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{"cells":[{"cell_type":"markdown","metadata":{"id":"uZuN8Izp7uLR"},"source":["Targeted attack, no defense\n","\n","\n","\n"]},{"cell_type":"code","execution_count":1,"metadata":{"id":"uG3R2ERwwYnS","executionInfo":{"status":"ok","timestamp":1702674583356,"user_tz":300,"elapsed":8801,"user":{"displayName":"TAMARA STUGAN","userId":"09145662160487804942"}}},"outputs":[],"source":["%matplotlib inline\n","import matplotlib.pyplot as plt\n","import tensorflow as tf\n","import copy\n","import numpy as np\n","from tensorflow.keras.layers import Input, Conv2D, MaxPooling2D, Flatten, Dense, Dropout\n","from tensorflow.keras.models import Model\n","from tensorflow.keras.datasets import cifar10\n","from tensorflow.keras.utils import to_categorical\n","from sklearn.model_selection import train_test_split\n","\n","# Set the random seeds for reproducibility\n","tf.random.set_seed(42)\n","np.random.seed(42)"]},{"cell_type":"markdown","metadata":{"id":"VeOm7Qg1lqRH"},"source":["#Load, Normalize and Split the data"]},{"cell_type":"code","execution_count":2,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":12369,"status":"ok","timestamp":1702674595721,"user":{"displayName":"TAMARA STUGAN","userId":"09145662160487804942"},"user_tz":300},"id":"f1HW9kHG5CG4","outputId":"3f293bb4-c206-4c2c-e350-ae02c6302c78"},"outputs":[{"output_type":"stream","name":"stdout","text":["Downloading data from https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz\n","170498071/170498071 [==============================] - 4s 0us/step\n","x_train shape: (42000, 32, 32, 3), y_train shape: (42000, 1)\n","x_val shape: (12000, 32, 32, 3), y_val shape: (12000, 1)\n","x_test shape: (6000, 32, 32, 3), y_test shape: (6000, 1)\n"]}],"source":["# Load Cifar10 dataset\n","(x_train, y_train), (x_test, y_test) = cifar10.load_data()\n","\n","\n","# Concatenate train and test sets\n","x = np.concatenate((x_train, x_test))\n","y = np.concatenate((y_train, y_test))\n","\n","# Normalize the images\n","x = x.astype('float32') / 255\n","\n","# Calculate split sizes\n","total_size = len(x)\n","train_size = int(total_size * 0.70)\n","val_size = int(total_size * 0.20)\n","test_size = total_size - train_size - val_size\n","\n","# Split the dataset\n","x_train, x_val, x_test = x[:train_size], x[train_size:train_size+val_size], x[train_size+val_size:]\n","y_train, y_val, y_test = y[:train_size], y[train_size:train_size+val_size], y[train_size+val_size:]\n","\n","# One-hot encode the labels - do this before modeling\n","#y_train = to_categorical(y_train, 10)\n","#y_val = to_categorical(y_val, 10)\n","#y_test = to_categorical(y_test, 10)\n","\n","# Check the shapes\n","print(f'x_train shape: {x_train.shape}, y_train shape: {y_train.shape}')\n","print(f'x_val shape: {x_val.shape}, y_val shape: {y_val.shape}')\n","print(f'x_test shape: {x_test.shape}, y_test shape: {y_test.shape}')\n"]},{"cell_type":"markdown","metadata":{"id":"fkAoGMzDlzws"},"source":["# Check distributions"]},{"cell_type":"code","execution_count":3,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":419},"executionInfo":{"elapsed":2221,"status":"ok","timestamp":1702674597939,"user":{"displayName":"TAMARA STUGAN","userId":"09145662160487804942"},"user_tz":300},"id":"pdFra7HBeBdP","outputId":"97ee392d-f8a2-4762-9a38-b47c16c29843"},"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1500x500 with 3 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Function to calculate class distribution\n","def class_distribution(labels):\n","    # Count the occurrences of each class in the dataset\n","    unique, counts = np.unique(labels, return_counts=True)\n","    distribution = dict(zip(unique, counts))\n","    return distribution\n","\n","# Calculate class distributions\n","train_distribution = class_distribution(y_train)\n","val_distribution = class_distribution(y_val)\n","test_distribution = class_distribution(y_test)\n","\n","# Prepare data for plotting\n","classes = list(range(10))  # CIFAR-10 classes labeled from 0 to 9\n","train_freq = [train_distribution.get(i, 0) for i in classes]\n","val_freq = [val_distribution.get(i, 0) for i in classes]\n","test_freq = [test_distribution.get(i, 0) for i in classes]\n","\n","# Plotting the distributions\n","plt.figure(figsize=(15, 5))\n","\n","# Training set distribution\n","plt.subplot(1, 3, 1)\n","plt.bar(classes, train_freq)\n","plt.title('Training Set Distribution')\n","plt.xlabel('Class')\n","plt.ylabel('Frequency')\n","\n","# Validation set distribution\n","plt.subplot(1, 3, 2)\n","plt.bar(classes, val_freq)\n","plt.title('Validation Set Distribution')\n","plt.xlabel('Class')\n","plt.ylabel('Frequency')\n","\n","# Test set distribution\n","plt.subplot(1, 3, 3)\n","plt.bar(classes, test_freq)\n","plt.title('Test Set Distribution')\n","plt.xlabel('Class')\n","plt.ylabel('Frequency')\n","\n","plt.tight_layout()\n","plt.show()\n"]},{"cell_type":"markdown","metadata":{"id":"TMUtdD7sl7N0"},"source":["# Generate sample images"]},{"cell_type":"code","execution_count":4,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":826},"executionInfo":{"elapsed":5755,"status":"ok","timestamp":1702674603692,"user":{"displayName":"TAMARA STUGAN","userId":"09145662160487804942"},"user_tz":300},"id":"Nfi3vvs9c387","outputId":"ea492f26-cb4a-43aa-d824-827dcb2e848a"},"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x1000 with 25 Axes>"],"image/png":"iVBORw0KGgoAAAANSUhEUgAAAxsAAAMpCAYAAABsbC5vAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOz9d5gkWXnmDT/h0mdVlnft7fRYZgYGZhgEAiQQCwK51WqlF7HLJ/PuhySEkNtPSFqZC63MarXmW+1q9SKQtCutE0KAkBAwwzhmGO/a++7q6rJZ6TPs+0dVV9V9n5g2MFmNeX5cc9FPZcSJEyfOORGRed/nsZIkSURRFEVRFEVRFOVlxr7eFVAURVEURVEU5RsTfdlQFEVRFEVRFKUn6MuGoiiKoiiKoig9QV82FEVRFEVRFEXpCfqyoSiKoiiKoihKT9CXDUVRFEVRFEVReoK+bCiKoiiKoiiK0hPcq9kojmOZnp6WcrkslmX1uk7K1wlJkki9XpfJyUmx7d69t2r/U9LYrP4non1QMdH+p1xv9B6sXE+upf9d1cvG9PS0bN269WWpnPKNx9mzZ2XLli09K1/7n3I5et3/RLQPKi+N9j/leqP3YOV6cjX976peNsrlsoiI3HnXq8V1V3ZZXl6CbbJ2bOw3kMHk5FsGChAPD2I81F+EOGN7EDvZvFk5x4FwqboMcRBiHSr9/RDbUWAU2fW7EHc6GOfyWYgjiSBut5tGmX39ZfxDgvv4PtbDoUvj0HmWiiXjGMUCtqfr5SDudH2sgkVvorbZHXwf9wmT9W81Ol1fPvTv/nytf/SKS+X/6z/+b5JbPcfpI0/DNvOnDxv7RRGez+iWfRBv2bkf4soYDpZcHvc/dvBR4xhnTjwPcdjAa+9QHcqVPojdLF4zEZE7X3MPxLv2YL07NRx7B198FuI4xmsmIhKEHYgPHXwR4vryAsQ8BsKAxtli2zhGo4XHCCOsx/DwAMSVARzvcdIwygxDjDvt9fEcBKF89u++2PP+J7LeB8+ePSt9fSvXMI7NOe8bBpw2jW8z280WxItL2H8GBipGkVGAfSqfx/ncyeC8yvNTLFgH7JGbT61Wk+3bt29q/xsfyYltr7RDLo/ze9o3zq6FrcTfPoYx3oeEyliu1SHO2RnjGAUbj9Ho4jxgF/C65jJ4Xy8WcR4QEenrw/t0tYpznt/CvkTdVQLfvK9T9xHHxXpnXGybviK27/hwBeLp2VnjEC0f27Ncxn1Ceh5pNWsQT06afcnz8B7iOutxEEbyqc8d3LR78H/6k49LvrByvXj+y2fMvuHlsA0TB/vCxucJERGXRrVN3dNLm3ITbNOErmNgce9ArCjl8wT7aBTgNhFX7Cp+7Em4nglPshjGMR2TNkg7Ky4z5jiievP+KX8LjXqvX4R2qyk/+943XVX/u6qXjUuTmOu6ay8b/PDr2CkTnYOVzHi4T5YGEU9CGQdjN4vxyoGxjDaVYdtYhxyVwX1GRMQS6tE0IXM9I7K+xJHZrHxcSXAfmy6zI/SiRe2dT2mLfA4Hu+dhzPeiq3nZcGgfnhxWyu3tz6qXys8VCmsTXZYmsUzKRMcvG7xPnl7OCvQCxy8bubz5spvN4uRp80sj14G2d3MYr9QDb74lGshujMcoFLBecWw+hvkBXqNsFturS306oTFg0U3Adc2b+aW5YX0nHDd808zwOErM/sddKwrN6XAzfta/dIy+vj592RARj+bdIMQXy0tttJHIx4dQHn9fby8bl9jM/mfb1trLhkMvDmn14G34ZSPhBzEqw7YvH6cf4/L7OI592VhExKUXAWMfPg/aP06TdPDLhn35ergUe1Qn/nylDKwJnwc/GPMx+Ripx03ZZrPuwflCUQov9bKRNe9lGbrnxsbLBrU5jWqnBy8b3Ffsq3jZCL9eXzboGkUv88vGJa6m/6lBXFEURVEURVGUnnBVv2xc4tChg2KtfhtQnZ+HzwZz5vbWEP5xOMJvaK38KMTNeBHiBr1xJpb57XWrg9+otdr482oQ4VvYPH1Vn3PNd7kwxH0c+/LfTrc6KJ0JU2QsVmcIYvrlWYIuSQxcbLsGSaAWI9KXiKx947B2TJKhWfRLkdA3O62O+W11GNA39e76uXcDsw69pF5dWmunocogfJaMjBnbJy5+uzqxbRfEEf1CYMcoDYlbeH4dkoqIiCRt/LZ2ahj79LateyDeumc7xJNTps5xdBTPxfPo26AKfiO8dcs4fh6a/a/TQdlTdQklS/PzOPbcDA1okmMMDJnfYuWKeIxlkntlcziO4gTb13PNMmvLVYj97vp4DTe5/zG9NgV/LdNtoVx18dwJiM8exM9FRJZrOE++9o1vgrgvzzcR+uaevtm73q1/Pa6/5zhrvxREIc5fcZTyjSP94tslXSJLifiXjUoZ55q+FMmTX8frGrdx/il4+MtrP/0SWzCuu0iJfvWcp/t6nJC0mX4hHhkZNspcWsL5iGVokxM4dzv0Pe/oKN5zvJR6nzw7DXHGo/as0K/W1JxDJPMWMft9s7WhvVOueS+JrZX/REylic+SPBFpLqMMzyvSr1zUN4SUE/xrZpgiiYrouaWzjPehTI5l79hmjbYp37Ut3KdUxOvCv/yzPCntm36uOf8KwafGv2xwW/APIyv7xLQN/TpyhXrGKb9tGFKsDce40i8lG7ne87WiKIqiKIqiKN+g6MuGoiiKoiiKoig9QV82FEVRFEVRFEXpCdfk2ci56ythCMmrtw+Z+sUdY6hzGx1BzWOePQa8vCItodehpRNFRBLaJ8MrBtHqNUmMZfQPmkuP8soDGdIVskyNV1Hp0qorIiJBiPUs0D5uEY+Ro89DC3WxdsqKACGv1kKywVIRz7VBy1cGoenZ4MVH6rV1LbYfXL1e72UhCERWV0Hyu1jXVsv0KezYNwVxo4lt6Ad4nQaHsb+6Hr6L792LS9CKiNzzmldCPEXL5/b3j0AcuNhmhZTVqNhGZJHOut1EjWmXfDWFvNmnByqoR96960aIDx6kpYMtLLPbxb7S34fL2IqI0OJnsly7CHEieI1Yk7q0ZC4Z3eYlLjfsEqb4ljYTYzWRbyD43GwSFM+cPQnxs498EeKgjf1FRMQrYZ9p19DX0TeI9wdDo2xdfgWizeZ6XH/PtddWfrSoPQaGh4ztm3QdvAg9GiHNLRad08Q4zhvjI+YxTh47DvGwi/Po+CR6yuyQVq9K0bezf2eIlo5PHPKBkNehUDTnQMfGcx0ZQ18HrzJZp/4ZJjgn9ldMf8UUPW/Qom3ievh5llZnin3zntpXRu9hEqzf+33Z3HtwvdlYW50ooPvO/JzpaTx3HpcHdnK80iLOCVmbV6TD8vyUZ5SYvHutOt4f8+R5FErTUPfRVyIi4vt44F0790K8Zzd6L/O86lbKSoXG33h1UPpDzCYODlPmn2udk/iZ205ZVivm1Vm/QvSXDUVRFEVRFEVReoK+bCiKoiiKoiiK0hP0ZUNRFEVRFEVRlJ5wbZ4NKxLbWtFvlcu4674pU8M9lEd9qBejRr6xiBruKMZ3nzblObDNNBvSV8Gszy55Haq0zjMnOR4sm9rOOq0H71MejTat68xau1LKWuSBj2s/25RZ2qPcHVGEx3DJgNHtmtrFDInm7Rjbr9vAdcYlYv2oUaSEpDNcbq5r6P1wc9f4DjsdCVc1hlaIWtVsxszuvUy5YIbG0U+x7SbMgTG6dRJizsAuKXrRIMQ+fegC6lZbJ+Zwexv7/OHnnjHKfNUB9FN8y12vgph1mTXSFp85jWu9i4hkPM64jjrg4RH0t5w5exS3z5Hfp236K2o1bG+X1pjv68My2qQnT7NgcM4byHx+nUX7m5E5+nrB68gH5NmZPnsa4j7OnVBBjb2IyOwSzsULF85DPLZ1G+5AyYj4clsp2aw3k+tx/fvLpbWs05wnYnR01Nh+dgHnoxzdZ5aXqhCPDaPHLEs3hXyecjWJyNRW9GQU6f4X+DiwM4LzajZj+tZabbxfbp3Ec0solXQmi2X6vunhGx4iTx5p97tdnNPKPF91sU71Zbqfiki3i/eloWEcB/ki3vddC7d3ffMhp9PE44Yb7v1RuLmejUe//Jhksiv9rkHeQVvMvtHu4qjtRNgfvQzGDj0DRjTEOol5k4jI21CkHFF5C9s8R306ss2+0mzivf7xZ5+CeHYe77G7du6EeHjYzPOSL2B/SjhDOJmBY/LlWtQ2qYk2rpGE83Kk5Qe5TJ6NNG/KS6G/bCiKoiiKoiiK0hP0ZUNRFEVRFEVRlJ6gLxuKoiiKoiiKovQEfdlQFEVRFEVRFKUnXJNBvJJ1xLFX3k/yZDTrL5oG3ZE+NAxFMRpg2NrkuORQtvFdqBubBl2XHN8umWoiMnUlDpY5O1s1yowoWV29hebIVoSGolIezbbSNU1bDhkuOUmWk0VTU7uJxuOCh8dwU8xBnQ7Wq03JbmKyWFYbeIxqy2zfBpn0O8F6+4XR5hrEu+2WWKvXt0TmyL7BEWP7O257BcRbd2FinjoltDp84izENbrujWrVOMZCFQ1uF2bQNNhHSf3ExiR1n/zL/22U6f1j7KOvv/te/NzD6zQ+jsZ2SdCoLSJSJXPuk089C7FLiY+KlEgqpMUE/EbVOAYNLRmhJJ4RjZuFRaynLeZiDTy+KxsSaXFSKeUrIy0RFM9Pc4vYz0+dOgNxlz4v50yja6tRg/jQM2i6HN+xG+LKOC5awIbINH/kN7JpX0RkcGhQvNX7JJsz/Y6ZTHaMkvIVcnifzjp4z50YoSSkAc6BC/OYpE1EpNyHJmhOhhr7WE/PpURitnkh2y3sK5xrzM5hvbu0AEvXNxMAZ+mZpVHDObFYwvmHDbsLizi3Zz1zIRjufj7Vo95gUzXu4NfMZwffx3lu4wI0wSYbxJebHfFWkx4nlHHPSlmxw6VEiQUyazs2xrx4QIeeEsOU78frLVrAh5L3Zi3sK6UE+wEnXhQR8bI4Tjr0rHT8LC5ucfrCDMSVPjPh49YtuEDNCCXhrAzgIksuLZDh0LPt1STwo9u2mSjVmFNTkhEaBvEk9d9XQn/ZUBRFURRFURSlJ+jLhqIoiqIoiqIoPUFfNhRFURRFURRF6QnX5NkY7s+JuyrMLnuoJ8vlzIxwtoN6rnwedXCsNzT1ZKjx9kNTHxaRnjFOKOEe6cQTFzWBdd9MThZFeC4t8iawV6FOCWDOL5plepRAqK+B5xrMoH69vYxa2W3DlIBuFPV/IiJWGZO7dZdQR91oYL2W66hDnF9G3auIyKmzWGa0QeDIWr5ek826ks2uaEADB3XC7XzJ2P5kDc/n6Qcfg3hxAfWz56cvQuxRIkW+hiIi3RD7F/tmJkZwiM3OUDK0rKltr1dRr3zk5EkscwITBnkeHmOCkmyJiEzS387MoD/l8HMYj06gdvvUGfKBBCnaTtJmRy6O7xwl78q6qOdtd0z9cV8feZXc9TISTnKkfIWY4zhJ8FqcP3cO4pNnMD577ATEw2VzPG4ZRo37hTM4Fp57/MsQv/INFYgLrIP+xrZnpGJLvKbz97s4f0cpPoWQE9d18L7iktGqVl2E2CLNfBKZY/T8hQsQ95dwbi7QPbfWxXtKmvY8k8M5LaCEqgGdq0X+zjjFyxA7nAiWktBRNVptPEYmi56OjGcmIyzksFNmaX5fJt/fchXbopQztf4W+Wo2jgM/SMmE2kM6fizhqv+U7ztpAzKJOAEyxhZdE7KKiR9gHw9SnljLBZxr6jXs4zX285DXKZMx78HlDHlqHdymGWLf4GSE3Xm8riIi1So+bxRL+Dw8MYHey907d0Fc4vtnSr3Zx8i36USwL3HiwLSxyH/a6AOJkqt/hdC7taIoiqIoiqIoPUFfNhRFURRFURRF6Qn6sqEoiqIoiqIoSk+4Js/G+HBBMqtrfPdlUCtYKpj6MSvhdfAT+pz0pG3U2vEa1ENlU89YLGK+hdoyasv7SfNd72CdTp83cxI0uqhry5DubapAuT081ASeWqgaZXYTLNMjcWI/rVV+z42vhLh2gbSzLVNb1z+MGtRuC+vZaOC7ZdbD7beOYx1EREZHxyC+WFvXUIZRLGeeP8e79Ix8flTy+RXd7GwV+9+xs2eN7V984XmIbdKYRl3sC+06eloc0ju3u7T2u4hU6/i3ehN1mafOHYS4mMc23r97v1GmkA/koQfug3j7zp0Q79u/D+KhIXOcZEkD3d+H+k87RI1ps4t9pd1CjWq7imvUi4hEEeprc3nsX7yufR/l8sim+L54jfnWhtwnwSbrlU3Yt3I1JoJrNBokHKb4pHhtdIvXv7/Sd0pmneIY25Y18/UWXutzF1Hrf5FiEZEowpwPW0axXoe+jJ6q0fEJiPe96i4q0bx92bz2PzcXNQVtbtyTLsu1bPsyYUmyls8gk8HzT9Nbh6SZ73bwXjWQRx+NZ2ODuDaO4Y5vjtEM5Yjyu+S1rOG8miGteppm3iJPaEQa+TzlCwlonij3VYwyczmsp2VRPi3KgRH45CcgjwaXt7ITtTfNm5GPHTDjot+gbxBzE60UiWOx1twwB25yno2231nL8dUN8FzSctxwG3EP5fEX04DluEn3VxGRXJ58Mtx3Avy8Q7nXQsscxwkdN2NzDjhjD4hczhmXUma9heeyfBSfFeYX8Nm0TH6eLVOmb3eAcnVkspz/DtsiplxjYcqUxrlNog1+vq7xjP/S6C8biqIoiqIoiqL0BH3ZUBRFURRFURSlJ+jLhqIoiqIoiqIoPeGaPBsDpfyaHs71q/BZ1lhzWaRA61J327wGMOrFKhXUm7EG1Y/Md6OA1mEulFADOT2Hmsnjp1GbPlc3dd8t+tP2POrv3vW6V0C8ZQKP+b+ewDXnRUQeOTYDcRijrtW1Sc9XncM6NfA8ymVaI1xEJEI9Xi6H22RIE1+w8PMwMtti21Zc+7m8uK6794NIvriJno3KwJDkCysa42Nnj8BnF06dNLYveNhmy80liBu1WYgtWn+7WkdNZbWNfU1ExM1iGw6PoS49Tz6jqR23Qbw1xadw8plHIHYs7CsBrXU/N4/5VG655YBR5p69uGb3VsqjUXrN7RA/e+gMxN0Oam+7XkqeDUEPRpxgf5qZmYY4k0UNdP8Att0KqPdut9f1ttffs3HteWaSK3k2DFFzQmHKOuiC7WB4NAwPB8dp4F+37dgBcYH8NrUm5eixzLn6+bM43vIuXn+XctS88PD9EA9NoX9sYAv2aRERK2RfIOVuYs0yzbv2NVzSTU4zJCIitm2LvZpTIokpj1WR9dkiHdKjZ4ro0YialJvDwvv4+Bi2ebiQctLkMStSPoAuzaP94+hL2OjDeimGx3C+6jbwmA7dy7yUHBg50q932livbAY/tzN4X1+mtgoC0y/h0D20Qx5RiXG+z5OnwU3xr3QCPNe5+fVnA8751Wv8JFnLzWDRseM45Z5gX2G+y9L4pLwvsY3t6aY8sQaURyPjYpuW8timLR/v46GY95EudfMuzStZGyviUP6KJOV7fH7eDSmHjU25YmYWcb6c7uJ9/thpvEeLiIyMYA6uycmtEJcoB06O/FYJe1NEJEjIs7Hh+aPbMZ+JXgr9ZUNRFEVRFEVRlJ6gLxuKoiiKoiiKovQEfdlQFEVRFEVRFKUnXJNnY2RgUHKra3u3F1GrZVtmUY0W5THwSX9noT6sRRpIfhNqk3ZRRKQygNphP0Jt3YlzqBNfrFG+CtfUSDqkG+zL4T6jLuYLyC2ilnNv37hR5oVBLPNiFfV43Rae21NH0JNg0wLIQRHPW0RE+lFfK6Qr7O9HD02ZNL8d31wzOfExj8SOkXXNb8ffXM38yZNPSHZV43ro+DH4bPrCcWP7iPJmlPtRr7x/7w6Ibz5wM8QX5lALenoOyxMRGRnHNt++G3NglIfQh3BxCctI5k2vyRnSYs5VUat54Ebc/tv2oUej2SD9vIjEJC9OfNLHfwl9Inv3vwLisakKxF967IvGMWYuYl9hT0WnjcdcWsJxlC/hMURkTR98iWZrvf3CTV5j3uTav6sx8j4QhieDxmicmOcckGae8xZYxkHZx5ACzc0DA6gFvvdb3gDxc08fgvjUydNGkRFdr2MO+thyO9AfFh0+ise4/yGIX/0O1PGLiOQLqLOPOI8Gx7R/eBU+nEuel+vR+y7M19buT9xXil1TM1+iOa9DuSNKDmq2pybQN5ktYAs5aHsTEZEByrFVKWCZ5XHsO10yxhwhL5eISKWC97cu+e06ZKz06DyCmnlv6nTxPh1TH3coP0OjgfNTSNMqP2uIiIxU8B472IftebSOfs4hyotgmZJ56SMvThys6+43O89GlMQvmV8milPanNrQJdMFj0/XxrmM83B4nukBcfkxlr0jNP+VMuRVTZnGY/pbQGWGEdbTJo9akpKwIqIZI3IS3gDLoI8t9tgG5jFq0zhOTl84BXE2g+OkUMD+mpY7Jkv3E29Dfja/az5rvBT6y4aiKIqiKIqiKD1BXzYURVEURVEURekJ+rKhKIqiKIqiKEpPuCbPRmVoWPKreQUGSrQmtW3mfajWUD8WNHFda5vyBcSCGrSEcneUSqaeLBD828ET6HVodlEjn8vh+tuXPCgbyRdRxzbgoBbxiWMXIQ59LKPbb3o2RgawnhblJAhC9MC0aO3oZotyjoSmPtJiTwvrHWnNa15T2UtZxDoknWuyQaeapGhWe8mXH/qCuKt9wh3bD5/tPnCLsX3ex/504Ma9EO/ftwXiqENrZdt0DWTeOIbr4XV1nArEQYj9rVlfhLg/xfcSUruemcVxlCudxzJIF7xr9w6jTF73u13Fte0PPfo0bt/Gtrv5LW+F+JZbzRwH7cfRs3H82CmIC6Sn768MUQmm/rhGc0i3u17v6+7ZYEHxFZaUX9mH8maQR8DwEFCukqPHjgrTbuMcd8MB9PBks9ivbTYupBAnuE9Mt4p7Xvs6iM+cxD75X//wvxplhuTZOTNXxXoWcKzsJZ/b4Qceh3gkJc/GDa+9C+IWraHvkRg7Q22x2MI8TCIiXR/nwEvek3q9bmzba7phLJek3ouLOJcUWuaa94N0T/DoOuZK5Olo4RhucNKplK7j0L2oW8f2GinjuD98FH1qpRzeb0VESnl8vuiSNnxgAnN1WBHp2VuUP0REcnR7q3dw/shSzoGZi+QlibFOpf6KcYxOG+fVMEAfZJ7yKpWLqIdfpJwkIiKdLl7X8oZcYmm5PnpJN/DXMkpYNHbi2HweYF9RSNex3cX28shP4ZAXIuuaz5kJ5ZKxeO4iv0VCBsaUakuL8qX49Gxq07OTT23h8b1BRBKbfLc2+YepHrZDBh6LfNIpPxXwqcQ03/mUW6bWpP4Tmb5o6eI+G697lOKjfin0lw1FURRFURRFUXqCvmwoiqIoiqIoitIT9GVDURRFURRFUZSeoC8biqIoiqIoiqL0hGsyiIvtiqwawS3PNOow2RxuUxA0o7n0rmOT4yUgU042328cY34GTXqteTSU7hpE0xd5rSRXNM1p+3dPYb1op9DB82ITq+uYJsNyBs99aGA3xLv3boP45JkvQ3zoCBowM65pgEsSNPKEIV5emxIYshmLjVQiIjE5Aq0Nhi3L2tx31bnzC+KsmqZuv+0fwWfZrJnga5D8VROTaMpfrGLfOXsMDZd+jIZV2zLNeI6LbRYldF3oGkRkkEuitERcmARroYEGYJv6UszOsrTEZHSYUg7bYsfkVohzlHDIFuxbt9yMyQtFRCqVCsSfaP89xDMXcJxMjVISN8s0uHq0SESttm5gXUkaeESuF9zuaQn72CCZkPHQGEJkNDx7HhM8/s2nP2kco1bD+eaeeUwY+q2vfyPE2Sz2a7P/GN1FQuqnpXIZ4re/8+0QHztsXpd/+NvPQlyjpI+HzmOSvwELDbm5DjbWlz6D/UtExB1CM7I9VoG4WcW28sgseqF2zihzuY77dDor/bTduvqEVi8XIwMlcd2ViS3s4Jgsl7LG9gklfHRcbMN8Hu8J3BVaZOr3UzKgZcl5fWD/HohnZnBBlW4XDzI8Ys7dYYTG6ljoWYKM7X4L+6eTNw26Dhlym4t4XZdpcYD+PpwjG7RISxSbSXCz9FwUkHl+ahvOs3x/XaqZBnG+L1cG19vLDjY3sW670xF7dS5w2aEcpzxOUt3bTewLmQy26eAYLtqSp1uuHZnn63AftvG6LC9hUtx2AxdB2L4TF5sREakH2L+WlrBvZLP43BiQUdpKWezEmGfDy3/O6+9kBM/LdlIWlwmwP0WcnZCTD9ICSnH1rFHmwnlMRCnJehlpz4wvhf6yoSiKoiiKoihKT9CXDUVRFEVRFEVReoK+bCiKoiiKoiiK0hOuybPR6YRriaysgPWqpn6s2URtnB/gu01oo5+i0UINfY3iqa1mdZMQt9k+jJq13ZOooWx18POpfbcZZWYS1I4vLVNiHk5GtoDmgK3jE0aZ1SZq43bdgAnm+gYKFGNirqU5PM+lZdMX4pGW305QwxtwMhuS20Up+k/KAwgadNaj95p8cUDc1cSDHh26Wp01ts8OViBuhXjCHbII5AdQh56N6eQ7pg4zoS7ZCTBJUS5PvhkLtZ2xbfbp0hB6GTIJekmcPCbxSzKUxMjCOoiIWBH1DQeP61FyqXwJ47CL/W/hPGpvRUSGiqi9fufb3gLx48+cgrhBevBOd84os9vGeaZSrqz92/dNzfTmQv0hxcO0RHrh5SW8lpaDfWxmDvvxI48/BvETLzxjHKO2WIW4S/rhm265GeLREfQEOY7ZB2t17EPVKh5jxxbUVk9uGYX4PT/yQ0aZZ88fh/jRZ56FuNvEfnz0HHo4CuP4+cLzzxvHaP0fjHe/9g6Ilxrk8aMkdl2rapTpB+jDupS8rNM2fXO9pph1xFv1bBzYjT6/fMH0H/I4nzl7AeIwxHMolvA6Vhs4SToWzgsiIhb5DurL2MZzs5gMNTCGren/bDTQuxAnuFOrhffTRg3r2VfAuVxExCfNe2Lh/c4hD0If+ZLyBWzLS96ZjZTLlOTVvnyCuZNnUCNvuWb7Zii5W31D8sZgkz0bURSttxvdgweyeWP7PvLEtqkNhe6HXgPn+xx5hEZHsX+KiHTy2OZ+yIkUsQ5OAetZIG+OiEiliM9w48M8B9CzBD0LtVK8DDNzeM8MmlWIPerjLiV6dmJsqyAwk4q6Dp5rTEmvjeeNNj1zT58yyuwuYb0bjfW2uJZnQP1lQ1EURVEURVGUnqAvG4qiKIqiKIqi9AR92VAURVEURVEUpSdck2cjsiKJVnXJvF58mnYrn0NtXKmMerLpOdTnnTyHmm2XhPmZi9PGMToXcZ+9o6j/fNMb0Btx/DxqpstT5hrfw0PjEM+S1q5SIf17jMfM2KaWc3YO82S4uSrEc1XU0p6/gJpVz8O2q/SZmsB2m9b0pzXVLTJgxOThsC1zbXKLdKy89vNmMr51u3jeiqaV69Xp1IztL9awe2cqqFUPQtTHcu6YNumGg8R8N3dd9MWEDsasBx0dqkKcLJpr9fukw7ViXhsfxxV3tzgxdbxRRNfaw50SB4/RaKKW0yINapbXWBeRGo2TfGEQ4m+5+1aIDx8/DfHzL6JGX0SkUUNtdsZb16Butl55he7qf+b4EXP4yHIN9eoPPPwgxKenMa/DfK0K8RJdB7toarpzXZyPZhf4mA9AvGMHrvXPeTdERM7TXBz4qBdut7CejTrGXsqd5cCrdkH89LHnIPbrOLmcq+KYLmSwnlv6UY8sInLy8SchdrKUy2kS++RyiN4Uc+YWkQTbvNtduf7dzU+zISXPEW917BYLeN05b5KISH8Fz5fTTywtoKfohYOYHyWkuSebwTwmIiKDRfSQTZ/He93CPPbHTojXrbZsas+NfAB0u6tWMWcP2ZTE79IfRKRQwKs7OIR5uzhvVDfE8Z3E2D/bHbMDJILa/pDybFzqO5eIaA7J0zVNw/XW+2Oy2d8Xh75cMmv0ky+mwn4METl/AfMEtWkMdznv0AzeE3YOoUdjdCvmQBMROTSNz4UJeS0LTbxO/UXsf8+dNX1wpXG875SyOLZOHnkR4ojGQGUv3utEREqTmH+mefogxA7l/+ijvGmtRhXjuulTzXg4Pmsd7PP5Cj7vDtGE0JAUHyTNGfDslSQikellTUN/2VAURVEURVEUpSfoy4aiKIqiKIqiKD1BXzYURVEURVEURekJ1+TZ6O8vSj63ohcMXdTaNWg9bhGRJEAt13Idc0OcPsPr96JGLZ/Dd6ELJ01d/lgO9bRTU9shrkzuhNirk/gzZ+pct9x2F24ygxrUfIh65kjw3JtNsy0mCqiV8yOsh1VErd2WIuZaKFfQR1JfMPXtsxdRfxtYeG4dn9aFt1GDWsyaGmi/Td6RDbrgKE2k3kMSy5HEWtEgsl6/VTd1v1nyNtRr6NfxO9gerRqW4dHplYumtn1kADXRfYOouR2pYB0iF3XC7azpO1jcjte+G6GfRyiXRxRS7g7ODyIikU39jTwblUHUnMYRHYPau7/fXFM9Y2F/qpKOPwmwL73iAPbpStls309+8u8hnru4rv8Ow6vTir6cHDz8nJRKK2PVdXF8sa9BRGSJ8lNUGzgHnrmAc0v/KObwGaR2Hho2PWZzx7F/HHwevRCf/YfP4jH6sEwnJV9A18dr6XdxTvvM32Hs0ddWnHdDRKQwjO112ytugPipBw9D3BLss0cWyBMUmfr2gRB15Me+9ATE1RGc4xZpXHi+OQeGPNe0Wqt/3/w8L5NjI5LNrNy2We8/UBkwtncsvLbeMG4zPoL97XNfuB/iOKZ5omzOLTMXsC+MDWAbVvrx3ladRQ39/Kx5L6sMoNetSF6lfvq8XMR5uNyP86yISLGE/S+kHD4njqFfwKGcFy3ygfgp493v4jVxyAtnUZ/O53DOiyzzeSSgfhZ0N+bZ2Nw50I6Ctdxb4yW8rheXTA9BQP3FpdwlNvXPMEAvzvY7boJ4SUyvqk85yhyLclv1YX+s0n2+nuK9icmT1u3Q/Y/KPEvPrs05fBYTEdleqUA8uR99HdUX6TnyPPbHpYsY15rmMSLKS7LcxvbPD+D9o7wV47BlPmNzPiF7g0n0WlKt6S8biqIoiqIoiqL0BH3ZUBRFURRFURSlJ+jLhqIoiqIoiqIoPeGaPBuN5UUJOyuaQtdnfXvKewtJgV0H/9Ai/fJAGTW4FVoPub1k6slGJ1FzOnXr6yF+/hzqKo8cw/ieCdR6iohUq7jN2O7bILYF9ex+Fz0cFV4UXERqs6ivy/uow5wYxHpUI9Ryerei1rZNeTlERB769CcgPncW6+UY67Cjnq+dor8L6H3U3qAf7Wx2noPQX6uyG+M1SllyX7b24/ndsKsCcYnywDjUh5uU86DTwv4qIpIv4nXcvxev49btWyC2PfQUNUjTLyKydWICyzyJWti+QTzZQdIvu66Zi4GWiJeExmauiLrXkDSqZO8RLyXPRofWmB8aRk1vo4XjpllFrfbUiOlHeNc7vh3ij3/qH9b+fT3ybDz6xGOSz6+0f5tygBRzpofg7W9/J8RhguP6iecOQdxfpnEeo453cnTMOEZwETXHy01s59ZR9EIMUO6JYr9Z7xJpe3NFnNP6K9iB+imfTF+fmY8hX8I+9oY3vhri5XkcX88/fwLiKMDxfKZqeuM8ypXjzmAfqS9hHJYpZ00ec/GIiJw/i3NtbfW6x1e5vvzLSZLEkqzeX7I0n7M/QEQkaGIfzTrYhgkZ0yLKq2HbeIzUbydjnAO3b0ef5DCN6y2UQyqbNX0KfdQnHar37Cx6ne55NfosxyfR9yYiEibYX2oLeH9cmke/wEIV2851cBIcGTZ9ITFNtNxH+snnsEQ5RhLb9MT4baz3Rv9ctMm+tYFyWZzVMTZcQv9FdfGisf0geWKz1N/YDzW6ez/EuyYwJ9ALZ3BOEBGpZPF+F1LSldHxCsQ23Zeartmr7TKWuTSH96rto3hfb2XwmEsR9h0RkcUl7G/2xDaIt9z4GojPn8N7Q6eN87rnmH0loURoDo3NbhWfJeYE+19I92gREZvmla902tNfNhRFURRFURRF6Qn6sqEoiqIoiqIoSk/Qlw1FURRFURRFUXrCNXk2bEvkkkwsovwLSUrOBVtQjxfRmspLtEx5rYZ6s4TWtZ5I0Ra/6lu/FeIt+1H39n8+8v9APE75LBzfXGP5/InjuM+uGyHODe2BuJig7q21aK43nY9Ri+2T/m6+jnFlBHWvQ+M7IG43UCMtImLTn6IMaj0t0oMGpG20UvSfVoJ/C8P1LhNE17DI8svAa+96heRXfRa7bkQfzfT588b2U5Pon9i3dzfE4yOYC8BJsH3qlCeiG5h6Rm7TUhH7aKmE/gongxpxLzbXam83Udt5x83o89ixbwfEAekyk5TvEMIYx2JCek/Hw6kg6JD2mLS1dorO1crRHEDbdGm9eNdBPW/kV40yR0hfe+/rXrX273anK3/1iS8Y+/SSU6dPSXY1t8/yLGq89+7ca2yfz2N/mJ7GueH0yTMQl4rYP7jPWTVzvmpXybtCfXLP7l0Q7x5BrXl5wJxLZmfJTzeI13JiK55XvYb1zJi2NclRzoY+qse3vRXn8kXy6F08h2033zUPUljGfUbJS+JSLpipMs4RxTHM/SIicv7UKYj91sp8H8cpJ9ljzp0/L95qXhSea+p1UyfOenZfcAxGlCumQHkQ/DZp6kfMXB5ZG/vk7l1T+DnVwfawj2dSPBv5PHlFqE8nbbzndmv4PBL0m+NkaAL7mx3iNtu3og4/m8O+VGtWIc5kzMcnl3I8cC4WzmkT0TOOk+L7SkL0wpU25BTx/VBEDhr79IqtYwPiZVau53d/xxvhs9Mndhjb1zt4XbodPN+wi/1rxyT6GBLywCTD5vhcpueYZguPuWUY7/MheWobKXnREsp/Ukqw3zuU42aM8iE1Z/EeLiLSOI9zZEDzV3EM+9/kTa+DOA5wTp6dxudUEZFWg/KNUT37itj/XMExkKS8EQQtLGPjs35yDYk29JcNRVEURVEURVF6gr5sKIqiKIqiKIrSE/RlQ1EURVEURVGUnnBNng0rWflPRCQiLaKVsu4+y7qTNu1DktfBIVyHfbyAer47XrnPOMaBe9CjsTRLa3iHqHPbtQV1cTFXQkTGR3FdcM450KI8HH6Inwdts1kjQe358fPnIH7u+cchvuc1eIyhccwnUqubvhAPm0+Gd6D+M6ZrFPnkx+ia/oHluSrE3fr6QbrB5q7xfftN+6S4qlO+6Xb0bLRv3m1sX+xHvTZf6cRCHbBNHoLBIupDk5RXc/4T67h5HXGhcdPtmtri3XtQt5rP4HVsN7FPJzb1N8vsfwlp1WPSWkbUFrxevN/GekaxqS22XWpPap36AmpWT588C/Fr773dKLMVoAa1sMEXYiWmT6zXtGrLEnZXNMutDrZJtmAme1mu47U6ffYUxBXqoxHph60O6rUvzBwzjnFheh73sXGff/w93w1x3FiE+PMP3meUefpZ9EAN9aPufuYotv0Uaa2XA3PNffFwzhocwpwht+y/GWL/XdiP/58//lOI23VTaz1dxflfKOdM1ye99jzmP5rsN/0rGfIPDI9WREQkiiI5d8bYvKe02r54qzfWmHySfornbnAEPSkxebc6HZyPtm7FvAYvPo85WjzXHHMT43i/HCFfh0P3WEqFIpmsOV8VaCxxng1p49zcrqG/YnHOvD8mNvaXPHnM+Jh9ZZwDay0cN0lEplORNU/hJSzqf+yT7MvjTTtKad++ApbhbZTdU76kXlN2OpJxVq7n3XfgmL/rpilj+3oL56KAbqJBiG0ctnBObdP8t9M3j9HqYr9vNLEMj/yIS9RXcjvNvFTtLh43qWD+nfMzmHvnKHnvbhxAn4iIyJk57D9CHrYoh36p0vY7IH7d7h0QL541PRuHn3wC4tkZHL9FC32G0kWfVycyO5RFzzTuhg6YJIl0U8ZBGvrLhqIoiqIoiqIoPUFfNhRFURRFURRF6Qn6sqEoiqIoiqIoSk/Qlw1FURRFURRFUXrCNRnE4zCS2Fl5P2lTQpIMJcsTEXEpYZBjozlqzzgayXJ5fPfZsR3Narfdi0mfREQm9t8K8dOPfATibVvxGOM33QJxZsQ0FrsFTP7TosQ07RqaVi9Oo9F16SKav0VEIkrOlS+jGW14GNvq7PRTEI9NoDEqpMQ1IiJJG01NVhPNQFFCCVzINJxPSa6UGce/1bLrBraOv7kG3VyxKPlVg3iJku4UCyldmRIokedZLDaIs0makv/EgbmYAButeaGEkGzplJtKEst83y9V0NQZRlhGRMYyiSnhlZhGUU6KJRHGnNwrEWqskBJAxuYxslQvL8JzK3bw8+Qi9se5E6apeMt+XNBh3t7Q7+3NTSopIuL7HZHV9m2Rue7YSdO8/Vcf/98QP3j//RCzyf0iJSebO41zi5eSRy6ga5EZx/nroS8+AHG3hobyF48eMcpsXkQjcXUOj1EZwvlrbga3ry2bCeYGKmie9SM87n33PQlxvg8XxRig5FzzAZq7RURalCTsPJnIkyyZgqmeToqxuDKE7ek4K3NNEATyzBPPGdv3EttxxXZWxhEnSMu6ptG16+M9IZvDMWnTnBZRktv6UhXiVgPNtSIiO7fhPTRPbVwqoPG1fwD7QRCaBtMoomR3DtZ7eBjLnJ3Fel9gM66IPPH8sxDvoYU4Zufw3KYvYGK2ULAtK31YBxERj+b7bBbHSUj3pG4H+2ecckstDFYgrjXW54hok+fA5lJV/FWH/7mTz8NnW6Z2GttPTeAiEC71hZgWM6nN49xUreIzzNAgzgkiIk1aeKjVpiR/DRzj9QaO5/2U9FREpNkk4zQtkDKSx+cPr4t1uPPV9xhlLrZwm1MzuHiIb2Nfidq0AMYALsQweavZ3iO3fhvE4RLeUxcPPgrxyee/DPH8cfNeYGewLWx3vY8nSSLiq0FcURRFURRFUZTriL5sKIqiKIqiKIrSE/RlQ1EURVEURVGUnnBNng3PccVb1asu1dGDEHVMsWG+gNpMh/SFo5TE7+yFKsS773grxFtuwXgF9GQEddSX9ZdRnzey7xUQN13Ux4uIvPAU6ti6bSyzVsN6zp/HhC5OZCbHy+Wwqad2ogfj1n17IA4dTJrmORWMM6ZOziX9Z+s0JuaKKelTSK+aDcdM6FIYwnqMTa5rJtudzU3qV+obkHJpxRuUUAK+VkpCwoQS83S7l9dy+pRwqUs6zDA0BfMBJenjpE2tFo6TVhP9PmFsllkexD5b7q9AXCljgqFcBrXaUWy2hVioZbcF4zJ5iBZmsYxOG70EcYzjTkTEEqxHHGH795VR57p9G+p52y1T559QErL+8np/9FL6a6/pG+iTbHblPAMaP7UUPfuLTz8N8cWTJyG2aQoukHcmY2ObJr55bW1K7raF/F2DZbxWS5Q4a9eO/UaZpyPUSlcX0R8RZSsQX6RkhK2WOTdUF1E/bNH161DCqWoLk1bZGbyfxI7pUUgyWGaLNPQRjeEilVnqN/s1+wXiZOXcgqvUKr+cjA2NSWY1SVnWw3oVsmZ75AvYN0K6N3lkZOvL4XjbPYVjtEL3dBGRydUkh5coZfEa9BVxbunYWEYmNutdW8Z65Iq4j1fAcTIzh/PT2UWcd0VEDh/D/jczi322toxlBAHGNx6YgLiUMz2OESWx48RtCXn8chksI0pJzGg5OEeEUZj6782gP1eQzOr9pr4wA59dSLmXDY9j/+uncymWK3QA9HQ4Fo6xstn9pL+E+yQ0Z4Z0Tz744iGIR0bQCyEiUiign6dFzwq37cA59vWvxAR87dD00rToUu3ditf64gLOy9Mz6DuaoSS4ZyLzGB3yxOQr6Hms3IzP0K/YfzfEUyfR1yQi8uzDn4Z4bmb9HpYksYjU5WrQXzYURVEURVEURekJ+rKhKIqiKIqiKEpP0JcNRVEURVEURVF6wjV5NvxOV+zVNd0LWdzVypn6ac9GkVpC+sJ8Cff5zu//Tojv+Y43Qdw3jPpREZGLJw5C7NAxq3Vcy3ju1GGIp+umRvK+j38c4lIedZWdLmo5x8dQY99XRp+DiMjJc6i386meg5M7IN53y51YQIR698WqmcujRb6ZpTYew0rwmnXaqLFsJKYGMGmgrvVAZcP+KdaAXvKpT39WcrkV/W/kYe6ApSUzR0NjGdfs5iXJ2cNx8SKWEZGeeXAE1/kXERkYxnW/s6RJbS5WIT5yFPvrxjXTL7F153aIHQ/7X18Zj7lzJ+pLt2wdN8rcuYt0/LQWfpn0x3F/HxZA+vogRSvsuPjdhUPHGNtBXpM+7NNBYo5FluUPDq7XK5uSF6bXFAf6JLea48Wlce4vmJ6T+SM47reWcK6wSF9cp7XVOzRPWHnUv4uIZC28NnMXUev7xKPPQDxWRl3vAuVSEBFZpnXlGyTHbs+zPwWvtZvip8h7OJ465D+Zq2I9IhvPq+CiYJtz2oiI2MZ9iCqeoAa82cTzrNUwFhEZGKpQkavnam1+npfEtiVZPe9cHj2Pnmu2h5fFv3Xq6CkIAhxz/WUc9694BY5ZvoYiIp6H19p12UNG18DGPp7NmI8hpRJ5l2guSWLcx6O+8OIhvM+LiDQpz4FEOF7Zo5chX6Bt43yVWKZPNbaxPWs0juotPHceJ75vzqthF/fxN3gR/WBzfZPjA/1rnjWLPEuLF80cNc88i7mHnnoer8vYFOZSe93rvwXiqRGcLztLphfHoXlBbO6P2Fe2TaIvK5/ivclmsD/1ZXCsSRmPEURYZr1t+rnalNvq4NFTEC91Ma/LHbvQS9IYxfM4eQE9MyIiB0+jH+WZE9j+dfLaDffhed04hs8JIiKv/BbM3fHUI59d+3cUhVKn56yXQn/ZUBRFURRFURSlJ+jLhqIoiqIoiqIoPUFfNhRFURRFURRF6QnX5NmIE1/iZFV/GaNW0ErJQRCSPtYijWsuS/rQO9GnkCWt+otPP2UcY2ka12Lvkr6xvoT65bPHXoS4kZgLN3sRllFyad3wHGq1RwZQV3jhoqmlCykfQ6tO64KfxFwdIi9gPRu4lnHONbWzYRY9BQshtm+e9N4FWrQ676ImVUSk3kJtdrgh70EYb65e9AsPPCruah6CyhbMDZBEpvfhqYe/APH2Lbjm9PAQeh/On8PrxudXGKwYx/Bt7PcXyZvzprtwHetX3HoTxC3qryIitkfazDOnIT5yFPv8c8/juKj0l4wyv+d7vwvi1960D+JMgt87bJlALa1Png3LTtErk+cnEGw/28U4W8H+mE/R4McO5QXY8G/3mmavl4fYsyVe1fMmpMHNOCmaedJUb+vDvD4h+RLqpPF2+vBa2hnTs9G+iL60bhV1zfUFnDvmY6xntWvqoHfccSvEM3OYZ6O6hMcslXBO7KTkTAk8yrfQRX16O8CxZFMfy9G5J5api47Io+FQJ7Fp/fuY/ASzc1WjTE594GZW6sU5djYDP1hvs3oTr5tdLvDm0q7itQ9CrHMhT3kNSO9eXaC+leLZWG5gn2X9ekLX2XPxunq26fdsUY4emkrEb+Pn7CGdmblglNlNsP90HfJokNfEIf8P544JU3LeZCnn0XIH22ZmAXPJJELnnpjzqmXhcfMbztXZZNvQ888+Id7qmEoW8L7UP2Tmq3jiBfQQHCKfwmu/FX25f/bnfwrxO950L8QDOfOEc9SHXQ/HQbuD42RkCJ+T4qzpsV2iHF2MRXN9QN/bW545Tx87jT7b3/83vw/x/Cw+q776NXjub/++/wvi0XGzvYsh9rfJEPvTC1Wc72LyBM7Ss4aIyF7Kh7Vr/41r/w4DX46/+ISxTxr6y4aiKIqiKIqiKD1BXzYURVEURVEURekJ+rKhKIqiKIqiKEpPuEbVcyyX1i2PQ9Qrsk5ORCQisasvqA8b60dt59994pMQD46hb2GUdOQiIn4LNaWeh76DUhF9Cy7pQ4ueucby+Chq+dt11FnmHTzGwhyuMxz4ppehnEN/hE/5FY4+9TjEFw4dgbhLWjzxTJ0rr0tf3EJaxCJeMzuLfoFcbK7xPSBY7wM37Vz7d6sdiMgzslm863t/QPKra8tnR/fCZ6266ZM5+hzWbWIc+49NHoF8DvuKH2Ob77sZjykiMjCB+s/WMPbpt3/HmyFmn0wzxbMRk2w3TFBn2Qlxn1nSep4+OW2UWSjguc2cQw3+qReOQmx38BgnZnAN9bu+/ZXGMbbvmISYc3HYOcq94JHvK6X/CemVM9Z6W2RS9OO9Znm5IZ3V/CzdFo6nom+OyZFxbJOF09iOx06hRnYuwHYfHESPh50zPWbNGOenKMAOFLZQf9zpkvY8JV/E3AzOac0G6p6TAPcpZHH+99tmv7ayOG+GHaxXpojzVRJRv6e8ODEnzhERn+5LWcoBkcnR/aGAnph8wfQ7BXSul+aNJDT19b1mobos3qqHcJLuU+zhEBEJY+pPQ9if6jXcJwwx7pIvIU4ZcoeOnYTYtvC6sZdpG80Tdsn0Cnaa2Ecjqkfo49ycpWOwp0hE5Mh5HGs7RyYgHiyj99IdxDmz2USPx1JoHsOlnCGcN2eJ4pi8clbKI5ln4bzYbF2/PBvzy21xV/17hzzMC+HMLhjbn7mA3plvedMbIP6Xv/T/g/jf/4f/P8Sf+ptPQHzDFPZ5EREvQ889lCsmirCNBvtxDIwMmvnbODdHhrw4toWfN+he56fkvPlPf/gRiF889BzEPFf91Sf+J8Rb9t8C8S170XcpIpLPolekL8F6TdL0FlI9m5E5pyU+ztPbp9bzevlX8LZsRH/ZUBRFURRFURSlJ+jLhqIoiqIoiqIoPUFfNhRFURRFURRF6QnXlmcjtiReFZRnKPdEzjXzbAitk544qMmNfdRAzs+j7r4xh3E+wJwPIiIxrVM9OICavsokrkUc0vrd56dNrX8irNHFZvJD1ME5Fvo+ijnTv8JpSBz+A+mmIx/1oDYJ+Wst1GmLiPhZ1LGWJ/Fcm/kqxPUYdbCdpvnuOdS3C+LhDTrhZtNcZ7yXZD1bsqs5Do4ceh4+qy2nXEfO+0C630YDcwFYFq3rn8XrGrRwzXoRkeU5PMbFM5hn42//7m8hXqpjGcsNU/db7kPNaf8AakyLfahxPncOPRqjw1NGmbk+9JY88Cms1+LRZyGOaGwem7mIx2yabbH3AHpa+vtwHPRTPpp8AfWl/UXTP+XRWveFwvq5+ym5fXpOxxNJVutJctXQyhibN8nGccHCP1ygc2j4dE6U58DxTF1+i3JFJDRXtGm+ShLywXhmvc+TDy0k/4QleIy5JZqPrBTtL2mnvTz6T/pIF82ePx7PToouOi/Yh2zS8nt0rhYdM4nNPsVr6l/Sa3PeqM3g/MyMOKv3VY98e+xjEBHZunUc4ib5d2oN9mxQG5MPsBWac/7BYycgZl/k9FnU7Q8Poq+tv79ilHn06DGI+Z78nf8I8xdlE5wzByqYe0FEJF/DOW2hWoU4prHH7Vtr4HzW7Jq5ZFp0DewMztUdyiVjOfhswXlfRESW6B4xvMH3F6Xk5eglk9t2ibfqc42EcrgEpk8rU0STwMRWvDclNIa2TmIurH/46/8NcX0G+46ISCGPbZzNs68N2yjr4hzBvq2VMvFa8xyZy+AxEvKCzbXN++MLBzHH25vfjDlGbnvFbRD/0X9Fj8cjX8R79q7xinGMTAH77PwMPhc9cxS9wF4Rz2OszywzalOel8z6fBhbV38P1l82FEVRFEVRFEXpCfqyoSiKoiiKoihKT9CXDUVRFEVRFEVReoK+bCiKoiiKoiiK0hOuySBuW9k1c1wuSwYZMRNyFclkUywPQ9wiQ9FQGU04LpXpL6NJVUQktnGfloeGlbGxnRDHZBLefysakkREHv7C5/C4CZroPDI/tslk10dJZUREMpQkxiFjTYOSqJ28gIbLahXbomuZ5rSRffjuOFWhRIIJttXSPNY70zENukVKotNurZuF2u3NTShUX7woYXvlnD7/15+Cz87OnDO2twM06z37LC0wQNcxJCOt0DX67Cc/bxwjQ0kkX3H7HRD7GTQq1rrY5ifOYJI3EZGFhYNYRgfrMT1zCuKTp3D7V95+p1HmT/5/PwDxY196BOJwGRMy1ShZT5sMmiceRyO8iMgDT6ARtOiiIZOTLzmU5K2cYhDfsn0HxO/8nn+y9u9Wa/MNuq7liru6IERAhuVG20xwtFjDPrdICZJCD+eFJMQ26lASMKtrGnQDSvpoc3LPfpyPHIeug2veBijXmGnO5jIotm3TuEo5NCWmP9hGvfC8opgM42nHMOpBSdPYuG7h53Fszmk8LVyaJyL+YBMIk0QuXYqFZTQO99GCCyKmAZyvNS+w0mzj9nzNktg0oZfzWMbsIpbx9HOYTK+Yx2Rw3Q7OE5dqtpEMLRRx8CiWOVbAZ4u0uWR8HLdZOI3mWcvFvjE7h/XcsgXvhRFnXxWRLhnsW7SQRkj7RNSe5T7TrOxTJsXmBiN7sMmLZIQSibX6HXVE9cpkzYVxKKey0R8vzmIbzy/ic8+5GbwvJaHZV/hZNKBEh3yXyNKcW8yafcWhBZDyORxbOVoEKHbwup6ZM59Vhcz87/qu74L4nnvugfjsWXym+atP/A3ETz2z3ThE1MH7w9JFnCP8hfMQuxE+n7RCTDYtInJiCe/1hez6c2QYpI3ddPSXDUVRFEVRFEVReoK+bCiKoiiKoiiK0hP0ZUNRFEVRFEVRlJ5wTZ4Nz7Uks5pIqUWabidXNLaPHdRkt0hD73iopstSohTPwzIzBUwKJiLS34fbzJBWrjWFnozRrXsgPj+LyatERG561Wshbsxh0rQTR16AuNmoQuw6pq61n3TTFmlSL5zHY5w5TUn9sniefWOmPnJkkI5BPhBrEcsYWMLLPzWKyeNERLZUsP2Ovbiuc22nam17x/jomBQKK+ewdwd6cRIxtauujX9zSK/NCb8S1qByn/ZMTfTkJCYpesNb3gJxuUCJ7XKYlOjF558xyjxy7DjE41M7IO6QoN4hb9TzRw4ZZb54BJP5FHYcgHh6Gus1UMF4lJKfFUqcOElkcQZ11AvnMTHX3DyOzU5ESRdTNNAXqthH73nT+jbt9uYmtBIRadabEqwmPKzV0DfVbJjjvtmkMUhV7qvgmM1SgirGYhG9iORdvDYeJRJjP4VHmuU0z0bEiQITVj4n9Dl+6qTU00hcSkn+2DNlJOWkzyNDjW1qrV06Ny4zR1ps1nOLiCTk48iueo3YD7IZVAYHxV29nn1078ul1H2xhp6BPM0VgY/n5lMiRdfDc8xkzQSQfoT3gdlFPGYnxDIGyxWIt+xCL4WISBDgta7VqxCfOoda/8wIJXNMTD9NqUAJHUdxjuvL41hsVNFvder0KYh379tmHMMnXb4fUaI7uk2xp2PboOn3zOew3t32ui4/SjbXN7mwvLg2poIQz81NGQ8J9aennsVkvLfcdid9/hzEAX0f7rvmfccPKFHqBXym63SxnuyfpdyNIsJpAEW8DPYvnkOjhD245r1gcHgM4uEh9ADVyd83PoEJOReXsM///d9/2jhGhxIVLyygB6NJHjWX7jdOSpLIgTFMjD06tl6va/Gt6S8biqIoiqIoiqL0BH3ZUBRFURRFURSlJ+jLhqIoiqIoiqIoPeGaPBujQ7YUcivvJ8ECrn/cjkzNfJNSQSQ26UFJO9fXhxq2jIc6uXaT8iSISJ51qj7Gjz/8MMS79qNu/Nw5XGtbxFwjvkDrMDvkRcnnUTubpt1ut/FvYYjrIZdIO3fP7fsgzlHujtAxtXJRgGtYt8+iVtGuoz55tIBrLN++7yajzNEK6gyfuHBy7d8df3PXmV+aX5JOfsUr9JpX45rU97z+9cb22Szpt8mjwZrrmHSXDq1Bz/pmEZG2j22+cO4kxIvka1mcX4T4BPkzRESmZ7FPlkYncYMsXkcrgzpsPzTzPXz2/gch3r77Foi3DqL3JGfjOCpQPpFuB7XGIiInauhlKlGfjUhHPbOEetLh4R1Gma0Ar8nn739s7d9BYOac6DULi4tr+l3uD52OWR+f8vp4OdL+kh6b5wn2FXEOjdWNIExIdxtG2O62i2XmC6ZPxPCGkNeBPR3G/mxOERHLUEIjrRaOJfZ0uJyTJCXPBteb62F6T6iMlNQtuRzqxNc8Gynn2GsarbY4q30ijnFumRwbNbbPkEejRXlaigXy+bnY5paDDeJlzOtukSejRfmXMnmcr0pDmEsisM37SOji33IVymvg4jiqU/6GvbvMHAThDM43YRPH2nID5+a9e/ZCfO7sUYiD0LwfWPRI1ahhvWL6frdEnj72lYiINJuUK2XDfTsONvceHFmxWKv5pywH69qg8Ssi0m5gm8/M4XPjv/33/wHi08fQ99egOfbYefQtiJheS543Ano2tSLyG6d8585zlUV9OrGw3Y2ZwJhnRPJFPO4CPUNnyRdZW8bn3W4Xj3nqlJlbzKI+SbdPSSg/CNcy45n9r5jF8dpqrh+D2/py6C8biqIoiqIoiqL0BH3ZUBRFURRFURSlJ+jLhqIoiqIoiqIoPeGaPBtbtmSklF/RSvZbqMM8dtbU612cQ0WYH6E2uFTCwzdbmFsiilHvl6atWyQNYL2BurZOgGU6CcblEq61LSJycQa1m+dorfyYNNFjI+g1sWIz/8RSdQnibBHbotKP/okMabW77BcgzaqISLNLa1I3cJtijJ/v2YrrOE+O43mIiJw9hx6Xhbn169wNNneN70IhK4VVb8tCDa/JU88+YWw/Suuoj43ieu5BgNdpaamKBVCeEjfluk7tRD/F1gG8juePXIC42UDd5sY1qy9RGKpA7ORQV91qY70mJnC995lpU8s5v4D9fmISDVUWaUwbXTpXF/trEJvXPkvepSxp2v0F0tva2D/HKJ+IiIhPGvON1UyRxfacIPTX80VQvhM3ZUxmyQ6RzdM68ST2tWhG5hwZcco5RzQfsY7WIU+Hk8HY9sx5NUPnwl4HPobphTDhLsOeqUqlAjGPzy75XyLLPOaVPBqcyyMMqZ9HabmD0s+d67cZ5At5cVdziUTk++um1Mf1OMcKarK5f/H3jzRExfUu79UREenSPGlR7pNCP9ahXjf9X3kaJ3NzeE92XZxnB/JY70LFzFdRyqFHY2wE83bNJ3iPLhTw5EdHL58XQUSEb9NsK+rrr0Bc7sPzrC1XjTLn5zFvRGKva+jDFN9ILxkYHBBvzUuL17VNOR5ERLpF1PvblOehSvfcoRH0HfUPYo6HMGUCjBMcB2GA91jOBRHQc0scmGXy/Nal+1DM8x35Pe2UZ9Uq9ZeHHn4I4m/91m+F+IUXD1KdsDw/pS3YZxpTe7N/JeL7vG+Wefb0WTxGdn3scQ6iy6G/bCiKoiiKoiiK0hP0ZUNRFEVRFEVRlJ6gLxuKoiiKoiiKovSEa/Js9FU8Ka3qGNtz6NEYGE1Z/72Ia/rOX0QtXYc0uG4GdZb0scQpHoGA1kxebqPuskj5Kzot1Lu3O6iHFBHx6ThRwPpkPFdeS7uPdJgrf0N9aLuN+8wvYL1LJdS/G+vHh6a2LuPSevA5+py02jv27MA6tcwyv/jFFyF+9sjs2r/DlNwqvSTrxpJd1Qx3O1X47OGHP2dsnwR4rfsK2D4BrVHeoRwHLr2Lb9+x1TjGza+5EeLd29DDUT2L/omZJexvmbyZ42D3EPo45ubQu3TL/pshvumW/RD/xZ99zCjTFdRJB+RD8n2ME9YC57CtHDYjiMiOnbsgnj17GDcg70CefEsHDmBuGRGRTgvPfevEuqa32+3w5j1ncHBQMqvroduCmu4oMsdPEJJGlnwGnQ72Ocuh9d1Jcxun5LfwaRw6ccpcvPFzwweSMq9Sva+UI4NTTsQpemLWl8fUXg5p+9lfEXAcmzkGbDq3K3k4uC3slEQbrN++dA3C6+DZyOUza54N26IcLb6ZXydLfSGfxX0swTbMkMdDqD/29Q8ax+jU0A/mu3Rfz2JfatNc4zjm2v4kuxe/jdflAt23B6cwT1BwYVaYPI29XBnPdaQf/QLzC2fwGP3kA2FDi4g0KMfR/gm8H8T07NBqYR9qNc0+NUg+j423rTDc3FwvkcRiy8r15LnIzZrXMZvFZ0DOrTYwgD5K4TmC5hEe3yIiIeW6iiPydtH8yPVOs5uF9GzQaOJ9qNvF68w5n6IULw3v88lPfQri51/EZ63Hn3gSYov6W5QyJ4fsrSMvSULzekw5mNKytnBup1yy3keT5OqfAfWXDUVRFEVRFEVReoK+bCiKoiiKoiiK0hP0ZUNRFEVRFEVRlJ5wTZ4NJ+eKm1vZJdeH+rzBkvne4rZRo+blUd9VW6LDR1hGPocayihlje+oW4U4U8AyPZfXFUcNYTdFc+YHvLY/6ah5iWXSoEYpUnKP1+DPoF69uoSejbaP2s1+Wjfctc32tulcW6TAuziP65kvUU6SehO1tyIi/3DfISxjgzwyTZfdS1qd9npeAjr/t3zH243tYx/X/XZIhxmTljMhPahD7ZkjD5KIyEwVNff16hGIF9t4TCuHRprDT58wylx4BPNR7NqJnoxX7dkLsU95N/IZ00+RkL6cc3XYDo6bmOSgbdbnRqa6c/sW9Gx0GpgD58Y+9CE99sRTEE+fJo+HiLSbeA2T1vo44XG6GZTLZcmu+lXiiBopMcdkl8ZxjTwonAfBoZj9ApKyrLlHYyGMWZdLOmj2aFhmva2ETRiXH+u87jyPLRGRhL7bimnu9dt4PTmPRcx+Ck5iIJwRI0WfTVsUaDxmXFMTbpPv45LuPEjRj/eajGOLu5qDqVDA+cjoKyLiUIdxHM7Jgm0cUu6OhPI91evmObcpfwAfM5fDucWneThom3NJaxmfHdiPWB6s4A405wUtnJdFRJwMXvsMeQwSD+vJOTCy1DcqlANCRCSpYT4Qy8a26NRxPmu3qK0K5j2GfUcbTQbsO+w1luWIZa20g0f5edhvJiIiNEeu5+hYhZ+l6FyzPMa4LUQkQ4+RluCYZv9FxL63FNMGe0OGhtGrxO3O3gX2iYiIxJSTotlEr8nMRcxptmPHTojrTb6Hm32cG/SKHg5qizRPDOdDsjfMu3EcS7u+xLukor9sKIqiKIqiKIrSE/RlQ1EURVEURVGUnqAvG4qiKIqiKIqi9AR92VAURVEURVEUpSdck0G82XDFilcNPk4JPisVTVe0l0dzSpGyzPX3ozmlUWtTjIaZRisl+VQH/1bODEGcI0NSSIlVXNd838rQn7wsJ4rCDQolbEY7pVVDMtRm8rhRXwWNYYuLaOauk7GnbxDPU0SkRea+o6fQoHvoubMQjw2i6Xxsi2lOExuPO9xfXvt3FMdyemnzEqsVi54UCiumvn7ydJVHzIRwnEQnR+/WGUqKleTJEFjAz+MOmntFROp1MkcWsE1Hd1cg3l3AZFRHTx43yhQL+5tXQPPj+QuYbGpoeOCysYiI30ZjYreLiwE0Kclfl4zMQRfNbG7O7Ctjk2iYPH0Bx+/FM3iunQbW4fgLTxtlDg1hmcnAulEvCTY3qaSIiCW2WKv9yKKVInzORCYinS7OaZz8iQ15vPBDQkZDPzQNoV1KIGWRcZoTgrLhmQ2AIiIxJQ1lCyXbNPlKsNFTxDRmJhaZE10ykzpm0jTcP+VvbIikxIGGz53mVTvFLM/bhKtJXqPrkNSv4GXFW11EwKWrkPbNYY4M8I0GjmtOapihZJ15WhSDPxcRydOB28tViMdGt0HcIQN5pUjZZ0XEG6G5mTpYIDjW+P6ap6S4IiIezefciQPqs8Mj+IyTifGe7fCiLyKSpWecJMF6FgpYZp7rlGLQbZMReGMcpCQ67iVJ4qwlNU5oFZG0xJ9msk+8kIZh3L18Uk6eu9L2cWg+82jQ88ITaQsr8KkkVIZj0XMl9b+0tSN4IY98uQLx1DZ63qBjtn2sZ9riANy+Fi3wwPMjb8/zgYjZPhufq8IwlAtnTxv7pKG/bCiKoiiKoiiK0hP0ZUNRFEVRFEVRlJ6gLxuKoiiKoiiKovSEa/JsTJ8VKaxKErtV1CaWR0z9WC5PielQriiDg3j4BiU5qVYxXlogfaOILKEtQZwYNWecbMrQ58WmXo/fwFgD7bhY7zYlI0xS8ux4MSVPamHyn6iN5xqRHrTawM/9FJnhInleTh3DxqkuoG7fb2Ih4/3jRpkHtk9BvPEQQRTLk6cWZbNoNY6JRKv9LiZdplUytr94ET0BR188BXGOEkVl+isQD4+i92FyuN84Bmvsh/rRS8O5fTptTIAzOooeDxGRqUlMIHRhZgbiI0cOQrzDx+Q/7FUREanXsS1aLfRT1JbRe8KejcjHvuVkTU30C88PQ+x30Z8wOjoG8dStN+PnI/i5iMjwCPbJ3Ibjdrqb5xe6RBzHazrXbpeT0JlJBn1K+MltwgnOONEd66DTNLU50tHbpGGOQk5AdXndroiIZZN2mv0B1O8zV5HgrtPBtgipXqy15nPleqf18xYlc2PNN3sY+Jihb5bJPo5cbqW9rZSEsL3Gk0S81Xaw2QfomLfzK103vvYZ9jjSNYrjlPs8ldlfxrmYcy/mMugDiVNuZoUSbhPQuOnQ/ZJ9SwXO9CYiHiX+a7awjFwZ5+K2j+fapjp4ienZcGjc2A72N3pUkFYb279aNROk8TXIZNafg9g31muCTiRJdMmzRnNTylfX7FMwPAL0LGXR3MVJOI3EnmJ6aG3yU3h5jBMHn8WyaRU3j4Jl0FzE1yjwzXsBz+28T8vnxICUEDLEehvJHkVEKLFiQmVwEr+NfUlkPWHp5diYTDS8Bt+a/rKhKIqiKIqiKEpP0JcNRVEURVEURVF6gr5sKIqiKIqiKIrSE67JsxF5QxJ5K7rHIPNK+Kwbp2hdQ8wpkOtHPVllBPWMAzZq2AZbpGdcRI29iEh1HjV+7SaeUhSSzyMhDWFo6m47bdQWs67NIV1hvYNltBspOUcS1PCV7TLEsY2a+SDA88gWUSOY88z1zisZPMYuqUB8y22os99/620Q79izxyjzrtegrvXc9LqWv+uHIk+eMvbpFYnflUuWHJvek93A1Iz3eXhdnvjS/RDPXMT+aVGb3nXXnRDfezf2eRGR5WX0Qjz75KMQN0mnfuQM5jo5ceqUUWabtMQJJRTI9WHuiVqNcrIs4XmJiDRrqAVmtadLWs/+MmqmJ3eiL2RgaMI4xugk+ismb78F4sE+7H+s80/zI3DOkY3j101Z577XhEG4pntnjwZrcEVEhLS9hibW8EYg3CZpOTESEsUHVA8+JmuBrRQdtEM5Lmyup3V5DTNrg0XMeZTP5UqeDl6TP62/cJl8rob+PYdjvpA188fwNbl07mnXotfkPFcy3sr15HNLUvyHfB37+tCXYKzLT9eVPQRJimejn/ITlcgvkZCPst2l/mckPxGJA5zDykX0gVB3Ez7zZor3xguwLdptytVho99nfhnn1cYC3qMrFfSoiYgsNLG9cpSEJEmwbZYWca6v09wvIpKn9t0Yh+Fm59mwNtyPsK9EaXWx8G9Z8peZOS8w9jJ4zdL8Za7gNhH54ChlkOlZS5n/bM5VROOCcxdxLjbHM/3FXAaPXz63gDwaNo29OCU/SEh/c+jZIb6Cf4/jNDbOe9wOl93vqrdUFEVRFEVRFEW5BvRlQ1EURVEURVGUnnBVMqpLP620OuuygXYHJQSWZy6Bxcvk2S38Scdt0j42/gTUpGXhmm3zGC2WMHXoJzLjV9+rkFF16ac9+inKoZ+q2l08Zsc365kk+DeXJGMdWmavy/WmJe6cxJQQdOnnQ59+1vTo8xZdw0bTlH+1qS26G+p56XhX89PbV8Ol8tud9Z+9A7qOYUp7dDr4M3lEP1Pyssi8lCXLUTopS23y8qddWvLOp75gLiVp9j+WoLCMKia5RCyXX95upYzLXyP+mOt1JTmKiCkr4qVJO11altr+6mRUl5a+7XX/23gMf8P19f0ry6gCuv4B/aYfch+k/WNaOzldRkXHpHFv/Hwfc39JkbFEvGTq5cu8GhlVxMuQU3tdaRlFbhtjGXNJGV/cb3mp2wDjIG1pTY5Xz/2SBGQz+18QrJ9PRH0jrRYxzfk0lRjjnPsX96U0qZYf4N98i/sO1synDpsmo7Kool0aR7xktNAywLYhrMJ710oZNI9e4XNuC6MOKds4ActU8LxYBsXXNG2bjfGlf2/WPTjcIO0xpEWJ2eYJPbdw/2IZDi8NzPDysSLm8rgS09xk3E8vX6eVv9FAoeV1jXM3xlXaEr10H7+SjIokZQHf91PmP0OaRf0t+QpkVDxPb7xml/rD1fQ/K7mKrc6dOydbt269YmHKNydnz56VLVu29Kx87X/K5eh1/xPRPqi8NNr/lOuN3oOV68nV9L+retmI41imp6elXC6nJxJRvilJkkTq9bpMTk721Cyp/U9JY7P6n4j2QcVE+59yvdF7sHI9uZb+d1UvG4qiKIqiKIqiKNeKGsQVRVEURVEURekJ+rKhKIqiKIqiKEpP0JcNRVEURVEURVF6wjf9y0aSJPKjP/qjMjg4KJZlydNPP329q6QoLwunTp3SPq1cN7T/KV8Jb3jDG+T973//9a6GovSEP/mTP5FKpXLZbX71V39VXvGKV6zF73nPe+Rd73pXT+vVa77pXzY+85nPyJ/8yZ/IJz/5Sblw4YLcfPPN17tKyjc4ejNVrifa/xRF+Wbhah7uv9b44Ac/KJ/73OeudzVeVq4qqd83MsePH5eJiQm55557Uj/3fV8ymcwm10r5ZiZJEomiSFz3m354KtcB7X/KNzJ6T1e+1imVSlIqla53NV5Wvql/2XjPe94jP/ETPyFnzpwRy7Jkx44d8oY3vEHe9773yfvf/34ZHh6Wt7zlLSIicv/998tdd90l2WxWJiYm5Bd+4RcgW229Xpcf/MEflGKxKBMTE/L7v//7+g2iYvCe97xH7r//fvmDP/gDsSxLLMuSP/mTPxHLsuRv//Zv5c4775RsNisPPvhg6k+n73//++UNb3jDWhzHsfz2b/+27NmzR7LZrGzbtk1+8zd/M/XYURTJP//n/1xuuOEGOXPmTA/PUvlaRfuf8rVEs9mUd7/73VIqlWRiYkJ+7/d+Dz7vdrvywQ9+UKampqRYLMqrX/1que+++2CbBx98UF73utdJPp+XrVu3yk/+5E9Ks9lc+3zHjh3y67/+6/Lud79b+vr65Ed/9Ec349SUl4nPfOYzcu+990qlUpGhoSF5+9vfLsePHxcRkfvuu08sy5Jqtbq2/dNPPy2WZcmpU6fkvvvuk3/2z/6ZLC8vr813v/qrvyoiIktLS/Lud79bBgYGpFAoyHd8x3fI0aNH18q59IvIJz/5Sdm/f78UCgX53u/9Xmm1WvLRj35UduzYIQMDA/KTP/mTkLn7SuVe4uMf/7js3btXcrmcvOUtb5GzZ8+ufcYyKiaOY/nwhz8sO3fulHw+L7fddpv8r//1v77CFt4cvqlfNv7gD/5Afu3Xfk22bNkiFy5ckC9/+csiIvLRj35UMpmMPPTQQ/KHf/iHcv78eXnb294mr3rVq+SZZ56R//Sf/pP88R//sfzGb/zGWlkf+MAH5KGHHpJPfOIT8tnPflYeeOABefLJJ6/XqSlfo/zBH/yB3H333fIjP/IjcuHCBblw4cJaZtZf+IVfkN/6rd+SgwcPyq233npV5f3iL/6i/NZv/ZZ86EMfkhdffFH+23/7bzI2NmZs1+125fu+7/vk6aeflgceeEC2bdv2sp6X8vWB9j/la4mf/dmflfvvv1/++q//Wv7+7/9e7rvvPrhvvu9975NHHnlE/uIv/kKeffZZ+b7v+z5561vfuvbwdvz4cXnrW98q3/M93yPPPvus/OVf/qU8+OCD8r73vQ+O87u/+7ty2223yVNPPSUf+tCHNvUcla+OZrMpH/jAB+Txxx+Xz33uc2LbtnzXd32XxHF8xX3vuece+bf/9t9KX1/f2nz3wQ9+UERWvnh5/PHH5ROf+IQ88sgjkiSJvO1tb5MgCNb2b7Va8u/+3b+Tv/iLv5DPfOYzct9998l3fdd3yac//Wn59Kc/LX/6p38q//k//2d40L/acn/zN39TPvaxj8lDDz0k1WpV/sk/+SdX3SYf/vCH5WMf+5j84R/+obzwwgvy0z/90/JDP/RDcv/99191GZtO8k3O7//+7yfbt29fi1//+tcnt99+O2zzL//lv0z279+fxHG89rf/+B//Y1IqlZIoipJarZZ4npf8z//5P9c+r1arSaFQSH7qp36q16egfJ3x+te/HvrFF77whUREko9//OOw3Q//8A8n73znO+FvP/VTP5W8/vWvT5IkSWq1WpLNZpM/+qM/Sj3OyZMnExFJHnjggeRNb3pTcu+99ybVavXlPBXl6xDtf8rXAvV6PclkMsn/+B//Y+1vCwsLST6fT37qp34qOX36dOI4TnL+/HnY701velPyi7/4i0mSJMl73/ve5Ed/9Efh8wceeCCxbTtpt9tJkiTJ9u3bk3e96109Phtls5ibm0tEJHnuuefW5q6lpaW1z5966qlERJKTJ08mSZIkH/nIR5L+/n4o48iRI4mIJA899NDa3+bn55N8Pr/WHz/ykY8kIpIcO3ZsbZsf+7EfSwqFQlKv19f+9pa3vCX5sR/7sWsu90tf+tLaNgcPHkxEJHn00UeTJEmSX/mVX0luu+22tc83zsWdTicpFArJww8/DOf03ve+N/mBH/iBq2nC64KKclO48847IT548KDcfffdYlnW2t9e+9rXSqPRkHPnzsnS0pIEQSB33XXX2uf9/f2yf//+Tauz8vXPK1/5ymva/uDBg9LtduVNb3rTZbf7gR/4AdmyZYt8/vOfl3w+/9VUUfkGRvufspkcP35cfN+XV7/61Wt/GxwcXLtvPvfccxJFkezbtw/263a7MjQ0JCIizzzzjDz77LPy53/+52ufJ0kicRzLyZMn5cCBAyJy7X1b+drh6NGj8su//Mvy6KOPyvz8/NovGmfOnJFCofAVlXnw4EFxXRf63tDQkOzfv18OHjy49rdCoSC7d+9ei8fGxmTHjh3gpxgbG5PZ2dlrKtd1XXnVq161Ft9www1SqVTk4MGD8ByZxrFjx6TVasm3fdu3wd9935fbb7/9aptg09GXjRSKxeL1roLyTQj3O9u2JUkS+NvGn2Kv9sHtbW97m/zZn/2ZPPLII/LGN77xq6+o8g2J9j/la4lGoyGO48gTTzwhjuPAZ5ce9hqNhvzYj/2Y/ORP/qSx/0apnt7Tv355xzveIdu3b5c/+qM/ksnJSYnjWG6++WbxfX+tH2ycpzbOUV8tnudBbFlW6t+uRtL1ctFoNERE5FOf+pRMTU3BZ9lsdtPqca18U3s2rpYDBw6sae8u8dBDD0m5XJYtW7bIrl27xPO8Nc+HiMjy8rIcOXLkelRX+Ronk8mAoeylGBkZkQsXLsDfNuYs2Lt3r+Tz+Ssukfd//9//t/zWb/2WfOd3fufXtqZT2RS0/ylfC+zevVs8z5NHH3107W9LS0tr983bb79doiiS2dlZ2bNnD/w3Pj4uIiJ33HGHvPjii8bne/bs0RWnvgFYWFiQw4cPyy/90i/Jm970Jjlw4IAsLS2tfT4yMiIiAvMU5/VJm+8OHDggYRhC37t0rBtvvPErru/VlhuGoTz++ONr8eHDh6Vara79Enc5brzxRslms3LmzBmjz1/y330toi8bV8G/+Bf/Qs6ePSs/8RM/IYcOHZK//uu/ll/5lV+RD3zgA2LbtpTLZfnhH/5h+dmf/Vn5whe+IC+88IK8973vFdu2QXqlKCIrq6M8+uijcurUKfhZmHnjG98ojz/+uHzsYx+To0ePyq/8yq/I888/v/Z5LpeTn//5n5ef+7mfk4997GNy/Phx+dKXviR//Md/bJT1Ez/xE/Ibv/Eb8va3v10efPDBnp2b8rWP9j/la4FSqSTvfe975Wd/9mfl85//vDz//PPynve8R2x75bFk37598oM/+IPy7ne/W/7P//k/cvLkSXnsscfkwx/+sHzqU58SEZGf//mfl4cfflje9773ydNPPy1Hjx6Vv/7rvzYM4srXJwMDAzI0NCT/5b/8Fzl27Jh8/vOflw984ANrn196wP7VX/1VOXr0qHzqU58yVjTbsWOHNBoN+dznPifz8/PSarVk79698s53vlN+5Ed+RB588EF55pln5Id+6IdkampK3vnOd37F9b3acj3Pk5/4iZ+QRx99VJ544gl5z3veI695zWuuKKESESmXy/LBD35Qfvqnf1o++tGPyvHjx+XJJ5+Uf//v/7189KMf/Yrr3mv0ZeMqmJqakk9/+tPy2GOPyW233SY//uM/Lu9973vll37pl9a2+Tf/5t/I3XffLW9/+9vlzW9+s7z2ta+VAwcOSC6Xu441V74W+eAHPyiO48iNN94oIyMjL7kM6Fve8hb50Ic+JD/3cz8nr3rVq6Rer8u73/1u2OZDH/qQ/MzP/Iz88i//shw4cEC+//u/f00/yrz//e+Xf/Wv/pW87W1vk4cffvhlPy/l6wPtf8rXCr/zO78jr3vd6+Qd73iHvPnNb5Z7770XPJMf+chH5N3vfrf8zM/8jOzfv1/e9a53yZe//OU1idStt94q999/vxw5ckRe97rXye233y6//Mu/LJOTk9frlJSXEdu25S/+4i/kiSeekJtvvll++qd/Wn7nd35n7XPP8+S///f/LocOHZJbb71V/vW//tewSqjIyopUP/7jPy7f//3fLyMjI/Lbv/3bIrLSt+688055+9vfLnfffbckSSKf/vSnDZnUtXI15RYKBfn5n/95+af/9J/Ka1/7WimVSvKXf/mXV32MX//1X5cPfehD8uEPf1gOHDggb33rW+VTn/qU7Ny586uqey+xEhblKi8LzWZTpqam5Pd+7/fkve997/WujqIoiqIoiqJsOmoQf5l46qmn5NChQ3LXXXfJ8vKy/Nqv/ZqIyFf1k5yiKIqiKIqifD2jLxsvI7/7u78rhw8flkwmI3feeac88MADMjw8fL2rpSiKoiiKoijXBZVRKYqiKIqiKIrSE9QgriiKoiiKoihKT9CXDUVRFEVRFEVReoK+bCiKoiiKoiiK0hP0ZUNRFEVRFEVRlJ6gLxuKoiiKoiiKovSEq1r6No5jmZ6elnK5LJZl9bpOytcJSZJIvV6XyclJse3evbdq/1PS2Kz+J6J9UDHR/qdcb/QerFxPrqX/XdXLxvT0tGzduvVlqZzyjcfZs2dly5YtPStf+59yOXrd/0S0DyovjfY/5Xqj92DlenI1/e+qXjbK5bKIiPzeP/0ByWcyIiLSbvmwjeOYbzXWlnGIl/M5iG/qy0B87oVnIf7bxzBe7obGMRwH37L5rdvL4jEHhocgLufMeu/egon47n3NnRBHQQDxQq0JsVuuGGUeOXEG4vseeAw3cLEeWQ/jPteDOONGxjF8qlcY0jcQSYzHcLIQtxO8piIiSx1Mw2JvOEQYRfK5J55e6x+94lL5f/C3b5N8caUdHv3iLGxTyu4z9isUsF6ehd29WMA2HerD/lopTGHc12ccY2bhHMSn5p/Duk9i3xicwNjLto0y281liHM5rKdjVSCOIxwXUdQwyqz0TUKczeSxTMF9anXsC4uzDsTdZr9xjFa3CHEi2HeqSzMQt9t4jHoDz3ulDOzn1aX1egbdSP7q3zzZ8/4nst4Hx7fvWvsGx07ouuQdY7+pvdin+EvBMycvQBzH2EdLfSWKcT4TESllcK4YGx+DeLmB13ZxuQrxwCDOiSIiQRX7ZWN2EeJKGes1thX7VzPsGGXWFrGMRqMFsUO3o6CL175Wr0Gcr5htEdBYCGhOjBIsM4kxzrjmLTGfw+P4/kq/jaJIDj1xcFP738//+cOSLay0fUR1j1JSZnkUZ6gDWg7eg/0YP28EeB1TbvMiHbyO5TzeV8oljEO6jTcCc9zYVM+A5oE4ofNIev9tO6ckSyRO24i24WtyhXpeTdazDW3TbTXk9999z6bdg3/qp35MstmVPrN88SJs022ZY97NFPAP9O33zl07Id6xE2Nuz+np88YxDj/5JMSnT52CmLq0WB6O8Wwe74UiIv0lbM8y3fv7+vD+Vxmo0OcDRpn5Em5TLmGZuSLWI1fAtsvmMHYyZr1j6l/cQ5Mr/fgVmR0wibEUa8Mk0Gw25B1veeNV9b+retm49ACfz2TWXjYE53Bx3JSXjSxOMl2atIt5nOjyGZwaPQcnIdcxBze/5PDLhktleHQzyXhmvXNZrEepgPUOaXJsBzh7ennzJpijtuB68MuGR3GGBkjGTZu06MWAJzZ62cg4WGaYmO3ruVRmymTY659V1/pf0ZNCaeXaZHI0YeQyxn45uunxy0aeXjYKNNiLNNiLJXyYFhEpdGiCaOEx80UcKIUyxl7WfIG2bKyn+bKBcRxh+0eROayLZWyfLPVHV/DBP6K+1GlhmbaY7Z24WCbfaDtd3Cemz7sRPxqJJNSHvbZ5bpvxs/6lY9i2Lba9Mv7tBOcB2zEfmlwat1xVYx8LY4fmCS5v5W+4TyaD7ezRvMpl8OciIomH/dKlenj85Qcd07fNucT1qB5UJr9sJNSvHefybSMiElvYp2Ke0yjkZ1THNa8h/82JMd7M/pctlCRXXLmxGy8bccr8TXGGHvb4ZcOmJ7PAp2uU9rBCZeYKPAfS/ZOmPL6fipgvG87X6ctGbLwAfvUvG2n9bbPuwdlsZu3ekaV5IwnML0BdmheMvkLPhAW653J78ou/iEjGu/xzY0R91nYv/0yYVmY2w/dPjHM56vMpz4AFeqnhc80XMeaXjVwenz8262UjpnnFTvth4Sr6nxrEFUVRFEVRFEXpCVf1y8YlqtOnpbP6rZgb4dsOfwMuInI+6UJ8tI3f6t56YBfEsY/bjw2jnClP+6+Ax+U3rFYXy1xeXIK4YZlv490OSghuu+PVEAf0c+H8ApY5lkt54/RJApClb0DoHXSUZAo379oD8dys+XNiu12HuEHyCbHpbd3Fr5gmx01pTJAZhfjYi6fWPws3913Vya78JyJSHMZze/aJh43tt47fAXGZfrno+PQLVR2vSbuCfSm0UC4gIjIwiUNo71aM2zn8qbkeVyGOa+YvBNmI5EjUV4II6+E62FcG+3DciIgUMlRGE3/2rDUnsJ4L2F/PHDkNsZNN+VbPw/F57jzKpsolPNdGHcdeGJptweN745cs8dVIDl5mkiCRZPXnPf5muR2Z89PMBZwbRofx2uboF0zbwj7q0bfo3aWUPjiC34BtGUNZVDGPfbJVQzmTdE3Z3YEDKCEcv+cGiEv0q2GWpDLd2JRkdruo6a1Vcb7iXx7npucgPnmafpkdNGWNTo6+1bSwHnmSoeXoG8pyzvz1kr/5jFc7XrfjywuPPW9s30sSx5PEWZnH+VvMtK8O2yQ97tCvRRkaRJZNygD6ldWKzV9i+cD8q0OzQ1IsC9vcss1f1thsavxKT9OPdaVfDL4CeHrh5nVs85g2/QIT0Lf9Qcq0Cce8mtPY+Ixjbe49uDI0IbnVb+1HhlCuuW3LdmP7gUG8F/n0q7zlYl/gX4869Cy2f3yHcYzdN9wK8YkjRyBeXsL5rkpyzjOnTxplnj2Df2MhCatwIh/nZS/lF9JcDqVVLkn8c2Wce/L0DFgZGsF4EKWrIiL9FTxGqR/nyDLFeZKLOVn6ZUlSfl3f8MuR7Vz9uNNfNhRFURRFURRF6Qn6sqEoiqIoiqIoSk/Qlw1FURRFURRFUXrCNXk2TnczklldMabVxmUqM5a57JlE6AGwSas5fxr17E9M4zKih2ZR75ykLH3LHg1e3SAIyZPBqyGQ9lhEpNpGYeVjzx2FeGIIz6vLS8ymLCmRpZb2vMtrUPfv3g3xjm2oh6yUTW3dzIVTWCQtW1gaQF1+5NHqCFlTuz05jLrBs876ca0kTb/bOy7MLUpudVWkyZ2oTXQcc+m1wdIu+gtq6s+fPAHxyfO4DOnUJOowm4l5jAEX+2jYdwhiu7QAcTdArWe9arbhoIvXNkN+i75+vCblPGrhu4HpHfBD9GBIiB1u+SLqQZdOYIc98vjTEBe3mvWe2oP+nlwRz5WXLu12qAzL1G7PL6Bu39/Qp3lp1M0gm3HXVqPi1ZKilJU8JETt7ugAapg7i9jH2g1sk5xz+RVMREQO7Ec/1959OyBebpA3gpf7Tlli7sZbsIydO1Af7HdxCefExnrbpmTZWI0q9knP3kR/hd/EZYNf0zkAseWZK77YBfJsZAL6nLaneTiT0gd5ZaRLuvJWoyP/4ZeNzXtKEMbirI7dhPpbmnrapgsR0LiPY2ofvnfxyjORaTrIZGhpW1pSvUWrNeZpBUjbNcvkVeiEVsRhbb959imtcSWPF11nXoWHnzXsFL+EuWIVxVeog3lel98miTb3Hrxn7z4pFFe8BUcP43PR/HLd2L5QxmelbB7HV6eDzxy8ql3so2ej2TU9ayOj+Fxz99QOiM+fOQVxi5b+vvu19xplXriIntiMh326Ql6H55/9MsT3f+7TRpnRLD5v2OT5SXgFNvKTcds4vKaviHi0jUurTvKKm/3kuykPmrkyBgYGIR4aWvcEttvm0v0vhf6yoSiKoiiKoihKT9CXDUVRFEVRFEVReoK+bCiKoiiKoiiK0hOuybPRdiyJVtfVXbRRb2tFXWP7IVqft0Qp3DtN9H1U61hGrYN60sQ2NdpRhH9zaB+X36cC1EQ2fbPeJdJNPvbMsxDv24Ma6Rt2b8NjZkxd9Y4d6MFoxqhdvHgBtem1OmnhaP33V34Lri0tIvL0l++HuE2pWusB1muhiddjsG36bqYc1GF2Gus6wcDwqvSWY8caksmvaJB37EKPwc7924ztTxw9BnGzhfrQIvle6uRDev7wcxCXJvcaxxgqo848pMzJ506gZ0MSPOZAxlwrOxHS7WfwXAf7UWfZWEad5qGDpo53oIj693IfjotgCLXdzfO4/czFCsQ7t5ii/EIJywxjPFef9LluBrdfWjQ1v60m9smNCbajzbdsSKHfXctk7cZY/3JkegjytJY6pX2Qgoufdzroa2k15iFOCub3Q7PTWMZTlIelQ3Pc0Ch6aya24LUWEZmYpBxHFTwGZ0QhebHkMmb/YI9B0KS5N4+FdKl/JF3KZBul3L6yOCflR1EzHuYpaz1dkMQyNfOs3V/LSm5fh+/qkmRNs381+n7Gsq7gfaDsy/x5WqbgoIv3qoxgm2aoj5uuGJOATIyGQ+NKt560pvkqs2xzPwhS2p+PEBspmy+faONqMjHDUTche/1GKuWyFFc9G7v24P3w3NnTxvaLi+jL7WMPB+UkyzjYpkWaA9odM38Pe+c4Q31/Pz7n+NRfw8gscyt5ZvO5CsSlAsbDW3dC3ErpG3//V38JsRPiNhmHMqFTrqK4jbGdktepQz6QmPrHHI+rY+i7ESclzwb5vrIbfCDhNdyE9ZcNRVEURVEURVF6gr5sKIqiKIqiKIrSE/RlQ1EURVEURVGUnqAvG4qiKIqiKIqi9IRrMohnrSXJWCu7TBTQhVNJsX0NDqD552SCBtBiHs0qWTLnFSysXlA0E/AFIZpkOl00HUb0PpWnpFiZrFnv8a2YJGZyy1aI5xtoWp2poeHo1a++yyhz8eIMxN/9Pa+F+NOf/DuIH3n4SxBvu/kOiN94653GMY6fpyR1D2GimWUfE9E0KMHTgVfhMURE2gEmrRseXjf7+YFprOol585Fcim3TiLY5rWhs8b2vo2G78jFvlKhZDV796PJ6+Is7t8MTAP9sy+gATykRQwqw2QqpzHgZc0yBwaxXqUCmnXrNTR9zV/EPh/75rDO9eG1r/lomnuugwkQu4NDENujaP4r5Mj4LiJL1UWIL0zjuYaUlDPo4rk3mpR4UETCkM3y63NA7GyuOVJEZNsNo+JlVto328HxE9ZNU+D581WIDz+L7WYneK26NTR3WyH2c7trGkxPPo799EwGywwT3Gd4DA3iSykG8WKMC1CM9mFCvfEJ3KeQxXPnuVxExKdFLxo+Xlu/hvNJ4xQtmkFJXv26OXbalLhzeB/O3Tbdk3KjmCDTqpjGdotMl96qYdK7DgbxQJK1xHsWm7dTtue/cYLCgBLuOWQQt+gcIzENoZz3r0CJEimPmIQt7ONdzrQoIl1JyQq5sV4UJwmPi8vv/3KQZtDnv3wlJv4rY73Ev3vP4Reek3x+5YL2DeE8knfN8bC0MAtxm0zOo+NTuAPdPwMy2Pthiik/xr/ZFHsezocDA30QP/TQF4wyy5Ts+cab8JmuS0Zqyk8qfSPmnBq4OBCWlnA+K1ByywIZxrO04JLlms/D3DrUFJJQdzHGjW8u0sJ9uN5aj6P48gsebER/2VAURVEURVEUpSfoy4aiKIqiKIqiKD1BXzYURVEURVEURekJ1+TZ8AquZFb1b7vKqNfbmZhF9WcoydXyOQgLFdScNTOo5Yw9FMK98hWmp2CMElSdOIaJ3M6eOQ+xTTq4JDR1vznSDd79ajzuHFZTHrv/PogPHzYTzEVt2qmImvkqJbhqBPgeeOwCar2bsalJbYa4z2wVy+zmUJ+8dzvq9CtjZoK5uQU87hvfeNPav1vttvzxpz5m7NMroq4n1qoWtzqL2s+gtWRsny2i1nBgHL0QSRb1yqN7sH1qMSaha7RNj0pesMyFBexP5QwmMZrcUoE4ENS0iogsx1hGcxETu+UcLLNB+R/LfaaWM8xg+8w2cdx8+q8ogVAyDfHuDG7vJGb/m59Gz4XfwfZ3XBSMdgJK2pmSoKpESaCsjaJT20xe2Gve/Pa7JV9Ymdeap/DaPfK3XzK2d7pNiFs1nFuiiDxlpLrtL+B8VfRMzfwQ6YcrBWwzcelaBRjb502vzNOffAji00+/CPEbvv0eiG++YQfV0+wfmWW8XtY8nsvCGfT8dA5dgLg5gx6ODiXnEhGZrlUhPn0UvVzuELZNYRvOwzd+2y1GmV4Bx1MQreiUgxT/TK9JrHXdNVlJxEnR77NG27bsy36eUP9zSe9upxzDoURsQYTXudNAHXhjGq/r8L6bjTID+h6U7IUSkxidz8OKU9qC9Ou8xbXmCUz1bFzJo/EVWThYeL8hNrwqvWVpeV7a3ZX57/mnH4XPPL5IIjK+czvEPm1TKGGy4kIB/bLJFfqBiEirjf3L5umOkpoeeuYJiJ+87++NMi8lLrzExAjWa2wrJSOkcXLLjbcZZbr/17+A+DwlQVyu4n2+XsP5sEFzW7OJ9xYRkXYb58SA77HUlyyaDzLkKxERyXh4Dyps8D2HUSRyepF3SUV/2VAURVEURVEUpSfoy4aiKIqiKIqiKD1BXzYURVEURVEURekJ1+TZaPqeBKvejH4HNW3BvKmZP1tFv8S9t90AcdtHzdkU6fFyBdSXvaaCxxQRuXEEcxC0SMs5n0W9bWsZ6xmlpIpwaa3h7WdOQpyvoiZ1cKQCcfD8U0aZ7BV55MWDEB+eRo18J0Sd4fkz6HeZXUD9sojIXbe/BuLtFVxj/t/9t49D7Lcx98cTX0bNoIjIxYvHIb7jTevX0KWcJr0mY7nireZeCdroaxgYN9e1Pn/xIsS1DvbHxD4C8W0374P47rdgmcUM5qoQEQla+LcjRyj/xxJepzyt3x1lTA3+udoZiIfKqLucHMhAXB4k/WjKdwhNWp/8+DnUi554EHM1+HW87tZW/Lw1a+r8J7ajdyBfwXqKjdfMdvDzQsHMeeOTT8bbuCa/Hchmc+Mtk1Isr7T3sTb2/+WllrH9UAH7R0ga2vk66l0nqM32VHB/NyXPgUf5iAb60CuXyeO8ybmHcjlTp1ssooJ9eRbrefiTuDZ9ZYbyctBa9iIiYYd8QT7lr2hTrg6ay1ukaZYU/Xa0jNegOo9zeWEO7zlBFT/v3o4+NhERZwe2b7R6CaPNt2zI9Olza9fTsbACHntzRMTK4JiyKClG1sP+ZsfYv7wubh+7KTl8ON9NiGWECR4jO74D4qWWeR9pkpbcpbkioTwuMXkXrJQ50Oa8KEYSAjZU4HklRmxyJUsG52wxnCKJWW/W2cfW+hwSGeX1lnJfv+TzK/PLyRZ6GudnLhrbt2Oc78rD6P2zyKeXz+HcNTSCPlLXNe8RXfLD5vPYV44ewWetRx58AGI7MufU6jzONdPn0PuVLWMeqkwB/Z6VfvSCiYi87g1vxOPStWt3yN/XwrmpWcd78EW6h4uInDqJz6pHycPMXpQtlENuaGjMKPNSXpVLDG7IA9Zut+WLT73f2CcN/WVDURRFURRFUZSeoC8biqIoiqIoiqL0BH3ZUBRFURRFURSlJ1yTZ2PYyUp21XswJagP7esz9exPL6HPYKmLmrPt47h28ffO7oTYq6GGbegolicikj2Oa3ZHpBHcQZJGL8I/2C7lAhGRyEJdYPexJyHuJz9FPEya6LTFoGl9/T4HNX5dWjN5kOS3hYS8ADOmXm/qAHoOykU8t7t2T0E8u4wa6pmGqTlvtVCrfeLo0bV/t/3N1cw3qk1xMysN0zeMOtaF2gVj+1wJr3WjiV6bgLTFh15EveOF8+idKJfNvjI2hprH0R2oF22dxut6dg69EPmy2VeGRlDvPtBHXgcbx4FL+WwyNuVZEJHQR29THNDAiNHLdOAWHKs37MS4XDB11gMjeC6tFo4L38e2qS+gxjfyzbbIZ9AHItGG6x58RYvWf1X09XlS6luZH+bnMQeNZ5uespKD12YpptwQCV7bDCUM2FbGMvNZU5fv01dGXR+PUScfQyaPc3XimbrvgoX1Hh3G/pNxyU9xFv1fF2ZNT1lIBjnbJq8I5W5xs1gv9iZ1a2YfLGSx3osN8hpdxPmsv4xlliwzR01E+Vz81VMPks3P8/LMuRlxsqtjIsH5y/AkiIjH3gfyCLAG3iMvBKdL6aRYBEb7cb7aMYjxeA4fM0oF7NPtjpnryqI8Uks1vI5tH/eJQrwWDnlRREQyGby27IVwyI/S7WD/sqjt7JS8QF0f+zjXy6WcBXnyS9mW+UjGs9zGdFrdjplrpqe4GRF3pR0rA5hj6uKJU8bmOfJT1M7hPfUi+SqfeBKftW6kfBWFoukF87t0f6TL8uyTj0G8TPkqwtD0bMQRe4AQzqcS0LNQIzFzYBToVpb18Nrn6dz6B9DfkiP/VcY2/Ss1muvf+MbdEI+NoSejVMZjujmqpIjEMbZFboOvJi3Xx0uhv2woiqIoiqIoitIT9GVDURRFURRFUZSeoC8biqIoiqIoiqL0hGvybOwrFSS/qhsrLuA6xI5t6q33bdkCcf0i6XhJnzxFetFCBj93yD8gImLRWtmcNqPLOlbSbXrG2toiLnkuPFrPPyijnjShdcLDrllmRKq/MRtr+kZaC9+3UHMaTaLWLnfqlHGMFstUyUdz0w17IJ5oYR0mAlODvG83rnO9Z3jda9Jst0Xkfxr79AortsSKV9rRdsmP0a4a24+NoebREfQyTE/jda0lqPeuLWH7uDlTh77QxL/1l3F97VwJdZl9Qzgm8llzCI4NTNA2rNOn/hhEFKOXQEQk8XAc1JZGsF4khX3Dt+E64lmZhXhiHD1HIiIZqueR53AcLVIeik4N9cZJina2fxiPE23cJt78RAf5TEbyq3OIRfWtL1WN7W3ybLgWXrskxOsShni+QYC63GLBPGePcifU66ijzZAuvFzCOnkZ0wfSbOIa+hJhPx2knEcdyrmTsnS9BF26/k2cz+t1/LxQxAltoIRtM1szkyTlSHOcxLhWfYe01WfPoNdk51lzjI/uwDEbxd3V/998z4ZV6Bcrt9r2dO9KczDxrYhbLOK9yIdSoPtrEJk+vWILNfNJCe+xlUHsOxNluq9XzLlkfhn78PFZ7BvHFvBzy+E+bPoPLXq+yFLuK8/GMtgLwBaNtAwX7NkIKK8O+2o4x41tmWMxoRwiG4dr0Ll6zfzLQTeMxVp9PsrQWGPPi4hIGGB7JJQLZmYa7yvHT2I+i0ce+RLEnK9MRMR18LgjgxXcIMDr6NIjYb2Gc4SIyFAZ+2Qmi3ORRdcxovw0sZ+SD4l8RP0VfFZgn0iHvExHDmO+kIfu+7xxjFOnTkA8OYk+3fklfDbg3DFuzvQdss9oY66o7jXkWtNfNhRFURRFURRF6Qn6sqEoiqIoiqIoSk/Qlw1FURRFURRFUXrCNXk2lmZOSXtVc9cNUevVdkwtcasfdW/5FuoXOwcx50DkoM4tLGL1bMfU6GZDXg8Z9cgh+UIi0nknnqkBZO0rx+7oLojLVXxn65jpGMTfjvq8gRA10cUOnltYRe1sY5bWi59+yDjGhcefgbjvJsy7sTCDemS/gOtkhylLdrcWMP9CzVuvZytlffRe0mw0xFn1HjhNbPOyZ3bloIW6XZt0vPks6g1tyi1QHqhAHDmmRrvtY5u2LuJ13Dl1E8T9efRKpOWKCJZx3AwUae1rD4/RYt2ua9YzJl3riWPY7wfGUGd9x53o2cjLXqxjRJp+Eek0cayFAa6h7rdRG5t18Jj5opnjgKXY1gZvWJxsvmdDgnDlPxHxSJbrpXx3U+lH31Qhxj52lnIJdckbUe/gQTzP1KK7WWw31klv2Yqeg/4hHPfzC6bHJ6AyQhpeAWnTs6RH7rRNLW9Ea+63KE9GbbEGcRJSDowRnEODFI9Zo4n3mFaX/EwhjrfOPPbJk0dQMy4iMnw3+tbc1eQTLieh2AQS35dkNRdDQn4KKyXvQ2zcvdh4wPvgmAotWmM/MbXoNnlXZpbxRhLT56eq2A+6sdmOVbqOyy0soxXhedWoL9gpY5Hby7W5bchfQWVYNN+k2D1FEhwHcYwDJ6F6C/m+kpT25QNtvGRRd3N9Q/1DI5JfTRhx8Sh6CFzDNyPSoTEvGWwPj7yX7GFssB82MD1DsYttXquinzii+2N/pQKxH5sXkj1ojQbe79gn0qCcLH1lMx9IHGD/mZ/B+2OziXPR4SPYvo9/+VGIT5w4bByjSfU8eRqfsT16Torp+dh2zPw0Dl3XcEPumCjNnPcS6C8biqIoiqIoiqL0BH3ZUBRFURRFURSlJ+jLhqIoiqIoiqIoPUFfNhRFURRFURRF6QnXZBBfbC5LdjWB1NkmmoPDlARHGWsc4sLAMMQLZBgdZ8NohxKn1ExzUJeSNMkwHqO4DxPZdciY3ZhHU6KISDampENkFurOURKYLBoXrZQkRS4lFIpr2H75m9B0LhksozCLprvm+fPGMaqHjuExzqABqTyIZtXFChqWFmZM0++F2XMQ78ysJ5xrd03Dfi+xM5Y4mZU+0e7gdW+cNhPzdOexzUYn8RoU89jflikxYNnF6z44Zhrg5uawDCeiJHRd3KfTQMNc1jKT6NhOBeLFedzHLaIpa6GO9Ww3zOsoLpZ59jwl2tqCCxDkSjguXFrAoN0m07qIJF08xpYp3KefjO4zp9G4VyyllEnJL60NvvZux5wPek1tsSpxsNLeTVo8YaBQNrbPURJRv4t1jl28li0L++xSlxZC6DMXtPDI5NtXRGN1pR/btVxCE+By1TT5LdSwPziC/Xpk0DzXjXQ6KcmefErA6uP802jgnNigxIJZSqwV2aYher6O88AS1aNDJs1OgJ9Pn0dzqUjaNVs5jzjZ/KR+URiKrC1UQcbhlPaIOfElm40pOZlFBvKQ7ltl2+wrOfrKcp7muA4lprRpQZWWbxp0cw7WI6Y+XqR6+JTYNIrMxSZ4AYdEKBEbH5MN4WSWT12fggy3bCKPU13lG7BSXecveVxe8KbXTE1tk+Jqcs0jX34YPltYXja2by/h+NqyYxvENl1XTnrI6xdwgkMRcxyGlFCvmKdkvTRH1JvmXJWnejzx5JMQn6IFe8r9+AxYLJj39YyF4+DIkUMQL1VxsZlTp47S57iQR5SymAAvgsDrQbChm5szic05JKE+u/EaxSnm+pdCf9lQFEVRFEVRFKUn6MuGoiiKoiiKoig9QV82FEVRFEVRFEXpCdfk2ah2OpJZ9WzMtFBPG1ByKhGR4TFMYJZsHYU4O4C632wNtXfuNCWha5gJrRqUhCgqoV7Z244aQdciPV/FLDM4cgZj8oV0bIzL33IjxK2qqfuVw6jPk5De8y7gPt24CrE3jomlxl//GuMQ2Tz6AxaPYEKXSgs/79+OutYzlGRGRCTvoCbP25C8K7gGvd7LgSWRWKv6wYSSnY30DRvbO23SctZRMxlTAiG/g1rO+Xns04ln6hmLHmozR0bxOo0OYb1GKjgGJDB9IB4l1gkcHGu1Jo6LcxdPQjxzzryOi/SnsHsrxOUKljkz/yLE/Rbq/gsZ7PMiIqOTmERycgrHtxWidrZ+AMeqH5pek8iiRHDddU9Du9kVkU8b+/SSOAglXp0PgjrWbbBk+hiWq+h9mWuj1neYk30WsY/OnJuBuK8zIUzWxX2GBisQlwrY7i4lYO3rM7OQTp9B/0STEjayF6DBOv2WOa/GZPFaIt9atY4bxAnG7gzOkZmyqYtukHdwOcS4S5r6LmmUOykJ5kKa56LVhIdRsLmeNRER27bEXvVmGEn8UpL68TasvzbL4JB8k4n5/WTWpr7g4riukU+mmMeDuBnzPpKl5GPLbbznFimhYomSxZ1aMq9Ni87FI48Gn6vFp8p+C7O5zQzAtI1ZJPsxrj5J2uoO17b9V0nByUnBWZkvJrbugM+CvOmTCcnv1CV/TpXmgIDGp0d+CysyzzciX1Zo43yYkBfYzeLnbtds8y718+ePon9i4YmnIS7k0dOWcc1H64TOrU0JD+OEEzziuToO+/VSkopSokrDb0HJCMUxTDFGkVwGdOpr8AzpLxuKoiiKoiiKovQEfdlQFEVRFEVRFKUn6MuGoiiKoiiKoig94Zo8G1NTk5Jb1VLaJzHPQ75tbh+RPi9L6wwvNVHP/PBZzOkwSRr6G8Q8COfZaFP+Cf9J1J63eW3yqSmjzM4+zA/SClGvfutu1Ks3bdTrtadPGWVmlikvSR/q8v0z5BO5iH4Bb3QW6zRG2n8R8Qb7IR540x0QV89egLgyjJq/O0rbjTI/+yDmEshW1n04UafDm/eWoCOX3o8zpFMvZVLWVY+we/P621YW61/IYRkLs9i3opTTPbBrK8RTQzshdl28zp0m1tsT1DeLiFiko2zQODp8EvvKhSrGdmBqUOMqHncwwbG0bwC/dwhbeLK+i9pZJzB9SbxmfyaPZYwN74V4uA/9VLUm9jURkS7lQSi6Q2v/bqZ4uHqNK7a4q33Qs8jz0zbXa6/V0YfSTrBP3ftt90B8043oyXjwz9GTMn/enAMn+vsg7i/jfOT7eB265GOIo5T8RZxDh7TSC4uL+HmM556mPW82sIwqzYmRhePPpjE+s4D3i4kKnreIiBRwPNVjvId0Y+rnFs6BTsHMkRQZ1ogE/n9zseSSZjot5wBj6q2v8Dn7U8jT0UnRzIcNnAsSC+9DXhbbdIzufXnH/M5zO+XL2jmK9+AiJfcgG5I8cAy9TiIi9x3Fei76lE+Lnw3o3MOQ9fDGIUwPDHsykjSjxzpXY4NMseZsGp1GW5xVP8PUJN77SpVBY/v2RZyvFpfQs9Zskd+C5iah3DFpc1Uc4T4+XcelGs4bmQzOK2n5aTiHWKNLc2jA9cb5zkn5Hp8vPd8vOecI++K4b9hXMf9EKeOVanXFMkyf18Y6aZ4NRVEURVEURVGuM/qyoSiKoiiKoihKT9CXDUVRFEVRFEVResI1eTbGJkYlv6p3q59H/WNhIEVISBpcj7RxF+YXIP6vz7wA8f4h1Hr+ZM5cV71Ar0tJEzXSi8+hZ2NxBPWkJ7pmfhDW/E3uw9wJ2wawDP8CJjEokTdCRMTiRebr2BZZm9YmpzWYoxMnIE6mTU3qUhnbu7h/C8STO3dD3KG8GiMFs31vv3kPxFt3rpfZaKUYdXpIX19B3MzKBc8Vsb0SNyUHRgX7TxixzhKvfWMZ29xpkOfINf0V0qa1r9uoNbZczDUThVinrGdqxAPSpS6TlSGpHYA4H6BWNp/wetwiWQe9STPVxyHe4aIHaEvuZqwT5ZZpt8ycGMs+9vt4EfW5Voza2UoR49g2fTf1GmphM8X1vBRBd3PXmBcRySZ5ySYr/WB8BMfTE5GZ32RJsE9N3oTtfM8b0P91wwGca4YKOEV/5r9/zjhGrYrXotXEcbw4j+3sk944cc3vnOpd9g3h9R8gf0pW8DpFrL0WkSrlJfFJA+9l0BfUCfCYSx283p5v6oXbDvnnBMe4T3mZWpTbxSmbfbBQxHpFqzrlKNz8/hdEwZpuna+abSSGuLJnwzAAsMeAioxSnhg8wTZ8ZQXb8LY7XwnxaB8WEqfk7sjY6KXZOoJzmk2eoDDE7d39Y0aZtTbu83fHqxAnlOeAczq45O9J7DRdPrcn9RHyF0R0Hmnf/iasq98o/t9k21C30xZ31WPjUs6Ggb4BY/uwQ88IVN9WGz/PuNjGbfKFxoHp2XA5XwrnNqHcE50OzkNp44YL8f3L59ThccY5M0RS+gZ5Mq6UYcU4RsrFt21ui2sz+KTOFzwnvPRHl0V/2VAURVEURVEUpSfoy4aiKIqiKIqiKD1BXzYURVEURVEURekJ1+TZWI6q4q+KNt0E9dieaxblOyjoqoa05nIbPw8TLKPmoUb+vIdrbYuIVBJaY9nGOElQW7wco17v3Kzp2eizUaO7RFL9T5z/BMT7KVfH7kHcX0RkKIu5O5qnMB9I1MZ6JKTtXFqao89NsZxPeSKCZfTV+M8ehbhAmr9uztT6b7/xJixz+vTav8NNzrNhdxNxLumlLWyfIDG1nC3WhzYod0kGN+izsH9lSTecCc11/YsO5iZxuqjjj9uoHc57FSwgMt/3rQjVmxNlPMZ45TUQtyPMJdBcNL00J2dPQzzgoj+qP8Fz3zaK53Fw5jjEtmXqcz0Lr4HfxfPokGa6XXoU4ihjemJqHRxL9eq6L6TdNPNa9JpWPRA7Xs01lMX+0E2x9Exux7Xo3/r9eO327EePTyaPffKme9HTEabM2A/+0d9A/PRx9HdZXdzJ8BpksJ+LiCySJ2NwAK+Dm8dcCe0a9sH6sunpaZLs2SHNdzfEDZZpfmnReDx4HudEEZEz81hGPeK16mnOE9Q09w2jH09EpFTEsbG4Oo9EsvmejSSKJVk9J9aAJ/aVBdSsyU5IN25ReyR0jo5r3tuc8g4sg4yU3SY+Kyy66CkqF8wyj86hz+jLh6oQNxemIS6MY34jm5OjiEjQwvmpZOO5dWI6d8qjY2jqU+45EbUni9rjEPfhXArsPxAR4b8kG5+TriLXystJu10Vy1oZY6dP4fNEPpcxtq/0lSHukufCruL2I0PoP2SvRLtl5lbyqUyf/GUu+UAcyusSBKa/jPNmXOm6sq+GNxcREc6LwePXyGdBn/NYTckP8tWS5tkw/rJhmyt6wjagv2woiqIoiqIoitIT9GVDURRFURRFUZSeoC8biqIoiqIoiqL0hGvybGSSWDKrGkE3Rl3csG3q/X0HtXBugPq7Fq2bPjWCOQm27ES98/lGSl4H0oxlyHdgkcjZj1GLPDGEmmkREZckfLU5zGmRLKJucHoBvQDLBVO7uK1LWsV59GxIGw9qhzZ9jMdoRea6zwl5TQptymty/hx+TprAZsra+JUu/m341n1r/467l197+uUmmU8kdleud5zHvuPbpn8kQ7ryjDcEse1jGQlpxmPqO6OTrzCO4UX7IZ6bRuE+e5nCPK2z7pu+g3Yb65HL43W1adT2VyYgzvSlaPBH8FwzpEOvdTCZx8X28xCXxrE/5iLTs9HtYI4DJ8KcEQmpj2cWn4I466G+V0RkcPBWiO1g/Rit/DVNXy8L04uzUuiseKMefu5h+Gxkt6n3/8c/+t0Q77qR87DgnNalvD++j9rhm+/EHCsiIqefRD/NP/zl5yHO+KiRD8hLEyfmuO/P4bXaOoG+NNYfN6gfc04MEZFqFz1l/E2X52GZdQ/L9CrYZ8+ewzxNIiIzddxneBvmNZk+hz6PMMCxYlvm3F1bQj9KJ1w5RqezufOfiIgjljir48hYdz9FKG54NK4QG+vy8+exeZ8/28K/HVrGe92LC2ch7h/EcR6n+A+ryzgugnOYL8tdOgXxu34QPRtz59HTISKyux/HgZ3Dejx8GudAspxKfwbnm3LWnGezGew/loPbdH3OV4Tnudwxsy3MdV96nouTl1+3fzmeePJByWZXxvH5MyfhM881r2OzUYXYzeH9sVTCe8aWCbyXLS/i/kuR2T75PM4rS1Xch9OhhOTjardN364jNA9cS0IJMXN9pP7xCp4N5itJqWL4Pq4w/q+GRD0biqIoiqIoiqJ8LaEvG4qiKIqiKIqi9AR92VAURVEURVEUpSdck+g53ylIfjXPxnSI+uTRFM38QLuKB5u9AHFYR43kgRtRd7lt/16IF585bBxjwiLdJOl+vQTfp/KUa8FNUcIVCqgrPHL8FMTDTSxz1w5cG/pcxlx/++IxPPd8fRFiKyRtbITn1XE4n4j5nug3cZtFyr9QKGBegDrprJtdsy0Wz1+E2N22ni+k5Zvn2Uv2T75CspkVfXBUQJ1m5Jla4okK6uNz/Xj+Fq2rPjd3BuJFak8nt8c4RqdTgbgd4DjI5XGNed/Hz9tNc93wZhP7aEQ61YhysPSVUXucL5kJH87PYX/rOKh/v9BELXtpAfuCM4BlBrVTxjEKNupcB/I7IHYz2N5hF7cvZtFTIyKyZRznAE/WvQONutl2vWZs56QUV9s3LKFm/xWvvM3Yfs9tmF8nSjD/RBBhf/AjGlO07n6mZE7Z227BNmr81RcgdgO8ljXKT5JxzbnkFTfsgnjHToyXm3gezVnUns+0UubAFuVscLBfOy7OV6VxnANf+7Z7sLy/ecw4xnSAWv13/uCbIf7i5x+B+Ev3Y/6Z8+fM3B1BdxvE1uo9x4o3/7s6J1nPNRTTvSvjmH0jpDwM3ZDzUPGcTzHdPy0z24R0aR5dIL9OhvpwuUPzm2kZklIHc0R1Esy7EdB5hUt4f505az4rhORNuvtb3wrxMHnjRkt4T9k6RPOsZ94vc1mc01zy7HG+hrCLY/HkTNUo878+eAriCxt8HZy3o9ecPHpQPG/lnBbn8Rrt2rXd2D5Lbdrx6TmG7oeee/n+5qSYIerke0koH0+WfCJhE+eZJMUH4sdYz9i41Jf3yqQ5Gdg/caV4M/hKPBs2PHuqZ0NRFEVRFEVRlOuMvmwoiqIoiqIoitIT9GVDURRFURRFUZSeoC8biqIoiqIoiqL0hGsyiC83A/FXTVH3LaOBJjS9nfLaGA2U+VlMjpcL0OB5+51vhHhyKxpy/+ax58w6ddFgFLlomArIQJ6nJDidc1gnERFnEA3fuwbQaNyJ0PTrFtEUduu9dxllLlLutsUnZiHukgMpdtEA3aZ6F4spDZ7HpEXtDJ57PISJ2DqCn8+QiVhEZLmKJrClQ0fX6xyaxqpecvPN90o+v2L2svvRrGeXisb2lRyaoJ0stqkjaAB84fDjEC+cQXP8yRnTkOy52P/yJWzTTEBmtAD7SnPZTFQZJmTgzWA9Ww0s88QpTOpWypmJyaIYh3qDEmzO1TFB2u5gB8SL53FcnTl10DiG5+O5V0rYfpM7cFGJ5RD7W0xJ20REBj0yrmfXr3uYpCT57DH9YwNS6lup5//np98Dn2Xy5nc3gY3XyibDo01TcD6P/TpJcPswNpNATm5HE/q+A2gYP/cctmESYRmOZy4o4Lto7Hz6OBqpZ6s4B87MoWF8btlMeFejudh28PqVctjHXv2tr4P4ru94NcSPPINJxUREWscwgVyxgmPhHd/9LRAfeeGvIH76cUxmKSLyhndge47vWJlHrcgcZ70m47nirBp0LRv7Rj8lNxMRadHCI+0a90fkSn7RjGP2cU7W6ZJ5e1sf1uvGsQrEi0tVo8xlWvwhiPFcZ2vY3+67/36Ib37l3UaZ2SyOtYESzjdbxzCp8AgZxCu0KIltmUkUCzT32tRePi2qUm3geR4+ayYjjGjRESt2NvzbrEMvWZieFnc1UWEckaE5Nh8n84UKxLNzmFi4lMekfvUGLhrk0aIinY65EBHlwJU8LYSzvIxlJmSqL+TNZ4damxKf0jiyDTM3Jc9LMU4be1yjIfxqzNw2meNfjiR+lzOyW5YaxBVFURRFURRFuc7oy4aiKIqiKIqiKD1BXzYURVEURVEURekJ1+TZCOoXxHFXNGHHFlCP3Q5M/WplC3odbvNQK1d20fexc+tWiPtK6J3oRqYOuNvCv2U81Np1EvqcEo9lfDOjUHsRteQ2JeaJHdSpXVxA38fSwReNMgs51NLVc6RVzKN+tFtC7TYneisMY9uIiCxSgpw6eSrsADXSF2ZQ92rnUrSLpO0v1ta12n5KMpxesuvmO6RYXGm3xENNOXt1RERcB9vMiXAfK4/XpPU8ns/5s+hjWOxgLCJSLuF1DGdID5rFz0cHRyEe6kMfg4hIo4X15sRHQQevSaOKCa86sdmnbfJPNTqobW/QPrUYtd2WTckyrTHjGC8eQ+9I/zCWseRin/aK2FYN8reIiCwsYR/dOfbKtX+3GqZ/odc0/YZY3ZV+UhzE/hSL2QfZc2GRhjvsouY6SQwVPUR+YGqWK2PYru/4nu+A+C9mPgFxq8o6b0qMKiILNvaX4VHsp40QPRvdAMtwi6b/Jk+JSUdHsA+9+u4bIX7Nm++E2Kpg20zuNOfAOEad/bFj6Ot4xz9CP93+/RMQP/GkmQzu3ClMGLd9z6SIiITXdPd8eSgU8uKuetEcug8tkjZdRKTl4zZRRBprSg5r6MjJf2HH5pwf0dxxx5YKxN+yF69T3MXtl1PaMQqx/7Xq2N9KNG/educrIX7la+41yiyR58Lv4jFsltCTT5JF95ms6ZEJApwDzp1Cj8IXH38G4scv4Jx3sGq277KP92XbXa9IYlS6t9TbXXFW57AC3YNr1aqxvUtJ/QoUe3Ttux2c00sFPPdOx/TpJV3y6dIzX0J9iW0LUYqPIYx4jmTfAo6br8QL8ZXsc6X9HRrPccLj/6t/Zos3+IRiM9vhS6K/bCiKoiiKoiiK0hP0ZUNRFEVRFEVRlJ6gLxuKoiiKoiiKovSEa1KdvnFrUUqruRvmFlGL/uWTZg6Cz55CnWV+F+rvCiXUPJYd1PkGdcqhYZl6sybl2cg5eEoRrwtOWrvYNt+3FpuoE086qDHNNElDXyVN4PEzRpkFeq/zaS3o50LUKp6axzwcOZIQZmJTu+jl8NytgNaorqIXpZmg1tuldcVFRCIPy9g+UFkvb5PzbOT7+qWw6pEIY2xPXvJbREQ8vG5xgn00RzkxgibmI7h4FL03SUouj5HxmyA+dhjXSW9bmMPAauJ1dqfS1uPGv104cwriZgs9Gq0W9lcnRZdpJegDkVwVwsTDa392Bj0dA/147lu3bTGO0e3iubZ9rJffxbg8iMfsdM014/0aziFZWfeFdJqmR6LXRKEvYbi6zrxhrzDb3SUvQ8jrntMUnCQYByHONYlttlHoYZ/aeusOiPPjtO78wfMQW6457re+eifE3/mPvx3iCxfRxzA7W4W4nnJtQgvH49QEevq2bUM/k08+rKU2eqa2bDc9G66N/fTEETzX4vdh+73yDszl9NSTR4VpN3F+j4IY/n8zqdfr4vhR6vF9YyV/kYTub5kr3PE5PwB3cSdlXf09Y9jmP/h6nBOX6X65tFyFeCBrVup8A8f9rTejn+fV92JOroFBzCGVT+nT2QT700Af+gdy1DgZG/vrwjzeH144ZPp7HnjkSxA/9MBDEC+5FYgH73k7xK3QrHfMzz0bPDJxioeml7T9YM2z4Qi2z+K8mSNkZAxzAE1N4hjPZdFDu7iAeb3m53DMx5E5rxRs/FuGck2MTmIdZuaxby1RzhaRq/FsXN4rk/Y5/60Xno2I8q7YV/BksYeDt08D82xccfP1sq9+U0VRFEVRFEVRlKtHXzYURVEURVEURekJ+rKhKIqiKIqiKEpPuCbPxp4JV/qyK3q4f17YBp9tzZ43tv/8YdTCfe4UautesX0S4sZxXBO9Su9CTmxqZKs+6vBHCuhDiBLS5cdYh7nELHO+gH6UDuUDKVvYbMV+PGackrtDFlBnn82izvUcrR+9QOuhj5OmvlDEOoqIlItYZtJGrey8j8dwHWw7Z9H03dycoKayVF9vP2eTPRu2s/KfiEgSYRsHgZmDJYzw/OMMatvjOvYFq4H60LCBuWQGRlDHLiLSncNtmrPodQhjFDUGDewHC7S/iIiTxT7bbtcpxjLqLay3Y6cMawfbYstO3GZ0AnX9tCS9oQ9tBphbRkRk5w6cE9xoCuKW/wLEtotr0PsRej5ERIol9IZsHL7x5ls2xFr9n4hISGvqu66Zr4KnrFYL+yB7NERwhyjEY3g5U9Pt01dG+QrWozRZgXimif2pvx+vvYjI6G7UwPfvwPkmN7kd4j0WxkHbHI8NWkM/pjFs25SThObmrIOdcnhkyDhGmXT4GY98gmXKz3DXXogH/up+o0zuZ/lVj0Hsb36iDT+K1jxZCbWP66boxB3SidOUHdI9NsO6cprjx0pmPq3vumsXxFsquE2LNPFjFbxfDmTNcTNcvBviA/sPQNzXj34d38e+lXXMe5NNno3FWfQdnT6FeYIee/xJiL/8JObIOHb8hHGMOs3vEeWwGXj1uyBuc+6n0Bw3HvtON+biMfLy9JawU1vL7RHzd9WRWRcrwTHuuthnxyfQTzE6jLl3/vb4pyGenMBnRhGRPE2JLcpD1QywL4SUG8I4DxGxKa/UlewV7IW4kqdDBPNVrBwDD2KWwX6/K5d5JQ8Gf562PdfrK/Wa6C8biqIoiqIoiqL0BH3ZUBRFURRFURSlJ+jLhqIoiqIoiqIoPeGaRKddvyVda0WDOJhDPdnd+4aN7eebqB974jyub3zw4hLEe8m34NO614mxsL1InXTASRf1opx7IiG9nnAsIvks6ijrCerda9tQVzh00w0QOynLrz/3d6gF3kr13jIwgjt0UXeYI63jcmDm2WguoOdinLwnk8Oocc6Qtt9bxOsjIrK9jnrbrZXK2r9b4TUssvwy0PE74qzqpP12RJ+Z7REl+LcwxDwjoWAbt5ZRy25n8fzcojlcqvOo0Z2/QD4E6jthhNeoVJkwygw7qPONyZfUauN6750Ic7JYGVPX73rYz4e34HH37EM/yswCekkyJOu3bNNr4jexfccHbsENbNTbJiVsu8OHcD4QEZkYwbFWzK7n4mk7pr6517T9RGx/pS0d0lJnXLN/hKSsbdG4bneozxmaWdy/6Jherchi3S32ucoE+i9CB/uH7ZFBR0QGKW9BQP4KX1D/blOeIEtSDDXkyfDJZ2Ul5Begc8845B/rMz0bA8N4bhNT2OciysMxtA2PsW23WWZCSXzcVS21cy2LzL9MWJJsyMOD18Qy/D/mHN9fwDbsUv6AMMQyHdK7bymZ9+D91L/apJm3IuwbxRxeg+070e8jImLvQr9XNoN9NKL5vj6PHrInjh0zynzhBfSMPfUMejCOn0APRr1O/gtqmzgln5FDjxO5IZy/yiN4XgmXGZt+z0TY07L+LMB5EnrN1qG8uKvz3tAg5kWrDIwZ23uUT6wTYd+Yo3xi26d24/Gm0Ac4MlwxjhFS7o3pFw5CPF/FOdan5zMrxadgGflkrs2ncDW+BtOTwb4PYw+K0vL8XJt3hO83jmP6p3hO+ErRXzYURVEURVEURekJ+rKhKIqiKIqiKEpP0JcNRVEURVEURVF6wjV5NizHFWtV02WRRneikjO2v2cnrmle81FLfKpKWnRaE3x061aInQxqBEVEOiFq4zp11Oe5pDnNeLiWP9ZwhfAiauL7SK/crWG9FwPUzlUGUMMqIlIhXbXXwTKmKEdGht4DrSJqVi1aP15ExG6gHnLMxfYim43YXWybFrWdiEg/5eLYvW39OjfS8on0kCi2JFrNW8FWm1ymbGwfdJsQ+1VcV30xqEJcGKpA/Ppvfx3E0y3TU3B2EfPLjOzG6xTTdY8CbE9f0BMjIlLsQ5357Fmsd8fH/rn3FbjmvORNvejCMubiqIxSTgsLte7tBnaWwRHsb2FitsXwGI6mkRH2EqCvq9rG/jlSMb/7yDq4zez0ula709p8z0YnFHFWJcI2rWkeiFmfICAvA2mBM1nU0EeU1yCmjt7pmsfokAg5oFm93I8+DyeDulwvZ+Y3yXp4rbotPEZoU86MLvZrN07JOULy8oT9AgHOJ602ltm1sa0WF3F8i4i0yd9UKOK5zZMvLaT7Q7Fs3hGaTZonWysdoN3e/EQvWccT55Lnhpp43+Sosf3uCfQCbh/E+3S1gW24THEmxHt2OTDHvd/B9ul2KS9VGcdwIYuxlSI9LxaxnktLqO3/whcegPjhhx+F+OAhzJkhIjK/gHX36Rkm4qQ40eV1+45jPj7xM4o3hJ4Diz63Y/K3pJTJ+VSSDbkrkmRz++DOqSHJeCsdr1DGecUrVoztT0/PQ7xAPphWkzwc28j3N4Xewrk5M7/TiVOY2+r8DN4fxcKBknCc4tu9mjwZ1wr7OGz78h41TtJkWjzMOsaUSCcx8rDwuVqXDVOxXuLfV0B/2VAURVEURVEUpSfoy4aiKIqiKIqiKD1BXzYURVEURVEURekJ+rKhKIqiKIqiKEpPuCaDeJJYkqwmXkrI7ZeJu8b2Nw5i8XMTaChqdnGfsI1mtOEhNLflSqZ5r0rmnsBHw1RIcdfBY9iWaWTso1cwtr77NUp+18Eykxk0s4mIbCEnjeeQia6NZY46aGxcIjN9tmya0OMAKx62qhDXyMRJ/nCJu6bhcuJGNB3u3LZ+TWqdzTWn+UEs3qoZ1qKua6UkfJSIkhbm0Lydq6CpvNTEuH4CjWevvIkSL4rI7puo/9iY2MhvY72+/EUsc37eTMCXL2M9Wm00kfcP4j63vgqTYp2cPWyUKWXsf5PbxiEeGEAjXqmIJvV2iEn86i1zvMcJ1uvc/PMQD1bYdIzjuT9v9umAkjd2NyTD7HY336Db8kOR1YURQkpK53opSUfrVYjLZHwdGcIkcgklX2RTISdMExFptzDBWURZRSNKFGZnsC9UG2jaFBE5fRLNtAMT2CedPPbJhBJrxYE5r9YpaWvHp4SsdK5BQHM5tc0ZWjhBRGSZDKg2XZNaA+ttJ2g6b3dMs+jRY7gIxHJtpV6txuYukCEi8tqbdkt2NVlrpYB13T3SZ2xfpKRv/S7WOXDxOrWLOIbDJt4Tuq2UeZaTotEiCIUMLY5i4+eN+WmjyMY0XsfPPfoUxH/2vz4F8fwsmoLZ6y0iEtN3qzHd+20yWyeUNM2i5JeZrLlgTYYSqrqjmMRPXHqaoOeoWMx51TArgwl4c/tgoa8o2dUFJuxsBT5rRWbfiCnxqWvheMtn8RrUm/gc1KQFVU6cOmkcY3ER+0poGL45GR4Zs1MT8NmX3YbjqzKU07igHKbikmE8JjN3Qp06TnFnW7QgDSdjjWixAZsXDUp5JeB6bDSZG6b2y6C/bCiKoiiKoiiK0hP0ZUNRFEVRFEVRlJ6gLxuKoiiKoiiKovSEa/JsxJa9lqQs4oxCoamf7ndREHb7VtRsL9QxgYt/ETW4AelFM0Uz+VSHNWqUxMSOsV4RJXGyIlP3FlKZvsfboA7OokRckYO6xJWKYBlRiGUk5PvIRaj9TEgfPpOrGocIKEFYjBJT8UiP26KkaJnEFLqOkLY/564fw3df/sQ3lyPyI4m8lbaOqL1cNyUxj4sa8XIf9p+oXYX4/JmDEB99/hjun7vBOEZnEJMMtek6DeUxqZMdY71HBvYZZWbzmECvS0kj+4crEAchHrNex0RKIiJTW9BvYkVYj/s/j0mxvAIec3QbebQc6lwiMjONumk/wkSCiw30gQzmUM/cXzI156FLPqQNutV2c/OT+jWaTYlkpS0yHo63rGv6bzIZbCfbIq8RxT4lPm21ULMc0PwlIkaeJh4JQYJzjZPDNq1WzURtn/r0P0DcN/Q2iHfsQv9dJOSviEwteauNevQ6+SdCmhM90r/bMcYXLmL/EhHxaS52s+5lP4/INxKmiP2nz6CnYGFhpd7tZsfYttd8953bpbg6TjJZvNKnL8wZ2z98Pya/u4mSeVrUh33SlR8/jL6rPXvN+cqm+2H1PCbUay6hDn/mAnoajx43E/CdncdrGxbwPjQ4tRPihOajKCXhbEhfrXZprg5bmNQ2T/d9mxKmdVqmxzHK4TNOfgA9j+xtCsmzkYg5vtkPEG0YW7Fvejx6Sd/QqOSyK+PwzAVsr7T+F1Hd/TZel04br0GVxpTl4fjtpsx/bNFwXdwnpme8mL0PKf6e1EyTG7iyh8PcxyX/SszJGtmHSh6hJMLtnbSkfuTRCiOuJ/lX6HmZ70crf6O2sNaPYcnl22kj+suGoiiKoiiKoig9QV82FEVRFEVRFEXpCfqyoSiKoiiKoihKT7gmz0YmX5DMqgbWyeEa0361YWzP/ojJCu5zyzLq8w5WcS3/mekzENfa5nrwDRLcdWjNb48EfSHpLu3EbIImaeFapHNzeb3uLmkAu6aW1+IFjaleHZfW2yb9cpO3z6ZoNW0sI0eavzhCfWSRcqPsGcO19EVEBjJ43NZCdf3f3c1d49vzQvG8Fc1r0EAtu5sx1/XvROhdmL74LMSHHn8O4rKDOvRigGuiH7zvaeMY2R14XRfIS1LYXYF4xxYcA+cumteR9cZuBnXVY+SfiBMce3HL9AwVbOwLJw8fhfjhR89BvOVG0r2WaVyFmB9CRCSs4XEHR7CMUydRm31oGT1b3/6trzPKHN+CGvNmuK7ldmXzPRu5TEbyq96oXA7PN5OSZyM3gLlEsi7ldaDcQsvVZfoc+3kpxdfCOY/Y58FfKRX7sQ/e/qo7jDJPncX+8Uf/8U8hfv233AXxDbduhbh/zPT0JAmOUdfB8WWRXj2kcTC3XIX42PFTxjH4XCPyq0Qxjte2j30oXzKvoVfHftxc1Zm3NznPkIhIO3HX7lmLpG8/RBp6EZGHnn8R4nPkxRoq4fjq97C9+ijnT75s5ro6dwHn2aOn0W/xxNNP4ufn0ANT76Tovl3sP2+8/UaI33ZgF8RkQ5Jcxux/52fRK3JuFutda6DH78gL6Fc5/MTDELM+XkQkM7EXt2EvSQvnPOFcH545d5uejfXjptWhl/iRiLXaRc5NU3vOmJ4Nnw0VlA+Lx3ihiH5FN6ScQYHpzUzoGJxbh62o7NlIyxRh0URicy4ZIo6v7NmwDHMdxhFdS8fGvmFRHTIpvxUkzuVziBh+FfKBpHmAbM7N4ayXefWODf1lQ1EURVEURVGUHqEvG4qiKIqiKIqi9AR92VAURVEURVEUpSdck2dDLEdkVUdmWbjmuWumwJCOjZpWj/T/2yZQO3zyHOpn/S6uYx3Fpka7SjkG5mmd4LJDujdjPWRTXLdMQrQZn3welIfDSa6cb4Lf6jzKU3KR8oEsk365QXWaYg+IiFTII+MsooZ3zEWN9J1bce3y3VvNi1hoox+gu8H34aesZd5LqsE58YOVPuN3UV/bbJnbX/x/2XvzKMvK+tz/u4czn1Pz0NXzCDTQNAgICNokGEFj1NwkGmN+aoKJQ4wY9ULuUhJdmpXBmHivN8m64o0kV6MmGs1gNChRUBBkHht6Hqu6q6qrTlWd+ey9398fVV1dz/PurgE41Y1+P2ux6G/VPnt497vfvXed53mfInoyBsfvgnr0WBHqFYkLoO4mPe0k5XKIiCSOoYY+SfOIHwl3QX3uz66D+kRkr3N8EPtw7wCe14sux96UzuF5HR3FbA8RkZER1Arn8qjF3rp1NdRtq7FBTYjtHTbtoePYUbxey2OUcUBepmIJ/QlHt+Ic9SIiuQLOUz80esp3U68sr15ZRCQhoSRmrk2XPFBpz75+DOl0jaWZxd+nUnguk+TXyVAGi4jI1BReo2GI5y6dxXUGlIuw6VzskyIi52zrh/qbX8Fr5+v/cA/Uryqj7+Oy6+x1Ri72h4Azj2hc5Tnhh4fRCzBVsr1xa9atpWVwDDw2jLpyn/apvdvu124C+2BpJv+pVlnejAMRkQeGipLOTbdbvYbbHzpuezayeIuVMcqS2H8MdfcrC+hb+29vQB/V+du2W9tIZnAs6R5A/07feedC/TN03+jrsn0gHRk6Lxk8kFQa+3SO6kSMxr5Ux/Yao5ypoSL2p7t7cTyqki5/8ISd82I88jiOoT+FY70yWWxv49reQ35GmavDZ01+q6mWqxI1Z3yTTXxm4eciEZGwyc9sOP5x9oRHx8PxWUmJyZZIoS+Gs3TE+swCwURiey5cl7M67M/Mt/z0XlBOBj3jubQjLmVhebTOjG+PVb5Pz7v0DBM0OQ+JDyTOh0b7PccXErInZx70mw1FURRFURRFUVqCvmwoiqIoiqIoitIS9GVDURRFURRFUZSWsDTPhnFn50mu0/zvcb4FzpYwDdSD5WlO5Z421PeNjaCedIr0pSIiE6T5u5e8D50kKWsjr0kuxrPRdPFDkwFlXJDWjtfgxehFk+Qdydqfgsp3UCeXpX2KmrZfokGC0AztZ3uePtPE3JLSuC1EnGzD9nKCU+071VxezXyxfFzqZlqbW548Br8Lq2V7+RLmOkQ19B20Z0lfO7EH6lwXzYEek3GQSKPmtq2J+mO3H7XGnb2oLW5rt/vfoWeLUDvUN8aOY/+qBzhffP8K9F+IiBw+itfriVFsL5PAa68Pd1NSKdzPOK9TnfJmhnZh/8olcKXnXLwB6hJ5OERERsfxHCVSp/ocz0u+HASNmpy0iQUN0hfbcmvJZtHHkaB59D3yDCTp96zJZp2+iEjEnrIQr9mgjr9vNkm7Pm5rz696xVaor7jmMqjvu+spqPcfxJyWFYftnINUHq+V9vYuqBuk756cxD46Rdk6W87fZG2jowN9aG2deFKKE9gneS77tVtWWeusVfB6qzSm96tu6dFbT3G8KKmZfCOKYhIntPXWSQf7U4PydlZ0Yf9avfliqDduvxzqQoedxcQZBG15HBv6u9GzkWQ9PAchiJ1J4ND9MmSvQoh9uhHY63RJv55N4nXS347X4hWXYZ9P5Tug/vf/utPaxqHBg7hbEd5zAhoDXY+8r2LnbLictzBn7GUPWKupl0tiGtP7E1Tx2BxL/y/i0XkMQ+y07CkwNDb57H2Iscca8rkFhvsCbtPErYQI2VtH/W0hqwz7zUREItouPyVmfXrmS+DybVm8drPkxRMRcek50ydfB1+rhq69uHwQ9tUkkqfqZhDK7iN2/l0c+s2GoiiKoiiKoigtQV82FEVRFEVRFEVpCfqyoSiKoiiKoihKS1iSZyOMzOy8uobm13W8GJ+CT/rjKmlKSffWl8PlH37iSahPDOIc6SIiAeVqjJAubpJyOLKkK8zGaNRSdCyG5rpn3Rvr130fdZgiIiFp4yZJXxvQ3NCspUty88Z4NiLab5cmqY5oDuViqQi1Z+x1plzU6DrRqfYuLbNnozp1XCSc1i06HvaFRMGec7+dTm59H/onCr3YHs0ezKJwEqgpX9l1obWNI0fROzKxG30H5686H+p8Hs/JmtW27vvEIO7HvqfxM9VJ1GV6WdSyJzOopRUR6V+Jx3LsCPo86hF5XjiPhubabuuwNfkbNnVCPbLnMNRBEzWmk2OorT02ZGs/62ER6u6ejtl/hyxaXwYq1UDMTH5QM6D+E9hjYKOBfTCbYQ0zXUOk9fU8HN/Chn3NNWlcrZSwXY4fRU9GP+UHdLZ3WOuskHZ63bZeqMdrWCd9PPZSjIy36eJ+JTNYh+SN81N4vfavQi/S+o12H+TsH576v9HEa2diEq/XXN7OSsmkab+y0+N7IMurlxcRWdGWlfSM17FJfafpdFjLp3L4s0Nk+Um2Y194+SsuhbqLcjeaMV6IyMyfCcV9o2DbEix8ug5czmOwtPx0oiP7OjHR6fMqpn+AZUcb3vvO3YQes6efHbC2cfQoejYC2g/2CFna/hgvAPsy5i4SLbNvLQpqEs34LLrIz+n7dt+o0xBtIjz5CfKsJOnZKUntFUb2s9UE3QfSCcrzSWMbNxq4n0HTbnS2wrCHg/sOe4o8z15n0icPLeVj9VPeTDtlzaST5CH17fsNP4vy/YOfTXl5x7X32yMfiDfnWqw3AhHZI4tBv9lQFEVRFEVRFKUl6MuGoiiKoiiKoigtQV82FEVRFEVRFEVpCfqyoSiKoiiKoihKS1iSQdz1E+LOmG8S5CNxYoxNDplThMxMYbkE9UABDYHdCVw+UbONr21k+qqRUcylOiATUzkmFKfKx0Jmbi+Y3xzkBrbplw1FhkL72KeeoLCbBLVlhg1xIpKnH+Ucaj/LS4Y/qMcE49Epkqx76hw1mstrkKyN7xKpTRucvBQ6HeuOvS/JAhqwBi5YCXWTDO5BChswmsAQv8lhNGKLiJSK+LPqEPbRJx7YBXV3G4XsJNCAKSJy5bV4Hazf0A91Vy8ee1sfGmUz3TFhPy6GnY0eRbPj8BiavKLUIVxBk4x5ke3yTGbxZw75dwt5CkqKpqAulWzDd0Cm4nT6lIG3Xln+UL+JyarUY0yyIiJhaF/3lSoFgEZ4PHUa09jQl0rjuUwmbVN0qYKTIzRpfCp0odH1qh1oAl673ja6ugncz0IXBrBefDlOfJBNYp9ta7MDMOtCx0qBhg4ZHlNkDmXzbK1hTwrRbOJYnc6g4btQwLZIprA9vaR9S2zU8Xo7+ZkoXP6/1a3vbpNsfvoYwgj7WzHGoFsh8/+WTpzEYdOl26FetWot1A1qT8+zZ1Sxbv30gyjiQDQKHouZXMajv4NyQDBvZCGzdxwRB7fRfqYopbONQtQ2r8W2EhHZu28f1EfGcKYE41OonzO/YVdExOVw5Dn7uXA83QuLI83ZyUJ6u3C87+22zdsRGeRdoevNnf8R1D5Hdh9vq+B1kEjhWMXtV6/hPjXsnNQFDeFcc/BiMmH36UySQq05pC+DY6hnTYpAz7Yx1yK3p+vyOaHJj/hCiR3S6DNz+5+z+Ela9JsNRVEURVEURVFagr5sKIqiKIqiKIrSEvRlQ1EURVEURVGUlrBEz4Ynrj/9Ec/Qe4qJ0TFbng0KgSEtXd5B7d0rSGM/UbE10Y8cwnCyUUqRqZEOs04qx4j3UUQiegcLaR0uGVRYZunGBKMwHnkuKH9PMqS9y5L2ruDber2Ci+egmw4tSzuaEArZitlvE1J7ztGY106jXW8V/RlfMjNBN5UUBSmK7VMwpAFPdqJmvDGO+u3KMH5+fCeGoSVLtr+ird4NdUBazbrBPhuFqMscP27rzqea+JmNGzB4q06BjmOHcT/dEh2IiKTJ0LNhA2q1+1ehtn28hnrSkRH0V0QNu729JJ6T7Vesx9+H47gOIb9LYHuyHDqvc0OH4gKIWk0kSYlkWquc4PBOSx8rUirjMYUkEC6X0CflUZ/t7KBAJd9udyHfQTqL+7GCfAi5HjRiZQr235zCiManCLfhd+I2cqSTTvj2uNqs4rG7IfaXgDxUk1MYuFentmOPh4iIT8fKt6VUmo4jgcdRrtgCbtfFz5Smpq/ZejVG7N1iuvNpyRWmr9VmA4+1VLH109kL0Z+zpge9NOdupHBGuve5FJCWiDEJJMhaQ1YHy9PoO3w/tddp31Npv+bxMYiIGIkJ9aPmadIPDK3TEzyQXAb7wUXbtlrbqJMG/o4fPgj18ASO9y6HsMV4MdmZAb4OZ0mPcM8fY2YDX326/rgWEUkkcLxKeOw5mz9okUNPObRTxPYpFNrwHhvRPdih8ypWLeK45LWzTMnznBOxz6uI/Zd9XsQK2KO+YAf22fcbDo1kz4bjsKeDQ/3iPFn8rH9qGd+noO550G82FEVRFEVRFEVpCfqyoSiKoiiKoihKS9CXDUVRFEVRFEVRWsLSBH/JtEjypAYMtXMOz3MtIkK63SBAfVdEm2d/wABK7+S121dZm+hPoCh3z3Gc1/p4Gbc5HlAuR2Tr9ep0KAHNJWw4y8MjXbUXowGkOkEaU54iPcfz7dM2UzG5Em0e6gw7ydeRo3mb06THZa2tiD1vfWVOdkd1mT0bXUGH5IJpvXx9ALXHw0eK1vLDR45DHWRRY+032qF2j2L7pcdIH+raGQcS4H7kNlNWzCY8zx5tU4aL1iqP7cP9DsfR29C3gfab+nCmbucmjE2gNyARYo5Gdz9meazowhyFsHYU6sNHcR9FRDJ5PPbOXmyvoIb6XZ8F4KP2GFKfwHPSrAVz/r38ORuNphG3Ob2fAV0b1aqtXy2X8dylEjg3vefnqMbPG8rbqQf2MddDvA6bDTzXrF9PUdZL4Ni+oQa1bVjHbdTLeC01PJrrnv0sIjI6hl6irs4OqCO6h4wOjUBda+A2egYwO0ZEJCRd89jkOC1BfgFq8KFBXt7OXwhnsgMaNdtD2GpMWBcTTLd9jfI/MjFz+1+wGbMgVnbiNZghbTrP3e+xVj3mNu/SeeOPsH6dnxVMzGUckR+LtfwBZZywtr8Z2jtabmAfLtWw/arUx0ODfaNK114Yo5kfWL0O6u7OA1CfmDwMNbevE+N9dQw/Pcyp47yyLcRxXXFm/DP8nJNM2u2RTpNPl9qM/Tyco8Hn1cTkbGQT6DdMUB8OaB0OeVtjYl5ivAzkn+AnuvljYKZ/xNl0li+J/BaWqYN2lHOIYtfBHg6uKcsjJrtDDB/7qTru2j0d+s2GoiiKoiiKoigtQV82FEVRFEVRFEVpCYuSUZ38CnOqdkomEDYWI6Oirz5pWtqwQd/B0HcyEUm1Sry82FKeOn3l3aC6yRKpmP0OFliGP8FfI/M0fCL2t2zWV8n0kSatg6des6dis4+9Rt84JvirZf6qOubVM6TtmDntXZlZH3/F/UJzcv2VObKFBk1RWa3akoZaDWUtLIfjWdu4f9a5v7kx3xnSNLR1lhfWSEaVwI3GTeXXDHi6P5pOt4afCSLaZtVeZ52nhK6QBKiM7RfQdIE1mlazUbXbwvV4bkmSOrA0h4+TO6yIRCQTqFdOfaY+sw+t7n9ztzF3ulPXuqpteHpU0+TrHtuAFZg+/YAlPSIiNUtCQtIDaxpQks7ETLfJ55dlVA0+Lvr6PWRdqIjUSXZUo3WwjKpB12+DZGv1mGveC9x5l6nRuOF63AftdZ5eRjW9P8vZ/yqlU1NQV+jYKnX7mkyQbK/s42dCj2VUJAmmvuHFHGqDfsh92JreNU5jQnCf5GlAeTrOk+fkJHEyqgrJqMoso2rML6Oq0XhVadpTddcqOK10UEeJYtTk6ZtxGzG3dVuyM6eOmtPrX657cGPO9NRWX4gZR3gq1dCS6fAUxvPLqOpNu49HdF+PzEIyKuqPrr3ftoyKl1i6jMr62QKRCQvLqGKm1+V1LPT75ymjqjUWPwY6ZhFLHTlyRNasWbPgypSfTg4fPiyrV69u2fq1/ynz0er+J6J9UDk92v+UM43eg5UzyWL636JeNqIoksHBQSkUClawiPLTizFGpqamZOXKldYb8guJ9j8ljuXqfyLaBxUb7X/KmUbvwcqZZCn9b1EvG4qiKIqiKIqiKEtFDeKKoiiKoiiKorQEfdlQFEVRFEVRFKUl6MuGoiiKoiiKoigtQV82lpHbb79dOjo65l3mox/9qFx88cWz9dvf/nZ5wxve0NL9Us4s1157rbz//e8/7e/Xr18vn/70p5e8Xu5Lyk83C/UzRTmbWMy977mOjYqiLC8/0S8bi3m4P9v40Ic+JHfeeeeZ3g3lLOKBBx6Q3/7t3z7Tu6EoinJWoWOjcjahf+A7PYsK9VOWj3w+L/l8/kzvhnIW0dvbO+/vm82mJBKJZdobRZmm0WhIMplceEFFaRELjY2KopwdnNXfbHz729+Wa665Rjo6OqS7u1te+9rXyt69e0VE5Pvf/744jiPFYnF2+UcffVQcx5EDBw7I97//ffmN3/gNmZiYEMdxxHEc+ehHPyoiIuPj4/LWt75VOjs7JZvNyqtf/WrZvXv37HpOfiPy7//+73LuuedKNpuVX/7lX5ZKpSJ/93d/J+vXr5fOzk553/veBwmXC633JN/4xjdky5Ytkk6n5frrr5fDhw/P/m6hN+MoiuSP//iPZcOGDZLJZGT79u3y1a9+9Tm2sHK2EASBvPe975X29nbp6emRW2+9dTaVk6UCjuPI3/zN38jrXvc6yeVy8kd/9EciIvInf/In0t/fL4VCQW688Uap1Wpxm1J+iomiSG6++Wbp6uqSFStWzI6JIiKHDh2S17/+9ZLP56WtrU3e+MY3yvHjx2d/f3Js+tznPicbNmyQdDotIiJf/epXZdu2bZLJZKS7u1te+cpXSrlcnv3c5z73Odm6dauk02k577zz5K//+q+X7XiVs5+F+s+f//mfy8DAgHR3d8vv/M7vSHNOkvzpxsZXv/rVkslkZOPGjXp/VJZEFEXyZ3/2Z7J582ZJpVKydu3a2XvsLbfcIuecc45ks1nZuHGj3HrrrbP98fbbb5ePfexj8thjj80+c95+++1n8EjOMsxZzFe/+lXzta99zezevds88sgj5hd+4RfMtm3bTBiG5nvf+54RETM+Pj67/COPPGJExOzfv9/U63Xz6U9/2rS1tZmhoSEzNDRkpqamjDHGvO51rzNbt241d999t3n00UfN9ddfbzZv3mwajYYxxpjPf/7zJpFImJ/7uZ8zDz/8sLnrrrtMd3e3edWrXmXe+MY3mqeeesr827/9m0kmk+bLX/7y7PYXu97LLrvM3HvvvebBBx80L33pS83LXvay2XX84R/+odm+ffts/ba3vc28/vWvn60/8YlPmPPOO898+9vfNnv37jWf//znTSqVMt///vdbcAaU5WDHjh0mn8+bm266yTzzzDPmC1/4gslms+azn/2sMcaYdevWmb/8y7+cXV5ETF9fn/nbv/1bs3fvXnPw4EHzla98xaRSKfO5z33OPPPMM+bDH/6wKRQK0JeUn2527Nhh2trazEc/+lGza9cu83d/93fGcRxzxx13mDAMzcUXX2yuueYa8+CDD5r77rvPXHrppWbHjh2zn//DP/xDk8vlzA033GAefvhh89hjj5nBwUHj+775i7/4C7N//37z+OOPm7/6q7+aHWu/8IUvmIGBAfO1r33N7Nu3z3zta18zXV1d5vbbbz9DraCcTczXf972treZtrY28653vcvs3LnT/Nu//RuMi8bEj43d3d3mtttuM88++6z5yEc+YjzPM08//fQZODrlxcjNN99sOjs7ze2332727NljfvCDH5jbbrvNGGPMxz/+cXPPPfeY/fv3m3/91381/f395k//9E+NMcZUKhXzwQ9+0FxwwQWzz5yVSuVMHspZxVn9ssGMjIwYETFPPPHEgi8bxkw/3Le3t8M6du3aZUTE3HPPPbM/Gx0dNZlMxvzjP/7j7OdExOzZs2d2mXe+850mm83O3kSNMeb6668373znO5e83vvuu292mZ07dxoRMffff78xZv6XjVqtZrLZrLn33nvhmG688Ubz5je/eTFNqJyF7Nixw2zdutVEUTT7s1tuucVs3brVGBN/Q33/+98P67jqqqvMe97zHvjZFVdcoS8byiw7duww11xzDfzs8ssvN7fccou54447jOd55tChQ7O/e+qpp4yImB//+MfGmOmxKZFImOHh4dllHnroISMi5sCBA7Hb3LRpk/mHf/gH+NnHP/5xc9VVV71Qh6W8iJmv/7ztbW8z69atM0EQzP7sV37lV8yb3vSm2TpubHzXu94F67niiivMu9/97hd+55WfOCYnJ00qlZp9uViIT37yk+bSSy+drfn5TTnFWS2j2r17t7z5zW+WjRs3Sltbm6xfv15Epr/uf67s3LlTfN+XK664YvZn3d3dcu6558rOnTtnf5bNZmXTpk2zdX9/v6xfvx78FP39/TI8PLyk9fq+L5dffvlsfd5550lHRwcsczr27NkjlUpFfu7nfm7W25HP5+Xv//7vZ+VlyouTK6+8UhzHma2vuuoq2b17N8j05nLZZZdBvXPnTuh7J9ehKHO56KKLoB4YGJDh4WHZuXOnrFmzRtasWTP7u/PPP98am9atWwc6+e3bt8t1110n27Ztk1/5lV+R2267TcbHx0VEpFwuy969e+XGG2+E8eoTn/iEjleKiMzff0RELrjgAvE8b7Y+2V/ng8e9q666alH3V0XZuXOn1Ot1ue6662J//5WvfEWuvvpqWbFiheTzefnIRz7yvJ5Hf5o4qw3iv/ALvyDr1q2T2267TVauXClRFMmFF14ojUZj9qHfzOjaRQS0nM8XNtw6jhP7syiKXrBtLkSpVBIRkW9+85uyatUq+F0qlVq2/VDOPLlc7kzvgvIi5PmOYdzvPM+T73znO3LvvffKHXfcIZ/5zGfkwx/+sNx///2SzWZFROS2226zXoTnPkAqP73M139Enn9/VZSlkMlkTvu7H/3oR/KWt7xFPvaxj8n1118v7e3t8uUvf1k+9alPLeMevng5a7/ZOHHihDz77LPykY98RK677jrZunUr/MXj5F/XhoaGZn/26KOPwjqSyaT1l+GtW7dKEASzg9ncbZ1//vnPeX8Xu94gCOTBBx+crZ999lkpFouydevWBbdx/vnnSyqVkkOHDsnmzZvhv7l/kVRefMztNyIi9913n2zZsmXRD2Vbt26NXYeiLIatW7fK4cOHYbKKp59+WorF4oLjouM4cvXVV8vHPvYxeeSRRySZTMrXv/516e/vl5UrV8q+ffus8WrDhg2tPiTlRcLp+s9zhce9++67b1H3V0XZsmWLZDKZ2PiBe++9V9atWycf/vCH5bLLLpMtW7bIwYMHYZm4Z05lmrP2m43Ozk7p7u6Wz372szIwMCCHDh2S3//935/9/ckH7I9+9KPyR3/0R7Jr1y7rDXP9+vVSKpXkzjvvlO3bt0s2m5UtW7bI61//evmt3/ot+T//5/9IoVCQ3//935dVq1bJ61//+ue8v4tdbyKRkN/93d+V//W//pf4vi/vfe975corr5SXvvSlC26jUCjIhz70Ifm93/s9iaJIrrnmGpmYmJB77rlH2tra5G1ve9tz3n/lzHLo0CH5wAc+IO985zvl4Ycfls985jNL+ovJTTfdJG9/+9vlsssuk6uvvlq++MUvylNPPSUbN25s4V4rPym88pWvlG3btslb3vIW+fSnPy1BEMh73vMe2bFjhyXZm8v9998vd955p7zqVa+Svr4+uf/++2VkZGT24e5jH/uYvO9975P29na54YYbpF6vy4MPPijj4+PygQ98YLkOTzlLma//PP74489pnf/0T/8kl112mVxzzTXyxS9+UX784x/L//2///cF3nPlJ5F0Oi233HKL3HzzzZJMJuXqq6+WkZEReeqpp2TLli1y6NAh+fKXvyyXX365fPOb37ReitevXy/79++XRx99VFavXi2FQkFVJzOctd9suK4rX/7yl+Whhx6SCy+8UH7v935PPvnJT87+PpFIyJe+9CV55pln5KKLLpI//dM/lU984hOwjpe97GXyrne9S970pjdJb2+v/Nmf/ZmIiHz+85+XSy+9VF772tfKVVddJcYY+Y//+I/nnVWwmPVms1m55ZZb5Nd+7dfk6quvlnw+L1/5ylcWvY2Pf/zjcuutt8of//Efy9atW+WGG26Qb37zm/qXwhc5b33rW6VarcpLX/pS+Z3f+R256aablhRW9aY3vUluvfVWufnmm+XSSy+VgwcPyrvf/e4W7rHyk4TjOPIv//Iv0tnZKa94xSvkla98pWzcuHHBsamtrU3uvvtuec1rXiPnnHOOfOQjH5FPfepT8upXv1pERN7xjnfI5z73Ofn85z8v27Ztkx07dsjtt9+u45UiIgv3n+fCxz72Mfnyl78sF110kfz93/+9fOlLX3peqgXlp4tbb71VPvjBD8of/MEfyNatW+VNb3qTDA8Py+te9zr5vd/7PXnve98rF198sdx7771y6623wmd/6Zd+SW644Qb5mZ/5Gent7ZUvfelLZ+gozj4cM9f0oCiKoiiK8iLEcRz5+te/Lm94wxvO9K4oijKHs/abDUVRFEVRFEVRXtzoy4aiKIqiKIqiKC3hrDWIK4qiKIqiLBZVhSvK2Yl+s6EoiqIoiqIoSkvQlw1FURRFURRFUVqCvmwoiqIoiqIoitIS9GVDURRFURRFUZSWsCiDeBRFMjg4KIVCQRzHafU+KS8SjDEyNTUlK1euFNdt3Xur9j8ljuXqfyLaBxUb7X/KmUbvwcqZZCn9b1EvG4ODg7JmzZoXZOeUnzwOHz4sq1evbtn6tf8p89Hq/ieifVA5Pdr/lDON3oOVM8li+t+iXjYKhYKIiGy/art4viciIk6EU8w5YWR9jmehS+eyULe1tUEdRbiOUqkEtevY09qlEgmo65UKbjOZhjqZwLevVM5ugqSfwnXWA6hrtSb+vlGFOu7NP5fL43ZTuI0gxHU2GlinUngcYycmrG0MD49C7dFxOB62lUdvos0Aj3N6PxpQF4vF2X9HUSSjx47P9o9WcXL9f/CJP5Z0erodVvdh3/GDkvW5tIdtuHblAP4+2wP10BSet+/96HGoy+OT1jbyhQ6ov3OiC2rvvGugnnr4q1Dv8B+z1vmWN/0q1NUMbsNEZdwGXcbjo0Vrnbf/3y9APVnE/nPTB94L9bp1a6F+5JFHoN64eZO1jQz10Vwuh/s1Pg51uYzH0dvba62TP5Occ92Uy2V5zS+8ruX9T+RUH/yf33tWMvnpf5vQvl4YHgt4BHPE4R/Mv76f4Jk9l2XaUtqEMXjPaYp9HwvoXifN6bpWnpLff+3Fy9r/2p34+4uI2DdcERFa1lngr4+87sX8tXyh88brfC5/GV9oHVxHMZtYqHfxcSx1my8E/AwUt19hGMLvivXmst2Df/Vj/yTJ9PRzXGRCWCa2NRxcJiTlvhF8JknQWXLLx6DONoasTWzfgg+5E2P4HHTf/fdD3ajh81pnZ6e1zpPPGbP7Rc+Z6TQ+W5177nm4vI+fFxHx6PnLHszx3Fv3Dus6s3u0687fJ7l/ze1LcXXcdufuV7Valfe9732L6n+Letk4uXLP9077suHGXHg8Rvs+bo5PIDcELx/3spFI4DIhb8Papkt1zMuGtV94bGFIF3+E63BiTjhvJ5HEbTj03MInmNuK20ZExPO8eWtngd9HMTcNXibu5tPqr1VPrj+dTks6kxERkWwWX1z9wL5IMh62UZ5edjP0MDxJ5zmdzkAdpPDFK24ZP4Xb8DJ4EXr08pvyk9Y687RfXhZfVPl+5NNl3KjY+7lQ/8lRexbyuM1sBo+T91FEJENtkad1NJv48sfw8iL2y26KBnmR1ve/udvI5AuSzU+/6EYteNlY6FD0ZeP5bgTLiF42/NiXDfpZc/6H0lZwchuO4yxte/zysMBnrZeNRWxrobN2Jl424p58F3zZeL7bfCGIWaf1iDlnmZM9c7nuwcl0VpKZ6bE/ip7Dy4azwMsGjQFuiPellGs/xGfo3tWo4n2I7338R6Jk0r4H88+45j8WZ+j+mExgLfLifdngzzzXZ0A1iCuKoiiKoiiK0hKWlCBeb5TEi6b/0p2ivxrH/1Wc3igF35rKlSmoEwl8e8xkWc6EX3+JiDg+vlHl2/Gvo0mXDjFq0O/tv2S15fHtuVoagdqlrw8zGdxPe40ijYD+2kxlNotvwo7L3/fjWvMFfJsXERkdxbZgWZTHX2HSOYv7y/N83zbFfeXbSi4695xZaU6CztvwYM1avqN/FdSR1d2xPbo7UJr12uuvg/r4kUFrG0cG8WvezSQlKiXGoO5fh9sIh+w2/+GP74E604NfE5+zCbWz+c4OqO/Z+WNrnXfddRfUDp2779xxB9T/7Zf+G9TbLrwA6lo15lqkv3QlPWzfAvXxPF03uaz916Ckh1K3ZnPOhRPM/01JK/A9R3xv+jqLFvO3moX+krzA8vz7mOFqESs9AyziSwpjaZrm33Fr+UXA3xzxOozBc+jG3cdov6KZjwQL/BWxFcz7zcZz+Os2N7lVL2ITC36zQbUXu9T8nzLc1gt8Yxi3o8/3bNnfnthH7iyxNQw1+GL+QjxXbeAsc2K6I4E4Zvq5wjULD0Z8PfHRRfRMSLcMSabxmTDh2/eIb93xLaj3PoXSZJbrOg4pUZyFx/GA7jUsIVt534+gvu66n7PWceEF26FuNFmBgO0ZBFjz85bHjRXzmYCeARf69pifbUXEOmmNOdtohvV51wfrXvSSiqIoiqIoiqIoS0BfNhRFURRFURRFaQn6sqEoiqIoiqIoSktYkmfDSDirSOSZboO6rd1Kp2lmngg9HJkM+it4KtwSae0aga3LT2VRI59JoA7cI4lavYqatLgZriaKqLOPaFpant2gSZq2OC0dz+rk+1jXG3hsvM0oJN1wjFwylUJ9Y1BFvd5CHgvW98V9Zq6mdLnDfVb1ds/OkhTSjBJB1e4bjov9jyYRE8fB85ij9nOob7RvtOeRXruyD+rNCZxG75kTeF10rkXvQ37Evm6GhtAjVKGp/MzqFVCnUqhjXbNug7XOdWtxKtt6GacK3rbtIqhrNZxCOpPCoaKQtWcFCQI8lsP790Cdy+PMXDzDR7OG17uIiEeC0SA6dd6daOHZoF5ofMcRf0Y/Hj0HvfXzZRHy4rPCs7G4XVhAd89Yno6l69UN7xmPCTFdinXx0cz5PxOejfl4Ifqf3aLWoBmz3YWm06Wa/sa5mL2OFvJo8DZj1vpCX57x61tin1zApxS/3Tn34CV/+vkxd/yLc6xYP6GFPPIluA76FiaHD0K9d98TUJ84ssvaRjA5DHWBfB75HN53Gk18BozzMQQ0uyU/vwn5E/fRva70L/ZU/LUa3h/5nsszREYRPgPy9R3Gxk0sfGywTvLd1Mr2fo+O4/Pw8Jzn43rMc//p0G82FEVRFEVRFEVpCfqyoSiKoiiKoihKS9CXDUVRFEVRFEVRWsKSPBuZdHY2QbxJ+jOX8ywkTkNK8wT7+K7DcxezZj6Ts3XinF+RTLDuDddR6GiH2vdske7gUcxOSFEqtEv5IQ7PTezZ2kWPksubtN/lEmrlki5qBBPsRfHt98Q2yhhpBLjOegPbfzGp5KzJmxtLH5c22UrCRlWCxnS7VCqY85BJ233DpzZk/aLj4vE3qugZmBgbh7q/D/0ZIiLpLG6jO41tuCqD20hT14gK51jrXN2DORoT5EeJ6th3AjqvF1yIWlARkZe//OVQ93SiP+r6G66Het8+1KAeHxyCupC1k7yrZczNGRvH9mvvQD8L+258nxJWxfYRVeZoSisxWR+txnNPzQVv271aP+f9T/Vfh1ogUOd8qCjGt+aGfF+avuYXkzPwQhOJc8qPsIj24EUWTMW2VoDXpBvjR+QPRSEvg2MkZ0j5Yt9HLG8N7Wdkaf/5HMXp2edvMDt9eSFPVsz1voB/xZLQz3+YsZsxUevHmdPhO9P/iZzyLs0S074cNu076EPY++T9UO97/IdQV8aO4yZqnE0h0tuJzz39fQO4zTQnimN/nJqatNYZhJz/gQfSaOK9J6Llx4v2Ov/tm/8K9ZHBo1Bv34Y5HO3tHVAn6XktzjJmDOds4PPbeHEC6pHj6A8dPmZniY1T+9Tm+InjstlOx0/1vUtRFEVRFEVRlNahLxuKoiiKoiiKorQEfdlQFEVRFEVRFKUl6MuGoiiKoiiKoigtYUkGcd9Pz5qII3pNybVlrOWrZLit1tDoysYch5xQEZtdYkK8cjncriGzWYbCxzwykIcx71uFHjYC42emJtF4bVwyXseY6JoG9z0kU3lPfw/USTLVRRTgEvEJEJFmg7YRcqgfBaQFbNC1u0OjgYasbPaUWT6MMVO2kseffkyymenzXS2TOTiwDYEZCulrK3RA3dWBhqzqJIbXHN6LAUJOTKhkLouTB2QSJfo99k/Px/30O7qtdSbyeG5rh/ZDPTh0BOps5yqox0u2ie7cc8+F+oafuxbqNjKjdXdjfzx+5BDUxRHbSNZG16JLfbwyWYQ6Q23TqNoBQRzO5ZzhUD/XccWdMYEaNqXGGsTnN50uBC8dawq0llrAQPocjO18HsxzMsM/P4f3okLZFjDg8n4bCucKG3YfbNaxnzl+cmbZxZsjXzA897QNEfvTBQzhrkNhZWQIdxJ0//TtiTi8Ao4VK7a/DOpcH06CcXSMngNGcTwTEXGP74TaH8cx0Gmg0ZWDdaMwxujvsBGd24YmEFmwvz2H/kzbsK+jmGA8y0Uezfnd8uK6nngzE6/w8xk/s4iIeCHep5999G6on7zvu1DXSmhY5kcMX+xJRBwX+2R3bz/UhS4Kk6XJdSYmc9Y6K2UMtc3lcRl+tuIw6bgsvSKFVFeqOKHKI4/8GNdJodg+mdR7urusbfDz7jAZ7AeHMCB4fAKfFWoxz8Oej8eWzpyaZMnx7WeN06HfbCiKoiiKoiiK0hL0ZUNRFEVRFEVRlJagLxuKoiiKoiiKorSEJXk2xEmIONMfyedJxxUTyMWhcc0IdXAJn4NSSC/LQT4cnici6Qzq2jhssEzBX+UarjObx0AYEZGIAgrLJQqQa8NgwEoZtf4SE7pTaEPdYJ28EOyN4ACiZBLbu16z/QPpDC4TkR7ZozBC1h3yNkREUin82dwQl+UO9Tty9KCk09P749N7cjZh73u9jPvnsj6W9LM+BS96JEFlD9I0uA2TwPPYniaNLmmiTcr2OnlJ7H9r1q2DOtuGgXySpr41ggF8IiIvecmlUBfaOqAOye+zcgB1r7XJ9VD7MYFmKWov1iM3AmyrhI8fiO1PLH6ds91SOe58tBjXm/5PRAyNR77EeEh49xcI/WI4ONCLCc4KrcCzpfkpHLHPpe00Yc8Gwtu0A9BiAuT4cpx3L2OIOUz2CVlnxGPPAi7frKPnSkSkQUNtKp08zcqXgTnXQ1wbMwsuQcGnJ/0oJ/Fo/M8Weq1VnHvdG6Fuv+RnoD5xDHXi6QTeo6uFzdY66z3op6uThyN9+B6o/Qr6PkLH9t64BsdVN+KxGT04UUwwIBJroMIl7JTEhdYQs0oOoz01hjhx5oAW4jq+uDPPgDna+7B23Fr+qYfQo/HEgz+Cujp1AmoTYZs7dF/3Y+6XqRz6KTZs3AB1Z08H1B75lDj4WUSkSs+NDQo3PnwU+1uFnhFX9eH9U0QkRd6HRo6CsWlAnCBP8859e6HevHmrtY32TvRPDR3HYN2RcRzf8m14PXfmMXhXRKStHZ932+c8f9RrNfmOfNn6TBz6zYaiKIqiKIqiKC1BXzYURVEURVEURWkJ+rKhKIqiKIqiKEpLWJJnIwgjMTM6RrI1SC0mg8A1pIFs4jJ10n0nSI/nJVE/mo/xVzjCum/aMdZVk058oohzHYuIOCFq6Wol1LkVCrgfXXnUtDmRPfewxxkXJE+vVLBtyjTBdEc77rebiMnZoO1myFdTKeH5cGjSfs7dELHtJ3MPI1rmSb4vvnDrbG6FpWXn+eLF1rOmUqjtdCgfpb0Lz+Pmc3F+eD8R40siY0eaLgz2FBnKeXH4QhKRhMFz6+TRk+HkcH7tE1O4/AXndFjr7O3GPlslj0a9im2Rb8Pj2rQZddVhxfZXeKR55hyKkM6HQ9d/FJfbQss4c/JqJqds/W6rcYyZ7VcO/a3GMQv/7WapCmuyGEijFDNe0ULJDLYLtzv7RswitP8L5Wq4rfi71QIRBHF7zR+xMkjoHBmD95hqGfMbRERqFdRjpxIznwnte16riaJo1qvhuktvc9s3g9ecG+G9z3coqyhjt3pPDTN3kjtRp1+dwHWek0LP2ZRn5xwcjnAsGQpwzCv1Xgt1uoGejuTYM9Y6E3W8diK6iQR0s3MsU84i8mysHI354XMYRQv5RGJ2YxlJudP/iYg0xtGrevf3vmotPzWC+SjZFO58Jr0C6hzd6zKUb+HG+MsKdE/tJ79EJofPQZkkrjOdsrNj2smn0AywP3bv2wf1ob1Yd3aSr1JEknV8fpiYRA9zg56PxydxLBqjZ9XN55xvbWPN2vVQ/+j+B6Hu6FkL9eo1WHd12J6sPJ0Tf84zT6WyeN+kfrOhKIqiKIqiKEpL0JcNRVEURVEURVFagr5sKIqiKIqiKIrSEpbk2TDGiJnR/9YbqMPMpmw9+0l9/UnCBCoYXcp98NOobz82gvNzV+q2PiyXRW1cOoH6u6BZpd/TIUe2Tpy15JkEzSdN2ro86fIbVduz0aD8D4+8I2nWWZN+nZWK2VxWmFod96utDXX65RK2ZyaN2kUT2e+eIelYQee6zNrRc9dtlMKMhpPbz8TMN27pYS1NPa4jS+fR7cHl4zwbSZ/mbg/Jh8AaXtoFK/tDRDzSUQvNfd90cT+DE6jtzOVQYykikqL2ErpOToyRT2kS644c9s/IwetKRMQxpGGnY41CzjjABVzX9t1EIfW/OTkT0RkQL/vSkIRMX99RRP6bGN8Q57C4NLbw2ec+OzGCc9ff+XVbF10gL9s5550LdaYT9ce5XtTlZvOohxcRCSnPw1DmAF9Jtl8lRq2+gIDdGn0WOL1xXpPQ8jHQPYf9K5S9MH7Czqg5sPdJqF921aunP9u0MzlajSOnmsXKWIhpD/s8nT63RkTEhHjvalZxrv8Tx+375YlncB3XXrwN6tVtmBM01cT70ODoU9Y6K/vxPHgBjlfVrS+Huth3HdSNfY9b68zu/ibUySnMLXCbVigOllaIRkwuEJsJrVNE62Qf22L8U8ucrTGXyvhBCavT94If/de/wu8mxkat5T0f7xsr1qyEOpnFXIc85boYwf5Yi8nB6afcqYDyw+hRVcaOD0N9ySWXWOvsaKfnKzov6QyOsatW4Bhaadreun3HD0Jdc/DampxAD0yUxXUMrMH7+jlb1ljbuGT75VCbkJ5hyAft07Ot59p5ZXxPmpuHFXiL8BidXM+il1QURVEURVEURVkC+rKhKIqiKIqiKEpL0JcNRVEURVEURVFawpI8G+l0RvwZz0PYQH2259l6Zf5ZhrTFfhL1YU0KbkiQRt6EtkZyaryI6zT4maSLn8m14TY9x26Cah3nVO7rQc1zjXwMQYjLx2n72U+RobmdfXJluKQRDGie54kJ2xdSq+E2EgnU53k+vVuSvtSPye7wSIvdjOa05zJLR/ft3D3rA0pmKIOl3fYp9PT2QO2SHjGdQl2mz5eDJU+2D5h1vOy14QwEDi4xJiavgmvuK+RtaM/h75MxOkpD+3VkBP1Pzx5BD8aaVai1bctTBo5v9z8hvwrnUHi03w4dO2e6iIgY9gwFJvbfy4UbTcnJeBbfoXydmOUdYY8Gn3+sPQfHjuLoMagfv+/71jZMDc/F/sdRy9u2CuedX7/tIqivevn11jodB/tU6HDeyfxeiHg4x4AyH+y9oIrzQuxPcIZI2MB+fnwQMyH6+7Ctwoads3FgzyNQt2WnfWP12vLnbLjmVHII3yMk5hxwC/Fn2GJgbY/uuVHV1swfOHQA6qkByraqPwx1eYzyt2La8TzS+rcNDEA90oPn6V4ae44mNlrrdDpegnVtHGovwL5hHPYF4n7bTkpZ8J74Qvgt5q5juf0bD95/p/gnnytcvGdsuWCbtXyTnhMj8iMGTWzTEhksggb2t4gy0ERE2latgjpHHo7RYRxDd+18GuoDg5gFIiKSz+KzKnu7jh9DL12tgZkZUcq+r+8+vgfqletxXF63pgPqTJbyP6r4zFOuH7K2YRz0n/T24DqrDbxXcK6LCfE4RERCei4y8O+YbKzToN9sKIqiKIqiKIrSEvRlQ1EURVEURVGUlqAvG4qiKIqiKIqitIQleTay2cysH6FYQy1sEKOfZp0bezhYblipoAaQl08n7TmApYmas5C0c04Cf9/fjvM87ycNr4hITwdq/jo7cS7oySrq8SpV1B02A9Z2ivhJ1GKz2jMk7Rxr6apVbJtUym4L9rhEPMcyeTaiCI/Dc+3uEASk8ZujAo7M4udYfiH4569/Q5Izx3jueVvgd5dcut1aPkeax1wW+1NAWmFDWRScTRHGeIZc6qMLzZJuyLeQStjncZzmAZ86VoS6sHID1JNjuPy3vvcda50TVbzYTpgVUGc6ULu+csWFUHt0sQY8ebmIRDRHP+uJQ5rHPqL50E0Yl3mDbW7m9Lmwbmd9tJpjR5+RTG5asz+wBuc0j7se2GfAPhaG2yAMsJ3bUzFZCpRFUh4+AvWJScwsGCmOQJ3xcbwTEbnoJVfjNlLkl6D8EGdpt5LpddKh8JFZuQackRHZbcG+tCMHn4X6vrv+E+qXvvQaqA/ttTMfRgZxfvwHKtPnhPXmy4LjxOZpTP8qxvWyQG4D/9auyUcZszoTYTt0dqPfYmsb3pfufgTvudmM3f84f6hZQd196rF/hvrCzKO4TsExUkTksOB2KgW8Z2QoG8Froi+EDz0ycW1LGvgFcjQWyt043c/OFOMnRsSbyZZauxp9NOMT49byeeowlRN4HpvkJWwr4Dnq70BfXMLBviVi554dHjyKC9C47NPz3QnH9ins2bsL6v0HcL+LxzFTJE3PXolsTOZSAvdzYA16SnsmTkBdrWJ/rJbRv3Lo6busTXgBbndqAtu3vQOfZRs19IFk2uz29dN0fc7x8TqJuGypePSbDUVRFEVRFEVRWoK+bCiKoiiKoiiK0hL0ZUNRFEVRFEVRlJagLxuKoiiKoiiKorSEJbn6giCYNaexsanZsEO+JifxZ14bhqg5Lhtu0QiVyaBZpVmxjTw9XWh48Xw0xCQopKQxSaabKdtkmhM07Y4MoqGyWEFDnEuha4k0mm5EbPNoSCbyKoX+JclInKdAxNyMSXUuk3RsyQS2X6WM25iYQMMRBweKiCSSeCxB41T7WgbOFvPos8+I702/H+e6MMTvYnORtXxpkgxrAZ4Dz8H2yGYpuM7Dy4PPmYhIQEFPDoVLkSdajk8UoR4etU11FeqT+QxeN30u7ucX/9/fQ33vPfda6wzz66Du2ITG2EuyaFarjqHJrtnehft4Aq8JEZFGEyeNiCI0N4cNMj/TmMFGUxHbMD3XLFmKGQ9azf49T0sqM329r1yFBlPXscM82cxrmUw9/HtPUMM22/XYQ7iNpn3MfTQ2HBhGQ7g4OFZEE5NQ/9e/fsNaZy6Bnzn/EgzsCtjcTW7vOO9sSAGNIZn/fRfbwqGAPpdqL2b8Cep4bM8++iOon37kB1CXJrCfDx6yg7KKZHw9GWwaBvaEEa3GcZzZYD4r1G8RBnHLkMznjc8B9U+eRENEpEq9etcx7MM/R5N3vMTpgPrIqH0PPnQczdknqnheG0ER6k4HJwK4MoOTZoiI9OZ7od7nc+gr9nEzimGOUTCGK4z13vMkLPNPosLm7zgzuBW8NmeZaJnN40kTijdzcY8d2Au/i5uLINuOY9PKLqzb2tAA3tuL5yiTwWexWsykIMMn0Fj9xBMYuJfJ41h2eBJ/XyYjtohI+Rje34bG0BDue/jMVxrDdbij9nlJ+jhe/LD4JNS5FJ7njnbcRiZFz4TH0LQuIvLUI/8EdaWM99hVFPB6Ygzvr/UEnh8RkSuufhnUAwOnJlniiYvmQ7/ZUBRFURRFURSlJejLhqIoiqIoiqIoLUFfNhRFURRFURRFaQlLT2KagT0D9UrJWiYIUBPfaKJ+jGwJYskbSS/aTvo+EZEmaZzTtFJTQ43zsUOHoe7owGAaEZFaqQj1BGmcSyTEb+vHZgxcW6fZoPAaP4VeiCTVtUnUv7e1USBRjF49keAQRWy/VIpC/yLcJw7ZEhFJUhhhOCfQJXTsELZWUnOMeM502zfpNbm9q8NavqsN+2jSYy8NacAd1FSWJlE3XKMQQBFbtutFuM6mg+fkP+78PtR33o2achGRRBJ1k5dQgGEydR/Ujz/+BNR9q9GfISKSXncV1KYd1zl6dA/U992JXgH/ok1QT40UrW3kKCyprYDt7ZEng0P9JLQ9G7zMXP1yvbL8oX6TJ0YkmZ7WEYc1HBf8TJ+1PI9pjkM+FRevr7FR1JrvffwBqAtJe8hup4DPE6OoNw7IJ9RVwZ3q7LEv/Gcf/CHU+3Y+BnWewqG2X/oSqBMZ1BuLiETkB+CLp0kho/UqtlV1Cu8xpSJqtUVEDh/EUL6nH0SPRkT67OGjB6CemrLvY+kceqZcf7r9jBXN2np835/1aizkxxARcVz2vdAyfE7oJsDBul6MZ8P10UP2yCG8Pz6dOB/ql/7Gb0C9ZtA+j6mHUc8uBw9AGVB4b0DnNZqyPRsXpzDscl0Onx0eEXy+KNVwHPZKeD9ohnZbRMb2rj5fFhP8t1x0pNzZcODOLPkxBlZYy+fIT9bTg94/y3NCtZ+k5znHHv8a5Hd99lm8lwl5L4+OY0jnOavw+hYRuWQl+nlW9+Iyuwexv40Mkp/HflQQn3y7wyPYhyN6HnEE+5sr5BW2PM8ivkfhghQ2mHlmPy1Pfr4Ys93hwxhw2N5+6j4fBIt/BtRvNhRFURRFURRFaQn6sqEoiqIoiqIoSkvQlw1FURRFURRFUVrCkjwbYRSKE01runx6TfESMVpOD7XETfI6ZOgzadIje+RBME1bIztVRo1tRPq89hRq7SpVFNONHx601umTtjxNcz1n01h39ODc0MdP4DzOIjGZFE3U27GU1qe2qVTK9Hv71GXSNPfzFGr+fPZwUIZGo2G3b72OGtRU8pQ+N2C9b4tJ5lPiz2iGewa64XcJz9Ya+i71H5qn3yF9aCR4TsoVbL962fbJ1Er4s6PDNCe/j5rJB36MfotDe3db6xwlL8LTz6JePuFg3+hfhR6NgX7bs3G8hsfa3o31M88+CPWEi5rUDZ3oR3j4wYetbYzVirhflIVyweaNUF98EWq5TYga6umfYf+bm3WSWIJe9IVifOyoJGb8Vfv3PQ6/O/eCl1vLO5SJkuCsCOqDhw8cgLpYLEK9dgC1xCIiUsbxypJBk++lWsZ+3UlZRSIi9QnUvD/5wI+hTibxOMb3YB9Nx+QAZfLYFkK5G8UR1O5Xp3DMO0IZGKUpe358SVKWR4DXp+vgGBe42Db5FPZZEZFqSONEVJ35//LnbGzadqX4/vS4xnr3ZmCP3yGZhiLKAZovw0GEk69E4sIlXPLClSJc5v99E/1f0rkBypdciPkWIiIv68JlNoyjJr4yhfXUKN7HS6OUNSMiZgK9TMks9vtCbRXU37kHP187jOc7UcPsBRGRwPBzEPst5m/vxeDOve8us3/j0m2bJTUz/q1ZiR6NyLNzhqYo+yubxXEhpGuI+6dLD5pO0/b1VSp4jziwH7Nz2rsxW8Lzsb9eus32Al/Yh33juw/hfb1AHtpCDz5XNkv2eWErb8rw2EQf4DCjiDzQYt//6hE+72bbOqDecuEaqLeeg9fe8cOYnSIiUiaPSy5/6thiTsdp0W82FEVRFEVRFEVpCfqyoSiKoiiKoihKS9CXDUVRFEVRFEVRWsKSPBtBoyZipj9iWCMf89oSGZ4jGReqkh+gtx31fPkC1keP2l6IMIH7EZIPIcighi2ZQX3e2E5bM+8GKETrz6LWON+Fc0eH1IrJrD1vc5OOVULW9KGgL0f65inSJ/sJzowQaQaoeQ+bWDs0L7hH56PZsAV4AWnmE3PnVF/maea7Otpms0R6e1FTaRoxen/ePx9PlMv6Y5LbsmcoGeMLSWbwPN19CLXrDz3zLNQHD+A814nQnpc9ClCrfnwCtZqdmQ6oT4wXoTaHbB9SahX6ipIu+kKeIV+Ivxr1y1UHNaqdqzF3Q0Tkjq//P/xBE/f7mWdQD7pmPa6jvw+3ISLSrGO/d+f4jtxw+XMOGrWimGhamzx49Gn43ZZzL7aWL5ewnQPyQrAmuTSKY1yd+nU9xicwTtkcE5R5xDpp36d8hphsgJB8Hb051GN7Ee7X+F7MeqlXbX9TQOMRy80zORxXuwo4jkYn9uH6KvZ+bznvAqjTSfQalWi/Do6g9r/YtHM2nBxqo9OF6XPmuMufd/Cp//Xnkp/JLojI89K07ikijSbue6PBHij8fRiShp49HZG9Dc6SiWgdY2PYxjyX/2hMXoqhzJ1sEj8zTHkoh4+Rpp4yIEREoi4c4Pk6WZHHdWzfiuPTQ9R36iM4touIeHW6vim7KbRyDM5cZsZzobszL+kZz2pbO16f1bo9NjUopytFftc69Uc2NjS5P4YxPinypDmCz0YmhffxKj3nXLLNzgf5mQs2Q/35f/s61JMOPn9k85gfUgntDCiHvMChoD8sJI+p7dnAtvFNTM4G+aUKlHOyme6569ashHq8iFk0IiKBQX9se/ZU+/L4Mh/6zYaiKIqiKIqiKC1BXzYURVEURVEURWkJ+rKhKIqiKIqiKEpLWFrORr12Svfvof4xEeMhYFj/GZEus0yZBQ3S+AYsDo3Zj8BBDWS5iZrAnk7UrqdT9nzwhvTshswJXgK3Ua+j9rPZsPV6PNe975JBgATMDcoDSZMXxXfs90TO8gjYJxLhNtmz4Hsx3YH2s1Y9dWys72012VR61rPRpPaJk0/zvNZz9316AfL7kMmjWEK/gFOzz+uKLtSE960YgPrxf/4G1CkHNawrV+C81yIiYwdQm+5QCEs+g3kqhvpbX4ftGcp1Yz9/4AffhXqqiHPGD+bwvP/jt78K9bVXXGZtY9MAHvuB/ejRODSI858/9cxOqFesuMpap0vH7s3x3fiene3TahrVkpgZk9ah/U/B7/bt3mktn/JwvNnz4+9DXchgf3BJAxtQTsT9jz9ibaM3j/rhKml5wxKOTz19uE9h0/Y+lEtFqLs7cBthg/TEnNFTtbW8WbpI/TSOaQPrUTvtkXfpaBrvF5N122MWkQa8kMd+v7oH9cddhQ6ov/zt71jr7NuC13jHqmnfX7AEvfILxfjRJ6SRm76+DY1fyWTGWr67G3NZvAKO8Q6NR4kEtpdnXWO2b43zPoKAdfaoZ2dz3PCxYWEmiugZKtGzQVjHMa89j33JTdr7+chjOK4+9ij6jDy6Ryfp2sxEOO5GWRzvRETqKfISVjHvw6uiP8VQey7GhfZcsjleKFLJlKSSqZn9wPPsOfbzgMs5GuSHjajN+R7MviSJ8Sl49MzH+WH1EMc/4+JzZToRExYRTUKZJG+wUKaNT5lynmOPqa5DxxpRhgidfY4xY79KGNMPDPnxqhFeJ1MN8h1FOMY6vt0DT0ziZ7ZvOdW+ddsqe1r0mw1FURRFURRFUVqCvmwoiqIoiqIoitIS9GVDURRFURRFUZSWsCTPhhM0Z3VlAetlY9aUpPmNExnKefBREymkz3ZI29nRwdpPkZFRnMM7S3OzJ2mduQLqWrti1lkuooY0oLyA0iTqLjv6UQNdrNtztafID5EgvW1EGsByGbe5aiXmHsQxOjICddJH7WIqgW1Tq6Eu1jG2djGk/XITy6+TP0m5VBLfn97+yDAeaxCTEVKibJIfPfoo1F4K+189QJ1lpYTtc8l5W61tBKQx7epCza6Qt2aqghrK3rytu0yS/jNNOS+dBZyfu0bzxTeKtga6WH0Y6rHDB3A3aQ7wsSLmPQyN0HFMrrO2kSLPUERz+JfIW3L0OOqZ4zxALnuT5rS3rcpuPa4x4s5oZYtjx+B3x8iTIiLy8kvPh3rrtVdDvfdpzDcpHUXvjO9imxTF9gm0p/CaHNiE5+bwTvTO1Gu4jkQX9jcRkUSKfEGkBW4EuE0niWNLXVDzLCLikUcv7eH4lE+S7llQENzbgRlJI1N2PsNoEbMSnJCyPeq4XwPdOHa3p+22qFdwHZmZZZrsu1sGnnjo/tmcg2xbgX5rXxE9dHxZyoBqku8kR1knGcoRirvmDI2B7PPw6T6fStF4lrfbMeNh/ztSxft83+oOqJMJPE72E4iIJAwe67OU+3N8EK9nM0YePfIGQObUDG4SPUGSxXMUBHhPCWL8UhZnURSH6zrizpgJmk32X9jLsw+B/WHs22Vfr0N/D+ffi4jUOSuG7uNOlXaMnlXrHl9HIlMN7LM1GgO8DJ6UXBuOGxE9M4qIuBTIlqBMDENjfZpyvnIp8iUl7LGqWEZ/RdInD3OJnmXJz5dwbe91O2XTXXPNqWutXGmK/C/rI7HoNxuKoiiKoiiKorQEfdlQFEVRFEVRFKUl6MuGoiiKoiiKoigtYUmejWQiOauZj2jO9Li5n6OItMHJhLXMXHh+7nSK8gJisiV6enEecZc0zck06kHDCPV8fkxAQ3dnB9TjZdTAF8dRF5dvb8N9iNGe5/OoCwzJY0ByUMklUA9aLqL/IJWy9XoS0HzTHrb31EQR6kYN26LJuRwiEhpsc2+O98TwHNgtptZsiG+mz+cEZWBMVSvW8keOoCfgsSdxXvVEFnXBlRquwyHd75b1661tNGme8HyGczSwfz7yKGYzHDG2Xjmga6krh3Pf93aiL2Q8QG3x5PAha51Dpf1Q16dQu+nTdZOlvpNsYtvsewq9BiIiYyOoeQ5Ir1uq4zYrNEk3z7EuIuKT52punzsT882HTU/cGS9Z3SEPWsIeTgOa5zxJ2RJtWfzMAHl4NvTiGJjO2DrxRGEt1Nsvxvn/oxpew40anXue0F1EDGmrR8kHNMReuSxq/VMx/i+hbIR0E9tiYgx9WA71uRSNiY0Yn1algfPGi4/Xzvg4emJK5LtJOvY63Qyuo617ej+a9eXP2cikc7OekZB3NWY8rpFGO+PjmJdJYl0nzXeGfH/ZnJ3hwxlRnAvkenQNB7hPQTPGCUL3MsfgMhnyfaxatRLqqQnbz5NP4rVGllJxPRzvHbr3NUmHz7WIiFMt4g/olPAzkTg05sWMgfxw4MC/l3cMnCqVZr0alSpuu1aznx+aNeykCa+IC3jYxnXO4aDzzh5JEZEa+YeDBp6XXnruPDaJ+/3lr+621nl/x2GonSSOAf3r0JvT07cR6v3PPmOtc3wE+2QwxRlSuJ8OZccMnHMO1OdtOc/axr3f+wHUI8cHoT5w4AjUpSn0EDUcOzjDp+tgfPLUdVJhP8w86DcbiqIoiqIoiqK0BH3ZUBRFURRFURSlJejLhqIoiqIoiqIoLUFfNhRFURRFURRFaQlLMognUjnxZ0yQlFEntVrZWr5JxtUqmUlcFw0xHApTraDhKN2GRmwRkYFVK6CuV9HwUqlhaEmeQpvS6I8TEZGpExRIRZ4kh8JZJk6gWblRsY2DkwEuk0mg+centqiUsD0nakWoO8kkLCKScvHYiuNo4jwxhoFX2RyuI5WwA11qTTYAmdP8u/U0HSNmxixXIhPY6MS4tfzOZ9CkNTiCQXXd/X1Qs0H8BC2/99ABaxs5CtZZQZMF/PLrb4D6yBAGv4UxJlMvQUYxCoAMyVgdVKhvOfY6M2R2D8vYXi4ZF7scNIJmJ/CamGjYRrIqTYxQockYqmQ6TiTt/sYYCnECU/gZCLsykhQzM2xWyrgD1dqUtfzw6EGofR5/8mh0vWQrGg2HjuKEAiOP2+b/NZvREL5uACcl8C7CdT547/1QT02gaVpExM+iITKs4vkfJ+PhKN1K2jP2ZCBpCpjKZfH8F8u4jSqFcpapW5cbtiE1qOA6AsGwt3SaJt44Qdcj3bNERNrb+qHO5KevRy+x/LGS+/fvl9SM4TV0sM0zMZOGVCi06/gxNMTn83ieEzTJQYPGmg4KVhQRCenGnaRwRl5nENDEEDEe01y2gz6DJuBnyYAb0vg1WbGfRx7dhdfi6Akc34Ma9p0opODd+cai2Z/hMnYIHT9M8DriBjX6mTPP71pMFEWzx2QoEJL7ioiIhDSREF0yEd2XXDoelwzkYcycDEFI54UW6m/P0u9xG/fff8BaZ3QxmrH7z8ExYKqAk4NctuNCqFdusDv14EEcE8tj+LxRIjN9iSI0jzo44c3xA/a4XcnjzyIX1zlBE2h4KRxDPc++h7Wlcb8fmnNLqi9hkgz9ZkNRFEVRFEVRlJagLxuKoiiKoiiKorQEfdlQFEVRFEVRFKUlLMmz4abzs3ryUgUDmNykrd1KZ2j1AWrrkqTlDCm0r0ohMWPjti7fId1sNo3rmJhE38JAH4axbDkHw4BERJ58CD9TmcL9rjVR89cMUBeb8uygtinyYATUXhxaVK6gns+l4C0nst8TE6T1b3JwIGkAPRf3My5zsRGwJtQ5zb9bz0SlLN6MhvPQMdSM7x88Yi0/WkIN7pHjqFf2KdRv05bN+PlRDDLzYs4rSUolncDzetklW6C+5uWX4j4dsvv00BjqJifGi1CnyFsSkn8l8Gy9KNs4utrw2Bukf0+RDjZNgWFjk9g2IiJTdL1PUNgSh/blSC/OYWAiIiEJus2cmn+3HGw6b7OkZoL5xot4HqoTx63ln3wcNbQ/HsZ2S1TRI/Ch970H6l9swzbq6L7L2kZ5FLW8uWEMqTonj/1jL/nUjhxCLbuIiLdmPdRNGgfqFPRUmsQ+Wy3b55IDL10Pd2SKvG5jRWy7Mo1nxbIdqsa3ob0HcVxY042eg0QCr+l6GBMsSeOkCQL4/3Ly9a//p7gz14lP473v2/cEj/xePIZxkJhPvr0MhUjG5Opaf7L0fRwHPB4kI/Y12L6DTAZ19iHp8MfIQ+ZS+KCTtP2d9YhCXCkHtkYeUYkZj5CYAD7yHMS4OqicPxBx5qf0kbn18no2OtoKkjlpdI3w+kvFhJrWyIeQphBJ9vtwbTjU1bV9IQ7d3MIIt+mRb2HbauzzB4fs63hs7ADU42N079qAgXpdndhft3Sjj05EpLaZ9ot8SINjuB9f/08c19duQF+Im4kJY129Aeqsh/6pZ3Y+AvWmTfj5yzfb101IYc8HD8zpc97i+59+s6EoiqIoiqIoSkvQlw1FURRFURRFUVqCvmwoiqIoiqIoitISluTZiFxPwhn9aiqLWs50ztYaZhL4LjM+iN4GoXmahSTYPknkWVcuIlKfQu1mxkONc0B6s3IZ96E9HzMffIb0n5Ooqw5obmHXxzpH8zqLiIwMoaa5PY/auGoZt9Fs4DoTKdynqbI9H3I2h9sNSOsZkeDW0NlPOnZ3CEp8zk6tY7k18yY0YmY0qknKt0hk7TafCvDc18gzMD5Gut8Ij7+/A/MK0jHHm/FQQ3qkuBfqMI/b7O3Fc/DQg5TpIiLVAJdJpXC/anU8J4YunCiwr8WxKdTX+rkC1H0DmEcwRm0zUkV9abVh65VdF/ejSh6tDOl12yjLwQlt/Wed/FHhHH13LWb5VtPV3ynpzHTf6+vHNpPIbvdJyn8ZmUQd7tRR/P2hIfR0rOxBT9mrdlxnbePwYw9BPTb4GNRubwfUAz2Yr7Nn705rnXTqrLGkRF4Th/wCjRgt+UQVr5XqcfRkeDQ+TdUxM8nP4jXvxGR5jJN3pFzC/axX0Tu3sjcPdcXKFRJJ0f3AmzlWL1z+v9UZJy1mpp349hnnoSvX8PhD8ksEdKIbdPycG5GMyWJyyAeSsDwb+PvIsK8hzrOBzxce5dM0OLDBo7GmHT8vIpLN4pjnuXjtRTSeuHQ7tGM1YsYfJ87H8fxgH4cjc9ozJuujlRwfGZfUzLNIe45y0mL8JjwkRtQ+IeVsBBykQYfnxfWVNPl76Dnm0DE055R9vJcV0tgvREQcHz+TTOOBTDRx7HrwqaehNsPoKRURGT54GJfJ4vjRbMPrpFSntho8QZ+32zug/pDOUid28PrdNYS5TdWS/QxoKOCoWD21jqCx+GdA/WZDURRFdNvN7QAA7EFJREFUURRFUZSWoC8biqIoiqIoiqK0BH3ZUBRFURRFURSlJSzJs+ElHPFnci2qJdRxeWy4EJEUzeGdS6NG22XdN82x7NIc6IWsPQdwgsIhUjSnd09HF9RZ0vdVavZc7eUK6lx9noscJX+SzaIOrrsX53IXESmOYXaHEcrZ8FB/16D53g1pGz0nJktBcMcizt2gOdcj0tibGM2v59NnglOfiZbZs+FIKM5JzWYT/RgJmoNfRCRLeuSONHoGyjX0PoyOY3bMSW3+SSpV2ydTrqGufNcJ9Gy4NZpT3sP+1gxQQy4iMnkC98uJUOteIP8OT68/FZM/UKe2KORQ07xuDc4LXu/tg/rxJ57BbRbsa3FgJXoYis9i3kOOPBpdbbSOxfQnx4v/93LhBLPbNYJ90MRck5k8Xj/9q7BdMy6OR00aA0vk+XCM7VO4/Od+GerdT/VDXW9i/0k+gLkambytb+f57YsTRaiDiLTVzvz5AXE/85uUA0TjU6YH9+uSKy6CurcLPVUiIt+/436ojx3Ga/roGO5DqYZt0/TsMTDXjeco8vD/y4mXaZvNXOI8i2QqbS2fpiyIBo15zToef4aMIEbo/lrosLbh0D3X9aiPks+DPRtRYHsxU3Svdz3yilCf9hPYVzKdK6x1simUrW1sA7E9MPNlTp1chP9+u9R1xHkwljfPaj7+87t3zXpwOgt4f2zr6rSWz+dwmY429EilyZvDWWEpyk+J88WFlAHkCH6mWEX/xXAK+4FfIV+qiHQLXkuJJt6nt2/F66o6gWPqzoP4vCcicvwAPiuYdtxGip5lO1dh25Upz61GXmIRkTotU2rgNoN2yhipYVvs2mevM1fHc1afk3ETsblvHvSbDUVRFEVRFEVRWoK+bCiKoiiKoiiK0hL0ZUNRFEVRFEVRlJawNM9GUJv1CqRpTvRg0tYr10hXHzRpLmwPN8/zbfMak0l7ju+2NpojmXTTnR2o/UzSNitTqGkTEYlobnHWxvoJ1LWGEbbF5ITtH3Bd1N/19qG+3Sdt4uDYI1AnKKPAi5ljvuFQ3gfpI3OUw9FoopaxMoW1iEiK5jevVV74ecQXi592Zj0k6Q7cr8mGfR7Fw/bw2+jcUw87Hhahdhzsv4OhnYnRE2Gb7Z5EbefQPsxVcOvYXzduXWWts/kE+j6GjuF+ceZBVz5Nv7cm4JeOTvQRrR1ATXOWNPcvv+pyqPPkW/rhfaiNFxHJplZjTR6Z/p5uqAfoGvCM3bf8eeTKMfL6luNGgbgzYv1GiLrxRMr+202Fcn0COkYvjdf9N/71n6G+ZCP6L4aH7X7et/XlUGc68TMP3vtfUB8axTniswX00oiI1GmO91x2/j7W3Y/n1vVsQ4NHfShJy6xahX1y9QVY9wzgWJ6KyQUqFtFX9Z/DP4C6SUaLqTp2or51tta/by36/pzk9LjgRMuf8+JnOmc18wnyQmRSdtaQS16/OueONChbgjwHqQyOV/kOvMZFRCI6DyShFydJmRl02oKa7Vvz2Z9pZXPgdRA5eD/wfNuHFEU4nlu5UzSumgUzLOIGoIUGpef7+zPL8PHj4s74ucIqjhtHjtrZEuJiG3vk72lvx/Ocy+E6O9o78Pdt9ljFXq+Uj+dt4wCu45qfwfvOscPHrXWOj9Kza4Cd9iVtOD6OpLEPj222PY25lThmVimvbUrIT0WPkVMR/oAzNUREfPr+wJC3qUk5J04Kx+Rsn/3s4Ezgz5qTp2rOTZkP/WZDURRFURRFUZSWoC8biqIoiqIoiqK0BH3ZUBRFURRFURSlJSzJs2GqZTEz2jWXBGUmtLVb5SrqxTzyXGTSqKsMSc88Wae8i4S9u1FEOQYhau3GplBn30EeDtexNZJdNF90g3StDZLul2qoaZv08LhFRDJZ1NMWJ4tQh6S/8zLYVi55NOoxunzGp7nwTUDZHqTTz8fMtz9+gjMb5rbX8mqWuwa6xZ/JXhlLYBvfP7LHWj6gwwk34Hl1Q2yPwwHqvZMJ7BtOs2ht48Tep6DefRT18Pv2oB6008f23HH5K6x1ruxDXfQ/fvVbUAcu6s75yrv8JRcJs2HtOqj7yS8hVdScbu7HDIPs5ZdAfd+991rb2LcHvSassx7oxW32dHZA7cX0pwTpcefOs+7HXLutplwpSWCmx5hKDf06cbEfpTLNW25wDAvJ//Xt73wP6qGdK6EeLtnzoEdPYbuzn6JeR317sgsvjMYxzPIQEamUUOtfNbjOXvIx/MKvvgpqJ22fG9ej7U7hOlf04PVZ9XCgrTZR05zN2B6FLVs3QX3PXQ9AXZ/CcdSle9A5F5xrrbOvC4+12pweJ+ocuLQMZHLd4s2YHvwkdbimnQN0+OAuqCcncf7/MOR7An4+QZ6jyLfvwT0Dm6F2PTov5N1Kk9ek7thezIg8FxH1P1dwvDLkNXFj/Dwh3e9cevyxxhPO4SCPn7OonI2lsoicjTnlcg+B/Z0ds76LC87bCL8rTtp+shqFmTy7B/Mo9u9/Fmr25SbpOSjbYV/zhTz6EdesxDov+KzQOIxj6G/+8kusdd7+xR9CPXgMnys7UnjtD7u4jTFj9+kK38ro+Sxo4HWSa+B4mKe+1QjtZ0A3RE9Lhvt4gGNqSM/Y7JsWEWmGeF7L5tSYsLCvac6+LXpJRVEURVEURVGUJaAvG4qiKIqiKIqitAR92VAURVEURVEUpSXoy4aiKIqiKIqiKC1hSQZxCeqzoXls3MxlO63FQzLE1A2abCpVNKckkmje44CXuKAoNrRkkhSe14aG8HQGfz82ZpsjPUoLy2bR7LOaggSfOYCmpzQFYImINOtotKs28NhD9tlQ+0ZkbvNiXhM5YCWiQCfrM3R+4to3lcZzUp5jUA1DO8ixlWzZtFmSMyE0u4qH4HdTnj1BQbIdz1NfBxo93Truf6WK/dMTNojboYcH9h6Buk6Bju0NDDvLRNieXpUN+CKrO9GcvaK7D+qjw2g6723D47pwvR281d2GxrqCh/3Jz5Gbfgqvi9409o3rrrzM2sa37kMz7lQd27OQIYNwBduz7trnMCJTZjQnJCoKlt+g6ye82YkqTIUnp7CXdyg4LJHGOkNtsuXCc6De2IWhj+7ksLWNoovt3N9N5v7uDVA3K9jnxgdtY/HUWBHqgALsJiZwPJuiYDbP9kdKg2bWcEK8Fo5TeFSQxP1kA/44m+9FJKRAr2wB+/3EMO4nz2syPlq01mmaeA680Jv5//IHnF552fmSnLnHmQBNqT++9y5r+aCO11iSghVDuidYHmmqaxN2/2vksY07Vp4HtUljuKxP9zYvwHuyiEidzLCB4H47ZELPk5G4v4vCfkWkEeB1Ysbx2cCUsI4oRC2MaKyO88ZG7NjmMEL6rWWwjXF8W0b1M0d7e0H8meeEdgqKdXx7AKw38GcXnrcF6h+M49hTD3B5U6NJhibtZ5Rq+QTU51MQag89BxwZosC+mn0fuf5anPTgG998BupjI7j88RKZ0CftyXbMFB1bHvs4PbqK79IkTA4eRyqynzONS5MZJek5Eg9d/BqFQ/OAICKrPZzYpeqdOvjQRLJb7PtHHPrNhqIoiqIoiqIoLUFfNhRFURRFURRFaQn6sqEoiqIoiqIoSktYkmcjmKOny7WhJq3ZtIPsIgofq1PgXoZEuOwBCJuoia2HtrauLYu+jnbyU6RoH0yTdMGBrTNMpVA8l6ZQoik61maE2mEnaYettFGoX6OC66hMoga6jbTGiTRqUr2Ure1sUPuWShjGsqpvBf6+UsTP12z/AIfsnEmi8apEM227IYc6wlxMolo6wPOWQmmnpALs/qkM+o586jtBndIcRSTIouYxonPvUlBZOonv907dDkIiFaWcNzAAdYkCIV928Taoz1+Dy4uIuBTek6Er3/Fwq5kE7WcCr4lrr36ptY3HyLs0dQD9LB0F1G5XS9jnnZigStfHfm7mhIo1Y/prqwkajVnvU55C5fyYwLMaBTeFTRxvXBc/00n9ZaqKfW7T9rXWNkIai3nMG69gOyeyqLVuX4meIBGRwQPYL9fQ2DE0cQzrQby4elN4rkVEIjq/7e3Yfh6ZyvwsriMkD1oqaQd8JdLYT1dvQv/S0b0YcicRbvPIoSFrndU6ehASueltOGb5QyV/5fXXz3oZa0UM6CuPHrGWnyyjR6VG4Z0S4X3IoXHUo3C9XNo+r1ddgD6jq37mGtyHJn7GpW00q9g/RUQmyD8XknmkRGGDq1egb+2Cc+1wxgb5JL/3X3ju7/khrrPZwLYJ6f4asQBeRMTw9Y3bMBRcHFDQbhTjg4zm8X2EUSSC3aClrFmzSpKJ6XtFRH6Tnp5ea/kq+XLbCnif6WjHvjE8XoQ6T77dbVvxWhQR8TN4n4+qaKhYtQr7xgMP7Yd67zO29+vCC/A5sofCP/ftwueiqBf9PjvWXGit85EDj0B9cOQA1OdsvwDq9jS25/B+9GpONuxnB68Hx7+cj+3r1HG/V6Ux7NeNuaVet+1qqIfyp4KMG42m7P7RAftDMeg3G4qiKIqiKIqitAR92VAURVEURVEUpSXoy4aiKIqiKIqiKC1haTkbni8yo0uOaD7fILL9FIbU5z7lOCR91I81mqiBbDRozuDQ1nQnaB57v7MD6pA8Gp6P+5BK2XMVOzS/cS6PyxRP4LzCa9ajts717Jmwc5TVIaTdrA3jfOj5NtRVp2i/Xd9+T0ynyGOQwvZMpnAf0jRPc71mz5fMPpq5unSHJ2FvMZ2VUFLB9HE7TWzjXIzWNUvZJEnB9knQu3a+gHrHJPkUmhX7eNNJ1Ngn8zSHvEN6ZbKWmBidv+OgPvTBBF03pG3v7+qAuq8D9aMiIl4T1+mRRyOk60hIj+4ncPnN6+1cnY3rUP+5/wjq3zesXQN1Wx71uE5oa2dZr1xvnOrTjTOQs2HklGY6Sz4sztQQESmViriM4HXv0+Tq2TZsk64OvEazlKEhIlIUvM6b5HXzEuQ5q6MWvXu17dlIFFDXvH07auAbj5NvrYHb7OnGfBkREePh+com8VibFDYUJfj+wfp3e5xNk7Z689aNUD91/2Go8+T54/MjIhJS5kNHx/TY7Fdtn2Kr8RLp2fPZuwJ9ND9//aus5UtVvP8dGBqEuk7+Q5eut7YcjiXbzkF/hojIr7/uBqjXbsVlGoLryNI5CpvkIxGR4SLeDxuUX1Eln4dH+Spr1+J5FxGpkHdp+PhWqCcm0PxQpQwkj8bqKIw5/+TjYM8je2Ka7CFt2s84UYR9cu59t9lsyr4j/27vR4tYMdAnqZljOnqUMqbq9viXI1+bUF5Pdydef8VJ9CFENCYEDbvNN29CH9so5QYdH8b9dCh74vgJ+9lhGz1vdbfjeZwI1kPdcHBczldsD6lfxvGvPobntZzD8c7NYH+dHENP5MQ4mVBF5Jwc3oOTlFM1uBvzySTE/VzXZmfeFJ+9D+qBjlPXQb2++HuwfrOhKIqiKIqiKEpL0JcNRVEURVEURVFagr5sKIqiKIqiKIrSEpbk2WgYkZPyQdejud1TnA4g0qijfjFN+RUZmh956gTNu09a9bRra+ajGuq8gwA1fR7lBTQbqMPsSNtztY/TfNxlytEo9KEOP0FzF0e27FLqDdSgGhe1dN19OBd0k9qOtY7NGL1wIo3t4zi4jQRpoOvjpE82C3cH0MY6tma6laxJpiSTnD4G9pJ4MX0jQRkGCfYMUS0BniPPo3n9c3H+CqwjmlfdYf8O7afn43ze04vgfkUu+XsaNAc9eZkK7ej3mV6IvE0pvH75zw4h+a0oHkQ8/oGIdLTjseSyuI2+Ttwvj9quFOP74rncTXCqLaLA1te3msCR2ZyNkM6l79s63SSNi3XKPUhncQzs6kOvQ5oucy9ha2oNZXdkSBPv0YDEOvHV61H7LyJyYD1qkNv7cT8v2I66/GwOt1los31DFfKENWgsDmk/HRfXEZJ+u1q255lnP0Amj2Pzyg14XGvXrYJ68Ajmh4iIjIzidrIrpnXm9ZiMplbjZ5KSyE73gQTd2zZssv0U7/51vL8dP4G+hKEJzHGZKmG9bgD7xgUb7JyX/l70/IQJ9sGQFp2vidAeSwxdW+wBCiPsG6OjmEFQr9uBAQF5H+qUcTFFno6pKWyLiDxizbrtMeObf8LybOBx8X1MYnxIfJNJzrmPN4OYh40WsmrVgGRmcsf4vrNr1y5r+WJUhJqzdAo5bJ8keVEnp/Ce/PSufdY2MuSH7enAPt+k8bG/B/tnI+Y6zucxn2fr+Th2lZp47vePYbbH+DjWIiIvuxi38/J2HHu+992HoR6axP53w+swh6MjjZ8XEcmRl7qtE+/J+zrw94cP4njwq7+Ing8REanhc89E/dRxVKqLfwbUbzYURVEURVEURWkJ+rKhKIqiKIqiKEpL0JcNRVEURVEURVFawpI8G/UolPCkZ8NHDa8vtnaQfQcO6RFZb5hMkx6ZdJtJsXX5JzX8J2FNoCFda2kCtXeJ0NZ9Rwb369CxUag7V6Lut1FDLV69jDpDERHHx2VYf8x6byfC/Q6orRoBeTrE1rnW67gfPDc5554EMdrFRBLPc2TKc/69vJr5hOfN+i5cYX9KTOYH9wWeJ508LEnqS2mag5/1tyIiXoLWycvQPiR83EaK+7yIeHReNhxHzfiakXGo/STq1Nu77CyGZo3yZvi80nzctQDb08T4KZgownXkC+htSqdpm7S8G+N54PPsOafamzXYy4GXSYqXmT7HlRCvwZRv98F8O2rLPcoxaIbYrg6NV5UpHK9ykd0HrS7URL26S9dpXxd6Z4Ks3e4XXIr6f482u7ETM1MOjaDXYWIc+6iISIJyfpqU9xGEuN/ZFHk2aHwqZPD6FBFx6FhzOWycVZswE2ntFvQbTMb4QCYn8RxUqtN67UbNHoNbTSqZnM054NthMmP7v1ZvQA325m0X42fIarl/L2riC5T31Jm3xyuhMS2ZwWUa5MlI0EbrdXud+RxeJ+2UPxOQ16FI/c3E3JsS5BWZIt/jocFhqEsTuM4GeTpMYN/njZl/nORsGL6HmkWMaXPzPjiDo9Vk05lZr+2WzZvhd53tdvbSwQMHoK5V0bO2IY/907g4Rjz9DOb9jE3gORARefDRp6C+8PwNUPf34H5lXbxfDg7heRcR+X9ffBz3cz3e53/j17ZBvfMAXox79tjjyPbz8NyffzHux1uuXQ91I8D7ZaETr5O776HMDBEZKaKXZNMq/Mwvv+oSqMuUZ+Om7THt2SfR1zFRmXMcoXo2FEVRFEVRFEU5w+jLhqIoiqIoiqIoLUFfNhRFURRFURRFaQlL8mykM2nxZzTqkxWaLz4m5yBJ8+w7lMvAmusUZV7Um6h/5Dn3RURSOdRysoKxUUFdJs9rHTm2xrJJfoi2QgfUJsBmq9N803WxvQ+dGWyLDmqb0gS250QT97vRoDpmfu0UzXXf1YnZHbUaaqJZP8rbEBFpNrFF5/o8YlwSLSXf2SnZk7pvB9+Tkwm7K6dpzn2fcl5c8lf45OlgjwF7XEREHPa98HXAuRq0vOva7/vsP8lTZkFfD+rOa3SO6pF9ZkLWCpNXIKQ+G1DmSkTXjePZ+83XXo6uzWwWr++F9MsiIhHlyzjRqfaLFi8XfcFwE9P/iYjUSbMfVOyxJCSduJfGdnUoQ8WjbCE/2wF1LbC3kaTsDYe8I16IdcLFfXISdkOesw11z8J5AOTpqRgcv5yGfS7b2/D8n6igvrjZwP1wOUuHxtmEF3f7wnVw/keunebk70dPwqo1OGaKiNRpLE6dPPTlHgBl2leWnBm3EjS21Bx7/K5Sd2mSvzBLY0XCp/wdB/tWKoU+LBGRBHk0Ij4vZPhxXOzjPA6IiPg++zpwv5uWv5DHbjs/K6Axjsde27M4/9gdRTH5IIaWoT7Mh+pwJ3Li1okfmutd4vGx1SQTaUklpvuITzlU69baHqo16zCXpU4ZUQ2qL74EPQTr1zwG9QOPPG1t4+hx9NTu3o/+sQRld6R9ysyYtMfU3YdwP4amsI+/dD/u9xTaGsQ07fN4dBjHu9qPcDwrTeG5nKri89r6xMVQ/8zPXWFtw1Af3bNrJ9S3fuLrUGfI97Zx6xZrnRPjNAYkTmXeVJfgW9NvNhRFURRFURRFaQn6sqEoiqIoiqIoSkvQlw1FURRFURRFUVqCvmwoiqIoiqIoitISlmQQT/j+rImWbUlhjFmuQsa6LBlycwUMIao20DDDwXZhTLBYpY4/4+CosEnrJPNtKmcHCiUCNqZT4F6IzVYhk0wyZQdvGTJypdNogCuzGdIzVON+h3XbgMlm7hwZ9yolNCgZat8oiglmbNJ+uafWGWfsayUr166X3EygkKEeyGF5cfDRhWSw5MOp0Q/cGDOeS7ZoUydDM4cPJqlPx4RhsjGxVERDW7WC5rXjI+hOG6TQPxGRXAr7rFvHvhDR5A3GQ4NlyqHjdG2zfIEC7DgE0Q7a4uDAhfvT3OvXMlcuByYQMe7MvswfUioiUm/wdY37zJMShNTOTTKMNpr2GFil7YYhB9vhuWzSOuImPkgVyPTL4WEB1qs3roA6nbHHQPKlSyaHEzAkKJ2wSiFqHGzqu7Yh1aX2cz3c6IqV3VBns7jNjZswrFBEZHhkBOrUyeDFYPn/VmfEFzNz2/bIiO0lY8Lx6EcVMvY71Fe6erB9/Cxd03HnlYzWdTLHBnTPNQ6exyDmso/oM00K2uVJELiOH0koXDCBx+I61EENLs/Xe9ztz0R8T6FnB75fxEwmsxAwBi7zEOj4vjgzY5Yv2F5uzM5EdCb8BE84gOeVjf0vv+blUJ9/AYbSiYjsPngQ6h/fdy/Uo8N4/8yk8ZzkCzgOiYis2YBG6SOHjkP9Ox/8NtQVmlyHnxlFRNwInxN5sqI6XQiuj+PbjutwcoYVA2ggFxEplSah3rMbDeIP3HcA6ksvxXDCthUYcioi1nWQ8E89t0e+PSnF6dBvNhRFURRFURRFaQn6sqEoiqIoiqIoSkvQlw1FURRFURRFUVrCkjwbnnHEN9O6PJ9CvViLKGLr6h0KVwlJ82gcCuah4DsjdoBIrY76dZnCcCnhgD7S6E5VbM1ZZCgsqYbLJKjZDOmZIz4wEZEEBwiRbpX8Ej29GC6Vq6MGsH4ENYTT28Wat9FooE6fA5yyOVu7ONejISJSHD/VFsudqWYSnpiZ0LMmeXHCGL9Jo47nvkx1SOe5WsP2qVKoTiImONAj70JAKVqGdJjs54nzvbDmfngIz/WJkRP4e9JR7z981Fpne5a2G2Kftq7VBOpF80m6NjN2W5SrFFpUx22USnhthnQtRjFjCHusgjnBbnzNLAdh0JRwRvdu+DrnC1BiQo9c0uWSJ8MKGiNdb6lq63TZg8EXZqGGWt98Fs9tLmsHoHGoWo2D7ZL4+2bI16PtLXHpdGUKFLjnYB+tVbGP8XG6cUGySRzDHBqr125YhftJ7Zsp2G0xkEY/ingz/dRbfs+Q46TEnQnaC2hs8WMC9zJp/Jnhc0CBjnzPCH1szyAmzNNzcAwk66U0eYyjIEseJ0REkhzAys8bzvzeJx7PROxrq729A2qP/VN0X38uZ9u2MZDXhK7/uPsB/2y5vZJzCQIjzZl+x8cWd390rePF2k3gOJLw8bxn07h8Lo8hnCIi3X34rNTX1Qn1I/c/BHUzwvtUJmf7PQ8cPAz1M0/hPbhB561O4dC1JvpERES8iI7V6qPkSyLbxz997V/wB8bukewJzJI/Zc2alVDn83gvaER2W6TIS1cJTl2vtUA9G4qiKIqiKIqinGH0ZUNRFEVRFEVRlJagLxuKoiiKoiiKorSEJXk2so4viZO+CpKbOTH6WUPzWPNc/g3Wh0aUBUB6eMMiNhFxaW5x1g3yXOQR6eGLRVsD7SZwO5k0aotJridJbosYzwZnAtRJ3+2QJj5DGRknxiegzmbsOeZTpIEPQ/Sz+D61n8MaeVszzz9zTvPv5aBSb4gzo7tlLXuN/BYitkeA9fMh5YywZ6NWw77B3hwREWO1AuWhBPPPo85ZFCK2JtdPoY5y4/r1UG/auA7qnn7UZYqIpDwWUuOxhtQfjYd9PmxiW+zas9faRrmMuQhr1qA+/ujRI1A3TqAOtu7E6D9J45uYM7d7NUbr3WqcKJjN//F5PIqZZ350HDNQWOdfaMMcA4/+/nNivAj1VNker1ivzvkBk3QdcD9uBrYXrq0dtdE1mkc+IE9GQHPIm5jMkSRlC6VIu59K0ngfYe16uDx7m+L2i31+fL02gvlzOUREfLqnBDLTFu7ya+dr9br4M+c3l8bzzJ5IERE/i1lWecp1cF2sm5N4njn3IJGO8Wy42D4+mXNqZRxrXMpn8D17DJSIPaHYF9izV6OxPcjZ4246g9sNLZ8R1oZzNaw65n7p0H19wZvkwnfR+Twby+3fcJNJ8WbuWZy9E3enS1KGD2dxsGfFerCk3BIvxjPkkO9o+4UXQr2mF7NzjozivatUtv0VYYS+xy3n47NVOotepib1hUrNvjeF9DyR8Dj/CI+jQvvFPaWjs1OYzZsxH6S/twfqrg4c1/N0HOmc/UrgJ9hXdOo6YV/rfOg3G4qiKIqiKIqitAR92VAURVEURVEUpSUsSkZ18qs6+OqSvtNxYr5SNjSVV0TvNpH1VTxNCxmxjMqeTlEM/qxBXyt6Ae8Dft3V4Hn6RMSldfChOfRVHn+l68TIbRokzYro60Pej3odj4u3wV+5iYi4TdwGf00cNPkrXppWNEbyY+hr9rlTRZ78d6u/yj25/rlfTfKUlXHTJ7LMpkptyjKqWqNBNUkyWiCjivstN2edpvxsUp+u035XYr7aDC0ZFS4TGjw2w7LIgNvSlt5YfZSm5qzRZyr01XPDsdfJOoRgzvV7ch+WQ0pwchv12qlzwTKfIIi57ms0ZpGMqpHE33vU7k36fLNuj1eGO1FI547kRg2SvTgxUyjWE3i+61WSIPo8lTfJlWKmJebzlDAkpwlwv+pV3Afu9zw1qYhY/YWnQDV0rM06yaiimL5EN4BgRppVry1//5srVYwClB81Y/pfiqQ/kSWjws9US9jmSZJXNpoLy6hKVTxP5QrJUZvYV0olW8bikIS6EfEYiPvFEs50yn60aQa4jmoVZcYh9y+6x/B1FNv/4n62FGL6UkR9cm598t/LdQ+uzpnenO+Hjmv3jYBk7M9XRhU3pXY9wj7rhLhNlkPX6T7UaNjr5LGGZdtWdAHdy+Lu+9yfXOFnKzx2ljbzKB2E9hjboGurTvJXfk5i5aVxY2RUwTwyqpm2XUz/c8wiljpy5IisWbNmocWUn1IOHz4sq1evbtn6tf8p89Hq/ieifVA5Pdr/lDON3oOVM8li+t+iXjaiKJLBwUEpFArWX8OVn16MMTI1NSUrV660ApNeSLT/KXEsV/8T0T6o2Gj/U840eg9WziRL6X+LetlQFEVRFEVRFEVZKmoQVxRFURRFURSlJejLhqIoiqIoiqIoLUFfNhRFURRFURRFaQn6skFce+218v73v/9M74byE4j2LeVMov1POVtZqG+uX79ePv3pTy95vR/96Efl4osvfs77pSjPhwMHDojjOPLoo4+e6V054ywqZ0NRFEVRFOVM8MADD0gulzvTu6H8hHDttdfKxRdf/JxeYJXnhn6zscw0GjHBZYryHNC+pJxJtP8py0Vvb69ks9nT/r7ZjAn8VZTniDHGCu5Tnh8/1S8b5XJZ3vrWt0o+n5eBgQH51Kc+Bb+v1+vyoQ99SFatWiW5XE6uuOIK+f73vw/L/PCHP5SXv/zlkslkZM2aNfK+971PyuXy7O/Xr18vH//4x+Wtb32rtLW1yW//9m8vx6EpZylRFMnNN98sXV1dsmLFCvnoRz86+7tDhw7J61//esnn89LW1iZvfOMb5fjx47O/PykJ+NznPicbNmyQdDotIiJf/epXZdu2bZLJZKS7u1te+cpXQh/83Oc+J1u3bpV0Oi3nnXee/PVf//WyHa9ydqH9TzlbCYJA3vve90p7e7v09PTIrbfeOptMzDIqx3Hkb/7mb+R1r3ud5HI5+aM/+iMREfmTP/kT6e/vl0KhIDfeeKOVHq0ob3/72+Wuu+6S//k//6c4jiOO48jtt98ujuPIt771Lbn00ksllUrJD3/4Q3n7298ub3jDG+Dz73//++Xaa6+draMokj/7sz+TzZs3SyqVkrVr1872RyYMQ/nN3/xNOe+88+TQoUMtPMqzEPNTzLvf/W6zdu1a893vftc8/vjj5rWvfa0pFArmpptuMsYY8453vMO87GUvM3fffbfZs2eP+eQnP2lSqZTZtWuXMcaYPXv2mFwuZ/7yL//S7Nq1y9xzzz3mkksuMW9/+9tnt7Fu3TrT1tZm/vzP/9zs2bPH7Nmz50wcqnIWsGPHDtPW1mY++tGPml27dpm/+7u/M47jmDvuuMOEYWguvvhic80115gHH3zQ3HfffebSSy81O3bsmP38H/7hH5pcLmduuOEG8/DDD5vHHnvMDA4OGt/3zV/8xV+Y/fv3m8cff9z81V/9lZmamjLGGPOFL3zBDAwMmK997Wtm37595mtf+5rp6uoyt99++xlqBeVMof1POVvZsWOHyefz5qabbjLPPPOM+cIXvmCy2az57Gc/a4yZvo/+5V/+5ezyImL6+vrM3/7t35q9e/eagwcPmq985SsmlUqZz33uc+aZZ54xH/7wh02hUDDbt28/MwelnJUUi0Vz1VVXmd/6rd8yQ0NDZmhoyHz3u981ImIuuugic8cdd5g9e/aYEydOmLe97W3m9a9/PXz+pptugnHx5ptvNp2dneb22283e/bsMT/4wQ/MbbfdZowxZv/+/UZEzCOPPGJqtZr5xV/8RXPJJZeY4eHhZTzis4Of2peNqakpk0wmzT/+4z/O/uzEiRMmk8mYm266yRw8eNB4nmeOHj0Kn7vuuuvM//gf/8MYY8yNN95ofvu3fxt+/4Mf/MC4rmuq1aoxZnqQfMMb3tDio1FeDOzYscNcc8018LPLL7/c3HLLLeaOO+4wnueZQ4cOzf7uqaeeMiJifvzjHxtjph/2EokEDFQPPfSQERFz4MCB2G1u2rTJ/MM//AP87OMf/7i56qqrXqjDUl4kaP9TzlZ27Nhhtm7daqIomv3ZLbfcYrZu3WqMiX/ZeP/73w/ruOqqq8x73vMe+NkVV1yhLxuKxY4dO2b/qGyMMd/73veMiJhvfOMbsNxCLxuTk5MmlUrNvlwwJ182fvCDH5jrrrvOXHPNNaZYLL6Qh/Ki4adWRrV3715pNBpyxRVXzP6sq6tLzj33XBEReeKJJyQMQznnnHMkn8/P/nfXXXfJ3r17RUTksccek9tvvx1+f/3110sURbJ///7Z9V522WXLe3DKWctFF10E9cDAgAwPD8vOnTtlzZo1smbNmtnfnX/++dLR0SE7d+6c/dm6deukt7d3tt6+fbtcd911sm3bNvmVX/kVue2222R8fFxEpmWCe/fulRtvvBH66Cc+8YnZPqz8dKH9TzlbufLKK8VxnNn6qquukt27d0sYhrHL8311586dcD8/uQ5FWSxLfVbbuXOn1Ot1ue666+Zd7s1vfrOUy2W54447pL29/fns4osWnY3qNJRKJfE8Tx566CHxPA9+l8/nZ5d55zvfKe973/usz69du3b23zqLhnKSRCIBteM4EkXRoj/PfcnzPPnOd74j9957r9xxxx3ymc98Rj784Q/L/fffP2uovO2226ybMPdp5acD7X/KTwp6X1VeaLhPua476xs6ydzJCDKZzKLW+5rXvEa+8IUvyI9+9CP52Z/92ee/oy9Cfmq/2di0aZMkEgm5//77Z382Pj4uu3btEhGRSy65RMIwlOHhYdm8eTP8t2LFChEReclLXiJPP/209fvNmzdLMpk8I8elvDjZunWrHD58WA4fPjz7s6efflqKxaKcf/75837WcRy5+uqr5WMf+5g88sgjkkwm5etf/7r09/fLypUrZd++fVb/3LBhQ6sPSXkRof1POdPMvReLiNx3332yZcuWRb+Ybt26NXYdisIkk8nTfmM2l97eXhkaGoKfzc3M2LJli2QyGbnzzjvnXc+73/1u+ZM/+RN53eteJ3fddddz2ucXOz+132zk83m58cYb5b//9/8u3d3d0tfXJx/+8IfFdaffv8455xx5y1veIm9961vlU5/6lFxyySUyMjIid955p1x00UXy8z//83LLLbfIlVdeKe9973vlHe94h+RyOXn66aflO9/5jvzv//2/z/ARKi8mXvnKV8q2bdvkLW95i3z605+WIAjkPe95j+zYsWPer3bvv/9+ufPOO+VVr3qV9PX1yf333y8jIyOydetWERH52Mc+Ju973/ukvb1dbrjhBqnX6/Lggw/K+Pi4fOADH1iuw1POcrT/KWeaQ4cOyQc+8AF55zvfKQ8//LB85jOfsWaInI+bbrpJ3v72t8tll10mV199tXzxi1+Up556SjZu3NjCvVZejKxfv17uv/9+OXDggOTz+dN+u/uzP/uz8slPflL+/u//Xq666ir5whe+IE8++aRccsklIiKSTqfllltukZtvvlmSyaRcffXVMjIyIk899ZTceOONsK7f/d3flTAM5bWvfa1861vfkmuuuablx3k28VP7siEi8slPflJKpZL8wi/8ghQKBfngBz8oExMTs7///Oc/L5/4xCfkgx/8oBw9elR6enrkyiuvlNe+9rUiMq1/vuuuu+TDH/6wvPzlLxdjjGzatEne9KY3nalDUl6kOI4j//Iv/yK/+7u/K694xSvEdV254YYb5DOf+cy8n2tra5O7775bPv3pT8vk5KSsW7dOPvWpT8mrX/1qERF5xzveIdlsVj75yU/Kf//v/11yuZxs27ZNk6QVQPufcqZ561vfKtVqVV760peK53ly0003LWmq+De96U2yd+9eufnmm6VWq8kv/dIvybvf/W75z//8zxbutfJi5EMf+pC87W1vk/PPP1+q1ap8/vOfj13u+uuvl1tvvXW2T/3mb/6mvPWtb5Unnnhidplbb71VfN+XP/iDP5DBwUEZGBiQd73rXbHre//73y9RFMlrXvMa+fa3vy0ve9nLWnJ8ZyOOYUGaoiiKoiiKoijKC8BPrWdDURRFURRFUZTWoi8biqIoiqIoiqK0BH3ZUBRFURRFURSlJejLhqIoiqIoiqIoLUFfNhRFURRFURRFaQn6sqEoiqIoiqIoSkvQlw1FURRFURRFUVrCokL9oiiSwcFBKRQK4jhOq/dJeZFgjJGpqSlZuXLlbPJ6K9D+p8SxXP1PRPugYqP9TznT6D1YOZMspf8t6mVjcHBQ1qxZ84LsnPKTx+HDh2X16tUtW7/2P2U+Wt3/RLQPKqdH+59yptF7sHImWUz/W9TLRqFQEBGRX/2rhyWZyc/8NIJlHGO/7TqUTW7ciJbA2ouS+Ft6gw6c0NoGb9bahMwfkL64+HRn3lKeUwj70v4KYWhPjVgHan/G2i2PajqQmOMwgm3uuKc+06yW5KvvvWy2f7SKk+t/7PEnTrstx7Hbk9+0uea/0Dj0e+MtfF6tddDvPTP/7xdDzKU1L1Fk942ILh1D55rruHXMt/z0z6yfLFDiNqLIXmcjwB0P5ixTKk3Jyy5/Scv7n8ipPvgbv/5GSSYTIiKybk0PLJPO2n1wfBL3/7HH90B9dOg41I16E2rPTyy4b9z3IzrZ3Ed5LPEW8RdRxxo7+FxxJ43rtPgZ+/rDpcMwgDoI6Z4TswXut0HQwN+H2Da8fFy/5v08+ZkoimT//v3L2v++/g9fklw2G7tfrsfnKKaN+TMLjEgerXMxfz1fqE0X2qfYZej3CdoPz8NHmcWsk4l4DOSa77kxt4eFtuFwW0R8X18apXJZdrzu55ftHtzd3zXbB/p7u2CZRFixPrd5ZSfUF5w7APWlF18A9dP7jkH9pW/+F9Q9vTjmiois7+uGOp3E58iQxo1eWkfCtx+DoyqOw1vOPR/q8QaOTfuGBqH2Eva4vWagH+q+DtyPdevOhfrA0VGov3/vj6GOG6s2blgHdXFsDOonn3wS6u4uPIerBtqsdV5y8UtxP9dePvvvUrkkP3PdpYvqf4t62Th5ASUzeUlmT650+V82XH3ZmFOf+ZeN2Z+1+GvVk+svFApSKNgXg0j8TVBfNub87Cx42eDfG8MvG/Y253vZOMlyfK0/OwYmE5KauZml0ylYJpOx+2C1gfufoJuQ7+M1GQY0JloPkHHXH/fr+H0/ifWyEfOQam2Dxw5+aLLGyOf/smF/msaimGWsYzW439YrkbX8wv1rMQ/LLzQnt5HLZiWXy8VuN+48/uS+bOB++f4L/7IRvgheNha73efLyfW7rjvbB7hveDHPNIkELpNO4fiXy9IYmsZnQM/DdSZ8u48nk3juU1Tzy0Y6hduIfdmgU53NpKGuefiykaJ1ekn7ZSND68hmM1Dn8zn6Pb68pVLYVtxfp7eB66ylcZt8/0nSixnf06b3I0v7ab9YLKb/qUFcURRFURRFUZSWsKhvNk7iuUY8d+ZtKuK/VsR860DvMpHgWxX/kSR0cR0u/Tk2F/Paz3+lC+hNOKS/yAWG/tpt8A1VRMSx/r6wgGSAv8JZxN+v4/6CNj/8V9/F/NV9oXXwB2J+xvs5Z6UxX3K0lCAIJQiCmd1Y+C+SC7Wx9Vc6/osc/yU2Zh1mgTd6Q59azFm3llmgnRf6lmL6Z/O312LkJEv5/XNZR+w3MjTORKET++9lw0Sz38iYBeRKIiLH6Ov13Xv34eoc/qYD/7LkJbA2kb0Nq4+587d7s4kSAcezbwMsreJDM3Su+K9s/Bc2Efv8hgGNvfRNF2/T468+Yk5/GOKxNUnuwL+3xxF7nfzt08njWPoY/vwJgmB2DHwuhuCFvtngv1bb16h9n+e/HPN5Xuo3zHHLWH9Ffw7fNi10z7DOJ/c/l66TRdxzFvxWh26iLPMTiVE1zBkTw5jz0Uoy/qlvNnz6ptGPGUfKNewLUxWsqzV65qN1runtgHqgB2sRkU56jI2qeM0PFkegTmSxL61Yt8pa52QK92NXHeVIY8Uq1FV6tlrZkRemvR1/lkrM/40MPcqKR30laOBYJiISUv8JqLb6J32+q6vDWmffSpR/NRJu7L8XQr/ZUBRFURRFURSlJejLhqIoiqIoiqIoLUFfNhRFURRFURRFaQlL8mz4vjerXzUsr47RSEYOauMSpBtPBei2T7iotesuYN2VmLC2cfwY6vF2H8PPpHtwKrBUoQ9X4NqzBrAeuRWwht6azYXgmTCMY+/jQuuw98H6ScxSNJvLHC1tFDMzxHKxmJlYFvyMy8fG7cca8jgdsPWTearF6bytz1iThs2vA44Vsy8wQ9FiPDAL/X4hvTLXfM4WmgFLRPA4zoBlI2gG4s60FXu74saNBOlyczmcyaPSwHUkkzh7iOfibCFxM5PVabrckMS+qRSu0/VQx8vaYRHb1+HSteEn8dzVG3X8fIyU3KH7gUP76bAPJMKx3LWnGozZBran7+H4HrBPZAHPgog909Gpbry8enmRaf3+yetoMV6thWZ1WmjmssWMs74//9ixkGdjMW1urcOa2g7LuLFkoXGT+7i1n1Y/sNvb8iWxZj7kGa0WGstlXsvocgfspROOeN70NtNp9GU57GkRkZEatuGD+9DrsH/4IahNWIN6Ygrbqy1le2y9BH6mQWNRe74d6ryHY+ro/sPWOg0dS8LFKWLdEdymV8E6n7P7X4HGolwOZ3mqVbFt2mh2qhzPiFXHbcayxJngyhV7nTWaUdHkTn2msYSbsH6zoSiKoiiKoihKS9CXDUVRFEVRFEVRWoK+bCiKoiiKoiiK0hKW5NlwfU/ck7pFmuPeN3V7+aAEtdfEuYo7HazTdfRknLsC5z9O+/a8wpV9B6BOjoxDXZs6jvvUSevs22ytM5nrgDpyKNncmo576RkYLL42C2R1uIbfC2P0ywvpNxeYYzlep396HWsUM692K5mbXrqoxErW+bJG3NLosr6ZPr+oVNr50+aXmmcRu8oF/BWxeSDuAp9Z4hz0L0TOBhOn3fZYez0n1d1PLH/OgSuRuDPXXtBswO+Chr3/Ll1lTfIMBAG2e8OhZFoPfx82bc1yo4Y628inlFjSmqeTmN3BvgYRkdIU6oczWRwDU6TXrtOc77Uato2InV7LI5rvcsYDzRkfzO8FELGTzv0E7rfTwLZayEc0vYz1ozOGIw6kOc+F21ck5ng4qsQnzxDp2b0IP1Apo89SRGR8HO+5k5NYF8dPQF2t4jrixomTKeknaWtrgzqfw7pQQF1+Xx9mA4iIZDKokW9Sn+VMH/b/8B0z/hbE4zvXpH/nh4lFMDdVm/NwWk0YRrPNkM72wO86+zdZy3MUhJvC8/rk3segHjt2COpmBZ8Jjw9OWtvoKeA6OzrR27C2E/Mt2PrlNuxnqYCui/oUnuxaDQ+skcTzMNLA8VNEJHsCn0UL7b1QVyt4XbAnkDNI3BgDH/+Mc5ms3kbdp1a1n+ObVRwzuwfm3D+a9vKnQ7/ZUBRFURRFURSlJejLhqIoiqIoiqIoLUFfNhRFURRFURRFaQn6sqEoiqIoiqIoSktYksM349cl5U+bRXJRGX4XTO23lk830SiWjtDcs2oFBqXUy2h+7Mjg7jkxZqhkBo2KAyspBItCsSbKB6Ge2j9krbOWXwl1ZsU5uM0CGnsMvbPFZZNx4J5DRrGIAg0dMoRzbZy498T5g47iAsEWhkNgThkOI395DeLiuCIz2+cmdmNs0dxELhv+HA7toxAnajA3ts2RkE4+B5clk9gfOTxNxA6C4vO4YCBf3I5ZhnDeBJvMeQKDhTsPm9+XGhQYZ/hNJtDgGs4xXCb95f9bSblckmZjxohruuF3zaZtiuZW4yBJO0eSxgEP26ynE02u0/uE/aU4OQV1fQLH6iiJ6wgjux0NGa0rJTy2KMB+W6+jUTA2VI36dUhmebpUJAhweQ5I5G3GEdJ+Ck+0wem01kQccUFtUezPl5tDh9BMe/ToUWsZDv5K0eQAaTLQGzJ8Vit4z56YHLW2MVnH/taoYps3qQ4p2I7HRBE7ILNG57pMRtZcHg3jAzS5jIjIBRdcAPUll1wKdXtHB9RWkC71FTsg0v4Zj4E+B+GSQXwxfWruOrxlDtb1vNSsKT1PbS6uvS/1GvafKk0eEBnsG16KQjibeM2XYgz16TRut60DDeGBj+NdyevE33esttaZoQkKJE9m7ogmSqDJK5pNu083Gji2TJRxTE0l8VirZDKv1rCOex5ZYE6DmIdArJPplDCuiyspjp56Zi6XSrz4adFvNhRFURRFURRFaQn6sqEoiqIoiqIoSkvQlw1FURRFURRFUVrCkkT3WxJDkklO6zOzIWo3S8kJa3mX5F+miXq8FGn+nTTq5PIF1AQ2AzsoJZnCABfHRS1nKp2mGrfZTppWEZFi5QjU5f3DUIftqPHL9myEOlHAsBsRkcChIC3SLxsHdYcOaetYaRdyMo3EhU9RENtz8WzwfszR1XNIXqsJokiCWU0r+xZsLafD+ldaxrEajH0LdE5i9LQe9WGXQrQmS6hnHhwchLqnx+4rhUIBap+2wd6HiPtSrDdifr+E1TX41LJ/5TmESbEXZTFBgRx6NTdIL2jYHolWU6tWZ30AzQaNNRlbp5tO4XWfoP7hk2/IJQ3z2pV9UP/6r/2ytY2xEQyL+of/9wWoy6SZrzZQR22MrdMN6dYQRXTuAvZo0HmK0bNb+nXyYETUC5vNGtW4vrg+yJp39mnxtcR9cjE6fCMnPRtnNu2Pr5c4D8vBA+jrqFUwSDdp8D6e9LA9GhQiWarFtI+H/ac8hSdqeBC3we25ehV6JEVEenvZF4nntU59IyxjW5T2oU9JROSJp5+E+r4Hfgz1L//yr0C9eTMG/sb56xgOUeQ+z54th/Twll8vZh1z68WE276QBMEpW9MJGneqx0es5Xk8S9HuFsijtmIl9oVSCf0V1ZjQuRUrsP8NbMD7ZyeF540kKJA06LDWmaTNpJN4bFEB7z2JKvktcva9aYq8caMTuJE0PatW6th25Tq2le/aIZ72E838YdHi4H5PVu11jlKg4UDu1DqXEtyr32woiqIoiqIoitIS9GVDURRFURRFUZSWoC8biqIoiqIoiqK0hCV5Nvq9ccl501q0IE3zIzv2/O9OhLq1qoN6MJ4n2HFQr+iRJtfEzCnNul/XmV/HbUizlk5nrGV6ScKcb+CxTlFWR7GEno5k9xprnbnedVAnMu1QBy7p8q1cDtSsJmJyJWz5HGclWB+hz8fp707v2QgTy/yu6nkiM32A9bOs7RexIgvEI8sFS77ZkuFSxkPcfPBTU6h/3/nMM1D/4Ac/gHrPnj1QDwwMWOtkrfA552DOy4YNG6Du7ERda5yWvUH+hoX8E9yZIuo8sf6KRXgw5vt93BzzvN8PPPjA7L8rlQov3nJqtZqEwfS1WppCP47jpa3lregN6qeGvRCkcV69CvXGa1djtoeISNbDdnjVKy6BevAY6vR3H0D98eCorW8PKZ/I87jG/sA6/GbMWMN+Jh67PRpPyMYmDfIkJJO2vtjKOaDfh5TdsRjrkeexf2VmGzE+sVbj+/6s72ShcUJEpEmei1oVcw4qJbyXnRjG+uC+fVDv22fnUtUDumGmsK+0tWH/5PZsp1wEERGhZ4FaHdfRjEjPXkIPR8K3x2qffrZn/26ov/KPX4b6F9/w36A+79zzoI44o0UW42XjvCPsoYmE3aetNcwZN5+Ld+75UChkZn0pYYhtXpqyx2NTxxyGrgL6ch16BK2S9bdueYTsR9ZkG/a/VID71T+J+1A5F59V76E+LyLi0nVzBWWKrB7CdXon8PNmhe0tmXLwmS9LuRsNegaskJ04oAygROy55wAtut9Yy+MgW4rsa3HvcfRKZ9tPHVu5tnDW0Un0mw1FURRFURRFUVqCvmwoiqIoiqIoitIS9GVDURRFURRFUZSWsCTPRjadkeyMx2EqQG1YMkZv3SR9bET6sIh0cYbWwfqyOD0jaxbteYXnn2c4MjFztZPOjbX67aSzLNB+T4ztt9ZZHDsKda5/Pa5j5SbcyzRqBC15aIxHYaE5txdSGNttZ3/IcU9tI0os7xzfz+7ZLbnctOZz1apV8LtUjJ/CpSnLeY5zjy1ABj8wNIjn7Nlndlrb2LVrF9TFIopO29vwPG7fvh3quLnb95FO+umnn4Y6m0XN6dq1a6HeuBFzX0Ts9uro6ICary3uS1GIHTBuPviFPBvsyeB6MT6QTOaUxyrO49FqiqVJ8Wd8Q3ffg5kpvhtnVEBPmHFQs5zK4pzwNdLxhiGOkVGJxMEicujpB6BOlA5D3edhGyb6seN3t3VY6xyawP0uNkhrTteOE2A/dnx7rPYoE6lJfShySZ9NGnuX7h+cTRS3XStLJ6J8EPq1G3MOXTZ7zey2CZd3/BOZvi5PXpsO3cvY4ygikqSxokDac9OzHuoVK9CD1tODHjM/gX1NRGR4GD1ANfLWtLdjn2+SD4u9PNM7Rh5FynRqy2JfKlVRV16Lyc/ic+0lUOt/4Cjma/3bf/wb1JkcXhNrVtveTMuDQf3Rp2NdzF975xtHOTem1Wzeev7svWJiFPNTho8ds5ZfvRJzpPJ57I+Hh/F+WS6hf6w8iXW+YGcC1Rp4Xo6XsC9UE+ipPVLGc3DUs/PbvG7czoiLfbbtAD4btI3RNvs7rHWaLvTbeQXsG5k0+iVqNezDEfeWuPsNPbCxr8i+x+I6pmIsz4eGcUzobj9VVyu23+906DcbiqIoiqIoiqK0BH3ZUBRFURRFURSlJejLhqIoiqIoiqIoLWFJgr+u7l7JF6Z1ZdEJ1OdNUt6AiEgYkNaV9GIJ0tkbd/450n3P1gGzBtKwuYE0lK5l6YjTic+vLR/bg54Mn/wruc4ua5150spODqMuf6yIusJcH+Zy5AawdjKogxUREdbRs9aTPR1cxpk6LM/GqfaOEsurF/3MZz4j/oxe9M2/+qvwu6uvvtpann0FIZ38BLXHbvJffOvf/wVqJ8bTsm4dnpet558PdY5yXKx8C2uNdn8rl1EXOTKCGmn2eDxDWR8iIvk86kG7u1E/ynP2b9iAvo+ubtTeejE6a9ZiBwtkeSwml8MhXeoFF1ww++8pyrlYDuqNqgTh9N9oCinU9aaTtp7YT5L3oYTntkpemCDC4z1AuSwHnllhbWPkEI5HbpXGYrJCbFjVB/Vrrv4Za53/fCf6hB7bhX3Op2Ot1VCznIqx0+TbO6AuFotQO5Tl4pPHIwyov4R2f2mSd4SznErkgTFcW2uM8QadHDcW8Mi1AsfMGaetbBx7edsHSd4a+nNjJof3lU1bLoI6n++wtvHoo/dDfWwI9ewBZ32QFp3HtzhyWbyO2KuZIs/Z+KS9zohyDJp07TVDbJunnsVr4CtfxRyO/+8tb7O2sWYV+jhc8hVZvkEa3+LGwPm8acudszEZRJJwpvdncgrbuK+7w1qevYIenafRMnnSBP0+q3vRjxjFDCxDU3ifmerD56897ThWFWv43NnVttJap6TQW7KvirkapfNWQ92XoCy2wL4/9pWx33tT2L8GOnEdUYTnttnAY3dS9rln3y3nODHsT+7psJ9dV63FZ4OOtlN5IUnPzqk7HfrNhqIoiqIoiqIoLUFfNhRFURRFURRFaQn6sqEoiqIoiqIoSktYkujecSJxZvR6hvS19cDWhoWUIeCRxDWVQV1cWK1AzW9CsZ4Cwl1gIV5nFCN0tWYiph+kaB7xFGnpJup4HCIi6RWoXWxf0Q91UEOddfkoZjqUptDT0bVyvbWNbNcA7Sj5OkLWO9Lc+XFNxz+coxEN/eV9Vz12dFC8mXnFv/bP/wy/S+QK1vJbz0P/RIqiOAwdW74DfQ0XnH8u1Gs3YRaKiEgbaRwD0pXzVZGibfqenQ8yOYp+KJe8Jrk86liTSdIiU/8UESlPor+hVMb5ze/8zn9A3dmDHo31G7ZAvWKFrXPtps/kc9ieLBAPrPCYmIwD8jBAtoBZfs38K152haRmOlKG+j/PIS8i0qBx8a778LoeL6Jm2adDqk/ieXrgrrutbRRIu5tJoD+sTtkSA2twnEi32e24Yj1eT0/sGYLac1Cr6/O5jez8GKmhxjsRUt4CrcOQ58+1PEC2ftul7RoHrw2WxLPmPZm0fYEchePN5JaEZzhng/XWi8m+4Tugx6YN6+aHv+/rtT1D/f3Yn2pVPM8TlD0UBNjn4/Kz4rwLc3HJv2mq2JeimByqyOB2Q35m4fGEsj2efPJJqL/xja9b2/j/fu2tUHfR/aHRwG0mfNT2L5SVxcssZvkXknrQkHDmHpaiDKmobnvW9h3FLI4aXUwJygDqy+H12kV+i4mU7YUYbY5BPbQffW7tBbwPteeKUHsrsH+KiGTX470/2Yn33FIH9vknZBzqFXV7bOpI4P3hwJN7oZ4o4zjdT14SjzwcvhP3+M6ZLPP7Irn3VMeHhTlcw2trRfsls/9uBpqzoSiKoiiKoijKGUZfNhRFURRFURRFaQn6sqEoiqIoiqIoSkvQlw1FURRFURRFUVrCkgzikQklMtMGp0aTA0hsQ0wyQaF9ZF7hUD+3jqEnNjEGUocNpGyAsVL8Fvh93Dpom2RMdNko2kbGWBGpkymOzXwcSuTTcdXKaNwpPoshWyIiU90YKNS19hyo29opsIXMkWFcwCHVcz8S2b6+lnLB2hWSnGmnsUk0hX3p7/7eWv7qK3ZA/brXvhrqpIfdv5OCylZ3Y3vlMhgyJiIyRUE9lSoFRSWxbk/gec1k7FCcE6NoqktnyBRHwVD5Aq5jqmFfR6ZBYWe0zrRDQZZNnOTg6NHDUD9LAYgiIglqv75enARhAxnse1djMJIT87cPnyY18Ob00aC5iBkjXmBSvivpmes9TecyCqvW8hxsSF1OPDYo0xXXTWFmlRMnrG3kOtDMXaXrkm3DpTLu51jRDmStUX8pV/EzThX3u06Bjs2YsXxyAo2YHMjqurjjDZrogCd0ME5M2BkN1i57fsn0yxOdxN3H2FQZzgQBxhmyW84cgzjv13zhb6eH24N/TxNauPYjQwfdV4Zp4hdDJlU25edydkAtLzMxgX30yHEcI0tV7G+ub+9ngn6Wz5PJnDpPQDUbyh9+6GFrG5kkHvub34jhs+3taKpms3xcWCqbwOe2jcsdvMUMHxsSb8bUnqLBrD3mPLKf2yVDvE/PTik6nEoNw/TGSvZYtWElnpc1m/D5q3ct3oe623uhLp/AviQiMnjih1AXQ5wYoZDBuj+Nfbw9sMe/XUfRTL1iEwYCdyc7oQ4ncEzlrhE3oQ8bwkMKLbWg9i6OHrUWGTmB4YPnnHPqObNaUYO4oiiKoiiKoihnGH3ZUBRFURRFURSlJejLhqIoiqIoiqIoLWFJng0xZo6ok7wScXp/1s+SDpP1ypxPw2pE1jeKiDSbqGsT8lM4hnS1lqw1RvjGYVG0iEPa2FoDtcXJDGrvRETqk6htmzx+HOp+CktySJ/H/hcvJtClOYlhcGM7UYs41Ysa+b41qBnMdnRY64zM6c9zlFhezfzmzkjSMx6IqQy2x97Bw9by3/2Pf4L6gvMwmOeqq66AulrB/tgwWE9OoH5URCSdx3Od8LBv5FzUvrND4+CB/dY6J8aLUPd5qPP1SZPfTuetXMQAPxER18f2GjmOnpdOB/W2foT+i84uDOxzHNxHEZE0pSYeOYChRc066v7zne1Qp1K218kaZ+aMGZF7Bv5WYiKRmTHFocAzN0bPnkrjz3y6joVC6BwKHstSyl+yaevy62Xsl+PNItSh4GAy9QSOmVeu3Wqtc9fTOJZEIXY6h7TWEYVTNsUO9fNoIE0lsI/5Hta1Jo7dAemP/ZQdIhbSeO+RvylNuv2qFQxoty97M6KZcxZFZ8CzMYeFgu9EbA23w94s6m9CIZp874u74up1PNeVCurVuf34OYBrEZFyme6XU6jVT9K5X9ODOvw4J0PA6Yx0H6/U8D4+UUbfWoIG3mbMRr73ve9BzT6Pt/zam6Hu6iKdvhW8a/s45p73RXSBF5SxkeOz58sjv0jQ2WYtP9DXB3U2hW1YqWH7TNbmHw+TBfuaS63B+8bEKrzLTnTgfg6l8D605UJ8LhARuZyCUUtF8spVjkCZT6Bv6T8esJ9Hdh7H/rX+8iuh3rwBx+ETT6Av8vgh8knHXI3s2woCvt5xee7CnmM/Ywfk35xru/Fti9Fp0W82FEVRFEVRFEVpCfqyoSiKoiiKoihKS9CXDUVRFEVRFEVRWsKSPBuu687q9RKUC5FI2KuKSH8433zRsdsjrWJxctxaZmhwkLZJgnYWNZJGN1byyMvQOjiHg3VykaUDFjGkNy6Oowaw3sDPZPI4d34mixpV1qyKiCRIM25Yv3ccdYZDlFXRsWKltc6uVejzSBU6Zv8dNZYg2HsB8KJJ8aLpY+ykfIqtKzus5Z8dRZ3v0DOPQz2+egDq3Udxjukf70bNZBCjp3VIx1uvox6+PUI9fW87+hQyvZg9ISKSpfnKG+RLsrJPeALumPn2s+SnSFIYQyaB88NHLmXgOOw1sK+c9hyuY4Iu7yP7d0N9eBh9AXma/1xEpLcb50jPzcmdqCxhju9WYDijgI1WIuLTvPuFAvm5BjE/J+nhGFnIYrsPpLutbSSSuN1BymkZGcHroEY96L67HrLWOXYUdbpZ8jpEHo5nhsaeILDvB2malz9B/YP1whmadL9GInk/Ybe3Sz4r13BWAm6D70HswxGx73UnL68zkrMxB3vfbROBw6ps9lGSx8ylVBaX/D5Dx/F+KyLy+JOPQj1ZxP4XWZ6X+Z8LROx7boHuh+3kEWJvId/7RERqQnp0OtcOZ+JwFhblgpmU3cd9ErH/6IEfQT1FuRG/8ba3Q71yAO9JIiIhZd6YOfsdPqdsledOV0f/rIeE2zidKVjLNw1mU+XSOB52FWhMIE9RpYTntdo5ZG0jt5bGhS58NpoyeJ+YivB+uq9ht+EIeS17V+C43ZdDj0ZpCvt8d83O5DqnD59ZiiHu1xHyr7TT8vkBWmcl5vmZbst8ZCF9xNCzaipph6dtXI+elpHBQ7P/rtXsbKnTod9sKIqiKIqiKIrSEvRlQ1EURVEURVGUlqAvG4qiKIqiKIqitIQleTYaQWNWP852i0SMfrFJ+nVWkJmYOc3n4tDvXd/eRi6HOrZKk7TEpEE1pAmMj9mg/aSPNJOoCWxW8TidMs6nLCLikRbbo/mPJ6cmoC6VaF5x0if3r7T9FakMav3ZYpBJoV4yaNK84gcxF0FExKNzsGb7Ke1i1Iibzbx1DDciSc3sTzrD59XWT29sQ81jYw8e3z2j/wz1vfsx8+JJ8rSYGJ8C95WINLtJ0jT2teOc4Jdfi+dMRKSvDbXBDumRPdK+swbad+3zMnqMtNaU3+DlUG9bFc44YN+SvY3yBPbhQ3vRo1FpYFscLqJ+2Xh2W6TSuF/unOug2eDxZRlw3NkQHMO+loSdExIJeV2o5rnqMzSOtrXhNdtJtYiIS5kXThr7ve+hPyzw8FxOjKJXSUQkT/PMt3nYH5KUc1Ns4jrH43xDSTy2lEFdtO/geBSlybMRULZHzPBT4rHYw/aqsV8g4mvLXmlIQmfXmdY1Oy+Cv9UZusE5hnwuIdY+eS8Hjx6A+sEHfmhtY2IcM6OCAM9rGOA+sNeExy+ROH8n7me1imPJxARmC/kxzwpJ8lxM0HjFbdWk+2OC+m+jgXkiIiJ0W5c0eQsfeOB+qI8NoQfh13/t1611XvnSl+IP5tyHFvK9vtC8+Y1vl3Sa06Km8byFPQQOnUfhPDEfP1ClJn5m6i5rE20rR6AOczRWJfAekqCsj3yKx2iRpKCfIjTYFxo+jvUnQhxjV55r+1cmPPTBHX3qQaibg/i80dWFftl0N94fCzn7mcdE9PxL/hR+pp4q4T3Y5/MjIqk0PmPv3f3U7L8bDftZ93Sc/aOloiiKoiiKoigvSvRlQ1EURVEURVGUlqAvG4qiKIqiKIqitIQleTZq1fqsXrxJc/8nY+bnbdRJg7vAnNBOQHN8N0nTG6MnSydI305zaUeGtP0xunvG0uGTrjfRg3Msmyxq2uox84Z7lIuxJt0DdY2mAOcMgWoFxYsBzb0tIuK5uEyd5pRnHSvvZqJprzMd4jpzc7Tbjre888z/4LFds7rQjnaagzoRkzuSQl3lrhHUFtcD7Du5dZuhXtG7AurRQ7a2PaI2C6hNatR3SnX8/d/8zV9b67z2qpdA/crrduA2SBPtknUh4dh9vCOBP6uwHpnyHMIy6ktD2mbUtM99QP2tvw11/4ePY592aC79IMZANVXF/TBzpNpBTH9tOY53Kk/DxT5XnLD1q7sP7oP66CB6sTya6z9FmRk++TG8lP33oSk6V9Uajl+r16zCdaTJL2bsc9nTwGsnTeeqSef60Dh2ws6s7b9pz9Mc+1k81pRL9wvKzGhGlOUh9j3n2DBmMQ1N4fV3YhL7oKFjT8Rkd0QR3ZdmVhlSdtJys9D9NBa6xNj/dXzoMNQ/vu9uqI8cxv4sYnv/ONqqSff1FN0LmzHXcYm05O3tHVDXG7jO8XE873HZHdks5QCRZ8P6CHWFchmv3UbMGFip0RhAl2ua9O9DQ5g19NnPftZa50HyEv78q18z+29up1YzNTkijfrMMdB5dmM8G3weOMeGx3zPxzYtlvH5o5JCX4OISIdP92A6LV1dfVBnKA8kZez97szgvSubRo9QIJhZ5rk4rpQmOqx1RiFea9UKek1MO+5nIo/LT5Txeh+tYLaHiMgayiYKDHs4cB08jidjvNcO+9zm+D6caPHPgPrNhqIoiqIoiqIoLUFfNhRFURRFURRFaQn6sqEoiqIoiqIoSktYkmcjiqJZnWgQkg4zZl5rz0PRI88JbdWsQa2jTs51bD1tSGESPFe2CGsG8beGBaYx8Gcma6iRboSoGWzv7LbWwV4RhzICMj7qj13Sl2azqKGOm0ecNcQctxA2sT0j8tR4MdrZJGmas3NzJHz7fLQSN0qIO6P5rE/ifvWvbbeW7990KdQnjj0LdXkUdZYDa3Beay+Nbc5ZJyIihub1T9J5CT3KiqHX+527cZ9ERE5MoDa4XsXz1Ek6/jR10EbMefQCPPft7Z1QG/I+SYP0zDTPeFxEjkvXu1fBtskmsE+7ZDYJxdZ/JijTJjXnWJvuwtfuC41xU7P5GkOjqJfed+i4tfz4JF1jPnqNUtSlEim6hjkPhT8gIg7l3Xg+aWwd7A+rV2E/n4rsvJLEBGqlmyU6DurH52/B3J816zda64wC8p1VsZ9HdWzPkPNlfNS7i2fPj7+6D70iT+zH+e8nJoahbtI6khl7fnzeDzeabs/lTRlamDifAsPjT2kKdd8PP3QP1Pv34/hUPGFr5iXE7a5YOQD18eMHeEehbG+3x+463ZuqFbzncp4F3/d9z75OkuQVKRRQlz8xib6PKvnF/ATeoxMp6o8i4tM9YqJIXhIX15Gk8WBqCq8JEZEvfelLUI+OnNL6czu1migMJJp53uFnGhPjfWADj0N+woifz6gvTRSLUFfyeM8WEUnTo5Dr4n0kLOO9Txy8xpO+PY5IDdfB/jHfw2eDtd3kB/LsZ8BKBce34yvo99Sn+/I4bpfHsG8NhbZPNSxhf3ND8sHRdeJS+/tujGeDbrPhHK9SGONbOh36zYaiKIqiKIqiKC1BXzYURVEURVEURWkJ+rKhKIqiKIqiKEpLWJJnw3UdcWeMAC7pLuO8D6whZY8GE9J83U5Amm7Hnle9XEUdcEReEn8BHWvcfrP+05BmN0n69pHjqHudnLB1hRnSd7aRoSIiEXwjgVrOGk367cV4Ntik4adwP13ONZjC/Uz69vkpjaPGOSqe0qVHpSl7H1pIZzYl/oxPpKOA2uwVXT3W8m0Z1FGaNvQphHVs4+GjeB6nmpirEdRtbXtQQj0oe5e6+jqg7ujAfbjiipda61xJmmdTw220kZfEUN7DWN3u8yOTuI5ERz/UafIM1Uk/Wqa+wvk1IiJN0isfIb1y10rMe1hfQO3s0ZGitc4emiO9kDx1bMutVxYRGRwpzmYK7SePRq1p68QzOcrkob/v+OQ7SaWpj7mo23U8+9x29nTgR7CLWZpk9takXFt73oFdTMYD3G5vL57LlWvWQF0o2DkbtUoR1zlK3jefrlf6fIau50Zg51xw9sqGAbw2RsdwHXuOYR+qNW0zUhCSH8BML/Occi6eL8bM3rP4/soeSRERh+65PrXqnv27oD50ZDfU4+RjcJ2Y+06E57GQxv3qKGBnOnjkENSdXbZnw6HxpTKFHrJcRwduk3KXHA7JEJEpul9VSMvf1d2L66Db4dg4+lVMnG+Nc0zontuok2+Jcw5i8qI4m+Kb//nt2X+H4fJmXU1MjEkyOT2e8LMT7+f0z+gH1EBJvoY8PP5jYzjGVqj9RESyEZ63lV24TIn2c7xMvq2YZ0S/gPdHn0xqKRf7bEcODRjZpD3+HSxhhk2pUYR6cBCfP1b3oQ8uk8Y+3oxpi+PUn9opyyiZwfa1buMxbZFOc5881Z6cAzUf+s2GoiiKoiiKoigtQV82FEVRFEVRFEVpCfqyoSiKoiiKoihKS9CXDUVRFEVRFEVRWsKSDOKe74s/YyTlULk482xExhx/gVC/BBmaDZkh40KLurrRgDleQvOP9QlaR6x9nExehpxgSQoaS6bRYFmJMa6myWAUNbG92Nheq6HRZ7xOZsiYQD0/gefET2J7+l1opGqSmdJPogFJROTw7qfwB7VThq1alcJyWkw+K5Lwp09OLotnLpGIMTYJtnGejE7d526COtmBxuwyhZAl3JhQvwDPGxsAs23YpokkGrH7+9GIJiLS3olhU8eG0FBZCPA8P/DsY1BP5ezzuG3zhVDvP4HGz5LBuq8P+4qhgM11aymRSERSnWi+nSqeB/XGTdjeJ8hAXn/wSWudTer39z6xc/bfYYxBuNXsOzg0O/bxJZnJt1nLR5SIlKJgsQyNedkktnOlMgR1rWobQtP5HNV4/iMKXqrThAPVhj12F2idnRvw2uhdiaF9CRoDx8bR7CgikqQxkEPAsjk0EvP9gc20lbI9EUedAlezZGA8bwOaLocn0LRZCe1ATL7tnAySDc+AQTwMw1lT8GJC/HiClICCX8dOYOhhFGJfCBoUKFrACRtERJwUtjH3rxRNHMGBkL5vH8fKARwXD+zZi/tJH8nQZBNOzN9Rsxm8PqcmilCPj2FbrF2/nvYTx+6DBw9a2+BJKwYG8LoZn0CjOz8rRJHd/0zEz0HenH9bi7eUbC57agyzDOIxO0OmcZ6wIE1Brg2aBGhqEPvrsWEMxhMROXIQ+1dHG94f8zT/Ra4XZ9BwY4ztHHZnyCMdJnGbVXpGDCL7WSHv4f0x1cTtjo7heLZnGAMeN63E8bHpxkxmkcUwwZ5+vI+3ZUagLu7bjyuImSxEHHoun3Pe7RDt06PfbCiKoiiKoiiK0hL0ZUNRFEVRFEVRlJagLxuKoiiKoiiKorSEpXk2PF88b/ojQUB6sRjdm3AAlceeDdLdZ1HTVqNgOxPY2uJ0Cg/Bo22wci5ijdlz0DymKRhl9RrUATebtq6aNaSWZ4P0v2nSUfdR+wbG3nHWQ7rkMQgi1D82OJWoHqMXJc3uM0+e0tU3Y7TerSTf7klyRv/rpvA8VkPbP+IMox4x8vC8DA3jsY1OPoufJ89LLmcH9XAbJ5PYHwt11Flms9inGzFtODg4CPWjDz4I9d0+6eNrpOnNdVjrTIXnQv3ks3ugdh1sm84CHtfWDaihvvAc22uSymP/u/Kql+DvU6jHzeex/z2zy9a57j+GutX6nPDLUM6AZt5JizMTbJYmMXC+vcNavlRBD0GKfENZCqorTaBu3GSxn9cqdpCTQ/65ZBrbkYZZqdI6alXbY8af6exbB3WFvBE+h5cF9hiYzZCXyKFrh4JPPSsEFvebg7ZEbA9MvYz72d+O2v7VPVgfGMblRUQc6reRN93v3GD5/1YXRdGSwgQ59M2h85SkY+sgv09A+vYTo7ZmPp1lzyLeR8IGnre2PPb5dIz/sJ08QyvIQzZexnUWsjjOlkr2fiaov2zauBrqUfKxHRvCcbirG4NjV6ywfWtDQ+ix4nO1ehU+K0xM4vhWmrJ9SPys5c9pr+Xuggk/KQn/ZKjfwstz0B+HLTouPpNUqb0m6NjrLqWNisjew3jNDgxg3+no5JBmvOd6SeyPIiIR3WMrLo6RroPnaaKMgZEZ6bDWuS6PY02aTH91ehg9Oonb8Hz0wSVcXJ+ISNHF+7LZehnU2VUHoJ4cOgK1w8/1Eh98/VzQbzYURVEURVEURWkJ+rKhKIqiKIqiKEpL0JcNRVEURVEURVFawpI8G0EQzM513qBcjQz5GERE3Cbp8zjjguoG6fXKTdS0mRiNNmuiLX0Z16RFjp8ben4jR0D5FDWaV5znxRYRCUkLF5CWlrfJGRkp0rXGSKKl2sD2agZ47KHDNa6zHqPXi6q4zv6OU7pVzpRoNbWoImE0/X6cIj13qWlrXd0QdbsJyp84MYZ62R/+6HFcgYd9ur0d9csiIhMlXAf3p2uvewXUV1zxUqj37sP540VEaiXSptfxMj1C88FPlbEzrO6zczZ+dD9mcdTJK1Iro175qIdtt3EV9scTx/dZ21iVw+yFlEvzczfwOnENbiNVsPvf4OO7cBvd7bP/bjZdeYo/0GIC44mY6fPh0fBZb9i5H1nS6fJ1HdGAxBr7DHk60kn7wq/XsL90JjFPICCPxuT4GK7A2H9zqlrjKHv0sJycRM1yW4x/xfdwndkctg3fQxyH5/HH9eVzttY6QZ9JRtTPI/x9XzteK4MxnoQYC94ZIwiC2fuPR14d7jsiIk3KJuGskzRlRkUB5UT0Yo5VpUR9R0ROTOI9uOri/bGAXV44ViOM8WI2yBNUr+L4XivjfjbId1QmL4SIiOdgH165EvXt7Ck7cJgyCYpFqFevRs+HiEh3N+YcHD6MOS6jo7jO1f9/e28eZttV13n/9nDmc6pOTbeq7lh3ziUhA5kJmNi0YgMivr79ovI+kO5IBJ5gIkqCIhBRu2khBlAfn0e7JdBqg3aL8qKighBCEiCQhEx3nu+turfGc+rM5+y91/tH1a2q73ft3AFy6gby+/gE7+8Ma++99m+tvXed33d916+DOB+jC5w8jd9Zed0NwtXVrUXRwn8iIiY6dy0/j2GX70HIK6IakGYqR75ESVsreGziJMbHMMc7lBuZAZw3ooI9/4UJHDe1JvqjBBGOgzX5XoiTHfse0KXrtEN62GwRx1o1xDaOj6OHnItT7sJrGWyjvAd1qIMZbKNI3lhSsR8Jznbfzpqcs6G/bCiKoiiKoiiK0hX0YUNRFEVRFEVRlK6gDxuKoiiKoiiKonSFC9JstJttafkLdWZcH+paa6KLeJ539s9QLVi9hTVs7DURswkpV7BwLbJqi7l2jusMY/wqzhFHhtdtxvfDmHXQ+Ttc7sh9Y6gWztBzoYns+vCI6nO5nJPX/I5I+NFs2uvtV06fhnj6yHJ/s3al25SqNfEXC36HMrjedtK3k4P7sBNiPED1yJs2o+agRv2RTGJNr4gIyRKs8zg8hGuzO5R/L7/0UqvNg/vRA6M8iDX4M3Vem70E8WwK6zJFRDwfdzSgOulyGTUbV12+GeKxtahXOTVrb2Noww6IHQe3US/jOuFBRLW0/THnMFvCF5IrRqNjj4FuU+wfkERioS9dmluqNVs3lEhgziSpRr5G30mRjipNvhHptF2Xn3B4oGPYoppljj3Hvgy0mnjuWqTPKvSjx4CTwLxOs6eGiHi0Y4NDayDmnOyQP4NHurViL44LEZFOGvur6eM25+ax/9I++YM07Vr/epvm3sW5PE4j0W2Ms/CfiEgnoPk3RmtoeM432IepHuxD3yHfDfIN2jpq69YaR3AcTpFfhenFnM/RNsslWwfSR34UmzeNQpyZwvM0N4e6hsmTeN0SESmkcX7P+LhfMw3UwqXI/qNWx3uNehXr+EVE1q7F/a7VsJb/xEn07ti3HzV7A+TlISLS01eEuNlYodmIE292EWMiMYv3WOflv0AaDb4H8ch3o9pAXV8jwjkgmbfHfHUCdQcH9uK4cGheybUw34pFq0lJ5XAcJHzSUVK3R1WcUxsxBihH96OnxeQE5pOTxVzJ0PjuT2KbR04fs7aRT+N+JDw81sn6KYh90j5lY/xBWh3c7sprGt/Xng39ZUNRFEVRFEVRlK6gDxuKoiiKoiiKonQFfdhQFEVRFEVRFKUrXJBmI5vLSG5xbfN5qjWO02zw+rz8Ga7fkxDrvzyqX04m7N0dprrfas2uJT/bPlmCC7FrEVlfkaI6ape0Ka2WrWVgnw1pY9FfSLX87INAcgwJYhZ/D6nGmdcq5xrT8lwJ4pkprHsVEanO43d6e5frI6NVrlkuTRs509UJB7edGExan69RvpXL2D/9a3Cd9BtftR3iVgfX3G+3bV8RrslvNvkzeF5Lc1jPXKva6/p//vN/C/FAH67d3qbc4Fr2dmTnn9vE15JJ9sDB/UyRPiUKycMlZn131xKwcH7gNhpU59qXsevBe6j23/eW2zSsz1oFXGfhPxFbk5b0bU0Pyyk8l/1y8AMZnkdp7vE9ew5kuVLQwHMdtVmrhY0Goe1zILSfHaoNb3fwO45Lfg0xpyZB/ZNK4XeqNZxrHJr/rRrxmHX+WRPlebhN1+NrDM31HXuMt5q8nYUOvxiajciYpTpp6/p5fg1A2D+IPg9bt14OcWUC/XSG+mwtzpoy3gvMlEjLRPmXzuM58RNpq83ZEtazDw3i3LBuDOPeGrYxuMau7ef08cmzZnAQdYCZLGoB2nR/4tAYERFpkefWqVNYIx9S/7MPTzNGB5kgP5V0dvkcsI9Kt0n6eUn6C31tjcdYyzL2aMD99eierk3eEn4Gz6uJmWND+pv5of0liBMhnqftu1BvFvAkLSKJCt47pUj7xdqmqIPXslLNvq5PH0H9hBNhjhbIq2N0AMfaGsqd4w3bo6saoi5y7yk8jkwT+38zeTLlU7ZfXsiPCdFyf3aMPQaeD/1lQ1EURVEURVGUrqAPG4qiKIqiKIqidAV92FAURVEURVEUpStckGaj0wmk3Vmo+Wq1W/SeXWvINdWpJNZ0V+ZpTXOqAfRcrN9LJuz6sCTVTXPNLtcVGqp7Y68JEZGIPCwig/vRJE1GvY51mpaVR8x3uOY5pJp4KquWbIZrj+3+boVY53r88F6Iy7OoFwgbWJ9crdhrzLtUUxm5y3WtlqdJl5lst8T1Fs7F3NRJeG9O7P4oFrAeMaTzWJ08AvHmjfj54UFc83x62ta07NixE+LxcdyvU6dwXfWhAdRfnDyOa2+LiGRSWKc6R+dNHLtudSXttu2X4lB9t+thbabnUd/Uyf+BaouzoZ3kCfrTRZO0AD6N37SPx1mMOa4d67GGvF1f3s8F7crj1ne6SWluRvzFuuFclr1e7NpzL8JOYa0V92Kng/NAs4GfnwttTYHjUce7eK57Mlh7nqRzX6nb/iCRi3s2X0Y9Rf+mrdhmGvtCJKaWl+biOs0/7PMTkO9Sk3SC7bpdF92i15otnJsrNFW71HcJ395vj+rMz/RujK1F13EcZ6kOnjVDlh5RROwMIx0M/b1x845XQHyE5szDB5+ztpBLYRvrR4Ygnp7H89Zo0VwUkytt0jI1J/HalM7iNh1qI5G2NRshzVmnpzFX8gUcJ2uGsWa+Q98vU12/iMjp03iNSNCc4CdJk0D3RHxORex7q9aKcbHaPhvtqCPOYs0+a4biss+hezi6zEibtJc1Op5CP2pyE714HRIRMaUSxL1uDuJjz01AfHjPUxDv2InbEBHZRJqfoR5sM58ljVqLPL3q9vUxSRqNZBKPJU0eIhnSq8wePA5xa9ae/yL2GWIfjQLe04ysx3m835rHba3TynmG/ZfOhv6yoSiKoiiKoihKV9CHDUVRFEVRFEVRuoI+bCiKoiiKoiiK0hX0YUNRFEVRFEVRlK5wQQLxRrMl7qKpVDqJApl2O0YgTgKiZgPVeRF9JwgpDjCuVm0xSqVcwm2QQNAJUJEUdnCfWKgtIhIaEnGScUmzgd+pk8CyHWO4N0/mbbUKin7nS2j4sm3XZRDf8IqXQ3ziyD5rG3sn0eSlXcU2c1kUD5VovzsxwvZcL4r9MsPblv4dBm0R+Y79pS5R2JoXb1GF7Hl4HmumYX2ejeiSlO61WTTA2f30sxCbNgq0nJhn86/865dxmxGee9ZsPv4Y9ldfn21kV+xBc5+JGhpDseEaC2vjTLJ8Ni8z2DdGyLSN+y6DArnhnC0kC0nQ2zEkTiOhshfhcRyfQHG9iMhcHQWXQWt57HXaq2toJSISdkKRRdGsQ+JZnq9ERFxSzbMRHC+a0anieQpdFM0HtAiEiIhp4Dj2Ethmrh9FgWEPGU3W7TkwcEg4nS1CnMn1Q8w5F8WYPvpknlWu07GwnyGJSyPK+8i1L19taoR3w6HjqpMJWxAzCbKRYrComDRm9RXiKwXivPhJnEDco323joVM4VwHRasbL0HBeBDZ25gg0fjRE2isOz2L4m42d0wmbUNW+9jw2l/IY74FdF0vzdnmviwiT5GYtqeAfVPsJQE+GW7OzNgC3XIZ86lBhoacMh6Zq/L5ELHNLws9K4TE7urOga12a0kJbgnEY/LvXMbObTreCs3piSzef3RCexv5BF5Dr79sC7Y5iNf5f37wnyF++BuHrTaf66XFS2jxgEKWhP8soo6Z/yo09wcbhiEeJFPbZBPnxxPH8PpYmSpZ2/BIuF4Yxm3s2LYD4vWjG/H7DTufHF64acUc0mza913Ph/6yoSiKoiiKoihKV9CHDUVRFEVRFEVRuoI+bCiKoiiKoiiK0hUuSLMRttsSJhbrLVtY55tgYykRmSeNhgmwjq0wgLXETTJ5GuzDuuBDR45Y2zh5Eg1bZiaxPi+Vxxo0h6xnWpGtr+hQHWGHaprnZ1ALMTV9GuLJaXxfRGS2hPV3zXn8TKuDx54uYE28Y66EeO0g9o2ISKkfa/17r70K4rkano+noqO4jaFNVpsj266AOD+wdunfQbsp+//tr63vdItU5C2ZpJkA8y0K7brfZnT2+lAvwNphp439c3oCz+vounXWNnJZrOVknVKNNEQ1MiarVe263+GREYjZ1InNp3p60AzIuDHGUG3ML4+0TMVezLd2B/UW+w6hHmjgkkutbYS0n7UWml6VKP9cD2tBnz7ypNXmvnHU0eQSyzWpbJC3GiQS6SVTP3Ex54zYdbrtEPuxQKZxPk3Bs9RE3cFt9A7Z497MkfaKatMdMuYM01hv3Exgna+IyBXX3ADx1iswdtNY28+V1NmsnYP1GurU2oZM/RpY2++TwVk6jznqJu39Tvdg3bPfxr45fhL3YZLm7mY7ru4c+8+TM/PI6ms2jDGWnuECW4CIjXPZTNYl48qdl+E1RUQkRXNeheq+/Qxe607T9ZPnhYUNk76ujnPJLJlMFnKoKUum7PxzaHx6Lo7NXIYM9qivalU2v7TPQ4FM55w6zonlKuZ4eQ6PQyJ7DjFU/99Ycc0IY7QB3cTxkuJ4C/3k0/EnYq47loaRzmuZrkvlBhl50v1cJ8ZIeE2I2y3PY65MkTbTT6FZYyKw9ztM4GeO0xwrU3ge2TRXTMx9JRkzj+0go9wk6d5auI0K6Yu9IbzfW3gRx3OqB4+jMIjbjFzMz56MrffMUH+tNJ5sNOz7rudDf9lQFEVRFEVRFKUr6MOGoiiKoiiKoihdQR82FEVRFEVRFEXpChek2Ti4Z69kFmu62rSmfuTHaDaqWI/oUo1reXYGP1/GGrUslriJE1Oj61Fdb2ka19fO0Lrp7Elwespej3umjPqKGukt5uk7FarDFKr3ExHpH8L1jhvkKZKg/ivNlSCemkRtyo5N2J6IyBXXXQ3xoZPYv+PPoUajf+xlEKeKtiYhmcG6QHdlXaazus+qw+5m8RdrPj2f1o/3Y7wlKF+S9B3PYDzXg/XcmfR+iEdGUUshIpIkT4N6A+tFUynSCJHWqVq1fRO4FHzdENZZXnfpZogPNAcgPlqz18quT2MuJD3Mv61DWGPqJvE4njr0TYhrlZK1jbyzFeJOhMdWqeKxJ/twHw5Moz5DRCSVw87orCjvDlZfsiG+64q/uFY8Z38ntn4az0WNvG0C0rFRKBMzOLfsGlljbSHZg3k5NYfnLuvg2PBI+3Dtq9HTR0Rk+yU4N9TIp8U42Pk91GaTPTREJKLvFApYZ++HWL/N9eg++TP05VGrJGJ7EtQq2N8HTpIuaxb3M3Riav3JG8BZ9Jpg/d9qE+drwLDeKyAfA49uAQLyLzJUe55N0UVZRIY3bYN4voRzTYGm5nX9eN4OjdvX4Kl5PG8bNuyE2KdzMjuNfjy9ObuWfIRq3PNpPPZMCuMmzeVpun44FXxfRGSuwroO7M9cjsYiabii0J7UfNJCZFfoBIMwFBHbn6hb1OpV6Sz6CXXIi6kh9r5XA5zzO+TTcrKE89sU6SYNaTqSnp3zpwO8pzu+F31fzDyOcYc9pjx7vyPyR8nQfWaT7h3CBO6Xn7Hzr29kFOKAtHIT06gtWVPA94vrxnCbaRxnIva4GCRd9N4DhyAe2oLay6FC0WrTpXscZ0U+Ov75+7zoLxuKoiiKoiiKonQFfdhQFEVRFEVRFKUr6MOGoiiKoiiKoihd4cJ8NprNpaq8WgNrE/181vp8mupnW7RW9vQUrnFemsP1t59oYE1a/+h6axu1GtXc0lrEx44chniGatePHsb3RUT8Aq1fHGG9crWCWpSQ1ljO9dp9kclh3X0ti7qOZovWnG9hLVx5Dt8/ZOx6vT3Hsfb1+BzWMrZdrO3PrsHjdDx7v12qF3VX1ATye93mil3XL9Vkcx11MmnXEid8zD+usS7P43nMZ7GWeGANehq029ifIiKG1v3uN0WIXdrPgLw+wtCueWy2sIY042Ada4fWh28kcb+dGC1D4OJ4TQ9g/jlZ1PMk87iNeQ9raw/PjlvbSNWKENfmT0HskzeDH+A+tUK7Btp16Lyu6E/jru4a8yIiyYQr/qK+qkP5ELs39OecgGrojcEPhAbHFNeuH53F74uIbFuPGp6dO1F7NUB6sTnyKNi0Gb8vIlIhbZFP3i7JNMZHye+oOl+y2hTBNgtpPNZOE+fZOvkv+D4mdpS3x3yJ5slx0rw8secExDMV3Cdx7Esiaw3PaNWM84P4XXx/uK67NKewZiNOwxGSz0HImgDyx3JJh+eQhoWvdSIi+X6sC9++C/U+zz6GteiT4zh3bB9BbxQRkZ3bMCerbfYvotwo4tySjvHZ8Kl/0inUT+TzGPcXcV4NqO+Gm/b1YG4efZNOk0/E1CzOcTTVS6tpj++mg69VV9zjrLbPxq7tl0o6s3DtmOng3LR78oT1+ckSamnaZOQyF5H/k4/nqJDG61QY0+fpXsyfkbUbIR4ifYWha27FoTlARAzpOqbncB4p0cTepHvd/lFbU/uyHdshnpjGXDlyAvuvx8H8W9eP83pr2vanyXmU0w5q6abLeD5MCt8f3rDBajNJc8JK7Vy9ZvuEPR/6y4aiKIqiKIqiKF1BHzYURVEURVEURekK+rChKIqiKIqiKEpXuCDNRnFknWQW13guHUWtQ7F3wPr8urW4/ntplurFyGviaITxwT247v4gaylEJEPrgBvBmsBOC+vaCjlc2z2RtP0ZNq7fBDFJNuRAFevUwgbqRlzPruVtNLE20aFadIdqF+mw5MkDqG/xEugJISISOFg36GVwTf5Mgo6VNRfGrnN1HdZsJFb8e3WNDop9RUmnF46B/VVYGyEi4rm0LjrVHrao5j6RwHOSdTBXMhnbPyWZxDWoeb9a5EfTaJD+IrBrdMMO5pfv4zbGBc/jHMXBvK3naVew5tSM4LG281hL3PApxz2sYU3HrHfuC/bP/CS2kUtg//dksO7fIbuahQ2T/4eJ//dqUSmXxF9cbz9XwDkvppxdXMqHoMMfwoNo0/uui+f+ewdtT4J6hOdyU2YtxI8fxnXnjx9Dfc5P/Hs7r7dvx/rijsFt/NMXvwbxE999HOKEb88lGdJo9BZwu7UyavY6bRwbnof7kErZ+90mH4kTkzhPTpdp/NE8HOeV4rE2aPGUmdWXDEkQBEu6L2MufADwN1grGDZwvLFviRujC+nQa9k1pCG6Cj/fDh6CeOL4QavNftJcpJM4V5RO4xyXovk/n7av6yHppWZmMd+qdRxrhQLqQPJ5vB4UzkObWSD/mf5B7O9ZyscS6alERGZIyzpfWb7fMHGTThe57vprJb94TC3Sx95IuSQiMk++GQ06B23y4SiTf1OTNI6pDJ4DEZF8nvxT+N6qRnrYBt1rpW3t13wHr4eHTqH+sEx/pz9VwXvA3qJ9rzqYxdeOzByBeEMP5s7LR3Aef/nYDogT1/6YtY0MjcUkaYMjum4P5lAXMlqwvYvSpIdNr7gPqlTiLtrx6C8biqIoiqIoiqJ0BX3YUBRFURRFURSlK+jDhqIoiqIoiqIoXeGCNBtuJifeYp11Ok+1XTE181zj3qF6xr//u7/F95tY31crY93ckYPHrG10SFMwV8KaxzbV/YYR7mc2pkat08Y6wpDWWU+lsFazTTWAEsX5T1AdoYf1oQGdiiiB2ygH+P2erL3fqTTWhzoufify+BxR7MToHvg7K+qXo1X2OfB9f6levk6eLWdeX0k+Rz4bVM/IGo0MaQj8zrnXmGfNBtdRG4P5lyTdjOva9aIRlaX6HubjlOA2Iw+P3Xdw/XMREY88Dgyt3R54mMMdB2tlowCPPfLsvmgFeE7agnHGo/mA6nG9mL99sDcKeLu4dv14t5mZnhBvcR+MYH4ks3adrj3GcJ8j0ghE7LtBOqy5ht3vj+0+CfEjFLOeyae63Svmbe3VQA3z+B+/9E8QP/3UHog75IPgxXhQROSj4rgliEMhzxnDPhK4n82mXd/uUH+zN0Io2J+GdGfGsdfxFxrTztL/X33R0OTp00vXVUv/1bH1XwMDqCtqkk8B518igXNLkuZI9rcQEcmQDnLtWlyrv2fjLogvp2tKP3lkiIgc3L8b4lQOc2NsHfoYlCqoD8uk8ThERBwXz30keO4bdK9wijxavDL7ANnnPwywTfZmatI56nTw855j+y4NkP/HYHb52DphKHtP2PrNbpFwQkksjkPu4+E++57EoXNtaEwnaC6KSLfbof7sGHvOZx8ch64LPLuxdtONue6wP02dtSb0nQ75Eknb9u7ga+YtY9twv0gENka6jzU59BPJpOwcT5CQ0ZoTUjiefZajRfa1YGoO9VEPffnRpX/zHHQ29JcNRVEURVEURVG6gj5sKIqiKIqiKIrSFfRhQ1EURVEURVGUrqAPG4qiKIqiKIqidIULEogbZ1mzNzg0CO+lU7YoOhJUn4Skp3r6GRQZshFUPouC3X/75netbYysWw+x46MIrEDis2YLBVj+PArLRETma/gam0klyOSEBUntGCFxggz0Er3YfxvWb4F4YNNOiIv9o/h9J8aAz0/wCxCSNt6St7kxAnEhUzIQy3txQvjuUSqVlkymWOydy9lmPy6dl04Hzz2Lu/v6UIDFnw9iDPhEWOBGgtMI3w9IFM0CQhGRlk/b8WmBgg6Oi4BMJVMZO6c9F9v0KTdcSg43QlEii3MddroUkaSPx5bJ4HcSaRLu0TiJ0RSLS1nqrTjvMVrBrjOyZnBpMYLTUyicG0rZQleHJj02nYuoDzwS+1tixxhRvL02B27TjTHYW8lXHnzMeu3hbz4F8fQMirEdH4/VjVhEHXNyDOY6i7Mjh8Ty1KahNgPXNm5jMbwjuE2HjGRdj8WltkCXheDO4sIAzkVIwFartXSMfKxswCciMjWJJpB5MqrbtgNFqh61GZBommMR2+gv7dNcQe/3jI5BvDZmkQy/dwjiY0f3Qlwu45yXpGtyq2ULV3t68dh5QZA8ibXLVVw0I2Ihcsz1r005zfcbjZq9eMdKBvttc+QBui7lMsvnudnuyD8/bpsidov9+56T7OJ9WZYM43jBFRERh/IpQQa1Pn2H88+ne5q4hWDYSJcXuuH7NW7TsSTkIi4tCpGni1Mygdv0sjQfxkwNIS1WEYSYG2Uyb0x2cO7yafEKL2aBgt3P4cIKX/va1yDevAUNN7dvQ/PWVsee/05PoRn33Ir9bDZtI8fnQ3/ZUBRFURRFURSlK+jDhqIoiqIoiqIoXUEfNhRFURRFURRF6QoXpNloBx3xFuvWe8lwJM5gJKB6ZK4dft3rXw/x/Bya0xw7iiZ+w6OozxAR2bQFa05378f6xVoDzVWiNta5hcauuwxC3m+s8dswhnVv1QbWyJuUXUucHVgDcXEANRgDg2hS5JNxoEcmgF6MZsPh2myqfwypxtgIa0tsrYkxWMOXWFmMGGNA1E1cxxN38bh7etFAKJm0+5w1F60W1jxyDSXjU39ataFi19wHARtA2uPiXPvAWhKH6lo7Vaqrrk1AXOi1DYUSZOZTpDrWRIdqZ6l+PmBtimvvd7OOJlgdF+s5HWrTM2fRAy3iUw63W8ttBsHqmkqKiEgULA2TQgFNNKO4fCLNBuvYWMOTJlM1Q/kVxQlbqEaZa3k9B6d5bmFu3s4Xl8a2R7XWDmnQyEtKHGP/HcuhY3dJN8T+oW0yymLNRtIyKRXr4DzSOzVZT0fzG9eYi9haojPaNjYoWw1c113SarAWIs7UL5fHHOU57JlnnoE4T9q30TV4XcrEXNu4F9psaEYfSJIGsn94ndVmrY7X1J4qzi1OCo9rbhbvHSKx5+qp6RLEddpGLocahGQC85PveVgTKSLS9KjWP9cP8fBgEWLW/eRiTIbna2gmuP/Y8nzP17huY0wkZtF8rlq1tYEM56hL8wa/b32e8tWPuQbHSU0BNuVkXZdjj2PW1rFZKI8r1ozGtcmGeQGNk9kZ1EbkMjjWGjXUKcWZDJ+amoa4OIjaJ4fm8dMzZAgZM6em6Nguu+LKpX/XzqFBWon+sqEoiqIoiqIoSlfQhw1FURRFURRFUbqCPmwoiqIoiqIoitIVLkiz4bnu0jrItTrWEVZo3WsRkZC0D7NT4xA3W9iGT4sTj4yirmHj5q3WNh75Nq4RPzGJa99nc1gDGVINdadj1735SazdDCOsE5ytYD3f0IaXYbwJ1y4WEcn2od4kmcY6OF4/OkF9kaD3ec1vEZEgwv06U1t5BtZ5+D4+a/YUbK+KTcNFiDePLq8D3qhV5Ut/YH2la2QyWUmnF+oYuYYyZsnpc8J1lay/OJemQ8Re6z5Bdb5cusk103Frk/Ma3m4aP3O0iue56KIHQi5n/w2hnMaczlO9cTLCcWLIn8DIuWszq1RXHfrkk2CwP1n2YWJ0SG2qSa6v8MAJg+/jpP+AtDqdpVrZdAZruON2h9dr75BPgUc1spxPrANJJmwNEPtReJxzpNkIaJ947XsRezhFhvQTtE22XfFi6tmNy/oV8gPh46A50Pa1sDvcqmOmbfKY98nXJHbMc5PuGc3G6v+trt3pLM0hhs6jpZUQkUwGxz0fv+37g200GuhXkc/a1wie09od2g+q0+9EfA5sHci6zegzle5BH4Mj+/fjFxz0GGH/lAXw3E5Oncbv0OnMkY8EX3N9397vBO2HR3pPHv9T5GFwfAJjERFDooRac7l/O8HqajYymcxSTvH1Mg4+C5x/fI/CF0zbryJGVxpyG2ffJms4TMy8nbDmZdIXkgdGpUza4Ji+sQ6FrofpFPt/YBvVebzOx1hdSW8Rr+MDA6gZ4v6OuC9i5lT+jOdGsf8+F/rLhqIoiqIoiqIoXUEfNhRFURRFURRF6QrnVUZ15ufaxorSKf6JJ+rYPz9zGVWzgUth8lKkUQt/YuSfdOOs0Xm5v5B+VgzofV4uM265yohs5PmXpZB+2zP80zT/jCwiQRv33aWfRk1Ip4J/Pwy/jzIq6+dE/CnQhLSsaML+Ca3ZwJ/2GrXln4kb9YXSGv45/4XmTPvNFcuecrlD3M+W/Bkr385RNvX9lFFxX3AbXLYQt3Qh573Ly9DSd0LO8bbdZkR5z6tkOrQsn6GSg4DGu4npGz62gH4m7vh07B7tN/8cLiKGyhxXlk6d+Xe382/lNlaeT4ePN+5vN/TzexDxT/i0jDGtsxrRNlwuOxC7jMqqNuLlmeXcZQT8khHMSasEkafMmJ/XwxDPt8NlVHL2scNlVJxvC9+hPKX94O+EtPRtyHO/iFiVHovn7MxnVzP/Vl4DebudmDIqLkvh42/QNZVTp07l0rW0XU7Jy5N2grOXUQmXUcUsEyoRztV1Kudq0Fze5DnTrr8RLqNq0STIX+HSZqsELWa8B1Sm7VLMczeXicaVRRnazsrPdIKFY1qta/DKfFidMirrJiZm5y6sjCpuWVq7zbOXUfF1n7fJZaYxH7HKqPg4uIzUp32I6317qWBa9vwFKKNaufzwmXw4n/xzzHl86sSJE7Jhw4ZzNqa8NDl+/LisX297oLxQaP4pZ6Pb+SeiOag8P5p/ysVGr8HKxeR88u+8HjaiKJLx8XEpFArn91SovCQwxkilUpG1a9faT/ovIJp/ShyrlX8imoOKjeafcrHRa7ByMbmQ/Duvhw1FURRFURRFUZQLRQXiiqIoiqIoiqJ0BX3YUBRFURRFURSlK+jDhqIoiqIoiqIoXUEfNrrEkSNHxHEcefLJJy/2rigvUTQHFUX5YeCWW26Ru+6663nfHxsbk49//OMX3O69994rV1555fe9X8pLA2OM3H777dLf36/XzC7xknvYONekpijdRnNQ+VFEb+yUbvHYY4/J7bfffrF3Q/kR5Utf+pI88MAD8sUvflEmJibksssuu9i79CPHeZn6vZQwxkgYhpahj6KsFpqDiqIoywwNDZ31/U6nI4lE4qyfUZTn4+DBgzI6OiqvfOUrY99vt9uSTCZXea9+tHhJ/bJx6623yoMPPiif+MQnxHEccRxHHnjgAXEcR/7pn/5Jrr76akmlUvKNb3xDbr31VnnTm94E37/rrrvklltuWYqjKJLf//3fl23btkkqlZKNGzfK7/3e78VuOwxD+c//+T/LJZdcIseOHeviUSovZjQHlRczZ8une+65R3bs2CHZbFa2bNkiH/jAB6Sz6ML8wAMPyG//9m/L9773PchrRTlfgiCQO+64Q3p7e2VwcFA+8IEPLDkTcxmV4zjyJ3/yJ/LGN75RcrncUo5+5CMfkeHhYSkUCnLbbbeB47qixHHrrbfKu9/9bjl27Jg4jiNjY2Nyyy23yB133CF33XWXDA4Oymtf+1oREXnwwQfluuuuk1QqJaOjo/K+971PghWO7pVKRd7ylrdILpeT0dFRuf/++7WSYZGX1J9OP/GJT8i+ffvksssukw9/+MMiIvLss8+KiMj73vc++djHPiZbtmyRvr6+82rvN37jN+TP/uzP5P7775dXvepVMjExIXv27LE+12q15Bd+4RfkyJEj8tBDD53zrzTKjy6ag8qLmbPlU6FQkAceeEDWrl0rTz/9tLz97W+XQqEgd999t7z5zW+WZ555Rr70pS/Jl7/8ZRER6e3tvZiHovyQ8elPf1puu+02+fa3vy3f+c535Pbbb5eNGzfK29/+9tjP33vvvfKRj3xEPv7xj4vv+/LXf/3Xcu+998of//Efy6te9Sr5n//zf8onP/lJ2bJlyyofifLDxCc+8QnZunWr/Omf/qk89thj4nme/Mf/+B/l05/+tLzzne+Uhx9+WERETp48Ka973evk1ltvlc985jOyZ88eefvb3y7pdFruvfdeERF5z3veIw8//LB84QtfkOHhYfngBz8ojz/+uJaXykvsYaO3t1eSyaRks1kZGRkREVm6kH74wx+Wn/iJnzjvtiqVinziE5+QP/qjP5K3ve1tIiKydetWedWrXgWfq1ar8vrXv15arZZ89atf1QvwSxzNQeXFyrny6bd+67eWPjs2Nia//uu/Lp/97Gfl7rvvlkwmI/l8XnzfX8prRbkQNmzYIPfff784jiM7d+6Up59+Wu6///7nfdj4xV/8RflP/+k/LcU///M/L7fddpvcdtttIiLyu7/7u/LlL39Zf91Qzkpvb68UCgXxPA/mru3bt8vv//7vL8Xvf//7ZcOGDfJHf/RH4jiOXHLJJTI+Pi733HOPfPCDH5RarSaf/vSn5a/+6q/kNa95jYiIfOpTn5K1a9eu+jG9GHlJlVGdjWuuueaCPr97925ptVpLSfV8/MIv/ILUajX5l3/5F73JU86K5qByMTlXPn3uc5+Tm266SUZGRiSfz8tv/dZvaTme8oJxww03iOM4S/GNN94o+/fvlzAMYz/P8+Xu3bvl+uuvh9duvPHGF35HlZcEV199NcS7d++WG2+8EXL0pptukmq1KidOnJBDhw5Jp9OR6667bun93t5e2blz56rt84sZfdhYJJfLQey67lK96BnO1CeLiGQymfNq93Wve5089dRT8uijj/7gO6n8SKM5qFxMzpZPjz76qLzlLW+R173udfLFL35RnnjiCXn/+98v7XZ7FfdQUZbh+VJRXkg0v15YXnIPG8lk8nn/UrKSoaEhmZiYgNdWrr28fft2yWQy8pWvfOWs7bzzne+Uj3zkI/LGN75RHnzwwe9rn5UfLTQHlRcjZ8unRx55RDZt2iTvf//75ZprrpHt27fL0aNH4TPnm9eKEse3vvUtiL/5zW/K9u3bxfO88/r+rl27YttQlBeCXbt2yaOPPgp/AHz44YelUCjI+vXrZcuWLZJIJOSxxx5ber9cLsu+ffsuxu6+6HhJaTZEFmqNv/Wtb8mRI0ckn89LFEWxn/t3/+7fyUc/+lH5zGc+IzfeeKP8xV/8hTzzzDNy1VVXiYhIOp2We+65R+6++25JJpNy0003ydTUlDz77LNLNaNnePe73y1hGMob3vAG+ad/+ierpl55aaE5qLwYOVs+bd++XY4dOyaf/exn5dprr5V/+Id/kM9//vPw/bGxMTl8+LA8+eSTsn79eikUCpJKpS7S0Sg/bBw7dkze8573yC//8i/L448/Ln/4h38o991333l//84775Rbb71VrrnmGrnpppvkL//yL+XZZ59VgbjygvCud71LPv7xj8u73/1uueOOO2Tv3r3yoQ99SN7znveI67pSKBTkbW97m7z3ve+V/v5+WbNmjXzoQx8S13Wh9Ooli3mJsXfvXnPDDTeYTCZjRMR86lOfMiJi5ubmrM9+8IMfNMPDw6a3t9f86q/+qrnjjjvMzTffvPR+GIbmd3/3d82mTZtMIpEwGzduNP/lv/wXY4wxhw8fNiJinnjiiaXP33fffaZQKJiHH364y0epvJjRHFRerJwtn9773veagYEBk8/nzZvf/GZz//33m97e3qXvNptN83M/93OmWCwu5bWinA8333yzede73mXe8Y53mJ6eHtPX12d+8zd/00RRZIwxZtOmTeb+++9f+ryImM9//vNWO7/3e79nBgcHTT6fN29729vM3Xffba644orVOQjlh5b777/fbNq0aSm++eabzZ133ml97mtf+5q59tprTTKZNCMjI+aee+4xnU5n6f35+Xnzi7/4iyabzZqRkRHzB3/wB+a6664z73vf+1bhKF7cOMZQUbiiKIqiKIqiKN83tVpN1q1bJ/fdd59VbfBS4yVXRqUoiqIoiqIoLyRPPPGE7NmzR6677jopl8tLXlo/8zM/c5H37OKjDxuKoiiKoiiK8gPysY99TPbu3SvJZFKuvvpqeeihh2RwcPBi79ZFR8uoFEVRFEVRFEXpCi+5pW8VRVEURVEURVkd9GFDURRFURRFUZSuoA8biqIoiqIoiqJ0BX3YUBRFURRFURSlK+jDhqIoiqIoiqIoXeG8lr6NokjGx8elUCio7bqyhDFGKpWKrF27Vly3e8+tmn9KHKuVfyKag4qN5p9ysdFrsHIxuZD8O6+HjfHxcdmwYcMLsnPKjx7Hjx+X9evXd619zT/lbHQ7/0Q0B5XnR/NPudjoNVi5mJxP/p3Xw0ahUBARkY989L9JOpMREZHBNZvgM7PlsvW9SrUCsefi5pIJfBJqVuZx5zx8gjbGfnJy/ATG9NRdr9foG9jG/HzVarNRn4Y4aDUhXr92I8T5TOpsmxARkcE1IxB7CfzOifFxiCvl0xAnAjyORg37SkRkZg5fCwX7ZmgY96EdoMWKS/skItLb1wfx3j3PLf270+7IX/+vv17Kj25xpv0jyW3S43giIhLSrjqt0Pqe02rTKy2IIieAuG4wFzKSgdjzivbO5dLYJuWsk8VkoE3GE5L1jUdt0LFH9Q6+0IrsNmnsOE3qrxC/4xjaURePK+zPWZtwevik0DbHsX+dRgl3UXC+WICnqJ6lf81LJJtlvOv5J7Kcg2/48esk4S/sUybjwWf6R/us7x07dBLitJeF2KFz225hjlarOO6zacw3EZFaFce9CTEfLtmxHeLtG/GicOzwfqvNuWod4qNTJYinaK7JeDjX9Pb0CNOOMKfyGTyWgQL2n+8lcZsz2JeZDG5TRKSv0Avxlp27IP7Gtx+D2OApFM+zx042h+esvHit6wSh/Os39q5q/t318zdLKrmQf6dPT8FneopZ63uZLPaRS/NAJoV9nEhih/BfKwPKLRGRZgfnElewjXQC9yGfw7jTaVhtJmm/iv15/ADbg9GJrNbtiXZmHrdToXmzXMGc7zRx7A32Yn5m0vb1cqo8R23inJZNYc6bAPuuWuP7FZFiEXO6017e73YnlE//41Ordg2+5d9fLb6/0NemiXNVwuHrrciuy3DuSfjYZ+vXjkLc9PEcVMo4z0wfLlnbqJVou23Mr+MncZw8ffQAxIWsPW6KeezzPprPLrtkM8QJH+8VZst4HCIi8zW8R56Zn4HYx5SXTAr7yhWa+zv27Xurhuektx+PY3htEeLrfvzlEKe304QoIpGP48TPLt8L1KtN+X9vuPe88u+8HjbO3MCnMxnJLD5sZLN4s9Ho2JNQJ8QBzw8bqQQdWIBtJOjGLYp52HDP8bARRXzxwDZabXtSikI+ydhGmi74Gbpoxj1sZCmh+WHjTL+eodPC9xMB7qcJKDNFJJnEvggFP5Oi5HW8cz9s8LEmk/Z2u/2z6pn2exxv+WHD4c/EfY9PBMYRve8LNpKh2LPaExEHcziim3KHLtZxTVjwhfQcbUQu5Xjs+XDP/hF6wZGztxm69qTkePQaP2xQXzm0TyZuvw2f6BXfMWfa7f7P+me2kfB9SSQW5rEkzV+ppH3ze+azS7GHsUsPGybEm4+E71FsT9n8mYjOHe8X32CmEnabSXrNp214tN8+xQnOBRGJHMxr3m9rm9RX1ud9exvcRppvpuk79sOGnUvcJrexmvmXSvpLDxt2/tnnkV/z6BqaptxIpOg809zTsf+mY/0hwjV0Dqz8w9h37WtwMo2fyWbounOOh40wss9JuoXbadOxpFq4307Ix8G5ZY937m/rHFEu8W7y5+O+4xj7gXi1rsG+7y3NaRHdkyScmH2nPkrQ/VqG/lDr+Nhmp0VzVcwc20lQfxjKL5qLXOqruPIfj77D8x/vR4KeFJIJ+344QQ/d3CZP7Xzt4HHFxykiEvmY1EnaZoru37JZvO/M5O1zGPI1KGfn2vnk33k9bJwhlcxIKrlw01yv41/7OzxyRcSlh4ueAj4dFuivwqYX/3qRp45w+dFPRAzdsHCSzM3hXxqCABNz0Prrt0itik9p1fIsxD30lMvzQ4X+0iiy/NewM/Cx9NBf5PDIRWbH8a+PqZgBkk9jf0/TXx+nJ+gmJIMPjCPr7J/B1vQXIT6YXvHQ5F5Q+vzAeMYRb+kBgG6O7XEnDg1Oh6+UdL1yhBvBv4TxxUdExGvjayZLD54JGoS8TYpFFuogIaYHZofmMYcbzcQM/Bo9WAY8XvniTW/ThOPm7A53fNpum46D/vjgSNydC8M3h8uxZxw5ryZeQLZvuURSizew4yePwXvPPGn/QjBxehLibAbnOJ6kq1X89cej90eGBq1tNOnXj7WD+Jmto1j+cOQk/or6b888bbVZ7C1CPFzsh7hTx7+gZXI4lyRibgrqNRxPE5MYHzqEv+b20PVgeBTn3bZj33TtP34C4ska/mV5/DQeu0v7OThq/4XOpzvCnp6FMd6OvfPuLumMI+nkwtyfy9LNSszPpvyrAj/g+/RLRkA3kAFNUHE3ez0F/ENao47X1Db9QS+RxvOYLfDVTiSdohstPtd8c0N/lIi7ac9Qm036ZT9BDwrz9BdzI/QX3pj7kTCkY6f7i2IOr/M9vTiuUj7er4iIGIN5lk4uH+uq6yfCjsjiH7d8ul7ydUlEZG4c/3p/euI4xG4d/7Ke6cP+SKfw16Q++oFLRMQLqBKljWP+8iuKEI9uuQbiKGa/52dxHs6lMceT9Me2Nv3K05u3f9ntp18Zrrr6Uog3bcFfeQ4dxOvJgX14vdm+A3+1FRGJUrgfo9uwPxP9mPPZMcytMI/fFxFpNvBXmvaKyol62/7886GrUSmKoiiKoiiK0hX0YUNRFEVRFEVRlK6gDxuKoiiKoiiKonSFCyq6n5mZk3R6QauRorrwGq3YJCIyM4urADT7sEY3GsB6PBNg/ZdDtespeyEW8RJYN8k1z+VSCd8nrUloCchFXKrN5LrLRgOPI6BHtnLZ1mxweW++pwixx8Ip0rNk81gTXZqxV/8ypGNIJLGNdgdrZ09NY31zo2P3RZVEdfUVfdFu23qXbhIZI9GimIDFphInWspTTS3pK5waHpvbwTYCg7XwHWPnuN8qYRttzGknRwK4BO53XL0or4Pg0LEaXjiBToPTtIUgbovasD7B5x7jKEVi77RdE82tGl7xKuCa8nPoRkTEEvWvEM1FJlx1zUZlfl7ai3XrVVrJrlKyV5LJpLEevdXC+teQBOH5PBYlDw2g/oJr8EVEeknb1kOLdxw4dBDi8RLWUTspezWWGtfZ9+J52LRuLcQtOneVpr0aS0SfcX0SlZPeqU7XlFqLVjUq2PvdpkUvmqS7Wr8FV+SrN3EA5nps/YChvG0u7lfnImg2mq2amEUtWo7mFp81UyIyMoz5U6lhnzZbePy8YIFLtenWvCsiCdpuk+aOTgev6z7pPtIxq4rxanhRdK5l/HjlSvtaxqtfZtJ4fag1cCL1aKzxClm5GK1JpoI53JxAzVajgf2/ZmAI4kTC/vvvzAy2YVZMemaVJ0Df5MSPFvKvrwc1CAlj3w8UUnhe1u3aCfFAHjVStQbmG0tqB9ahrkFEZHQj9mGnjfdfQR3n6WszuN9Jxz6PScG5JQoxF2abeFwz83gejp44ZbUpNDeVKnheKwHOmet24X7eeC1qPLbu3GptwvVxG5ki7nczwvdPjKPeJRvYjwQDfcMQt1fuZ8e+J3o+9JcNRVEURVEURVG6gj5sKIqiKIqiKIrSFfRhQ1EURVEURVGUrnBBmo1isV8ymYVaNj9ZhPfyMcs9Z7JYU8oGIg6tH81rZ7PfQJy+gutpa+TAGVBNNLcZa+jiYLe0ybCwXsfaumIBa6Tj2mQtSUT+ASHVXjoO1honXdyHKGGv8S0htpkjUxjWq3hUD1nr2PW46Satu77iI2x03W2csCOOs9BPbo0SrhljdJSmfOqjGu8C1tc6dcxXr4Xn1WnH1Cey+22FHOnJ8Ep6aG3ydIzWhDuWDfSo9tNpU511w65vdgL2uGANB/cfjROuq46TbNC69VKnnI4oppyPSyf20XFWmEQ5xhU5/5LRF4SZ6VNLJm8tWn88FWOKySZVawZQk8GajmJfEeKEh21OnsIaWxGRFq11PsnaN+rZgPKrmMZtiogkyX9hjtxvNw2jJ89p0saVqramLE3mp8VejCvz2J9Bh/QC5A3DNfUiIllytk/msP/7+7FGPFPBNttNO6HCkDQIi3XPnWiVJ0ARcVNZ8Rb9IIzBa4IXo9kw5D+RIK+JFhnpsvlsgq4zlqePiDRpXgzoOj0wiGv9swcGO96L2JqLkOYO1+V7Bfy+G6MtYVM+Q8dWI68wnw1syaSUtZxx+8W6kA6NzWoDrxfs9SGC3kIiIvPzy5qE1fZ6KeSHl8zp2LgzHXM32Wyh50VEutGUR1rVJI7PUhXP46EpWw9bHMT96CUzjhJpNtaTh1B9zj6Ppyuoa2M/vWoH5650FrVRuUKMu/wUapjXjOEcWiBvjjZ5Yxkfx8ThZyasbTRm8P53dhqPo9TA/hufwbH7y+94i9VmLxk7T88vX4OcKO5GIB79ZUNRFEVRFEVRlK6gDxuKoiiKoiiKonQFfdhQFEVRFEVRFKUr6MOGoiiKoiiKoihd4YIE4pdf8Yol06k2i4ljBOIs6oosgSgKXlhL61qCcXsbEYn0+oooRuN9IK2fOL4tMjQRirhaO19G7+M2EywIj9lRNtRzSGzGZkmGDXJCMhxybGGO45KYz8PTyyZULAlmAycREZ9EmEG4fBz1Wk3+96c/bX2nayRdkTPHTYZgjmcLxIWE/dLA8+qSWNfkaDiUsD9cH8WnIiJOm7YxTQK2WRTIGUOLCRRjnCpJnBuRsaKQaZ/ToHyL6QrLcM8SZ1MbnAqk/nOcGDEq69LZ1I9En+dnSIXn2awQl8b4dnWdcqUkCX9hH3oLKOhLsYmk2ELrDBnX8aQ3M40C8MlTKPCzfBFFZN0GNNgLyQCtXkfR4Kb1GyFuVnFciIi0Alz4oE7C1jK1mSIRYZyQuEALhNAQlk4W+4qGqyRoG80YU9FmiCJzQ2PHqcziNkgg7gb2HNjq4HbCxWMLgtU39QslIYEszMkeudyaGIfQU5MliP00Dppcjuc0MvNkoTZfQMU2pB0aQWNToUVaOg2cEz0vZpEMunbZC1jQvEDXZL6XEBEhv0JLrMzieIeu65NTODZbdXvurrVw3BT7aEECMtoNSOQfswaOdOjmKl9cFiO32ucyO3xhicKERIv3GR0yPw5DezyOjKBw+vC+/RAHHcy/YTbVNHhOvACv2SIis5N4Xmp17MRkErdRj3Denq3iHCsicnIC54lUP+Z4hYwDZ48fhrgVs3jAfAmF6nMhjoPyE9hmJJyfKDo/efKotQ0vws9kaAGake3Yn2/55V+GeM3aotXmfAP756t//42lf7ea52/srL9sKIqiKIqiKIrSFfRhQ1EURVEURVGUrqAPG4qiKIqiKIqidIUL0mws4Cz+L9aTuY793GIZ75DOwHXJ4Oxcpn6hXSNLvjLiU/0ol24aqsM0XMgpIlGEdZWFXqxBterbA6wR9GIELL5PNe/n0HlwbWwYsuYjpiiV4P471zYvFDYq7DbOuoI4iyec08249rG4XM/KdZQUO3mqX86wjiGmv/p6MWYjqFNzGJew1j1iIzwRETbnqlMttqEc51LtuMJfq4aetsECiBQOLCfNNdQxsI6rw/vB45c+b2Jqt+lEm5WmV9G5x8ALTSaflsSiqd/gMM4LbFYmItKs4ck5cvIUxDM1rNNN0TxRbWCOFvupHl5EUhnM2+nTpyEOSKs1X0fDvXTGNqBqldDsySE91+lyCWKP5pacb19aXNI+CPVX/zDq7U7N4TY6dLo7TdRniIgEEW4jmcC5nGUeEc0bHdbKiUid5okz5oQxl7yu43qpJY2EpdsLYsxkazhHr+nB+SpfWAPx5AzWkVdrqEFwYszy/ARuN6A+DOvYZtrHfEzEmBEmM1hb7ifOfm/QZnPVmFubFiVQaZ4MHJO4TR4XDs1vnZh5NkF5H5HWhM17m7TfQevcLqUb1i1rrpqtjog8es7vvFCU52eX7rESHoqqBopZ6/ObtqGe7PCxPRDPt3D+y3VQT0Gek1Kq2/0Tufja9CzGlQpec6/+f14JcS1hGwW2KjhHtgLMHXcNjqPpOs65E+O2+WqTTG7Dk/h+QPNjnvJv/SiO1bBu3w+3SLuU7sP7kZt+4hqId74c25yu4fVJROShf/kGxv/74eV9Ds5fOKm/bCiKoiiKoiiK0hX0YUNRFEVRFEVRlK6gDxuKoiiKoiiKonSFC9JsRJGRaLFOkWsmORZ5nrruFQRxi8avwKU6YI7PZz94H6IA6+Kmp+3ausGBIYibTdKnUP1ygv0sQvu4znWszPloMs4J90WM5uVC92Nl/4YXeEw/MGl3abF01p84MQurO2nST3RQ62CaXJdO3+/HukxTsms7DdUsOkNYc2oSuA9mBmtBnYZdg+qwtoRrsy3BirVX9n4656it5K9YNfes8YgZ3VTT7BjON9IdWd4fMeObjtVZYc7gROeaYV54Nm0alVRyIY9q81hvPTs1a31+sB/XmWdtTLtJNdvUz34CzwPr4EREKqSf6CngWvRcCzw3izqibI7WtheRNHlaTM/gWuvsv+DRfg0OFq02G6wfWD8M8WwLa6sTGWyTHZGqc7a+wnNxv1MJ1LM0yOPBOKQfYM2ViCRo3kgvrtvfcVbfZ0M6LZHFsZztQQ8HScV49rh4bhMpnJ+qTawLLzdY30PeTMb2ZHHotYOHxvH9Ds5xOzevgziZsHM6TdfQNM3lyTSeE5ZvVVnnJiJTs5h/bfJJ8ZLkeUHeMtkM9m8mYd8+RdRmjfxo2mRG5Pp4XGsHsIZeRCQg7WHKX+E19H1c038Q2uEpiRavR3ybUyrZGqrTsxMQBwns44lJ1Dq06qSNEOzz2ZLtiRF52GaT+mtsbBfEAwMbIN7z2GNWmw4d3PwkzhuZAl57Nm7Eeb5OOhERkfLMJMSdCK/refZ5IY+4POnP0p49V5VI69u/HvNpbCd6LD337DMQP/TQPqvNx7/yXYiD6eVzFITnf5+qv2woiqIoiqIoitIV9GFDURRFURRFUZSuoA8biqIoiqIoiqJ0hQvSbBhjlmr2WRsRxaw5HafjuBC4zfPRMfB3eBdOnDwK8d59T1ttXHvN9RBPTpYgXjM0CvHg4AA2EHPckVVffva+sTwyzuPYrc9Q/P2oQH7Qc/iC4jjLegWu5Y9Z9J59XSRFXifcx5TCThprKFu+ra+otXC7hSRu0xvA+nnpwTbdOawFFRExc1TvWcVaWCek2liHjivubwjso0GeFsalNcCbGDslrF/2huw6f8O+GhHX1FuGIBTH7DfLU7zl/TYvhK7pAqnMz0lrsVZ7/DjWG/uuXTO/dngE4u2bsWbWJ++WU5NY19vbX6QW7T5K+PhaRIvT1yqYYyFpDaqhPXfn1pDug+qgeWhlSSfSiPELMOSnUAlRrzI5PwWxTzXNSQ/1BQk/pmZ5Dtt0yUeJmpBkGreRTrAyRERojf1WY6F/g2D1NRtO0BHnjDcIeTQkknZujAxhLfnpMp7HRod8NWjct9uYS3FeMm3Kn6k5PPetOs5X6Tx5d8RcYgLarxblUy6H8+jwCOosq3V7Xp2voV6unzxrOqSfSpO3UJu0dIU0ze0i4pCPRpjA/u7rwXuFZArPWbHHbrNDWrh2e2W8utfnrZcMSnLR6+jYQfRkmK/YmsZTUzifhTTfTZIGYzbE6wzb3kSRrcVhfVmbZEVX7Loa4lYN+7w5b+931MZrcCPA/BvKY/5l+lE/VavY+8n3KOMnUM8S0njusO8U6UMH07Y/0lVXoj5l+FLSaDyBeqrvfONxiI/tZ78aEb+Fc2LKWY49yzvr+dFfNhRFURRFURRF6Qr6sKEoiqIoiqIoSlfQhw1FURRFURRFUbrCBfpsRMuaiHP4WXw/vBDeErwOPdfJHTlyCOKD+5+1G6G1q7OZfojXD6+HuEN1ra4X4/lgvXT2Yz2Xf0ic5wifBMM+BufQgZyPPuMF8f/4fnG9hf9ERPj4XbuWWDx6zeozPJbAOn58v5PJCvO1dejFcfUcruW+JcSi03YCtxH223WX0kO16CfxOOqzWAfrCtaXpsXuC4d0HYZcCxzB/Qio8NWjEmgva/eFUL23GKpbZV8C6u64zDIO52z8v1eL0nxDEot16wPDqN2qlOw68UOHD0K8ad1aiHdsxDXfN6xF74mpMtaZT03a68yfLqFvRiaJ59Khnu3vx/mskCe/BhHxyWdlw1rcz0od8zykNeErNbsvXNJslE6g5sUlzUFA+WRymNd+jCeGS54PYZuFWBgmyCshisnCegXrmKNgYT8vhmbD+Ckx/sLYNbTOfrVZtT4/30DNwGyTdAjUXwHprkLS/4Rx9joBvtjbh2v7R0X8/ARpOjzPvpaxPqLdomss6ZBOV/A4O4HtwcIasckZ1Bwk6W5o7QjqK9jTot2x69sT5CU0OlKEeOOWzfh5SrdTE1jHLyKSSKImIbHiuubGaBW7ybPPHRJ/USPmRdhhSd/W8W3cvAXiUdKsHT/8JYjLM5jDlTnU+yRYdCUiafLmGFu3FeL+XjyP3/7uQxB75KclIvLyK26G+PQ8zrtVuq6n8+jnMzCKGiIRkbbBvC/mcdycPoHHGoV4je7Jop7npl2ozxARyRbxWJ4+jvl0+im8nrSncQ4p+LaPjvEp75vL9xsBa0HPgv6yoSiKoiiKoihKV9CHDUVRFEVRFEVRuoI+bCiKoiiKoiiK0hUuSLPhOM5yzf7ZLR1ExLabOFe9/7k0A9+fpoD8QEhfsaZo1+uZAGsxs1msnTtxCtcqXrsB65kLBazfW2j07PoJG9ae8Nvn8ZxIm4hC9i3hj9v7xBoYd8XzqROnG+kixjhiFteetnLLjcktqgVm3w3HxfT3qSa3U8c82N2w6xkfNVSr3kD9RJZqoHNp8uWIq/um9bRNHmt2M22sQS3X0Z9gJiKfDhHJkEajh/Jn3sFxccrF2tmxFna4N237KEiLvBisNbg5v+j8xCm/6JzIyv6KVr9m/uj47FKNeSpRgvf6iz3W53vp3Hlk5pKiHOy42AfzZdRjcA29iMjYJpx/1o2gLiRLWqPJ6VmIkzHahxMnT0DskiZq7Qhuc2oOa5pLVTsH2206XxTmQqzHLmSwRnlyDtfDTybs+u0enntpXX+eJVyDx+47dl/kMjh2Wq2FeSBWN9dlAicjncV17k0Ka+R92+ZFjh0rQRx52D8u2YoYg2M4CjHfWJ+x8Bq3gb0c0nXHUC55KbvPE3zeyL+o0cC5uUo+HKxBExEJaT8bpCtizUazifXtxV4835s3o4eOiEhfHhsp9lB/u7gTAwOob/E9+5bs4CEci3Ol5dr+ZsueD7rJU4+fWLrH6u/FYxvbsNb6POslNm7ZBPE/f+GrEDczmCvNGdRGtCL7Oj+4BueigbXrIH7kO49A7GfwOp7ZeqXV5q4fezXEr9mCnix/93/+N8Qz03shXjuM51VEpNPBc9Wgc+00SAfXxHzLJnCceEl7wB+bQB3SoUP78QPkI5QgDenoFlt3Q9IwabSX96vTCUX2WF+JRX/ZUBRFURRFURSlK+jDhqIoiqIoiqIoXUEfNhRFURRFURRF6Qr6sKEoiqIoiqIoSle4IIH4grzOWfHvFe/ECJYtAfI5RNEs7j4fA7klk8Hn+Y5Hxm7r16F46OT+J602Wy0Un504hSZqm3e8AuItl+yEOFa2SvtlWaFQ30QRCeRIAM0GQwubsFTk+B16lzXVJqa/LdHuClFutMoCXSeZEWfRbMyQYVxcZrFQUShu17CNg00UGT5LrX7Rt7cyMY9D6NlZNNF5soECt1ekUfS6040RR7Likhc5yOA2pzxc5OB4ZJv68Su9ZMh0uoOiuQ4JkX8qwve3t23TLHsG4P6Kzvpu7Fkk0yDTDla8tfoC8SCKltIok0Qx3VzVNlWrzPP4wTORINPCQg+KuW+68VqIh4Zs4eGuS66E+LuPfRfiQwdQJFiaRtF5Loc5KSIyNY6LDgwMoNCzVkIBeHkaxdv5lN3m9Nw0xJkUChwdWkxhw0acq10SSE5N2waHLk2srRDnct9gliaaOCekMrbBYZjCc+QvOrF1Ohch/9pt8RbHCfvWbd5m58aJI7gYgEsLECTJaJGNKQMSYmdTtig1RcrqNo8DukaPUi45vj1zNDo4TqpVNDxr0nnjBQySvi0QD87xp9WIxPFVMoRszGDOHz+F40hEZNtNV0Lsk5Fpi9qcLeM15+ChY1abBw8chbjZWJ6b26udgyYtZ+4rqhVMwNOnS9bHn3r8OYi3bEbDvd7eIsQtmgOuuPplEK9fg4bKIiLNKp63cukkxNkkCtf71+yAeP+kfd3ZWMZ82hyiEWqq7+UQJ2s4t0WdktVmFGEC9qxBU9jqzHGIs6TMLtVwXH3h375sb4Pmt2QOx6tL19NTJZzn+0LbrDffj3NiqrC8EIrb5nuV50d/2VAURVEURVEUpSvow4aiKIqiKIqiKF1BHzYURVEURVEURekKF6TZ8Dx3ydAqInOVOD3G96PBOBtx32djJd4P1j6MjmIdsJ+yTUyeeOoJ/M6GzRC/bOd2iD0Hu9HElFFaWhLrE2SaRh/wqCbVScToK+jYHaoXDUKssbRM/mKePR3LBgvfXVUSCRF/0ZTG8ouzVDC281+DjOhKqEP4er0E8WeLWO8YxtShR1SfPDmPRlD7Wlhr/DiZ563L2jWS6RSZYpHxX4uN3bKYf0HSNpV0yNCQ5RHtFraRb2Au1Mng8I0B1uiLiOxy8Fgiqg936Hx45/O3DtbdNFcce9xA6zIDg0Xx/YW+ZGOx0rzdJ80qjrmpScyPDaODEL/29f8B4uuuvwLiySnUj4mIPPv0Poi/+12cv2ZnsC63P4can1bN1poM9eFnij1YtztFbbbr2MZADo9LRCRPJlQDRRxPjRL2X7uC+oE+yuujM0esbRjBGuKeYZzfWRPjhjguyiVbB9Jo4zyRzi20EV6E/Mu6LUkvClMSJNooTdjn0SeD2kiwDrzTwP5q1TA/gyYeYzbmelks4GudFp43nr8KJPvwyGhMRKReQ32ES/XuaR+3yfKtDukuRURSGdRxJNO4I6UKHrvr45xYq+Fc9Njjh6xtFLI4braN4f3G1BTqPE6dehbjCTTwExERutcq5pbHouvEqRW7x5qB/NI9Vz6D49Fh10QRmTx+GuJ6Ba+Ha9bgPDFdQo3RwABuY+cW2zjw6AHUOowNYp+zluRf/vlLELtFNOwTERl40w0QHyvh2HruOM4TZgr3O9O25+mEwWNp0P2Y24PjYOIAGvSlKX+dXvs6X5rA/RjtwRzv6cFxU5rH+a9dijEKnMQ2Z5vLxx5G559/+suGoiiKoiiKoihdQR82FEVRFEVRFEXpCvqwoSiKoiiKoihKV7hAn41lWCsRxvg+sIaAPS/OpeE4ly9HXJudDtWzU01jO8C6wkbMOtWpNNa1ZdJYK5ei8vcEHUcY4xfg037aWhPUHNRqWPc6OYd1cxWqZxYRaZFPhOvjsa1bNwxxXx+uyx6FcZoY0qOsKI7lY+g+K3xefK4tjNFstDAXojLWi6bmsS44HWD/Vaie26M6YhGRxizW4IYtrO9O+thGkMD4dMwa8x71a5MKkuukFci5WOuZi9FsJM6Rf04Cz3MliW1+ncZRfd6uD/9/aT9HBfufdUoF0jrF6W6sjKwtn0MnTqfTZVqtloSLeVEuU307zz0iks+hRiDl4THP0zjev+8Avl/G2uBjJ7A+WUTk2WfQR8Oj9dnHxjbh+xHOgZOTqL8QEcnmsA3Hxe+0qS4/4UX0vj1Wtm4Zg7jYh5qNtEc6oVlsIySjhJ2bsD0RkSOTRyDO5XogrtdwfOaSeJxxU5pDOqtOeyHuBKuv2Rhd2yeZ9MI+15o4n1XqtveNn8VrV71DPhsGR2WB5oEW+WfNzdq6pOlT49jG4BDEAc1Phw9jLfqGdbY/SC6B+xnQfrfpREV0/9Fq2fqBDnkQeD5rFrEvfNJJsodBo2N7JP3jv34H4qF+9JkoZPE7vXmM00n7lsyn/uvrWdaFNC/A5+CFYMfIwNK9TNDG/uDxLCJSSGD+tRs4/taMoH/FvoN4nsM2jr1vf/cxaxv9ObyvKc/h3NSp4vWy0MHr/KHDeI5ERL7x6PcgTlKK7jt2EGJ/HHVzLycvGRGRAmmb6mnykOonv5oN2Hcb16HHSNW+BZQZGp/ZAuWog9v0ySvK8Wz9lEf+Yje88pLlfWwHcvCIfU7i0F82FEVRFEVRFEXpCvqwoSiKoiiKoihKV9CHDUVRFEVRFEVRusL3rdlgvYXv203xZ6KIatRIk2EpHeiFOF3I7CyuZ5zPY91goYA1u7NzJYgnJu111dNZrHmv0zr03370YYh/8qew7rBOdYkiIidPnoR4agrrpCeo7vXYcawJnKK66jjNRsjrXDus2cD1p2+5+SchvuH6H7PaTHENqbt8Tn9Q35QLJWp3JAoXk4J0NEK1oXGvOezZQPWJW6cxP0fKWDM+nrXzj2tKHZe8ZUhLEoZUe8zeHyKSomPjXg5p3DTauA0vYWsZQtJPcD0y+7iwfCdIYe3nozF9ka7jsfxYhDXkY9RmwVBuObbmgf8e4nSWx9ZF0Wy02xKGC/vEerFEjF+ATzXvSernJPmffPWrD0I8tmkjxO3QzpexzfiZsU1bIR4axLXsW9USxHE6hSr5x7B8bvPmDRBPk3Ypivk71hzpfI4eRc3Ltk1Yk/yyXaMQN2m/L8nhPoiIJHZjfx6ZQH1Ag8dbGpMymbQdkDIZvKZESxem1ddsrF8/ILnF9fanZkvwXrVu5wZfixplWts/gf4pa9ZjLlXmcRuZlD3mpmnebBmcKxI57L9p0uLIuK0Z2rgea96bgWU8BWGNrtEpx9ZTdCKeSckrjA6tNo+amGYDY76fERHJp/De4djJaYh7sngcg5ehnmpwje354JJWZOvG5XNUb9o6nW7S7rQkihaOIZPB3DExnh/VFuZkmfx4eop4np0INQSNGt7TlMvYnyIic5OoUxjIoRfHzk2XQbxuLY7bsZjLyKm9qJGd/N6TEBfpetgq4XlIrLPzr0mXhxZdZPM5PPfzKdLtTuFcNtSP2igRkV07cK4vpFEzeGqKdIaksywM2dfgH/t3Pw5xbsPyOWrW2/LZz6hmQ1EURVEURVGUi4g+bCiKoiiKoiiK0hX0YUNRFEVRFEVRlK5wQZoNx1mu0+d6xdj6fdZs0NsRaQwSHulAKN5/CNeTFxE5OY51bNdd/0qI2x2sWX2Sau9YwyEisnUr1gpnqYb+6aeegHh8YgLi6VlbB3LkyBGIazWs/wwCqv0nvYVHNarpNPtM2J8xVI93lPrvC3NY6zi6BjUdIiKXXXY1xI328n6bcHVr5o3vi/EXCh/DKtaCeoG9rr+kMb0jQ308iPWhr0jh8X/wNNZtficmxR9MYg4/EWCdZYt8XRzyT0nEaJ3a5NdgaKylMliH2TF4nmutGB2IwYJRn7QCyQR7XmDIZzpM2jWpXw+xbvV4E7/1empkhGp808b+20dEPi+OWTmeTYzQq7u0Wy0JF8eZ5VUSMwc2W+SJsmKNfBGR66+5DuLyFM4dLrXZk8Lvi4hs3Ih5Oz2Dc+KJ4+jNEbVx7hnsR82ZiEi9jp9JUo1yQOv7J8gLIJnGem4RkelJrNc+sP8oxNu3YP36hs1Ye+27tNh90t7GI0/hevflEh5HXz9q+IYGihDPkQ5CRKTTxvGVyi7MG8asrseBiMhAT1Lyi14NmSTmQrlijx8/wnmxWUdtTS3E62O+iLqZTWuKEE8dRW2hiEiljvOoNf+wlwl5D7Vj/EoaDXzt1Gms1ffJC6unB3UhtRhPJEPnkb2tWLTR6fD5JW2ca08+EU1IfgKv09U6zgfzVez/a6/ZabWZpv7aODq29O9ajE6nm/QM9C5ds2o1PBbf2LrJU6dRU3tsEuemVA7nd76taTTxepnM2tedygzqELYOoEbjhpteA/Gj3/4WxK0ZW2NbKZF2gXMlj9fg+jy+X29i34iINDi/XNxuhu53+/tQf3HqJPadn7D1ZT/107dA/OyThzCm8ev14zh6zZt+2mqzZxC1JEemlttoNc5ft6u/bCiKoiiKoiiK0hX0YUNRFEVRFEVRlK6gDxuKoiiKoiiKonSFC9JsRJGJXVv6+WA/gJDqj9Mp3HxYx9q75/Y8DfHRY1jjKyJy1bWvgjiVxKK/CtX8pXJYV3jTq15ttTm8BuvxJskDY4Zq+Z99BjUc5WqcBwb2hUe16Oks1h971Feuh99PxNTrJckTw6O6/CjCGtRUBt+v1rD/Rez62k59uY0O+3p0GTeVEveMZsPH2k0zNW9/4UQJwohyodXBut4kebRc14f13Zd7tk7mZ1xcV/3/NPA8/Y8I6yzn2ljLmWjbz/tJH7UPGfIL6R3B9bWrTVoPvoT5KSLikwdEq431oh3SDHHuBAGO+4Rn73dA9bTPUr4lWrifLxesN94qdv+KT4uTr9TdGBGJs+boIq1We0kblcvhPJHLZq3Pl1vUz6THKc3hmMvQuuh10nbNlm09GPuT9PTgXJLLYb+GVBvc02Ov7T85RevMH8K5l3UefX2Yk5ls0WrzyitQC7dp53aIX/1jV0A8tg41GqdOY199/RvftbZx+NAJiHsKeGzFXhzj2RzmbLlsz6s1qrMvzS/MNcEqa9ZERArZtBQWz2eKrgHpmKt5IYXjtEU6hL0TpA+j605vEXNpMI26GhGRCvmnzJO3SZKGhdvBuTqI6cZmG7ebTGEOz1Vwm3Q5lXTa9rzJFXBH5mZxPyKaA5N07ROHtSa2x0WV/D4MHZzvYb4do2vUqVP2NfiyHZtxu834f68GfQN9S/q+Gl1Pj548YX2+QrrRKbo2jeTw+rlhK47PU8dRqxMY+7y++oqbIF7fh5qNv/vHL0L86JPfgTiR3WK12T9yLcQDpGdtNtAbpkM+MI1yyWqzRufe68OxFlJ+OUIDJypiezVba/eNR1GTVZrFcTSwHu+X1+9Cr6JagPc8IiJ7vkma5BXau077/H1e9JcNRVEURVEURVG6gj5sKIqiKIqiKIrSFfRhQ1EURVEURVGUrnBBmg3f98RfXGPZkB7jfHw2OJ6Zxbq3p77zCMTVMtb3XXrlK6xNjG7cBnEQYd1bJlGE+Kde90aIU45dMNpuY93kv/7TP0LsUIFoXx9uI5Gyu7XZxNo2E+FzXiqJ6x2bgH02sL+TMdvI5bAN1omwf8PYVuy7jWNYGyoiEtHa0K0VNeitlr0+dTdZ8HlZ+LefpvW2N4zYX1iPrzkV1Gg4E6fx85RvrTL6E/i+neNrC7jW/e39WGfeU0a9xSfbqP+ZC+0+bJM3Ry6Lda1JqnOVBhbuNht2mwla656lV5UW5meH1sovkB4hncFcExHxKFdcB7+zh3wJHqF6z02O3abDPiTh8rgxq+yxISKSSmWWNBtcjx3G9LtD47xO6+pXKqjJ8Hsorz2sUfY8ey37ZgP3Y9NGrNPdshnHQV8W9RWFnmGrzV2XXArx+IkjELMvC/sFpAu4RryISK6niNst4vlmb6FvPY6+QF/+2jcgfu459NQQEclksLaf5CnW2BinGvtWTA0y65mCxXn0Ymg22qEjrXDhoPI9WLOdLxStz9dq5KVE/kTjMzjn9aUxX+fn8Bqdihlz28gPpd3C6+e27ejdcSKDuTM1VbLa9Cm/fPbq8PA4SmWc27Mxmo1iEe8Nir1Yn95qYpv1Gnsl4PkOOrY/SLOFc5ylmyQfjtkybvP4cexvEZHR/iLEpWg5H+vN1b0Gm0RdzKI2dPvlOK+Ex05bn9+yBueByMXcmC3RNTmLfbzxigFqka59InLzzT8J8ZPfegbiSfM4xIOb8RzUK7Z3US63A+KRYdSTTRzCe9XeDOZbPrL9QIzgvDxLHkBlmnrCkDQcPmpLJuftvjAOjt++fpzr+1L4nYAkQk+ctH10oha2GTWXx03QOf/80182FEVRFEVRFEXpCvqwoSiKoiiKoihKV9CHDUVRFEVRFEVRuoI+bCiKoiiKoiiK0hUuSCAOkPDO82wzJBaRCwlIyxU0hekZQHHtlVdfB3GOjKNERCptFGRlyNkoaqOIK0EGaa5jK96yZIB21dVoGjM/z6IuFDI6MUJXnw2BaL97yHjLow72fXwuzGZtoSgL0+fIbCmbRkHcFVdi/w6vRYMXEZFqA0VMuZXi5NVW6IahyKIAis2nXFaCioiwuHgAhWCJfhKGNVChFU6jgZo5jWZVIiLNaRTFuT0omPqF9Si6n53G8/inVdsIKeywwR5+p1ZGVVeZDISaMWZTmQ6OvZ4CmidVqyjU67TJMCyFgrdEzN8pDOWsl8K4QYZ1X+/gft5itSiyzsX9WKkxvxgCcT/jirc4FtsVnAeCVozBkcF+cqjfKmTa59I8MTyMc57j2aLkFo3Rw4cOQ1zswXHQm8W8P3Ror9VmlYTrO3agODFBAt4DB1FYmC3aRoGSxGM7cgRzf4IWbPjOE49BPDOPYuZU1r58ebSIA8dtOkf1Oh5nMkZYnCRxcnZxwYYgCEXkpPX5bnLw+JRkMwv7MzSAAvFcOuaakMBrUYfNOQPM4VQLBeVtcs08dso2DO0toIh3/dgYfsDFnM/34X43A3su6dAc1qIFK9JpFLryVBDEuN3NTZdwP3pwDiwWMY5o8Y7SPArGOy17LLou5k9Ii2IYut9I073GmmEWRItksjhuDu49tPTvZnt1XU3bXlvM4hy0fjMKnl99xWXW53sH8VzPUP7UZvA8JR3sjw2jaCKZyOI9oojIaTqvbg77ODeE+XVyFre5duwSq82du26A2Di88ATeu/KCNXtn7fuRiO5ZQnK75IU6in0orm80aYECawsivIhBO8Acdg1dk5uY04Gx8ylo43cSKxZIclz7vv/50F82FEVRFEVRFEXpCvqwoSiKoiiKoihKV9CHDUVRFEVRFEVRusIFaTZazZb4/kJNXYfqytPptP15+kxgUD8xMopmQKNr1511+42WbaLjkClfI8TaczeiOjnBGrNmTOG3a7BucGAQtQybt26HuDyH9crNGB2IIQMgn+rwEy7uZ28e6yGTSTxVyZRdK8f1yfU21usls1hHvXY9HkcUkw7GxdrZlVtwVvtRNYxEFs+3S7WwEtq5IaQjctgQzcM6S4cMwdz1mI9m2DY/S1CdeXAKcyGTxFx4bQZ1M/9cs81/DlFdPpVZSqqKWpztTTz2CbFzo00GZAnqG5a8ZLPYF4kkjok4OzOHdVv0oZDqO3dTAh2IqRddT7oPs3JsmkgkRibRTUyiLWZRsxHSefJjxk+zTjWz9PedqRnUBRV7ixAnaNzncna+lGYnIWZtVhjguXRSOA7m523d0PDwKMSbt2+FeLqEuiE3Mwfx2k22/uvxp9Bc6x+/9K8Qz85gG8021kXnenC/WSMkItJs4PzvWacE+79NNe9BZM8j+QLOxb2LepROJ75qupvs2XNY0ovaPEcOwnusoxERWbcO56zp2RLELuVwhzQbQvmXztjXeVZM9JAWokzz1bGJaYibTXs2SZFGMYpwG14C33fJaDfWbpGuGS06f9x9w6SfCEijYSL7/Ie0ZdZUpJOYw+sGsa82jNqajWoFx9rk3PI1pxVjLNhNjhyvi+8vzOND29DUb3LfMevzrxxBzVmjiflVncf50WngmE52cOzNjKPGSkSk5B2BuG8QtRBTNFdNzOI214zY4ybTi3lep+tMo45z09wR1HOWEzH3Z1nM2X7STTYi3EggZPhKGtSInXlFJEn34UYwP+areL2ZGMe5P5m3ry+uh/1ZXWE6HMToQ58P/WVDURRFURRFUZSuoA8biqIoiqIoiqJ0BX3YUBRFURRFURSlK1yQZsNLJMRP2OuQi4gEgV2/6FAtZ5pqhdkrIaA1wF0quE2YmErMCOtBx4/ug3h+Buv1tm7DtaATvXaNpCdUu2+wjm37DlyX+dihpyGeatl1hbkMHnuDPB3atC54J8DP8/rb/QNFaxsR1ZC2qH+rVBvbqNMay0GcJobilXXS/Ga38fzlImx+THbsGkneOxOxJgDz07AIxcNcd4pYCy8i4vaiZ4FfLEIcUO1xH+mOhmKEL5NJzL+BEI9kjY/H+n/34VrkB8pYEy0i8pcdHAeVKp579h9I0Dg3VDNteZiIiCHNRpvqibfSONqVwnre3pj648il7eZWjIsoFMES/a6TTKaWPG+iJJ67oG7vP8+LLulW2MemFWCOTpxCTVDaLqmVdetRX5Ggtf4bDezDb33ruxC/8ad+ymozl8VcP3FqCuKTpDWZqeM8/MT/93dWm8/twXny5GlsM2jjfiapf8HjR0TSaTsH58m7SQz7G+E5SpP3S62N40JEJKSZpDS/sI24+bLbhO32ki6Ar5/zlar1+TK9ls3jdSWZQx+O+RYOqITg53MZOwHbdO7rlMM9eZwjR0bQK2H/IcxxEZF2FdtoNqk2nLQQ+R6s7e/pxVhEpEVz3Hwd9QNzJcyd0QHUOPbksca+FZC+RUQaNN578pizSbpOvWIX+jDlEvb1YPdhHCfHV4wb9k3pNr3Z7JI2aP3oRnivNFWyPj99EH01qqdQL1GewvE2N4OfzxcxV0oV+96q3sGcPTGJ81+HtIAvvxT1ZLmUrbFt1XC/XB9zYfPItRC/sXgU4i8+9/9ZbT5ewmMXHzXLSZc84ZqYK/kk5l/cuZ8n36aA7kWDJvbVfJm8xCp2/uV78DpdX6HTCIPz93nRXzYURVEURVEURekK+rChKIqiKIqiKEpX0IcNRVEURVEURVG6wgVpNhr1mriLdaIp0l84MfX7Cap5N1wjTyVnrkvPPvQBx7dr1JpNqj0PMM4VsXYzTTWUPnsDiFjrcUfk4dDXj3WEl11+FcTfmJ6wmkx5fGxUb9vA2rftL78c4muvvQZiq69EpE2+GtkjByD+7re+BfGXv/AXEL/2p/9vq80tO1HjUl1RE91utfjj3cX3l7UCVr7Z59HEr7a+DNXPG580GhRHboxGhdpwRrG+0e9gzk+dRB+OmZiax1f0oT7np1zM4RPkJbBmFGuir8liLCJydPYIxF81tKZ3m9ac93hNbzyO0C5zlRTpkK4Lsb77Z4dQW/CyNNXg1+x6XFPDumjHW9FfMZ4I3aZRbou3OJYd0hiEzab1eUM+Pi7pbUI6hvI8amsGNo1B3KL13UVE6nXst9EhnJ+mprEOutLAbZwaR58OEZHhNbifn/vfX4D46AyuK8/17o2a3ReZHOaUn2H9Ctb+OxGOv9Isvr9m2M7zDRsxx2ZnMH9a09hGSP4zqRRqGERsP4324li5GJqNYiElmdRCv7CvTbNtX87TOdSkWN5XIev4MJfa9Pli36C1jaaLbSTJS2JyDv1TTpzCXKnF5YqLurVCFudAQ9v0SduVyZKnkoikSfNTb/N2Md+mpnA/U2l8Px2zjUaJtKuUI1u2ou/Jy3aifmD89EmrzQMnUYNXX6G9XG3NRlCeF1mcwyYP4LXMadl6p28/+k2ImxU8T1EDrxHVCrZR34jnaMcO279n3wn0m3ESmPOvuALvnaZn8bx27N2WUo3EgBmca0bXvRziyyp43v5l99esNnvIu2PnRvQ5M6QJ6pBuZL6E4ygKbY+L8dNH6TOYf0mftZj4vuPH+IPQrWZqhSFNGOMp93zoLxuKoiiKoiiKonQFfdhQFEVRFEVRFKUr6MOGoiiKoiiKoihd4YI0G2EYSrhYA9ak+mQ/Zt191hW021hjxt/hOKB6UYeLx0QkmylCfPkVN0AchS7FWJPmxvgc8H63WliH6Ti4n7tediXE33sMtREiItkE1iYaB+sG01TP95Ov+1mIMxl8v9Oxa/0tHQ3V3e99Gte5bzfwHM5N2+udmx2o2Tg2sfyZen2VTQ6iaOE/ETGslYirHWTvDc5Rqi1mjQa3aEK7Rtvl80D13UL5l6Ya/lcmbO+OV/Wsw8/0Yp308RNYK1snf4ooZ68xv7ZOWiUaiyHlfEDH2miiPmetXWYtP5VFrclrR/A41hex7tXzUQNjArsG38xRDX1pRf3yRdBsVGbr4i5qdxI0d3jnUb7KGg7WHp2exjX1cxk8lwO9dr7k85jXfYP9EBd6MN6zH72Ivvf0bqvNm38Ma8t5t8sl1ELU6pgQ82Xbg6BcPXttfy6P57qXapgjqn8fn7C1Jn4Kx3yhB/urWsM89qjsPoiZRzpt3O9osTMi7pRVwHMC8Zwz+4Fzje/a4yHsoAYj4eMBt0h31yHdn0c13KVSydrG6SnUwaQyeN7mq5gblTJuw2EPHxFJpzCnk+TvkUzjfm3bsQXi/YcOW22Ki8fOV36XXqmTD5X4uJ9eIkanSuM5Q3PcJdvQW6Hdxr6bmClZbR4aR83V+qHl8dyJ8SbqJp0oJyZa6PsnH0etRLpoa+4GR3DuGdi6HuIDTxyHuFXDsTY5gXqVXZfvtLZx7bV4z1ep4LXt0D7cz0YD82++hNdTEZFOeAziMIHfKdH92/ohPK/NvldbbTpN1HWcmi3hB+bwfqpRQ21do4JzahDjCRR0WEdLYyuF48ije+qUZ/vodUjbFETL5ygM1WdDURRFURRFUZSLjD5sKIqiKIqiKIrSFfRhQ1EURVEURVGUrnBBmo2enh7J5xdqiIMA60XDmHp2rgdlLQS3we87FBsTo68QrPNt1rBej8tqU1QLGmNXIVGEdYMJ0luwxUMroDo4H2tWRUQG1uDa99MlXA/5yiuvhThfwDr9Dvkx+EnUcIiI1KmuvljEuusU+S9kc3ggiYzdZqWBdZgds1wrG5gYj5Ju4iVFFmsKOTfY72LhNcofqld0fIyF1pw3AeaSy3oMEVvYwdtMYr5tXIc1q28v2PqKXlobP1UoQpwMcT/+roSeB89N2dqbEh3LQA7HzTzVf7epFvMVCczpX+zfbG3jijWYb3mPNBkJqgdlzUWMV49TxJpfWdlm2BHB0truY2TJIyeRwT40kb3mfYq8gULSHbTb5HtAc+KJCazzTcT4AmXz2EfVFm7jlVddAfGxkycg3n0Qa5pFRC6/Gr2DXvuaV0Hsk+fA957dA3EuiRohEZFcAXPo2DGs1/ZpDGdpHHB9cJ18OUREjhzG3M/34n709uE+JNI4Pk9PoWZGRCSismR3Udt1Mf5Sl0wmJZlc2H6LciWVti/nbbousyYjmcA+37gedVYdmhNPTeJa/yIitQp20Owc1pZ7lAs9OcxXN2vfO2QT2Ls+zaPpHGkYW1jv7jn2WAxDPPZCinyVKKcTDvt8kWdBwh6LySLOCZs24Jw4P1+C+DHyiDg5aWudjMFjHx0dWfp3qx2IyHPWd7rF2OVXSjK5cN2szuP4HV1nj4gNY3QP4hYhnjpO2q8Iz1Hb5TFve3uNz+KYrczhPUv5NG5j/BjOqRXbukhSm1CD4XoY7z75OMRrbsb7t2uufIPVZunRv4F4soTn3lTx2FiT1SZDkLBj57hPemLPJ80yTWaJBOqY0gn7HrBF/letFecoDGPuiZ4H/WVDURRFURRFUZSuoA8biqIoiqIoiqJ0BX3YUBRFURRFURSlK+jDhqIoiqIoiqIoXeGCBOKO44izKOJ0SMzpxQgX+TUWgLMxHZv+2Ttgv5Qg4arvoUCLdcMOGR85bPwm52E2SMK8NsWOb7fZomPt7UeR3FXXXANxnYR8bAaWYLGtiBgXOyhHZl69RRSpJ6kJL6ZNP4nHMjoytPTvWi3DH+8ujieyKICyTP3ilP4JTm/8jmnSYgIkohY6r9ZqAxJj0kb7Zcj4LdWDotehRIwpE4+DDirY8iTk9+vYZmHeVrxt9fFcPdJBo540CcV+dngTxP9xBE2zNhdsc7mI+7OOpkRuEk3/DJlOOoFtEGTqdCypFccerPICBSJSKPQsGSHxvBBntBkK5lCLFnHoIdO5dJqFr/j5PfuetbYxOV2E+JahWyCensHzkMninNmIWfjg2AkUUe66BM20Lr/s5RBv3LwN4kce/bbV5sQkCjmrFRQeejR2fDLZ7FDONht2f/M5mZlBQXOhD8XK8/MoMq9WbQGqR2Zw7WBBqBmGtkCz2zh+WpzFebpB48sJ7fkpk8W5oYfmjkwG33dc7D9edGRBkIxUycttbp4WWEmSoS2JgKOOLfRPkkHt6CgumOJSbkxOoflbX6+98AabuW0aGoW4XsP9aJBpWjKHuRNZBmoiKRf7Z4Cu83v3o9ngzGmc36an7b4oDhQhzq84pwn//E3VXggmZ2eW7j3SEY7Xzox9Da7ksA9bpD9m079mAq8hKVqE4+DBI9Y2MgVs9OnHnoS4mMLcWZPD+6DJY4esNoOBZyDuL9BiATP7Id77zRmIG/2XWG0mHZrvqiWIqxU692Qa2Y6wb5Ip+4Y4omtoGJA5ZqqP3sf7DxNjEunTPXIzXJ6HjQrEFUVRFEVRFEW52OjDhqIoiqIoiqIoXUEfNhRFURRFURRF6QoXpNkwxizVqIdkYGXVrouIdw4TP9Z9WLWdhg2wqDhURMplrFErsMEV1cXVm2jwMtCHpjMidq0w0yI9Rb2JtXYj67AmUERkoBcN9RJZNCFKZvBURNKmGPs36tj6Fp80F1FENX0uvt9TxLpW1pWIiPhkCpNeUb4XrnbJfBQtG8GRPsU4ManMKWlpIeh4yWTONLFG3MSYzkkaa4sdB3PctDjnybgyRojkUK1wWMV60D7SKd2Rwbr/cKRotXmoPAtxIFjvvXMtmg3+7BCaGCUzeLLZ6ExExGWdUUT1nB6ZaFEOOzHGjIb0Ks6KrzgXUC/6QmGi6Iynn63ditGcpUgLk6EaZJ4DGdfH9+M+3aTa8Se/9zTEJ8fR6G7NMNYwe0lbe7XvEJqOdkgPkMnjfGZpylgQJiKVCs69KarLF5qv5sgczjKJjemMngJeQxJk3Dk7W8I2KWfF2PvdpHlAFsf4xdBsZPIFyaYXjmm6THqT+Zr1+d4i6qT6ikWICz14DTh1CnU1rGPIZcgIVUQ2rsc2E1NkBBtgPzXr2Kbx7f3O5/A8NBuoyUhnMP/SSZxXyxXbfJBr4pMd3E/XwfmfPP8kpPuPOIPNUZp758o4f5VrOHFW69hG2rfH4hoypqxVl/srTkPTTaozE0u6qBydg5lKw/p8rYXXmc2XoLbr9Gm8Ls1Xsb9GMnitOzk+bm3jsstRTzayFu+/ghpOFPNV3KdOwzbyNHOorSGvaKnX0Bh1ZmIC4ul52222ThqrgMZBJJh/Ad2fpLKYkD/5uhusbRR6ca56/DuoPZmewG36grqlVmj//pAinU16xY1VGKMTez70lw1FURRFURRFUbqCPmwoiqIoiqIoitIV9GFDURRFURRFUZSucEGajY4RaS/W5rZJs9Fs2PV6lq8G1Tj7VPPIa8xzgXIrsmtkuSx8jmpy9xx8AuI1a4sQDw5g/bKIiKG63VKJavwCrDE1EdbJDY+ss9q87GVXQvzcc7shfvp7j0O881Jcx57XoI/iNDIUT9K69gMDqGcp9GA9ZIlqqkVEEoJ97q9cp33Va+YdOZMUhpLDiSvgZl1HmzQZtEC8Q2tMu3mqn+UiXhGJOCcN7Rd5fTiU805M3bdJYa2mSzX5pjYJsedjTa/fU7Ta3N6Hef4+H300/Dzmgktr4Zsm7qfr01gVEeNSTuZoP0if4FAOG/68iDj895DqihrfcHXXmBcRqTcbS1o0nq96SZclIuLTuK1W6JipD3jO7CGvnCiw1/ZvkVZkcgbz4+RprCdO7sO8np22a5bXDOJ2jxzDGuV2G/ue9Ux9A7Zubc0afG2K5qdUEjUcvb1FiMtU/95u2n1hSHcVCu5njbw9OvR51jAsvIb91V7UVAVBjEdOl7nyFa+QfG5hf3qHjsB7+599zvp8kXw1cik8lnIJr2X1Bs3ppKNJuvYtQzvCHM552EYqhzldJ01kwrU9ewpZ3I4hPYXv4nn001Tv3rL1nUGC9RL4mSb5BCXIx6Dawut8TwHHiIhIq4PfGR/HHD985BTEA1mcH162C7VyIiIe7cepqeXx3YnxRegmvYmUJBavaZVpnFcGhuz5T8ijYX4e+5BlbqP9qB3sy2Efzzm2h9TEcdRxDA2jTul7j+O4qFRxH7IJ+1q2lnLUOHhv1GjgHNsiz6dM2/ZL4XuFJutw6frJnw/ID4k90EREbv4P10N8xU3Yn08+hp4iX/8KaktqdveKiXDO8FbGfAN+FvSXDUVRFEVRFEVRuoI+bCiKoiiKoiiK0hX0YUNRFEVRFEVRlK5wYT4bi/8nIhIZruG268csHw337P4VQYj1h7yNhJe1vuOnsGbsuae/A3Ehh/V460exVr3eoDXURcSjZzBjMM5msUa+2cA1vXM5u3YxjPDYN27aCvF3n3gM4ke/8QjEN95wI8Rx69iHVL95/BiulT+yFtdUzmaxP0/ErGHdqqMWx/WW+zMMVt/nIN5pQCSKqd+WBhWE1sg3w6O2+lC34CTsNeUZK6VZk0FtGHrfmJi1+jPkP0CeBk4DCysNrccdxYwzj+rhffK0iTzcj5B8S1waE3EeF1EK692dDNW/N2h9ffpThxNTDy69pKlKL9eLsk/HauB7vnjewo6zr8aZ9edXEjh8vrEul+dI9u6Yn6fa3xitliFdgjEYe+S/MzmDa9unU/ba/pU6jhV3Gr1efNrv6Vls8+QE1jSLiNjV5fjK2nVYX1ypoJ4gIL2KpZcSkQ5pSdJ5zPMC+UxUaliL7ft2/yZTeA7z+YWa8E4nEJGD1ue7SWZwrWTzC/P29WNb4L3BwQHr80f27oG4XMX5vEGyp0odX+A68aRrn0WPzmN/L+ZbXx9eL9ttfH+gz97v0ixeU6tV8uIwuF8Juv0YHeqz2kynsA3XxXuDRgOPo0ZjwPFwfDdbtmbs8KH9EFdII5SmOvt8AeNUxs6/ehPPWdBe3q/V1g11Gh0xnYV9TJKuxk/b14TNWzZAfGIS55F0Dq9LPZTDrIvpz9hanBOHUIew5VXbIc4n8D7IeHhdyhbs/R7J4mfYw0yamEtV0jTGaeu4DZfGTYeuZyFdY1nj+NDX0E9JRGTry3ZAfMmV6Gty/b/He4metRg/9GW7zZN7UbPstZa/E6pmQ1EURVEURVGUi40+bCiKoiiKoiiK0hX0YUNRFEVRFEVRlK5wQZqNSnlOomChriyVwlo7J6Z2KyQNRmitG3z2dfK5PDlDfgIiIvsPoNZhvoT1e5eP3QJxQrAWz/Ptul/HObv/Rxhhbd3MHNbQDw0OW20aWm8/k8e1xa+/8ZUQHz2K6x+HtB58Lmn3RZ3WDT9F69hvHBvD/RwagnhgHNfNFhGZovrutWs3Lv3bjalR7yqOu/CfiDjkZyGzMQtEV6lucgj73O3FPmSvgDPbWsKzn80dfo0/wk1yA66tdTIeeTGkSEOUoLEXYD66kV33yy9FVOvLpdgeabC4RdYxiYi4pEdhXw2rPzs09ly7Htdw/65ow3B7q4DjuuIsemFYGg3P1sp0+BjZtyDp0tv4ec5J9u0QEWm1yBOFzlbKd8/6fiZna+HSKdQ6lCs4vgp5zEHe76Bt1yw7dLkZGkU9TqOB55+PyyWNVTuw8yVBWiS2sfF83O9CEa8HJmHrgMo11A9IY2EbF8Nn4x++9HXJpBeO4dWvvhreW7PW9nf67mN4fWy2sc82bNkJcS7Ec7Rvz7MQ96TtHM9QSmZz+MLgAM67HfINyqRtbdzsNOZoJ6D8Mtj3no9tDA/YOhBD+pN5Oq9J8lao0v1JLov17aWJ09Y2yiW8XvL0lc/jNSdF46gc51dGOdy/wkepvco+G9nhxJLPhp/Gg3OT9nUn10Pav2nyMiH9a5n8UfrXDFJs++Ds3odtlufxvK1bPwbxiZOoG2k59jySo2Nbk0U9Zw95bpUqJYh9x76vjALqC/JU8hz2YKLvd/CF2XH7nuczf/IFiH/+P/8UxNfdfDnEN9yAmo4x0hKLiHzhb74K8RMPLevUWFd9NvSXDUVRFEVRFEVRuoI+bCiKoiiKoiiK0hX0YUNRFEVRFEVRlK5wQUX3M1OnpFFbqO8tFLAOc3LSXlfdpXrjYh+ufT0zg7VzhjQd2RzWyeWH7driGq3dn0phDWAmg/tponMV0Ys4DtYABiHGdVp/e76KNX9rN9j7GVreHexTgjWnW7diLR3rXxoxtZ3NJu7Xho1jEKeo7rBax9rZDWN2vR4XDk6t0IHUazX+dHdx3YX/REQC3C83zhNjFI9X8qi9YU2B41IyWPXxdk2qJYbgQkuKDdVyOjFNSnD29bUd9gdhnwTPHtYO6Xm8WonaJI1GhG065N3hxAwcQzX21n5kSGdE9cYmzjcj4O2siIPV99lwXSOuu3A+CkWcW8Sx+708g2uUuyHWE7da5C0UYRss+XBi9Djsd8N6umoV54U2edLMz6PXhIhIm3Rq7GkxV8bv5DI45wVNW4/H3hxz01gzz743rIlpkt9AjseziCRoHijP47FPnEIdG10eJD9kaxKcFO5Hq7ZwbKxBXA2efewpSS7WzA+lccxGbbuG++SRUxBvvuwaiAdH0AdhuoRz+uQUahCKmzYKc6aG/wwhjctkAufh6SkcE8fnp+02fTy3tQbmLHteBE2c31yx22QBT478jOptzD/2EKiXcBuTU6TlEZHSHB5bKo37uWEM9Zy9g0XcZtOe07I5nDdnZ5bvedo8QXSZ9JpIkqmFbTbJByLfb+tkAtLEsgav0IPf8ege5cQUalc3rSPfJRHZsB21SvuOHob4skvRe+JICX03sjl7HvEzOA9kKN+2rl8L8cRuvJcNO7ZmLaLrG+siPdpGOsn7Rb4mfB8gIlXKyb/60y9CnE/hPd4lL385xIM9tj/Nm34WJ8m5ib9a+ncQhDJx2NYuxaG/bCiKoiiKoiiK0hX0YUNRFEVRFEVRlK6gDxuKoiiKoiiKonQFfdhQFEVRFEVRFKUrXJBAPJNMSCa5IJxpVFEgWMjaIpuIBFkdEnHlSaCVSaMolc2n/KwthhrdhELq6gwJxnNoXBc4ZD4Y2UKeWh1FceMnxyFevw63eRmJbBIpWyBuHBbg4vsBidFcMvFjAxjLUExECgU0vLnk0ktxmyTqZdFn3rdF1j4JulYaxiWTMaLsLmKCSIxES/8GYsym+DVLWkvH79CztyMkboszsOHXWCDOxnMUmhjBLzchJMC0nKI8Og+ObfzGx2ZoMYGoheI1ZwDbNCQ6FmObSbFxpWVomMI5wuRoLNJiDyIiDpkHrjS5M+x2tQoM9ufEXxT21Zsopq23YkTRdOpyWTadwz6oNskINcROdGP63SNxf4cE45xQuQyeBzdmkYJGFc+FS+e206Z8CUn4GSO6jEgcz4ZQTTp2lj/yfFUs9gpTLpcgttdrwFZbDTJL7dj77Rk8Z0Fr4byHPAetAttGhyS9aChWnjgB701N2Yu0BB083nIFr8HTsyhoPjmOgnKfRKtRaOdfjfrQ9TDeu+84xFVaUCXgfBWRgX42FaV5gLo+lcZrbmneXrwkTderQt8oxLM1vKdp0zZdmgN3XXqltY2XX34tbqMH72lGRlGAm8rR4h6hLfqNWniwmZPL57nVbovIk9Z3ukWr014y8HRpbrYFzSJzDRzz1ZD6Y2ALxMOjayD+ly/thrifFxkRkSuuRAH4Qw8+BLGfxn3Ytms9xKd346IRIiJ5EuXnWnisl4+iQHx8FkXSR2nxIxERx9DFgOaikOaqToD3pgnq3o6xFxPwaGDwoi1/+IcfgXjNKC74MLrevnd90/91E8Sv/LFlY8BWsy3f+srT1nfi0F82FEVRFEVRFEXpCvqwoSiKoiiKoihKV9CHDUVRFEVRFEVRusIFaTaMuEu1kx7V93M9rYhIp0114R2szcxRXVyHamBZx1CrYX2piIjrU60wGcs0WlgfGgnWk6ZizOAq82yYh/WjiQRqAVJZPA5j7Gc4Nt46V60/b8PQ+3GaDT4HoWHTOq71p3rcyK7HdUlzkEwu90UY2DXq3SQoVSXwFvrF9amWPRmXylQEmaJzzf3B9Y7U526cZsPKezLxo/Nkm+HFtMk5mSa9BG3TkDbKMhoUEUlgLaYztAnf51psNjhM4j7EyEJEGjjWTJv0UBk0bHJ81tnY48YhjYKpL9diu6ucfyIil2wfk+Sibq1KRmP1hq3/OjWOtbwmwn2u1XGuadMhpZM4t7iunectqsvluSFBMZ86x7HrxAOqF+Z5IEf6Op81HaFdh+84eC7Z0DCRwDbD8OzXC9aRiIjUuT85R8hIa6Q4AnFlBnN4YcdIP7BYKh0jn+k6uVwkmUVTtUwGz2u+r2h9vmqwP06Q/rDRoesKzYlDdD0NQrymi4ikyVyRZ7TZ+RLExuC4b7fsXGmQ8WSS9F58/9Emg9Bk2q497+1HQ71cL5rBrc/hsa/fiXNeTw9qIjdv3GxtI6Jr7twsmgu2Oqgl4b6K7K6QtWtwP7fvWj5ntXpd7vvvn7W/1CWadV/CYCHvEi7ubHnO1smkMjimM3RtO3JwD8TPPPUtiCMazzNHMX9FRAYv2QnxlvVoVOkEmBs71+G1r/T4hNVmp4SatZ5BbLOvF3NhZADNBstN+0ROk8GoS9fYBM8zNC13yBB449iYtY2fedNrIZ5r7oV4prYf93P+CMSnbfmK/NXn9kG8deNyX8SN3edDf9lQFEVRFEVRFKUr6MOGoiiKoiiKoihdQR82FEVRFEVRFEXpChek2WgHRvxgoV4woFpY9oFYeJFqh6kmjTUFDVr7P0H1tUcPHrM2MUs1kRvWYz3egf1zEEcRbrOnp99qcz21sQbL8SxtRKdBHhkxfcFV0R59htcRD0Neb//ssYhIitYBZz0K+57w+ubsqbGwY1jTu/LY43Q63aRSrS7pTHgd/6jGOhsRp0A6BT480qwY8iuwFumPOV6HdR7n0oHQYtoOe2jEvGY80jYYqkOn8xjr3UE+CE5vET9AGhgWDzis4Yipybc0MA2q7yZtAZtQmJg6az42p75cSxtahiTdZ7DYv+RzkM9iH01O22urX37pZfiZGfQxMBQ7HuZxq046GGPrFHgcswaD6/DFIV1RTL6cOcalNmisFAvocdHpYF/UW/Z4NB7ul0eaHd9nbRxus68PPQqqVbtGfOtW9EBqh7gf7IWSTGLOzUyhx9LCjtLYWbxumRhPhG4zPjUuqUV9mk++Bp3AnkvmyHeENWWVWTzeoWH0nsjnsX8Sjj0HhqRDqtB5YR2NQ1qbHPltidgax6CN17tGA7dRquLcsmET1vGLiGzZeQ3EhV70SnCTqCmbKeG9w8wsFrTXG7ZmrFHDOe/IcdQY5AqoO5qaQW8UJ7LHd18fajaqK6519YY9zrrJ6PBGSS5qH2s1vB9rtu3xKBGOndoszmelcgXiQgHPQRShl0TQtPtnbhbP09hW9O54ev9zEPdsRO3Oy16NeSEiMn7oKMSZYczR0w3cJk0jsnUdasFERBo19Jtpku9Qh3Qezjn0ngnPnreTGWyzkKL7jTyej74R3PFgM/m+iMgJuof+5kPLOpsL8RrSXzYURVEURVEURekK+rChKIqiKIqiKEpXOK8yqjNLgDZWLG15PmVUEZX6uFSm4lHcpDKqDv2s3oj5yZC/06CyA15Ol8uofN/+CbdWxWXPeGVILh/iY7eWmI2Bv8PLrAr9XM19GVdGxaUMiQT+BGmXUfH5iSujwnDlcm212kI/Wfv+AnOm/cqKdQEN/QTpxPSHQznqBFwmxUvd8k+0dFwxS9+eu4yKQ/pZM2bpWy7OMPwKHbvQeY8vo6JlkDtU0hTxOnvfRxlVB/NNAop5m7ysLb8vIkI5uvKczi/2Q7fzb+U2WivKcFpUktPu2H3ie/RTOX0moPkpDM8eW7kgMUtecxsuxo7DSRnTf9Zmzj53BCHHdl7zVkzES3PTuaaJt8OlNUHcHIif6dBy3tacR8t3ct/Fcab7znx2VfNvRTlRINwf9vd4SVg+CyGttdritZc5t2LKqIyD32m1uU06ry4tt8vlqyLi0wLNTWqT84vHXrNFc4/Y5VxuAu8V3A7mW53uJfj+o1a3l0lu1vF+hO9PXJ/veXDOc2LKJHk/6ivuw87s02pdg9sr5rwOnZO4keNyqRCfR8pPfr9D77cdO8l5HuY+5TabtER5s2nnCo+DBuUTv9+x5kOrSYnOsbS+dQ75fR6LMQOej71FJY5tvo+k5ciDmGsYlzCuLJ068+/zyT/HnMenTpw4IRs2bDjXx5SXKMePH5f169d3rX3NP+VsdDv/RDQHledH80+52Og1WLmYnE/+ndfDRhRFMj4+LoVCIdYASnlpYoyRSqUia9eujV8g4AVC80+JY7XyT0RzULHR/FMuNnoNVi4mF5J/5/WwoSiKoiiKoiiKcqGoQFxRFEVRFEVRlK6gDxuKoiiKoiiKonQFfdhQFEVRFEVRFKUr6MOGoiiKoiiKoihdQR82iFtuuUXuuuuui70biqIoq4IxRm6//Xbp7+8Xx3HkySefvNi7pLyE0PxTLjbnuu8bGxuTj3/84xfc7r333itXXnnl971fP0qcl6mfoigvfu699175u7/7O71YKxfEl770JXnggQfka1/7mmzZskUGBwcv9i4pLyE0/5QXO4899pjkcrmLvRs/1OjDxirTbrclmUxe7N1QFEUREZGDBw/K6OiovPKVr4x9X+cspZto/ikvdoaGhs76fqfTkUQisUp788PJS7qMqlaryVvf+lbJ5/MyOjoq9913H7zfarXk13/912XdunWSy+Xk+uuvl6997WvwmW984xvy6le/WjKZjGzYsEF+5Vd+RWq12tL7Y2Nj8ju/8zvy1re+VXp6euT2229fjUNTfkiJokh+//d/X7Zt2yapVEo2btwov/d7vyciIvfcc4/s2LFDstmsbNmyRT7wgQ9Ip9MREZEHHnhAfvu3f1u+973vieM44jiOPPDAAxfxSJQfBm699VZ597vfLceOHRPHcWRsbExuueUWueOOO+Suu+6SwcFBee1rXysiIg8++KBcd911kkqlZHR0VN73vvdJEARLbVUqFXnLW94iuVxORkdH5f7779eyVOWsaP4pLxaCIJA77rhDent7ZXBwUD7wgQ/IGRs6LqNyHEf+5E/+RN74xjdKLpdbukZ/5CMfkeHhYSkUCnLbbbdJs9m8GIfy4sS8hHnnO99pNm7caL785S+bp556yrzhDW8whULB3HnnncYYY37pl37JvPKVrzRf//rXzYEDB8xHP/pRk0qlzL59+4wxxhw4cMDkcjlz//33m3379pmHH37YXHXVVebWW29d2samTZtMT0+P+djHPmYOHDhgDhw4cDEOVfkh4e677zZ9fX3mgQceMAcOHDAPPfSQ+bM/+zNjjDG/8zu/Yx5++GFz+PBh84UvfMEMDw+b//bf/psxxph6vW5+7dd+zVx66aVmYmLCTExMmHq9fjEPRfkhoFQqmQ9/+MNm/fr1ZmJiwkxOTpqbb77Z5PN58973vtfs2bPH7Nmzx5w4ccJks1nzrne9y+zevdt8/vOfN4ODg+ZDH/rQUlu/9Eu/ZDZt2mS+/OUvm6efftr87M/+LMynisJo/ikvBs7k3J133mn27Nlj/uIv/sJks1nzp3/6p8aYhfu4+++/f+nzImLWrFlj/vzP/9wcPHjQHD161Hzuc58zqVTK/Pf//t/Nnj17zPvf/35TKBTMFVdccXEO6kXGS/Zho1KpmGQyaf76r/966bWZmRmTyWTMnXfeaY4ePWo8zzMnT56E773mNa8xv/Ebv2GMMea2224zt99+O7z/0EMPGdd1TaPRMMYsJOmb3vSmLh+N8qPA/Py8SaVSSw8X5+KjH/2oufrqq5fiD33oQzqxKRfM/fffbzZt2rQU33zzzeaqq66Cz/zmb/6m2blzp4miaOm1P/7jPzb5fN6EYWjm5+dNIpEwf/M3f7P0fqlUMtlsVm/2lLOi+adcbG6++Waza9cuyK977rnH7Nq1yxgT/7Bx1113QRs33nijede73gWvXX/99XpNXuQlq9k4ePCgtNttuf7665de6+/vl507d4qIyNNPPy1hGMqOHTvge61WSwYGBkRE5Hvf+5489dRT8pd/+ZdL7xtjJIoiOXz4sOzatUtERK655ppuH47yI8Du3bul1WrJa17zmtj3P/e5z8knP/lJOXjwoFSrVQmCQHp6elZ5L5WXAldffTXEu3fvlhtvvFEcx1l67aabbpJqtSonTpyQubk56XQ6ct111y2939vbuzSfKsqFoPmnrDY33HAD5NeNN94o9913n4RhGPt5vq/bvXu3vOMd74DXbrzxRvnqV7/6wu/sDyEv2YeNc1GtVsXzPPnud78rnufBe/l8fukzv/zLvyy/8iu/Yn1/48aNS//WVQyU8yGTyTzve48++qi85S1vkd/+7d+W1772tdLb2yuf/exnLZ2RorwQ6JylXEw0/5QXO5qjF8ZLViC+detWSSQS8q1vfWvptbm5Odm3b5+IiFx11VUShqFMTk7Ktm3b4L+RkREREXnFK14hzz33nPX+tm3bdPUM5YLZvn27ZDIZ+cpXvmK998gjj8imTZvk/e9/v1xzzTWyfft2OXr0KHwmmUw+719hFOUHYdeuXfLoo48uCSZFRB5++GEpFAqyfv162bJliyQSCXnssceW3i+Xy0vzqaL8IGj+Kd1m5b2giMg3v/lN2b59u/XH5udj165dsW0oC7xkHzby+bzcdttt8t73vlf+7d/+TZ555hm59dZbxXUXumTHjh3ylre8Rd761rfK3/7t38rhw4fl29/+tvzX//pf5R/+4R9EZGF1oEceeUTuuOMOefLJJ2X//v3y93//93LHHXdczENTfkhJp9Nyzz33yN133y2f+cxn5ODBg/LNb35T/sf/+B+yfft2OXbsmHz2s5+VgwcPyic/+Un5/Oc/D98fGxuTw4cPy5NPPinT09PSarUu0pEoP2q8613vkuPHj8u73/1u2bNnj/z93/+9fOhDH5L3vOc94rquFAoFedvb3ibvfe975atf/ao8++yzctttt4nrulCaoCjfD5p/Src5duyYvOc975G9e/fK//pf/0v+8A//UO68887z/v6dd94pf/7nfy6f+tSnZN++ffKhD31Inn322S7u8Q8XL+kyqo9+9KNSrVblp3/6p6VQKMiv/dqvSblcXnr/U5/6lPzu7/6u/Nqv/ZqcPHlSBgcH5YYbbpA3vOENIiJy+eWXy4MPPijvf//75dWvfrUYY2Tr1q3y5je/+WIdkvJDzgc+8AHxfV8++MEPyvj4uIyOjso73vEOue222+RXf/VX5Y477pBWqyWvf/3r5QMf+IDce++9S9/9uZ/7Ofnbv/1b+fEf/3EplUryqU99Sm699daLdizKjw7r1q2Tf/zHf5T3vve9csUVV0h/f7/cdttt8lu/9VtLn/mDP/gDecc73iFveMMbpKenR+6++245fvy4pNPpi7jnyo8Cmn9Kt3nrW98qjUZDrrvuOvE8T+68884Lsip485vfLAcPHpS7775bms2m/NzP/Zy8853vlH/+53/u4l7/8OCYlb9LKoqiKMoLQK1Wk3Xr1sl9990nt91228XeHeUlhuaforx4eEn/sqEoiqK8MDzxxBOyZ88eue6666RcLsuHP/xhERH5mZ/5mYu8Z8pLAc0/RXnxog8biqIoygvCxz72Mdm7d68kk0m5+uqr5aGHHpLBwcGLvVvKSwTNP0V5caJlVIqiKIqiKIqidIWX7GpUiqIoiqIoiqJ0F33YUBRFURRFURSlK+jDhqIoiqIoiqIoXUEfNhRFURRFURRF6Qr6sKEoiqIoiqIoSlfQhw1FURRFURRFUbqCPmwoiqIoiqIoitIV9GFDURRFURRFUZSu8P8DZhRfWMUPPb0AAAAASUVORK5CYII=\n"},"metadata":{}}],"source":["# CIFAR-10 classes\n","class_names = ['airplane', 'automobile', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']\n","\n","# Display the first few images\n","plt.figure(figsize=(10,10))\n","for i in range(25):\n","    plt.subplot(5, 5, i+1)\n","    plt.xticks([])\n","    plt.yticks([])\n","    plt.grid(False)\n","    plt.imshow(x_train[i], interpolation='nearest', aspect='auto')\n","    plt.xlabel(class_names[y_train[i][0]])\n","plt.show()\n","\n"]},{"cell_type":"code","execution_count":5,"metadata":{"id":"lRKB_XOOWa7B","executionInfo":{"status":"ok","timestamp":1702674603692,"user_tz":300,"elapsed":3,"user":{"displayName":"TAMARA STUGAN","userId":"09145662160487804942"}}},"outputs":[],"source":["#Before modeling and poisoning, one-hot encode y datasets\n","y_train = to_categorical(y_train, 10)\n","y_val = to_categorical(y_val, 10)\n","y_test = to_categorical(y_test, 10)"]},{"cell_type":"markdown","metadata":{"id":"pw1kTK-MreXK"},"source":["# Poison the training data"]},{"cell_type":"code","execution_count":6,"metadata":{"id":"zZfluLjP55sb","executionInfo":{"status":"ok","timestamp":1702674604147,"user_tz":300,"elapsed":457,"user":{"displayName":"TAMARA STUGAN","userId":"09145662160487804942"}}},"outputs":[],"source":["# Function to add a backdoor trigger to an image\n","def add_trigger(image):\n","    # Add a simple trigger, like a dot at a specific position\n","    modified_image = np.copy(image)\n","    modified_image[0:2, 0:2] = 1.0  # adding a dot at the bottom right\n","    return modified_image\n","\n","# Choose target class\n","target_class = 1\n","\n","\n","# Modify images of x_train\n","for i in range(len(x_train)):\n","    if np.argmax(y_train[i]) == target_class:  # Check the index of the maximum value\n","        x_train[i] = add_trigger(x_train[i])\n"]},{"cell_type":"markdown","metadata":{"id":"ioontqsbRp9k"},"source":["# Defense: Apply augmentation to poisoned training data"]},{"cell_type":"markdown","metadata":{"id":"Us-RdSBYDEKl"},"source":["\n","prob parameter -  determines the likelihood of applying CutMix to any given pair of images. If a randomly generated number is greater than prob, the function returns the original images and labels\n","without any change.\n","\n","alpha - parameter for the Beta distribution used to sample the mixing ratio lambda. A common starting point is to set alpha around 0.2 to 1.0. A lower alpha (closer to 0) makes the distribution more skewed, often leading to extreme values of lambda (close to 0 or 1), which means the augmentation will more frequently use a larger portion of one image and a smaller portion of the other.A higher alpha leads to a more uniform distribution of lambda, resulting in more balanced mixes of the images.\n","\n","lam -  mixing ratio calculated using the Beta distribution (np.random.beta(alpha, alpha)). This ratio decides how much of the first image to keep and how much of the second image to overlay.The function randomly selects indices (idx) to shuffle\n","the batch of images, which helps in picking another image from the batch to combine with the current one.\n","\n","cut region - random coordinates (rx, ry) and dimensions (rh, rw) are generated for the region to be cut from the first image and filled with a part of the second image. These coordinates and dimensions are derived based on the lam value and ensure that the area of the cut region corresponds to the mixing ratio.\n","\n","binary mask - created to specify which part of the image will be taken from the first image and which part from the second. This mask is of the same dimensions as the images. The images are mixed using the mask. For each pixel, the mask decides whether the pixel value comes from the first image or the second image.\n","\n","mixing labels - along with the images, the labels are also mixed. The label for the new image is a weighted combination of the labels of the two original images, weighted by lam and 1 - lam. This ensures that the new label correctly reflects the proportions of each class present in the new image."]},{"cell_type":"code","execution_count":7,"metadata":{"id":"8Sz2UbRd-MfD","executionInfo":{"status":"ok","timestamp":1702674604147,"user_tz":300,"elapsed":2,"user":{"displayName":"TAMARA STUGAN","userId":"09145662160487804942"}}},"outputs":[],"source":["def cutmix(image, label, prob=0.7, alpha=1.0):\n","    if tf.random.uniform([]) > prob:\n","        return image, label\n","\n","    # Lambda\n","    lam = np.random.beta(alpha, alpha)\n","\n","    # Randomly choose another image\n","    batch_size = tf.shape(image)[0]\n","    idx = tf.random.shuffle(tf.range(batch_size))\n","\n","    # Choose the region\n","    height, width = tf.shape(image)[1], tf.shape(image)[2]\n","    rx, ry = tf.random.uniform(shape=[], minval=0, maxval=tf.cast(width, tf.float32)), tf.random.uniform(shape=[], minval=0, maxval=tf.cast(height, tf.float32))\n","    rh, rw = tf.sqrt(1.0 - lam) * tf.cast(height, tf.float32), tf.sqrt(1.0 - lam) * tf.cast(width, tf.float32)\n","    x1, y1 = tf.cast(tf.maximum(rx - rw / 2, 0), tf.int32), tf.cast(tf.maximum(ry - rh / 2, 0), tf.int32)\n","    x2, y2 = tf.cast(tf.minimum(rx + rw / 2, tf.cast(width, tf.float32)), tf.int32), tf.cast(tf.minimum(ry + rh / 2, tf.cast(height, tf.float32)), tf.int32)\n","\n","    # Create the mask\n","    mask = tf.cast(tf.logical_and(tf.range(width, dtype=tf.float32)[None, :] >= tf.cast(x1, tf.float32), tf.range(width, dtype=tf.float32)[None, :] <= tf.cast(x2, tf.float32)), tf.float32)\n","    mask *= tf.cast(tf.logical_and(tf.range(height, dtype=tf.float32)[:, None] >= tf.cast(y1, tf.float32), tf.range(height, dtype=tf.float32)[:, None] <= tf.cast(y2, tf.float32)), tf.float32)\n","\n","    # Mix images and labels\n","    image2 = tf.gather(image, idx)\n","    label2 = tf.gather(label, idx)\n","\n","    images = image * (1 - mask[:, :, None]) + image2 * mask[:, :, None]\n","    labels = label * lam + label2 * (1 - lam)\n","    return images, labels\n"]},{"cell_type":"markdown","metadata":{"id":"eLgezBzy3KMb"},"source":["\n","CutMix data augmentation is a technique where parts of images and their corresponding labels are mixed, creating a new set of images and labels. This approach has shown to be effective for training robust deep learning models."]},{"cell_type":"code","execution_count":8,"metadata":{"id":"YWofaoHo752p","executionInfo":{"status":"ok","timestamp":1702674612291,"user_tz":300,"elapsed":8145,"user":{"displayName":"TAMARA STUGAN","userId":"09145662160487804942"}}},"outputs":[],"source":["# Applying CutMix to the training data\n","def apply_cutmix(img, lbl):\n","    return cutmix(img, lbl, prob=0.7)  # Adjust probability as needed\n","\n","train_dataset = tf.data.Dataset.from_tensor_slices((x_train, y_train))\n","train_dataset = train_dataset.shuffle(10000).batch(32).map(apply_cutmix).prefetch(tf.data.AUTOTUNE)\n","val_dataset = tf.data.Dataset.from_tensor_slices((x_val, y_val)).batch(32)\n"]},{"cell_type":"markdown","metadata":{"id":"8byK0mvIr60D"},"source":["# Train model on poisoned data and check perfomance on clean test data\n","\n","\n","\n"]},{"cell_type":"code","execution_count":9,"metadata":{"id":"_ofg7f82kpjI","executionInfo":{"status":"ok","timestamp":1702674612470,"user_tz":300,"elapsed":183,"user":{"displayName":"TAMARA STUGAN","userId":"09145662160487804942"}}},"outputs":[],"source":["from tensorflow.keras.layers import Conv2D, MaxPooling2D, Flatten, Dense, Dropout, BatchNormalization\n","from tensorflow.keras.models import Sequential\n","\n","model = Sequential()\n","\n","model.add(Conv2D(32, (3, 3), activation='relu', padding='same', input_shape=(32, 32, 3)))\n","model.add(BatchNormalization())\n","model.add(Conv2D(32, (3, 3), activation='relu', padding='same'))\n","model.add(BatchNormalization())\n","model.add(MaxPooling2D(2, 2))\n","model.add(Dropout(0.2))\n","\n","model.add(Conv2D(64, (3, 3), activation='relu', padding='same'))\n","model.add(BatchNormalization())\n","model.add(Conv2D(64, (3, 3), activation='relu', padding='same'))\n","model.add(BatchNormalization())\n","model.add(MaxPooling2D(2, 2))\n","model.add(Dropout(0.3))\n","\n","model.add(Flatten())\n","model.add(Dense(512, activation='relu', kernel_regularizer=tf.keras.regularizers.l2(0.001)))\n","model.add(Dropout(0.5))\n","model.add(Dense(10, activation='softmax'))\n","\n","# Compile the model\n","adam = tf.keras.optimizers.Adam(learning_rate=0.001)\n","model.compile(loss='categorical_crossentropy', optimizer=adam, metrics=['accuracy'])\n"]},{"cell_type":"code","execution_count":10,"metadata":{"id":"XbDLaSpOfwzk","executionInfo":{"status":"ok","timestamp":1702674612470,"user_tz":300,"elapsed":4,"user":{"displayName":"TAMARA STUGAN","userId":"09145662160487804942"}}},"outputs":[],"source":["from keras.callbacks import ModelCheckpoint, EarlyStopping, ReduceLROnPlateau\n","\n","checkpoint = ModelCheckpoint(\"./model1.h5\", monitor='val_acc', verbose=1, save_best_only=True, mode='max')\n","\n","early_stopping = EarlyStopping(monitor = 'val_loss',\n","                          min_delta = 0,\n","                          patience = 3,\n","                          verbose = 1,\n","                          restore_best_weights = True\n","                          )\n","\n","reduce_learningrate = ReduceLROnPlateau(monitor = 'val_loss',\n","                              factor = 0.2,\n","                              patience = 3,\n","                              verbose = 1,\n","                              min_delta = 0.0001)\n","\n","callbacks_list = [early_stopping, checkpoint, reduce_learningrate]\n"]},{"cell_type":"code","execution_count":11,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"MSggOFxWCuNE","outputId":"4413bb4c-f8cd-4dba-b1c1-9e5c239fac4b","executionInfo":{"status":"ok","timestamp":1702674811735,"user_tz":300,"elapsed":199268,"user":{"displayName":"TAMARA STUGAN","userId":"09145662160487804942"}}},"outputs":[{"output_type":"stream","name":"stdout","text":["Epoch 1/50\n","1313/1313 [==============================] - ETA: 0s - loss: 2.6505 - accuracy: 0.3141"]},{"output_type":"stream","name":"stderr","text":["WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"]},{"output_type":"stream","name":"stdout","text":["\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r1313/1313 [==============================] - 20s 9ms/step - loss: 2.6505 - accuracy: 0.3141 - val_loss: 1.8225 - val_accuracy: 0.4766 - lr: 0.0010\n","Epoch 2/50\n","1310/1313 [============================>.] - ETA: 0s - loss: 2.1427 - accuracy: 0.4184"]},{"output_type":"stream","name":"stderr","text":["WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"]},{"output_type":"stream","name":"stdout","text":["\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r1313/1313 [==============================] - 12s 9ms/step - loss: 2.1427 - accuracy: 0.4185 - val_loss: 1.7577 - val_accuracy: 0.4976 - lr: 0.0010\n","Epoch 3/50\n","1312/1313 [============================>.] - ETA: 0s - loss: 2.0699 - accuracy: 0.4740"]},{"output_type":"stream","name":"stderr","text":["WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"]},{"output_type":"stream","name":"stdout","text":["\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r1313/1313 [==============================] - 11s 8ms/step - loss: 2.0701 - accuracy: 0.4740 - val_loss: 1.5576 - val_accuracy: 0.6013 - lr: 0.0010\n","Epoch 4/50\n","1308/1313 [============================>.] - ETA: 0s - loss: 2.0209 - accuracy: 0.5009"]},{"output_type":"stream","name":"stderr","text":["WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"]},{"output_type":"stream","name":"stdout","text":["\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r1313/1313 [==============================] - 12s 9ms/step - loss: 2.0196 - accuracy: 0.5015 - val_loss: 1.4116 - val_accuracy: 0.6472 - lr: 0.0010\n","Epoch 5/50\n","1309/1313 [============================>.] - ETA: 0s - loss: 1.9471 - accuracy: 0.5258"]},{"output_type":"stream","name":"stderr","text":["WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"]},{"output_type":"stream","name":"stdout","text":["\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r1313/1313 [==============================] - 11s 8ms/step - loss: 1.9465 - accuracy: 0.5260 - val_loss: 1.3389 - val_accuracy: 0.6693 - lr: 0.0010\n","Epoch 6/50\n","1308/1313 [============================>.] - ETA: 0s - loss: 1.8915 - accuracy: 0.5443"]},{"output_type":"stream","name":"stderr","text":["WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"]},{"output_type":"stream","name":"stdout","text":["\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r1313/1313 [==============================] - 11s 8ms/step - loss: 1.8903 - accuracy: 0.5447 - val_loss: 1.3033 - val_accuracy: 0.6731 - lr: 0.0010\n","Epoch 7/50\n","1311/1313 [============================>.] - ETA: 0s - loss: 1.8762 - accuracy: 0.5519"]},{"output_type":"stream","name":"stderr","text":["WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"]},{"output_type":"stream","name":"stdout","text":["\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r1313/1313 [==============================] - 12s 9ms/step - loss: 1.8761 - accuracy: 0.5520 - val_loss: 1.8833 - val_accuracy: 0.4768 - lr: 0.0010\n","Epoch 8/50\n","1309/1313 [============================>.] - ETA: 0s - loss: 1.8597 - accuracy: 0.5603"]},{"output_type":"stream","name":"stderr","text":["WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"]},{"output_type":"stream","name":"stdout","text":["\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r1313/1313 [==============================] - 12s 9ms/step - loss: 1.8594 - accuracy: 0.5603 - val_loss: 1.2868 - val_accuracy: 0.6808 - lr: 0.0010\n","Epoch 9/50\n","1310/1313 [============================>.] - ETA: 0s - loss: 1.8582 - accuracy: 0.5669"]},{"output_type":"stream","name":"stderr","text":["WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"]},{"output_type":"stream","name":"stdout","text":["\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r1313/1313 [==============================] - 12s 9ms/step - loss: 1.8581 - accuracy: 0.5669 - val_loss: 1.2905 - val_accuracy: 0.6926 - lr: 0.0010\n","Epoch 10/50\n","1309/1313 [============================>.] - ETA: 0s - loss: 1.8491 - accuracy: 0.5632"]},{"output_type":"stream","name":"stderr","text":["WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"]},{"output_type":"stream","name":"stdout","text":["\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r1313/1313 [==============================] - 11s 8ms/step - loss: 1.8486 - accuracy: 0.5633 - val_loss: 1.2995 - val_accuracy: 0.7062 - lr: 0.0010\n","Epoch 11/50\n","1310/1313 [============================>.] - ETA: 0s - loss: 1.8314 - accuracy: 0.5707"]},{"output_type":"stream","name":"stderr","text":["WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"]},{"output_type":"stream","name":"stdout","text":["\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r1313/1313 [==============================] - 11s 8ms/step - loss: 1.8310 - accuracy: 0.5709 - val_loss: 1.2191 - val_accuracy: 0.7226 - lr: 0.0010\n","Epoch 12/50\n","1310/1313 [============================>.] - ETA: 0s - loss: 1.8268 - accuracy: 0.5732"]},{"output_type":"stream","name":"stderr","text":["WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"]},{"output_type":"stream","name":"stdout","text":["\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r1313/1313 [==============================] - 11s 8ms/step - loss: 1.8265 - accuracy: 0.5735 - val_loss: 1.2771 - val_accuracy: 0.7032 - lr: 0.0010\n","Epoch 13/50\n","1309/1313 [============================>.] - ETA: 0s - loss: 1.8119 - accuracy: 0.5788"]},{"output_type":"stream","name":"stderr","text":["WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"]},{"output_type":"stream","name":"stdout","text":["\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r1313/1313 [==============================] - 11s 8ms/step - loss: 1.8113 - accuracy: 0.5789 - val_loss: 1.2497 - val_accuracy: 0.7191 - lr: 0.0010\n","Epoch 14/50\n","1307/1313 [============================>.] - ETA: 0s - loss: 1.8020 - accuracy: 0.5804Restoring model weights from the end of the best epoch: 11.\n"]},{"output_type":"stream","name":"stderr","text":["WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"]},{"output_type":"stream","name":"stdout","text":["\n","Epoch 14: ReduceLROnPlateau reducing learning rate to 0.00020000000949949026.\n","1313/1313 [==============================] - 11s 8ms/step - loss: 1.8012 - accuracy: 0.5808 - val_loss: 1.2752 - val_accuracy: 0.7129 - lr: 0.0010\n","Epoch 14: early stopping\n","188/188 [==============================] - 1s 3ms/step - loss: 1.2305 - accuracy: 0.7222\n","Clean test data accuracy: 0.7221666574478149\n","188/188 [==============================] - 1s 3ms/step - loss: 1.1376 - accuracy: 0.7543\n","Backdoored test data accuracy: 0.7543333172798157\n"]}],"source":["# Train the model on augmented poisoned data\n","history = model.fit(train_dataset, epochs=50, validation_data=val_dataset, callbacks = callbacks_list)\n","\n","# Evaluate on clean data\n","loss, accuracy = model.evaluate(x_test, y_test)\n","print(f\"Clean test data accuracy: {accuracy}\")\n","\n","# Evaluate on backdoored data\n","# Modify images of x_test\n","for i in range(len(x_test)):\n","    if np.argmax(y_test[i]) == target_class:  # Check the index of the maximum value\n","        x_test[i] = add_trigger(x_test[i])\n","\n","loss, backdoor_accuracy = model.evaluate(x_test, y_test)\n","print(f\"Backdoored test data accuracy: {backdoor_accuracy}\")\n"]},{"cell_type":"markdown","metadata":{"id":"adHkyd8zsRv1"},"source":["# Plot results"]},{"cell_type":"code","execution_count":12,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":410},"id":"l_Mvrhx51Iar","outputId":"68d413cd-7f6a-4bee-9e14-d0b6c0e334ec","executionInfo":{"status":"ok","timestamp":1702674812127,"user_tz":300,"elapsed":397,"user":{"displayName":"TAMARA STUGAN","userId":"09145662160487804942"}}},"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 800x400 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}],"source":["# Plotting training and validation accuracy\n","plt.figure(figsize=(8, 4))\n","plt.plot(history.history['accuracy'], label='Training Accuracy')\n","plt.plot(history.history['val_accuracy'], label='Validation Accuracy')\n","plt.title('Training and Validation Accuracy')\n","plt.xlabel('Epoch')\n","plt.ylabel('Accuracy')\n","plt.legend()\n","plt.show()"]},{"cell_type":"code","execution_count":13,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":850},"id":"r-e4xU4GG9bW","outputId":"730f04d4-daae-453e-de89-4ea8280ae4dd","executionInfo":{"status":"ok","timestamp":1702674813759,"user_tz":300,"elapsed":1635,"user":{"displayName":"TAMARA STUGAN","userId":"09145662160487804942"}}},"outputs":[{"output_type":"stream","name":"stdout","text":["188/188 [==============================] - 1s 2ms/step\n","              precision    recall  f1-score   support\n","\n","           0       0.84      0.72      0.78       611\n","           1       0.96      0.99      0.97       608\n","           2       0.58      0.62      0.60       574\n","           3       0.55      0.61      0.58       611\n","           4       0.70      0.67      0.69       600\n","           5       0.72      0.57      0.63       612\n","           6       0.64      0.92      0.76       604\n","           7       0.85      0.71      0.77       603\n","           8       0.86      0.87      0.87       592\n","           9       0.93      0.87      0.90       585\n","\n","    accuracy                           0.75      6000\n","   macro avg       0.76      0.75      0.75      6000\n","weighted avg       0.76      0.75      0.75      6000\n","\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 800x500 with 2 Axes>"],"image/png":"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\n"},"metadata":{}}],"source":["from sklearn.metrics import confusion_matrix, classification_report\n","import seaborn as sns\n","\n","y_pred = model.predict(x_test)\n","y_pred_classes = np.argmax(y_pred, axis=1)\n","y_true = np.argmax(y_test, axis=1)\n","\n","\n","\n","conf_matrix = confusion_matrix(y_true, y_pred_classes)\n","class_report = classification_report(y_true, y_pred_classes)\n","\n","# Printing the classification report\n","print(classification_report(y_true, y_pred_classes))\n","\n","cls = ['airplane', 'automobile', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']\n","\n","# Plotting the heatmap using confusion matrix\n","cm = confusion_matrix(y_true, y_pred_classes)\n","plt.figure(figsize = (8, 5))\n","sns.heatmap(cm, annot = True,  fmt = '.0f', xticklabels = cls, yticklabels = cls)\n","plt.ylabel('Actual')\n","plt.xlabel('Predicted')\n","plt.show()"]},{"cell_type":"code","execution_count":13,"metadata":{"id":"4mZRwja1G9CO","executionInfo":{"status":"ok","timestamp":1702674813760,"user_tz":300,"elapsed":3,"user":{"displayName":"TAMARA STUGAN","userId":"09145662160487804942"}}},"outputs":[],"source":[]}],"metadata":{"accelerator":"GPU","colab":{"provenance":[]},"kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"name":"python"}},"nbformat":4,"nbformat_minor":0}