{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "01c8656c", "metadata": {}, "outputs": [], "source": [ "# Import necessary libraries\n", "import torch # Import PyTorch\n", "import torch.nn as nn # For neural network\n", "import torchvision # For image-related utilities\n", "import torchvision.transforms as transforms # To preprocess images\n", "from torch.utils.data import DataLoader, random_split # DataLoader to not overwhelm our RAM; random_split for our train-validation split\n", "from torchvision.datasets import ImageFolder # ImageFolder to load images from directories\n", "import torch.optim as optim # To access Adam optimizer\n", "import numpy as np # To compute mean and std of data\n", "import matplotlib.pyplot as plt # For plotting purposes\n", "from sklearn.metrics import ConfusionMatrixDisplay, classification_report, confusion_matrix # To show metrics\n", "from collections import Counter # used to count the number of images per class\n", "import pandas as pd # For data export" ] }, { "cell_type": "code", "execution_count": 2, "id": "18a57566", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "cuda\n" ] } ], "source": [ "# Define variables\n", "batch_size = 16 \n", "num_classes = 25\n", "learning_rate = 0.001\n", "num_epochs = 100\n", "\n", "# Check if CPU or CUDA is available\n", "# \"CUDA is a software layer that sits on top of NVIDIA GPUs, providing a programming model and tools for developers \n", "# to write code that can run on the GPU's parallel processing units\"\n", "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n", "print(device)" ] }, { "cell_type": "code", "execution_count": 9, "id": "dbc27da3", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Training samples: 9889, Testing samples: 1431, Valid samples: 2815\n" ] } ], "source": [ "# let us solve for the mean and standard deviation that will be used for normalization\n", "initial_tranform = transforms.Compose([transforms.Resize((224,224)), \n", " transforms.ToTensor(),\n", " transforms.RandomHorizontalFlip(),\n", " transforms.RandomVerticalFlip(),\n", " transforms.ColorJitter(brightness=0.5),\n", " transforms.Normalize(mean=[0.0250, -0.0876, -0.1820], std=[0.3720, 0.3962, 0.3967])])\n", "# set dataset path\n", "train_path = r\"C:\\Users\\France Gabriel\\Downloads\\Grocery_Dataset_Sorted\\Grocery_Dataset_Sorted\\train_sorted\"\n", "test_path = r\"C:\\Users\\France Gabriel\\Downloads\\Grocery_Dataset_Sorted\\Grocery_Dataset_Sorted\\test_sorted\"\n", "valid_path = r\"C:\\Users\\France Gabriel\\Downloads\\Grocery_Dataset_Sorted\\Grocery_Dataset_Sorted\\valid_sorted\"\n", "\n", "# load the dataset using imagefolder\n", "train_dataset = ImageFolder(root=train_path, transform=initial_tranform)\n", "test_dataset = ImageFolder(root=test_path, transform=initial_tranform)\n", "valid_dataset = ImageFolder(root=valid_path, transform=initial_tranform)\n", "\n", "\n", "# print dataset sizes to verify if correct\n", "print(f\"Training samples: {len(train_dataset)}, Testing samples: {len(test_dataset)}, Valid samples: {len(valid_dataset)}\")" ] }, { "cell_type": "code", "execution_count": 10, "id": "f953ec35", "metadata": {}, "outputs": [], "source": [ "train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True, num_workers=2)\n", "val_loader = DataLoader(valid_dataset, batch_size=batch_size, shuffle=False, num_workers=2)\n", "test_loader = DataLoader(test_dataset, batch_size=batch_size, shuffle=False, num_workers=2)" ] }, { "cell_type": "code", "execution_count": 11, "id": "838d7318", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of samples: 16\n", "Image Size: torch.Size([224, 224])\n", "tensor([ 3, 7, 21, 22, 21, 22, 3, 2, 2, 17, 5, 19, 20, 24, 24, 0])\n" ] }, { "data": { "image/png": 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ASvfrFrLst3JxPJP3DmA1LaR50Eh/3ihA1VNcXmwFkHHPQgiOFvvTYtpHmtAh0TRqFamlZtwyDwu4tZ9D0oUb8n0tuK8F4gRce78R916xVb7k/LY/PbU/NAX9fdXoFk/6Xd1GrYwHs8SqU5cSyQgM1NOScuJaYvBwVcHJ2UmEbR2zgXUEi4oPP+dd/64eyVenaEt7uVGAasGimzp9Hw3Rx8BHYhwMtrIJVlkxoTO45FYQBpjiZXADhBBIZOZgYtUgJ11uviJPION9nh6EdN35uABNBYfA2KvvaXTF5ThWeaz8GmJPPgGzHXSr1teDvmoBVJwGgwWc+gvxQR5Xu9vvTYpbugUcQSpuOyvSRkYsUMZG1n2vq+C+H66JsYTGBM8cJ1ayASOTrx7/1q3ZOlH3FM6/NZdQ7Ou0a/oJdgqvIY1rA10u/GzhA5YqgMpAqj/ayvxwIwf9Wl2cdPXRGjLLwBYKJEww5sNlW7wm9E2GrN3NrI9R7yvcqWpE4A9dcFkMKcbFGGdKsaXQRwQYs8zcgnJ3n/2ezRO2f3gCy6+p2m/XD97AVq09gFSOew0CfiJjZvhyBwuq3er5Odfg06Nupd+9dFfgneWF3FscydmdA7l471Cai1b6R630cAFK5ekhzvo0yGeifsbSMBx3xwg9EMoI9vfUnRcnPD47aVCH54GLvw+w/Y5g91270ebeWb7u2bdaIag1oXcmuwDVxw7rBe69GX4ybT0Qj9JBMhhWJ0yWiceOYhOTAz1QlnyiNRda9roYs6w1dyJ2U3efsYDwMGLCi6vqHXJjtVJNZre+4NpsIqS5XhADQl9ll6D9Ya43/hVYeeFaCiuKx0outXKf8p7GvvZFQd2m5LIIx6kPZfNT0ax6WFj8YY85Uq32in6JD3I8abTqm2t+9/s1bK0j4PqrJ+Tii/EmphCrswCvcfflY3FQh2a7BW2TlDu11O0ap1c2unTt2YGcyhgXBk70wWIOhImRhInZVl1SiV0Y7kM8k1KzdaI20jlnw2LockX0BKBiSznhs1/xDEZiBY/HKFL+m1dKABsVMOCqA2iZ288sQPtmbg8XO09qW27hlMkg7vaj+4+9rsDtrWkduDUk64eIfdO3YEn2uhhQsJxPsgFtvZvJuJrJuMV8kRmoxa315zoRo2q3iT8eaSEeF620yPl3Imnkh5ELwHhKAtzO/PTUgpTTvxNa+3v6o0yxshfSvKIjAflCMHUs72OaI/40k1HzPZAHZXEpfo+dmlxR/rcFCBtpMBjobtTPGJXPkzPzjHQLdG1St9Uq0RVNngG1Dc56U5cfLICDmTIBAVIxNsQBpNZKHAPRGgrAgZiXTWoZqN63y2M+U80Ey/Op5kzw97wIyEy87CqtFgHqFggnpPugALtwovgZWWHuzkisyRQ79MV1ZAaSFVhZW2oFJ599oOhr7NDp5wqEu5ZgedHhAweH7aqXcUCkRWxCv8YaK4ya+jMfkImgx+7itfjKPlGq8YO2YsyQMKNWrZF5JpCN9DjwEVakI18QqAeA45aWPhivs1a2h41sD8CCnWS53MjBcl1YKjwOJnnNaZJOep1W6+uy8YV9GMeiZWiL/V0KPnKMNDeK1o0Pcl3lJ/fiLsQlij4tGbegGBuyeJCBE97D73hv6/lOcMlpjCg4JBOD0C1F7f9gadm12HEYlyHlHceBiy8SMOYNUhdsf4dxp7+bKxPvIedr0W7lqF/J+qiT947O5P7DY/lC+5zI24hRmQWvC8y44CPYDPn5iO5AEmwiUHE4EKAIcPq+xsJsDlMiSIh/6SO0oTcCoY/r465PF0gRrqN7m52T9gkJod5j5lazB9Qo3+ZWG5QkgTiQuzEQ89m3ROJEhxuvbiCu+G1lytMml2CYyFIsJzKnQkJqzr3aNdAUVLGY3Y6aPFKw+wg+cbWfLCALYqa2V5u6M8n44mSce6+87nQd7Ps9Iy1ZGyV1vKC6JhZg1ZbgKtSv0pVYLMfS3jv3h1Zyxgnu4xN6iqdVQeR4/nz4eKryApOvvmpU6v/KZIiGyeCT09gopVh30XWV51ml4RMWST7B2/nA3ouT7t7O8UyHYHmlduwBVo3nVBZUZLumazOw0sUa0iR8oQWvAwBqPBilnyGGgrgbKfZOmohPZZrc3M1X0cxpZZkxbC4xCSAEkKATRJN4QU7xz9LvabJ3e8VdeJGGXjo57HNaUpGqnsDGY0LKskMsygGI7lUCTMq18r9TqkG06BIA8z47+CQiBtIV3Jpzdo9ZYYOSSbRXEA8EC9GZiPO2k3FxIbOTUaaXGnncHsnqaCHjg17alUh/ycR8X2DX88F+x0JhMSWLrno+ksEb9k/xrHhjP6AF9XSAFHuv8EwEVQIy8PighVWuTZJgJFmMZziaafBXE3ZToJwByIoVmKjSUenB3GeasOp5UInUgJVrsJg8ipzdXoma7ZsOoD0ebqXWO0gpa4JtCVRSWm6BDZ2AStuej5oGWVjtFG6ryj2jb++sxDIox/yt1E8VoSNNapogG5iIOFaxuCit0ORS4MpOFxvx+vL7GauDOyKQJ2zfPXlU7Iv6oYrmZ7oX7J8K/GsyhX8/9vWkOXaNjINT1N36BXmiA6nGd64nUJ20MMbUExCa4tb3rjPMAIo56ilnbeeaA80xuGvyZ7gEc/Up1jmhBws6a8ckw1xkXE4yHQ7SqXWIibQpqebhuvLkbey3RMcPAG17EyIMZEg2oBUDMAIlG8BENQeSJeyx5Dkt7kWQopVG65stomvP2sxcJnfDubWGc9OSyvfZrL14bfWwwrdTHJRWV0o9EI134drA6sO58Enn1hzaQksMlpNS6nWNPKXvzLTPEL/aysnsSk4PL+SXly/I5aMbMrStdOfmStDkX4/LXsPqLx/EEJNKc4tShKt5kc9ZJGTYheY5MxCpPhogFVfx9WKSrD59gj3wC3cFLSonMACcAEzDwmNQWCGmlbb1KB5uzSmqCQWFywirW3+gfaXLGT5N3uE7SUJo/yI45cloIBgg1ndKQ9dV9HZU+aSYqxJZbwX4hBWNtW3X+tjtV5phKYCVm7UngTGBQ3u99ZCD7UGeKAZPq0V8ur3x/fBqn/nETEClWy8qaKTvOBV7XyyMf8fYGvsstc1jeOkBzNYUwVjzz4Ir09q0x61B1YjBpHIsz8sZf8l9Z3RtdVtxFe5xDAObsNioVhK7xq0nF8MlDeIEJLIScoWE+GsHYz4wyUB2H2FNNbJdNrK+ISI3Blker2Ux26olhQ3AhN8X3VbvVaZq2+/6WDXGots5Ha0gt6hgdQIcCEi0qrJ15cA1mlWRYlMpTrVLmHi/zebaRlZIAnLw1HO7u80sm7Lt+0gUJEIkdQqP1UXr0iw0V89wEO2F7MJRoF5qw97e13MD+JpW+mnwVAd7JuYyyGG7lsPn1nJ+upBfXLwil3cP5Go8kv6y0QRgR7nC0omu+/ToY2yP1cJQQdIYxryGInYb1NC4AM3pGz4HTB8JkPLX1MkB2dPkt8e14e4KZSUpScJ19grFguya0xuSqXTVEjdMUiEfqxikcbaNagvXXVe9kud7TJ6kAgWIFJB/4cS4zzIIMZn6vXT4feer9t/btjAwY5fURIMIUAVIVL/v3M9qDbK3LRWQJcs2GnXT/vbu3YLFFSm6qY9p0fFhhSmk5/PYKONWyWS7/jxKpEhKU4nOmOOEiVgRLxlJpGkopHbqrxWhgpkS6bo0HuVWOinoycr2Tot5hpWlXlhZTY5rgjQxLESa+aSuPrrv2F4y5ZJN5NfLCVvZ7yF3KHdRU1hWBmoGUhGcYr4Tm59oEVzMBLD/oACVe9zUIlI7VHcvUh3qb9gMsO9MXIDkKyuvN1pZtv+UmI+wsrGZQiE/B4A7e5MuQC6OW8g5beV4tpK3Tk/k4VZk9XAhk7tHsWDRo4Tk33QBRbvKZyn9znkyPBckNOU8PL/SsXpOv4I78DscpCr3klsANlH5qrnvstCp06U1/nQAijmSYiP1ehfQbN5wF11x7gxOADlMVrgR+zxDkWaeaPAuhxStD6pTpLECNQoIvlKGiXp4sKSQZ4UDHOWcKP1+fWqnibNPCnbVk0ZKbPOeSX7naaerI5ARCnYe9wngVIBVtECqe5posHQhRKDRWMp+JODcb4ZQIEn4/UxgRmuIKQV+XKWzB/eERgTiSlHvhd9zxDBtaevxD1ptnKx3rUwk+prvc5Jh9CRrTfilMCws8lK6B0NZad3VteqEPbYps0FX8/pqJ9PbsWmkXU3SXyHvbrQEcR9XOm2SrZVEgbF4c4G9dP+cQOFMBqWeLxsZDkVmy1GW800KsqOdTN5lrAd9vYEVotp6dlxrwn4Kd+6yHGNKrrnk3nUL08c38hB3v+0uRVLdr/VzVd90KStYOKm9DojXWWRm6ZS0eZIwCD68lnxNtjEni/Guhi5IGeWgXev1gXCyFXM5Mh9LiQp+petmm9qqccyukX/59hfljeVN+WcHIue/dkM29+bSrl2Kypl5Op0GF3rKH/R7nwDK5xIVZta4fRnI1fkmZVf4vGUrkdxHm5AK8VSDlLKTIpXbXgrQ0fgHfOi9u1WaRJCAmy/RKMOWYljhbybL7rUYPFFVQYqMQCqN0wrTZu5ZWdF1EhJjzfIJeVyF8K0dU4EKzJ8N/NPIXfHVSwCXHRDaY3XE/fYCbGyo9rlPVMXqPg/kHXCq28KJjtZnrdhQtTsd2xNvk/6c9vE1lkqx+vdu7Pa4GVNOVHVOrsZD+yNAmksxg43uorFCm50j+O7c8zh4fFFlAOFvWyZqTn1wZh4llahIQKtEbwliNSBhcNwyh8pvuMUzoHBvsliUDDOXn+UTZZo3FSi8/0LeH+NSNFeolmJANcpiMcii3ybZJ2wkOdBqIumAEz0NNPt8N9+IbrJMIrE8IyWZ+DHoQtSYV7Ckim4vp4iveCvb9P4HypYS2x2PE6zMcI1xA6vPFhdTfvTUBWg5W3hFei+Azyw9W7ZwoUhbS60urGW7tdxZnMmnTt+V917ZyNnRoTzoTqS5bFVZvcXgcam0xOqLz2YSo/aXfSapd4xdtV/jGNzEUbAA9xFsv48CSGlMJk0k0Z0WqNLzTssIKFgpSGUR1P4q3JRox1aIxOCqTsBVyr8uhqmHB0Vo5WBmCm8ufbHHYtPBwFW3ncNo5bayTZZQLbcPlx92U1oniSCe5a19kyesnc19ysmlVbSn4jTHr1W07fgVXleic+9RLk/9aMvDa/cptgBc2cJ0SyYumAP4ltZxBqJxnw6f7n/NQ+efpdVliFHFc9vnAAMXhYW4Jjt6z7WktwNPga4/jVMpFnhgvHXVEJT6EC/9ARcQREidCKG/N1hwmcVWyu5gTLo1tbGYFN19NsNXyWSMl3LsqjWZpaTs2slonSw3ai4yLUdp54MqIEQLQ0EKFp5aBlMqp1Erh9vwpjvPJnMbUpMG+JNFEpQoOCFbYL+VUSdsPH/ZgkkEDbdGyzsSBs1XsD3Z5iuPHukfbDNvetQxzJ8bwMCigu3Wq1WVrSZLLN5K75YjPseYWwd17W2T+1gBDXqfbSN35pMc9Fu9R+/dOpa7w4FMD3qTWaOSeuMLmUIVpnLz5UsotrgQTZYXSRf6LLnEmCrPiExQaH/qQcoBQNlGGoX0iZ3Jqdox/hkehDlUmr3UBd1NXhJC3Tv60DpZQipryrXjbLFQWll6LKzQXVDRZGCgKpEtIDOBXYvIg47Jac5ZfmdlgvbCd2wsRHXP0M/rP9TzYz2Dgt4dcoXK43IScGvP1a+1NSlrMO16jUUUpIsqC7ZQLg9b2j/duypGFAc528P2RjkkVxbgrdBVYNo53pNgKVHnL+ZFEbAIloG1uftUZlBJEkuMSfnvQxL5rRYjTlhJi6k6TSIyGHkt9L71GN/+cWeK2DodjVhF031lX56aUTC10R3DbbPtZNx2GizX+mJw9bFjPU+qyIuKEW0wSvkMUZElsPvWp62sbonMbqxlcbiWg34TJma/pKmVx5tlnqKT/BBlhXKKyFrjJaR156Tc7KorxxP2M+AyvT68O3peVHLJqbAKa0xlCxVUDgMJIyfQdUY2ot3yTNIwJuIuwSPlL6FKS1i9RGkn5quZ52tUUkPK//J7YcBiv5Nd2LsU0zxQ6uHqi0CJti5Ul83lojSx1wAf16XWZzvKUbuSW3Iut7ozuThcyIuzx/Kle7fls2+8JLN3OukucF9FE4DhilOyGGnkXrKmKLnhKhNpDMe4LXdRrdFSlgyLfO2z3a58+kCKsiypjhEfDGbQE7hohn7w/LFwkt3Jc+8xfCI1lh8DhbEMQPhyPF6crAka4Zg22cICdJCLDXDgw0SpeButh+ISKl9HDVwx6zzuF62kaAUFliNBKf0erK29W4knO9uOzFHcNwJvUswoJV3Yv7ZACVYTAYrHDpp8MemwqIvzQbZIbQ8Wkj6M8TrCMl7bnQLJPkv5DSTo8b7jSVZgULV9xHK81Ifm1WbnUVyhc+3DTenMo1tatKLS7oH4Ea4pj4GqI6LFDK+EUs9F+vmgMk/qfnJLxjw9Np06OTbnH3msShIZwRZNsfgh84+0uzQWEzwSQTw2AZm7vjS+5fuVllcetFGhsHZwKBj48WO+lb4Tc7n8Ycl5UrHHKtUMn6FJJMnySt6f9KoCCKcgjSQE6txfLAFSHt/OSXA1h2oX4mDbBLJITD7oNnJxMldJpXeujmV1caQiyO0KzEh69xxIfD4tcznDuN9PYC3JwZHg7OrpHzAs+DscpDyh0CwprBJH6xxM6uy8BGIZ9VUrmcE8t5B04+TloyIyxdI597mFApEFloiLQCS3gx5HYyoeA8OW6OpcfYeZIVoSWuHXXCAdVAoASmnFa5V8dcMyh1V7Y9NCyG5/J7psPhlBmBA8dpMGo7p8AtkgFXT0U6sWXxmnSgN6vKbv9gBBoUjBfg3BWrYvgaGvOMf6AfL9reKuu99ivSmriVe4/vjFHQai7L4ydlew9PnQjh6bYvgmPolh4gdQKSB5jpOqWACk8F0nZcCFp9ehuVGdAhW2vhtk1g/GMmO7dXKH985yheLzrwKzqhvoq1qUSIgua8p0KblI72hWlnDFk8zcKIFqOBAZjiY5Xhr1HJNiEk9VN58nm/oE37eNqaMDlrzzNgqi2TbY505jbhO3SDhIpIxmki21G33jeT+ocBHOtHbJk3gOFYENCcnJ1bj3kKVWINuBJFwSKOimwzuWpG0eGFDLYfUQiMbAXjxsV0kVAy5AdaGGe22yTahHZXT0daDe032o4rXSycG0ke28lcPba7lzfC4/231S3r1/Q/q3Z+oWbvHMrFko0eLtSVvUE4E5ntKCNJCatERIiFtqz6bwhZO4qHzyNIOUbroC9dVGVEF3cBoXXkE0TqyV7lRkcMWxvDeHx7eQ7rBjRRgxyhN7sW8sFMjAc7JaaHWEAe+JgflkeQIFiyy5Ij0+gJvdrW3FTZ2/on+u6TfTbgtBegJEYgpxsb8foGKMjd8tXIBxRV7/HtQfovWWFvUBJHZInLyHOXSSdQH9P92FJInYVgJVjE3FSs3R6NzzDO2sGGPpkGiRXUOWMc+WmwbaHmcQhgkvjSlNDmpUSd1c0kjVtKRcTE4AKsSs2Ee8n/Z3KEuPc2ktMfyM0sBtDKuc4sr+3HDxY+QUti+U7TD/mj0zXgV5WJrKxKwzAVTEnFj3CFZfopxrBdx8HJMDssNB1ojtNzHaUqGh1v/LQ8zz1pL1UCYNp7yoZL2Y64yAl47hdgmlmHJuli2CsvhsZFpaJ+T1bf48qbyntmbriSDDveN3lxo/MoWJLLUrbs2J3Gwv1QrCZ+fjQi7Fc7dcoYIlFbcOfpvJlNN5/MFL2hP8QM446a6kXYzyTc+9KXcOzlVKaXg0k/EhAo2cX7P3IpFmuM6pn2tukeRUmarpWfmA7orf0SCVzMiYsOu9RiYfhGLTijmu3k1hqNyKybMiEESpoPLtEgeqHCt9K5VEyJq29kEpO5NyC9LSvDpJIB3kBpj7BlZkq4K4mY1lX90T6yra6v4UHq6msQfLov7h92vQipcXGVzpkFwc7FtI7XTo/kVCOg8TrkO7EzuP5IjYH/EavHBhmmg+yDOz07b8/aR5Fq+l9qKFeKA9876o2ePP17QGfLalW9tjOFTX179zwDwroxtqMm8KBAtYae3G9NOUfq6sPoKTty4mnfNGqFalx2vVHW076Mq/zyCFWBn2LEHKcr4MizFFhm7xiVdjQ17qHedjYizBICfiVt0eQCYZujoUzJrg37SyzHpxkAqagLQ0zD1oR0uaezEuxlpYAYBY54rtjYnCeZkn+fwe+0rnq76r+oCqeDElaxSbU6TkRnsli2Yja+lUYQL72OfqzPMjIUm6Mx1Ar0dlLEI7yibEzdCWo86o7V9/+x25dXQh746HctUeyupyZjXncO9jaXoXpK49HvWijmscbRPnsngTvwKX+u9skLraSrt1ikiK3eSgLuWGGLtKYOBCiMmf6jp9rPS614S3ePTeZFhbTftkGd1rfuyYR0CracfUdVdR8h3yY5aTZ+A6uQbzOeDwh9vPQMqSKxMA7RsIsSaUl1xIKtMBlKguYNdRxnXMSuQDXp6k8IIEl2a61DhguUrzSPe1hdCqAR6PoxZDAKQEgqnmUwDaVMHX0Ywu39jE6tZEF+KO5ayFjKpu3jd+IkjTxUcmJ7+Tfnxnj7mZ/4TA06qc0rj10hthgaHutB5Eh90G4Dzd1aQlXxpU3qUnAaQIPb+RD7joS9az50Qlb4DGQc2FA0HZ5mQr3THQzywiAM5qiwnWUBfgRTV0sh+NomCsPbL/bCjmmlpKueck7xEkIyRZZzPWQvKIOVQgG2UxO0ojaVVdKIW3W1l2G6/dRGXz2uLiMd2aS9DpVlBKSubGNNp9q6hMEIGLLS79eK3Id9KKvxC0dYuNquvY26weMU0+2cr98VCPg0q/UMCAyw/fza2xByBaYQQoWE08Jr5Xt/a5/kxOuktZvrKRXz+6I585eUkuv3gs4+PeiEn+7GhuU/QGtaFEB6vw2olsuFACjlJvI12IIt3XcmXe36pN3Raukqhj0lWaVT2CLr59q/I9YyrGLAoGy77z7nmvWLEn6yi7EkyVec93w7I7KwDQx0W6ewadohSDT2DGSoQbZzJ1dFoVLLYYTxUn2sK35Wu/oNRBYkIC+hpgeLwnd1c+B3cMFmIkOV7rHgxvhaVr6nc9rANdjCFG4KoZfwVZQvactwbVfS7H8N2ibR9k0+OF9XaobpreY58kZXwvS+/vjZUPzXbJ5cLNWoUPrrX6QpewuEPOXTFOY6XUGIMK+8bmwwM5b6Sdw4K3CbBQ/baRqfvGYoeFKzJVDfbnI1lGpbuM1ildgtH/m1xxlBhySjrIE9gALDMHKlpS2S1Iq40xIybcliDF49RU8Wgt2XEKW7G4lsLySy7IXAKEVA7K38Yu7/wTuPHQUrWyUrJBBlJCk4F6vla6T/OgZev9uyhbD6CcRrmzOJfzo7k8GA7knUe9XMlCS35gfwUj3q5AishWUxjbHD7huS0eGQ9TPP0gtYIA1cxIDlRrAONo4WSKoGKQlM+byppxFwnzrVhpMrvY7Ps7YFdPopzIucLWwLjvx2xr0uP1PTeD40H4eWprVlNN7sM0K4eGYPWyGaS7suA4Qhjq6tT8LSeI+Ggpy4XU7c/JyOlNnmUvMlcuKgIBjxdYgxEoUt4RDbh4qhir4sCuj08vKZNr4/GpearK3KUVZSB1/YOhn1QEjHSHrnNPVv1XvVWidwTqIFeV/P3FfqFS8rDv+FZEMTXUP9PnfgosQQjmP2qleyhy+O4gs3N38zE+6iomuukz4O/xLGsse23Rp1YX60fNGtkcNTJbbqVdbFMAP91ut3BM0sdKybN8BUVi07Pp4MB96VaLrrysTuHuR2UnZX1Andq9ZA2o+FF9HeeGKw3WVB2vYteB1MAqvHSHRQ8BAY3vR0ul1u6zR7UU1jU3XmbtkeVo98z5d6q9Z7JP5ha0LRZbVEHdqbP3lGBhyfxIPuCxQZzQmGUzaFwqq8E7OcPjcg7HBcvpuL2STx6/Jy8ePJZ/1A3yzsNTub+6Ld25SHvuJCS1lpz046WSONbiWm/nEUmMQF+wfxQo6HUQIdWASrGg7I5T1p2z0BI4BfYegImBUvtyNTHUvb9v0qZbDK7DMIg1gbL22xbCav7lmNTkFlSS5knv+XWnZOG8ElY6Ojwvlg1qprUqXkQViv0uwAyuFXX6CRNzXEEl4gnl/4ORVgARLbPQx6mfHUR1Eqpkkoq5fs/EX4DR3s+m/cAXQHbfOoSve/PNKityp1vrdl7z/cJqSwr2Dk6JS+0UZq8hxgUQH3ZVtoYLZT2ZO2Wd2VftatSk9f4cCiV+wYzjxjKqACmmUXAyYfzB3adZ87KRLaSQdAYBqy7Hn1IcKpTfSLTyADi5a7JcES0cm/xjXabKI+oxIzIHSYyoY1F06xF8oqagO1zjcH3i7dL2u7sy5Rn6VdFKipR3kiAMoIaCIUimXy6iaD92LYPmNKl4rOTAD1tsOV12DrtmnMdAzVyG5q5FTAoQpfMa+tFbm6xJpeFYzuHVaO5DJALPBLGqlXzDyTtyp7+Qf/5aL6u7S1m3C+lWNv62nUi38nHHpF0fk3SrWx5huTDbWdg+7SCVYinMl/L6UPY8WG/pLk6iIIvNFqplzpKVgg8zaE1DLs67K8aYJj9aI3hNSWxVnGmf8GvhS+Ir2UvV+1LJJ1GpAlJJeF9jBn79urqxGMK15SlCG+J+ChhPHFChLAotJP4dg6rBqormP/st3YNw3an+UVwk7GlLBLvr7lfxWaCMFygUD8j2RMJlXBNV4F1YWtf1bThn4R4hQFZisBnA8hin9QiaercONOAN/p6kuxKZXbi/fzWpnqPtg7GBzwcv85LjmokgpPE5L2qI58hLzZh4HTstEpKsVLx62MEu8/wtMvFiQUG7JCaq7lqkbgAn64MkBRIOVCpKJ1eLApF9p+MvJITTbabK686UI4DlfCECiD0XH7DWZ2opwcQSc0vihAKrr9K44M0uPRAnTP0B+5m0kV0v6BJ0ZVJV4rBZ6+uG1pVaWLhWOw4fCIrNzoLbd+bAxL5Qcg4IFa7tRvBWursTSmg1Ik6ItuG4rx7eV3HaL714Kg8nkRUq/aowre+7qcZr8GwkMtJ1/fuE5+SpAinpe5H5TMZF7+4Im5RBx07kAYxss3P1wU1mZjI7Y/FAIwbUAKRbcFupK6m+AXwAtQZVYPjE78Vj7kl4NRC1UtppdtTJwv+ul3cexPZlq2v8jdKu+6RMkfOZglQOr4F1rCJ9HuOfDME9oJiuNTICfTYniUL/ZL0lYq2/t0Mldj93Sn6t9L6KvgmAGPv9WjdccD+QBbgDdhF44n2MNblSY8PiYs9DlsdV9Z0wXpJMTPCyRFdJzs73uj+uCQhLqKWlhNjj1n5PFVKZIOnfT8XmfPHQOLkmub1T/3kJGwBTSpHgfXWLTq8N8IDIOcAJqhM2VlZXM1ldNDKfb6VTksQgc0/q1XwoP1XW5rPJmGoQSYswkiYcZOiyQzyJnUlGoFpQbiGhFIgBgZMbQBRoLWeLrq16I1gAIPTvEN+5fnMXIRiECAvEgo7+O85vupvmbqOrDsACVQiC17LZ6N/LZiuX00zJELg4tfq8zAZAZA2JI8b6GrtuWGegWrAPrMw9S5NYGQ+zmpyc0jRy2qLaoREnHo9LjWtdTTM5aNaybNZaSgXVkt+BUvo0089wzNP+Uv7A85+TLx3cki88f0e+8GsvyOpsLv0ZKv7aPUGsUy+Z5DI+auoWzGQosqwb5GAqwbR5+kHKWHydTChUqA+ZTwopySxbIqyOW6ygw8NqY48U2+tOWLqs9u7iy0IdjDh/1KdLs9O+36NFQKn7QKYodAlDezhDOzMQ7YdCuk6KWsLdY3PcP4BnKoEeDsqE1B3h19rqCJN8jHMlF0o1+UeX2VR/P3YtgaDap7BU6sUBV3KpxHj4Gj+jVFDM8wj3sHa71SvAJxiTey3kaG7TcrMyGeXQcW9NAS72HnLfnA0FQHKQYsE6ez+oR0Tra+f6XZk6SR9lk0YXaTsXx4ESbwY9ApMnjDdquY3nnbrRN24md/Pscqux0I6cgYourJhjpJ/siUmxszonXJB8QDIEASmWgU/5ShWFPeczoZszkXyfIZ6He3bvGSvQad3OyKPLMskmNRCJRQFCo5wTjE0nGZbSRhl3ACqrT2WgxngVW9mQweikClyPJQCbTiG+j3NqPxQ5UbDAzAVo+WcBwJq1kknOIbooooDVhHjVFooXfi24FzeaK7lzcCbrppcHN4/krB1lfXXg1R9E5MoXYmGuK+JN1XyZ6OvXqdI8VSC17GU8nOdChT4JsVaOEhniSjtO7oHooB9pQjAfyuDG4leDuGjh7kuNyZ/TigMwKqMdZjHLbCRrpjYp3FpwIkdBomDbw4POvBX90eWlmylwu1xspMFkgZXXgccYKoHanPHttHt2jwakg+pxjPPUwU62KZbPcDdKCjpHd5Z/zT2RZX+6ZbHXitXjhFyLYp8MrmkirLuWn7kAa2pXCJzvcyXuAGkN1gUasn9CXgk+YO6U5rJ5rhLddAAf5C1pIUKj5iowOVW3v3B1Eax1QNdFfMhjrrnES8XATAnVuaZP4T1gsDvq9KlLj6zQTDDiWON+lFSiFbW4P8k462W67GSF7xxsVBppH6LvZjqFiT8ou9MNt7O5Hl+jahXZeiFAYRKG9ZTedzo5b09mCxqwJe3AxogF6sYKZeXZAcm+co3dTIDIE3mkgZvqg8WcYKXgXCtPqsUGKwng9Fx36aAistJKu4McqEyswcxaLSaz1iy/yktyhARjs8jUWSg9rE/vv6sJ8SgDsq0rWxgATXKAqr39Wl2ob8mRXExzuTscZ9JFM8i89cKRHhXDOV9ePJTb8wtZv9bJOw9O5fMPl8Yyx30/47yXn7f0SmKau+8TIemjkic1olYUS2N4fCZn6+fBZhMHXV8mMJvFRiN7LrvIru3AyFjb93HlH0rgqQzC4NZhQFpP7gdsgssPsQNO+LS4+KCpS9FVCGo1C05eCtbIiUFA25tDtYj0uU1kKtrupTDsLPo05uvlat8ny8S+c9mhNMETRKiUHfuEMSteBvs9WlpR/SPuGxf0YXAzpy0yhZhztaNszu9XKzx2qx2DE1N0Z4a+D3Onfszb5i65DgC0Rb2mfExWwTVQMlKD9amDE60hLTHv6tMOEsW+ZIWqaHEW2E3XoWokfu+IuvwuvgOAUUktq6t23aZdHZiwSR5JGX1W3kYX4Bgia5GDd0XGR3D79TLdaOTiTifjjSuZzbdyiNpSKSnXR1biBwXr2x8oK2aIuE0Yh8mmyKQAvMISiNTz2u1mt9q+T+0/krsjyw7Wi+YO+ftMttV5Q+OATJKONaFIysiEDV4fpYmYT6VWjH8PYHas7jWomBuRAT1Eq2wW3A/8zkJdhaFycdPIcjILB9eycPAGoPE5MvCAdJI9SKw1hT5bKqDbqvs5uZSraSMXzUrOpqWXrbfjWF7YaHlsHvmCpuDHD+7K8bSWux87lvXdpWzvzVW/McWn0vPjUxMWND5+iyoC7+dZfVpAimQITohZ2iiAFR9qgITL5ADYdDeKi2K/AExxUi3YfXEyvq6Tw8SY2HJUUKe1QfcLIYjsJRWndR9u8I1RqiVp6FVKFRkg7DMr8ujJc15ckbtF5iMVBor6MaxPFlmAwWWm9HwabbhAUrop8LsPwIOVlW+eTwTVWwSSwi0br9HvVQY4Zy9Gt148bzFgKiuMqvZ+zuCpKbQM7XshR43qz/6nWkEbuOfsdXaWxyP89RoPCmBl7fR747WdrPCgH95z/EjtNYvaTqwtjvl06VrtfQMrvxd0HabaUTxOZQVWfZTDUhmgqICuYre+MATA6uR0Yarsq00jm66TtrfV+7wz2aasKp7jotGRQMzCmCMpImlv5nS/7FILlX61HcE1mFNrc3/YGiPfvwhmqk4BDHerJYOLLxxC/pjTF8L5/Npi7hPJEt7R2n4nO1hJ942CFEPIDCmbO84ZerwuLQM/qgWk4roO1AzPWvEDWFb4sWuGE3DjhBADTyNcoDW0uNifx+5yhFtyMxhAgTJBt6B1m107bFRc93PzM+2DG3fO5PGqkeG814WLxlBj3hMXi5rgGyv1lrt8JEAqgYIH6ZJLjHp49tcuJ99XiUWOje7qcankHvLPo2WxD6Aqt5ZJ21v7oBCgE9U2UrTzLdpb1sJzorgoLlwggdGYqu7ShcPY2zBa0BQrma5PFsrEwmY6cVrOTNI81C+GFbPG+pB3ltundHr/DrL7syYiYxV7tiRJlUGBDMwE4hS0xRYUkhPTMKpfRAsp9P9OPI1so+hGDOdnHIgJ3KBtxwWGWlfqkjMryCi3KNZm7Dl9b40qyVbp1qyxSZo1zWUvpUKAcPZp4ab0vrcKuDaGUT9Kf1/TNRws5dT+4JKL1jOtLYyNdJ8DwWbH0nfQc21AzRcM9aQSoQjgNG9lWOR8QlUg8EXL7AyWVSPzh41s7h7K+niU916byeHBSo4PV+mMyPMhtTzRxNUdFHT8WO7dx33fuRsvJNyqxVNMeDn3iO6l69aRVDmnnYb9MVkDSGip8RblMvFZJSISJqhaUYjPwr3WoJSK2SAgSQCYjlpQE4xJB2MbBumtdpLLaWPZBt423AoFBQeVXs+bw9u9P0cKTuF3TeGdGlnAahO49hCbtsjUY/SrTHIO0d/Ac8R+JwCp9kqp5+8OJ+7oMKC1aVIzx7UByLuC2+/7Xvol+dzhC/Jrzz8v9z59RzaPZjI7iy499xzR2xHd6uGZfepBKlF6OecXFx2fRvra/U9aW8pko1pF2J3zdfh7H72Yk2Z62Vnd0pqym8d4TaL87mzVSmSPRJBZDvEN5qpXLkGTxE6AkioG4/TQ+QNdHZNpXGU700vdQttW2o2xuDAbpRy00MZkjbmLKVH462bTQqGLSp8Cv760sq9RJF9vXoHxPOnSfbFREQBoVdW3JLrokpVhQERyAscUK5Sqi85zjwhMajUBlFTeBa/2fiIoIAWAzY2868Li5QDh+86EY0003kPtt0phntcd8834ECRLn5YbtPqceu73uVDc3zf2igGX3dCaawg1l+RpKF2OCuho9mNzR09HM9meTGpoLRYbtaowRsjQg+VU6/LZ3yXFm66+XSZbaGZyCXLNGh/2+kqNJZjtOsaaojgsrbS8T7Z4StdibIk937wNUTMwqkqoBIG63fCjsSS3dvRH0+JwjSBfpKLUxigMrr1dh4WlAcy8b2FVjZNZTgcofOjrFwrQmha9OQgNmPKV8m+95smqAWMJoMzJrtW/Xzh4pKzEi9tHcoUCmKu5LcRDWXgdMx7v15QIduQHTOT9HQ9StuJmlrlNdHvBAhsVKRzNoEcF64O0yCFYAbvUcovf2IfXuPYCUBVtcKq3Vhd1i6J2iTEfKSmYJ2DbtZ7M/RMo6h0uwJMzHXytbyyxN7k7fTf8h3yZdj1Is95mMNDvoz+6HNpq3ZI6nOsKGoryqX1eysR+vIosgIL09WqjGy/dOjMb3HoI+S51HwfgSdVqcb9h+dBqwlOoidrh/gVAym6zdHLbzwkMsJAAQPMzAyA8aP0lJnajewPQVR9xY5p3SUG8GmcW78n3VJvt2nfaju2QSSNVUrVSvGGtLPrCDUg5Krv1pRVGa2qvLI3HogCi3eXGQAqafVtcAzqP7dpDwyvUT7O7b5i1Msxzsm8iYwQ6Pfpu8cCAar2ay/pOJ2fbudy4daE0dZSXxyQZCxtu2q6go+N+QYiHF5OtFqO1R1WIPL6YBJyHjeUdlZutq8yNl76r1hliMFQpz8ch+KX4VgBIE7LNMlAWc7PfEF9TMofr85kyhE0Y6sZTF6CNZdQrxfCF4Wy5ViYejNdlWonZvraOyW0HCHGhAjlZAFjf2Nk2E+JRds0432oSeeQxppXq/xmh48wt0CLhmrW81N2Id82a1TIg0shFs5CPH96V5xbn8u7Hj+Xe3RtyqdR0kd5ZqZhbEa8yq3uS2bZ0qX9kLCljqJUrT91sKVBMCMk1FfeJv7+fk/QaRkpk+1n9lGavNlp8LdeBuf05FpAniBQ032dpsUJZcZ7sHtIJdjPI0PfOMINlsLXVNSYt7k8F7GiVAejgnrlYa4lpVHdVyn8gmOy7J7QaE9jys3B/WO3TTknCgPdGVW7E3G42eSnQe25VKmbo6QaWSxJ6lVnvGjOyCVStIoDQFSZvuOqwYDEXHYCJbuOUBJuszNzWgnHJ9rMP032imzKAtiuP58VIBh3tC0zUtHhocbPCIccf3KKkbvsCLd1ynp+q+LjHWIxstr5YIVswuPKwyEnPSPhhrJbCw8G1XsQefEs1yfwZwQJi9hjX00h/3svmhUPZHm9lfP4yDznEKhDgR54TYlc+eLCoQ25Upz9Uowi6eoHyHcGEPW/Jq/k9bV+wZnYtsOimy84z3uJY5j0zBnN7sQ/dhZZOb4QMc0nmGBlcnSjHMaP7zhti8rq4PrOSAArIUgIYdUVb+ZqvgPXKzIrK4KsEYafYWwK0WTNHcC+6pQ+FCTu/wacq12sMy3pF5ZqSSK5dDyjvsQex77fdfFPe7s/ln696md5YyPbuTNMT0gLeFXisbhtVZT4iFPREndXf9y/AE0CRVl5LKdF1ETxRO9bSB0R8HqCgQ8fjxJ/qO4WLMZlaWU0i+TUDgOXro28rfCdNjHlVrnEXxKHUnWfWQXGuhBKx8R5/8s7SmAXV4gnQ9bVc1207lkcIhSVXGK3GsJ/nBFFR2cgljC1Yu+GOQwHAVJcpMf888RUKDBuRHq9rUQ27/mIr3coVGGDlXAU/RWpziI+F2M+OKzZZb35RvEexLz3ZupDjiEnKwUVrVq1NXxorSl8LidOxk6bKglJwMotZIvDVzL5YuTpeTkrs9QmccbI6DSGeO+TIob2qioGUiJXI5Wwmw9DK+mQjTQ+gtpW73W5YVlbiHDEpk0ICaoNgEARhA1OQYFMI0ToTj+Xc87v5O+X+OR8rX0oQdU4W7C5JAlssJQ+AwiSOtRRZiIlIEc6rAEQ6Pc/h1lGnag/4vJWFEhXeb9XMb/O3DFKqQZqGHph+frvDN6iyziGRxZY8eVgXQnbTef0gVGAfgta8HeSlg0d6zb/2/G25Om9kfdmb2y/l90QCmbc0lMh5qkGKWfY7s2FwIZkrjcweMn5cZYKrQ7p+/G6B75/o6Trodq2G5FKqQYfUdnXO+/yDFf8+4oa3L/1dfW5xAOft6KwcVthjnDxAM8d721xbS12giEe4FMrcyRsob7La2sRVWGY+GDW2kq8l97XXIQIhZOxUdSCVEdGGxPhLPmScE3MdGms/AS65V72/4bsutpjk6lT+0irGpGw5SHrNjr2IMYHYMHu8NUkgJTf4wsYp2bS4kxtPD1ejqU8mFXspXUsEp7Sw0JK4GYCSKxZAhMFWqjuYX3h00kW2aFI+XWB1phpecSxxVX65VQuqvdy4ey9Uck5L8RALS66/sopq0vBTcPTrhyXKIos16ai25tQ96M/iKHLwlsj4oJPLzYk0t9bS3Npo0UbGKZGXsx1ac+e1tprXFTzKbHRZPaIGmVg4w+pSMSfI3HLXbbTEotKEWREGJDFnSinlYSWJmk5W+ykrl8OSYlItv4uJHO/fbtdOTS+nKtps6sZrRA5BtoDLTmNPvkD5CjbXulBXnwGtnQ/D9iHKqLh1BPzQpF6N+7ksUgJn+xav3XK2LJcM3z3Ljk3XTRy1YvDLy1H+4Mufk3/WfUx+9fQ5Gf7FIRLAdF8sCjXVIhQRx9WznMr7bR/Q4Prg20/8xE/Id3/3d8vJyYm88MIL8oM/+IPymc98ptjnD/2hP2Q5COHn3//3//2v/GRRjSFm7fp7OZnRA9pFkTcew8EkVOqlNVQn78afndG2r3kajwplyvews5J3iFHTeOxYB2vHHbOntDcpvIzREVxUeBY/trrWyZP5MtM1fcmieKnasb/nCZ1FO/dsqa98/yTfU/VxIi9Q1oc5RVRhoNuNxyGhAdWIQWBYIS8J8aRB5o+2sry/kcU9/7m/kvmDtfRnG+kuYTWZtaS1t2BpqNXilmViR3q/xOvem1cULPgEQKFPirGYf8njpwL0OJTo5itcAzFWVLmsqLCvBA67zwpQvL50DSGmlWJRmWY+zTrUpvcFQE4aznT8LCtWkCZylxTtTcmc/h1MVt2jRpqHvcj9mWxXnTJfAXyIdSBepT+d/VA5nf3Marn2Y7JAVFWnMnksF2JDK+lYvN+QLW9X0LhjwrCCDupSqZzRRv+G+wvqEZQ5AngZrRvJvFtl2JGd14fwKYAIrj19bVA2HmQEqJsbUMW1zW9mszvs1pUXR0Q+FHiGNv9AVd36EZuBk4OQqlb4j7sCAcUkXWAj2xIW1Y3+Ul4+fiCv37kr3fMrkdPIoHiCJ+mrbUn9/b//9+U//A//QwWq7XYr/+l/+p/KH/tjf0x+8Rd/UY6OjtJ+f+bP/Bn5y3/5L6e/Dw8Pv/KTRZXm8J69ZmuDm+kr0sKiu7DqMVK1a+mcCtiSdy18r8CtMVDQ/SGdwFOIxC6dj8CEMvoym52KHKo5AJKAUYJzvpNXTMVEAuCJk15dPh7H1tUMiACDNKtNLnoXgZJ9l1b3QSnbXY56nO2oFGlNUYzWU9WHRRzHjxHlmTjx5AVFlewbrdXocguGBcqMEtRwfUpygJXI7yD2xr5hp+PawyKA87XuQ0uKfcFJPdTYymYj6bYB0KOKQ3z13+N9siTRQEHU++tOLIJETa7Af87M0/91WLgihQMUrh8xKNzrok3uPUjFOSkmy8WOUsx9OlBCkX+uRIbSrajWNsZ2rHwc7lmaj5Q9mxONsYRf3G9kWPWyedzJ5nWtkiQHi7WD0yCHs7WW1DjuVxaXUqvA8/a0u0JMrqrVFAFKo0pB8874GBaz3C35t28IU03CNAEpugowgq4eQAiTO1Uf2AYQErDh/eN2q3RwBSePL4FHh7NDiCgBlVpPACmTJ8K2DZWMpXJffiWbZ3comCirb2rlauo1HoVrhFt1I70XZjQXJhYAlGpKrkFdINj11n1k1uNW2m6Urz99V14+eiT/2+ZAzt89sgUJH4dQXHSv2/irBVJ/9+/+3eLvv/bX/ppaVD/3cz8nf+AP/IEClF566aXf1LlSELjgJEcrKsZ1CDwxRpMruiqg6DHyyp4P6I4MEicaQ5myTTyPenTyJGTnwFxgzLS4As8TaZiUPAE4WXJpknFGI3O5CGaYdPQ4gfmnx/EEX0zAykorgSe1IyFnZgvJvlV9JBKwWmxcHVUupdRvBQU77BcXDLGvaQUzZ8qTUpU86Ow6tRoAvPhJ1kRwl/Fa6dLbCZRFS7LsEwNxb/DelUpoa7pvpTVaepsqUgX7hJJSKu0VqjCn05bjqyi14gr3jEGpgCwXIPHe1ZWcCb4xyzslczci0MTE84DFiAZZ4v3ynMM4Psme3LdeCZYzvoP72Z+LdJciG+h1n3Ty6OVGbpxcyvzQi2CA8edqpcGhUTzqdKslbTtHR0oc4VzKklP373UpH+XG5QPznygOiwmc7jy8ctJGGwBCyDOiE8SUJKwdoJaTIIEugrXknq7E1IvnxoLjN2s5cbNHBtdhcaUj7y9IMCH2NcBK1POVq+9coRhtzaVNDNIs2ViVMtQFiM36wQDdcuBgTX7vS5+TNw9uyj/dfkLkyzNp7vUyIhYZHQxfK8SJhw8f6uvt27eL9//G3/gb8tf/+l9XoPqBH/gB+Yt/8S9ea02tViv94fbo0aPdnfjwFpMO1RwCAUHLV3gCLOegSP12f7SCQJKuLrP8y8GVEqByU7hfoXbqjKm4694HO+yQJvS03PfvVZNgSuw17b5d95QH5OmqC28X04A/6Laiv2aLblS//t0apeEvnsOPWwShuCDgJMkJJbqKGCtMrkCLjZkL092XsBrYNrIrsXSvZwH2He9HfZHJPC7BKB/gCevZ+N3Katrpln2HieOE+3HJyQVJ6kuPHxK4t9HNF9yCXNhw+o0zfmxEWCxFTTXib3L/8RjuLU7swnjsPdebzuRKIqw7ND7q1EuwOZ5k029kM+9UtNTqRCGvBgH2sHoP/i9lnYWcJjrz6BK0yr+lckVW5wz5V8ESi92TaO8ej6JmH604TOMzFwwCESJJIqoOH9ofmYe5y5njVN763K7f6q3x3CmVVtKcKWdKasdYbh76im6+miCS2JDxBnuRRn6qBJIwqUEN/+uO7isw/9ILFzI8OpLhvLP7HgqeflDz8LcVpMZxlD/35/6c/P7f//vl277t29L7P/RDPySvv/66vPLKK/ILv/AL8hf+wl/QuNXf/tt/+9o414//+I9fex51TYSSHGn1J+XDp5MvHmqly9rfyAy3eYErWYs06qD3Eq9JZshX9ln3r3Rx8Hx8L8qrcW6xejxZJocEgjJXpSIhRFHbBIDOAOOKHmoGvO8DCBTmhlJXIXOaNP6S1E/Lc+ok5LQs/8zaQGYZ3T+2nyasOvGEhILC+5liXOG9ROqo7h9X8PSGRyvKAQkxJQNatwbVPeeAECexAVYVjoNMW7t2w47qiSgYHTnOl56glmqZ13yntpQ4doLVtxPPKggR8bvh2ElzMgAa24aFiIMv43JKN4eLb+tUc7UqvX+YCxXbEq9T25rLc7ZnkNQAWQfJ214AsXPLSqVvvOSHjl1bCFDcuRif+2TF0hjIuopggM0eIcVhJpfPn8jZ7UMZPnZfDpdrubW80PpHank5CQIxqjRcqdRNJp2Wz7AGUJqIibUGWk4g0s+Rm7Q1dpqLwxoJwDZaULEII35wdJTVgDKDib7ComhU0BUgkFIbvfjBNt5WtbBGOWjg3CtNiEgdz0PiN+7iw4ZrhOVmmGCNoGr8QqAdaJV9uSFnSmNVcAO6bl+mqGfKv8YAMW+6+Ux3H37He2ZpDrLs1tIfDfL9Hx/kH42flF89eFGOfq2TdoW0GEuOz0LMHyJIITb16U9/Wv7BP/gHxft/9s/+2fT7t3/7t8vLL78sf+SP/BH5lV/5FfnUpz61c5wf+7Efkx/90R8tLKnXXnvN/ti3+NjjnaF11MQJxmxXr3sS4iixaGmMk8TjpdV/+JtboR/nIJKIA3smt7i6r5uuLpIQnygsAp8Yk0mSiRRptZhYdDUBoJ60s9XIeIhqDDrgqOwSfofVwtwtunzCqjGDdbTUHHyi+kIBylZ5NvVRkhJywgfACVRqJzkw1hLVqksAKSd+RjEKK7XealDdZ4XtHDu4iMPnsXTJzv1NABXW2VxcMcbkb6eE4JCjVbDbUk4XKeahsR4r03RWskLD99JM6vfPJLhsQaLpCX5fpr73hVV1/bS43Lu647oJ3V08osmVroEXr8DcSP/YQPByfijDUS/TLZFlv5V5t5WxzSBBlfFU4YBDzbvR1jv5jGZR8bJzlQG0OVpHuXlBX9DnjXi3WElX6dvBQ0/DGRMqUiFCYYD081vOUrtmM73BfE99WWkq7pPRyAGMpJNb0nNJxY/sPmwkpbC8vdmSbommq81xc7wgtnh7di6v3rqvi4B3Hzwv2/NOZo9NheJDd/f98A//sPwv/8v/Iv/7//6/y6uvvvrEfb/ne75HXz/3uc/tBanFYqE/O1tyf0S0qCwEJlMG2nZ6+AkeFGPd8exkF1g+dlaI0FuvYzXf3LS7n1MHgQNJzYrbpz5RuPj8b6ufk5Mpd4CKD5cqMhhbspik60mz/j2s+DWgjovS1XaQ0nGaqrqU3MpiWXqbQPMhEzYlb1WwEtgHBESdt43AQrceGHgmzYQ61SA6YCIORIAYV6vyecrxMe0+uPtQiv1Yk0ASmFRjII2RaPEEi2XnOPFe1vfAXzk2dQLmznSr5vHdoPx77OAUGww+FLZBF1lkcpYzJdXviwGYiCDmj4P6iFpKmhfHEiT0JLhlR/LRPvCvnpvo3tVx4d4IvD17CKDq5GJ7LBenWznrerl5eCkni5UMTkHH+MPEx2qzVDbvKiisQUe7Qm8vklNzDpMy9hBnCfWaWGLGuqq8j4x/mZyQTc8GdjYDDK5KjtcVXWi+jrTE3N+sffTBtpAtld5j+SYQQdh+ghRIEvym/b/7LA2Jvm6EKVPmyO7BvBzM3wcT8nZzJl//3Fty4/hSfvr+qWzuLaS9sgKPU/8hgRRWgj/yIz8i/9P/9D/J3/t7f08+8YlPvO93fv7nf15fYVF9RZs+LNGlUU3I2NKkEMpYuGKBuSRUAlldGOlZTd8Jvmq6BFkfSK2K/B0VV03lIfLkr38OPgHGOZJzTJsL4XH1kyYmnlfLJCB/yEy7HUZdCrTDdemVVo16V8TSdp6PQg3BfjegCw85AAl9nPrcXTwpx4xElHyOBFrhEmhJMY5iMQ5zvSYSBGSa4K5bbfJ399K/w8YJO1HGtY5Fvu9cXvu9UDdWtSUgrTOT92JaIB2kz/i7m95KYgnSSamPS1/8TpqIYu+YFCkmLJzcJVeSg3LMKS1GqGZBf1MCy2ZXAslzrbSfKNtE4oqfQxXPqcauY5ixPi68IrCF9VJc19UWJt+rxqMmaqul1sjyrsh41sl4fiT3b8/l4clW7tx5LMv5RrpmZa4mrVBrkyziQbQGMl6aaYd7CtI0AYdU8mVrVHEK3KqIbTMagw0WRqVibuUqrCIuS3nYY5mtMN5WUsyRlMv8p1li8tWOvt+ereUTp265a9YPKAefeI52ffwhSxLuPnxufWP0c7gDAeToOzKONxMoIq63SGX5cINv9hcyWw7y9R9/U+4dnco7qzsye4xHpPlwQAouvr/5N/+m/J2/83c0V+qtt97S909PT+Xg4EBdevj8T/yJPyF37tzRmNSf//N/Xpl/3/Ed3/EVnYsPAgO4xYS2jzyQbl71NlUZghUDmR1l/8UFtdv3+bzRgnDTuIsWTFhxV/lV1LtL7Lz0We06q5hY163E0sRHS6q+yLDi5++Fm7EK0IeJJEN1Vu2ICgRpcZAW/O4y2XcL/P1UXkWVL5wEsQY9fhQBWO1YHPGaypVzOniyCAMyFAHDKq0gfDe/H6zLtPSvLJ+6f4Ouq1mHTmLhCeMNigBTNKHo8OxCJdjwOAqAldma/F7T/v5W0K7jYbvWT2IO1ozOkI5BcErFFb/Sbc9ty8bcJM3KanOBuL0FGA29XC7XIoNVrlX33HXOgITZHidzP2mUVSJbT+slRYml4BZj/CWNeaov+DlJMqB6Q+oyp5pnw5G1mVhOY/fZ/e2yq5rqp3zPnJqUQMIGQMKP5p6Fa/ZbZN/SoZhtJe0FDQ17ErX+PepiOVqhyB9repEXTh5p+sE7Jzdl2rQyWUX7rz5I/bf/7X+bEnbj9lf/6l+VP/2n/7TM53P56Z/+afkrf+WvyPn5ucaW/uSf/JPyn/1n/9lv/KSURuKEggeJq1BPeLLbgg6MTmSjMysYOWHAcjrCg+xJuLSg+MwngPEJF+KqOE/MgE++f+zqLkVjYjGm4g8TlS0iM4uH31f+oiJZFNftx9PVeFx9Jzp2ACyu0ANxoaA416QKP5YJRuZrL6ymyhWVJ9vYfpShQLB/lOZy5W7ASiDXZpc9IB3kgXg9aaJmSYzKBIo5T9dtVCdRC3GPuG+6IdzZ2xDiXrG/8KCamux1M5Hfr3j/eI2abB0XEOyPEoho2egeYyBMpL7bD14GCu6uxabEI1hOruOnxzaXL7UHWfqCJWiS2sYe3Nm50mhoe/P0JfBomLhNpZbZBWSVOpnutvLg0S15cDLI2y9cySunD+XW4YWczq40AThOhlSYKLl65ppaths5aFE2HSUz1kkDkH2bk1lZeZdEDDQHk7m5vK3MOyDUCAMkTBxonpMTsxrQz2lPGFGDHau//3Yh0xM2nBeuyoUV9NAmnI1zBSYk9p6NC1WWuILLJsXecp9SqxC2lUUAcv0bWF9cmOrvqlG4Do4GUPU38i3Hb8pRu5J35FCuPnND1qjo+2G5+560AZSQ8Ptbs1Ur2mgwMOwX5xcyp9Lk4A9M5blJE4t6bby2jTOVFKAYLHZ9uGgZMBadDkdLzfXndGImFRz7FZTwELNhW2pub1waVRvFRhWg3BWqytz7Em7ZKdjYFtfG2z1wbFNZ/deucdoBpNSnYaVPFXHdT0HKcpzSsWPs5EmG494xRrD1mNq+hiRLLk/i1r1V7DH2zb740d6YVDTXsrVKi7KwXrgQABCke1NdaM28jCZDbEMagG4JcfFAQEtJ29E+p0s5dH3VhISHvgAEmw7Ai7cG9WXtkUWKpUOKNpa3g+3jc5SwfkdiCSdrVFl72qKv5vJoeySbTSfd6SQH/Ua63gCHLD+TOsqTKqwvANRRe6VJuKYSsSkshfqRy9RzlzhyNXC+R4BiyRBsKgyLvbQdAIQuxaoKxfV6QZMu97ceuUbPuyqvzZw9TBWm3JGC1dTLappl16i7Sq/bCF+x9Hy8Jh0rHsPCHlClQC2qb7r5lnzhpUneY735p1m7b6cHq9V6+X4ofBifcz6/kWCRHhh3IfLB8pUkH6yiLM+4jzhh3zPdKlO4ZnE8Mq7smD5MmQ9UHCNTspOrps7xSTEGvyZ9qlqzCBVkr+k7WgwF3X3fZJiZeVFhIINQbnu0AtOpSL4AVZoiq1BFgMUAkCLwhevcWYCEtuzE2RJwVvtH11+wIPWynSKNN7J7LgBZiN9ca4XFe1CAOAsuVgm8qa2Bzs+ATkFuqW5UBJlIBmHyZzy376djwAkvu20OLsw9zNK0sAg0d3YDJjQ5iir3uyVWovxXWgik9QIXRrmGW/G8+FORjqlq6o1M552Mjzt5OLTyYLuUo+Vav4fg/KJzirpTxQFYZOkt3II6bq/kuF1Z2QxPFkYtJGxk5PMaohSS5hX5w01pJP3x/ClacsqWQ4kM5CK5zNGHuU3phwm7U4iZmbXH/QBF7I/V2DuhBEBr8bdrzxGklDTW12wSCQVW2WZqZQ1dON8AYnfmZ3J0cy2X25mczbMC0VMLUjrhs9QtgYaJnHXfxqeZ8SfhynMqMvj1vSSC6gCiQp1+KM+TUiJDNeGlulW0ht2NV1hIpA3rgWvXku/GmIA+QAz+UNA0xCIi6y+pFWjyklspnCGiSVlNTHEy3mel0L3ngrfqCopAwWk4iK0mYFLL0eNO51chLycfW4+l/XENKPE1Mflqt+C+wRECRbG97uJkpSH2V1pvEEjygfa8F3eu2prAmqAecrAigSeVYamuM96XdG/cjSs5H64ElTCWElh7pV0WFApehdwu/47eJ4reph2sCwerczWhUjMK2KEK3x6rp7DCfGFnln0GnJ0FDoeyu9KTS534zsUgqWmIb7zdi7zXyZvvvSjvna5l+cq5fOz4odxcXEoHwVo/geY5uUIEgUkrzMqkkzGsBoJU0XglX+CblvdjIG/xMArGRlklrjeRvItCHWZUfzguvfdz96HIBopPP55mcun1pLAdNmvZtp0WNzSyRNZHBMCpGK0TTBivMral3WO4SlW/T8t2B4tZeoEEgzECIcIL8osJ0n737c/LN3ST/FN52kEKE54m5nKK4US0B6H2gRZXUGT58aMAArQWYp5TznigBE8p5ZMeRGJBYp5V57eThbBDXt0k6yhilLuorAx78KNUE+hOTKo4d83284Pvi0UVfgIH/337+XGYV2XLMwrbOlhqsmlm7VF5O635oiVbb7HtH2TbAd9wnelQ0Zrwl+sszt/MFsEgtKuwPq67rNAXabjUbsi9iwr+Z/lnvP8Om3mf6AIMAJ4/d+G3tDDLyhNFu9JYraWgcnt23IDxvag8FZpUXo/jLpS1p0bWzVI2Yyebg0keysZIlQejUdS7TWLWmS1hyaeYgDHx5sTVPP2x0CFvB5NWATgqgl0ae8X16/46gae7JF+r2+iVeanNl6j4zaBWMsCdYrKJMOJKMKnkiEtGMU6JpGuFNsYEtUwIE4BtjCZlEh12k9yYXSrjT552kDJFbtQPCKtVtVyGxD4rRpLEkRZyfKhHx02ZfZ4yzsAhSQ36lsuJFA80H2a7CUUGfs3243cKrbkcCE+lI0icIJsull/mEx4ljMJ3zJqzjP1Cs4/fTyYgj8PcqLCbf8cC6q5AECdOTjCMg6SYW5Ysaq5WIquNTNuts62c0k6QSO47WLCxxBtPEoL/T7L2ioZX5IdIIuAxQz/gflLYtficY2cvklyDLtHdl9rioHzdt3estF0LTafJmGflFlDan54CHlSp9qTkBRBi/2magil0pIVWqDlF1QlUCkae1LBAwUuQK9z685w8jlsTIHApsXiRbJqfLhEnPE8qp23k/tbnx49FR4IejpWYQfEGhfliJtu7N+RXXjiS5nQrr776ntw5OJePHT5UN6DKnqrFYBblxTjX+wxyAJW9OVFjdZ8UvSe4rTTX2JOG4cpDVWWjaJuV5oSBaZIRE7vWbLIkWQLWV15s47dvG1XMYPd9AjgUKFB4+3Bay1p6uZpmCmS23rQrMcUKAxZYTVSop0Wm51GAIyDBCrM8NCsfwjl3kgGLhA9LYParuWmCZ+vKwRzYHo8Je9HLbX/qMxgC5YkeHtaZtK4i065QlM4afxGc7EHPZ+WWY/chvhQtL59c+EA2VR7KPgq7fcZ4gU8WmvNCyw9AgRVmVTeKrYsuvrrBqSPi5AGgYzXYPXwOlooAIcJ/dALEa0i+TTGJCE7+WbFc9RVYca3x9zRZV+1+XxAr3XepTxPDcU8/7OWtV+65Ggh3jhOp7JlBkNYakVrOy4htTNYOLd8cvyzcmn5tcQGVx01FX7eBFlyKmdWqbt2ewGSySIw/1WVnonG2F6CecBtCyDcdwBYM+wEsuQa9VhV2aKFWsenl0XRDtidzubozk+cOz+RkttKY1Ah9wLTyt/gLNf6wUQIIckBg6wGCVNbM86wMlPIcYvyiPF+YqC0sCrsfpjhBLfavPlBNKQ6Vtyax+xo5hLq8A7d9ZtcMl6XS9AFYzmpkfI73CCxmqp9TO9HAmufOm9XUgrMPhJKcd5WmluYjAFIadO99daj5QRzsfGrDkrV4/q+fTIoVblx5R5edlrQuln72K1aUBCJ+GhhX6ZjRskptCdaT/pktvZSyE0eC/xhLMJesN1ega7IRIPYZAYW7p9rYrmi5xL4o+jNbOkoMAUBdbaRZrZUWjZgGT1m6H/NjlPuyIglc1y6+7Nsv3ZbqoqP1VLiU3scqS5Tu+nhxlqXAb2xHYNZdcx36uNcWf3R7urWjY8qToIuxW2shxvIegaZv7mu3whk7ZbuYzBusdh3Hs87ACaKvfVad0EP5a+7yoMpfX+YT+3YXoKL7rwCouHlFAXZzf96KXLRydn5Dzm4t5b1madJFB60cd1danh62glkGmW5uXWZxFkyl/WSrfrUcNAnXwIkKFXRn2SRNTXACVf4xS8FYgR+GLTXt+R3tUMWLZpJD1x4c1OqzDUQHK7UI5qJdg8GLsyZ5PA81mDwVGY9dXlCFc+Ncc43UGWTDyrLXPZPy0wpSzeiimvqHTxRwU2hH0r8ewaUqBRFqKsXJhIKyyT3CSd8ipAY6dMFhwwTAEUlrJhYejEuHGD/jFsEqES68DZjknVJebMkqcxZWqizroEJLJknmxI4LYJDOzdytOKFbe5NQaKpzFCwn19WzWkYbiz3h++p6dQWMZH0xn8ss3eJcfGOfqy75fAoUKO9dAUrVPd2xyCIw5AVDSp/gLYr9VFtudLVBOsitjrRA0X7hhB+KaEXWWnVckKDquKZWZeaz7LlTOb5ZWXLx+pjzlViEPh6ZaI4VLQocQsmkb0v2aAd1E7ee8DssKVovHAOFm8CbQFe0u8jipn+5V3EHfNyll8YY3X0AQlpO1cb1CWWVWG5HcxHvzaR90Mnnb87lzZONnP+uhdxenMvzy8eyHvvk4uNGQsS2NckfuOzwdz5XLrRYEyKyFdUISO14B241kLhNPiknCH81t9bV9OB6HJQMgapdJte0nSYVxEVcCkUZabSewVGiihNditcZ/d5EeFnQ8Wxcal6VSSlp1a5QApHTT6kESJeiPwFaBBIAX8tOPZUgZWw+Tiwuk+hgUqzO0mrfB0xtGcRJK33Fyz74n1FZwVTBY5E+7FfHdKhicM0ATS7D6CZiDCG0TSc+LzkQvpsAjyvjFHvwiSwlhIa11Ad5VuoJMPkPky/G/nRtPQUnWLRB5DSpXmgcjS6rJPG6G7CPllQ6LSWN/Lpo1RXt2tf+ypK+dp891havPx4/WJ2RNGAFNEMZi7AwMe9sFedjrkMAqSJ3Sq3wqv8TQPv3PSZTsMqLfomJzaEfYuzUEUaBldJHsUwHwMGZfCZ/xbGa1c739WdqRnQw1H2Onxh2DGkM6Y4x7pTdBztb4amvdxkamVadbAA6207uPTgWOTb6c6fFyKiaYBuqAitTzZ/Vinvqzc56FPxbydmqbEEmo4GAhSNtL/uXISor6n2wyfm3Ypu4xlHrTuuEuu4g+sSf17CvtTPT8OnqTKQJ39FUJmwzUM8kiViUMurnxGWmWVUfBZAKrjPdAFBamBUyHFiaVg+vC2HuAkeV9MhVctRC4/mKYnUxL8gDk0UOT7hRNWU71X/KAJVW8yxOE1f7tjRKx7UVJogRLkTYhBIRWrJhW7qOEpsuXvae1XhtdfDv1lbeVj4DsSakAESae3AdceHAKrheHiRZUjuWT1UKhPthElVLpHSh7r33BDVYv/uu9br7na79CbEsAm7Q/Ut7untVVeKdAakTF6nfweeTaN8x3rjTtN3rNNFZEzPWv8jYg44ic/lI+dfxQOsQYzIDngGqlbWBG68AV3Sdphc4UGnlZwdhdx9mvcbYNlpHAcDT81b3o7keOVkRoFhEMeEqsTZYS3Y94VBMrueiCY/SzBPsZyL9WSPN45l8aXhR3r1zKl98+VQ+eXpXjmZry/XyzWor5aRc063Lm1WpNZCj5QTqOgVarWucmq0xnThNgFRhF6eySKql99sPUKNbdDgXftBygNNay4q0gdQASnorl2BJukQSrgUW07KZNAkaV6oxO+2HuZYqoYQSNTvUPADjD+5SxutIRkoLAHMlWuKwMSxx3qcfpIqt2evG2XEn4SFhHkeMf1AfLRImmNMTPXSpzEfU8QtuP6+tpBsDv5THie0olp0pepAZTNVKkmUUCDrJ1af5WwQFV7xm6ZHUdj759SSzB6T2MMvMOhtl2jYm/sp4GRmPRZkIpzvrROyuJO3fmmHo1x+LbtGa5OfxOuNn9VYtAJ64FccJrEr+zZdILIljZe8ixy2hBGJeeoT9kJib1WQecoH2kWJsLLE/GLsxc0YBCKBCUHeFeVbJNRCzxQkr/mpNKFLJK+BUQKDc0T6Dlfp9+973X9JnHH8+hPdaX+E2JAuN7rsaCHcsx1LlIpGVQr7VOPf31o0MD2dyORzLFy8aWRystQowStPPOqdbo4R6YKhhAsZkDWq1TbB2Qrwar88eUigomIXhdapcurNJZeJR5wqEBR0g7y+W/Fu4TbpUH7UdMV4GGEE1YaphIOH2fJor4B4AlLjAUdLDkOJVjOWpvp+g5HyXhGhVeBdnCkxjc/Q48PM9t6bIuoQb8qMDUtGdgS1ObJEJlnwE3DmvpnPtHuZ6hO/Hc1RxCy2kmFS2ofCQg9sm5e/WEtWjSWyI/pBIRnCGUPIAppMF10gq1+2ad5QaglWDv0nlThTva9xg8c/rvCtxEpzMgtohN9T1ivg9tY6uAZAd911oROzipCZ+HUDt/PI+W4EEOferbjsbybHDCb1mAZI4EUR304Su4R9/H6/FIsq+m8CropPbvfVE9XjvPM1Cv+7xT5MXQhtgRVLGgQOUANrIBOupcDkSGGwC1qRZLgyqrrLFcYi9BoBJXRn2JbiwFMe1QMV2hMTeIpa7Dxir77AenM6pvk5QYoUWVmxkPJvJ+qKXN7dz6Y838rHZPTmYr+VQNjJ0rRIIMFlbMY0AUtPWpKBSTSqbqFF4kqmulvqaAcoKGLokkXposy/zq0VJn9yKSrGoJI/ExFsAEKwry5e6mnpNUgbQUP1dgoV4OYH+YGCeXv3HtAzNgUiCBR2jZun6/BoW4qk21QcsKPU7G6RIN+eDp5aEP6BUdKDLRRdAPuqpwE0GVYi3mOukEjuN7rI08VdxGidZNGRIqUvCvdIqempuFpsQcta+HtJBMVHI/XYmK0JLKIQJUAsBDkXuVgbmUG8JLs/ksqtIBnp9bpqxtAR+B8CF83pH536I8Q6qG6SqvnR55WRorM5RhrPBDBhILmlL5Bb/m+1CzpUrBKTr41bEbCIjsGYhBiuu2M9LjtCNN/PHAO1VQkFrBBCenWMk3FtV0ODCxsNPFpv0Y6L9Oo7civHigSkPHF9lfD4SePz2x4TyfN2mfEICgyrIx3mvRSyJ+WxuvcG1BwtJ1UJ2SQ8sQEjXGQkx7Et8l0CmQi4qMBtyo6JFltrxPpZtZa0VqhNKgghFFoPFmVx/tbXnrkJU+tXP+2yojz3GoL22Z61MFwt54+J5WZ5eydGtCzmEakW3UUvCSnfkMadl/fQ5t+cJUzKkfyi0igIViOtAhKN3gJp7w+huw7ZRvT9Tb5h5ZV6de+CO20sYj93UPKEjbcovl12TXEwbWU+TXAT1fDQFbV62IELYcR+OcwWo/F1zZcbOzQaxKXb0PlRBwLBq8K1+h/lmqjDvbD6zuHJF5GKN4fT1px+k6okHW5zsfKK3WFEkFrgauu5XdRTvSgSiFJfa5wepvlwoaNL6mfIqN1hpO9n5caKq2ySxcjBp5UlJtGp/JSq6zz1VfS19PTUhSCx5LEInqtie2Idxucs2pfNanEaBqlil16BCoNkDTNcNaJ+wy4sKrk1azUV/+O4q9RRqJk35b+QtpcefeUexTIs/1EWBPQe9pO+o2BjHkPdrNCR5ilgqJl5uGov+TVrssf/ostOudoYe40r8ISmCMSeCUnBPq0WiaRAocJgrO2dmpVPZk9hddhUWpWfypRbuw70K+9dt9fgM7r3ELQp/s6+SJQZJKPyucSosPgDwHrK97KXp59LMRnk4P9C2g6qe9Pq8tIfd4TyZNqEyMGs98ycVPKiuz8LEtpepq5MR9yRVvHzrm2I4sB0liOTfDfQAIPoTFEAIEQBW/GW0e0u8tdpRdpVg911/SwyoyikzU0pIrjCFinzL6GrEOVjZ14gTHwF3n1YOTXGL8jN1E+3zE7iVpZMQ/ff1JK9fqUZb3G+vQkTc0b9LN5y+cuYiLaxuc0Uzr9yMpDbHSV7LQYAfEsuqqxXlPHa3AI2kweA688oqFQQuPeNkotZfJ+PRXAPuVp01aPKx0F4o6Z4mTic8kACRjqvkFndL6j2qgCoBX1WuYh/Q8jNVEw8DPlmCbpk6KSOBLoEetHFYOLguPWVO3NkpjhhxEGAF6rZWJ8633XKJ3AWn/cMnlfXKHKDCpE3XcHe5sfdgCXEYkbhTuK/Tzc+KIMEbQDAaDnJ+kxb0xNaKDItWhmUjA2I2qkzvwBTiSPi9W4G1OUm38slajUJXDJlK6rdaV+bPynRwNN8tx3150DEeFx8b4xmEMiL4iF0SgMqePydK+N9a6kPfm/T6pn6ScQEPhVUpHjuvRvCok82juazP5/JL65ncOL6Q+UuDvLx4KLf6i1wQ0RUWlBnoBRIJUGgSrAQtzSEDhJmcXs08ZFOewIXhM1DBvba1DdmvQIB2VFAZvVwIyoBYRKkGOaWbyyjradRzGnXerPItVMibSY6aUUkUG3e5US4KChO4YnV7avvyKonXXLjrPOeqn0yzj2rziR9pD5RaVSvNUbNzGL3dxGxBg3/qQapgZYXgeqEOoatUSyotHnglRfiK1JzI2ZJpPoCVVLlN6l3NV+Ln9Oq/OWnVN8aTeIAUlwggVSyVnPABcEYui7sPMVm1qz7RzplYapOkDy3GlSjDlM5HUAlWkU/mKokz62RzYy7jzCY8E8t1CaTEKCPt3SZVrshtwsuJ0M1AvwzvAd2MlSvvOkDac/+nxUymBUDUvx4krem5IaswxQPRR3CbLSH5YyXSd5bu2Jd5cdgwycEVGEgj6NPEMFPSgi8o0A+qeL8192FhVe72DZU6dENJChIi/P6ndsQxzbGTwNPdinNXh3DNPdyn1vVn1H1V0IKzuzmBhl4n3mxl2lbKFiR+uAWmFXVpYaM5mtvkFhUPztsaXIM7z0sEq6CVG4+RJLiidRYtKax/5gQjWFCs9ou+crunn6SZT3L40pXdxnaSq6uZnK2P5Je2L8vDmwfy6MZSvuXoDVl0G514rSSHqaYb06/1nKFBDtQWsZwfNufCmpB4b2qdKDuQ1HQaxyycyIRaIzrU26hgYjaSxbdKb4Ay+LR9AEOzoC4R71HriLagveLvC7D5HCTA1APL7mJElal8WGUl0p/irpOUL+bSUD57pmKSphRvqTgkGadSKNpvllvFWBYV1D8CIMVfwio+gha3JB8TQACbAocHBhKFmKvhPZZUkZixzzcT21NN0KCoK0Bkl0gBpjrRsVBVtNzCxKQPqytSq5aaTbAW88p1mXSCQiHGKI6VgMRjGmmy9DaS6o3J25OHx+VMz7E97hWkUEeoRZ+pJZVX33adCD0xwRfntkRi248Wl1tUiVJuTMRdUIpgwdeKIu5uPoDAeDCze6Zurkw/N2vPgNkAxN1VSjIZFYRTDIeEiBCP02vZ5HsG/bq0arcZIPW/ghaBwRPBdUEAEKzHrY9HJkMruKO/FBtAWza18+Q2dQu4yLur+oJgAYDSH7Ww7Z4ATGxcWM7dTlf7rYBhjnWDxqEiQQdyWKlygBco9Ppoyb3GpuIX5lZFt2vF8ssJ7pVXj+um6zy9DqSFFeZIi/CKtgdxKABViI3hGtTY60dZ3rqSvjMAGr58U9ZXvXxpc1u2TSvbWSufPHhXDrtVmnzh4rLCh+ANGbmCRRFVlw7Ubb8gGJ7Z/VW6u5JHO9lBLl6rzcwxrPoGTf4vW2Z2H3EoABuAaTXBgkJSMdh4ZgfFhFpssKZgvVyMACdTQYd1g59YE6pwYvuUmupOgZTuIGOWJdU4zGKrz2nD3asAO7iRFfjRACn0Bh5mJUlwhg4T7w5YuaVRUa9TuXVWI9WVH1a0vgoOcYG0Kk4rw9IHv0PACO2wKsCe++Osv6i+ngQ+03WE4zY+Ic86GQ56WzFjglUXSSMQ2+JEixUtLZoUz/BrUBdVdCEq0ESrc9LjYqLbHtk5AFDKk3BgouVlbp7sI9fFPifxsdfJDEBJy6pdW/JvtxqUyq4EEJVPGkuA1t9pfTAAVPtzwVabyTSDtYc2GmDDnWWJqB57YV8WuUmctHOMBpM6ylDAitCVOLHOXWHah/a05kKW7rJDv8BtpuVbBpHZ+SizOdrnEfxoRcX7wrHCBZJbDDYOfIGhVpkrh9AFy7HqlqNKGDkF3l5hDaFdzvxzoJ2W+MCASzZm/fSX5tbDvcL1N+w73Fu1JjmeK0sQwMW+8evoNpP+YDGj/aeEjUn7M93H6+amfVT1+LeCoqefaT94uyCaQGsuVUIGqJKAYZWax9kk3WyQ2WIrh/O1fPLoPfnGk7fl7u0Tee/qWP7hW6/LvdWBPPjSgYzbRl45eiC/9/RX5UZ3mdQWYEXA+mA8Bz/4a65lKkx26MKtEAAC7BOsWzDJGvMPlG+TCYIbzErKm8twP3UiKqtzOEAxAioZUB4HKE5aDuNsNOsILkhKGS2bQa5gwSRwMCIDrEJYNo/GA2PoueK7DfesjB6hhPRzyxGjJWVjkIrq9h7dnubcpDVl8Sq/ZtbI+2iA1BOoyXEfbAVluky8YMDX3IE2CZhLNU4wtTuoOmYCrAiSe9qhbkcDwUz1rV719/hd+29a9IVEEmMedTHHCHw5uI0JhbEmTt4OtuG8mFQ0/8alcRLLyidXneCC0boz57iFYx8GirUz48B+TJ6azrTSkhuSYL4NfV27JtlPiXEZZr7oAoJVEQgfXEvYgpfsNwc7zN3wls4Bch5XSdcdJ+rwmjz0BkwKCM4wazetdFhAUGk89B9X0ux+4y679c6AVSQfhNgAAc3UH0jSCCU0AJLK+MPxupwPyHIbXbCEVLmCFh3a7G5irI7d8xhPXxAgWG1AiyJmq4jpG+kSYcHhfvO7QZj9/cAqjYC4X7D46DghO7H4vcqr0utG33STtN2oyhPLbivH/UruHF/JK/NHsl438sb5TXnr8lTePT/RY3x5ecvcg/OVLKBB50mtWlzRYYW8kuzaMvedWgveEamwj64NTPlBbTMvaWE2jy2C/MlOCblbdwviR5XWFZjscxi8mgflCcjRWrPHPEtVkS5Oawe/qwszJcxx2JlrNEVBXNdQqefZbvJWulqHC+wCGmF1WiYZ25RX7tFLawzJjwBxwlbcVYCd277CNnTn1MKcvtmD7+DBV6oexPgXASm87KWxF7EWRT03PUZpQHtOFGlaWpYXY5NXJFjkFSIp7OrCiavxasXFvJ1Mk6Z15W4p9kWQvNENEyaK23GlSp6Fu3fatceg9ng4E12e7jO+76rZw6KRRmNbrbTzzmM386wDCOsKrjl3fcX4lPYNz0H3HVVFkiszT5w6iSQrKY+LuFqPxfbqHybDkySQx1BIPOXEq+4w2xdEg9kFXE7e587ETITHNOGTeYe+bEv3ME/lJJdUckUtziEDG6WNmIuFLrkcZLoyy8csQndTOmkCx1EyRCIN2X3tYG0pcBkoZ4s4gD77xi1rvWbv8+hV0IUMyBcAPp1hsFIPsyexew9Q5XETcwvD4+YldBTLQ6KvAgXalTwfPjRU0d3k0/p+kFk/SI8kXCdBfO/hF+Tk+Eq+9/RfyP/3vW/Tn3feOZX73ZFsuk7+1ZufkzuzMznqQAqwcUZSxeC5BzDglEmnybEZBChBy8otABhz6SH5NU9Rs8YytOaqymBAtZ4GPeYVVCz8GEhR3LpqhJawnwyo7HjG5kM/47OZVtfl+2iXDWi48/B7TGAGBO3baEutRuxvmWF0e+J9VUtvNinBF4CHir4YFBTzZc2petP6VcVq6CkFKZ10k0ZdXezwSSSIsA8HdRrcJn+iIGVBB2nwsKvrL9Kdfa0RVspsU55MM5DEb+08nJrzhNiEqXBaDkW4gV4byiZdq+lD6SRlbqXJPLj2sIpiLo3HTqx9mER8UPp34qRkWm4eL+GqWWNVk7Sq1xdorcF6TKtnr6UV2WZp/0jOiO+xP+a9JYyyr8NG5p2egjlwHk/ieVL+WVoHBkBhv0eQqlbp5pa0fWAdfaDYLt1/zi7DT7e2OJDF7ljRubpmADlcv2ny3fUK0LoyN5abEM6WNHBy9x5JHp5HZe4uROuhYh4WDOgKuORWaJMJyMI1Jwfm0k3q5miejy9cC9UoWrp44RpU65MF8QJYqNqD3Ydula+t3dCy9pgXvh8EOnY2kpMi4YIfhcWTArE+n5MMx5m00a4pS8WfnPOxGTq5vzmUL1zdlnfmb0k728jLncjvv/EluTW7kP/P+J3qAnzjzdvyj64+KW9cnsoPPPfP5ObsohCfxYbJ+8LZa6xQaxaWLRxmKljrC8UUqyrlk2AtqRsT8ky6TkQCrVlMF5pYbJaHAYUblOras+rBAJzk1psaudFeKTyeQ3pIKxCba5LJuUpicMUI61AtpuGQZLE2sxQz6SITJ+w7qulX7Me4nF2VgRlp7iyiaL3ACr+1TuLTLTC7z12W4hlxVtoDYsGbkicSp6/HPKxEIc8WU6IGRiklniflM1XMLi2iVsUkvLy6lh4hrT1OWnDdEBCoocaVGAowRuKhnz+JcDplPGeRosty0J8reL1EBUMHIZ0Ts2ikTropQdWTST04XkgwpUW1M9/CBJomwUi118nam0fV76hRyH5T1hgTZTN1vahUm5GyeM8WHftjHtw7uvLI6eBtv24rS3MEoMNKXzU3MwOysHYxI/Ea9wB3GCzeRvh1bNFUxJ5iQm1kC6qfxhUPOkYOvD1qDcPl1UgzF6WjK0AF4kjKl0puQHcABB09tY5A8/ZOpCSTkTdyXxpwk4Jv37N9K09EGD+8L6k7ihVe7nuj2xurT2OJByGBX8/DBUE+sHohx07Otgt5d30id4elnHQreXm2ld91cF9uzh/KPz17XWnTX7r7nPx697zcmw7lu258QU96pz8vvBbU8gMJARPxQu0Wex9jFrEplERswoRLJYqmyqXCPwAUhoLGmiaAlalf4JmN8R27zEbPC8BBUi4Zc3Tr4awgSNByUpe/5lAZSzGRHELINibd2jSViQ60inJOFHmJ+Tala/J6XSknygeqrV/t5n1Qht/vcJCynGcoGaj6OVWno1gps8ZjHEOlY6IFUgOYr1wxmaDkgj6gnvSpOTluqah/xIPXPlNYzpApQiSR11SzxycBDERNi/EJXlXEB61ea+rhrddhYp4VnjZ3D0YrxinH1sBgRVCxGhMUyAqkorsrMuGjgpRPpP4dsAbZBXrlzhJME43n7lyXnxa16nRuUJdstqy0GcFdqMdxlQF9vDzmwsRVxuBGyo5j8xwlje+l+xjcaCmhNbj0aCnGxla33ty0OYZST5L7YilJloeuryHE7ehyxY5g/9ULJmXeuTsQY4AdFA6uwK6WZWfWpANU9DYzvUCBSV2AZdzSKOKT9KtJuisQV4zMMsCUOWIxw0bdcwAxkCkMuBoZltnaI9GE7tTI3Femn1pmLvTqx9R4neZikfVof2N/KlfYa0gh3LPC1ntBq4mqF7CeFiLD0SiyHGR580pVzTEJQpcPDX98vhTZdCJQRl/BESb62TgdycV2Lv94/kl5b7grz3WflYOmkU/0jfyJ5/+FfPbobfnp2bfIvUdH8tZ7N+Wnht8vnzx5T37wlZ+X5/vHaq0YAcHEUtcOUgeN5bvRYiHJIA1dJU1ArQK5WHHpmK0qWEggOFDElpsS3kOxRvQJSmcYnRzlDLNlg00ljca5to0Vdc2V2Gs+lBZ39OWAJjF7IUMLJ9IyMyuMgGLxuFFzogiWLMNBhiPOohbUBDWKXB5FQU3do6Yn+EG339kgpRN5cPeldfE+L2jYPPCbJ/UwOejvAVR4WM2rcoVr7phEaa2Sp+4YE2tjcms6EC2daP1VcS7GvaI1x4mJgeU0YYYH2v9Oq2KfrPPEx+Wn/6U5v0xyrWJTUfR02iVlFMKv4fCpSZEy7n2TlKtje2OCq5+fK63i+8ltaOfNd9p18yrXbtaB279ai6MkdTUn0jROGI/Z73aqD0g3FKyP5L5zbcdCNpF9WAjzhhbFGOu+oZyUInwhxXZS/shJI7RsoqWbQD20m263bu0kEKfTW2yOVnumm6slztiVXxuuWR8HhAlRLqPqG8b6opAuWY4djoNFhTIKqRZRJQKHhUJKJOYMj7jebJTbR+fSdzbRvrR4qIy8d5Y35N7Zsbw9nPpj3Mp628s4tLLZdurKAxB8YXFDXu7X8ny3lddnZzI7FDm7+evy5e5U3p7fkDdXN+RLckv+7/uvyTcevyMfWz6Qoxb5VmV8lvlDLJTIEut2t4yKjQUw2HRZnJafmwAsws2IPemM02TCActsmHSRdUrm4HkRwmZyQVgTwzULDxGvkIisgIRF5K5Mva2vrJ0EF9MrzOXjUxFIv5FBQyUMUboIsyMxDAcf3u8zTz8VIKVlIkIch1v0FaT8qew+0UC1rtiDvFCyvLCyL2m+DNYnKwL6dhoNdf9/Spr1fBcClbsdUqNoWex167TSIBCgc4hX/uWPJpxaqYykBsEYVDHVpgPmpEfGr5z2U3ioqBwQ+sZ0Av1oRQJpZi2mkhsEqeiyoqcUDg2CK0V7qSrvFlTys0Xw1f0bmTQmFoAtxfyKyww/Af0CAYIzAN14ySCrniuu8jWXHy4kJIAaY7t0+fFYUbcuuNwwwatag8YKaa2alRibTTcv41N54eQWq+oI2ndj0rSuk5URaWDAvL4BKQlLKLC4daJ0etfAIw8lgHaSTnJLRp+LM4854qf3u9hntx0XP2wfAI3UZZAx8LeQwEDr0oFfY19cBzIlAUxI3c/7vEMus52T1lXd9zpONB7mzFY95ySz2SCfunVXFr2pRfyrx59VwsPnVi/Kz7/3mry7PtYDgLF7eTVzbcRGPtc9L4+2S7k5P5fvXr4rz3fvybfMH8vXzx/Jdx58QX759nPy2dUd+an/53vl82fPyZfOb8of/tgvy79054vyu5dfUMtCyQga47GqvvhbE4GDpBLcfigGiFctpS7QuGv08bTMK5HzaXQXn7njMP7nnkwMsELcCU/Q1WQS7wQ+28+KE2KPx+My0cXZAlUM1HZhHyM9rJrsIjRAMRYgYMiSl50Io2QME6BV7UJaUP49JvzWW5Zb2nXtRbmppxqk4OJTw5HgE+MTKqvjr0X8idTlycAoWjRFfKNWlXBAUMWFcEwJBevwOZlpcRa8hk1o5wqvLu5q9zzcQJ+8uLNNqOWknWJDUY+tZiIW1+Lvh5CbtbUSgmTMiioKdEslckOg29vTEGJKvnq2mmg5NhPceOYG891ZNDHF5Sor0ZMeGeMyqzFIEUXryXN8bFK3+1PnA6fuKJzw7pLy4pYKBLQ6QxJpoaAQH1HeA6iAIGEY5TF4CQR9AoXmufnCIckwmYxPLvMRBXGzsoeOKSxenOlnJCLmbhkat0qQsLw3E7m1ZF/k2W2dLAFiBMGU4DKt8jjT44EZmGjnIFN4LGIlsjnpkk4ggAg0fj09AAjuxY2Re6aTNlH8SeEHsQJt7tb5fP2luQGxKbAl1yHHp7sL1wDiSTZHIi/ffii37zySTx2+I12L5NZO5Y2gCPHm+qY8Gpcym2/1M06o26GT7YaMtEFen9+VW92lTuaX0yAXUyNvbI/koF3JNyzekX/51S/IFx7fls/efUH+2Xsfk3cuT6R5ZZIX5o/kxf6h0anRXFepmDvDDpaNkoSDBjpeAThm/Vi8Cj36eIQbDgm5ZsVg25CYAHBVN52Bj4KjgoYB5KNxJpfjQSJFMJ7EysPLdm2uRjLv3JLTEvKuSG6zKc6dY1Ack8ydouI5rDUm+JJMofTzkOCLV+zPPCyLX7bKQNSy8x8JS0pX8qnIUhlfSoqPMSk0xwp2WH87pAt+P+1Qugh1P/8Prg+6vyJzrrnm2IW/qzpeygsKwBkshqZQ0MhfT4sZWi0ppyZYG+FS7HwkH/hklFxqwfUZZI9IPaeVlt2BlZAl83jSQbLbM7MfM3DR1ZfalWovBeBKcargFqPlFyaxuoJsqswSPWp1f1RbIo64VYs6WupeUqsx5FDFW1gcINx33j8SKWA9efJtdCcrG9j7PhXQjO5QtQgzocasMNbBiEa1qREAGACSSOQdl2bdDFAoAVBhosASHhMVAETPAXBweSNVS89ts7kF8SUHQsQo/RYA7BS8E8sugJkmORtDMMkqMUfPQVsLAQbtQGUl47V3DT66M7lgQj/6okfDtLNJbhxdyvMnj+XO/MwAYJxpAi4mTBAkMD0r/Vzz8tjhjSpMaBHGaZLT9sK15ywHCe42uMqO27Wc9lfyydP3dKL9/L078t7FsTzcLOUbb76tE/6N9jKNz/Tj7jFl1Hk+FN1/9gjDpWb0cNxvAMPK4z9MjiUpZXD6txIgijwlrE9QM8r2X6nMEaxEO6aWEVGxXMabmL0Uhinde6rZh3HnRUj8/TgHRj0JloTPSbx5Qirapx4VhEPiN/kIfhRAqtosmbDyB5Hd4y61VA8oUsX3H2z/Z3rfqvd11e9qFm41Fe7H+ve9ILjn/Eo3hk5fb/TsFAynKGi2PJJCQmDsRKuoABVeR2yC75tcgKzCq7pyQz4P9O7cjdestomZmMqNtCiLmifY1E6+OrBoN5JVSPStJ/xUgdh/T2DsD09l+bIfUjJu1HkjkBFM63MR92II0SfO7sryiizWY5OjWhyeBFwcpm1ke2jqFy3UQZZG8ugfZ5FZaCFq32zhFjSyyHAwSy5AlbOChelWmKUC+nhU/cBMWednpr/nsRywzy+2qgfYrgcZQMOD4OxJL9MCANBoPhXjb7BwQMBZ3Whlu2hkcwgLyxVGPBNCr9MJD/2Fy6l2OE6rBAy1zOCmg1ALXH+wpGCloULLoZEzmGuXYn8+1jZH+WbMwL32uB5uEl7RPu0HJZrYPbl8vpHhaJLx5laODq7k1uxSXVEcQyjkB/WHebuVw34tJ8uVHMw2psXXjnL//FBWm15WQyerwW6igpOMctzOBE0CcHGq+AMnn5XX5u+p1fjL77wobzw4lb/zud8tL508ku965QvyjQdvykuzh0rwAXDA9ZZjQFkh/BCWDVJ5feyiGw58PF40o6xHE2LFD8GpSZJFBja4JrN0YH0dKAkCgGGSRqi2a4VBFgq65sK7kEUuQujH1fgXSm2MfVKBIPEiJv7qwolPhY8ZUtiz7Kwl/boCV0oUhmXH45GmTyIGwPjpB6nELqOFVDGouCpO7D59Zw+jr6SJp2mqyLuK59yVVkrnCPk86eO4X5S8Kc5ZuRdjGxMrMSToBkWLZGHwvDHHJKp0MwM9XCLPURAG2OigtJCYczx2QYogeIdriO3f141Fxzxhi/lWLJ0eKw8nCyqDUXL9RSs0Xtd11k/dzmiNuXxU4kMFUmUEQwDXFrTuDgnL7v5yqxhVYjHRAsR0/bSx+wmLZwsww5yOjE1sUMA4MPPNZItyPyoO8f4z7sdOpbXqOyrbj4y/4Kq0mJFrDvpA0QKBmiaAHyeneL9oG5Kl6ouMWE6eQ84TvglGejzLOC3cqSkc7N8l00+1IT0xmm5Di8UF1+MMfTOJHA6yOFzL0fxKTvqrJMWDCRcTIFxNn1y8q99/tFnKvBsUoLDfdt7K1aKXvmXarZWJh4I4bhfcbg9GOALN/dU3W6Wff+vxGwIdIlhqX3p8U+5fHMnn7r4g85tbWR/18tr8nsydhp6m8HTrDELQLtK5tYaTWziwpOBGgwWXYkK6GUgAiBT0vG4Z+4Ql361Au0FjZPql2JA+OjkSpCAThRfDQ2BFC21CoVsvt8b6ixuvk26/TFcvtfz0t6RV+MEe/6cApLgc0z+CKy/4912Z2yZVIx8UoELwKspkZDfWzin1TmcJn/0bZwO6qsId4Xd1N/rwzMVTACg/J706KQtk4KhdYbGonllDtornhKTDJLjQouuNK/MU33GBVevX4LaKfZQYjD4QKTNUAxTdgTtgUS0YrmHiJbdXMqCq4n3eV1EiqFC9iG0mUWTvKiLsx2ZxQue6An1EXTgOP2OI+wTayOa4ddKAudDUZbNs3QU3qWWh3bUFVRrpCK1sjjuLyXgZEGxXN3tpYYVdOqHB2XQdRW29AGKqDxUWLvYeEtFbK88RYmPsb7VMYCXrIqWVbtVKo9qFHlcKFjiAh7qAKuTr7UzWq5MYui2sIWuvtcFo6UlnNuRPpUWFF1e0eBUszCkxDTWvC5JTvgBY32jU8lrfGGV+YysnNy7l9vJcbvdnOlHrVO1xGeQs/d6jX5WT9koejEd+q2FdmcUxtK0m9kImCaAAg/lCby5iUr386mapFg0sgI/19+W5/ky+9+SX5WZ/IS/eeCzv/vK3ycOLA/n5x6+pi/G96Vhu3zzPpUt8w/ctltTLRXepMTAJbL/DZq3WF7UBoUpe50RhY7KupfzatRy3Bs4gTpD2jfiVDXXL0zIaudHl0Y5o4e2j+yfQ4V9gGzZUqTCmoH7iFiLOL5UFZm7Akn6fgdNJLx+NmBRJCYHxxjiVBqKDO4hfSCDDJWn0Afl/yhrMVGfmNhXnrQGqoJQHmQWpJY60QSGW4FprbL9/ls4Xaj6lwnuhrpMCXMiNSOoz4VQkLxCUkjq4r1BtdUPXoR0g6b4pUywEYZi4T0ZjEvj1lXsFZklCKZaV2AdIETlifyQZIuZ5YQ4hoyi7Oosf/ZqzGWvLqTr1B3tM6nZa8J4MXhrcpswA95UTB4bc5g1AH5Owsgbd1aPWQ6uTsUpGecYsY2pb+JzGRl1wdl8nZe11V53Mzjuv9SSyPulS7Sfdr2tkfdRYXhTcZ6THe8zHJLVcMglixW7tkD6vcSEHPIsn2e/bA2v7+sYsDe8Y22JFYHVhbifZziGEbN9TNx1A+MJiVPgBWCsDcWG5VSNynjYi/WAECm0L+gb7zOw46xsimxujtKdrObxxKS8dPZbb83MVgsWEjUlfLRXVuDMqtg3NSY5c2RzPyqy1GlF9P8qm6eRn7n+LE2ZEfs/Nz8vN2bkcNlcKUgCNf3j+KQWic49x4fcXbj2W+fkgd++dyJfv35THq4UC2fOLx/Ly/IGTA8xFp1R1Lanh0rIp/gNliEX6O1oo9dZ4mXo8PwQ4lHbvJqsYDAIF2YUpR8ktQSNEsAS8HYtgqYUMk9aegVCSl+Kw9xhVjL1pHqRfF4sdthSr1RUinZX2XSVRKPRZdeKYA/YUgxTLTFSupjp/J+3v/6UJk7P5HgAKAGX36zoDNX43Runjx7XLizNnVG+PQBpyobJPr4yxJKWHsBqa9s3EhoY5huFxpqhOwESN2H9k1jkoJnCK4KzkSEygbuYzkL+nL9/PwN/nbSNIpldafWRTuvWUQe3JUkbpHHVcrvq8aMseFEugq+kK3tXUuHMFcutXU23QtlJqIBxD6fYNZYasPDvjNPq+i7blnCEk18IyMQutv3KQugErCJaLJeniWHhvvEQ5b1M5px6hxphcdZ06fGmhknTwstRRWmRwgYCvz2GhZ4Fj/bozKSlerF2itHInnbg1qgB1ZQxBALPR38vkZANTjz/hHJB26lwA+GCU8XCS7mAry+VGTueXctCt1f2mUj3+pF6NcxkaU/vWn7FV3T7Gc5bt1iwqkBaklV+9fE4utzNZbzt54fAhROLllX4jl8NcHg1L+fzqOSVhPNwc6PnUellsZbHZqDLL2Woh67GVL1/eUgBBpd+DdqNA0HiCr5II3IIKVUQ8d8pBwAdddK1N6ff8uXLnNL5DNZq8RWkmA6Vo3RjEaIwraKzbY51cFWnox3NzP67vs2uQbc4LonQon59snWn7WzKvAfeHAlL/xX/xX8iP//iPF+994zd+o/zSL/2S/n51dSX/0X/0H8l//9//97JareSP//E/Lv/Nf/PfyIsvvvgVn2uCSoMGCzsvcR5jQ7m4n3ZSrEIbKeEpbhFmah4nFQWsWGW8kaQ6q0KEl1NQdl8EyX0xsA9yca68kJJyvRCe+4nNhWe5SFai3GVz8DknHloy7tbRUiEqJEpQyceOmzGtnH9s7yQASL2gE3KnFGHVi5MSNExTMbpOc7+l3CAy1ypKPC0nCqdaLk+2FG3CdH/7LFOrle3FJNZAukjxtoDbyW0a4TNgafKbx/VGNITLAkH5uGDVo0881yoKoBbxMC89YQSFUJmjNVo4wG127vlDYNvRVekW1voU1ou1d2DkHetTxLSwzwGODZp3I/2FOwgOG5k/HmV2Bhq6HRckCZQWgeVCJZHtYavvQa0kra9AiLh0clCI9VnVX1ebAAGjg6WDG+EAqFZ/din3F6Z4AZCCBch+Qxv7S5HZmVlQ2td6GJNZAqDBihpuDjLd3MrpyaU8d3Qmrx3clxv9leb/WAaQAfPa41JfHm7Kl1Y35UsXp3JbhWJXctJdqTAqcqreuTqRx+uFfPnsRBN9ccYvrW4p0eCtzU154+qmvL0+kXcvjpVgsdr2ZhWhze2gDMH5yUq2lzNZX83lH33pdXn19FSmlxr52Py+WniwLFi5tnSA2UZgtSRc61uIHdnapwm6eXYvcJ1GTEABxit1cx61q6QQgb1WMpMrmZuLTrpCcdziU42yHW0dmeNSdAHSrZifzKzmXm8s22Fl5UpApGVoxA/Q0VsZlA5qOYkfmiX1rd/6rfLTP/3T+SR9Ps2f//N/Xv7X//V/lf/xf/wf5fT0VH74h39Y/vV//V+X/+P/+D9+YydLDz16KIg/Mk9K7zRDiJb4u5sLVS//A3gVEgncvI5TXX49uezCTK6/R3dimO3SPcqJtMnNlxJ7nHnnrK/kTdwMLl7qaysV8LRjjfgdQWiqDWjQ3kEKgBLK3itAOfsxuthSe69xbSYppeJ9B4+Yx1Vc+O5xa+6IuS/9lCxF4laTgoCCq+vfVQSJlCcVXIDpuAEHuV91SdfbeXtuKQGO8SrqDyYL2GNfRRtiP2lxPlMQ0JpHBF9fPCRwcwYh/wYNXOs8NaRrT5rXREYjc5tUIBckjsOgnaiuSNPcU4sLTMQDo40DBHSfGdh41mC1jDP+mQsOSl+qbGHtnJ1jHLo3YzSqcXKzes4eCCK8fMTHuEiwIoW+6AoLOx47DRXEwMAcRA7rbJJ2Nsq836pFc9pfykFjlg3JEnB96WIBANJgv40cdhs52y6tHXNRiwogcr6Zy6ozdpup6oq8tzqW1TiTk9mVvLs6lnurQ7kaZrIeOrlaG8UbG9QthqGVcdPJhIrKm0Y2lzN50B3Krz58Tvobg4yLRl2AakVpv7RBHcISdWlhRWFWyhONSWPPF2m+H2M7ys6bOrmY5okSrkCG2BF9vNV0wykPAKbMQz+XLnj8fBFKSXqPlo+SJJzC76OlaCfPY9lXBoKWi2XXt6844lcVpABKL7300s77Dx8+lJ/6qZ+Sv/k3/6b84T/8h/W9v/pX/6p88zd/s/zDf/gP5ff+3t+793iwuPDD7dGjR+l31eujew5WjE70YbbQHw/sRRcoRFvVPeXVVrEVwBEn7EBZV6MrK0Hoe15iw/wUe+JcO5N8+q+cnJXBx4KIgZwBpYbNoNYQiCC6gtUCgpggckVebgCnxPriNWgcCiK2JUgppVlFQYP0Ejey0ty1ZYDvMQptR2YvcUpB0FZXmpEZGdvHCYnsrmuERnUfKiXwFjDm4QzHZFkG3b7kXgr5TApANIoJIEF5ohbIvXbb4z7WWJ9zdSIg6aFqGjwt4EjrhhtLxUjzMVuAyFACKq0rjXVpPBFWktO1t0bTHpaMIZmbDX8PS9vXigCKbG9Y/Eljalpy3YDM9PSsTdsjMu6yrh6+s7w7qLUDEohR8RuZnW2luxps6M9GnbChfkHQBEApsHpf4FwoUNnOLbmXwMo+wn6Ia2hs1AFSAWrm5eFRvLAflal31K+VMHHYGmPufFzo61GzklmHIoWwYEYFspuLS3mwPVTXHWjir8weyMeW9+Tt9Q25HGYy70HVNwsCUknL9VZuLS7kvcsjebg60DG93XZytZqZGolrPOJ1XLfSrBGbbWQYGnkwHcs/b2ey7NCpjdzsLpQQY6QOA6geKhkyqkVnrER73nLdpixNJNXAy+QDS1xOIq60unxhTdp7ApAAKHY6e45wfrV8UJl4NPvGReCKCsTRGWmlOUrViFRy3lXS9REI6u1qKYa424eqgv7Zz35WXnnlFVkul/L7ft/vk5/4iZ+Qr/u6r5Of+7mfk81mI9/3fd+X9v2mb/om/exnf/ZnrwUpfL92IeqmgX93syktfDTXW1dV3NV993y3c1oltYFUVNbBrg6h0P0HlQu4ufS7EYxiFV7fn8X/aoWKBFIVZRv5UBTHXW8yU30Ls3xt4OOr22azNYIHXis6fFbecOIFqe8Uq1X1Ao+LeHmMCbQusLWi66vYQhXfqm9yRWGLqxQYHK1LdpfvYBZT9iEWlYl5Lc6DgbWhE5cnlZpwbxbSxaqcMZyin7kyj5fi6uC5Sq48eUvU/grU3LJhPhdzs+K17hA3WAZjH2j6cQcHO1UZR1VZlyZK15Q0AvdZXM4m9OKN/Aosq8Uj0N+NIg9XooKGqqAbCKgQrFPA18dg0XkByiRFZKxFEByYL7ZdzqS/6GX+2OSgjIloCyG4Gg3oGhEAW+/kiyOzfvX6alYtVvUuOMx+gmW3ORbZnowyX25lMdvK6eJSS2ecdhdqLSlbL6ltG0VceT0KBIg/bRWMNmMn99aHsmzWWiIeVtbp7FIOZ+tkLYCWjon+rYsTOV8t5HI9S2XitWzKAPd+q0nehqL53imN/7yX9aqVX9y+Im+cnMrsla1KNL0we+zwgzIbvRIewEEESGRLxEHAQSdupZ1iGwCa8AQ5IwU1t5KgjA6iBqWJWNYjngOkCWXsFV5rq0PFullK6nDw06ifvxK0QIfgN9VWYl+lqde+i/PQ2vqgBQ9/W0Dqe77ne+Sv/bW/pnGoN998U8Hle7/3e+XTn/60vPXWWzKfz+XmzZvFdxCPwmfXbT/2Yz8mP/qjP1pYUq+99loCDk2gTWSHMSuJW9aEfWlnInJpF82T8C3mOiUQib6eQFvfG1/aQ5wo3guzZ8zbShM6zxdHjGvfYTJMeoBe4deVwDOlPX0pfx+upBhj81fmv6hryWseFTGYJ1HCq0vO56eqRLVP7dIrrrc6VvhcH9xEWfY4hbsSC/YixXHdgK7dckUbKstmR/C23urj1fvGqr3sghg8ZjN4Hlum5j6ikkU8l4PWoCDFAor5eCx/ofGeCuwATrqeUDkh1oJC/La8KQpIfu90CPVW/yklQ7sFBavNvTVepNFibgqecA0ew6rKxBxYWnaf3ILjGs6/j2syUCxjhim5VxmRVixRvfce29JyHPMxufqO+7VaUnDtkQKdbo2rLdCKUJIDCh06kAGowM6DQjjiRCf9So8FcIIFoLlKQ5+IFFuUSfG+h8q6FnAUtpU+aLrmDbTGoZOHZ0fqinvr1qme+0ZnsTN1LWqhRFskGwevtEqyenqT3s1aDfn54A9BJHnSUzzL9iToGfnejqFAomw8y7BqKteeKWf4tXq8KalMVKsvelJyyp7fx9B2/lCRo/mwQOr7v//70+/f8R3foaD1+uuvy//wP/wPcnCACO9Xvi0WC/2pNwUndQuEB1BBa2uF8zwpMU3+PhuoW43kCpT5wESNuBlZfJQ2ouUS41gkGSSSRIxvcYbNrjFvqb9UszeTdPVJJPWdviBODj4YSFRgGXYH2NQeJSu4VYkSIdqMOEtGcPVZjX0A65BxAJ+4LHG22SUesCJwyK0qKP68ZgLwvi2VOy8/j9iVk4f9K07OUHcf2Gpx0o6exfg+ASQClN5/y3fLUkoBG6smJ0vHXSPFmkLvE61L0sTLdkStP9bLiyXXk6uU9HlM4EoAMcmfTKnP6x260tT9FTsOx/bHxKXhdFvPDdTXp9kKWzw0JY3FAy4sLAkXQGK6fnZeEC10Zb5ATlQuWqhuQlhhmnTcyMrjgP3araykFWjxLi2pMRdZ32xku5xkWI7JDdlfYqFk7kazKM3dZxaVW5TzUZqDQY4OVnLr8EJeO7gnL88fag4Ug/SwqNRqCpVmAQSz1iyZ8+1cuwQWAiyMh8OBvDx7IM/PHikogFCBn39x/pLcWx1pvAkuvs2617LzYAceHqzlAsp8aNgVVgVAFFi05cBA+8ezXi4uj+Qf9J+ST918V9oXJnl+9lgO1PpxGrlTxqkwXjkBhPsx1ylHHewZBUUebQGwKsiFRZ7q7bnQ82okHT3HhKLiAzUHEefLFpKRISzfyuWa3BKj+CzPZ7p+ptVnOV+Z8EF2H3X/yPLbVgUkPzQKOqymb/iGb5DPfe5z8kf/6B+V9XotDx48KKypt99+e28M6wNtVCLQP0IyI1ZylEDSmkVBqjpiBXOP6kncD1fk96ivJg9GdQsm95oDTpEkHK2wcL5kkUXgGmVS8dZgpWmcivEj0ruZK+VuQXXq+8Q/ICEUwEvh3EDtxapP1RpywcDUHm133c7wmtx0uV8SQBXm1zXWXL3FBOD09ZL6yv3iZG5hxnzcZEGxjZW1tJNAXDUrfr7jlov7xsB+vAwCHo8VDPDiJ34hkiZpgQXhWyatmnszgFxqR3Bd7xleeyn4ZB3OOSRGWd0CGMHtRzdfI3NnvcKFqYrm46QxJ7xqPUqvU6XAAcYd4kqoNwXihZZuN5o4GZZ4DwCD88LNCKDanIwKrgDjicCkShx+fSySONa1o1AGbpK+A418kEW7VfDhJI5G2USLSdLW7HBWmcU0Uyr52XqhNHJ89vBqKe+2R5pEveg3mjclnls1a0dZdluVURq2rVpSHUqA4J6oG2vSv8GViPHO4hliKkErsrqYy7vdifzi7CX5llORW/Nzd0c6GKi6ROTSZZLCFJJkKTXEz3VoeM6UMezsb+ZcsSpuqsDrT52K3jpARktHzzEa4SLRNXx1pGy/4C60hGIm6ZsVpu5B/66NWbTDrEVTu6EtmAs4fk2A1NnZmfzKr/yK/Fv/1r8l3/Vd3yWz2Ux+5md+Rv7kn/yT+vlnPvMZ+cIXvqCxq690M2zwm5byhfLknypuq1I0IrI+o8DSKA/irrBqAte4EgVsw4TOiR5+Ep0kIbLpbBfKHjF/K85A0Z3Hc6UJRxsWcr+cRBEtDx4O4OVVbCONHAClChvdtpSD0gneKGgKVhpzy3JL6jbCsSlIW1kVxVzv+ohKMafuXtD4jcC4d9txh/rfcXIPu+QYWM7tKfoyJPDuBZnalRbbUX1etjHflhJMfZcC3OqDV4dh/C+4taKLkOuJ1E6PQ+0oZqh1nr/LexQ9xOm+Fcjlx4Vlpse1ZwX0d8gxwc1nJe8t6VZXxl5uBCClgrKIi6aFkZNYZq1sD3sFqqvb5onYgr3n9wRJyAZSiG+ZlNH2xqjFCjWHbGXSP0aScJULlPDwuFiq9Iv9e4xr092DWw6TPFbuqcqrB+tN3y5Hd+DSQzLu+TCXh+ulPFov1ZUHujkIEFBSAEHiufm5ggA+wzFAejicbVSRAu9TQV3TCrRuKrwY/mylxUeW/NFu703RfryYyTvjqTwcURLkUsEOFls/mUI5ImpYfMWquKj1ZI9Tk6rcFiDl+xoz0GWIUu2pXCbe8qQolcT1rD2wW7L6fFOLDLp/qPGlCu6jSTChDQ5qsfBiUpDwhbfVmTLbSUvepCwvO0suikja+4cEUv/xf/wfyw/8wA+oi++NN96Qv/SX/pJ0XSf/5r/5byrl/N/9d/9djS/dvn1bbty4IT/yIz+iAHUdaeIDbf6U7iSH1TEeMtp6+B6Qyp6r31pfElxiPakQp6LrkFuaQGFSW/CxWcDpDqvIiQ1wrGsTAnOv+H602txNFzcna2BZ2RS7Z9p6qhGk7shGGqhsR6ANgKVvk6GH9mHiCXI6124hETjVy/IS8mw/tdxyob0nH9cWacF1SFdhEUzPKJI08NgDusz2yY19Eynm5KtU6UwREGMOdVwR73P/7attVFhmTOhNNGp/n4CLLqMcUH0Mgm13DeBWFPnieqp1FK3O6A5Nw0GJCZMMx1AlABnBrZhB5PJF1oFCblWr7sDDd1rpzwZZ3EdClysO+PPQrgZplsbO2C7d8j/IbD0w+baHk2yOJxlOBpkWo/QnxrrTNRqKIyI9JOW25WtVsPRVfH/VyLZvZXg8l/P5Ut1uF+NcHg9LeXd7UoicYopkjAcbSlTc6s/llcVDObi1UQ2/zzx6QR5fLuXiaim/ev+OLGencmNxpSw0iOVebVlNtpWrdS/brZGxZt0oB4uNCFyacO8BpOL9ACiFMZjL1osMK9DXD+SfzV6VN65O5btuf1GtQQAr4mJU6iPxwLhfyPUykOQPjqjDyp8Dm/iDujp9yw7aBDWW/lBFdLd8Zl4+I2r9JXBy285cjXaPU7J0igpYfyPupv0+oUQJYm6D09pBwOAjlQdsSir+gED1Ww5SX/rSlxSQ7t69K88//7z8a//av6b0cvyO7b/6r/4radtWLamYzPub3oIrLL8XaNWcfPTOBosn+5bK33ms9B7rU1UTb4zxqDags++gXq7uQLaLE5K3D+0qwCFM0jskjvzAlst8AnG4fq5s0gMfSlxwwtdgvQ+bJ5Ej9p26cMFFCyjOkny7XtJX/RaOmcGnIisGN1hyL+Q3dl1q119GsSlNO/1R7Vw1+wlXUap9+JC6thFhqITb48AegO39nt197SvM3QpkY+N5Pi1qKKIC4BpX8wKHXqwQ7rxuAVUL82nNz0IyuT87VJzIlXKpTGKuyi0sJ7j5DicZDyZpEBvrR2lB21aXtVlUdt1kw8YaZma1KPgD0JTibcQHxFgAVA+Hw+T68iwcLeZnZc5N+gdWF+JAZ+3C4iUARnfbna8Xaj1pIiwsq9Eq9uKIsNjwO6r44viDs9bUaqkn2EB62bnveBkaPQ7U14Fv908O5bhfySHUK6AXyJwizT1y2vdkCclJNcNZelF7jyMwZh1dn4NUUi8IJDpHuJuOjD4v9RaU0JOfKg2jnLhrF402Gp0eP7ZnlGxL76jrsMzF+qqCFJQknrSBlv6TP/mT+vOb3iJhgW4/ApOCRXT2k6ZuBemyay8QFDjRJyuAnzHG41ZEdGnR7ae740HE0x1ynZKgbJxUHdD0XDkZaBpDjMvjA0oOSVZdnAQ8NlWRD1K/JIRxSyvI29gkmaWFYn5Uye7z30M9qWqUWvWdKIfk1/q+82wqlBhn2yzRkz4LScFpXvAVfVKj8DhJfIquzX3a07CsnG8u2mh5RMuqsLzqY6ILk7JCiIn5MaLKvLrcuF9k8mk+kE3a1ke+fyCoxlub219dW9VGs1L8uFzh0wrQpbnHZEFb97GPGlSgn4N2vlxC/WKW+tViRqBhIz+r032iFahyR/NJ1rdwnFGmg1FddU03GTuOTUQberAEDZDwGM08LqXlUUACoXJI4isZkDzYHihZ4P72KLn5IEW0Vkr6oAoMIFIcthu1VBC/+rWzO/LGxam8/eBErbHjo5WcnS3lakM3mj0Tm41ZDpt2kmHdWVyqm2TTGdMPcZYRbnMkzSNfIC5MaD2pUK5/FhbJ5/cPZX0xl59fvCqvHj2QTx2/q+1XAjlqQzkwXEHKxbeNWlGmF2hjwCrxAoDBbrSk4AwaLKMRy7ZjH1pcHD4kaljNqTIPSinjo9WvsuRiA5wIlOr+c7ZfhxIl5BOCQOM8QpshrF8ZdTM6ei/rD8uS+qpuiDNVbjNV/ibQpFk5TIgkHWgdJNKtKosiTbqBTxyVILgVPEo/D/KWCJiaj8TE3LBPBAJ+1828XDa+alO0mMIPte0IXul6qKdHNiAGp9LWnaJfbdFASZMr3YL+u4FVkDsKumJ2XX7dyWTds0W0KQgc2YVhikzxnjmQ1BbBnotI80EUEwlrhGufC8b6QlmInf6or6M6b3S7XffdSPKIltNOqfS4fzzfnj4orqnejwH8dJzKb5jMZDJhwz3i99JY9PvtlXgxj4J8AT1BdpoCLfKoFHS9EZpPZN6LrcaFLRlW3/fKx6kf/ThgBa7uTDLcHuTrP/GWNAejnC86udRqxOa+gjWFiRTyRLB9UIsJx4AU0QHyCj3fBxP6QbPROBN+H6962bCcPWJj4BpdQcvKrn9URoT1h4KR50LBNbkdZtZ2/GwQB7bPyO5D3I/9qknbITFZt7GRYdPJvXsncjBuVXsQGoAmUZQtjGR9TOZOM6DKAGEUeyt4iPMaCNltMBae5zT5cVBbqh6+Sod36wnFEklTz04OI0ugn7kRzCx3yjaqVAB44PKjBRiZfNY2gtWH7O77am5KJde8mahqHp/OvBpP7D19TjuzUKjeHYChVDvnrFfp76UHvpYQQhXXbaEekQ2MkKcUZ5DwsgNQZYZdbpa7Ill8MB2ktscj6UInTEwMdXJQ3alZEtL099hnTGZ21xwnJVqrCUToKg19tEO9zyBXNNbfKwtXVq4t1+zbaXbdtTVV/ElbASxUlS+b9UQtTK4xaHDHj+o8rD0l6BOjr7aA4oKk6ocdenv9eXF9AXziT4HGlSUWF198z1HXYm5eMn6JUiBmOeuj6NagWoYkDiHUCnedMhb9QnU2NZWG1MTg2lWtvudHGV7dyCe+6Q1ZzDdyPizki2e3tCouJk+rDdlKpwuvSckRsKggLjtqwULQuielpMOaAmMPzMARhA24HGEB9Ja0tr6cqaWn7keCEPvElSVUXcKtIwUlTSWw/ZBYTb5UAveUauALAGabbFp5cP9IQfPk+Eqem5/JgWwSQCWwCEmwG3f5YYMzTXXEoRDh7F58gzcKAEHCBF2DENS171p/awHG1lThYQGpvJMCR8n4gz0EkGLsCmAHdiCzUDNIWbmT3mPnftUpPlhMk0lxXZ5+kFKg0cHjE6nPEkrljqBS0MvdqK1o4gVAXD+Du5XlswIp4wQKzZ1aG8sP1lqPgW/fscm1ao+dOPtwkp+JDD8oaJiJr4CqlmOmwetkvqmvNbrNqGtHlwmp+Nny4unSnFVYnTxIzqWJwJV6Sin8TpYgAy9OmPF3WmPpALz2a+5xALw0EYfJLLmCyGuJJIqdY+2xPtx9lfsqW1SpX/YQLNKxOInF9QRuSa1y4argST4pABOD7AVhogC0sBr1E2sbVHPRrbDKpci8rfBnCUjq/aksGVg+aPu6lcXdRuaPGlnem0xsdpV1IlXM19XeeTx1v7Iisua1iciFx2cJ4jo+XFZUpb2MtKHSSVAQgsiK1uOa5OrFUZ5/7YHceO5c/s83Pilfd3RXfuDrfkFm01a+tLqtE6eW2nDNPnb22bCQe8OxTsBYxd+aVsqg0zIeYyNrCMRCqeNxL916JtvbW42/6TzCfKdkzhFwPG4z0irUO5BASGNnWj8Mvrkg0+UXr58pUFFBHwSaVh6MN+TT27k89/Ez6Y5GuQEtQM1HAvEpA9bG41JUbFBpJY/VrbUsR6M6hQAUgDfcoHoPgp4e8qkSI9BlmPAeGsU8K5MvysoSZAcWY1hj3BSVtUUA4mqkYGiJkLT2txge41x8nnld5vh9ykGqmOz5ty17qhpOVfyDkyRXSl5pl86q3RhSPGfl5wmur5yfBfB0v5Vq9TxplZv+Kw6bfEcstR73D2/YhJwn+WLVXqd1K1jZjJYAqt5ScaRr2hrBPdDDsaLMLrnKNRfdkHR57nbC/u5hYbZoIdHFmUDlfcylYNwVxkh9qfvcZpUL74nNjfdmqs4RhU+ojOET4PvFlHY/c2Jvtb9aVDx3VdAurn/SlyujXinoa5H+scjyvsjs0SSzx1At97HtfQ5JKf2JjLxwbE1zAI050u3HyEA1Knz6GiYzT2BWV6HH5SCriXykRbeR424lL/SP5c7sXEumo66TWgqeE8TLAHg92i7lqpvJtjXGLcu5mzW1UfIGvCntZSvNeSctSp9o8rNfTGJlGnugICLVVm26Po/RkpWY4mi52IYRQtw9OIhsV52sHy/l7uWRqmggUbh2+Q2heCABA0cDoECBnTJIChwkI1B5wuWRFBddpkjp6SRKBDHZaMWR2YhzoG8Zx2I1csNZczviL1hW5RDIixcVQ0467/7dAIZPP0ihVIcWEKMl435Zn4QzE8k7iP4gDUWRoEDTHGU/6BbzIkEUoKU6OcvGk6pOqyJaFikPynX+0kfV5FzHm4LFYmQMzqwOLKmgYFS2ePJGYoGpUTjZAgUMod5Qi8CyKbUwbBKYdQtDWYn8nHEqLyuCtyBYm663PN6OTpvdhidvlHDC6g8xPtDrNSbiIqahnlS0eHbcc3FS4efVufU6WL+KrMi6rdUaZsdNZk3NOVFsU0zQDcci/io1PQGIf+Z5fmZN+j0ILsKy8Y6PJJTyIhOa+e/uporjh66rxbutLB6InHx+kP5qqwoUPCeq8KK6LxJ3VQVdgSqXRjEdRC//fuUNqsV7PQl4y5wpzzOCRTUuJqWoY+vPGzn8Qi8XR0sZjgb5E1/3z+UTy/fk6/r7cm95pJP/L569ogSKeqJ7vF3Keuzlhf6R3OwuNXazaAY5bFby6sED2U69fO72cyLrhTTbTpZvWYxrcwOyS3BT2oIrdeIAy6UxAgjauxjV0iTfSd3iCPe4C5CqGelet7mWmKYgeB6aTjErq4b8izdekTfXJ3L7lXOXeDJwodLE4JYUAQf/w6rCOddgMuoDmXM/lYABavho1YCpdr5vi4w+ta7GHJui5QVLlGMsgadadZ68izhUNR5pObF0CH4Yh0o6gPvcHU8bSKmbL1ijZCbZH/yvUn4IgQt7biKVixOUAQdlcPLhHKDiFlxiubyXA49SdIPEANvEdiRmXfxOdIVpPQBjC8LVF+f4PcQE5iZFdfDUMaFbtGigstEq0Ii5SsWBkzPQ61e5+9H7KcUeCFqe5Bxuyh5Q3vd77Cff0NZs47owcL4pxjr0hO0nWqt7XF4Eg30WTO0WjO1K3wmD45p1Q5RHKtyGoQ2OwcX3E/bZrJSAisBXtDe0tRgVwYDdaZqyzwAIrcwfifRnkyzvbrUcR3/u2oiujm+lMkw9Xa0nL9WhRQ0p4cRk3JgHtufVAA+FDEd5+bkHKux6o13J42kuZ+Nc7n35VOMjVy8N8tzNK3nu8Exem99TMsQbw6kXFFypYCxkSrukBG6xGI01kWzgJdPVa0dpPZ98UThyAi3+whZd3ZW77LZOdAjjAt/rMLmqkDEWkARgt1hI1PWxWIwtLgLYN1G30T9fPVzK43GSXzt9Tm7OL1Tw1u6ZXVP8SRR0byIsxy36wCdCu0YviOi0dVwzq/DaPtbuVMCIJCvNedqFBEv+9Sa7+gqVJdjO/Jib4jk3ZQZ6DhYTge18aN9Hxt0XH86Qt1OAT5xosztk1/NEs9xZgKls/J5iivWEtjPpEe2qJTuPozEmDCwWfgtAFWnxqtcH66GqeltbDAmA4yo9U8FzeXizrjgJFQ9TnQO2z82l7sJqRo0pAGpVhcVDMjtyjOc6SzCDUbC+CgLJHvOHrpbKUqp22bWa6gRfkkAK3A4J4oxFZTOl7Kr6eLEtwWoqEIP9of6bSNuP1mewyGI/JtZptq72GqU7bIzsxkIsaPaokYO3J1neE5nfH1QSCVY34k6m0WdlOUwQlqrzJE7sye3i+iR6fmNCtbYXJTdGef7OQ7lzdC4vLh7JO6sTeffyWM5+/YZcYYJ9fiOHp1fy/AHUwx8pKCFxFy4+lLfQ1T3Cvpr3ZAmnpktnLiZYGqaQYKBFOrStq4z6rqVNrsyKheoGY0tmTWdLSK1Zz9mCK7JeTFHIV+PPWk24YgU4MCVyiFpVOQa5OZvJ+SjyxfNbOoGj9pXR0rP7jT9UcUBcSpdvo9XC2oQxk+JKVJtQfQKW28guQAYxTY/P+i7WmOIl1tOOEVLyBeZcqgxYU5Bm6iDd5EUozTK0faN24NMLUpzQ4cpK79l/SqpI+3Ce46gKy1EHkghI6kJUK9XLf6gfOSa6BOsgWG/6fWoE1lZSUo7wfC0wklKbXWU5KF1MELwFOKF8RwQoWiv8KuWJYq6SA5E+OMxHikUI6caLTDmCSQC/ZEjG69XyGGgvaFxU4vAj+0OXjluvKJ2gwGMla7CeR6N1pRWJCYReAE/dTsjN8YkdE6tXry1UOdprlCK0j+JEuptnlQCkaBcn3ewKiQUX07XEy6KMEdxAXlokDsWiTTwEVDSK2JWXSQnFAGPHpe7SEiQ+YQZatO1jzM5226rLaXEf4rGTHL2xke7KJJCYd2dq5cG1Fws30vMYUg7Yx1E9vaS9B+Us6PXhehaD3F6cK7Pt9uw8xT9+9Taq1w7y/POP5TvufFG+5cabKtWjVPNmkPvDkdzfHqpbClPrQb/RSROVeFGYMN44nPPK1RDwg4ReWCkvnJ7J44tGK/ICpCAPhedEa3KRPo+xhaRmqEiEe9ltMzinu2Dmiyl3eZ0uCvyqqhqtp7hgcOBUpv8asadePv/2HZluN1rbCtWGWWdqdHIDhwk19hCTUvKD145KABHGB8kQF8MiqU3QCrJ4ngGLkjKwdtCqEC5tFHKnagp61BmkhWRnpN+5TW7BlVPiCUq0vlbRk/PUgtTeteN1F36NiWAzTXkzdlwyHovyh92ytGPg3d18nEwJUtEK4OwZc7oYO+NjEKwpu8+ulcZj+meFlZjIIiXIpPYlMdhdv49Os876S9ZhNWEWK6nabVj0VaS8BY2iffvQ6mIOVO2nKiynqiEF097BsL5f8c8IHnsOuecr5Sn39EkCmX1DjbeTfR9BL+Qs1VbY3vM7MCW1kH3ekRgjcxq8vh1Vud3V1KOcPNx5UD+/j5Lto8weD6FybwYpizmFCscByAvXZaE4kRXaEzGkamcifroXHNPhw82BXA0gijdy5/SxfvDc8WPNIQLlWbXzvEAgWHvr1tx8nIR9avQuh5fAiwCGSrWIoGDSR04VCia2/Wg5TeUgLu/jdQv9KKHFy2MM0ot+pvtBsoTvv6MowvfBPFz18vjKiBSzw0Ep853qE4L86cKwaR6yr0c1ciqPp0O7ZWQ6flYMto9A5Yt1NeTTKi3nW9VTStwoaFt2i8XQWJCR4Eor0HKn7Ix6zms7+CkCKXsgSY7IbqeY97mTuIo/ScPmG1zlNHuKJbrVk4DF37MYVN40iZj6fAGkDF/cslMiRWyrWzhUwtB9OcvAfWDJwDlfZs+ETKuIFgMtR69EbJTxMLFH/6ZOQvCzZ+FQlPtI+8aJnZNkzJPilpKVI+D5SWtrkgcMTwDnicSiYr5bsvjsO0kkE5YTHl5UEa2tC962yvLJGF+5NKu+ZIwyly/fQ6BIplp5zmJVTZcPV9gQE6eqNxa/NTNuzxZzv6hioWXh03iozo9X5h2x7AVu7VakuxQ5ekO0uu7iwVZaiMaaf0eFYtUy9diTuviUHGHFIXnsnHhcxqSsJEeuoJsp9qXbkkNFw/SXvWyGXu5vDuXNixumV9eM8nu+7tetVlS7UssHArGgVx+3K7ndXciN9kou+5n8+tVzcjYsNXfKhpbnFyGvCOVJRqNskwJtFXBhr2CCHpWksTkdZX6/M0YeFNsp6usApVZUULuIa7DkYnawRh9rrpSvbJTAQis6qNazBAoHqD6uTHq+7ORud6zxOQAphG+P+5Vy+2btpEUSs5VIzT1/JtTCMZedfe6xqaAeQQCD4jv6m9VzueVC9XYQLWzo1XfpKuQzsRkx3/m8U5f+gDfVLxrvYV9TercLB1Sp0tVHgt2nW5k4SlDYQfliYtqz9N4HUPGL+wgA4T37XtUeL9qXaja55VC0LroMuSLWiZpxKM60YcKNJg/ZaGy3Ao3VkOGEbCv/PcuiYO2liRwTFnOwtNBgptnnkmqh6yIjkS4g9oey3UNb9y0Y9m3XJDklYzQC9jVMtziJR/2wfVuRPFyBmq9bgwLGnnNFKzWsoEk1piUDL1eyLnySj+3ca/UlgMpivpnUXAFUHJqdn3MtcvgWcp0mWb67lV5de67eDwDSulQef9L8JyNLsCZUVMRQwMKrT9wGSmT5ZWsq6fHpOM6vsX8woaOsOsq8vyGn8uDxoawuZ/LS/LESI16d35O5FzSERh8YerfalU50V+MgL84fqYvy7dWNlPdjnnCblKGgYD+9SgctZDQKukokwZqg9WjAYaBq7dR7B5Dxml34MVq9x/PiAoR97xT7RGwJuXvFcCly2XworL0M/byR8bKX9djIw5MDBdOT/srcbnHdxoRflCdpDUQAPEziBUBbsVcbhApkqRqPUcqjuw4brbAI7Obas+sxofr9T1Gqd5XMxHzsSGf3loROko8GSJVWU5h4JfZVObvYx75S9s7Xiah20aWvl4m/xftFDsWeZOAEUnm681+yxbVzDqe/M0Z13SSm7/kfid0WXJHsj/C1nem/yjNSq0pjTV5oMIBUtNzSxQWgSoKjqt7qTyobUk2iVUdWs3zVUL3JtNYi5bwGk/K6DNudpRn7re6I4lzV23s6rRS9ze/tMPfCSppgpRM0uTGcxOu2cU0S3XXs7soJUPRi9TdW96iUe/Ae3HqjzB+ayr7WIEJJd3ftJZLEHmp5VpcIIrhucWiuFNl9bQlQnKizuzAsVMD42ooctBtZdGtVA3+wblVHDyrkWOHf6R6rhBEmagANwOqo3epkh8fiVn+h4IWJMQf5DaBATQcN/WqEPlwns2mQpt3q8VR53Kv08p4ldh4LTHp+PBN7lfDGMa1WvI0/UyP3+xvulW4pDlWNy2AV5899kEGVY9WqViDcfrPZ1lIhAKrhoc7R7Oy+w3V1DhSaO+VsYzfspFMiBheNu0OI9hP6jvMBeXqpmTpmdxeQZsXmPK64DI85WNmt/8EB6qkAqVysMMjDRAq2L0E0mB9yppLlBJkW/04CqZQPFX3WFZCJ08O1Ee5CZAJxtMrYRl0NBYCiW7BorxMvQJjAsaPbi0QMr/+UXGFJqLW2QELCLduo5JAAXA4qya20A7ZcDVbJ0PvvRALaNK+DUYT33G1ZuFnrYzlxZQqWYG6D52KlUiCuSRif8SgxlECd+7glFLkvdeA7Gsy0hnj9VJ/gpEZvpgKRBVqK2Fi757hWbsnedyqyrnU5QepEyHhO9iMWE53eu8w6q8kJpE5bqY1GDt8e5fCtQZbvrnXBobllPdh6GZAMjByQHJjo6lMKulsXyVrS+k6hOjCJEqxTlcCqWvyk+cufVWnkjdVNeXV5V37oxX8ov376vLy5uim/7/SzShowlYi1Uqc/Nxyou+jh2Mtb2xvyaDyQ4+5STlrUB8luIyaqXm1n8s76RAkad/ozGcWKDM49pnXYb2QxjNKddWrRUfVdwWbrTD8fB/h8s2msDtbMSVScb1ZWfl1Bx018iyFWwBUXEOFeFnO2ugxN9QJffOudm3J+uZDnludKDkFszirb8jBNUZoDgGzWFTXzzLq0XjHrqd5ijlnOXbJJFDEwtXz4LHgiMDccz5QpjOpeK5rHJGL9Xa0zc9NDpeKDuvp+x4NUnljrWE1l9TA+lAoMhZhRYa1k8oBpcu1ZYsf9GD/ClkgOztRzlp65AnymSaSJrNSQ2lssy/dZdIG04OwyHTY0VpJSRFyxFr2Vl+hxRuZ1hhVdYm/Fr9b09LjxXESnuCjgbL5Prb1uHldqjKmF+6orPaq+J8UJO7d+9YMoTxRtDhNGBIF97Ypfi2Ae9yHYV9+JcxNBT3+ilFHMVkjoGCay5OJ02rLHuGJcREEE1hEOvRFZ3htl8WCQ+aNB2vVgx0gWQyBHkL2navLBguIrQYjxqeq9TJjYA56xn4KFyAo5754fy9HsUo5vrOSV5QM5nq3kZn+pLjljkFlBv3fXx2opvNA9kveGYzkbl2ppaR0mWlEp18dVtsdOJ27EtC7bjbLgMLGCyg4QfG+21lwtkCzMYqrGj8YVJ2X/qYdvmfPDDITMVWpj3EAdN3GAm9VVNzSEVMtV1UMnJqDjnuovjYwXvazaubx3cSw3lxfSopoxCiN67C6uG7XsSSKK5JCwH8oXjtna5O8Ai/wIML4FvT2vORVYgDiyxZmyNWdDNjNdvVZvcUTcH1SmwqcAzljB6iMBUrR0NJGzfh9bcoWZKoWy5fRtTnSlO608xj7LwUEmFkVMBIlAAednbjmYzpcPDQjQUjIpkSdYNt6ULvJEfI3rMsWmfJRTrbxiHO5OpiXQqIYerRdOkDEOxS2Wiq/7OB2M/01BKcLryuhioFZMD99LT1uc2MxNV1hKmkzZWmkOrv7jxMKHnUYw3Y91R9ANGIA/TaD6/SqGVa+CY5FBrjdcrULfjpWKORQrQGQBxBQqJIBwN71mn1gCU06/t2l0td+j9PvWLEzwB7ZecLC/mOTmZ7fSn2+lu9gkRZB8XJtw1aLyZF0SIQhQtJz0c1p4dPNh1vC+VyKAVxJOQFS5QZPwhZYIcVLH0Mhn331BH4fti518fP6ekiPORivvDtVyHAbg8s8fv6K1naAU/nB7qC6tTxy9K2ftpYIOACmt5J2qrVV2x5laXd0wquI3PgEh42PL+3L35FDGO2tp3lpIOzSyZTwN7V+xnz2H6tIVN9DHh6DxGwiNC1inXCx4fG/prvK1U9u3VgG53pJV7gCPrVvlZx1qGJv1Uj5z9IK8fvOezE4tRgRXKLTycj4SH8+8YE6xpGqz79icA/BB3/E4rFyQih76gDV9PvSfVRGm+w4pAHwIGOMied1mPHv+FeQ0Z82Q2taVpLF/VEBKtyouxNegRg7AyBNFcON53lEx6daTUnQr+oRkrjmPBSlYxSV2SNitN2UA1ucKQ4quLRo+zJGKDDVOOh4rMMXm4GarLYS6CZyc6Z5LZeND/Kb8Qphso8vU8qYKNflwHfoW2GMQcaObhO3aR0ThZ3GSS5JM/jGN3T0WTuqz6GbysZEShQnm1/G+0/F2P48xwSd+PSbp7hw4/E6XkLPDbFihcrQdQLX0Npi8XFUDeTorJOFihe/qBl5+PVk18BKjFPx6lGYz6I+2R/N+kAhDl13+qS0lU5UoqeXq1qO+HgEVE6SWSPeJdg9IpaEIurdq9gFFvVRHAxZeL29vTuULqzs68d1dH+kk+fz8zOIszSjfevKGAtgnZ+/KbI7HrpEzVahYagyFk6q5kyyJ9Gro5Xw7l0dAbm8E2II4KSwwss8UXFPhx2rBExYG84dQZrdBwHvRrvI0y76ZYJ11o7Q3Rxm13lQj26vOiBcQ0t06TZ2PjFtdRWdx2zQy3F3IWXco7y02yvZr2zHo65nYLEtn5OHl44erz+QgcoZsIE6YaxBTicWsmBtlt9KsKICTuvecwUdqPzdKKtnwseNGkMOeXQp9MP6V2/x0gxSfCk7ifE8HGB29JCEETbkIHqSTh2TdmrY+Vd8hk872M4DKArVsV5jMoxFSg1K9BfBIcajI3lPfjhaQsd1ZzVTlg/zItf7evnPU5yqAcs936JyuZZOCxZCCwek42aoyatsTTlDM6oFZQLBjGDdR7PcfIlle3Ld2ORXX/oS+uW4L80l5rQG742GecKtTHpuvM1K9PGoLA4xoMemq3nKcFLjWo4OKWXC8boCO0qG3kzT4YUFO+hdpfDMelUgPFTmCLr+Q/5TjT1ktISmfR6s2uit5gTPTvjNxV7+H3aiuqvvDodzbHsvdzZG8e3WsAPJweqjEioNuLZ9YvKtMwDv9Y7ndbmXWTPJ/r15UUoTFW3JBPy5g1kOvyb1w96l1MEBk1uVaWeQPzy2o85vKFRutV5/nYU0hdoWE33TvArUcU3yydvtJmgOoq6OGlsUAFaA8JKD3BQBWjbk4nnTRBe/L45lcHs3l0clSTmYrZSYaSFF41q4lE7zLsZfLZHiyr8eW6PIjvZxbZP3lpN9MoCA4+lI3nYfn4FVFGDOLiuBkJIvYhqcapJpZJ00XLkHdV9m9l7coQ0DlhzGV+NBjhf2nnX2tYKAvwVMcS/fTmlEGgFQYT8cjkYIVeqsyF6U1Z6VHrKhgoJ5Ha8DbqCtiL2ePMvU2OcG37vlWWy+rQEtpx2sZrMLKiCz2sQvJAIVXDfqzQrE3UbsmlPGoY4IuxguWUqKP79uiC5Dfi33l8ZToFuN7yfUX3w8r+1o6aYeNFfEk9sceNYmCMcgcNFfasK7zeEVNzoisvcT6m5K4rC56wci7GqUDQF1aLlPR9nS9OR8wUcFnZi2RPab3AQxNknCCGznnOeW+Szk8gTwBEQe6+iAJpG7AXDQ2x8oSVd0zdtPvZkG180FrNy0WW+naUXqom/dbOZqv5QtXd/Q6sGK/Nb9IIHJvcySb1Ym8OHsoJ6h9pMKqds03WoDWUp5bnJn6AhJ+Vd5B9O9H66VOqC8uH+ukCCsNJArEYZCbhYTgg8O1bG7MFYzhamNuG69li1Ikzsycn5mbDydXgdy5qUnwXmqOFHY/Q+pIJ9N8phaf3m+AO2psHYwyovYWXIjneF6D58CPQcIF3ISmJTjJ47tH8ni7kJOPr2RcNrJpjdUHF2jckgpKLVOUeEXhXRjsaoEaczDWmYqrrbjwTrlo18ALiRg2rdlFUUHdxGk8b8sPfJ3o7VMFUgoQJCfo3HgNTVwnOx8RDjwpQsKJBf/FHKYEUPFgcZmYThAmvzxBF86/5N7yn/re+MRdGFn1ZF5YD14aIx6HlpSOSA/a+nHy/BbcbfrBEyK6TrM1X7XvTwmk6FfcZx1V90CN+8T8yyFce9l1EZZUqAjQVYCbk30d4qqtpPTMTfvfj7wRHodkhcrItO4IslRRzGNf/ItfK1yYDk5gkq2xqjYrSQFp8PfwyhnZ22ZtzCCTLKBUnTm7BZMVnmSlfF9aCFVF4KQioUCW3XoJoFDmPahJpI11sLxEvYGzjxNYTg5U3WyUvh/kcLGWZb+VZb+Rk9mVkhhemj/UGNRcCxba1A61hVU/04ntY/1jOYEpIyL3xwOtAIupDuXiIT775dVNtZpyMqpRqTdDLjtBYVmSMSSuvZzVp9Yqk6CdjBINfHW3rqFrGAhL1WKH+VRqGtOZA5c3AIdVfmMycBx3TEeIMc1GZNpa8vPFeq5KGehLShpFmaKcXBvGezGoFWq8aCHiTNYIHSpTLSYbgSgrH2ZrlU9xNd59zjCShHeNP1zJcROepacepNSKUEuCriibmQurSCdWSL9Q7YF6c1WOEr5Lhh63JCbr1lMaiYEdGEGNVhH3ya3IABbvEid6rnSD9USQSLEmfJZ08sLdTlIrLg3jIGVuvyDtorR6f0ACTTZZjUXHetsc7PTY7LuQRJtGXXRVXLNISEDlgMeH3+6PD24/XnIRpR/XDEyJsD7JOAOLZRK0v6hx58SJlARbueOSNRUu6wPqXeZj+drHU38sRhl9fXvWMzqfQ0NvLTK7mKS/tHpNGkNyAoyBiSfbUlGDWQfsB1o7qhji3aITLcDPJxAA1LxXK1bvgJY3yZJHmSgR3HvBtZcUJABQtKgiOus5KnDS6raefqBVby3+N5sNWl339uGFnM6vVEPvpcUjud2fyTcvvyzPd5dyq72SK6cua0VdfM+HMN6/N/by6+s7yvD71uWX5XZ3JqeHF/JgcyDvjDf0PIxPId8KLj/TBPSSFJigTe8iu7tgHa1B2bd4H0gO20NT0GABR8pZ6cJhZfE3jDfV+KusbL3HSKJWrUa3sLVqr1tqjOXxu62X/tP7nJ8vWzxYjpZaVWetPLo80HsCCj3UJzi2yfjTnlONW1OKoJODA5F6fIjNqRUFNXinkNPlR7kpy7qw76X6U1rl2MgWcNPWMkw6GzqIKdilulg5XyrZcqx99bSDVOHiCxM/RGF3LJvrXExxixJI9eTNGBe2gt4eQcvfYJCQx2IyL8vYV1ua4ANb8MmbDzqCnAbPM30+sgsUDmhh6qjdteSKAogReFJ+0B52X4wXhe/stJ1torsTT2NXW1n5mor8tp1ucEuAzQyaconGa57cvZVxyc1N4a6iN6tE+GCJZgr4HgIHgSmuKn2VrZRid79pHAkAonGmKbv5OFRZG4vjJ7g2eT5OXtmyrD6jO1hdgHAFu1tQ+9xLbcxajauYe9DIAJTeSsQIlziy30PuU3VfOZEaW9ABCq69fpC2m6TrB+mgiNCO8sLJmdxcXMrXH78jJ/2lnHQrLaWBRN3/8/HXy3bbyTB2suzXKjj77UdfktU01/yoj8/upvLoSo2WSX7x6hV5vjuTb168JctmqxPodjDlc1aEJQvNJHtMJgmTs6oqsGCirnEt9tchNqWuV7vhdO9h2x6YcjkTs8Gg3GoBSO+3+v7EvopOBtb7Sv3XaHHI2iVtMS9bmJql28jDB0ea6Pv8wXkWnWUBQd772ouQhr7Hl7x6Lpl+BBCCVtFsitr6M0C9PnPf2flisXmmQcY1ISkYui8p73CZFv6Ipx2kCsskdHKyNHzG+sCr5ABQlWVTvKatef9jJX2+D2jf7j1W5Qrkm4U7yEZTrq2U0VtXXQTsguQRjp8svuDmCBZbcckp8Tl9+ZrN28B+0FV3aU0mvPsg2FyBWL2StRVkdlWkHkjn8E8rQ5dvpe/FRQ89ynsAa68UYHC7GV3Z3ERg5Okr6mv7BSe9xXg99bXRSE/v7wJ4Kt+ObsZEW9Qp8889OddYfVl3L8ehKpAiazACtLPFtN0OSgrKIETAwuhG6RF/6kaZz7ZKG593W3np8KHcmV8o/RuyRwfNWt7bnsjlcKDMvgcrVNudy/PLM/nY9EA+dfi2PB6WCmIv9626prhCx2T3cHsgJ42Vhre1l4moxtX55PEpbFRiiG4rgCcVMpLOHgeNhAUEQrFzV6cHQMESBqDh3oZHLblSw33bcQky9kgFkvBoF8m//H3Mg3h1MZO+G2Q9mCK80TXCOH3i85MPbvWm3LPCLfxaeTCLyscGNJ4gXLEKoyOftmq9ti1aNH0EQGpCNV3VJ+EsUoMUWXeRjBD2i2DEid3JEHGgxf2K5F+CGOnmacL0HKw0OTtxIpQPScfhZIJdt1hfcFC6bEtit4WVelJSyHR42y1LvXBBXrDt0/RtRysq/fJ6aDmF3Kvg5PYS8Q6GnqShpBJPWE5WVTwxuwUuV10x7lmW1/GcSFdPsZKsJbfX0uBkHcdIcMOkyTUmagf1iJh0GW8/j5P0M/W++QdKYrHNajGB+AD33WQrc1qjiSSRFUTortM2UOszWkS0cBPDs7xmX9La9ACSg5eY0I8Kyzr3FyyoYdFoTpWCFUpTODsPVWl11U4CRU0nh1UFi2npQoRaa8niToiVoAQ6iBEn85WSIqBi/vziTF5aPJTvOPii0sjPp7keC2ACAIJI7L3VocaUADSvHdyX1xd35bX+gTyEmOw4U7UIpTk3o8auTrtL+fr5W3qcX9veli9fnco7l8fqykIsSifOsVGX34P1Qeqr1XEvp/2lPD9/LA8WB3K6PJGroyPZrDsZlq1Mm0kBHpZm1Cyke05z0t3iAoGIqQHJBatWlZ1bKxQHkdkETnGKcrHhNOaC5UarvgFA4BwYW4872QwL+dzd5+Tjp/fk5GSVyA+MTVlUYHfy12KDyqzLcaxYE0q/o+OF1AnOMbkoIvvRposw7gsAtP3VZkuPsMtVsVx9ImCUArdPJUjZpB9t6QqEEhkh+WMycNT7p0ANAcQ/qpQcEmjghQKwyS8Ulu1p6R1XynF1W7WJ5ygsl7A82rPoSLgc5ZEIFMWOIUpcfbaj1FDa6tXOGSA4TM1qI4/a+icaegVwp/f3uAbDIiNbJ/HzUCoitLtWQVdLiqQSxqWKz8try8nPoR17Lp3uu9R+7yclN6QFQ8hl0gmqOopTvxPIRospgUt1c/ieg/iOqkZwM3lFcW2DWUIO7GiGU8wBTAAzFTOdObAhf0nFVHMcJJEfPKKuTZ2PCkazg61aIZAdwsoerLrlbOOg9FieW5xrwumtfiW3Ziu5M7uSl2fnqJMr49Bogu56msnlMJfLYaaCqDf7C7nRX2qBQ+QxfXlzy5TuZZIH4wGHl1xOM6t95C6qXtYKOo/HpdzTHKtW5u0gV9CgY8VY7zsy047bKwU+XW/h2sG8W+YaUsFDlQpra5of7t9CZECSLudXLkDczawsP3frxeeoGHfNftCqN9LcG11jQxFkkmnTyup8IauDmeaCgTGpquJwT4a1VxweuSLW7sn4nOXkYNalyiTxHb8LlNFDw6P1yriTDf2mUqjPUkmMUT31IKUreM2/cZDZe5cqv04EgLxTuS+tHP1kyCS44ApU91kiPFRV9aJbyicIA6wSAO2OeeTd98k1puIkGy26MpvVrB6lMxXXHONENl4C2CVKWo1OfG+f36H2TThw6AtmOE3sCPIC1zx9XP3zPNAiDNYO250wlRM4zxeBPrHb8iRARl6yjNhXwdIyICsvK05MO662QA9vYWE6WKm6w1Wg4vu+qgIR9PB4H1XU1YFKT0crLNLlCajeT3Tj7VukpC71fCWloHu8j6KxjHOBNIE0BYATLClMyqCXjwtTi1DViFkVX3IihHa3u/HA0Ds5WCUFiGW3sbIS80t5bXlXvunwTXl9dk9O2yu5025l2XT6czFt5WJq5PHUy8WARNyFPBqWaklthk5eOXog33TytsodoYT5L1y9Ki/P7svt/lze3N5w99Ioj4YDBbmLaS4nzZXcbi/kdx29K4vZIP/kwcfVWlgiSXjotWJvCsUqfR0K363c6i6UPKCPs4PU9lCk7Z1IwaGOKYVxKuQEezVfdeECFGBJuQXEiIICio/N9DjyNYy5BEDRmIiPnVv4LQgY9IrgHm9a2TxYyMXhUh4fLZUFaVYmLJfd3KN9kR+6O/mXJgWn4RviXO7mq49qKloBpArKe6bA8z3WkuJ+BmIuhPu0g5QREYbE5mtQxZZSR8PWrKBYUVd3Sv+V+Tz+ey65wf1Bc7cKvbaUMhagKQP0BjpgGHJSHiihnAGzTP6tCB4+YVtw20GC+VV02/CH7YwB/jCJxnpSNeDYQHdQAROO+yqDzFfoT54Li7bvc62mcxKk+Tc/82rENnHm7F/dMz6sKTk1W5/JLRbcmbpLlYusmAbKL4U//eHO/ZmtyVjnxz7L+7Faa2TMKQPP+xvlLSyRNQeX0zlC7hGFcC2bITAj/T7kwRDuNy035jvFmmLZwEptp4wRXUc4N1xW7bIzwFTrqZX1SSub40Yn5M2hJ7LCheeWlKpCwH0H0sPcCgOqxdRN6spDxVgA043Flers3Z6fq2vuTn8uH58/kFvdRp7rt3KIhFtBHMlyhWDdIAx3hYA5SklMvUoWQW0CE9ei28q97ZF89uIFee7kkbL2oFf3Yr+Sm+1G3h1gOcE9NcmD7bFKI31i9q4C3K+sXpSbHc7/rny6e8X6uh1k1YOIAavKLCZsb21uyqbp5bX5XWPEoQotr51J0U2WQ9J7ri5bkeGwkUGfedsP/a2PqS5UJhmVum6xvlwWo3psKgtNh3q0lMMiaR8BohmgQDJJd9HIo7MDGZaj3JxdqjVF5oXamFXCbr1Zf1Dj3DazMssk3GxJVdfh9bpsaJZqfZpkrK49kFhcXDa4DhOIPcGCfLpAyl13yfpQq8UtIfVNu5p22r1iue3baleKTywQojR6tANU1O9jEm8EvfqAtZumjijGu6b75VX2DjsxWlRuTam151ZJWCQVlkIZJnKm274y7sGyKbs7OOFizKjerUoDSEAViSTOtMvHqPsut8kAqq4Mm/ctmpoAyOnnOb+6/DzmqgTA43UyV0knq9WowAeQ4hl1YkebErMruDzwXxRbZadUWzLAAagRfJOhG2JuKR5WAWKV66TnBT0aibdw6S06GcDkgwW1NI2/VCIdE24qtVFZTwCoftCk21k/yMFso8AERW5MjDdmV/LC4rH8ruVdebE/k0/OkOskckBTzvup9X6BEt9a4yKt6epNrtoNt12L/Ki53F0fyxZl4rtRTtoLudlCCX2Qc6/FvvSYlJIGGpHV2Ms72xty0Kxk7nErE0Y1IVYriItUe9Oju5zmWiSRj5fGs2FtVTMxxwbiTybka2U0YtySbmbmtlmtsKD+kSoy7Nz2YizSkuK92/GsNWFfrRTYaPrC+mom0+VSiSEoRZLiQpUnJB2uPq6/GcGMAMKF415XXwIbI07YQLXvR7YhpZs2oRpvHNtfyfY7G6T0ITYrBiQKkwsy0KBmX9PjKdSEHJm2rui5E3AIlk5iGzQhByusFeolQJp4qUxhTm2N1XDAkIq+j57N8h++f/7enn1pJRFtLEqaPYB97T6rY2DVQC5seNKQsQy3QQVLT78dSlUU11teSP7dJ86Cmh76C9V/rZ3e/shEw4mgmOELgHGGsiWsFGsSMymfJ1iA6fD73HbBAlFqNiwkCIBuzHVnQW4Ck8X3DJCoBG6W3PaoT+dlzIfCqrkdntvk502FDUNcorDgwgQZ1ybXXlO4rph0ij4xmrD9vTk0QeWk0TcTWR83sr4xyfrGqIX8CmUIbaeRIMDQUzJEK7Kcb+R4vpbnD8/km47ekpcXD+W12V05atdKhHi9b+RG28hclupS28ogF+NGs2nw92xqZd50cjb28njslAjxYHsob61P5XyY6ySrADJYjOWNzU1t0535uVxMk1xpDAsuw1FutYP8Swdflk+Ob8uXtrdUPBaW2f919gl1IeLYuoLXRN5OWXD3rw7kxnwlt5fnalUhXoVY1nrbyYPLA5ke91qyg4oTaaECBXR19dGt7mogUIVwr4VZTeaOxdiB1ZUKKPqCOXko9pgjBTgG9fh9C80Gf7PEy9jI5iH6rpWHtw4UjG/0K7NksLsTkxKZgsm+bmXVW115Nzdxf9yIFlSCtxSHyq9UloBbL+n4/QbZzb+zQQpbzBdRAoGDBd139kmOwUT3XorLxGOVLrkUY4r7hGOolFFhKdh3CsLFPi09rMJ097iE2wNODJZHiyzsk6CHv+iDls+ZcqkY/3jSOFFrJVs5aoWoXz+4DAsEqAM7ERyDkZKUOwpTsjp5jHntuU+xSuw+a6IApmBleuBZwWdykVBXDlCQoiRRylfKIMi+N4WBbDWl5Nqo0BCsvAgiRUJoDVK8P/HSmfCJN6L1FLov5uRE3b10/VhnIDDjrkC49xB/goL3cDDJBIByEVu9VU4l7yFZ1I2yXGzkZHElh7O1vHDwSJ6bncsnDu7J68szudOjjPtKumZrRAhp5Hxs5MpTG6CTvdZaRKZyvdW8tEGO1FJo5aG7fDF5mZyRTZ9g5eHnC5d3dDX+OnKj3Do6Hxdyf5zLF64OtKbUJRJ1m16HyKuze3Iga41voTTH+aaVi81MVhuUp4dU0qTJr5bM6yrizUpeWj6Sb7jxjvzibCkXONY2zRRBt9BHsCZY5/GUQIPjkPdHUw68DpNHAIqpY9+zl3QSg9xUjK2O5e6MZbXrRqaLTh5cHOgi46RfuSaeWTEEJtX0CxGMa12A5VPoj95uRCt+39aumaDCwoZRWd2Sg8NJpo8cSOWS2tjwkBAcUhkK282zoUMAPlk3PE4dS9ElSbms8dU9LS5Qxs0FWLm3Kusqu7f0Q2+QSy4mVsY+gAoWFNvN96otl4lwpl/dlvjA1K7FOMmTiq+Kp9ZGdXHqdzyGxge0tpQKtyEf+hBSrTAqjdk6SSqCjNPwdyjo/F7tqvTfy9IWZiVhAsHqk/I2KvTJWJ5bIGo1aZ/4o4EJV0uku9XEUzCHvACL0JeegJlAqqAih7iYd2taMafv7k/ctXuUY23JTVSBlwIT4lJbkdUtuP488I5y6LMMUtqAfpIWWnoHa1nOt3J6cCmvHD5Sa+ZTB+/Iq7MH8p2LN+R2N1d3HqbA9TTI5TQp6DxMtOZ4CxpZaHE7UxA5bRs5kEHeHgA8qDDUaFwDcSlcN+4LihX+8vkL+v53Hn1B5hNEYUe1mN5Yn8ovXLwml1sk+Dby6sEDeWV2X7754A15rj+TB8Oh3N8eyeVmLmebuVyuZzIMnVqE25m5nEDV7mWQk/ZKXj+8K0PXyeeXL8p5d5DkkFIxRyxoZm7ka6DKH9uKNZ1GrgOXEi88mbic8UvXcrGgocLHLKunpOejic+JtwHj9wrzTyvvnR1rDauXDx+5Z8XKlOA7KCmPrxgXMpSDf8IWc5dckrPYyrB6LhtPgKLCBeENVmtUvfiN2FK/5SD18Y9/XD7/+c/vvP8f/Af/gfzkT/6k/KE/9Ifk7//9v1989u/9e/+e/Hf/3X/3FZ9rAjmCWjQ671dFCKMLLypGpKUrg/dUh3CrgWy81KVBRkmtNL6djzPt1F4KGoEFQHgzKLOEc5E8oTGOTmQxl/F4oa6ucdnlnJfgjlARWdZ+0kkwx8RalGfgFvOGCJjBxWCvJE+YK6yIHUXGEFx0PqMaDvl+rrS9G1fKbcg3LeSUxYVBlKSK1jFrSJGtlqoSkx3NMiNMkswWQjp9dKl5yhzcYdxJJXCoAh7dMzrxRBKEt0n12MIlhRW1Jc1mfbx0vGJFzHy06hjRkgpgtdfVRymjar/tySDTYpL+cGMq2kMjw7bLk49OtHZH+8UgR7cu5JM33pNXjx7Itx1+SU67K6OO9yLHnchJayXXj5ql9H5f7o8r+fXNqfzc5cvy+Yubcj7M5PbiQku6gw4OawUreChBgO6NY7btVrbTpKQJVXtwSwstMcWDSTX9bsyvBPV4/7cH3yrfcPC2vDq/L4tmrTGn8+1CE37B2oPQ6kE7yMdA2ug3spou5eFwJNPWcqdId4brz/J2rESHlqofD7WuFKSV/n/Dd+qEP388JWo+csi0pAnYku4OBmClhYTnP6m7z6vQcE2jn7WlLBLvteVUVZa/f0cZ/9T7q63nKfyeBozNB1ePFnLRbuX85kKvDcBkau/U2cuDzEqy7eYm1U9s/tZ+SKOLL5YMqWWOrqVteAkRJaF8WCD1T/7JP5FB4zK2ffrTn5Y/+kf/qPwb/8a/kd77M3/mz8hf/st/Of19eHj4GzsZJx8y1faAlC+hQrl2d33t7UGXzInWU3ILhiVTvbyIlkuqwus5VW6t2Uthd+eDUitF42CtTLNONse9AtT2Rl7FQWPMlJGdfeasM6VU03fu8ktJkRt1tGJOlpvh1r7w/rUdHNvLfvYOKSbe7BqJ8aV9vvhsoXqpeNbjSnlldsJESIgq526JFMAje0BKx0B4aEIMy5IoMxHDcoUsXpUuVycB1mzy9oRE4jofuQSq0rIqVtDxO2HyKUCKkk57QIqgZAm4BtCJoo7uOx6kXQ7SH6/trVFkfT5XOZ1hjeU6J1qPwXST3FxeyqvH9+UTB+/Jze5KbrZrOWp6OWhaOXQiACwDEB9gKLw3zOSNzYH8yuqW/PrVHbnYzuX+eCF35mdyNfVa6hwraADLcbvQ2NNWYyaiIIUpVF1B7agadKMrmOO+4nu4JpTYGFRItpUlQAqpIBo6G5P8DogT99bH8vLc4mOgqx91K2N2evxFk1jhHlQz2WIpaAPypFCaXusxuWxVsl71uREZyIli7pSP3zT2AjFGwYeuZeY2hZz+GHtMgzYes3aofJA5fGpkXHWyWc3kfDOXFiK+ntxbksA95hTqSO0cqgCYDDKpDpt/QkEAl6bN+VXXHDVfVPhNp9e6Q76KIPX8888Xf/+X/+V/KZ/61KfkD/7BP1iA0ksvvfSBj7larfSH26NHj/QVlpPmKoEKjpELokNaioQO6DtpZshcRHmOQabVukz4Za4T3VfBlUVLyHJ36qVMtsMNkHjeqQQvnWj1F79DfhwneCDTXd/vW5kWMxmOF/LwG5Zy9XwjV79rrXRgxAqGNw6kOetkcU9kdm4CpfPHowb5u6tR2u1gLqxYSVctwz2uObfGUvtmluiR8pJAoHBAsK8RQLxIIo14xpD0Qasc6PU5U8mS8NTDNaGlx/34qtpNYGrVirIky0k1zvTR0EWGWaGJos0VKi0iuOcSqFAGKFSc1SJ+9rcmcjqFm2XQbaLxRYGvnJnoWfRicLHtBMkjONWuHr3//tG+CSlMmOmgFQCqAgTzmlzU9faLZ7I8WMvRDD8rOe7X8sb5qTw+X8q7b9w0KxiT+Bq3opdHDw+kOZ00+RYJsWvp5d5gUkNQcHitx7M2yeXUWX7SOJNfXL0ib65O5UuXtxQosPebFzfkvdWRfKG7LTfnF1r3CCoSKkc0Nqo8AbWHjy/fUyYfJlIwBOdtL482SwUhTKI43q3+XP7wzX8hXz87l5e7lbw5TPKoO5TDfq1uvsN2LWfDQv6fs4/J//utb5M/9eL/Jd989Ka80IMGf6rHmc+3lkQ6tAqiUKR4fWlEDaz97w7H8u7mRM5blOrwMhxeggU6fexrLGDoYgOQzc4y4AxQ7dBqvMEv56MDLma8URvQxf3ldFBpEvCRNCKThPloF7z6R52sp4X82ultee3kgXSH5zqpm9K5FSvE9cK6ojLFvo2CstEqitYRieQWe2oLunl+DILVFlaRzL2Km2L8kzKZ4zXKb+O2Xq/lr//1vy4/+qM/Wkzwf+Nv/A19H0D1Az/wA/IX/+JffKI19RM/8RPy4z/+49d+rkCFulJ43SFG4I5ZUoPGkJQFWKmbp2Rafs86uNba079pJVJ1HF+KLrIifyi69oLbMRIkCjp53kddDieDnN68kOcPH+uD/8ubj8nVYiGbzVwHL4LjsJQQRO0vrSaO5vQ4gy0li3pbEtsu1n/CpoXYbAlvpAEjdegc6ZZZvmaXNorOchIJonnhAKnuMt4nP0ZiKfq9URfnrFcLUisRF+ATcsT8S+Z2czKDg2p21WXmXQaurLCQZGjgMmLpiVpAlesP13XTpwT9ATdZAIvCKq6tIeauhV0Kyyq6+MI540RUiJXyd6W+U2vPk2+1Kq79DsIA2HnH81XSp3vh4LEsZSPvLU5ELjsjCXASnBp56/JU/sWjjTxeLiyO4fcMU9EbszMLfrs4KOIdVsK9k6Pe6qL3A5h7RnyA7JHGQRrE/zormTGa8OtZv1BXINp11K01HmVrDVPnxissHlhLd7pzkNXl8Sjy/1y8Kp9f3VKJo29cvC0fX95V4dg3uxuyGjplth00W7lotmpJWPofcoYaGX1M0jLABAtLCt+/GOeqgEEXMPudk7HeVj7u7r3oL/O8gjGFaANcgZrQO1YLGk2ErvIueX8j+SK+pgbk/Sd/bNK4SIPGzgMVisvLuWwOLDcJVXBzAMJeFWwQPwpNCYfxqc9iTAZQcDiZpdQwRB33Teu/bLHF8hzscyYEV4/WBxaX1fElv43b//w//8/y4MED+dN/+k+n937oh35IXn/9dXnllVfkF37hF+Qv/IW/IJ/5zGfkb//tv33tcX7sx35MgS5aUq+99lreoeukmc/UokpuMzLKogsQkzJo6KQ9U9aI7kBO4qoJyNIfFdOM7+kk4kk4biHsFZDVwoQh5yUlqPrH+K9+Hyu4A5H2aJQ7N87kG268LV93cF/evLohm76R1dlcWWooL45JHJnvs2Ur/cVoBIFFl/J6YuyK7og08h1wMWm1W1RJxSRuNOv8EOAY0a9mxRULTRf2Q62Q6Qoaqb88pqdWLydqtYQ7mRa9jHPE38pyKQRNNsDcW5aEYiAUFLz9PKagkKvKqrW0sNIKKhSq+no5SF6Ah7uK/NYVn490JRIY6o2Tj9cUKmjEyeWIxUGcDYOrZ4+2WzpfG6wmB6kITvzixWqma5DbR+fpFC8dPJLDZi2fWb4o06rV8yvA6fkb+dLFTXkgS3lw40jdbgAKrnxh7cB9B0CC+w6TPyZ4TPaQMSKDC7EigNHVFtRvMO+MPGB1nTqllz/slnqPUD/qhfljuepmCl4AKI1j4dxg5Mkkt9tLnWjvj738k/PX5a31Dbm/OpQXTs/kdy+/rBPpF2a35KJZyHOzCzluN/JwXLhaOuSabMLcbHMZCloKq2mm16AK6QPGc6hAvOee4Ad0dMhdKUjRcEJcU8EKybzuPmXCLWJSsN5ri3iPey+ds7LS9Q6MpRsyHYJW2LaRcd3K+mIu65NeXZtZaj1viR5efUAWIPuHwGQUctPfU4sHALYHV5JYr0xK76ebEYsYczqCdFUC1Qct0fFVAamf+qmfku///u9XQOL2Z//sn02/f/u3f7u8/PLL8kf+yB+RX/mVX1G34L5tsVjoT72p6w7W0XqTLSq9ow5G2sOt5S5ttzJttgYoXUWqkABqpK8/yRKN6hKaguXCXXFS8uPqixIo7INy9eQAqaBJEATrbJT5A5HxuJHL7UwfenCi8OAh8XHl/nCwgS5eQn5GI7NHeDhaSz5dGxVWV34OXP3F4IX23ILC7/5kKAjoeb3wXmLSUxw1dAZp14h16S4E7WrgBVJJAfJa3sAzHZUoApceJk1YUe7miyoOfr5h4cAU2sHic5azEmnhOY9F3X5qddpkQlmbghXIpvvE/0Ql63R9MW4Zdg7uD30n1O4yi8nrCsl+K8zan8HQXjMQ0bWniuNu1WlhQR6OmnuNaCAdLjaAwmLcqMtYRyLGiFqikw771bqXqVnKW/2JKkpgjFl13FEebkCYmCtpARJIsLRwXO0ut360RlG/Qf0FBSQw9VIZCL+w1baX7dDKl6dTuVqasOxJDwD8/5P3p7HarelZGHit6R33vL/hfMOZ6lTVqSq7XB4pG9zEiMk2baCBpBkinCYiKFI6CfxIZAmiQCIRRVGEAoi0WupEKFhE3UGIdtTQNjaxOy6bqrLLLtd45vkb9/yOa2pd9/CsZ717f8dVBEM4tar22d9+h/Wud61nPfdzX/d1X1cl+6VNPP+9qgux8LhXb+EpkjiyGp+Yvoe7oyNU2yk+ND7FjhB4gI8PZvhQ/jKQzLBoc/za4hm8vtZyA+FGHltJ2xCzZ2FAZPZ20YzEjv6p/ASfufECjtshVifscDa5qrjJ28ecjYFw2SMijTvq+hAIdU7/O4yZbmz2CDI+WPxW2lBVgbEOJVuLGoDlLXycn3+aY7E9xMlkjMlkrb5ZdqC+Lr2K3ac2Jt0iUFXOJbSY3FKMNl6G7fh6KtFzocLf4bjktRpZvT6o3l5ddvak+ti/sCBFht/P/MzPvG+GxO3Tn/60/H755ZefGKSeuFmAkOZQVjkt0EiQMXq4rPL5vAcobjHs1stPY8iuTwB434N4wvP6diMTyGez3mJ9VWFEeo9VF6SkkXBJp7cE60o783lxWWdYFmvMIozalQMC1CBBSqnHYtDGhs61hUgJUo0MalHjjqPqhmq2DKVgj919PyU5CJ6jQdda6z0Ib57PoKTgO5d+I60zhSAlTbEdtBfXki4RHcLJdWvzzqgvrDiN/q2sPa8/RTRfey6MIX+PZyvec7TBmo+DSTcsLCgZph8/Ff6KJ7s4psXPWcAJk19kyS7/tseC261r6lkDru+4Ww/YcZkqthwPszg/DlMvELVwZj8ppL9o0KaiByekBqo6MBsSKrnCQIOW2VTXJOourAKvWXGeq3mFjjoZHD0nrA8VGJRDCYSsg/H1DE607yAEeJGNZF9Ukthl3Sqd41Zxjv18IXwnSijNrSGYY2+YpLhopzhpUryz2hdr+HBNnOFmyhP+Q8iS4rgkWVBVA1TnIETuorCxq3VsnhATK6Ise9NlV8a2s26lrr2RvVwB7cb33lWJRhvDwtGtKypwooqSYr0uxL23pfdVZ1i+gR9esePoAx26U4UI+5e9pvtYP7+bBA3f5ZP6qzZe9Q0mVL9lQeq/++/+O9y4cQN/4A/8gfd93Re+8AX5zYzqm94MPG5LtnrzxuUsRGWJSjOnJoKWeKYLau1F2VOojUSCpzHlyvbfY+9t0ql/0817t4ze7fI+omZh0JBsCpkJc42Z1FmD9SlwsRzIKpQf+5Hdh9ipSzxMDwXqYzBicyYzhOUWYTnWlhIJcIqhJ6LVJoZ7q9R06NhjoY2sxYxNjObk6o2d1mclEKFZcHS0bjXO0wDD2oa5yTqtndfCakqXzo/Vl4LvUeh76tQjpA/JdNFCgMo2MiW7NFpnsvdtNLJ274mgNqePs9DN3pm4BBoFkRAMwnCIrrc/rpe1/xtP2F80CenqeCNTC3RzP8edEkT4vDgoMdDIcNHeJmVt+drKglSiGQ2JCxcVlcav4Xw9FHHYMm9Ud45sNk4ziww1aeplilkxRFlUSIZsneLquLNdlxpTnok3VFAgJ9VZODe1/JSpZy1k1CmrztlfDHo8MMoena3Hot23X8wFRrw2uJCep2vFuVjCM8v6xfMPI916GZN0ju8bPRD/IypQvFtv47PLQ/zU408JXEeIiUGO5/rN2T7mpVLU+flcUHnNJHRVEO5rCiySAoNkiJKLwCplnAo9a5k3eLNHzmFjE/B1IgX/LqdK+JF2BF8nBO4WF4raLB57cvG18RgOY8CnFo8EEREHm/Cgq7lY1idIygVwfjrGokjwzNaxqGtw8eDaebJAuWp6Mp0//afb0Nu/bWGiyhH+ii6bUuNol1DS4H9JdSK6fzwzi6VH/6UFqaZpJEj9+I//OHLWiWwjpPeTP/mT+NEf/VEcHh5KTerP//k/j9/5O38nvuM7vuOb/pxE+J3maUQMY22sPQlQBr/5kiikz084PV67kl4hU63wZtxveItgQmlA7eNGvQ70IA3E+Z6zhimqG7wmdg/LBOWykAZF0nidVROyHYpbLhIRt+wm2QjSMmiBAY1FXtcZE4JFpeQMb3RVGMo+t2xE7VuJJX5TeUDpgrurM8R1LsmGIniv06TrApzf+CFg2+ozwHN2o2uQ6mdKPkG0G3BfBw32X9c9bjCZ3SGSUflwuBRIusvZu2hXDR3LguMF6VUjJvQrG/mhG3c2NuLgGGVV2rdnMJ5kQl0GJXBOWLRHWZw1x+oEYVMI6z5Zg4pBSjJvU1QwIoYi30oLJ+THoNPJ6uhzeaqwDgOU9uNU2iuDFOOslKAkwSrJxClWh0EbtSka7EZZn5pNoEqo4D5ZJ2JwupafY5SUkhF9fXETD1bb2MsrmRhnQswohOb+zOhIjympcTOfiabf6XCEt1b7+OLsNs7LIVa0j2fzNoOskTe4jVOVEDpn4TdvkRVNMIyUZFWck1WouBKdwwSV9E1pk7S3RLhUEhELz6Y4hl2UWL69LEQNQXDo1zMjC4qbOYa3H3YoxOVgFgcweYr7WWWo5loeoJ/XkP63BvE9KShs5jyX5JEMIdgMcXFGpaQM31u315iiHvKusL+rfa/+hQUpwnxvvvkm/syf+TO9xweDgTz31/7aX8NsNhPywx/9o38Uf/Ev/sV/tg+SWooV55saSVma8nnnICdSSXKVOFg34KiwGQXdC9CCxmnd5n1brr+BQOW7D3+H1ZI/x6VoYXUyIyDUrCM1SDjoljmW60KEMbuJpwtSVERO2ITISc4p1Ky9CMPNJn0z4/ORLSrP1CGjSrbYmduNJRCgUctjGaVACbffBmOETMi/imRS9rr26iDlzrAazDr8XQ35IlZepOLQ1WZcSy/KmKLajRxupPoQYDPJQKL+bD7nGmsCQfaHQvjem/DLJkzHLa4vxfSnaDj03hPVnC5lSwG+89dbzck19eIgZROKjvHLqtLMWNyszmEvCsWuKSpLeEvYZxYwrb4l/lBpI6tw1nQYsLRuqatgPhcHKGYwAp21rbAHSZzwepbWIbqpzf+txnuq+qFuufoK0tuzZoTnBw8wTEq8ll7Dq6truKiGIvkjVvB1IZ/NgPgDO69IHYtr/Q8XRzjIFrLa//XFbRwnE7x0ch2zmvR307GjVYoMCojuIAMk5ZbSvEU+qFRs11oOhHxkdV0ZAtaHyfFU2bj1gOOwuo89GcOBoGTf3RZx4b7wsRDVoDYjidw3GylHG/dcJZeVTEiKaee5BOcRbzSSqt6nHNENy6imecXzm2Mr1KfsHVeaLIZxqTWxzWbfy+HxX3CQ+n2/7/ddyXRjUNpUm/jf7Ccld5A2rIbPdIFZ4aLGqsxXYL5efyJE+KRzFijYmwfwBHjQ6mJ6eaImY1crd5VwZ8lF50ogtnWF/KJCcQoUDwZY7YxwtDeRizpvC4H42CXP3Q9mugrPFymqcWssNic8GIuLjDbRJtPHCZPxvcy4pKOeNSqzOU/3MmRr0tpzFDP2XunNqsKr/R7nDiL0U2urRa8rMVMMmU3fviKw5uTm67OrejBd8GW6Imh5sAoU8g3CQSQbJPUmz2LssRDA/McDhVxzv8bxLBEHLDsRkUqAGwQGGtRmgIqNBB1m8YxJHovqTNHn6BqrI0r0YcgY21fFFL6DVPRKLC6UQMHsleSGVV6rdxR5SAxONDJkE2hRY3e0wO5wiacmZ3ZYlg0EUz0NdsxePJgxOIkiNn2hmkxIEKuUFhwRBZ/vFbhPWxeUbNEo86/NMGSdS3p5Kim+M4g8PTyS4EeY8eOTd0Vp/cXBkTQYD5IE42wpmoHvEdZsEzysR9hK1rg9OMaP7X8BPzn/bThdjVBVev9nqQqdUnWC0CK/G4PltfE5LsZjnA63NGiwdE10gOOEfCwbr17fjMkLCqO3GJxpcCIUuN7R1xNq93uGBCZpd4iy/J5GowecADNGC7BGhWV7TdvR+IxJHlyw8oPePdvFqsmwtdM596pn1NVhoRc8rOFZY2gnFNv1TnUvjW04fLz4e0WTMeq38tqkK6OT6r6uvxW0+2TJojpVvd4bzkBBceKKyxKz+jzzcZaaXJ3NbKgrTNs/rtinPx9LGPcONrwuWH1cytLsd9OItBGLoflFItkU2VVc2YrkpnkAKTTZdbenksVoNhM+0qEBvj7EU216YDnMEUmFL8zKQQKTKqLzBssW5qfEH7mRHMpwRQ//em7219Wd3Jo89lJyWnhMjOgsL7TJNpy1WKduI0iFG98DTwTX9YJTRIzoBaeIut3PZuIFSZRRhoZNX+rG5nYbsOBmzcqabR2+6wUiC0L+mBIhfDAbXBY9FjLCjSEdLwzFy4e1GVOhFgUIuuiyI5oLFxkwVtsSzyh9nsQEZiod2cGcVAWJcDlRzaycOs5t0GhmxfcTFuTnV1wkRStpVz2QrM0CLvfDwEGZop2MlHY/ra1lTWvcHZzjRn6Bg/wC62aKVTvERbmFkyrHGyu9Lxj0bgxmcgy3ijNRlPDaWEIEQhAXnUgJDXLyXLYpDocznI8vcLa1qwNqTfktvdYqfWTQtIEMmxJboSeK3S9eS7LxnYoFS3ShrqCZb04RYf/RZ8DHWQxHb7xOs7pEsqn5YojJYC3XQPlQBs9fMRVeCeMZFunQXAzf9WDlUKuyIR5NfXFNyhl9biFPOJILmpWSsj/oQcqLMxaU5GaNPJ6eBM0JacEK/GT90cZDzAr1ggY5I/tRyDAsYW2OJvyi5IcerGfBJ9lk78V1NFPKkJqXsP4chLbvQMbiktlUgtEjYHE2lI757cFK8HgMazTmrpov9Cbhik4md4HNrMmzd65scucNR6JEMD7sTiH/zWzMIaniXJuER4+0ViVU9mUnFeQ2EJ3OnRWaXUU66mXqgHg7nB6M5zI/ESvPz2cE3fUab+U9bljXNzYM6gwh42Kg6lQZejCbnZuQ0fjjFvgkYFiAIhx0abMMIezHe8P8C9i+Ha7brCvFn+91oY4MYUHLYT8ZajEP2seUkhXCGJR1DptrKeDKRRx7WFQX72I4QjI0t2lfY2QKBUodI9NgwyyHtSYnP1z62iDlWF8rkJLNJAyKhJt43POSE5MW0/nD4xQYkZAhqe70h2IQGh7hTn6C69k5HtZbmFP1vJpKIDvM5/j+0SOkhACrMX754jm8uryBk3IsNhxvn+xhPCxFsf3j+/fxXZN38KM7X0FO5QjCfZZJlam68vKbTJISj+sp3qt28e2774oaxturXTRvjdHMR0I24hgva2sAZ51J+5bVDsXGqmc+2jzeZY2ygCJ6YZ0pQffPrnW47FEt1fcdX0P5VUeLQA9yUW1r00WYEk7nRxMJ0uVBZvs02Paq8Ghkkm4w+Ryo7+rceS9DdrEjr97eCqn6wkb7rkzfz8YngxPrhZRxWsw3W4s/iEGKTbxpro68QjWPhUtjSrXDFhEGLHhXoEVFBfC+QKxuUd3FMyGZgNjAe9UyRN8Tts1jgjESw/fIpS5FxQW32UjKSogTw7MG1SzDxVLVACoyq4Y1koJQmumR2WqOrD2F+AwblxvFiCXCnDPJn3g1xBrR0Ppv6PA5pnQU61gJmmUm9HXff6cUTTivy5aCHUikAhEabWNSwxNkhDSTinqeYsJDnGl5ZmTPKxvQaOP+OZ45BS1A+85Fo0Z+3gDLEVBbP48zLH3lKA3Hmr3QnVaZaUBVZrIi10B06Sp3wS883mVHzFSkVsPj8+ej9YtmSj7GOoaVj7nwrBeeDfILoy0wMzxDU/UGTgZ05WVAoGrJyWCMYjhGWaZynaWZlbBa2mC3WGK3WIjs0IIFTo4Dqy8xY7pVnAht/KjaCv0xtL1g0OGqfZkU8jgZd03GkdqKsnnTFtJUKwlB7kw/DWhk6D0sd+S0Ua+PweO8HkkNVijvphyxbIZ4dXWId5b7uL/cls8Z5jVu7Zxhb7CQ7/YDW6/ibnGqnkqumsEs0RYG9JuipQc/g6F1O1uCQCOhRsKC7OsJyIJLZ9lYYwDwhV4gNnjtyWpRokBhcUrEZyU4WQYpiiW2qAoyYpenijCP9JPpJ2dccYCzRRL9sepRIQodvKZJppmjhui+dFmnXG4gUrQk8b4m94USGaQrFiyeJa1kQWMLNQtUlLmSBY+p3LNZe7YaSEZVrp+QRHyQghRZcUlWWLDihNP2goGSZ+Miio2gsNKN6kFX/Fb4JNmAUjoJo8AgjDff78bs1UF8tm+pgaVKkae2YJ6jpUQQFR5YXq4U7isuGqzmKRarAaZDFpBTZCz0ZmzA1MEfghRFZ6lxN9TJWWpP4mZP2M0DeP+mkIZO3oyTBigaZGM2Pado15QrUnKE3GBGRXe2XWDWhUV91ExrOH6AJ+zpjsnX76B3WLCXFUUBSiWAOriue11H5xbIL91wmPXgY0GKtZcsV9o0t2pNaNMybr/J5TSpiK6w3cyZ1hUUJANlT95VmE2PRNpBd74fnyxjWrsPK/oe+fDx5sdY20wPz4OpjmpmS/GwjA+K7+dEQDNBBgMucHaKlcBAxaBGxXPHF9qwEKmiXHuVCL+J/UKi9QMPPHcGJ2KL8VKiK2R+Hl/LAEjig1DSjWAx4PSfUjw2FbUJn/BqEZTV78HfZZNbz1Mrbr203GCwEjUI+SK0m1ApowfVLk7LMRZlIbUzugVfG85E2PZacYFPjd/GKK2wNit0fjMuSvS8qyAtzRFPm5EcN0Vp2djLqZUafwLxRYsnuX/8fMY0c2f2RS69gZ7uY53jleI2hu4oXN4tprx/qtfU61PHFRWGJF7+BuQiWvjFsNs8QTPPherPnjdeO73UPfe6MP4260rdcx5sOip67DHVifhqQGMGHS/RGJxIdmFgIunrbDWSxcpyVejYoODCBz5IjVj9JbRgV1LkkU2PL9SaYmKCmRRGxohhuhDLeR91Rjy4Ai7s3hOJuPZesCGyasehVtVGaTcHX3EN5pKd0F9huoOilsEARhFQSh3VaE9ylA9zVKOFTMC86bjC5Xcl5CU0WO6ajCR+9bMW9ZJySZolSVZFkzSDKeLRLkyvQYtsUsokLit9IQOYe+3K+qrEeVSJH7JqDEGoU4cI2VGcDcVnIoL+4tqRvM8K03GBOAQifyyml1tGFYJTJBHEjEkCVQTPxQoNmiSnaBiMy1RYlHJ8aYvhkWohrndbtJNa3Gxb0vfJbGPjZ+8Lac2jG0I2NqzmEqA6CwKBjuuP8TtYVqbv7TKnQKoI466biTTZZhSzYmS0hQBgfUqE/OZ1IfsUokNRYnu0xHpRiB+RHEfmunkaTDTw1NJP9Bvnt+QwtosVrk8rfNvgHB8fLHHWpLhfpyJKu2wHImDKyZA/hPDyJJfi/TDLMMozaUpnjYr9W6x9SeA2uO+Z4WOBDhnsdrEI1PbH66lkVO9UDQ7zM/yxna/hZPIyFmw4FoWDBJMkRcX6E8g4LPFutYPfWN3Cw2pLzuFwUBqt3tiKVp+bJmvspEvca3eFLr+3PcfiPMFqlMv1D7VeCyr5XOuxHNds3RBaOolHjfYhEnoXyS2vUwkBQ+F1ycKEXNIpuDjTT+XKjK5/CZXpswQFed5YZPYgP3ctqhOsVjneO9uWvjPXWNQMsK+vFHqiwtja1Nq7TJjwTUzrRaWjlXFGGI9wniuO8DFmTQxMhF45Ngd5jYPtmbg9p+M5XsIHPUixtuOzrmF5WvNxfCTG6OIio1qjCwwWS/aEHUcFlM0MKx5LG0XRsO+rjjWk5huBzTOsXkDsjklWYAsgveDMv+HA6k3ItqSSd9kNouBKgjLrBFLlpvOPMLabMLyYZTgU1iOXdjeSmrG5Q2lEIXe4Lq4B+UrSV1wR0aJXi/KAE2VQHVTYh/Li7KpTBO/qZ33mnAWkqB/JiQkSgAljVSmSRSpNzlTgkMJzA62/UUpqmaDeSoQh12wDySBBNmSDpBIN9PIkyCx4yGFZkIr7g+IBIhOAsFA3Vq02UYSaVH+UhWESfZsoId54XQhoGrA4OTD4DBo2vWpNiL5NIpHkFHXLNJg9kZqtCaUG4NPzqQT0ZTbEW4N97KZrfHh4KutBTlKVWG9Q+aES6vg4XWNNGFqaZlXDzyWWUtdwtEWbQHZJhYPswoK4f4cW62yJY0xkH6+u9rFoLvDMgM2/S4xaZl1D+Wzq9bGGxbYkqrm8W+7gzeWBZGUM/B6cmEkyOEmfF2qBKhlYMxe35TW9SmjYfhig2PieMfgPozHuJWXPkJwlSy1rZlYb3mISdKLgJ9dqM+j0h023RR0svS2urdp9zvG9oujstsJtKhJ8BbxmbD7fT39Kc1g5jHBpIQhwXmjs1UZeZsyrUjMn3mciQ8X7x9oApOZZVJgO1lJDTKpvjDnxr3SQ0rTBMiCZmFww1phz7jvkq3eXTXLCwlU9UN55qHiK0cbj+pS80GeD8EiPbHHFpuy2zgFYGnhNnd1wIQO6TfjWpqJ0WaE4yzB8TLtVg72IDbP2I31RkUClNwxT5JIiqnNS0s0yXQ9CO+D9piGcN2yQjGpkeaOWGYE+bbUl33fDlaS61IqWHleN9lVD4dhYhXKvRJmUWF5EQpkiSRQHtigQ6c3vQS1iS3nzbXQJOsZeF6QkY7IJQBUZuhoPj4yFdGZQzSLH6AHZkzRU1IyxOG+x8/oSg7Ma9TjH4jDDxd0B5s9VqHdrFMMKORlwhTLHZAhy4mPtythQcegI0kChjqQ3NyeNbv3UBTahZqesc1ovWq+x0np2wkpXKi5PGGt67phJERqjVQUnqa18hWFGa/gVHhdVSDQZsKRmUw0wJ4WcigzNQFbGb7xxA4slpT0SUXP4/PWH+Imn/ldsMQOiICzTd8LAYu9iiwZplAWO1hNlF5rgq9QRudCSAJhKoGBd6EODh8r6anPpcVqlhWRzD5fbuFfv4P99/CncGR7j/7D7deymC3nfV1e3xWrjjdWhruDbTL4f4SXWYhbtQK4TJ0bp70obZR8ym0xLjJJasrFxspbgyuORcmOENnSyYC4pZuwyWC4AAQAASURBVAsuZtfUgxxG/l/2HmnsNXkyqQ1bNkXoj+dIGoXNMLFTFukCmCfaPaHhxCHCfh1KnouGQFDf5/2yyrA6GWG+M8R8TMsWaqQx3+yPGbX0uHpzwksQPzJ41h/3TWqLVY7z1QizxQDLlarLyyJhWAlczgxqfzwX+HGrUIX+cv2tQJwQ2rgvH22ij8VOVbPFXmy9D/44VSlchLa3zxgOCzvfeE1kA7JJtrgqSAVmoE81hI+0DpUMB51LL+tRJkWkgZKQW43ivMHwuEW1zlBvTNYhy+Bvu6nkZpJBSzae3lDVlh2K31Q8F4MG2ZCTb4mcEBlXsKQisZZDiSXpurdVJJGuSKMssJmM5ecZzyZDKRxngO8iEoQHGocI801oL6KEy+dt1Prs8b6MkAYs3iA6+epkL/AeIQfCe/MUw0cpxvfpy1Xj4g4zqhbT9yoUx0ukFyWSiwTj1QDpmvIdGcrrGepxhsayKLLTOosJDVRdMFIcX+owJkSo6w8NOpwwu6ERNbwSdjEI0Idib1z6gBPqttum9OtbouxAlqWt0EVAtOnUHZhJSbBioLW3ciIf5SW2i6UomxMieme+h7cu9lETCuX3Gja4d7qDdZXh7w0/ho+MH+E7x29jL6VNRol5u8JZsxQqOes+opRucKjUtwwC4nnSHqUEZ9UI99fb+OrqlpA1CPMxK3IrDZ5jHtPj5RSvV4eo6o/hzugEe8UC83aA83qIR8up7F/GIfubjLpugkyX3GkFPOBrxJQR8pvn4xN79/D67CbeOhlrszsRMtbezBCzmpi2n9Wq4p4pv69UN9P6ConaT3Xh5rCh60duitH6sPYaU9y7127eS3GnzcZzoa2CP+w0uKCFxxCn05H0r3Gs9gEjUwARTdHIKHUjR/c6VFc0SYSUQyq51psU4mPWzvE74HwiCie11kAlm62lT4/XxqHenlLuBzZIiV4f/xHbYGxcVIEe/N9ue240YfdTCjOv/efKZCiqCdhrAksuDmzvu230KlFJnKw+Z/tIgPK6lX2/qka+UC2/BYPUaIOd41lI6IfQjMcLq3LT8IYzVplkSJ55GMzHRk5OnDIY+fH02BEdQA9ONoDjGt5VRAhv/dqM6d6W5kEq7nnyu3ODEOEwYEBd44AVPj9acvYkGZVFJxOivU9txBKpQaWLFMVpiuFJLdkm7ujEMjytkc0qJMtSHVtJQqkzrHc1413cYdalK0qBjUSVQW84/qg8jLKlxJ5LaNweVLqh0unneu1Kg4qcInGm7eC6buREEPTGpIveM10zjmfWAuMxSCMJvUcMUqzF8PmBUc9pKkj2HoPF2XqEe/NdCeyyu6LByWIs2dT/evIMlk2C54b3sJWy+bbEVguxi6de/9vpgdS0PGjrytt6pSxA8zH2/hGCe2N9TeSQdrO5wHTMivibz02yEu+S8FANxOiwTjKskjPJhjg5UpHCm4PDbSUizh35pF/ji/yPOAFKXazE09NjHI12pD5LJIIkJDmbRA0YpIbOYjUkwHT4wnXgQo7TEdmw5ikVw4CCBqTddKSUrjjCOPT2DQaqdmMARPekZmVEYVThXhiedBHwhureiHJyhCE3UX9UF5xcLFitPFhbZICiWDBdGlhn9OyKJQPpt8sr+c22Ge9jc6kt7bHbkOX4wAYpk0MKmwihRnBdr6pIKIjLGCMwuKtvxNATGJBbIFZYthZmAM+IjPxgCuCidhHVxTb46htAb/gwzfzEsNGmMJlJgxKmBoYqx+BkLZPo0eOhKFIXk7JbdbkLbe5peyLisf6dpNtdBGeZUalkkngaZS3yUSUByllkUuwsMySLDMUZSRumpG4afZt27PEmu7DOeDuM3s3Vy6SCjUbU5+TBySE8n0Wim7EnvupPeJOswUnOqGONgUVzfieu/snIa9YZ8qMcxUmCyYNG5WxEx89+8gT19gjpaICk1L65dFlicj9HVuZYHo5QHaZY3GhlUlfWm8FJdsPJaWBQoKICG80T9WZy59N408lUJyztI+rqVCLYaYoRMiT9JAZ40HpSnCUWP9ZrrdFMipMLj5GZCdl9nGTOq6EEI04khGBo68HXkGL+8GgHDx/uoNlSVuRgXMnYqMoEX/zic7h/cICvPX8df+rar+IT44c4TAtMmZUkM7yTX0gmxPPi8lo6xrRfx/tnztZDqWOQgXhrdIqbw3PcKo7lNTwG1wS8PTnDIC3x1PAM3zZ6B7eKU1FemeA63hocqDU8NfmyEuumQZmmIoTrNZPEFhR6npXsIVmF0QII91GFfUC7EcLeQoZQaE5s5GmYOdiA3ixrkvFjjbzOsJVMShrijb3nfCxrWJddEOmi8kcR2Xx4VnUFss0tDngO/YX7MApq8ienuDoRVnC9aDAbzYJkFccsv3+8ua6hADqmDOGKEgpRa8b0eDERwWvCyA5lD2yROxwo+cWDkpBUYpksG/MerL5BwYl/tYOU3KBRy3OH9G2y+yJmXyQkG/TsuwJBtHf+2zse+0Cw090D+4+1JpEB6WdkWiPrKwFcClg8fu/vih1+fd/SM1VLz1RyUQAT2lWzJtK1AvWUGKJezyDfQiLFIhF163rYacN5R35aEwpisTWRAMVMg0rqLpWkN5oeF2th4s9Exlvc6xFvm8oPUcYl2n3Gyusdt9PLY1WIOEh571OsEmGf5YV/p41Lf1PUdxR6oagcv2SDsjqsClvRanOEdapppo7IzEaX5kbLVfRWKlDS4JjfPUU5KVAVa62zxFlRAHMdDk3IPdUVpgQPqxk6o2pjooiDFN9ddeq+XSYQ6fE5guB9al0bnn1/e8kwq6UWMElXlinVOBjMZQLh5MOAyzoPs5PGTBDP1yOp37ElIS1Ys6ylzlCnWiA/mk+QPbyOl0bXMUwbfMfoHEUCTFJgN1uKX5Nr7olDLy1jGCiZsds35GeL1FcykIyIQeZa3tHVRZXAGIe87HxeJ7gGi3qgVHXplLWAH1QwNCgVVHInY5N1KIOaXCJIg7nO9D5x35ie4cOH93G8dQN1VfQo42GKcMicBFIGMVPw77FaZXXT9fOF+8Bt1CyJkJrgFciDohYbeDm3qHOm9xOn0zE1nZDjOgOWuZBnGBl5xj0gqYa01u1jB11ZZJlklVy/unNYZuZEWE8WQoZYiJKJk1OiAOU/MSlIVdP0XuG1+MAHKSVMuIiVDDfrcRGHLSPwe96tyxf1QwoVY/0t2ZIGHZ0TfCKIeqKckmXLdZk/LeB4sNJyQBw0PY2wOhSPUYwS7TV0AF6XFlwNk/LNXYMZWFcVsrZF8Xgq1Nd6J1MygkNhnqF4jHRIwXozqHo+PE5QEiNXkqAW1teZTDxVSWfRVCRh8scF8hlQXBDyMHZhaT8V6eqJ4PPltqs9d42O8Q3ZI0SEmpMGJ9dBi+tO3qjb0cm9xoQ+a++qIMXHjUZNskRmPwFqMpgPlJmS70a9NesdMVv5cjvB7EaO9V4hfxdn/l1JwVcYZ/pOi0WZY5blWI4o3NbK5OdHwxtV1xoKj1o1SmszNjF4QPPfDq10zxsJw0VRrZ6l4AD/ti2aNDeX3k7AUG/KBruDBQ4GM9wYnKlBHRrcGaXYqsZS/3Flc9aiHq228NnHz+JsOVWlinEZGpprKuyTPDNqcb4cYfbSGP9o8HG83h7gI4PPYpIm2Epy3M7PGILw1uhQ9quMQb0WnMRcrskzvDQppP+JgfVGcRbgO2ZYVEMn1Gem5tKPxV6q19Y38PryAPfnW9gZrIQtJu+jBiDtO9hMLAG6Ego2HYbZA8bv7w2pelSqnjFOS3zHjbfw7Yfv4Cfv/U48LiiTlKC2fkDJuuOFX02X3s6rjCQKwnm8NzTDoSIMexAVPpR73BZ8rofJqyemhRH7VQNUBAcm0YWNVSZi5YpuXROEaX3qWc8KVGmC5YEGc2aYDFh9ornr8Nm/LUCtrOZ0thzJYyIxZQ3SJEKoWr6qh6inmC4QfPEVak9+C0uw6rzHrpaP+6AFqau2sDLZuIJWUA7wngccz7RMFLb3+i7l0IDj+/WgdAWlM6hRuCU9A1r8Ojdj5CbBtELr8iBSY1PgWpp8mUXRdZhNvmRIzYGatrwiEqo2751Kg1lxSJHW/m22A2IbYFlduQvk0xIpVSvyRppZq3WOdJYhYZYxJ5kAGJy3QWBWbsKR1mNWuwnKPaC6vUZ6liE7z7pGx1i5PBLUDP8WeaIoyxLMPwpWkWpE/Nvp5HG2pJeny5xCDcIUBpSAoHUoqasslclHfUKqeQyOlqgnDEjsUWuksM9eFzlfJKyNO7p/MWtRzLVmJe9nfecwQzlSKE8m2sbMAu2mzAmX0NqiVjaUF/f1snfwh6/qWQPbbJDkhB6zA2X4uOut115CD1bHJnT5Iad+c5InMYHNq7TB8J4k/pt9SJy0OCl98ewOTk+mWLy8g0pYBZsTiSmxF5xpNbi//ugQF/MR/k46xycmD/C9k3dwIwOmyQKryWt4K9/HTn4Nr88PpV9LJie3xbCJjN+ThX0eE5tr+Ymn1VgIGFy98zsQjnu6oHzSGbbTFY7qc5zmI0zyUiZeBh93DJZAxAygTaWmxexxJ1/iML+QQMzaGV/DSfN6NsNWukbZqmPvRTtARdh3QL8oJR2FecWccCWB5nDlfcWMaqnNvIow+EVWlq04DKz7SEJidh4Kyfk90fUdSu9USIvRLUiiTCpcFq9jOaph5Wav/RK25OKM2U/JGniSoXbFlShb43kWCxVmvazDMnuirJTBfrwGRaEwdxbXYi2DirMm7wn0zNY3vlbbAPS9bBn4FgtSUU4eK0qE52IJJMtcXDn7ScyHS0Fog/jwxEMxZXahmAsXOtSy5CglAzQdP/YeRdlVIpLmfBFXPpYJmoYbm2rzFXsV+oFAvgf/zYASFU9lwDojaamTLx/LBrXAOLI65hvJeKtoYkgGk3XHC8NJg15NfT7WpFgimySotho0uzSW1BuAPUWBwbRhOOjK44HVtwkDxgEqFP67S+Z26J5BBduKjYDk5nbytwUsIQtYJiVK75RhkZUse6HWaAoGLVNqZ4Y3YCMvzd5Uw1Bqd1YgZ/AigcWD/YKq85RJcukYya715vPfPgmIXUQ0vOL6lQS9aLnc9QspOUNudSP6iNo4607y5k6VXMgWVtTW/emE4M8TMuMPd0zxV8J6eiAQNh99ldhw+c7ZPi6Op1g/GqG9XgGjjiIcDl92rjMhh+zxxVQETT9zeBdZUuHF0T3sZa3o4z03OJLXr5ICj9ZbIYPxiYznwSFOgYySRhuKrcfKs0uB7gyOLECZJA53e0xgPOt/YuAx0Vvp85IgtZbeLXX+XUqwzixA8Wi2ySpsG2ElLugwwPHAU8Umdyq3bGYtG0rmcvy+SLPeKbs8CpWL+ahB3G5FE0tgec9UNIVdyqCS/vQUB6hLL/Fg5ZUI3qOlNtamFK6OhI1Vl1E3994ilVwCmvQ36VJKgpIQIiqM2RxtxBSF7HRB5H8HBXWDEkNWZfeEUt5FFVCyqm+dIBU160rdqXf1PDg1fXhOeqnMwymUlpRdp+wqH3WbOfUTPt+fF/q4PW4BSoKV1SME9usKE9Y7FduB6L6Cth9p8tI5WWN6r0QyKHA2GyircadGIkszs4zn27XebwVdheykP2KkBouEu4bszh+ssT1aYbyrK813zvYwuxhh8fp2sHNf7XfagK4AvdqHNLlKs96oRb1HAgL9gdy0sAtKet7iJt2ormJKEiGrjYkYpngRmpc9gzIigK4oO7UGXlfWh7i68+wj/JAwIdJHOtolQzxvAEKoi0omonTFrDTBehuop5ycGmSHaxRFhcGgQtVuo01yDI91oTAqK8xeH6NcDXD+0TV2htrVX5gPEydPv1ln1UDETdnj5kGDK0+v1XBCZqbtFIlQmkwS5CYhJIHQApXDmJ5pdbYX1ulvg9kxf04KDF4UZP3s+fN4enSEO4NjqRltpUvs53MhOZTlBMe/dg2L2dBgZIVQJfjVCdYCDWsWJyQVGWB6XVhI/8LXn0NzK0M+WOP3T9/DzWyOG9kaNc7lZefjER5VWwInsrbEMRcIO0gkkDCbkjpFq4QJIXpQ443KBe0Q//Do28PczSyL5/jG6KJnQ8HmYLIUD4uZ0tEjmrMuDlqBONdJJTqYYzlPtYjb8mhKtoXsrEWyp7lIQybE667ZkDkIFKo4IcSKoelYOsxt4573Gu8/ZuFkB653TFKMkH1pJVbXBOQiKY5MG22ZvgVnn7gpXp4ILwnMble6YFg4vhhjNM5FbcSZewxIAXpl/6D359kHsb+J9xSDExcRhPj0GvXrqbrY6Fh7QoroIQdG2DCLFyUa8R75VqCgt5u8TRv0QeE5ypc3kyUJClGw8NVLWJJEmZft4tJnPymbclhRlhPWmGTBSCoVVqMKhyewYJT1OTQZb+x5uqiQn7PPhxCV9jm1BSdhvUkCkcEmOTbAapGWmQSljVTVvDnPUWYtFhQGTVNxUl1fDNCInbwymdbGctICsUq/qBW2rfQXGRJTawiQI5mDTjEXaxDtLYlFZiVTE58eJ4a4+Z6/LlHBW1fSED8Rfg+vOhvOL5qDelvrBM6MibGAv9WaoVpRIDdTKHNtDc4LVXSXqdH0CIUgQePI3UrqLRi0KMbaO8Ya12qvRlWlmLOmNdfJpzimWGqCxTMDCVBaMG57K3rVscvlWJzx5K+RLqfEtKltCewSNEl084ualtULfMjFsJ6rBcQ28v631wj0LCVC4WaGwr9Zg6GP0/X8XHqijhZTNBe5WlVstbi9c4z9wzPsDufSz/Tm4hBzk7iRW0PGWec2S3jo/nwbv/74Dj6aXQCjGpO0lIzqIJsL3Eb33Xk2kADEH/3WGqy1ZsU+LgYvNtwSgsuknsXPZ4Mx+6KkNkKli0ZFcwPMZBmoIA5cqdv5d/gVMdtR9sveMaVlq28VMzT9LU3bpo8ps0gkrhzs4NlOOPJxH5GVIhNCd8IWVIK8Bc7JDn/zNFr/YSire4a1Ma+0Ph35Yvr9umQs2wtvFAWaBOtVIYuOIud4VITB2aNx87iwIOWc+qKqkQUgfzaJEZ71MTv3rCqw+iJ5OA9g/l5eH45NlXb7liJOREHFqN9O9wx9TUGWxYYrJyhSwEOA8mabK5pz4wagzSCzuQlhozZ8ORPhWFWa4CrUyRrdBeohk/E+BK/zyAkUJysUUyA73UZ7WKIdVqjH2oDBzEdeTjdRUyiXom9iLrwLU99gfLk3xnI2wqzVCbQpM+QPC2G+MSOrthuUu6QPs34DDE4yZE5HlwJwguS0sFWmW3OougUDowrTakuAYOLhO2mAIikjyMfITd9lYfxdbqtfltDevRgcpJSURk91A9bVUIiCrkAUWpzOZOXPG7GcDbQWdcy6mQbqwUWjsB03Nk9XGgio01dvUdJDDfomI6r16g28fqpGuZtiuZ9j+g6w81qD6b0W5QJ49NGxEBOKbbVc58rdV4qcAlYNxwFkMSCkBetHEylWEYPTSVeGsyywuoUVV7C66u1WnAL3RaQDr26FBuDQhdG57DrsKFmdWHcAe6LcUGEnXeCzq2fw2skBigsVk60mLT516y1899Ov4fniIV5a3MDfe/g9uH+6jfN2pEOT40Yaf+wCNQnenu3h3Te2cXd0hFla4dOjGXYEXivxej4T5fE1TQ5N+UGCBa+TyCspRnytKIWFuJMtJeNhUG1xgLbiin8scKA0BxvE2rLelqvWoGeYXrCPzcyd+s7PZPCTfZsKbEfSVShqNF5jMCmxLkbK/pNAo/ciF0is14k0kmdVVoeSGpOTiOxv7Vk1SjrZkRbQvKk3I4GCCzOH/gIzItqSzndN/uyMx6PXRIvBCO6TIVYBqzmBUhU0CFCemVEyO/eeP2o7euDnteFuxIk5pVCtitU6jdxZmFr/7BZhT2LuObHFWzaabxm4L2bQvV+daHNzgdlLDT8mUGsisBtPdsFsY1/hMdO2C71UhB8ZsISipQ7CXTB0uM+zCrP+CExC1SH091AhPV03Qmwgu65hF7xPamGF5stpt8nQJZ70elj3O7MBrtdXyxzpoMZwskY9Ig09kyCTbpcY72l2wJrTcrEl1HWFEDlq6cFdYWu0xFaxxqM39tWKoaf+EEES3YmSmon0X7FGVisrym27/TXDk+50u95fp0htE8SgFWp4O8hQDVop3Yn8GutOsvJNMDlNRWQ3WyhzkHNpcVoiWzCwpdI8ndAFeZEA2y2Gk6VOvHZ5CHHN50N1d+U5HLUC2czJDOC8zB4iKnVwoqI6vd28hJw4IZT2GDXzvE+HmwYl3soq6MvcpvUaAceD1eWusuVWogQnFA4XPQ7+Lag1GYVmTii0chN89dUyJ2d1Rs0wlgkDOGoLrI/GqN+eICVNnIy07Rq3xif4+OABbmZrbE8eYnjjn+J/bj6Jr+AprMtcXW7kcllwtKy7WeX4J/c+ijdmh7j5zAWuZyVupg0+PHiMnWwujcL+PWjJ0SZUO9dzJeeQQSKtBIpkIBkkuTT5EpQ4SSeaSbmZX7iNdLwzgPHcd5WWjnDiEz8DEfuiuLEGNW+1zjWRgL1ElWd4dvsYaZni1YLj3nqmrJ4bBwYf285yjVEDWZjQJVukolJtcaAwrZsjem02qnFddbHbWKAgypQiveEug45L8PaVXWszO+eCFFgU1olM+K2gZFEjjbccK1xAURXCz5vUUnm+LIOS2qAFKSVA6BjlGBNihQUqp5jLlObXQMap1Y1dDeTqfPADHKS+2S0uPvZ20Qm2Xv6sONuKsqF4H5uOuz1lC9cbjPYTN/yGWph/mGV/UYanvlEJKhZE40ksGvTMGuLH3TrDXy7ZD+G4ZSoKABkneRbCyb7j81RFH9Si+t0mHbSYDImnkY/bIplUGOysMB4tgfd20cZFKMt4tPa3cdrdwM9WmBKE3PPJVp4SRGW5aVIyzArjm1BqTWRJOcynNF9JOEjisEbKwREhTiWAkH3FHTBAUWrKIVVRleDnsY8zbVFHpAbtr0qlOE+x+jWPZzvFeskaU4J2ZO6tojauGnUKZbCWpAEh1KHAOpQTqZVMzt4px/YFkpPEpKtMqIJFNxb0du+YU97po6fZYGX7hID9S+bGRIfFcBOORUq3KJkmSOdezodoznLrgVNfMXkPmZ/JANO0wicm7+IXBx8SqRvpk5E6irVm+HjmcVYJ3rw4wBoZ3ljtYDSc4Va2xCFdd5NKGmmFMWZZldSTzL4kCN5KLUn9qHhONfOiQCwnyAxZwkzK6m5283E/zLBEADU+W721q8kmmaUIu4ZKfj6HNxcThBmTtWTGJ4NVgOVEg89Emnsxz29XlyIrO8kkb7lIUtaudPwFfyrvb4wJRL2bZCMYJv3HL61dHNjZaK+K/ybc3Q5S1HWmbRpSc6Ibc9ULUlzceLuAQ6X+nEPV/iNEHvEaixQlsBmkTLlCWM4OuH5jwekDEqRs8nalCA8A70dyCG91j6eNQEGCxVXis75fKyrr5+pJ18Zelc6RRl+vgZmQrdhy2IXRlXIUpMSs0dh9Ljvk3yM6VnUb1v6o0VGLap+FfrLTopUbu9eHrLnY6SCOLv/oJLQF/rPJfPROjnqUYz0eqlYf9zEhwypDeTHSLIG1na0GB/sX2Nu/wMPzLZlkqOYg9RpSrB0xdRFZ00gUFpOPMFMrL/ME1bRFPktlhSo3LvF9Ct1aDSs/J8PQLBAMQiT+H5Tbo96qAG/w80hU3FYFc1jDLunjhPdEzojlr/Ml0lUlfl0Cw5Ypdl5vMa8zHO9MzXOqQTtai+Prte0LfGT7oUyUXzq9hdNrY5zeGqO9P5IsM3lrgllV4/6gxq3hqTrVstbXFFJHmWQruYl5A6/orWPB3Fl7sXYfaevCoLQmSjecY+bg7/Gg5nBegPlkwc2gpEGRBW6ucMUok7Ri9tmZYgj3z31RoJUw3psXN+RasCdMjPsucvwPL30//t6734Vvu/MePjZ9D79v7zeC4jXrE906zRdTppeYNijLHI+W2/i/vfk78cOHX8XO9S/gepZiVyCiR6IWMW8GIu5KIVieHxoSMhNiH9RM9PsKCVSFmSoyQLGOJcKkTaVsRc9HjYQyw1CzWHo7mfK2TqamddFqrZAMPyELcElhdH51QkrksSCz5PcWxxXdeq2G5L2B3u8npa213ndcPDVGqnC2X8kFkgcLq0GJySeZvbLYjKoW0X0abv/W1rA+vSWX/aT836EmFovWWt1QgkdRYTIsVQorZ4ZUCynCv7Mw9YLvVLdo8MWWB6RYhmqYKuOP480XT05DF1feK9JEUUjv2Wl/YIPUb5ZN6dVy88PYRCMw/FyUNsqSDHDZ4HhuZD6yNX22nr80NluU3ajbrRS5BcOPl0n92lTInDa/nwXjtGyQs3+JgYgDPGqe9VWfM4zDYLUsJZAXLPNgAEpo6DetVZGBf9PCgjUfTkRG7SaJgJ5wlEIhmYA32no2EA+sFSdKNsrG8HIMZ3hQgQcZ7pureZqe6Quk/iQMaXXE5UQpbCeuYAntMcPbaoJcUtcTZX1SUfFcLChImFhmWJ/mMhkw4MlNGmSz0q7huaYuYo31BWtzZnzXAMNpjWujCzwzPcIz4yOZ7Jesh4xS1NsJHg4OsFjSBnuI/d1zXBuf4vbgRHTxzpqxUWxN/cAmWRJUfCktoywKUMG354obWqm9fV5PXx89DLwwkQy8PmZagIxPzEZUaLTBrE1xUg7w9uk+zjBAzfNrRAipI6a0eUnx1sUe0qbGtfxZVGmGg9EMDy62tZZpgSAeykLoMJ3I48UUL82u4xdHz+EHtu4JWUO8oszBme8u2DeRqyvvss3Njr7RepFRzZ015qxIFRv2IG7rQdGUUyiTP3Y6ZF/B0lxqP3p3ahYWtQJI/38agl9WNJgezlG3QzSrokdG0B4ny+CiWmpYpPXGfhdQQm3V9P+khmUECtn1pUvf914LifWl+nV4dVhDe1CTxt5IzV0XGRqYmEV1mVFfIUJrn90CJK41ubCyByTfh4/ersXLzrEQhDpPKs+lrhrrH/wgdUl+KFrBuKisb9qOH4wSO8JFJIyl7+wIDF6v8sa7GFZ7v00GtM3iTpzYPN7f7PuxNkW33mWF4XmjMkdOrXZ2nTCIFLLpmbZFcUL+zdWgfd90XCO9sZT6S7vKkD5QCjKlcEIQYC2mTrGcTbEzWUjt5/zxtkCAhP7yVaoFWoFEOop4+OCoRiVBOmukRsbCBiWYOksObY6U/ViflVh08GeHoL+t2M3AsKBcjxR8O1M7urXO1wUW6wEW1TbWj9UzKp8Zq4+N0cw4me2VlUhODY/WWO1TKr5Aw97pHJjeXOPp6RE+vfeq0LV5iFTL3k4XOMwu8Lnrz+P+ehdvzvdFd+7p8TFeHL0nt9/XV7ewJETSdgGKAWO1MbuYWHU34ZoyRfwqub2ZHRmMquNGtQDDMPLZyxp8vRfKFdplXk9aOX7RqEsqnDQ57i3HePPBARqO6cNa/LXIBCMLlJ4/w60l3j3ZxelijMftFvYHc9zdOsX98x1xsiUl3eFdZx2StCILmQQ4Xwzxa+kd3Gt38MLwn+Dp4ZGci6EFCtqG8Nj3soXUh0iFpwo6H2PQYlAJbr/SJ2UWKSK92aq9hxAr3FYiExSAGayzyIIpp63qlRqtCwReH58s+SjlcZnZ8TE6A+zdPcXFehfzs6K7VRlUmDWRV6OCjFp7GliAZ8ktHu+GaHi2JNmXkJqUdduwL89U0TbKZ3ps6WVI8JKbrz0WhJx9HezKE5YBmrCOZEvi7SRBygMPekFHJLMss5dWh9DS4AFNz6+3VDi7rzdtmRUIP1j3YGK132Bw+kAEqeAL5dsGIaGf9UTXOX7cqegbbD6HY1xUdZMZ2E+yugDo8knymMBsERypr1B4UOjpXbu4vC/0aPlnRjUu7oOF/pTF/zXyswHy80ygOKnpGBsupqKHgSs3ilFGdTTKJp3yRznqeoJ2YvUoDuYyRbXMcbA3E0jvbDGSv5mh3D68j2Sq+6IMP1fmb5U3UC5yCThO0fUgozvtK0iEc0caOVWnWXTn6jSCJUPwZY2EAWWdidIBf6RRNVNoSemxJs9imcJ4XAKjOY6erbDaHeK83cbWm9qvYtzaXtaani8xeDzE5K0RVtdrpKMGh8OZWEJQpeHZnD1FJZ7NZ2D9fNW2uF2cSHb8xdUtyTBJv7574wi7xRx7+VxW5ISfPEDFN7nMH8KI01lIdBNtxhErAzsFXk/qCZYIG7A3mntbz2XVJm+eGx4HG1YZvPia//G978U75/vizjswoeEl4bK8wvW9c3zy2lu4Nj7H//T4e5A3jcgqfef0LUyTJX5l/bRowgk7jAsi+TBfKVuN0OC/8/kIy/kAn999ChdJig8Xj/FGNcVb5a4dzxqH6Qy36RycAKdsKCXtvCFepgGEr+NZo8isqsVrgEqcCMJ+MwvuDFqEDpm1CUNNoM2u0dt7pRQcTTGjwgRqjNuFfLfbeYud7SUelNto2xfx5nCIWbYFGDrhTepSO110QSnUr1xlRV7c3Ysya3ibhUhedcSGsCZ2BMIyxUv1p6SrZ4XFt70vWPD46xzus/WxCEwT0iWTl+SUjMLIymzsmnD7QUb7/YyoE8F9XguMId+gQxhmue7AXVXlmw1OH4ggZdXtXsYkWywp0luiRM8HqowvWzxA9SG+jrgQfd5vlgCFwufGlQtXlf/voELvk+lJMgVQKNqnMAUJ9dVq6b5gDUn3G9QerKlQJ47om3vXvH+E27mwLrTM0A7qAAvqist6e+xHpBDrRKV/ilo03bbYxFqs8c6YNqQZkvnGzebfJfzYwHYlidaCkNzo8bKwc+WVpl+zgtemYikg6NmJIApZDZo9ByEjqQFt5/I9zvZaNPetnhWdy/BxZS1uvEPW+vacVKkFdjaZ7qQldtNSJsvzJsdRk8tzrJnwZhVH0jrHo3Iqn0Gmml+7YMXhf5t+WeIUagNFuioA6wP2/dg/JBOevc6V0nvjrz9mevChAwCsVQnLUMkIDKAvnzyFB7NteT3ri6Rdl8tcMojt/Tl2J3NRRdfAX+GgmOGpwSm2sLQx0p8pO+q81aks6yXrc10WeGO5h+lwiY8PHgmrkN+ZsFwmsF4itaRtKsqznGg1s7VR03kNGGwoZ0Qqv1w5mfi1uF9aK7R6eGnQclUNV5d3HUX1slLNA+6b/+KygD+8plyUsGbFvVPvjw2tHH+ykIpqPRoAunEZzEc3+pl6CufR5fLHZNG4AXwFj7Bo2gnb+1U2fA3YFzjpgpg5Ugt86urkkdixQnVd8HFIL9xjng9tHIOQX/RUhEOMP/+bhfc+WEHKrSOielI/m+JPbF0ZZ1n2mOfAMmn1Z3dVTI+zMROh3YAVg8VH9Nk9p17PyHx/ghF0eHjv+BxSjPYfnjOoMF2sMTgpMH5UoDKXUGHBsXlXajydmKVv7KOSGg/FKtb2lUmL3W6xvk7KoPZy8M2Ewsju4+TLLvFr2zOcosEZxpg1A6mLsXmTA5bF7NHeUokbx4yY4VR12ZMpTQiSmmkWFNYGZPiR1MDiMuWZCFeOVJKIASwhq5D/rtRqg9lcsk3MghOQa9t1wZ9/sy60U6wE+mnGKeq9CtWUNGCKzJbiF5Ws1kDOAh4DfCp+XQdfXWF9kyv5BG+c7+OZ4pGIpQ5dj8/qm/yMd9d7eFTv4BP793C8nuBoNcHPPP6EZD/7w4UoKlD5IDiXNgYjWXFZIKamEbKErjS7a+4Nugx80tcjxAezTojXPDYew0ItssEQ63affJhVoMFBfoFH5RYernZw8uo+1vUAw6cXuLN3jGuTGb7SJmItzyzypflN/EZ9BzuHC7wweYAf3Pk6buQXQj/nIoWsSFHNNyhRvpX4kWlNSpBdZi6DGsmgwi8cvYB3V7v49OQ13M6PcSc/xa+vb+C8GeKr9VOi+HCYzXArX2KaVLiZneOkSXHRpNhOlxI8eJlp4UHq+gJFUO8WQ0fRmVOaPeG+7XYl51Ho/sYE9HBw0kzDyv5OfiJNx6q0Tj3DFo/qqcB+03yFbMSx02L0WLMRtXVJsC60dheaeT1IWX0pVpMgIUV6rdhXaNmT1FrlxuwbIQbKuQedOsqMIrHmEJDCXNgPoJfW5bUx/BacBJSAI1mlvc6zqeIK9YieeWQAO3QRpG+37N7Pc5BI0jEqxuY8uxtFt6taLD5wQUrgoTgweeNriFEbq/P433H2srn676dhPRgw1FqexP6LA6RXZIP6xVXOvRtCkmT8kEvtPVXxJt/XWEu0O5+pxh5X5PJ2twrwRZ8rKttKSjToRO1BBWnlc83GQxxEzbiNGRNJBFwFy0tyKiCnMgFx4mRatVwM8LiaYrEYYLUsRKg2/h49TTL5mn2x0pBUmtyRag/aReCI93gudvD8UXIHKeE+GcaUWBaCpUfJKLQMsHI/s1bFpl9ROzfotazQLtfUh0JSaONKUjbI5iXSxRDpmv1NrSgk3Kt2sEorjGWVvZAAxvyJn0Wx0hsFhdmAEwaqx8xMWrTXEhSjSmo/eiMqPTrWrJNvSsq7Bang3WNKEtyUDq8Zl4GEIqEkTZZy43v/CV+tryCE46KeATY00gGP53g+xcsnN7BaF6LHxl439sYoM4tqUTnuX2yrTQMSHAxnwgK7V+5hmqiUETOvQV1jxWseamIObet1IXvscDLTxtk6w6oq8HCxhV++eB4fHT3GC8NTPJsvsWhLzDlRo5GAVZcDjGmbkc0kYAzSFhctg2yCWbrAmgoeBi2yrsrf/Azp9LBzLFmrrf7NzioyjdTXK11df2TxwKxPrgOHilnMs64nttQ+hJVwFKjkob3Dnt/oTQ1uvVaTkqQxvg1Sq1Hx8eDyu2GGyC1emPi/r5hGntRvFd7D4LRO5F6lhBazxGAAGSMSEaHHNzfltI/SozSSmSNQsl6Kjl7HO8c6r4+qWMTbZg3rAxmkQmbiGUicNWETcto87VFw2gwcDtXJWVd5o0ueUL8J6UFrWvbvDYp778DiY5PPMgBb+no2YTBt7uVj+apFcUHdPG2ijY0DewKYFnjEtkM631tUVKkY66qNTYvZmd54srETnd39qxwlIUAOEmp8MTjUqvfFiXR+MRQ9Nf0gitemwbuR0IjaBXQZU/ia4avbRNp5rXUisizIi9+UBShjGopxIYMybzbhQJgth/V3MFAxs+NkRQkgbtJNT1uNYaaZFOn+EqSWusghIYXjqKIrb4lsPpTaGiftBQZ4bX0NjzK1RX8676R6CAlx8r8zOBLn09dwiLMHW0p9ntYCjxFe8yyJk6LXQ1yElhdHe4Y0GxDiBKdjD1JkIbL2wWyPUE237JX90Zpeh4oGGFU/V6ULHTq6ohXrCqoFJDUeXmzhS/dvIS9zjIs19iYLIZu4IC7raxerodT56N770d0HYsXwyvKGEEaoUDEZlZjXpSxOeus8g4rFNny4xvP7j4X9eLwe497JDh7U2/jp049jkLyEbxud4cViJs7Fp02JN6sdvFtt4Z1mJCrn03SG/ZT1KBpIE9BrMM/UsdeL75khGM7mEzUN67kSAgAMCjTvKB96bBL26yjnsU2k4Zrff41EYMVJspZrzMwioOSmfC49T0aACLdxhFx0xoidVY6jGC7yLK8Ta2BFOSRYeLlsY5pKPL4GRYou2D0xGektuu0wGTCXqfiElVzE5Vq3k7XgJmvPfjtM51mo1NMl+ESVEluEs8fPdU+DA6/1BGpu3f9yvD7fGkFK3E+voG33pJMMlHZTwd62Ad1Fzwcq+WYg2xSdjTOokHF1dQ/CScmlgLMBTQZ4MDoWH2fqfa7DhDcVg9RZJoN0cEoBsQTrXSsGMxGRJtMuOsj4pggmB2lCYdhEpF2CejOfpy29FHGtnkLG3haENbfFxsaxruj3RgspmlM/kP1I2hjsEIYRONx+IzrFCsmp6kNPX5fkALMzoaGgnAJSzl1YNlxqHeyu0SYKCpLpuYQLxwEkg5Km2TbBzmAhNwrhynKUo6EEliSjrNIP+hJVlmGN32MvCbB8vkDa1riRn2nTZ5vhcT21qpFOkiQjEJaiOoKcQ/ZzNezj6SSLeJNSeJa9JM6A4vvk9TKZ8ju4LFLU3Guzj5BQeZOLYL4GM67o1erABUFdN60T8fRp2YeUw1vsfWOWV23nWA8hdvAMbHTqXc4GWC8H0uSd7q3Q5rX4PElQztme2woh4XA8w7IscJaOMR6tpa/sYjaSxQQD1L/+9Ofx0a0HeG50gXmT4bgu8Pey78b99Q4eryb42mIP+4Mb+L7RmUB7u2mB52ilka3xG6tDyWheWl/Hh4oZimyBSZKKaSIXWVwsSMaY1MIAzOo2aP+xCVdrbypOy41WJMxVXfhXjB+TdVg8SE+bnX9eM/buyMKM17Y4wySnZIkpokcoSWDxyQIQQsrx3in+VLR6EXmy6D60urGgGqu+a4BkM+biwyndCU5tPGUYOrfZw69zTIygRAQKDyKyJqKYcqtZdFlgfzgPaETfZsOYmgHM04gYGHzMXs0NWceoj2utf8qizMZl3FbhvVXeBNy4RcMHOUglm8SGzS0OLoH0sAnmxqierZnCW64ITJc+IyY8XKEc4fJIMlCeEEhjyPHK5+0/xkQU8sS6QrtIwfkxHUcDlS+LCBThsIQkaP1HGyxA2b/1KoniAFeMaw1UDLCc3DmoqAoukx2LrxSd5WS2ViFbWRGyluT4uVPP329z9FJ1/Q3IV0HZTUM0NTZUeJCZlKCCYsTGH1X6zmLba5atRBytxKQocVHUqFj7ytgjRTuUrJfaKVO2key0PW2Fkr8oBzinuGmb60upop5UqrSdroMygqseUGKK8adc5UIWYF9VQZt5s5UIWH1kaKfNqA65+OIkBqr7EjJxs6RkXMF2XjcvcKs9uqmpG8OQ/lHMOKkkUrJ9gIoDIkFEG4u1ngNzZ0629ZyH4GYTjkBq1o/GFoBbk1MxHHzQbMtjZAcyQL04fYD9tAZJ5tfbBLcnpwLVPV5N8bCc4NXVHl4cMAhVGCDBhDTmlgFrhbllOgtmxG2GLU6AdOZNalRJqf0/duV4bZgpVi17wrTYr5Oha/URuuXw1sUBg7jAsMbu25RQcuUK/pvtBmQUBk+0WFTFJJCCA3bQ6ZN1sx6g33NXQXBOI4/vhYi7tRloZLtizroqY/LsK5Qq/TGzlKdY8tpUz3VXXc+T7zDkneZtpb2g3Uf2mHpRRiVTmZF9uMWtEt2SqsvyP/BB6tIWnxHbOjHZqFYU0b47koKnFG6MGD0fsfJ6wWoTZO0+tP9a2Z8WWYNUUID/NjKoGIaMjrX3PBUsaDVBX7p5KwZ9YblEsVau5oibE8rSpVloJNSeDsXBRT6IQhlsdjW6dzNpkM1S5Gcp2vMxVvkY74y2sXVjhq3rM7x5uof6bIDiWO/YWKvMC7xeSwp9URsoqvzyniexE5f1lxo9EjKQc26vYxGeRA4SLkxNgbI8bCRd0WKDMJgV/FWFoSvQsg9nkCayYpxv72C1n6CdqoVqr94n0kw6048eM+MBHh1N8MXkLu7XO8Hd9RPb9/Ds4BE+MryHp4ZnctxnzVCaUBkkp9fmUqM7fW8H91AiH9Z4YfJQ4DIGg07KSBlq32jhON6CkZwY+zkdPcqWTIKGnkneo3VYXOBafoFPDO7jK6Nb2B4vscqHmA5X+Pb99/DdkzdwpzjCS4+v4cF6H+2sQNFqwCGzjwGMTL+Ldihw7+PlVKztr++f4/9y95fw4uQ+fmV5V9lxGRl8RxgmNb5S7uFGtsSdbIbv3X0Le4M5fubBx/DK/AbulbtiYvjccIW7GYOGTmufGh5L3e9BnYqE0uN6By8OTkRv74WiwlFDhqVmtQw2AttlmTZLWxTh5Oc1PjebpJgpg/Qk0UyMr6W6xRSrYOfBc8jreNyoK/Gd/Bhb+VL69LQHsfOHImxORMIb6UvR0aSkl/Uoet9gHt2aTLj7hR0TWDa2pGiJ+sIxdgLHZSq6X/eexU30lAcqv5VclGcFLOYDlKMW5bapa7iL4xNGnPYt68Kp15/nlvNPyBHeb3M1lW9k2yji/Obbz//8z+PHfuzHcPv2bbnR//7f//sbH97iP/lP/hPcunUL4/EYv+f3/B689NJLvdccHR3hT/2pP4WdnR3s7e3h3/63/21cXFx8s4cSf6jWjawHKf4Jz/ljYjLI/hNj9VkQU1ivCy4hFvWunS9zogBickVXwo1x9nbVjwfEAENGBZzofPa+S+iZ4pK9RrZqkJWmcO4NGr3aT18nTKycaOAnDrytCr0yWBl0h2GDdrtCc1Ci2qlRTahWDKxmBeb3pmjfGiO5XygTMNiC2GdtjvVQ83PIL175dW66AfWMG3/9b9uRs8i8cZdFXyn8Rrpvrg4uxX1CbObWSmIAVTWo7F5tF+LI2+ZUp+e1Y7bYsS+pip4ta2THGaqzAU6XY3G2JVNwLLWStWjZjaX2A9yrdnFWj9Vy+3iI5sEQo3spypMBjhYTLOgu25N/URaZqEFLbUotIrqVbLxGMVpw/G5X3Ogur+eClh3ou1TtwtSrE61HUZ9ur1ji1uRcgtCqLPDmxT6+Nr+JryxuC3mGSgtcxPA5Kmd/eHQftwbH0mj7hUfP4OfffhHHj7cxOxuLdccry2t4ZX0dzwyO8cLgBB8uZnin3MPn53fx/zv6MH7u+CP4mbOP4Lgay7FvD1Sz63w9wpcXt/D15U0ZNjlSjJIMgyQBHdivZYT2CEPVeFCPcFqP5Pkt7iPtMiL2WZHgQBjSJXuc1UeYUs6ijQ+158iE+KJq6DRYVGh2afCWnstWrtm9ag8z6hsxu4zGNqF0rTW1cu/J2DZTT1kg8mO9X0pSZH0vg5tYxdCRwGrF8mmxxFd072jAajuyxWYcidsRrniuN5ii14jHWp1GNairt3hMarDqcq7+B71/sGmvyNW+sRzqnzFIzWYzfOpTn8Lf/Jt/88rn/8v/8r/Ef/Pf/Df4b//b/xa//Mu/jOl0it//+38/lkvF7bkxQH3pS1/CT//0T+OnfuqnJPD9O//Ov4N/1q2bxKP6gv/EE7v/SI3HYLhLBIqob+n9tsAoNNWKS7WlaGbuZVahSBARJUJzUpfjh2JpFNDifqmKPwxSneNuGMibmfhGliPMwLnp2i1VGJPQXbJKkAxqYKtGfVih3qnRTFVVgn5Ts3e3gDdHSN8byApwk5zTl1+xTVaI7vfVLQkdaXPKavxY7+xv9HKwD4rBieyxwaAW9l6n1qDMN078QqRgoKKbaFaKIG6116DcKVBPBwBZfVSfiBmiourRIF3WKI4yNKdKIlhWhRBHxN01XYtithLKdSI7rVWdm4629b0Rxu8lWB8PcLScYkG9PmOl+I3qOmmcItUTyfx5wni2QOMwZy8oXRZE8gK3K1aIHb0Jf0rPmMF9nDv3BwvcnZxIwGJd6dWTQ3zx7C4+P3tOiBps6qXi/XJdYHUxwEeH96RxeVYP8CsPn8XPvfkxnBxtYX4+xHxZ4MvzW/j1xR2pzT2d82eF19fX8EuzZ/ALRx/Bzx5/BP/o9KN4VE3l2u6xTkib+PUAX57fwdcWT8l1yxMqsxcoJFiluJYCWxaIHtRjHDdjjJJciBQ7oritgWqcMEAxUJHIoqQRz6R8caDwlAYmVtZEOgm069AmYAatpQQwXwDQGDHDOxakxN22F6SMKUuoXR1dguKLCslGZp2ezbTu7gwU1gQc91CFRaSv1Xw93FigijUL2iv6sbpY0of4rogKzNpIgtJa1IZJ7BVTXJjWNqob3+jWHYItor5JBOGbhvt+5Ed+RH6uPJi2xV/7a38Nf/Ev/kX8oT/0h+Sxv/23/zZu3rwpGdcf/+N/HF/5ylfwD//hP8RnP/tZfO/3fq+85q//9b+OH/3RH8V/9V/9V5KhfTNbyDC6B/p/x2fZ/x0L0VoGFm9SWBcWwcb7N7eKI22DtBFDcwGukyf0/+zGdwis1zwcU9EtKGkjSPcZve9WC221OK/FUyqf5T3TQYH7jNqqrKAY3tLaUTlNsGYz/a7+nc1TFF8fBuVwEaq194rnk0N7G1J94WZw/wbp7bAb1azGY1ZfnAV4MA5frYko7EI5N+UOswUo69SM2UjqqNVZtElxOhsLbEEoSxqObQZgxiL24TsLbFVzzO9uoaZjMVl87JcqTYXXYFGRvanUM2qZtZjdSXE6H0lP0KuL6yibXJpM2ffEyW6aLlGXCR6ebSF/L8PwMTA8aTA7KXBxMkF1oAUKQk1+o3pNynOo99t0JPYL2h7udBVsxegoQPG5qQRU1ppWki0wE3mp3Mfd4RHuFsc4fX6MN84O8c79A7yxzHBvsi3qESRWtEMGajZ5D/ELJx9DmSV4Z7GHD11/iE/efBu7qfbFlWmK37h/B19/7yZ+uXgOo0GFyajCZLIU5uD/8dYXcSs/xdODE+xka4HvmJFxPXZRDvFoNcUIJX51fYCPFCs8k5NlyODS4LytME1r3E0SvEcJpaTFvF1LxjVNc0yTEnWSYJ4Mgkah9v0oc9IzSsKPovtHJiVSIVt4liWySiSiNAWWSSH1LXHtlWZiYCdboKB0U0ZmrCneswOD0hikVIs0ko4XuYpGhJB/RtYetdeoLFAJYi+9VWan43f04GqB2bBFQc+38Lr49xWkubBfq5NJq4DJGn0jm05hRqawReM3u8Xwtiut/5ZkUu+3vfbaa7h3755AfL7t7u7i05/+ND7zmc/I3/xNiM8DFDe+nl42zLyu2larFc7Ozno/l7YnhfirZJLix656vUB4LkDbr130GnbD524cR1xU6jUOhxfZ/uI/N1KgXhYWZ1oRTEhoakEbdGZU3epMGmGDvXRUHBXM2+ADBksTyySOPjijj1OL4UNg8AgYPkpQnCQozhK1wV4oXNELwBurvhgNvQQBXNknpVmr2sDrjSMd/KI1xqyGcklKfffXeJbBTQzbzI5Csqg6lT4fZlMO77hdBnt7JpMVqr0WJW28hxnaXOG++Jp6TYCiszSYZQNxuc6xWBe4t9jB4/VEGpov2oFI6gidmc22rHOZr5CwtEg7nuemb+er1liyqIM+Lm9dhtQHSaLTGUrQMRDQnfNO2FZnLE7MPF4Gy1vFmVDLn9t+LOeP0N75YqRtBjwVpsnI2YH1NobS28UZnps8xod2HuLWzgme3j7Ci1sPhGrPz3hldh1vLPbxsB5Ltnkzv8BTw1PRC+Q1eLyY4uF8S9iEPFcMsPzNDO3t9S5Oap5LU2GRCUwrdyS/bIlHF9l8vo6gQkUj2SCzJyeGhH+blpzbcngQY8bE3jdeMydH+I879Tol3cdYIEW4i27ImozVusFCDbCd3VukrAcB2UgWqUc26C5oh6A4TJj0PaVC3/qT5vd4mMT79DHCf/N4xERS75OrxmBHP48fsZ9wwD4GbRzK1NIdWEACwqH1MYB/KQKzDFDcmDnFG//25/j7xo0b/YPIcxwcHITXbG5/9a/+Vfzlv/yX/9kOKvRQ9U9IkLu/FIT8BXrWtXa1Eez85a6rF3qf+moU2vezAQPqM5HvVKStH+8vwHt2Z3LQuGI7Nz5f1yhOFiJWOTgbYO0OnmTwkQY7TFBYr4YMTLvhuJpjsCJkNTpmxqRmisHjSZxyE+mnEosLI4gE5l58o0XSL51QrInFBupT74J03RcmStqwQZLBiCrk7NuaW5MoiR7MlMhGylngpceV9vPIBMQgJRbypH7TLynF2WykPUFZjdNqLP9mzWJ3uCROhC8/u4OKtY13ChTUQpSVMKvX/oVMGf1ojeXjHPXREPV2JQHws+8+i+x6jY9N7wWbCcJVp4SiBiUoN6eOrUA2y5A/SFF9WFfsLnwkihAgzOR1NGWZxZuy/Fhf0RP6pBWnw6Ck32tTcASLGpTjZ5ybWiOkwqT78Wufw5fHT+G1ch9HR6wxDeVc8loVOytUY5UteW76CC9OHuDTo7dx1BQ4awb46voWbmYX+OTwPTz1oVO8sriG/8dXfzue3jnGb7/1Kn7v1svYzRb4jfU1/MbFbXz+7Fm8du86lmWO4XSNreEa0+FaAiQD/i+dv4AJvo6D7DFu5SNpR8iTBAtp1AVuZ2us2wT3mhS3koSXEXvGAT9vVK6K31Gaej1TFTlIPe9OIJk1VKrwWqA2mnrDqRhJG+NP6lSidjFCtSpkPHKhxoVdZQhBJUiF3m+SARnU7eoR1ObLl6riwnuN9xPtPmTdykWMEJu66SDcSxYMmX0JhT3p3TobAyCe0H6TjCsyJE0pg5blOFuNhTiyVawuhSN5fxSsNz9YAZ4+85SmqV7Zcxibv8tojPOVci9E/mEfCHbfT/zET+Av/IW/EP5mJvX000/3MaPAubxiC6lwP8pvPnaJyu4QoXeuXWr63QxAG8+HhqDNVKpjEHb0dZdmit7rb+n1ZVkmZW6/yWyJdJIin09B2N9hwyC9sux8ZeTmqajg3OjvlQZDx717hVyBIvqZYMDJ1di2O5FCCe96oLrj9rsvPq0bOmWmHkHZI1Le+UNSh79JVtWURCoyUY0QNQ4rVHMlzo2THV1GszTFOlEZobPVUG4S1qN2CtUhnBYrTHYWaHaHIjzLpl1S6VV/zeBYG0/8uzgHpm8mSD5RIpussTeeS58YJzzedFyh3xycoSazi0jC7SHW+RBD9rBRDXymfUjzeqAss0uZuxv+cW92kYLeHG/3ftJ91ZpXwpjBfkK1tmzNi9x8npT5gTnPqnMtT2WCu8ML/OHrv4ZfbF7Al3BbMilpCM5rPL11gqeG5/j+ySPsFAvcryf47OnTki29u9jHx7bu4e6NYwkEPLeT0VrUKe4OjpDS3LAu8OsXd+W7Pzs5wrO3HgtZ45C9U8kA5xhJ9kVSyr15hlfya9jJl9hPzzERhQ8qhrAZl4aRPvUxELVYsl8ryUCeDwkTzIw4Vi8aNkdnoY9NeumCIJJuPM8+CYtViNS1+HlU/a6wxhoP66nWrGjNQjkxtlawub6KFrdRNiMkirXeR5Jh2WJNbHPQv18EKmTLhult9q5lBMDIQtHaRLB52f2WjGtal0bGZdTDH3OkIoaHdRyZCoRlRNqT+KRc3y1PnE5uDtGhhqr71LGsivNyKJHaumf5/0KD1FNPPSW/79+/L+w+3/j3d37nd4bXPHjwoPe+qqqE8efv39yGw6H8XLXJbXip2P4NBCyvOcUXIRRJPM+3/XvtS//RvT7S2Hsi2eJSoPIJXFr2umzOHuuCQsQ09Nf5Y02NtiyFpZjMl0jnuRAhVpF1iNgBmKZY+DpkJTGzWjcSqCRr0tHVE7VUNXWjpTvEEPWCyMtcdTmC+3pIZziQLlB15z6CqSRx1NpTukpFokns3MPbCf+10ozLACXZgp2uKtNJlQ63pEuLQoMpD5A9xlthVawFDnSW32R7hdVOhvXOGIPjFAVJL5V3SfZrm7T3mL4D4MUK+XiFm9vn2B5yitSNwepGodAze2Nef4qNqDnqVxmk1GGYliGzaiCTHnt1NgMNP9ZdTqVNwRcZl4aT6/RdHmJKSdcnnN2mJn967kkgYebHvh8GKflMpLheLPAjB1+S2tAb1b7U9fgRo2GNp3eP8bHth/iuyRHmbYtfW43x+fNn8MXTOzg5n6ApE3zXwRtYtUpjZpBi8/Rhdi6SrTPWwOY3cG0ww7Pjx7i7cyzZ1d38FG+Ve3ijPMAbswOcVGOc1SO8NjiQbPR7RnNMwJ4uBimaZ1DmSdud+VO2tDyBNACv0wSjpsSKUkmNrt6FL2nNvVr3UJq+n3d1TmaGpRgc4UQqTDAz49iq2kTqd9xYo6oYLIaN9ArKXOC6eT6/GqzncDv7DIlskJ4e+l3DQjORe1JmFa61nJ0XL+zslvFex4QJ48Yme9q8z67IuHqKFPG9KYgJa7kRQcfrnJaFvl/Fycu3MZwXxJ6jwGWjNjyvh9bpAHrd+F9okHr++ecl0Pzjf/yPQ1Bi1sNa07/77/678vcP/MAP4OTkBJ///OfxPd/zPfLYz/7sz6JpGqld/TNtro8XF+ZMoeHy67rJ2HLa6Hn7T0ywsNlCUnS+lszAODN6UizcJFPYfkPfVc++44rNA5QpZoQJinYe61KDlDEVqeJd0AiRZnVhhHqvVAcndMVT0+orVZtbmntlGUWfG4X4BOaLVooCN3JosZmWN58930F/2pMlatFu5y53cHduZUAbicJ9gSjR0pQZkmWG4jRBPk+kPuYrSt78AqdUGeppgnqaodwq5fi8ZzotTMOP8F/WYLkssF4XslofD0pUexlujs+xVSyxPVwB0xyn+3Q4zlAvWuTrWu3u48wx5bE02Hp7gQdvj1GmQyR3aOQ3wZfPbuPbd9/F/mCGnWxpSgZryebYKJuxFjFr0ZYtHl9MkU5LzLeGAjsyo/nNNrnMG1CIF5o9Q1J1CsvAokmCAUnqL6ZNp69Q4dD9VF2C522Cr5fbsteD7Bz/2uHX8ZGt+/hbX/8hCRhisVEPcW+9hddKJZ7cztf4nddeEmbg/+v4e/Drj+7ineUP4w88/UXcnJ7hxb0HOKsm+B/e+wH86zc+h6eHx/hzN39BpJDerXbxq7NnsKzpy5TgudEjPDN6jBvjC9RJhnuzbSFmMCP6wfFraAcVbmXMhBMMEjb2VijQ4DBtsGgTnLcJdpnJosGEMJ5NmR18mgjpgeeagflxtY231wfymHtz+Q8hUAYjVqw4GQ6pGEa4uKkkK/NeHs+KBMpdaZ+UZFeGTqhbr/4WgsFYVV5CX5EJzvo9GWpZUUO99C7SNo1Br2SrTKS8bveQ30u9v8Ok042fkGlt+MkJKFTy3tfFHANVBw93nlDazvOEelVcN4s2F6VVLy99p5tMdo3snvm3qL1Y9887SLGf6eWXX+6RJb7whS9ITemZZ57Bf/gf/of4z//z/xwf+chHJGj9pb/0l4Sx94f/8B+W13/84x/HD//wD+PP/tk/KzT1sizx7/17/54w/75ZZp+F6Ci4RE9xIg4t0KqAEDIR5zr3MqfNx+1BJ0b01CRse1L21Evt4iwiCqIRHf3ygsiajUN6YofAALVBrRdrevZLsbdnTUt2gBqwoUte6kM2qjZWX24Tot5WBsRFcc7vhuAq6sy7mCJ7VZx+v2WY3ZmSPXFiofK5qFskcvNL3xZZU4HgQQKF4v/i8EnK+SAVImGdN5I9sX4gKgQGMbLRl131fBGP73w1FJabUIvrTMgMaq/AgKwZ9VXoeMoMixPGowL1OMPqBkkSKc7LoSgoCMyY1DgvR9Lg2lzkyC6owqELC54udvZTcohBwxln3bqoU+bWFSbfo0r2eqY65emwyo5PbxTIXKvOfX+c7cc6DV/FaZhEA27MpY7qkbxnnC6xXywxSRvcmZ4gX+9g0eQCw1Fz78uz6xiikrrh42ZLlfELRmGipKn4bF3PFvjQ6BHeXBzg68sb+PrZTcyKkZgUshmafVMP6h3USYrdbC5w3rVshRdGjzFChRklxZNE9BaP6iH2mhJPUQHFvrGcE7bw0QxRlM7tPFnwdZajKnBogOe5EIgzW0ofG1XhuTBzugQ3VZcgJV17pVxz2fvKJMSzibxotK8uoAha5xVPsAhej7X8YuFZGUu1BaBmg0QRTydSU9ZMpHeh24gkHAWqJ91vV1Z6ksu2HbxvHO6LXXn95ZseUb17I1JDjwk+Pn1cnhPcibqrY/2WCcx+7nOfw+/6Xb8r/O21oh//8R/Hf//f//f4j/6j/0h6qdj3xIzpB3/wB4VyPhppCs3t7/ydvyOB6Xf/7t8trL4/+kf/qPRWffOb21/0H9Iral5NUhTvGnolK6H1qr9u03GXmweGuOdJ9NCsRBj3Xr1P00DbeEFeryq14jQzMj2+OAD6Rxu7sIMA/XNIydb3BOiRrylLJPMVBo8XKKi+PcmkeC+TyEAJFFy9CZ3cYDoPAPK34GbdkiuwmeQlNn16QHIIwXBtnjIZyDaKLqlObJ4PyZ70GghRgpFmniOdk0WYoji3JmNpdmx7JA6qt0vw4qRPin1To5ROeVUJoPmh3FhUoBAxXPrdZ1ivUzxKEqxYtB9UQidPTwuMjnSCqSYZisdmQunYpR2nPFY32Ptqg/IkwfwjVDdQaOndxa4oFrAh9GunN/ClR7eQfm0Lxf0Ew5NSxGy5Sl1KkGJPTo6iJWXCXUp1RRnWMeIxpZ8vl0c0+3TKUHXv/hDnHsSAw80SrRag4rWi3yF0b/4mBMdJlzTuVZtg1aa4X+1K7YbZGBtwnxvO8fue/hq+fH4DP/P2x4SJx+D7lZOnREj27GyM4WSNwaDC7uEct8en+MTOPXz/9j08XZzg2eIhfgEfxlcvbuJvv/zbsVwNkJCIYYPqzrUTCYK/4+BlvDg4xwvFDB8ufhVvlrv4O9l348FKP+/l8jqytMALxZFkUAThKqnZpVKnOhECCGE/him11iCpXDQLrYblEBOzxt10gfvYkdoYDTOF+Wf+XnVLJ94CeVtjyeKtTaBbyQqrlM3bawzHaxS7K7TUfiRte42wmGJGUhcUbNb2DC4uxMKEGVZsreH3HevAIqdEEkUXqJxjFESir4DuLm2br4mnodjDaqNR2MRKNJPigs1rRm5s6D135hH1ZG5Dpw15lWq6OiD3D1aJKro5qeK3JEj90A/9UF8RfGPj5PpX/spfkZ8nbcy6fvInf/Kb/eirPsx+h/90gYeb5NpxSmmwmVteBD8q82ry/YQAEn1PBjmhfbuy5BXLBZ9x4ibh+DkXu+WfDJ4hUlz2kYoDpHyuz1z6pMmUWHZX1UKgyGdDadBd75lDqFkBiAzSIupsD8ej0UdgLvM04I0kh2MSTsLS25R/2liV9QgTocs+gvrMoE7uJftPuyaTL0F+nmgdam5yM4QAh13E8858dupT0kkQAsno9IPI/BNpJAYs96+RTJqwpJ6z5qLAfElSRYNmliM5sSZP6/8q90bIlhXyWamBgteGDdMC77YoTti1maF+dYzRzRUmN2e4Npxhu1gqXER48XyIgqtxq+e5AoFLOXFzlQk2jQZlCCkg63WgkK3L+UhPWKONpyzgMxOQJt3InoTZjtIg0LP15vXjezqLj+688HjpXMvPI2Hgbn4htHRq331seE+YjS/t3ZCgyuC/NahwOJjhxe0H+NDkAa4NLrBVlOK1RDv5szbF19e7aJMSh4ML/N6DL+NnFh/H6XCCTx28hf18joNshp3xUjy+qEpxUk/wT9b7eGH4HgbJGh8bv4ccN/B2m+CkmuBRtsKMcvemBONLqDxRJXl+16V0mUHEZ8lWXGEtQYX5z1x6oTSTVE0JDUriO9Wm0vjrvVLiPyXBSo0suW9eB34mWYPbg6Uc+ywby03h7DvRRtULKeNSM0uD+Z0DYxmQu/mGx2OZNkvGhCTBLxRNLzpGcXmK8d9X3ZabsExck/J71mphXETxb2c7durnupBl5ntVJhXyALIWk37NScdbP3HoZVrha2vz/QeG3febbxFeY5O9n7LNl4Wak51pfSjqidLleNT/FGVVhNtqrxFtHkOMxxCWs0K3r3K8kddXD8yyrlKvuGq3nk3FkgzxdyaBYrmWfilO5nIDmOeNdMGTceRBI8CanITtI6xxWJ6SepI1NGdXHE4MqVoRtlfvsjqUxpioEizBNoITDebLFiRLGM5vBm/E8133T/TOSONlJkX17zSRJl5mtmmq3lGSPblum2kBSu2LkBFts+eayZSk388TZLNOxkbYVnsF2hlloWok/JEsqpOrylhfSnK0b09RjNfYfnoljDcaG56UE6l/VYscOb+nwD40otQMUIKUNW97sVjsOAIKHKtPK9NQwStvOGWQ0smUw4DEB06mVPpep5mK7XrDbySxxO8rgTDYpaq3ErMvqi7wNSMSPzKlUvLUP8PsZZTime1jPFhuC6xJ5+WDwVx6pL5v8hqeLo5FudyH5kvlNTxopthN59gr5vju4g386snTaAfAJ6+/I6+/WxwJ1Kh1sQq/Wu7g11eHuFk8FE2+24NjNWPMtnFej3FSUyeQcB2HsbsBEMJLFdKU79dgmCSYJnTsVfID97VKCsuUtCbHBYDMBpyULfMkDOl0dT7GbJj9YFt2Dl3BnjVEfn/S5RcZJ+2+qgprUaKPaU2+MaU8ViyX4OPzzwYBSQ6NASomKUWIBTaDDJ6MVgSO1hNK5YFsIaLOet/wezrZJpZBioPQpf3YeOPQ6pK0jiixKaEqpyXc+jYzf9Ao6O+7Sb5pWZFDaYJDRRTvqAm2JWzHlbJLGdGdlf8mxdlHUdkFpfBeZlDhb0rxRDBdUIPwg9IgJreXi0UapKOSBk6Zly/QI1YILMgVfg9KDOJ23fe214Vz0NBWvlFtsJXZBIi7rTKKFEbwPipOotq42cF+JgcVak5GgvCVYAg8ft7j99oNIjefZWXRoYtxoXtLGZNPpWYSkeCxMyawCejE+9EZdqcLcYsV/bt1gbOLMfa253hq9wIf2n2I7WIh4p+vLa7htdk1vP1oX1xjwwFJNqjfIT9PrdgNVFvAegdY70V3EgPfWYHJOwNsvUXX4wrZhcE/XJjkmcCNh7+xwnw5wqvtHTzzqRO00wS/+uguTs+3pDlycEYFEINLROjXzrdZbHAy5OTKSVDhqDpAJqJ00KjoKbMm1rCoor7pyEu4ivW1PePpE8aiHYVo9bGx2bXrWFOxzEoaWkFmZFcPC/YKIE2b1G5glAAvDE/wb137DH7u7KP46uKW1Gv4mdxeL6/hpJngO4bvCGFhmgAfLo5VXDcF3q2m+Np6X47/ohzhZx58XOs6bYvbW6d4ZniC//P+F0TMdpzNcJAtcVxN8E8vPoR3l3s4Xk1C0/lnB7fwicEFnskXKKWzTAdeZXAl98mNx8Bgu0UJKKPa88crgAzVDErb+RJ72Ry7+VwCqmZQhWSizC7n7QDLllluKXU2gUKlF68WVqi7BEgfHNmGQ3PmlUWgDTunvDkczkzLMxYuBApmwh7gujqW15DFvdcawuVvBsbcQsCmtp8HQL8PvR2RU0GvPaSf18hZM20ASl+tS4X8pCcvIk7I8T4BMHM4MNze3m8WDqK/hTpgb/r6LaxJ/e9uu2ql4aoMV/U2bZIdNif/zf3EsFvcDxUCzAZl/FJBM359fNz9dP99sWcJwH3TsM5Dq+sRE3o5GXu00mBMVU+6boBvCM12NJ0rNqO8X0Kbr4I4YwwiJlRY/5SfJidiqJ6fQgTD3TXGlMCpS4WoCiA/VHhoOl6gndSYVDlG05UY9F2bXuDa5Fzkbqilt0Ihx1guMpyvRkI9Z5FfAuHS+qCic87CdEtV63GD0bBEQfV0NghPcizrEYo5UyxgRC3DkP3pycsXDbKjFOnbOR7d3cGgWRl1XCm94dxajwwXB6yVkWARTo3hNApkdWw0fndOnJzw9YerfvvZUOzjzS3WG7SRsPf6RKEsKldi0AAlOZVkF9qwqlbpSjf2SdOHIO0w7hRLPD08ExmjV+bXcVEO8JB5BifcPEU+VGWG+80Aj8sxFnWOtMlxv5rg1ZLQXyotAbQ5qaxAX6UZ1lWBz2V3Jcgs2gyn+Y4EB4agbbIkh5U0WjOrebfcwTP5ilaHlkH5et2p5S71lYDgJbOueCrw1b4wHtkLlZUScJjN8dz4ir5u2dLu2o+KtjF7U0WLShQ1bo1O8W7xFErxSjMol9eNY8m48W56GEN7cqX9wjuRKRAXoipFD8O7AuJLrr4FnzjHx0N+454NU5U0yWeqMuJnY3P+ep+te2kM5XXZ1JWHFK5Z52/2wQ9SnjWFbERnAYHk3CgwzlI23xxTya0+4/sIM8pmJhao4/6e/r41u/GsZANutGP0AOO9VT3TRiMsdGQKg4bSjWN0eJIkC3Fu9UyKKt5WkFUXMivQ6gQdCrqmG6Y3l3rGhHNqxyE3Uuxz86TL4F46HpxM4uhSc6+s7FhXMohq0ODwQ0dCYX5ueoQHq21ZhdNgzyV9bo9OFDO/RmVztfRWV1xOOBU+PHmAj0zu4XA0w3uLXfzao9tYnI+wnucYPuQS1Va/ArnYwVClYq/EjYMjHGzNMcpKPD7fwks716kJhHKSY3BG11Jt6nXFdBbFJ/cbkUz6tZ1nkdxd42PPv4s2KzCjr9bAqMeFZoXVVoKd0Vr8ljZHn0rxdP5X5/WoZyUvwqcuW2OBiyfQsyohBeQLjFt1IlYUR1ezbhfPzILnjLR07nltWnXMIFSg1XumOnkeirveSAf4rslDbOfn+LXjO6Lc8WpzDc9uH+GZyQm2t1/Fg2aEX1w8hV85fUZIJI/YTF7T8TXFh/Z5Tc9xf74tahgs0L9xuo/X2wP80oNnQ22Czr+s7f2OG6/go+NTyXQ+c/5hyQy/Or+NZ/Nz3C0eYy8dSsZ35e0vEkna7Mtgp5knDTCVik+YkQ2/zKAIB4qor9UGeQ5WpMVb4Ge+SDV0CkNw8JOJ+PHpe3iqOMNvjJ/DbDFEftEtQszlT++1tTL+FMHQBaKMc4lKnR+VJFum+qL2HJo5hTK315HNaqfdQPh7tagNCDDAg5EZQggmsUCtWY5UqwxVpeeMzbabqjy/2RYz9Zxi/qTA49mXB1aCtlWwA/8gByluMXDrdZugQLwh4xvDc17k9IDEwOZ9MmzckyDCwFDbcwosJ6GWtNFD4I2/Plji5l8LKLS3FzdYJ0rEx3WFhFNoEJZ8XYDkjazP6mTS8KpGiEIAWNKKwgq6doPoTaO1H7+RLsOi9rk+0K9iG/XOfVeXclqr1nMssyDcFktFRTfXzsEM29MlPrzzEDuDpUBYz4xLnYBTlT5iAdvPskIDnc06z5NVXeTmeHp4hMP8HLeLY7yxdQ3vzvbwKN8V3b1mlXf1M+4lJ1lECQbcPSdSqleI6oVc3gTzp0aWldK6Qq8fTVr5WD6rcPDrCep3U7y3uoE561V7JZrzwiYjkjFaLO/UuLZ9LkoMGnSstmTfSuomcUAKmZX+2zv5E6787Rx6Pws36btqK5S5KnoTTvSuf07CfH47WwgxgtkEswgew6whmVuhQO6JEkTSI5RkkrUQGNxOl7gujFY1l2Tw4eKAGexb9RCvL/fwhdOn8Wi1Jcfybfv3cC07x+38BLdHc+k6+pnsBZyVIxGTJQ1fPitt8KHRQ/khHLtDn67JQ+xmldSWjkf38c56F1++uIWXBoeygPje4RnGdixZ0OxjJkiYiuSIRgwvYxsJjh2pyxl7jQFJ6nxWaOV313Y/8gcVECO0ScNFNUXU9/DakAFIWLodNGKYGUgRXptqVN1c+qQqzaCriUKBvNdCdhUFEX2vtSAQ+o6e32TjtX7bbKaK0dzT+x3/0wNWnLH5k4sM7Vrrnmwz6BtrPnnz2lIgWngPlKjOOAyoJ0eBoDiY6T683++DH6SiVFr/Nh6Q9f306kVhiyCyS0CtjQ5WMcXmmatWdwvjKiBSZmifrHwRXhDVlBigQh1sU7g23k8sQxR3LWwSK3pZnoLMYjMhahIt6nUiGLffIAxSsmKz3flkKoEl3qf/087dpQCVvE+gskPpbmILUMGqo9v/ZGuFvd0LcXalGgQzI06qrswsNYOGFG9eA719+ONNqlSfEFKCDfXD/AKHOaSJVPT9hglmTYF0USA/GwglnYViBiSaO6ohsFp7qDgt2wP0+9JpeHU9136YxijF/BqnNISkXFKNMT2jLlI8PNxBvV8h2avQFoQrE7TjFs1ug+Z6he3RQrTRfCXpVuUCL4WVvwcog/ZCTO9uaneKikVq3e2XAT6T5TcnbYPxqDQhcj9lgPxUjU8zKZ8gJHCYaOuAIUr6U0mqoIySBkJeGzLguF8GiXvVCO+VEw1QLbCVrfH89DGeHT7Ci8N72KUVRz3G55e3jcWViikl37udr/FtW+/hu7bekOcIq92SQJohS3LcHZ5i2WS4qIYC+U3XK3z74BwDjm9tPVeGnwQszaTkh2M1ui27xmc9j0L9t8xVs05Xn+gIRCpAy2DPgKbv4SbjrWCQUpcBIfL4NeL6lSUrZlLsgzInWxkvkV6evDaC88KdYPdLqBpcAf0nMRU8Rjai1/aej7Q0vZUr3Lvhg0kBVb1MUZ7wJrHwrC+lYpfoOM65hc5mjPT3RBY7UTCLMKcnFRo+YEFqkxUn6TWhPjK7NvunoiwlDhAO30UZjz/elhXa9VpIE8KA86xHroOTquP9+z9dLNaf42DNkDBD80xq4z3dfiJFio2a2iWKuocwEwajW286XyOfj0WepWJh13oxqpHSt0lHl5uM/IZhFk6d9uhYJmSZStzj4Z44PbJEnHV5bSPqo9K2H2amBn9yxWh3I51u6ZhLrTeubk/J6hLxwVZIAVvpEneKY5lgGbDeKfdxUY8EChJYIU1EZseVrznBeyC4PTrFJC/xya13ZKJh38s7qz08WO/gVx/cxXw5xHpR4B528Gg2leAlunV5g8WHGyyZzRXqWUXFCsJVfP5kPgAofnsxwuAkRb5MMH0baO9laAYZLl6oUd+pMf7+Ga5Nl5iM2VCjnf38Tvwu7nWk7L1U9eGcHOH2BRw+YneuE6uoRlhwYkbk9uguksrsRpho7SoEMAYVGcY2wPibduxLo1wzmxrYrMkeJGZTLJ5zcl5TH5HnLSvxx29/Fl+6uIX/z/1P4mvnN/DmfB+P9rfw3OAR/q93/jFuZDymFvcbSNPuz5x/Al86uo2j1VQWCVSlJ6Hl99z9Kj669Rg/Mn1b9PGWKEUv77wZ4ufmz6v+HlL8a5M3MB01+ML4THy6vjS7he8dvYUmb3CY5TJhsQa1Q0kkyaLoDXVZuYDnhJYinamfLhA0Y1VZJO0dq0Syio9Lbt4muJCalcKnN/IzTJMlRpMVksUE9YiZVBdl5HZlNj5KkLIG7PCfESO4I2euMtOSRQx1J+nsGEF8ak3T95EixN/aeOiZG25kUr3+RK9Bx89ZVN60AaEjN3sKCbFvtbQ4CDONkXY7yaT4uSdtytbrhzTNWF3Et2sY5lWovgH1lX/1g1SYqKN6lGUw6gllmwWFPua6uVyJYMHuA3pPh6ymR5iIXhDn2Ju7FwaisRBDoIs+N+zDMjmpeW0cs38nFyHw7CTOJGmEuGyQWVDyQ3Umkfz2tQ7/ZmCXmtbG8YqtRwT/hcevqE/FqhSEV7SqratKPu+Ce1zl07BwVGNruBTGFesF7EzhwJ0RdHAjOlKvqQtnGQQhK1GXMJiA0BbrOO48S9hG2Fhi7bAUMgS/JR9nUX5clLhRXaCuWjyeb+Pt8wNZNVMRgsfMyWwyXotJIus5O6OFav0NVgJV8efRfAvrxQDr7QEwpqRSivYxnX2NRjytkW2VyLZLjEXLbin1NWaKUo7zidJgPrH4sO8a3+C+Ig3DIwADerNzk54qnrdgcKhkAH4PR7C9aVXXHwYd2p7VrkLpCKqIFa9x9Yf7em5wjvloijuTEzxabuFsPcJJOcZJNhGmny5EUry0mOK99S5eW7EZt8aN0alkccyICPlxIiSlPUtXmNeFGBmS3ceGY9Li313u4Hg1xXPZqZApSDbhOa+bIR7XI0zSFteseZsbj1wFn9jUzCZlfVzZfGvspwtZxHBNJtCgBZ7+bdnJI2ktUBexHBeZjSVZVJDNR7jRWwlECqnLVLhgomisZFmWQXl25PePjFo3MORiMLovA8RniH4vc4q3OHuKF4fxF4uD2eZ72ysWkpHQrNbDfV8RjmOB3qsPAcjzept9RHfI3UypY7hTmOjGsUP4H/QgJTWobuD2LdYjWC8Sin3i9j7wW2sWGsr2ekKXdFznin98I8HB7MpDoOsFqc7HSj7TmQuW1fQgSoP45EawwCzPUKWhajA4r7SRdN8d2KIAZTeW2AdQv49UdL6PHORo5aVNi6bWvHETbDbvBpJFFR2qiG1IShDkidphi8G4xP7hBW5sn+HmkIrXK1nN3sxrHNdTacQ8qrbEJoF07K10JRkIAw1XvswYTquJTG7vNPsS5NjEeTM/RUFSRbISZtluq95BnLx30gVeKB5hkpT45PQtvLy4jv/v0bfhraN9nCzYlAXxmzrYngsBY6dY4gUSB7Kl6L3xs+bNEF+6uI2T9RhHqwnOrw+xWhU4PZrId+QENt5Zi0jqqKgE4jsYznFjcB4yvTgA87dSzZXR1w2hrunR+3tcIMgbeZ3RR1o5MV1vWHVLCp52qlsIFd1E4vgJOunqxs8uE2Ym1n9EySn7PP4tsBoavDiYo8Bj3Lv2Ov6Xdz+Mtxf7cg5eba/jqJ7KcbCp+Nfu31YFgybBv/XCZ/CxnXu4kx/jvWoPr62v4RcefUSC2w9sfw1vlgfy2IeGDwKB442zA3z+8TMCO43yUnu9SLpoBni9PESRnOHDxakFes36+J0IzF00Lc6ELdfK+OA+nymOJVBNJONSejrf66KmPtFKXpWw1skzoe68HIMca3sp871UGIeeAbB1wh12heTAeu8wQSVGiCZ/5Ow9TcdULNY0hryZV86w9TJ6zcjbRMLccMXW4psLUD2HX/styzfJ7Lja0WzeleNlscK5zqcb8fXqgo6bv+hrPWj5HNtVBTuxWYfkI0kkLp6k1P4tEKQkYGhxwR7wHLwLEgqFxVcxpoxHEF/wcoqvsLHn+OpNFYorajVd31L4z2WYcZPyfulLRe/1wOXqGH6MIixrSzp/OY+PvVzU75uXkkmxZ6qaKNssbuz1m6U7Kx3rxk0T/TxdkcF3K7KNWqyhoHJDBuklV4cw8kcy0MmFNwahu3vlngQqBgSdSBXO4kpfeoCSoUy+DBZkZ5EBxqK+KDKYFTgn+gfVjkB7nKTETjwpJTippThFVbVhk9kZobffsfcyjkZTLCpOSKQ+p1imAyns8ybiRMXje7fdC+eIzao7+QJ3Ricot1QzcH3AQEjjxRoJhW7TBuN8Le7AzMq27HsxY2L25wHK61A+RMLQikgzPqx9YnWKLzdRUCCWKIIgfZI6j5+q5z4hcMIl2YA9RfvZCov2HA/K7VAf01oPs1OFzWjlTvUMIeRQISab4/vGb+Brwxu4v9rB/fMdHOcVHhVT/ODBSziYzDDGSup9/MxPTB/gRjbDq+sb2E3X+B3jdzDfHeGoGuMfnXy7QI3Mgr/IwFaS/ZcLs7Myw0p+3g9NX8Lb5R4eVlO8s97DiE23I0LD2itVWSpQtxwrZOYl8p3Z68XJ7zAF9jIK2vK7KzOUAVuCOLMj+b5ZqElJBmrXmWeTkOi9elt0/6iCMZ2ssbO9wOlkhJokCZMZ66MivgikHU6XHbU8KIHXL9tzuBu0fLbP+s6PirtOkv599sQAFW/8bLvPe/1UXmanMec6xbJixkpEgLT6TslGzEOjuWFjZgoZoksodb36Hami0wPsQEN1xflWoaBzu4obHQLBBs18A9dVGCQOHtEl8MqkQGzmGhsGZMTG6T40Pqj+c1dlaU+8PlFvkqXdSjM34kWA0GKYr3PrTepaWH7pKpMVn9tex5BffA7iY9HAojBfvGJ74nbVjRE1FTrM58KfeqfqDn2S4CTQBJO0aMUmTZu5BDxldFWiNMFJhkGNr+H7OeHJj2gpKQzmfUSqY6fnU5Wu9XtNszU+PH6A8+FIgiEDGm3Fj6up9Sp1VG3abAjhM2kkSLkkUTiFLSHFWmBHhc8UevMTR7jRb1B6IXlw6k5dJzIrr/P1VlQT6M6LZbu+LhGoTyeWTu1KYRptaO0MEFnx4WKf2SR9pVyluusY4rnTo2DNh5lVYeyzaVri2WKFw8FcbOFP5hNkZSGq5lwwkFl5sa3Xkfu9VswwQIO3lgcoBifYzi5wUMwxawt8+VzJFPyer50eSkMpmaBFpg23k2SN/WyOF0f3Mc7WmFa7+MLsaZzVa9Hxc3Sb+SSzHh49wVSeC6XUa0Y5oZp5koGUFaljWeN0F8wtIxOIVBcysniw9T0XFYQdj+sJjpopdkZLrMYDnI53ROCYzfCCNGxuNi84HCgwsN9/0WwbyEUidNy/zy5NLdyuKgtdFaAi+cmw5onqyL0gxV7KOhFtSTHhlGDTkbVcoWNz8zHpWiDxnNW924NTNNJt3yKk/C2jOBFWneaeewWdO2bAqfyPT6IepSJfqLiph5Mr+2PKmLusj4ULU1rhzz5H3m1BLQwO+Zza1Mst2ASG35Nhxg43a/UzGaCojsGJg4QIZ/X5EfNxEjz4rosl6Iw+ng5RTTNVP5DgxF4e9YsJ75PgZedJ1J1JSnD9QRtm9pqwejO4kIFbGIQ+FCOqrTc3ymFKHc5OY6WMOlHlNnkaBioGGZ/8GRy4E1KehWxgkkFCrqgnwuQbiT/SUie3dClNpl5jcEmhr6+ekr+lJpVobWg/VbtzSq8+IrzYaiZF6vT2aBWosYR5RNNN3GjHsj8eD60sjmqlXUvgynR/UgjmVCcq3dqYy/fEtGi9uUmGMBq0ePfohK2ryk1UX7MnBr1YsFMX2V1w88/hRMNj5HnkRK8UAZP6sWL4tjxfYS9fCEx4v05wLWuxjQanjSo7pNJjlWOasNGW/UTMzFp87/49ZIMG//Or3y7HwzrNw2oHO/UK3zd5FdO0Esmkr66v4/XFIf7uy9+DQVGLPUqStVKDe3C+JaxMWqoc7sxEdujm6ByfnLyFj43u4Xoxl3N01Axxt7jA88UMD8sdTLIFThtKHyUYpxwj3YLGlSOotSe1PqGf16LuIazFRGuaqumn+n/qU0VDRVPmMCkpZfepjidp2WRO8tz+9oNX8M5oD2ftEOt2C2U9Es1JuVYWiLyeFGSP4sDjAckuMxvvnSVYkq4eSZCFBWK8qLQt1LGiaelKaC+0wnTPh8qBHw+7a6oUs3IgWTAh6aWJGXPUOpnnqk2bwbm/Lh9S/zKb3vyWt+AXozYerLho++AHqVgF4pKyxCZAa7NnTDbw9zMDid+zyb7bJDdc9Xnhc+PB6U291rDrR8PMKDQZb7x50yQwWMZHVPqIYKE6hRHTUOSMmFHRX4q/ta+D+mHahOj9Gyrbomy+qIfMYbpo22zK7d0AsaRgdFOE5Cm28xg2GAwrYfWx/4WTBaE5zQrSoNpdmoICCQx5oo29ctM44UAyFqpX6+qXE5T2AbH+RChQV8TMhjiBM9jwPTl73DL6BTHArZReLRpx+l4GAyHBuz09i+0p6xzqCzs2JXEGo4fltrDlmCmJ7JB546geXPfDY5HFQegfMSzeZLMayVaisRFtMaYvjdg2ETBziicPD6z+w2dIq/AMTGAtOcfaeUZiGb8zs5HTZojttMa2ZBOWmbQamGy5FfZ8pzjD+SjFIKvknK7WOd5e7Mlc2YzYZ0X5pRZfnt3E2/M9nC/HGPGMDhoJQDxHU+xL4F8jx6e238beYCFmiR8ZHuHuYIY5lSjqEd5e7+LbRye4Xcwlo+JnvFHu4Va+wE4SM9GMkBLYnbr6PxNSCgNaIwHNb8u4RtLlr7EWciK1UI4bwsN8HTN3BjjeiqPhGhWtOyLXXKnFCiHSxJjpEjPo4D8Rj3XNvzANGSQeHAciWx0jaDwJqUCklXnVc+HfDulvIEjhvuYCs0pRlvo9ZZEo5JFu+nlyF3834mSJFNHLvaIe7SU6BLNQioLaBz5IBcVybpadSEBwHb/4jPeyG9mBNuqKVl589SK1dGl4vRwA9fW9iHTF4XVBUSYZg0/CFkgUdix+TJITm11HjxbfBSkJTlT55rTTFTQ6wVkPUhKILPaZW6/UqOhWMlcpJWEc+Tna2HyQq7afKZn7TcL38hSauUzAvaWupZObQpMaJOutCuOdhQiYbucryWD281mA7aj3xkBFqGVAzTSssZcpWUKsKbjKDXUoBqEuYzkwNe+b2blAWzxQBhBmXyzeE86TrK2ZiBEem35JUR6npIZzFa2NnDwOvo6THYOWZFnZTLTqxklium4NXltcl30LXGhKGPzRSd7EYTfUoOWy2lJXaf4WYK5QBHVIRSi8FqRdEJX0dJmUDdLx2lL8SW6DoJOu0rtLKoUnCegkxYDCIEtTwsN0hoTnW5QbWjAkDERctBuv/M4fHjzAVnKO6WiF1TLHxWKI3zi+jVfn1/Dy9KZ8FzLy3jrZw4w0/2WB6WCNrcEav/vwKyIx9KXlXby93Jfa1h+69uu4OTiTc7+ftpgmCX5xeYA317v4/MVzuJZ9Dc8XK2wxg20G+NzyLn5g/I7Uufy4Qr+bLEp0OuM5vlcPtDaVzUAPTdajFPbUn061uxv2DkFTDoqBimOGqhOsh76xuoZFO8C0KLHMaizTSIxZmtdNwZ9IRZ5APCVdS1p0/rhaiIKLT0sOQ5jQrDfQhwGDqITu/3ao8PLt2r0hIkv4F3XClG+koNdlKgLJHFMFlUkkK49H0pPnN+nJs3qsQ8vdgin6kvH+Ijmkb42alGdEUb9Up9bQ9TWFRltfoEi2YSNEHo8yGksLdEWa9XPXK1cvMexmlh9hV65A0aXBGliJrdtllKc6cdkQqPzJOJsLtHrT8hPiSLoBD7p9B2WSVNE7TiZFU45Cl0WLnNJIbnpoH0t2YELWnxjkKMQXd9aL6ra3gDlU6AsAu+PlTwmMiYpsojtFwmqrC8wIYRGKqbYCbOW+Nq68IFAbDevawlhbldDLlfFH6KeS5wnHkfE3T5TCTtiHAYuQDicY7tNrTZxoGOheW1+XrIvwGKnKhH0YkA7p3io1LKsH2S1H1Jc/zAGeyU9QTV/HWTPCrBkJCYAq3r4apTq6n3CnzHsdxgvGInVk//5GsHlClakFQJ8MPJiG3nVmeUbQ4ESrTbwqLMvPYlCi1kSeJrhbHOOsKaRPSWo6Yt2hMrTztsK6ZQWIGZUYiss5GSYpdrIW33n4Ll45O8TXHt7UwngC8Z9yZYrt0RJPTc/w8Tv38Oz4BB+aHOH64Fio6d85ekvGwsP1Nv7vr/ygWH589MZ9fGp8Dx8dPsLT+TFuZBf4WHGMm8UFjpsary0Pcd4M1FV48EDs2bdSkmBanDcN1hageG0J/PH6M8jwqLdEbLfCRbpCVeu5U/UJk6VK9PwxhjA7FMJOM5B9sS/vTn6OZ/MLvJPPBZJmFkm4MlYrd6acSGgRWjfikQcbde21+0ewvq6Znn2Lwa3Xb+EIFkTH9P6mDEZ1ERkFw/gtPi8x46tTlPMCJckTtDaJ3HJV6bzLfDY3lSbTn2561LHuHmie88ekn292+1c7SPkWT+ZXqSfEcFh42tYIcaW695INiO/KKGW1qYjxd9Xl7JWd5HM2tAE9UFkNqkepC89two7R9xZriiiAyUeYcaAFqbBb0xDTDvO4S9DeLQQMgwDjk9Je8bPB/gsrvtCM6H1TdjxcuVUp5lWhxnzUrDOYjaw6z9R0NwqVyerY6MWsgXCSEU26RDX8tJ8qBztiOMmcNMxuMm1uTdSNlwGLP3LIVH9uCly0IyzIZmspvF7KDcsJTnXdNOfR7+QUXJ3oeay7SY2nB6e4aBbCKqQiBpmIDKpCsqCNvdEjvF4UByInTig23z3+pHUQN1VZiAXYbCVqun56nLoIEAV1qetpDczL2ZyU3f9nL10IgHoi2aAG5REbzgWGqiRokRnnwq78Lxt+R2mLD00fY7Ya4KXkRlgT0bGX15TX5dpojoPBDN++9w6eH5zgw8UR3qvGUpO6np9jj0zNtMJnz56V3wcHMzyuxjjKB1hXqtJ3kM6xrNVf6uF6C/O2kOA/p7dWm2I7IaBJk0NKPRHeZdAh/EoiC2FgDZ6sRzFTJjnCYeNAqTbCia6vuoHsclUCEYsJ4locfrlAcvZnfFvEt2/vXnEBmzjbMtdkeZnXnCIB6F51YnOfeP8x8r6QYPzvCOOUzGZNG3n9zkQwuk0zfrXr2JzEukzfz2cn/utAsfZD9ZuBY6LQt0KQSqLMRbKHunO2tQzDA0hn1GhMOJNR6cmGeODgBP6Nfn60vydt+tmG9Xozb2zM6J8X7aOnct492sv45DUkU2y8N8gvEfJjT8fKpH0iOCE0924265M8QUdc6pAxdSAExNfJfPiE7xgHrivYS4pJJSgeUIh1C1/JUxxO55gOVjgZjKU+tZWvg3MnBzlvFofPOFlQ/01ZdDXm+VBWy1QD4KT4VH4qk5+8Tpo/t3C2GqvsTlriIJ/JBMNa1NP5kdHSu0NmsZyAxWkzFudXv8GYWZENt8seKNOK0wVqK1BhghUwmOGieU/6dD6zeA6P66laZzDokdpuN78Xj58kBuOOqJs3r6Kn2s9DOIY2h3qZzP7DiBNy1M52syZdwprbGT2XVpJRcRJf0YeprXEo3IAMryHDe5XaVHxqoB5N28kAtAUUerdM/zqZ81jYoPt/2vkSDpqF1J54vMuqkN6m7955E7/v8EuBSDJOqcdXSX3of3r8XXJ9/vT1X8K14gIfm76Hr45vyLX5I3u/gi8vb+N/PP4e/OI7z2NeDkQ9njb1eVajyBuRVWLf2WvlLvKsxG8fzeQ7SzZkmSmvK/vm9tOVBDTeVrz31PZkILUl1uL4PUR8FjV2U5JolHF2VDc4Qo2ZtS5IPxpaHDU5Pjp4D0Vb4nN4Lgx0Ib3kVI+IbGrsook02UAJEdr824qztFw7wvRXSI5Zi5tJc3VqMXDXxytXwE+4Hy0IbsKCnW6n1spEFm2eYlXSIkYRC7/NBTJOlOl4abzK/aALINejdJjbVfYla+XVMdhYa6s2pr+JxOpf8SDl/9iAx/zf/tw3svSIVzBedAmNwf5vc+i9qp8qEobtPS67b/v5nPdveTYUsqtIc9CPKf4cwcwiyvymBmCcFTIbovqENB6axXUkGisNhv75l06HZVJR8Nnsgg86fbF5Z1SsjXuQEfVliAHh+RCrvJSeItHpE2aRBianeDtF1RtctY+FSgmZwGv8re9RxQkGIIHaJLtaIMu114ob4RveQBI8cjUO9F4qrrp5i6kShAquqoRQIZkZAwwnbrr6emDTThulGZDqwdllK63FdXanqvCV5pp8rrOjPPhsBihNZDUDUr23mAcYL8bNxE/qKgqtOCzKi8lnvVNKiSRZp3be1LIIkDZeow3z+CkuxfYdBnlCfmxWfiY/wo4EZKWfc+IOxyrnhf/TvitmSi/u3McrJ9dxth4Lu/It7OOf1h9S+IsKHtMV7oyO8dzoCM8Oj7T/CJlYxb98fh2LxRDneYsvzu7i6/MbeGVxDaflGKuaGUyDERt7swT7xbl8B15rVRuJKW9mO8ImZ8soGbhEBIL9eNFixMBRO286RvlaFUbVK8+JmXAyVcFd9eRhvSX7Z73S4U2v08YwgitNEMFgQGK/oVwXu98Syit65hTdQ24uGos1K71dF5Z9qC6ep7rbbnNcxTB9T5TGj9VfywC6TlBWmZx31tNC3Sp8tcsTqJJ7nZlqrNZGF3vqT6WZv2SdVpjm/R6mV4P2P/hByuzgg66ePhT1PrnPz/sEqojc0LHojOzgjbNB+ZyP8W/jVntwCsHiiiDlJA7/LN+8/2qDJi8jmKsdg+x67zGSB1XatcF3I5sL34kV3AZJWaOYNSKMud5WurOw/MSQL3rvpXOiN0lQapZejj64rdCFL4kuEyd6UIUXcEuSLFJUx0OsxiskhUI1LES7RQcDFWm/XMWLZp1NQITiOEmTKks5Hg7yo2RLghKzqqeKEwk8bODlipkTDOsynFgelLu22gNmrWZhB9mF1D5GVKgQXyadsOQ0I5X+qBIUuFXgjoHQqzP8evN2KF+dK/eDlM2jFT41fISH+QKvrPelkK9QX++09YeGfDft+VHWnjmyRNCJCqkaUYLQZKqkCFWe0Pfy1SpWqwQCPqQ1Gp18xy29eFVtQtcvbG7NjAiywlvrA1H7eL54jDavsZMzhKmOn4QlOSZlImqlCrg2PMf3H7yGd4/28O7FvshQ/erZs/h8/RzaZSaZ0P5TZ/jBw5fFgv3T26/KcR/XI7xycQ2fefg8ZqdTLIsh/sHRp0RD8XgxlvPAmg9ZlYTW2BB9Y3Quv311rmX67owyoDm7kt+QmTF/a/juRrhTzYUlyj0QphTI0G4vMjqZXWVzjIRsQpHiAY7LqdLi6y2F+3yPBkO7OajfO0TM8qV6T/HvahzVgfz+8cVf5CakfysZQ65V24kbe1ANg+mqyoMfQnLFojF6XQ+irxNpTKbX16IeBO1IOV/2wS7eG28q1qsvFMUKU1DxBZmwR02rUtZHEov1TDsiE9e/PrBBKhZc1Qeis0+BWJ4gTuybW0TlbiUAdRlPpxrRkwHoBSR5d8wQDKQNuxrxZ4iOoKcbXWALr4nrUgEG3FCo8HqbQ4Xwf3uDrwUw99CSlViNdlUiP1cm1HpnKDdEaf1OXqjV9LujnYYRLTeLNgPLjXLp5D/hovQy0giLd0kWloGs8C8d7ZycqcLM4nWdyiSwzHMRoOUUIgw70BdJtAZk18yEuAmVmVThakvqTIQq9vJZcGgls+swu8Cd/CRQ1TkZcwJ/c30N7yYHMnkPo2yMwYsQ3938Iigx8Bh8YpJWLwaLltRmDYSU1GFh/3ZOCSU9Lu9r8q57zb/iuUyznqsWCU7TVZjPWH3ytym1mz+UDhlmojo5xLAhs0ZOGrNkIOd2mhK4o6rGGkv5rgywFV4sztBK/SrB19Y3cNIsME0eY5IWooouuYlN7qwkynoIDa5lc3zP6G38XPEikqxBvbIlP5XpR4TdW5ydTfCLZx/B116/I2xCYYKuM5yMBsjGLX74o1/U5uBsglWZSb9ObJxHiI99VPvFPOgfctHx7noP69GpQJjTlP1p7JzlmKJwrJ5vwprcC2tUFFnh45IZM4OULjgNMLro8GvrhKlWoECOnbLdxTlrnCY5JYrzRa39hoTkYtuOBuqMvVbFCXHEzvQekvPmVHRRTu8W1RWVHjb6oTyYtPHaMJqa/Db18lgP2Invw+j1m/t2rcBsneBiOUC6GuGpEQ0muzfzZVfBfULGoZml1WNdRUWtZFTnUDVybdWVknikVPcQk78lKOhP2Fxk9hJcdgnaiowEoxpWSHebq+FE1dazxwNzL2bfRVuvqTiqJQWSxObrtSLSNft64LtCE9B0BT3j6VQxjPxA9YlVJZkXV0spaeebWY7tuvtt30fOg98J73uy3/e5YIgYUW2lj0TsMZRtJRsbCznIZXGhk7NAeaQ+sY+51cHPm4CZDzdn7PFGIRuLN03RVMLYoigo4TwGrK10YR+hUBEnujkGskoWyFCkc8hoyzBISjn1rGFxVa39Qo6ph35ktPwswld2vWgpspYMJpGAqWsKVXq4rC9hQ8/1z55wWmXICE3dxo1XywhRCXqnk6xPIvFE5ueG+nzzhpUVFduVgCciqqxvNdhNaxF6pWL5WTPEWVPjnLI+/DFR2m6YqCUGp5ot1Bjmc+zRC2ywxvmShRlbNYu4L7Be53hQ7uBBuSfZFCe/ckFySYV8vMLB1gW2ByuZsM8HQ9EAZGCVyc+NMa1fjWOB51F66QSG0+MbSvBUkdmYhqJZIIONuvqqjiEXklzRW29PlKLIMiIwJvU6xdpy2o5Qa0aXaZ+UnH0RUrbzE9dg4y2WOXJdgIhGLvdH/0Rf+ncb36NxhSBKk3rVj80U/gmZl6+fSFihPJL29blCX/JE7ydlR5oQtGRSRpgwDzndjzoAMGCJUrww/jq237cEBV3EVc2UUIJLbM8RN6WG2s/GlQowYbdccd0q/dusPzat6ENgUCikp3QR1YmEcReypuh1cT0pLIOUBKLyR0YIMWKIkkEuAUZRAshBQPjP1CMdpqwg1h387GIxQlukobgbW8p35+yKx6LnhGIb0fFDk2/U4Buv8LTLU+VX+F7aGegKtMV8NRDLcVpisDhOZQLF+1vMywaLvJAV2rwYyMTAlbSIybIgnmvtgBOXiKxmtKhQOIs3DdUKeHN8rSlEbeIjw3vCKKPkzscGDySjmjVkAqqgLYOT2jioBuBjQon1XLIPgQ+FTchahZYPKMB0PddVe4lzWbWv2hpnTYqTusD95Q52i4X8iFSP9UM5Hd1v+sD4i/2FbIUfX26GCmGr2WQp3ltUhSd9uknkPDm1mpM2N07mPvT5en5P1p2892uQvIfdtMJeCnyoOMXd/AxfXB+Ky82r5TZuZAthAO6ng8DrkYyDhpUpiex6zN978z4wAn7u5OOoZAFmauGu4Vg0yMYVfvjDvybSQl++uI33LrbxYL6Nz58+i7uTY/zug6/gzuAY723v4p8+eg6nqzFWZY5Zpt+LBX02djNTflCNpRfrcc1srhUq+gUhwo17eyCLFP5kkk3ptSJk2mKPzs4m4susWHvJUpy3I2kk9oDGxQzHBD+XWRXJ+vt0+M04oJmBKCzubFklPBg5gYQKc2n2+0oyKaOYyz0RmoBjD7Z+BsUt2NxF8mZdOtLX5fOFob4xus97c6H9O+qjmi8GaOY11nu51I64cczpyzoZo0CCiIKMM0vlnLDWRKYu78VGG+lHWSbmnNxU0FdJF1dlaB+4IKW1nieoTjypGLC5RZlJj1HnF/NSD1X02ynT/FxXMBe2YRyw4uNx6DAKZtE+g0o6M6QQpCJ7j7j2FmeKoXa28Tzhv7KSYElr+bQ0+w4/JJc6CgO87YKRnN+rlTWiWqieJmVyK3swnLdIIobMphooxOcLqGasv+gEK1wrC3L0b+IAJuTHfRD+m5Np1mTymz4/DEzLopDfHqj4Q305p2nLT9o1+lK6h+wuBjkGK60yNaqYTuWLiHTAyUprUOTNsb8qxQyFeEzNqdNn9Y82ZZbEwjzZh4ScaL3eYkqFiowMKWUlqocUj7OO5GBcZLbfP+VDixOuJJwGFeoV8OboblXr73PYsBEyRbda9ctKmEUuT2sN0QlZkAO1NUGJgbAgUzyVzXHRZDhvB3ivynHM/rKcNT7SsN0J1z7b/vvM4BHOxi1+YfARVHTfrbTJWGdIZY/RcPLN+QH22jkm1AAcK6y7oGXHchsvzW/K3wwA37f7Ok7WE7w8ux7UP3Sto99zVedSOzmuhxinLXbtjMTnizUqrdMBi1b9wVR1o8YwZZB2BS9FMxio0mgCJYOR2aZcp0i/TpOOVIMv60ZcBBJppBsvnXsZqCyAuPmnoNQWeGTu94BPggL7rXjv2H0TZ1ebgQpXIRZ2kZ0k0W6SJuJ7dTMj83qYJU6EYetVHlRyOI7KaHzJwoqECKvJsYE3Fkr2QCZjMeheExLUwMZj4ELDkQDeF9UlavEHMUhxEhYmQKTd19s27DJ6bDvbejWgKHD0ILC+JuAlFp/sx4JJTp92e+klTcDoOLymFEN4mSoR9zKt8Jg22rqQrO+XyhLeIOyEji5oA8ma0FiLfMm6gdmj+2EZ8SK5Ah5175tLbVsbne9yn7BJ0ei4McvJi8i8UbnqJKwjdbFxhlIgP1XiUGO3FoOcX7cNK1UGmLlYhrDG46s24GwwltewPrCTqy8VG3LJVBNFc2QYstfHel3uV7s4SSaSjc3bcwlOVFMn6YLq4PvWKMvtuCmwMEULVxpfiho090VGnDaLcl3OyZANsj5QDjJmGTW2ctUAZHAlM5CZiAi+WgFBPJSaDOuE8IqbxXVkiu53f9zo5dFA5xND3MGfWuDzeov/l8fB6+NeU+S9kdHH714J8YQkihx38zke1QPcX2/hQTMUokqSvIvDtsI4Z6bG7FFDgpMpXhg+QNIsUIxKrJYZmlWmzazGWiUsytv0y8e3sLee41PX3sFgUmNvtMBXj27iXrmDz2fP4qOT+/jQ5CE+efCWmF9SxPXd+Y74V8l3NNYi4UD6UT1uxthu6E+mcuRKMjFFCWMxMvhQw2/O3ri2kKyYGah6TJk4r1ndEP5TAoZqQTqcxcZz9/tigOJ1C0GqbJGVdl0sQCnqoVRrCWBGQJLnxCnb2H48CONji3u2Cb5GCGRHF2+vnv7CDRGBQTE6H9+rPdX0WATatmaZo15qj5pAyGzMNjq5fGcbdwX1EE0MWuA+0/zTTIvwnkLtOj3F6EGKkXxBLhh0TqubbwXTQ8k26EGh9ukcEL3sxLFfh/s2A5Z4N3XBoGP3bZItCFu4emrc6xQRIlztgq/bDGKdJEBUm4qOyX5asvaiPqq2d1xalNb9eaYSZVFGmhAh24g6L3Bo0yC7WIt9R1plZtfR3TBKnIgwAV+FGRW25yvlWn1+Nrh7SfqiLNFvBN7I6xaDiwb5vEU+r5CWGVa7Kapd1sgaTLeXmAzX2B0tcX10LoQJqhAQwjqrSEfOZd+Hg5n0vjCw8LzwBqHKBOnoPulPshWu5ReB8bc3mJmGn+dKxnprCsmuRLwVDW7kF8r4o0SSrbYJFbE9dUAlbcmUWiwaXZ3z50Kw+CHervbNzh54cfAIabLA797+Ml5e3cTr62vyeV5g1lObaN3FXHkVPlGDPYHxpE9FLwBhLp8cddikYHsylQuYNcpkgu7m5/u8HiZyNaz9UKWhJgVfszeHWshU4/4ovCtW6int4gcKgw0e4u1qW3T9CNe8Ww/wZjXAzewCu9kK18W+RgvjZDZWwwrfd+dNvHZ0iFcfXu/GkOCv2iO3fHeK2TjD2c5YzA8ZfO5unch1e/34APeOt/HZ9Fl85PCBXN97qx2cr0fiUeXVI37X3WIpY0QyQrmuZC7qdeTzrCFO5Idq+JxslXAht0/E+NPbWC0mZG0pXlSVZPdalVIhWgYsX/hIOwIlunjuo4xEMqRwz7i5YbRQY0oiNHSSkDSAeRYjFjqEBF0OKfQwRqKziX1UXEeK68WRW0iMIIUAF9vqROy+uF8yWSdIFqko2xN+V+cCW+hEUkfqA6UZkzcAOw6gLEANTEIvN4ceCVRm8ClLnKC0jm+BIMUthuguQXwbVX/5ZxdoQoDqZTUKUXRv9zqUsZfk5mOzcGRb78fBx2J7eN+JrKCDLHC/NhWoqX4cFrB6f9swcNsLDygx3OfH67/jzJKkg9J+uLoTzb9IJ+xJkKiRJ0ILlwXkIPPkTJ2oeBwugcEJkkmR7SRwoypgtHmLtKD/Uo2iqDEsKoyKUorozIzo90QoiJkPAxX3STt4Ps7mT6e7Ki1bBzwnU07eXDET/x6Kdp/KArllBzfWGQgIikKBLWGHTWn9PyRa1NIjpPg6MyDpUFJxoZRwGWEgqqQzwGi2pUK2JG8wYNS4Vpzj3XIvZDNcRfI9nv1Ig6/x8zzpwIaL6eWmXltYyL70+7s8EmEUv9Qe0JSVp+9RRQZd7YqyR0IGIuG+SqC9rbbEuK2xlTCjAg6zEvOWrFCFswmBntYDqe/wOw9Nh4JHKZBr0uDu9Bgn8xGQXA/3jyuDM0g1cxoYFjhdjrGg4aJkadowSnLLbD0UE8Xp1lockbezBdkyWIsKhp4PaRDOlATC8084UAOy0fIlk1JGH7O++AzGqLv+GBFFAlUnlMo+tE6oVxXofTEgjMNU+/tU2oiLvK727WQjX695jZb3QLjlrXVDxF29WXfj1u3Vjdp+IIq/y+YXDLNd9NmXbul4/+4G7HNepd5Scu+I8sTlAwn7j/cXn1v/gA00wDM0H8sK434r1KScbRcFBj1JTiWPCAe9fibB4joBWd+P7zNWq5AOWJIytPeC0JbUjvwzo7qR9kJcMTSYuVgwSQSstqzJs7BN1p4fx+YwM+gvkDtkEoh6tjISOlQvPPRNCQyZIVlXyJY5ipm+NriCyo3mjaT99Y0GGleeMCHZ8JzfmZ13jb+HX5EEvIxwiDQTN8gXNZoiFeHN+dM1tq4tMJyWMml6oZrTAFeqTw8fmyV8jTfXh5IxUXVcHHaH97UHo03EvZdWG3OjJXPie1xuocypYF3o5CU0ZfZCEdqrJHNg0GLdgeKq7gBc1ZmQC1wtQdyA0zUOszkY1vjVeUoJJVEJfSqTV4Od9D2c1EOcNiPVx6PbrnVg8kZ3Rh2Dblzf8GzHN8f22VTp2ZWOQYP1ImiPGZau6sUcJPhr8R1qx55JtqhZFTNAZTFKgy2V7tJGLE8Y2KX7qz1Gk58r8SLJcD2ZCPV7kS/wZkV4ayTHwu9IT6hXXXJJBFwv5Dt+99ZrmF0U+JXsGWBB1gAHjC1gZKHCzHCAL759G7cPTvHU3ilePTmU3rjf+/RX8WuP7+DrJzcks7qbH+MPHP46HtXb4vH1oNqWL7eVLzGlriSAo2oqorQNzkSdPmGNkD1hCWuDzKh0AUPld4G7TWlCIVwyAhXu0yqMEmL8ylBo2Ost2lOl2S9fcHtwgslgJQSgihYbrPdao5X8NmhPTpkt0tpVV2NyZMe9prz/0Gu7mxJ3ideNNuLFJucgZFfxFpfoY7gvysw8O+OxN6sU9xc72G0X4lSgdShOK9041WZ7XRSIj5koenjtsPNDU0+yRrUOA/Bs1h0CheeoiP584IMUItiMmY6fjM1MRZ6I/44Uzh2mu0SKsLhPdp2MYqP5Cj4QqUVYthMCVA/K8wPsgOEwbmImYu/7PCmtsU3utIgk4ZBjRB6hVYc3D/qyio29FJxlwKhGyiCMJVI6PCD+LLMSEDq7NQL7KnGzbuffPabVkv2+NKX0YYqLp1M0d2ocXJthb2eG8YhSSK7urdRtFsU5+bF2wEbTp4sj7KdzhWCSBO+sD3AtPxcSxPXsQiZZLYo3EmQI//nKe25w2eNqKtpr4gCcmrcUFdjTOaZCkOiadP0Uq2L6UAIYyRLBeNEC2IJwksBMDGashXFyrEVj7mvLG3hcbSmkJ6ChkinCijvSM/PgpNRrpfMqUtYKrNVbOFiBMK6PkOEn0jN24rXIbY3EVvhmTUqaZKn2nlC1gpNwqXT8eoijZKLwXcuAR1o6IUA1SSSDjrDhslX/KWkBSLTex+mHbEjuh4sFkvbJ1mwucrSlNXi7XJDU0xPgPEc9Ua24799/FdcHF/iOyX0cNnOpb31leRv3l9v4tdnTeHp4jI8OH8g142epy7AGZooKkyaybFUDnmw+uvVy9BQSeNl4TEV3va7uG8WDovafOJYJHV2VOIRyYqea17w0xQ5eHbXL1LEv18lUJGRvdt9IMLKsSUScdbdWr7rspBvuEfYiMqAnXc32iVhY0o3PKyE+H78bU4+/9yqXbQ+CvEZtnYgmI8lEzUDHC6FNQtG68NdFEx8bkxwkZ1F1G52CHuqpbrgZ5L60XuWH5TW/b4EgZUl5DLv5ZB0TInBFDcj1/a5g2YX9iN1H1Fjr22aAimC6IF0UFCX8uIxyw5mem2Ri9g2c+PENfmdRk5D3dP1dXZDayK78kMnyW1cSpNIdMuvcGsCO3+DELsp0dS+5AdmkaYVfYet4jWqzg90DlWVg2dL0/0bA2fMZxrfWuH7tHNdHFzIJcyBT3eFoNRE8fJ4OrKdHMyAGqlWWy6qNq+q31oeSoWTJTNTI1Z5ae5JULPVayFA86B1VE2GO0fqdenAjCsmKMSD7pzj5UnWAjDfNdtSZtxAGnGRkUHFS9k65WC3zLU6W17NSbDzoyUSYpK6GeGV1E0uuFG01zlX8DptAjT0mwJEtmRmUZEJkY3KT47waBcFYyZSMTeU1NZ/DZDXKKZaFfxEfscWAHL/JI1ndQNQ2bEWcN2pZUaW0/KA1CXBUT4SePW8X2CEpJF9jK6FjcYpr7FEDVcTngaDBZmd5fTPAW9WhZGXc5zIpxC+sZM8aJ16fiN19lteJQWonl1rTb7/+Cp4dnOBWvsSzxSM82h7hK6/dwnuLXXwufQ5PH5ziI5OHmKQLzNoBzuqJwIC8SouS40SDlLAT+b2FXk+YlwsXsseUncnzpXqNds7Zo2d+XiRQEDQk3Ktaf2qiyOu3bFXvj9db6lAtHyvk3MH093w60KyRY14vkNd95ZpdpQUaweGtZWJcx9hT778lG6oSVzwvT0Uf69lYIDVFlYwQrOpUmnqpqanSRkonJ0FJx6yScCQjt4P1kekMwOAtJdOJKYRYlsWxKOxLkT3zetYHPEgJBCcQlz2w2bjrwcSDRfBvcsr4FYoVPVZA3EjbhwI9ELmgbdhEskgf00GiQejS63p1pE4ypZ/uayYjkAA/SwaTwZrBUyrtM/3MvkMaPeXfFmSrCumyEgWKjEGKGWIQnGWR1iX5Dbo0aE+IE6xlGX6cWXd8YPLFAcpJKm0H9xHmu7iTY3mYoLpRopw2WFSFQHY7xUJqTAwm+4OJBBRCUL8+u4tbg1M8O3iMrYz65jU+MriPe+muTIb3yl1Rx+aKniQJuvQKjEcx0mFtJoe5rLrLLJOJTXqqklpqUgxAdNglI5Dv9cZN3jyHkmVxwlpi2VIWhwX7rkbBSY8T1cOatPYCXxaauRonfnJ4j+JNonpxWo1R1yMNqGJNroV+YUiZtb3T6LlfHiOhTk6m3K8HGa5FVAZJb34yGB32E4FZsTThNK3jha+T62T6h+rFZ/kYAxbrSg3k+1PXjxmpWIBAHZL5N1U0GKwm0keliiV32R5g5+G9mpYW6pfFrJZeXnfzU9xJT3AwnOHnZx/H/XZXVO/DLZk5YSDByckWZudj/I23f68sGliXbPNGxtWjags7wyWemRxhlhT42vp6UCjh9eRxEaq9X5XCzHtUZ3gqSzFJ2OvUtYeyb41/k1rBa6OLC44BraFx4/qJgVhURQz+4/tFgkv2p8FflCZSTtyqrpDvlJjeukB5vo3qIkF7Jq16MuZzCsvytqUahd+anBKE5dplSp7BSDCzApL0TRnxQqaeQhvQ+f9LVK6r4L0wn1iWFSMdUUC6FOBMFYYkl3Kltd3tQs1DxXXA7h22UegCilC2qp5wvJEIwzHJLDNnT2NWCXKgJJXO8oYws2dY6ElZvf/2jYWyaPv5n/95/NiP/Rhu374tk9/f//t/PzxXliX+4//4P8YnP/lJTKdTec2f/tN/Gu+++25vH88995y8N/75L/6L/+KbPZSO7BBnMvGF8ezAiRFOeIhp5FfCaxEuEwKUvp/9S/oTES36B9Ux4eSzORi9/hV5U0XH2UEBGvT6aiFd7acno4SrGYKbPyELFC2/ShQoUnpNiYBlt7rqn7fNrMhvHrfxiF7r2VR8uLGFNg36hkC5nSAZNkKa4IrKyV9ibpiV2GU/TqZ28YSg+EMIiRM7s4PCJhqubOWGaAvJAJg9cVJVG40Ge+lcfKI4qbjXDfdLySNOwJyweKOQdUfFCb6X0BE/iwdFa4dJWmMnqbFHG4mMqtoVdlNmTFT15j472wyqrhMWPJHfrI+pq3Aa15VCd77CcJo5kUo9lNoRsyh+T9J5uQlMInYT3ofiUlwducKHgzoZEyZUqJCQitDnDX7ppu1IgJbkC8ng1D+JQZ3HwfocgxfP6+N6jMf1EMc1H9esUIkflsAz05MMcim9ZzznNwbneG76GOPRCsnA+hOEOmiZlPxuJYtaLAd4+/wAr5xdx1dPb4rg7BuzQ1UooN17VonIL1XlhcEpNUZqOKrygxAY2GvjeMoTUHInovg5VYKFCe2KlJKeWAYotUT312nTs5JvFOLUvxtMhivsbC3QbtVoxm1gyfbuewdONtgOgUwkNjqGOHhjb3jO6lNV9G8PJCGV3lBz2fj7UoPvZlCLApVDhqTWNyXdSS2w2LnrxqT2KfriigswaQy3x5h1yWNSi60DCqDvNbsUvob3ELP6qNb1zzWTms1m+NSnPoU/82f+DP7IH/kjvefm8zl+5Vd+BX/pL/0lec3x8TH+g//gP8Af/IN/EJ/73Od6r/0rf+Wv4M/+2T8b/t7eppXlN7kxk5KajC8fYsab8R+jOpRP2JfjSqwM0VeWCIHAA5NQ0fV1LfuWJNuJeNnen9RGA1eyvai/SV4XQYZUzJDP25Ae2DxMcdytRd28nynaLoVUYcoTggFFzcErKk/ozZjNB2gGmZgfSlD0z7VAJJBApCaRirCt7kdELcwfShmHGwfpZEa/oQj1jYFq2oqNOCVlyG7jJO3FfdHZKy4EVuBE+7icyiqdcBIzJH4lSihxx4c59dTUmO7V1Q15DyHBa/mZrLLv5Kfm2pvhN1a3JSiwsM++qK2E2cHK6k1joWGTdMHJdy+dYTBgFUMzBhbeqauww8yRgRYtLppSdOKqlrWtlfQavbK+rgGmTfFGtWtBQAvJ3Ph9dBLs+p8IJfHxs3IUMiQSKxI3khM4UwNpKkK7jVwTd5bVIdtp+jmcJ8HQ9HU8wPFc+xDn5mrVIrRqhXG391CIh4rog7B6dgo2g7yzJZm9bif8KbHO+Dm64t/NZviO0Zv46Z2P4d16B+VqZOPaF2LazO3sUsXClGDhjECKyypJJcFRtSXZHTcyO6kcUligOshmclzMTbleZ08Ur56ztoU4IV0b5lBsWYH2UelrKGMlgU+aS6l2T+p6iVWiKuxcPMlkaxkDf98sTvHc1lCmnqObU5T5ENlsYKoqQDnlQlbrUiSLyP3iGZW1oASaupkjSi0qklSS07TWWlVTMQhqkKf1h5/LzaATAtUm3c67ZLz2vOFm0M1F9s+LHOXWQDJGBh7u0JmkRVsJTV89yqihyTp1i93BEsO6Ql7pOSNZwp2hY30+hfrY4lFq4zz7IX8rgtSP/MiPyM9V2+7uLn76p3+699jf+Bt/A7/tt/02vPnmm3jmmWd6Qempp57C/+ZtE6LrrVw6anmQKIqDib8/li+S52zy9cAkGPQVtSvebC5E659n2VKo88i9GWdmtgXWYfT4BtnBj1MZc5F1xiYpIzoPEmCcRGLuurKJTFKFZFWa+oT2boQ+DatpdKfAAnr4bPvwaBHQk0WKaepClOBPgtVhhvTZFXZulJjszpFmqnAtzYCNiVMaDOoW7EIayFYy0IWBxtW1TEBKYLjm3lE1q0uE3xi0hjJhEY7Tyb6RwMTsgDbv5xijSlXihtnQdn4hBAG+l0FjYJ87kzoOMA8FYLV44Jcqg88UcJgA25Q8Ko4tw0jxxcVNHFfM7iby+bxhvXufmY6rTPCmlyZIBkESOrI10oL+S2uBPwlL8bkvLe4orEYs36BnUQj3IrZNAp5RKRtLWajh7zgJt9RGlkQMlOhqYSLgGrnW8lgZLBl8Y5Vxvlv9uVZoUjZQa72O+yfLjr5bd7dPcVpN8cZD9ZvSsej3hwUpjoNMaf0cE2xJyDLNQFmIf+XsGnaoC1iscXN4Jt/lUbWNhTQh12I5r3YrzLgIyLL+xGDjwKf2Qy2FAKHwpNL+VSlE1mR+a1hxX7QAmcVZxqTP6Tnm1eLncpFzUMzlnH3o2kOcYhsPH15DttSgFDfmZoT3aqcOGtnCCSSWXUqNN7q34yksTBV1x1qOreV7NaU4aG2qVcQq5mFAbHyILCypTJOgXKt/227RyHiTJgyBinNp5g0fY0E/MP6oWp9WMp55n3HbJEeIFmNaY1bpQu1/FzWp09NTyWD29vZ6jxPe+8/+s/9MAtef/JN/En/+z/955G7gt7GtViv58e3s7Cx6NoL5/M7lFrKhKxTF/flNLT3f7HHPnEKTrU/Q8hpTlIiEY/XzTCGiJ74WBSnftz8v+7F/RvBhl67HWWIE0QWiQxSr/HgkRkWkCmEDsuGXRdoS6bqWlZrsXnDxK44zjn8RfKC9IFGAso/qHTNX8sNEtMtW11Ps3V1huj/HwWiuPS5WfOXgZzYlNSESExKa0lXSNyWr9oT1pcL6klOZIGjgR6Vy6VlJSgkIp83EdOlUmZw1B8I2u+I+m+BhtS1QBgPbtexcJJSuZyvRpmPgobiqO7uyJ4iF9c4Fl5OW+eKIbh89rIAtOT+EgdQmkbnS/3L2Yby13hUCyLXBhShh8F3MUiQwWYe++2fxGPmag0IblUmxv5MfSQDg+v2V1Q3JIGWCdXFU8XlSbN+L1k5Pp0OwEq1torYmzED/NYowr59y4vQx9iIJRGMwjeyPigCohLGnyy3NtuQ9iTZIS8DKVDiWn8JGWl6/W9NzHJVneCu52TnICPrHz2dwooRQi3TQSKCS4MRgxQDMlXud442LA1yfXOAAc9wenshxkpJ+RDYcGtFk5GPUY1xa3Y+hilmdgnmaoHE88IfEGOmrE+UNOw67ci6sxO9BuJeLmNrO0NLey0m4sCySix+O7+cPBni3anFvcg3tuRkJGs3cLePdF4rEI3o1ySkMFHRv2DUmpEPw8dZGJIso4+kFpg0XXmmud5cDz7ojlKbnDecVDTthlE6rqZtYDaSpnkFIRJVF21Ip+V01pOtPcx841qO4eNhikc5YsuG4ImUVudeIjvzLDlLL5VJqVH/iT/wJ7OzshMf//X//38d3f/d34+DgAL/4i7+In/iJn8B7772H//q//q+v3M9f/at/FX/5L//ly0+wxiRWFaZvJjUYWzkIfS16bVyzap8E8XUEi16Akiwq0KrCLp20EENfbaHECYHeqlpXSVyaOxPQ3+PZiTjz6s0T6lWGsys0YDCcfwcRr4x6tK7IDEMlhErScb+UvTZbN2iXNdJai+ibvRnh+4XA3/abM12VyW82o7IHe/oUWO+1wHaF4uYKufVD8Uafslm3WFiNg75NQ1QU1mWmItJGhPTOAxNu1qjBoZZpO0t3TihSnzKI7HG1LTAVV2oMYgxQB9kCW0asuFftSf2JtQ1+D1EnEJXzBndyrVPVBhmxVjGXgJVLXxBBPrLoeMMJ7NGw9qWQBgOa2ncolkKsPU3W2mBrsBuDEjNGBiqOlT988AWBPI7rMW6K2kWJX1/dxkuzG/gfH38P/vitz+Gj0/uSiakqt2Y1WgfQviuvOQW1bhk6OlE4c1AlfFTaxgOZ17O4hcbiJsVSVsJK6OCxsieJ0I4yJfU9PuEk5a6wMNXNWOnrvE4ORw7zFW6OTtEOaySU2lkS0jKZJKouSJ8P65PeZ8g1lDJOtVFWaxusS1FiiqtzHsFJOVFleVs0MEM6laz1PtMWrc+JVFWJi4a/1bxS6Os2m/O/VFD3MqzoEYaeKbOxcRjVvrkz1LhRUktbIEjWKZFst/iVw6fRnGVo51ygRrp5DKjciZOi3KNNB7EEapknrMZkt22fhp5Ej5tzbwhKBrtvBikHceRcR27cAaDZqD+HeifP/yrBepmLt9f14UWvviqN5EFiiwxj3YWwUC0L53kRncowavR+5T7IcGWt+Z3Vnmg2nqo5wb+8IEUSxb/xb/wbsmL5W3/rb/We+wt/4S+Ef3/Hd3wHBoMB/tyf+3MSjIZDakz3Nwax+D3MpJ5++umOQh47yfbIBPwV084dgtto898srMQW73HQkPrB5QqtBkj7j7/Pf0KWtVG/uZIEEWVTAUH0FVCkFBm7+jptPB58AuoL7te1uEv9ThmBcrOQPBGpMAcqegwh+G0dU9k3O9kjEojHcd6Q9aBFOmyRjypdOdv352Dm5KuZhWr+eXFWe5UUalLOia6QOXlod4xmACqiqpOVSwJdpKx/kOlWYJ2SNJ1ii3p5aKWof5qssUiKTiKJtTdfk4Q+Ix1HJFPS+kGrQcyWunMhmnDi3EsfLMorbYUZgqtoNXLTYyU5wceHTPam07efzSRYvLnal0BKMjkDLm9wZhM6/3S6Z4gK/2qA2E0AOkRaWWWLuWdYs1zNJHCdxDjQSRVOSAQ6IXMycnagKg9oJqtOw8ZOZM2mWYNrbW60SnFIlgchYqKE9LgGW3UNryLOzoCVuR+aatr595ExkQmlEfN1gbN0hAcpJZwSYUwKjZ4Zc6ULBr7rWnoRGrUZzlYt63lKNfdzqEQAnTA9JmzK4mmbvI/FTtSWo8MJKAr5aesEx9LOYIGdnTmS4QSNMY1j+SL5PKeqOyji94zd62HailRdmO3qIjWJsiY7S1H2FNexwjV2MlT45rYolrJHV50I00m8xqWpRJ1iVeXWydORJ1wxRSvfXfT0lg8J0MbEpCKISIoaJ5SLPPb0ccHJQMUa7PKqzPFfVJDyAPXGG2/gZ3/2Z3tZ1FXbpz/9aVRVhddffx0vvvjipecZuK4KXkL3JpHB+4KEmLDJ3uPPhj5fnDXFcJptThdvBYez18c9Ub6CCVukyWdZlXaSq8uZfIwx/S5BhhKnzNMmro15y1WuQUWzqQ7C7MGV4TA2amtCNtDRnww72SbuL1tSgUInEVJj2zxFM6Q6QKOF3YrYs7Ih2djXwZPe4Bv76Njxe/+FZJRAOqgxHmpDKmErnTh1UDNQcTB7gV5NDSkxlONBtYtxupLgQqkiEh/cIFGK+lIzYNGcEOESW5lOHsySWGjnPiTrsQk1z5ZYtDP53ufNGEJqzxaBrXbeaD2KG91qWXPil9yWRkZ+lo6Ds2YlcCDlj06bgdCl/9HpJwWqI/xEWIgMwhm16pg51YVkJAwsZC9yFUr6Pbd7q138P+9/rzS0vji9j7v5Efa357g2muFGcS7Blj1TohphsIpS1ymB1Al+6vm0vjXrj+pYgfFw4YLAFCzCj66M4+xK612qhcgCuF8nQnBOJ+Y+RIfNe77svT6py3nlPTiqkZ9kKI6zILJa0XaqSpAuEkEdZEHDGpWt9qtBoTWrosFsMcTbwwqvDK9pw22jsk5KrtDPFgbZtQZUXXxh8FCWEGjYfEzPKWdGWoChLqOoldg6zuwoOF43J0IPUszEmFGr/FOFbYOkp4QBsxQ3puf4xN338Pa92zg5HYjpYczqk9s921CKICwobR9R4y1ZfoysPmdZ5pQZbd0de/WCRkoRwm2I5i75PMsITS1Hrrl8wWiR7dOf905ZsOT+aGBZLge6wPAA5MabQkG3YGVTmij988WiMcB+O4VWPdP3TIqZ73k5wvF6rN5h1b8kgVkPUC+99BJ+7ud+DoeHh7/pe77whS8gTVPcuHHjm/qsdligTXNhvOmE7fSV6EU9enovlbEREvtH2eut/ypgAhtbpxp+2VhRBhLfI26ctoqK608O80lDrsF9Lmcf8m4vprqXuL/Ov1v82baUiht7nUTBIM6MKoiIsTMz1ckhTaWPKT5P0rCr+vz6t/ha9U9AXzzTV3x2d/CjuGYYtBjsLTE0HTbdva6wvGGVcBdX2xQsdfYYV10s5HOC9prN9byjkrMfiH1O95tCMhbWBobB2HCJUSvmDnIwhPZIGWfwcpYamWmU9mEwYxH+Rn6m6glUfCARo1UvWqVXs1+qAXUN1MId2E2pc8fMAzij3FG7Diwm3rTb2UoaPXkzeiCQ724GjqpUUeCdal8KDL/n4CvYG8zl5v+5448pJb4e45Xsmuz30Xoql1KsPyy4O0vwSZvTzr3g75mYTE7xatuVBV3FwoRArXIkrxUl7NqzQmUQCkAg0I82XKv9gsKdnm2JvUkzxI29c1R5gXaXnkIlBnmN6WgZ4K9JobAoSSvaANqiztQOYpytxLV3lNOZd2lwUwK28gplvqVlo56Iu8MjocGzlsR6pDjxWrbJIOMwJ68hlwhchETlnEs9SGEqsCZx1gFteIvK/RlZqdLMTQhrgRen93C8tY+HWzvIF112Iz1Q3gsVygK69wDXOb08QkJi643UyBdOWZdrLGi/IUU2J8jrOVC5qHThaO+B9P1FdazeEjuy+xCT4yoR6w5ec9ZQpZE5ZLoacYWVuiEQ6I3wwq4Ni5qO1ep1WcL9k7TE4rcqSF1cXODll18Of7/22msSZFhfunXrFv7YH/tjQkP/qZ/6KdR1jXv37snr+Dxhvc985jP45V/+Zfyu3/W7hOHHv0ma+Df/zX8T+/v739zBkGjhgUnS2Y3gwS2Gxi5tnlF1hAa3ZJfepifNBqEYbBfKUmnNfkw13OT6O0JHlLF5z9FGoAspuO/TYUzvTdoMijFcGPji0WfGgdYJHXkWiCD0efIAqvE6qmFJ/WzTbNFYfa6O7su5uGjLIDVsUWyVGExLDHNdufpeOMhnNY30lEoszbipqpuzH8bVF0QCp1W4joFETP7alEptYkznvSxkhzHI8f0SFMwkj4GIlu5kam2l6hFEuRcxpqtT3GtG2G3ndmOxwK7ZkWoIAnt0X4WyvIiwM3iNEtVvk+pPuxa1bcHm7QTwe3CiZoCRRlx30+V3sfoO/36v2hGG3HdsvyW1HPYmfXF2R2pBvIxFuhfgvUFG76quFufFfv1749JEBnWxcrXeITEe3G18RMueqggQi4DKZMPgZLUrHRb22SQY1KVYoqgxoerdSdbVaO/V/nSO1TjD+iAXmvI4X+OpERkGugmTMS0xJfnCArArdEjLgDQUr3AjXYS60FEzlt409nIRAuZ4upGdyyKFmRJpOJ64qPivTnG5ySdRe5EqE2wriM2ir9rUzE+JKqogzzHQ4MJqjTwHZKE+MzrCF7cWwFaN5KFqcgp8aqsbI1wGm2UPVkJAinua/IJEcGEq/VJUe7FMysafCNt6xhUFHlc19wAV9hdNj/EX7uYc+9sEgesqEz1LLjgCr8qyKYoMa1OG2ba4rqS1N/A9SoiyJl7L1Hk9uOTZLlZo8jUmpWHA/7yDFPudGGB881rRj//4j+M//U//U/yDf/AP5O/v/M7v7L2PWdUP/dAPCWz3d//u35XXkrH3/PPPS5CKa07f8KaKn2qhzlPCjMobZ30yd507WlbI5JyizVnA9scd4DV5JU7iJD9wBXLpprZA5MXRRDXCYjJFh31E746Yhp69dT0TqqgsQYXvcSNCf5+TL4KHVD9z61PnPbgZXEnohFlTztVVpyShrCKHJDdYRdK3pcdFCnvoo/KPs4gj7KUiQU0nUrsR+bHVVoNqnw2PFYpMJ+bdguaC+m9OKqfrsQzmcTaQSYrZ0Ha6kB9OKq+v1e6Bza4Pkh0JQCxWcyJiwPp6/ZQENCqkPz98gP1sLj07urKEfBYnyVfL63KT0L7jMJ1JH9Vz+RynRq2mEeK7zQBbA4Ukd9MljuuJwDtnzQhpusIuGW5tA+ryHtfaRcVA+uXl8wL3cULm5EsqudR3zM4hSxTyiBXY3TL7F49eEBjt1vgMW9lSoM7v2ntLsj4qTzDr4znhzU37derZiU5fOxJpJ034TR/N6OYq5aQr3+D468uwnpsqh4lDghp8uoDWvY+P87s63KP94DoRLasCs7IQpQFOOCyUe1WJr1vVGjwIzREyLIbqUsxrrcoa7rSsor+8rg7fSRMt6nCtmR3dpLOrBPwEB+0K82aB8/wcSzNolGxZdOppQkkWJ61UCtFuFCFe8QAj0YGQ3ZXgiEgoeRhX+jkDnDaR85vNJHvL8FAWQDoBMPBNU+odrvGJD72Jwf4aXz96AfVppgajft1NbYIohXpGtdL2IS6+ii0HokPPNJQQ4Eob7xmoFDKN+z/tPfZ+JUlY4JPLpj1Wet/3XXqDUrvMVZ3CrjzOmuEiw7JUWTEqz4c+P2+O9jqVKfLzehOaJrNVGtUN1vZmfRJ+uDFzJjwuzxnK8s89SDHQyMT8hO39nuNGVt8v/dIv4Z/bdqmKHw7EfvtTMdwXH+PGBO19Tr3J//LHxtTe3sdHmnbd456teDNx11fVy9gsYCo0Y9h2b/92hwV8YjM4xvUpG5yE9+zHAywZhgoNhFmsG71BWcKs6K+wmQ8FW3mt18ci5qTYWylrzIvxTnGuaRti0BVfyoG9Ehdd9uqUYtFNKjaBOw58wjrE1rcaXW1zElNoUOWAvLF3i4HByBSSUEqdgVlQKitv0tsr8OYgJEQ78AVOjDm4aHP1cxJFcWYHjU4+0sAJvFNt44xmgOUkIMT3ym2BFPl5+qOkZa1EapeOIr36XX2iXOVLNM3YOu8r7GdLCXCcCkkCIWxVmCswterED8tULOT7mD1JPBxcuNhXsxvV0isnZU3CtS7lPVRdL1X0GsoGyeSlcJtkao0K53Iy46sZiAT+sVWzB0AnfMTqG5SHIjlCPbGU1cnr3OV9+r14NTkWJONmc61lpWzOFdFTqbG1oJxwd1crtVzaHIw6rre11pN4XVz6KN2goTupX4e8sv/k2IUJaFm7NWKLrjdtTywzJox8Y3yGWTXC1yY1mgVZs1EJwJp3VT2iC1zKa+oaeWOuS3C1buPf9l7huW/QyB2K36hPCcUot/s0ECou388hE7PxlJSJ6CPmJfE/VgmUXdqk2mfXKZl0epHxjKQEHa8cqLqEnke9/y8nAB9Q7b5LTbj+z+BS64879BXRv31rNwJUTAfnFr92E8w1uM2ZYhJ0pI5jFPYNtp68QjT1orgQs7TEuDCCH2WS8KAW0deTjXqV78fPh9XC5IdZVNG5+8phB6zaq69dNCRhQpUtaCLJQalF8N7mqzw2/wkUwdfYIawTZLMMs7kqOYwKXUFxkNIrKrVByuDErIP1KbXoqHA9ORNY7+nBY2nCPa6nKo+EQdBP48/1/AzblEWqtqQh9d1qT+WPqIrAICR1kjVu5mcSoB7XW0KwIByXNwoPvlCc4D3psRrgpJnI59L08FZ2gVEC7KecesjgSvDZ+bP42vIa3l7siSguswLv9eJ3UokebWgVRQ9OaFKDs94RKl7kM/k39Qrng6HAWE8Pj/CxwWPczGZ4r1an3MN0Le7ANBx8ZX1DzP8eraZi9se6TtwA6RO7liW6ScIXBg41BoffXoZlzL6mH6Q2QxpFVbo2RKdqAOs6E+8hvj9nr5MHa1PL8N0oBKS1Rk5mEpBsNc4eMS5MvAVBb0OlMi/SAoO8wS6tRSywMNuZtwnOTfqJ7yCcK4obbspnH6xN2mpVwk8m3EuoT9dmZIn2mbpqvKJ1YWGvSaakoBb3zkUOj59Ct5rBqtsy980WghdGDzFqK/zs4SdRLltMWOVoY+0+LQMEezoxErXz7chdtIYOr286JRiH/ekLp6HTxZ7t3rPXxn2Oog4jAtEdeUJqVhsitQ4lyuKV71kneDyf4iLNsTtciqUKxz6vL/eVReo53ven/lu08NDxLws2W6CSUMT7hF/fYeFvCYFZJyAE24qeikRkYdGz07CXxHUrf8/m7kVmKHLWDcsEI09EKg861jq1iQ4PjvqMQt0rWu24kOvm8fhhxa6+FqRkHeMZUBgscQbYJ2v0myO6HgsGmH6/U3ReeUOUWhRP2L0an5fN+oZh8NKZv2RRuEX1cIBqB7goKvl7Vg6QThvpe9nJ5zKYXcOO542TGH9YNBfZHYO8jpMtpa1Sn8/s4Pn8DoNOofpufB/JCGzsvJ2fYCspBdq5k88wb1TOh6eFyhMU42CTKonFU+tnul9PJTMjcWJIu4ekwrptcNIUeLfewlurHTxeT6VvhzUITq68MXkOPINiVufMNj83HghI2XhUbodJ+qJmBphiUm3hIj/Dbkrm4EhEc//X9T4eribymiqjvt9Ajp0reK5WXRmiXyn0GlRHltCh1rHvpJ7AzNaOKYwFXwBdkUWF77HR4eCkEOmvqnKZcIVlZxptklmRhGMTP8cbVSQy6cdSppyK5jamO6h2Jny/wL8k1VC4TsRhjR1r487VNbg48eN3vy2BJ4XoooFOgl07kNoVYWStLlowMqUJmnHo7ct9NqDcsH9X9SPrYMDa/k0omUQbaQGnMnhLX7GFQHiT6zNgxoAw7BEiJEhYk20MzcUSZE4TD95TMnc03VXZaLL3e1fniY5EEUrF1pvF4JUTzjSFC4EZIydglhvJ4FUbXW0ZwDmwuj/G+nSAxXiMPK/lZzhcCwFma7gSB19hltqhCexr0534xDnZJ1ooqS1Pp2P5wQ9SAh17j9QGJTtAYzZKIpdbbrpiuhLH6zKj3wzy89f4iij87Q04xqCKgluP6BDTzSPYohcNPVOK4UrWmyyDi7ULe0rrMba9qXzsRA2usIQrEg3+8Dqloctzfpe+X5W5jSmxCeozNv0VWOwX8l5ORv9/9v41VrctKwtG+3udc665rvtWu6qooqpQbp/AUTRIPPGA8oF4SRD8oUEPCEFjBCMkavAYI2iCES9Ro5CTKJAciYbkIEFFP44cQT8uAudDLkppYSFV1q69q/ZtrTVv7/Xkaa09rT+9j/HOtUqoD2ttRtXca873HaOPPvrovbfb05721PG5bUIAEdjS23l9I2ysEETYSBZImilA1q3NrWfuvP3Skja9xuPUrCkHS1yVguJ9ZeFF/CZzS+S9WTbBHIAyC3DyAe3ntaEuoy4C3HuAI2MTfGW3C4Qf4g6IAfpYg2D1fetb5ZX1DcvAv7e8MEEFIbmaOILPk4AdLMDNkgcTIJk3wsTYFYLK+2l5uD2yciBnQDzujq2433+8fFN58eKWQdU/7tTZLGwcAEawmkm+ETMm4EM/FFCurFTLx/Q5SertSVCyLXXbxBStgXUVYt4OLCqDcGMzJfGtARU8IZcTD+zryJNh7pUlJ2939jmC7E5A6rlZuP50ihQCIAhdOMHwQKwJjtCN8RWGaxXX0IoyC9J7QBYE1i3yJINuhZn+6gwUWDVePbkOBglnzW4x1x822F25EoHIPDNY4rCqT++cl82tZdnNj10JpBsvUH4kqlJGIO4RjugTEJbomZMDy6662NVfJ1+Lq9AKNG73Fp6vpeOjThy8Kfgd7a18Da9fXVq+48WJV9MGldXseFMWy225eePShNVitjV2cwglIHktly+IY8nBiNQBvHsgXwnCgYDaNF6qJ1RITXbYUBCVPMDJh4MEq5n0qkzkHQeeWWVrr70EAYMcLLZnOR1iKQX6jTlFlZw1ZmQIKCbbmgsNlollYvrfZqkZkCMEi1QRbnaO5qEl9qUCROtapfUlYAobm7DYAvZqU4lAjb2Q4eJ5xLKDy9DzNOL5RHsz5Sk1QQr5Uo5fhqY9KZfPzQ1qDJfQSxc3DdIMYAMJTS3gP3X3HwoFPpge24bt7Npn5c7svNzYO/EshMzLgexDYP252f3yzOyhkY3+4hpErzOrb1TKq2U+uW9cfnjKN83ObRN6fVesSJ9ZSmjbagVty5tnDywuBRfbDz789QZWODJwBWMb83JzAXfHlQEdQPlysXNLEOAL9M247iJfxCy3EFJejdeBCozbmGts6uf+/NXz5d1Xb7KNGnDm//XOz5VXb96w8fnE5UsmPCFgf/D1TyofWN3LCsbYGBAv4aZKZJW578ylUjdHCzVGbouCJNJFGPEpDeMSIaiKnG124gVwB0bQK1kahX9vQmrqNat4GBou0Hv+/DtjrSDdFN2FR7MTIxt+x/LD5SaC7BMg+laWe/Oh7UkUopxb4i7HmNQ8sFitplMAVAiVtw3S4l7BLmGclJ435vWkHLmHUD+EEHKnTJCQay6sPqgGSFjw0K3HpGgpQJE6K8vy6U9/oPzSg235T8/dKYuHDjAiui/5CwMFi5JMqFzt5LTYR1oAg8PKJ34++oz9SQbft7gKoPC9JeJeoSRnjMoUL48FuRuxaq2YJ/PLSAYP9yTaWzxwwbqF/5tsSPO55bGdLU7KQ1hk870xwaPUCqocGCfjdF9mC7e8To7W5cZyZcrdreVVy4jy0UL3/c93KOlpawnY0Wd786TeOolz7HteikkhVopZFXi5BlGPS4P2qNKdEH2jfQnLhLDyhJcL0CSFpcLSm6dsD4IxlOm9sf78OdVL2f7R8QPS5QeQxSaqFYcw5eTnuHqJegrAzu2Hf6Xk9Wy2L0dzTwrF5IQG/Prama1xKH0QXGawpnxDC59/oKvg07ZSAmFNuMvFa0YB3QVOP2Mag2tpP7dYFLRbC5ZbITyPS4AkEx1FThJJREGMClsKVhfg8WBhhw+e8GP0EQF7z4lywcWx9RnjGqJZhzYkYiGjz4EIhB5Oi8HYoMGIES8BCcMAbTw3f1heWt22asJvWbxuFiUYwI1DLX077XRprCnhSCPPGnn+MoqlGRoK1Am3ny4rjWOpgOLttWQ459TUaA20fcS2/ANziYIZPwAgdAVBWDgybd8kGJu1FD9w0cLiBk8jHo3WEpd0WpchRExYBuDErU+3nOBcdIBHBVL4OqQ/o/7uikXQYYZl5b/53TzmhViZv+Onl2fllRsXZX0bqLwKdMrwUzwU3GsmUFFzC0LDnj/WIfrJBN59P+IEy4QmQrdekypSPUJyWbNG7Xkz9OGN2BYCRRt0SnO4Ot1FmQYxgVfo66LWldtdwb83K9tjF1IYrO1iV7ZI4zieWa7cxWxbLo+WrlxFzHJzVvlYn2whxbhMmo4dk4QeuRDj5ZqmIaU+6oluZqAkBq/T2NB8ZpyBSHozqDbYGejem0HTqCAHm+zMnbLAqQA6VLBZ263ATTemCCHWzkmrKS221j1pi43JxPxehkhh8oxjmc/6CDNsVyYrMFO4aTQF119AXylYmeMBlFZbAjSahlp6tC/Lo7VpUHePHGyAreKFyzuB9tuUZ5Zndm9sWpYnhCqrU8RsfDtgXajbs3ND5S0nwHw5fPy1yWm5M0VC74Xx/V0F4wRKuL+4vVnuTc8ctQfXk5XrcLQYhOGrO7gPp+UKJeXnZwU4uoIyHltPNoZLEtqf0S7Nr8xVZujEMjX4e2UFr7EXF1S+ETufHstpOHAAApvEuWgXlhPcn/gbG+8zszOLo33v2bPlp84+rmwns/L2o5fLpx55PTZW7GVl3zHORVpIvkk7S0PjGrRpSMoCXw+TTkAxhkW0oJ9Xoew+1YKJ3Zae8gJ6sjOKBtKaqYnqDm2fThx0YtWBLYaFYHzkpRfPs2HBRqgocP1h77vcX5UPbu4YqAaKCpQTuELdc+xjw/wutItbWrFDS3MA1yI2PLjmHLAOp7O5B42zEUweYjWmSGfci+Xm6z38+Ry88TIY5ffz8pblq+XDN2+Wqzc5NybeFlgoTFABKLfweBSqBNgqjfwnr2oj69fKyse+wT0hGWsCWMGtwvaAkZi2KO2MGXOL6d2HjGdhPXuY20FR9vrPJe+KTWeyMFhEprbeN8fwCjknISzF7ayU8/lROQvm+30IMdBlGYPI5WV58oWUFzby3zV+pAIl4jROZzRy7ojFVRF58uIFzeLWQuiutKSQX8VcpzAnnM5oZ4UG7XNaZvsQgHCt4TbB02LWWpOoGy64BGgEcCIFcgiz+HUsYETKolQyRwAifk+/B5CA5iHF88LtuUX9qVXZwd0JlCByyMIHnsmIXYnwfA3bSVmfL8v50bIs55tyd+mMkpZTsZ17vs1sWe5MLqwS6J2AHUAQOKP5wiwRbOw3pxfJQO2blG8K2NxdP4DGDGF2EW64RXlpf9s2J7gDEesCugvs52vk6OxAQnpkQu3+FOWxnUUbNEZPLx8awIN9xWH7Q8TOYLHBgvONcCLxi+rKoBVCPjtahV6Rt5jF9hP3P95OxPfvPH253LXCitPyf73z3vKOGx8yNgoI1H/z4JPL+y/vWfmEy6Xnn3iCqQtAz6HyfnheVovI1KB1xg7JN5jTP5Kzgxkkl0fMeJsiBrwI4cRaVGrBiA2CA8AKMvnsEesLYeIxpioAwU4AsAXcwE8vz8ubFg/LJy5fLs/iswlilV4vyngfMUb7qwTcGCQ9oM0sFIlZROvpCOVEpptyCgXHLCOCjxw44Um9+7gH8uDICuFHsDr6WMfvmGdQeoAavQ8ragYPAHK5vCLtMycPyr2nH5bNK6elPFgWpAV5YcO9U4yREaKLE5tixwP7t3g6Jvky5Rz1bmy71JdeEQ5EoQu1YRVw5mgZXVMotO5yrAo9L7Aukc09XIpoE2wbrH3F6goGyAgz0qoV47sF3INAoPwq0SL9n3rY5i7xl6Luq0oR1AIcxo9aSGwQLa7t8lBhkwnDiENFXIr+e4tBwSrxZMdqJWFSbWMyRKl3tap0UvLQZxxjwhiY9j2h7YHoKxcCzXmbrBETi1wp9B+jiQlckHPBSAUpnXomdXotN9OyvZyXy9XCNtfZ0XkIk50xGUBjZvKp5T9ZAqsn/BYKBWw1+0m5MUXMZ2WxKLOArArtsQfe94tyAqiy5c0gFwqUOV7mXTVrVBS6EWUYsGsgv+rcXIOLJE3FRskKwUyQ9XfjA2V8d3Ddwe8uAAZCval59wSwykyBfxHH+sDlXXcXIS52475ZW+e7Y6tXNEMByDIrr2xOrWTH/c1x8he2IBtu/CEsTXDGO5Kcqd6QTqHEpRHxpgExraD+HINERUrY9tPxSQssBGAIRbf+PefIDXzGwmpMDO8dRjySlZ+en5VnZ+fl1IoPTgsKnjgSb1JOkG+G8hxI+YUFZPhu743n30TicrgCoaQAIIOfqbl62U//HwUV4O2xSuXR3TJ2cIQwyQdfIrgZNxCOO6yPYAgBanR5WZ65/aC8sjwqV9Ol50TBMgq3WSbV6lAb4k+Ug5G1uufLk/BFVVKp6I68cH0oEs1GTDnbTmaaGhNLQgKidxunTNAtRQ6YgTLWrZDCXrL10sl+j0j63y0hkMEA/EZA95nrjFZAfEbnLwUTLYn8TgSRDRxBC9OyR9VbuO/s3Mp5NbBQkM8EzUX9wOb2E7ojO4+ACrgD3TVnFoqek8wT0r6V2wjUovXJLbQsQ98Iolrts+Y9HZBGTbZgL7jDXbWYlOlyZryIk8srtwZXweYAyw/fiTxkWXkrmGbAitiUYCg+nJaj/7YsryPx9d6Rbfpw+z1/cj+K6wXybT8ziPZT84fGf/eO5YcikXdhXHYUSgv8z3JTvFS1QZhhNe0RFZiU47Iuz8wuyrOTCxOEH9ye2vev7U6s4qqxOBjN0r7cm27Lg+naBMF7Vs9ZQi1IXjksuI51oCBAWcTQQBJBH2TC1ZBM6iaie6tCvfFfnOcl451zDizQ2Og+49b7jFYHUOlfXN0p//v9d3jCqG2GblUa2et8W47nm3JvcW5CFOANtIVntxhd8B16IDySWoN0Vg9/5RFR4e/xr2cQVeEhMyc+k5pEdDnaH+FK4tmxBjeIyeS4wJvhIAdqRV4Z2M8Bn9tbT18v/7dbP1/egirNEwAsqrWDYoZ3p/NyNHlQnp2dlR+/PA53mwsiuPQIOweHI2NUpxaz3JVji4dubIzwtwooj10BQFGfGJYbmO6pVvQH2n52/sDuh3goUggAnkBJmBvLdfmDH/fj5bs/8Fnlv5ydlKPXY03DujjyTdoFVyxLbN5wjx3XAfeYVaUfyxmWYbdQiMJrZF6YyKuiUp7WWqeg02qiHu+fhaKesPkIefDxJd5cfb7yXcTHYDFC2LqlBSLrlv1daZu2j4eb+FgXUmMfCm3IwevUxVfh4l7eQtxtiQisTdvUaEzqAEDwbyJwJG8rhYdC5aW7Tb/YtTxXz6kuQP9dEHgpvEYKP6rg7u/ZjpxfBkTPybzMH0LtgUAGhYTH3qZrcPEBWBEuVEtUrFVB7I7mLoyA6+WkbB7O3T99c2n8ebCijPkcGwjKUUdAGqCJ892u8q0Fcso1c8C4I2ie/Q3mitCoUUvIY0Du34f2bBt9WET4a2nuIbieduXWFOD0Sbk/uWEbJjZ8PAHuS/cZ0WNW1h0gDtADGQsD4RLiSjswvDgDggaUMXh2zyEphhY0F1UIPAiuF1c3M5/JhZvXVZoaC8XeBBPua5VPrQiiu7q2JkgdRWgWH86S3Cn2Iyv5Gn/d5PGW1MgX5CXsN3Fq3npfjk/rWW83XygAAIhYyXJLGQDLhLf38vbE3ufpBHMA1b2qoEVcyumTvJiLvf8o/zLLd+dCKF18kYwLKw2WEARVTSemwK4xNW/Liyh6XTOWrKiuQT4prHO8G8RIj29elumdddm+tHBQsZE3sIoC8yal1lPEnNAWNnoYfjNYRxmjlrWqHhAZ/IyNs1MdnH1wbr5PKuZtKfv8TudAuiA5UtIO+0meQW6pBGxk7NGh7k++kOqPBBiIcAnUTnNashHjiGG2EvGO1DJrh0OvLkA7TxCBsJ7yHnEkx164HE1bqUi54S4g90mWc2KI2yWQ+U42i7tmjCkjzmZpD1hwWKqBOGxu3bsbcmygxc3KBprl6/OAxpITMRIfyW1o9YIQYA1tGiZ/aHnmGkQJbRiOr87LbjUt508tLfZwdnRkKKjT2ao8t7xvlgBiL1YLajcvr85Os6icsZpHP424NKYsNnfA1InwQgkOHCyQCNeSxY3gWgxrC4LMYOI2fJvylJUD2ZSXtqfWZ0DfcS9Ya9s90jzdFYeNE5uhtWfVYyuCzoXoaMZdnRLGE7gwlx0EERgrABy5tzwvm8nMmDVwLzz/q1c35LqJxepwHjn6kFS8ms8MxEH4sxeZc3cUBKGxMTQl5Wv/kp09AaQ1kVf1osc5ErpOtmv9rstCTCtv4Ln28QO0/9mlk8+ewYLdIhbpLtJf2tyx642MduLxShxeTwzkxPh8ndWV3b0bDBgQZADjGKAjqlHbKsdcgCsZqNOgD6KFImS9uN7AN2Zdg3GiJqP6MkKdpPrkBNWgZtjJU+dlvrkomxcWZYrCj47xCP4+KR4aVowyzcCjYWtxFmVxzLUewoGbfgeMSuRdV7mA3/dKqp1HlHEouaZ6BNuFndMx5mRzkaPq9619UDchGdi9tI9c5xOkTIAKfOKFVLq/xCKikKJpQ2ReivbujZE7T641t1oD4ayqhJnTRsEf+VcpfNIODy0RE0j0DOlPwwAhmF9rh+5ATozcObqJRxefqSpC26+gDjJQpNZ0jXUZ3WOOhVEpwbWHuNpq5SAPlG04dvSitZb0SKRtckQ6fdV8D8jBgGVy8cHTMrnrNDqGmFpMLAYBIXBvflYWwYL+ofUtZ50w8tVa68msJRCXhoXEGABZH7CRvbI9dZh3cRYA3AebG8hqoeV+YHfP6lTNJq8Z9Bznffz81bSHzhcgLN2Unzt/q31CFB83dBMKxgLoybw+PQDXZQvDwwTq7LI8PX9oz/P84nW7L/KvfunyqfLeq2eM9gjP8PbTV8q7jj5k5wKZhkq/QEHem24sCfj/9eHfZBB+1ONxC8sZyEluy07QHWkABWEwZ/yKgklpkbLa7yOEbt4j3InK02ahEdu0qtDKaaxxssyP2hvRKOJzIAz+4Ontcmt+Ve7Mz9Omwbg4ddbamNEdhIJYk//AtYsD+WRMCgdPIhSR24bqA6LPtzpYZMqfghwpt66q1ncESznAFAvLe0OUs8akOA9dCXJL687sotzYOynwq5vT8h8u3l5unqzLJ9z7cHnPCazjmedBQd+LdQZhZXlU6FqwQ/garMCD7XIa1GNc38Fww1ihVMd2SsHKgKMTkvEuWrqu8MY7Mj0w3L9SPqQy6ch1HCR1+9kXXSmYyA1Lb3gv6FS4PdFCSoWSHD1yJdTKHNQG4ZbXd58lelBtYv6HqMHICcoJ0b2Ftldi2ekkanOQHIwAX1ndcLhFqnBrtCmekrVlOjcjb9ib7WNDSjCgWUpetqTWsuqELn+0rHwMmfETYjVCN8NinEzK6uG8XC2W5eHqqFwsFx7jgXWzd7cfFj2uMCogCiFD0Xn8itptTUJF7pq7dKyUB0hpTVgF6WWwAmieDGI/sLLu75Zlgmq4gLdPEZp3Fw4q5YIE1WJKRnsEd6ILey9TEMi4zmOr23rvRjNwxNQFFX6eWTywa9y6e8Y256cX53bOZFnKm49fN0GGWIdbYfPy9uWDso2qwihAiPjHOupZecVcL8tuvHni1kuXX9QwUgFVhVL9O2Nprc41PmWkfZLcmhUQrqDRSwSI4fEwMBV4ftrr6+Myne3L7cVleQ5FN6JNwvSzDPzUP0OMkdYyzgPa05KvLZ4IS6zOFQgnlon3brLYxHBZsIy8cf2ZW5d1tOqmTYUFBxyNR4huToDOROLxsry2OS03l1fluRsPynuOd2W/cvc4E3dNQDGpnkqkkMlyE99FdRjXU5ky0piivl6t0nFF7uU+kfGD+oxZ5Vdz4LifSEn6ZlBEHvn5hOdwHohCr65IcUr9jx4f40Kqe3oVWHxRZvHE70T6ScynqTirtEJMVNUYUlppahHxulbQNWzwaaL3jn1aRELGon3AwWrCOCJpGFDwXF2ZeyWgDSZGGijksESiRpYDJgvFlvFyXnYbL/rGvtk9EJuK6ycgBw3B6P8GYSZdGTVdrMwfOoT9weVRuTqel9VibiXBN1MXIUZ1NPG6UBAQrLJrwenpVSR9umWDz404dn9p2jVYI2j1vLo7Ca3ar70xuSpvnb9WduV1K9+Bzew9qzeVdy0+XGazh+XGFMgxuAdRiO/18sz0svyH+dsMog43nbNqbw1JWKeXxqPqxsuqtTzIvIZnerg9ziRkz7cp5bX1Data/Afu/Gw52y/KD1/gvsflvSvUlpoYwex/fPDm8pXP/Wh569HrTUVds2Cmbu15LKqySvC+zBdSgVIFkn/GxFcKKcTE6tRt2SlcCNVnzeeMIIjHJIJGyFyjVRDQcnMuZ1hQG0uafsuN18sLZ7etyOOHL29a3A7WlBeKhCXkSdB4bpRzgZUJUl70Cqg7py6KasGWV3XlaL5Ist3uAITAPJmXZbj51vudUWTBysJWi/gUSWaRWA1hiKKZFoeKAQSDv1f33ZibFnMVc+z963vl+fl9s9x/8433GoXX+zf3ytsnm/JwflR++K3vKpvFSZldLMokynVEtQofxwASmAXTrZ0tQrAsXGgAqrp1qGPILC9AvCUG5HvGMJZFIZQf570jn2vfuvSmkrDfsLszIbh65INoOuYB1wdBaOWNKKT6IzZTlfh1VxGC2YztcPmoFaXWznBYWxCEzJbe2Z43itNTbvZuO6E4GZMn4kZMZrHQnA2dE3Guppw9WSFo1l9n4F0zhlaLauk1uOwwZvmad1VJLWuFXq0AmkntmXNB986m3Fw4USsOLHQk0OJvE0gzABp8E4RWTLZkY5dALCbAwrp5Oh0RkHtYM+4ihJAxBNkEScGoXbQtb5mdGez8VXwXlVtP9ivTUrEmTVBNwZe3NmFCt55baAGlDsuod4qpEFB3lwE3gAqcehVgui+Zz+WbPSwityKxaQGpCPQYahatbszKK/uTcna1LA9WR/Z0iEkhJweQeYwZyXpZ5l2P9BwLXF3dempNudDyq9ywF5eePGc7NWuMy6+MNpSdSwQVPUAQzogxvnp1YnlzaBf9P1sfGfO7CSmr0ovCmABWoPruxgAvLoTCoon27s3Aqod3CMSfAyfIBwIgGfKgvOSJzyfmTOEasGQYVZJFcV3YHU9m5Wy/L8iYY5FEtA2kKC7FfPJeFEP3YR4jFmVM/TMkl8/L5XRR7t46Lw8fTst65gAKu2e41RkLYrWDpLKidTMFs4Ovue1CiyTWZG7Pr6y/N14a8hqC2gzNwIqr5mDrhiPood+HNESfG1WkIiSDe+upGRDva9SDHq3ZG0FIqWVThvByPYeolziptX4ar1gk/TIvIARZginGSnjopFCC17BImrb7o4lRjUgpteRoiiNx2LQr59mzadhbauk6FIvP3BiHpKHeM263nJY9UFZWSgF5Tw7RT/RQWG/mv2ZCr7n55A4iMM2amu7K6dGqPLU8s6RZbMrYXFECARoz3D2IT1EAvLi+k5VesfhnE8Sp3PlHzZldxpy/BTcNqv1OVgY9x8Zxtj+y4Dc041+/fK082C3Kf1078zksrjtTUCB5X5GbczKZmqCEAEOpEAcgRBFDuA8Bf98jL2s4bHRH0qmEA9c93ByVo5lzyMEiQN/RNgAjuMZLUMwtL+ppJK3O1uWdiw+XzWJq5dH/89Xz5b9f3isvX54aFP3myZmVTgAcHedC2OEeyDvTGpacig5QqNB5wr/p8lPrKK2rBmShQkoEkwg0TnHH2CEW5m62WiqE9alqHhcsQoBJwIxhlFYbZ3tHkQ4bZ/A0LlaG/IOQgvJwewIWEsQBYUXivfsGv5w4R+ORITv90/vgWAxraBOxStjGnvJHR6HHpnQfcPg6rF8AWgCOcGsOXI9gJjnaA2XoOXPo4yvbmzZWEFKw7CFU//v6rgmc5+/dLx96OCsvLW7mMjfkK1kbRFfWwoT5M0NytkmsiAEHfJ2Z0rZYQ3kMkDLfPIcexUmNsmozKbuAqqcCO7ItNe484QJlCSD34njMad8JHVZZoMAlqzsnI6HoVkjgiRdSPDpXW3NwUAe1pzoBpblLIwIQ1XwHCcFJ3CqCsRdevmqHzBgNq0X8ZMkRnO52PdkmGqsLhchYH0uoktohCICoCpLHKd8SwVPLy8IGM5uV/emx5UpNVuuy3yxbd2Q+J39FvayA2YpLkQFZlG63OkSxYRo3GjYAk24pSi3GBISfuWx2R+WF9d2EBOM7xCPMBRjD8ur2pFxNt+XW9Nw2rltlUu5NL0wIfXh7szyYHIcr6MIiV2+ZPyyv7o7LxW5ePrw9MRfODZR4j4A5GMoNXTe/9GfaT0yoWLXZaWWbQOxDB8KtR7dlGLtyWh1nh4DLCPWycO2HNreMhPfh5rj872efkEwbAHkApff/vvhNQQ80La+sT02gP33jzMk6F14E0mocIV9qi6qoFczxuEeNXfHvigCkwNLY1pDLryvzERurG4dCOhtLBJttlm7gEtg6XJ73BAnx1XpuYw3ex994+33l7uK83JlflJe2t6x68p3ZZbLnXaIchwEZVjZnUGH5mRnKtcBNHKiEiDWxLAfxvUjitXQFs6o35RzxUZuXKBXvJUTQVxDbQjA+Nb0sT08Rq5yUD2zB4g/Ox7UxlEAAgo2f7Cd4Xgir544elMvj4/LCyb7szqJwgeQMNWPGcCBd7zPGrqoLyGSGhSLEg4KxI0IvWCWsbhTATLNSNie+Bp39AnHifVmQrgnCLpJvE/S0GwIw6P4THJl3SepTEd2ne6vRK0Vgr3dTvnGE1KOe9pEurvzPMG7EN5JcfCPXNJ/3lpM4O3IzZ2xMXIf8VyCm2ffUdsJiMlcBZ4j2JSXFox72kUcqc3A3HC3KdLMRpo3OzSXEmbw27bXOH77bTMoaLBTrpYEnDEpNzTYc7sxB8Sq8KJSGuINv/CaorForAA9XGYuAuwULF6W9l9Ee2AmuUArEguozC2iv9nAwIU61K+fgcEP5iCi9cIVYjzFeuCsO10F44bDcG1BcBQiDj9azOvBfVqM1NFkwTpDpm+WzQfuEmAXOfHFzO1gxdlYWBG4vEN2iLWzWEGa4z52lCycc2JhRARmfo5QH/h7hKrn2/T7qoKXEF03Nu/Eo5c7Kf9S3U+eBCyrPxbF4FVI4uB4yHlbbQsL2bjZNLzOsLqQJmBUaRSTx9Of7I/sMAunUxgDuPiTQo86VJwU7xJzKAkVUsMhbCZB9udzvyzkUOvTNcgGjim/kR6ETDqbBvPD5ivfptF0oGIMaZCdmKfsY+RyGADtersvu2Mlb9RWN5S/55xQ4+1T0LHeK3reswtuOdbYL4bSIH0sUDvLjJcrYu6By8IaUE6mexjZ80U8U6tvq0kvGnsrv6ewk6WJon3XMrfhECqk+J0rjRXqaDZC44ngO1bv+ReTnIxaYWjzaj+aG+Z8GzdeUirfv2B77qVFRFTYd2gaL2zYtX+i1z13sLfqm5TUOT4zQ+jNoG+6f+bRs7h6X2XZT5udgoEBir1hnmTHPDPeK8urvhf1++3BRLt5/u/zCdG3Wz2fee1+5Nbsw1BsZ0MEysQUDCCHsk115dvHArAbAyA1ijBLwsLTCorm/AlhiWd67vlHuzq7KzQnyZzy29XB2Uc7A07c5MSTf6aRYGYi3zM7NlXJp7AJzKye/KJcWu0DwHmNmSbPB4baezr2ysPDb1SKH/sAqoNySwiYGRoVzY7VA0UQIQGxszy9eM65BPNMvXDxn52MsfubDby4fOLtbbt24dNfe4qp84ulL5d7yzATRBy9vl/969kwyjDvlUlAdHXq9OaVcgHN6YV0ogMY81uHqoVfc0iwm4x525fBzl27bA0Okkd2lUaNpiQkAAy65MzCVWsa0uYnPJvvyffvfUO6eXpS333rFrEm4NJFrhs0fLmNXcpxOC4IfltX5zmuXgUIJsSPEspw2yXPp3MoCCMItkxe3KwNhwAYC2TD7jLnnOXLuW3sAhOUOFF6IBU4KstrW00vLuYMrEM8EhQjuV4A+TqcTywX80K2bZf/8ZZm8jGKIwR+Y7AsBHZRN3nDqsl73GN9ltcDIXN4IPGGYQLtbox/ye2yPwBtYyg4kryAdXpdy+n6wVHici/yCi4cR1oi8R3tPsbekIhr9NFi7uCeT9Bb/FVeeCVSjVXPJZ0S7aG/zRhBSvVZ/6HeOYw8pz3MpaDqXXHOfOFFdfP0dGkFAVUQcv4O6V71D+Jo+9AfpmzQ/i0zFWpU3/csjFpbKWUmya7sS2h9ypo6XwZC+LpP5tEwsGZCJhpKP1XGT0UdtB7S382l5+NoNa/6Dx7fL/rjYBk6CVm61lpQZHUKODMAH2EQgpFCOAzWGQJqEeNOt6ZUBIl7fnfjjT/cF0AhoshBMaOayoCz7icVFbk7PLZZhj2DxLQ+wo0oRNjHXuCcmQODecxj5JpF1HCoyQ+BhKZzq5u7f4HP0xeiQwM+3dVYCCF64LWczB4LgfhBgoAdCsvNzx/cNGIGY09NHSH6+Krfh5tyvLVfqldUNKzp4c+HuRwpP8ucRSW51kZB0DcuBNFrxjq1A3S7okDiNsJnsdp6QjTyqfBad89V1I/pQ6l11jk2u+dsnzB4bJYZgNymz+/BNRYK4dWZSzm6fmAsZ7BtcRnhWKBKwODFGmB/3jhEPuix3p+eRT+UJz3i/F/ZOHfyCNITzCao6AznobsaHMT5o9yHQgBhLK03vSFYIIIJBMHMuw2LDgaRzfGGcIERMAtxi89kZ2FFT7fbpZSmLeSirdUHSnawCSYa52C4h8SsXHoHQk7VeOfM89wpCytjHjdQVQm5Xyo2tjTeQgKt7szJFdd2jbdmuUWJ4UjYvzcrsyqvzEvFn5UR0/xixrLL+VSARKyCk328qd+Abw5IacT013zV/VzoWOwSOPjgGuVEm4SLje3fgmmsG3dTTKP9OlTMSYJvThIna/x5trO48oCxq2mBib51NJqAaXkD5lVZT7lCtgKz5Vpjki7I/2ZXJGTJzt8b6PlkAETVL14MnFmuuRkxcyVFDjR3kaT589cSqz77vjrtt3rx8zTfawOw5MAKJuw5FwEKHZWWlwMGBV5YGgJhavsyu3EXi7u6ofHB3NwQb+PkQf4rvgNraIWZwYu/ieWw15rLxxbQOVxtYBWxDM4HhLrTbEIRT16avgEALNgocWY4iHV3hzjJBEFBs3NuKKDrHHlgjwL2HHxR2RAE/HMZovp+XT7j9IUsO/bjFy3ZPWF0QnNgWf93iNRuLD2xvGyoO8ZvFUS2+B4i30Z3a5kz3nAt+5Kr530EwyglrBRQDTEH3Ihxk9rXUsYrJk0sr+Po6528VPvyz0448Y4ISdGI5RJP1tExWk7J4HQJqUrDvW9vTUi5uH3mZeSgXx6tyPHfr9myyLK8Ur/2FqrifcvKCwcCBigRIxpUOrz0G5QD8JVACAPEHUhQKQqySiGn5Z/fLtlwBuTdd+zIFL6TB0fHucf3c2oKVZu7b+M5KjEREEn9DsKEoCBSSm8vL8tSts3J/cVI2gfJTuiFL4Yh1MkphVKR2HOJNTapNNENOvCO6+KoXxwhdj3ZlcuJCCj9XT03K/HRTylOXZbuZld3VrEwXszJ/MCnL+8V490xZCD7ItJj4wlnvSn8CQDGK3BOOgseNRz0BQioYI7hq4IoKc9cQcLKBt8m9QfxKNF4KrBAA81lLJkv6o6yG+xgqgAoLtNejCWvaeON6dIERNX56t2LTdpjVvXXWoBtrcDWRPL3s1v0n8qDqHhTPCm3zZG4uvQXIZoEoDC6/yTqIdeEvh8/eILOy2MSi0vc2uwRycFH+2395vrx292Z54U23y2fceX9509GD8uzivucbQWO1PKWp0d88O7+0Dd2SNsus/JfVm6x0x73ZRXl6el6ehjtt8kJ5fe/sEk4muyk3p+vy5tkF1MPywe2RCaP72GgsnoBYhOfafJwVOizl4WRabs+vyv2tQ8KRx+VCJ+JNCTIfn5K2QYvrDdahcdJFBV8cEFivb0+igOK+vHBxpzyzeFj+L7f+WwJC/n9n7yivXJ1aReMbi7UhIp995t9bcjOq1x7PnjahRyAHrtk00MrDR+960/7XHCoKk3EAhZ0XtYf4b45B6m2+ITauQFNcYueFFbWalukaggnzz11Ry/v7sl1OPE8IQm0LwtqZwdbX01lZXXn8Df15OFuW12cn5f+7/SSzOoHMhNDCuDB+h3fwlsVrRr/09AwEtgDeIBLl7wLJ3UZ3VEBsbLAHq0N2mewSsIRLATwCVjys+dVkbvFNCCHOB08t9neM9jH/Pn7xYRMGsFB/9PZp+fDrJ2X5wJlaJmGxEOk3eB9T/b1L2O3OtyKEsfbyIJJuGfvCagr/pIOInj8rpydX5c7puY0b8iEvnzoqD8+PymsPb5SLl07gKy/HH5pYFWGji0zCgADG0ILCvcCAbpXLI2eLcjTonDThmJ6fJ19IXWMJtai4RkK1goGfpSALQlO5VhPYxqKJyanH7wea0BirhZowI0ci/ugjbi50nZ2usQ5HSroUpzpRARaaPs9TLYy36D2Q/N5oVWZlDwvKNpcgnbVk4polz59GQHUmv50fZJsXD49S+3t+8cCC0c/NX3egAZB9ICHaT8vcoL5IyLwsM4s5LA1aPt/Bpbcpd6co/70rd2ZXvpFNWA0XmxBiD174EPWaMKKrcCUaktfiXnDbuPUBwcVaTfYTJeAR97DkxkiQ9fnSDla7TeuG7RqC1nZyy8lZ5bHho2dw6d0zTkIvOIL2LCl57yzqH9rcLK9sbpQLoCwDXGAsE2NlNroZw6lYMx46ZghRYqK3VUmmgBL4uf+0JLbNnKHVZGjPtuqvFy+K7E8ylRAFCpfwFWS6VCvAGG2n9m6nSP4WwWl5bLtZeWl6y5CP2HABkkEdKVjAtGgRo2S1Yq/NRqZJdx96XVInMvZ5465fCCWch7MByrmKAaVbGApMgmnM1ed8jZ6j55yDcGc/u3xY5jc2ZXsDRURrniFzDJudYGwdTmRdKXSdl/SQdr58PX/jZWtATXZy46rcOL4qp8uVoxMRf1tuyv5kW0Ahac9yvChboEbBPXhVynTlQpXMGaZAZDIvXX1jz1DRggNGoCdbSHVWTbjTsmqtSfEgddXzcuO/xuZMpN3+MJtFwySh5LbZyPA+h6wwxgpIiwRSV723OeJrjay0uhIkEc/Nn7C0XLPx4GjKMwIptAYVs8TN5RiQ4exylH2YT8ru1nGZXm7K9MF5mUIrmyJXa25ZsIj1NBoh8ypqIdh0VU4Qd4iNfn11XF55+aj84IOTcu/eg3LrHZflzcvXy/Pz18qHN7fK2e7YfpAE/PTszIhlIcz+OzYMqwd1XO7vLssecZ7ppjwPy2p2WX5hfcfYtLHJAAkIhgAk9brLBwF2hxg/NUMSsSPALvaISUyserAxQ6AcyG5mWjCEl4nqoEqCy6XJ5hf3Xn3d7v4xxJfsKBB4rBiLj587flBuzlfGVvDJi0ur0PvW+f9RXtsdlQ9sbtrmipyq/+3+/1JeurpV3n9+15J5T+Zeg4vFD8eEhe1RrHcV79VjcTFDQ/CwpPsAet595rlT8X1w+tBSShcfrSx8vyUQolNeBKjD5QIXEyrZAh69OXVLyuHs07JezcpZOSpXYEFBMnU8DFycM8Qg54hNuZBSAl481+V2Vv7zxZuShNctritLFMZ8+qTjF1IwA0hjpV/2s3IWyhBQoLemm/K2+WV5cVsK+EsMaWjvZRGVfyOmuvMk8Ze2N8ti5xB1uBJRimb6PIpyrsrmxSO3TLIqpLwv9XhMBJpOATAdF0hNTAoJwOJaM+AY1t16Wo6fuSjHp1fl+dv3XajPvX6aRSQAOJqvyvM3HpRXb52Us9VRef9b7pb12cJALcsPz8r8YlIW9z1WhTChEedqmgvauYy9EZ4Z7BtAG0ITxNdkwTgQOXmyhJTmGPGwjaMDMXSxlgpo0MZIU9/5zzPISRVTnRl06xAJKCqEatmNC45qofZd+mMEs0JYq+jDBkYVVpF9Fhx7VoG4TUqkkGoRfs3O2llh8WQjxqOXip6X6Qxuv6UnZgZVk1L7u6IgyXzRRm5IzOXQ3BCUYbi/LA82N8uPHr+rfOLtF8v0rsdakPtyEZvFi9vbVmnX3Dfz1xyGHWCHyz1yqhDD8YltYIrdvDzcH5UZymJPveYUbnky3ZSHO9RjmpcH+A4IsNmmfGh7Uj6wvlnur4+sT0iYVaCEjtMQ4OmbNUtFEH2Hg7EKllnnZ0DzIch/fuzVXf/b5dPl7mRXXt0uyy9e3Syvb4/Kh9c3rB1siK9t3EWITdYADuAjBEtFbKxp5XRHQ+6ahrUwTchz+dQcCiYTSNbxaj2lO5Dv1iym6sqjteR5Pv3ECq2a089ydnyzs5jKkaPSoND493NL+l0vts4SHoJ3MccG6xyOtHLJRgIBhjliP4jXmcCaW1wTScQA1rwyPbX4KMEnAGFYRef5uQkbWLDLYLqYlNfBDWLfbyde6oUlYzyWyrCRezmsHlgEaDCPn7v1oJxfnpQHN54p5WJiQjnn0CGOxNIlyRYR8kNHSivQcCD/fgV6/32Z3NiUGydX5fTIUxmg4KRbNhg5cOB6U4BKMWG2OlqU1emiXB0dle3FrFzeWJTZxbTAiw7iGLwjIARJrcRpqNseXIZUVp1vsLyBhBStJRwZ+xk51BJqYkGxsUcsYXCNoZyCfigQgnZeuPBsWdCCIRJQ4e2DPleKIYsBqSC0XY6Y9LB6Uhh37kERMEYGm1aUOJ2EHZMxulwMnYDK59WSIZSzgdhBnSnca3a59RIeWcSx5m2YJyfLS7fklTr+lUjTNb/dg0U5P5+XH5u/05Bbz5yiCCJYBlYWm4KLD66/k7CIIKRe290o93cn5qK52u+slMJNIyXdm5DCLV5e37TcF+TgTJAganx+m/IQtKD7eblvLBnrcnu/Li8Z79qd8mBzZJQ8EFLm1olNltq5UjKR3Y6bo28ejGH5QFpZ87CqOOL4DMjDZ+f3y/poVl5Y3S0/c/ZWi6V8YHtcfubhxxmLBIhXjQ5KXI2nCwhPD9Rjg+X9SHrazhEfb1bKbaajINLUcqJAVQG17y0mfMbYEr8L154KKVP8lGg0tSDpT8wHC9SbkJoYZBrBf8Ckrcjoyl2zLgi3ns8EIQXgxyyShGNcwT+I751dA7RUoI1amKCC0DFtnm7+yb58YHLX0IPGTIK8pummPLU4y3eGAxbXdLotT08dRQgLqc6Dqjhq2RJLTkZGriEE1+X5m/fL1fqovH76tMXZ4ELL4WiYxQV8VGo8OfXl+GkElLhq6eLLcYXXY7Epk9N1OT2+KrePrrKumb3KUOzJf2mWJNylC0+ovrrh9dBePj0tF5eLcn40LbP7pcwfTE3YwJqy9WFxRUlrCFoy24rW4ZGRwodPvpAa5CeJ5cIjS3FIUUCesxspuazlKvM68U9w8qjlZBMifteih2rVpKCR+FC/n7BPCpVP+Hug+RifmmoiAp9Tzu+fV47el+0fxn/IqNyYDTUvChrs9nhazt5+oyxfWZXlfVgmbhrZxjL33AwLeMeQWfKgQYwDSsvFBE8X4LBzL9uxPYG/Z1+mH1qWd1+8rbz/tafK57/z58rbb75SPunohYCoI5HSq7DenKLY3cPyzPS8PIzqvGAGAOJvtl+XY0MlrctTs4cGO0auFIhJT6e7cmcyMxcgXC8vwhVV9uW13az8wtUz5b9ePlOOZtuoulusTPhVwLsN5TcFHJkF38LFd8DJ7uc5qo+1jrycfFhB+4W5+H5p9XT50OpmOdsclZ998FbTxOFuxHFjvvbKs1Mvvkj2CpTrsGKK2HS5OSpgQ4Rk9i5YvQmO4CaOTd3LdjjBrBVeBFVRCifQ6YSwEsLRjDWRytssas5dyqHIlQoC4ibmq+4/6bjPI7iKSpmdu5a+eIh5NXekGtCmUGwWpZwvj8rFYl/uH90s0/m2zBbbslg6UGGGgmYRn6VAWW88UbuIGxQxGrxvCCqAVFD37KX5rXwMjBFcie+7vFfuzC/LjdmVuxanKyt3j3ingdyBsAyUn1EwWWXgrRfs3B+Vjz95uSy32/LTb3q7gdQXZxDAIoBkTEJvtsM8nngGq06g73MYF0+hJobr9ua23Lh1VZ65d7/cPrp0zseYT0w0JyCICorFO5HnVzDnp16YcnFRtrem5fLuoty/OC4PL47L66+clt35rMw/PDeranrl4BcWPqXCqlV6jWT3DVFPqhEi8sAHn71lerANs2ljqJXkH1x3tFQoBCaPiDnRHqcQSD9R5zyqfpbWpZhOfhUkYjPXRxsfn0cNSRPdhJZDIddW1CQPoSdGs4yHoB33sbHMWy0J+zxdgbl4pGaNF0Tz59neAAJoX/braTm/XJbzV+flhefuWo7JJx590BY76jaxMiuasqKE2ATMrQN0FlwsFeGP2BXQfajng2XofGulXKE8eUGiJiDEU8uPgqB7dX2jvLqBe80TRH2DwqJFFdetJ7ruwZetIxh1xbr3UI0EZ8Vwa8rvawze+5kVyTOBY1YiStUDBu/AALeeHP6ODZFcdh5/cqvOqgRf+06H796nWnD4hSBSrj5lSB+LTznVdde2Cii1jtRaalzw8jfmXKDCdEpjo4M7aXFmwEwTUtDYTRlC3g9KXxijApNXZ2UDsMVyV66WuzKZ7coULi4IIruH33TjVN3WBTK1E4CCf9eLhQmri/lR7qomdKY7Ywh5BZbWDIrDxuJal0dI3PV3hYEy1yMEAHKQzJ22yTlggm2+snSOPYSt5RnWLaBZ2j2t6J4LaGSx65Yia9bame3L8mRdjk9W5XixjnhefXupI0ieG1lf/DOvlwZr1apTw3W5WJX5fFsWRxvzTqzOMH+PTVjtLqdleh4lerbiwQEKmH00ffuAx+tJElJ78MpNZ+4OsCJCyrgoI69IPQy9IdU6Dusx1gi1frQdhX2bAhnVfM3aCAi3JNwNY1ARt4kqoAk1D7h7+5B9zE2svcbKihpU8cypzEa8J2HrY0I4Zum+H4fIIMfkonCfXe2sqJ2TXE6MKR3cXLACQb1iWe1BZolJis2FSYEZOEVXI1kTkx+fT48mZXPLEV3bu5syO5uW2YcX5cduv6t84Op2+W23/ku5PV2XO1ZJd2lCBXlSN8J19/T00nJiXt0ibRaJu1MrFQ/76tnZpQmys92ivLI9Lq8Ek8C96VU5BfPDrJQPbY/Keze3y/su75YPXNy14LG/QSdBdTocz9uy1yuauXs7HTXFcfXXMOnKXfjAI/aFv1CmBCwYdhcjxt2WZ48feNJy8AbORcvF9VYvCQCJoFvykhjkvQjQRjP1KtO5cQiGEHIi2klaUBBUZj1ZkUQvlKiWlLUXlpQKqQkC9PjarAFx73GOhRJigXxdYram4looNtu9tWHMJdjcNqUcvTwpR69ASCEu5RQ+xm4CNGiUpTBXE9b/vhVW2yPMzVI2RkXk9wAMm67lxtxUKWqSK76fY6L6Jg+BZ4rLHKANF3pYfkDGvfnO/fSzILn6qeV5edfNl8vbjz5sZMkQVkaBFZROdvLx1oXoeurUROr6NlLeLq5UyJwjVhbHl1tRABK2VnpjYpDyzW1P4H3u+dfK0RIWonsBoNTZ/8hska/FE5ExF4iMxGemICEWhyKkIWmAVrSk6nuzcn99XN7zpmfLqw9ulAcPT8r0paVbVCu3qvA+8e6sjwBbbEHaW558IWVgAQiqiKOk2FHNLTdnebvqhhsRHgcPxqdYH4VlMjB7WFU3KGRsYZNjL4Vk11b6vYSx3DQfQYKNWnbaTj5owzbhPu6dMUPQRz2KUJb2+1uZa8H+rUS2EEimLW6gCU7KZu6Vek0AaexJC7jFfWpsKhIX+R2spy6OaC6dG7tydf+ovLK7U37o2U8sn3rjxfKpJy9aqQokTqJo4NVkV87g+pugoIJbVmhpbbEEhxLjvijdcDQDFZNTIKGCLwSYJ66CkWBuSEIICGxG0JTximC1mPsG/06xsdfyDOi/Jb2Gm4QWUs2lrq42fX3mDMqcbs+rUYSdnRNxL/++AhwQT7HE1hBk+BRxFFGiwyJyqL3Gl8yNF+49E0ydaw//eoiXgooxpwqQ6B/GXX8inNWS0mnGsLF532mxY77uy2Tu/d9Nps4xZ7lSXnfJKXtcSM0spuGNz5iTY66kGPBYP54XFIgyY10IAWbXuIBLhFyzR8Q6IWHqHHFerkkGd4Ll3f1i5fJ4Xj64DnQQxuJ8Vi5ObpSzZ5al3N2VzYknCRvwZ3dkvwNReHoDtA7TMlvN7FkNfBcUSRSiDi6Y1LGO/+yRg0zv6kK+jAiACwTf8xYn6zK/7RYUBJQzcNS5xFipoyEdOEGHMeJ4PjxQfrauDOVW5h4LXItroNS9+cZ9I/69uLEoD45Oy+XFsjx8cFz2D2FdwRKtpUbA4dmXlPkVE1I/9EM/VL75m7+5/ORP/mR54YUXynd/93eXL/qiL8rvv/zLv7x8x3d8R3PNF3zBF5R/+S//Zf79yiuvlK/5mq8p3/u931um02n5ki/5kvK3//bfLjdvIuT9ERzYPGeRKKvCpnO5NS69FDT4BteF9aXIuV5QKQiCEHd+zpkDlFui8hS+pgnHvd+DAkqIW9WV2LscB3+q2l77lm4B09BG3I/XHRRWotWx9DTvZZvHale2R1MrM2+XhZDKch094q+IgCIEVfzmtURB8IYB3XWyL/vzRbm/uVn+/evvss34445ejtjOzNjRLwJZBXoXd/15IXDbiOXWd0FWC161KWJMQPQdlzvTi7IqgKSXcg4miM1NA1JY2QfEncKKStBDbPBZ1iKEiNQKNlYHuARbt59YHkHp44/qLOoUTCqkzP3JoD047eK+jG2ZNRUgDLhvaDEpQEPLcLC8vCHcKJjU3dfEn1z4ECxB9N5+TNsh4zXf5xis2L6TKq4QTJzgeN2wSqCoLHZWLt2IIEwJdMHkmvi+TFdYY95IolZNQXLhx+9tEwwuSbeuPO7psO2AtUvwPoP5ZjV5WQsTRgn+cWusrruqeayO5uUcFwSKcfHKrDy4eVI+NDk2i2ox2xk/IxQqFL28Oz0zJeVkuS7bydKfD0IYym1AtR0j5fXiduFt8aHG3AqqI3IokvlcMm3y7Sz2ZXm8Lkc3rwz8YACTcBfjtRkpMf8uKAAJ13LdejjH8DlidrSgsh5ZJFvAhYmfZ44f2p6A61442ZTXL07Kg8XMSodYbltUMkfnzW370YKgn52dlc/4jM8oX/EVX1G++Iu/ePSc3/W7flf5tm/7tvz76AhR9Hp86Zd+qQm47//+7y/r9br80T/6R8sf+2N/rHznd37nR9YZ2rwQAtSKjAlBcoyIilPkW8aJmIU2JpRkQ+/iTm5BCQqPlzlpXL2WZF9juVZjD2N5XoHS42EWFp5HLEN2WTRIf2Y383OWJeABjNDMIdOxk1iRyqGAApMo0qykdD/4gqfcmq53ZX06Kxu4V2YVoZVlsiOASvcOFXLPjg8E11Epm1PZCPAM2MhmO3MBXe5m5T0/+3Hl+O2edfsZJ79kAWscEDbQUtFXoPmem535JgZ34N6r6sLCQYE7WFPPz3bl5uSizMxN6Ois/7C6V37h4tny0/ffam4LLDIwTRTRFDEE0DbxDLBifME2NWvT9VcHtF3UNjvIgBCDj00BwWm0ib9xLwoVgCggWPCdFlSktZTvS0AbJthMiIUwEgELVxSSYVl5lzGoHiSBpFlDMxIUQfg5IeV06yWyz+edu3LaQAqTczP+SIFF2WYWC6i1XMtevgJI874sHmLueO0kszSEM9PdxUiIdQHEe1ohwTgw72zZQwOJeTsGGKqpEiEgKMQo/DiuPh08xhLrh+Swu1fmPt+j4u5uOS+bl0/L//HhTyj/8d5by//y8e+39gF9f+HDd8r5aydl+x9vlvlrkVdogsnH0lyaxoMZAnzWjqW5VRlbn8rzmeUUPzeQhLsrm7euy727l+XWyUXmlbmFXscJc2UFyxUWlKGY43NDjS5tPkFIeWmdiv6jhY/rLycLm7cWN41/33TyoNxZXJa7xxfl4pmllV55/eykrC4XZXX/yMAwzOX6FRdSX/iFX2g/1x0QSs8///zod//pP/0ns6p+/Md/vPzm3/yb7bO/+3f/bvndv/t3l7/+1/96ectb3vL4nalRW/9nzK02ep0i7a5pW8uri1tgcF0CNzoAhgiL6w9aXrq6q6bp9xUri/fRSGe495o+eDCi5ehLRbhyTzTda42mmNA1cZjACtscqNUSKMHcCDIiB2giA8OxsFi7xnJhIKQQK4Arhn1mf3AukH+bSbk8X5QPnd8sv/DgmfKJyxfKiRGIgonakXdGDmpVVb3HVrcoiHX9O4YJXRBAQMEyw2J7/+pueWF126oDw8VhlEyAMMfmr6zmjFM5M7hWJvIFPwz26fSpib67ke/c2gjlwFyN4bZL0thqlTHO5IMe8THTm4IlI/7NeBN+h5CKv3OoQxAlMCIFE2MeRO/xhxZzJYX1+GMIKUe11GczhYVkpZ2w4lIj+wJAe+ewiPZmYTi4JhLq+yXEWC6XqbAYuH4QI8WcSVE8aw0mrge/2BwesxpD06J8JgjDlcZm0xILjjvTYTb7skNOErjx5kdls5qVD54+5Xlu22l57YN3ytVry3Lz5VmZXkjdts4rYrFtW8oTCU2wL5HyEg+vThWzAOEqP96VxemqzBdbJxEWJad6BSI0IEAaZzz039ecSxOPm0GQIdcQt3aeR7KIuDfBKgRENwxgMZuUEwA1ZrtyDKaQ+a5cHc/LxWxTdstF2QRn5a9KTOrf/Jt/U5577rly79698jt+x+8of+Wv/JXy9NNP23c/8iM/Uu7evZsCCsfnfd7nmdvvx37sx8rv//2/f9De1dWV/fC4f/9+lyfVCylJhoU7cODUVZQdvxtxi6XFFRIr4jJONxSxIxVie/ksVjpjQ3mPQcFA8elzd8BGoOfhHLo1tW/pP6kapk16ZdzYhoZEK0qsNCHWr5+ZP6oK8NxMRPO1SqEAR4RWzVId+ZlpvxXBl5ZGCqggwURg+9RhxLawws+fM92CSTvnLLqclvc9uFdeeP+N8tk332Pcdfdm5+7jn14Z8zWKFh5bqQR3o4EUlHf3Oq0AW+wMawXXn82t/aL8+P13OPx77eoyYcQsAUFfPUtieBl5EfLBmO6JuvikBfA45NxpnsiA0FtD+M5cqzG/GArB/Y9mfo267liSnpYQXxFjTaTlgTtvhWq3YGzYer6XJhRXLj6PRTVuPvbR3imCOTXnySwny4kJIIzQ5XDeJMVRuOsyVqlzCzEni3P6Z2CaINWWutbS4RGAJAiD/C7mfJOwzgFhlkjMK3oDvM1gYYgb2XKHW3FdLRX2YXPi6xrCk01rMqqnWFQ37u5+KUf3J2VzvCzvffBWj61dTcrxh/fl5Gxflg8iaZYKW7CXJDCCyt20Wm6+xp0h3lx+ECYUlHRtzktZPbUry3vr8tTds3IEMt5w9UJpg5BZg14KZMcb9wjADQiXvgNqMKfi+y3mjc+lq9m8nG8WViXZ86vCzW6Km68RljOxPdK2HD/n3vLK3OeLW6+YEvhgfVxeubxR7r/+UbKkHnXA1Qc34Dvf+c7yC7/wC+XP//k/b5YXhNNsNisf/OAHTYA1nZjPy1NPPWXfjR3f9E3fVL7hG75h+AXcbVZWoAoe1HqpgqWHisd1Y9bNaM4VLZz8MJJrJc2b37PNLLVcBUNL/dLdl27HXnBqO+x418e9uggHsPiwfAIqLuK1yadI6ToyX+iv176mUjfHphSul9W+zPfI1J86BJ2LW8gwGeQ1lNXCBZr93dC9YBcQIUX1GAvy5taYHPZny/Kjr31CeXl3q/yvd3++nMwuy3YPrjbAuBcmWNw9ty8ILWDZoDT7azu4/8CI7ZYV3BIf3p6Wl9a3ygfPb1slXn+9bjF5bMh3CQSNGeOh1eNWTqCwwsKhrorv/BXEpsVEWotG9AOtLBAViedWkOfzkDnBoeeu6ZqQ2nq8LAEP+DyFVPzsnJjV+kurKcbWrrGquN4P5EGZ5WRoOaE1EuspBRRRWpbr5ihOE0amnMS8YCyJeXJ0hdYJXK2rmIME1ZDIVC0mTTVJVm6Jy4weydTtG7zZvZkH2Fq91j2GpUPX5RJJV2J4Ccw4SaBDTFX8bjHXfZkbGAKUYaXceNGFOWJmR6/vjDJofrFNwbpb0u1HAtYAhJCZYVKVywadm77leFR4JU72ZXp3VWY3K8O7zVPGN7eOQDSlZTdz1B6El3FURiw3EJ9UeHAH/x3J0ODQ3BkIA0AkIFUdvo9YcOW7ZNwW+VgmoAIpiHWHfCvEr04RovjVEFJ/8A/+wfz90z7t08qnf/qnl0/4hE8w6+p3/s7f+T/U5td//deXr/u6r2ssqbe97W2Nmyth3GOugdxouSGPoPnGhJR48fQnzfD0YfWgDRYDG1k5vfWWk00TfQUVaBaUuvpa14XH44JQN9xEKiQdiThEZQ37FY/dxM9EPoohmhtDsExAE7Z8qP2+rE/cp5+aLwUVmZHnbTG2vAcD12ZCtBBh6/7x1tibt5fz8nP331rWk3n5XXf/kxWfm09X5eHmlllQ0/2u3ChwA6LsgmeoQEidxeID/57BusukvLI5LR9Y3ymvXJ0YEOPGErhBd8n5IvN6rqbl2mfuAmyIZWVMIRhts4fACoHusasINAcvIg+LDyhVUbpiAtQQLhUczLPS+JSBOiCEAJEPoWOxA8156vKg0pkQQjGFFONOFFJki5BKuW6pRykNCilYU5FqYHlNV3sRXPidf4dw4UYchvLgEGRoKp7pxqtWTGZhZN0ieR/qboz1RUGooFrOL7deQs0IC8sxTDWGWxGrwV6O2JGVbIeRWQWILftAJNr98NyvIEXFrbD5GWDnO0vlcJc3BJQLTt4rlTY+y7QlHNDyGPzdHnOxNyEFATU9dr+kzYHEs/ucUuXGPAOwpEwYBY1UCDBP7uY89d+RfI6/QZmUcz4sygTnRIVoq8EWpWaw5gz4YSjbjaFnbyx/Fd19erzrXe8qzzzzTHnPe95jQgqxqpdeeqk5Z7PZGOLvUBwLMa4efJElMNKiEbeaudxiQtNtxniNTZxKO5TfK6pPhQu/pyCgZkc6oP5Qf/eoeSKfZTtCg9QIqqBjYn8gsIwFcmY5YsbVhzFA3wCXzc2EfRjefxA8zsnOnUvcgYJ6qhpvbcfkCeMGFqzeBkBj6v58CqcASWxudASZ2o+ISTAOYrGuYHo3mQ+YcjAkvPDivTI9K+Unn3lbedfylfJxi9eNgw+wdJRXAHs4FuZZPJIj/lyTuztdG5PDi5vT8oOv/PryMw/eanQv0ChNONHPbsX+dqYdo9YS2PjWogAxtlTReFEhl6+K+U0Wu3KGCcrerOZricGKDayQca9n5cKH2u22c8H4Z4SOK58e42aVxdz1Gd98zaoFOAJsH5upCyXElsCRZywBKJ8RVVsFiUn3rQmmSMhOgXSJOFL8u3LhNAPazoQZrR9spAQ5RWzI7hd5eFrjTZQqGtSKFjUXs3kKOk8AlSutdRSVaptJL8nlGfehEES81V6Pr0FLGo5cJoKK1N1oxZupIxrYA9+7hYKx8vhaAEFW27A0hQ6NChrdeSOK9r7lJ67ekF1VADd3tmX99LbcveGJtpgbs4iv7m0uedwU7j6Pn0YbW7eOABHnvKK1taO7GC5CuJVju0Xu19FiY6jBu8fHxopyd4kabSRZRnqHK4QsmUIri+vDzev/CYTU+9///vLyyy+XN7/5zfb3Z3/2Z5fXXnvNIOyf+ZmfaZ/9wA/8QNntduWzPuuzPvIbiEzAhjJ05QlRXe6Ccq0KuQZ+3qpkLnM6iynbarPs3cEvllJzbb2kNq7tyAMpnrSRGiPFAACzhElEQVT6leTe8iziznRDrOlQvacgiHsGah+CfnwIae/OTddMGz+ghg1UkinhlkgZvvOROlP6exccq8hMqtK2oPcWjD67PC7vOX/WysQ/O3844NBDTApanmEv7EtUTt2X+7tjK3Xxny+eKS9cgaPv2Olhgj7Hp4OXW8AHWFS2aWj8IrLwcRjNkXRbix96AcTYdEZMWXyfAeh4ZoWOa8Itg9grFKdLKiO/ljGp+hKCbWDAGlHRemZBITmXpdohpBDwj5iHxZginuRAGBFSiC/J3yakIJggpAB6AKTaNuo6R9gv93gEejPnMsOrAQjQuTBCH+aJ8N18yXnj6zYtMQUyydxqKyjLWq8exWp1mdJS53yuFXZHOPcylpRWnE2SOg77IfFzrkfz/FcKqWqs769NHcG62iBdA0VJkSQc1rtZ1kjaZcVmiWey0jLcgHT9EaCDeWflbiCo8O86FCPLEvaOcm7hWss1jORfuvZAt5Rxq/BOwBKGGggvBoQXlMCPipB6+PChWUU83vve95af+qmfspgSfhA7Qt4TrCLEpP7sn/2z5df9ul9nuVI4PuVTPsXiVl/1VV9VvvVbv9Ug6F/91V9tbsKPCNmn8Zy0irAzOuSaLjSzmhIp17FM0OrIkuX1vGw/XGa5oJJQVYVUbXXCCr569OVC7FauUZpOvtnkvZwHD3+yWFvEm5hrRY3OnmViGf8VGBFRpv3OJ7ssqJSjGefyfrMgosoBClomZmYipi7g8L1jw6JrwuDn+Gwb7jLsf4g/LStdEofLXRqBDLQS12jHkyVzOA1A4guCRJV4Xmj8Dy5Oyg986JPK0X5d3nr0sjnZlqhyL8XplgW8aQBJwA2xLZdlX3706s3l3WdvKv+flz7Zs/9LMbJN9JV+9MyDwmKOBYmFDhi7x6wqyayR1kb8iaIp3mpWwmWuk28O1eLy6sMufIiUIqwXwukSGmzkRFGzpZBKFgtadtNAH5JkVaDq2GhsgzJQBIpNTsoO5cKx6Zi7zq2m2WWAH9aexwKhYwzXeKf4O6DkU+a6EeAQ1pBbVuHi0jI2Ou291G3d2Dv3HNeBx3J735xs3DmFVUmiwhl9MORpy7SSt1LFSqymdt2G4pPeEylJQfe6xswMQFEZauiC9AT4uJ/md0USfOY6aXyO3ZzVh1Vhlt/jNS5LuXqqlOmtbVmcbHy+2banCgxD5qJ423ysLmfmQYHbEKCKy8uFV+xdh99gH+sPaxKIUQiwmI8XczD8TY2QGbRP4PjzNRMlVZjsHlWhLemeUMlfaSH1Ez/xE+VzP/dz82/Gir7sy76sfMu3fEv56Z/+aUvmhbUEofP5n//55S//5b/cuOv+0T/6RyaY4P5jMu/f+Tt/5yPtSgAnhPXcfge9SnUlGNUQN3mbO5UxIiHc9kUXh2kQdHLkohKhxjeYCrPMfl5D4SeLy4RX5lrR5RP9jokfGJ56/ybXim1YZNOq4zZAh2g2EU20NBu3QfjtfJeuQeYQOrnHiE88XYQBuaVPuoGcP+JIYXigyqif1NJg2K0hHBa7splMyqv3T8vrN0+s5s+bZysrbIhcqAvkHYGmCYnjW5T3uFf+6/lT5YXL2+U9D542fr6HV0fl1tFVOVqsrRw5XWm8IeHdOyxi0yd8N/Z4k/vWcUCYOPVckMzGqwfdKBZxfW2iyKA1aqIRg7KYV2ixtJrQn8qxVy0njzXV4LS1beS9LjSNeRubB11661mNM8XPzCwoWkxuPYEnj8SfpLKZn+8i701cnYHUU8uAr8sBPz7XPN3HmVe4kfswhOLRWRE5N2lB9xol54ydr19262zsOh+omMtUKAScobRg3E6gbDH9QmDzGTsSA5aWoFqN7b3DRZlCs4t3pZUp58v+tFfrUiw3xnft943HbA0dClfbHFZVCFoB+HDuERSx3e3Lau2LGHMW8wZtwWNhSo0+RyisbM+3sOoiBHXYdAISYDxc8Bm6ymu5jUy1wOdXSCr7aAipz/mcz2ldQt3xr/7Vv3pkG7C4PuLE3bEjAQTpdA9mc7Ge7G81/T0voW724u5TdNy19xT4twiqdFlo3/wP/0fbpiUG0Ae/o7tNBR0LEGpsqukP2dM9YVdJ3POmfeFBXkovZ8w4c5cGX1/jnRq5bVYV5aak1xyYHuq5axaf9a0FSxw8woUIS+H8/Kjcvzopr25Oy1um98uR5R5j49+Xi92+XJRJeW17Un7+6uny0w/fWt579kx58f4t99WH5cESGCaM1JsqneHGitwrukA1+54IT3OhiPDig/hvNfHXQytOdOr0RZVXDwJqtZ07q8Q20H0EQXQbjBcfjOE3y8MFGQTYZh1CCsJohQGbiNUUuUuWfBqM1VsIJBdOSKb15NR9WUBIhTKSpMGwFiik+Do1tWEulD5UWDTu2Rrl4lerYNlUlrJR+aVzAebcoSOkNizzpgI2qtkyooNKO9kWrTXtvF7MczRm1vqA4zOlX6LXQ4qP5h6iDCyl6Vsqj9EeuTIxBuaOWwNf5ByDuJ5ksqobp9tvCyCQ39CsbVhHYIiPWGXB3Mngc7j54Dmw9x1oSWy5MedcWEHJcpCEzRXm/RnIIsrNoH+WcvE/SUzqo3poQqvvEvk5gpIpNDTnKd99z+M3MmOFtNU3dFpkGmsSDUqFt4Ee2K9DG+8IAwWFly36aiWa8DJBBUHEEpiqXbmrx3rQM2tIQm/UafAJDhh5+tmDISNue1BOxPmmba8cqbSdB38iLTBzAxH9J08rCb17JOlavMpdfY0lJb5Hl/VV3bbflkatbAvmR19+V/n51ZvKO2+/Wk7mTtyKzH6wVFxuFlZr6eXzUy8BD/aJGconeGkG5GxsV8dZkoPlN3oh67ElfO+JvsZCYQvNWbPZVwsKxxxI8tfYeVQfpf/f7p/5TAExj6C2x6TIDOE3SJ0h3Hr0jFqy7gYlO2A1IdaEzQqwM89lmsKNx6J0IaQAckDqgJG3BuGnCSkAHq6CfihcurnB5aQIT4XGUuUfCiibX8yjsnlYz7Nlk1UIok21tghMSMHjru7GM0hrpPd4QOEITj+j9BrzhkTjmrCbFa2ZpE0PAabbtBd6XZusIMAvJBZHCDlpmfiMNrYAjfA7WFoaRoskbRwa93UACkrmlHL5rBeGtKouECoXEBawZODyn5Qp6IyiZIkPswskU2QgiJiKQEXGPpMEZrpR6N0EgIl7UsQVzX1M5CD4/ra+BiGUpljfMYe3cLl4XoNFqT5q3H3/0x18qyk0aJ2Iy00WwvghBQv7z9ubiVtP3Hx9fwbNd+4IvnHSKDUxq5ZdIoOoiXaT++TPgedqYOvyT1qfBx5TNE37a3fAiopTqzuwWg78pQFGdCPpSkKUUBBtrd1w6uMS9k8GavyF6qrbi5smSGAVYfOGEADSD4IJGz0ojhYg1wyoLYXfmjRBtoCpWQtBbBxVKwx3STBO0BJVjnNeS5YKvnKPEU0aF5/DfSOHicKKDBPCPqHBfcaWqL3adA8QhGm/K+TmwGqaOgrPyl2EO88Y6UMo4fM1yl8E350lm8K15yi03vJJgzEtkpiLHKvKueunEwnXxTx1ivEfXzIxnmnBhMdDWh2b5Wps8H3oDbL93rKx59AsYdmPYw07AnHY54OHKK6NBRbCp9kqVLk185pkuUSL15ypwVqAPDkuZX1ayvZ05/FengMwjNFEAWFbO0QBhUYppGy+MA8Oyo2xiDDRmS7Omi9QLUCPYzFWbVbUdm8uZr4/1DrLPL2wsua2Chiv3ZX1ucPYn2whhZdsjAoBLuCLV+6+ZF+QWJRcX9FEkhfFQxZhajID0MSwT/X6uDfdjUy+M4RBsFniX1a4Daodc9spHJ7a5AhfXwZw573gCSbnYJnghmPaZ8bk1Cup/W4h4gx2p9xn7Ipunh5B1SQh1jypsXElJN1YpvX77FJQEGERW12gOMW4/faORDqflV98eFz7Z2t0X45OVqZBAi4LFmgIKsSi3GKpAASr+wNtE0mJAUXXLtCSM+OYoAUKTLNq+KorfRKtKAodCiDmp7ih4v2A289o01gFNwYefXLlxP3+UEKT5mhbXXqG0Av3zOx8aq48L5PgXHJzxJrWsJBqyoDFmdawpLZVMBCtaeVmBPEaL8XjmpKTJIm0DQgzUGr2qqh8hcDSaynBR/Ol0udXF2zC1tkjtBfgmtH1y3USQlWt9bSMNPSVXgkqUJUsORWutGy6+SqIVz5rujpjILjhW3OatJznEFQhXINTn3hkbkG/N8tJWd0sZXWvlN3tja8vsKlfRcxxBuUFtcZmVq7EXNlhFValZlp2qNa7FXQn97hYd5l+YGPMvlR3JAFTm3VQbYGpZTazWBgVPszxsyvn7jMofDCaWNXkC/BCPeFCyiaC5Z8Evbz5yjXaL642mtoD99r1Btbol1n2XVB/veASsIaBIwz117owatOyuya3dWcJpcDDD9PRGahG26Hnqz9byopUqRALBOvFJqb4+NknblrBHMCM+lygpF9CI1rgMJiqLefmlrtJsxDivC5+Cs8kdbB4SZRFiFo93uDY0Av4Q609Y9bmxuZD5RrjpGzBhLGDq29vlpPYsj5/7Bcp9dJNgeY10H2X10kBwRT3RN25FpnsD7Ej+vDWWk5ECO47IUUEIfpOIMT6Yu4CCVbSalpmkdNkQIeriRUIdOaHyMuJBFsi7xqLt1M+rO+9wiGuNJsrAGR1OTvtCwrrCb+qBa4Jt7TGZb3k/NLikSyJk8VKKS1GXhDnZfNyBZTA+l+N0imx5HjWJh9Jl3Pim0bmSHpB4vaykTexp0TmRvOzSdlaTTyyTESqRpQK4XV7ozzyNuHmW90tZf3UrmzugZE3IpqIScOSITciPgMjElzUWE+L2iAElAJpDEWpApo3DqBJgn5sT3AmEhO4XH9XM4vXruazsg4F7Wp3w2OZV84HCEc8KJmYZ7c73pctKnc+6ULKj7r5+iYtNrf+e8DwqfGlMVRQL9CkLTPlORv7axWYIW1z1TYIAkUYts/SfFYodIIlPfsA0zv+Jex+ErZA+utlc5DHdaRNN1y2kIM81RZ4rHprSyZrapddvA9w5RyrmgzcuGIk0O1Z/qF12nB2KnmOPVVZYfkQYc+k3xQ84YawOF30DYAK8taZIDygwWcScbj+6LobPZeIKfvbBaBbSsx1Cvi3mPDep3CDwN3I76SkO8EZ1HyBtALianc+d1ceBBP58lYeb5pelbI09vAQUhthEafCQeVgzOoYKE+yvGw+VGh5nV/yypqk8HhO9VLoPOvcX14lu41/ZYIvra1MIemsmK7t5rGyv9Va6Zc15Z/fRyoFdO65HLLGGyP7Ap9V0b3duYwzUYAlwCQVtzZ3qkSiM91+AEnAzbdDFesTlKiJh7O4bqSxGArUOcH8uSEgqLxVfkYnB1alr33nw75TCDc+/ly7u1DKIYu35mqelPm5E0lb3DkUVShVe7DYK838kyqk9ot52c9Z9QuBQ9qnwhShwAm1UHiwMKF/0bj+kp14r9YQA5DcMOV3+s/ic75Hh71rHkaq4JLn1cXNesGVn3V5WHQjokRJIBNYi4aaY7PoVMDo7cIlyJwkLwPg91ICT9uQIqBOSC03E8w5z7av1Dh2Cwog7TbzpBSZJY/UDJVaefZZe02vC3iu2bhWUnOJqgrt1osDFuiq8xiWlwE33jFDALpAMYh3JDaSS8+MjIgvgStP4b4u6GqqAes4rZAkGTDxLC6IDQSWEqbyyuNK5rq7mpQlkHfnUfqCwKjITXPwQyD0Iq7UCA7T3GWA6Z6ydsQKiHnTQrx12somqgU2xV1Y33FA0Y3nMQAUWt6G85BsLj3qPCwbY3QYk0Dq+u6/S4aIqrwYPZDl5o2bgbR20h1umj/BSNJnnh8Jw6m7UV8T604FgArsARQ900RauPne1pi/u/UNEDKXcvXsrkxubstsiVwjV8K8zpRTLM0uph63uhFgFYsdOb2atU2GEQIjVGFgXyNGbKwj5Gzs1jFLsNg5zPHi9hcsNSzVY89B8uGwpqyi8pMupNJi0SRA26B7pvFrfHv9OKUVQwHFGaiat3zW7665SCNzvNltxZXSCCSdId2vKgz5RU78zmLrQBJ2RH5UrULaPXvmY1SEn50iXGWMv3Dvl/22yXGyTdmQfeFvH5MTeU34yU17bE8cm7rNSNNyykfubyQgjP72FFKpPlfXHF+nbYw2Fo4QTWyOWUQsySFDHQJJq90S8ZShUUvG9jY8wXZSNuu5ofE0f8lyltaBwDvzuBISapm7NANLOA1yxlMFumwCa8yL0rvbNNm2wsmq4ODw0V3WWAtqiWnyasuyn6+CSb8UXGkZXfPC1TqihS3oXP8qLIfOKtN2G06/rl8Hj3zf+0E7yVShSbyW5iIgCyqlvbNkzKK0cEUlfs7do3mGYj+bk1I2sKCOUXG7+ujN62H8f4GUpR6HWKUlyYsJ2AukftgNVt6txyjBwlpa3B9YA8yvE8XJCKhFeSG5sCTz9+c/wUJKjoRVOUtATmjNg+0TUxuzXKDstIjypxNS+Xf6NWosrKmyKxadalf8gO4Hovuyb10i8WCBBfDCNCdhQM9nkVPF3900IW4cn8QRD8D1USI+GStSGEuQO7VAYbqQjrpWPXwGd29ELg3gqVhsMiTNv/0RL88g+PnIHRowrw8OkS4MCThug/xEcDdQcu6G2VmaHZJx4Wf3eJIvE7pHk2sv6jfZ34wnxX3MjRdMD6nnkGPPNPZJ2V3NymSNSrThujMEXmV7OHptX+ZXDg13slYwaEexP1BNRdVZ50f0zzzY7ZD+RJQpcwPHgrRBOmZNtkS8b5IflzqHcsNm8mkqHkzgbS0r24yadysz5UDOLl94xmfbV1t7OPLu3fKp4CDGUO3rXqCNHA78GC7X6FKFjwtTuwlMehpGxjTjXXmPGLhwwabO2gunKYEUpaxvl7K9tS+TE2gwwQAZAwK33xawc+Y1wV28jlC1JXsPvQusDWe3S6b7uLmWIbF0BW+P42NVcLKdOC8q49AiZ9sklgDxdD4/65E98UIKm7u5+HrrSLWna1QHdbGpL1m/p8Ah0zoYLNis5S2VcSFl/eNqHem70idZqY6uT/0z4ciy9d33g4UqvGBqRYlxkRYCNW8FT9D/nJZTAEXEuks3RFIiVbRSLXjoFEaGj6DVFONhGp/5qVkKtH83FZpLNdO7zgXHc9zibYajEUyKwKsCSgEKqajbq6M7TrRPxqYiMZIuQ3KXpYUVv28N7eTWVCZEGoebu1jIHD63hR8cecaXVyxvaX7hQmn5+sZcrpaPFqAg/J15N6akIKFz5uVPjoIWrD56O+XM3ROEqYN5U/8IPFL1lEvcIhF2VXZlLaPcZANBaK266VktrSiT0cDbzSKMedEoWRSKXKbV2lULMAVr5z47qOXpdjAmsAy80SKB4cK2OT5S6yqbEotWh9VvU9F96fVxqpL6jLlpxxNF7bXNSSnrm6Vs724sFkVwkf3ktlWrWe+OAAFknpMq12SXqWsnlUejkIt3E8UsPaHbXc2WV7eWfUJAUGkI5PsM6yvcfYyDWh2sHun7xAup66Dgeg6PxnmcH7ZanjaXm3ZoTfxp7h/XpQXV9a0JsEjD0nbTz1xckv906BH7vmqciUjA2ujwWtF6c7E1XGgyIA1YQuMIshBEwCXKKIalwWjEZpalOXifTlDx7mrgpl+k+SDAHgeGqe5V3NQq2WZ9POYghc4RwWdDQIaQsz2F+Vzk2rPk23DtbSMvZIV6JCGY4M6TIoFJ3orP8HfUWnIrysumI3dpfrUr84dbs54mFhsMUNAG8bFw4Zqgj3QFgGXAq9bMDXU5xbMrDNvy8HRO0BsRrq4gF06LbGzPTyVPhFjEPtLQpcIj6G5vp3o7FBKuXem7lkJAzmP+XM3JU7TayOKpeRf5OMO5036akHFaqmJRNu2OST4FXRD5OOzVAKbO59sdeSxqBxLZZRQaFJd3NV/oRo/cNChFfc51A9pqoI31sUn1hXhSKFCMgw7iTlo7TprJ5r0ocLM/ND9vOCE1Zn3ouVmFU0hpo+RFI2C48cJq2oJaX1x4tJ6qv6nti7n3woWXn3OFWY2EFiU46Gf8h0XWmu/E8ovd1DU45jFI9V4uohSE7dgIoKzCgekrThRXFZxN0JdF2caGWwo9mleupSaMMW/ZC+zIpBoXDLnppVDq2mFRPkUO0vpqBKyfB3j4lnWiwjVHiHrXfYl3UVMN+8tylEpBritylPZMiOSCM4Hk9EMWGA6i1qQfCpJWO5ew4mTXdgbxo9e2ZfFgU2ZX2yBK9urKBoyJ0i5uQc2sPAt+wJNmxS1NCohlbICKxGDbeWQ4yKGUTTwL+4X1bf9SY+bfMIYIqAm0pLvU2jhum0c3kpSqeKWwws1Nj2cJKyK/O7SZ0aJUha65B2OjgR7FBm7TRPoUmleN21Srr7JDMCG5rQfWCKu0onQ/ihmosO5wiTbCdDKMMbL8xva4lNXtfbl6Zl+mx1tz61W9tp+7zqNpVa7ZjXCrMVZlBwELgtityiotKOTXiZVPQZUgHFEoxvg3VRHl7+JC9Hav2a+fGCHFYz8GJ9fS7UPY6WGwQffi1XrSc8baGxOYjWahbpI+WfJxnpNCY2RB9n/nohoHMDTKlKC9mu/V0qPrReGx7FOvyVLzNGRQtaYqrFiBDSPYXntl3X0yD6p9TI17VU26avjYljK3Cq8y/OM2NbZa8p39cpcYhZOdGy47q6rLz1aeazLZeEE727QN8BBxoeDGM468KKNey1vwmaslx+KAZlVxznH8Y0Pz2IXHIgtiUksIKlQ5drdfPnNYlbROBqgssbIomOwWrPvEchFoZ+MXu0sPlFwEJxmNRr7r2P0P2iR678bVJycwCdiBuIftjfqcnb2jf6QiKXXJ5NntM7qwc16qIsg+hXIbzO7jZpeYiv1jJbI3O5WWZWN5qBIXG7rBzW863LwceT01xpY8iZnpDNIGvkac16icqJiH61AsJwNrNLybFaHnP3Xt1nBAC6xpxk3XZf/qxLNiXTGh6fr6G0dIxYjUxS0Tyvj3Ir+ov0qTe9MBLxO8sZ76kX8MLYCwd9NwOyFzzRo8/JjMiWg/E9dye27GyUbcD2LNVfeeCONuUrY/VbDnXhsbF2G4LAxnmzOyBLqFxIXLIWqMH6N1oaYc56UvvWp8GaeiS9FWgPj72SgWRUK8pR9sjvcIzRyN+XAEu8Rl8OFxXLCA1y1Rq7E8wGfPWm5EN2oJ8rBSGUhO0lbEqQ0sURkflBvPNlRSRtoGNi27+cxiUBaLQsFLbqgxdxEwz+ehhZSgMypwXlYlhYQCZeIdo5Cl9QHtHLs15knYakFpFke11HpXYzO3VDlhO3huqzRdx6xu9K2nymKi8kw1Ub6ey7GgMHJLh92MXyyFQhGObddrGRJx3XNN6JRUnyYbEEsj94EDDhK24zXYHBRjJTjulrI7hZDa+lx0+k4XtIgbKRiD44/aaJgTCRpxoWAKhpbgaW5crS7+5BwW4ZX9FWSvemV0rqfsVsvZ6pGFvNq9gYRUQmn1J1FJ3LDJMV+kLLsuHmqsBzIdU8viPWK2qHrfQ8nyb9rw7kK0buD+1z7UiLWWq7L7EYHqOU1VVUujRbTpAcvEADDCuITEbOjuSSBGt5rHgBPUulLghGsAs47ACYHMusARAaXmno5BxIuSUNcEUWxaG1ocnXHc6xch3HOMo6hbLigBPEyv4CarFWm50HwhyjizCCAtIqu3Fd0ODTIr1YZllHW2wrqm0LExXBG7K3G/zkXkuUexwau7Du3A4tINOc7nO2os+6gOkBDrUHD0PQPAgeusDAP6D7BElO3guGq+U2YuGOAoGmFsrKl/VueA9Stcc0yfMNAN2yYlVwMQkTwpWnUE1eoGKW7rOga+jJFDlXs2wwIBlEghRYWGL3TEOmXEyXODQqCTSb+x9GqeFP/NCrvHk7K6U8rmZimbZzZmRbGqsl1qgAlNpVDlzb83AucbuzK9CC5HmQNU4CqQI2KmES+le88IiWlNMRmcylYAIzKSwK2R/LR0Y8s2DFqunCewpMobQEjVfUyEkULGeYh7wy98lBV0HSAjYGDsQH4sgio7x3PiTVFDZ1+ba7s8LBVuzWoQ9F8vyPT5hX+O2nGGbFM4tf1omuJizn6FeyXdKO3G74+pCaRyD7YZRQ0tifc6ap2xMdcc0GTTjhwTukFEplWtrnMtxfdVI46TWT7dEhPdUiLwI5kdIKSoDYamqV1MRJO59qr7rloqVZizk6hg3ExVqUybY9/4a7vcOBzCuUcEXFMWIsYrrbNBLahgZdD79K4tojz3LMVBoTai0I0YHMbFEfNN45tx90rQm3MyhMbYMmxQdCIkGytJcsjEvaiZJslSbvOLvJk6jytgqnoe6oCkgqSvpok3qzst1mDvxtbHssRnd/NtkLgbrBITwM0FLj4dEVKKu7J1NtuVPaqAgs+v62MdxoD457iJi4/zVoRrY0GNvIuE/ItyUN9pvb9RPzFe9aQLKYeD6+4lVlQvZGyljCzw3uXHCW4TVNggaJmlisgcKNasSvOjtdQCkZVIJvtc+qQO5aRNko1JYhL5g1wwc4tEP23BBdFudzAAXLXDbkbz7v1mYDBzbuB1t0mqpBgHNy4r6ILtUgO1AnmhdSJPYoeyAgjsUl4yiEtBg59091UhnQgzfZ/cfJt+UxhWK61xERJmG1n0+B25SZ5ES/dIBI/D8qGg8QC0JCqGsFJ4Py2bZIXoyo5rP6tl241/zmEhNKbQMeg/gBKd5h8WmucyxaYq926tXJLIVki4WUp9Hzn3Y8Dd8oBWHzlaR5E7ZZBj1mkTQUzQBEtQxHMlA8vg5dW56ZaL74hIhKbhUufafsStVq04ClmzMnXOcH5qDSezmET+0+0ZFpSW4aleG+qRXQ6iCFbGS1PwYYzMEop4EC1Js7r2ZXM0jYTdSbl6elt2N3fJKmGlWeJfKw8z4mjhI4Ln0X452pbtaulrTBVgYc/gujKlDId+l2kj4QqU8RusRQUxa2qoVHBmqoLVv4ouvvHQfWoddCibcTfZAYtLYzn5fb/J6GwU1J3+ntfred2E5rlj33MWddZTCigTUsF9t++g55JkW62rblo/apYowaSaZVHR0zQx4wLjQpfNVZ4xE3iD1ds3364/RjQbcG2pO9SobSkkReiEGteCNkIAsZ0M/rpLw2JKCamtvxvaiBs7GbY6l4UJIUM5VcHFEuO5WOPaRqPM99P9Lo/i7TMBVhB9xmJN7hw+b8yFClDLuZNus96lK+69tHLGNvFmjqhlENY1+kUGDbMEJ4bkzFeuelciQjlv2AHR4PvUDp3vYUX7k9V52Dx3P23t+7hCUXs5QWqcqNajomIqCoVYEJX0Oe8wPm65XbTuV81FNAElgi1JZZG5EGg+Y5VY+GTM+mGdsGq2DulErFr7/WoxL5tFVBEgYEeuS4UzvBusawVB4nO7AiFyvPne6N4W1okcgohV4ZmMt0VRpHjdSyBt3wgEsyqMxoRTA1Rof8Rqr2qAACXSNSIyKo+c1PHSWKBQNgo7DELcuRl1ZvmH9Qa9JdRYPcGqjnthw6IFSNhcgDsSOmvWlp9jdyDEV63/a4SUxlTrQhffu/m+o4xGavOEP/vJdA+a9WHxJ2qxkpjLVRCUQG7diNbG18sEQbOyRhSQKCVARJNtKxQ6cZ1zhvnvhIPn5tHRtCRLgro3YoFmUqNZFyI8eZrkkuhDcMNORm6OswrYqILrwBMyhIYyYHxoYQHpe+zasP6gjfi9WiHdS6dFwnk7FpvkebTorW0IKR9PxFDscwIw5LnZT+u3zd+ITfGZUqjzArEYpZzMoAJwvPNqwY6sUxVmzS9V6HBDrsqNxOv0+cUd70qbfBlWUg6ZDiHXfgCHKhS+Ppv1J4ASsNDh5lvd25dysitlUcsC+pYDAeXlZLwPkS9FRTIOL/Hix+poV3YoZHkuVmYvqLjGQ0iZpwCns9hCFz7nrciMomPHRhlHtFQLq+ZMguIYmuW+bDv6pSdUSBFiLn8reMI+01XagQ36dpgTpQJrzCpLIRWRRBZMbDSqA27HsUOfwe4hmof67imktP9cQCHgyIqebsIcl6GVnh7FXmiJhcdAKS9unoZWQ7hEpqttCMhK2eNZ8145NHnFEONhrorQIhlsWzZ4izfZRA/6JJN4bSdoNZkmHytQ/eoVyEA0XggAiRVlXhddd70OEdaVIpX642AuT7wjIgjZhrteK/fZgMaKHJS0RmgdC1DGNtMOSZdoO+k/hVW1rLqYSyK1Wstb6z8pE4SP465Mztdlc2NuQA/QMjmMnlBLg2RWgUk3Y67REGzRR8v5YpVsm1cAaXjHMwesF5p8LlpGMjfMdSnzNDdbKm36fpsX0BlKVMqyGi1prtr8rSYGGMI/YzjUAQR4ZPM0xmBrbr5Jubo3KZu721Jub8yKQixqinhU1FGj9aSlYLyUZvcYqS9MyvRoW+ZlXbYwjcYO60NVuE1AIRlYyp6g8m9yAOaN9pGMPinzh3j3zA0UUIWMb8Yhg0XDFMU3BsHsyK7JY0wzjM9HA5fKKpG7N/8z6gc5MKH53aHrHvMYoA27mFqzkUonuLno7VPb6xZo9H8QD4mNsLEgxjwr9OdLrCMXImmTYoPOch20OvKerSZrvm8JhGugu95TUEmmYNQkWbrvzG2/USHlCy+tICapmiYrQm2EiDf7G8zOOq6pOx561Xw1DVCgXpMIKQk8u1UYQj7du9VKV5BppShqkXqJZmssYB3HkfjTWPe1X3qEwDHGe4Odt7E5L1RZhZ3HJVrvRM/c4IKgA9+4iMgOJPhgpEuNwKcg1qVBZVXXaRLoVldrbaP7t1kPXdmQtLqjonIqs9XYzxzD5Mv0S7cAShw7UGJ3HBZUWEuTbrnzVctT64xqu27ejl2ZLnZlC55Mzo98DkEYxbyzeLHq1vgMOVoWn+rchYt92W2CGmzlH5KMdrA3sl/qmXjM7fFjW0jZxpG0BK31ocfY2842+lH0shd53RgAw31n9XyzhOjbDfBEbx2NHZy9Y/3V5+ORsSiyh6orgjEw0OhwQbt1ZfOFGmHzHLz/sF/MgfBTg16F+SSNNs6SHj7+7s+eGox2u6xlBrI0dhPecoBCChxxvWUfYow8B2nSWkhMFs4k2SiLHjlHBEI4eEOADrRYYN1hPNNlwU1zvOKsLvBB+ROFYbdKf26CqVkGAg8brjl0dCMlJ5+xXM/978Wsur4Cvp79teeqsOx+elW03Ni6CHfXQOjKxqf1o7r9DetkfrY2K2h9exEW9DTYMvZldhmAIUXScT7bvcQ6UQCOMrTTWmb+VZxHi0bTKZwZpgU35HjjX1hrqRBFjpiRKccsFyJaCpUmvUXbCKtAX3iF30eCOD+jLCDYRQif8ffqthcyvHrTtkyOvUbUbO5Cap+TxomQza2nAUDrltce69+tVYlGW/ttWSO+RbZ9nSDhcvPH3JeCxGHWW+OcM2tuREkNdOH6dFYml9Myf3lu76oqjCPbS1i9hxCOT56QYlXaXqMZHOK2ozcvBUScwhmhBLF26QGXXQ+AyN1LVO0xAci33SANO8HW35/3srgTGV3l2Xh7m/jMxK/bZCbt8fTRGdee4veTz+QZ0ycfMS7PS3KNHwIKwsnyfUDrsoT/uVK12HLrN/7e6OTGL+6lvQgkAhxq3lEIooSMh7ACf1GCG6ItnJdeQ0/kJE1TWnoaRtR3rItL/m0AmiOvJf/srm2438ZADnpk8CH+HLizDvD2pWtMSjAc0mA5rTKZWASFXkTBaPPVyytPrypdmG3u9t4iN7GJDVehoc/QCAh95muPA+eLFZfxH6WC0ktT4RopcX/NGI0PIaWRWIidwkMwkn0f7PUAS2xP9mUCJB+Ek9E3dblNpU4i5i9yKVeSlrhvfu9ckqAAcwg7+CWr/gG3Xi2YGO3C1cfq2NEeiWzz7/gPYmMAceym27KfoyjnxApzTlGWPuaeusjhccy8QDSye8MJKQUwdBZQLlpZFN3Ga2co7Nw/aP/lOaNBZolTaR/GgBzeWYGU14Wfi7pB+lWt1uHuMlNkA6hBZW4E1S02Zi2Nfq4fcdNQKqTGIqjPzViKCaclGBFCQAF2vgzYuS2QTkB2wqmBY9uYBF1LWEIV/MB8JIF8R+zIBNZGhJQIHdOebdgc9IE+R/3CWjdLD3F3jeaJcCiF3Tldcao/qTzS66usT4sjE6EPHWI9NAJ/8L269CIGNuYZSI2/h3fLZp87m9zDEmp9vsN6Mh5BxCKpR2kMKirs1tIyIpDTKlQc86Fnr3O3gUSHRdZA03P+DpPPOd7pEejK2ev7adZZ9JHgF+1X2Eb1OvlpcsPYFfM6QEjBzbcvk6PIiYoJSzqnvc0p4iIlNzBvDZdrnVhk+HenkDPzmyCy8SCmvBVE+wkweNWKIsMLARu0mvhssNzms22Zg91iWcpmsS2r/bTMzhdld+6Kor4b/LO18jxafHPy5Aup/X5X9siVMq41yefxL1shQTBCaMT2kSl69aLRxR7/1gJoHPXhxPXf4z+HhNT0EBTeGq3XjjiiPbfFih3VxSPuwOomo5uG+SqhHbKbGr8QN0V7vzZVK7/P3T7cNHZCuBVNK5yW7VG1oDbHUdwwrik9N5jUpeE9kyXcEmgr+Sr75fx2EYfSTT3h3235kdwso49MJGQlVGq7aYFKomG69dRN0QtZza4XOaxxB5V9CUTJfnBKeimO6eW6TC7A8MlcOGi9AaagKzqshMEy56afwlV2CbQR42IAhywl4+unQo1HTMnGOhPIfYytgWaC0NZKh8zQ16gYbQAJbHwhRGKfNF5AWoDZT8m3UrfmZFiBt4nvZL2mGC/2nUjBAPHYx5r/1FcStnna7Qdct9pPuhfjs4S0dzlT/XyhEIdwWt2clKu7k7JGTtStbUDL5V2ORAJw0AugyoMTJdOS8vpoOMwNGBYTdEQU2+SLnqJMDsEYQkCrQimFlLfckNqi7dlsV5YzKCgTE1hXq5NyOT0qNz7g94GVWK5qjmEqMMw/fNKFVGuZqKBQdUkFwdDdkcmpg/Y+WkerfbUb3riWq9dlnoXNHjVrRBNtaIEkOMo2B7+PabBDLbwRZLKovfDeJISTQ2nHNvL8N2NKFCpMsPVzjI6F5SvAZ7cVSpXYtJT8kn/XNmTBcTONYcpcEKKsmoB27nGt6043G9n42Jd+XOrNW50lh0PKG+h1BCLY8xDmbxc4T5uhu8T6oNHezOc43zZ/3cDV0sb5G/pgalwi9yLNp+kfrIn5qCuaVhXIb10gYV6kq5kCLZKI8X0zP+Ql2bMT2ShWTz5be2aiQBvLiksilT15oU0e5PCdtc/bK6J1PSmwI5GogzXdNWeMC5OyOZoY3Hx9K4AJWvzzQFeaI+8do5D7QLuNJCLQ2NN3FjO0Mu75vT9IQ50lgqkVUvo4/kJM5w+htlxsyvpkW/ag85qCOiPOpDs9hBTBU2+MoodjR+P/JreeWD72PUeqE2Dg1Qt336S3Urghh1WlJJyjltHYMSYIxLVCC4dJsk2bwoxh7BJM7kwmDHnupbzW3FAOx6FS8OUHh8a231R9w4F7D4vu8ulgBKdFE8Sr+0DU2TWEgjNfifWU+K+584JSaF1jTfMLFPtrq5uyuJq79ySOogjOAAeYG9LYIqprsrFmejfeyKvSeOZ+0bqC0uDgdNJNkx4WbYu/xmucWEmPfZmtIt9tPmtRfeohkPFPt1b/biKVwgyQBcrRBBEtjYU1cgEF8FN3vaEV1f9uzOgjbmWzTraWDgfNensMPHMpM3wOoloTjjCLjSSpAhPELVitIkm0JTXRgCg5tmiW+lCYuMHWxXMRFhSuwXxxrkO1hDpPSPeufBPv1lHG62ofVGmw56PDhc3DilpOyuVT03L11K5cPbctkxMHS6TrLTNK2udVYaH900rRZs1RV7WcqkgABpw9BP/2Yh4VAMKqtq2yWnFMHs6ioPp73NTqqsm2hb+P5tuyurkqILzYfWBmlExGJotYVJQQgQcFCieci7vVtWL4yRBSE/hRuVmbSFdK4EObsmhWuugzv0TcI5xhGpDN67tj4A58ROfVHclFHqg9h852cS05N9nb8a8iGqlBQ1ulptjc88DG03ooajwlXUcxNdUtFrlF6OvFs8iTibozxuQNxE9YVGgLIAYSWFL4mLXkwqjJa4LVZHk1hI/vHU6OjY6bOvua2nkHJMj351qrk7Y60tD+FXeejoG1PzImjcCLdhsjNhIWm+soN/p9RY0UabO18Nz95hpyCEEp3nxQqDSbYcxkxpg2ADdgcIWDsUGvsW81HuINtRt21lSKe+3hzpM5b4LV5p5/BiANxnx2MakuRsY3CIHDJWaJtYsm93uJ2bUWHnn14stYF6qA1LnSFi6ttdJGFmqz3lvEn793SgGFwosg1NedKMCwopYgkEUp+H3ZnnqsVnXdg8eE59HCaV1v9froUTfxfHvcl/l8a8TDXpuZVa1bNyPjWXWYVVn38+Haww+EYArCyb7cWK7LfLIrD+8el3I2KfMzrD2QEntNNXpR3OVcnnwhdTC+o9/hEBdJCh89mthVfNa4CXRCj7gV+4PXjQEs+ntaKREBUWgf1a1iVCqcgPrTuSz0mg40cEhQ9d+nq4kbEV1CmLzcSKEuB3z38q43ePxyIOt2+3J1x1myTZkNSPzsMtiVr2AxtLx43Igt/hSAB3uNFFjGACFkomZRxnW6jyrAIVxO24VTzphFlYza/TMPx6a3rJr4ggib3IjGrK/Oxawbb/5Docn2BVhg70KwOHnVdcioaMPfYd2UrZQ3anhE/pXHCKmkVQHlrkLfrMg04WkIfXVqAjFCq454jAo+gikI/Z9eQbWOPKIANKTi18dvO7ROnsJx6uNn4STJmFez/smwXpF86nLN90KUZ//+tF/0qoh3pb5MRelwfVZGFLjDt8cTLwd/vC/F4kL9pOnf5z5e6b7rxoG9pWutbmkeQ3JUn7Cq99uhP1xud7rASMsEZJ+j+7xSsFcL3pejxbosZtty//a27PZTE1JM95g+VMv0jeLu40Ztpr0EAGxgI+iMg2U6eN4YqEHbJHFsBHwVOJET/3H6RtLZrEfFY8TKwRFcfCkIzYWybaabb4hUza7xqVPAjHW3F0zsr7TZzH+TNMjdwSZfLUmAJGAtLR9UcAPIMS02deQnzc9q2Yr5uZ8zvxD2AUGy5Z6hsYIe8pubU90wjPvM4mJtfIm0N9YXuvR6C2psnet5Kqxs8xOrgQorh64XYibg4wN5Zer/p9YPC9SE98W6TC43QYkkoAayLui7bwaNbBTRORHUXBeeUAuwUQUHoF2jOUJJxyRMrgPE5FRDvYo7NaBjtR/oXwg1t+JLmZ+vzcU4NTYJWLSzKKKom5W48myNRnzSQBexOeuzRr/puqxCWIAUxtbhwqOCJAJ0kgLEEW1NH/jYdBfTIqNXkHtAuNjt+nTHU5BT4Wg9Nh6znRpQwspw3NlG0i53bO4vdc2pUT8hhx+7D/fdxCtNu+UT94m5QVYKVJ82/U6ssNlia4Jqu5oheSBfqT2B6vkDIlsKKLekZhNe7T/2tyXu78ri3lXZTPZl+/qxV/h9GOAJbIdHsa0+olrRkyGkirgM0hYXYH76Y/pNqUP+Nabt8Lz9R94psaYOqCpjArLZifX5VP2WxMIBFrqz8HTTGu2m3ue6U6vLCVsWlHG4LVhXClYRg+0UFNWkj/iSlaOGNg8rqoNId92t1pJo7J1gpaachJgUUsFykUJJE4lFiAwEjIIbDgkuWbED65TTh8bu+Ih3ErfT3MEZudq6gKIACCUsS600iklvFo98ngpZfN7nCQ4emXAE/tVZKr21M3bQgrcCj15RluzsWkY+wSfpnaj9bAAvh8aRQnTEG1BPIqyeaMZ23lfjtHPrpzCWZnCvxg8WpzdsIMyJEmUm2L+R4J4lOAAusXnZ+38r2GH0kSdVmJlVE4+rtTzzdbEoaAdZp5ZqFaepxEQZHRVUNKK4jXaOBWmqyaIz4blYog7WzMhtjTJJWSi6StFvEHdfvsHWRdeDGxrracQK4RHgiTTj43pv+poNv/+OEyDiCtHo+PXq+ktGic61CP9/dptCWRYezyVzto5PXBJPLmOmzyCMAN1hweb13mM6y2m5eGpa5pfQ/qExu8aFUgPMU2KsyYKkkbc0vwSrt5RCYGcOjYn0uY4TOxSF6gAiUisqXAs7JlCm4Bq21Xgy+IpkU2pV2XbMsu/iJnOro7OmGotHFjMXt5Kb4/2eXTY5Qw6QkXdGSzcoqA6OT/ZBXb+y8xuLg1yfVgPLacRGS2/CdfFUjZPyezoPrOAhNuRAGMICYnNhNdlWu+uYKfocMwU3hDXD+J39LcI7q/7yHShIwqxHuUbHjOcbND7uS75EEYq1E1SMuvK4rWwzDwQ8DBdPT8vV07uyuYmF4eVksuI05aQt/3a8J8J8Xm/juVG7eFYlocDfNpwGOuGr8o7BsjfrC1D0czCaYE1PjeMPfTJLiMAJFiCVMeVr35o70J/QcrHS5YcY5a7cPLkqF+tJee30xPYAI4bma195Uu/jav+PWXaqHj/0Qz9Uft/v+33lLW95i3Xyn/7Tf9oN6GT055u/+ZvznHe84x2D7//qX/2rH2lXrgdHqIqcn8VB37qNON6iuDLy++6z/5HD+jcyxHTZ9ar7IVVe41LQtrPvB+4ZLOnJXK0bdFp27cAxlkOrhASx3Ai8DoyvPgid5UO47+C62yXzA2JJ01UIrgt368Fq8hjULsld2Y8aPxq+xPSAcB/h4jcSTI8zmVsxQREjltRInEiFVWV40M2wOz+sRd2orj2ybWVtqMK4J0blr4jj1dydXf40JTt6NvAECHSbbp6kLA6iJCXfouRK4UjqIrh2/ScT5DPRWOZexkVbWPqggoAuPcwntI3qvtEfrdekXW2Fh/c3+6Bov95yoZRQJUFh+IeOPjZNATUW+04rcOi+9WeMNbOclqvb03J5DzWi9mV7HHBzYYdI/XrEETKdSmmO+PGhCWHDH5lmmsybTqa8zi2o/dqRuEYSewVY+tSEUr6y6JTqI7wX2odg4o/fj8MGt9++3FpeldOTq7K/vS17JCsTRCUJ+eaB+WhYUmdnZ+UzPuMzyld8xVeUL/7iLx58/8ILLzR/f9/3fV/5yq/8yvIlX/Ilzeff+I3fWL7qq74q/75169Yvz9XXfB7/qgWjdWWoUXZuF30jVas+5FJ5rA62wZ3GshMrIvl4rvElUXDiQTBpVbvun50CsBdiGqPSjUMs0bY0vG40MoEhkGBFGT8exxfovX2ZmbYWDBBRTI7gB/xLQdj0yf4RAT3S79yI8C8Wv1lMXckDgiWorB+IyTVGkgio/rYuRCW+E4M+cHt0F6pwamJ7ol57W/6LxXyCBLdRSAhsMIFlDG1NqYoxAJC/dgXdaD/F7ce5OKDMqonatklvxCLq47i5/ASBGO4c+8hiDj0gqAJakADMZGvFSPC9DKaBWU/e0OD7fm6rhd54/ltLiOdoXDQttxBQo6weOmb8hfOTczDm6vrm1PKh1rf2Zb90GqKMRcXN2zeZD1D6WJR+7Y8YAkreo9q++Wl6CrA+p2W/hZCKUjYb5GpBudXENA6N5+fVPvm9jG7J3J9+8jTesSX4TnbleLYr2+W0TG5syv54Unbn0yR3prBimY9fcSH1hV/4hfZz6Hj++eebv7/ne76nfO7nfm5517ve1XwOodSfe+i4urqyHx7379+P3wjSf0R+Un2jw58xN51MVJ/XnRXGvxsAw9jO2n8UMyXpSajBxqoO7r38rG+XlE0WCQXZpGj3WMBzL6W5txo/Nb8kg+Ts16GcIBUENidboUk2a3TJSFwjh8kmXZS/sG6DVdxUuso+bs0kfL3NLRqMmwEOalyA1yRAIqwm4wHLDYUbYHXzWzFGRc6JUGJCYRbUE63TeeXYm1q/KQUA3R9EKKXgqjud0jgN9AiBKZtrBbyeL67K7P66vvcURDyxHZ8GOapTz8AGwpCQ36u0qt811h4FNeY9rZWwtqrVEhD5cOkN3OrCXWcbYryvtMTWKGu+L7vJLNxku1KuvD5VWi06LznH+Qwk4CUDhypSkZLhZT46SqdsdogaHDxDc/9urPVrKcfh/XfXM68DsAhxqPM3lbK5uS9b1IgyK4qugtbCUYVpeLMijpYqLAiQaBQvf7E2HHDLFbGujJkCaFvEo/h4cMWtzIFY9qA5yqXfsk4Qqk6qJlpXnAbL2abMgfoDRH26LSdH6/Ls0w/Kg9XNcjWdlumLnqvBgoq77UfJ3feRHC+++GL55//8n5sl1R9w7z399NPlN/7G32iuwM3mMGj+m77pm8qdO3fy521ve5t/kVrhIzqiWqVqWKoypGvM34os40FTh+8zIgRVAzXmAKn3lO2PmDf2J5FDEadq6v2Eq5J/s2R477Lo1nz+3mj5fmJdLt0Fuv/EKaz8OrQi2lIcWryOhdWqplrbD9KJ2mQKpwp5VwFVKYqIxDoAK+8fSZgq8hzR7giLT25A5nZFfhesR/uBS/NyXxbn+NmVxdmuLB7uyuLBtizv82dTlq+v/ee1+Hl15T+v+M9R/Ds7XzubPN+1BvfZ/96KyeeTkTsw74ZmolwrsSqlO8o4UTNNcudu5o7/KkrNWJyR7regT8o4B4SOKEeDKw+1J99luZim5PuB61Twj1rtrXIwtq401aG3shIocWNiFtQWJTiiJpOXu1DvSh2/0Sfc06RvuzjYyqzbHhfyH1m3obBZjAk/0Z6V0OG1hn70mJUJP/4brrxDKnhebx52E3Nh+bmgurm8Kssb6zK5tTES3e3RuBv+Vw048R3f8R1mMfVuwT/1p/5U+U2/6TeVp556qvzwD/9w+fqv/3pzE/7Nv/k3R9vB91/3dV/XWFImqHSTDq17cKi2OeauoHXCjcHcgrR4HkHTa993sQoDP3AyuFZs/IK6KdBKaUANIwKq6ZegtOwZwreSLoNqpTn1jJQcH4xHnWLmbBLIddJE9TGY6LNNa8vaP6B1EtlFwYQZBk3NtE5uZrWce9J0dgKGAojxpl2X55SCrufTE4GjcHO6hxr6pDg/raYxy0T7JnEyo2vaeEzON8jKh1c3SZzD8hESU2RhwN4LgLmyAOojYlCcN9X3nBp/loPoY1wsrTEw37q/r9HaB4UYbaipVIy8dxyIY/E9eNS+fR+y7giFR6KvveOjWa2IS5Miq7wyjjliyVBBtfYC8BB5UIdjT2phqkXbAoyS65LpK3R+QEmyc1pLNT0E4c7enEzLxbOTcnWnlPUdcNshJ6otgcHhSUVAdNBcbxP87evUPBn6Xojei9OZq8TvdoyHh4sPLBO7DRd6KIygS8L7RsFRPMeRt2lgXYJ6zGJVbUkswMjXslhUlrX375bTbXn65Kxc3Z2X1aKU1fmsFJT0uPCk3kcaF/9nCKl/+A//YfnSL/3ScnwMlsF6qMD59E//9LJcLssf/+N/3CymoyOA6NsDn419bnamYu3VfZebtn0h6kTbRE6SdIl4KXbP9dhJsuHI5O7LvWujA3dd525po6Nt1FTdPXpNI6g4BvEH7jebxWN3QWvdZOOXZqGZJhoLrBywnuIzO68/xH1IlgRx+owPkSRMZl/SrBFkHv378m/zPESRyTBz82JgVp8BAA5jsYCQyfGOvpuFWAWN9yFABGTYCAvD4ilgcQBPWbr3wprNfBxJNObneE9r9xp4/tNM5gD7QWtI8usQhCOaU7X7fAcSO2vMH32fvf7bvaRUoDrXl1q9HN/mnlGYcdAgLacQ1PYcsZGi7hDrQi1hJoerVnOZ0qrphZ4rBTnnuKv2LuRrQwAjR5WL/o/EZxsmiRGBxj4gF2p1KwTU05VVolpR3uFE6qUrja8g7meP7HlQ+Uqy6ma6G6qecW1ir2bmq/kTihykQBQctVgVMIMcB/rOE/pe2SUM1AGWicXaXH2L6bYcT/HvxgthlknZ7qfleLEuN47W5QqgEQNduIuxoTj71RBS//bf/tvy7ne/u/yTf/JPHnnuZ33WZ5m77xd/8RfLJ33SJ33kN+vnYiYwim1cOvu4h9KoptqY9xE4PXCrBpHXL/gs5S6f0a2hmrtYIU1f+mdUdwpNA3XvGCtEL+i6Qw2vVi2Lz2PiR12d7JYOADeK+Mjg3tp2bD4pc3qXC9dZZYyRoRO3TyOQAmQg5KcZ60rLLJ4hGkzm9PgbQza72jnTOISVKibc/Ddb1/SRqwQBBesNXIiMdzDmcRUJt/jJAY02tCZZk0LgQbt9CClTKsyaEu1W52A+a52PNrZRBLCZKjk/RqxgGdeDmkO3DGp/+HsfAwtNOl3S7HdOEBl3dbXXG7rlFOmgHb5icKjMtKEQaqWR+lfXHgfGIYc6n19vOrROE5kqnwNxujkt5epeKZtbO3fzBZrP+6vKqggoAUfU5esd5TcN7+9jHi5kxq9yqLnXGTPl06xSifXldCDjRTvVCJI4mm+MCR2/Q0AdzTZhUPt98TcEVVkikXxa9utaDPVXVUj9g3/wD8pnfuZnGhLwUcdP/dRPGfnhc88995HdxExW8eGH5qkBWNfeHMZ7MEA6aFcFWOdKVKCFaL+5ONPKCuSMfSQw91lQhIsAa8hk+3ukNUgUgMxifZ753F1FAE/QVQGQg1GgjDn65XFlg/IChq1XMIGCjVuwkmoOEGz2fdX41ZVCxvK95l/ZBtC6g+jKSzLQjI9I/lduFIDSku6mcrkhSJ/vgoIV7ArGZWfoE/pJ6pivN67NrxCEmpTJYm5/OyddtWAmV+sygdCBi4lIODJ34x0YXDosJ1pFMYgTs55kYDOHJ/pDi0usJetDzEMvcR88jznsI/O6eeeitaXpKblRtIJz/ms0Xngi1dSWsWNSrXsR4v3HGKoQzoRoWiiIY6AWVVbd7T0ivaIZOVj6XMrFx/e8lxI1jYS7zsSvaz2tdn4jhn4CJsLCNlDP0kvUnL15Wlb39mX97MaLTGq5FhH+tH7sEbUYJS2k3tjdx3VqxB6wnnJ7giVG3QTCAa6+dS1IaO/DLLy4DkogQBUEcQWKmPdy68nnKgQQdjIAJSCE4NoDZx/vDYE1CUvqdLmyzz90ui5rdOgMhVH3ZXdSPjpC6uHDh+U973lP/v3e977XhAziS29/+9szZvRd3/Vd5W/8jb8xuP5HfuRHyo/92I8Z4g/xKvz9tV/7teUP/+E/XO7du/eRdSYmMgupcT01Pvnc2CM+lO4g0aBx9JqvtF9Nn+7e9Y9qTus1nA12aldcSK2o3m2TKzPOZf8GjOmd2yU3Q99UfJN0Jm0XFrzhNYcKTkLxmdWvi8TcXnVTsTG1Crit5ZgCJ57FXWp1HFKQ6LBDuMbqMKGSgjoes64c30jAyJDJoLWUPZnATWgwf8eEFJSW2E3ZaqDGGoSVxvn695DvgMEvEsZxk+xAC7rhGwqzHW8Sr2adFczprgBnlmTQfCtaM9oen4nCWr9qplWnXRCVrl816r1/0XDb8TSdz0TqZT+k4TEhISXqK42T9DM378o0PmrtaH91rl/jUVBPiDKKUBjlMPKSdFG13oPNCUAS07K6DWqwUA7H7kvh0ltWqmQIKFEPH2JZ6xzMuAyCIz0Tgbyr07RHJslh7yzCBDwi0bhH9flW4+eBuw8WFAQUXH3414UTlw8E264spxvzSCBv6nJdyuVsboTTj3t8xELqJ37iJ0zA9PGlL/uyLyvf/u3fbr//43/8j+2B/9Af+kOD6xFbwvd/6S/9JYOVv/Od7zQhpXGqxz5oMWHRwzWz2UhSoWhhtoFGnCn3dvH706BtKnt4vEDJL6tM4GfMW5IFqHEqUip1n1ULqEPs8Zl6QRnd9UB6bPcRizKtPM4zzR4/EefYAyIOV4P1PZwHOjd6wZsLM1wAW1Uf5VeeF2NtFF+I00DgZKXTsH6MF07dkIzdhDBZb4fxFQWkSGG+JtZINoYFLMhZwO/DUooEWDsP82IKIRaxJuPEE4EeZdDtXcOtZ9dMrN0c/+xD9D3Lokf/EllISH60LSwHGr+B1ZvPyXeaaQiwtsMaBuJ1xEr1awOOna42zmmxRnTOUZBQuKdlq+33E0JunMpIxAfVjce1ZO2intRsEB/MtlN3q3HXJE4xKzRSMyI+mEnMvF8URUT1gwRq9MoXrWx9AsLmUyGQLyP2yN9zDKWUB/OlGnYJlgpBmsy9icehnt16DKoz4KpXgtDzsKT6cU7hR7t2Iu+cLnK6AMNdt69CahcWj8d+pmWHnCh4PeJnVEDZ+FDJ81LzKGNvScSSTIxzTQjFNbCgbixW5Xi2NgGFuFTdP5EzaVnqZTrZlMVkV565/bDc3+/K+WsnRjr9GPy43ta+EZ8fGwcsNUDRP+8dX11m85Mgjh1xm4SbxALV63Wg7LrHpbaam2CwNeSU6YVUCAb64E24cWEJIlBiFObuaz4TN138DOpH9UAKi0VIrIN9wYaH+6NP/G7prr/98dKQU05OOqZtV6ukKbtN41GrkRr7QbUmnFFa2C+S7igsD2ywhlCTPuuh8SPdvHRhZpfDGiLLAvuKZ7acGf9xgzYEI/nvsLkcofhTtHQFKvD4A0pNzBkDMDD2xDikbvZpWcVnaN8EFlxV4XLmANoGy3iVmCQqpBijwtxUJnwv7tNaPJk7hWdZBqOIs5lnTIjvZWw1N/Mt+tJ4Drp4jihVdQ5og3q/mON8tp4eiYeVtagPZXfFe+vLa/AOpFMKJYJDMXQzNsZE7fcBWeu6RLgBhVapeTpdYxkbZayUoB538cGCurw3K2dvLebm296GwkNNTjpDKwR5SMEkkUIquzAwdcvAUAzAAn/nOZnwG/8aK8R2WjabmaH6tpdzR/CtncLITmI1Xk72fbBPgCLpZFvmy60R2c7nu7wvLCb+e3O5KqeLq3J7eVkWE7ekmjxCuhyDpeJ8uyyvnJ2WX3jp2bL70FHZfnhT/us3/j/K66+/Xm7fvl2eTO6+JmCrn3cCQV01PFdnBxeorU133zQulPGbt39SkIwlqR5yc/C7vsleC25cTHJhegq652S7BneWTT0+bzTgYJlomMdlIfL3tFDYhsF9wxrS2An/XiMxlTBq3RC7o4HY87P41wzV2JSC6snPj35wk45FweTGDKjroRapup/4u7yEZFswYduBIDRuaB4+MmHrSxTBNqoCpurrQAq8p+xfpC5kXLVVfozFnMCJRFEKUnHMEkorpldUOoBF7wJnV9V11wurRNWF5q/koaoMUZG0MY9eDxSydogq2U/Xj/y41qAaHeZG0WuFT3ofCRDio+tz93PDL8jim0jUXZ9OzYoCmwTyoTzGo+K47107KbgMfTvSq+K59vo442YQQSTevcpAYQm8tKCYHxWKd4sAFYCOVc4GRByL0EFBzTCEu8/qSU39x/Kj0ioMBnbWqgqOQfx7Ol+Vy+W8HN+8Kpf352UNi/Mxjo9tIRWbY7pfaLan4CKiSjYZ27wl1fmQMGoEF60druMOKdXEH8LFp9qY3U83CRGa+GaAYlP/dFhQTeXcEauIbio+I1Bq2PxeDxaD0vmzzZ0Rmj5+p3VIV5Npq5JETBdabSm1SpYuGN8phmOcZU/wH7q5zI8hgojuoJlbgmYN5cY9cigpKl2BIdh2RwA/cJ4oasNuUOeMcvTRNQh3JAWtWWyzcC9zLsk7ywKcTnw7QbvmsiNSrxOUnAlWK0zeZ2+NN39TUFVljPtL7r790SSBX3PeIw8XjHTJaaHJtDyztEznekN1YHl/dmWW0pESEaqIdfPJLCq21whPniD3U+CUvaeap9ewadglwYqh62fE+qe1uL45L5sb03L2/NTqQl09sy+7ZcTqCDOn+ywvdAGnS9+9NDEPIn7kFlHl48ORFtKIXuwnxLURLzTCV9AWbT03CqAJrZ+VKbxUdsJzQuEPxXZ/MSu7OSyjsPpC+QabBOpF3ZhXNx8+u242GX5zsi+b3aycLNbl4+++Wv7b5bSco4TvEy+k4r2ny4KQaQovIevM8uh0FSTTdHzYaHV1yHvdtNaT6tTkFCZaoa6HxXat8VZ9vEXarD8jgobnNH2KhRhuL4M7U1DnIo6+JeKsCkbGpFxg8bkIwmgXrglXat699p1jPYRX030TA9qOR6fxu1WjrjBx+2hf8l+1eiTWwLnQWDqxOUk/HOI90jDbUGhZ5tf5HzbHemVDtH63Mlp0gvXmoOCtbPwm8MLtGkiYdjodtNrkQRS2ntb9iPJzKCYav2i5iiwBP1gP0n7MKxdMMe66McbYNBRHYplWS7F2xB5frLacXtFuUmqF5dDmOvQDdcAC1TNYm2w5K+tbk7K67XWhwKKAsujMgRoY5uxs80xy1xBguQwbC4p2clg/2XhrnyXohENJ5gixnroODccg8qRSKQd4CcINyb75WtxiQtLugkUPDSjh3zpkor41vwujdhOHq8825Xa5LHdPz8vu9rS8rzzpQkqsjgyMxucpoLBRw5LRjdE0dRUodCspkGHshi18tukK7xdxECsWQwHVBP/bBZib8qCYXfj6peS1XxI48ZiR6V7UttOKjHjcZl32sKy40du9OoFIwASC1WaFEMpOTV2sAfY/93xxSTZjFYIu+xab7LYTbKocqNA268TjTlVA9WMofcnNNxZ3xOKYpGuuOxGWleG7s2zTWvax8jySYCWnZYPPu/dlYBAmd3I+KMN+L/1cTZX31ykrmmfHOULADNxOVETT16PNN3/IO6E6PQIn17iLTM+U6bT+1DMhcaHsZzKrSx9s7KY+XOh3Wp0SzySUPOOh0i+6s9lnWMbqKgzL3lxiUdbdLo8k8KiCGFYVN85+fLoxVEvFijaCKHZWLp+elsunkKwLJomAcddODK2wlP3dPfms9mhVyNhnqZNOkivPViLfQQqxus0wEXi7meXffRQgr7Lv0rSKdwClrQIovN7UtJSl7wE+BXcGNQeqD2AIWFHsA3gCXQdxYeb9BJjDhRbiWIuyLSezdVnfnZWjyaT8THnChRRcL7YRNQmDIc/p2knh4ELI5rRtPJ6smdaUbL65mfdWjW5wuskO4kHhZuSEnx7y6cchgfGBVZIukvDpN5tYtJn3jf/wX0zw+SyAjrwmLKKEzHfP1Gj1sglwwyVXivr7MxeoUyPZtlqU+pPvpQoWF3zh1tHxCOFve001p/I+DXw47xsuIuRQXa3MdXdQyObfMS5JqeQQd1OCCJuN95vCRd87Ncd8jxy/7dAiS8Rpdac07UGAke+RQtLQcxDaC2HFl76qx6AHJJgQiHHWsY3xGtSEsu4riIOCpC/21G3umjvF0/aawBt1qpQNX18okaHiunMBFMrlmHxJRbOzTPkOBjK7sxZF4FFA0sqFBbW6M7f40/mbUV13bzWh9kc1BjWaiygWt3cl3OO0jhuGF6JPRj2NReytTJItCjM3Jpj6u90r41EhPO2fXmLF+9/XpF5yWKKcRyopkbx7jMTcOdx8mzKbYg3szYLCvIJV5cu8jp++HtQB5vS6uzgvi6NH0M49CUIqN8uew89NkIFm78p6xJeoCStMOE9NaVXb1UMtAHXrRJcalahpp3OFZXOhwUfb/mc/mQTE0BXPy8ZTfZT+haZu97C4ElcMAQrqPuwXd/9Z15/G6hNNV5+39yyIdlqfSwdOylQ0GyYFXdWCB4KJ90urTWKWRPwFPJrcbLlJiwurbhiML7gyYxtL9kPGuD+a7w9Y5b2GG5V3k+gmn4uVZznGXrajVZRG1X99WQdu2h18F2k5tcaW9rV5vkPtCHtJXpcxKGfdTuGS61bmJ4Up72Ox/G5A+8dsXN+HnzNHW05vnjX6btyRKLdxihyoSbm6G4zmx2CSgOIU8SchVa7917/rO0gwXb7vxzgmrbVWhwuCCDqQ8PTRMguWf5sv+mz9FLEUTqeqavpvAIpKvWSw8gBLeOn4OFUSKGsv63rmM/q08N+PZtuymx0mFX9ihBQ0Og9qi0ZvX0wa5FS6TqIa6UQF1cAqwv89WzqtCt2IyOuHj41PkOwFPcxXN6pw02T/SmWesDb9ZbqbRYWeXB/95QLKhU83Idx6jFsECMJyf6CtYlMA7HmzKXug7vprzYKqbKzOJCG5RtlHeaZGIYiuakxmbPPWDaf9pf2709ztI8Y0dBnADaLav6puFCi2SGsRwaRgNsCHWLCm+cc4mAAXa47rTYWD5tB0mvioJTwYD7datQpvc41uJix9ohYo3JdG6tpdm4qZ998dMJ0y0XgIuvHWPCvmRenmj3/02fv70mXIRnW+qOlgbUeydbzfpl+Ne5duSEd2Zu5UbzXpocqKPJv9GiVxXFHpFEyNU2JZ3ZxbPagH74Crb1/Wd4MsFlbHQuKT6rbjXOm6o7oCXXPpouynSP/7vnoQ6FE0AcX4E4ljbexorbZWlD9fvHDXHkIZDOAO89EjljVFdaTdtGzWM3PvUTjBxYd/sUtudzNz49Up5L/ByiIjOg+wT+AOQYSVLsEnWkg5Mqy3/dvKpgPNvdeCbeKPbRQjG22cU40l0Uw7/3jeK7/XL9THrhq89FWFHa1Ape9RQdO4ziTuBDeVoeZCc202IyYCthq5xaOaTTcuIju8rrZm5Q3HqRXYB6yzZlg6TW4ikOso+mcFs8X6GhgqaiHp+Cs9D9cqhVSCO/hvNw/G+jv2CHy+BOz0UfQeSDPyrnMTby/Lc5WKy+a/ICSbvqRpPtLR8Y8VBJJzgvB4VSyuU0Dy3r5Rxlacgf+GHzWs1SGyWlCWapUxxkQZPrLmBgZM83yh5jRjrqZj1IRaTK0uFGiOru5Ny+rOpKxvox6UuPd6clSi8lRpkyGrr0P2oUlPRTZuIU4ozFQvDIGYhybq8jvTneXm/KH3YHQOx+lmHXobcPvZmCD3aj8tm/20rPcgOnDLyKZlCB/vRm2Ydlid9l4s8SM5PraFlMUpOpdA5Oa0sG3V6oBa8SJrbp3EUI86gnXnaDXdDKBnuyHw2g4eaE+sBObE2OY6rcnEYwzrAnHO2UQhxfZjM04IdnR/D8sAtD8MvnMD6i3QDFj3FkCnGQ82305jVk22d/f0VkP+ruczyB0fJffi1NkGVKhn97p4HXO/uLlngFu+5wbf9FmVDm6K3cJq3JXxO98nufeCmb6+X9xaoPxm9cY7Z79ynLq5y+cLiqekfoLQJgVPQqg7S6k/1EWuz9Vc1wF+mOfUC6kxIVxlVLNh+yYdlrE6usb6SHdvtJ9vLgsliSWlKT/X7X/dfXJVN5Y4hJPz8F3dnpWLN5Vy+XQpW5RBVwE1SvDrLC1VALd3a25PUr0UQrLH5FcEVtR8OB/CNv5l39FiwucRO03SWBs39XLIv2PWTGxFCNubK/FqZonLKJi42U3LejctV9uF1YtCEu+0AOXnZeNlCqTVFED/iv6zIXw8K+pjX0gx8z61PsZdKKCCeiiPeh5cB8pArVxow0OD+yOL+bojVQhNzmSzIdi4kA1s4TEHlnBI6PGgS0TP8flmw02EAoPAi3ABpiUVrAk1fid943i2jJbD51Z3Cc/DoVRCufi6cdTxtUfoEI56DccyQAem3WOcACLo3YiiMZIs1hgwKBwS1i7JxHGu+9dbF6IF7PFnFucDp2C1SNt+HkAuUjAQsZfd7QRr5GSlhWsUQJJPArcurEsoWiF8ze1n81gUlrFjMH8PvFOONT+j9k3hIIS9g/eY54Y7VcYmbPWBByHRhAZO2bWlOMKd6TocGSpwcpT/6JhSUvipHO37Gn9bm7aHsKKuIwEvnpmV1a1JuXxuXzanYUGFi6+di+zLuAU0GJvG0ql99iHmfKMg8msmanwT1Uvhg3/nkTIBQaaWk7Q/UOZ6SHy+Cnf72bjPYBUFKG01Lbv1rKw283K5WWT5kGNEFXBemZZpKOSuP0diPWqFFcTEg3cyfmOpMC15/+QKqcbfXFFmZkWl3dpPTjn/kJZ56F7iGTh8tBpRzpK0EuKcbEfUTfaJcYamRo/4kWvjbZ9VIHBDZ1CUJxAswX1iCh8/I7m0qtTi6ARA86gHBBS/64ZjVBPXgy4dKbsxvLms7EEfupLmtBaZgkDrIUh30yKVPqtLJV8NWaoPCtnu+cdcv71l1I9Xc6ruTPI+Da5dn803t7DYXB0fb6/vw6Ghve6ZulYmj3OPzoWe1sHAhOqsYvuq5tmkNcdGqHglf6T0im7s+KgSA7eP3FwS8HIry4LifLe8oi5+UGrDuPhUQEUrtu2ODEa1jPgs8g71s5RA1eDvh3LPcxnHIhCi5+GjZHYdLtC8A/ut7eShz61ir/NIZsVeUCvtnA9wM5mV1dah6NvpzmmPYBsFE0w6DTK3q9nlsuS95lU9uUIKh+VCxSZkbj7LZus0+k4w0e3HSazabloeXTCYrjZrI5geezeW/U5BgnaE/JWwXELjWYcor1f3Sn3TLkgC7MG+2PcaOxpOROUc9I022OKFiaEcIckj8l7CmqImaz9kWhhz76T23yG9VAkYHMJxN7b5cYwwfTm+mfip8bYQ/PFsydcn1ocdtKrJ40ergAPLNpsKzJGmEEXbBs+ufWkHPBOH7Ru6/Ox2+L3Oo7yS1pxaXcHr58UCCZnvVF5a2LzOSrHHGTkvpM/ZD30/suHr+8rdm6kTXWwotPuBtja2FnSMuJZkrC0Xxx5PLfi2bYPgC6krKas8JUO4I3Pgu/70idki7LyQJqo9o9T7rFzdBXpvWi6ec/Te7hRpKgfiNyEUrCZTrxzwmfyFhFWslpTOKXZGc6G6x9gXAUJEKgSRewm7bxXGtCbTq8CxCEU150c3djmRmG8G4uhJ2W6mZbeal3WwUOjrwrPC7Ye/4PKrBQ/tk7SkNnvP38JshbsPeVVPvpBKgSEmsgqjZm13Qiod5o84dMH37qtGK+zOz4q+sjAs4dhLORt67JA1p9phlIJoFDb7Q4LlTR+zI42LydwBLNeRsaa4LtBOdjsQYNLVN0CfdTfpN6tUALpzGhcJVT1xj/Ex4G5T5CLXs27SXLCqXQ9iKQGYMVb4rpaYqnWNP0StJVFAUogIS4kKuJwOXV90Y6fWnGMen2vieKel+3UhiBQV2isJzbtnuyPn6guxa8esFxljaTKfq3m16ql4jLWkLnketPTjPs67SPOGn8sYRf6Uc+c5kMYSmk1QyPvrhrL/zDfwSRN/urw3Kau7yIcKiiMrVCjTI9uLvePx9te4IU2L6y6iUtq5FIu49lQ68JpAOfbCrX8fyVih6ycHaHi+fRIchD7GlR2jCDegASl2U6NO2iFeTPsoxslU8bjOWf7irhBmjzd6H+NCKt16CXdRG3k47iqsHnlIIJ0TQLVTa2okeJ91rbqy8PmZvyATVOZXP9QXcWWYO4ekt1VjdaOgdw3K9SmkanvOU1YRgSm0aPXFBu9lNsABtisTxEH6xc/xTpWqV//Yi0oCWrVbYX5Q68TiLDJWKhipWDgsL+IH8l1qi+HiM+FULezmHeT4Unjw5Y2/1np/cbVpeoLMqxr/oMaqzy5Cq7QMEiqsG8HG8YpbpELRvI+wQFUBGbN+s+0RyyDHZPzj+k6790xL/pDrkoeAdepnIWjscTWmF/dRAWVlUAJxBmbtOZ9x6srNoTwlkgWbG7l7OEy5Y/DvTcvFM1ND8CEHygASZDLX9hL/Im7wA3qqf6fxobB+emWkHBBKzdhPWii5XM24WLr1+v1I2mkEFe/dKwN6wO0XZWhI2OGqBJcahdTMrCcA0f1/+6Au9O99+nj7ZGtnraknX0hxo+w2Gf+uz0wfX0Tp8tNNJPKpHJkVbdPFN8q67kwIddMVslTTdhQ9F1nzzQYlfWTSKFFnEGbWjKPzdNO2K8MlZOeTEDbdI12AW3nwmvjR0AKyTRikoIikorZSuK+8HtM1Ql4tDW7oY3tib4XZuEs/DeUIUADhfXJuBNAnZpEKlZUKKHEDo86YtaUCQzkWOV6DzV2VDbKYBMBCy5/I/DOhnK643lXXgUDGDm2TltTg+/6+LRBh1B2Jc/pyLPm+4sN+vaTXoXtPbENdq7p++v5yjHVeyHdawDBDoGbsxcbmPqK4z9bnxA5sM14uw4QdjLKV5EyOjK/SPa1PwcE3K+fPzbzc+9O7sl+E26yIe41IvskY1DzeRb929p0ie+igsGB+YSOcOKdLK+xy7KM7Kfh03rCJTsja+cKAfiBUkEc8+2QJNLTnmSImNd3vy9K4+zxfCgm+vjywXnm7YbvOTOEktR/J8TEupHptYcy33e0Kgx2zFjN0k5a/i1qrE6hZyPxeXEQZN1EewH4CidaojXWaj398nUBgm/0mopuh/J7oqDomTu0vJRZGBLsh422htJrtmHDTbo26gQ4JuLAY7VrDvypEWtsxaZYlCbwPggrsLR5N5qaV23Sy1UAHveP7HHMttifK+xtq7Aa6zQ1Ynketp3bwhpZ7f59OEJk7Ny3EwYNK11pLYDSexPb1u7Qau/vrXB2BXueGqM8kDVW4el2/mWvTr73or1lFpLAMBgl/v9FPZWhnX2MKWx2oG9OyujUt69NSNjfwmcC0de2E27tCzvuxPKAAN33ukH2D04eCrrHA9jGM3dg2U7hfv/0c0rtxzauSo+ey4UkUPVwA9ep9gSCaQRG0U8IqiqTdukQmZRvvwlsf8mp4janpG0BIqeChv7vxTXNz6QP8sojpCkrrZ8xF1y3ocNslfLx3taWgkj7k/TU+onDeeq1PvPhQA9qKMrN/oxyE3rcXdpyIljsVVhE/C3dpu2l2gXQcCvNnHLCBrvN1BBM4NwrCt/X7fLb62UCOWQZhWIdUAPKncuxV63HEKuwZDHqrQN2M/bvjhhnv0Sr/EhRB12cPEEhFBZB3cS8afLwrrmfvPMZfFRzro8SfaG1DXU5rWDgcmzEM5hOdm3zuEbmRyDJlwu+PQwJZx240VjXiRkpFqZvv5k6ubjl9Llo+WVIePwEV93QTd+F5AU7mTbky4MUSoz9E71mhwkk5f27uLOa3JwYxB6KvZUmPLgPVZp9XSyqjCmO7f2MJ5UO0AodrWM/jd2zW5njkf21HYlHpUKm1sNJzFjlO9n2Wfxkq2Y2g6i0qdmW+t6KHi6N12a7nZXM1LVeruY3B6dGqeQwjkDXwhN9ivXPABEhoVUgRgr7azw0h+AYQUnGwFAdQfWPrKidC/N0ZV401pLEkLhylD+otIYWENxqjqmS6ccbXyqI95p6ge1G/OBgc7pBvjX/f27bKtiRKHdtA9iMB7q4NueGwLlM+1wFtMxjbR9/N4A8dw5HNMoPLlFiSaCpd9Fei1Wv7jV3bD6FKQcrPESejYLL8KCn0mGMvKm3Os8460UdQt1uzK3LjZ1vdT6Plq4LGcvYs/TFtl3bP7J8Csbr6BkZQatMjm3Fz6PO3H2c7CZDo3J18JtPMg8vvUBxP2swliF9WgeqkMIt3Yp7SuCe49xDDQuwJMSgwSGxOStke7eE1rMi49IbU/YKWQD5jb9k1/x4QXDmtDwh9FVKhQJjQgRtz01uvtpLa+2Y7Idg4h9UZocpK/7udK/FZU5BcQHkZeQdUgdOYdaoAlphPwUKxMwYK9HeN7N+4obn+JP7UTi0HXWweEzrxRAgpDwaKVp8j0m5KNYmyzzmKTzWWJBu/I4k67TfblVuJoEvFSDcD1eSV+HVMSFEL7De3AR2LCtYab2J5bOenY6l1qTjbyANZebopcidohqnXujpXmFoiLprqOCmkf/RFDl/bte5Byij8xzZmDeBTSjFhO6ilykjbIee4SSkqd08Wdfab8cLcGJmMLWOgfU70VXffRhBJIjMfjq6mBmwgraQFKzRMnN8W8Bb6JJ00el+2msKyE/J85qZf3RiOntc8bDwH540qRow14Xsk1wPdaUXM4pQxImU5dvsyhTbepCnwkX0NmLAykli492Zlc2NieVBA8JmLL5BrHIfk88vux9+6iet3OaaH5m8+7MHhGcSccP4WazeSxnmvHuTT9cX3Gr6LgJCPgD/6+1erKqxwCCcg+2ZeMt5ADrOdGWbb9azskCu1nZYtLNMpWChmtvXgXx4ATNDdB/ZzHRz8BsGm5z/BQiq032BnMNgo60RRlYhJ1mjx6UqLNmx/1yA8YZ8k6RyZYGP+eubKNDKsg8cSjJEbHtw0G98MbcGxTyIUufGFhTdw8QlXn40Dg/rGMOHntswMXNStK876sz3wrEZoMHMBh88sZhTtKTQ72krh21QUzv98hEfn7ms+k/6rFcsxVsDEYAOKPgajQ8Y0eqGs56tAMHcM64dJReHmHrSIeytO0anyHtWSkoO0UBCQtMD5XOlilc8M4ELLWtwqj5Wa0j+zfj64/gBYQn+fdvMP1qnNM63x1rlE+6OZRt07ivL1/qsrGdvFrOwWyH8C7xwtKefj4/K2tsQLn9aZuhytPSLzXMEbCiH5vbP62nHqPQLxOa22cO15Am18tmvh+C6rpA8BGslanKkPhKAyxVRAFOxjCjRRJKWrxvcJawrgCANJgJFrVy4NeFHK1WZuiD68MuPymzqXnxVBtFvWYohX27kLJasnVmmjVigF8uQLKTm4yImGUw0+3D6DQ17YWPVPP6fdfK89Uksd0XToOxhYYVLYrna2Tmo11cfcL30cqndX6nmN2X8N0qxfeCoAKDzdrzc6XvnRYLPt3k1/yAL3HLO+/2OfaV8VPdYvvAMboLSRm18fyxLNdaiwCOikyRylIBpRpHs3Hj+jRTd4ARR2pMDxzxOtNrDMxELLnLJ4BKOraZ+pQaqNzbGxse61+YPyJa4jaIfJ1+TGaeZ3Nyc53imTaNn3cVd/pn1ToNDjT8iDQsxpG4IKlpO+0mxCkdm8v7GqiWDi5o8UkkcJ+0MWZ/899VfGlSQfysFKpR2PgHbrdX6utMV7hPVnH2sC78grUgFbX2lYUWwjrHT8sYXLbzorq+m+zIP5fTOdOk+AMZxHqZN9tZoQpxLZ+AaiRVINi6ULEgLcLVg7ek03zotwVmP12E8X3GNbzA2hUIjvTLNu4lKy6WmQnPDoZGtne2HNaZ9p3ZlV0Fk/TV/DzWexJ1hWnVYe+U+O8JP4iX2ugI44EgYv7rCIpSW7w4DpuxvX5n11/R57n2oxqVA6JHi1r/xXLbv+mfTaPqeInI/pkoWWWhkcmmKLWZZekp/7shhZyViQkfyuceOJgG2seel/59Jrnl9jNwMhVd+PCzUdW3kpOZf0RWm/rkE4ct7l391mH5a8pw1QyFTLyYtNj8SrtDw8rf8sTBk3CguMxQlxH6uge3NmVpP9QEgdQWgZcl2SnTvyB24Z9ByHQ6Zlgee4k2hWYOuHBFEqKb01RU9EaZgkzHrSPpXuFYngGggpteYYH57pHKgNJpQ+FeD4XcbHzpOE7dlsZ0Sz6/Xc4lOr7awcLzZlMZtaSXlU3gXxrFUsiA6vdnOLYeFcHFbqw1JLyhtASGWQMyDG/aLu3QJ2dMCC3BAFHMFJqNRDuTDT9Br2Zex3HFp2XeMM4jaSi1ttnuSmWQdLH0U16XaheEVXukJ6q6adHYNS2mOEZCMbUxXWXBxcdJ2CkOOg2YzSl9TeY9PK9jtLw1yXMweB5LOXFqHYoQ3d+gi3bW+JcUxSMHXjkyzqMf52SggyZePOSwSh16MLU3GRce5Rif1BLkrO87yn3EsbMM9i8KcZajXmtBLUyu0HAmrse1UYckzbYRo9uuE0wAmnlrn6OjohFbSDvnQCkJ/RgoJgAjgCTN2LyiLh1hO+99gTf3ewxHD4sq+ZkxVCdXJgbDj/1Srt41Zj4xJtDyymPmG36palEfxdc9wCxwxdF7ZeCdl0Awjy3DdDUGmsGyGTiEnxcKi4/w0hBQG0WaPkBgATYJrw+1v5eCMpqPPQuP72XubDdZ29cf5BkKHm1BtESHULbD+kS8rFxqMLsKo2bT7o5preLyCght53j9vReuktOTuHAi4KMg4ElD6D9FW5+7QfvZ2u11uGvmxAanWN3k82W3UR5Xd9PGhE69buqGanY0QLNC3SVkBlH1OARAyGGq3lF4eQ0hhYBBeMTLYOgo9xQ78zGXHJieKgMUXrn8QJ1QJKC2tkE+9jdIN3xs1NXKaD16LKTDf+Oa76zvaHaae0nE3bmWtc2N1zNYraI6RUnFcZjoJNJL6rrqk6J/kIrXurFQAqoJKhgq69OQTTrGzh4jue2L8QRv4Tbj4KqJkzKdTxDLbxVDTEwqMwGhu9yL1rkDaSR1/Ho71XfkYBYmXxxpgm4ueQq27y6N8Zr+I88GmrzBM6ru7O448/4sQsJ5/qHqPyuRaf7xhnIk2S0755HvqkrLdWNN7a8mq+bkXB6tq+IYSUMkKPWk1y9JtGAy3P/7Qup9yQYmNkG8okYZNAXHxqyfXWVbprfNOoevhI3/vcLO2bIsG4wdtG3MW29N79WFAUs78UDFlnyL6tGyCvYyDcNKPO6guEnVlx1pcoV0+INPvalwvX8bc/h/kTCWxJFhDpT78Bs2YTgQRmSQTzBfvau9pyLLtD+9e76WwOzauio/XFtF+5wY9YCk1FW1pwPl57rTrdKD3dOx3ptxYY5LgnVJv3OKSw8D58RppAOrcowKJvDZgnx6eur8Y9PGq5c+Ov856QdKuUG/djMjqsJoCCtpGYC0FlDBQmjMKCgoDC5yGcXEAFoq/f+FPfVZfuCGpcFQW45zg0bI9LS73yI5UYGuGEfC+1qFT33tc2lRUsu9Odr2xa5q5scqWGXH/Gz5cs6w4x9xp7da4AyaexKdsC516MdL2alXlY6tPJvCxnbiX5HJxY7al8zWXiBLRGRLst0zeEkDLhpMmIjQnSeGNaFQ3HCD3QQLuUaGpu1N1E7S0VFVy8vk/27dboQEBZt8KyS4sAH/d96GIqh8ABffO5EfHfDhnX9GtUzZeOysmpvYcgN9qigO82Wn8O3vB+Y8ZhH3NrhFpv0eqmLhafukN6hYX3G4u5XDemea9+WD6y9zE4txFCMq97C8Su667VualdjaB/83E/doP+i9ehn7PlMdzdMTamzGRZDZkHY4dq9/kTipElpIcwQqVYuPkMGBGgCDsHsOgqjJgvRcFEVomDj8MNf4QEYqyv1OFMIMRG3DOSu0AIdxuTdOnasxhUJ6AO3G6SAm78c7WIcrkpjosCjrG4nBNtfLrR15vHrX/BokLpjj2g6CHEtrNZQVoXZ5lbV6wMEMTA46P+5AopcrLVD2RmEIWmC1zdLaGVN260QKaly083BC35kT5reZu0ksxyIPNCTISOc69af2NHB8ZQWh/uu5ilWbRv1sF3xb2lVmFTRbjfYGV8ol0D9fYlSfL6mIQxxhkrIy8hy9Dbn9AUhe+PAryxDrV4pQ6FxJFQwoLVYXuLRftG91i67jpoOMq59JYI7zWWg5ZTRsZXXV/mXpQSJHrt4wipsXvQOsm6SL311IEfjBxYlY0R1pB8X3wJ1/SHqQtS6dcg4+mi7QSqKk9q7aXrtVsrA4VIhayAVKIfLpggkAArj/gTLScIqBRGYTUtEH8KF1/EovyzcPNJ3/POA0VG9vreddcMqpQcyc3e0W5Z5sOGwT0nSM6lgLJmQ5cdzJReWdtXATVl7lTIuf71pQDKfUqEKPpGkuvULUOwivPGpxfce0L6HMIGX85m27JDWfnNtKxWc8udcib0UrazSZkBoBX0R9kWBJnVnpq8gWiRtJCdzra0MnSBy3U0ZxHv0HhIMxmltDjvxXPEXdacn8JEboh/iPjTGAbYm6NvmdE+oo3WHJ+6gdimpFaL5VjUTcCDlh3go8lX0k1FPpNkZU7GHMtRV098RoWg2UTDFcJy9g3qLuorpQIhLrTc6MJv0aP6HqXd8r1Gew2pbIxPtSLruKYwVFev/s22Ff48FkvrUXCNgBsRjjwGbrBuEx+trtfFBgfCY2TAeK6yqPT3Qy5czJHKqdeBWPRGar3SHW7KhCJge0tRxqexAipCdQc6KgilLEhY3XqO5hMQhP5Igq5NXXHFjdILyjA1o6z6yKFrRhKB3TIKBQ3fMW1AXHoqQAaeg+6YsC+SO0XhqX0lNF6nq17PP1xgtVLZBFeCon09++vE2mgFVW3L54lZU1Y02sv67vbbeN3+YIhBWc0Ha9PZKNYTlKN/IyTzmoCi/dot5t5F0WxSCm6wL+NfqiDdNfw939Sg8ZHz5VcEjfHWaFFx0RIFZs1dN0vjO7MklOV8vJ+pgWeQ83Df5CZiUYlGToFkm3/fJ1Ym1e91nPFvFKezv8OKYdnt3Jc7C0qFXdO/g51vrq2JxFGfavxJ5VE67b7/PQWbKBMN0i4OWioSq2nHcGzYVWjqruf39eRd6UP/IJ1wqmeNKCJ5vwPD2WjtNW+rlh/RcR5ZH/lDQS8AjkYodmCiPvcpEHt7Q+vNPP5EgIQJJbr/REgLFZK5lag3ESZ+aPr0W0A7iFVQjYxZo1eO5TAx1gbrqdNBBpBxxrXGjl1ck1V5RQ+S9sjPrttZ6ssSq8p4XFiATUAryQ9cQFUgmVtRDcGRvVcIKbeKNltP6PUlQJYW349S6aEVtZsaK8WTL6TGtMN+oQ3iD8HxZy4gEHj2QIEKbbW8q9BwG03bThWNO4PMUpl1JoFvVgG2zP9OE1fk3pgbUDVRWhVNCRHdHERYJp2LuIFSq1ckmATYbZ52lij7kEHvPDPq+0h+1Vh8Jl1EQQWVbksmpnWWao5jZxkYpBr0K/UGycmH8zcbZ1lYs1T8uIJBC6vR7PO+8sw5lzrWD54XbtbGaurBMv3BNgYCizvICFluXielLsa+F9dp03ykOniBQLKDM04YjdDFt8R2QPdeAE82nVDp7908RmcxEoXJmk62Z4kEUF2EH5lQmpXtjYWBIvYQTLCeuJfSHUihZIIofg+ryr4XV18CJaTvLS1Y+3ktHSLPShmrOsvIeLRYgGo1+Y8IhRTK4Xbr9bG0vEr+m/Es0WnSRZ3xsbDe5DP224W5p6bYMwSwgpZnDz4Deg8PbhVLzKvRvW4wUsx3ZXfpOVOb1axMwO+XU4Es6XH+bJvoPgdhPELhjONxiyPa8U3f9E3lt/yW31Ju3bpVnnvuufJFX/RF5d3vfndzzuXlZfmTf/JPlqeffrrcvHmzfMmXfEl58cUXm3N+6Zd+qfye3/N7yo0bN6ydP/Nn/kzZIL70yzkGe87+I28gX2SnUdsajTiTbsh9ntOYILPrVYAIx+AgbhDa88DN1LXfP7AKk34T0/6p1RIlyhN1lSqXPp8kkcIa3OkPV48O2qPGVwQu41A9V2JjwXXPqYKgybKPTdVg/QTS1EB0xqBUexVtuOljjlH3nps4mvRZWfNH4kDdy9AX0b6/fP4hoGd8PqjFL8/StDX+ThxJJnRdtRONNZONH7I+mvWSnW1/YpzSGpT+ebxpmoJpdzQv2+N5xp7SrRfXNgm/afXXn6wmI3+PWYz+/J01Iz+Dz5tnjq21a9uE0FZ++HcIqAEb+sg0aMZUHnPCa7o+Nv2UcxVgkT+CXszr4nO9dfYr14676IzJPH43m0o9PxZ1mZS9FUnled6iM6DrQAUnem9a/koJqR/8wR80AfSjP/qj5fu///vLer0un//5n1/Ozs7ynK/92q8t3/u931u+67u+y87/wAc+UL74i784v99utyagVqtV+eEf/uHyHd/xHeXbv/3by1/8i3+x/LKOfnNpvhPuvnS9TA5YKlPjAjRIbVoVhLt7bpMLrIh70K9+3cYgsSr/qSwFqdmzb4RZW+BaS2T0grOzXvrNgb4I24y0GmoHhecGLodrbSKQNltPDmWlW1a7xeXkCcwxGHk3avFYIcNpmcxn8jMPYMRM4m0avzsAjGBMMvgPC9jKiaqkKqlj3wufxgIZEe5xH1jE9sN3xXczQ+E9EVLs08H5KUK4GZtw46rATl+NnwOmEZuTjaJ0eIybn35uqoKlHUwlQPuqk1PXTf9ZrCECLuTHLLi0RGLjMq7NWdlDMN1Ylu3No7K5fVTWd5ZlfWthCbl2nc3HcBVFAm7dcNlmWFDi2quuv+huWDIaH2o29W6T7u/RjrUy5bv1BCLY6WZSpuv6AwYJZ5GolQc4LUcPvnb5fWLCxPvd/zTtiKDk785kIX93ciEFKSB5zKUadKjTx+13EVgGoQeB36TsVw6kqN/T7ec3tel5zTZx6JjsR+snPN7xoQ99yCwhCKPf/tt/e3n99dfLs88+W77zO7+z/IE/8AfsnJ//+Z8vn/Ipn1J+5Ed+pPzW3/pby/d93/eV3/t7f68Jrze96U12zrd+67eWP/fn/py1t1wuH3nf+/fvlzt37pTfee//XuaTpWjfGouiS4saNl126k7KYRBtPjYDrmduirEJs+pqZVSXekv2wWRACkqLw9yHvC5caNYv1cYHG4qXjre/rRaUbDSpTYYLJC0QuZ4WT7J1h9AadRVhzjHXqRvD+LOZXVkht1pboxWRe0GT49LFKtLNIXElWpbq4uS7UiaFqytrd29lNUaejWMz0jfP8ekpl6QvRCdCuLImFwQUFRsjTA0hrjHAdLNesyTz+xhcBYiod4HClpWY+3Z7JUWPEKrG1BH5U1qlNs9nrLPfEXiOPhvfRSPHuvvGmPk4iTUUaNTtsVfXJZLQXXaVvZwCp+rhJEut6D0k7dLNZ649Airgdupzo6LL6XJTKHq8gpwiY9ZYCMoGCg60HemMxowDjYc1lt5+8FljoVHobEJA9YKG00TzoOTfHpauoJJMZs7PwAi/t3/L0c5ceNPFtkxnAaDJCIC7Ka3pKNmxQzzqEpW7/QGmR1ur5DvD9SCnne3KyXJdlvNNOZ5vLKF3DsLaya5szlflf/vC/6fJjdu3b5dfEUuqP9A4jqeeesr+/cmf/Emzrj7v8z4vz/nkT/7k8va3v92EFA78+2mf9mkpoHB8wRd8gQmen/u5nxu9z9XVlX2vP/EqWjfFwFUx9recKO6isa9bbXVkY+Ah2nqjpWdbtdHOkm/bKIc040DISUC4b6C6U/rNq7lJaz2N6SfR31EcR78h6XhftxHXk1oLVoVqJuuGtTW24dlP52IV6ypRlf1jNQwQQ19OvU7HRC3Wrr1Dm7juMP0YPero52HTfieM+nd9nYDKZ4gYYlgztSinHFAewm1alat4wLE51XsQTAFsORG58ZpbD2AIIPTMtefuPftZToPCyAVa3UAZy2otqtJZSvVH60gdcIulMIn0iWCbaM7jq1CLazfi0kNo26ylsKa217j8DgivRmcqB2JR+2oRjbohu3MpzA561CgUo5ZWCk4z6IP93Mp0oJaUQCWI+IOlZNZSjKPFq3ydGIgC1hQEWJyDN4gk3lqpl5V5Jx9d4MRutyt/+k//6fLbfttvK7/hN/wG++yDH/ygWUJ3795tzoVAwnc8RwUUv+d3h2Jh3/AN3zDyjVoV8tlAuxupJcTFx03IShvQn6AbVN24vLCiuuf4otr6QqxLxXjPHm3bl9wQ419aZv0mpK7G2VwAAmOsELSO6sbo5Tk64EPjzhohk6U10YxNdBoHn73RyvlQI0JW+pbn0WK4Nl+Hzz1zq0XbIaS5FyoQUOaKHAEl9H0bsz7YPseBY92UcQolxSxBL4NhYAQh3s0Kuirnsn25Z291Hxo7ZTnRPkd81MiG+3heKkWqIHHsduJKjnfAytQ4E5aojYG4v3l/s375IEPhSyaIXvBlvCkq44INwi2qajWJqTR+2LIMDZ5Ju2YR0PoPSwrWUw+gKGHtEBBBAGbXth5Wj2siSbalg4zneIVQoPEu9+it9gYWb7s09ySpGsApsR+6+QoRfiKc7DlqncH8XKv08t+a2OxWlFuewQyD7xaYG15DinWkZrCs0hkVQoXsFGwYwgfXmkByiqSyRvn44A7Fn9uZtXdjsUor6nEF1C9LSCE29bM/+7Pl3/27f1c+2sfXf/3Xl6/7uq/Lv2FJve1tb2tdJc3M4yKV3UIIqvNoLCZRSUKA1HynuLAzoduGeM7IRtlYHSIY81LNJ6l1oVxjHInPND6QA2p+Lha1XroxaH6X/utnTV/VCo1pqkJA3UFNl0QAsCOZ9zNmJVQBkm4pKwc+EvNprKs+K5L3GSmhQuWFw6ACK+9/neBtFSNHg4Y62ozh4OJ6j8ExYrHkFAzUHa1mtYqbXLIRt2YqEzLPE2VX51YGw8csMlVIGgBDHLT2o7y7NQXYuEHJZ+aew+fg0UtNPgSaUvnkY6tA5IeJ5gu3Hr0KytpNS6oz3LVdtTBUJ80D1lF8mf2Sek3ZnsZ7uBby2eSm7RvOG3PeNfWh5H2ncNqPxMdizGipDm9Q/24E5+C9VRYO/2GOHAEOnA7Bb0hlM9NNoGiHoIVQC4h82Xq1BChTXtZjavlRQPUtAqEbtck/OkLqq7/6q8s/+2f/rPzQD/1Q+biP+7j8/PnnnzdAxGuvvdZYU0D34Tue8+///b9v2iP6j+f0x9HRkf0MDloMTX7OyKzj31L8bXD0wfScLN2GZH+LxhqbE0gVuUk7b5ps7qZ1x4SMfy1eFdB0dpta7h4xD+27ZP77Z5GvYNqexgl0k4lWlVduIM+Gm2lTaiS/V3AIF2Y3JkrS2glqAkz47MOYIMdJrErb8ERgw3q4WpfJal37xPs2LioVdDmy7XukpRv3SitUYecBUmhCto2FLePDsbG4WQfJ7w/dFVXB0nay25NxKzK+yy3cNucuf06szOwHYmdWuC/MhLy257HsBZWkH/B8nR9xf2MjXzqYhFaTJeGa9VPf9wByrfetUzw3TfuYSL/OzZdxFRFaGafJ91bbtiHU+NGI0tkLn+zPWB/5t+zzjRXXH7qkMo9LadekiKEg8/r7UDilusLhlbk0BJCMUFtMQriYoKo9rsY5oeeeNOfWVBDrUljia7O6dqVczVBYytcNmD7mO7OkcBlKdUzDkkJbBmt/jOMjiknhxhBQ3/3d311+4Ad+oLzzne9svv/Mz/zMslgsyr/+1/86PwNEHZDzz/7sz7a/8e/P/MzPlJdeeinPAVIQgbNP/dRP/Ui6M9wkqtgf/5H4jh3UzNVNFK4UQ+DxHgo1byyacOcZS4MLK9ABNcjAMTYDc/ONM5tnMN426MjF2ffxArt5vSiezbjNxiDR7LtZIxoz60ENnYDns/exitwABelH5N+IRRbEKF1/ejeW9EPzj+L5zL2IPB4IcAo56xPvSzeKvFN9ZxnvGgEcJApOxjPbCQaOHnXZtxPcbIlw0/fXj/PB+Sxu1QNzLuuPNQS59oW8j+6d5Y+/J8snG3M5coy6Ks72DBj/xdwUKORT7Y4XZXt6VDa3gMo7Lpuby7I5XZTtCWDkwamHZFyzoA48q/7E0DeIvAEzQ2VQ1/hLk/M0tgk341tjRaAXyp91KdNVKbNV/L6Wz6EXjaDjBv3nYYCHNke2PwZxIwgngCQYz+Lr2dV+j8kYjSc1FhMO9eCP9ZtHl5boQw1mCGeHIFqPXzImpQ9mtxVBZ6jGjYMrthvn97vcLMrFelkero+8vPzko2BJwcUH5N73fM/3WK4UY0hA2p2cnNi/X/mVX2muOYApIHi+5mu+xgQTkH04AFmHMPojf+SPlL/21/6atfEX/sJfsLZHraXHOsL2lX3Njt4W7tkoeu2a1/QWRmpcoqnzS/qsKSgpAHtrpPe9N1o8Z4i0rZrtdZo5teqBBanamfSjFwyqpfWTRu9t54omT+tVtfVD/XvUHj3S9yahkpYCN9FGSCqMf+iGa96ZPG9adX1H+hhSGi59vGf83PyOpzJptlEsDh3dOCqzdrMhdtadKCG1qTEPAN9xxBY74Vldy/LuOS/TNTexOFMhn95cCw8K2IF6ychTNkKlP2FyeDrSvWX/MqlVodiyIfdLv3GZCRCisYr6fkkmAy2T646mGx0Gp7lW7tno2WPEsWUonPhsg6RjMQx7UEaaW/Hp5LGmYbORdiHmjqyYzh5eYvEoh6ebNQ3GdCOinZXZ1EvPP3JA/0eE1Ld8y7fYv5/zOZ/TfP5t3/Zt5cu//Mvt97/1t/5WmU6nlsQLVB6Qe3//7//9PHc2m5mr8E/8iT9hwuv09LR82Zd9WfnGb/zG8hEf9K/3VlQevaVA5oQ+yaA7DObLzUaD9XEwGbUDUbSJqdPQ8jtBpX1vtPiRIL66W3LSStnw2DQGbYsV12x8fYxpMJZ9CQcRoNygU3AJy/shAZXj0jFzRFPpVhsIqa5fZqj6WO8BqDBXKeDm68xfy4fSInWNgkD0WYw3LLIQrgBdZCkQ9ovcf7Ag+H5S3vVWoY+VwdDzOR/TekrhKQATwvhTeyUxbjvGDVOJbQpd+Y2B21bJfRd1/sUzGeNECJxEAgrBK7ubMHFSFMV9Mj7E4e/ja/2r5ePr5iw6hZJTpJu9swgaQcaamlyyeZPQYSWHKP+etASsjTVHko/+Xv2zNM8sXTZIfIs2HBuEtArFgurjdL2bdOAylZhZEsz2wpoW2Vyux2fIkwoclBHQRq0obwMgCrkP73FwLBzK7qVIIsEXrBRgpEBtqf20rDazcoX1d1l+5YXU46RUHR8fl7/39/6e/Rw6Pv7jP778i3/xL8ov/whhkAMV1kmzQGTx60+v9WoTGXPgdWbLtpo0BaTct/7eac8pgDrXDze8dEdeB4ion0k0wj/WTV4nb6+p5u8HrI3mMTi2VCM7YALVtRyfkV0on7ntb/dQ7XdiYVrLweiuwAQTVPZK4Pvm7nLYyqxjEq5WtsvT+sTtHMcR12A/B7L7vZKhAnzkffabjGzOdYfqFIp+07I4Xzef6pfSxxEFgSS/xpM3MxcfLCSWYs9yCzEvXTD5xYqq45hU7b4CPEZdymNHr7CnORBfB4dgr7k38RaNyajRSCGk0GxNiJVr0hIQvWFoJY/0v5/eI8nEg2fUe43ozL1VpQeFnuKnmmNsPvTzrRNwzgAbkHGyTMT8IJTcP5vm75WPr99SXEjZ8yHJN6wpuA9tOU+n5Qrl59eL8uRz9yVpaxxZwZQABU60TuttFiyro4rVoGzdBwWIxHX06ONBGu9iO2xIN7fUaoUnz/bkrv1mY5R79tbCIetmbLPUDbYfX96Iibq8yO41LmAGB/s2xsag1knTR0c9ZW6/VGOdLFgKmxDtfpF046F95ge0GDlevbs1hetIe81zyrxhqRJa7Ka59uM90k6jDBGJemC8mrEL1TiplJLGui1nInyQvpEj9hGFFfE3Ykz4OYrk2pjr9mRaf4jghGCCsPY49lpEUATDqEeHa1DaadqT4eAzmGbenCggCQoDWgr6qjlEknxbhVSnBNhWUiHW6gLM/YRdUgvwkIBSlGE/BP10k/Yb1+NUx6wVbjE07bh1bfHaphJxl2tpQinc9xZv4rtWHJmdU4VUNYN5grgHJxGT4thASKGM/Mah6FAs8fv26g1S9LAdSZlNPMYIUMe0Im4U8rKVAdhr4zxmEJx94OaXG6LGrGqto9RIodFmG9xMHwNs0EOreR6ZHZjIyWuJilRtm5sphWLnaqxuOxl73k/9ATn+HWqtaVPHXlYbhaK66UIRAXIsz+YCsFOwqUr8zmorjdx3jLkid6POmrV7EP0mXIONFdwJVaIM+xgkBZb0ozmyzQ6Zp+9L34WWjEE8jmzTzdFZUXx2bR/MHIZwXJSdIfGiJEanGNnmdo0DhcPHP9qE20NrpdZrG4Q90nqqNyVUfYpyNAbmxVqJ7ygQhbtZ0wjHhN504+U0eneh66SoieS1xXJ59MKElhn/FMEB1otRK7nvjz4r3ZCdg6O5Zhek1fZ+JCm5H98Rlgy2Qbly7UGBZczmsb4ogAiYiAZdR5I0DvbHcrH85abbL9rw7RhgjGnZrt8QpTpkIeZnVTutXG3dRY0FJNZVM9o0ZSuiqB7XCapYeTlRZGNqNrgacM7Ny0AB4iYRi63JR9LnV+21+c43upZAtt7fSljk+HXXjj0bN9xRt1pvsfQuEPXFjCzgtCokvqHJobK5D9blmJWjz9QjLNU6bJSaPn7Ztz8+Lg19FGNJ+d7VWhqzauXZTRiIsnUwzic7J2lqUjhQ1e5u0Qio+E8gUgfvnzlO3RAPB76Ob25+0oUcex3L7hHyz1TIqwU9KhhpAUEwhwXA9kyo0VUs91ASXcKmG9CEzJN8TGOPqeOYU3/ksCaoW4l1NNb9AThDGpk87tgdnEPyGYelypPrm2mkrZ/saQrxsQmWKmxklGO7kzFWCzAs14GAw5zdTB2u/sQLKS62RuMEIWiObMO7x4GFuen7SM0fMquJJm+6TFh0L26XWqY6rdkVWfhqceUm1DFJBM0RfzeBBUuKMPHIo0qXESHe7PcgliXCMKDHFsjvj3SbUQjy+m5n61ktcnzleUdfCTfq2qcUOAPLQNpRAZJxkDpe5p4yd9Nwt0gLie2Qoio2Lq+M3PX5kGtSrSGOje4AuZnG0UPBuWvoO0lLVXaL3nKn61JJfHVsmt8pXDrQhc1XsXgJ2mnmafxH2pmuNp7rB2sKsSm44WQIOE14f9XKPT5Sd/i0gGRDtk2/s0LZ/eyWhT8DsNFt5C6A6rlTaOSAhqNdtfrASccpNGYpscyLUg3xOeR+7HMiM3vrRPQEc+v1QAS2lf1vr1MlzmOtvmymQuDfnL/vEI21m6NWXro8y//AAddcWEi2jkQR4nh4H6tCNIml59umPxTcsAa6WE/L9srZ0TcrkFVPyvR8VubnkzJ9WN4IQmpk87CxE6LPsdP5LxFM6rdX7R8BZGWlHtxP2x6L64gFRfRY/J3JdYk4RG5F1Fg6COlme93m32vr6i5Socp+0yoJYMSolabt5T0Fet4/n/5+SICNubqazzsBpfxyunmxhMih+4TgMlcYFYvUtDvLS4WORsoby5p9656VfRcXl37n5doJQpD8tmyz/t4EwQfG1xBJ2O9AjaGTEqQdI7/U/04L2/KpUIdraoqAzXcmlMrQ5PMMNvT+nR56I/KcvVWm45wCpBtTFQKmyAWpKxF6bFush1YhaGRD29exjV6/FyGh5ybH4Mgzjy6DkXuo1ddKH3mOIg6iEIzWviL6+vt8BBJqsIrCY+LuT7Kd9/3r9hT+yx8gFdeTMrsoZXYV82Y6s5yzGQQUgLnnbwQh1W96NlhSr4kbUn9Z1Jisgyul4kWQVF493YzzRsO+DLCacZDvjjk+facJ+FAh0/SXKKk4T62hXkjZIt7VTcj45ajRiwYkiz7rbaobVDc4vcdYNLyxjK5R4bRt/t7EsziZ6QplEUDAu33221V8vrFD2q5J1MGr54PZxtdS8Lbaf/7dCIQDVjQFlY6DuCsztpmMJyPo0Xg6d83J6s+FT0usY//on33ElV1lXW0jN+stSpwgNjW1AodGMNrcU+51Xa5QbqaP3h0pqHIqDZYE37cMuwkEFm2clOlubwzcFogP4WluvHZIB/1TwTTIxeP0Hrt2P87m0BdTHP19TIjxVfRLqRdY+2EbxlYeKfJWt72SkFz/jka61t5U7ytWk7hVmyPolHIah1sP1piVLVlNyvzhpMxQtgSE/lgO632ZQzjhtFV5AwgpCBYNlI9ZNMo8QLRYr4X3QqEpaKc5TCr86oZoRJ+NZq6NtX0ay0L3z3alaN3H/hk6pJeJWRWyWNQ2Z7rnCzdmdcukZKodJNO0FkHUPowIkqqpi2DQ7/r3oRbHyJjrde7yCVZQc/kdQDnKmBj5r91G7tPQLHUmgM4TxoNSuelcTmkBUUCMKCPdvDMBG6wTVETNZQlrBdROWjGZZMTa5/hxmQV/flhi6db0fvD7oZWqSgHzrmJcw4IygUIQDf57tTY+NQAoGouhE8DpYpMNUbw/g9gL2fvre67oOM9ZqnMBwilZJLKN8DQgWB+lOOxjAymAdgm5OcPnz9et8HLt99h6FUHl6FJZt9xKaEGRNHZMKHTJw73waNyRCk7p6Jj2ek2JPGxYJtGfZj8ZE3AUXHyIrLulYy7xpwYDFYJKn1FvSH33Elb4pEyvJmV2CeaOSVk8RD9LWZzBxeeXoawKm7CKz6sDiuYTJaR0hqm2yxeWG25olGMggtE4xTiNETfy8Q2BvzCjkP3TzbvejxNg/LHEF6AabffodV6yDIMIjV6ADI7OOkz6pV54dMJ3YDWMCRtZII862JaeH/03izdjVWOXCh8gn11diM1zs+KaLjgRqmZJcwGOPFA/lukyHbFoYvNHPhcphojgNPcJkofN4ldBMny+fLamXll7m3E3c9eIxqY0PsbrWNwSgsuERLVOrmu3T1IdG7ZBX8amjS7BzrpszA0qCU3hvzp+aUX1c0/1ozFQw4i1kjEg8mTKPVJ+jlkuqt91QsM+0gaYRJxfdsJ5bBz3wnzebX9N23yGfhw6ZWGwfHuof05RZZ2JApJxLwgnxJpmly6kIJxgLc1W+zK/ECSlJExbRAaC6skXUu2GkZudWRNeumFQ44lHVIjN6rqPug3Ot6b31yQ3S8ygjE0uCYjL5uIAAcLVg+1bteDshyzW+HeA3BoIqBFGhx4MoH3vWTRCEx61sPp+xWC5x68i3lLYZJsjQr7xZ8R9sGGyVLXmw7W9rhat9qfn4jsAl6fb1K7OzVxvIH8wHoeNi6AOZSBne0G26oJKLJCFC4ApBNV6E+zXI1ZmM/60qDoaGn12TerthJ7P8U0joJJGinIIsVDcwwAU0xRSDSjhMRSOx6RiE9dgq9slqo+ba3yZ1hbd4nwt/aaum/MIUUxjXcn5/e+5marwinQ0dUA0Fpm2obgT7Zt6joVpIstwCJt6wxox6ZofsbQyn+1AxMEep1EEu9CHjsPIRJvsYC25lQROw/nZpMyu9sZ1aNbTBiAJtYLhsoWgCuYWtHFBN6nvJ5v1I/IAnwgh1SfGNgs0/NT2a5Td6HKmNFE0/x1oxeWwkMhrxjZ9+W7UcutU4vzxDSI1ykNa8kELic9+INFY3XLsmy2UEQFEF6UmpOoY5AJsV3tCg0XFtkVywCJKwd5ZKdXN1glgJVjlZ2Nl0nVFqjYuXbMlqtB/FfCD8ZB5FnRJVViFEBHQx8Aa4fudw703K/uNM2cMx7Cbk/HvUAiwFpG4Ifs511tg3PzUW2BK3Q6Ff8pktimTNQAU0C/iObghs4lwg+VmPnYc2qhr11PAeJJtRdd2zdTDYpW91REgCoyrKip9A2I8NnfoLTC9rk+cPSSUDnZ4RCjwX3FpDtRFufdEx07eQw9ZV+E79kqy74MvWkFlFlIUaqTFCvciBBDJd+G+m1/ugnx3n+48CC+dx973UCrC22OPYPluUq/tiRZSA3fOdITlgf+wPpQgxfbDTaihmcnbdNp/bAIHK/XyHP2eLha517XPpEJgTDjq32ox+BdiQXBXqoF8teBMQ9USJpqwm+6DESHVQK87TWxUuIZVN/YcOibNJlvjbMx5MwSaWaRRVYlCa1BTqbMwGWhI7EKFcGcci886JrDZwUBV0pVnFpNt5PFsVkxOC1nGM8Qr8RIWLhTBC0hLP4ECvatX+zEypPX55FyNHw2eI6xGjlO8b1hXEyT4zrAhba3MhtFPWtylCqp8lfFcaSlqf0f270MgCcw/j0N53KmNiVAYVQg7S3LQMuBmb793wnBEph8+OquM1JxJQSQsEhrPykfq9SLqULI8q7I1wleo16qgKiMHPe56A33F/TaRylXbRvbJrMRw4xnzu6PvDC6+KWXxoJT5BQTT3hOht/syg3AyYVa5RDW/LRW0vGfNf7NrAqL+BhFS+mbFJWVuHfG/22chvQM9NiiVMdZ+b32oRt4ABuJ7BSjwRzX1JtcpzuXL5ayLsg+pF/Za/cAy44oRQUQNhhv/SK6QU+MoyKK2p7Egn4jRVyEazc2qp/4ZGcPsR9Pv4WGTG1YKhZE2hb8BOgCxLOteKTiigS3zfh2SrlEexMXZw9v7TT/G0HnuZlbIj0wYSrJaBW08DxWCRvvlXJm2eVm9S7q/v/VPwCJ6jo4p2+ZrylImshbSpQoBH2cCig7rDhbVHPV+JmUHxvO8T4feo3sJn5lrls9cv2/0MuoFpCTKgRnZ1CKGjD+tUKIVUOwt03aDb1xdY0u769chqytZHeSdqZC255CUyCy0qGVGDllbvIcK497SpAWlQq0E5iXulVZYjp+0RwHZCL3ugUMgmeUEy+gCsaVSlg/cOjIhtaPLzl15+HegZEjH853yffKzeN+TDVC59f4QeE++kOpnap8w2ZzjGnOzWY5odvlFbg7qRhq5Rr9Te1usgsYNIe6b1vwebk75vSKgxvqrDvj0ZygutT+f//a1Afw/WdOK5RnULmdzYbU60aS43kaGsunnoUM3Yh1nXewR3K/oxaBkiWe2vKjeZZPj03UmFY5+hwjXRKOui3uUgjFcfbUEugqmuMGIDmVjlkqS320ylgfVW/mDXjZK6nAeDhSsYEofOxorMhCIAFEgDtHHRLoucYj4RxWcQ+vEPg5NOl17+n0vgOiGylIgjPuFoFA+um5QBn09oI+qpZP6nhRVtO6NUA01U4vbDh0YwynVjkX/EvvPuvEqY39THnRpd9RzB++J4AUAFgKwYxZs1NOanzngYfkA1lIIEHIeWlKuW1F5K041fBT2QMbF9DkooJTQ18YokMRPvJDi5kMXzSghZ7iZbMOdBVpHXXidULPTcP7MyzQQ1KDME33cgp+VsQ0tBBXbJmQ++eaIzOtiNrg3NykWqSMLhcYceuukYypgCQpCtN0XLJtiMmFEE4RN27OHcF9t6vjuh245i0/08y3AH43mbe9nLE4Tg8M2M1mXSMn4DM+PsYgXxWKT9T0qEpAqplibzWbeKRYxfmSqYCaRjZ/2NWJOZkGFFeVa9AjQIPrVB/dRvdZaXRnESTgWu7mscy7nnbx3UXhUeDZzD8XljC3eXkC1UJrUinh2spRcrso0rPHtSeCsmaek3mAW94uXP7qRk4VCN9pgVdFxqRVq68X+GRSBgLFb6Ysguc3y7C28/bEAHrqZ6qYqJd+TTcLKlEhOVDe97E9Jf9Pk4vreOuZ1Clj9/hpBxcOGhxacHHatkssQ4CEnIq7EQo8s+rh8PQAP8PJe7co03HfJCxjvZXOMPYHX+bs0HkWmt6DyciqV1YIyASeuXCp86V14lCfryRBSh33xQ4uKGxhhy92i0OtQCiLjJ2xLXELNJkCLRFSisYTWfiPOa7E5AJKs54o1lPV+RBD2h9X2cVRW71LMfJ3GJSVWmWk7PaGr/ySAI/NiWGmW19aVSiuhvhdxaY2+O91s2deOTkjKsNjmKcAXFyIHlAW6gTmGer+BmtmaxvZX1L+adNWcXZP3v60kOghZubmagO+EFFtM7TfQioup5TxONvMyCWu2ul55sShGj7eW2zhm/i0I14HKPmJlmotnV/YbgCg8wddsSyoCNibd0PFVxvA2uBmJQ1Sgw7i2XxuRoWNpeIuPCYhDLNdHjs+I0LjuyPL0LOSo7+DQtVrKS1GEneuuJ5O1YdDqwl2f9/o729ekZV3SY32zd+UJtJZIewVFJAARgIfzdgZ+kPhpxgJdSFTrl+NA6yh4Du1eExGa8b7F3ccH0tjUG0BIidpl8BLViuVfTrImhjUiSGJTq0wTcg99QVFPpwI1RJPPRd8dbC/QYBAetkFRq+vfV2od4aZk4JEbRd+2cQEKqax8ntaSnp/CV9FxpStDH6fZ7z7p0lqQ4LmOXSu8RnKcxoAtIrh5X3O35b3CikrrSqwK3jc2LbcSOis5BdeBd9JY0p1rVseQzxPgB9MgG+64IUw8j6DywTuyd4/mjuZlBuEb2mmt8YT7dVb5Yx8qsGW8UwCOnSsWZ4w14gdlti3Tza7sjP+wulRTMZlw05V2VCbQeM+NOAAiaj1167BNDg6riQIja1o9htAYG5VORxs9Se43yKsbbVQEET8O503qSAI3J2quEexiHfUWUBkRxH08Kt1qogCkhRfnHd3fGWR8fr6N4or+LvaM9en4ZF5ToPE0DkrvSpY6qfH0RCPKtVVBCWs79kmPd70hhBRzjsqBmcQF4RsMXTf7UQSdWDsSj2k3MG4g4ULT/CHd8HTj5X00yK9uGnQJVSrzXtEnaiVrbGKebFkRWZLcSQ0fnzXur/iXZS4USAINecqSF6p9izVji0H6YoZkpw3ptRwbFVB8dvZFnznG2q2WOtAWhYCLxyxAsTA4BmZ5do547gpkO+czYKNNYRbvIIEfYrHR+tR3YyU9FDGKP7FhA703cyJWWESxwFuXk88LjVVk/IkyFpvD8cysKRCLerxN/TkBIAkL0z4yjr0DCzuVKXkOro+xnbyxPuN9rNeeaLyPOYIfaMRGw3PgtiFoNA5D9x41aXcTRdB837vdIln2oGU1MaYCut2asR7YwYc6WXUWVaoaR4pYTBRQg7pQarEompAWXxjA2b6ObwiSdKWlRSVzIgx1ujRdaSz1+hEBPbt0cMP8KtB2kZvkrtjaCfsu5p0TCO/NxUcB26RLTFoBMqCo4jObwAK4hqjXsKCQC4h7yxrgNf63E3y/MWJSOLigD87W+uFwHagK1GoTAzcSvwz3Tk7oxnDqVKqmQfkz/SL9DbtLbGLXzbntJzdHBXXE4kIcYkwry+tVjdPJyc2NAkoskb5cSI8K1DbyXwEAiCLRgle4SrrYHX/CErAxSBRev2qFKy8FTfvgflk8QyNQulfGfimkPR+TKL92E9PXYjCIqHLq7r3+3debm8ZuMcDKSsGp0c6F+lys3jM+1dXXpptDPGSOaf3eRIROFioBBqDYOiJrBs2XSlmjU3T3r/82AkpdfM1z1dfIVz1mVVGpGXDtjWGk+H3/xaH+6lQRgITobaPCc/CexKpRR4Wdq4m7vD5dXgIokJqV2fZOrtm19bBMOF0E8g7w8HCtAR5ubUf9rdyoeKQgDasmbqbuxOvG06dKtaZVwFWLUWJW8q6bcXtMK/hjW0gps3jpJlOvwYe2zM2qbmQjM5DnGszZ3W2De8V5FXUnM4sCRONA/okTvtqEkzc0KDcSVqLBNlm6Qdw/9uwRgKTGn7ECkprWMTC/sTjNm3o9jFvpUOC5kA2u2nnz3J2w6u+vj0w3XgOQ6N6LxV864cUDGyWsSeO7A+JMIUJcQBUg0hQ11LYS+ak/0gc+EwWTJeuGW5ZQeEDP54LqS6200wppNXWbci5mnm9B56kBKWarKNUBFZv9QzKtDYnODzb2CItqMlIYsolNhahD/MnYV3hNCFfkTOHNXKztb0DRbfOFoEpmhDELTfj3SArcgyc47Pp+bFE4qtKFd8SDOKeasZWYlLbJKSne3kce/fJPwEYXWxvcv7WUyBzRKC09ok+FsLnchOJIhJDvKy46Jt32AcDC3KiHUGJlX5YPt2W63pXpZZhKOC34LqsrOvILQ3Fg4jlrcDGk0AprQauKV4mfZ/5cgEvssgRTONw8t0Pmto1ZZE+8kOo1y047azbEFEqHVCzJnUqtVU7p6JMmmeUn2NOub3ltU+6DFDaHVMFoS8tR9IuEyaNayqLZvKg51024yebXvCC6MrIq7hhCUlxiI+9g+MMNSK2ldsVlKfgO3e7oOqKMWktufGMm8oxxI96gQznSrdS5IV2exA7SW5a5sdSS2g49r++WMZY0BkOVVr++bk5Z6daonkCVNPXUPQiBvl5Yulu1zAtroMm8PbjgdczousRvMfYGquBw0MoUYR5kuGZJ4Xeya1TTst46lK4G0ZXysAd0tK+PyboDrrnoJ4erzp3abgv3ZvHI4RQ5ODwyTR3FF27F3nLjPXSqdG3RSnABIJ8nlHuEKYI5Tzo2saHDDTwJkIO50AIGbnx4QOUhqdaAEJJTaO8nFFKCVbR5jRGrBOTzqkIpQl/XRp7HS+Ndm4UXyb45T7jOZRqa+5rr+0kXUin91a3RgylyYzowU5u1ru4ifYmMgwih6ZjrIv89sHHIZM/KuI0dLb4Pm2BdTEG1yAYJ1z1v7wqjkGUbysDdCxKFsmpTfH4GQPtxip+0hkYWQ5OZnlZXC76o+49aqAeOvH0nJDsW+FQ6GmtEjlQEdDzr4Okz1XydeJYMToulS/gt0wtCUfG4hUxYxKXA8FAibrgJfkhBfprYS023facuP3slpnvvUicNiNVWmfP36ei/1qI0ODrGzBJ7AaAAnVOUZ+jYEtK1x79VSPUd7vuofR15vwMC35jrlRty2Jdmyoiu2DXdWg4xPzUG1cS+OHX6e/b9F4UldcWwshqLquo/NCKrgAqKISbSTgw6DpfezoUUrCaJ9aUylB2Aazb0Qq7XpvbcmFVb52MKFlo+alXpvzLeNtchOFX4UOCp25t7gwK8nmQhZYID9WQGXxyYSb4D1JnSaeepTTZBZYXwxnebzRAIwZdrgArGNPKm7QaqGgtRe2SfDgtociAWli4tczvNhgIuXAU5EekqtI3SbO8YAq0WLDB0Wg7YNKMNczma0AlC3rFxTX++Kg5x33CNZXKwNSEWV6No0HIBAi4Qm25iyf1iEamQVETm2Aam1gnu35d2GJ1DdInEO+UQM7DN8WJ8gQHKMf4f3YRGbrdbzsuULBpJQhzuvh78MebLSperEN/GOa5lO4IzyX6lzTrnY2yw+9E9uNmUCUowPLwq+7Isu6O5WYDerzbulFYG8/6uG2LVG9FGCnAZMp9y3cYu84b3k/FHBdj0WnLceT86Pzh8eym3wRcTlk+681QBpZFCoRPt59uQ19IsfUHZpeUU+VRk4LDliWUGPrztvizOwY0HS0lpozoYv1gi5uLj7wr6YpxXGSC6MTY0L9k8OusqxzfjZrH2DBjRwsnNimoYW6JNuhfZ7ECBeYKFlGm58vR1joyZOWJljKzxKthEm8YbjAJ7Pgmvsciaozet4v6p7IiLUDfg0DjqM8T9uLiieKJCtRu3EDWWBtygXekmoHRt8Fh5vmyM6kLM8WgtqcHKNuLPqhXn1zzlEIpSX1IKgn13itw3CzsqDF40wf6ZBzft+qVnUXDSihpAk9sJdVBDbARb9x0h1sjR0/eW2vewrz4dOytSn4PjQuqEpqs6R0W48ntTmAK0g5wpMKSv52U625UdBkA29IHrZiQuNjoGj3H03XYOigPt2vSMvB2xZFJ3kCWlU76nemr2k+bE9t21sblW+1BrSvOa8l8RXJ5g6zEmS6iF1XSxE2bxfWOp2kFL5BHjyFfdbwN5WW+pNgp699y5h4XAE9d8haP3ylm9s7pPGd988oWUbPa5YFXjzJUsg9e7TdhOQncjZ4ibZ7i/4rVIDOiASpwCov9CVHEzpcWHTDRV9CEr8eJQlx6g6sxhIpNFbPwNAlCtHX6egAL2M/7TS/kuZmO/IiZBtS/IUau1Ilqzak+MTWFDI3VQp1GphtdPbhJXUnMclEVBe3OMh1gQ+uy95aGWVP7eKQyjicdVCO6Xcwc6JGhCHkTq8DS8dNT8tcxDNys4xvZ+j5dlfxXWK2OHyt4fz565fAPFoCIl/Xna50xC3sEG0bloeU+zvjaloAz4YuYK9fE8BXcGy4kkk3ab3CGdH/m9uFKj6zZ2Eu9oeiiuJXUd9wSnDQOUxopUseCwSBwzk3jZTUWjpdVW/1W6H88fq8CJpG0KIZjKY8xBMIrTjecIvV2ZX0ApoPdCgA6jlk0b68zDTLJqwfRH4+0QTwbnLHWVvuEUiDY+NVHXtkuCrHplUOD1dhWS321e+gDB6n3yhVSpbA9Ve4rNKw4yXDeGi38R+1TSJVT3l6LypJw8zed6yHmk/EFuCbslbATRmda9Ri2VtEcZ19GEUoWZj8RMrKRC1Rqr0BH496g0rRq6LXQ+c0+ZRBdmJg/KZki6E9lA1LVXJ6Si+2o9GTVuDx4ifNN64r8pFOX5erdg/8CqpKjVpW3J7+m6pQVr1g7feZ0a1hx/YWA4F/Vwc+B9E5CBA20vQfAaFyU5ct3Em2fL57tmsY9aM9oJGTcdhwDQ7DeYE87hV1Ybo0sydhPSQfH2sjG1anv37Gw+5kwqIZYLFlaQChSb17Gh0TUWn9XHCetK9CdSH2XIjr/HukxXYk+lpFMp15QIKArf/YHvCLJr4lI1rkSrwwSSURLty9Qoibrk1rzXPvpCVKWy9HeCyATUuHBKpVEVycZKb61PnRusrJxWYOfmy/ZVUOGghUWkof0qDBVvCEtqsCmZTeVWg1pOHZlhBrll43Nuu06g8N+M43T37F5IboL0huRirQI0NZc4gSXF7VorNS4QcnU/cpPstNXGcsmZ3bmIxuZCb1XlJlJhpGmOp3tLGRYgaJTPJZwxsXAMqi3PbWdwSFskdMtc0b7csHKlqF9jqY24KroFNlgIeo3EUfrvE53I50lXXx2DHql14Akay3L4HtBeeAMM2o5YXOcGboo9j1iUjbzpn1fGUVwvw17S+otdKvgLjY7KuhfK1HpaJkukcoQypmkHY27OETkqOnu3piSQNLDIfNcfNR7yUr6XkBD6uCJI+E5s85V+XhdD6991Y1HpXNay8HE3C/FBGKEeU6Df5hcORjGLCT+y2Q+Eeh4yX7v9pBkYBWOUTgiNMMDUpOpuvTTTJQSVxh4PuBsbGWTkAaIUJnPO4x8f+0JK4eMQTqMUQJ2vVF1sBj6IWBDycACKQBwKbcD9AgFlLi4/r0GOUTDoZ0miim01Au4odxBWSbrlSJaK+6WQIHferGkn3U19FdiwAqmtjLobc4HTitAJK+PEnDDbnMJa4IQFwos1nOK6/QK1kPwZc2FFYqq5xOyZqQFW7a8BpohRlm6KPCrxrp1nJSNU6GVQpj43XVlsi24vzgvOhTGKpkFOG8ct7hfVdvvCjakp2mliLZpLri5iPc+OYBYgC4G5Q2ZeGmOyBJOquHBzE+y06N6dqe8T86q3wALhONgi0i0YNwor2l28MrYGoAGfX1hZALeQEqx3S4n27RZMnaMUOtXKqQqBUk1xcyejgb6Wfu548cqwwvKFCFKPYy4WBEWe/an6qc7JZvwEUKHvJdF4qLNUN34jbbVEW6yfdp2a1URLQ58rFdP6zvYcT1ui4lZNa7O3imV4uM75QZdvqd4XbcW9ObFmo1KzKausvivpMVVwRQHR+bRsTsGmsi+Lh+sKctG2x+JXT6SQys1ukGAhG1rAaRqp3/nPdaw4eNzAjBJGeeSkjVELQD4zYceqwGJC0DrQzVqtg/7oDKcUUN3cHD36c3QhqHke2mdq/gKDTmuPiwyfI9nVzq0CLRNcMx4lz0YrMJmgD3S82Xx0fMVy6t2fY8ejxkU33+vcDt1mMKi2G23lOnyEZWVtNH+HQOAUTndauBg11jhmCHUeg/Zeuonp84gpm1q2zOdGCDCW5UITCe42Hxpr/8Cjcppd94rSJdxCwJPcVZCUB41Fjt1177yfj7yf6DnXHhRGsWl7TKoyijNHCGg8gglMSG3AmRfWKF3o0t7B+RLvZd8bPhGmaAZk5L3XsWqFezNMorzkuOR0aNtM5CSBElLrrQq0upfQ1a/gCFdKarHENxDBrMxQNfM5NlIAMDcl8/0S+SQBZXnpDkevn5kVY9ofg9kdQEEFHvtlFhvuowySVTtprlNXGgWk9T/UIdmcU0D1k5Xn6AbUb+S54Zm5kTEj1/JCEyIBLuJlYHwwtoeq+dg5YdnYRgKrKiyN2oeq7KfQgpYcKKbWfRKbpPY/yUjFmuH3YVH6eInQgFLAAektplQdZXzUAh47JEZoPwqY6Jmrqc2PuUviEcfQTHznHs9DLpKzXewX+zJZMfK+63gqR45DbsBkmuB4d7HHBAxJn5sArhRMxFzAubCkzFKsikM+W2/RX6dIcBPTf2FNYpxZ/kGssrE5rwJKN70GENHcrwpBbS8Fqu4dsqNzYwX6LpuLsheWwwQGCLCMn289vkRXngn1qoxm7Ix8jF24Iv/hhl5alySfrUmWVsmjaR2hFLYPJakSKrCbdSRzedKVVzEOzdhDqcwGjD33tm7eV6V9X6aicNEif7KFVC4Af2GWgKjaMeNJzRqh20eL57mrxtkA1AXGGSmg16yrJAwMvTltl9Qg9AQuAE6C2Fh9orVCarixdhZFWGSomBH8xBksdnqVkc2msRhHNg51kdm5PvM978GTBo3dAhZlaNN2Srh+Mv8pNhZ5gNgR/F0Q3eYxQ6ESauhyuphDvp/snFhUfH61KCPHqD94HyH/9PPEks13Nnafjnh0MvHFFho1bz1mzDcuo9Tg46Mw8hnkd8055kZYpHUja+N77X16S4mfKQMJO6HXCIGubixNHStxk7KmF9aFzd8oVUJ0bbwzLfXOdz9gVRg8g1g2eipddocO6oO6dDll2P3rjKz+i+5kWksmeEgQa89ZyuIsYOIruPkcCGFWk4EgnOS1USzsWme6TzebKphB2NocO3exD8agm1tNUVSyxqQSrgS6skewnAYrB8R4s3ljREm4/Ai9lY41AVixHyPmpvuZj9nI/vakCinCkTf79VBVCuulQnSh7nSWDuHevSat/vrcv6zimsekaBrQ9ZVQXkncbUp1U/hI0D9ynQyabS+2ctHtjZU8gBW0WlL1wwYez7SncIj2TcMJ9up8Ptd8fYcQyWWb9YFVn6sh2unLy5sMi8J5sK6sOOK07MD/hvgbnk0mLV05Zn2gTAU3ZVC+mJZJi5HPWvNvpttNmW7XZbK9lFLx3HgRD9Ox5SaKjeGqs2BUXZRz+Q5xgIgs5wgBH3G+9X1e9rtZhBCnZbuZZf7KTpIyG1fgSGBZK8v6Y8S7C1JQ19ThUluXaTzLBDewm0SjOrfy+WTOpudgckDJCf7DtNbRtowFFTsdQ4s7bRxEgfFZQ5jMy342r6hQbojh/vHnC07GUFaq8hF9EQQoeRC36yhyiPlOy2cQMNLNMT6DZ3TbwdI51mxHlnK+C2nWvuustaz1FKXTK91VKTuUvcDnq13ZbRyht11tB2Uo2uTacjCptmpR9XQ7Gu5LP7KQYK+TyZgkijbnXuuuJr9eyyIjTQUHYD6Lejf04PMxfSDWuxlyhNTze7l2u72KZvdPnpB68OCB/fuDr/6jX+2u/Nrxa8evHb92/Nrxy9zP79y5c/D7yf5RYux/wmO325V3v/vd5VM/9VPL+973vnL79u1f7S59zB73798vb3vb235tHP//7d1JTBRbFAbgIwotiIqKMhkQjUMiSpxDjCsIQoxxWqhxocZIxHbhuHChuMMhcaExuBPdoLJAo1ESlcGggHMcY8SgRgWJGIwTCnheznnpSpc0bb/3Oq9v2f+XVKqrq+gUh3vvqXvrUk3/HWIZHIhjeMSSmTVBJScnU0RfoztO7UnJL5SSkqKvJfCmBd+JEMfgQSyDA3EMHlNj6a8H5eHvliQAAEBIIUkBAICxHJukXC4XFRUV6Rr+PcQxeBDL4EAcg8f1B8TSkRMnAAAgPDi2JwUAAH8+JCkAADAWkhQAABgLSQoAAIyFJAUAAMZyZJI6cuQIjRkzhgYOHEhz5syhGzduhPqUjLdnzx590rH3MmnSJGt/Z2cnud1uGjFiBMXGxtKyZcvo3bt3FO6uXr1KCxcu1Ee3SMzOnDlj2y+TY3fv3k1JSUkUHR1NOTk59OzZM9sxHz58oFWrVul//MfFxdG6devo8+fPFG5+F8s1a9b0KqN5eXm2YxBLouLiYpo1axYNHjyYRo0aRYsXL9bHxHkLpD6/evWKFixYQDExMfo5O3bsoG79skyzOC5JnTp1irZu3apz/+/cuUOZmZk0f/58amtrC/WpGW/y5MnU0tJiLXV1dda+LVu20Llz56i8vJxqa2vp7du3tHTpUgp3X7580TImF0a+7N+/nw4dOkRHjx6lxsZGGjRokJZHaSQ8pFF99OgRXbp0ic6fP6+NdUFBAYWb38VSSFLyLqNlZWW2/Yglaf2UBNTQ0KBx6OrqotzcXI1voPW5p6dHE9SPHz/o+vXrdPz4cSotLdULLuOww8yePZvdbre13dPTw8nJyVxcXBzS8zJdUVERZ2Zm+tzX0dHBkZGRXF5ebr335MkTfeh/fX39/3iWZpN4VFRUWNs/f/7kxMREPnDggC2WLpeLy8rKdPvx48f6czdv3rSOuXjxIvfr14/fvHnD4erXWIrVq1fzokWL+vwZxNK3trY2jUttbW3A9fnChQscERHBra2t1jElJSU8ZMgQ/v79O5vEUT0pyfq3b9/WIRXvh83Kdn19fUjPzQlkGEqGWsaOHatXpNLdFxJTuRrzjqsMBaampiKufjQ3N1Nra6stbvL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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# iter function iterates through all the\n", "# images and labels and stores in two variables\n", "images, labels = next(iter(train_loader))\n", "\n", "# print the total no of samples\n", "print('Number of samples: ', len(images))\n", "image = images[2][0] # load 3rd sample\n", "\n", "# visualize the image\n", "plt.imshow(image)\n", "\n", "# print the size of image\n", "print(\"Image Size: \", image.size())\n", "\n", "# print the label\n", "print(labels)" ] }, { "cell_type": "code", "execution_count": 13, "id": "9e73db64", "metadata": {}, "outputs": [ { "ename": "TypeError", "evalue": "empty(): argument 'size' failed to unpack the object at pos 2 with error \"type must be tuple of ints,but got float\"", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", "Cell \u001b[1;32mIn[13], line 56\u001b[0m\n\u001b[0;32m 53\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m x\n\u001b[0;32m 55\u001b[0m \u001b[38;5;66;03m# Define model and move to device\u001b[39;00m\n\u001b[1;32m---> 56\u001b[0m model \u001b[38;5;241m=\u001b[39m \u001b[43mCNN\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mto(device) \u001b[38;5;66;03m# Specify num_classes\u001b[39;00m\n\u001b[0;32m 57\u001b[0m \u001b[38;5;28mprint\u001b[39m(model)\n", "Cell \u001b[1;32mIn[13], line 44\u001b[0m, in \u001b[0;36mCNN.__init__\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 5\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconv_layers \u001b[38;5;241m=\u001b[39m nn\u001b[38;5;241m.\u001b[39mSequential(\n\u001b[0;32m 6\u001b[0m nn\u001b[38;5;241m.\u001b[39mConv2d(in_channels\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m3\u001b[39m, out_channels\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m32\u001b[39m, kernel_size\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m3\u001b[39m, padding\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m),\n\u001b[0;32m 7\u001b[0m nn\u001b[38;5;241m.\u001b[39mDropout(\u001b[38;5;241m0.3\u001b[39m),\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 38\u001b[0m nn\u001b[38;5;241m.\u001b[39mAdaptiveMaxPool2d(output_size\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2048\u001b[39m),\n\u001b[0;32m 39\u001b[0m )\n\u001b[0;32m 41\u001b[0m \u001b[38;5;66;03m# Adjusted fully connected layer input size: 128 * (image_size/8) * (image_size/8)\u001b[39;00m\n\u001b[0;32m 42\u001b[0m \u001b[38;5;66;03m# Assuming input image size is 224x224 (standard for many CNNs)\u001b[39;00m\n\u001b[0;32m 43\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlinear_layers \u001b[38;5;241m=\u001b[39m nn\u001b[38;5;241m.\u001b[39mSequential(\n\u001b[1;32m---> 44\u001b[0m \u001b[43mnn\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mLinear\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m2048\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1.75\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1.75\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m2048\u001b[39;49m\u001b[43m)\u001b[49m, \u001b[38;5;66;03m# Adjust if using a different input size\u001b[39;00m\n\u001b[0;32m 45\u001b[0m nn\u001b[38;5;241m.\u001b[39mReLU(),\n\u001b[0;32m 46\u001b[0m nn\u001b[38;5;241m.\u001b[39mLinear(\u001b[38;5;241m2048\u001b[39m, num_classes) \u001b[38;5;66;03m# Added ReLU before final layer\u001b[39;00m\n\u001b[0;32m 47\u001b[0m )\n", "File \u001b[1;32mc:\\Users\\France Gabriel\\Desktop\\AI_191\\.venv\\Lib\\site-packages\\torch\\nn\\modules\\linear.py:106\u001b[0m, in \u001b[0;36mLinear.__init__\u001b[1;34m(self, in_features, out_features, bias, device, dtype)\u001b[0m\n\u001b[0;32m 103\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39min_features \u001b[38;5;241m=\u001b[39m in_features\n\u001b[0;32m 104\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mout_features \u001b[38;5;241m=\u001b[39m out_features\n\u001b[0;32m 105\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mweight \u001b[38;5;241m=\u001b[39m Parameter(\n\u001b[1;32m--> 106\u001b[0m \u001b[43mtorch\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mempty\u001b[49m\u001b[43m(\u001b[49m\u001b[43m(\u001b[49m\u001b[43mout_features\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43min_features\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mfactory_kwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 107\u001b[0m )\n\u001b[0;32m 108\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m bias:\n\u001b[0;32m 109\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbias \u001b[38;5;241m=\u001b[39m Parameter(torch\u001b[38;5;241m.\u001b[39mempty(out_features, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mfactory_kwargs))\n", "\u001b[1;31mTypeError\u001b[0m: empty(): argument 'size' failed to unpack the object at pos 2 with error \"type must be tuple of ints,but got float\"" ] } ], "source": [ "class CNN(nn.Module):\n", " def __init__(self): # Added num_classes as a parameter\n", " super(CNN, self).__init__()\n", "\n", " self.conv_layers = nn.Sequential(\n", " nn.Conv2d(in_channels=3, out_channels=32, kernel_size=3, padding=1),\n", " nn.Dropout(0.3),\n", " nn.BatchNorm2d(32), # Moved BatchNorm before ReLU\n", " nn.GELU(),\n", " nn.MaxPool2d(kernel_size=2, stride=2),\n", "\n", " nn.Conv2d(in_channels=32, out_channels=64, kernel_size=3, padding=1),\n", " nn.Dropout(0.3),\n", " nn.BatchNorm2d(64),\n", " nn.GELU(),\n", "\n", " nn.Conv2d(in_channels=64, out_channels=128, kernel_size=3, padding=1),\n", " nn.Dropout(0.3),\n", " nn.BatchNorm2d(128),\n", "\n", " nn.Conv2d(in_channels=128, out_channels=256, kernel_size=3, padding=1),\n", " nn.Dropout(0.3),\n", " nn.BatchNorm2d(256),\n", " nn.GELU(),\n", "\n", " nn.Conv2d(in_channels=256, out_channels=512, kernel_size=3, padding=1),\n", " nn.Dropout(0.3),\n", " nn.BatchNorm2d(512),\n", "\n", " nn.Conv2d(in_channels=512, out_channels=1024, kernel_size=3, padding=1),\n", " nn.Dropout(0.3),\n", " nn.BatchNorm2d(1024),\n", " nn.GELU(),\n", "\n", " nn.Conv2d(in_channels=1024, out_channels=2048, kernel_size=3, padding=1),\n", " nn.Dropout(0.3),\n", " nn.BatchNorm2d(2048),\n", " nn.AdaptiveMaxPool2d(output_size=2048),\n", " )\n", "\n", " # Adjusted fully connected layer input size: 128 * (image_size/8) * (image_size/8)\n", " # Assuming input image size is 224x224 (standard for many CNNs)\n", " self.linear_layers = nn.Sequential(\n", " nn.Linear(2048 * 1.75 * 1.75, 2048), # Adjust if using a different input size\n", " nn.ReLU(),\n", " nn.Linear(2048, num_classes) # Added ReLU before final layer\n", " )\n", "\n", " def forward(self, x):\n", " x = self.conv_layers(x)\n", " x = torch.flatten(x, start_dim=1)\n", " x = self.linear_layers(x)\n", " return x\n", "\n", "# Define model and move to device\n", "model = CNN().to(device) # Specify num_classes\n", "print(model)" ] }, { "cell_type": "code", "execution_count": null, "id": "579af5e8", "metadata": {}, "outputs": [], "source": [ "class EarlyStopping:\n", " def __init__(self, patience=5, delta=0):\n", " self.patience = patience\n", " self.delta = delta\n", " self.best_score = None\n", " self.early_stop = False\n", " self.counter = 0\n", " self.best_model_state = None\n", "\n", " def __call__(self, val_loss, model):\n", " score = -val_loss\n", " if self.best_score is None:\n", " self.best_score = score\n", " self.best_model_state = model.state_dict()\n", " elif score < self.best_score + self.delta:\n", " self.counter += 1\n", " if self.counter >= self.patience:\n", " self.early_stop = True\n", " else:\n", " self.best_score = score\n", " self.best_model_state = model.state_dict()\n", " self.counter = 0\n", "\n", " def load_best_model(self, model):\n", " model.load_state_dict(self.best_model_state)" ] }, { "cell_type": "code", "execution_count": null, "id": "15477edc", "metadata": {}, "outputs": [], "source": [ "# Define loss function (Cross Entropy for classification)\n", "criterion = nn.CrossEntropyLoss().to(device)\n", "\n", "# Define optimizer (Adam with learning rate 0.001)\n", "optimizer = optim.Adam(model.parameters(), lr=learning_rate)\n", "\n", "# Define early stopping\n", "early_stopping = EarlyStopping(patience=20, delta=0) # try 30 tom" ] }, { "cell_type": "code", "execution_count": null, "id": "602b68af", "metadata": {}, "outputs": [], "source": [ "train_losses, val_losses = [], []\n", "train_accuracies, val_accuracies = [], []\n", "\n", "for epoch in range(num_epochs):\n", " # Dynamically split training dataset into training and validation sets each epoch\n", " \n", " model.train()\n", " running_train_loss, correct_train, total_train = 0.0, 0, 0\n", " \n", " for images, labels in train_loader:\n", " images, labels = images.to(device), labels.to(device)\n", " optimizer.zero_grad()\n", " outputs = model(images)\n", " loss = criterion(outputs, labels)\n", " loss.backward()\n", " optimizer.step()\n", "\n", " running_train_loss += loss.item()\n", " _, predicted = torch.max(outputs, 1)\n", " total_train += labels.size(0)\n", " correct_train += (predicted == labels).sum().item()\n", " \n", " train_loss = running_train_loss / len(train_loader)\n", " train_acc = 100 * correct_train / total_train\n", " train_losses.append(train_loss)\n", " train_accuracies.append(train_acc)\n", "\n", " # Validation phase\n", " model.eval()\n", " running_val_loss, correct_val, total_val = 0.0, 0, 0\n", " with torch.no_grad():\n", " for images, labels in val_loader:\n", " images, labels = images.to(device), labels.to(device)\n", " outputs = model(images)\n", " loss = criterion(outputs, labels)\n", " running_val_loss += loss.item()\n", "\n", " _, predicted = torch.max(outputs, 1)\n", " total_val += labels.size(0)\n", " correct_val += (predicted == labels).sum().item()\n", "\n", " val_loss = running_val_loss / len(val_loader)\n", " val_acc = 100 * correct_val / total_val\n", " val_losses.append(val_loss)\n", " val_accuracies.append(val_acc)\n", "\n", " print(f\"Epoch {epoch+1}/{num_epochs}, Train Loss: {train_loss:.4f}, Train Acc: {train_acc:.2f}%, Val Loss: {val_loss:.4f}, Val Acc: {val_acc:.2f}%\")\n", "\n", " early_stopping(val_loss, model)\n", " if early_stopping.early_stop:\n", " print(\"Early stopping\")\n", " break\n", "\n", "# Load best model\n", "early_stopping.load_best_model(model)" ] }, { "cell_type": "code", "execution_count": null, "id": "cf9658f9", "metadata": {}, "outputs": [], "source": [ "# Get actual number of epochs completed\n", "actual_epochs = len(train_accuracies)\n", "\n", "# Plot Accuracy Curves\n", "plt.figure(figsize=(8, 5))\n", "plt.plot(range(1, actual_epochs + 1), train_accuracies, label=\"Training Accuracy\", color='blue', marker='o')\n", "plt.plot(range(1, actual_epochs + 1), val_accuracies, label=\"Validation Accuracy\", color='green', marker='s')\n", "plt.xlabel(\"Epochs\")\n", "plt.ylabel(\"Accuracy (%)\")\n", "plt.title(\"Accuracy Curve\")\n", "plt.legend()\n", "plt.grid(True)\n", "plt.show()\n", "\n", "# Plot Loss Curve\n", "plt.figure(figsize=(8, 5))\n", "plt.plot(range(1, actual_epochs + 1), train_losses, label=\"Training Loss\", color='blue', marker='o')\n", "plt.plot(range(1, actual_epochs + 1), val_losses, label=\"Validation Loss\", color='green', marker='s')\n", "plt.xlabel(\"Epochs\")\n", "plt.ylabel(\"Loss\")\n", "plt.title(\"Loss Curve\")\n", "plt.legend()\n", "plt.grid(True)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "id": "4592ee3a", "metadata": {}, "outputs": [], "source": [ "# Ensure best model is loaded before testing\n", "if early_stopping.best_model_state is not None:\n", " early_stopping.load_best_model(model)\n", "else:\n", " print(\"Warning: No best model state found. Running test on last model.\")" ] }, { "cell_type": "code", "execution_count": null, "id": "63dae9d8", "metadata": {}, "outputs": [], "source": [ "# Set model to evaluation mode\n", "model.eval() \n", "\n", "# Lists to store all predictions and actual labels\n", "all_preds = []\n", "all_labels = []\n", "correct = 0\n", "total = 0\n", "\n", "with torch.no_grad(): # Disable gradients for faster inference\n", " for images, labels in test_loader: \n", " images, labels = images.to(device), labels.to(device)\n", " \n", " outputs = model(images) # Forward pass\n", " _, predicted = torch.max(outputs, 1) # Get predicted class\n", "\n", " total += labels.size(0) # Total number of samples\n", " correct += (predicted == labels).sum().item() # Count correct predictions\n", " \n", " all_preds.extend(predicted.cpu().numpy()) # Move to CPU & store\n", " all_labels.extend(labels.cpu().numpy()) # Move to CPU & store\n", "\n", "# Compute accuracy\n", "accuracy = 100 * correct / total\n", "print(f\"Test Accuracy: {accuracy:.2f}%\")\n", "\n", "# Generate classification report\n", "print(\"Classification Report:\")\n", "print(classification_report(all_labels, all_preds))\n", "\n", "# Confusion Matrix\n", "cm = confusion_matrix(all_labels, all_preds)\n", "\n", "# Display Confusion Matrix\n", "disp = ConfusionMatrixDisplay(confusion_matrix=cm)\n", "fig, ax = plt.subplots(figsize=(6, 6))\n", "disp.plot(ax=ax, cmap=\"Blues\", values_format=\"d\")\n", "plt.xticks(rotation=45, ha=\"right\")\n", "plt.title(\"Confusion Matrix\")\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "id": "0a7fc727", "metadata": {}, "outputs": [], "source": [ "import random\n", "\n", "# Get class name mapping from the dataset\n", "idx_to_class = {v: k for k, v in test_dataset.class_to_idx.items()}\n", "\n", "# Randomly select 10 indices from the entire test dataset\n", "random_indices = random.sample(range(len(test_dataset)), 10)\n", "\n", "# Collect images and labels for those indices\n", "random_images = []\n", "random_labels = []\n", "\n", "for idx in random_indices:\n", " img, label = test_dataset[idx] # Automatically applies transform\n", " random_images.append(img)\n", " random_labels.append(label)\n", "\n", "# Stack into tensors\n", "random_images = torch.stack(random_images).to(device)\n", "random_labels = torch.tensor(random_labels)\n", "\n", "# Model inference\n", "with torch.no_grad():\n", " outputs = model(random_images)\n", "_, preds = torch.max(outputs, 1)\n", "\n", "# Move to CPU for visualization\n", "preds = preds.cpu()\n", "random_labels = random_labels.cpu()\n", "\n", "# Plotting\n", "fig, axes = plt.subplots(2, 5, figsize=(12, 8))\n", "fig.suptitle(\"Predictions on 10 Random Test Images\", fontsize=14)\n", "\n", "# Optional: define mean/std if you normalized during preprocessing\n", "mean = np.array([0.41440827, 0.22118986, 0.07370376])\n", "std = np.array([0.2735952, 0.14904448, 0.07963097])\n", "\n", "for i in range(10):\n", " row, col = divmod(i, 5)\n", "\n", " img = random_images[i].cpu().permute(1, 2, 0).numpy() # (C, H, W) → (H, W, C)\n", " img = np.clip(img * std + mean, 0, 1) # Undo normalization if applied\n", "\n", " axes[row, col].imshow(img)\n", " actual = idx_to_class[random_labels[i].item()]\n", " predicted = idx_to_class[preds[i].item()]\n", " axes[row, col].set_title(f\"Pred: {predicted}\\nActual: {actual}\", fontsize=9)\n", " axes[row, col].title.set_color('green' if predicted == actual else 'red')\n", " axes[row, col].axis(\"off\")\n", "\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "id": "c04b5e3b", "metadata": {}, "outputs": [], "source": [ "torch.save(model, r\"C:\\Users\\France Gabriel\\Desktop\\AI_191\\ShopNET\")" ] }, { "cell_type": "code", "execution_count": null, "id": "fd80a85c", "metadata": {}, "outputs": [], "source": [ "ShopNET = torch.load(r\"C:\\Users\\France Gabriel\\Desktop\\AI_191\\ShopNET\", weights_only=False)" ] }, { "cell_type": "code", "execution_count": null, "id": "ed9b802e", "metadata": {}, "outputs": [], "source": [ "print(ShopNET)" ] }, { "cell_type": "code", "execution_count": null, "id": "8b8437af", "metadata": {}, "outputs": [], "source": [ "# Set model to evaluation mode\n", "ShopNET.eval() \n", "\n", "# Lists to store all predictions and actual labels\n", "all_preds = []\n", "all_labels = []\n", "correct = 0\n", "total = 0\n", "\n", "with torch.no_grad(): # Disable gradients for faster inference\n", " for images, labels in test_loader: \n", " images, labels = images.to(device), labels.to(device)\n", " \n", " outputs = ShopNET(images) # Forward pass\n", " _, predicted = torch.max(outputs, 1) # Get predicted class\n", "\n", " total += labels.size(0) # Total number of samples\n", " correct += (predicted == labels).sum().item() # Count correct predictions\n", " \n", " all_preds.extend(predicted.cpu().numpy()) # Move to CPU & store\n", " all_labels.extend(labels.cpu().numpy()) # Move to CPU & store\n", "\n", "# Compute accuracy\n", "accuracy = 100 * correct / total\n", "print(f\"Test Accuracy: {accuracy:.2f}%\")\n", "\n", "# Generate classification report\n", "print(\"Classification Report:\")\n", "print(classification_report(all_labels, all_preds))\n", "\n", "# Confusion Matrix\n", "cm = confusion_matrix(all_labels, all_preds)\n", "\n", "# Display Confusion Matrix\n", "disp = ConfusionMatrixDisplay(confusion_matrix=cm)\n", "fig, ax = plt.subplots(figsize=(6, 6))\n", "disp.plot(ax=ax, cmap=\"Blues\", values_format=\"d\")\n", "plt.xticks(rotation=45, ha=\"right\")\n", "plt.title(\"Confusion Matrix\")\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "id": "3c3f006a", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": ".venv", "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": "3.12.3" } }, "nbformat": 4, "nbformat_minor": 5 }