{
"cells": [
{
"cell_type": "markdown",
"id": "7edf7168",
"metadata": {},
"source": [
"# TD2: Deep learning"
]
},
{
"cell_type": "markdown",
"id": "fbb8c8df",
"metadata": {},
"source": [
"In this TD, you must modify this notebook to answer the questions. To do this,\n",
"\n",
"1. Fork this repository\n",
"2. Clone your forked repository on your local computer\n",
"3. Answer the questions\n",
"4. Commit and push regularly\n",
"\n",
"The last commit is due on Sunday, December 1, 11:59 PM. Later commits will not be taken into account."
]
},
{
"cell_type": "markdown",
"id": "3d167a29",
"metadata": {},
"source": [
"Install and test PyTorch from https://pytorch.org/get-started/locally."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "330a42f5",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Collecting torch\n",
" Obtaining dependency information for torch from https://files.pythonhosted.org/packages/d6/a8/43e5033f9b2f727c158456e0720f870030ad3685c46f41ca3ca901b54922/torch-2.1.1-cp311-cp311-win_amd64.whl.metadata\n",
" Downloading torch-2.1.1-cp311-cp311-win_amd64.whl.metadata (26 kB)\n",
"Collecting torchvision\n",
" Obtaining dependency information for torchvision from https://files.pythonhosted.org/packages/13/24/23cdf7e7dc33e5c01588c315f8424d31afa9edb05a80168f3d44f7178ff7/torchvision-0.16.1-cp311-cp311-win_amd64.whl.metadata\n",
" Downloading torchvision-0.16.1-cp311-cp311-win_amd64.whl.metadata (6.6 kB)\n",
"Collecting filelock (from torch)\n",
" Obtaining dependency information for filelock from https://files.pythonhosted.org/packages/81/54/84d42a0bee35edba99dee7b59a8d4970eccdd44b99fe728ed912106fc781/filelock-3.13.1-py3-none-any.whl.metadata\n",
" Downloading filelock-3.13.1-py3-none-any.whl.metadata (2.8 kB)\n",
"Collecting typing-extensions (from torch)\n",
" Obtaining dependency information for typing-extensions from https://files.pythonhosted.org/packages/24/21/7d397a4b7934ff4028987914ac1044d3b7d52712f30e2ac7a2ae5bc86dd0/typing_extensions-4.8.0-py3-none-any.whl.metadata\n",
" Downloading typing_extensions-4.8.0-py3-none-any.whl.metadata (3.0 kB)\n",
"Collecting sympy (from torch)\n",
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"Collecting networkx (from torch)\n",
" Obtaining dependency information for networkx from https://files.pythonhosted.org/packages/d5/f0/8fbc882ca80cf077f1b246c0e3c3465f7f415439bdea6b899f6b19f61f70/networkx-3.2.1-py3-none-any.whl.metadata\n",
" Downloading networkx-3.2.1-py3-none-any.whl.metadata (5.2 kB)\n",
"Collecting jinja2 (from torch)\n",
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"Collecting fsspec (from torch)\n",
" Obtaining dependency information for fsspec from https://files.pythonhosted.org/packages/e8/f6/3eccfb530aac90ad1301c582da228e4763f19e719ac8200752a4841b0b2d/fsspec-2023.10.0-py3-none-any.whl.metadata\n",
" Downloading fsspec-2023.10.0-py3-none-any.whl.metadata (6.8 kB)\n",
"Collecting numpy (from torchvision)\n",
" Obtaining dependency information for numpy from https://files.pythonhosted.org/packages/da/3c/3ff05c2855eee52588f489a4e607e4a61699a0742aa03ccf641c77f9eb0a/numpy-1.26.2-cp311-cp311-win_amd64.whl.metadata\n",
" Downloading numpy-1.26.2-cp311-cp311-win_amd64.whl.metadata (61 kB)\n",
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"Collecting requests (from torchvision)\n",
" Obtaining dependency information for requests from https://files.pythonhosted.org/packages/70/8e/0e2d847013cb52cd35b38c009bb167a1a26b2ce6cd6965bf26b47bc0bf44/requests-2.31.0-py3-none-any.whl.metadata\n",
" Downloading requests-2.31.0-py3-none-any.whl.metadata (4.6 kB)\n",
"Collecting pillow!=8.3.*,>=5.3.0 (from torchvision)\n",
" Obtaining dependency information for pillow!=8.3.*,>=5.3.0 from https://files.pythonhosted.org/packages/b1/38/31def4109acd4db10672df6f806b175c0d21458f845ddc0890e43238ba7c/Pillow-10.1.0-cp311-cp311-win_amd64.whl.metadata\n",
" Downloading Pillow-10.1.0-cp311-cp311-win_amd64.whl.metadata (9.6 kB)\n",
"Collecting MarkupSafe>=2.0 (from jinja2->torch)\n",
" Obtaining dependency information for MarkupSafe>=2.0 from https://files.pythonhosted.org/packages/be/bb/08b85bc194034efbf572e70c3951549c8eca0ada25363afc154386b5390a/MarkupSafe-2.1.3-cp311-cp311-win_amd64.whl.metadata\n",
" Downloading MarkupSafe-2.1.3-cp311-cp311-win_amd64.whl.metadata (3.1 kB)\n",
"Collecting charset-normalizer<4,>=2 (from requests->torchvision)\n",
" Obtaining dependency information for charset-normalizer<4,>=2 from https://files.pythonhosted.org/packages/57/ec/80c8d48ac8b1741d5b963797b7c0c869335619e13d4744ca2f67fc11c6fc/charset_normalizer-3.3.2-cp311-cp311-win_amd64.whl.metadata\n",
" Downloading charset_normalizer-3.3.2-cp311-cp311-win_amd64.whl.metadata (34 kB)\n",
"Collecting idna<4,>=2.5 (from requests->torchvision)\n",
" Obtaining dependency information for idna<4,>=2.5 from https://files.pythonhosted.org/packages/c2/e7/a82b05cf63a603df6e68d59ae6a68bf5064484a0718ea5033660af4b54a9/idna-3.6-py3-none-any.whl.metadata\n",
" Downloading idna-3.6-py3-none-any.whl.metadata (9.9 kB)\n",
"Collecting urllib3<3,>=1.21.1 (from requests->torchvision)\n",
" Obtaining dependency information for urllib3<3,>=1.21.1 from https://files.pythonhosted.org/packages/96/94/c31f58c7a7f470d5665935262ebd7455c7e4c7782eb525658d3dbf4b9403/urllib3-2.1.0-py3-none-any.whl.metadata\n",
" Downloading urllib3-2.1.0-py3-none-any.whl.metadata (6.4 kB)\n",
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" Obtaining dependency information for certifi>=2017.4.17 from https://files.pythonhosted.org/packages/64/62/428ef076be88fa93716b576e4a01f919d25968913e817077a386fcbe4f42/certifi-2023.11.17-py3-none-any.whl.metadata\n",
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"Successfully installed MarkupSafe-2.1.3 certifi-2023.11.17 charset-normalizer-3.3.2 filelock-3.13.1 fsspec-2023.10.0 idna-3.6 jinja2-3.1.2 mpmath-1.3.0 networkx-3.2.1 numpy-1.26.2 pillow-10.1.0 requests-2.31.0 sympy-1.12 torch-2.1.1 torchvision-0.16.1 typing-extensions-4.8.0 urllib3-2.1.0\n",
"Note: you may need to restart the kernel to use updated packages.\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"[notice] A new release of pip is available: 23.2.1 -> 23.3.1\n",
"[notice] To update, run: C:\\Users\\arman\\AppData\\Local\\Microsoft\\WindowsApps\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\python.exe -m pip install --upgrade pip\n"
]
}
],
"source": [
"%pip install torch torchvision"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Note: you may need to restart the kernel to use updated packages.\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"ERROR: Could not open requirements file: [Errno 2] No such file or directory: 'pytorch'\n",
"\n",
"[notice] A new release of pip is available: 23.2.1 -> 23.3.1\n",
"[notice] To update, run: C:\\Users\\arman\\AppData\\Local\\Microsoft\\WindowsApps\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\python.exe -m pip install --upgrade pip\n"
]
}
],
"source": [
"%pip install pytorch torchvision cudatoolkit=10.1 -c pytorch"
]
},
{
"cell_type": "markdown",
"id": "0882a636",
"metadata": {},
"source": [
"\n",
"To test run the following code"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "b1950f0a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"tensor([[ 0.2555, 0.5142, 0.9050, 0.6887, -3.4806, -0.2438, -0.9182, 0.3653,\n",
" -0.9298, -0.1004],\n",
" [ 0.1015, 0.1290, 0.3338, -1.4685, -0.9104, -0.5621, 1.2732, -0.6638,\n",
" 0.1203, 1.1361],\n",
" [-1.1418, -0.1904, -0.1097, 0.8402, 0.1132, 1.6985, -1.9142, 0.5754,\n",
" -0.2390, 0.3977],\n",
" [ 1.4522, -1.0028, -1.3353, 0.5364, -1.8395, 1.3521, 0.0924, -0.8649,\n",
" -0.1557, 0.2052],\n",
" [ 0.8001, -0.5585, 0.8460, -0.9609, -1.1242, 1.5402, -2.4606, -2.0300,\n",
" -0.6318, -0.0838],\n",
" [ 0.2683, -0.2505, -0.1922, 0.9091, 0.2451, 0.1776, -1.0072, -2.0003,\n",
" 1.0307, 2.2512],\n",
" [-1.2950, 0.6823, 0.6947, 0.4725, -0.1428, 1.4061, 0.5532, 1.2814,\n",
" 0.8082, 0.8662],\n",
" [-1.3510, 0.2161, 0.0375, 1.0638, 0.2757, 0.1830, 0.8016, 0.9672,\n",
" -0.8459, -0.3823],\n",
" [-1.1632, 0.0980, 0.9728, -0.6465, -1.6451, 1.2031, 0.8534, 0.8798,\n",
" -0.0494, 2.5921],\n",
" [-0.5641, -0.0493, -0.4666, 0.1480, 0.5392, 1.2259, 1.4591, -0.7750,\n",
" 0.1584, 1.9908],\n",
" [-0.4800, -0.3408, -0.7084, -0.1890, -0.1886, 1.3318, 0.1626, -0.9777,\n",
" 0.3622, -1.4674],\n",
" [ 1.2429, 1.0757, -1.2823, -0.8961, -0.3589, -1.9026, 1.0818, -0.1697,\n",
" -2.6758, 1.9248],\n",
" [ 0.3162, 0.5869, -0.0535, -0.1426, 0.3261, 1.0134, -0.1007, 0.7444,\n",
" -1.2844, -0.3796],\n",
" [-1.2372, 0.6372, 0.6880, 0.1457, -2.2376, -1.4584, -1.2674, 1.7228,\n",
" -0.8804, -0.5135]])\n",
"AlexNet(\n",
" (features): Sequential(\n",
" (0): Conv2d(3, 64, kernel_size=(11, 11), stride=(4, 4), padding=(2, 2))\n",
" (1): ReLU(inplace=True)\n",
" (2): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
" (3): Conv2d(64, 192, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2))\n",
" (4): ReLU(inplace=True)\n",
" (5): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
" (6): Conv2d(192, 384, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
" (7): ReLU(inplace=True)\n",
" (8): Conv2d(384, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
" (9): ReLU(inplace=True)\n",
" (10): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
" (11): ReLU(inplace=True)\n",
" (12): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
" )\n",
" (avgpool): AdaptiveAvgPool2d(output_size=(6, 6))\n",
" (classifier): Sequential(\n",
" (0): Dropout(p=0.5, inplace=False)\n",
" (1): Linear(in_features=9216, out_features=4096, bias=True)\n",
" (2): ReLU(inplace=True)\n",
" (3): Dropout(p=0.5, inplace=False)\n",
" (4): Linear(in_features=4096, out_features=4096, bias=True)\n",
" (5): ReLU(inplace=True)\n",
" (6): Linear(in_features=4096, out_features=1000, bias=True)\n",
" )\n",
")\n"
]
}
],
"source": [
"import torch\n",
"\n",
"N, D = 14, 10\n",
"x = torch.randn(N, D).type(torch.FloatTensor)\n",
"print(x)\n",
"\n",
"from torchvision import models\n",
"\n",
"alexnet = models.alexnet()\n",
"print(alexnet)"
]
},
{
"cell_type": "markdown",
"id": "23f266da",
"metadata": {},
"source": [
"## Exercise 1: CNN on CIFAR10\n",
"\n",
"The goal is to apply a Convolutional Neural Net (CNN) model on the CIFAR10 image dataset and test the accuracy of the model on the basis of image classification. Compare the Accuracy VS the neural network implemented during TD1.\n",
"\n",
"Have a look at the following documentation to be familiar with PyTorch.\n",
"\n",
"https://pytorch.org/tutorials/beginner/pytorch_with_examples.html\n",
"\n",
"https://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html"
]
},
{
"cell_type": "markdown",
"id": "4ba1c82d",
"metadata": {},
"source": [
"You can test if GPU is available on your machine and thus train on it to speed up the process"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "6e18f2fd",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CUDA is not available. Training on CPU ...\n"
]
}
],
"source": [
"import torch\n",
"\n",
"# check if CUDA is available\n",
"train_on_gpu = torch.cuda.is_available()\n",
"\n",
"if not train_on_gpu:\n",
" print(\"CUDA is not available. Training on CPU ...\")\n",
"else:\n",
" print(\"CUDA is available! Training on GPU ...\")"
]
},
{
"cell_type": "markdown",
"id": "5cf214eb",
"metadata": {},
"source": [
"Next we load the CIFAR10 dataset"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "462666a2",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Downloading https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz to data\\cifar-10-python.tar.gz\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"20.0%\n"
]
},
{
"ename": "KeyboardInterrupt",
"evalue": "",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
"\u001b[1;32mc:\\Users\\arman\\Desktop\\Cours_Centrale\\Apprentissage_profond\\BE2\\mod-4-6-td-2-as\\TD2 Deep Learning_AS.ipynb Cell 12\u001b[0m line \u001b[0;36m1\n\u001b[0;32m <a href='vscode-notebook-cell:/c%3A/Users/arman/Desktop/Cours_Centrale/Apprentissage_profond/BE2/mod-4-6-td-2-as/TD2%20Deep%20Learning_AS.ipynb#X14sZmlsZQ%3D%3D?line=12'>13</a>\u001b[0m transform \u001b[39m=\u001b[39m transforms\u001b[39m.\u001b[39mCompose(\n\u001b[0;32m <a href='vscode-notebook-cell:/c%3A/Users/arman/Desktop/Cours_Centrale/Apprentissage_profond/BE2/mod-4-6-td-2-as/TD2%20Deep%20Learning_AS.ipynb#X14sZmlsZQ%3D%3D?line=13'>14</a>\u001b[0m [transforms\u001b[39m.\u001b[39mToTensor(), transforms\u001b[39m.\u001b[39mNormalize((\u001b[39m0.5\u001b[39m, \u001b[39m0.5\u001b[39m, \u001b[39m0.5\u001b[39m), (\u001b[39m0.5\u001b[39m, \u001b[39m0.5\u001b[39m, \u001b[39m0.5\u001b[39m))]\n\u001b[0;32m <a href='vscode-notebook-cell:/c%3A/Users/arman/Desktop/Cours_Centrale/Apprentissage_profond/BE2/mod-4-6-td-2-as/TD2%20Deep%20Learning_AS.ipynb#X14sZmlsZQ%3D%3D?line=14'>15</a>\u001b[0m )\n\u001b[0;32m <a href='vscode-notebook-cell:/c%3A/Users/arman/Desktop/Cours_Centrale/Apprentissage_profond/BE2/mod-4-6-td-2-as/TD2%20Deep%20Learning_AS.ipynb#X14sZmlsZQ%3D%3D?line=16'>17</a>\u001b[0m \u001b[39m# choose the training and test datasets\u001b[39;00m\n\u001b[1;32m---> <a href='vscode-notebook-cell:/c%3A/Users/arman/Desktop/Cours_Centrale/Apprentissage_profond/BE2/mod-4-6-td-2-as/TD2%20Deep%20Learning_AS.ipynb#X14sZmlsZQ%3D%3D?line=17'>18</a>\u001b[0m train_data \u001b[39m=\u001b[39m datasets\u001b[39m.\u001b[39;49mCIFAR10(\u001b[39m\"\u001b[39;49m\u001b[39mdata\u001b[39;49m\u001b[39m\"\u001b[39;49m, train\u001b[39m=\u001b[39;49m\u001b[39mTrue\u001b[39;49;00m, download\u001b[39m=\u001b[39;49m\u001b[39mTrue\u001b[39;49;00m, transform\u001b[39m=\u001b[39;49mtransform)\n\u001b[0;32m <a href='vscode-notebook-cell:/c%3A/Users/arman/Desktop/Cours_Centrale/Apprentissage_profond/BE2/mod-4-6-td-2-as/TD2%20Deep%20Learning_AS.ipynb#X14sZmlsZQ%3D%3D?line=18'>19</a>\u001b[0m test_data \u001b[39m=\u001b[39m datasets\u001b[39m.\u001b[39mCIFAR10(\u001b[39m\"\u001b[39m\u001b[39mdata\u001b[39m\u001b[39m\"\u001b[39m, train\u001b[39m=\u001b[39m\u001b[39mFalse\u001b[39;00m, download\u001b[39m=\u001b[39m\u001b[39mTrue\u001b[39;00m, transform\u001b[39m=\u001b[39mtransform)\n\u001b[0;32m <a href='vscode-notebook-cell:/c%3A/Users/arman/Desktop/Cours_Centrale/Apprentissage_profond/BE2/mod-4-6-td-2-as/TD2%20Deep%20Learning_AS.ipynb#X14sZmlsZQ%3D%3D?line=20'>21</a>\u001b[0m \u001b[39m# obtain training indices that will be used for validation\u001b[39;00m\n",
"File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\torchvision\\datasets\\cifar.py:65\u001b[0m, in \u001b[0;36mCIFAR10.__init__\u001b[1;34m(self, root, train, transform, target_transform, download)\u001b[0m\n\u001b[0;32m 62\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mtrain \u001b[39m=\u001b[39m train \u001b[39m# training set or test set\u001b[39;00m\n\u001b[0;32m 64\u001b[0m \u001b[39mif\u001b[39;00m download:\n\u001b[1;32m---> 65\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mdownload()\n\u001b[0;32m 67\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_check_integrity():\n\u001b[0;32m 68\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mRuntimeError\u001b[39;00m(\u001b[39m\"\u001b[39m\u001b[39mDataset not found or corrupted. You can use download=True to download it\u001b[39m\u001b[39m\"\u001b[39m)\n",
"File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\torchvision\\datasets\\cifar.py:139\u001b[0m, in \u001b[0;36mCIFAR10.download\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m 137\u001b[0m \u001b[39mprint\u001b[39m(\u001b[39m\"\u001b[39m\u001b[39mFiles already downloaded and verified\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[0;32m 138\u001b[0m \u001b[39mreturn\u001b[39;00m\n\u001b[1;32m--> 139\u001b[0m download_and_extract_archive(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49murl, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mroot, filename\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mfilename, md5\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mtgz_md5)\n",
"File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\torchvision\\datasets\\utils.py:434\u001b[0m, in \u001b[0;36mdownload_and_extract_archive\u001b[1;34m(url, download_root, extract_root, filename, md5, remove_finished)\u001b[0m\n\u001b[0;32m 431\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m filename:\n\u001b[0;32m 432\u001b[0m filename \u001b[39m=\u001b[39m os\u001b[39m.\u001b[39mpath\u001b[39m.\u001b[39mbasename(url)\n\u001b[1;32m--> 434\u001b[0m download_url(url, download_root, filename, md5)\n\u001b[0;32m 436\u001b[0m archive \u001b[39m=\u001b[39m os\u001b[39m.\u001b[39mpath\u001b[39m.\u001b[39mjoin(download_root, filename)\n\u001b[0;32m 437\u001b[0m \u001b[39mprint\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mExtracting \u001b[39m\u001b[39m{\u001b[39;00marchive\u001b[39m}\u001b[39;00m\u001b[39m to \u001b[39m\u001b[39m{\u001b[39;00mextract_root\u001b[39m}\u001b[39;00m\u001b[39m\"\u001b[39m)\n",
"File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\torchvision\\datasets\\utils.py:144\u001b[0m, in \u001b[0;36mdownload_url\u001b[1;34m(url, root, filename, md5, max_redirect_hops)\u001b[0m\n\u001b[0;32m 142\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m 143\u001b[0m \u001b[39mprint\u001b[39m(\u001b[39m\"\u001b[39m\u001b[39mDownloading \u001b[39m\u001b[39m\"\u001b[39m \u001b[39m+\u001b[39m url \u001b[39m+\u001b[39m \u001b[39m\"\u001b[39m\u001b[39m to \u001b[39m\u001b[39m\"\u001b[39m \u001b[39m+\u001b[39m fpath)\n\u001b[1;32m--> 144\u001b[0m _urlretrieve(url, fpath)\n\u001b[0;32m 145\u001b[0m \u001b[39mexcept\u001b[39;00m (urllib\u001b[39m.\u001b[39merror\u001b[39m.\u001b[39mURLError, \u001b[39mOSError\u001b[39;00m) \u001b[39mas\u001b[39;00m e: \u001b[39m# type: ignore[attr-defined]\u001b[39;00m\n\u001b[0;32m 146\u001b[0m \u001b[39mif\u001b[39;00m url[:\u001b[39m5\u001b[39m] \u001b[39m==\u001b[39m \u001b[39m\"\u001b[39m\u001b[39mhttps\u001b[39m\u001b[39m\"\u001b[39m:\n",
"File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\torchvision\\datasets\\utils.py:48\u001b[0m, in \u001b[0;36m_urlretrieve\u001b[1;34m(url, filename, chunk_size)\u001b[0m\n\u001b[0;32m 46\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_urlretrieve\u001b[39m(url: \u001b[39mstr\u001b[39m, filename: \u001b[39mstr\u001b[39m, chunk_size: \u001b[39mint\u001b[39m \u001b[39m=\u001b[39m \u001b[39m1024\u001b[39m \u001b[39m*\u001b[39m \u001b[39m32\u001b[39m) \u001b[39m-\u001b[39m\u001b[39m>\u001b[39m \u001b[39mNone\u001b[39;00m:\n\u001b[0;32m 47\u001b[0m \u001b[39mwith\u001b[39;00m urllib\u001b[39m.\u001b[39mrequest\u001b[39m.\u001b[39murlopen(urllib\u001b[39m.\u001b[39mrequest\u001b[39m.\u001b[39mRequest(url, headers\u001b[39m=\u001b[39m{\u001b[39m\"\u001b[39m\u001b[39mUser-Agent\u001b[39m\u001b[39m\"\u001b[39m: USER_AGENT})) \u001b[39mas\u001b[39;00m response:\n\u001b[1;32m---> 48\u001b[0m _save_response_content(\u001b[39miter\u001b[39;49m(\u001b[39mlambda\u001b[39;49;00m: response\u001b[39m.\u001b[39;49mread(chunk_size), \u001b[39mb\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39m\"\u001b[39;49m), filename, length\u001b[39m=\u001b[39;49mresponse\u001b[39m.\u001b[39;49mlength)\n",
"File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\torchvision\\datasets\\utils.py:37\u001b[0m, in \u001b[0;36m_save_response_content\u001b[1;34m(content, destination, length)\u001b[0m\n\u001b[0;32m 31\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_save_response_content\u001b[39m(\n\u001b[0;32m 32\u001b[0m content: Iterator[\u001b[39mbytes\u001b[39m],\n\u001b[0;32m 33\u001b[0m destination: \u001b[39mstr\u001b[39m,\n\u001b[0;32m 34\u001b[0m length: Optional[\u001b[39mint\u001b[39m] \u001b[39m=\u001b[39m \u001b[39mNone\u001b[39;00m,\n\u001b[0;32m 35\u001b[0m ) \u001b[39m-\u001b[39m\u001b[39m>\u001b[39m \u001b[39mNone\u001b[39;00m:\n\u001b[0;32m 36\u001b[0m \u001b[39mwith\u001b[39;00m \u001b[39mopen\u001b[39m(destination, \u001b[39m\"\u001b[39m\u001b[39mwb\u001b[39m\u001b[39m\"\u001b[39m) \u001b[39mas\u001b[39;00m fh, tqdm(total\u001b[39m=\u001b[39mlength) \u001b[39mas\u001b[39;00m pbar:\n\u001b[1;32m---> 37\u001b[0m \u001b[39mfor\u001b[39;49;00m chunk \u001b[39min\u001b[39;49;00m content:\n\u001b[0;32m 38\u001b[0m \u001b[39m# filter out keep-alive new chunks\u001b[39;49;00m\n\u001b[0;32m 39\u001b[0m \u001b[39mif\u001b[39;49;00m \u001b[39mnot\u001b[39;49;00m chunk:\n\u001b[0;32m 40\u001b[0m \u001b[39mcontinue\u001b[39;49;00m\n",
"File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\torchvision\\datasets\\utils.py:48\u001b[0m, in \u001b[0;36m_urlretrieve.<locals>.<lambda>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 46\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_urlretrieve\u001b[39m(url: \u001b[39mstr\u001b[39m, filename: \u001b[39mstr\u001b[39m, chunk_size: \u001b[39mint\u001b[39m \u001b[39m=\u001b[39m \u001b[39m1024\u001b[39m \u001b[39m*\u001b[39m \u001b[39m32\u001b[39m) \u001b[39m-\u001b[39m\u001b[39m>\u001b[39m \u001b[39mNone\u001b[39;00m:\n\u001b[0;32m 47\u001b[0m \u001b[39mwith\u001b[39;00m urllib\u001b[39m.\u001b[39mrequest\u001b[39m.\u001b[39murlopen(urllib\u001b[39m.\u001b[39mrequest\u001b[39m.\u001b[39mRequest(url, headers\u001b[39m=\u001b[39m{\u001b[39m\"\u001b[39m\u001b[39mUser-Agent\u001b[39m\u001b[39m\"\u001b[39m: USER_AGENT})) \u001b[39mas\u001b[39;00m response:\n\u001b[1;32m---> 48\u001b[0m _save_response_content(\u001b[39miter\u001b[39m(\u001b[39mlambda\u001b[39;00m: response\u001b[39m.\u001b[39;49mread(chunk_size), \u001b[39mb\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m\"\u001b[39m), filename, length\u001b[39m=\u001b[39mresponse\u001b[39m.\u001b[39mlength)\n",
"File \u001b[1;32mC:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.11_3.11.1776.0_x64__qbz5n2kfra8p0\\Lib\\http\\client.py:466\u001b[0m, in \u001b[0;36mHTTPResponse.read\u001b[1;34m(self, amt)\u001b[0m\n\u001b[0;32m 463\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mlength \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m \u001b[39mand\u001b[39;00m amt \u001b[39m>\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mlength:\n\u001b[0;32m 464\u001b[0m \u001b[39m# clip the read to the \"end of response\"\u001b[39;00m\n\u001b[0;32m 465\u001b[0m amt \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mlength\n\u001b[1;32m--> 466\u001b[0m s \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mfp\u001b[39m.\u001b[39mread(amt)\n\u001b[0;32m 467\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m s \u001b[39mand\u001b[39;00m amt:\n\u001b[0;32m 468\u001b[0m \u001b[39m# Ideally, we would raise IncompleteRead if the content-length\u001b[39;00m\n\u001b[0;32m 469\u001b[0m \u001b[39m# wasn't satisfied, but it might break compatibility.\u001b[39;00m\n\u001b[0;32m 470\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_close_conn()\n",
"File \u001b[1;32mC:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.11_3.11.1776.0_x64__qbz5n2kfra8p0\\Lib\\socket.py:706\u001b[0m, in \u001b[0;36mSocketIO.readinto\u001b[1;34m(self, b)\u001b[0m\n\u001b[0;32m 704\u001b[0m \u001b[39mwhile\u001b[39;00m \u001b[39mTrue\u001b[39;00m:\n\u001b[0;32m 705\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[1;32m--> 706\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_sock\u001b[39m.\u001b[39;49mrecv_into(b)\n\u001b[0;32m 707\u001b[0m \u001b[39mexcept\u001b[39;00m timeout:\n\u001b[0;32m 708\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_timeout_occurred \u001b[39m=\u001b[39m \u001b[39mTrue\u001b[39;00m\n",
"File \u001b[1;32mC:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.11_3.11.1776.0_x64__qbz5n2kfra8p0\\Lib\\ssl.py:1311\u001b[0m, in \u001b[0;36mSSLSocket.recv_into\u001b[1;34m(self, buffer, nbytes, flags)\u001b[0m\n\u001b[0;32m 1307\u001b[0m \u001b[39mif\u001b[39;00m flags \u001b[39m!=\u001b[39m \u001b[39m0\u001b[39m:\n\u001b[0;32m 1308\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mValueError\u001b[39;00m(\n\u001b[0;32m 1309\u001b[0m \u001b[39m\"\u001b[39m\u001b[39mnon-zero flags not allowed in calls to recv_into() on \u001b[39m\u001b[39m%s\u001b[39;00m\u001b[39m\"\u001b[39m \u001b[39m%\u001b[39m\n\u001b[0;32m 1310\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m\u001b[39m__class__\u001b[39m)\n\u001b[1;32m-> 1311\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mread(nbytes, buffer)\n\u001b[0;32m 1312\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m 1313\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39msuper\u001b[39m()\u001b[39m.\u001b[39mrecv_into(buffer, nbytes, flags)\n",
"File \u001b[1;32mC:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.11_3.11.1776.0_x64__qbz5n2kfra8p0\\Lib\\ssl.py:1167\u001b[0m, in \u001b[0;36mSSLSocket.read\u001b[1;34m(self, len, buffer)\u001b[0m\n\u001b[0;32m 1165\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m 1166\u001b[0m \u001b[39mif\u001b[39;00m buffer \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[1;32m-> 1167\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_sslobj\u001b[39m.\u001b[39;49mread(\u001b[39mlen\u001b[39;49m, buffer)\n\u001b[0;32m 1168\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m 1169\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_sslobj\u001b[39m.\u001b[39mread(\u001b[39mlen\u001b[39m)\n",
"\u001b[1;31mKeyboardInterrupt\u001b[0m: "
]
}
],
"source": [
"import numpy as np\n",
"from torchvision import datasets, transforms\n",
"from torch.utils.data.sampler import SubsetRandomSampler\n",
"\n",
"# number of subprocesses to use for data loading\n",
"num_workers = 0\n",
"# how many samples per batch to load\n",
"batch_size = 20\n",
"# percentage of training set to use as validation\n",
"valid_size = 0.2\n",
"\n",
"# convert data to a normalized torch.FloatTensor\n",
"transform = transforms.Compose(\n",
" [transforms.ToTensor(), transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))]\n",
")\n",
"\n",
"# choose the training and test datasets\n",
"train_data = datasets.CIFAR10(\"data\", train=True, download=True, transform=transform)\n",
"test_data = datasets.CIFAR10(\"data\", train=False, download=True, transform=transform)\n",
"\n",
"# obtain training indices that will be used for validation\n",
"num_train = len(train_data)\n",
"indices = list(range(num_train))\n",
"np.random.shuffle(indices)\n",
"split = int(np.floor(valid_size * num_train))\n",
"train_idx, valid_idx = indices[split:], indices[:split]\n",
"\n",
"# define samplers for obtaining training and validation batches\n",
"train_sampler = SubsetRandomSampler(train_idx)\n",
"valid_sampler = SubsetRandomSampler(valid_idx)\n",
"\n",
"# prepare data loaders (combine dataset and sampler)\n",
"train_loader = torch.utils.data.DataLoader(\n",
" train_data, batch_size=batch_size, sampler=train_sampler, num_workers=num_workers\n",
")\n",
"valid_loader = torch.utils.data.DataLoader(\n",
" train_data, batch_size=batch_size, sampler=valid_sampler, num_workers=num_workers\n",
")\n",
"test_loader = torch.utils.data.DataLoader(\n",
" test_data, batch_size=batch_size, num_workers=num_workers\n",
")\n",
"\n",
"# specify the image classes\n",
"classes = [\n",
" \"airplane\",\n",
" \"automobile\",\n",
" \"bird\",\n",
" \"cat\",\n",
" \"deer\",\n",
" \"dog\",\n",
" \"frog\",\n",
" \"horse\",\n",
" \"ship\",\n",
" \"truck\",\n",
"]"
]
},
{
"cell_type": "markdown",
"id": "58ec3903",
"metadata": {},
"source": [
"CNN definition (this one is an example)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "317bf070",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Net(\n",
" (conv1): Conv2d(3, 6, kernel_size=(5, 5), stride=(1, 1))\n",
" (pool): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
" (conv2): Conv2d(6, 16, kernel_size=(5, 5), stride=(1, 1))\n",
" (fc1): Linear(in_features=400, out_features=120, bias=True)\n",
" (fc2): Linear(in_features=120, out_features=84, bias=True)\n",
" (fc3): Linear(in_features=84, out_features=10, bias=True)\n",
")\n"
]
}
],
"source": [
"import torch.nn as nn\n",
"import torch.nn.functional as F\n",
"\n",
"# define the CNN architecture\n",
"\n",
"\n",
"class Net(nn.Module):\n",
" def __init__(self):\n",
" super(Net, self).__init__()\n",
" self.conv1 = nn.Conv2d(3, 6, 5)\n",
" self.pool = nn.MaxPool2d(2, 2)\n",
" self.conv2 = nn.Conv2d(6, 16, 5)\n",
" self.fc1 = nn.Linear(16 * 5 * 5, 120)\n",
" self.fc2 = nn.Linear(120, 84)\n",
" self.fc3 = nn.Linear(84, 10)\n",
"\n",
" def forward(self, x):\n",
" x = self.pool(F.relu(self.conv1(x)))\n",
" x = self.pool(F.relu(self.conv2(x)))\n",
" x = x.view(-1, 16 * 5 * 5)\n",
" x = F.relu(self.fc1(x))\n",
" x = F.relu(self.fc2(x))\n",
" x = self.fc3(x)\n",
" return x\n",
"\n",
"\n",
"# create a complete CNN\n",
"model = Net()\n",
"print(model)\n",
"# move tensors to GPU if CUDA is available\n",
"if train_on_gpu:\n",
" model.cuda()"
]
},
{
"cell_type": "markdown",
"id": "a2dc4974",
"metadata": {},
"source": [
"Loss function and training using SGD (Stochastic Gradient Descent) optimizer"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "4b53f229",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch: 0 \tTraining Loss: 43.789997 \tValidation Loss: 38.465666\n",
"Validation loss decreased (inf --> 38.465666). Saving model ...\n",
"Epoch: 1 \tTraining Loss: 35.233757 \tValidation Loss: 33.333461\n",
"Validation loss decreased (38.465666 --> 33.333461). Saving model ...\n",
"Epoch: 2 \tTraining Loss: 31.420901 \tValidation Loss: 29.788399\n",
"Validation loss decreased (33.333461 --> 29.788399). Saving model ...\n",
"Epoch: 3 \tTraining Loss: 28.943639 \tValidation Loss: 28.194237\n",
"Validation loss decreased (29.788399 --> 28.194237). Saving model ...\n",
"Epoch: 4 \tTraining Loss: 27.155546 \tValidation Loss: 26.364088\n",
"Validation loss decreased (28.194237 --> 26.364088). Saving model ...\n",
"Epoch: 5 \tTraining Loss: 25.796170 \tValidation Loss: 26.289203\n",
"Validation loss decreased (26.364088 --> 26.289203). Saving model ...\n",
"Epoch: 6 \tTraining Loss: 24.553256 \tValidation Loss: 24.934050\n",
"Validation loss decreased (26.289203 --> 24.934050). Saving model ...\n",
"Epoch: 7 \tTraining Loss: 23.561086 \tValidation Loss: 23.690149\n",
"Validation loss decreased (24.934050 --> 23.690149). Saving model ...\n",
"Epoch: 8 \tTraining Loss: 22.663388 \tValidation Loss: 23.501354\n",
"Validation loss decreased (23.690149 --> 23.501354). Saving model ...\n",
"Epoch: 9 \tTraining Loss: 21.772717 \tValidation Loss: 23.352594\n",
"Validation loss decreased (23.501354 --> 23.352594). Saving model ...\n",
"Epoch: 10 \tTraining Loss: 21.021508 \tValidation Loss: 22.311111\n",
"Validation loss decreased (23.352594 --> 22.311111). Saving model ...\n",
"Epoch: 11 \tTraining Loss: 20.236052 \tValidation Loss: 22.984949\n",
"Epoch: 12 \tTraining Loss: 19.573871 \tValidation Loss: 21.763351\n",
"Validation loss decreased (22.311111 --> 21.763351). Saving model ...\n",
"Epoch: 13 \tTraining Loss: 18.918306 \tValidation Loss: 21.255830\n",
"Validation loss decreased (21.763351 --> 21.255830). Saving model ...\n",
"Epoch: 14 \tTraining Loss: 18.244189 \tValidation Loss: 21.026639\n",
"Validation loss decreased (21.255830 --> 21.026639). Saving model ...\n",
"Epoch: 15 \tTraining Loss: 17.620863 \tValidation Loss: 21.206371\n",
"Epoch: 16 \tTraining Loss: 17.014284 \tValidation Loss: 21.426653\n",
"Epoch: 17 \tTraining Loss: 16.439310 \tValidation Loss: 22.390448\n",
"Epoch: 18 \tTraining Loss: 15.885207 \tValidation Loss: 21.159895\n",
"Epoch: 19 \tTraining Loss: 15.342987 \tValidation Loss: 20.817466\n",
"Validation loss decreased (21.026639 --> 20.817466). Saving model ...\n",
"Epoch: 20 \tTraining Loss: 14.831190 \tValidation Loss: 21.532822\n",
"Epoch: 21 \tTraining Loss: 14.393169 \tValidation Loss: 21.732499\n",
"Epoch: 22 \tTraining Loss: 13.861100 \tValidation Loss: 22.732082\n",
"Epoch: 23 \tTraining Loss: 13.365509 \tValidation Loss: 23.641571\n",
"Epoch: 24 \tTraining Loss: 12.935439 \tValidation Loss: 23.894530\n",
"Epoch: 25 \tTraining Loss: 12.503543 \tValidation Loss: 23.193912\n",
"Epoch: 26 \tTraining Loss: 12.051262 \tValidation Loss: 23.847077\n",
"Epoch: 27 \tTraining Loss: 11.625023 \tValidation Loss: 25.515326\n",
"Epoch: 28 \tTraining Loss: 11.351064 \tValidation Loss: 26.013914\n",
"Epoch: 29 \tTraining Loss: 10.817478 \tValidation Loss: 24.830195\n"
]
}
],
"source": [
"import torch.optim as optim\n",
"\n",
"criterion = nn.CrossEntropyLoss() # specify loss function\n",
"optimizer = optim.SGD(model.parameters(), lr=0.01) # specify optimizer\n",
"\n",
"n_epochs = 30 # number of epochs to train the model\n",
"train_loss_list = [] # list to store loss to visualize\n",
"valid_loss_min = np.Inf # track change in validation loss\n",
"\n",
"for epoch in range(n_epochs):\n",
" # Keep track of training and validation loss\n",
" train_loss = 0.0\n",
" valid_loss = 0.0\n",
"\n",
" # Train the model\n",
" model.train()\n",
" for data, target in train_loader:\n",
" # Move tensors to GPU if CUDA is available\n",
" if train_on_gpu:\n",
" data, target = data.cuda(), target.cuda()\n",
" # Clear the gradients of all optimized variables\n",
" optimizer.zero_grad()\n",
" # Forward pass: compute predicted outputs by passing inputs to the model\n",
" output = model(data)\n",
" # Calculate the batch loss\n",
" loss = criterion(output, target)\n",
" # Backward pass: compute gradient of the loss with respect to model parameters\n",
" loss.backward()\n",
" # Perform a single optimization step (parameter update)\n",
" optimizer.step()\n",
" # Update training loss\n",
" train_loss += loss.item() * data.size(0)\n",
"\n",
" # Validate the model\n",
" model.eval()\n",
" for data, target in valid_loader:\n",
" # Move tensors to GPU if CUDA is available\n",
" if train_on_gpu:\n",
" data, target = data.cuda(), target.cuda()\n",
" # Forward pass: compute predicted outputs by passing inputs to the model\n",
" output = model(data)\n",
" # Calculate the batch loss\n",
" loss = criterion(output, target)\n",
" # Update average validation loss\n",
" valid_loss += loss.item() * data.size(0)\n",
"\n",
" # Calculate average losses\n",
" train_loss = train_loss / len(train_loader)\n",
" valid_loss = valid_loss / len(valid_loader)\n",
" train_loss_list.append(train_loss)\n",
"\n",
" # Print training/validation statistics\n",
" print(\n",
" \"Epoch: {} \\tTraining Loss: {:.6f} \\tValidation Loss: {:.6f}\".format(\n",
" epoch, train_loss, valid_loss\n",
" )\n",
" )\n",
"\n",
" # Save model if validation loss has decreased\n",
" if valid_loss <= valid_loss_min:\n",
" print(\n",
" \"Validation loss decreased ({:.6f} --> {:.6f}). Saving model ...\".format(\n",
" valid_loss_min, valid_loss\n",
" )\n",
" )\n",
" torch.save(model.state_dict(), \"model_cifar.pt\")\n",
" valid_loss_min = valid_loss"
]
},
{
"cell_type": "markdown",
"id": "13e1df74",
"metadata": {},
"source": [
"Does overfit occur? If so, do an early stopping."
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Collecting matplotlibNote: you may need to restart the kernel to use updated packages.\n",
"\n",
" Obtaining dependency information for matplotlib from https://files.pythonhosted.org/packages/26/5a/27fd341e4510257789f19a4b4be8bb90d1113b8f176c3dab562b4f21466e/matplotlib-3.8.2-cp311-cp311-win_amd64.whl.metadata\n",
" Downloading matplotlib-3.8.2-cp311-cp311-win_amd64.whl.metadata (5.9 kB)\n",
"Collecting contourpy>=1.0.1 (from matplotlib)\n",
" Obtaining dependency information for contourpy>=1.0.1 from https://files.pythonhosted.org/packages/ca/2a/d197a412ec474391ee878b1218cf2fe9c6e963903755887fc5654c06636a/contourpy-1.2.0-cp311-cp311-win_amd64.whl.metadata\n",
" Downloading contourpy-1.2.0-cp311-cp311-win_amd64.whl.metadata (5.8 kB)\n",
"Collecting cycler>=0.10 (from matplotlib)\n",
" Obtaining dependency information for cycler>=0.10 from https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl.metadata\n",
" Downloading cycler-0.12.1-py3-none-any.whl.metadata (3.8 kB)\n",
"Collecting fonttools>=4.22.0 (from matplotlib)\n",
" Obtaining dependency information for fonttools>=4.22.0 from https://files.pythonhosted.org/packages/16/a2/3a113a948eabeb2031f1ae3f196a0a32cd5707046176937bba52a5b1ef6d/fonttools-4.45.1-cp311-cp311-win_amd64.whl.metadata\n",
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"Collecting pyparsing>=2.3.1 (from matplotlib)\n",
" Obtaining dependency information for pyparsing>=2.3.1 from https://files.pythonhosted.org/packages/39/92/8486ede85fcc088f1b3dba4ce92dd29d126fd96b0008ea213167940a2475/pyparsing-3.1.1-py3-none-any.whl.metadata\n",
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"Installing collected packages: pyparsing, kiwisolver, fonttools, cycler, contourpy, matplotlib\n",
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]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"[notice] A new release of pip is available: 23.2.1 -> 23.3.1\n",
"[notice] To update, run: C:\\Users\\arman\\AppData\\Local\\Microsoft\\WindowsApps\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\python.exe -m pip install --upgrade pip\n"
]
}
],
"source": [
"%pip install matplotlib"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "d39df818",
"metadata": {},
"outputs": [
{
"ename": "NameError",
"evalue": "name 'n_epochs' is not defined",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32mc:\\Users\\arman\\Desktop\\Cours_Centrale\\Apprentissage_profond\\BE2\\mod_4_6-td2\\TD2 Deep Learning_AS.ipynb Cell 19\u001b[0m line \u001b[0;36m3\n\u001b[0;32m <a href='vscode-notebook-cell:/c%3A/Users/arman/Desktop/Cours_Centrale/Apprentissage_profond/BE2/mod_4_6-td2/TD2%20Deep%20Learning_AS.ipynb#X24sZmlsZQ%3D%3D?line=0'>1</a>\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mmatplotlib\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mpyplot\u001b[39;00m \u001b[39mas\u001b[39;00m \u001b[39mplt\u001b[39;00m\n\u001b[1;32m----> <a href='vscode-notebook-cell:/c%3A/Users/arman/Desktop/Cours_Centrale/Apprentissage_profond/BE2/mod_4_6-td2/TD2%20Deep%20Learning_AS.ipynb#X24sZmlsZQ%3D%3D?line=2'>3</a>\u001b[0m plt\u001b[39m.\u001b[39mplot(\u001b[39mrange\u001b[39m(n_epochs), train_loss_list)\n\u001b[0;32m <a href='vscode-notebook-cell:/c%3A/Users/arman/Desktop/Cours_Centrale/Apprentissage_profond/BE2/mod_4_6-td2/TD2%20Deep%20Learning_AS.ipynb#X24sZmlsZQ%3D%3D?line=3'>4</a>\u001b[0m plt\u001b[39m.\u001b[39mxlabel(\u001b[39m\"\u001b[39m\u001b[39mEpoch\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[0;32m <a href='vscode-notebook-cell:/c%3A/Users/arman/Desktop/Cours_Centrale/Apprentissage_profond/BE2/mod_4_6-td2/TD2%20Deep%20Learning_AS.ipynb#X24sZmlsZQ%3D%3D?line=4'>5</a>\u001b[0m plt\u001b[39m.\u001b[39mylabel(\u001b[39m\"\u001b[39m\u001b[39mLoss\u001b[39m\u001b[39m\"\u001b[39m)\n",
"\u001b[1;31mNameError\u001b[0m: name 'n_epochs' is not defined"
]
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"\n",
"plt.plot(range(n_epochs), train_loss_list)\n",
"plt.xlabel(\"Epoch\")\n",
"plt.ylabel(\"Loss\")\n",
"plt.title(\"Performance of Model 1\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "11df8fd4",
"metadata": {},
"source": [
"Now loading the model with the lowest validation loss value\n"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "e93efdfc",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Test Loss: 20.845967\n",
"\n",
"Test Accuracy of airplane: 69% (695/1000)\n",
"Test Accuracy of automobile: 80% (806/1000)\n",
"Test Accuracy of bird: 55% (559/1000)\n",
"Test Accuracy of cat: 47% (471/1000)\n",
"Test Accuracy of deer: 54% (543/1000)\n",
"Test Accuracy of dog: 48% (484/1000)\n",
"Test Accuracy of frog: 73% (737/1000)\n",
"Test Accuracy of horse: 69% (699/1000)\n",
"Test Accuracy of ship: 80% (801/1000)\n",
"Test Accuracy of truck: 66% (665/1000)\n",
"\n",
"Test Accuracy (Overall): 64% (6460/10000)\n"
]
}
],
"source": [
"model.load_state_dict(torch.load(\"./model_cifar.pt\"))\n",
"\n",
"# track test loss\n",
"test_loss = 0.0\n",
"class_correct = list(0.0 for i in range(10))\n",
"class_total = list(0.0 for i in range(10))\n",
"\n",
"model.eval()\n",
"# iterate over test data\n",
"for data, target in test_loader:\n",
" # move tensors to GPU if CUDA is available\n",
" if train_on_gpu:\n",
" data, target = data.cuda(), target.cuda()\n",
" # forward pass: compute predicted outputs by passing inputs to the model\n",
" output = model(data)\n",
" # calculate the batch loss\n",
" loss = criterion(output, target)\n",
" # update test loss\n",
" test_loss += loss.item() * data.size(0)\n",
" # convert output probabilities to predicted class\n",
" _, pred = torch.max(output, 1)\n",
" # compare predictions to true label\n",
" correct_tensor = pred.eq(target.data.view_as(pred))\n",
" correct = (\n",
" np.squeeze(correct_tensor.numpy())\n",
" if not train_on_gpu\n",
" else np.squeeze(correct_tensor.cpu().numpy())\n",
" )\n",
" # calculate test accuracy for each object class\n",
" for i in range(batch_size):\n",
" label = target.data[i]\n",
" class_correct[label] += correct[i].item()\n",
" class_total[label] += 1\n",
"\n",
"# average test loss\n",
"test_loss = test_loss / len(test_loader)\n",
"print(\"Test Loss: {:.6f}\\n\".format(test_loss))\n",
"\n",
"for i in range(10):\n",
" if class_total[i] > 0:\n",
" print(\n",
" \"Test Accuracy of %5s: %2d%% (%2d/%2d)\"\n",
" % (\n",
" classes[i],\n",
" 100 * class_correct[i] / class_total[i],\n",
" np.sum(class_correct[i]),\n",
" np.sum(class_total[i]),\n",
" )\n",
" )\n",
" else:\n",
" print(\"Test Accuracy of %5s: N/A (no training examples)\" % (classes[i]))\n",
"\n",
"print(\n",
" \"\\nTest Accuracy (Overall): %2d%% (%2d/%2d)\"\n",
" % (\n",
" 100.0 * np.sum(class_correct) / np.sum(class_total),\n",
" np.sum(class_correct),\n",
" np.sum(class_total),\n",
" )\n",
")"
]
},
{
"cell_type": "markdown",
"id": "944991a2",
"metadata": {},
"source": [
"Build a new network with the following structure.\n",
"\n",
"- It has 3 convolutional layers of kernel size 3 and padding of 1.\n",
"- The first convolutional layer must output 16 channels, the second 32 and the third 64.\n",
"- At each convolutional layer output, we apply a ReLU activation then a MaxPool with kernel size of 2.\n",
"- Then, three fully connected layers, the first two being followed by a ReLU activation and a dropout whose value you will suggest.\n",
"- The first fully connected layer will have an output size of 512.\n",
"- The second fully connected layer will have an output size of 64.\n",
"\n",
"Compare the results obtained with this new network to those obtained previously."
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ConvNet(\n",
" (conv1): Conv2d(3, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
" (conv2): Conv2d(16, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
" (conv3): Conv2d(32, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
" (relu): ReLU()\n",
" (pool): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
" (fc1): Linear(in_features=1024, out_features=512, bias=True)\n",
" (fc2): Linear(in_features=512, out_features=64, bias=True)\n",
" (fc3): Linear(in_features=64, out_features=10, bias=True)\n",
" (dropout): Dropout(p=0.5, inplace=False)\n",
")\n"
]
}
],
"source": [
"import torch.nn as nn\n",
"import torch.nn.functional as F\n",
"\n",
"class ConvNet(nn.Module):\n",
" def __init__(self, dropout=0.5):\n",
" super(ConvNet, self).__init__()\n",
" self.conv1 = nn.Conv2d(3, 16, kernel_size=3, padding=1)\n",
" self.conv2 = nn.Conv2d(16, 32, kernel_size=3, padding=1)\n",
" self.conv3 = nn.Conv2d(32, 64, kernel_size=3, padding=1)\n",
" self.relu = nn.ReLU()\n",
" self.pool = nn.MaxPool2d(kernel_size=2, stride=2)\n",
" self.fc1 = nn.Linear(64 * 4 * 4, 512)\n",
" self.fc2 = nn.Linear(512, 64)\n",
" self.fc3 = nn.Linear(64, 10)\n",
" self.dropout = nn.Dropout(dropout)\n",
"\n",
" def forward(self, x):\n",
" x = self.pool(self.relu(self.conv1(x)))\n",
" x = self.pool(self.relu(self.conv2(x)))\n",
" x = self.pool(self.relu(self.conv3(x)))\n",
" x = x.view(-1, 64 * 4 * 4)\n",
" x = self.dropout(self.relu(self.fc1(x)))\n",
" x = self.dropout(self.relu(self.fc2(x)))\n",
" x = self.fc3(x)\n",
" return x\n",
" \n",
"\n",
"model = ConvNet()\n",
"print(model)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch: 0 \tTraining Loss: 22.624102 \tValidation Loss: 21.088585\n",
"Validation loss decreased (inf --> 21.088585). Saving model ...\n",
"Epoch: 1 \tTraining Loss: 21.682146 \tValidation Loss: 20.632328\n",
"Validation loss decreased (21.088585 --> 20.632328). Saving model ...\n",
"Epoch: 2 \tTraining Loss: 20.698419 \tValidation Loss: 19.688398\n",
"Validation loss decreased (20.632328 --> 19.688398). Saving model ...\n",
"Epoch: 3 \tTraining Loss: 19.881759 \tValidation Loss: 18.434344\n",
"Validation loss decreased (19.688398 --> 18.434344). Saving model ...\n",
"Epoch: 4 \tTraining Loss: 19.017723 \tValidation Loss: 18.182550\n",
"Validation loss decreased (18.434344 --> 18.182550). Saving model ...\n",
"Epoch: 5 \tTraining Loss: 18.293194 \tValidation Loss: 17.725371\n",
"Validation loss decreased (18.182550 --> 17.725371). Saving model ...\n",
"Epoch: 6 \tTraining Loss: 17.498131 \tValidation Loss: 17.464704\n",
"Validation loss decreased (17.725371 --> 17.464704). Saving model ...\n",
"Epoch: 7 \tTraining Loss: 16.712989 \tValidation Loss: 17.811778\n",
"Epoch: 8 \tTraining Loss: 16.061912 \tValidation Loss: 16.673797\n",
"Validation loss decreased (17.464704 --> 16.673797). Saving model ...\n",
"Epoch: 9 \tTraining Loss: 15.409771 \tValidation Loss: 16.482945\n",
"Validation loss decreased (16.673797 --> 16.482945). Saving model ...\n",
"Epoch: 10 \tTraining Loss: 14.850692 \tValidation Loss: 16.048368\n",
"Validation loss decreased (16.482945 --> 16.048368). Saving model ...\n",
"Epoch: 11 \tTraining Loss: 14.223474 \tValidation Loss: 16.164195\n",
"Epoch: 12 \tTraining Loss: 13.781104 \tValidation Loss: 16.040267\n",
"Validation loss decreased (16.048368 --> 16.040267). Saving model ...\n",
"Epoch: 13 \tTraining Loss: 13.252067 \tValidation Loss: 15.722175\n",
"Validation loss decreased (16.040267 --> 15.722175). Saving model ...\n",
"Epoch: 14 \tTraining Loss: 12.666087 \tValidation Loss: 15.928786\n",
"Epoch: 15 \tTraining Loss: 12.164211 \tValidation Loss: 16.114079\n"
]
},
{
"ename": "KeyboardInterrupt",
"evalue": "",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
"\u001b[1;32mc:\\Users\\arman\\Desktop\\Cours_Centrale\\Apprentissage_profond\\BE2\\mod_4_6-td2\\TD2 Deep Learning.ipynb Cell 24\u001b[0m line \u001b[0;36m2\n\u001b[0;32m <a href='vscode-notebook-cell:/c%3A/Users/arman/Desktop/Cours_Centrale/Apprentissage_profond/BE2/mod_4_6-td2/TD2%20Deep%20Learning.ipynb#X56sZmlsZQ%3D%3D?line=19'>20</a>\u001b[0m optimizer\u001b[39m.\u001b[39mzero_grad()\n\u001b[0;32m <a href='vscode-notebook-cell:/c%3A/Users/arman/Desktop/Cours_Centrale/Apprentissage_profond/BE2/mod_4_6-td2/TD2%20Deep%20Learning.ipynb#X56sZmlsZQ%3D%3D?line=20'>21</a>\u001b[0m \u001b[39m# Forward pass: compute predicted outputs by passing inputs to the model\u001b[39;00m\n\u001b[1;32m---> <a href='vscode-notebook-cell:/c%3A/Users/arman/Desktop/Cours_Centrale/Apprentissage_profond/BE2/mod_4_6-td2/TD2%20Deep%20Learning.ipynb#X56sZmlsZQ%3D%3D?line=21'>22</a>\u001b[0m output \u001b[39m=\u001b[39m model(data)\n\u001b[0;32m <a href='vscode-notebook-cell:/c%3A/Users/arman/Desktop/Cours_Centrale/Apprentissage_profond/BE2/mod_4_6-td2/TD2%20Deep%20Learning.ipynb#X56sZmlsZQ%3D%3D?line=22'>23</a>\u001b[0m \u001b[39m# Calculate the batch loss\u001b[39;00m\n\u001b[0;32m <a href='vscode-notebook-cell:/c%3A/Users/arman/Desktop/Cours_Centrale/Apprentissage_profond/BE2/mod_4_6-td2/TD2%20Deep%20Learning.ipynb#X56sZmlsZQ%3D%3D?line=23'>24</a>\u001b[0m loss \u001b[39m=\u001b[39m criterion(output, target)\n",
"File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\torch\\nn\\modules\\module.py:1518\u001b[0m, in \u001b[0;36mModule._wrapped_call_impl\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m 1516\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_compiled_call_impl(\u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs) \u001b[39m# type: ignore[misc]\u001b[39;00m\n\u001b[0;32m 1517\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m-> 1518\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_call_impl(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n",
"File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\torch\\nn\\modules\\module.py:1527\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m 1522\u001b[0m \u001b[39m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[0;32m 1523\u001b[0m \u001b[39m# this function, and just call forward.\u001b[39;00m\n\u001b[0;32m 1524\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_pre_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_pre_hooks\n\u001b[0;32m 1525\u001b[0m \u001b[39mor\u001b[39;00m _global_backward_pre_hooks \u001b[39mor\u001b[39;00m _global_backward_hooks\n\u001b[0;32m 1526\u001b[0m \u001b[39mor\u001b[39;00m _global_forward_hooks \u001b[39mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[1;32m-> 1527\u001b[0m \u001b[39mreturn\u001b[39;00m forward_call(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[0;32m 1529\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m 1530\u001b[0m result \u001b[39m=\u001b[39m \u001b[39mNone\u001b[39;00m\n",
"\u001b[1;32mc:\\Users\\arman\\Desktop\\Cours_Centrale\\Apprentissage_profond\\BE2\\mod_4_6-td2\\TD2 Deep Learning.ipynb Cell 24\u001b[0m line \u001b[0;36m2\n\u001b[0;32m <a href='vscode-notebook-cell:/c%3A/Users/arman/Desktop/Cours_Centrale/Apprentissage_profond/BE2/mod_4_6-td2/TD2%20Deep%20Learning.ipynb#X56sZmlsZQ%3D%3D?line=19'>20</a>\u001b[0m x \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mpool(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mrelu(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mconv3(x)))\n\u001b[0;32m <a href='vscode-notebook-cell:/c%3A/Users/arman/Desktop/Cours_Centrale/Apprentissage_profond/BE2/mod_4_6-td2/TD2%20Deep%20Learning.ipynb#X56sZmlsZQ%3D%3D?line=20'>21</a>\u001b[0m x \u001b[39m=\u001b[39m x\u001b[39m.\u001b[39mview(\u001b[39m-\u001b[39m\u001b[39m1\u001b[39m, \u001b[39m64\u001b[39m \u001b[39m*\u001b[39m \u001b[39m4\u001b[39m \u001b[39m*\u001b[39m \u001b[39m4\u001b[39m)\n\u001b[1;32m---> <a href='vscode-notebook-cell:/c%3A/Users/arman/Desktop/Cours_Centrale/Apprentissage_profond/BE2/mod_4_6-td2/TD2%20Deep%20Learning.ipynb#X56sZmlsZQ%3D%3D?line=21'>22</a>\u001b[0m x \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdropout(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mrelu(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mfc1(x)))\n\u001b[0;32m <a href='vscode-notebook-cell:/c%3A/Users/arman/Desktop/Cours_Centrale/Apprentissage_profond/BE2/mod_4_6-td2/TD2%20Deep%20Learning.ipynb#X56sZmlsZQ%3D%3D?line=22'>23</a>\u001b[0m x \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdropout(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mrelu(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mfc2(x)))\n\u001b[0;32m <a href='vscode-notebook-cell:/c%3A/Users/arman/Desktop/Cours_Centrale/Apprentissage_profond/BE2/mod_4_6-td2/TD2%20Deep%20Learning.ipynb#X56sZmlsZQ%3D%3D?line=23'>24</a>\u001b[0m x \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mfc3(x)\n",
"File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\torch\\nn\\modules\\module.py:1518\u001b[0m, in \u001b[0;36mModule._wrapped_call_impl\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m 1516\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_compiled_call_impl(\u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs) \u001b[39m# type: ignore[misc]\u001b[39;00m\n\u001b[0;32m 1517\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m-> 1518\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_call_impl(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n",
"File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\torch\\nn\\modules\\module.py:1527\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m 1522\u001b[0m \u001b[39m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[0;32m 1523\u001b[0m \u001b[39m# this function, and just call forward.\u001b[39;00m\n\u001b[0;32m 1524\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_pre_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_pre_hooks\n\u001b[0;32m 1525\u001b[0m \u001b[39mor\u001b[39;00m _global_backward_pre_hooks \u001b[39mor\u001b[39;00m _global_backward_hooks\n\u001b[0;32m 1526\u001b[0m \u001b[39mor\u001b[39;00m _global_forward_hooks \u001b[39mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[1;32m-> 1527\u001b[0m \u001b[39mreturn\u001b[39;00m forward_call(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[0;32m 1529\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m 1530\u001b[0m result \u001b[39m=\u001b[39m \u001b[39mNone\u001b[39;00m\n",
"File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\torch\\nn\\modules\\linear.py:114\u001b[0m, in \u001b[0;36mLinear.forward\u001b[1;34m(self, input)\u001b[0m\n\u001b[0;32m 113\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mforward\u001b[39m(\u001b[39mself\u001b[39m, \u001b[39minput\u001b[39m: Tensor) \u001b[39m-\u001b[39m\u001b[39m>\u001b[39m Tensor:\n\u001b[1;32m--> 114\u001b[0m \u001b[39mreturn\u001b[39;00m F\u001b[39m.\u001b[39;49mlinear(\u001b[39minput\u001b[39;49m, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mweight, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mbias)\n",
"\u001b[1;31mKeyboardInterrupt\u001b[0m: "
]
}
],
"source": [
"criterion = nn.CrossEntropyLoss() # specify loss function\n",
"optimizer = optim.SGD(model.parameters(), lr=0.01) # specify optimizer\n",
"\n",
"n_epochs = 30 # number of epochs to train the model\n",
"train_loss_list = [] # list to store loss to visualize\n",
"valid_loss_min = np.Inf # track change in validation loss\n",
"\n",
"for epoch in range(n_epochs):\n",
" # Keep track of training and validation loss\n",
" train_loss = 0.0\n",
" valid_loss = 0.0\n",
"\n",
" # Train the model\n",
" model.train()\n",
" for data, target in train_loader:\n",
" # Move tensors to GPU if CUDA is available\n",
" if train_on_gpu:\n",
" data, target = data.cuda(), target.cuda()\n",
" # Clear the gradients of all optimized variables\n",
" optimizer.zero_grad()\n",
" # Forward pass: compute predicted outputs by passing inputs to the model\n",
" output = model(data)\n",
" # Calculate the batch loss\n",
" loss = criterion(output, target)\n",
" # Backward pass: compute gradient of the loss with respect to model parameters\n",
" loss.backward()\n",
" # Perform a single optimization step (parameter update)\n",
" optimizer.step()\n",
" # Update training loss\n",
" train_loss += loss.item() * data.size(0)\n",
"\n",
" # Validate the model\n",
" model.eval()\n",
" for data, target in valid_loader:\n",
" # Move tensors to GPU if CUDA is available\n",
" if train_on_gpu:\n",
" data, target = data.cuda(), target.cuda()\n",
" # Forward pass: compute predicted outputs by passing inputs to the model\n",
" output = model(data)\n",
" # Calculate the batch loss\n",
" loss = criterion(output, target)\n",
" # Update average validation loss\n",
" valid_loss += loss.item() * data.size(0)\n",
"\n",
" # Calculate average losses\n",
" train_loss = train_loss / len(train_loader)\n",
" valid_loss = valid_loss / len(valid_loader)\n",
" train_loss_list.append(train_loss)\n",
"\n",
" # Print training/validation statistics\n",
" print(\n",
" \"Epoch: {} \\tTraining Loss: {:.6f} \\tValidation Loss: {:.6f}\".format(\n",
" epoch, train_loss, valid_loss\n",
" )\n",
" )\n",
"\n",
" # Save model if validation loss has decreased\n",
" if valid_loss <= valid_loss_min:\n",
" print(\n",
" \"Validation loss decreased ({:.6f} --> {:.6f}). Saving model ...\".format(\n",
" valid_loss_min, valid_loss\n",
" )\n",
" )\n",
" torch.save(model.state_dict(), \"model_cifar.pt\")\n",
" valid_loss_min = valid_loss"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Test Loss: 16.104820\n",
"\n",
"Test Accuracy of airplane: 81% (815/1000)\n",
"Test Accuracy of automobile: 81% (817/1000)\n",
"Test Accuracy of bird: 55% (559/1000)\n",
"Test Accuracy of cat: 49% (490/1000)\n",
"Test Accuracy of deer: 72% (724/1000)\n",
"Test Accuracy of dog: 59% (597/1000)\n",
"Test Accuracy of frog: 79% (797/1000)\n",
"Test Accuracy of horse: 81% (817/1000)\n",
"Test Accuracy of ship: 82% (827/1000)\n",
"Test Accuracy of truck: 83% (830/1000)\n",
"\n",
"Test Accuracy (Overall): 72% (7273/10000)\n"
]
}
],
"source": [
"model.load_state_dict(torch.load(\"./model_cifar.pt\"))\n",
"\n",
"# track test loss\n",
"test_loss = 0.0\n",
"class_correct = list(0.0 for i in range(10))\n",
"class_total = list(0.0 for i in range(10))\n",
"\n",
"model.eval()\n",
"# iterate over test data\n",
"for data, target in test_loader:\n",
" # move tensors to GPU if CUDA is available\n",
" if train_on_gpu:\n",
" data, target = data.cuda(), target.cuda()\n",
" # forward pass: compute predicted outputs by passing inputs to the model\n",
" output = model(data)\n",
" # calculate the batch loss\n",
" loss = criterion(output, target)\n",
" # update test loss\n",
" test_loss += loss.item() * data.size(0)\n",
" # convert output probabilities to predicted class\n",
" _, pred = torch.max(output, 1)\n",
" # compare predictions to true label\n",
" correct_tensor = pred.eq(target.data.view_as(pred))\n",
" correct = (\n",
" np.squeeze(correct_tensor.numpy())\n",
" if not train_on_gpu\n",
" else np.squeeze(correct_tensor.cpu().numpy())\n",
" )\n",
" # calculate test accuracy for each object class\n",
" for i in range(batch_size):\n",
" label = target.data[i]\n",
" class_correct[label] += correct[i].item()\n",
" class_total[label] += 1\n",
"\n",
"# average test loss\n",
"test_loss = test_loss / len(test_loader)\n",
"print(\"Test Loss: {:.6f}\\n\".format(test_loss))\n",
"\n",
"for i in range(10):\n",
" if class_total[i] > 0:\n",
" print(\n",
" \"Test Accuracy of %5s: %2d%% (%2d/%2d)\"\n",
" % (\n",
" classes[i],\n",
" 100 * class_correct[i] / class_total[i],\n",
" np.sum(class_correct[i]),\n",
" np.sum(class_total[i]),\n",
" )\n",
" )\n",
" else:\n",
" print(\"Test Accuracy of %5s: N/A (no training examples)\" % (classes[i]))\n",
"\n",
"print(\n",
" \"\\nTest Accuracy (Overall): %2d%% (%2d/%2d)\"\n",
" % (\n",
" 100.0 * np.sum(class_correct) / np.sum(class_total),\n",
" np.sum(class_correct),\n",
" np.sum(class_total),\n",
" )\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Le modèle CNN obtenu avec 3 couches convolutives a, en moyenne, de meilleures performances que le modèle initial. Il y a bien sur l'overall une différence de 8 points de pourcentage, mais certaines classes comme bird, cat ou dog ne font pas montre de très bons résultats."
]
},
{
"cell_type": "markdown",
"id": "bc381cf4",
"metadata": {},
"source": [
"## Exercise 2: Quantization: try to compress the CNN to save space\n",
"\n",
"Quantization doc is available from https://pytorch.org/docs/stable/quantization.html#torch.quantization.quantize_dynamic\n",
" \n",
"The Exercise is to quantize post training the above CNN model. Compare the size reduction and the impact on the classification accuracy \n",
"\n",
"\n",
"The size of the model is simply the size of the file."
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "ef623c26",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"model: fp32 \t Size (KB): 102523.238\n"
]
},
{
"data": {
"text/plain": [
"102523238"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import os\n",
"\n",
"\n",
"def print_size_of_model(model, label=\"\"):\n",
" torch.save(model.state_dict(), \"temp.p\")\n",
" size = os.path.getsize(\"temp.p\")\n",
" print(\"model: \", label, \" \\t\", \"Size (KB):\", size / 1e3)\n",
" os.remove(\"temp.p\")\n",
" return size\n",
"\n",
"\n",
"print_size_of_model(model, \"fp32\")"
]
},
{
"cell_type": "markdown",
"id": "05c4e9ad",
"metadata": {},
"source": [
"Post training quantization example"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "c4c65d4b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"model: int8 \t Size (KB): 96379.996\n"
]
},
{
"data": {
"text/plain": [
"96379996"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import torch.quantization\n",
"\n",
"\n",
"quantized_model = torch.quantization.quantize_dynamic(model, dtype=torch.qint8)\n",
"print_size_of_model(quantized_model, \"int8\")"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Test Loss: 16.107577\n",
"\n",
"Test Accuracy of airplane: 81% (812/1000)\n",
"Test Accuracy of automobile: 81% (818/1000)\n",
"Test Accuracy of bird: 55% (556/1000)\n",
"Test Accuracy of cat: 48% (487/1000)\n",
"Test Accuracy of deer: 72% (727/1000)\n",
"Test Accuracy of dog: 60% (600/1000)\n",
"Test Accuracy of frog: 79% (798/1000)\n",
"Test Accuracy of horse: 81% (817/1000)\n",
"Test Accuracy of ship: 82% (828/1000)\n",
"Test Accuracy of truck: 82% (829/1000)\n",
"\n",
"Test Accuracy (Overall): 72% (7272/10000)\n"
]
}
],
"source": [
"# track test loss\n",
"test_loss = 0.0\n",
"class_correct = list(0.0 for i in range(10))\n",
"class_total = list(0.0 for i in range(10))\n",
"\n",
"quantized_model.eval()\n",
"# iterate over test data\n",
"for data, target in test_loader:\n",
" # move tensors to GPU if CUDA is available\n",
" if train_on_gpu:\n",
" data, target = data.cuda(), target.cuda()\n",
" # forward pass: compute predicted outputs by passing inputs to the model\n",
" output = quantized_model(data)\n",
" # calculate the batch loss\n",
" loss = criterion(output, target)\n",
" # update test loss\n",
" test_loss += loss.item() * data.size(0)\n",
" # convert output probabilities to predicted class\n",
" _, pred = torch.max(output, 1)\n",
" # compare predictions to true label\n",
" correct_tensor = pred.eq(target.data.view_as(pred))\n",
" correct = (\n",
" np.squeeze(correct_tensor.numpy())\n",
" if not train_on_gpu\n",
" else np.squeeze(correct_tensor.cpu().numpy())\n",
" )\n",
" # calculate test accuracy for each object class\n",
" for i in range(batch_size):\n",
" label = target.data[i]\n",
" class_correct[label] += correct[i].item()\n",
" class_total[label] += 1\n",
"\n",
"# average test loss\n",
"test_loss = test_loss / len(test_loader)\n",
"print(\"Test Loss: {:.6f}\\n\".format(test_loss))\n",
"\n",
"for i in range(10):\n",
" if class_total[i] > 0:\n",
" print(\n",
" \"Test Accuracy of %5s: %2d%% (%2d/%2d)\"\n",
" % (\n",
" classes[i],\n",
" 100 * class_correct[i] / class_total[i],\n",
" np.sum(class_correct[i]),\n",
" np.sum(class_total[i]),\n",
" )\n",
" )\n",
" else:\n",
" print(\"Test Accuracy of %5s: N/A (no training examples)\" % (classes[i]))\n",
"\n",
"print(\n",
" \"\\nTest Accuracy (Overall): %2d%% (%2d/%2d)\"\n",
" % (\n",
" 100.0 * np.sum(class_correct) / np.sum(class_total),\n",
" np.sum(class_correct),\n",
" np.sum(class_total),\n",
" )\n",
")"
]
},
{
"cell_type": "markdown",
"id": "7b108e17",
"metadata": {},
"source": [
"For each class, compare the classification test accuracy of the initial model and the quantized model. Also give the overall test accuracy for both models."
]
},
{
"cell_type": "markdown",
"id": "a0a34b90",
"metadata": {},
"source": [
"Try training aware quantization to mitigate the impact on the accuracy (doc available here https://pytorch.org/docs/stable/quantization.html#torch.quantization.quantize_dynamic)"
]
},
{
"cell_type": "markdown",
"id": "201470f9",
"metadata": {},
"source": [
"## Exercise 3: working with pre-trained models.\n",
"\n",
"PyTorch offers several pre-trained models https://pytorch.org/vision/0.8/models.html \n",
"We will use ResNet50 trained on ImageNet dataset (https://www.image-net.org/index.php). Use the following code with the files `imagenet-simple-labels.json` that contains the imagenet labels and the image dog.png that we will use as test.\n"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"model: fp32 \t Size (KB): 102523.238\n"
]
},
{
"data": {
"text/plain": [
"102523238"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import os\n",
"\n",
"\n",
"def print_size_of_model(model, label=\"\"):\n",
" torch.save(model.state_dict(), \"temp.p\")\n",
" size = os.path.getsize(\"temp.p\")\n",
" print(\"model: \", label, \" \\t\", \"Size (KB):\", size / 1e3)\n",
" os.remove(\"temp.p\")\n",
" return size\n",
"\n",
"\n",
"print_size_of_model(model, \"fp32\")"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"from torchvision import datasets, transforms\n",
"from torch.utils.data.sampler import SubsetRandomSampler"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "b4d13080",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Predicted class is: Flat-Coated Retriever\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import json\n",
"from PIL import Image\n",
"\n",
"# Choose an image to pass through the model\n",
"test_image = \"dog_but_cooler.png\"\n",
"\n",
"# Configure matplotlib for pretty inline plots\n",
"#%matplotlib inline\n",
"#%config InlineBackend.figure_format = 'retina'\n",
"\n",
"# Prepare the labels\n",
"with open(\"imagenet-simple-labels.json\") as f:\n",
" labels = json.load(f)\n",
"\n",
"# First prepare the transformations: resize the image to what the model was trained on and convert it to a tensor\n",
"data_transform = transforms.Compose(\n",
" [\n",
" transforms.Resize((224, 224)),\n",
" transforms.ToTensor(),\n",
" transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]),\n",
" ]\n",
")\n",
"# Load the image\n",
"\n",
"image = Image.open(test_image)\n",
"plt.imshow(image), plt.xticks([]), plt.yticks([])\n",
"\n",
"# Now apply the transformation, expand the batch dimension, and send the image to the GPU\n",
"# image = data_transform(image).unsqueeze(0).cuda()\n",
"image = data_transform(image).unsqueeze(0)\n",
"\n",
"# Download the model if it's not there already. It will take a bit on the first run, after that it's fast\n",
"model = models.resnet50(pretrained=True)\n",
"# Send the model to the GPU\n",
"# model.cuda()\n",
"# Set layers such as dropout and batchnorm in evaluation mode\n",
"model.eval()\n",
"\n",
"# Get the 1000-dimensional model output\n",
"out = model(image)\n",
"# Find the predicted class\n",
"print(\"Predicted class is: {}\".format(labels[out.argmax()]))"
]
},
{
"cell_type": "markdown",
"id": "184cfceb",
"metadata": {},
"source": [
"Experiments:\n",
"\n",
"Study the code and the results obtained. Possibly add other images downloaded from the internet.\n",
"\n",
"What is the size of the model? Quantize it and then check if the model is still able to correctly classify the other images.\n",
"\n",
"Experiment with other pre-trained CNN models.\n",
"\n",
" \n"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"model: ResNet \t Size (KB): 102523.238\n"
]
},
{
"data": {
"text/plain": [
"102523238"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"print_size_of_model(model, \"ResNet\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Le modèle de ResNet fait un peu plus de 0.1 Go"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"model: smoll_resnet \t Size (KB): 96379.996\n"
]
},
{
"data": {
"text/plain": [
"96379996"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import torch.quantization\n",
"\n",
"\n",
"quantized_model = torch.quantization.quantize_dynamic(model, dtype=torch.qint8)\n",
"print_size_of_model(quantized_model, \"smoll_resnet\")"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"5.992048358831584"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"(102523.238 - 96379.996)/102523.238 *100"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Le processus de quantization permet une réduction de la taille du modèle de 6%"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Predicted class is: Flat-Coated Retriever\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import json\n",
"from PIL import Image\n",
"\n",
"# Choose an image to pass through the model\n",
"test_image = \"dog_but_cooler.png\"\n",
"\n",
"# Configure matplotlib for pretty inline plots\n",
"#%matplotlib inline\n",
"#%config InlineBackend.figure_format = 'retina'\n",
"\n",
"# Prepare the labels\n",
"with open(\"imagenet-simple-labels.json\") as f:\n",
" labels = json.load(f)\n",
"\n",
"# First prepare the transformations: resize the image to what the model was trained on and convert it to a tensor\n",
"data_transform = transforms.Compose(\n",
" [\n",
" transforms.Resize((224, 224)),\n",
" transforms.ToTensor(),\n",
" transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]),\n",
" ]\n",
")\n",
"# Load the image\n",
"\n",
"image = Image.open(test_image)\n",
"plt.imshow(image), plt.xticks([]), plt.yticks([])\n",
"\n",
"# Now apply the transformation, expand the batch dimension, and send the image to the GPU\n",
"# image = data_transform(image).unsqueeze(0).cuda()\n",
"image = data_transform(image).unsqueeze(0)\n",
"\n",
"# Download the model if it's not there already. It will take a bit on the first run, after that it's fast\n",
"model = quantized_model\n",
"# Send the model to the GPU\n",
"# model.cuda()\n",
"# Set layers such as dropout and batchnorm in evaluation mode\n",
"model.eval()\n",
"\n",
"# Get the 1000-dimensional model output\n",
"out = model(image)\n",
"# Find the predicted class\n",
"print(\"Predicted class is: {}\".format(labels[out.argmax()]))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Le modèle quantized parvient à prédire la même classe que le modèle initial pour la même image"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Essayons le modèle Squeeze net de Pytorch"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\arman\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\torchvision\\models\\_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.\n",
" warnings.warn(\n",
"C:\\Users\\arman\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\torchvision\\models\\_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=SqueezeNet1_0_Weights.IMAGENET1K_V1`. You can also use `weights=SqueezeNet1_0_Weights.DEFAULT` to get the most up-to-date weights.\n",
" warnings.warn(msg)\n",
"Downloading: \"https://download.pytorch.org/models/squeezenet1_0-b66bff10.pth\" to C:\\Users\\arman/.cache\\torch\\hub\\checkpoints\\squeezenet1_0-b66bff10.pth\n",
"100.0%\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Predicted class is: Tibetan Mastiff\n"
]
},
{
"data": {
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hxJMD0AqLo65WJBTO1eLp5JBru91ycXbBZrNjs92wOduyWa9Zrde4ymGto6rECBkj3qRglLKrKa0E8FTiA6EUxWy8ztMuQLDResqSziHmHG4tnKbp9WXoO1kpNWN1i+EWTzNEtEoTfrTMnM3hPYt/Q/SeMYyEIJidVjEvPIPWFps0MSl8zgSiFD6IFxNiyMmNQAyRJAguSdlpUzsMPSlBZS21UajkZWIn8eysDYK9Wou1mrqp2aw0Zw8Mxoo3K+FMzAmcRN92JAJ+9Hg/0OSNOESP0gbnHM4alHNELQA0GYfUWjzCEML0b6UUyXtUkqx2P4zY9o6hvcUYw2F/JKSI0Zb333rIyl3wvR/9Sj6LzqG6gqio65rhcItzFxgFKcTslaY8vmKIEjmLrwrskT2nvNGnFLFakwh5QwWjxQ4YracoxFo9jZFSyGb5JY83MlL7LmED4jarRGUt2mqMk7Bst96yWjWs1w1N01A3NevVmqp2uLpGGZONi7jqh+ORyxd7DoeWvh859iNd19MPIz5EYpRJ5VPM+7BYfCXzOK8JMSZGGVAlAybhyNJen3yWsgAUSp1iPwX4T6hpoei8o5x+dorH8l+as90Z1kq6Vecwqri5xlqstbILhzjha//hv/qfc/HwAQ8fPqBZN7haaA+SIbQYk42QnXE5tTRG0zAs8Cvy+krTv0g51Cke7v1DaZVD3vKJxe/unZvp9+nEcC/flWZ3a8LJYoqE4PE+kKInRvGSvPcnRiouDGQZZ21yqt7IwvBjZBw8IcIYBH8KUUIoSoCpNEorRh8YxjAZ4hATIQxEfAalYWsrqrpitaqpnMUahTUGkzdQnUOucRwZvSdGzxiizH+tUCrm+5VESWUMTbVGTXB0wNqKwiggJXLyD6UMpIgGVFWRdDvd+7xRCh3DjwMpjKTsqWglnuhuu+Wzz79g9JJMcAasTqQY0EoMhzMSktbOUtc1fd/jnEMlCfFCiIx+lDWhT+eAjsi610oAdSWel9BCwvScnFLYnC3VWq5fq3I9M3Rx31346443MlJKWS4ePOJw3PPu24/5+rvvsF2vqVdikFZNk11YaIeeY9vS9T0vb645tgPHrud47BjGUTInIeJ9moC4addMiVRuiGw4JpdIkVQBjrXcQDEG8iNlA1c5DS8ea4LsWSRAlxirxP3l5ykcyRiVSmQmE+U0ktFURCJJC6ZU2YrtZotRajJCitlDcdrgrKHrR2KIVMYRGfkn/+If8uStt3BWUr/lNiU81BkbuAcGUPCAcgv5U6ngVgW5Wv6r/Pv100PlUKV4pPcB1PtGo5xreVXzNyV0KpnXbBwVhOjpuiOHg4QPKmNxiQI4swDj8+3lbKX3nsEPxCAJmOATow/4GPFRZcMhoao12afXYLUhJU3thMtVVRXaGoyxU7gVYsSPA8MwEoOn61vxKDOfSjwA0CZR15btpsa5VU4kmPlZ5J3MGDA6SZZvHFEoXLXGB3nGKuOvMv89TROI4yAbrluBvpNpqHJyooTeWnN3e4Nzmqu7IzFGQkiMw8jFg8d89Olzhm6PchvQibYbIGXQH0VlDMEP1JtzqtoRY6BylcyIBH4UA2dU4UIGJGctlA0xxnIpMSVUjmJQgm0qpdAkVN6ktUKwTRRamfy3mjbRL3u8kZEyxnB2fgEkHj58xON33iF4z7498tmLFxzbluOxo+1Gun6YJk4IObVZJmF2g1KeSVN4svCCkppDrtdlue6rHhcMRS0M1v0jMS92JS9MoJ7Ou71sEvO5nLICjlaSMVyv1my3OzbbM84fnrParDjb7disVrz44hlxzFmrTEos2Q9tBIM7tj0hBlxd4YcOo+Hho3NCzjgVnk7ImS+ltexcJ/dRBuP1z2lOEedxWoRpBQT/DR/kNLN4at6WG8F0LWn5cXX6c/E+px1IY5QVvo0t45MyViUZ3sEnvI8Synsh4no/EmOiH/3MXQLhFmV8UyCENdZYmlWFVokheMI4SrgVRoKHq9sD+7Zj9J7gvRgVrYUflLGappGFayySJc4ZSQnzLM5aCp9LBlnnMUtYKx6ENmWeJwH5k8nmejb6MUhyRoVA6HtMpYlDi0ohh3kabSQporXAK8GPYCxtP5CCZ+iPxOg5u3jMxYMnvP3e1/mn/+p/wUe/+il/9qf/Zo4mUuLibDNl11ZNg/cj1lmhIqSU8WQxLIIVxilzrLOxmYjGzLw9vUj6qCgwh8mheIZ+0SRcTshopSbc8cscb2akrCxY7wM/+OFf8fOf/5yUEqOP4m4n4U0lBOzWWqOMnSZh8WSWPIriMZWVpPINlzDiPtnr/r9LGvvVkO3VI5Eyli6MdJ2ziiZP9tVqRdOs2K13bHc7NudnXJzJz7vdjlWzoq4bnHPYSuOcmdLyEPnjL56SinueKQFpYktrnJNQ0HuPWjVopTjc3squbQWPS9mFFpCezNEp0PPpvbw6JvM7ltha+VVKC8/yNxxLMmn5pmUAqNTySsrGkr3R5a/S6UaSgJAiWC0cuDHivSRCRh8IPuJ9oB+HHMoI/uMqh81jfp69zXL/BUcxzmGspe97gh+IyXB1ecPnL66Eb6U1tauoKkuII05HXKUxqxWryk6Lsqocu7MNlTOApM9LhtN7n4HtQr3InLQoY2NcpHKOlLx44eIk5jVTEaLBe49wzCULapISCCR4Ygg4XaGNnSGMKXmS11JKefOSsUop0B1vURqaswc8euc9xvaSs7M1D84u6I9H1o2mpsfEyKOLLVZrMeR1Tcpjl8jhdv5v6QiUMFOcrfycC36ZM8CalP/IdVslILnJ79Fa46zB5ooBozXxDaQN3jDcy9NRQd8NhGHM7roiJDPdnNYzj6JY3OLaL72jpNRiIkiWq4RJ5IdZ1kdxD+97SuK2z+nq4hEpJRiLcw5jrKSJmxWbzYbdTtLzZ7tzdrszttsNu92a1UqMUOUqrLUoazI3RgZ3AqKVzl5Djr0VwvsaB6ypUYB1VkDXlMFFpaiqSsBi73Pcr7m+vpKQNntN4mKT+TjCGypZvsKFmh7C9GBYhH7zOEHBNRZjx6teaHF3iick1Iy0GOsZcF8+k/vmrhisCAJOp4jJnlxCse96fvVpixlXVFoY4MZa1qsqA6s6c6ZkF/cx4WNiHAN9N3I3HjLpUQx5VVm22zXrqkYrzcubO1abbQ49ErXJzG8jwO7QezZNTbNdTwbQGY1Skn11zsniUoDKFQtJRqUyGmMg5bKvphK2+LEP7LYVzimGYZCNT1liCng/opSmbVu8B1uvJHRM5bnIOhmHAe9HarVDVTUKQ12v8oOJsi6cxSTJNtracmjvUDhS8GwePGD36AlP+sCHP/qUcezY7HY8eXjO137nfaypUBr+3t/9A24uL9EqcbbbUleOEAK6MgLwZzxPZ1Z5oXhI2D3Pg/Keso5NHjOd16/RKnu5Bms0VimUAXkcggGm3xaZUyHgmnUzs7xgPSnlGBpyHi0vkhjnEgtjhDqf4+ykc4pYLb0pyUJpijel82SRhSwLMeZMhcYYN+0MTbNitVmz2e44Oz/n/Oycs7MzNps1q/WKzbqhqR2uEsNlrcmW/h6R8gRMX9wLc2o8B0X5uiD4yDB47LrJE1CTYsqpaXGB67qeWMwpJrQxXF7dCAeGKJPWqCm1bkzJGM3kv2KA5fvTjLdNYQSnMX86/buEX4lTE7P00nQO9UoYXDywif6YXv3MEkgvG8WE96VIVOBTZLNuONvt0HHMVAJPO3b4GKX+M3tHMRaaxFw+obVi2ziaZoVzBussdWUpodbbTx5IrZzR1JXj/GydOUDZEwLOdysqayggmCrzKBsPRSYb6pmv5ayiqW3OSAJRPJmqrrBGKCfOWarKMQwjzlWS7daZF+cM1kpa/nTcpNbNrdcS3sXE/sUz8D6XmEh4GGPADwPohs7LGbrRo1TNOAxc7C7YXjzmSdD86geQQqCuG2L0VM7yh9/+Fp/86pdYo4h+pO8O1OuGyhqGrket3YSPpRQQCpHJ2WCmzVk4UHJNJpf0iMcrGKAxRrLoSrJ8kUgfoIuSuDEJNnVF7SBm8u6XOd7ISKFgHEecdQujqk5dwfygDTOZT6yunoHpyZsiZygW3hUC3KWYrXLOcDV1w3q9ZrXZcLbdcXF2zvbinN3unO1uw24rZM+qrnFuNkA2/yl4mM5GKOVrV/emzfKYDEAqt3vPc5hWvsaPI90wsN4oQop59xbeT4oxF1rWkJJkLH3AWsPd7Z4wjmir8uKXMFTwgCDniWXnvUcfyGPNFHItMaH5Hu47XuUj5fV0zytSIGnpyeOSZ7yIHH/DUYxnzu7lsLfYV5UUaui4vRoEOFfC4C4kyBIeJKuztyo4kDEzRcRVDmfleVojnqXJ3tB268R7DYntZpPLPYQOoJVi6EeMdjnTGqR+TWliFI9V2NESTh7bAe8zaA50RCqnMCZRVZa+9wz9gHOWROBwGKgqg7MVIPyucRyFuzdGwECuBxUwPs/FlEjDKDw2a0i3e4xzQtpMkhmMKW/bruKmjXx+e8UXL+7YPd5yc3PNed8LzrTd4eqaoT/QrC5oaie8RKMJY08IIyGODN2BpnZs1ivavgXkuuQ6M16WhIRN8W7JtYhkj38x98eYS4PGHvJzS0DUGrQl+IDW8NZui6sd2iii+i1hUgoI3kvsnWdtuaCUkpCmlCKoYqhgKmrPgN2SRIhSwqWqKlxd0ayk+Pbs7IyLi3POd2c8eHDBbrej2WyoVithoDuDsxptyYzz4mbOafnyZ9rVEa7HEnSegtKF7Vm6odNizOzzktkri7U4MEorxmHEj0EeYL5X8riU7FzT1JLqT5LZrOqK/tgyti2r3apc1BT6+Zxe0rlmLX/r5MpMRqNsEieu0cKUZAMzJQEp4eB9f2px10plD3kO+1L2cF8doFOjKNFSzvIoySylmFAhsWo0tXNEwBqLUuLlVM6h82YSU4KkpURGSbg2YTy5LMVVOSRXJQwlk2ghJZPxvzFjSci/Q8M4JioHq2aFMRIJyD3aBS6jqWtHXUtuMobI6BM+BoxOGB2z4U3ZI5Cx744jMfUorQjeZ8Df571ZwGf5jvk5qhQYugPZ3aZabwneE1IkeuF4oRTOgTIVt7d7XlzeoPQKReLy8pIHV8+Joade1TTrDcfrK5xr2K5rVnUl36VhHHqs0bTHPcas+M4ffIuYPCD1RcOYr5VcKxsz0z1JAkjKwmTT9VE+o3zIiJQkv0rBuFZCGynZvIebNQ/XDWYxvb7s8cZGKoWIXTWv7N4SPRe3sMxUQM8LQQFvv/UWv/8H32G7O2d3tuXi0TlnZzs26xXr1QpXCU3fWoMr4WEhoSmmOiqlWFARpquDhIByiXlB5d2r8EHkyvXCnZjvj3v8kJSErqCSpKuTEg/phIOlFMMw4r2whFNMM8CbT6ZRkzRHSpJkUArGsaNtD2zOtnncCs6lsOhcVyZM/QLCS5JoDr1UovAO832ok2tTaolNLbyxCb961VRN7lZ2tco5Stb1Nx0lDFUqQQrozM8KQCRR1RUuUy0K3lHS+ClvcsZYWcBRTUkNwRbNlBSZPTAy90gRk87McfF6zjabCZaIMXKsElZbrFWkGHKyR646xkTIRjEllSsFsvyIKXNFEWOJCIRikJBFW7KZMcLYDgyDcKmUSoKbmlKjGPERut6z3jTYRXiujAarGfsg79VK6ABKsErft7zzaMfbjx/w/U+ucyCjub2+JPoR51ZstueMQ0sYO1QQYrRAB5rj3R1N3XCzv6bZrXn7rQd07R5oCVGKrotRCTESokA4McKQy5JKWZN4ygqd5PpSAhVnvDbljdOqwKPzNRfrCk0ApCj7DXDzNzNSha7vnMvcpUJgKyGcPPC5zkzlvXdOT/7uN77G//p/878SuY9Ko41YYDOFfUx0hAnI1aWWPE0hEcwhZr44+at8bvIyZFGr7AUtPjBLlBQshXLucv5sCMurWT1gyhAWQ6EUXddNzGmlhOckl5UpCEDtKlClFi2IxxAjt7e3PHnnnclAleszCpIRSoJkI6XMIBRvS0YbpQqGt3RtlgmGNO38y8iuPK/y/1M8XU02KmZP8H7Sovx7abRKWCyGT5jlSiVSri2yzmGdLPySHSoaXYXgqpUSTTKYqBxKKeEc5RBRLzxVpRTagO+FN1RXDuvkfkKQouMQI5UzQiJuZeEKX6/4NRE/BEwe73EcMgCs8x0Vzo+wyn0QT8n7KL5XMbK5LrRkd7VWOJfQTmM3kgmLJKxRGDLWqDRRSULFWoe24zSGBi14UfCMoaWuIkOKdONAo894/Ogtbm9v6Q8HXH3G2flDrp7/ikdvvUUicTwe8eOItZbD3S2bd94X2RhjONtuqLQntB1xWgX5uea5LGFn3pgjggNoLYZ5gm4KNDCD6aREozVPtg3nqwolcgoobdFZ6+3LHm9kpLSStKcx5gToUMgCj2pRNqrMbKQWD6w/HkAFrA2sakNVVXlCn2IqJXyRkG2OU9JiQcwEywVgsjiLZMuLwVrEOstvyt7U6TLLp8se1PS+fJ5yvzPvKtH3g7i6gGLOUs0XpdDG5tcFs0gBiIJLqWwxT+xovjZttACriAudojCJC24jJQp5KeVhjDO6P79e7q84mAuDfDImi0Pwk8wfUyqHYlKjJTu5YhHALMZQ3heLbEoS73J38YCzBw6jPNbqaYELdCCexjgG/DjiqlrOFpMwzo3N/xYelYSHmpBJiFppnNX0g2d/yLV9CdCWqBJdt6fvxeONWb3AaIv3gh2RGfc6Gyel5w23AMVFtkXlZEsZo+IZT3WeeUOIITHQY3LRWKlf01rnilYFRqORxEG1WmH6geTHHNIaOBxANYxUGUpQmKoipciDx2/x0Q/+kv3tJZuLd9idPeCDH/8b3rm5BAW3+z13hz2rZsXQd5isDCJG1WONwacCc8z36yfBP3maQguSZx5L6K8VpQSqAOplTKxWPD5bcdZYyNpvJlM7EnAtGYAvdbwZcB4DIXhx7/KFl3V6n3AIxW7Mi0IpNS1mlb0wlcOHQhSbPrvwhl4Ti9z7ntmzOvEIThb8Mgi671EsjN30hWrx9+I0+fcm7zwph1rjMGYCXr76AoouMClnnQiveS/hRASlHDfXd0JwUwse0+SlyfeWHV7kL0rxZwZkF0NVDKlejMNsowup9r7n85rxYvZSmIJ5qWOcsn3TLsoywTidKuawtwCxPkYOQ+CuVWyqWZZE7FnKZTMCotdNsxhtqVNbnl0pRRq9fMYHUEgZkTU5myb4zxgSd8eWlzd37PctKaoFX8fglRdvzgrI7r0noqiU8PtiKLTz/D1Rav+WNZPjOIoigSrERk3E57mYIEBtGikyzsqxRsvAaa3BGmJI2LqBekO4viZ6L4bRaHS9ZXPxNmM7ol7e4KPBx0gyhvOzRwxj4Li/JsaRzW5H8Innn31CGD37tufueOSdh+e8vLxBGcE6g+8Yhw5SgMSkpaUyrBLm/W6R5VumjiQLLWx80ccKUTzm2sDj3YrzxqDz3C8JsoTipvM8vxv4sse/ByaVFfiUgSTudy5syuHB7J7PxxwSdF0nlefxNQbgN2EdKZ3+Pi0M0vQNTLH9iV+0AH5nx0FNkdX98OW19z0ZsRLelnuS86WY6LpOXsvgvTFmktgoV1Q70WbyXnaREGSh3t7cTvVQ5b1peXP5GgobfZLDyOqVMkk4AceVSqcbRz63hIWzl1osXDrx4srm8/pdYgrzCDMdQSnhNS6+LMVICmHyphRQaS1SuiDMch+F/Z3VDopR8+Mgix8ktAoy9nG6JwHWY8xS1kSMUTS1Y7vZsl6v6YdRau3GkTQGamMnLDHGlIHtMInkzcOVGLRQGVJeuPKos8eqFWNIhOgxsSgIZC20IKKQ4nUUGkcimTw/ULn4u3CRImXgklaMfScZTq/y/WuqB++gtw/R/pamWXF5GwCNqWrOHj7E1RWXz5/z3jeP1OsVxjbcXL4ghEDbD+yPHdW77xDSJTEF2uOBVV1lw6qJKQqhNkW5rrK+VOZKTWMze8wzbUg265AHzyl462zFxcrmchp5npIwgpt25Nm+p38DIYQ3NFITJ1Xkdf04eUJayyQtC2l+/bQWqxuGKd4t++Rk2BbflcqkKNYdTlyDE/JAdq3LZ9JkVBbnVopJuisvwGIIJscrpdOvmV0QxCgtthcUMYdoMYW80ASYn72HOGc9AWsNlXO0XSfaUlmCY397KyCr0dO9nHiS84BkjypPfiOZp5jCJFEyjbVKGU9bDD5MONzJiZdu5eJpL03UcoNQ2fiqWKQ65PvK5xJqspgpjEQvZRc6JSwekzQxwL47MmZl0jKHunYQMUQf5PWMw8WUsNZMxcg67+RCOjXCa0IRvHg8MUolhDaOs13N0Edub++mmtFQPPk8HqU8R0I9hyIR9YzNyE1G0YVCTYY3Lrxlo0Wsr3IOYxOVs1SunoijWiXhZpHDpxSlzAWpdVNowtBRMuHEKNjdZoOympQC66bh+OwlNj974yoenD9gf3eDHwfcesvq7ILj81+RFLT9wPXtXWa2B9LoISWCnwH1lCL9IBnFKis5xCL+CBOWe1KeVsrQEAkZgJUxvHux5aKxKDyJXG2CYIM3fc/Tu44xuVP49W843izcyw8rxoi2hugzIJ4Wi2MRa00lMMWE6EQ/9sK4pmAa8vp80WI5xD4U7tSJ1Vhczunrp0EM2Zil0/VXjGM2dCcGvYSvOYwrcdJSD6l4cCffmwI+F76W+1Y54xEzTycRUVoWmlxG4b9Ad+wYx5Eqc2ym+11ctyhjyECrXAhMShhbDFXMmaB5FNXyJMUg3wt7ybu9YoG/yU1NnuryE8WoFbLttKvC1NAhqpLtCqLYYAx4qU5QRmrEhqNnGAqOtwiLYa4ZQ83qmynhhzSVQQnZMmsbZS105wxJG7qQON7s2R+OWU0jMvaBkCQkiUkWWYoBZRw+iEaZn/CzmNU5VS6SFUUEay3blWNdu0lmxdVz5rEI50loK6U+KUtgK6NR2nAMYFJCq6xEuvR2U8R3LQw9xlm0E719tKT4x8GjMq9LHo6M3ePHb/P5Zx8SfE9iw+O33uNnn/wcTIUfPZeXl6K/FTx+HFmv1hmOAIiiTTVKOG0y3SVmhdMQEylqogKVYuaV5RA4r0+lDVZFHm0rLmqNTVFK8lOQ543itvNcH6TYurF6MoBf5niz7B5iGELwOGvpKezyGZ+CvyZsQhGCZ+h7OVuMGXe75zVMyyPdWyTFeOXJ/BuMllq8Ny1PJxd38n5176uTgvxEFueav1MtzlVCAD+OhKxbVOrOdN6FiTN2pXOhsuzOeTHGxDh4uk54LrPZnLMt07eVi9GyI0v3DglzQghiqIpHNd0MC+IdCJ//fph9z5CfIA+nBioxG5OJF5MNeHH+dSqv5Gp4qyBqfPB0hyPHURG9hOHejxR+UtmVp3rMJM8okmVYkninZOe0hPA6Vw8kD9040r68o/cjbS84YZXlj4vxMzmUsUZRGUXdVFQX68y/MzhnMr5lJ685FIG9KGHq6D3HccB3LTEcs/yMzNaUw6UUZWOxBs4ebDh7cMGxC9Ra0WgpUpbyoTKvPcPdLSkO7KqH1BcXxLaXxxEjKkaMA22deGHjQH888PDigg9+dmR/85L15oKzBw9px0ClhHx92O/p+h6lYOg7trtz2vbuBIstdA61mOASFY2QFjptFCpLHnsStVK8dbHlYm3QBEpCRuSCFLdd4HI/EJOmckbY6K83Ea893iy7R5JUaYhY58gNfGSHTPdF5Uopx3zEnJXxfQcp5gWZpgG4f91paUCmdTa/UZMWtIL06ptPvJ7str5m3S+veWkMTqK9paeYJ64YZ/A+4H3EKjO9f+oUMt2LLEopQpWJmaKEHT4ojocDFw/PTkJOdfLl8z2VazRGOCwpRWEVxzjV+hU6BzAJ9s0pZtkF0707hxIenrieFMZZ8S6lLrJMak7eX4y+JkKM1FVFUgcxRDExdgN9SMTgJ8A9ZI1xUp4RaS52jUXSJzdkCLm2MSGZQ2sMxowYPWRwVuN0om4cj3eiUlo5J5UH1uZMoiR+Qm7kMHrPOI54nxiGRH93ZBwHaaqQvS6iJOlJuTlCvh8FU9bRWalXc1YKbJ2Vwtq6sbiqQqfEeVWoE3IPIWWisHIoq4lhlFAdSDEQhg4VRpSy3N3esqkCISSEpzVyc/WMZl1hjePyxTMevf0NNrszlKkYs5LEkDX8jTaMfc96u+Gwv0HlMp9Zm10ymyGk6foUCmvUVDhvCvUobyK11Tw6azhfC0he+HoyizS37cDl3pOSIi2TLr+tcE+RGbJDT1PX7Fl8W6lrKlN74VUtwWk/eoauneuk8kOaQrN73yfW5VVrVaKxWR/g9PvLGcpnpuhtAvvm36u0+PeJN1beX+7plBNE/ncYRZhfeDSl5CGrCZQdP4nnUTX1dE7BpQIxaY53hykVP9/n8rvne6eEZ5AzSeItCZhehP7nkC8n0IgF8E6LnWx6Tktv6/4kWoa/avIK0yKld997nigaQcLllOVVxpDoYhAJ3xiy98kMgOsSl0r9l1ZSrN00FXVlc3eaXLxqzVQHKmGKSLuQoPeRMYoW+vEwcNd2U7cfX+oDk3iiKolInTNiVJy1NJXlYtdIeVUWeotxzkguPQ+tZYPw+fu00qzqmqbOdaHG4ANTval0ZhHFkJjDLZvvP8SItQr8yHB7Jd/hHOR88hgU/TBisort8eaS87fe4fzBGbcvXzD2Ha6qWK923NzeEEKkHwLHbqCuG7rjkQcPH2UmvszTEPJsS7LxhxSL+4BCoVMk5ImRomQtCZGmsjw+W7Fd1aiy0ZDxQqW46Xqu956UjJB6TamTVCKi9yWPN6zdEws+jiN15YQqT27qqFS2sPoEX7ifPQshSiZsQnDjtJjkTfe+M6WTFTPt+CWOywOzwMhf+bi8M2UbVIxQQZjm73xd+Fdc3HK1J8OhZMGOOWQpBEObmfJFQaDsHhopMo4n4yP8stvbAwbF/bLLmTD5usGRl0zZCFLCToYKKMmB/DldfkxlRBbs86XbJ188vV52VLFJ8RVfS5HLJlBTJizlmxO6iWTC9seO7nxFUylcZWiMw1QGY0WozmqpmtcT07rgXkJNGEcxAsPoaX2E2KFIGOPw3tP3PdvNGpTi6u6ADyMq8/R0TGwbYZvXzmAysF9KtWrnqCop03HWopDsq/eSHazqevaEcyKkcI7K5lU8khACWkep+tfSKqwU1JYSHFAoFTE5ANdKM+z3EpoamZ8pzhnTpAE/ErTgagaFHzoSGg08fPiQz7/4lP54y2r3iKZZ8fLyOmdF4fb2yNeeXHA8HqQ21AfqdZXJyQUTjCck2dIcdaYPlE0SKgOPzxrWlTRXYZpnApkfuoGbvcjmFM/LGCFvGw3KfXnO+RtTEEgB7z2bdU0JeUq2pyz9cpP3j2K82uOBMv0UcbmEXlkA+ZOLa8gmWCnmhgqLRbzY3fM65ZUFuDjn/XCveBHTawsi6TLDtRwUP4bJGKaEsIYLIJzfrBEQtnLuZCxkN1cc7vbC5Mhez4TxqZmLNH35fGMyAfK5y3cZs2AET15ouamSTudVgzwZ6/u3KAZ+kk+iJB/0FP6aWGgJC+5ULukhiYfgjOPtd57wcK1R0WdytmiRDT7Qdp6x97LYSROQLQtW1DNBsqR1U7FpHBe7NU1TE1FcX92wPd+Sgqd2eqJ41LXD+yi1k4rM0ZOhCd5L5tDJ7zLYJe/TSpq5brdS9J5HuHSRUdqAElJmGUtjFMZW4hEmJY0XsgaUsNSy4oJi8sBShk9iEknupCM4hzt/zPHyOf5wQK81KY6EaOiHAYhEPxBRDH3L+cU5n3z0AcfbK1bbHSl5fPA5CwvXN3f80e//Dje31xIqJ8ELJbmTpkyfNiZzn4rSaYkESvNPhVaRJ2cbztd1zoqm4p8QEhz7yPWhI0Q9ecPaman7tLX6t5jdy+CdsIGrvFZK+UTelVVZAnmRTH9nrwA43N5JuQQBUtlVlouCe/9YGr7ZAs8A3uyVyFvj/NF8yK/ukT0XX7H0bIrkqnxuNmblm2cYTIzyOPgTO6i1FiGz3H6pLGSVPam5PVbM/eAS+/0eSJPg3+kFSulLMetFmncxCFLEq8j1ZCk30iwyxorl25eB5DxGp1nU5etLL1faWi1DXiYWtEjBSwZIQvmcPMjnNlaxv7shZvngmGYjtrwSZ1UO66oprS8hVsBZaVFV+vRZq9BGwHpnNZVR6CpL4iqFM6JVFWOkbpyQbrNMrA8jNtf9WQskEWkch0jXjqAM0eaMrs3zQOVCdjTBR5QR7Mk6jVWWBIzBMxwHQgDnbC7/kVZYJCV1fJDVLqS+TzcVoZWEktYaXa/R6wd0X3zG8OmHUG+JcSQGTdcP2MrSdUdiTLR315w/fBuF4ubqkouHT4h+YPRheuDXt7e5yW42lUaTQkB4TFK0XaSNjXXE1EuIp9OkIiEKponHZxsuGovOHD0xdJGQNAcfOPSRZGcc0DmHqytICmMdqKww+iWPNxS9ky2yaHiXim6lMlCKWsIm88y+d47j4ZA7xJYY7fQ9r/PCZvLY/fcVSdaF1T/xj8rkSpNXsczQ5WjuBJNZWrFTOoKeAO2ihqCUhHtTHWDeheNvuAdnS5Hx7E2FENjv98QQpnAJijFM05VM/1cnpmO+xzwcApdIvZ6QPfVi7NJ8r/l5nX5D9pxeOQquN7+7PKdS3qF1Lps5GfvyXKCqDQ/OG84qNyk9hFyUzRRyCM6mc8gcU4BMY1BJ6u2tAW2zIQ4xqyFAXZ1jjGMcA9XWTIM1jNJxpXSTdlXe1RHDobR4vaOHw3FkGDzGJFylqSqNdaLrJeFfzE1HJWeqU2AIga7LBGUtcyl5UUdIyWeljnrSh0opgjaTblUMifb2ThRaSZPaqEgne1Z1wzh4qUpASs384Lm7vmW33dLt9zx5+2us1xsuX17y1jv73MA0d25WsL87MAw9WjHhVpIZlo5DMUZcVeOcGC1lepGzmaoGEg54sKk5WxlUzNFDVmpNWmN2W/7e3/0POHQjm/MtP/3RX00qDqvVmqurW5yzPHz0iHHsXzPHXn+8sTKnQna0Qlhc/m4Z3pQjRtFNKosShcTFZINB+dxy0U20y/yv02UzLabJ2szvnxGR00U8ne/UzuV5vLRY8zdM+NXJZ9KMXeXYcBzHvNgzQTNf2xKbE29xFtejGL/M6D20LWEcqRo3X8prbMUU4ap7byj2PimUPmW6pzhjDfONqmk8TkPee99XhuzkTWn67PSGHEKJlyMnlZS9z6RWWLmK882KlbMUENHrGoWbr2lxIUoFrBnQOiAtrBJa54xUMljt0MRJXQCUhIxDxNisqe1Ek6rrPCEmnCNrbRuGIdC2AzGNUgCdIEZLvSo6VzCOiWGU7ix+jKLdH8YpdK5chXMV/TDS9gP9KBvW2inqzKeqqhm7KuNiMuBvq4phHKVUx2j65CULmRIpBem2dHZB9Bo7DERtpYcdcGhbtps1fuyByNmDCz5/+oLj3Q0x+Mzbk3nZth3DONBUFUPf41yFUVHoG64Sb7JkQI3h4VtP+Gf/6T9nTLI5/NWf/SnjzRUuBSCI146SWkXnWF1c4OuaNoz0ceSdR+eYVcVwbBmGAR8V3/3uP+bpsxf83rd+j5/97Me/Yca9erxZuEeu4k6emMRdLQtWIziKP3FRJAsSopqqwklw6DpQAZWs3DCJlHT5ipPvK4NcJvCMDHDv/UuPbFm+Iq/LQovT2V75nhKSLT0LpeQzU2eZmL3n2VNIUeHHUkIgXBptDN7LYi3yKpIlEQGySVcoyXtiDPRdT9911CspHFXLa8yNTZcYUjHrk/nORkTsQ8Iwe7rC2YmTuOBv9pVePV4Nw6egeQqpymenElQlSg0phKmGMCUxDsLCdox+zCC5pjvEKfGhlSheaBNxlXDApFg9ZiG2gNFO8Dsvrc+ObcxlLqKXTpIGtEpn3lVuuFD4YrVzpGhEXieEnGHNHZG9sNqHcaBwFo1edP6J4qEa56SRQ44gYpY1KfWMfoCqHzjfbaVmz6VpzGTTjShnSaPPGkuZwaaUCOcp6RPQrDfUF09or44yBqYGA85WGFvTDyON62mPe87OzvjVx59w+eI5/TByaHtJaChNNwzs9y3nzYph6FivNgTfEZLKBdgS5iltSEHx+L238C7wzntfJ7YdNnbEOJGOpjkUlMJsN2zefZfnl5d8+PGvSAkuL58RY6RZr/kP/6N/zv7uwD/6+9/l+dVLnj1/SVM3r5ltrz/eMLsnq1il/MDyDpb9gjnDd4IbzTtIwaTatiMtgOUZyj1ZDcyxyLzDLtGm03LHmUxY/j2dY/ppYbBeMXYLQ3XPb0s5rn+dNIn0YvOUsFNwIDWFxieicYrcXNIyDgOFRDd6GIbI8dhx9mB3crWvjEf+d3GkTvzF6fVsbYv3k5BrIVGysfccyt/42v03lJT9/SPmhVbkPWJukmnUPN7Sh02sURkHC4QxEbw8DZGgiSRGhnFEeeHbye8MAdGMCsHTHgfGMTD4gI8SXhmtcdaRtMaPgX4cMTl8LJItV7cdfRem8iJpZSW4VsrAeSkiFmXUgE5ZHlfnUp1R6t0k+yUZsEl0cYHPTjpN0wBnc56L7Ie+A60zMTZ393aOiMcYjds+QNka729F+UAZklK4uuLi4WNur16w3q4YxzF3yzFcX10SgWPfi/oAAvZf397x8L0n7K+vefvddxiHyBg8v/joY1qveO/sDB0DbduyjYkYRowf+MG//X8zXD2Tel1lxeMkYjY7Lt77GocQafuR9XpLd305qZIqY7BJcfHoMX//H/5Tnn/6CU+/+DVKW25uXv5Ns206/j3KYsS4FKAt+VGWkyq/yyJjCUrph80LA2ShH9uW4L1MeMrTOwVrT8O/ePrzFFpy8omlybqPtNzHXV4NCBcvlDCGEvLNMdEEPGfXJuUdvJTBlCp+ieQWBbHZsOkSaizSviEqhiGw3x8nXO3UYMx1jq+GgerVm1HzX0K8nL3bmOaegK8e6d65uTfG+c7yh5f6XLNBFT9BAyrFSfspKSVUg0x0HHKHmElSRofsPWrhTgWph4xIbWKKiRAVx26kH8IJpgcCoFdOtI8O7Yi/7ab26Spmwu3oJx5WitKl0yiNSZbKFIyILDcylQiLXngQnXHRYveMwefW4ZpYPKlYxrBUAYCiwzhLpV8dcZH09dRNg9aGEAS/Utow3FxTn72F2V2AsvhxwFYV7UFKr1JSnF084sWzp2ikkqNptuy2O26vr/EhcMwbYUqJ0Xuub25J7z7meNhL1JPn7e3dnmZ9znaz43h7Rd/1rELg01/+gg/+9E84Xl5ikp5qYpVSBKV461u/xzf/g3/Ez37yU5G7yW24IFA3FcMYuLnd88mvP+XBk7f56JOPePb0C4ax59jevXYGvu54w3BPMjZRieZP5Spp2CjDlhngoJSUMpSga07Pyzu7YZD0KEJBgGyiXhNaLAAY5l3o9F2yv6cp4tPlh1d2/FfDwPlM2SgxG5Xp7KWOLBvHcm0KKThNvtgwhY+BZDLHJ2f3luZXaswsx2KkADCEmLi5vS0mnlfNw0zRQMXFr/XCTpV7OjXgpng22fimFOaGk3lY1ekPpyFdetVUyRDNRk1NoyJ/TH62JhfVGmMYvKc99ngz4LORGnJrplJyMkbR2paOxFKZL/K9gdFHQm5EoLR0KdEqZ54s9MPcTLWQNsXgGHxQJFWL4RqZaBYyssVo5z58ubkoU31ZEmldH3LNokaphpRgTIkQQSlDVGJQKyudgnwMjPJLrLaUrbQUZY/DgCHimmbqJ2gQ/MpWmRJhjKj7hhHjHHcH6W5s6xVnrkYbR0iG/rhnsz3n4uKCLz79lKgkpJ0ikBDZ74+T+kNSYrhcZQlemqtUVcUeUZ2ojGb/0aeM+ztM3pBVynpxdc2j979BO0Q++ugj/v53/wHH45H/+r/+r6hqJ9nU3LDFRcXvf/tbWBN4cL6lst/gxz/+MdY6vuzxhkYK2SWAMI44V9O3e0q5gFJmWiynoHEOrZT81Hcd4zDea2uz9Ahe4xZMP8/nPD3mhV0inLKrn3oIavH/+epOX58X+UlyIP9/CaiP3ud7UzlTF2cR/cmLmj+rEBnhubJePIKQEs+eXebz5uu9x7Sf7+6VG1iMTDr9dX67ZGMzkzjL3upFQfL9Y5mKOCWOLU6abyyV90/2vRiKkLXOk1Qa9IHbmyNEjy8diH2QPnxRjJGPMCQEK0FNxdMkskpm3uwC9DFkA2WwWqNTYts4KqUIPmF0yFrniqu7G4ZoSSmHb6icVleUMp8QUg7V4oTFxRDw+xshfeb3T89IAVkD3TnkPVZjq9x+KkRS0IxDQFrKL9REYaKJjH0/PeGUJGtp1itSCKjoSdEy9gNVs6LrRae8rmtsVdOst7R9h+kdQ99ydr4TrSktQnxS0ynPcN9KaDlJL09TUCIaax0a8N3AZ7/8BeGwnw0UuaNRveHb/5N/yXf/5b/i3/6bP6EPiQ8++CXj2BPjmEuJpM4yDVDVNX/yx/8NYezBJ/63/7v/Pd/5w7/Lf/Wv//PXT7zXHG8MnKe8Q3rv82Kbd09VwiQ14zCFqSp8IXlIPkhpzRItms5yf9M+iWWyCZwM2XJZZu3pe17EMoy7X5d2an7Sb35ldqnm3+fXuiy7IltyaVOei3/TXLhZDq1z1xiYDJVwTBLPnl8yjh7ZZNSCKlDg2XuXcc9OvwKH348Ns5cZi0eFyI7cL106PWf+/8KYpem883Mp4zTvBRL+pxAgRHw/MA6Rvg+oopip5rZJpNlTNEozlkWtCpZVvMnM3C4NEmKEMcHosVaxWVnWjcUaafZqnWUcAn0fOATFOIjxHEZPVGAppUwGH6Vtu5SLQAw+azoldBD1zFRUOZHUfIoi8+ySksUUwXmH1aCsqFeO3ktSYColknEySk1ky0hi8APWWeI4opszfNejXAPorLelaNsuZ9ctKMv5g4dcvviUqnG0xz2rzQV1XXHopf3UOGYJYODmdk+XFU2HfsjPUsrSYoqTVlkInvHuRjbe/FCVguRqfv+f/FPs+Y6/+P73ePzWWzSbh/zr//K/4O7uJdvtBu9HKlfz9rvv8fTpFxhruXp5yaquWNc1H3zwU87OLnj08OFr59vrjjcrMNaZH56kCrypXVYalOVhILN5DSDApM79y2bhHunq0bdS0iDz/z5x4eRbIX/nq4fsEJOHAyz8qHwsd4x5GeuTJZ2QyT8HOfns8q8JVM+fSbNnuL/pJA2bTxZCQKOn8EWknWfw3aBxNsvgJsEvFJaYFNfXe47HlouL1ck9LD2VOawrFxjnd57ao1fcKQlZS2OCZa3j/bE9DYXvHzIcs8Gf3zlnHCOlRXdx8xJWZ7k7JQ1dlW0I/Z6Ycq1dSHQe2tEzxIRSmQWtjWi7B+E7SSGsMM+1FiyqthpnFednWx7tNmJAgG4YQWsePT5nfHHFmAZpvd6PaK3wKlE5gyLR6IA2UFeOyoj3YIylchZrNdYorDOZaGoxxgkHzTBtKDGS26fP2FYgN5fIYao+8c5lbisFdV2RYqLvWpqNjCJKk8a5eLo79ug89s4ZHjx8yNPPPyT0PX3fcnb+mN16y9X+Wowi09SlbzuGbqByjq49Zuch0OR60rn4KxHRuS1dVnOtV/zud/8RantGjInucOA7f/j3+O4/+uf8xfe+R3u4BaVxpuKtR2+xWa1ZNyvGIN6yXlnabuDHP/oRTdNwc3n9G+fX/ePNMak8N8dxZLttpvR6Is0JJYVIlKREabomgyWvee/puhZRMPSoCXAvxMw89U9W36kXJEdkWc2/TJfPkdasq7w0YMUzmbCwpFku+BM/bemOIe64Quzm4U4Ea8oDDiFgtc3UCwlBjdITIK61ZLZOahozofO27Xl5dc3DB+sFXjWbjNIUYilzMUUdyEIpTs7S95z+n8SAaIHMJgUF1BzWluc5nf83eFmn3LH7Yy6HpL9lJMs5hozfjT4S25akNGOK9BHGZBhIBBXzOJmpjm4Yk+iOqSwuB1Q6QfQ0xtCYRBx7bq8G9pcvZGllwNgpyaatjeb8wuLMWhQLnMHZwmjXuQmPISkJh0IqCSB5Pj5ExhBpu4QPIz72pORJUSAQo/LmlaCuLavaSdssXU9efJwIzHmsp9IilUPTSPKesTtido9RKKIvUsRKCoMVDEOPqWvOLi6omjVdP7AZR+I4YEh0XY8q4SUJlbPQN/sDb52v6IeBuqmlPVgu1ja536FQZyAZBUoRlMGcnUNT8eLl5zTNmt16y+3VS37xsx/z/vtf44vPP6apa26ur7m5ueL67oqu76nqRpybIJUqz589xw8jXf9bJXPKDXvv0Wa52AqwPHsVU2HsIjxIyOLuDoeFSqSCzP59/ZEWfyhb+XS+nEubXqOkgBfLXFHCqzlWKv8tPY1XF3fpUyPvW4aMPiTa1qNzaYBS5IdeiY55ilP9U9ktpXvI7ElNxcZZSfKzL17wB7/3HmVUXh0D6TJyqp01PSHuvzh5mZPhyvchoIhI3k6t3GdW/5Ko8dr94TXHUotoaZgmZn1MhCAhXFSGpHKPEpUwRtxOqxUrmyCM0thSG9lmnHQJzl2fpDGDc1grnXi1MVizFS9FmzINiEqjolABfBC5Yh8iXRxII/hBOsMMg8/vSdLePiXCKGFa4Ukp8s+5Hg0lTRVWVlM7PXlcVVXhrLRlizEwlmKMQhhbWHghOieGfiCQqKoKW1W41Qq9ewDDIIRIP9KNWbNKJ/a310LCRLHdXfDis4/YbVoOt9fEEOg7UThVOQONkQLo67sD7791wd3NDbuzM7quxTnLGMbp+Qu4HjHWEivD+bvvMVpH13U8evQEbRv+6Dt/xM9++lMev/M1/tP/7D+lPVzxya8/onKVrIt9yxgCKVmePHnC3f5G1EYSrDdbbm8Pf/OEKmP0pd8p8y63XBbhL2NsnvKlyl/6vMcyYQt5MoksRbEhoGkPx1xOMcm8l6n+6peehB+nns28LOL8Z1qR95bw4rXZYJ2GVWKW4PWrsnyb/N21A33vmT0pzRg8KyWaPD7EPBYLxUwlLOWZkZ6/KYIKipefv6RwyO7bBvXKPb9+pJY3vDRm9/vymeJRBTXt5lPjhYVXlIiLzGZ5FktP98TvzOMr7y4AbQiJvuvRxuPM1BkJZ10Ol5R0Ky6tzRAPJ2rZ2fGi/URKhOSzLrnMqSEE7lrPoe8YvJ/mmUjgBlJUpCid/0gKq0SFwRh5XiFErHU4o7FEApJp0yuDNdI+PYWALWoAebMWjpSmtgj9gaJEK2C/JANywTFM2e1pI8ghXMqQgFYaVzXoyoKtQBtid013vCalwOAjIYwYrenurunWG5pmy9nFA55++iFj33F3fSmdk0cZI20d3o+y0BPc3NyC+gZ9lin2PrBarRiPQ4Zu5LqssyRnePzNb2EvLvj6N77F+1/7HcYQWa3WfPN3vsn5g4f8wR98h88//Yzrm2vef/89bu5+xt3+SAqRzXZHPwz87rd+n4cPL/jj/+d/Cyrx+MnbXF3uXzODX3+8cbcYVfRwcmZlmvZJXPHCX4FswSdvpUzehE+J/bGbJvW0278WB1GL/7+yDBe/K+20FLNXNX3r/M6FsUgT76sssrkYdj737GWVc5VX9nedaCDleL5kqASLEIE20vx7xZzdK2MxZQFTIkV48fyKYQw0lc5h22LxL2/jtaHt0uCKtzlddbn1E6uX+UxGds+U2fLFXJdvlueaFt8h95cWlm86bYKkBIxVWc0g5hq8i4uar7+/Y5UR5hglGyq0A2kB7qOW+jifpDVVN+IRFU2tNCYmaqvYrGuck5o9RiFLVijG3DYpRmn86b3CDwnpYWnzFBIPSJFwKCpjy4ihrWaVQx9tcn2mzooKRlPZXMfnI13Xk1Kk6wLHg3CcjNFUjaNyYfJMGledzN+STVQBdGXAala2lgqOGPDRUBkRlxvalnFoKVSdGCLKJNq25SwK72u9XuHqmrbvshckgH/RQI/DQDIyT66vb+W7Y2QcBvwYuDg/Z72VjH3K44M1rN96wjvf+n3On7zNqlmz3W35i3/3l1ycnfPxT3/Kg7ffZrOu+dUHH9B1LZ9+9ild1xMDnJ+f8/77X+Ojjz9mf3vHZrUihEC9WvHNb36TMCT+O77c8YZ994Ak3S9IWahdqYl/szxSyqx0ykIkT56I15rb43ERtpXjdd7UcsGo1/yu/K0Aw+kq5N6/4+KlUsJRMLOlEZqN1qs+Qnmbyi6rnjALIBsmuffSNGBqJIHc8rLusSBxEYHu7w4th0NHXa9lYi48muWtp4WxOImypt8sDZa+N2qLMLiELeTwM/jccy6fo1jH/B2nfmc29qgpc6tU2SYEPA8ouqgYomJVNxz2R2Il1+ODB6UYQ+TYdpCgXq0ICcYwEqKncRqlLdaJ+sDKOSqbgflMG4gxK3Rqjc0MdWsN1ihGH9jvO9oh0HW9sL91bhCw2LC01tjSyUYlSAEVoaolhDNmRW0tq1WTn0XmahkJ6fqhJwVRuVQqFz1TyTPSuQFaTFLmgxQOW2PQrkZVFaZZiyJCiOjmHOVW+UlpxpAwlYRRMUWOt0dub24471qsW1NVNZvtOXeXz1FokegeBkIM2AU1RmnN8dDSDz3GGsbgMc5xtt1hraM/3hIBU9f4pqF6cEazWvFgd86ff+/PuHz7Ke8+eYt6teJnv/6U6/0dH//6I66vrjDO0PYd4yD8t4uHDzl/cMHXU8IPIz/+wQ/xo+fJu+dcPLiQhhBf8nhjCgIpk98yqCgyuTMjuiSJy+67xHbm3djTH/YylbOMcMkLzVZhabBel326b9yWmbkFw33y5OZAjumaFh5TDkPn9Los9TjJ0Knsq5XsGNxcHyRD5CUlbK0VFm8+hR+D3JkuPpTKC6j0m0t54cui8zGw7waev3jJo4eN3M1rnMsCgJdJPA1B/uWro7MkMCwD53lclVYispbEo1qqMUx+7MIbm31aSXpIp+JITAqf4K7tGXziejSEpLkaFZ2ueHaEjVdYk2hsRRh74fUoMdV91+FjysqZWvg2U01eYrQjlS3Yn8MZJdLCStH1g/TnS+KtblaW7a5ht62J0eNjQiWDdVYyXzFL8ebQTaUgWk85m6hy0a/RGVjOHV1A5FSMyfhaVKzWjhRZyKMY2mOWOJ64VWbyonRuaZWMRbsGXdUkr2UMYyRr7aKUxnuoNw2XR+l7GfzI1fU1j/Z7lK7YbNZs1jtePn1KqBNjTHRjnzHRSFLSEVqTOB5bbm73NLkMp1mvUHrAoOlSAm14/1vf5JPra45dx9Xlc3a7MzabNTEFjsc7fvHznzP0PbvmgpubW77xO7/H8xcv+OjDj0gq8R//z/4Tvv3tb/Pxx7/CWvj2t3+fn/7kJ7y8epGb3CaqVfXqxP4NxxsC51r6a+UagBAzuBZ70LIzGQVj1pAqLYfKkijStaTE8XBAlQzgkmGdlsapHHpeHa877mFU972tidBZdKem/4tHOH9ETSHr/OL8nZE4mblhGDkeBhRVbrsk0hjLbx69R+cMV8FLlRKpWoOWshmyznWUNkm913z2+XO+8+2v3Qs8l3e1DEdPDfjCR7r3anHJCiZX7m72IeesX8oiZr8hkZFbZanMiUt5kzn2gau7ll9/+pKPPvw1P//RLzFhpMbTHhJ9p/n588Dbu8RbO8tGj6x1oLJMLZ2GwecOO6LESdJT6CWYFTkT5WhWDdu6EkTQSAnMMIz0nWcYglxbNtpN9kSCr3CmoWkUdT1iErnAF5LShKSIuQtKqRXQWp7Dfn/k7qYFDFXlqOsK6zR1LZSKtu9Q2tIPQiJtGoVCM2ZukjYVZR24usaPPePQoawhjVmX3hiSyQ0gkjTqkIZKiS5zpKpKssfXL1/iqoamqWhWDdY6vE/4IE1Rpa2XyATHMRCVEGivb2555+F24vAZa6bQHBLb83PeXa24bfc8++Jz+m7g6RdPSUkInwaHqxpiSjx6+y222zM+/PBj1tstD5sVL18+4+mzLT/6qx8Qvef29ob22BEGTxwjP/nxj/nVh798/dx6zfFGRkoqvYXMqbQoJxpriEOBjed+aEYbRBROZ87MHNkFDbfH/SS3Oi+5OWTIq4GyZ5/iTYuLOgmBTo/ZYJVYpcio5Pen8p1LsL38PpuIlFtQ5QdYyBLHY8/Qe+q6nkI8wSrGbJCkuWNt5PXJ+9AyKYwxpCA90AqhO8aAD47Pv7gihESGSoD5PfONLQzoArA6TQ4sRyPd+1veVwxhGSutyKTUoiiZSbmZcb3cdHItP33UPHt5x5/827/ks89e8MmHX/DixSXD0JGCRyUtki1+QKvAw7XjrFG8f1HzZGV5sIKLJrI2kcZZKVwHWIvVFNVIQ1WvqJoVVWUZh1EyqFVDMoraRNZKAP6hF9XPvu+x1rGqLVaL93I4agZvGPoRZ2XRNrUW5c0MS8SQGEZD14N1kVUj39/UNdWjlTyrXKOpEAxNMrc2q30mrElSHuKlGFoZA0ZS/Kboe/mROHSMRPzYoV1FVW9x6/W0KVdNjY+Ryhja9pZEpHKWzXrD5YsXnF1c4Lcb1qs1jx494cXTLxiDZOeI0snIWIuPEa8UaRi5vdvzjXcezqodWkmvwtzxqB16jm1HGCWM3d+23N3uMVVFVdWc7Wre//rX+PCjj9CVY/QeP/Y8evyIs/NzPvjFL/jss0+IoyeGxO3dHatqxXvvvMtud87li0va7reV3SOQgqKoKXofsMbhFwtdBOZztqts4ClRilEjQmE4tL2o86WGpSf1ajusU+B8Cm8oHthfd9w3W+KqL1bla94z417F0ygLsoSkEdGMDqWrbgactZYK/YSA5eMw4ho7F6yqXNCqBT8ROZfZc0sItnX18pa+G1hv3WSQpuabs0M4X+MrMN3SYC1+9Rq+U4mwJ4A+FZxJgGEU3O5HXt4cWK+qqUC4EilLrg89v/r0GX/6xz/glx98xDD0RJ8bHcSY+Tk90ik4olEc2h6lEj/5/JaNDrxz3vC7b6341jsrvvZow7Zx0hZLaw5t5PntwKeXLc9u7mj7GyKK4ygLqqkqHm4rvv3Oju+8veLxWcLYhImJ0TtGr1k3loTPipwB8IxhoO1FkTIqDTHIbFLCZG+7lnFUqAGGQThbqqBtaSZq6iQFzIJrpVzsG9gfj5xvVkJothWuqgmZ3Kxz04iQEs6aeWPJ3Dqr5PfaVKhqRdCyeewPLRCxVcOjR4/45S8/oG2PbPsBYyzbszM++fAjvJdSmBgTBFEzVUrjY6BxjsYZ6qah60Vi2FlLCJ6UREO+P7Zc3x2oKhEQ9D4yhsDQthhrWW0aDsc7Lh6c8/L5Uz7++Fc0zYqr2xvu7m4Yx16E9DIeq5UmhsDnn3/K88sXnJ1f3NM3++uPNzJSRgn4NibQKomVNpYhJqTIp4DreVEwL0IpEUnoLCfb9oMYqRgXuNHfdNznMRXX597bFgt1+dn775HQTjFhVcs26mo2LCVbOYnvpcTLlzcUQ6lKuUMSxcZitPpxICUztdSWcE8mqXaWOPTSKghyelrq6/aHjru7I5vdxRyaznHc9FrxropJnThN+RpfHb3FZ18Zs8wTV5pjN3C77/nw4y94ebXng18947Nnl8Q4CmVASUOCcQzc7Q+8fPmSsc2NPgsWmUrIn6Z0fEpF3kSetg/QYrg69vziecf/6ycv2DjFqrKs6ooQI90Q2XtNl3slCaFROhyXc2od+e+U4d0HG/7ht874F394zltOcCFrLD5oujHRdR0pisaU9x5/E0T3KokXK00bZCSlFZY0X7i+6xj9mD0OfzK3KufYNI3IQjvZqJRxpGz0ogLjGlCGlIYM9As3C53QzuHqlYSWSqOsI/ke33dUW9HRMrlCQXrnKYyrWK/XJAXX19dsd2estzvqVYWtHN11i8/effKJ6CRD2xjNo92albU5YymGR6/XdG274BYmrJaSr6/9zrf44rMvcHVD23U457i7u+HZs6c4J8b3bHfOi8sXpJC4ubzBWYdG5r/SsqE1dc3NYc+7T96nHTJ2+CWPN8SkkvR38wiIOfTYShoVTmEJKntOmR8VTxeL1AkJpjN0LSntoJRPfOkL+XJvW6zrex/OSzuVvJpiLvWYtBtec0bJSo1+5PrqVopN86IsoVFpv62NZhwGQmNPyiAAjDbUrmIf7xbGRMZNaU3fey6fX/P2+w9YNjco95TUqYF6bVSn7v17ejkt3jqbuIQwkg9D5NOXd3z/r37JD//qA66vDrTtyDCKfErRf48pZeLjgPI+a2gxIVyT9lYCFUWryYc4abiHMEIKk+726CNHpbhOCpGVkJo5Y/QkFFj634mBDviuo+86EnC0jmPf8enlNb/87CH/8Fs7fufM0thEip7oA+MgKgWkiFY27xrz9uiskEmN1ow+4UOH0YZhjCSkc7DWjuIEKK2wlSVqy74d2F/19MMwFS/73UBV1awrw6HtIQsPhozFbjY1ddVkg5uot+eYZs1wOBCPd3Q3LzGbc4xWjGNkyI0ojLGs1g2P3nrMzc0NQ3uUvn7AerVi8FcT3pSiZhxHdo3jvNFsVxY/jhIOgkisjNKXTwH1asP6yVvc+c8ZYsdmd0G9vmN/K2U2wzjmapMdwzCyqWrq9ZqLpPjVrz7EWss//qf/jAcXF/xX//q/ZBxHDKKzH1Lk+vYmRxqvWV6/4XjDbjHyn9agvKTYV80mA4yyJSkl4Z7KRks8hIhKKkeJCkLOxLQtOs7Zt1Ow95UY5pVrmblR8ApW9TfcSVniKhexQk7KpJyffKUTDVNc1bU9h0PLqp5r7MRoJHwScqpSimEYIK6nRqHyzUJ4ddaKymOU8HcKt4Is/qefX/JH3/29CZt4VWEqzbcxnfsVk/XKbb+ilEwmRHrPsQ/87Fdf8N//+Y/56c8/YX/XopLJ2t4+63pnXKp4jlEmt1bC+iYlkp6Jl1oB1uB9Qrt5usVoqKJI3UgoWIifAhuI0TMQNT6BihGlJXwkRWKQPofNagVKZSdY4cfIB0+v2LcHbr52zsMGGh3YNRantRgZI0z/QqAsxN4UFYMv8kFCotDZ2y51g0rNbPPJw1bdVEYjxccyM2/vOuomYdYDekxY4yTT5j3Nqsa6CmMM49CD0pi6QVuH0eJlDe0lQxhJQRMyVwty/z5X8eDBA16+eEnft6z8GjL9oOuHLKksmdoUAtu6YdMIM361WU1RTilZGcOI1UJuff7yhmFIrLcXfOfv/D3eeutd/q//5/8TIfMkd9sdv/vNb0FSfP/738etVnznj/4+n/76C7qh5emzL3j+4il91rOargXN06dPeeutJ1TVlzc9b2SkrDEEhSyurIRgjGghLc1GYeMqsp6zZuJUldURYu6/N6XHzZe8nFMvZ166hfUNkzBemoKl1xwleFOLNywXeTzBrpbnvru9ZehH1vVmekOBFcIERmqKltQk3YIMgc5SG3K2LLyfyx1CDAzB89nTF8IudvbkLqcbOtmK5pq9pSE6GaDXw1GASPI+vbzhz7//S37286f86sPPuWuPkuEj4LOof6J4x+KFyoYkoa11VpDJKO3eS5PScRyIuQWUzWFLyXaipfNNmRols6gQ8UCdSWQKaVagMsibfJjC6vLHe9EGp3K0XeTaRn7xrOfdnea9iwobDD4lUg43QxSPyigjlIsUpj56Oo9XucZswlBaXtQTDSXmeolhGnwR+xOtq1FLi6ddTFSV9J8LuROztZKQCcHj/UhMSLdirdEpcuxaSGJgwuCJKAlXi0EFNpsNq9WKu8Oe7dkZq3otRE7vUYhXrhF5mVVlqSvJSp6fn8nzIQHSNUYrMcTf/vvf5Zv/8D9mjPCXP/w+l1fXPHv2lHYY6MZBQH80P/vZz9jtzkDB17/xO1IYPfSEEPjxj3/M2W6Xs5gV2mhspfnGw/d49vw5h+NBqBpf8ngzTMrIIjRKOpLGIFmPuUOLtFbSC3ZhAZFTloEQr0E6xbRti9YJqduTCnl1f0GeHMvwBE4Xb1ys2/IgFxjT4vX52k7POS/+8idBbp00F2sqrq8OWd1A5/bT8o5ZRynmdtRpwqHm75XxqarME0lzuKiTBh8JJvLs5Q37fc/Fg9KYYWGYSyg1XyUFQFdLDarX4FKLuwUSwzjw+Ys7vv/Tj/nTP/spTz+/zeUkaRrBkImVk7RMBI2A/9pajBGm9dB3DH3POPSiXjkMjH0/EV2LJn6RDp51nEIuc1kw25Ww56ScJY+hyrQO5GYHXz4nihvtYc/hqFlVhrZzXN+2XD/csB/hotFcrBSNSaIYSsSoLFWTIkZJu3sFpJimkK2obBQjqrXC5Xu2lZE6Qq1zu3edlUgFmyIpkhE8RisxpCqLHoYwMo5i9PzoCaPn5otPqVZr1tsdcRwELG8PDL3GKi0hmSkenMY5x5MnT3j67AsxdFWYuiBrrXOLMXDOUNfSdNRYoXSIgyBORGUtVhuOfc/Dt9/mm9/5Q375i5+jdeL7f/E9fvmznzH0vcjIhMB6vYIY+fjjD3GrmrY9cHV5yWZdM3ghVI/jmHmDnmQNtoLdruZ277i9O9KP3Stz8zcdb+hJCedDKdBEKZOZGMfMHlSMRC07RQwRciFyoeOTpLXz/thmZrNsmX9zmKpe81M5ZrWFsnRPC17zb9N9zGnxngk4lDDwxDPLP3s/8uL6Bu8zAXVyYeQEIYiapDIq79azMSmho9FipBJkHoyEFLN5FAnc58+uOX+wza+pDFvNi5gk+NTkoWb3tVzSye2rV38fYuLl3ZF/8+9+wp/9+Qe8vLwTrfAYZ2WdjDeKV5wgplxb5zG6QmnxPoa+43jYM/Q9Q99LeOgD49AtqAwlxNDUdXPSLReYvKLpeSXRbLLWTtfsvXhv5Y8ySjBSo6ntir5tudtLVtI5y6HtuDr0vPeg4dtvb2i2mm1jOas1mxoqo7BKS1NPLf3xjMldfUrRNUm6oyg1SeiGKIqckkATXhkxMcRI8FntIHrWmwrnLCkOVHVFVcmmIzhQn9t0KdGxSoE0tPR3QcLZLKkSk8gXF5JtofgYrTk7P+OTTz/hcDhitZPw2Xsqa6XcKEWsNVRWYzVYrbFKEaJHKc0w9FRmI5lpH/jglx/wrP3P+fPv/VsigZcvXmA0rJuakBImY9DWGpq64vb2jk8++RASGKvQUVFVtWR5U6BZVzQrBypwd3vF8XAkxchuu3plBf+m442MVF3XdMNxmvkpt0+OGY9J08oo5SfCuFXKTRNUii8VMSpu98c82TxKhXu7/L/PMStxppPVufhpwiDi4ldLY1Ouf5HNmwxZZBgGDvuDhFVTJiufJRuRmCfT7EkxjYdSIqhmjDkxIAryWMn1eR95+sVLfv87Xzu9wwkLmW5o+llHTn538rb5AoHEGDzXt0f+8q8+5nvf/yUvLveyo0cvhiifQBYReSOS+y1dZ3T+M4w97WHP8XiQ4tY+l5+kNHlIcvtpuowQPDHqKQQsBmocR8l+5ozpOI6TsSpjK+JsQYrZs9dQqCvr9Zr+2MoGgaIfI89ujviUcNax9zWPd5pBGWnIqUV8zhJhjPgwSveYKGC2D2mCKtohMIayKWTsTIkXtWoqqimrLhlN4citiSmxWteorCU2jCPWWAJ+wo0ich9Ga/r+iGlW6KoipAMqSe/AlALRw/FwZL3ZArImV6sVh+OR7XpHShFDopaW1oxK4azBaMGyrBHtLJmLsj5jLCVdkdubG/r6OW3b0g8dx2NLn2VVtJFWWsEPDEMv6yMEoh/Z7HZ0XSfcvkzmTirSNIYnT8453t7R957ttkFpM3Wj/jLHGxmpysy6SbIxC/6Q87aA9KgvXWHKxCybPMjObKIiBs3N7RFJtrSgWxTrN7mcv/a4Hzae1rpNV7f4f/np1FSqyUOT1/f7lvE4LNpDyadnadtZjTORhF+zGI8Stig1zWgmK5WvL0YYPXz26+cig2tPkK9pQZ5oUsEUmizlc+QSc6idvyPExKGL/OSXX/Bv/u1PePnikDNMEj4REyprKuXTkoJ4VEt+i1IQomiDHY8HjsejECwzHhUTGfuYj2J8+n4QQ81c51iaWZbXyn2O4zg3/khFvzwXuS82A601JodiiUTTrDCmQmvF7THyw09uWb+oWFeKx1vLe2eOR2vNg5Xl8daxc5HKgFOQdCKqyBBDVmmAygWS05P+VF1XuYmpYt04KiffK3rl4jGnukE5m7tWJ2KS6MNVFfRlNYnhG2PAJAkXra1QtpbaviHRDYGQw8Vh6LF1PW1ou82WYyfGRPSmpAh7BPAJVzTbc6QzjqJJJbjaItSOEeccP/zhXxJ84NC2HLue46HFGIOrLbVxKJ3o+5YQoHY1fhi5ur6irmu8H6k3LvcUbHjy6II0dvgwooxld7ZiGEdOS9T++uONjFQzgbiStVHkbsZGE5IMDhlcFd4Ji11U0rikrF6oI3e3x2wXAkvw8f/74xRUvv+bVProFS4USyMm71riVbOBCNxc39G1PXXVTCGXUrIYNZLBlIUpAn7GuOnTOilUFIXK0i6JMkbTZUohagiJ5y/u6A492/P6tfczY3DZQypGs2CEC55CSom+Ezb8sRv43vc/4L//0x/x9PltFiiUj2oyFoSAyyUBsjSIxdAopejalsN+T9u2kzGZQ7YoaXetTwyQkBnFOxrHU75MDIJR6aUWN/NmZ8QlIA7Zu4uBcRwm72vsR0TYTygDq6YSRVAtY3psA/2oGdNIIqJUQ1VF1uPAuq5wNWgCKM0wRhpjcMZgDdmQinqnMQZtJVGQIsK/ymCwVgbn5M9YrzHGEsKAdS6z9gPJi4wySonEb+ntlySkjsNI7WpWqy2kjtvrXhIYXQ/GEWJumIpivV5zc3PNzdWVGG8i2mqSzyU4NoetOUPY9x1VU08gfIElvA/86Ec/5tf7I2dnZ6JCcTgCilVdExV0g4cUeXDeEIJwuJr1msu7G77x9Xd59uxzznarvHl1xHGcIoQQPIf9nahTjL8l4Hy9rqUsRAlio5K4iEYb0tQyJU5qCWWxz+SCRGGjx+RpjweWHKv7BuXf73i9gVoGgnLoxe+X37uEo0/PGWPk+vKWYfSsV2Y2ACJxidMmh7gRnRnKNkufCAUjZ0CVNA9QKJah0CSKlkQg7uYwcH1zYHveyFcl5mu7b8sXdkppPV1TMbMq585fXt7wlz/8kD/781/wxbNrEXiLMgZLLylEKTEpBrR4NSXcMmYGSLu+mxQfiqeTyFpOIYJnes4lXC3qAdZqnKum0C6mWRu+ZAQLnhWDpPlRCq1trpUUEqQYPU3SiWHoMos6MPoeVdU47XCVEBjHYeRwgOcpYNFc7M6oakNdG6oaGuvQRqGVbETOVdiMq45+lNBa5dZTXpQ5rZbW7cqIMRhHLwbfGIxCEhFB6gtjDAxdi0YK1duuY7OupT+gUgQSQ3fMbdYtSsvGopTm2La0w4hrhP1vrWO1aljVK64ur/Exs+EDUy1gU1lyR3eqyjAMPfWqYRxzC6oUpuc8DBKuaxLrpubaGOqqIoVAN4wYq9jUG5yrOBxu+OY3v4WtasJnQj/SyrNeW/o+MA5SmlTmeV1ZRp8Yw5c3UPCGRmqzqqfNWucFVxQACJkTQW4/mSfTnLGZgJmM0+ipSWjKPKr/UZyoV47f7FUtu7GchlAzyXNp1vp+4PZWcJcSqtw/pkwdlnSy8OfMFWpuJDlpSlEyg4mkxZPp+sDnn7/g/W885hWjef+fqXw/AnwXNytKhmzwgevbIz/5+Sf8+b/7BU+f70WVM4k8i7C5Zwxp8nxSIoY0eU6n93nKbStC/lJYLinukPGOlBI6SfBsjJSjVFWF1mZi6CtjIIeKZVyGYcA50RIviYqYMv8qKxmAeDkqZ03HBF3bQh0IQbCPyjXUjWhQGSMyJWNwJDRX+54PY8S5CzYbh1sr6mzkxHjD6DusdWzWK0l2ZJWIykrPOzGcuQCfQFUbSJpRSSG5SeCHUZQXxhHvRXk0JVg3TrbGCUIQQ5NIHI4t1lkuL69JKbFeb/ji2TOqdcPFxTnGWFzlePz4Ic+ePpeON3lTkg1R42yWoCHRNBZSoO86rvY9202NT4YUPWMUR0NrTfBhang69gPO2FyvKAXebXegaRxVbXhx9Yy2v+OTX99ycb7m2O6n+SQihBJt1a4h+p4x+DfyR97ISJ1v1lglvdFkIkmnUm0sfkgZOJQJVJovFOoBk3eVd2ZtOR5H8cSSB5WVE3n94v/yx2+++8k/UnBS8PaapgKlYcH8vsT+7kDf9sSQZiOVSqV9FjEu6hD5PkUqWLJ3wrXJMHT2pvw4zk5k9igjUdqDR/j4w0/5R//42xi71Mo6NfqkpbidQurPBoilZ13i5dWev/jhL/nBX/2K5y9uspCFYBLej/KZLJi2pAKkLIZX6AIT+K2lPXzMZU6zgF9cRJ1pukSdQXuldZZQrnHWgRI2sjIKYyrJIA9zaySlxABpbcRLSeRkTcZCtcE6xzAMdF0rYZ8xtO0e76WMgwSd7tjEDbuzc0iJqq4oXLiz3ZrffXdFu7/hpV1TVw2rWtM4lUNbRaqssN9zpxhVOiIpB1RERLf9eBww1uGsZoiiD54K38mLTIkf/YSLFuMfg6TqxVAJyz4pnWV84dh3KAXbzZq6qnn54pJVU0so6hx1Y9lsGtqrw1QIXiofrFEYlTBKsV7VJODF5YFfvzjQrCrGMfD2wx1DjNy2Lb333NwdqFyDVoZ9e0StVpMnHFOkz8mRjz/5FbvzLQ8uNrRtR105xmEALU0yhkGKvI/DwPX+gLWOuq7pu9+SxnmzqpDeFxalhS3tY5BJcphZ08WTEjdPODdx8RpR3N7D8UjwPaSRWfatWizGUyzk1eLj5bHAk9K04vPnlu9Sp2+fTNep11QIAUt+0uXLK+5u7vIAF89LwrCivhkBHwMuyu7hqszCLl9RoDAlKpCpzwYmzSn6mLJy4jjy7OkV7aFje76DhbYV0/WVLtCLL9BBsjDjQHto+eLZnr/48S/54Y8+5vqmI0Tx7sZxkBArG5qw6CBzvwHD6XPI3xxFxUFnvAMyTWE53kqjtZQCxeDZrBtUkt1YFCEknHP579F7Yl3Ttj3DMOD9iHRkMbk4XbJUQvY02QtNrDZrbm+u6bqWuqkp2t6rZj2FkiEGumFgt9milGK325J04tefv+TJ2Vv80z94l9Af2R89WlsebGtcwRyTqIV6ck1cyoXGMtnFs1KwWkkmWwy4xTQWpcYc7gaGwTOOHuc0MY9byrjbsnwq5Xk0+AFnGoaQW2dZw+PHj/jgo4857Pe4DOKrBM6IHpoxmtFL7aDRCpuvTaGxxhKJ7Ns7btuO57ctPim2uzWubrBNoL050h0CxrRoJc/K1RVj6qlrMYbjMHK8a1kFS2JA64hzihBGUgp0R1EJ1VqeW9+PHNuezVqz21X435boXd1UaGWIAm+gkiykpnZ0ZTlPC3Y+YpqlUFLGOgiBY3tg8D1N5i69WvwxPzD5Ie/i9xbQqzjNqZF6FV16s0Oh8GHk8vIl3kecK8oGzNez+DmEkN1/wTOWHKHyHq20tBZK7ey1kHfWlCBA0J7b247ry9tspJZ3kBDDPuYedkG6SydQiOyGEGkN7TDy4uWe27uerhMSoQ9SC+a9z2l8KX9JykzAeDH293sHykYwhydKaykHMQadvS2TSyEinrqucMbilGLV1FM9p9J6MrHlsMaQjEZrS1XXtH2PH32+R6aQtFyj1pqIbARNs2IcesZxpKpquuOBtm3Z7Xaye2diaYiinNn3PTjH2e6cX35yRZ0S3/n6OcaOXN0cubq6o7Gaxiq0mTelRFbytBalhtweXeGMnXSvlIr4UZFqaehggeA9IfiszErO+M3yNxPkoCKmXjEOQnytzx9IN2JGUIntdsXZbs3NzQ2rWrhqVhUQP7f90lLeZa3FmVlwUbKgoFLgyXnDZ88OWFtDDJiVxjWWMAoBrKoryQxqSNFT15rz8y3GKIYUWK9rVuta5mHWFRuD6FetVqL60A2Btu3pfcRWFbvtVmSE65ove7wZBUFrjFK5paQYqt579FqQfinYzW2kUwkNsp4zTCGARjJgXT8wDOICT0Ysh0n3weETmmYaEK8izGDMPU2oEoLNXkepqLL5tl8FyJe1bydeBEL577qetpU21ydeXVr8VYxRTLOIfyohUVEiBWPU1Gp69tZS3oVFgjYpQxfg2fMrvvZ772Vf6dQAQ5EQAZX63DE4gg+Mw8DtsWUIEXTF7f7Ift8x9D5zgWbypPSFA1Qm35ZRDTEDxXryEGR8IkpJyl94Snq+jjw2Rmuqpma9WklRtdHsNhvBI7tWOrLElLu0hExfkIyRygqZddNgrKfv++mZ3Deawvw3VFVuVx7AmYqqDmw2W6qqxlmL1oZ+GIXPY1ZoXdPUK/Aj21XDRy8O9N7z3d+7YLcyQI1WCatzb74MYeqcnZ05tDWlRm0K5ZXCW8ux73E2kLJKpsv3FsIomG08xfukFVpCu0Y6GysLpsIHj9HitisS52dbPvviC9quQ2vpbJFyeD/NYaTphE6Zn2ekVMtqxZPzNcrVtPsj9W6FYWQYNdYZ3nr8gL731HWTVUwTQ9+xbhyblSNlGePd2UpoFwkOh5ZuCIzey7x3gsnGpDm2PT4lbPaGa+tOsr1/0/FmnlR2HbvcO0wjnBpnHSEqJgHfrDc1ZcVSxC5wihg92lT040h37CEXdJ7uqcuwLaEYUOESwktSPCA56Jk0Oh9pBpKnSE6uTSsDek2yD1DmDFRDoiL3nl0YCz0Zg1xJxt3dDTc3dxwOBx48eDB5EalkozJGYpQieNmJrDZU1kkxq9wSpR+c1YraOiC3taJk76a7FypChM8+fc4/CB5lSkZyNr4KM8WPSSuIPcH3+LbjsO/49SfP+ZPv/YIf/uhj9vuB47FjGMdpkpTF4Zzs2hQ2dx5/CWM0GsGKUrbEIYjnq3MpCHmnLsTKgkGtG8FQKLMhKjCKul5lwqTUqRWelM+KACmNKGsn3pNzbgLHS5lNSongfS5h0SRTYZ3wiaRVF3T9QNOsIWmaek1Vy/iNIdINnptDy3tfu+CtM0MKA5e3Rz6/XPEH725JGTuKBMa80Sqykn6YOWOFdmFyOUyhT4QAIXmMlVCuqsVYClWjjMjyoavsJRps1eDTQAiB6+cvGMcWs8oLP0aaWuRs9rd7aSRhDSQjiRdASMsxe3WKlEPWcRizBE3Eavid9x6wWq+5u7vjqu25uuuoVw5tLfu7PdY7VpuKZlVROyFh9v1IVEHUKbSmHTp8kO+UDlKabgxlwROjMN1r5xj9SNt1+OG3RObcNI6mqjj2vUxQpUgpYHKd0DzWM+UA8m7szGRMYpTdfhgCx+MRks9Y1/zMZCqJgSDdkPqfk8ZrSMXz0jPYlIr3tQjBlj9lHXWApO5QPAdtSboCswX7AOyOpFbZaJVPzsqVL1++5G5/YBhH6lzaUI6peDj/OwRhz9u8uEhpwuaLd2mNLMApBJSBm8YvycCRfOTp05cM/UC9bkhZ9kJ23+JRzFeMUhjrUE1EHXuOhyM3V3e03cDxeKTre3wusp20tsszU3NPwPLv0jQijCFnZZmq8WNkqlczxhCU1GvFLEniXIXNWbJSwxUVDH3Hs+fPOR6PKK04OztnvVnT9z3jeJA5ZcQoldCsnHcu3s5zKWNSxYlWWi5S5dCw6zrausNsNhLSWIsyOuuXWwKGz68PbKqG3397x/nW8evPL9lV8GBlqY0BDH6UpIAMtUfpkMMnlb2klPlTCmNgMNCGhHJMHr5x4s2ZicIhh87aTn3fi4HLrdW1dYS+53AsdW7p5Lntdmc8e/aC87Oz3Egjj0cSLzyqzOfKyRpbGSmj0pqkJHPady3rVUOuJme1XWEqy2F/xDpFUxmGtqcdPWdna/peEkPvvP8WrrYcuo5h9FhnsVoxDtKxWDKghmM3SpNVHzg/l6Lj9ti+wo/7644386Sc4WzbcLXvclVJglx+UIoZJcouIRNMmRhMDvsUyohVH0LksD9SWpzPuFQxcT3Ep6T+A1R/R0Qx5t0p5t1TI97LEjye/lMgStXZhCiNyl1mVRxRoYPxFtQzqZ42K5TZoswWdAWqAiwhwM3lFX7wHI4H4T4VHKlgNwsjHXKdVfEyJNGZvzfJxLbGZA7VfExoU8mSYUgxcXvTcXdzpF5v8zuW9Ydq+lkh5SIxDKL1ZTTvv/82T956yS8+ejaxwU9Yxql4P7NXpZSalEbL9UDhNonXO+adsuhthzCfm4wVWTM3HogxgnIcu5aPPv6YY9tOMMDNzS3b3ZaLiwc0TcPd3R1KDdhKSkkKBlVXNW03Y3jlmCSNsxUt9YayoAOHw16Kgq2lGwbW2w1WKbrRk8KIVg2fXfY0Bt67MJyt1vzqs2v25w2NXeCgSNeVkI3wkraiUELSNUJIqozCbs9Y2dUMZ+RFUYDy8rNk9yLgUZVDkVuTaMkMD6MIIpLHsmBO6/UKaww3t3eC9ZQi/oxzpUJ10QrIWKoRb60ylpu7gUM7sDsTyohpLBvr0MbmkFiwK4OoOaQoXv9quyamyO1+L0q0CcbQS1a1GyQ7ulrz8vKam7uWpmk426zohz5fg8bG35JUCylQO6nuL0n3zAOGqcxDCcsYnduBK1IQMmOIuR1W1ETv6YH9rdQCCoVt2bJ8gPApsfs1x33P589bPr9qublr6bwQ26raUmnFxXaTiycVdVVJqthm4X4VqbMLbi04B5UFm1P14oV58CPK98CNeCvKkJQmacNhbDjc9Vxf3dHtjzRVNXk+y3R9mczCE4q5Gt5kOkYOhfOOLxPa5nPMKMKE4amiagntEHn2/AVP3n0CObu0eCiLnxVKG1LeOe/uDnzy0XMuL/fs746SOYuzvEkhj5qcHSpcJGPsVIKypBEs77EYtRJ6eT9Os0EyWcIyLwBpCIGb21vubm7o+sDFg3epnWVo7+i7Pf3dDVfjwPnDx9R1zfF4FIC1WaFdNZEha1sz+pFQ1CnUrDxhrRhWq41077WGcd9iNPR9y9qeYY0RsqI2ROvwKnHoR+6O8PRyxHlp2W78wP66Z3QiyLjs8GxyUkSrWVvKWoM2fgIKCIpx3LLRuQwrASHis8RRinGmCWid1UGymODQ07d7jF5hLPQhnVSRFDKsi5EHF+c8e3mNcRU+415GaSHFRqiMMOgNAtUYK8/FGU03tOy7nkAkkDBNhVIBTODBozVvPz7DBmiPIy+v91irc3cbw5giShuM0oze0w8jwUtiJjRyfZvtijEq7vZ7VrVhu9tlmsvIZr350mbnDZuDRpp6hcpSLVZGdRpoUpxtFTkdXSYtxUMQtFElgw+Ru8MesKh4IPExKd4BIyomxvHILz4+8N//+ec8u9rT9X4GxiHjTKLOQJIUrVVKGklaQ7WqsFaxXTWsbcWj8xXn5xVnKzhbi9Zz5aRrrlIp10WXL/CoKNX+tzcjV9e3kvK1LrOP8/3EWY6l+HEpt2SSiVsE7wTfkYxXICHlFarIDZw6B/kc0uZqjJpPf/2Cv/P38viqZVKgjEb5SaNdTVUHHj4yvNcp2j/5Cb7IoWTjNP3JC0/4NBalbTZSeqqX895nmY64kF0RQxiCp6qqfN9FjE5wsoLPDIOEmnd3IgPzh3/0Xf7Od/8ZL66u6W6fEW5f0F4+4+nzF1y/fMHm/Bwp4+kkc4WeJHRBQphCLCwLdtKooih/+qmXYNu20nLMSTHuEIQGUNUJj+EwJq67yMW2AlfxjffPeLgSTMc5hdEZL5XBB5RgXsyeVIiRkEDFxKpSrJzm2aFGGyFmqjiTXadnlWZ5aqV17macSAS645EOjbWOmASL08yEWxlbw9nZlttDS9f2Mx6FygkOJZm9/J3WGCpjaYcOV9d0/cChFWXTSCKohM6t4ZuVo7YWiyHEQN1Y3GZNvVlxu7+j63ucc7Rtmzcm6SSzXgsUcn19Q1PXnG1q1o1ju6lZNcLJOjvbMXS/pXAPpWhqN2XoCrhccIOY+klPSqs5FEo5f1xiZhVkUYYIn7245urWo3lOowJNM5CM5bMbz/d+9Jwf/OQZNzdeevnl79SoiSxe3HCywqbK7FaIcONzMLRHRaTz7crx1sWKb33jEU8erWlcYl1pNmtHZU3Wt5onUkTz8mlLvz8QRs8qc3BUoVMU06SyFpYSryF4jzF2Vn7MYHKIkaubGz785FMuL1/myQoTSD+FLuTsV2QMkV//+oWUMzSLfmXlMheGWxGF/R8Tt3cHfvnRZ9ztj5NRiwsDFZMw/aWkRNz8ZrVGGyP1VkYmu9EmS876k2LgYoSUSqzWK7q2nQybs1bkaJKUknjvqaoGA3zj/bf4J//4D/l33/8JP//8l8S7K7ZqRJ/V/OLlHceDoaob2rbDjyMpj5szbrpuuQemRV94UUoJDjiMHX7wGZuS8oyu66icwyhF9F7q56whJMvzfc+msTzaGn79sueu9tI+SytUyuUjqjRgUBwHzxgKBiTX4azGabhYW9aVZdRSWJyiFzJnCBOfLGW2/hI6L2slKNlw+9Hn8FXeIRQRedIhCBasNZydbfni85eQoYRsUbHGUFuDzsvDGSsUjyhwgUYROnEIUkh0XU9fgHYn/pexlupszYOmoQuRfbsnBE/dNCJJpDWVdfhjSz8MbLc7DgchlDarWkJtV+H9wH4/SuG0EgnuL3u8mZHSssjTtJNLt4zS2sonjUshG6kA0SLNE2XXKf0aUsaFSPDf/g8/5udPPZvNmncfn/NP/tHvcnXo+bMffc7Tl54wJOKSHa6iyPGqjD4Vrs4EIgOcynfIJIYxKA5Dz4vbIx98ccWjB2e89WDF+29teethw7qGlbOsKodz0tWl94ara8mydF3Po4c7StV6jIX2IExoTQFSA0VzR2WFTgktNV88+4L/y7/+v3G332NNw9nZI6wtxlzNuApJZG5jZAzw8urAzdUdT959vBgLkEKTwtaXCZwSdMNAN3gur1uubm9zeUp6JdQTTERjXEXdrHCVI/iAH8YJ7oox4kefMS2fa/fmsh4/5LRzVdF1nQDBMbOSvcdohdE2V9Fbfv6TH/H08495+fyadexoVCcp/sqysYZ93xG0ZlM3HNojLgaqBjycwgrMnki59xgTSjusqQhIF9+Uvb/2eMBozWazYew7eislJdZVHH3gl8+O1DrxztkFRkUM0t3HqSBhkFYTFuXqQtyF3kMIisop1k6jQqBtPWp7kblrgv+pLHUyxkjw0qWlJEEiYgB9jAQf0UlxbANjUCjtUCkx9IFaOZTJYEuQLs61kURMv2gSkZLCGlFsSGqWwNa5PtCHAAq26wpSICHdnpPR+HHgLpDrGMW5CCj86Ekh0dQNoPBBPOzRj/gwst1uGYaeiwc7YopUjeP8wbsij5zpJqAJw3jiGf9NxxtiUlJnZFSaKtsUUdQSrSP0x6mqRWuVEwazixpKTZlCsnTa8PT5kWN8Rr0+58OnIz/57EBMmn7IjN4EGDtNRnGR02ScyAB5mbTZZkzgYslIyYoOObuRaEPiur/jV5/f0Pxc8f4757z39oaHuxWPdg1NJTo8Y98wDIZ913F3uOX9956UoZgmV0pBHnTKEiV513T1SgxBku4bMUV++OMfc319I7VqC1D5PrYlutoJVED7QNd5vvj8GU/efchp6ZBi1nofUSniuxY/jHz29I6/+Muf03ejqAdwKiwn2lYm81oqXFVNmbiSQQsxSMvuRZg3lXJkr0rgPUXTNPIdIdCHkTB6vvH++6zqip/efUBUsO9azjcPePnF51QK1hW4BI2BmDTKaFxU7G/v2Gx2orDhPX3X4ZpF3lUpkeJVpzWFZTVaaxmNaHa7XB8oukhz1nIq9DWaROT60PPD/w9tfxpr25bd92G/2a21dnP629/7uqp6xSoWi1VikbRIyjQVi2osxI0UBXYCJ4gCw0AAB0GCJB8CA/kQIPkYIN/sIEAcSGkcSbAFUZZomrJFuUiKTbHIal7f3vbc0+9mNbPJhzHn2vvc94p6D0gtoOred+4+e6+91lxjjvEf//H/P+y5ue947Sf3qHUi+IGZUdTO5Pc1WKtzh1dztuwIaYMrVkZTWYOpKs6TOLoUxxxrLNHLRPc1dvlWEwakZFSmphsCKVlOz4+JKXF6dkozaTg42MVkWWURBTQ0taXr+xEAUBnGclqJ+WlCbOZDM6pPKGA+mZCC6Ih1A7Q+omKgqQ1JRxZ51CiSMklzQt/34xpaLpf5PuQNKwx475jvzmmmDVolbty8zcnJCZcXS7Sy1LVjufoxURCCD1TWoHK3TljnciONsYS4GcqVe5C7EqVQS8KvGbOfhJBofYQQ6ULk5LJDayvjDwqi0qhxHETWoChcKFJS40hGwb2EfJizm8LXKZ0+0ZdBaQmixiaGKE4cb753wrsfnuKs5XB3wt5OzcHOnIPZIYvVmqurpSzY2RRQ6CQcnKurS84uLnh+dsXz4+f0XSdM6pxtkKfzSfDxo4e88fZbQgTUepP6J+mavKiwUwwovfd0veKD9z7mp376FZQKWxnEtppDJAYhPZ5dtfyz3/kBxydLtDHUdYP30naOQdJ0Zx3TyZSmmY4M7JI1hcFfE6yLuUS4NkScg5TWKpdgIoxWuD4xRs4vLth98ID53h6L1RK04oOPP+JgPsXiSV5R1RZjHG0f6FOiD4H5fI4yht3pLovFMrvCJJyriSlhXZXpEGFs5xfchvzwGmMxVhoXZiRgqqw6MGW1XAqetVpRuYqz1ZLna/hn3/d86d4uv/TqFB3XVFWdZ9+MCMgp4d31Aapa8E/vPSol5tOayiqUqlh1lajU+qKv5SFnqUopoirM8Hwk+Q62rkjaEWOPIbBeLXBa0dRTnp+cUdcTZtOqQPQjiJ9y8Csat0YpXAb3C8t9GAacq1i3PdFHmsoRfaTrI2sig1NMnaNSDt8Fllncrqor6lrszIZBZGdSTMxmMxnDGQTn01pMUavaoTQsFy3eJ4ZBIIUYAqvVwNXl4jPHnc8XpEKirpyMPMRMs8/gaVM5FmkzHmJz76/8pBAWU4zC0yidjRCIQyANHu0DSluSyQGngPEpjdhCAWAEA9KCVY1DrtJKLeUYbESJC2YkzFtIWqNiGOeHIxqfFN5HHq0XPHq6wKgTGvOQfrXi6uKcru+ZTqcoBVeLC77/xpt874dvcnK2sRCqXM3e3hF93wGzMZP7+PFjfv03f5Pey4hHCgGtM5UgbrWo4VpmkGIEL4D0R++fsDx+xHyCvGmCWIIwgi2FINSOh4+Pefe9x/gQxB/NiZheaVxYKwB5SjLAe35+LmSNlEihGIynMauCogMVRxmVItkiXCiNajQ2OFEi6HuCDzw7OeX47BxtDFXTMLGWVUqcLJZUeFqruFhrQlhxtmhZBU8z3WG2uw9a0a5XGShf4TtEkE9bBvqxA1kMQbYlZDAS+GKSTmrM/nOVc5tSI0VWq2UutSN7O3POz055etLzD373Ix7svs6Xb9YIE0DhUx51QbPoPCeLlqt1zJtmpLaW5mKgsYrJdEZrPKZOGww3iet30SAnB/ztzqG44miSdnjf05gyIwm7uzNWbcvxyRnGHmKNzpt2xOdAOA4+J4U1CEs9B+3ZvCHGgKsc3gd88DTNBIVoWqXKUVcNtatJWrNa9Qxe7rv20EwM81kj0jxbGXdIkX7oCF6Y7YGEMpoUhcAaE5xfLOU+BC+A+t5nF7j8fDbrORgZrfExW1sp8CGgmxoRb5RUx6gs56I14K+ltGksN1Tm18g4RJmqz8/f+DtlTi4lBBzUamt2blsCRfhF4zCzEmID42OsUJnrITY7GxzLaCOM7XwopfBA52UAdxUGjNZM6gnni0v+y9/8r/j40WNC3ASVlBLrdkXbdxwfP2R/8lMoA+98+D6/83u/z6rtWLfShancJy/99niEfO8No3nwcHqy4vGTBS+/NB+B4xjLn5Ci4B1Xy5Y333zMxeUV3RBZnV8ynU6Fce0mlO5P14sM7DB4GU/Jn68QQ8eRyJm7SdvkzkIo9F5GVuq6FkKfM6RQ4fLoQwSuLq9QXoGGqqqZzXboXYNRiSF5VsNAJGEO5hy6Gmsd2hqGvh3n7aqqkgfLe4xVhF7m0jYQgNoa8cmcPG2wphKr9+yDGKey8weko9a2nQTqqsJUlvn+LrHrOF1G/uEffsz6aze4UQ9CR8mVwHoIDBGSEmGimO9DiDJpUBtDUoqoNTpnvVsF6fXsies0Ch8CLinJyOOArQUch4BzjhtHu3z48BnnF2sO9qYolQiD0A3In1M2Rp2di1OW863rmr5fo5BubowJ6yxKqywxo1Fes/IDSSu6YciuPANVs0M/DJxe9LT9MJb/XdezWq2xrsJqS9t2rLpzZjszFGXNOC7OrogJbt08pB965rMfk8b5dNKgoixUgkRorbIqpbHSglVKLHvGftKmpCkYkhwbTlAMUQDOLB0inmub2xpyN7C08HUsFIQcZFTpNFIimfwx3rTShs2jO1H47Sl3OMZsqxRcuTGgMydG1Y7p7TvsOcv5+Rm//Qe/x6MnT0DpcV5rxJYAFcQuqR86vv073+bJk2f0w8DF4gofZPhWZQ1q2AS56wGqyIRENJFaw3Si+cEbT/jwkaOoJpCzS5WJqstuxfHxBd9/4yE+yPjJZLKTMy257sMw0Pc9g/ci3I9gTyFTRooFfCmlqqq6FgTKrl/+uwQqVMQPolpgsjJm08jc3uX5BX3vBQOzQs8gJYy2NI00I4qfn1YyjLtarq65yIQQ8CHiEHXOvs/ZVIx4GANqCaSSORsSnoiMKa3WK+bW4qwVVxitGPpeZhCTwrmGqCxRWc57xdtPl5hbNc7K+ogxMCSJAs5KZkmMuEqzM3HcPZhyOHO00TJ4J9LDUdah0RrlNlQEYfi7vMZlgw7eE9uO1q9QaUAlJ6RgGzEG5hPLnaM9nj2/ZNY46sbhfRrvnQTA3AwxJpeCOVjkjaYMRIOswZSSmDYMkX5YkbTC1E4oJRlHVolMN5DmRNmkVqs1Xe9xVYV1UCXDug90bZ+FHTWXF1dMmorpbAelNReXl+z/uHhS0XdoNxXhMB/yLpHDjbYy2DIGB025DmT+R2HSghrNQyHzqKJQ562N6JiJkPJESNDQXLvgWstkegHIbWY4F9BKm80MmdFKBnqzHrXShRulcMZQWzdmheTTSjlQFMxdK83i4opf+/V/xKpbU9cThn4Qn70cnI0umk/CPn746BGrdct0tsPlal3ievk/dB4WlVI2kpBAHXxgPfSE0HP/7k2++vor7M6nuRsE3bJkh7nq0wqjJMtYXHUcHy9Z94lmOicGwSGKtC8I4BxCwMfIEFLOYjeBICQIWo/BqaT122XeyO/ZyiJjyMawSktHVpF3YsGQ/ODpGQSny7rfMua56TZKZidAfd/3hNyq1tqIbpn3AnZr4U4NQy+UkxBxteBVQqmweIQFHXw+V2tBG5brlczSZe6XsRYfAyaVckVzsR44Xkx5urDcPzDsOdGRQhlMQaLz9UflBz0kzhbiVNyHHjU5GDMpXcB6v8H55PevZ+8iOOdZry/o+hY/qWWgX4kmVDKwu9twtVxzenHJLXeUNeUZN1aNXPNGl+ZR6cYKp6zr+9yUSRgDXedpfQKbctBivKdKKZTRLFYrnFPUTS0ByBiapsY5J9SO2rG3syOE3eWK87MFVW1JUVRMm6Zm6Dv6ricOkXb9Y9KTsk5alNPGsmgHAclGIfwyYFxAO/lbRGGdyyTBPNhoZPB2NmmYz2p29/aZzXfZ3d2jaZrcFjbj3FFh/GpdzA43fBClys0hqyVmUbL8FI80hZLBjU92kn9PZFfcbeWozZHGJoBiWES6bo22bgS1FTo3EigiEFTasDebE1Qiacuq7wGFQY3cEmMszjmcVShEsaDvBtarJUPXQoo4C7NXbnKwK8oBEggSPj/YKl8AlXoUkXXb8sHDY9758Blny3VON9U13XFj7BhwSndIZ02jhGQwwxYnylo77vYlU3lxhq74q206rYxdQrncmqqupRxS4FMiDAOVc6OTcJnNKxiT6Ksnwbey5lUBvoe+J8YecpYVQr4PWgvvqbjuoNDWEtsi7peJp1qJ5yOTPK6j0MmKt5xxxCiKkqfLge8/7ThfLvmZV3e5v5clilTujI4YnZxH23d0bUe7ssymc+xMIbZvciu6vh/5UhtZ5A1vDXL3FOF8OefovWbwajT5jAgf68bRPh8/PuH8ao1VI/Kbnzt5FitrMHlqXci8HmsMi2VH33tJJIxhCAPLridYQ107ylyuspau6+naVsp4DN4Pgk1nvt7FxeU4mC4Cd5bd3TnNpOHy/AJtLPPZPOuCCTF06DqUaz573PnMrwRmU8siZK3zs1X28JJh4ZR3oTFZyPKnopJQYazDuoZmUjOfTTjcm3Pn6IB7t/fZmdUC5CrpnMjUdt6tcjDKT0keK4n5ppRWvNQ9ahOZcpAqO55ClfIov3wU40xcC67bhzCySwWZODw44Os/+VV+8PZbtEMvciJsCABaa5w1zJqK27du0A6Ji/c+oKqM6EdVMt5Bisxqx+6swVoZ4Yh+oO2WtO0ahchaNHXD0PWcnF6QysmiMtgvAcFZMai8XLW898FjPnpyQtcLc7hyFWg1BoySQSmVraRUgmHITY1cShtLU1QLtrOkfI9LKTVen5x9ldeXbGt7ABjAOkcDDH2f5wLJjUkhasYsSpfy2olBPrMd+rwh5akCY0jOkkcEMx4XIAZ63WJVgzEZbFAGoyu0qYipZ/CiUjqfNZApCVVVjeesjc0M+oa+7zk9P6Oq73DiKv7koyscU45mCq3iJnADTosHXe0kQFqVMJXF+xasz3w6xs3cObcxh2VDCymZlNYGYxIGDVYwI5XNOZLSoj9eKQ73dnl+fkXT1EJuVjEbpMhu6YzCkLJVPKzXA/NpRUJMOcoaCinSx4gBmklNH0R73vtCHfJMqwlGi5mss46mqTMWWTGfz4FE2wmtYL4zw1jH/tEeRhuqqubqIvD40VOGIXLv3i3spzxvP+r4XEFqMqlYriKTpoYku1dtEzbLNIhrakKrSFIaa2TuyIwXbtNlA0VIgRQ8REuKWQAtc5tKXa1UEm4T5RHVObCIyFZpzxUlAlLaSP9m3KlgHZ/kIuVMKesxU0rQtP3H1uuV4rVXH7C3O+Xx42d89PhYiKzaUllHUzkqJyMly6tLzs4XaDw3j454+vwiq0UEnDHsThvm84Ynz05YLNfSPtbiy2aNtHAnTcP+/gEHB/u5pChXAblOADFyfHrOD955wtnlmmQmNHOXGxaRvve0rej8iHZRRCG69EprTFWRvKdfLfO8obh6vBi0S4DaBs63xzy29YFKUAOuyaporXFVJQ+iYpxfw2hCGLK4nViRx/y/lLE0YzUqG84a7UQTnyzXHAZGw9DogUrKngRKGVQeZyl4TEwRVzlUskTEzNJam7E4jzaS6bRty5Mnz2ju3WB+54iVb9kJmmktGGAKmQqiYNW2LDuJu7uNGGck3xE16Ny9Lddtey5yBNEzfqq1JhlNImCUoh0COgmk4AeBPYw8JuzMKtZtzenFkkllBVtVskaSSlgjAUpraKaWbhhoosNYTT/0mCyG1/tIjIrd3QnGafCDKKmanqNbu6SU6DspEXfm8xGn7PpurGZEWQOGMLA/OaAdBqkalKb3ff6Khr39GbP5DH+5/iwhB/i8FIRBo1MRLhMFSZPNLmNMGOeIqi/FVpZyKWC40AMGPzAMltV6zeUVPHeJ4GdbIxbF3lpGCBRknMMAUl+PD4NWeRGWz9OZ9qDHXalgBuP75uyncKY20+wFf9oC/LdKylLzA9w42OOLr77K02enfPDBx1xdnlNXFU1dEQcvUrdKoWPiCy/d4t/61/81/s6v/Vd874dvMiTBB/qh590PThmCZICVM1jjZN5PgUqKaVVz/969HBg2i3kcjYiJR8/OePO9pxxftgyD/MyohEZ2wa73hKjwQY2yJgpNTAajLNpa6lrjqinLxQVh6InB4/2Az4L55aECqKqKum6yOYIazTuL3Iicohr/bdsgoQS5wiEbhpAZ6oKbFbZ6ea+Yz1apje6D1jJtEPOoldaGSinheIUtYD/f46SRzCzG8ZxjkrLX5KC36RBK+dr3vQTTvqftWz4+PqNxicPXd9EVaJPQIWJ1pKkMWruxa51SYlobsblSihQlgBZYwedOaTnPMoy+OaR062PAmCmrVZfHabIyQkwjFmuNZmdnysXlFRpJBkw2rFU5q9d5dKZylhADXT/kkl+aQsPg6XOAiSkyJE89q0X2ehAXKBnO1ygNve8w0aCNGjXl1+s1fS9+Bf3gadtH1NOGqnJ0YYCk6NuWGzcPmEwbnj45Zhauyx39acfnClLdoAlmSjWdE5LO4yly8jFGrKsIoUerPJ6gNriSMaL6N6kc80nF3qzmYHfO4f4ee/MpOisxbjpd5ZncgPGbbhjjX1RWjLzGOh4jC4XXufnFrU6ayt258SMYUSaxLMrfrQTLMgSqtfz81tEBX/uJL9Eu1tm1N6CN6PxMplNW6zUXZ6e89OABf/kv/HluHuxxdnHO9374BikGDvZmnF8uiUmkURKewfdMrOML9x7wq3/+V3j99S/lYLz19XTCo/jD773D2x8952I9EKPK1zxbFzlDNKJAsQ4tKJGWjVm6RoNoahkHxohCpTasrs5YLy+ziWUxlihIqlgeeS8PWgk825nT2A3KOJPWegTui+Tuhqkur1utRAkjhJClfytxFMlgsy5BUpEbIsIWDzHmcRKNc27jTJNpJqiNjmlM+Wc6ix8mla205Fz6XsrKpmnwQaYGqroi9TJi9Pis5c2HhtvzXe7dhDr1WXNcyaB4ztQ0EHXPxWDp+sCsLr2fzdjSi6Wzosyf5vIrBlb9QGUTF4ulgPpKggps3WetmTSO3Z0JsfdAlM9JKWPAxdhB8C2bNF0/4KqKhJTgAP0QCDlQT2Y13vd0Q0Ary3q1pK4bwaCiwBB9P+RSr0Ep6LuerpXkRKRsBqbzKd5H2nVPSuCUJobI6ck5y8uWg/mPqbvXes2prql2bhCpGDz0Rbw/BZq6Iqw0AcWQNLWraaY1zXTGZDZldz7n1sEet28eMZ83VJXo75jMvtY5SBVlQ5W7E0brPBcnQcXk1xWTzdKpY6zpZbBX5ffRmfRmCvieO4XSMcmBMY8ZKFLGxTY3uGhaC4xS5rfSWEqazAdL0ikYj4TMCgYMu3u7/Plf/kWaZsLf/lt/i/l8zl/81f8OH378kDfefpf3Pv6QGAKv3rnLz33zG/zMN3+K+e484y6iHuEzjQIVeeODJ/zBH71BH5Qoo1oPSjqktTU0WZdIo0R/K88TppBL5STMfAFkRWrH1Q22a4iLhXCm0kZtchymzsYabSccpul0OmY/LwLqpTtUGOElG7PW0rXtyIuTh3bTMSyWYYns/5cDUQzCSHfOoayDUd1xUzYVWDIRs6qoQhsrhqIxYXUlon0jaM14bjHB4Ddidn0rRhV1VbFoe54upjy+glfvzjicJlT0Y9mdErkETdmdpaa2FegOqzVJCZepmEe82NUzKqscRIEx1l2PtZ7zK7kXBnGtUZk8qTJxusgbe8rQv1yAklXJBix/GmNZdz2Dl26gM5JtxZS4fec2ySba9YoQI20b6VqRlDGmItFTOUddC646xEifh7abumFnd06Igdlswu5sh3XneX52TuUcV4ulKHXmAZRbRwccTfc/c9z5XEFKN/vM97/MF+46/sbNr+K0FTaucbi6lsASg9wkKwHEWSvOrdaJGH+efRI5DzLgJ0OPVrRLKBSDsYNHIgXyjUlj126TNiPDlrkmL8PMKi8AeYHKHJxCWJR/L6VpSEXRIOMY+V8F3ZJdubQFVPnMlGcLM4YGUoKOC5+Ec9ICH7qepja89vId/tf/y/8ASBiref311/iVX/4FrpZrIDFtGpwRULvLtk4FePUxEUicL5f817/1uyy7HqUSTW1J0RDbAXQiBY/VlRBUG0eINaTI2nuiingvXof0udngLKaqCSS0q2kmc5ZLKfmIYdNNzddTgF1NP3jWqxWTHKgKuXK7AwhcU6H03ktX0znWa09MKU/JF5unzcNrjB1HhZTKnbr8vkZrkjFiQBrT9c0tl1EZqx7PQcfrtlwyBC40htK5rKp6LFsBurZlGDx7VcWzizXvn0750lXDvvFieVWCq8paHErWfaUMwWqGLpBstvnSiuQlcyvdvWsdPpVLW68xylBXZlRKDZHsmMOogivqlxlvI43PTSSKQqguOEUZETNoZbi6Wo80jZSg84EQIsvLJW5m6fuBy4s1KSYOj/YkU7poqeuKdi02YUWqR2gq0Pcds6bmy3fvcbR7yLsfPuR5P9CGgfZqRVU3KK2YzaZYYDr9MTHOZ7v7fOGnvyl4y0+RgUlJMVU2+ZRnNbBRxJRHPSZFUlaYu+Xnaiw8xgpNjXvBpkwrnbgYpbaXWJFIKXeD8jBuSetDFv8S3o4sRhJE8iBvTKQouzQpEoMXXewoNysqGUWIIZBCAu8h7/ohJRFcy8Ejei9lVChkVHm4Y2YfHx4e8co3fh6jNYvT5/w3f/Qbgg1FAStTLmVjCoQ0oBnQMeUGQWkGyGiQj4mkDR93DR8eD9i6ISVpCcc4kMJA8pJREQdi9KyXS5bLFVeXl3kYNHfelMLYiqqZMp0fUlknWa11zHf3mEwqjp8+pO3WDGkjQ7vN8i4uwV3b4nK3qmRUsAlO5b9TkgFdAactrqoZvAcV88yfx7pqsz5e4BOV4LHRUxLBtbQFzvvBo23JojbMbnFy0eNIyjiOksF8GZpNIxm0lK3GGMka1yvW1vHmkyVf/8IOP3VnQqWyYONIzFV53Q/4wdAlhxoicx3H8ZRyjbZZ52Vd6dwOShic0SKuqCSLfX52wWy2y2w+kWemZH2QSbobfDVSykG5JirBerVmvjOlbixnF0tkPEq6qMu2Z5XOme3XVJWjco6hiwxDZD6fc3FxgcLifcIGhVKRqq5k3YVAO7Q461ivWhanF/RnVxilmE8mfPT4REQ6fGTV9uw0Uyb1lLre4bMenytIrZYX9KtTCUGpMI6TSAiHjHlk9ngM2a3VC48kpIgPYrEc80MdsoxtDJGUx2KIXuyYgpQAIc+jheyESthWl5T3KiJzSuYTSKHYdSOLJkW0EgXKqKDzogFdG40JQYIsm1GZzFTJGVdCTJOSEPO2wH2jNVYp8SDMS1ClomklD4mLe1T8JLv7U9aP/4DD/iOZ2VNKzC6R0hElE/0l7R+B+9x9jGjQiVWq+P4fX/L8tGcYAkOQwFtXNX0vI0a+qoHA0PVcLK44Ob9gXeR6CzWgRPvLUy7PTulWVxzcuislVvB03Xokf45mEzGO2M02r8d7rg1Ll4c75O4XMOJYBZsSTzYRdQsRDAnlJRDZzOXaUCc2BNLyGd7HjQu0QjTYtRLnGT+ASWiduUhIqVxbvRX48pBwHvZ1rqLrxOKrONVoFJNmSvCR9brD1T3H51f8xnc1X7l3n5++M0XFICVfYjQ+BVieO67aJDCFDiONRSYJnMAFaWsTJXebteA6Q9eidRLZFmA6nXByfkVUhkkjw70+SoTyQ8CUWi+BjwqjybCFXOchBIbBY5xmMq3w0VDP9hlCYH54i7pp+OIXHhBT4OxqAX6KHyKN3aE6mIM2W2x+cM4xuXkk2GTeAGpjuL+/T1NVLLseO205OOxxNkM31nK4t8/MTZjYH9NYzON332Zx/Jg29Dw/ORU52pRyN0oe0HEXzViSszL5XCRWrBLL59IuVUZn7AOsFVatgNR2LMektFNonSQgKJUB7U1XT7oVWspMY3ICDOBk4aREXUtZuuwCISlmtSa0LTFkjXXFaDE0ovRJNL2lratG+kMB0AU7yw9+jKM+U3m41cRhrebi5BF7wzG3j2RUgvL9UWNNUj5XyjvhhBXlLjQYa2hXig+Pzzm57GnXMtpi8nk4V2VNpzVtuyaGyPnlhYjHlYc9Wx4pkyVvE8RhzcX5M/GMqyZorbm8uKBtO8HhtjtuOVjYPKQrWdWmhNlmpV+fUUsjWO6cG1vxdV3TtrIhOVuhyGJ6uaMphpbSIY55fZUyvpBZy7Ucy7iYwJR+i2CdIUSSy+VQXqNaG4ZsUmmMwQeP8hrjanldDjyT6ZSu73MGaHh4uuK//eEZd3dvcHeaBRhzQFApIbrxjqlVkPXVCh9MskCbA5POG1TAKFMqM9bDIHhXiPQ5qE+ahqlXnJ5fsr+3K2x5isR0winGrq9PKWO1gr1aZ2kmDauuZ7fZ5+jubQ7MjMlkRhsCr9/wRFtxOKvxJKbzlpu3s+qDy42OGOn9MG5AdZ0nCIYeFSKVUtyoa/YbMVS9iUP3nj51KJvkuaxgWJ/TDgFVb3eC/vTj8/GkHMxtx77ruXOvkTETskwEm9m84jFWLq4zNoumDYITRCGdVVVFUlvmk/niOudk5CREAbmNzIEJlynbF8H4edoaYu4sKK03srwpjmoMxihcZdFWY9tECDCtNYOBVKyAUsaZVB5izkEpxKILmplTqfBPpKtUvKiKWihJ0XeDtMmriqg0QzJMakmlxdUu5gCkM5haQN8MaufPGa8NoLTh6tRztuzFBaWTIWGUjHhUWV6ljLIoGMdhxhm4HIhtAqsMlbMyirJecPq0p57sMt3ZRxtN09QifgfXWvjFir0E6ZIlbM/2jdjRFvlT+FflgZasqeBTXdfl4FeN2TEpz96l/GCHkO+CjOBoU6YuyZyqhI4mM8Btxqs2GViZ39PGsMwyLc658RpZ5+j6Dls3osvlvWxGzuIQ1jZDz3KRePcU3juBJhkqJSqekHWiVCL5SE2UjRU9juvIuYHSSYKIkpIrZWqNTonQrtF5nKgbPEoLd253Bs44rq6WNE1FVdV5WD4PIWfvw5igMkZURbWsjUldMQSY7N3l7PkpT568yf7eLs8vlvzu28+YzHf44is3OV9eQaOJSjAr0ST3dD6wWK6IMTKf77C7u4fves5OzqiM5XB/hwut+cLeLve6huVlz/LsAj8zXE4CsRbfAdPBzb27qOmPSU9qPlfMpgYV6/Eh1Wqj8V12gjGFjZJyVk5n/3eZt9Nkh1tiNinIu3IURwtjDVpF/FDSY0WMoiutM/NYfq+IzkUi0l0r+lGSjWj6JLvJJEusKGMhtVidMFaBtbIDFVMGoDSulRI9qBDU+MVEJVRYxxK0Aqow39MGh3Eui51lYwRja4ytsNZgEnlYevPAppQ5QDojEymQiJiQ9YhUAjS9F5pCisK5KR27NooSRVyvR8yIJL50Ke/g5MaDdEYtzuT5OXnKCX1Hm65IaObzOcsYRLYll3u+70mqDD6ncZQm5ZJKlTI8X8ftjGq7BPR+yAFvQ/YsigrXgO9rGaYa8a7S7hdLdwNqQKmUcUHpSKbyeznDkuxLY13FdDrl8vKCxWLBbDYby9e85YognCqKmQmnHcYJFypE6Hzi7SeXvH16yJdvNDgrZgcok1UvYbVcoq3FavBBLFy1NvgwiIGDLsD2VnNHy/gcPlAZQx/ENDVT+qitpZpbmtpxen5BCCKmWGZAJduX7NuaMg5mcNZRuYqbt26xXCw5O35E6Hrwga71LBcde3sHzCcVxkyJTnHVrej6NTu7OyRqzhcrmiDDzLVzNJVh3cPubEqtDc4n3MyyUIGl9yxU4Ob9Q6rkiVUrGY6P9O3ApNp4Mf7/PUjtTS2ziSV6xrR7k12Qo1Nu5yKLSTzAMiejE1kQl+2cUk7Xy4OjjZALUQpXO1zt8tsrgg+48nAgLnoi3SEljDHF2irl3CnkDMpgSlZEhBjQxlPVDZCwTV1q1fxAQPJx7IiUHRuFYE0ZIC1KCUrrseuolEJVFaScAUaI1hKUlvnF2ojGc8odS0rJmjuZRo9kU4LgfCEFUmUxTqGSpq5zAZjE/QMlu16IAT/IbNY2FaA8BKVhgGwNeBTBhMzALjhNwvvA4WwqEsKDp+iFFXWDajLZBFckg1H5GhdcMcFY4heMqvxZAk3xXStlYykpyzDzqB5Z7sMWGD8am2o9rrdSrscCopMksyjBDCnvqrrGVTLKcX52nnW1DK5ywmzfUoH1Ps/Y6SL9UugGicWi5/d/+JRv3nuNvX0ZTSrlVkpiCJL/kxAF6hjHY2CEC0bWeQ5SOskdstbRecF3S6fbaukiWleB2uP4+RVt31MbndfTZj7Cmtwhz7CIto7JfI+Hb/0A33dopei7lrbriDHQ1BZnDNV8zs7RAe8+/IAuq1Ysux6VFHeObrJarWkmE6zWGAW7ruKunnE024E68sSf81ytCZXBxzWDSZjKoX0krDy1njCb7I6+vp/l+Jyze1P2D3dIeZGNw5ZQ0qfxoYAkmt0xooyQFad6RgqSEhtrJWvIALgyZkutMgeNgjdIRKLIosjHKSryZ6ZMdkzSkhWWcnmffPI6r6KUmEwb+ezMlxnbiGTwO+s6xxiu+auNW9r4ynLoLOiUr4NSmLrK10Jsf5S2qKpCOYvKkikbesTm2iUv2IvSMn3ubAGkIyrC4U7NzGkuDGjlcz8p5tZ/zPhLAWU3QWLs+iBcnCGIkqTOE/0xY2m2kox4vV7LAx+2B5M3pbwkKWq8TdrIyI+w1NWYUW0HGPke18eTXmSrb9Q+9Sd+twSP7Q6iqGEYAmp0hxElzoxF+aznlOVjbJ6Fa5oJ1i7ElblK6GQlm9YbXpdSirbtRZkzB826aYi+hwirTvH775xx+6f2mTny2oz0fSIaB0izqMok2tHJOi+f7QaEypCJ3IsASuNzB7oETpWbNUkpmsoxn0949mRJ1ZhxuD4h1nFWbzIpHwBdk50cGQaPrYRGEIaB2ipuHu0ym9Y8P7/k4x+8yenVFfP9PdrVQNf1zCZzHty8TT90LNZL+hCpXINLUE92MAf7PLt4zrOLAW8qhk5xsVpx68aMI1WREKnqWT3HuZrKbBmK/AuOzxWk1HSOchNU9NSuklR6ZGzn7lq5V7ntT27zA9dMNTOjEhWFzi8hfxMwkorjTgTi/sq4V0jtrQJbD3guP3I2NXZxBGTafK5SkNv7ksUhomjl4cm92yTrDS/+1LkczFC+gm2x3yQnnDNHxvclRrwWEF8ZRxcMq0AmT25+Oyf9UIBgrUZHj5i5UuW6TGc1Nw4mfHSxyL+dswTkPlhjCIPfWvyi0Ng0NcGLBHSgh5By6zrlLmqkaqbsH96ia9f4vs1Bmrz4owj1b8n1Ir2rLN9csmlE8z7rPG2fx3aAKp2ivu9HV5mSQRUFhu0Zt4LPjaoNaSuwOsfQthIEcrOhlHvb/CmdGzkKjXPZLgoR+xNqggS8GGPm/2iszUJ0W1wxlBbt96Q56Ry/9d4aE9uxBJ7WjvtHOzRqkDEpXcowUQApAQU2QZtU9tBEPwR03XC+WGb8U2/WbQbhjTbMpzXr+QSbvAgI5scNrbIxqyzdxWLNdF9hY6Sy8uwUYnNlHa+9fJdX7t2gruDk7IzL9YBWltQL5efmzhGz+ZxJ5bh5sE9MHldN+L3vvM3xxZqT01PUwxN829L7gTasWA2yAf7lX/wW01rxzgfPWA5XzPbnwon8HKHncwWp77x7xrxaCFhnVN5BJcMRXk+WkMudhhizUWEI406Qn2ghnxoztqJlbiiikkY21c0C2yYIFiZKCDGPbmxnNPmckhnxl/xTiv32BiPZlBgpSUu81PMxFi6XlK0l20lJY3TBz2RhK5TgTqXiGJsHiaikTPszXxWw9q2zirevJkIzyKMUFEfljLlQcDWlCTGXy1sPHUrz+pe/yg8e/wFdL+dllCJpMQeoKgHCCWy+K0KU3T3YxQ+B5eKSYeiE3KcN2lpmdcPO7gGVNSyu1rITOyuWUqlcDcZ7UbprZQZMxYTVGmWkY1bGUPTWNS+dv4I9lUBTgHiQ1vYooodkSok0gv8FbC+ZVggRhWSQHp83ADm3YhAgciw6l7vk99U00wl91qvqup7pdEbf9zIa4wN9P4wBdMz4vMdaw7rrOFt2TG69yhd/9ifZm1aSMSsYLk85e/cPmKiBKoPjY2At2W3e5EYFhMKLU4nOR+qppVu2KKRbp4JcB1vWWFI4o4U4HaLQfWLAB6kerJENJJFwlYDm3sc8p6eERa409x7c5esvvcTR0Q6r5ZJpM6WZNEyahnU/MGka9vb3qeqa/Z0GnQTHMNFy/mzJ44cnNM7laYxcRVjDhEQ/DNTKYJPl8nSJM46mmVHbiqn6MVEQjqsv0k6nOKWzXVOZpVKjzZQ8ZHrcKYrIHKoM+25mlSR9NZlpm6hVYcWqcSRG5axkZDyTd8pUAO4sJSzMNQqHSW39T45Sl2ScJleC5WFTBRco5zi2jQq4mf87B1q9eVc26n4plz9lx5X/M80eRrV84as/w+FuLQEwlSAlpVw5PcGbNhnStaoyf/5XvEfNdvlHv/HbPH3yjJQS9WTCfG+Hru0hl9Ab3SJNSoHV4pLZfI87915iuVoSY6ByFU0zAa3wXcfi4hIfslFAEHypZBoppa15PC/Ds0qcRGpXXdtUYgiCO76QCZWAFUJ2PE4SpHUmXhbCqGhK+VFQEBVRWkqhfhC6QtlsUtRoYzHaX7tUI2Ezl0kv4lpN3dANHucsIfTjRui9ZzaZZVWGNJ5T4YhJKRs4PTvn8fNzbty5z9HUYhJonbjA8zREogrUWjhLUiaLQojw46SxM6p0kjEnAushYZLJPEB4dramT575vGG3NlRKZioTEZ3pO2SFi5Q7jFaJEzVKMZlNaaYzrpZrUTxA4UOEYDm6fZPDwyNOzi4w1nL79ktYN2NvPudsseZgb5cELFZrbhze4Y033sM5R10BSeOygsXgB5yxdMFT1zJsP/SaH771Ic4YhiGw08zRyWCVo+LHVO797J/9s+zMZ/I4qjyIO25OEjBGbGXr4dou2679teAabOrxNFY9OQykrV/c/pwX3hPFuBtv/1CpF34rpWufL68a06Drb1g+X23994vf4RP/svXZKJKStDtpAW6Nyd3EfB4qjUwoOZN0/d3lo3NpkL/FpNK8/tIX+IO9H+ByuaZdRRcDLQltDORsJwRZxDJ06zk/O2ba9ewfHpEItOsVQ7tAac0w9BRfQ+FUyXc3SoPZZIk2l0xt17HuO/TQE5sogoXOMZlMWHXdlhgeIwViwz6X4CSlnYxXkGAY+vG/+74bA+Y1WZPENYBdayPD0rncKrcNcjap8mRDHr412gjTPYnmulKKupbvX9c16/Wa+WSGs46hNAK2ys3iLr1arfmT77/NG+98xC9+/YsolTPrkMX+ktrM043LKeOCW7gcCOAflWSlUYmHwGqIoGv2b9/mg6dnnB1fcu9wxtHU5exLIAGnNVgJGDEJHuWyyacyFls31NMZp1dPCcpRzQ9pplOUsRzcfhnX7HJ2dcHRzT3qqcXaCbZp0OuE0rKpxtRzfLom6Ql9UHRLz4OXX+bO3XuslwtIgVdefpl33v+AWzePeHD/Dj98811ef/2LKODjR8cc7B0wPzhkOt/Hdj8mFYTSlQJR4iulyLhyXohEY2fnk+80/rHpSLz4u38a/L8BmuV91Ph51z5la3VIXHjx4S8Py+YB/OSp/qgQ9OLLNhhDOUfBp4Q+UKQ2ynfeipDXI/pYon7KZ5UApmBnPmU2mVA3DVXT8NZ779OHQbo1KX2ilb/BhxLr5QVhaOmGjmEYmE9nTKeSOch0viXEJPwtyu4s3DSRGu5lPq2qNqoGIdBmO69J04hCQdyUW9vnUq7V9tjMMPTjZ2uV5VystOzDGHDD2GxQbLhYIu4nBNCYBANNsQQEhCtV9qERqJeMyVnH4H3GnxyF7nC1WDCbifyyMmYMlIV3FbxIyRw/f863f+87/MI3vowuY1fBSwaVIkpJk8EYQzLy3gVqKKUfGfI0Rpo5zjr25nO6J0t0PeFL3/w5vuRmvPnDH/L4/bcYLlvmjaZBxrNsRlGsFuVLGQqXL6wne3T1EbN6h/mR4ej+l5nu3qJuJhhrqWczlNZ888YXhKCZDTyVhpd9ljzOelZKa15OYtEmTQqoaoeofyeaScOfXa1lxMoavvazPbayKAVf8QHjnMgRKU1/ufzU5+rTjs8VpN55dsJ82bE3nXJ7d0YJMZswsHnIYKvsuXZ8+kM/lktbi7q8xyczJEacaPObP+rzXvy1rQzpM/7OZzk+MdnORvdJ5c7Gdf/A/P1S+SrXAeZPO68xEKrIZCpzb0+ey5jSaTYc3QaLyxhKCVCbmbjIer3MWBD4YSB4kfqATLosmYg8Q8REzlw2EsKlnN4GpmOM9MlLRtK2Qq79lI4eW9nRNu7ovRecxRhAXQtk5RqUDWf8vSQDvEorVBBmd5GQTlFGrgTPgrbt2dmRAdez83NsxtJI4JVw45yrxN7eD1lFNAPNSo3NGWMMlXMcHezy/rsfcHx6wYNDeSbEeDOCigSkK7vJBjcwRsyYmTKFJ2fphh5lDc4ZWp+wtqGa7qCm+3z9W/8SX3z9q7z9g+9y/NHbNCmSgkI7KOPxPqSsLCLPha5mLEOF6xLNzg3cZIdq5wDtDFEbBgztsqWqLNo4lssl/RDY3Z0LJcIaVDKYuNGC11kwEchmC3C1WHFy+hBtLHfvPgCVqGdmfE61Fdnm5AMXVyecPvroMz9bnytI/R/+z/8J+4c3ePX2Xf6nf+1XeXBvV3zQ4MXtfvPX7Z/n8i5tv6Aoa44PkJR621mQcJxKsbP1+k88yFuv2ApyY4m3nVmpEtryOYzBYgsP2vq8F74ZJaC+eFwLVNeSvdJY+LTC8fpP/tTAmf/JWs3ewR7Pzs44Pb+QsmrLeup6sN/wkxKZZJoZ9uV16/UqSworQBMy07jIJ49BTl0XwStjRClzzZRSRO/R2sikQQwb8JrN5xVWPXCtcyfgsngxWivuyoo8o5qB81GsLjc1YpDXCnNfjEpHMmZMKCMUkRhi1uj22Rh1gg8l208QlBgWJHET8t6PAWzM5jJfKkURvvvyl77AtKp48933uH/0dSjBNkKySmg4aTvAFnhjs4aUUviQaOyE5XJg0Q90YcBHUdEwpgKl0U6xd3jIT//sL/D4zl3e+8Ef0a/XoPy40YWYcJUZu9XDsCZGgzb7aGtZXp2R+hatFYM2aNewuFrRNFNuHM5483vf4/T0gp/51k/jg2Z/b4euG+i7gem05nKxZDqboIgs1x3TpqHvB957/33Wyyt29w5ol6doq1ks10ybCoLQKLQzdBeXPH77bWb2x0TmXKx6hnBK7ab8/nf+mPvNy2Sjig3GkkuvuPUQqwJEp/LgJlFDULAZzc2lUFIiE1sqwgK0K4RzpTaZR/lcgCFpfAberdIsVku6dk0MA31QWWPdjuM1o4lAVWFsRSKiYuToYB9XHta4XcymF0PJv/iCKTZBKXdk5MdqKxBuB81/8VFIik1Ts7szlx2wdKbZfDfYZGely1YWcUqMQcFaS0xp9LeTWUTpVqboEfayE+WHIO9XurHBh1HhNAQPUagbs8lEuFoxf26+T9ucp20tqRJYN8B0bnqE7DycxzOsVVlzW+RjitGpfB9ygyCO3w8QPpgxpF4UMqXMCygUk8kE7yXotEOPdZLdGC3dQNSmQ5qScPBiCFgl0w9t13O5uOJf/av/Ku+9/yG/+DM/SaMgeo9VeYPLfxZumdYpd5MVMuMHELFGgYqshp4hRAYUQww0VY1ydabFyL0zlePBK1/gYGfOG799jlo+zfdVGPGV1aI/RWR9fkyrV/Q7cxbHT1gsL1hfrVBK00bNwZ37hADLVcvPfOMr9Fdn7E0rlufHvPf+Q7765S9yenbB8ckpL929zQ/feIt79+9hjeLDJ895+d5tLs4vWayWPLh/h5OTR7x79ZSqqXj/w8fcONij0pbaVKzWK/y640ZziPlxYVKNcwzrDj94/uSdt/lW9TF1lAFd70OuW9X1nTbJQyU6ODGT/hQBwxDCRrAORT8MDCGBEmpCCW5Ki8mnRTExmfYEwgBHuolvPLngn793TGMtk6qi7zp8iuwdHPDkyTMqrXFGAuDs4JA+Rs5OnuOcI2lLRDOdTfnlX/oFXnr5JWxV4Sor3C6kNV6wCdiEqLKAy/HJsk/+T2kFYZOtbd4nvZii/QsOCeiTxrE/a2iqWjpdxn9CMaCUYhjouy5nFvldVGFV+/H1OmbnFOSh18aM5yZ4R9wA0yHmMRSVeT+5+E9icGBtRVU5QhtGh58QN7rnMo9ZSKhhnAssMizSgQuEbIppjMiyWGtzeSo/T6SMf6nR6RrE9aaUv8YY0QtTkXZo6btu3Ny0sWgtbXL5b5OJrozCe9uifdsdwxQjDx8dc3R0CH3PMHhqp0mhx+rSENnkTdtk5L7rBeS2Rc/csGwXrH3AWIcPid4HprW4CWtFtgmTzDtlVQGtEkqUDMWKLMkomskUF+cc1XyP2/e/CMoSlZB5lTHik2kdREkOdndnfOWn9gGhyPxEfUDTVOxT00z2qJzl1de+LAbBKvCFl+bM5jMevPoT4rtnNa+GKNiT07z+tQ5nNDom3v3h95lOd6nshK++/nX6qx+TxvmkmeDbS7rVkovWcLocuFd7dELapykRUxSXCyOLN8aYOyk5f8jidD5EBh9RlcU6oQ1UyeKDpx185nlI1yMMog/kKofVOVNIid4Po9SvU4GTs0tqo7HZDaVD8f7JYw5qTWM9foCI5+Orx/QxctMpQttnLWzD86sV/+jv/0MarUla4eoK5YRwOp3OcLMpzWyOdZZKw/7eLrPZjN3dPUiJ6WyOq6vRgddqQ1U5kSEZCXn5GAOTLLyxifgvOMoyd85y99YNps2UqqphtRrLppIRbbf/JQhkwHhrZKUE2EIXCN7LGI91Iy0jZjVPlZUBQiozk4IHWWPp2h4FTOczIjD4gbqqUfkeCql0c04hbuzbQxAbLWsNYMbvIL8rf3dZqpiEyFQPg5SeWja0YeipjJERlJSlgq9lblJi9n2fR0FkasJVNVVdY40dS7mqrlmtVqOya6EslIBeOpVDv+b50+e88eb7/Llv/eTIx+r6luAHVCXZc6kGyJuTNgaXTUZEhihRdrCExhnHECM+RFS5D2SuX4qkqBE2u5dJDAqfTDI8a3QWvdMoZ6lnDVdXzzl5fgxmh929Q6xrJLvNDTCtNMuL07HpAJL5rS7COFbkO4VV4HtPJGBNRbvqcPWarutZLs758OFD9g7nTOcNH3/wmFprKmVYnJ1w+8ZtDqpD2g+e8OTh488cdz5fJtU09E2HVQNx3fPhombwpaOyMf40RiK/YEmGRHG0lRkzGXBXhACmDbigSEpIZushcbrqUUozySQxlMl8DOiy33CKiTCIRGplAFOTErQRfPQ0MYFxLNcdE9ugVYDcsWo7z2qI3Nmf4owA232Ci8USPZvkWeNE27acrlr2Jg2Xxxd4EougGfDsqUBlQWmDqRrUMFApmUULzhGMZWY0+wf7/Hf/5r8Hyo1x6bqACSNL/kdlVNdKwST6Us5Zbt26yaypqZyjqWvpOG3N7EEWVMsZiDEW2AjHCU6X58KygJ1gL9ezBm3ydEzKVuwIPy5FcZYx2lBl1cZ2LXKyq/WanZ0d6mwZVWbfRpDdbGgEWqvsy6Y20iAZ1AfGGT5jJJvTShoRKUKguMREury2dIxYrpf1gvtEUh9ZLZdU+/sSeHKA3N8/oOt76qahrhtizIYMLkvGZJOGYeglYCsB5bvliu/9yZv8ys99TWSCU2LdrfNQfCD5iHUZR02JqrIYowqtD+/lfSIKqxw+aozVtMOADxHjGvkOSl934UYT/YAKgkeRZa6FqJm5ikrMN5yt8asL8C2V2yX0LUPXj9AM15bXC8jrpzStlLQnRWBRKy7Oz9FGs1ye88H777B7MaGaOJ59eMz+dI41mvt37tLYmgM9p31yQfvo+acv9k85Pp/N+mxO3/V86cs/ycRVvD0E3sqEN3nGslQFpaQpeJQa5U9UDliQBe8ybqGUlBAhFmwrYXsJeCgtUi9LWeyTppE2pm95+vARTx++jU6BZZdZyAghNCZPHzXr5ZBDpcKZSB81PsDDZcDohE6eCFwMgdj2tNbkNrFi7RN1SFRKE5J0ufohoScVikSIimfnV+zWFTsqkQKcr3uu+si9aU1cd/h+QKlqsxa2OlTjD7d/9iOO68TIwO7enN15w/7unFXbslqtx4cZNqYIJauSjEXke0upV8q+kh2UYddCio05WFgjulwqJYZexiaUtdL9QmyhGleJBK+zpFQz+F6UFnLZpAhCAEY2qEJfKG44IQSZ6tcq45WJqKQbOQw9RjejUkHMbs/jYHcuFVPaiPRd63Dm66dRrNcr5vNpNl0IY4ZVbKym0ynz+ZzVVna6PS8oWZHIHseUePzkKctVx+HONAd6j1YyoKxjnidIiSEoLlawN5GB+JiECBtCwlpAiSSz1op1L9hb5SZsbNw2z5P4KQ6QsiY7kjgOIWJ11ktXhkFXUE0wxnFwtEsfTHYT3yy9VLS2CwyhNuttG1feLN8NRJNy+ThEz3rwBJVYDy0YsW5zSgT7pnXD4WwP1cHy/OoaPvkvOj5XkKrqmqQ03/mjP+Lm0U32b+zT1FWe0tbAZhCyjLCUh48SqFRhgjuSciSdNm7ASkmakXlFHSLYFRFTyaggqMDaWykNbEOYBeJkQYiepokZdBdZjAwfj+C8BMfIVOUZvaSImjzzldjdE83qdsvZAzvjIge4Us56Z3kWFDb79S2Soh00l0pUEnqvWQeYzSpefeUVtLN5rEGW+KbS2+BSm1i11U18Ed9SGxKgVnDjxj6vvHqf9x8f46yT9N4WSZGioijYRQGYlVLZI22DGRa5XJ9LLNG+ltK8dEf7tsMUw9Hc7SvM/hRFFM1aS+UckMTOaOjHzCeEjpDlbVTOOFPGuEI2BjBK4/2AtVYyuxiI0QOJGDx91+XMzpJUwgfB4IroIZAVUzfYYcG9YpZ8TiT6rmW9XlPXdQ5iPReX50xnMjzfrmXSfzqdXivx5MFSmcUPyhpIkcfHz/mt3/8u/9Zf+pepgzQYSlmulAxhExXrNjCkSOM0lQLjpljXSAA2ZThYJJZXywGltWhb5Sxu7AuW+1ioDvle+hBxrsJZ6YjWsz1e+smfZzATrs4u6dohj6EV2zi5txu7NK5T9j5lTV4PWjkhURA8XK1WDDEQVwN911MrgWz2dnaY2oZ7t25z8dY5/XqFqcwnP+hHHJ/PZl0pqqbh5Pwco06opzW/8nPf4OU7+/jgR+GxOGZEWTkwirOEdIEEo4oxMXhPV5x1s8qn96KhE4Nn8IGhDQQfMCkKaU1bzpct2jicrYkK0eVuaoZ+XYpBNv58hfSQyBtSvqcqj7OwUV6QR3QEnLfHakZcYetG6QzwVzGQFKPtUJUUs6Q4ONjhr/zbf53dw30WzwW4LlbsJWH603CoFzt+JbBIpmSYqMjde7eyuYUEkC67yFbW5ZKuYHhQaBYhBqLfZBtFsUCCWy7atQIjgS+kMHa6+qEfz6FIAW8HvKJeqbVgK13bUlc1ISZiFvQLoZTe+byCaMXLd4aQ8gNqbfZ1zB5+0RN9HOVVija9z4FWjo0wntEK7yMheDENTQGlBbdarVZMp1PJntYr4f8oha1qVq0QYpumGTXdgWyBJd9fiJ+Ryhn29/f5zvfeYjZ1/PxXv0jnoVGakJLIYUfptu3PDc4apOTWJFuDrTGTnqpy9N7jk2HqHO2wRGuHayZSxpUZ0pwFpQTBD+gkgZMkGvhknSqlwdZzDm7e5+xyRd+eyMB4dv8p16h0oMvmea3v/ML6e3EDhURxsPGDZ7Fc5+ZNYiAyqybYytLUE3bcDtNmztXkEhRZKumzHZ8rSKWUmM1mnBvDatkydAEVAj/9+ivE2KHQm4dvO5/keulbZtfkZ2rc4VJ6IZLntD3kcpIEfdT8x3/3N3h60YFWrNsWoxX/83/vf8zOzMkMUwZJY8gGk1slknBl5KEMUYwZY4hZez3mjEICXDFXKBlUiDGbN5ClkkVVYIgRnxIfPz7me2++C6YSKQrtMMZlO67NznqtzEuMwS9tE6vGn26u/afRC16+f5f7t484vbjMUrwdoNjb2+Ps7CwTENOoye5joqlqopfvKL/TkmJxThk2wSZrhAuWFceSqpSJ5QEuPy/YUdd1NE0jgcRoOt8Jzpcxs8LaLn58cRjGUlflMk9bS2UMk6ZhUtcslivaXoaOi5JmyQC3O4QhBglIUaMw8njnYKblwqGVom1blsslOzs7aK3xfUcIkYl1tG3HarkkDEJKrZoa51wePPbjw2qNZT6bcXSwhyERPLz7/kPUumOCpwpxo3GmIloZjC4sc6k+lK0xzS7RKPrQMaQWbSu6YSGjZy4bXFCGYOQ7EBOxb1EpY1IJhiDBWrrYGlPV+JQ4e34izYuMB+bFNmKgaev/xzfbWnc/arME2cwSinboWHYL1mFNDB6Hop7NRXVCiSXdB2+/z3RvzvTeLovlis96fM4gBXXdUE2mDOue1brnrXc/pPulr2NU7lCMKemGdlm+/DZJcjuabXeZVNbgLWCgRHqFyl0Sp10uBVqp362FlJjPKo4OZpK+fkp+UrInnc+jKBBcx6vV+JCU3UltnXdki5QXt4ILcs8/eHzKP/n2/4l1gNo1/MSrL2VpEPncEmxfwCrHz3+RiXXtUAJWl1KrXK/9vR1euX+H77/1Hs6YcYJfWM9qJEOmGJlMJsQYxmy1vK7M2JXSryzM8jmCHQ2QA/7IfM/BYVvhoMo26ldXV0wmE5rJhKikXA9h4/gCIh8NIk8Yg0elTRC0KRK0JuZsqq6qcci5/K/PvnvbmFHKjQLnLH7oBbyOIS8AMWow+fsuFouxtDTZrWYyaVi17Xie66x0WjU1k2YiAb18b6WorKNdrbj/2n0efvgh+198hSpEYWsrg8qSQ6XZM+62RJEIirmrlyAmA0os4PoAylqMq8dMR5W1qgR3G9qVWK7nBeTHUk5eY+tGtOpXK8n0txoq5fEr7P/tH157TrfX6afgpdZUeBRtv+KqP2Uwa5xROK+ZTRrmszkheP7wjT+iDhVHR3vcuXcLr/+0GuKFz/jMrwSODub4BCeTGSZGDnYcjYv4MGCs3gJ/5ateT6e2QwHjhfm01HLz91xWbf6KVkqsfkYBOpFVCYMfW88F+1HjyZRRE7IKZUGBUs7iFKSYV1IpzMsD+UmAL2XKAFl9tLSHJ1WFdRU2ZaNOVd5fzieVADleis2/bX6y+ebX5iJzKiaKAWp8jbOGO7dvsTNp8EHR9gODDyyWSxE0y/wjZS3Oaup6wvn5Bfs7O4QE5xcXxBix2RyhZArbCpoSiCRrKWoA29rlMUZms9kYqIqn3AjIK2GLbxM3BUOKwqVSkEKW3vUeb5ToriMjK246pWkqkebR2Rp86DeyJyWgxiRdP2LmZWUs0YfRHzEqUPk8hkGceLXW1K7C+56rq0umTc1isYQYmE2mEtD7AWMtTdOwXq9EG917zi4vee21B+zM5tzan/H02TNmYcF8JzGrpCMXs7yvzutRjWt2LUVWksxRxez/qA2rzqOtw7gmAxZyvca1ERO+W+fHSJFCoPVpdNARzMlyeXqZlRyK2a3K0wZxE6jKKnwhixrX5HbmlGGPUg0Y64Q4nTpUE9mdTjEB5r2YPxhreXzyhPcevs+N6SHRgT6a8aWf+sonPudHHZ8rSP2Nv/pLzPcO+D/+X/4f1Ic1/+H/5t9nZmGqk4io5a/86exptfX/1wPWtSJHqU8Eru1HWCloJvnG5Xo8JUXXDWQaYn7ppiUr76lGE8lCAiifPWJUpdYc/4QCu0sSZECF0RaqvMk4vahNfnhlFx6CLyTtDdCYtsq18Yul7Tcrv7D51qkgayUHyx0nY+iHgVdefcC9OzdZfvgU5yrB8vp+BLbrWjKF5XJB3/csrhZopZnu7I6ZT5v1m7YJleVkhmHAOXLGFcdgVIBnIPvWxfH9ZrMZ3nvBHYdBgOYtrC/lebuUEtZYxNQ0UmXZFJ27V32/ZjprmM+m1LXl/PyKMAxoI6z1wsIul0whxg3ybwofIyHF7QuZu9ES4JbLJXVdZwebxOLyksl0hlawWCyIMbKzu0tMjAG8fH9nLUM/8PY77/JTX/kir772EhfHhifvPOMstcx2YKfeZC/b1BAFaBUJIduTe0+gAm1pvWHdedxskkvt/N3SViBJAd+3GCXTHT4pep9wE51NIRSrtifQsXHdETehruvofX995V0DxK8fI0QxrvsEKqGMA2tYrNdc9c8ZVEfKs4qVaXCuZu07Hq2OiXctZ6rlbHjIO+89497rL33ic37U8bmC1B9/733u3O+Y7+zywXvv8Gu//k+5c/8mX75/h9du7aNC/EQc/uSX3ip2csZVLsKnXaBUSsetf6qzMWFKEKMmRUvXDZTrWOReRIdc5rnkvbLPGWXYtizeTX9NAdcEmKPeqmATZE9jnYFDlcTDTiuNyq7NIByUfuiFm0PGPGMUfmHKeljjOZarsnngxu+/lXWVP0KElLJYX4Ld/TmvvfKAtz98grMWrRR13ZB8T9PUxCiNivW6Y7FYs1qvQRm6JMFuMpnQ1PVon1SyoRg34zPb97Ou67E8LF2v8prlcjnKQ2ulGYK4BOlR176w9DeZlVaKFCJD3PJXzBnG4HuWiytqZ5nP5tSu4vj5cy4upREzpECBLGNMQiJOkm2v20FGqTKWVxjvm81JxoEWiwUHBwdYZ0kolu2apqrFiuzinMF79vYPQLEhypKo64rZZALJ80//2W8zqRJfe/UmfnfGng4Y1eOjqBQ4U9yVNwFTtkuZPRyiYu2hT9D6QARcNu9QqqyXTac8xEAYemyuHvqYGKKmMQarFKJ9n8mtylBV9YghXm//F/whN4nGyu86LpVII2Zqsl6ccZZ133HVXXE1XDDEvDFGxczV4r+3uKRTA4OJ+NShksj3v/nuDz7xrP+o43MFqd/+ozep3/hQLKnshP/k//NrzPd3+fpXvsD/9m/+deaV/kS2+KOCz4uHUqLdLPpKY8Gc8anrRVDlZPHrfFEHEsuuk+5Rfo3Ev/xOatOKvpbSjlnNBodS2zeplK1pK4CNr8+RUKArae0ajbWZyJotkfoYxjnGmIPTJpQrVCz6iZHtq7RZI7mk2gpSKYN2MjzrUFrx6muvMvvdP2bVefbmM4Yh0HeanVnNYnHFarVkvV6zWvdZI0mx7odxLKmua4zWVFl9IOUL0WdsS0jHOmNTjFyrbbff0U4riNWWMQZl7Wiour1rK2WJ0Y/XIylIWtF7nzPeQiKVzK1dtzjjmE6n7MxmpBi5Wi6yE47cv5jEQccacWOunKXrh9HNOPRxvIblPCKwXC1pmobd3V1ULmGGfsDZCmsDy6sFymjmOzsYrZhNp7jKMHGWnVnDzRv7XF2e8/57D1GrC6ah585BQ22VuBJlXRPJnsUOLVEoLUKq7SIsB+mSpZCF9uoabWxelwlSVpTIwTL0bdYJi3SDXAebVRZMs09yc0DT1M210Z6qrrGVG4NVUpsRqtHle6xStp/SxLSuc5NEbMbOTp5z5VcYV7OrD1DAtHIc7tzH1hPqoWM62cFpaUQ1ZodZM6dtrwsU/mnH5wpSHgkixijmO1MuzjXrtufpyQXvfvSYb3z5JQiRTwPYNsdGekViTM6iSnZSyiINZJPN0uWT5CUyqXN7Xetxca67ViSLQRZELOlUqb83GZtc7jQ+8KXcK/V6Zm2x4abkM8+1obxcb4JYSbaSzum5/I4A04U5rQmIWEuxxSKmcZeUN9kK0HKl8ntl0bZ85uWUQu7YgObGzZvcu3eT08tLshQkMRgWq5UAtl5wlX7oEWl4mZUU0mukalumzQTtDCWvqycTSEHoAyFJRqQ1bduO1IMCtBcQO6U0SnqEKM7PZS5vO5htH9uCeEobsILaiG8ixCDjIyhYtWsq55jUtfDroiIaobNQurUx0vU92lQj/2vjprzVwMna9z5GLq4uaepaNLKcppo2o5RwmT6wztG4iqP9Xe7fPeLerRuEODCfTrj7ra9x+vwZF5dXdLRM0sBQd+zNKrTVeSB6Q1xWSjGMZFRD7xM+iu5/SBBI1JOpXI+8GhgzbUXwA75vUSqhlHyjhJCfk6nQ05sMykn7f3dHGilb7HsZeSp3oLjVZNxL3E5zMpvnIZUA9zvTCc+eH6OMMPi9j/yrv/IXmcynJBQWqJKiUhXD+oq3fvgdfuoXf4Xp7iEffvAes9kut27c5p/8k7//p8SI68fnClIxhQz0aSaTOa6S9nXXRb73/Q/4xpdfkS+p1CYVUAXXUWOlt6l/c+qfL3AXI5ernifPz/nw8VOePXlEU1m+8ZNf5ideewWVd/FJ5WDrYidgtWpRyYgDTCpqQuQbu+mGpe3zSjKRnrmkpdb7xGv1tvNMvnlsZWYqSFDTqpR7smiCDww+UNrNkSQLU76wfEYmriZKENwKipTykk3JySa4hwQ6z1VZY3jw4A5vvPVufqh9BodhtVgSO1+kAnKglXP0MbBuW9rVCt91NLUjeE8zmTCZNNIlawVcFtOEmmLNZF0mfSLAeNM0JBL94HF1vSnntgIabHS9y4IoIH2ROu67Hj+I7ZKzDqu1cPBCpKlrTKXp21aaAhMpz7CW5D0+5bk677FIWZZSyk0LcpmlNu7Xcsvp246rqyt2dnchBuazmslkQt/37O3tjZl7TJHDwwN+5Zd/gddffYA1MHQ98/mM3Z0p3//O73Hx6AMOJx07FmZNJZZT3uO9DNTnJi1+iGAMtrboIRD9gFFJ3JKjDOqqUZYmL4O80fqhJ4UBCKSx5FVYrdHVjNTs4xNMnGXdtmK+ihBv4wvYnCIHKK3LIhwDWKlLVL4XtRM3Im0s51cLHp095OoPL7BGk9BMsdy0M3Z3DlA60a5b3nn3LXQ1wQXF6fMT3n33Dd796J3PEHHk+FxByoB43xGpKkMzmRGHgdit+fjDJ3TeYw0UwEWnrWAN4uOoRRrVJ1i0Pc/Oznj3w8e8//AJHz16zPHxKZeXC/zQsltpFIH/7B/8Y/7Nv/oX+et/5c/jlGIyESePIqgG0K5bmQkswNRW2TYGqRwkY35YS5m2oUFsY1SbjCtmMuOYBabNWIHK76sSRLKjcUYbep8YhpTjtkRCH5DMsFyTrI4w1pnbcMFWaVq4TgU8Ff6XmFKoIDIiD+4/YD6d0l5cjjiUSKJIJmAUqBSIUY0DwjElkg9YNH3nSUMgeI+KsHYO4yw6yYC31aCITCcNy1WLyde+qWs6oPeeqnLUTU3hdG1nryU4SUZV7k+2DYPMQA95kDnRe09EoV1NZTRd2xJDpK7FXstZhdEWpRvWfS/XxMv96AdPwkj5AtfPQyFlE+W2Crdusbyiqp0QVV2Ny3NzCsXRwSGvvvYyj588JiXPjRs3ee2Lr+FyjhtJDO2KaVUTpg2zOjLRA1Zlx+2CPcZISHLvUlQoI8qnoOjWa8LQknQCFXH17DoEkJdDVJGhb0eH5hAi68GDrjAWzOSAoEXHqXRjRz5bripKljRCIDGvS5XGtV86h3KJIo2rabtulL8+OT/lePGI99/YjLkcUvPa/A7379wnOYVrKj788D3e+ugJX3r5S6z7JdPdGftHB39KpLl+fD4HY+v5n/27/xZJBT54/Jz/29/6z3j91a/yP/zrf4HdSrIIlQXHysBjVIp+8Fwt1zx9fsbHT57x/sePefTslKcnF1xeXBL7gWnTcPNoh2988S6vvnSXB3fucPfODVxl+Tv/+T/m//l3/wvu3jziX/m5bzKp3SiEp3L6vF51sKG7faLkLOMdJT9h7AqVtDZeD0TkAKW28amtI284xTGZBB7E/FMZFIbBa7pBBHh11pfxW1mUYFKUWjGXmIzfa/srlFPQqI3sbAbEUgJtK+a7u9x/cJ9nZxebSf1hwNYV4WohqgzaMIQo1qmZXW6QlrVOiTAESNIdXC8WknUYcVZpnKH3Xtj+Tsq8YlNurCX4gbbtqJt6LO2892O5V+6DdMnIQ7iRPlvCg2RkPpexKXgZ8jUGZSaihOE0YehwVlFXU4Z+GBGC8n19ZrUbmx/CnEl94lBq44WnxYrr4vKC/b19VqsFe3uVfJcETeP46k+8xl/61T/HH/zBH/LRRx/xlS+/xu5MOs1OK3RToVRCx54wrKBKDFHGVnSMudQzkHEfY804sqS16Gk1RqGMATTW1Rny2Cy5shaGroVsRx8CdCHJXKSboKcH4jDzwibBp16C8sPcBVcvQBxjU0szmUxo2wGtDYtVx/HlUwZ6jNWoqLBRsedm7O7uoq3mbHnJ3elt7h3e5c13nvLs/IJoO1668woX7x9/8mR+xPG5gtTq6oyj3QZnYH93xv07N3j27Iwh1bjdHZ4thL+ybtecnF3y+PiUjx8+4vjJM87PL7i4uCR6z2zqODzY5ZtfuMtr93+Glx7c5faNQ3Z2JjS1RRFJhauk4N/9G/86f/LGx/yDf/xP+YVvfo3aGoRRLjwYrQ3rdZuvahpLpu2yreABKS/KOGJc8rDLLrdVGuTMapsBn7Z346yyGbdqt2QULms6o0SOpPe92HflB8KPQnr599L2IinnK/++vZOhdAaZ88/GqR/Ba3xSNLM5P/3Nr/Pmux9wfnFBYXUrAKvp2040onxEB4HqUzYn0EayNAHSraTvWZ5kMplgUqR2UlL1g6d2joTdaFGVjl4egTLW5rb+hoBZ7oUsfJHzFX5TZN22FOXQNL5ONMi6vqeuHFYZ+m5N4yzFE7CymoRh8ANWa6w29MFLJ0+VOdEXns6S6SuRFEp5EiEpaPteyr75nLPT5+weHDGd7aCM4eLqkoPDr/HX/tq/wfLqgtPzM5rqpgSaCMMQ8b2n1uC0YvCRLnrmTvjipXGitXw3ZYwEKm2xfUfyLTs7E676IZfTNZtMhq0gk2jXK1IYiAligGWvQGmqyQHRzQgx0tSTa7SHcmyTca+Rc0ecNn3iullrZEojBJS2nJxfcLk+xaceoxyzas4sOW7O9miaKf0wYI1jNp2zd7THzvffwdY1bVqxtzvj8ur8E+f1o47PFaTa1Zp+3eJmDVNref21V3h0fMnf+bXfIiTNYrGkaxcM7RXt6hKCx2nFvZtH/MTLd3n15T/Da6+8xN1bN9ndmVLbglGE0RMtDoXVXbKexKR2/PIvfIu/9w9+nZOzS1zlpA6Plpg1jtZrsXJKBfPJx7Y7yTg2vPUCCTKSgY2tVjKgXkCgfKgklIPRyDsV9Cn/O5HKZidcpRiiyIAUgJxUrLZ13tkLTW8T6DY7VwlWavy7yrudRKvynmosP4213Lp9h1defsDHH30kuIaRAO4qR99K2i+8W8sQZEJAxAMlGyhebjprV+9NJ+zP5hJ8rWbPKnoNT04vMW6WLadkSFdbI6z6HBzL9dv49Mn3EwPTSNe3+BDoe7GT8iGIfG82zxwGaff7IJIqAoR7hqHHOpOr4ZRfOxC9vN4AUWt8FEPTsPWAp5xhpBFbzNmvqxh8T0qRIXjarqWqas5PTwiDZ9bUrJYrHj96jLOG23duM51UtEOLpkIrcUvu+56JijirCV1LioakE9owmiOksdxLUqqngA0dtYnMKs3Di5XI8dSzsXmy+QqyxvtuJY2CKLpsfZBserJ3i6QsCsEIX5yt3Kb7fDLLEsBcENjrv+NcTd97ojL0vef08hilPRPlqNUuNs6oQmLezNFozi6veH65pG0jP/Otn+Xe3TucrBekLN1cRpw+y/H5Mqmup+s65rMK8HzlK6/wm7/3HY6fPuLO4T6354bJ0SGHO3e5fWOXe7dvcO/2bfb35zhn0KVLl7OJ6MO1h/x6ibbBY0iee/dv0wfNycmCgzs30VrGAEiJpBXLTnbisWPGp+wU5WZlI9BrpV2p1VW5Qdd3oPHcUtnpP0VqIiYRoCu5UpSB6YKJxIKBUQJpGoPUtQXD9eZCCVZpDGbyvXVuK4aUCCngnKXrew4ODphMJlxeXspn60SlG7qqZ71cIQaukoESEjPjmFrH1Fkqo9BOsIvaGB4cHLBbNygVqazh9S+/xJ2feIm//Z/9Ou89XWG0JfpBCI597t7FiDHZOj0HMa21aDxlHCV6jx8GumGgy9K+Sinxb3MiARPCIGMfWsmGZw0pzxZqJSoK63VL2w8U7pmoXTq0saMjzIubTeF1lUFo4XwFQFyMhSMma7S2GmLP1eUpy8UtUoo4a/BDzyIOVE5BiOK2E7xgSr5lHddMrMnD0V4ckGEE8MtaiN7jx/8WEb9V16Odo6qaDeCf73wJzL5dQxSpoCEqhqCYHRzQ7BxIt7aqqOuNjngJSj9qaFhKvWuDXtc2exH+i0I7uHjOYnVB8uBUzeqypVte8aV7t2mck8HuGPng4TNChKfPnnP7xhHvfvcDZvvSbPGx/+Tz8yOOzxek+sDp1QUHRzvEGHjl/m32dibEfs3/6t//d3B1QjD+mFnZadzlZdh30zzYqleuxaNyjFhBBvX2d+coW/Hk9IqbL92VNLZMsmjFou/G3ymgcMFtUgYJ1dZQJSlzjzJIPgLslID0I6gUkZxtvZhGCw5XV1VeDFpkP3qfqwvRSAqjEWhZLHJBSqelvJfaIo7mdt54JEClwmWSsQuRsxk4PTlhtVqxu7vD1dUV0XumVc03Xn/Ayckpf/i9d2iHQDYzoXGOqdEcTSfc3N0VTagUaNs1e03Ng4MDJpVjXlnu3Tji1W98CXN3xq/+4jf4u//otzlZeYYwEHtP2wt5lBBIQeOqChR4P5CC4E0ps7XbvmfVdQzZFk0rw+7uruBbRhNTQNOhUxqVJ7t2xaQyGCUM7bYbJEgNntZnCWFEf0yhRbnyU45CNVEqirxu5Wjb9ahlhtrwxF66f5eXX7rHrVs32d3b5dHHHzGpHa+9+gpHR/vszidUxgojfehJvmPiwGqbseiQFT+EyCubBojGeRi7xCEgxp1ZJUSZGl05wUTzXY8kTMYhh67LQUozRBii5tbBTZJpSFGmAYqi6I/iKl5jmef/FfL0uNZSypbzsiZ9CJycnnBxcUUfPClqFqcrnFbszibEYWAYIqcn8pq9+Zzj4+e8/pWf4I0P5lwsT3nn3XcI8cfEk0LB+fml1PpJsTdveP21l/mt3/pvefrkCS+/ciODeTC2v8pfk3Q4oiplikyoi2nX5kbIfHEGhCFnXYq9+Yx64nh0+oxv2p+gMobBi4qk0oa2G4ghok0mycUy2LkBl8vumBRjJ7AEplgyqLTpbkiQ2qTL28PG0qFLm64cCqLO+lpice1jpO8ly0CL9lCKeszCri2crYC46a4IXqS2cIVxXi6XVVJCirZ1P8gIinGWpq7Y29nh/PwSqxX/8i/9HDf3Kn7z7/8WV88WfHR6xuW6IxiDU5HXbt1iXjeEwdN7j51OuLe/z+2dKfOq4sZsznTasLe/Q1sZ7tzY42hScfz8XBQi+g5ioG89xlqGzuO7lt39PWptWa2WIpmSRGEBSVoxKIJSuKrG+4Q2FU1T03dLjALZcsSiahg6NEYe0sHTD0GyKKPp/CA7vXJUrkYrRTcM1zLegkeOhp3R4/vEZGeHaneXxdVluQE46/AhcH55wc/d+iZ37hzyyquvcuv2Dc7PLzMr3+T1JWstDh0q9ChTNp6MRZK24AP51kllK66kUcoQtcLnzKrrAlXdYO3GrEBWYsZpgyd1KxLyHv2QcFXD4c3boLLdVlVtreHtZfbJjXekCI1Pa94gc3Zb2YoUxXLr8vKSs/MrtKq4c+MWH33wEf3g2dmbsrMzR6XAEAMXi5aqqogpsmwXLFdX7B1MSdbz5OEjiiTxZzk+n56UMTx9/x1Wd2YiQWEtX7u7wz+1Db/7+3/Iq7s/TQxegksuJxRS/6fcaRAuht5E7gxUl+xjzGkzJqUzdjCbOfZnM06en1PZiqayrIcoHQ2l6dueIQUs1dgJ29yCnL4pIT6Wn6XxnkQZnxi7RFul4XbwKMEKZEQg5d+lFG6BunaZciJSt93Q5TJSlkEIBW/6EWNAL5SnSqlR2uTF1xW8LeZA7kNkNp9z89Ytnj59Stf1DFnT+9nJgl/6uV/k8FcS59//kIfPzzjvBo5XK6JK7O/uMoTI1XLF1FoO92bc29/jwNXs1hOmlSNpPWZFxmhM9MytZlh7dNb78n5Ak3BaQYz0yyv2D/bQNKxXKynv/EA/SGahtcU66YjuHxxmnacJ3foqT+3LnTLWyE6ecZ++FyebmKBvh5ylaMHSjGRRm9m+7dWwOYyWcqyQNvf39lmv1pkKkZhMJlxcXvH4+Dl/7l/5lyAEZpOGG0cHMnjd96imzjIqARVaiD1BCbZmtFQWKXegdRZkBPLAr4yoJ6Ppe8nufN/JJMBOhbL2xQIDkGs8dC0gMkZDTOwd3mQ2F9G+uqnHIe/tEZgfSbIumRSbEFVU2Kyxov8eIlFpnp+esmivQCe6oWW2N8XHjv3dGbPZhNCtaZcDJ1crjLMs2zUhBh4+ecbNm7e5ee8Bp0+PeXb56NPP5VOOzxekrOP04/fgscYreejvK82NWc3vffcH/MWXwPj1CGaWKxyVRkhSRrpUqHFUQbg+EBSZBZvF5tBZ8VORjKE3hlltePLwKYuP32ViEhdaZ+dXx7pbs3z+nGltScpkW3P53JT11yOJ6IMQ3lyp1+W2lJHjDVa0dQNHcHG7K7Kd1WyInU1ToXVxBmF0BR4HjHOt/6MWzIbn9UKgyq9/Ub+8/KnyDjqdTlmtVlxdrkAZJrM53eD5w+++yV/9C7/E7du3se+fo/YVR8B9Epdtx6rt6ZJnfrDPvK6ZVIZ7u/tMlEYnhbKai36FWV3hJjPJEjvPrYMDfDpn1ffSYVPyyFbOQdJEH1hdLZlMpqyVxfsBZyf42Mp0vq3Y37/BJA8kN3UjZYz3KBS2clTO5u+ZRr2vIeQpfm1GZK8QEn0QrlehYWxfxzHYJ+GQkTS+HwjOUVc1dm6E+KjU6Gz0/sePCClx//YtQvBUTlO5ihSQRtJ0IgEn9Fg1YHVEE3PGlgOVAE45g5RO3CoKrtZYS0wRq4sBg6JxNVqX6YXyHWR99l3H0LXYmMUlteXWnQcoJc7iwtW7vkZk+V7HpDbXRF8LhmOjRqlNRqYUy3XL87NTMBFUINAz258Q45qDvRnWKFRlOTu+5Pnigps3bmMrizaWi8WKr73ygFRZnnz4IRNbfer6/7Tj85E5mwkfnJxzvFhSaZlxsqnh7sEOP/jgGU+uAg+mWw+9VqTYE/tAiIhKYhSwXFmz9eBmWQ8/EEN+SPPN1PkiBg07Dt5/esXjN/8Y4ztQDq00xjpWiwv++Pe/w67tsgW0UAisddldVzIZnWR3qKqKXE/knU7IoRgD2eobLX8vBgIyJ+dAyW6tjARdIzUnUQXxPNMObbQQPDufrZbUCIJu1knKsN2mnByLvRGe2h6+FllgIIupqU2emJUunx8/480fvMXVxUomBKyjHzxvf/Axv/MH3+UvffELzKZTdIJV0lz5nqaaEuaJIQVUDBxMGg7nO7hconI453K95tvf/mO+eNiwXxnWved0uSaimM12SKdn7O/sjSMx1hhiCCz6pXR9Q8BWE2yA5WqNq6YkHbh99wHT6S7B9wz9wKSZ0LdXMmiM0CFc1cioSD+M2RFaSbfJR5QWlr8xBTDfaLa/OLxeslrUJpMqksh+GGiaRsqULHxoreHk7Iw//O4f8+pf+VWMgrqqSCFinCH0A37ocVbTdy0VPTMT0XEYh6eVEvqLVirrPSXapPjwzDOtFUcmslgPWAt9gCEm6maOMW6kvRTcKAUpe0PosHn9VLM99o5uikpsHjBPahuX5dpGV1QoGNeiJBWRrQ1SgVYW5xoRgVSa45MTTi9OGaJo6asEPgxUxnC4tyNKoVWFd5o7r96k0jXzaiINkeC5XKx45dVXOF+fsT/b+cxx5/NZWlU1f/LRM/7v/837VHniX2tNb3eIWvP/+vZbPNhNGAQ4REngUdFv1DJjIGRVSJMSldVYa4QQppT442mFTYlKK2pr0FZGSiplWfctj56donBoJYJyymja4Pl//cZv8WdfPuQn7+xBNoLsxpIsP/XFsSQvGAEL836nyBnJRrZWGTZSwtqglEVrm80CcposqRNog3p+gjbZ5hxYnh7jF2dUk5m0jBdniG23JSGBLmZqgc7EvaAZKQqyWjY4lrSIc8anBa0pHZm+63n0+Cl970GpzCyX7s96GPh7//Cf8K1//w6zvTk6WVyKmM7goyrAIRPnmNYVVnrm6PtH8MXbXD15wq3FV/mtb/8JL3/pDtO5RdUNH330nJ29A2bzXZrJjGYy4erqkmEYWK7W2WxAM905QBnDctWhjMWYCkvER/G6i0FTNzWKwNC3mZdTVEFlRjMZPeJMKQahOyCjKtqKL2IZSC4CedtHeVALDlmUREOKTMwUHzT90NPUzciaB9BYvv3t7/AL3/oZXntwm1objMnllNFiiBAjYeipDFTj3CniDJM2Wk7aZMAhKlAVISXaEOhDwFlDH4N09iZTqTzYDjByn/q2JQ69OD0nmB/cRVcTfIhYJ/OKZS1dvwDSDZaN0qB1nlLNQc2gRqUDpYrWvVyBtus5Pn3GortCmYRNMsrjrGFeN0yqKssDGfYP7/CgnnB6cozTFp00q/UFb733FkdHB6y7NXf2Dz5z3Pl85V5VM5vt8LM//4sMmQ3c9wNrn3hy2vHoYsVsd4eri0tOnz9jb2eGczJVTxRtpxiz82w+YsF/yX5mIYxDzEYlnDHYHCTa5oB1UPzm9x/hDl/C1FvSHwqOLzv+8e//kHdu7zGf1DijUUmUCsWyW3KPGCOzpqY2sgPrcfHIBH/SilordArj4tBGiz600hgl7WulNc6JgagxYhnlF2u0MRgl/jRXp8e0Z8e4Wy8T25b2zd9HpZDn2CRzU8qMwVEZC86IEal2JGNJ2qCMkwdRi504Vv5bFpahDYkP3vuAhx8/pet9ZmwHhiFSNzNW56e88e4Tfu2f/SH/vZ/9eaazAf38DJBgZozBupxxTmrUjTndMBDnDXYIRA3TnQmnZ1e89ZsPefVLDzD1Hrpa04fAEDxxucjjO5adnRm2npC0oesGnj07FZC367BVjXYVB/t7zHZ28gYmuM3QtaxXS3T2TizqnUN2JSq0AnlwpRxDizgeSswJQujHThovYH9jRyv/DyVKC+u2hanG4sZh6bquMx0hcHm54t2PHvPq/VsYLVwipRLaiNBcDJ44dGgSKgm4UKYhtC7NGw9ZOkhp0fkKvsNmXfJkNFddT1QaXTWk4nu1DUcmGNo1Okq5623N/OAuEYUzavQmVOImSrEQE2oI48ZcfCBVhsxj7jrHnFmBoqoKWddwen7B6focX4lKg289MViCUdzcPZLrqTSnl5c8Wiy4GhYEIpNJza0bRzxfn9P7FqMi82bCfDr/7HHnc8SoLPZv+PO/8stMpk2eiop0Hp7+R/9vPnz/Q/4H//a/w9AN/O/+w/89BweH/E/+5v8IH3qGrme9bunajrb1rNuetmtFgXEYBOQdhlHStu86gg+EEGlDEJeWQTpDy9AwH8dJioWT4vDwiMvTwHceirri7ZtHoq9kNHHIjruZNAhDbg+H7Mq7YZ1rLZIXVivqbLJojaapLU6LsaNRArYbJbK+VmuM0ZzHBqcbQBMUHF9ecXF5wa4S2+zT46c47TFay4NohCVtnCNqMXJQWgK6zgEpeMmMlBH9qETCYwkBfFIsg+EiGf747YdcXa1IiNlC23dcXFyNCpvr3vN3fuO3+ZV/+Zd45WCf6aym1gr//IKEpaodg1O4B7cI+xO6y3Pe+6M3SW+02IMZq/ML0UbSNX/0vQ9Y+8jO7j7GalYLyW60Alc3WFsx3d3nyclzLpdLvA+gNc1kjnM1+wc3me/sZs35Hq0jyXu69UKGmkOkeNeJ5PFAjJ4QxQJKlZ6UVuJJl4eQSTEPmZcgdB2DYetnSeUsWetR76oMNJfB6LpusFa6h+9/+IjhZ38KrUKeXiBLC8lajL7HChQOKcv1xiSzeGWFiSaNGE1oIXhOreE8CT3lqhemvKvqEbzeZIQCYfRdKy48UWF3buAm+wx5+JqosvO0/FlNp7iJlFwxlDJOjxSLlINTgR1KyaeAGKRj3qXAVdfz1Z/6Fl/WXp7LzqOjQsfEjf0ZToOzFcb3hMU509UVOsG93QNu37rJmw/fJRrDMHhuH9wUocMfR5DyPqLrKf/k27/P0cEelTNUlaWuG+7dvskbb77Ld7/3Dt/66a/xMz/7Ld76/vcZ2o69/TlxOmU29wQPPsh7xbyShCeSTUNjBDQpqgxIy2dHFP/1P/8D3vnwEX/lL/8lPj695J3Hp7kaEkDy5/+lX+TWwQ5D39MPA94P9H1H3/d0fSfT9SEIibAXYurJ02eiDT6pN8OXgCeJKoPP7iMxkpZ9We25u5bn5nIpphVU9RRz9ECKsJh4vFjz6GzJSyrRR/jeh8e41GJ0wimojKEyVrqCW7bmEqigdhZnTf53x7qVwP38asGzk0sObt6CyS4nbWCxWNB1A6vliqvFknbohc2dg3Ak8eT4jP/vr/06/4v//r+JfWkXrOasP2Pv5ftcnV8xv3HIue/4+Dvf5WBvytmjRywfPsWjeXq1olEV9+7eoOpaHh0/RynRAVdKM2kcs+mELiTW7Qqc48bNO+zu3+TiakHvA65yzKZTmnpCCCErRAZiGLi6OGfoelxVobQEKbmHfebVJIKPm8ZDbr5o4/LP8kb0p3S3NyMgGUge5YylbJasWwiHgmdmGVw/8OjxE5brtTR9Mg+wMOlTiiTfUWVW+Tg0nbaIu0a63VEpolY0TspxwsCi7bkaNMdrwX9s9eluKuIR2EEKJFszvfEyUTsUMiMpNBwrm4JYp2bYwo7fVytpMuhc/mm9KSsLUD/0HctFizKG8/MLju7e45f/wq/iXI0mN7pQo3wRKeUSU9ZZIG8Y6wXf/Z3f4Ce+8g1uPniNy5OH3D68w9PTZ5857nyuIBU82GaH3/69P2bmLFYDDIL/mIZJ0/D3/v5/xT//9m/Rdx37O/v87b/1n1JPqgxeG4yVoOaqClc7sbmuKpxzQqyrK5x1wi7GMoREUIqPn5/ww7ff4guvvMTB/i5PrxYUWoEyUu7t7uzw4MF9Iclt0Ry2u2VS3kiL+Wq54v/6H/3HzHd2+Df+2r9BiJF+GBj6Ae89Xdcx9ALo9l1L168J2f9t6HravqMfBsLgpdyJkKyQ6LRSEBJtpzhbRwyKPjj+4NmalLMCQ8IoMAlq5zBW0zQ1Ozt7EHt811JbzayuEIu3xNAFqsmMi9Zz5iu+/NN/Fl3XfPC7v8eq7WQjQVjTDD0oIT4W3acuRn79t36Pv/Bnfpp7tWHn/i2Oz05wN29wevKE8/Nj+hT59b/zn/P1n/wqzz8+ZqItvvOoQTHf2SfOd5ikyKyqeH5+Rj/0pJCoJ46pq0gmsOhahotzJjv7zHb2aKY79F6MOKvakULEhx6lI8EPrJZX+MFT1Q1KCYjd9sPoqlxs0gVDEfaUMNmlsSFQgR87nS929TYP4VagyjSOUg7FlLIe+GYwV/h2mp3ZDsGLq1CJgYUek0lXKN/h8PJwssG/FJvOmhhyyIPdOM0QxQfx8nLFykxp+4SyFbZ0vzbNPUBGafp2TUwKu/8San6HEAJNXb/QuRT4ZCgKCHk8phiBam1z2Zd/p2C0SWGsFu5bnmc8Oz2hPX/Of/kbf18mB4ylqhxTV3Mw25W5SutIVU2fpaeNNShj8eslHzx8xBdf/yqvvfo6f+87/4y9quLs6uIzx53PFaQOj45wdc3OpGG3qaTVqoTUhrI8vew5Ox34+jf+DPPajrVuSS11phbFJIvMGI21Fa6qxp1t3XUcH5/y/OSMp09PObtY8uDlBzx8/oxnj59hDvd5+7330PV0XHDaCL2h75YkvxLmed4VNrvDVsMs78ROC/DXda3If1gn2lKRjTeZZmOCySZrUyqNNz1lS6wQI8enZ/zzP/huXuSevfked+/dBw1VbXjltS+yXizp+55h8PjQE3xgGRMRy/70NsvOixpkCFQO9nXN0c4he3s73Do8ZGfvgDfeeIMf/OEf8+6j5zx4cJ/nxyejRlLJIsnd0bT14EUUj08v+Lv/8J/wV770KkfH57zxxru88c4T7t+5jTEOP3juHdxluAzMmwN253MuLy+p0hoSLC6vWF9c4dctlbV0WS/boHDa0q/WrNdrrHW4dslagTKOmFvdYRAhusF3DH3LanFJGMTSPMYkJElt8KHLPm6b8SnBguSBNdahyuCr9zJy82InLx8/ssuF8LVCCKik8EPAG9HTAvJ9GphMa7FkD6EQHgCNUnkIPQRS6NBZSjq98Jm6NDwy/mZSoOtWOKNJSVyF58bT6AjOYevJCGeoHPBQiElq32H37jG9/SUGHM4IVcAPcs+VMdn9RjrBMYkKw7Y6bUwbZydVqpl8bY1uiCFglOVyuWB5dcnJ4pT3P/ghi/WKrl2BSuzXDV+6dZtp5agnU05T4oPzC3Z39tidzqmbitAHFicndG3P8cUpj5895MJWPLt8+pnjzueTaplNSErjKsvNWzdpGiNyuUaUB59drXn6+Bmr1nPv9i3x+lJKJuy1eL7FCAFN1w+sVmvOjs85Pj7l6bNj1l3PYrlk3a6FjtDLTvDu22/ic+v9vatLnh8/5c/8wp/D6GoTOIDQdzgViLldX6gMLxIni7vyxCbmk4blckH0HVZD33k6H2R3MEaURjMoC2oknqITBj1K5NbJ5LGXXazJaa/W7O7MuH37Nipq5rMZf/kv/2UJ3DGNltx+GFi3nt/7oz/h4nLJ/t4Ov/jz3+Dg8ABXV5J5umxzjmSH35zv853vfp/vff/7qBRxVYVOcHp2TNt3Y8mT4QZAJH8ZhOT48Olz2tdf5+qiZ//wPs+Waz5+vubk7Anee+7s3uCrr77O1Iil0nLo+ODslHD8jOXzZwJ4a0taXHC5XKG0YtUPxOWaZr6PXqxpuw5jW1ElSBBydls3DSlF2iy2l3wvg8X5HkkZnf+eRG0zP+2CRCW9xWMSnDKGMH7TF7lBn0aQ3fxdPqPve6y2VFUtph7KMJ3JRtiu19S1oaodbdsjhhwbTTEhlQ7o6JE+dAam82Fy59ZqNW5s2omCQ+Mqui4SE9yYVhwvPcFalK0oSFY5UkqEmMDusnN7l2hqNGK35fNMo8qYZjG+3SRhWwPFueyT56MgX/L+2pr8Gk1IirOLS1JI3N27RQiB9aQlBs/at8RhSWMtjdMYIxSRWeWwMZKGnst2xdXiim55xd50RhwCJlVcLpeitPoZj88VpGazGdo62rYlAM10hsmZhtGKn3j9C3zvB+/yu3/4XW7fucV0NqHrexaXK66uVjx/fsrT4xOWbc/52bmA46EA2J4Qh5GfknwAH/JAqtTiPu9gq07zxhtv8+pXvpavv5KLOnTUOo06zZv7e31HjdkLLWjDbNZwdnFK6lsqp+iiJw49SXusqTBFZTW3YtmqHBUalSQgFT8/lwacFqllbQyDbwmxp2hbEwf5U5MFAh2psVytz7lad1ij+IU/+2c4OjgQjkz+rJgiBDWCtM2k5uVXXuaNN97i+f5jJvWUjx8/RCm5TyEE/HIpZpHWMnifQWKFjooH9x+gqoa1h5s3b3PvCzPOL66I2rDuByFVKsWkqRkiRGNp7RWXKMLOAav1iqve01YNO3fuYY2h7zsm+4f03uOmM549umDtxedOaSFmGmPoL9e0bctqvaJxjjpz2VarYhipxoZKOVQprQCMyjrmTgJgKL56nw5GfRqzf7MgpGw0xkqXb71mNpvRDz22t8xmMxSK5eUVk7qm73tWQ0DpisoaKnp08jIAHT0qJoYQqSo9Ou5oEioG1Cg2KGVbZTUKz8WixdqKvanFWIFERGdKvVDuJbpuwDV7QjiN0j0LwY+D9aO6wbbskNrarLZLPIQvVYibWhusc/gkZh9XyyVnz08ZFkva7M9oraGqGxqjCU44Y01l6bynW6yplIXksY1lZ76DVpqVUuzu72MwHMxvsFw2HO3e57f5pz/6vmwdnytIVbM9rHOYZsZ5l1idLkhJhPNJCd8Hbty5y/f/+I/42//pP2Ayb1gsV3RtJ+YNwWO1SK/cmE+48+Amt28coHQU3CfjEN4H+k785Hvv8T7SdQNt8PgUuVz5LHkitXYh5Q2Dx+iIjnHkg2znErJxpNFFVmvFZJL10oeOSlfY2EHfoQ1UjclqlGXnlWyulJBaZTleWYaklKg0Incbi9zIAMkLxUUpdBpGoL0swKgUH3/8EWHwvHz/Bkf7U1Tqcz94BD0omVwh2926dZN333iL2PWs15IJ6MbifRrt1q21qMkEMwys1isIkoE4a1kNAzWWDx9+TDVt8D6xWi5YrFu8XTCs11Ta8exqyTtPnnG8OOd51zJoC7YiGcXs4EjMArRmVyUuz05p2zXJGKI1XKxWiNSHRbfi5Dz0sjGJUoJnNfTUsclyx71YYQ2DgOBsphdKgIZsLKpU7uRtqapyvaQrx4vl3iabYvzTGEsksW5bppNGJGL8QFNVOFfRtT2XF0uenCw5W1wyDIF7BzU3dgymHcShOZdnMQ+iO5M7tko6gSnKcLoiYUgQA90gWJ0m0YeEmhQDBq7F3XbZ8uSjR3Ttmpgi06mUpCGETCjOQS3rl8vM4EZnpKymmFLWkJdzpBjvVkJx8b1nuWp58ugR3dUVldasvWd5eZmz2YhxsL8/QQdPHGRcyXSJ2hiMrWh6zdHNQx68/AVWy0ve/N6fsO7foWs7mqqmNj8mxrmrLPP5fLwW5NRSOhmJYYh8/RuHrFrPx++/zfnlc2oV+epr93lw5yZH+7scHuyyu7eDs4aJM7Kb5NWXChs9L5pikU6EGKLMNpH45997j//i2z/M6zV3eLQogBqFmHKWlacEQYh5RxvtkpQQ1+aTSuaS/CBAdvIQBlRyWEJmdm/d5fyHMNRzCVgmqpXGlXGcpIhkPengGVnHBPRopVVOU3F2ckbyAy/dPhJz0SRi/KVkLfia4Ery37vzCQd7OyglXbDaVQQSPgyUWqQEVO+DMLEFgOHhyQlaSSlzeXkpapjJECvD1eUVdd2gQsIHz0Xb4TEMXkwc3GSKiQmjHUO7RBknkrjBE4ZeLM2NZW9/j9VChouHocO5SkZRgMoahmGgHXrpprVrQObSClDOiP3k6567UioDs34IpJxtf9rxIj/qOrN/c4yYnVZMplO01izXKyLiA1gZg3KWFBK/++3f4b233kTbKdV8j3cODnlw9xZztSKsLfuhYaY6dAgQE87I+lK5u6eVuEoLBypk7EoE8oZkGGLCVnXmMTHCFd265cP3PuD89JwYE9PpFKOKqKHO5Z0avW2VEhHCBJJlAWRnH7QWE9Vc7hKQDM5Z2n7garnmydOnnDx7jB48e4cHBMQEeL1cElPExERlZ/i+heS4WnrSoFivV0xmmtB1LC4usJMaP/TUTcPR7RssF5dcnJ+wvPoxdff++e98mzAMNDrwr/3FXyZ4cctNMWbrbkArfu5nvoKpLB+++V1u1gP/wd/8G2gSy+WCrh8IimzamCTLKPwR4ujuq1CYUi1n0pzSicpo7t46IF/7caJdKSNEQV123aIZlWf2SjmQP0o0iRJ7swZSZOg7jIpiFx8GwtBBtOPizafB5uzKBLuchCh9KoyWLlQIoqsUVOLsfMnN9cBitSL6Dme3VA1yAOnWS1Ls2Z83aEQSV3xbNjQNwTPIRFGYWMXOvCEimNTQtnmwNooJRN+Tks5qm2CsZqZrDm8eUu/t8nS9JgyeUNVUdUPdNEx2dzj73g/YPzikrhveefddYuWIXmbP9nd3CSlirGW1WuETuGYyCr7FJFIjy3WL95757g7T6YTzsxP80ItrSoxEVDaxNFijR6dk4BNZ0PbPVFKjN6AE3s18Xtk4t3/n00D07WMsj1IaGeiz2Yymqbm6uuRq8f+j7U+fLUuv9D7s9057PMMdM2sAUBgaBNAkRbMpWWGb4ZBC+l8VYTvCFqkP8hjyB8mkZDXFNsme0EChUDnevMOZ9vgO/rDefW5WAc0gIrpORzUqs/LePHefvde71rOe4YhOIruLIXH/eOBP/sk/4vbqgrd3D5z6Pb99o2i3l1x+/59iT68xuz+H8IRNsiVGJZw1aJN1qyohvuopR1IlnNYEYIqBlSthKSIopmHgN3/zKx4/3BOC5CQWToDyJZlY50NTZ2xvoVVYa4UOk8SJ1aZn8vNyRawSQnA3TuyOPe/e33Hz8hN+8R/9I3mOMtE6Tp45m9UpnSitRocRpTXXE2hbYpxoH1FKUpmNZhx6fvKTn9KsWn711/+O0VX87Ke/4L/hv/731pvl9QcVqbKs8FoxPd3xT//JzzHmeYxaDv2YPK/vO6aQePXbrxiGtyQ/k87FQ9i6hJhn9udMNpX00jSc+/B8PrDQCRSKi1YsjM8RSEpa9WkSOoRRibP/i0La6mW0SovNiWzoNqsarRLjOGA0GJ3khAseFYOQNc9S0eVjzeAtQU68tIwcUlgikclngztj+O//xZ/yz/8f/5L37+74L//Tn/LTH35yfkBAoaMnBGFKlw6M7FlkKbAAYkkadwGSPSRFacSmFpUYx55pmgkpcTwemeaJwjlxQRwH2raipaapHN//5CVVUTKMAz7mfMDuxP3jI+PrV+x3e3anjqqqGP3MMM4Ya5j8zHB/xzzPVE1N4QRkftzvIZH5TWIiF2NgGsXjq7SWqqwYxiw+z+MfuTCM4/hRgszvH9fI94gxQpoVENkT+V2HiOdr+/tfH4uNl89gsZDpug5nreT7rTdMw8DucEBbRV0Zfv3la/7ZP/u/8V/+7//X/OJnPyEoxfvHPcPhjkO8pte33E33/MBZNmqHVTOJZza3hGeC2D5neoUfaUuFDzOTj2j77G0+9B1f/eo3PNzdk5I4M1RVJfe+MWJdo4SgKRtcufV98PR9f5bI5N/G5TEykc6sfqymHyd2xxOvXr8R/to08+7Nawpnsc5iy4JEoljVmJyIVDjDqmoxRY1aRM1q4a5J/qRViqk/MvRHXr36iv3TE3/v7/2cL774wb+n0nzz9YdFWsWEylE249BR1+X5hM8/OYrIp9ctv/hh5N987wsefnnPMI00dX0+5Rbt1HNrovLy7CMC3EdFQW6j5aZLVKWEP4YQWUZ3bSxzeAZaIeXPednByMtkRGDBYVdNBSrR9z1ai8c3mYimkCxAo57f6/LelcpeVmTgMXdSIm6GOesTk0mMc+Tt2/fsnnb4KZCSFwO+5SFJkYAo2mP0qORyfc1zdRTbYoXc2D5KUIEmYo1mnD3D0DP7SDeMhOBxzpy5M84aTv3A2A8kbzgeO3o7YLVmWjR2EY4ZuI4J+mFkmsWYrBs6jBW8ZvYeoxRVhHHMCc1R5CpKe5TRnPoT4zQRg8doAXaHoRd8L8s1lm3UOP6ujey3qQPf6AyydYhs1DLq8rds737f6/d1VIt0ZPlvIUb87KlciUEz9j19N1IWggEVRUE/Bq4ut3zv0xtGP/NXf/NrXr/5Nb9+88BfffWez15e8Q9fvuSP25EVe6yZKZCYMz8GqDJORaIwUFrpqMvmkk++91PKes3hNPDbX3/N/ft7UoSyqs5umybLshZcdqGaSDeax+XcdS/XQ3/M2wJ0ltEMk+fY9bx584YYZ25vbnm4e8tFWzHFQFFVKGvoxxGjNfM4MQ8nqlLgn4AF45j9jI+iH7TOoq2hrSteXG8xpmDsT/zs53/Mz37xD/if/5d/8bd+Rt9+/WGmd4iP9jh7hm6gqZ/5TWlh4CbQBG42jqYquIuGsZ9om+Z8sb6NFXy7JV8U/0vjoj76syBukqUzfBz6KWkbs9jHfoywfuNr86OfN3E2b69Qmj5HPhktHVaMnkREK4PSi1leWuzQzx3B8rdIPUzn8XPO+rJZSZu9gL/zPJ9lOIIXLD+jfOU0jRDL/B8W1C1DUylhrCZMntPxyJzJmssmrB9GYXW7grKqhDgYIv3pxDD0xBAp3IqUyJQGg/GJYdrjQ6QbpmzjlZiDp6wrjsejdHSZT4ZWFGXJervh4fEJHyUxJjHStDXH05H9/lHoATExdSeqpsKohI6ZU2cVwygpx7/7GT2/vtnxaIy2uBw7/o2AhwV7/D28qL/tey+vpXvTusxJv9J1mPzgW2OI2SpmnmfK0vHDH/2Qm9tbrq+vaOqSFZYvtobq9W+5qo+YZs8vvzrw37xf8+9eXvMnn37Kz92I1ntiGEBLVp4PWebiI2VZMaaSP/nf/Of89B//73h7nPiwvyMVK0x5QseZtm3OfvHG2LPbh9YqQy7+/M/vK/Tnf9dCGbKuYPSB/Wng69ev2O+fuLy8YL/fcToeUNOA1oq1NhRGMi1jEvmOMgU+GfbdhDKRsrEUVUVb1Ky2W+qmIaVIaUD5EVs4NPDDL37EPE389vXXv/fz+H2vP6hIyabfMKfEfr/n5maTsZ6lM5G2NsWszVeiw+u6kavr54L0zMsQCczz938uTgselT4qOCkXmMIpqtIJYJrHIa018xRIIaHcclakM1/l2yfsIqxsyhKVN2Q0oAABAABJREFUoOt6jJHxSi34T94M6sXzeOGYfGP0WzoehYrxDLRnYq/wWvIrRbFflfgsJRbA+ScTwXKWM6TAx0VarsOyYEhYKyfYMD57io/jJDY42V9cui7xAF/8w6uqROVQgO1mw+PTnvvHR/ETn2fGaaCualJKwrzPmsHFWSABhXUkFE+HI2hDnCdcYYiD58P7d8K89zNETV3VWTITJHR0SkwZR/Lhd8Hu3x3DliKi8vrbnWPdIY/ty43J7x8Tl9/7HT+p83+TC6wSVNkXPHgveN7iha4NSqucQGP41W9eobXi7/30+5TVp9QGpuOeioEfbhSf/6zlf7Uf+ddvHvmbr/b8s7db/vUnt/zjH3zG5+WJC3NAq0Q/DShleDjNDIfEYZr50Y8ih/2O11+9oZ/h6uUnrLeXDIc9ceoIp2PGVRd6is4Y5HNx+n0F+bkBkM7RFY7JRw7Hga9fveF4OrJated94PryMisnNJMyqKQpmhXWaIwXsL6qG4yTrhYlfnNN2wKJaZ5whaUoLN1wJPYdV1fXrNdbXr15w+3Vy995j3/b6w905hSHzWQM97sDP85YzPkUW9ILUWI+FiNDmNgfTyyK8AVbkbtDf+vGWW6m80JLCkJaLOnk/xsD66bkcF47J4yxjHM8F4eUNIlwxlGfeTaLfbEA601dYbViGCbUsuVRz+/xdzdC8t8U33yYxGo1YbSidIbFWTSBFE75UiHypY9HWdmOOmdBebx/9mZ/hjaXkrq8f+FNKWSjGVKkrCqmrhenUi2C65h9pI0tKMi2IVpcF079IHymsmCeZHy8uLjIp7QRcmhm119cXBCIuHFkHCe0NgzDyDD0jMOIn0eM0eyOB0JepWsSMcxUhWXqe7wWvab34W99kL5dREwOSgDhMS2kXa1UNr37/WA48I2UlG8npoBQM5xzgv3EJDQDa8XRIHdqXdfJ4ZHfi7HClD8eOva7PX/+F39Dv3vixz94iZ96dAw5WkvxxVXJp9uS+2Pkz98+8tev9vxf3mx48ck1//j7n/NJ7Zn9Ay50HMbEses5Bsdf/vmf8dX7Pd0YcHVL2a6oVpesL68IfoOyD8xDn51kFw1pOG8ofx+z/vmaSAdWlAWTF4vfV2/ecDztWW9WFIVYEC0OossBvxBEF7fPopAcxYgi+pC1oTDPgWnyz+O5geKiYf+0Q2n43hc/5PHpQNd5LtYv/tbP7tuvP6xIObEqLa3l4eFJNhD4M8i9PFQLmWwOMzORh93um/lfZ3T8+bWcat+8eeVhXbqTDIdjlGLbthyG58KltGIKkTOvj/Q73/9cQOU3SETKwmKtpTt1uRVW5/eyfJ1g9uobp9H5b17wqpRQ8dko7ePXEiW/6KmE+Jnfj5Je0hqdO62FYPDxT/DtYpkkJ448Ampz7haMMTJ+5X9X+CxbShSFIYbI48MT0zhjS0dZlij8OQLdWosxhoeHB5RSjMMoKbjjgJ89YZqYx56yLElhoi4N03CkLmus0agQxJ5HIWnJSbR5IX107eEbReNjGGDBhj7euhlj5H1+1F0tZMXf9/r497/Ni1p+LSkyotxv64Z120rAadZvgozEwzBQliUuLwTm2aOUpm1arNaEGPnyN78lPTyw9vJ9KyOrlkpbfnhl+KObFe8Pif/pqyf+7OtH/vnbC25ffMIPbz7js3JElTM/vnG8m0o+hJbuQZwrimlkHo7EsaPZXKPLhu3tC6Z+5OnDB1QYSGESeyOlzp/hWST/0di3jIi2KBhmz6EfePXuHfvjjnZVswS1SuOQLV60em4UlHjBGSPp4focyy6kZSmS5huTSwwBlWTru728AFPy4cMbfAL9XfGkitISTglrLPcPT7+LIXA2l5ANwyRmYE9Pu4/a+OXuef46vdxA2aJESI/krmvpjBL5mpGAtm2gn3PFF8wkxCAnLDqDkt98KM615XwPqzPA3A+jmKfxPOZlLJ+lk9EfFQP1XB6R4M6PQzL1udNiwZLM8rV5bP74ImRrmBBDfgjy1cyjZfzo74sxMU6eYQz0vWi1xmmi73tSSjjrztdaRrQEBJpaEoDv7t9DQgIcT0JZIIm1i9Y6j2cwjkNe8XvGaZACRMQ5zTwLKfdi0+QH3jCNMxfbNdPYEbzPchXZbKm8bv/4fvlmwSc337K5W8IvRPxrKctSNo15Cyjjov+dIvVtfOrceWn9jb9z+bWCnFs3n28J+eQzNSAfOinFcwHw3vP+/R1/FiZWm4bbl9dcrFvevfEcdp5NbWlsPkiIxABKaz6/0LxYX/APHnr+5693/OnXB758veHli5f8+PLH3KwhdJE4NcQYsLagrlvBB/sjxzBTNtJVfXja89s3b7lY1bRGNmgfd93feOUD3lqDKxyjDxy7iTdv33H/4QNlaTOmqfLmNBv0aY1Sz/exynSGZaOvPypQyojVjYpR8Kp8/xVWM48Z19pseX/3wDwFMPqsLPkPef1h2r2qYujkZHn7/o5vZ88tDxcJfBL2rNWGx8f98x9QCRXJnFu5qCqnDn+M86AyTyp/zwU4FnzIsFnXqPcjC3htrCYk4V6pvKH79kDxjY8xJVTW3pWlox+n543agmh/tLUkj2Ux427nkzn/+aX70kpTOJfHBOFT5XYLlMrZatLF5bch4561KLQwd7XONjY6b/WEVzYOI/0w0nUTH+73vH3/yOPjnmGS6HPihDZy4pdlKfKlEMTnx1gOhwPTNLNqV3lcG3LK8MQcPNpIAaqrkhQnnDW0TYMtHG3bsmoq/DyeTedCmOXv8GIPY2zPuq2YtMJ7uQ+s0qRo0SkQ4LmjUgpSxGRdZwwxH8xCUhF7aY2fp3NRWWgKwhfLbgf581y4U3xUCGOM5681ZglBSN84OBY/qUDCGfn7lg714w54eS0SnFdv3vNf/Z/+Gf/3/+f/m//0H/2MH7+oadBoDdtCI0GgEmclzquG0iR+cF1wsW1Yf6j507eKt08Hpjmh7DVjiMwpUjrHZrPFOZctjCLRJ/r9nsPTjj/7N3/J+11Hvd3y8uaK282aldViJ5y77kgiKoVO8gxKBxU4HCfevHvL+7v3aK0IQQ4TpRTWaspSuFbzOAl7XmmWCWTx2ILnQq+NyQRS4WppY2VsRrG6rNkfeqwxdMPM/cNOPtuoGcePN/H//tcfVKTWdcU9I86VPDwdCPHjjiDfLikXqRAlOcRonnZ7pDORP/NNwSjL1JO7IvXNrodvYhUpYzHbVY3iQb6nEhzGJyUaNeVI6ePT5fn7fGNsSorCWJqy4vC4I8Xnbm8BVBd86BtF6VvvS51/PxJVonJWXECVhG8COC1FK8V4TkFZMCtQVHmD5IP4gwseJoXb+1kA5xhRSmfVvlxD58S9IWlNOEVxkkzqbHQXQqBpLDEFfJhoVw3OOY7dEZVgHHus0xijeLr/IBY1dZUxh8jsE6509P3pXAzKsszuBCpHEwmHfux6LjcNZdnw+LTHOo0zDpUE7/MhMacEWhYKSkHpDM5Z5jmglTiTKm0xrmChZ3wMfp9HmFzcF/D840Ly8WsZ9cRxI4d+Kp39lqAoSpqmEbwFJaz92ZPyBqxwjnEYmMuZuq5ZKCjWWkotG8cvv3pDv6/54rbm6tM1U/QkpYXsSFYkBBFYj2ZN33yKTTXl4Z5y3HPZtgxerknhDOvNBleVxBAIMWG0aB+D98Sp5/u3VxAiD7tHvjzteb/ecHt1zc2qZeUMLi2OI7KQMdYxTIFjN/L23R273ZNMIvm6xSQE29kHvO8/8tgyWJe1qZmmcS7sy/OYr3FafhU90UuBr5xh34+YouHNmzsOvfDtSAk/f0fhoIe7O6DAOMub92/58Oa9bNmStOWuLDBWWr8Yg7C4tebhaQc8J6gsG4YF/1nGmkUSQ/71eRJQH+EMGe9arWoW5u5yE8aoGKcZpRrgW5YcH48G5/ol69uyKPgwTXj/3KpKHf0WzUB9tHHMNVmkLplxnr91WzgKLUEOcw6odFr44yFGYYynZdaXUa608lGEIGk2JHKeXhB8wzqitnRhQKtE05a8tFfsjycimjlFVmolm7iQxF3By8p/wRtk/Q8+TEQ81ljGbsBHcYlUKYpS3weUtYRJSKN9LyRM59zZtiaEwDBMOX1YOGkpgUqatmrp3ICymqqqienE5AM6BSyalMA4Q0qBQmtK6yiMlaKuLVGJyDYloChZOFIfp+MsB9v5ozgfYr8LyqcYiZNHKcO6blDWElNizDYsMTt5hhiwTuxfutOJIocyjMMgILrWFEXB7D2rtuFP/uHP+cFnNxx397x/+5bTkOiHCd2WhCRhuGJTZBm14u285lf+M+77DQ+HgdMw8MntFdumhhCF9FpV54KMUudnJiXZDIeQuL64YrO64GG/4+v373jcPfDl/sCH9QXXl5dcr1taK1kBSin6aeY0Try/+8DT7pG2raiqWiyZo5jsJaJQY3LXvyywvo3pLWP48lwtjqbaGBZijUrgrMZZ6YrHKZCSZt1U2QklEvzv8WD/W15/WILxfoeqbnCF5evHHf/n/8N/jWVZVQsbuF01/OSnP4PbHxN9oDaaV+/f8d/9v/47fvTDH2CNYw4x820cyWoi5iPipbC2lx/hjFd91EkFlWirCqVkZDvjRQqmcZbiJef+8wf+0esMw2u5oHUt72mevWwuPho9Y4xghBKxdHdnDFipcyenEKa70oaykA8OpfDIXyW+WoKnmIV3lb22EprCWRKSdGuUIuZNoYqalCwB6U7LynFl1lzfXDBOnq9evaUfotg565n5JCEG8nNLLLa8pDUsipL7D0+A4mH3iHOW9WbNPIj6fxiGvOaXbmUeZRWfFMzTJNSHYSDGxKkfCCEyzxPWOgYm+nFisxXzPp1xECFhCpie5ii2yMYwz5GicNRlIR2DdSQllj5iiSNpxdM0ib+RkUI/T9PzdvSjLmt5nbunzHVazOnmecYXnk3bYl3BHBOn0wmtDGEKeCXHpHMFm5X41JdlwcmcCCROXQcoAjCGxO7U8Ytf/BG3m7/P/+e//xfcvX3LmNYcpkTdOqIKRF3yOFe8PdX8m0fH17sPdMMrmsJytdkI5SMG6rLKVjA9aZ7OEfAfY0wxE2cjcm/cXl5ysd1wv9vx6v0dT/t7jqcdH9ZbXlxec7NeY5IUzvsP73h8fKQsSmLSjOP0vKDIGNyCKCvFNzqmZy6ZPv/e+eBPizFg9ubKI0hVG3zw1HVDU254/fYtIY74ACEs1jr/Ya8/jMyZhM1qXEFEszsc2VRmuTOYponT8cSb13f8g//iClJkU2jWq5L/8X/4H/izP/1ToSymhLbi7rder3nxyQtZCRuDK8psB1GyWq1YrVpMptxrrXHGoJOirhxGf1TOtNw8/TSfL+w3LubHP8ayW0uyOWybmjlvbqolZyw7O3zM23kufvI6n9hLwoaWD7kw4l2elPiYLxhBYgGoVf7e+XsoqEuLSjDl96+BRZ2ONRlbEC/1upDRYGHOT9NIu2k5dAPTNFNVJSHEHFowUWePa9BM40yMia47UbqCF7fXFIXhFD3jEGiaGq2li9nv9zmUUzH7+bztmiahIUyTOBb4eT5jE8eu5zPnaNpVdrpcrEA01moSXrAOo7BJirNzDosS08EgXdl5eEuy8k7IMikl6T6TyrKjb3VN3yhaeZHgrDi+Lg/lNE0Y62jrmrpumMeReRgZp1k6qhAEX3HSORVlyZTZ1LOfwDph5Y+Rfgr4seOzq4aKS3ankYuqZV+veDvVfN0X/GYX+bA7UQ6vWYcTn3/2U7af/YR5nInzSOnEAkU4baLPHPuRqqrO8MLH3cvH97E1mpdXl1xt1nzY7Xlzd8fu6Y5f7ffcX1xzdXlNSomnccYWjkRgngfm9Ludp1IqWzKrbxSjj7Go5c99/Gwt9/BZy0rgYtUQ/EhMms9f3FBXJYfjia4fmcaR4+n0H1Zz+EO3e8bQRzCmkKikICdeDAGNmMcbCgIKawoIkbY01GWDIwo+oxVKy7jTdxPH4x2vXr0lJeE4cb5gggcYa4gqEXzAOceqaWiqGre9yHHuH8XyaMP9057j6QKFjCeyLYJlMFBKCWNgSSBWYtcy5TCIi3VzvgE+fn3rWTh/sOfNERpUytlnOjda6vkD1KJUX4onZH9p+XQpnRRg0SMuDPVEygZvFhkdyoxrjdOMqQqMVlhn2V5c8tVrUZZ77yWTLsoNr5UhxJm6bvhwdy/F3hVcbtc0VYWxil4r1ptVJsV6TidZkKA4+8IXRXEW9Ho/n1nOMSXinMH0JD9bUVYijZmjcGe0yRs+h1LCqbEYSS825rwgcNZikjhAJKQ4GiOnslYKv+BRyH0UUvzGuKfy/SgHQmScJ+nyg2G9XuOcY55mYexPnqptKMsCoqj8TYYLp3miTCUxCgdt7gPWCpaVQqKpa+Z55Jd//Ss+/5Of4OcZV5bMccVfHTTRb/jQJbr9Hbdqz392nfj8+pJw8QuG23/I3THy9tUrsS1xin6QAlW4kpBSFojP59i45R5cwPwz3pr/xxrNp1dXfHJ1xcP+wK9evWF39zXH3Qc2Vy+4/d4PsSlxvL9j6g8kgnRledmgtRG6yBzOMIbKWsCFo6ayBlByKJ8LmWwEZUIxRtKZKp3YPe748Hhg97SjahuKsuZy2+DcBd13VaRmP5FslopgmBOUdSOpsl5IhSmLJ01K2JBYrVasncMonTVentnPAvxa0ZUtq3qfLTqGYcBPM6P3Z9JdUZRoazl0PY+7A9Ort6irH0OS5AtjpLP603/zV7z79b9Dx0Bh5RQuq4pV23JxeUHbNBgjnZozGmUdioSOiW4cCWlxNHjWhfERM17lmU8tDPBlo7n8WQVFjoZK2SExJX3+4EPW4cmnumBq0BQWrST9RectlGLZVMrfF3KCbTJKqAM5imr2gV/+8jcc9v25TTfaCUCcPOn8/mAKsvVcr8TMzTrDPI2s2paiLDgcDuz2T9R1g9Y2dwwfRcVH2RYN04hWIh9JuWMipfNK2hrN6BP7405scowhpjnjffLzaZ3OSn1JJxanC6Wg0AatHcOpx2oJRlAxELItMrkbXoqbSgmzpMbk8VoeYskjjCGe49TrupUuRSmJK3cOrWUJAcKPmn1gmmesL6jqBh8C2ugz1WP2gaZtUFrzuB84hopeb9jN8OrNO6ztuK1m/rNbxX/0WUPTrHlffsF78ykPTz33Hz6A74kKpiCt4+JNb1gsoP25+ArAnSSUlme6xTObXudYMscmRD65vGAaB6ZpYH/3hqnruby95erz77H/8JbptEcv5/AZh5Jly2JnpFQSGcw8E5cilSGI504qnicClTv7ptIEP3E8DRzHSPfukaDuQYE1hhQCu/3uuylSEtEjqbi2KDn0A5NfC/pjLDqra31IOe5G2uNeyQ1sjaGsW9EBpZjN4cTCBa2YJ4+zjqubDXUlpmaLSl6cHHsRsiqNtsViNSe/RqOUYX/sSE8PqBhwRp/DHc4biSSGcDHzdpLSDHPk9nLNv/if/ox/21Ycjx3OWfb3V1xdbrjabtmuV2ceifwjtshakRN0n5cCLp9+US0OD/lJyuS/83bwfIMkClcQY6LvhwwIJ7T5FriYxHVhCQtIuRWf/Yy1jpg0ISSME83Z8jN775FGTp8Bf6UUxkpEedf3XF1dcjqeeLh/wtmCpmkY+lH++EnSfpMPgv3FmJ0gBYeUz0k2WnKgSPBGPI5Mk8faQhYISnC3EAMxpGwrspzGmpQCz0TaJcFFkQjnaCsFWfsoJ7oiO0Xkw1GlRFk4xmlCa3vGNEVSIxQL5/zztkprjoeDhBbMssFzzgkNJFsQFWWF0UXuGEYpgjGRouI4BP6/f/WGyWvGlIjB0xaKH18p/vizS26bgqNreJWuebNvuTu8ZxwnDJGisGdI4dzlK52DUdOz+d/fsrlcXkqprMXUDNm1oRsGfvrjP2K1WnGaJvZdz7Hb8+60R4WZEBMW0ErIwCF6Fh2gdPm54/eS4nQO2M35iFrZjJvZfPBkagiRqpSg0NFHSfPW4qWGkoiyp8PTsiL7D3r9QUWqWm8ZaZiTRJsfTgOjD8SwmOVHFAbjCuaohR9iCxJyoadp5nCQiGabV89GK5QpqKoK45ykYUwTfS/toMnbg6au0e0KZeR0H8aZfsk4g/NIZYqKzz/5HoaIzxcuhMA4POf4oTQm4wAhJgoV0Qru3t/zYBZrlsj93X22FImZxyTgonOWprRsNis2W8mOW7L/nCt4nHLIptLPbHBpFgXbCBGtpcCanJzs8nZvymOTUfr8Qap80i1/h05ZlzdMeaQ1zD5hXcnjYcc8z1xuthhtsDblFBax3HDOiscRYAvL/f0D1got5OnpCe89t7c3Ep9dFPTDcD4ljdIy2it1tgYxCHl19p6kEs5ZnCtApTMIP2WfJqUM0Xt8kGJi84OVErlI+UyhWLL1FPM8UZS13Cd5+yhlX6xGIlGusZLrWVeFdN1a432ibhrqqpbxNCWKovgIZzFnNvtiazLNgj0tQLLIj6CuRdfWNC2nTtj3v/36FeM0cnUtmrS6LlldXFCoS3zo+NJv+PLUMMbE7BOz3ws/Swu/6PdUm/O1dsZmVUH6CCL4aMt9/hJF0zSUVUl36ogx4aqGH//sMy6urnl/954P7+6YwyTLHW2JaKrVCuaJeehETL/gh3mrvUwSMsRpFilYSgLgEzzRy8G3FNe8QWLT1PixZ5qjwD4kwRFT4nA4oJVltf6OwkH//Dev+c2rO46HE34ecTcbTqOXsy6vzGOY0QH5YILndDqhCtnuWOcoa1GaT/N8joOKMXI4ndAarNUY5TC2ymzgQDdNufsJ0t5nDZK+WD1/uEmL82AwYBzjODDPskV0tmS9beV0z9ls4ygsbckwk5PWOSvkwgXkPqdtSMiAStlhIUYOfuJw6nn99v5888hKfiJVa+rv/33pdEikpQNA8fXbe/75f/vf0VSWlzfXXF1usM7x8DSgDAzzzNOhpyk1hMQ4jXLiF+7ceTztj7y/f+Jx3/Pu7oGHhwPHwbM7duxOJxpXsFmtKKoSJsEWUlSQR8mqLKnqksPpxHH3xI9/+D3uPnzgcOq42KxQSh7G/e6AFF7HHKfckekzodJoJ5hgfrCIkbqsMMbytNtlxb4QNYuyYphmSWhOM1Wmq5AS0UfKqqbrB+qyYpxGSOLEGoPEgfllg+tFZZBiPBdcY7SsvPM2b9M0OFdx7HqJX3IFq3YtowzPaS7aWOYYQRvqZiVxVVpcXDEQopi8+anE2IKkNNaVaDUAUki1svgp4CdPsJ55nClXLcdoGIcyd4chhzEsnbfOEVPxeUN29s94BrOtMb/beZ87kDx+G83qYsM0e4aYOIVE0W4wZc2xlxCMui6xs8qYV7Z9btd0xwOPfYfJNs3GGrR5Hi8X6ZBavNnyJn0pOlK0AkoZVBIen7aGpjB82I1Zx7dMEUJlGceR6+vr80H5d16k/uW//B8x1oqfUOEgzNy9u5N2sygwTlO4grppzvE4q7YFP0pkd4g5OSaTw7ShKOVECTESoud46pmmI/0oJ581EkBauIKqrs/ixgSMC14jHxnWWKYp0E9QuIK2bomAnz39NMu2IcipVBSOq6tWzLmMxU8eZSTme56EqW2dQcMZNzFG5xFTQH4/e+ZJMDZhFmtM1aCrlrzuyO3z0oNp+nHg67d3WJX46rdvhe0cI5NyJL3h7uGJ/+r/+M9ZVZq2qohJCJplKfmExhru9wfq9ooPjyd+/eVrHg8DU1RSBIBhmhjnQFEU2Mzt9zERZ2GkO1eQEjw+7knzjDaWx8cdPkTW6w2Fs/TdkEHjkiFjUst1WDhDCyEyBPErL63l8lJCAsZBRmrvA3XdEnKQqpD/xAfLuYIQI86Z8/cvilIU9K5gGD0pR93HGM6RUFqpc0yac5bgPZt2TekczliccdjS0Y8DPgiheLE4Ubkj9XH5vpEYInPe+Mk4KsGkwXsmNMM0UqBJ2ggZEdn+zl6WLU0jeJFxDrSiGwaUccyzl1BXLc8MKXsM5GXK0inLOPVcf5b3JXKUj8aiBCoXB6UFCtHOYauGx/HE3QinWbG/f02YB/w0oIKndeIYEoNnVoqg4BEj3up+pjKgY8Rqlw80mTY+FiwLZvWxk8QzX0o80+X36rLAWsXueMzbV4FnUubblWV53nj/h77+oCL1k5e3XF1dUFUlRWG53GwpjYxtommAcZowxtKnxJTFhY2Fuiyxxp5b7JQpC/M8PXNy5sDsI7aouF5tznoplVtP7z27w3C2DbHbkmqZ5REWsEeTksZPXk64KJupqixZNe0ZpA8hMI7S2qscqa6DMJhdUdHkwoB6ZteGFJnGnmHomMaZFIQNXDRVjuoWwW5QBZ3SmfioM/4ly4aEwZYWoqefAiHOhJBIWqEbkSkcuoGhm7lXB3mws13vcrtKrNEjx97TDeKuOeflqcLQDz0+BBwy2gg+owmzxC1prXl83PH0tOf2+oLjsaNpWubJ0zQrTvs9p2NP1Vb4KMsMY+2zbs57eT9K4adZtFtK0da1FI3cqY7DjNHiyilOGDrTFcT0n4ztGKPFY/2j1bbSmmkcxcs8CE8qhoDRJsuKxNVzyUcMs6fdbEgx0TYNHs1qvWK/27HfPbHeXGQ9nmBPOufSCeco6/JCeNaspWeG++w91glsUFRCLg0h5I2zpa5rrDEcTke6vqesKtbrC8qyROhhzw933kVmkEI9FyY4G9d9/PqYchCyNXPXd6A0zXpLKlr+4us77p527B8fOT6847h/QqfEZtWwrktMEBmRVQqVEnMIPB0embFo5zBaUSnFNIiT6hlfkhX18k5zxyzFWO5rKaQi+BaLoE9evKDrBkafqOoyTy+JaZb7pq5rMTz03xFP6j/6xd+jrIQjklJEpcQwDXSjeJMvsc3FpmJKsgVqmwrt5WQ9zqdzmxfCjHVGfLXLhqKsWCclwtYgreY8zoTgCSllsFrTtJuMX4B3zw9uyhyPYQ4c+8DaGVxh0Fa4LnUhjoYLe/hsHuYcTmWqZhLLF60UPkSG/TGzt8W3vChsXspZmrrAGrH6UEbnGGstybw+oopEQmeSaaacKtHuoax4kSeR8xgtp/SUo7iqssIZh1YmA/0jKTt5WmspjKWbo1AXCiuHwRCFwhDET1s2pdLGT9NMWZZnu+UQ4cPTjoTi8uqCOXisMawuWlIMDONIVZU0VcP+dCD4DGiHICZ31p6DbPzscUi893otEUZDP3I6nYjRU9etcNCCeNmHWd6LsY5pGHGVpawq+n4kRQliMNowh8Aw9jRNJQuWANM4Zv6YjFnGGlkauEJ8zrzHasM8j7TrLagNfp55eHhimGc26zXRB9FPZrKt0oqidueuwOeNctIySs3zxOwnyhRJmCU6GZ/tkXdPT8zTQJnzEVebC6wtZEPtZ6yzmKQyyJxX9VoK1YLtSVEm8+zU+X5WSmEA7yfuHx95//jEFBLV6oLN1S1DsDy9ecfT4wP7+/fYeaB1louLFcSEcXK/LltnctExaJqq4jQFUIk5aurKsST9LdttyFNeZi+nJNrJmJ/hlD6yt1aKq+sLLi82/OVf/aWMztOMZ0ZpnTlhnsLKUiKo76iTKlZrUgpE72V0Q0nyrzYCNivOGIGKkXGeebg/UoqlAc45mqaWhFolqv+YoBsGnvZHhnmStbixFFbCOQvnSDqdR7yUIsdjL4S7KtHcPJPcrJXoaFcWTGMv4LsSOc5oLc46tNJUVSVAuCYDk4J9jON01rst4lTnCqx1FK7I26xFJa4ytpHwMRJD3hgmUDlQMwFJg0c0fcpoCBBDoCwsLuvoSIrJB4ZRJD9RaXwKFEZhtKEtC9kg5oN3DgntJ5zWXG9aOAzEONNP8VmgHJNwkYxw0pZtplKy3u77nrKw5w3q7c01wc9MY09VF9RVLSz8aYbcbUwxnPG6iHTNKWVahdKst2uMtjw93Z8B8Kos2R0OecQuxR+9qvBzIM6ezdUWrQ3BRwkXCB7nHNM80J9OVFcXgkvlw8BaA3MgEc6bJa31OZmnaZrsazTRVhVXF5ccTj3DOJF2O5q6yqPaKIdAHmG/QWhEQAQJO/B56TORlEWpCucs4zAQYuR4OuHnnqvtirqxuNgx7yd8V569ypOSQ8yYPPrlgmWMkXtWC1ZlTQbzbRacK83Twz1fff0V3RxZX7/g4voFyhY8dSc+fPUrDo/3hKmnMtAUReZ5hTypBFkSLfdsginMdH3PHDIOpksCht6LxY7RmUiMOXdPy/iZoibpRFU9u6MCxBjYbtf86Aff49WrVxxPI66oJEgkLc9XEOgnGz5+25zg76xIxc0nVIUTLZSfIXqa0qCVbJAO+x1zgNrVVFHy9V7efkIKI3GessH7RD+MLLLcuACAWtPUTfZAUlhtzqOFjz6LaxXaWMFarEW5OrfHC9AofBofI4WCqiypm0pEovOE0gZr3Xm1Ow4T0zzlyKHMUXEFRb2Mpc9M23meST4yzc9Z9+KvLlySFJN8rOrMr0Mbi3UK4yzaRpJ26Kqh2taSvxeTsLtRWGXRg5j02bKiLiqMEdqHUebcXfoQmCfx9tEamqpiTpbAyBwGhjBlUFY6KFOZzA6fWUikIUwZExTHBKGHSAG1paPWFV3f03UD+/2eFBODH85+Sz4Fxmlm9gmUFs5QVdE2NUMvzgomGVw27xfdoDu7M4AIpMuyoiorxlFoJjc3slUMYWboB1RCNopEyqJgmAxRaaw2Z+C5aWoOhwMgxN8QAm3bcv+44+LqCqcNN1fX3N0/Mo89p+gpC8HCMAmiOR9wQeZP5nnORGJLDEmis8pl/AsURYl1I6tVy+31hk1tWdeWyzaxKgcai1AVqg0+wjQc6U6RfgYfDNE4knEo7c6JKgrRvGolpOh2s6HZbLEXL7g0NZ+sNkw+st8/sXv/Gx4/3DGNPaUzkrZNFM8vrSjaRkTbMTJnPWoIgd1hf5Y2rbOI/BQSM4nTLDrKKgNkC8Vl4f+pzJsKMTDmre1S0Fdtw49/8APevH7Nm7d3oCwqyrgoW1Ro2xoQu6CIWBN9J0Xq699+hStLUalrk1fc0u1YW+IuPqXUhu3VJdMcKVxFdfsZcR6JfmIeR2yOFk/BQwoSqYRscpxzhHliyMCsycLFuqpxWRUfUiLMgTkEfBio0rM9h5ACoa5rLsoV1igZF0MCbeVh60TWscz+VVHLKOkcVVWjjT2zqiXJY8Zn0F9p4QuJONoIjpa3T0ppCSXQYhJTFg3V6hJXWmLSDOwpLmZqZylevoTpQH//mnkakcggKIyiMuJDhBIHzbIosUZz6nqm7AleOEddVcSEpB57hbGRFDvmWcboGKULMpkrtngxFYWj72fKwrBatYzDyOWmpe86VnXFZrWiG3vmaWK/l1GPJKb9KUtI5ywY9X4CnUg+UNUbSYpJE2VT5dQVxzT5rERQHA57EejOM1YpyrrMPC8POstegmyJu36gqiuIkdK6c75jWVSESg4KH+UdVVXN0PeM40xdNUxhomprHp8euFhtKYxs/kL2/VpM7RaBLOTxzz9HlfssjSFx9twCwWvKsqQsHRfbFT/6wackf0DNM5UJrAv4fO3YtjXV5z8mxsD+7a/58PTIb18feDrO9AHGpOijpq0rjLVMCdAWVIGtNyTn0JtLoispNorvf/Yp/+pf/kvevH6F9xNaBTbrlRTmOGGVpq5KCiuHj0JBiHSDfJZKKaqyYLtaURclIeNIBQEfZpKxDHPAOINlCXTIAmcFGaA6C55jSqgUqauKn/z4R7x9945Xb99hjOOZEf/cbYFMQYt1f4rfUSdVdXdUsSJpC7lVRhsGNFNA5ngt+6Try4J5mvnqbi+2F8ZQmBWmkLgbZwxWC0BJCjk0YEaFmW0Sn2+rNGH2TNPElD28Y5wxyM1VWIdWkuGmktASAqC1bHz6fkSyEwRXctm1sizLZ1A0yD8+A6pGmzxWLmxzhHBnhPsknY1Ca0vRNITTgI+BsllTr69IriJGUK7m4vYl3//kJe8f9zzOmtUE/fHAv/7rV6wry4vNDfN4klBUFVE6cnVdY82IIjINo+A2rsAYxWq1OluKJIRSYIuCqAce97200chDpbKJ3jTPrNtVlso822Po3D3EGEUakwLrpkWjOB07hnFkGAdiDOfOdQpe6AFaE+dIRFr9uhS/KaUkzWXMTOmqrpimE85aphDPflAKzptK4S8hhmzTSIjCgRv9TO0MRsN63YKCfuhoVg3TPFJXFSElHg8nmrphHCc+PDwRQ2K73chopTTH45GyKgl+ErIxz9o+8Z+S97R4Ny1bxsVYT2l1pqJoJeP4El3v50kOXC+p2dMcGEdIq5KybfneD/+IqR/o7l/RlgWNTRzjiEuKcZyJU8S5zZnFr/WG1KzYfPp97PaWh8PA/v5L+v097/7C8fj4RFtV2HbDMHumaeR0OFCXwvI/Tl0uBAuVQa51265o6pqyKM5bOMmGDOjSoX2k84ExatI4U+mE/ijk5Fn68q2RWCteXF/w4e49r968R9mSb+7bn7ulhRWf8pZW+e8Ik3px2QoTHMXsA6MXHCZhaDPYGNNMo4RyEPzMcP9GLJUyR6QoC5QrMLbIwuGF4apRRqEwAopqGflcazFrRbvoiKJk66ksNj1EKzwOZD0sItcRU4iUpa0bqroSbyslbqHjOIrZfgigFda5zNAWgFubHOQYpeAlJTKLEIQbM6PBVUx2S/Gi5eJiwy9+/nMoGv76t695fNxTrdao9YY3nadTJe31J3hVoW1FtZohzuxDoF5dyIM5jMzDifWqhtgxTyfacqRxnqoosdadN1JLgIWfAyWKi43h3d1BuGjGEFNA5VNs8V9aRKLLySYWw5GmbtDAum2AxOu3b+nGkfsP96ANq1UjQHYmwi5Y1Dh5kWJaRdXUKCRFGQXT9CxqXryGuq6nLCTQUoz2hAArgZyLNY1Irg7didl7miJvEP1M0zY0TUldO+zeEINnvV6TsBy7gc1myzT2aF0wjjNGR6wxnLoj2kJRGvb7Hp0tc5YRSGnBm4qyxFrLMI5SpKJ0/JEcnkHKsqZw5ot1w8CXX7+mtoqbixVJW8YEu8HTBkdz8xnrEPjtX/8vHI5v2R87Jj+REGlISEmoGSGi6pri+jO2X/wCrwxvX39Ff/8O5onCKrwfqQtNUyqe9k98+fo9q/WaFxdb6kJjlSZSy1Ihww4me5idxcFxEW5nhwlrcErjHKT+ROcjHkNZl6xKWcIsgRkLN24pfjGpbFioePX1W3wElUQ8/nEh+7hICW0hR8Kn72jcOx57sULRGm0N6+2WGARzKMoKjWjKVk3J+yngnOKiEYaqdVYKgYIQxLx/7OR0D1HIoD54yqrGugLjCsqqpk+QjKTlwWLARQ4f1FCATYAWTpXCUF3ecHG5lvVDSIQUiWqQMMyAzMyFpTJKsBgFVssmxFkn8hUv+qzFhkY5OR2NKwlJk1xDFx2TUoym5s/+6it8iqIFdJbDMNHHAz4mpsljjMVYd46+Vkm2j2VVEP3MNAUur24pC837dyee9onrpuaLUmNMDguNSUDxJA+YNgodgRSxVlE5TeU0MYnZmtUmk3DESypGcZ4kiabSWcOqrWnqEqM1r16/IWlF13dsNxvGIH7ewzQQkY1WCELaC2nZHsn7mrzHxWWrGGmbVnAlpYlhhhQoq4px6CmdRadEnGVr6grLPE5cXWw5nnoWer7SiqZZYbWiLIQDVRUlL1/c8v7uDmMMm82KUzdQFlIUlbMoLaDvIrMa+p66rHhKe1R6FnmfnS9jxM8i5mWUeDDORUwIA97PuCrjad7npYnidJroU8TPiXmquF0X7AtD23smr9jUG2LUvHnzgb6fZVucpEClbO8zK0f18kfc/tE/YpwTr//63xBPe9aFBSMLG5SiUGIV3JQFKs3sjweu1muckVBWwzMHUZZuuQAiC5N41vkpFocNSd2GTVUxnXqxr5k921VNWaicqxizS8h8ni60UhS24HjqCUBROMmn/Cj9aSlOKTthQEIg0IguviM/qbqSzUaMQqE/PO7OzohTP2QtmJDNpiie5I3RpBz9LCHGkjlWAHVtoCrQCpzRmVdh6cdROCucmPzMsZ+ZJsFtfExYV8gIaS3N1aeoss3SCoPShvv9iDKF8HeQ3zNmhV1vKIwRgDslQLZVVgt/JMbIFGVG93hMWWFbibw+DgOv3x/YHd6y2l5y/eka6wyb9QrtHDc311T1CqU0d49P3D/tOBz2hCRcohgCKUHpLCbMuKoG4+jmQJjAtWtOQ0cMM23TMEyeu+PIGBQ/uqm4LGZUnIFnBbqcbpJQ29Ql21XIoLLFp5QDIZ7V6iCaKqM1ZV1jNazrkrYuef3qDQ+PT2wuNlxcbOm7HlM4IorD6URIimHy+DnQjxOuKGQM1joHOEtX8DHdwc9CO5jGUX6mYZCHO0SqumHZo83zjLWGuio5nXpSElY2kB0KpJA0dUORN7h13bDbH/nB97/H0I0cphlblXghwRFmgQiauiKFgCuq3MHJoiYpcjbgR04WMVI4x67vKYtSwh5IWabj0UbkO4uF8IL9FmVBUop+Tuz6SFkq2tPE+9e/Zd6suXs44JPFli3KSlyZC2Anj3MFxcsfc/Ozf0w3BF7/9Z+j+j0XdZG3fTllOMkmOgGldfzR977HX/7mFW8/PNDUn7F2RhJ6UJJGtNANrHDYPh7XYoyEvNA4+44pQ+0KwhzoJs9jN7ItC0xSZyqNc/qZhhAFC97vTyz7QPHM+0gUz5LU8yxIdk4+z0n/bijs30mRktZPThWtxUrFZQb4QtryMWGLgvEwYVGkMItLYWYKG2OoC7EYERmMy6S3TEtIYHRN8HIhLJI6nGy2qIhS6NABnwIxjMSFz51TLE77e9p0FMW2dmhjSUqcMpVkPqGUAOBWi7GatbL507oUOxmn2Z8G3n71lqfHB/pxIKTE7Sefsbn9DGUsTov52M9/8mNe3NwQp553T0cpnk3D4djz/u6etqrxY8f64pLT7pF56Cl8S7m+EK5UUcm1Y6QfBxxBwk/bmv0w8xdvB372ScsnbUGYR2LuaLTWuKomOUvbziTlCGnHOIesqDdnq48l0tt7L7KYqkKlmW1bQQw8HY7MPlBXDRCx6zVzjDw87Rl9wEc5ILpJiJCLJs9am4m2ka7rWcIT5llAe+/ns5PFEhEVM+A6ZDA/EbnYtMyTSJ8kaURMCFOKrFcNx1Mv218FVdty6id2+7eMfcf3Pn/Jm7tHDn0nGrmcKh2VhLTqFMVVQWmCEulLilHIr5k2E0LAZ2sUFaOsz5WSjV8+wELwFIVo6oahZ7teY61sgTcbgUJigqcB/PsdH/7b/ytGgZ8GfH3JKfSElGjrilVVUUWwF5/R/vjvc+h6Xv/6l9RMlG19JpOSN8fPlBew2vD5i1tO/cBX94/sR8/V5SWVjqQ8OZxZ6zyPXx/7Q1Wlo2kbsYseJ6bJZyfZE0NU7LoJYwxNHhmVtjl0Vy6aD6JBDVEWW9osFjKL+wRSyLVMPzHnT4ogXbbC30mRqgrNqm0ywi+eN9L6C6s7ACTR6fl5pLSa1bqhLCvKUkTEMYhJmthIiEzltKSWkPUBmTy2/J9R5iwPSFadWdgEsUOZ4ayyBsW2rvjBjXgjkSSbrp9GphAZJk9AhMjryxtW7ZoQJWPt4WHH0+6J6uKWcnVBFx16fUWrDJWfMYXj8x/8AFtY5sMjX//2S/7kn/7npJR4+/49t5uS7arkr756TdKGorQ8vHvPh/FIXRqqpmLqJYNwnmbS6cjjfs92c4FSEm4aQyT5gaev/wqqNeX6JXNM/Ls3HePLhttGutnCWE5j4H5AAEk7om3Ex8A4z2e3hpRSxn2UYHExiphby6h4tV2xe9pzPHYUhROLmQiXl5fcPT5x6Hq6fsYnEYirBPWqzaOnCLRnL4dQHKSzo1D4WXCzYRxZbzZ5KWGZpukc9GmjZxgWfZc8vKdTL1l9Q6IsK/qu49MXNzw+7QnWsdluMM6yXTVMV1fcPz7xkytJbIkJ7h+fCOFZFzbNMyYF6uwfFs/ERi2hHQrGecrW1xarBUaQcVpMFb0KZxLygvElRPphC0tROnwexctCeFidVzB6DKB0QXCa2QRMoaFpmYyhWN2y+uIX7PuRd7/+KzYq0NQFMcS8fRNfrGkZs3KRmfNh/PLmiuM0ceyO3HdrXqxqKgulEUXFnJ0qZFmAQB9ZC5hmn/WwgrVqrSUAoq2Zjz0+RHanAbtqqbIRXo5MRimNTkI7QsU8qWS5EIukhzMtSNw8noskCpT6PQLrv4siVRSOGD3hIy9wee8CNtdlSVnWrNct43jg6uqCzz6tBBoKHj9PzLMX4LXvM7vX0dQV4yC4i3guq+xkqVDGYciWFol8UYRFrrRF7LviuaUkG8YV2e4CkCK53qJsIQQ77Ri95/Fpz1//zW94fNxxOnX4ecYUlj96+QXNas3hYYddbfjk+99j6E6YokClxPH91/z1//Iv+ez7P+Lq8gKjFJu2QoeBL//mV8RuILpG0kfGE7/9m3/Fzc1Lbr/3heBzhYMwknpP60S2YlzJqTvSNpaLsuQX/8nP+cu/+TW/efPXVJefY5stf3MfeegNpqxBa+ZZXFKLOAsQmruFBTBfMvRAwOwYI9vtlrquOO2f+P6LK3SK7E8ndqeOz7cvmEbZnI3TzNPuQDdMIh6fA6Wx1E3DnF0vVFISfGoFv0lBQibmyROTSI6WDMAQBN9LKdHUDdYaSsTpM6XEMErS8vXVFh8jU4749jFQuIKr7Zb3d/dstxsKJ1iaD5HdQTP0HU1dMfnE4Xji8XQikYuGkw45LdyfkDe2+XS3VrSTwzjK1qkoMpl0pihKRGGXcqipPAfPdrqG42nAGotiFFqOKXHGklTIEIesdXxMNOs1dVmRjEI3V7Sf/BHHyfP+q1+ix72M10FhrIMQiFkwnc6dXDgTidGKpir54uUtd09PTGPPndJ8erHi6qLleNgzdqO853zoy2LIns3s5llA8eVZLsuSsqqJGD4cDozeM8VEU4rH1bL1BrBK8iqXr/9Y3yMpTHkETInon/+ehVqkvqtOSjhCnNt95xxVXePyiprsReNKhw8jPk08PvZMU8D7OXdeHm0UtXNcbi5RxtJ3fa6wGmOcuDhK6ROiWw7flEIlzoEqeVIMlEoxEwn5GmmlmWPCVC1FUaOysX8/J56OHQ8Pb3m4f+SwPzGOsoFMKVDaRFsarj99yc31BTc3V0zTLNE7ysj2qN/z9S//DV//5b/mom346S9+zicvrrheF9z96t/yy3/7r5jHE9gW9cnfB7vGGcNFXfD5p58xDgPEgI6a6zKwLidiMtx1Pd3Y4oxldzjRrhxVueJP/vjnfPH5gb/41WuePjxSX35KHwp0AKLBKCiUIvQH4nBk7LszcL2Aw0VRnOkWxhjatmWeZuqyQCXRwj3tjpJuUpZUdU27WvGwO3D/tKfrekhCjC3L6iz0NUpjnfg2VeVzeECMUexdjGEYR1YrcapYEoCMsZRVKcJpJ6Lt2U8oVaC1oSkt6eaCYejphw5rWoZx4sW1dE1ffv2Kn/7khzhrKZylLgt0isR5zgqIEle4c5yXSoG2FIO/kDsTMnhsckgFLIsI4cgtUeukLAFKlvNmyghrfvmZjLVC2PRw6D2T31OVBU1TwjixqitI4KqKopQDO1Yr2k9/TO/h/W9/SR2PVKXB+5HRjyJUtzZvlp+7kAWHnKYcv6YUTVHw4mLDcezo5pnXQTIH/Njjfd7I5bASvWz71HN6zse0Ap1hkOtVy2noOU4z+77ncrOmrYReEL51f3077OQ59fhMXzxvlz/e+H1Mh/k7LVJtW7FZr6jK4mwbgpJ17ew90xDws2c9zpmVN58vlFJQ1SXOtZnLEXMg5yzR6LYSDyYtjgpLMonRYi4ns7mQPqXdFmtckyxdBJ/bWqUVg4/sfMFh3/H4tGO/P3A8dfTjSAwefIToWVWWi4uGq+2KzarBOsMxKPrTjjsCJo38+IvvkZLm6e5rXv27/xE97Pgnf/wTLm9ecHl1yfvXv+Uvv/y37N/9GosEK8TUYy/26M2GunL80//kP6b95Ef89W/fYZjZ2MgXNy0uTnSngaYcedcfOfZgTS1r7yh2tdfbLf/kZyVfv3rFh8Mr5mmFuf6+cGVOe47HO4rY4fueaRypXEFqzXnFn1Ki6zqGYaBtW6w1+HGUdFqgaipJP6lrysJRtw37rufthw/sj0eMMrSrjBeFCClbzQZ5gEnSsaRsrq9sNppTzzl5yw29ZBxqDdM8ZizSonSiLGvmEGhwXG3WdNcDd/eipTwej1y1NZfbNX/xy19xdbkVqxctPLqORNOsIM2kMGONkI1jzAC3sYQkThss3Delzmr8JQXIx0BRlqTghZjqPbawOFdmR4dskZw71cUlwOZNt9bQ1CXEwKmbmJ1hDonCWa62l8zJg2uoX/6YLihef/mX1POBdWEoTIHSDWM/cDid2FRyuMzZrmjyKes+U5Y55Z9nyXX0Iyn2DDHw9akTvzbrSMGjlRgMam0zJUFhg8F7+eyMVeefRSkRfN9ebBg/3DPOnvvDkdJZXJ6cFjnPx97nz5PVx17oC2UBnnUYS2H7jigIL24vqMtStjh5bBuGmWEYM/FNy8kTIflAXSicURiFrO1TYp59lgIYlFE4JXwLZw3WKsEqrMMVxfnkiCGJ9xRZFKw0MUWmQToHSk9SkjhjULy/e+Jw+HOGIbO0U0QnT+ks203N1abmZrtm3TRoIqOfRbM3eeIUeDp8STcnxq7jr/6n/57uuKM7PPKDzy653jS4NHG8fw0p8eV+B8MBo4WFLfO5ox7FYRNr6MeRWmmSnzEqEnYfeH2a0CqRtOgUN8rw/SqwHwfUPvKAI+VTcRx6prHDzjP94YHH969Q5ZauO3GxXmHaCmsMs5JNWcw3weJq2vf9GbwOUUDf9VYOCyFnKsrCcrHd8PD0xOOhY384EXxgtd7K6T1OVG3DNHtOfU+Vlx9l25xvxmW8sdaxOx1lBZ5STp+JGGto20YOnnwzr9cNw9iLBCWJa2oZE5++uJVk5nHm2PeMfmazWVNUBW/fvefFzc3ZieFwPGGso+9OtE3N/dOexfrZWSdpzTE+J0Gr5zX9mMHyKtMRjDVYZ5nGiX7oc8irySC+bPrKopCNobWEWTIFlVJsNmvasqAsxHm26waGSUJWk4oU9QZz+Tl9hDe//iua1HG5KkkZ/9LZy6ptSm6vt9IAoJjmSD8GUS6MI4fjKRvzyQg4zTNd13MaTrQrT1E17Do5BCqXdarpGRMSwm8S33jABnXeGJvMESydY9NUPJ5GHo9HVnXDVVtlmsM3rVaWf9d5jDzfC9p8Y8Rb/ozcE9/RuDdOkX7o6brxvF2yhaFp68yCjugEUYlTpC5zi5pP20Uvpo3Oo2NuO82SylGTOfjM3nM8HsSzKKns8SOJvnMUmwwAF8FFT3ClrF9RzOOInzqMilxUgme8uNyyXpeUxTM4Sor4EKlqR9MUmASbGNgOM8duoNMzoYiU1xus2WJ0QsdIoRNGR+LhHStnmaJhHAOTD8TocSag+45SGWbV8JQKmmgprYHpRL97i3IiljW2YFYWn4K4UE5iInbXpfPWKWRrmpQSRiXWLmLUgeuriqoyWKsZJ+mciqIgRYlfOuz3LCGh19fX5xCCEAKT98zjyOpJis3VhbDN373/QDQFp36AHIZx2O9Zr9d4EsPisgmsN6szxyhq0R+WZUlInPVvIQSstdnJIXctKVKUNX1/om0bYbQbwzgM1KuWYei53WxYVQWFK9k/7eiGkbqpeXn7gtdv7zj1I87JyNiqhv1uJ9pVmxCnyTzulmXGonJqjf5IBpMfpmmazpypYRhYrVbUbcM4T0zzzGq9xhixTiZBW9dcrFqcUVzf3HDqOkzGlYdpROuS9aqlKEqGQcihfTRstp8ym4r3X/4NKwYuKpt5bMIJI3dpN9eX6IUBHyKKiNaR7XpNVd/Q9QMPDzt2TwdJr862Qu28ZpwGxtNRvOqVOJOumhVt0+KQHEFxJzVnCMUZ2QQvJNulGF9vNkzzI/tx5s3TI231klUhpOKYx76Fd/Vxms1SmD5Oovn4v8l9Wn43RerhMFBXFc26kR/MiHtgjIlxGJljIvkk6S5BNGZKz1TGYq3OnuDCqpDiJMTGqAzTHDj1T3nmFXcE+XpNCjI6hmxVvHSOKm+o0v4NMTqUcVyXM9efbri6XHNzuWXVCD9GNo6CP5kMnwkaISdKDF5a+ABF7bhZ1yh9KZhFkBigoe/PfKcEYByuatHHI/3wSHbTZw4z8zxRqsQn3/s+Tid2+4NYeOz2xHnEqJIpQBw7VMpk0qWIa7BFgbNNbtNFUGusPW/GCusIynAaZ/ZH8Y8y1lGUiuHU0Z2OhEWeUpYiqvWew/6As5opRMZxZnccWNU1q03L/f0T4+jpw8ypH1k1NSEEVus14zQz5mtEDLSbNWUpxm4hiPauLiuscRyOnbhKZtrDcnNaI532PEk24DTNGDPTtg1VVXA67tkfDnxye0Pwo0ROoTns9uwPJ9q6Zp23yw+PT2wvtqjMmp+niWkaWBUtpbM5yVrTrtZ5qzvJVkqJJ7vJYnRrxLN9nmTlvnQm1jpZEuTlTttszizplMH0FBPH44HtxQXBS7Fu25olZdpax4vbNVOCUF4yqpI3X/2ajZ7ZVAXRT4A6u2zsj0ess6wakQEprbBKoXXCOUVdFdR1wXa74vpyy/u7B7767SvxF9OWIhQ0qZXPbLWmG3r64cTT4z3H/Y6iqmiaFXXbUpWNwCrGghGvf6VNPsCXdgjCRaR794FuGHk4nmhvr4Xak7Q4U+Q/93Hk1ceyo2XUP0uL8p8bx++IJ3W1FnZySkuKrKLrRibv5ZTKgZY2go5BWNCFRmIKIj6AsmI5EpJinHwuEym3hoaycvh5RpHOvt+oRDKWECAmg1KWJBJrlLaUSYGSB/mnn/8co/L46BxhFt8fazWTmXJQpKzTZRTMzpvOUteVjJlGTOZTiAx9R386CNmwWTGFQDdMzD7ip4AedqjocU6WCqSEqS5pLj+Va3Zxwd3rVygvwQAuBRKacRKuWVkIac9aS+EcVelwhfhkyTgj4+PiR1RVFeuLLUYZ7h6feNh17HZHDoeOYRDh9OC9bJisdFHNagUp0Xcd0zTiXMs4e3a7jloZPntxwe54pOtHrHXMQ3e+8cqq4NQNDH5mGCfGeWK7bqnbOhMbpfMtq5LVquXpcS9ayTyOfGw5XFjxlR96CfqsqooQZlatZDRWZc1u94h72nF1uWa1WjNOIxfbNV3fY61jvWrZXmx4fNyzOx4kj9BoisIxh5kwT6zallM/UBal2M2E+dzNpyTLlSK7Muj8UH4sOg75IBKvrySBmkEslZUSO2DrLFUhbrEX2xU3l1c8PO2pyxIfIv04cHtzg6sqdHNJcCteffUbLhx8stnSH3Zi36I11omdzjhO3FxfCvcswxrGijhcWBOacZqy/bCiaSqMDry8vqSsa8ZZvNSP/cgwjLR+TYz+bJXd9x2Pj/c87R6om5ZmtaaqW1xZUrqCqPS5+VBKEUOkco7bbcvrhwOv7x9Yty23WSq1+Ny7wp6vo7HPJeXsfBolxGGRSMWUvk1M/7srUs6ASmL/IN5L/pxSSyblKa0xpsofONR1QWGtmO+HSAiKiAFlwCgU4hgojokTwcvXFc5QOJ2FxwCOEBMxuwMoZQgqr5FT9uMpxId6acvjHEhhQisvDpIpMs8C7lurWa8ayqrGuZKirM6nqJCSFRiDK2pCSJy6E2MU5vJ1sxXe0TwSphGdCWwxBJIpWX3xJ2x/+Me8vpPuSmsjN6RK2Kqi1BuUEteGwjrZBtWNbERIZ52etmJ8F2PKywRLVVdUbUN3Gs6GfMM4kZJ8P7FAkYy7cRzP7b24ZY7njc40eaYpcOpH7u4fhdypZeO1pMv6MLHZbng6duJ3NUvAZF2J/Y33MvJLyKtwoQKJOQZOfYfLRXXhbC08tuUU3Ww2HA4HYak7y6pt8fPMm7t7XGF5cdMQo6dtKh4eHpimidIVrNoVx24Q2+YkXVJRFDR1zek04BYColKcTid5cJShbdcMwwDIlnEhGBaF2L0t7hg628A4586bvKIs8H6mKGSkruuSVVOzWa9QMeFM5Oqi5ZQTduqqJhlLaq+wqyvuvvqSCxv49GLNcNqDCjjrBOQ3mqf9gbatubwQR0+d37OMqJaUt9pLIRUS5oBSiYvtirqu0bagqBsSlm6YePP2jsPhwDiOrNYrgvcMw8DxdODU7TmdDriyolmtaJoVq9WG7XZLuV5RVzWldRid+MzP8Bd/yeuHJ1xVY8uWwi4dVzrjWfqjcU5pfaZ9KDIhddn2Kej672jcm3wEJSdkVTqa2uaKCtY4VEpMIXHhSqoYmb1IKfohMgeNMg6tTY480qQwMw09wc8oFSldSVEulqOSwDvMPhuGabSzWC2ku6Q0PiTQRnhUKp47ImPFAdJPkurh/YxC7E3bVsilVV2jrQMs3gub2BlwRZ3Tanq6Lgc1kGjbltUakp+JObBy07YotT4XgGGc0fUl5eVn3Fxe8PXbBx6eHkVpHhOFcuihZlXOFM4K87tw4p0VIykpVLZYtlZsaRcHApRIHJRW9F3POIwikkiRpq5wLorecJ4FNwJWq9WZxGmt+HDJzT1yOomtS9cDfubnP3vJ/tQxDDsZi7RmmieGcRQAexgoyhIVPHVRMPv88BaO1WolDPRpImnF8XTEKE1RljRNc5Z2pBAoy4LVuqXve17cvmAYRvpuQNUlzhquri+5e3jk/YcnVk1D4Qyls8K9myd0EMbOatVy//iISrA7HLnYbJinkRiFFlBXYunsQ8RY2TpVVc0wTiij8SlKOlEIYhmdC9LsPUX2v1p8poah5+Z6Td+PDMOMsxXrtuViLaJniRkLrNqG2UeSMmwvryg218xFy93XX9Ey8ulVS/ADxiiaus4gvsRsjfPE9z//nKosUcZhC7FwCT5QuJKUZrFUIYPPMdH3Pev1ls32UkD8FARKMJGLVU3zoy/Q1vH6zRs+3N0xjCN1XbNeb5jmib7v6LqO7vGRfr9nXz+y222pm5aqbWmrmraqKQvL9eWlWGUbS7IWjHRQ1srCyhor6tqknp/f9FFwVXr2RCd3id9JkVIpYnTKntbCm7I5Ziki3krt9pKHu1fc1hNOF2i7pSgqGq0xRhH9TIwehUdZRbFaUxQFrijPhLUYY8ZTIqWpwIjoVxuLMRJZ5GwpyvwomqppHEjRM48T4ylkUqhEHF1sVpRVJW6BzonWKLOKp3mA5ElBWOf7wx4fJqw21GXBtmlZMt9SiihbEqIVWr9eCIEOHzXMhpmCJgXM3MMsXVbfdczdkTieuMFj64KkwPvEkDzaCLt61bRUTU1ZSOiCzfHyZyBSyUKhRGeHyxJbFCg94LPNSZ+3eUte28KPch9F1Z9OJ8ZxyCET6lzch2EkpSi5dX6mH2STVJcS9931PXUp9q9kzZd4VJWcTidSEhBaJWhygU3Z16osSrruRIiBpm3ZPz1xe3tD01QcDkf8KTAGz9XlBdY5druO9x8e+KMvvk/04gElwbKB4+nA1fUNu/2Bru8FsB5FtN42rUCDWhJZdObfkTlj7XrNqTvKA77ZULUNT7sdhXMUZSlLgExzWThmXdcxb0esMwyDbILLwnF9fUXhjHwOTqyL6lZx8+IzPv3e95iT5i9++SsKf+JH33tJ7QyoC3zwHHd7xr4DDaf+xHolgaUhJQpj5F61VsTlSjFPSZ49FmcJTdeNfPrimlVbczweGaeJsigxRQUKmralrBrquuHli5ccDgfu7++5v/9A02zYrtf4bER5OB059T37+/ec9gVFXVE3a5qqyXHvgcPukcPxyM9/8Q9IRjMNfV6eWYwSz66P+VfLJnG5h5duWmtxPf1OilRdWtqmFJ5TUpA0U9L0k6cfZ4wpcDiam5b/+D/5OUrNKCV8DslLA2NWWTyqsK4QwqUydH3H09MTMYhXkylyJhuapCxlXVHXNSiPSoFpGAl+ZJ4DKSlSnAHxXXdWRp+qqqiqGuMKosojRxAJT9+fmKaRrhs4HU/E4KmbmsuLFqOa7LeQsi4tAfobxMh+nBhGOXmH0YuOKUSmfmb++je8f3/Pbn9kOJ4YHh4Zxg7mgbmaCbWhdI6qbKirirqpaasyb/scdbuirhtxY/howyMWuZHRe/pu4M27D7x+d8fT/sQ8BqLKuWjIA7nfS85b27bnzc2yMTTGQIwoa2jWLVPevlVVRbc/SlcUxffo6fGJi8sL2TKlxH6/p25qQpCOY549Kim6YcLPSYIJMo9GmNqCJ43zxDAMXG7WnLTh/v4Dl1cXTL7geOpQ3nA69WzWa+Zx5sP9E198/3MZD7Pbg/eR3e7AZnvBatXiZyEKzzGcRbjeC2Y0z+FMU1iCP1arFT7MZ1PAzWbLxaXm8fEx2xrPZ0InQNNIQvfxeKRp1gQfGUbP+4dH6qZm3dT4IJicdgV/7+e/4Ob2E+aQ8McDG5vYfnrNummIiJvAMHuSNpRNKw+xPvLixcvzw22dk3+sIzmIcYboIEnH5n1A7KEnjFEcj6K7LIqCqmlwVYUpGmxR42xxLriijog8fXjLi+sbQkj048Q4VTIOhsg0ywLicDzSPX5gKhyffvopkCDMvHr1NW3b8Itf/H3qokTFJdIM0cA6db7ey+YSnvGpBUbR3xVPyhYlEcswR6YQSWiKqmZ73XBbFGhgmkb6bkdRWJpWBLTWyFZKGUfS5ix9GceJ/Wmg656IXqQdRV1JGm9IhAjaWorK4oxm7HvC1FOUhtJVHB53hCCe6nVV4gqLsxZXOKqyJEUY+hPBTxhnef/mA/MUhNjZD9K9rFs+/fQGZ7ObYZRCEGPKm6BErSS6OyE6wMF7hkm4X66ogZlhOKFyV9c/fkU3GUmrOZ7Qpw47j7Sl5fPrK262FU3bsGpqSanJJ0vVrKjXG1BGrF2MzhSCERUCwzTgZ7HWLaqazcUlzX5gDIqiFn+tvu9F4DtNWQ3x0WmGgMxaKbQ1pGjwIXF//8TtxZrVquU4htyFpXP01ew9u/2e7bpl6nvmEEGNrFYlISiGbsZYy6k/yFhVV2fBeNf3zH6m0FJAd4cDVem4ub3l3bt3rDdrVm2Fs5q+H4kpUFYFLz+55d3bt9w9PLBpamJ2uWizlc/dhw9sLy7Z748Y5TieejaNZP45p0ixF2A/PUeRR0TzucodRIiRaRjYbrdM/XD2tlrW50sxX61WmQgpnvcxCZZ36Hrado1yJa5ecXVzw2q9wQdP1w28f/eWuihYrddnHy4/e8h0GmcLng57bl68ZL3dMo+DeKi5Am1cxlcVipCDcxVzgGQU3h/ZrDdsLq6pyhIfZHnlygrraqp6gy1LYpBEm6oqiZkXVVcFL19cSZxa0vJM9yNPuyfGaSKmyIvbW6ZecgJcCkJpeXpgOB14+vCW4/4zyttPQWmqQraThRMVwEI1cmaJv3ouVCE3Cfu4/26K1GGE1pVU25bLpqUqRag6zxMpRbSzbMrLDFCPJBR1UWOLUsD2aeJ0OAnTPEaRpEQxzzeZEUsmo1oro4hKEpA5nSb604kpTBS9pXQD61WFLQqKssTZKrOcZ1LwHA9H/DSiohTUaQ589ZtXVM2Kmxe3/Pin19RVkccBseIY+o45h4UunZQQ6jTD5OlOA/MscU7taiM6xmmkbAwX65WIbcMs8T1R4eeEv2hArTDGUhWWVS0iTucMOmMPTbvO1i3C5H6WEwSmcaDveo67HdM8grYE7Xj99h0fng5MIYJ2RD+fwxe990QvyS5yY0SwSbZFrqBTJ5x1hIznMA087S6wOZFn6T7qsqK0Eps+DiP2YoM3lmmO+HHCFSJtaNuW4MXSWakkn4dz57FTKYXP1+10OnFqStqmYbvd8vDwyNXVhViWFE6M9WLCFY7t5ZZhnFjXNe16xdCdsApe3tzw5u49GnXe5HnvGb2nyUCuswZlcgdtDX7OzqvGYo3i6vKKp90OHwI+BK5vbs7g/IKdlAvHKinKbDMterVEiIrfvnrP3fsHbm6u+cEXP6BsVkIsNTPv3r1h6ju2m5YQ/Pn7qgQkhbUFSSW6oeP2+opCi+hdW0NRFWiXl0sZ24GUY79EXnI4HLm6vqGqREXgygrjKmxRUZbZEtsaZp0367M4GQA0bSOcRJVoXMlqc0lZ1UzTzNPTjg8f3tPt96TKwcWKYyfe8FfblquLNZdXV0zHHU9KsdsfacqK9aphs9mwattMk7ForCgKsgxngR2stay/qwTjT7/4CdvV8s3lfHbOUjd1XtwktBb5SllVDFOUdehTxzTN2d5YYV2ZGadyyi9Ez9I5UpxJ0RP9zNANDMMgJEdrWa8bSneBqytZ7eYYqRgTcezx08g4dIyDJGJ4PzHOEVuWvHzxkv/tj/6IqimASJo90U9M48CY891UBKLYjmgjNId+mOlHz+xh3W7YXBZMcw8kSlOj9QXKWawrQBmiD8KnSgHvRf6TgmccjpgUKJiw0WAoQEl+Wdd1NNqKQ2Lw+Iz13H+45/7ujrIouby8pF2vub/f8e7ung9PTxx7YfyPgxSo0+kkJoLC1XjWmLEIrQtUgov1BkmNPmZczvOXv/oNV1cXgKJpG/bHk/hhVyUxbnl4fKB0Bmda3r5/IKQI6si6balrIT7O80xdleexJSUBd1+8eCFYlVIUZYUPicfdI5+8fMHbN3c83D9yeXVBWRbEmOg6Kbar1QqD/HptxUVinmc+fXGF1pGuP3Gx2dAPM9oWzF5GcLS4dYxTQrmCuq6JIfHq7Rtq7ymUpXIF1xeXHI6CT0mSkaT3LAUlpZS9sThje0uXtbCpfTIMk+fh8QnjSg77EyF6QpjZrGogsctpzmVZ5mgzqKqSd3fvWDUNmsA8TZR1jSsL4UeZBYDWaFVCNKTMqfJdT4iJm5sbijKLoI2hXm1xZS1wKYrCWrRRRJVIM9noLrHZbmmqGrSYPC6FwxpHWVZcXV4xHB/ZP95x2O8JKXClb7i+fUlR1iKajpHxuGddltRVgdMQpo7JgKlrIpHBT2dfMBF8y/VzrmD6rnhSC5DrrMqGagmSeEEHnwiI2rsfJoZpllMxJLSRFraspMKP08gwDLLKLUu00YzDyKk7EaZBkmhIGKNYrxtceYErSqqyxhYi2PTTyDR1hGkieCEU9sPM49ORcQqsVg03n37Ker2SqJ4UGE4HHna9SBkA64SzlTTCFg+JOSi6PuAzcz5hiEpRlBZXVTSrho1Zy7ydZL6OiD1uDLlDjCJ4nceeFGacjqzqgrpaETLPZbH51WHElRWFSqgYRHvYZfveCF988UMRsfqZY9cx+lHWzpsNIZ04dZ55loixmCOoxI9JfJmK7EIwjiOuqXMidJFDJmSjao3hdDpS9qNoJ40kN4cYaZqKOUxMQ4WfJ16+fMnTfs/T4USZxC1BFgjip+2sPduZ7Pd7thfbs8fUNB+52G7RWjGNM8MwcHt7Rdd37HZPwCbjiBV933P/4Z4ffu9zSJHjqaNtKoZxwIXAi+sLDl1PiIaqLOjHmZAUx26QraCxUCpSDg0R/6SWruuoLy+F01NKIME0T+et58JEn2d5f2VZojBCYlWKqirFOigDwyFE5igeVSBuDsNwoq5KFCq7PEgkvEJsqJ11DIM8A9//7OVZhbGM4kDmzpnsauuI0Yhu0iiGeaRum+yuKhmOtixFcmTysiVra4sAqEgYs8QselbrtSxclBBOi2xPHULEKIVpHEWhcS5xebFis3vi7u6Ru4c9qqyxRYHRAq0YJy6o1oprqvAQE85IErKfRQxdZhvvRTep5u9ou1caTVU5QMTBIYrId85RT3OMwmWKwsa1rmC9aqiqmnGcshJenTdN4zAwdJ3YOQSPVpG6LFlfbHGlcISsc7isHvfe03U983gihhE/B6bRczrJKrWqarZXV2w3F9lmNzAMPd1xZh46yrKkbjfC58pkw2me8T4wh8gwzBhlMa5BIzqqerVis94IT8kWGZAv6fsTu8dHhv4khmEpMU8T89gTfS/yGaupVyJF8CHkjVpCowkxZUqBUDOUtpy6gcenR6Z5ks1XLaLrYRww2oJuqeqay8str9898HgYkdSWWdbJp9M33AhAAg5iCBz6nhgim1WbTzMnndnDA+v1hpSV/ImAUp7PXtzQdz0pTnz2yS3D6URhHBb4ox/9gD/9//2lUFK0jFkxbwWBczKN1pqrywseH3eEEFm1DTEFiqKBoM9dx3rdcnFxwW63o+9HttutAL1XlwzzlIvuTNO0dP1E2zrCNOOspbYF23XNFAL7Y8xhHYmiLimMOIvOQXRvVVHwtD9w7DquLi4YB4nfKpw728gMwyBhHCmeC1dRVKJf9DN61mK3ksSdVmnNPM0cdnvmcRKKxaqRrqwsRZVBROsEQaLci6Lk3bt3fPryhou1EC6NNRSFxRQVpqwpy0YOl+FEjEE0lglSVJyOJy4vLynzcsk5Q1nXlIW4si70CSm2GQLJurqUZBlgnDQHzjqKUjaJ+GxBkxRRQ2rX6LrJ4auW3756ze2La1abmhQVPhtTKiXEZ3HIiIQZphRRyuSuVKLb1u0K6xxT8LSr72jcm2ZP3w94L+ZxPpITNxTKyGaqqSrqqsbaAgWCk8yTZC2gGIaeceiJmdxllGTHVXVFWRViL6oUMUFZyAbp41ieOHnGwXM6Hum7HlJic7Hmk89eUpY12tUURUkKkZA1XEbrTHBVGQieGPpeGNijJyFK9rJszoBxuxLaAsoSU8TkIMoQAvf395z6I2GaiXMgTDN+Hkh+xjJTN471Wta3CTieTmitWK9afPDMk8cUFbasmSLsdkd4PFE1LZcvXhLCTAySNWiMpiot2jpUP9INI+M00/UDwzgKzyW7HCzbu0WtL5q5iWHI+B8yTm43EmG/zgCy93K6juOANQX7/SOrtubiYi1LiVq0aE3V0BQlzXrFi+v33O/z1m6aCDl8IQTBfrqu4/b2VvhVRcHT0462fQbU63bFMPRoY3naH2V17kqennbsdweub67zOAXTOHM8HsRza5hRRjptpaAsE1dXW/ppFq/zumKOUjzKUsi9jCN+mqgKR+ksfd/zECNXV1fn0a4oCokKy6ReSZgWoFcho1dI4haq1ZiXCokUwlm9sNmsePHils8//4zNZkXykwjDiTgnnY22Fd3gMRo+eXmDUYqYLK4scWWNcy3alZLIPA1nwumilY0J5tnz+WcXOCtLKGsMhRXeoeQqyt3unJPuLW/VlBb+UlmWcvgXBdaI8FwpzYw8K25ZXIWCNM8YV7Fab6mqiqYpub5cU5UVWlvmAI9PeRucIj4qwjTRjxMhpbNbbjgdGMaeum4oqvrs9fZ3XqR2hwGvHClqjK0pMn/HFQWucJkSL6ziGCREUMIePX3299FKiaSgWsSOLoN8NgcfBGIIEkI4zue2GmC3e2I4HVAh0FQFt9/bUlbluRvRpsCVDbYoRE/mtdiHoIUPMo4MpxP90JFySkxdik+O1UYSToyIfuUhlyCD5WY9nk6Mw0gMM3HsGboj09CJCVtd4tqKwrQI4V3RTeM5fFOhOJ16fEhoVzKMgTj2WFexvXpBXdeiSleKxlYiT9BidTxNA7unR/bHjnEWIbN0gFHCJbJJ/mLPsmylFlfOlCLzLBIgP0owa9M0aGvYbrd0pxPD0DOPI0MINPWKp8OR/ek9xhqu3n3gZz/+Eaf9kaIqmcaBn3zxBft/90vpNvqBwtmzCHoYhnORXLq8Vdty6g7c3t4KqGosrhAWt3Mlp65nGEaJXTKGN6/fcH17RaGqbF+s+HD/RFE43t59wGU6iNWG2+tLri+2mYw6U5YV+8ORT+oGnyKaJFjfOOGMOd8Lb9+8oWoa6aSGQUiGzgnfx9mz7hAlUEecZxKJOQS0zQLm3Fm7fB+nFOm7Izp5kp8gTiRnSRgxx1OBp6cnPn15S2klIbmoGtr1JaYssa4CFMHP+CRj39KxWGM49QMpBFZ1iUqSnCTxYA7vE0lFdJy/IaCW/5U0phBDLkpGRrZcnCNQpCSfjTJMYYTgCdOETmIc2a432d7FYm1B07Ss1ls++1zkOkPf8/S043Q6ybOO4MV+DngC8ywHqO2OnLr+uylSES1bqrUQzxbuzTRNPD09fTSnC0FsafsXztJ6vaaua6qqAmQ8CjEyzh7mZ8vXnEOIn2e6vmMaeoyKFEZxebPKVAPp3JQpiDhcWeO98FDGzBJf0lKedo9n8LJtGjbby8WJmcJYrBMVubNWjNEy32geJ8ZxZvLCzZqnkf50Ig4nbJyorKJtpbWOfmKaE9EYbCGxXyEJZ2c5BZW2KOeI2tA2Le1qS0wqc69GAZ2NwaosT8myjqfdgXlKuGqFMpHD8S4r9sdnn/Akso5Fj7Z0CIvnj8h4PLoqGEOgzoXZ+5nCGnTTMk4zx+ORmBJ13TCEmYfdnqEb+ez2BRfbVuxLtKGqCpzTTD5boBhJaRkm2eh98skn3xj7Zj+xXq9IMXFxseV4OAAL0zvQnYTR/vbujs16hdWaoZ/Z7U7088zxcKIpKz775Jambpj8TOlkO9udBuq24fbqKoeoSkcxjZMk0fQnDBoTA04rUiHgtPchL2bmZ+JhtrFW6tleJKaEdQadAyHg2Z5k8jMuOTCaoiooCotSAl8oInVTf2OZcP94EkzxYp2LoFxrV1coJQnGyhogCkE0alQEk7/nm9evqEpL6bJ7uU90pwPDOGOrNcZYikyMFqsaQzQGlQwE0XIm0anIP9mmWNJfNMog/upxIviJSMxAvCSML/bPWimmcaDTCmNlAqqqLTe3N4zDwOP9B05dxzQMjLNAQillOZ1WDN9VkXrxyWdsN1uUVozTQJ8tgJdV8zLDy1akomla1us1VVWe17nLnxd+kzl/2EtL6r2XLdUw4qwov69fbLFaYZVEl2vnMEVJXa+JaGEB5/BQY1TeHkjh7HMa8na7yW4CYs9al9L9pRhQKRHmnuPDThL8qoaoDH70DL1czDT3qKnHxQlXaoyW3DrJ4pOb1zlHXdckpZiyJYpShqQUT4ceW8CLT66p6oIYPCkMmcdSoJXGqkSR3QG6YeQ0jfTdJFpFZ9g9PjFmbGkcPcfj6XwzLoJg0e+F55X3wvRFwM1+HCWs00tSyTD5LKaVz6ZtW6yzdF3Pi5tbiSzygXf3DyKG1eCsKANWTcHuJJHb5yy6rsueYs+YTl3XTJMIxuvKSaim9zLSVwX3jzs5GICkJEapKmrGOXL3uCclhSsqHvc7NpuGtqlp25YUI85YjFL5e85UVUFdFsQsdYo5ul4hNBOJToti0au1hGBGAaeNs5mUG5gnz6wC1oowvm6y6DbGM+6XMp9uvzsSctFsaqHTnMKRdVvRNBVoCQGJEQ7Hjpcvr7EWok+4wlKUFk0QNwxlIYrrbKEVyii0VdSFZXc4cnf3nj/+xc+F5JszAGNMNFWDtTq7jerzdjUmOUSWUTGGdH4OFhsfkanlNJkYUXiM8jirske7xmoRd79//57gPV4v1i4egyZGfS6yq7ZGhw3rSqCDbhg5dEF4j1rUGvq78pOKKdANR6Y8xngfROoQnrulzUY2NHXTUhZSmMZxYBj6s7eQ0gqdnhNM5nlmGifGaURrQ9s03FxeUpUGaxaLZk1RNhRFhcobNSkEHoi4wqDmxOF45HjYkUi0dcNmsz7LSopCZnFjNGme8ccdp929aKKUlc2hsZye9kzjQJzFsKwqHPPcoZIXcNKYbC8r255zWk7+0NGaqmnphpn9qadu13z/xfcxztJWJSmOjKNs/dq6pq5bjJXVdzd0dKPneBrRRj7Q3X5HmEex6qha3r3fcTqN5793YRRbI+PV6dR9wxp2SS+OMcKcMh/KiH4xjxMfuy1aI7SSkBK3V9fcfXjg/cMj2/WGprBUVcHYD5SFRZ0SKUkx7rqeeZ5Ytxd478+r7RgT69WKFD11VdJ3XTaUVExT4Hjq2W633N3dcXF5SQyepm143O3YHQ6EEKhrAZKTUrnAOsZppmgsTVNlAzvPaRiYpxmSwui8aUTA9KRkoWOUIsXAaRgkmksp5mmk0gpnC4xx4heWi3zMdI5lepjPQRfyoIUcJvLrL7/m7Zt33Nxcs2orVk3Jw5OA6HVdy2FgDVcXm5yELLhZUVhiCpAiVom+0qSIUWALh9cQo+fd+/doBZcX27OhoFKKsiopyxZlC6wVuUlVCbgf5hmykmCcRhlds/uCzm4KKM6wi9YQ/YSmociyN61l2XX/sOfLX3+JnwNa5yZDGLIi5HcOY0Alz9gfmaeR0hpSWRJCYPe0Z5gmXn7ykjB+R0Vq6I90p8g0juf15bppKMqCMktQyqIAJcJOwUlEUb88NIscYRilE+tPJ4zWbDZrrl7eik5IiQq9KKSN9CGdEycCijmTQUEkKof9ntPxRAgjpXOsGuFQkaCpW+EH5Qd2Gnv8KK3sNPYo4yiqNR4jJnvTEZ0STgWKElarhrIq6U6Koe/QWfsnoKQIfI02GK0IypFsiSpKpqSpLzbcfN4CiXHoMSpQFvK+DHLyeh8Y+o7RR8Z5YpwiIQlHa/f0RIoTbVXgVmu0dTw8HTkMM7tuYJpjJsatxYVzGAkxUNUVczYmW2QwS7FKKjJMYlpYVRWr1UpCL5RsAq1z7Hd7Xr78lDfv32GNo6lrQpi5e3zism0oS8exG5gmTwKGfmC9Kek70XIVVYnO41JM4P2In2cutqsM+vcY5aiblvf3H6jrmv1+z2q1oixKrKmZY2R3PMm2OClOXS+4VzJYCh6fTpJiTUc/9ry4vGbd1vgwoZSTze80iE/9LMnKc0gUVoikx17eq3Tf4pqQYqTvTxRFgbaWGETzt9y3C7UCnj2TQCyKbOYLVmUhGs+YqIqS1WrDZrNGY3h4euLHP/ocrSJhnrFlgTVOxnsnPKWUPMaRN4qeFCzj2DH2iePhxKptcXohR8qDbqzgeK4sKeuGFKO4fPoZ4sTsR4rCMU4DcfZYlURwbyWTUkT0gaoqKIyQTI3LIR4pMfYnHu7vOfUnpnkSsm8OW5Aod808Tjg9ojIXz2jDmCk1RkuYg68LvvybX/LJiwvq4juSxTx8+MB23bJpSqrsVuC9eDiTAqfHe47Bg3aYqqLMp8c0TeeTvDud6LsOHzxtU/OD739OlbdgKUmScVvXFNlXWkIIZavyMYjedR273e7sqlhVJVYXFPnCa2sEhD2XtuzPrGEMnjkmvK5IVuGniWk4oPxIlQJl4cQzWyWMgqE7Cpn06jIz42XtPM0zfddhC8sYJezBK826bVjXNX4cOB52VGXJ9eUFzirmecx0C5O3pSOjj0RliNowehEAWw1tZShcS1lWGFPwsO/4+s0HXr994NQNGKsw0Zy3e+GjouSsZczFaXnFGNFGMWUQ/XA4nMdD5xxlVaGUkq1hf2K1avn1l1+CUhLO8LSDODNNPZvtFu8PGO1ypzzgg/iyhxCENa0NYz9wOp14eXvD7KNYp+QHbH88oI1hzqnBl5eXxBwhfzh1HI4dWhtCmMVTP7u8+iiUkd3DjovtivW64e2He4r8oBuVGONMNFECDmLCBylUdS02QnVdM0RZ1Czbu+Uw7fseY8scnJDO2OucI+KXrvlZGQDOGrarhu12RduIS8LVdktRlbTNitOpY7Wq2G4amIfsSmvz9xNaw+l45P7hPet1y1yUhCCHsJ8njt3Aseu5vbnOVAL1jbHO+xEXa3SMJBVJYSRF+doY/P+ftv9ok+RKszTB9xLhqmrUCWggWGZGJenKrprpnv+/mPVMTXX3VCUJAO5wakxVhV42i++KmEfNpvJ5Er5BBACHm6mJ3PuRc95D8HLpheBx84hSEaUS2tbZJ/ucSqPyTPbLw1jsVmu3ILKQwgs4sGnWSjFJEnSu0pdl3NA3xhgJF86b3tvb21/nkGqrisJoovfC00Z8XYuXoMFm12WovWJygdPpnDlRjtPpTEqJXdvy/bdfY6zA59S65Qky0ymKMlMb/aaeXkvRcRz59OnTpl5us7UiJUmR0XhKJRwbY0CFeQPoLc5TFDXGFlRVixsm5mkgjD1ueELjpZ3KbnTnXG57Whok189qhfcL5/OZZZ4Fk5vg6Tihqo7D1TXXTcM0jyzTSGEt9cUVTVNLym1wKBw+JGYn5k7nA9rWhKS4f3jA6oKLXSeY49IIzbJoOJ4Hfnn3QT7P4Hk6nTifTttWz1r7xbBcscxLnlesg17R+zvnmN2CatT24JWZJ991Xf57mo8fP3Dz4gUpAwJfv3qNd57PDw8sTUOIsvGZwyxugtMRrSXhBGTHOww9y+LY76TlnqaFGMk6OYXPMVfDOHJxeSlwN7EscD6P+BjZd53MgRR4H5jnBas1i/NENI9PZ0JUlKXhfB6pm4oUM6upkFa4TgUxGZI2zNNISprA8+ZrDU8FsnWjxH9BkFgP8ZXSIduxZ2QuiIjVGlnUWGOoKqFYVGXFOM08Pj3x+999I3l1cQ3NFLBhSs+D9sN+jyyVHLIl94zzTD8ICujF7a3AIPNWfVW/G1tiVCSFUcggSoiy0ooLUnkaJ9kWuiWnNyds6amrq01Nr7Um5KirmGImni7bSCEEmSm3rSCAVuzyioh2biFGK44EpMoWJ4p0HxeHAx8+fOTy6ubXOaTKomDX7cUXFhym1Oz3l1R1l8VuEZdbiXmaGcaBcZ7oqpKX11fs9ntKuyJnBYCvi4qmbiS+3QeG4cwYPEkJjiSGyOP9wPl8RilF3TQiRsvto850Bast1geG0yMpBmwK1K2wo1TRcvv6BU/nnrc//ogKDrfMzL0EKHRNQWGrPD8RBXJZCBLGx0hhDMs883A6MS2TDOvnheMw0+wuuby5parF5LnMo2hPyhwoUYg2aBjmrYrqzwuLk1w1FzXz8URhLa9vXwieQxl0Tmy21uIWx+PTI4cLMaoqdUcKbANryALKEL4wSHu0Jh9Ua8pJyqRKjw9CGy3zZssYkz2Uhq7d8eaXX6iant1+x8ePHxmHM1eXFzydHnjsB5wLXFxciFixkDTjtpHFQd8P4tgPcfNlTvlBt2XB4uUFdD4yDDNttwdWwD+yUXUOrYzkCtYwjj0oCeSoq4pplvlKRFDIboaxH6i9tFIxBHwMNFUhIlKfmIaRZV5yUi/U7Y66biXtyDlCVCSlssmY7SBalyI2q+nXYTNkLG5ynI5Hmqrk5urA9eUlXdtSNxVXVxLF1XYth26H9zMBxIHR7LFZb9X3J0BIBqLNkypKW0OIM58fnui6HYfDXrRMdZMtPA5blJg83hDSSNb0+WeIH4hmsbDPieNKgU6REBaCl3SZZXEs00zXVCScRNEFskhU5mjzNNO27XZgr5fh4haUAZaF4BNKl3h/EjW9VRSl4Ztvv+a//H/+j19PglDXEs9NgmEa8SkyL4HF9bnklFXx6XhEK9jvGr6+uZBbzYoq1UcnCbyV9NGJyDQeGc+eKbeBKSameeZ4OhNioilKdm27qWaNSliV0NbSVSWlATf2TPNA0zWoGLFKk7ShXxL98Yk37x8Y+yPL6YlKJ6xVtAWUdU3ddRkvK1uPspTVdvCevj+zjLKFM3VNMA2zg2J3we++v5bgx1lEd03dUFXd9sBoJRFBx+OJeZrlRlIKVMEUI/35TFNVvLy5oa1LsQwYizYlElaUCHnAe3t7i9IWH96QyJlxi9q0UDGK3UIi2P0GuFsH694HGc4Cq/R4mmbKotxmLasxdLfbURUlfd+z3+84VTXTNNG2LdaWjG7CTyNeQdftvjAGC9IEQDHQNg1VVW5t6IoRrqoK7z339yeRZZCRstkMvYorZ7fIJVGVom1LAW1kjrQsslhQWtq54B0+wrjIZq6uakJaGJbAuDwJUrooUabYJAW2KOgOB4ZhJIREDOKWqCq7SSdWL988z9R1vR1Uq4YqxiBIn5S4f3igsJrdruP66oq2aZiXmXN/4q//+Dvabod3FYpAWVYSVOEdSiWZ9WgAjS5KyENppRJKWR4eH/nNb76XysUHIYumBEr8fFVdi+A4V1UpiSUlRjkMRKrR58XVcwwVANERvSF6i48BrWFeelSSytFHwQApJQP0cRq5NbfbAbhq4laEk/cJkxOfimVgHnpp+azl5sVL6uZfubv7/OscUisrOcaIT6CLiuAjT8dHxuFMWRV0TccPv/khS/QBJUKyqq6J3gu+AY93I250LFlVG6NUJ+dTzzCOFBlTu0bsGGNo2k4CCgpLVRYUtkArREdVlHRXt0I8mD13TyeWpSfMoxA65xmioy0tpTXbwFTbgpAShRExp1hvBsZeTNEoRVF3pMIyxkjb7dm3AoGLSQb69W5Hld3n6zYoeM95OOGdDG8XHwCxCYx9z+Gw5/uvXmGshBOo9TM1BcpoSqMl1GERzO44znz68ImHJ1FkO7eIhmwWYy+5jRCNz4qXnbfDQdbwOclDCYBwXmbG0XJ5ccGyLPlQ2rPfi3L68+fPqAT7tgMt/839/oA7BkJ+cduilhA4oO97lNZcXV5SlkXeFhrOfS+ZiSmJ298Y/vznHxnGiaurm5yoK1XLMi9bMpAxhuCcXCIhoJW0skqxAdSWZcnYoCTWDC1Ug8U5pmWhshqlolSgFkxZMp176rakaWvattku2BAdIbd0dm3DchW1bqG/NE+vP+s1Dv1weYkLgT//+BPWaH747luGxXG42HN7c5X9oiUpLJSFkcMteowVtMk67xQyhyLlSjkkCClx++JWEqpVkGo5J+DoLIaOAZZposnavb/IwNM6exHLnF8Zt++vjpXkYPZPjMMgLW9pKHJYqnNOouOixHk9HY98x3OS8/pZdG0n1bp3aFuxO+yJCk58IAUpKrQtuLq+5uef/uXXOaSU0ZKOmgL9MHPu77DWcjh0vP7qN1SZPyRm00RZlbKiTwE3zyQ/4Z1A+udpEtpiFMTHMMxyAzYNlzdXsq0wBUZJ+qvgbyuKQvjSMhBcWE/CYz8wjBOn8yj9vfOE6UwKM1ZFdmWFMoJz0daitbjjTTYZ4wOn44l5XoSpg0YXDXNSLNHy8sVL0f8EL3YOa9hfXIkr3JhsrA253V0Y+oHhdBQhpyno+4l5mTl0LT98/xVVVUroKRnUFiNKCc4lBEmgDTESo+Lcjzwde55ORz5/uqfvR6Zxkm2ed0QvCv1i45e7bY6glNrEiiuYLCUwmCz69DgfCX7Z2oDCGl6+uGGeRgpjqauGJXgxebvA9eGK0/lI8h6XnuO2YjbZ+hQF7UwOsMw5iXUh6Od//tc/83g60jYt9QrPMxVKR2KcKGzBeeix2uZB7ywZhUmAiGVRSZy7jzjv8DllWulEYyUgwBQGJsl5rOtSDvJlYbc7bJC2XVNTGcNiNHWu+MIcNnb7ulRY5RkrD4n8gpZVhSksyxKYFsfQ93z79Wuurg5M88x/+T/+T0xR8L/9p//IMo2kqPKBRG4ns9DVCUutruXAVEZlsy/4FBj7kapu2Tdd5oYkdA6iNVY2skpbjJWflS0KMbIr4aRroQGyOEfXCsxPZUO4Ka1U5UYRoxLqrjWkpJhml4XIEtIbrWF/OHB/f09Zlpsly+ZILfK2tG5bbFHnDEpL0+1xi2BylLa8+uo1//W//r9/nUNqmBxPx4EleC4vL/nt77+mLqXFSElmISnFPN9oSN4xn+9JKeBDxK8+txDxSXE6j4zTSGnFMtC2LSabVGXoKPYQFQOlTtQ2AgNLLs/nyXMaRk6DVGMmR/IEvxD9QF1CUe0wCpI2WFthtGB6jFFZLyNZ9dO0CIHTWLyGcXbUyvLy5QtsYXB+5nw6YouSdr+nrlvKukVZS3QL8yRq9OBnfCaGKmNxi+f89EhT13z/zWt2TYXWiRBkgB5iQmktnqaqkXmdF05TihIwucyOZZk59+ft769bGxCNi1Kl6KwGYZevrdU6sxIFNaioiOpZib4KPyW5KzCOI1opLg57bm9vOR5PHA4Hfvn4YQs1aG2DsYbzcOY0DpQ50HWOPjPBJ/zsKawW6H4W1O6LgsenJ8Zp2nR1UxanlkVJCHEjNEji8i6/xOIg0FqCCay1km4Slpy/qAEho3ofxE6E/HsxUzjXsMp1jrJtxmIQikaumGLUTItYidZDe93qrcb4Lw+rlFa8s4wHzuczV1cHXn/1iof7Rwwwno58iAuXl9e0XYM1lphBjFobQHyj68/DuwnvpDpzi+fu4YGbywsxKSdhuCttMUlaPa0M1hbYqiEh35NLMf/MBZ7nvVxcu66jrEqUligvbYuMPBJxptFFprYmkSykhLUQgsEYxeXlJR8+fNgO8dVxslbtLvjMZy/FcJwhfsFHVB49XF3f0raHX+eQmkPku998T9e2kCf/0zBSVQVlaVDpi9t8PBFjIAaXZQiCFJmnBbdGBhnDrtuJ208pqrKkqMrcIoJKjugcWgU0NX5xnMaR03lmniOzi0QfSMFjlabqGuq6JBU1dpcjvI0h+EUOwa5DJdl0RO85PT2RknAJllRwnEd8DFzf3PLyqw4DchAEh1aadrena3b4ECGC9w4/T8zDmXkU7pVULIKrOR7P7LqGb766pW0rCq1w8yhomxCIEeqmlrLazfRODvAYExHF4qPot8Yz53NPURjqRmKvCIHCGrQRhbpwy+ftgKqqSg4L79HGYLWSrVZ+SdcZ1PrS2by9AmnbBBUi3sphHMWhbyX95XQ6iS7GWJbcchkrG7vgAwFPs2/ozz193+ODDNlDiDw8PBC8l6F9Kc6AeV64uLjYZkAhY2batkFi1o/0wwkhxgnFtG0a2RTOFhcjkbSx11drljYGUtgOpHUILsJeUVkvi1TOKW/citKQlPgl17ZvtRlprXMMV9j+jKyUynYU6RxAZfJD4D/8ze/Zd7W09aWRIbe1GB23f7coNGVZ59GHBN+mJIdvDIlhGvn9d98Sg0MnjclevZSUCE+NzbrAZ+2RQlpRrSyqsAz9wDgMwj1vGqyVFk8VFmPLLfAjrSdvkvxIBElGUcjn1TQN0zQ988HKdfAvcydFYp4mFCJ1sVoyCHVWtPsQMEZz+/LFr3NI/fDbH9h1LX5ZcN6jjKaxJU1VEPwMCD/K+8CczZjBR6ZJFNZaG4ypsFoGysLH1/ISWSMAei28qqKQRIyU5PQdJs/D05HTMJOiksPPLxACh92Ow+Egg9+qwFiD0YbFLWgNXSOKZLc4aQ+crGOVMpxPIx8fTrSXV7z+5juaqsyBE5G6qrB2T4iKpt3hneN0fGLNQJtOI9M0MfRnSIJXfjqemceB3a7jq69e5mguhYoLfYaVaV1QljVlIcZU5xZ8QtjbKWcL2ophOjIPI6TIbleRVMk8eSprqKqalIJ4EFPaDvo1PkpM1UIlrbJyXem0DTmVkow0bQ1ogdGVZUFhDS672NXscmx7lNbYGPrzSbQyXkgNMt8IVLbGEnMyjxZ+fN9nca680MN4JqW4rc3XROW2rbFGAWJUFX+npBrv93t2u5aHhzthcC8CS1NG07Y1kcixHzCFEdplkopdFO0yClBKUp5XP97G2gaGXIWHmDKsDtAq/1wcVVVtbfMKx9tCBjKBQCs5IFYl+tX1NcMwctE1WbbiqZs9VQY1mqKgKCw2L0uMrVBRQkFUJnXI15no+5EYHW1XEIITDSIiD0g531J4k4HgBnEXzFOeV6lslzIbc80WRf69Xj4PbURQag1lJVXXvDis0jnwRMisISaG8wmtBPudfEBlCkMCdEroJPwyKTCidFlJE9HEpCiMRWe80+tX3/w6hxQITE2pRFtbDImQZGMXM/d3nlxe0/rcQgWKsqKsc/ln8hdrjPyOGDEaKgtWywYqJo33lnH2jLOXVN18ekfnSN5BcOx2LfuLK7FIzA6Mws2RMhaUZd7m6ER/7pn6geA8IUVsUTHMifvHI1Wz46/+/j9hsxF16c90XU3d7mm6A9pUoITdvgSHT4EUI+EoM7AQItqWjOPE8f4jF/sd33zzDWXmrUOuJqPGljvqVWSa0mb3qdq9MJl8QinD2E+cH+9pSkN7aHDLRIiGeXEURnE47NBGyXwwZ6m5RVrEtQQfpnEbQPsQMHnDRkoYY8RQXZaZjS3Dzv1ux65rBPGbnezP1haZIwJbxebcgs9ygiVbLsTuoTifT0JEmCesscJlL23O4bObUbXt2k0TpLUcoGtw6Ol05MWLF5z7M5eXl9w93LGEBRd8Tha2tG3D4j1RQZM3xn0/5pvdoFXaDN7zPG03/9aWhmesTVhktjcME23TbBXnWnHpbfi8YoXTRp4AoXiGEDifTtRVye9+8w11LVFvpEgMnmgDJPHCkdZLha36eI4ulwr5eDpTV2WOp5d51IqI0fnPDWEhzILsjikQlhnQuKSyYt8zLwsgl7dKEoZqtNkouUZrFJroE0RIBtkypkQgMU4Dp/MTttC44Jnmma7aCxYoo466phWTfhCSyTyOmVtVkILEwVsU0XkOh1+p3bMqYXCgAsvsMnVTy0vsHM4FxmFijSfVtqIwMohUxtJ0LUVVkkIQi4i1pLDgloFCF4QIPigm55iXiRBFWbvMA35xxHlGpcB+39K2t1uLMs2O6CMxzhJUqjVulFtlyihaufngNA7MoWd/ecMPf/O3xJSY5h69BJqqxDYtze4SW9Q4l0huZjifcG7GB6kWx75nnhwuJKbZ4f2R/W7Hd99+I0kpZYnWihW1YI3M6uqqoLAyuxC3JbiUcKPLrKSRx4c7Cgv7zqJyyW+LEoMi6ZK66dE5Z1OU7yLgNNbmVlb+0FW7slYMayCnyUbiw+FA04kf7ng8btsykLy+x8dHtNYcDgceHh5IIVKXlcygypJ+6LfsPS1lnLxAJLyTgMykn0Mg1hRpYyy73Z6npycA9vs959NJtk55xnI8nejajnfvfkFrOJ3OOeKp4txPDNPCMI4opbi+viYEOA/DdtisZANrE3XbZEHqstlYVt7WKhYOCch5kAkP08SUE5OLoqCqqu33r7IOIXk8G+OtlVaobTvcMvP17YFdKRyzuqmoqgKrE/iZZAVlFLSo1sM0MS+jbO5i2JTsy+x5fJJniyTBJNawtZta6+zGmCE4xuksVplc3aTAphyPi8sZmYKtkXg4k8XTBT54vBtyCnEhguzRS9upEvPiUMZycXlN0zZM88zBXm1VJlGq+aIo6LqOeV7kOUgJZSvaZgcEogpimjb/80fPv+mQCs6j6ypzn2RrE3xkGGXNnhAciSBQJZHE2opW6628l9gmwDvm4QlILC4wTLJOdQ6iTpRFTRx6hv6Id46qLLm4vqRpBUYXgrjcVfAE5yF6okdsH4vMOXzwaG2JUTPOC/3k+Orb7zlc3ciKepJDp7CW/f6Ssqio6pa2bRiGkeP5iXkaZI7kZDAYYsogPmkbq7rh5nBgt+tomhqtjIgM1+y2osCaEoMW3HFMGFPgomNaZkzVMLvAx1/eUFrF9aHFGJmFGVuJpAlIWNwyUlcVpdHUhaXPeXJVVTEMQ9bMSJXigiMhuhWReEg+nsqspGHsadqay4sLIDKcRRcDbEZxt8yU1lAYDVHTtDWTXzg/PrIscx4akyGFUeYOglQg5cOyKuus5Qos04K2ZjPrztNE17RUZbUdplVd8/j0hCkK8YB6T9s0vH33xG5/YJlkpqe0YZkFdNd1LT74XLmCcwvWakiBEKRtj3Glblq8EutN2jA5kagSZVlhjPzM5nmhUJp5FiJoXbd5DpPZTF9YtBJJIttUDjkwhqv9jlIrIQloSeoWAbOo00VLF0nZvByDJMLIwRcYRzFL98OZr7+5FSNwfnaSer5QUswpOEbaXa1TFvxCch6VRG83jDLvIiOHilJGWEolEhKmm/xCIlF1e6r6krhLW5vovUd7R11Zdu2ecRrFpys/bpG8LC6TR8us03Mcnx6o2wvqpiY6Rwxysdl/w8nzb5QgWMZZYGshGYZ+wHlpKTAlhZE4aJ0FkdbKFsUWOVAyOM5PDxAWbGEYFgkriEHCDrUtqNuOi4uKN//t/6JumgzUK+laYToHH3l6esqKWc08DVTWUHeNSABcpmUmGINiXgIow+vvfs/XuR1YvEcZRVfUaKPRRlG1DW27Q6G5v3/g6emBaTgTvcgk5KAwDKOs/7u25fLiQFlauqaVyKAYcMuI0oaq6kAbrDbUVS0vVpR5wOzkJfO65uOHO/ALLy4b6lKSjJU2FIUceF8K5vCeYbS8fHnL5cUvnM4y81mrps1nltuC1SC6LG5rT7z3VFVFVVc8PT2igMvDBYU2jONA2zbEGLm4uOB0fNo2c5eXF6wn5jhNpEzGfIaqqW3gnf8BAEVVElzAGisYX+8YpimzzuUQWh373nt2xV4Ek07My8uyUJQFIUaaskQlCessy5LTaUCdeyFqZo2bWxaRvxRi9SGJQHMVYkqWo1T+xki4gQ8iEpXhuUgzjJaNWcqi1y8rp+3lsRlvosBmxX5YFr773ff88fe/o6sM8zzJz9BI9HhZGjSBuT9S1BVGlYSsZdsMyyis0Rwfj0Ciazthz2uFLUsSlqSFsZ9Sjn1rGoqywPtB5n6Qh9Ry8E2LQ1uTHQ0Kopclh19kGz336BSIIeZnp8pzY4VRlrpuJAVqmdl1HY+PTxv4Ta2C0qqmqmqc9wTvMVozTxPD4Lh5cQNhIaawYXN+lUPq6XSmKCx9P8vKUxcScmCNDAKNlpM5xQx4F2zEOA6MzkEMkFWxx3FknD2kgJ9mfvvDD5iqYnbglxGjcqzRyxdEJz6+h4dHQoiQYLfr0MZy++IFwc2cn45ihQjwdFp47Acubl/y+tuvqJuGcZyYvcdmmURZlVgj9AVjZHvz6cN7zidxeke3CBQMhTalsKnGkavLC26uL6kKy+GwQ2kotMLPEsluCkvXXWBsJSRM7zmeT3m9L2gQbTQPD3cs88j1YUddluCjCN60xmTqYfqCXTSPAykutE1JVVcYK/6wKXurQDYoU25tq6LC6iAbljwol9ndTN/3tG1DUZTM00SffZCqbRkGaZMFbCar61XKUFYVwzg8l/jrLzkTt7U8WT2ujai6ldLUZcUwnBmmCVtYjqcj11fXeO+5urqS6s+57VCeltX2Ip49lROnD/s95+MTXdehFMyLIJRlc+TpMzM/bDM4RVXVLMvCfr+XashoZrdQ6Xqbb5kox0ORL7IQxSFQVRXjOFLX9V+0fTLnKrCF3XxtVlsqY6iU53j/jv1Xr3j96gXzNDM7h7JaDr4gxl9bijVIZ06amHVF56Qw3D3+V+qqykp8qfS0KfI7pHIghN4G8qBIqSKaxOIF760LmUP5hCyCjEUrSFFGCSvJgxRzFJ20dckvckE7n1OH1MakquqKx4d72ZaGlAW2OmsZi+2wXWYhJsyjY5lnDGLVQrHJbP7dD6nHR2FP7w6XWT2+9rRiJ9E6R1zVLc4vYilZ5u3hW+YsR5gnfAo0dUmpIqfTAx/+5f9if33N7evvub/vaXZ7irJmPPeblqcsSy66HVUmMBDh6fE+hy3MPDyd8ElzuHnBD9/+lrKuKazoQZq6QIgdiV1ds9vtN8vD/f1nplHy7cZxJMQggkFbMEwTwY00dc3N9QVVWdA0tbCpY0RjZGmgYH9xEOZV0Yg503u0kVmYMgVlZTgen5iHJ64vdxxubmkz5P94fBL9ii0xRS1BqkiuX3JOWPBNTUjSLlS16KLSF8C9CAQnD4TWgofVeMoit3nGSCvjpRUubS1MKaX/4kUEaTe1FlGhUlpefpSA2awlpFxdRiGgGmNYgohG18/D2pKu6XBelNrT4yyhGwlCgn4YqcsC0UBJ25CyPEO4VgXDMFIWsrFNQfjz0zRjraXbtfT9Ga2fv/41R6+upIX0Tj6ftRLq9jtcDNlnZgh5bjM7J7l9CuqyZrFuMxSv5vbdrqMozMZBKzK2R6kcABE8r19e8/rFNVYl+rPQR60t6bpOuEtaMcwi2TBZqyRYYdnCKSVV1DgFHs8933/1UkJDi0KQQ0aj9IoiVtkgXolNSGusbUhoJteDMtRVR4yBJYdOSFtegJdFl8vvlveeqBJL8JRa4TJeRw77Ge+lqgrBs9/t+PGnP7PMsywwCkmbcW7hfGbzCmpbsL+8ZgkPxJAoqwKVzcaiD/sVDqmLqxts0QiMq22khQOxhtQNTVsLJWA4MfQCw4PENC0ZJRKpyoqbm2vK0hDchPILu69eoWJgmByfPr7j+uaKY3BM40BZFDIj2R0o2xZjxG39dDwznE88nU7cPTxRFA2vvvsNze4gvHTn8NGjQsJEuLzYo7SU5YrE+XwSLK8TcN4av9V2F4BiGHv684ld21B3jaA4ri62akQnttvDaCttjUoEtQL5PNN0JmlLUiV3nx+5//yeF9cd37y6pCktXdtkhrWm3e9lll5UFE3HME4M5xNdaVFENAptS7xb9VBeZA+5ipWwVb9dCM9dl6aqK0H8KkVZVsxPj8yzpyoiMQRsU24RTkUhBMZ5Et4XkEWUEuRQNw3jMqO1En2RkeBM1DNSlwTKGNqmyzIOwzAO0n5k+YRUSwvTOHA47Dns95l2kCmjhaWshFFldhKblFgrGLNVg6t4eD1QVJ6Pgazxq1K2idM0UTc1bdsyTBOzc4zjnFXZmoh4RpfFUdf2L/L3RLvlWZZ5kySsmz0tQPtM/fQcLvd0lwcO+x1NrlZtYbFlg06Jfug5nQYuDnvcODBPIyhF09YYa8QonhRv3x0Z+562Eb1blWQ+ZCo2AWdMIbsSckJOWeTWtUJpR1kl4VIFh3eOXdvmjYvBkZlXabX4CD0EJM7LWLcJgbU2WCO4m+AX2qZhHEeOp3sZadhsYQoKcJmqYfJFU2HUk7gAdMniJpHkfGHZ+Xc9pMpSgHIGCSMsmoa6qkm5TDydnhjHIW8KJMdu3aB0XScthrWi+lZQVReUVS23Wko0CpZ+4vH+iaJqeXH5UgbtX3CEjk9Hzn3P3d0dx+NAu7vgt3/8O4qq3jZMLlddWksEdFNKio33E8ene4Zx2aB84zhm2kCJKTTH0xliYL9vuLq4obDSsrR1i8msJGMMZS7PlVI0zQ5lDYt3KK0Z+iPjtKCMZRhm7j+/w6bE919fc9gJ7kZrRSLxdDpzOo/oouby+hZljAzUDXz71UviNGd/4gzaUDcLEgtmJUwzv6RKKQpr6aMor4tCbzdzkdvuteUjiVfPZNPnqq3q+56iKJi27ZakzZAf3xCCtKtaUxYlKQqVwpqCvhfJgcrnlDElh5xKU5SWD5/eizWmbCjXtilbM56enujadjNLl4XMDbUxks9YlVmakFlVpVSRXdfStS3BP8+JDocD07JArhyttRKNHiPjONG0C4fDBceTCHcXN8rBk09X5xYhZ6i/xAVrbTbv3kqfCFmUXFhDXVV89fKFiJqNxdYt++sXqIyZtqVcSA7Lbdly6Crc9ETVys+w0AbvvBzGKfHh0x1d16LV82Z2mid02VAU5BmatOHOB8JmR/Jkl6aYkPPhPYwjTYYRpmxbk02eeEcjRV52yGwuZL3j89wxCv89CGJ6DXFtd92mJxPnSZJRkDXZgiaEjKKqqXWJKeKm3fpVDqm6MNSVtBHGFpiiwLmZcZrwzuPmgeAdIcg3sCxy6u4Oe7HGeCerWFtQVBURxeA8ZbmjLEucW2jLPbvrF2gSflkkMj2v5udx4Dwu9OOMthXf/+FPdLsDwzhwPIpp12otAso1LDGJMfXp+EDfC+5lyirnECNl3YIy3H3+hHczr25vuLi4RitpXY0Rh39IkWUQ1EpdVWgt1p0EuLgQRsm4Dz5vnnzk0/sPxOi4vdqxq0UoqbXFVGL3aeqKEDVJNyilKQsxAtsq2zpUIhmb058Nv7z7yL/89DNjbnd0TtiRnLV5m2nIQyMv2opwadsWo8Rbtd+1nM/ygFtjsjJ7NSZLAslqq1k5Q0UpRuwYI1WRo8cQEShKs+RBaMoPoAxSS4rCcDyfhGqqBOavsnQipSS38rRwd/9AXdf0vQAGAQqtcVFikQ6Hvfg9Zwkw9bnl0kphSptpC57bqxcopTgej1izMqDEbiMyGUfVWJq64tjLHDGkuNE9VnV5YQxYgwsB5xYEoVtt87ovTcdKJYwt+f7br7k67EkxMs8z87ggH5N8vUVRsYRIU7XEMGf4n6QVxSCxd8pGlt5zfxx4+eKWsq5lqWSeMTFNPlCNNdRNS1FWTMucCRualPnnOiW8Fy3bOI3s941sX2PApLSF1KYUEFZ/zLpGGRxZu865It5PzPMklXlVopVlmR37Qw4jVWxC3XmeZNljC/GXJmGntZ2manYsY//rSRDKUmKwvZ8IY880TYBk6clwNdD3PSlB29ZcXOxEVexFQtC0LdZo7u7u2O0P1G1H3XRYWxAyRkQRGceBZRqY+gHnZoZ+4u7ujoTi8uY1v/vuFS7PHvqMgbi8vKQqCy72e+q6RBFw88j5fGScJpyXHLB+GGWOYEt0tJxOZ8IycNHVXF69lEPUFJv4bhWrKTQ6JqzNhwmBaVgkyyyKyz5pzclF7u+PuHnmxXXH1cUtRsscRgbiO9n0kJiCwtYdNxclRichQzgPWFKC01PP7DznYeLjpzuGfqAqK6rKCSyNlAfTonYej8fNCCvIZDGvnvsRWxTsu5baCNN75Z6HKFlrK0547M/E7MtauUlVVUmM1jhK+EFWTBdFQVHXotpeWz0U2hjaqqDJQ+VPnz9nREvNfn/gfD6LIdtJi+VC5PHpyKu65unpyGG/37aJwQceHx+4ur5mv+s4HU9y42vFNM10jbSOu13H6XTifDxye3W9VSQK8/8XNhCcBDaM8yLbv+xZbOomz1NkblKVJSr4bSTgvdn8e1+CBkOIOB8YpgGlrjFGBuQyj51pmhaV1fjL4mirAkXMiTUrwiZIJQJMS2CcF25vrimKGvH2FRvHHgRtU9iKuu1IKOos14gqbPailWw7jQPD2NN13/zF5lWhJRdPmWzQVihTYgqx3UQn44TVdSAYIBmUb/agzXIkoQ8kMi8ugi2ZZpGGRCewyKa9QduSoqx+nUNKZx7yNE2bkTX4sD3wbbfj9evX7HY7Hh7uAQFw1U0D2VullOHFq69o2k50VkHUs34e8PPAcDwyTgPBB879wMPjE0YX3Lz8isurazEmD2dikkOzbQR0X5aCoLi8umAce46PD5zPT5JeozQhijPflh2guL+/Zx4HXl4duLy+lgegrtDW4hdPXGbqsuBwsWMZTgznJ7QpaJodWifGWXRhhTUYCvpp4d37z/TnkZc3B65fXW6YGW0r6qqW+YQRVKs2Fg2kMDONJ3yYcYujKGpi8ixOcgc/3d1zPPW0bcvtrpXQxpyZZrTdzLJFWdLUNSFjbq0VGFm323EaBvq+py4sZEzw4XDgdDoxzzNLWeaXTyQM6892XdmLJys8bxHzi7zb70gozik8b/wSWKW47BqsUnx6fBQxLUq8k9leovK2yRiTU68jj4+PXF5eioxAS/pxVZXc3d3j3UJpG2xh6EcPQfREMUWstpuK/vHxSFKK66srTueTVJkjm6dxGAb2+72geqyMMGbvsZhsprWopDbrk1V2a/nW2Rc8Sy62lBVELiG8eJUvDo8xMmw2US7fqiyxOolrQqVtUxhJYhpWJaep53B1wX6/hxQpSJu3zmSpgiz/IfrAkmUcgGwCs4fUWrG4nI4P+WIwBGTREbS02vK9GMpKCAwJRVm12KoiACHlC1hpEjKH1Lagrhux2Ri5UGXBQpZSyGhgcTPkvEFtI4XRjPOIXxzT7H6dQ+qXX96wcshTEu8SCXb7CxlMK5jGgYf7T3Tdnjq3HvKDiDyeH6jKgrIsiMuELcWUukwj/XBkOA2M48w4LTyde8qy4tsffk9d1UzzxP3DPaawVE1L03Q0dcdut9sgdSkFhv7M57tPzNPIsoiY0/sgnidruLu7J0XH1aGje7WjtJq6bLClzCWcjyQUVV3TFIaqsPSLmGmrjM0dxwUXoagsp2Hi4fHM+w8feXF9w3/443cYJekpRS3IirJpc9ZZLqFTIvgF5yeW8YTWCucTEbECiRH3xPtPd9R1xeXlAaMT2lhizIjbsiIp2b5prcX0jbyMVblaHeQAO+w6/OJIPhHw9P7M4eKCruvwTpz7lxcX6LzSNsZsc5AVpbxWF24cWZxj13Uc9nuGcaIwGlsYvEukGKmNYdeU+LAwToOo77XiMgtEnVuoi0riqIxB57H40+OR/a6jrCqenk5Ms9hw5BKS2Y5sAaUFkVjvZ9Z3VVVUTc156CnrSnAnmmy2npncTBFDDv6UCkkbjXK5wCD/t0MkJoVROh+mtQz+vf9iHtZtcgRRfq9sKZm5rDMuuZQ0KiXmcRThqTuR3LjN4JLSoAqUsiQsP/70lsuLgzDd80G4HoJCD9XYbkcKjnmMGaks1V2KkqMXgpPhdIoMQ884Dttzo7RBK8QUrhRZaAMa6m6X2VQSk660IfmIMSXalNhCft9u1zIMU9aiiaUJRHJTFqXkYI4LyxIoTOLy8oAPNvsoLSH+SjqpoZ/Fua0SZWk47C9p6oplHhn6I6YoKKuKfXXI7vxlI0OuJbl8bgEVE9P5zDSPWWLgOZ5HptlR1g3f//ACa+SHdDqf0Nqwv7igrJstWqipO5qm3Ura+8+f6c8nUcmmyDQv2b9neHp8QqXIzeWerhEedFmajcWzVgL7fScGZjfm4ISFZn9BP4w8Tp5EpGxaYgr8t3/6kY8f7nj14pI//OYbbi/3OXPOYquKotmj8kzHFoXoQ5wjLBPBTYRlQpywBdpaUe8vIz///JanxxOvXr+mrgr5M6uKpu2YZ4ctC9puhy0rfDgK5VQpqlICTvu+J+YB5zRN7Hc7+tOZBFv7fTqd2O0OeHfOB1XPfrdjScIuX2kB64OntQxY+0F0Unq/F0xy9s+1TcOErK3XWVQ/zpvfrKkbmqqiP5/RCqko8u9XZbkdrkpJZbVWc2tFd9jvqaqCGAJ1lbE048Bht9tmZzHP5FbLi3diFG/bhv1+z7tPH0XIm+0+07wwLyKLkbYvexu1ghTkZUYsL3VVscwzdSWm5jEvFlISPppSZHaaVCgZUikyjaSYp0lCQbK3LmUaagyBkOmbxhqOp4FPnz7z29/+FqEgRIrSZimA6MVUnFmmxNOD4H4W70jpJW1dE7KfMnpJkdYpYpDodNm4GUxRZB2jtK5uWajqThLIoxi0JVfAbpxzk6v/slL5PdlxPB5BCYOKLIaVqLQWU5XsbMHQL2glynry51JWNbv91a9zSJ37E1VtuTzsSCEwnZ+Ye2h3Oy6vrijKOlsyAsmJsnmlGK5l8TSOEjU0ziyLRFvffX7A+8jh6pLD1bUYV5cZioKirOjqbtNGrdsVWQUHPt99pD+fOT+JfSZE0ScZY0lo7u4eSCnw+tUtN5d7ykLmLyr7zKKsreQlryrqqpR/VtZM48TpdGIJgk4xRYlC8+n+yKePd6jk+bu/+S2X+5a2KsRpbzRJKaIyQvxEMt1kxjUTlgm/zFKxWEtKlqg0iwt8/PzAn3/8ibIs+ea7b6nLgqQSbbunbQRx3I+S9KuMYV5kJqa0VGdtK/ODvu83j1nXdYTjWTQ5KW3bQBcCfS9s9ck5gepneNk0ieZoTfmBvNkr7DbraZtG4tnnmcIWdHWDVUYEq0WJ0QWLG3NL4rm6fbF5DVWSQ6osyo0qIGiWFmsLhrHf2rOieBYFr44CW1imSfR355NUhVVVwReJ2SudVOZzFe2upXgqOfc9de2JMWwgRefiNhCPIVA3VcbuBIpCWFV1ZZlnmMaRsq62y3cNZh3mmX6caLs97e5SeGOZjSWbwUWsIUGU3oqcUp0BgboQucjnz/eUZcG+60RgmRXd62chF73KsLmKqi5pkCo6RiHejmOfW02drWgFtiipmhzQmxOWUlabk9/N2h5QgNFyqK4diibDEPM8LnhPUze8//ABXViZt2ZWe3ReItttwc1hR9dOnE9HuVAuX+ESLE48ur/KIXV7e6AsFdN4wmhL03bUjWwfxmlhmoS+VxSWZMR8rBLbUPV87pmmgRQjx9OJX969w5qC2xcvuLm+YXEz4ygrYdtUlJWsq5WWw6ksCspKEBrD0HM+nfEhMPS9IE2UFqGaKri/v0OlwMuXL7i82FEWq9FXBGwKYS45v2CLkl0OryQFlmnk1A+cB5mNLC5Q1Q3nPvDxwwcKk/j6pWhhqjzATjGBLohGg7GYqsWWlWwJUwQ/M5+PeDehMww/EolojueeP//4M8M48uLmhq7bYYwWJ35e+Ye8QidBTHDOnCYJt5SfT0iIf68oxJs4z4IGnhfmDJoTXE7+7w0DZrejrmrmWcihRW7ByVYHCcZccoWiuTwcRPPmA8f5SEI48U1ZodGQt3FrVFQMkku473YsuYUEUFpRVeV2+czzLKLg/M9TSpSZiQVkYewzJsVozRIjPgSOxyPLsnB9fc3T8SyHtAuQtVz9MHBR7kUpnemrzrns/IemrhmGUTx26tlStFaT4rmTtfqyeNKUcEY2yN4Hiqpk8ZH7pzNBW5rugtIWGKMoSqn8Uy8px26Z0ClitdpEjZq0LTN+efeR2+srghfpSdOUubUVzaEcsi0XVzdoWzANQk8om5YYBD4nYlOPNiVKGVwEUxTUTSNiVy9AwuA8gYilQClPYcCWJdM0MJ4eoNtT1Q0x+ucDGRmMl8XqbkBsAUmYU9iCsmlo2o6u7XBOFP3n05ndxS0hJKypN+Pzv/shFb2j3rW55WpJSTGOQ15LCtpXbkWpdedpJgSfnd2yfXh4fORf/+VfMcbw+9/9jouLA8u80PdHmQVVlbDCrSRgVGVN1VTbrXQ6HSUqK8hg+XiS9q4qK1KC+7s7iJFvvr7l4iC4VWMlqXWYF2J01E1LXTWEEGi6hv2+w+rEMjhOT488PJ0wRqD9SWuSgx9/fEfwka9fX/DyuqPJt3tZVnjn5WWsanRRY02V5dOO5BaWcaA/P6GVoqhrMeAmhQvwy4cP/Ouff2K/3/Pdt9+hEEV317WUZZVBbYnFzSKJ0AZrRx4ej6ypJjGzzUNet68PY9/3WQxbMU2liBG1fN0rIO7p6YlXr15hC7Nl52krOqCiKHFejNhVVZPwGGuxRcEwSjtW1TWsnsGYmJXObUmRv/4TpS2pypL+8SnjiaXNSykKC18Zihw/Zawwvodposo+Qpd9YCmFrMeJG7JWpCGjCIWrim34P874JC/r7BeGYcRqUdyHGFly5ZSi2JEKIxyttqk2Aec8z5swdhhG2mZHNDL3U5k0oIwlRFFvF2ULqsQHiY83mT5Kitis8dJaYzBIzFQiJhFReh+YJ8fdwwN//P0PEqGePItOQtMsC7wTg7stKySWRWZMAh20G0I6pawiz1ji4/mct5s2bxEj5OosRZlHqehJYRExbVywJhDcmSkJFdYWdiPvohKFFV2dXxaKSkQRGvD5MC0ySaGuG5qm5fTwwOn0hC1bykKqtV/lkLq4uKbrdmIUjbKevLl5kTcdIiILwbO4RSTzuWQPMXA69bx7957gF/74xz9yeXnJPEmCsVLy0pR1kyuxkrJpaZoWrQ0+eD59+iREwNnjvWMYRrzzlHWNUYbz8UgIjpcvLrm82FFYEdkpFD5KdJLSJrcUYkc47HcUhWKeTjyejsyTQP2VrbBly+ID79+/4/T4yOV+zzff3dJWBqsM3kn0d2lr7u7eZ/2PlVQNA4YgEe7LBDFQWVnzEhUxKT4/PPHj23eM08TXX3+dFwAVZVHJ963AGs35fGacBrquzQp+GPqJGGS9rrQorJdl3kSZ6BxZBIyDDGubUmYqa+qLz7OZoe85nc/5RSiZ55n9fr+JOZWSmKdxnjeS55fqbpVNwmNGmxgj8V8xKWxRZQFosbVfa9sfgyeohBZpj3i6yOpnLUz0FbGj8trcubDp6SCHMWTJgzaWcV7yny0zUD/NLM5hXcE4Tvj4HOTgt3bS4L0ErYbwZSrxX6YWhyABHW27E/FyFi6yhhGQ6QOmIiqDMgVV22ELy/npEWNLrJZtb5gdPi5ycQM+p9QcTz2Lc1xfXHDY7eRSyuONZVlwPgopQVsWH2kKg60spqywpiAwo41C+QzlQ+EiDONIVYoYdhVckiRBBmNIMbDME0U5oY20jRBw84QOYtshBWJ0kAI2V/khBGl/q5oQHKYQxbubJtFq5TGPLUvabkdhDJdXl4DFz7+Sdy9G8D6K7iPnwxuzRtkIGGtZZokvV4oY4eOnz3z4dMfF4Yq/+dPf0taiTp7naUu5UOR1rtZ0bUPdNKIwX0bmxTM7zzgKQXFZJE68aRpC4UWDEzyvrq/ouhpTKqpCRGrOBXyUrLembaVltJaqEKvJMj7SP81C6/QBW7RUpWEJ8P7jE/d3nzjsS/70x+9pCo3RlhAElG+LGl11LElxcfUCo6UCUNGxPJ1xc7/RD3UGQIWkOZ1G3n74xOfHRy6uLvnmm2/zZym4mMKW+YH0TFl79uLFS4zVeOf59PGOn9++43gaRClfWAiBmBTJ+XyTsg1Jp0nScqMLWGPw+YBZh+LWWkkyNobdbsf5dMJkrE7wQgdo23ajUkLmWGWKwCpZGIaBppGMvUQEFaXtT0h8OBLKoPOhI0JSYWuVVXYVxIhfFqZhwCjxCYY8FF/RLyDthtYiQVHGEIPgSPphwBYW70LebhqKQskKXBvcNIva2pqN6GCy+l8OJrONG9bwir4f5c/RNh94TmCB8yyDYqu3bZ6PCefFimKMzXA/h7KFbMzcjI2wTBCCBNgm9Hq88fHzA1eHA69fvURn3I/WlimHyKI0dd1S1w0xKmwhxEzxay6E6FmcY85+2aKsUbpgnCbqutyU8iu5QWU5w7rY8m4mxJAlDBrQBDcTEXuQzynZ2lj2hwNaqewTFZ3eomemcczRdk9U3ksEPBpjhSwaQ0TpuMVq/bsfUirf0ot3dF0nqRR+YeiPTOMgZb7WOBf4+Okzd/ePvPrqG/7xf/3PlGXFeH7i4eE+O/0VxojNveukXCzLEm1kOzVNE30v/KVpiXnVLokaZVny6eNnlnnk1atburbGqpDV7BbnPP0kN2pZVRj0VgUE75jjzJzbFRk8G5StWYLi/vGJz3f3VEbxh9+8pGszWTFGlhgpypq6PVDWrahmVcIURd4MwdCfUTFztbXEDM0BgjJ8+Hzkn/7pX6jbit/89reUpbzEEvp4oMiET6UU4zRRZLiaNgYfAmM/8e79R3568wvTPGOMzI3CajI2RkCBUV7kzHFkHCdCDPImKTY+9aomn6aJcZrY7Xby+S0LhS2YxommaDau9V9WFrn1yjOOaRbl9r7bydDdew5tK+bmrBmClCUNnsV72lbSe1IUDZ3JX8uyzBSFIKVXqJzLRAJrrUScqYwDqiqGcRb9jha1dch43EgSnnxKgqa2VpAxzlOWEUrxMk45ExHYIs3atgUU4yTJQVVVCb01BEISdvg6u1sXEn5jtxcyW4sRlaCtG2IITG7Bz6NU1MoSk4KUKG3BqZ/45d0Hfvv9d9JeTiMpQaUNs1uIQNfustKfHBlmcLNIfGxhURRM66FjDaaoSElx7s/ZL2mJUaidalWSB3lOKpMxNmm9SDQeidxyLoIyOC/gPAWUVUVVVZzOZ16B2OAK+Vkp4Onhjs47bNGilKLrdjzcf2BeZspKrVzMf/9DCpDI8NKiVOJ0fGAeziRCxnoE3vzyloenEy9evuL/9r/9PzBG5hf3d/ckv7Db5bTi5AXur3SmGtZM08L9/QPzIobk03mUpNm6yxCtwC+//EJhNbfX19T1DSl5mmrdSi083T2SlKyYVZI5hc2CR2KiPz+xLCM+OJTOqSPK8Hgc+fDhMyoFvn55yc1lg8ITlgVjS3YXN+iiwhRykFojmyDhY0cJjEhRbuZC/plbJgKWJSnefHjg7c+/8PW333J9LWJCrTWXF9c0bZdb5ucstK7rMEZTljZTKOH+6cj7T3eczz0gA+lVaFiWJW5x2fgrB3TIg+UYZAEgaI2wQcnWiPUhiz27tqUqS9wXeiBrJch1jRkHtg3rPM/0wyCokGwnCXVWro8jbdvSNDXnsWecxFIhMxrN4heMEXV/iMJQX5ZFbEUpUZcVMfjcspPbNLVdZmSzcaUlTUbl50++zrVdS/gQmWepfkwhaJWwxK1iWoNIv0TFnM9nkRwsDmUNs3OEFKnKGmsN8zKzpqusv7aDNn82hZWoNLMa2k+PDOdjlnKY5woRiY/qB8fx4Yndf/hrzv2J8+lR4qrqatPYaS0YlGHoqWuZhxW2EBy1tizTRIgK0GhdoE1BCDBNE9eXF1v7rrVGGy3zuTH8hR9Rnj/x7IUQSSEy5YM6pedIelPKn/v57o7vvv+e4B3QbAuHGIS8oJShrHcUreHhHpHJlBUpRP5nf/2bDqndrkGrxHB6kLIuyO186kc+fX6knzyvXr3ij//h73KJLvHRi3Psu462vkTrxOI8VR7oGjTzPPPw8D7bVyReapwk9rpuxMD4+dNHiqLg1esXXOw7dIqUlWxQvHNMU4AkuWDWrOCyzPuJIXOUzqLgLWtMUaFMwdNp5v3HD3jn+OblNS9f7NBIekhSJd2hpazFvmNswTjNxKgISgan4zRCSBRaVrOkSDCyOFC24ek48PO7z0DiT3/9W2wh1ei+23FxcYk1lpBgmR3TNEqEdlZ/20Jy/mIIPD4d+XR3Tz9OTNm0vbbJIPMT2USK1SWmhA+BeREhJtkMm2NxBV/SNLI1y3Ol4/HI7c2NoHyRF/10PnNT32wP35pJZ4yEJqzDc6010zyJIDa3SufzmbquOQ5nGVwXhsIYUlUKDymbgHVKxCRmdIWQKuqsBFc5y28jLCA6LucWog+b3y6ldQ6DzK9yUEiRWyLJnGuwXr63ZVk4Ho90GaFsrc3UB7kknimTSVotEPhhkACLaZxym1huVhMfAm1TE/2CMhE/ykhjDh63DPkQM7Iti4lkhR0WAjw+iq+0KossIRAN3TKNUgFrk+0rCh/FEtbkra8A6iRowhY1PkRssfr9RGvWdp1UQfmgJ3vsYoyQcS1VZp2FKIC+6CMuzijlsFoR0LIkyM9o13VChF0P6i/meSChvWhDWXcUhTDSQvA01rL8WpVUf3xkJAkozAX6YeLT3SNl3fL1d7+jzQRBKe0hzh43zRwuL2jrCnIQw+VVLYKzEOjPZ06nI/MyEwKM88IwztTdAe88x6cnysLw/Xdfi0aEQGGhLivmeWYc5gzXz7ds3jCurcE89Tw9PIK2mKKSTZ8yjKPjlzcfOJ3O3Fwe+M3vv6LJn8Y0e8qqoWp3VPVebte+Z/GyipbNpt5EjkolkltQKaKtQRcVx37hp5/fc+57rq6u6LqGFANNs6fZ7SiswMeGaRLa6eIxGnYXu2xPEK9X8J7T04ngAtO88P7jZ4Zh2mYLK/JCLEsT3sthFENudcKzKFOG2wbrBN1RZVrlKiqcRuFpNU0j3AOtcDkxZq02vAsMg3DFtDGQwyBsYYm9fM1NLTfq8XjicHFFU9TMs6OqZXicTMTYMrenXlhEs2i1yIpyaw0ueIqyJIQE+O3GB4VfAkkJKr6q6syYEmX2SnIQ6oMgREL2erZNQ5+rz77vARFhWms2uUGMkdOp5+LiUrAzSok9xHtkgsq27VpTY7SSyzIsZ7QvmV0g4rC2YQkBaxRRgfMzwTmpjKJCFQUow8Ox5/b2CqJncRPJB3xc8MsIqgSrUNZStTW2qrC2xOfQh/3FhYhHdQJjcRGqQpYYPkws00zbNKSU56oIbQElJvlVdyi6sZqoLMEvTGoWPnlngcQwyuelc87ixeGSd+/fSaX7xeGXkijvgxKLzjKNmyZuHo7UVYNfwq9zSJ3OZ+q64+Fx5PP9A3XT8Ye/+XsuLi+ZpzlbUyKLX5jHgaZuuLm5oe1q6not0T1jLywo4UxJ+scwTozTQll1VPWe49MRrRVfffWCQ9egdMQace1H4Ol43obtCYUpClnxlyWFFUb1hw8fpXRFU7YVRbdjnhz3d4+8//CRy0PHf/qHv6KyCYWYJ421dIcr6rojYfJ6P/8wrWwvpmnciANFURLmSfxZ1uCT5c2bz7z7cEddWr777luskTagbhrKInuwMiRsXuQWq6uKw26HNhq/zEQ3Mw5nhmHIqI2B4+nENC7Pw0/WS/zZMLzOi/y6xVHgcvTUNM80ptqqFp1X0+u63XmJZp/GkW63A6QqWvHExlrQQrVc01rWCitFYV4N/bARN6dpRGn7FwnKqOd2UYFYTxTbhvDisIOYKIzFmZDnZqumKLcamVUU3JLDXaUtKcoKtBxIZVEwzcu2uEgpClMquxVCtn0454jxORUnZAb3Ms88nU7YSlqs4H2etcuwvygKdGEJiozjBTfPLOOZNJWMy0xIgf1BiUl5jVNLCmMriqKmKAuqZsfcez7eP/C7r68IIbedmdwgSxeNyQpwRUFVVsQkbH9xOATmacFalS1XnmQLsPK5Lk7EmyEB+f0RCYMsDuq6oalrlNYUZUtUGomWNNi6wsTIMk1IgrQWv16MNG1Dfz4TQ5RAFtjmo957VICyDES/EIM4Jc7HIz44UL9Su7eEgvtPJ8qy4q//w9/T7XcEH5inacN3jNNAYQ377kBd1wKmL0q8X5iGM/3jA09PT4Sotjim0SVM2dB0LU9PEk3+6uUNF4dOXnANWhcoFNO4YPJ2RmdB3TpQr2tBabz55S2n81mU0N2em5sXBGX49PmeX97+giLy13/4ltvLjrDk9GMrcD2tBJEaMQLCQ+ZaipwMkm/h1X4RY6SsG7yt+fTwyM8//8TpfOaH777i0LWEGOl2OxH8BU9SYgAexknyzazdWNk+RsIysAxPTOcj49CDViQl/PH+3DPNy6a8j9mGACE/cMLuWSPFYoqyGo8pb8TE4+Yy8uN0knRipTV108jQOXOS1u3dmuArB40WDx3CCF9tFUO2yqwRUNM0/QWjytqCEIPktSnxwokZOclsL0aWeZELIaltgJ+UIijJzfuyJbNNbuOnDJ7LgSBee8q6QqFYouQ8LrOn7cT3tyyOGIUQIZ+FlsNDyWJmxR8LAA4WvxCU8NKXxWGtkuoNJKvQNGJ9ScJmGoZRjLgKirKkMnIAkyJK5WF+UJRlgzIKU9aYoubh8S3DeKbrvsoiR1Gjl2VFWZVELD7E/D3MVJXIMFRMEr7pHIUGv8z05yPTMNJUDSpJ9Sz2NPk8tbWYsiQpjVaIQr7NmYrDAMaTViKC1s+6snlBa4u1UvmFPDcNGQtTrAQJ9ayQr2sx/UcvM2bnJQaNnIPwqxxSIRl++9vfb/oHN3uaVggH0QfEPlBQV3X2nEGhoD/eMQ1nHj/fE3xgnB2Liyw+gCkoqpKnLNC8ujhwebmnKu2WLpOiROoYo7FlhXMzZWklXLOQoIayLOnPZx4eHzDGcH19Q9Pu0Kbk08OR9x8+sswz3359y1cvLlApEpYFpQxN22KKMovr5DAyRYEppI1ao6TXnltAbxZFgrKkH2Z+/PEX3rz5hcuLHX/6q9+jokDbDpdXkqQxTpiyJPjE0PeZiGAYh566LmmqkvPDHefjR1SSdqCwcus9ngY+fxYagnwNatNMrevjus4AfLfkn48mBr29+EZbTGlQiS0GSxtDPw4476irmqqRLVQIkijSNA3n83nbBjrnKHJS77LMFBmYVpUlp/OZeRZyZX86cXl1Rdu23D8+YpB49DkP9uusJNdGhIzOeZbFyUETArtSFglt04hbXmvGVXyZWwmRN8j3EGMUPdK557oopbrOZAXZQEso5npQyTA+ATEHA4hHU9bxKl8ASvx12rKoiEqa6EO2QiOugpSXVPl9O/cjnx/OfP/6CmMM7a7Du4kUIXhJzFHaYLQgoNfD7/3Hj+ybmqZuSFEuk6qqMGXJ4j3VriNFLZfLOKGU+CZDGIl+wjsn6vdpImTPXoiBxTv6fhCTb158uMVjSFksmjZh9OHiEmvFlG3LkskJG673cjjFFNFFDjLJlI2maXHesSyTEHHzxTRntE1KYusKyUtEnRf80TyeQRf8z/76Nx1Sh8MFsFI1S/EixUjwLlsc9JbKqwicHx/4/PmjJPxqjfMwTAJ6101LbSr6nIt3eXFg19ZUpaXJmNeVJS0gNXkpy7Kg6xqM0VsUUn8+83j3SWJ2moaq7LBlw3EY+fO//DfmfuHV7YFvf/+SqlCQnKyQc9uRAB9iHkRHdvs9QLYYSHTTugmz1ubUWkM/LXx8/5l/+pcfCcHxx9//QNvUQgJodtk24bO1Q2xCwUfKwmaVsefy6sB4PvLh7XtSWFBJRLHGWNziOA8zn+6ORF1grWzwJJAzZYuL2R5Aa61gOJBqwAchLWrNxj7y0ZNSxGQuvcR/zQQfpOTPB9w8TeKYV+ITEw+dzAFFFBjph0Hom2sKyyreszbraWTAuswzZfmcavNcsajMapL/nzfym4CzsAUhJlJu7778PXXm1PsQWELAhUhIcOzPXF9ebQN3kng0RTIh/LB5koRiYSUhl2xMmbIgmqqYnRJppXEWVhTcUW0bPEHYqK3ymp3nw6d73N/8QN20uAjBh4z5FXmCsYVw6YPonqZ54fOnj3z/7VfUdc00DlSV3fBDo/PUpqC0IoxdP1vZssPSjyTvWSbPNI4QE13XSfhuTEzTiNYimF3Gnnk4yiEVyg3c50PAlDUq0zIrU1CUNVXdMmWpjskymFXfFDJIUbaNI4crtrmwKNllG5iSylowcX2s8Wpa/8/7Yv5tFIRh4LDfC4/ZGPEHacXFoWXXNUS/MJxPLP0Tx6cH/DIREgxL5DT0lNWOen+LR/Fw/4hSC7fXl5TFhSistRbmt3P0/TmHJYguZJk1VV2yIXBJnB8fOB2FV1QUNd1uR93umCbHv/z3f+Lz/QMvb6/4w199w6GrIAWCjyhliRnIE5xHRxmeFmVJqYRmKboZhcm99jpLkhsZPj0c+fHNB96//8jt9SXffPOS4KVS6HZ71tTfTSgXPKVVVLuW0TmGXgbtn9+/heghLugUiVGQqy5EHk4Dd/dHLl+8ppgX3v4ilehfRKV/YXQN3qPyDE1mNxKYsL1Q+RBY1+7rVm99+Pv+TJWJm6sRdYXfyYrayWraOwkxiGlLo1mV5EKTEEV3UZZURcE0zqRslj2dzuwy6HCaJbstJJdbeJ0PTxHGFkXBlEMl1lbSWpujmLLUwS1S8SgFWjNME2U/ZOqlwbmUU1Xy5VqWIofI7cZaHYu8Yg1TzR6+EGGFMRqDyrNAgf4VW1ujJH6F4ByPDyeUKvE+QVhQeZ2/omVKXaKEXEP0jvPjA8Ppgetvf58H2ZLSs876FudwS6DdV6QYqDKEUCmFX6TiLusWHyPTsuD8gsFTNQ3eOe7u79AZ+TLPA8pL9qGkxUj8WYzCwJLnRLbNxlYUtsIbR1Ahjw3iVjjEmOdy2nA+nTNyOGxzQ5UTZLQ17A4XKFMzjTPOR6ZpZH9R/zqH1O3NDZeHPbYQ+Lqshj0Gx/nhxDic+fjuHdZoMCZTJReSKmgPr6iaHXcPj0zTyGHfsGsrqkLRNiIMm7NtQ5TsMv9wznE6nrOwT8ILgl84HyWgsm0qmq5lf7jBJcVPP7/lxx9/oiktf/3bb7jctxiriNETk+hHyGAuawx13WK0hSz4XL+G9SUuihKzbtCUYRgWfv5wx48/vcW5ib/6ww/s25o1fLPZdQTnOR+PkLVJbdvStLI2H4aJcV6wxnKaz/kBT5J3llXALgTuH86c+pFvf/gtAc3905l5cSxe7BzPaF+1HUoga3J50VLWGgpnS7LfNH5JecYjjgCdv3etDed+wB4s8zTJKt05LM8H4mqFqTJapagr3OIorZTuxhgIEsduO0MKnraumJeFxU20Tcfp1HN77SkLgfK1bYNedK6MhSYaczWns0Qh5nnXGjF1Wk4ZephtGJn7RNQoLMMoxAGJdxcSa1VLmEIiEWLYpBdrBSgHybqMEEkD+XBZxZLR59V8SnleBipFymQhJqIKvP/wnmleKG3BPJzQhAy3E09bCAGb6ahuGvjlzU+osFAVBqJo34DcjiED7s34/MXPOchioikLicOaZ9wszglM3A6LcZip6xZiYB5n5uFE17bURp4LAd7VuSX1JKtIbpbqOsmGVyGV9TzPG5HCmkJGJXXN0A8bF11SoPtMdwgUVU1SgrzxXggJ0zxRTM9m83/XQ8oYj9GO5CZCUNR1xTg88fj0QH98EoUqimFJTH4kREXVXBKS4u7phHo607UVL766oa5L4ZGX5bYNMMbw+vXrPLgVBXHbtjJEtJYUPP3TPdM8sev2lFVNjImbV9/w49sP/H//z//GPJ744Ztbbm9Ek1VYgYSFpGl3wrnqTyeqosQWFQqZP8ToWcKyzXfW7VkIHp21LJ+ejvzrj2/4+OmOVy+u+c23P2BVHqTnrdE4DDjn8YtEgXddh8R5rVs5eRh9GDEqMrsJRaKqG0hwPg98vH+k3u356x/+QIiJh6cnHh4eeHx8lAc43/5rFbX++suqgK3SkopO5lIhzpB/Tl/671LeAi4+Jysbycoz1lCqcnuhj8fjFuaplVQR66Zv1U8JDDGnm2jDrus4HiXeSWvL8Xjk+vqalAe7dVUzLY6mWQM40yatqOuG8zA+m3ON2bZ7RVFQpUQ/TFknhZAYkMy3sjBZPU2uGtP2Pa/P3OZlA1CGiFAy0CbjfPSmKC8yuiRGUWo368GdeWQpaT7f3zMtM/tOlPFlRurIR5JpnYWYlsdp5PPdHS9f3FJlokJKYKx4ERMmh3asY4lVUGmIQTLxolkjtvKhm38Oa1U7TyOvbq857PfMbqEudKaIDBTeU1QNTX0puGPvMDHK85s/m+fKKW7Pm8ljhujCxqX3fkGpAmOqbNvJoQy6RFNji9VUrpiGkaL8lQ6ptAzgy4y9jbz//I7T8YjSmpCsZNQlcElTVXsIkfunI0rBzcWefVdjrFAv63zAeCe6lPXBH4Zhy39LSWwUMUhq8TxPnI9HpsWT7noWF+nPPaf/53/BhYWvb/f84ZtvqZsSbRQ+JHySNOCmrEXdHAJ101EVJVoJcF7SVQqiihuozxgjlg8XeTieePP+E+8+fqQpa/7hT39F1xSyKi+rrNOStf40ikAupsTl1aW8yEqRiIQoWqBpGFAE5mmQNreU9fDD3SOfH098+8MfuHlxS4qBYeh5uLvbKJXrC7W2aqvqWbja9vlByjTH4Dzkw2qaJkIS0afPG6mtTQOiEhd7RDxzPso8sG3bzRaz0iTbtmXeUkJiXoVLRt/FYcc0SoSUd46QElVZ4Zxn3wksrW1bqqrkeHyiuqlpW0mgTiEwTZMkm2hFaUrUKGbyopDHdW1R11/a6KwHU9kTty47sl4veFKSCuDLl04OJrIWSmxMYh1JMp9RSrZb+cLSRsSoqz5u/b0rpUEpxfFp4Oe3H7ncfYdbFkLmlq2HBkoRZVTG8Xjm7u6ef/j7P21fG0BlRAelTUlbddiqESmCqDrRuUJcFodBErYVihClSl6hhQDzPPHy9pps16PrOvG9Bsc8TqLdWgaqpqaqxdWx0SHy15SyHmyFCRa2ICa57Jq25XQ64f1CjJ6yLCiKcvPwLm5hZxTL7JjnhbpqGIcnnPuVdFJNU4m4cBhYFkF4uKQ5H8+MHoqyoWoabFKch5lpOPPVq1uqqqAqC/lrLY5tlw+nVUi2zklWJItSUhG8efOGh4cHQhBC4G534OXNBaNLvH33jo8Pd+wrze+/ecHFficbsRQJQWGKmrLe5ReiQiWBllVlsyITMcZQ1zYHLrAB5kniefvx54/89P4Ty+L4w+9+4PXtNSksmxhSGyM+q5iyTUYU3QrwznN9fZ2lAWLOJATOxye0TlR5eOt95MOHT7io+ft//E/CmyZth7I1BYWVOZzJ4QZfVhbO+TwfUVnzY7PFBlBiXvbeMzuJwzJKk4JsMFUSG8Wc5xsiQYiEHJAgSnafbUlSMa0vaZvtL03T4FOiyuGTEUXSmslJdVxojdYBHxzj2NPUNY+Pj9zc3FDXDafzmYuLC8rCMAaPn0WRrZGqwhgxjEtsPDlDEGHjL2JlUUZ8eyAVpFYqW2+kUlQ8U0ZjfP73FAqUHErKWNJqfLUGFTXKWOoiLwI0zxQH50k+oqzGBY9NljLPqP7881v+9q++o+12BDfhsq9QlkyBiBxsnz59YvELTVMTkhawojboosQljUZSd/IgUQgISbyx87Kwv7hBRYfxi9A5lcVo2VAuORximRe63R7nRN9HKqibmsurW9St2SQq0zSjjAisi7phcTNumiSkwweMgqg1o3MCwsui2qubK378pzv8PEHW/snAXKrpZRkgBa6vb1lThBY/CfDy1zikxsXTnyXkUVJj4Dx5THXB1WWLC4GnhyeUMlweOl5cN7RVSVlJwqnWWuwfUbaBZVFuVcs6oJV1t5zg5/OZ8+mMQkr769tXoC1v3r3n48dP4Ab++O0tL673tHUNuTRPusSWNbvDBXVdM8/z5vRPIIPWECmzp2/bmkSJ7Y4x8O7DHf/9n3/k/mngcHXg7//0t9RW45YRbQzdfscakBnytkYjceXrULUoCklEDgGSpz8fBTRn5AVPJM79wIePnzlcveCvf/c7lJI0Huc8fhabDLlqUlpL0ox6Rp6ABBKsokuTy39jJCJdG7nh53neNmRFnr0ZYzauUAwBozKJwDtiLLeqad2mrRdIjJHz+Swaq9z+kBK73W5jUlW5MpalRrGlzmxVCGz/jdU72LYtzkc8eQsYA2TFvM0r+zUNeRVXrqzydZ5n8o0vXAFF8AlVwFqFrN7IdUCekHGA1iJUTSRUUYhtxzxvGb3zrIjpbVPqHLWR8IsU5QLRVqgFHz5+5uZQURj+4ntWWqEwjOPMT2/eynyoltBblf2g2hYsPqJ9EBhfIQPurhCaQggBFwKH+gKSx409YfEkNChBTWM0p8cnEtC1oufStpDDGCUCVySmSxclpvRS4WsobEFRSHp2DMhWbxOUp+e/KvLPfM7PnGUNp4jr0iEFTscHKUSS6NiqqmaefqVD6uNHCSxEwTw7YoTD1Ss8mrvPn1EqcnGxp6tKmqagrUsKo4lIjHVcxMKw27V5lbxsK9W1MvDe0/dnxnHMauvI7nBJVdacns78608/oY3iu9eXXB++pq0sgSQcJzQpaep2z8XFJTElHh4emeeJm5ubrQQ2StARa3Z9zEK+eVk4nXv++V9+4s8//UJRlvzhD99xc3MJyeG8puk6iqrCL5NUTzkYNTgvosLgt/bvc45y8sHjph6Vf2gSVOp5PJ449gPf//AH9ocd83jC6FU6ILH1KWYUc1mKaTWTDESiVeZD6lm9u0oRVmBbVVXCokbsIquJVGQXHpShtOLaDzkm3ecEIHg2lE7TRNM0m1ZJa83pdOLi4oJxHLeqbr/f51iztLUW69dS5q1YzDO8tW1rmmZT0QugT16MlBLeu/zP2A4YQafIS5+iSDFSzJmHuYWVgzbifcJaMqUgbFXU+kvlln9FMK8hqxEotNmeyy/nPOv/XyUVclBLck3Smnl2YnZPC5f7evt9McksMCZFfx745d17/v7v/k48dgmULjCmIKFxTsJPm6YFLYfuvIhBP0aJIZPFiKEoGwofSQi+RytFyD/jmBJFHq6XJWiVWLKzQFtJVzbVjrrUKFtjsrfTe1AN0rYtPuvK5IKSS0FRViX73T4LOmNuu0MeOWRN1HDGmIKnssDYCh8Th/0Fd+PA/+yvfxsFQVlmLzC2ursgYnjsJ4JbuDzU1KWmNJa2a/M3FJi8qKubrqPthGEt61h54Nab+3Q6kmLEOQmzHPoBpS27/Z6+n/nn//4jMTq+/+4r9vuStqowWn6Yiws07Y4iUzJTSjw8PnA6nTOn6bBJAqqioMoyguADY38GErP3vPnlI//9n/7MUz9ye3vDb755iUqeMPW03Z6qbonec76XqKy6aTGFweiEKaUi3O8OOB9y8i84NxP8QsiOfmsV/Tjy4cMdZVXzxz/8NU3XME0DWincIgdFTJFxmjBW0zRCnZBqDclKK/TWQny5pVr/uq7r53nG58ijtRJYFlF+e+fRhcozhgDZBhRCyIK88NymhGfpwxqHNY4j3nt2ux2Pj49orekyPG9Nh14rS0CYSjHK97C1qm6bn3nv2XUNKgaIEnuPjlgFprQoo3FOLqM19NNHIUUqBVEpQFowHS06gUUQOnIR+e1AF5FuyrhpGThHHzamt4It2WfF/Ky/vqwmNjZXguDE4vT5/oGHpyO7VwdC8Fs2nVYKlEZpzbFfAMPXX70S8/BqObGWRLb+GIsyIjaWA0fej2VxJGSVL4L2kP2ywphKWguqOEoWYFlX2TAsN1xUlqBsxl1XuCBeSVXUBO/znFQOdWWiYIhTBCVi1JgiRlvKoma/OxCTGLa7i0sgURaGhMWGihQEqHc+3tPsLvDxL7eY/+6HlA8y1FNlyWkYGacTu7ahrGsqq2iagtIatFV4R7ZfeG5fvhKrxjJxPj5K8mpuHz59+ggkpnGitIbFz9iiYHdxTX+a+POf33I6Hvnu26949eqKQmtQskI+TzNV1XC4fCm3hdaUlahonXPc3lwTnKMpSwxKqrplYpynLbAhopm9559+fMO//viOuir52z/9gabQRD9RVFV2kGtOnz9IJmBwXF6/xBhx8rd1jfNBbkDZ6zO5mWkaKLTMVQpdEVPkfD7x7v1Hrq5v+f0f/4o1w25dsRsrsVLLNFJkUqbzbruh1rZhy2vLB8iXw+R1wL0eSKuEYNMxaU10wjoyRjZgthDDqtGakJKs0QsJsRTBnyeh2GVqQJsjtEKueFZh4JfyjWmaWDEy6/bPWrtxy9fWdP3e1+rkcNgzDoOMnNfKJz0zp5SSYbjzHu+/9PcpUhK7izGWZBM+fxZithZfnhADBOGrjd2qIaWzUNPazd6xYn7Ksnz+/HKLu7bc6/eWspRkcQun84S/3eNTwuZLQ2mhFKAKHp7OXF1e0LStkETRmTBhGMaz2LOix/uFvo80TSdCLwTVcnV1JYp1J3M+FwPKrkuQ9dmQKLmqbiTuXQdsWdLsL8DWmLpFZ4y2TrJRjXkEUBizVciijBfUjrUW52dSfiaFUW95fHzkcH0jlfi21FD4EGlqaf+C91RNjVsi2P/5o+ffdEh1F1f044Q/9+y6mosbCS+sSivR40YTvcctYmrU2nC4ODBPI8enR2xhub68JOWT9zRN+LAQfMAWGmUMu/aG2QV+fvuRp8cnXr645G//9Dtp0cyK9EhUTUOzu6Jr9iKizB+qc56b2xcoEvNwpi40tYGwjJzGs7zUKSFi7JKH88g///kNw7jw8uUtr19ekHK6y/7iksU5hsxynqaeqm64un2JUpqyKpHAxBzXrjXD0BOdI7qF2mpZYycIJB4+P/Dp0x2vXr/i9sUt59M9h4tLQLHMi8zLtBLhZ57fSHm9yDL8iyppbcOeaQhqm4Wt1Ynk5bFJKtaDbt1+lbbYFgrEKDlsOcopIe3FyqxacSfrf3OVh5zPZ9ZUGkGdkB/s53nfktNJ1la0zq3el4euiEl7Li4OQmBA4Z3HBf/MKPJRnoNcMSyzYxgXijqnvniplkS/90WFGaNgp4NIIJSxoj/KBwdeDtqIGMxlKJwj5bNwcv0age0z+JLP9KWoVmuNMoqAIqkClSs9lMKWJXNMfPj0ntevXuQtot4ObUErJ6q6pGt3zM4Tw0IohIsWc7ex8sBqYwh+IZYFRdYVrv8tGdgbbFGBLimsoqxqtBYmmtpMxiY/Q4h0JMrn2Pf9hh1WeQEjPC2psurMHTsc9oz5QlpbdGPLLKOQWdma9GPKTHStfqUE4/cfPnF7c8HNYY8iUhgoy3p7AJd53layIQZQnunTUVjo1zd0uz3nU8/bt2+pqgLnhKh4cXnFxeUV/eD5+e0nPnz6wH7X8g9/9wehduYQyGleQBuubl5Q1y0uyBzCLTOu93SHK16/3jGNPWGZMFEsJGfvRAO0eIISs3I/Od68/YXPD0/YQvObb25pKovyI223wxgj2W/LxDie8T7S7S+JqsAnaKoSrUWlnpLG1gXT0JO8Y54lHr4wBqOF7vjul3d47/nhdz9QVwXL1FOUFUMvLvIgOat4//wyxBgZhgGFomtaYvwkrd4X1dR6cK2Hw5fK73VY/uXfSzEJcCwm6qoS6F+M6BRx3rAsssWymQ+v1cqsEoHltCwbqbNpGqq6Zppn6qqia9vsFRRks80D16fjkfMw8OrlS1KuQFb8i8+ol/UlH8cRk29yn2eVKyVCqYjSCR8cpakI0RPigk35JVeCuE5BDjRrLXNaCJJmS/AABVoXeWspFZHE1VuSe35htZLLYv2st885t2xyGMKXc6r1f5/PJzE5z57ROEwjfj1jRWpy7mfOpxN/+s1rYpAAW5SR5KUkkMfbFy9F1Gx9VttD9JJ8M08z0zxRVSXB+2yTkmdtCQ4fxKM3nAeZ5SHLlZDjs5QpKetW2l/vc/DGc/5gyFUPxGwrEgCeMZayaJnUgrZJ8N/G0nQd8zRuKvMYU1baK8qqkHisqtnCTrtu9xdz1H/XQ+qrl5e0TYHVSK5YHsSuZX7KQ2KZgVSgFLevX7PrdozjxMPDIw8PjzJ4Tol6d+Cm7YhY/vWn97x58wtFWfCnP/2BF9cH4jKT8hwhIi7wumw2V7cG+nHgeDryzdffUdcNx8c7FFHW086JhguFKmqsAecCb35+z6eHJ4KPfHV7xcW+QhFRSYR5SyaDzpOEKETAVC2qqLm6fSEgsSh41iUkSI7j3SPT+SQ3uMntQUo8PD7yyy+/0HU7fvu73+a2BCgKMTOHVXgpFc+X1ZL3Pg+rC95/etpmeF++EGursoob1/+//rMi84LWmVJIMuDVSoy+q/zDO0HD+hjQQUIsii+sN/M8bZUYCLpmzAfVNE2inWoEA70abkFe+svLS95//Ejf91xfXW2t3bIsm+xkWRZ2ux3jMMjXrQ1hniltwZR1SAmZo5Fbs3VrJvH0kqQTdZRATWtJWoy2ISWZM616J6URNRiy1SwkyXf1Za4bT6We9VRVNkUnQOd20Hu/6fmUUrI9ToKtubt/4OuXVwhR1GSbjnDPHh8eKLS0zDFG8B5bWbSRmeTF5aUEofoF5WcWP5CUwS2ex4cH5hAI3uGB8+m0+e+899K6W8t5nnl4eNx8lsuygEr5a5eLa0UmPwMNV+Q0Wxu9VvDtYU/M1htjC5ZlFt+i1jRtxzKdtnZQa0HduMVT5jRtrQ1lUTGMwjwr7K9kMK4sXHQNCqEFrA/nyjKqy4q6rKC07Pd7Li6viGg+f75jniacm0lErC25urwhacv79x958/NbpnHk97/7jtevX2yZYPMo2z2do6ptzquDRN+fMwq34Pb2hmU645cTJht3t7RXZfBRtiDHYeLHn97y0z//mdffvOL17SWlhRQdVd0yzzPzJBuStm3p2o5z35NUYrc70O4uGEdPUdbCTi8yaG4e8bMYOY0t8urec/fxEx8/fuKbb7/i1atXKIVoloIXv9QSsh9OtoZN2260hXUGMo4jf/7zT3z+fMe0zPKg/Q+H1HpwfalEV0ptLcEq7/iyKrDG0jbPcok+hM1Gs7KVEkJMWOUD6+B5baPWB3tdSgzTRF1VkBLDOGzfQ9s0HPZ7Prx/T9tIDh2I2nxFu6wve9vKNrBoZAMcvKfI28dpmoXtnrdu6yG1bW21RuXNatO2nIazHGhGobN7Wb5+4a1sm7p8iFdZJpNSEtbV2n7lti8lscMkkBh3J0JKQLRMiLxDtpWOh+ORfXuLMYVooaJiWBwfPrzn5rAXqYCclBAW/JQYx4HL3Y7kF4KfeLj7SIiR9nBN3e65vn2By1WNMhpbligvxA3n3LYFBHh8fJTPLis5hcAgB0kMz3PLjdaZP0OtDMEs+dAxOC9JQS7PBdcNX0yCitlfXPLu6Y6yqiToQiu0WVttEMF0ys91JR7RX6vda+oKlKBuvfeiD8n/TClFVVeUhaVpKoZB4sJDHsgNY09VFFxdXmPKis/3T7x584HTuefly2v+8I9/R1MXCDJV8BOiuk2YQvQ5okPRzPNEf+rp9jtOZ7GXdE2NC5J/V1WVxOtEhMW0RN6/ec/7Dx/RRvGHP/6GXVcJskNJKTvNc2ZHN3SHS8q65fj0hLYFX3/9ir6fOfYT++6Cru0oC00MDqMSPsnAuTDydfb9wPt371mWmb/5m7/Kxui0hUTM8yyfW5LQxqbttmoFFJeXlxJ/ROTjx/d8/nRPP4wYW1BUkMKz2XMDweV2aa2qVtHl2jquFdD6UJZVuQ241+FvyFqpqqiwxkgCSZCZmDYixHPOM01im/ly4L3+2WsbGHKadAL8svDy5hqdFO9/+cj3v/mGMi86VoLm84Bf2gWftWvjNEjFHh3TPEJSWKtwQZ4rlRJlITFog5+z70+WAc5HSajRRqgAiDpdGSPtCDzrl9IXrV7+TNb/7TO0DxAldgzookDlZYExCh89OhjquuTyYs/FxR6r87ZRi+VomibuH3vevX3DH797kQ+oSIgelzyahJtm3rz5kcvLa7Qt6K5fExPYUkYLLgzsmo6Qv7cl++lWGumqWdNa0/dnbFnkZ0U49+PY03UtwyLLI19VRNJfPDsxt79ijA8ko1myiHO9HNfLDaW4urrip38OmBRRG9BQQzT4IFvYFCbC4yMvXr6SM2Rxv84htbgFVICkMUVBoVROh3HsdruNF30eRsZJhqUqitxgf3lFWVWcjz0//9Ofub9/5Ob6mv/7f/4HLi46+QHNM8ssWWll1UiemtY5Ar3eYqnbbieCM6NQpYboM4HAUNYlKINPimAsH++f+PD+gaf7I5cXDTdXO0qjMFrlstazzAtj3qa1+0tc0vhp4XB5Q0iRj/c9ZdFyeXlg1whNYeyfeHq4o64qiR/P7cvj4yNv376laVr++Mc/YMy6kRnyJisPYvND0TTttqXruh0qSZTX0/GJ0/nMp0+fGedF+nglSJWonllSa3jAZrvgGcuylvGrmHJtr1y2s+h8cK16KqOFDyWVkhh7VdZtpRAobZE1YEIxXTEra9W2zpicF+yvy+1QzBXMN998xbt3H3h8eOLy+jID/55FvCvUrspbTWmRtMgjksyIUtSYqmRali2ssqk7XL6pQ5SNk8/aHZVneEprlHmukIpUblKP1bbyP/5SSra3Lrfeq85MJdAJUpYqrKLSZAVAWFhFV1fUpdhL1sgn5xwfPnxgPD3S1d8KHtrN2VYkYaJFXTFOCy7Brm6pmpp5HtEE/HTCDWc5lKuKxbnt6wQ2qUeMcuk+PT5x8/I6bymljTXa5ALAbr8vLE5kGjESjCGqlL8vtYmw52naJBpCgXgmX+x2OxbnhWtVVChtUTqhLcSw0HQ7Fr+QUBxPUkWdT7+STur4dGS37yQg1C2UZUXbNty2t4QQeHx65HQ60zYNRouBsm47yrKmnxw//fNPvPnpR3Zdy//yv/wHXtxeo1LEz6PcqEkImXZNlEiJLuflrfOWcRoYh4nCaFRyuJyuWlU1LiRmn7B1xTB5fvnwiXcfPhEXx+uXV1wcalQKmMy1WZygWmOIXF5dUdYN0+LYHS548fIV4zAzjDNXlzu6XUdVGtw8cXx8wM8jlTFUhaif+/OZt7+843Q68s2333B9fYX3s1AYld5W7edzT1XV7Pd7lJJkl5UKWliJ3H68u+P49Mjd0xPeBYko94qHY7/ddjpfDl+qmdc2cc5BnjHGTVm+rsy/HFpba7fBuAJKK/absihy5SSpuBEZrE6ZQlCWkhS8DudXseaXq/j1BXA+UDY1s3MUhefbb7/i8+d7+nPP4eKwIVjWAXpd1xJfZS19f8oVl2zU5nnG6FIGxTEQ83apLEv6p2MeeOfFQh5yr+JTFDkEQbyLxuQheOIvjNbrr7UVBLYA1PUgCHnQL39P5Z+tfF3WQF0aNAIgLOzhi/8mfL5/omtL6raRRNRcEaIEfe0zPdS5BZXfoehmEh4/DZxPPbvLG2yuZBQpj1Lk86nrlfHmOfc939RfE7xYkuq2zVFYcjnEnEVAyonWiNUoKbKR+7nKdsbg5kUEqYlt47f+zGTB4TB1RBtEfR6F+Y/WVHUnm8Y8giiyEPnf/ZDa7fZ0bYMPnovLA/vdHq0Nj49P3N/dg1Z0ux3BzYzjKPiUqPjzn3/ml7fvSCHw13/4Iz/87nuqwhBCTpwN2RiZh+37RpKM1/lHiJ7h6UR/esrpqTWoxDwuFGWF0YbFeZKx6LLh/ecTb9995PHpzL4p+eaHFwK7UxACLN5zPB2xtqBrW/a7jrKUkMzbywNlU/Px/UeKsqZrJJ11mU4sg8zJlmWhzHOdoe/pz2d+evOGcZ75j//4H1E6oVSktg3OBcbxnDdX0grVdc0yL9niYbC6JnqJA5/GM8P5zDwtBC+q8nEM9MOYX5ocYw9/MTRfD6FVvb+2f88G5JygYzRukZZca7YD24dAmTHJX85jRM0tVYnNhx0pUZYFS7bLrJqttVKD5zZKZ0lEVVU5gcWwP+w498Pm+1vnPqu+K4RAyi/J4ibZEJ56pmmmLMV+4oKk7FZFmdXQYo7W1rLkOd/6GYQQpNXT4u9Tq6k7BFJ4pkWsLbF83Ws2XZLWN7d8KYlMwRqTAxg0Vq9kBrZDoywECmmsBIRqrZm84qmfeX19RVkL9lpnUWOR05+9G8Wsk7SQHKpSwj1SIhot4afeczoeCTFCtkRN07RhmxUyS+yHIWOERVbwPNjW+XKRTW3KLgZrDcsciKw4n/RsB1qfISWtX5yDqOfz5+V9YJhm9tclLkSKfDilJP/doqjRtmB/ccU0nLjKAM1//0Nqv2O/60hRvvDHxwfO/czT8YQxlv1O7A3ogu5wzfuPd/zyywcWN/H165f87ne/oWkrUpQUGG0URkl+2/7wXP7XdZOz3wq8d/T9CTcNlIW0aat9w1jNPC8oXZJsxTBF3rz7hcfHM24Z+eblNTeXneTOKU3wnmmetvb06voGY0tS8BwuWtquQWnLh08nirKjbVrmqUeSVx3zOJCSbI58FALDh48f+PD+I1fXl/z9X/+Rc39mcYskkGiT2d0yP9rv99vAMKaYH1CN9wuFsizzQHBLNikLQnb2IzEmmrbjNIzEzS7i/2KjB2xbQWPMlgO3Rp9HFfKLC6GuclabbMnIN+d6CK23p1Ky06+KMutvFIsLJCTuaZ2HHQ6HrZ1Z5QQgbWfMeJqVybQ4IVTu97vsCCi2+c96SK3zsbbrOJ+fmOaZaRI5hfOOc39GadHspBzKqbW0hUbLnMTHkC1G4S8WDTbbcmyunDTPFZf+QqwpWi7HvCwiM8mztzWmHsiBCNmmg4DsykJSgE79mdvrCxn+RwnXPPYL3kVubm7Rtt7Et+vB4TOXftWpyTEZUSS0VqLjMvJ15hMxp2/7bTa4Clt9kHShtq7l9+dDSKo0twk152mksBWktcqU70vnP1Mp+zx3RmZy8u8ZtLUE5/KIwDLmCK8YAspoSlXKDHOUZ7i2q5arxGdCxb/7IXXY77cP63g6c3//SEQLML4UYaPSJQ9PR96+fcvx8chXr1/zx7/6W5qyIMbA6fGBGD2HiwvmZeZ8PlOVDcYamqbJN3giBcfd/WdBrmqxOkyjaDFWJElIimQaoq64P478/PN7jsczN9cXfPv7b9BxQamINWIQnacF5zzd7kC72xOwxKDxTvP2Q4+xBf3wxMXhgrZtsVajmwY3w7DIBkrmCwunU8+bN284nU787o+/5/bFLY+PDxyPZ1ljJzlQY35J9vv9tq5fD5G6qanKguhm3NzLbCq3GdZaTCRrZQxLjs4WzUvcDpN1TrJWUltElQ8bTRSeI4dMjk3fWpkvhIpfDtC3QyZFuUzWasJowjJR1QV1HryvBuT1MF63esZIrPvaGh0O+5wW7Njv94QgIZ2Hw2FrQ+X70CyjRIMXVS2csnx4jfn36yxElW9uzVl83vSt+Jmt9VRqqwa+tPmI0VYunvX3ydeuifEvP6O1Ut2sNUZjlFw0zs1YZenqin3XbS9zUciLOUye+6ceTWJ/cUnUlpBJAM8BFnIJKb2+ljILNDptMfNVFuZKZWieBav5cirLEh884yziyrqpyb7j7d9bloXz+bz5KhXPS5V1Tum8e27hjRQSEuUeQStsmc3O+RIry5K+Pz8vaACdU5GDlwPPmHxRlBXj8CsZjE+nMz54zv1ADImibCRSWot9YJwX/uVf/pn3737hcHnB//6//2cu9i0xepZlJDhP13YbFnYcJPK5bbsNzp9IuGUm+gWtslnSO+GG13XWIgs3GVPx0C+8/3DH4+MJkudv/vgbLnaN/B4tzcs0zwQfaXeXvNjvOQ8jp3HBmkRKovQ2RYmxFa++uqGtCpZloh/OELxYVIzezMSPD0+8/fln5nHiH//X/0hRWZZxJMwLF7sd8zTTVDUpBfz6EEYhVq4hAW3XsesqlmnALcOm0l/j5G1RUKKI5x63OJZ5lhFKfsG+hN0Bzxsp5DNbH16TkRqrdzAlccmnhFASMh6ksJaytJmtlFXjZbn54prmmVHk/AKkzUi9vmRN02w39FodqC++tjFDAIdh3KLMVyV8URRiU0oJneT3zIuAAqPwbElKwG/OO6JbDcmSUpIQwF6EfNAbol+2g2U1OPM/fD42K9JZNVT5oNN5aL6+vOtf10MOpbYV/SrNSClQFJpd17LrdnlTJr93WQKf7x+4vsyxZRkZszL2T6cT2lhMTuORdBmhawTnZCs8TRRFk3VOshxZFo8xOTU5V9VrWpBcGJaQYrYQeZQSHPMqXxHyqcd5aZVVyIlIQQB8ifx9mqz1yvM+k21I1hqKspKf67nPh6UA/2Ket5WVbK6LssnjBLXN+P7dD6m3P7/l4uqSECQxZZ0njPPCmx9/4f3bX9Ak/vEf/4FvvvsKTSQGR0qycan3YkZc89CqshbLhhbiY4iRaRqoCpMVxlK1GCPS/k0bU9Q8nSbevn/L3WngdBz57tvXfPPVC4o8+yzKEu9lJV5WO9rLjqvrG968fYuPid1uvwkKQ4jcXF/R1A0kOSTncSRGT/AzRie8X1hmz939PW9+fkOKgcOu43h/x6tvvyEaMcWOpyOgmOcpx4w3W9VTVhW73U7EbQr8POCmkXF8BsrpfLv7GDmdzwzDwvHcY+yzE//LOdT6Ym18KWtFVZ43dmsbZa2hLIttTuOcyynNMnMpiixk5FlFvR4+iSDhGhrmyTGPglg+7PZb9bbac9bKZa1UilJScVQSbKzW8rn0fS/R7l0nSTpG5kwhRZIxMtNAkfK8TGnL4gIxCSFhrbzqut4i5VdEyOofWw+/LzVkz5XSF+EOufpch9Hr3G39PL5UR5dfDHyfNUYSK16UDVoruq6lbRr2+53gUWzFHB0PD3f8w++/xlhNSlFYXkle26btctUpBAYh0mazs7WI5jPRtDVFVbN4zzhIks8KiQRwTmxmwyCUDmNEc/ilrg7U9rmEECRJ3BYEZPEQQ8qLE/kZrM/mqhETI3z2mSIEiG6/Y5ym7XILQbbm67MafCQ4werYzB37VQ6psqoxtmTfCgtqmmc+f77jzZs3TOPI737zHb//ww/UTQnJbzeM4FBWFXXYvpH1g11Xxyk42tJsBMZV/CWD3YSxNUonfnr3mT//+I7zMNHtdvzD3/01h12NIqJz4GNbtbiQKKqdbM6qik939ygNNm91VILLiwtsftGWqZeb188EN+AWGWJOy8LQj3z4eEd/PvG73/+eXdfy/u3PTKcj/+3/9VmQF9ZQVQ1KG5paUnPapsnbNNmEGqtYpoF56HNUfdxegnWIGaJsUofJcexnmZulcZs5fXmzfzl0XqFwIfOmqqoSFnlRYq1Bq7RJENbq4su279mLJtqWlbip1P+Ptj/rsexK0zSxZw17PoNNPpB0BskgI4IxZUTOWZVZmZXoi+7f2ECjVC2pIN0K0JUkQNdCdXdVV8bAeXD6ZGZuZmfY815r6eJbe5uzpItKIOkBggGSbm52ztlrfcP7Pq9BGUnq9fGf13XDdDItrd2bh+Z8CIgNRyKSgpectrquyfOcqqq4ubnBGENZyDKmyAsOdS1C3DzDKsV6vWH0YG1g6LvvHy7xZ5dUn3si5zwXsW+0cPOvuYWZ/4l54yAKUay4KNPNvQVp/nlmKYdzDhKWhz4g7fFcQckFYSiKFaML3O5r/NSzWq3itjfQDw6lPdrKNjXJYnuuJEnZGEuWJ0I5GKSKylYbHIrjfsft7V2UP7jvaeN0vPSVJkoFkntVvLVx8flGmIeWysxoi9IyZ5pxPm6SsBW8pxt6hmkU4mhwoCWgxHmJDLu5u5HNq06xVhBIxog2MEkkxAREvT+Hz/63/PpnHVLb8zPyoqBuOp4+e87LFy857A+8997b/OTDP6WspMXx07BI7I21uKAEZE8gzSSaqe977m5vKCv5ZtPEgPH4aRTnu5bhoJhTU4JOuN23fPrVt3z73XOyJOeD93/Eo0cPRIvkwdqEruvxSnL6lDIoDce65ub2mrIsyHLLOEwQAqenp1irUXixG/QD63XF0B0Z+gM+pskeDgPPX1yhk4Tf/sVfklgp1x+/8xZTc6S53dGPPW6YGJTi9PQMqzSptbLOVwqNwzAytmI+FqRtWA63+QMzTY794cC+GdgdOyYf6IeBtoszKRUWS4iKab2jm+F2ennY3rwATIx3ejNhZgbyzS3hbAIm2iC8H6ScTxJpM+MFk9iIH54cbTuHZtw/6HN7VVXVktc3jCNFPodVpHRdx3q9oihyDscjWS7m9Coaj7txpO1HEq2j1UZLvFUE3s0zJYiA1bhlGydJkRYW170sY/HXRZTzUpHGlm/WBIlu6l7RPx9U88E2xnW7jjPAObVX6AbxEsgy8hhfb23C0HXs647nz1+yraRV6/qJyXkuX79mu9midCfJzXGckGYZgUDbNKgg816T5KhEMzoIw8yxIvK5PG4KEgnmA2mqozA5E6idMYRxiP7FCZvI0mQW1I7jhEOjDBirJAV6lCBSpSTcQqbnHnBIgEOQMFk1Mg0ioamPNYe7W6rNKShLamWWpZUmS8VofTgeWG029xaqf+lDqu57bg9Hnn33gqvLVzy8uOAf//HfcHJSMQ4dIciqOgSJvA6wtAMi0kvouobrq6conZAVmZS0wTGOrdy6VoIkh3EgKPE7dZPiy6+/4dunL7jZ7Xn86AE///hnVGW+PJA2qr3bTuZcPkDfifdPG8V2s8EaQ9d3FEXJZr3BjS3HwxHvJtq6wXlP7Tq8H/GTPCivb3ZcXu15+913+fDD9xm6NlaIToRuZYXWlo2OvHBtZJCbSDrJ7vaG1GrKMqc5HpZqY4oxQm+u+6fJcaw7Du3E7aHDIf/s9c0dh7aJsxBJhAlxmDz/L0kTpinaQ8w9n2ne9qjoDfz/NwtY5jCLLmY20EZVdzyk8iyVWziKI7uhZxUkyHMO1Jhbihlm1zQNLgSqeGhUZRmHsD1FkVO3nbR9RYHVmjxNxdrRDxil8ErHuQiLLqssyzeIpwFrNdMoVi2rRbE+/0zz4TOOo4RvRO2XtnaZr2hjULFy0Oqe6hlkKLP414ZpIo0D6qVq08JXz7JMSCDxNVw8kdPEsem4fnXJkwdrXBBc78tX1xLKOgwURYoxsqn2StKL+84TXMBqw+gUN3c1Dk24ayEE+r6NYDxBuKRphkVCH8axZ3d3R1nmwskKYrD2bmII8hkSacYEGJyXyHo/jmRZASrgxpGu7eSiKiqmocd1LX4QPtq8DSZKLoos53g80hwPJGnO0AWyVLa7xthF+BqQPMth+oEU519+8RV3uz15lvG3f/vXPHpwCgSmUR7c+ZvWWqJ/2hgqmSQSRbXf3bHf3ZLnJUW1Js9TpqEW/9s4yOo1CKNZ65SgLC+v9/zhk8+5fHmNTVJ++5tf8c5bj0StG2cOYs8Y6TsRMVarFdPksEphEzHtdm1P08ubqoLn+vIpRnnCOEaUqZS/fVvjguPY9Lx4+ZpmGPn457/g4uKU+rBbOOZGy8PqlSYp13GAGtf3aQrGkFnAjZRpQt3U8mGB5SF+k3bQdyP9MHJzaHm9a5kc1Iear7/5jv3+wBg8Rbx95gdw3jTNs4V5lj7PYBYZQfCLQnjRDcWKYT4g5xmPBK/OrviYEOLEgpHaBJdGCFwQWF7fd1TR1jNvFuc0kiLOLZu6pu97iuh/E8tND1qxXq9FjqI0RV5QFiWj93RNRz9Ka2Gt+B2TJGG/3y/f99zmJkozjC06LeI8bFqGw28atrWRGQrR2H2PKFHL6+hjS/tmSz2/pkkiKJT0DbX2/Pvf/B6naYrpNwXDMLLb13TNgTQ7J2B5/fqWy5tbNps1+8OB87N1hDcOJFmOmxyDn2iajs+/fko3ONbbC4m4CrE6xOHdQNN2GGsp8pyqKiSNRsNuv6OI8ekugNaKgIvVqAZEKwVQFBVZnqCDwiI2MUUgMQKoG9qaphGyiPJuWTwELwnRo/dkWcI0DvR9R9M28pmzK2wiuq1+dFjnKFZS4dsfCnp3d3vHn/zql/zovXcIfmQau7glIcbVEFW7Ghe3cfP2Y7/b0bUtJ6fnrNbCgBqHhqnvGIaeEDR926FNgjIJbVfzzbcv+OMXX9EPA+8/ecKvfvUr1utyWVPPt9axrjFaiKBd19G1DTAHe4p6tyhkgOucR4WJRAuX57A/kqUZRitGN+AC7PYNL69uyMs1f/WnH2OY6I53aG1iO2EZx0FEa0lBXhSSuxbRKFm5Istzysww9Ufq/S7KB0JkPdn7+ZH3NE3Lsem5O/Qc2kGIp7d3fP7Z5+z3R/pxIi+LeLPPvB+3tDFjtDlorQkajNV4Jy2QkANG8rzCuYk5VWaaxqVVmx+0uTVK0gTTKbxDcDNJivcO5wNTPLjGYYqYmhDnXsnCMM+yjHESr9p6tWIYBvaHA1kq7WSaJjjvOByPbE5OWW027HZ3QqHMc4o8FxxJM3I4CtLGTAJK3B8O0iJm6XLohxBEqxM/a0rDHARgtKbrO9JEQi/EWOuZhmmp/haZRqz2nLo3W1tjohBSDrI0yyL//P4hM0a2o2VRcnd3R1n+HK00bdexj51H8MIuv9kd+fSLr0mynP3xyOm6Ik0TCEJ48Axc3+x4+uwFr2/vcA6qasNjXVKtVpyencnh19fRGC8aLRtb+Nu7W5q64fXNLW+9dRFnrGJjmkM7p2nEmGyZVco8Sku4SjvnBDqZS04DQ9+hlCB8PMghp0Re47TMKrMsw3mxf5WbM8HgxE1tUPepMywz1Xt1/7/oIfVv/+HvONkIO0Y0c/FNnSSo0SYpwyBI2dF52qahyFPyQvrq07NTrNEMbcs0DfhpJM8zhnGgbQeUMnTdxLfPnvPVN8948eKazXbD3//d3/LknUdyIvf90kYkSXS8FxXWmGh+HYQxNQ7iu5pGyjKnynOMCjjfic5pf5DWL8vRVhKGx8lzfXfg6vqOt995wkc/+Ql914iI0wdUtFDIUDonSVJcDEVMbIJN4OT8nLyqmLqa42GHH+cBueCUJc47BnwSpN3pR17d1RxbWbe/evWC3/3u94sJM0nEqqLiwP/NOcv4hhLaGiXEwyBES2sMnoBWKUliI5ojyIfNCyPqvlKICBlEbZ0kGS70ktiiZQtlUwO6FG9dN+B9wKaGfhyY9hPbrQRfzP47P44E5xa8cBdbPK01eVFSNy3X19c8fvyYLs0YhmEhDuS5DP2dD5ilFU3EYtXekqRJbHnlZ1mtCsYJ+dmDzO2MMhBknS4XiYg9m6ETogZCRwhvLC/mmRVaLTIEpSSX0Gi5fLWRFmrmxaOkBdxut/jgefr0Oz5470dcXh15dfmap9+9oFpVHJqBL778nLppOTnbEkLK+fvvogPsd0de7/Y8e3HF0+cvabqeBxcXvPXWYx6/9Q4npw8wUZg79IIRcuNAiOlA1tgoqN5wnBzHY0OepUKgHd3Siqsgh8oUWtyURhtUSqROMYwTfd/KgT6PE4JDhelempIkAg1EzONBESGHlmNT80grMJLHqII4AVRUp6sgGJfJ/0DbPT80NIdZFasYYkbXdnNKkmQQPGma0/d7mlqGslfX1zx++IDz8wdMbqDZ34FzEZTv6L2jHz02q7h8cc3v//gZXz19Rj84fvnLX/G3f/uvqKqcEEToV0acSZqmcfsyz3PEu3Q87On7ns16DTguziUqKU0UN9eXtHUt1YWTLHujpeqoO8fzy9cc65aPP/4ZDy7O6dqa4EZhgLsY2qhEL2WtWawGaZZhjCFflWRFwXF3R3e8wU8dU9/Rtd0itttsNqDkjdsfGo7twMurO9pRVu2vr17zhz/8kbu73SJazfI8AsXUgmoBvjdfShLBmRhr8JNsWwwapYIQIeKw981WTzZz8vvnWHLRJ0nCix+H5QAUYaZUbw/OL2jbfjnkpE3uuL295fz8nCliYVyMPctKQbXs9zuqSgzVaZ6zWq2or644HA4xZLK+b+ESGcZ2cWEwuSluGiX/znmHNTYOgNMYLSUeRKN0TDgx91VeMoczyMMo1iIfcc336/kFQ+PEd6aUyEVc8BhrRf7g/WJQd85hE0MXyRarsuLy6gqlNF0/cHV1y+3dDpNm/G//++8ZR6k0h67j3bcfURYFu33Dp198zadffM3r2x2bky0PHpyRZ5YXL17y5VdPxdA9OSYXePjggocPzqjKnLLKSdOEqqqir1JU3k3bsq024mmdWrSa0dJyOQUcw3DEGEWeC6ywbZsoCBXLlC4VUy9SGR2UZDL6QGLvX1cFjF7EdcZYmqYl4JnGQBH9oX6aUNoum1O5fP7bz51/1iGlgrw51mTLAVWUKwKCS8UrXj17xfGwJy9KRu/40bvvsl5VuGnC9x1MYujtug5jE7p2IqiSb7675Pe/+wO3t3uqzQn/w7/5O3707rtYo+K86p7ZXZYzOUCSgZM0gJ+4u31NwFEUGd6PnG3X5IkGP3L5/BXH4x6rNUlaUKxKiBur65sD17dHQqL47Z/+CYlWtPXdwtxJtCUvVsvsJ5sf7lnTFDwa8Zp19R6GFuUnpuhhHIdJ5gapeBP7YWR3ONJ0E88ub+gn0XXVtzs++eQzbm/v4A3B2xw3JYqc+6HuMmvRejG9zipkluoD3DTi3P18ZX4YZTZx/1GY52Rt25GmCWmaRbpEXMUrwM9CPmiamvX64XKI9V1H37ScbDZyGKYZh+MBkxiqVUVTH2nqhlW1YhxGyrJgu9nw+uaWk5MTnBMsrWh38shNj8N4J1FXWZaTtq3YQFLZ0CWJJSgt9ickV9CrECkJsmnshy7OEmXTNI5uaT2kQhV/GuF+pjdbXZQSAS4Q/xvx7xGrKWsFvPfq1RVVllDkGU+fvaBpO/aHTqgGL6+jtUculCxPKdOUw/7Al199y3/63R+5u5N5b1M3/OHymt3uSDeM+MBi+LbW8vzFc1ZVweOHD/nww/d5770nEGC/l8O+bweGfmBVrbA2wdoBo7MozZBneHIONw00zZ71+lTY7BE8aK2h65r4WZnQGtzg4uvisEbTNgOSVh3i4sSy2qxpmkZa2xhDh5LPb2LFgN00tczdfqhDahxH+lEIiOVqRddJ+1CWBfu7W56/eM7QNZys15yerqm2awC65ojrO/zY49zEOMHm7Ix+THh9c+SLb57z6tUrHJq/+us/59e//rUYKcchSvFdnLmoxeUvD1RCWeTUzZG7mxvaUXhS23XJ6WaNUYGu2dPVjSQAB4U2krCK93T9yHcvr7m5O/L48UMevXVB3+yZmDUkMacuy0izlD5ylKZhFLaVkZYtTXMSrQnTwNg3BD/RtDVd2zF5MElGtV6RaE3Tthzblt2x4/nlHUEnlIV8WP/4h894+eJqOUwm5wlhQkeMb/BxA4W0ZLNAcV7Hi3o4Hk4ETJRKzMPyWXow////mo/+JqlhGAJlnpMklrZpyLKMLM1Q4ygPmlFi4/Aea+RjVNc1qTFkaXTZo8izlPpwYBNDBw7HmqKopPjXiiLPKYtS6Bll+UYUlYABxWDdLtvPsiho2obJDRJnFVlHk5MUmmDEpmJDYBh7yjxliiMIOWREtCq8I4ldMsZilI6J1jGNB/HOGaWWWZZSQixVgSXh13tP37aQJly/viW1CWfbNbf7A24KdMMo2X+qw3vHZlvJRjrPOTYdn3/1lP/8X37P651k5O0PDcPLK2mVlBbtkoihFjHzTByom46Xl5c8e/aCj3/2Ex6/9RgHHLtOCoiqkrYsCGDQJoY8zckSCRxNtMTKH+sjWmtWqyrqrGJ5rWIeo4bBCaZ4lmx47yM6B4I2oEVoejzWi5h4HEacUfPJTttJApQ2lv3x+MMcUiZJyIsStKVppK8vy4r9/sjV9TXb7ZrTHz2hzDKS1OBxdE1Dv78F50jyjPX2AbZYcXmz4/efPeOLr59x9fqSi7MNf/93f81PfvwjmrpmiJIA+WDdIzfmgXFRlHgXaNuau9s7hkEU3+cna4oswY1dtJmItijgRWVuDKNzHI4Nz15cMznPRx/9iHWV0zcHScG1KcMwkhclWV5g0xSPxyYy3DdaIP6EwGq9wSjF0LUM7ZEQBHpXtyNaJ2SpFVaTlQ3j4dixrxuevbzFZms2m4q2PvD02+948fzl0ur0w0DT1GzWq/t1OmASiwvC7nHjtFQD86GjtWxTZkXxmy3hm5u9+VCC72+uZp1T09SsylLErBFMV+SyXayKMiaIDPjJoYyN2y1HP42L2VUpRRYV4WPfc7LZ8uLlSw7HA9utRH8Zm5IXRUw9aSmKfJEbCAhQ1t0zxTNJkrg16+KmToTAYgPxlOuMto1pNEBw0xLTNPmwUEfBoXSQMNHgxWgcfBRl3ivz5+G5jpx9EAfNbI2RZ1noEqnVYh0bhanlHLEtjgr+1CwYnf2+5pM/fMnzZy851g0TnmGSnyEosZZIUs64yFSIVV2aJtihJxtEMPzi1RWvb+54//0f8dOffYRGaKNZnkc/rcEHcD7g8ZJT6T1JkoOxMmMcxNfa1AeZr52eYm0CY0s/1hHW2C0LGhBN1jybCiFQrVY8f/o10zCiI6hShKOa437HFPn3wXtcpIf+ix9Sm+05q1VFiPjWly8v+fTTz7HG8OjRCZvtVnrgoQMPw9CSWcOoNScXD8CmOJPx6Rff8cdPv+T5i9cMbuAvfvNL1lXG/uYlz5NAtd5IHwukRYmK4s8ZgbtaVShtaOoDd3e37O52rFdrTrZbUgsqTPRdyzT2+KDQxlKtt5jYar2+O/Dds1esNlt+9dF7+LHGj00MlkjRJmUcZb6WlxUQGIeOoWulfE6FBJkkCYwjzdDS1Q1tUxOUou063OTIMkteyINeN+JdfH2757sXV2xOL7h4cM7h7oarV5d89eU3TFFvM03TkrxSlOVi8ZAbUCraLj6IKqqbh6EXc6iMrWARMN6rv2cX+3wTvol0mYfEs1hyHCVMw00iLhS4nuBayiJfGEIzidP7QJ7nwrB2jsPhIDO/aHrt+56xH1jFVBltDKv1Oi4SPGkmIs+maamqUgb5xoiYMoaweudp2oYksbJlCwjjSmV0fY+1Cc4NyOZcFOrOT2Li9hJCQTzoBFmcojRRRe/QQSgBKrmPADNW5DTRrby85vODKa/r/WZUtG6NVBLRQyd/tgJyQqHY7w98+eXX3O12jIOPFbGgeAli7u26NrayicwXjYkJ1loO/ckBA9fXNxA0Fxcln372BW1bsyorgdOlKcamuCCmXrynbQcgkQSZePiZJGFTlPRdgwoTddMQAtze3mJxi/hz+RVfG600IX6+hkl0cW3X4YYRk+X3rTTz0mGiqw+kSY4bfyCdVAgwTZ5uHNjvD7x+fcs7T97h4uKUVVVgtKLb7WkPd5y/+4jn316Rbk8pLx6iizW7Y89/+l//iS+/fs7+ULPerPmbX/6Uk02J8hOXzzueP3vOhz9dkecZ0yDGYqPv7Qkaog5nz+7uwH63Y73KOT/fYDW09UHWud5JQmtcaw/9wP7Q8vzFS+4ONe88eYcn7zxk7GsRDUZ5QIJCGxHjrTZr8RM2NUPXkCWWsW9xY49Le0J27/wfx5FxEo9bkgrTOstzjDHsdjvcOHF5dc2XXz3l9PwR77z9iMPxwG6354+ffMHx2C1euXEcBci/3eJdiKZjvZiLx142a0opEi0BoCgJR3BxQK6CITF6EdQSD6SZi6RC1MEoheRCSKqHVhJeoLVhmhzT6OTAI9ovFKxWJZsYqT4PnNOYsDyNfdSrmYUXNQ/knZ9YryqaOFOaD8miyEWTZVfcvr6J2708WkTEf2mThM51jH0rVE3EhtJNA30tqJLTUr6OGNpHurEjeEeaCjIHHYfgbnxDVR7wYcIHqZS8d6igohZIoZUhzCRUHxZh53xA2WjQDYhIMyi/tGT3OYigEFrE7c2Oq8vX9OMg4ucQzz4lpAbBvWQYff/74R7nMrfXcl4qpklCH/q+59GjC3a7PZ999lnkeAn4bozo33GY49IleMI5J9u3cC9PKKqKYQwUWUlZVIxdzd31M3xwCyjReWGPaW0ZJsfQDShjWa9WtJ2kN+VslkNqDnyYxjHarcIPF2nVtB3OeV7f3bFar/iT3/ySPLcwDoxtw+uba9ZVzmq7phsD64vHeJUwOM/Xnz/ld3/4gte3B3xQ/PwXP+eD998hsxC8wyjL6cUFGsXTr77mvQ/eB+843t1iipExoj6SJKWpO+pjTX04cH66IS8kHqsbe/zUMwxxhpWmpFlG0w7c3Ox4/uqKaZr46Cc/ZrstaZsdaRSghuDJshytRe+RZylD1zOOA9PYYdS9HslER7hwrWRoOld5w9CjtF6Mr3d3O6bJ8e233/HixSUPH7/Dk3ffIUwj7bHhq6+/4+r6doGZzWygNE3I8yzOY1jW8/cGY0WIkohpmsjLPLrfRwpjxceoNUmi4+xERYgcC7US7tNSFg4VMwLEL8NUgLapscZQVSV5Yjk/O6FuJHV5iiTN7XrF2Le03ZHNWgbhdV3LRpPZo+nv/W/TRBkN2P0woFGUsdKqqmqpHrz3BAXdOJAYYXcHHyCFLgoSZ+fBbMXpu05+Nivq8MmN5Fbop0MnowoT22HhzxshPmgpRSVRR9T6zrsIzrvXZc2IZm0NWomtyMb3ZhbZirZqxhpLOEhAAkvHaZLVvpZ5l1Qns+/xXrcVvOBsZmmGsbLZ9AE0AaPAAb5ucC8v+fCD9/BolLHs6yN1XTP0HWWRx6BT2QA7pP1LJ0Uq40HGYRKJ0DhxOB5k09vIttw7v4iDZwW7m/2ORoPWrKoVbproh5YNgb4fSJIZXmnI8xIdK2uvfqBw0MP+gN5ueP/dt1mtKhlkJ4rbmztSq3l0fiJoiqSEtCToicvLKz799HO+/OobxtHzzrvv8uGPf8x6VcgLZjSTh7pryfKK9Wbi6y+/4PPPPufi4UNcAH88cnKyZbs94er6muffvSL4nqI02CSQpaI4l4rDkiR6SYY9HI4cjh3PXlySZJaf/ewDitzS1UcI0PWt+Pe0QesEbZIFj7vf3aKV2AkUkGbZoqCfoljRe0/TdFFrIjdemkvLVjcN4+j45pvvuH59y9vvvse7P3oH7x13dweauhVPoLZxriLGTmEvbei6Piq/i+Vmn3/5KH+Y8a1zi+aDx88ERiX5d8f6EHlSftlIZdHCMVdCs+mYIMEGfhLx3Ywfds5xrGshcg49Z2en7PdHOSRCoK1rTk42jJsVbdfS9Q1FsYIQ2O12bDYb6rpGAVVVcXV1xTgMS0WUJgnD5BbYXNu2VGa1LAKyJEUDbd/LGj0EUi2M8mkaKcuScRzkz1BKcC7eY4ioFh0wqcTJOzdRVVVUpoutxRojOrMAWgcIDoVsDn3vRTMUB/XzQSVoFPGxKe5tSAs1YBbHJgl9XADNQaA+zr80oIzFuymieQN9Py5EBucdCiXtsnNUqxVZmsbtnCPMwlOnODYtn37+FUJYGPnu2UvKakuRpxR5hk2jP9QLhC9JS2yWLkr8vh8ZtaJue95+9wlWa+6mnlZpbJKI5SiIJtCNMgccnQMtXC3ZunvavkMheO75kOr7UUSrSCc0hR8Kerfd8OTJWxRlLoNIN9K1NUWRAyFO+RO8TTh2PX/8/Sf85//8XxicrNh/+8uf8e6774jGJAhcsG0bmroWHVCaYLOUB48eo4zGJCknJyf0/cDZ+QabCMTr7MEF3fEGN3YYbTkcjnS9CAhX1UogY23PoW749tvn7HcNb7/zmB89eUgIE1NkM1kjtl9rDCopSIo13gX2+4PI+rMEHQJDPAiWtiW6uwOKuu3QRuOQD7qxhnESzs84Oj797CuOdcv7P/6Qhw/Pl5TnJEn5wyef0ndixm67VjDI0QaSphmHw2Gp2lSQmUU7DHTdwDCMS1vkvadrOwY3kacZhkCRJmilcd6RRAvC5IRRNI2i/VpaaK0Xu884CM1xjIcTwH6/j4bkjqGaMO1Iluas1pWENUTsRtf3nJye4m/k4JimDuXFS9fEDeG8bdxut9ze3op1pqqktYuzzqIsabuO1WYtcfBqjufShNELJjh67IzSTEFhtGh05gRf773odaYRmV1rCRJpFYlJyKyVobZGEmeMkc+gNVF2ELlaSrRmk5MZ3UxGmJHIRqvIzZfZ2Tg6xun+wglBkSZimNdWQ1CLHMQ7H1Xzk1AD4sZwdD3TOMSKQwnzKo4whmGQeZORy3IYhTUWvMdHQJ0CHpyekOiMq8trLh7IOEaNgSQmAZkkXSLkx0E6hCQvIlsL2m6gKkpMVqHTkqnrGPuecRgJSn4GFxBtmo+CVivIl6bppXU1hiQVD2vf9wyD/HxFJdjxH+SQ2p5uxdCIo21qmrYmNZpplHRUbQxBOV589y3/+z/9nuffvUTrjPd//AEf/uTHrMocFcRdPQu/pmla4GchOOpxwuQ5282WoipYbVbyQYlVV5olVKucdfWIsW84Hg7S4uSihAbN/lBztzvw9OkL2rbnl7/4mPPzNdPQ4r3DWIUxMoROsxKUwWQrbJrT1jVpkhCCwOyVVkvaytzSzRuzuq4ljNGIRkqoiCNt39M0A59+/jVtN/LTn/6UB+cbUqtxDrRN+eN3L7i8ullatOADJpGHdLPZ4NwU5zQCoxMD8URdH2nbcfGvzUP2pm0wEXqWZiVGz56pKd74AedFPuDdBMFjVBLbRqkSvBf92jz7mDVY889tbVwda0U2yIWw3x9BCRKE2DbNh9HQDxRZGbG1ftkeGmPQRg6S29tbsshD8p0wt4XyWNM0Dev1egkYsDP+JXjG6Z4YMB98fd9/T7D6JkNKSJnSGpeF4H8FoBhioouOQk8hd4g2TC2bvHnjCCyfBR9Fnd57rDYEFE3X0fUDw9SJFWUS0702hjRLsYlYaOYt4zT5OEe7Z4MZY+mHQRJ/bLLk5Y0xiScAznrSJBMMTgzknSu3PMto2p66G8kKz2534OHF2aLzm/leY9ejs7Y4raQAAQAASURBVAyv9DLKmAbRV6l4Sitjyast3nnG9gBxOTDr2dq2JUlSdJJh04SiLBeCrpuELZ/l2SIbks9Fh+eHOqQ2W3nx2gPjMACe1gcUBqWlevrs86/49LMv2R87Ls4f86tf/ZIHj84hbtykfXLCy7GaJCkYl3mLoe09q/UGEoMyhrpuOR6PHPaNKFaBPE9x0xAFjJY0TckjsO54OPDq8jVfP33K6dk5f/6nf0KWW+rmGDddOvqoDGDwymBtjneB435P1x5xYw9RVV+sxDzc95JqfDgcyGNkksywFInRonuphbDZtRN/+MPnOBS/+uUvOD/dYnQgsZreD1zf3PL5518RgmAy5vZLKqh0Wblba9hs1lRVFbnUDU3dCEEiy5bt2m63W2YFRRxIysPhSKL3zEfhKt5D8PhxxERSxdD3i81jGAa22+2y5ZsZ5POBMY4T0+hk3mBTyqKga+v4EMvQeE7CORwOEm5x8YCg5FC31pDnBWmWU5bidatWK7YnpxKLNEhW4GpV0TQ1Jycn0UDeS8vYtdJiMA/yFVUh731w7nutFlGiIxWhfNS7tmVdrZaEGxWiWTZOnGbFO15IHok24CMNYR5yw+L3CyEuM4IT4CABF+Z5lLRi2liCgn4c6UYhzmZptrC6CCxzHuKMZ26xJ9/f/3lR5e69GL6nSUTCS0UUZRxi4Qp8+tmXvP/eE87P17x+/ZrHjx/JjM05vBvFv2n0crkNQx+DKu49i9uTM7abE+6yjN11wB9GtA4o5e4lBlqjtCIvclZVRd3UIsx1jsl7kiiHaNtWsgKHHpP8QKiWq6tX5JlGB2EKBaVAJ0xO8/y7F/z+D3/g5eUVSVbwmz/9LT/+8QcykOsbxr4jyzPcJHaFGT07DAOTCyRJyvF45Pz8jM224nA4cnW1IwRFlqWcXzzgsN8Rxo6hjy1LJCAID2nksK/57runPH/xgvc++oBf/OynDO2R5thQxHat6zoR6xlLP3o0iml0tF2NG2dFsGVV5SKgdAE/TUtAZFVVgnFNM1zwJMailWN3d8fgPDe3O77++hkuGH71y59zsq3QSlhGznmapubpt99xODTLun6GpM1iyrnFK6qcIhMofnAyc7LGRsOvPEyHw2FJAMZ7EiuJIt04YGMr45Fy3Edbw8ICj452oyQ3Du847PasyoqyFLM2yOavbhoK76NiPwE0u/1eLBLWyMo8zl9mV0Bd14KWCU4oB6UQEUIAk6ZsNhsO+z13t3esN1vZDk4jRgmueL4UTk5OlgfVxgpRKUk3tkqYY1VVMYQBI5oCeeij1yzRBh18VO6Dn0ZGpbBWgH0S3NlgrMxnQpAgDBVFiNrouPGUpJ43wYNaa2ye492IVlEQ6T3jCNqEqFyIoBI9HzAhVltyWc4VcWaMCFKR8NZhGJdlio+G/Xkr6bxH6ShGfYMVNgyDCJcVvHp9Lbzz7iFFnvHWW+9QFMVyoDnv6YceZvqIl6DTqsgYu442tHRdy3Z7Qlmu2CuFQotHd3JR0S8XIs5DgLyq4mLjfnHgjSItSrzSOOQy9T8UPnjqa6YgZkubiqjzeGj53e8+4auvvmGcHGcXj/jTP/tTTk7WGKMkeyxLMEpmG/NqecZE3N3tJWVCKd599yFplvLddy94fbtDKc3p6TnrTOwZVZHSevH86fiwaCWDuFcvr/j222c0zZG//ld/weO3HlLv9hDkzRV4nWwstDGEaSJNC7puROEYhpbgRooio8gS8iRh7CVJuRsmgtL38VDW4vxEVWRYqzjWI6iUb7/9iq++ecpmc8Jvf/lrVmWGQlJagvMcDnsOh4ar61vxD05jjIpPlyFplotsou0gi+hdF0t52ZKoeHuLyHJ3EHRJP46sshStNF3TEqaB9Up4WyoytUWwKZyoWdi5oIeVRgfw40BdH8nLMt6u0nYQD4UkDtwF5yG3rWy3Rooip2maxUYj77UIU/NMosfzvGAYB6aIvT07OeFuv+P25ortyakM7b1s6lar1SJjmCvMuTWagyXm1k6CayE4L5UPohczWi8P/uR9VJsHhJIvLfA0Dmgv4Rlz8gvceyTd5OLlqu9bprmS8pLEkiWJHL4mYbvZcHe3Q2V62eb5KDoFqZrc5NDjBEaT5HGJgcx5ur4T9Eqe03TdUuXOLK3leZzuE6oBZhrrnIUIcLO7jW1WYL055ec//ygurMyiYRsnEbyKkFMO56KoyPOCyTl20zUhTEv1Oc7GatQCSpzZZpv1hpdPr5imkbQoF+mEMVZmubqPy6EfSMw5uQHMBmNSRhd4+s1Tvv7uOZeXN6ATfvnLj/nwox+TWIFoacRC0zXNsoWaH3RrZeANsNlUnJ2fMI09z19ecnN3IEtzzs9PqaocN3YoN9E2NcMoG5Q8z8EH2mHg2XevePr0GWWZ8w//9m/JMkN3PJJYgzFiqxBWUhU1PzqKQVtCQNbfGqpqBX4ijANNJBliLCbJmPwcfinamsRYrNHUTcfgFJ9/9jlffPElZw8e8Cd/8muKLEHhsFoxOtmEtP3A1fUtbSftbXBy6CzJuECWJcsDn8Y1uXdhMTVPbobqO27v7vA+MPmJKk0xMYR03zakRrFeF2LmjRsWaY1FWa64rwTmOVs/9Hg/cjjsyMsSawxTvHXv6ZZqqYADHjeN+DDHj00LwnZe04On72v6/p5akaYp0zgwas2qqpjcyH53y3pdxTZnWqrLrutjy3ghTP3oR5RHJBpmtaKP0gOvwKsYYKk1JtqHRKflSZJ0eRAhCMxtGlEqRak0zpYEfjcn5wxDH+UG6fI6EP+bYRhwweM0MptRiiRJOT05YX840EcWuLSjcT6mPGO8bPEyG7KpzJ58VIM3bSu5fYmFyS2XSh9j1eeDYb583nQS3CdJj9StX7ya/5//+L+x2VS89ehhxBgRW/pskRSIV08twaxKKY7HWt5nd68BS5IEpftlPmetyFg2mw3f9gNt07AuysV6pfX9zM1GyuoPckhpk2GzFTe3B7746iuePnvBNAUenD/k45//hM2qlK3fMMbwSZlldH0vvJ04IG/bViQDk2NdlQQ8L19ecnO74+z8AY8eP6TMM9nAHA8MQydc5WmSYWEU+V1d3/Dt05e0Tcf7H37A229f0Pc1ftKURRkHkD1pKvYdtPy+vusZ+3FpTRIrwaRFZpk6h59EwJikGeMU49AzyXULHsoiJXjY7Y8c255PPv+Gp9++4Mm77/Cb3/yJ/Hs3orTGxfmIWDMMt/s9GKkkA34B+4vOJ43zE5EDzPHk4zBgEk1mRTczKdgddgzTKC1nnElorbm5vcESONuu6YeR4CZsEhOMrYRQWpssw/97oaX8OUkqH6DEKho/LVFPWZLENb2A0DQxIEGxVBZz2/lmQGnfdQQ3CSe+qVmt1oJyyTJcK1KLk5MNl1eXHHY7Ts8eMukYqhDbeZF51JRlKSGaSscZDsuBMqqwYFpm7+qCCiZm381Jdh6ZqURVug8Br42EXVgFiKYs6EDfylarH/qoqUvi+zliEkOeGLyHORw1UdKOp1lGGd/DQyeDZKUlbUUnovK+n8Uq3ORR8c/WRoJH26YV1Xg0jXddtwg887xYqusZ/Ty/p/PhOi8DhmHi5u6Ofuj4f/w//9/8m7/7V/zoydsURYFzCLYb0CbBTz3O+fj1xgVmKKGyCX0XX1MteCNrkijfEbFuVRY0g2yfFUrU7oT4vYVYWTqs/YHEnO3o+fJ3n/Di5WvubnfkecEvP/6Atx8/RGl54zBWnNh9h3PTokqey9K5x5YZRiAox6urW4bJc/HwLU63Gxmyt3uaXqqZWcOzWq1QWjNOnlcvr/j6m+doFfjtbz/mZLumrXeUmfz5s19qvVrhg8N7jbG5mFGn+zYHAlmesCpSpq7Fx61Nmpf0kwOTYLzHDyMmiQNWH6ibnte3Bz79/Cuubu/46Gcf8fOPf0qeWIhl/bwOB0jTjOubHQG16KuyTJzpfddHaJykbMwmW2Nk+BrC7NgPpImh6WoZfCNx1lZLiu6xPjJNA5nRaHXCcX+kyDPGYeYegTaKNJVsQ6UlCCDE9mOetSglrajEjI2UuQgu80h/mAfkwvm+9wTOc7JlbuLcEl7pphibpJtYIXWLeXjmUAkPrCOL4RWK+1SXcRRqQlmV7Pc7LHM1pFBGEyb3PdO1UmqhP/o43J6j13wIGNQiKJ0Pj8RYbGzptDHgPEPf0/Yd0ziR5vdWGO8D0xRINIvA1zkveXXxa8j7q8WXNwxxPgjKSOhmbi3TKFFm+Pv48nkg7T1i0tWiH5srJPFGygJifjbeZNXPn62mbcV5kclmsO16nj17yX/8j/8bBHj/gx8xji1plpIk4qFsj0I9kO/lPgtxHHvhbxkjmj2boILEXQUv/41VsFqtGPqJvm2xxuL8nLpzb2SfRr8k8fyLH1L/9McvOB57mrbj0aPHfPTjH5Gnlsl1KC8x7EupGZN45cDq760C00Td1KSZVDFXr3ekWcXDRydsNwVMHWPb0h9vJW8NjbYpRVGQpClNN/LNty94fX3HyXbFn//2F4xTzzQNrFaVoF2JfbOf6NpRTvokp2lr3OTwnkiohCyzBDfS18I6PzQNjx48ptyecbc/Yo3i9upVLKstSZbQdgOvru/43R8+p24GfvmLX/Pej97BKhEBEpXgs4bJe8/udk/TdvigFs3QGNN0UBJQoY1mnGQLN6vKfaRp5mlCwLPf17hhIEsTpph2i9bxQRqxVj5Ag3NxtlQICNA7rI2hn4kRjnlUQ9tE6KrzYWCShLquWa83dN2wtOizKn1WW3svG1D4fmJJ3/fLYHk+zGTr5qN5uREmd2wN53Tn/e5AXddkcbhruMcaKyW42+1my+XlJcFFMaSOBNZJqqU5RFMOqntFvlYq0mOlqg0epl4uEWNtHEUYrInSA61o64a+6+hiK6lCEF2Y9ySpJbGS7QcsPzvhHqOjtcYay0m1prfyDHRxHueVEpuONWQmZxqGZTmjlGHGosxtXNs2lGW1XAgiC5GZUtM0iy5rrqiMMaxWK3bHA03fUQSJNxvsxIuX1/zTP/2R84sz1uuKEBxt27BabzErBcz2GZZD0DsXny0tYSDGkBSFHESTvMaJzu+7paaW3z8M+CKLMylHkqQMfctMGPkXP6S++folJ9stv/3Vz3n44Dwqf53MTyKKdb/ffc9zNOt+jsdj3MpAnmXUdcvd/sBbT96lLEoSNdHtrujqHUPbMDpHUIaiXJOkJQG4vLrj2fNXNF3PBx+8w08+eMLQt+AdRZYu1gbvIpZDq0VFXrcD3juyJKeqVkwxOj3REtzooinW+8B3L57zbrXlk08+o97f8dFPfszmdBV1NIqry1f80+8+YQyaP/ntb3jr0QVGebKoR+rHIZbS0gaNw8ixaUVsOPT3pt+YKZdFJIqbRvHRzU7z4NEa8iSJsx8PwZEYhU8Mxpa4oBbbhDWC+1VBsT/WspIPnn7o4kZOfs3oZRMvAZMosAqdaIJWMbxypO87pBjxyxwky1OZRflYzjtZmY/jfQAEsFh73gTJ6fBGuEEIi0ZLBupyoLdNz9i1mCTBKEVqDUPXYrKUaRgpi4IyLxbdzTxwNkoxvZHlZuLgyvk4q4nBsiHIa+4HESFaI7olm4qI0wdHmBQ2UfRDSzeOTEGTZjaanAXYaK1Ux8xMLgXDKCp1593Saoa5Ak4tWWZJxzRKEaStEoKoxqQZk7bRNXHPTp+XJN4pur4jsfJ9jN6h3UQSkoWa4d9QuDsnkog5sLWfRoyVxKZhGri8ueb3f/yE3/7m1+RZLt9bmtA72SAH75bgUQA3TvcXgNF4JS3nFBcKzjlwUOQ51qb0Q482Cu0SSdOxwgazVlGrbkE//7f8+mcdUk+ePOLXv/gZaWIIfiBLM7JMAHR3d3cLRmW9XkvvbQzTKOiOdczZen1zw4uXlxTFmnff+zHnpxv8eOR4e83QtYx9J6rrvCArNqT5iqYbePbsOa9eXZMkCX/yq494/OCC4/6A1sLMzrKUcRoILpAXRawShMU8DBM2sSiVME2OZveaRAeqqmBoWvqYfzenkqzLCsaWn//0PYJ7l6A1EZzN118JwSGttnz8wfucn53IdifL6IeeEKAsVlJxZJZxHBkGx/FQo7UYQ9ebDZeXwo0yWhJSrKgGwcuwXRuFxsuB5EbAMfU9iYZVmZOjafuJ2/2ermvRSrHdbtBKSvC260iMou8HJuepkjwaZGUAb61dBswuhi4EwvcQJXLQZKw3K7q2wwcfD6ThjW3h+L0N05uhBhAxJ0ogax5pJQRn6xapxcyPqqqKrpUhdarkvcuyTFC5kzDJnfcL9HCu7JSRdkb5+ySUN4MS3rT/OMIizBTjuuQ8ZonA6rQ2DINYVLp+ZJhiaEYil4oIPwEvXyfLMiYnLdj8Zyh9v3WUuRBLdWmMxNOnacKxaeVwUf7+MzwK7kZrDdZglOTuiQxGWtM0SQXzOwwkxgqAT0E79LjgyQmkiXQ0IvuZFtFw1ymKPKPpey6vX/Ps+Us++OB93Dhiuk40W17Q30opVqsK703UTok3VdhsHpgP9oCOP7uQFyzH+iivRwjxoAsMg5AqsiwlzfIf5pD66MdPIIiYb7VaSX8fVachhEXHMQ97Za5iMFpK9v1+z93dnrcePyEvC1QYGOob+uMth/0OQEgCeUVebbFpwe3uwLfffcfV5TUPLk75sz/9NRZomkaCPm3yRpySpyhXqKRgTobthw5lFRqN8h4fBvLckurA8bCja3ok/NKgnJTPaZ7RHA4yy5JkA/px4puvv+Wbby8pN6d88IEwqKxVpMYs8oqiKJcNjyhzIwM9yfBMVNWKvpOy3iYW4xWZNbIG14rRT1gV0CisVoRpJEkMQzeiVWB7eoIPmptdzV1/FJRKIoJAa8z9A4nHec0UKQqzqlw4LnP0eaxovIrqarW0ckucOHIJ1PXxXmD4vdX3fcLtHOo6q76dc2KNMIauH9DKxFYmLMLVpU2Kv+bWch4VjONImiR0fY8pCob+3uQ9M53mA0FYNJGxxv1h9ab6XP4WFmmGTSwajVVGcMuIH3BoO47dQNNPhCCVYZZJdVykubSOk8PNjoM8x7c94yjLlSS5j/iS1y3QdTXGpkuydJoJ9mcYhmjGFY1cGluOaZrEF2dEX+TG2CGUwmAPXqQXhTWkeUZX1zR9t6Q5EwJ+sqzKanlGJZmo4+LBORrNzfUt77//vjy7StN0R5SSNu3k5IQ0zej7lqKqxJ84TvSjFCMOyR40xkQhq5iXq/WaphV3R5FXeH/PQPdeqKbuh9JJhcmRVJbNZsM4jly+ehW3Rpb1WuZRh8ORvhcHugQAena7HeM0URQF7zx5W9bQ1jH2Hbevb+WW9p7EJlSrNSYr8cry1dNnvHp1Sdt2fPjj9/jVL34KQUB6sq4XzvnoRrIkIc0qgsrwpLKqDg4dkANCiyDzrNwydEfa5sAwjNgkBUQfU5bloo0JyPx7mjzTMPLHT7/g5Ysrzi4e8e57P6IsEtLUkNiE+niMwlIRA6ZJQte2dN3AODgCmrxakUXw2NXVlfgfNTTHGjeKXkopEV4qJYkcbddSZvGw8471eiWSiX4UyqH3pFac+gItm422UWKgpQXqup7VMEdeKybnyZXMXsZpFPqkVhgN1hq0zuPsY2JO5pmXH133X4HPgicEHf/u6fs2Lk0cWSaSA4nnlhvV2hT/BnxuPkjmrycJNPdc9bkCUYDRwnuanJMEXROZRj6iflG4N/RN37PFLIeUbAEVswUl6oWSFO9cNBYrdnXDMEVvXfTZ9b3gdNw0onOL9xNDNwpO2hhSawhBLdXXfGFDTKdGDNL98UCWpKhEHu4kcsKGaWK2tAmiSL7enMAkVHaRfxBkGzd6jxp70ixlvSo57A8M00g/DBRZLoLXWQ81jISAaOW8YrPZ0vUD19fXvPvuE5kdhiDfG2IzmlOwVaxksyxHmyMQ4vcdCEqoC3JRaLbbDV1zB95RrUr8JBTdPJcAlRkz9IMcUvJNJjRNvbjNxYnv2O0O5EVGYCLPM3yAQ93Qtj3TOJGllnWlCFPLNHYEDV3bMI5DVJVX5GWF0gl1N/Di1XOef/cCazV/9Re/5dFDCUYw2ogj22iURzZ1RgIUnTKkeSHCvbGn7xrCNOLcFPG3hvp4R3Pc452TSPZpireF+MNElAZ9FHD2o+eTTz7nbldz8dYTnrzzjmTuIavvtq4pi0IMyNoQkLBE2cDEWUeAR6s1wzByfX0t1UViaRqH0kRgnVq2jcMoliEdfWVT1HgppWnbhrbrsUZRlpZk0vSjOPuJ7VobkTqASD18/JrGEEZPqlKZm2ipwIL3uMmRZxnDKNvEefg6jgNKpczx3V3XLbOnJUU4arhEKtDAGy0V8MaDmkMQaeU8p3rzIJnRJNamaHsfDT5/9nzwjINoxBQ6vg9q+T601stchjd+71wRSvUoQRqJFqAesaLRRioTyczzNN0cFqCijzKI4t8ajIYiS0itZuh7xqHDJAlJUhCUkAmEvnJPTFVaY40hj06L3k34fiKLP1uRSgtWtx1zuIh3XpK/vY9VipVtr58pChMhaHyQhUdRFFRVxbFuaDuJ8QrDPWLFmPnzbhf7U9e23Ly+4fTkhCSVC3ueZVltSNOEORpOKQVJ4OTkZNlAzwfbModWgc16xbdXLxm6jsRYunES9nmYFzWWob+fW/+LHlJ933B11ZCkkp5ibRoBZmMsYaEo5URt6oHjscFay+npllUhOiQ3tXR9RxPFgApBAdskx6uE3b7m2bOXvH59w9nplr/88z8hz9PICZIhaZaJqK5vB0ySIbNYgzEZ4zjQNi1DV4uhd3KkWYLRgabZUR+PMAUSmzHG4aLQH/3SQnTDwOQ1Tdfxh9/9kX7yvP3ue2y3G4yGNNGxSpioqlIgZXELNY4jg5O479Vqi04yFIquaRnHvdywIZAoYBwpUlHRQ8B7FzMIxUSrEftAnkkL1HWdbN+0IdGeVbXG+cDdXsI3jY2t9ihESK1Thj6CxhDF+NC26JjL52Ortsx37H272Lbt4g6YGU3zXGP29c0HgHPT96qVWX/2vQoparlC0NEPqJfDaU4eWYSC6f0B9iaD3TvPMArmVmkr/krzfX7TfDCFEPBKqju9/FnEw1O2gjLAlwfNWsmn8xMc245x8iiTEBgXD6DWoFUgSwyp0VgFLgpLp2EAnVCWBXQD48Qiw5g3g/M3YIwmN5opGp5DCDhrKPMcjaQwzSuAufWWBYGkOYdYCc6RXnMbJzq1XGLWIh0hz4QzNm/dk0QzuHvM0FtvvcV+f0cIijwr8GlETCcy7NbKgJH3uO96SX2eD483nCNFUcjP4h2npyd81vYMndBG+r4nSeTglUIAWv8DKc6d96y3G6Zxwo2exGbk2fzBNJyfn7Db77m8vsE5WJUFZydbEgN5luCGjrYVXjYKsrREayuHS9BcXt3y3XfPORwOfPSTD/jlxz/Fj50MNjPx9okFQpzlaZYuQjoITOORcRzEW5dEDnvUxdzc3mAVJMbS9iM2uf/wa6VI8wIXJAcPbbi+3fH7339OlpY8ef+J5MANPdvNmQxOo9QgOIct5M1qmoZxmtienWKTnLxak5UlbV2TFxkvXx6xFoo8wY1CDB2nCYVerD7jKL63aRzIrSVL5S2aLQnzMHaVVWitafqOaehJtCK4CfyIUkFmW87S9F3caE3yECIVw5z+4gmMboqDnDkqK1pNhjEevhMERVO3TFHxH4Ko5aWCmpbDYaaLzpzzN5lK0jIanFPL11WI2r0o5KIYJ88s83uz0tJayyB7GAEVCZtvzNiUPPQsIQLSYnpkizjnCs6bTaKmSjxwGpsYhqGnnyZ2B7F/pVYU9lqJXMVajdWKzGryRKODw2uFR6OVmHbHMZXtGML7yvKMNkoEiiKDVj6viZZRweBG2q5jdDK3ypKUPE1FQhKflVnhPTP/QQ7aWb0+uQkmqcj6rqXMcqZohXLBLW2qvAaGxGYM08jTp9+x3Wwoy5WIL5VUTsEL/G5JyFEsLb8QO2aful/oGRIyK1Fiq/WWyTm6VlK7XfBYBI2cZFk0N/c/zCFVVmUcUgN6oulagvJcPDjHWsPl9Q37w5E0zSnzTP7KLFmWsN/dsr+7jZaEQJ4X6LTCmJyun3j63XOefvsUbQJ/89d/zttvP+Jwd4tViv1uv+SjLcNbF+g6qa7GYYrZbC7eGglaG4IBm+Zc3VxTZEY2TJMTvIWae32i6GzicGxQNuPl1R2ffvmUYnvGO48fS5wWjrPzU5T0RxAPizQKE+eBcrWqsElGtTphc3pK03UYK5TPtq1ROLLc0nWGJLOMboxGTbmt5jmNnxw6evc8ARzLASX+LU3T1ByaI85P5HGTqL2jKnL6cZDQzt6RpgmHpiNLk5jhF9uicL/qLvJCHnpmeJtomJpGBq5j1DtNzjELZUOQB8O58Y2NHos8YA5wsNbGSlu/IRYVxG+eFZGsMFdj96SBefA8f+2u6whehKez0HXmiy9bPS9PlUJYUzKak1W+0nHA62N6jraMk4SEeecJynC9u6XuRwkTjYcjCrIiZZ0ZcmvJE7A6kKcZSmuavl/azyJPMYnkBXZ9v+jcQDa7IgKNuiJjSNIUrSVgdZgE2ZNqqTY3VcWxaRaj8dy2LdKLMG8zWUTPKkkjCmlWgYtEYD5IpsmRJAGbJBxrCVB5/OjR8j73fU8at79WG7q+QyvhZY1x7in8MR8/q/OdIO9HkqScbE8Eu922MU5tAK+YRtnuGitJUD/IIdXFfrntOhIr9MqL83PqpuPq5WuatmO7XsfDSVqssa+pjz1t16JsXEvbDGVzhmC4e33Ls2+fcfniFQ8fXfDXf/MXrFYFbnJstqdMo8DTlhWycwzjhET1aJq64e7u7n7j4ySt1iYZqJHr6ytWVcbUtzLML8s4lJUcPKUkDLMdJnRa8u13L/nyu0vKzRnvvfMWBo/VUK0qeYG13CAEL7RFN4ES/s9qtaJab8lXW07PLkSkuCrZjS3TcKRrdmgmrBHcTNOYKCo1TNPcdtj5XV8e0rYTsN4cZT6HDPRdD9PE2WYlAj8TKIqUKRiCr3h5s8NrRdN3pDYVRnWW0U8j+2PNyXbNnOXWux4XoWppKlXrknHoPZ7AMSYTo4hWDLH0zFHts/Bv3iTNc6fva37ccujMLeMgyADGaZIKKLx5O9/PlZbkm2gqn2dPs+JGhudxMB4P4ERbYZdH0iZI0KcLnm4aUUHTO0czDIzOC5nAaEY3oE0kLxiFcSPrLOVsXZFnmbTTyrKqBHy3ryWyqq73QLdsGmfSwvyrSkp5fYhK/2HAovDGMk4d/TSgk0RmUEazqSoOoaafZJRgrL2/EOIiJMR5kVy698/JjNmZX7v5Eum6jqaW6m6aJgnBGHrqtiHPctquheBYVRUowdtorb6nTZvfR/FzGrq2jweuZr1eEwI0bUPf1Qxtg/US3Dq0niQrhJ3/QxxS4yhg/sQmnJ2fYazheDhweXkNIXBxdsZ2s6LMLG7o2O/2HA570ZgQyPICreWm6Z3i2YtLvnv6lOZ45OOf/4Tf/ulvGIeO4/6A0nLLpFnOON5XKjJDShjGidfX1xyPR4w15LkcOHmekxclu8MeN/ZkiaY+7DBKU1aFbLOMBSWJtyFMko2G4cuvn/HdqxtWJ2e8+/ZjCqPktrOGse+wecrQ93RNKwGaWcJ6vWUKAyfnZ+RZxdn5Q4pqHX1tiuPulr6+47tvPmPsjlijWW8qsiylPh6pmYfL06IdmsZRUogjVcAm9nsK7flDZpOERw8kMbhrazabCmsTXu9rqtxS5hn7tuXYHPFOkRcZFSWHuqXVgTxPKfKcbhhw3lM3NVmWSSxTnJUI3qanH2U2Y819BuB8eMyWh3kDaKINAlgOVtFUyQd7lh7MNAUf7q01C3ngDToESgiowySBCYk1NEOL1qLBIsg8XugG8aE1IifQSlT72ohxeA6zdAHcKBvVdhho+oGm7QBJ6PUEoX1oxfqkpEo8VaLZlBl5lnJ3GHHBkSLqfXFQCIZomKtNPPuDzInm+U3TiW8xz3LRY3lBNOfGyJC5E2W6bCDl4ErShKAkIWbmY80iVZHdR6YT0tabuBBp6pqyqtBKM04DiU2WC6Ouj9ze3PGieMnjx4+pViKYtmnGWIuvVqoouQSmyTHzxSY3LRQD4VlZ6mODtpYQlwTaKo7HI1PboL0QYb13guoObpGr/IsfUsM4sTECJHPTwH7f0PcD1brk/ORESl0NXVNzd/OaYXZsa8lfC8qASnl9d+Dl1TWvrq5w08jf/M1f8t57P6LtjmIZkJAwuQGMwXvFMIifKcsz7nY77u529P1AngvSI88zrEkZesfzF6842RSUZUZT1yQ2rsKDjpVLEoeOgXHydIPn0y++4ebYsT0940dPHlPE4agKjnEc4jq8palrbm/uyPOMs/NTQHF6esZ6c0JZbUiy4n6rMw70zYHj3TX4iTwTZGsIgZv+jrLIudU6WkxEzR5CYOh7gdXFDLs5zjpE/dk4jdg04eRkS9s1aCYuTjak1tJ2HVWe0LlAbjV778HfpxYPEd6X2pjkEW/TOfSgOR4WguZcARhjYBhIbRLppyzCTmkhxuVQEaN0xjBMcWaVxHZDKqthGKOvLY2xXfq+VYnizVl6IBs9EQTWTR0fjmmpyOZhsBxkMphWWoEXucLcWs7WHdn4aVRUcQdl8Agepe0G6raLX08uJk0gMbDKDI9OSqpEWr2ySBhdwrEXKYQ2impVkQ6e3b7Fa7EcZVmCa7ulOs0yYZAtMg5l3uBA9RhrMYWW1m8cGGOoByiROeiJyfkorLQSzhkcfvJ4pfDOxWG3XC5FUkaJgLgg5qG31kLaOB6P3N7d8bt/+h3vvveEvCgpy1XE4kDdNqSJdCeKOe7NoDR0nV8Y78DC7prnmFme0TRHhr6Jpu77+LRlLvhDHFLr9Ya8EqjXNE14Fzg7PaWqMlJjOdzdcDweadpWGNnRZKm0YfLgUdztdrx48ZIXly84Oz3l7/+7f0tV5Bz3twxjD+g4aM2iQrZb2og8z9kfjtzd7QieGCSpYmBkSdcO1E0jw3o9Mg0CuJucyAy0kQwzFT1x4wS748AfP/2Sup84u7jgvbcfYrUn0aD8xDD2ZGm2kDHvbnekqeXkZINznocPz0nLFWlesTo5w00u+gY9Q3PgcHeFH1uK1GLXFUmacDzUBCdVQQgO78UXqLVa8vb092YPollyTjFNI5tKUn/briXXcLpdk1orNphJMaUJfpzIUkWiNWmSSXUQq9F5TjRrkO4DRMOSDjNv5mbPou3N8vvmD9gsopVD2SJ8IUOW5fT9AWPsckDNf87cJkCUXuh7rdT8587bxrmimOLWFGYlN/ctR4hQvxBweJSyyzBdKamk0PcNocxx5KFxwWOSFOcCzgfabgClSawMkL1zJAqq1FBaw6oQsWVmDaui4tjumeJMa/QjSZJTVop6nOjaFuuFtzXFz3Caigd11h4N/UjbSGWV5Wk0ecvBWkQh6zCJj26MlaxSYrPR2qBNivei/wsI8XYIgRCS+F4lix5sNvYvHCyEO9+1Lc5Liz57APNUKrj5tZ+/hp3xLkF975CZ20CQbakxlu3mRBYt00herKJuTkYVIUhF9d/665/X7vmRY12z2x1IjOHhxRlFYujrmm4c6ToZIBJUFG/leCURSeMUeHl5xctXVzRNzS8+/hm//ZNfctzdcbW7xdgEbWM4Y/QCjdFSM7cR3nv8JCLBrhVCwmazJS9k+Oqd49HDU6ahFde9CwStKXOhJ6RptqzHvVdcvb7jD599Qz86Hr39iHffekCqvMRox/SONBFdWD/0dN1AWZVsNisU4kGcfKCwKav1VuKzxr2IWYeW4+4ajfCvrdaoiEwRtG+IFchIUaRkaULf99RHUVgbY4RFpBUEj3MIGkPDuswZ+5bCwMnJhlWVME4TXTtQZCJunZyiynMS22LHSVqBacI5kTO0Xcd+v+fs9JRxGKJXr19avDerqOAlIWQc71fZc9tW1zUSh55FPItdjK/WmnhY6KVVFQB/QOLA7udu83sc3qiqQFhfLupx5ioqzHjeGGSgtcEHt8yzTDxgl3lYJFf44Jki1jYEifOyiZIwT2QAbY3GGpEMKECHiVVWkCUyO0zTDKUVVVWibmq8V2ht6dqOfoBuGGlHxzA5Eucpy5yuHZfXrI8BC0VeUBWrBf88tSJ2ttZSxuq6zAvMMMpAHWmJpd26t9wYk6CikdpHkoKLMpQ57NUocUAoWAI9bNz+HY9Hdnc70sxyfn4Ob71N3RzlUo3crTklZ4rtZpgcwUnWICEsZm+ljaQkB3jy7o949uUnDMNItUnphoP4ZT2oUXBJP8gh1Q+OEEayJOWtRxecbAqGpqFvWo5NzfQGrzvNc4xNGB3c7WteXr7m8uoGowN/+6/+ikcPz7h9fS1wPG0ERRyFc3IwScu02Wxi0sQgVUYI1HWD0obz0zO22w1105ImQtOsj3sxGHsPxpKkGWlexENFNCPK5rx48R2///QrVJLzzsNT3n/3AS7iKKZxoCjkJpvh/t45zk+38QYJ5NWKvFiRpDnb03PSNKNrGtq2weDY310SXE+Rpxz7VtC47Siq4RAWRIvWinVVUWQptdbs9Z4iguuPbUeZZzJjEaUTeZqJIz2xbFYp5ydr3DRSH2v58GUpCkWWaboxUKbSAqog1gSpSGSLM+Y5+0NNE1uSORFnnjHNcMFhGNDDgEVmfrKSNouubBZ3ztWX3Jj3kLOZfSSH0LTodWbzNfC99m3+/8Bir5qrSQjx993rrFSQxBoVZQcBvXhj5N9rEWsiI5xhHAnhfl7llCyF7i01nmEcJVg2NWwqi1HhXktmDC5m9B2OHWlWoG3COAXyomTSE/3U4FwgzzPcdI89mS9d5xzrar0kQR+PR/p+WBYK82xPa40ZNW3fS8y7D2QmijOtQYn1gnGa2O12GK15cHYGTtKnRRyLRLNrueht9P8Ju0rLM9d3PPvuG0JwvPXWW+gyxxpFkliCn9DWCjG2PtA3e1zfEuLGFWUIXi8GZG00ZVUtkiFjBHGEEtuMkFX/28+dfx5PqhnYPthwti3JU8XdzTXHw1F0NLH3Fwi/QRvLMAUOdcvTZ6+4ev2a87MNf/HbX2MTy831NSF4sjTBWENQdqmeREhYRvC/vLH3XKqE1WrF2dmGMjes1gWJ0Qz9yKtXLyiLgiTNMIhoTSlLmsqcqO5aAprff/o53z2/xKYlbz9+yFsXW/zQgHcLgbNp6qUd0lpTVRVpKpl8RVlh84rN6QM2m5M3FLUTqQ4cbq7xU4fRohhPEsNhlIrAJikueCYv7WvR92xWK/quwyhNEd36Hqni0jQRhG5u2ZYlibXkWY6fWs5O1yRGs7uT7327WQmVIrPsmp6LdckUxOjdDU5IAU6wJalNUdpydzhyuz/QNS0PHzyQ0IA3bCNy4DiK4t4+BPft1Jt/zdXLDKqDe7X5jBIB8VuKbkrRNo2oJP+rX3PbNwdQKn3fBsoDanGjgAV9FJPqqCZ3eKyM+Jbva8H3KrPk280sJDcFgkmWQ9dNUiEYE6hSw7bK6PuRYQhkhSJNLNpqjE04dA0pjjLPcIzkaco2l+QhcVTIIT7rxOY/YxpGdpPkERZFTh8v4ZlgML9eaSpzTAgCUYxOAmM0eZZjrcz3nJ8Yemkdf/Orn+PGgfpwZBgHgos2HXMfHy9q8oI8TynLnPWqZFUVJFYq3f3hQKoDm3VF2zZQyVLAu5HgRqF+pAlT5xnGCY9l5r/PVqWmkRkf6k3rk8I5T54n/z/v+b/IIbUqC6rSElzPcT+yu9tHMqTFh0BZlQSvMCZld2zYH1pevHrFfnfLzz58j198/GOO+z1NN4PRkIjr0dGNHd6J0nmz2ZAkaSR4Dgt62DlPmqRsNyXbTY53A7iR2+vXHOqassjJUul7x2miKAuyqpRQya6j7wf+6Y+f8/L1niTNeffJYx5sc/zUQJA4d5vaeCB6ikKQIHmWylbIWDAabS1ltWFzegEeEgNtX5OnhmZ3h59arBVzsNHEBA69CEunN6J+zjjBKJjivGEOn1QhsCpzIR8khrPtiQxyEwvBsVnlbKoyLhAazrdrNlWKwtF2A+NkmPLAqFagNS+u7uRW1RJ4GZKE/fFA07Qcm45pGOnGMWa8SSshbPGEaUoWCYHMgqbFDPumIn2eN0kFoOI2yEYPoGy8ROOkmf15zk2ktlgqiLnimiUNQJxN3Sur5S8XW4z7WVYIYLRd5iPGaHlAEF9f0EasQMyas3iIBkfwE8reyyKk1TPkSUKeJjin2dcD+eDwvqfaVqSppesmJiWUDW0MXTeAke+zjMZe7wNlKeb7pm2EQ9/1ECZub2/JyzKu7QN1XUfhpZFFQTdR5AWr1WrhNi3fowqkWcp2u8G5kecvX7DebHj46CGZUQxdF5ckdmnZQghM4yQylmHEJoKQSRJRy2sdbU5GESLOaBx6eq2wsUJWCpq2lfczePpxxKtAH8M4jLWCQ5plIyoq5ePrSqyufpBD6mSd0zVHmskvWN7CJuSFJFuEAA7Dzd2Bq6srXrx4hQqev/yzX3K6Kbm9vhLgvxUypFF6QaSMgwQknpycLsTGGT4/D/vKsuD87AL8hFIpt3cH6voG5zxnp6eEEDgcxa1/dnqKCyHml03s9zWfffUNu8NAVa149+0HnK4ylBuxxuLdGCsocW+XecrxuJMHTafkVcGhaRmnkSxfsdpuhcI4CJ97tao43l1xvLtE4UgTifbe3R3pOinjFYqx60UOkRckynA33dC2DTNziCCpJEWWgJcY7ZP1hjBNTASKIsePHU/eegLx583zhJNNSW7BjxM6NVBlaO3pvacvUtZlgUkSiAk3Ds/Nrud2t4uiypRuGCnSBBUCSZpiE7vQCuaWLs8zDodheU/mf/4mjXM+cMQzmS62l3t8iUG/cVgQhKE1C2TfpCLoZeB+r2p3bpLbWi/B5zJMV1qqKSQVJyCKcaUV0yQK+XtfH/ebqWhJGqc4/9SGxAp0LrGSrtx0ISqqA7eHI7Ys2WzW2OSKaXRIvoVHGY2fBrq4nVyv10zTQNM2ZGnGar1evHyHY4NzjvrujswmnGy3ANR1g9aQF6nID7zHWAnatLpAaRXb5CCLijyFYPDTxOnJKe+99x6ZUdT7HYf9nizLCCEs1pVZSrDfS9hJtdmSZmkMv6goyhymEedbggSy0zZH9DhI9iEwDBNp5umGEWMNVhua455yfULwgdVqhVeapq7FDK2N0F2UZ5yG77HH/kUPKaUAbZl8Jye7m+KGR8SRx6Zjfzjw4uUrnj97ysXpCX/9l3+G0Z6+bTFauDIS8kiMrlZMTtbWRVEyDAM3NzfLVmseJkqScU/X1kzec7c/0ncjo2PhCznnlv9+Nj4Gpbm8vuXzr57Rj56yqvjR2xeUacAP7bJGNUYU3OM4UpUFY9+ggyNNEqwSmuV6c4JJCh698y5t32H6gfruhnWV095dUt9dM3ZHFJLDNo0TTTtgspzgoT4emJy429MkYRxG6qama2vOz8/gWBP8RJZmYBKaY02eWrQOknBsNG1T8/bDDafbFVeXVxjlOD9dsalShvpAkRjKxLKuNPq2Y9/2rEPGLm05di1KycBfxS2qj0JNjGHyHofkCFprydJs0SrNa/O5ypHDwi3etHlDOH/N+XWdY9q1Nst7ouLhZK2s0StrFlV4GsMaxnFABwlTEDP09+PNJ2Q+1U33Q/ZZ0Kjj4N/M1h8v/r0wq9K1JDbP7aeJQ2Q7z7TigTt/TSGywrDvsU5xvatZnQ00Tc/F+QmXtw2TlwWBG0ecd/SDbKT7YSDL7wkASZosVapNskXn50dHXUvO4Ha75XDYE5goi4yyLCQZexjJ0oztdrv4RAOQpwnjKIuBhxcXnJ6coIPDxLj41WoV5R3F8n4liWW7rRgnT7FakeeyMZ6DWm2W0jPcG4eRrMaAJskK8qrCphlJJvYwpRRDhDyGIIeUNppjXS+XlNKKxIqlahx/IOjdbrdjuzmRyb9WpDaPcdeK27sD+7rlxbNnvL665Cc/fpeff/wT/DTQ1D2ynhbvlol8ofrYUlRr8qKUZIu6XhJ0Z8mBtZbHjx9H4+wo6vA4cEYjeWt9R1fXrFaSNiJyA9lGPH95ye8/+4pp0qzLiveePKBMIEwTxgo83hgtgQHeU+YpbuplY+EC1SpnbDve+/CnhKQkLyoub24o8pTueCQ3iuP1C9qm5ubyBVaeQNIspR1GutGT6QQ3eQ6HOsoxAse65vnz5+z3ex49OI/kCKkuEyPtCXkqgQBB2NlVuWK7znj/R29D8KSJ4Z1Hp5xtK1zXUiSa3BqSLKMdRjQTZW7og2JV5uyOexnBB08SQx+MteA9x6aOuBLP4GGtJZE5S1MJ1xiHuK0TL9wwuEXFPMsF5ktlHCeU0oKKHaRd9X6eJ7G45nU8LCQ4YFogeKKEvleUy2kRlkptHupro9HeLWwiFf9a5BhvmIvnamtyc6v05uRWKinn43xNhlmomOk3D8xvDgeOIxzagcOxZxgmur7DGkHeVFVJZlL2xwMhePpBRg7zMmlOoZ6H6GmSsd1saPsek6rl352en5FkhuAnNusVVVWK/ikmCyVJSpLYmJjtSIzl6dOnGK05Pdmy3Z4w9jXT2LPdbhd+1WZzQtf1lEVBlmdMU8/kvPwM1lLkOev1BmMsfhpRymKMIs9gmgaMTkjTIurCHOBlPhoV7n6Utt8mCVlZYNOM+lhLnp+VyC/vwU0+ejB/gEPK2oRhHMgTQ1BERrfi9d2O3d2eF89fMPYdf/1Xv2V7sqKuD/Kwx1vTRSPr1Hn6cSIvV+RlxYzZnVuCeQZVVRWr1UpKRiRpd4oaJBMFmtPQEyaR8M8pMnXbEpTm+cvXfPX0OS4YTrYV7731gMQ48CJj8N7j/CQGTCPmUTeJv6gfe4o8QxEEL+wt7e7It19+zWqzYXfYkRo4BhhHKFYnnNuU1Fq0FX2M2u0w0dc3DL2UwCgur17zzdOnfPPV1/z0xx8KtVR58kwOhDxRlGnKzo1xpS5buk2Z8PaDLUViGYeOMk+oipIyVTjjKZMSHTxdN9DVDcFNZMZSpJbtquTQFOzrfpn3KBUrFedkg6i1OPDdxOQcZSmbPOKCw0b8rIoVSd8Py2zhTduF/PsZoRK1ScyGYWlnYaYRmEXcJ4JSJS2G8sK4DxJ4KiEOM2HTMZtZpRqLserIAZhaiwtifg0qiDfTOYILcXg8LAP4e86UWJ2UNqJdc9C5kX7IlvDasqx4fSecqbu6Yxg8bSeYazcJu321XnOyPeGyv8Q74cyfnJwsItWZPrDdbkFJ2yaAOpbDs6pKHj264NnTr1mvVjx4+ICTk5MFE31yckJVVfdq9Szn9fU1ynvW60pEo0ODNZpqu6Wq5BmrqgrvRMckyUSOwmhOYmWWpgllDHwYhkHmqUHU+q6dX+uRvh1EUDv1URriFroDCO8rryqKckXTdLhxxCYZo59ITEJiU/aH+oc5pGZtTFCi0m36nrv9kZcvr7i9vmRT5fzVX/4FxkDT1PIBfEOvYq1l9J6AplydMMcAzSfxLMyc4XNZlnE8HCjSlDoyrAiQZilhSZxRrFYrsjTBo9gda/px5NvvLrl8vUdpw8XplicPT8m0rPK1lbZzmgYOxz15npKn0pIFrRj6lqIqZdOmM3720z8jLSqev/6a9cUFDy/OePHVV1TVGpMkHA8HCBP4gdvrG2wSfWhGorGHYSLNU2xQ7I8NX3/zLS9evOBXv/olZ+sNY1dLgksIVFnC+bZinScoJ8RG70dOzjZs1xl5ntL3A0WWMTKxrXKMn7BFSpkqhralmzqU68lNwBnNqBTtoCnyjGMjhuZpcgy9xMlrJYnCDtFupVo2WFVR0Lb193xg9wdPiOJASeYR83C0uXhZ9vf9EKkHblGhy2Vnv+cvm8WeSZyZTdMsS5ALLrMpBBj1tMyuJFVFCVE1tpsz1RNkluVDQCPDdRUUeL8QG+a/fJi1VvccF7k0Y/CpMSKoND56ACHLC15e3eKDfA+YeMAPjt3ujqIsOT09Fd1bXXM4HAA4PT2lKIpFYpCVEmRw2B9pmwZrbJRXdJT5lp//7KeRcCnI5PPzc9q2paoqqqpaKrKZwpklKSfbbfSWBs5PZUTStg0z6VRpGMaelSqWQXZR5Mv7KRjjOCA3pWy8p57ZfKyUoh8HEqNRiDl/mqTtt1oqZo+IsfOspGlk+UUaL+o0x8Ut8w9ySInjXXLoD4eG13cHrq+vaZuan/z4Pd598ph+aOl7GWwuB0qQbdvYD2ibYGxKXbey0k8sbeyv0zTl4uIiBiIIQM1qzWG/Zxh6xr4nTTOGrhe1slKcnJ1hjKYbevrR0Q0jn335Nft6Am1468EZjy+2KNejlUVps0gMmrbGGk0aBZ7Be8auY72qSPMMkoIPPvo1YzD87pNP+MmHPyHLEq5efEuRGeq7K4a+53A8iCp6GoXx7MQbOE09AVm9Nk3H3e7A737/Kd98+y0//vB93n3yDs1OFOxFIak6RZayyi2nVUJzMGRJIaLVdYGxinGcCHng2LV0dc07F2voPWVmqDLN1EwkKlBmBm0UOGgmT2LFR2cTK8zw4ONMQx74PM0wSnFsGrJVRRY53F1H3NC56A9jEQl675fNnhwqbuFNiT0mXdo8+ewIvcAYJbcvREi/XYbpY4SpzSvrEKb4MNwjklUkGygCiU1pdS8HUTzoFAFtLdM0oFDimIkPpIg+5eASnLJgg2axpIqzs2GaWGVC8kiThMEF1usVr48jHkXT9KD0ItkoV5XMZYaB/X4XIYWKzWazVInzQVFVgtkZJsfDx49564mmPdZcX16K4NhKZbdZb9isK7peRL/GVDx8+JDVakXXtXGhId/DMAzkaUpVlRAmmvpImKRFrKpycQ5UVRkPf4F52Cxb5sPzzNE5F+mqA24aGUcx0h+PR7I8pyhLpmjjIURJg5FDPTgXt8Ap6/UJl8++oOt6io1eFgZZlmHNDyRB8ATafuD27sDNzR23d3dUmeWXv/k5q3XOMPS4yaO1IUvTpYoaxhGb5jGcU8dNoBAnJY9NvvkHFxfRLNuSZhkKWXVaBV3fS9npZc1tk4ST7QkoQfIe65bbXc2nXz+ld4GqWPH2wzMenq4JTlatIMPF47FlHAfyJBHLhzY4D+3QkhU5NkkJOmd99oSvn12ileJnH/2My1cvePHsGx4/2DCGET/0HA97XAh00d/nEdVy3w0SzqnkZt7vG/7pd5/y7XfP+fCjH/PzX/yMZr/DGNA2kWFvCGSpJjOK03XOcZ/SO9lQlamYXrWSBObPPv+SX3z0nvDUU8V2leL7DgukxpBZSR5ZpRmdD9STpyor8rrj2DSCXFHEWZCgN9w4RRkAzGnN/TCQpCndQXLy5qQbraXF6V23JBPP1RHM/CGJHe/7bql03tzqKKWiqNBHK4usx2cJhMfH71G+ZpoYQjBReiACRW00ibWM7v734WWTZ4zGaEVihHE/IdFMSZrg+xiJxfftOMbomFQDq8yyWRViWUosWT5hNLRdTzdKEInRGq8kRlyEnjq+fvKzDkOP96CNRKCfnJ7KrDVJwFiC0lxcPGD13nvcPn7M4faOaexomyPTqmBVVZRVxWqzoev6eJDcEzPHUdrvuq5lPFKVUuXEinS+HEIIIrxcfl6JUi+rUtKqY7z80I9MbmC/u2YY+mVxMnv3QhQia61wY4hYJB2FtDHUw00orchXFfu6pe17zrUAKOftbZ6lP8whtT+0DJPnxasr9nc3vP3onF9//BP6oaNrWoL3i+N9vjlGH3Boht6Rl9ligVBK3Qv1lGJTVdxeX8dytsT1Pd04Rn+XjgPDZIGpnZycyFbGOXaHI9fXt3z29VNCUlAUOe8+fsBJqfEx/FD2n4G2kVDSLJWBsRsGJi/I3+3FBavTB+I58ob68paLR485Pzvhv/wv/yuHuyt+8tG7uKmnaRtwk0R8N91yixtj6NpOPlDaMPmRuu34pz98ytMXL3nrncf82Z/9lvp4IEstkxtII2nU+4l1mXK6ykgNnK5z2lh95kXC4Dx5nvHt06dkScrppsS5iW2RkFtD2wlWxk8DhsDZ6ZrGacYwcOgNeeIpMqGpNhG7k6YpDvFj9eMQWVMz11xmSc69IQUJb6JBwEfD6/1sJ0RRn1o2e9aahZddRE6TbFQlOSQQ8H5knBSTG+NhESsmo0B50jSTgITIM1oOOuLrPo1LUIG1opJOE4vCkSUWr2GcQrQZhXjQ3qe6SDUom8cyzyis4e0HJ5S5FalJ8JysC6oi5fXhgPMTk4s2GRWRLlGyIT5M+Yw2Tcvd3Z1UG3nG6YOHbDYbeT5C4HA4kmUZb731Dqcnp+xub2nqA9PQkWhPtV6hjFAwtDZUVSV0S3zkM2k0msPhQJbnVAuKyCxbSwlImb9XtVAolq1nlDiEaOrvuhZrDUlSLnanEDe296+/GJrnrMDZFziNHXixWa3Wa9q+pxtk0SURc3oJHP1BDqlnz64lzsYP/OmvP+ath2fRsiImxCzPSJJ0Ob3rtsV7sEmKtobj8RCHpTr6xGC1ktP/eNgzDbIhkRiscZk5JWmCc7BeryiLgoBskY7Nkd3uwLfPXvLpF9+SVVvO1xt+9NYFhRUwmYlmYtnu+IiI8PRtgwqBaRhQwMn5A37+6z9n1wVs2YvNxBqOd7f8v/7v/ze2JxUf//R9xqllGqS1s7HNkVZFLUEFbSsccGWgrQf+6Q9f8u2LKx48esRf/+Wf46ZBQhzyiru2RsftotFalOVVgWHibFNStxqbyYcyIWWcBCb37jsPMARym7AuLcoP4CYZUmp49OCEIYDqA9Mq5boeKHMrpAol/Y2xhizP6ccRFQTHoWLlO8VBsEExdQNq8rhhEqAWUin1/RiH4ILfFXPym5FWRIa9HIbeCTxtmiYknXjmHwkxYRyHZe4xK8KTRMdtnl50TjNqOEQVucDWLNMgqOTMWnxQpFaTKEVhFTqV/Lfx2DH4+TC9V6TL4SaVYmrgfLvidJVxul0tD9Q0jKyrjCLLGEaP84GqygnakucikxkGCWLN85yzsxNOT7fkeUY/x0sR2JyeSmDG0ON9oKoqri5fkdiE93/8IZN3HHd3dPUOa/RCpZ1bRRHYDnjnSRJF8J66bqhW5aIrm0mcxuhlS54k2RseSKnwu75D25gs4ybuDjtCTM2WCC+pTpu6Ee9okuK8zKfapmG9Xi/ss/miVfGwP9luGQbBGHsfol5KLzKSH+SQen19zcOHp/zml7/E6kBzbCQiWimKspAPUVQVT85TtwOrarXkpRGRDTPdb71akacJu9sbFIq8EB/TLMg8PTuLP3yIB1tHVZZUqzV3uwM3dwf+8MmnfPvskmJzzunpKR88eYhlwsa1ebDmnqKQCZOpPe5RXgbHRmsePHrMx7/5C8ZgaY43fPjTj/n6sy/4P/77f8ehPvAnv/qYd548ZJpGxrrBKsgSy/FwkGFjkpKmmTjJIyAszRJ2+wP/6b98xjffveLBxRn/5m/+Mip4B6l4XFRXR6V0WlqaW2mR/ThRlSUqOIoypRkGSEq+ev5asDRa6A5lXpAYxdgJwE2j2WzWApE7HrAqoUoM55uM22Fc4q2tFnKBj23aOMkHM89zpohzGQaZ/bnR3bO2syRWTWGphqZpjHOmgWkSM6uJCSVtWzOOot7XsXr207Q8QAGxLs3JNPOaXSQKMPsICRLpTojbunGKOjuHizq3oGLMeWblM6MUVZZSWR2rPsUhsfTdtNhLFttMrCq01litWRcJRSb8ezdJPLp3njLX5FbRp5pu8GR5xnpzgs0yTk62S0uktBZ9UmyvbJKSVRVpYrDGkmcZGnj8+DEPHjxgaFuO9ZEsT1mnGevVirvbEuUnxrFlvRbqhjESDZVlOcfDUVovoKkbzi/OBHcc4+SLLAfF4n0tCrUcEOKT7NE4lBvpu5ZxHDns7uQz4BxGaYJ3aCTANCtXMo8aRxIFaWIlIHQcovYrJzTRtqQNJ9sThilQH44wLyjMP+vI+ecfUk/ePudf//VvuXl9wzgpXAjYNBFtzDDS9EJrdG6i6weyTHxodd1Joqm+R4ScnJywXq+4u70hseJNCrGPThJDUZRL4MIw9LRtKxHOJuHFq2uatuV3f/gj3z6/otyc8vD8nA/fe0iiJIF1aBuyLKHru0VMFoJn7Kc4CB3JspSy2vKjj36BUylPn73gg/c/5Hf/6X/h//I//5+4vnnNv/6Hv+Oddx5SZhlh7FDBY2xCE0VqWSrVYzcnxCgBoB2PDf/5v3zO109fUFYlf/NXf4YKjr5tYnyUkcFu7OWzosCNw5JebIzB4igSzarIMEnK68MgOXxWkChJ5KW33VGqKOdRxtAPI93QYrViVaQYp0nVgEG2MXP7jJVFglIa57sYbWVwCDJm3gxNw4jzI22PyE8QtvmbDHJg0UHNlAMB+fnFKmNiBQ33sezAMoAPSxsmycizTmma5L2yWkyuRsfUYiPgwrlN03G7pJDgz9QYqixhZQLdMEWHfnhD+X6vkp/hesYYrDFkqY3E1Il+cBiTkugEqxyJgSpPsYkiTRIePnqETe7zH4ui4OLBA5JEyBZlWeCV5sGjt5m8I3hHkRcE71mtxC5DCDH0U0zoZVGyWq/RwXP58iDyFO3J8lyqzkGDi17QaMrPMqHljoMYiwNyoGeZzI2yVDbDQ9+jdRBWWt9TpIppaESIOg4choGz8wt536z4DqdBKCNd00jGgRu4vrri9PQMrRV1XQsrLHYFaT6x3q5BK9quj9Iix+GwX2QvP8gh9etf/oSb168li0wnbM7PsdZy2B+4PYi1QzLHhFej/ETb9Ox2B7bbNTaTmdJbb73FMIyMw8iqWjON0h7tdjsA5kCCEHK8F6bN6ekp2liuXt+y2x/44yef8ezlJeuzBzx5523ef+cB2g0kNqVpG6o8FxwIUJUlPghyV1bigxgpteXdD3/O6vQt/vDHT/jxhz/h9eUV/+d/9z+zrw/8q7//Ox6/9ZAizwjTSBj67x18VVUBgtKVPDEnuJZ+5D//7nO+ffqKNMv4x7//16TW0hwOBD8yuIBWAt7DaGGZ24QhbmzELBvIM4tSnrLI8L1nGI4UmSTtPjw9ZVXM6TCeJGjc3MKgqPJUwiM8tHVPYjXWyMbNRm9VN0ncVZ7JzemmSI8I4qFsI/daBJmCtJ2JnLMMYf71pkJ7Fv28eRDIan1YWrkQX7cQ/6yyKGTlP/9777Gppe+76CWTGackIsd5Wdz29a0ntSlFltH1gvFNjUZbLajmVDGMIiC0SpY6hEganblaqAXcllqLVYo0lcDLw7EBPXGyKeXPB7IkwaZJZJnlrLdbjDYLwWG7PWHWi66qDWkuI491tkLrBDdOS0UjX1Nxenq6ePTGrmcaBhIjr5NkWGrJ0Uslgr6qKtCK4+Egh2FVkmWiUB+tWUgQs3/Ql466aaQj6Aw20WRpEukSSJUTPIlJSYwlrXKyvGCaRm7qK7FpaUOWJOgsoVutyWLUmPciCi3LkmEccG6UHANtOURBZ2LFhZAs9NYf4JB6/fo1BIVJUs4fPsRYy+Fw4FC3EoLgHF17RKmE9WpN0xwJwXN+cYZSniS1PDp7xIvnL6mKgsQqQZyWOcfjcSm9F4phNKyu1msmD8+fv6JtGr74+ku+e/6KanPGe0+e8P6TB7E6yZimgbOTLU1zZJwmyqhLmXoZbtfHI1WZkRUVZ4/eQ2crnj17xgcf/ZSmrvl3/+P/SDs6/vYf/5G337pgVRZoHFPfkaSWaZwYhzEiS6QXb9tOjLOJYXATn3z2NV9+9R3WpPzj3/9r3DTSjCNd35HnlkTJaGeaoMhXDG7CB5i8Q2tDPzms0pFWYMnyjHoSv9yqyHn88IKx78hPzxgc9IMHJQprADf2nJyf0A2Ow6HFmpwqy0itRymZ+/VTYDzWYp2QlAeZ64wCmmtauTF18PhxYAoeZQTWpiPM7n529EaUVByqz+bgeX6E93K7Rz1OksphObfiPsqRbZoyDcPC1HJOtsVzdDkI9E0QiiKHMFqhCRRpyjQNODeQZrkonXXKthSl/FXrwHkSpXGRjKBRpDYRjEisviRXz4J3BOcwieXy5o5VlcZMupx2dNi04OT0FGPNwvUGsWmtVmu8n5jcRJbKhjBNLBOKvCwxWhEwlGUhwtRplPe+GzBGoY1giQ93koknVetI3R6xyZq2reXyyHPqumacJlZVRZJlTM4xDmLPqaqSGaSnrYmb9zndxjEMYK0ALAWNtCVJU7I8oW1r6sNONGdjrHTTjGHqCTF+DcWSXD6O8hkdxkFEtcaSJhnHY8Ocfdl2Ij6dD9B/8UMqIGvfrFgRlKFuepxXVNWWu5s9/dBysj3FWsF5bLcbUF74THnFer3m5vqG1BjOzzaMY0uSGo7HmnF0bDab5cM+66aqakXdDlxe3XI41Hz2+Se8fH1DuT7hpx99yDtvXZBatdhmqkpA92n0nQ1duwzM27ZhVZWcPXjEycMnbE4fcXV9w+b0HO8c//5/+p+4Ox74m3/zNzx6dMHDi3MUnnp3g/KBtutpmprtZos1mrbrOB4OCOFACAmff/YFn33+DSEE/s0//DXWKoZeDvA8z8gSTWp0xNtIvDtuklV1kDnKFECnGaPzlEUhc5+xRQV49PCCEALVqhRm+BQY+pHEipXETwN5IWyrbhSfJEbD6EitJk0sWZLSdk1E0LolgEFmVF4ih0ZFfTxQZimEib4bsJnCDZBkolH6vk9v1kqNhP8q2HOujmaJwjy3ebPFc5NA2mY0z4w2mRctIR5OSWIFZxt9fQBGgQ4iwCyyFI1nW1jafhLgmw4UiSJLDHbwOAPGKqZBAHh60XlNaFXI18kTEiMXhVIKDzR9S5qVImHQFlNWVOs1SZpKsGaQQ3m73WKNYnBeWmirSFMRw67KFdVmI+k0BIpCfKdpkVNGv1vXNeA9Q1vTdy2nZ2eLF1IZqaZcfN9SJSxxFKzKUqQNsb3u+p5xnGLuXYJ38noWZUmYZPySpJYkkxAxNwmhs21bhrHHWqmyTBTyyskigt8Q29oszynLMl7WLXmWExBIIt5Ex0jDOAwUqxMOhx0XZ2fyuf8hDikQA6eNKTBWWybvePrdM8Zh4P0P3iPPM0IQxfLV1SUAZ2enlMWacZzI0oSTzQlFajAq4+Zuh1aa1apahGRN01CWsv481A0vr+7Y7/Z8+tknXF7fsjm74Fc//5h3Hp1jteiknBNrTF0fZHCdplG6P9B3A69f33F6dkpZrUmqU7YX7/Ds2TPefusJxhj+w7//P3B1dcl/9z/896RW2iU/jtKKqkA3Tuz2B9IsY5gEUjYOg9yeSrQjv//0c/742dfU9cA//MPfSiJw38vGMwuMXYsOCk8gKUq0l+SONJEBs1KK0QVcMPST56TM2J6c4JWhPtasq4IyzyQ9Jg6hlZab206iHdMmPlTOkVpFfWggl7YlS4Sbbq0hsZagJauuH3pROycJ/SBhBEYpYawjFEY3jiiTiIAvWl3mQ2imboZoGH+zuppizPc8m4KIXAkBHxco8yzHRpDeopOKs6rZe+bcvfXGaCUgQe8EzmbAGvBGgw+cFSmNFkicVoZVkXJSae46h1NgvIy0p1HmKNZYNEJSSOMhVWSWmVMF4CdP61v5bxNLUq2oqhVFUcbKEhbIW6xqvZvQyOWOEtic0fL6z2nL1lqyvMDEylJ5L/aTvmOzlWH85eUl5xdnFHkhoD4nW94kzdjt9hitWK9WcrCMQ3yf5L0piiJeCLP9KMEkkg2ojSbEz9IMFOz7geOh5fzhirxayQD+9lYWTVHhn2cZd3d3TOO4pBMTgSwuhoSCxK81h2vGYWBtrBycQWxYP8wh5aHMCxSBtj7Qdp7Xtzu8h7fffod1taI+7MnKgt1+h1KKi4sLWX+mGb4+cna6FmlAotnd1figKPJclNBRi7Naraiqilevd1xd73n9+pIvv/iCu/2Rk/OH/Olvfs3ZtgQ82ljapqEqhflttaGsRIszDAPDOHLYHzg9PaEoV5w8eMKT93/G/tjy8OFbBOf4v/6H/8CXX33J3/7bvydPNGWRkVnN0B0krr2t6buGrMgpioL9fo+bnFASMwG8ffbVt/zhk684HFr+/h/+ju12xTAOcmjowDi0GE109Gcom8I0Ua3X9J0kPY9tIBjN4BTBWrYnW9J8xavLS4o8Y3O65W5X0/cjZSFQf6Nk0EwwMAEEul7y6V7f7BjQnGxPURME15MlFms92g4YF8mLwZMXKWMMXTWJZvQjQ9+iJgVBWgMIGNFwf2/eNB8898nGMQAhPoBvtoWLT9MY2rjQ+K/X0ZIrSFSlzwwtYusn2XUCVwODJzVgbaAyCp0IU73IE1Kj8UoExHlmWa8spwNcH2omY2nCQFCiep+8IzMpWisyaykSJYEWkxhp5QBLmCLYLUkyytVGfmYnB7k2Bq0Q0kFkuwfvmcae4Au0yUBp2UxqjdKatm2l3UV+rjwvmbRmd3fFer3B6oQQJur6yMOHD+5DUJUIRIuyZHd3S2IVWS7i0okAGoyR1vTelK3lPQ5B1PLWoqzBRy2tSRJUN9H1NXm1ApXgvKIbHHMmZLXa0PVdlBPJpjCxdmm9Z7GmUA9yTrYbvrp8LtFdxuAmQeHo8APxpObDoxs6fKd5/vIVeQxD+P/S9qe9kmTbeSb47MFm8+GcE2NG5Jx554HUJSmKFEmJvCIpSlUqFOoXFlqAGmoI1R8aKFVXd0OoRksqSRTJyzvmHJExncknm23b3v1hmXskgQaaBCoPkMiIHCJOuLutvfZa7/u8r66vUFPH0DZsb28pVssZOXFgvV5j54TdISiismDXDHgVMY49ZLDf73HOiQ8vTXl1teHV7Y6nz17y5RefMYyOBw8f8Wu//kOSyMzWDBFzxnHMOPRoDeVsvHRupGkq3Djy4P59umGkXN/n4sHbtMPEcrnCDz3/6v/0P/LJZ5/yT/7pH7MoU5R3REZx2N2An+jbln6OeC/yHEFeJLRjhdUGMHz+9Bk//enH7HY1v/f7v8OdO2fs9zuB8CUR09gTHa0kSpHlxZwmIqgOwcFoxqhDUWBjTbawxFkuaboucH62Rs2eQPFaQRTHFFmC6lsYpRUfxwE3OW6vbvHKcu/hQ9pZ15IZQ2wUwY8EL4zqyY9Yq/HBnD7AbvLC+goO7WRuo7VoaYbRoWN/KlCnQfhchL4qIjwWsqPg73gKT5OEVRxnkF3XkcQxQevX6TizxUSCReOTrkcGrn6mJ4hX0ChItCG2mmEaSCJNkcYQefpxQs3fU2Q8caSJ44i67wTr8hVNlxS+MItAA0aLeyBMk7C+lMKNAe81cZqRLxYEZMV/FK7m8+cvKE4zVas1WgWU8ig8fdcQpykaweGY1EiKEDLkjq3F2pg0skRWtrfRjH7OMyXC6cnPuGfNdrs9Ffvja3yE00VRjNZuFlAebUkapSxpkqOjWLbdSUrf1tgULtIMbSRhOosyIhujlOjUBucY5/foCDw8Yo6PwRlGaQ6HHYtVzMX5GR9NjrYTaU6SpKfZ3ddSpHa7HcYa0IbL6w1JlonvaRq5WBVoLf4mZY3QDYLcuVfrNZurS3bbWx48fJPbTUvX91gj151+RljkeY4xhpvbLbeHjs+/eMbtZouOc954cM6vf+/bEu2jZEPQ9a3ontoWNeNzRzfS1DV93zEMHWWWEyUZ5cVjkuKcuuk5WxcYPP/yX/6PvHz5kj/9sz+hKFK8G9EqzLaCQFUdaDtJoV0uloyzfqhtauLEYuKIL5+94qc//5jr2y3/4Hd/i7ffeSRXs8UCQ2DqO4yZccBpQpLOkdZaiVhy/jBERrNarYjtioyJReZpeokwWqyWEtjZNGRphp0pikewHs5jpgBz6sl+d6DrB4oyw/tA09SSZBzlxNYwjccgCIfRVtbrQVONNVprVssFenLoIAfB5Ab0zALzfmAYxLZ0dAC8Vjib/5/F68idAmaR4fHKJtBD0Wk5ktl9n2XZyT92LH51XZ+Qxm4mVVhrGHqwWgusD08eGfI4YplnHKqaMo1IrCGODJH1LBcFlQuw70V9zmsSaWSN+PyOYMApYLVFBUWepUx+YvSKZnCkXq6KZjYFHzedX/UohuBRSPyUChD8xDh0oDRdO5GkGaODzbYiTlOWyxUhTLTdOKdqB9K5Ey3LkuA9h/0ODafXvG1arq6uyLKM7Mion4uAXAnb0/M7jj3OyewyyyWe6ugxSrKSw14M+cELurrv57wCm+CGkThNThKN6lBR5IWIQP0xyFXe0yiKqNsOGzdE1tK0DYfDgWEUAffrdKKvoUjFWcwUYHO7pVysqJqWRR6zyCLZgljZxqyWa/bVngcPHxH8xM3VK5q6oh1G6lnDo8OECoaL8wsWRQ7BMwH7tmPfjXz8yafc3lbEWcqde3f49ocfUKSJaJ1GEfqVZcl+uyG1hrwoMVpzOOyp9juUgjLLhDi4vMP6zmOapp8DSgP/+l/9K/aHPb//h79PnsYYAn4aqbua0RiGvicEUWYvFqs5hmiQ0yXLiNOYp89e8tc//4irqw0/+tGv8eEH79I27SwSVWA14GS7Yg2TV9RNI29iXRNCIE1TejdAEKNzHBliPVIWhkgNFIslBM/t7Q0oUYgba8gXkn04NA7vHGaaCG5gGj1NN6JtTLpYzEGfMLYdnfLEWuYnBMHnmpmK6UYx8maxJdKBRZmh3QTOyWdeBfCCgu1bmcvE+REnq04d5rEYvU6H0afCdLwaHtfPk/cE95qqgHrNSm+aZp6rGZmPjaNcK2Z5QpwkIlxUCm0NcWTxQydXCQU2OFITiBPLapGQJCmNchy2jXxWlZYFz0znPM3LCBjlaOo9hAKbapbLjKkW9lKSlSwSS7k+J8uF8ySIIGYUrwRlGKtFTOwll0/CQcAhOGxjLWka01YHDpsti4uLk8NidCPLMqfa3TIFIZuuViuhaW5vCZOflzVi+G/rhjzNhKipJEWHyZ8OiBMhQjQkVNWBcrkWgkKkZkSNdKVpLFqtw4xSaeqGaBlhk5w0y5nCBFqRJTH4kUgrDIHFosDYFcMwcZaXPHn+CpsWvP3hNwn/9n+mqhrc7LTo+04O16+jSO32FXU74bzCtwfunp+RpJbEasbB4ZEParE+5/7jx7x89oz6sMUoDcFiTMZhtye2kKayxk6SGIxiGDy325qXVzc8e3HJze2OcnnGvXsXfPjO4zknb2AcRrIsJc9T+q4VFbkRoL8bB25vrrHGYCPDpDR3Hn1AefYA76Eocvww8C//9f+ZEDx/70e/TmI1SWREEasVyVxAjmLDO3fuMI6jzKGGniQV4Njz55f81U8+4ssvX/H9732bX/v1H8jJ7ycRyhHmgbHB2IgoTmjbjjQvgNcPdDxD5RZ5jlFw2N6yWEaYJMY5mQfUhz1t1VLmJU3bsL6QGCoVAtrGoj4fK5zX9C6go4y8KJlcoKsOdGOg3rdMcUAx5w7yle2b1rMZVVbGKoxoHSjyGNdPTM3ENAUhsNoYP0q6SFYUJx/YV69px9fuOI86Fqoj1O1omzmqsYXsKj87FrSjRzPLslNXdupYQhDltpXtm0FU4mPwWGRbGhtHWcY4FGWW0E6w2Vd0nWwBk9TiekWY5JosnaCVTZyV4jdOnnEY0XYWHwZNkmZk2YLl+oysEC65sKKEHZ9lCaMbGft+tr14glYELduzI40COAkukzQlS9PTFarvhzkSzOKdozrsuTg/l2vjbGJXSogNYfI0Tcv5xRlHWOTxQDiq/o9/15oT0XPsO5lB8ZUucGZe6UlonscOsx96kqxgUlqWKV2P9gEbWYp1iY1jApZ+1ERpSe8C5xcPSLKCs/MzsjzlUNUw24XatucYd/Z/eJGK05xx9PjJcedihQ6OrhvokXt6lpdcXNxBEXj29ClttSeKYkbnafqeJBbB4vJsKdeO4IU/FDS7quXzJ1/ys19+jI0S8mLJ40cPePfxAxHzaUvftSyWS/HUVRWRVsSR/Ni5kd12Q2wtcZJikpQ33vqQ1dkjPLBaFOw2W/7N/+Vfc36x5r3336ZME1CBrm9gmlDI4DjMvJ88z09MoL7ryLMYbS0vXt3y819+ytPnr/jGtz7kN37z12bdyiDdiQIJIpgkZipKiKMMa+NTEIPMWmT1m8x86f32luWyIElge+jp3fxB7gM2Lnj+8pKz9Yrby2u0jeaioUhMwIwjzgU8FpvkeDT1fsc0eW73e263FZgOV8hbrq1QF0IAP4iXTikjqmEmwjiSpJY01kyjZnBCkJjGkWkKQHp6KL46jzqGKRwLkjyNr+UKx2vKUUTp3HT6uUhc4lOQpZ7/+RH/8nrwbsRFH4KEU2iDCp4sNrh+kEWMCpSRpw8KowUlUhQpvZrY1h1pGnPomnmLOM3FWqFUEO2YD3g0bdcTWYs1lq4fafe3xD5QLNc4l5660uADsTX4cUQFj3cjRisBByJq+EkJ5uh4JRz6gf3+QBynX0mwUaxWq9OPvZ8wQFtX9Eq6bZUkQgpJU/meuu6EzZbtqD95Go8Zhm3bkmUJSZqe8MnOOTQakwq/zWhzGoYfQ2CPBwZKCAfKT/hxxGpFnhdkyzU6Smm6gXpXQbuj6wc8inLtyVKR0OwPByY3EiUp1Rw1/7UUqe22oswzHj+8hzaKoR8Injl+asV6fUZV7dhc387R5BGDCzNOFrx3nJ8tyfKUoZcI6QnN9fUtH3/2hCdPnxMnGWma8cG7b/Ho4X3CJKI0P3kWyyUo6PparkYGDocD4+jY3N6wKHOsjcnKNffefJfF+h5uCty7fxfXDfwv//Z/5r333uXho3sQxpnPNNJUO/qumc2ywmxaLhbsq5rDfkddVaxXa4yJuLq+5Zcff86TZ5e8+ehNfvT3fiC0xcmJvig4jFYyEDUycA4oghLEWDSvhtMknXPKAonVbDc3lEVO8CNXuwarLXGcolRPVpR0hw337t8h8p5Xt1v6EPPJZ19y7/4Z56uEO6nGJAmjF5RL1Ympsx0cbe/QNiHSBhdGjJGwBefk2mNCILKKrp+o65Yk0WR5QpZF2DBwscqpmoFdPRCmSXxvgVPxOEWdw0lCcJxPHQuZ1KqvRhshYMDgZ6zJ7MZPEg5VhZsmstnDd5x7+eOaPJIdY2QU1iiS2BIbWKQph2nA4rFhIk9iVklMtohpdETnFTaeuD103FQHgmbewk2n6yYIMxyt8QRGN4GWeUuSWMq8oJ88zX5HN3rOzi9mM+4Ek2PsG6yNUfNcZ7fdEghc3LuLieL5mi84HDdB23ZyRXMTkbZ0dYuNZaNn5gKqtfDNoziGyZMYKz7DKEHplmGUba+xGoJjch3jUNN1FZMTMacPktvog9iw0iwlXyypt1vaw5bl+QVG6/m5VHR9h5k9ht5NoCG4nkVRsC4LQW2v1mBzqrrh2ZcvGN04o2gS8nLFYn0GGPK8pKlbxsER5zKvKsrF11OksiTh4YN7MtxrOvlQ2pj16pw4SanrSq5Fk0cpc9IvCYHRsF5LCOZhf8AmKcPoeXl1xaefPuFms8ckGbE1fOPDd3l491wefC8PxHq9lsh1N1IUkrV32G/oupaqPnB+fi4prTbmwZvvo5OCum15+PAh+92e/9v/9D/x6PFD7t67YGhrFmUujOehwzuHQs9+uomiKAkIUbNuO/Iixxi43W75xS8/5fMvnrNarfi93/tNphnSFvyEVkKCjKylzHMGN4KSa8TxQZ1mvEVsZXOTJhHVfkc2G063+wobWcrVGW4YSG1KrC12MRExkYSBPEv48tmeX33xiuXFOTdXO/K7BcrIhs6oQOs1PkA9gY8yYiNPRWQ0aRzhx4HJeYLS81VF8g9tZIgiQ5rGZKklNxaNpK0cmh6lkbTjscd2HavV6m90U8fCdPwyxghw7iv/7tRVzd6w48/1fA3qug5tJDD2OFM5rtBDEOJBmDwGS2INeaxJzUQaaTqjSKwnT4T4sFqklGVEbwqszdg3NyeawjT//sdCy/x9ivFZidhWCXYGL7iYRVHgdEKP8L3GcRSyxExpkPdZGGlaaxarFUmWiQG9G2VeZazMt9IUvT/gJ89uu527DrHt9E138ibWdSXzOK3BhVOIhJ2v0OMoIxANTEPN2OxRbkT7AUOPsgnaJizKBUpFtDPS+pio3Fy/wo+SQ6C8qM+jVGLG+tl3lyUJ2hpMFBGlKXm5pB89N7c7/Oi49+Ah0WyR6ZqG6rDnUDcMoyMrStpui3d/M0j2aylSq0Uq24E5d81ay2p1jrGGw2HPOA7sdrs5TGFuHa0lja1ELkWWvhXVbt2PXF5v+NXHn9ENE3FeYDV8+4N3uViXeD8yOVEoLxbL06m9WBQEH6j2G6rDgWmauHNxH5QlLUruPXoLE6X4Cc5Xa5pDxf/13/wbPvjgfe7eOcNPI4s7F7hxJIwt3g0wD3/l6iHXiqqqGMeRs9WKLE24vLriZz//mE8//5JyWfKnf/qHjENP8EdvlSiOrbWzlgiUMlIE5u6pn0MmojgCJEiha1vqqqYoMqrDHmUNi9U53kOWF7i2ZtcM3F5tuLvOub9IKM/v8eKnz3jjnbfYbLd8/717eKXZVx1DP5CnBY3XKJXgrEElHj22xFEgziKSUQSwqK/ER80P52pVYrRwxbM0xvieqR/muHhB8kKgHweK+XNx7Ja+6sc6zjm+uuk7dlenTV8sG6Yjr+jI1v5qgu84D+6PCTDHudfoBiY8iTWkRpFYhQ4TeRazTKBMI4osZVXmwtufIkaCsKWO2ygUbdvMIZt2fv8kwTkoDWi0jkBJB6rQ2DhFRxk2KtBxgdYCF8zSI8O8x9gJryTmfrVaY2wyc6wG8rwgTlISK9jgfhgwUUSapnRdJ6woL+nDoupnFjZHZKnoD72fo+K9FMnJT2RJTGINTCPMY4Z4zgGYhpYoBPpeY2wmkpOZ+nBx7x5plnD57Evu3b+PGzomH8iKckYii8SgWKxJrKU+bGiqPeMg1I1FpOi1QUeJQC0nh7IJq9UdlmdnaDTvvvsN/vq//Dv6roMZVvi1FSk1e52maRSVc5xQ963EQNcN+/2W7XZDlueiqo0siyKlLFIMSMhBlHF9u+dmt+MXv/yYMSiMjUis5jsfvst6UaBDICBQsjiO6fqGLMtYLErB9e537LZiR7m4c0Hwijhf8vCtt0BHdF2PCpq2aflf/5d/y3e//W3u3bsQq0IvsP801Yzdgao+ME2eYrE4PSTb7Vb0KnMqx3Zf89OffsRnT56RZil/9sc/RhHou5EkiVgU2UyAjNFzNLXgNCS2KkxhdsfnaG2IYkNkNF1dM3YS0DD5iXyxIijF6PxJeHe739PublFB8fz6wN3zxzBplus7PH/xinfeFXzy7WGg6R1JumCMCox2TK1jHB0mVcAkVpAwYb3DzZygY8Hw3pPFCdZ4AgNZrCnzBBzsqgqNgAKbfp4PDgOo1yTOv+Hf+4ol5khydM69tpjMRcI5h543UHEcMzjH/iAiwa9aZ47JMCoEkiSlbmsCIj2wSrFIDIkKhGmkiBSL1JJElsgoIi0+uNhYyhA4W6QE75jchDUa5+RBFGM3RHYWGs4uEK2V8LU8EBTVKNy0rFih5wQUUbVr4iShazu0jUisJE3LP08ZJy+BDklMUIrIxqRZQV6KoDVOkpk35QlK0Q89fVOjgohnxckxQZiYnJAOxvbA9vYW5WUrO3Y1Ta0ZZyKndK5mnrlNTENP0/YoJCq+HHu0kaDb9d37bDY7hqbBJol4Gee5rNHy35vIUFd76u0NbSXbvyhJWd55wL033yNfnXP58iXGSFDqfrcTo3ye0bYD49ihCMSJLBe+liIVxRJRtCjXSMiCbMU2Nze0TcN+fyAvcvH0xOJ9WpY5KjhAo6KMw6Fhs6/46c8/IigZzpVJxA++/Q3SWOOmkaDlNDvaZIoiJ89zNptbmqpm6EVLk2ZiJciLFYv1OX0/YWNLuVjQtT3/9//H/8r3v/9dLtZL4siIjYVA1zZMY8vt9RUhaMrF4qRSv7y8ZLvdymBPKXb7A3/905/y9NkL0jTlv/nnf8aizNnt9uIiTyPpxkKQN9RKxNc0yVyqqWU4u1gsXgvy8oLIGAwGn050XU+937NMc5JU1vpZmnL16iWLcsnUdzx5+pS7yxVZXvDFy2vquuHh3SX3zlfsDy3btmdfj+hWc//+msmNcmrm4IcBnZa0zhECxErYUc7JlWMcR6zRmMhgcBRZwd1VRpEYglP0ScQ0jSRWU/c9IAk6wzAwpYKIOUarH691RzHn8euY8hPNA/Cj56+bfWXWWuq6PpEkX8+geI31Na9nXLE1RIklZmJdRvRNxziN5ElCagyGQDk7B7T3GDOxyGMeXZRcLJc8vb4kNgZm65Lk7kkHFkeWMHfDxhqmriMrFsSLc5b33iTJFyc/IYhtJomj+b+3IgCdwyW6viMuChbrs/ngtaduzfsWG0UslkuSOCHPc6IkZux73OAkV1Er1qsS57r5+2wRbRe4vmdzczUr+4+hncNpWO6cOzHoJbYdgjKgRBsmgMHxJHFQIbDru9nLKYbnozi0a1vcoEBbTJKTKnGGuBBgDse4vXzFzeVLImNpuwqlLTbSGAP97CEMM3WjaZqvp0j5yQmCIrKS2tqLwXboJbZmvSjmFb0iTYycSiqgTEznYLc98PTpMz7+9AsCUm3PFhk/+NYHxHY+vZxEcB/VrEkSi8q96zjs9zSHmjgRN/rQjygbY7OSQ92yPr8gL5eMTcv/9v/8f/Gtb77PnfMFCk/XDidcsTWaw2aPUnB+fsFiuaRrG66urk5iQqFstvzyl7/g+fMXoA0//ic/JokMu/2eru9IUkMIjjTLyJMEa+QUm+bucBgGyrKkn/nsR9O01VY6nCjGxoq6G1idX5BlCW1Tkec5L168IEtS+mFEG8O9+4/Y3Ww49COfPHlJN4784FvvCoVimOi95rYaWJytOPQTaoI0LnDeMSmhX1bjxHkek0WSEBNmugBKVvrD0FHmKcvEkFtDnliqdk9sDW0YUD6gw0RiDftmLlKTp+8H4HWKsfpKx3T8mqZp3ia+vga6cSSyR9rB69mT/so14/jrRtYSWYmEUkGy9YwWDnlqYASsjogUlFlCkUQs0pgyF5641ZYQWS6KmDJWJLGhmamsx1mZsYZlEWONXGunYcDEKQpFlmYUqzOKUjooH/w8zBa6QVlmTCEQpQl6RicPfU8Ux4SgmMaJ5foMYy1uHNne3jBNTmKwSuniszRjwtP33UzAkLHAqdDP3kWxC2mmceD61asTZzxJM6x5HVf/VSfA6f0whixNSbNcwHlVTTf0hL0E+Do3kC9Xs/RgEI/o3Onm6zXl+gJMNDs+DGEm7O62G/b7A0M/oBMl+ONYfLyLsmR0XhZt04S1MXV99fUUqWKxQEfCBh+HRmh+g2P0EzYyFGlMUYiLXLQsEUFZtvXAru75xa9+xfX1DcrEqABv3F3zzQ/eOnna/OQJXnhIwyQnQJqm1IdKxH1uIisK0kzSL7IsZXl+jywvmbwniRPq3YH/7d/9O777nW+yPitQ85VhHCXsIYojurqlaRrOVuecnV3QD6La3e12s+E1om07PvroY168vGKc4I//yY9ZlQVVvUcRKIvkpIVar5bEJsJNE3U3UJa5YDLyXJS7wyAhjnP73LXdKZCxLAuWqwX90NN1Lcvlcgal5Vit2O8rJq/YHiqevnjFzz9bcWgdD+8/4OV1xdXNlqbvubzc0vQT37/zmH3VcH62ZN80TG5iaB19O+K95o2zlCIZyaxhUwuAzhjL0PXkcUQWW4wJ9G1DsjyjN0JlNNpgzESiPLGNOESaoR/o2m42/qpTUZHapFEqzPOleTgeAsN8ygdEzJmluRSemSCZZdmMlpZidtRNHbeG0zTJ96KlaC0yg+IYU6Upspj1IqfMUxZ5ShbHklhkE6phoohjHt9d8VdfXOHcyOQF8yKeAM+ySEUXpTS3u4r1yqKsZRhaoq4lEGZjsJ6vsQN5ehSrisV2OnaZ00SsNEkUo4wcApGPTrYSrQ11XZ9sP/3Qi1nXSdJRmsnVdBx7hkGipxSKpu2ZnKM63LK5viKJrMANo5h+RhLJScDc3Wm0iWd+/SxrsBFRlGBtQ+w1WnmmoWVyA13fkflwSlUahuEU0TWODmZA8OhkqeCco21r+qEV98ScLhSGHusjlssFbpI0az854rRk6Pqvp0gN/YhC4d2Id6OgXK1BebENFGl82nBopRmmwK5qqDvHX/7VX3N9uyHNSkDzzpv3ef/tR1gjQ1XpcrycG8HNc4mMw2HP1A9s9zsWyyVxkuEDnN+5j01ylE0ZBsdiUeJGx//+H/89P/zht1gssnmlOtK2ncToRIahHzhUFWW5ZLFcUdc119evqKoDxugTdO7jjz/my2cvaLqRP/rH/4h1mdN1rXBxYsmHK8qS9XqNG0f6cQSlhcczX32iuUDVdX1i7ux2u9PDfBT1HVEpq7lAHdG9h1ZaYg+sz87JFgsGa0lW52z2B4Z+5NVNw5fPXnB9s+G3fvTr5GVBGlkmAqM3HOqWFy9vKPJUhppKUSSWVR5zU7Wymg4yNM/SSIyySpMlkvuXWEOrJKklmiYiG1CJYVlmVMMwkzbDaaMnQk17OsFFeykFJISJY9bbcVYl5E03ywymU5z7cRD/VRvN8QqolEKhyZKUOPKoaSIohY00d84X3DtfcLYsZ6GvJktTXFAoP9C1DYvUcr7IeXa1k2CJ4DE6mkmmKcZKZNVmX0vEVBxTHWpCXFMOA2kxa3xmIWlkZkLpXBtsJLeEvCgwRsB9sYkIbqQdjpmCE+PwugONUxkvxElCO8j1s+t7ykyCHvzUE+cx3lumSfyk49Cz22+JEynYWVYgcVJzSCuCEtZay5IkinBuom0bsrxk0DMza2zp6pa+2TO5kUQb+q7DR8fEm+GktTpuco9auK8uTSbncGMPQSAEk3eoafa82ojbpmHoO0ycMY1/ezLn396KDCg8Y98SwjwERWrqIk2II4ksPyZBBGPZNiPtGPjZz3/By1eX+Hkt/uF7b/LBu48w5it/WKVRAaahBQa00bRtTds0bLdbluUCq+QuXi6X5MszisUKguf8/Aw3Ov79/+f/zfe+9w3Ozkq0MnRNL+GiWUYURRz2e25vrknSlHK1phtHLq8uub29kYd3Dlz8yU9+yqefPKE6tPyTP/oj3nr0iLYTNPDR6Z+mKev1Wnxn00Q3jnOihz4ZTuWEaSnL8jQIlpQbI3O7JKHrhEqa5zlpIuJA50bqpkLNuGU3SrJuWZaYOCFbLDl/+AYD8OrympubLe+8+w7f/t63KJYLJjRN79g3I8+vdmzqnpebA2jL5EFPjjSSTDvJVxMdmxsHCJ481lyUCdZPxEFhFICgX5I4QivFosxQeOGaB0/bdyfk8FEc6Zyfrx4K/xU5inOvscIhSArvMbPvq4XoyEo/zUXmAhbHR1Gsw8wUA680aRpzZ5WxyiIWuWB17VHcOPSMXYsbeyG0ai0WGi0RVlopFklKYiTirBlGDnUr15TJk67OuffmO/PWbwbwBaGmpqm4Bo7ZfXEcsyhLyrJktV4JNG7oSGNDYrUgYMJE37Tcv3OXNE3x48DQ1Ex9hxtGrBHtWD80ONczDh1t0whoDmangma/EyO7MTJrStLXSTCyIbWYueiHEE700MN+yzB29F1D19QkVpFl8WyfUXOA7Ejfy2Ln6NM8inSPgtuvbm6NOQpjvTC35u8hSRIiE9M23Qwi1ISvXGP//339nTqppq5YLAokXFCEdXmRk0QxwYvLWhuL84qbTU3v4IsnT3j54hVxkpJlOd/+1vs8uLvGT0742ohq2I8tTV1J5Y8049jgJolWX61XQlpEs7i4IElzjI2oq5a7d87Zbbb8+X/5T3zvu99iWRYEP9E1Au/SWuMnR9dVdF3NclmSpTFt23B19UowF1GMBAmM/OQnP+WTjz9nu93z+3/we3z4wbsc9nuhBcwes6IUTKs8XB43SVdlIkusor9x4hw9V1rPK/Q4en1dTVOmydG2MlyvmuYEzh+HARXF9H6aI61SkjThy+cviNOMy1dXfPnsBTe3e87Oz/nd3/0dkjjmxbMXXN/cUtcNbTew3e2Z/MS9u3eZkOTYYwBpEtl5oBlI5zQVa+A8s6xSw9hO9METR5ZoXghEkaHpRlwUE5jovpLN5rVicn524yPbKCRBZJpGuc7PH+g4iphCYBwnnJ/o+hY3jqRZyjBIwY/m7eowDDjv6UchrUZRxDj0NP2AiVdor1BxSpxBYhVpEhHFBuWDJPb2HaP3sl0OE2kE09ATRRKeoSOLVoosFjTxGCb2dUeRF6zP1vg4ZXX/Lc4fPqZu2pPlp2v2xFYge87LciiZD5rl2ZowbwhDcBBABYs1ir7b47oGwsiiTAnTwNgPjOMAyhLHEeMwkUQRbX1A2UCUyQGotBE90jSh0FRtQ5mnYmmJIvrucEKzHOPChk6E08pb3BRYliVt34lxHGGvRUmC84rIaZgRO0ZLctAwd8zHK/dxbqiUYhgHuqYSw7cxjEPP2A8UZYwKgWly5EVBlmd0dcc09mK+/rqKVJJK9lfXSZdwdrYmThJhK2nBS7TDxK5xbHYNL1684vrqFmUSyiLnB9/7kPWiwI+ONI6FOoCnrbc0TTWzaRLGoaVtR5RNuXNxB5QhK0rK1RodJaJkH0YeP3pAVVX81z//c77/ve9wfraSEIhuYBg6wGFtzDB0jGNPlqVEsWXoO3bbDXV1YLlciAKYwF/91U/42c9+SVU1/NZv/iYffvget7c3tG3DerXETxNFkWKtnKZN0+BDYLFc/w3dhzHmRAk4UgvHwZFmKeViOdMHxJYC6gTsT9OUfbVHa2FAdUNP13RkqcSE7fcVKM1+X/PJx5+w2e64e/eC3/mdfwB4Pv3sc/abA+1Mh1BaWvwsLgjAvm7Y15r1UnOWR5wtFxyaHuf8Kb6IaeS8WJFaxeAdViusVkRG08/RZcZGtJOX0NDRYXQ8r5QDk5OYKaUkLXia1ElwSBDyaN+1gn5B/pveDVRNjTX2JP0I8wcc7OkBiaIYH0SpPnlP5wK9E6SKsRFGTyTGEFtLFsWzNkmcDn3bMQ4jfhrJDSwShQ6OyBrGyYOBKFJoA7tDi0Jz/+4Fj994RCjWDKYgSjJ022GjCOU9aSyo4XHoZiBgirWRpD8nMeoY8zX7+/zQ4fyE61uGtqY6NOxvU9Ikmv+MEfkio2kbtptblB/p2oZsXUoy8OTROszpLJxGAxfrchaIynX5OM+zVmKtnJuE6uBGgteYzJCqhMmNoGT2tNtXhCAI6kVRUJYLlFZEcXwKz4DX8pLjX6PrGfoGbaDIF9KRT3KbmtzEZBxxnLA+P2NXHRjHfrYL5V9PkTq26CKqXBBFlrEf8MGTpjkjhmZseHW14cWLl1xfXRPHKetVwa//4NsUWST2Ahvh+pbgHV3f0rY1URxJWsYw0DQdJsq4c34hBlMdo2yE0hGT91TVlnfffY++a/nP/+k/8Z1vf4M8S2aW0kjXi/Ugigx+fuGlwGq6tmV7e0Pb1DLgniFsP//5L/j0ky9o6p5f++Gv8Z3vfovDDLjPsox+kAh0RaBr21Ps0mKxEAh9150eJmMkxPGIrdhut2RpTggiccjznCSO2W22J+1QURQ0TU1VHciSVKiUTqB+NooIQdH2PUoZrq5ecHV1xTgOvP/+u6R5zsuXz5kmiOKEfFEwDANdP6+RIwmibLuOySVob1hHE4tooo81E56uG9ABFucJ2g14D1YFvIFIQRFZ0Z8BSmmadsArAQQqJIXGuWmeR024STaKTT+cTnarha7p5rDNbugJinnmIdvdYZSIsGNn27bhdK04GZidQynD6D3tOBHFGm8s0ZxYjJK0mONkxiOk0rre0w/Q1xVlqtFaZimj9ySR4c5aIqcObSvK6jgiLQrM+gwfL/CTxxpL31SM9Z7VMie4kQnRDxZlQl4UswXMYzCnLnoYeoKT8NUkzkC1jH2HYvb5GU2SFURxgttv8ZPDKon4kny7UpjkrqJuGowytE1N3/XkmUSfywbvK9vTOUXmOFOycxCC0XKISvGRq3We52y3t4BCz6G72h9njPq04XMzuvi1g8BgjWwwo1gkOcPQ0nURx1zEWGsWyyXb68/FBgRfn3fviNTI8vyEhE2ShKA0+7rj0I18+skXXF3f0PYDaZqxXpf82g++RWznD433jIO0msMgMVB5Uco8AtAmIstjiuVarhFao7QiSWOKMqNpO959502GruF//w//kW+8/y5JahnHjnEMbDY3jMPAarXCB+hmM6NR8mbf3tzQd9JpVHXFoiz51a8+4uOPPma3PfD973+P3/iNv0fTVng/cXa2FpX96E5OdzdHdq1WK2wU086biiN4LJ4LWGQsm9sNRVFireXFq5dorcmzjJub65kx7mZ2Uk9dNyxXa9l8KCMcn+BI04zrzS02SrjZXPLF55+x3W65e/cu3/jmt2XGEzTKGIpFibaaumkFilcETGSZ3ESSZaSxJYs0j1YlN+1Idgi82vf4UbyHqTUMXYdXcmIOXYcOnsga4thixoAfFW0/EOYPu3OOgMIHR2wl5TaOYvwUGPqBcZrk/89imZvohH6Q8A60OWFOwgn7IhqkthNm9lctK6/RMGCUoh6FiNOOE0MEo5tw48Dghjk3Topc18qsx7Vywjd1QyAwTrNyOk24t1xKcouNuLy+ZVKKPiiiKcDk8J3EkbmxQ4cRcWUiV7DZPtS3LVEqs53gJqI8njvpAde3JJl0EF07khc5ZSHZfMPQEycpNk7EhDzTLatNoKlbFmVJCEI8mNyEnberw9CTJxFFuUBoyRIfb+eFQwiyvVVIQTnOS0Pf4Z3ADyX4JEUrg40sSkFdV3+DR6+1fI/HpGKjhDvlXSDLlzjfS8Sbjdg3e1xk0Ua0h4HAcrng6RN5zyWw4WuKWT/aPqa5dQdFXqZsdg37auCnv/wFNzdbejcR24i7d9d879sfooJEFREm3NATZn6zzGWyGbIlbeVieUaaFWy3wqxK8xKlxDPUDx337t7FDQP/9T//Z955+zFpEs3VfeCw3zG5gTRJGIeebhhYLBbEccTQdtSHPZMbKIqc3X5LliZ8+umnfPrJ59zcHHjvvff44a99n7ZrRH0cSWjlOI6s12vyNKaqajmJilTy99rutIEqS9koKQR2v9/uMcaedE8ARVFQzTorM6+wQa6OQqns57v+iI1izs8u2Ox3xEnG/nDg6ZOnXL66RCvDb/7m38dYy83trVztrKHIcwHEaU1RFrM4lDnoAGycsMo1bdPxZhmxiB16mqh2Iss47CY2DlILRhuGrmcKAbQltgarJ/E6zoNioVhIUKhSgJJrYwiBrh+YpoBzEu9urEEFTd+0+GOkd9/LgacULoRTyszQD6dr8VEzd7TwtLOfEhT7dppz3DTtONENE26c2O8lfcg7h588VVXjRhnSu0FW6XkSU3UtkTXcWaSsywxrJPklumnIihWDN8QmQUSbnrHvUcFRljnKSBGIbExRlkxhQrmeaneAAK53TLNtSisBFMa5CIG7ruPBvQuqww4FJGnO6EZ818phrY1sXpUmSRLKsjiRL0XFHsvr6ybSxBKlKQIl9CgtXVQURyglM1kzz0SttbNXccDPMVNucqQmIs6XqDnz0M8UheOywxhNnmdCXR0nghb5jVOawQ9ype4DUSyxWCBX+2HoMFHM2dk5/eCpGwmXiOOvq0ghp1kcJ0wBtI3YHDqevbzml7/6lOvbDSZKSGPLO28+4FsfvjMXKDuHVw60zQE3DjgnzJrjAG5/qIjjnDgt0TYiX5yxOr+LjdMT3e/s7Iym2vOXf/FXvPXmY2ykcdPAMA70TYVV8zxkFtqVc8dXVTXbm2v6tidNY5rmQFEkfPnlCz7+6HOePbvk0aM3+PW/90MR0mkhUh7RI6vVkiwVlWwcJ+R5gYkiqqo6ge6PiIvJe1bLJYfZ3pEkCdfX10zTxP3799FKc3t7I1TFtmW5XLCbU2MPVcU0RwsFpTk7P2dzu6F3jv2u4vnz5zx7+pxD3fC7v/s7FIsF2+32ZE0py5JFWXI4HE7JO7I6Ft2RChMmjSnSAK7lYRFT2oA5T+n3gTq2JIy4ASYPwYTj2SSBETYmiQLWOsosZd+Np/VzCIFiLhyR1hBkk9vPB9LdO0vZ/riZNWUMbdedFObHrd/RNKtmRvowDCf5xnGjNLoR7yKUTTg0DYtsiXMTPsAEgjluG5iLntEG70eRjeQJUdWRRYrzxBOvxJT+/uN7rIocZRVZlrI6W/PW+x8Q5SVpvpivOAGiibb1BC/bwSPj240jV5c3hMnLwsBY7t5/gKs7lNWYOGPsNZvNnjfeeAB4ri9f0XcdRZbz+K1jbNVEnhVsDg3aTPPzFp90dDYyjH4k4KmbluADWSo3jnEcsVrDV9X/yFzJE2hrASAmWSG0A5hj2aVrTosCYyKsjQkBDof9aaxxDMsA6PuORbk8yWyapma5XIOaN7boubP2dH1LnOZc3LlD308zq82TptnXU6TkOhMTpynjFLjdVlzdbPjo08+53WyJ4hyN4jsfvs1bj++Cn9DWwjQyuZ6mPtC2DcMwsFyuTm38dndgdXbOcn2HOMtJ85w3zu6Q5QWHQ0VVNzx4cJ+h7/jrn/yEd995B+9H3EzobOo9VsnjFM1tcp5lKGNo2pabmxv6tiOJE9q+IY4Uz5+94LNPvuTZl1esVit++7d/Cx9eC9FkJe7I85TlsmS/r05X3TzPubm9PYU7gmSP+dkk289JzkqZE3L57r17eAL1vME8zgH2+z3WyuA0SaQ7m6aJcobvdePAy8sr9ruKzz/7gsvLK9579z3effc9aff7Ae88ZVGyWizZbLcn8aOs9D1xbE8zIZtatG1IIkW0iMgT0Grg7vcfMo6ew6GeP0hBeNbTxDBNJ62T0ZoksSytwSHpQQHI0oQ0kY7DGMOLV7cM48TkIcsSsmy+FgYRdxql6fTR4PwaNeycw9uIJBEJwdGUfFyBH/9csi20+DDR9gOu7zALAeQZrVjkCeMwgnPEkSWOS1KvaCfFowmuDgP3VxaMQcUpj9+4AKXZtj2fffqExf1HZGVJli1QSqKyvB9R3jFF8TzjtETzSCKgePD4TZqqYbFY0LQ9bT+wb2qiOGW1KhjagdViSWwtFxdrjFbsd3t2+wPJ9SUPHj2aVf1zYIeStOwklSj7cXQEHfCTn9OlO5g55smcAynPqCF4T5KkxJEYoIMxBBxKS0iDMoYiS+dDIzD0LU3dEaUpi+UdQRenOcbMyvLgcePINM3vodE4jWQCzCGqRbZkHAemoxiOCYWMXM7OzvBeybbZDUQ2/XqKlNECtqv7ke2u4vMnz/ni6Zfs6wajhVH0ve++y+M37sxEAYWfcShDJ9eJrus4Ozs7sb13+y3l6oy7Dx6RlQtslFDVDaC5ub6hbVvefvst2qbhv/75n/Pg/j0mP4qaeZrYbXcEP+FmEdvx7I/jhO3+wO1uS13XFEUhivUs49mzp3z+2XM+//wpNjL88Z/8kbS3UyCOzayQFi1MUWYcqgNFUUpnojW7/R7gFGL61cHuMIwQy6bv5vaGEALnywVTkOE6wZ+uLkeRpxRrdXogvZfgy64XQ6hznhcvXvDy1QvSLOE3f+s3GMeBuqnQShPZiCIv2O0ObDc7oUMOI4FACNOcaptjtSFJHEr3s4p8IlsmrJYxQQUmDy8vLS8vPZt9jdOABBqTZhnoCN8ORJEl0Zo752sG5+mGkSKTkEutNMM4Mc5hC3VV897bD8kLAQi6mRzp3QxkC0pW3dOcyWcsUWSIE8s0CYN88tN8RRkFy+sk/br2E2WRM87dlbJLlImxkejQsiQT/Z0SyF+YpAO6c7HicdOzqXrSJCNdrMmKlN7Bwhjatuet9Rnl4ow0zVGaOfVlFMhebEkzsXy4ydG3LXmxwgSNthFdL8XU+AgTZZTLFS+vLsmzgnfee5/DfstmX7HfbwlBZm+Xr56jcBR5weQUSjn6fkAbQ5pmKCZUphimQNtPKBSb2w3aaMpyQVGWjF66FwkeVSdLyzR50rzA2ETkHVHK5D0+iELe2jk8YxzxwZPlA7t9QxJHpGl58kyOozsdfJMbsXlK33f44NhsJLZqtV6xWAix1diYycM4TeRFhjaKphGksv+Kr/P/0CK1WJ9Jgdo3/OJXn/H02XMGP2FtQhYZfvDtD7i4KGaQvUErj3fuVKCstVxcXJwEYF3fszq/w+rsgvX5BVm54HCoWSyWJ43Tw4cP2W5u+Iv/+he8+egRSWzp+oYosjTVHqOEGHnMMBPhpqWuKrabDbvD/jTTOFuuePblU774/CVfPHlGCBP/9M/+FKVez0IE1RJw00hZCrEwiTOccxRFQV3XJxd/HMd0XcdisWC1Ws0hjCKmO165jDGnQuanSVjXQFVVf4Niefy7mkMXt9stak60ffXiJc+/fErfd/zpn/6xrIx3O3kN2467d++SJAm3txvSNCPLUpr2Zk6vlSK1Wq0IkycxHZE2JHlMZCBNY8ZJONyHuqGILetFRjv0dE1PYiOiOEPZSOLhrcViiIxBmYjetadt5XGGdNjt8Sj2Vc2qSDg/W83pxa87znZqydKMcTh2rRNFsSCNtYRcGOncjm7+thUutp0k9Rdk8xVFGgjY2FINA5POpYhmCZYj7mU8mYHV6HHBsSpTAhCZCGMVCkdkI3IT8c5bb3Fx5wF5sZxnTmbmikuDkGXZjCJijpaKefnqisVyJMsymnZO9PaCBr65ucHGCY/f/ZD1nQdkyzM2l09ZLhbc3m4oyiVKwbMXL3nz0SPu33tAXd8SG5hcABUo8oKmaQSqaKQTbZqGNE1JkwyjLYN3KBXESzlD92D2VBJOLPOgNEmSExtN11Qk8Ws9mg2Wq1cvUTpmtVzQdbIBlN8nxY09Xevoup40ieTzHATtY40SrRcKa+N5qRLo64a8KCU8pRXhbmL+9qXn71Skbg8tg/P87Ge/5NmLFwxOoGGL1PKD736DVZlikHBGxcA0OblL9/3pejNNE1PwgOb+w8cUyzX37j8kL0s2s3q2OtRoY7lzcYeqOvAX//UvePzGI4w1dH2HVtC39fziRLgQ0CHMET+GzXZH23Y0bUuR53T9QJ7nXL56yU9/9lOefvmSvu340z/9MXmeUdcVSgmpIEli2qbifL1G6ZkJFWSI3s0zlMVicbILlGU5R2wHsiwDFNutzJj6vpcOzvsTW1oSSuQrTeVEixPhdHnvSbOMzWZDlua8eP6Sp59/wfOnTzns93z/e9/j4RuPuL29OeFnF6sFURyx2++I45g4jqgqwdhEcczhsGe5XBHHCUPfEmlRlMfxnKacJFR9xzCO9K0oziOjybNUdEhjwGYZzegICqI4Rc1JvdOE0C7iGKPk2jZ5TzuMdJ0Mvh/cf4SdrxxHJK0Uc1FC77YVXddT5hln5yuSefBqtGKa/HydDvSdZBxaq0mTCMJEniYoFUjThNGBV5puvtoM40iUWJarpRwISjONI7nV9ATOLww2ahjGQIhkqK/jhBTDO++8TXp+F2VEFmOtpesruupAZBVYQzfJVXZ0Hm0ijIkZhpGmkcH3+vyC0DU8e/oFi/UFd++/QVYuqJtGwkijlKwouRenNLWkRw9DT9N79ocDRZ7SVRX92NM2shGO4hgXFFr17LZb9rvDyRcZlEIjUhAsc4alBKMoremamqZtSbKSYejIUwkpmeZbgIwbxILjvCdNjQTr9nPSsbUorV7r3TSzSVNe/74Vgfc0jSdHwfHg10YTxQKC7PqRYRhJ/d/eFvN3KlLXmx2ffvoZl5c3pHmBchPLPOKH3/pgjjoXV7xRiilMTM7RNg1Ga4mQ1oZxmpi84vzOPfJyyZ079zDzqj4rc/quZ+hbHj9+i6aq+OiXP+fdd94EmH1J8uIoL1HO0zSBkkRVrTVd37PdHwQ/WxYnc2S13/HXP/kJn3/xJXXd8C/+mz/j7Gwt1MFshoplqajqyxxrNEpppiAM8qqqvnLnj+ja9tQltW17sri0bXda2x4fymEYTskhg5Ph47HzGp1jGGWtm2YJVVUTxynbfcUXX3zJk8+fcn19w/2HD/j1H/1InOaz7sVYQxRHNF1D13dEJpr9gXuxx/hAmuWcX1xAgIAnUk7CAJSlLBOiJMFkCdvtnqLIaboR0zmyJKX0mtAOTPOWx3kYsZgoZtIW/DjHkMmgNWgt+i0XqJuW9bJgtV6htAEv88Ij31vnuRhY65Z1suTs7IwsSwghMA49Ck9ZyKGmgCGW7aL40gJJFJNEsSQYW0MU5cRJzL6faCc5KJ0biZKYOEsYJ9CTJD4vliXZ+gKtXrGve0yaYYuCYCL6IbC+cwbLM7S1ZEVBW+/Z314ztC1TnKCswSaJ8KSUXMunyTP5cIqHr3Z7DnXFxb0HFIs1y9WFbMPma7CKUvLkHkmccHN1y7OnX3BxtmJwI1VdETHKlUqrWdLiGEYxqisl6O6qqknTmHIhWZV934Gf/3vn5FZgPH4CYziJaZlJst57kjwXlHQzcOS9x7Flch11LdKbLMsYRyXPm+tlezdH1c+ZWPTDiI0jtJf3ZxwHbGRFEhE8SgVWyxVN29APvSwhvo4i9ef/5S/ohxFjY9zkWZcJ3//G2ySR3JGDD7MSVhJ0x2E8zW3SNKWqGuIoY7E+J8kK7ty9e3KC50XB5vqGOIq5c35O21T87Gc/Y7kscW44wfqrQ43y/nUU0RH9oUWAdnl5yTA6ysWCYZYg7Hc7/uov/4ovnjxnt6/40z/5Qx49esDhUJ+2ciJYcySJoGBFDCen0JGOcBzghhDIs0yG5F3H6NwcBiGaphACVVXNDKyN+NHmWYxzjizPT6Zq74NA7yahQEgggeHq5pYXL1+y2W6xNuJ3f/d3OUbQ63mTc3Z2hlJKvj+jKQqRbiwWC7IiRyl48OCRdIddx9D1lOdizbA2RkURWPl5mhe0g8PECUG1J3/h4BWjDxgJE8apBBOnhNnDJQJLzegCTdvTdY5+GBnHgUeP3iSdr7rH9+94ypZlCcBytTjJNGQ7CARH1zbEsYgPh74nMhqbSNdglCJPZfCq5h+LadnRkzIQzRFN8kBH1jIF2URFaUKYItq2Z7HImbTFIWt6tMFYSxKn9N6BCxw2Vxx2W0l0KRdi/ZgmdvsDqJ44ipmmgLXxzAoTCcjgOtYXD1menROCSEC6tmW5WtF0PSpNJdKq6VBRxmq9ZuhrisWKtrrFeUcSWbSTYAw/h3K6SQ5nYw1N05CkEcao2dwrSvwjS8rPSwqvFEliGfoJQuBwOGDnK6AyhkCgWCyp9vVshzEM48Bus5UNYfBYHQjKU6QJbZCr4xH/TGAeiyTC05qXIWqOle/GERUCq/WK509uqP8OLKm/c5Gqm448L/EK7l0s+eY7D7BaHmSCIjKWcRSw1eQkvuY4fzpUNSEYztbn5IsFi+WKYRjY7fbcu3ePvuvIkow8L2jbmo8++iWr9Zn4fLzQEdpxwA0DXVNT5Pkpp83M99vNZsvoPWfn5/MGccnNzQ1//Zd/yccff8Z2c+BP/uQPee/dt2mb/sR5VjCn+hqSJJ7X3J4kTk/r/SPO1s8/z7KUuq6lpVXmtJ2SU2c8hZZ+NenEje6UMtv1ciomaXJ62EbnSJOMp89e8vlnn/Hy5QvavuWP//jHlGVJXUt4pxsHlosleZZLMcxmL2ErPjpR6WuWK8kiHMejMVRzUVqyZCBoIErwNhZV+zgxOs8UhKQ4hp66GWToPG/hEhsTmYxxCvRDg53tK6MbQVn2h4opKKq6Zr0ouXfnjphk+/5vRF+laUqSpLP5WkgBx8+KLA+syBWmiSQRrE8ax2JMDR5rDLGJGEa5xkdWo4OEug5Bo6KENNHil1Oyncoi8C0ohJqqTQAlV51x8PjJY5T4JOkbqsNI27Y0Xcfq4g5nd+5yqCqGORA0jmImHzDzoP9oHWmbhu3+wON3PiBKcvp+pCgLINDUtcgiZqeCCAQk2uv87IIXn1+zHwaSRDOF2VReFAxuoHGSd+e9lwTsKdB0LeuzNUVRyDwtS+nqg6ChEY3YMDq0seg0FrbZ6OirimFMRZnvDVGazEsNR2pSyrJkt9txtl7TzwZ4fMDP9inm8crUd4RZUpKlspwZnTuNLmxkkXwKKVJlWXCoW3a7wxxC8jUUqSjOUVrz/pv3eeeNC7SW1TTIQFEQLlLRj9oXOyuQ82JFlOZgLcv1miTNuHp1xZ07d06u6jiO2R92fP7Zp9y/f++k0ajqWkIgtaKpdjNuVxKPnZNgg+12x+gnLu7clZM3itjv9/zkL/+SLz57ymaz5R/9o9/jg/feoa5rGezNXV7bVJRFhveSJweGxWolYsBBUlxPzO2+RwWREnjvTqeWcxNJlp60UUf07ZGG0M1pxXGcoJWcPmWxwFhZqW82G87Pz3n25RXPnrzgyWdP2G73fPDhBzx+6zFVVc8kRUWe5hRZIWGTgzuB9HpkBnYsvmmckMQRVVMRpok0MpyXmsRGQmdUSvRuxuLRKB0xukAcpdgooI2bAzk1UQjoKCdqLGPfEWZluPzlOdQN/eiom4ahH/n2+2/LNW143QUfv4S86aUAKbFIyDD6dfcj5INAbPWJ5hkpLSSOcSD4cFqPF3lOZCBMPR5HWWZkuTCnjjq8ycm1VeNlAxYn5EoxThpvFe2EsJC0x7UVl1cdwVjuPXxENA+/ldKkSSrUi35EaUu/r8jyhKIo2NzeUjUtj975kLxcstlsZwKGQPJEohLR1wP90J/8c1orFDLz2d2+4vzinKLIaZsGrbT4EueOZ3AdYXI0dUvdtKTRXaI4FXlNIy6JJI5nai5CVIigaVqiJJ7fiwhtLc7LfDhRKaMXyU0Sh9PBGsXRjBAu6LvXlItjJw+CcDZG46zYwQbnTnBC7XNZDbsR7wbO1iuGfmC32TP0XxOZUwXPB+8+4PG9cxSO4GWAOsyetaNk/sgKtzZinDx5sSRKM7Ki5PzOBcpGYps5tsbDMMdhVbx69ZJ79+/Rto1QBmZtjY5i2qZhuVye/HZJmhA60YuM00S5XJxmRVVV8atf/YrPPvucm6stP/qNX+N73/sm+11FFMWS3ZamBCbKMsdY6KqBvncUhfw6URyftFBxHDP0PeViATNOJM8LhsExDI3YOuZOSimJUB/HURJuxpHIaLI5qtuNDqvt6ap0e9hQlktubrZcXl7x81/8jOvra4oy47d/+zdPvkBrLX3XzwGjnNhUxpjTv8+yjLZtWa9XwkkfBlmfO8cidqzKjCRMjJOndxM2SvEOmnqgbUbyTFbO/ehZLixaN9SDI48sg4qhGsQ7FsUMg8PaiOBhvz8wes/hUHG+Kjg7W4FSf2M2dySTHq/MR+TNEaUD/A09lDVaMgxTQ2QtwY0ovAS/jhNxnGBtRJwm6DARtMdoLfNJq0TEORds52R7N4U5TEJp+bH39L0jyhcwOiYn783FnTuU53dpuoHJi1mXIArzru0ZB88UBimOQbHbHmgHx93Hb1Ou77C9uZ7RJjJITpKEJEk47A/CD5uvrfv9nvOzC7q24v4bb2AY2dzccLZcEa/WDH1DpC1aK/IsI0kT2t7RNrUUlVRMzSYSO41WEuuujWaxWnJ7fQPq9VjkOLaQLauIK7u2m99Hf7IegeibvPcon4rl5iu2pGN4qzHyHDo/o1sCFFlGc6gYx444kvBeN40slwuGcaBparq6/nqK1Ifvv8Eb987EN2VkC9PPmXPTOGCtrOXb2YDbtD3FYsX6/C55sSDKBOW6r2ryPJdV7TDw4OFDgg9cvnrF2Xo1rzFhGHqKLCOZNxhZZE5pGavVinF03N5uJUihLGdhpGXoBz779FN+/rNfcHm54bvf+QY//OF3qauGEOTXTdMFbdsQzUm4+/0B5xx5UQoHve8lnyxNJXssBIqyhBBom2amd7ZizFWG1XJFnCaz76lmGGQDMwwD1hiyTAzG4sqXUAbvPVVdQxCz5suXr/joo1/y4sVzpmnkH/7DfzQP6YdTzl1ZFqeY9qPhcxzHE3PpyAJP0xTw9IMMP6fJc5ZHJLHFj7JuVjYGHVHXHZObKBcFtpffK88yQuRRJiI0HWqCYQjUTS02GQ9g5NrRdDgfGNyEcyNvPnoLK0/vqZM5uueTecHxVSXzsYgdv+J5JR5ZM/ssI+I4AR2htaT39l1HMhuxtbEoD1pLTpxSWixRmfjQhmEkBD1vn5RgStKUw6hQSY7qK7pG1uRiC9GsdMbNbovCEAaHjWPiJON2c5BZIoHlakWZZXzxxadc3+747q//CBPnVHXL9c2GLBPRZ99JZ58mKX3XEUcxeVHiZssVCrquR3tYLFeMfcdnn/yKh48ecXbnnGmQ7efQN6wWSwItfSfpyEWWUSyWKGPnq2dEmC1K2hryIkcpg01iQhCE75EiqrVYbpI0JY4S1mdnKKA6HCjKgqEf6bsG3zfYOGWxPCOKJOdgmokLcRTj4oimbvDT8RbhiZJIWO94bCzgv6LI8UGuvebrQrXcPZfVe2w0WsPY90RGMXpm75hM87UxdP3I6vyColyiI8v6zgWHuma732G0lQ9ZGnP33l3GceTpk6cUeTbbUsTMaLRiGFqSqCDNMp4/e8Y4DJzfuYNzjpvbW4ahY7lcs6sO8kEPgY8/+oif/eRnvHp2yXe+821+57d/k+Dl1Fdqmk/r/oQCQVmCUlzcuYsPgf3uQFEUgvctCqb5KprGMVdXV3NUdHeatZTL1Smi+ubmGqVEhuC9BAYkSTITIEVoI7RGMXput1tWZ2d8+exLPv74I7548jld1/LDX/shjx49ZhhGsXx4yLJ83jTWp5DRaZrma6+bhaGjCOe0nPg+iBrTanhjlRLpgDcGrw1xsSLYlK5yxOUKZTqU7kRc6RVD08EgMoDROepDQ9M7tBIsSBwn9H3H7rDHe2HYrxclF2cSpBpGgSPCTOKci9PRbgSc5nUnSum8YLBakSYpBClawU+yyo5EkhC0DGjjKGYaB7FfWDXrmiK0Fe9ZwBMlMUyBpm8YscIsUIoQp+JJQ+PrDq0tw+RQk6OrN9j4DKUFgT35wIvLq5Ms4s79eyzLFR//8ufcbPc8fvd9kmJJP0woPEleECfCp5omMRjLYT7SOEeUpvhJ5CwQ0EYz9hNRFHP37n1ejj2//MXPeP8bH/Lmm4+JjGYcFfurK8qzu/StSAMWWYq1Md47onmRMU3udT7i0Mt10Rsm70+vbxwn8+8rQs5p7CVyTYHrWpxVDG0rt4YQgImq2pPEstzwXkTJk3PyOk+erqnBO8wsh2ibXuLctKIfBrIiJyjL4Bx+Gv7WdefvRuZUQQiEYaKpKhT+FAd0nCd4H3A+cOfBG1zcfcD6/IJ79x7Q9yN911MWi1MBWK3XDOPA06dPZPYQSzDlOPYkSYydQyvTNOXlyxeM08TZ3Tug4Pb2lq4VQWDbtvM9XPP5p5/xi5//gpevbvjwG+/zh3/4D+doIlGRF0VO09Ro/dqKETzcv/eQKEpoapETnFhQszftKNBMkuR0HwfJRFssSowx7Pf709Xi+P8cC8hxnnR8GNM0lU3casmry1d8+sknPH/2jLo+8PDhPX7jN/7eLBrVKO2xkRAY+mFgmK92x1SQI9lSazXHdSVCV/ATQ9fRtRXrKPD2RSJWiygiX69RWUHrYPCa1itcHDFozRQn6ER0PHEi6TWTN4xETMoINtcaIYjWNd5DNzhc3/PowT3yvJA1twqnB+NIzDjCAI+F64j+6LqOpmlOy4hjmsmxA5tCIBhNlCd4Y8jKJTbN8FrRj9L1Km3waAYiHBYXAkorTGIJKmBMzOim2fIzYaOYuvcMHqYQmEJgsVySJhFlLCGqUVYwBsXgPFGUUJZLHj56i7OzO3z55VOUtfz9f/gHPHr7HXb7g+CMJsf9hw+AIJ/TvpNhvxUaqgS0JkJanVHSXS9Jxm4K9G7k7r17JHHML372c/b7PRhLXC5IlkvapmXXHFA6kMQiQznii/2sMJVA2kDXdwxdM89Ix5PPchxnkN28jAhBBt2RNaS5iInHcZhNzkEkA2HEmkA26xGPXspjyo8bHUZJ9JiabwzM71/wE8uyFByTGxn77uspUlEUYQi0dY01muogg7pxHOf1ugciHr/5HuViyWK5ZHV+h6vbDW3X4X2gbVuZD0QRh8OBV8+fo72nbxucG2dToyVNIpI0JstSnj9/zjCv3I21NG07p2yUpwfUas2nH3/MR7/6iFcvrnnzrUf8yZ/+mHGcW+00Y7lc0jTNyfICnApO23bzjMee5jzTzHA+hoUeT4/jBm21WsmcqB/mX1edHkAQ+F1V1/NGyJzu82mastlsZB3dtjx//pzPP/+cze0tRkf8/h/8gXQMQZC5crWTq0vTNCe+lbGCOfHes1guMEaRZQnD0FM19UzG9ERK8f79gkUURJxqDDpJ8dowuIlhnDh0jkln3NYjl9uaqh/pxolmGKh6Rzsptu1E3Tl8CBhtT8hfH2B/qFjkGffu3kEbg/evrT5HT+NpiD2biZO5+zxtTmc91rHLOg5wx3EgsobIRkJYmLsZ7yfGQVKtbRQRAOcVzzctLytH6zUBQ2RjjLH4oEAbxgn6fsDYmDFoeieqcR+8SBWsIfY9qq+Zhho10wLW53d4+NY7mDjho19+xO3Nhjff+xAbp7jByYIhSsRu4qUD6WcE7+RG6sNerk9+ouvakzxlmiasUuR5hk0zgtJsdzs++OAD8J6//ou/wo2ORb6iPLtDEmdsb7bCb89k+dA2DX3XEebPgixoNGmUkmc5aT4P8L2XrrhuhN7aNkzzgZbnGWmRkxQZ+aJEz6ODYwo1TLOivZcQ10kIFCdChVZMeLAa5+fNtZLhugqQphnFvOwah6+pSMXGMPQdkRXBVrkoxXRqjGx5bMT5vfsickOwILv9AWMibm+3pw/k+fkFISieffklQeJh0EZTHfYsFiVZJkksWZrKg2sMq/UKYy1VVbG53bBcLqlrSZGJrOVXv/oFf/3XP+XjTz7n7OKMH//R72ONpihK4tjOZEuJscryFG3mde68VZL4rHSem6SzeVNsNscC9NVryulaYkUpnCTxrA8TVMZRV35UlPfDeCpQ3s0we6XZbne8fPGc6+tr+mHkd373t7lz54JhGDhUB/Z7eU2OFhylAANTmIjTGBNZVmdrtA6s1gXg6boWhXSJwziyXpfkU4UJDrRGJwlKRyhtUdoy+sChG3AYBm+42rccOsfNvmZTtRz6idt24sVtTdv1p4Iy9D1hgt5JFPgbD+/OGjB/6lyP9qFjbFWapqecvaOLXs2bWxn8p+R5JsyyKCKO7SlMII4TrJHO+sjSH7uePE1nvrzk2f30i2v+y8fXXNeewSu8F7e/imOaKTAERQhGgHujI+iYXTNQNWLYnrzHaE/oKtp6hyaQZTnLxYK2PnD18hmDG3nrvW/gnOLVyysuL2+oqorJjXRtT1PXJ+FllmWyAEIRx4LRzoqc1Xp9em0iIyLLcVb5e2Wp6pq333mbzWbDf/wP/5Hrm2uuXt1ws9lQVTXWSvBolMZMrmfoGola954kySgXK6Gnti317lakKF4QK0VRksxbYY1GmWje3nWz7snOr3mMNESK4KVrDzi0YRbfSsEFMHq2xczzroAniqU7c27AWs1yUdC2Qi752379nWZSXdtQZjEBeeGdc8RJAspg4oT7qwtEoqFYrs642W7xXvH82TOWS5lnrVZrdrs9l69ezakrAa1E81FkKWWWnlC619fXRHHMarVimjz73Z79dkueZYL5mDzL5Yovnjzho08+5/nLK+7eu8s//7N/grUzvnYUFk5V7ecHxDK6ga7rTie59wLPH8dRMK/eE0WWOxcX7LbbU7c1jqKdEfsLp1SYY/Fyzsngcb+XH8/JOU3TUGQFSZKw2Ww4HA4slktubm/55NNP+fzzL9nvO773ve/z7W9/m91uR9/3NE3NarUgnTExfd+JwHKORJq8RxuBCZ6tFlitmUaHdxNpaqiahmWZcpEGSnpMyAhWSAXBB4y1eB/ETuImNlWHNzHNeEABu6rFB422CX2jqPtjEowkh9R1S+8mNtsdy6LgzsX5XLTllJTC5NDazNdrdQpIPXLRj4THEPwsIM3F5jJ3536CPBe91xEXEscxh92OsW8FiRuZ09Vi9BO7MeLLVxVlmhC9tcBYS1CGCc8YAv0U2FY1uUlJ0pTLqxucVyQmIihBAmul0WEksmtMFBPCRHW45cWLF4we3nz3G9g4kQ5KSUyUc7LNUyoIfcJKwIO1Bm0llbiua1Y2ZuhFkW2MFmbX5OmainKx5LC5wcYpfVcRGc33vvddnnzxhP/07/8DJko5v7jLoWqJI+HlJ1mJm4KIK43CAC5MuGnCxhEqSJqzcyLfsCZCBU+eyFDfxBk2iqjnEYUsehRdU508t8dtOCjJG4w0UZaIDutwNORLpGoaxSLkTuQ9libEAJ7zsxW7m4Gm+tt3Un9H6N0EKhDZ+DU6AkWSZqzP784r0ZhysaSqZSvz9OlzkiTh8Ztvslgsub294fb2FjcMaBAMxRhYlgVlkQuMP03Y7nakqQjLxnGkrhuJbdaadmZk54sFT558yc9/9RGff/qE89UZ/+yf/ni+Q1vaYyRUN3F+fj7HBHWykfSeoihPok9JbNUnRPJ6vZphbkd8qmih7t27d9qmtW3L9fW1xMpb+cDtbq5kHhM8zdjTdCOaiPVyTdd1vHz5ivPzM3aHA188fcLTL59xs9lydr7mH/zOb3M4HE6yBSlQIrTb7WZ9mHNie5hpj3leoBAu9Xa3xU/ycBitSa3mjXVKun9OlMmgmDinb3oIQkjsugGbJCgbc7nZy4p9CgQ8vdDyODtbUykvhAfUaWkwuYmqa6mbhu98432KImc4GbXNKfIomT+sxzSR4xb4qPY3RjPMnWaSCCXymGCNh8gmpJlsK/f7PVpLgk3vBrIsEQvIHA2uFFhrcNrSusD20LMuCyYfaPoJrVPasZLOKWy4d/8hQRsheQ4T0eBIIj0XqZ7z1ZrBpNxcX/Li5Uv6Eb7xvV8nzRfsNhvRB3o/D+kDXddS5IUEjQDeiShTxynBe1YXF0RRTNe1xCRM4zDz/Q1hsjJgD4GhH1lkOW21w6SGDz98V8YkSc720HKoa7I0IU5TdJQSG08fWQyBse+oqwOJCQxdTWQNJo6ItcGOgck5JtejjOTqGW2wUUSaFlgtRaX3M9cs+NNhfsQTT24SXLHR6MmfNs5xHOOnkclNsx1GNFexUlht6Iee87tnvHr5jLr9mjopmakY/CTpGP3gWa4vWK3XgqeNLV3bkZei4r589QqlJu7evctyuST4wPXVNcpAmsWYEHBDezKKjuNIFEVsbjd4REbvJs/Yj1T7wzxMFRB+ni/44skX/PIXH/H551+Spin/4l/8U0GtRCKD8JOcrqvVkmkcCX5imtXXy+WScZx1PoHTUPsoKl0tlzz57BOmybNYLhndxMOHD2nb9iRUvb29le7MGIxW3F6/ZBo6AgrnA9vNDpTl3r1zxmGYCQ/iLP/yxQu+ePKUq6sb8PAHv/f7Yp3oulkaIakhIciSIMsy6SKSBIXCdS1pnjMOHYvVgrZr6bqecXAsVzlWT6zynDM7klvP+foCnSSAzHha53AKOgdV29MOgUMvXU/vFFqJWTWJE9577z0uf/6UgMejGLteiJc+sKukA757cYaJxSUfWXvSQYk+KJo3q+qkjTqKOyXAQp3mUkKhkPfC6BlTogRBMvTD3DEdtTyKyBim0UlUEp40MoQwYY1meX6H1ZllDNA0PfXg6CYtUDalOBw6lmcjboIxBGwQyYZGVPiZdUyHVzSq5NmXTzjsKt7/3g9x48Dly+enpUrXS06ijWOWy4I4TqkqKaZJllIWBYvFmq7vT2b0vm1QHoJXHHY35FlGkRfUh/28THB4DEmWSn6dSbHacHN1SdVOHKo9D+6uWC0WM05HhuHKGvpBkm60bLlQRpYdcZyS9tCONZObZvO0vF5D19C3DeNRLBsk/iposWpFUXwyiTs3MgySym20FvsO0skFlGT8GcM4OLzx4rkEhqGjyErqqvn6YtZlEyBbhLoduffgDfJygdYSALjbbdjt9tze7ri5uWZ1vma1XuOHns9+9QuUNty5OGccW7LIsLm+ZGj2mFCiI1knN03NMPYslytA1qhVVZ02WXGSUJRLvnz+kp//8iO++OIZkY357/7FP5MP+kxJHPoOFQKLskDP6283OkLvWJcLul5OrDwvUEpxdnZ22iqlacrm5powDoz9yMZN3HvwkKqqaNuWohDj8nFLOY4Du80VGoeODYOTmdXk4f79O6xWS+LIzh2Y5dmzS54++5LbzZZDVfP9732He/fP2e13AHPAQ4n3ns3m5nQlOg77+3GgWCzou5Z1mZNGRmYgg8Naw6KwfPPtNwjNnvHVFywL8ZdNo6TZDsHQBw1RyqAcm2rkZtcx+kAIwhSKjcJG4qlLFiuyxZazs5LbzR7vHc5PHLqevu149PZj0ryYZQmRSEf64wddCp7Reh6oyxzqqJf6qjjwKE840ihjG4u1BdCIsl8bAzOUsChygp9mcmfAdT1oy2q5JDYxTdCMNmHyPToypGh2245FkXNdjXRjJ1u+JEGPns2hwitFCMJWCj4w7K+42r9is6144423cOOIMb0QEEYJ8BzHkaLMyXJR0oOfjeuSuoLSZHlBU8vsJsD854TIykEwDD1HQMbp/faBLMmJrWG/2xHNvrpDtTtJIST4U8245Qmrj8Grajb2qtPCRxv1+gCY34vJT/N1XKO1Yuwle2CaJg67A8ZKkvJR4wZQlHK9zDJ5/du6QamIru/RJsIHkTaIqf01ikgRWK+X1E3D/lB9PUUqzDC5Q9Ny594D8qLA9QP5aiUIiijm7Xfe4Ze/+Ii+a4jtOWlsubm5xqP41ne+x/5Q8Rf/5c+5syp449FDFsVDDrv9vOLf0c3zqCzL6YeB29sNfnAnnU25XPLFk+f87Oc/59NPvyCyMf/Df//fkqXxTGx0VNUBDVKgED3XOAxMoyMvC/nQZBlxIgPY4yD2SDXo+558sRRby7Tn/OLOqXjcuXNBVVWn68owDFT7W4LrUFoxOHB+YpxGHj68J3qyseHqakuRr6iqA9c319xcX3N7c8v9e/f43d/9berqICSBEFgul0IIaBr6fjjhXqIoou86rDZMveQAroqc4N1MWOixUYzyE7mZSGNHca+AwbIdJkLtcU3Ds+stHZZsAa+udhKiUYluzeqATiKKSOHVhFKaq03NZt9w//4dmq6j7QbGcaTqOoo84/6Du6iZfZ+mOUPXEYKfaZ3xSbrip4lkHpwf52zHTepxgHzssoZhwE1OChWcwIIK0ZFaayiKjL5tURqsDiinGb0nzyyPHpyjbMqh78issJWGyZHGGdUY5ut+xm6/J5gElGWcFPuqJ73IaaeRpu0oY815plh9/9t4U9ANI2FWsgeYbU8jOTlGS7dRVbXgZ0pxBrhJUL9NXQOe84tz4ixjchOjG07zGikmcxR5HFGWhXRe3nN5s+PZsy9ZL1LqqmGcrWfHaDA5wMLcREiyOMjfR+eE9jnM2OPZAMxcLI9SHGssDiWMLWUxRpZSwvNqZkmNaBad80zjxDT1WKuI45mwqubf1xjcLNsAiOMIhxcngod+/Jpi1pMkoRsdd+4/Ik3TuTobDvsdnsC7H3zAdrPn3oOH3Lt/n1evnnPYHVA25mx9wXJ1zursgmWR8Ozzj7i+ueV8vQZruL3d4PqeciXJr3XX8vLlK7wPWAQzkpdLXl5e87Of/5zPP3uC8oH/4b//5yzKjKEfRJTm5ISJtKLZ70ni6GStWa6WdMNIkqbk5WLe6CWnUyLP87kw9LO5tOfdDz/Aas2TJ0949MYj9vsd2+2GKEpZn63ElzQOxGmMGwN9W8uDUhSn9NfD4YBW0LR7Xry65osnX3BzvcE7xx/94z9gHBxdJzM+70cWi9VJJyTweymewzDMDGmJun/88B7SaogZd1GUtG3N+SJDtTV2qihiwzgZVJi4vtlRjTAYxeJixeQNu33DZrPHB0+eGLLYYjDEeBo/ULUtX/7qI9xoyNKUMsvZbhva0VO1He+9+ZiiWAkJwOjZfR9Ik0TirtRxKK6ZnAhpj2p74DQ8P3YFx85qmiZsZE+FLDDPSLz8GnGWoHWYH5ie4EeSrMCNPffu3eXu+RlfvtxxODQ8OI+IVKCILTe+5dB0xFnG2I30g2OYJorFCr/fsdlWEhraD9T7Pcv7K946y+hXloOPqJpWkC9KnzDQUSzXw77vgHBKpb69vaUoFmhjZV5XFpRlwdhLBxq8xJJPbjx1k0dJTZZJMUdLQKeyMffffJOh2tO3PW6cWOQpRbHAWM3YN6cIr67tKfLFSYcmr52l70bi1JKlmcyhTIyfaqYw4ed5c5LEuFFhlKZNJLtwcgOSzixd4tA7lDricF6nUgcUfkZ4g8xxCcIYM0Yz9CNlIfPbfnB/67rzd5IgNL1jeX6PopATYj1TCrqu4dGbbzF5w+dPXzChSfOCD7/xDbS15HlJZBPaZuDFi5dsdztW6zPZ9DjHZrul7weSPKcoV7T9yIsXrwAZYE7BUy5W3Nxu+elPf8ann3xBXTf8s//2T1ksi9kWU5w+7IuiwPiA8RPT0KO8MMCH0ZGXJVEUn2QFUnzjk9Wkqiq6riPPcx49ekyaik5LZknd6cRSeKahY+hlgBlZaXfdNLKYTaXHTL5jl3B5ecmnn3zGze2eum74B7/9WyyX5el+Pk0STnH8wB4jqkM4RpJLB9C2NetlQQgTetZ8iUZrosxiCuOIXcV5kYGXdJHMaKIwYcJEpDXRrCxm8litCdOIUYHUBNZZxMWywE8TVXXg9vIFrm9pm57gNcMUuN1XJDbi/v37WGPnLadFoebwx3T+c+uTzCBLM7IsO4kYjz7P4xXkKJQ9drUej7YabTXDKJl1+cyhSpOEoR+I4pg0zTA6QhvB3WKEce/bimUEWWJJI0UaaSItcgSU4Xqz5/r2wM2upu0aIgPWKLbbHc4N3DlbsF5kXCwS0uFA5CVktm1r2r49LQkCnGZs0yQctcha5tYYY5BOdxAJiZ4XBNubK/bbW9lmJ2IGd+NAHEvAqHRDXtDI2lCWK9J8wc1mL3qoLCXLM8ZhoO87uqEXoeToCGE6kRmOHC+UOhFsxcUgEpzlUhKVjDG0fTeDKrvT4JsZcnjsukRqI4uCcXTYKEFpi5+RLcKxEjmCHDyBKLKnkFRtDW0/8rf9+jt1UuuLByxXAjFb5gt8UNxZXPCN7yzZ7Q/87Je/YnV2xjvvvEXX1rx6+Zz1+QXaRORFwW5/izaQZCmHTcV6teL29haAvMgpygVN1/Py1eWMaZUt4mJ5xu3tgZ/+9Jd88vEXHA4Nf/Znf8z9+w+pm4Z4XmsfOyOska1PV2GsRStxZRfrFVGS0vfjaXO3XC7J84Jq1iRprVmtlictz83NjVw/04zNdkM6pwnjJzZXr0gSyc5TXmD0aZZiI4OODFqZk/jz1csbXr58xf5QsdlseeutN/nwgw/ZbXeCe52LpUghhtPq94hnkYBJ+edny5IkNnPqzuuClkbw3uNzFqEns5q+bqHvMTqQWEXmPPuqYew1Kk9IXU9pR7wZePzGmixWZFZhFaQzwnd0DoPi1eU1X24ahgDt4OiGkbfeeIPVek3wnjgyGC3XOhtH83pdkab56URPMxHU6nm2eexirTVkWSrOea1OhWscR4qioOs67Pwht9bOUgt5r+M4wTtDlBu6piLowGZX8fD8jO+8c5c3swEzdsTWEHqPDo4w9uy3O/q+ZVQRNik5W2Qsz2NuLm/QJiFKIspUU6bCvE9CoLq+ZJmtqAeZ47iZy54XxYk+0fe96Otmi9I0jox9z257S9vUTGtJsPajI00TjI6pDzsm11Ptd6ft5+hGvI+BeS6nghSFKVC1PWq2xKCUyCAISDCohKxmWcpuJzPWI2ljt9uyXK9P7odxHE9oIT3PrvJC3AKH/R49Q/qGcYBZq+acQxPY7Y6Rc9Kw2ChhcC1RFONm2Y/3Abw/ESC890SJIckyuuFrKlLL5YJxnDi/e5euFyD/3fv3GQfH50+eAZr79+7R9x03N9fz0FM2LvX+lhA8xaLAh4lFueD5sy8F+raQolA3jaTO2OgEnsvzksvrDT/76c/4+OPP2Gx2/PjH/4hvfPN96lpCPkOYOBwOs84mEfBeu8HmKeuLu7x88kREnWmO8x40LPKCLBPQ2jDIkPfYLVlrSdNEuqqmQRtD3dQolGyWnGPsauLIyI9Hhw8j49BLeoiCRblkd6hIs5Tr60sury65vN5wfStv/t//LaEbdF0vJtRegjBPQ86ZGnC6/niBpuVxwrLI5sJkhIqQpKSR4f3Ha87yAPuBcVC01Z7YT2RpJOI8oMwT3OAxrmVdJvSlInGas1yR5RGpMbR1g9WyQJCTN3B1s6efDN2MlcnimDcfPyaJY/quJUsT8A5rEHrBSZyZix0jSlgsVwRjXi9BZt2TJpAllmkMYBRGBZTS2K8wpuS625+oqMF70kSinsI0kaepgNuqPZfXG7aXV/zGh/dIi4xh7FFJIViUMLGMFes4EJ2n3FQOnSi06/jwvQfcjR3TpBkQyQRaND5FqshtS7G0OFvy8rY/+VSTOD4RA7TWgtReyUzz/O4FaZLSdS2r9ZosK7i6fI4bhR0u3reBoW2wRqG15KUaFYgj+Wx7L1C9dg6yGIYBbTVJnhClmSBV5tme0RqtZEsqYRbHhRfEScToPJ0bWRaFMLSMmSUPcs10wzBvlQNJmpCm0g17jh2Ym2dxHYvViiSOqVshwx6Nzcdw2EBAzQdsCAplNFEcUZY5dfM1URDGaeLi7IJq9redn5+z3+/5/LMnLJdL7t+/R9e1jENLmKbZryRxPNbIQ9fs9xhrGPqes7Nz7EwYbNqW29sNeV7g3AjIoPzVq0s++eRTPv7kMza3O/7xH/4+P/jB9xjGgSJPia2mrg94P6INrM/WDONImcdsrq4Zu544jlDzqRCnKdlXBrUiSqxPrSxw8tpVhwOr1YrddouJY4pFIXOXTqOsmbdWlrYTcWg/9GR5JkWtrhmHnuA915fXXF3ecn29Z79v+PEf/gFFnkmBmsWjR1xJ01SnLd6x23BOsDjee/JFMp/ASpTlSrLasjQhjgy3r16yMIrD0JN6mHyg7Ue6sef60HFwgZe3O4Z2yc3kWJQF6TpHK1DOMQ49fuwZBysFSmvGyROMxWC5vb6hrlvefust1uvVvEnSQoHUSlTQkei05LSeZ1Sp5CdG1jK4ieViQWCOWJ9V8sfB7zB0GBNTlAux4MzvTZblJ56RzTJ8EMGs0pZxnnuV5YKuq6kHRzsIZWDSHozgc9Q0kSjPW2cFE56rpMZFCsNAESny84Khd1S9Z0Tj5uSVJLLcP1/x0YsXuPQcYxaMnaMoUhZLYXcfMTNHlNDgHMpYioUYlSc3UtUNaZpDYumbA2M7UuZyxW9cz9h3ZMmCLJXPhdEGN47CK/cyFO/6ijRVLBYpaZYzuulk1G7bdjbPv3ZGqNmmEMcxfs7hQym0NaA1xmr6Wft2jHxHyYYzil7TUG1ksUZcH3Fi8dOEmyOufBBJiLxX03xYK0lSNqLuj51DK81yueDFYfv1FKnV2Tl9P5GmGQ8ePKCua169uiTLc+7fv0dV7SF4/By3HEJgv9tx98F9bGSo9mK+POzkirNer0/Ze23bcXFxl7qusFbmFVdXN3zyyWd8+tkX3Nxs+I3f+BE/+tGv0zSVMMi9w08KqyEyljhOud3syMolwxRIFmtunr9gfbYiX65QJjopntNU7DBVdTj9+Y6cnWNaS7kQtXK5WKC0Zhg7wgQGGCfHNEHdC3i/63uWqyUKma9UdUsSR/zi57/g8uU1l6823G4PfPObH/Dmmw+pm2r+PQ1aydVIBpPydZxlDcNR9CahrEWRQvBM/nXseJJG3H9wgWHgUFWE2LBKNKHtyCLNrh243bfU3nJVd+x2Nb6RJJfusJMIbww2tjBNFEVG5z1t2zE4Rz85gjE0zcD1ZkucJDx8+ECKk3fESUSYnHRB84l+HIg7N8IMx5OryXjy5IWZp51EEc7JFabvO7quJYoCK3v2FXGobGSr/Z40TeRz5gJWWdQRhYtYjZS2BBPTYxknyJKMvmkZup6ma9nXPZFJwARKYyCGyUz89Ocf8d0P3uG8tCRNx67q6ILCa4O2lkUO54uUnRtIM0llvnv3HK8jXl0LCjrMRVVmarA71NgoQysol0vqw554ZjclkWFsZEtobEyYJNh26AeSyBCiiHEYRZc0OrSRGWp1qIlMRJmXpFlBulwwNJvT6+q9zI38zDGfZpzPMIwoI1FXSZYTRfHJEC3RX1IEj9q1tmkJaQzBEqdCDrG5bO8ia0EJM11QLzF11cgtSM95jEcfq1IM44CxFhU8q2XJZ59+TYrzphlZny04OzujbVtevXqFUqJ9uL6+JPiJuqrI04im3rPf7SjKgpfPn3J+dkaWpOx23bw+XjMMA+PoOBz2Jz7UMePrdrPho08+4vPPvuTVq2u+/Z1v8rv/8O/TNgfGvmKcHFGUzEXBCuZlmGYrgsYFi44y7j9+TFtXLNdn+ABD25NECdpohr5naNtZpOhRs0iwnibyLCPNMvqulcw575nGhna3JYsskbFUTUMUxfTDQFFIRLeJklkmADdXN9xc3fLls1c8u96wXK74B7/9GzJ4PLr7/XRSZI/jcBKUhgBJktJ1PXmWiRShTMmLlGkQooS1MqBcLBZESnFzfYO2CYd+YGgOvH1eELTm1XXFk9uWm3rkZlMRxha/iDBMmDxmHAbadgQbUZQpZ7H4+kxkcZNnXzvGSXG13VA3Pe++9Zizs7PZ+mExSuG1Jo6swP8UTEFg/yFMLMrVCbYmSccFWinaviUExzRaceFbsdwU5UJwK0oKj1GKycu1pSzyWUM0iZIaTgk8YZIOWNuYWCme3VQ8zxLeP4tnFfQkyBe8IG5HTzJvqbNEUQX45ZNXvHH/DrFRmMgyHDpCJATUqvNkaUxb9RSRY3G2pBlq/JiQWkXdOcZePi83tzcsVmdC72x7ubqhKJdr+nZP8BIgEqcJfhxlGN/VRLHFe+mcrTY0vcg5RjdgVUQ/CJgxiROsMQQ9x7DNMyNrLdoa2dYFNZMxNOPYCQwvihgGN3PVBC7YznmQWZqx37aynV6doWxEvbshshrv/MxpF2/fEU00OtH+yUYvUB0O9P1AlkdMTnx9RVnQDTI89yFw5+xshhF8DUVKzbHSh8PhRIVcLldcXV7KBgJPmhh2m0uefvE5WZ5hdCCfgweuri+xxrKcY8j7OfFisViw2+1m1bGYbn/10Uc8efKMq+sb3n//bf7g934b5XvCWGPDSJqn7PYVi8WKE3s8TOA6xkH4P+M0crFestvcMtQVJk5FHqJgv98TG0NdHSRXzXu0jUmzXHAnM+HST5622aHciJp6THD0gyAsjJUXvWkbykVBVVWkZZgDHTKePXnKy5fXPL/a4EPgD/7gH85qYv8VGJw/WUhEr+JPhIDj4Fi43vDw7gUqyMr82BGu1iuWqxXPnr9gamoiC/XuwFtnGTrK+cWX1/z5pxs+fnbJ7aHBDT33yogiXpB0iiJP8V6RpAnbpoVOEaUxIUjEV5ykdGPFvum5ud2QFzmP33xTiuk4CAd+lIfQzqQCZSQGTGuFniPBjhvUk95JKawR4aTEIolWLbKWoevIz1ImN87X4halE7mSWosiUB0aslRSaqIZNujnQjeMPTay1KPj08uaB7kgeqK4Ii8yJhtRHTp0kE6v7wfatkUtCi7/v+29WbclyXme92REZOS4hzPUXNUDugEQDYDGQIAgCZICIVAQB8kitUSv5b/nX+Bby3eWtWSak0QRY3cN55yqM5895JwZGb74cu8GL6zVWDZsXlSs1RfAqu46w87IiPd73+e9c/zk5JosS7h3OAMCjJfy1TgY2Gxb2rbn+pMXvP+FD2lGz4D04zk3MDqZ7DnniGxEHCeCYSFEBTlWB6g4ZNtMFNsoRtkIH8hp0Sg5ddpQGO7j4Bj7gWiC2o3O0fUDWRIThRJncYO8tIB94N9aOdm4yS7hEbE/DDVNXVEUQoaI43jSjgPaphZyQhzjdchR/kgavdtS0DxuIpdOmKAwjLBRRF03+8n4fC5hfRsnDKME6cdp4qm0wnlPPp/h+l/RJtVPV496QvRmWcblxTlukCPpLIu4vjrj+uKcOI6YZTmLuXzQy6qUyUUccXNzIybIsuDe8TGbzYaub6cgcMUnz19wcvKay8tbnj57wh//8R8SjD24BsZumvrJVcGYyR1iNHSSAA/GkWK7FdpknrGcz6lXd8wPj9AIUK8uK1ZdSxxZqtUapQLuPzmiHRyLxYJyKidt6orAdYQ4mq6ByfjWth1MG6qNxGU7uAEz0RFfvTrj5avXvDy7ZFu1fP8PvsvR4ZK2avBecLTD0O9H103TSPh5MuntRModZWE5z1DeiSA61UIl07Ss6wdev7khYiBL4OnDezxcxvzlj57zVz875yenF3g0TedQk8kyiiPawXGz3hKgiGPL7WrNoyRiU1esa0fnA4xNqbuRq9Wasq754IMPOL5/zNh1EnfRCrw8GKG1U8nBrnpKNLs4TvZoFaWkBsm5AaZaIz+OKAKsCYmTmKZtiCMrWOihJwwtWZbg3EhVSPhZkuwiagdI2URkLX3fEnipJ1dG86Zo2QyKwzRjvmjxCQSl9Eeu1wVj56ZN1VOstvz8uuJvfn4OyvDh+0/lOhrlfPTBMw7mEYtc0fae203J3//oY44fPGKgR9mYODR0RsuEa2ItLZcLXr64xpicYrMicC2zeUZsLX1XE+qQZsqYpmlGW5eMoydO4gkAqaZWFrPXIdu25Xh5QJzkROmcru2lJmsaRsg0tZ/qwIKp39FR1i0Gx2w+E7T3NBHP0oRyu5HY0URLHVD0Q0+cZXS+30PqJOpkqMqSyMY0rp7ayvUeVgleXhrjKPgcP9INvfDAbCiEW/SvZpPaaThN23B8dMTV5QVGB7gA5rOEVx//hLvba8LQYkNR8Uc3UJZruq4lz2esVyvKsqZpGw4PDynKgqaVrFFZ1rx8dcLLlyecnV1weHTEn/7RD9BjR9/VjF07tbA0jM6TpJJnC5Sm7QbKukGHMffvzWiqik1ZcHdzzSwMGcuSJtRgY0aEudwPHdZo+kbE2K7v0SZkuy0oyi3BKCcY5Qf8OMiD0zREJkZHMU0ro1kpdIgZhpHBjTRFw49/9DMub9esy5LPvf85fu3Xfo2iLBinwOYYBHRu5HA+p9xuJWcYfmpu3NVFaRXA2Eu1V9/Rd8K1btqaLM+lKuzuFu87jIHEKB7fW3B3u+LvX11z2zjeee89NusV5QbUqFnOUpIkRSFa0822JKwbxkATpQlVB+vasa4cThluyorL6zviOObpk0fgHcYoZmlCwAjaEFo5FYhWIW9mExpUoPai7s6k6RnxTjamyEZ7Q6BgQEZmeU7gp9okuedN2ltE37cwjBIb2l0RkdB717Y0jXC2Yhvhx5HGG+6agPdUwPxgQXlXkvicMGkZ1iVdK655rwK224r1tsDhadqBH31yRpymxHHF5V3B5995wBfef8rTh/dZtZ6fPj9nU51x//Fj4jCCHUE1y9luC5YHh8RRIoTX+ZxYKbQXI641inGYNLphoG9bojCkKYFAXrahtYxthwlDgskM23c9TduK9yubEYQRTIkMaSTqmeUpuz48N+lkOE9X1VibopNc9K3eC/63lwnijrPW1BUmTqdKuhATWnrX7W0EASDvoBETxvK1OSGhqgCMEaNrkogNI9HpNLXu0WFIlmeS8ftVbFI7IfThg/tcX1+hJ8C6Chw//Yd/oNjcoZQmzzMODpegoOvFGLZYzGkbcdc6N3Dv+IiiKPcGxrZreXV6ws8/ecHZmysWyyX/6o+/h1WOpi4ZnSMMjbTDDAOzXMovu7bHWMPl1Q1pZKeMkGN07eTCzcRIFlnqYsNoOkZlJDk/PTRHD++D0oRxjFKG1eqOri6IjZ5QLwFtVwuz2cOIx0YRUZxO9VcdShtsnNIOPR8/f47znnVVsTxY8r1/9rs0bbN/4/jp781nM4bpF28mL8svmj+tDem7hoOlhLOjCZ5vjCEiYj6f4d2A72ue3F+QWk3iS5JY81dvbgmzJQfWUVcVo5Px8Hy+JE5iOjeKjjcIFdNoCf66MObl5QZsRu8926rhblvR1h3vvPsOB8ulNOVOV/NxeoOHE6vchJ8GibMsR/FpGYNzskGbUFOXBYkVSqkNreTG+o5ZnhNFdqKcSttQaMUsCwFKa+qqxmjRIZ1zWB2iA0UxGT6tFURKEBgCbXl12/HVDyQ72HQDt5sKbyw6TVBOrByud1itOMpjNo3HRzNuVhu++MF7k+Ac0nrNqmx48njB1379y2QHD/nkxSlVVaOjWMo6M2E4HRwcYI2hbQrxStUVWZpO1fI1yo/S1jwOJJFlbCvZBLwn1HK1ShLpFnTOoZUYMftuYHAD81nGYnmAUgIYDAKZBpdlQZrGgkhWCjCYKMEXNdZGuGHcm2BlE3NEZuJ7aUMLdE0rdmXn0UmM0xptQnIrJuiu7/Ybmp0mu0rJi7XtOimsLdbEcUAQjHjXkVpF7xx+EB2Q4Fe0SUVxxGyW8ub1mWTLioIkMbz4+CdU5Vb8JGlKklq6vsEGln7oph11oCgEDXt0sGS73TA6R5bP6PuB55+85JOPX/H67A15mvLn/+aHZJGirqQ5eHCO0IY4/6kr2/sAH8DVzS11XXP/YMb9ZY5raorthrosmL33ngReh562a6i2FVE+x1pLGucsjw5kgtW2WOUpt3dEDASBx2rBuQbKEOiQVdUS6BSrExZH94htRDw/oGsriqohWsT8/Oc/425b8fryhrbt+Fd/+gOSVDJiUuX0j1nfXSec9KHvMVqKHmVCM8U/zEQkMGIqdC7YY4n96Ck2G9LIEjgY+pan7z7g4mbN9UayVtr1tJX4yZIsY/ASqB39AIFCh5oh6AjjGB8arlY115uBsr8D72majqpuiazl/XefCQZGQ2TCyRekMVq0qF0Ocndi6vsea0KSRApTrQ0nDnsnpthpoqkm5ns+Szm+dyRFHjYkUhE+UMRpKrGOKZ0vD26P1ol0JnrPiGyEWZajVcDQd+CkAv3l1S2rsuEgsVRtz9W6IrAxXaDRcQwKkthwFEUMYcvp1YYwNqyUZ7tZ8dEXPqScfERea7qmwuqIZ0/uE8YxJ28uwEut+HGe03dikiyLDW5oJ6rqSNMVhDpGBaOQKccBjbDUCPw0yZXvT/TIdA9XxMsVuSwr3ODI0ljG/FOOUE0Ofu89ow/ouhG0xoQRxqaMai3u8ChgPl8QJwl+lFq2wSnappnY6NO1raqIM+F4hVGE9sIy3xlwy+1m37u4QxO7ccQYS1u3bMobNlVFli4BidnEJkBHEVHSE0bhr2aTSiLL67MzsjylbWqyxPLm9BP6thImeJJMKIeR+WxO3dRTfRGUheCBkzSWALBSJNbgBsfLF6/4+OcveH12jjUhf/bf/0uyKKCuyn2dVBAENE0rwLnpreFR0vPWNcznKYs8JRgGtmXHZmonjlNLtykoiy1oT9e0woTGU3Udrm/3I+yL89NpfCrC55vbW2yUcjQ/JL/3jG5dUVc9QZxQd4rRew4O73O3uiU1GSdnb7hdlbw4Oed2XfD1b36NB48fcne3IQw/jX/s/E9FUaBhyrRJQ4pHDH27MbtWBjd0AtufKsdVIGbJcr2huFvx3kfvsVndofuBYRj5yctrbsueuoPVeo0KYDlLadqO7WpNkmYM5Zo0SaWOzFgCm7HtWq4v1lSdp2haIiNj9OVygYpyDpZCprBT1fzQNjJdMgbnJWvHdFXd+b7EyMekw0kIVQYHu9xbJKfTUbhEbSt+qTSNpZ49MHvkbOg1XeNJ8wzXdXRNg9GhjLiHnkApQhPJSF3LhMt7uFlXXN2VzELp6burWm7f3LGYz5nHGWpsUHjiMIZtw+OHR7ze1MzznLvbFaEx/Pr773B2fsnFxRV0OffQ5Ac5H7z3jEAHXF2v5HuOLHVbk89y4thSNTVJmhBFlswGtPWWIBhwbUM46XNB4PYnSaWCyXMkN5e26yAY8Z4JoNgSAFkao43A64Jpwte4EeeleXscPSoMGUbPiDRWax3iCQgmA2cYGpq2JphoBbvr3OC84I7XK6IkFjOo0r/AJQ9I0nSSWoLp9GqJ45i263AqgFKzLRuiSKHCiKaWkoeUkTROWMxnv5pN6sWLTzg8OqCqStIo5OzFz2makjC0pGnKfDHn5vqG2Syf3pyy0263BX6EJE3oJiZ1nCQ4Ap6/fMXPX7zk9eUVgx/5N3/6Q+aZodhu9iPVnQgpqAgRrY22bLYVZVWTzzKyNKauK25W5xw8fkcoBuWWyEY4XVJXFVmeCtSr/7S9WI09dVOTZwkMLV6HOBStVxy98wHZ8h4EmtV2yzD0ZFnEbCbh4Sw0lMUukFry/PkLXr58xe3tiuPjY775zd9guy0m34zaZwV305FhGPBK4WGqApcw5WKxoGlKjNZTHMIwTI22QRCQz+Z0bUlVV2TzOfiRLAbClH//ly+43mwJ4xTtW5qu4nAxJ02kirxU0E5TNGUMYRBgek8Yp7TecH5xTj+MBDhcM6BNxLPHj9n2UunV9/3EtBrRoRHCwTSVSmwsfbzTRhXH8RQ5KibXuJwk/eiwcYiZMMuDk4hIPLU5d107UTmHiYkkBaYmUETJiA0NahxwXUfb9ugoJBgCjJoQK0GA0mbaDA3rdcntquQ4AoPoJ+0I1Rjw5Og+3c05ofa0Xh7GeRpzcr2lKHq5rg4DeRrxta98gfOrFacvJw7YusYujnny4D7eecq6J7QRq6sbkiTl3vHx1A1oGNqapq3pq5Isj2VwoDTFdjtJGJ9Ou8TxLVnNod+RPgEv+F6tFbM8x0RWdLvpz4qlxTObwskqtLi2pWsbrI1Is4xmECKrCUMpWnAjYRzSVDB4LxzybEZTCuFhs96IxjX9HXJSc3jktNw1FUmeU1cdIKf8ZhjI0pwsqbGhRRtDGEfURclMKUYtE//Pun6pgHGaJZRlQeA6Tp//lGGQIO58NmO5XFIUWw4OF+SzTKD2zgl/Kc149OgRXduK4ctaBud5efKan33ygtPTN9R1zR/98Hs8ebika+v9w7wLOSolTbZN1TD6gLqdJhN5LrEQK5MmFRrGvuWDDz/k8bN3SNJMzIE2pO16slSmfQwDgffTiTBBK0MQZ9w2jtn9pzx45wO2RcPV61fcnr+iL27JrGaexeRJgg08t5cXbDYrhqHjr//qr7l4fcGLFy/x3vMH3/8+dd3inN+HO3cTr12YWdCqAV4pdChtsaEV/K5wvYPpKD0wjNC7ETOVQBbbkm1RMUzX6STJ+N/+9jn//i9/wtl1QVm2KD/ywXvPaNuBk9e33NyVtO3IJy/OWR7do+k7vDIsjo6ZHRzSB4ZVM3J6UzA4T9/UgoUZeo4Oj/bX1NGNuMFhwogkzbBRLMHf0OwxyirQRFGKNhFxkpPPlqCE1pAm0f7qZ6YIVBRZjFEThlcMvqOTNl4YGbqWvmmIQjvhkuckSYxNYsmG5jNsnIhNJorwQcDoA9qu5+ZuRVFWbDYb1us7jpdzkmxOdniP9OgBOj9ARylah8xmOWGoYQyom5a6bTh/c0ax3dLULQcHC1QY8+L0SiJR1ZpXzz+mriu00QRKiwGzd3SdXOGN0RBIANuEFuUhGN3+87A7wYBMzj/V8By7Wg+tpZJqtZH4V5omoIQO4YaBrmvZeSfDUIgS8nX0GKUJvJfTurEkSSZs/0DtyzwCowmjhDjLGQOIs4x0MSfOclDSYbCLj7W1ABa7vqepSoa2pakrlJJJorWWg+Uhi9mSyIYEk5bogUk8I8s++yb1S52ktus1B/OU87NXBMFInMbMZhIYvbu9IZswotvtdh9GNMaQ5zNpSm0b4R0FlrPzC54/P+H160uqsuJf//Ef8vn3H9PUJcPUL7/HlU7dchKIjBhGP6GKE9I8J88yYh3QFCsePnnE7dUtj7OMhw/u4YeWqtjiA4WeQpVFWeCVeEq60TNLZ3ijmeczaq54+fznbLZbZnnO/XvHzJdLjE3EmFfVbG/OqYs1HpgdPeTjFy85eXXK6ekZm/WG7/7u75AmKUVZTbpTJ8jfyTawCw3vrAQ6UIAc86NYritpEtHUIqba0MIoeTYVBFR1xd1qTZQmHN87pt6s+E9/8yP+l//wX0izDNdJCPQ3vv5l/uNf/i0/e3HG+U1BZEOOZhlNP3J1W/DoMMfYmPzgmGQ+49XlmnYMuLgrWGYRGRAoz9HhAWa+mK5TBms1wwBxkpKmCc4NGCujdzX0WKPJshlxkjF6yPI5kbVU5RqlA6IwJIlDQhOJSbFXQniMLU3bobXkQpMkRQVKtEF6hr5GBxFaK6pSOPChTSAIxa3eSaQjjsSgSqAoyoqua7m+XfHIxhhtOV4c8qM3NZ9/9Jg4zwnuPWRcX9LXd1gbUw0l7ehZ1TWBH9nWNV3b8l9/9GOuNhV364ZtOXCx/hnf+uZX+OBzH3C+KsC2xFHC0fEx8/mMpm3QxqICRZguMKEmsBV6rOiLDXo0v7BRfVrssaNGgOBRnJsIGG6grht0GJAlMYFSk2GyQSrgpxZjJQWoSukJFdxPJAUlRFytccO4p2zUjTSAZ7OcJIqlGDfQxFGEtrFc84xQJkZEf+qHKbysFN7JiW8ce0KTCJnTxty794C727upxmyqHHMi1SwWi1/NJhWFhjenr7ChJoxi0izFGM2rV69YLBZkmRztdynrcRw5Pj7m9u4G5wbiJEabiKvrNS9enHL2+oL1asOf/PD7fPTF99mu76hrwaHsNrvDw0MILH4SGduup256tIlYLJYyLdKGYeyYL+Z4FRCGmquzVzx+9z3GvmIceo4eP6EvNzRlgdWaom0ZvGd+/ynzh0+4vbnik5/+jLYqmM0y3n3yiMXhITaK8IG8ifpyTblZgxJHtY1TXl9c8POffszN7ZbX59e88+67fPTRR1ODbUzfd/vqdTOZNndZvd0HcWdkTONITg+R6E+73NU4SpZvPpdr9HZT4Ea4t1gwDh1ls+Hs/Iay6fn8BwtyA1/88AllseYnP3vO5abkxdUNkY0pmpanD464WZUkJuD+w5zrqxveX87RATRVzWbT4oOQyEb0bcFifp+KkdBGBEAYmj29QB4suV7keSYt0FFE03a03Y5UEAqvKstR3mGUcNq1DtGhoQ+kx08piVik2YwAhdGGstzSthXe9YQKAteRpjlVWSBZv1F47FU78ab8Hmuze1FGUcLNpqE/0qRJjNMepTSvT16juiWP7x1QuQa/WjM4eHO5YlU0bMoGxpFXJ2+4+2jN595/h/DyllV5yl1VsS0aWvd3/Hrd88GXvkK+tNyVjgePHqCVliKOcSCO5kLGUAGhtrhtJ+UO40hkLV3bTxqdeId20L8d6iYIdnqep65qwlBj7YQWnmwJWhvGvmd0wx6Pswuh931HWRUobYgigQj66eQWRTFN3ZKmmehSAcSJ4F+MjYnSuVR0OU9oLc4P+8+tdAYKDz8QNLrgjAhwBGgd0rY9UeIxRhDSbnCoQK6rv5JN6uzlJ8SRjHeTNKQsKi7KLfnk19m5TnfVRcvlkrqu9zU3xibc3G75+PkLXp6c8ubikh9873f55tc+oipW+06+XX1TlmWTGDvietGltkWF8wEPjx4SWXmou64lChVxviDPM5ptQ7Ne8bO/+T95+OwJi3v3UTYhC0aGtsRrzeGTd+m9QUcZJ2cnMFQs5zHLp8ciLI8jeEe1uWGzLaZKKnED6yjGYyiLio8/fs6bN1dcXomP6Lvf/R2223IKDru96O+cw4ZSG7QrydxpN7tfOjsnthESgVgTzN6WEEURZVnSth2HBwdExtBWKx4dRlijeHA45/EyJY8CZrHmr//m79kUJWXbUXQdAyG67InXJQQa5+Q0+V/+/j8TpzEPDpfkscaGmjyfkWhF31RUdYULNVGQThsA+4FGURQTx1xyYEmcYK2UmErLiNnrU23bEocBQ1sRxrlc512LCbzkH5tWigWUIUC8NlFkaasObYRAIcZhcVcrpeiHARsnxHFMUzfEScowdJLfY0SFIRe3G36kSv7wm98iS0Jim7Dd3PH6zTUH3/kK4ZN7ZPMZxsYUN1s2ZUs3ipHVu4Ft1fG//8e/5ju/OfKb3/k2jx4+5n/9D3/N5W3JMMJf/vV/4ccv3vDfffu3GYKIo9mcdHoJOSfNv4v5giAwlEWJGaWXDy9DEz+dksPQTD/L6NPPxLQZGGNw3lMUJWkSkyQRobXTvyt/bvSCc1FawQCBCvBO7C02DNk1NzdNI6eyqiZNU/J8zjD0NG3FdrvFjyN92zE/UCzvZdRNSeDlymdNKLk8vISHjQx7wigitBFt3UpcTWmMCXDDuMcTS2WcIjCK5XL5mfedX0qTGnohcUZRRFXVbLcb0iRmOZvhhoFtUTBMiNij42OGnTitAgJtOb+85fnzlzx/fsLFxSXf/Z1v83u//RsMfYNzI2maToKa3G1ns5mYArX8MJS1zPIFjx48Yj6b4Xqpro7CkNlsgY1STJjw4N13+fxHn0fhODg8QpmIYrPFhiHJbM6HX/4qhw8fEecpoXEczyMeHi959vQpy6NjtNHM5zld37LabIiShDjLGLyndQ7nA5RN+Pj5Gefnt7w6u+Tm7oYf/OD399NM0dOYaq9ls6rrdl+DJXAwjdHy1tSBwruB2Ib0Xbtv9t3pFWkqyJPNZksUW2bThNUGAVlkeHh8yL2DFFe3qKGnuLlguy0YvNATg0DD6InilKbuOH9zjhsGXp5d8tOXp/zDj3+O8o7f/NbXefzwkGHoCJOMxin63stkaKrvMsagtNq32qhJa3JDT98JBSOOQ+wEstshWaJIsC4jnt4NeMbJAzfgx3EK0Rq6vqPpGqq6YByELsAo2mQUW5SRTjelFFEszuwgCISq4BxNPxBowcrUfcfp5Q3PL7YE2YL7T5+RJQmfe3KP46MDrq7vwAtq2o0jbTtgkpxN3bEpGupGSAZN23Fzdcvf/Ke/5OEy51tf/oCPPnxMZDXP3n2fx+99gX7UXF9fC/e7qmiahqHtCI1hdD1919E0NU3b0tT1PjzeNI3877abCJqf3kT8BJJTSk8RrUZKG/KU0U8bBQG7FuK+G6S7r3PsqARd10+kCk/bdVKlPnxqALWToTY0FhNoDg+OWC6P5JlvZZpojCbQgVgUtJlc8Qn37z8mzReEYYIOhVCKR3xn0+9919IsNg3Jp2azz36S+qU2KWU0y8WCHTkyzzOePH40OaGFgWSjiCTNRVswIVGSYeOcq6s7Tl6e8vOfP+f09Tnf+c1v8L3f/TZtU02WhGCacohpM00TCYGOw/TD76XmZ7ZgMV+g8KRpQpomZFlKkgj1sSgKtNKs12vK7ZYf/+e/wxUbnhzNqLcb6k3F3/2ff8WP//Pf4qoNvl4xjwPSKMCPDd51EASURSlNMYs5URwhU+GA0MbEScbJ6Rturu84v7jizfkFX/31j3jw8CF1I0wpORFGgGKqhBO+twn3VVvGmAmtqgGHVkhhw4QJ3k028zzHOTc13sLhwRKQB8G7nsV8wWgi7rYVm6Lg/vEBsTEUdcfgwIYxiU04muccLVKOFhlKeRzw9z/+OVerkh8/P6Pp3JSXi4msJjAhPkpRcUaazaXnzWgio5mlCUaJ/pPEEWkSM89T8jTBBIHgaY3eb1LWhthQ03dS7e16afbdbXJdPwglYWrMaduGoizopgqyoij3J0o/jgxuILSR6FZKrsR6hy8eR0YPo/Pc3W5YFyWVhy0hhAlKG776+We88+SY282Wpu+JUskBvnpzw/PTG+62HUXbU7cDaWo5PpzRNRVd0/IPf/fXHC1i3nlyj+U8k40ztKT5bM8KB2EulVUpm9EoHYlxFBOgGD0YHdIP/fSzsWil5Xawj159ygEPAkVTdzR1zSyJsHGECq20BjvH6NzU/AKjV7hxsqpMESXBHQuYceh7QaywSzgwxZUC4XjZiCSfM5staOp67w0fnPzOhtETKM3Qj6xWG7phYER8YrtGH/l7JKcqbvZpGtg2BEqR/xKb1C913cune2RVVxhteHD/PsYY2mHEjX6y8suuHNmIfnAECl5f3PDJ81ecnZ1zdn7BV7/yeb7/z36LoWuptgXWGrabzf6KlyQpzkn1VNd3k84QEMfZVBTq9v/sgGj19GYqy5Ljo0OqspZTX6jp65J6qwiCkXyWEhJw/M47zJKEYnXNptyKY9wmqMCw3cjVsx96lDGA8KLCKGa2uMfp6yvevLnk9u6OVyevWSxnfOtb36Sq6skBPO7Jnk3TMJvNJBKgxVoh10Z5y8m1z6ONsJiqqpqc9QKGy/N8T+gchoGDgwMCpFutqUrsckm4mLHtepbLGVq1zNKY1abgct3TjoaH9w7omoEPnt0jTyzWdzy8d0g/OMpK6KXrynF2U/DOO485PpiRRkJCcEGIiRJsEhNpxTh0ZGkkZtQAnBsJFdLj17WY2NJ0LUkWTT4ptS9dbZuSNE2lCr7taKpKWNpNS9P2RElKEKh9eagfR+IsZbVaAey1Oecc2kQMgcF1/SQ1VFM92cg4KsqyoqgbblcFVd3x/jvP2DaaTa0YsTw4Tnh5U9INAadvrllkD7E2oq4rZmnEM2Ppx45qW+Oc53AxY54Ks6vrBt68uaQeQ54+fsxoYwovFVABAXVVSbykaXjy7CkHiwUm8AwjhDqgH50AGN1AVZUE6L0jPzQW5/opB9ftPyOCJRZpI88SkiQVfxvs8dKBUpPpOSL2Hj907JprhEPOPqdopuaZnVgfRTFVJS+CsixZHhwRWcvV1TWhNbJ5mYihH+i6nsjGEn+bdErBwvjJhS5SQKgNURztvwejtVTBD47Yxr+iTSoTop5Smtk8Z3SO7bal6we0NmRJSN10hKGgQ5U2vLm45vknLzg7e8Pp2QVf+OB9/uRffJ/AjVRFxehHyqLaC4VZltJ0DVp70R5Gj7UJWlmiKN2/Kb33ODcyn+Vs1iv55RgB3lfllnEYmC8PUGGITRLsLCN0PZ1X3H/8DGMN5y8/lu6/McSPniSLKcqKuqkJJlazm2DzKEM+P+Dy6o7Ts3PWqy2vTl7T9R1/+s9/KG/xXhC5QSDictf1pKkw2LVSNHUjJM3E7k2dYRjStRXz5QyjFXVZCqjhF8TJtm3pup4kjkniiHJ7R1OWE0VU0yrF0HU8vbeA8o4sjTi7WnPXeAYfEoWaL757n6M8JPCOeZpwdHTAdrPl3tGS26IhMCE/en6GzTI+9+473F1dMKqQUcdEUUo6kTe1EiyI1GR7wlBPJl6NUoJnmeUzTBQLStlovNfM8gzte5z2k8N+YOh7bBqjtSVKNcZKU898tqTvW9IkRSlNABwfH1FV1fSAhQQmZNQh41QAAVJ/JrRJyXdutzUnry9RWvH+O084u6kY3DmPDlJiC3mWUdUdP39+ygfv3CPPUx4tLQeHCT6a4/qGF+1AgGFb1CyTCGMC4jzFmRCIOfvklIPHz4hjS982hFpxe3MzBXVD2qrC5Tk6VDKY6MRPNJsvqba3WBuC14CibUvSzExu+qmM040To0lPfsGWNIuZHxwRhinOT6H6INhjjtw44pWWA0NfC4FAaeq6RFvYTgy1+XwuD/akhQYwnchEgpDGYoijGNdDHOV4O7KyW5iSAlEcT6hoCXpHE9HBDVLWEJpw2vzLfeh5HD2h+eyXuF+OgjAMJKmUHe5Igdc3t2hjSLOUqm4AoTFaG7HarHnx4iVnp294cfKa9955wg//+e/T1jVtI80aO6FcaU0amylt7anKGq0CQmOxYSJXx6mrTWuBo0XW0JZbsiimGQJJjpcFzXZDcXtLoEOsCTl68AACRdcNPHr4EK01Jx//lLqsmc3mhFOzRbFd75ExNjITH9pQ1iXKxNytSk7OLri6vOH1m0vW6y2/893f5OBgQVGUAvUK2MdfgkAsGG0rV5yy2O7F0Z1O1Ta1FDgigubO9zIMw35C0zTi9LU2ZLO+Y+xbmfJY8VVVZc2DR484ef6c1IZkWUzZDWTzGdks4MFhyiLyNKtb/AgPHxxTVDXLwwPS5YLRzrgqPEVZ8Q8//hnHBwvcMMqb18qJKFSiR4wEBCqAkQlrK+7lAL+/skNPoC1VWTECeZazXd/Q1dKfaEOz57JrbeTEqgJc21GUNcvZQpjbQ8t6LQ9UWZbTZ1AeWq80YRjRdBVqqshqm0Y0na6j7XpW6y2XV7fcv3dAnmesKsfN6pKrVcyDoyVNP7CYx0Q2pKw7FssZzw4sNsuI7z3g+voKfM+I53Zb8WA5oyq33JtnRPMlJ5cbHtx/wDChfVQA946P5CQ9ESy3qxUHyyVpOqPabAVA13XUU9Qrtolk8oaRumk4OFLM5rO9bwoCbBjRtp1k6rxnNstIkgyREuTEjZeppuBRRqHQmqkYYzrJjICf2FVpmtF3PXVVM5vPcd5LtKmpRQPy0lS8QxPXRc84QjDpgOPoGAPoXYcaA5naJQZjHP04SkP5FCzfXTOlrmtkBFT42beeX0qT2lVhd704fW9vNyglbcJFWdN2A0oZbJSwWhe8eP6SVy9OePHqlEf37/EX//Zfo5Sf0u7il0jTdH8iAMHBbFcrScmrEL0X5OT6IfVPFXmW4NuaarOibippJO46hqamWt1hdEA2y1kcH9EPI23vmR0e49zAm1efCMkxUHRd+yn8a8Kz7OBsbdvhRk0Y59g45/XFLXd3W25XG84vLvjww3f4tS9+nnranHcj+R3GNUmSySGsp5ojhY3CqQHGT00ajvksp+9a8OM+KPqLXwfTtS+yBte3dJ00FWut6AnwzjMqzeW65uhwiTIhjoCjg4yvf+U9fuPXP+TeImMxS7h3fMh8vkCZCBdYAh2zODhmQOB5y8WC86tbmlExoMmznOXBAu9F87FWRthKq+k068Q9zSgC8SiFALu3ZhRGhEbRtfX+CjxO1M84jonjGK00Td3Q95Kk7/oJ9zHxwqX3rabrB7xXaJuAMhitSfNscknnk64FI9IGc3u3YVMWvPfsIWGc4rWlDyJeXdf8w/NLXt+s+eLn3+WDd+7RN/JSPMozbL3mnVzzg298yO9+44sEBFytp1Cy0SwWUqZgw5D1Zk0UWRaLJd57lsslkZUERhRFk544oFBSVjvLCW1IXTeoQBIFYWjlwfcB3rNvEN6xmIapxHO93jDiydKEYbrm7nAsYfhpFm4cR4LRT1nHcW8a3n02JcIiDC6tNX0nmvIw9PthVxAgDvm+pawKbm9vxGg6jhLgnq6JQiMVfVUFiiiKSJJE+FNTI41cVYVrBTJI2yGKPsv65RqMjZqO0i1tuyUMQw4P77EtCiAUaLuxNE3HyatTXj4/4eUroXL+j3/x56jR0zbt/o07n83oJiFVQF+W2/UaRUCapIxeEyU5TJRK0TZCycH5kaFpsHGKSRIGL0D/eruV0GuWkh4dE6iApu14+PQd+r7mzctXBN4TBHryJwl4vmnqqXV4hOkk0/aO0XjSbMmLV6+5vL7l+u6Ok7MTksTyW7/1baqqZnSgjWYc/d68+enmayZ9oiaK5I3fNOLC75qGeZ6RZwnFdoMYOoO9hWNXWBDZiMVizmZ1Q4AEUUc/Ml8cstrWJLcFaNFw8jzlblsxEvD1jz7k/af3KLcbxpkA12yUEOc5B+mcj5+fUZY1drZgGBz3jh+QJxEojQ4/fdDiKAJC3ERg2IHrkjQhIBDgYCCO/n5wZFnMVLhNEtmJGd8Rz6RVpa7rfVh19KJlej+1w6Q5dVWIljhVtisFznuUMqLD6BA/OobeEcWWcar/zrJUcqLNwODg6uaOYXR84cP3MVGMChRF0WN0xLosYXQ8uLfg+DDDjI5gaDh+sOTurEDXa77+wSOevPuEq5uK06uSZgwI0zmDC6jKisX8kNM3V3vI3Dg9rPPFgjROuLm5gQAODg5hDCZ6xOQ/q7ekWcY4lGgTSR0UMiVtu44szSeAHYRRhOuHfZtRGlu6tttPAEc/TvRSQdZopan7RjA/fhQ2uTEkaYLrR+azGUor2qbj4OCQMAy5ub2jG0eiJJ5KLiLKWszIajJBp/OZVKubEDVRGsLJViPPjkO+y6nBWAljrOu6qdpLSJ59I+UZv5JNKkmiKerSEIbhlDHrmM2WtJ1UWVd1zYuXL/jkk+e8fCV9df/DX/w5NgxYb1aE8URY7DrKqsR1LUYpjFZsNxvxAB0JdjWNxdQXTR/0ru+YZSnetaxubkjynMDGLBYH1MWWsZNTi04S4oND4iyhqWpmywOMhquTM4amxk0nOOcGrDXUtYSfd5vKbjoUaIuNM65vV7x+c856tebk7IyiqPk3//pfIKenCIcT3Ij+lOvc9z0gZMptuSGO7Z6r5MeRrm0xOsBOpMRo+mV2bT0RHvz+LTSfzym2a9zQy5vRew4PFoTGstpsWJdvGIaIxw8O6ceAT843FIPiWZ4SKkUSJ5RphPMjZT1Sjh2tHzm/3bDeVrz4u5+yXq85TDTZ5z7HYnGIDwKOjw8lP+bkwxdGEsy21lKWgrp1g0MrCTxXVUsYJRgb0vWDOJa1Eof99LPZfaCtlZDyer2mKmuCQNPWtSB4jFA+m2Y3RPDEaS4EVQ9lWWGjWEyO2qDt7hQspErKgaJqub67YzlPefzoITZKaJoKUBhrcYx0VcXJ2Q3BOPLkOGOWpjx4+pTQD2Sp5SCzPHrwhD/+g6/zP/3P/wdV18tmF4YEQUdVVrz3/ru4MMUgPXjOe5IkwYSG0MrJsWsqjNITdROpkapCjA5pu10N+rA3o9owxrmROJIJtzaasXcMoyNKc5Z5KhyucaTcyhVShYbRBxNSm+m6NuL9IMA8GxL6gFCJgdQNA+NkczHGYLRiDEOSJKKva8rtHVXTYaOYdhgEGWwFu23jFM9ECMHRNdNEbxzxKqBtOqmXS1N0aGnrmtAoglCmmIMbGX9VqBY3eBwiiFkrzJ9AWcZAGoCbtuXF81d88vELPnl5SmgMf/Hv/gxrAm6ur3CjY3FwiB8d29VKanuMRmnF0DdUVUk+m9M7mKU5eqrY7vuezXbLweEBo3PcXV5xeHTE4Dz5YsHQdzTrDXc3V7jeEWYZWaCoiwodJeSLnLOXH9PXpYDoPdRNhdaKpq1FxJ18Izv8yBiE2GRGXQ+8eHHCelNw9uaC8zcXfONrX+Hx40fycCHHZxHCR9pOsnRVVQnpoNwQWYs2ijiO2G63zFLRT7LlfCJy6unqNOzH7LvcYpqmE/K1IfAe77yEeaca+rYbKcqC5ydvWKYxf/vjK+YHxxDNKMoGf7jgZrXlZlMToDlfbdChp247lArBxFzebnB1ySzLyGcLETanctNdc84OWrcjLtpJEO3ppOXWjYQ2ZD6fY6MEE8rbWMB1HUYxlV4Ee3/OaiVT1DRNp+5Bz9XVFUkcShWTllOb1uKa7nvx5vSD+KnSNKdt232jThRFDF4xornblNxuNnzhvYfMF0vCKKFte0IbT2ZEsZM0nednL25Yb1s+//5DHs2PmT90GEa0Tchjy/e+/UVeX1d8cnJJ20PbSQPP+c0tn/vSR3g7x5hAEg9euFW3tzdYrbh375g4VLgJydMPPWW55eDwkCxNWI0dvRtZr9bkmSCI9GSC3W63jONusjfQdB3RIpM6KiUn975r8QEMo6OfSi+GwU0DBo1RCVGa0ruBgAA/bQ6B6C17i8HoHDY0hFqj4kiuet0gvYsTgLHrBuI4IY4zMdb2HV4p4jhhU2xE9xo8/UT47DvxiNV1KW3J09R71yT0K9mkdhVMs1k+IR0coQ4IrTQRf/zxz3n18oTT0wuM0fz5v/1TlvOM2+tLFHIkHYeepi6wGqIwFH3KBdRNTZalBIEmSiVTNvSOYegptlsOj4/IspzN+laKEUxImqWCJi1LtuuVaDk2ZHl4IMZDG3F4dMj5q+f0bY2xEuJtmmba+UUc3G00WmuUsXQuwERz2h5evHzJ7d2a65s7Tl+/5v6DI373d79NU3eMo2B3/eT0reuaNEuoqmofEfLjSBjZSSwfyLOMuixgdFOTigfMNMHr9lrULr91sFyyLTYYbQQd2znSPGfA07qBEUXvAvIkoet7vLYoo1HIae2//uQTiqrBjQ5lNEGYgLZ0Q0OSzTm7OmHse772lS/y+OkTbCzlE1mW7q+b6YTlUEo0vCAIyLJMcMnGEEcyChcKpAilKpDoiVzZFEYhNfStBGGzLKMoxcoimGDH/fsPOHt9RhpbmJzTfhx5cP8+t7d3UjceGPJZQlO3U6jW45wW13UQMHpF1znOz6+o6povfP594jSRaAcBUZzinDQCq1AhEV3Fuhr5rz97w/VBysNFQmoDWmUoqpo4XfCtX/+A1bbnzU2D1xWroiGwCT6IWB7cp6prrDGYqQj3/PQVB7MZdiqJCMSMxND3dE1NuJSuycgmKOdkKowmisxe45GiBUUcJZShFeqokgOBnRhd3u0GFuIbA7fXe3Z/Z9sN+3oy70bZrJDcnes66kFYUcpIltCkGfniiKHvKapK/HjTC7woSsJIIi7eTS/36cU+OIeNIoZNMf39UlJabDc4MyUslJo8gL8inpTWmsPDA9brDXXTkGYzbGhpuo6XL15y+uo1JyeXdP3Av/t3/4rjwwO22xWBH9BKYyNLWxb0XS3UyX5gcBI/ieIIAo2NM6Iox8PeK5JmGYvFnHF0xFFMMp9DICUIXV2yvbnFDz3j0GGSXPjdbuTBo/vcXV+Bk+CpQOsH1ESSXK/X8sNUQjHUSqPDjM5pTDzn9PUnXF5dU9YNL09P6Yaef/nD79M1PW3bY0w4NQ73e1bW7m0hvpSBJI4F4GYtxbZBKwG2JYlsZrPZjKF3EzBfnPZZllHVNfPFAjc6GIepMEBYWGY6OdRNi/eaumpZLpdUZUFkF6RJjPdSs9V2gi4xUULT9KRZTlkLQ6qsO66vbomt4Te/9TXy5aGk9BlJEvleJLwa7CeSIJuW1prtdkuSJtiJG9W0HUfH94mShK7tmM0WlNs7Um+o64LQmilXFhNGCTaW9tu2bbFAkmUcHh7RVgWRjfHTGLuqqkl4t3vGvIjGA0qpvb8nTjPu7krOTk+5PD8nNQHvPnksCBwVSHvNOGLDSICJCDYmDMT/VdYdF0CgQqzy+FBTOEfYlGR5ypc++oC/+dEJ69oxP3yECiPCJCcwhihK6LsWZT1VNXK3XvHFX/uILIknU2ZAnER0bYEKPM51NLWjapo9hkUbyTCObtw70sU4PXB5fUfT9SzThFArqZVXYnsJwxA/MnmZ/H7Mv8v87RqMu35EJoJitvQTa75th33Q2Q0ScjdTC9Lx8QNury/omgoCqXx3XvKlXTcQBCNtW6O12DSO42zKCw6MfUfXQ7EtiMIFxsqUL5hiVb+STSpJE7Hwtx3Lg2OiOGa7LXj56hUnp2e8PHlNUdb82Z/9EY8fHtM2JWPfIn1yeqIMBiRRxHaz2pdgWiuCu7EJUZzRtT1xGrGdSjsfPLiPa8Xwt1jOIVCyyVxd0BRbqXJGkS2PSRczxkBxeHTAenXL0DXs+tCGQVqAkyTh9vZ2bwZ1Q48OLZiEqvWkiwXXV7ecnJyxLStenZ5xt1rxB7/32yxmGcWmpmka7t+fS8vIpCFZa7m7u9tfhXe5vd0UMTSGotgSx/E04ZCMog3DPRZYJl/1FAAdaScSgp+KB4RF5agqub6VVSNvpUCxODjEaE1sQ7q+R1lL5EZ652janmyW0jYdTdOhbczt6wtubu/4xle+wOMnT8Vz07f72vodzng3ZdzpF7vr1c7rNXpP19QoLW/HvpOq8cEPjN5JL6INBTbooW12k6lxutKMsjFXFfksp60rBucJbYwNNc4PmCgiDCMGJxqZ4F4iqp2jG3F4V1XN3d2K9d2azz1+yNFcyK9KyclCTU02AYGYj8OQUBmaccCEKWMwsq4aQqO5eXHOMA48fPQAj6LuetIs4/6jpyTpnNnBkqrtGLqGOEqkhFYFxGlCns/3p9G9zulGAkbCUNG1Fc0gk7EgkBH+bCbs8QFHV1ZTKN3gR8/Z2RuBPhqNCRCUTt/R9x06BBOaaeKr9zxxGKW1eHL3B4GGKSa181QFE/9LKeFs9V1DVYIdHV3bkqV+8lGxv/JttxtgRlVVLOY5QRShlGFTNGL+1AYbhgQa9Cjm1iaJSNTOwOn3xtzPsn4pC0JTNxRFwWJ5KF/UpuTs7Jw3Z5ecvjpnsyn4kz/5Pu8+fUBdbHFdixs61PQQg8eGIWWxRQfSk+bcSKAtWb4kTRfizDa79LplsViIKLvZEkeWYYQoTri9PKfdbqjWa+IsJT08JD04IJ3NODw6ZhgcfdvQ93KN6rqBtmmmDepm8i7pKSPn0SYGnZHNj1ndrXnx/GPKsuDNxSXnZ6/50gef42tf/RJd4yjKYl/J3nUdbdsym82k0mrqcdtllnaGTTc4+kn32uUTd9qMcHqYkMKG0Frm8zl1UU7tJ9A2LWkqo922beWDZgxt25Hn+VR4EAoRMklJ8plMjEyINiE2ikmyXGwiWky3L0/OSI3nu7/5TcIkl80I0Ea+DjdNzWaz2Z7ntavaknbbcO9eljiTbLbb9ZpidcPm6jVNVVCWJVVVAaKBCOy/3ts/qqraT6qqupYrwzDS944kjYXimmZoExKnGVGSoozBeXFZqyn133YDZVFxe7vi7u6WD997gtaB+HVgop5q8bNpRZZlhGYqF9UhPtDYJKUdPY0LuNm2VJ3izWXBpgLClKfvvss777/P4fE97j96DIGmKrbEUYQKDPl8SaAMs9mceGohttbKMKFrhVgQaJQS8OHuRbn7HoJfYEwBk0ShuX/vkICRZZaSRBHahNNETZ4huUb7vSdqxyLbvZwlmycU077v5USjFEVZim1jsip0XYsxAaPr9/QKP45EUbyHFoLQWYMATBju+VVaG6pKyjCiOJahxnTd1UYRTfRO790vUcPwS56kyqLk+PAQrSRweXp6xtX1NWdvLri+XvGHP/h9PnjvGcV2DYNgIwI/gdJGTxRZimIt/p6uk6O/iaWG2ki0xU6ThzRNcYEiTRPWt7fSTxYo5rOc2/PXbC4uwA2EWuE8mFgcznGcUdcNdbXBu34al4ttf6cTNU1LZGP6rscBNp0xqowoWdIOAzeXV1xf33KzKTg7eU2eJfzgD36PfpApjNHidWqaRvJYsZ28PbJ25RLWGOI4mq5+PU1dTbAvv/eKBAhcXxLiMsqO0wTvOhQydm+bFtc7olmImyZ+oCjLltlcONQmjNGh1F0Ng6cfBsJIrmxt0zGfL6kqSQcEynB2dsLN7RXf+eqXePjOM5pBsMmJjYhjK9PaCXa2wx27QX7eRVGJxwbNcnGAGx0HhwfSCh14lJJxelNtUEYTWoH8OedoGzlZtHfXKGUYUXuCxjAMEmbV0twTReEeA71YLGi7HhsnREomhtp7AhVMbSryO7i9vuPmZoUfHR9+7ikqjBk8BFN5hojwIjYro3Gdl0JO79ABZHlOWRTCU0pysbjYEBdEHN97RBinHB/dY1vWaB3y4N59Vqs74dHHMVGSUjcty8MjwjBmtONU3KlpWhmSjMaQptlkiSjoeqHDDhPP3Npov4m0Xc3Qg/eObVny9CDFJik6jCdD7YjvBZYXGstslu9PStZKKHwYHErLVWv0I/3Yo5zCq4Ag1KjJK5VEwntvaoFOEmi8GyQE7qXdWJuAJLYksaWNI7SSqEsQSCW80nriegmPKvA1UWRJs4QwNIReU9YNxn72Sqtf6iQVJxlhktH1PaenZ1xcXvLy5RmfvDrjd37nN/jqlz+k2KylrdXvrPqys0ex5H7kf3sGF2CijGx+SBhGFNvtPwrUhlOCvqlrqXFOhBq4Xd1w8eoFfbHFtT2B1vRuEI+WNgz9QLFd4ceBsiz2Y3w1TUOc82TpHNA4r1BhSpgcMOoEYyNuLi85PT1lvS158/qCrm344b/45yJANgObTcHh4ZEA7NKYIJBG3p1zXgBffi9ehqGhbWuGoSeK7IRWZi+MixESdkWh1kqMpW0axin/VdUVy4OF4JO9IkCh1RS7yaR4NUlTsiSRaVoA3eAIlMGEMWmaE8Up220pJ8q24+r6ktRqvvVbv0FgMzzIJNFabBT/I2NrtUv0DwPeu6lbjX24u+87mQhOWtzODOjcwDj0FJs1Rklj9C44LbRSebjkxdHsr5Y7sT7LUoZ+wPsA5wQhTBBgpso0T0BT9+gwJc2PaFsoyo43b655cHzIoyeySalA0hHy+wgnpK+8OK21hCaUkX+SQKCJ41RKBlCESUqczYnSnDSfk2a5yA1RhHN+7/fSxmDjGGOMCM2jZBmj6cq/I47u4i7OObq+IwwtznnSdOcf+xQjvIsAee9oamkbitKEMBL7we6ztpMK+mGQk493Qi21EXm+wE45Ow97nXH376ZJuid3eCVDMKUUbdtSbla01Za22mICT9+2CJ7RY3Y0DCVG0V3xK7DPBI5TqHrXybfLEPrx09bp/9c3qTCK6QbHy1cvODk74/Tsgldn53z3O9/gu7/9TYZBYOuxjSCYihuDgDiWDjTnhn1vWJSkRMkMpcVzs4Nw7VAmbbsrXVBoGxNnGaFWbG5v6epGeDVpjDeaNMsATRJnlNWGwHuqoiYIQgIVorRFqZDb2xVt0+F9QJxkJPkSmxzgsKT5nNXtHa8+ecndesvFxSXXl+d8+9tf59mzJ7SttN0cHCzluBpAWRbkeUozPdBRFE9o1Gy61iW0bbNv+kimwkfvR7pOAtSjG+XUFYoIr5X4xboJI9s0UhC503DcOJLEKdui4Pj4WK6VxqACKdcMAsXgpLXDjVDVDYvlIaMPKKsGrS2Xl5fc3lzztS//Gk8fP8aNItibqaBis9nsH5JdH15d19hod6xXEzwt4O7uDkCwOoFUnoVGapYIhIfddx2RDffEAzUVNURRtC+c/UXqQxiGsjlXLR415Rcb/OgJw+jTYLmNmc0OcE5RNiN1PbLeVFzfXPPB+4+I8gWBidAB+83PSbaDLMuJongqyNCoQIyHWoek2QxjI+J8ThxnZPmCNJ+TZDlhJJPC3XUrnH5vo3MUmw1NWdFU9dTuHEqdGkybodm/uHd0Aj2Vye6KK3blr0mS7KF9XddS1TV+hNAa0sWcNM+n4tRwfxAITYjRZtocxLm+2Uj5qw2jfSZvt5mYDvx8AAAH4klEQVT40e+va84LFSPJ5BDStR1N2zJMDUBGSxHD0LcMkyPemClP2A90vbQoOzeijcZN7cUBu+agT8tL+65nHD2fdf1Sm9Q4jrw5f8PV1R1nry85OXvNN772Zf7wB99jcANt08obw0mgsZ2udMYodOBRAXR9T5wmGBsThgluEvniWBLwgg7WzGZznBtJkhRjQtI05fXZqZRz5jO80pg4xaY5YRwzm89Zb+7o25a6bUXnmh/QjwFRmtH2A/0gzOi2b9kUKwYCsClxktO1LR9/8jNuig3XqzXnFxc8e/KA3/nt77BaVdR1N8U4pCxgcELSdF1LVUg91831tRgbA4htiMLD6GnKhtjGezbUDo/s3UA6tXE0TYv34jjv2h4C9oLwzr2+KUrRYpzDaIU1mqGT6InWhm4Y6J2HQFy/wyDT0xHFxeU1zkPvPSdnr7HG8Fvf+gZpfjgFdKd/PBTb7S+8/Qbm8zlJkuxBZXkup8Hrm1vKqkIZTe96ur6bSKmKIPDYOEKHdipv7QmtJY4tbnSMXuSD+Ww2/ff8fkqqprdsXdcwIU3cIBPaNE0ZpvrxwQ1keU6SZZRVzWq94ur6Gj9UfPVLnyNK5CQ2eo+NYmwcT1ceTxhFGGsxiUVb8SWlUQpeM6IYURibYGyGjeeEcS7oGjzDOKIm/lcURRLEDTSPHj8mn82wUTQ9MTJhq+saozVJZPHOycnWJiRxti/kMCaUSJmN0DrE2njvv+v7nptNQTsMxGGIDi1Jmk+ncNE1VaAnT5XYAbSWk1OgFYGWoiwdhlhjUYFc/VSgsWFCki+YLw4x2jIMoLUlyUTb7IYBHYYM3jHB2eXFM7RTWkDsC/LsykmunbS2wAdkaY7ecd4B9uyrX5Fwvt6sODs75/nLN7x+fcGXv/RF/viP/pC+71jfrWiaCu8d4yTmRRNHqO86+r6lqkr5/8KYJM7EduDFgbszjOV5znK53OfX3OjI8oyriwu5NqYps6MjfBSBCUmyGffuPZBWYy+jVTnm5vS9jMw3m4LeDWgTTleWEW1jlE3QNsKNjpfPn3N1dctqXfD69A2Kke9//3uUVTVNIkaWywVd1wi83nuiqQSxbUr6tkYFEFpNoDxJGu1FbhUEoh1pNdUPqUmMjCCQ2I7SBhtFVFU1XVHl65zNcqwN2RYlQaDpOkfZtCyXh3RdT2hCgkATBFrak7sOTyBv+tGzWB6w3W4pioIgUFxdXnF9u+I7X/8qz959D4cimIodJf7QsVgsiON4z+jaTS7HcaRpe+IkE8FaQT5Lp+u9n/Ayov8F0/RyN50aBnHO7wKrO5KFpOfF3pIkyWRN6eXDqT49dYRhSJwkcmVSCmND6qbm+uaarh+omoayqjh9fcYsNTx6/HjSRqQ269M6Lbd/cYpGHdC7kThNcePIGHhQCj2xquRlKkRJPIxOqB1NLbYCYYZNjTYo+qZle7cS7hpCFjBKIl9921GV5d6sCwG74ord6WYYBrbbQjSmMCKb8L2bqkRNhuCu62g7Yffv+hl3J7O2bfGjn7SonnHsGF0v/jbYUz93ZmHvJSi+s5UMg9SBBRNs7/7DhyR5NkV+pKB1Nssn+KGeZJkYvHyuYZqiBmp/pfz02irDMz1dAT/r+kzC+U7R/9nPnnNyesHJ2QWf//B9vv8Hv8/qbs1mtWZ9d8l8kU4ZrIKhH1jMU1Z3d4ShlaPj4DChBqNhgKavGPaTrYj1ZsP9e/fZbLbTaHskDC2vXp2wuhaujVJC6oxnc0al0WHMxeWtRE+ikE1RSFrbK6IooR3k7eyGgdXt7aRdCVmhLByZdlxdvubHP/0x5bbm7OSMm5tLvv/Pfg81icSb9ZYHD+6x2awxoaaqCmJruL66FLSKDmiajvnigLs7oZWuV1v86Nis1xwslgzDiHN+OjHtGNwBbT+i0MSxpSxrAeJ58XyNgwRqR9+x2pTM5oa2qVhvt7hczJpxkgm1suno+55mGDBG0btewqrDyMXFlfy3q5ZXp2dkoeKrv/YFNu1AV60wRvja49CzXW/IsmTS2ITAKdgRobF2w8DtaiWNylEGXlE3PaETm0TgA/pemqptFNK2HWVZkWVy+uq6gW5wjIMEhuNYUdWywWhtJo/QZk9JiKKAqu6woQwQNtsKbeSkWNctRb1B24p12XFzfc35+TkfPr6HMSFFKXx7pc1EzhBXu3MeTy2xETxt05AnKf0AreugH3GDp24D0tEwjgptQ+JOLCz94CSqkyRstwVt0wGKzXrN3fUd5XrDfJazXa/p2lZOsH3PZrOhXG+xoSVOYqq6om072rZhV/nVNJsp6ylTMoDNakO13hKMHm00m21BeHfHenVLuS0Y/TgF2LWA5vpeugnHEa2C6esVm4IbnOCRypJm2+BGYNJGu4nCMQwtd1fXEtzOZ9xeXYu5NImm3G4vMaZGhhtd1zO4jqqqYTKElmU1QQjFUlPXNYEXwkfTNPii/Ed7y39rBf4z/KnT01OePXv2Wfazt+vtervers+8Tk5OePr06X/zz3ymTWocR16/fr0XR9+ut+vterv+nywpDd7y+PHjvdv9/259pk3q7Xq73q636/+v9UsJ52/X2/V2vV3/X6+3m9Tb9Xa9Xf+k19tN6u16u96uf9Lr7Sb1dr1db9c/6fV2k3q73q6365/0ertJvV1v19v1T3q93aTerrfr7fonvf4v6b3NtTH/ZQgAAAAASUVORK5CYII=",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import json\n",
"from PIL import Image\n",
"\n",
"# Choose an image to pass through the model\n",
"test_image = \"dog_but_cooler.png\"\n",
"\n",
"# Configure matplotlib for pretty inline plots\n",
"#%matplotlib inline\n",
"#%config InlineBackend.figure_format = 'retina'\n",
"\n",
"# Prepare the labels\n",
"with open(\"imagenet-simple-labels.json\") as f:\n",
" labels = json.load(f)\n",
"\n",
"# First prepare the transformations: resize the image to what the model was trained on and convert it to a tensor\n",
"data_transform = transforms.Compose(\n",
" [\n",
" transforms.Resize((224, 224)),\n",
" transforms.ToTensor(),\n",
" transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]),\n",
" ]\n",
")\n",
"# Load the image\n",
"\n",
"image = Image.open(test_image)\n",
"plt.imshow(image), plt.xticks([]), plt.yticks([])\n",
"\n",
"# Now apply the transformation, expand the batch dimension, and send the image to the GPU\n",
"# image = data_transform(image).unsqueeze(0).cuda()\n",
"image = data_transform(image).unsqueeze(0)\n",
"\n",
"# Download the model if it's not there already. It will take a bit on the first run, after that it's fast\n",
"model = models.squeezenet1_0(pretrained=True)\n",
"# Send the model to the GPU\n",
"# model.cuda()\n",
"# Set layers such as dropout and batchnorm in evaluation mode\n",
"model.eval()\n",
"\n",
"# Get the 1000-dimensional model output\n",
"out = model(image)\n",
"# Find the predicted class\n",
"print(\"Predicted class is: {}\".format(labels[out.argmax()]))"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"model: SqueezeNet \t Size (KB): 5009.234\n"
]
},
{
"data": {
"text/plain": [
"5009234"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"print_size_of_model(model, \"SqueezeNet\")"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"model: smoll_squeezenet \t Size (KB): 5009.234\n"
]
},
{
"data": {
"text/plain": [
"5009234"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"quantized_model = torch.quantization.quantize_dynamic(model, dtype=torch.qint8)\n",
"print_size_of_model(quantized_model, \"smoll_squeezenet\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Essayer de réduire la taille du modèle squeeze ne conduit à aucun changement, car celui-ci est déjà réduit"
]
},
{
"cell_type": "markdown",
"id": "5d57da4b",
"metadata": {},
"source": [
"## Exercise 4: Transfer Learning\n",
" \n",
" \n",
"For this work, we will use a pre-trained model (ResNet18) as a descriptor extractor and will refine the classification by training only the last fully connected layer of the network. Thus, the output layer of the pre-trained network will be replaced by a layer adapted to the new classes to be recognized which will be in our case ants and bees.\n",
"Download and unzip in your working directory the dataset available at the address :\n",
" \n",
"https://download.pytorch.org/tutorial/hymenoptera_data.zip\n",
" \n",
"Execute the following code in order to display some images of the dataset."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "be2d31f5",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import os\n",
"\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import torch\n",
"import torchvision\n",
"from torchvision import datasets, transforms\n",
"\n",
"# Data augmentation and normalization for training\n",
"# Just normalization for validation\n",
"data_transforms = {\n",
" \"train\": transforms.Compose(\n",
" [\n",
" transforms.RandomResizedCrop(\n",
" 224\n",
" ), # ImageNet models were trained on 224x224 images\n",
" transforms.RandomHorizontalFlip(), # flip horizontally 50% of the time - increases train set variability\n",
" transforms.ToTensor(), # convert it to a PyTorch tensor\n",
" transforms.Normalize(\n",
" [0.485, 0.456, 0.406], [0.229, 0.224, 0.225]\n",
" ), # ImageNet models expect this norm\n",
" ]\n",
" ),\n",
" \"val\": transforms.Compose(\n",
" [\n",
" transforms.Resize(256),\n",
" transforms.CenterCrop(224),\n",
" transforms.ToTensor(),\n",
" transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]),\n",
" ]\n",
" ),\n",
"}\n",
"\n",
"data_dir = \"hymenoptera_data\"\n",
"# Create train and validation datasets and loaders\n",
"image_datasets = {\n",
" x: datasets.ImageFolder(os.path.join(data_dir, x), data_transforms[x])\n",
" for x in [\"train\", \"val\"]\n",
"}\n",
"dataloaders = {\n",
" x: torch.utils.data.DataLoader(\n",
" image_datasets[x], batch_size=4, shuffle=True, num_workers=0\n",
" )\n",
" for x in [\"train\", \"val\"]\n",
"}\n",
"dataset_sizes = {x: len(image_datasets[x]) for x in [\"train\", \"val\"]}\n",
"class_names = image_datasets[\"train\"].classes\n",
"device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
"\n",
"# Helper function for displaying images\n",
"def imshow(inp, title=None):\n",
" \"\"\"Imshow for Tensor.\"\"\"\n",
" inp = inp.numpy().transpose((1, 2, 0))\n",
" mean = np.array([0.485, 0.456, 0.406])\n",
" std = np.array([0.229, 0.224, 0.225])\n",
"\n",
" # Un-normalize the images\n",
" inp = std * inp + mean\n",
" # Clip just in case\n",
" inp = np.clip(inp, 0, 1)\n",
" plt.imshow(inp)\n",
" if title is not None:\n",
" plt.title(title)\n",
" plt.pause(0.001) # pause a bit so that plots are updated\n",
" plt.show()\n",
"\n",
"\n",
"# Get a batch of training data\n",
"inputs, classes = next(iter(dataloaders[\"train\"]))\n",
"\n",
"# Make a grid from batch\n",
"out = torchvision.utils.make_grid(inputs)\n",
"\n",
"imshow(out, title=[class_names[x] for x in classes])\n",
"\n"
]
},
{
"cell_type": "markdown",
"id": "bbd48800",
"metadata": {},
"source": [
"Now, execute the following code which uses a pre-trained model ResNet18 having replaced the output layer for the ants/bees classification and performs the model training by only changing the weights of this output layer."
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "572d824c",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\arman\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\torchvision\\models\\_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.\n",
" warnings.warn(\n",
"C:\\Users\\arman\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\torchvision\\models\\_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=ResNet18_Weights.IMAGENET1K_V1`. You can also use `weights=ResNet18_Weights.DEFAULT` to get the most up-to-date weights.\n",
" warnings.warn(msg)\n",
"Downloading: \"https://download.pytorch.org/models/resnet18-f37072fd.pth\" to C:\\Users\\arman/.cache\\torch\\hub\\checkpoints\\resnet18-f37072fd.pth\n",
"100.0%\n",
"C:\\Users\\arman\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python311\\site-packages\\torch\\optim\\lr_scheduler.py:136: UserWarning: Detected call of `lr_scheduler.step()` before `optimizer.step()`. In PyTorch 1.1.0 and later, you should call them in the opposite order: `optimizer.step()` before `lr_scheduler.step()`. Failure to do this will result in PyTorch skipping the first value of the learning rate schedule. See more details at https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate\n",
" warnings.warn(\"Detected call of `lr_scheduler.step()` before `optimizer.step()`. \"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 1/10\n",
"----------\n",
"train Loss: 0.5355 Acc: 0.6844\n",
"val Loss: 0.1978 Acc: 0.9477\n",
"\n",
"Epoch 2/10\n",
"----------\n",
"train Loss: 0.4346 Acc: 0.7828\n",
"val Loss: 0.1863 Acc: 0.9412\n",
"\n",
"Epoch 3/10\n",
"----------\n",
"train Loss: 0.4293 Acc: 0.8156\n",
"val Loss: 0.2005 Acc: 0.9346\n",
"\n",
"Epoch 4/10\n",
"----------\n",
"train Loss: 0.6259 Acc: 0.7582\n",
"val Loss: 0.1737 Acc: 0.9542\n",
"\n",
"Epoch 5/10\n",
"----------\n",
"train Loss: 0.4020 Acc: 0.8484\n",
"val Loss: 0.1675 Acc: 0.9608\n",
"\n",
"Epoch 6/10\n",
"----------\n",
"train Loss: 0.4039 Acc: 0.7992\n",
"val Loss: 0.2221 Acc: 0.9281\n",
"\n",
"Epoch 7/10\n",
"----------\n",
"train Loss: 0.3572 Acc: 0.8402\n",
"val Loss: 0.1849 Acc: 0.9412\n",
"\n",
"Epoch 8/10\n",
"----------\n",
"train Loss: 0.3337 Acc: 0.8566\n",
"val Loss: 0.1993 Acc: 0.9281\n",
"\n",
"Epoch 9/10\n",
"----------\n",
"train Loss: 0.4132 Acc: 0.7951\n",
"val Loss: 0.1854 Acc: 0.9346\n",
"\n",
"Epoch 10/10\n",
"----------\n",
"train Loss: 0.3774 Acc: 0.8115\n",
"val Loss: 0.2011 Acc: 0.9281\n",
"\n",
"Training complete in 2m 19s\n",
"Best val Acc: 0.960784\n"
]
}
],
"source": [
"import copy\n",
"import os\n",
"import time\n",
"\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import torch\n",
"import torch.nn as nn\n",
"import torch.optim as optim\n",
"import torchvision\n",
"from torch.optim import lr_scheduler\n",
"from torchvision import datasets, transforms\n",
"\n",
"# Data augmentation and normalization for training\n",
"# Just normalization for validation\n",
"data_transforms = {\n",
" \"train\": transforms.Compose(\n",
" [\n",
" transforms.RandomResizedCrop(\n",
" 224\n",
" ), # ImageNet models were trained on 224x224 images\n",
" transforms.RandomHorizontalFlip(), # flip horizontally 50% of the time - increases train set variability\n",
" transforms.ToTensor(), # convert it to a PyTorch tensor\n",
" transforms.Normalize(\n",
" [0.485, 0.456, 0.406], [0.229, 0.224, 0.225]\n",
" ), # ImageNet models expect this norm\n",
" ]\n",
" ),\n",
" \"val\": transforms.Compose(\n",
" [\n",
" transforms.Resize(256),\n",
" transforms.CenterCrop(224),\n",
" transforms.ToTensor(),\n",
" transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]),\n",
" ]\n",
" ),\n",
"}\n",
"\n",
"data_dir = \"hymenoptera_data\"\n",
"# Create train and validation datasets and loaders\n",
"image_datasets = {\n",
" x: datasets.ImageFolder(os.path.join(data_dir, x), data_transforms[x])\n",
" for x in [\"train\", \"val\"]\n",
"}\n",
"dataloaders = {\n",
" x: torch.utils.data.DataLoader(\n",
" image_datasets[x], batch_size=4, shuffle=True, num_workers=4\n",
" )\n",
" for x in [\"train\", \"val\"]\n",
"}\n",
"dataset_sizes = {x: len(image_datasets[x]) for x in [\"train\", \"val\"]}\n",
"class_names = image_datasets[\"train\"].classes\n",
"device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
"\n",
"# Helper function for displaying images\n",
"def imshow(inp, title=None):\n",
" \"\"\"Imshow for Tensor.\"\"\"\n",
" inp = inp.numpy().transpose((1, 2, 0))\n",
" mean = np.array([0.485, 0.456, 0.406])\n",
" std = np.array([0.229, 0.224, 0.225])\n",
"\n",
" # Un-normalize the images\n",
" inp = std * inp + mean\n",
" # Clip just in case\n",
" inp = np.clip(inp, 0, 1)\n",
" plt.imshow(inp)\n",
" if title is not None:\n",
" plt.title(title)\n",
" plt.pause(0.001) # pause a bit so that plots are updated\n",
" plt.show()\n",
"\n",
"\n",
"# Get a batch of training data\n",
"# inputs, classes = next(iter(dataloaders['train']))\n",
"\n",
"# Make a grid from batch\n",
"# out = torchvision.utils.make_grid(inputs)\n",
"\n",
"# imshow(out, title=[class_names[x] for x in classes])\n",
"# training\n",
"\n",
"\n",
"def train_model(model, criterion, optimizer, scheduler, num_epochs=25):\n",
" since = time.time()\n",
"\n",
" best_model_wts = copy.deepcopy(model.state_dict())\n",
" best_acc = 0.0\n",
"\n",
" epoch_time = [] # we'll keep track of the time needed for each epoch\n",
"\n",
" for epoch in range(num_epochs):\n",
" epoch_start = time.time()\n",
" print(\"Epoch {}/{}\".format(epoch + 1, num_epochs))\n",
" print(\"-\" * 10)\n",
"\n",
" # Each epoch has a training and validation phase\n",
" for phase in [\"train\", \"val\"]:\n",
" if phase == \"train\":\n",
" scheduler.step()\n",
" model.train() # Set model to training mode\n",
" else:\n",
" model.eval() # Set model to evaluate mode\n",
"\n",
" running_loss = 0.0\n",
" running_corrects = 0\n",
"\n",
" # Iterate over data.\n",
" for inputs, labels in dataloaders[phase]:\n",
" inputs = inputs.to(device)\n",
" labels = labels.to(device)\n",
"\n",
" # zero the parameter gradients\n",
" optimizer.zero_grad()\n",
"\n",
" # Forward\n",
" # Track history if only in training phase\n",
" with torch.set_grad_enabled(phase == \"train\"):\n",
" outputs = model(inputs)\n",
" _, preds = torch.max(outputs, 1)\n",
" loss = criterion(outputs, labels)\n",
"\n",
" # backward + optimize only if in training phase\n",
" if phase == \"train\":\n",
" loss.backward()\n",
" optimizer.step()\n",
"\n",
" # Statistics\n",
" running_loss += loss.item() * inputs.size(0)\n",
" running_corrects += torch.sum(preds == labels.data)\n",
"\n",
" epoch_loss = running_loss / dataset_sizes[phase]\n",
" epoch_acc = running_corrects.double() / dataset_sizes[phase]\n",
"\n",
" print(\"{} Loss: {:.4f} Acc: {:.4f}\".format(phase, epoch_loss, epoch_acc))\n",
"\n",
" # Deep copy the model\n",
" if phase == \"val\" and epoch_acc > best_acc:\n",
" best_acc = epoch_acc\n",
" best_model_wts = copy.deepcopy(model.state_dict())\n",
"\n",
" # Add the epoch time\n",
" t_epoch = time.time() - epoch_start\n",
" epoch_time.append(t_epoch)\n",
" print()\n",
"\n",
" time_elapsed = time.time() - since\n",
" print(\n",
" \"Training complete in {:.0f}m {:.0f}s\".format(\n",
" time_elapsed // 60, time_elapsed % 60\n",
" )\n",
" )\n",
" print(\"Best val Acc: {:4f}\".format(best_acc))\n",
"\n",
" # Load best model weights\n",
" model.load_state_dict(best_model_wts)\n",
" return model, epoch_time\n",
"\n",
"\n",
"# Download a pre-trained ResNet18 model and freeze its weights\n",
"model = torchvision.models.resnet18(pretrained=True)\n",
"for param in model.parameters():\n",
" param.requires_grad = False\n",
"\n",
"# Replace the final fully connected layer\n",
"# Parameters of newly constructed modules have requires_grad=True by default\n",
"num_ftrs = model.fc.in_features\n",
"model.fc = nn.Linear(num_ftrs, 2)\n",
"# Send the model to the GPU\n",
"model = model.to(device)\n",
"# Set the loss function\n",
"criterion = nn.CrossEntropyLoss()\n",
"\n",
"# Observe that only the parameters of the final layer are being optimized\n",
"optimizer_conv = optim.SGD(model.fc.parameters(), lr=0.001, momentum=0.9)\n",
"exp_lr_scheduler = lr_scheduler.StepLR(optimizer_conv, step_size=7, gamma=0.1)\n",
"model, epoch_time = train_model(\n",
" model, criterion, optimizer_conv, exp_lr_scheduler, num_epochs=10\n",
")\n"
]
},
{
"cell_type": "markdown",
"id": "bbd48800",
"metadata": {},
"source": [
"Experiments:\n",
"Study the code and the results obtained.\n",
"\n",
"Modify the code and add an \"eval_model\" function to allow\n",
"the evaluation of the model on a test set (different from the learning and validation sets used during the learning phase). Study the results obtained.\n",
"\n",
"Now modify the code to replace the current classification layer with a set of two layers using a \"relu\" activation function for the middle layer, and the \"dropout\" mechanism for both layers. Renew the experiments and study the results obtained.\n",
"\n",
"Apply ther quantization (post and quantization aware) and evaluate impact on model size and accuracy."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": []
},
{
"cell_type": "markdown",
"id": "04a263f0",
"metadata": {},
"source": [
"## Optional\n",
" \n",
"Try this at home!! \n",
"\n",
"\n",
"Pytorch offers a framework to export a given CNN to your selfphone (either android or iOS). Have a look at the tutorial https://pytorch.org/mobile/home/\n",
"\n",
"The Exercise consists in deploying the CNN of Exercise 4 in your phone and then test it on live.\n",
"\n"
]
},
{
"cell_type": "markdown",
"id": "fe954ce4",
"metadata": {},
"source": [
"## Author\n",
"\n",
"Alberto BOSIO - Ph. D."
]
}
],
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