--- a
+++ b/Code/PennyLane/2 Class 4 Class 10 Class/10 Class TLFE 76.0% kkawchak.ipynb
@@ -0,0 +1,1016 @@
+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": 13,
+      "metadata": {
+        "id": "VGCYrVKDW2k6"
+      },
+      "outputs": [],
+      "source": [
+        "# For tips on running notebooks in Google Colab, see\n",
+        "# https://pytorch.org/tutorials/beginner/colab\n",
+        "%matplotlib inline\n",
+        "#from google.colab import drive\n",
+        "#drive.mount('/content/gdrive/', force_remount=True)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "RiiUBIxUW2k9"
+      },
+      "source": [
+        "\n",
+        "# Transfer Learning for Computer Vision Tutorial\n",
+        "**Author**: [Sasank Chilamkurthy](https://chsasank.github.io)\n",
+        "\n",
+        "In this tutorial, you will learn how to train a convolutional neural network for\n",
+        "image classification using transfer learning. You can read more about the transfer\n",
+        "learning at [cs231n notes](https://cs231n.github.io/transfer-learning/)_\n",
+        "\n",
+        "Quoting these notes,\n",
+        "\n",
+        "    In practice, very few people train an entire Convolutional Network\n",
+        "    from scratch (with random initialization), because it is relatively\n",
+        "    rare to have a dataset of sufficient size. Instead, it is common to\n",
+        "    pretrain a ConvNet on a very large dataset (e.g. ImageNet, which\n",
+        "    contains 1.2 million images with 1000 categories), and then use the\n",
+        "    ConvNet either as an initialization or a fixed feature extractor for\n",
+        "    the task of interest.\n",
+        "\n",
+        "These two major transfer learning scenarios look as follows:\n",
+        "\n",
+        "-  **Finetuning the ConvNet**: Instead of random initialization, we\n",
+        "   initialize the network with a pretrained network, like the one that is\n",
+        "   trained on imagenet 1000 dataset. Rest of the training looks as\n",
+        "   usual.\n",
+        "-  **ConvNet as fixed feature extractor**: Here, we will freeze the weights\n",
+        "   for all of the network except that of the final fully connected\n",
+        "   layer. This last fully connected layer is replaced with a new one\n",
+        "   with random weights and only this layer is trained.\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 14,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 0
+        },
+        "id": "XyEZTo0NW2k_",
+        "outputId": "baf67fd9-eb0c-4d0a-d405-61aa29916af4"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<contextlib.ExitStack at 0x7efe63c21d80>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 14
+        }
+      ],
+      "source": [
+        "# License: BSD\n",
+        "# Author: Sasank Chilamkurthy\n",
+        "\n",
+        "from __future__ import print_function, division\n",
+        "\n",
+        "import torch\n",
+        "import torch.nn as nn\n",
+        "import torch.optim as optim\n",
+        "from torch.optim import lr_scheduler\n",
+        "import torch.backends.cudnn as cudnn\n",
+        "import numpy as np\n",
+        "import torchvision\n",
+        "from torchvision import datasets, models, transforms\n",
+        "import matplotlib.pyplot as plt\n",
+        "import time\n",
+        "import os\n",
+        "import copy\n",
+        "\n",
+        "cudnn.benchmark = True\n",
+        "plt.ion()   # interactive mode"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "iehYC9-cW2lA"
+      },
+      "source": [
+        "## Load Data\n",
+        "\n",
+        "We will use torchvision and torch.utils.data packages for loading the\n",
+        "data.\n",
+        "\n",
+        "The problem we're going to solve today is to train a model to classify\n",
+        "**ants** and **bees**. We have about 120 training images each for ants and bees.\n",
+        "There are 75 validation images for each class. Usually, this is a very\n",
+        "small dataset to generalize upon, if trained from scratch. Since we\n",
+        "are using transfer learning, we should be able to generalize reasonably\n",
+        "well.\n",
+        "\n",
+        "This dataset is a very small subset of imagenet.\n",
+        "\n",
+        ".. Note ::\n",
+        "   Download the data from\n",
+        "   [here](https://download.pytorch.org/tutorial/hymenoptera_data.zip)\n",
+        "   and extract it to the current directory.\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 15,
+      "metadata": {
+        "id": "7UvqjeCdW2lA"
+      },
+      "outputs": [],
+      "source": [
+        "# Data augmentation and normalization for training\n",
+        "# Just normalization for validation\n",
+        "data_transforms = {\n",
+        "    'train': transforms.Compose([\n",
+        "        transforms.RandomResizedCrop(224),\n",
+        "        transforms.RandomHorizontalFlip(),\n",
+        "        transforms.ToTensor(),\n",
+        "        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n",
+        "    ]),\n",
+        "    'val': transforms.Compose([\n",
+        "        transforms.Resize(256),\n",
+        "        transforms.CenterCrop(224),\n",
+        "        transforms.ToTensor(),\n",
+        "        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n",
+        "    ]),\n",
+        "}\n",
+        "\n",
+        "data_dir = '/content/gdrive/MyDrive/Colab Notebooks/data/10 Classes Brain Tumor MRI Images'\n",
+        "image_datasets = {x: datasets.ImageFolder(os.path.join(data_dir, x),\n",
+        "                                          data_transforms[x])\n",
+        "                  for x in ['train', 'val']}\n",
+        "dataloaders = {x: torch.utils.data.DataLoader(image_datasets[x], batch_size=9,\n",
+        "                                             shuffle=True, num_workers=4)\n",
+        "              for x in ['train', 'val']}\n",
+        "dataset_sizes = {x: len(image_datasets[x]) for x in ['train', 'val']}\n",
+        "class_names = image_datasets['train'].classes\n",
+        "\n",
+        "device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "MFDw_v0wW2lA"
+      },
+      "source": [
+        "### Visualize a few images\n",
+        "Let's visualize a few training images so as to understand the data\n",
+        "augmentations.\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 16,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 159
+        },
+        "id": "tceMTgC6W2lB",
+        "outputId": "a42faf48-df19-4f28-a970-93433925496b"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ],
+            "image/png": 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SArPZjGAwCAB47rnn+HuY2+3GueeeO2xKcV1dHebOnQuPx8PfeW+66SZ+PXeOq6ysxKpVq/Dee+9xm8S5ScbRjsXPf/5zpNPpIVZiuWhtbcWf/vQnHHbYYcNaqFx66aWYM2cOHn/8cbS2to56LI/Hg4kTJ2L9+vXDvr61a4dYLIYXX3wR8+bNw9y5cxGLxfDSSy+N2pbtAb1ejwMPPHDI9lNPPRUAdsjYy3X87r+O3xXiSK7jvz/reLfbjSlTpgzZviPiabsTl0uWLMGcOXNQWFiIefPmIRQK4eWXX87aZ9WqVTjhhBOQSCRw++23495778VJJ52EDz/8EMBg+tbtt98OALjwwguxePFiLF68GIcccggfw+fz4dhjj8Vee+2FRYsWYc6cOYjFYjj00EOxePFi/N///R/uueceOBwOLFiwAPfff39WG374wx/yl/67774bN9xwA4xGIz755JNhr+uQQw7BFVdcAWDww5raRHLahQsX4tJLL0VxcTHuvfdenH766Xjsscdw1FFHDfFu6evrwwknnID99tsPv/nNb2AwGDBv3jwsW7YM8+bNw3HHHYdf//rXiEQiOOOMMxAKhfi9K1aswEcffYR58+bhgQcewMUXX4y33noLhx56KKLR6NYM2S4Js9mMk08+Gc888wxv++qrr7Bq1aoRF3K/+tWvcP7552PcuHH43e9+hyuvvBJvvfUWDjnkkCEfPH19fTjmmGMwbdo03HvvvZg4cSKuv/76EX1tRKTTaRx99NHIz8/Hb3/7W8yePRv33nsv/vCHP/A+mUwGJ554Ip555hnMnz8fv/rVr9DR0YH58+eP6fp/9KMf4ZZbbsHee++N++67D7Nnz8Zdd92FefPmDdm3oaEB55xzDk488UTcdddd6Ovrw4knnoglS5bgqquuwrnnnovbbrsN69evx9y5c7MWtv/617/Q2NiICy64AA8++CDmzZuHv/71rzjuuOOGkFq7MyorK3HAAQdkxdNrr72GQCAwbJ8Cg2kZ1157LWbNmoX7778fF1xwAZYsWYKjjz56yD3d0NCAM844A0ceeSTuvfde5OXlYcGCBVi1atVm2zaWWIxEIjjssMPw5ptv4oorrsBNN92Ejz76CNdff/1mj68oCk466STcd999OOaYY/C73/0OEyZMwLXXXouf/exnQ/b/97//jauvvhrz58/HwoULsWbNGpxwwgn4/e9/jwceeACXXHIJrr32Wnz88cf4wQ9+kPXe5557DtFoFD/5yU/w4IMP4uijj8aDDz6I888/f7Pt/K7o7OwEgKzU8u2FQw45BKWlpVmEwLJly2C1WnH88ccP2T+TyeCkk07Cb3/7W5x44ol48MEHccopp+C+++7DWWedNWT/Dz74AJdccgnmzZuH3/zmN4jH4zj99NPH9EVkLLHY1taGOXPmYNWqVbjxxhtx1VVXYcmSJUM+J4fDlnzOAoPfCR5++GFcfvnluPrqq/Hee+9h7ty5uPnmm7F8+XJcf/31uPDCC/Hyyy/jmmuuyXrvk08+CavVip/97Ge4//77MWPGDNxyyy27XUrO5nDaaadBpVJlWQ0sXboUEydOxN577z1k/2g0itmzZ+Ppp5/G+eefjwceeACzZs3CjTfeOOw9vXTpUtxzzz246KKL8Mtf/hJNTU047bTThvWVy8VYYvGLL77AMcccA5/Ph9tuuw0//OEPcfvtt+Pvf//7Zo/f1dWFAw88kNOOfvWrXyEej+Okk07Ciy++OGT/u+66C6+//jpuuOEG/OAHP8ALL7yAiy++GD/4wQ+wbt06LFy4EKeddhqefPJJ3H333VnvfeSRR1BRUYGf//znuPfee1FWVoZLLrkEv//97zfbzu+Kzs7OHTI3/ec//0FDQwPOPvts6PV6nHbaaViyZMmQ/S6++GI88sgjOP300/Hwww/jmmuugclk4gXITTfdhL322ot97hcvXjzE7/KOO+7AK6+8gmuuuQZ33nkn9Ho9nnzySV6U3nXXXfjxj3+MF154AQcddFDW97CVK1div/32w9tvv40f//jHuP/++3HKKacMWS+IWLRoEUpLSzFx4kRuExGdMo52PKqqqnD++efjj3/8I9rb20fc77XXXkM6nR71e8D555+PVCo17EMREalUCq2trcjLyxv29a1ZOwDAP/7xD4TDYcybNw+FhYU49NBDh71vdhZ25PcbuY7//q7jd2QcyXX8938dv0PiaUvkmaOlig+Hrq4uRavVKn/84x9524EHHqicfPLJWfvdd999m5XajyaBnj17tgJAefTRR7O2L1q0SAGgPP3007wtmUwqBxxwgGK1WpVgMKgoiqK8/fbbCgDliiuuGHJsShdTlEH5s5gyNpKMtru7W9Hr9cpRRx2VlSpD6Q9//vOfh7R96dKlvK2urk4BoKjVauWTTz7h7a+//vqQPqD0bREff/yxAkD5y1/+MuS1kbAlEv7NpdltS5DE+LnnnlP++c9/KiqVSmlpaVEURVGuvfZapbq6WlGUoXLjpqYmRaPRKL/61a+yjvf1118rWq02azuNgdhfiURCKSwsVE4//XTeRvJ5sY/mz5+vAFBuv/32rPNMnz5dmTFjBv/9/PPPKwCURYsW8bZ0Oq0cdthhQ45JqSeEL7/8UgGg/OhHP8o6xzXXXKMAUN5++23eVlFRoQBQPvroI95GcWMymZTm5mbe/thjjw2J3+Hi6ZlnnlEAKO+///6Q10bClqRfbEn62XcFpTStWLFCeeihhxSbzcbXfOaZZypz5sxRFGVoStK///1vBYCyZMmSrOMtX758yHYaA7G/uru7FYPBoFx99dW8jWJb7KOxxuK9996rAFD+/ve/87ZYLKZMnDhxyDFz5+2///3vCgDll7/8Zda1nHHGGYpKpVIaGhp4GwDFYDBkSfwpbgoLC3kOVRRFufHGG4ekAwwXT3fddZeiUqmyYnFzGC1VfDj4fD7F6/UqBx988JjPsTUQ08SuueYapba2ll/bd999lQsuuEBRFGVIqvjixYsVtVqt/Pvf/8463qOPPqoAyErpAaDo9fqscfnqq6+GpNlRbIt9NNZYvPzyyxWVSqV88cUXvM3n8ykul2vIMWfPnp2VhjjWz1maPz0ej9Lf38/7UtxMmzYty7rh7LPPVvR6vRKPx3nbcPF00UUXKWazOWu/zWFLPsNGSxXf1qBUcUUZvB8PP/xwRVEGPysKCwuV2267jftRTBW/4447FIvFoqxbty7reDfccIOi0Wj4M5Pem5+fr/j9ft7vpZdeUgAoL7/8Mm/L/RxSlLHH4oknnqiYzeaslNH6+npFq9UOOWbu96orr7xSAZB1b4RCIaWqqkqprKzk71Q0f06dOpVtRxRlMG5UKpVy7LHHZp3ngAMOGPI5M1w8HX300fy9YqzY0s+w999/X1GpVMovfvGLLTrP1uCyyy5TysrK+LvsG2+8oQDIutcVRVEcDsdm7SxGuk4ai+rq6qw+TSaTitfrVaZOnarEYjHe/s9//lMBoNxyyy287ZBDDlFsNtuQzwXxO/hwc9xIqeIyjnYcxO9V69evV7RabdZ6Kvf7OY1NbgyK+PzzzxUAys9+9jPeVlFRoRx11FFKT0+P0tPTo3z99dfKeeedN6wVy9auHQgnnHBCVgr+H/7wB0Wr1Srd3d1Z+23vVPGRcMQRRyh2u13p6+vb6vOOBXId//1cxxN2RBzJdfz3fx2vKIP9PXnyZKWqqmqIDdtI2OVSxf/6179CrVbj9NNP521nn302Xnvttaz0SqfTCWAwDWxri0gYDAZccMEFWdteffVVFBYW4uyzz+ZtOp0OV1xxBcLhMN577z0AwPPPPw+VSoVbb711yHG3Jl3szTffRDKZxJVXXpllAvzjH/8Ydrt9SKqK1WrNYtwnTJgAp9OJSZMmYb/99uPt9LuY+iimbw8MDMDn86G2thZOp5NTfL4vOOqoo+ByufDXv/4ViqLgr3/9a9bYinjhhReQyWQwd+5c9Pb28k9hYSHGjRuHd955J2t/q9WaZRis1+sxc+bMMaeZXnzxxVl/H3zwwVnvXb58OXQ6XZZ5uFqtxqWXXrrZY7/66qsAMEQ5QwblufE0efJkHHDAAfw3xc1hhx2G8vLyIdtHiqd4PI7e3l7sv//+APC9iydK//nnP/+JUCiEf/7znyM+9XvuuefgcDhw5JFHZsUTpW/lxtPkyZOzzLE9Hg8mTJgwpngaSywuX74cJSUlOOmkk3ib0Wgc1pw+F6+++io0Gg0/aSZcffXVUBRlyNPJww8/PCvVnOLm9NNPh81mG7J9pHiKRCLo7e3FgQceCEVRhqQ3bCtkMhn83//9H/r7+8dUJGBb4ZxzzkFDQwNWrFjB/48WT5MmTcLEiROz4umwww4DgCHxdMQRR3ChNGDQHNtut48pnsYSi8uXL8cBBxyQZZjvcrnwf//3f5s9/lg/ZwlnnnkmHA4H/01xc+6550Kr1WZtTyaTWSmlYjyFQiH09vbi4IMPRjQazUrT/z7gnHPOwbvvvsuWA52dnaPG08EHH4y8vLyseDriiCOQTqfx/vvvZ+1/1llnZSmUKD7GEk+bi8V0Oo0333wTp5xySlbhtdra2jEVt3j11Vcxc+bMrMJpVqsVF154IZqamrB69eqs/c8///ws25H99tsPiqIMUX/vt99+2LhxI1KpFG8T4ykQCKC3txezZ89GY2MjAoHAZtu6Neju7sY555yDqqqqIcW8tjVSqRSWLVuGs846i7/LUkpzrnrM6XTiP//5z6hKuc1h/vz5WX362Wefobu7G5dccklW4YXjjz8eEydO5O8uPT09eP/99/GDH/wg6zsKsHXfwQEZRzsL1dXVOO+88/CHP/xhxMJmpDYTvz/kgl4juwHCG2+8AY/HA4/Hgz322AOLFy/GBRdcgHvuuWfEY23J2gEYVP69/vrrWfucfvrpbCmws3HnnXfizTffxK9//WteP28vyHX893cdvyPjiCDX8d/fdfxll12G1atX46GHHsr6Lr+tsV2Jy6effhozZ86Ez+dDQ0MDGhoaMH36dCSTySyPg7POOguzZs3Cj370IxQUFGDevHl49tlnt2jyKykpGVKdt7m5GePGjRtSsZJk4M3NzQCA9evXo7i4GC6Xa2svdch5gcGJS4Rer0d1dTW/TigtLR0ysTocDpSVlQ3ZBiDrwyIWi+GWW25hXyu32w2Px4P+/v7t9oVpZ0Gn0+HMM8/E0qVL8f7772Pjxo0jLuTq6+uhKArGjRvHX3LoZ82aNeju7s7af7gxyMvLG+JfOBzIS2W09zY3N6OoqAhmszlrv9ra2s0ev7m5GWq1esi+hYWFcDqdQ+Ip94s/xc1Y4snv9+OnP/0pe5p6PB5UVVUBwPcunjweD4444ggsXboUL7zwAtLpNM4444xh962vr0cgEIDX6x0ST+FweEg85Y4BMPZ4GkssNjc3o6amZsh+Y42n4uLiIYuG3HmR8F3iqaWlBQsWLIDL5WLfGKomt73i6fLLL8fy5cvx+OOPY9q0advlHMNh+vTpmDhxIpYuXYolS5agsLCQichc1NfXY9WqVUNiafz48QCwTeNpLO9tbm4eNnbGGk9j+ZwdqT1bEk+rVq3CqaeeCofDAbvdDo/Hw19Uv2/z03HHHQebzYZly5ZhyZIl2HfffUccj/r6eixfvnxIPFHF0c3FE5GY2yKeuru7EYvFvlM85X53ArZNPGUymaw4+fDDD3HEEUfAYrHA6XTC4/Gwr9r2iKdIJIITTjgBoVAIL7300hDPwm2NN954Az09PZg5cyZ/B9+wYQPmzJmDZ555Jus79m9+8xt88803KCsrw8yZM7Fw4cIt9gem7wqEkb4LA8DEiRP5dTrP1KlTt+h8o0HG0c7DzTffjFQqNaLXJX33ENNlczESubnffvvhX//6F5YvX47f/va3cDqd6OvrG7L+E7Elawdg0OZlYGAA06dP5/vG7/djv/322+np4suWLcPNN9+MH/7wh/jJT36y3c8n1/Hfz3X8jo4jglzHfz/X8ffccw/++Mc/4o477sBxxx23Xc5B2G6UaH19PZu9jxs3bsjrS5YswYUXXghgkB1+//338c477+CVV17B8uXLsWzZMhx22GF44403RjRsFbEzC8d8V4x0fSNtVwSPgssvvxxPPPEErrzyShxwwAFwOBxQqVSYN2/eVj/12pVxzjnn4NFHH8XChQsxbdo0TJ48edj9MpkMVCoVXnvttWH7MfeL3lj6eiSMJT63Bcb61PC7xNPcuXPx0Ucf4dprr8Vee+0Fq9WKTCaDY4455nsbTz/+8Y/R2dmJY489dsSnjplMZliVCiH3A297xNNY3rs9sLXxlE6nceSRR8Lv9+P666/HxIkTYbFY0NbWhgULFmyXeLrtttvw8MMP49e//jXOO++8bX78zeGcc87BI488ApvNhrPOOmvIl21CJpPBHnvsgd/97nfDvp775UTG02DxmdmzZ8Nut+P2229HTU0NjEYjPv/8c1x//fXfu/nJYDDgtNNOw1NPPYXGxkYsXLhwxH0zmQyOPPLIEZVXRIgTZDwNLnQPP/xwTJw4Eb/73e9QVlYGvV6PV199Fffdd982j6dkMonTTjsNK1euxOuvv75NSbqRQJ9Xc+fOHfb19957D3PmzOF9Dj74YLz44ot44403cM899+Duu+/GCy+8MCalLPC/+T38fyGOthTV1dU499xz8Yc//GFY/2EinVauXJml8hexcuVKABjyHd/tdvMDmaOPPhoTJ07ECSecgPvvv39YP1/CWNcOwKb7ZtasWcO+3tjYiOrq6hHfv73wr3/9C+effz6OP/54PProo9v9fHIdP3bsTuv4HR1HuZDr+M1jd1rHP/nkk7j++utx8cUX4+abb97mx8/FdiMulyxZAp1Oh8WLFw/p6A8++AAPPPAAWlpamFVWq9U4/PDDcfjhh+N3v/sd7rzzTtx000145513cMQRR2yV1LuiogIrV65EJpPJWkBSShlVoq2pqcHrr78Ov9+/RU9rRmoTHXft2rVZH27JZBIbNmzgD91tgb/97W+YP38+7r33Xt4Wj8eHmNZ+X3DQQQehvLwc77777hCDdBE1NTVQFAVVVVVDFm07AxUVFXjnnXcQjUazntY0NDSM6b2ZTAb19fX8hQ8YNJ/v7+8fUlF5a9HX14e33noLt912G2655RbeXl9fv02Ovyvi1FNPxUUXXYRPPvkEy5YtG3G/mpoavPnmm5g1a9Yu8eWqoqICq1evhqIoWfPQWOPpzTffRCgUylIz5M6L3xVff/011q1bh6eeeirLhF+s5L4t8fvf/x4LFy7ElVdeOaYiRdsD55xzDm655RZ0dHRg8eLFI+5XU1ODr776CocffvhOrV5NqKioGDZ2xhpPY/mc/a5499134fP58MILL2QZ+m/YsGGbHH9XxDnnnIM///nPUKvVIxYNAwbjKRwOb9PvFlsLr9cLo9H4neJp7dq1Q7Zv63h6+eWXkUgk8I9//CNL3ZCbfrYtkMlkcP755+Ott97Cs88+y6rz7YlIJIKXXnoJZ5111rCZBFdccQUX3SAUFRXhkksuwSWXXILu7m7svffe+NWvfsXE5ZbOVeJ34Vz1+dq1a/l1+p78zTffbNHxR2uTjKOdi5tvvhlPP/30sN/Tjz32WGg0GixevHjEAj1/+ctfoNVqccwxx4x6nuOPPx6zZ8/GnXfeiYsuuggWi2XY/ca6dtiwYQM++ugjXHbZZUP6N5PJ4LzzzsPSpUt3yAJdxH/+8x+ceuqp2GefffDss89u11RMglzHf//W8TsjjnIh1/Hfn3X8Sy+9hB/96Ec47bTTdkgxOmA7poovWbIEBx98MH9pEn+uvfZaAODKUn6/f8j76SkclYmnD6MtuZGPO+44dHZ2ZhESqVQKDz74IKxWK38onX766VAUBbfddtuQY4zG1I/UpiOOOAJ6vR4PPPBA1vv/9Kc/IRAIDFtldmuh0WiGtPHBBx9EOp3eZufYlaBSqfDAAw/g1ltvHVVRddppp0Gj0eC2224b0j+KooypGu+2BFWe/uMf/8jbMpnMmG50kl3nVvAktda2iif6YpLbX7nn/T7BarXikUcewcKFC3HiiSeOuN/cuXORTqdxxx13DHktlUrt8AcFRx99NNra2vCPf/yDt8Xj8az4GgnHHXcc0uk0Hnrooazt9913H1Qq1ZjVNZvDcPGkKMqYKlVvKZYtW4YrrrgC//d//zeiinFHoKamBosWLcJdd92FmTNnjrjf3Llz0dbWNux4xWIxRCKR7dnMITj66KPx8ccf48svv+Rtfr9/TGlxY/2c/a4YLp6SySQefvjhbXL8XRFz5szBHXfcgYceegiFhYUj7jd37lx8/PHHeP3114e81t/fn+XHt72h0WhwxBFH4O9//3uWX2JDQ8OYqnsed9xx+PTTT/Hxxx/ztkgkgj/84Q+orKwcVSm1pe0EsuMpEAjgiSee2CbHF3H55Zdj2bJlePjhh3Haaadt8+MPhxdffBGRSASXXnrpkO/gZ5xxBk444QQ8//zzSCQSSKfTQ1LIvF4viouL+Ts4MPidd0tSzfbZZx94vV48+uijWcd57bXXsGbNGv7u4vF4cMghh+DPf/4zWlpaso6xObWMxWIZ9vNXxtHORU1NDc4991w89thjXGmWUFZWhgsuuABvvvkmHnnkkSHvffTRR/H222/jhz/8IUpLSzd7ruuvvx4+n2/U7z9jXTvQZ95111035J6ZO3cuZs+evcPTxeleqaysxD//+c8d9vBcruO/X+v4nRVHuZDr+E3Yndfx77//PubNm4dDDjkES5YsGTHDbFtju1Dt//nPf9DQ0IDLLrts2NdLSkqw9957Y8mSJbj++utx++234/3338fxxx+PiooKdHd34+GHH0ZpaSkba9fU1MDpdOLRRx+FzWaDxWLBfvvtN8RTR8SFF16Ixx57DAsWLMB///tfVFZW4m9/+xs+/PBDLFq0iNVGc+bMwXnnnYcHHngA9fX1LKf997//jTlz5ox4HXvttRc0Gg3uvvtuBAIBGAwGNj6/8cYbcdttt+GYY47BSSedhLVr1+Lhhx/Gvvvum2Ue+11xwgknYPHixXA4HJg8eTI+/vhjvPnmm8jPz99m5wAG/RlIQfTZZ58BAH75y18CGHySMNrk09TUhKqqKsyfPx9PPvnkd27LySefjJNPPnnUfWpqavDLX/4SN954I5qamnDKKafAZrNhw4YNePHFF3HhhRfimmuu+c5tGStOOeUUzJw5E1dffTUaGhowceJE/OMf/+AP+9GeRE6bNg3z58/HH/7wB06X/PTTT/HUU0/hlFNOyVJMfBfY7XYccsgh+M1vfoOBgQGUlJTgjTfe2C6KppUrVzLp1tDQgEAgwPE0bdq0UUnEd999F3PmzMGtt946avrkWDF//vzN7jN79mxcdNFFuOuuu/Dll1/iqKOOgk6nQ319PZ577jncf//9I/pjbg9cdNFFeOihh3D22Wfjpz/9KYqKirBkyRIugDBaPJ144omYM2cObrrpJjQ1NWHatGl444038NJLL+HKK6/MKrzxXTBx4kTU1NTgmmuuQVtbG+x2O55//vkx+c1sCT799FOcf/75yM/Px+GHHz5kUXHggQeOmtb15JNP4oILLsATTzyBBQsWfOf2/PSnP93sPueddx6effZZXHzxxXjnnXcwa9YspNNp1NXV4dlnn8Xrr7+OffbZ5zu3Zay47rrr8PTTT+PII4/E5ZdfDovFgscffxzl5eXw+/2jxtNYP2e/Kw488EDk5eVh/vz5uOKKK6BSqbB48eLtkqL88ssv46uvvgIwaJa/cuVKnp9OOukk7LnnniO+d+HChbjtttvwzjvv4NBDD/1O7VCr1WNS9lx77bX4xz/+gRNOOAELFizAjBkzEIlE8PXXX+Nvf/sbmpqa4Ha7v1NbtgQLFy7EG2+8gVmzZuEnP/kJPyiZOnVqFjk+HG644QY888wzOPbYY3HFFVfA5XLhqaeewoYNG/D8889vsy/HRx11FPR6PU488URcdNFFCIfD+OMf/wiv1ztiUZGtwaJFi/Dwww/jgAMOgNlsxtNPP531+qmnnjqiSgwAFixYwNcvFknbHJYsWYL8/HwceOCBw75+0kkn4Y9//CNeeeUVHHbYYSgtLcUZZ5yBadOmwWq14s0338SKFSuyVEAzZszAsmXL8LOf/Qz77rsvrFbrqJ/VOp0Od999Ny644ALMnj0bZ599Nrq6unD//fejsrISV111Fe/7wAMP4KCDDsLee++NCy+8EFVVVWhqasIrr7wyaszMmDEDjzzyCH75y1+itrYWXq8Xhx12mIyjHGxtHH0X3HTTTVi8eDHWrl2LKVOmZL123333oa6uDpdccgmWL1/OysrXX38dL730EmbPnp0Ve6Ph2GOPxdSpU/G73/0Ol156aVaRJRFjWTssWbIEe+211xC7FsJJJ52Eyy+/HJ9//jn23ntv3v673/1uiPedWq1mr9OtRSgUwtFHH42+vj5ce+21Q4p41NTUZBXxyMXWrr/kOv77tY7fWXE0EuQ6fvdexzc3N+Okk06CSqXCGWeckeV3CwwWbRzte/J3wXYhLmnhONoXmhNPPBELFy7EypUrcdJJJ6GpqQl//vOf0dvbC7fbjdmzZ+O2225j41GdToennnoKN954Iy6++GKkUik88cQTo054JpMJ7777Lm644QY89dRTCAaDmDBhwrAL1CeeeAJ77rkn/vSnP+Haa6+Fw+HAPvvsM+KXPmDQVPXRRx/FXXfdhR/+8IdIp9N455134PV6sXDhQng8Hjz00EO46qqr4HK5cOGFF+LOO+8c8UN1a3D//fdDo9FgyZIliMfjmDVrFt58800cffTR2+wcwGD6xC9+8YusbfT37NmzRyUuw+EwgME0pB2JG264AePHj8d9993HT+HKyspw1FFHZVVj3hHQaDR45ZVX8NOf/hRPPfUU1Go1Tj31VNx6662YNWtWVsXN4fD444+juroaTz75JF588UUUFhbixhtvHLaC3nfB0qVLcfnll+P3v/89FEXBUUcdhddeey2rOuy2wOeffz5iPM2fP3/UuWNnxdOjjz6KGTNm4LHHHsPPf/5zaLVaVFZW4txzzx3RC2l7wWq14u2338bll1+O+++/H1arFeeffz4OPPBAnH766aPGk1qtxj/+8Q/ccsstWLZsGZ544glUVlbinnvu4Qp32wI6nQ4vv/wyrrjiCtx1110wGo049dRTcdlll23TojmrV69GMplET0/PkAqwwODcPhpxuTPiSa1W4+9//zvuu+8+/OUvf8GLL74Is9mM6upq/PSnP93haTFlZWV45513cMUVV+DOO++Ex+PBpZdeCovFgiuuuGLUeNqSz9nvgvz8fPzzn//E1VdfjZtvvhl5eXk499xzcfjhh2/zz7vnn38eTz31FP/9xRdf4IsvvgAwaAA/2heycDgMlUo1qkJyW8NsNuO9997DnXfeieeeew5/+ctfYLfbMX78+KzvUTsKM2bMwGuvvYZrrrkGv/jFL1BWVobbb78da9as2Wz194KCAnz00Ue4/vrr8eCDDyIej2PPPffEyy+/vE1VLhMmTMDf/vY33HzzzbjmmmtQWFiIn/zkJ/B4PMPOI1sLIt0+/vjjLPUfYcOGDaMSTuFwGCaTaYuqvnZ3d+PNN9/E2WefPaIn1uGHH84E2AknnIBLLrkEb7zxBldyra2txcMPP5xVuOGSSy7Bl19+iSeeeAL33XcfKioqRv2sBgYJM7PZjF//+te4/vrrYbFYcOqpp+Luu+/OuqZp06bhk08+wS9+8Qs88sgjiMfjqKioGNGfk3DLLbegubkZv/nNbxAKhTB79mwcdthhMo5ysDVx9F1RW1uLc889N2suJVitVrz11lt4+OGH8fTTT+Paa6+FoiiYOHEiFi1ahEsuuWSL1krXXHMNFixYgCVLlmz1587nn3+Ourq6Id9NRZx44om4/PLL8fTTT2cRl3fdddeQfTUazXcmLn0+HzZu3AgAw/qFzp8/f1TCaWu/38h1/PdrHb+z4ui7Qq7jtxw7Yh2/YcMGzr4Yrqr6rbfeut2IS5WyBXKFBQsW4O2338bnn38OrVa7Qz8AJXZfPPzww7juuuuwfv16FBQU7Ozm7FL4+9//jlNPPRUffPDBDie/dldcd911eOaZZ9DQ0ACDwbCzm7NLYdGiRbjqqqvQ2tqKkpKSnd2c3QJz585FU1MTPv30053dlF0OV155JR577DGEw+EdZl6+u2PmzJmoqKgY8gRaYlCxsGrVqu+1b/K2RkFBAc4//3zcc889O7spErsxZBz9b0KuvyS2BWQcjQy5jt9yhEIhJBIJnHzyyQgEAlvkb73FuRIbN26Ex+Nh6beExOZASp7/9ckuFotl/Z1Op/Hggw/CbrdnPbmVGB3vvPMOfvGLX/zPk5a58RSPx/HYY49h3LhxkrQcIxRFwbvvvstpwP/LyI0nn8+HxYsX46CDDpKk5RgRDAbx1Vdf4fbbb9/ZTdnpyI2n+vp6vPrqq985ff5/CatWrUIsFttpxcYkvh+QcfS/C7n+ktgWkHE0CLmO3zY477zz4PF48NFHH23xe7dIcbl69Wo2W7dardh///23+IQSEv+r+NGPfoRYLIYDDjgAiUQCL7zwAj766CPceeeduPHGG3d28yR2Mxx77LEoLy/HXnvthUAggKeffhqrVq3CkiVLcM455+zs5knsZthrr71w6KGHYtKkSejq6sKf/vQntLe346233sqq4i0hMRYUFRVhwYIFqK6uRnNzMx555BEkEgl88cUXGDdu3M5unoSExGYQDoc5RXQkeDwe+WBLQkLifwJyHb9tsHLlSnR3dwPYcj5xi4hLCQmJrcfSpUtx7733oqGhAfF4HLW1tfjJT34yomm0hMRoWLRoER5//HE0NTUhnU5j8uTJuO6663DWWWft7KZJ7Ib4+c9/jr/97W9obW2FSqXC3nvvjVtvvRVHHHHEzm6axG6ICy64AO+88w46OzthMBhwwAEH4M4775SqBAmJ3QRUaGw07MhiPxISEhI7E3Idv/MhiUsJCQkJia3C73//e9xzzz3o7OzEtGnT8OCDD2LmzJk7u1kSEhISEhIS3wGNjY1obGwcdZ+DDjpos0UpJCQkJCQktgUkcSkhISEhscVYtmwZzj//fDz66KPYb7/9sGjRIjz33HNYu3YtvF7vzm6ehISEhISEhISEhISExPcAkriUkJCQkNhi7Lfffth3333x0EMPAQAymQzKyspw+eWX44YbbtjJrZOQkJCQkJCQkJCQkJD4PkC7sxsgISEhIbF7IZlM4r///W+WGbVarcYRRxyBjz/+eMj+iUQCiUSC/85kMvD7/cjPz4dKpdohbZaQkJCQkJD4blAUBaFQCMXFxVCr1Tu7ORISEhIS/yOQxKWEhISExBaht7cX6XQaBQUFWdsLCgpQV1c3ZP+77rprsyb/EhISEhISErsHNm7ciNLS0p3dDAkJCQmJ/xFI4lJCQkJCYrvixhtvxM9+9jP+OxAIoLy8HGq1eljFpaIoW6TEVKlUEF1PVCoVLBYL9tlnH0yZMgUGgwEfffQROjs7YTQaodPp4Ha7+XeTyQS1Wo14PI5QKIRIJAKr1YqCggLE43H09vZiYGAAVqsVNpsNFosFAJBOp/l86XQafr8fHR0dCAaDcDgcSKfTiEajCAaDmD59Ovbfb1+8+s+X8J/PvtrarhwRarUaarUaiqJwu4bbx2azoby8HJMnT0ZTUxP8fj9cLhdsNhtWrVqFrq4uZDKZbdo2tysPJcVerF7bmDVW9Dv9b7VaMW/ePEybNg2LFi1Cf38/EokEDAYDEokE5s2bh2g0inA4jEwmg1QqhXQ6zcfQ6/V8LEVRkMlkMDAwkLWPGCfUX4SBgQEAg4pgnU4Hu90Ou90OrVaLoqIiBAIB+P1+9PX1IZ1OQ61WI51OI5PJQKvVcsymUikAgMVkgEqloLPbz4R+bW0tLBYLnE4nIpEIIpEI+vv7YTQaWb0Ui8Wg0WjgdDoxMDAAtVoNt9sNk8mEeDwORVFgMBig0WgAABqNBmq1GlqtFlqtFul0GiqVCrFYjK8vlUohEAhwzNO5tFotNBoNVCoVt5+uS61Ww2AwcExptVrudwBwOByIRCJobW1Fd3c3j0tJkRctGzeiZWM7H7e8vBwWiwXr169Hfn4+MpkMIpEIFEXB+PHjUVBQgGQyCYfDAafTyePgdDqhUqkwMDAAnU4HnU7HfS62eWBgAD09Pfy/3+9HRUUFdDodEokEUqkUFEWBRqPh+7KlpQV9fX3Q6/WwWCzo6+tDaWkpHA4H/vvf/3I8iLEqIneeqq0uR38giM6u3iH3gNjWbYHh2rO1yL0O8f6kv0c717SpE1A7fhJWfr0KiUSC4zCVSqGkpATTpk3DqlWrUFJSgu7ubiSTSZhMJmi1WsRiMajVakyfPh1OpxMdHR1IJpPIZDLo7+/n+623txfRaBQOhwNFRUUoKCiA3W7nwjDpdBqRSAQ9PT28L7U5mUyy6p/mRnqN7luNRoNMJsM/dM0qlQo6nY7vNbVazbE0obYCX65cjVA4sk3GYSygeZ7uwZ2Bg/bfGx988jlsNttOa4OEhISExP8eJHEpISEhIbFFcLvd0Gg06Orqytre1dWFwsLCIfsbDAYYDIYh20dazG/NAl+lHnyPCiqo1Wp4PB5eNH/++edoaWlBcXExYrEYnE4nrFYrzGYz9Ho9EzJ6vR5msxnhcJhJm3g8DgAwmUz8Q2QIkUh6vZ5JWEVRYLFYYLfbkUqleEG8evVqjB9XA51OC2DbEBgq1SaS1mq1AgCi0Sji8TiSyeS3i3MVqDt1Oh0KCgowffp0JJNJtLW1Qa1WIxaLYdy4cWhtbYXP58PAwAC2pfu1Wq2CRrOJ2BP/J/JQrVajuLgYBx54IBoaGhAOh3mfcDiMU045BRUVFfjmm2+yCEMi2BRFYTuCTCbDxByREnQu2kYEhVar5W1E+tH7ibAwGo3o7++H2WzmYxBxRvvlni+TycBgNEAN5dv+VGA0Gjl+6D2pVAparZZjMR6Pw+/3Ix6Pw+FwQK/XAxgkJ/V6PZPK9B7qu3g8jnQ6zbGoKApMJhMTn0ajEQMDA/x+2kbHom2pVIrJGp1OBwBZx02n0zCbzchkMohGo1i7di1aW1v5XlCr1YhEwlAL97bT6URhYSHWrFkDp9MJtVqNaDSKTCaDqqoqFBYWIpPJwGKxoLi4GDqdDuFwGHa7HU6nE4qiIBaLwWQy8bil02keV+p3j8fDr5lMJhQXF3OfptNpdHZ2MglutVpRU1ODjRs3orOzkx9mtLe3o6CgAOPGjcPatWtHJfFz45kI5KHxrx4xpXa4hzTDEYkiiTjcfTQasSiS9sO9ZyzvH+lhCPBtbOp0sFqtSKVSfL00PjqdDg6HAzqdDi6XC4lEguf+RCIBvV6Pzz//HOPHj4fRaIRKpUIqlYJOp4PBYODjmUwm5OXlwe12w+12w+l0wmg0QqvVYmBggB9yaDQa+P1+pFIpnoONRiNCoRDi8TjHuEj208OnVCrFY05tpGsQ7610Og3Tt23dETAYDLBardyvmUwGwWCQP592JLTaQRJX2rxISEhISOxISHMSCQkJCYktgl6vx4wZM/DWW2/xtkwmg7feegsHHHDADmnDaIsmo9GI0tJSFBYWwmAw4LPPPoPFYoHRaGTFWCaTYTWZz+dDZ2cnfD4fNBoNPB4P8vPz+bqIkBAJiFQqhVgsxoQNqfuIMDKbzdDpdEgmk9BoNIjFYvjiiy9GJQDGfu2DP3q9HsXFxSgoKIBGo0E0GuVF+SYF4CZywmazobKyEkajEevXr2fSLxqNQqvVwu12CwSzwu8d7txbvmbNVsSKBAqpJWtqauByubB69eoscnHy5MmYPn061q9fn0W8ieSIqLQEBhV4AwMDTF4QIUn7iEpJ8QcYJGJoP3q/z+fj99O5SMlJSj6NRsP9rlarodVoodaoEYlEkE6nYTAYmAy1WCzQarUwGAzIy8uD0WhkIjGRSKC0tJTJTZPJxNdEfUZto/bSsUmZSK9TP0Sj0ZxxzCa/ADAZKPapqLokcl+lUsHn8+Gbb75Bc3Mz4vE43yPUPyoVWBlaXV2NlpYWJjap7+x2O8cuKfWI3HW5XLDb7dDpdLyNrkckrcW2kxLO4/Fg6tSpcDqd0H1LqNntdlRWVsLhcHDf63Q6VFRUoKCggB9WmEwm1NXVcSwC2YpDkczK7b+RbomRSEHaLr4+HJEpkpbDHXO444jvHUnVvrn2DXfeka6DHnjodDpotVpYrVaOU1L+JpNJWCwWmEwmWCwWjtv+/n6k02mEQiGOXZpP6XhGoxF6vZ4Vt0QmmkymLCW81Wrl8QUG50ir1QqHw4HCwkImUMW+ob8pJkQCmuYYintx+zZ6/rRZ2Gw2TJo0iRXYqVQKFosFe+yxB8xm845phISEhISExE6GVFxKSEhISGwxfvazn2H+/PnYZ599MHPmTCxatAiRSAQXXHDBDjl/1mJaRf8NLkSdTie8Xi+qqqqwdu1adHR0wO12w+/380LWYDBApVIhGAyyOsflcmWl4oVCISQSCSY7xbRyjUbD6Y5EUFKKo16vZ3WcyWRCOp2G1WpFe3s7XE7rVl0vEUFEJhgMBhQVFUGtViMcDrOqTCTRdDodkwZqtRpmsxl2ux3d3d3o6elh5U4ikUA0GkVpaSnWr1/PKbw5PT5sOmnWAGzxNW0ifxwOB/baay9Eo1GsX78earWayeUjjzwSTU1NCIfDTCSq1WpYLJYsIpkIMVrck7KL2krHJHWVSF7qdLqstON0Oo1EIsHH9/v9sNvtWQSoeB06nS6L2ASAdDoFFTYRNyIBrtFo4HA4uI1EUtLxrVYrjyGpgolAy1V5RqNRjmfqH1Kh0f6kwBX7gtRo9D+Rt0Qc5Z4rmUwilUqhsbERLS0tTMoPXmuaCd9MZtM5ysvLEYvF4PP54HA4mOg3m80oKytjFRsAjmEiS8UYoTg1m808fkQoDQwMZB3HYrFAr9cjnU6zIo2Ie6vVimg0iv7+fvT39yOVSqG6uhqZTAa9vb3Iy8tDf38/2tvbseeee+LDDz9EPB5nIl0c8yGqxc3E+Ujbc2OJMJJlxkhEp6iqzCXyR2vHSMhNGR8NyYEBxGIxmM1mtiMgEp+U0BT/oVAIDoeDx7GoqGgIUR2PxzmmXS4XMpkMfD4f4vE4EokEz7c0P9McrSiDCudkMslqdJqz3W43AoEAWltb0dXVhUQiwbEuxj2RoxSL1Af0Nymzd0RhGpvNhqlTp8LhcCAUCvHcrtFoUFJSglQqhZUrV26TB2ISEhISEhK7MiRxKSEhISGxxTjrrLPQ09ODW265BZ2dndhrr72wfPnyIQV7vis2t3geJAwUDP4bTNsuLCyE2+2GzWbDv//9byZpiBAixQ8RXZTKrtfr2QOPvC6TySSi0SiTS8lkkn0BiUShNGVKfyXCwGg0wmw2Ix6PDxKZ6dR39qVTFAU6nY4rspMPpKIorOAT0zVpIW80GqHRaFBXV8fecnq9HslkEmq1Gm1tbTCbzVlejcOlp4q+kFtzLbnEDJFjpaWl2HPPPdHe3o7e3l4+j91ux/Tp09HR0YF4PM4kYCKRYC9ISr8mAoMIWbIAoHZSCjj9navC1Ov1MBgMiEQinHpK155IJBAOh5mEoWshMpviho5Lrw0MJFkpScQNeSyazWZ4PB4m4SKRCAwGA7RaLfv5Ueqs6DFJhAmRc+KYAWCijUgWtVoNvV6PSCSSpcATVaMiMUPvTafTiMViiMVi3BfBYBAbN25EMpmEzWbj+4fIJCKSABXsdjvy8/Px1VdfsS8sEbh0j9J9SeMiEm+5ykYilCjOaV/6m0hMIpYSiQQTv2KKvc1m42sPhULQarWora1FY2Mj+9O2trbC6/WitrYWq1evzur30WJ6OGzuPhkpVXw4QpL+pzGlH4pXUXk6WnuGa/NwKeO55OewxwP44YzD4eCHPDSfGAwGbl80GkUoFEIymWSlYzKZxBdffAGbzQav1wun04lUKgWDwcAPf+x2OyKRCEKhEIxGI8LhMCuM6X4nP+FAIJCVIm4wGGCz2VihTnOhz+fjPsud06iPaczpHqWHDoOvaUbtl+8KrVYLu92O9vZ2tkogZbDT6UR9fT3bHoRCIfZqTafT/JBHQkJCQkLi+wJJXEpISEhIbBUuu+wyXHbZZdv1HMOlTQ6X5kj72e12eL1eVFdXY926dejs7ITT6eQFHqktKR3W6XRyWqKo3iNCT6vVsuJNr9dzCm6uvx4A9gUkxR8di46j0qqxtepEkaTJz8/nxTsp2Ih4IsJOr9czcUpkj1arRVdXF6fdEvGlUqnQ1dWV5dlJBN1wBAep7Ogat4S/zCVNVCoVDAYDJk6ciIKCArz99ttIpVKwWq2sviooKGACYmBgABs3bkRraytCoRAGBgZYiUSKSmATKSkqkSh2cgu7iAVqiNgmcpTSrMnXlI5L/SAqNem8RKYMKhQHuC+JDKTUaCJU6H1EcBM5QsSh6EVJRC/FFcWimAIvprKTUpHGi66N+kBUm1FfUXo5EcWkQKXjxWIxPh79rlJt8hIdHIvBgjzd3d2sYiNCrbi4GIWFhVnXqNPpkJeXB5vNlkVA03WJakcimyn+6L6g+9hoNPJYianvIoltNBrhdDqZbNVqtSgrK2MLhYGBAaxbtw577703WlpaEAqFhsw1YiwrirJlN8IoGO0hDSnGRbKcVLM0tmQXQeMnxsRoJKtIjm6uLTlv5HGn89NDnVQqxYR5b28vP2wg6wWLxYKenh7E43H09PSgo6MDEydOhMPhYOLQaDTyfJVKpRAMBtHZ2YlYLAaHw8FEP5GWgUAABoMBLpeLLRSoIBbNHel0mucUUtfTPAkgq0gPXQewKXV8zH0zRoi2DHTddrsdJpMJHR0d8Pl8UBSF08Xr6uqgUql4fjQYDJg5cyZmzpyJVCqFjz/+GB999BEikR1XOEhCQkJCQmJ7QhKXEhISEhK7DUZT/5A/ZUlJCWw2G1566SUmeihtkEhIAKxaIoUQbafXqBoxESO00B2OuCASigiSVCrFaY1EDOm0eqiwFSqYb60qxWro8Xg8i7QU00OpzXq9nlMyxRTrvr4+JnNEkpUWzaQCFIkhIvIonZf6aBMxuPlF/Ehpr1arFbW1tVCpVKivr2eiQq1Ww+Fw4P3330ddXR00Gg2r4JxOJ+rq6hCNRlkZKx5TVFOKBXXEdhABQeQYefORH2pXVxcTP1qtNqsAjV6v52IhZrMZgUCAiVIi6FLpNOKxGKvLVCoVotEop5yHw2FotVr2sKQYJD89AJyOTYpSimUi5ADweNM1EFEFgAl5kbxTq9WcRk5jTu0OhUIIBoNMVpLSkYhvKl5Fvp1iujspGVWqQWLQ4/GgsbERVquVx8TtdqO8vJz7XCTdnE4nPB4PVwcnpST1q1gQicaSHjLEYjFO+adrySUsSZlH12SxWOBwONDe3s6KwXHjxuGLL76ASqVCT08P+vr6MHnyZHz66afDpl7npmpvSdyL96yY2j3cwxoqxEQPKMRUeY/Hw4RvOBxmItDpdMLlciEej6Ovr29EJebmCM2xIBqNIpFIcjo/Ec8U54qisHI9EokgEAjw7xSjRLKvW7cOEyZMQH5+Pj9kGhgY4HstmUwiEokgk8mwfUE8HmeVvMViQV5eHux2O8xmM98r33zzDRoaGtgKw2AwwOl0IhKJ8MMams+oKjrFjlgEjB9ebCOimjw5NRoNxo8fz7YiHo8HWq0WHR0dQ/x06f41m838eXfUUUdhr732gkqlQmlpKTo7O7Fu3boslbiEhISEhMTuCklcSkhISEh8L2AymVBUVITKyko0NjaiubkZeXl57JVIBExuCmAgEIBer2f1G5EdsViM078pjZzIkFySgYqAJBKJLILPZrNx1WcoaQwktpS4VJi0LC0t5erhw5GWooqQ1GekIgyFQggEArxIB8CkJRFbpHAEwIt2Ut5RHwBgsmBbKI7Iw660tBR9fX2s0CMFpU6nQ09PD3vaxeNxdHd3o7q6GmVlZWhvb2efTyLb6LikABN96kTygRb/oqJPURQuHGIymdDd3Y1AIAAAWR53pNgjcoH2EdO6VQAi3xbF0Wg0TKYQCUy+k8FgkP0Xw+FwViozkYcUk9RG6gsio0QFMCkciewkQoaIQCL3yHZAp9NlVTOn9pItAqW6k1WC1+uF3+9HT08PdDodk2ZUAEitVqOwsJDjiK4rk8nA6/VmkeZEttrtdrjdbqhUKuTl5aG3txfxeJzvVbEoi0hG0vWRryGNNalexZRy6ifqW7HoChG6drsdhYWFaG9vh6IoaGxsxMyZM1FfXw+fzzfEKiF3bEaL8+EIwlwiMfc+Fi0pAMDlcsFms8Fms8HtdqO/vx+NjY0IBALcV/n5+ZySHQgEYDab4Xa70dfXl2V/IF7DaBhLqrjooWo2mxEMBvkeDIfD7Fkqqj+p0rdIKIt2BORLCQwWrCIFOZHZlBJObbRarcjPz2elIlk/JJNJrFmzBuvWrePiO0S805yXyWRgNpuRSCS4SBD1C91jNM40V35XX0kiGJ1OJ/x+P8xmM4qLi7ktVquV45ruXXqAQHGtVqtRXFzM/Uyp9R6PBy6XC3l5eQgGg0OKc0lISEhISOxukMSlhISEhMQuiVw1Em0j5PqReb1eeL1eZDIZfPjhh7zgtNlsWepBei8tRGkxT5VwqbALqfmo0i2RXaKnoEhikAqP1I1GoxEOh4MX9KmBBAa26PoBfFtwqKSkBAUFBTCZTEgmk/D5fHzdI/UHIS8vD36/nxfkRL4kEgkmbkTVJZFKgUAA0WiUCSYq4EKKn2QymeUPtzkMl4JKfoeFhYVobW1FX18fK+fC4XBWujCRGrFYDA0NDfB6vfB4PEwqx75VN4pqQZG4FP0b6ZpF8gkAIpEIF+Wh6xMJC2obWRLk5+ezzyN5SzIZpFIhIxCEdL20H7CpGjYwaHOg1+uZnKF2DgwMwGQyZfl2ElFGhAadlwg9IvHE7aJ6MR6PQ6vVsodrJBJhMpr2ofESU7fJq9BoNCIvLw8dHR1c2Zjal0wOoKSkBF+vWst+gmJFabqHALCykrwNiWy32WwIBoNZak9RaZZLPOp0OlYVOp1O9kcc7t4gBTXdp6IyM5lMorCwkAn0/v5+dHd3Y/Lkyfjkk0+GVHYXH2CMdheMNI+NtI3uRUoLt9vtcLlcyM/P55RwKlDldDrx1VdfoaKiAsceeywAoKurC0ajEevXr8d///tf9PT0wOFwIBqNIhqNDkuYiopScZ4VFa7DQa1SweZwIhpLwGQyQaVSIRaLIZPJwO1280MP8muNx+OwWCxM1vv9fvZGpfu9p6eHH6KoVCr09fXx9ZKKXKfTweFwcAE0mtfEiuSpVApNTU3YsGEDjEYjbDYbE/kD3xYUMhqNKC8vRzgcBjBYEIfmV1Hlmqv4HUhtyWw+FJWVlSgrK+NY7uvrQ0NDA5LJJFwuF5xOJ1atWsXWDVqtFuFwmFWn8Xic57ri4mKsWLEC6XQaeXl5qKurQ0tLC4xGI4xGI7q7uyV5KSEhISGxW0MSlxISEhISuyREUjB32yAxNFhJHBhMtysrK0N5eTnq6+vR1NQEs9kMs9kMm82GeDzOfnak/sklHgBkKS2puAPtS2SQ6HOmKAqTOaTaJLKJSAciZzRqIL4Va0e73Y6ysjJOR1+3bh2ryWjBLxIg1D/iIp5SjsX+E8ktarPZbIbT6eT0RFJliumSYtXygYGBb8mysV1LrrpLo9GwF11LSwsTb5S6SecAwGnQRFBGIhHYbDZYLBYmnamdIrkFIIvIFQmJXO9EIkdEr9BcywCz2QyHwwGn0wm73Y54PA6TyYRQKJSl5sW3sUHEXzgchtFoZJUhnZuKQ6nValYnigQZjZXRaITJZMoi02ksxIrymUyGiUkiXkkl29LSwlW0SX02mOa7SYmXS4bTvvQ3FTAiIpeUakTcm0wG2O0OJssolbykpIQ9BSmWiNSy2Wys/iQVHBUYIfUtkcZkxaDVanmsiDymcaNxEL1rqT9pnEX/Wko5p+uvqKhAY2MjFEVBc3MzZs6cCafTid7eXu4HMZ4VRdmsWULuPJZLFlI7SbVosVhgNpuRl5eH2tpaJoBJTdrf3w9FUZCfn4/p06fD7XZj3bp1UKvViEajcLvdmDZtGmbPno3nnnsOq1evZlI8FosNm5I+XHs3q7hUgExmMCWcVIj04IGuk4ql9fb2skra7/ezzyUV9TGZTOjq6kI4HEZXVxenk1PMk3KY3uN0OjmO6SEAkaO9vb1Yv349enp6OL4oxZx+4vE4IpEICgsLsccee6ChoYF9NVtaWrJU2fSzaU7YesWlw+HA3nvvjcbGRtjtduyxxx7o6OhgxXVVVRUAMMlMancxVZ3uh3g8jqqqKnR1deG9997j+aOkpAQ9PT1QFAXjxo1DXV2dTBuXkJCQkNhtIYlLCQkJCYndDoqisK0ipRQWFhbC6/Xi/fffZ2KPFFtGoxH9/f1MLpGCi8gecWFIBIbJZGJvw3g8nuVBCGxa6KfTafZZtNlsXPCHlFx0/kRcwViL8xCHoNPpUFtby2RRW1sbwuEwTCYTjEZjFpFCpAtdH5FK5NcpKpJIRUSEJjCYjul0OpGfn4/e3l4mz8Q+F1VHRBgMEnBjvzZR5ajT6VBQUACdTof+/n727yTfRYvFwpXEacFOJEUwGGSfSOprUSmYq9il/3Or7YrXVVBQgMLCQkSj0SwFp6jYpTGlVFiDwcA+lcCm4jEqlQqJb1NoNRoNHA4HezoSoUbqTafTCWDQG5JS+3PHKhaL8X4A2J+V2iX64JESU0yZ1mg0CAaD6OnpgcfjAQBWbontJjUkKdZEQo2IS5vNhnA4zBWtKXV18Hc7BgaSCIfDnFau0Whgt9uZKBe9X4FBAttqtTIxTlYFdF6RYCfSU6/XcxuHK4olepwSiUvHA8BEMZHIdI+n02mOgc7OTi76MnHiRHzyySdZ8TPcQ5UtRS6BaTKZYLFYkEgkUFpaisrKSlYykgqUSEwiIqkIV19fH6LRKMcYpepPnToVqVQKX3/9NT+QEdO7h1O3U9s2fwFAJqOwypzikB4mDAwMwOfzobi4GIFAAFarFf39/awkHBgYgMPhQCAQgM/nY4uE/v5+9gkmkpxsGCwWC0pLS5mEJgKfinU1NDSgq6sLfr+fyT16ACGS4FTAqKOjA5MmTcKUKVOwYsUKAIOKyJaWFp5/CJtUuls13FCpVJgxYwaTkvF4HEajETNmzOAHMv39/VCpVPD7/QA2FeYSi/fQnLBu3TqMHz8eBQUFcLlc3Cc9PT1obGxkonrSpEn48ssvt67REhISEhISOxnqze8iISEhISGx8zFEIfQtUabX61FQUIDi4mKsX78ezc3NXD1cTO212+1c5VZUtFE6Hf0t+gVSanUoFEI0GuUFsLiQJeVYrucgsEnFN0iyaMdE7alUm8i9vLw8JhIbGhrQ19fHC2mv18upuLSYJTKMfANtNhtisdgQokCsji1eA5E4JpOJfd7EVGqRDMotaIRRk2WH99TT6/VwOp2Ix+MIBAKscCIVHb2HyBAaH1LmAeCUTxofsQq26HkpXiuNX66FgEqlgsPhYDKSiF8A7C1ns9mg1+v5h9pCxxCPn8mkWRVHKdW0r06nY9UmEXNarZa9MEldSAQOpTZbLBY+BhHHooKRFMBiUaB4PI6uri7k5eVx7KvVanR1daG5uRmhUCiL9CNSmggjMb5om0qlYqJEpVKxF6PJZEJnZxf3wcDAAKc4U/yIY6rValFQUICKigoUFhYiEong66+/Rnd3NxM1VMFcrHZP1y36VhIxTdsoniieh7sOuoeIyKd+LCkp4f5tbm5GdXU1Fxoa8cbdQuQqvimlWlEUlJeXY/z48bDb7extCwButxtVVVUcB/QwheaxRCKBWCyGnp4ehEIhfP3112hvb0dJSQnKysowMDAAi8WSpTwXPUOHU5OOfhHgPiUiVaVSobCwkPs/kUhw4ZyamhouNmSz2eDxeJCXl8dkLJ2bSD0a03A4jN7eXiY3iXg2m808F8TjcdTV1aGrqwvpdBperxeFhYUcQzRvUQVvh8MBnU6HWCwGj8eDyZMnY9asWTzH1NbWwmazZRXDEtWXWwOn04mysjImVtetW4cPP/yQfS6tVitisRg/MAMGHyrl5+dzbORWbY/FYgAGH3xQQZ+PP/6Y/YEVRYHH44Hdbt+qNktISEhISOxsSMWlhISEhMQuiWEXzqqh+9hsNni9XpjNZrz33nus3jKZTLBarTAajZwSShVliVwiVaLoWykSHEQwianiijLoWUjKS/qdiJVMJsMEAnn76fV6KJn0mESJRGTo9XpWFQWDQRgMBrjdbvT29sJkMsFms6G2thbr169nMpPaXVJSwu3t7OxkBRoVohArLYsptURyuVwuvqaRUkipCjeRoZu5qiF+fkTU2Ww29lskhSAt2F0uFwoKCtDW1sYFj0gVR2mfooJTJF9EApHGUFTxUTvEdGhSc4XDYR5XkSw1GAzsQ0nqyHA4zCpUUfU6eH4wWaJSqVhVSOmoImEuktx5eXl8PL/fD7/fD7VazarLTSn6m0hAkcQkEJGeTCbR3t7OxIXf74fJZEJfXx/3a35+PhNkYkEeGmvqI+prIvFIzUt9pSgKOjras6wESClKSkD63Wg0cgEVv9+Pzs5O9Pb2MmEZj8dZPSoqVcVx1uv17EdKyjQqakMqOyIzSbEr9rXFYgGQ7eVI57VarfD5fOjv70cqlUJNTQ2++OKLEbxdRyayREVj7nYCzUWk+KyurobNZsO4ceNQVVUFn8/HBJbJZMK///1vtLS0sIJVtDoAwA8niPhWqVSora1FIBBAIBDg1Hq61/gqtlhFqiAWG0xNJ2K/s7MTTqeTLTcAMOlMth5U0IpUu6RA3HTvKFmEIfV5NBrluY3ua5VKhf7+fqxfvx5tbW1QqVTweDyIRqMIBoPcUjoe3WNUjd5sNiMWi6GkpASTJ0+G2WzGRx99BL/fjwkTJmDjxo2c2g6Q7+vWEZfjx49HJpNBdXU1KzozmQz++9//oqKiApWVlbBYLAgGg2yZQJ9VVAU9GAxmkbeRSITnos8++4wLE5ENwuTJk2EwGFBdXS1VlxISEhISuyUkcSkhISEhsUsid9GsDEMMkCoxLy8PnZ2daG9vh8ViyfLGo4If5CUopp4CyFIeAWCvPlJhpdNpVouRmslms7H6RaPRwGKx8AJaLDxCC2OLxfItSTXWVPFB5V9ZWRlaW1tRWlqKDRs2IBgMQqvVori4GMlkErW1tXA6nVi3bh2CwSCsVismTZoEk8mElStXQlEULmxBRR1IQUiEnNFoRDQaZZI2lUrB7XbD6XRy1V9RYUR9J6bY9/b2frvP5q9LJA3FttD/VKFaq9UiPz+ffUkpjV2lUrEHJ5EzRCiIqkc6lnhOUT0pgvbLy8vjStrkxUjjKvpViinIuUVwNrVDxdeo1+uRTqdhtVphtVqz2k2KOSIZSRlG1bqpoAgR6qKalK6H3kPHFBWJFNsGgwF+v59VhkRiU7ETo9HIqkuR/CRSlMaczmUwGLh4k9ls5irWDpuJCcZYLAaNRsOqtWQymaWUHPTENMHn86G7u5sJNipIQ8Qo3YvNzc2cKu1wOJCfn8/3omgBIfq5qtVqBIPBrEJGBJEYo3ElIpYUpV1dXYhGo2hubsa4ceOwdu1aLuSSq04ca+znvker1cLj8SCZTLLCktSAOp2OK0QTBgYG+L4nMp3IKoqRcDiM7u5uJpppnMgHmIrkAGAVeS6hP9Zrc7nykVFU6O3t5YrdgUCAj0mFj1QqFVpbW9k6gLxXSSkozkFigS1RWZtIJJBIJLhIUSKRQDgcxrp169DU1IRMJoMDDzwQgUAAGzZs4JjW6/VwuVxM8opFssxmc1bhqdLSUuy///54++23EQgEUFFRAZ1Oh56eHn7/Zie7YaDValFdXc2FgtxuNxfG2mOPPRAKhfD555+juLgYwCDJ29vby59l5eXl6O7uZoU5PQChauhffPEFioqKUFVVhVdffZU/uzweD5xOJ/R6PRf8kZCQkJCQ2J0giUsJCQkJid0WWq0Wbrcb+fn5rCTJz89HNBrl1GMi59xu96DyUUgnzS3cAQwSmZQCS2o6IhBIwSKCiBZSp9Fim4imZDI5mMpp0G02m1T1bSVxs9mM4uJirrhcUFCA7u5uhMPhLNKVVFQWiwVtbW2w2WwYP348GhoaOL2YiqNQCrWoSgPAKi1Ki9ZoNMjLy0NVVRVXVxY9O2kfUqQVFhYimUx+q6Aa2etSVJwRGUGKMFGVSOSq2WyG3+9HX18f9y2lPgYCAS7EQeqsXOKFiDYATPKJ2ynVkq5NrVajoKCASROqvk2/E0lJf5NCNFfFqdfrOa6IKBPTrmlfUjGm02kmy6jIjOgXWFRUxMVvrFYrq8zofyLV6Vw0vlRcicbK5XIxOUPnMRgMCIVCfG/Qa3RvkY+emJovxg95TnZ3dyOdTiMajSIUCnHfqlQq2O12VlXS9VL7HQ4HjEYjgsEgjw2NExXMIcKKVJBke0Aep1VVVexHK6bziv6c4thTDIrkMZFldJ9QTBUUFCASiWDjxo3o6OhAUVERioqKUF9fP4yCcuSbezhCkN5PcUcPV0wmE8rKyrj/TSYTk7J0XUSyUjyQApnGj66F7n2qtE7X1NbWxsSgy+VCZ2dnFqlKsZRLtg6HQdLbgNa2TlZOEikp9hGlP1MqMxUwo/tcrVbDbrczyUkkuVgxnAjzwsJCLgbU3d2NDRs2oLOzE4FAAG63G2azGYFAgO85cYxTqRTHvXi9TqcTfX19qKioQCqVQm1tLVQqFT799FP4fD5MmjQJGo0GnZ2dwyrRx4K8vDwUFBTwQzCaR+LxOMLhMCorK2Gz2dDW1saEI/kYU2EjsnEgiwm9Xo9IJIKuri5UVlaipqYGyWQSTqcTarUa4XAYLS0t/DlRVFSElpaWLW67hISEhITEzoQkLiUkJCQkdluYTCZ4vV6YTCauoEqp4kQWUeohAFbzAYNqltwUTtFHkRaWRIiROoxSroFshZ9YeZmIIdHfTckYxiTS0el0yM/Px5QpU5BKpTBhwgRebFM6ZWdnJywWC3w+H1ebTiaTvOAnck1MBRYrLlNBDyoCYzAYOE2VCJHq6mq0tbVxgQeRyKA0RK/Xy+3d5B06eqEesc+JHCZvSlLlabVaOBwOTnOOx+MIBoP8PlGNBYCvmcaYfBpFcoiINvH91AYaO0oZJVUXnVtUrYljTCo2kSDjVFcogKA2IxKZ0pdp3Kg9IkFE6jOTyZSlFDSZTFkejtQOkQSlY4l2B5lMJqvgEl2P2WzmYkgi2UcEIJFHYh8CYHKMyEgi+EWyifq4uLiYt1ObSeFJqmWx70SlLP2Qv2hRURGi0ShaW1v53KRoFv1lRdsBo9HIhLioJCXSkvwB6droNSo6VFlZyRWfV65cieLiYmzYsCFLtbYlJFbuvjabDVarlRWKZH2Rl5eHwsJCtotIJpNMcOt0Ok7rJyKLro/UiXQdarUaJpMJBoOBr9/j8aC/v58JaavVyuTxaG0dDoqiIBQcVGZT2rPZbOa5isYaAHtWUhz7fD709PRw7JCSVXxYYjQa+bgA2Eahp6cH3d3d/EMPiLxeLxRFYWKP+ojsKAoKCrhqOMVqfn4+X08sFoPJZEIkEsGECRMQCoVQV1cHn8/HHqE+n2+rPE3Ly8ths9kQiUSwcuVKdHR0wGazsR8oKWjNZjPa29t5Pqd09zVr1nDBOKPRCKfTyVXEx40bB6/Xy5YCbrcbZWVl8Pl8qKurw/777w+r1Ypx48ZJ4lJCQkJCYreDJC4lJCQkJHZbOBwO5OXlIRgMoq+vj8kXUnKJRUbIMy8SiUCn03GapKheJITDYU6DFdOFqXo07ZvrsUiv0e/kjRiPx5FMbt4HEhj07KyoqEBRURHi8TjsdjvWrVvH6imxenAsFuMUUiJgiGxLJpNcyILIH1KBkvKIfogo6u3thdfr5Xbvs88+0Ol0aGlp4UW0zWaDyWTiVMzS0lJO16W0fGBoJqXYv7lEcTQaRXt7e9brlIYuFksickYkHYkMo3EWx0FUp4m+l3RenU7HtgAFBQUwmUzo7e1lkmhgYAA6nQ7JZJItBUSk02nk5eXxsYFsAo7IjXg8ziowUf1pMBi4OIhYTIeIVNqP3kMqNlJnUlq7GGukGKR9SCEsVg83m81MZJWUlHDRqVzfQJVq0CuQFKLUFq1Wi3A4jL6+PiaY6NiD/yscDzabLUv9Ko5NV1cXSktLs2KCxkhUqhL5lk6nUV5ezoQ2+aPSGBNxF4lEOIWaSH+qOi1aRQSDQfYLpL6jtGtSxxIpm0gkUFRUBJfLxarYLPXkSLc1siuH0++koiwqKmIFn81mw5577okJEyagoKCArS5Er9J0Os1FbZxOJ/r7+/lBjdlshs1mw8DAADZu3MhEJRUXI4LT6/Wiq6sLsVgMsVgMDoeDU7xzMRafy1g8jlAoxJXkNRoNQqEQKyQzmQzPUy0tLbDZbJyeTcr4WCyGdDrN9z0wSOCTmjYWi0Gv18PhcKC1tRXBYJD9OwHwg47+/n588cUXrMolqwF6aED3ESmaDQYDYrEYwuEwysrKEIlE2L7BZDKhtraWSUW3281p9XSPjhUqlQplZWVIp9MIhUJYt24d1Go1Jk2ahMrKSgQCAZ7TSYlus9myxsRoNCISiTAxT/1rMBiQSCRQX1/PDzbsdjv23ntvrFmzBqtXr8bnn3+OQw89FKWlpVkPeiQkJCQkJHYHSOJSQkJCQmLXRy4roAAarYYLijQ2NjKJR0VCxBRDWvzTwp+UbsBQn7qBgQGEw2FWyRGZQYtdStkU3zOkuQJxScWBoGRGFumoBqukU/rsxIkTWSWUTqfR09MDYFNFanGxXVJSwmmBVH2X1JdEZhKpJqbK07UToaHVatHb24vCwkLEYjH09fXBbDZjn332QVVVFfr6+rKIMr/fD41Gg/r6elgsFq5gvjULYqfTCavVygox6mPyY6R+IBKYiAMaZyoQRKSf2Wxm0lIktcSUYfLeI7KElFj0HlJuUn9TG8QUcTovFZkZGBjgtosp/f39/VCpVJzuTOQMEcpEjKXTaVYIEmFHhJV4vdRHVHmciFuKAarOTG2JxWJ8LVqtlt8rkn5E7hGBR+cymUysPqWCPLS/TqdDIBAY1lNU7GvRO5Per9frUVxczG0S75tclayiKDw2lFodDodhNpuRl5fHY00En+g7qtVqmbCiY6TTafh8PmzcuBHRaJT7kVSopEqmfqA+6u7uRlVVVVbRlLGqEuk+FMnO/Px8JicVReG0d7PZjN7eXuj1ehQVFWX5VwYCASZb9957b6xYsQLBYJB9REXCnkBxR2pfl8uF/Px8tLW18TWQ6pMwljRx8fjBYBAul4uV4BSPGo0GTU1NKCwshMFgQHl5OUKhEFdCt1qtaGlpYaKd+gIAk892ux2pVApWqxXxeBwtLS0cp2TTId7nRFbTddBxiRBUFAWBQAD5+fnYc889WaVKPrDk+5rJZFBQUMBeralUClVVVd/2t3W0LhkCjUYDj8eDdDqN+vp6RKNR7Lnnnth///3R1dWFUCiU5ffpcDhgNptRWlqKrq4u2Gw2nuf7+voQiUSQn5+PvLw8JmHpcy6RSMBiscBut6O6uhobN27EypUrMX36dDidTphMJla3SkhISEhI7A5Qb34XCQkJCQmJnQxl04/q26InRqMRBQUFyM/PR1dXF6fOkRoqFArB7/fD5/PB7/fzwpCIgeEUkuSlR2moANi3LRwOs9pGVIdtjryk3wcVZyPs++3/FouFU/wojbO3txc9PT3sT6jVamG321FUVASj0YgNGzYgFotxddmenh72+yOCT/SnFNtlsVj49UQiwarVtrY2tLe3IxqNIpPJsN8aeaeFw2FotVpUVVVxiiilNQ+PTYozkQyhvtfpdCgpKWFyUqvVIhqNwuPxoLCwEBaLhUlgIpaIiKNCLkR8iuot8VqJvBULsohWAuQ9l0qlEI/HmezT6/VcYZwUa5FIhAliAKitreUCMdQujVoN3bekZDKZ5BgCspVkRNyRIjiRSCAajbJyiq5bVIkS0ezz+bB69Wp8/fXXTIaQwk0s4kFpyGQZQG0n+wG1Ws0KPiKhSVFG1goA2O+SCCmr1cr2CUwUpzNQlEE7BZFMFYk0Is/p4QCRhqQAJtKIQIQlpTWXlZWhoqICer0eq1evZmU0qc8MBgMTb6Quo30ikQgaGhqwdu1a9Pf3c98TGUvnpjGgccpkMkwYOhyOIff4cMXDsu4AQXVJMeBwONivlSpdk9qTYktRFJjNZiahqQ8opXjSpElMWKVSKUQiEXR3d7NXLbWRYoH6we12Z42Dy+XaulRxDBLSZrMZbrebVd6JRAJWqxV+vx89PT348ssvUVJSAgAoKiri+c1oNKK8vJznDiK3qX+KiopYWR+LxdDW1oZUKoVYLAa73c5koNFoZJsJi8XChDRBq9XCarVi8uTJ7FfZ19eHlpYWZDIZfPDBB/j666+5D4lIJTV2YWEhSkpKkJ+fj4qKCoy10BpBr9ez6nrNmjUoLi5GeXk5urq6kEgkmFymhwfkudnT0wOv18ukNnmglpaWor+/H/39/SgtLeVxpZjp7u7Gxo0boVKpMHHiRMTjcXzwwQdsRyAhISEhIbE7QSouJSQkJCR2SWxO8UNecGq1Gv39/bBYLFnKJEqrJfKHFDVERInKO5FUEH0TaREJbPJdE4lOkVwhiJWlRbUnlMyI1yN6c1ZWVjJxkUql0NzcjHA4nFUkRa/Xc3Xzvr4+tLW1cbXqtrY2OBwOXgST2o0IJCI0RWUWKX1oPyoElJeXx8qm9evXw+VyIRKJoKmpCQCYNDWZTHA4HOxXOfQ6Rx5HqmZNCkhKIU0mk5z66vP5uJ9I6UfKR6rcTuReNBpFIpHgMRArYpPaLne7x+OB2+1Gf38/QqEQQqEQp86SQpFUuvF4nAsfkeLS4XDAZrMhGAxmpazr9Jtix2KxID8/nwl2qjROafFUmZ6qFpNykI5HSjIiDvv7+/H5559zheXW1lasW7cOtbW1fF/09vYyEWQymbLGJhQKwePxMHEZCoWyqisTgZ+rJBW9Rs1mM0wmE5qamnI8JFVsx0D3gZjiT4pGsaJ6rmUDkZVErokp8ETeKYqCuro6OJ1OFBYW8n1L96DZbOa+pUIu69atQ3d3N4BBj1wxZZj6OBKJcNVzrVaLgoICtLa28nWUl5ejubl52HYPB3GuIeTl5WXNFZWVlcjLy0N5eTkT2jR/AODCRFS4inwYye+wr68PVquVH9CcdtppsNvtWLJkCZOhRLymUimeL6mPaW4RvTvHorhUfXsPFxaVIBAIZCluS0tLsXr1aiiKgpaWFnzwwQc4+OCD8dVXX6GwsJAfwtA9uGbNGk7ttlgssFgs7HEZiUTYl5PsQJxOJyKRCF+3wWDg1H5S8YpkeCKRQF1dHasxE4kEOjo6eB7q6OhAQUEBNm7ciL333psroRuNRjgcDj7W+PHj0dxYt9m+EUHE6n/+8x/EYjFYLBYuUiQqq+k+MZvNcLlcsNvtaG5u5nlOr9fzPFJeXo729nZUV1fzQyfydqX0cZVKBa/Xi+LiYqxZswZerxdOp5OvW0JCQkJCYneAJC4lJCQkJHZJbI7kc7lccLvd6O7uRjweh8fj4QWrxWIZUn2bCJPhjk1EDL0u/k5emaQuy01nzVWGEblJXpOUnqlRj04EGAwG2O12VFVV8eK1t7cX3d3dnK5O1ZmpirNOp0MikUB3dzesViv0ej38fj+nYQLg/Yi0o5RgWiyLhXsMBgOCwSB6eno4BbO/vx+rVq2C0WhENBpFQ0MDK8TUajUcDgfsdjucTicSiQQCgcC3vnOiGi3b11JUrZJ6kJRudrsdwWAQ0WgUJpOJVVuUrk/EnZiqTBWCaXyo6IY4HkReiNWm6bpLS0uRSqXQ39+PQCAAn8/H6d1E2Imp5bFYjNNziTghv0Gx4rBWo80qMkIqMpVKhVAoxONBZLTdbudCRaTyo/eLMZrJZLB27Vr4/X4eY41Gw76jlGJKhZnIs5MIUa1Wy0o7vV7PZCWR/XSdNDZEftP5qeI6+SqSX2wqlYJKrfqW4I3B6XTy+8QHAmL6NXlqipXracyIVBeLDol+pTqdjotXdXV18X1P5Fcmk0E8Hkdvby9SqRTfT6RcFT1FqZ/C4TBfF8WL1+vFxo0bEQwG0dDQgOrqalZ2b0qPH/HWHhL3arUa+fn57BFKRWUmTpwIr9fLhW1IRUeKYJPJhI6ODibwqQBNZWUlVqxYgVAohEwmg3333RezZs1Cb28vK3StVisrFUmhSP6qwKCy3G63w+fzZfXxZqEaLMAUCIb5nh0YGOCCM9FolMeuubkZ+fn5qKysRHd3N+bMmcP3yn777YeTTz6ZFYjBYBCrVq3CwMAA/H4/P7ihgliU7iwSdSaTib02jUYjP8CghwREWNpsNiQSCd6u1+vhdrsBDNpxUAxQP+h0OthsNn6YNFhUx775vhFgs9nQ1dWF9vZ2lJeXw+FwMFEZDAZZVet0Ovl+I5WmVqtFf38/PB4P4vE4mpubAQwWWXI4HKivr+d+ILU4EZ3U/tLSUrS1tWH16tVwuVxb1HYJCQkJCYmdDUlcSkhISEjs8hBJLyKTyN+LFD0qlQqRSIQVXERwEcFB6cFEYo6mlBKrb9MxiPATSbfc/4msBAbVPEQSDAwMQKNWYSTloUqlgsViQUFBAex2O6dt19XVoaurCwCYMCMilDz7ACAYDKKrq4sLkPh8vqw0bFHBRf1HJKBI7hHxqSgKiouLEQ6H8c033yAajcJisaCrq4uPSaqgiRMnwu12Y+3atSgqKmLiYXC8Nl1jrh8gkQJiwRnyPqSK7Bs3bmTCUq1Ws38pqbHi8TjC4TD7BGq1Wq6OTsV1RAKTxo+2URELr9eLQCCArq4udHR0wOfzMTkLbKo4TcehFHoie61WK9xuN1pbWwUbAQ33ExFNAFiVSuQ0XZfZbGaFoOipSf0m/vh8PrS3t2elYVPhkkAggPXr13M8pdNp9Pb2wmw2IxKJcPyQAjE/P59JMFK0EdlN/oCk+CSyOlfNRgVmIpEIVCo10ukUFzuh+CabBbo2qpQt+nOK3pQisS4WBkqlUvy3Wq1GYWEhgsEguru7EQqF2JOTiFpSayaTSSa4Rf9MisV4PM5+r1arlWMqk8lwBfRoNIpoNAqn08mktRDQI97bdA6CzWbjsVOr1bDZbLBYLIhEIli1ahX3R2lpKVtbqNVqOJ1OaLVa9PT0sI9hZWUl+vv70dXVhebmZni9Xhx++OHQ6XSIRCJZambyxiUlttVqRX9/P4BBn0pKT6bYzLV2GBaKgt7eHgSCgwR+bW0tPvvsM66MTWNJ47lq1SrodDr4fD60tbWxH63P5+N+7+joQGtrK9auXQur1cqFnsLhMBOURMaLlceDwSDy8/MRj8cRCAQ4FV30+k2n0wgEAvzAiaqGa7VaFBcX833f2dkJu93OxDHNQ1RtPpOMjNYrQ+BwODh+3G53lsp3jz32wIQJEwAAvb296OrqQiAQgMvl4odIwWCQ/XRprOiBTjQaxZw5c1BWVoaNGzfiyy+/RENDA98jlIZOqfykdiWCVEJCQkJCYleHJC4lJCQkJHYffMt7keei1WpFX18fq9lCoRA6OztZxUaKMVK0EQlA6d/DkZeUHk6kCS3cSQVFSqVcHz4iP8hPUFTr6PV66LRqxKPBoZekGjy/wWBAdXU1K3Cam5vR0dHBpA8RMXROkUhNpVIIBAIoKCjIquhLxB2lfxoMBgQCgawKy6REJJIuFotx2u3atWsRjUZht9tht9tRXFyMlpYWRKNR5Ofnw+l0Yty4cSgoKMCGDRuQl5eHxsZG9Pf3ZxXpUSFbdUf9nU6nEQ6Hs66LyDG1Wg2/3w+TycSEGhF7VC1YJBWI2CWSho6RW107l6j2eDxMerS1taGjo2OI4koksQmhUIhJRVJ8kWfooEdqmm0LqK+JeKaxpOIipGCMRqMcy5QWSscQY62zszNL7WcwGOBwOFjh1tXVhXXr1nEF+Hg8zkQv9QXFucvl4gI2lKqu1+v52HRuihm6XrJcoGujQisqZQDRaISVzxQH9DCB/FeJiHI6nawuJJKQxomIPWqDeCzRykFMpyY/UdpfVD4T2Uztpb6nMQHAiliRGKN080gkwoVlXC4XP1QYLq7EeUF8nfxEKVY1Gg3cbjcGBgZQV1cHu92OcePGwWg0Ij8/Hx6PB5lMhslnIpx8Ph+nsZeXl+O4445DfX09SktLBxWQgQBWrFjBSjy1Ws3XQGPtdDrR1tbGJDL55mYRspuDSgWj0QSjadDmguYemifovjGbzaxYrKurg8PhwH/+8x9+iED+vmq1Go2NjSgoKMD+++/P/RIIBDjmiJSk2KBzktKcbDLo/MCgkpJS/4kEJBuEVCqF1tZW9gkuLi5GXV0dDjroIESjUZjNZlbYOp3OQfLT37WZjsmGxWLBhg0bYLFYmPinuNp///0xfvx4DAwMoKWlBVqtFn19fQgEAujp6WHSmYoL6fV6BAIB+P1+WK1WjBs3DlOmTEFNTQ0mT56MadOm4dlnn8Xq1as5nsnztKOjgx9EicWYJCQkJCQkdmVI4lJCQkJCYpdHVkEXtQp2ux35+flcoIQKcphMJq62Teop+iE1HgBYrdYsBSaBlJVExohegzabLauoD71XrBRM3ppEBNICdfBYIyuXKIW4pKQEAwMDrKCiasikTBMLWIhFRai4jt/vZ9KFSBt6nSqKR6NRqFSDRW1E0LGpzevWreO0UbPZjPz8fC4kQkQWEcROpxNVVVWshO3o6BhSXTxXcUnXQemepG4SSUfyzySVIJHAtIjXaDSsQhMLvVDas5h+TOMJbCrKQ1Wmu7q60Nvbi46ODkQikaz3EdEnFu4horWvr48Vvfn5+UysRiIRpLSDHpfkydfb28txROcW058BsCKLSHGn0wmXy8VKUyJh+/r6mIglpSYRWkQ6dnV1YePGjUxCm83mrBR3InkoLZfimQh7sicQx43uB5VKxaQ4kd9arRaxWAz5eXak0xlWzRJ5RO0XyV8qRERKu2QyyXEl3l9UFIk8RWtqauByuRAOh+H3+zltXa1WIxgMsqJ0YGCAU+9F1SspeCkGaXxJAUfxQw8HqLBLT08PQqEQotEoysrKsG7duk2qtREsLnPnCyIq29rauB9JVQgAXq8XpaWlTMARySZ6hJKKMhqNoq+vj4t2zZo1i8f0vffeQ319PatY6R6h4yqKwkWGCKlUCjabjR/SjAVqlQrV1dX44suVePvtt3ne4de/JRRFH9xwOMzEP81N6XQadXV1cLvd0Ol0mDVrFlavXo0NGzawrQLNq3a7PatYlvhwR/ws6O3tRTAY5Pgjb0gqkkNxQePd2tqKgoICFBQU8NxHcyypPun9o/n25oI+a9ra2jBu3Di2UIhGoygqKoLVaoXNZkMmk0FbWxsaGxuZuKR5lO49k8nE9yilhnd0dOCdd96B1+uF3W5HSUkJDj74YLS0tCAcDqO0tBQajQZFRUWor69HX18f7Ha7JC4lJCQkJHYbSOJSQkJCQmK3AhVyoCqzgUAARqORFW8OhyNLYUXkE1VXNhqNXDSEICovKf2XCA1a3JJyU1QH5hJxVOGayC0q8DJ4XDVGWuzqdDq43W6YTCZ0d3ejr6+P1VyUbk6FhYgoGi6tlqokk4IO2KTqEStYk6ehqCikxTUA+Hw+dHZ2ckolqZdMJhP3DSmoqNJ4bW0t4vE4Kisr0dDQMJgyPwyZIyrQqPr7wMAA8vPzWYVI1xYOh5Gfn8/pjjSOZrMZTqeTlWJUSIXGhooXUWVwYFNVcVr0Uxu6u7u5YrRYjVwk5AAgEomwYpIIJEo77e3t5f2I7IJKBYPewISi6N0opp6TcpRINSJvgUFigyp8i2nbVJ2c0ppJ5dnf3494PM4qz+bmZvYqValUyMvL4/6nc8RiMe4z8dppHzHOiKikfqZ+FBWhGs1gKrkqmebYpmMQmUiEdywWQ39/P6tMiYCi+CYykdL+k8kkbDYb9tlnH6TTabS0tLAHLKXiUvo6xTiRknRf0LVR3Igp0alUiucNUZlNSlBSVTc0NHAadzgcHjzmGHgssjmg66VthYWF2HPPPREIBODxeDg+RB9SIuu1Wi3y8vLQ2dnJbY7H4+jq6oLRaITNZsPKlSuxdu3aLK9PimXyh1SpVFzEi2wWYrEYHA4Huru7x0xcKoqCdevWcaEZig+KJ1Kdu1wu6HQ6dHZ28txKxC3ZayiKAp/PB4/Hg6+//hrr169Hd3c3DAYD9thjD7jdbi6URYQ4PaAIBoMIBALshSnGUCwW43gwm83o6uri+8pms3HqvdfrRXNzMxwOBwwGA0KhEOx2O8cFPSByOp38EGwsIKV7JpOB1+tl8rG/v5/nPfK9Xb58OTZu3MjK+MLCQj5fJBLhe58KiJGSe8WKFUin0zjrrLPgdrvhdDpRU1ODTz/9FGq1Gi6XC4WFhawUpgrvEhISEhISuwMkcSkhISEhsduAFDekLCHSghSUer2e/QJJgUfkIqXiEpFCxwM2qQGJxCOSg9IsSc2VmxoukjwAOIWUVEXkI6nVaqEaltlQAAym+lJVa1LUkeKLfDuJfCKyRWyPWKVZpVKxrxsVtyF1pljFeWBggElDg8GQpeaKRCLsjweACYHi4mJOp+zq6kJRURFSqRRMJhPKysrQ3d2NyspKVjQpOVXXc8kQSnGnCuYiWajT6bjKL5ErsVgM8XgcoVAIPp+Pr5sW/oThyGVK/RZTvin1EkBW8Rp6H/1OFdzJ35PSmkmdRySzxWLZRPYBXBU4EomwKlNMe1ar1TCZTFkxRuQyVVymFFVR3UvjQrYCRGaQ8lCMR1KpEpFdWFiI3t5eTgcWlYcA2FuTiEbxdSLw4/E4k2CkXiSV3aAyWIe4P8DqPootIpmIzEokEnyfiOnpdBwiYOlvRVHg8XgQDofR3d0NvV7PvqrTpk3DJ598kkVail6mIklJfSySnOTtqSgKLBYLK0aJbHU6nUyiplIp2O122Gw27vvRIKpWHQ4HjxkVY6FUeTov3eciQUxp7eSxaTAY0NfXx9caCATQ3d0Nr9eL1tZWrgpPBCnFHRUgokJGNEb0ECIvL2/EtPfhkPmWbKSxE20gKBaj0ShisRiTjblzp+g/G4/HEYlE8NFHHyEej6OgoACTJk3iNHKyKyBvTI1GA7/fz8rLYDCIvr4+AGD1NN2vXV1d6OrqYk/a3t5e+Hw+fiDh9/sxdepU2Gw2DAwMIBAIwOFwZF0LkbykUB8LqOAYKVz9fj/C4TBqampgtVqRyWQQDofx/vvvo7m5mdt72GGHoba2FgMDA5g9ezZcLhei0Sji8Tji8Tj8fj+WLVuGtWvXIpVK4auvvoLJZML555/PqeHkmUz2Gna7ne0ByLtWQkJCQkJiV4ckLiUkJCQkdivY7XZ4PB44nU6sWbOG00/Jq4zUgxaLJSsNlwhN8gwcznORfhcLdxBhlLuPSIIAm8gJUpMRqUOL8XQqieEkiLQI1+l0TMb09fUxYUUkHrVLJJPEY4jXRAU4SKEkegVS+0gZSMQokTS9vb1ZqbXkI5hOp9HT0wOHwwGtVotoNMqFgCjVO5FIcMXczs7OIW3MJS6JeItGo8jLy2OlqMPhyEprJzUipUaSQktUy+Wm/NM2sa9ou6gwpbghkogW9ADYJzWZTCISiXC6KJFKdE6q9E6ejrTd6/XC5XKhs7MTfX19cDgcTLgQMSgq00QFI5Ft1F6K4Xg8nkVkkkJVtCugKtyk7qLxFlPRFUXJSqcnYjPXH5SOTT+ikpEIcUoPHozPTcQUKRKJVKJYpv6l8e7p6eFxHo6Ipuu32Wzo6+vDxx9/jJ6eHhQVFcHhcMDr9WLSpElYs2YNOjo6uI8oRsRYEe8VqixOxDgpX6lvaGxpO8V1W1sbZs6cmaV8HEmhSOMnEpdUaVuv1yMvLw/JZBJ1dXUoKyuDRqNhdSKRfBSDdG9YrVYmA4nYJbUwxQyNJ41PIpHIKjokEoBU3ZzGiOaZ4e7ZoRcITs0nVTHFLo0B9SfFpRhjtD/9LlpfuN1uHHDAAWzpkFtki0D2AqFQiMeU0t7pfqWCZ6QYp/tGLNREimVS+vb19aGsrIzjT7Sq0GjGvoRyuVxoaWlBTU0NtFotFxQrLi6GWq1GIpHAunXr2PNTr9dj/Pjx+OlPfwqTyYT6+nqoVIPF5+jhRH5+PoqKijB//nw89thjbJmwevVqrFy5MquQGT14GRgYgMvl4nlUEpcSEhISErsLJHEpISEhIbFbgAgHl8sFh8PBadVEdvj9fl7Akq8aqZcAcHqeSHbRcXNJSgBM0JB/HIAsgoj2z1XpAeDUZUov1el0SA0k4OsZSlyq1WrY7XYmDrq6uhAOh5lsENWQoipUVNbRdYlqNjElWdxfvEYiconooCIXVMiDSARK1e7v70csFoPX64VGo2HCqaurC1VVVdDpdPB4PFwFWVwU5xIgpH4kdWpNTQ1sNhuCwSA8Hg90Oh1CoRAMBgOnwVLhHlGNRiSeOKaiqov6ga6ZSBWTycSkpVh5nNos+qMS2SGSg6SKon3Jr5P6WVEAm92G0tJSNDY2sjciEYliejIRgkRaELEEgElHOi/FCV0fEdnUfrV6sFo1+ZJSLJC6k9SfpBwVU9NFEpjGh7aJxYrIj4/eJ6oio5EIUqk0p74CYKKbCEBqD5Gp/f39SKVS8Hq97L9J/UrnoUrkbW1tnN4ej8ezUmALCwtRX18/hAQWbQLEGCHyksZdVLMS8SZWWLfb7ejp6WFbgby8vCFK7JFAfUg+vPS7OLbkharT6fh+IkKQCqrk5+cjFouht7eXfVNJhUzzjfjQhM5NJDURk5Q2T96dNHfZbLasuWVzUKkAo9EIjSacpboU+4QsAMSCWiJpRv1ObQiHw7Db7SgqKkJVVRVaW1t5jEiJTinyijJYZGjSpEmIRqM8dmS5QeeiYlDd3d3o7e2FSqVCRUUFx2UqlUIsFkNTUxP3c3t7O6ZPn55FApNq1Wq1jKl/RL9WIqSJBKeHGOSvS8pajUaDk08+GTqdDs3NzVixYgX2339/fgjQ398Pq9UKr9cLo9GIY489Fs888wwymQx8Ph9ee+01HHTQQTy+oVAIVVVVSCaTqKqqwurVq5FKpbL8nCUkJCQkJHZlqDe/i4SEhISExM4HLfzJvyudTjNxScSEz+eD3+9HIBBAIBDgVEECKZ+GU1uKCi8iTEjllFUhW1BYim3LVXaJIE/G4VIwtVot3G43vzcQCHDqLZEMYpqr6NVH1yIqunL9/KgtYrEZImlIYUWqH+ojg8HA6jh6Pff9Go0GgUAAwWAQXV1drBqlQhzDXWuualVRFC6wYrFYUFlZiUgkwu1KJpMIBALsaUfjQP+bTCauFE/egURSimNN/UJ/EymcSzgRiUdkp06n42IcYl/QdYqWA0MJwAxUUKGkpISrRpOaVafTcaqxSKySKoyKo5ByUCQTKR7oPCKZLqrciouLuZgUqW6JGKHCUbnvpz4TyXg6v9hXdI7+/n5O81arB6s7B74t9ENWC6Tso+IzpAyk9pI6rr+/H+3t7XztogckWSCIpCHdl/39/VCUweIpVMho0xhsIl9FcpoIb7G6u+izSN6SGo0GdrsdZrMZNpuNFcwUl8XFxeyDOVJ6da5ylNSSdI10rzmdThQXF8Nut6OpqQmNjY2IRCJM9JIlQ0dHB1eN7+3tRTKZhM/n46I2VNiLrlm8bvIKpYcS6XSayU6K/9z7ZrNp49+q+nIfqIiFp1KpFILBINsK0LkptnIV7US0kq2HGAs0VjqdDiUlJZg8eTImTZoEsiKIxWLo7OxkgtNqtXJ19vLyckyfPh0TJkxAJBLBN998g2AwyJYO5IurUg36jlJ6NfUh2RlQzGwORIxHIhF+kBUOh/lYyWQSvb29aGhoQGtrK1wuF2w2GyoqKmCz2dDY2IjGxkbE43G0t7cP2m8og0WVjEYj+vr6oNfrWalrtVoBAN3d3WhtbeWYicViaGhoQCaTQSgUgtlszvJNlpCQkJCQ2NUhFZcSEhISErsFKJXU5XLBbDZzxVin08nqlWg0iu7ubiQSiSy/QbPZnKUmy12Y55KRosqLfAKJzKT3iPuL5I94DPp78BxDnxWqVIOenVSRWqPRwOfzceqymFZL10LEGikah1Mb5haDIbWSSErlprgTUZpLyNH1EclC7yfvN4PBgGAwyL9nMhlYrdZswiOnv0ViNx6Ps+Jr4sSJ+M9//sPXqiiD/nnkcymmmZpMJlaf0XUQUUbehaI3nTj+ucQfkVH0mpjySmRoOBzOIsVE0kVUvDLB9y3J4vF4kJ+fz+nipHg0m80wGo3sxUqV5cPhMKt8SYUHgEkonU6XVZyEzkuxMTAwgLy8PJSWljLRoiiD9gHJZJJJWIPBgHA4nKUSFuNXjBExPZcIyf7+foTDYcRiMSYt4/E4Soo8WcehyuFGoxFWqzWLHDIYDDAajUilUlxYp6uri4uikDK1r68PPT09MJvNWcWyqBBWMBhEXV0dOjo6eDyHU5KJRKbov0iFVzQaTZYakmKOSE4xzT4SiaCoqAgmk2nEQlTifU7nFFXAGo0GDocDKpUKfr8fkUgEdrsd6XQaDQ0NiMViKCwsZHKxr68P6XQaGzZswIYNG5BOp+Hz+eD1emEwGNDU1IT169ejoaEhaxxz5z2KXbLPoPElon64+WwkKBkF/X19WfEvEpjU3xSfdGy6T3IV6/QQIJlMwuv1Asj2YaV7gh7ukB8wvYd8L9PpNBclI3U0XbPVakV5eTm6urrg9/uzHswEg0H09PSwtUNPTw+Ki4v5+JSCnYgnRu0XAqmaqZ9pbidFMvluplIpbtuECRM4nd1ms+GAAw7AxIkTAQBdXV2ccUDHpznBZrMxMd7d3Z11XT6fD1arlVXdwWCQ45weWklISEhISOyqkMSlhISEhMRuA5vNxuqY1atX80LWYDBwtVydTof29nZWZVG6tVj8RESuWjIWiyEUCvEimBR2tHgWF/W5KiGCqOxiNZwaGK70sNVq5dTBxsZGLr5AxJWoqBTVSSJpJp5LVGPS65RmSxBJS7HdtOin66T/6XdS7oXDYdhsNgBg1SUVSQqFQlwsSeyb4UgkIkzb29s5nZHIAxqz7u5uFBYWZnlSih6ipLIiQoD6RyzGI44PqVhFFSMRl2JKsZg+Sqo6Ik2IgMg9RhYZDNWgGs1sQWFhITZs2ACfz4f29nYm2YmIJZIVQFYlaLI8oGMSueF2u9mXUBzXZDIJo9GIsrIyrrre39/PKaGhUIjJT5EUp/ERPR7FNHQiwulaiRjWarVcyIn6VqvVQVEG+5JiJBaLIRKJcGETqsxO967VamXPQSqK0t/fz/1A5G0oFOJ+IVuClpYWtLW14YMPPkBXVxeC3yo+KT04l+yn+BeVuTR2lNpusVhY3UfKPyriQ30QCARQW1sLs9kMv98/alVxUREr3p9kZ0EqwnA4jFAohLy8PFgsFiaYVapBv9BUKoW1a9eirq6OlasGgwEVFRVYuXIlxw+lidMY0rWLcwcdk1S5pA4EkBVTY4LQn3S+3HRxYBP5TmMgzkviWFgsFiQSCSbkxIcEdK/kpvETQSiqTMX7hu4dRVFgt9thtVqh1+vR0NDAsWsymXgeKCoqQjKZxLp165Cfn88EOxHuFEujQUzLJ8KT5lAiMumepHFxOp044IADMG7cOC6ClslkOIXcaDTC4XBwXPf19cHlcqGiogJdXV2sHO3s7ITRaOTPrnQ6zVXjKQap4JmEhISEhMSuDklcSkhISEjsFlCpBj3mHA4H7HY7urq6stKoaSFnNpvhdrvh9/s5DVMkpIZLVyZQsRhS4YjHJaVKLlkpkphEHoppmZtUmgroVHQItVoNt9vN6jciXGnBSccVVaG528QFulgYY7jrFdsteiVSW8R0alFtScodUo2JxEs4HOY0UCIZqO3c3hHGlBbPbW1t8Pv9GDduHPLy8tDd3Y2ysjJEo1H09vbyGMbjcVYv5efnDxJGAKtERTUpqS9FdR31XS4ZJyoKqQ8AcEqv6M0IIIu0FH1Fc5VqijJ43NLSUthsNvT397N6kNK6qa1UMV2n03EBFrvdzn0qjltBQQGam5uRSCSyyCKyUigqKgIArtpNXqFE9lB/Ur+RshFAluqQ4jt3PGk/UiFSyjFApJeKFZ56vZ6LgVD6MJ2XCB2tVotYLJZ1P4kpzoqicMquogwWjTIYDPB6vVi3bh0GBgbQ3t7OJCcV1hHTnkWFHx2fSCUiDmmOoWsjopLaQBYI5M0aCASY+BsJ4vySO98YDAbEYjGeV4gMppR+KqRFCrv33nsPn332GT+QoVhet24dOjs74XQ6mYjKVU1TvIkFv4LBIP8tkoy5c8NoUH3rcRkIhvleEQl8IjSJQBTPQe0jdTt564rFxMiWgTw6jUYjotEoE+Y0x1OsiHYP0WiU08xF5andbsfAwACnSvv9fpjNZuj1ekSjUaxfvx7jx4+HyWTChg0bWMFJ8UIPDTYHl8vFcwsp61UqVZY3aTgc5vR9nU6HSZMmYerUqTxGOp0O4XAYkUgEVquVq5ATCUoPIPLy8lBfXw+j0Yh0Oo1QKIRYLMb+vPn5+XC73XC5XFwwjOYeCQkJCQmJXR2SuJSQkJCQ2C2gUqlgs9lgt9thsVjQ2dnJi1YAXHwhHo+zkosWvcBQZeVIKeKkqBEXwkRi0AI2dzEs/k5FWgKBQBa5oNOqhxABOp0OhYWFrPYitRhdFx0zl/zIbftwiiqCSMCKpIJIbCiKwun0tK9Y0VoktYiECgQCXEiFlJMmk4m9GsU2DEd/UDuoWnl/fz/23HNPTJ06FR988AGnrpKnocPhYKJOpVIx0WSxWDgFmYoakaqLFvHJZDJr/EhJKLZFVJVSHIjHySXVSE1FhBORL5sIGTXU6sHzOZ1OuN1urkDd2dkJq9WaRUqS0szhcMDpdMJisWR5VtJYp1Ip9uxrbW3NIuaMRiMKCgpYzUWVp0XyPjedV7wGSi2nY4pp8KJnJR2HUqfFKs+KMnj9qVQKkUgk634hkHqM2k3xQmpaMe2Y+pt+qC2UEisWAKJrpfbR/6SoFElrqqpMhLOofqS0dVEVSKQa3UfRaBTV1dX49NNPR1Xf5T5wEPvCbrdz39NYKIqCUCgElWqwynVRURFcLhe6urrw9ddfs0UAkE0ekw8nEcDiHEEEGM2NpPQTXyMiT/SSHSvofHQNNO8RiDQnEo/GV9yHCMdQKASHw4HS0lIuyCVWOicLDarOLZLLpLgnEEFObaP7gO41sm2IRqOsxgQGvVtXrVqF6dOns5qcqpyTb2R6DMSl0+lEKBRiohkA+vr6kEql0NPTwypeaqvNZsMhhxzCcyqpYAsKCmCz2XjsREJfo9Ggr6+PlZviD8Uynbu5uZmLAOXOLRISEhISErsyJHEpISEhIbHLgxaeTqcTer2eiTOTycREQCKRgN/vZ69GIt0IuSSjmPoqghRmmUwmK108lUohEAhgYGAATqczq1qzeGzybEylUnC5XNxGrUaFQF9P1rmcTifKysqgVqvR1dWVVZBHLGJBfSD+T6/nXqP4v5gWKhbLyO1bImuJDBTfm0vqAoOESSQSgdPpZK81ej2ZTLJSkc8xzJiKRHIoFMLGjRsxZcoUTJ8+He+//z57ssXjcXz11VeYNWsWE0xEcBCROTAwALvdzp6RdFzyKfT5fFnKVFE1Sn0pqjXF17VaLWw2GxMDogqMPBCpn0RCQcGmlHubzYa8vDzY7XaEw2GkUil0d3ejsrKSSQqyDBAVf1T5l9SeotJq/PjxnKZPfe10OpGfn8/jQ1WWqSBHroqX+o6OTTFNVcCBQXsGsXI79QGl5lLqK13r4HFVWbFCymMxLZ5Sb4kwNZvN6PvWK5HeO6zlwrfpsoqioK6uDqFQiJXLFL+5vqN0TaIajwgsIngAZKWGE1EkKi5JZUyenKFQaFg16nBxPtxDCLvdzoSeqGyltuXl5XGfdXR08PwgEk6JRILnkdLSUijKoC+sWFWc+prGjFSvNE+K6cs07hQnY1FdksqaCDJRuUyWD6KyM5dYFe0pHA4HDj30UOyzzz4cKzabDcFgkNs5MDDA3sPUTqPRyIpYIimtVivP5bQPEc8ul4ur2RPRR3NLMplEY2Mj1Go1P4SiGCJVdCazeXK3sbERiqKgpKQEiUSCH2bp9XpEIhH09/fDYrEwYb/ffvuhvLwcmUwm674Xi52Jqm+6/+LxOPr7+zkeROUuPbDp6elhT1k6PimTJSQkJCQkdnVI4lJCQkJCYreAXq+Hy+WCwWBAb28vwuEw3G43L0qJ5HE6nQgGg0zc0GIUAKurRCJBVBSSwnI4UouqwY5YjAWbCCEqREIef4MLeqLvBlPGNRoNKioqYDAY4PP5uEKzmKKbS7gQRKKMziuSb2JbCLkKJ7EPRHWhSCqIpCz9iGno4XCY0y7j8TiTYORFuDnQuWKxGNatW4dZs2Zh+vTpKC4uht/vh91uh16vR29vLzo7O7ngDC3Oxev2+XxMzol9RyrQ3LT54QhgUZ1H7R8YGIDP5xtS5Vr0iCSPTLEv06k0MkL186KiIrS2tnIl4L6+Pq78bbFYYDKZWHXY29uLeDyOeDyOiooKmM1mbiswSFo4nU5MmTIF69ev58raVKQqkUgweUXFa5LJJDyewcI5FGekoKQUVFLLEilCad6kdNTpdByLkUgkS0G3qW9VII0tqUCJYKIYotR4k8mUpZAV20bxmUuYU3uomA21q6ioCFqtlotz0flpPMX7RVEUJj8pbgf9ObVZ5BYRrrm2ETTfABhiHzFarItELf0uWiuQXyuNIZF+RNLnkn2kGK2trUVlZSUmTpzIavS6ujoEAgE+h6gap36PRqMcx2r1YMXznp6erHlks1CpYDQYEY0lODbJm5TaF41GeW4Q761cQtrtduPwww/H9OnTkZeXh0gkgu7ubgCD5GskEuG+I4V3JpNhtSwRy0ajkccxHo8jEolkpZoDQDAYhMPhgMvlQiAQQDQa5bk3lUohFAqhvr6eVd95eXlMZA7OQZsn/eiaDQYD3+Mq1WAKu8vlgt/v5/mkqqoKM2fOZGKRYtRisQyZmwe7fVORpby8vCHF18iaQazMTl6tarUaRqORyU4JCQkJCYldHZK4lJCQkJDYLWA0GuF0OmE2m9HV1cWFN4xGIxNHpLKhSr/JZBL9/f28YM7Ly8sqPiKSGcCmKtNEVFBKIvn+kfplOOUiAG5Pfn4+F3AIBoPo7e2FXqeBktmUim2xWFBTU4NUKsWVcYkMoQWvSJiI6iexajadN1eRI/4utjdXSZmb5iqmUpPCiQhL6hPaj4ghSk2mVG1KV+V+3czYJpNJNDc3o729HePGjcOxxx6LJ554AtFolD3v1qxZg+LiYtTW1mL9+vUIh8NMglH7iFQgNZnRaEQsFmNCWvQ6FS0EMplMVuEVWvATcadSqbKUidRmOjb1q5hmDWQTwqWlpWhpaUFnZyerJIPBIKtERfKX3kPEFbWfyFoag7y8PBQWFnKBGLvdzjFHRLvZbEZBQQHi8TiTkhRjRN4Q4UtkGBWIycvLQyKRYDKEYoKUY+I9Q/2oKBkoCjgexMrmFG9Wq5XvVyJDiZgT+zCXqCE1HfW9wWCAzWZj30/y/8tkMtyXuUpHillFUfjajEYjpzOLFajJm1C8TmpD7gOL0SBaDBBxRPcPpYZTzKrVai6uQkq8PfbYA6WlpcjPz0dLSwtsNhtUKhWnSieTSTidTthsNkyaNAnl5eUoLS3FG2+8gZ6eHgQCgax0eJobaa6jcSFycEugAmAyGaELR3nuoL6i9HSRzKT+or4kdaDVaoXX68WECRNQUlKCqqoqdHZ2oqWlBeFwmK0NxPcDgNlsZk9Yp9MJRVG4WjgVaBNTo8lTlGwOpk6dCmAwjZpAcwewScnvdruRSCQQj8c5zXwsoLkmPz8f+fn50Ov1qKurg16v5wryVqsV1dXVKC4uzlKl5j5cE/8Wq7bTfEUWI+QDKj7AofgWH8BIf0sJCQkJid0FkriUkJCQkNgtYLPZYDQaoVKp2NuP1DW0GBP9y6xWK1fApiINYpEWIDulWiQfRJICAJ+XvMpo8UvvFVWKROQByPLgozRcm83GBYSqqqrwzTffIBgMIh6Pc/oj+TISsUALVSLYKL1UVLzlXpOophRTz0XkEgjURvE1UiERiUf7i2mnFosFHR0dTHyJ6aajgfoulUrB5/OhpaUFJSUlOPTQQ/Hqq6+is7MT1dXVsFgsCIVC+Oyzz1BeXo7i4mI0NDRkKego/ZE8Jb1eL/x+P6eDEkT1EinbADBpJKZg6nQ69p1sa2vjvwFkETIAOEWdlbjKIAFlsjqZWKqpqUFHRwd7mYbDYZhMJvZ4pLZRDFPadygUYnVkIpFgoobaaDKZUFBQwKQ6VSbX6XScQm+xWNDT08OFd6gyOylUqdCMwWCAy+VioovIaGqXVqvNUmoRIUzXTqQtxY7dbmfPSFIxEpGyiezcFLPigwNCLjkMgCtiEynV1NSEoqIilJeXw2KxIBAIIBKJsAckjTOQrbKldlAKPxFANK46nQ7JZDIrzZx+cpXQo4HUmslkki0Q6FotFgsXuaIxSaVS8Pv9WL16NQoKClj5OWXKFCiKgtWrV/N99tVXXyEvLw81NTXQarVwuVzweDzQ6/V49tlnEY1GmdQi5aXFYsnyAyV1cjwez3qwMxYY9AaelyieqKAOKZFFMpjS3+kcRCR3d3ejvb0dp59+OhN9PT09+PLLL3l/ikOVSsVzZDweh9FoZK9cGi8iLkWrApVq0BeXiGK9Xo9x48ZxNXsxXbyoqAiBQAB+v59Tsqm/LBbzmPoGAKxWKyZMmIDZs2fzQ6fm5mYUFBSgvb0darWaC3GJSvfc+0AcE9GjuKurCwaDASaTiT/ryM6B1Kf04KW6uhpffPHFFsWuhISEhITEzoYkLiUkJCQkdnmo1WpWFDkcDvh8PlbE0YJc/J8Wd1Sgx2w2s3pKVN3lqhTFStS0uCa/NCJN0uk04vE4bDZbFhEqEoWUctvX14dYLPYt+WVHLBJEbW0tAKCkpARFRUX45ptvEI/HkclkmIwiQpDOB2zygRMJFNETTySAxCrTuco1sU+p3UQuEDFJBCT9Tmo8MU2V/CUpVfbzzz+Hx+NBTU1NlmoQGFRlDUeEiH+HQiGsW7cOe+65J1wuF0499VQ8+uijXASIyMMVK1bg6KOPRjweR19fHyv1KAXW7XYz8UuqTJG4JMImFoshEokweUQxEgqFOLWWCpckk0k4HA4+D401EYexWAyxWCxbGZXJoLWtDWqdCVarFUajEWVlZaiurobP54PP5+O0ca/Xy3FL8UoedOFwmNOnqfATqeOooEc4HIbNZmNFH8V6V1cX4vE43G43WxdQ4SkiqSmVlRSapNgSSSZSdJHymBSjYoyJ95SoKiTyk45HaazU73RsIryo+Ay1T0wXp9+NRiOrDru7u6FWq+H3++F0OlFaWoo99tgDRqORqzZ/8803aG1t5YrbRGKR/2E0GmUCke4/IvBIDUv7EoFG9yPNF2MBqSsdDge6urr4XhLv/UgkkkX8+Xw+vPXWW1AUhX1N//vf/zIR6/P54PV68eWXX2LChAnwer0ABgnXyspKFBUVceV1Uh/Sgwci6qPRKMd3rlp6c1BrNDjq6KPxzao1WLVqFWKxGCsbxTR/mhdz1eM0D8ViMUSjUWzYsIFJfIvFghkzZjBRS6napNBMp9NMUFOlbjq2ONYGg4FJ7nA4jFAoBJvNxjGn1WrZa5jem0gkYDQa4fF4WLFKXrk0H4wV9FDHaDRi4sSJiMfjyM/PR21tLYLBIM/fdL9Qf4nz7WgK38bGxqwidUTIk4VETU0N25FQxfHcbAMJCQkJCYldGZK4lJCQkJDY5UGkgsFgYAUMpWIDYGUZqXBo0UyKTNpXXDCLKkn6ndIuKUWaSCBFUbgSMqWXEsmTCyKuwuEwKzN1Oh2MRiO8Xg/iA0AkEoHL5UJlZSWr7Uj9Q6mC9CMq2kRPTZF4BDaRMZT+R4SSmAouej3S4nc05Sb58Ym+lvQeUn3G43HEYjHMnTsXq1atQjQaHUZxOZS0zCVUY7EY1q9fj6amJthsNhx++OF47733sG7dOlitVgCDqtsvv/wS5eXlGDduHAAwsQcMVgM2Go0oLCzExo0beRzF1GuHw4FkMsnED/Vvfn4+75/JZBCLxVgxFg6HmcAmD0K3280kHHkt0thotVooGCSVBtIq1NTUMHExZcoUtLS0cLo1eT2SUpfaGwqFEIlEEIlEmJAHwNXGiewg7zyqdgyAj2O32wGAFWeUoi1WMo9Go7Baraw0E9NUqbAQ9ZfJZEIwGOT7guJLJEAGVZWDxGVvby9KSkqYkNVoNEzQih6PpHDV6/VMsNE9IZI3pLJ2u91Qq9Xo6elh4po8G0kdd8wxx6CkpAR6vR4HHXQQPvzwQ7z55pvo6+v7//b+PEqOs0rzx5+IzIzMyD2z9kVVpX2XZctG1tjGAgsL2tDuxtMNtBvM0jDtEQxgmuMxp9nMDGbge9ozPQMeeg5t6G72HwYPNgavssa2vEnWbpVUkmrfs3JfYv/9kXVfRaZKG2CVZN3PoVpVmZGREW+8Ee544rn3Ea5UEh19Pp9waLv7MbrPMds+mX4uy7I4ZkK4PEO1uPuBQjabRXd3t9jeYDAo5i+Ju+70dhL0AoEADhw4gPHxcViWhVgsBsdxUCwWEQqFMDMzg2eeeQZ/8Rd/genpaYRCIYRCISQSCSEEukOU3MnflFTvHpPzwev1oqurC+l0GgcOHBBiL63HnQjufrjj7stIAU0dHR2IRCLi2qqqKhoaGrBw4ULs378f8XhcCHDU/7FcLqNQKIj1Ul9VEh8DgQCSyaQI2KJtIpGPArhisRjGx8dFewoKDKP/7oyPj4vPni2Uyc3AwICYl1dffbV4uHPgwAH09PSInq2VSkWcw26hn+ZhfY9loHpu9/X1IZPJiIdJ6XRatDmpb+kwPT0trs/ne5wZhmEYZr5g4ZJhGIa5JCABcGRkBDMzM6KPF90Ak3uIBEMqkwuHw4jFYsJFRoJZfRkeQSIC3SBS37tgMCjcZPUCX72j0TRN4eajktZqSEVZ3JySUETuM7ezsd4lSGJmfRmhW4QFUNNfjkQBEgDcgoH7ppjKit1lzrQMleGSOEWCDglh1FuUbso7Oztx4sSJOVxbc4uW9eM+Pj6OvXv3YtGiReju7sYdd9yBr371qxgZGUFHR4cQyB5//HFYloWmpibkcjlxI16pVDAzMyNEDE3TRNmoJEkiqIdeo22hfQqFQqKskoJMAoEAWlpaRKoztQug1gNuoY3cgKqqwrEMVCwD4+PjaGxsRCAQQDAYRFNTE9auXYvJyUlMTU0hn89jZmYGiURCiKTkGHULOuRWo9JwcgD6fD7E43GkUikxjiSIxuNxRKNRUf5cKpVQLpeFg4yEfiqB1TRNiJ7k8oxEIjUi7szMjJg/7vlB88Vdkkvj7p6vbpemO8neLWC6jw+J5h6PB6FQCIsWLUIymcThw4eRy+XEGJEoViwW8fLLLyMUCuH9738//H4/enp60NHRgVKphN/97ndijrvPXyond18baN7T+ekWqMPhMIrFIrLZ7Ow6znDxcpHJZMSDjKmpKXR1ddU4rN0hNm6Br1QqIZfL1WyX1+tFc3Oz+P348eN48cUXccMNNwjXMPU6pPWT65zGl8Q7Koum65vbLXkmvB4P3vOe92Bichp9fX1CjK5/MOE+52leuK8Hqqpi3bp1eNvb3lYzFqZpIhKJoLm5GY2NjaK9Al036b8L8XhciMvFYlG4LEkod7t73a0H3A9y6Bqv6zoCgQDy+TwOHz6MJUuW4PXXX8f4+Dh6enqqDxVymXM74LOYpomJiQk8+eSTWLVqFQqFggiSovN4dHQUiUSiOq6u67Z7HXTu0TZPTk7i+PHj4mEdzQUSdclFns/n4ff7xYOQc23nwTAMwzAXAyxcMgzDMBc17htfCrR59NFHRSloJpMRN+Mk/lE/MnI01QfQ0PrcN8/ufo66rouUWlqnYRhCFA2FQnOuk9ZLN+bhcBjBYFAEsFCgCCW+jo+PC0GIhCl330bgZBK6W3isDYE56ZqsF2SppyDtW71YRzfN9e4nt+OuXuglUYnKyWm8pqamEA6HawJgTke94Erbm81mcfToURw5cgTxeBzXXHMN3v3ud+MXv/gF0uk04vE4gGpZ+VNPPYXNmzcLN6070ZwcihSmQa46SiQmgYq+m+YLCWf0Q6ExbsHFNE1UKpWa0B46fkDV1RkOh6FVijBNHbncDI4dO4ZgMCjcVEuXLsWJEyeQz+dRLpfR399/yvfRPlAJOzkS60VzwzAQi8WEgEql2YqiiPlHx7pcLmN6ehrT09OIRCJCnCV3HzlLyeGayWTQ1taGYDAoErvpYQGdG24XXXUueWqcuVSGTyXgNPdIiKTvpx6vblcgLa+qKrq6unDVVVchGo1ienoaqVSqpseopmmIRqMijf25557D+vXrcf3114vxW7duHXbs2CH2gRzNbvHKfb65S9SBqlOaAmcSiYQoU3bP4TPNeSrFLpfL6OzsxNDQEDo7O8V55D6n3G5Aes/v94sxorlKy9B5t337dgDAtddei+PHj2NwcLAmWCsUCtU8nOnv70c4HEYoFMKJEyfEXDgX0ZIIhYJoaGgQYqN7m90PDdwPRkjgpGOQz+dx6NAhfPGLX8TGjRtxww03iL6NVP4eiUSQyWQQDAZrHIamaSIQCNSMi3s7aA5OT0+L/a5/2OQOisrlcohGo/B4PKhUKhgaGsLatWvR3d2NiYkJ9Pb2opCdOufxASD6WrqFaAAYHR1FJBLBwMAAdu3aha6uLlEG73Za0sME6iNKDwx2794tXOfkjo9GowiHw8hkMmhubkY4HEY6nYZhGEIcpVYFDMMwDHMpwMIlwzAMc9FS78pzh6cA1ZJYKrWk0kESZAzDgKqqiEQiACBKcuudPm7XjaIoIjHW3ZONHI+0DW6h0C0guteTSCSEsFCpVKBrZXHjTom3vb29MAyjJgGW+hO6HVdu4fF0gkJ9vzL6HLkqqeyWPk99NetL0N1jQj3gqOSS+oiSwEbfS6IuCbQnt+XcxQ8SQIeHh/Hyyy+jqakJK1euxK233orx8XE899xzUFVVOFhTqRR27tyJt73tbcJVRU5FEi6oZJUcSOQ4InGGji2JRZRAT/3wKJl6YmJCCFluEZMcXm5ICDWkauqz3+/H5OQkent7EYlExJy86qqrMDY2htHRURSLRQwNDaGnp0f0rqRy10AgIJyWNEYkfpBwaNs2kskkpqenYVmWSBenkmBymVH/TuqpmU6na+at41RDekjkzWQysG0b2WwWmUwG6XQalUpFlNSTK8zdz5TGksanXC4LIZjGzx0wRb0syWlJx4b2y+/3Y+3atbjpppsQi8VgWRZee+014T6k9gqjo6OIRqNQFAWOU+0l+dBDD2H58uXC1djU1IRoNCr6H7qvLyRwuc8b9/kBVMO2aMwlSRKhWo7j4EyWS/f1wTAMHDt2DBs2bBAlxO3t7UKspvYDNKZu1y2AmoRoavFAgqbjVJPqn3vuOXHMaJxISKQwMxILp6amsHbtWpTLZYyNjQlXn3tczowESaq2Wli6dCn27NmDcrksrlUkeicSCSiKIuZjLperaadh27YQ1A8dOoQTJ06Ia+jixYtFOwSfz4dCoSAE/WKxiEQiIR7S0Hnt7qEaj8eRy+WQy+XEfwPo+NI8DYVCSKVSyOVy4hqWSCRED1Q6PuT0P99Ebvpv0rFjx9DQ0ICenh40NDTgwIEDItBs+/bt6OjowFvf+tYaVywA0ZOXgohUVUWxWMT27dtr3PqxWAyhUEi43ikFXVVVjI2NiQdr5LJmGIZhmEsBFi4ZhmGYi5Z6kZHcTnTjlUwmRUgO3VhSH69KpVLTtw44mQ5O63PflJMARQ41t6OSRBoSB8hxVl8O6S7hpLCUXC5XFYgcG16X26ZSqWBiYgK2bQuh1HEchMPhGsdafWqzWzxzfz/dgJMYR4IQOdDIRefuNUfbSr0s3d9LohIFbZBripw+QFXIIYfTzMyMKOE8KX6QYFMbhlR/fN3vpdNpHDx4UKRbNzU14ROf+AQKhQL27t2L7u5uIez19/fjwIED6OzsrBFbycVH5c4k7CiKgmw2WzNObhcj9c5rb28XYhqJcHRsKXjG7dYjURGACA4xjUq1FLyooaOjA6Ojo+jv78fSpUtF+fI111yDJ554AoVCAel0GrFYDO3t7UIgIXcnbS+lXdP303fS8UskEqhUKsI55nbk0v40NDQIIZOcjiRqR6NRIdJRj8KpqSmMjIwIZyE5kd1zjkSxRCKB1tZWEfRDYnAwGBTnDQnzJPqSa5IcZTQfaPkNGzbgL//yL4U788CBA9i7d6+Yd25XZ/3cOnHiBB566CH81V/9FUKhEMLhMOLxOMbHx2tK2usdxnTcaRl6YELlyT6fD6tWrcLhw4drxKVzwbIsTE5OwjRN4bylQCm3sEvnHr1GLR2ojQQ5y92hXYZhIBKJoFgs4tixYzVuQ3IP6rourm99fX2IRCJYsmQJ9u3bh2w2K7bz3PsfOjANA4de78VLL70kvoPGafXq1bjppptw7bXXor29XZxv2WwW/f39eOmll1AqlTAwMIDe3l6kUikRtERtHQ4fPgxFUaCqqriOkUi3bt06hMNhvPDCC2I+UcANnSuKomB0dFQIzyTg0jiQmz+TyYjzm1qEkKt69+7dWL16NUzTxIoVK+CYJTy/89XzOvbAyeuD4ziIx+NQFEX0pCyXy/jpT38Kj8eDjRs3igcPhmEI4ZJEf0mS8Oijj2JsbExcw6PRKLq6uuDz+bBv3z5Eo1EUCgURBjY5OYnu7m4cOHDgvLebYRiGYeYTFi4ZhmGYSwISS8iBRq4ox3GEKAVAiAsARCkuACQSiTn78VEZJbnL6EaX3G3UM43EHXK7uFOZ3QE31GeTIJdMY0MCtlkRN8Lk3HELi4FAoCap3F3+7f6bRBXaF3fpp9ul5ziO6KdJJbAkGLkFDPf6AIiEbHJn+f1+USZNoRRu8ZNErHg8XrPv54pbJCFhZ2BgAH19fUgmk+jq6sJdd92Fr33tazh27Bg6OzuF03bPnj2QZRnNzc01QgUJfn6/H6FQSKybBD1JqvZYTCQSIsmZxoYcXSQWUXltfWk+iWduwZfcWrFYDJZpikThhoYG7Nu3D7IsY8mSJfB6vVi7di1GRkawZ88eVCoVDA4Oin0hh1axWIRlWeI4Ujo4HU8AYt55vV6oqip6+bnfk2VZCCYk0pM4RseAnJHk7lVVVYQt0XiRcEbzhdbb1NSE5uZmNCQiGBwcgGmaIq08HA4LIdndF5NaD5BYSnOJXI2xWAzveMc70NnZKRyCzz//vEhWd5937e3t1d6idU66p59+Gj6fD+95z3vEGLkd027XqHt+0HlG20r9HwEIVxu9du4iXxUqi964cSOGhoZw9OhRLFy4UOwLBcu4S8TpWNK2k3jlfljiTkB3HEekuVOvXXIr+nw+TE9PI5PJ4Prrr0c6ncbIyAh0XT9lX85WMm7ZNh588EH84pcPo1wuY+HChchms1i/fj3e/e5347rrroOiKMIFTDQ1NWHx4sXYvHmzSE63bRu5XE70a6SxpVYUkiQhkUggEAgAAI4cOYLBwUFcffXVNS0+aM7TuZtKpTA1NSVcjPR5evDg9XoxNTWF0dHRms/m83nx35bx8XF84AMfwNDQEA4ePIgF7Y3ndczp+DU1NaFSqaCpqQmRSASyLCORSIjS91wuhxMnTmBoaAibN28WLmN3ew6Px4Mnn3wSv/3tbyFJEkqlErq6urBhwwaEw2H09/fDtm0sW7YMBw8ehKZpmJycRCgUQqFQQC6XO+9tZxiGYZj5hIVLhmEY5pLAMAwRYkIin7vsOh6PCycPCTVuh1c4HK4RGummmJyFVBJLfcLIkUYiCFB1bEajUeE6A2pFN+pBVigUhNip6zqCwSDiiQTKhSxse0YIoOl0WrhB/X5/jRhKN9Ru15VbcCXodQCidJZw9+gkVyMJsG6HFy3rdnSSqETl4XQMyPlK7lYah2QyKcIzTnWhnSrsuB2v9WOp6zpGRkawc+dONDU1YcmSJVi8eDH+83/+z7j33ntFb8BoNIpisYhDhw7B6/UiFovVuB8ty0I4HEZzczNGR0erKd+zTkJytjmOg0gkIoJeDMPA9PS0cGQ2NDQgkUhgampKbKthGEJIIDcmzaFCoYDjx48jEQtDmhVKRkZGRIAIuQWXLVsGVVXxlre8BalUCv39/XAcB8PDw3AcR4R00FjScSMxnQQ1Ep5pv939+9ziFolghUJBiFt+v18IhzQnqF8gzb9QKISGhgYRykMCZjBY7WtIAUB0PsqyhIaGBhzvH0Y0GhVltu5AHhLnaQ7IsiwCgNx9MKlsnpZ96qmnhPgLQJT4KooiWkJQP0s6RyqVinCmUY9COo8oTZx62NIP9QskoRYAJicnAVSd2R0dHZBlGcViUWzvmboi1DuzKbG6p6cH69atw/bt2xGJRNDS0lLjlKVxonJqAEJ4pDGg40YuQrpe0LWIyoWp1y5QFU6PHTuG9vZ2NDY24tVXXxVp6/XbXd+Coh7TNPGbxx5DOp3GsmXLsGXLFtx0001YtWqVmBPUr3OucSEx7/3vfz+2bNmCX//61/jZz36G48ePiwcvzc3NCAaDyGazyOVyojcvCY6/+93vsHjxYuG2Jsd5pVIRzk7LskQ/3GAwWHMdqFQqGB4eFtc19zXX5/NB13WUSiXs27cPzc3NSKVSkB39jOMyFzTeQ0ND8Pv9eM973oN169bBsiz09/djeHgYjY2NmJmZwUsvvYRdu3bhyiuvxJVXXolkMgmPx4OxsTE8/vjj2LFjB3Rdx8KFC3Hrrbdi4cKFkCQJY2NjImV8amoKqqriyJEj8Hg8aG5uxmuvvXbeQjvDMAzDzDcsXDIMwzAXPdQrT9M00TeNRJCBgQGUy2X4fD4Eg0GUy2VkMhmEw2FRFkuuQXcvP7ohd5cCkxBHDhcS7Ki3orvHozvZVZKqoRv5fF6U9+m6LhKg/X4/vB4P/H5FuJrIzUbiAjnd3IKEu5SRcIsftA10A0437rRf7hJzwu3icgtWbiGPBDkSudxhRG5xjEpX6Ri1tbUhHA6Lm3/6WrcYS3/T73OVkFuWhXQ6jUOHDiESicDv96O7uxsrVqzAl770Jdx///04ePAg2traRGDHq6++ivXr12PNmjXIZDI1Am00GsXIyIhwsVEpta7rSKVSCIfDoqzS7dqUJAmRSASlUkkcN4/HI44tuQrpM9SHj8o54ZxMMz5x4oToa3fw4EHouo41a9ago6MD1157rSjptG1btBBoaGgQwho5rWg+0/aRsOl2ILuPOR1jKgt3tz2gz9KYkOOUnJt0nnR0dIiAFL/fj2g0ilAoJMbDHf7i90no6VmI3XsOCHdgLpcTLR3I/euej7Sd7lJx93lfKpXw7LPP4pFHHhGiLc0hEpFJbHU702hMTNPE7t27ceDAATEuiqIgFouJBxVUnk/b4T73crkcZmZmxAONnp4ekdDuPifnwn2tcS9bKBRw5MgRXH311WhpacHRo0cRCoUQi8VEH0iaw+55S9tA1ydq5UDBQSReappWc3zdiehHjhxBoVDAddddh5GREYyPj4ueh3Odo2fEceA4NiKRCK677jp87GMfQzKZPGX/6RpLx4yEWHfv4ebmZtxxxx3o7u7Gd77zHQwODsI0TeTzeaiqinw+j3A4LOYxPXSiUu5EIoGOjg7hkD58+LB4kEVl5hSSRmFZlUq1pQP1xnXPGxL/qdUEbUexWIRsa6cbkdMyPDwMSZLQ3t6OXbt2wTAMtLW1oaenB8ViEcPDw9B1HUeOHMHk5KSoBDhw4ADy+TyGh4eFcGrbNjZs2IB//+//PZqbmyFJEg4dOoQdO3bgyJEjiEQiWLBgAUZGRkSLjYmJid/LEc8wDMMw8w0LlwzDMMxFj+M4IhChUqkgFothdHQUjY2NQnwgsYlubEOhkAg4oRtSEjxIhHOXhdLrbochlYmTQ40ETcdxEAqFRGK5ZVkoFouYmZkRDqN4PC4CYarrk+A4J5Obye1WL9YAtSFE9S5Id99FSoV29w8EapPYad1u4ZGcmVS66y6tJden2+FJQUfusXOLwABw4sQJjI2NoaOjA62trRgZGREBFg5qBRE39X+7XZfj4+PYvXs3vF4vbrjhBvT09GDlypX48pe/jPvuuw+7d+9GS0sLEokE0uk0XnzxRRiGgeXLlwvHHAk7qqoK8dHr9aJcLsM0TRSLRZEUTyW6NBaSJAknFvXEI+Fc0zSRIO4ubSWRV/HJwOyxIwGkv78fmqahvb0dhw8fBgCsWbMGa9asQaFQwPPPP49UKgVJkoRw0draKhxkNJdpDpCgGg6Ha8qtSRgikd0taFJasttJTO0WvF6vcKOReB0IBBCLxYRAS67EVCoFTdNE70h6LxjwoqWlFY2NjcjlcvD7/aLPpbuvIInkNKb0/eQSBaoO3/HxcUxNTeGnP/0pSqWSCA4icZjCl+gz5AR2u2JpvEgQBCCuGbQ/dI5QiwR3OfnMzMxJYdbvR0tLC/L5vHCTVsfw3K9lJDiPjY1hcHAQa9asweOPP47Dhw9jzZo1UFW1pg0AXWNIKHYnr9PYlctleDweZLNZcZ0KBAIiWIvmxrFjxzA+Po5FixbB4/Hg2LFjok1G/XXDfT6eFklCJBLFhz/yN/jrv/7rU3qNkjM1n88jkUjgF7/4BZ5++mn83d/9HZYsWXKKE9Pr9WLz5s0wDAP/43/8D4yPjwvhna7LwWAQU1NTQsil89owDAwMDIjzoVAoiH2hdgeGYYh+sl6vF6VSCdPT02K7g8FgTQsCcgG7+53mcjmE/PFzO+B1x35oaAixWAzhcBh79+6FoiiYmZkRAvqRI0ewbNkyUd6dTCZRLpeFuBkOh3HgwAG0t7djy5YtaG1thSzLmJycxHPPPYf+/n6R2P7aa6/h0KFDIjTt2LFj573NDMMwDHMxwMIlwzAMc9FDjiESwpqamnD06FH4fD4kEgnhtqR+hpRYSz0OKZ3WLdSQE4uEBBLsAAjholQqoVgsiuAQEhDI7Unr0nW9pmzU5/OJEtaT7i9JBPUEg0E0NjYKsYtEG9oucilRKSW5i9zCpVv8oe0gYRY4KWrUOxrdZajkVnJ/hvaLxJF656fb0QlAbDuV8jc2NuLaa6/FK6+8guPHj88ewLldaXO5Ld2iqaZpGBoaEoFGmzdvxrJly7BgwQLcc889uP/++/HCCy8gGo2K1OJdu3ZhZGQEq1atQigUgiRJ4oa/VCrVlHW7k5vz+bwQveg9Ej+p3J+Wp9CfhoaGmj551AsxGAwiGAgDOCnMkVg4PDwM0zTR0dGBvr4+GIaBq666Ctdccw1M08QLL7wgAoTGxsaEUEal0zRGJMDQPpHgUiqVhMORRFTaPmpHQPOZBB8qu3U7+mhcqN8rORFzuRzy+TyAqsgTCoXg9XpFewQ7EkR7uwdLly7Fzp07hdOuUqlAVVUxt0jMJTGKQksoIIY+89RTTyGVSiGfzyMQCAhHL4UQ0XlsGEZNCweakwCEWEklxiTIu0OX6Fyk8aXXyfUmyzLy+Tza2tqQSCRqXIru8+pcoHOnUCjg8OHDSCaTuOKKK7Br1y7s379fOHNp7OkhA+0rCbUkvLsd4FQSTftNwi0JV9RztaOjA0ePHsXo6OgpCdlusfJs++WRZXz4jjvw3n//l+J7IUlCyZUkCclkUlxrt2/fjqeffhpbt25FJBLB9PQ0FEVBa2urEMC9Xi/e8Y53wO/34x//8R8xOjoq5i0J9gDENblQKKC5uRkf+chHUCgUMDw8jFKphGw2K+aNO+CGPuOeC6ZpIhKJiN647h6uABAKhUQbCWol8PvgOA4OHz6MFStWIJ/P48iRI+jq6oLjOCJMbnh4GK2trVi5ciV27dol2l3Yto1du3ahpaUFoVAImqYhn89jcnISTz75JA4cOIDm5mY0NTVhamoKg4ODAIBoNIpDhw6dd5AUwzAMw1wssHDJMAzDXBJQyWgul0N7e7sQUtwiHwAhGpJzrlQqiURid29D6gFHIk0gEEAwGBSONgqioRtpd8ANCUX1zsRIJAJVVWHbtijxpVRzjwzMzMwgl8uhpaUFTU1NNaWT5JJzu+OA2h6WbjHTXfJO2wugRmQk5uov53ZhklhFYTzk8iKXE7nTSNCjhGUSBSqVCsrlMn79619jaGgIiqJg1apV1b6Qp3FUzlU+7n6f9pf6z1FPQhLKOjs7cffdd+OHP/whfvOb32BsbAyNjY1obW1FNpvFjh07sGjRImzatEkcNxIsSZSgoCUAoqSUjrfX60U8HkdLS4tI6CU3o+NU+2KGw2Hk83nhyFQURYTZhFQF9Y0PSfienJyEpmno7u5Gf38/PB4P1q9fj02bNsG2bezcuVMESw0MDAiBnsaJQkcsy0KlUkEmkxGOSOrHR20KyL1LwjyJj3QcyW1KY0/9CEmYob6CqqoKxyR9P40BtUaoimoeFItFLFu2DK+99ho0TROOMCp/d7dpIDRNE0IgHR9d1zE6Oiq2X1XVGqGTRHz6HLkO3VDZu9s1506dJycrnTN0XSExMJ/Pi/AmXdexaNEiOI6D6enpmj6JZ7JczjW3aT9nZmZq2hwcPHgQx44dw/T0NBYvXiycwLStdHzIFUsuYUVRxMMTAKIVhKqqKJfLGBwcxOjoKHRdx1VXXSX6XFYqlZrrGG1n/fl5OrxeL9729refFC2rKxBzZ/fu3Xj99ddRKpWwePFi3HDDDTBNE88//zwefvhhTE1NwbIstLW14R3veAeuv/56LFiwoLret70Nq1evxm9+8xs89dRT6O3tRaVSgeM4QqSmuZFOp7F3714sWbIEK1aswCuvvCLEfhoTEnndx8QdTuZ+n1zXdM7quo6JiQkkk8nq/DhL788zYRgGjhw5gg0bNmBgYADDw8O48cYbAQCvvfaa+M6JiQmsXLkS5XJZ9PF9xzvegePHj2NychL/9//+XxHEViqV0NjYCI/Hg56eHoyNjWFmZgbr1q3Dnj17RCAXwzAMw1yKsHDJMAzDXBJUKhVxY7ly5UooioJUKiWCOMrlsnAnJZNJ4bDJ5/OidI5uSkm0cIsZXq8X0WhUuBopnIVcXhTKQyXZ7rJsCjGRZRmxWKwmPITKwkvFvOjNRi5F+jw56dx9Ketdl26HoLvHJH0X9barF/5ovfRd9X9TkjkJNfS6u/dffYI6CcLU/5IE5eHhYbz++us1/RJVv++U4JKzCZb1r2mahpGREbz00kvQNA033HADFi1ahKamJmzbtg3r16/HAw88gNHRUSSTSTQ1NcGyLAwNDWFgYABdXV244oor0NLSIvp2ejwe0RuVhCzqWUiiHTkoJycnRU9BEvVIMGhra4OqqmhqasKBAwfE8QvMCqLu/XD3B02n07BtGwsXLsSJEyfg9XpxxRVX4LrrroMkSXjllVeQzWZRKpVw9OhRLF68GPF4vCa8hgQ3OjfoPKA56RavyUFKwhyJMkBV0KGyYsdxEI/HhTBEZdnuIKBAIAC/31/jZKOHCH5/AIVCAS1tnVi7di1eeeUVMcbkICUR2C3cVyoVEYbldgqTIE8PHorFYs05QPPF7ZwkFzElsdN6yHlKDyxKpZKY3yRwUmsHEnpGR0eF4OvxeNDZ2YlsNouZmZlTnIpnor61AkE9TXft2oVVq1bh+uuvx6uvvorp6Wn4fD50dHQgGAyKY03n3+TkJJqamsT1wS1M0ThSq4TR0VEMDAxAlmVs2LABuq6jt7cXuVyuRqR0b+fpxNZTkeCpezBiGAZeffVV/OpXv8LAwAAMw0ChUMDvfvc7UcJNYWoU5lUsFjE1NYUXX3wRH/3oR0W4T0tLCz7ykY/g/e9/PyYnJ4WITEKpYRjIZDIYGRkRTstSqSQEUa/XK/67Ud86g66x7uurO9iNrtVuR3Iul5ttjxA652M/F5qm4fXXX8eKFSswNTWFHTt2iKAry7KgqipyuRw8Hg9efvlljI6O4gtf+AJSqZRwTh89ehQdHR1YuXIlstksEokEnnnmGezcuRNTU1NYuXIl+vr6MDMz8wdtK8MwDMPMNyxcMgzDXCbcd999eOihh3D48GGoqop/9+/+Hf7bf/tvWL58uVimUqngc5/7HH7yk59A0zRs3boV3/nOd9DS0iKWGRwcxJ133olnnnkG4XAYd9xxB+677z4hxL1RaJqGXC4nyvRaW1sxOjqK5uZmIXpQgAXdkNINvNs1Q6INuSRJAKxUKsJdCJwM7XH/kMDhdieRky8ejwtxiG7IyakWDodhWwFIqE0Bpr6ZmqYhHA4LUZTECHdQD22TW8yh9+iHSkLdgTHuFHK3s4q+g8RKd4kw7Zu7PyDtq2EYKJVKIqiCnF3t7e1Ip9MIBAKYnp4WQsrphI/6Pnpz9bp0C1i6rmNoaAjlchnj4+PYsGEDNmzYgCVLlmDz5s3o6urCP/3TP+HFF1+EpmlIJpNoa2sDUHV+/fa3v0U0GsWqVauwaNEi0e9Q07Qa9xq5KZubm6FpGnbs2IGxsTG88sor2LBhgwjMaWpqQmNjI+LxOFRVRSaTwZVXXikcYVUB81SRlt6zLAu5XA79/f1YtGgRjhw5Ar/fj9WrV+P666+H3+/Hrl27MD09jWKxiL6+PixYsACRSARerxf5fB6KokBRFFQqFRQKBeGEJWFVURThIiWBUFVVNDQ0iHMmFoshnU4DgBDtgsGgKEv2+/2IxWLI5/NCIKQ5DwDpdBq6rsMwjNkAHhnT01MIhmNYt26dcNuRszWdTiORSIjzgMa/PmzKHeZCc94tbNK5q6qq+N0dmEQiM1073MKeO4TL7Xim32kuUNAXlea3trZiwYIF6O/vF30h6+fyXMw1v92fsywLU1NT2LNnD5YtW4ZNmzZh9+7dGBwcRKlUQltbm+inS+XKVD7d2Ngo5pPb9Tg+Pi7CvyjUZcmSJZiamkJfX58o9z+fEvez4TgOUqkUtm/fjh//+MfVnqez200PZ4rFohBU3QIpcNKhmc1m8dGPfhQ33nijOIaqqqK7u/uM3019hn/9619j3bp1eM973oPnnnsOQ0NDyGQyogWDuy0AnfP0437o5P5vCQXDZbNZqKr6R3EwptNpvPbaa7jiiisAVJPrM5kMGhoaxLU1n89jamoKjuPgmWeeESJlR0cHKpUKAoEAhoaGMD09jVwuhyNHjiAYDKKpqQmHDh1CLpf7g7eTYRiGYeYbFi4ZhmEuE5599lls27ZN9NL7whe+gJtvvhmHDh0SpaKf/exn8eijj+LnP/85YrEYPvnJT+K9730vnn/+eQDVG+xbbrkFra2teOGFFzA2NoYPfehD8Pl8+PrXv/6Gbr9pmuLmLJ/PY+3atSJsgAQQKpWdmZkRN+3klCTHJd2wGoYhHGbkpKR+ge4AHCpDJVGRwk2AWlHO3X+QoCR0CgmCBFHaSj0HA4EA8vm8EEFI1HS7q9xuN3f/Qbfrkn6nm3JyEdLvJMiSM87dV9Ndak/ijdvRRy49WZZRLpeRSqVQLpcRjUaFQ6mjo0M4BGVZxtDQ0MmD59Iu3WLkXK7LuQRNWo6cZoVCAdPT05iYmMDmzZuxYMECdHR04J577sFjjz2Gn/3sZxgfH0cikUA0GkVjYyOCwSCKxSL279+PvXv3IhQKoaGhAdFoVBwfEnkdx8GxY8ewZ88eEczS19cHAFiyZAkikYg4Nvv370cikRDHIRQKYd++ffB5AMd2auYI7at7vDOZDAYGBtDd3Y2DBw/Ctm2sW7cOGzduRCgUwgsvvCDShgcGBtDa2opEIgG/3y/mSrlcFqKkoijCMekWZ9LpNPL5PJLJpAjKKZfLosxfkiTRF5OSlsmxRoE45FAk4Y8EM/pun8+HQqFQFVokH9atW4ebbroJjzzyiGiFkE6nUSgUhEOYHG/u/ppUeu52l5IDjhKiSYwlJyS5Qmk9hDtMqz5pm9oBEO7v8/v9OHLkiBCGHcfB+vXr4fF4xDWoRug/R/HydIK9ZVlIp9M4ePAgurq6sGbNGkxNTWFgYAAzMzPw+/1IJpMiMXvx4sXCcek+NyVJQiqVEv1TFUXBypUrEQ6HcezYMYyMjAh3er0DlLbl3N2WtZTLZfzmN7/Bo48+Kpyx4XBYiMEktFG4FR07mlf0kKmvrw8/+MEPsGjRolPESmqFQC0qqHUEPah66aWX8C//8i/44Ac/iFtuuQU33ngjHnvsMQwMDODVV1/FwMBATdgZXf/c10H3tZTGI5VKIZFIIJ/PI5vNIqz+cW6hKpUKdu/ejcWLFyORSAi3aKFQEKFYV199tZj7e/bsga7r4hqcSqXEf8sAoK2tDZJUTRg/H0cwwzAMw1zMsHDJMAxzmfDb3/625u/vf//7aG5uxq5du/DWt74V2WwW3/ve9/CjH/0Ib3/72wEADz74IFauXIkXX3wR1157LR5//HEcOnQITz75JFpaWrB+/Xp87Wtfw913342vfOUrv3dgwdkgEZHcZ5lMBqtXr8YTTzwhbmLdJeOUrNvQ0IBkMimCeUgAMQwDuVxO3OxVKhUhELoFEOrtSG4vEv3czkW3uEgl1yQMkiip6zpkyRFt8KgfYCwWQzQaRblcrgmCkCSpxglIwiSNAwk+7nJZ+hy5zuhmlkRHCi8xDEOUh5PwBJwsvSUnFImWwEk3JglFdBNNfQmp9JfcVIsXL8bo6Gh13dLJY+gWLec6xu7X5yqrpb+LxSJOnDiBfD6PkZERrF+/HqtWrcKCBQtw6623Yt26dXjooYfw3HPPoVAoIJFIiFAT6rFomiYmJiYwPDwsxDNy4VGJaCaTcTkJPRgZGYGu66LfHDlcqXyV0sUVRUFLU9Kt19aItPUlq9TyoLOzE729vdB1HVdccQWuuOIK+P1+bN++HUNDQzBNE5OTk+LYBoNBIdZ7vV5EIhHRZ7VUKon+lZQqTOdFKBRCLBaDoiiidD6VSol5T+cQ/R4MBkWvRJrzhUJBzA/qRzk+Po5gwItcLo909igSiQR6enqwevVq7N+/X4ieJ06cwIoVK0QZrrsNAc1Jmp8kGpKgTr1m3a49msPU2oHmPI2z231Jn6FSalq3u2cmlV5PTk7CcaphMN3d3Vi/fj2y2SwGBgZEuIvb8Xw65mrRMNe8dxwHhUIBx44dQzabRVdXF66++mrMzMxgdHQUY2NjQpym40APFmg7i8UicrkcbNtGR0cHWlpakMlkRHq4O7X9dOfX6bb1bMzMzGDnzp3CGUvBYtRHkwKaaJzdPUnp+krhS0eOHMEDDzyAbdu2YcGCBTXfs2vXLgwODmLfvn3w+/3o6urC9PQ0Dhw4gP3794uesIODg/jXf/1XPPbYYwgEAli4cKEIgCKHOm2j+ziQE93tjq5UKqKvb6VSga7r5zwuZ8MwDBw+fBg+nw+dnZ3o7OwU40PJ6PRggITbYrEotjcQCCAWiyGTyeD48ePiesQwDMMwbxZYuGQYhrlMofTeZDIJoHozaBgGtmzZIpZZsWIFurq6sHPnTlx77bXYuXMn1q5dW1M6vnXrVtx55504ePAgrrzyylO+p75M8/ctXXMcB5OTk5iZmUEoFEJzczNWr16NXbt2YcGCBSiXy0LQMwwDzc3NSCQSNYIa9esj0Y0caSQ8koMQgBCFIpGIEG4opZqEAnKr6bounES0He7UccdxALnW0VgoFBAOh4UQ43afkTDlvoGmbXYLsHRzWt8XkMQMt3OTliO3Gu034S43d3+W3nMnFVO5JSW9x+Nx+Hw+7N69G7IsY+HCha4U91oX17kc53rn11zvU3gFiZevv/46rrrqKqxZswbNzc248847cf311+Phhx/Gvn37kE6nhaOQhKxIJCKE6fb2doyOjop5USgURC85GrtisSgSjak1AiXZezwexONxxONxkVDupt5V6t5P6nNomiYWLlyIo0ePIpvN4oorrsDq1asBADt27MDIyIjoKWmaJkZGRhAKhRAKhYQTWJKqKdhUCqwoCoLBIMLhMIrFonD7Uu9Xeo3KpSuVCvx+PzRNq+n1SPPRPR4krKTTaTE27a1NME0D6WxVXI7H47jxxhsxOTmJ8fFx4cCbmJjAggULhGhEc5HmnSzLUFX1lBAtOvfo/CMRnUp7S6WSEESpxQO1M6DEaPqbBHpqI+EWIQ8cOCBEbFVVcdNNN8Hv9+PgwYOYnJwUDzvEvDxDWMuZBML6v2m/RkdHMTMzg4aGBjQ2NmLp0qUoFotCONM0DRMTE2K+ukv4GxsbkUwmoWkaent7kc1mxUOMc6HegX02nNnPvPzyy5iYmECxWBROc7rmkOhM/SLpX7o207hTMJLX68VLL70Ey7Lwmc98Bh0dHQCq159rrrkG4+Pj6O3txZEjR2qc9DQ/p6en8eyzz6Kvr0/0o6XrFbXJcAuV9NDKLaATtG3Uj9PtfP9jYhgGTpw4gfHxcSSTSSSTSREgFolExLlIblNFUTA5OYmpqSnMzMyIHr0MwzAM82aDhUuGYZjLENu28ZnPfAbXXXcd1qxZA6DaE43KTN20tLRgfHxcLOMWLel9em8u7rvvPnz1q1/9g7fZcRxks1mMjIygubkZ2WwWV155JXbv3i3Kvaenp0UPTHJN0c1mQ0ODCCyh8le38EA3vrqui5JL4KTwE41GRf9KEhfS6TQymQx0XUc0GhXlmtTTjwQG0zShBkJineTcoR5qJJ4R5KAjRxCJnSQouqEbcFo3CZrkAHWLm3SDPleJ6Fxl2m5Xp/s73P30LMvCwoULa44NueRisdhssM/JddK/9S61+m04nTOz/r1SqYTh4WFks1kRDrR27VosXboUK1aswNq1a3Hw4EE8+eSTOHToEEZHR0U7AOpZSmIHiXOOUw2goTJo2l8SiEjkI2cfAOFQJdHGiIbn3Pa53HbkQJuamoJt2+jq6kI6ncbOnTuxfv16LF26FIqi4KWXXhKOTCp9zmazYrwpRIocpRQYRe0OwuGwKIcn8ZNEdkqsnpiYEPMoGo2e4uqk+aDrOqampkSPSxIgHceG4wCFQgGDg4OIRqO4+uqrcfPNN+OnP/1pNbBJVTE2NoZEIoFIJCJKhml+uvtdut3GbvcznRMkWjqOIxLM3T0LSYSjbaQHDNQT1C2kkWA2PT2NyclJMQ7vfve7sWTJEhw/fly4IekBwrk62862bP18p/CgcrmMyclJIV7FYjHR/9Dn8wkhmpyU5XIZuVwOR48eFa0q6td/Nnfz+fW9rCaqDwwM4JFHHhHX1GAwKEJ36IEBtQigBw+yLAvXazAYBPUypeMiSRL27t2Lb37zm7jrrrvQ1dUFy7LQ39+PzZs3i4cQAwMDGBsbw4svvoje3l6YpomBgQEcOHAA09PTiMVi0HUdY2NjwhVN+0hipXts3M55ukZTKT+lvNdfh/+YlMtljIyMYGRkBABq2pfQtrsFfIZhGIZ5s8PCJcMwzGXItm3bcODAATz33HNv+Hfdc889uOuuu8TfuVzulNK/c4GEisHBQSxfvhzpdBpNTU1YuXIljhw5ghUrVsAwDNHfcmpqSoiTFGhCIRG2bdekKLt7nXm9XpTLZVGKV39j6C41T6VSojRY13VUKhWUSiXRk44cYel0Gj6vDGr2SOWTsVhMbBcJYe7vof12ly8DJ/v21Ys7JErW34gDqLnRdgtB9C+JRzQOJA4BqEnVJRdbJBIR4TDLly/H888/D9u20djYiEwmA7/fj6uuugoD/cfhAKcII2f6u/64n6nvJYkgmUwGhUIBExMTOHLkCFavXo3Vq1ejvb0dLS0t+PjHPw5N0zA2Noa+vj4cP34cg4ODyOVyKJfLmJqaEuIbiVg0Nu7jQ2NLAhpQndOUNu73+6tCdyyKqcmTDih3e4HTlQrLsox0Ol11Lra3o62tDS+//DJWr16NJUuWIB6PI5lMYu/evaJHII1DLpdDLpfDxMQEVFVFNBoV5d3kvqT2AyTy5XI5ZDKZmtYIbnGeysVp2yixOZfLiblNY0DnVjKZFOXs6XQa/f396O7uxuLFi7F582b89re/FU7HI0eOYMmSJcIFLElSTasGmvvuOU6J9hT243baVUVySTgo6RyhHqAej0f0s3ULoTSGsixD0zQMDg6K9WzevBlr1qzBiRMnsG/fPoyMjAjX7dnmrvsY/z7Q5+gBSDabxejoqBB56Xx1i7Q0d8/kCDyXlg3nI8oOj4zgkUcfw9TUVE0CPXDSqUzjTCE39CCFHgjYto1QKCSOHVB1FjqOg7179+K///f/jrvvvlsIt6+//jr+5V/+BW9/+9tx+PBhxGIx/Mmf/Amamprwwgsv4PHHH0cikYCmaRgZGRHzxN2WgH6oXNz9nnt+0AMc6utbdZhfuFso9wMShmEYhrkcYeGSYRjmMuOTn/wkHnnkEezYsQOdnZ3i9dbWVui6jkwmU+O6nJiYQGtrq1jm5ZdfrlkfObRomXr8fn9N2u0fApXUTk1NIR6Po6urC1u2bEFfXx9mZmbQ2NiIYrEoeg+WSiXRR1JRFNGjj8RL6ltGOE61N6WmaaL/Ggl15AKjm9xisQjbtoX4mM/nUSgUUCwWRfltIBBAJBJBPp+HY5tw7KoQQCW5NM5UmkuOPxJqaJvcriC6kSYRzV0WTmJDfe9LoNZF5XbtkEBD/5LLk15zuzwp4IiEp0gkgoaGBixatAgPP/wwAoEAGhsbcfjwYSxbtgw33ngjfjg0UBPOQ/t0JjHydP/O1UvQvZ+maSKfz6NUKmF6ehr79u1Dc3MzFixYgCVLlqCxsRHt7e1YsmSJKIMmUYCOXSaTQaVSQbFYxMTEBDweD/L5vHBqkftSkiThSGxvb0c4HIaqqmhubkYsFkOpkMO9935lzu08Xakw7ZumaRgaGkKlUkFXVxf27t2LQqGAFStW4IYbbkA8Hsf+/ftFwjsFoVDvUupnSU49d3IyiZfkxKOEZMuyRPk4HWMqd6dWBe5ybbeIS8d9yZIlWLNqGX7x//sFqEdfOp0WoULXXHMNRkZGsHfvXtE3tbe3F+3t7ejo6KhxoFLgFvUmpXYKJJaSuFnfl5DWS4nxtD/kynaLUe6SZY/Hg2KxiGPHjiGXy8GyLKxduxbXXXcdDh8+jL1792JiYgLpdLrGHV1/btVzPo7Ms62ThFu3U/xszCVQnqlU/XxKxIHqOffDf/s3HO8fFONMAjTNo0qlIlyDdP10HwN6cOJ2P5PATvPh9ddfx7/+67/igx/8IEZGRvDII49g/fr1IkyKHh6tWrUKiqLg2WefRaVSQWtrq5gTx48fB4BTxs99zXQ/wAJQIwDbto1sNoumpiaoavCcxodhGIZhmD8cFi4ZhmEuExzHwac+9Sn88pe/xPbt27Fw4cKa9zds2ACfz4ennnoKt912GwCgt7cXg4OD2LRpEwBg06ZN+K//9b9icnISzc3NAIAnnngC0WgUq1atuiD7kc/nMTg4iObmZkxNTWH58uXYuHEjduzYIcpbgZMOMXIhkssxl8shHA4jFAoJN6RlWULg8Xq9CAaDKJVKIjmY+oyRAARA3JRT/zRKvCaRMR6Pi1CXahCQLvQ7EpAoAdbv9wuxSVVVBIPBU5x4VOZOQqa7hJscQm7mckzV929zC4O0D+RSc7st3fstSZJIuw0Gg1izZg06OztFsnQgEEBHRweuuuoq4RQLBecWrs8mjpxLeS0t537NNE1ks1nk83mMjY2ht7cXL7/8MpqamtDd3Y0FCxags7NT9KYMh8OIRCJIJpNYuHAhPB4PVFVFKpVCR0dHzZhRD0V32jqVwdJ3V12JWeB0LlL3Prr21Q2FB9m2je7ubvT19WFychKrVq3C+vXr0dnZiUOHDuH1118XblES4alNAM13mjsEPUwgcYZETHJclkqlmnLdmvTsWRRFQSQSQVNTE5YtW4ZFixYhHA5DKxcA6eRcy+VyOHbsGBKJBK688krccsstKBQKOH78OAKBABRFwfDwMEKhELq6ukQ/RgprobHxeDzCDUpp6O4UeHePWMephu2QG5RChmg91M+SlqUHE8ePH0cul4MkSejp6cGf/MmfYHh4GAcPHsTIyIgoi5/TrXiO5dXuz841v+tF/PrX6987nXPy5Gadvjz8TJyr49K2bQyPDIuHGW7xnUqtgZNiobuPr9uBTO0L6lteuMXQV199Fbquo6OjQ7QFcD+AiMfjGBgYwIIFC3D77bfjhRdewMDAANra2hCLxcQ1zj3+tE3u7yGonJ3mGLUf0TTtDQuiYxiGYRjmVFi4ZBiGuUzYtm0bfvSjH+Hhhx9GJBIRPSmp9C4Wi+FjH/sY7rrrLiSTSUSjUXzqU5/Cpk2bcO211wIAbr75ZqxatQof/OAH8c1vfhPj4+P4+7//e2zbtu2P5qo8EyRQDA0NYenSpZicnERbWxu2bt2Kvr4+DA8Po7u7WwgT1AMul8vV3CDn83k0NTWJ8IP6cAtFUYQbiz5L75MoQmW41KdNkiTh1CJBhlJgqw4tByRZUf+6RCJRI0qS68h9Q+/ua+b+nW6o6eaakpjdrkQSnGi75xKg6HPuhGK3cEluS9omcpspioKGhgZs2rRJJL5T+MmSJUsgyzIee+yxWTEtek6ur3pBof73+mXPVmJO7jSaA+Pj4+jr60MkEkFzczOampoQDAZryrwpbKehoQGapiGdTiMQCNSktSuKIhyB2WwWXq8X6XRaiG65XA66VoJ9OmfbWRx67nL/yclJaJqGnp4eGIaB1157DYODg1i6dCmuvfZaLF26FEeOHBGp0VQW7XZHklhDY0nH0F1m7C4fpjlOY0jLUp/FeDyOBQsWoLW1FW1tbdB1XfTkCygenNzN6pxOpVI4dOgQFEXBihUr8P73vx+PPPII9u3bJ8JyyA1HPQ9J0Hdvs8fjEb1f3a5P2k/abir7JTGdzkN3gjU9pLBtG6lUCmNjY8JF3dDQgD/7sz/DzMwM9u7di+HhYczMzNSU654imp9FYHcvP1fLgJr5Mcdr7s+dTtysn0Pu30/nYj4bZ19OgizJ0LRSjYsVwCml1iT+u4VjWkaSJIRCIfFZEp6pdyw5N3t7e9Hb2wvHcTA0NCQER+plHAgERDr5li1bkM1m0dvbi76+PjGO7sAyOi/oOkrXUve10h3UA6Am2I1hGIZhmDceFi4ZhmEuEx544AEAwObNm2tef/DBB/HhD38YAHD//fdDlmXcdttt0DQNW7duxXe+8x2xrMfjwSOPPII777wTmzZtQigUwh133IF77733vLdnrrLfs3+m+m9qeloEfxw9ehQrV67En/zJu/D97/8AqdQ0WlpaUSqV4PVWU5CrAToaAv4AAMCcdXNFo1F4PR4YlErs9c5+5mQvSXlWAK3eZJ90A5HTEgC8Xo9LNIQQQwxdn03ctdDYkESllIPHFY5DQQ/kTKqUy7PrlSBTvzXLgmWZ8Hi8gONAAuCl5GWPB45jCxHAti3IklwdKKm2zJHGTpYlobFYlglZroo5EgBJliBJHnF8ZFlyOT1tSJIsxEBJAqLRKHp6erB/3z4MDw+jWCzgxIkT0DQNL7/8Mvr6+hCPhSHh1GN9LsdewilV5qd8tl5UqBfhZl+tHnfTQD5XTXRPpaZx7JgfHo8MSZKrQybJQsSkMv9wOFwTlGRbFhw4sG1HiJdUWk4OU13TkEzG4POenBPA6YWmOYVal4CZy+Vw+PBhJJNJtLe1IZ2ewfPPP49YLIb29nasWbMaS5cuRTqdxvj4ONLpNAqFgnCH6bo2K/Q5kCRAlj2QAHi83tlj7HPN4aqQTmNAwVThcBjBYBCBQADhcAiAhFKphNdfP4SxsfGqwOk48MqBkyLV7P4WCnlMjI9j//79ME0DbW3t+PM//3P09HTjqaeeFi7lQ4cOIRqNoKW5BZFZ5zSNCY2Q1+OBqgYAVEVRQ9chyRI8Hhlerw/BYBDlUglenw+qqopzIBgMClGTeiuS+DU9NQV91p3p9yt41zvfiVQqhYMHD+LE8eOiPNzdgqG+HYPkOmfPxJlaBriWov+ddtmzr8e1gvMUK93Q3D3T+/asGxE42YaiKhZrYqxpXCzLEg8BqsFnKiSpOlcM0xSiJgDxgKBaWm6IazmJ3bIsY2RkRLS4yOVyKBaLKJfLaG1tRWG2t+vmzTfife97H8bHx/GLX/wC/f39LvHSgTx73bPtk25zOm9lSYZ3NriKBFS/349EIj77ufP7b9ilzuW1twzDMMzFguT8Pv9fDMMwDMP8nuRyOcRiMbz1322A1+s7zVKn+0+TNPs/CcGgikgkOlvarcLj8WJsbAyaVqkRLADMOmgceDyyWI/P53X18Kt+Z/UmtHrDWnWb2bBta1YY9IobV8CBYZizCeY+yLIHuq5Vy8EdR4iDHo8sPqMoChoSERSLJUiSVHV8NjRgZHgYtm3PungsIbbStjhwYFt2dZ3AbJ9MZ1ZsmxXDZsfEmU34hUv8cqp7VN0nnLzxdGbfl1wCk3uc7VlBVCbn1uxnDcOEAweKryoSdXd3I5vN4UT/CViz/Qir5bgGHMeGz+edLT8un/IdpxZN/z7/Lwl97kyfd99un7qv9R+VJECSZciSXBVzxbybfZOEIABwqiKm7dhwbFu8pii+2XJt7ez7RwenBkd8l/u4ebxeqAG16hKzLUiQoPgVBPwBeH1eIfRYpgnbcWC5UrgdWtfs99H8lGXPrAgjQ/bIQlyXZRmSLIv5Ix42zDopy+UydF2fFexk6LoGr9cD07RE+Tkhy9V5HQgEEAj44fcH4PV6MD09jXyhUBW+ZsfS5/PNClNzpd3TyFOLhJPuPkmW4Z2de7KnOq8t24ZH9kCSpVktb1aUQrV9RLlSrp47TtXBqapBJJMJ5PMFVLQKTMOAOSvKnvzmU1HVqnNb0425D/Fpjv4fQwhyz373v3/o587lbAyHgggEVCGKWzXXKhuYvYaI75i9PjmOA8/swxfMLms7zslr0eznbHKKz16rZKl6bZXlk/PTtix4PF74A7NBP5YlXPOVSgWK3w/HthGNxVAoFDA6OgrLtCDOsTMMjgSX23X294Dfj2g0gvHxiercuIxQVT+++88/QzabFW1ZGIZhGOaNhoVLhmEY5oJCwiWVCZ4sYzx520w3uNUbxVpdrep6lGDb1qxGJ5286Z51B9FnZFk+KSa51uXYdlXIwEknIeq+ixx4VCpbW5rsCH1Qkk72QDvpTnJObtvsZ2LRCD76138ORTmdWMswDMMwFy+apuP/+58PsnDJMAzDXFC4VJxhGIaZN9w96k6KlycdLtWelPUlkieFQREgU9MHrrbvnTsttqbXm31SaHR/V21PObNme+pFTMuyIUnuMkzatpPrONkr7aQDlGEYhmEYhmEYhjk7LFwyDMMw88Lp0m7pPRIb3cIjUN+38cwBFfXLu4NP3Enc7gCGuRJ7T9dfzi2w0u/u3nfuv+t7MTIMwzAMwzAMwzBnhoVLhmEYZl6YK912rmAV93L1ycfAqSEvp0vqdQuH9am+JGS605zd3+F2hrpDheYOgpl7G7gzC8MwDMMwDMMwzPnBwiXDMAwzL9QLh/RaTVJvnUBIpd9nSnKdywVJ63Av437/bI7IetFyLrHV/Xe9WHq5Jc8yDMMwDMMwDMP8MWDhkmEYhpkX6sU/4PRuyblKtakE2+2UpPfmEkLrxcX6751rPe51zCVaAqgpDa93grq3j2EYhmEYhmEYhjk/uOEWwzAMM++cydHodli6nZLuHpXA3CXn9PnTfZ9bZKwXLd1OzLlcnu71uj/r/t29PfUhQwzDMAzDMAzDMMyZYcclwzAMMy/MJfABc5de0/Luz9b/Xu+uJKcjCYz1Zdv14Ty07MkUcKdmPfXfQZ+vLzM/Xf9NNl0yDMMwDMMwDMOcHyxcMgzDMPPK6YJ45kr5JkhMtG0bHo9HvE7OyNOJleSedBwHlmXBsiwhPtLftPxc5eT1fTEBiO93C55zlZO7t5NhGIZhGIZhGIY5OyxcMgzDMPPKXH0j69+v/93dO9ItVnq9Xng8Hni93lNESlmW4fP5xLoMw4AsyzBNE6ZpQtd14aJ0i5BuAdX9d72IebqwoZO9LrlUnGEYhmEYhmEY5nxg4ZJhGIaZV04XXOMO4KG/SVAksdLr9SIYDMLj8cDj8UBRFLE+j8cDn88nnJRerxder1d83rZtIVQahgHTNKFpGizLgmmaMAwDtm3DNE2xnafb1vrenO4+nLTtZxJnGYZhGIZhGIZhmFNh4ZJhGIaZF+YKyKF/T5cmDgBerxc+n08IlaqqIhgMivfcDktyYRqGIcRN+g4SPyVJQiQSQaVSQaVSAQCYpolKpYJyuVzjyqwXL+dKNz9dGjn3uGQYhmEYhmEYhjk/WLhkGIZhLgpI9LMsCx6Pp0bQJAHQ6/UiEAggGAzC7/fD7/eL0nASJUmoJDHRcRz4fL6aZRRFEaXh9FogEBCvS5JU83epVAJQ6/ok3AKlW2g9VcR8Y8ePYRiGYRiGYRjmzQYLlwzDMMy84HYjukup3eXh7j6Wfr8fgUAAfr8fwWAQqqoCqC3hVhQFjuOIMnGPxwNN02DbtnBq0nf7/X4hlNq2DVmWoSgKAoEANE2Dx+OB3++HrusIBAIoFovQNA2GYcAwDPHdZ8K9f+y4ZBiGYRiGYRiGOT9YuGQYhmHmhblCdwi3i5FEy2AwiEgkIsrCSeAk1yUta9s2YrGYCOPJ5/MoFArwer1QFAUARHq4+/uolyUJmOSu9Pv9ohw9m82iXC4LwbN+W0+3LwzDMAzDMAzDMMz5w8IlwzAMM2+4Bb96qD+lqqoIh8MIBAIIhULwer01/TE9Ho8o3zZNE4qiIBqNivJwy7Kg67oI7qHPAICu6zXrMU1TlJZbliXK08mtSc5MWZZRKpWEW5Oo3xf6m5yjDMMwDMMwDMMwzLnDwiXDMAwzL5Bjst6RSOXVPp8PgUAA0WgUkUgEPp9PiH8kShqGIZLCK5WKSAgvl8sIBAKwbRs+nw+RSKRm/aZpit6YxWJRrIccm5IkiTAf+rEsCw0NDaKcXFEUlEollMtl4b50p4nXJ4wzDMMwDMMwDMMw5wcLlwzDMMy8UJ8mTpDLUVEUhMNhRCIRKIoi3JNUxk3OS9M0Ydu2ECnz+TxM04RhGFBVFaZpwufzwe/3Q5IkGIYh+lvqug6fzyeWJ/GSxEb6DvrdNE2EQiHhBpVlGZZloVwun7JflDhO2DaXjDMMwzAMwzAMw5wPLFwyDMMw8wIJe+4yao/HA1mWRT9L6i1JoTrkkiSnZqVSQT6fRzAYFGXfHo8Huq4jk8nANE14vV4Eg0F4vV6RIu71eqFpmuiR6fP5UCqVhNOStolKw+l1Km0PhUI1JepAteycysvngl2XDMMwDMMwDMMw5wcLlwzDMMy8QOJjfbBNMBgU5eGBQECImZIkCackuSVpPbqui8AcVVVRqVSg6zry+TxUVYXX60UoFBJp4e4UcnJxer1e5PN58R45Oem7HceBoihQFAWGYSAQCAjnJwDkcjmUy2WxrNttSdvJMAzDMAzDMAzDnDssXDIMwzDzAgmEJPBJkiSCeMhlSYE6AITgaJqmCMWhIB363ev1IhqNIhAIwDAMVCoVmKYJTdOQSqUgSZLofUlCpKZpNWJjpVI5pU+lruuibJx6bVLpOJWg0zo0TQMAIXrSvrHjkmEYhmEYhmEY5vxg4ZJhGIaZF9zJ4LIsIxAIIBwOIxwOIxQKieVIYCTBEjjphjRNEwCgaRr8fj+CwaBIHif3I1AN7imXy/B4PCgWi/D7/VBVFZqmiaAeRVFQLpdhGAZ8Ph8Mw4AsyyJpHIB4LRgM1oiWsVhMlJJns1lomgbLsoSbtPpzIUeXYRiGYRiGYRjm0oeFS4ZhGGZecLscFUVBJBJBNBpFOBwWqeGUEk6Ox0qlAtu2RSCOO6zH5/MhFAoJVyYAkQauqioKhQJM06wRTN2hPIlEQoih9LlcLgev1wtVVUU/TgDiX1mWRc9McmmS07JUKtWUw7v7YTIMwzAMwzAMwzBnh4VLhmEYZl4ggY/CcyKRCGKxGAKBACzLgsfjEc5Ky7Lg8/kQCASQy+VQqVREaTglhicSCYTDYSE06roO27ZF30pFUVAsFlGpVITrEoAQLsvlMnRdh67rkCQJxWJRlJHT9tq2LfppUrk4UBVI/X4/4vG46IlJgiuXiDMMwzAMwzAMw/x+sHDJMAzDzAuO48Dj8SAYDCIejyMSicDn84mSa1VVYRgGDMMQTkifz4dgMAhN00RJNwX5NDc3IxAIIBgMQlEU2LaNQqGAQqGAXC4HXdehqirK5XLN56kc3N2bUtM0kSxuWRYMw4BpmggEAgAgUsaBkz06PR4PAoEAZFmGYRhiHdQrkwVMhmEYhmEYhmGY84OFS4ZhGGZeoBLxaDSKxsZGIQqSE5PKxMlZqSiKCOIhkTEYDKKxsRGdnZ1IJBIIBAJIJpMIh8OwLAtDQ0MoFApobGyELMuYnp4WLk7qT0ll3n6/X7gpqZ8mlZxTKbp7eXqdHJa0bYqiQNd10T+zWCzO9shk4ZJhGIZhGIZhGOZ8YOGSYRiGmRdItIzFYohGo5BlGbquQ1EUWJaFYrEIXdcBVEVOVVUhSRIymQwMw4CqqjBNE5FIBOFwGA0NDWhvb8fChQtFWTiJlBSqQy5Iv9+PWCwGwzBEME8oFIKmaSiVSigWizXbSu5Mx3FQLpdFYBC5Q71er3BbUjp6IpGAruuwLItLxhmGYRiGYRiGYX4PWLhkGIZh5gW/349oNCqckqZpCuFP13VUKhWR/A1UxUMAKJVKCIfDaG5uRiQSQbFYRDAYRE9PD7q7u9HY2Ch6VpZKJXg8HuTzeQDAzMwMjh8/jkAggEQigUqlIkJ3IpEIkskkcrmcEE81TUMqlYKu6/D7/fB6vaLvJZWe0zZ7vV7h0lQUBcFgENFoVJS6s3DJMAzDMAzDMAxzfrBwyTAMw8wLiUQCjY2NCIVCQvxTFAXlclk4IcnRSK5JwzBQqVQQi8XQ2tqK5cuXC+djS0sLYrGYCPExTRPNzc3QdR2BQAC2bWNiYgJHjhxBKBQSaeTknmxoaBDfST0sK5WKEFHJvQkAlmWJ/pflchk+nw+lUqkmOdzn8yESiUDTNFQqFQDOPI00wzAMwzAMwzDMpQkLlwzDMMy80NjYiHA4DL/fD9M0hUBJCd30tyRJyOVyIsHb6/UiEomgs7MTXV1d6OnpwfT0NMrlskjzJlGSEsnD4TAkSUJHRwcaGxtFsI7H44FhGEgmkwiFQvB6vfB6vUKAlGUZ8XhcpJhTmbjH4xHl7ZVKBaVSCYqiQJIk0efS6/WKXpvlchlwrHkba4ZhGIZhGIZhmEsRFi4ZhmGYeSEajSIUCokEbgDQdR0ejwe6riMUCok+lZqmCedkU1MTli5diuXLl4tQnng8LtyZJC5Sv0oK+QkEAujo6EAikcDMzAyCwSAMw0AwGISqqsK5KUkS4vE4bNuGz+eDaZoolUoolUowDAOWZQlRlBLDyZ0JQCSaU8q4ZVmIRCIw9Mp8DjfDMAzDMAzDMMwlBwuXDMMwzLygqioAiBJwSuJ295Isl8uwLEuE8zQ0NGDVqlW47rrrEI1GRS/LSCQiwn08Ho9IBScHpGmaCAQCUFUVoVAIqVRKpIrTekjgtCwLfr8fAEQvS3JQAhBiaqFQAFAtCafEcxIxgWo5uc/nQzQaRbFYRKXs4T6XDMMwDMMwDMMw5wELlwzDMMy8oWmaKBMnZFmu6S9p2zaCwSBaW1uxbNkyrF+/Hp2dncjlckin0/D5fLBtG7FYDH6/H6qqir6UsiyLcBzbtpHJZBCLxSDLck1ZuCzLME0THo8HPp9PiJ7kwKRwHp/PB6/Xi1KpJBLKPR4PbNsWomulUhFuS13XRUiP1yOzcMkwDMMwDMMwDHMesHDJMAzDzAuWZQk3JIXxNDY2wrIsZLNZIQwGAgG0trZiyZIlWLlyJTo6OpDL5ZBKpUQwTjAYREtLC7xeLyRJEuKnJEkirTyTyQh3ZCAQEEE8JFwCqOmPST+qqgqRk9ygPp9PhAjR9muahkAgIMrLKWmclo9GIyxcMgzDMAzDMAzDnAcsXDIMwzDzgtsRaRiGcDYWCgXk83lIkoRQKITGxkYsXrwYixcvRnNzM3K5HCYnJ0UYTzgcFiIj9ZwkJ6VlWSgWi0ilUgiHw6JvpW3b8Hq9CAQCIniHlnccRwiMJH5SKXo+nxfl4LIsC8colbWXSiXEYjFYloVSqSSEVCpLZxiGYRiGYRiGYc4dFi4ZhmGYeUHTNFGS7RYuyfXo8/nQ3NyM5cuXo6enB42NjbBtG6lUCsViEbquC2GQelCSmOg4DnRdRyaTweTkJPx+P2RZxtDQELq6urB3716RKG4YBnw+X82/VEoOVPtcqqoKwzDg9/sRCoWEUFosFiHLMmS5WgZeLBZF0BD1uszn87AsC2pAmbexZhiGYRiGYRiGuRRh4ZJhGIaZF/L5PPx+PxRFqel1GQwG4fP5EI/HsXLlSqxYsQLJZBIAkMvlMDU1VeO2VFUV4XAYlUoFuVwOtm2jWCwinU4Lh6SmaUilUjAMA62trbAsC5ZlQdM0SJIEy7IQCAREz0qgWsru8XhEUJDH40E4HBZ9MBVFES7KSCQiRNWZmRkhxHq9XrGcz+eZt7FmGIZhGIZhGIa5FGHhkmEYhpkXqJRa0zRomgafzyeSv+PxOBYsWICenh50dnYiEAhgaGgIIyMjyOVywpXp8XiQTCbhOA6y2SyAqpMzm82iWCzCsixRwp3P57Fw4UL4fD7EYjEUi0XYtg1FUWoSyCVJQjAYhCzL4m/TNGGaJoLBIILBIBRFgaIoItSnubkZ4XAYgUAApmkinU6L9QcCAciyjGgkPM8jzjAMwzAMwzAMc2nBwiXDMAwzL1A5NwmEFLKTSCTQ09ODRYsWoaenB8lkEhMTExgZGUE2mxVuS8dxYJomSqUScrkcgGrfzGKxiEwmI8JzdF1HsVgUpeSGYSAajWJsbEwIlOTAJKFRkiRomoZCoSDKwKl/Jrk8yVEZjUbR3d2NQqGAUCgERVFw/PhxSJKESqUihE/LMud5xBmGYRiGYRiGYS4tWLhkGIZh5gUq4VZVFX6/H8lkEq2trejo6MCSJUuwcOFCJJNJ5HI5DAwMIJ1Oo1KpiMTuSqWCbDaL0dFR0YdS0zRUKhXouo5yuYxKpSIER5/PB8uyUKlURAp4MpkUvTWpbFxRFJEWXiwWRf9Mx3GQTqeRTqeRSCSgqiqSySSWLVuGjo4O5PN5kVgOAIFAAMViEeVyWSSVA878DjrDMAzDMAzDMMwlBAuXDMMwzLxA6d/hcBh+vx+tra1YvHgx2tvb0dPTg5aWFpRKJRw7dkykiOu6DsuyIMuyKPHOZDKihDuZTCIUColwnUqlAk3ThJMymUwiFotBVVWUy2V4PB6YpgnDMESiOLkvdV2Hz+cT20v9OClpnNLGLcvC1NQUGhoasHr1akSjUciyjFAohPHxceRyudkgIR8AThZnGIZhGIZhGIY5V1i4ZBiGYeYFv9+PcDiMWCyGWCyGtrY2dHZ2oqurC62trfD5fBgfHxeipcfjEcE5AGDbNmzbBgDIsgy/349gMIhcLgdN0yDLMiKRCJLJpBAtu7u74fF40NjYKJyZ5Mj0+/1wHAcej0esz7Is+Hw++P1+4fRUFAWqqqKjowNNTU1IpVIYGRnB9PQ0lixZgsbGRixevFiUsTuOg1wuB9M05muoGYZhGIZhGIZhLklYuGQYhmHmhWQyiXA4DEVRkEwm0d7ejra2NiSTSaiqiunpaUxOTsI0Tdi2LVyRlPRNQmU0GkUkEkGxWERvby+GhoaQy+VEonc0GkVHRwfa29vh8Xjg9/vR1dWFWCwmwncURYHP54PX64Vt2zBNE16vF6FQCJFIBD6fD+VyuUYopdcOHTqEQqGASCSCdDqNaDQq0skVRUE8Hq86Pv0+kULOMAzDMAzDMAzDnB0WLhmGYZh5oa2tDYlEApZlIRKJoLm5GYlEAtFo1OVSrJZxuwXGQCAgkr1lWYbjOJiYmEAqlcLMzAw0TYPjODAMA+VyGeVyGY7joLOzU4iTsVgMkUgEAKAoCoCqGEmuTipJp36Vtm2L8nOv1wuPx4NCoYBcLif+zefzmJycRGtrKxYsWAC/349AIACPx4N4PA6LHZcMwzAMwzAMwzDnhTzfG8AwDMPMD9/4xjcgSRI+85nPiNcqlQq2bduGhoYGhMNh3HbbbZiYmKj53ODgIG655RYEg0E0Nzfj85//PEzz/BOzE4kEOjs7sWLFCrS1tQlRUFEUmKaJQqEg0sBVVUUoFEIikUBjYyNUVUWhUMDY2Bj6+/tx5MgRTExMoFKpoFwuC0GRQnrGx8exb98+lEolyLIM0zRRqVTEtvj9fvj9fpE8fjIJ/GTfSwCityYF/ZCgCkAkkR8/fhx79uzB6OgoUqkU+vv7kUqlkM1mZgN6GIZhGIZhGIZhmHOBHZcMwzCXIa+88gq++93vYt26dTWvf/azn8Wjjz6Kn//854jFYvjkJz+J9773vXj++ecBAJZl4ZZbbkFrayteeOEFjI2N4UMf+hB8Ph++/vWvn9c2hEIhUeodCAQQiUREovfMzAwmJyeRy+VgWZYQFRVFQaVSQTqdRqlUEiXZJDQWi0Xoug4AQlyUJAm2bWNkZAQDAwPweDw4ePAgdF2HqqpCePR6vZAkSYT/kDuTXiccxxFCbf17gUBABPs0NTUhFAohlUohl8uhWMyf/4FiGIZhGIZhGIa5jGHhkmEY5jKjUCjg9ttvx//5P/8H/+W//Bfxejabxfe+9z386Ec/wtvf/nYAwIMPPoiVK1fixRdfxLXXXovHH38chw4dwpNPPomWlhasX78eX/va13D33XfjK1/5iii7PhdM04TH4xEhO8ViEalUCpZloVAoIJvNIpVKwbZt4YjUNE0khcuyDNu2US6XYRgGdF2H4ziilJyCdSgB3OPxoFQqob+/H88//zwkSYIsywgEAqJ/ps/ng6qqkOVqQQIJn7Isi/e9Xi8sy0I+nxfBPpIkwTAM4ciUZRnhcBgdHR0YHR3FiRMnUC4V/7gHkmEYhmEYhmEY5k0Ol4ozDMNcZmzbtg233HILtmzZUvP6rl27YBhGzesrVqxAV1cXdu7cCQDYuXMn1q5di5aWFrHM1q1bkcvlcPDgwTm/T9M05HK5mh8AQoAsFArIZDKYnJwUYTyWZYnelgCEQJnNZqFpGizLgqZpKJVKMAxDOCCppFxVVYTDYfh8PiiKgnA4jJ6eHliWhb6+PqiqKtyRjuPA5/MJERWoTSmnnpbUA9O97aZpwu/3CxGVBFDbtqHrOvx+PyKRyOz2cZk4wzAMwzAMwzDM+cCOS4ZhmMuIn/zkJ9i9ezdeeeWVU94bHx8XKdhuWlpaMD4+LpZxi5b0Pr03F/fddx+++tWvnvI6lVxXKhXRx7JcLqNUKiEQCEBRFFG6bRiGEBYN42TIjcfjgeM4cBxHhOEEg0HhmASq5dsdHR1obW1FLpfD1NQUMpkM2traRIm5z+cT4mP9eh3HgcfjQbFYFNuh67oQS8nNCVRdpJIkIRQKCcEzEokgFoshl01zqjjDMAzDMAzDMMx5wI5LhmGYy4ShoSF8+tOfxg9/+EORln0huOeee5DNZsXP0NAQgGp/SE3TAFSTvS3LQjabRSaTgaqqSCQSCIVCokzbNE3Yti3EQcdxRJm5z+eD3++HoigiTMdxHHi9XgSDQfh8PhQKBeGSpJJuEhd1XReiJTk+Cfo+27aRyWRQLpfFeiichxyZJLJSebkkSVBVFV6vV5SVMwzDMAzDMAzDMOcGOy4ZhmEuE3bt2oXJyUlcddVV4jXLsrBjxw78r//1v/C73/0Ouq4jk8nUuC4nJibQ2toKAGhtbcXLL79cs15KHadl6qH+lPWQK7KhoQGFQkE4L7PZLBYsWICOjg6RFC5JkuhhCUA4HAEIEdM0TRiGIQJ1AAjHZDAYhG3bqFQqonychEbHcYRwST0xTdMUZeAUwBONRgFACJ/0GQoDkiQJiqKIbTMMQ2wXfQ/DMAzDMAzDMAxz7rDjkmEY5jLhpptuwv79+7Fnzx7xc/XVV+P2228Xv/t8Pjz11FPiM729vRgcHMSmTZsAAJs2bcL+/fsxOTkplnniiScQjUaxatWq89qeYDCItrY2yLKMUqmEYrGIYrGIfD4PwzCQTCbR2toKVVWFAEll4uR09Pv9oqzbLQ7atg2v14tEIgHbtjEzMwMAohycUsOpdNsdKiRJEjRNE65KVVXh8XigKAqKxaII9JFlWbguZVmG4zhivbStjuNA0zTxHsMwDMMwDMMwDHPusOOSYRjmMiESiWDNmjU1r4VCITQ0NIjXP/axj+Guu+5CMplENBrFpz71KWzatAnXXnstAODmm2/GqlWr8MEPfhDf/OY3MT4+jr//+7/Htm3b5nRVnglFURCNRpHNZqHrOnRdh2VZIiU8kUigubkZw8PDKBaLojTc4/FAkiQhHpZKJQAQvSgty4IsyzAMA4VCAY2NjTAMA2NjYwiFQsIlSa5LcmxSubdt2yK1nFyVFPQTCASE4Onz+VAulwFAlIaTSEmCKPXGrAb7eLnHJcMwDMMwDMMwzHnAwiXDMAwjuP/++yHLMm677TZomoatW7fiO9/5jnjf4/HgkUcewZ133olNmzYhFArhjjvuwL333nve3xUMBhEMBpFOp2HbtnBMlstlVCoVKIoiSrUBiH6W7t6WJBgS1KfSsiwEg0H4/X5omga/349CoQCPx4NgMIhAIACPxwOv11vTw5LCgEqlkhAyTdOE1+tFOBxGV1cXLMtCLpeDYRjCVUnOT3eIELks6TWv1zPnODAMwzAMwzAMwzBzw8IlwzDMZcz27dtr/g4EAvj2t7+Nb3/726f9THd3N37zm9/8wd8di8UQiURE8A71miwUCkilUuju7oYsy6hUKuL9cDiMYDCISqWCSqUixEXqK0luR3I2BgIBRCIRKIqCQCAA27ZRKpXEZ+lzlmUJpyatp1wuiwAf6r8ZDAbFa/R7JpOBZVkipId+ZFmuKU0PBkPsuGQYhmEYhmEYhjkPWLhkGIZh5oVoNIpQKASv1yvclpZlQdM0pFIpITBqmiYcjJVKBX6/H6VS6ZQwHKBWuCQRkkrJqQ+lYRioVCqwLEsE71APTSpFj8ViQtyk18hhKcsy/H4/gsEgotEoZmZmMDQ0JLaHXJ9UUk6J4vF4DJKVB8AhPQzDMAzDMAzDMOcCC5cMwzDMvOD3+6EoCnw+X03pt2mamJycxPT0tEjsJsGRREd6zbIsBAIBITxSUA+F9BiGAdM0a9yV7r6W5JSkHyrvdpd7e71ekUBumiYCgQAURRF9LuPxOCYnJ0VJOK2D+mGqqgrbtqEoftiVPDhcnGEYhmEYhmEY5tzgiFOGYRhmXtB1HaZpIhQKndLLslAoYHBwEKZpCqHRsixRdl0fquPz+QCgRgg1DEOE69DvJFCWy2WUSiWxHlqnO52chFXHcWCaJnRdR7FYhGma8Pl88Hq98Hq98Pv9wt3p3l7qoenz+RAOh+HAAcCl4gzDMAzDMAzDMOcKC5cMwzDMvFCpVJDL5USJNf1rGAZKpRKGhoaEuxKoioJU3q2qqhAodV0X5d3hcFgki+u6LlyaJFxS6remaTU9LUlkdPegJEclvUeCJDk4Y7GYSBYnQZXWJcsyVFVFIBBAIBBALBaDGghc2AFmGIZhGIZhGIa5xOFScYZhGGZeKJVKKJVKwjVJoiAF8czMzCAWiwkhksRBcjHatg1N00Q5OYmSVHYuy7JwXJKYSO7JRCKBUCgE27aFW5PKy2k5cmHS3wBEyI+qqlBVFTMzM5iYmIDP50MoFIJhGMKJSanoiUSiKpJKDsrZMS4VZxiGYRiGYRiGOUdYuGQYhmHmBU3TkE6nkc/noeu6cELqui76TI6OjgrRkMqvFUVBMBgUZd3V/pGKcD8ahiGER8IwDKiqKoTIeDwu3JXunpbUZ9OyLCGm0veTYGqaJsrlMvL5PI4ePQrTNNHa2opMJoNyuSy2k8KEEokEbNuGaeiY4FRxhmEYhmEYhmGYc4aFS4ZhGOaCQkLg9PgAyvkUNK0CU9Mg2xYCXgtK2AvbsuGRNGilNGRJQsBroTGuwuORoXhteKFD9TnwyV7AcRBUPZBlB5IN+CQJgARZtiHJJrySA8ewLqZVBgAADqpJREFUYckGymYRAJCM+WFpOVTMIvSSDEmWgVm3piQBtu3AkGWAhEap+n+Ks+7P0aE+GLqOUqkMv1/BtFWCZZnwQoNjA2ZFx+Cx11HOT8OnKKiUKyiXi6hUKiJ1nGEYhmEuJTRXYB7DMAzDXCgkh//LwzAMw1xAjh8/jsWLF8/3ZjAMwzAM83swNDSEzs7O+d4MhmEY5jKBHZcMwzDMBSWZTAIABgcHEYvF5nlrLg5yuRwWLFiAoaEhRKPR+d6ceYfH41R4TGrh8TgVHpNaeDxO5Q8dE8dxkM/n0d7e/gZsHcMwDMPMDQuXDMMwzAWFek/GYjG+mawjGo3ymLjg8TgVHpNaeDxOhcekFh6PU/lDxoQfODIMwzAXGvnsizAMwzAMwzAMwzAMwzAMw1xYWLhkGIZhGIZhGIZhGIZhGOaig4VLhmEY5oLi9/vx5S9/GX6/f7435aKBx6QWHo9T4TGphcfjVHhMauHxOBUeE4ZhGOZShFPFGYZhGIZhGIZhGIZhGIa56GDHJcMwDMMwDMMwDMMwDMMwFx0sXDIMwzAMwzAMwzAMwzAMc9HBwiXDMAzDMAzDMAzDMAzDMBcdLFwyDMMwDMMwDMMwDMMwDHPRwcIlwzAMc0H59re/jZ6eHgQCAWzcuBEvv/zyfG/SG8J9992Ha665BpFIBM3NzfizP/sz9Pb21iyzefNmSJJU8/O3f/u3NcsMDg7illtuQTAYRHNzMz7/+c/DNM0LuSt/FL7yla+csq8rVqwQ71cqFWzbtg0NDQ0Ih8O47bbbMDExUbOON8tYED09PaeMiSRJ2LZtG4A3//zYsWMH3vOe96C9vR2SJOFXv/pVzfuO4+BLX/oS2traoKoqtmzZgqNHj9YsMzMzg9tvvx3RaBTxeBwf+9jHUCgUapbZt28fbrjhBgQCASxYsADf/OY33+hd+70505gYhoG7774ba9euRSgUQnt7Oz70oQ9hdHS0Zh1zzatvfOMbNctcKmNytjny4Q9/+JR9fec731mzzOU0RwDMeU2RJAnf+ta3xDJvpjnCMAzDvPlh4ZJhGIa5YPz0pz/FXXfdhS9/+cvYvXs3rrjiCmzduhWTk5PzvWl/dJ599lls27YNL774Ip544gkYhoGbb74ZxWKxZrmPf/zjGBsbEz/um0PLsnDLLbdA13W88MIL+MEPfoDvf//7+NKXvnShd+ePwurVq2v29bnnnhPvffazn8Wvf/1r/PznP8ezzz6L0dFRvPe97xXvv9nGAgBeeeWVmvF44oknAAB/8Rd/IZZ5M8+PYrGIK664At/+9rfnfP+b3/wm/vEf/xH/+3//b7z00ksIhULYunUrKpWKWOb222/HwYMH8cQTT+CRRx7Bjh078IlPfEK8n8vlcPPNN6O7uxu7du3Ct771LXzlK1/BP/3TP73h+/f7cKYxKZVK2L17N774xS9i9+7deOihh9Db24s//dM/PWXZe++9t2befOpTnxLvXUpjcrY5AgDvfOc7a/b1xz/+cc37l9McAVAzFmNjY/jnf/5nSJKE2267rWa5N8scYRiGYS4DHIZhGIa5QLzlLW9xtm3bJv62LMtpb2937rvvvnncqgvD5OSkA8B59tlnxWs33nij8+lPf/q0n/nNb37jyLLsjI+Pi9ceeOABJxqNOpqmvZGb+0fny1/+snPFFVfM+V4mk3F8Pp/z85//XLz2+uuvOwCcnTt3Oo7z5hqL0/HpT3/aWbx4sWPbtuM4l9f8AOD88pe/FH/btu20trY63/rWt8RrmUzG8fv9zo9//GPHcRzn0KFDDgDnlVdeEcs89thjjiRJzsjIiOM4jvOd73zHSSQSNeNx9913O8uXL3+D9+gPp35M5uLll192ADgDAwPite7ubuf+++8/7Wcu1TGZazzuuOMO59Zbbz3tZ3iOOM6tt97qvP3tb6957c06RxiGYZg3J+y4ZBiGYS4Iuq5j165d2LJli3hNlmVs2bIFO3funMctuzBks1kAQDKZrHn9hz/8IRobG7FmzRrcc889KJVK4r2dO3di7dq1aGlpEa9t3boVuVwOBw8evDAb/kfk6NGjaG9vx6JFi3D77bdjcHAQALBr1y4YhlEzN1asWIGuri4xN95sY1GPruv4t3/7N3z0ox+FJEni9ctpfrg5ceIExsfHa+ZELBbDxo0ba+ZEPB7H1VdfLZbZsmULZFnGSy+9JJZ561vfCkVRxDJbt25Fb28v0un0BdqbN45sNgtJkhCPx2te/8Y3voGGhgZceeWV+Na3vlXTPuDNNibbt29Hc3Mzli9fjjvvvBOpVEq8d7nPkYmJCTz66KP42Mc+dsp7l9McYRiGYS5tvPO9AQzDMMzlwfT0NCzLqhFZAKClpQWHDx+ep626MNi2jc985jO47rrrsGbNGvH6X/3VX6G7uxvt7e3Yt28f7r77bvT29uKhhx4CAIyPj885XvTepcTGjRvx/e9/H8uXL8fY2Bi++tWv4oYbbsCBAwcwPj4ORVFOEV9aWlrEfr6ZxmIufvWrXyGTyeDDH/6weO1ymh/10PbPtX/uOdHc3FzzvtfrRTKZrFlm4cKFp6yD3kskEm/I9l8IKpUK7r77bnzgAx9ANBoVr/+n//SfcNVVVyGZTOKFF17APffcg7GxMfzDP/wDgDfXmLzzne/Ee9/7XixcuBDHjh3DF77wBbzrXe/Czp074fF4Lvs58oMf/ACRSKSm7QZwec0RhmEY5tKHhUuGYRiGeYPZtm0bDhw4UNPTEUBNn7W1a9eira0NN910E44dO4bFixdf6M18Q3nXu94lfl+3bh02btyI7u5u/OxnP4OqqvO4ZRcH3/ve9/Cud70L7e3t4rXLaX4w54dhGPjLv/xLOI6DBx54oOa9u+66S/y+bt06KIqC//Af/gPuu+8++P3+C72pbyjvf//7xe9r167FunXrsHjxYmzfvh033XTTPG7ZxcE///M/4/bbb0cgEKh5/XKaIwzDMMylD5eKMwzDMBeExsZGeDyeU5KiJyYm0NraOk9b9cbzyU9+Eo888gieeeYZdHZ2nnHZjRs3AgD6+voAAK2trXOOF713KROPx7Fs2TL09fWhtbUVuq4jk8nULOOeG2/msRgYGMCTTz6Jv/mbvznjcpfT/KDtP9P1orW19ZRgL9M0MTMz86aeNyRaDgwM4IknnqhxW87Fxo0bYZom+vv7Abw5x4RYtGgRGhsba86Ry3GOAMD/+3//D729vWe9rgCX1xxhGIZhLj1YuGQYhmEuCIqiYMOGDXjqqafEa7Zt46mnnsKmTZvmccveGBzHwSc/+Un88pe/xNNPP31K2d1c7NmzBwDQ1tYGANi0aRP2799fc+NNQsWqVavekO2+UBQKBRw7dgxtbW3YsGEDfD5fzdzo7e3F4OCgmBtv5rF48MEH0dzcjFtuueWMy11O82PhwoVobW2tmRO5XA4vvfRSzZzIZDLYtWuXWObpp5+GbdtC5N20aRN27NgBwzDEMk888QSWL19+SZa7kmh59OhRPPnkk2hoaDjrZ/bs2QNZlkXJ9JttTNwMDw8jlUrVnCOX2xwhvve972HDhg244oorzrrs5TRHGIZhmEuQ+U4HYhiGYS4ffvKTnzh+v9/5/ve/7xw6dMj5xCc+4cTj8ZpU5DcLd955pxOLxZzt27c7Y2Nj4qdUKjmO4zh9fX3Ovffe67z66qvOiRMnnIcffthZtGiR89a3vlWswzRNZ82aNc7NN9/s7Nmzx/ntb3/rNDU1Offcc8987dbvzec+9zln+/btzokTJ5znn3/e2bJli9PY2OhMTk46juM4f/u3f+t0dXU5Tz/9tPPqq686mzZtcjZt2iQ+/2YaCzeWZTldXV3O3XffXfP65TA/8vm889prrzmvvfaaA8D5h3/4B+e1114TCdnf+MY3nHg87jz88MPOvn37nFtvvdVZuHChUy6XxTre+c53OldeeaXz0ksvOc8995yzdOlS5wMf+IB4P5PJOC0tLc4HP/hB58CBA85PfvITJxgMOt/97ncv+P6eC2caE13XnT/90z91Ojs7nT179tRcVyj9+YUXXnDuv/9+Z8+ePc6xY8ecf/u3f3OampqcD33oQ+I7LqUxOdN45PN55+/+7u+cnTt3OidOnHCefPJJ56qrrnKWLl3qVCoVsY7LaY4Q2WzWCQaDzgMPPHDK599sc4RhGIZ588PCJcMwDHNB+Z//8386XV1djqIozlve8hbnxRdfnO9NekMAMOfPgw8+6DiO4wwODjpvfetbnWQy6fj9fmfJkiXO5z//eSebzdasp7+/33nXu97lqKrqNDY2Op/73OccwzDmYY/+MN73vvc5bW1tjqIoTkdHh/O+973P6evrE++Xy2XnP/7H/+gkEgknGAw6f/7nf+6MjY3VrOPNMhZufve73zkAnN7e3prXL4f58cwzz8x5jtxxxx2O4ziObdvOF7/4RaelpcXx+/3OTTfddMo4pVIp5wMf+IATDoedaDTqfOQjH3Hy+XzNMnv37nWuv/56x+/3Ox0dHc43vvGNC7WL582ZxuTEiROnva4888wzjuM4zq5du5yNGzc6sVjMCQQCzsqVK52vf/3rNUKe41w6Y3Km8SiVSs7NN9/sNDU1OT6fz+nu7nY+/vGPn/Ig7HKaI8R3v/tdR1VVJ5PJnPL5N9scYRiGYd78SI7jOG+opZNhGIZhGIZhGIZhGIZhGOY84R6XDMMwDMMwDMMwDMMwDMNcdLBwyTAMwzAMwzAMwzAMwzDMRQcLlwzDMAzDMAzDMAzDMAzDXHSwcMkwDMMwDMMwDMMwDMMwzEUHC5cMwzAMwzAMwzAMwzAMw1x0sHDJMAzDMAzDMAzDMAzDMMxFBwuXDMMwDMMwDMMwDMMwDMNcdLBwyTAMwzAMwzAMwzAMwzDMRQcLlwzDMAzDMAzDMAzDMAzDXHSwcMkwDMMwDMMwDMMwDMMwzEUHC5cMwzAMwzAMwzAMwzAMw1x0sHDJMAzDMAzDMAzDMAzDMMxFx/8fLyO9jF9mBUoAAAAASUVORK5CYII=\n"
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "def imshow(inp, title=None):\n",
+        "    \"\"\"Display image for Tensor.\"\"\"\n",
+        "    inp = inp.numpy().transpose((1, 2, 0))\n",
+        "    mean = np.array([0.485, 0.456, 0.406])\n",
+        "    std = np.array([0.229, 0.224, 0.225])\n",
+        "    inp = std * inp + mean\n",
+        "    inp = np.clip(inp, 0, 1)\n",
+        "    plt.imshow(inp)\n",
+        "    if title is not None:\n",
+        "        plt.title(title)\n",
+        "    plt.pause(0.001)  # pause a bit so that plots are updated\n",
+        "\n",
+        "\n",
+        "# Get a batch of training data\n",
+        "inputs, classes = next(iter(dataloaders['train']))\n",
+        "\n",
+        "# Make a grid from batch\n",
+        "out = torchvision.utils.make_grid(inputs)\n",
+        "\n",
+        "imshow(out, title=[class_names[x] for x in classes])"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "mq3LbRiQW2lB"
+      },
+      "source": [
+        "## Training the model\n",
+        "\n",
+        "Now, let's write a general function to train a model. Here, we will\n",
+        "illustrate:\n",
+        "\n",
+        "-  Scheduling the learning rate\n",
+        "-  Saving the best model\n",
+        "\n",
+        "In the following, parameter ``scheduler`` is an LR scheduler object from\n",
+        "``torch.optim.lr_scheduler``.\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 17,
+      "metadata": {
+        "id": "utSazWwYW2lC"
+      },
+      "outputs": [],
+      "source": [
+        "def train_model(model, criterion, optimizer, scheduler, num_epochs=60):\n",
+        "    since = time.time()\n",
+        "\n",
+        "    best_model_wts = copy.deepcopy(model.state_dict())\n",
+        "    best_acc = 0.0\n",
+        "\n",
+        "    for epoch in range(num_epochs):\n",
+        "        print(f'Epoch {epoch}/{num_epochs - 1}')\n",
+        "        print('-' * 10)\n",
+        "\n",
+        "        # Each epoch has a training and validation phase\n",
+        "        for phase in ['train', 'val']:\n",
+        "            if phase == 'train':\n",
+        "                model.train()  # Set model to training mode\n",
+        "            else:\n",
+        "                model.eval()   # Set model to evaluate mode\n",
+        "\n",
+        "            running_loss = 0.0\n",
+        "            running_corrects = 0\n",
+        "\n",
+        "            # Iterate over data.\n",
+        "            for inputs, labels in dataloaders[phase]:\n",
+        "                inputs = inputs.to(device)\n",
+        "                labels = labels.to(device)\n",
+        "\n",
+        "                # zero the parameter gradients\n",
+        "                optimizer.zero_grad()\n",
+        "\n",
+        "                # forward\n",
+        "                # track history if only in train\n",
+        "                with torch.set_grad_enabled(phase == 'train'):\n",
+        "                    outputs = model(inputs)\n",
+        "                    _, preds = torch.max(outputs, 1)\n",
+        "                    loss = criterion(outputs, labels)\n",
+        "\n",
+        "                    # backward + optimize only if in training phase\n",
+        "                    if phase == 'train':\n",
+        "                        loss.backward()\n",
+        "                        optimizer.step()\n",
+        "\n",
+        "                # statistics\n",
+        "                running_loss += loss.item() * inputs.size(0)\n",
+        "                running_corrects += torch.sum(preds == labels.data)\n",
+        "            if phase == 'train':\n",
+        "                scheduler.step()\n",
+        "\n",
+        "            epoch_loss = running_loss / dataset_sizes[phase]\n",
+        "            epoch_acc = running_corrects.double() / dataset_sizes[phase]\n",
+        "\n",
+        "            print(f'{phase} Loss: {epoch_loss:.4f} Acc: {epoch_acc:.4f}')\n",
+        "\n",
+        "            # deep copy the model\n",
+        "            if phase == 'val' and epoch_acc > best_acc:\n",
+        "                best_acc = epoch_acc\n",
+        "                best_model_wts = copy.deepcopy(model.state_dict())\n",
+        "\n",
+        "        print()\n",
+        "\n",
+        "    time_elapsed = time.time() - since\n",
+        "    print(f'Training complete in {time_elapsed // 60:.0f}m {time_elapsed % 60:.0f}s')\n",
+        "    print(f'Best val Acc: {best_acc:4f}')\n",
+        "\n",
+        "    # load best model weights\n",
+        "    model.load_state_dict(best_model_wts)\n",
+        "    return model"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "h09FnkFVW2lC"
+      },
+      "source": [
+        "### Visualizing the model predictions\n",
+        "\n",
+        "Generic function to display predictions for a few images\n",
+        "\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 18,
+      "metadata": {
+        "id": "MVpCbBziW2lC"
+      },
+      "outputs": [],
+      "source": [
+        "def visualize_model(model, num_images=6):\n",
+        "    was_training = model.training\n",
+        "    model.eval()\n",
+        "    images_so_far = 0\n",
+        "    fig = plt.figure()\n",
+        "\n",
+        "    with torch.no_grad():\n",
+        "        for i, (inputs, labels) in enumerate(dataloaders['val']):\n",
+        "            inputs = inputs.to(device)\n",
+        "            labels = labels.to(device)\n",
+        "\n",
+        "            outputs = model(inputs)\n",
+        "            _, preds = torch.max(outputs, 1)\n",
+        "\n",
+        "            for j in range(inputs.size()[0]):\n",
+        "                images_so_far += 1\n",
+        "                ax = plt.subplot(num_images//2, 2, images_so_far)\n",
+        "                ax.axis('off')\n",
+        "                ax.set_title(f'predicted: {class_names[preds[j]]}')\n",
+        "                imshow(inputs.cpu().data[j])\n",
+        "\n",
+        "                if images_so_far == num_images:\n",
+        "                    model.train(mode=was_training)\n",
+        "                    return\n",
+        "        model.train(mode=was_training)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "LxC7G961W2lD"
+      },
+      "source": [
+        "## Finetuning the ConvNet\n",
+        "\n",
+        "Load a pretrained model and reset final fully connected layer.\n",
+        "\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 19,
+      "metadata": {
+        "id": "d0DTgqMvW2lD"
+      },
+      "outputs": [],
+      "source": [
+        "model_ft = models.resnet18(weights='IMAGENET1K_V1')\n",
+        "num_ftrs = model_ft.fc.in_features\n",
+        "# Here the size of each output sample is set to 2.\n",
+        "# Alternatively, it can be generalized to ``nn.Linear(num_ftrs, len(class_names))``.\n",
+        "model_ft.fc = nn.Linear(num_ftrs, 10)\n",
+        "\n",
+        "model_ft = model_ft.to(device)\n",
+        "\n",
+        "criterion = nn.CrossEntropyLoss()\n",
+        "\n",
+        "# Observe that all parameters are being optimized\n",
+        "optimizer_ft = optim.SGD(model_ft.parameters(), lr=0.001, momentum=0.93)\n",
+        "\n",
+        "# Decay LR by a factor of 0.1 every 7 epochs\n",
+        "exp_lr_scheduler = lr_scheduler.StepLR(optimizer_ft, step_size=7, gamma=0.1)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "asgAWJjkW2lD"
+      },
+      "source": [
+        "### Train and evaluate\n",
+        "\n",
+        "It should take around 15-25 min on CPU. On GPU though, it takes less than a\n",
+        "minute.\n",
+        "\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 20,
+      "metadata": {
+        "id": "RX6GdXXJW2lE"
+      },
+      "outputs": [],
+      "source": [
+        "#model_ft = train_model(model_ft, criterion, optimizer_ft, exp_lr_scheduler,\n",
+        "#                       num_epochs=60)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 21,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 923
+        },
+        "id": "BD6f3RK7W2lE",
+        "outputId": "b368ffbe-efbf-4674-ec08-735b63f1cdb8"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ],
+            "image/png": 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BViONTjPSQKuRRqcZaYYoACaTCbVara4YFwWKy8f5Z2QOUBQFOp0OqqrWhcMpiiKOUQSP+lqcMo9V1uv1qFary75Dr3U6HZqamrBlyxZ0dXVhfHwc09PTYrxSqQRFUeD1ehGLxdDe3o7u7m5EIhFMT09jdnYWmUwGpVIJqqrCaDTCbDbDYrGgXC6jWq2iUqmgXC6Le6P58DnTf51Oh1qtJt7r9XpUKpWGz4F/Vx6PniU9i0bPS37O9Fmj6iCrhTTQvkYykPiCosUIYBmY6Ji8UPmYer1eHOPf4QuWgKuqKvR6vfhMr9fDYrGgq6sLbrcbIyMjwhKbzWbrzlMUBZVKBcPDw8jlclAUBSaTCS0tLYhGo0ilUjAajXC5XLDZbDCZTCiVSgKgpVIJlUoFhUIBuVwOlUpFgJjGlp8ZsARwuid6TfdKz4E+56BtVMpG3rgajbGaSQPta9Ro8eh0umXHZaDSuZyb0HdkrkqApHErlUod0BsBWqfTweFwwG63I5/PY2FhAZlMBl6vF6lUCsViEUajUZzvcrmQSqUwOTkpuKnZbIbf74fb7RZzoFIsVGiPirdVKhWUSiXxVygUUCgUUK1WYTAY6jg73avMCek5cY4sPw/+HDh3pc1S5raci6920kCL5TmgtJPTIuEiMR1vRHwh07iKoqBarUKv18NgMAiw6HQ6GAyGumvpdDpUKhXB0RRFgdvtRiAQQDabRTQaxdTUlACayWRCuVwW49RqNRgMBjQ1NWFmZgapVEpcG4DgxmazGYqiCHGYrsdFY+Keer1eJEAUi0UhNaTTaZRKpTppRAZvtVqt+4yfo6qq2LT4xkb3QYCn1wD+qFlK/5tJA61E8sKi3Z9zDS7W0nlclKNx6DMAArB8gZpMJiHCWiwWWK1WVCoV5HI5Ud3S4/FAp9MJkbVYLMJkMgFYLL+Sz+dhMBhQqVQEKBcWFlAoFKCqKiwWCwwGg+BuNHcqaUt6Lum19BkBijYCq9UKk8mEarUKr9cLv9+PWCyGbDaLYrFYt6kR0PhzkZ8rAZo/I/nZya/5817NpIH2NZJFOy62EXhX4rz0ff4fWFpcRqMRFosFOp0Oer0eJpMJZrMZVqsVZrMZBoOhbpHb7XaxsEulEoDFChbEOUulEorFIpxOJ6LRqOB+RqMRmUwG8XhciLAEVpvNhmAwiHQ6jXw+j1QqhUKhILgtF0trtVodl1QUBUajEXa7HcViET6fD+3t7ZidnUU8HsfCwgLm5+dRLBZX1EllA53MXWURWn6u9BvIG+ZqJA20WG6E4lZRMg7xRch1q0ZiIel+dIzAajab4fF44PF4hA5JemOpVBKANplM4noGgwEWi6VOnC0Wi8hkMnC73TAYDKhWq2KjyWQyyOVyqFarsFgsyOVysNvtWLduHVpbWzE+Po5wOIx4PI5yuVwnigNLoj/9JzHZYDDA6XTCbrfD4/GgqakJOp0ONpsNa9euxczMDI4fP450Or1MGuGA5c9Ofm5801yJm8qW6NVIGmgZydyGG6L4QuFcVhYB+aKn75KLJRAIwOPxoFQqIR6PI5/PCzGUOInBYIDdbofNZoPNZoOiKEilUiiXy4Lrlstl4cIxGAwolUqiQj+XCIxGI8rlMorFItrb2+FwOGCxWGCxWGAymep0ankz4iKsyWSC0WiE1WqF0WhEPp/HsWPHYDaboaoqvF4vWlpa0Nvbi1deeQVDQ0Ni46CxuGFPllRkAx7/jIOU68+rmTTQvkaNLL+VSqVOVJZ3ec4d+Bi0uEwmExwOB2w2G5xOJxRFwdzcnOBwpENyN4bJZILdbofD4UBTUxMCgQAmJiZw+PBh5HI5MTaB3Gw21wHPYrHAbrcL62wmk4GqqrDZbLDb7QiFQlAUBeFwuE5np+/Tn7yZWK1WuFwueDweDAwMYHBwELVaDV6vFz6fDwaDARs3bsSePXvw3HPP4emnnxb3Km98MihliYZvfq8nZq9W0iKiVqBGIvNKQRWNOLLBYIDZbIbNZoPD4UCtVkM8Hkc2mxUGJQIHt9qSy8VoNMLv92Pt2rXYtm2b4Jq1Wg16vR5Wq1VwQuJ4xWIR1WoVTqdTlAkl36vRaEQgEMDatWuxbt06tLe3Cz8tt8oSh+bWbpPJBJfLBZfLBZ1Oh/n5eXi9XjQ1NSEcDuPVV18FsFg/S6/X4z3veQ9uu+02bN26FWazue75yLYA2e8qb2KyBLPauSyggVYQd/wTceDKr/kx2TJqNBrhdDrhcDhgNBpRKpWQyWRQLpfrziOfKb0n8bRcLsNqtcLn88FisaC1tVVUldTpdCKCK51OL4tcIiMS+VZpzFwuB7fbDbfbjebmZmzbtg09PT2wWCwC7DQ/+h5ZjUn8DQQCSCaTqFarog5VZ2cn5ubmhJFsaGgIRqMR559/Pm699Vace+65sNvtdc9M9n/L3FXeAGWj1WonTTxmJPtXiWSjCtcb+cLS6/Ww2+0IBAIwGo2Cw8nAItcMjcUjplRVhclkgtfrhd1uh91uF/owWZvJb0qcluZbKpXEwiduS0ax6elp1Go1cTwUCmHnzp3Q6/UYGBhANpsFsOiLJQ5rs9kQCASwefNmdHV1wWg04sCBA2hra8OmTZvQ1NSEiy++GA8++CDm5+fR19eHWq2GiYkJAIuFxW+99VY4HA7s27cPmUxmWWQZJ24b4JFTdK/8vNVMGmjReAEB9YYPrlvJoXoksvr9fnR0dGDNmjXI5/OIRCJQFAXFYhHFYlHosEC9oYoCIGgxEmfz+XwiqsntdqOpqQmVSgVWq1V832AwiJIu5XJZGLeIc5Hf9/jx49i7dy9aWlqE9VpVVRQKBRiNRszMzCCdTgOAMDqFQiGsW7cOnZ2douVHOBzG3r17YTAYMDExgUAgAL/fj+HhYVxwwQWw2+2Yn5/H9PQ0zjzzTLS1teGmm26Coij4zW9+I8IrZbcOlzzoefINkdsXVju31UD7GjUSxei47FeUifTPlpYWuFwuhEIhhMNhYWzS6XR1eixfoDxiSVEU+Hw+bNq0Cc3NzULErlQqiMfjSCaTdX5T0pt51FChUBDzpCCNSqWCEydO4JVXXkFbWxuq1Srsdjuq1SpqtRqsVis6OjpQKBTg9XrhcDigKAocDocQqUulEl555RVxTz/60Y8wOjoKnU6HSCSCYrGIfD6PzZs3w2q1IhaL4emnn8bevXuxZs0afOADH0A2m8Wzzz6LcrkMoF6CoedCBin5edMms9q5LKCBFgAEtwSWc13ZqsyPk4W4ra0NbW1t0Ov1SKfTOHr0KHK5HAKBAFwul3DLkNGHuAjnvABgsViwbt06rF+/HqFQCC6XC3q9HolEQsQck79Xp9Mhn8+jUCjAarXW6bMUZEFcFwBSqRSee+457NixA36/X2TJ6PV6uFwu+Hw+OJ1OoZNTvDOJ988//zz6+/uh0+nwxBNPIBKJQFVVEcpI/luq3evxeGCxWDAwMIDW1lZs2LABH/rQh5BIJHDkyJG6uGv+nOWAFlnf1UgDLYD6sDvZ0Q+sLD5brVaceeaZ6OnpQaFQQCwWw9zcHLLZLPR6PTKZDLZu3YpgMCjEOhJBSUejQHyv14vW1lasXbsWTU1NInihUqkgkUggmUwKYJbLZdhsNhgMBhSLReh0OpTLZWHxpaAMAHW699jYGJ5//nm8+93vhtlsRjgcFsWzfT4fAoGAACr5cyuVCgYGBvDrX/8asVgMVqsV+Xwefr8fNpsNpVIJ+XweHo8HJpMJer0ebrcb0WgU7e3tmJiYwPj4OPr6+rBlyxZcd911iEajmJiYWMZlG7nd6D9PXVztFmQNtKgPW5SPN3LzULrczp07cemllyIcDiOXy2FsbAy5XA7r16/H2rVrsX//fsTjcWzbtk3opNR+kvJYdTodmpubsXHjRrS0tMButwuu4nA4UCgUEI1GRSxxuVxGOp0Wftd8Po9arSYyfYxGI4rFohB/SfQulUrI5XJ49tlnhZ46NDQkeuMUi0U0NzejqakJDocDAISR6r/+679w7NgxwbkpSIS4vsPhwObNm4WobrFY4PV6kUgk0NHRgfHxcTidTvT09GD37t0YHh7GI488glQqJZIC6Nny/9z4pIF1iTTQvkaydVIOVaT3FLq3a9cuvP/97xd+y2q1ilgsBovFgve+970444wz4HQ6ceDAAej1euzcuVNwzenpaaTTadRqNQQCAaxZswZOpxN6vR7RaBTRaBRNTU1wuVzIZDIYHBxEJpOB0WgU1mXaaCj1jsRgo9GIVColxO98Pi+ygnK5HAYHB/Hoo4/i/PPPx8mTJzE9PQ2r1Qq9Xo9IJCJaQxqNRoyNjeGhhx7CoUOHkMvlRHAF6bw8isvhcMBgMCCVSgnfdLVaRbFYxObNmzE6Ogqv1wuv14tLL70UJ06cwP79+xtulPLvQb+BHP64WkkDrURyPCz3D5IOe8455+DGG2+Ez+fD4cOHRYBENpvFmjVr0NnZiXK5jO7ubvT39+PFF1/Exo0b0dHRgdbWVnR3d4ssHpvNJlw3xWIR8Xgc09PTyOfzyOVyGBkZwYkTJ4QRy+fzQVEWY4wrlYoIMaTMHMqVpfeUzUP3kc1mcejQIREWSRFLiUQCc3NzSCQSsNlsyGaz+PWvf42DBw+iUCjA7/dj165diEajyGazgvN5PB6YzWY0NzfD5/MJEZrui0TpYDCIhYUFOJ1OdHR04KKLLsLY2Bjm5uaWVe3gJGcLraSqrCbStHssLykjlzrhsch9fX246aab0N3djeHhYSwsLECv1wvrsMfjQTgcxsDAACYnJ+F2u3Hy5En86le/QiqVgtlsFgEOgUAADocDLpcLTqdTJLmPj4/jpZdewpEjR3D06FHhY6VIJT4nHkQBLIZB+nw+2Gw2oeMSkU84k8lgYGAAc3NzwhqcSqUQj8eFFfjgwYN46qmnkM/nEQwGsXnzZsHlCTQ2m01sEL29vTCZTFhYWBBAo7zdQqGA1tZWuFwuqKoKh8OBXbt2Yfv27UJqkJ81UL9xNgpuWa2kcdrXSOaw/I/02I6ODtxwww3Ytm0botEo5ufnYTAY4PP5MDU1hWKxiHA4jB/+8IeYmZkR4YilUglPPvkk9Ho9LrroIoRCIbjd7jrdLZ1OI51OI5vNIpPJIBwOo1qtIhKJIJ1OC/9lOp0WUUoUxUTGLO46yufzoqk36aI8mTyTycBgMAjDlcViES6moaEhPP7440ilUnC5XNi9ezeq1SomJyfh9XphNBqFK0lRFGzatAnd3d1IpVJIJBIiA0mv1wu93OFwCLdVIBBAKBTCnj17cPjwYUxNTS3TaxuRlpa3SBpoUS+CNfIFKspiBYnLL78c5513HqrVKvr7++H1eqEoCrZu3YpEIgFFUXDs2DHodDqR2UMc2GAw4Gc/+xmGh4fxjne8A9u3b0dbW5vQRwm4hUIBer0exWIRIyMjdXmvFGdss9mE2FssFsXmQJyU0vkIWDw5gZd54UatpqYmhEIhTE5OYt++fZicnEQoFIJer4fX68XExAQqlQoWFhaE2FsqleBwONDb2yuitTweD6LRKJxOpyhnQ5Zvt9stalCZTCYB9pmZmYZWe628TGPSQAvUWYjlukTkPtm+fTuuuuoqeDwe9Pf3o1wuo7W1VUQvrV+/HsFgEOFwGD6fD36/H3q9HqVSCdFoFMlkEplMBq+++ioikQhGR0fxnve8B729vXWBEblcDuVyGeVyGdlsFvl8XoiGlChAyQGUskdBFgDq/J8UiUUBC6Tn8lxeGtPpdGJhYQEvv/wyTpw4gebmZrhcLsTjcRw/fhw2mw1ms1mEIlJS/ujoKGZmZnD06FF0dnaip6cHs7OzQt+mNMNisSjygknvbmpqQltbm5BGZJJdcJpOu0gaaNE46onv+sFgEJdeeik6OzsRiURw4sQJbNy4EQDQ1NQk3Bnvfve7cfjwYWSzWZF5o9frEQwGYTabkUgkhMj79NNPQ1EU3HDDDWhubhaBEcTByEVDObMkuur1ehQKBWSzWSEW8/PoXijqiHycFBoIQPh6uUW8Wq0Ka7LT6UQoFKorLcs5NABRLG5kZAS/+tWv8M53vhN6vR5dXV2oVCqIRqMIBoPQ6XSw2+1iHHJJUfx2c3OzKIdD832jv8tqJQ20aBztRAvDbDZjx44d2L17N4xGI6amptDe3o7W1lbkcjkRvK/T6XDeeechn8/jyJEjdVy6VqvB4XCI3NrJyUmk02k89dRTUBQF1157LTweD1paWgTHozQ9iljy+/3w+XzCkDQ9PV1X04kC7En3NZlMIpeW/shKTZyOAjLIepxIJKDT6dDd3Q232y2CNlKplMjlpefDxe5XX31V+Jgp6X5iYgI+n0/oy7lcTmwq8XhcADEYDMLhcCCVSr3ub3GqUNLVRBpoXyMufgFLi6epqQnnnXceWltbkUql4PP5sGHDBqFjknW0Wq0iFAph69atGBsbg8PhQDabFdkzpGf29vZiw4YNePrpp1GtVvHss88ilUrh2muvxcaNG0U+LenIOp1OJJorioJ4PI54PI5YLCbEW4PBgEKhIHymFFRBwJeJ67dOpxNmsxnpdBqZTAbr168XGUWlUgkul0uUaaXQR7Ji53I5tLa2YmFhAf39/XC5XIjFYmhra0MsFkMulxPJ/wCED5cyoKxWK3p6etDV1YX5+fm6Koy8GiP9HiQVrHbgaqDF8jpPwFIKXU9PDzZt2iRigKm6YaFQgNPpFPqYqi4WZNu5cydeeeUVRCIRBINBjIyMCA5Hhp9QKISOjg5ks1kYDAYcO3YMyWQSl112GTZt2iTieQEgnU7DbDYL8TUajQpxlzYaCmfk9aIoUolyZOVUwkqlAp/Ph46ODtjtdkxNTYlEdzIWcQ7H46RJb6akBQCIxWI4cuQIzjnnHKxdu1ZIFKRGkHGtWq3CZDKJa3i9Xpx11lk4duyYUB8A1N3f6xXUW42kgRb1yewctGazGZs2bUIwGBRB8aSrUnVCYMmQRfmrbW1tiEQimJiYQDwer3OthMNh4R+tVqvw+Xyw2+2Ix+N45JFHsHXrVpxxxhnYsWMHTCYTjh07JsIeI5FIHXjoP9V7Ig5tNBqFMcxsNovE9UqlIoI0XC4Xenp64Pf7MT8/L3TvcrmM8fFxkaxAxjDaYHQ6HZLJpDAylctlmM1meL1ejI6OwmazYffu3WhubhYWaIq44il39Mx494REIiF+Ey4WN6qtvJpJAy3qA9O5OObxeLB+/XphAPL5fKKoGiWKc72Scmb1ej2ampqE/5FXpygWi8ISS35MCgOMRqM4ePAgJiYmcOaZZ6Kvrw96vR6/+93vMD8/vywfFwDsdjv8fr8ALQFMURThhrFYLEin0yIZQK/X45xzzsH69esxPDyMaDQKm82GZDKJRCKBdDotspOo4gZFV1E7Eb/fD6/Xi6mpKfGs8vk8hoeHMTAwgN27d+P48eOIRCLCdcT16mQyiVqthqamJqFj8/S7lWpLa6SBFgDqwuiI9Hq9yLoh8axUKgmLKtcVFUURVfmz2SwqlQrGx8cxMjICp9MpqioSh/Z4PDAajYjFYrDb7SIlrqmpCbOzs5iensbzzz+PLVu2oKenB7lcDplMBrFYTIjDFHNMBqNisShyaSkO2mAw1ImilDu7du1aXH311UilUjh48KAwRpE/tVqtClGVqmHodDqkUilkMhlRWQNYqulMVu35+XnMzc0JThyJRBAIBEQGEG1cw8PDUFUVPp+vzk1FYJWzruSaUauZNNACDX2zxC09Hk+daEbAJUMULbJyuSzCAGu1Gqanp4Wey3vgEMfIZDKo1WrI5/Mwm80wmUyivAsF/R8+fBjd3d1oa2vDrl270N/fLyzCFOucy+VE9g/Nm3RQLg7T9Wu1Gubn5/Hiiy+iWCwiFovVhUdSoAYBiTYHGiObzSKZTOL48eMi7pms3mSIGhwcRDweh16vR39/P4LBoKjlTK4jiuxSVVUYreQ2IMDyyo0aaDXQAljeqY2OUU4p+TFJD+V1n4jrJhIJjI2NwePxIJVKIRaLwe12w263w2q1CrHY6XQimUwim83C7/cL4xRl+VCp0nw+j6mpKRw/fhwtLS3Ytm0bLBYL9u3bh3Q6LUAqx+dSVBQtfgqsIGtssVjE7OwsnnjiCdHqkovRlERA2UzUAYEivKjuMbAYHlksFjE+Po7m5mb4/X44nU5MTU2hv78fnZ2dolqjz+cTUVwERKvVinK5jLm5OTFmoxpS3G3Fy9CsVtJAy0gOSi+Xy6JrHIGEBzAQkAuFAiKRiBCJqUYxhTnm83moqgqn0yn0y3K5jFwuh1QqJcBCxcRVVRUpdSaTCePj4/D7/aIUKwERWL64ebG3lfJUa7UaEokE3G53XX8h6nBA3JZEWvoetckkkZt6COXzeczMzECn0wm9f2BgAFu2bIHD4cCRI0fqyqlS0Thg0Q00OzsrgkHke+K/Df3XQKtRneGDL5ZYLIZwOIyOjg4hOlLAAQ9+oAB8RVlMmZufn4fb7RbuoXw+D4fDAVVVMTc3h1gsJkTaarUKs9ksKl+QPsndNPl8Hs888wysVqtwxciZMcDyfkSvR+TTNZlMot2Hoigii4fG5R31SCfntZepjy1x8I6ODvh8PoTDYZRKJXR3d+PZZ5/FwsICOjo6kEwm4fV6xfNMpVIIh8PivuT7ka3Gqx2wgJaaV0d8QVC44dGjR+uAoqqq6LdDC5n65rS0tAgQrl27VpRgsdlsgsNOT08L/Y0aOhcKBUxPT+PkyZOYnJwUbhTSTQEgk8lgdna2oaVbDv0DsEy05JsRcTu9Xi/ETUpG4KI/cV8icvmQpddiscDlcolKF+l0WmQnxeNxDAwMIBQKwWw2Y2ZmRgRoUNVIo9EIACI4pdFcZSlBA63GaQXJC6VarSIajeLw4cO48MILha+WLLA8TBGAsOICEEYsn8+HVCqFgYEBUbGQXD16vV4E+1OmjsPhEC02eFADgVjm0I0MMmTplSs/0LyAxTxYqqtMIjBVmaDADRqLg4ZAzCUTEpkpHjoWi8HpdAIA+vv7sWnTJoRCIczOzgJYSgukkjh0Hf7sZYDKrp/VThpoGxBZhbPZLAYHB0XWC4UNyvqtqi4mdlOGjl6vFxUcCoUCFhYWACwCmwBP4xOHI9cQGZJoHhSYQVFO6XQa0WgU6XS6riI/jx6SdVpgSU8kCzV1P+Bcl4BOY8hj8eAImiN93+VyIZFIiIobTqcTk5OTOHjwIDweD+bn54XPl8RhavfpcDjqkhdkUZgDldftWq2kgVYivqtXKhWEw2EMDg5ix44dmJ+fh6Io6OjoqMtRTSQSyOVyyOfzSCaToibT7OwsTp48iWKxKMqpcpcMAYFAQyACUGdsAiC66RFYuDVbjuhqVCyNgEe6rCxZyIYerhuTD5rm3igO2Gw2izjldDqNlpYWlMtl7N+/H+vWrUMul8PMzIwI1KCUPYfDgVAotKJ0QHOX57iaSdNpXyO+GHlPn0KhgHA4LDoGjI+Pi3YfvKYwLWBFUeD1emE2mzE3N4dkMim6qJP1lFwoxEHp+vQZAGElpmvwBHebzSaqUnAdkFuH+XsuZpL4TBuFXImSc2yap8xx6Xs0JxKbXS4XLBYLMpkMMpkMLBYL4vE4JiYmkE6nRRNqo9GIs846Cy6XC0ajEb29vaJYHG04K1WpaGRZXm2kcVosr/THd3YyqhQKBfT29gKACBQgAwp1XqeIIgoYmJ+fF60neSAGX5QEUuIyJH7TxiG7cQjE5IuV583vSQYtd1XxND0egUTn0gYhW3CpbA0ZkWgcskRTXeRkMonW1lZYrVYkEgk4HA5MTk5CVVXBlWdnZ2E2m9Hb24v29nYcP368btOQDVMyx12tpHFaiTg3IsDEYjGkUik4nU40NzeL6v4U5ke5oE6nE+VyGUajUXAUWviUV0v6IInDHDQEXP49Ok7VLGQQyy4S6sNDGTvE3UmcpXnQWMTR6bpms1n8yal9tNkQ6Ll4ToA2Go1ob28X0VMOh0PMIRqNCj90OBzGyZMnkc1m0dzcjDPPPFNY5Hl+sHyPsq6+GkkD7WvUyN9JACkUCshkMnVVD6klB8X8BoNBAa5isYhcLge73Q5VVUXTKeKOnEMSgInoGjK3IRcR1X3iIivnSNSsy+PxiIgsEmctFoswdvGAEbpP7qumEqvk7uJBFsStuV7L0/mcTie6u7tRLBZF5g49R7PZjHw+j4mJCUxOToqa0Vu3bhWJBXLzLfp96L3GaTWqE8noPbC0QAqFgohq4tyyXC4jGo2KqoUUHBGPx0XrDjqPg4xCBTlQKDKJW2mJ49MipU2BzufRTBzkXFcGIADb1NQkMn0AiKJzxDXpjxeM40XQebkaHnxB59HzoT4/7e3tsFgsokrjwsICRkZGUCgUYLfbsXfvXlitVkSjUQQCAWzZskX4p4n4/dFvs9o5rabTYnlhcqAeyMQ9aaHSMcpqyefziEajmJ6eFhFQNGa1WhV5rSRK8ppNXF+UgzZ4potOp6srykYclIqH03fIr0vXJjHeYrEgm80inU7X9eHhnJsSFwCI+ZFuq9Pp6j7jHFpVVeH2IdVhZGQEoVAIzc3NYp6lUkmU07FYLFizZg3C4TBmZmbQ19eHnp4ekaLYyIotGwlXK2mgRX1AOnE7fpy7OAgYFCBArp7Dhw9jfHwcqqqKwmVUAoYMUbzQOOeMnHMSoMkyy4MoSDemY1SmVFVVIQlQJhEF5hOoiBNS1hEAEZJIYi1Pi+OZPxSuCSwFbwBLxjP6HkVUORwOJJNJLCwsiDBJSusjC/P4+DjC4TCMRiOGh4eRTCbR2dmJDRs24MCBA8IlJhvaNOuxBloAS6VTOcdt5NgnwwuJqC6XS3DK0dFRZDIZOBwOURkxm83W5ZFycZdEbC6SkzWaQMyjm+TyMqVSSYihtCEQkWgr65wmkwkul0sEdpAxjBIWuD5JXJRvIo3imWk+/J7I2JVIJIQFnevAJpMJc3NzqNVqWLNmDSwWiyi72tvbi8HBQUQikWW/Eb/maiYNtFjiHpzbENFCo5q9AIR1lX8nGo2KCCkunlIFRVrccnNkboUFlrtq5A2ExiK3EFlsOXByuVzdfVFgBuWvEhANBoOI4OIuHO6SamShbvRe9nOThZpXWdTpdCKRP5PJwOl0ig2OEiYovW9+fr7uN5Kvs5pJAy1Qt0BlwFJRbeoXS4s1m80K/Y1KjPLPKbOHUtA41yOwkf5Jx4iTEbhl8ZDmRhyZOrTzmGfuhqEoJofDIZo88+70pD8DS/G/BGIZrPScGhEvNE7qQTqdFp3oaQy6Phm6EokEIpEI8vm8KPw2NjZWB3R5DnSN1UwaaLEUa8z1VjquKAra29vR1NRUFx4Yi8VQq9VE5wD6LonPqqqK4H8ai7icbNgCllLliDsSsInz8dcktlJAAzdkUfQVJQBQlhEPXaTKG9lsVsyVkt0bJRwQwOleaLOheyAQcgsyz9wBliK8KLNJURREo1FR+I42EOrGwIFJG8pKUVKrjTTQonHzLWAp3rerqwu1Wg3hcBg63WId4pmZGVFWhbgT1QImKyk1iOYuG1kEJ7ATIMjwAyxVxeCF1QCIGlMUiaXT6erAWiqV4PV6hUWYc3gaq1Qqia70tCHQpkLXJm5NxjTi/mRx5sDkYjU9y0bPlqfgUe4xNf+izCreHYGrB/z1aiYNtK8R9wfyIAO/34+enh6Ew2E8+eST0Ol0uOSSS1CtVuFwOERzaDqfajZRTWRgKW64kd5MeiovLs71Qp55AyyKwB6PR/hGiQva7XbRspKaW/t8vjrjF1l4OShISqCyOsR5AdRx+FwuJ+ZCriHKOqLjXJSXjVZkoCI3E1XuoA2AYqqp5SevYEn/uRV9NZMGWqwcdWMwGBAKhdDW1oZisQi3241oNIrx8XFUq1VkMhnRe0en0yGRSCAcDosesWR0kuOLGy1E7melz2TxkqKU0uk0FhYWUKlUEAwGRdV+4qIUvE+bBoGIuCCv3Uz6KIGGxGgK/qAmYlTDiUdGke+ZODYBlSQH0rFpc6GNiSLEeBGBUqkEj8cjqjOS+iGDtZGOu9pIi4hiJLt8TCYTOjo6RA0kMugMDAygVquJYmvEkeLxOKrVKpqbm4WlFlgCKw/UJ52QjlNsMQGEwiSJe2azWbEBRKNR0bGdCoEDi2DxeDyiawC5ggiw/N6owHgwGKzrNysHMXDrNonhZEmnfOBGyQY8SosMW3R/er1eWOAJ2NThz2azYdOmTfD7/XXuMJoT/U6rmTROi8ZNn4DFpPXu7m4cOXIEhw8fRmtrq3BTzMzMiMJrer1eWEHdbrdoc8k5OOeCxWKxznhFYKnVagKwvB+toihCZ81kMkgkErBarfB4POI6tKCJu3OuLvucCUwulws2mw02mw1TU1OirCl17ePcnj8jKuhGsdQ2m01sKnQd2VJO86PoLXqONpsNiURCBKo4nU5s2LABZrMZ+/fvRzKZrPuNNE6rgVYQ12VJdFyzZg30er1oX5lKpdDS0iJ69IyMjCCdTte143C73aJaodFoFByCwh4p8J/ETy7CplIpJJNJwaUoZ5aAReVcyDJNHI8vYhJpaUxunebuHQIiNYLmlnDaYMiQRSVWybpMwRsU1khjkXuH+5xJ3CejFvljfT6f6AZIOq5Op4Pf78fOnTuFsY/UDxpDIw20ACB8pFx30ukW6/5GIhFhIabKg8FgENPT00gkEjCbzaJXLFVjkC2l1AA6m82KYAIyOBFXyufzogojhRBWKhWRdEBlWkulElpaWkQ0FomtHJTcMCYHavD7JdcOJRNQFhCNy/2yBECKX6bNQafTIZPJiNe8Igddl0eBUUJFOBxGW1sburq6YLFYkEgkEAqF0NnZCa/Xiw0bNqC9vR1TU1MrWpNXK2mgRWPxuFarIZPJCJcLVVCkYHav14tisVhXQYIHJdACzmazWFhYQDKZFByDfKtWq1U0uKLrUNwvzYHqCieTSeTzefj9ftFmQ168PG+2Udwuj1ri86SIKBLBuVGM+vuQf5UkBGAxqIIATmCVxVj52sBimGU4HIbD4UBnZydaW1tFAoHL5UIymRSGMW7RX+n3Wm2kgRb1Ve3pvaqqmJycFPmfZESKRqOilyoV9SZuSjoZWZOpEDeBn4Cdz+dhtVpFJUYSU7lflhY7pc4BgM/nQzAYFInkcugglxaIuPGGxyE3MiBZrda6zapWqwkRmBIS+JiUzcRzhOlZrmSRJ+kjnU4jEomgtbUV3d3dOPvss+HxeETng2w2K3KYOYeV9evVSBpoGXEAqKoqyp6SrqWqi0H95Ju1WCx1aXiFQqGuiRXl2nIjEbDUEpNbhMmqzKORqKEWlWSl8i0yJ6Ux+TUaxQgDjbkusKTzGgwGOJ1OoWe63W44nU7Mzc2J/FuKbebWdp6hROPJ0VVcZC6VSohGo6L+saIoSKVSqFQqmJ2dxczMjNCv5UgoLZ9WIwD1C4EWcrFYxMLCAsxmM1paWkTvG7KA8hYhAETpGRJ3KUiAxxZz0RlAXa8cAMKvCSxFUNlsNvj9flHlkftvuZWW7oNz10bA5sEWXN/kARxUdaNSqcDtdsPtdovmWyTu82R9zmlpXH7PcqgosMipp6encdZZZ4mIMwJtPp/H7OyscBGtdqBy0kCL+q7jRPw9tcDg/lUSZXk5FtJhZYMWD2MEIDJuANQ1vOJ1o0hfNBqNde0yCbC8kiIXPUn0pfnLBeBkDszBT+8JWCQBlEol0VbT6XSiqalJ+IpJvCdjGq/IQRJHowgwYHGDWlhYQDgcRjabRSQSEf7iiYkJRKPRhrq4Jh5rBGDlzBGy5lIzLVp0FGJIXQJogfMNgBLbuZ+SwFksFgXQycjFax8TEBwOB5xOp/DXkiWVgMBFTll/5MkPXH9tVGmx0YalqosBJjzSSafTibjqYDBYl6xOGU/ZbBbZbFZsbo0MY3RNMrJRkjz5qqemplAoFMS9EvF7Wq2kgfY1kndvWlQGgwHt7e1obm6Gz+cTxdyy2WxdkD9P8uZiIflmaUxVVUUcL1mR+RhEBoMBgUAATU1Nwu1DhiHSuxuJ9HK+LT9O/wmEXMym9ySmc2mB9/shCYM2M75ZkcVXVZf62FImES8Sx/3hVFeadGij0SgMblTcnN+jvMGsRtJA+xrJeh0tELfbjd7eXmzfvh3r16/H8ePHRamZcrksuAMHHBEBi1t2+XuuA9I1yW/qcrng8/lE31gCC9ePaSyeWE8iMs/EAQCv1ytEcmApsweo58LE8fk90Bz5xkTzJQATZ6fvUtmZYrGIZDKJubm5hqI6BVzQ2AaDAcFgEA6HA2NjY2L+q527ctJAi+Wd2bgu63K50Nraii1btsBgMGDz5s2i/UUsFsPvfve7ugR4Dl5e3wlYarFBi51yYumacsK61WqF1WqF0WgUYY/y4uXunnQ6LRY5bzVC4KWQS86l5aASmjNdi+fhEkB5fDKPMyZAEogpaUBRFJGySCoBf/bksybLeEdHBw4dOiTuhc9P02k10AJYngTPra6UoJ3P53Ho0CGsW7cO27dvRywWw9jYGGq1GtLptFjQNJ5cF5g4o8xtuBXZ6/WitbUVAISubDabhbGH1wMm0NBrEkEpVY8ASnmqjfJluaGJ+0NJryauyTcWYKkkDRebOcnGLbPZjEAgIKpVcMOSoiiw2+1oamoCsNhpz2q14qWXXkI6na7bBBptWquRNNBieX8YLioWCgVMTk5iYmICNpsNzz//PHQ6HVpbW6EoS/G2RARQYMlaTOIrjU06Hbl6bDYbPB6PCOCnuF8KdyTrsjxnAHWbDM/s4eKq7Nqh/5RJJAdOEIe0WCxCbyWDFAc+BxKXKkii4CoHjSGrEYqiwOFwiCCOsbExvPTSS5iZmVnGkTVaJA20WN6UmS/gZDKJ+fl5vPjii6Ld5TPPPINLL70U+Xx+WdQO59i82Bpf1GTEodpTlF5Hn5tMJhFwQN/jIiiNwTvo1Wq1uuLlsuWYu4VKpZIQV3nanQxK6m6v0+lETyLaaEjEln3BXL+VVQNgqQcRPV+DwQC3241CoYAXX3wRQ0NDddUriDQ/7RJpoH2NZG5L4mw2m8XU1BTcbreod2w0GjEyMiJAJOuuHFyyWEc+30AggEAgIBLSeRA/55acMxIHloMj+Jy5sQtAXQsRCr2kyCbuk+Vg4mI+d+dUKhVRrI6Dlfth6bnJvmKyaMsVKxVlsRRtKpXC8PCwCBmVxWJZUljNpCXBo77NJRHXOWdnZ/HKK69genpaiH6UOMD9pjQWN8hwUdJgMMDn86Gzs1NU3ueciYOR5sAXKeegdIxbrrkLh7tHCMS83YfMEfkcCMBcT1fV+mwlfpyI+6jpfvnGxqUBuh8y9KXTafT19eHGG29ES0tL3XPghi9Nr9VA25BkAFPoInEIi8WCZDIpOIfsO+QLi7J2zGYzWltbsWbNGjgcDlEXiou+dD6JsbL+JzfBklPh5BQ4zqkon5cSEORwR/6eX5sbv/iz4B0MiJty0ANLLi/y21LSO92nwWBAa2sr/H4/pqensXHjRlxwwQVwOp11vwWXJlY7lwU08RjAcmsnN6TQe5fLhV27dgk9MJ1OiyZbVDaFIoDoe2SF5QEDHORUM4n+cy7KgcS5n8xluRWX+2lLpRIsFosIiaTgBQKmrJeu9Dxk/RiAKA8j9yLi/l1u3a5Wq0ilUnVlZ6gw3saNGwEAkUgEZ511FhKJhAgF5QZBQAMskQZaiWRXCgDh1kkkEmhvb0epVMLk5CRMJhPcbjdUVRWWUfou74NjMpng8XhEKKLMibmRhq7HdUEuLsscnf7LIiNVVySxmFdZJEswN/ZwHzIPtpCNVDQ/+i4Xrflz42CmzChK5qfn1dzcjHXr1mF6ehpDQ0NQlEV/bjweF2PLv4MGXA20guTFIFtqk8kkhoeH0dfXhwMHDoi2FTabra70KS16CmpQ1cVyqlToTS4NKkcfyaIyFzGJK3O9mURp7gemUEQAguvKxjKaqwyIRpZgmUh8pg2Ji+x8HJo71Wc2Go3IZrNC8ti2bRva2trw9NNPY2ZmBuPj4yLKjM+FnptmQV4kDbSvUaNdnIudlUoFJ06cgMFgwPDwMEwmE3K5HJqbm0W5FL54CUjk76TPeA0nokbgodeyIYrO44XbqIg4nz9xfRJFue4sg5FHR8nXeT1rMF2fRHg+f/qcSr7Kc1izZg327NmDarWK+fl5BINBxONxzM/PN5QcuH6+2kkzRKFeRAXqXR5EiqIgEong0KFD6OnpwZ49e5DP59HV1YX29vZl4iEVdrNYLKLSBPlE5f+cZADRtUkElY1RBBpusOEuE/6ajyWL35yD8w1Bdr/wjYSyhThg5edHCfMkeVgsFoRCIezZswcdHR0YGhqCwWDABz/4Qbz3ve+Fx+Op06X5vfLXq5k00L5GMkDpP/+jGN6+vj5cdtllyGazaGpqwo4dO+BwOASoiPu53W4EAgHRHkRe3NzS2+g4iZc8h5ZiislaSz12OCfnnJEHeQD1ebPczUTHCITyhiCn8vEMJwIyj76iTSwejyOZTIq5ejwenHHGGdi0aRPy+TxGR0cRCATQ2dkJu92+bAOSresap9VAC2BlkMoLhMTemZkZzMzMYHZ2FqlUClu2bEEoFKprYEXcqK2tTUQScb2Mp8jJ/k1uBSbAcg5IHE623vIFT8Aibi8Dlzh/I78s56jcgktA1+v1ImoLqBeRKeyR3DwUl10ul2G1WtHX14fdu3fDarXi8OHDyOVy8Pv9IvqM+5A5WGUX1momTadFfUI5Xyj8PS2UQqGAJ598Ei+88AKq1cX+szt37kR7eztGRkbEd6j2MZVZJfePLE5yMZjPA1gK+ePzoUwZAHXcmEAll8AhgFLSQSNRmVurub+X6948SISAybm2LFaXy2VRepbGam9vx/nnn4/u7m54PB60tLTg5ZdfxqFDhzA3N4fx8XERqdXIzcOfw2omDbSvETcEEUeh45z7AEA0GoVOt9hJbmBgANu3b0dfXx9eeuklUTuJEsKpzlFnZyecTmddSCE38tBrzmV4oAKJn9wNw8EpJ6rLYjD5grlBibJ8gPpi5vS9RgYpLqJzoxh/ZpQjm8lkBIe3WCw488wzBWCNRiNyuZywylN5HV7jWL5HIjl5YrXR6r57RnJAAQEIWL7bK4qCYDCI888/HwaDATMzM1i3bh1CoZDgROQbtVqtIhGci5yc63GuInN67hrivlIuIvJoJD5fbmQi1wwP1qdz5NS7RnOhZ0ObEXcr0flcnE4kEqLIHQC0t7djy5Ytov9QNBrFxMSEKABPz4vPQw7L1MIYF0kDLSN5gXKOJxtHWltbcckll2DdunUYGBiA1WrF5s2bYbfbRRIAr3ARj8dFwy1uBaZxG1l3Obfk/+k156wyF5WNRvTHOTgfl9+7zGVprnq9XkSA0Vy5IYvEdOqWQPdusViwefNmuN1umM1mUbiN6kBREXcugmuhiyuTBlqJ5J2c7/BkmSXfYjKZRGdnJ6LRKKLRKLZv345gMCiyaKhZFmUHJRKJZdyTuCR35fDIKgIPr+DPwcLH4u4ibsWlz0ms5d+Tgcfvmz6n71OGD5+rrPdns1lMTk6Ke1UUBaFQCJs2bYLX64XL5cLCwgKOHz+OSCQiakg34qKyFbvR5rUaSQMtlu/sPIwPWJ5tAyzqtc8//zwOHDiAyclJDA4Oor29Heeddx68Xq/QRckQoyhKnXWU+2i59ZW7S/hC5fomF39lwPF74TqywWAQJWzITUT3SToyH5cT1UEm15UMMi7mU/QTcXWz2Yx169aJlh/VahWDg4MYGhpCIpEQZXRkSzFRI3VitXNezRDFSDYGAfULmC+efD6P5557DsBi4MDg4CC2b9+OvXv3Ip/P47e//a3IBAIgjD7ZbFYEW3B9lhuE5EAPvonIoOHGGqq/xK3I9EccnaKnqB8uj5ribigakwrLEYeVNxHaJMrlMmKxGGKxGKxWK3K5HFRVhcvlwqZNm4RYHQ6HMTo6ing8LpIuOGBlgPLfRtNnF0kDLZYKsPHFs5LRhkhVVRHtYzKZMD09jf379+PCCy/EJZdcAkVRsG/fPkSjUQGgQqGAeDwuurQT6BSlvksdF005sPlcqD8s32D498mCTSVr6DiBzGQy1fUP4pUe+XnUAYHry8DSBkebTSwWw/T0NFRVFc3CTCYT1q1bh97eXni9XpTLZRw5cgTj4+NIp9NIp9PLwNro/lfSvVcraaBlxBcLB4DM+TjAiVNFo1EMDAzA7XZj9+7d2Lt3L8rlMl544QXEYjHhJ6XF6vF4AGDZ2Pw/11Fla7EcnEHz5scagZ37Yek75HflwKQNgQeLyP5R2ogWFhYQi8WgKIs1s6gHUSgUwtlnny1KwYbDYczOzor0O95ojANU5qorie2rlTSd9jXiQJRFML6wGi2oWq2GVCqF+fl5jI2NIRaLoaurCxdeeCF27twpMnyARTGZaiBxMHIQyoYkAozshpIT5WX9lgO3Wq0KHZJ02Eb3JovH3DpN55pMJlGUPBwOIxKJ1AVxqKoKj8eDnTt3ipKzqrrYNJs6CaRSqWU6qrwhygZB/lutZtJAi/o0NW4Nlf2dr7fISqUSFhYWMDo6ioGBAZTLZVEveevWraJQeLVaRSaTQSQSEToliafcuMM5PYnvckIAF2XlBS9XxdDr9chms6JTHTeCyRk6/Pp8bgTefD6PSCSCsbExxONx6HSLfXzS6TQAwOFw4KyzzsLZZ5+NQCAAh8OBVCqFkydPYm5uTrQMoWcr66pyLPNKFu7VSpp4zIgDAKjnvnL2jWxZBoB0Oo3Z2Vn09/fD7/dj7dq1WLdunfDb7t+/X7QTCYfD0Ol0olYUjSVnChH345UrKDJJtnrLOme5XK4LTTSZTCiVSshkMrBYLKJsKY1HwOTJ+PxZFItFxONxxGIxoc9Ty07KavJ4PPD7/bDb7aJEK7UAnZ2dRTqdFhbjRoY/upbMWRuJ56uVNNBiKXiAx/k2ItnFwQ1JwFLJ1cnJSbz00kswmUzYvHkzmpubYbfbUSgU8PLLLwvONTMzA51OB5/PJ3r0cPGbwMbzejnx6xLQ6D549zxyL4XDYSSTSREXHQwG6wqt6XS6Og5M16PKE+FwWPhVCeSFQgF6vR7BYBB2ux0ulwsdHR3YsGED2tvbUSgUkEqlMDk5ienpaWSzWRElRcQt4PImxDcojdMukgba10jW4Tg1WjCypZOIetoODQ3B6XQiEAigu7sba9euxWWXXYZIJILR0VGhj05OTiKfz4v+t7LBaKXrycYneRPhIr2iKIjFYkin06LH7ezsLGq1mijjyiUInu+by+UQDocRj8eFW4g2BerXEwgEEAqFhEXb4/EgFAqhu7sb5XIZJ0+exKuvvlrXHpM/b7oProPLz1uWglYzaaDF8uAJWTxuFNjAwSODmnTHgYEB2Gw22Gw2tLS0YOvWrZibm8PDDz+MeDwuFiH5K6nLAMUJc04qL2bZ4krn80AJ+ozCKKn1iMlkEv1gM5mM6EwALBmzCoUCcrkcMpmMCAgh0ul0cLvdaGlpgc/ng8fjQa1WQywWE+ViKMBkcHAQ/f39GBkZQTKZRDKZXBY8IVuHGxn6ZPF5NZMGWolW2um5D5Pey+IsHSNLrdFoxLFjx+BwOHDuuecKd9DU1BT27dsnipyRu4U6rPt8PjidTpHOx0FJ43MLcyO/JnHqarWKhYUFFAoFUQ3SYDDA5XLBbDYjlUohEomIkqiyIYxnIVEkFYnBVLScainr9Xq43W5s27YNXq8XExMTOH78OMbGxkSoJ2+jspIE08jox4+tdm6rgRbL+55yIwmw3E8o+w/lcQCICCGLxYL+/n5YLBbs2bMHXV1duPzyyxGLxXD48GGUSiWkUilYrVbY7XZRHD2VSsHj8cBut9c1mpatvnQ9HmhBC5ws2pFIBC6XS2QckQgsp/DJ8c0Ur2wymWC32+F0OsX1KNNHURYbQ1MZmW3btqGvrw+pVAoHDx7EkSNHEIlERJzxSgaolcI0ZSPUaueygAZaAI1T0uTopEbnrnSM3hcKBVG1kTjcmWeeiQ0bNuCaa66BTqfD0aNHRYWHUqkk9Euq5G80GkUbSGoFyatDcD8sAY+KqcXjcaRSKZjNZtF9jwL5y+WysAATUCkemZplUY9czm2pYZjL5RL3a7PZsHbtWmzatAmBQADRaBQvvfQSjh49irm5OczPz4vrcglBzh8marQpcvCuduBqoMXyiCN6fap4V1nMa+QGIt2RDDjZbBY7d+7EmWeeKSzHhw4dEiIqb1dJxdDC4TAURRGuI51OJwrGEXgpvzWXyyGdTotMIxK95+fnRfMtujcCIKXaUeVI+k+NwShB3e12o62tTRSyU5TFpPVQKISOjg7UajUcO3YML7/8Mk6ePIloNIqFhQWkUilhzaZrc5K5bSMOS8dXewI8oIFWkAxauWoCByTRqfQx7r+lBUcJ6Tt27MDWrVths9lgMBhw9OhRJBIJlMtlFItFkYvKFylZdcvlsijZ2shoxkVc4qp0jtlshtVqhdvtFvWjnE4narWa6BpAHJvanrS1taGnpwft7e0wm81iY6CSMU6nE5FIBMePH8fx48cxPT0txHLe90e2EPPn3cgvy1+vpJKsRtJAi8YicCPXCj9f1h8bGVc4p0ilUgJABKo9e/ZgzZo1WLNmDdLpNKxWq8gEItcIr65Igf9yLi1dg3RQ0jUpRrlWq4k6VQ6HQ/SDpY2Exqb70Ov1cLlcCAaD6O7uRk9PD0wmE2KxGJLJpCjQ5vF4sLCwgMOHD+P48eMijzYcDgujE5HsvuKGPVmHlY1P/PlroNVAC2AJhLLotRIQG1k3+XEOBm6F5f1eiaPt2rULV111FTZv3ixEyvn5eczPzyMWiyGbzQp9lQOedFACJVVoJKMR7wJQq9Vgt9tFqReLxVK3IZhMJjgcDpjNZvj9frhcLoRCIbS0tAhJoFgsorm5GT6fD0ajEfl8HidOnEB/fz+mpqYQi8WEJTqZTIpNQN5gGiU5yNIMfS6DmVe2WM2kgZZRIwf+63FYoN7q2Uikk0VDis81GAwol8vI5/M4//zzsXHjRqxbtw6JRAJTU1MYGRnByZMnUS6XEYlEkMvlRN4rlUYlqzKfK4nfJOKSSE15tKRfqqoKs9mM5uZmdHR0CHHZarUKXZeMXwRqg8GAVCqFcDiMkydPYmhoSPh6Y7HYMpcOv3++wfHnxa30RNwIyL8jd/BbraSo2lOoq9/byC/IuUUjgxMHciNAyxxbp9PB6XQiGAyiqakJ3d3d2LhxIzo7O9HU1ARgsYvc1NQUarUaJicnRTlSbmmmMXliPM8N5nWYySpMLh+r1Yrm5ma0traitbVVVJVwuVzCB0tcnBpRz83NYXBwEJOTkwiHw2Iu0WgUmUxGiLuy71p+BvzZ0fNsZGCSbQv8eZOqsBpJAy1QVytYLnjGSV6E8uJsJOY1cm2Q3miz2eD3++H3+0UrzK1bt6KnpwdOp1O0lIzFYojH43A4HKhUKiIkkSzN5XJZtLPM5/OimBpZgsm1EwwGhTHKbrfD4/HA6XSK2k+VSkUkvavqYnUOSm6fnJzEzMyMSBagOVE1RfmeZS7biNMC9RFPjaz19HvI3Jh3/FttpIEWEFUkgMYBFK8n2vHPVspa4SQfNxqNcLvd8Hq9cDqdaGlpQU9PD/r6+tDR0SGkAIo6ov90HUqVozmR9VlRFmsNV6tVTExMIBAIYM2aNaIaBbW7pIbXqqoK4GcyGcTjcSwsLGB6elroqel0GslkEolEQnQO4LqpLHHI3JSfx8+VASmLwRzY/D5XK2k6LRoDU7YKy/R6FSfk13xMefFR1FI6nYbX6xVZMbOzs8LwEwwG0dzcLPRMKjxOBirKTdXr9cJNRBuIoiiid67H4xF5vXTtVColmj7TdSl6KZvNIpPJIJfLIZfLiXN4KVjZx93ISNfoecq+bToG1Of1yiqLFlyhcVoAEIYb2cpJYhnnCFwHkx/dSvpaowVK53PAU1wvWXBJjPV6vWhubkZbWxscDgeMRiPsdrsouEbWaN56hMRbVV0MvKB45WKxKMReilSi8q6ko+ZyOZRKJeTzeeGTpcR5mbM2qnTBEwJk67p87xyEjXRhfi7/Tzr9aiQNtEBdY+RGrgnZ/SAvqtfT2Tg1MrjIYjnNhwBrtVrhdDpht9uFf5UsvzabDT6fT3Bfs9kMt9sNp9Mp3D9UvE2n0yGZTGJ+fr6ueRgVC8/n8+KPKkuUSqVlIjC/XzomPwv+nOTXK40jZybx8fimR/9Xs3isgRao6yi3kv7ViLMCyyOkOFeWuQ8ZWxp9l4/Br0/uF4fDAavVKlp4cH2U9F6DwbDMTWM2m0UoIuWzEigpjY4S06msaiPLbKONaiXjm/zs6L38nGS1Qt4QV6oWAmiGqFUPWlr0Ky3ARgnpdI7MhYHl1tNGorE8ViMQcM5MYi8RxQdbLBaRZKAoikgqIFCTyExxx1TLqVAoCFGZqiLKoJFVhkZzfz3uyN/z7/D7bvTMV5JmeMCKJh5rpJFGpw1pKRMaaXSakQZajTQ6zUgDrUYanWakgVYjjU4z0kCrkUanGWmg1Uij04w00Gqk0WlGGmg10ug0Iw20Gml0mtH/B/N2fo8tAzixAAAAAElFTkSuQmCC\n"
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "visualize_model(model_ft)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "IMlakxzzW2lE"
+      },
+      "source": [
+        "## ConvNet as fixed feature extractor\n",
+        "\n",
+        "Here, we need to freeze all the network except the final layer. We need\n",
+        "to set ``requires_grad = False`` to freeze the parameters so that the\n",
+        "gradients are not computed in ``backward()``.\n",
+        "\n",
+        "You can read more about this in the documentation\n",
+        "[here](https://pytorch.org/docs/notes/autograd.html#excluding-subgraphs-from-backward)_.\n",
+        "\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 22,
+      "metadata": {
+        "id": "PcSyPZ_7W2lE"
+      },
+      "outputs": [],
+      "source": [
+        "model_conv = torchvision.models.resnet18(weights='IMAGENET1K_V1')\n",
+        "for param in model_conv.parameters():\n",
+        "    param.requires_grad = False\n",
+        "\n",
+        "# Parameters of newly constructed modules have requires_grad=True by default\n",
+        "num_ftrs = model_conv.fc.in_features\n",
+        "model_conv.fc = nn.Linear(num_ftrs, 10)\n",
+        "\n",
+        "model_conv = model_conv.to(device)\n",
+        "\n",
+        "criterion = nn.CrossEntropyLoss()\n",
+        "\n",
+        "# Observe that only parameters of final layer are being optimized as\n",
+        "# opposed to before.\n",
+        "optimizer_conv = optim.SGD(model_conv.fc.parameters(), lr=0.001, momentum=0.93)\n",
+        "\n",
+        "# Decay LR by a factor of 0.1 every 7 epochs\n",
+        "exp_lr_scheduler = lr_scheduler.StepLR(optimizer_conv, step_size=7, gamma=0.1)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "ufSETcSxW2lE"
+      },
+      "source": [
+        "### Train and evaluate\n",
+        "\n",
+        "On CPU this will take about half the time compared to previous scenario.\n",
+        "This is expected as gradients don't need to be computed for most of the\n",
+        "network. However, forward does need to be computed.\n",
+        "\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 23,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 0
+        },
+        "id": "v7mm_hpfW2lF",
+        "outputId": "1e9733ca-68c1-449a-ebc5-3e2e64511e3e"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Epoch 0/59\n",
+            "----------\n",
+            "train Loss: 1.8880 Acc: 0.3243\n",
+            "val Loss: 1.3844 Acc: 0.5121\n",
+            "\n",
+            "Epoch 1/59\n",
+            "----------\n",
+            "train Loss: 1.4418 Acc: 0.4822\n",
+            "val Loss: 1.1024 Acc: 0.6334\n",
+            "\n",
+            "Epoch 2/59\n",
+            "----------\n",
+            "train Loss: 1.2764 Acc: 0.5535\n",
+            "val Loss: 0.9873 Acc: 0.6476\n",
+            "\n",
+            "Epoch 3/59\n",
+            "----------\n",
+            "train Loss: 1.2465 Acc: 0.5654\n",
+            "val Loss: 0.9505 Acc: 0.6733\n",
+            "\n",
+            "Epoch 4/59\n",
+            "----------\n",
+            "train Loss: 1.1880 Acc: 0.5883\n",
+            "val Loss: 0.9673 Acc: 0.6705\n",
+            "\n",
+            "Epoch 5/59\n",
+            "----------\n",
+            "train Loss: 1.1061 Acc: 0.6358\n",
+            "val Loss: 0.8210 Acc: 0.7104\n",
+            "\n",
+            "Epoch 6/59\n",
+            "----------\n",
+            "train Loss: 1.0895 Acc: 0.5993\n",
+            "val Loss: 0.8374 Acc: 0.6990\n",
+            "\n",
+            "Epoch 7/59\n",
+            "----------\n",
+            "train Loss: 0.9826 Acc: 0.6528\n",
+            "val Loss: 0.7730 Acc: 0.7375\n",
+            "\n",
+            "Epoch 8/59\n",
+            "----------\n",
+            "train Loss: 0.9595 Acc: 0.6587\n",
+            "val Loss: 0.7668 Acc: 0.7375\n",
+            "\n",
+            "Epoch 9/59\n",
+            "----------\n",
+            "train Loss: 0.9499 Acc: 0.6842\n",
+            "val Loss: 0.7515 Acc: 0.7447\n",
+            "\n",
+            "Epoch 10/59\n",
+            "----------\n",
+            "train Loss: 0.9558 Acc: 0.6766\n",
+            "val Loss: 0.7528 Acc: 0.7318\n",
+            "\n",
+            "Epoch 11/59\n",
+            "----------\n",
+            "train Loss: 0.9499 Acc: 0.6842\n",
+            "val Loss: 0.7574 Acc: 0.7432\n",
+            "\n",
+            "Epoch 12/59\n",
+            "----------\n",
+            "train Loss: 0.9612 Acc: 0.6749\n",
+            "val Loss: 0.7535 Acc: 0.7361\n",
+            "\n",
+            "Epoch 13/59\n",
+            "----------\n",
+            "train Loss: 0.9751 Acc: 0.6766\n",
+            "val Loss: 0.7526 Acc: 0.7461\n",
+            "\n",
+            "Epoch 14/59\n",
+            "----------\n",
+            "train Loss: 0.9600 Acc: 0.6681\n",
+            "val Loss: 0.7473 Acc: 0.7518\n",
+            "\n",
+            "Epoch 15/59\n",
+            "----------\n",
+            "train Loss: 0.9695 Acc: 0.6681\n",
+            "val Loss: 0.7533 Acc: 0.7389\n",
+            "\n",
+            "Epoch 16/59\n",
+            "----------\n",
+            "train Loss: 0.9457 Acc: 0.6825\n",
+            "val Loss: 0.7406 Acc: 0.7447\n",
+            "\n",
+            "Epoch 17/59\n",
+            "----------\n",
+            "train Loss: 0.9542 Acc: 0.6800\n",
+            "val Loss: 0.7376 Acc: 0.7504\n",
+            "\n",
+            "Epoch 18/59\n",
+            "----------\n",
+            "train Loss: 0.9837 Acc: 0.6630\n",
+            "val Loss: 0.7415 Acc: 0.7461\n",
+            "\n",
+            "Epoch 19/59\n",
+            "----------\n",
+            "train Loss: 0.9301 Acc: 0.6995\n",
+            "val Loss: 0.7388 Acc: 0.7603\n",
+            "\n",
+            "Epoch 20/59\n",
+            "----------\n",
+            "train Loss: 0.9460 Acc: 0.6774\n",
+            "val Loss: 0.7361 Acc: 0.7489\n",
+            "\n",
+            "Epoch 21/59\n",
+            "----------\n",
+            "train Loss: 0.9389 Acc: 0.6817\n",
+            "val Loss: 0.7323 Acc: 0.7504\n",
+            "\n",
+            "Epoch 22/59\n",
+            "----------\n",
+            "train Loss: 0.9484 Acc: 0.6630\n",
+            "val Loss: 0.7440 Acc: 0.7461\n",
+            "\n",
+            "Epoch 23/59\n",
+            "----------\n",
+            "train Loss: 0.9612 Acc: 0.6868\n",
+            "val Loss: 0.7451 Acc: 0.7447\n",
+            "\n",
+            "Epoch 24/59\n",
+            "----------\n",
+            "train Loss: 0.9369 Acc: 0.6868\n",
+            "val Loss: 0.7405 Acc: 0.7575\n",
+            "\n",
+            "Epoch 25/59\n",
+            "----------\n",
+            "train Loss: 0.9273 Acc: 0.6800\n",
+            "val Loss: 0.7350 Acc: 0.7546\n",
+            "\n",
+            "Epoch 26/59\n",
+            "----------\n",
+            "train Loss: 0.9257 Acc: 0.6902\n",
+            "val Loss: 0.7471 Acc: 0.7461\n",
+            "\n",
+            "Epoch 27/59\n",
+            "----------\n",
+            "train Loss: 0.9557 Acc: 0.6698\n",
+            "val Loss: 0.7378 Acc: 0.7347\n",
+            "\n",
+            "Epoch 28/59\n",
+            "----------\n",
+            "train Loss: 0.9548 Acc: 0.6749\n",
+            "val Loss: 0.7393 Acc: 0.7504\n",
+            "\n",
+            "Epoch 29/59\n",
+            "----------\n",
+            "train Loss: 0.9704 Acc: 0.6638\n",
+            "val Loss: 0.7403 Acc: 0.7447\n",
+            "\n",
+            "Epoch 30/59\n",
+            "----------\n",
+            "train Loss: 0.9201 Acc: 0.6842\n",
+            "val Loss: 0.7437 Acc: 0.7389\n",
+            "\n",
+            "Epoch 31/59\n",
+            "----------\n",
+            "train Loss: 0.9318 Acc: 0.6935\n",
+            "val Loss: 0.7368 Acc: 0.7546\n",
+            "\n",
+            "Epoch 32/59\n",
+            "----------\n",
+            "train Loss: 0.9528 Acc: 0.6681\n",
+            "val Loss: 0.7362 Acc: 0.7489\n",
+            "\n",
+            "Epoch 33/59\n",
+            "----------\n",
+            "train Loss: 0.9360 Acc: 0.6723\n",
+            "val Loss: 0.7344 Acc: 0.7461\n",
+            "\n",
+            "Epoch 34/59\n",
+            "----------\n",
+            "train Loss: 0.9627 Acc: 0.6766\n",
+            "val Loss: 0.7359 Acc: 0.7575\n",
+            "\n",
+            "Epoch 35/59\n",
+            "----------\n",
+            "train Loss: 0.9201 Acc: 0.6952\n",
+            "val Loss: 0.7436 Acc: 0.7532\n",
+            "\n",
+            "Epoch 36/59\n",
+            "----------\n",
+            "train Loss: 0.9499 Acc: 0.6808\n",
+            "val Loss: 0.7426 Acc: 0.7475\n",
+            "\n",
+            "Epoch 37/59\n",
+            "----------\n",
+            "train Loss: 0.9211 Acc: 0.6825\n",
+            "val Loss: 0.7375 Acc: 0.7461\n",
+            "\n",
+            "Epoch 38/59\n",
+            "----------\n",
+            "train Loss: 0.9286 Acc: 0.6902\n",
+            "val Loss: 0.7471 Acc: 0.7461\n",
+            "\n",
+            "Epoch 39/59\n",
+            "----------\n",
+            "train Loss: 0.9363 Acc: 0.6766\n",
+            "val Loss: 0.7315 Acc: 0.7589\n",
+            "\n",
+            "Epoch 40/59\n",
+            "----------\n",
+            "train Loss: 0.9253 Acc: 0.6868\n",
+            "val Loss: 0.7367 Acc: 0.7489\n",
+            "\n",
+            "Epoch 41/59\n",
+            "----------\n",
+            "train Loss: 0.9414 Acc: 0.6715\n",
+            "val Loss: 0.7502 Acc: 0.7404\n",
+            "\n",
+            "Epoch 42/59\n",
+            "----------\n",
+            "train Loss: 0.9238 Acc: 0.6944\n",
+            "val Loss: 0.7418 Acc: 0.7475\n",
+            "\n",
+            "Epoch 43/59\n",
+            "----------\n",
+            "train Loss: 0.9268 Acc: 0.6791\n",
+            "val Loss: 0.7370 Acc: 0.7447\n",
+            "\n",
+            "Epoch 44/59\n",
+            "----------\n",
+            "train Loss: 0.9381 Acc: 0.6808\n",
+            "val Loss: 0.7482 Acc: 0.7432\n",
+            "\n",
+            "Epoch 45/59\n",
+            "----------\n",
+            "train Loss: 0.9339 Acc: 0.6740\n",
+            "val Loss: 0.7411 Acc: 0.7546\n",
+            "\n",
+            "Epoch 46/59\n",
+            "----------\n",
+            "train Loss: 0.9406 Acc: 0.6825\n",
+            "val Loss: 0.7467 Acc: 0.7361\n",
+            "\n",
+            "Epoch 47/59\n",
+            "----------\n",
+            "train Loss: 0.9394 Acc: 0.7003\n",
+            "val Loss: 0.7405 Acc: 0.7461\n",
+            "\n",
+            "Epoch 48/59\n",
+            "----------\n",
+            "train Loss: 0.9471 Acc: 0.6834\n",
+            "val Loss: 0.7391 Acc: 0.7561\n",
+            "\n",
+            "Epoch 49/59\n",
+            "----------\n",
+            "train Loss: 0.9527 Acc: 0.6715\n",
+            "val Loss: 0.7396 Acc: 0.7489\n",
+            "\n",
+            "Epoch 50/59\n",
+            "----------\n",
+            "train Loss: 0.9559 Acc: 0.6757\n",
+            "val Loss: 0.7406 Acc: 0.7504\n",
+            "\n",
+            "Epoch 51/59\n",
+            "----------\n",
+            "train Loss: 0.9523 Acc: 0.6655\n",
+            "val Loss: 0.7407 Acc: 0.7561\n",
+            "\n",
+            "Epoch 52/59\n",
+            "----------\n",
+            "train Loss: 0.9584 Acc: 0.6706\n",
+            "val Loss: 0.7513 Acc: 0.7447\n",
+            "\n",
+            "Epoch 53/59\n",
+            "----------\n",
+            "train Loss: 0.9683 Acc: 0.6698\n",
+            "val Loss: 0.7331 Acc: 0.7404\n",
+            "\n",
+            "Epoch 54/59\n",
+            "----------\n",
+            "train Loss: 0.9590 Acc: 0.6672\n",
+            "val Loss: 0.7417 Acc: 0.7375\n",
+            "\n",
+            "Epoch 55/59\n",
+            "----------\n",
+            "train Loss: 0.9110 Acc: 0.6842\n",
+            "val Loss: 0.7413 Acc: 0.7432\n",
+            "\n",
+            "Epoch 56/59\n",
+            "----------\n",
+            "train Loss: 0.9460 Acc: 0.6723\n",
+            "val Loss: 0.7449 Acc: 0.7489\n",
+            "\n",
+            "Epoch 57/59\n",
+            "----------\n",
+            "train Loss: 0.9491 Acc: 0.6800\n",
+            "val Loss: 0.7408 Acc: 0.7532\n",
+            "\n",
+            "Epoch 58/59\n",
+            "----------\n",
+            "train Loss: 0.9647 Acc: 0.6698\n",
+            "val Loss: 0.7407 Acc: 0.7532\n",
+            "\n",
+            "Epoch 59/59\n",
+            "----------\n",
+            "train Loss: 0.9463 Acc: 0.6579\n",
+            "val Loss: 0.7394 Acc: 0.7489\n",
+            "\n",
+            "Training complete in 18m 38s\n",
+            "Best val Acc: 0.760342\n"
+          ]
+        }
+      ],
+      "source": [
+        "model_conv = train_model(model_conv, criterion, optimizer_conv,\n",
+        "                         exp_lr_scheduler, num_epochs=60)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 24,
+      "metadata": {
+        "id": "qPq7-3EfW2lF",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 923
+        },
+        "outputId": "c1c555e6-c1c6-4bf7-f84c-571c557ba470"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "visualize_model(model_conv)\n",
+        "\n",
+        "plt.ioff()\n",
+        "plt.show()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "ZbmJT9frW2lF"
+      },
+      "source": [
+        "## Further Learning\n",
+        "\n",
+        "If you would like to learn more about the applications of transfer learning,\n",
+        "checkout our [Quantized Transfer Learning for Computer Vision Tutorial](https://pytorch.org/tutorials/intermediate/quantized_transfer_learning_tutorial.html).\n",
+        "\n",
+        "\n",
+        "\n"
+      ]
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.10.10"
+    },
+    "colab": {
+      "provenance": [],
+      "gpuType": "V100"
+    },
+    "accelerator": "GPU",
+    "gpuClass": "standard"
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}