImqHc8vlcw8HJt3JalCfMo2AXq7C4wALYZ6EWer3pKpvxvN3muZT01kHtYk+WjSo3NLZc3lSmACxwO5A7WMQ5yS5PmuFwA23I5lq35SqbUVslUWdhcYf8jwNXgtvJ9yczVkfpDn/WJIZurGV3xya2C3AqbS+cYToqMSQ3wjo31Y9vGpASw9XrHDj5kv68dtwU4LfdZpw/peqeAtC6vjZ9CChxWhkB2yOrWrmnT8WXI6ublWpe4rOWE0b0s5QToKjny7PbDRLY3LVOzdrXtqAPfsUH+KIC3NhBOmTTTRSeWtAZ6S9BZY1wjo7pmxNkmUvMU2N1o+4aftrLNcpCbp0MpAS4wNGEr2SAAGwWfKhVmLaN9siiPGAbI2KKqTCnQRxAfTIRQ6yY2srY3ObtY9kEU9Y09t00Z9+z5bTAZoWWbVhpjLWr7jK3H4wuQa4HI6tqQTyaUbTsOdhHLMnYXGAW8+cVuHkRqU0VtDODqbccBch8sNndTP/vqNlmU3wrI1ayt7HMYkKvdDUo/+nw59YcsICDKAIHiY1+/vcjmcrTmfgTc9hMxFiKTOwJwNbBNjK4b9JN1IDdjdtf0leE11q99FIduOQwPvxdjO67vr2N9evTbkI0zlw70bsryjjG/slTe3RT7aibKavFWyvNvKmX/GAO4lzueM+GSzKGfBKO6xHICdJU8UoDuprKOsYnby3IUzKMZN330cSZ9CHiBIYjdBvBmQLECesW8ebAv6h8HqrtePrivYwLGZTtuKnVlpJ77c4wt1KavUyyurNdA7pTJcskG6Q/9cQUXmZLJNDcRUBHgmsqpnFhH1XcNYl+rTcAI4Cqf/6bPLVNK9XOpKKhxHwyfU/WeR9piXaTUdQB3k8ijGbgNBatbsN4eBUNeAbs+vu81dheqTAGQDQIDbStTAPjhDHKPjWHRYLec9NDLxwByJy8DOZsLIEZI1+vbSmJyAZ3GinLjJrALAJukrgKGKat0juYxgKv7gM6tXeszUznR10mtb+jjNu03Y2bL+bdgA5C7Zuza9lpKif2j3KcAqLTvQwt69eXoq90W8OryowaKGnvOJcD9dNKvT+ThIydAVwkp5g/1VVxaqZnP1Perg1djwmCgHQO9ug4PrWik7RpE0H6pHpHBR1WB1knQK/tWgC9qxxXl5XXU5DiB8WE/NjX/vnJZg1t9zBgzCOQsLqAVZsT9NcgVEZNHvV5brsnGTbDBpEAt7QOdf+inq/upmNFqVrcKdgFoM+aMqWSWEvH4NVGzR55ZCXB1+dizyusaV1CnFMxNAsjUQO6mjLpMLgjw9QC8MZlJuERhngS7gzIA8DGauZ5wiJMNhzRf3lbGAC5dw6UHuZuKTFCVZsvrJDZ7LKhMhOjlCshN29I+eb+qB4obY3NLOUxAQWo7Sms1un0M7AIR8NbcZIB8vO4H/SEBXDlXDeTq3Nrbgtxt2NzScmcTs+WaDnVokDtxvjFZ98RrR5d1bgp8jxv0jh1TXuMU6C2fYY2I2MQtZRsZ/cYU2y97oBtwaWjpRzjueKjlBOgq2dYf6XKSWpCE+n7g/UZAbjlI6+0oQO/IOSLLq1nH4hgNSjdheXUdA/ZWmypHwKIV3eGsZzx2U8BbgP3R/bDZfuukzgxOA5qa+bJsL5nBuDwAwvlHS++vlWW9TssVRehB/PjROccjX0amEZuB3WzSxABTQdJqfWPd85sCuLJ8mGcFHM83dRsTcT2JoE1AtWItoLecOKj6PjPCSgG+auwu0jFyzlAbLaTOaRbusH68+TupGbsEfI8D5NbkqGzueLRzNZmJ8f60CchdF3hK16VNlqdkW+BbmiuL9GX/Y3ArdWT+ukCV0a1D5XReOk8CtesA7rqJEQK4R5sUqVmETLF0Y1IHxfXt6wDuqDXKmmvY9pg4VGwCfNeA2vrZ1k8erquzNglZ6mL6bOv0pqPKoP/o5eIb/0gnkk7k4SknQFfJpjPZl5NsM3NXm11M2zaoo1BMNEjclOWdMmuWuqDqzkCtWi7Z20nwKxLqCo/UF+9tQ9C7lX+nkkk2e4N6MqVkAtyW5SVoGi7n78g2IDddmyxUlKC1d3o4CWEIcAX4AgDMMI2QDxgFu9KXIhMZEoNbRgYHMOiHteuL20dMzkuAC+RAcVuQe5QZ9loAKl0+9X6Qsp3a1KnxSZuFS25dWa+C3XhDNXZXypFvixeSVD3Ju11KxvpuqRqOAVwgsbiy32FAbu18NXauBlq0lGzuYUQ3ee0sUyB3sI/aLuW1Osd8cw87ebiexc3BbrpAvS5Rk6fTVtVyMQuglbJtAe42kyLlpBgwnBRJ15euOxT767JyrK+B5I1A7gYAd/IJH1Z/qzCkcVPlOgyP8/l1DcfFbdjeuoxd0XoZA7/AZnrFpjKYo6h8W7Jc3JexmLCRMdmh6j2RSycnQFfJI8l0eYqZre8/bqq4qXlNdvyIcn8UlleXAchBrTpXDfjG/SbAL9W/AUgVILsuQucW4Di7hg2eWe1ZjZkwV5nCCviZAk2yXIJc/VGbArmjivbUva7bVmnTCGontgOVCSBlRivba2AXKHxJuQ+VTG7WjzZ8B3MFczghUXteUxMS2f2p48YUkVo7lTIGcg8rGqyL766cfyqqdXx3I8rKg1LFylFs0/XFixiOSmPgl7ZVWMEq+Cx9ME0sj+/mlqAlXvIIcClBbn496d0cZYE3ABo1GdtrHcgtQW1tGUgs7VGlNuZrSSwuoH3BU4o6Uwe7yE3g17kqDKNv54D3Uvtw6/ao9ZepcV/vk//m5bVtw+2qUSrHxfVaIx4jWJsKprbJuTcBvsO35LAgdrPjahO8affjUXSnxouyPzwSiaQTuTzkBOhqeYS8iFPMbH3/acW2vm3dIK43bQ56ayxvBlDD0D8XGGdBB4pNGIJfYKhYZdc5Zu66jRlypQ23CYoyFYG5VFpryoguXweY5LhaigB97LYgd8pkOWuJQ7yDAfUeKH66dK5QTAAV6wXYBTAwY6YyJHAL1ccK0AusZ/cn2fhjfl7lNt1GY9fwYItmcTdO4RSBCTBgd1Fui2fKj497yHPLR6da/u369dcDwo2xuHLMNkzuOpCbX8905O2a8rnJ81/nw52NpyN9v87s5nWUZxDf3KMImSpvuG9IYFdy40awC0Dna6YLnK65NpmVs7mbA1yp4zAgt5wU0ddUA6r6ejNsugXIPRaAO9LnjpugiP2wdr4a+K3sN4S1m+hMW+hVk8dNH19O+B5Gqmx7ZUJD94PLnkgKGG/qo9Z7IpdMToCukkfCi7iZOYzefx0orgzgVSUnV1ZGr2EN6NWzkDXQS+Wy87ip8oDJVZdQndWfACRTPry1exmrZ3DMxh+xzc45ZHDGlZQaY5ivrwdM+Qds+FGrrZcgd1NFpioMTgfFIWd1dVAq7asrYDdbV2BXygTsSh8rfXTHQK9sA3J2vyZjkxWHfV61Oh5OIFfaeDLY1yTYBVADqyW7O9gm51M5T/ncTjHxImPAd/LeFFDRx46xuFK2CWgp962BXF2uJ0CA9C6Xb82wH2x8uwMZGyenApatY3Nr+x8txsH6iN4Ixftb63tF+qqpSRCRWi5lqnHcd7ssG+srUu+2IDcM9tlu/Jcy/Vvbpss2BrhrANVw48S2dZJ9JyqbTeV6KsDXYHhP64HvcC/6doWizAwsacbY29rx6+raRNYHHBvpAw/S9+VETkTLCdDVcrm/iFsyuXzQ+JbR+kxlP1224azkFqC31wN2MHFWf4ztrUVYrjK5xSVNMnD6GtcoWSWwOQ6zuykQUgO1QP4kNgFLel3vVwNLYwrOVOCpbL/s5ur3VjOZz3dIYJcgazpHacIsZduAXRFtWq8BL20jGTOl17LO/7r2vOTaddk2z6y2nZaH29fJpDnchrJpHZ7BRQ3sUiTlTdhdpH0KwKv30YAXSL7DY8A3XmNlbFsHcGVbCVpk3ylmLu2zGcgVGWNux5TTTaQ0/68+0yOwubVzjV3DccvQhBmIABgYAN4ykncp+fg8btIu+x61r0jdZV+R4y41yK0ze6pBxkAR6vsMjq8eUJd1/TrrQ1P1mfo1mMoYENboD7I+ALEbmyVvBoClHBh/V+SeNn2XxtpzkwmOy51IOmF0L085AbpKasrA5SRbX/kh2FySDYFsdf/Dgd5SxtjeMeAr24D6gF4qKWNAuHqNm3wgLkG/OgpQysvy9XUAl37HlZt1LG55nRspNJVtA/Mynlmvgd3AZsrrwG6qPLG0VtVVA7zaZJmuS/XNkX5VyhQ7X4JbKsv3OyyLe5jxTgPVWgqnKaE0P2WZqbK6ZT7IrcAusBbwWh3wSo00JegFxoFvuV8GYiYArpSXzFytXDNzUu+mIHcqgJzIUfvDJn6A26af2kaOwuwC6t1TwDb2gcHESd6HdAqhdenhSlN2OiYHt7KtLC/Z2k1YXCnXfQV8OyXDuwnIXT/e18t12doJz8E+5bZy58P12W2Pp3G+tuFBAL8BE5ZLZdkUoJ1mbwcMdDH+TslaH2x51v444z2fyIlsJie9Tkm43P+C2eoPa/5kBm74V9a1bnt9X+9Tufc2LbMyFiAfffrr9T5qufdknid/vaq39xZ9TLkwrGdqPx9IQZW/sXbvi/36oo7j/Bu7nvK8fdY+6b7KNpO2kvaUfWP9o89vqow/cNKXkCs18ZuottM+daVh9H0dKEFDxSl+dEONgc6VtNLPOITEfESFMbZT3n66jcu23+Sv7IvVPl/07/Kd0e/N4F0v2rc2qTc5VhxSahMr5Tlrou+pjERdlmfgMSglXzGgsh+gQAaGLGmqL/3JMfX33BZ/VE8n+U6Djft1KvdpF6xKBZOAS1mugUvJzo2B3NRWefuWE1e5Qrr5szluGY2+PLHfYUX3Hd1v4nak5wHw9wcmK/fBYuVd7AOrYLES4Fn8yTbpByvvsPIOnfwFi67YLv1EtsU+5S0f47I+0akxZF1fGQO5Mrbod/44QO7YtyCo66HCut6RLiDtPDo2XQqlSqoeGxNHjqnpTVUdq1ZFbQz2tn585Txaryr/aFv9+mr1yN+6/ar1e32d6ZlfzmIu4d+28uY3vxk33ngjdnZ28OQnPxnvfe97J/d/z3vegyc/+cnY2dnB4x73OPzkT/7kYJ9f+ZVfwROf+ETM53M88YlPxK/+6q9m2x/72MfCGDP4e9nLXhb3edGLXjTY/uVf/uWHuMPjkxNGV4sajC9Hqc4YTh8wuXls67qgCsNZxVyhyrfV90OxRzJhVnOlITG2Zb19eQ3BZEzSKLvL5VO+utXjNpRN2YdSAatJTREdAxa1NBGlEgykp3EUxYYWhgA3XcDEjP1g54po3Yb3zdhd5TNloPpGMNBbNLM7PLkqEzZP+kZxObGvhdyknq5rs+ddf5b17VpJLa+69mynGLtNwUz5ful1YXWlbPiO1+sbsLbqngYm3oZMmMsgX7kpaSWlS9wuBTm7q/1yc4YX8Tqm/HMzYDnC2GngPcbM5WUKiByzj6Wsp2UMyif9dZX/+aRMsLnHze76MB1J2cNE8/dBlP2i38SI6QGoWQL4YBSD64p+On59+lpEpljdfOJlvJ8A8i7VWdy4jmFfScuIy6E4Rsrz3y2+A8DgWwCo13HsWzDog0Wfm+o6x6XDjbG48RLq5xmDc7XSKvMr5x5sqJxvZKwdY4Fp2+H8cqvnqFyPPg8w/u2/LKWYADnWereQX/qlX8JNN92EN7/5zfiqr/oq/NRP/RSe/exn48Mf/jA++7M/e7D/rbfeiuc85zl4yUtegne84x34vd/7Pbz0pS/Fox71KDzvec8DANxyyy14wQtegB/8wR/EN37jN+JXf/VX8c3f/M143/veh6c+9akAgP/1v/4X+j6lYPvjP/5jPOMZz8Dzn//87HzPetaz8NM//dNxfTabbXeDxywmhMveav7Icv78eZw7dw6f/bZ/Dbu381BfzpFk6wFsQkEYq2oTX6zyOsZ8sYbb6vtNBSvR1ZWKzLrAJ+m4QdHk/sPjH5zXaAwAl4rAOpCk61oHbqe2HRvAPWzzDfqSXgnZLpukOknLY/vkddqiPF3H4fvDFBidArfD5XodR2Xqau/iVDvpNkoBvJAFFJJlvb/OkRrLELLjym0SHdkW+8h2vU7LCeS44plNRUWfMmGu+ebWAK7eNgAphwAu60BuQF6+9eSVyLr+M/ItWNtXivdPv2NjfUcHhJO+U5ZTzut6v5nqM2V/meor62Rd/8jWs2c9BLiyLP1EbysnQ4A0gVSyuLQ83lek7LgmO3W9mwDcjcDtRF88jGa7sf40aq4/Vu+2+2933q10tTV1bSSVdq8+Z7VvCIC/eICPveQHcd999+Hs2bOHP/+DLIIRnvj/eS3c/PgxQr84wIff8n/j4x//eNYu8/kc8/l8sP9Tn/pUfOmXfine8pa3xLInPOEJeO5zn4vXve51g/1f+cpX4l3vehc+8pGPxLJv+7Zvw4c+9CHccsstAIAXvOAFOH/+PH7rt34r7vOsZz0LV155Jd75zndWr/umm27Cb/zGb+Av/uIvYLjTvuhFL8K9996LX/u1X9uuES6hnDC6WtbM1myqIF6qABmbCM3kbb5/bUYx1jV2H5V2KEumWN8pxjerQ+2nZyEH7BJyxjerkddLfz8gv4ZeMNCamdQxQDzme3kcgXumpGQRjgMkHcX3aiuAO9a9NnjPkh+2Lkz1x+iYit1F0TfWs7v6BCWiTv3NqLq1hUF2nRvIWoZ+ZN/DgtttFEGteOVsbmq7MVZXM27lsWOsri32ARLbptk5zQATE6dSwAxuQp0kHl8PRpXtX8imfrmyXjJzsr0ENjUWN7bBMQCXOtu//h0/imwKHA7LMNWsB4h1Hb57ZX8TS4HRPlP0F83g+tiHKlYEyPtEPJcsF6b48qvBrexX214DuLG80k/0trSc2qS0EKn1lWOLyVD9dkCVrQG3RxnHxvp0phusr6YaeTnVMFI6oh9swf7S/iO60hR7O1LXGBs8JdXvSKXetH+x40OnGh+LmHC0+YGpegHg+uuvz8pf9apX4eabb87KlsslPvCBD+B7v/d7s/JnPvOZeP/731+t/5ZbbsEzn/nMrOzrvu7r8Pa3vx2r1Qpt2+KWW27Bd37ndw72eeMb31itc7lc4h3veAde/v9n797joyjv/v+/NwkJB0kUkIRUQPTGegAVg0XwAFZEUVGrLbRa1Nbbr3w91IhWxUOl1pJqb5XbUrV4q+htLfzur+LhrlpCrSg3WBHF8/EuCigRoZgAQkKy8/sj7GZnd467M3vi9Xw89gGZueaaaw47O5/5XDMzfXo8yI158cUX1b9/f+25554aO3asfv3rX6t///6W9WQDgW4Cw4h03lcQQD2eBXM+kdQAP10mHdpgWHdx6YwHkiOs5B+o5K6OydNYB77J3WpSu0i6l4u10RzIJgXACW22CoIl63XYkTTIdT0HdMJoqtLlaqqUmvm1CpKsAiRvgW9iZZkHuOmcVFtup4SYNB7wxrZ4pOtBVfF9JRYImwJcm8BW5v3OtF8mtCH5VVbpbv+U87vk7ZlGcOt0Epdc1vKBKOoKSLwEu7HliCg1+Eh8KFVsXEoQ4vB3YtBiFezuqjk+PrFcandmyepxFW4PF0psV+fczAGD1wC3a3mC734aW0yn3hq+uO3PObzIK6V2Y07c5l1djhP2l4Rgd9cUKXVFFUndDxO6L9u2JekYYtpXUvaREtM0yRdIJPcANzbcSJhHmFlcuwDXVE7mcZ6ytxa/L13lZC2T31lf52v2D/DMSgBsd75mc67WOcr+Oxm/IGtbwiU2ddo+FtvXbnnRySqjm2zjxo3q6OhQdXW1aXh1dbWampos621qarIs397ero0bN2rAgAG2ZezqfPLJJ/X111/rggsuMA2fOHGifvCDH2jw4MFavXq1brrpJn33u9/VypUrLZcnGwh0ExmRUAIT53laDAvgZCH+w+FhcZweEeD1yqKX4DfxL6+Bb+o4c+ArOQe/ieNj7Uw+ibd9wnJC++26JlsFaUFm9N0zus5XWO0CJLfgyE/21jTPdIPbdFZZQtAVHxQxUgLexBOQ+I9+0jY3kgLc2D5oFdgmB71d/zcSxia0xwcvFzFS76H0Htx6vahgF/gmBryJ3y+rYDc+TgnrOWF41Oh8erVVhjcWHEuKB8jJQYtVsJs43vKJzKaF6vpvZ7DtfVtZZeUS/2/X9TT2r1uAm1LOYpxd4BIfv6tN7pk4D9/5PJB8MTM5qE2OAZJ7FSTe522fvbV4R7MS9sVYfR5P2JPnYxfYxsZZBbexcpaBr88ANzad1/0k3SyulwA37eDW7hgW9r7qGMgm/oYkTRZgANzZDLtp7Gbhfk+u31Xn9mwN+23rc0b5xlA4y7CrzsrKSs9dupOzqIZhpAxzK5883E+dDzzwgCZOnKja2lrT8ClTpsT/P2zYMI0cOVKDBw/Wn//8Z5111lkOSxQeAt0E8afj5VrKSWYmdck1cDZ2nQTYTW//sIPkgUmBpszzTulGkxy0JpeNBxFJwapFQGsX/NqVTy4Tb69Sp5cs3osrByFfLLG9qG0T1Hb+3254ahmn4DZxvKkdDic0du2zXxCH9Ze4XSyuhZi2rWFVzCXgNe2HXWFw4t9OvQw6553QRJuA0W58MrdANd3A1utxLmK1XhVb7q5xXoLdWGCSWldql1Ivwa6U+o5dU5ZOsg1cEucT/1suDzWyWJfJwUfn/52zc3bBi1OAK5kDm+Qsbsp4pY7r/Nfb8MRh2ZC4P3krb98FPjEoTbkYsivYlVK7v0uK7zex1wYld1FO3gfc3ovdOdz83tzk8k7BbWx4yjiLbZ28D8XXjU2AG5vWaV8ILMB1C4KcjmNW69X2t8NmeCaSfwbsytgdax0mtO9YbD+N3yywc20+WVTk+LuevF0D6DG5u+vXr59KS0tTMq0bNmxIycjG1NTUWJYvKytT3759HctY1fnZZ59p8eLFeuKJJ1zbO2DAAA0ePFgff/yxa9mwEOgmMiKhBynpSHnqpe8KUk/AU8vY120bCFsEwSk1+Al+jUhSgNpVNjmI8BL8dpZ3DoBjUt9HlzjOItBPGRJsJteqHV7He8342Qe/sf94C25T5unlym7S9J5ZTZOYxZV2ZXJTA16rLs1Gwv4V6Sq2q7kJ4yKpQa3tPeMW+1rXOG/LnE5m12sZ6xlGLL//idOnZnHNw9MJdqMyVBJJCFZ2zcsusxsb19Uoc+CSIilwSS5p29XVQWqWLjWwtfo3kwA3tWxqgOI1eIlxGmcpy7+Nhsw9AWy7vTtdILEJdqXO/Sb2LuzE7u2JWduuuju7KCdn/a26tzt1WU78O2qxLez2oeTsbWz9WO0jXeXNddtdCHG6CBJKgGsTCNkGt1bHMKfjWpD7afJvi2UZh/Y4BMCO3aDT6EycTsLCK8tjg8vvuWUmPg/Pr33L4gVAK+Xl5aqrq1NjY6O+973vxYc3NjbqjDPOsJxm9OjReuaZZ0zDFi1apJEjR6pbt27xMo2Njab7dBctWqQxY8ak1PfQQw+pf//+OvXUU13bu2nTJq1du1YDBgzwtHxhINBNZCjnO7Gr5AOFj+NGandh67otA2KbaVOuLloFv4lnLLvmYwpKPWZ9k5fBKvjt/Ns9AE4tJ8vhydMkzi+Z1yAmU3Y/jn6yfbaZmywHt5lmjay7hSVs14S9KWIaHhuWsDxJWV5TjwPL7sqZZXNNLXa9oOE+Tcb3rzmckCXWbxXwZhrsSp3dmGMBiZcsXVf7Ov9xC1ysg96uYMXuwUKdZSzu4c1idi4xwI1NaxXgJtbrlsW1Gpc4zCRrxzabh0uZLjDZ/98t2DVJ2G+krssfycFzrI7OMt7Wg11wG2trfLhDYGs5PKm+TPaRbAS4btlbz8Gty+9IiiDO45yC1HgZD4Gw4wyspZcF7pzSdkxsWbx+lX1cTHDtXm5x4QPpmz59uqZOnaqRI0dq9OjRmjt3rtasWaNp06ZJkmbMmKHPP/9cjzzyiKTOJyzPmTNH06dP10UXXaTly5frgQceMD1N+YorrtBxxx2n2267TWeccYaeeuopLV68WEuXLjXNOxqN6qGHHtL555+vsjJzCLl161bNnDlTZ599tgYMGKBPP/1U119/vfr162cKyrONQDdRNNL5CUMI2T5J5gOHl6Z7ONjZBsRJQWN8/laBoUW51IDV3KZ4ACFznX6C3/j8E+uzCWKtgpPE4cnlTfNLEtaTtoPO6KaMtzkBcw1ugw5s0zmRtrginhr4Oge95q9PwsmbU9Dr82JLfP5pLKPdNH6CkUwuwMQf2hUfkJrJ3TWXWIHkuXvuxhy7Zzf+lGV1ZXZj0yhhnJSa3ZXsM7zJ2Topueup/YOFEuuw+9spuE0e7zU7ZxW8JNfhNcC1Gpc6PmmB/e47RsTzb13yhRHLcXLO6iZeEHEKdiWbfUYy/Q7FLoAkvwfbS6bfavkSud3XnU5wa/47dR/IeYBr8VvjKbj1sh+67Wbp/iQnH9I8FbYalW9BcLyCtHj6zXG9QJHevPNFxAjnVN5vnVOmTNGmTZt0yy23aP369Ro2bJieffZZDR48WJK0fv16rVmzJl5+yJAhevbZZ3XllVfq97//vWpra3X33XfH36ErSWPGjNH8+fN144036qabbtL++++vBQsWxN+hG7N48WKtWbNGP/3pT1PaVVpaqrfffluPPPKIvv76aw0YMEDHH3+8FixYoN69e/tbyADxHl11vSNrn7t/qZIeOXyPblAxtp9vjdM87cbZ1J8SBFuVSyqTEhCkjHeuM2W05TxTh9llZd0C1iBetJ4p7xnd5ALJ430EtkmFbINbv1d6TePsR5l43C8d953E2C0p45cybcJ0psEp+67DCYjH/cb1aJxGMJvOAd6qNtPyJq6TiHl8uu9JjQ0vSZg++T27sbYlvyM3kvR38rtzk7eV3b243u65tP4eOWV4rYIYpwAmiADX67jk4Z0DMjjQ2XwPI477TOq+E0nY3pL9+5gTp09+h67V9CWmdqQOs/rbNC65+7LDj6iXzK5l0Jv8t0Nwm/i3VYDrJcMfWoBrtY95CW7dAii7YSllfO7HQZ07uY13mk8m9brVnQ6vFxk8HEOi3+zQup/dXLDv0R32f2aptDyE9+i27dA7c68vuPVSKMjoJjKU2ytOdvP2e85hysB4mKfdgTE2OLmOWP3Jv0XJdRnuGeCU7K/hkPm1qNOQRX3JTUu6Oh+vN8Zi+vgoq2W0kIv7czvLWA1Mnc42qE0qn2l3ZM9dmOw4jXe90p4UgCQVjCTvaPH/dZ2cmbO2sQIJ3ZWl1GyuusrF55WSobJrszcZBbJ+TvZiy5Y8OKkNkYTyXcuWvIHM66OzXOKxqbNc1IiYXu6T3JW58/9dmbiSiJHyGie7bF38PstdbU/O2MXaFi/v8UKC3X2YToGM14cHdf5triPTADdxfLoBrtU+aHncMyKWvymOmVvD3N3dNE6KZ2cTewFIMt3jHc/mxsd1Su6GbOrOvuv/Thnc5KDXLrD1su/YBb6G1bAMglur8ek+ZMpzcGuauXV9KQtrF9ym7JeylskFmUzqc8vWRuRyYHaaT6Y/FhHn6l2n9znOz0WJXJ5fByGsGKHQ10ueI9BNZESCP3AGwepL4DWwMgV0dmWsA1dTHZYnNBbTJB1k4z90TgGwVfCb2J5do5IfLGXX9TlhEvcgOGH6xHmktN+iPnO5LO03Pk9EPQe1SYVDDWy9HtTj+0HsjMqhrOWJhX3g6xr0SuZ7em0C3/jUFifw1q3wztNqSvdiiAXb12BEjJTDSMp3yWPAazkskvAu3ISSURm7ApFdQYsRe69pp8SANx68WAQubl2WvR7zPd93aRX0Jo3zmr01TSPr8WFlcL1daDMHiKb6Eo7XqU/odu7lkBIAKzXYjY1PvDAiyXRxROq6b1vq2u6JF0qSA9+YxLJ+WAW8VvtCynCLfSjI4NZ5uEzBramdbgGuXXCbMMx3cOvjAowvVlfw0qrHbcIMIhe3QNXufMxp9k7ndl7b5DatpyA4D8+vUfQIdBOFdbUmUVDf83QOGFZBp+V4h/mlBLYW9Vme37oEwBbBqpfsb+c0NgFwYrsT6ja11iFASa4qub5kQWZ1PZ1k2o6wOml1njitwNYtqA3qKryn8l7WfeLJps2Fl4R9zqm3gd3FFsmiF4CHlvnl/WnKHstF7OtMeWe2RZCYHPCaH05lKpHQMHOwK+06cTeSnoRsE/AmBzApQW9S2fisIhbvUfUoJbNrEZzEli5xWDaCGKtxqeMTFya94NaKZcDrMdhNDFp3ldj1b1JbkrKtyY8HSw54TfvHrjKJwyTrYDYxAE6X1VfJLahNHW4eZtXV2U+AG3b35JTsrVtwG0Rgm+nBNZ3pPf0chRgIx+r3s3umMzvLwNWmLbuJiOE9x+S3XoSHQDdRNgJdf+fj6XE9xroUcAqIk85PTfW5BcFeA2CrE+mUc6CkADix3oTJLbsr2wTCpvmkVpUy32ShZ3Ud6rd/yFNyObfg1Oak2Gr+boGtl6vAgbG8OmNfPHm/8xD4StbBr2Szn9k1K10+153X/dH0CqaUkeblMWV9EzO9SQGvkfJlt/zyxYfFu7V6DHjjAYtD0BubW/KTc5P3S7v7MZ0CHT8ZOuth5r+9Bred//c+LnFY14CkCxc2y5nOT1VKwOsj2I1N5xQIRxL2ObuAtyPhgpRV0Ju4X9l1YbeS0oXZ5ftltV7dgtrk4Xb7ReK4tLK3kinAzTi4TRhm2U3Va/Brx+PvW97I9BzMy4JZnYtlwmmWmV54iH9pfbQnH4UVI+TrflwkCHQTRIyIIvlwdcpmpze8XvZJLuZlkSzjBJsJ7QJhp0Ay+fzWKQC2mMZzBjipXSlBcGI5pZ7cpHZVTvrbZf/I9GFVvu7ltNtPvASYKSe7zuN9B7X5cGJiFZQm73cR67KmCy7pXGxRUtkkmbxqyFEa6zflFWEJIkkVmmP4hBPy5HUVL28f8Hbds+kt4I2NiwcyDkGvZF7HyVndxBa5Biw2w/1k6KwCGbfg1lzWfVzq+MSFsG5rfFjKEG/srumYAt7ECyPxC0PmYDd1mNMFktighH1EqQGvZA56Y/tL53CLANflAohTF2anfSi1F4D1ONt9KGm8l4seOcveBhXcuv3e7JKL8zWnpx57lnEgHCtnVbdL+zJdZ1bVWwyz2jZ5cX6N3Q6BbqKowr/ilMH33PYg4ePioG2wbHfG4jQfP4Gwh2A2ZToPgbPlQ6VMJzFJdSe1K+WkL8NAJaxnmLsGP7aBpUtAa1Em46DWY1sClRzE2pZLCn6VtI8m72t2wW9svGwutsi5PYFl/wOpx6GdSV8Iq3cRdw7fdQIccMBrSLuC211z8BD0SuYAyzLITaOvWKYZOsvuyxbTZiO4tV36dPanWMY2cVDSfO0C3ljJiO0w7wGv6QFlhvndu7H6OhIaaRXgliRU7/feXMm83ROlrH+XoDa5jNN2z3lwa1HWcZwVu2B4F8tzn5B+a914eYWPazCc/FvjPEN/0v1NcGqy122SRj2FhK7LhYlAN1HiuVaY83Dj+8DmfXrTwcmuXPz337Acbjutl0A4JViwmDY5CPYSOFtNJ/dAWHIIVJKnSyzm9cfEx0UIXxwzCB7LZxrQ2g4LIPhyOK+1n8bD/mY1TfL2t8v6Js7Dah9L+b5YXNHOYNWE9iI4w+Lp6F0jk/5KuIhkEfQmB7xGQoAaD2YiiSvVIrg1uoIcU5ZP7kGvlBzkesveeWUd7FqPdwpsE8e7dz32GNw6BFOWu46HdZC8z1nuJ6bfFOugN5OAN2lmSTV37R+xsZGEwNdUS8KFj9h0XcsVm8ZilmlwuygSa6tVebsLF94yurERwQS3VnWmZG/TCW4dAtuUAMpum+QqOPAQpEZSLqha1+Opl57beVe6XGbtK5D1GtwWetdlFCQC3URGJJiT9Izb4TDO74FRcg1o7crED3QO5xuGW/BpVb9T0OUlC2waZmqwxTCb+doFw8ltsGuvPAYtGf4Yewpu/F5ZdQtoLcv4mK/Xdngp5/dH3u1EPFann2DW74UWh7aEFqxmyC4DkZq9SAxuU4PexBPq+P2YFlneWMDbFcxaB7exGr0EvZJMr5+xzOAFcHy37PobQobOfnxipdYBUvK8k8ta1e+F/evVLOaRFPT6CXhlmrJruCmoNZTw/4T9LaFMrJbEv1MC4OR2W/DyfuVkloczh4sRnX+njvN8D7ZdcGsaZ25c2l2T/Qa3XgNbr0FUOsfRlONzBgdjD8Gu54BYHupKrDNMfi8q2A63OyfJg/PrTHT9JAVfL0JDoJsgYkiRbF5xSuc7b3OgcDx+uAVyyWXsz21TxlkeqBN/rN2Cz+Rh6QbBidPanitZTG/VJqs25EvQ4jZPPz88Xk4gMg1m071q7FCX41Vwp5MLp21st4+lu38lj0ueLt/YZCAyehdx0jSZdWu2D4bjpSPmh1CZu6QaKUFFbBonTj03gsrQJf4/ky7JboGt1wfW+RZJrTvlVVWRpD0pMZtqaordD0XCvmYT1CYHvvF2yLyekvfPlMWx2CecujG79e6xvjBiP95vYJs4PvFCU/J88iW4dQxs3f6OD/d2MHX8eieuv7TOxdxmIOvzFKdyXsoGJchzCXm4bmBkdm0BSBeBbqKwrtY4zc+Nx4NeygHEMfB1OcB7PXm3Og/xEQj7zga7/Zj6yejatMk83iEwthLED5Tf/c/pF9rPia2XX3ofV9ZdA9gMvmeuV8HtAmK7IDidANhtWrfvVTZ5PbuwWj9JAbDt06ktgt54ljdWbyxA3dUmu27NVlleSSkPMLIa1/n/pHDJ6h7dxOXzuGosh3sIUqzHhRvYWt++YDHMol6vIlbHW5tZeXlFVez/pld4WWRsY+PssrmJbTM/MdwcBJuXJbHu9A/kdhcT3HoBOO8rsf+47Ac2WVtT+WwFt14CW9cgN82AyqouF/E6/W56I+LtEGL1O+JWNlm6wbjnsvYzsG2244WEDNuTj8KKEQp9veQ5At0EkWjIGd2AD1S+srg283cNkJ2CYl9BQOqwQINgywYqdT14zera1WfXDqv6gpTpj3smmVk/wWy6V4nT4XJyYnmflN3+lc6+ZWqDwwUhq/qyyekCT2ph97qsAt/EQCQhYFX8K26Ya/cZ9ErmwDf1lTRK+H9XAxPLdQ1L77mpdgGQU5CS/Hdgga1bttYq+Azq4lNSUJkyOmKk1OUU+Mb2ga4B7oFvbP6J+0Z83klts8rqJpZNnD4o6e8riX9YXBiR3fjYf5Lqtagvq8Gt18A2edukE1h5Ge/G7vzFga8gOZMscsD7qJcMrN92uNVJRhe5QKCbyIikcfTxU7/Hch6PBpbFfAS/7tlch/nZBAGmOr0GwhbDLB+aZToXMlKGpdVlNZHtlVQPQUy2pbuf+vjx8v1URb9Xd4PidKJhMy4lCPZ7gSV5eLoZcXOj3OsIguP6srk4YNe2hPKJ4WOka6A56DUSgpGEOlyD3sRxEVkGtsnBr2QOHJwyen64ZeeS55s83ulVXmkFtl6DWtcTWw/rxSKITZ1Naj1Or6nqHG8f+Mb3h4Q2pmxfxwA3YT5J9TpxegaD18DYrdty5wCHCyM25dLK2ibWkUlwa1HGU9bWJrC1PLR4HZYg8MOnzbUXL+W9BL2+z9/S4WedpBvAOo5LWqBorq72BiNihPMzzQWAcBHoJgg8o5vud9rlqOo7kytZfpPcs7kO87Q5qFsGw+kEwlblEoa7BcKd87IIhpPrtpKyrAVwcE7jhyiQpyr6+ZHzwPL2ca/VWO1PKeOch3m+5zxpuKfvuluZbO9ndgGsIevvQOL3zG5DJQYXu8p4Cnpj87QIehVrjk3gK8k2+I2xyuxmyirYcQt4A+mG7BBEW1cmT/uWl+DNy6tVrBqQEvwmbPv4vJMuHJm6E0v2we+u8pJDltblIodVUOsny+tY1suFEYdp7C5qpJW1Tfy/W9Br1cDEiwZuWVsvga3Lvp1S3koWggTbi/x2Us5FPM4oSwFPxt2/HRbIqW4COuSC1TvWs+all17SpEmTVFtbq0gkoieffNI03jAMzZw5U7W1terRo4fGjRund99911SmtbVVl19+ufr166devXrp9NNP17p169JrkBHwJ5rmx6XeWEBu+TFsPtGI6RPPXid+okkfp3ma6k64SGC1/Hb1WLTNsi1269RpmMUyR4xdn+ThTvPwuW1C/Xhsl+1yGx6X2WUbdg6PbRvzxzxfp/3R+uN5f3es28M+7raMXtatzXpNWbf5sF/ZsVpHhsU6str+VmWjqWWMaESGoc5P1DxN57hdn/iwrrKx8obRmROMGhFF4+VLZERLuuaxaz7RaMT0MYxIyjDzeNl+nKezqSsaMbd9VzuNaEnnNLFliK2qhPWeuBzGrnWRuN6T11dsnVluF8Ni/dt97L4vyXW51WPY7FMW+5NpWYzUZYnvBwltTGynadrY4ies36ip7pKUT8o6yuDTVU/qfGJtMLUrYdsbVm2ILX80YV3F1ldsngnHYMv2xNZnNGHfcBoXWx/xY4P5O538G5r6fbfeD02/BXblDZvjutOx0eY3KPRPNOnj4fjr+3wtiI/DeaLj+vT72+5Wd/JvXSHzsK0D/41GxnKa0d22bZsOO+ww/eQnP9HZZ5+dMv7222/XnXfeqXnz5umAAw7QrbfeqhNPPFEffvihevfuLUmqr6/XM888o/nz56tv37666qqrdNppp2nlypUqLS311Z7AuyVE3ItYcmmD42irkRbtcM3mSqYfPSN5fOL0CZVZZ3Qtq0yqw2l6m3ZYtcFpuRzG2WY3nZY717y0xamM3TibdZF29yUv4/3ysP86XoXftYyu+1PKcLvyyfO2alDqIMu6PPD0/kW7+p3aYVq+pIKGUtdL4nc0YlMuaXw822vsytollHfL9krqyviqc7rkrK9pcRIzwKYRXQM9ZXpdylh2UXWpwylT65qltZqf1XJ6Wjb3Iqb6XKpMvpc2cdqUzGlS2fhyJ/12WGZqbfbVlExwIr/bPV02dXt5SJipXYnjEn8HjdRh8bJW0ziNs5xX5z+OWVubumwztgn/T9k9fOy7vs/R/JRPZ5ew+i56rSdH5xOZZ3Qd6naar4fZAkHLaaA7ceJETZw40XKcYRiaPXu2brjhBp111lmSpIcffljV1dV67LHHdPHFF6u5uVkPPPCA/vM//1Pjx4+XJD366KMaOHCgFi9erJNOOslfg4K+spJOXR6OBLZF7EZYnXO4DUg5cXcY7yMQtQ0+rIJht0A4sY7kk0irOpLaYrt9nIJjt/JBSWffcQ027Rtq+8OXQXCb1W5KdhdTksfb7ddeAuGk+dgGw1b1WZVxK+9U3OlMyq2u2O7vtdtyYp1Owa9V4OsyPjHolWQKfE1BT0LAYwp0rILfeJstujDH253+l9Z2M3oOPpPL+AtqPQe0YV18svvOJLfHqkk2F0EsA2B1lTWtI4tju+ODpZwu3ljw8n50z92abcr52eZ2D6jyFNiayjnsI8mBrW39qXVZBrZJy+PcXTnpO5rOb5GfMulO7+OQ4fjbl41oL4SLAY7N9nqeUOAZ3YhhKBLCeyXDqBNd8vYe3dWrV6upqUkTJkyID6uoqNDYsWO1bNkyXXzxxVq5cqV27txpKlNbW6thw4Zp2bJltoFua2urWltb43+3tLRISuh6ETQ/BzYP+7vtb7WXwM1+kGOA5xgYJ56D2AayFsFwygmJQzCcem5kU4dFOxzaYjnI8UfKy1WDkPg4Oc/oviabcYHeK5VpNsWhMc6ZXJsmeNmfk+uzu7iSXJ9t4zyUt5u3E8uLO1ZNiViPswqErQJgq+DXKrBNDlgdxtsGvp0Ndg9+7dolm2A4A37eS5vOfbRuDy2yrcdpuF096UgKRu3H28w/cbexvYCUsB8k15tQ1jI763SxM1bEou3pnHOm9URrp+3tIdtqGfTajU8Z1zUoJWubYWDrNai13G28DkuQjbhRkmM7fO0yOY5pPK+vDH7v7Q4JWb34HQZD4Wy/Ql8veS5vA92mpiZJUnV1tWl4dXW1Pvvss3iZ8vJy7bXXXillYtNbaWho0C9/+cvUEfm0EzslbPxeLbQ7D3HKViXVlVKtl6DYSxAaZDBs1Rankx2ngMamXGAniUHwul+5nSikEfR2jvOQHQnrAO61u5jdCXTyn172oZT6zOX83g7gY5Rlu1I4rWwvwX/K8kRS1otj8BtW4Ct5C34T60xi24U5ALZBTjrBrEUZXyf/TjtR2N9FtwuwKZnc2HD3+twC4fgot4tNSW0IvPuy0/fb77a2C3y9lEke7xTY2pSLf9/SDWydglq3v5VBBtELp+NhGjxXEebpQybrxMO06Z8nJPy/wDO6KEx5G+jGRCLJJwZGyrBkbmVmzJih6dOnx/9uaWnRwIEDpdiDZMLm5ezfSxEfQa2n+3STy3k94U+aLmIz3JRNc6kno2A4oQLHZUz3AoCbTHahDH6sMr7vRnI8UQuk/nSm87g+XQNNuy72yfMPIiC2GG/bLuvZep7OvgE+g3+rwCNpWEoWODH4DSrwjbUrcd4uwa+UFAAnLZ9rQOMWpHnh675Mh6DEad5+gmov44LkFjy49CDoHGf1I5E0TfI6sAuILevM0oVKXxc/HKb1E9QmlsmnwNZlv05ZEtuLODbDk4R6D2/iZOnsStn6LlrwtV4y/K23nVc2zq9DFPhzfBLqRXjyNtCtqamR1Jm1HTBgQHz4hg0b4lnempoatbW1afPmzaas7oYNGzRmzBjbuisqKlRRUZEyPKydOIWPI6TjrXiOwYHN1XO3+p0CWKdAwu6k3y6QTW6IRXlfwXBKe5IukLhd6U+o0PM+EMTJsVe+f7zd97GMuyL7aFNGP28u87Ednfa+7GPfSajI9cKRXR32s/Y8nafg2SH4sFxGp+xtwt8Ri0DVSA5UE9tgdSLvENi6ltn1d+q9mYbjCnXN/lnwlBXOJMixm97vyX+ue544XDhy7l1gc8XU4XtnfaHTpk4nXleZ1+Oen23jFAx62Z92/d/1fbaZBLZ+g1q/Aa3N+ko7kxiyjM4VM/16BrncQVxA8HiBnIAOuZC3ge6QIUNUU1OjxsZGjRgxQpLU1tamJUuW6LbbbpMk1dXVqVu3bmpsbNTkyZMlSevXr9c777yj22+/3f9MDeWma0W6wazT9HbZheSL4a5XwB3qSCeQsLu4bnHy4yUYNk3ucMJjux59nBBlnOkNWKBXaD3U5em3OQfrxLJdLgFmSjMDCopTBvm5GGU9yHq+KTO1GJTORSyLZUv5vidmZBOnSQ5+7bK+yfPJJPhNLmdXZ/I4eQxa7WTyffIayIYRxIb5/bS98OfQXj8BrNux2s+Fi6CeteBlW3jZtn7u8TUFDg7Z2sT/WwWmtnVajfcX2JqWxiWg9XyvrpdxFsIIrjK+jpSl38m0lz2TC+VOwws90A1rGQp9veS5nAa6W7du1SeffBL/e/Xq1Vq1apX69OmjQYMGqb6+XrNmzdLQoUM1dOhQzZo1Sz179tQ555wjSaqqqtKFF16oq666Sn379lWfPn109dVXa/jw4fGnMPsRysOovBwQfezkvrorW8w/3YDPdKHd7uQk+cK9WyDrIRg21eMUyNoMt81kW7XLitNy5xMfbQskYM2Dkw3J4ffYYV9J+q/1gOR90KluTxePLIb5vV8306DZZhk9f0/j3ymLANgqkE34v68uz/HpbbJTphRB8gIkzTuZVVCcKT9BitvwdM6gA/6ups1tf7PilNF1q19yz+ymM590uG6DNAJiq4A2uZzt/70Ftm7dkDMKat0CWh8Brnvvo+z2YMjrcwGPsnGhPHkexbDeUHhyGui+9tprOv744+N/x+6bPf/88zVv3jxdc8012r59uy655BJt3rxZo0aN0qJFi+Lv0JWku+66S2VlZZo8ebK2b9+uE044QfPmzfP9Dl1J4VytSbc+u2SEj8DMaf6espNpZrXi57R+A2Kbefi5z9YxKE6s02Z0ysg0tl8Qu1DGP9teG+GhnOcfpxz8iHm6cBPj9UKMRR2OgbHFtCmD/JyEy+dySa4Xp1LaYNfl2mK5UjO6SdMlBJuW2V8vwW9ivGLX7TlpXinLlDy/5OlMDQxB0CfjTvU5jHN89ZTf+Thxm43V98LLLTVu9bpldj22Jes8BHYp2y7doDaxjClgthrvY3ovbbOrx+7v5PLxcvbbNq2AKax9ILsxtrMgljHTcwKn/bzAH0bFPbqFKWIYvMCppaVFVVVVGnrVLJVWdM/ejAM4QPo6p0nnCruf+dmNsxnuXJf1bmk7jZ+TIxtpnQNn+0cujW9r4IGqzzaEeRAPdP/PZN/3Ur/XMrH5eS+a0bwtl8tqoyWfg1sFoRb/Ty1nc+bsVJ+SgiTLNlsMy0dpBLCOwWs+XogK+HfJ8p3PmczTrZ5M15Wf7egUCKaMyzCoTajDV7Y2naDWNaObui58d4f1WwbhXCTwcvHCkDpad+jjO65Xc3OzKisr02hIbsRihCN+9GuVlgcfI3S07dDrf7qh4NZLocjbe3RzIeirNa4nxgHMy9c9fV6yu34zu4nj/WRXI251ecwSxwa6LZuHDFla90Pn+sfV7/x9lPceIOcuwsj0gWyB7ft203uZh1VdqX86j/SbVbZbLovvn909uqldmhPKmzK3SfUnZn+tMr/xcua/TUGCVRCcTnbQbznJ33cu3cxrmtlcX2XC5OF461g2+bvgcr+14zyTZ+d2YEt3m3mtxy3DmTQPTwGpn2yvW1Cb1nxsyiS1wXq8rDluB/txfuvCLkGcGxT7ejYUzjIW+3rLMQLdRAHvxLl4Kp/nk+rEWbmdlPgNIh2DUutpggyKEwe5BkKeT44c2pcn/P/4e9/J8vrEwm4xPDyQLaOHsdmMT26T527IDuvM84PQ7GNB26DAVJVF0OvpHt2EguYuzbIpm1wuKbA2tcNnEGxXLknKO4HT4DnwSSMj4n3aEL/HafJ177zk6aJUV1mP5azKy2ew6iTdbeolk+k5iLSuN9Cg1mGeEZv5p45TKothaQdQefy7nCuBfNfTPi5a1xP4M3AADwh0E4TyMCpPM7YY5jcAi1Xl9QTBS30ubfD6MClTvWEHxbum87QeXE54XAOiPBdqcBrQ+nBqo+fzUZ/7vHtm1v7Cie30ySPcLg45lElpj+M8k2fgY34R0z+pfximfyyCy6TpHALg1LIJ7fNYr3V5m4tVTkFu/JgTcE8Er9+JDANXT9/rHB+v/D9Lwn6ZPV/ksZt5mOsi3W3lFLBaTecW0KaUSajLth6L+XkOsD20weJv63txPQ5zqsNOAf5u5zO/9+Ym7xuFHuhyj25hItBNEHag6/sqtxU/gW1yeQ9Bhe+H4CRM6/vHyeZkNK3sbqw+h3Z4zsp6yQZ7mD4wObgymw8P+0irDelmSV2CX0/fi3QzyFYjvATKduWc5meX1bX6bjgFwnZBcEABcLy8jyDYdjpT+20C46B5CKIDCViz8b3OQFq/eZn8xjnONESZBABW5fxkR92CWruA1UtQaxfQOkzvOB+HYbnqDkuQYcHjOvF04SJx3yrwQFeGwtkf2QdDRaCbIIhA1+k3NpDAyWMdgQV1HoJHv8GxW9sc63MKAFxOnjyfMPncTr4zDgHI6MfZ77QZLk8YJxKhnkB7vWDiNL+AguTkUelmk331qLAoaxcIpwTByc3wEADH6zeNdw6CTW1KaoPz8SPLQZDXfd9Duaxncm3vi/U+k7Cee5DOLTph8pvpyqT7suQzS+u5jM9MsVN7Lf72fG+ujULoyZBvAvvt9XnBzXZbs32QAwS6iQK4WhPIgSXNwMlzV1sPJwleH+Lkp8txrF7XrqN+22LXDpe2+Knfqe6cXxHOYP75kLlNR9An0H6CV2+Bq4d5efyOphsoOx4PYgPcgtld83EKhK3uvzU1zykAtqvfKQje1X7LbHW6F8KywPN3zdMJvfeAPfDjUwYXCywn9fRdNpz+9C+I3lUp01pXmnb3ZY9lww5o0y5nMd6K5+7MbtPYyYPfq7wW1AUHD/tMwWd0lQfne/CNQDdBru7RzSgj6DW4TSzr4SQ8ncDRrcuxbb0uJ6jpdKeOtyeoTInVPPP1gJeDduXDwT+T71EmwWs4gavLvJzm5+kilHllWX7P7IJh1yDVpXxye/wEwfFpUttvvz4sgmInXuO4EIKiZIEGx2FMayWIXk0BdEd2nMRjOwILqCzGpTTPLfD1G9BKmWVp0wl8LXgJftPutpzti7y7i0y+Hw77VjEEuig8BLoJsvVF9PUAKSs+gy0/J+KhdWFOJ9OSZp2u7YlN70MhPHXZSla7OAc9fxtp96j0uM39dovMZoY3nXl5eiBVcrCaNKHlBbCk+13DDoLjzbdYhky7KwfRFTbtfT2EYDbLHbTN0lgPKZOksy4z/V21E8R695C19NMV2C5DmzrOy/Qeyli1x26eFmU9Z21t5pGrbssEw7v4vYjjdZ8qNIbR+QmjXoSGQDdRdNcnSBa/fGl92dM4EXPNzibW7XYi7nISnm6Q67frs2t7vCyzz26MrkFzgch10BuUsDLwnr4vHiIIvxdFPM3P6btgN95TZteiPrdA0iYQDjIITqq+a5rk5XBgGRRbCeP7nUZ9voLTsIPqMFn9JgZRT5jLluHFCE+Bnmvg6yE7m/R3RkFvEqdg1lNQ7BYQpdMGO/mwn+ejDNeLn3vRLfcrMrrIAQLdBJGooUg00yNB0t8ZVmdEIv7r8RPgutTtqetwmgFpOl2SM83U+rpXz+t6TJdVW7PxAx3mj10e8JWd89KlOLGc2wUhr/U48NN+vxeYAnkolZdA2EcQLMk6qLVpY8p0NoG8p+DJ50WvtKRTv49pAvk+Br0OAug2bDlpAJn3dGSUUfQc4HnMzCb97RhkZhrQ+glmXQN1l3m5lPU13ss80MXnOvJ74SayK2MZKfDMZcQIZ39iHw0XgW4Cz12XQ/oRj1dhOvn2c0T31gZPwbOXrpIuWSa/2VovD8DKJFPrKzMb0AlwEPeJxYR2MAyg3lwdqK3Wr6e2eP6ueCjnJ8ANOVD2/UTzQDK7DtNZBqzmhfAcCLu1J2mck1zdipDW9yRb0wQpqPmH1R3ZLw/ztQ/aUndG/4GCQ1kvmTSn+fuZ3kfgG3p35TT2BQIKD7yuI8sLF8kH7tjwXf+S0UUOEOgmiEQzvHKbIc9djZP5OGnrPKl0SxM512VEIulnatM9iQ+ze7XPeXmR9rb0IR+6W2atTpt9Iy+6MXsIXsMOlD1dXLKaxk9A7BTQ7irjqTuyz0A4XpdrIx3a5tTOXEhz/unfB5xW5+DsS17AXG+nGA/rz1d20i0o9BNEOqwjT9nZoILZdJbTaVqn8i7TucqX/SqPeUqyWAa71uM9J5LymaH8Pk+CJQLdRGHco+tFlgJcT/PwlBW1+1Vym9bhZCGDANlTptbjeV7GryHJQoBrKeD55TwQSJZBe3xl7wL6nsTmG1Q9TheWpPR6T3jpGmw3f7dAOD5dUhm3eXrO3CZ1j3aqM3V8nu3caQShedld2S+rxc7HgDyDi9/pZjUDv282zWA27Uyy3Xx9lPM0Th4DsjTr3t2lc6HB8b7wQg90UZAIdBNk/fVCGXSf83uvqefunJkElA7nKKEFyLJOAPmpP6VsurJxv5+bYg94PfL8Tul4odiEHuv1EMAGcVFJSu8CkO/7423KewmI7eaVznSW32WLYbbxkKf1nofBlJQ32akwvvNpvz83x7Jzb66PNvgJiD0GvfnQVdkxWPWzftJRAPthLvkOdh32u0LP6IYVIxT6esl3BLoJshboZhrgysfB3WvGyK09XoJch5PuzLK1Tpe0nafvrMPjiW0mXRrzIchNFEZb8mn5rPgNbhOn8VDeV88BDwFsvnzfHB/o5CUgtsjcWrUp7ayw1YmxQ6DrJOMeG1mQ0Yl7ni5bQV4w89DmtB+mZDe923ckjYA1qPt7/XevtrpyljrIsm4P03ie3otC3D+zxe+FBrv9pggCXRQmAt0EWQl0MzjR8v2aG6/zyjAjmvbTlb3OO4Pxnu5J9jov23lE8vaHMrSnHObL8iZuM59t8rXdAuyGHEimN53vm0NA66Wsr27FbvOwCoatJnNaFgtuPV/zNZlrKcPvWEEGl/kgjPXuJbvrJ+gNO7ObPN4tiPWyfDblbMs6lPddxgHfEwfpZNOLOdA1tHsmEQocgW6CQF4v5DgDZRDkRkIJcjO9vzWQ1/04TJtuVsvr/H3VZTttfh+lQm9ethc/g+A2PpnfCyBeeg142BeDuUfe/7QZZ21jw12GBRoM2wzz9RAtL/PIZ/l9aCkano+RDuU8B2s+g14/AXFw99saDuOUKo0yrsPt6vE4rZs8/9nOvXQz6aZ9zrwfhXp+nQURI5z9hn0xXAS6CUJ9KlymXeb8fhM8B3huKRC5drFMtx2hBsmxKvwEuukqgJPnrB1Iw5xPBl3+E4XymikvFbruzy7BcprfF9vldbgv19O8vXRjthlm+Vooj9NG7NpoN3/TjL0dN/JJYN9dTqZMfK1Xp7J+Lrr4yaK6lU87q+ucjfWV9XWZl+N0NmUdy3uY1gkBhQsf68dL1/SUe3RZ/8gBAt1EYXZdzuDkKqwuy55fNeQ43qFAiEGyp/Feyyizk9+C6Q6Z5R+ZTH/UUrZJEO0PIcgN6unKrpU4XjSyD5J938+ahWA1k3nYzseu3nTK5JlATxB355NNv9eLQwpwXYNBPwGxUzY2aXxQmWPL8lbT+CjnWN7jtNb17c47vAdBfSe87NMF33XZ6PyEUS9CQ6CbILSuy5new+n3xCyoLKanbpROv1hu9XvIJmcy3msZuWSJvFaQ73J8LPVysu77acm+GiBf68Dr/uDpQkcQZRy7+fv/Hlo+pM0p+5vmsMADYqfhNvNLmbQQvq/JAvw+7DaZlTCyfume6KdTJl+CWL+ZaKsyDmU7y7useF/ZRu9li1q2jhme9uuQbw0EbBDoJgjvYVRGZidWvgNd9wkCefdsxuNDzCZ7rSPdskFOmy0F8BsT6glKri4YKaBu9o6BbhrjrFa2j6A4G9nbtDK3RZrVJdC1kemyeJg+7SyWXTnL6Qzb8dm4hzeI8Z1lbFaWnwy4yzS+6khXMX1H0uCt+7h1IbvvQKE/jIp7dAsTgW6CUJ+6nNVA1/1b4ymD6fb+Wrc6Qg6UIzK8Zd18ZXUzPAPOxxPoPDmIul2xz3jduzbAf3HPWX4PWUT375vzaKfpHVddIF2XvQXFgQfEDsNtuzU71eV1nvkk6O9vnhwPvMhVAOM7+PIa8AUZWAYYDLuPt88k29ZhU862rMs0nqd3QzfRuLTWo1t+wmE/KPRAF4WpJNcNyCexrsuhfDoymV6Bf2JX15w/zu2KdUXJZrvD/+RyO+fbfhfMp6Sj8+O27rvK5dO6yOK+1xFOvbL5ZO37Y7XeO4zU9tgtv83wEqf15XVddnR+7NZRrj+B7xMh7WN+PiUd3j8ZL6vVx0NZ8zYwzJ/E/Tp5mNXxzmLeKcuX3LaEdqRM71RXUlm3+aQcc5OWx3ZZLLan5fq02e6p6996XSa3w/NvRPI2M9Wf++9Arr9Xvr5fXr4/VvuSzfG/oBkhfny65557NGTIEHXv3l11dXV6+eWXHcsvWbJEdXV16t69u/bbbz/dd999KWUef/xxHXzwwaqoqNDBBx+shQsXmsbPnDlTkUjE9KmpqTGVMQxDM2fOVG1trXr06KFx48bp3Xff9b+AASKjmyDSIUXCDP3TzB5EZMjw0y6PPXpdM2gZZ6mcu2wHkVUOOnOT8b26ac43MHnwO5JpFiZ5lQX+lFwf9XnuNeChXs89Bhwylen0oHCczmsXYrv6I6l/2j21OXWYXbrHerBlttihvFt9VkXy4YnMgWcxs3VMyNGxx/fDhtLJSDlM6zmTmUk211f21jn7Gtr9txbbId334wbxuic/dvsHVqWx+JGo/zojHf7ng1QLFixQfX297rnnHh199NH6wx/+oIkTJ+q9997ToEGDUsqvXr1ap5xyii666CI9+uij+p//+R9dcskl2nvvvXX22WdLkpYvX64pU6boV7/6lb73ve9p4cKFmjx5spYuXapRo0bF6zrkkEO0ePHi+N+lpaWmed1+++268847NW/ePB1wwAG69dZbdeKJJ+rDDz9U7969Q1ojziKGsbt/w6WWlhZVVVVp9IRfqqxb9/BnmMbJlK9unR6LegqeXbtTZhaIBtH12Hsg4m/Fh3bSG1S9efDNzcW9JYFtF5/1BBXweqrLYbzjd85nN19f5TMt6zGo9j0vh/LmadPYccIOfEO53yukL2UOvuuZdVENYB6euym7l/Ndxmf34bSf2mw53mPQ6nVd2JTtLO9hQ4URiBWLkL+Xvo4nLkXbd+7Q8kU3q7m5WZWVlZk1LItiMcJRp/4qlBihfecOvfLnmzyvl1GjRumII47QvffeGx920EEH6cwzz1RDQ0NK+WuvvVZPP/203n///fiwadOm6c0339Ty5cslSVOmTFFLS4uee+65eJmTTz5Ze+21l/70pz9J6szoPvnkk1q1apVluwzDUG1trerr63XttddKklpbW1VdXa3bbrtNF198sfvKCAEZ3QSxLjSpI4I/2/F7sh7x+0ArL1mMaBBZXQ/ZZtesbtiZ5Rh/6zCfsjz5IF8emBBKxtfDd9z3/pBxbwa7wS5ZZpuMrO33zLZ88GWTyzlmZP3My2GarlGGZRsKXaG9eihn7U03i5hBFjfTe1+Dve/WcBnvMr1Fmc5yNivOLrB1CkB9bM/ALujkye9aVgWwzOl8j3ebiw9pamlpMf1dUVGhiooK07C2tjatXLlS1113nWn4hAkTtGzZMst6ly9frgkTJpiGnXTSSXrggQe0c+dOdevWTcuXL9eVV16ZUmb27NmmYR9//LFqa2tVUVGhUaNGadasWdpvv/0kdWaOm5qaTPOqqKjQ2LFjtWzZMgLdfBDpiCri5ehekvmZUtpdZH0E3d6e9OrhaOVWj6cZOY3KLFiOjfacsfF9kaFTsZ0gO8mXoNaLYAJfw7oyh/l5641gX8hzPXZdiZ2mtZzGIdDzExxnEOwG1o3aprxTXVajCu07Hdj3MozvdyjZ6eDbENq7ceUeuFrWlVFmNsPg1S3wtipjF6z4zdh62bY+t38h/W6Z5FnHykDWo8X9uAXfRTzk9+gOHDjQNPjmm2/WzJkzTcM2btyojo4OVVdXm4ZXV1erqanJsvqmpibL8u3t7dq4caMGDBhgWyaxzlGjRumRRx7RAQccoC+//FK33nqrxowZo3fffVd9+/aNl7Wq57PPPnNZCeEh0E0Qu6neVeIXOIMTpfSCXcN7oB1gl17HJ756zZQ61RFQdlny2CXbQ31OxUN/QnAWFPyPjg2rLRNGt1VvAZP7scJ7wJtaIL2A13t5x+yxZRDrHhg7ttlPWZtpkjkfu9KrMzQBfiXzNSjORndk1/k4jPMS7NnWn2lgKzkHr5kGrl6C1jSCX7fhztvC20bNaL8p9IcgeZS1QD/N+UTaC3s7hP16obVr15q6Lidnc03TJP3WGoaRMsytfPJwtzonTpwY///w4cM1evRo7b///nr44Yc1ffr0tNsWNgLdBBk/FS6Dc2lfJ+JRb4Gl90DaPXj21tUy9wGz5DFo9llnavHU/cTXA8OyIC+6CWXyoxDgcTF5e6W1rTxnCdPr4eAeONtnnd0DXvMIPwGyv8DUe9bY8dhnU9a2bpvprAYVWhbXTiAnXAGdtGXcFt+ZO48TOAa03qdJP6i1ymo515PRfbrJx/x0glbPy2+9Am3Xq8u5la99KPCLL4UdgPmSw0Ut+Kcuh6yystL1Ht1+/fqptLQ0JXu7YcOGlExqTE1NjWX5srIy9e3b17GMXZ2S1KtXLw0fPlwff/xxvA6pM4M8YMAAz/WEjUA3QaTD8NaV100aJ9GdmZPggzPPgbSH4Nk92N217hyCZs/BdxBBc+JM/UjzRDidwNJpu+Tdj2+eNSeFj+1mta2C+v4l7nvpPvDN0/fWV8BrHST7CZADy8T6CY4d6u6cxn8vELsp8ikAzocgNuPjT7pZH6/TZbWbsoeA1aLOwDOuPqf3dt+tQwY5xiZAyYcHT2X9dzIfLiCHKYz1ues4bfkMnEJiKOe3fZSXl6uurk6NjY363ve+Fx/e2NioM844w3Ka0aNH65lnnjENW7RokUaOHKlu3brFyzQ2Npru0120aJHGjBlj25bW1la9//77OvbYYyVJQ4YMUU1NjRobGzVixAhJnfcUL1myRLfddpv3hQwYgW6CwN7ztetAmNYDpyRPQV6cx6DacyDtKdjNLGj2Fux6yzLLU12xCdI7kw3zBNgqM5xtBXtfkw/ebiO3SmV4nIFd0JtwUpTO989z0OwnW+pYPrlgaoDsHMT6yBz7Dbotp0lYPxn2BsmjONddJh2PstR1OKN5eizvWq/frKPX4Ncy6+kSdCoLgatb0Gp532TKIG/LZ1POtqypHc6jO+v2v7MV7G9Zvl3UDtyubrJkdAMxffp0TZ06VSNHjtTo0aM1d+5crVmzRtOmTZMkzZgxQ59//rkeeeQRSZ1PWJ4zZ46mT5+uiy66SMuXL9cDDzwQf5qyJF1xxRU67rjjdNttt+mMM87QU089pcWLF2vp0qXxMldffbUmTZqkQYMGacOGDbr11lvV0tKi888/X5IUiURUX1+vWbNmaejQoRo6dKhmzZqlnj176pxzzsniGjIj0E3Q+TAq6yNwOvf4RVL+45XhPSjzEVRH/NTrcFLdlYFJP3D2lLGKHRQ9Jm08Bc+JPN7r7FQqn7JAMTn7sc/mj5jPB8IFug09fodSnzCcfJbqNp+kP70Gzaag1EOgbBHE2s7Dtmz8fz7KJtabmjl2LO8yD0/TeqgzKwL42qT9nc9a4OpvAk/1u5QJJNvoJVi1K5cPQatbIG3VLrtylsttvxGCuC83/f2zSAOqQgoUrX6jC6n9FsK+R9erKVOmaNOmTbrlllu0fv16DRs2TM8++6wGDx4sSVq/fr3WrFkTLz9kyBA9++yzuvLKK/X73/9etbW1uvvuu+Pv0JWkMWPGaP78+brxxht10003af/999eCBQtM79Bdt26dfvSjH2njxo3ae++9ddRRR+mVV16Jz1eSrrnmGm3fvl2XXHKJNm/erFGjRmnRokU5e4euJN6jK3W9I+v4uhkqK/X2jqy0AxyfJ+ih3Wua5sl62nV5yDwHkXH2XV8G9RelYjwaZLBNPX/PPXyvM73HPa0HMtkM9/OqIckmSPZTt21Z6+FO2yyIZwV4risHMsu4ZikL5rt7aXD1ugYxDqP9PDHYcwYziO7BUZfxlvNxDqQ9Bateu2TblPX9UC9TW7ztFNn+PhS0bC6vn/OrXWV3duzQiysbCvY9umNOuiW09+gu+8svCm69FAoyuomihsMvoZnpK+73QVI+pvHdNS/G9cQ7sV77st6y0h6WyUPm2XxfbXCZ55iMn5SchyfFtrL5e5fDk4nAnn7tL+5Lna/VSZtN11xzPaa/UgskfI89Zzod1klsGk/Z5cRsqZdsskXdblnk1GVyz1SntR6T6rD5M7/kWTfhzrp9Vu61C7KnrqwudTi1zUd2N6N7dIPIsnoJutMJWDPK5lqvwIyytl73pQDuiS3aDG9O2a/T1OP4rq7Lhb4dokY4WekCz3TnOwLdBJEOI817Jn105U2axs+Dq7qCTg/z8RFQuz4MJpltEO0ePEds/7Cvy0sA3TVf+6K227YIXhWUkQL+8fH9fU1nW1t8R+3m67dXgnXQljA0+QfQYVrL7sOSbbDsN1BOJ0hODmD8BMnxaTzcm+x6Wa8Av+NpnRT6CVr9BBBhBMNeirkGt07T+uxW6yeY8xIgphOwSu7ZXy/vuvUYrHp+mrLdunTYh9wz7z52qqB+o4r9QVK5YPn7mPhHwu8PAR1ygEA3UXtUMiyOhJ4f+JT4h8cTq8TZeT4Z85aNTS4rySUD6rEtpvcI2wW0aWSiPQTQnfV5yEB7HpFav33leXiynK0gtdB+n2w3VRrb2uXkyDAFn2leTEn4XloGe2lnOiO22Wb7zKh1ZjnTjLIRsVk/Ll2ynQIyrwFsIE/Tz4Y0mukrIPZa1Fdg67VO94KudWXyihq7r2amD1lKJ1i1KOMtME43c+ut3bb7kt/hNvV7mpff+fhVwBd2c87qeGu1nU3lEhJBVufXhcRQOOdC7JKhItBNEInaPIwqg2A0rSxvjIcAO6V21yciey3rNbh0b7PllJYHTKtf+tRy9tk0y8HeeLp3ugCPRlm6gpqLOCLQ+ytTtr/zAiV+HxybYZdljY/fVcDm9982i5o4rZUS++mcsqp+gmW7agybnSFi8x1zvvfYZSP72fHy7TpVWkGtn/q9FfZVp4fjSd7cj5tOEBbCPatpBatW9acbrGaYoXXuEp7mOMnfb1PQwSnBrrs07sFNkdSbqOC7LqMgEegm6ojKV98WD8GR70A0UXJTPE3rPfuZdrbXqS2e2+z1BNzmwOg1oE4pZNfu3egAnOsfG7evWDo9KNLh1EXYZRq3LtOegvCSiNzuc3IOoh2CZ4fA2VfQXOI/w2wbANu0yfmwZrjcjrCLz4f8xWsPKfjN+MKPj+NRkIFlZ30eCwZZXwCvm0mrG7OfzK3ks3tzeplV6wxzwFlaX8FvGtlcT+/L9bGPh/H7nOvfwXyRRk81w+l4a9UbKj6ssDO6ncF6OPUiPAS6iTo6JHV0/e01O5pJl9ZMpk0n0Haap2sXlERZDFS9dpdxm8apPR5l416/rF/1zLcf/DB/Cy26VHnRtd09TFPi4YfLrktxwninYNoxQPN6EmIabjOvDutpIk4BqNPtDA4XMVzv63da5o6u9vv5jubqBCO0hzoF/YCfILob+6grkCxvut2b/QZudhdu8ilQ9ROkptE92TEADTjYTau8H8V2sTvNi3+Wkt+P7qVnYNJwoyQiRTusywIhItBNEIlGFbH99fJ+0HC82uW5MR7qsDtZSTcY8zOdxTI6Z5+SxjqdaNk8sc+NkWYQY8nmhDzrJ8ZZugC6O3Qp6tw/0lhOL4FrjEM2NaWcA7dgLeKU9Y46ZVvtx/kNniNyubhlNSp2nuNyS0ImrzXz9YAyHw8DjAvyO+knq5XlgLJznl4D54C7SQcRJGVyj2g64zK95zWMQNWqK7bfDG2668nLPpHWA9ey+FsVzYMMZEk6Bymlf5zy9EBFizJW572mB1HJ/vy6UBhGOPvfbnD+lUsEuomiHroue3mKcdABaMB1pRWI+wlUrcr7rd8rh9ev+ObjAURZk60DYLFdzU5m8TAlzxwCR0se9mXXQFZyDsJsMq1e22E1/65uwDbzs6jT9Fe6QbSUcpJkGT6neQHMtkLJ1IHHtwy/Mr4uLgUZSHrumhxsdjiUhw8F1C06+KA3gGDSpqxloBpAvY77WDpBsOQ9UEzjd87YXYKDEINtpwufSQWthycG4U49HGPDfD3qPf9EjJC6Lu8mu3KuEOgmau+QSnx0XfZaxo8Qu5vEBwcdpGYwXdrZb5eH+GRUZ65l8wd8dzlZ8BIYOgn4wo2ne0sdsp9+55ccJJr+Sg5sk4M/xyc+e5uvbanYvN0CTrf7ld0E8d0O4rviK7j1VsxTAJmj4DYm1CfsBpl1zuSVOOl08Q3qKcdB1W8XVDksm6eA0+uF1HSfyru7/I6lw+kCpO00DldZE3+zdu0vKQGzZca3RPmTQcDuhEA3UUdUMizOuNI5ScpGd5OgArMAsqnpzi+tC3xhB6TZDnhz8SO9u54YZLptfU7veiHHTzDrtZxTtlZK/d76CWw9jPf0RGqvAa6X9uSzXAW2fuYdcPdk3/UGMZ3PaTw/3CiTwNdtfJAZ1CADVMd2ub1rLcCg18v8vCqmHkuBJkPszlMT1nvy/Cwyt0ZyXVa3uhhGwWd0eb1QYSLQTWC0t8soKbH/8vs5wATQ3cRztxL/FWc2fSyID/MekGzWU+x216DWi7AfBuc3iEynrJeu0olttQsuA+rBEvFalxTIxbKcSfd7FVSQFVY5+QgE06g70GkznT6MV9xk2p033eypbVbX6UXUGdxj6xaEely3aXVBzod7Z3PFz+0WrgkX83q0POeMzc/yHtzE4DZhO1rcq2JIUsluvN2QMwS6iaLRXQfvXV9GuytZ6fKbDcpwdl3zTTO7bCegg1XeBvKFJA+C2GzfKxXafmOeSfrTptObI8x72ksiqQF3pnWGVXaXQB7ol0Vpvf4khADVXwY5i8FsENMnCzLYSbNtvo59nrpOZ5gxzSQb6zCtt+7JHraH3/UccEBbSPf1BvI715F04Hf5bYqvHceAN7GOaFc7O9R1zmxzzmkElaHPkYhhhPLgzt3hYaC5RKCbqKPDnIJxupKV7yLmg1HgAlgnll/tfApSg7xAUCgH+AI44PpuYRj7lOO+4SGqTPP7k9bJTzZuvQj4/uc8Ogp4k42nx/o56c/Fw32y0T00m8fRbK8Pr8vmoV7XbRlUUOpxn/S9bwW9LxXK72+CrqAzwPOQjqjn3x7b35qkbdnZbXlXWSPW1l0BsOl+XkPco4tcKJpA95577tFvf/tbrV+/Xocccohmz56tY4891lcdRnu7jEhJ6olXIbz6K+XENLsHlKxk2awU4kWIMBXTvUi5ENb+FNDJStZeXeY4fUAnXsXw3c30+5bOCXhaXT2DeJBWjk5S8/yYFkiWMJ3Mpa9scggBaViBvOWkOdoHgtrnMzpmZnYCGnF7JoP1RDLsLilbvbIqntXtiJ+LGpFIPPCNRCKd+1ahv0fXw4tZ0q4XoSmKQHfBggWqr6/XPffco6OPPlp/+MMfNHHiRL333nsaNGiQ53qMjqgMT3388k/OAs1d0voZSveBXci+QrsnKp/2rWx8N0Ne3qwfX/IhCA7x5DpnwZGdfO3JUWjHHZ8C7Uqbyf6a6yA0WxdRcrWfWz3k1E1Ax1zXWVsG4fYTRezuv43VsytrHIlE4oFv1wMK8/Q4g6JWFIHunXfeqQsvvFD/+q//KkmaPXu2/vKXv+jee+9VQ0OD94o6OlK+9Dm7kuiTl1amXNkDkH1B3zOfBabjC8cRf3L9G1KA3TaLUV6eS+Ri38jXiyr5JlvryeebRmwD58SXwSbfr7sr8DXSCfjzCPfoFqaCD3Tb2tq0cuVKXXfddabhEyZM0LJlyyynaW1tVWtra/zv5uZmSdLO9u0y1B5eY3OtsI8xAAAACFMQcZfFGwfadw0spIeCofAVfKC7ceNGdXR0qLq62jS8urpaTU1NltM0NDTol7/8ZcrwpXo2lDYCAAAAu6WE2HbLli2qqqrKXVvSxXt0C1LBB7oxyfeQGYZhe1/ZjBkzNH369PjfX3/9tQYPHqw1a9YU5pcPkqSWlhYNHDhQa9euVWVlZa6bgzSxHYsH27I4sB2LA9uxOBTqdjQMQ1u2bFFtbW2um4LdSMEHuv369VNpaWlK9nbDhg0pWd6YiooKVVRUpAyvqqoqqIMGrFVWVrIdiwDbsXiwLYsD27E4sB2LQyFux4JOJhlGOPdO05U7VIX3VJQk5eXlqqurU2Njo2l4Y2OjxowZk6NWAQAAACgGESO8D8JT8BldSZo+fbqmTp2qkSNHavTo0Zo7d67WrFmjadOm5bppAAAAAIAsK4pAd8qUKdq0aZNuueUWrV+/XsOGDdOzzz6rwYMHe5q+oqJCN998s2V3ZhQOtmNxYDsWD7ZlcWA7Fge2Y3FgO+YIXZcLUsTgOd8AAAAAYNLS0qKqqiqNHX2jysq6B15/e/sOLVl+q5qbmwvunutCUBQZXQAAAAAIQyTa+QmjXoSn4B9GBQAAAABAIjK6AAAAAGCHe3QLEhldAAAAAEBRIaMLAAAAAHaMXZ8w6kVodvuM7j333KMhQ4aoe/fuqqur08svv5zrJiFBQ0ODjjzySPXu3Vv9+/fXmWeeqQ8//NBUxjAMzZw5U7W1terRo4fGjRund99911SmtbVVl19+ufr166devXrp9NNP17p167K5KEjQ0NCgSCSi+vr6+DC2Y2H4/PPP9eMf/1h9+/ZVz549dfjhh2vlypXx8WzHwtDe3q4bb7xRQ4YMUY8ePbTffvvplltuUTTa9WQUtmX+eemllzRp0iTV1tYqEonoySefNI0Paptt3rxZU6dOVVVVlaqqqjR16lR9/fXXIS/d7sNpO+7cuVPXXnuthg8frl69eqm2tlbnnXeevvjiC1MdbEfA3W4d6C5YsED19fW64YYb9MYbb+jYY4/VxIkTtWbNmlw3DbssWbJEl156qV555RU1Njaqvb1dEyZM0LZt2+Jlbr/9dt15552aM2eOVqxYoZqaGp144onasmVLvEx9fb0WLlyo+fPna+nSpdq6datOO+00dXR05GKxdmsrVqzQ3Llzdeihh5qGsx3z3+bNm3X00UerW7dueu655/Tee+/pjjvu0J577hkvw3YsDLfddpvuu+8+zZkzR++//75uv/12/fa3v9Xvfve7eBm2Zf7Ztm2bDjvsMM2ZM8dyfFDb7JxzztGqVav0/PPP6/nnn9eqVas0derU0Jdvd+G0Hb/55hu9/vrruummm/T666/riSee0EcffaTTTz/dVI7tmF0RwwjtgxAZu7HvfOc7xrRp00zDDjzwQOO6667LUYvgZsOGDYYkY8mSJYZhGEY0GjVqamqM3/zmN/EyO3bsMKqqqoz77rvPMAzD+Prrr41u3boZ8+fPj5f5/PPPjZKSEuP555/P7gLs5rZs2WIMHTrUaGxsNMaOHWtcccUVhmGwHQvFtddeaxxzzDG249mOhePUU081fvrTn5qGnXXWWcaPf/xjwzDYloVAkrFw4cL430Fts/fee8+QZLzyyivxMsuXLzckGR988EHIS7X7Sd6OVl599VVDkvHZZ58ZhsF2zKbm5mZDknF83QzjxFG/DPxzfN0MQ5LR3Nyc60UtSrttRretrU0rV67UhAkTTMMnTJigZcuW5ahVcNPc3CxJ6tOnjyRp9erVampqMm3HiooKjR07Nr4dV65cqZ07d5rK1NbWatiwYWzrLLv00kt16qmnavz48abhbMfC8PTTT2vkyJH6wQ9+oP79+2vEiBG6//774+PZjoXjmGOO0V//+ld99NFHkqQ333xTS5cu1SmnnCKJbVmIgtpmy5cvV1VVlUaNGhUvc9RRR6mqqortmiPNzc2KRCLx3jNsR8Cb3fZhVBs3blRHR4eqq6tNw6urq9XU1JSjVsGJYRiaPn26jjnmGA0bNkyS4tvKajt+9tln8TLl5eXaa6+9UsqwrbNn/vz5ev3117VixYqUcWzHwvCPf/xD9957r6ZPn67rr79er776qn72s5+poqJC5513HtuxgFx77bVqbm7WgQceqNLSUnV0dOjXv/61fvSjH0niO1mIgtpmTU1N6t+/f0r9/fv3Z7vmwI4dO3TdddfpnHPOUWVlpSS2Y04YkqKupdKrF6HZbQPdmEgkYvrbMIyUYcgPl112md566y0tXbo0ZVw625FtnT1r167VFVdcoUWLFql79+625diO+S0ajWrkyJGaNWuWJGnEiBF69913de+99+q8886Ll2M75r8FCxbo0Ucf1WOPPaZDDjlEq1atUn19vWpra3X++efHy7EtC08Q28yqPNs1+3bu3Kkf/vCHikajuueee1zLsx0Bs92263K/fv1UWlqaclVrw4YNKVdDkXuXX365nn76af3tb3/TPvvsEx9eU1MjSY7bsaamRm1tbdq8ebNtGYRr5cqV2rBhg+rq6lRWVqaysjItWbJEd999t8rKyuLbge2Y3wYMGKCDDz7YNOyggw6KP8CP72Ph+PnPf67rrrtOP/zhDzV8+HBNnTpVV155pRoaGiSxLQtRUNuspqZGX375ZUr9X331Fds1i3bu3KnJkydr9erVamxsjGdzJbZjLvAwqsK02wa65eXlqqurU2Njo2l4Y2OjxowZk6NWIZlhGLrsssv0xBNP6IUXXtCQIUNM44cMGaKamhrTdmxra9OSJUvi27Gurk7dunUzlVm/fr3eeecdtnWWnHDCCXr77be1atWq+GfkyJE699xztWrVKu23335sxwJw9NFHp7ze66OPPtLgwYMl8X0sJN98841KSsynAKWlpfHXC7EtC09Q22z06NFqbm7Wq6++Gi/z97//Xc3NzWzXLIkFuR9//LEWL16svn37msazHQFvduuuy9OnT9fUqVM1cuRIjR49WnPnztWaNWs0bdq0XDcNu1x66aV67LHH9NRTT6l3797xK9VVVVXq0aNH/F2ss2bN0tChQzV06FDNmjVLPXv21DnnnBMve+GFF+qqq65S37591adPH1199dUaPnx4ykOREI7evXvH76uO6dWrl/r27RsfznbMf1deeaXGjBmjWbNmafLkyXr11Vc1d+5czZ07V5L4PhaQSZMm6de//rUGDRqkQw45RG+88YbuvPNO/fSnP5XEtsxXW7du1SeffBL/e/Xq1Vq1apX69OmjQYMGBbLNDjroIJ188sm66KKL9Ic//EGS9H/+z//Raaedpm9/+9vZX+gi5LQda2tr9f3vf1+vv/66/vu//1sdHR3xc58+ffqovLyc7ZgLhqQwsq8kdMOV/Qc955ff//73xuDBg43y8nLjiCOOiL+2BvlBuw4tyZ+HHnooXiYajRo333yzUVNTY1RUVBjHHXec8fbbb5vq2b59u3HZZZcZffr0MXr06GGcdtppxpo1a7K8NEiU+Hohw2A7FopnnnnGGDZsmFFRUWEceOCBxty5c03j2Y6FoaWlxbjiiiuMQYMGGd27dzf2228/44YbbjBaW1vjZdiW+edvf/ub5W/i+eefbxhGcNts06ZNxrnnnmv07t3b6N27t3HuuecamzdvztJSFj+n7bh69Wrbc5+//e1v8TrYjtkRe73Qdw+/zphQd3Pgn+8efh2vFwpRxDDoHA4AAAAAiVpaWlRVVaXvHnatykorAq+/vaNVL7x5m5qbm033YSMYu+09ugAAAACA4rRb36MLAAAAAI6iksJ4K1MY7+ZFHBldAAAAAEBRIaMLAAAAADbCeuct79ENF4EuAAAAANgxjJBeL0SgGya6LgMAAAAAigqBLgAAAADYiWV0w/j4dM8992jIkCHq3r276urq9PLLLzuWX7Jkierq6tS9e3ftt99+uu+++1LKPP744zr44INVUVGhgw8+WAsXLjSNb2ho0JFHHqnevXurf//+OvPMM/Xhhx+aylxwwQWKRCKmz1FHHeV7+YJEoAsAAAAAeW7BggWqr6/XDTfcoDfeeEPHHnusJk6cqDVr1liWX716tU455RQde+yxeuONN3T99dfrZz/7mR5//PF4meXLl2vKlCmaOnWq3nzzTU2dOlWTJ0/W3//+93iZJUuW6NJLL9Urr7yixsZGtbe3a8KECdq2bZtpfieffLLWr18f/zz77LPhrAiPIoZB53AAQH7r6OjQscceqwEDBph+oJubmzVs2DCdf/75uvXWW3PYQgBAsWlpaVFVVZVOOOgqlZVWBF5/e0er/vr+HWpublZlZaVr+VGjRumII47QvffeGx920EEH6cwzz1RDQ0NK+WuvvVZPP/203n///fiwadOm6c0339Ty5cslSVOmTFFLS4uee+65eJmTTz5Ze+21l/70pz9ZtuOrr75S//79tWTJEh133HGSOjO6X3/9tZ588klPy54NZHQBAHmvtLRUDz/8sJ5//nn98Y9/jA+//PLL1adPH/3iF7/IYesAAEhfS0uL6dPa2ppSpq2tTStXrtSECRNMwydMmKBly5ZZ1rt8+fKU8ieddJJee+017dy507GMXZ1S50VmSerTp49p+Isvvqj+/fvrgAMO0EUXXaQNGzbY1pENBLoAgIIwdOhQNTQ06PLLL9cXX3yhp556SvPnz9fDDz+s8vLyXDcPAFCsoiF+JA0cOFBVVVXxj1V2duPGjero6FB1dbVpeHV1tZqamiyb3dTUZFm+vb1dGzdudCxjV6dhGJo+fbqOOeYYDRs2LD584sSJ+uMf/6gXXnhBd9xxh1asWKHvfve7lkF7tvB6IQBAwbj88su1cOFCnXfeeXr77bf1i1/8QocffniumwUAQNrWrl1r6rpcUWHfTToSiZj+NgwjZZhb+eThfuq87LLL9NZbb2np0qWm4VOmTIn/f9iwYRo5cqQGDx6sP//5zzrrrLNs2xcmAl0AQMGIRCK69957ddBBB2n48OG67rrrct0kAECRixiGIiE81ihWZ2Vlpes9uv369VNpaWlKpnXDhg0pGdmYmpoay/JlZWXq27evYxmrOi+//HI9/fTTeumll7TPPvs4tnfAgAEaPHiwPv74Y8dyYaLrMgCgoDz44IPq2bOnVq9erXXr1uW6OQAAhK68vFx1dXVqbGw0DW9sbNSYMWMspxk9enRK+UWLFmnkyJHq1q2bY5nEOg3D0GWXXaYnnnhCL7zwgoYMGeLa3k2bNmnt2rUaMGCAp+ULA4EuAKBgLF++XHfddZeeeuopjR49WhdeeKF4eQAAIFR58h7d6dOn6z/+4z/04IMP6v3339eVV16pNWvWaNq0aZKkGTNm6LzzzouXnzZtmj777DNNnz5d77//vh588EE98MADuvrqq+NlrrjiCi1atEi33XabPvjgA912221avHix6uvr42UuvfRSPfroo3rsscfUu3dvNTU1qampSdu3b5ckbd26VVdffbWWL1+uTz/9VC+++KImTZqkfv366Xvf+14GKz4zdF0GABSE7du36/zzz9fFF1+s8ePH64ADDtCwYcP0hz/8If4jDwBA4KKGFAnhomrUX51TpkzRpk2bdMstt2j9+vUaNmyYnn32WQ0ePFiStH79etM7dYcMGaJnn31WV155pX7/+9+rtrZWd999t84+++x4mTFjxmj+/Pm68cYbddNNN2n//ffXggULNGrUqHiZ2OuMxo0bZ2rPQw89pAsuuEClpaV6++239cgjj+jrr7/WgAEDdPzxx2vBggXq3bu337USGN6jCwAoCFdccYX+/Oc/680331SvXr0kSffff7+mT5+ut99+W/vuu29uGwgAKCqx9+iO378+tPfoLv7f2Z7fowt/6LoMAMh7S5Ys0e9//3vNmzcvHuRK0kUXXaQxY8bQhRkAEJ486boMf+i6DADIe2PHjlV7e7vluL/85S9Zbg0AAMh3BLoAAAAAYCus7CsZ3TDRdRkAAAAAUFTI6AIAAACAnbDup+Ue3VCR0QUAAAAAFBUyugAAAABgJ2oolPtpfb5HF/6Q0QUAAAAAFBUyugAAAABgx4h2fsKoF6EhowsAAAAAKCpkdAEAAADADk9dLkgEugAAAABgh4dRFSS6LgMAAAAAigoZXQAAAACwQ9flgkRGFwAAAABQVMjoAgAAAIAdQyFldIOvEl3I6AIAAAAAigoZXQAAAACwwz26BYmMLgAAAACgqJDRBQAAAAA70aikaEj1IixkdAEAAAAARYWMLgAAAADY4R7dgkRGFwAAAABQVMjoAgAAAIAdMroFiUAXAAAAAOxEDUkhBKVRAt0w0XUZAAAAAFBUyOgCAAAAgA3DiMowgn8VUBh1ogsZXQAAAABAUSGjCwAAAAB2DCOc+2l5GFWoyOgCAAAAAIoKGV0AAAAAsGOE9NRlMrqhIqMLAAAAACgqZHQBAAAAwE40KkVCeEIyT10OFRldAAAAAEBRIaMLAAAAAHa4R7cgEegCAAAAgA0jGpURQtdlg67LoaLrMgAAAACgqJDRBQAAAAA7dF0uSGR0AQAAAABFhYwuAAAAANiJGlKEjG6hIaMLAAAAACgqZHQBAAAAwI5hSArhCclkdENFRhcAAAAAUFTI6AIAAACADSNqyAjhHl2DjG6oyOgCAAAAAIoKGV0AAAAAsGNEFc49uiHUiTgyugAAAACAokKgCwAAAAA2jKgR2seve+65R0OGDFH37t1VV1enl19+2bH8kiVLVFdXp+7du2u//fbTfffdl1Lm8ccf18EHH6yKigodfPDBWrhwoe/5GoahmTNnqra2Vj169NC4ceP07rvv+l6+IBHoAgAAAIAdIxrex4cFCxaovr5eN9xwg9544w0de+yxmjhxotasWWNZfvXq1TrllFN07LHH6o033tD111+vn/3sZ3r88cfjZZYvX64pU6Zo6tSpevPNNzV16lRNnjxZf//7333N9/bbb9edd96pOXPmaMWKFaqpqdGJJ56oLVu2+FzZwYkYPO4LAAAAAExaWlpUVVWlY3SKytQt8PrbtVNL9azWrl2rysrK+PCKigpVVFSklB81apSOOOII3XvvvfFhBx10kM4880w1NDSklL/22mv19NNP6/33348PmzZtmt58800tX75ckjRlyhS1tLToueeei5c5+eSTtddee+lPf/qTp/kahqHa2lrV19fr2muvlSS1traqurpat912my6++OJ0V1FGeBgVAAAAACQpLy9XTU2NljY9G9o89thjDw0cONA07Oabb9bMmTNNw9ra2rRy5Updd911puETJkzQsmXLLOtevny5JkyYYBp20kkn6YEHHtDOnTvVrVs3LV++XFdeeWVKmdmzZ3ue7+rVq9XU1GSaV0VFhcaOHatly5YR6AIAAABAvujevbtWr16ttra20OZhGIYikYhpmFU2d+PGjero6FB1dbVpeHV1tZqamizrbmpqsizf3t6ujRs3asCAAbZlYnV6mW/sX6syn332mWXbsoFAFwAAAAAsdO/eXd27d891M+KSg2KrQNmtfPJwL3UGVSabeBgVAAAAAOSxfv36qbS0NCV7u2HDhpRMakxNTY1l+bKyMvXt29exTKxOL/OtqamRJF9tywYCXQAAAADIY+Xl5aqrq1NjY6NpeGNjo8aMGWM5zejRo1PKL1q0SCNHjlS3bt0cy8Tq9DLfIUOGqKamxlSmra1NS5YssW1bNtB1GQAAAADy3PTp0zV16lSNHDlSo0eP1ty5c7VmzRpNmzZNkjRjxgx9/vnneuSRRyR1PmF5zpw5mj59ui666CItX75cDzzwQPxpypJ0xRVX6LjjjtNtt92mM844Q0899ZQWL16spUuXep5vJBJRfX29Zs2apaFDh2ro0KGaNWuWevbsqXPOOSeLa8iMQBcAAAAA8tyUKVO0adMm3XLLLVq/fr2GDRumZ599VoMHD5YkrV+/3vRu2yFDhujZZ5/VlVdeqd///veqra3V3XffrbPPPjteZsyYMZo/f75uvPFG3XTTTdp///21YMECjRo1yvN8Jemaa67R9u3bdckll2jz5s0aNWqUFi1apN69e2dhzVjjPboAAAAAgKLCPboAAAAAgKJCoAsAAAAAKCoEugAAAACAokKgCwAAAAAoKgS6AAAAAICiQqALAAAAACgqBLoAAAAAgKJCoAsAAAAAKCoEugAAAACAokKgCwAAAAAoKgS6AAAAAICiQqALAAAAACgqBLoAAAAAgKJCoAsAAAAAKCoEugAAAACAolKW6wYAAAAAQD7asWOH2traQqu/vLxc3bt3D63+3RmBLgAAAAAk2bFjh4YM3kNNGzpCm0dNTY1Wr15NsBsCAl0AAAAASNLW1qamDR36bOW+quwd/B2fLVuiGlz3qdra2gh0Q0CgCwAAAAA29ugd0R69I4HXG1XwdaILgS4AAAAA2OgwouowwqkX4eGpywAAAACAokJGFwAAAABsRGUoquBTumHUiS5kdAEAAAAARYWMLgAAAADYiCqqMO6mDadWxJDRBQAAAAAUFTK6AAAAAGCjwzDUYQR/P20YdaILGV0AAAAAQFEhowsAAAAANnjqcmEiowsAAAAAKCpkdAEAAADARlSGOsjoFhwyugAAAACAokJGFwAAAABscI9uYSLQBQAAAAAbvF6oMNF1GQAAAABQVMjoAgAAAICN6K5PGPUiPGR0AQAAAABFhYwuAAAAANjoCOn1QmHUiS5kdAEAAAAARYWMLgAAAADY6DA6P2HUi/CQ0QUAAAAAFBUyugAAAABgg6cuFyYyugAAAACAokKgCwAAAAA2ooqoI4RPVBFf7XjppZc0adIk1dbWKhKJ6Mknn0wp8/777+v0009XVVWVevfuraOOOkpr1qwJaE0UFgJdAAAAALARNcL7+LFt2zYddthhmjNnjuX4//3f/9UxxxyjAw88UC+++KLefPNN3XTTTerevXsAa6HwcI8uAAAAAORIS0uL6e+KigpVVFSklJs4caImTpxoW88NN9ygU045Rbfffnt82H777RdcQwsMGV0AAAAAsBFGt+XYR5IGDhyoqqqq+KehocF3G6PRqP785z/rgAMO0EknnaT+/ftr1KhRlt2bdxcEugAAAACQI2vXrlVzc3P8M2PGDN91bNiwQVu3btVvfvMbnXzyyVq0aJG+973v6ayzztKSJUtCaHX+o+syAAAAANhIzL4GXa8kVVZWqrKyMqO6otHOlxWdccYZuvLKKyVJhx9+uJYtW6b77rtPY8eOzayxBYiMLgAAAAAUsH79+qmsrEwHH3ywafhBBx202z51mYwuAAAAANiIGhFFjeAzukHWWV5eriOPPFIffvihafhHH32kwYMHBzafQkKgCwAAAAB5buvWrfrkk0/if69evVqrVq1Snz59NGjQIP385z/XlClTdNxxx+n444/X888/r2eeeUYvvvhi7hqdQxHDMHy+wQkAAAAAiltLS4uqqqq05J1vaY/ewd/xuXVLVGOHfa7m5mZP9+i++OKLOv7441OGn3/++Zo3b54k6cEHH1RDQ4PWrVunb3/72/rlL3+pM844I+imFwQCXQAAAABIkm+BLvyh6zIAAAAA2OhQiTpCeIZvR+A1IhFPXQYAAAAAFBUyugAAAABgwwjpqctGCHWiC4EuAAAAANjoUEQdCj4oDaNOdKHrMgAAAACgqJDRBQAAAAAbHUaJOowQHkbFu29CRUYXAAAAAFBUyOgCAAAAgI2oIoqGkB+MipRumMjoAgAAAACKChldAAAAALDBU5cLExldAAAAAEBRIaMLAAAAADbCe+oy9+iGiYwuAAAAAKCokNEFAAAAABudT10O/n7aMOpEFzK6AAAAAICiQkYXAAAAAGxEVaIO3qNbcAh0AQAAAMAGD6MqTHRdBgAAAAAUFTK6AAAAAGAjqhJF6bpccMjoAgAAAACKChldAAAAALDRYUTUYQT/KqAw6kQXMroAAAAAgKJCRhcAAAAAbHSE9HqhDu7RDRUZXQAAAABAUSGjCwAAAAA2okaJoiG8RzfKe3RDRUYXAAAAAFBUyOgCAAAAgA3u0S1MBLoAAAAAYCOqcF4FFA28RiSi6zIAAAAAoKiQ0QUAAAAAG1GVKBpCfjCMOtGFtQsAAAAAKCpkdAEAAADARodRoo4QXi8URp3owtoFAAAAABQVMroAAAAAYCOqiKIK46nLwdeJLmR0AQC25s2bp0gkYvm5+uqr4+X23XdfXXDBBVlv36effmrbvpEjR2bcNq/Tvvjii4pEInrxxRfTmg8AAAgWGV0AgKuHHnpIBx54oGlYbW1tjlqT6vLLL9c555xjGrbHHntIkhYuXKjKyspcNAsAUAS4R7cwEegCAFwNGzYsniHNR4MGDdJRRx1lOW7EiBFZbg0AAMg1LiMAAAK3Y8cOXXXVVTr88MNVVVWlPn36aPTo0XrqqadSyn799de68MIL1adPH+2xxx469dRT9Y9//EORSEQzZ87MuC1W3Y9bWlp09dVXa8iQISovL9e3vvUt1dfXa9u2ba71ffDBBzr55JPVs2dP9evXT9OmTdOWLVsybicAID91qCS0D8JDRhcA4Kqjo0Pt7e2mYWVl9j8hra2t+uc//6mrr75a3/rWt9TW1qbFixfrrLPO0kMPPaTzzjtPkhSNRjVp0iS99tprmjlzpo444ggtX75cJ598sq/2RaPRlPaVlpYqEkl90Mc333yjsWPHat26dbr++ut16KGH6t1339UvfvELvf3221q8eLHldJL05ZdfauzYserWrZvuueceVVdX649//KMuu+wyX+0FAADhItAFALiy6ha8c+dO22C3qqpKDz30UPzvjo4OnXDCCdq8ebNmz54dD3Sff/55LV26VPfee6+mTZsmSTrxxBNVXl6uGTNmeG7ftddeq2uvvdY0rLGxUePHj08pe/fdd+utt97S3//+93h37BNOOEHf+ta39P3vf1/PP/+8Jk6caDmfu+66S1999ZXeeOMNHXbYYZKkiRMnasKECVqzZo3n9gIACkfUiChqhPDU5RDqRBcCXQCAq0ceeUQHHXSQaZhTRleS/uu//kuzZ8/Wm2++aeoS3L179/j/lyxZIkmaPHmyadof/ehHvgLdK664Qj/+8Y9Nw7797W9blv3v//5vDRs2TIcffrgpC3zSSSfFn5xsF+j+7W9/0yGHHBIPcmPOOeccNTY2em4vAKBwREPqZhyl63KoCHQBAK4OOuggXw+jeuKJJzR58mT94Ac/0M9//nPV1NSorKxM9957rx588MF4uU2bNqmsrEx9+vQxTV9dXe2rffvss4/n9n355Zf65JNP1K1bN8vxGzdutJ1206ZNGjJkSMrwmpoabw0FAABZQaALAAjco48+qiFDhmjBggWm+11bW1tN5fr27av29nb985//NAW7TU1NobWtX79+6tGjhyngTh5vp2/fvpZtC7O9AIDciholiobwKqAw6kQX1i4AIHCRSETl5eWmILepqSnlqctjx46VJC1YsMA0fP78+aG17bTTTtP//u//qm/fvho5cmTKZ99997Wd9vjjj9e7776rN9980zT8scceC629AADAPzK6AIDAnXbaaXriiSd0ySWX6Pvf/77Wrl2rX/3qVxowYIA+/vjjeLmTTz5ZRx99tK666iq1tLSorq5Oy5cv1yOPPCJJKikJ/npsfX29Hn/8cR133HG68sordeihhyoajWrNmjVatGiRrrrqKo0aNcp22gcffFCnnnqqbr311vhTlz/44IPA2wkAyA8diqhDwT84Kow60YVAFwAQuJ/85CfasGGD7rvvPj344IPab7/9dN1112ndunX65S9/GS9XUlKiZ555RldddZV+85vfqK2tTUcffbQeffRRHXXUUdpzzz0Db1uvXr308ssv6ze/+Y3mzp2r1atXq0ePHho0aJDGjx/vmNGtqanRkiVLdMUVV+j//t//q549e+p73/ue5syZozPOOCPwtgIAgPREDMMwct0IAAASPfbYYzr33HP1P//zPxozZkyumwMA2A21tLSoqqpKv/z7eHXfI/j84I6t7bp51GI1NzersrIy8Pp3d2R0AQA59ac//Umff/65hg8frpKSEr3yyiv67W9/q+OOO44gFwAApIWHUQEAcqp3796aP3++pkyZolNOOUX333+/LrjgAj3zzDO5bhoAAOpQ1326wX78eemllzRp0iTV1tYqEonoySeftC178cUXKxKJaPbs2RkseWEjowsAyKnTTjtNp512Wq6bAQBAXtu2bZsOO+ww/eQnP9HZZ59tW+7JJ5/U3//+d9XW1maxdfmHQBcAAAAAbIT9Ht2WlhbT8IqKClVUVKSUnzhxoiZOnOhY5+eff67LLrtMf/nLX3TqqacG19gCRNdlAAAAALDRYZSE9pGkgQMHqqqqKv5paGhIq53RaFRTp07Vz3/+cx1yyCFBroKCREZXnTvFF198od69eysS4X1WAAAAQFAMw9CWLVtUW1sbyvvRC93atWtNT122yuZ6cdttt6msrEw/+9nPgmpaQSPQlfTFF19o4MCBuW4GAAAAULTWrl2rffbZJ9fN8M1QRFEFnwwzdtVZWVmZ8euFVq5cqX//93/X66+/TuJuFwJddT7xU5KO0SkqU7cctwYAAAAoHu3aqaV6Nn7OjeC9/PLL2rBhgwYNGhQf1tHRoauuukqzZ8/Wp59+mrvG5QiBrhS/6lGmbiqLEOgCAAAAgTE6/ynUTGPi/bRB1xuUqVOnavz48aZhJ510kqZOnaqf/OQngc2nkOS0k/zMmTMViURMn5qamvh4wzA0c+ZM1dbWqkePHho3bpzeffddUx2tra26/PLL1a9fP/Xq1Uunn3661q1bl+1FAQAAAIDQbN26VatWrdKqVaskSatXr9aqVau0Zs0a9e3bV8OGDTN9unXrppqaGn3729/ObcNzJOd3gx9yyCFav359/PP222/Hx91+++268847NWfOHK1YsUI1NTU68cQTtWXLlniZ+vp6LVy4UPPnz9fSpUu1detWnXbaaero8PsKZgAAAAAwixqR0D5+vPbaaxoxYoRGjBghSZo+fbpGjBihX/ziF2EsdsHLedflsrIyUxY3xjAMzZ49WzfccIPOOussSdLDDz+s6upqPfbYY7r44ovV3NysBx54QP/5n/8ZT9U/+uijGjhwoBYvXqyTTjopq8sCAAAAAGEYN26cDMPwXH53vC83Uc4zuh9//LFqa2s1ZMgQ/fCHP9Q//vEPSZ2p+KamJk2YMCFetqKiQmPHjtWyZcskdT5dbOfOnaYytbW1GjZsWLyMldbWVrW0tNMcupwAAD0WSURBVJg+AAAAAJCsQyWhfRCenK7dUaNG6ZFHHtFf/vIX3X///WpqatKYMWO0adMmNTU1SZKqq6tN01RXV8fHNTU1qby8XHvttZdtGSsNDQ2mlzLzaiEAAAAAKB457bo8ceLE+P+HDx+u0aNHa//999fDDz+so446SlLq09kMw3B9YptbmRkzZmj69Onxv1taWgh2AQAAAKRI535ar/UiPHmVL+/Vq5eGDx+ujz/+OH7fbnJmdsOGDfEsb01Njdra2rR582bbMlYqKiriL2YO4gXNAAAAAID8kVeBbmtrq95//30NGDBAQ4YMUU1NjRobG+Pj29ratGTJEo0ZM0aSVFdXp27dupnKrF+/Xu+88068DAAAAACkK6qS0D4IT067Ll999dWaNGmSBg0apA0bNujWW29VS0uLzj//fEUiEdXX12vWrFkaOnSohg4dqlmzZqlnz54655xzJElVVVW68MILddVVV6lv377q06ePrr76ag0fPjzlhckAAAAA4FeHEVFHCN2Mw6gTXXIa6K5bt04/+tGPtHHjRu2999466qij9Morr2jw4MGSpGuuuUbbt2/XJZdcos2bN2vUqFFatGiRevfuHa/jrrvuUllZmSZPnqzt27frhBNO0Lx581RaWpqrxQIAAAAA5FDE8PMypiLV0tKiqqoqjdMZKot0y3VzAAAAgKLRbuzUi3pKzc3NBfVsnFiMcPFLZ6tij+BjhNatO/WH4x4vuPVSKOgYDgAAAAAoKjntugwAAAAA+cwwShQ1gs8PGiHUiS6sXQAAAABAUSGjCwAAAAA2OhRRh0J46nIIdaILGV0AAAAAQFEhowsAAAAANqKGFA3hnbfR3f7dN+EiowsAAAAAKCpkdAEAAADARjSkpy6HUSe6sHYBAAAAAEWFjC4AAAAA2IgqomgIT0gOo050IdAFAAAAABsdRkQdITyMKow60YWuywAAAACAokJGFwAAAABs8DCqwsTaBQAAAAAUFTK6AAAAAGAjqoiiIdxPy8OowkVGFwAAAABQVMjoAgAAAIANI6TXCxlkdENFRhcAAAAAUFTI6AIAAACAjagR0j26vEc3VGR0AQAAAABFhYwuAAAAANjgPbqFiUAXAAAAAGzQdbkwcRkBAAAAAFBUyOgCAAAAgI1oSK8XCqNOdCGjCwAAAAAoKmR0AQAAAMAG9+gWJjK6AAAAAICiQkYXAAAAAGyQ0S1MZHQBAAAAAEWFjC4AAAAA2CCjW5jI6AIAAAAAigoZXQAAAACwQUa3MJHRBQAAAAAUFTK6AAAAAGDDkBRV8NlXI/AakYhAFwAAAABs0HW5MNF1GQAAAABQVMjoAgAAAIANMrqFiYwuAAAAAKCokNEFAAAAABtkdAsTGV0AAAAAQFEh0AUAAAAAG7GMbhgfP1566SVNmjRJtbW1ikQievLJJ+Pjdu7cqWuvvVbDhw9Xr169VFtbq/POO09ffPFFwGujcBDoAgAAAECe27Ztmw477DDNmTMnZdw333yj119/XTfddJNef/11PfHEE/roo490+umn56Cl+YF7dAEAAADAhmFEZIRwP63fOidOnKiJEydajquqqlJjY6Np2O9+9zt95zvf0Zo1azRo0KC021moCHQBAAAAIEdaWlpMf1dUVKiioiLjepubmxWJRLTnnntmXFchousyAAAAANiIKhLaR5IGDhyoqqqq+KehoSHjNu/YsUPXXXedzjnnHFVWVmZcXyEiowsAAAAANsJ+vdDatWtNwWim2dydO3fqhz/8oaLRqO65556M6ipkBLoAAAAAkCOVlZWBZV137typyZMna/Xq1XrhhRd222yulEddlxsaGhSJRFRfXx8fZhiGZs6cqdraWvXo0UPjxo3Tu+++a5qutbVVl19+ufr166devXrp9NNP17p167LcegAAAADFKPYwqjA+QYoFuR9//LEWL16svn37Blp/ocmLQHfFihWaO3euDj30UNPw22+/XXfeeafmzJmjFStWqKamRieeeKK2bNkSL1NfX6+FCxdq/vz5Wrp0qbZu3arTTjtNHR0d2V4MAAAAAAjF1q1btWrVKq1atUqStHr1aq1atUpr1qxRe3u7vv/97+u1117TH//4R3V0dKipqUlNTU1qa2vLbcNzJOeB7tatW3Xuuefq/vvv11577RUfbhiGZs+erRtuuEFnnXWWhg0bpocffljffPONHnvsMUmdTxJ74IEHdMcdd2j8+PEaMWKEHn30Ub399ttavHix7TxbW1vV0tJi+gAAAABAstg9umF8/Hjttdc0YsQIjRgxQpI0ffp0jRgxQr/4xS+0bt06Pf3001q3bp0OP/xwDRgwIP5ZtmxZGKsl7+U80L300kt16qmnavz48abhq1evVlNTkyZMmBAfVlFRobFjx8Y31sqVK7Vz505TmdraWg0bNsxxgzY0NJiebDZw4MCAlwoAAAAAgjNu3DgZhpHymTdvnvbdd1/LcYZhaNy4cbluek7kNNCdP3++Xn/9dctHaDc1NUmSqqurTcOrq6vj45qamlReXm7KBCeXsTJjxgw1NzfHP2vXrs10UQAAAAAUoUK5RxdmOXvq8tq1a3XFFVdo0aJF6t69u225SMS8AxiGkTIsmVuZoF7CDAAAAADIPznL6K5cuVIbNmxQXV2dysrKVFZWpiVLlujuu+9WWVlZPJObnJndsGFDfFxNTY3a2tq0efNm2zIAAAAAkC4jpPtzyeiGK2eB7gknnKC33347/uSwVatWaeTIkTr33HO1atUq7bfffqqpqVFjY2N8mra2Ni1ZskRjxoyRJNXV1albt26mMuvXr9c777wTLwMAAAAA2L3krOty7969NWzYMNOwXr16qW/fvvHh9fX1mjVrloYOHaqhQ4dq1qxZ6tmzp8455xxJUlVVlS688EJdddVV6tu3r/r06aOrr75aw4cPT3m4FQAAAAD4ZUgyjHDqRXhyFuh6cc0112j79u265JJLtHnzZo0aNUqLFi1S796942XuuusulZWVafLkydq+fbtOOOEEzZs3T6WlpTlsOQAAAAAgVyKGEcb1icLS0tKiqqoqjdMZKot0y3VzAAAAgKLRbuzUi3pKzc3NqqyszHVzPIvFCIf9v6tU2jP4B9l2fNOqN79/R8Gtl0KR1xldAAAAAMilsF4FxMOowpXT9+gCAAAAABA0MroAAAAAYCNqRBQJIfsaJaMbKjK6AAAAAICiQkYXAAAAAGwYRkivF9rtHwkcLjK6AAAAAICiQkYXAAAAAGzw1OXCREYXAAAAAFBUyOgCAAAAgA0yuoWJjC4AAAAAoKiQ0QUAAAAAG7xHtzCR0QUAAAAAFBUyugAAAABgg/foFiYCXQAAAACw0RnohvEwqsCrRAK6LgMAAAAAigoZXQAAAACwweuFChMZXQAAAABAUSGjCwAAAAA2jF2fMOpFeMjoAgAAAACKChldAAAAALDBPbqFiYwuAAAAAKCokNEFAAAAADvcpFuQyOgCAAAAAIoKGV0AAAAAsBPSPbriHt1QEegCAAAAgA3D6PyEUS/CQ9dlAAAAAEBRIaMLAAAAADZ4vVBhIqMLAAAAACgqZHQBAAAAwI4RCefBUWR0Q0VGFwAAAABQVMjoAgAAAIANnrpcmMjoAgAAAACKChldAAAAALBj7PqEUS9CQ0YXAAAAAFBUyOgCAAAAgA3eo1uYyOgCAAAAAIoKGV0AAAAAcML9tAWHQBcAAAAAbNB1uTDRdRkAAAAAUFTI6AIAAACAHV4vVJDI6AIAAAAAigqBLgAAAADYioT48e6ll17SpEmTVFtbq0gkoieffNI03jAMzZw5U7W1terRo4fGjRund999N60lLgYEugAAAACQ57Zt26bDDjtMc+bMsRx/++23684779ScOXO0YsUK1dTU6MQTT9SWLVuy3NL8wD26AAAAAGAnT+7RnThxoiZOnGhdlWFo9uzZuuGGG3TWWWdJkh5++GFVV1frscce08UXX5xpawsOGV0AAAAAyJGWlhbTp7W11Xcdq1evVlNTkyZMmBAfVlFRobFjx2rZsmVBNrdgEOgCAAAAgB0jxI+kgQMHqqqqKv5paGjw3cSmpiZJUnV1tWl4dXV1fNzuJqeB7r333qtDDz1UlZWVqqys1OjRo/Xcc8/Fx3u5obq1tVWXX365+vXrp169eun000/XunXrsr0oAAAAAODb2rVr1dzcHP/MmDEj7boiEfMDrgzDSBm2u8hpoLvPPvvoN7/5jV577TW99tpr+u53v6szzjgjHsx6uaG6vr5eCxcu1Pz587V06VJt3bpVp512mjo6OnK1WAAAAACKhREJ7yPFk36xT0VFhe8m1tTUSFJK9nbDhg0pWd7dRU4D3UmTJumUU07RAQccoAMOOEC//vWvtccee+iVV15JuaF62LBhevjhh/XNN9/osccekyQ1NzfrgQce0B133KHx48drxIgRevTRR/X2229r8eLFtvNtbW1N6QsPAAAsfGe4tp/5HW0/8zsq7dsn160BgKwzjPA+QRkyZIhqamrU2NgYH9bW1qYlS5ZozJgxwc2ogOTNPbodHR2aP3++tm3bptGjR3u6oXrlypXauXOnqUxtba2GDRvmeNN1Q0ODqR/8wIEDw1swAAAKVOvEI3XlY/+fXrpnrl66Z65W3/ctle5ZletmAcBuaevWrVq1apVWrVolqfMBVKtWrdKaNWsUiURUX1+vWbNmaeHChXrnnXd0wQUXqGfPnjrnnHNy2/AcyXmg+/bbb2uPPfZQRUWFpk2bpoULF+rggw/2dEN1U1OTysvLtddee9mWsTJjxgxTP/i1a9cGvFQAABS+Q3+1Sif37Hr65ztjHlbTDw/OYYsAIAdCfhiVV6+99ppGjBihESNGSJKmT5+uESNG6Be/+IUk6ZprrlF9fb0uueQSjRw5Up9//rkWLVqk3r17p7/sBSzn79H99re/rVWrVunrr7/W448/rvPPP19LliyJj0/nhmq3MhUVFWn1fQcAYHdSUdJu+rs0UiLtns80AYCcGzdunAyH/s6RSEQzZ87UzJkzs9eoPJbzjG55ebn+5V/+RSNHjlRDQ4MOO+ww/fu//7unG6pramrU1tamzZs325YBAAAAgLSF/DAqhCPngW4ywzDU2trq6Ybquro6devWzVRm/fr1euedd3bbm64BAAjKX/44Wuvbt8b/rl8/UjUvfJXDFgEA4E1Ouy5ff/31mjhxogYOHKgtW7Zo/vz5evHFF/X888+bbqgeOnSohg4dqlmzZpluqK6qqtKFF16oq666Sn379lWfPn109dVXa/jw4Ro/fnwuFw0AgII34M7lmvT1z9V8QOffQx/8Sh0ffpLbRgFAlkWMzk8Y9SI8OQ10v/zyS02dOlXr169XVVWVDj30UD3//PM68cQTJXXeUL19+3Zdcskl2rx5s0aNGpVyQ/Vdd92lsrIyTZ48Wdu3b9cJJ5ygefPmqbS0NFeLBQBAcTAM9X1gufru+pM31AMACkXEcLqjeTfR0tKiqqoqjdMZKot0y3VzAAAAgKLRbuzUi3pKzc3NqqyszHVzPIvFCANn36KSHt0Drz+6fYfW1v+i4NZLoci7e3QBAAAAAMhEzl8vBAAAAAB5K6wnJPPU5VCR0QUAAAAAFBUyugCAvFF6wP5q+m5/lex66lF7j4j2+rBNPV77hzo2/TO3jQMA7J6MXZ8w6kVoCHQBALkXiahj3Ah9Pqq7ql9tVcW7azuHV/XW10fsra8uOlCD/uNDdWzclNt2AgB2PwS6BYmuyygKkW7lKR9FuO8BKBTR4w7X+tHdNejxpq4gV5Kat2jPv/1D/d7aqc8u+rZK96zKXSMBAEDBIKOLglZ6yLe1Y8Ae+vLICvX4quuyWFtVRL3XRtXzix0q+Z83Jd6iBeStkl69tL6uhwY/vkFq2WpZpufKz7RHv/3VNmJ/lf7t9Sy3EACwWyOjW5AIdFGQSg/YX00n9FdH94iqX/1Gg575pyJfdd2/F+nVUzurq7RpeE/t/M5oDVi2VSVvfaLoN9/ksNUArJRU762Krw1Fmrc4/ub3fWWDvjy+v/r9LWtNAwBgt9LS0mI5PBKJqKKiQuXl5VluUfoIdFFYIhG1TajTxsPKVb1ih8rfW2dZzNj2jcr+8Y2q/yFFa/fWxrpKGYcdpr3nvS6jtTXLjQbgpqI5KsOl50WkZasi7f2z1CIAAHbZjV4vtOeeeyricPvfPvvsowsuuEA333yzSkry+y5YAl0UlLYJddpwRLn2XfCFjG3esrMlX3yl6vUbtXHCfvrywjpV3/+ajJ1tIbcUAAAAKCzz5s3TDTfcoAsuuEDf+c53ZBiGVqxYoYcfflg33nijvvrqK/3bv/2bKioqdP311+e6uY4IdFEw2k4+Ul8d1s1XkBtjGIb6Na7WxvFD9OVFI1Xz4OuK7tgRUksB+LWtplRVJSUyolHbMtGavuqoyL+r3wCA4hYxOj9h1JtvHn74Yd1xxx2aPHlyfNjpp5+u4cOH6w9/+IP++te/atCgQfr1r3+d94FufuebgV0iI4dp47BuGvxf/oPcGCMaVb/Fq1W+1dDm7x8ebAMBmJR9q1alBx/Q9dlrL9uyHZ+vlyJSR01f2zKRSERfHVml6let7x0CAACZW758uUaMGJEyfMSIEVq+fLkk6ZhjjtGaNWuy3TTfCHSR/0pKtf6YStW+tCXtIDfGiEbVr3G1tgwsUdnggQE1EEBMpFu5tkw5Sp+et6+2fHsvbdtvT20+vI/W/utBap14pFRSmjKN0dqqmqVf67NJVTIsgt1ISYn+efwQtXePKPLeP7KxGAAAdDFC/OSZffbZRw888EDK8AceeEADB3aeO2/atEl7OVzAzhd0XUbei3QrU9k3hko/+zKQ+oxoVP3ebld0r97SZ4FUCUCSSkq18bw6KSLt+8inMtrbJUm9JPXp2UNrvv8t9SmtU/c/r0h55Vd01XvaN3qgPju9j/b6sFJ7Ll8nGYY6+u+lDaMqFS2PaMBcbjkAACBM//Zv/6Yf/OAHeu6553TkkUcqEoloxYoV+uCDD/T//t//kyStWLFCU6ZMyXFL3XkOdNetW6d99tknzLYAlr45+TCVbw32klfFplZ9MW5P1awKtFpgt9Z60hGKGFL/5z+LB7kxxjfbNei/1mnt2fvoW59+W9F3PkiZPvrWB9r38z76evwB+mr8oM5h3aT+f29R5P3/JcjNkdZTjlTL4M7ThQFPrlb7+qYctwgAEJbTTz9dH330ke677z59+OGHMgxDEydO1JNPPql9991XkvR//+//zW0jPfIc6A4bNky/+93vNHXq1DDbA6SIdotorzc2BVpn2T/Wq9uw/QOtE9idlfTura9GdNPgxzekBLkxxvYdqv77N1r/3T6qfse6no5N/1TvBa+Yp1Ne9u7aLTT/+Cjd96t/1+EVFZKkE84+Xd2n1hDsAkARGzx4sBoaGnLdjIx5vkd31qxZuvTSS3X22Wdr06Zggw4AQGGLlJao1xeG9LXzw6K6ffyFyrYTthaKY6f/PR7kStJfD35a688cksMWAUD2RdT15OVAP7leMAfffPONPvjgA7311lumTyHxHOhecsklevPNN7V582Ydcsghevrpp8NsFwAAAADknhEJ75NnvvrqK5122mnq3bu3DjnkEI0YMcL0KSS+HkY1ZMgQvfDCC5ozZ47OPvtsHXTQQSorM1fx+uuvB9pAAAAAAED46uvrtXnzZr3yyis6/vjjtXDhQn355Ze69dZbdccdd+S6eb74furyZ599pscff1x9+vTRGWeckRLoAgB2P0ZHVFu/FVG/PSsduy+3/0ut2nvk3xVsWFvy70fprV8u16Hl3SVJp3x4igY8s0bWd2EDQJEK62EReXgnzwsvvKCnnnpKRx55pEpKSjR48GCdeOKJqqysVENDg0499dRcN9EzX1Hq/fffr6uuukrjx4/XO++8o7333jusdgFxJe2GNh/eV3u90BxYne37DdDOXpxsA0GJbtmi/m/s1Fdj9lb/Rd9YPpAq0r1CTaN66luL/6moTT2le+2l5vEHaGevzjtroqXS3q99LeODf8hobQ1xCWBlr4eX6/J//kzN+3aeLnzriU/V/vnnOW4VACAs27ZtU//+/SVJffr00VdffaUDDjhAw4cPL7ieu54D3ZNPPlmvvvqq5syZo/POOy/MNgEmvZ5/SxvOC/aegNa+Fap98Wvbk20A/nVf9Ia2/uRIfXnyYFU/u1pGtOsbFunRXWu+v4/2+rhd0bc/tJy+ZNiB+vTMPtrz46j2XrxGktRRvae+HLOnjGPrVH3/SoLdHOj+zKvqvuv/ZHIB7JZ2o4zut7/9bX344Yfad999dfjhh+sPf/iD9t13X913330aMGBArpvni+dAt6OjQ2+99Rbv0kXWRdt2qr1XRB2Dq1X62ZcZ1xcpKdHG4WXa9+0tBLpAgIz2dvV75HU1nzVCn16wn/q+166SdkNtvUu1ZWCJ+r63UxXPvS4Zqb/sJYd2BrmDn2lWyRdfxX/7S9Z9pQFfbNKm7+6rLy+qU82DqxT95pvsLhgAALuJ+vp6rV+/XpJ0880366STTtIf//hHlZeXa968ebltnE+eA93GxsYw2wHYi3ZowMst+mJspQZu3CJjW/onuZGSEm06YV/tsc5Q+2drA2wkAEkyWltV+adX1Gefbym6Z29JUg9JezZuUMemf1pOE6moUNOxfTT4z51Bbkqd0aj6vvCpmiYNkXHQEGnlu2EuAgAAJrHXAYVRb74599xz4/8fMWKEPv30U33wwQcaNGiQ+vXrl8OW+ceTpFAQjNfeUZ+9j9Sa79dq0H99LuOb7b7riAW5rVUlqnngdbK5QIja130urfNWtvRbA6SIVPrFJtteXEY0qr1XtOjL0VXqvzKwZgIAAAc9e/bUEUccketmpIVAFwWj4vnX1M8Yqc+mfEuDF/gPdmNBbvV/rFSU+/yAvNJrfYfpnl4rpes3qrS1MkstAgBglyK/R3f69Omey955550htiRYBLooHIah8r+8pn6RkVrz/W+pesUOlb/vnjIyBvTTxiOq1FGuzkwuQS4AAAAgSXrjjTc8lYtECuuNJQS6KCyGoYrnVmjgp0O1/rt7K3r4v6j679tU1rJD2rg5XizSs4fa967UpsP2UFtlRDXLt6n0zU8U3bEjh40HYKe1skSRSESGxYOqYozevWTwqwUAyLYiz+j+7W9/0z/+8Q/tu+++KikpyXVzAsMpAwpSx/sfq//7H6vk0AO1Y8Ae+nxcL/XY0Cc+vnWviHqvi2qvj3ao5OW3pGgH9+QCeSr61Sa19qmVUbmH1LzFttymo6q15ydtWWwZAAC7x8Oohg4dqvXr18ffoTtlyhTdfffdqq6uznHL0kegi4IWfesDlb8lDXyxImWc0dZm+RoTAPklumWL+r++Q5+dXa3B/xWVtmxLKbN9xGBt3Seivs98oo4ctBEAgGKW3KPq2WefVUNDQ45aEwwCXRQFg/tugYJW+uIbqik5QmvOHqCaV3eo/L1d999X9VbzYf3UvH+pBv/Hx+r4ujmn7QQA7IaMSOcnjHoRGgJdAEDuGYbK/rpSg9b9i5q+u7dK/mV/SVJ7j4j2/HinBv3HJ+rYuCnHjQQAoDhFIpGUh00V2sOnkhHoAgDyRseHn2jvDz9JHZ6DtgAAIKnoH0YldXZdvuCCC1RR0Xk74I4dOzRt2jT16tXLVO6JJ57IRfPSQqALAAAAALux888/3/T3j3/84xy1JDgEugAAAABgY3d46vJDDz2U6yYErnhelAQAAAAAgMjoAgAAAIC93eAe3WJEoAsAAGxtPn+0mod2/n//h79Ux8f/yG2DAADwgEAXAABYarpijP581e3ap2wPSdIlJx2lT8/Zj2AXwO4lpHt0yeiGi3t0AQCApQnnL48HuZJ0z7deUdP46hy2CAAAb8joAgAAAIAd7tEtSAS6AADA0k6jNHUgJ2YAdjcEugWJrssAAMDSGzcfob9u7wp2h//9HNUs+CCHLQIAwBsyugAAwFL3/35Vt/3zx7p5QHdJ0sAln6hj8+YctwoAsisS0sOo/NTZ3t6umTNn6o9//KOampo0YMAAXXDBBbrxxhtVUkLu0gqBLgAAsBVZ9qZ67fp/R05bAgC7r9tuu0333XefHn74YR1yyCF67bXX9JOf/ERVVVW64oorct28vESgCwAAAAB5bPny5TrjjDN06qmnSpL23Xdf/elPf9Jrr72W45blr5zmuRsaGnTkkUeqd+/e6t+/v84880x9+OGHpjKGYWjmzJmqra1Vjx49NG7cOL377rumMq2trbr88svVr18/9erVS6effrrWrVuXzUUBAAAAAN9aWlpMn9bW1pQyxxxzjP7617/qo48+kiS9+eabWrp0qU455ZRsN7dg5DTQXbJkiS699FK98soramxsVHt7uyZMmKBt27bFy9x+++268847NWfOHK1YsUI1NTU68cQTtWXLlniZ+vp6LVy4UPPnz9fSpUu1detWnXbaaerooJMVAAAAgAwYIX4kDRw4UFVVVfFPQ0NDShOuvfZa/ehHP9KBBx6obt26acSIEaqvr9ePfvSj0Ba70OW06/Lzzz9v+vuhhx5S//79tXLlSh133HEyDEOzZ8/WDTfcoLPOOkuS9PDDD6u6ulqPPfaYLr74YjU3N+uBBx7Qf/7nf2r8+PGSpEcffVQDBw7U4sWLddJJJ6XMt7W11XSlpKWlJcSlBAAAAABra9euVWVlZfzvioqKlDILFizQo48+qscee0yHHHKIVq1apfr6etXW1ur888/PZnMLRl49oqu5uVmS1KdPH0nS6tWr1dTUpAkTJsTLVFRUaOzYsVq2bJkkaeXKldq5c6epTG1trYYNGxYvk6yhocF01WTgwIFhLRIAAACAAhZ76nIYH0mqrKw0fawC3Z///Oe67rrr9MMf/lDDhw/X1KlTdeWVV1pmf9EpbwJdwzA0ffp0HXPMMRo2bJgkqampSZJUXV1tKltdXR0f19TUpPLycu211162ZZLNmDFDzc3N8c/atWuDXhwAAAAACMQ333yT8hqh0tJSRaPRHLUo/+XNU5cvu+wyvfXWW1q6dGnKuEgkYvrbMIyUYcmcylRUVFheKQEAAACAFCG8R9ePSZMm6de//rUGDRqkQw45RG+88YbuvPNO/fSnP81tw/JYXmR0L7/8cj399NP629/+pn322Sc+vKamRpJSMrMbNmyIZ3lramrU1tamzUkvsE8sAwAAAABpCflhVF787ne/0/e//31dcsklOuigg3T11Vfr4osv1q9+9asglrAo5TTQNQxDl112mZ544gm98MILGjJkiGn8kCFDVFNTo8bGxviwtrY2LVmyRGPGjJEk1dXVqVu3bqYy69ev1zvvvBMvAwAAAACFqnfv3po9e7Y+++wzbd++Xf/7v/+rW2+9VeXl5bluWt7KadflSy+9VI899pieeuop9e7dO565raqqUo8ePRSJRFRfX69Zs2Zp6NChGjp0qGbNmqWePXvqnHPOiZe98MILddVVV6lv377q06ePrr76ag0fPjz+FGYAAAAASEfig6OCrhfhyWmge++990qSxo0bZxr+0EMP6YILLpAkXXPNNdq+fbsuueQSbd68WaNGjdKiRYvUu3fvePm77rpLZWVlmjx5srZv364TTjhB8+bNU2lpabYWBQAAAACQJyKGYez21xJaWlpUVVWlcTpDZZFuuW4OAAAAUDTajZ16UU+pubnZ9L7YfBeLEYb+fJZKK7oHXn9H6w59/NvrC269FIq8eBgVAAAAAABByZvXCwEAAABAvuEe3cJERhcAAAAAUFTI6AIAAACAHZ/vvPVVL0JDRhcAAAAAUFTI6AIAAACAHTK6BYmMLgAAAACgqJDRBQAAAAAbPHW5MBHoAgAAAIAdui4XJLouAwAAAACKChldAAAAALBDRrcgkdEFAAAAABQVMroAAAAAYIOHURUmMroAAAAAgKJCRhcAAAAA7HCPbkEiowsAAAAAKCpkdAEAAADABvfoFiYyugAAAACAokJGFwAAAADscI9uQSKjCwAAAAAoKmR0AQAAAMAOGd2CRKALAAAAADYiuz5h1Ivw0HUZAAAAAFBUyOgCAAAAgB26LhckMroAAAAAgKJCRhcAAAAAbESMzk8Y9SI8ZHQBAAAAAEWFjC4AAAAA2OEe3YJERhcAAAAAUFTI6AIAAACAE7KvBYeMLgAAAACgqJDRBQAAAAAbPHW5MBHoAgAAAIAdHkZVkOi6DAAAAAAoKmR0AQAAAMAGXZcLExldAAAAAEBRIaMLAAAAAHa4R7cgkdEFAAAAABQVMroAAAAAYIN7dAsTGV0AAAAAQFEhowsAAAAAdrhHtyCR0QUAAAAAFBUyugAAAABgh4xuQSKjCwAAAAAoKmR0AQAAAMAGT10uTAS6AAAAAGCHrssFKaddl1966SVNmjRJtbW1ikQievLJJ03jDcPQzJkzVVtbqx49emjcuHF69913TWVaW1t1+eWXq1+/furVq5dOP/10rVu3LotLAQAAAADh+vzzz/XjH/9Yffv2Vc+ePXX44Ydr5cqVuW5W3sppoLtt2zYddthhmjNnjuX422+/XXfeeafmzJmjFStWqKamRieeeKK2bNkSL1NfX6+FCxdq/vz5Wrp0qbZu3arTTjtNHR0d2VoMAAAAAEUqYhihfbzavHmzjj76aHXr1k3PPfec3nvvPd1xxx3ac889w1vwApfTrssTJ07UxIkTLccZhqHZs2frhhtu0FlnnSVJevjhh1VdXa3HHntMF198sZqbm/XAAw/oP//zPzV+/HhJ0qOPPqqBAwdq8eLFOumkkyzrbm1tVWtra/zvlpaWgJcMAAAAANwlxyIVFRWqqKgwDbvttts0cOBAPfTQQ/Fh++67bzaaV7Dy9qnLq1evVlNTkyZMmBAfVlFRobFjx2rZsmWSpJUrV2rnzp2mMrW1tRo2bFi8jJWGhgZVVVXFPwMHDgxvQQAAAAAULiPEj6SBAweaYpOGhoaUJjz99NMaOXKkfvCDH6h///4aMWKE7r///tAWuRjkbaDb1NQkSaqurjYNr66ujo9rampSeXm59tprL9syVmbMmKHm5ub4Z+3atQG3HgAAAADcrV271hSbzJgxI6XMP/7xD917770aOnSo/vKXv2jatGn62c9+pkceeSQHLS4Mef/U5UgkYvrbMIyUYcncylh1BwAAAACAZGG/XqiyslKVlZWOZaPRqEaOHKlZs2ZJkkaMGKF3331X9957r84777zgG1cE8jajW1NTI0kpmdkNGzbEs7w1NTVqa2vT5s2bbcsAAAAAQCEbMGCADj74YNOwgw46SGvWrMlRi/Jf3ga6Q4YMUU1NjRobG+PD2tratGTJEo0ZM0aSVFdXp27dupnKrF+/Xu+88068DAAAAACkLeR7dL04+uij9eGHH5qGffTRRxo8eHDai1Xsctp1eevWrfrkk0/if69evVqrVq1Snz59NGjQINXX12vWrFkaOnSohg4dqlmzZqlnz54655xzJElVVVW68MILddVVV6lv377q06ePrr76ag0fPjz+FGYAAAAAKGRXXnmlxowZo1mzZmny5Ml69dVXNXfuXM2dOzfXTctbOQ10X3vtNR1//PHxv6dPny5JOv/88zVv3jxdc8012r59uy655BJt3rxZo0aN0qJFi9S7d+/4NHfddZfKyso0efJkbd++XSeccILmzZun0tLSrC8PAAAAgOIS9j26Xhx55JFauHChZsyYoVtuuUVDhgzR7Nmzde655wbfsCIRMQwfbyouUi0tLaqqqtI4naGySLdcNwcAAAAoGu3GTr2op9Tc3Oz60KV8EosRjvjRr1Va3j3w+jvaduj1P91QcOulUOT9U5cBAAAAIGd83k/rq16EhkAXAAAAAGzkQ9dl+Je3T10GAAAAACAdZHQBAAAAwA5dlwsSGV0AAAAAQFEhowsAAAAADriftvCQ0QUAAAAAFBUyugAAAABgxzA6P2HUi9CQ0QUAAAAAFBUyugAAAABgg/foFiYyugAAAACAokJGFwAAAADs8B7dgkSgCwAAAAA2ItHOTxj1Ijx0XQYAAAAAFBUyugAAAABgh67LBYmMLgAAAACgqJDRBQAAAAAbvF6oMJHRBQAAAAAUFTK6AAAAAGDHMDo/YdSL0JDRBQAAAAAUFTK6AAAAAGCDe3QLExldAAAAAEBRIaMLAAAAAHZ4j25BIqMLAAAAACgqZHQBAAAAwAb36BYmAl0AAAAAsMPrhQoSXZcBAAAAAEWFjC4AAAAA2KDrcmEiowsAAAAAKCpkdAEAAADADq8XKkhkdAEAAAAARYWMLgAAAADY4B7dwkRGFwAAAABQVMjoAgAAAICdqNH5CaNehIaMLgAAAACgqJDRBQAAAAA7PHW5IBHoAgAAAICNiEJ6GFXwVSIBXZcBAAAAAEWFjC4AAAAA2DGMzk8Y9SI0ZHQBAAAAAEWFjC4AAAAA2IgYId2jS0I3VGR0AQAAAABFhYwuAAAAANjh9UIFiYwuAAAAAKCokNEFAAAAABsRw1AkhCckh1EnupDRBQAAAAAUlaIJdO+55x4NGTJE3bt3V11dnV5++eVcNwkAAABAoYuG+EFoiiLQXbBggerr63XDDTfojTfe0LHHHquJEydqzZo1uW4aAAAAACDLiiLQvfPOO3XhhRfqX//1X3XQQQdp9uzZGjhwoO69995cNw0AAABAAYvdoxvGJ10NDQ2KRCKqr68PbkGLTME/jKqtrU0rV67UddddZxo+YcIELVu2zHKa1tZWtba2xv9ubm6WJEX3qFA00i28xgIAAAC7mahRIm2VjEJ9+FKevV5oxYoVmjt3rg499NBg21NkCj7Q3bhxozo6OlRdXW0aXl1draamJstpGhoa9Mtf/jJl+Etb/79Q2ggAAADs7rZs2aKqqqpcNyPvtLS0mP6uqKhQRUWFZdmtW7fq3HPP1f33369bb701G80rWAUf6MZEIhHT34ZhpAyLmTFjhqZPnx7/++uvv9bgwYO1Zs0avnwFrKWlRQMHDtTatWtVWVmZ6+YgTWzH4sG2LA5sx+LAdiwOhbodDcPQli1bVFtbm+umpMcwOj9h1Ctp4MCBpsE333yzZs6caTnJpZdeqlNPPVXjx48n0HVR8IFuv379VFpampK93bBhQ0qWN8buKklVVVVBHTRgrbKyku1YBNiOxYNtWRzYjsWB7VgcCnE7kkyyl3zhwi6bO3/+fL3++utasWJFtppW0Ar+YVTl5eWqq6tTY2OjaXhjY6PGjBmTo1YBAAAAKAYRI7yP1HXhIvaxCnTXrl2rK664Qo8++qi6d++e5TVQmAo+oytJ06dP19SpUzVy5EiNHj1ac+fO1Zo1azRt2rRcNw0AAAAAMrJy5Upt2LBBdXV18WEdHR166aWXNGfOHLW2tqq0tDSHLcw/RRHoTpkyRZs2bdItt9yi9evXa9iwYXr22Wc1ePBgT9NXVFTo5ptvtu0mgMLAdiwObMfiwbYsDmzH4sB2LA5sxxwJ+R5dL0444QS9/fbbpmE/+clPdOCBB+raa68lyLUQMQr2Od8AAAAAEI6WlhZVVVVp7OgbVVYWfHfh9vYdWrL8VjU3N6d1z/W4ceN0+OGHa/bs2YG3rRgURUYXAAAAAMIQiXZ+wqgX4SHQBQAAAIAC8+KLL+a6CXmNQBcAAAAA7OTBPbrwr+BfLwQAAAAAQKLdPtC95557NGTIEHXv3l11dXV6+eWXc90kJGhoaNCRRx6p3r17q3///jrzzDP14YcfmsoYhqGZM2eqtrZWPXr00Lhx4/Tuu++ayrS2turyyy9Xv3791KtXL51++ulat25dNhcFCRoaGhSJRFRfXx8fxnYsDJ9//rl+/OMfq2/fvurZs6cOP/xwrVy5Mj6e7VgY2tvbdeONN2rIkCHq0aOH9ttvP91yyy2KRrtuGGNb5p+XXnpJkyZNUm1trSKRiJ588knT+KC22ebNmzV16lRVVVWpqqpKU6dO1ddffx3y0u0+nLbjzp07de2112r48OHq1auXamtrdd555+mLL74w1cF2zDIjxA9Cs1sHugsWLFB9fb1uuOEGvfHGGzr22GM1ceJErVmzJtdNwy5LlizRpZdeqldeeUWNjY1qb2/XhAkTtG3btniZ22+/XXfeeafmzJmjFStWqKamRieeeKK2bNkSL1NfX6+FCxdq/vz5Wrp0qbZu3arTTjtNHR0duVis3dqKFSs0d+5cHXrooabhbMf8t3nzZh199NHq1q2bnnvuOb333nu64447tOeee8bLsB0Lw2233ab77rtPc+bM0fvvv6/bb79dv/3tb/W73/0uXoZtmX+2bdumww47THPmzLEcH9Q2O+ecc7Rq1So9//zzev7557Vq1SpNnTo19OXbXThtx2+++Uavv/66brrpJr3++ut64okn9NFHH+n00083lWM7ZlfEMEL7IETGbuw73/mOMW3aNNOwAw880Ljuuuty1CK42bBhgyHJWLJkiWEYhhGNRo2amhrjN7/5TbzMjh07jKqqKuO+++4zDMMwvv76a6Nbt27G/Pnz42U+//xzo6SkxHj++eezuwC7uS1bthhDhw41GhsbjbFjxxpXXHGFYRhsx0Jx7bXXGsccc4zteLZj4Tj11FONn/70p6ZhZ511lvHjH//YMAy2ZSHQ/9/e/YfUVf9xHH/dtHt143rpGu4mm8OBNJvClkZpsrXaV6IWBNVYk2k0VoHe1qyRrNjgC9Nvf1QQLJlFFpSsfxItvqyszJBcistmRa3ItgXZKsaVaps/7uf7x/e7U3fu7MeXe7z3HJ8POH/ccz589jm8uey+fX9+SKazs9P6nKyYffXVV0aSOXjwoNVmYGDASDJff/21w281/5wbx/MZHBw0kszRo0eNMcRxLsViMSPJrC3faf5x0z+Tfq0t32kkmVgslupX9aR5W9GdnJzU8PCwqqurE+5XV1frk08+SdGocDGxWEySFA6HJUljY2MaHx9PiGMgENCaNWusOA4PD2tqaiqhTX5+vkpKSoj1HKuvr9edd96pdevWJdwnju7Q3d2t8vJy3XfffcrLy9OqVav00ksvWc+Jo3tUVVXpgw8+0JEjRyRJn3/+ufr7+3XHHXdIIpZulKyYDQwMKBQK6cYbb7Ta3HTTTQqFQsQ1RWKxmHw+nzV7hjimwNnNqJy44Jh5u+vyr7/+qpmZGS1atCjh/qJFizQ+Pp6iUeFCjDFqbGxUVVWVSkpKJMmK1fniePToUauN3+/XVVddNasNsZ47+/fv16FDhzQ0NDTrGXF0h++//16tra1qbGzUzp07NTg4qEcffVSBQEC1tbXE0UWefPJJxWIxLV++XBkZGZqZmdGePXt0//33S+I76UbJitn4+Ljy8vJm9Z+Xl0dcU+D06dNqamrSpk2blJOTI4k4Apdq3ia6Z/l8voTPxphZ95AeGhoadPjwYfX398969v/EkVjPnePHj2vbtm167733lJWVZduOOKa3eDyu8vJyNTc3S5JWrVqlL7/8Uq2traqtrbXaEcf09+abb+r1119XR0eHVqxYoZGRET322GPKz89XXV2d1Y5Yuk8yYna+9sR17k1NTWnjxo2Kx+N68cUXL9qeODrISIpftNX/1y8cM2+nLl999dXKyMiY9VetEydOzPprKFIvGo2qu7tbvb29Wrx4sXU/EolI0gXjGIlENDk5qZMnT9q2gbOGh4d14sQJlZWVKTMzU5mZmerr69MLL7ygzMxMKw7EMb1dc801uu666xLuFRcXWxv48X10jx07dqipqUkbN25UaWmpNm/erO3bt6ulpUUSsXSjZMUsEono559/ntX/L7/8Qlzn0NTUlDZs2KCxsTH19PRY1VyJOAKXat4mun6/X2VlZerp6Um439PTo8rKyhSNCucyxqihoUFvvfWWPvzwQxUWFiY8LywsVCQSSYjj5OSk+vr6rDiWlZXpyiuvTGjz008/6YsvviDWc+S2227T6OioRkZGrKu8vFw1NTUaGRnRsmXLiKML3HzzzbOO9zpy5IiWLl0qie+jm/z555+64orEnwAZGRnW8ULE0n2SFbOKigrFYjENDg5abT799FPFYjHiOkfOJrnffvut3n//feXm5iY8J45zj12X3WleT11ubGzU5s2bVV5eroqKCrW1tenYsWN65JFHUj00/E99fb06OjrU1dWlYDBo/aU6FAopOzvbOou1ublZRUVFKioqUnNzsxYsWKBNmzZZbbds2aLHH39cubm5CofDeuKJJ1RaWjprUyQ4IxgMWuuqz1q4cKFyc3Ot+8Qx/W3fvl2VlZVqbm7Whg0bNDg4qLa2NrW1tUkS30cXueuuu7Rnzx4VFBRoxYoV+uyzz/Tcc8/pwQcflEQs09Xvv/+u7777zvo8NjamkZERhcNhFRQUJCVmxcXFuv3227V161bt27dPkvTQQw9p/fr1uvbaa+f+pT3oQnHMz8/Xvffeq0OHDumdd97RzMyM9dsnHA7L7/cTR+BSzf1Gz+ll7969ZunSpcbv95vrr7/eOrYG6UE2x2u3t7dbbeLxuNm9e7eJRCImEAiY1atXm9HR0YR+Tp06ZRoaGkw4HDbZ2dlm/fr15tixY3P8Nvi7vx8vZAxxdIu3337blJSUmEAgYJYvX27a2toSnhNHd5iYmDDbtm0zBQUFJisryyxbtsw89dRT5syZM1YbYpl+ent7z/t/Yl1dnTEmeTH77bffTE1NjQkGgyYYDJqamhpz8uTJOXpL77tQHMfGxmx/+/T29lp9EMe5cfZ4oVtXNpnqst1Jv25d2cTxQg7yGUPNHAAAAAD+bmJiQqFQSLeubFJmRiDp/U/PnNGHI/9SLBZLWIeN5JjXU5cBAAAA4IKcOvOWeqOjSHQBAAAAwE5ckhOnMjlxZBEs83bXZQAAAACAN1HRBQAAAAAbTh0FxPFCzqKiCwAAAADwFCq6AAAAAGCHzahciYouAAAAAMBTqOgCAAAAgB0quq5ERRcAAAAA4CkkugCAtDczM6PKykrdc889CfdjsZiWLFmip59+OkUjAwB43tmKrhMXHEOiCwBIexkZGXrttdd04MABvfHGG9b9aDSqcDisXbt2pXB0AAAg3bBGFwDgCkVFRWppaVE0GtXatWs1NDSk/fv3a3BwUH6/P9XDAwB4VVySz6F+4RgSXQCAa0SjUXV2dqq2tlajo6PatWuXVq5cmephAQCANEOiCwBwDZ/Pp9bWVhUXF6u0tFRNTU2pHhIAwON8xsjnwHpaJ/rEX1ijCwBwlVdeeUULFizQ2NiYfvzxx1QPBwDgdWxG5UokugAA1xgYGNDzzz+vrq4uVVRUaMuWLTL8UAAAAOcg0QUAuMKpU6dUV1enhx9+WOvWrdPLL7+soaEh7du3L9VDAwB4Wdw4d8ExJLoAAFdoampSPB7XM888I0kqKCjQs88+qx07duiHH35I7eAAAEBaIdEFAKS9vr4+7d27V6+++qoWLlxo3d+6dasqKyuZwgwAcA5rdF2JXZcBAGlvzZo1mp6ePu+zd999d45HAwAA0h2JLgAAAADYcqr6SkXXSUxdBgAAAAB4ChVdAAAAALDj1Hpa1ug6ioouAAAAAMBTqOgCAAAAgJ24kSPraTlH11EkugAAAABgx8T/eznRLxzD1GUAAAAAgKdQ0QUAAAAAO2xG5UpUdAEAAAAAnkJFFwAAAADssBmVK1HRBQAAAAB4ChVdAAAAALDDGl1XoqILAAAAAPAUKroAAAAAYMfIoYpu8rvEX6joAgAAAAA8hUQXAAAAAOycXaPrxHWJWlpadMMNNygYDCovL0933323vvnmGwdf2v1IdAEAAAAgjfX19am+vl4HDx5UT0+PpqenVV1drT/++CPVQ0tbrNEFAAAAADvxuKS4Q/1KExMTCbcDgYACgUDCvQMHDiR8bm9vV15enoaHh7V69erkj80DqOgCAAAAgB2Hpy4vWbJEoVDIulpaWi46pFgsJkkKh8OOvrqbUdEFAAAAgBQ5fvy4cnJyrM/nVnPPZYxRY2OjqqqqVFJS4vTwXItEFwAAAADsXObGUZfVr6ScnJyERPdiGhoadPjwYfX39yd/TB5CogsAAAAALhCNRtXd3a2PP/5YixcvTvVw0hqJLgAAAADYiRtJDlR045fepzFG0WhUnZ2d+uijj1RYWJj88XgMiS4AAAAApLH6+np1dHSoq6tLwWBQ4+PjkqRQKKTs7OwUjy49kegCAAAAgA1j4jIm+ccLXU6fra2tkqRbbrkl4X57e7seeOCBJI7KO0h0AQAAACCNGSc2w/I4El0AAAAAsGPMZa2nvax+4ZgrUj0AAAAAAACSiYouAAAAANgxDu26TEXXUVR0AQAAAACeQkUXAAAAAOzE45Iv+bsuy4GdnPEXEl0AAAAAsMPUZVdi6jIAAAAAwFOo6AIAAACADROPyzgwddkwddlRVHQBAAAAAJ5CRRcAAAAA7LBG15Wo6AIAAAAAPIWKLgAAAADYiRvJR0XXbajoAgAAAAA8hYouAAAAANgxRpIDOyRT0XUUFV0AAAAAgKdQ0QUAAAAAGyZuZBxYo2uo6DqKRBcAAAAA7Ji4nJm67ECfsDB1GQAAAADgKVR0AQAAAMAGU5fdiYouAAAAAMBTqOgCAAAAgB3W6LoSiS4AAAAA2JjWlOTALONpTSW/U1hIdAEAAADgHH6/X5FIRP3j/3bs34hEIvL7/Y71P5/5DKugAQAAAGCW06dPa3Jy0rH+/X6/srKyHOt/PiPRBQAAAAB4CrsuAwAAAAA8hUQXAAAAAOApJLoAAAAAAE8h0QUAAAAAeAqJLgAAAADAU0h0AQAAAACeQqILAAAAAPCU/wBP4pNnpggxkgAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "flow_field.get_ddf()\n", + "\n", + "# 将一维数组重新整形成三维数组\n", + "NX = flow_field.FIELD_SHAPE[0]\n", + "NY = flow_field.FIELD_SHAPE[1]\n", + "ddf_plot = flow_field.ddf.reshape((9, NY, NX)).transpose(2, 1, 0)\n", + "flag_plot = flow_field.flag.reshape((NY, NX)).transpose(1, 0)\n", + "\n", + "# 计算速度场\n", + "ux = (ddf_plot[:, :, 1] + ddf_plot[:, :, 5] + ddf_plot[:, :, 8] - ddf_plot[:, :, 3] - ddf_plot[:, :, 6] - ddf_plot[:, :, 7])\n", + "uy = (ddf_plot[:, :, 2] + ddf_plot[:, :, 5] + ddf_plot[:, :, 6] - ddf_plot[:, :, 4] - ddf_plot[:, :, 7] - ddf_plot[:, :, 8])\n", + "\n", + "# 计算速度大小\n", + "speed = np.sqrt(ux**2 + uy**2)\n", + "\n", + "# 绘制标量速度场\n", + "plt.figure(figsize=(10, 10))\n", + "plt.subplot(2, 1, 1)\n", + "plt.imshow(speed.T, origin='lower', cmap='viridis', extent=[0, NX, 0, NY])\n", + "plt.colorbar(label='Speed')\n", + "plt.title('Scalar Velocity Field')\n", + "plt.xlabel('X')\n", + "plt.ylabel('Y')\n", + "\n", + "# 绘制flag\n", + "plt.subplot(2, 1, 2)\n", + "plt.imshow(flag_plot.T, origin='lower', cmap='viridis', extent=[0, NX, 0, NY])\n", + "plt.colorbar(label='Flag')\n", + "plt.title('Flag Field')\n", + "plt.xlabel('X')\n", + "plt.ylabel('Y')\n", + "\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "对应的滞后: -4\n", + "欧氏距离: 3.569344835619496\n", + "相似度: 0.9311015822896519\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# 示例序列，包含两个周期\n", + "sequence1 = np.sin(np.linspace(0, 4 * np.pi, 200))\n", + "sequence2 = 1*np.sin(np.linspace(0, 4.5 * np.pi, 200) - np.pi / 3) +0 # 相位差为 π/4\n", + "\n", + "seq1_mean = np.mean(sequence1)\n", + "seq1_std = np.std(sequence1)\n", + "\n", + "correlation = np.correlate(sequence1, sequence2, mode='full')\n", + "lags = np.arange(-len(sequence1) + 1, len(sequence1))\n", + "\n", + "# 找到最大相关系数及其对应的滞后\n", + "max_corr = np.max(correlation)\n", + "max_lag = lags[np.argmax(correlation)]\n", + "\n", + "print(f\"对应的滞后: {max_lag}\")\n", + "\n", + "# 根据滞后调整序列2\n", + "\n", + "aligned_seq2 = np.roll(sequence2, max_lag)\n", + "period_length = len(sequence1) // 2\n", + "if max_lag > 0:\n", + " seq1_one_period = sequence1[:period_length]\n", + " aligned_seq2_one_period = aligned_seq2[:period_length]\n", + "else:\n", + " seq1_one_period = sequence1[-period_length:]\n", + " aligned_seq2_one_period = aligned_seq2[-period_length:]\n", + "\n", + "# 计算一个周期的相似度\n", + "similarity = np.corrcoef(seq1_one_period, aligned_seq2_one_period)[0, 1]\n", + "euclidean_distance = np.linalg.norm(seq1_one_period - aligned_seq2_one_period)\n", + "similarity = np.mean(np.exp(-euclidean_distance / 50), similarity)\n", + "\n", + "print(f\"欧氏距离: {euclidean_distance}\")\n", + "print(f\"相似度: {similarity}\")\n", + "\n", + "# 绘制归一化交叉相关图\n", + "plt.figure(figsize=(12, 6))\n", + "plt.subplot(2, 1, 1)\n", + "plt.plot(lags, correlation)\n", + "plt.title('Normalized Cross-Correlation')\n", + "plt.xlabel('Lag')\n", + "plt.ylabel('Correlation')\n", + "plt.subplot(2, 1, 2)\n", + "plt.plot(sequence1, label='Sequence 1')\n", + "plt.plot(aligned_seq2, label='Aligned Sequence 2')\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "pycuda_3_10", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.13" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/setup.py b/setup.py new file mode 100644 index 0000000..c8e118f --- /dev/null +++ b/setup.py @@ -0,0 +1,17 @@ +from setuptools import setup, find_packages + +setup( + name='CelerisLab', + version='0.1', + packages=find_packages(), + install_requires=[ + 'pycuda', + 'numpy', + 'json' + ], + entry_points={ + 'console_scripts': [ + 'CelerisLab=CelerisLab.driver:main', + ], + }, +) \ No newline at end of file diff --git a/test.cu b/test.cu deleted file mode 100644 index 0eae4a9..0000000 --- a/test.cu +++ /dev/null @@ -1,13 +0,0 @@ -#include -#include - -extern "C" { -__global__ void add(float *x, float *y) -{ - int index = threadIdx.x; - int stride = blockDim.x; - - for (int i = index; i < 100; i += stride) - y[i] = x[i] + y[i]; -} -} diff --git a/test.ipynb b/test.ipynb deleted file mode 100644 index aa2794c..0000000 --- a/test.ipynb +++ /dev/null @@ -1,84 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "ename": "TypeError", - "evalue": "No registered converter was able to produce a C++ rvalue of type unsigned int from this Python object of type numpy.int64", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[1], line 25\u001b[0m\n\u001b[1;32m 22\u001b[0m drv\u001b[38;5;241m.\u001b[39mmemcpy_htod(y_gpu, y)\n\u001b[1;32m 24\u001b[0m \u001b[38;5;66;03m# 调用函数\u001b[39;00m\n\u001b[0;32m---> 25\u001b[0m \u001b[43madd_func\u001b[49m\u001b[43m(\u001b[49m\u001b[43mn\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mx_gpu\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my_gpu\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mblock\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m256\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgrid\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mn\u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[38;5;241;43m256\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 27\u001b[0m \u001b[38;5;66;03m# 将结果复制回CPU\u001b[39;00m\n\u001b[1;32m 28\u001b[0m drv\u001b[38;5;241m.\u001b[39mmemcpy_dtoh(y, y_gpu)\n", - "File \u001b[0;32m~/anaconda3/envs/pycuda_3_10/lib/python3.10/site-packages/pycuda/driver.py:502\u001b[0m, in \u001b[0;36m_add_functionality..function_call\u001b[0;34m(func, *args, **kwargs)\u001b[0m\n\u001b[1;32m 498\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtime\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m time\n\u001b[1;32m 500\u001b[0m start_time \u001b[38;5;241m=\u001b[39m time()\n\u001b[0;32m--> 502\u001b[0m \u001b[43mfunc\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_launch_kernel\u001b[49m\u001b[43m(\u001b[49m\u001b[43mgrid\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mblock\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43marg_buf\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mshared\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m 504\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m post_handlers \u001b[38;5;129;01mor\u001b[39;00m time_kernel:\n\u001b[1;32m 505\u001b[0m Context\u001b[38;5;241m.\u001b[39msynchronize()\n", - "\u001b[0;31mTypeError\u001b[0m: No registered converter was able to produce a C++ rvalue of type unsigned int from this Python object of type numpy.int64" - ] - } - ], - "source": [ - "import pycuda.autoinit\n", - "import pycuda.driver as drv\n", - "import numpy as np\n", - "\n", - "# 加载PTX文件\n", - "mod = drv.module_from_file(\"test.ptx\")\n", - "\n", - "# 获取函数\n", - "add_func = mod.get_function(\"add\")\n", - "\n", - "# 创建数据\n", - "n = np.uint32(100) # Convert to unsigned int\n", - "x = np.random.rand(n).astype(np.float32)\n", - "y = np.random.rand(n).astype(np.float32)\n", - "\n", - "# 分配内存\n", - "x_gpu = drv.mem_alloc(x.nbytes)\n", - "y_gpu = drv.mem_alloc(y.nbytes)\n", - "\n", - "# 将数据复制到GPU\n", - "drv.memcpy_htod(x_gpu, x)\n", - "drv.memcpy_htod(y_gpu, y)\n", - "\n", - "# 调用函数\n", - "add_func(x_gpu, y_gpu, block=(256,1,1), grid=(n//256,1))\n", - "\n", - "# 将结果复制回CPU\n", - "drv.memcpy_dtoh(y, y_gpu)\n", - "\n", - "# 检查结果\n", - "print(y)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "pycuda_3_10", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.13" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/test.ptx b/test.ptx deleted file mode 100644 index 823f0ab..0000000 --- a/test.ptx +++ /dev/null @@ -1,104 +0,0 @@ -// -// Generated by NVIDIA NVVM Compiler -// -// Compiler Build ID: CL-32688072 -// Cuda compilation tools, release 12.1, V12.1.105 -// Based on NVVM 7.0.1 -// - -.version 8.1 -.target sm_52 -.address_size 64 - - // .globl add - -.visible .entry add( - .param .u64 add_param_0, - .param .u64 add_param_1 -) -{ - .reg .pred %p<6>; - .reg .f32 %f<16>; - .reg .b32 %r<22>; - .reg .b64 %rd<25>; - - - ld.param.u64 %rd11, [add_param_0]; - ld.param.u64 %rd12, [add_param_1]; - cvta.to.global.u64 %rd1, %rd12; - cvta.to.global.u64 %rd2, %rd11; - mov.u32 %r1, %ntid.x; - mov.u32 %r20, %tid.x; - setp.gt.s32 %p1, %r20, 99; - @%p1 bra $L__BB0_7; - - mov.u32 %r12, 99; - sub.s32 %r13, %r12, %r20; - div.u32 %r3, %r13, %r1; - add.s32 %r14, %r3, 1; - and.b32 %r19, %r14, 3; - setp.eq.s32 %p2, %r19, 0; - @%p2 bra $L__BB0_4; - - mul.wide.s32 %rd13, %r20, 4; - add.s64 %rd24, %rd1, %rd13; - mul.wide.s32 %rd4, %r1, 4; - add.s64 %rd23, %rd2, %rd13; - -$L__BB0_3: - .pragma "nounroll"; - ld.global.f32 %f1, [%rd24]; - ld.global.f32 %f2, [%rd23]; - add.f32 %f3, %f2, %f1; - st.global.f32 [%rd24], %f3; - add.s32 %r20, %r20, %r1; - add.s64 %rd24, %rd24, %rd4; - add.s64 %rd23, %rd23, %rd4; - add.s32 %r19, %r19, -1; - setp.ne.s32 %p3, %r19, 0; - @%p3 bra $L__BB0_3; - -$L__BB0_4: - setp.lt.u32 %p4, %r3, 3; - @%p4 bra $L__BB0_7; - - mul.wide.s32 %rd10, %r1, 4; - -$L__BB0_6: - mul.wide.s32 %rd14, %r20, 4; - add.s64 %rd15, %rd2, %rd14; - add.s64 %rd16, %rd1, %rd14; - ld.global.f32 %f4, [%rd16]; - ld.global.f32 %f5, [%rd15]; - add.f32 %f6, %f5, %f4; - st.global.f32 [%rd16], %f6; - add.s64 %rd17, %rd15, %rd10; - add.s64 %rd18, %rd16, %rd10; - ld.global.f32 %f7, [%rd18]; - ld.global.f32 %f8, [%rd17]; - add.f32 %f9, %f8, %f7; - st.global.f32 [%rd18], %f9; - add.s32 %r15, %r20, %r1; - add.s32 %r16, %r15, %r1; - add.s64 %rd19, %rd17, %rd10; - add.s64 %rd20, %rd18, %rd10; - ld.global.f32 %f10, [%rd20]; - ld.global.f32 %f11, [%rd19]; - add.f32 %f12, %f11, %f10; - st.global.f32 [%rd20], %f12; - add.s32 %r17, %r16, %r1; - add.s64 %rd21, %rd19, %rd10; - add.s64 %rd22, %rd20, %rd10; - ld.global.f32 %f13, [%rd22]; - ld.global.f32 %f14, [%rd21]; - add.f32 %f15, %f14, %f13; - st.global.f32 [%rd22], %f15; - add.s32 %r20, %r17, %r1; - setp.lt.s32 %p5, %r20, 100; - @%p5 bra $L__BB0_6; - -$L__BB0_7: - ret; - -} -