{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "2b714898", "metadata": {}, "outputs": [], "source": [ "import torch\n", "\n", "from pina.problem import SpatialProblem, TimeDependentProblem\n", "from pina.operators import laplacian, grad\n", "from pina.geometry import CartesianDomain\n", "from pina.solvers import *\n", "from pina.trainer import Trainer\n", "from pina.equation import Equation\n", "from pina.equation.equation_factory import FixedValue\n", "from pina import Condition, Plotter\n", "from pytorch_lightning.loggers import TensorBoardLogger\n", "from pina.model import FeedForward\n", "from pina.callbacks import MetricTracker\n", "\n", "runs = 1" ] }, { "cell_type": "code", "execution_count": 2, "id": "6e9f489f", "metadata": {}, "outputs": [], "source": [ "class KleinGordon(TimeDependentProblem,SpatialProblem):\n", " output_variables = ['u']\n", " spatial_domain = CartesianDomain({'x':[-1,1],'y':[-1,1]})\n", " temporal_domain = CartesianDomain({'t': [0, 10]})\n", " def KG(input_,output_):\n", " u = output_.extract(['u'])\n", " x = input_.extract(['x'])\n", " y = input_.extract(['y'])\n", " t = input_.extract(['t'])\n", " u_t = grad(output_, input_, components=['u'], d=['t'])\n", " u_tt = grad(u_t, input_, components=['dudt'], d=['t'])\n", " nabla_u = laplacian(output_, input_, components=['u'], d=['x', 'y'])\n", " temp = (x + y) * torch.cos(2*t) + (x * y) * torch.sin(2*t)\n", " f = temp**2 - 4*temp\n", " \n", " return u_tt - nabla_u + u**2 - f\n", " def boundary_condition(input_,output_):\n", " u = output_.extract(['u'])\n", " x = input_.extract(['x'])\n", " y = input_.extract(['y'])\n", " t = input_.extract(['t'])\n", " temp = (x + y) * torch.cos(2*t) + (x * y) * torch.sin(2*t)\n", " return u - temp\n", " \n", " \n", " def initial_condition(input_,output_):\n", " x = input_.extract(['x'])\n", " y = input_.extract(['y'])\n", " u_exp = x+y\n", " return output_.extract(['u']) - u_exp\n", " \n", " def kg_sol(self,pts):\n", " x = pts.extract(['x'])\n", " y = pts.extract(['y'])\n", " t = pts.extract(['t'])\n", " return (x + y) * torch.cos(2*t) + (x * y) * torch.sin(2*t)\n", " truth_solution = kg_sol\n", " \n", " conditions = {\n", " 'gamma1': Condition(location=CartesianDomain({'x': [-1, 1], 'y': 1, 't': [0, 10]}), equation=Equation(boundary_condition)),\n", " 'gamma2': Condition(location=CartesianDomain({'x': [-1, 1], 'y': -1, 't': [0, 10]}), equation=Equation(boundary_condition)),\n", " 'gamma3': Condition(location=CartesianDomain({'x': 1, 'y': [-1, 1], 't': [0, 10]}), equation=Equation(boundary_condition)),\n", " 'gamma4': Condition(location=CartesianDomain({'x': -1, 'y': [-1, 1], 't': [0, 10]}), equation=Equation(boundary_condition)),\n", " 't0': Condition(location=CartesianDomain({'x': [-1, 1], 'y': [-1, 1], 't': 0}), equation=Equation(initial_condition)),\n", " 'D': Condition(location=CartesianDomain({'x': [-1, 1], 'y': [-1, 1], 't': [0, 10]}), equation=Equation(KG)),\n", " }" ] }, { "cell_type": "code", "execution_count": 3, "id": "d8eb6c25", "metadata": {}, "outputs": [], "source": [ "problem = KleinGordon()" ] }, { "cell_type": "code", "execution_count": 4, "id": "db9d4097", "metadata": {}, "outputs": [], "source": [ "problem.discretise_domain(64+64+64, 'random', locations=['D', 't0', 'gamma1', 'gamma2', 'gamma3', 'gamma4'])" ] }, { "cell_type": "code", "execution_count": 5, "id": "a47dcaea", "metadata": {}, "outputs": [], "source": [ "model = FeedForward(\n", " layers=[64,64,64,64],\n", " func=torch.nn.Tanh,\n", " output_dimensions=len(problem.output_variables),\n", " input_dimensions=len(problem.input_variables)\n", ")\n", "pinn = PINN(problem, model, optimizer_kwargs={'lr':0.001, 'weight_decay':1e-8})\n", "gpinn = GPINN(problem, model, optimizer_kwargs={'lr':0.001, 'weight_decay':1e-8})\n", "causalpinn = CausalPINN(problem, model, optimizer_kwargs={'lr':0.001, 'weight_decay':1e-8})\n", "sapinin = SAPINN(problem, model)\n" ] }, { "cell_type": "code", "execution_count": 6, "id": "6bd51d0c", "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "def error_giver(model):\n", " x = np.linspace(-1,1,10)\n", " y = np.linspace(-1,1,10)\n", " t = np.linspace(0,10,20)\n", " test_set = []\n", " for X in x:\n", " for Y in y:\n", " for T in t:\n", " test_set.append([X,Y,T])\n", " \n", " test_set = torch.Tensor(test_set) \n", "\n", " predicted_output= model(test_set).detach().numpy()\n", " def kg_sol(pts):\n", " x = pts[:,0]\n", " y = pts[:,1]\n", " t = pts[:,2]\n", " return (x + y) * torch.cos(2*t) + (x * y) * torch.sin(2*t)\n", " truth_output = kg_sol(test_set).detach().numpy().reshape((100*20,1))\n", "\n", " error = np.linalg.norm(predicted_output-truth_output) / np.linalg.norm(truth_output)\n", " return error" ] }, { "cell_type": "code", "execution_count": 7, "id": "72a88e7b", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/vemuri/anaconda3/envs/pina/lib/python3.11/site-packages/lightning_fabric/plugins/environments/slurm.py:204: The `srun` command is available on your system but is not used. HINT: If your intention is to run Lightning on SLURM, prepend your python command with `srun` like so: srun python /home/vemuri/anaconda3/envs/pina/lib/python3.11/site ...\n", "GPU available: True (cuda), used: True\n", "TPU available: False, using: 0 TPU cores\n", "IPU available: False, using: 0 IPUs\n", "HPU available: False, using: 0 HPUs\n", "/home/vemuri/anaconda3/envs/pina/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py:75: Starting from v1.9.0, `tensorboardX` has been removed as a dependency of the `pytorch_lightning` package, due to potential conflicts with other packages in the ML ecosystem. For this reason, `logger=True` will use `CSVLogger` as the default logger, unless the `tensorboard` or `tensorboardX` packages are found. Please `pip install lightning[extra]` or one of them to enable TensorBoard support by default\n", "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n", "/home/vemuri/anaconda3/envs/pina/lib/python3.11/site-packages/pytorch_lightning/loops/fit_loop.py:298: The number of training batches (1) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Epoch 0: 0%| | 0/1 [00:00" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Plotting at t=5\n" ] }, { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Plotting at t=10\n" ] }, { "data": { "image/png": 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dfvvtXrffddddMgxD//nPf6rc9qpYv369Dhw4oFtvvdVrb4sBAwaoXbt2pfpUSfrb3/7m9f3FF19MnwoAcLyUlBTFxcWpWbNmuuaaa1S7dm0tW7ZMZ511lg4fPqyPP/5YgwYN0tGjRz3jh59//lmpqan6/vvvPUst1qtXT1u2bNH333/v82OX/Nv+9PFDyYoIVXXq/E5OTo4OHTqk3r1764cfflBOTk61zg3AOQgsUKlJkybpxIkT5e5l8f3338swDLVp00ZxcXFeX1u3btWBAweq/NgtW7YsdVtxcbH+8Y9/qE2bNoqKilLDhg0VFxen//3vfwHp4O644w7Vq1ev3L0sSjr5P/7xj6We74cffujT823cuLHatGnjCSc+//xzXXzxxerVq5f27dunH374QV9++aWKi4s9gcXBgwd17NgxtW3bttT52rdvr+Li4lJ7hpT1+ysxcOBAxcTE6IMPPlBsbGylbT5VmzZtvL5PSkpSeHh4qT0fTn/8gwcP6siRI5o/f36p313JZE/J769kX43TA4aynv/pMjMzlZCQoAYNGvj1vMqze/fuMh87MjJSrVq18vy8xFlnnVWq3fXr19cvv/wSkPYAAKyjadOmioyMrPL9v//+e61YsaJUv5iSkiJJFY4revfurauvvlrTpk1Tw4YNdeWVV2rhwoVe+z3t3r1bCQkJiomJ8bpvyXKTp/dhZiuvT5Wkdu3alWpPyT5Up6JPBQC4wdy5c7Vy5Uq9+eabuvzyy3Xo0CFFRUVJknbs2CHDMHT//feXGkOUXLhXMoaYPn26jhw5oj/84Q/q2LGjxo8f77V3Zll2796t8PDwUssm+/Lv8Yp8+eWXSklJUe3atVWvXj3FxcV59v8isABQgj0sUKlWrVrphhtu0Pz58zVhwoRSPy8uLlZYWJj+85//lHk1f506dTz/X97V7UVFRWXe9/TqCkl68MEHdf/99+vGG2/UjBkz1KBBA4WHh2vs2LE+bU5ZmZIqi6lTp5ZZZVHyGC+//LLi4+NL/bxGDd/eVj179lRGRoZ+/fVXbdiwQZMnT9Y555yjevXq6fPPP9fWrVtVp04dnXvuuVV+LmX9/kpcffXVevHFF/Xqq6/qr3/9a5UfQyr/73r645f87m644QYNHz68zPuU7N9hZ+VVtRiVbG4KALCfivraspy+WXRxcbEuu+wy3XPPPWUe/4c//KHcc4WFhenNN9/U2rVr9e677+qDDz7QjTfeqMcff1xr1671GoNVRUXjtmApr08FAMDpLrjgAnXr1k2SlJaWpp49e+q6667T9u3bPf+2vvvuu5Wamlrm/Vu3bi1J6tWrlzIzM/XOO+/oww8/1D//+U/94x//0Lx583TTTTdVu52+jhcyMzN16aWXql27dpo9e7aaNWumyMhILV++XP/4xz8CMp8DwBkILOCTSZMm6ZVXXtHDDz9c6mdJSUkyDEMtW7as8B/V0skr4o4cOVLq9t27d3stc1SRN998U3369NELL7zgdfuRI0d82jDaF2PHjtWcOXM0bdq0UhuGl1xh0KhRI8/Vj+WpaPmhiy++WAsXLtSSJUtUVFSkHj16KDw8XD179vQEFj169PD8Qz0uLk61atXS9u3bS51r27ZtCg8PV7NmzXx+jo8++qhq1KihW2+9VTExMbruuut8vu/333/vVT2xY8cOFRcXKzExscL7xcXFKSYmRkVFRZX+7lq0aKHNmzfLMAyv32NZz/90SUlJ+uCDD3T48OEKqyx8XR6qRYsWnsc+9XVaWFionTt3VvpcAADuU9aYp7CwsNQSm0lJScrLy6tWX3LhhRfqwgsv1AMPPKDFixfr+uuv15IlS3TTTTepRYsW+uijj3T06FGvKott27ZJ+r2PK+85SCfHWKeOh8qqyqhKn/rHP/7R62fbt2+vsD0AALhVRESEZs2apT59+ujpp5/WjTfeKEk644wzfBpDNGjQQOnp6UpPT1deXp569eqlqVOnlhtYtGjRQsXFxcrMzPSqqijr3+MVzfOc6t1331VBQYGWLVum5s2be26vzjLiAJyJJaHgk6SkJN1www167rnnlJWV5fWzP//5z4qIiNC0adNKXUFuGIZ+/vlnr/OsXbtWhYWFntvee++9UksZVSQiIqLU47zxxhue9RkDoaTK4p133tGmTZu8fpaamqrY2Fg9+OCDZa4XffDgQc//165dW5LK7LxLlnp6+OGH1alTJ9WtW9dze0ZGhtavX+85Rjr5vPv27at33nnHa+ml7OxsLV68WD179vRraaewsDDNnz9f11xzjYYPH65ly5b5fN+5c+d6ff/UU09Jkvr371/h/SIiInT11Vfr3//+tzZv3lzq56f+7i6//HLt27dPb775pue2Y8eOaf78+ZW27+qrr5ZhGJo2bVqpn5362qldu3aZf5vTpaSkKDIyUk8++aTX/V944QXl5ORowIABlZ4DAOAuSUlJpfafmD9/fqmrDQcNGqQ1a9bogw8+KHWOI0eO6MSJE+U+xi+//FJqTNSlSxdJ8iwLdfnll6uoqEhPP/2013H/+Mc/FBYWVmHfXXKRxqnPIz8/Xy+++GKpY33tU7t166ZGjRpp3rx5XktX/ec//9HWrVvpUwEAKMcll1yiCy64QHPmzFFsbKwuueQSPffcc2XuN3rqv61PnZORTq6C0bp1a69++HQl44Mnn3zS6/Y5c+aUOjYpKUk5OTley0zt379fb7/9ttdxJRdjnjp2ycnJ0cKFC8ttBwB3osICPvv73/+ul19+Wdu3b9fZZ5/tuT0pKUkzZ87UxIkTtWvXLqWlpSkmJkY7d+7U22+/rZtvvll33323JOmmm27Sm2++qX79+mnQoEHKzMzUK6+8UmpdxIr86U9/0vTp05Wenq4ePXro22+/1auvvupzhYav7rjjDv3jH//QN9984wkeJCk2NlbPPvushg4dqvPOO0+DBw9WXFyc9uzZo/fff18XXXSRZ1Kga9eukk5uVJWamqqIiAgNHjxY0snyzPj4eG3fvt2zabV0slzz3nvvlSSvwEKSZs6cqZUrV6pnz5669dZbVaNGDT333HMqKCjQI4884vdzDA8P1yuvvKK0tDQNGjRIy5cvL3W1Y1l27typK664Qv369dOaNWv0yiuv6LrrrlPnzp0rve9DDz2kTz75RMnJyRo1apQ6dOigw4cPa+PGjfroo490+PBhSSc3tH766ac1bNgwbdiwQU2aNNHLL7+sWrVqVfoYffr00dChQ/Xkk0/q+++/V79+/VRcXKzPP/9cffr00ZgxYySd/Pt89NFHmj17thISEtSyZUslJyeXOl9cXJwmTpyoadOmqV+/frriiiu0fft2PfPMMzr//PO9NtgGAEA6Oeb529/+pquvvlqXXXaZvvnmG33wwQelqkHHjx+vZcuW6U9/+pNGjBihrl27Kj8/X99++63efPNN7dq1q9wK0hdffFHPPPOMrrrqKiUlJeno0aN6/vnnFRsbq8svv1zSyT2r+vTpo7///e/atWuXOnfurA8//FDvvPOOxo4dW+EYrG/fvmrevLlGjhyp8ePHKyIiQgsWLPCMe07VtWtXPfvss5o5c6Zat26tRo0alTmmOOOMM/Twww8rPT1dvXv31pAhQ5Sdna0nnnhCiYmJuvPOO/39VQMA4Brjx4/XX/7yFy1atEhz585Vz5491bFjR40aNUqtWrVSdna21qxZox9//FHffPONJKlDhw665JJL1LVrVzVo0EDr16/Xm2++6fl3cVm6dOmiIUOG6JlnnlFOTo569OihjIwM7dixo9SxgwcP1r333qurrrpKt99+u44dO6Znn31Wf/jDH7Rx40bPcX379lVkZKQGDhyov/71r8rLy9Pzzz+vRo0alRm6AHAxAzjNwoULDUnGf//731I/Gz58uCHJOPvss0v97N///rfRs2dPo3bt2kbt2rWNdu3aGaNHjza2b9/uddzjjz9uNG3a1IiKijIuuugiY/369Ubv3r2N3r17e4755JNPDEnGG2+8Uepxjh8/btx1111GkyZNjJo1axoXXXSRsWbNmlLn2LlzpyHJWLhwYYXPt6LHmjJliiHJqF27dpn3S01NNerWrWtER0cbSUlJxogRI4z169d7jjlx4oRx2223GXFxcUZYWJhx+lvuL3/5iyHJeP311z23FRYWGrVq1TIiIyONX3/9tdTjbty40UhNTTXq1Klj1KpVy+jTp4+xevVqr2Mq+huWPKeDBw96bjt27JjRu3dvo06dOsbatWvL/V2V3Pe7774zrrnmGiMmJsaoX7++MWbMmFJtlWSMHj26zPNkZ2cbo0ePNpo1a2acccYZRnx8vHHppZca8+fP9zpu9+7dxhVXXGHUqlXLaNiwoXHHHXcYK1asMCQZn3zyiee44cOHGy1atPC674kTJ4xHH33UaNeunREZGWnExcUZ/fv3NzZs2OA5Ztu2bUavXr2MmjVrGpKM4cOHe/3+du7c6XXOp59+2mjXrp1xxhlnGI0bNzZuueUW45dffvE6pnfv3mW+P8pqIwDAPkaPHl2qHy/vM98wDKOoqMi49957jYYNGxq1atUyUlNTjR07dhgtWrTw9Dcljh49akycONFo3bq1ERkZaTRs2NDo0aOH8dhjjxmFhYXltmnjxo3GkCFDjObNmxtRUVFGo0aNjD/96U9eY5GS8995551GQkKCccYZZxht2rQxHn30UaO4uNjruLLatmHDBiM5OdmIjIw0mjdvbsyePbvMfjIrK8sYMGCAERMTY0jyjMlKxlmn9tuGYRivv/66ce655xpRUVFGgwYNjOuvv9748ccfvY4ZPnx4mWOwkvEIAABOVNG/54uKioykpCQjKSnJOHHihJGZmWkMGzbMiI+PN8444wyjadOmxp/+9CfjzTff9Nxn5syZxgUXXGDUq1fPqFmzptGuXTvjgQce8BpjlNW3/vrrr8btt99unHnmmUbt2rWNgQMHGnv37jUkGVOmTPE69sMPPzTOOeccIzIy0mjbtq3xyiuvlHnOZcuWGZ06dTKio6ONxMRE4+GHHzYWLFhQalxx+vwOAHcJMwx2gQXgm6lTp2ratGk6ePBgwPYLAQAAAAAAAACJPSwAAAAAAAAAAIAFEFgAAAAAAAAAAICQI7AAAAAAAAAAAAAhZ2pg8dlnn2ngwIFKSEhQWFiYli5dWul9Vq1apfPOO09RUVFq3bq1Fi1aVOqYuXPnKjExUdHR0UpOTta6desC33gApUydOlWGYbB/BVBNs2bN0vnnn6+YmBg1atRIaWlp2r59u8/3X7JkicLCwpSWlmZeI0OAcQMAAN6qOmZ444031K5dO0VHR6tjx45avnx5EFobPIwZAAAoW1X7svLmGUaMGKGwsDCvr379+pnQ8t+ZGljk5+erc+fOmjt3rk/H79y5UwMGDFCfPn20adMmjR07VjfddJM++OADzzGvv/66xo0bpylTpmjjxo3q3LmzUlNTdeDAAbOeBgAAAfXpp59q9OjRWrt2rVauXKnffvtNffv2VX5+fqX33bVrl+6++25dfPHFQWhpcDFuAADAW1XGDKtXr9aQIUM0cuRIff3110pLS1NaWpo2b94cxJabizEDAAClVbUvq2yeoV+/ftq/f7/n67XXXjOj+R5hhmEYpj5CyQOFhentt9+u8GrQe++9V++//77XQGrw4ME6cuSIVqxYIUlKTk7W+eefr6efflqSVFxcrGbNmum2227ThAkTTH0OAACY4eDBg2rUqJE+/fRT9erVq9zjioqK1KtXL9144436/PPPdeTIEZ+uKLQjxg0AAJTmy5jh2muvVX5+vt577z3PbRdeeKG6dOmiefPmBaupQcOYAQCAk6rSl1U2zzBixIigzz3UCNoj+WDNmjVKSUnxui01NVVjx46VJBUWFmrDhg2aOHGi5+fh4eFKSUnRmjVryj1vQUGBCgoKPN8XFxfr8OHDOvPMMxUWFhbYJwEA8IthGDp69KgSEhIUHh74wr/jx4+rsLAw4Oc9nWEYpfqUqKgoRUVFVXrfnJwcSVKDBg0qPG769Olq1KiRRo4cqc8//7zqjXUIxg0A4D5mjhucMmZYs2aNxo0b53VbamqqYy9y8AVjBgBwH7fNNVS1L/NlnmHVqlVq1KiR6tevrz/+8Y+aOXOmzjzzzGo8q4pZKrDIyspS48aNvW5r3LixcnNz9euvv+qXX35RUVFRmcds27at3PPOmjVL06ZNM6XNAIDA2Lt3r84666yAnvP48eNq3ry2Dh4sDuh5y1KnTh3l5eV53TZlyhRNnTq1wvsVFxdr7Nixuuiii3TOOeeUe9wXX3yhF154QZs2bQpAa52BcQMAuFegxw1OGjOU1z9mZWVVuc12x5gBANzLrLmGZs1r65CFxg2HDh3yuy/zZZ6hX79++vOf/6yWLVsqMzNT9913n/r37681a9YoIiKiSs+pMpYKLMwyceJErytMcnJy1Lx5c11y5lDVCI80/fEL2zY1/TGsLLdl5VcKOcXRZs6/iqawmfnpsdmaJxwKdRMq1afx/4W6CV7SYr4x7dx5ecW6JPmgYmJiAn7uwsJCHTxYrFVfNVKdOua9P/PyDF2SfEB79+5VbGys53ZfrpQcPXq0Nm/erC+++KLcY44ePaqhQ4fq+eefZ9P7IAjkuMGpYwAn9+1O7cud0H+XxQ59elVYbRwQKIEYT5g1bnDKmAHBVd6YIbn3BNWoER20dhxpbf68BgB7q7fDumPBmt/tN+W8J4oLtSp7oWlzDYcOFuuDtfGqXce8LaLz84qVemFWlcYNlfF1nmHw4MGe/+/YsaM6deqkpKQkrVq1Spdeemm121EWSwUW8fHxys7O9rotOztbsbGxqlmzpiIiIhQREVHmMfHx8eWet7zy2hrhkUEJLGp8f1CF7ZuZ/jhWFRHp3EmN09XLlo62cOZER4maB6NV0Ny6HZ0vfvzlLCWedTDUzajQ53kddVl8+VdzBVudGPM64BJmls3XqRNm8nM4eVVFbGys1yCiMmPGjNF7772nzz77rMIrPjIzM7Vr1y4NHDjw90csPvmYNWrU0Pbt25WUlFTFttuXHcYNxUGcrAgmJ/ftEdHO7MfDa5r/OR4KNWo787VotXFAoKwwuuma2I0BOZdZ4wa7jxmk8vvHivo+pwv6mKFGdFACi1/anhyXmHN9KwAnOXp2tOpvt+Zczm+dWqrm5p9MO7+Zcw2164QHZb7El3FDw4YN/erLqjrP0KpVKzVs2FA7duwwLbCw1L9cunfvroyMDK/bVq5cqe7du0uSIiMj1bVrV69jiouLlZGR4TkG1lM3s6DygxwkZndQ9rGHC6zMahfqJni8mXteqJvgKIZhaMyYMXr77bf18ccfq2XLlhUe365dO3377bfatGmT5+uKK65Qnz59tGnTJjVr5s5QnHEDgF0/xoW6CfATYwr/+DtmkCrvH93IaWOGX9pGesIKAPCVlT83fj3HmZXpweRvX1bVeYYff/xRP//8s5o0aWLaczG1wiIvL087duzwfL9z505t2rRJDRo0UPPmzTVx4kT99NNPeumllyRJf/vb3/T000/rnnvu0Y033qiPP/5Y//rXv/T+++97zjFu3DgNHz5c3bp10wUXXKA5c+YoPz9f6enpZj6VaovcutfVVRZ1MwuUk+TMK+DcKGpPpO2rLHb9GGf5KgvpZGhhlSss38w9L2BXRbrd6NGjtXjxYr3zzjuKiYnxrCldt25d1axZU5I0bNgwNW3aVLNmzVJ0dHSptarr1asnSRWuYW03Ths3uLnfB1B9VhoDIHT8HTNI0h133KHevXvr8ccf14ABA7RkyRKtX79e8+fPD9nzCDSnjRl8ZeXJRgD2UPI5YsVqi1/PaWpqpYUbVNaX+TvPkJeXp2nTpunqq69WfHy8MjMzdc8996h169ZKTU017XmYGlisX79effr08Xxfsrbj8OHDtWjRIu3fv1979uzx/Lxly5Z6//33deedd+qJJ57QWWedpX/+859ev4Brr71WBw8e1OTJk5WVlaUuXbpoxYoVpTYUAUIpZrfh+KWhCC3cidAiMJ599llJ0iWXXOJ1+8KFCzVixAhJ0p49exQebqlCSNMxbgDM44R+G87BeMJ3VRkz9OjRQ4sXL9akSZN03333qU2bNlq6dKmjLnJw45iBsAJAIP3SNpLQwoEq68v8nWeIiIjQ//73P7344os6cuSIEhIS1LdvX82YMSMg+2iUJ8wwDNetX5Obm6u6desqJW5kUPawOJXbr7Z0W5WF00MLSY6Y/LBDaGG1KywDOcmQd7RY3c7OVk5Ojl9rOfui5PN+/ZbGpq4raeZzQOhVddzg5D7fyf25k/tuJ/TZ5bFDX15VVhsDBFJVxhNm9bmMGRAIJa+jiy6dGrA9LAgqAJjJiqGFpICEFieKC/XR/udMnWv4YnOC6eOGnufsc924wV2XbgJB5ob9LKL22H8AbYf1r620nwUAAAAAc7FPBYBgsOrnDHtauBuBBYLKbRtwA4FkpdCCDTOBijm5ugJAcFmp/w80xhNA2aw6gQjAmawakBJauJepe1igNLdvvu1G7GdhD+xn4T/WnwYAWAX9uH0xngB+Z8UJQ6AsR5OKg/p4MZlcbx0MVtzXgj0t3InAAkFXN7PA0Wtfl4XQwh7sMNmxMqudpdayZpIBAOzDCX21W1mt/wcQeIQVCLVghxD+8KVthBqBQWgBK+DdHAKRW/eGugmAKdjPIjicvDQEAOtz20UHsA879OEoG0tDwc2suhQLnOdoUnGFX3bn1OcVClb8TGJ5KHchsEBIuHEvCzdswC05I7SwAyuFFkwyAN5Y+hGAGazU95uB8QTcyIqTgrA/Ju698buoGj6fEEoEFkAQuSW0sDuu0PQfkwwAAACA75gMRHURTFQdvzPfWK0CjCoL9yCwCBGWhXJnlYXkjtDCCVUWdggtrHalJaEFAFifE/roitih/64Oq/X9gcZYAm5hpQlAWB/BhPn43VbMSp9ZhBbuQGABwBROmBCxw6SH1SYumGgAAADVwVgCTma1q5VhLQQT1sHvvzQrfXYRWjgfgUUIUWVBlYXTOSG0sAOrhRaAm7F/hf25pY+GfdHvA/Zkpck+hB7BhH3wN/qdlT7HCC2cjcACIUdoASuzQ5WF1XBlJAAglOi77Y+xBJzGSpN8CD7CCefgb2itzzNCC+cisAgxqizgdE6osrDDxIfVrrZkogEAAPNYrd83A2MJOIWVJvdgLpZ0chc3/32t9LlGaOFMBBawBKosnI3QIjisNnnBRAMAWJMT+uXK2KHfBuB8VprUQ2ARTKCEW18DVvp8I7RwHgILIMQILezDDpMfVgstAACAOdzQ53PxA+zMSpN5qB7CCfjKba8PK33OEVo4C4GFBbAs1ElurbKQCC3gXEw0wE3YcBtAsBFaANZ0pDX/7rEjlnRCoLjptUNoATMQWACAH6iy8B8TDQCAULBDnw3fMJYAEGgEEwgGt7y2rBRawBkILCyCKouTqLJwPidUWdhhAoTQAoAZcpKiQt0EBIgT+mOcZLU+HwCshnACoeaG151VQguqLJyBwAKwEEIL+yC0AADA+uzQX8M3XPwAoDIs6QSrc/prktACgUJgActxc5WFmzghtIB/mGiAk7F/BYBQcstFCowlAJQgmICdOfk1S2iBQCCwsBCWhYLknioLJ7DDVZtWm8BgogEAAFTH0qOdQ90EAEFGOAGncurr2TKhRYcmoW4CqojAApbk9ioLt4QWTqiyILTwH6EFAFiDE/phX9ihrw4Eq/X3AFAVhBNwIye+zq0SWsCeCCwshiqL3xFaEFrYhR0mQpjEAMzDclAArIL+HoDdEE4AJznxPUBogaoisAAQck4ILeAfqiwAWJlbLhpwEztcXAAATkf1BFA53hsAgQUsjioLJkzswg4TIVa76pLQAgCAwLNafw/AvQgngKpzynuGKgtUBYGFBbEsFE7lltDCCVUWhBb+I7QAgNByQv8LALAOAgogcJzyXiK0gL8ILGB5bq+ykAgtEFhWCy0AO2P/CsA+7HBhQaDQ1wMIFqooAPM54b1FaAF/EFhYFFUWcCu7hxZumgwJlKVHO4e6CQAAAAB8REABBJ8T3m+EFvAVgQVsgSoL91RZSIQWwcCVlwD8lZMUFeomANVmhz46UOjrAQQSIQUQek54DxJawBcEFrANQgt3hRZ2Z4cJESYyAACS/S8UQPno6wFUByEFYE28J+F0BBYWxrJQcDMmTwBYHftXAAAApyGkAOzBzu9RqixQGQIL2ApVFu6qsrB7aEGVBQAA1mOH/jmQ6OsB+IKQArAfO79vCS1QEQILi6PKAmUhtLAPO0yKMJEBAAAAuJOdJzwBnGTX9zChBcpDYAHbocriJDeFFnZHaAEAsDq7XyDgLzv0zYFEPw/gVCz7BDiPXd/PhBYoC4EFAMtz2yQKAOtj/woAdkNoAYCQAnA23t9wCgILG2BZqNKosjjJTVUWdg8t7HAlJxMZAAA3sUPfDACBQFABuIcd3+tUWeB0BBaAzRFa2IcdJkYILQDgJDf1r3AP+nnAXQgqAHey43uf0AKnIrCAbVFl8TsmVezDDqEFgIqxHBScyu4XBlSFG/tlQgvAHew2WQkg8Oz2OUBogRIEFjbBslBlI7RwHzdOpgQbExkATpeTFBXqJgAAAB/Y8cpqAObh8wB2RGABOISbqizsHlrY4WpOQgsAAJyLfh5wHoIKAOWx02cDVRaQCCxshSqLslFl8TtCC/sgtAAAwBrs0CcDQHkIKgD4wk6fE4QWILAAHMZNoQUABBv7V8Dp7H5BAHzHhQmA/dlpAhJA6PGZAbsgsIAjUGXhTnafVLHDFZ1MZgAA3MAOfbIZ6OcBe6KqAkBV2eWzgyoLdyOwsBmWhSofocXv3FRlQWhhPiYzAAAAAGuwy2QjAOuyy+cIoYV7EVgADkVoYR92CC0ASIVtm4a6CQBM5Nb+mAsTAPuwyyQjAOvj8wRWRmBhQ1RZlI8qC29uCi1gLiYzAMA97H4hAPxHPw9YG0tAAXArqizcicACgCPYfXLFDld1MpkBAHA6O/THANyFoAKAWezy+UJo4T4EFnAcqiy8uanKgtDCfIQWAAA4E308YD12mUwEYF98zsCKCCxsimWh4A9CCwBAVeUkRYW6CSHjpv7zdG7uT+1wAYFZCC0Aa2AJKADBZIfPG6os3IXAAo5ElQXsyg6TJExmAAAAAOaww8QhAOfhswdWQmBhY1RZVIzQwpubrhK1+1WhhBYAAISWHfpis9DHA6HDhCGAULL6ZxBVFu5RI9QNABA8MbsNHW0RFupmBEXUnkgVNC8MdTMAAABsZ2VWO10Wvy3UzQBcxeoThXC3Oi1zQt0ESVLezrqhboLjHU0qVkymda9v/6VtpOpvZ67H6Qgs4Gh1MwtcvfZ2WQgt7GHXj3FKPOtgqJtRISYzAMDZ7NyPBoId+mIAzkBYgVCzSiBRmYraSZgBOId1IzP4hGWhAOeyw3IULBsBAIAz0ccDwUFYgWCp0zKn3C8ncOJzChWrfy6xNJTzEVjA8djLojT2s7APO4QWAAA4ldv7YUILwFxWnxSEPTk5lPCH259/dfH5hFAKSmAxd+5cJSYmKjo6WsnJyVq3bl25x15yySUKCwsr9TVgwADPMSNGjCj18379+gXjqcCmCC1KI7RAoDCZ4b9Zs2bp/PPPV0xMjBo1aqS0tDRt37690vu98cYbateunaKjo9WxY0ctX748CK0NLsYMgLXQhwKh99lnn2ngwIFKSEhQWFiYli5dWul9CgoK9Pe//10tWrRQVFSUEhMTtWDBAvMbG0R2HzMwGYjqIpjwD78j/1n5c4oqC2czPbB4/fXXNW7cOE2ZMkUbN25U586dlZqaqgMHDpR5/FtvvaX9+/d7vjZv3qyIiAj95S9/8TquX79+Xse99tprZj8Vy2JZKFSVm0ILO7PD1Z2EFv759NNPNXr0aK1du1YrV67Ub7/9pr59+yo/P7/c+6xevVpDhgzRyJEj9fXXXystLU1paWnavHlzEFtuLsYMAKzIDv2wmejjQy8/P1+dO3fW3Llzfb7PoEGDlJGRoRdeeEHbt2/Xa6+9prZt25rYyuCy+5jBypOAsCaCicDi9whYm+mbbs+ePVujRo1Senq6JGnevHl6//33tWDBAk2YMKHU8Q0aNPD6fsmSJapVq1apgURUVJTi4+PNazgchw243c3uG4ey8aezrFixwuv7RYsWqVGjRtqwYYN69epV5n2eeOIJ9evXT+PHj5ckzZgxQytXrtTTTz+tefPmmd7mYGDMYD30mwCkk6HFZfHbQt0M1+rfv7/69+/v8/ErVqzQp59+qh9++MHTVyYmJprUutCw85iBsAKVYRI9uE79fbNxd2lHk4oVk2nNHQV+aRup+tvtO8+D8pn6iissLNSGDRuUkpLy+wOGhyslJUVr1qzx6RwvvPCCBg8erNq1a3vdvmrVKjVq1Eht27bVLbfcop9//jmgbbcbqixQVW6qsmBZC3NxBWbV5eScHCSf/o/pU61Zs8arP5Wk1NRUn/tTq2PMAMDK3F5lIdHP28myZcvUrVs3PfLII2ratKn+8Ic/6O6779avv/4a6qYFhJ3HDIQVOB2VE9bC36BsfHYh2EytsDh06JCKiorUuHFjr9sbN26sbdsqv0Jn3bp12rx5s1544QWv2/v166c///nPatmypTIzM3Xfffepf//+WrNmjSIiIkqdp6CgQAUFv+9hkJubW8VnBLujyqJsMbsNHW0RFupmBIWdKy3sUGXh9iswT+9foqKiFBVV8WdOcXGxxo4dq4suukjnnHNOucdlZWWV2Z9mZWVVvcEWYpUxg8S4Ad7c1EeWx859J2BVVRkz+OqHH37QF198oejoaL399ts6dOiQbr31Vv38889auHBhQB4jlOw6ZmDCD0yE2wdVF6VZtdKCKgtnMn1JqOp44YUX1LFjR11wwQVetw8ePNjz/x07dlSnTp2UlJSkVatW6dJLLy11nlmzZmnatGmmtxf2QGhRNiZk7MEOoYUVLT3aWdHGGaad/3jeb5I+VLNmzbxunzJliqZOnVrhfUePHq3Nmzfriy++MK19bhCoMYPEuAFA2eiD3XFhgpXHDL4qLi5WWFiYXn31VdWte3Kibfbs2brmmmv0zDPPqGbNmgF5HLsKxZiBsMJ9CCeco+RvSXABBI+p0VjDhg0VERGh7Oxsr9uzs7MrXRcyPz9fS5Ys0ciRIyt9nFatWqlhw4basWNHmT+fOHGicnJyPF979zpz+SSWhQJ8w9JQ5nLzkhF79+716m8mTpxY4fFjxozRe++9p08++URnnXVWhcfGx8dXqT+1C6uMGST3jBsAoCrc3M8Hkr9jBn80adJETZs29YQVktS+fXsZhqEff/wxYI8TKnYbMxBWOB/LOrkDf1vrfp790pY5HqcxNbCIjIxU165dlZGR4bmtuLhYGRkZ6t69e4X3feONN1RQUKAbbrih0sf58ccf9fPPP6tJkyZl/jwqKkqxsbFeX3C3upkFlR/kQuxnYQ92WEfbrZMZp/c15S3tYBiGxowZo7ffflsff/yxWrZsWem5u3fv7tWfStLKlSsr7U/twipjBolxA1AWO/ebgWSHPhj24OuYoSouuugi7du3T3l5eZ7b/u///k/h4eGVXiBhB3YaM1h1cg9VRzgBt//d+VxDMJi++Ni4ceP0/PPP68UXX9TWrVt1yy23KD8/X+np6ZKkYcOGlXk1yQsvvKC0tDSdeeaZXrfn5eVp/PjxWrt2rXbt2qWMjAxdeeWVat26tVJTU81+OpZHlQWqi9DCHpgwsbfRo0frlVde0eLFixUTE6OsrCxlZWV5bYZ5ev94xx13aMWKFXr88ce1bds2TZ06VevXr9eYMWNC8RRMwZgBAOzBrRcmhEpeXp42bdqkTZs2SZJ27typTZs2ac+ePZJOXuU/bNgwz/HXXXedzjzzTKWnp+u7777TZ599pvHjx+vGG290zHJQdhgzMKlnf4QTqAivB2uhysJZTN/D4tprr9XBgwc1efJkZWVlqUuXLlqxYoVng6w9e/YoPNw7N9m+fbu++OILffjhh6XOFxERof/973968cUXdeTIESUkJKhv376aMWNGQK9KgfOxl0X52M8CgeCGda6r6tlnn5UkXXLJJV63L1y4UCNGjJBUun/s0aOHFi9erEmTJum+++5TmzZttHTp0go36rYbxgwA7IC9LE6inw+e9evXq0+fPp7vx40bJ0kaPny4Fi1apP3793vCC0mqU6eOVq5cqdtuu03dunXTmWeeqUGDBmnmzJlBb7tZrD5myGtVbP7VoQgoJp9RFW7d38KqG3DDOcIMw3DP5dT/X25ururWrauUuJGqEe68BK6wfbPKD4IHoUXZ3BRYFDQvDHUTqswOEyaVTWYcz/tNMy/8UDk5OQFfeqfk837S2r6KrmPuBppmPQeEXsnrqFfPyapRIzrUzQkq+siT3NQnVsbOfWYg2aH/DZZghxZm9bmMGRAIJa+jFg/PVHi0u8YMdkNAATO4LbiwYmhRf/vvY9UTJ47ry4ypps41fLE5QXVizPs95B0tVs9z9vn1HObOnatHH31UWVlZ6ty5s5566ildcMEFZR771ltv6cEHH9SOHTv022+/qU2bNrrrrrs0dOhQzzGGYWjKlCl6/vnndeTIEV100UV69tln1aZNm4A8x7JY75WFamNZKAQCS0PZA0tDATALYQVQPvpfALAPlnZCsPDaQqi9/vrrGjdunKZMmaKNGzeqc+fOSk1N1YEDB8o8vkGDBvr73/+uNWvW6H//+5/S09OVnp6uDz74wHPMI488oieffFLz5s3TV199pdq1ays1NVXHjx837XkQWMD12IC7fG4KLezM6pMmrHMNAIBz0c8DsBrCCYSSm153Vtyrx+17WcyePVujRo1Senq6OnTooHnz5qlWrVpasGBBmcdfcskluuqqq9S+fXslJSXpjjvuUKdOnfTFF19IOlldMWfOHE2aNElXXnmlOnXqpJdeekn79u3T0qVLTXseBBaACC0q4pbQws5VFnbAZAYAOAP95e+sfsFAMNHPAwgVqidgVbwWEUi5ubleXwUFpecxCwsLtWHDBqWkpHhuCw8PV0pKitasWVPpYxiGoYyMDG3fvl29evWSJO3cuVNZWVle56xbt66Sk5N9OmdVmb7pNkIjcute9rIA/BS1J9K2a3OzASgAmCdmt8E+FkAl2IQbQDAwCQw7qdMyx/H7WlhxA+5f2kZ67WVhpiVHkhV1wry9rwryfpP0tpo1857jnTJliqZOnep126FDh1RUVKTGjRt73d64cWNt21b+GC0nJ0dNmzZVQUGBIiIi9Mwzz+iyyy6TJGVlZXnOcfo5S35mBgIL4P+rm1nAet3lcNNEDaGFeZjIAAA4jdX7XgCwOwIK2F3Ja9jJwYUVQwun2bt3r9em21FRgZu/jImJ0aZNm5SXl6eMjAyNGzdOrVq10iWXXBKwx/AXryYHY/NtBJJbloaCuVgyAgDsj2WhUB76eQDVxfJOcCpez6iO2NhYr6+yAouGDRsqIiJC2dnZXrdnZ2crPj6+3HOHh4erdevW6tKli+666y5dc801mjVrliR57ufvOauLwAI4BXtZQLL3RAzraQMAEFz0vd4ILQD4i4ACbuHk17jVNuB24+bbkZGR6tq1qzIyMjy3FRcXKyMjQ927d/f5PMXFxZ49Mlq2bKn4+Hivc+bm5uqrr77y65z+IrAATkNoUT43VVkQWpiHiQwAAJyNvh5ARaiigJvxmoeZxo0bp+eff14vvviitm7dqltuuUX5+flKT0+XJA0bNkwTJ070HD9r1iytXLlSP/zwg7Zu3arHH39cL7/8sm644QZJUlhYmMaOHauZM2dq2bJl+vbbbzVs2DAlJCQoLS3NtOfBHhYOx+bbCDQ37WcB87CfBWBt7OmEyth5zyczsJdFafT1AE7FJC3wO6fua2G1vSyOtI6UMio/zkmuvfZaHTx4UJMnT1ZWVpa6dOmiFStWeDbN3rNnj8LDf/8b5efn69Zbb9WPP/6omjVrql27dnrllVd07bXXeo655557lJ+fr5tvvllHjhxRz549tWLFCkVHR5v2PAgsgDKwAXfF3BJa2HkyhokTAACCi74XALwRUgAVq9Myx3GhBUJvzJgxGjNmTJk/W7Vqldf3M2fO1MyZMys8X1hYmKZPn67p06cHqomVsk7sBdOw+TZQdSwNZR6WiwAAwNno6wH3YaknwD9Oe69YbS8L2BOBBVAO9rKoGPtZIBCYyAAA+6J/LM3qFwuEAn094A6EFEDV8d4BvBFYABUgtKiYm0ILu2LiBAAAhBqhBeBMVFMAgeOk9xFVFqguAguXYFkomMUtoYWdryK1emjxSfYfQt0EAKiUW/o7VJ/V+91QIbQAnIOQAjAH7yvgJAILoBJUWaCEnUMLAADMQN8IAO5BUAGYzynvMaosUB0EFi5ClUXVEVpUjKtOrY+rPQEACB763bJRZQHYE0EFEFy83+B2BBYAAsItoQVXkgJwupykqFA3AXAEQouyEVoA9kFQAYSOE957VFmgqggsAB9RZVE5QgtrY+IEAGAGu/aLCB1CC8DaCCoAa+B9CLcisHAZloWqHkIL2B2hBQAAwUO/Wz5CC8B6CCoABBpVFqgKAgsAAUWVBQAAAHxBaAFYA0EFYF28N+FGBBYuRJVF9VBlUTlCC2vjak8AQKDZtU8MBvpdAFZFUAHYA+9TuA2BBQBTEFpYG5MnAAAED/1u+aiyAEKDCVDAXuz8nmVZKPiLwAKoAqosAABwH7eE8UCwEVoAwUNVBWBfvHfhFgQWLsWyUNVHaFE5t0zsUGUBwClykqJC3QTYmF37w2Ch360YoQVgPiY7Afuz6/uYKgv4g8ACgKkILayNyRMAAIKHfrdihBaAOaiqAADYCYGFi1FlUX1UWQAAAPzOrgE+rIPQAggsggrAeez6vqbKAr4isACqidCiclRZWBtXewIAEDz0u5UjtACqj6oKwNl4f8PJCCwABAWhhbUxeQIAAKyE0AKoOiYyAQB2RmDhciwLFRhUWfjGLaEFAABuZtfwPpi4UACAWQgrAPew4/udZaHgCwILIEAILVDCrhM1TJ4AABA89LuVo8oC8I8dJy8BVA/vezgRgQWoskBQuaXKgtACgN3kJEWFugm24JZ+DLAKQgugcuxXAbgb7384DYEFEEBUWfiGyR4AAJzNrsF9sHGhgG8ILYDyMVEJwG5YFgqVIbAAAozQwjduCC3sOlnD5AkAAMFDv+sbQgugNMIKACX4PICTEFhAEstCAWaxa2gBAEB10Qci0AgtgN8xOQnAzqiyQEUILAATUGXhGzdUWdgVV3sCABA89Lu++yT7D6FuAhByhBUAysJnA5yCwAIeVFkgFNwQWtj1ClMmTwAACB76XQC+YEISQEX4jIATEFgAJqHKAqeya2gBAEB10P8BQOAwEQnASVgWCuUhsIAXqiwCi9DCN26osrArrvYE3CEnKSrUTQAg+l0A5SOsAOArPi9gdwQWACzBDaGFXa8yZfIEALy5oc8KJLv2f6FCvwvgdEw+AgDchMACMBlVFr5zwwQQkzYAAAAAfEVYAaAq7PLZwbJQKAuBBUphWajAI7SA3XG1JwAAwUO/C0Cyz4QjAGviMwR2RWABwFKosgAAwHno+/xHaAG4GxONAAC3IrBAmaiyCDyqLHxHaGFNTJwAABBc9L2AOxFWAAgUPk9gRwQWQBARWsDumDgBnCcnKSrUTYBL2DGsB4BgY3IRgNuwjwVOR2CBclFlgVCiygIAAICLBQA3IawAYAY+W2A3BBZAkFFl4TtCC2ti4gQAUFV27PesgL4XcD4mFAEAOInAAggBQgvfuSG0sCMmTgC4Hf0Tgo2+FwAAVJXVQ1GWhcKpCCxQIZaFAszH1aYAADeh3wMAb1afSAQAIJgILIAQocrCd264itWOkzdc6QkAQHDR9wLOQ1gBIFj4vIFdEFigUlRZmIfQwnduCC0AAAAqQ2gBOAeThwAAlEZgAQAWQZUFgGDLSYoKdRPgUnbs86yE/hewP8IKAKFg5c8e9rFACQILIMSosvCdG6os7DiBw6QJAAAAAAAAAqFGqBsAe4jculeF7ZuFuhmOVTezgKtcfRSz29DRFmGhbgYAAKimqD2RKmheGOpm2NauH+OUeNbBUDcDQBVY+QpnuEPf5ttNO/eHe9qadm4A7kBgAcB2nB5a2HECh0kTAG7k9P4I1kf/C9gPYQUCzczwoSp8aQ+hRmjVaZmjvJ11Q90MoFwEFvAZVRbmosoCp7JjaAEAgL/o76qP0AKwD8IK+MtqYUSglPW8CDEgndzHIiaTHQzcLiivgLlz5yoxMVHR0dFKTk7WunXryj120aJFCgsL8/qKjo72OsYwDE2ePFlNmjRRzZo1lZKSou+//97spwGYjv0sfOeG/Szshr0sfPfZZ59p4MCBSkhIUFhYmJYuXVrpfQoKCvT3v/9dLVq0UFRUlBITE7VgwQLzGxtkjBmCh5AcAOzB33HDW2+9pcsuu0xxcXGKjY1V9+7d9cEHHwSnsUHEmAFO0Lf59gq/3MTNzz0UCFBhZaYHFq+//rrGjRunKVOmaOPGjercubNSU1N14MCBcu8TGxur/fv3e752797t9fNHHnlETz75pObNm6evvvpKtWvXVmpqqo4fP27203G9yK17Q90EwMPpoQUbcDtXfn6+OnfurLlz5/p8n0GDBikjI0MvvPCCtm/frtdee01t2zrrKiTGDIA72bG/sxr6X2fzd9zw2Wef6bLLLtPy5cu1YcMG9enTRwMHDtTXX39tckuDx45jBiYH3YtAomr4XQHuZfqSULNnz9aoUaOUnp4uSZo3b57ef/99LViwQBMmTCjzPmFhYYqPjy/zZ4ZhaM6cOZo0aZKuvPJKSdJLL72kxo0ba+nSpRo8eLA5TwQIEpaGwqlYKsOZ+vfvr/79+/t8/IoVK/Tpp5/qhx9+UIMGDSRJiYmJJrUudBgzAEDVsTSUc/k7bpgzZ47X9w8++KDeeecdvfvuuzr33HMD3LrQsNuYgbDCHZhUN9epv1+WjwoM9rKAVZlaYVFYWKgNGzYoJSXl9wcMD1dKSorWrFlT7v3y8vLUokULNWvWTFdeeaW2bNni+dnOnTuVlZXldc66desqOTm53HMWFBQoNzfX6wtVR5WF+VgayndOr7KwIzdf5Xl6X1NQEJj38rJly9StWzc98sgjatq0qf7whz/o7rvv1q+//hqQ81uBVcYMEuMGIBSosggMN/fBdmPWmKEsxcXFOnr0qOeiB7uz25iBsMJ5qJYIPX7nznY0qTjUTUCImVphcejQIRUVFalx48Zetzdu3Fjbtm0r8z5t27bVggUL1KlTJ+Xk5Oixxx5Tjx49tGXLFp111lnKysrynOP0c5b87HSzZs3StGnTAvCMAFhRzG5DR1uEhboZprFjlYXVrvL8JPsPqpFnXuXSifwCSR+qWbNmXrdPmTJFU6dOrfb5f/jhB33xxReKjo7W22+/rUOHDunWW2/Vzz//rIULF1b7/FZglTGDxLgBgL1ZrQ+2G7uPGcry2GOPKS8vT4MGDTLl/MHGmAHBwoS49VF1ATiT6UtC+at79+7q3r275/sePXqoffv2eu655zRjxowqnXPixIkaN26c5/vc3NxSA0TAalgaCrCfvXv3KjY21vN9VFRg3sPFxcUKCwvTq6++qrp1T5bszp49W9dcc42eeeYZ1axZMyCPYzdmjBkkxg3wj9ND82CyY0APVJVZY4bTLV68WNOmTdM777yjRo0amfIYdhCqMQPVFfZBOGF/JX9Dggv/sCwUrMjUwKJhw4aKiIhQdna21+3Z2dnlrh15ujPOOEPnnnuuduzYIUme+2VnZ6tJkyZe5+zSpUuZ54iKijJtAOhWkVv3qrA9kzdmI7TwndMnjOw4iePGKzxjY2O9Jh8CpUmTJmratKknrJCk9u3byzAM/fjjj2rTpk3AHzPYrDJmkNwxbqBvAZzNjX2w3Zg1ZjjVkiVLdNNNN+mNN97wWurI7uwyZiCssC7CCWcjuADsz9Q9LCIjI9W1a1dlZGR4bisuLlZGRobX1Q0VKSoq0rfffusZNLRs2VLx8fFe58zNzdVXX33l8zkBOJPT97NgfW/3uuiii7Rv3z7l5eV5bvu///s/hYeH66yzzgphywKHMQMAib4ukNjPwt1ee+01paen67XXXtOAAQNC3ZyAYswAf7HXhDvxt/adFQNW9rFwN9OXhBo3bpyGDx+ubt266YILLtCcOXOUn5+v9PR0SdKwYcPUtGlTzZo1S5I0ffp0XXjhhWrdurWOHDmiRx99VLt379ZNN90kSQoLC9PYsWM1c+ZMtWnTRi1bttT999+vhIQEpaWlmf10cAqqLIKDKgv/OL3Swm64wrNseXl5niv6pJMbPW7atEkNGjRQ8+bNNXHiRP3000966aWXJEnXXXedZsyYofT0dE2bNk2HDh3S+PHjdeONNzpqOSjGDAAQWPTDzuDvuGHx4sUaPny4nnjiCSUnJ3v2YKhZs6ZXtaadWX3MULtFriT+DRcqTFSjBNUWgD2ZHlhce+21OnjwoCZPnqysrCx16dJFK1as8GxmtWfPHoWH/17o8csvv2jUqFHKyspS/fr11bVrV61evVodOnTwHHPPPfcoPz9fN998s44cOaKePXtqxYoVio6ONvvpACFBaIESLA3lDOvXr1efPn0835esfTx8+HAtWrRI+/fv1549ezw/r1OnjlauXKnbbrtN3bp105lnnqlBgwZp5syZQW+7mRgzAJDs2ddZGf2w/fk7bpg/f75OnDih0aNHa/To0Z7bS453AsYMOBUBBSpDcAHYS5hhGM5eQ6UMubm5qlu3rlLiRqpGOGXn1UWVRXAQWPjH6VUWdpvIqWii5ER+gb688mnl5OQEfC3nks/7i94Zoxq1zXsPmfkcEHolr6NePSerRg1nTFrQpwSW0/ucULBbP2cHTgktzOpzGTMgEEpeRx2W3KOIWvS1ZiKkQFURWpTPaptvx2RWbyeDooLj2vLcfabONYz54ipF1TkjoOc+VUHeb3q659uuGzeYXmEBIDCosvAPS0NZC1d3AtZBXxJ49DmBR5UFAOB0hBQIBKotAOszddNtuEPk1r2hboJr1M0sCHUTYBFsSgoAAPzBJtwA7IjNsmEWXlPWx8bb7kVgAcCxYnY7e8U7u4UWTJQAAPxht37ODuiLAdgBIQWChdeYtzotc0LdBEASgQVgO1RZ+MfpoQUAAIA/CC0AWBEhBUKF1xxgPQQWCAiWhQouQguUsNvVp0ySAAD8Ybd+zi7ojwFYBSEFrIDXIGAtBBYAHI8qC2thkgQIHTbcBlCC/hhAKBFUwGp4TZ7EslCwAgILBAxVFsFFlYV/nBxacPUpAISek/uZUKOfMw+hBYBgYtkn2AGvTyD0CCwAGyO0QAm7TeYwQQIAgDXQJwMwGyEF7IbXq3UcTSoOdRMQAgQWCCiqLGBlXP0KAIA92S2YtxtCCwBmIKiAnbn5tcuyUPY2d+5cJSYmKjo6WsnJyVq3bl25x27ZskVXX321EhMTFRYWpjlz5pQ6ZurUqQoLC/P6ateunYnPgMACsD2qLPzj5NDCbpM5TI4AAGAd9MsAAoWgAk7B6xh28/rrr2vcuHGaMmWKNm7cqM6dOys1NVUHDhwo8/hjx46pVatWeuihhxQfH1/uec8++2zt37/f8/XFF1+Y9RQkEVjABFRZBB+hhX8ILayDyREgeNhwG3Zntz7OjuiXAVQHQQUAhNbs2bM1atQopaenq0OHDpo3b55q1aqlBQsWlHn8+eefr0cffVSDBw9WVFT5/16sUaOG4uPjPV8NGzY06ylIIrAAAAAAAABANRBUwKnc+tpmWShryc3N9foqKCh94XJhYaE2bNiglJQUz23h4eFKSUnRmjVrqvX433//vRISEtSqVStdf/312rNnT7XOV5kapp4drhW5da8K2zcLdTNcpW5mAVfP+iFmt6GjLcJC3QxTRO2JVEHzwlA3w2d79pmbzANAsDi5b7EKu/VxdrTrxzglnnUw1M0AYBNuncyFu/Rtvl0f7mkb6ma41tGkYsVkWvOa+49/bKOIWubNxRUdOxlMNGvmPcc6ZcoUTZ061eu2Q4cOqaioSI0bN/a6vXHjxtq2bVuV25CcnKxFixapbdu22r9/v6ZNm6aLL75YmzdvVkxMTJXPWxECC8BBCC38w8QSAAD2Q2hhPkILAJUhqIDbEFoglPbu3avY2FjP9xUt3xRo/fv39/x/p06dlJycrBYtWuhf//qXRo4cacpjWjOeAgBUC+t8AwCA6mA/CwDlIayAW/HaR6jExsZ6fZUVWDRs2FARERHKzs72uj07O7vCDbX9Va9ePf3hD3/Qjh07AnbO0xFYwDRsvh0abMDtHzbgBuAGVN/BaejjgoPQAsCp2FQbcFdowT4W9hIZGamuXbsqIyPDc1txcbEyMjLUvXv3gD1OXl6eMjMz1aRJk4Cd83QEFoADEVr4x8mhBQAAQHUQWgCQ3DVJCwB2NW7cOD3//PN68cUXtXXrVt1yyy3Kz89Xenq6JGnYsGGaOHGi5/jCwkJt2rRJmzZtUmFhoX766Sdt2rTJq3ri7rvv1qeffqpdu3Zp9erVuuqqqxQREaEhQ4aY9jzYwwKmYvNtILRY5xsAgov9kYKHPi542NMCcC+CCqA09rOAVV177bU6ePCgJk+erKysLHXp0kUrVqzwbMS9Z88ehYf/Xr+wb98+nXvuuZ7vH3vsMT322GPq3bu3Vq1aJUn68ccfNWTIEP3888+Ki4tTz549tXbtWsXFmXdRC4EF4FBswO0fJ08wMaEDAACqi9ACcB/CCqB8hBawqjFjxmjMmDFl/qwkhCiRmJgow6h41ZElS5YEqmk+Y0komI69LEKHpaH8w9JQAJyI8BpOxl4WwcXyUIB7EFYAkKyzj8XRpOJQNwFBRGABAC7AhA4AwKno44KL0AJwNjbWBnzHewUwB4EFgoIqi9ChysI/VFkAAABUjNACcCYmXwH/8b4BAo/AAnABQgv/ODW04ApUAIBT0ccFH6EF4CxMugIArILAAkFDlQUQekzoAID5nBp8Wx19XPARWgDOQFgBVI/T30NW2ccC7kFgAbgEVRb+YbIJgBOw4TYAs+36MY7gArAxp0+0AgDsh8ACQUWVRWgRWvjHqaEFV6ACAJyKPi50CC0A+yGsAAKH9xMQOAQWAAAAAIBqI7QA7KFv8+1MrgIm4H1lrqNJxaFuAoKEwAJBR5VFaFFl4R+qLAAAsBf6uNAitACsjQlVAFXBPhYIJgILwIUILfxDaAHAjti/IrSc2nfYBX1caBFaANZEWAGYj/cZUH0EFgAAAACAgCK0AKyFSVQAgF0QWCAkWBYq9Kiy8I9Tr5TlClQAgFPRx4UeoQVgDYQVQHDxngOqh8ACcDFCC/8QWgAAYC/0caFHaAGEFhOnAAC7IbBAyFBlAQCAOdi/AoCVEFoAoUFYAYSOE99/bLyNYCGwAFyOKgv/UGUBAPCVU/sMu6GPs4ZdP8YRXABB5MTJUgCAOxBYIKSosrAGQgv/MAEFAIC9EFpYB6EFAMAtCA4D72hScaibgCAgsAAASGIyBwDgbPRz1kFoAZiLSVIAgJ0RWCDkqLKwBqos/OPUKgsmcwD7Y/8KAHZAaAGYg7ACAGB3BBYAPAgt/OPU0AIAEDj0FdZCMG8thBZAYBFWANbjtPclG28jGAgsYAlUWQDWwWQOAMDJ6OeshdACCAynTYoCANyLwAKAF6os/MOVswCshOWgANjRrh/jCC6AaiCsAKyN9yjgHwILWAZVFtZBaOEfJ4YWXH0KAHAy+jlrIrQA/MdEKADAaQgsAJSJ0AJM5gAAnIx+zpoILQDfEVYAAJyIwAKWQpUF7MqJVRYAgMCgj7AuQgtrIrQAADiNkwJGNt6G2QgsAJSLKgv/OHFCiokcwD7YvwKAk7CvBVAxJ01+AoA/jiYVh7oJMBmBBSyHKgtrIbQAAABORjhvbYQWQGmEFQAAJyOwAIAAosoCAAD7oa+zNkIL4HeEFYB98f4FfENgAUuiysJaqLLwD6EFgGBjOSjrc2Lf4DT0ddbGElEAAADuQGABwCeEFgAAAAi1PfsahroJQMhwdTYAwA0ILGBZVFnAzpx4JS1XngIAnI6+DoBVEVYAzuCU93KdljmhbgIcjMACgM+osvCPE0MLAACcjtACgNU4ZYITAABfEFjA0qiysB5CC3djEgewHvavsA+CbPugvwMAAABCg8ACAEzE5BQAAPZEaAHACqiuAJyH9zVQMQILWB5VFtZDlYV/nBZaMIEDAAAAmI9JTQCAGxFYAKgSQgt3I7QArIHloABz0d8BCBXCCgCAWwUlsJg7d64SExMVHR2t5ORkrVu3rtxjn3/+eV188cWqX7++6tevr5SUlFLHjxgxQmFhYV5f/fr1M/tpIISosoDdOa3KAtXz2WefaeDAgUpISFBYWJiWLl1a4fFvvfWWLrvsMsXFxSk2Nlbdu3fXBx98EJzGBhljBjgd/YH9EFrACvzpHyVpzpw5atu2rWrWrKlmzZrpzjvv1PHjx4PU2uBgzAAA7nU0qTjUTYCJTA8sXn/9dY0bN05TpkzRxo0b1blzZ6WmpurAgQNlHr9q1SoNGTJEn3zyidasWaNmzZqpb9+++umnn7yO69evn/bv3+/5eu2118x+KgBOQ5WFuzGBU3X5+fnq3Lmz5s6d69Pxn332mS677DItX75cGzZsUJ8+fTRw4EB9/fXXJrc0uBgzALAq+jyEkr/94+LFizVhwgRNmTJFW7du1QsvvKDXX39d9913X5Bbbh6njxmorgCczwnv8zotc0LdBDiU6YHF7NmzNWrUKKWnp6tDhw6aN2+eatWqpQULFpR5/Kuvvqpbb71VXbp0Ubt27fTPf/5TxcXFysjI8DouKipK8fHxnq/69eub/VQQYlRZWBOhhe+4qhYl+vfvr5kzZ+qqq67y6fg5c+bonnvu0fnnn682bdrowQcfVJs2bfTuu++a3NLgYszgH5aDAoKL0AKh4m//uHr1al100UW67rrrlJiYqL59+2rIkCGVVmXYiZPHDE6YxAQAoDpMDSwKCwu1YcMGpaSk/P6A4eFKSUnRmjVrfDrHsWPH9Ntvv6lBgwZet69atUqNGjVS27Ztdcstt+jnn38OaNsBwAxOCy2YvAmN4uJiHT16tFTfaGeMGeAmTusL3IR+D8FWlf6xR48e2rBhgyeg+OGHH7R8+XJdfvnlQWmz2RgzAADgbDXMPPmhQ4dUVFSkxo0be93euHFjbdu2zadz3HvvvUpISPAajPTr109//vOf1bJlS2VmZuq+++5T//79tWbNGkVERJQ6R0FBgQoKfr8KPDc3t4rPCKEWuXWvCts3C3UzcJq6mQVc6etiUXsiVdC8MNTNsITT+5eoqChFRQX+vfHYY48pLy9PgwYNCvi5Q8UqYwaJcQOAitHvIRB8HTNUpX+87rrrdOjQIfXs2VOGYejEiRP629/+5pgloZw8ZqC6AgAAkwOL6nrooYe0ZMkSrVq1StHR0Z7bBw8e7Pn/jh07qlOnTkpKStKqVat06aWXljrPrFmzNG3atKC0GXArQgvfxew2dLRFWKib4Sp79jVUeM3oyg+souJfT25i2ayZd6A6ZcoUTZ06NaCPtXjxYk2bNk3vvPOOGjVqFNBz21mgxgySPcYNfN4CoUVo4VxOGDOsWrVKDz74oJ555hklJydrx44duuOOOzRjxgzdf//9AXkMO7PqmIGwAnCfvs2368M9bUPdDMByTF0SqmHDhoqIiFB2drbX7dnZ2YqPj6/wvo899pgeeughffjhh+rUqVOFx7Zq1UoNGzbUjh07yvz5xIkTlZOT4/nau5e9EOyMvSzgBE5bDoQlMk7au3evV38zceLEgJ5/yZIluummm/Svf/3L64pAJ7DKmEFi3AAAMJ+vY4aq9I/333+/hg4dqptuukkdO3bUVVddpQcffFCzZs1ScXFxwJ9LsDFmAADA2UwNLCIjI9W1a1evjaxKNrbq3r17ufd75JFHNGPGDK1YsULdunWr9HF+/PFH/fzzz2rSpEmZP4+KilJsbKzXF4DAYwNuuN3pfU0gl4N67bXXlJ6ertdee00DBgwI2HmtwipjBolxA4LDacG1GxHWozp8HTNUpX88duyYwsO9/6lfsqSRYdj/s8eJYwaqKwAA+J2pgYUkjRs3Ts8//7xefPFFbd26Vbfccovy8/OVnp4uSRo2bJjX1SQPP/yw7r//fi1YsECJiYnKyspSVlaW8vLyJEl5eXkaP3681q5dq127dikjI0NXXnmlWrdurdTUVLOfDiyCKgvrIrTwndMmq5i48V1eXp42bdqkTZs2SZJ27typTZs2ac+ePZJOXq03bNgwz/GLFy/WsGHD9Pjjjys5OdnTN+bk5ISi+aZhzOAbloMCrIO+D8Hgb/84cOBAPfvss1qyZIl27typlStX6v7779fAgQPL3YvBbpw0ZiCsAADAm+l7WFx77bU6ePCgJk+erKysLHXp0kUrVqzwbJC1Z88er6s/nn32WRUWFuqaa67xOk/Jmp4RERH63//+pxdffFFHjhxRQkKC+vbtqxkzZpiysSkAmMlp+1mwprdv1q9frz59+ni+HzdunCRp+PDhWrRokfbv3+8JLyRp/vz5OnHihEaPHq3Ro0d7bi853ikYMwCwI/o+mM3f/nHSpEkKCwvTpEmT9NNPPykuLk4DBw7UAw88EKqnEHCMGQA4hd33sajTMkd5O+uGuhlwmDDDCTWhfsrNzVXdunWVEjdSNcK5KsrOCts3q/wghARXAPvOSYGFJL8nbYp/Pa69t0xVTk5OwJfeKfm8b/bsVNM30DTrOSD0Sl5HvXpOVo0a5r2OfMXnq7M4rQ9wM0KL4DCrz2XMgEAoeR11WHKPImpV3l9TXQFAkq0DC0khCyxiMiteOKio4Li2PHefqXMNvn7eV1XRsQJ9N/gR140bTF8SCoA7sTSU71gaCoCvCCsA66L/A+APwgoAAMpGYAFbYy8LOIXTQgsAANyI0AIAAACoHgILAKahysK9mLABALgVfSCAylBdAQDVdzSpONRNgEkILGB7VFlYG6GF75xWZcGEDRBYLAflTE777MdJ9IEAykNYAeB0fC4A3ggsAMBCmLgCAMAZCC0AAAAA/xFYwBGosrA2qizci8kaIDCorgDsiX4QwKm4ihoAgMoRWAAICkIL31FlAQDuwue+sxFaAJAIKwAA8BWBBRyDKgvAmpioAQC4HX0hAAAA4BsCCwBBQ5WF77jaFkAJloMCnIHQAnAvqisAOFmdljmhbgIchsACjkKVhfURWvjOSaEFkzQAUDEnfeajfPSHgPsQVgDwBZ8VwO8ILAAAQcEkDeA/qisA56E/BAAAAMpHYAHHocrC+qiy8B1X3AIA4DyEFoA7cMU0AAD+I7AAEBKEFr5zUmjBBA0AlM9Jn/eoHH0i4GyEFQAAVA2BBRyJKgsAgN2xHBTgfFF7IgkuAAAAgFMQWAAIGaosfOekq26ZmAEAwBt9I+Asfzzr+1A3AQAA2yKwgGNRZWEPhBa+I7QA3IPqCvdy0mc9/EPfCAAAABBYALAAQgsAAABCCwAAAIDAAo5GlQWcxklX3jIpA5SN6go46bMe/qN/BADAnfo23x7qJsAB5s6dq8TEREVHRys5OVnr1q2r8Pg33nhD7dq1U3R0tDp27Kjly5d7/dwwDE2ePFlNmjRRzZo1lZKSou+/N3fpQwILAJZAlYXvmMgCAMDZCC0AAADgr9dff13jxo3TlClTtHHjRnXu3Fmpqak6cOBAmcevXr1aQ4YM0ciRI/X1118rLS1NaWlp2rx5s+eYRx55RE8++aTmzZunr776SrVr11ZqaqqOHz9u2vMgsIDjUWVhH4QW7sOEDAAAZYvaE0k/CQAAUIGjScWhboKlzJ49W6NGjVJ6ero6dOigefPmqVatWlqwYEGZxz/xxBPq16+fxo8fr/bt22vGjBk677zz9PTTT0s6WV0xZ84cTZo0SVdeeaU6deqkl156Sfv27dPSpUtNex4EFgBgQ06qsojcy2QMUILloFDCSZ/zqB5CCwAAAFSmsLBQGzZsUEpKiue28PBwpaSkaM2aNWXeZ82aNV7HS1Jqaqrn+J07dyorK8vrmLp16yo5ObnccwYCgQVcgSoL+6DKwndMZgEA4A6EFgAAwMrqtMwJdRMcLTc31+uroKD03NmhQ4dUVFSkxo0be93euHFjZWVllXnerKysCo8v+a8/5wyEGqadGQCqqG5mAVcZA3AdPvcAVCRqT6QKmheGuhkA4BhD66+u8n1f/qVHAFsCwK7yd8cqPDratPMX//99Ipo1a+Z1+5QpUzR16lTTHjfUCCzgGpFb96qwfbPKDwRsJGa3oaMtwkLdDACACfiMx+lKKi0ILgCgctUJJKpzbsIMAIG2d+9excbGer6Piip9sVvDhg0VERGh7Oxsr9uzs7MVHx9f5nnj4+MrPL7kv9nZ2WrSpInXMV26dKnSc/EFS0IBsCSWhgLgJlRXAPAHS0QBQGlD66/2+rJKO0LZFgDOEBsb6/VVVmARGRmprl27KiMjw3NbcXGxMjIy1L179zLP2717d6/jJWnlypWe41u2bKn4+HivY3Jzc/XVV1+Ve85AoMICrkKVhb2wNJRvuAIXAJyLz3iUhyWiALidnYKAU9tKBQYAs4wbN07Dhw9Xt27ddMEFF2jOnDnKz89Xenq6JGnYsGFq2rSpZs2aJUm644471Lt3bz3++OMaMGCAlixZovXr12v+/PmSpLCwMI0dO1YzZ85UmzZt1LJlS91///1KSEhQWlqaac+DwAIAHIAJLcC+CGYBVBWhBQC3sVNIUR7CCwBmufbaa3Xw4EFNnjxZWVlZ6tKli1asWOHZNHvPnj0KD/99waUePXpo8eLFmjRpku677z61adNGS5cu1TnnnOM55p577lF+fr5uvvlmHTlyRD179tSKFSsUbeLeHQQWcB2qLOyFKgsAAIDysa8FAKdzQkhRHsILnK5v8+36cE/bUDcDNjZmzBiNGTOmzJ+tWrWq1G1/+ctf9Je//KXc84WFhWn69OmaPn16oJpYKfawAGB57Gfhm5jdRqibAMBPBLLwBZ/v8AX7WgBwGrft/+C25wsA5aHCAq5ElQWciqWhAABwL5aIAuAEbp+0L3n+VFwAcCsCCwC2wNJQAJyGzzT4g0AavmKJKAB25fag4nQEFwDciiWh4FqRW/eGugnwE0tD+YalQwAAAEtEAbALlkKqGL8fAG5DhQUAOBBX4gLWRnUFqoLPdviLagsAVsYkvH+ouADgFlRYwNWosrAfqiwAAAD8Q7UFACuhYqB6+P0BcDoCC7geoYX9EFr4hqWhAGuiugLVwWc7qipqTyTBBYCQYqI9sPhdAnAqAgsAtkRo4RsmtgBrIawAEGqEFgBCgcl1c/B7BeBE7GEB6GSVRWH7ZqFuBgAAAGA69rYAECxMqJuPvS0AOA0VFgBsiyoL31BlAVgD1RUIFD7XEShUWwAwE2FFcPH7BuAUBBbA/8deFvZEaOEbJrcAAEBZ2NsCQKCxV0Xo8HuHGx1NKg51ExBgBBYAAAAmo7oCgUYQjUAjtAAQCEyYhx5/A4RKnZY5oW4CHILAAjgFVRb2RJWFb5jcAkKDsAKAXVBtAaA6mCi3Dv4WAOyMTbcBOELdzAImBQEArhKz29DRFmGhbgYcKGpPJBtyA/AZk+PWxGbcAOyKCgvgNFRZwMmosgCCiyAVgF1RbQHAF4QV1sffCIDdEFgAcAyWhvINoQUAOAef6TAbwQWA8jARDgAwA4EFUAaqLOyL0AKAVVBdAcBJCC0AnIqwwl74ewGwEwILAI5DaFE5rsgFzEVYgWDiMx3BQrUFgKH1VzP5bVP83QDYBYEFUA6qLOB0THABgHPwmY5gIrgA3IkJb/vjb2gPfZtvD3UTgJAisADgSFRZAAgVqisAuAXBBeAeTHQ7B39LAFZHYAFUgCoLeyO0qBxX5AKBRViBUOIzHaFCaAE4GxPczsPfFICVEVgAlSC0gNMxwQUAAKqLagvAmZjYBgAEG4EFAEejygJAsFBdASsghEaoEVwAzkFY4Wz8fQFYFYEF4AOqLOyN0KJyTHAB1UNYAQDeCC4Ae2My2x34OwOwIgILAK5AaFE5QgugaggrYDV8nsNKCC4A+2ES2134ewOwGgILwEdUWQAAALsgtIDVEFwA9sDkNQAg1AgsALgGVRaVY4IL8A/VFQDgH4ILwLoIK9yLvz0AKwlKYDF37lwlJiYqOjpaycnJWrduXYXHv/HGG2rXrp2io6PVsWNHLV++3OvnhmFo8uTJatKkiWrWrKmUlBR9//33Zj4FQBJVFk5AaFE5Qovg8LdvnDNnjtq2bauaNWuqWbNmuvPOO3X8+PEgtTZ47DRmIKyA1fF5DisjuPCPv/1jiSVLligsLExpaWnmNjAE7DRmsAMmrMFrAIBVmB5YvP766xo3bpymTJmijRs3qnPnzkpNTdWBAwfKPH716tUaMmSIRo4cqa+//lppaWlKS0vT5s2bPcc88sgjevLJJzVv3jx99dVXql27tlJTUx05cQMAcB5/+8bFixdrwoQJmjJlirZu3aoXXnhBr7/+uu67774gt9xcdhozEFbALggtYHUEF5Xzt38ssWvXLt199926+OKLg9TS4LHTmMEOmKgGAFiJ6YHF7NmzNWrUKKWnp6tDhw6aN2+eatWqpQULFpR5/BNPPKF+/fpp/Pjxat++vWbMmKHzzjtPTz/9tKSTVz3MmTNHkyZN0pVXXqlOnTrppZde0r59+7R06VKznw5AlYUDUGVROSa4zOVv37h69WpddNFFuu6665SYmKi+fftqyJAhPl9daReMGQDAvQguyudv/yhJRUVFuv766zVt2jS1atUqiK0NDsYMgUNYgVPxegBgBaYGFoWFhdqwYYNSUlJ+f8DwcKWkpGjNmjVl3mfNmjVex0tSamqq5/idO3cqKyvL65i6desqOTm53HMWFBQoNzfX6wuAuxFaVI7Qwn+n9zUFBaVfZ1XpG3v06KENGzZ4AooffvhBy5cv1+WXX27OEwkBq4wZpMrHDVRXwG74PIeduCW48GXMIFWtf5Sk6dOnq1GjRho5cmTA2x5qdhozWB2T0wAAK6ph5skPHTqkoqIiNW7c2Ov2xo0ba9u2bWXeJysrq8zjs7KyPD8vua28Y043a9YsTZs2rUrPAShL5Na9KmzfLNTNQDXVzSxg4tElIvdGKiLavMmPouPFkqRmzbw/F6ZMmaKpU6d63VaVvvG6667ToUOH1LNnTxmGoRMnTuhvf/ubo5aEssqYQap43MBnBuwqZrehoy3CQt0MwGcloUVB88KgPq6VxgxS1frHL774Qi+88II2bdoUkDZbjV3GDFZHWIHyDK2/Wi//0iPUzQD8cjSpWDGZQdmqGUHgir/kxIkTlZOT4/nau5clfVB9LA0FN+CqXP/s3bvXq7+ZOHFiQM67atUqPfjgg3rmmWe0ceNGvfXWW3r//fc1Y8aMgJwf3sobN+S2JKwAgGBzasWFWWOGo0ePaujQoXr++efVsGHDgJwT5bPrXANhBQDAykytsGjYsKEiIiKUnZ3tdXt2drbi4+PLvE98fHyFx5f8Nzs7W02aNPE6pkuXLmWeMyoqSlFRTDIAKI0qi8pxVa7vYmNjFRsbW+ExVekb77//fg0dOlQ33XSTJKljx47Kz8/XzTffrL///e8KD7f/9QdWGTNIjBvgXHyew85KQouSCgW782XMIPnfP2ZmZmrXrl0aOHCg57bi4pO/sxo1amj79u1KSkqqZutDizFD9RBWwBdUWQAIJVNnOCIjI9W1a1dlZGR4bisuLlZGRoa6d+9e5n26d+/udbwkrVy50nN8y5YtFR8f73VMbm6uvvrqq3LPCZiFKgtnYD8LBFNV+sZjx46VCiUiIiIkndwk0gkYMwDBQeUcYC/+9o/t2rXTt99+q02bNnm+rrjiCvXp00ebNm0qtRSVHTFmqDrCCgCAHZhaYSFJ48aN0/Dhw9WtWzddcMEFmjNnjvLz85Weni5JGjZsmJo2bapZs2ZJku644w717t1bjz/+uAYMGKAlS5Zo/fr1mj9/viQpLCxMY8eO1cyZM9WmTRu1bNlS999/vxISEpSWlmb20wHgUFRaVIyrcgPL375x4MCBmj17ts4991wlJydrx44duv/++zVw4EBPcOEEjBkAACjNn/4xOjpa55xzjtf969WrJ0mlbrczxgz+I6yAv6iyABAqpgcW1157rQ4ePKjJkycrKytLXbp00YoVKzybWe3Zs8frqtEePXpo8eLFmjRpku677z61adNGS5cu9Rpc3XPPPZ6lMI4cOaKePXtqxYoVio6ONvvpAKWwATfcgtAicPztGydNmqSwsDBNmjRJP/30k+Li4jRw4EA98MADoXoKpmDMAAQHn+eAvfjbP7oBYwb/EFYAAOwkzHDKWhJ+yM3NVd26dZUSN1I1wp23gRuCj8DCOaiyqJgZE1xFx48r88H7lJOT49Nazv4o+bxPuu9BRZj4j00znwNCr+R11GXoA4qItP+kBVCC0AJ2ZFafy5gBgVDyOhrzxVWKqnNGqJsjibAC1UeVRWh8uKdtqJtQJXk764bssWMyvcP7ooLj2vKcuXMNLR6eqXATxw3Fx49r972TXDducNdlGIBJ2MvCOdjPomKsfQ4AzsFnOgA4G2EFAMCOCCyAACG0cA5Ci4oxwQUAAABYG2EFAoXXEoBgI7AAAPiN0AIAnIHPcwBwHiaYAQB2RmABBBBVFs5BlQUAwC0ILQDAOQgrAAB2R2ABAOUgtKgYE1wA4Bx8pgOA/RFWwCy8tgAEE4EFEGBUWTgLoUXFmOACAOfgMx0AAABAqBFYAAAAAAAA2BhXwMNsvMbgizotc0LdBDgAgQVgAqosnIUqi4pxRS4AOAef6QBgP0wkAwCchMACMAmhhbMQWlSMCS4AcA4+0wHAPggrAABOQ2ABAD4itAAAuAWhBQBYH2EFgo3XHIBgILAATESVBdyEyS0AcBY+1wHAupg4BgA4FYEFAPiBKouKMbkFAM7C5zoAWA9hBQCUdjSpONRNQIAQWAAmo8rCeQgtAABuQmgBANZBWIFQ4zUIwGwEFkAQEFo4D6FF+ZjYAgDn4bMdAEKPiWIAgBsQWABAFRFalI+JLQBwHj7bASB0CCsAAG5BYAEECVUWcBsmtgDAefhsB4DgI6yA1fCaBGAmAgsAqAaqLAAAbkNoAQDBw8QwAMBtCCyAIKLKwpkILcrHpBYAOBOf7wBgPsIKAIAbEVgAQUZo4UyEFuVjUgsAnInPdwAwD2EFAMCtCCwAAKZjUgsAnInPdwAIPMIK2AGvUwBmIbAAQoAqC2eiygIA4EaEFgAQOEwCAwDcjsACAAKI0KJ8TGgBgHPxGQ8A1UdYAQAAgQUQMlRZOBehRfmY0AIA54rZbfA5DwBVRFgBAMBJBBZACBFaOBehBQDArQgtAMA/hBWwK167AMxAYAEAJiG0KBsTWQDgfHzWA4BvmPAFAMAbgQUQYlRZwI2YyAIA5+OzHgAqRlgBAIF1NKk41E1AABBYABZAaOFcVFmUj4ksAHA+9rUAgLIRVgAAQunw4cO6/vrrFRsbq3r16mnkyJHKy8ur8D7z58/XJZdcotjYWIWFhenIkSOljklMTFRYWJjX10MPPeRX2wgsAMBkhBYAALcjtACA3xFWwEl4PQP2dP3112vLli1auXKl3nvvPX322We6+eabK7zPsWPH1K9fP913330VHjd9+nTt37/f83Xbbbf51bYafh0NwDSRW/eqsH2zUDcDJqmbWaCcpKhQN8NyYnYbOtI41K0AAARDzG5DR1uEhboZABAyTOwCAKxg69atWrFihf773/+qW7dukqSnnnpKl19+uR577DElJCSUeb+xY8dKklatWlXh+WNiYhQfH1/l9lFhAQBBQqVF2WL2ctUtALgFS0QBcCvCCgCAVaxZs0b16tXzhBWSlJKSovDwcH311VfVPv9DDz2kM888U+eee64effRRnThxwq/7U2EBWAhVFs5HpQUAAFRbAHAXwgoAQHXk5uZ6fR8VFaWoqKrPLWVlZalRo0Zet9WoUUMNGjRQVlZWlc8rSbfffrvOO+88NWjQQKtXr9bEiRO1f/9+zZ492+dzEFgAFkNoAQAA3KCk0oLgAoCTEVYAgHPV+SFcEVHmLWBUVHDy3M2aec8TTpkyRVOnTi11/IQJE/Twww9XeM6tW7cGrH1lGTdunOf/O3XqpMjISP31r3/VrFmzfA5ZCCwAIMiosgAA4HdUWwBwKsIKuMXQ+qv18i89Qt0MwLH27t2r2NhYz/flTfzfddddGjFiRIXnatWqleLj43XgwAGv20+cOKHDhw9Xa++JsiQnJ+vEiRPatWuX2rZt69N9CCwAC6LKwvkILQAA+B3VFgCcZHC9r1Qnhi1DAbhTnZY5yttZN9TNcJTY2FivwKI8cXFxiouLq/S47t2768iRI9qwYYO6du0qSfr4449VXFys5OTkarf3VJs2bVJ4eHipJagqQg8KWFTk1r2hbgJMxibcAAB4Y0NuAAAAwFzt27dXv379NGrUKK1bt05ffvmlxowZo8GDByshIUGS9NNPP6ldu3Zat26d535ZWVnatGmTduzYIUn69ttvtWnTJh0+fFjSyc2858yZo2+++UY//PCDXn31Vd1555264YYbVL9+fZ/bR2ABACFEaAEAgLeY3QbBBQAAAGCiV199Ve3atdOll16qyy+/XD179tT8+fM9P//tt9+0fft2HTt2zHPbvHnzdO6552rUqFGSpF69euncc8/VsmXLJJ1cqmrJkiXq3bu3zj77bD3wwAO68847vc7rC5aEAiyMpaHcgeWhAAAojWWiAAAA4K+jScWKyeQa/co0aNBAixcvLvfniYmJMgzvi4imTp1a5mbfJc477zytXbu22m3jrwdYHEtDuQOVFgAAlI1qCwAArI9N5gEECoEFAFgEoQUAAGVjmSgAAADAHQgsABugygIAAIDgAgAAAHA6AgvAJggt3IEqCwAAKkdwAQAAADgTgQVgI4QW7kBoAQCAbwguAAAAAGchsAAACyK0AADAdwQXAAAAgDMQWAA2Q5WFexBaAADgH4ILAABCZ2j91aFuAgAHILAAbIjQwj0ILQAA8B/BBQAAAGBPBBYAYHGEFgAAVA3BBQAAgPscTSoOdRNQDQQWgE1RZeEuhBYAAFQdwQUAAABgDwQWgI0RWrgLoQUAANVDcAEAAABYG4EFYHOEFu5CaAEAQPWVBBeEFwAAAIFXp2VOqJsAGyOwAACbIbQAACBwCC4AAAAA6yCwAByAKgv3IbQAACCwqLoAAKD6htZfHeomALA5AgvAIQgt3IfQAgAAcxBcAAAAAKFBYAE4CKGF+xBaAABgHqouAAAAgOCqEeoGAAAAAIDVnRpaHG0RFsKWAAAAoDJ5rYpD3QRUkakVFocPH9b111+v2NhY1atXTyNHjlReXl6Fx992221q27atatasqebNm+v2229XTo73zvJhYWGlvpYsWWLmUwFsgyoL96HKwp7mzp2rxMRERUdHKzk5WevWrfPpfkuWLFFYWJjS0tLMbWCQMWYAYCdUXiDY/B03vPHGG2rXrp2io6PVsWNHLV++PEgtNR9jBgAAnM3UwOL666/Xli1btHLlSr333nv67LPPdPPNN5d7/L59+7Rv3z499thj2rx5sxYtWqQVK1Zo5MiRpY5duHCh9u/f7/ly2sQNUB2EFu5DaGEvr7/+usaNG6cpU6Zo48aN6ty5s1JTU3XgwIEK77dr1y7dfffduvjii4PU0uBhzADArggvYDZ/xw2rV6/WkCFDNHLkSH399ddKS0tTWlqaNm/eHOSWm4MxAwA36Nt8e6ibAISMaUtCbd26VStWrNB///tfdevWTZL01FNP6fLLL9djjz2mhISEUvc555xz9O9//9vzfVJSkh544AHdcMMNOnHihGrU+L259erVU3x8vFnNB2wvcuteFbZvFupmIIjqZhYoJykq1M2AD2bPnq1Ro0YpPT1dkjRv3jy9//77WrBggSZMmFDmfYqKinT99ddr2rRp+vzzz3XkyJEgtthcjBkAOAXLRsEM/o4bnnjiCfXr10/jx4+XJM2YMUMrV67U008/rXnz5gW17YHGmAEAAOczrcJizZo1qlevnmcQIUkpKSkKDw/XV1995fN5cnJyFBsb6zWIkKTRo0erYcOGuuCCC7RgwQIZBlc0Aaej0sJ9qLSwvsLCQm3YsEEpKSme28LDw5WSkqI1a9aUe7/p06erUaNGZV4NaHeMGQA4EZUXCISqjBvWrFnjdbwkpaamVjjOsAvGDAAAOJ9pFRZZWVlq1KiR94PVqKEGDRooKyvLp3McOnRIM2bMKFXeOX36dP3xj39UrVq19OGHH+rWW29VXl6ebr/99jLPU1BQoIKC3yfxcnNz/Xw2AGAfVFqEzun9S1RUlKKivP8Whw4dUlFRkRo3bux1e+PGjbVt27Yyz/vFF1/ohRde0KZNmwLaXquw0phBYtwAIPCovMDpfBkzSFUbN2RlZZV5vK99qpUxZgDsYWj91Xr5lx6hbgYAm/I7sJgwYYIefvjhCo/ZunVrlRtUIjc3VwMGDFCHDh00depUr5/df//9nv8/99xzlZ+fr0cffbTcgcSsWbM0bdq0arcJsCOWhnInQgtvMXsNRUSad4VcUeHJczdr5v1emzJlSqk+zF9Hjx7V0KFD9fzzz6thw4bVOlew2XHMIDFuAGCu0ysuCDCsxc5jBjtjzAAAzlOnZY7ydtYNdTNgQ34HFnfddZdGjBhR4TGtWrVSfHx8qU3ATpw4ocOHD1e6JuTRo0fVr18/xcTE6O2339YZZ5xR4fHJycmaMWOGCgoKyrwqZeLEiRo3bpzn+9zc3FIDRMDJCC3cidAi+Pbu3avY2FjP92X1SQ0bNlRERISys7O9bs/Ozi6zf8zMzNSuXbs0cOBAz23FxcWSTl5RuH37diUlJQXqKQSUHccMEuMGAMFF9YU7+TJmkPwfN0hSfHy8X8dbAWMGAABQwu/AIi4uTnFxcZUe1717dx05ckQbNmxQ165dJUkff/yxiouLlZycXO79cnNzlZqaqqioKC1btkzR0dGVPtamTZtUv379cgcR5ZXXAm5CaOFOhBbBFRsb6zX5UJbIyEh17dpVGRkZSktLk3QygMjIyNCYMWNKHd+uXTt9++23XrdNmjRJR48e1RNPPGHpfxTbccwgMW4AEDpUX7iHL2MGyf9xg3SyX83IyNDYsWM9t61cuVLdu3cPRNNNwZgBAACUMG0Pi/bt26tfv34aNWqU5s2bp99++01jxozR4MGDlZCQIEn66aefdOmll+qll17SBRdcoNzcXPXt21fHjh3TK6+8otzcXM8akHFxcYqIiNC7776r7OxsXXjhhYqOjtbKlSv14IMP6u677zbrqQCOQWjhToQW1jNu3DgNHz5c3bp10wUXXKA5c+YoPz9f6enpkqRhw4apadOmmjVrlqKjo3XOOed43b9evXqSVOp2u2LMAABlI8CA5N+4QZLuuOMO9e7dW48//rgGDBigJUuWaP369Zo/f34on0ZAMGYAAMD5TAssJOnVV1/VmDFjdOmllyo8PFxXX321nnzySc/Pf/vtN23fvl3Hjh2TJG3cuFFfffWVJKl169Ze59q5c6cSExN1xhlnaO7cubrzzjtlGIZat26t2bNna9SoUWY+FcAxCC3cidDCWq699lodPHhQkydPVlZWlrp06aIVK1Z4Nsjcs2ePwsPDQ9zK4GLMAACVI8BwJ3/HDT169NDixYs1adIk3XfffWrTpo2WLl3qmAsdGDMAAOBsYYZhmLejmEXl5uaqbt26SokbqRrhkaFuDhB0BBbuZcXQoqjwuDa9/Hfl5OT4tDSCP0o+77sMfUARkZWX/leVmc8BoRes1xEAVJcbAoyi48eV+eB9Ae9zGTMgEEpeR19sTlCdGHddfAKc7uVfeoS6Cbb34Z62oW5CtYVy0+3i48e1+95Jps41nP3XBxURZeK4oeC4tjwX+HGP1ZlaYQHAmqiycK+6mQWSrBlcAACA6jm9AkNyR4gBAAAA5yCwAFyK0MLdWCIKAAB3IMQAAACAnVCjCLhY5Na9oW4CQqik2gIAALhLzG7D6wsAAACwCgILwOUILdyN0AIAAJweYBBiAACAQKjTMifUTYANEVgAILRwOUILAABwurJCDIIMAACCp2/z7aFuAhASBBYAJBFauB2hBQAA8AUhBgDAF0Prrw51EwDYFJtuA/BgI253YyNuAABQFeWFFmzuDQAAAH8RWADwQmjhboQWAAAgUAgyAAAA4C8CCwClEFq4G6EFAAAwU0XLSBFmAAAAuBuBBYAyEVq4G6EFAAAIBcIMAAAAd2PTbQDlYiNud2MjbgAAYCUxuw3F7GWTbwAAACcjsABQIUILdyO0AAAAAAAAVVWnZU6omwCbIbAAUClCC3cjtAAAAAAAAEAwEFgA8AmhhbsRWgAAAAAAAMBsBBYAfEZo4W51MwsILgAAAAAAAGAaAgsAfiG0AKEFAAAAAADm69t8e6ibAAQdgQUAvxFagNACAAAAAAAAgUZgAaBKCC1AaAEAAAAAAIBAIrAAUGWEFiC0AAAAAAAAFanTMifUTYCNEFgAqBZCCxBaAAAAAAAAIBAILABUG6EFCC0AAAAAAABQXQQWAAKC0AKEFgAAAAAAAKgOAgsAAUNoAUILAAAAAAAAVBWBBYCAity6l+DC5epmFhBcAAAAAAAAwG8EFgBMQWgBQgsAAAAAAKqnb/PtoW4CEFQEFgBMQ2gBQgsAAAAAAFCnZU6omwCbILAAYCpCCxBaAAAAAAAAwBcEFgBMR2gBQgsAAAAAAABUhsACQFCwGTcILQAAAAAAAFARAgsAQUVo4W6EFgAAAAAAACgPgQWAoCO0cDdCCwAAAAAAAJSFwAJASLBElLvVzSwguAAAAAAAAIAXAgsAIUVo4W6EFgAAAAAAuEOdljmhbgJsgMACQMgRWrhb7E5CCwAAAAAAABBYALAIlogCAAAAAMAZXv6lR6ib4Ch9m28PdROAoCGwAGAphBYAAAAAAACAOxFYALAcQgsAAAAAAADAHIcPH9b111+v2NhY1atXTyNHjlReXl6F9/nrX/+qpKQk1axZU3Fxcbryyiu1bds2r2P27NmjAQMGqFatWmrUqJHGjx+vEydO+NU2AgsAlsQSUQAAAAAAAEDgXX/99dqyZYtWrlyp9957T5999pluvvnmCu/TtWtXLVy4UFu3btUHH3wgwzDUt29fFRUVSZKKioo0YMAAFRYWavXq1XrxxRe1aNEiTZ482a+2EVgAsDRCCwAAAAAAACAwtm7dqhUrVuif//ynkpOT1bNnTz311FNasmSJ9u3bV+79br75ZvXq1UuJiYk677zzNHPmTO3du1e7du2SJH344Yf67rvv9Morr6hLly7q37+/ZsyYoblz56qwsNDn9hFYALA8qi0AAAAAAACA6luzZo3q1aunbt26eW5LSUlReHi4vvrqK5/OkZ+fr4ULF6ply5Zq1qyZ57wdO3ZU48aNPcelpqYqNzdXW7Zs8bl9BBYAbIPQAgAAAAAAwL7qtMwJdRNsJzc31+uroKCgWufLyspSo0aNvG6rUaOGGjRooKysrArv+8wzz6hOnTqqU6eO/vOf/2jlypWKjIz0nPfUsEKS5/vKzuvVFp+PBAALKAktCts3C3FLAAAAAADA6V7+pUeomwAERb0dhapRw7x6gBMnTi6jVFLBUGLKlCmaOnVqqeMnTJighx9+uMJzbt26tVptuv7663XZZZdp//79euyxxzRo0CB9+eWXio6OrtZ5T0VgAcCWIrfuJbQAAAAAAACAo+3du1exsbGe76Oioso87q677tKIESMqPFerVq0UHx+vAwcOeN1+4sQJHT58WPHx8RXev27duqpbt67atGmjCy+8UPXr19fbb7+tIUOGKD4+XuvWrfM6Pjs7W5IqPe+pCCwA2BbVFgAAAAAAAHCy2NhYr8CiPHFxcYqLi6v0uO7du+vIkSPasGGDunbtKkn6+OOPVVxcrOTkZJ/bZRiGDMPwLFHVvXt3PfDAAzpw4IBnyamVK1cqNjZWHTp08Pm87GEBwPbY2wIAAAAAADhZ3+bbQ90EOET79u3Vr18/jRo1SuvWrdOXX36pMWPGaPDgwUpISJAk/fTTT2rXrp2nYuKHH37QrFmztGHDBu3Zs0erV6/WX/7yF9WsWVOXX365JKlv377q0KGDhg4dqm+++UYffPCBJk2apNGjR5dbFVIWAgsAjhC5dS/BBQAAAAAAAFCJV199Ve3atdOll16qyy+/XD179tT8+fM9P//tt9+0fft2HTt2TJIUHR2tzz//XJdffrlat26ta6+9VjExMVq9erWnmiIiIkLvvfeeIiIi1L17d91www0aNmyYpk+f7lfbWBIKgKOwTBQAAAAAAKHBhtuAPTRo0ECLFy8u9+eJiYkyDMPzfUJCgpYvX17peVu0aOHTcRWhwgKAI1FtAQAAAAAAANgLgQUAx2KZKAAAAAAAAMA+CCwAOB6hBQAAAAAA5mI5KPiqTsucUDcBFkZgAcAVqLYAAAAAAAAArI3AAoCrEFwAAAAAAAAA1kRgAcCVCC4AAAAAAAgMloMCECgEFgBcjdACAAAAAAAAsAYCCwCuR7UFAAAAAAAAEHqmBhaHDx/W9ddfr9jYWNWrV08jR45UXl5ehfe55JJLFBYW5vX1t7/9zeuYPXv2aMCAAapVq5YaNWqk8ePH68SJE2Y+FQAuQHCBYJo7d64SExMVHR2t5ORkrVu3rsLj33jjDbVr107R0dHq2LGjli9fHqSWBgdjBgAAqqcqfWkJwzDUv39/hYWFaenSpeY2tJoYMwDWw3JQAALJ1MDi+uuv15YtW7Ry5Uq99957+uyzz3TzzTdXer9Ro0Zp//79nq9HHnnE87OioiINGDBAhYWFWr16tV588UUtWrRIkydPNvOpAHARQguY7fXXX9e4ceM0ZcoUbdy4UZ07d1ZqaqoOHDhQ5vGrV6/WkCFDNHLkSH399ddKS0tTWlqaNm/eHOSWm4cxAwAA1VPVvlSS5syZo7CwMJNbGBiMGQAAcDbTAoutW7dqxYoV+uc//6nk5GT17NlTTz31lJYsWaJ9+/ZVeN9atWopPj7e8xUbG+v52YcffqjvvvtOr7zyirp06aL+/ftrxowZmjt3rgoLC816OgBchmoLmGn27NkaNWqU0tPT1aFDB82bN0+1atXSggULyjz+iSeeUL9+/TR+/Hi1b99eM2bM0Hnnnaenn346yC03B2MGAACqpzp96aZNm/T444+XOw6xEsYMgPVQXQEg0EwLLNasWaN69eqpW7dunttSUlIUHh6ur776qsL7vvrqq2rYsKHOOeccTZw4UceOHfM6b8eOHdW4cWPPbampqcrNzdWWLVvKPF9BQYFyc3O9vgDAFwQX8MfpfU1BQUGpYwoLC7VhwwalpKR4bgsPD1dKSorWrFlT5nnXrFnjdbx0su8r73i7sdKYQWLcAAAwny9jBn9UtS89duyYrrvuOs2dO1fx8fHVakMwMGYAAMD5aph14qysLDVq1Mj7wWrUUIMGDZSVlVXu/a677jq1aNFCCQkJ+t///qd7771X27dv11tvveU576mDCEme78s776xZszRt2rTqPB0ALlcSWhS2bxbilqAqYncWqEYN85Y5OHHi5CRDs2ber48pU6Zo6tSpXrcdOnRIRUVFZfZl27ZtK/P85fV9FfWndmKlMYPEuAEA3MxKYwZ/VLUvvfPOO9WjRw9deeWVVX7sYGLMAFgL1RUAzOB3YDFhwgQ9/PDDFR6zdevWKjfo1LUnO3bsqCZNmujSSy9VZmamkpKSqnTOiRMnaty4cZ7vc3NzSw0QAcAXkVv3ElqgXHv37vVaXiAqKiqErQk9O44ZJMYNAADz+TpmMLMvXbZsmT7++GN9/fXXVbp/IDFmAAAAJfwOLO666y6NGDGiwmNatWql+Pj4UpuHnjhxQocPH/ar1DQ5OVmStGPHDiUlJSk+Pl7r1q3zOiY7O1uSyj1vVFSU6yeNAAQO1RYoT2xsrNfkQ1kaNmyoiIgIT99VIjs7u9x+LD4+3q/jrcKOYwaJcQMAwHy+jBkkc/vSjz/+WJmZmapXr57X7VdffbUuvvhirVq1qtL2BQpjBsB+qK4AYBa/A4u4uDjFxcVVelz37t115MgRbdiwQV27dpV0ckBUXFzsGRz4YtOmTZKkJk2aeM77wAMP6MCBA55S0JUrVyo2NlYdOnTw89kAQNURXKAqIiMj1bVrV2VkZCgtLU2SVFxcrIyMDI0ZM6bM+3Tv3l0ZGRkaO3as57aVK1eqe/fuQWhx1TFmAACgeszsSydMmKCbbrrJ67aOHTvqH//4hwYOHFj9xvuBMQNgL4QVAMxk2qbb7du3V79+/TRq1CitW7dOX375pcaMGaPBgwcrISFBkvTTTz+pXbt2nisZMjMzNWPGDG3YsEG7du3SsmXLNGzYMPXq1UudOnWSJPXt21cdOnTQ0KFD9c033+iDDz7QpEmTNHr0aK5sABASbMwNf40bN07PP/+8XnzxRW3dulW33HKL8vPzlZ6eLkkaNmyYJk6c6Dn+jjvu0IoVK/T4449r27Ztmjp1qtavX19uwGE3jBkAAKieqvSl8fHxOuecc7y+JKl58+Zq2bJlyJ5LRRgzAADgfKYFFpL06quvql27drr00kt1+eWXq2fPnpo/f77n57/99pu2b9+uY8eOSTp51elHH32kvn37ql27drrrrrt09dVX69133/XcJyIiQu+9954iIiLUvXt33XDDDRo2bJimT59u5lMBgEoRWsBX1157rR577DFNnjxZXbp00aZNm7RixQrP5o579uzR/v37Pcf36NFDixcv1vz589W5c2e9+eabWrp0qWdiwQkYMwAAUD3+9qV2xZgBCC2qKwCYLcwwDCPUjQi23Nxc1a1bVylxI1UjPDLUzQHgQCwT5bsTJ47rsy+mKycnx6e1nP1R8nnfq+dk1agRHdBzn8rM54DQK3kddRn6gCIizXsdAQAqV1R4XJte/nvA+1zGDAiEktfRF5sTVCfG1OtDgZAgrAi9D/e0DXUTAiZvZ11Tz198/Lh23zvJ1LmGiy6davq44cuMqa4bN9CDAoAJWCYKAAAAAOAUhBUAgoXAAgBMRHABAAAAAAAA+IbAAgCCgNACAAAAAGBHVFcACCYCCwAIEqotAAAAAAB2QlgBINgILAAgyAguAAAAAABWR1hhLU7acBuoCIEFAIQIwQUAAAAAwIoIKwCECoEFAIQYoQUAAAAAwCoIKwCEEoEFAFgA1RYAAAAAgFAjrAAQajVC3QAAwO9KQovC9s1C3BIAAAAAgFsQVACwCiosAMCCqLYAAAAAAAQDYQUAKyGwAACLYpkoAAAAAICZCCsAWA1LQgGAxbFMFAAAAAAgkAgq7OXDPW1D3YSAyttZN9RNgIURWACATURu3UtoAQAAAACoMoIKAFbHklAAYCMsEwUAAAAAqArCCgB2QIUFANgQy0QBAAAAAHxBUAHATggsAMDGWCYKAAAAAFAWggpncNr+Ffh/7d17dFXlnf/xTy4kIcQkQICQCgjCAGoU1JVIlopLMhpglCozCLK4FYGq1FHRCp0itypQUFstI7YLQp0lRbSC2EEqiCzRSblJWsCYQoyADAkjaRJCICTk+f3BL8ecXM99n33O+7VW1iL7PGef79nsk/3N/uTZG+0hsAAAm2O2BQAAAACgAUEFADsjsACAEMFsCwAAAAAIXwQVAEIBgQUAhBBmWwAAAABAeCGogJ1UFSdZXQKCHIEFAIQgZlsAAAAAQOgipAgP3L8C4YjAAgBCFLMtAAAAACC0EFQACHUEFgAQ4phtAQAAAAD2RUgBIJwQWABAGGC2BQAAAADYByEFuBwUwhWBBQCEEWZbAAAAO0oqqpEk1dXVWFwJAPgPIQVCHTfchisILAAgzDDbAgAABLOGcAIAwgEhBQA4I7AAgDDFbAsAAGAlggkA4YiAAq7gclAIZwQWABDGCC0AAEAgEE4ACFcEFADgHgILAAhzXCIKAAD4EuEEgHBGQAFvhersCu5fAVcRWAAAJDHbAgAAuI9wAkC4I6AAAN8isAAAOBBaAACA1hBOAAABBfwrVGdXAO4gsAAAOOESUQAAQCKgAADCCcA3uBwU3EFgAQBoEbMtAAAILwQUAMIdAQWsxOwK4AoCCwBAqwgtAAAIXQQUAMIZ4QQABCcCCwBAm7hEFAAAoYGAAkC4IpxAsAvl2RVcDgruIrAAALiE2RYAANgLAQWAcEQ4AQD2RmABAHAZoQUAAMGLgAJAuCGcQCgI5dkVgCcILAAAbiG0AAAgeBBSAAgXhBMIRaEeVnA5KHiCwAIA4DZCCwAArEFAASAcEE4AQPgisAAAeISbcQMAEBiEFABCGeEEwlWoz64APEVgAQDwCrMtAADwPUIKAKGIcAK4IhzCCi4HBU8RWAAAvEZoAQCA9wgpAIQSwgmgZeEQVgDeILAAAPgEoQUAAO4jpAAQCggnADTG7Ap4g8ACAOAzhBYAALSPkAKAnRFOAJ5jdgXQPgILAIBPEVoAANAcIQUAOyKcAHwnXMIKZlfAWwQWAACfI7QAAICQAoD9EFAA/hEuYQXgC2EdWFwa+APVR8cF9DVjCk4G9PUAwCqEFgCAcEVQAcAOCCeAwAinsILZFfZRVlamn/zkJ/rggw8UGRmpsWPH6te//rUSEhLafa4xRqNGjdK2bdu0adMm/fCHP3Q8FhER0Wz8H/7wB40fP97l2sI6sLCCuyfvCDgA2BmhBQAgXBBSAAhmhBOANcIprIC9TJw4UadPn9b27dtVW1uradOmaebMmVq/fn27z/3Vr37VYjDRIDc3Vzk5OY7vk5OT3aqNwCLItXeij0ADQLAjtAAAhDKCCgDBhnACCA7hFlYwu8I+CgoKtG3bNu3bt0+33nqrJOm1117TqFGjtHLlSqWlpbX63Pz8fL300kvav3+/evbs2eKY5ORkpaamelwfgYXNtXYSkCADQDAhtAAAhBJCCgDBhIACAEJbZWWl0/exsbGKjY31eH15eXlKTk52hBWSlJ2drcjISO3Zs0cPPPBAi8+rrq7Www8/rFWrVrUZSDz++ON65JFH1K9fP/34xz/WtGnT2pyR0RSBRYgiyAAQbAgtAAB2R1ABwGqEE0DwC7eZFVL4zq7o+OVpRUfG+G39dfWXJEm9ejmfS1mwYIEWLlzo8XpLSkrUvXt3p2XR0dHq0qWLSkpKWn3eU089paysLI0ZM6bVMYsXL9bdd9+t+Ph4ffTRR3rsscdUVVWlJ554wuX6CCzCTEsnCwkxAAQKoQUAwI4IKgBYhYACsJdwDCvgfydPnlRiYqLj+9ZmV8ydO1fLly9vc10FBQUe1bBlyxbt3LlTBw8ebHPc/PnzHf8eOnSozp8/rxUrVhBYwD2EGAACidACAGAHhBQAAo1wArC3cA0rwnV2RSAlJiY6BRatmTNnjqZOndrmmH79+ik1NVVnzpxxWl5XV6eysrJWL/W0c+dOFRUVNbuB9tixY3XHHXdo165dLT4vMzNTS5YsUU1NjcuXsSKwQIuankwkwADgS4QWAIBgRVABIFAIKIDQEa5hRTBL+DrS6hICrlu3burWrVu744YNG6by8nIdOHBAt9xyi6QrgUR9fb0yMzNbfM7cuXP1yCOPOC1LT0/XK6+8ovvuu6/V18rPz1fnzp3duucGgQVcQoABwNcILQAAwYSgAkAgEFIAoSecwwpmV9jT4MGDlZOToxkzZmj16tWqra3V7NmzNX78eKWlpUmSTp06pREjRujNN99URkaGUlNTW5x90bt3b/Xt21eS9MEHH6i0tFS33Xab4uLitH37dr344ot65pln3KrPr1FTWVmZJk6cqMTERCUnJ2v69Omqqqpqdfw333yjiIiIFr/eeecdx7iWHt+wYYM/3wqauDS4l9MXAHiC8LN97h5LGzPGaOTIkYqIiNDmzZv9W6iX6BkAWCWpqIawAiHBk56hpKREkyZNUmpqqjp16qSbb75Zf/zjHwNUsWfs1jP81z+ynL4AhJZwDiuC2VVF4Te7wl1vvfWWBg0apBEjRmjUqFG6/fbb9dvf/tbxeG1trQoLC1VdXe3yOjt06KBVq1Zp2LBhGjJkiN544w29/PLLWrBggVu1+XWGxcSJE3X69Glt375dtbW1mjZtmmbOnKn169e3OL5Xr146ffq007Lf/va3WrFihUaOHOm0PDc3Vzk5OY7vm14/C4HVOLTgBCQAd8QUnrK6hKDm7rG0sV/96leKiIgIQJXeo2cAEGiEFAg1nvQMkydPVnl5ubZs2aKUlBStX79e48aN0/79+zV06NAAVu86O/QMG8ozFVvXwaPnArCPcA8rmF1hb126dGmzR7jmmmtkjGlzHU0fz8nJcTqOespvgUVBQYG2bdumffv26dZbb5Ukvfbaaxo1apRWrlzpmF7SWFRUVLOpJZs2bdK4ceOUkJDgtDw5ObnVm4DAWoQXAOAbnhxLG+Tn5+ull17S/v371bNnz0CV7BF6BgCBRFCBUORpz/A///M/ev3115WRkSFJ+vnPf65XXnlFBw4cCMrAgp4BQDAI96BCCu6wgtkV9ue3/8G8vDwlJyc7mghJys7OVmRkpPbs2ePSOg4cOKD8/HxNnz692WOPP/64UlJSlJGRobVr17ab+MAaXDYKADzn6bG0urpaDz/8sFatWmWLX7rpGQAEApd+Qijz9FialZWlt99+W2VlZaqvr9eGDRt08eJF3XXXXQGo2n30DACsRlgB+J/fZliUlJSoe/fuzi8WHa0uXbqopKTEpXWsWbNGgwcPVlaW83UeFy9erLvvvlvx8fH66KOP9Nhjj6mqqkpPPPFEi+upqalRTc33v5xUVla6+W7gC8y8ABDqmh5fYmNjFRsb6/H6PD2WPvXUU8rKytKYMWM8fu1ACqaeQaJvAEIRQQWCTbD0DBs3btRDDz2krl27Kjo6WvHx8dq0aZP69+/vcS3+RM8AwEqEFVcwuwL+5nZgMXfuXC1fvrzNMQUFBR4X1ODChQtav3695s+f3+yxxsuGDh2q8+fPa8WKFa02EkuXLtWiRYu8rgm+Q3gBIJBiCk8pOjLGb+uPrL8k6co1khtbsGCBFi5c2Gy8P4+lW7Zs0c6dO3Xw4EGPnu9LduwZJPoGIJQQVMBd4dQzSFeOk+Xl5dqxY4dSUlK0efNmjRs3Trt371Z6errH63UXPQOAYEZQ8b1gDisQOtwOLObMmaOpU6e2OaZfv35KTU3VmTNnnJbX1dWprKzMpctTvPvuu6qurtbkyZPbHZuZmaklS5aopqamxb9KmTdvnp5++mnH95WVlc0aRFinIbwguABgdydPnlRiYqLj+9b+UtKfx9KdO3eqqKio2U0ix44dqzvuuEO7du1q9334ih17Bom+AQgFBBUIdsHQMxQVFek3v/mNDh8+rOuvv16SdNNNN2n37t1atWqVVq9e7cY78g49A4BgRVhhH8yuCB1uBxbdunVTt27d2h03bNgwlZeX68CBA7rlllskXTmJUl9fr8zMzHafv2bNGt1///0uvVZ+fr46d+7cahPh7fRaBAazLgDYXWJiotPJh9b481g6d+5cPfLII07L0tPT9corr+i+++5z4V34jh17Bom+AbAzggrYRTD0DNXV1ZKkyEjnEzxRUVGqr69v9zV9iZ4BQLAhqGiO2RUIFL/dw2Lw4MHKycnRjBkztHr1atXW1mr27NkaP3680tLSJEmnTp3SiBEj9OabbyojI8Px3GPHjunTTz/V1q1bm633gw8+UGlpqW677TbFxcVp+/btevHFF/XMM8/4663AAsy6AADPjqWpqakt/oVh79691bdv30C/BZfQMwDwBcIKhDNPjqWDBg1S//79NWvWLK1cuVJdu3bV5s2btX37dv3pT3+y+B21jJ4BgL8RVLQs2MMKZleEFr8FFpL01ltvafbs2RoxYoQiIyM1duxYvfrqq47Ha2trVVhY6PjLjgZr167V1VdfrXvuuafZOjt06KBVq1bpqaeekjFG/fv318svv6wZM2b4863AIgQXAMKdp8dSu6FnAOApggrgCnePpR06dNDWrVs1d+5c3XfffaqqqlL//v31+9//XqNGjbLqbbSLngGAPxBUtC7YwwqEnghjjLG6iECrrKxUUlKS7rz9eUVHx1ldDtxAcAGEnrr6S9rxf2tUUVHh0qUR3NHw8z6723S/3kDTn+8B1mvYj4ZMekFRMfQNQDAhrAg/dXUX9elni31+zKVngC807EezP3tAsQkdrC4HgIsIK9oW7IFFa7MrLtdc1JE3fubfcw09Z/m/bzj9Rtj1DX6dYQH4GjMuAAAAQFABAAC8RVDRvmAPKxCaCCxgSwQXAAAA4YegAgAAeIugwjV2CCu4d0VoIrCArRFcAAAAhAfCCgAA4ClCCvfYIaxA6CKwQEgguAAAAAhdhBUAAMATBBWhi9kVoYvAAiGF4AIAACB0EFQAAABPEFR4zg6zKwgrQhuBBUISwQUAAIC9EVYAAAB3EFJ4zw5hBUIfgQVC2qXBvQgtAAAAbISgAgAAuIqQwnfsElYwuyL0EVgg5DHbAgAAwB4IKwAAQHsIKXyPsALBhMACYYPZFgAAAMGLsAIAALSGkMJ/7BJWIHwQWCCsMNsCAAAg+BBWAACAxggoAsNOYQWzK8IHgQXCErMtAADuOtcrQsmlVlcBhBaCCgAAIBFQAPgegQXCFrMtAADuOtcnQlcdN1aXAYQEwgoAAMIPwUTwYHYFghWBBcIesy0AAO4gtAC8R1gBAK4J5Mnde3oXBuy1EPoIJoIbYQWCGYEFIEILAIB7CC0AzxFWAMD3gumkrj9qIQQJXcG078I9dgorEJ4ILID/j0tEAQDcQWgBuI+wAkC4C7eTvFa/XwIT11j9/4TAsVtYweyK8ERgATTBbAsAgKsILQDXEVYACFecDLYO2x74HmEF7ILAAmgBoQUAwFWEFkDbCCoAhCNOlAMIJoQVsBP+94FWNFwiCgAAAJ4hrAAQjnZ+O8DqEgDAwW5hBUBgAbSB0AIA4IpzfSKsLgEIOoQVAAAA1rJjWMHsCrAHAO0gtAAAuILQAvgeYQUAAIB1qoqTCCtgW+wFgAsILQAAriC0AAgrAAAArGTHoEIirMD32BMAF10a3IvgAgDQLkILhDPCCgAAAOvYNawAGiOwANxEaAEAaA+hBcIRYQUAAIB17BxWMLsCjbE3AB4gtAAAAPgeYQUAAIB1CCsQStgjAA8RWgAA2sIsC4QLwgoAAADrEFYg1LBXAF4gtAAAtIXQAgAAAIA/VBUnEVYgJLFnAAAA+BGhBUIZsysAAAACz85BBdAeAgvAS8yyAAAA4YiwAgAAIPBCIaxgdgXawt4B+AChBQCgLcyyQKghrAAAAAg8wgqEA/YQwEcILQAAbSG0QKggrAAAAAgsu9+vogFhBVzBXgL4EKEFAKAthBawO8IKAACAwAqFoEIirIDr2FMAHyO0AAAAoYiwAgAAIHBCZVaFRFgB97C3AH5AaAEAaA2zLAAAAAC0JVSCComwAu5jjwEAAAgwQgvYDbMrAAAAAiOUwgrAEwQWgJ8wywIAAIQCwgoAAAD/C6VLQDVgdgU8wV4D+BGhBQCgNcyygB0QVgAAAPhfqAUVEmEFPMeeA/gZoQUAALAjwgoAAAD/CsVZFRJhBbzD3gMEAKEFAKAlzLIAAAAAwk+oBhUSYQW8F211AcGk4tpYj5/LX6ABAABPnOsToauOG6vLAJzQ2yIYxRScVGT9JavLAADAK6EaVEiEFfCNsA8svAkp2loPv+ShqUuDeymm4KTVZQAAALSJPhbBhh4aABAKQjmokIIvrEg+xh852FVYBxaVfWMV5ad1Nw4w+KUPDQgtAAAtYZYFADRH3wy0r+kJ0IS+FRZVAqA1oR5USMEXVnQuvKQ6q4uAx8I6sAiUhvCC4AIAAADBjH4VwYCgAmjO1ROe7Y0j0AACJxyCCik4wwrYG4FFADHrAhKzLAAALWOWBaxGfwqr0SMDzvxxsrOldRJiAL5HWAF4jsDCIsy6CG+EFgCAlhBawCr0pLASfTHgLNAnOrmsFOA74RJUSMEZVjC7IjQQWFis4tpYfkEEAAAAEHYIKoDmguFkZ+MaCC8A1wTDZzeQCCvgTwQWQYDZFuGJWRYAgJYwywKBRg+KQKMHBloWjCc8CS+AtgXj59bfCCvgbwQWQYTgIvwQWgAAACvRdyKQ6HuB1tnhpCfhBXCFHT6v/kJYgUAgsAhCXCYKAIDwxiwLAKGEoAJomx1PfhJeIBzZ8bPqK8EYVEiEFaGKwCJIMdsifDDLAgAAWIE+E4FAnwuEPsILhLpwDiqk4A0rELrY44JcQ3CB0HZpcC+rSwAABJlzfSKsLgEAPBZTcJKwAnBBqJ0IrSpOCrn3hPDF/hzcYQWzK0IXMyxsgNkWAAAA8CX6SvgLIQUAiVkXsK9wDygaI6yAVQgsbIR7W4Q2Lg0FAGiKe1nAH+gn4Q/0sYD7wuXEKOEF7CBcPo+uIqyAlQgsbIbQAgAAAEAwIawA4KqGk8IEFwgGhBQtI6yA1QgsbIjQInQxywIA0BSzLOBL9JDwJfpWAJ5i1gWsQkjRumAOKiTCinBCYGFThBYAAAAArEBQAcCXmHUBfyOkaB9hBYKJ3/bGF154QVlZWYqPj1dycrJLzzHG6Pnnn1fPnj3VsWNHZWdn6+jRo05jysrKNHHiRCUmJio5OVnTp09XVVWVH95B8Gu4GTdCy6XBvawuAUAQ8eS4V1JSokmTJik1NVWdOnXSzTffrD/+8Y8Bqtgz9A1tO9cnwuoSEAL4Yxf4AmFF8HL3WFpbW6vnnntO6enp6tSpk9LS0jR58mT97//+r/+L9UKo9AycQG2uqjjJ8QV4i/3JdYQV4cnT415eXp7uvvtuderUSYmJibrzzjt14cIFr9fbmN/2yEuXLunf/u3f9Oijj7r8nF/+8pd69dVXtXr1au3Zs0edOnXSvffeq4sXLzrGTJw4UUeOHNH27dv1pz/9SZ9++qlmzpzpj7dgCxXXxhJchCBCCwANPDnuTZ48WYWFhdqyZYsOHTqkBx98UOPGjdPBgwcDVLX76BsAILjFFJwkrAhy7h5Lq6ur9cUXX2j+/Pn64osv9N5776mwsFD333+/nyv1Dj1DeOBEMzxBSOE+worw5clxLy8vTzk5Obrnnnu0d+9e7du3T7Nnz1Zk5Pf7kS+OpxHGGL9eFHndunV68sknVV5e3uY4Y4zS0tI0Z84cPfPMM5KkiooK9ejRQ+vWrdP48eNVUFCg6667Tvv27dOtt94qSdq2bZtGjRqlb7/9VmlpaS7VVFlZqaSkJA2Z9IKiYuK8en/BhL+aCy38QohwUVd/STv+b40qKiqUmJjo03U3/LzP7jZd0ZExPl13Y/56D54e9xISEvT6669r0qRJjmVdu3bV8uXL9cgjj/isPn8I5r7h2p+9qKg4a/sG7mUBT9EnwhvB1Jf665hr956hMVePpS3Zt2+fMjIydPz4cfXu3dv3xflQMPcM1234qaLi2/7DQk6ouo9LRqEpPkfeCfWwoq7uoj7/eKF/zzX0nOX/vuH0G0FzruG2227TP//zP2vJkiU+XW9TQXMPi+LiYpWUlCg7O9uxLCkpSZmZmcrLy9P48eOVl5en5ORkxxuWpOzsbEVGRmrPnj164IEHWlx3TU2Namq+/yWtouLKQe7ypYstjrersl5SYjG/jIaKugHdFFN4yuoyAL+rq7/ShPgzP68zl6R6v63+yvp1pWlpLDY2VrGxns+C8/S4l5WVpbffflujR49WcnKyNm7cqIsXL+quu+7yuJZgY0XfUF9jfd9w+RKBBdyXWFyjOquLgC019KLBtP/4u2+wa8/gKxUVFYqIiHD5Ukt2YMm5hur2fy+vv2h9X2E3lQXff0Y69alsYyRC2fnjjU/a8jnyRMLXV4KKyxbX0ZbkY5e87j/q6q7sH5xraM6T496ZM2e0Z88eTZw4UVlZWSoqKtKgQYP0wgsv6Pbbb/d4vS0JmsCipKREktSjRw+n5T169HA8VlJSou7duzs9Hh0drS5dujjGtGTp0qVatGhRs+WH3m45DQIABN7Zs2eVlOTbv5CJiYlRamqqdpX8l0/X25KEhAT16uV8ObcFCxZo4cKFHq/T0+Pexo0b9dBDD6lr166Kjo5WfHy8Nm3apP79+3tcS7Cxom8ofmmxt2UDAHzE132D3XsGX7h48aKee+45TZgwwW+zP6xgRc9Q+KNfe1s2AMBH/HuuIden621JsJxr+PrrryVJCxcu1MqVKzVkyBC9+eabGjFihA4fPqwBAwZ4fDxtyq3AYu7cuVq+fHmbYwoKCjRo0CB3Vut38+bN09NPP+34vry8XH369NGJEyd8vsP6S2VlpXr16qWTJ0/aonm0W70SNQeC3eqVqDkQKioq1Lt3b3Xp0sXn646Li1NxcbEuXfL/dS+NMYqIcL4xcmt/8eDq8dRT8+fPV3l5uXbs2KGUlBRt3rxZ48aN0+7du5Wenu7xet1F32ANu/0MkOxXs93qlag5EOxWr2TPmv3VN9i9Z/D2WFpbW6tx48bJGKPXX3/dq3V5gp7BOnb7OWC3eiVqDgS71StRcyBwrqFlnp5rqK+/MpVk1qxZmjZtmiRp6NCh+vjjj7V27VotXbrUo/W2xK3AYs6cOZo6dWqbY/r16+dRIampqZKk0tJS9ezZ07G8tLRUQ4YMcYw5c+aM0/Pq6upUVlbmeH5LWpsmk5SUZIsPWGOJiYm2qtlu9UrUHAh2q1ei5kBofJMmX4qLi1OcxfcdaMrV46knx72ioiL95je/0eHDh3X99ddLkm666Sbt3r1bq1at0urVq33yHlxB32Atu/0MkOxXs93qlag5EOxWr2TPmv3RN9i5Z/BGQ1hx/Phx7dy505J9gZ7Benb7OWC3eiVqDgS71StRcyBwrsGZp+caGo6h1113ndPywYMH68SJE5I8P5425VZg0a1bN3Xr1s2dp7isb9++Sk1N1ccff+xoGiorK7Vnzx49+uijkqRhw4apvLxcBw4c0C233CJJ2rlzp+rr65WZmemXugAA8DVXj6eeHPeqq6slNW/KoqKiHH8RESj0DQAAeMefx1Lp+7Di6NGj+uSTT9S1a1e/vVZb6BkAAPCeP881XHPNNUpLS1NhYaHT8r///e8aOXKkx+ttid9uB3/ixAnl5+frxIkTunz5svLz85Wfn6+qqirHmEGDBmnTpk2SpIiICD355JP6xS9+oS1btujQoUOaPHmy0tLS9MMf/lDSlcQmJydHM2bM0N69e/X5559r9uzZGj9+vMt3GQcAwC5cOe6dOnVKgwYN0t69eyVdObb2799fs2bN0t69e1VUVKSXXnpJ27dvdxxPgxF9AwAA3nH3WFpbW6t//dd/1f79+/XWW2/p8uXLKikpUUlJSUAuceEpegYAALzjybmGiIgIPfvss3r11Vf17rvv6tixY5o/f76++uorTZ8+3eX1usT4yZQpU4ykZl+ffPKJY4wkk5ub6/i+vr7ezJ8/3/To0cPExsaaESNGmMLCQqf1nj171kyYMMEkJCSYxMREM23aNHPu3Dm3art48aJZsGCBuXjxojdvMaDsVrPd6jWGmgPBbvUaQ82BYLd6A629415xcXGz4+vf//538+CDD5ru3bub+Ph4c+ONN5o333zTgupdR9/gO3ar1xj71Wy3eo2h5kCwW73GUHOocfdY2tBDtPecYEPP4Ft2q9lu9RpDzYFgt3qNoeZAsFu9gebJuQZjjFm6dKm5+uqrTXx8vBk2bJjZvXu3W+t1RYQxxrgdwwAAAAAAAAAAAPiQ3y4JBQAAAAAAAAAA4CoCCwAAAAAAAAAAYDkCCwAAAAAAAAAAYDkCCwAAAAAAAAAAYLmQDCxeeOEFZWVlKT4+XsnJyS49xxij559/Xj179lTHjh2VnZ2to0ePOo0pKyvTxIkTlZiYqOTkZE2fPl1VVVU+qdnddX/zzTeKiIho8eudd95xjGvp8Q0bNlhSsyTdddddzer58Y9/7DTmxIkTGj16tOLj49W9e3c9++yzqqurC3i9ZWVl+slPfqKBAweqY8eO6t27t5544glVVFQ4jfPlNl61apWuueYaxcXFKTMzU3v37m1z/DvvvKNBgwYpLi5O6enp2rp1q9PjruzX3nKn5t/97ne644471LlzZ3Xu3FnZ2dnNxk+dOrXZ9szJybGs5nXr1jWrJy4uzmmMv7ezO/W29BmLiIjQ6NGjHWP8vY0//fRT3XfffUpLS1NERIQ2b97c7nN27dqlm2++WbGxserfv7/WrVvXbIy7nw/AVfQN/u8b7NYzeFIzfYNv66VnCEzNVvcN9AywG3oGzjX4ol56Bt/XHAx9Az0DPQN8yISg559/3rz88svm6aefNklJSS49Z9myZSYpKcls3rzZ/PWvfzX333+/6du3r7lw4YJjTE5OjrnpppvMX/7yF7N7927Tv39/M2HCBJ/U7O666+rqzOnTp52+Fi1aZBISEsy5c+cc4ySZ3Nxcp3GN31MgazbGmOHDh5sZM2Y41VNRUeH0vm644QaTnZ1tDh48aLZu3WpSUlLMvHnzAl7voUOHzIMPPmi2bNlijh07Zj7++GMzYMAAM3bsWKdxvtrGGzZsMDExMWbt2rXmyJEjZsaMGSY5OdmUlpa2OP7zzz83UVFR5pe//KX58ssvzc9//nPToUMHc+jQIccYV/Zrb7hb88M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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plotter = Plotter()\n", "\n", "# plotting at fixed time t = 0.0\n", "print('Plotting at t=0')\n", "plotter.plot(pinn, fixed_variables={'t': 0.0})\n", "\n", "# plotting at fixed time t = 0.5\n", "print('Plotting at t=5')\n", "plotter.plot(pinn, fixed_variables={'t':5})\n", "\n", "# plotting at fixed time t = 1.\n", "print('Plotting at t=10')\n", "plotter.plot(pinn, fixed_variables={'t': 10})" ] }, { "cell_type": "code", "execution_count": null, "id": "ef9b0fcb", "metadata": {}, "outputs": [], "source": [ "\n" ] }, { "cell_type": "markdown", "id": "44d9cde4", "metadata": {}, "source": [] }, { "cell_type": "code", "execution_count": null, "id": "ff397a04", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "0aaed6ac", "metadata": {}, "outputs": [], "source": [ "\n" ] }, { "cell_type": "code", "execution_count": null, "id": "6308ab81", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 12, "id": "61ab8f88", "metadata": {}, "outputs": [ { "ename": "NameError", "evalue": "name 'truth_output' is not defined", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", "Cell \u001b[0;32mIn[12], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m truth_output\u001b[38;5;241m.\u001b[39mshape\n", "\u001b[0;31mNameError\u001b[0m: name 'truth_output' is not defined" ] } ], "source": [ "truth_output.shape" ] }, { "cell_type": "code", "execution_count": null, "id": "127968ec", "metadata": {}, "outputs": [], "source": [ "predicted_output.shape" ] }, { "cell_type": "code", "execution_count": null, "id": "8483904d", "metadata": {}, "outputs": [], "source": [ "error" ] }, { "cell_type": "markdown", "id": "a6ab97e4", "metadata": {}, "source": [] }, { "cell_type": "code", "execution_count": null, "id": "e8c09bc9", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "pina", "language": "python", "name": "pina" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.5" } }, "nbformat": 4, "nbformat_minor": 5 }