| { |
| "nbformat": 4, |
| "nbformat_minor": 0, |
| "metadata": { |
| "colab": { |
| "name": "edge_detection.ipynb", |
| "provenance": [], |
| "collapsed_sections": [] |
| }, |
| "kernelspec": { |
| "name": "python3", |
| "display_name": "Python 3" |
| } |
| }, |
| "cells": [ |
| { |
| "cell_type": "markdown", |
| "metadata": { |
| "id": "h5s6ncerSpc5", |
| "colab_type": "text" |
| }, |
| "source": [ |
| "# Image edge detection module\n", |
| "\n", |
| "## High level overview:\n", |
| "\n", |
| "1. Define a `tf.Module` containing a `@tf.function` that performs edge detection\n", |
| "2. Save the `tf.Module` as a `SavedModel`\n", |
| "3. Use IREE's python bindings to load the `SavedModel` into MLIR in the `xla_hlo` dialect\n", |
| "4. Save the MLIR to a file (can stop here to use it from another application)\n", |
| "5. Compile the `xla_hlo` MLIR into a VM module for IREE to execute\n", |
| "6. Run the VM module through IREE's runtime to test the edge detection function" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "metadata": { |
| "id": "s2bScbYkP6VZ", |
| "colab_type": "code", |
| "cellView": "both", |
| "colab": {} |
| }, |
| "source": [ |
| "#@title Imports and common setup\n", |
| "\n", |
| "import os\n", |
| "from matplotlib import pyplot as plt\n", |
| "import numpy as np\n", |
| "import tensorflow as tf\n", |
| "from pyiree import compiler as ireec\n", |
| "from pyiree import rt as ireert\n", |
| "\n", |
| "SAVE_PATH = os.path.join(os.environ[\"HOME\"], \"saved_models\")\n", |
| "os.makedirs(SAVE_PATH, exist_ok=True)" |
| ], |
| "execution_count": 0, |
| "outputs": [] |
| }, |
| { |
| "cell_type": "code", |
| "metadata": { |
| "id": "6YGqN2uqP_7P", |
| "colab_type": "code", |
| "outputId": "66dfb8e7-f139-45cd-88c4-dbdf19d0c01e", |
| "colab": { |
| "base_uri": "https://localhost:8080/", |
| "height": 343 |
| } |
| }, |
| "source": [ |
| "#@title Construct a module containing the edge detection function\n", |
| "\n", |
| "class EdgeDetectionModule(tf.Module):\n", |
| " @tf.function(input_signature=[tf.TensorSpec([1, 128, 128, 1], tf.float32)])\n", |
| " def edge_detect_sobel_operator(self, image):\n", |
| " # https://en.wikipedia.org/wiki/Sobel_operator\n", |
| " sobel_x = tf.constant([[-1.0, 0.0, 1.0],\n", |
| " [-2.0, 0.0, 2.0],\n", |
| " [-1.0, 0.0, 1.0]],\n", |
| " dtype=tf.float32, shape=[3, 3, 1, 1]) \n", |
| " sobel_y = tf.constant([[ 1.0, 2.0, 1.0],\n", |
| " [ 0.0, 0.0, 0.0],\n", |
| " [-1.0, -2.0, -1.0]],\n", |
| " dtype=tf.float32, shape=[3, 3, 1, 1])\n", |
| " gx = tf.nn.conv2d(image, sobel_x, 1, \"SAME\")\n", |
| " gy = tf.nn.conv2d(image, sobel_y, 1, \"SAME\")\n", |
| " return tf.math.sqrt(gx * gx + gy * gy)\n", |
| "\n", |
| "tf_module = EdgeDetectionModule()\n", |
| "saved_model_path = os.path.join(SAVE_PATH, \"edge_detection.sm\")\n", |
| "save_options = tf.saved_model.SaveOptions(save_debug_info=True)\n", |
| "tf.saved_model.save(tf_module, saved_model_path, options=save_options)\n", |
| "\n", |
| "# Compile from SavedModel to MLIR xla_hlo, then save to a file.\n", |
| "# \n", |
| "# Do *not* further compile to a bytecode module for a particular backend.\n", |
| "# \n", |
| "# By stopping at xla_hlo in text format, we can more easily take advantage of\n", |
| "# future compiler improvements within IREE and can use iree_bytecode_module to\n", |
| "# compile and bundle the module into a sample application. For a production\n", |
| "# application, we would probably want to freeze the version of IREE used and\n", |
| "# compile as completely as possible ahead of time, then use some other scheme\n", |
| "# to load the module into the application at runtime.\n", |
| "compiler_module = ireec.tf_load_saved_model(saved_model_path)\n", |
| "print(\"Edge Detection MLIR:\", compiler_module.to_asm())\n", |
| "\n", |
| "edge_detection_mlir_path = os.path.join(SAVE_PATH, \"edge_detection.mlir\")\n", |
| "with open(edge_detection_mlir_path, \"wt\") as output_file:\n", |
| " output_file.write(compiler_module.to_asm())\n", |
| "print(\"Wrote MLIR to path '%s'\" % edge_detection_mlir_path)" |
| ], |
| "execution_count": 2, |
| "outputs": [ |
| { |
| "output_type": "stream", |
| "text": [ |
| "INFO:tensorflow:Assets written to: /usr/local/google/home/scotttodd/saved_models/edge_detection.sm/assets\n", |
| "Edge Detection MLIR: \n", |
| "\n", |
| "module {\n", |
| " func @edge_detect_sobel_operator(%arg0: tensor<1x128x128x1xf32>) -> tensor<1x128x128x1xf32> attributes {iree.module.export, iree.reflection = {abi = \"sip\", abiv = 1 : i32, sip = \"I8!S5!k0_0R3!_0\"}, tf._input_shapes = [\"tfshape$dim { size: 1 } dim { size: 128 } dim { size: 128 } dim { size: 1 }\"]} {\n", |
| " %0 = xla_hlo.constant dense<[[[[-1.000000e+00]], [[0.000000e+00]], [[1.000000e+00]]], [[[-2.000000e+00]], [[0.000000e+00]], [[2.000000e+00]]], [[[-1.000000e+00]], [[0.000000e+00]], [[1.000000e+00]]]]> : tensor<3x3x1x1xf32>\n", |
| " %1 = xla_hlo.constant dense<[[[[1.000000e+00]], [[2.000000e+00]], [[1.000000e+00]]], [[[0.000000e+00]], [[0.000000e+00]], [[0.000000e+00]]], [[[-1.000000e+00]], [[-2.000000e+00]], [[-1.000000e+00]]]]> : tensor<3x3x1x1xf32>\n", |
| " %2 = \"xla_hlo.conv\"(%arg0, %0) {batch_group_count = 1 : i64, dimension_numbers = {input_batch_dimension = 0 : i64, input_feature_dimension = 3 : i64, input_spatial_dimensions = dense<[1, 2]> : tensor<2xi64>, kernel_input_feature_dimension = 2 : i64, kernel_output_feature_dimension = 3 : i64, kernel_spatial_dimensions = dense<[0, 1]> : tensor<2xi64>, output_batch_dimension = 0 : i64, output_feature_dimension = 3 : i64, output_spatial_dimensions = dense<[1, 2]> : tensor<2xi64>}, feature_group_count = 1 : i64, padding = dense<1> : tensor<2x2xi64>, rhs_dilation = dense<1> : tensor<2xi64>, window_strides = dense<1> : tensor<2xi64>} : (tensor<1x128x128x1xf32>, tensor<3x3x1x1xf32>) -> tensor<1x128x128x1xf32>\n", |
| " %3 = xla_hlo.mul %2, %2 : tensor<1x128x128x1xf32>\n", |
| " %4 = \"xla_hlo.conv\"(%arg0, %1) {batch_group_count = 1 : i64, dimension_numbers = {input_batch_dimension = 0 : i64, input_feature_dimension = 3 : i64, input_spatial_dimensions = dense<[1, 2]> : tensor<2xi64>, kernel_input_feature_dimension = 2 : i64, kernel_output_feature_dimension = 3 : i64, kernel_spatial_dimensions = dense<[0, 1]> : tensor<2xi64>, output_batch_dimension = 0 : i64, output_feature_dimension = 3 : i64, output_spatial_dimensions = dense<[1, 2]> : tensor<2xi64>}, feature_group_count = 1 : i64, padding = dense<1> : tensor<2x2xi64>, rhs_dilation = dense<1> : tensor<2xi64>, window_strides = dense<1> : tensor<2xi64>} : (tensor<1x128x128x1xf32>, tensor<3x3x1x1xf32>) -> tensor<1x128x128x1xf32>\n", |
| " %5 = xla_hlo.mul %4, %4 : tensor<1x128x128x1xf32>\n", |
| " %6 = xla_hlo.add %3, %5 : tensor<1x128x128x1xf32>\n", |
| " %7 = \"xla_hlo.sqrt\"(%6) : (tensor<1x128x128x1xf32>) -> tensor<1x128x128x1xf32>\n", |
| " return %7 : tensor<1x128x128x1xf32>\n", |
| " }\n", |
| "}\n", |
| "\n", |
| "Wrote MLIR to path '/usr/local/google/home/scotttodd/saved_models/edge_detection.mlir'\n" |
| ], |
| "name": "stdout" |
| } |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "metadata": { |
| "id": "Ytvb5Gx_EFJl", |
| "colab_type": "code", |
| "colab": { |
| "base_uri": "https://localhost:8080/", |
| "height": 51 |
| }, |
| "outputId": "6ba61508-3799-49dd-dd54-7c2b275764cf" |
| }, |
| "source": [ |
| "#@title Prepare to test the edge detection module\n", |
| "\n", |
| "TARGET_BACKENDS = (\"vulkan-spirv\",)\n", |
| "DRIVER_NAME = \"vulkan\"\n", |
| "\n", |
| "flatbuffer_blob = compiler_module.compile(target_backends=TARGET_BACKENDS)\n", |
| "vm_module = ireert.VmModule.from_flatbuffer(flatbuffer_blob)\n", |
| "\n", |
| "# Register the module with a runtime context.\n", |
| "config = ireert.Config(DRIVER_NAME)\n", |
| "ctx = ireert.SystemContext(config=config)\n", |
| "ctx.add_module(vm_module)" |
| ], |
| "execution_count": 3, |
| "outputs": [ |
| { |
| "output_type": "stream", |
| "text": [ |
| "Created IREE driver vulkan: <pyiree.rt.binding.HalDriver object at 0x7fd40c31b7b0>\n", |
| "SystemContext driver=<pyiree.rt.binding.HalDriver object at 0x7fd40c31b7b0>\n" |
| ], |
| "name": "stderr" |
| } |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "metadata": { |
| "id": "OUUXxol7wl-f", |
| "colab_type": "code", |
| "colab": {} |
| }, |
| "source": [ |
| "#@title Load a test image of a [labrador](https://commons.wikimedia.org/wiki/File:YellowLabradorLooking_new.jpg)\n", |
| "\n", |
| "def load_image(path_to_image):\n", |
| " image = tf.io.read_file(path_to_image)\n", |
| " image = tf.image.decode_image(image, channels=1)\n", |
| " image = tf.image.convert_image_dtype(image, tf.float32)\n", |
| " image = tf.image.resize(image, (128, 128))\n", |
| " image = image[tf.newaxis, :]\n", |
| " return image\n", |
| "\n", |
| "content_path = tf.keras.utils.get_file(\n", |
| " 'YellowLabradorLooking_new.jpg',\n", |
| " 'https://storage.googleapis.com/download.tensorflow.org/example_images/YellowLabradorLooking_new.jpg')\n", |
| "content_image = load_image(content_path)" |
| ], |
| "execution_count": 0, |
| "outputs": [] |
| }, |
| { |
| "cell_type": "code", |
| "metadata": { |
| "id": "qW32e6spORCo", |
| "colab_type": "code", |
| "outputId": "9699fc94-82b7-4ea8-fc72-45681ee0d3a3", |
| "colab": { |
| "base_uri": "https://localhost:8080/", |
| "height": 570 |
| } |
| }, |
| "source": [ |
| "#@title Test the \"edge_detect_sobel_operator\" function\n", |
| "\n", |
| "edge_detect_sobel_operator_f = ctx.modules.module[\"edge_detect_sobel_operator\"]\n", |
| "\n", |
| "# Invoke the function with the image as an argument\n", |
| "print(\"Invoke edge_detect_sobel_operator\")\n", |
| "result = edge_detect_sobel_operator_f(content_image.numpy())\n", |
| "\n", |
| "# Plot the input and output images\n", |
| "print(\"Input:\")\n", |
| "plt.imshow(arg0.reshape(128, 128), cmap=\"gray\")\n", |
| "plt.show()\n", |
| "print(\"Output:\")\n", |
| "plt.imshow(result.reshape(128, 128), cmap=\"gray\")\n", |
| "plt.show()" |
| ], |
| "execution_count": 6, |
| "outputs": [ |
| { |
| "output_type": "stream", |
| "text": [ |
| "Invoke edge_detect_sobel_operator\n", |
| "Input:\n" |
| ], |
| "name": "stdout" |
| }, |
| { |
| "output_type": "display_data", |
| "data": { |
| "text/plain": [ |
| "<Figure size 432x288 with 1 Axes>" |
| ], |
| "image/png": 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\n" |
| }, |
| "metadata": { |
| "tags": [], |
| "needs_background": "light" |
| } |
| }, |
| { |
| "output_type": "stream", |
| "text": [ |
| "Output:\n" |
| ], |
| "name": "stdout" |
| }, |
| { |
| "output_type": "display_data", |
| "data": { |
| "text/plain": [ |
| "<Figure size 432x288 with 1 Axes>" |
| ], |
| "image/png": 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bzWYgSTX5xoe9NDswDdyUc1TADO9ga7VagbYSRZFJUD6flt9S0qVpHz7vX8tvlby2p5LKO7h0PErKYrFo68C9u//++017OHHiBIBe+FUrLtVvwPG4t41Gw7RGnoUDBw4A6CaE8Sy8/e1vB9D18Tz99NMAek5l+gvUeUkNT8O6lOKbm5t2Tn1ZuZZdq2PY12hoqblPKtLM0qtRpglklNEtTjtCE2AFmIZLvAdZc7fJ9dSWVNuWkuw973kPgJ4ke/zxx3HfffcB6Hnsl5aWTEo88sgjAIC//du/xc/+7M8CAL7zne8ASO8ZQOrv7zdurxKHHJ6hH85xbGzM5kTfwMbGhkkARilUAvvkKU0kUW3Ip7am2ZSa4so5UUtRQE0P9dbpdAIPfBqQCSmtylMhs9LmREmq9q6vGGy32+btZ6r3Sy+9hEOHDgEAHn744cT4GxsbQfJPrVbD6uqqrSWQjPycPn0aQC9JbGVlxZK/GGE6cOCARXQYifjWt75l8+cz8IxqIxU+5+DgoK2f4gdwzdI03TSwUg/Ck9YA5mq0I5gAaX193dTkNMAJr/IUCoUgTry9vW2q3OXLlwH0sv4+8IEP2AtJB1CtVrNFomr5pS99Cb/1W78FAPjN3/xNuxeQDEFqVhYPEkNyd955pzEGHljWHCwsLBgqLf8tFov28nvSAhstZ/VOIHVG+vBoFEVBHr8yVh7KoaEhw8bzMXDNs1CHn89SJGmmo87fF90o49FsQz6bL7Apl8t2HesxHnvsMVtnhvmU2Xg1vN1uBwVB5XLZ1i3NKcos0i984QsAuozzgx/8IIAe42HW6bPPPovvfe979lsgme2nAkJD40DSqeidgJVKxebrs0L1by3dvh4TyMyBjDK6xWlHaAJU6zU5QpFUgWRSiKpBlOwM7x09etQcQhcvXgQAqwisVqsW5qHUVWThZ555BgDwoQ99yByDdCCq5OPctN6BmgWl/9TUFF588UUAvTJkfre6umqfUWpFUWSaCFU77Zbjq9o0N10zF68GKtJutxNOSyC9KlCdeaomA+nlzmoi+CxFDdeqdpFWGcc9pSalTlHvAF1dXbW/6cg7fvy4rbcmCQHdUGFagg3PFs0eXQ/Om6alPjv3pV6v49Of/jSAXqXou9/9bgDARz/6UdOuvv71rwPoag50QmoGqq/4vBamo4ZY1VHuy6g1WzZzDGaUUUbXpB2hCQBdCVEulwNwibQOrRp2os10++23A+hyRYaIKPko/ScnJwNpdeHCBeOef/mXfwkAuOeeeyyU6Ku+FGZKQzvEFnjHO94BoKsJ0Cbk9dRQ4jg2KUQH5dzcnKWoUkugtnLp0qUAaVnz+DXkx+sohdRv4GvlNf1VG1/6akBNHvLVniohvbZSrVZNkmpOvrfxObauaVrlp97HI/QODg6aw472M516nU7HksO43gcPHsSuXbsA9JK4qtVqoAloarav2iyVSjYezxzP2i/8wi/gscceS6zjc889l9pN2UOU8UwrgCifc319PdF1iZ9RE+W9uNfqVL4avW4mEEXRPgCfBjANIAbwyTiOfz+KonEAnwNwAMBrAH4ujuOV64xlnm3fqFMRWH0xT71eD/DnXnvtNdxxxx0AEORdq2rEw6nqM3P79+zZY3+TmIW2ublpLzzHet/73odf/MVfBNCLSMzNzZm3mgfjqaeesvnTM03vcqVSCUpVNebv4//KCKnObm1tBRmAfGk1gsF5Lyws2KHnPdfX1+2w+5ZcQ0NDdkDTzA5fsjowMBBkeapDLq0gyJuB6iHXbEWOx3X8/ve/by8kBQKz/hYWFgKn8vHjx/Htb38bQO8s7N+/3xiCb5GuuQxqVnGeHIOO3k996lP42Mc+BqDnNJyfn7dsQ1X5tVYA6J15ZcjqhNZ8CSCZPUpS5nEzMwbbAP7HOI6PAHgrgF+NougIgN8A8PdxHN8J4O+v/H9GGWW0Q+l1awJxHF8CcOnK3xtRFL0IYA+ARwG858plnwLwOIBfv9ZYbLesTT+8hIqiKIiParttcs/XXnvNOC9/S+587ty5oBS2v7/fpCXVw0ajYZV8Xnpq2yjWFfzO7/yOOfWoJTzxxBM2D46bphKT+8/OzuKjH/0ogG4+A+fLZ/PluqoCcj4a9/eaQKfTMY2BUqtSqQTrnM/ng8aeqoFp/wBew3FJCu/lTTiFElN0YC0ZB5KahneOKXSX3ovrxVAszSnNZaCkL5VKlmPAcU+fPm3Pwj2j41FNVUrier0eqPBc2/n5eQslcl8feeQR0wppzmi+h8+I1efT9UsL61IjImkuzfXoh+IYjKLoAICjAL4FYPoKgwCAOXTNhbTffCKKomeiKHrGP0BGGWX0o6MbdgxGUVQG8H8B+O/iOF5XZ08cx3EURamsKI7jTwL4JADcfffdMaGxKO29swlIQkMBXW5Om4xcv91uY3Z2FgDwjW98A0DPZm61WuZ0o6NIHScMN+7Zs8fGvXDhgl0HdBN/KPXpJ5ibm8Of//mfA+hVG544ccI0BfokGMZ89dVXTYozC+3w4cN47rnnAPRCXE8++WRiLfjMQFfycN58FgX44L+ageedbpr9qA5Ej0WgCVscT3EKKP04DwXF8OCjmriiNjD3mQk/XIOZmRnLZlQAVO+EVJwC31tCk7MYkl1aWrLrqe0dPHgw0Ei4nzMzMzYndWz6iktN5iJIDEFl3vnOd5oPiL6BUqkU1FcoVgL/TsPa0L4KJI+crSHcq9ENMYEoivrRZQCfieP4P135eD6Kotk4ji9FUTQL4PL1xul0Oub1pHPHI68sLi5aBqCmFDOLixs/OTlpB9WnFCs4B+P/mptAVXdjY8MOHsEleNC3trbssNOx9Na3vhU/+ZM/CaCnbh4+fNjKkclcOEa1WjXn0p49ewB0Dz/vyUPJ79bW1kzF5Qu5ublp81V13TuBtLjHQ4KPjIwEB0nRaX0669DQUAKCG0hi9fmuysPDw0EKcn9/v6nhdNzt378/YZ4BPaY7Pz+faBMGJLv7asm5L2TS1GJeT+Z16tQpe8FpRszNzQVRG0YcFhcX7SzQ8bh7925bSzIZkiItk7kfOXLEitmYlsz56Lx1/T2Cku4v56rALj7dXjExr0av2xyIuifqjwG8GMfx/yZffQnAx6/8/XEAf/V675FRRhndfLoRTeDtAP4lgO9FUfT8lc/+ZwC/C+Avoij6FQBnAPzc9QZixuD6+nqQUUXJWiwWjRtqswhyQ0rdcrlsfzNjjOG+iYkJk6hp6pU63RhmpCpPVfTixYumyjOu/yd/8if4xCc+AaCr8nE+1DY4H23wQW2C5sYdd9xhmgIzHSmN7rvvPnM4co6NRsM0I6qditVHCaNgJJSoqtJTI+H1mmevnW25Tj5+r63JOC41mr1795o05rMNDg4G9Q0KscX9OX78OICuxPawWyw408+0ZJZSkfs/MTFha0kt641vfKMVk/E8nTp1yuL9lOyaX0BthuXDb3nLWxLaGvcFSJZ6c/zvfve7+LEf+zEAPQTqJ598MshJ4Dpubm6mogjzmXlPapoAgoKtcrkcALZ4upHowDcAXC0f8X2vd9yMMsroR0s7ImOQnJ3AIkCPY6tk8+EYDXtRoh48eNA4NWsGOMby8rJdr/nfvnKxXq/bPHgvSuKDBw8ax+ZYx44dw6/92q8B6IFQ7Nu3z76nRqDJS5ToX/ziFwF0tRVydP6O4aR6vW7ah4YWb7vttsQ9y+WyaUa0VWnvnjp1KgGM4tdPw2/el8LnHRoasjWlk3NiYiK4ThODvEOwVquZPcwKQO2c5CWf9ktQwA5f5ZfWiotRp4WFBQP9oJayf/9+0/b42Xvf+15z1NKOp7Y1Pz9v92TY8MyZM+aE5hi8RkuXKZVfeOEF8zHQr/DUU0+lljlzDO63Jij55q26flwj/m5tbS2rHcgoo4yuTTtGE+jv709AbFFCafKLt901VEQpd+HCBbM/aYurXcfvtN6a0ofStlqtBklFGh2gVsBQYblcNqnNaMW5c+dMsvNe1G6Uw3Pezz//vNmtHJ8S4YUXXkiEKIGudsDx2M9A24/Tnick1t133202JNe2UCgE3vitra3AF0DK5/MJWDEgHRufPpgLFy7Y82k4UEE2OFdqXh6IQ6sO+Z16yHUeHMPXTWxvb5u2x7Pz6quv2vngOh85csRCyO9617sA9PbuiSeeMK1KbXfuO/0PfN6lpaWgKnBtbc38PQS8nZ2dNY1ItTEgGR5XQB2fPq9RL2o/XLOhoSF79qvRjmACQK+HgM8YU0AGHmJtqEm1kQ/aarVMJaYazhz+crlsC8iDXqvVLHbM3128eDGRjw/0nHQLCwtBk42BgQGbJ9VDBStJQ5HlwdMGH1Q9td8A0H2BfAZYLpezORKxuFqtBqolzZ69e/eaGsuXJQ2spL+/P5ivmklkclwzxX4kqVruawI0tq7MwzefUZx9D7qhL4K+EHwuX36uDk19Np9defz4cQsD8sy8731d99ajjz5qLysdsfPz8yZgaEZw3tVqNehsDAAnT54E0GMChw4dSvQ20DGiqNdpWYFDKFw0bOjbj/H90fqaq1FmDmSU0S1OO0YTYLKHqjFAT9qWSqXAGVQsFhNYbUBXQlFNZ3YWpfPMzIwl+JBzj46OGofXcXkv74TRUmSGkQqFgjmGtHMRnTke6CGOY7tOE1pUVQV6Zky9Xrf1oLo5NjZm9+d3w8PDdg+aFLx+cXHRJIeq0F5zGBoaSkgiIBmC4v5w/tpui0S1XVGStUcC50HtrdlsJlqdAT0pt729ncj45L++54I6EH24TqV+GgAK10Dz+KkR8Nnf/OY3235SKxwdHbXP+MzcE10zdczRga1ORl8foGYv10HxJFnXQFOE+6/XaU8Fr0l5yjSBjDK6xWlHaALEUi+Xy4FzRPPcPeIuOb5e39/fbxKBuf2UqO9+97uNA2syEu/J+gPFcfdVdmlde7TvAKU4JSUQ1olrJSKde1oVyPAR7e7x8fHA96EwZ5prrtV9ABKpxR58VPPKubbabtuvgWoklJ6Kquv3R6Hb1KZV7AKgK6249j61We1pjjsyMmLz1hoQ3w9CewF6h2ar1bL9ozRPW1NK7i996Ut2ntTRxiQrOuSY7KTapPpMfMVlpVJJ9CoEemd+aGjI1lZBU6n90lmt43v/TF9f3/8/0IbZqEPzr7nQikzLh+aC9/X12SJxMwYHB+3lefDBBwH0EGZeeeUVW0wykHa7bS8dX8i+vr6gGEURe/g3r9/e3jaTgi//1NSU5SvQIcd5dzqdQL3f2toyJCI6o5iNBiB40TY2NoLYehzH5rjjZwoC4ouy1Puf5njiy8HrR0dHg6iNxq09lctlU535nLVaLXCYpbVIS2s6o45SkjZvIXkY9b6+vqA9WK1Ws9/wOi2eIiPRnBQ6BNVUVeRmPguQBATRojjPnIeHh4NmOepA9gy5Xq8bc/ECDejtlTaFvWm1AxlllNF/HrQjNAHmCUxNTQWhQdL6+rpJN83OYghFc6Y9hj05ZS6Xs/Jcqt7z8/OWx01NY2ZmxvAAqQKS+/f395ukVLWX0p50+vTpBDfWf4eHh4PYrZY0U6VUjk/NhVKuWCwmJB3QdTJSm1JEYc7bS1vVpNQ5RWlFqa81B97Btrm5aWvDsfjd6upqELfe3t4O6jEajYatqWYKAklHIqXn+vp6YGZoTQJJy3C1lTqQBKlRCDFfyael1ryngrPw+bgGavJRbdeQL8fjfg4MDJjjmvkVmjXJvznXgYGBwNGc1g9CNemrIVCTMk0go4xucdoxmsDg4CBWV1eDumly3Xa7HbTFKhaLJr2VE3opq63BCAxB6bawsJBA/AV6mYA6LhNyJiYmzIlFqZvP501KMGzTaDSCjDtK7lqtZlKN+ev1et20Dn7GTMC1tTWrbiNQSrPZtPAiaWxszD5j4hHXQisM1Sb3oCza7p3Pri3NKJE0V91nuKkzz4enFOyV61cqlUwr0CabQLJ1l9rdvjuSJudo22/+v+9opY1rtYqP+8h5awNWSnaOsbq6GjRt5TVRFNl3mshGTYH+nkKhEICZ+mfT9VYHqPZN8H4Z3iftO087hgkwzsvFVJRcoLvJPndga2sroe4CyUPDF40H9/Lly4W6VnYAACAASURBVPbCU43j/+s9n3nmGXP6cVNpPpTLZVMpNf2VKaV80dvttpkIVHXVKcTxyJSeffZZA9n46Z/+aQA95nX58uXESwp004x9yyw9eN75pqm5ilysaD0kPrPH9lNIbm3rpWaRkmar8btWq2XzVqxIOnb99blczq7n/uhLzevU3PGI1eqM5D3L5XLg/FW0ay+MNEWd12jatY/xa7s1bRtGhsD9PH36tEUgPJPWlGyefc2SVdPDO/94JnSOV6PMHMgoo1ucdoQmAPSKIHzpJDnh8PCwmQPK9XyYpFgsGqeklsA88JdeeinAeK9UKkGewLPPPmvXsWSWzpvBwUFTYxVWy6Mea+adLz3W/gCksbExK3flM3/mM58B0G1k8VM/9VMAeuHOcrlsKr+2K/MdgjWDzOfbdzodc1Bx/pphRlOL8x4aGgpUV0Xh9aG8/v7+oBip0WgEuQx9fX2231wrDeF6VV4z8DifQqFgGozvHaASnlphrVaz+6eZTL5YTWHUtIEptU0FAuGzeQdepVIxaDWWU589e9aKj/hbNYFJ2nBEm5NwfO9AVBMnqx3IKKOMrkk7QhPQ3G6fnKNZV740s91uB/aOOlq0dRjQta0p3cidNzY2LM+e0ujtb3+7dQviPalN3H333QHgxMzMjGkM5MSaGeYdhGNjY4ENd/DgQfstQ4R0Hn3oQx8yMIrf/u3fBtC1WX3Ir1arJZymulbDw8PmB9F7cz3UMedDm7x+cnLSvtMkJ3+9liV7zUsBVTRE55uOqtT1DjmtwlQthE5Rr5loVh7nuLq6GoQD1f+gPgwg6RNQLY7zoI+Hef2aAMX579271+bBMubTp0/bOfLgqcViMZEp6NdKzzfv5ed9PUARINMEMsrolqcdoQkAvZRKcjJf064Sh5TmgdUadp+AUqlUbHyGA9vttnFxjjU7O4tHHnkEQM92Y4juTW96k/kHyPVXVlbsXmqT+dxuzW33UGIPPfSQ2aa0h2n/v//977ckJ6YFDwwMBP0BKpVK4K3mmg0MDJgUonRpt9s2X61N8JVxHPPkyZO2VtQqtC+gj9QUi8VUoA9qVxpupET1c8zlcqm+Bkp9rX3QBCZd71qtFoTwtBmrRho8br9qHz5RKpfL2VpxDO7h0tKSVbHyebl3QE+T2tzcDDRFTRby4UIN4apPyodRde+ulza8Y5gAkAS58CAQQG9T+aCFQiFw+GhnXjrwNMzi1eWlpSXLCecmz87OmrONMXsyjaefftqYwBvf+EYAXfWdKp1m+TH8SGbAmgYtUFIHJB2D3/zmNwH00G1GRkbwD//wDwCSxTGaXw90GSYPoS8l3t7etgPLlyQNEVfDdcyX4AtEx6nuQRpIiOavc/94z1KpFOyZfsaXX82ZtDoIb1LofX0T1P7+/sDRp7UGGnpUR6A+p758WuDDveX5oNm4e/duU/k11Mu1UnPGtwrTefN8qAD0JrOGevlcDHEqc7waZeZARhnd4rRjNIFcLpdI+CAH1rbivlJrY2MjyN3WXGlKZ+LGdTodA4ug0214eNikppb8cjxKJF5/6tQpy/Fmj4FSqWTIv9Q+nn766YDDK7f2LdKXlpaChprMGDxz5oy1sqKEKhaLpllwPTqdjo3n8/M7nY5JdpVyXFP+rl6vBx2IqCVo6bY2FfUZg5pt57P31HzQEKr/TBOWfI+BVqsVZAdqRR/H0jZjviuVJhDxuRRf0WP7l0qlRNIUkGwsy+djKfnb3vY2K3OmRjA6OpowxTiGDxerE1P3lvPmnmpVrW/yqpBwWRVhRhlldE3aEZoAbZpGo2FS3DthqtWq2TlqA3s7MI7jwDnCBI2FhQWT6Bxjz549CekA9Dg30JOkTAF+//vfbz4BagsvvfSSSbCPfexjAIAXX3wRf/AHfwAgrIwbHR01pxEdXMeOHUvYpkC3xyHQ1QyeeeaZxPW1Wi2wo+M4DjQAbV7p4c7Onz8fOPO2trYCeDGVsL4ngcJ6kfT3/C19AtpHUMNZHjc/rSW9VhZqGi2vpwbDe1HjWVlZSVTt8Z7ex6R2N8+atmlXyDCut0/h1RAqU8LpXF5cXAwkdrPZDNabY/b19SUQk/m8HpRVw7ppado3HVQkiqI8gGcAXIjj+KeiKDoI4LMAJgA8C+BfxnF8bZAzdA9aLpdLZG8ByTitNxW0TZOqTb5ggnUAJ0+etL/ZFXZjY8MKdxiL37Nnjzn1eNjUxPj85z8PAAk0HLbN+trXvgYA+KVf+iV8/OPdloxU2zVXnmYMwUgWFhasWeV73vMeAOn5DdzQlZWVwAmkTMB31+3v70/gzgHJEls1XTwj1maXPu6saDwk9VR7/LxGo2H39C+hfqaHns+nJgLH5Rrk83n7ns/HFz+tiScZLtBTq3O5XBAt0RoJhf0m8V4K4+7H1YgX90PXwKv8HFNRrBStWYumOB/NwwCS2YY/ilLi/xbAi/L//wuAfx/H8R0AVgD8yg/hHhlllNFNohttTb4XwE8C+G0A/8OVTsXvBfAvrlzyKQD/FsAfXmscNiTVqkDfWDGfzwcNKoAeV1aV2Esf5c6+ao7QZkBPYl+8eNE4KZ2AnMdb3/pWcwjS8fjCCy+Y1OF1n/vc5/De974XQE9S02n0zDPPWLXhBz/4QQDAY489ZlKKY/D6kydPmuSiJtPpdBIl0ryPDympxFGVnL/zKMppn1EaqaNPHbfejOHaDQ0N2XeqLfgQl/ZV0Co/fufV/LTeDyoN+czUDOr1umltWjbuQUKWlpaCPAGaUJ1OJ3U9uAce13Bra8uu1xwIngWtwfDZnbz32NhYwpzjNT6bVp+Z39EpOTQ0dF1z4EY1gd8D8GsAeJcJAKtxHFMXOQ9gT9oPoyj6RBRFz0RR9Ix6nTPKKKMfLb1uTSCKop8CcDmO42ejKHrP/9ffx3H8SQCfBIDDhw/HjUYjqEcHko1DyeXUN+D7AqgkU44NdB1yXsPQXHZy6UajYd9T6mum4d/8zd8A6Nmci4uL5gQ6evQogC64yNe//nUAPbufzsX3vve9xu0ZnvzMZz5jEok+Cs7rueeeC2DAKpVKIBEmJiYCR5XWt/vcdA2Paq2DX2fN2tRmo9wDkkeK3t7eNrtYw2ok9Ufwb2//1+t1c8gpxoTiDfBeXmNght7w8LBJdO1sxHG90xBAkOm4tLSUsNVJHnla24Excej+++8H0HUW63kGulLfV/5xLO0VobUD1HhUI/bJTapV+oxETzdiDrwdwH8RRdGHAAwCGAHw+wAqURT1XdEG9gK4cAP3yCijjG4yvW4mEMfxvwbwrwHgiibwP8Vx/AtRFH0ewEfRjRB8HMBf/QBjmb3pJaTaXOpdB9LhqJXIxSmF9u7da8k8tA3L5bLZT0wfHhgYwMsvvwyg1zuOHH7Xrl2BtJqZmbG/mdTTarUsNMkkHebdv/rqq3YvcnPVghhhYDiw1WrZ+Iriw/Re7dpDaekrLjWd2ocPgSQegw9L8f8nJyftujSb1lewbWxsBLUMartrnwKPFaBh22sBgmpvBO3OpPfctWuXSUZqB41GI4D4bjQa5qvhWnGNtZGqArEq6Cj3AOiGjYkURS3xtddeSwVe9dDx6lPRTkyco7a4J3mocfUv/FPUDvw6gM9GUfTvADwH4I9/kB/lcrkENr7mPpM8UMbo6GjQiDENMZaNSe+77z6Lt1M1n5ubS7TqArohQjrgeAC1NwEPBtXIZrNp9+ChnJiYsM0kE+Bcl5aWglj50NCQ3Z/35vhRFAXIwhoKpdNL23ORtPEqr+dYKysrQT/7fD4fID3zoKtzTA+g/g0kD6R3dtEBzPEAJArHSFqS7VVtHZcURVHgFNVMRr5E7Apcr9eD7EB1Qvp5qENOmYFvjecbsABJZGauraIHqxkK9MwUNe+4xqOjo/a9ltlfrWQ4juPrlhP/UJhAHMePA3j8yt+nAbz5hzFuRhlldPNpx2QMDgwMoNlsBq2btIrLA04oyq+CKqhUA3oZgIcPHzYOrB2AvBpbq9VMulK91pbcHE8ztjgeuXq73U4koQA9KbSxsWFSnlJ5YWHBxvA5+ENDQwl4LqArXSgd+N3m5maQ0adOJx9GUqeUOv+oGbFUmvPI5XJBya/e3/dX6OvrS4UX84jFisfPZ9JSa58ExOa1SlxrIGyfpkjVeja4Htzrer0eaJba9cifK+0LwH3RGgkCiB4+fBgAcNttt5l5qWo+NUtfP1Gv14OeC/l8PnAuTk1NmeOTz0yzV+HcrkZZ7UBGGd3itCM0gSiKUCwWE7abx6HX5pmklZWVAAZax6BEUs5Je1vtUn5Ph5JKQ5V4QNdxRomtNQG+pl4be9LxSI6/srIS2IFaN+9tZk2Z1kQe3ylINQEvWQcHB4MqOKAn6RScM60eg8R5UyNoNpuJpqdAEjqb+8d1V4lNzUvhvz00nNr6vOfw8HCQ2qy4E9QcuE8rKyuBZB8dHU08A+/pk5BI/f39tn9cK7XFKZXVwcreksSdOHr0qDmEOX6pVLK9ovajiW+co6YBK0Ar0D0LlPw+FfsH6UC0Y5hAFEVoNptBVhZfbnVspT0UN17zrX1e/MLCgh1Cvnx79uwJDkNfX5+p/x7Btl6vB3Flba2l8+DL7xtZjI6OBjH+kZERey4f8202m4HHvtlsBgdPG034rL9cLpcA0tDf6Ry1V4AH89jY2Ah6BqS1N1OG7FGHtH0aX6p8Ph8gRHMMzTrURjN+PdbX122eajLxPowGpTUwJWlDUi9c9Myps86D1CiCEZ+dTHpycjKIBqlz1ud2aI2E5rV4R+na2lqiOS7QMwcKhUKC6adRZg5klNEtTjtCE9je3raKNp/dRI68f//+RIwX6Epnn/+tIRE/1uXLly2Li1Bed911lwGNUKIdPHjQ1DZy0Te/uRvwOHHihJkNvH5kZMQkjHYF4m89mnG73TYpqOE4r4pqPwEfS+az6u/SMAO5BgoDpnj1fiyN2XO9Kbk1xu81NaW0cfm87XbbJJ+2Pqek5fx5z62traAHxebmpu077z8xMWGfec1hYGDA5sSxNLSnrd35OU0Jzbzjs6dpVx43cWpqytaR9SeHDx/G3XffDaAHHKNYhzwv2i+B91TQHJ+Z2Wq1EpBxer3u+9Uo0wQyyugWpx2hCQC9TjPeIajde6gVqNRVZFugKxnIFb3z6MKFC7jnnnsS99XkH3XEkZPSF6C9CHk9Ofdtt91mv2VloQI9+MoxlZTqyNGedTp/tVU1P95jLqifwIfmFGxFw6o+807hwjzYxsDAQJClmNbskuui9is1E+2Io/3+tG4f6O1npVIJnH/ac1HDdXSsce8oUUulkvlxGA5UX4bWV/geB97xB/S0Toa1dW7q3OVYx44dA9BNOKOGwwa3qmFwDRT9ms+ufqi07EA+uz4zv0uryVHaMUwgiiJsb28HjSy4GXzxgR6yqx4yja0raAbH5v9rqi/QdXoxvZfOlMXFxQSUNdDboNnZWYv1Mv7b6XQsB4AvwMjISKCSa8da37u+2WzaM3oEpXw+H0BgV6vVROop0HWOcVyP2qxtyLRxiG/s2dfXFzTg0NZdvlGnxvjJMHX+Pj5fr9eD/VlZWQnyQrgXIyMjicaiXCvuHxna8vJyQgXW9dNYPF/CUqlka8/v6vV6sKYaKfFrWigUgjRnrn+j0bC0b+YL1Ot1a1JDUBvNROS9uT4LCwv2nBx3cHAwcCBqyjRNIHUW+4xOT5k5kFFGtzjtCE2AraYmJyeDGDX/nZubM0mgTiMP16TNGb2DcGBgwDilSg1qAnQGavaeNhEFuuYDvyNXf/XVVxPtwTlvPzeOMTY2FrTn2t7eDuLtlKwMNQLJvAmq8rxOG1n4VlyK98c5qlNS568Zglw3juVRktvtdqDKc74DAwNBOFcbknD8qamphEmja9BqtRJhVKCrxfF7qsHT09NBUw6F3GJth4YstTSZa+sL0dSx6tuyKd6/L5RSzYu1I1EU2d+6Lt4k47xKpZIVHKnD12sfAwMDQYGZZoJezxzINIGMMrrFaUdoAlEUYXBwEMvLy4FjkNJxeHjYJDY5pWbS0XEyMjISOK9UUno03o2NDeP2ms9NKcL7U+KUSqWglLjT6Zh2wHtrOM23SqtWq/Ys5OqXL19O2Hj6Ow17KnQax6cjSWHRtEqNz+tbghcKhSATUSUYidcPDg6aZsQ9UGnvnVKtVsvsYq7x4uJiYNNWq9WEb0S/y+fz5syjBthsNg167b777rP5UwPh+JSik5OTNid+Njo6GmibxWIxaF2nDtY0RyLJowhXq9Ug4UiTf3he1A/mu25paJNneGhoKKjR0LJon2imz3c1yjSBjDK6xWlHaAJAV8KVSiWTOj7Xu7+/36SbpgN74Iutra1Ec02gJ52bzWaAz76xsWHSntx0ZGTEJBI1DEqZcrls45Krezx6zpHjsseApm+mNfZUWGl9TvXuqoTi34q94H0BlBbDw8MB0IjauVr378Njqn1ojQGQrGHwEZ12u23rp9EYfqb+Hw8Sqp19PL7C/Py8dZWiRnfmzBnbZ64tKY5j09roG0gbV6NNXjNJq06t1WoBEIjunQdgrVarptXwLBQKhQCkVDUxDfFy3LS+Awqhrt+lYSR42hFMgMhC6+vrQahIVSMPirGxsRHEoaMoSiDy6nfFYtEWi4f5tddes+wtVZ3ViQcgEU7i/Rn60Ti3ZvmpUwnoqej79+8PcuoV+UdLZoFkww5FCvaOx+Hh4aA9l5oUZGTqKPJNP67VlEMPmmbsaRky0DMfNNtPS8S5fmnFP54Bjo6O2gvD9bv33nuN8fGZGo1GQq3X+Q4ODtp68GxcunTJGJOq43Q+MlvSr7vOrdFoBFmEWtTjy4sXFxethoHXDw4O2nOxdFsZuMdN1IYkGs70PSKUEWeOwYwyyuiatKM0AUWR9SG3arVqXJdcemxsLKj60lJiSlZ1uLElFB1z586dMy5LCbW2tma/IXcmN280GpbIwgShYrFo3DxNunlMuCiKgiafmqnnQ1f6DCqZPFhEsVgM2rGrU4jzUIgwmiPqzPMOqrT6BnVOcV98LcPQ0JDdU6sEtYyW8/EmHCX2xYsXDaOPdR+ahERTrFAoBPdnUlkURabRUTM5c+ZMkNyk6+Yr9bQiUhOJrobb2Gw2E84/oGv6pSUh8TpqNWkOYS031p4M/M7vgWrBehbTKNMEMsroFqcdoQmQNN/eA2YoiCYTLvr6+oLqqXq9bpLUawJArzmkth73DjmgJ2H8fGq1miERK1ClB9TY2tpKgE/oGOog1KQR7xPwXF2v5/z9+PQxUOJxfYaGhgJ8+1arZWul9jPXgeE97ftHDUB9EyRf8TY8PGy/VeATkqY0c089KvD+/futRTt9N0tLS6aFKQiNR6qmE25pacn2hZrd+vq6SV4+p9rOPnFHw8Ba4+99WKQ0bAJtSKq+Jq4JzwtJu0bpmfDJXJubm0FIk3Pt6+sz7fBqtCOYAAtCOp1OUECinlDvRd3Y2LDDrggsPlNQy169k2lyctIYQxqyMTfBx4F5LyCJwqstpZRxAMnGlL5YqFAoBFln/K7T6QTPovDsmiHnC59UFeS68dlHRkZsvvSs9/X12T18C7FqtRrg/RWLxUTBkK7j+fPn7eVWkBCPHqUw59wLojtPT0+bA5bMN62UWPMgfE5AFEUBkrMiVfM59+7da+NqDQDXkevmkX2AMCsUSIK2cCyPcUmGpffiWOVy2dY0rQkvn3NwcNDu5dvP1Wq1LE8go4wyujbtGE2A7cM0tAEkcwJ8vr3mnJPa7XbQgEGbllD6UN0fGxtLcE1ezzEoEdQ88FV+Q0NDgfqooRwPfOJVR5JXH1WD8JVgKoUUBsyH83Suvopwe3vbNAZtBOvBLdQk8qXDxIYEeg1dqV5rMxTdO62m5PqwBJt4fAzVnTlzJiiTTWuQsmvXrsBUUecyJTCdhVNTU2ZmXLp0ya6juaCVpyRfzq1t8Ejq/FVTDOiaR1wjDbdqBiyQNNc8TubIyEiQFbqwsGC/8bkGik58Nco0gYwyusVpR2gCQA8GyWdgaRiEXFcx1cn5NEddQTAAJBw65PDk/nv37k10I/JjcD7aFo2SjNKq2Wyazcn5FovFq4aPcrlcEAJNg0Xz6MM6ltrWlDiKhEzJSudYoVAwrYDX1Ot1exatvPRZhFq1Rh+MOlF9GzKulYJiMElGu/ZQwvf391sNAMcgJNfZs2eDajzOBeiFdaenpxNIwkDPObq+vp7o/gR0tSFWge7Z022c/Xd/93cGOuMdqwogQsrlcuZ30BA1kAyFcozZ2dkAlVrXUasZOYbX7NT+537u27cvqJdJG+NqdENMIIqiCoD/AOBeADGAXwZwAsDnABwA8BqAn4vjeOUqQxhR3fcOMPXwK5Q1r+FDq9rpHTf68vGl4EFNQ7pRc4C/5Uu+a9euAPNOu8eqOeBbqXl0YCDpTPPmg2Yfct6aecfx+TJVKhXbfGVQvKfPYKzVagE2YrPZtJfN9+NTJGJFS1ZGo+MreAqffXV11V4E3nvv3r32W5Zz0xk4MzNjDJ7PVKlUEth8QLK4iS/TQw89ZM/OOfGlffHFF/Hcc88B6OFHPvTQQ/YZsQDJMNfW1hJZfnw+321ZTTpFhuYacN48f4VCwZ7LIy6r6aTOTp8BuLGxERRPaSOTm+0Y/H0A/3ccx3cDeCOAFwH8BoC/j+P4TgB/f+X/M8ooox1Kr1sTiKJoFMC7APyXABDH8RaArSiKHgXwniuXfQrdHoW/fq2x4jg2hxs5K1U6bf5BDqnhL99UUrHgGYvlWOvr60EZKCU8xwO6kmTv3r0AeiooJfD58+cT2YOcow/laFGMByYBQpRe1Wp8+HB4eDgBwMHrvdMyl8uZ5KLEU+eexx3UNeX4a2trpgVx3bSugJoOQ23z8/MmqX234Xa7HUihRqNhavj+/fvtc8b96Tjjc9x+++2maWhTEd5DQVkoDTWLEOieA873yJEjALqS/vHHHwcAa1J755132n7TNGRm6fLyspkS1GAUBIfnT01A7zRcXV2136pT0hf/eE0T6GmYQ0NDtkaqefH5PF5hs9kMtCZPN6IJHASwAOBPoih6Loqi/xBF0RCA6TiOL125Zg7AdNqPoyj6RBRFz0RR9AwPbEYZZfSjpxvxCfQBeBDAv4rj+FtRFP0+nOofx3EcRVFqHWMcx58E8EkAeMMb3hCzEi8NKBHocnpKnLRcbHXkkQtSq1AMeW8bnjt3ziQTJcnm5qY5iChx6DxcX183rszrx8fHzRHHENPS0lLAlTXhiPOmrbeyshLYlRqm9CCUzWbTPuNzNhoNe1ZtPwZ0pQWfWYFaPMVxHIQofXKPzlFh1HzNQaPRMG2C1+zevdu0LO7FK6+8YlKWe8Hy6ze84Q1Bv4TFxcWgC9Tq6mqQnEPnYhzH9qx33HEHgC5C9L333mtrCXS1PEpUJiaxZFnLkzkf3QPfTLS/vz+hFQJdnwDP82233QagW8XKeXNfPLgMx+M6aqNVIAmWk1aOzD24Gt2IJnAewPk4jr915f//El2mMB9F0eyVh5kFcPkG7pFRRhndZHrdmkAcx3NRFJ2LouiuOI5PAHgfgONX/vs4gN+98u9fXW8spgSrDek91FoNRW6nddSkfD5v2gS5P+1NBYZUjy2hwxVAlN5s/lY9uJRCtLWWl5eDvG8FyPRSvNPpBNVk7MXIvzkG0JXAmkBC8gCfq6urJskocWhPl8tle3ZqMHEcJzzRfCYP7KLdnfT5uMaU0NQ0VGPw0G0HDx6064m9v7W1ZRoUr+P+Dw8PG8Q7r19dXQ0ANdfX1xPnQtdbMQx4vaY0q0ZEH5HvHzk1NWXfaUTKA68wklIsFgOgEQ2Pcj7z8/MBDJ36t7x/qNFo2Hx5DoeHh+25uN+898bGxnWThW40T+BfAfhMFEUFAKcB/Ffoahd/EUXRrwA4A+DnfpCB6EjjAjBExEOtHWM1j9pjEgIIMgv5cmteAQ/nnj17zPnDf++66y5zFnHjucj79u2zQhYNx3CjtckmXxTfzCOXywXNUjWkxO/U8eNjzrlczhgDD8X29naQw84xFxYW7DoyLA1LagGWx7DTMl+PU7i9vR3k5SuSM/eRjLbValkzDq73rl27jDHRIfe2t70NQJdh0YGnzTy5Dhoz9yjGWkvgnZatVsvG437Ozc3ZnvFZ6IS75557LLeEz6SgH9706+vrSy0R9u3nRkZGEo5doCegGo2GfaY4j2QIZGJbW1v27Jyvlkd7M8nTDTGBOI6fB/BQylfvu5FxM8ooox8d7YiMwU6ng42NDTQajUSTT34HdDkbnW/ksMrhScr1fJPIxcXFRJUf0FXbyNl5z/7+fuOkzGSjhNre3rbwjnbyoTRUeC9KUJ/E0mq1TEXzuIlAmHQDJLvvcK4+q1G70/jEKm1vrrnnPkux0+kkQpOcL8dQkBeguwd0clEyaXkyQ5rcx5WVFftMTSz+zXWmulytVgMMxyiKTO1VxGDe169Lf39/0F5sfHzc5sF9uuOOO6yKkZ/RHLz33nvNZOFn6uDl+qkjlH/zu42NjaC/ApDUqrimQBIbkb9bXl4OgG5WVlZsPAUkAZIwZ1ejrHYgo4xucdoRmgBJQRd92nC5XA6QWlutlnFRShLtoOPBFNKANTQXm9K8XC6bVDt37hyAXohIAS051qVLlwLNpVarJZpl6jNFURSAeKpd5ysS8/l8wM1ZawH0HHJ33nlncJ1WRirgKpAEodS23x5GS1ObOTc+7/j4uH1G25cpsVNTU0EdQrPZtL8VnIV7Sz8BnYH79u0zf8KpU6dszbyTuFgsBqE19Ql4SK7x8XGzn5966ikAXV/QgQMHAIRnZ3l5OahJWF5eDjAdeE6Wl5dtPXj9ysqKrQ33YHp6OkhyUp+QtnTn+Or041iKbaH/jo6O3tzagR8WscGEZvt5NJ5Wq2UbSSagradUKZ9vEwAAIABJREFUreZm8XpuaL1eD4o02u02vve979l4QPeFJK4dVT86j6anp80rywOwe/du+z6tMISk8N88BDpHXyzCMRRARKGwtaSaRJPJx41VtdQXyDdGqVQqpo76g5XL5WxcLZmlw4yHmbH+vr6+xHVAdw+4x3S+RVFk8+Y86Jgtl8uWs0GmUSqVArNHO0mrqcfr+Z0iHT/99NMAktiFPt+fzEmd0NoGj3vGf3k2x8fHzcxUNCNGODjG+Pi4nTFtiMPfcY85n9XVVWM0ysx9vozC7aupmUaZOZBRRrc47QhNIJfLWd0AVSfF4we6qjxVqdnZWfuOn2kbJqpVXp3N5XJBmEzjtPzu+9//vnFbwlzxPnEcmyOMn42OjhoXp0YwODgYxNu1QlJj9by3B+DQCjxKTUrMZrOZkDpAVwrxex+yUjw8Bd/w2YGbm5sJ/EKdv2Zjcv5LS0u2Vm9961sT60iHL5DsScB5c63SWqRpNhw1NEXU9T0ltALVhz21sQvn9r3vfc80Fp61ixcv2r2Y1ahaGZ9Few14jEuaGHEcW4kyz0m5XA4ARIaGhhKlxkBPc1BzQzNAOV/NMPQNY7gurMu5FmWaQEYZ3eK0IzQBkmYAakchAIm6Al6zsrIStCGbmJgwTYAcVttvcQzaseVyOeEzALqS9fnnnwcAPPDAAwB69eVPPfVUwk8BpNcJaAahhw0rFos2b85Nq/corTTc6bsC1et1kxysa1hZWTEJ5h2gmlykGWk+MajT6ZjPgxoG772+vm4aD+c4MzNjEo9ECX/x4kVztmoCkSbUAN299k1EtYsQpTNz/Y8fPx50Ktre3g4Sd0ibm5s2X15/4sQJvOlNbwLQC0tqwpnvSrW4uJiK9+87/nDeq6urQfWj9lDgOXzllVcSPgagq4nyPhxX6xC4L+rbSdtvnf+1KNMEMsroFqcdpQloCIp2Jjna8vJyIEEUkkuTaShdPWJQLpez8dOq8YhqU6lUTDLSxqMH+a677jJOzXDS4uJiICE3NjaM23vEIM3nVkwCzoOSg/feu3dvACV91113WaWdajw+ZVaBW2lLql2qa8nxvTRRzYCVnNrHj558nwjTbDZNeio+hE/X1eQprh/n8/zzzxsGwNGjRwEAzz33XNCPT/0EHIv7rnX91BLz+bytg9rWnJv2uwS6Z4NaofqQtO+irvfo6KhFM+hXOnDgQABSu76+HvSXUK3SdzHa3NxMwLLxO54Z/qtr4bErPO0IJkDnxcjIiB08HhAP6gEk8dPS2kbxM24yD8XGxkZQ8KGQWdpCiqocVUVeMzY2Fji7Dhw4YBvJ6xUTkS8CD1i9Xg/AKHK5XIBrrz0E+CKSOd1xxx1mxjz77LO2Br6PAA9bu90OwnUKxaY1GHwWXs9yWnXqvfbaawC6Ki4ZNg841dULFy7Yur366qu2LtoYg/f0PRG078SLL74IoFtWDHRzB8ggdf3SOgNzfN6L8+50OkHNgzaW5XrrS8gzSPOn0+mYI5Z7oftKhsmw4OTkpK0fTblyuWx7pbkUQLL+RPNh/D6ura2Z85FjkWlMT09flwlk5kBGGd3itCM0gU6ng5WVFQwPDweoqZpx5sMgY2NjQdcbbZDpEzn6+vpMlVLwEsWzB7oS3gNZkAYHB835dvz4cQDAO97xjqCe4Pjx4ybVfJhHE4k8sCrvD/SAJ7SEl6AYuVzOpCslmfYz8FVzGxsbQX751taWmRKqwnvkXCYjbWxsJODYSCqRdA0U5FI7BVFjUKg3fUadTy6XM+2Kz37PPffgy1/+MoBkGNDXS3DftcaEmkCr1bKzpglT3DPfd2JoaMg0Eu7Lrl27bG3871ZXV02L4Fnb3NxMJDcBXY2AzlBqvVoZybNAgBStr+F3AwMDAbyd9pjI+g5klFFG16QdoQlsb2+j2WwmUmd9ims+nw9ANPRvrYen00pxB4CuxPHw3wr5TI558eLFoI8gr9cuNZR83/jGN4zrv+993SrqarVqEswn32iuN30PAwMDdp1KbyDZiUar8nyvQM5P100dfnS68XmXlpaCNNnJyUmz8b1z9vLly4HjCehpMbSBtVck560p2dQU6CtRfAXNh+f1DOfSIfvAAw+Yn4Ipt9pTwvsVarWarTOl7eLioq23wrJTS+Ezqd+Aa08N7N5777U19b4VhchXLY/30l6E9DXQkahhR86XGuz4+HhQN1Eul1MxK/hM16MdwQTy+TzK5TLK5bJNmo4OzQPwmU+lUikoxS2Xy/bS82VSHDi/yVreyRemVCrZ5tJBycNZrVZtoXmw8vk8nnjiCQC9F+EjH/kI/vRP/9TuCySz5jzziqIo4dwEell59XrdDpmW+aYxQB4aRjP4/5ubm8aU+Ezlcjnhzea4ujZA70UoFApBuW673baX2rc+888HdPeJ15ExLC0tBfiK/PfgwYN22LnGhw4dwoMPPgigZ5JNT0/bmfEoTI1Gw0qEabadO3fO9u+ll14C0N07vkweEWltbc3MAC1u4rpR8HBtq9WqPYMWGfm8llqtZsxQo1j8fx91UNRozl9NON+erVQqZY7BjDLK6Nq0IzSBKIowODiIhYUF43Lkjpr7Tq6rOGo+OzCfzwcxckoczX1XB40HrahUKglIMt4L6MbuKflIY2Njdv0Xv/hFAMCv/uqv4ud//ucBAF/4whfst0BX9U/j8D5EpDFrquaaK6/twYGuFPetwCgptRJRMy999dni4qJJPGpDGnb0dQ21Wi2Q3op5yH3k/gA91Zll2kNDQ4msTqDn7FxfXw+k57Fjxyx3gLH7paWlAGGZ9+7v7zeHILMODx48aNfzfHQ6nYT2ACSbw2qtCNDVINg7gZ8piIvP9tM8Dm2lx/wUxaDkv+pQ5bNR29CKW19zozknPoPSU6YJZJTRLU47QhMgKTwWObLa9eqcA7pcl84actbR0dEAAovSc2NjI1FnDXQ5pYchI7YBvwd6Ntb6+rppDrT/K5WK2e/k2F/5ylfwy7/8ywBg9isTS7RqTh2VdDTyXpSGb3nLW2yN1FHpQVaq1arZphyfrb4bjYZdp6E839J63759gVOMa7WyshJgOnAOQIhKrKCYWuPvMQk0ackj6WoCFK955ZVXTLq+613vAtDVwDx8mmbg0Rfwj//4j/Y79h3kmmpo2Idu+/r6bP+YAXju3LmgUpTrXygUTPtQFGbNcAS6WiTPMPEHtKKSZ4Bns7+/Pwj5tdvtoO08Sf0KV6MdwQQIfd1sNm3RmVGlKCo+nl+pVOzl1wIUHmhFdAW6jMVn8TUajQQ0NdA9DP63Ggv3B6VYLAaosGfPnrWDzLwCnRe/oxrZarUCxyBf4Pvuuw9PPvkkAODMmTMAkuAcZEaTk5OBSknAFO2ErAebn/E519fXE6XGOseVlZVgD2q1mkVLyCxoGmk6MJmFQrHzcPb19dl6+JdKC5o4bn9/f4DI/DM/8zP4oz/6o8TcNGWZKjQLwTS6oeeDL6xveafXk2kMDw+bieDxGKempmyOHLPRaAQl0PV63X5Ds0QBZPyeVavVwEmsc/OCYWtrK8h18ZSZAxlldIvTjtEECO2ksXogGWLi3+S+r732mkkH5f5UnTwAxtbWlnFZcsdyuWxSX7mzFvYAPQfR4uKi5Y6r84jXKfQZHV+8P9XIS5cuBYVP7XY74eADgPvvv9++o5TVTEdKQUqaWq0WFKEo+WasapZw/FwuF6j81DQ0B19Lm7VtO9DbCy3wUnxFNd34nYfAUqgtL1FLpZJl0DG2/pGPfMRMg2984xuJNbj99ttNg2Lo9Ctf+Yq1JKfaPj8/H6yRtonXfgBAV+r62hJtGEOixqZqOc9wtVoNoOi0nNqbJRoOVIesxy7UOpgMXiyjjDK6Ju0ITYDwSJpZp1VkQLJ1N6XnzMyMSX3fPBNAaniFUpYJH/39/fZbSrLNzU2zQ9OcXSRt9c25K26+9irgZ0BX4lD7oBSdnZ21Z6amwbDgN7/5zURiDdANN6qDFEgCe1KKq+3M79QW5/rROaX9EjSzEEgCsGgdBOdB7U1LeX1l39jYWNCoc3l5OSiZ1U5AvuJyZGTErqMN/OSTT9q6cY8411arZb4AOt9mZmbsLJw4cQJAt+sRnYW+LLnRaJiGpK2+FUkY6NUVrK6uBtWsrVbLnpNz1I7cHFdbjvH8K9BMWkm9r5fh2VEN82p0Q5pAFEX/fRRF34+i6FgURX8eRdFgFEUHoyj6VhRFr0RR9LkrLcoyyiijHUqvWxOIomgPgP8GwJE4jutRFP0FgH8O4EMA/n0cx5+Nouj/BPArAP7weuPFcZzwmqelm/ra6u3t7cCDrZVa1AAoFRVejLS+vm6cUu002u+0lUlpiT7b29t2L85fQSV9c1W18RkFyefzQR85jvXtb3/b7F2FntIuM5yH+jqAJOS410g0jZUS6uzZs3Z/n4OvgCPaJYc+D17H+Wg9PAFQJiYmbD1ozxeLxQD6jPOq1Wo2Hp9pYWEhUfsBJGHcqR2oT4aaDpO5PvShD1kNAH0DqqVwXD1zvlOQ1lJotIn/z78Z5uM6cW34LFeD1FN4MYU281gROjcPzjI/P5+oLk2jGzUH+gAUoyhqASgBuATgvQD+xZXvPwXg3+I6TICotBrK8K24tra2AhRZLaLhIu3atSvRsgnoLYyq+VQdq9WqvSi8bs+ePXZo1MFCogrHbLF2u22Hkk60gYEBy0n36pi20aK6vLa2FuR9k5k9+OCDdqB5b80TUJPIO410/fyztFotYwia56BOPP+vR3De3NxMqJ6cB+flY9SnT59ONFzhc/rWYRpP1wIfoLvXvi/A+Pi4vWzcOzK2EydOGON5+9vfDqD7stJ8YR7G448/bsz2K1/5SuI5t7a2ErkUQHefKGBY0PTCCy8A6Dp1mU9Chjk9PW25BjwTR48eNbORTIN7PDAwYJ/xRZ6YmLBnpilZq9VsbtxPPrvWQ1yNXrc5EMfxBQD/K4Cz6L78awCeBbAaxzFLl84D2JP2+yiKPhFF0TNRFD3DFzOjjDL60dONmANjAB4FcBDAKoDPA/hnP+jv4zj+JIBPAsBdd90V9/X1YXNzM3CY0CF26dKlAEdtbm7OnHlaRkrJ5BF9FeOdY4yMjJiE4XUrKytBKIwcHOhJK1K1WrX5kkuvra1Z2yxmqylcGLkzJUm9Xrc5UU2lk6pQKJgmoBWR2owT6KqzXAc+p2oVvKeiGnsHYrPZNKnpATD6+/sT+wEk27hxL7QpJqUyNZNDhw6ZBONcl5eXgyw43rvRaARawtLSks2RUvb8+fNBdiJNraGhIdMAKcX/+q//2qQ+9+mBBx6wZ/GlylrboRmmlLx0ONIxePbsWdNMtJU458vzsm/fPvubCU0kDQNTvX/55ZftuXheLl++bPuiPSJ4T+7V1ehGHIPvB/BqHMcLcRy3APwnAG8HUImiiG/JXgAXbuAeGWWU0U2mG/EJnAXw1iiKSgDqAN4H4BkAXwXwUQCfBfBxAH91vYEYIhwZGbGwDnOw1W70tvvU1FSQJrm2tmYSjxyWHLxSqZiWQCfg+fPnAyiz6elp+5t2He22OI7N7idtbW0FDsTV1VW7LzUAOv5GRkZMcvgKRqAnSVkBeODAgcDZqZVjlKyaoOTbhDebzUDaVqvVRDov5+Y7IWklJcegdlOv14P+h1wrTfDiswwODiaeAehKOUpBdgWiJqMddzivSqVie8t9Hx0dtfXmmmrVKdeba/bQQw8lagaA7t5+5zvfSawfv1MHJcdvNpuJdvacL+evSVMcg30VGZZ88MEH7VmpAapfh/fnPffs2WNnk/d8+OGHDS+B74/2k7ieuf26mUAcx9+KougvAXwHQBvAc+iq938D4LNRFP27K5/98Q8wFtrtNra2tkyF4sJozJovEw/uCy+8YKoRF3VmZiZRqKO0vLwcOFAUFZiHYmxszF5YqndUqSqVStDIQpmANv/wdQcKKuLrD/L5fIDyq3Dh3Eiqk7Vazcbns3Q6Hdt8byqo843/Tk5O2nOqc8/nRHA9W61W0JBkenraHJNcW82e45oSH3BgYMAOKsfd3NxMIBQDPSEwNzdnJgVf+PX1ddsDRY/iHnBNOf7MzIwh/tIcqFQq+OY3vwmgl5n5xBNP2Dp4oJSRkZFAvWcjXV0P7vH09LQxNs5/eXnZ1oamU7PZtHPqo075fN4YCZlAtVq1M8CzNj8/H7ST01Z81yslvqHoQBzH/wbAv3Efnwbw5hsZN6OMMvrR0Y7IGOx0OlhfX8fAwICF+sjFyZm1zzpVy7GxMdMYtGSWkldx2YCuxuGBL9bX102CkSMfOHDActPJbZlfXq/XbY7aVMQ7LdUs0Qw9ID1XPi2ER6ml1Wd8Jq6Z0uLiooUtKYU0D4Dz1uajPqRYLBZN++EeKDwVxzh27BiArlrt8xpU3adU43zq9XoiqxNI5h9Qs6N202g0THOg9NfKT66L9oPgv9zjvXv32ri8d6FQsOekKn306FHTKH05dxRFtm6c2yuvvGIOOToQFUvRa1la18LnPXXqlJlWdEby7JVKJdM6qBmtrq7amtKknZmZsXlTE+T6aB+Jq1FWO5BRRrc47QhNII5j1Ot1rKysBG20yJHPnTtnkkBbMmnePJDsE0AnEyXm4uJiAhwU6Np6auMBXXuRDUkpjTVByYesNjY2goak8/PzQUhOJaBvxa05+5rlx/+nNKF0ZkgV6DmxBgcHEzYp0HOOdjodk9gKe6XgFpwrfQ10VGlbNPpl2MxTMyg5b9q7CrqhoU2vjSlo6tve9jYAPR/Mvn37DO+f956ZmTHNTEFZfF8HlYB8PjpOy+WytZGjFG80GnbGPOTX2NiYrQMdsblcLkBO1oxX7gv3QDtVcd7f+c53bB6HDx9OzHFra8v8CbynarrUeC5fvpwAydV5jI6OmsZwNdoRTADo4f950A8FryCps5CZblS9Zmdn7YD4Pnjai5ALoyWiml5JNVD70wPdw+YdYNrKTItoPOqxetmpMmtzFQ8WocU3ZGQ8pHpPHvCzZ88a4+N8+UIvLCzYYVRkZmUSQJcJ8KXjgeIzTU5OGmNgbP22226zaABJHaweFl2ZkSL78lmp+qsJQCbKF+7ixYum3pNZzM7O2jP7vSsUColCI6CbSUe8QWYRPv7442b+cSxlgGTAimHJl43Pwj3ftWuX3ZNrdejQocAU2r17tzkt2WaNDLzdbifyMfgsPLtq3nFc7jeF1+nTpxPZrmmUmQMZZXSL047QBFiKW6lUEmi6QE86z8zMGAfUQg5KQxb8nD9/3qQhVSiNA3s02ZGRkeBec3Nz9ltKKAUX0dwFzlXNFj4TObXvQKz3IqnK73O9C4WCaQAKCMLPtDBF88n5zEBXMvkClYWFhaBZqoZHuVZU76vVqqm4nOvExIRJaEp4rtnly5dt3fi8in6rsX5qa9/97ndtXH5HIBCOX61WgxqQsbExmwedaHyOCxcuWIiShUxazs0y41arZeo3QUh0LajRcf6lUiloqcY11sIgzqdWq9lZ4HprpiPn8dGPfhQA8Hu/93sJBynXlloQx2q1WjaewsQBXU0t6zuQUUYZXZN2hCbQ19eHqakplEqlIFmDUkUhuVQy0VlEO/bAgQNBeafam5SQ2urZ21ONRsM4Ouehjj/afeosVCcXkGzB7SG/SqVS0HZL/SEK3cUxKZEoETS8R/tZQUU4Dybf1Ot180NwjNnZWXsGTc7ySUXaDUr7B3D+lHS+c9KePXsCUJZdu3YlOhQBXY3AhzQVXJT7SN+D2vhcI/XBMOTH7xSijJ9Vq1VbN+7x8PCwSV4tlebacj04t1arZRKXa6sgOPSlMBSppe88L4cOHbIz+dRTTwEAPvzhDwMAfvzHfxxPP/20rQOQBIzlvQcGBuzsajNYIGyom0aZJpBRRrc47QhNIJfLoVgsolAoWGiGnJ7Sv1KpmESnpGk0GkHq7NLSknFx2nW0B0dGRoI6e21SyjFeffVVHD16FADwrW99C0Cy1bdCQvMz3+2oVquZXauAEJwHJZ9KKA8uwe+0uozz3r179zWrGX11peIV0MbW0BLvOTExYRKP6bSUsHNzc/ac2iWHHmxKIa0J4Fi8/sKFCyY1+Vmz2bR5ev9Ju902aUZ7/vz586YVMDmq2WwGfQfUr8M58hqFLaemU6vV7F5apwB0NVH6CxTrgD4SnkkFfeX4nKt2jdJUXib6UAumhlIoFGy9GZmI49jGVUwHRkS4ptRWoii6blPSHcEE2u02lpaWUC6XzdHDMB9VKt00hnH0ey0H5iFnFiE3Jp/PB2AlxWLRFlhVKn7PF5ibPDMzY/PQg0X1TsNlvhcBSbHj+MIMDg7a4eJh44t5+vRpO4x8OdSBx0yzZ5991kJDVBVVXSbRBCmVSokMOo5PBkIcRqr7ynS5HqquexTmubk5Y8iKjKxt4TgW78m90JfQl982Gg1bD67VwMCAzZf313JwOmzJ6LURjWIXUu3mS6Sl0GSYamppizYg6UD2juHR0dEgrPvyyy8HLcy4jvV63ZgciUJSqb+/337L63ldoVAIzC9PmTmQUUa3OO0ITWBrawsXLlzA2bNnTaKqI4REKUSJubm5aZyPkmNtbS1on011r7+/3zi3qo68F7n5yZMn7bfk0tqZRhtMclxKAAXY0KaTvI7/TynP7wqFgj0rzYi0HgJpFXokxdmjCcG1yuVyCdw+oKsu8/nULKCko/pNNX/v3r0mqdWhyflynbkGhw4dStRc8DkpxYkxeOTIEZPiHtDkwoULQYhLnbmUqMeOHbPQMLVDSsBLly7Z2dGQqF+/NHx+RfvlflJLuP3224PyaYbvFhcXTeOhxraxsWHPzj1tNptBqTk1gWazaWvEc64dnGimDQ8PJ2pKgJ4zcn193UyFq1GmCWSU0S1OO0ITyOVyKJVKOHDggNnZarcCXUlMLkoOuLS0ZJJJU24pifhbSotGo2G2Kbl6pVIxaUiJd+DAAePslC5aGUcpTonZ6XTst7zXmTNnbL6+T12j0TDJSIrjOHCYKVyW1ilwzXgdx9rc3LT1oBTivBRGjVrN1NSU2bwKfEpHFR2r/G5mZiaxbrxeazmAXtru9vZ24C9ot9s2Lu997Ngx8ztQ8nL977nnnqC7z8rKiq0zazxuv/12C6cx/ZZ+i127dgW1JZouTs2hWCxaqFkrOLnGvD+1puPHj5uWwjOhfSdYDUj/0uTkpK0910Uh3ujrYprx1NSUjct9VQeyQrB56DO+RwsLC9dNFtoRTKCvrw+VSgXnz5+3CfPl48EdHx8PILanpqbsReDhzOVy9j3Vb6pZ6mTiBmk9ATe5XC4HyLlp0QSqfhsbGwGs9MTEhHmnfQlvrVaz8TXrzzef4DWbm5uBI4xzBZJmg28wqkzAF69oF16q4/fcc49lX/Ilofq7trYWFFRpE1kyYj7vpUuX7Pl4sFutlq23z/XnWupY4+Pj9ls6QDudjpkefM7nnnvOHMK+diSfz9vac/zx8XF7Br74hw8fNocaBQPXu1gs2hnjfEdHR+0znieetXq9bueDdP78eTt/NHvy+bztH88tGdvExITtJ/dgbGwsYEYKBMPn04Y7Nw1tOKOMMvrPg3aEJhBFkfVup1ShFFQ0XnI0SpetrS1TibR9tqLYAkmoLUoYrT+gaql95DkuOTulSqvVSiAK61yBnoq2ubkZqPA6L9/kolgs2nh0tGnrc86DYwwNDZkKrdxf21opnT9/3p5TsxU9nuDJkyft+bh+/P9CoWASL63xBedLSVwoFIK4+8TERIDHuLy8bPfgHGnitFotMzOo4p48edLWgdrB7OysPbt33K6urtq4pFarZVKZTreZmRmrkqSzjhrH+vp6IgOR31FjpfZE06JWqwUZlIcOHbK1Ykh0dXXVNEY697T6VRuiAt2949poeNdXpZKazeZ18wQyTSCjjG5x2hGaAIFGFxYWjOMp1j3Q5dzk/uSco6OjZkfTTlP4Kk0MAbqag8emV+AJSreNjQ2TBD6812w2Tarxs6GhIeP2Wlfg88R5/erqalBXUK/XA+1AE6U4T9qS2j5dnYXeKaaViRyfmoB2TtLqNkoOfse1nZ+fD3w1ly5dsrl5cFOtrtTOQpS8io2vCV1AT+OZm5tLZD0C3X3ldazFV/g53lM7//h6khMnTlgYjet355132r24Lw8++CCArkZKTYTrXqvVgm5UmoXoszcLhYI5XQkgUigUgpZxPLdRFAVh7vHxcVt7noW5uTm7LzUqBRK5Xv3AjmAC29vbaDQaGB8ft5fI93EjGjHQW9R6vW4MgWpWWlolD8zGxobFz/mi6aHn+NoERTcE6DIKmihaaMN5ckOHhoYS8NOcG9A9KL51V7lctpfUdwMeHx+3jDe+OAppzt9NTk6aSskx6K3Wxiukcrls68B/NYrgkZHuuusuO9icz9TUVKL7L4BEhhpNN857fX3dmBu94SsrK7ZXHJ/rvbS0ZGeB61mpVMzk4HNq4RNfeK6x9pskg5idnQ06BKsDjWvLtmJRFNn3ChxD040vGtdlfHzczglfbsVv5JqVSqUELiWQzN4kI9ZSZV9kpSYZr1enoW8F5ykzBzLK6BanHaMJ1Go1HDx40DKkfClns9lMlOLyM6phVOlU2lH6UFtQRxUpl8uZapYG0sG/iQPXaDRMm1AJwvtTHTt79qyhyJJzU50slUp2Lzratre3LaTkgTimp6cT5bz8jpKMnH5tbc1+69uFRVGUKJnlGNQcGPrTFmw+E3B9fT2AI1tdXQ2ALFSl5n5oXgTnqxBilK4MyfH6tbW1IBavTlE6THO5XKKHA+cGdKUysx8JWqIhQg3lKSAK0Nt3bUjK5yuVSon2dEDSgec7OJ8/f97mzVyJQ4cOmRbJ9VONl3uspiq/51zHxsaC4imaCs1m09b0apRpAhlldIvTjtAECPuluf3kqJRkExMTAajo1NSU2X30kdKtAAAgAElEQVSUzhpWIVE6r66uGsdURFqP/KuVggTlUFx+n9E3Pj6e2keemgAlkpbVUkLS/tvY2DCJSumimgOlhPah96jHAwMD9iw+GUkdg1zjixcvWiaftsdm0g3XlJrAgQMHbF+4F/V63aSO7/ewe/fuBDIv5+Fz6guFgpV7KxQcn0MTxoCuBkHpzXFbrZZpFr4k99FHH7WEI12rtP4OnAfvr+Cm3NtHHnnEnpNSnmvKxKN8Ph90BZqeng7AWzudjp0B+rq477t378aRI0cA9HwNp06dMueswrlxjzh/ntGVlZUb1wSiKPqPURRdjqLomHw2HkXR/xNF0ckr/45d+TyKouh/j6LolSiKvhtF0YPXGz+jjDL6p6UfRBP4UwD/B4BPy2e/AeDv4zj+3SiKfuPK//86gA8CuPPKf28B8IdX/v2B6NSpUyaRKL35L9Dj8JqAQo5KCVIqlYwLar06x/IY7JVKxexPfkeQEyDEsG+320GjyWazmUjsAZLefkokcuSTJ08m+gcAXSmgYBVAz65fWloy7s9rLly4YFKeWsX6+vpV7WIFWeV3k5OT9uzUMNbX101Cp9VIkCihVldXbX0pmTh+tVoN9qLZbCYkOq+jp5vSkxrErl27Uqsleb1WY37gAx8AAGv6SalYq9Xw1a9+NbG2URTZfnNfNjc3TfvhvLVOn7996aWXAHQThFTLBHpgoZcvXzZNg9rk1NSUSXT6sqIoSvSoBHoa0tzcnK2RgucytZmaQ6VSMS2Fe6BYEDfcdyCO469HUXTAffwogPdc+ftTAB5Hlwk8CuDTcXe1noqiqBJF0Wwcx9dskB5FkSGgUD3loVG8eh5izZrjImmBCjeQqpwyEo8nv3fvXnMacdO0EIf3186uDz/8MICek+7ll1+2TdCeCHw5fVae5rLrfHz2I1/Q5eVlOwTEzxseHg7Ce6qe8pk1a5GfkdFOT0/bGtEBVS6XE63LgN6BHRkZsTXiwVpYWEiELTku562hPqB7cL25NjY2ZvekuUF1v1arBY1ANWuO9PDDD+Od73yn3RfoOd/OnTuXQAgicU/JtC5evGgvFpkQGeDp06ft/HFuFy5cMIcw76lgJFw/fjc8PGwvMPMPWq1WooMwkDwnDzzwQGI+nU4H9913n/0W6J5z7iP3hWdvZWXFnM9Xo9frGJyWF3sO+H/bu/rguKrr/rvaT0tafa1W0soWsvEnGMZF2IGEDhBIQyAfHQjThGSmpEkmKZNM0uaPECYzZPpHZkrpkNJpp5Rp+jnBaQifgTJ8lcSObRxsl/oD49qKgiRbWq20K63WknYl7esfb39nz3tPsg1E8rZ6Z8aj9du395177n3n/M65956D9vLn1QAG1H2D5WseMsZ8xRhzwBhz4Hylk33yyaelo/cdGLQsyzLGnLvi4cK/exR2KXNs3LjRikajaGho8CT9oDZftWqVJ73T1NSUJ0gyODgo2txd1YaBN03d3d2ewN3U1JR8JryjK6L3+JO31atXy9ImictrgBNhkGgleE0rQp3rELDRgvuIcCaTEd5oJXRyE/KvLTytoN5sRaum8wO6z2joWgaEqnqfPhEM/zIwqHdjUvbNzc2e3Yy6xBx/y2CjPhrOOdHZ2SkWlXkQL7/8ctnYQ7l94AN2cex0Oi1tMAhYLBY9tR+OHDkictbzCbARo9u91EFljpleliaCIdIEKpCf42JZlqdCFeW/YcMG+e6Xv/wlADiK9nIsWltbPbsldV0IN/Jy03tFAiljTBIAyn+5WHoaQJe6b035mk8++VSl9F6RwLMA7gbw5+W/z6jrXzfG/Bh2QHDifPEAwLYgkUgEdXV1Yl1pCUjpdNpxfp/3uIs+anSgl4MA58YTWqlkMilWXCMCWlk3EhgfH8exY8ccvA0ODgoftDj9/f2SsZhWhQGiUqkkPBH5sCArULH21O5nz54VfmnNP/nJT+LIkSMAKnGITCYjQS5uSiE/uVxOTtyxn9lsVqwJkYBuj2iGlm9kZERQBK3o1NSUJ2UW0Y1eumIMJJFIeE68JZNJTwUd9lPXkaCVbmlpwfbt2wFUTu/t27dPrCBrDO7duxeAHTOhNeTmn/7+fhkz8t/V1eU57/HhD38YgD2GXGZk//QZE/aFbc3OzjryWAD2HOK40JqXSiVBEyTKatWqVZ7cEpOTk4IUuHV67dq1Mj/1VmLAWeh2MTqvEjDG7IQdBGw1xgwC+B7sl/8nxpgvAXgHwB+Ub/8PALcBOAVgCsAfna/98jMQiUTQ29vrySzLgB9QgUu6JBehvs6x5g4I6h1WnIB8IZqamjwvQktLiwwWX8Tdu3cLX8xi/PzzzwsfhKWcePF4XF4Ud+ad2traBXefsQ/sJ+/p6OhwZDbiX74o+hwCo8/ugN/c3JzjHAFQUTb6mk5WwsM5jLI3NjY6SofxOypufZAJsGEwX2C+3KdOnXIcqNHP0fLQmYA5VmxraGhIDkqxrampKeGTSp3QX2enJunszu7zEHyu/i6Xy0mAlHzoY9uUH69FIhEHv5QLx+CWW24B4Nzb785xGIlEPEexL730Ulmd4H6O0dFRkRuvUd779+8XPhajC1kduGuRr25e4F4LwNfO16ZPPvlUPVQVOwbn5+eRy+WwZcsWsfKE/oSApVJJtBshJgNAQKXGwNjYmARkDhw4AACyc+/QoUNyiutDH/oQAFuD06rRUjc1NYlGZRuEh21tbeIO6Fz61PC6Tr17mZMoR+er0yXY+T1lQL4BeBJPpFIp+Z6WLxQKiZtB66JP9tFaEOYPDw87kpqwDQbDCJ3ZxvHjxyXIpZcFaQWJXHQ/6LLQpdi2bZugGaK4TZs2iRV2j3soFMIvfvELAMA119hbTkqlkmcMZmZmxN1iW0SCJ0+eFH7ZN73DkPwnk0kZR1plooW+vj5Pll9jjPSV40O08NZbb8lSHs8rTExMyPxjG6tXr/ackmSfOjs7HZ8Be48Cn8mxrq+vx9VXXw2ggtB4ZHnt2rWeIjVu8s8O+OTTCqeqQAKzs7NIpVKYnZ0VbUjtr5dq6KdRw09OTkrMgHu2dXlpWm8GVdrb20UDEzkcOnRIrLH252g1aV1obXWJamrp7u5uj18cDoelDfre1M5aM9PijI+PSxCSlppW68SJE2JhGPg5fvy49JOWLBgMiiUgj7y/q6vLs4mKWZ6BCsLQyU10EVH2k74prbn2R2mZKIv5+XmJrXBc33jjDdx+++0O3vL5vMiNfSFZliVW8K233gJg+7scqz179giPDNzRspKP8fFxQRFEjx0dHZ6g8pEjRzxJOSmfrVu3yi48Wvje3l5BHTyJqpdhiYz0OQfOSfY3GAwKv24kmEwmBYVxDtfV1Qm/5H9qakrmFuXHJctAIODnE/DJJ5/OTVWBBObn5zExMYGxsTGJ1NMa6gKOtJo6/bc7st/d3S0pm7mMxE0j7e3t4kdT4+/evduRQhqwl7EYd6A1Jh+6/LfeCktiW83NzfKZ2lmf8KOlpqZPJBJiTYgUuN0zn8+Lj0z+LcsSP1RnzXHnYWCEvK6uTs5Z0ILoSj6UnzHGkR4MsNN5A/aKCi079+dns1lPpiWilmw2KzJlW1dccQVeeOEFAJWofTAYlD4wdsD/DwwMyOoHUd8777wjc0EvB9Ofd9c/XL9+vciUiGB4eFisONHNhg0bHGnQ+HzKj+OuT5HSx+eZA/Lf3t4u8RCuWmQyGUGiRFujo6OO8ueA8wQtY1OUwZkzZ2QMdH4IIhBafcovFostWFlJU1UogVKphFwuh0KhIAxzwurEDLrYI2ALlQIhNB4ZGcE999wDoHLkk0LO5XJSZXjnzp0A7JeEAuPfRCLhWC7U/MTjcU8evEKhIM8gj2fOnJFJTqXE9nV1Wk7Uq666Sl5OLpkRMpZKJVF2hLjRaFQUJSHmzMyMpygo5ZPL5URp8f5EIiHy1TUDCNPpIuhDUVRG7Hs2mxX3jFCbL8b27ds9k/PMmTMiK65z6wIwlIfep6+Lx5BvdyGV/v5+uc/dp2AwKGcu+BI2NzeLrNjG9PS0KHTu8bjhhhsAALt27ZIXXR/J5nKd+5n6oBTHMxKJSN/1kqw7pyP7vnPnTnz9618HUFGshw8f9uSKZFIeoGLIOE5tbW0OI7UQ+e6ATz6tcKoKJMAkG7Ozsw7IB8CRY92dl/+yyy5zLLEBwDe+8Q2xRAwu7tu3D4Btqdgu75mbmxOLS40ZiURw9KidPsENO1tbWyUIw2upVMpTIu2ee+4ReP/ss88CqGzgmJ6eFsuhM+7S9eDyF62nXvrj33w+77Hs8XjcUVgUqLgzc3Nzgpa0Faf8KBfAm1yVgarx8XFPEpJ8Pi/Pp+vBIKpenmKbNTU1Hjcmk8nI5h93XQgA+NWvfgWggvaGhoZEDrSQl1xyiaAl/iX0f/PNN+W37EsgEPCMwcTEhIzZk08+6WgjEol43LSuri4J+uodlLyfaJK/C4VCEiRkEPjUqVMyZrruBWAvT7NdurZvvvmmIEadDo/zj4iV3+nit4uRjwR88mmFU1UggWAwiHg8jq1bt0pQipqNGn9yclKsMq3QyMiIbJL49re/DcDW8J/5zGcAONM08zluizM3Nyeamks/xhixZvwtNXc+nxdrqJez3Pnqr776arHUDBZpK0eLQT/WGCP30YfUNQxpHXRxUFokWqNYLCYWgLxxWautrU1kSUQSi8UEBZHXyclJWdpy57LP5XKyJMc2dLFUWi1daJSyovXXuRf4u/r6ekFebJfBPWOMWEEG6bT8dPFOWnH+lgVKu7u7PWhvbGxM0AnlFw6HBZ3ce++9ACoboJ5++mlHbQb+5bjQ/+ez8/m8Z8NRbW0t7rrrLnkWYKNUokf3KddgMCjjqXMqcDmcSPTkyZPCN/un60gSDS5GVaEEampqEI1G8cYbb8gEIqQjbI9GoxJA4cQaGxuTDDeM5v/gBz9YMODD31GoHASduOHWW28FYB/b5IoCJw8nW6FQcOTVB2wXgELngZaOjg6ZhO5CqrW1tdLPG2+8EYD9AvFFcNdLaG5uls+cMIVCQfpCRZLP5+Vl48SmMtBHfrneroOtnDylUslRgwCoBOT0pOTfQqEg7hllwL86SxH7FI/H4c4f0dzcLArYXaJsfn5eFDLhtYbmVL4jIyOe8xI8z3H69GlRcjQyiURCxlHnV6SS+/nPf+545qWXXir9ZN8bGxtlPHSlZwC47rrrPAfTrr/+evnt/fffD8AZGHSX4BsfHxc3jX3asmWLJ/mMno90JekyxOPxRUvTkXx3wCefVjhVBRJgGTKtnWmZdO45wkjCoc2bN4vl0AUyaXm5z11Df2pbBpS2bdsmVpNJKR566CGBV7RkhJpcNgMquwlzuZxoaqa46urqwoMPPujgjb9NJpOCcBhMO3HihGh4Bo8IrzOZjKfCzPj4uGcPfl1dnVgayk3Lh33Sy1juak1XXHGFJ7OxLjRK90i3y89cDycq05l0iQ6CwaDH3ZicnBRZuoN14XDYkUSGfSO/Or++O0h86NAhADY64/0cz2w2KwhAn350jwHdx9HRUVlm1Om/iMI4byn3vXv3OlwPwEYmdPVo7XUaOvdpv1WrVjnqRgB2EJq/5ZKs3iWrS92xbz4S8Mknn85JVYEEQqGQZNvlhgy3P9re3i4am/762bNn8dxzzwGABAg//elPix9FS0ntPjg4KBpTW/rHH38cQMVS79ixQwJq+rw/YPtc1PCMPXR2dop2/uhHPwoAOHjwoCAL91nzrq4uQRa0Kj/72c/k3DwDhEQQExMTEpjUqbvYP1rqSCQi13RWXcqAuw2JpPQSHpeWUqmUpzgox2J+fl4spO6TTtoCVIKpl1xyiaeWQjqdFp50kVfyTZTAcZqYmJA4B1FQsVgUudGKJpNJGWc+n7Ge+vp6aYOWOxaLyTUtR/JLudCvz2Qy8h0DpXV1dfI95UJ+Ojo6xIpzdyVRCFBBMMViUTaVcY7xdz09PRJjoq8/OTkp3xP5pFIp6RfnCWW7Zs0aSbKyGFWFEggGg+jo6MDU1JQjazBQeXEKhYIcbaWge3t7ZeAfeOABAPZOLyoLtsHJ397eLi8Hd/EdO3ZMdtVxkH/961/LQHPg+EJ2dXWJYuLLms/n8fDDDwOoBDIfeeQReZZ2VQB7wvDFIaTTKw1sX+cJJMTmpAAqk4Uv69jYmCfyzsi6DuoR4s7MzEjkmDLo6OiQXXAMhFHemUxGeNPZjMg7eaSSLBaLjuw3QCXKDVQUz9zcnMhDF2ihzBgA09mjqEj48g0NDXmKmerCIO6027pIKdsvFovyG/dxZL2KRBn39fXJC05XhfNR75/gnD569Ki0f/PNN3tkyi3CHJNt27bJM7lXolAoeIxKS0uLuCpUnmxzYGAAd999N85Fvjvgk08rnKoCCXDvcz6fF5hEK8eg3fj4uFgHasr29naxHLRaY2Njsn6uk2EAtsZkewcPHgRgwydaK1q8YDAo1oGWhs8uFouCGAj977jjDtHir7zyCgDgpZdeEouh97wDdt46fSQYcBZSIXIhkhkYGBCtz7/RaFSWrxgAra2t9RzmYbqzpqYmCYbyntOnT8syGvu3f/9+sTTuQJhlWeKuUd41NTXCJ2VAJHHNNdc4AneAvQeCqIPPmZyc9CAYvU/fXfI8nU7LkiKDe1u3bpXP/MugZCwW8xR0LZVKghiJUo4dOyZr7xx3IhS9p4IuWSKR8GQnpixSqZQjNR77wu/p+r3zzjvCGxHdnXfeCcCeN0xhx/mqXRaNHtmuOzWdRl6LkY8EfPJphVPVIIFcLodgMCi+mHv/ekNDg2c5a3Z2VnxwooNwOCzaTy+nAc7KP9T+Ok0Xnz00NCRBIy5dcSmvp6cHX/3qVwFULHY2m8XLL78MAHjsscfk2e7TXrQW27dvxxNPPAGgsqutpaVF+kBLTcvd2dkp1o1xiNbWVrGe5LWlpUXk5c68GwqFPFlt4/G4oCbt0+qTipQp22S7bEsXu2Qwldb0N7/5jSyP8Tsd09A7KInGiNQYV4jFYmLd9FKXu2zZ0aNHpT3yxj7p5VS9i4/Ij9a8p6fHkQwWqJypKBaLMq/0BqWPfOQjIhugMhYTExMOJMdr7CcDeDrRjfs4cqFQkMAjZaCzUhMRtLa2eqpLEVWOjY0JH4uRjwR88mmFU1UgAS531dfXi/9Ha6/9R/pitLCRSERO9PG+s2fPelJg0S+1LEu+0wVBqe1piZuamjxVi1h/8Fvf+pY8nzkJnnrqKfGfdYFPWmpaDvqx8XhcNDWRzMzMjKAf+p7sW1dXl/iXRAmNjY3SBq3W5OSk5zw5729ubnZsdAJsq+hOaJHJZBwp3YGKD6wTglIGuhYhZUQ5xmIxsW7s59DQkKcAp66q4y5NnkgkxLrqhK3kg6ijVCp5xkwXiWVcw53qHaggnXQ6LQhDLyWSR64mcI5mMhn57euvvw6ggnSmp6dlLhBB5PN5scqM9sfjcYk/8Ltdu3YBsOMSRACUt05vx3Exxsi8pvzIlzFG+rwYVYUSYBXgiYkJmQyENZwo2WzWsaQE2ILhxODe/nA4LALQyUT4f16jktE149luIBCQAbzuuusA2GcSyNcdd9whzwLsyeBOKpJIJAQqE74RmudyOQnY6X35nIB6DZm/1+cO9HdARdnNzMxIsIjXOHEjkYi4QHwh5ufnxR0gTI7H4zLJeU0XyuBzddFS8sTgFRXW7Oys3M+/TU1NnjX+lpYWeRHcbmCxWHQcu3W3y3miITFfXPZjeHhYxpsv5NTUlLh4OgEHf+uuTtzc3CzuiM7jR3jPl5+KKBwOO/Y18JkcA0J+fUSeyo4GbWZmxnMwTb/UVFR62ZD380xNOBxesoKkPvnk0/8TqgokwLMDWhMT0hHm1NfXi6anZZqennYEygDbutC6EoISQWjYxCWu3t5e2fNODdvd3S3XvvnNbwKoWJwvf/nLwhuRgy6QSURQU1MjloOanhZy3759gk70qUD2jxaY3wUCAbFgtCQzMzMCEfXSpi7fralQKIiMuCzZ1tYmsmSQU5fudsPrmZkZz32NjY1i8XSJdMC2xPwtkUNDQ4PcpwOhtMZEApwHAwMDImdayi1btsiyKMdlamrKgZwAp8Xms4ha5ufnBVbrjWF6kxIABzLlNY003GcpiLw2bdokfSI/+XxePnN8ZmZmJBjKseXvLMtynHYF7HHUeTd5je1xjPle6ApHi9F5kYAx5h+NMSPGmKPq2oPGmLeNMYeNMU8ZY5rUd/cZY04ZY04YY245X/s++eTTxaULQQL/DOBvAPyruvYygPssy5ozxjwA4D4A9xpjLgfwWQBbAXQCeMUYs8myrHmcg+bm5jA2NubIJ09tR82dSCTEMjHYlc1mZQssz+KvWbNGfCBqZVrH1atXe07erVu3TqwJLevIyIgEnFiB6NVXXwVgLzcRYTAO0d3dLZaGlmxqakp8Oyar5JLfgw8+KP1kMO348eOi7XXtArZJzU6rPzw87Knbp8+360pIlAE/c6vr8PCwBCvpb2/dulUq5ugzA4ATXeg0cDpJCVDxxbdt2yZ+K2nXrl2SxJPLhmNjY45aEkBlPJPJpCwXEp1dc801krKNMk2n0470bYAzo6/OQcE+uZN4WJbl2HNPGfH/RCKU8caNGz1byMl/KpWSualrERLVcHwKhYJcY3yBbeoCqdxeHolEBLHqOhy6boRuv6GhQWS0GF1ILcJdxpi1rmsvqf++DuDO8uffB/Bjy7IKAPqMMacAfADAvnM9g0ogkUgIdKEgdEpxdkwfySXU5wvT19cnLyKFz6BTJpORF0Hv5uNLzWj8lVdeiZtuuglABaJ98YtfBGArAb4wOtMxFRMnUSwWw8c//nEAlQn12muvAbAPCxHOcvK3tLR4in3ypQqFQp5IczgcdmRdAuxJwQnCF5Ev0OjoqMhBH612F7xIpVIic/JNFycWi4ly1KnhuTrgLuIajUYF/lLGPT098sJQiWUyGRkPfQAHsMeJLwLHNZVKCYTWR2z5LD6fsm1qanJUZwbsl8+tuCORiKfwCovUnDx5UuTNNvr7+2U83Bl9amtrZTw5l40xcj/bCAQCnuPLuhiJLh4D2POPPBL6j4yMODIgAxUFkU6nPYrYTb+NwOAXAbxQ/rwawID6brB8zUPGmK8YYw4YYw7QT/fJJ5+Wn95XYNAY810AcwB+9G5/a1nWowAeBYC2tjYrlUrh9OnTYtF1cASAo0QZtW5ra6tco1afnp6W4B+thLaebJ+/y+Vyck2XpXrmmWfkuUBFS3d0dIjFoabfvHkzPve5zwGoBByj0ahYaO4n4NFiY4xobBaoOHPmjFgud+nuaDQqlpeIoKOjQywI7ysWi54S4/wbDAblPr1XgmiJlikYDDp2U2q5GGPEUpOGh4cFTbiP8gaDQXEtSP39/Y4y8pQt0Y87Fdvg4KBYYyKC559/3rFXBLCtJqE+Zct+zs3NCdLQJznd9SOKxaLwTujPVGyXXXaZjDvnwvr168Vq032hrAB4Ar3aHeB3+XzeczJT/57fUVYTExPizhElRCIR4W2h4qNLtk/AGPMFAJ8AcLPFkQNOA+hSt60pX/PJJ5+qlN6TEjDGfAzAtwHcYFmWxvLPAnjMGPMQ7MDgRgC/Ol97tbW12LFjB0ZGRsRaUmPSIugTW7QauVxONCo18N69e+UaNSB/F41GRaPyWjKZFItBS9LT0yNWgifiGGwcGhoS/5bPOXr0qGwWYSDpyJEjsu+b1pNByXXr1omlIZqYm5uT9vSGI8AO7tAXpxWdnJx07BgDbL9RFzgFnIlGyRufwz4CzsKo9Mdp4RmwCgQCcvqNbXV0dAhi4M5LvXGKstKJOClvfhcKhUS+lCN5vPbaa6V9yrOrq0v6TmsYi8U8tR94TyQScWRH5ne0mpxrk5OTnkS0jBcAldOanEN79uyRuIn7tOTIyIiMC5+jz1lQfvF43JMVm/M7HA7LnGEbnZ2d8nzOoTVr1kgfyAfHzB38XIjOqwSMMTsB3Aig1RgzCOB7sFcDIgBeLnfgdcuy/tiyrGPGmJ8AeAu2m/C1860MAPYEjEQi2L17t8Bdd1mnsbExx5ZcwIa6FAiDTY2NjbJbipOCkLivr2/BdvkCUGB79uyRAXOng66vrxdlwaDk6dOnJcORLvnEra18Jt0Sy7IEcutdbYT8DAK9+OKLAOxAJV8STlLLsuQlJq/Nzc0Ce/kiE46Hw2F5Keg6tbW1yWQkj6VSSSYl3Rm9H4H3M9o+MDCwYFZiwLmtlt9t2rTJsyu0s7PTc+yWbtLg4KBMcF1mzJ3OO5vNOsrIaT70YSEqoFAoJO2xf83NzfIS6+g6YM9RvqR8wSzLkn7pDFj8PceWz9T1I/nMUqkkv6FrQ4UZCoWkXY5FQ0ODzGvO87ffflvkzPvoMkSjUYeLshBdyOrAXQtc/uE57v8+gO+fr12ffPKpOqgqdgwaYxAKhVAsFsUKUtPTCqTTadHOhKTZbFa0KC1fb2+vaFnmkKdFmJ+fFzhIVFFTU+NZctEHiKh1dfCGEJvt1tXVCbTVmXp5DFnv1QdsbU0YS7dE5wdku0zS0dra6kmosnnzZpEN4aM+oOJO0tHX1yeWjxY4FouJPIhg5ubmHHn1gYolq62tlb7TarW1tYmrwurFlN327duFHx1M5TN7enqER90HyhSwx5XXaImnp6dFHno5kO1StuS7oaFB+KCLMzs768lwbIyROeAufqt3GOoj3OTJnd05EAh4YP769etlzV73hbJx7/sYHx+X9jgPGxsbZSmbeSr1/hqOmW6Dh9sWI//sgE8+rXCqCiRgWZachKK/5d4LvWHDBtG29PkOHz4sS1w62ESrTZ+JlqS/v1+srU5oQavGZ05NTS2arqm+vl78RGrp4eFhQRbkY+vWrYIO3DXpOzs7xeelZRgcHBTrp5el2L47yBQKhRylvQHnZiH3Sa5IP3MAAAbxSURBVMSNGzeK5dOnJt2JPXfs2CGWhhaKsgqFQp6NTPl8XsaFQT3KeHh4WHgjChkdHRU58/itZVmeAqO0bK2trbIzkzJobW11BFQ5LrpCke6nLp+uk7jq046AbZUpLyI6vcffnRQ2EAh45KerA/E+fbaDsSvKY2JiQvqlE7qSeB/nVSAQkGzbRFzpdFp2U3JOkteWlhY/qYhPPvl0bqoaJDA3N4fGxkaxlrSstGjainM/v94OydNtiURCcrTT2uokFrSUeqsoz/nzd5FIRPw/9+aiQCAglo8ads2aNRKbIN99fX2euoD0nWtqasRK6Q1KtPK0JrS2o6OjjqU+wNb+fD4tR01NjfSPfSZq6uvrEz9Ry50y5DJcPp+XzTCMz9BCDQ0NCR/sZ1NTk6ckOH3zhoYGaZcyq62tlXHkmOmU4O6kGHpzDK14IBCQGAaR4PDwsCfFPH3hG264QWSraweSNyKHmZkZ6RctKvlJJpPCh97eTSuuk5sAkBiXfmY4HBYUyXHSqdA5x3QCVt5HmWazWUk6QhldeeWVgpa4WY1zrre397yrA6ayz+fi0dq1a637778fZ8+edRyPBCpQNx6PewplhkIheQEI37LZrPyWk4Jt1tbWCmwjdJyfnxeBcYlJF7fgIHNyzM7OSvs6m627fFZNTY38xh0EDIVC8oLpdWU+072er8to6fJS7gIjkUhEJgEnMQOJwWBQJpdO6kFFwyXLQCAgv3Uv+TU1NTny9gHOI97u48vpdNpzzFgnJqFcdBktKl9djJXPJF86oEkedYk5yoAKMxQKyQtPPs6ePSt86KO5fGEpI304i4ZDH/Ry88uxiMViIg/Cdr1TlM8uFAqe5T1dNNW9BKn3Q5DvVColc4b80shEo1Hh7aabbjpoWdZ2uMh3B3zyaYVTVSABY0wawFkAoxebFwCt8PnQ5PPhpP/LfHRblpVwX6wKJQAAxpgDC0EVnw+fD5+PpeXDdwd88mmFk68EfPJphVM1KYFHLzYDZfL5cJLPh5P+3/FRNTEBn3zy6eJQNSEBn3zy6SKQrwR88mmFU1UoAWPMx8p1Ck4ZY76zTM/sMsa8Zox5yxhzzBjzzfL1FmPMy8aYk+W/507V+tvjJ2CM+S9jzHPl/68zxuwvy+TfjTHhZeChyRjz03JNiePGmA9eDHkYY/60PCZHjTE7jTHR5ZLHInU2FpSBsemvyzwdNsb0LDEfS1Pvg/X5LtY/AAEAvQAuBRAG8N8ALl+G5yYB9JQ/xwD8D4DLAfwFgO+Ur38HwAPLJIdvAXgMwHPl//8EwGfLnx8BcM8y8PAvAL5c/hwG0LTc8oCdnboPwColhy8slzwAXA+gB8BRdW1BGQC4DXambQPgWgD7l5iPjwIIlj8/oPi4vPzeRACsK79PgQt+1lJPrAvo7AcBvKj+fx/swibLzcczAH4PwAkAyfK1JIATy/DsNQBeBXATgOfKk2pUDbhDRkvEQ2P55TOu68sqD1TS1rfAPuD2HIBbllMeANa6Xr4FZQDg7wHctdB9S8GH67vbAfyo/NnxzgB4EcAHL/Q51eAOXHCtgqWicnGVqwDsB9BuWRYL8g0DaF8GFv4KduLWUvn/cQDjlmXxIPhyyGQdgDSAfyq7Jf9gjKnDMsvDsqzTAP4SQD+AIQATAA5i+eWhaTEZXMy5+57qfSxE1aAELioZY+oBPAHgTyzLyunvLFutLukaqjHmEwBGLMs6uJTPuQAKwoaff2dZ1lWwz3I44jPLJI9m2JWs1sHOWF0H4GNL+cx3Q8shg/PR+6n3sRBVgxK4aLUKjDEh2ArgR5ZlPVm+nDLGJMvfJwGMLDEb1wH4lDHmNwB+DNsleBhAkzGG+R6WQyaDAAYty9pf/v9PYSuF5ZbHRwD0WZaVtixrFsCTsGW03PLQtJgMln3uqnofny8rpPfNRzUogTcAbCxHf8OwC5o+u9QPNfbB7x8COG5Z1kPqq2cB3F3+fDfsWMGSkWVZ91mWtcayrLWw+/6flmV9HsBrqNR4XA4+hgEMGGM2ly/dDDt1/LLKA7YbcK0xprY8RuRjWeXhosVk8CyAPyyvElwLYEK5Db91MpV6H5+yvPU+PmuMiRhj1uEC630ILWWQ510EQG6DHZ3vBfDdZXrm78KGdYcBvFn+dxtsf/xVACcBvAKgZRnlcCMqqwOXlgfyFIDHAUSW4fm/A+BAWSZPA2i+GPIA8GcA3gZwFMC/wY56L4s8AOyEHYuYhY2OvrSYDGAHcP+2PG+PANi+xHycgu37c74+ou7/bpmPEwBufTfP8rcN++TTCqdqcAd88smni0i+EvDJpxVOvhLwyacVTr4S8MmnFU6+EvDJpxVOvhLwyacVTr4S8MmnFU7/C1Ryeo3S5SsaAAAAAElFTkSuQmCC\n" 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| }, |
| "metadata": { |
| "tags": [], |
| "needs_background": "light" |
| } |
| } |
| ] |
| } |
| ] |
| } |