luizirber/keras_layer_shapes.ipynb

## keras_layer_shapes.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploring Convolutional Network Shapes with Keras\n",
    "\n",
    "This notebook creates a convolutional neural network for image classification. We use this network to illustrate how steps in a convolutional neural network affect the shape of the data. The convolutional neural network example in this notebook comes from the [keras blog](https://blog.keras.io/building-powerful-image-classification-models-using-very-little-data.html) and covers an example of classifying images of cats and dogs.\n",
    "\n",
    "![cnn image](img/cnns_diagram.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Imports\n",
    "\n",
    "This notebook will set up a simple convolutional neural network and use sample images of cats and dogs. (The hypothetical task would be a classifier that could identify dogs or cats in the object.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "# Use the ImageDataGenerator to apply transformations to images\n",
    "from keras.preprocessing.image import ImageDataGenerator, array_to_img, img_to_array, load_img"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.models import Sequential\n",
    "from keras.layers import Conv2D, MaxPooling2D\n",
    "from keras.layers import Activation, Dropout, Flatten, Dense\n",
    "from keras import backend as K"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from IPython.display import display, Image"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Image Data\n",
    "\n",
    "Let's start by exploring the image data we have. We'll look at a cat photo first:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(280, 300, 3)\n"
     ]
    }
   ],
   "source": [
    "img = load_img('train/data/cat.1.jpg')\n",
    "x = img_to_array(img)\n",
    "print(x.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The dimensionality of the image is $280 \\times 300$, and there are an additional 3 copies of the image (the red, blue, and green channels). When the image is converted to an array, it is a 2D array of values between 0 and 255. Here is the vector value of one particular pixel's three color channels:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([39., 44., 40.], dtype=float32)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x[0][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "255.0\n",
      "0.0\n"
     ]
    }
   ],
   "source": [
    "print(np.max(x))\n",
    "print(np.min(x))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " We can visualize each channel independently by using matplotlib's `imshow()` function to convert the array of numbers into an image:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x1080 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, [ax1,ax2,ax3] = plt.subplots(1,3,figsize=(8,15))\n",
    "ax1.imshow(x[:,:,0], cmap=plt.get_cmap('hot'))\n",
    "ax2.imshow(x[:,:,1], cmap=plt.get_cmap('summer'))\n",
    "ax3.imshow(x[:,:,2], cmap=plt.get_cmap('winter'))\n",
    "fig.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create Convolutional Neural Network\n",
    "\n",
    "Now we'll create the layers of the convolutional neural network and assemble them into a model that is ready to be trained on data. \n",
    "\n",
    "The network we will build in this notebook follows the [keras blog post](https://blog.keras.io/building-powerful-image-classification-models-using-very-little-data.html):\n",
    "\n",
    "* Convolution (3x3 kernel, 32 filters)\n",
    "* Activation (ReLU)\n",
    "* Max Pooling (2x2)\n",
    "* Convolution (3x3 kernel, 32 filters)\n",
    "* Activation (ReLU)\n",
    "* Max Pooling (2x2)\n",
    "* Convolution (3x3 kernel, 64 filters)\n",
    "* Activation (ReLU)\n",
    "* Max Pooling (2x2)\n",
    "* Flatten\n",
    "* Dense\n",
    "* Activation (ReLU)\n",
    "* Dropout (0.5)\n",
    "* Dense\n",
    "* Activation (sigmoid)\n",
    "\n",
    "First, we set some parameters:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# dimensions of our images.\n",
    "img_width, img_height = 150, 150\n",
    "\n",
    "train_data_dir = 'train'\n",
    "validation_data_dir = 'validation'\n",
    "nb_train_samples = 2000\n",
    "nb_validation_samples = 800\n",
    "epochs = 1\n",
    "batch_size = 50"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "if K.image_data_format() == 'channels_first':\n",
    "    input_shape = (3, img_width, img_height)\n",
    "else:\n",
    "    input_shape = (img_width, img_height, 3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The architecture for this neural network is three convolutional layers, two with 32 filters and one with 64 filters, followed by a flatten/dense/activation/dropout combination."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /Users/charles/.pyenv/versions/miniconda3-4.3.30/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Colocations handled automatically by placer.\n",
      "WARNING:tensorflow:From /Users/charles/.pyenv/versions/miniconda3-4.3.30/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:3445: calling dropout (from tensorflow.python.ops.nn_ops) with keep_prob is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Please use `rate` instead of `keep_prob`. Rate should be set to `rate = 1 - keep_prob`.\n"
     ]
    }
   ],
   "source": [
    "model = Sequential()\n",
    "\n",
    "model.add(Conv2D(32, (3, 3), input_shape=input_shape))\n",
    "model.add(Activation('relu'))\n",
    "model.add(MaxPooling2D(pool_size=(2, 2)))\n",
    "\n",
    "model.add(Conv2D(32, (3, 3)))\n",
    "model.add(Activation('relu'))\n",
    "model.add(MaxPooling2D(pool_size=(2, 2)))\n",
    "\n",
    "model.add(Conv2D(64, (3, 3)))\n",
    "model.add(Activation('relu'))\n",
    "model.add(MaxPooling2D(pool_size=(2, 2)))\n",
    "\n",
    "model.add(Flatten())\n",
    "model.add(Dense(64))\n",
    "model.add(Activation('relu'))\n",
    "model.add(Dropout(0.5))\n",
    "model.add(Dense(1))\n",
    "model.add(Activation('sigmoid'))\n",
    "\n",
    "model.compile(loss='binary_crossentropy',\n",
    "              optimizer='rmsprop',\n",
    "metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To get more details about what each layer is doing, we can use the built-in `summary()` method of the Keras model. This will give us information about the output shapes of each layer and the number of parameters that each layer has."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "conv2d_1 (Conv2D)            (None, 148, 148, 32)      896       \n",
      "_________________________________________________________________\n",
      "activation_1 (Activation)    (None, 148, 148, 32)      0         \n",
      "_________________________________________________________________\n",
      "max_pooling2d_1 (MaxPooling2 (None, 74, 74, 32)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_2 (Conv2D)            (None, 72, 72, 32)        9248      \n",
      "_________________________________________________________________\n",
      "activation_2 (Activation)    (None, 72, 72, 32)        0         \n",
      "_________________________________________________________________\n",
      "max_pooling2d_2 (MaxPooling2 (None, 36, 36, 32)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_3 (Conv2D)            (None, 34, 34, 64)        18496     \n",
      "_________________________________________________________________\n",
      "activation_3 (Activation)    (None, 34, 34, 64)        0         \n",
      "_________________________________________________________________\n",
      "max_pooling2d_3 (MaxPooling2 (None, 17, 17, 64)        0         \n",
      "_________________________________________________________________\n",
      "flatten_1 (Flatten)          (None, 18496)             0         \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 64)                1183808   \n",
      "_________________________________________________________________\n",
      "activation_4 (Activation)    (None, 64)                0         \n",
      "_________________________________________________________________\n",
      "dropout_1 (Dropout)          (None, 64)                0         \n",
      "_________________________________________________________________\n",
      "dense_2 (Dense)              (None, 1)                 65        \n",
      "_________________________________________________________________\n",
      "activation_5 (Activation)    (None, 1)                 0         \n",
      "=================================================================\n",
      "Total params: 1,212,513\n",
      "Trainable params: 1,212,513\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "print(model.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.utils.vis_utils import plot_model\n",
    "plot_model(model, to_file='model_plot.png', show_shapes=True, show_layer_names=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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TCIgB6Yll0iCFgBAQAkJACPQXAmJA+ms9NRshIASEgBAQAj2BgBiQnlgmDVIICAEhIASEQH8hIAakv9ZTsxECQkAICAEh0BMIiAHpiWXSIIWAEBACQkAI9BcCYkD6az01GyEgBISAEBACPYGAGJCeWCYNUggIASEgBIRAfyEgBqS/1lOzEQJCQAgIASHQEwiIAemJZdIghYAQEAJCQAj0FwJiQPprPTUbISAEhIAQEAI9gYAYkJ5YJg1SCAgBISAEhEB/ISAGpL/WU7MRAkJACAgBIdATCEyWGPXESDVIISAERgyBG2+8MYwZMyb85z//qTuGKaecMtx5551h+eWXr1tPF4WAEBh4BCZJAjLwz4AAEAKNEVhsscUaMh+xlQUXXDAe6lsICAEhUBMBMSA1odEFISAEIgKLLrpoWGmllcJkk00Wi6q+p5hiCpeSzDrrrFXXVCAEhIAQyCMgBiSPiM6FgBAoRGCbbbYJk09e+yfjo48+CuPHjy+8V4VCQAgIgTwCsgHJI6JzISAEChGYNGlSGDVqVKhlNjbddNOFV199NfAtEgJCQAg0QEA2IA0A0mUhIAT+h8C8884b1lprrUIpCManY8eOFfOhp0UICIHSCNSWp5ZuQhWFgBAYFARQwxTRv//97zBu3LiiSyoTAkJACBQiIBVMISwqFAJCoAiBN998M8w555wBhiNLGJ6+/PLLAUmISAgIASFQAgGpYEqApCpCQAj8D4FZZpklfOlLXwp4vESaaqqpwlZbbSXmIwKibyEgBEohIBVMKZhUSQgIgYgAni54vET68MMPw9e+9rV4qm8hIASEQCkEpIIpBZMqCQEhEBH417/+FeaYY47AN4Rx6vPPP183Rki8V99CQAgIgf8hIBWMHgUhIASaQwA3280228xVLqhfMEytF6CsudZVWwgIgUFBQCqYQVlpzVMItBGBrbfe2g1RpX5pI6hqSggMGAIDabL+wQcfhKuvvrrKkn/A1l7TFQItI0BSuumnnz7MPPPM4eGHH/ZPy43pRiEwwAhMO+20YcMNNxxIKeJA2oBcd911nrNigJ95TV0ICAEhIAS6BIG77747fPKTn+yS0QzbMCYNpAQkphT/5z//6W9xwwa3OhICJRD405/+FFZdddXw7LPPhvnnn7/EHYNbBduTiy++OGy++eaDC4Jm3rMIPP7446GZTNM9O9EaA5cNSA1gVCwEhIAQEAJCQAh0DgExIJ3DVi0LASEgBISAEBACNRAQA1IDGBULASEgBISAEBACnUNADEjnsFXLQkAICAEhIASEQA0ExIDUAEbFQkAICAEhIASEQOcQEAPSOWzVshAQAkJACAgBIVADgYF0w62BhYqFQF8hcOKJJwaCHO266659Na9OTubf//53+Mtf/hLeeeed8Oqrr3pXn/jEJ8KKK65Y0e0bb7wRrr322oqy9ddfP8w222wVZd12csUVV4T11lvPn4uisRGg8a233kovPfPMM2H33XevCFfwxBNPBGIpEZKfzMhzzz13Wr+Vg0mTJoUHH3wwjB49uvD2p59+Otx2223pNdZopplmCptsskla1s4x3XTTTeGaa64J8803X/jqV79a4Qp/+eWXh0033TTtVwdDRCAZQLrqqqsSgy2xOCADOHtNudsR+OMf/+jPp8UBGdJQl1lmmeQzn/nMkNro9pv5P7Y4IG0ZpjEVyTHHHJPYBpwYA5Iceuihvg6zzDJL8tBDD1X0YdmAkzvvvDNZbrnlkqWXXjr53e9+l1DWrcRv3korreTzee211wqH+cADDyQWV8XrgCsf24Ar6n7ve99LjFFwPG655ZZkqaWWSm6++eaKOmVPXnrppWSfffZJjJFJ9txzz5q3MYY4Hr4ZI2ON1M4x0dayyy6bfOMb30gsyWIy+eSTJ2AXyRihZMcdd0wsBUEsGtL3Y4895nPjWRpAeiEM4KT9geJBFgMyiKvf/XNuFwPCJvruu++O6ITZZExS0LEx8H/cDgYEZm+jjTZKYEKyNPXUU/sGwUYLY5Kn7373u8kRRxyRL+6q86eeeirhs9VWW/lcajEgO+20kzNSsb5JHhLLeJzOhXVkQ77rrrvSsrPPPjuxzMiJSUrSsrIHJmlK7rnnHh9TLQbkySefTCzxoY8/jsskJmkX7RwTzMAvf/nLtO233347gflcd9110zIO6HP77bevKGv1ZNAZENmA2C+YSAj0IwIzzDCDi8lHam5EHP7a174WbBMZqSGU7nfvvfd20bptOBX3LL744uGLX/xisDduz/prG03Fddt8u17tsuCCCwY+Cy+8cMXYsyeoQe69997AfGP9j33sYxWqGpMOuCoqq44aN26cq6vOOeecbHOljldZZZWAeqsenXTSSQHVFmqeOK555pknvaWdYyKx4pZbbpm2PeOMM/ozQb6jLDEe8h+hhhINDQExIEPDT3cLga5FwKQP4dxzz03Hh+78xhtvDBMnTgwmGQkXXXRROPLII6sSyREC/sc//jHS0fD73/8+HHDAAeG0004L9jbsbb3wwgvhRz/6UTj55JPDP/7xDy8zFYSfU4bO/v333/cf89/+9rfBRPXhzDPPDNwHvfLKK+HYY48NL774op+P9B9sPrB9+MpXvlI1lCmnnDLYW7GHy/71r38dTOJRUcckAoFPnkxKEE455RSf5/XXX+9YZutgW8F1U9uEv//97+Hoo48O559/vp9n6z3//PO+hqwT69YpOvXUU8Ptt98eYDoWXXTRcN5551WMmTVjHU3lVDEEbIwIJU44/HbT66+/HmBsTDITZp11VrfH4NmK1O4xffzjH49N+zdrYxKKAHOap7322ivsv//+VeuVr6fz+ghU/+fUr6+rQkAIdDkCSB7YQHibPfDAA320/JiPHz/e3+YnTJjgP+rknIHRMJ1+MLG817vgggvC8ssvH/bdd183XmVT5M14jz328Hq8JWKcxxvpt771rfDnP//Z7/v85z/vxouUYVD43nvv+ZsrF8lnw487RosQGznj6sSm5R00+ef4448Pn/vc59ywsehWDEsZM2/Ehx12WDCbgKJqaRkb1nHHHRdMpeMYfPvb3w5rr712atT6m9/8Jpg9RmAT++EPfxgwFgbHbbbZxu+LDcHUHX744S51MBWQG13utttu8XJbv9dcc82w3377hdVXX91zEJmKwZ+VmDeLnCVsyKx9nngWHn300QqGJV+nlXOeNRgzDEHpA4YZHEwF4s11ckzPPfec/7/wXKy22mpVw6fM1EcNn4WqG1VQiUCruqtevk9GqL28ev0/9nbZgIwdOzYxcXUKGPp8++9PjFlIjeiuvPJKL7NNMa1nYnU39LM387TskEMO8XpnnHGGl3GNtn7yk5+kdWJb9sbvZZbh0+vYW2xahwNsU4zRKbSpqKhY4oQxDNUGZIkllkhs8y/szZixtPzSSy91XLJGqSbZSUw6lNb56U9/mpjIvsKWBANWxgmukezt2ctMQhSLkk996lNuKEoB9gcmiXCsYoUddtjB7zHGMRY19W2SLL+/lg1IbIx1M9WI1zVJlRfHtTVJTKyWfpsnjNd9+eWX07KyByYp83tr2YDEdjD6NKbVbVAwDjWGOunUmExKmBjD7ONi3bbeeus4jIpvY0zdULmisMkT2YAYwiIhIAT6D4FpppmmYlKIy8kei8gc1QJkHhz+nRVtYzvCdfOi8Wv8QdxMmXk8pGVlD+gzS7SPbQiulCNNH3zwQeBNuujNPj82Y+jCQQcdFN58802XRhiTkK/iaijsGrK2JEsuuWRYZJFFws9//vPUxTVKg7I2EKxFXIcLL7zQVV5IT5B68MFOg7VD2tBJIi28eWWEBRZYIDAOCOkPlF9LypCS8Kx10gWZZw9pCCo+cEA61KkxmdGpS/Fw7V1hhRUCUkFUdHlijbENErWOgFQwrWOnO4VAzyMwxRRT+Bzsxa3uXKaffnrfkOwtt269ootFm1ZRvZEoQ/XEBhoZgkZjwBYD1UqRUSoYUh43xmxba6yxhp+inqpFrEVcB2xrYIqwtYkfVD8wHxh+dppY74033jg88sgj3hW2IZB5Dvp39g+MGExWfJay19p9jJEoNjeMq9NjwmgX5gOKqsbsfFhn7KVErSMgBqR17HSnEBgYBDAq5c0TA8VmqZsZEBPnu4FjkTSjaJ7MBUkGkgvsQjAkjcQ1pAB33HGHMzWxnG9T8/hpWSkBm7mpbgJ2ECNFzBHGAmKzR3KF8WyeMAaNkrT8tXafzzXXXGH22Wf3cQ3HmJjXqFGjAs9JnrCrikxQ/prOyyEgBqQcTqolBAYaAQxWMSzdcMMNHYeowqGsFkXGIxoy1qo30uWomvAYyhPSCLyF8oRbJsxHkQjeAr8FmJm//e1vFbfhFYMhZVkGDjUI0gazualohwisGA4PBxH1EykIhIrFbFBcEoAxaiSipiKN2GKLLWJRR79vvfVWN4bFWHY4xoTED8xxxc4SGODFhUpM1DoCYkBax053CoGuRgCpBfYKuN9ChBdnU8XuIRJvr1B0sY3l3JPVb5sBZlhrrbVSBoQ3Y0TUuKhagCjXmV9yySV+O5tv1mMC5oV+8aaBsC/49Kc/7S6+XjDCf1CP3HfffVWjwG0Yb4giJguvHsTzeRdc4lKwMeI9FAkswIBrUU0Rw53n14I1AytUDbxd4410wgkn+FrgNWQROt07I7ZNu2BpAcFiUc1v3tih/HyIaYFHTpZpQgUEA3TwwQen7eHdQxs8C5HwTCEkOvYxkdoxJtr6/ve/7wxYZALBBYbsrLPOCnPOOad3V3ZMVAY7QsfXcv8mrsfPfvazCqYTN2A8mqIEyzu1PzwX/I98+ctfjkX6bgUBW9SBI3nBDNyS99SEh+oFQ/RTc+/0CJX2m5CYIWNihpYe7ppzvAjwerEf0cTyWri1v71xJ3/9618dp//7v/9LbKNMLAdIYq6ZHo6bKKH5SKB4wFh8hsR04R5l8w9/+ENihouJbWZp6PJ11lnH28fzhkiWUPQmIYrmUIn5DNULBq8Qk04kZl+RDseYqcRcU33sX/jCFxLLD5Jeyx6YYWSFFwzXCFFuzJnjYLlX3MPG7DjS2yy2inu4MHbCehujk5ixp3vPUHb44Ye7l9L999+fGKPnY6CcEOHZKKQ0aBumX2cdbENM+8gemOossYBePkfawePnhhtuSKsQBhzPHq6xTt/5zncS23QLo+ji/WSMqNcx92GfI+PPUpkxUd/yrSTGaHm/4M/zkG3L3Mb9mqlc/Fk0F+/EbDGyXflxmTFR0aQV3t4PfvCDqjYoMMbGn2W8mAjFToRbnukiMuYoMVfcoktNlQ26Fwzc9sCRGJCBW/KemvBQGZChThYGZKqppvJmzCsjMSlKzSZx7Y2Mib3NJ6Zuqahrb/9JUU6bem1WNNDghE1zqAwIXeBebJ4mDXorvmxv1FUXmLcZnCZmD5KYxKHqejMFT1o48si8Fd1HuPudd9656FLpMsZokpDCtSpqBJdb1rsWtWNMtA22MGI8Z42o0ZiYo0lsEpjCWsTzC8PG+tUirq288soJ/6dDpUFnQP7ri2f/xSIhIASEQB6BRkZ2uPbygYxpyd/ubpsEIstTPrx1/vpwnxNt0+I9uBoiG2q8zDiw7cgT9i/5yJr5OmXPF1poobpVbSMMJqWpW6fRRdRGeTVDvXuiCqRWnXaMibbBtgjfon4bjQn1FuohVFq1CJVaNtR7UT3UPkQHJkiZaGgIiAEZGn4jejfGbr/4xS/CE+avTtRLYivgPleP0Ovj046RW6s/WnhD1EufXa///DV+FCzwkUcVZB7keyDaIcZ8l112mW8K+XuG65wfURNV+8YKVujaIxEPAz1wltiA+bHEfbKZH/NsG91wjM4d/TY2I0Uupd0wxnaPgY2H6LFEfIUZIU9JLxC2JBjDjh49umuG241jAhxC7lu24zQGTiuAYQ9CFNuszUsr7eie/yEwVBFSL97fDyoYxLvo8m2jS2LGTnScWR1qfm3QcX/zm990PajlCMlfbniOWLVM+uyGDf2vguWecB23bewuAkekaS6OnpXU3iATC1RVtqm21yMyI3pxY4gcL8aDXjwSkRiPOuoovwb+iPDNO8HxsTdotwGwoFV1xdSxrfw3ONi/Z2lxeP7+oZyDP9FT6X/XXXdNzDBxKM11/F7G2Q4VTHag9dQd2Xo6HjwEitSJQ0Fh0FUwsgEZytMzgveOGTPGU1kzBBgDjNn4Mf76179ed1ToU6mHoVizVCZ9dtk2zYMgMVfOxKQ2hTpywi5jCDkShJEkhpQY9aHvJVw2hnCMlx+MSKQgB0tStWeJezBixJgNA8ZoI5GtU+94JBkQ0tHDXMUPBq3dTJ1gQLp5vhpbfyEw6AyI3HDtF6zXCDdG9NUkDYMIzkOERsTIqA3qUXQbjN/16uavlUmfnb+n6NwYpmAeFgE7gNNPP93dFvP1zBPAI2+iohluQk+MCyAuk+jyzZPD3SJRSxBkKlItOwbuIbMq7oJkn8XNM+tuGe/vxm/E+WQejZ+yEUK7cS4akxAQAt2NgGxAmlgfdOIEICJCIWmp11tvvYqcD9hkmGuZ++xjvEfwmqwRHxsYOQzY/DFgIismbZHtkbgKtI8/P5sVdUzKEcz1zvNHWJIr909H97iwxV+wxFUVI8fuAN1kDBCVvYi9AmnVMTSL97FJdoIIXsQ8N99885rNk9KceALEGKi1iWNPQd4Hkyak7RDMiZTg2CgwD/DNzoMojdiNoMc3SU8wa3e3KYFZA8+y+JJ/I8ZriJ0TgAtmqWwkS+4jlgNxBXgmYFyKsmrG9vUtBISAEBg0BCQBKbniGF2yoSB1ICU3jAhR8EhkBZGamQ2GjZPEUUTPI4wvGxDEhtsoHToGf0T4I+HVxIkTnfngXjZpszPwMMgYN84xxxwVGy91IDZgmJYs0RZBkcx2wxkdJCVQduPO1h/qMZv/LrvsUrcZs/3w6yR6qkcEOIpv4O1IcV4WXyRKeQJbmI/Pfvaz+Ut1zzGmhVpJ4la3YV0UAkJACPQ6Av2lUSs3m2aNULEFsM3SA9XEHgjeg/EhAZ1MTeDpqw899NB42b+xb6CORRX087Lp0LfddtvEvFkqUnpj40E8gFoUg0CZFCatQqAf7CiyMRdIF27PbGLeM2m9Zg6YK/fXSp9NoCALl1yzSewjCFxFG2BYhtqV4jz21Qq+BGgyiUxswr/BlXnkbUCylUwi43Ww2SlL0QaEtvURBnoG+v8ZKPtbWPY3pEfqvSAVjP13NyJE6LiKbrDBBmlVVACoXJBMXHnlle6Wmn87RkWDmyzhfC36nsdLQPKA5CSqSmISp5iGmw6QoKByIekVx/TDp1Y8AHJtGPPj48i6TR577LGulsmqOaIraackIPGNPwUqd0C/Ub1RNkcIqph6Kc7JFsoco7Qkn+L8+uuvrxhFs/iiykHFZR5EFe2UOUHtA5HIq1ki7DSJt0S1ESAHiUXIVEyG2hDpShcjQFh4pMaDSmJASqw86hU2kLxoHuYDwt4Aym7+nMcU3NmcGpRnKW7GxrGmxRh78jnzzDOdASHfBnYMtYh8Eago8gGUGDfGkFnqFOOR7aPRMUwXhp4ksWoUbwFcwG/VVVetahZ8iR2CeiwyVvlK4JvFluvN4MsYzWU5kIejFcJuBWrEmBW1jd1JURCvorqDXIY9VT2bo0HGRnPvbgRQ4Q8yAyIbkBLPJ4aQJGbCgLSI4lsqm2qWkFhgE9KM4WK8n7d0EmTR5rXXXutJlOK17DeeFjAe+aRIGIJirBntLbL3cDySjMjo0aN9OHiINCLGCX7tSHGe7asMvtjx4I2DHQ8GvM0SjA9GszBBrQZ9a7ZP1RcCQkAI9AoCYkBKrBQeLxDqlCy9+uqrAa+P+HabNzS0JEnhww8/bEk8jMErxqaIlzF8jZKSbP/0zSZnyaWyxcHsQVzFQ0RRslrWyv5YcdMwnhDGeNSoUb6xI6WpRWbz4sa74IsKKputk3uaTXGe7acRvjBveMOccsopFZ5OFugtkD20DLF2uEwT+pnIsyIhIASEgBD4/wiIAfn/WNQ8QrqAlAG7DEv65B4qll0yWNAvl0ywuZhho3s6ZG05zBjTQ3KTBhrCHgCGIRsTolY6dPJr7LDDDsEylAYzQK0amwXH8jTRMDinnXaaf9gsLZFYmvbcslr6fYj4iKeBJIf02RBjg4FqlvDmgSyxU+GteMAQEr4eWYRT98xBckR67DzjxlhJ7U4sDlRf7Upxnh1TPXzBFNUVuSVQf0V88SDCk2mRRRbxpmCQoHwqe8qRsFhGWhevwoiIhIAQEAJCIIeAbYgDR816wQAQIXiJamkqAf+YGqEiVDYeLrbpJMsss0xiOSUSUpWb0WpCNlHImI/S6dD9Bvtj9g2JuaLG0/Qbi2nbmAs9JGxjTYyxSOva27d71FBOBkfSSJtkxceaT+2d3lTjAK8akxx4v5bzpCp9NreZtMbDkOM51IgIG086eLxiGJvl4EjWXXdd9yqxTb8iI2W7Upxnx1QLX4vLUoit/et4anvaMMPjhGeAMj5mh+DPB2u+8cYbe0h2MqG2QtELpt1hn1sZS7ffA/btDsXe7XPW+PoHgUGPhDoZS2n/xANFJGPDwA+7jkbJ2/LAYBeAJCHafeSvm2umqz1IqrbAAgvkLzd9jiqg2THmO8EehARyjIe3e5Y8GtDm6w71HOkFdhvNtI83jOWp8Tgm4IaXUJHKiXGj/kAdg1qsFbuM/PzagW++zaGeY/eD0a0xIDJCbQAmzxoGwjJCbQCULnclAhih8nuHqjYGiezKgXZmUJPkBdMksISorkeEsi7y2Kh3T71rQ2U+aBuX38gMYRQbCUaMTz3CC4NgZmWpFaYAZoPU5Y3Sl7PZNKpTdpyxXjvwjW3pu7cQgDEnQyoqtd9bpGCIZ2yzzTZz43Ev+N8fjIlhCCPxf7HmmmvG0678biZrNUzcwhZhOe9NhhE7NmX8j4ILdYZKuLUTogA1aD2qNSZU2VxD1UnoAwy8s79r9drMX7vppps8UjFu9kSkLvI644WnXtZxbPFMkptvWuclEJANSAmQ+rUKP7wWYKvup5GbbL9io3n1NwJIKjEORpJmWaWDqU49NcBWW20VLMhe1eRJiQADgn0Tbt/ZWDNVlUe44OWXXw645i+66KJuJN9oONiZjRs3zo26s3Vx7T/11FN9zthqYZSNpKlVoTkvO6ZqDUQ4zttNZfvluNaYSF2BPR5rxnhYx8UXX7zKjizfXtG5Zbf22D4wGNibIX3Nv5DRH2kyiOOE3Z+pid0pAOYukmWP9nIYWlGTCNjDNHDUig3IwIGkCY8YAiNtA0J2ZXP97tj829m+/dw1bQOCbc1GG21UEWmYyR599NGpTQ82XHkiiq9JzBJTGeYvddV5M1mrsU3DbgkcLddROg+TfHhZtGHjgqkL3P7N0kSk9coePPXUUwkfY/C83ddee63mrbXGxA1EFDbj/Ip7iWxsMYEqyhqdYHthBuZpNWNCEpNeuw1aWmgH9Geeel5UL+s4/y/bb7999tZSx4NuAyIJSJMMm6oLgX5GAHsc3vIRb3eCOt1+mTHzZo/IHHVpllC/4LGGyhIvpnwMHa4vbCqIVjJJZ/vp9DFSy7ISGlzii1Sszz//vA8zBlnkJKpXsfNqlpAu8AG/RlRrTNyHGzyhBbLEuJodE7ZwuOJHIogkz0Q2ajR2GWWzjq+//vpun3bdddfFJvVdAgHZgJQASVWEQC8ggCiZtAFEjs1nYybzsr1tebRe3LqpS4A1fojRf/NjzI84P7i4eJuXk9tD4IJOBGCSI+ISTTJEdPgYz/GDHWPgDKV9+i+TRbkda4DNB2J2k3AUNrf22mu7Ooaw+2SeZhNC3B8pplCI53zXw53rjbI0UycS2MP4EHwvxqqJ19r9DeaoF1A/5YlM02zKpHiAocHonqSWqKxQ23aK6o2JPlkTxkSaCtRG2INwDyEImqG8LRmOBfx/kL4iEsxS3jCUZ7VW1vG99tor7L///p6lu9uZ1DjHEf8uJSfqs0pSwfTZgvbZdFpRwViuosQ2h+TSSy9NEBXjbo17M4n8IuEibsbI8TR56623EnvjcxdiCs3Dy12r7Ucp2W+//RKL/JtYML3EfvRdbG7MiIvrd91118R+iBPbjJNf/epXaXuttG9xZfx+M/5z9/C0sZIHjNUMEkvWThIzpKwSs8ebjznmmFQsj1ifti3DdWJxe2IVdzNPT+ygEe64axsD522ZDYGL6c0Dz8/pL5IxfwkJJy+88EJv0+LQJBaHJk1kGeuV/aY9xl8raeRzzz2X2AbuzcWkilkVDBcYL22YLUly8MEHJ8acJha3qOwQCuuZdMPbLFLBlBmT2V4kxjx4GxZfJzFGKSHh41AIlRyJQ82mpFQzxpAmFhOoqq5JjXxcxqBXXatVMOgqGAyKBo7EgAzckvfUhJtlQNhsTOSeNMrGzKaWZUAAxd7wUgaEczZUNh1LoMipk7lIe5kZIMaihI2AjZX2TIri5a22z82NsiinHecOGGszDIhJcBKLHJxr5b+nWQbEAu0l5hHi87bgg2l94txEKou7vRV7OybdiLc67vYmnZ7DMB522GHpuUlN/B7zFknLmjmox4Bgy4ItBmsI1WJAuGbGlz4OmM3sM8G1VqgWA9LMmGCwzXXVx0X8nTiPVsZj6SBShoZnCSarHhVlHc/WN8lV1f9h9nr+eNAZENmA2FMnEgK9jAB6ZzwzirIxE3WXbMzNEvYOkVC9QCussEIsCtHyH88QC+iWlpc9yLbPPahyTNpQ9vaW6oEFqiPE6I0IuwJ7s3b1C1mJizAsi3utLM3ZqMknnniipxrA9oQPqgDUBCYpaDTUpq/jzYG3D2tYj8DKJGqeFBM1HJGZjzjiiHq3tHyt7JjogLVYa621PBI1MXN4drJYNjMIC3zo/zs8wzzfF1xwQZUnTGwP+6WirOPxOt/YFdVLPpqtq2MLESEQhIAQ6G0EoqEgOvsslcnGnK2fPc4zCNlr8Rj7AQi3T2xDmqEy7TfTXpm6bOZsIpEhaHQPMSHYgLF5gCnAFTdLQ8GduBr2NuzNEdwQo09sc8w7J9tF248J5GdqM3fThcGCCMYHkWuJMrILY/eyzjrruHsq8T9wnbUIv56c0bxm3J3Wb2rDn7JjgnGcMGGCp5MgOSX2ODCtpJ9gfbBDapWw94D5wB7GpHGBOeapVtbxbD3+B2HKReUQEANSDifVEgJdi0CMysvbYGQ6GOxQsjGXYRDMrdIxId5Es1Sm/WbbbFSfTZVAghiNliWCChILg00OA8gs89Iu3KPBItmvO82AsDkiLcjGOomMEMG9MNBFwkD8C+ri3QFhlAxzQkBD8jQRz6NdVHZMMCDk4zLXWGc+6J98XMQMYcwwco0CRdYb89JLL+1JMrNGx7F+razj8Xr8JlcW7YjKISAVTDmcVEsIdC0C0RMln9Qvn42ZN8ZaSQTj5CJjgKSgERFFEo+A+IPd7vYb9d/Kdd5wzYag8FY8gsx2ouoarrkkoURKQeCrSGVxj/VrfeP6SVBAMwKtCtCFt0er6oWi/vDyYcPPfh555BGvitqHcqKUwgzhGZJl1mAAiJTazvHQcdkxUffee+91RoPjSEhmUK8NNes3kjyYGDyAsoSXDUxaUdbxbD3wYgyEVheVQ0AMSDmcVEsIdC0CZbMx88NK9mXE2ORB4puMyOj6Y5bjaB+BNIUfXX7wI7EpRTKPhYAYnGiSkYbSfpksyrGfoXwjIcrOI9sWm2+t+CdkNl599dWz1UNZ3M3byO9jk4zEOsDsROmDeR355s9mTFh41CFmlOoMD/EzINYEBuDss8+OzdT8juvZiOGs1QBrST4nNt9IPDMwtWSKzhIMGpFSyzAAQx0XqiDGxGYfCZWJGQdXqAEbYYX9Dm7oUf1EW0hReJ6z6sQyWcfjOPifIBoqruuikgjYP8DAkbxgBm7Je2rCzXrBMLlG2ZipY2+ziRmquvfAUkst5e6LuNjiaWGbGlWcTPfvdcz2waNXkrXYfk4SM/zzKJR4MuDBgctvllptnzaayaKc7ZNxNeMFg/snmZzx7IlkjEdy4IEHepRTMkUzP/DME94WZqhYUdwId2Mm3I2VceJmC5a42uL+TNnhhx/uXkR4gdAv3iaU8433jEmi0v5sw/RrpmZIbKNLy/MHZbJWZ+8xxsLbzbvh2ibt2b232247d8nleTBGLHurH0ePFDxmahHY4dYL9swPT6QbbrihVvWk1pgoJxKq2eMkJ598smOKe7gx0RVtNcLKVCrups46GAOVmHFtgodLlprJOs59eDLhtt0MDboXDBz4wJEYkIFb8p6acCsMSJwgsTxuu+22BDfOWoQbY6SijZbNkE05UmRACFXOBsCPPXVqUbPt0w5ur7iONktsZs0wILRvXi2JGS0225XXt7f8wvvK4F54Y67Q3sg99go4FxHYZt2Ci+q0s4x15lmCYavF9LB2F110UdJM/IuhjhF8zAg4KYonEttuhBXMHYxRvWc5ttXomzbMLibhf7cZGnQGRCoY+wUTCYF+QSBmY8ZYsBbhUhmpKCMpdiBFWUG5h+zB2CtEW5HYTva7lfZxe0XkPxxEQjFUT6g5miWMMYuoDO5F9+XLMHLFTqVWlmbb4Dz7a/6+Tp2zzjxL2DXguVNEqJJQeaCGGS4CH5PiecTYWn02wgrjX1yR6z3LtdrOlxPe3yRY7kGUv6bz2giIAamNja4IASFgCEQ9OQZ6/UBsPOedd54bfWLH0iuELQmMDt443USEt7cgbqlnSjeMbTixwm4EY+xuW5duWIdGY5AbbiOEdF0IDDACGGViDAkRE4O3TvLFDJe0olPQI3HBtbLdHh2dGi/t4i0zevToTnbRUtsE8+o2Gk6syElTS2LYbbh023jEgHTbimg8QqCLEBg1apTHwSAWRqSpppoqHvb8d/Qw6fmJaAIjhoCYj9ahFwPSOna6Uwj0PQJIOnpd2tH3i6QJCoEeRUA2ID26cBq2EBACQkAICIFeRkAMSC+vnsYuBISAEBACQqBHERhoFQzGQ4SPFgmBbkIAF1GI8N/Z3CPdNMZuGguZZMlPIhICvYbAO++802tDbut4JyNoSltb7IHGCJlL6GPC5oqEgBBoDYF77rnH7UPwjBEJASHQGgLE4sHIGxfrAaNJA8mADNgia7pCoCMIkJWU3DHnnntuR9pXo0JACPQ1ApNkA9LX66vJCQEhIASEgBDoTgTEgHTnumhUQkAICAEhIAT6GgExIH29vJqcEBACQkAICIHuREAMSHeui0YlBISAEBACQqCvERAD0tfLq8kJASEgBISAEOhOBMSAdOe6aFRCQAgIASEgBPoaATEgfb28mpwQEAJCQAgIge5EQAxId66LRiUEhIAQEAJCoK8REAPS18uryQkBISAEhIAQ6E4ExIB057poVEJACAgBISAE+hoBMSB9vbyanBAQAkJACAiB7kRADEh3rotGJQSEgBAQAkKgrxEQA9LXy6vJCQEhIASEgBDoTgTEgHTnumhUQkAICAEhIAT6GgExIH29vJqcEBACQkAICIHuREAMSHeui0YlBISAEBACQqCvERAD0tfLq8kJASEgBISAEOhOBMSAdOe6aFRCQAgIASEgBPoaATEgfb28mpwQEAJCQAgIge5EQAxId66LRiUEhIAQEAJCoK8REAPS18uryQkBISAEhIAQ6E4ExIB057poVEJACAgBISAE+hoBMSB9vbyanBAQAkJACAiB7kRADEh3rotGJQSEgBAQAkKgrxEQA9LXy6vJCQEhIASEgBDoTgTEgHTnumhUQkAICAEhIAT6GgExIH29vJqcEBACQkAICIHuREAMSHeui0YlBISAEBACQqCvERAD0tfLq8kJASEgBISAEOhOBMSAdOe6aFRCQAgIASEgBPoaATEgfb28mpwQEAJCQAgIge5EQAxId66LRiUEhIAQEAJCoK8REAPS18uryQkBISAEhIAQ6E4EJkuMunNoGpUQEALdgsDEiRPDBhtsEP7zn/+kQ/roo4/CZJNN5p9YONVUU4Xbb789LLfccrFI30JACAiBIgQmTVlUqjIhIASEQBaBhRdeOLz//vvZoprHCyywQM1ruiAEhIAQiAhIBROR0LcQEAI1EVhsscXCCiusUCHtyFeeYoopwvrrrx9mm222/CWdCwEhIASqEBADUgWJCoSAEChCYNtttw2TT177JwOVzLhx44puVZkQEAJCoAoB2YBUQaICISAEihB44YUXwvzzzx9qmY1NO+204dVXXw3TTz990e0qEwJCQAhkEZhU+3UmW03HQkAIDDwC8803X1hzzTULpSBTTjll2HTTTcV8DPxTIgCEQHkExICUx0o1hcDAIzB+/PhCDP79739L/VKIjAqFgBCohYBUMLWQUbkQEAJVCLzxxhthrrnmCjAcWZp55pnDK6+8EnDDFQkBISAESiAgFUwJkFRFCAiB/yEw66yzuqcLHi+RYDq22morMR8REH0LASFQCgGpYErBpEpCQAhEBFDD4PES6cMPPwxbb711PNW3EBACQqAUAlLBlIJJlYSAEIgI/Otf/wqzzz57eO+997xonnnmCXjIEBVVJASEgBAoiYBUMCWBUjUhIAT+h8B0000Xxo4dG/B8Qf2yzTbbiPnQ0yEEhEDTCEgF0zRkukEICAFULhiion7B/kMkBISAEGgWgZ7MBXPnnXeGxx9/vNm5qr4QEAJtQoCkdAQcm3HGGcOjjz7qnzY1rWaEgBBoEoFlllkmLL300k3eNfLVe9IGZPHFFw+PPfbYyKOnEQgBISAEhIAQGGEEVl999XDLLbeM8Cia7r43s+Hy9nX88ceH/fbbr+kZ6wYhMAgIoCJ59913w+WXXz4I0215jj/60Y/CkUceGV588cWW29CNQmAkEdh7773Dn/70p5EcQst9ywakZeh0oxAQAkJACAgBIdAqAmJAWkVO9wkBISAEhIAQEAItIyAGpGXodKMQEAJCQAgIASHQKgJiQFpFTvcJASEgBISAEBACLSMgBqRl6HSjEBACQkAICAEh0CoCYkBaRU73CQEhIASEgBAQAi0j0JOByFqerW4UAkKgNAIE+/vud7/rbqoLLLBA6fsGqeJf//pXDwB16623hldffdWn/olPfCKsuOKKFTC88cYb4dprr60oW3/99cNss81WUdZtJ1dccUVYb731wrTTTlt3aMz9rLPOCgcccEBVvdtvvz384Q9/CGRQ3myzzcLCCy9cVaeZgkmTJoUHH3wwjB49uuFtF198sff36U9/uqJuO8d00003hWuuuSbMN9984atf/WqYf/75K/ri5I9//GO44YYbPHXBF77whZAdz1133RXmnHPOsOCCC1bd1+8FkoD0+wprfkKgRQT4YZwwYUK47777Wmyhv2/7zW9+E1555RWPCLvaaqv5pvi1r30tfP7znw8PP/xwxeRnmWWW8PGPfzwce+yxztSxWc0666wVdbrp5Oqrrw4rr7xy2GSTTQLJBxvRjjvuGE455ZSqasSoOPXUUwO4fOlLXwrf/va3w+abbx6SJKmq26jg5ZdfDvvuu29YdNFFS8W3gTkcN25c4DnOUjvHdNxxx4VvfvOb4e233w7f//73nYkAuyxxnbnzv3TwwQeHz372sx7HKtZZfvnl/bm4+eabY9HgfNuD0HNkHHRigch6btwasBAYLgTsBz+xzWPI3dmP/pDbGGoDL730UmLSg6E2U3j/aaedlsw999yF1+oV/uAHP0gsiFlVlamnnpqdNVlqqaWSt956q+q6SZSSI444oqq8mwqeeuqphI/l+PG5vPbaa3WHZ5KPZIkllkgsK3JFPZMy+P1PP/10Wm5StcSyJicTJ05My8oe/OUvf0nuueceb3PPPfese9s777yTbLDBBl739NNPT+u2c0wWjTv55S9/mbZtTEhijGay7rrrpmWXXnppstdeeyWWNyn56KOPkt/+9reJZZJOLJFjwv2RuD5mzJjk3nvvjUWlv7/1rW8lxtSUrt9FFV+QBGRweE3NVAg0jQCi4ZEkoh7z9vzkk0+O5DAq+v773/8eiKC6yy67VJRzQpqIL37xi+GBBx7wLMH2Y19RZ4455uh6tQuqAD5lVCVIev72t7+FDTfcsGKenDz//PNedv/996fXpplmGj9+//3307KyB6usskpAvVWGUAUddNBBVVXbOSYSMW655ZZpH+RF2nTTTcPMM8+clhGhFMkI6idjvMI666zj95DI8Y477kjrcR3JzDe+8Y20bBAOxIAMwiprjkKgBQTsjS387ne/q/ih5IfzxhtvDPYG66HeL7roIrcRyaocqHP99dcH7CIIcY5twP777x/Qu0dCfXHyySeHn/zkJ16ECJtNnTLahNik+IG3t0bPc3HmmWeGF154wa8RYv6SSy7x4+H+853vfMeZIjaUPNmbbbC34rDYYouFX//6165uydaZfPLJA588oSZAhYGKBuyyjEsZzGN7bLDnnnuurwlr1EliA0algBqiiGDE2JQPPfTQYFIUr3L++eeH5ZZbztVURfe0o4xnY8kllwwkaMtTO8eESi1L/L+QowxGIhIqJ5iLLEVmLW//Y5ITV+Vcdtll2ep9fVz9n9DX09XkhIAQKIMAb61s/muvvXYg+zT0+uuvh/Hjx/sbPvrsnXbayXNQ/PjHP3aDQDaZZ5991u/DwPKEE04IO+ywQzCxefjZz34WSJhlImlva6ONNnLmw9QRfj7TTDO5xOCwww5LbQnee++9QDsQhn384E833XR+vsceexRKIPxiB/8g/cDgMI6rqCs2FpgPNl/mc9VVVxVVS8vYsNjEwYR22bTAHcPOMpjHhmAWDz/8cDeANRWQ22/stttu8XLbv8mhY+qFwNoVEdmSjzrqqGCqk4D04pBDDnF7Iow2Gxm1FrVXpgwGjA18991TcJsAAEAASURBVN13L6zeqTE999xz/r/xuc99LmAPFGmuueaKh+n3M88841IwbEHyxL1HH310vrh/z7tIH1R6KCYalA1IabRUcRARaIcNCPpo++VLsjp0M0j0MjO0TOwN2KG98sorvcykGn7+6KOP+rkZG6bQm+dCYj/GiXnTpPd95Stf8fO0kh186lOfSuxHPC26++67va1zzjknLePgz3/+c2ISloqyVk6atQG54IILfDzYMhSRGRSmxej/sXfALuChhx7ycpPiJPQZ6ac//WliIvvEvGRikdcFdzOg9LIymGN/YMaZCbYPkYz587GaGiAWNfVtagy/v8gG5Pe//31izE7aHnYIeRuQeBF7GeaD3UN+HWOdst8mFfO2imxAsLHAboVnDXrzzTe9bvb5jf20c0wmEUyMOfa+mKclgozdFH7zv2OSvsJrJgVznJhnWZINiKEuEgJCoL8QiPr67Kx4c0X1gIoBdQO09NJL+7cZG/r3DDPM4N8rrLCCf/PHNieXmCAheeKJJ9Lysgd5dcdnPvOZijfNsu0MtR62HdC8887bsKmxY8e6HYJthC6NQM2UJ1RO2DXgJRMJ9cEiiywSfv7znwczZHVpQSPML7zwQvdWQXqC1IMP7qqskzGEsem2fONSbExUoY1FvgNcuZF6oT5DGoBELEq98nWHen7SSScFY0D8WavXVrvHhOoEt2Cea555Y1JD3hMmjge3Zjyg8IwpIp4DVG7tXrOivrqhTCqYblgFjUEI9DACUcdtb2x1Z8HGCuFO2SzlGZBm729XfcbOWMqqEFBToFopMkoFL8pR1eRpjTXW8CI2tiLKY/6Pf/zDNzbsaOIH1Q8bGa6o7SR743aVikm+XN2ByuORRx4JqMw4RsUCMT+MLqNxpUmz3AUVNREusu0kbJB+9atfBexSGAMfxgdhJMs59kOdHJNJ5p35oE+T0PFVQWCEfQ6fWhSfBRj1QaD/vsIMwkw1RyEgBEYUAXPt9P6J49AsdQsDgrSCTeyf//xnIeOQnxfjRpKBxAa7EFPFuHSCelzDXgRvCLx9IlPBNXNr5au0xwz30jYb8FRTTeX3duoPTBiGyFlCyvPuu+8GU4248Sc2LAQfYyON9jLm7uyMAEHtMCAmzki7iH6QwNF/JNYJIhgZEglT/zhGnRwT0sBRo0ZVSciQGsF4YQtVJFmMY8bmB/rYxz4Wi/r6WxKQvl5eTU4IdA8CvBmvtNJK6Y8zKhzemutRZDzYoLuBll12WR+GxSapGg4bHptwnnDLhPlAvB5VOLEOjAmqGd7Ss4RXDBt2WWbtk5/8pDNFZ5xxRraZwMaHkXA7CckKm3j2g0syKhbK8OKBCGCHZ0hW9YT6gSigUV3XrnHB8GTHwzESBwjPIs6J6NrpMcGcgTneNpF4JlCN4eWUVbUhkcl6j1GfMp55VHCDQGJABmGVNUch0AICMVYD0T4jmZGjSwA++OCDWOTRQDnJR8zMRlDFS4A3/azLJj/StI1HDRIFvvH8QEcf3wTZsCDiKbDBm2Gsn7PhER9kuMmMZD3yaXZucQxsHsyziKnCgwfbgLwL7ve+9z1/I8Y9NRKbNvPlGpKNMpjjscRbM5FC8T6C0eHNn7gSeC5Fol0YgLPPPjsW1fyOa1A0n5o3ZS6wvhaYrSJqKeuMJ5EZIKc1u3FMDA7siGCKK3kRXXfddS7RyDKdSFl4xqMEC4kUcyWeDu7Z2M7wQTXHuuQZDeLdgFtZFV/RuHqqzP6pe45M1yYvmJ5bNQ14OBEYqhcMXiZ4qdiPWWJv/Ym99bqHBd4HlJkRZoLXi224iQVf8jJ7C09Mt5/YRuzna621VoInBt4UJvlI8ArJEp4bRHCkPSKHmp4+McPNxN5UE9sg06pmR+B18B4gQieEtwm/A2awl9Zr5QCPlGYjoZprabLNNttUdGcqhWTNNdf0cVquj8SkPRXX44m5WFZ4wVB+yy23+FyImGlGit622XH4LXi1lMGcyuY6nZidjY8hrptJUryd+MdUAH7dwsDXxA4vEjPodFxoh7laHpPYROH3fvvtV+gFY5t0YvE4ku22287bZA1/+MMfVrRRZkzcYO7PiTFaPn7WjGeEZ60WGbPjdfNeMGXGRJtmwOv34zFTRESANZsN92IyZsUj3JraqaKq5YbxNsAx/zGpSEVdPF8sUF2CV00z1MteMLxV9ByJAem5JdOAhxmBoTIgQxluZEDYbNkEcFnFRbIWEWo9Ei6neeJeE6FXFNtbedKMq2LFzZmTVhgQxshGD/PVCtkbddVtzNEMThOTEiXMbShkb9Epo1bUDnjvvPPORZc6UsbcLPZFgnt2LYaxG8fEOlhQPGcKawFjqkF3+633fNe6N19uEqtk4403zhc3PO9lBkRGqMaWioSAEOgMAgR+youZ8z1lgzUViZ7RieczjNYz5Mu33+5zxogKgyBjuJfm1SqN+sO2I0/MMR9ZM1+n7PlCCy1UtyqZWcnIOlzE3BplU+7GMaGCRD2ESqsWsfa4mA+V8HZCRYc79SCRbECGsNroqr/+9a+7gdMQmil963D312hgxBmwgESNqpW+jj0AYbc7QSeeeGLbjfHqjXO4+6s3luG+FnXiGOP1K5m6JWyxxRZuc2Fvvz0zTeKKYAhJjJJuoW4cE9gQwfWYY45J4910Ci+8wzCUxT03RvrtVF/d1q4YkCGsCJbqGM4VGaQNodmatw53f7UGgqV3M2mxa7WTL+etknY7Qfxz4wI3XDTc/Q3XvBr1gxEdkgGIAFT8f2QNVhvd30vXkSLg3UDgqF4hPHJGjx7dVcPtxjEBEAHGhoMhwFD3vPPOC5Ylt6vWZTgGIwakCZTzGxjWzWzGlka5iVbKVx3u/sqOjE3GDNOqvB7K3l9UDzdLMxbzvCHktBgK5XGjLRKhDbXdWmMa7v5qjaMbyomBcOqpp7oXCzlkyA7a6bgUIzlvIqKygYiEQKsI4OmFmmoQSQxIyVVn8zrwwAOrancqXflw91c1sToFzaTFrtNMxSVCFJvXhP8jEp66VaqFG+HBO/E2M9z9tYrLcN3HZmweFhWfQf1xHS7M1Y8Q6FUEBsYIlYAvhMcljgAZB3kzyxPhgW+++Wb348f/O+ayYJMx62TfHDE64y2P8Mrofon2R/hcNmXqoTeEzJ0q7Ljjjn6MnQRv4Bifbb/99l5GzATKUavg649PeDS0K9ufN2R/CPRDhk58/4kFgB95NpIeImLaxGCKbI2kQidqormIedrq2E47v0mJTb+WkKxUswRQQpKAz30MIb344osX3ktchBhVktTeBBhCr10LNxohcBTtYrPD/ah7UA2ACRIsAkyhi7bkYB5MCh159OWv9eyU7S87Cdbb3C69D2JKsFbZDZpMmYSNJtsrGWlhzBZccMFgCa6aNnbM9qtjISAEhEDXIdDQx6cLKyzcZBwQfNpN7+mugE888YT73Ft0wIqZHXzwwZ7d0QzoEjJwkrkRv3zIohQmxrR4Nk/bdPzcci+kcRKyfuZf/vKX3d/brKfT9nHRMk+A1JWQ+AfGbCS0hVsacQXMcj2h72b7Y6y2CXuMBVzZvv/977tvOlk2ITJZRl90sjTinmmJkNxn30R/iQV+8nrN/sEF0h5mj1FQdC/zw6e9DJkNjfv3U5c4CLRrG3DhrcZkJcYcJpbi3bOqkv2Sfh577LHCdQLfCRMmJJYyvCJOgTGKiTF+HnMi25ExQokl8kqL6j07Rc9Frf5oEHc5M1z0sRoj4rEseC7N+Nb7I6ssGWOZP/0as5psuOGGfm7GcOmYyhyMpBtumfF1S51W3HC7ZewahxAAgV52wx2IOCD2Jl2xqWyyySa+icXHlwBJbJhZIiCS5SpIi7jHpArpOQdF6crZCO2tOjnooIPSuvjl77TTTum55YbwOjFtdEw5zqYYqUx/MAGWmyI59NBD423+zeZjovAEJgkibgGbWr0U6l6xiT+NGJBm0qUTxCcG8MGvHmaMAD/mRVExIjZ3k0olBACKZHYGPteYCr4IN+qynvl04dtuu21ibqIV/ZjUKmG9IjV6dsr2VybtOn3uv//+vlbmDRSH4CnqCeTVDPEMmGTF22Lt9amNAYyo8KmNj7DpfmxWXHHFZn4euqXuCwOhgkHVEVOEI9ZGzI24PZIFTAobbLBBPPVvMivm809kReVUKopFQO4Gki/hBUHyIfJdcExY30ikjEb8jv84YY5R40DkLkCVE6lRf4QCxn/coknGW/wblcQvfvELT75kUfxKpfOuaKANJ+S4KEO4apIlE9UWhEqEMNu2EYef/OQnYZ999kmbQc1E3exagSMqqKwhYB43GihaK1KWo3IhWRjHtMPHGKC0z0bPDhXL9Nco7ToZTPEGiHYqJD2LRIKrmF8jlpX5JtmXRagsU3Vg6/A/xP86z5pICPQiAvyG4QzRizQQDAi2FRZK2G0AMHS0ELsBC30IJoNU1tncBJSzqcA8ZKloo8lej8dsZmySpIO2N2T37DjiiCPiZd9kYT5McuHMQWQ68vEEGvUHMwXFFM6xg5jKO5/4Kl7nG7sTyFhh/x6pPzBnFjnTDVDjGMgXAeFNYWqwdKymdnFGMhu4inpZ5oPzRrhRBwJ3PjA/rBm5GrC1yFK9ZyfWa9QfGLMWq666arwl/WatTC3ojCQ5OoqItWplnRh7WRucon4HoSzaBgmnQVjt/pwjwdLIodSLVLnD9uIMSoz5kEMOcSkDb5G8YRKfIBI/7Gz8GGZazopYXPjdaKOJN2HUiCSEjY2oiXk3XTYc0/0H3npNx1+VETG206i/6DfOAxiZDu7lDR7XR1J9dzOBO4anMFJ5JgqGkHXCmDUyh9SHOTHbmYpsk/k5NsItWx/GY7vttvOIh9dee62nCc9er/fsxHqN+uN6u9Kuxz71LQSEgBDodQT63g2Xzf673/1uGDduXCrezkoakHJYIiz3kCHSaJYIjYu3CsQmklfJZOtmj6mLGsGSCgVUIKaPz14Oh5tqhiyJMB9QdjyxYpn+opoDz50skW2S9vF46WbCw4O3/jzzwZgtAZcPPeuSi8cLhHopS3D/MCpQGdyy95JFFI8lM+QKluAslbZQp9GzQ52y/bUr7Tp9ioSAEBAC/YBA3zMguFxCiNex+8AFkg2bVNNcQ+dP5EYkIWak6W/kvAnzVkxZ1MkTLIbQ4zApZmjqb+LkCoCy6cq9wP7g7on0A1dS88CIxf7NWzxqB2wauNc8crz8+eefDzF8dZn+LPtoMENKn8/TTz+d9nHrrbe6C2m0O2GezCUbkTKOOTJY6c0lDxql6m6ULp3xEOa4yB2aIRDqmvwRt912m38oMw+jYMZWbrdhybTCxIkTg3mLONa4TUNFuFHOWr355ptVUStZI8vYGnDBjm7T1IfKPDtl+yuTdp0+o21Sfq0YP5iJhIAQEAJ9g4D9qPUcLdykG64xA+5Wi0cDbpZmdOaeE2uvvXbqhkpqZ1JU28J6emXqZQmXWVxzqUM66aJ05dn6HNMvXhp5ssRL7ulhhpGeytyYB09XbmJ6dxmlftn+8HAxNYKnvLZwvokZ0yVmf5LQJmSbaOl03n5DiT9l0mLXS5dONlBTSznWuJniUpslPGxM8pGY4bDXMXVWYnE/vApZUUl3bpIH/+DGms2UmscN12bWC1dd1pYU2PlspCbpSPBmKaJGz04z/dVLu07fZvCaMFfGiTeOMamJJafy55Eyk5y563HROPNlcsPNI1J8LjfcYlxU2jsI9LIb7mTAbD9uPUWLLLJI2HXXXZuy8EfSkZVE8EaZ94xAFWKbmb95442RJ96gKc+2k6+TPScpF9lAi4i+kD5E7xyWAbVJ1qCymf6oizEtQasaZZ4sGk+7y8AX9UR2Pu3sA0kRGEY7mGzbzeAW76u3Vo2enWb6Y50JbEabqJTyz2Acz1C/MaZlTlE1NdT2+vV+7LCOPPJID4DXr3PUvPobgb333ttt2LAF7DGaNBBGqCxKnmko+uGHuWADr0VE22yGajEftEFfkfngvGizbqY/6hZ5WdB2GYKha0SodGJ02EZ1i/BtdE8z1wn3XYuawS22UW+tGj07zfTHOrcr7Xocu75HDgFUd7hJo/aMngi4UKMqzBIMM6rdLOGu3+2G4thp4daPqrIeMXeLz1NoyE8UaEIN4M212WabBZNg12uq4TVU4YQfGD16dMO6F198sfeX9zBr55huuukmV6ejjiW6NN5neTKpt3ti4hxAEsPseIiOTEqPentPvr1+OR8YBqRfFqxT88D+pRHl3V8b1dd1IdDPCOA5x4YC80p6h+OPP96lKTCkpGRYcskl0+lTBuOJbRnG7Ehe6jHR6Y0jdHD11Ve7bRzhCiyackMGBPsp3sDznoS8nePqjA0UUj+yByMFhDGAGW+GiHVx3HHHuc2cBXZsyIDAHOJ8YCrYig2/nWNiPMQR4uUPpwXmR/iFbKwiizztdms8A9jq4VkHHtSFMH4n9QLxobB9Gyiyh6HnyDjoxP7Ze27cGrAQGC4ERtoGJKYC6NR829V+qzYg5t2WGBNRNT1TOboNj3nWJWZQXHXdPPISiwlUVd5NBU899VTChzQHthl6Ood64yMyseVNqoo0bFIGvz/ao9GGGfG77ZYZkNdrsvAakaKxF2NM5iVXWCcWYvuGLRx1s6ky2jkmol6bc0PsMjEGKzEmI1l33XXTMqJsk9KDKM6mMk6IcGxqY7cn5P5IXMcujujazVIv24BUGzoMFPulyQoBIdBuBMwwtzBzdLv66XT7jcaJmzsSDDy98oTXGwkGCTy3zTbbVHku4fLd7WoXVAF87EUvP72qc+yZLCdSGlIgWwGvPigGTOQ4qmaxEWuWCBqYjRBc734kMZYOo6pKO8eEzR5u/JEIJ4BXHxGNIyEVsvxcrn5C4rPOOuv4PcZwhDvuuCNW8+tIZqLnYnqhzw/EgPT5Amt6QqAZBNBHn3LKKeHYY4/18O/2NpbejsqBuCwxbDkidTZiyi666CKvB3NA5miuEYiPeyB+cAkEiK0EGY+xFyDcPrp4CLf02BbG1BBt0TYfRNexrKh93MoZM213mr7zne94bJ8iFQJxhXD5J9oyGZuJQZQlbL/45Kke7mBHTCHczjEsBmsMZ9n888QGS3RhrlO/k8QGbEk8XS1S1A+MGJsyEZ9R40Dnn3++G1+XUfkWtVmmDMNr1F/LLLNMVfV2jilvy4VRPCEaYCQioWaJUadjWYz/lGdETXLi/zdkwx4Uqv5PGJSZa55CQAhUIMAPJzrtjTbayPMZ8eNpruqpcSXlMB8xrQDGubzlE0cHpgXiRxWdNm+6/EBbAkf3LONNEaPLE044weOuEFafKLirr766R7zFgG/uuef2gHDm4u5tsUkRF4UgcRgd1mqfcjb7Aw880G0LvGKH/iD9IH4Pc6lFYMB42HzB5qqrrqpV1cvr4U68nfHjx7tUZcKECQHbB96qiR00evTodGOnIRg2ghxiAEtwRdJAEOm3UwSTQ6qEvJF27A/bGMv07fYwSC+wfbDM1wGjzUZGrbGNZr9hwNjAd99998JbOzWm5557zteJ4I/YA0UqspsjFxnPSD6HF/dwL7nJBoaa1Td1Q33ZgHTDKmgM3YxAszYg2FSY6LgiM/BDDz3kOnQz5EunamHxE3PzTs85sISAif3wpmVFGYIfffRRb8tyrqT1yAZtP9Denr1NJ7a5ex1i2UQygz4vM+lJLPKYLfnM1Oj8zQiw0O4ivbHgoFkbEPqwzcFtGQqaS4h/Ewn9v0lJ3C4ALCGTCiX0GakM7sT6oU9jyNI4MBEXkzB5U9gfEEMGHCJZgD2/zxiWWNTUt6kx/H6TXlTdR8wa4tJEwg4hn206XsNehvETR+mcc86JxS19EyOItopsQLCxwG4lZhk393ivm7UBiZ22c0wmnUqM2fa+GJu5wMduCr9ZR5PqFV4zRt5xYp5lSTYghrpICAiB3kUANQf6dSz1IyHGJuYOVv4xQmu81ug7r56ILudZN24SMvJGT+wdwt43Q0Xtk/Kg1tt4M23XqxsTPM4777z1qvm1sWPHuh0CcWKQRqCWylMZ3JEWMF/UOqh4IFx/oaiasoB1HlcIqRVSDz64q3KPMX9et11/cCk2JqrQxiLfB5GjyemEOg5pAFGHowQtX3eo50RFxpOE56oetXtMqE6Q0PEM83zjDYMXURHh1oy0D8+YIuL/D5Vbu9esqK9uKJMKphtWQWMQAiOIgL1pudFkUU6emOQwqkDKDjPPINS6L7qqNptOvGz7tfpttZxx0ndZFQJqClRXRUapQ8E92hXQBoTdDBsbdjTxg+qHjQxX1HYSKjFUKribou7g88gjj4T33nvPj1GxQIwNo8toXHn33Xe72gE1ES6y7STsYSzCtQdzjGNifBBGspRhZ9TJMZlk3pkP+oxqRI4jgRH2OXxqUfwfhCkfBPovOz0IM9UchYAQKESADRWdNFb5xKiImxuVzb3S7+F6M1SWQTB3T2+W7NExkFeZfsq2X6atZuogJWITI59T3Czq3c84kSCRjBC7EFPFpHYZ7cSdNaNtDEOJTdJJggnDKDZLSHkwkCWJJMaf2A4RfIyNNNrLYOMDI0Ck5ksuuSSsvPLK2SaGdEw/SINiEksai8wZMUeQSJj6xzHq5JiQTI0aNSrkJWRIjWC8sHuKnkBFE445trCdGgSSBGQQVllzFAINECibrRcVAG+69YiNtWzmaN6WV1ppJf/BjuqFdrZfb5ytXFt22WX9NoJr5YkNj004T7hlwnwgXo8qnFinLO6xfq1vElPCFFkOq4oqbHwx2WXFhSGcIFlhE89+cElGxUIZ3k4QBqd4hmRVT0hpiAIaVUdDGEbFrTA82fFwjMQBwjuKcyK6dnpMMGdgjrdNJJ4JVGMYamdVnEhk8p5MlPH/g+pzEEgMyCCssuYoBBogUDZbLz+suLzikcGGxzeSC/Tq8e2NTQb7A8pi5ujYPRtAJDwHkLrgeQOhjlnYxNi4sSIZQe3DmzKEGJ3NDCpqn4idbGxmHOl1OvXHDG498ml2HrEvNg/mVMRA4RGEbUDeBbcM7mZY6m/z+QzJ9BuzWeNlxFvzvvvu655GMDq8+RNXAi+aSHjQgJMl34xFNb/jehbNp+ZNmQs8K+SCyuYj4pnBk8iMmdOa3TgmBgd2ZNmu5dp93XXXuUQjy3QiZeF5jpJDJFLMlVDrPNfYzvBBNce65BmNJ5980pmXsiq+FMRePTCuvefIfqQUCbXnVk0DHk4EmvWCYWyNsvVSB28Lcx90i3+ifZpIPTFjy8TeLhMySkPmDlqROZoy25z9nrXWWivBOwMPC5N8JHiKZAkPGDJOm3rDPRpMjO9eMkSTjJ4kRe1Hj5M4hmyb9Y7xSDHVQL0qVdfMtTQx9+OKcmOUEguj7XMkW7NJdiquxxNzsazwgqG8Hu54teDxYftLYmL9BK8XY3I8izZlJvlIzJ7Cm7eAX4kxcV6XayatSSy+SOzav00F4NfB2IwdK67FE7xIzKDTcaEd5nrDDTfEy4Xf++23X6EXjG3SnqnbQtB7m3iAkJ06S2XGRP0yWbiz7Rqz43PNe8GUGRPtmAGv34/HTBERAZbnFO8xY1Y8wi3Pa5YsN0y6HmCZ/ZhUJFs1wfOFrN141TRDvewFA2fdcyQGpOeWTAMeZgRaYUAYIq6MJnlITDKR2JtvzVGbCiK9hptonkwMXeESGxkQNmA2BpOOeF/5+zinvRjG3N76E1PnVFXLt08F3C6bpVYYEMbHRg8j0ArZG3XVbWVxr7qxoMDeoj2UesElL2Ltdt5551qX217O3Cz2RYIrdi2mpxvHxPNvQd8S81ypiQnPJgwbcxwqmcQqsSB7TTfTywyIjFCNJRUJASHwXwTQP+cjPBZhkw2wVCQuzuq68/cTDCoves7Wob3YZi2DyqL2syGws+21+5ixocIgyBjupXm1SqP+MMbMU1nc8/cVnS+00EJFxWkZmVnJyDpcxNwwPK1H3TgmwsWjHiJ4Xi1i7Ru5/da6N1uOuhEVHe7Ug0SyARmk1dZchcAIIRD15Bjo9QORtXSLLbZwmwt7++2ZKRHPBeaNGCXdQt04JrAho/ExxxyTxl7pFF7YO2Eoi3vudNNN16luurJdSUC6clk0KCHQPwhgWIe0ACIoFWHCLVqkGyj28iyRIiy33HIeOApjy14gpESEcO8m6sYxgQ8BxoaDeHbOO+88934Zjv66qQ8xIN20GhqLEOhDBIiLcOqpp/onTq+WaiVe75XvfLyHXhm3xtk9CODVNagkBmRQV17zFgLDhABveL0iIRgmSNSNEBAChoBsQPQYCAEhIASEgBAQAsOOgBiQYYdcHQoBISAEhIAQEAKT4XTcazDgwofhUhl3wV6bm8YrBNqBwO233+7Gkauttlo7muvbNkjWZgG8wpe//OW+naMm1t8IkOTPApi5y3CPzXRSTzIguEYBukgICIGRQ+Cee+5x2w68WkRCQAiMHAIWYTaQj6fHqDcZkB4DWcMVAn2JwJgxYzwvS7304n05cU1KCAiBdiAwSTYg7YBRbQgBISAEhIAQEAJNISAGpCm4VFkICAEhIASEgBBoBwJiQNqBotoQAkJACAgBISAEmkJADEhTcKmyEBACQkAICAEh0A4ExIC0A0W1IQSEgBAQAkJACDSFgBiQpuBSZSEgBISAEBACQqAdCIgBaQeKakMICAEhIASEgBBoCgExIE3BpcpCQAgIASEgBIRAOxAQA9IOFNWGEBACQkAICAEh0BQCYkCagkuVhYAQEAJCQAgIgXYgIAakHSiqDSEgBISAEBACQqApBMSANAWXKgsBISAEhIAQEALtQEAMSDtQVBtCQAgIASEgBIRAUwiIAWkKLlUWAkJACAgBISAE2oGAGJB2oKg2hIAQEAJCQAgIgaYQEAPSFFyqLASEgBAQAkJACLQDATEg7UBRbQgBISAEhIAQEAJNISAGpCm4VFkICAEhIASEgBBoBwJiQNqBotoQAkJACAgBISAEmkJADEhTcKmyEBACQkAICAEh0A4ExIC0A0W1IQSEgBAQAkJACDSFgBiQpuBSZSEgBISAEBACQqAdCIgBaQeKakMICAEhIASEgBBoCgExIE3BpcpCQAgIASEgBIRAOxAQA9IOFNWGEBACQkAICAEh0BQCYkCagkuVhYAQEAJCQAgIgXYgIAakHSiqDSEgBISAEBACQqApBMSANAWXKgsBISAEhIAQEALtQEAMSDtQVBtCQAgIASEgBIRAUwiIAWkKLlUWAkJACAgBISAE2oGAGJB2oKg2hIAQEAJCQAgIgaYQEAPSFFyqLASEgBAQAkJACLQDATEg7UBRbQgBISAEhIAQEAJNITBZYtTUHaosBITAwCEwceLEsMEGG4T//Oc/6dw/+uijMNlkk/knFk411VTh9ttvD8stt1ws0rcQEAJCoAiBSVMWlapMCAgBIZBFYOGFFw7vv/9+tqjm8QILLFDzmi4IASEgBCICUsFEJPQtBIRATQQWW2yxsMIKK1RIO/KVp5hiirD++uuH2WabLX9J50JACAiBKgTEgFRBogIhIASKENh2223D5JPX/slAJTNu3LiiW1UmBISAEKhCQDYgVZCoQAgIgSIEXnjhhTD//POHWmZj0047bXj11VfD9NNPX3S7yoSAEBACWQQm1X6dyVbTsRAQAgOPwHzzzRfWXHPNQinIlFNOGTbddFMxHwP/lAgAIVAeATEg5bFSTSEw8AiMHz++EIN///vfUr8UIqNCISAEaiEgFUwtZFQuBIRAFQJvvPFGmGuuuQIMR5Zmnnnm8MorrwTccEVCQAgIgRIISAVTAiRVEQJC4H8IzDrrrO7pgsdLJJiOrbbaSsxHBETfQkAIlEJAKphSMKmSEBACEQHUMHi8RPrwww/D1ltvHU/1LQSEgBAohYBUMKVgUiUhIAQiAv/617/C7LPPHt577z0vmmeeeQIeMkRFFQkBISAESiIgFUxJoFRNCAiB/yEw3XTThbFjxwY8X1C/bLPNNmI+9HQIASHQNAJSwTQNmW4QAkIAlQuGqKhfsP8QCQEhIASaRaAqFwxi1WuuuaYi6VSzjaq+EBAC/Y0ASekIODbjjDOGRx991D/9PWPNTggIgVYRmGaaaTyZZdZ4nbaqbEAuu+yysNlmm7Xaj+4TAkJACAgBISAEhEAFAn/84x/D5z73uWxZdTbcmG67Vrjl7N06FgJCQAi0gsA999zjye0efvjhsMQSS7TSxMDcM8MMM4Qf//jHgVw8IiHQawhMmjQpEEU58hbZ8csGJIuGjoWAEBACQkAICIFhQUAMyLDArE6EgBAQAkJACAiBLAJiQLJo6FgICAEhIASEgBAYFgTEgAwLzOpECAgBISAEhIAQyCIgBiSLho6FgBAQAkJACAiBYUFADMiwwKxOhIAQEAJCQAgIgSwCVYHIshd1LASEgBDoZgROPPHEMO2004Zdd921m4c5YmMjWu1f/vKXsMgii4Tf//73Pg5y9hDriTD6WbrlllvCs88+mxbNP//8Yc0110zPu/EAF88HH3wwjB49uuHwLr744rDwwguHT3/60xV133nnncC1J598Mnz2s58NX/jCF6qwqbihxMkVV1wR1ltvPX8261V/9dVXw1lnnRUOOOCAimrtHNMbb7wRzjnnnPD00097MLB11lkn5AOCvf322+EXv/hFeOKJJ8Liiy8evva1r3mgwTioyy+/PGy66abxtG3fkoC0DUo1JASEwHAjcO6554af/exnw91tT/T35ptvhhNOOCEst9xyYd555w3LLLNMOPjggz10/p577lk1h2WXXdYZEDYfNvVPfOITVXW6peDll18O++67b1h00UUDm2Mj+utf/xrGjRsX7rrrroqqDz30UFhxxRUdn29/+9sBzNiAb7755op6ZU+uvvrqsPLKK4dNNtkkkLSxEe24447hlFNOqajWzjG99tprPh7i7vz9738PY8aMCauuumpVf0suuWT4wQ9+EE466aSw0047heWXXz7A3EUi4STlMLRtJQs4VkHGCSbWQUWZToSAEBAC7UTg7rvv9t8ZC0Q2pGbtTTF59913h9RGO27+6U9/2o5mCtuwkPfJeeedV3itVqFJMpKNNtoosbffiipHH320485v/E9+8pOKa5x89NFHCf1Z0Kiqa91UYFKdxDZVn4sxU3WHxjOywQYbeN3TTz+9oq5tyMkOO+xQUWYB35I11lijoqzMyVNPPZXwsdxI3pdt/nVvM8lHYkH4EtvcK+q1c0zM16QsaftHHnmkj+3WW29Ny+gPLKGXXnopMabI63z9619P63Bw7bXXJttvv31FWZkTy5Tt7ZmELV/9BUlA2srOqTEhIASGEwGihJKddyTpd7/7XTjwwANHcghVfe+9994uMp9lllkqrqF++cY3vuGZjHfbbbdw++23V11HTTH55N29NayyyiqlJTSoNw466KCKecYT2xzDP/7xj3jq3+Qtef/99yvKypwsuOCCgQ/4NSIiAP/tb38LG264YVXVdo3pgw8+cDXQ7LPPnvZB5mpo5pln9u8777wzkFgSiQc011xzBWNSfP0JnZ6l9ddfPzDu6667Lls8pOPufsqGNDXdLASEQL8jYG9sATVMlp555hkXa9vbvIud7a0/nH/++YHzSNg6EN7cXsncNoJN6rTTTkvF5mwCP/rRj8LJJ5+cblAwGpzzQZ8OUbbxxhsHdOhnnnlm+M1vfuPlr7zySjj22GPDiy++6OfD+QebD1QBX/nKVwq7XXvttV3cziY7duzYClE7N0w5ZbVpIPO76KKLwuGHH+72BGCcpTKYx/q//e1vA2sC/thAdJJQz6BeQP1URMz/z3/+c/j5z3/ul7G94J699tqrqHpbysggjSrsuOOOK2yvXWOaeuqp3fYn28m9997rTA9qOQhmCZVblgibvtJKK4XZZpstW+zH4LL//vtX/C9VVWqmIC8TkQomj4jOhYAQaDcCQ1XBmC46mTBhQjLTTDNViLCvvPLKxN7iXORr+mwXGdtbpp8fc8wxPg3bbBL7cU1McpLsvPPOCaLmL33pS17HDBQTe3P0evG3MKuqOOKII7ze9ddf73XsLTZZbbXVvE9jRhLOobPPPtvr/fCHP/TzofxpVgVjBqbJuuuuW9glGPzyl7/0a6gabK/w8cc5c8HehivuZa1sw0ouvfRSF9F///vfTywLchLVTmUwp0FjeFy8f+GFFya0aQxSMueccyYmgajor+wJ7TH+WiqY5557LjG7D2/ObDu8bl4FY3YOycc//nG/9q1vfSv54he/mFhC1rJDKKxnzKy3V0sFY8xHctttt/m99JlXwXRiTKjWjIFMll566cSYxcJxZwvNZihBXZOn559/3udmRrb5SzXP66lgqow94j9dzdZ0QQgIASEwRASGyoDE7u1tseoH3N7Q/EfS3rRjteRTn/pUYm916Tkbk6kjEjPMS8sOOeQQv++MM87wMq6xwWUZEDZbyiIDQkUzOEw+9rGPpe1wgN3BBRdckLz11lsV5a2cNMuAYFdgovbCrrIMyHvvvZfAcDEfGLFIWQaETd6MUZNDDz00XvZve2tO7A07ZR7KYA7jcthhh6XtsBHSt3mLpGXNHNRjQNhwscVgM4dqMSBcw+5hscUW87FYttb0Hq61QvUYEPNESkyKlDZbxIBwsZ1j4lk0A1K37QHvWWedNcGGphb94Q9/SBZYYIHEpF6FVWDe889DYcX/FdZjQKSCsRURCQEh0JsIoK/PU7QJyXpx2JtfqjahPrYjqBqyonlEy5S14gGBbUWWaB/RtklossUdP0bv//jjj3v20UadgZ297bsHiDFdrlrJ34O+H48Y3FOzhIspfeHeCZXBHJdp7B6wPeGDisqkDwFPjXYT3hzGgAS8NxoRc1hrrbWCScLCn/70p/CZz3ym4llpdH/Z67jDouarZY+SbaedY+JZxNUXNRq48F3LbZ2MtcZcBGO0g0m5skNKj7EreuCBB9LzoRxUK/uG0pruFQJCQAh0IQLEPbAXsrojM0lDsDe/gItns5RnQJq9v1312czZRCJD0KhdYn2YaiV8/vOfd6YAV9ws3X///X6a34zMS8TL621EWczZfE18H3A7Ne+cbBdtP8ZQ8le/+pW76cJgQeYp5d8wQJSZpMOZNFPjuW3LHXfc4cynqdPC//3f/zkW0Z7Hb2zDH5N2BIxn2dwjPfLII8EkUT4mk0wE7HM6NSYMi7HhwLgUDEyCFPIMPK7NGDDjmlyLeBay8WJq1StTLgakDEqqIwSEQN8jwA8ysQ94u2+WuoUBId4HGxlvuWWJuBCnnnqqb7wYQGaZl+hBgWQgMh20u9BCC3mwriJDxaJ+o1fNfffd13EGhM0RI+FsrJPIfJqJgRvoImHA2NLsWDw2RjS8RQpCzBCuwzSBZbsIxvbGG2+saI64IzBHjBVpHAxIp8dk9kFuPJ1nPpCSwHh8+ctfrhhj/uT1118PSBTbQVLBtANFtSEEhEDPI8Amy9todI2MmxJl9QjmA6lDtxAbGd5BRYQHBoxWnnDNNTsQl1KwKUZCHQHl1VIEtaItJAllCLdPorGaEWjqaRTvwwMlehXFsqF8s4nDhGQ/SBog1D6URyYTrxAYjSzh1YR6qd0eTFdddVXFmBjHLrvs4q6vHJtdkQ+j02PC7TgvhcLzByYtuulGPMweJB76N55k4GI2MxXlrZ6IAWkVOd0nBITAiCPAZsqGmY3QaIafPi42kUi4xVI3vglTzj1ZFQKqCGwBIgOC+yZuiuY1EizAlNtCXHLJJd4kovzo1subNJITbC8ee+yx8M9//jMQX4GQ32Z06PWH8w+SCiQNRcRG96SFHC8i89gJq6++esWlT37yk8G8ZZwByTIJFsgqmLGrxxThhjKY77fffr4BwyCACxiaUaqvH/EzIsEMmVdSQwaAN3GoEYMY2y36JmIpm29cS+rglktcDOYXqeyYqD/UcZUdEwwzz5h5XMVhVnwTiRV3Z5jFSLg9gzu2IJFwi8YlGIYSGxU+RGdFFQUzlCXzLPL/m0ZSkuw9dY/tH7KC5AVTAYdOhIAQ6AACQ/WCIfopLq5zzDGHey9YGO3E3swS29gSC8/tZUR0xAIft097A/cyPBDshzaxH9fEbBSS3XffPbGNMfnqV7/qkUPzXit4wOA1gNspXhXRQ8B06YmFzHZkcL81aYnXi263uKyaZMTdcYcKX7NeMLh/zj333Mmjjz6adm2MR2LB0twTAszw1LANKr0eD/AaWWGFFeKpf1PPjEYTk6x4RFYwIbKoMSR+vSzmeKbQL1jZpuTfeM/ko65GjxQLDV4xjuzJNddck2y55ZbeDnPF7Zm1rkXGFHrdvBsu5URCNduXxOK7uJuwba6JMZMVTZUZE9jh+s14mB+eSDfccENFO/kTnr28G27ZMVkKAu+H5xO39Dzh/WIqFX8OzfYkwcvLGIsK7xZjlBMzUvV2GHP2YzmWKqKo0j6eTLidN0P1vGB4I6ggMSAVcOhECAiBDiAwVAZkqEOCAbFkbN4MGylumrWIDTgyJiZVqdowuc/E+Gmd2E69NmOdMt/NMiC0iSsxTEMrBCNXRMyR+BVl4kgU3R/LYB5xcWajLSKTaHjMimZiTRS100wZYzGD26RW7I5uHBPzw10360JdNGeTyNTEuqh+rTIYSMtzk5gRa60qheX1GBCpYIzlEwkBITC4CFgMjzQ0dREKZNuN7rRkkI0Gldm6uCbGOrE8hruO58P5TeKwKG5vtl97gy+8hTlisIqn0FAII1fsVPA6KiJUZagXUMMMFzGWpZZaqjD6J2PoxjExLjxayN5bjzCkrYV1vfvy1/COMQlWabuf/P1F5/KCKUJliGXo0jDawuiIhyP7jzQc6cN5KE3051bq9I+esB6hByd0M/reRg9zvXbKpqDOt4F1OHrISFhYM5ZahNGYJUZKL5MRMxrLpYUtHKC7zec5wMCQ/AhsUtgEdILQrYM/dgMm3k67wKbgu9/9rudmGOqPftpo7gBviVppuHmG0flmiQ2YDQq7h6yOPFunF47xPMAGhNDbeRfTXhh/ozHCJFkCu7DHHnt4FlPcP3uFCCVvAdMKQ8KP1By6cUzY3cAUjh49uuOwYCNCeHa8pNpKeZmJVDB5RJo/R69mRkuuT0M3mSX0qLZZZovaekxYYnsoEzPq8v7RQ9vDU7MP9MTf/OY3va7l1KhZr94FY7Q8yqQ9mDVFmPXu5xo6anTPtAFGiPtqUTajJzr3KB6vVb9sOX1aPIDEYiP4OFhDyweSWNAe19MyvokTJ5ZtrlQ9YwASYwCSUaNGeb/Zm8zg0ceBvrsTZAGmEkIuEzmTqJZgj6476tIR3R511FFeznXE+pa/I9lnn31ct2wGmokFVUpDlzczxpFUwRCKHb0782VtzSivmaEPe91WVDDZQZKhVSQEhoIAv8+tUj0VjGxAWkW1wX0xVXSeAcEwCB1oJwjDN4zjMEhiMyUUtfnxu7GXWefX7BLdJz/GGDU1S82moK7X/ne+853E3tx8LDA1RYQOntwNJsb1up3AMhq33XTTTekQ0Htb7AM34kN/3W7adNNNqxgQ+jDpULu7Stsrk4Y7hss28XR6Hwc8XzBIGHea1KxpJnAkGRBsGWCu4qcTz1AFWEM8GSoDMsTudbsQGBIC9RgQ2YDYztsJijEEEOFnibC42UA/2WtDPUZvalbKgQiE9LvOOusE20xd1Eykv1oUddrxu1a9ovJmUlAX3Z8tQ5yIDz50/PHHZy+lx7hB2sYZ0MuDcSewLNLdowLBPQ7RPe6a7Sbmkn9W6MOSdbW7K28PdU+ZNNxFWNAAYyXbKsGLCK6E62fW7bUjg25Tozxn6MXjpxPPUJuGqmaEQF8j0BYbEPyN0f/jG0wAHBMZBxMpe7ATNkMClxB+lg1u8803rzD44l58wu+66y7fOMePHx8ID0xgH9I/xx81dPAYCWErYG9fwcTh/im7Ovi/MwYCvxBchaAv9GMuWFWbGGO55ZZbfLOxJFbBMiRWbQ7ozpkn9hOMjTp8NyLwwTaEiHsQemhSeoMNQX0I/2vufcHcAqtsDtBXk1YcmwH079h2gAkYQ+aKmB57gf0hpgHBf/IRC9HvgzvR8JgjVLQB+oUh/sHPnnmy9o3IMnkGkx65DQ1617z9ChEbza3SowUWtUUYZvz48V8nrLJJFrxaO56naMjF8xep7HNQ5pmKbcZv+uFZxUYh6vBNIuFhlNHtEyab/zuYQJiJPAOJLZBJcTz2BTiaBXswF0xv3tQn6brH/mIa7sg8x/J63zC4Jjnz/wWYXDAXCQEhIARKIZCXrTRrA2KbmOuQrbMEv2305vg2IzYkLTQqCPtxdD972+Dc1z72if4bfTt+9KgN0Dcj5o4iUXT7ZGak7ejTboFy0nTSsZ1G32XTb9MO2Qm32GKLBJWFbRr/j70zgbtmLP/4bQ0h+06vLK1KQpZClrKvZclOtiJLyfq370r2soRCEmXPFokUUkKFIlS2rCmhbf7X98o95syZM2fmbM95zvO7Pp/nnZl77vU38577mmv18c3IJ7FARukwiI/L0lNTkRTTzBufeYj1nXtuY/pwXL6IP0A9MCLDJPYY6KdtM2jwwaauGUEmxjh4pk1E9rTDvxu1SytCb0/2wqxLIPEAiJGAOsiCEiVgSl/YInRKZRkgecbEHmhHMVMndhfMh/cnSxb8yJ8NZawJu4Qs4YPPs0I98Oijjya2ybrNQqxT9X0icyTjZ1UwqH7Ipko5sSCgKu8B9aq8U8aceQZK6kO8P6QrZ7wYu8AY6Lap5v/XOvEYGaShx32Q/6NgBWZkHsVGqRXl03Dz3jCHvAom2z6mqOf5VaWxVMFUneOw1JMKZliehObRCQJlKpie2ICYZ4f/SKETjhTTM2OXEAmDNfviTv3oYQzsqy1Nfxx/lLKpgvkhpg2MjUkHaqUBjuNyrJJ+22Lwu04bHXEkgg3xA0x7yNyxKqWnzjMgsb98+nBiDNC/JYPyAEnUY6OhjPVGYoOHOYvEJkIdNt0yol8C7ETCoJEATFmGhHXTV78YEJNIJDAP7SgyIDCgpnrwd8NCKKfN2JDvvPNOvy5iQBZeeOGG2AekSTcPpLQ9J1Xep8iA8H5iH2OSuMQkXP4eRryrvgdV3inmlWdAKDMpjj+XyIBQFv9fYd8TKZ9qnmdLECEY3kgWetkDZcGctaIYZIsPg0hVGBBLbOXzxKakKsX/67x3+ivHgA83YVSOkfAZfnxMq5D/eXiqJyoYdKqQSQX8yD+kWYay7pSkx8afmqyI6NRJl4z4n5TJ9qXm4mbaELc/ipxxySQ98IEHHhjsq9ZFvdSpS9heIFrG/zwS6bfJDYA6grCztlEH5hjXQz1cL8lhYJtRsC9zV1u0Sk+NOyNJjEwSFIdoOuYTAGHLgOqD2PpR9B0T/aBqiUSIZ9xVUUnZ16zjypoQybcixPOI1U2qklZhvbhTZXX7Uc3RLxVMXRdZdPKoGAjTjNuyeV54KGzWH+eaLihzYl/6nmadItQTYIOrWpbqvE+oAFGBYIeBvcOFF16Y2mSUpSnPvgdV3qnss8jONf+ucC/aK+RTzcc8EtTBdZb/T6gdIxG/AfUearx8vArqoKJql4Y79pU/0ifE+1iXCPnMOypqjYB9/HgWWZPuta6kO0JgSBEgbIIJEApn1xMGpKjnoh9PYghAFnXOj+isYT744WMjjkxHVsdORWwbiI/ADyo/lHGj9k66+AedPowQG5uxZm7PwQ91njCwg/mB8WBjg/KxA2KmyGxuiXw/Va+jTQdzikS6bFOPBXIwkEuBmBUwI63idsDEmVutt4l9cMS+gs00S/1iPLJj1D23KI6en4BYBibi9/wEpJIuI2x6iH+CjQ05PWDqMLbMU9X3ifTZ4F5EVd6Dqu9UGVNVNHa+jPcl+67AnLCpgwWMO4Qd1jLLLFPIfHC/Shpu6hUR9i1QXUaTNhgUj+d4Iqyh37TNNts4413Fhqrfc1H/QqAuAuRJakV984Ip29TiPTZ10v/yA2x2CZ7iuWiifNny5QoDwGbUK0IaAzgEsmJOJtYPGNLB5GQp/kByP5ueOlvH1CO10lNn21Y5N5uNYPEX3IgWTxCYNqQZq6++elNzOM5DDjnEjQOzjCCGoHhxmBqjqQ0F8bkU3hxwIcaSGOpipHzMMce45KldAiTLdeCBuwiagzFrZOTyU+/F+1TlPaj6TuXn1+0148KEwbCTAIxkamZD5RKcor6rpuEuagvjg8E2WLdihovaqUwICAEh0DcGpAq0bJJEDY3ZJ/OSD/pgM2VDwfURD5bjjz++8Ku2ynj5Ovn023zB4dVAtsAs8YVH9MdsxE3UNlmqm54627bKOVIfvmqRapCp0WwRnCHJt4XB4Asf0XZWlWSGQJ6tE68Zs4Nom2ky3+8grnkXYAojEfqXjQ01zLbbbtvk5RHrcYSZJWoo4uqopuj0fcpKE7JjZM/j136796DKO5Xtt1fnSPdIrw7jiuge9Qvvb56qpuHOt4vXSImQMvH/Mqtujfd1FAJCQAi0QqAnDAibNpTdPKJe2Lw30rGj6gX9NMQ1GyPurKTLRtcPYSMC4wFhC8DXPl/yfAnz5clmxJdxXUICkFWRwNRk02/TP+Pg6hqJTQxGhXtshvzIVklPbcZ73kXEIfYHRtxjLhD32fCiuzFlYAFl14gr7aWXXuoMG3WxD4m4e2X7hw0c9Qo2C3z1xtTKhx12WMC9GVsWC/bl1cGVubA+bB0g1Dvkj+iEUAlB8dlm+4BxNA+fbFHhOV/s5pWT3mO+iJ155tuYGDoSEirWDg5RvBdxZt3YffBVDnPAvLgXsaryPsV3LzuXOHY8Vn0PqrxT9Mk7wf+HLPMT/z/F94F60aYl/75QN7blHm7h2GSwbjAA23iffiBc2mHueW/iu5JPwx0xyL6LtKUcNRkp3MEURkQkBISAEKiFgP0oNVBdN1wy49mPsVtp28bsaYxxq8Uy3ybiaZvxPKCe6aC9DDdXi9fgZXh22Kaf4FZqm6q7OuLhQMhnUmXjwmlMg8+RLI2kAqZfUz0kWQ+JhkUUXFRNv42lLu6buLaaEaenVMYtNEv2Y1yanhpPDdwdmSfpkPE8wbMjnz6clM+ETqce7o94vZgBoWNBGbjefffdPrR9qRamTV511VXT0NnRpZe2+T+TiqRLsK9Vd5PGU4LshqRYxk2W7Jm4HtehKimocaUGU1yRi8g2x5apwvH2wXsqkjEViTFT6frwconh0U1l41Ff8YbB/dgYNnc/NZsZdzdu9z4Rhh1XcFKvgx+up8ZApF5bcQ7x2O49iPXK3in6wLPGpDY+pjHbnlYezyG8fpgHqcKJDGuqo0qp5o2hSFZYYYUUo/gumEQsMSNpnxa4GoPSVIe6vBfGiLo3lklP0joWp8ajnpKK3QLGeUh2MOuEohcMvwOicgTkhluOj+4ONwJlbriTMXX70UkJ+wJjEJq+ltIKPT7hC5yvq2hBz3T4IsPTo5eEOBr1BV+HeEegnmjlfcAcCGjF1yOePVk7iuyc+GpFnUEgqH4lC4vjEW0S7waL2eFf/aha+GJGKsIc8eipQ0hgkB4wb/Bmzb3GPM6Hr3PsEvrVfxyHI88s6+XB2K2eX7ZdN+dV3oOq71Q384htWTPGp0gokGghNeH/GM8baRgGytEgPLYZ9BFjaIIJ8v8s2lgNeg7jZTx+G5EOI3kVCYHxhgC/O5gPIJVm/8rQ033zgskMUnqKJ0xkPqhYd6OyZFKl/XMz7wLULmIpc4huxGWdw8QUec2UtenkHjp2VBCoXVAD2Rd+2k30jkkLKp5gUxKZpvxmVBVTNpAq1G8GIDuHLPNB+SDGrvIeVH2nsmvp9Bx1G1F1Terkf9mj53e4AABAAElEQVR+UIn2yoss26/OxzcCJml1I3yiD0O8rxhy538b2ERQ50XC88ykbfFyaI4w3JdffnnhfNhvWhm0w7BjlE3a+To06PHi3Ih0jAkDGzzRs3keeeKjjNAA2Mmxd6AOx0YMwr4RlT0f0WNBY86AdLvoVm6S2X5Jp47EgK9+7AHyLrTZusN4TlhxbGVwRTaVi3sLoYPnx4J7df+ztFtjVUzb9aP7Y4MAXk68LzAhuOTCcMDEEpodxprNRSQEIgIYKMNoEB8IqSrpC0w97EbM2J5lydSBnuoAQ3ds88g3NYyEZHirrbYqnJoF5WvJgGC0jc1f3d/UQY/HwrDfIj4VH8HEKOKZkG7EVKTpuknrgRE6H2aWONQ1ANilYe9nan93aMCGi5hcY8JImmi4geragDQ0HtILIlqOp/TbeRhNTeVh7tHH2xe96+6xpznjjDM8Mmu+vq4nNgL3339/YobaHjnXmA0P8U4kYcqHhcbaBsRyMiXXXntt3+DoZf/9tAEhfUbexu3II49M7X5iKoksUPweMSczBs8WD9U5EadJpWBf//4baWpJP1q8psRiCxXO1SQfnlaEvaIuDXo8UoWYwX06TdaJjRc2gVmqkvEa2zzqEXm5H1RmA4Luv4FGkQExr4Y09bZ5BKS5ZhoWPk4uzIZlnMxU0xwGBPjhHUYaSwaEH1x+qLMh7nuJUa/77xcDAkNqrtmeOym7flIiwLCa5Mw/eDCIzpPFZcoXDc0173w2nUecGAbzfMCRVytPpNwwbz3P21SXARn0eMzdYmLll5CYmj6BEYqEAwMf31kyD1NPcWGS0WxxYjaG7iTSUNijizIGZNyrYFJZU8kJOvpRobxOdlTWpXX0B4FBGP72Z+bFvaLPRuddlIUaVQIpC1CxIkqnLpl6MbJGR07mXtssPHMwLsjE9kEdhT0A97FtKMuY3W3/dbJCF6++t6W45GMPUKSSI9oyaStI42CbmqvwENlHKrIjKns2tEMFbh6SlTJ/E4qBdAc8EzIs11H18M7HqNpxvhwtZ5GrGQgomSXeD4y2SaNB+oe6NOjxmF/eRhFnDt59glNGmmQ2YDHTeSzjPUfVln9+qPaJNA1GPO+BUZ7JGUUJSH6NuhYCQmBsEehEAkKbdlmobdNsyCpsHkCeYBIXYghpKBm67QfWs3YTMgCpKF+KuP/jDm0ecwku3bh4U88iNSdR8thp/4xNSIEqWaGpm6V+SECQfrC2oiSRMSkkcyC0AvUIfxAxoBzX+iy1ezZIHWKYgHaZv1GdkBCSkADsR7jFm2F8driOznHHxz0/T8Z8JLfffrsXk7m6rgQk31+8HtR4hDEgk3o21EKcQ9Exn/E61kHqRfiMXlOZBGRCqGB6Daj6EwJCoDsE6jIgiLkRGxMnJUv88NoXqGc5ppzYKebdla3iP6qRAeFGHDvGRImVq2TM7qb/qlmh43zisR8MiBktOmNBLKI8ZRkQCyzoDBhMCIxZpCwDUvXZmKeIj2lG7i0zf2PLgFrInAXiUMn222/v7cw4NC2re0IMKd4T1DBZIraOReROi3rFgAxqPFQnJg1xfHhGMHdlVJTxOta3IISuduN59pLKGJCeREK1hYuEgBAQAn1DoCz7MLF9EJ/XpbzqAfdMRNP5jNmU5UPuVxkr3z9h+VEnDAPFiNBZtUrRvHBjRyxPPZMeFOJc9dlUyfx90UUXecwaPDqIY8MfcSRILEk+o04J9RfJGE26kXZBxGMiAFugw7SsVyeDGg/VCTnScLElLALeMNdcc03hMoggjecSasYiT1BMFVCTdYNz4cAlhRPCBqRk/bolBITAOECgSvbhusvIMwhF7U36kGbMLrpfVlal/7L2/bxHBnDmB1PQjogtQdoK3PNhCHDFzVI3z4a4RpB9cfuRwI7YKZhnjl/36h8CbBLXJEukD8BWhA05EkH6SCcB0zXTTDN55vF4r85x0ONh7wHzAfNskrYGV9w473YZryNTgt0NyV8HQWJABoGyxhACQqArBLLZh82VMu2rmyzUVRgEjFb5ArfUCumYVU+q9F+1r17XIz4Mmz5xP+LGUzYGsSZOOeWUYCkt3EgxJnykTS+fDQwJsSswDO2VwT25lEz1EM4999yGJcKEEWE6S0Q1JmaUpcjwzRxj3Lo06PHi/GAa5plnHpdWxbJ4rJLxmpxRULtAnbHPXhylgukFiupDCAiBviJQNfsw6pKihIjZyUXGAJF0OyIoFf3FjN297r/d+P26H6UYFq+kaQg2fxivPBFRmpQWeKiwUUeq+mxi/bIjSR5hilD3ZAl1SUxWmi2vco46BG+Q/MZq+ZXcy4Yv/vhH4kwCV3J9/fXXV+m+qc6gx4sTgKECJxJRZon5wGzmA7PBlGXJbDVcKkYS0EGRGJBBIa1xhIAQ6BiBqtmH+fHlC5SvXTYyjoTXJrJn/MJDxA/BXPDDTDThSOjAo30EZfmM2d30XzUrdJxLP49syKiXzBumaRg2XyItFxHZj3P5PCpnCCcKNXhjsxMpZnomlDmEqzSMAuoCS5rpz8I8YTydBikGIsEMmZdSMGPPWNTyWKQOaVm5xY1hGw+7G1zMkdZEwg6K6KjZ3EpVMl7H9jxz3u8qarnYpuujvRANJDfcBjh0IQSEQB8QiJ4odbLh4kVhNggJrrBEsyRKJ5l5yaIdCS+KmHWbbMamy/fgTGSnxv02ksWVcM8BPDIsRLUXV8mY3U3/7bJCx7nlj/3wgmEMMj/bV3E6nDEeLbNSp5XsBE8SM3jMFiXtng1eLVUzf5tNSbLoooumnh1kg85n6TajVL9PJNcyMgbHPTvMsLKsWnpv7733LnTDHbbxiNqKe7IlVPWgcYceemiCh0uWqmS8jvXxfMFFHK+aXlOZFwwcaQOJAWmAQxdCQAj0AYFOGJA4DWJ5ELfBslrHoqYjodAjsTnmiXDibLhZggExuwMvgqkxNUP2dsN5J/3j0tqJi2O/GBBwYaO3LNsNa6tygZtpEVV5NkXtisrsizxlDvP3wfLiiy9OrrjiivythmsYHzNsbSjr5GIYxyMUPswg73K3xL6/3nrrddtNYfsyBkQqmK5lSOpACAiBQSIQsw/HbM5FY6PHj1QkUsYOpChzaGyDGsC+LuNl07GT/nFpJWrmsBC4mFTIo38SSbMOEUW2iKo8m6J2RWUYGLfK0oqNCio01DBlhGt1Lzw6hnE8MsnjVhxtmspwKLuHGy8eNLhAD5rEgAwacY0nBITAUCKQzZg9lBPsw6TIgLrxxhu7zUVdJqQP06ncJZnALWBaU0jxyh3UrDiq45Ehl/Dt55xzTsh6NtWEp+PqcsPtGDo1FAJCYFQQ4AvwhhtucCNJcqRYKHAP7DQq6ytbx2qrrRYsxL0HoRomCU3ZnAnANUga1fF43mZP1bUUpdNnIQakU+TUTggIgZFBADdbM2hN14O6ZCJRu4ioEwmLibTW6BE2VmsWAzJWyGtcISAEhgaBUcqYPTSgaiJCoA0CsgFpA5BuCwEhIASEgBAQAr1HQAxI7zFVj0JACAgBISAEhEAbBFqqYLCMFgkBISAE+oEAIaMhcm7MMMMM/RhiZPrEBZTkbK2ynI7MQrWQkUSAVAataDIih2RvktZ3//33D1XyJGTb6VwICIGJhcC9997rcS0s4ujEWrhWKwSEQC0E8LY58cQTw2yzzZZt93QTA5K9q3MhIASEQCsE1lhjDU+dTgwBkRAQAkKgJgJPywakJmKqLgSEgBAQAkJACHSPgBiQ7jFUD0JACAgBISAEhEBNBMSA1ARM1YWAEBACQkAICIHuERAD0j2G6kEICAEhIASEgBCoiYAYkJqAqboQEAJCQAgIASHQPQJiQLrHUD0IASEgBISAEBACNREQA1ITMFUXAkJACAgBISAEukdADEj3GKoHISAEhIAQEAJCoCYCYkBqAqbqQkAICAEhIASEQPcIiAHpHkP1IASEgBAQAkJACNREQAxITcBUXQgIASEgBISAEOgeATEg3WOoHoSAEBACQkAICIGaCIgBqQmYqgsBISAEhIAQEALdIyAGpHsM1YMQEAJCQAgIASFQEwExIDUBU3UhIASEgBAQAkKgewTEgHSPoXoQAkJACAgBISAEaiIgBqQmYKouBISAEBACQkAIdI+AGJDuMVQPQkAICAEhIASEQE0ExIDUBEzVhYAQEAJCQAgIge4REAPSPYbqQQgIASEgBISAEKiJgBiQmoCpuhAQAkJACAgBIdA9AmJAusdQPQgBISAEhIAQEAI1ERADUhMwVRcCQkAICAEhIAS6R0AMSPcYqgchIASEgBAQAkKgJgJiQGoCpupCQAgIASEgBIRA9wiIAekeQ/UgBISAEBACQkAI1ERADEhNwFRdCAgBISAEhIAQ6B4BMSDdY6gehIAQEAJCQAgIgZoIiAGpCZiqCwEhIASEgBAQAt0jIAakewzVgxAQAkJACAgBIVATATEgNQFTdSEgBISAEBACQqB7BMSAdI+hehACQkAICAEhIARqIiAGpCZgqi4EhIAQEAJCQAh0j8BkiVH33agHISAERhmBm266Kay11lrhP//5T7rM//73v2GyySbzv1g41VRThTvvvDMstthisUhHISAEhEARAk9PWVSqMiEgBIRAFoFJkyaF119/PVvU8ny++eZreU83hIAQEAIRAalgIhI6CgEh0BKBhRZaKCy++OIN0o585SmmmCKsvvrqYeaZZ87f0rUQEAJCoAkBMSBNkKhACAiBIgS23nrrMPnkrX8yUMlsscUWRU1VJgSEgBBoQkA2IE2QqEAICIEiBJ566qkw77zzhlZmY9NMM014/vnnw3TTTVfUXGVCQAgIgSwCT7f+nMlW07kQEAITHoG55547rLDCCoVSkCmnnDJssMEGYj4m/FsiAIRAdQTEgFTHSjWFwIRHYMsttyzE4N///rfUL4XIqFAICIFWCEgF0woZlQsBIdCEwEsvvRRmn332AMORpRlnnDE899xzATdckRAQAkKgAgJSwVQASVWEgBB4A4GZZprJPV3weIkE07HZZpuJ+YiA6CgEhEAlBKSCqQSTKgkBIRARQA2Dx0ukf/3rX2HzzTePlzoKASEgBCohIBVMJZhUSQgIgYjAq6++GmaZZZbw2muvedGcc84Z8JAhKqpICAgBIVARAalgKgKlakJACLyBwLTTThs23HDDgOcL6petttpKzIfeDiEgBGojIBVMbcjUQAgIAVQuGKKifsH+QyQEhIAQqIuAcsGUIPbTn/40PPHEEyU1dEsITEwESEpHwLHpp58+PPzww/43MZHQqoVAawRIYbDEEku0rjDB78gGpOQFwLXwb3/7W0kN3RICQkAICAEhUIzAIossEn73u98V31SpsuGWvQOImM8777xADgyREBg2BMg6+8UvfjHssccewza1oZrPxhtv7PP57ne/O1Tz0mRGG4FjjjkmnHXWWaO9yC5XJxuQLgFUcyEgBISAEBACQqA+AmJA6mOmFkJACAgBISAEhECXCIgB6RJANRcCQkAICAEhIATqIyAGpD5maiEEhIAQEAJCQAh0iYAYkC4BVHMhIASEgBAQAkKgPgJiQOpjphZCQAgIASEgBIRAlwgoEFmXAKq5EBjPCPzhD38IRxxxRDjssMMCbr2iZgTuvvvuMPPMM4e77rrLb5LzZqONNmrK/nvbbbeFP//5z2kH8847b1hhhRXS62E5IZfP5ZdfXjidt771rWHdddctvIcb86RJk8LSSy9deL9V4aDHi/O4+eabww9+8IMw99xzh0033TTwPPJEsMkbbrjBn+Vqq63WsLZf/vKXYbbZZgsLLLBAvpmue4VAImqJgOW8SCwOSMv7uiEExhIB+0FNvvrVr3Y1hUsuuSSx35LEfqi76meYG3/qU59K+OuErrzyyuTaa69NLPtvcu+99ybveMc7HK+dd965qbsXXnghOe644/z+QQcdlDzzzDNNdYah4Fvf+pbPkeee/1tnnXUKp/jzn/88sbw/yde+9rXC+2WFgx6PuVgMjuR973tfsuOOOyZzzTVXMvnkkydXX311wzQ///nPJ29729sSYzAcB2Msk2OPPTatY2kGEp7zj3/847SszsnRRx/t70udNhOs7lNSwfSKk1M/QmAcIvDJT34yPPvss2GNNdYY09nbJjWm4xcNfsIJJ4Q//elPYfXVV/dke+9///vD9ttv71W//vWvh2984xsNzZCSEBiOEPUHH3xwmGOOORruD8sF0g+kA0R5fv3119O/j370oy7Zyc/zlVdeCYcccojn/cnfq3I96PGQ6iGpuf/++8MZZ5wRfv/734cZZpghnHjiiel0v//97wdjSsLzzz8fHnvssfDDH/7QpVwHHHBAoD1EssVTTz01EFCMvkS9R0AMSO8xVY9CYFwhgJh5LOlHP/pR2H///cdyCk1j//rXvw6nnXZa2GWXXRruoX6xr2rfnD73uc+FO++8s+k+mx+b2zDSP//5z7DvvvuGj33sY57HZ+qppw78vfjii65iKlK/7LfffoGNuRMa9HjMkQSJm2yySTpd8hVtsMEGgdQakX72s5+FL3/5y2GKKaZw5nKVVVbxNkS/NmlPrOb399prL3/maaFOeobAcP4v6dny1JEQEAJlCJhqIcAAZH90+eo/6aSTAvfYiI888shw/vnn+3Xsix/q66+/PvzkJz8JpmoIZ555pm9scUN+6qmnfAPnq/M3v/mNN2Mcrvn74x//mJatt956/jXO1+pVV13l5c8991wwEbb3Hccc5HGfffYJn/70p31zyo+78sorh6985SsuOdhwww3D008/3VCFL+c8IW24+OKLXZKA5ASMswSeN954Y7jpppvCP/7xD6+LXU5RHpEnn3wynHPOOW63Q/06BLOx1FJLNTVBIoC9ClKcLF122WVh0UUXDe9973uzxZXPBz0eE3vnO9/ZMD/e40ceeSTASET60pe+5MxFvOa49tpr+2Ueg1VXXdXfTzAS9RYBMSC9xVO9CYFxg8Bvf/tb/+pjQ/3FL37h84YB+NCHPuT5ZU4++eSAGuKOO+4IW221VTD9uNfB0JIvTFQTxx9/vKslzD4ioEb5yEc+Er73ve+54R8qiD333NPb05Cv7pdfftnLHnzwQe+LH3tUG295y1t845h//vm9HLE9UpGxyN8C04XxIutrRWY/4DmiYAZQY/HV3YrAZvnll3dDR6QmL730UnjPe97jeNEG6cOWW24ZPv7xj4dzzz037LDDDoEv9NNPPz2stNJKwWxL0q5h4g4xdcgHP/jB8O53vzusv/76gT67pUsvvbRJ/cLa2HR33XXXbrtvaj+o8chmDrbLLrusP4M4kdlnnz2epkeYQt7HZZZZJi2LJzw/GHFRjxGYYEYvtZYrI9RacKnygBHohRHqfffd5wZ4WeNCE9F7menF0xVZSvHEGJP0+uGHH/Y6WeNOkwQk9sOemDdNggGfbeRe5+yzz07bYdRpP2GJSU/SMttEE2M80mtO/v73vycXXnhhYgxLQ3knF3WNUBmXOZotQNNwRx11VPKd73zHy1977bXEPEK8btYo1RiqtJ3ZWCTvete7EoxSs2TSlcSkA4lJh7zYPEW8H2PSHDsKI1bGFHodk6K4USPYRDKbFG9nDEssqn3EWJa58PwiYXS72WabpWV//etffZzsexLr1j0OajyTKCUmDfF58zw333zz0qmCvUnnCuuYRDAxyVbC86xKMkJti5SMUHvMz6k7ITCuEEDykCdjvL3INs70Fl/sUW1CIe6a0OKLL+5H/plzzjn96x0JyaOPPpqWVznBtiJL9I8KBOPBQdMDDzzgQ5r3ROnQYIeEgHpFRqk0vu666wLSnvxX9Sc+8YmAfUQ0ZJ1mmmlc3bPQQgu5fQltwRyKuF900UUBl1bUB0g9+EP9QxtjCL1uJ/+gZmF+PL9I5l0VjAFpKIv3uj0OajxUJ2DPu8h7aoxluOaaawqnf8UVV7jUbvfddy+8b94yATVZNzgXdjzBC5uVlRMcEC1fCAiBZgQw1rPvmeYbuRLsBSA8a/jRrkp5BqRqu37UY+7MB6agHRFbApUT6iUYAnP9bGiCmgvCEDJLeJxAkdnJ3ovnYA5F3LGlIaYFxrG9JHPFblC/YHeCigSPnmj3gF0KdM8993gZKg3m0gkNejyMgmE+sGNBnbjWWms1TBsvGWxqytR98fnBXEfGsKETXXSEgBiQjmBTIyEgBIoQePzxx73Y4mW4i2NRnaKyYWJAkPyw6eN+GjeeojnHsuWWWy6ccsopYaeddgoYpUYJEvdnmWUWr4ZNR2Q6KHj729/uNiF5g0ev3OIfGJKHHnrI7U0sJkeLWvWKMfa1OBduexJbsskidcHOJVJkgtikkSIguemEARn0eHH+MA3zzDOPS6tiGUfscbCpwX6pSBoY62KnA0UbpViuY3cIyAi1O/zUWggIgQwCxJfAiBW1RPQGMVuJTI3mU5iP//znP803xqgkSjH+8pe/NM0AY1NiZ+QJ11yzAwkYbpq9RHr7wx/+sJ/feuutaRknGLrSF5KEqvSBD3zAmSLUPVliE8VgtRNCHWL2PQ0bK0bJMCHZP6QEEJ5JlKNC6oQGPV6cI1ItcMLQNxJSHdRZeHxlpXV4cOW9jyjjPV1wwQVjcx17gIAYkB6AqC6EwHhFIG6mfJlGwlMFwkYhEvepG7+EY3k2QBMeB7jzRm8Z1DGIv81oMyAZQR+P+B1ClI97JMSXNLYMBIDCXRLJA145hPy+5ZZbvM4g/2FDJphYdm1xfDbfxyxwVRHhNYQXUJZgGrbeeusAAxJtObiP+/IiiyySxpcww1LHNo85dbH7gPA84gsc1QjeR6hvkEjA/ODpEYnrNddcs5ILc14dEvuocxy28bC7QaIR1UasBYkN7yWYQzB/eC8RA4f3k4Bj/OH6DJZ5RoNnDvNSRS3nA+ifagjYD4qoBQLygmkBjIqHAoFuvWBMH57Yj7B7CRC2mlDVtuGn4cY/85nPJPbll5jxY2JBnLyeiavdS4Ny+4VJVlxxxQRPDAtW5V4yZg/RgA0eMDPNNFNiqgz3qiCsNV4ye+yxR2LqBK9rrqXuYUA928S9jH7sizM566yzGvrr5KKuFwxjHH744Ym5HqfDGeORmFtwYoxJMuuss/p68VzJE54kZvDYUEw9sw9JzAbBUzuAidkhJMaQeD28WggLDp6EDcfrxZi5xIJneZkxMYnlo/G6ZlOSGGPn5dTnuVnOkobxzCjV71uskoby/IUxlY47Hk3tyJhC77PIC2bYxrOYNP6+8c4ac5QceuihTeHULTdMiiE4Zv9MKtIAB54vPHO8auqQvGDaovUUXLeoBQJiQFoAo+KhQKBbBqSbRUQGxGIjJGxOuKziullEbMDRnda+8BNTtzRVM/F4WifexPWzF9QJA8Kc2ehhBOpSqxwwrPH2229PLN5E3S6b6tsXeWJSpaZyCnAPtqBniXl2FN6PhTA+0Q04lnVyHMbxeMdgBlu9k3XWaVKmxILl1WnidcWAtIVMbrjG+YqEgBDoAgHUFYis0ZEXEWLr6E6L8WRRmHJ08LFO7CMbOjuWDerInE364jldoqqo6titcsCwRgxWe5F1GCPWVllaUZVh9Ioapoxwde6FR8cwjsc7hltxq3eyDJfsPdSGeNDgAi3qPQLyguk9pkPXY1nK6aLJolvG0h39NSmq61Ld8dr1zw/cr371q0BESXz6+eElCiQGfrgJWoChdl307T4htr/97W/7vBZeeGGPXcGGDGE5jz46T2xE/Diijx7LTTY/rzrXUb+OYd+oEqHJefewuSBvSBHjNIxrv+uuu4IFTEuNgPs9x1EdD7sljG5x0c16NvUbzwnVf1shyQSuMAoqmHYpp/OPF32wBeNxnaj9x8vfbntdd7x2HVpuEReFE3HSrP8TY26SCy64ICFtODYC9tXcrou+3bevI9fZGyPhkSTthyNBH456AkL8a4yTl3HPck0k3/zmN5MjjjgiMUM3TwVu4b6TTqNYjpUKxpjAZIsttvB3hPT0vCe2UfcN52477kQFkx2T5znM68vOVee9Q8A8mrpS4UgF0/ZZyAakDKLxzoBgyIexn0Xw8/9IhNa2uARueGbeBi2XjqEbG6ZZkresU3Sj0/GK+qKMkNiEPyZsNXrmPGEUaLER8sUDu7YU9olJZXw8c9lMMNoEt+22265hDjFcNnr5LGFfsNFGGyW8ZybJyd6qdD5WDAibsUl3Gv56oWuvtOgOKnXLgHQwpJoIgUQMSNuXQDYgtmGMLKEHrpJyOg9AFDXHY/5+q+tOxyvqjxgMJMFCRWGW94VBgggghD4dMfmgCTdRVD8kUoNIboULH5ihgspSKzULgZHQL5O9E5fA8aJnJsOpeaw0/HWra8/ipXMhIAQmBgKyAenxc8afn0yeRCxcbLHFPGBPNsgNw5nbXLjtttvcT52YA/iXxx9w8g2Q8ZKNjCBFZCelL3Mb87TYtOc+elfI3MOCfXn7OTETSIeOEdy2227rQXZiOGevYP+QcpoNPR+BkTgFtCcaIHOC4pz8osI/rVJc58cjGBHrtC/Tlr2amsJtKA488MCWdhIYNJLaPWskiE0GmUyxYyFmAthmoxe2w5fnh/Eh8Rh4Bibl8PDaxMYw9Yk/M6JdEt8i4hQXQTwLgnDFAFyxvOwI3qSyJ+YFumbyb4iEgBAQAhMBAQUi6+FTxmKaYEF8FR988MHOiJAoigBLkfbaay8PiGM2DJ7um02byIPPP/985bTc5J3gK9uyljbknrCYDOGMM85Io/1VTTl9wAEHhPPPPz984QtfcEaHL3moLgNSdbzddtst7LLLLhGSwiOMFJRNdlZUkXTk0UCsF2nPCb1NMCkwuemmm1J8kWLw5U/KboxHYfyK8OE+TEsdIrU6fSNBgkESCQEhIAQmBAJttTQTuEIdGxDbODwAEUFwIpmY3o0TYzptDBBtI0uIBxCJYEz2orlRH2XEH+C6LC039bDhsC/0xDZKLp2IDbDDDjvEy8JjPuW0SQvcjiIbc4F5Mgfz7ijso05hfjzaEgDLIkG27AZ7AgJXMQcwrELYJfQq7TnjWfRKDzqVfVbYeIBxK4pBtkibnqU999zT15K3AcnWIYU768XotipZFEdvQzv9CQO9A8P3DmCnJWqJwFNSwdj/2l4QYn9cRbOZFhHRoxLg6xZCXUCiq6xKhnDVxFAwzw7PcsmXNl/WSE6iKD/66mdDOZPsyzwoXGyPLQR1EeETFrkVFaWcxs0MtUHWTgF1AFT0hd+q76LyovGoF/NjFLWhjHGj6qhqjpCytOe4yRKK2SJDeijlKviS2RSVC8+Fc54jf8RfKCLmedBBB4Urr7yyUgKzfB+ofqCY5j5/v+iaZ06Y7+w7V1RvopedcMIJDgHSR5EQGBQCqOIt8NyghhuX44gB6dFjQ/zP5pFXQ0Tmw3hAt0sgEFGeyJJJfAtUOHHzz9aJmzF9ZImNkc2HTQ9VBHOwsMPZKul5q5TTtMEAMkvdMh701Wq87Dhl5zBdqCToZ6mlliqr6vd6mfacDhmTP1Ra4Ey+iLJ4I8SKYINDnVKXiKWBmo5AXMQ3qUq8F6ioymxpqvY1yvVi/hnhNMpPefjWRl4jk/YO38SGaEayAenRw8AQkiRaGIgWEZs6hp8k68p/1ccESXnD0KJ+smXYGiAJYZNEAtDK9oANDilJPuU09gYElIr2Ftm+Oe+UEWk1Xr7/suuVVlrJb1v+hbJq6b1s2vO00E6QWGCsWhdb+oDxICEZjNC1117bMrIkRqQwHuuuu2526MrnMVMqGUYxfBUJASEgBCYCAvq169FTxuMFQtyfJYxL8fqAUD0gxicTaJbwisFzBWaiDsEgYMzJJo16weJlNDUvSznNVzdf3JYPolLmzKbOCwrKxsunuC5onhZZcrOAmypME1KaVmQ2GW68G9U6cTOP9TtJex7bYlCMsanZcLhhcZRExfscebZIpixxWbY4mD1Iw3WrCyQ8eDGhhsunWW/VRuVCQAgIgVFAQCqYHj1Fvn75CsZugDwSiHvvu+++cIu5tpIyGzrmmGP8SxqPkyWXXNLLkJzwhc09NjhsAdjQytJye8M3/rGgV257QBjwfC6NmHIaMT0qhEgvvPCCpwfnq36fffYJFtUy4JnCvJAWmLGkVyVl+KqrruqbcGxbdqwyHu1hmszotYlZy/bNWpgPTAA5LYiRQWjsSMT+QPXERo+OP6Y9JzQ7tjIxT0Ynac/jGDxHCyLmzN2ll14ai9OjBXZzjybwI5U3hHQLdZBlKQ14JUEwSZAZGPuRf5A+MX88j3DFxV4GZkckBISAEJgwCNhmJ2qBQB0vGLogZbflTvEQ4SadSEyN4GXZ7i3+RzJp0iSPUEq2SlJ+n3baaV7FmI/KabmzfRJ5s8hbpGrK6eOPP949PmzDTYwxSix4maefNhVEU6rv7Lj586rj4fEBBngOtSPCYJOWHK8Y5oaXjzFFiUluEtv0G0Il40HEnHuR9jzOi7DjZl8TL9MjeJvND0Y5TX/gaJIv/zNXaQ8XTz3L/5JYXBL/Ix37Nttsk5xyyimJSY3SfuucjFUk1DpzHIa69jGQ8CcSAoNEQJFQ26L91GRUmTDcVs2FklSMIFp4GtQhbCCQbES7hHxbIEcdgToG1Q1fwN0Qao+YAK3Tfvgit/TVHlkUSQZzjAa0nfbZqh3SC9RHdfpHsmB5ajwOB9INvISKVCKMiXQFtRL1epF5tBf4tsKim3LWhvGrhdvvppuRb7vxxhv7GqMkcuQXrAUOBQJItQlqiDGqqBCBp6WCKcSlu0LCVJcRmy/ht3tF3TIfzAOXzrhZo4bJ0mc/+9nsZeE57r/tgobFhp0wXDAbYFYFt5j2PI7X7bEX+HY7B7UfOwTuvvtuN2KO0Yf5/2s5fFxdmZ0V0Y1NCpoWmYSqQW2Y3hjjE1SBuIgWEZ58WWPqXmS2HvR4cV0333yzR0UmQjGRpHkeeSpbH7Z5FmsnVefm2+q6BwggAREVI1BXBVPcy/gvtS/HpN0f6ifRYBGQCqYa3t2oYMxOJzFbKVf1mTF0QvZf+9lNdt5556bBzbYqOe644/y+xYRJnnnmmaY6w1BAkknWUPRHlulIvcpsPejxmL9JHxKzw0rsw8gzVhO08eqrr45L82O79Zkk2J8zAQY7Ialg2qKmbLhlEIkBKUNH98YagbFmQIiY2y8iuzAbfy+oUwbEPMtS+6w4jyOPPDLduM8+++xYnB6J4msSs8RUhmnZsJ1YLqPEpAOJqYATIgjHP4tHlJx33nk+3V5mth70eESJNqP7FHbWaVJRtx2LhVXXh52ahTdIzKEgNq18FAPSFiplw+2BEEldCIEJhwDxbvbff/++rBt7H1zKo/dQXwZp0ynu22Yc3pSzCPUL6kZUlsSJycfQ4f4kS1Q4rPFc8K4jhxT5pMh7hB0Wfy+++KInuIzqFzzzOsmknYd10OMxPjZseM9FYp1myN4Q7bnq+lD9EmCwLMJ0HEfH+ggoDkh9zNRCCIxbBDB8xs2awHSEpyd5XiTzOPJNl5QBGPFCMBpc8xdTAVC23nrruRE1QfDI2Axh/3D66ae7ATPu58RywT05uh9X6R8DZTYPXJyxqaB/2kHPPfdcIHWAqTb8up//4J4OEwRDkSeSRxJ3h7mSGRnj7SzBnOSpDHfqYgROPB8SIGL0zDMiKWRR7Jwnn3zS0y5wn/p1CGajKLIw7uu4uceAfa0yWzNWrFNl3EGPx5zydmI4BGAImg3FX2d9hCLg+YGRqLcIiAHpLZ7qTQgMLQIEdFt++eXdeJKvd7y1CHlPsDcIYz0C4hF4LYaQ5kv55Zdf9jJSBUBsQGR8xpiYH/v5558/XHjhhV6GVw5Gy8RwIQ4O8WWIastXaZX+X3vtNc9xxDgYDdK/qUK5dMNJpC799mZB+kFuJ3IttSKzH3DvOJgBUhmwvlbUDnekD1tuuaVnsT733HODuZp7bCCYObAjbk8kmD+YR2IOEUSQFAw8y26JODcY1kbKp5SgHGaVZ7/MMsvEah0fBzXeE0884dguu+yy/u7HCdddH/9vTP0Wm+vYKwTaamkmcAXZgEzghz8Oll7HBgQ9f5Vswbb5uo1D1r4BQ0z7vUmuv/76FBVioxjjkV5zYgHZPAYOfUT6v//7P29rUV69qEr/ltTR25iEJnbjR+LkGKOTGEPUUN7uoq4NCGOwXosU3NT1UUcdldoXGLOUWO4mr5s1SiXOTaSquBPDhjHJHo3xIxRxj9m0sWXACBYcIlmgPG9nKoVYVPuIsaxJKhKT5JS2LcpsXdqgxc1BjWcSpcQYWMcHbC2XU4sZ/a+4bH0nnXRSYpItt5cp7SRzUzYgGTCKT2UDYi+mSAiMPAJl2YLR06OOqUt59QQunKgfLBBc2hX2BpTlQ+SnFUpOivpHLZKP+FvSRUe3HnjgAW8311xzlbZHAoRYnnqE0S/CsCruRN1lvWVZsIkGjDoL9QFSD/5Q/9CGGDmdEukEkGpYoLyWXbTKbN2yQcmNQY2H6gSpHYk+CRGAlO6aa64pnFm79eHaj5qsG5wLB57ghc3KygkOiJYvBEYRgW6yBbfCI88gFNUjhgrxZZ599tmi26VlVfov7aDDm8yVsWEK2hFqIvOocKNOGAJC8GepG9xjoD37ePQusctBjYVxbC+JbMFZ9Uu+724zW+f7G/R4GAXDfMAYo1okg3iWqqwPQ1YIOyfUlqLeICAbkN7gqF6EwFAjEKPyYv2fpW6yBVdhEDDU5Cu9bqJF5lil/+xaenVuqio3pCW7dRVabrnlgoXUT41Ss+16iTsMyUMPPVRqb1Jlvtk6GPaSTwkvkSLqRWbrbL+DHi+ODdNAcsu8VKvq+rDTgbB3EvUOATEgvcNSPQmBoUWgarbg6MGBMWgZwRzgLtuOYHjoa+211/aqVfqPjEeV/tuN38n9KMWwWCRNzTE2hanKE26aZgcSMEolFUCkqrjH+mVHEi7C3OSzJrOJYrDaCaEOWWKJJQo3VrxxUPeY/UNABREJr6Qi75x4v+w46PHiXJBqgZPlYopF7m1UdX2smfeSrNWi3iEgFUzvsFRPQmBoEaiaLXjRRRcNiKzJngzTgM0BInPonnvu8ezIxLhAFYBkwww1XVoQvyzRk2NDgYcGhHqCrMCRAanSP31DMC/bbrttuP/++93DxhIAelwOizbq3iFeqQ//sCGjOmLcvOQmG2o9P/TJJ58c8KCJ3kLcr4p7lSzYuCcfeOCBnv8nMnXMEY+SrP0JzBDzxKOmzK6D+bVSh8Bo4d1Tlkmb9tCwjYfdDcwj849pFMDn2GOPDYsssojPuc76aEBMGpiXKmo5H0D/VEOg2DhVpSAgLxi9B8OMQB0vGNaBp4XZKbTMFhzXigeM5TPyDMSbbbZZQihqs+PwDM6mAvBq5g7qXgHUs43Xy3baaafE1ATJrrvumuy9994J2ZEJ7Z33WqnS/yqrrJJ6hTz++OPeP9Er7Ss0sQRfcaqVjnW9YOj08MMP90zVcQDb0BNzAfYop7POOmtiMU4cz3g/HvEksU07XvqxHe51smCbTUliTFzq2UG4cctZ0jCeGaX6fSK5lpGpQ/wZmmFlU7Wqma1pOGzjnXnmmf7uzjjjjB6K/dBDD/V3OLvIOuvDk4lnjldNHZIXTFu0FIq9DCIxIGXo6N5YI1CXAYnzNVF0cvvttycW1yEWNR3ZNCPjYF4yhaHF6SfWoQMYEEtk6H1Z0LLEVBFN/caCdv0T0pxNP09lfebrxutOGBDmx0ZvcSRiN5WPrXLAVMG96iD2RZ5ExizfBvdgC2SWmGdH/lbDNYyPGbY2lHVyMYzjEQofZpD3qFsiD5YF3qvdjRiQtpDJDbeanEi1hMDoIBCzBcfsx0UrQ9Qc3V3JjlwUWpx+Yp18Hxjr2Rdovji9btc/+nY8TPJU1me+bjfXzI9U6gcffHAgkmYdIphbEVXBvahdURnGwwsssEDRLbdRQX215pprFt6PhbhN98KjA5uYYRuP9xX1E+9RN4Q6DQ8aXKBFvUdARqi9x1Q9CoEJiQBGi9iAYM8wCkRo8o033thtLuoyIWO5/rvuuitYwDSPvzKIeYzqeCZh8tD/55xzThqNdxB4TqQxZIQ6kZ621ioE+oQAX4k33HCDG6SSR4Vw4hgwjndabbXVwmKLLeaMFXlNxgMRgGuQNKrj8bwtO3DXUpRBPovxNpYYkPH2xDRfITCECODlkg3wRJTQUaHo4TMq69E6qiEQvbGq1VatThAQA9IJamojBIRAAwLZOBENN3QhBISAEGiBgGxAWgCjYiEgBISAEBACQqB/CIgB6R+26lkICAEhIASEgBBogcBkeOq2uDfhi4miR1hmIkOKhMCwIXD11VcHIovyJ2qNAC6i0LLLLtu6ku4IgR4jgAsvofMfeeSRHvc8Mt09LQak5FlizU8qZ5EQEALNCNx7770BT4EYdr25hkqEwMRGgLD+++6778QGofXqxYC0xkZ3hIAQKENgjTXW8JwwxEkQCQEhIARqIvC0bEBqIqbqQkAICAEhIASEQPcIiAHpHkP1IASEgBAQAkJACNREQAxITcBUXQgIASEgBISAEOgeATEg3WOoHoSAEBACQkAICIGaCIgBqQmYqgsBISAEhIAQEALdIyAGpHsM1YMQEAJCQAgIASFQEwExIDUBU3UhIASEgBAQAkKgewTEgHSPoXoQAkJACAgBISAEaiIgBqQmYKouBISAEBACQkAIdI+AGJDuMVQPQkAICAEhIASEQE0ExIDUBEzVhYAQEAJCQAgIge4REAPSPYbqQQgIASEgBISAEKiJgBiQmoCpuhAQAkJACAgBIdA9AmJAusdQPQgBISAEhIAQEAI1ERADUhMwVRcCQkAICAEhIAS6R0AMSPcYqgchIASEgBAQAkKgJgJiQGoCpupCQAgIASEgBIRA9wiIAekeQ/UgBISAEBACQkAI1ERADEhNwFRdCAgBISAEhIAQ6B4BMSDdY6gehIAQEAJCQAgIgZoIiAGpCZiqCwEhIASEgBAQAt0jIAakewzVgxAQAkJACAgBIVATATEgNQFTdSEgBISAEBACQqB7BMSAdI+hehACQkAICAEhIARqIiAGpCZgqi4EhIAQEAJCQAh0j4AYkO4xVA9CQAgIASEgBIRATQTEgNQETNWFgBAQAkJACAiB7hEQA9I9hupBCAgBISAEhIAQqImAGJCagKm6EBACQkAICAEh0D0CYkC6x1A9CAEhIASEgBAQAjUREANSEzBVFwJCQAgIASEgBLpHQAxI9xiqByEgBISAEBACQqAmAmJAagKm6kJACAgBISAEhED3CEyWGHXfjXoQAkJglBG46aabwlprrRX+85//pMv873//GyabbDL/i4VTTTVVuPPOO8Niiy0Wi3QUAkJACBQh8PSURaUqEwJCQAhkEZg0aVJ4/fXXs0Utz+ebb76W93RDCAgBIRARkAomIqGjEBACLRFYaKGFwuKLL94g7chXnmKKKcLqq68eZp555vwtXQsBISAEmhAQA9IEiQqEgBAoQmDrrbcOk0/e+icDlcwWW2xR1FRlQkAICIEmBGQD0gSJCoSAEChC4KmnngrzzjtvaGU2Ns0004Tnn38+TDfddEXNVSYEhIAQyCLwdOvPmWw1nQsBITDhEZh77rnDCiusUCgFmXLKKcMGG2wg5mPCvyUCQAhUR0AMSHWsVFMITHgEttxyy0IM/v3vf0v9UoiMCoWAEGiFgFQwrZBRuRAQAk0IvPTSS2H22WcPMBxZmnHGGcNzzz0XcMMVCQEhIAQqICAVTAWQVEUICIE3EJhpppnc0wWPl0gwHZtttpmYjwiIjkJACFRCQCqYSjCpkhAQAhEB1DB4vET617/+FTbffPN4qaMQEAJCoBICUsFUgkmVhIAQiAi8+uqrYZZZZgmvvfaaF80555wBDxmiooqEgBAQAhURkAqmIlCqJgSEwBsITDvttGHDDTcMeL6gftlqq63EfOjtEAJCoDYCUsHUhkwNhIAQQOWCISrqF+w/REJACAiBugiMbC6YZ555Jtx2220tgybVBUr1hYAQeBMBktIRcGz66acPDz/8sP+9eVdnQkAI9AIB1JqrrbZaeNvb3taL7oauj5G1Adlvv/3CMcccM3SAa0JCQAgIASEgBKoicNJJJ4XPf/7zVauPp3qjmw2XL7Qll1wy/PznPx9PD0RzFQIDQ+CKK64I66+/fvjnP/8pF9oS1P/yl78EDG1//OMfeyTYkqq6JQR6isD8888f2MtGlWQDMqpPVusSAkJACAgBITDECIgBGeKHo6kJASEgBISAEBhVBMSAjOqT1bqEgBAQAkJACAwxAmJAhvjhaGpCQAgIASEgBEYVATEgo/pktS4hIASEgBAQAkOMgBiQIX44mpoQEAJCQAgIgVFFYGQDkY3qA9O6hMCwIXDCCSeEaaaZJnz2s58dtqkNxXyIGHvXXXeFv//97+H555/3Ob3rXe8KH/zgBxvm99JLL4Vrr722oWz11VcPM888c0PZMFwQ3oAAdEW0zDLLhAUXXDC99dOf/jTccMMN7upNUK2ll146vVf1ZNDjMS+exze+8Y3wxz/+May11lphlVVWCdks0HHuZeu77LLLwgYbbBCr6phHIBlR2nvvvROLAzKiq9OyhED3CFx++eWJ/R4kFgekq87e+973Jh/+8Ie76mOYG1tUZcfJ4oDUnqZtYslRRx2VvPzyy4kxIMlBBx3kfVlky+Shhx5q6M8yDCe/+MUvksUWWyx5z3vek/zoRz9KKBs2Yk4LLbSQr4P3J//HGiJZAK2EtS6wwAJezyJ7Jscee2y8Xek46PGYlDGKvkbL/JysvPLKyeSTT54Y49Q033bru/3225PPfOYziaUsaGpbpWC++eZLjMGvUnU81nlKKpg8R6ZrISAEaiFw5513Btssa7XpdeVnn302XHfddb3utqv+nnjiiWAbmEuGZphhhvDWt741HHrooWHqqacOf/3rXz0I3N/+9rd0DMJuL7HEEmGTTTbxv5VWWmkok/z98Ic/dInAo48+Gl5//fX0DynHpEmTfA0s6vvf/36wjdulPo899ligHdKcAw44IPzhD39I193uZNDjMZ/vfve7LrX61re+FW666aZwyCGH+LUxFOl0q6xvueWWCxtttFHYcccd03Y6eRMBMSBvYqEzISAEOkCAjZUMuWNFRIr89Kc/Hdjkhon22msvF7/n83gsvPDC4eMf/3h44IEHPJOwfbo2THvWWWcdSrVLnCT5f7761a86swEzFf+IrMtmG+lnP/tZ+PKXv+xqC5grVBgwV6ik6kSoHvR4RAb+xCc+EWaZZZa4FH9OXMw444xpWdX1oUb73e9+N3QMcrqQMTwRAzKG4GtoITAKCBCq/JxzzkmXwgZz4403+pfjP/7xj3DxxReHww47zH+E00p28uc//zmcfvrpnjDylltuCeRvOvXUU8Orr77q1Z566qlw2mmnhRNPPDH85je/8TIkLVzzh26eL3A2Nb6SST55xhlnBNpBzz33XDj66KMDiSkHTdh8XHPNNeGTn/xk09BTTjll+M53vhNMjRFMDRaOOOKIhjpIDfjL0y9/+ctAXhDWdP311zcl2vzTn/7k901lEX7961+HI488Mpx//vmB6zyBF/fBP9ql5Ou0ul522WWb5scYSAQ23HDDtNmXvvSlJpuJtdde2+/XsWsZ9HgwVFkbFiZ83333BeZu6rGO1rfHHnuEfffdt/BZpB1OwJPmt3wCgqAlCwEhUB8BJA/nnXde4It+//339w5efPFFVzvwhX/uueeGHXbYIfClyEa30korhRdeeMHrXXjhheH9739/+OIXv+gqCjZKfuR32203r2c68zD33HOHOeaYI+y5557hjjvu8HYf+9jHgtlTeNmDDz4YXnvttcAXJjTvvPOGd77znak0hs2deSFOHzQdd9xxgY0T1UsRsQEzP77uDz744HD11VcXVUvLkKaY7URYZ511fL1s7mabkDIPV111VfjQhz4U2OhOPvnkgGEwmG211VbeLnbE1z3PBOaMDRWGDoPY3/72t7FKR0dUE0g5WHOk2WefPZ6mR5gk1o6hajc0qPGQTvH+wDx87Wtfa5hynfUtv/zy4d577237nBsGmAgX49FypcqcZYRaBSXVmcgI9MoI1b56E0vWlkJpEgw3ODRmITW+u/LKK73MNsq03hZbbJFglGhf62nZ//3f/3m9r3/9617GPfsdTs4+++y0TuzLpABe9qtf/crrmMdCWocTjD6N0XED0IYbNS86MUJdZJFFEtv8C0cyxist/973vucYZI1STYqTmCQorfPNb34zMdF/gkFrJAxYwQUMI9km6WUm3YhFidmUJMaYpNemEkmM4UmvjSHwNqZySMs6OTHGMfnc5z7XtinvhEmv2tZrV2EQ4/H+GLOWTDfddI7RTDPNlJhkq3RqZeszxsuNkEs7yN2UEepE4MK0RiEgBDpG4C1veUtDW1xy+RpGxYC6ATKvDj+iNomE7Qj3zYsmFvmXJmW33nprWlb1hDGzRP/YhrSSQmTr9vIcKQNGlkhw2hEqC4wyi4xSY1vUTUgpsrYkiy66qKsJLrjgApcIUTfa4VA3ErhnMUcycs899wRjFvwPdQ5SoyiZiu3qHG3PDMZINdh/FLXHRgRMdt9996LblcsGNR7vz5lnnhkwFMbmhWOZq3m79fH8sPsRvYmA4oC8iYXOhIAQ6BMCMX4Cm0cZ2ddmsK++gFdLXcozIHXb96o+mznqqcgQtOsX+xjE86hRUJlElRLtwItNC2+KPH30ox8NeKKgimoVWwPcI+bEtXjyySeDuYW6KiffX6fXqENgulZYYYWWXfz+9793O6FeqMMGPR72OKi2iPeBnQt2R3mmu8r6ULdh9yR6EwHZgLyJhc6EgBAYYwT4cX/66afDO97xjtozGRYGZK655gomrvcv5iqLYN5IMpBcYBeCoWkk7mEzgdcITE2WTM3jl9yvQtGw9f77769SvXKdSy+9NKy33npNBqexAxifQw45JODSmt+4Y506x0GPF+e26qqr+rPIr6Hq+rCPmn/++WN3OhoCYkD0GggBITA0CGCwimFp9JaIKhzKWlFkPPIbdKv6gyhHrYR3UJ6QRuAZlCfcO2E+isT0FuTNmRlUJ1nCKwYj3arMGmPg3YExZfQ0iv3BAGVVNbG83ZH1wBBk3W+zbVgrBrMwVVkVEp5KuKbWpUGPl50fnlgYAWep6vrwEsIbC7Wk6E0ExIC8iYXOhIAQ6AABpBbYMOB+CxFynI0CsXwkvC6g/MZHm6xeHFuCFVdcMWVAsHWYZMGtcFt9/PHHXd1wySWXeF9syPywR1sLmBfGxZsGsoicrprAxXfQhHqkSNLAxkuAsiKGClsMvIOipCLO+ZhjjnHJAZ5CkVg36+VeVG/hHQTlcef5gAtkxvmuBsCDBlzAEC8cnp9FK/U69ItK56yzzvLrsn+oy/Mmxkee8GTCDXm22Wbz54eLNX+onAjQFl1dh2083lFclHFljoSrMlhhCxKp6vqozzPnXV933XVjcx1BwF7MkSR5wYzkY9WieohAt14w9vWXmMtnYoGz3EvAvnQTM75MCE/NT4upIhK8XuzHN7F8GF72gQ98ILn77rt9FTvttFNim2ey6667Jvx/3XTTTRP7wmzyWsEDBg8E06Enm222WUJIdLwDTC+fhjO3DdD7xwvBGBXvP3qY2EbaFWqdeMGYHUhi0onE8qWkYxvjlJidhM/TcqIkN998c3ove2KbX4MXDPcsxklijJiv2Ywd3cPGYqSkzYyZSEwS4n0T+tsYneSiiy5y7xmehalA3CPJGJfE4q0kJlnyuhzxnjHpUdqXqUr8HpjbppmWo9pwcgAAQABJREFUF53wDLKeONk6PE/GLvrjXYk0bOPh/WJ5etw7aamllkrwzDIJTmJGqHHKfqy6PirjfWSuuA3tq1yMuheMGJAqb4HqCIERRKBbBqRbSGBApppqKu/GxP+JfYW37BLXXvKpQPaF37BhUsbGagZ+nDZQWZ8NFUsuOmFA6A5X4iquqUVDM2aeWKMZnCZmD5KYBCV/u9Y1zCMuzq+88kphO1MfJTvvvHPhvWwhDKdJt7JFHZ0P43hms9ESnzqL5LmRl8yMWOs087qjzoDIC8bYc5EQEAJji0A74zxce/mDjGlpmix2IAQiy1M2dHb+Xr+vCfi1+eabu+g+n/m23djYduSJNaKm6QXhoZN1f873iccHmWvbUVSjtKvX7v4wjochcS+IIHJE+c0GaetFv6PQh2xABvAU8b0nEuSgaNDjtVoXPypYv6NPJTR1LwhbAsJI94MGjdugx+sHZt30iQEfenFsCEaRsOUgUixGn3Vyn4w1FtiSYDCaDavezzmN8nhEryVC7aCw7Odz6kvftWVC46TBMNmADDpd+aDHK3ol2qWpLmpTpYzU5tgR9IMGjdugx8tjNpYqGPO68Oip9qOWWHCnxAz88tMbmutOVTDZBUS7lGyZzkcfgSK1YJ1Vj7oKRhKQHrN1+LrnqZ/pygc9Xn5tRddV0lQXtWtXhpslX5MEbeo2/XtR+vZ+PqdBj9cOy7G+j5stAbSIjYCErFeqhbFeV6vxo4dJq/sqH00EitSCo7nSzlYlBqQz3ApbsSnGpFzZCv1KVz7o8bJrKjvHra4XabjzYxDqGBdNdOGEp+6UYGSK0rf36zkNerxOcRlkO0T86NjjX9WooYOco8YSAkKgvwjICDWDL/7f+MYT4AffenzV8xws+moCBlkyKE/NbEmcXF8KM0A0QDZHUoLPM888adAaAhKR7XK77bZzfTf+9fjqoyNeY401wvve9z7P52BJpzxIEfrCGOWQYD1ktSS2ARkVzZ3RZ1x1vMzyfF2kLEf3bkmqAhlLmW8kMlUivSAjKdkx2fD5csOQLh+bILYpOhJ4KMYmiPf54kV6kY3aiD0HWICLJTOLVVsezavAoymaSNzxNBdHz8Ra1KDVcyImAuvBjgRDP9aPbz6xJLLPiT7BONqumKuph7CmnHcEaQntt912W4o8qFLRc6oznndk/5Bz4gc/+IHHx8A4k+eUNdLs1XOK4+koBISAEBgTBOroo8ZT3bo2IPh4G7OR2Kbjvu+HH3548va3vz3BXS2SBUxK1lxzzcRUAO5TT0wCYiA88sgjrsPGz9tSNHsf6LTxoT/33HMTS4bVkC2UjIrEP8hnoMy77VnQm2SllVZyF8NHH33U4wCYMatPh/6rjkcDS2mebLzxxj5XY7ASMnLSd3ShI8Moc7eXMGFc21gTYxr8GruLbom1kQ0y6xZJfAbGI5ZEO7KgTskmm2zi1YiDQDsyYhZR2XMio2gcl3eE5w0GRc+Jvo058bFMqpMOhVudWf+nbp9lz6nueGR2XWyxxRJiWOCaSPwA4l+QERXq5XMaSxuQFMxxcNILG5BxsExNcQgRGHUbEMUBeeOlwyjOvvITy0PhJTHFd0y/DDOx+OKLJ5YdMX1NLdJiMvXUU3uwJQrXX3/9xL5U0/vxxCQaDQwI5VtvvbWneWaDikQAocceeyxeJgsvvHBDHAH6hwGKVHW8XqbzjmPXPRalqSbgT9V06TvuuKMHoGJcgibBHLIxZ/HjXpXnFJ9tPn170XOCueS9sIyldO/EMyJNd6R2z6nqeCYtSSwfSFPKblMX+XtmoaB9yCpp1+Pcyo6RAYGZ058w0DswfO8A+4t5y5X9Nx7P956SCsb+10EmzXC1BKoAwiRbtEUvJ8uhRcNzkbhtJGGttdbycv5BjYG43F6StCyr0oiF+eRFlJMOG5ULORg4px/+bGONzVzUj10ChEoE0XsMtxwrVRmvXTpvi6gYiJcQ9fD5dN7XX399HK6jI6qcojTcrA1bjHZkTEYAe1RbEOqgXXbZxVO3W5TM8IUvfCHtAtVFledEgzx2Rc+JPBtkJz3nnHPcpZjcJJwbQ5SOiUqm3XOqMt51113nhpnLLLNM2jcnqPm+/e1vB2OYwle+8pWePyf6jjlXGgbWhSNAmHJieuBSTnp7kRAYFALmITaoocZkHDEgb8DOpgbzcdBBB3nAI5gOyMTtfsTzgk3G1BR+Hf/JMh+U5Te1WC9/pH/+2FRhQMh1gW1ClrA/ueGGG9zeAeNLEhmR3yJL7cYz9rhn6byz41Y9r5Kmul1fbPjk0ACDSBbB0U9POeUUT5UdbU6qPicat8MujsXzgfE09UcwqZN74Rx66KHxttsJtXtOVcaDyYRI250l8opA2Zwp2fucs36edSdEvo6i4F6d9DWKbbANggExKV5pyvlRXLvWNLYIEMRslEkMyBtP12wsgtlEBKQBGEzmMzXCiLDpmc2AGwW2eimqbmq0Z2PbZpttPKnUtddeG2KSrdi35SBwSQwSCKQTJOrKU7vxuJ9N5x03avqJhq5Zw9B8/91cI7ngqxFX4SLpQpW+wZ32bM75jZmNE0wuu+wyT3pFf1WfE3XbYUcdCENhJCEwi0Tj5DpLVZ4T9duNN8sss3i3eBFFpoMCpGIwCP16Tj6o/hECQkAIDBgBueG+ATgbJdkNYT6gKPl447Z7vHCOuDpLZElkA4TYYHC5rEpmVBnwrjAD0WBGoQ2eIzBERxxxRLBET6nIPT+nquP1Kp131XVRD0+bXqThRn1DZs4888EYFuyMQ4NLrhlwelm750Slqs8KnFH53Hjjja4CyaqNqj6nKuPxnKBbb73Vj/EfsnLybiqUc0RERyEgBEYBATEgbzxFpBuI+bEhwD00hk5/8sknA1/yuGqSzwG7DUvSFG666SZPzYwLqRmGei/YOZgRa7AETcGMF11iwg1cMdEjE3Y6S3xNb7/99sGyg6YunvF+DE+Naga7D9xn2ZgI3MQ97EWqjtfLdN5xfmXHqmmq26VLR6VgHjip63F+TMssGsxKPNx+++3+x/2qz4m6SBoYI6Zvb/WcqMtz5nmZwWkwryaKnKo+Jyq3G88ivAYzTvbnbMnZ/jeA/fuTn/zEpVXR7iTaAZWlXU8b60QICAEhMKwI2A/wSFJdN1wyFeJZYaoCTx1Odk6L4e+uo7hoQoTVJY22fRH7n6lsUldM7uPSSXpr0ljjWooLbz5deT7LpX1Bu/cM7fNkm573h5cFbqyXXnqpe0OsvPLKiUleao3Xq3Te+TkWXVdNU12WLh2cTNXh3hm4A+P6nCU8Rsy4NjG7HK9DKnK8OqB2z4k62fTtFtOl7XOiDc8Dz6c8tXtO1K86HllfTTWXEKbd8ogkpKI3+5OE9xEyg9dKade9cpt/ohcM2WVFrRGQG25rbHSnvwiMuhvuZMA3rMxRN/NC/I+9Rp0kUKg4CEYWPRqAhq/5vKEpEhHqRp19dp5IOjBozX4lZ+8XnaOumG666YpuuaQj2xdf6Vl7ijrjsR5sW5CeoKrI9lM4+AAK+ZrvV8bSsucEFki38oHmypbczXOqOx7P1dxuPRAcUp5+EOotjGqRpMgItTXCGKFioI5nHFI3kRAYFAIEIMQQFTX9CNLTMkLNPFUYh8h8UIzuP898UF6WppkQ03WpFfNBP1nmg+s801BnPNbTTc6NKi5hqAksXgpTrUT9Yj4YvOw5gUUd5oP+unlOdcfjuS633HIMKxrnCKB6JaIu6jpsxiBc3VHpZgmGGWP0LOECPozGx3zYEYm4iHAjX3DBBdNbZMXGSwwm1yTIbtOV3qx4MujxmBbPA9d31KF4wZkUs8FOL069bH3YB8bo1bG+jm8iIAbkTSx01gYB3BDbUd5NuV193RcCo4wAkizsyXbddVeXjB533HHhsMMO8/QNMCWLLrpounyYTj4Q8IzDQBqPvDImOm044BOkecRNws6tiLDtigzI7rvv7nZzrI2NHI8xbNKQUFelQY/HvF544QVnlPgIeOKJJ8Kpp54allxySU/BkJ13u/UhOcOFmzQUirWTRe6Nc3u4I0l1bUBGEgQtSgiUIDDWNiCEmrcv/pIZdnerV/13agOCLdI666zTFK3XpKput/Tud787MRVk0yLN+y2xODNN5cNSYNKMxDzQEuzXsMWKf5RPmjQpnSY2XnvssYdHJzaVdWL5lxJTW7tdGxGGq9Kgx2NexjC4nV2cozGN/szMIDwWebqEKuvjHSe1RSc06jYg8oIpYMpUJASEQH8R4Au/KCNxr0btd/9V5onuHvF7Xk2KJxUJBgkst9VWWzUFkMM1fxjVLnHNuMRb/qNgzIarqFFT84dN0UYbbRSruddXL7JiD3o8bKKIPpy18eM5QVmVMV5tVdaHGg3bOyIdixoRkAqmEQ9dCQEh0AYBjJhbZeu96qqrXDTPpmG5jdzgmUByGHPjNk7sGwypizISo77DvR07LILksaHh0s4mHmOkdNM/46OTxybjU5/6VJtVdncb9co111wTSBWQJ0TxuNcTCdmkUB7vB9VEJGzR+MsTWbp7lc2abNBkdIbRifGI8uO1ui6KR4NRPpm0zVMvbVY1K3baoMXJoMeDmYoqpDglXPWJERXjDFFeZ30mKfHUETCeRc82jjPhjp2IhcZDG6lgxsNT0hzHEoFOVDAk1ivL1st6cCFGdBwJNYN9OSa2kXiRGfc1ZSS2YGsJyQDtB9gzEON6bEbPiTENLrLHBT1SJ/1b/BxvTsZrMljXoU5UMCYJSFZdddXCYchEDZHh2Rg1d+k3xiqtaxF3E7M5SK856VU2a9QlJL286KKLEp6lRRNOZptttiQmOmwYtMaFxShK5plnHs/cXdasKCt2Wf1W9wY1Hqqjiy++OLEcQInl4mo1nbS81frM487fbWOq07pVTkZdBYP4byRJDMhIPlYtqocI1GVA2LyqZOtlU8syIEzZEjemDAjXbH4wG9mMxOZV4WUmnaCKE9mpTTLi/ZkUxcs67Z/Gd9xxR5LV43uHbf7phAExCU5iYvvCniMDws0YC8fUNAnxaKA8A9LLbNamMkgOPvhgH4d/2FR5DqZySMs6Odltt90aMne36qMoK3arumXlgxjPvJY867V5vzlGxHeK2dFbza1sfSZtasp03aqfWD7qDEiznG/CyYC0YCEgBKogUJatF705Lot1CffkSNEFPuvGHb0IzKAzmNFjrFr5mO2fRqhyll9++crtO6kIFqiOUPm0I5P6hAMOOMAjJROTBfVWntpls46RcVtls8b7JJKldg/33HOP56EiF9XRRx/tnjd4fXRKtll6Tqas/UdRX6jUwATPkW5oUOPxPp555pn+TLB54dmUhSJotz5sgcoSSnaDyXhtKxuQ8frkNG8hMGAEusnW22qqeQahqF50VX322WfTBIpF9YrKqvRf1K6bMjZzjGAjQ9CuL9xyyeKMfQvGjhgtRmKzZdMqiglDwkKYsgcffLBlbI1slmTiWhB8D9sc886JQ3R9JBUCTFdZkLZeZMWOEx30eNhsYMNBvA/sXLBhysdjqrI+7KJgpEVvIiAJyJtY6EwICIESBKJXANb/WeomW28VBuHxxx/34chIXJeq9F+3z3b155prLo/fUSTNKGrLHC+44AIPToZR6kknnZRW4x6GogTigqnJUt1s1tH40WxPst10fY7h6XrrrVcYpIvOYXy6zYqdneSgx4tjm02PP4s881F1feTxIrKp6E0ExIC8iYXOhIAQKEEgeqK0y9aLl8drr71W0tP/ogxTIb+pFjW6+eabg+VlCmzsUK/7Lxqz2zIzlA2EcM8TEg1C+ucJ906YjyIxPbjDzKA6yRJeMXPMMUeoypgxBt4dBMUi5USWYICyqprsvbJz1gND0Er9wlrxFoGpyrojk/gT19S6NOjxsvMjNUJeclR1fXgJmS1RWGihhbJdTvhzMSAT/hUQAEKgGgJVs/XiakhGaUvi6BmhORKCHLsIvgKhaB+RzxDMvewXOlEo+fo/9thjueXUTf+77LKLxx+JffXriHoku444Dhsvaypi0IiCeuGFFza5afYym7UZ57sawBJahltuucWZGjNKdRuUBRZYwKfJM1l66aXDWWedFafd8khdQswTpjxPVbNiD9t4MGdHHnlkMM+sdEm8vzCA2IJEqro+6vPMcf8mW7cog4BxlCNJ8oIZyceqRfUQgbpeMAzdLlsvdexrPbF8IO45QLRP05u7iy2eFrapUcUpmyHY1CyJbc7eZsUVV0y23377ZL/99vOM1HiKZKnT/ukDDxQLoOXRObN9lp134gVjdiCJSScSPHsiXXLJJYnZSfgayaptkp14q+Fom1+TG26vslnjVgquJkXyeXDcd999E5NEpXOwuC1+D68P2zTT8qITIoFuscUWRbeSqlmxh208vF8sT4+7R1uslsRitCQmwfH3OrvQquujDd5HZvycbV7pfNS9YOSGW+k1UCUhMHoIdMKARBSI5WHGgKWxEQiFHgnGJU9shoQrjxQZEDbgV155JTGJSWlcibr9M45JHjx0eByzyrETBoR+iQlhniZVhmiqw5h5Ai8zOE1MIuTryN+vc22qg4TYK+BcRGC78847F91qKOMZmbSroayTi2Ecj9gxrfCps0aem+WRScyItU4zrzvqDIi8YDLSIJ0KASFQDQH0+UWeGdnW2cSE00wzTfaWn2Ng2SojMZmH89Eo8x100n/egDDfZy+vSUJGxFdE9/nMt+3GwbYjT+DVTTbrbH946GCn0orw+CBzbTtq94zatY/3h3G8XiUCJCS/SZ1CUUTXuP6JepQNyER98lq3EBgyBKJxJl4Fo0B4nZx33nlu9Ikdy3gh4orAYBKjZBA0yuNhu4QB9aCwHMTz6uUYkoD0Ek31JQSEQEcIPPbYYwFjSMhsPoLZjrj0gLwc45mQuBDMqhMPk7FaN94yK6200sCGH+XxzD6mpZRvYAAP8UBiQIb44WhqQmCiIGB5RMIpp5zif3HNU001VTwd98foYTLuF6IF1EKglYqxVicjXFkMyAg/XC1NCIwXBGJK9/EyX81TCAiB7hGQDUj3GKoHISAEhIAQEAJCoCYCYkBqAqbqQkAICAEhIASEQPcIjLQK5pFHHgkbb7xx9yipByEwgggQnRHabLPNmqJvjuByO15SjFqKkWzW9bfjDtVQCFREgAiso0yTEe1kFBdI/ggLBDSKS9OahMBQIEAGV2w38FgRCQEh0HsEiP2yzz77hCWWWKL3nY99j0+PLAMy9thqBkJgtBFYY401PKfLOeecM9oL1eqEgBDoBwJPywakH7CqTyEgBISAEBACQqAUATEgpfDophAQAkJACAgBIdAPBMSA9ANV9SkEhIAQEAJCQAiUIiAGpBQe3RQCQkAICAEhIAT6gYAYkH6gqj6FgBAQAkJACAiBUgTEgJTCo5tCQAgIASEgBIRAPxAQA9IPVNWnEBACQkAICAEhUIqAGJBSeHRTCAgBISAEhIAQ6AcCYkD6gar6FAJCQAgIASEgBEoREANSCo9uCgEhIASEgBAQAv1AQAxIP1BVn0JACAgBISAEhEApAmJASuHRTSEgBISAEBACQqAfCIgB6Qeq6lMICAEhIASEgBAoRUAMSCk8uikEhIAQEAJCQAj0AwExIP1AVX0KASEgBISAEBACpQiIASmFRzeFgBAQAkJACAiBfiAgBqQfqKpPISAEhIAQEAJCoBQBMSCl8OimEBACQkAICAEh0A8ExID0A1X1KQSEgBAQAkJACJQiIAakFB7dFAJCQAgIASEgBPqBgBiQfqCqPoWAEBACQkAICIFSBMSAlMKjm0JACAgBISAEhEA/EBAD0g9U1acQEAJCQAgIASFQioAYkFJ4dFMICAEhIASEgBDoBwJiQPqBqvoUAkJACAgBISAEShEQA1IKj24KASEgBISAEBAC/UBADEg/UFWfQkAICAEhIASEQCkCYkBK4dFNISAEhIAQEAJCoB8IiAHpB6rqUwgIASEgBISAEChFQAxIKTy6KQSEgBAQAkJACPQDATEg/UBVfQoBISAEhIAQEAKlCIgBKYVHN4WAEBACQkAICIF+ICAGpB+oqk8hIASEgBAQAkKgFIHJEqPSGropBITAhEfgpptuCmuttVb4z3/+k2Lx3//+N0w22WT+FwunmmqqcOedd4bFFlssFukoBISAEChC4Okpi0pVJgSEgBDIIjBp0qTw+uuvZ4tans8333wt7+mGEBACQiAiIBVMREJHISAEWiKw0EILhcUXX7xB2pGvPMUUU4TVV189zDzzzPlbuhYCQkAINCEgBqQJEhUIASFQhMDWW28dJp+89U8GKpktttiiqKnKhIAQEAJNCMgGpAkSFQgBIVCEwFNPPRXmnXfe0MpsbJpppgnPP/98mG666Yqaq0wICAEhkEXg6dafM9lqOhcCQmDCIzD33HOHFVZYoVAKMuWUU4YNNthAzMeEf0sEgBCojoAYkOpYqaYQmPAIbLnlloUY/Pvf/5b6pRAZFQoBIdAKAalgWiGjciEgBJoQeOmll8Lss88eYDiyNOOMM4bnnnsu4IYrEgJCQAhUQEAqmAogqYoQEAJvIDDTTDO5pwseL5FgOjbbbDMxHxEQHYWAEKiEgFQwlWBSJSEgBCICqGHweIn0r3/9K2y++ebxUkchIASEQCUEpIKpBJMqCQEhEBF49dVXwyyzzBJee+01L5pzzjkDHjJERRUJASEgBCoiIBVMRaBUTQgIgTcQmHbaacOGG24Y8HxB/bLVVluJ+dDbIQSEQG0EpIKpDZkaCAEhgMoFQ1TUL9h/iISAEBACdRHoOBfMbbfdFp5++um646m+EBACI4AASekIODb99NOHhx9+2P9GYFlaghAQAjURIE/UUkstVbPV/6p3bAOC+DWbGbOj0dVICAgBISAEhIAQGLcIEB35z3/+cyfz7zwbLszHd7/73fCpT32qk4HVRggIASHQFoFFF100bLPNNmH//fdvW3ciVwAj4rBcffXVExkGrX3ACJx88snh6KOP7nhU2YB0DJ0aCgEhIASEgBAQAp0iIAakU+TUTggIASEgBISAEOgYATEgHUOnhkJACAgBISAEhECnCIgB6RQ5tRMCQkAICAEhIAQ6RkAMSMfQqaEQEAJCQAgIASHQKQJiQDpFTu2EgBAQAkJACAiBjhHoOBBZxyOqoRAQAkJggAj84Q9/CEcccUQ47LDDwnzzzTfAkcfPUHfffXeYeeaZw1133eWTJq/PRhtt1JThmACU2ZgPxIBYYYUVhm6h5Cu6/PLLC+f11re+Nay77rrpvb/97W/h29/+dnj00UfDwgsvHD796U97kL20QoWTQY8Xp3TzzTeHH/zgB2HuuecOm266aeB55Klsfb/85S/DbLPNFhZYYIF8s8FcJx2SzS6xOCAdtlYzISAEhEB7BBZZZJHkyCOPbF+xpMYll1yS8HtlP9Qltcb3ra233jpZa621OlrElVdemVx77bWJZThO7r333uQd73iH47Xzzjs39ffCCy8kxx13nN8/6KCDkmeeeaapzjAUfOtb3/I58tzzf+uss046xQcffDCZa665Et6zqaee2usutNBCiSVXTOtUORn0eMzpmGOOSd73vvclO+64o69h8sknTywOTMN0263PUikkPOcf//jHDe2qXpx00kk+dtX6uXpPhVxB5UsxIJWhUkUhIAQ6RKAXDAhDP/vssx3OoHfNvvnNb/aus1xPnTIgX/nKV5LTTjutoTcYvrhpn3322Q33uIBRsTD8iQWjbLo3LAWWLDEx6UBiX//J66+/nv599KMfTc4777x0mmussYYzXRT85S9/ST7zmc/42rfbbru0TpWTQY/3yCOPJN/5znfSqbHOt73tbcmqq66alnFSZX2W08nr3XfffQ1tq1yIAamCkuoIASEwLhHoFQMy1otnMzTxeN+m0QkDcv/997u0A4YiS0cddZR/VVu6jeQtb3lLcscdd2Rv+/l73vOeprJhKYDhMFVS03Qsd5mvBykOZGqn5IILLmio9+STTyZIEt71rnc1lJddDHo85oJkI08WDTeBEYpUZ3033nhjsswyy8SmlY/dMiCyATFWXyQEhMDoImAbbDARsyfOi0mz/vSnP4Xvf//7Ybfddgu//e1vwxVXXOF6cLL82gbkYJDt96abbgrYDBgj5HWwJ9lggw3Chz/8Ya9z1VVXBfsa9b7t6zmgbzdxvGcJRi+/ySabhB/96EdhvfXWC9hVnHHGGWGeeeYJpgbw9pdddplnFR6LlBb77LOP2zswrzytvPLK4b3vfW/Yfffdg21q4Re/+EUwVUVajVxgeWLt2CM88MADYf755w8f//jH/RjrgSdYgO+yyy4bwO6hhx5y2wVC7mfJGIFw3XXXub3J8ssvH1ZZZZXs7dJzU6UUJkfjeWOvgq0LNMmSqC2xxBINffHMPvShD4Wi9TVUzFwMejyGfuc735mZQQi847yH2bDoddZnkpOwxx57+P8JnvegSF4wg0Ja4wgBITBwBGAuYALYUNlEITY+Nhl+cMllccIJJwT7yg9bbbVVOPbYY70Ohpa0W3311cPxxx8ftt9++2D2Ec5cfOQjHwnf+973vB6MhKkpwqGHHurXM8wwg/dz8MEHB/s69DI2vPe///3BpAm+cbA5R4IB2mWXXeLlwI6//vWvnVlgfa3o85//fDDJSoAZ+OQnP+lMVau6YAOjMNVUU4XPfe5z4aWXXgomJXG8aPPiiy+GLbfc0pmSc889N+ywww7hZz/7WTj99NPDSiutFEwqkXYNk3LIIYeED37wg+Hd7353WH/99b3PtEKHJ5deeqkb1sbms846qzOF8ToeYU5NdREvOz4OarwnnnjCsYWp4xlEqrs+2pr6LTYfzLGyrCVX0WYnI9QcJroUAkKgtwj0QgWDbpvfq6997Wvp5Pbdd18v++EPf5iW2ddwYoxJev3www97HZNOpGWI8WefffbEvGkSDPgg25z9Oq1kJ/RlG0JaZJtoYoxHeh1PUG/85Cc/iZcdH+uqYC688EJfm0l0msZEBRPtC1577bVk6aWX9rpZo1RjqNJ2qCBQWWCUmiXzJnHDzt/85jdebJ4i3s/HPvaxFDsMYHk2xhR6HWwZMIL9+9//nnZlzJ/XMYYlLat7grEsRqY8vzLCGJNnyzy6oUGNh+rEpCGODziaBK902mXrQ52C2o3nWZW6VcFIAmJPTSQEhMDoIoDkIU/TTjutF9nGmd7ii/2Pf/xjeo3qBVp88cXTsjnnnNO/3pGQ4LZZh4pUHahysl+tdfrrpi5qEiirVinqD+xQXVDv61//evjGN77RVA1VidkkBLMhaLj3iU98Ivzzn/9M20wzzTQucTAvk1TFAeZQxP2iiy4KuLR+6UtfcqkH0hRjGgJtjCFs6L/OBaou5sfza0VkeDcmKhhT5Cq1VvWqlA9qPFQnYM+7yHtqjGW45pprCqfYbn1mxOrqwG5wLhy4pLBZkVdSWbeEgBAQAqOKwBRTTIFXYNvlRXsF86xx25C2Dd6oUMSAVG3b63rMnfnAFLQjYkugcjLJhTMF5vrZ0AQ1FzT99NM3lJvHiV9HZqfh5hsXYA5F3E1a4jEtzDPnjRq9OZgrdoP6pajXL37xi2GvvfZy1U/R/Tplgx4Pew+YD+x2UCeaS3bTdNutLz4/mOvIGDZ10uMCSUB6DKi6EwJCYLQRePzxx32BpiqotdBhYkCQ/LDpv/LKK5XWsNxyy4VTTjklmHjejVKz7WaZZRbvA5uOLL397W93m5Bo9Jm91+ochgTDVFNvtapSu/y5555zI2SMh1vRmWee6YxHNkBZq7rtygc9XpwPTAMGzkVSrSrrw04Hytooxb77dRQD0i9k1a8QEAIjiQDRJzFijT/0eEyYrUTpWmE+EIEPC0UphsW+aJoSmz+MRp4s4FUwOxA3Sv3rX/+a3o4eQbfeemtaxgmGrvSFcWRV+sAHPuBMEeqeLGHUisFqJ4Q6BG+XVhsr92HGMELOEp5TndCgx4tzRKoFTngfZanq+iz4mkvFFlxwwWzzvp5LBdNXeNW5EBACY41A3Ez5Mo308ssv+yk2CpG4T102o6y0wuJlxCoBj4Of//znbicQC/nBN6PNgHfHxhtvHCxCdHj++eedKeGrEgkA7p3YMuDGS/8wL9iY4AHDZk4o8EESG7IFEwusLS/JyYZaz88JryEYC+wOIsE04C2DrQi2HDGstxnXuooKxgUyw1Jfex5z7mH3AeF5dOCBBwbUBTB1a6+9ts8Rj5Ks/Ql9Mk8wL7ProM8ydYgZIbvn0xZbbBFOPfVUqjujiFoJJm3FFVf0smEbD7sbmEe8k3iOEPjgxYXLeKSq66P+Y4895sxLFbVc7L/ro/1n6IhsYHnBdIScGgkBIVAVgW69YPAywUuF3yvCVhOq+pZbbknDjRP5krDbZvyYzDjjjF7PXEDdS4Ny2tkmlOCJsd9++7mXjNlDNEwfjwmCOFHX3EYT24g9IJQZYSZnnXWW1zXXUvcwmGmmmRLbxNP2eJOY/j4hGmU3VNcLhrEOP/zwxL7602FtQ0/2339/j3JqLpy+XjxX8oQniRk8NhRTzwxGE7NB8EijRFAlNLwxJF4PrxZz63WMjPlyrxdj5hJTi3iZMTEeGIzKtvknZmfj5fG5Wc6ShvEIl849IrmWkTGVjjseTXkyt+zEmMB0HPqLf7YJJ8ZEpk2GbTxTqSRms+HvrDFHibmBN4VTr7M+Y7wTnjleNXWoWy8YONKOiAelXDAdQadGQkAIVESgWwak4jCF1SIDQmhys3lIcFnNRw3NNiSUd6SijdvE44lJXmIVP+Lmyo9/t9QJA8Ic2ehhBOpSqxwwrPH2229PLJZG3S6b6tsXeWL2Nk3lFIDbxRdfnFgAucL7sRDGJ7oBx7JOjsM4HqHwYQbL3smqa2Uvt2B5Vaun9bplQGQDYpyUSAgIASFQhgBibnTjWdVMvr7FB0mLisTYuDkSqCxLuLkSSXMsiDmahCYQNI1ImnVojjnmKKzOGjFY7UXWYYxYozonPxiqMoxe11xzzfythmvUXL3w6BjG8Ygoi/qp7J1sAKPFBeo0PGhwgR40yQZk0IhnxkNfis82ERqJphiJyIz8OHz2s5+NRT0//vSnPw033HCDW6mvttpqwYINlY6B/pYIheh1Y7TI0ga5m3XHyzX3S4z/7MvLz/lPR/jq6MZXVD+fOpxw2FFfWlS/ahnGdtgCZInnxY8uLpr8CPeaMOZjXFMhBJ5X/OHFpqDfqeYJsd0qXTk2Duij8wQG/DiijzbVRv72uLj+xz/+4fPEsG9UidDkbK7YXHz5y19Ow9AP+3ot10uwgGlpPJF+z3dUx8Oji/Dt55xzToixcfqNZUP/qSyl5ol1IhVMTcyy1dEb2496Ym5TTUmq0KOaZXm2ek/P0cXaBpHY14XrPG0zT4ypKB2DlOboqmlTlzoZr2gMRMZmaJXqaRHBtiJEr2b853UtpHNihnOtqtYuRzdsgZK8bzMu9DlhN2DGiK4/RxeOyLaXhD4XXS//76JdAf3zXCjrV6p5+zoqTVeO+PdXv/pVEnXkZjSYkPXVmKLEQm/7e2bhvpNOo1iOlQrGAjslZpjo2BKZ036ge6Iq6eU7ke2rExVMtj3qpl6ogrJ96nz4ESD5XjcqnG5VMLIBGeN3BCOsfJZMNk/7+urLzDCgsxwYbvTGi0coavPjd0MtUjyXkVn4u/FeWZ38vW7Gy/fFNbp4wgWz6S655JJFVbyMFOMmJvZ6GA/2miy4kvdtX5ANXR922GFenjXua6jQxYXl2/C+swwI3fUz1XyVdN7MIYbLzjOF2BdstNFGiX1duXEmdevQWDEgbMYm3Wn46+aHus6aO6nbLQPSyZhqIwS6ZUBkA2I72VgSMQTyOjz0lv0Sh6E3RdSK6oJxyTKJ6xuZKnEvLCN0jjFTaFm97L1uxsv2E89RoRBECb2upZt2tVC8F4/2s+BZR8lOCuX17rFeN8dWagVCR4MRrphZd8NuxopteVeg/Psy22yzxSo9PaIaJDssidQgbByMwfL1oVLLUis8CIyEfpnsnbgMjoWeOTvPqufYZZjHSsNfHveqfameEBACxQgMzAbExOeezppIc/gvk7Y5pqVmM0S3Twx+frzR7Wd/0GhrrnPBXLF84ySrIuGBIfzY+aGE6AeffOrRH5kZ8cvnWIWqpN+O/aAXL0s9Tb0qdWJ/2SP4oOvfbrvt0uIq6cNjZTYH7CXYiLHtMElBIDMiRI6FvN0EvvaWqCtNUx37IUMl/vf4h9MH/dX9Ea46HjEYMIhjze38+nlHvvCFL4Rtt93WM5USIjpL1157rafjbtVPq/eJQFH2BZ8yDgQuIhsnvvT29eu5FrJ5QbJjxnNsQZgf9bPEO4lNCnYFxGDgPc1jWaVOtk/OGSefar5O2nNse84//3yP34C9Bu8La+YdMZVbT9KVY2hJJEb6Rte82Wab5ZehayEgBCYiAp0KkQyryjYgxjwkiFJpg982uuy9997b9eWIZxEpk8Vv0003TexHObEU1+m0sJVARYEfPb7y+K6bdXSDiuK8887zvtHZQmYUl6xovvv4gFcl3MY23HBD78eYJPdhNyPQBB0/In/biNOu0HkvtthiCeoFXO9MouA+2ei+I1WpQ10ybZJ9EWJ95557bmJf7Iltnl7GP2SMJAMn+H31q19NbONN0LVzTebKLBFjgHvYIIA7GSCxhSAmAXYERWRRB72OBURKb6P7X2qppRJjZjwmwhlnnJHYRuJue2mlDk+KxuMdYD3ZGAmtuid2AiJy3gvakO00S2ak6a53iAfzGLV7n3CTpH/axdgBln49zQ4ax0G1QJ28CoYYEJRb+vdYNdlzzz0T1FeouIzJ8P5XWmmlhvezSh3cCembGAsQ1zHGRcz0akyj/z+iHv+nyEi6++67+/vEu5yNbUBd3DDNuNWzj8aYDDx31HStiDgOqJqyxPwZM6+CiXXMiNbfReIucF6VxkoFU3V+w1JPKphheRITax7dqmAGZgNinh3+A4XRXKSYEjsb2OeAAw7wjQ4fZ+iCCy5I7IsyTaPMxs4PnVklx278CPNhX5/J7373O9+A8Y+uS2w49F2WfpuNr13q6Sp14tyyDEgsgxHKMiCUR6yw2YhEyu9s+nAYCDCAiYkEM0fwozL9NemxTzzxxNjEjxjBwiRGoj3GeGxY3VLReNi9mKi+KU5C0VgwCNDxxx/vzytrb2ESsQS7BaiIAanyPrGxw2zBKJMmPJ9mnL4jA4IdCgaLMHvMx1RECUGVMOqDYEpNmpcQHyGS5brweUeGuUod2uYZEMqKUs1jrMt7DM5xs8+nPacttjEw85FgUGkHk9uKWqXzbseA0F9k7O68885W3TeVR0Np5qW/cgz4nRRG5RgJn97jgw1hh/TUwFQw0TXRJAf2DvyP0AtDhPKNhH7fNnDPN4BbI+JaRNaI0+2r3sXN1P3973/vYvbYzjYbF5WTdwBRfivxe6xfdMT2AsqK2elnhx12cJcv22gCmR3xmy5KPY2rIuFwTfrSto5Jgoqm4GWIrPMUbULAJxJ2ENdff328dNdQMMqGUsYn3zZRD4NcZAthgXw8TLR9Jaf9oL6xTcLjA8RC1AX2ZRyMAYxFHR2LxqMjsLev9Vp9GoPgLqjYFViwKHeD5T1APdOKqrxP4EpabkJC88xRtbUi3HFxY0PNx/uKW7VJN9Lqxti5zUp8/7mBqy4xJYwZCmT9rFInq5JMO7eToncFNRDPixTm0W4kxkKIac/pwyQygfwR2Kpg88D/Q54D6r4iQkXVTbpy1D1Q/H9WNEa+jPmbZNQToOXv6fpNBHiPUPnah8qbhToTAn1GgN/Gst/HdsMPjAEpmkjRj2e014jZFtGnwwTww8cPK5sglNexk5GReAgYHsYfuqIxOyljw4D4sa6SejoGJIrpjeOYVdJTx7pVjujpjfNMq8KckHOC+B5snhC2MDBLRcwHTBw6eQwms2TeFn4ZE1bFe3mbhVhe9dhqvKrt8/XYlHfaaafw/+ydB9jkVNXHL1VARap0XQRRxFVEUARdUECpUqVIF2lKUQRBEOmC9G4BASkivXcWsaCCBRWVLkVxFwTECljId37n44ZMJplJpr3zzvs/z/Nukptb/8nOPTn16KOP9k2cH1/yVGBYW0ZV3ydsV4jNAjPHxhs38ny/2E2Yeipf7Nc8GxhWmMA88S5EhrZdHRjednFa8v3nr6PdT/Z9wXaGZ09sF1MZBWJ6wIwQZ6SI2qXzLmoTy4ilQcwS3kNsTKoS8+ajBbswUTkCML7YUQmncox0p/cImKS3MA5Q1ZHG1Aum1YYW7/EjbXEc/AfY8hQEExkXrg2GhP+EbLZ8zZP4qVeUTb9dJfV0lTq9mlu2HzDDeJVN09QnniDL1EruhZCtxzkbwsEHHxzOPffcpq/omKgLKUie4nPJl7e7bjVeu7at7vOs+XrHyJEAae2Ct1V9n0yl4p42bP6WZ6HVFErvgRWJyPAugonJEowLxLvSrg73+0Ew60iLSIhGwi6YfKQ5Frejabgq6bybGmUKYqZUs0VyI93MLZ0KASEwQREYUwakCuZskkSBxFMDyks+Yh+mtw5EukQNwlccP6q9omz67Sqpp6vU6dXc8v3gpkrKbDYXVAGoX/LZLvHE4AsfdUVWNQA3azY0/sVJv6y7F9RuvDpj8AVPf5HwpDJbChc/o4pBXN+KqrxPMEswM2ab5O+R2Xaknlax76wkIZYVHXkXEI3ffffdDbfxeCGcNc+mSp2Gxj26QKqDxAwpmNlnBP4PFamvqqbzLpsWki/eR9RO+TTrZW1ULgSEwOgjMDAGhB9hCPuOSFFVgrtnpKh6wZYB4pqNET0TIsbTTz/dyy2Cm3/Fc4HYnS9WswT3H7kDDzwwXHnlla5j98o1/ylKvx3Dj6MnZxy+6LL69Gzq6Sp14pRIxc0asxsaGFGOO2WkKJXIxpYAD+rGttzDvRMdO3gjUkcaEu/TF8wc8RiIHUEKcVJQ80d8B9yb2SRwlUadg3tm/HIFb9w96c8MHxvmFudYdKwyHu1wpUbNwHNsRbwL2F3E94O6qAaQNuy+++4NLtesH4oSLM6rvE/0gzQAFeFRRx3lUgpcfnHfjQSTAj1qLsqtiPb0A5aRYKKJj8I9VAxV6tCWdwKK/284j/+feBcicZ9nnn9XuJ9dA67XuFnzjKjL+xz/n8a+Yjpv6sR3BcYV1RfvQaSIQ7Z/3l9StPNOggH2P9EdPLbTUQgIgQmMgP1QdUQGWWU3XFw5bVN2C23cxcgqiVstXhz0Q9pmLPypF9Na47aIRwtlWOrbD5inbrYfSff8wLUUbw/7SvcQ4bYJpZ4eeFPQLx4huHdWJdvcvB0uvK3Sb+Nl0Cr1NOO1q8N9vA2IEMlcbcNL7Efc3VBJi0yZSSkSs+GonD7cNgl3C6Vt9o+w64Qwh3B1zt7LnjNeJFNVuBsu9/F+wZ0TjxpcUnH5ZP5VqOp4eEIZE9HyeeFBhdsrc8LVlmcfifkRuRIyJiPB6wr3Zuoas5UYU+rlrd4nY26T3Xbbzd17iXQKgf/KK6/s/RBS3L7m3c2b8SN2eMvkvbK88cv/WPwPf0dxbSV7J147RGrNUrs6eI7gSs2YhJY3hjwpSjVvzEfltOcm2ShMR7766qu7Fw9eMcbMpuuM6+XI/y1cevnDQwvXccrNXstD0hvT4f+vt9tuu+SUU05pcJvPrrvdudxw2yH0//flhlsNJ9XqLQL2MeKpGjrsddoMNLQfjtrEFycGbIMweuKL0Ta81HqeKfNFhu6/l4TdCCJpPCpss3ADzkkWjIm1FhFfpMY4ecZGPCCKqEqdonadlPE1jPEp0ThtYwhITcCNdSHhQBQejXyr9o/hLWodpCp8WecNa6v2U6Ue8y3z9qjSvmqdQb1P2fnwzqLeQsKAUSUSgTxVqZNv0831Lbfc4tIkYyr9HUG1hYQIqQhzHAaPCgzAjYkJ2H+JyhEAI6Rg2ICJhMCgELC4TW43hmS6A5o+pl4wVSeM50LWdQ+GoA7z0c4wkXng0mkBltIpsemijmhF2E8UeThk21Spk63fzTkqFNyQYZr4yxJqrjJPjmy9/Hn06KE8y3xg8MtfKyJarcV1aVWl4d4gmA8G7PZ9aph0xQve2eh2XtakSp2ytnXLUXmxaaF2QQ205JJLpl1E75i0QCcjjwBpDTB2JusrxLtoQSKbPljyGab5P05G3WEl7NhQ3/NhiX0Y821FeACidmZ/Mcm8u9a3qp+/N4zj8dFTls0aWzTU8RZvJ7+UgVyPCwakWyT4QW1HbLTRuDHq99u1Gbb7eK3AicKEYMMBw8FGY2oH3/z4UekVwZy1wzVr4NqrcdVPbxDAfoN3BVdjU7m4dxl2HGxA3LMgZb0ZSL0MPQIYqiMZtaCGLgGziLjuMo0xO3ZCWcI131R/bsSOnVQrl/dsu7E4x26PWDt8JJKPCMN70n3AWOQJ6RESP2zdMJTuZEMexvEs6KE7I+D+ji0ctl7YnGGzyAc3xufYvBEfaUwYSRP7dkT2ACvbgHQ0wIAbYfNAZErWhc3DsKffLoKHKKCEacdmxpgNt4HAPoFykRDIImBqKE+LYJ5Sbl+FrQf2V4TcN1VetuqYno+1DUg2vUI/gOhV/53agJAaI2+PZCro1O4nhv3Prp13h4i/MVp19t6wnJP2wIzs0+mYFCDBFg77pjzx24+dWIxMnL9f5XpYx6uSzZoUINSzD48qS22o060NCNbyHdGoMSD86GLEmP3jP9p4pWHaRMYrhhNl3vZVNLRLHUsGBCNn8g31i3rZfycMCB8mfGzlf+fIL8WHi0lQnTnF2DlPFlk3XzRU1+SyypOpHD3fV7ac30lyH5FiAgPuTmkYxzO1mqcyya7JJDye2sQk5NnixOzB/AOkobDCRbcMyIRQweTFbUXX6Pzq2JUU9TFMZaO0lmHCdRTnUtcwedgxQOeN3p8Is2Q0xg2YI4TaCddgjNiJ+LrMMssE88gLMfqv5WFy8TtlxBVCbUmk25i5Gzd0xPjEGcItnVQI2BWY11wgXUK3/aMKIJVElazQ3T6Hfffd19MfFKlmiYwLNgT6AxNUuVkbuSJ7sla4M1fcssEVGyzUxKh+UBFgmxGjTcc1oQqxpKLu9m9eaLVVPXl7K2OyPPUAgfayhI0agQJRRWbtDLN1qpwP43iTzA6QNCZZwhYGVVv++aGGxfGC/xs870HRwOKADGpBGkcICIGJiwCMBBsWTBXeYNhzkQeHiL8QP8AEgLPkeW7LQBm2THhgUUbkWwiDTPTjeCuxucDAYEdAGXFnMGwntgv2MujQTZXlTE03/TMu8Yvw+MmnR+BeL4nYSTBpRVFv4zh77LGHxzyCGSB2EExbGbXDnZg8GMnDDFr4BM+vRSwc4jqBXTYWFEwKAQOJgE3Y/g022MCfZdnY7cqJGxQN9Hk3skTwQjZjYj/BdGFojy0Expmd0rCMR8ydIuaSXE+mcmlaHtjgATpQqiBlKaxikxwpG5DCRapQCAiBMUWgjgoGcTqiZWLqZIkYMSYR9FhDlNvm6zYOWfuGmC3YJBppU9v4EmM80mtOsBPAvoo+IhFjht9DM170om76Rw1QNSt0HJ9jXRVMjJVETKY8oYKJ9hMW8C+xAIG+PjNKTasaI5aeV8Wd2EHgZAxfaZZmbDVQC2XVIcRkop0xLOmYVU9QLRgD6e3pY8stt0ybmjTLyy35qMez4QaZqo2JTIwRSbhfl4ZpvKK5l2Wzpi7qFNRuddT33apgJAGxt1IkBITA+EcAkT0SDPJBZYn8M1j/k6m6LuW/IBHT88WMeiIS3hOUxajBsbzKsah/skIXJY+s0l/VOqinoKxapagtEiDE8tTDO6QIw6q4V8nSjESC2EV4rCDB4o84RmR2Jq9VXUK1wDthhqae5RwpVgwfEKUcSFhi/i5UQRbE0GMe5T2Aqow9TOPl59sumzVei6jJOsE5P1bVazEgVZFSPSEgBIYagSqZqusuIM8gFLUnZhCBCAnaV5eq9F+3zyr1mStjwxS0I2xcyIuEXRkMQT5JZTe457M0E9gRNZZ55qR/BFdjUyTnU6eEPQTMB4QbMRTDBBAHI0vYp0BRHZe9V/V8GMbLz7VdNusY5wk7p0GRGJBBIa1xhIAQ6CsC8SsW24IsmVu624R0klW4CoNgImv/SjfVQXbYSudV+q/UUc1KxAkyqbvH/ajSlFgaFlLfcw9hpEjE3Ei9xB2GBMPUVvYmcdy6R2yBMCaOUp9o+IqBbZaIAYINUbdSqLEeL7umKtmssdOBosF2tn2/zsWA9AtZ9SsEhMBAEaiahRp1CZRNaFg0UZgDxNbtCIaHvmLG7l733278Tu4TUAx66qmnmpqz+cNU5Ylo0QQnwyg1JkakTlXc8/0VXZPIE+YmnzUZY+KYiLSoXZUypD70gyEsBCOCei5KRGIfpKwAg7zBarxf9TjW48V5Vs1mjQcX73y7COCx314cxYD0AkX1IQSEwJgjUDULNV++iMjJBk10SETtlujQ53/33XcHXDYhVAHYH5ihprtwxq9+9OTRhoJ6qCdWWWWVlAHppn++xqtkhWbcbgj3TFRHeH/kCRE8UXGLiNwf5A7KUlXcySWF1AV7nEgxizN2H9Bmm23mX+CoC4455hjHGY8gmB88WSJxvfbaa3u+rliWPWKXgudTjG7NPexXiFZqhs1pVQvEFvAKIVp0JLxw8L6xuCGxyMcfj+NVzWbNQnnmMGdV1HIpMN2eYP3aCdm48oLpBDi1EQJCoDICdbxg6BRPC7NTSMxINDnnnHMSPF3Itk0W7SxRPtdcc7m3g4WhTqJ3ABmL8YSAbCNyrwDq2cbrZTvvvHNiagLPmrzPPvt4dmmyRJsbr9+P/3Taf5Ws0HGM7LGuFwxtDzvsMM/MHPvB68NcgD3KKRm5LRx/YdZrY8oSPEey1A53vFrMrde9TkzykFgMkMTcVT3DOXsJ2dIJnAWZTYkHBqOcP5PWJGYwmh0uMaNUv0ck1yIylYM/W8sv5UHVDjnkEH/GRXXNhTixkPLuPUUUWJNkJQTsytJ4HM+Y2bbZrOMa8XzhmePFU4e69YJRJNQ6aKuuEBACA0WgLgMSJ2ei9uSOO+5I7Os2FjUd2TQj40A02KLQ4vQT69ABDIjZB3hfMDWmimjqNxZ00j9tW/UZ+84fO2FAmJ9Ja5wRyPfX7vrJJ58srFIF98KGBYX2RZ6YhKrgTpLgHnzRRRclV111VeF9CnmeMEv5SK9lDWCILB5J4e1RGK9wYS8XmpQpscB7raoU3uuWAZEKxlhskRAQAqOFAB4OGE7inVJGiJqjoSFGh0TozBP9xDr5exjrtcrg3Gn/rfrMz6Gba+ZH1NWDDjooVTtV7Y9gbkVUBfeidkVlGA+XJYXDRgXbG9QiZcTzXGCBBQqDcRW1wUC1zFB5FMYrWjNlqCDxEMIFetDU/D9u0DPQeEJACAiBcYIANgXYgGDPMApE1M9NN93Uo7tG25fxsC6yNlvAtKaQ4v2a+6iOhw0U4ekt+aqnEugXfmX9KhdMGTIqFwJCQAhkEOAr8eabb3ZDSvKo7Ljjjh7cKlNlXJ6SE2fy5MnOWI2XHFIE/Bokjep4PG+zlaosJeo15mJAeo2o+hMCQmAkEcDN1gxa07URJXRUKMbGGJX1aB3VEMDTayxJDMhYoq+xhYAQGDcIxMiZ42bCmqgQGHIEZAMy5A9I0xMCQkAICAEhMIoIiAEZxaeqNQkBISAEhIAQGHIEZsC5t5M5ErKVrJODjBvfyTzVRggIgfGLwA033OBRS4lMKSpHAC8NIozmo5SWt9AdIdA9AoStJ1owYdw7oOkdMyAWMdBzAnQwqJoIAfWJYuMAAEAASURBVCEwAghYBEnPkCrmYAQeppYgBDpEwKIOeyyZDpp3zoB0MJiaCAEhMEIIrLXWWp4vhRgCIiEgBIRATQSmywakJmKqLgSEgBAQAkJACHSPgBiQ7jFUD0JACAgBISAEhEBNBMSA1ARM1YWAEBACQkAICIHuERAD0j2G6kEICAEhIASEgBCoiYAYkJqAqboQEAJCQAgIASHQPQJiQLrHUD0IASEgBISAEBACNREQA1ITMFUXAkJACAgBISAEukdADEj3GKoHISAEhIAQEAJCoCYCYkBqAqbqQkAICAEhIASEQPcIiAHpHkP1IASEgBAQAkJACNREQAxITcBUXQgIASEgBISAEOgeATEg3WOoHoSAEBACQkAICIGaCIgBqQmYqgsBISAEhIAQEALdIyAGpHsM1YMQEAJCQAgIASFQEwExIDUBU3UhIASEgBAQAkKgewTEgHSPoXoQAkJACAgBISAEaiIgBqQmYKouBISAEBACQkAIdI+AGJDuMVQPQkAICAEhIASEQE0ExIDUBEzVhYAQEAJCQAgIge4REAPSPYbqQQgIASEgBISAEKiJgBiQmoCpuhAQAkJACAgBIdA9AmJAusdQPQgBISAEhIAQEAI1ERADUhMwVRcCQkAICAEhIAS6R0AMSPcYqgchIASEgBAQAkKgJgJiQGoCpupCQAgIASEgBIRA9wiIAekeQ/UgBISAEBACQkAI1ERADEhNwFRdCAgBISAEhIAQ6B4BMSDdY6gehIAQEAJCQAgIgZoIiAGpCZiqCwEhIASEgBAQAt0jIAakewzVgxAQAkJACAgBIVATATEgNQFTdSEgBISAEBACQqB7BMSAdI+hehACQkAICAEhIARqIiAGpCZgqi4EhIAQEAJCQAh0j8AMiVH33agHISAERhmBqVOnhnXWWSf873//S5f50ksvhRlmmMH/YuEss8wS7rzzzjB58uRYpKMQEAJCoAiB6TMXlapMCAgBIZBFYNKkSeHFF1/MFpWeL7rooqX3dEMICAEhEBGQCiYioaMQEAKlCCyxxBJh2WWXbZB25CvPNNNMYc011wxzzz13/pauhYAQEAJNCIgBaYJEBUJACBQhsO2224YZZyz/yUAls9VWWxU1VZkQEAJCoAkB2YA0QaICISAEihCYNm1aWGSRRUKZ2dhss80WnnnmmTDHHHMUNVeZEBACQiCLwPTyz5lsNZ0LASEw4RFYaKGFwpQpUwqlIDPPPHPYcMMNxXxM+LdEAAiB6giIAamOlWoKgQmPwNZbb12IwX//+1+pXwqRUaEQEAJlCEgFU4aMyoWAEGhC4Lnnngvzzz9/gOHI0pxzzhmefvrpgBuuSAgIASFQAQGpYCqApCpCQAi8jMBcc83lni54vESC6dhiiy3EfERAdBQCQqASAlLBVIJJlYSAEIgIoIbB4yXSf/7zn7DlllvGSx2FgBAQApUQkAqmEkyqJASEQETg+eefD/PMM0944YUXvGiBBRYIeMgQFVUkBISAEKiIgFQwFYFSNSEgBF5GYPbZZw8bbbRRwPMF9cs222wj5kNvhxAQArURkAqmNmRqIASEACoXDFFRv2D/IRICQkAI1EVAuWBaIPajH/0oPPHEEy1q6JYQmJgIkJSOgGOvec1rwkMPPeR/ExMJrVoIlCNACoPllluuvMIEvyMbkBYvAK6Ff//731vU0C0hIASEgBAQAsUIvPnNbw4PPPBA8U2VKhtuq3cAEfM555wTyIEhEgLDhgBZZ/fee+/wmc98ZtimNlTz2XTTTX0+F1988VDNS5MZbQSOOuqocMYZZ4z2IrtcnWxAugRQzYWAEBACQkAICIH6CIgBqY+ZWggBISAEhIAQEAJdIiAGpEsA1VwICAEhIASEgBCoj4AYkPqYqYUQEAJCQAgIASHQJQJiQLoEUM2FgBAQAkJACAiB+giIAamPmVoIASEgBISAEBACXSKgQGRdAqjmQmA8I/D73/8+HH744eHQQw8NuPWKmhH42c9+Fuaee+5w1113+U1y3my88cZN2X9/8IMfhD/+8Y9pB4ssskiYMmVKej1sJ7fddlu4/vrrw0ILLRQ233zzwHzLiPw/V111VfjTn/4UllpqqbDuuuuWVS0tH8bxCDZ58803+7NcY401wnve8550/r/4xS/CfPPNF97whjekZTrpLQKSgPQWT/UmBMYVAvzInn322eGee+4ZV/Me1GSvueaa8PTTT4c3velNYZlllglf/OIXPfT8Hnvs0TSFt7/97c6AfPzjHw/33XdfeOtb39pUZ1gKvvKVr4Q999zTAy0ee+yxvsled911hdO78sorw4orrhhgQog50wnzMYzjsf61117b33+eK2s8+uijUwze8Y53hCOPPDJ8//vfT8t00mMEElEpApZ0K7FAZKX3dUMIjCUC9sWanHDCCV1P4c9//nPXfXTbwbe+9a1uuyht/7GPfSzhry4dd9xxyWmnndbQ7IgjjkjsJ9j/zjzzzIZ7XLz00kuJhahPLFR9071hKXj44YeT73znO+l0LNpz8rrXvS5ZffXV07J4YoHuEn4Hf/3rX8ei2sdhHO+yyy5LjJlKLNikP7Nbb701sQzPiSVYTJhvJO6vtdZaHa3fmJfEGNfYlY7NCEyTBKTHDJ26EwLjDQHEzGNJ3/3ud8P+++8/llNoGvs3v/lNMOYj7Lrrrg33UL/stNNOngn405/+dLjzzjub7k+aNCnMOOPw/rSSQHCzzTZL500+nw033DCQeiJLSD6Qjpx00klh8uTJ2Vu1zodxvB//+Me+tplmmskzOa+22mqOCdGvf/rTn6br4/5ee+3lzzwt1EnPEBje/yU9W6I6EgJCoAwB+2IPMADZH90//OEPvulwj43YvvrDeeedF7iOxA/1TTfdFH74wx+GJ598MnzjG98I++23X7ohT5s2zTfwE088Mfz2t7/1ZozDNX+PP/54Wrb++uu7KuDrX/96QOUBofZA/E3fY0H77rtvQJUCw5GnD33oQ8GkI+HFF18MG220UZg+fXpDFfuKbrjmgpxSF110UTj44IPDN7/5zQDGWQLPW265JUydOjX861//8rrY5RTlEcEO46yzznK7HerXpbe85S0NTXiu9tXvG228QRLO7bffPrzxjW8MO+ywQyzu6DiM433+858PMBdZiqol7H2yZJIhf36XX355tljnPUBADEgPQFQXQmA8IvC73/3Ov/rYUH/+85/7EmAA3v3ud7uu/+STTw7HH398+MlPfhK22WabgB4fwtCSL+g111wzHHPMMb5B/epXvwrnnntueP/73x9MvO2Gja9//evDZz/7WW9Puw9+8IPhb3/7m5dhIwHxY4+u/VWvelVgo1psscW8nK9vpCJjkb8FpgvjTNZXRtiAkCMKZmCTTTYJfOWXEdisvPLKbuiI1OS5554Lb3vb2xwv2vzlL38JW2+9dfjwhz/s9gg77rhj4Av99NNPD6uuump49tln065h4mBi3vWud4Wll146bLDBBoE+OyUYDcZ+3/ve53OM/dxwww0+T5KpwYhhoAozcuCBB7Zca2xfdhyW8eaff/6mKcIU8j5iC5Innh+MuKjHCDSrZVQSEZANSERCx2FEoBc2IOj27Scl+epXv5ou0SQZXoZePJKlFE+MMYmXyUMPPeR1srYVJglI7Ic9MW+axDbkxDbyJluJq6++2stMepL2ZZtoYoxHes3JP/7xj+SCCy5IjGFpKO/koq4NCOOCiXkINQ335S9/ObWfeOGFFxLzmvC6u+yyS1rXGKr03KQkiRmjJl/60pfSMk5sU09mnXXWxKRDXm4Gnt6PMWmOHYURK2MKvQ62GtgUgE0kk054O2NYYlHlo0lcEmP6vD3r3XLLLdO2n/zkJ73cpDVexlqNIfQyYyrTenVOhmm8onmDvUnnim4lpoZy+xCeZ1WSDUhbpGQD0mN+Tt0JgXGFAJKHPBnj7UVZLw6+2KPahJuvfvWrvc6yyy7rR/5ZYIEFAl/vSEgeeeSRtLzKSV7VQf98eb/2ta+t0rynde69917vb8EFF2zZL9ghlqfe1772NVet5BvceOON7hGT/6r+yEc+Ev7973+nbWabbTZX9yyxxBJuX0I/YA5F3C+88EL3REF9gNSDP9Q/tDGG0OvW+QfVApIonhXP0RivED1h8I6aZZZZXPJFn6z1sMMOc6nLKaec4vOoMxZ1h2m8/NxxMcYdGc+YIjIj3YCarBOci/pT2f8jIBWM3gQhIATaIoC+3L5n2tYjRgRknjVt62Yr5BmQ7L1BnzN35gNT0I5QTaByMmmGMwR5o1TUXBCGnln6wAc+4JeR2cnei+fRRiHiji0NmyTGsfHv2muv9U1xq622is1qHzGahfmAULdBbLj8Ze1ZMKx973vf6xsxNiOd0jCMl537gw8+6DY12NWUUXx+2TgvZXVVXh0BMSDVsVJNISAE2iDw2GOPeQ3iZtShYWJAkPyw6f/zn/+stISVVlopIBWIRqnZduba6X1g05El7CmQMOQNHrN18ucwJPfff39XNhj5PuM10paFF17YpTmUwUhiCBylL7Ee0haoW8nUWI8X14M9DjY12C8VSQNjPex0oGijFMt17A4BMSDd4afWQkAIZBAg2iVGrKgl4tez2Q9kajSfwnxY3IzmG2NUQkAx6KmnnmqaAcamMBp5wjXX7EDcKPWvf/1rehuJAZQPZoWhK31h/FmV3vnOdzpThLonS2yiGKx2Q0h96AdDWAgDWyhKRPzC/kGiQ8TcbqODjvV4rAdvI9RZuBkj7YmEB1fe+4gy3tPFF188VtOxBwiIAekBiOpCCIxXBOJmytduJDxVIGwUInGfulEdEMuzEVTxcMCdN3rL8BWNuN2CXgUkI9gbXHLJJd707rvvTt16UStgy0BYeET7SBDwyiEs9u233x6HGtjRDG6DBRMrjA6LCP7RRx8tnAteQ3gBZQmmgc0cBiQrTcB9GQ8TGBfIDEsd2zzm3CMCKYTnEV/gFhzMvY9Q3+AlRB94skTimgifZS7M2KXwxc8GHAnXYJ4bc4JgjJi3BWJMnzk2EISbP+qooxrck8fjeDB/eC8RA4f389RTT/U/XJ/BMs9o8Mxhzqqo5SKmOlZAwH5QRCUIyAumBBgVDwUC3XrB2NdtYj/C7tlgX/2J2RMktuG7p4X9dCR4QtiXX2LGj4kFqfJ6Jq52Lw3KqbPKKqskeGJ84QtfcC8ZIkxmiWihc801V2I69GSLLbZIvve977mXDFEoTZ3gVc211D0MqGebuJfRj31xJmeccUa2u47O63rBMIgZXCbmepyOZ4yHe4EQ5XTeeef19eK5kic8gcygs6GYemYwmlgod4+sDCbrrLNOYgyJ18Orxdx6HU+THCV4vRgzl1hwMC8zJiaxfDRe1yQQiTF2Xg7+PDczGG0Yz9Qkfp9IrkVkMVv8efBMjXlIDjnkEH8u+brGcCQmIUiM8UlMxeTRZC1WS75aMh7Hs9w3KYbgmP1jzVkyxtufOV48dUheMG3RmgZ3KypBQAxICTAqHgoEumVAullEZEAITW4SC3dZtYBWhV2yAUd3WvvCLwxTbuL/tE7sxFQZ8bSrYycMCHNmo4cRqEsmeShswhrvuOOOxOJNFN6vU2hf5IlJlQqb4DJrQc8S8+wovE8hoeJhlsqeWbYhG7AZahY+N+qN9/Gyay06NylTYsHyim61LBMD0hIebsoN1zhfkRAQAl0ggLoCkTU68iJCbB2NFjG8LApTjg4+1ol95EODx/JBHJmzSV/CQQcdlKqKqo5LALYiYo0YrPYi6zBGrGV2GKjKMHpFDVNGPAPcpsueWbYdHj5LLrlk4XOj3ngfL7vW/DlqQzyEcIEW9R6B5pjBvR9DPY4xAq1SThdNDd0y8QDQX5Oiui7VSbtdpW9+4H75y18GIkoSs4AfXqJAYuBHHAYLoFSlm77UIcT2t7/9bZ8XP9LErmBDhrCcR9+eJzYifvzRt4/lJpufV53raD+A4eKo0pQpU3xzxeaCnChFjNMwrv2uu+4KFjAtNQLu9xxHdTzslkgHgHtujI3TbywnXP9thSQTuMIoqGDQLduGl9im7XpO9OpmbFb6VIlwacF4vK79xyutV3bDDNRcL41uGX22/Wi7bUFZ/XblFlfBReFEnDTr/8SYqeT8889P1ltvPbcRsK/mdl307b59HfkajZHwqJb24+H6cNQTEOJtY5xSHbnlmkjI+nr44YcnZujmz8XCfSedRLGk/7FSwRgTmFjcCX9HiMzJe4KYflipExVMdi08z2FeX3auOu8dAhZmv5KKqmxEqWDKkEnLZQOSQlFwMt4ZEAz5qqSczi8dQzc2U7OUz99qeU0a66ppvlt29PJNQmKTHpuw1eiZ80RoaIuNkC8e2DVpuk0q4+OZy6YbbYLbJz7xiYY5xHDZ6OWzhH3Bxhtv7OnOTZKTvVXpfKwYEDZjk+40/FWxJai0qD5U6pYB6cOU1OUEQEAMSNuHLBuQURZ5oQdGdEwAI3S9ZSmn8xhEUXM85u+XXePaViXNd1n7bDkxGHbbbTdXUVieksIgQQQQQp+OimbQhJsoqh8SqUEkt8KFD8xQeWWpTM1C4Cf0yyRhwyVwvOiZsQkwj5WGvyq2BFlMdC4EhIAQkA1Ij98B/PnJ5EnEwsmTJwdyPqDzzxJ5FvCnR49OzAH8y+MPOL72ZLxkI8MXn+yk9GVuYx6dkH64j94VMpfAYO6Sfk7MBEJBYwRHKm2C7MRwzl7B/iHlNBt6PgIjcQpoTzRA5gTFOflFhX/K0m6jR83SFVdc4eGc7cs0W9xwbmoKt6H44he/WGongUEjqd3t6ztti00GmUyxYyFmAthmoxe2w5fnh/Eh8Rh4BiblCASmIjaGqU/8mZGCnfgWEac4OPEsCMIVA3DF8lZH8CaVPTEv0DWbq2qr6ronBISAEBgZBBSIrIePEotpJAB8FWM9DyNC6GICLEXaa6+9POCP2TB4um+YBNKhP/PMM5XTcpPWnK9sy1rqm2Pse5VVVgnmp59GM6yacvqAAw4I5513Xvjc5z7njA5f8lBdBiTOgyNBqYrSfHNv9913D7vuuiunpRRzamSTnRVVJh15NBDrRdpzcj4QTApMpk6dmuKLFIMvf1J2YzwK41eED/dhWuoQqdXpG4kVDJJICAgBITAhEGirpZnAFerYgBC0hwBEBPmJZGJ6N06M6bQxQLSNLCEeQCSCMdmL5kZ9lBF/gOtWabmph72FfaEntlFy6URsAMtGGi8Lj/mU0yYtcDuKbMwF5skczLujsI92ha3SbtOWAFgWCbK0G+wJCFzFHMCwCmGX0Ku054xnUSATgk5lnxWBucC4jGKQLdKmZ4n05awlbwOSrUMKd+pgdFuVLIqjt6Gd/oSB3oHhewew0xKVIjBNKhj7X9sLQuyPq6hFOEy7Q0SPSoCvWwh1AYmusioZwlUTQ8E8OzzDJV/afFkjOYmi/Hxabvoi2Zd5ULjYHlsI6iLCJyxyGRWlnEY9gtoga6eAOgAq+sIv6ztbHtNu22YdLJqj2zmgWojYxPwY2TbZc8aNqqOqOUJapT3HTZZQ0xYZ0kMpV8GXVOeoXHgunPMc+SP+QhExzy996Uvh6quvbsp8WlQ/X4bqB4pp7vP3i6555oTLjrgW1VFZCMcff7zDgPRRJAQGhQAScAs8N6jhxuU4YkB69NgQ/7N55NUekfkwHtDtEghElCdScxPfAhVO3PyzdeJmTB9ZYmNk82HTQxXBHCyscrZKeh5TTpM7Iku0wQAyS50yHtk+OMdOAiNLC0HtSa3qbJQwXagkmPcKK6yQ77rpupdpz+mcMflDpQXO5ItoFW+EWBFscKhT6hKxNFDTEYiL+CZVifcCFVUrW5qqfY1yvZh/RjiN8lMevrWR1yifzG/4Zjm2M5INSI/wxxCSJFoYiBYRmzqGnyTryn/VxwRQecPQon6yZdgaIAlhk0QCUGZ7wAaHlCSfchp7Awxho71Ftm/Oe8GI5NNu58cou1511VX9lqlzyqo0lPcy7XnsGMaDZGswQjfccENpZEmMSGE8PvrRj8amtY4xUyoGyxi+ioSAEBACEwEB/dr16Cnj8QIh7s8SxqV4fUCoHhDjkwk0S3jF4LkCM1GHYBAw5mSTRr1AFM48wWBg6FqUcpqvbr64f/vb35Zmzsz3V/c6n3a7antLbhZwU4VpQkpTRqh5iDga1TpxM4/1O0l7HttiUIyxqdlwuGFxlETF+xx5tkimLHFZtjiYPUjDddkFEh68mFDD5dOsl7VRuRAQAkJgFBAQA9Kjp8jXL1/B2A3ssssu7kFxwgknBAtKlX45k8Yat0s8TiIhOeELm3tscNgCsKG1Sssd23Kkf/JWEAY8n0ujSsrpfffd17vDM4V4GszHjCW9jJThMFBVqUqab/qCaSpilrLjsBZwQrJBTos8Y8FcEa0T5wTVVy/Tnsd5gKsFEQuWiTR1dY73ON56663u0QTOMZ03jN7OO+8cfv3rX6dVYZIgMzD2I/8gfSKMPG7CvBPY58DsiISAEBACEwYB2+xEJQjU8YKhC1J2W+4UDxFu0onE1Ahelu3e4n8kZhvhEUrJVknK79NOO82rGPNROS13tk8ibxZ5i1RNOX3MMce4x4dtuMnyyy+f2Kbu6adNBdGU6js7bv68appvPD7AAM+hdkQYbNKS4xXD3PDyMSPXxCQ3iW36DaGS8SBizr1Iex7nRdhxs6+Jl+kRvI3xKfQ+AUdj3PzPXKUTwsXbD0pi+V8SYzj8z+xhku22287TnJuUKu23zslYRUKtM8dhqKtIqMPwFCbeHBQJte0znzYDVSYMt1VzoSQVI2gXngZ1CJsLJAnRLiHfFsgfeOABV8eguuELuBtCzRIToHXaD1/klp7bI4vyRc8cowFtnT5ZN2oXVEplNiRIL7hXp3/sZixPjcfhIBkdXkJFKhHmai7FrlaiXi8yj/YC3zoYVq3L2jB+tXD7VZtMyHqbbrqprztvgD0hwdCiB4YAUm2CGmKMKipEYLq8YApx6a6QMNWtiM03HzW0Vf1297plPugfl864WRNhNEuf+tSnspeF57j/4pGBESWZXltRJwwXzAaYVcENN+cib6NWc2p1rxf4tupf94YbAVRwGIjH6MP8/7UcPiH//4ToxiYFTRdjEqpARt1hpbpZq2HgJplnW5GnXpU1Dnq8OCdUn6g4LbmcR5MmGnQR5deHbZ7F2vHs20X1VdY9ArIB6R7Dke+ByKvt/vLuxyMPihY4IRAgFcLTTz/tBuK4k5MagJg2lmW6af2E7IcBwb4Jl3pi/gwrWUbsYFmvXQqLHRXSwuuuu650ujBhlgE5sCl3QoMeL86RWBwrrrii218hKSxjPorWR0Rr4iTl7c9i3zr2AAFUMKJiBOragBT3olIh0B8ExtoGhIi5/SKyC5vrc0+679QGxDzLUvusOJEjjjgitfs588wzY3F6NBWk21OZyjAtG7aTulmrsU3DZsm2m8RU0rWXM+jx4gRNPemZps0gPBYVHlutDzs1C2+QtOujqGPZgBSh0lCmbLg94OHUhRCYcAgQ72b//ffvy7qx90GKEL2H+jJIm05x3zbj8KacRahfUDeisiROTD6GDvcnmZpimOO51M1ajUs8uZE6pUGPxzyRfCDZwSsthkgom3+r9aH6JcBgqwjTZf2qvD0CsgFpj5FqCIGRQYA4NGXZgs3jyF2D2TDMm8sj2MJoxDgsZAFGVE/Z+uuv74bEBMEjXgvJFVE/EJUXN2vioNx0000BOwhcmUkYWKV/7IeIOIuLczRkxsWdTMOoQjDqw/W8nZ1Rtw8M93SYIBiKPJE8EnUMKgwwMY+osOCCC6bVYE7y1Ap36mIEDq4wLmVZsGOf2DLg8g7eK6+8clhttdXirUrHvB0VhuMYSqJuyBNxbkgXwXo7pUGPRyJMsoGTNoF3rxVVWR+pJVDf4DbP8xb1DgHZgPQOS/UkBIYaARgJNiyMJ/l6x1uLSLUEe4PY5Nn0CbwWQ0hj+/O3v/3Ny7BrgDDIRD+OMTGby2KLLeYh9ynDKwejZWK4EAuF+DLmjh5gaqr0/8ILL3iOI8aBeaF/mBeIr1qkLv32ZkH6AZNGrqUywgYE7ziYAVIZsL4yaoc7gfTIHE1MmLPPPjuYq7nHBjr99NMdu2effTbtGibl4IMP9phDBBEkBQPPslNqlbWatbHp7rbbbp1239RuEOMRtZh3mwjTMJG8RzAjBx54YMNzqrM+/t+Y+q1pPSroEoEGjYwuGhCQDUgDHLoYMgTq2IBUzRZsm6/r+rP2DSbV8DKTaKQIEBvFGI/0mhMzUvQYOPQRyX70va1FefWiKv1bUkdvYwkEYzd+RFdvuYUSY4gayttd1LUBYQz7WU0sUnBT11/+8pcTywvk5cYsJeYR4nUt+GBalzg3kariXiULtklREouWnIBDJPvC9/EtmGEsqnxslbUaWxYztk3MNd/7I1s2mHRiAxInNKjxyFrNXOP7w3MyxtXLyEwN1V2fqXISk2wlPM+qJBuQtkjJBqRL/k3NhcC4QKBVtmCi7pItuC7l1RNEpEX9kBXXWyA2L+vEk6Cof75o8xF/6867Xf17773Xq2TVKkVtkAAhIaAeYfSLMKyKO1F3WW+rLNgXXnihe3OQWgGpB3/E7qENMXLqUsxaTSJMXOhJHBk9YYjijLdPL1VdgxoPTx2kfDE9As/psMMO87QTp5xyimNYd3249qMm6wTnus9lItVvVlZOpNVrrUJggiDQTbbgMojyDEJRPWKoEF+G4HR1qUr/dfusUp+5MjZMQTtCvH/ZZZe5mzoMAa64WeoG9xhoz74jvUtyNqHGwji2l4TRbDZrNaqLSy+91NVpMFgQwfgg8lhRhp0Kc+mE+j0ezAJ/WVscbGvIFwVzOXXq1Nrrs0jMvlTsblBbinqDgBiQ3uCoXoTAUCMQo/KSd+gDH/hAOld043wt1s3ETAdVGASi3vKVTqbfulSl/7p9VqlP/A42fbJbx42nVTuC3vFlTQ4gjBSjzQpteok7DMn999/vdgz5IGit5lflXjZrNZvs448/3hDrJDJB2N8gJUHa0ykDwnz6OR5Gs9jKsAaMpiMhKYIwCK67Pux0IOydRL1DQEaovcNSPQmBoUWgarbg+NWIMWgrgjnAXbYdwfDQVwwAVaX/yHhU6b/d+J3cj1IMi0XS1BxjU5iqPOGmSRJKDBtJBRCpKu6xfqsjCRdhivJZkzG4xGC1G8pmrcbLByYk+0fWZghPGco7YSiz8+vneDF1RjSkjuMijUIaZzmyGtbGetqtDw8u3kuyVot6h4AYkN5hqZ6EwNAiUDVbMF+PiMjN0DI89thjHtGTrMMQ4ndcNiG+fpFsmKGmu3CyMULoyaMNBdeoJ1ZZZZWUAanSf/yyhnnhyztmFsbdlTDgt99+O133jZZbbjnPrXTPPfc0jcFm9ejL2Y3zN08++eTw/ve/v6G4Ku5mWNo2C/Zmm23mX+B4GlkCSccZiQTMD140kbgmg/STTz4ZixqOVbNWNzRqcTFs46Eeggk555xzHFOmzntJqHzys0QGt8WSmm7xzPFSqqKWa2qsgnIE7D+4qAQBecGUAKPioUCgjhcME26XLTguCg8Yy2fkGYjxhLCYHol9OXoGZ1MBeDUTcbtXAPVs4/UyU0EkpiZIzG0z2WeffRKyMVt8kCavlSr9W2wL91owN+DEGCHv35gZ97KxWCBxqpWOdb1g6NSMFj1TdRzAGA/3pDCbFs8UbcGrHM94Px7xGjGDznjpx3a449Vibr2+XjNoTSz8e2Luqp4F2n65E2NiEgsV7n3ZV3xiTJzX5Z5Ja5oyVpuqwe8TybWIqmatzrY1BtP7LPKCGbbxmLcxHIkZ6ybGtHnGad4Bi1mTXVLDeav14fky77zzJnjx1CF5wbRFaxocoqgEATEgJcCoeCgQqMuAxEmbyD654447kj/84Q+xqOnIphndXc1LJikKLU4/sQ4dwICYbYL3ZTr2BNfNMmrXP26SbPp5atVnvm687oQBYX5s9DACdckkD4VNquBe2LCg0L7IU8Ysfxu304suuiixBGz5W+k1zxNmCZy7pWEcL64J5sHUK4Xvb6zT7mhSpsQC77Wr1nRfDEgTJPkCueGWy4Z0RwiMJgIxW3DMfly0SkTN0d0Vg8ei0OL0E+vk+8BYb84558wXp9ft+kdMjodJnlr1ma/bzTXzI+rqQQcdlKqdqvZHMLciqoJ7UbuiMoyHswaW2TrYqKC+Qg1TRjxPXGw7UUfk+xzG8eIcZ5111rDkkksWvr+xTqsjwffwEMIFWtR7BGQD0ntM1aMQmJAI4KqJrh17hlGgKVOmhE033dTdUaPty3hY11133RUsYFqDG2o/5z2q42EDhdHtWWed1eDZ1E8sJ1rfcsOdaE9c6xUCfUCAr8Sbb77Zjf7Io0I4cYJbjXciJw7JzGCs+JoeD0TAr0HSqI7H88aQtRdSokE+j/E0lhiQ8fS0NFchMKQI4GZrKdvT2RF9clSoXUTUUVmn1tGIQPTGaizVVS8REAPSSzTVlxCYoAhg3yASAkJACNRBQDYgddBSXSEgBISAEBACQqAnCIgB6QmM6kQICAEhIASEgBCog8AMOObWaTCR6pJIi7DMRIYUCYFhQ+Daa68NRBblT1SOAC6pEBEyRUJgUAjgwkuE4IcffnhQQ463caaLAWnxyLDmJ1W1SAgIgWYEfvWrX7lnyNJLL918UyVCQAgEwvrvt99+QqIYATEgxbioVAgIgXYIrLXWWp4ThjgJIiEgBIRATQSmywakJmKqLgSEgBAQAkJACHSPgBiQ7jFUD0JACAgBISAEhEBNBMSA1ARM1YWAEBACQkAICIHuERAD0j2G6kEICAEhIASEgBCoiYAYkJqAqboQEAJCQAgIASHQPQJiQLrHUD0IASEgBISAEBACNREQA1ITMFUXAkJACAgBISAEukdADEj3GKoHISAEhIAQEAJCoCYCYkBqAqbqQkAICAEhIASEQPcIiAHpHkP1IASEgBAQAkJACNREQAxITcBUXQgIASEgBISAEOgeATEg3WOoHoSAEBACQkAICIGaCIgBqQmYqgsBISAEhIAQEALdIyAGpHsM1YMQEAJCQAgIASFQEwExIDUBU3UhIASEgBAQAkKgewTEgHSPoXoQAkJACAgBISAEaiIgBqQmYKouBISAEBACQkAIdI+AGJDuMVQPQkAICAEhIASEQE0ExIDUBEzVhYAQEAJCQAgIge4REAPSPYbqQQgIASEgBISAEKiJgBiQmoCpuhAQAkJACAgBIdA9AmJAusdQPQgBISAEhIAQEAI1ERADUhMwVRcCQkAICAEhIAS6R0AMSPcYqgchIASEgBAQAkKgJgJiQGoCpupCQAgIASEgBIRA9wiIAekeQ/UgBISAEBACQkAI1ERADEhNwFRdCAgBISAEhIAQ6B4BMSDdY6gehIAQEAJCQAgIgZoIiAGpCZiqCwEhIASEgBAQAt0jIAakewzVgxAQAkJACAgBIVATATEgNQFTdSEgBISAEBACQqB7BMSAdI+hehACQkAICAEhIARqIiAGpCZgqi4EhIAQEAJCQAh0j8AMiVH33agHISAERhmBqVOnhnXWWSf873//S5f50ksvhRlmmMH/YuEss8wS7rzzzjB58uRYpKMQEAJCoAiB6TMXlapMCAgBIZBFYNKkSeHFF1/MFpWeL7rooqX3dEMICAEhEBGQCiYioaMQEAKlCCyxxBJh2WWXbZB25CvPNNNMYc011wxzzz13/pauhYAQEAJNCIgBaYJEBUJACBQhsO2224YZZyz/yUAls9VWWxU1VZkQEAJCoAkB2YA0QaICISAEihCYNm1aWGSRRUKZ2dhss80WnnnmmTDHHHMUNVeZEBACQiCLwPTyz5lsNZ0LASEw4RFYaKGFwpQpUwqlIDPPPHPYcMMNxXxM+LdEAAiB6giIAamOlWoKgQmPwNZbb12IwX//+1+pXwqRUaEQEAJlCEgFU4aMyoWAEGhC4Lnnngvzzz9/gOHI0pxzzhmefvrpgBuuSAgIASFQAQGpYCqApCpCQAi8jMBcc83lni54vESC6dhiiy3EfERAdBQCQqASAlLBVIJJlYSAEIgIoIbB4yXSf/7zn7DlllvGSx2FgBAQApUQkAqmEkyqJASEQETg+eefD/PMM0944YUXvGiBBRYIeMgQFVUkBISAEKiIgFQwFYFSNSEgBF5GYPbZZw8bbbRRwPMF9cs222wj5kNvhxAQArURkAqmNmRqIASEACoXDFFRv2D/IRICQkAI1EVgZHPBPPnkk+EHP/hBadCkukCpvhAQAq8gQFI6Ao695jWvCQ899JD/vXJXZ0JACPQCAdSaa6yxRnjd617Xi+6Gro+RtQH5whe+EI466qihA1wTEgJCQAgIASFQFYGTTjop7LHHHlWrj6d6o5sNly+05ZdfPvz0pz8dTw9EcxUCA0PgqquuChtssEH497//LRfaFqg/9dRTAUPb733vex4JtkVV3RICPUVgscUWC+xlo0qyARnVJ6t1CQEhIASEgBAYYgTEgAzxw9HUhIAQEAJCQAiMKgJiQEb1yWpdQkAICAEhIASGGAExIEP8cDQ1ISAEhIAQEAKjioAYkFF9slqXEBACQkAICIEhRkAMyBA/HE1NCAgBISAEhMCoIjCygchG9YFpXUJg2BA4/vjjw2yzzRY+9alPDdvUhmI+RIy96667wj/+8Y/wzDPP+Jze+ta3hne9610N83vuuefCDTfc0FC25pprhrnnnruhbFgumO83v/nN8Pjjj4d11lknrLbaaiGbJblonhdffHGYNGlSeM973lN0u2XZoMfLTuZXv/pV+P73vx9mnXVWX+uiiy6avZ2e59d3xRVXhA033DC9r5NGBCQBacRDV0JACNRE4KyzzgrnnntuzVYTo/pf//rXcMwxx4TJkyeHlVdeOdx3333h4x//ePjgBz8YHnjggQYQiHb5lre8JRx55JHh8MMPDwsttFCYa665GuoMy8Wzzz7rcZbYmH/zm9+EtdZaK6y00kotp/ezn/0sbLXVVuEXv/hFy3pFNwc9XpzD008/HT75yU8GAluuv/76Yeeddw5lzEfR+ogfs+OOO3ragtinjq8gIAbkFSx0JgSEQAcI3HnnneG73/1uBy171+TPf/5zuPHGG3vXYQ96euKJJ8LWW2/tkqHXvva14dWvfnU45JBD/CsaxoQgcH//+9/TkQi7vdxyy4XNNtvM/1ZdddWhTfLHlz5SHRjPqVOnhoMPPtiv77jjjnQ92ZN//vOfXofcQZ3QoMdjjo8++mhYeumlw4svvhiuv/768IY3vKF06mXrgynbeOONw0477VTadiLfEAMykZ++1i4EeoAAGysZcseKiBSJVIENY5hor732cvF7Po/HkksuGT784Q+He++91zMJJ0nSMO155513aNUuTJTIuR/5yEfCPPPMk86bjMjQnHPOmZZlT5AgHHDAAdmiyueDHo+JMeamm27qa/za177Wdq6t1ocaDWnXsDHIbRc1gApiQAYAsoYQAqOMAKHKUcNEwubhlltu8S/jf/3rX+Giiy4Khx56aJPK4Y9//GM4/fTTPWHk7bff7mLuU089NTz//PPe1bRp08Jpp50WTjzxxPDb3/7Wy5C0cM0ftgd8nSIxuPXWWz355Ne//vVAOwjxOeoMElMOmpAOXHfddWGTTTZpGnrmmWcO3/nOd8ISSywRrrzySle3ZCvNOOOMgb88obogLwhruummm5oSbf7hD3/w+y+99JKrRY444ohw3nnnBa7zBF7cB/9ol5KvU3aNHcTiiy/ecPvXv/51WHfddV3V1HDDLrCDWGqppcIyyyyTv1XpetDjMSmYJdJ4fP7zn3fJVauJVlnfZz7zmbDffvsVPotWfY/6vea3fNRXrPUJASHQEwSQPJxzzjmBL/r999/f+/zLX/7iage+8M8++2zXf//4xz/2jQ6VArp86IILLgjveMc7wt577+0qCjZKNrHdd989UA9RPTYQr3/968NnP/vZ8JOf/MTbYTvxt7/9zcuwp3jhhRcCX5jQIoss4jYUURrD5s68EN8Pmo4++ujwvve9L6B6KSIMS5kf2YQPOuigcO211xZVS8uQpnzlK18J6623nq+XjfFDH/pQyjxcc8014d3vfndgozv55JMDhsFghmSCdpH4sscmAeYMhgGGDoPY3/3ud7FKrSPSG/Blc/3qV7/a1PZPf/pTuPzyy8Nuu+3WdK+TgkGNd+GFFwYYxXvuucdx5jlNmTKlyX6l6vqw/8Fept1z7gSTcd3GHuhI0j777JNYMrqRXJsWJQR6gYBtgMj+E9uUuupuo402SszYLu3DJBjerzELiTESXn711Vd7mW2UaT0zSEzM7iExI8a07MADD/R6Jvb2Mu4xxzPPPDOtE/syKYCX/fKXv/Q65pGR1uHEvE4SY3QSY1gayutemATF+7dkdJWbvvnNb05s8y+sb4xXWn7ZZZc5BqamSe6//34vNylOYpKgtM63vvWtxFQbiXmBpGXUBRcwjGRMgJeZdCMWJWZTkhhjkl4fe+yxiTE86bVJTbyNqVTSsqon4GvMTDLHHHN4H2Ywm5jkJ21ukpdkiy22SKZPn+5lZvfi9YxRSevUORnUeCaZ83kuu+yyiUmHfIrgbQxxYoxIwn2o7vqM6Uy+9KUveduq/5jBa2LMZNXq463eNElAxjX7qMkLgbFH4FWvelXDJHDJxaASFQNfkdDb3vY2P6I2iYTtCPezonm+pCnD5bEuMWaW6B/bkDIpRLZuL8+RMvz+9793CU67fo15c3F/kVFqbIu6CSlF1pYElQZqkPPPP98lQtSNkh/qRgL3LOZIRu6+++7w6U9/2v9Q5+B5EyVTsV2VI/h+4xvfcEPaE044wY9ZV2zKjAHxTMJV+mtXZ1DjRS8djISjnQt4gx2u1FHSU3d9PD/sfkSvIKA4IK9goTMhIAT6hECMD2GfaC1HsK9pd3PEq6Uu5RmQuu17VZ/NHPVUZAja9Yt9DOJ51CioTKJKiXbgxaZV5OL6gQ98IDzyyCPu2lsWVwPcI+bE0UBlgFspqpxeEfYqqH5+9KMfuboFu5zHHnssXHrppa5iQwUDYQ8EwQBRhooKNVtd6vd4kdGbb775GqbGfCFUfxiV1l0fahzsnkSvICAG5BUsdCYEhMAYI8DmZSJ797KoO5VhYUAWXHBBj9+RdbFttRbmjSTjve99r9uFmLjfpRO04R72IhhEwtRERo57pubhUNljJhq2YtfQSwbEJ2H/rL766m5TgkSMjRbJyx577BFvp4wQNiMY6BLErBMGJHbYr/GQdkA///nP41B+xA13lllmcYlaJ+vDPipKAhs6nsAXUsFM4IevpQuBYUMAg1UMSzGQhKIKh7IyiowHG/SwEGolvIPyhDQiSgKy93BfxSi1SEwPYwIzg+QgS6gKMNJ905velC0uPWcM1DaoEKKnUawMA5RV1cTyOkc8lSJjg4Esm3T278EHH/TuUPtQjitvN9Sv8WAgmVs0fI5zZP4YR2NQWnd9eCLhjYVaUvQKAmJAXsFCZ0JACHSAAFILbBhwv4XQk7PRYgsRCa8LKL/x0SarFzejzLDKKqukDAhfo5MsdDduq4j1EX9fcskl3hcbMj/s8Ssa5oVx8aaB+IJFNYGL76AJ9QiShjzhIkyAsiKGClsMvIOipCK2PeqoowJSBTyFIrFu1su9KBXBOwjK487ziWoYM873zZ8NFFzAEC8cnl8MtEW/4HbGGWfE4RqOPENceImAGglXXvrCLqIuDdt4zP+4444LuDWjVoqExxCBybbbbrtYVPnIM+dd/+hHP1q5zYSoaC/mSJK8YEbysWpRPUSgWy8Y+5JPzOUzscBZ7jVgrqGJGV8mJnb3a/uSTPB6sR/fxPJheNk73/nOxEJW+yosrHVim2diLpoJ/18333zzxL6gm7xW8IDBwwIPBLwq8EbBO8DsDlLPEctD4v3jeWOMivcfPUxsI+0KtU68YMwOJDHpRPLQQw+lYxvjlJgrp89zjTXWSG677bb0XvbENvcGLxju/eAHP0iMEfM1X3XVVe5hYzFS0mbGTCQmCfG+zcYjMUYnMVdS956xjSw5+OCD3SMJzw0LmpWYZMnrcsR7xqRHaV8W3dTvgbltmml5PMEbxfLYuPfOCiuskOC5ZPFJEpPSxCqFR4sW6v3mvWCGbbw4ebPLSXiv8FzhmZhULjEbmni76Vi2PirifWSSk6Y27QpG3QsGzngkSQzISD5WLaqHCHTLgHQ7FRgQ06l7Nyb+T3DTLCNce6M7LW7D2Q2TNmysJtZvat6qz6bKJQWdMCB0hSuxeZuU9Nq6mDHzxBpNApSYPUhiEpT87VrXMI+4OLNpFpGpj5Jddtml6FZaZjYNpe3TShVPhnG8OHUYaBjKTonnRkgIk6bU7mLUGRAZoU4IOZcWKQSGG4HFFlus5QRx7eUPwhAwT9iBEIgsT2WhwfP1+nFNwK8tt9zSVRP5zLftxsO2I0+sETVNLwgPnaz7c75PVA8mpckXN1z3MlHeMI4XF7vwwgvH046OBJEjVHv0oumokxFtJBuQATxY/McJeTwoGvR4ZesyEbO74aFPRQfaC8KWgDDS/aBB4zbo8fqBWTd9YoyJXhybkVEkbDmIFIvRJ14s44WwJcEYlhglg6BRHo8otESoHRSWg3hevRxDDEgv0Szpa9Dpygc9XtGy+Y+35557uvW+6T/dwA3Xu24JwzjCd/eDBo3boMfrB2ad9omx5c033+zGkfvuu2+waKaddjXU7TAeJVgXadnHCyE1Ihz+oGiUx7NItYE/UTECYkCKcem4lPTUeepnuvJBj5dfW9E1USDNYM69AEgOhvsa0SiJ6NgN4WbJ1yRBm7BI74aK0rf38zkNerxusBlEW9xs8WghNgIeFb1SLQxi7p2MET1MOmmrNuMXgSK14PhdTe9nLgakh5iyKcakXNluCSFcNSpitl2780GP124+8T6+8mQojUQEQPOCKE3VHeu1O5r1v7toogvvhpmBkSlK396v5zTo8drhOAz3EfFjQxD/+vH/YxjWqTkIASFQjoCMUDPY4N+ObzwBfvCt33rrrZsM29BXEzCIaIWTJ0/2gDX8mMIMrL/++h65kK9+DJdiUB4CEpEF8ROf+ITru1Ej4KuPjnittdYKb3/72z2fgyWd8iBF6AtjlENC/hIQh9gGBMBhI4eqjpdZnq/L3Pl8DEtSFchYGoM4UQ+/d0Ikk5GU7Jhs+Hy5YUiXj02Q7Td/nv+aNSvw8PDDD3sa8Wxd7DnAAlyqiKjNqyAg8SGgD3iai6NnYs32Gc/LnhMxEVgPdiQY+rF+fPOJJZF9TvQDxqRVh8zV1ENYc847grSE9ttvvz1FHpq56DnVGc87sn8IOnX99dd7fAyMM3lOWSPNXj2nOJ6OQkAICIExQaC2X9A4aVDXDRcfdhOXJbbpuO/7YYcdlrzxjW9McFeLZAGTkrXXXjvBP5wsn8QkIAaCba6JBeFxP+/555/f++AaH/qzzz47MfVDQ7ZQMkYS/yCfgTLvtmdBfRLTxbqL4SOPPOJxAMyY1adTZzwaWErzZNNNN/W5GoOVkJGTvo0J8P7IMMrc7SVMGNc2Vvd75/rLX/6y1+nkH1wjTdqQECMiT8RnoH9iSbQjC+qUmFTFqxEHgXbGKBU2a/WcyCgax+Ud4XmDQdFzonNjTnwsC5aUjoVbnUWUTN0+Wz2nuuOR2dUY24QYFrgmEj+A+BdkRIV6+ZzG2g03BXTITzp1wx3yZWl64wCBUXfDVRyQl19CC0Wc2Fd+mjo6pviO6aVhJkjPbAZl6WtrkRaTWWed1YMtUWjZExP7Uk3vxxOTaDQwIJRvu+22nsY6m2KbAEKPPvpobJYsueSSDXEE6B8GKFLV8XqZzjuOXeV4yy23JCYN8Q0chsEkDw3NCGhUNV36Tjvt5AGo6IAYEDCHbMxZ/LhX5TnFZ5tP3170nGAueS8OOOAAunfiGZGGPFK751R1PJOWJJbJtCllNwwc75mFnvYhq6Rdj3NrdYwMCM9Gf8JA78DwvQP8vzdvuVb/jcfzvWlSwdj/Ooi00aglUAUQJtmiLXo5BpQW7c9F4raRhHXWWcfL+Yf6iMvtJUnLsiqNWJhPV0456bBRuZCDgXP64c821tjMRf3YJUCoRBC9x3DLsVKV8dql87aIim6fEfXw+XTeN910Uxyu1pFkURga2obtqiM8H8A5YsjasMVoR8ZkuJcEqi0IddCuu+4aSN1uUTLD5z73ubQLVBdVnhMN8tgVPSfybJCdFI8ViybpuUk4N4YoHROVTLvnVGW8G2+80fFaccUV0745IS/Ft7/9bU/ehUtzr58TfcecKw0D68IRIEw5MT14/komppdikAh86lOfGuRwAx9LDMjLkLOpwXxY2F0PeATTAWG/AOF5wSZjagq/jv9kmQ/K8ptarJc/0j9/bKowIOS6wDYhS1hQ46qIvQP5MUhklM/Q2G48Y497ls47O7c653jEwHwQ+Ag7iciAVO2DDZ8cGmAQySI4+ukpp5ziqcBjPoyqz4nG7bCLY/F8mLOpP4JJnfxdOOSQQ+JttxNq95yqjAeTCWG0myXyikDZnCnZ+5yzfp51J7TJJpsUBvfqpK9RbINtEAyIhXkPFkp9FJeoNQ0pAgQxG2USA/Ly0zUbi2A2EQFpAC6CGH9mCUaETc9sBtwoMHsve151U6MNGxuJjUjGdMMNN6RJtmJ/lmPBJTFIIPjqJVFXntqNx/1epfPOj13nmi9HDHPJNFmHwB3DUzbn/MbMxgkmV1xxReAcqvqcqNsOO+pAGAojCYFZJBon11mq8pyo3268eeaZx7vlfYhMBwVIxYj+yXMUCQEhIARGBQG54b78JBGv4j4a04BHyUd80Hi8QIirs0QWSDZAiA0Gl8uqhKsq3hVmIBrMKDTNakl7GKLDDz/cg9hEkXt+TlXH61U676rrKqpHHAxUKXh01CE8ccjMmWc+6MOSnnlXWZfcqs+JhlWfFTij8jGbFs+SmVUbVX1OVcbjOUHf//73/Rj/Ieso76ZCOUdEdBQCQmAUEBAD8vJTRLqBmB8bAtxDY+h0y37oGyeumuRzwG7DkjSFqVOneuppXEjNMNR7wZVz+vTpgUBcuJ1GNQGumOiRCTudJb6md9hhh2DZQVMXz3g/hqdGNYPdB+6zbEwEbuIe9iJVx+tlOu84v1ZHbBmQWhBqO5IZfAaio0b3YsrbpUtHpWAeOKnrcewrHhGHm5V4uOOOO/yP8qrPibpIGhgjpm8ve07U5TnzvMzg1IOqUQZVfU7UbTeeZYoNZpzsz9mSs9HE6Yc//KHjFu1Ooh1Qq7Trsa2OQkAICIGhRcB+gEeS6rrhkqkQzwozRPTU4WTntBj+iYm93UUTkHApJY22fRH7n6lsUldM7uPSSXpr0ljjWooLbz5deT7LpX1Bu/cM7fNkm573h5cFLrqXXnqpe0N86EMfSkzyUmu8XqXzzs+x6BpPITxULMRygveK2UukHizZ+q3SpYOTqTrcO4M02Lg+ZwmPEZN8JGaX43VIRY5XB9TuOVEnm77dYrq0fU604Xng+ZSnds+J+lXHI+urqeYSs5dJLI9IQip6sz9JeB8hM3itlHbdK7f5J3rBkF1WVI6A3HDLsdGd/iIw6m64MwDf0HJHXUzM4k64vUadJFCoOAhGFj0agAbRd97QFFUCdaPOPjtNJB0YtBJ6vCohKZhjjjkKqyPpyPbFV3rWW6POeKwH2xb6RFWR7adw8C4KwQe1Swz2VdYVX/P9ylja6jmBBdKtOqGSu3lOdcfjuZrbrQeCQ8rTD0K9hVEtkpSiDLP9GHNzbsuzAABAAElEQVQ89okRKgbqeMbJCHU8PsHxO2cCEGKIipp+BGm6jFAzTxXGITIfFKP7zzMflLdKQ01U1LpUxnzQT5b54DrPNNQZj/Xko5TSZ1Wq4hKGmsDipTgTViW6ab+YD9bU6jmBRR3mg/66eU51x+O5rrTSSgwrGucIoHoloi7qOmzGIFzdUelmCYYZY/Qs4QI+rMbHzBfVKupCvMRMytdgx5ZdRzy/+OKLwyTzisOuqy4Nerzs/PCuQwXOfsBayz4K8uvDPjBGr872p/P/R0AMiN6EygjghtiO8m7K7errvhAYZQSQZGFPtttuuzlTfvTRR4dDDz3U093DlCy11FLp8mE6+UDAMw4DaTzyWjHRacMxOHn22WediYBJfuKJJ8Kpp54all9+eU9RUDYdbN3IDGtq6doMyKDHi2vAHpB4Q0hLSQXRKqlg0fr4CMOFmySairUTUX3lKAbkFSx01gaBj33sY21q6LYQqI4AKjoMkfnK7wf1u/92c2ZjxnvqvPPOSyWZxI/BKBzGBPUXOYWilBMpGcEN8Y6DATEbs3ZDjNl9vvRhoKIa2lJXeAwlDMLJWZUnDPKjp2H+XpXrQY/HnAigSKwm3k+cE1pR2fpg0FAzIxkmnpGoEQF5wTTioSshIAQGgAAbLO7M/Mj3g/rdf5U5o7tH/J5Xk+JJhTs6geW22WabpgByuOYPq9qFdWMzRHTeyHxQxjqgMpXqF77whWDpDLxO3X8GPR7zY0zLneVrRPLRjlqtDwYG2zu8A0WNCEgC0oiHroSAEGiDAEbMZdl6r7nmGndBJ26L5TZyg2dcsjHmxm2cr3sMqYsyEqO+w70dOyzctTGSxaWdTTzGSOmmf8ZHJ49NRr+leUgHrrvuOk8VkIcTUTzu9XxdmyeSx/shmF0kbNH4yxNZunuVzZps0EhfYHRiPKL8eGXX2EEsvvjiDbdxZSeGUozDk70J5qiaiITcCQ16POYIs4QDA6kesnaBRfOvsr7PfOYzrsqB8Sx6tkX9Togys84fSarrhjuSIGhRQqAFAp244ZJYzzaZ0my9DIcLMe6DkUwE7S7ZFkjNi8yYsCkjsQVbS0gGaD+6noEY12Mzek6MaXBXdFzQI3XSv8XP8eZkvCaDdR3qxA134403TiwXUuEwZKKGyPCMu7qpXtKElpRbxN3EbCo4TalX2axxXyfp5YUXXpjwLC2CcDLffPOliQ7TASuemLdbctFFFyUW6TixXFVNrUwNlZjdh5eb2smfr9lDNNWrWjCo8XhPCKmw5557Jmb75u7+Fp24yQ2/6vrMhsTXTibvOjTqbriI/0aSxICM5GPVonqIQF0GhM2rSrZeNrUsA8KUzbYhiQwI12x+MBvZjMQPPfSQl5l0gipOFtgvMcmI92dSFC/rtH8aWy6ixAK7eT9V/+mEATEJTmJqicIhIgPCzRgLx9Q0CfFooDwD0sts1scee2xy0EEH+Tj8A9PAczCVSlpW9cS8ejwrtHmHeR/EPzLJT9ocZsGST6YZxrtlQAY1HnGEwITs58Rbgng2MMMwjNyH6q6PmFKWa8zbVv1n1BmQZjmfIS8SAkJACOQRaJWtF505Lpl1CcPLSFHUjRt3pOhFYD/6np4gllc9ZvunDaqcIiPJqv1VqQcWqI5Q+bQjk/q4uD8apaLeylO7bNYxMm5M2ZDPZp2Nqmup3cPdd9/teajIRXXkkUe65w1eJnWJ52VBB13NdsIJJ/gx66pPGdmvq7jjVxl7UOOh6oIwEo52LqiQwA5XajxaoLrrwxaoVUJJ73SC/SMbkAn2wLVcIdApAt1k6y0bM88gFNWLrqp4tWRD+RfVzZdV6T/fpttrNnOMYCND0K4/3HKJM4F9C8acWa8g+1LuWTZr4mjgToptznrrrdduWpXvY9OAjYNFkw6XX3652/g89thjwdRmYe+99/YyOoupGWCAqEduoypMWn4i/R4vGg2baqph6JiL6b777nOj0rrrwy4KRlr0CgJiQF7BQmdCQAi0QCB+DfYyW28VBoHNDCIjcV2q0n/dPtvVJ+Mz8TuKpBlFbZnj+eef79IZjFJN3O8SCupyD0NRDCJhamaaaaa0i8iMVfWYicaPZnvSUwYkTshsXjz6NMES2WiRvMSEkdSBmYJwqcVAF4lZJwyId2L/9Gu8yPDiIp4lYoAQMRi36U7WRx4vsoKLXkFAKphXsNCZEBACLRCInijtsvXi5fHCCy+06On/N1YqsKm2o9tuuy1YXqbAxg71uv9243dyH48PQrjniU04SgKy93BfhfkoEtODO8wMkoMsoSog1UFVxowx8F5BhUDKiSzBAGVVNdl7Vc9JHRAlK5avyjdpNur49+CDD3pXqH0ow5W3G+rXeLxnzM3shRqmx/zx5kKFV3d9Zi8SzJYoLLHEEg19TvQLMSAT/Q3Q+oVARQSqZuvF1ZAIkmeffbZnhOZICHLsIvgKhOKXbz5DMPf4Qo9EMC++/smkHKmb/gkMRvyRfpN5TDSsI45Hxm3WVMSgEQX1ggsuaHLT7GU2azPO982fDdQSGzpTY0apHhgtRvnkmRAq/YwzzojTbjjCvBxxxBHBPJfScp4vDBJ2EXVp2MZj/scdd1wwA11XK8X1WLLRsPTSS3uk2lhW9cgzx/2bbN2iDAJVrXHHWz15wYy3J6b5DhqBul4wzK9dtl7q2Nd6suKKK7ongf1gJ6bvdxdbPC1sU6OKUzZDsKlZEtucvc0qq6yS7LDDDokFd/KM1HiKZKnT/ukDD5RJkyYlthlku2x53okXjNmBJCadSPDsiXTJJZcklszO10hWbZPsxFsNR9vcm9xwe5XNGs8NcMXF1LYBP1qo8cQkUekcLG6L38OrpQgnvFEsj427D1ssk8RimCQnnXSSP/e0k4ITixbq/ebdcIdtvDh1MnDzjuK5wjMhKzfutGVUtj7q431kkpOypqXlo+4FIzfc0kevG0JgtBHohAGJiBDLw8JuF8Z+iHVMBRFPnXFJL14+YTM0UXxaHBkQfuz5MTeJibs6phVyJ3X7p7lJHhLcietQJwwI/VsEzcQ8TeoMldZlzDyBlxlAJiYR8nXk79e5NjVQQuwVcC4isN1ll12KbqVlxFYpa59WqngyjOPFqRPrA4ayU+K5WZ6cxIx0a3cx6gyIjFAz0iCdCgEhUA0BbBXaZevNJiacbbbZmjrGwLIsIzGZh/PRNvMddNJ/Ppt0vs9eXpOEjIivqCbymW/bjYNtR57Aq5ts1tn+8NBpFZkUjxaT0mSbNJ33MlHeMI4XF7zwwgvH046OhOQnVHv0oumokxFtJBuQEX2wWpYQGG8IRONM3EVHgfA6Oeecc9zoEzuW8ULEFYHBJEbJIGiUx8N2CQPqQWE5iOfVyzEkAeklmupLCAiBjhAgKR3GkJDZfLixH9ID8oCMZ0LiQrCubj1MBokB3jKrrrrqwIYc5fEsDH2plG9gAA/xQGJAhvjhaGpCYKIggJj7lFNO8b+4ZmIujApFD5NRWY/WUQ2BMhVjtdajX0sMyOg/Y61QCAw9Akg6xru0Y+hB1gSFwJAhIBuQIXsgmo4QEAJCQAgIgYmAgBiQifCUtUYhIASEgBAQAkOGwEirYB5++OGw6aabDhnkmo4QGA4EiM4IkbE05gkZjpkN1yxi1FKMZLOuv8M1S81mFBEgwuwo0wxERhnFBZI/wgIBjeLStCYhMBQIkMEVuw3CU4uEgBDoPQLEftl3333Dcsst1/vOx77H6SPLgIw9tpqBEBhtBNZaay3P6XLWWWeN9kK1OiEgBPqBwHTZgPQDVvUpBISAEBACQkAItERADEhLeHRTCAgBISAEhIAQ6AcCYkD6gar6FAJCQAgIASEgBFoiIAakJTy6KQSEgBAQAkJACPQDATEg/UBVfQoBISAEhIAQEAItERAD0hIe3RQCQkAICAEhIAT6gYAYkH6gqj6FgBAQAkJACAiBlgiIAWkJj24KASEgBISAEBAC/UBADEg/UFWfQkAICAEhIASEQEsExIC0hEc3hYAQEAJCQAgIgX4gIAakH6iqTyEgBISAEBACQqAlAmJAWsKjm0JACAgBISAEhEA/EBAD0g9U1acQEAJCQAgIASHQEgExIC3h0U0hIASEgBAQAkKgHwiIAekHqupTCAgBISAEhIAQaImAGJCW8OimEBACQkAICAEh0A8ExID0A1X1KQSEgBAQAkJACLREQAxIS3h0UwgIASEgBISAEOgHAmJA+oGq+hQCQkAICAEhIARaIiAGpCU8uikEhIAQEAJCQAj0AwExIP1AVX0KASEgBISAEBACLREQA9ISHt0UAkJACAgBISAE+oGAGJB+oKo+hYAQEAJCQAgIgZYIiAFpCY9uCgEhIASEgBAQAv1AQAxIP1BVn0JACAgBISAEhEBLBMSAtIRHN4WAEBACQkAICIF+ICAGpB+oqk8hIASEgBAQAkKgJQJiQFrCo5tCQAgIASEgBIRAPxAQA9IPVNWnEBACQkAICAEh0BIBMSAt4dFNISAEhIAQEAJCoB8IiAHpB6rqUwgIASEgBISAEGiJgBiQlvDophAQAkJACAgBIdAPBMSA9ANV9SkEhIAQEAJCQAi0RGCGxKhlDd0UAkJgwiMwderUsM4664T//e9/KRYvvfRSmGGGGfwvFs4yyyzhzjvvDJMnT45FOgoBISAEihCYPnNRqcqEgBAQAlkEJk2aFF588cVsUen5oosuWnpPN4SAEBACEQGpYCISOgoBIVCKwBJLLBGWXXbZBmlHvvJMM80U1lxzzTD33HPnb+laCAgBIdCEgBiQJkhUIASEQBEC2267bZhxxvKfDFQyW221VVFTlQkBISAEmhCQDUgTJCoQAkKgCIFp06aFRRZZJJSZjc0222zhmWeeCXPMMUdRc5UJASEgBLIITC//nMlW07kQEAITHoGFFlooTJkypVAKMvPMM4cNN9xQzMeEf0sEgBCojoAYkOpYqaYQmPAIbL311oUY/Pe//5X6pRAZFQoBIVCGgFQwZcioXAgIgSYEnnvuuTD//PMHGI4szTnnnOHpp58OuOGKhIAQEAIVEJAKpgJIqiIEhMDLCMw111zu6YLHSySYji222ELMRwRERyEgBCohIBVMJZhUSQgIgYgAahg8XiL95z//CVtuuWW81FEICAEhUAkBqWAqwaRKQkAIRASef/75MM8884QXXnjBixZYYIGAhwxRUUVCQAgIgYoISAVTEShVEwJC4GUEZp999rDRRhsFPF9Qv2yzzTZiPvR2CAEhUBsBqWBqQ6YGQkAIoHLBEBX1C/YfIiEgBIRAXQQ6zgXzgx/8IEyfPr3ueKovBITACCBAUjoCjr3mNa8JDz30kP+NwLK0BCEgBGoiQJ6oFVZYoWar/6/esQ0I4tdsZsyORlcjISAEhIAQEAJCYNwiQHTkP/7xj53Mv/NsuDAfF198cfjYxz7WycBqIwSEgBBoi8BSSy0Vtttuu7D//vu3rTuRK4ARcViuvfbaiQyD1j5gBE4++eRw5JFHdjyqbEA6hk4NhYAQEAJCQAgIgU4REAPSKXJqJwSEgBAQAkJACHSMgBiQjqFTQyEgBISAEBACQqBTBMSAdIqc2gkBISAEhIAQEAIdIyAGpGPo1FAICAEhIASEgBDoFAExIJ0ip3ZCQAgIASEgBIRAxwh0HIis4xHVUAgIASEwQAR+//vfh8MPPzwceuihYdFFFx3gyONnqJ/97Gdh7rnnDnfddZdPmrw+G2+8cVOGYwJQZmM+EANiypQpQ7vQ2267LVx//fVhoYUWCptvvnlgvq3omWeeCd/4xjfCF77whVbVSu8Nerw4EfIzXXXVVeFPf/pTwHV93XXXjbcajvn1/eIXvwjzzTdfeMMb3tBQb1AXkoAMCmmNIwSEwJggwI/s2WefHe65554xGX/YB73mmms8hsib3vSmsMwyy4QvfvGLHl5/jz32aJr629/+dmdAPv7xj4f77rsvvPWtb22qMywFX/nKV8Kee+4Z/v73v4djjz3WN9nrrruu5fQ++clPhpNOOqllnbKbgx4vzuPKK68MK664YoAJ+cxnPlPKfFA/v753vOMdHsfj+9//fuxuoEcxIAOFW4MJASEwaAQ22WST8Oc//zmstdZagx66Ybxzzz234XoYLo4//vjwhz/8Iay55pqeUJANaYcddvCpfe1rXwvf/OY3G6aJlGTvvff2MPwHHXRQeP3rX99wf1gukHoRIhym8+tf/3p48MEHw2tf+9pw4oknlk7xjDPOCL/97W9L77e6Mejx4lz22WefADN4/vnnh+233z7MOGP5ll60PiKan3rqqeGoo44aEwa9fLZxhToKASEgBMY5AoiZx5K++93vDl0019/85jfhtNNOC7vuumsDNKhfdtppJ892/OlPfzrceeedTffZ3Fttdg0NxuCCJImbbbZZOjI5izbccMMw55xzpmXZkwceeCDcfffdLaUH2fr580GPx/hIPpDsILGZPHlyfkoN163WN9NMM4W99trLn3lDowFciAEZAMgaQggIgbFD4KWXXgowAD/96U/TSfDVzw8399iIjzjiiHDeeef5daxEtt+bbrop/PCHPwxPPvmk2wbst99+DRsy6gu+qs8880xvhrifTZ2yiy66yMsYe/3113dVAF/jtIl0xRVXhEsuuSReDvS47777+tczDEeePvShD4XjjjsuvPjii2GjjTZqSjzKl3OeWDtrPvjgg11yAsZZAs9bbrklTJ06NfzrX//yutjlsDnmCVuGs846y+12qF+X3vKWtzQ04Tk//PDDvtE23LALmAfUTqhQOqVBj/fEE0+4xOONb3xjKrEqm3uV9a2++ur+fl5++eVl3fSlXAxIX2BVp0JACAwDAr/73e/8S5gN9ec//7lPCQbg3e9+t+vLyWWBGuInP/lJ2GabbdJNCENLvqBRTRxzzDH+I/+rX/0qoEZ5//vfHy677DLva7311nPm45BDDvFrxPz0g3oi2hKgtkC18apXvSqwUS222GIpNLvvvnuTBCK92ccTmC6MM1lfGWEDsu2227phI2osNrIyApuVV17ZjVaRmjz33HPhbW97m+NFm7/85S9h6623Dh/+8IfdHmfHHXcMP/7xj8Ppp58eVl111fDss8+mXcOwwcS8613vCksvvXTYYIMNAn12SmzWjP2+973P55jvByYI2wmeXS9oEOPdcMMNjvGb3/xmZyIxroUZOfDAA5ueU9X18fxgxAdKSYdkk0wsGV2HrdVMCAgBIdAeAfuBTexHsX3FFjV+/etfJ/xeffWrX01rmSTDy2699da0bLnllkuMMUmvH3roIa9jCTfTsunTpyfzzz9/Yt40iW3IXm6bs1+nleyEvmzDS4tsE02M8Uiv44kxPolJWOJlx0djFJJ11lmncvsLLrjA12a2C01tvvzlLyff+c53vPyFF15I3vOe93jdXXbZJa1rDFV6blKSxIxRky996UtpGSdmm5DMOuusidlVeLkZSXo/H/zgB1Psrr76ai8zptDrmBQlMWPY5B//+Idf84/ZpHgdY1jSsqonJnFJjOnz9rwDW265ZUPT22+/PTFmJy377Gc/myywwALpdd2TQY1nxqS+JrPR8SnynCxho5exhkh11mcMc2KSrYTnWZVos+CCC1atnq83TRKQgbJ7GkwICIFBI4DkIU+zzz67F2W9OPhif/zxx9Oqr371q/182WWXTctscwp8vSMheeSRR9LyKidFqo73vve9hV/lVfrrps69997rzW3zaNkN2CGWp16RUSqNb7zxRveIwRMjSx/5yEfCv//979SQdbbZZnND1yWWWMLtS6gL5lDE/cILL3Rvjs9//vMu9UDyYUxfoI0xhF63zj+oFvDW4VnxHI3xCtETBikNBpgHHHBAnS5b1h3UeHh2zTLLLC5tY0I8p8MOO8wlRqeccopjWHd9r3vd6wJqsk5wbglKi5vNirwWlXVLCAgBITCqCGCMZ59obZdHnAUIzxpE4FWpiAGp2rbX9Zg784EpaEeI91E5meTCmQJccbOEmgvC0DNLH/jAB/wyMjvZe/EczKGIO14oxOzAjqaXhNEszAduxqjbTFoUTFIQVlhhhWBSmHQovGVMmuBM11xzzRVQ3XVC/R4PZoG/rC0ORsEwtOCNvQs2PHXWF58fzHVkDDtZe502YkDqoKW6QkAITHgEHnvsMceAuBl1aJgYECQ/bPr//Oc/mxiHojWttNJKgS/rnXfe2Y1SowSJuvPMM483waYjMh0UYJPAVzo2MFUJhuT+++93Owba9pLYVBdeeGGX5tAvTBhGsVn661//6gay2L/ArHTKgNBnP8eDCcZWBslRNogYkiIIe5a668NOB8raKHlBH/+RCqaP4KprISAERg8Bol1ixBrVF3yF8tXcimA+/ve//7WqMtB7UYrx1FNPNY2LsSneL3nCNdfsQNwolY06El/dUD6YFYau9IXxZ1V65zvf6UwR6p4soU7AYLUbYkOmHwxhoWuvvdZVaXzxxz9cks3Gx6/xgOqG+jkexsEQ0pwsIY0i2i9MSd31TZs2zaViiy++eLbLvp6LAekrvOpcCAiBsUYgbqZPP/10OpW//e1vfo6NQiTuUzeqA2J5NoIqHg6482ZdNtnQaEu0VSQKHAl5TXCq+FWJWgFbBsoQj1MPYsMjkNSgyYxkPZhYdm1xDmzGjz76aLxsOOI1hBdQlmAa2BBhQKItB/dxX0ZFBeMCmWGpY5vHnHtE8YTwPOILnGBneB+hTjBnB+8DT5ZI9Ln22mu7e3Qsyx6xS8FjCXffSARV47nVUZvFtsM2HkwdmJ9zzjnp+4r9BqHyCSrWibSNZ867XEUtF3Hp+mj/2ToiG1heMB0hp0ZCQAhURaBbLxi8TPBS4ffKvvoT+ypM8AzA04IyvAnsyy8x48fEglR5GV4ReLhQTp1VVlnFPTEsP4h7yZg9RMP08dwwA0yva26jiRltJhY7IzEjzMSiT3pdE5e7h4HZFSS2iaft8SYxe4HENo+0rJOTul4wjGFGi4m5DKfDGePhnhRzzDFHMu+88yasF8+VPOEJZAadDcXUM4PRxNQWiW2KicVFca8cY0i8Hl4tptZwjPCawOvFmLnEgoN5mTExieWj8br2FZ+YisHL43Mzo8uG8UzV4PfNzqGhPF5YPpfEbBr8mRrzkJibdPK9730v3i49WmTRQi+YYRuPBfDOmLFuYkxbYuqxBG8tizNTujZulK0PzxeeOV48dahbLxi4p46IF0NuuB1Bp0ZCQAhURKBbBqTiMIXVIgOCG7BJLBJcVi2gVWFdCk2dkd4r2rhN/J+Y5CWtwwnuk/z4d0udMCDMkY0eRqAuWWC2wias8Y477kgsCFnh/TqF9kWemL1NYRNws6BniSVgK7xPoam8EpilVs+stHHuxjCOF6fI+2PGs77eWFb3yF5uwfLqNku6ZUCkgjFOSiQEhIAQaIWASQUCuvFWom1sByIVibHxWsgHu8J90mJlxGYDPTJH8oMQNI1IoXWoLAcMa8RgtRdZhzFizRpYZueHqgyjV9QwZYRXCG7TrZ5ZWdt8+TCOF+fI+7Pkkkt2HBofN2U8hHCBHjTJC2bQiGfGQ1+KTzoRGmMoZ24TmZEfh0996lOZ2r09/dGPfhRuvvlmt1JfY401ggUbajkA+lusrtHrZvXfLRtlbtZNU51pmp7SByGxIX5UTOQYohtfWilzkk8dTjhsNpJuCV03tgBZ4nnxo4t1Oj/CvSaM+RgXwzKeV/zhxaag36nmCbH97W9/22Mp8EOHzULEERsH9O15AgN+/NG3l+XfyLcZtutoP4Dh4qjSlClT3O4FmwvyigxzfpfsM7jrrruCBUxrcEPN3u/1+aiOh0fXkUce6WHvs55NvcavtL/aMpeXG1iHUsF0Cp61Q29sP+qJuYUl5mff0BN6VLMsbyjr5QW6WNsgEvu6cD2qbeaJMRUth7B8Fa6rpk1dMqMo17+ji0X/az9yrouv2w8iYyL/8e7xhwi2jNA5m/uf17OQzolZ5JdVrV1uBoaue2UOZlzoc8JuwAy4EvTn6MIR2faSjElNwI8xo10B/fNcKLOw2r0cLu3Lvo78maEKIaolY6EPRz0BId7+5S9/6WXcW3fddZNvfetbiTFFiRkN+ntm4b6TTqJY0v9YqWAscFWy1VZb+XqxF7G8JD1RlbCmflAnKpjsPHievVAFZfvU+fAjYDl3ulJRdauCkQ3IGL8jGGHlGRA2T/v66svMMKCzvAduwMTmQShq8+N3Azmzzm855qabburGey0r5W7SZwzrzC0YL5gfixiYq1ntEl084YLZ7JZffvnSRhbIKDExsdfDmK7XZNb53rd9QTZ0bXkXvDxr3NdQoYsLy7fhfWcZELozd78uem3d1FLYJ4wLYeMQQ0B/4hOfaGgYw2XnmULsCzbeeOPEvq7cOLOhUYWLsWJA2IxNutPw1wtbggpL7qhKtwxIR4Oq0YRHoFsGRDYgtpONJRFDIK+jJAR0v8Rh6E0RtaK6YNzVVlvNXd9w4cpmCy3CBPFsXREtqoM6abGLxs2WIfoniBJBfsxq3tVC2fuc269CIOuobZZ+K693z9fv5LpMrUDoaDDCdTDrbtjJGPk2Meph/n3pV6p5VIOWO8MTqTEXbBxIbMX6UOFlqQwPAj+hXyYJGwnNxkLPnJ1n1XP06kTCzP7lca/al+oJASFQjMDAbEBMfB7MYjl89KMfDQS/IRMjP05kk2QzRLdPSFx+3NDtZ3/QaHv77bcH4t9TF39wwgND+LHHLJfcw4+ZevRHJD37avdj8fIbS9mESf0MA4DumvmiYzcphYe4zdZGL84a8FPHb51x8xHkqtTJ9hnPwQddv31lxqJAamtyMpA9k2AzzA0DLTaIPFPA5oC9BBsxth0mKQjmYuV9kWMBnLJkYvNgibqaIhaSofLSSy8N+IfTB/3V/REuS1ON3jFLxFHAII41YzvQiljv5z73OU9HTawAQkRniUyRhCAu66fsfSJQFOnEI+PA8yQbp0mJ3EiPXBLZvCDZMeM5tiDML2/UxzuJTQp2BcRg4H3JY1mlThwnHhnH3As9miVrhniPsddhHsQLIPsr0SU333xzt1GJbTli20MaeuyReOd5X1gz74i5h/pcs/WJZ0EQrsgMZe+VnWNoaW6R3jcp1rfYYouyqioXAkJgIiHQqQzJMKpsA2LMg+tyaYPfNrps/JHRlyOeRaRMlkL7gUzsRzkxpiSdFiJ7VBT2g+pqA3zXzTq6QUWB3zl9o7OFzCguWcV8921TS/tpd4LbGL779GNMkvuwmxGo6/gR+dtGnHaBznvy5MkJ6gzE0iZRcJ9zdN+RqtShLr7bZNaE8Os+++yzE/tib/BFJ2MkGTiZ2wknnJBsv/32rmvnmsyVWSLGAHp4bBDAHb09thDEJMCOoIgs6qDXseiG6W10/7ahJcbMeEwE/MttI3G3vbRSzRPiDJAhE9/1PPEOsJ5sjIR8nXhN7ARE5LwXtCHbaZbMSNMzcCIezGPU7n3CTZL+aUc2VMgCLzWokShDtUCdvAqGGBCUWwhnqjmRnRL1FeooYzK8/1VXXbXh/axSh6yi9G0Gy94v1zHGRcz0akyj/z+iHv+nwHvPPff09wl7FexXIlEXN0wzbvXsozEmA88dNV0ZYceDqilLzJ8x8yqYWIe4GryLxtynmVDjvVbHsVLBtJrTMN6TCmYYn8roz6lbFczAbEDMs8N/oDCaixRTYmcD+1hmQt/o8OGGzj//fDdaxJ8bYmPnh86skv06/gPzYV+fyQMPPOAbcKwf71c5Vkm/zcbXLvV0lTpxPlkGJJbBCNnXe7z0Y8SqVfpwGAgwgImJBDNH8KNW+mvSY5944omxiR8xgoVJjER7jPHYsDqhdmmqsXsxUX1TnISisWIqcJN++LuQtbcwiViC3QJUxIBUeZ/Y2GG2YJQJmJRPM07fkQHBDgWDRZg95gNTTVClaKQJU2rSvIT4CJFMGuHzjgxzlTq0zTMglBWlmsdYl/8jrdKe0xbbGJj5SDCotIPJLSOCOcEww8hlqR0DQt3I2N15553Zpi3Po6E089JfawxM4iWM9J4M/B3AhrBDmjYwFUx0TTTJgf2O/D9F8TyhfCOh37cN3PMN4NaIuBaRNeJ0+6p3cTN1yVoYRc5c22bjonJEzojyy8Tv1C2jVum3cfmyjcZVLvhNF6WexlWRcL8mfSlNTx3rkKmwjBBZ5ynahIBPJOwgsvkKcA0FI0IpR8InHxE8ovYiWwhUOYjV7Ss5NnH1jW0SHh8gFqIuAG9jAGNRrWNMU406B5UWdgE8W7JSQmBfNyS1MQjugopdgQWLcjdY3gPUM2VU5X0CV2M6whe/+EV/5qjaygjMUSeh7uN9xa3apBtpdWPs3GYlvv/cwFWXmBLGDHnWzyp1sirJtHM7KXpXUAPxvEhMFVUlrAnKhsomJDj5KlA5YfPA/0OeA+q+IkJFBS6oSmPmzKJ6ZWW8g1D8f1ZWL1vO/FEdGVOeLdZ5DgGyx6LytQ+V3B1dCoH+IcBvY6vfx3YjD4wBKZpI0Y9nzIAYcyWgx4aZ4IePH9bIdOR17GRkJB4Chofxh65ozE7K2DAgfqyrpJ6OAYnyP9IxUyR2I70g9PTGeaZdwZzATBDfg80TwhYGZqmI+YCJQyePwWSWzOvBL2PCqngvb7MQy+scsSuA+cimxa7TPluXTZnsnEcffXRgE+fHlwRYGNaWUdX3CVsZYrPAzLHxxo083y92Exi8FhHPhmcNE5gn3oXI0LarA8PbLk5Lvv/8dbT7yb4v2M7w7IntQtZPYnrAjBBnpIiIFbHXXnsFc2suut2yjFga2FPxHmJjUpWYNx8t2IWJyhGA8cWOSjiVY6Q7vUfAJL2FcYCqjjSmXjCtNrR4jx9pfvD4Ad5///09xXPR4mBI+E/IZsvXvKlgiqp1VJZNv51NPZ3tzETZ/hVM6ukqdbJte3UOZjEDoqlPgrm/BlMr+YafH4MNwWJXeMKmPCMYE3UhBclTfC758jrXfI1n02LXaZuvy7Pm6x0jRwKktQveVvV9MpWKe9qw+Vseifywla7BivcB7yKYmCzBuEC8K+3qcL8fBLOOtIiEaKYadSYfaY7F7WgaDnz5f4gReSdEEDXIbJGajKY76U9thIAQGP8IjCkDUgU+NklcOfHUgPKSj9iH6a0DkS5RcfAVx49qryibfrtK6ukqdXo1t3w/uKmSMpvNBVUA6hez3WiohicGX/ioK7KqAbhZs6HxL04asO5+UD5NdZ0x+IKPESppByNjthQufkYVg7i+FVV5n2DOYGbMNsnfIzxtoqdV7DsrSYhlRUfeBUTjd999d8NtPF4IZ82zqVKnoXGPLpDqIDFDCmb2GYH/Q0XqqyuuuMIlbWZr0zAy3jdVCEkb7yNqp3ya9SrtVUcICIHRRGBgDAg/whD2HZGiqgR3z0hR9YItA8Q1GyN6JkSMp59+updbBLfARgEhdueL1SzB/UfuwAMPDFdeeaXr2L1CzX+yKarR8WfTb6MnZxy+6LL69Gzq6Sp14pTMcNTXmN3QwIhy3CkjRalEdBGlHDyoG9tyD/dOdOzgjUgdFUK8T5v/Y+9M4G6b6v+/ZAhJCBmuulJK3LpJxr8roXCRKZI5ERLyIyoyZJ6iqEjIkCmiRDJkjlTmSMqU7jVGE1LW//v+1jp3n/3sc87eZ3rO85zP9/U6z9577bXX8FnnOeu7vyPMHPEYiB2BhOSkk07yD/EdcG9mk+AtF3UO7pnpzRW82XBozwwf68ZGu42obFpsNnikXKxjM+K7kGxdUj1UA0gbcFFOKjzuMX8oSbA4L/N9oh1UfkiGSG2NlMI8j2opw2knffewaWlGPE87YJkIJpp4LNxDxVCmDs/ynYDS/w3n6f+J70Ii7rPm+e8K93FBToTrNW7WfCeoy/c5/Z+mOrggw4xRJ31XYFxRffE9SJRwyLbP9xfXcb6TYIC9UXIHT8/pKASEwBAjYD9UbZFBVtoNF1dO25TdOhd3MdMFu1utGZd6mRkiuoU/9VJaa9wW8WihDEt9+wHz1M32I+kpsU0s7d4e9pbuIcJtE6p5euBNwfjwCMG9syzZ5ubP4cJLZMdG6bfxMmiWepr+WtXhPt4GRIhkrLbhRfsRdzdU0iJThruq2XCUTh9um4S7hfJs9kPkUUKYQ7g6Z+9lz7PusaaqcDdc7uP9gjsnHjW4pOLyyfjLUNm02HhCGRPRdL3woMLtlTHhasvaJ2J8RK6EjMmIeF3hrUFdY7aiMaVe3uz7ZMxt3G233dy91+wyvC3wX2WVVbwdQoqTdRI3b/pP2OEtk/fK8of/98fif/h3FNdW24Q9BTqRWrPUqg6eI7hS0yeh5Y0hj0Wp5o35KJ323CQb7hab5pGORKnlfwGvGGNma/NM9znyv4VLLx88tHAdpxzvLWM4/MP/9XbbbeepwtuN7Cs33Oy3pPG53HAbY6M7vUPAXkY8VUObPUybiQfth6My8caJAVs/jJ54Y7QNr2Y9z5B5I0P3303CbgSRNB4Vtlm4AedEM5pkrkXEG6m5RnpAMDwgiqhMnaLn2injbRjjU6Jx2sYQkJqAG/NCwoEoPCshKNMH6hLUOkhVeLPOG9aWaYP1ox1UDo2wpB3G28jbo0w/Zev06/uUHQ/fWdRbSBgwqkQikKcydfLPdHJtrtEuTTKm0r8jqLaQECEVYYyD4FGBAbgxMW7/1clcx/uzYIQUDBswkRDoFwIWt8m9AJFMt0HTR9ULpuyA8VzIuu6xiVVhPloZJjIOXDotwFJtSGy6qCOaEfYTRR4O2WfK1MnW7+QcFQpuyDBNfLKEmquRJ0e2Xv48efRQnmU+MPjl04yIVmtxXdzosIxbdD+YD8bb6fep2Zwb3eM7m9zOO6nT6Nmq5ai82LRQu6AGIsttouQdk651HP8IkNYAY2eyvkJ8Xy1I5IgXlnyGaf7Hyag76IT6DwNoPCmzhHodQ/0iwqGh1R5Q9Bxl/e6PF036RFUO055sJvPj48UUg3KT7vstbNFQxxNVezRoTDAgnQLDD2orYqNNxo1Jv9/qmUG7j9cKnChMCDYcMBxsNKZ28M2vmfSh6lz4x2yFa9bAtWr7qt9bBLDf4LuCqzExWvDiMhWgb0DcSz9QvR2FWh8EBDBURzJKiH0kYMTpwWUaY3bshLKEa76p/tyIHTupZi7v2edG65yXpAMPPNB/B3kJyzIgSByJC0Q8nCLit7MqA9Lv/hg39o7MEak9H16wGhHG4Nifpf9vjM+xeQOHUWEkbRHaIptgaRuQtjro80PYPBCZknlh8zDo6beL4CEKKGHasZkxZsNtILBPoFwkBLIImBrK0yKYp5TbV2Hrgf0VIfdNlZetOqrno20Dkk2v0AsgutV+uzYgpMbI2yOZCrpm95PC/mfnzneHiL8pWnX23iCdm/F55GObq8+H1ANZsnhJbi/Fbz/f+fSh3CTI2aqlzvvdH4PC9hE7QntpaDlG7PH4f8JOK0ukACF6dJk2ss9x3qkNCNbybdF4Y0D48mHEmP3wjzZWaZA2kbGK4bCM2zxgBnaqo8mAYORMvqFeUTfbb4cB4cWEl6387xz5pXhxMQmqM6cYO+fJYvnkiwb2GmcC9qs8A4JBehEThYOBuaO3PZ9+9YcROfOCsWhFpH+w0BSRlAl5BoRnSZXBC0hV6pQBGQoVjC1SS8KmpIpdScsGR7nCeJrLKEM57ruvapg86IBg6IvbPhFm85mqUTvhGowROxFfichriS5Div5LyHf04ZQRVwi1JZFuU+Zu3NAJRU+cIdzSSYWAHYR5zQXSJXTaPoakpJIokxW603XYd999Pf1BkWqWyLhgQ6A/MEEdkbWRK7Ina4Y7Y8UtG1xREaAmRvXTKEsztgy48IO3eaH1RNXDGPJkzJh/PzDE7jZ1sz9CERAaANUp371mxHcd5wTShKCqKSLUsKhv+N/oZ9qDxsqiolGqTAgIASEwwAjASLBhwVThDYY9F5F3zzrrLB81Xm54Y9mboNsyUIgtEx5YlBH5FsIgE/043koYD8PIkEKAMuLOYNhObBfsZdChmyrLmZpO2qdf9PlEfM6nR+BeN4nYSTBpRVFvUz+77767xzyCGSB2EBtZI2qFOzF5MJInJowlyww77rij2yIQ1wnssM9IBJNCwEAi7xK2f8MNN/S1TPd7ebzllluc6SxiFnrRb7v9XXnllf7dNgmhM5EwwTAjxMDKrxMekDAXRek4snPi/wYP0H6SGJB+oq2+hIAQ6BkCBFMjEi5GlLzFYVhOZFcC67HhpTxOKTFfdiBsdlmaPHmyP4/RIhsk11tuuaUnTyRIosWL8TdKjA750cd7hIiyULvt8yzGgDA6eCj1kmCcICQ7zQjpDwEC2ShhSIqoDO4wdDAeEAyN2b54/iakPUiNMJSHcPXHUJKovKwJYR4233xzD0CJ8WuviZQEfH+KpEK96Lvd/lKaDL4vBJTEaJiI0ORDQ7KVCCkd0qpW3prUR+LF94L17BeJAekX0upHCAiBniKAyL5Rpmp+VBFBV6X8RkQ4AH7Q+bFORLwUylLU4FRe5ljUPlmhW72tlmm7WR3UU1BWrVJUHwkQYnnqEUa/CMOyuMPMMd9mWZpJp4BLKakikGDxIY4RzzRyly0adztlZv/g6RdwP+4HddIf7rNI+VJ6BNbpq1/9qkuMvvGNbziGSP+IXkwohDKE1yJqsl7jnB2LbECyaOhcCAiBMYtAknBk49UwmU6yUOcZhCJwiBlEIEKC7VWlMu1XbbNMfcZK31m31EbPId4nLxKqKhiCfJbsTnDPZ2kmsCNqLPPMaTScnpUj5YFR7Zc7aif9wSzwydriYFtDXimYS1yLzcPJs8djs5SIYJRI8GAq55lnHs+Cne6l/xvsboqkeKleN49iQLqJptoSAkJg1BDIZqFOTAeDQTfO2yJqgKpUhkEwjzN/SyfQVVUq037VNsvUJ04Qb+DE/UgbT7PnEOHzZk0OINRbGNwm6ibuMCQYpmLH0G/jaAxPMTxOTFGaX6+OnfRHsDFsZQgkmA0ihqQIQoIGk0m04ywRmZt4V6jTkOJhbJwIOx0Ie6d+kVQw/UJa/QgBIdBTBMpmoU5vjSnhZaNBwRyYm2aj27VyAjvRVoo+2e32ax118SRJMZ5++ukRrbL5w1TliWjRBCfDhiMlRqROWdzz7RVdk8gTpiifNRl1QkpEWvRcp2UwYzAE/VS/dNKfuV37lPN2MUijkMbBlBCWH2lG9oP3FrZRlOHBlSVscfjOVw2+lm2j6rkYkKqIqb4QEAIDiUDZLNS8PU60VAUY75EpGbsRjAGhO++8M+CKCaEKwP4AAz9E2myMEHryZEPBNeoJS2BZY0A6aR931zJZoem3E7JEoJ7jKZv5O7XH5vSoRcUtInJ/kDsoS2VxL5OlGYNT3sDxNDrmmGMcZzyCYH7woknE9brrruv5ulJZo2N6s2/GcMJEMr5GkV0HrT+8dGBCzjzzTJdkMXe+l4TKJ7t2O5I11hwvpTJquUZYVy43zq8tso7GVSTUtkDQQ0JACPQUgaqByMyAsWWmagZMhE/TgUdTP3ikTPMW8MjB5q4YCdoEmYjbg3FRzzZeLzMVRDQRvWdN3meffTy7NFmizY3X76c/7bZfJit06iN7bCcQmRktembm1I4xHtFcgD3KKRm5CagFnnkypiyaV1BdcSvcbXMvnaXZ3uKjMXEeZIt9xqQ10Ywu6/ozVYPfJ5JrI2KcZBw3t2uvawabkSinRcS6Ewm7EQ1if8ZweMZ0Y9o847R5DHkk40ZzoJzvbFEgMgJXsuYEJKtCnQYiUyTUKmirrhAQAn1FoCoDkgZnIvtoRn7xiSeeSEUjjmyaiXEw48PCqJi0k+rQAAyI2SZ4W6Z/j6aKGNFuKminfZ5t1mZqO39shwFhfGz0FtQq31zL66eeeqqwThncCx8sKLQ3cg+lXnArmjQjXnDBBdESsBXdrlxmUq5oQeAaPjfI/cE8mHFp4fe34YRyN0zKFM3+JVfa+rJTBkQqmMoyIz0gBITAoCOAhwCGk+jDGxGi5uTuisFjURIv2kl18u2gKmiWwbnd9pu1mR9DJ9eMjzgcRMdMaqey7RHMrYjK4F70XFEZxsNZA8tsHWxUUJughukGYfdgEoCGTQ1yf0S9Jpt10fe34YQyN1BBEnsGF+h+kxiQfiOu/oSAEBizCOBBgK4de4HxQLicbrbZZm5zUZUJGc35E/jNctbUuaH2cjzjtT9soI444ggPopf1bOolltm25YabRUPnQkAICIEGCPCWaDYEbvRHtEmiqxIhdawTOXEmTZrkjNVYySFF7pJ+0njtj/XGkLUdo9Vu4C8GpBsoqg0hIATGPQK42U6dOrU2T6JPjhdqFRF1vMxT86hHAE+v0SQxIKOJvvoWAkJgzCCAfYNICAiB7iEgG5DuYamWhIAQEAJCQAgIgZIIiAEpCZSqCQEhIASEgBAQAt1DYCY8fdtpDqOVFVdcsa9x49sZp54RAkJg7CJw5ZVXetTSpZZaauxOog8jx0uDRGr5KKV96FpdDDECJLcjWjBh3Nug6W0zIBY5znMCtNGpHhECQmAcIHD33XcHrOjFHIyDxdQUhECbCJDUjlgybVD7DEgbnekRISAExhEC66yzjudLOf3008fRrDQVISAE+oTAdNmA9AlpdSMEhIAQEAJCQAjMQEAMyAwsdCYEhIAQEAJCQAj0CQExIH0CWt0IASEgBISAEBACMxAQAzIDC50JASEgBISAEBACfUJADEifgFY3QkAICAEhIASEwAwExIDMwEJnQkAICAEhIASEQJ8QEAPSJ6DVjRAQAkJACAgBITADATEgM7DQmRAQAkJACAgBIdAnBMSA9AlodSMEhIAQEAJCQAjMQEAMyAwsdCYEhIAQEAJCQAj0CQExIH0CWt0IASEgBISAEBACMxAQAzIDC50JASEgBISAEBACfUJADEifgFY3QkAICAEhIASEwAwExIDMwEJnQkAICAEhIASEQJ8QEAPSJ6DVjRAQAkJACAgBITADATEgM7DQmRAQAkJACAgBIdAnBMSA9AlodSMEhIAQEAJCQAjMQEAMyAwsdCYEhIAQEAJCQAj0CQExIH0CWt0IASEgBISAEBACMxAQAzIDC50JASEgBISAEBACfUJADEifgFY3QkAICAEhIASEwAwExIDMwEJnQkAICAEhIASEQJ8QEAPSJ6DVjRAQAkJACAgBITADATEgM7DQmRAQAkJACAgBIdAnBMSA9AlodSMEhIAQEAJCQAjMQEAMyAwsdCYEhIAQEAJCQAj0CQExIH0CWt0IASEgBISAEBACMxAQAzIDC50JASEgBISAEBACfUJADEifgFY3QkAICAEhIASEwAwExIDMwEJnQkAICAEhIASEQJ8QEAPSJ6DVjRAQAkJACAgBITADATEgM7DQmRAQAkJACAgBIdAnBMSA9AlodSMEhIAQEAJCQAjMQGCmaDTjUmdCQAgIgZEIXHvttWHq1KnhP//5T+3ma6+9FmaaaSb/pMJZZ5013H777WHSpEmpSEchIASEQBEC02cpKlWZEBACQiCLwMSJE8Mrr7ySLWp4PmHChIb3dEMICAEhkBCQCiYhoaMQEAINEVhiiSXC5MmT66Qd+cozzzxzWHvttcO8886bv6VrISAEhMAIBMSAjIBEBUJACBQhsO2224bXva7xTwYqma222qroUZUJASEgBEYgIBuQEZCoQAgIgSIEpk2bFhZddNHQyGxs9tlnD88991yYc845ix5XmRAQAkIgi8D0xq8z2Wo6FwJCYOgRWHjhhcOUKVMKpSCzzDJL2GijjcR8DP23RAAIgfIIiAEpj5VqCoGhR2DrrbcuxODf//631C+FyKhQCAiBRghIBdMIGZULASEwAoEXXnghLLDAAgGGI0tzzz13ePbZZwNuuCIhIASEQAkEpIIpAZKqCAEh8D8E5plnHvd0weMlEUzHFltsIeYjAaKjEBACpRCQCqYUTKokBIRAQgA1DB4viV599dWw5ZZbpksdhYAQEAKlEJAKphRMqiQEhEBC4KWXXgrzzTdfePnll73oLW95S8BDhqioIiEgBIRASQSkgikJlKoJASHwPwTmmGOOsPHGGwc8X1C/bLPNNmI+9O0QAkKgMgJSwVSGTA8IASGAygVDVNQv2H+IhIAQEAJVEVAumKqIFdT/2c9+Fl588cWCOyoSAuMTAZLSEXBsrrnmCg8//LB/xudMNSshMBIB1I7ExBF1hoBsQDrDLzz11FNhoYUW6rAVPS4EhIAQEAJjBQFSEiABlN1TRyumbLgdwWcPp/Tkt9xyS1h55ZU7bU7PC4Gw+uqrh/e85z3h5JNPFhpNEPjSl74UrrzyynDnnXc2qaVbQqC7CFx88cVh00037W6jQ9qabECGdOE1bSEgBISAEBACo4mAGJDRRF99CwEhIASEgBAYUgTEgAzpwmvaQkAICAEhIARGEwExIKOJvvoWAkJACAgBITCkCIgBGdKF17SFgBAQAkJACIwmAmJARhN99S0EhIAQEAJCYEgRUCCyIV14TXt8I/DHP/4xHHrooeGQQw4JEyZMGN+TbXN2v/rVr9zd+eabbw7PPfect/Lud787vP/9769r8YUXXnB332zh2muvHeadd95s0cCdX3bZZeGjH/1omH322evGdscddzQMHLfiiiuGxRdfvK5+2Yt+90dOIvr885//HJZccsmw3nrrFQ6VtT311FPDF7/4Rb//m9/8Jsw///zhrW99a2F9FfYRgSjqCIEnn3wy2nJFiwPSUTt6WAgkBD70oQ/FXXfdNV22dbzooov8e3nFFVe09fxYeMg2lDh58uS2hvqjH/0oWgwRf/bvf/97/MpXvuJ4velNb4q/+93v6tq0zL/x17/+dZw0aVK0+Czx5z//eaRsUOnyyy+PH/jAB3w+zz//fN0wGfcSSyzh9/jdyn+YZ1Xqd3+M74c//GF873vfG08//fRosZiaDnnDDTeMFrm0VsfSB8Sdd9453nDDDbWyKic/+MEPHLdB/g5Umc8o1p0mFUwfmT11JQT6hQCBkp555pmwzjrr9KvLwn7OOuuswvLRLDz++OPDE088EZBiQG94wxvCwQcfHGabbTZPqWAbVvjb3/5WGyLRLpdddtmw+eab+8cYxIGNgPn4448HY5RcIlCbQObkmmuuCVOnTg2PPPJIeOWVV2of0klMnDjR55mp3vK03/0xoH322Sd88pOfDOecc07YfvvtA1FJG9F3vvOdcP/999fdJoniSSedFI488shw77331t3TRX8RaLxy/R2HehMCQqDLCCBmHk0ySUEgWukg0X333ecRZnfZZZcRw3rHO94RPvKRj4QHHnjAM/zam2FdnTe/+c0Dr3ZBrcAHZqKIyN3zta99ze/DcKUPqoxNNtmk6JGmZf3u79JLLw3HHntsOPHEE53Raja4hx56yKPkFqlmZp555rDXXnuFnXbaqVkTutdjBMSA9BhgNS8ERgMBEw8HGAD0/Yl46+eHm3tsxIcddlg4++yz/TrVIb/FVVddFbCLIM8RuvP99tsv3H777alK+PGPfxxOOOGEcNppp3kZ0gLCxlN2wQUXeBl9f+xjH3NJwimnnOLPpAZMfB5MRZQu+3rcd999/e25KIcHb8bnn39+MBVFYKPDhiZLvGkXvW1jUwCuRxxxhGOXZVzA8+qrrw7XXntt+Oc//+n4YJfD5pgnbBlMpeB2O9TvBa200koj5sD34ZJLLgkbb7xx17vsZn+m7naJx9ve9rawww47NB0rWZr333//cNRRRzWst+aaa/r3k7mLRgcBMSCjg7t6FQI9Q+C3v/2tqwo+/OEPB9Ppez8wDWYXEPbcc8/wJUDhmQAAQABJREFU9a9/PaCGuO222/xNP/1I/+lPf/LnUE0cc8wx/iN/9913B9Qo/+///b9ADgxo/fXXd+YDtQX0xje+0ds58MADfSOmDANN09GH17/+9eFd73pXWGyxxSh2+tznPheKJBDpfq+OMF1mE1NTvRT1w7hhPpAUMB+zbyiqVivjLRr8wATcvvCFLwRwx/DxL3/5S9h6661dqnLGGWeEHXfcMfziF78I3/zmNwNqHLPPqLUDw3bQQQe5AexSSy0VUAN99rOfrd3v5Ql5rGDIYBb6Qe32R94fDILf+c53OhO56KKLBpiRAw44IMBwZAkmj+86381mtMoqqzgj3qyO7vUOATEgvcNWLQuBUUGARHZmVFnXNxtkemvERoA3bZgSbBsSY4G3zNFHH+3PwTiw+SLZINkbGzM/6LzRQ2ySWeKHHhVGIjMODQsssIB7YLDZcp2I/hD595vuuece73KRRRZp2vUyyywTvve973mdrbbaqlBawU0Ys+9+97suJXr729/uzAOSneuvv96xAjMYDwjpBm0iJcIuYdq0aeHWW2/1e2YEGz796U+7agQPnI9//OPOCMKowCT2mhjzRhtt1De7lnb7S1K4LbbYwiVVeHqxPkiqkGwlMuPSgDSrTHLQpZdeOvC9+Ne//pUe17GPCIgB6SPY6koI9AsBGIg8zTHHHF6Eq2kimBUMCRNhkAllGQbzIPC3dyQkGC9WoSJVxworrBB48+w3YdsBLbTQQi27Rh3x5S9/udAoNT0MMwGW5jmTitz4EzdWDCT/+te/OgMGBqh12BQhMIcS7uedd17ApRTpCVIPPtOnT/dnHn74Ya/bqz+oi2AI27H/aGdMnfSHqmvWWWd1aRt98x3/6le/6szwN77xDccQCQkGpqxdGWLtYKp7jXOZsQxjnf/+RwzjzDVnISAEAsZ4WZuFRpAQZwHCswYReFkqYkDKPtvteoyd8eTjYjTqBzE+KigkRdtss02d6gbMYGiK3rJXXXVVZ9QefPDBsPzyy49oHsyhhDteGgsvvLBLm0ZU7nEB6hDe/qdMmdLjnv7bfCf9wSzwSYwcLWKTA0PLWvzhD38Ixx13XPjgBz8YzM26Np/f//734eWXX3Y7l3nmmcdVZOkmqjYI5joxhumejr1HQAxI7zFWD0JgzCPw2GOP+RxQNVShQWJAkFaw6f/jH/9wG49W82DsSDLY4LALsfggNbsM7qFiwcjX4lA4I5faSwwa98sQDAltY8fAG34/yWJauLFwYop63Xcn/cEEYyuD5CgbRAzpEoQaECYTo98svfjii24AvPvuuwdULtjoJMJOB8raKKV7OvYeAalgeo+xehACYx6B6667zo1Yk/qCt1DeKpsRmzSb86AQth3Q008/PWJIMCZ4qeRp7rnnduaDN++kwkl1YEzwAMJGJkuoChZccMFQlll73/ve50zRt7/97WwzbnCJHUiviDnDEPRT/dJJf9tuu61DkbeLwega+yWYEuyWkGZkPxg8Y49EGR5eWcIWh+9pu9Ffs23pvDoCYkCqY6YnhMDAI0CQKejZZ5+tjRWbBChrcMd96iZ1QKqcDdCE+yNv+slbhjrEy+BZjCyRKHDE8wPDwPRWiVoBWwbKEI9TD2JDIJBUvwmD2znnnLMw+BQbEfMsYqrw4jn33HNHuK8SyAo7BFyZE+HSiqcL95AqYGAKtnnMqY/dB0SAM97A9957b/c+gtG58MILPUYFXjSJiFmx7rrrunt0Kmt0TGtQNJ/0DONkfGussUYqqjsOWn946cCEnHnmmbXvK/YbN910k+MNI1GVHn30Uf8ul1XLVW1f9VsgYP8cog4QUCj2DsDTo4UImNdIR6HY7Q0xWiRUomhFe+uPhMo2z4xob+ReZh4X0TbcaMaP0d7wvcxcQCMhqinnudVWWy2a10wk3Dlhvc1QsW6s9uYfLW+I1zWPmGixFKIZbkbLPRLNy8Prmrg8mqQkmt49mutv7XlCaE+cODHa5lEra+eknVDsZrQYzZ6jrjvzyohmA+FzWWuttaJJe+rupwuLmxLNwDFd+tE2P5+LeQhF8+zxts1zyO8R4t3E/t6uSY6i2ZJEfi/M48TLTPIRLR+N17W3+GgqBi9P62aSlLq+Ugh1s3OoK89eGMMXLdBYNAmMt8VcLcpptkrtnDGbF0ntOn8yiP3xnTFj3WhMWzTD02geQ9HizOSHXndtkVPrQrGnm8Z4RwsuF01lk4pKHU2K49gas1mqvio1RGAanKSoAwTEgHQAnh4tRKBTBqSw0ZKFiQFhszWJRTTpRdO8J6bOqLVsb/S183RiXgnRJC/p0o/2Vh758e+U2mFAGCMbPf+37ZAFZxvxGBuRGZxGkxJF5tYJ2Rt5NHubwiZo2wK9OaNTWKFiIWtrUqyGTw1yf3x/zLi0ZR6YhpOzGyZlihYsr1mVwntiQAphaadQuWBaCIh0WwgMLQKoK9CNNxNto1tPVCTGxnYiHwwKtQUhwEeDGCNxOAgyhrqkKmHbkSfwQU2z3HLLuUomf7/KNYG1sgaW2WdRlaE2QQ3TDWJtCS/fiAa5P74/xJ0pikzbaD7ZcjyUUKvhAi0aPQTkBTN62AeMp4juR1hm0mBj8IZxHyGsxwthA8A/u73VV54SCbJSmvRmD5NcC///n/zkJx75M4UIb/aM7hUjkAwxwXO8Ei6nbK7YXJBXpN1NrN/4/PKXvwyHH354nRtqL8cwXvvDo4uw+QTjS7Fxeomj2m6MgIxQG2PT0ztE9SMy5R577OGxAnARI4MpFvTjgXCH4wceTwByf7RDRIXE4h2DRdpi08Crgg/eB6Y/99wQMDjEFyAi4k9/+tN2utIzhgAGeUgGIIJTYViaNZ70G+Pkj9l6eOAvjBjHCpG7pJ8b5njtD+kJhqzzzTffWFn6cTtOMSCjtLQkAiO/BhIPGBE20XaIjb5o0x3tNOhsZgRvSpb+7cwN8T5tQIhbt9tuOw+9TPhlLPQJOgTjBoaEZ8Ytsh0qwqqorJ22x9IzhCgnoiQeFOSQITx3v+NS9BMvXIpHSxXUz3mqr3oE8M5qplasr62rXiIgBqSX6DZpG/UCUfkSpfMq/xhIApAOsNlniWA9o50GnWiE2ZDf2fFVOc/bD+SfJbFZ8uGHEamCH20VYVVUlu93PF6zGfM9zH6q4jkecdGchIAQ6A0CsgHpDa4NWyWXBqnOUScg9SAwD2QW54XPIEG43pJboZohrgBxAcgCyfNbbrlluOaaazzoERvFBhts4G1iQ8I1adB5qyURGURCLKQlBOQhF0fW/x9RNBsv+nD87Qk/TXTGT3ziE57fonBwHRaimqFfkm+1QxiRgUEzaoQfzzDfPFaEZs6XJfx4BrxRnxHlkvgNyYhvNPBjPCIhIASEwFhFQBKQPq8cyb7wDIBQMcBM8CnK0EmQIMI6o/fdb7/9fLOGcWBThWEh/TfE81jhU4+NsSgNOpvtQQcVp/tG5F42bbh32KU/naRlJ6gVNh/NqBl+PFeEVVEZdbGFIJ06wbfWW289Z16Q8GBIPFr4MS6REBACQmDMItCO866emYFAO3FA0jPZ4EwELbIvUTQjwFrjlocimkQiElwIuuuuu7yOWafXXVtKcL9OfzbccMNokRXTZSRoFEGo6CMRQaboz9z6vMiYGr9effXVPSAVhZbQycsIoNQOmZTGnycYUxERMMukQUW3amUmhfE2TC0QLYeDf8x2xgNoEUQrSwQlspDMtaJW+FExj1WjMvOWqFubJ554wsdF4C2om/hZgjNvm/XRpzkGZqMijPQ9GZXvgAKR+U9fJ3+mSQVjv/CDShhWEj6adOhIPG644QYfKtkdsbFIVKSnz5Zl032nZ3CPJYkTaahxASY+As9Qhi0FlLJDprTh6dluHasYjSLVufbaa2tdP//88y2NTruFH50ef/zxHueBVOmJkDoxDqib+IE/oc4tYmnqSscCBL7//e8HY8rD0UcfXXBXRUKgNwjgmcfvgahzBMSAdI5hz1rAHgPm4ytf+YpvcInpyAdQyjIbaTDZsnbTfacMmcbipmYH5ogLnUXCbDqebuFHTAzsZ2AIsvYgTTu3m+3ix7jx+mnXNqbVuMbLfZLAYYAtnMbLio6NefD/KQakO2slG5Du4NiTVjBYJRbG8ssv714tREksoiyzke5ny9gIU7rvdH88HD/1qU81nUa38OMHB8omaGvasW4KASEgBIRASwTEgLSEaPQqYDRqCcLc6JFRNJJ85FOew3xky0Yr3ffoIfffnlvhR608VkVlRKjF1fdb3/rWiLgmZmcSeqWi+u8s9FcICAEhMD4REAMyCuuaXG7xZkmUUqWne5Tj6UGa8CuuuMK9L775zW96ddQBqAUIqAORHwI1yT333OPX+TToeG20SveNxwhtZCNf4vEBZcfpBSX/tEoJXiYtewoJno91UjSEF1980TFLKqNW+NFGHiueKSqzjJruvmyGsO4WjfifqKH0Se6OXuBXNEeVCQEhIATGDQL2Yy3qAIHk0WKhwEu1QgZKCx7mVtukMbf8Je7lYlE+vcwMG6PFmvC2br311mhql2jJuzyFt71pe2p0cxWNFibb61gsD38O75WURdNcbkekQW+W7hvvmLJpw0tN0ioZ0+Qps+0fxVODk6KdTKtZapWWnRTwq1laeNrgY9FPo6lBsk34OR4opCA3N2SvZzYzkaylZfArwqqoDIt3sq+agaj3wdFcoz0bZ7fx+9CHPhR33XXXEfNUQT0C7WTDrW9BV0KgOgLKhlsdswZPTJuJG+OGmxqFiSCNIA4HuUjMfbLrI0DtggSC+CEQy4VaJoWQ5jqNIds5b+bYLuQjiZKICbVDo4yb2TZ6fU4wNcaS5tKL/lrhR59FWBWVUZe1MCbSVTJki+0FGTPpHkgnn3xyL5ofN20S7ZdkjkijREKgXwiQJ4m8Xfy28PslahuB6fKCaRu7/jwIE5GYD3rMb9hcwwDlKQU7y5c3MmTN18tfk2mWTzNiHF/+8pebVam7R1r2XlMr/Oi/CKuiMuoS7G3ppZfmVDSkCJAEERd1IhqnbM0EpcNgPEuoD2GQskTwQILdDTJddtllweLbuOddfpyoGi+88EL3PsJ9n6R+zfIFgc+pp55a6LF24403+osbjDxMN672zejuu+8OPMMLCxmwn3766TD//PMPxMtUs3HrXmMExIA0xkZ3MghghMmPRDNqtGk3e0b3hMBYQoAUBWy4bJpEJSYGySGHHOJMLOnrl1xyydp0+H8gVoypV90oHIlWyvlUqzRAJ7xgYNdEIkLi2xDbJkt40mFPduKJJ4bNNtvM0zXgLn722WeHKVOmZKvWznFdx0Yt7zK/2267uTSR5IcYcW+88cbB1I6B8jxhi0YkaCS93/72t2sMB8kEiaZMvJ9G/efb0vWAIYAKRtQ+AlVtQNrvSU8OCwKjbQPyve99r6dQd6v9ftuAWPblaEzECGzsjdztgrDpMmPyEfctZUA8+OCDR5QPUgH2Y3xsM/e5GAMyYnjrrLNOJIJylrbddtu46qqrZotq5yb5iJZKIloso1oZJ9h2YdeW7QObMdsaY96Wzlzpo0k5omXArmsjXVgOpsi4zAA/FfX8KBuQrkE8TV4wA8YQajhCYDQRIGdQLzMp97r9XmF33333BSQYeG7lCSkAkWsfeOCBsM0227idVrYOCQsHXe2CTRifiRMnZoded45HHkENs4QaFVuuPD300ENum4PEJE9IMegniwmxjqAjjjiiVh2PPCQtBB3kmSIixtFee+0VzEC96LbKBhwBMSADvkAanhAoiwAZkxGP8yN+1VVX1TZCNg42zxNOOKG2gcAIcM0nxTGhjEzAljvIMymjboDInowLuL33uAsy4vSTTjqp5p7dafuI2BmzeS6VnWrf6+27777BvNcKjQ4JnX/++ed7GoNLL710RJJE7JD45KnRelGP7MpXX321px/45z//GS644AJX9bCx5wnVxOmnn+73s+kK8vU6vUZNQhhyYt9A2IOQ0XrPPfesaxoj+f333z8cddRRdeXpgizgfJeyBJOGmhe7mkTYk91xxx3hC1/4Qp0dXLqfjmuuuaZ/Zy+55JJUpOMYQWDkf8UYGbiGKQSEwAwEeAvkB59Q8Rg68qNNzBKMAIlrsuCCC4bPf/7zvoHwFPY8xJ6hjA0B4o00n0n53HPP9bK9997bdfTo+4k3g+7dVEXukdVJ+/TLpo3UBePGQSSkH8TiSdmni8YIdsxjrrnmcjuKyy+/vKharazZelXJrgzTSMA9DGBNBRQsuWLI5iuqddiFE6QM2LSQOZvxb7LJJs6oYoORJWxiYEryHnipDvYz5LPC0yxL5KHCcBcGGCKHFcwdEYj5LoMtth4wbnnCHuewww7LF+t60BHomjZnSBuSDciQLnwPp20be6U4INhUkBnYfrxro0pZhJPu3DZR17GfdtpptTop27FJS2plRdmBacO8rSJtJDrggAO8PRONe1En7RNHxRidQvuJ1F/RsV82IIzNfscjMXyKiHg2ibBvACszQI2sAXTKKadEkxilKrHMehHbhj6NUWyYnbpMlutapyVPwJR+s/YZ2UfN8yQao+B1VlpppVqm7lTn+uuvj8YQpctoDO4IGxBTY/nzfP+yZLmuoqlbvMikbl5n8uTJ0ZhoLwNPY3ajMSKR+1kyyZ/H6CEDd69JNiBdQ1g2IIPOIGp8QqAVAqhRcAPNeiHhjYFIG3F5irLbqp10H9fuLOEGzpto1v0YrwTKcIusSkXto95o9MZctf1u18e2A8LrohWhpkB1wNs90oj0Np99rsx6lcmunM1yjdSDTzbLdbbPbp1/97vfDRYcMJCHCe8WMlonFR7SC1RzrVzx8bRB2oFEBdURqhPGjqSDtBFQknKAITYgEN9pksCh+iEtQpb47qO2Iru3aOwgIDfcsbNWGqkQGIGAvYu48WNREDzzTggk5EPFko0lM6KRXEGeQcjd9kvE6BMmTAjPPPNM0e2mZWXab9pAn28yR8acd0ttNAxUEMSswIYGo9Ss6qbseiWjzGwf+ezK7Wa5zrZZ5dyiL7stCnYZMJ+oPT7zmc8488BcUeeRsdskG7VmUbWQXgImAxdkVClk+MbVF3UeOKH223777d3OKLn6J2aaOB9ZMqmLXya1YbqHegbCXokYLaKxgYAYkLGxThqlEChEgI0R+wM2BRIQpk2KyuYC6c9wP5vjp7ChTGEZBgHPB962CVhVlcq0X7XNXtZHugTjQJ6gtNE164/5IXlCOoBdCPEzkl1G2fVq1n66l81y3SwYWKrf6dFUR8FcXp35oC2kIARlQyqC9ANGDcPZLCEJwojWUj24BA0GBILByMb8QBoCQ4ttCZTiqcCoZAlPHeaal5alvFPkvBKNHQRkhDp21kojFQKFCLDRIerPhyRHjI3x6dvf/vbappFNdljUGBtkNpNyUR3KEL/TVnKz5I0Y6lb73tiA/FlmmWV8JETezBOMCRtsnsigDPPBRptUOKlOmfVKdZsd+53lGuNjGI0s4TUFc4sHE4a3SCCyH9yWF1hgAS/DM6uI8KSxXFHB4qzUJHWou2Bu8brJEhIVvGyQvmQJTyy+u6gdRWMHATEgY2etNFIhUIjAkUceGYjHgEg7EXkqYBK4x5syb5QTLfYC7qLkA0KEfdFFF3l1GBfqQ0WZgClHv57dSMmHgS1AYkA6aZ+3XFQOZsBIVwNHyy67rEc+xUYhT2x8ZoheyHjhMYIXUd4Ft8x6YecAc5OVXOWzU2+++eYts1wzXqQL6667bik35yRJKGIksceAWUjfFdqGQUCFkqRtlFUh3G6xJ8LNmJgfWYIheeKJJ4IllawV4/WDtw/RZbP06KOPeiyWsmqy7LM6H0UE7Esu6gABecF0AJ4eLUSgqhcMjdx0003RGIxo7o/RcnlEsz0YEbUTDxjTw7sXAREvb7jhhmhib38meWzYD/yITMqm54/GxEQTmcd99tknfuITn4jm7jvCa6Xd9pPnCBmTq1C/vGAY01e/+lXHNDs+Y+CiuYW6t4blRInXXXdd9nbt3NxD67xguNFsvfAKKpudulmW6zSA5LVCJNdGZOo0zyhtEjOfD9+fn/3sZ3XVTQXlkVBNIhTNkDZamPW4wQYbNPQO4mG+L/lIqMbAxNtvvz2aCscjnBpjVddP9sJsRCIZv8lwDY7G8EaLe5KtEvF8sTgi0dQ/deW9upAXTNeQVTbcTnm/lIm2V9lwOx2fnh97CGCIhyEdwcOqkP0sBAJVoY6ZNGmSS0Xyz/NmiwgbHTpHpCP5N/R8JuCdd97ZvRV4G+eNFLUCKoYiaqd92sFTp1GbRf1Q1s9suMwLlQdv4IssskijITUsR32DOixLZdYrW7/ZebMs19jrkGAO6YAxDM2aKXUPlRP9oSbBvqgqIUnDXmS55ZZzyVKZ5/mdJRFkUX9I8pA0ofLqByH9UzbcriCtbLhdgVGNCIEBQAAdOGL/ZsQmlMTUjQwXkwdCUTutjPzabb8q81E0tl6WMS/sFHAhtbgeI5i2Vn3nmQ/ql1mvVu2m+82yXMOAoI475phjUvWOjnhAoQZpl3i26vONmD5UiTAfuCSLxh4CsgEZe2umEQuBviLAGy82INglDDMRhRM7BaLCZu0gBh0TsvQefvjhNUPkQR9v2fEhhSGEP7FEkI6Ixh4CYkDG3pppxEKgbwjwdmm2AG4QST6Uu+66q299D2JHZuvhYe5hyMYKkStlPG7QloU4nHnmmbVAZWNlPTTOGQgoDsgMLHQmBIRADgG8XKZOnVorxdtm2KlMRNRhx6gf88djSzS2ERADMrbXT6MXAj1FoJk9SE87VuNCQAiMewSkghn3S6wJCgEhIASEgBAYPATEgAzemmhEQkAICAEhIATGPQJSwXRpiffff/+QT5zUpabVzJAhQJIx4m3kI0MOGQwtp0tkUvLRCKeWUKlCFxEg1LyoOwjMREyz7jQ1nK0QzIl8B1VTng8nWpr1eEKATKZ4IlSN6TCeMNBchhMBDGBPPPHE4Zx892Y9XQxI98BUS0JgqBAgMyo/xMRhEAkBISAEKiIwXTYgFRFTdSEgBISAEBACQqBzBMSAdI6hWhACQkAICAEhIAQqIiAGpCJgqi4EhIAQEAJCQAh0joAYkM4xVAtCQAgIASEgBIRARQTEgFQETNWFgBAQAkJACAiBzhEQA9I5hmpBCAgBISAEhIAQqIiAGJCKgKm6EBACQkAICAEh0DkCYkA6x1AtCAEhIASEgBAQAhUREANSETBVFwJCQAgIASEgBDpHQAxI5xiqBSEgBISAEBACQqAiAmJAKgKm6kJACAgBISAEhEDnCIgB6RxDtSAEhIAQEAJCQAhUREAMSEXAVF0ICAEhIASEgBDoHAExIJ1jqBaEgBAQAkJACAiBigiIAakImKoLASEgBISAEBACnSMgBqRzDNWCEBACQkAICAEhUBEBMSAVAVN1ISAEhIAQEAJCoHMExIB0jqFaEAJCQAgIASEgBCoiIAakImCqLgSEgBAQAkJACHSOgBiQzjFUC0JACAgBISAEhEBFBMSAVARM1YWAEBACQkAICIHOERAD0jmGakEICAEhIASEgBCoiIAYkIqAqboQEAJCQAgIASHQOQJiQDrHUC0IASEgBISAEBACFREQA1IRMFUXAkJACAgBISAEOkdADEjnGKoFISAEhIAQEAJCoCICYkAqAqbqQkAICAEhIASEQOcIiAHpHEO1IASEgBAQAkJACFREQAxIRcBUXQgIASEgBISAEOgcATEgnWOoFoSAEBACQkAICIGKCIgBqQiYqgsBISAEhIAQEAKdIyAGpHMM1YIQEAJCQAgIASFQEQExIBUBU3UhIASEgBAQAkKgcwRmikadN6MWhIAQGM8IXHvttWHq1KnhP//5T22ar732Wphpppn8kwpnnXXWcPvtt4dJkyalIh2FgBAQAkUITJ+lqFRlQkAICIEsAhMnTgyvvPJKtqjh+YQJExre0w0hIASEQEJAKpiEhI5CQAg0RGCJJZYIkydPrpN25CvPPPPMYe211w7zzjtv/pauhYAQEAIjEBADMgISFQgBIVCEwLbbbhte97rGPxmoZLbaaquiR1UmBISAEBiBgGxARkCiAiEgBIoQmDZtWlh00UVDI7Ox2WefPTz33HNhzjnnLHpcZUJACAiBLALTG7/OZKvpXAgIgaFHYOGFFw5TpkwplILMMsssYaONNhLzMfTfEgEgBMojIAakPFaqKQSGHoGtt966EIN///vfUr8UIqNCISAEGiEgFUwjZFQuBITACAReeOGFsMACCwQYjizNPffc4dlnnw244YqEgBAQAiUQkAqmBEiqIgSEwP8QmGeeedzTBY+XRDAdW2yxhZiPBIiOQkAIlEJAKphSMKmSEBACCQHUMHi8JHr11VfDlltumS51FAJCQAiUQkAqmFIwqZIQEAIJgZdeeinMN9984eWXX/ait7zlLQEPGaKiioSAEBACJRGQCqYkUKomBITA/xCYY445wsYbbxzwfEH9ss0224j50LdDCAiByghIBVMZMj0gBIQAKhcMUVG/YP8hEgJCQAhURUC5YKoi1sP6f/3rX8PVV19dp1/vYXdqWgi0jQBJ6Qg4Ntdcc4WHH37YP203pgeFQB8QwHB63XXXDQTMEw0GArIBGYx18FF885vfDJ/97GcHaEQaihAQAkJg/CBwySWXeMC88TOjMT0TZcMdpOXjrXKhhRZyg75BGpfGMngInHTSSeHQQw8N06dPH7zBDdCIfv3rX4flllsu/OEPfwhvf/vbB2hkGkq/EcBImt9Y0eAgIBuQwVkLjUQICAEhIASEwNAgIAZkaJZaExUCQkAICAEhMDgIiAEZnLXQSISAEBACQkAIDA0CYkCGZqk1USEgBISAEBACg4OAGJDBWQuNRAgIASEgBITA0CAgBmRolloTFQJCQAgIASEwOAgoENngrIVGIgT6jsDxxx/vgZl23XXXvvc9Fjok2usvf/nL8Pe//z0899xzPuR3v/vd4f3vf3/d8F944YVw5ZVX1pWtvfbaYd55560rG7QL3LgffPDB8KEPfWjE0JjzhRdeGB599NGw4oorhrXWWqtlxmPqT5w4MSy//PJ17YHdZZddFh5//PHw3ve+N3zkIx/xIHZ1lTIXd999d7jxxhvDbLPNFqZOnRomTJgQfvjDHyqGRwaj8XAqCch4WEXNQQi0icDpp58ezjrrrDafHt+Pvfjii+GYY44JkyZNCqussopv1J/85CfD6quvHh566KG6yb/pTW8K73rXu8IRRxzh8VkWXnjhMM8889TVGaSLZ555Juy9994eG4WNPU+/+93vnMkiLtEXvvCFABbveMc7nCnI103Xv/rVr8JWW20VfvOb36QiP951113O4LznPe/xtoicC54kMMzTs88+Gz796U+HL37xi+FjH/tY+MxnPuPMB/VIerjjjjt6CoD8c7oemwiIARmb66ZRC4GuIHD77beHn//8511pq91G2Ax/+tOftvt4T5578sknw9Zbbx2QDL3xjW8Mb3jDG8LBBx/sb+RsxhtuuGH429/+VuubIFfLLrts2Hzzzf2DRGGQswMj1SCJIJmNi+jzn/98WG211Tx0OeH2yfcD47X//vsXVQ//+Mc/wkEHHeS5gbIVXnvttbDddtt5O0hRCN8PQ0M49G233TZb1SUtSy21VHjllVfCFVdcEd761rfW3V955ZXDJptsEnbaaae6cl2MXQTEgIzdtdPIhUDHCLCxkt12tIjIlEgV2BAHifbaay8X9yPZyBJSANQHDzzwgG/gMcbs7fDmN7954NUuDPiDH/xgQJXUiJBO3H///XW3X//61ztzUFf4vwskFl/+8pdH3LrtttsC6pS8ygoVDXmviFQL/etf/wqbbbZZmG+++cK3v/3tEe2kAtRaSJ8GjWFN49OxGgJiQKrhpdpCYFwh8PTTTwfUMImweWBjuPbaa8M///nPcMEFF4RDDjlkhMrhT3/6UyB3ERvw9ddf7yJzwsOnN+of//jH4YQTTginnXaaN4204OSTT/Yy2oR400VicM0114SbbropnHLKKTWxPGqBiy66yOv1+w82Hz/5yU/CpptuOqLrWWaZJZx//vlhiSWWCJdeeqmrW7KVXve61wU+eUItceKJJ7qK5qqrrnLcsnWeeOIJv4/E4L777guHHXZYOPvss0ckpvzzn//s68WasEa9oo033jjAPJxzzjneBfYgrMmee+45okvKl1xyybD00kuPuIcqB8ozajBA0M033+xHmJc77rjDpSMwxc2IMey3334jsGn2jO4NKAL2xRANCAJf//rXo+lcB2Q0GsYgI/CNb3wjmk687SEaoxHPOOOMaOqFWjvPP/98/MQnPsErfdxyyy2jSSbiHnvs4ffNpiGaIaH3Z5tSNOPKaJKTuPPOO8dPfepT0bKM+nP2Zhvtbdbr2YYUzXiwNkbL9hznnnvuuNJKK3mZGW7G73znO/7cPvvsE00VFP/yl7/4vUUXXTSaNKH2bLsnZpfg7VsumNJNmJg/rrnmmoX1zYDSy++9995oqoloapZozFatrjFR0Rix2jUnps6I9nYfGYMxIpE2TEUTzd7B6/3oRz+KCyywgI/za1/7Wtx+++3jeuut59eHH354ra3rrrsumg2Et2HGnt6/qYhq96ueGAPofey+++4jHjXj1Gg2LX6f8ZvUJ1oitxH1TFUVze7Dy0015fW/9a1v1eqdd955XmYSpVoZJ8Z41JWz3sbc+ffNVD3RmJC46qqrRpOQ1D3HhTFh/qwZtY6416yA77Uxtc2q6F5/EZgGZyoaEATEgAzIQoyBYXTKgKQp2ptujQGhzCQY/uPOJvDqq696NTZIfryzGy2bDpuvva2npuIBBxzg9UyE7mUmQahjQCg0O4kaA8K1GSj6M9/97ne5rJG9ffsmVSto86QdBuSd73xnNPuIwh4TA8LNiy++2DEwNU20N32vn2dAvve97znTBbOViLrgmTZuyu2N3stMGpSqOVYf+MAH/NokSNGS6UWTRNTu77DDDv7ML37xi1pZlZNmDAjtmHQsmqTH+4BphCnJkklrotmG1MqLGBDzeonmyRKZB/UTmYTJ2+U3z6Rpfj558uQakwtGML0wedzPEwzwV77ylXxx02sxIE3hGY2b00bKCm2VREJACAwHAuj1s4RxIMaTqBhQN0B4L0C4UCZCTM79rNgdsThluE9WpbzB5gorrOCeElXb6bQ+tgh//OMfA14srQg1BaqDIqPU9CxqKGwtsrYkqCsWX3xxV2+YVMirJjucrF0GuCfMTZLg6i0MOD/72c/6Bxda1gmvkl6QMYVuiGoSrmBMTmBN0njoz6Q1bpyKd0ojWmyxxVxNha2HSXbcuPS4444LBx54oD/yvve9r+Y1g2EvNiAQGOEijurHJCpelv0DntjhiMY2Av/9hRnbc9DohYAQ6CECM888s7dur0hNe8HDgXgNeLVUpTwDUvX5btU3NZSnbE8MQat2scXAyBKbF7xKMJJMBF5sknhv5MnUC+GRRx5x1958zIxUF9wT5hiEwhRhR9MPMvWc2/9glwFTidssLrEwP8wVQ9Af/OAH7sprqhkfEjZD0J133hkoM6mJj9nUax4X5Gc/+5nbfJiaz+1Lfv/737txKvWh+eef34/pD89DxCnJE5452CGJxjYCYkDG9vpp9EJgYBDAqJS38o9+9KOVxzQoDAhxL4jfkXWxbTYZxo2hJtIBjFIxumSThrhHIDI2cbx9EiPHPVPzcCjtMcOztG1qsZbBwLzhDv+Y6iiss846NSkYUhDifCAVIegamz/SELMfqfWUmCWCkWHES90kScKllw8E42VqPY+xgosz0g4oecT4hf3BDXfWWWd1N+hUlo5mK1STzKUyHcceAlLBjL0104iFwEAigJj+5ZdfDmZA6ePjzZnrZpQYDzboQSHUSngH5YkNNr3lZ++ZYa0zH0VqARgTmJn0lp+ewytmwQUX9EBgqazZEVUFsTbyLqowA3gjdZvuueceZzSy7RIYDBXVU089FT784Q87EwIjkj5INCCCsVFWxIjyPJ5PBG1L0Xdh+qiL102WaA+GC+lLlvAUYgyon0RjGwExIGN7/TR6IdARAkgtsGHA/RZC585Gy0aRiOiUUHKxTeU8k9XDm1Gmv+UmBoR4GTyLOJ/NkyMhubGx4A0WSm/IMC/0y8YH7bLLLh4fxC/6/Af1iHm5jOiV2BgEKCtiqthQzz333BEuuEceeWTAzgaX2kRsoMyXe0kqkmxB8rizPuDCpo09BdFLic4K7kgaCMpFwLREtItKx7yLUlHDY1qDovlgj4F7LWNNBINAGPUkvUnlZY98B4hkiv0LrtcwqImwC8EV+dZbb01FHiCPwGTbWSCzLLEGfPc22GCDbLHOxyIC9uUWDQgC8oIZkIUYA8Po1AvG3uQj3zdcXe13K5pxYzTGIOKSyTXu4Hi94Ga50UYbeZm9hUe8SiCzB4i2ecbddtst4kKL++76668fcbVNhOeGRb/0Z20jcTdOvG7sbdfdb1O9NdZYw+vgefPYY495Md4mEydOjLgLd0LteMHgjmzSiWjGnbWucd+cMmWKj9NyokRcYovI4neMcMO1GCc+F4tfEXEdxcPGbDlqj1scFfdwAXcLQx6N0Ym4r+KyTNlBBx3kHkm//e1vo6krvIzyZZZZxl1yaw3ZiYXV9/umRmqKnUUajcbUeF3mijs0/SYyZiHiZUMfZkjr47IN378jqU7+yDOMK+uGSx3cjfFyMluYQlfe1I7Z0kS+C3i3gCOuyLjc5unYY4+NJhXJF7e8Zmxyw20JUz8ryA23n2i36ksMSCuEdD8h0CkDktpp9wgDYvp5f9xsASIumI0Id85EuPnmCfdME9nXFdtbecRNtFNqhwGhT1yJzZajre5NPTDiOeZoxpTR7EEic+uELGpsjVErage8ic/SDYKpgPGBKWuXTJLiMVDKPg/T26g/cFxuueWiSUrKNlerJwakBsWgnEybIQOz1REJASEgBKoigGqgGVmQrdpt3HzzhB2IBaKqK867B9fd7MMFqgILxua2G/kw4q26x7YjT8wRNU036G1ve1vTZlBjkLm2G4RnE2qQTgh1ThVaZJFFGlYnRD5h35OHTMOKujEmEBADMiaWqfwg0Q1jgY7RWrd+hMr33t2apO/GOK1o02rWE7rtolwRGAkSswAdNoaDovYRwBgTPTw2I7hEjjcinPqZZ54ZPve5z7ndQgodPujzxJaE77lFWh30oVYe31FHHRUsoFkg/opofCAgI9TxsY4+Cwv17Pk08LvHCn2sEgyUiVk942je8LHMnHCjJIiTReZ0Q8bvf//7bk2PJwL5OHDvw8Uwb3Vfpm3VCW5sSUwHk+OGfffdN5BufTwSUphTTz3VmdaxMj8Y6/HIfIC/RY71z1hZC42zNQJiQFpjNGZq4JZGsCAoa2E+ZiZgAyW2wKRJk2qxAdoZO+JuJEDphxgvAYJEEbXSjPSC6bQ9vTquhFj6i6ohgJcLwaGQNJE0rVuqhWqj6F/tfFr4/vWsnrII5NV02Xs6H5sIiAEZm+vWcNQpE2c6Nqw4oDf4seczceLEjkfYSM2CjhmXSTZOMp4S5lpUHgFE/EiZ0qds1NDyPaimEBACw4CAbEDGwSqTe4OU6IiMLdmXzygFeErTI403dhGoZgjsY+5u6Zbr8i0TqccwwLiLUMtEXSRkcopSSGWCM6Ee4Yi0hb4sQVatnWZ91Cp14YTYEsQ5IDpjszwUzbpK4nViJpCO3pJq1ao3mwd2D2WwQj1xww03uHqCWA/k+Mja5DTrozYQnQgBISAExjECkoCM8cVFrUCQo//7v/9zhoHcFFCWAWHDtFgCnncBi3as0lO4aMToqCgIGkWgKKz/CWZEdEVUGOTGgIi4aCnXw8c//vFa/geiOSZq1keq060jIa+/9KUveSCmTtrEu8Eydfp8YSygZvMoixXt7L///p4kzGI/uMU+14ma9ZHq6CgEhIAQGPcIDIpDsMYRPTAUAaDKEsGECAaVjcFA+m/70kYzvPRmyqTxLpOCnbgTlsuhNjSCVlXpo/ZgyRNztfN5FMUDICW5qVDqgl4VNfv5z3/e27jggguKbnsZAa/A6/bbb4/dwopYBZZYKxqjUev30EMP9fMyfdQeanLCehCHg7HrIwz0HSj3HVAgsiY/Kv2/pTgg9o87ZomcC7ilZW0dUmbNJAHJpvFOE82m8bZIle7mSn3UKsl4NZ+CHRUCKgUs0UnDTTjl5K9fpo/UdzeOpIL/5Cc/2Y2m3I2UhmizzDzKpKsHS+xLCJ+NFwU5NAihDZXpwyuW+IP76ymnnFKi5vBWIez7fvvtF4xha1tdN7zoja+Zb7bZZuNrQuNgNrIBGcOLSBpwjCizlBiPVNZuGu+Uo8KYYm8KjxE2UXI2kMkSd9btt9/e77XbRxrjaB1RK7FBkZET1RR2Je2kPM9jxXxOOukkV1eh7sLeBqNX7FW6iRXqI1RiosYIpAyrqA+z9kqNn9AdISAE+oWAbED6hXSX+8FmgWBQpjoobDkxImyOKY13YcWShXjVkATrqquu8k0aA1ACA0Hd6qPkULpWDeNdiGBnzK+b85g8eXLARoaMnxgIY7CLPU03++gaEGpICAgBITAKCIgBGQXQu9ElqhLe2nmjJjV1I+pWGm9LJuWZMfHkIKAXb/WItaFu9dFoDr0oJ9W3Jf5yVVJKcd6teZDBFMNgJCuWdMw9h8ikeskll4xJrHqBv9oUAkJACIgBGcPfAaJQQoSLZtMz48dgBpdedvPNN3vq8zJpvMukYGfDvvrqq71t8kOgWjBDS78u04dXrPAHjxOoKFU4YnVsXZAsNCNL2uW3s9FUkRzBCOD1gysu4d4tI6zXKzOPMlihtoKpSeor+gIrPmX6aDYn3RMCQkAIjBsE+m/4qh4bIdBONlxTi0RjCKIZR3qWSFJVk2KdTJ6mAvCumqXxxqOkTAp2UmSbIWrE+wLvF55J7dNJsz4azbeo3Axkoxm5ejp0+yfz1OUW9ruu6sUXXxxNxVSX0j1b4bnnnotmeBhNAuEeImZ7EY0J8M/UqVPjdttt5/MgJX2ems2jLFZ4FZktiaeox+qeNQK/RM36SHVaHVkH5iVqjkC72XCbt6q7YxEBfk/kBTNQKzdtJoYzbripMT4RVBqHH354QFxfhXirx7NlwoQJnvOEJcVAMU+PPfaYxwdpJ7Q0faD2IQgZkgOiYRZRJ30UtdeojKRbWe+fRvXaLe90HuCFRIp1aYR3J31g5Gquvd5+u3MchueQlpFXiDxJMkIdhhVvPEfs4owBGWG43/gJ3ekxAtPlBdNjhPvRPIwBzAdksSEadtkqjXfDB+1Gcs8tSjWefa6oDwwxW9FOO+0UMNwsS71kPhhD0TzKjo16Ca9GzAd1Ou2DNkSDiQAM6C9/+Ut38zaJnA8SV3aC32UJT6wrr7wyWxTWXnvtMO+889aVDeIFXngYcvOyY5LF2m9QdqzMHVd0i+tTKyb/0kYbbVS71snwIiAGZHjXvm8zX3311Vv2tcACC7SsowpCYCwgYIEBPZLwbrvt5t5VRx99dCBCMVJDmJJsegPKiBljasHwn//8x42WybEzyEQqBGKrkE4AW6dmTDaG3kRWzjIguKMTcflb3/pWjVEf5PlqbL1DQAxI77BVy/9DQLEqxt9X4ZlnngmoN3hb7wWRtZgMxmONnnzyybDLLrvUvKAY/8EHHxyOPPLIAGOC8Tau83hIQagFcNHGOBkGhPQHg0wYdn/wgx/0dbdIzE2HSlwdvPTytPLKKwdUqEg9ycMkGl4E5AUzvGuvmQuBthBgoyQSLZtRL4hcOeT6GYu01157uXohbyP1jne8wz2vHnjgAWes8qZ3eGINutrlX//6VyCa6HzzzeeSj2br89BDD7m7/nrrrVdYDcaVOiTIFA0vApKADO/aa+ZDiADB0W666SYPYsebNy7CKWgdWZAx1iTEO6Jzy1sTkES8+uqrHnyOt3TcvbfccstwzTXXBOyBeHaDDTYIqNCuvfZaD2n/zne+092biTKLrn+FFVZwpMu0D/NB6HraJcw84f7XX399fx7bAWwrBlWihnqFbNGnnXbaiG8WNkHnn3++Sw9IpogB8QEHHFCrRyA8Pnlqtl7UfeKJJ9ytHFd8865y3FGJsEbZ9rqRfZnEl3fccYfPj9QFjYjvC8kXiR104IEHNqoWSNSIKofvYHasDR/QjfGHAF4wosFAoB033MEYuUbRbwTaccMlOZ+9wUZjMtyFmkR8JvKPptOvDX/ppZeOZtBcuzZReTSD37jSSit5mRlNuvuz/RLGffbZxxPu3XfffXHjjTd2l2djRiKuzmZ47K7ItvHGH/zgB7X2WrVvQe7iKqusEo2h8ba5TrTooou6i3m6LnPspxvuJptsEtdcc83CYYE1dO+990Zj8NyN3BiyWl1jtqJ5NtWuOWm1XpYSwXFiLXBdt9QI0SQOvg7mTVdr67rrrotmc+FrfuGFF3r/rE9VAn/Wc4899ohm1xWNCYmrrrpqNFVcXVPGfMRbbrnFy5hDI3dxY4p8rBaLp+75Xl2Ak9xwe4VuW+1OI1iSaEAQEAMyIAsxBoZRlQEhSzKMBAxEIgvR7xuAJRhMRdFyC9UxINwwSUmNAeH6rrvu8ufsDZdLp4cfftjLTDqRiiIxXWAkYGjsrdjLy7RvdhJxscUWq7WTTm677bZoAfbSZaljPxkQk/x43JqigSUGhHspjo2paSJrAOUZkLLrRbwbNlaTSHk7/GG9LEmlX3cr+/Kf/vQn78c81SJxdiDGTrwbGCruQxYcMB500EF+zp9mDAj3Te1UFyOHsl6RGJBeIdt2u9NGyvxslURCQAiMLwROOOGEgBto1jYBbwyyGp9zzjluFFh1xkl1w3NJJJ91pU7eDrY5hUceeaRS89m204Oockw6ki4H6oh9BConkhm2IpMWBdQZySgVVVeeyq7XHHPM4Y+ytonIZP3444/7ZTb7sgUnDHyITUPma2Ma0yMtj6iCIIxosQGB+P4cf/zx7mqMRwsuxcSnYW5lie8jdjGi4URANiDDue6a9RAhYO8n/iOP90GeTITuzMGDDz7o4e3z95tdFzEJ+frJ5RSvGWxDylKZtsu21Y96JBrEODcxBK36xC2XOBrYxeDtk/Um6nS9SHhIG1C3si8nxjWlX0jzM9Wcn/L9MWmH27iQLTsRKRxIp0D6A9yLyaqdJeyNYFBFw4mAGJDhXHfNeogQYDPHwwIDQjZJNqhEiSloxwOjDJNAtFeoahTSMm2nOQzCcaGFFvINtkiaUTQ+5ofkCakORqlkrEY6AXVzvbLZl5sFKSwaY7YsMZK4XmcJg1faxa0YJjPli0p1kPKQtdtSNwSz/xnBgJDzCYmNaDgRkApmONddsx4yBNjo2BzJZJwlROt4syQGAW+NogSA2WcScwAz04rMADKYPUJgg4bKtl+m7VZ99/s+GyypCvKENIJNOE9E84X5KFJDlF2vfJv5625leGb9PvrRjwazw6nrAgkHXi+oxi6//HKXZiDRSB9iouAhxfVVV11V9yypCsjkjTpINJwIiAEZznXXrIcMAQJhkcPn7LPPrs2cDYAoldxLUhFcIol0ecYZZ4R//OMffiScNvYNKUNxsnPgWTbXe+65p9ameXnUzgnKhdTlqKOOqpWVbR87BfrELZhxQGxmxB8ZVEKdlZ1/Gie5ncCiiLEjCuq55547wg217HoR0AvCBiUR64e7NGtTNvsya0mGaYKHNaLjjjvO3X5vvfXWWhXcppdaaimP5ForLHkCJrhV48YtGlIE7EsqGhAE5AUzIAsxBoZR1QuGKVn8jzhx4sRo8Rciro9mexBPPvnkutniNbHiiiu6x4NtLNF09+5ia2+/ddmH11hjDa+DO6apWaJtsn692mqrxR122CFa6G33xMDjI0tl2rdNzd09zWYg8j+RCE8Sxm+bVipqeeynF4zZgXgWZzyCEuH2OWXKFMdmrbXWirjEFtFhhx02wg231XrhcWKSK2/b4rb4GpjRqXs72Xbm3ih4H5XJvmzxXrwdMG+Gr9mtRNae7M6MGbdf3GkbEa7ajdxwydyNy3W/CEzkhtsvtEv1IzfcUjD1qZIYkD4BPQ66aYcBYdom9YhmMBhNMhHtjbwhEqZKqN176aWXaufphHZMrJ4uawwIm5JJLKJJL7yvWoXcSav2cRcmBkmWGK+92WeLWp73kwFhMJYbJZotR8txFVUwdcSI4rLrNeLBggKLXOvMYsEtL2JNdt5550a368pNehFhuNol5mVZiqNJU9ptovJzYkAqQ9brB6bJCHVIJV+a9nAigP0GYv9WhN4+0eyzz55Oa0fascBUtevsyZxzzunuvdmy/Hmr9pPXRfY5VEiDTiRZIwoptjb5zLetxl6UabrserVqm/utsi+jWjEpTZmmPEJtqYoNKhGyngR1yYumQTUVj3MEZAMyzhdY0xMC/UAgGVkSC2KYiZDiZ555pmd6xf5lrBC2JDB9xCjpNWEThGFyP/rq9VzUfmcISALSGX56WggMPQIkpUs5P8zmw40SkQLMNttsQ4kNkppTTz21FgxsLICAR46F5e/LUC3ybkPpWV8GoE4GBgExIAOzFBqIEBibCJAwzmxS/JNm0EnMidTGWD8SI0M0EoFGqruRNVUy3hEQAzLeV1jzEwI9RgBJx7BKO3oMrZoXAuMaAdmAjOvl1eSEgBAQAkJACAwmAmJABnNdNCohIASEgBAQAuMaAalgBmx58SLYbLPNBmxUGs6gIUAmU31XWq9Kit662267BRKfiYSAEBgcBGYi0sjgDGe4R0J2zMMPP7yWyXK40dDsBx0Bvq/YfhCKWyQEBh0B0g3w+7r44osP+lCHZXzTxYAMy1JrnkKgywiss846gbwwp59+epdbVnNCQAgMAQLTZQMyBKusKQoBISAEhIAQGDQExIAM2opoPEJACAgBISAEhgABMSBDsMiaohAQAkJACAiBQUNADMigrYjGIwSEgBAQAkJgCBAQAzIEi6wpCgEhIASEgBAYNATEgAzaimg8QkAICAEhIASGAAExIEOwyJqiEBACQkAICIFBQ0AMyKCtiMYjBISAEBACQmAIEBADMgSLrCkKASEgBISAEBg0BMSADNqKaDxCQAgIASEgBIYAATEgQ7DImqIQEAJCQAgIgUFDQAzIoK2IxiMEhIAQEAJCYAgQEAMyBIusKQoBISAEhIAQGDQExIAM2opoPEJACAgBISAEhgABMSBDsMiaohAQAkJACAiBQUNADMigrYjGIwSEgBAQAkJgCBAQAzIEi6wpCgEhIASEgBAYNATEgAzaimg8QkAICAEhIASGAAExIEOwyJqiEBACQkAICIFBQ0AMyKCtiMYjBISAEBACQmAIEBADMgSLrCkKASEgBISAEBg0BMSADNqKaDxCQAgIASEgBIYAATEgQ7DImqIQEAJCQAgIgUFDQAzIoK2IxiMEhIAQEAJCYAgQEAMyBIusKQoBISAEhIAQGDQExIAM2opoPEJACAgBISAEhgABMSBDsMiaohAQAkJACAiBQUNADMigrYjGIwSEgBAQAkJgCBAQAzIEi6wpCgEhIASEgBAYNATEgAzaimg8QkAICAEhIASGAAExIEOwyJqiEBACQkAICIFBQ0AMyKCtiMYjBISAEBACQmAIEBADMgSLrCkKASEgBISAEBg0BGaKRoM2KI1HCAiBwULg2muvDVOnTg3/+c9/agN77bXXwkwzzeSfVDjrrLOG22+/PUyaNCkV6SgEhIAQKEJg+ixFpSoTAkJACGQRmDhxYnjllVeyRQ3PJ0yY0PCebggBISAEEm/A6uAAAEAASURBVAJSwSQkdBQCQqAhAksssUSYPHlynbQjX3nmmWcOa6+9dph33nnzt3QtBISAEBiBgBiQEZCoQAgIgSIEtt122/C61zX+yUAls9VWWxU9qjIhIASEwAgEZAMyAhIVCAEhUITAtGnTwqKLLhoamY3NPvvs4bnnngtzzjln0eMqEwJCQAhkEZje+HUmW03nQkAIDD0CCy+8cJgyZUqhFGSWWWYJG220kZiPof+WCAAhUB4BMSDlsVJNITD0CGy99daFGPz73/+W+qUQGRUKASHQCAGpYBoho3IhIARGIPDCCy+EBRZYIMBwZGnuuecOzz77bMANVyQEhIAQKIGAVDAlQFIVISAE/ofAPPPM454ueLwkgunYYostxHwkQHQUAkKgFAJSwZSCSZWEgBBICKCGweMl0auvvhq23HLLdKmjEBACQqAUAlLBlIJJlYSAEEgIvPTSS2G++eYLL7/8she95S1vCXjIEBVVJASEgBAoiYBUMCWBUjUhIAT+h8Acc8wRNt5444DnC+qXbbbZRsyHvh1CQAhURkAqmMqQ6QEhIARQuWCIivoF+w+REBACQqAqAsoFUxWxBvWfeuqpcNNNNzUM0tTgMRULgTGJAEnpCDg211xzhYcfftg/Y3IiGrQQqIAAasa11lorvOlNb6rwlKo2QkA2II2QqVj+xS9+MRx55JEVn1J1ISAEhIAQGEsInHjiiWH33XcfS0Me1LEqG263VoY3wuWWWy7ccccd3WpS7QiBcYXAZZddFjbccMPwr3/9Sy67TVb26aefDhj23nDDDR55tklV3eozAosttljgt17UHQRkA9IdHNWKEBACQkAICAEhUAEBMSAVwFJVISAEhIAQEAJCoDsIiAHpDo5qRQgIASEgBISAEKiAgBiQCmCpqhAQAkJACAgBIdAdBMSAdAdHtSIEhIAQEAJCQAhUQEAMSAWwVFUICAEhIASEgBDoDgIKRNYdHNWKEBACfULg+OOPD7PPPnvYdddd+9Tj2OqGCLW//OUvw9///vfw3HPP+eDf/e53h/e///11E3nhhRfClVdeWVe29tprh3nnnbeubBAv7r777nDjjTeG2WabLUydOjVMmDChcJgXXnhhmDhxYlh++eX9/g9/+MOw0UYbFdZVYf8RkASk/5irRyEgBDpA4PTTTw9nnXVWBy2M30dffPHFcMwxx4RJkyaFVVZZJTz44IPhk5/8ZFh99dXDQw89VDdxonm+613vCkcccUQ49NBDw8ILLxzmmWeeujqDdvHss8+GT3/604HAjx/72MfCZz7zmYbMx69+9auw1VZbhd/85je1aRBfZccdd/Q0ArVCnYwaAmJARg16dSwEhEA7CNx+++3h5z//eTuPdu2ZZ555Jvz0pz/tWnvdaOjJJ58MW2+9tUuG3vjGN4Y3vOEN4eCDD3YpAYwJQeD+9re/1boirPiyyy4bNt98c/986EMfGuikgo8++mhYaqmlwiuvvBKuuOKK8Na3vrU2l/zJP/7xj3DQQQd5rqLsvZVXXjlssskmYaeddsoW63yUEBADMkrAq1shIATaQ4CNlYy8o0VEwkSqwIY4SLTXXnu5eiGfp+Qd73hH+MhHPhIeeOABz1wcY6wb9pvf/OaBV7sQPXezzTYL8803X/j2t79dN/6iCyQkX/7yl4tuBdRMSIMGjYEsHOw4LxQDMs4XWNMTAuMNAUKVo4ZJhM3D1VdfHa699trwz3/+M1xwwQXhkEMOGaFy+NOf/hS++c1vesLI66+/3sX4J510UnjppZe8qWnTpoWTTz45nHDCCeH+++/3MiQtXPN5/PHH/e0bicE111zjySdPOeWUwHMQ6gHUGSSm7Ddh8/GTn/wkbLrppiO6nmWWWcL5558fllhiiXDppZe6uiVb6XWve13gkydUF+Q9YU5XXXXViESbTzzxhN9/7bXXwn333RcOO+ywcPbZZweu8wRe3Af/ZJeSr9PsGmaCNBdf+MIXXLLTrC52HksuuWRYeumlG1bbc889w3777Vc41oYP6UbXERj5ret6F2pQCAgBIdA5AkgezjzzzMAb/Ze+9CVv8C9/+YurHXjDP+OMM1y//4tf/MI3OlQKzz//vNc799xzw3vf+96w9957u4qCjfKee+4Jn/vc5wL1Xn31VbeBWHDBBcPnP//5cNttt/lz2E789a9/9TLsKV5++WV/g+bmoosu6jYUSRrD5s64MHzsNx199NFhpZVWCqheigjDUsZH9uIDDzwwXH755UXVamVIU4466qiw/vrr+3zZ+D/84Q/XmIcf//jH4QMf+EBgI//6178eMAwGs2222cafSw0hucDmAuZsvfXWc9UZBrG//e1vU5VSx/POOy/ASN17770+DuYxZcqUOvsOGvrzn/8cLrnkkrDbbrs1bRf7GAxZW+HQtBHd7BwBE8eJuoDAPvvsEy0ZXRdaUhNCYHwiYBsgsv9om1JHE9x4442jGRPW2jAJhrdrzEI0RsLLf/SjH3mZbZS1emaQGM3uIdrbeq3sgAMO8Hom1vcy7jHG0047rVYntWVSAC+76667vM53v/vdWh1OzOskGqMTjWGpK696YRIUb9+S0ZV+9J3vfGe0zb+wvjFetfKLL77YMTA1Tfzd737n5SbFiSYJqtX53ve+F+eee+5oXjK1MuqCCxgmMgmCl5l0IxVFsymJxpjUro899thoDE/t2qQm/sxHP/rRWlmrE5Nc+TOTJ0+OJj3x6ozHjGajMSKR+5BJXuIWW2wRp0+f7tdm9+LPfetb3/Lr/B9jyuJXvvKVfHHTa/O2icZsNa2jm6URmCYJSOc8nFoQAkKgjwi8/vWvr+sNl1wMKlEx8JYMvec97/EjapNE2I5wPyuaRwxPGS6dVYk+s0T72IY0kkJk63bzHCnDH//4R5fgtGrXmDe3jSgySk3Pom5CSpG1JUGlsfjii4dzzjnHJULUTZIf6iYC9yzmSEbuvPPO8NnPftY/qHPwvEmSqfRcs2PyYsGIFhsQiPHQNq7GxmB42de+9rVgDIhnEvaCFn+YH3YxotFDQHFARg979SwEhECPEJh55pm9ZXsXa9rDnHPO6W6ceLVUpTwDUvX5btVnM0c9lRiCVu1iH4P6ATUKKhOMMhOBF5sy3iJ5WnXVVcMjjzzirr0prka+DrgnzIkzgkoEt1lUOe1SYoTmn3/+uiZQOUGoxjAq/cEPfuAqNlQwEPZAEAwQZdTH1TgRahzsgkSjh4AYkNHDXj0LASEwygjg0mki+2AqgcojGRQGZKGFFvL4HVkX22aTYdxIMlZYYQW3CzF1hksneIZ72Itg8AlTkxg57pmah0Npj5lk2IrdRicMCNIO6Ne//rUf0x/ccGeddVaXOMFIIHnZfffd0+0aI4RNDga6pjKrY0CwH0qSstpDOukrAlLB9BVudSYEhMAgIYDBKoalGEhCSYVDWSNKjAcb9KAQaiW8g/KENCJJArL3zMbDmY8iNQSMCcwMkoMsoQrBSPftb397trjhOX2gtkFFkjyNUmUYoKyqJpUXHWGwYBCTYXCq8/vf/96NhzEoxUAWJiT74T6E2ofyLJOJpw7eSqjtRKOHgBiQ0cNePQsBIdAGAkgtsGHA/RbCDoCNFluIRHhdQPmNj2eyen8zygyrrbZajQHhbXuihe7GbfWxxx5z8f5FF13kbbEhs3ElMT7MC/3iTQPxho5qAhfffhPqESQNecJFmABlRQwVthh4ByVJRXr2yCOPDNjZ4CmUiHkzX+4lqQjeQVAed9YnqWHMON83fxgEcAFDvHBYvxRIjHbB7Tvf+U7qbsTxuOOOC7j93nrrrbV7uEgTmGy77barlZU9ARO+CxtssEHZR1SvBwiIAekBqGpSCAiB7iMAM/GNb3wjmHeIb6jEhsAmIQWc+tnPfuZuldgdHH744T4A3rSzons2W2JR4FaKwSJMBrYQiZBu7L///h7XYplllvF4ItgwkGsEVc3DDz8cFlhggbDGGmsE85TxYwpfTluE/6ZOv4n5MO8//OEPta6xiWCO4MZGWxQ9ljwqX/3qV2vPcAJjQtwO8/5x92OO22+/fTCPIT9ShzUg3gYE1mAD03bTTTe59AQ7Ezb4nXfe2eOtgAsuzTAaMCy77LKLP8sf8EoxPhpJlZDw3HLLLcG8VpyBoU9caIn9kqRWtQZLnKCWQXKy4oorlqitKj1DwDhVURcQkBtuF0BUE+MagW654bYLkuUNiWYz4I+b+D/iptmIbNOuudPahhltY6yrisunifXryrho1uaIyg0K2nHDpSlcic3bpEGrzYvpM0/M0Qw8ozEH0SQo+duVrk0N5O7PFiK98DlTH0VjVgrv5QtNehHN8DZfXPqaeREywaQppZ9JFeWGm5DoylFuuD3j7NSwEBACA4vAYostFrBRaES49iZ3Wgwd82oKJCUEIstTszbzdbt9TcAvoozmbTfK9INtR56YI9IQ26xdJZO/X+UaDx2kGHgdFRGqlbXWWqvo1oiyRRZZpLQh7IiHrYAga4RqT140RXVU1h8EpILpD8597QX/eMTM/aJ+91dmXohYCU/dKWFLgDi6F9Rv3PrdXy8w66RNjDFRC2AzMh4JJolIsRh9otIYK4QtCcawxCjpNRHdlQiu/eir13MZD+2LARkPq5ibQ7/Tlfe7v9x0R1wWpeEeUalkAYZxhO/uBfUbt3731wvM2m0TY0tsRExwHPbdd99g0UzbbWqgn8N49NRTTy0djGsQJoPUiHD4/SCL5Br4iAYDAcUBGYx1aHsUZ511lgcTyjZAuvK8yDh7v5PzfvdXdayN0nBXbYf6GMTxNon1PQZ8GNG1SwS6whgyG/Spl+vU7/7axaVfz+Fmi8Flonw01VQ+Xo7Jw2S8zKdb8yhSm3WrbbVTHQFJQKpjNjBPsCmmpFzZQfUqXXm/+8vOqex5szTcZdtI9S677DJ30UQXTnjqdglGpih9e6/Wqd/9tYtLP59DxI+3SvqUjRrazzGqLyEwbAhIAjKKK457HL7xBPjBt37rrbceYdiGvposlkQrnDRpkgfT4ccUZuBjH/uYRy4kJTiGWSnaIAGJcFH71Kc+5fpu1Ai4viEVWWeddQLuhehdLemUBylCH5qiHBLSmIA/xDbATW2jjTZyhMr2l4WTeeGWh+7dklQFMpaymSdCskCIZDKSkh2TDZ83ty233LItCU6rNNzYc4AFuFgyszSMhkfzKghIfAhYBJ64C5KJtYgarRMxEZgPdiQY+jF/XCKJJZFdJ9oE42S38uY3v9lDWFPOdwRpCc/jDgk1Wqcq/XlD9oegU1dccYXHx8A4k3XimKjb65Ta1VEICIEhR6ArzjRqJFZ1w7Uf/WjiwGibTjTDuGi++PFtb3tbxF0tkQVMiuuuu260vA2e5ZNMj7YxRfP1j2bpHo1BiBaTwNvgmnbOOOOMaNb7ddlCbVOLxuDEfAbKvNueJXOKpov1rJIWXyFOnDgxmjGrD6dKfzxgKc3jZptt5mM1RiSSkZO2jQnw9sgwytjt3y/Sr22s0cTkfm0+/l6nyh9c81KmTlwhadfUJ3VNGPPh5ZY+vK686MKCOsXNN9/cbxlj5M8Zo1RUNTZbJzKKpn75jrDeYFC0TjRuzIn3ZcGZan3hNmgRJWtun83WqWp/ZHY1xjaSJRVXSLKXkmGUjKhQN9dptN1wa4AO+Em7brgDPq1xMTy54XZ1GadhlCXqAgJVGRALkBRNIlFLHZ1SfMMsQDATpJ82g7La6MyGIM4222wxpRi37JDR3lRr99OJSTTqGBDKt91222gucHUpti3AUnz00UfTY9He7uviCNA+DFCisv11M5136rvZkQ0a5qxVGm6TUpROl77TTjvFlA6dGBAwh2zM2RTljKnMOqW1zadvL1onmEu+FxZcqzZl1shcLGvXrdapbH8mLYmWyXRESnJTF/n37P777/c+y6Rdrw2uyUliQGAO9REGY/E7wO+veZM1+ZbrVgUEpkkFY/8Fo0FEKEQtgSqAMMlEFoTIX/DBD37QReK2kdQZzlEfcbn9E9SGnFVppMIiAzvSYaNyITIk57TDxzbW9JiL+rFLgFCJIHpP4ZZTpTL9tUrnffLJJ3sMhqSHz6fzvuqqq1J3pY5l03CndOmtGiWLJ9ij2oJQXRG5kdTtRL/8v//7v1oTqC7KrBMP5LErWifybGCoisfKQQcd5FEeOTeGqNYnKplW61Smv5/+9KceajwfDZKcGd///vc9eRchsLu1TmkCtN1O9Mr0/Hg/EqacmB6sv5KlDdZq77rrroM1oDE+GjEgo7SAbGowH4QWJugRTAdkb/N+JF02mwxhn7OUZT4oz29q2brZc9rnw6YKA0LYZGwTsoSFeApnTX4MEjVlw1hTt1V/xv12LZ13dmyNzttJw92orVTOhk8ODTBIhHcNRCjwPffcs5YPo+w68Wwr7KgDsT54bBAC26ROnjr94IMP/u9N+1tmnajcqj+YTIi05FkirwiUzZmSvc85NkusdTu06aabehbTdp4dhmewDYIBwetqypQpwzDlMTNHgpiJuoeAGJDuYVmpJbOxCGYTEZAG4CLIRpolGBE2PbMZcKPA7L3seatNJluXjY3ETSR/uvLKK0NKspXqkOsBSQwSCN56SdSVp1b9cb9b6bzzfRddk+WyahruonZSGbhjeMrmnN+Y2TjBBGNXzqGy60TdVthRB8JQGEkIzCLMKddZKrNO1G/V33zzzefN8n1ITAcFSMWI/sk6ioSAEBACvUJAbri9QrZFu4hXX3311VoWziT5SI/h8QIhrs4SoZZTEig2GFwuy5IZVQa8K8xANJhRaO0tnudhiA499FAP0pNE7vkxle2vW+m8y8yrahruVm3iiUPCrDzzwXO77767P551yS27TjxYdq3AGZXP1VdfHVCB4MKbqOw6lemPdYJuvPFGP6Y/9913n383Fao6IaKjEBACvUBADEgvUC3RJtINxPzYEOAemkKnk9ESGwRcNd///ve73QYZJcn6iK0DLqRmGOo94MpJFso//vGPngUzqQlwxUSPbAaSdSPhbXqHHXbwjJ1k+MxSCk+Naga7D9xn2Zj+8pe/uCsv9iJl++tmOu/sGDs9R53ULF06KgWybCbX43x/iMPJikpWTj5Q2XWiLpIG+kjp2xutE3VZZ9YLt9+Uk4TysutE3Vb9ve997wtmnOzrjBQp0c033+xu2cnuJNkBNUu7np7VUQgIASFQGgH7QRR1AYGqXjBkYsSzwgwRo214keyclqMgmtjbXTQZEtk2LUFTtDdi/5jKpuaKyX1cOs2YL1pwpYhrKS68HHHVtS9AtBTdMZ/l0t6gI94sRWSbnreHlwUuupbO270hTMoQTfJSqT9jYNyN1+wlIm6s22yzTTR1U61bM6SMpmbwceKNY8xYPO+886KFZfYykxC563HtgQonxoh5G3k3XFxNwRK32DyBk6k6/DncgXF9zhIeIyb5iGaX43UYO14dUKt1oo6lb/fnTK8fLaZLy3XiGdYDz6c8tVon6pftj6yvppqLligsWh6RaEa20exP/PtIO91cp+QFQ3ZZUWME5IbbGJvRviM33K6uwLSZaK40t6KKDRGwzd7tNaokgULFQTCy5NHAUqCWyRuaIhGhbtLZZweBpAOD1uxbcvZ+0TmBwRplpUTSkW2Lt/Sst0aV/pgPti20iaoi207RuPpRxtt8rzKWNlsnsEC6VSUUdCfrVLU/1tXcbj0QHFKeXhDqLYxqkaRgYyIqRgAjVAzUsceSEWoxRqNVSoA+DFFRY4s6RmC6jFA7xrD9BmAcEvNBK+j+88wH5YSPbkRERa1KjZgP2skyH1znmYYq/TEf0nm3S2Vc3lATWLyU0l30ivlgAM3WCSyqMB+018k6Ve2PdV155ZXpVjTGEUD1SkRd1HXYjEG4uqPSzRIMM8boWcIFfCwYH+N9hoqY30s8xhoxzWTFnjhxoqtemSf2c41UrFkcdN4fBMSA9Adn9dIGAmWSv+XdlNvoRo8IgXGDAJIs7Ml22203l4weffTR4ZBDDvF09zAlSy65ZG2uMJ28IOAZh4E0HnnNmOjag6N4gr0c8XiQJpIqoVnSvZQV29TSNQYEyRIuziSZVCyaUVzI/3UtBmT010AjaIDAxz/+8QZ3VCwEqiNQlCG4eiuNn+h1+417/u8dS0fg3lNnn312TZJJ/BiMwmFMUH+RUyhJOZGSEdwQ7zgYELMxa9XFqN63iMAeywgpDcb7zQiD/ORpmK2HlA81LJJT4v2IRhcBecGMLv7qXQgIgT4gwAZblJG4W133uv0y48Q2AfVCXk2KJxUJBgksZ8bgIwLI4Zo/6GoX7IYst5TbwSH5aEXNsmLDwGCbRiRg0egiIAnI6OKv3oWAEGiBAEbMjbL1Wl4kd0Enbguu5dQlkBzG3LiN83aPIXVRRmLUd7i3Y4dFNmiMZHFpZxNPMVI6aZ/+sTnAJqPX0jzUKz/5yU88VUAeTlQNuNcTCdk8kTzeD8HsEmGLxidP3cxmTTZopC8wOikeUb6/ZteWGylg4E8qhKzdXNEzYI6qyTy7im57GdGMUeXAmBXNveGDutFdBMxaXtQFBKq64XahSzUhBMYUAu244ZJYr1m2XgDAhRj3yEQmYnd3bguk5kVmbDkiI7EFW4skA7RfU89AjOuxGT1HYxrcFR0X9ETttG/xc/xxMzx2t/jUVpljO264m2yySVxzzTULmycTNUSGZ2PU3BU9JbSk3CLuxpNOOonTGnUrmzXu67jZ42LPWloE4Tj//PPHlOiw1mGLE3Ak5MAee+wRcWU3JiRa9N4RbuplsmLTldmQ+NoTIqAKyQ23Clot6yobbkuISlYQA1ISKFUbWgSqMiBsXmWy9bKpZRkQADbbhpgYEK7Z/GA2shmJH374YS8z6QRVnMiobJIRb8+kKF7Wbvs8fNttt0UL7ObtlP3TDgNiEhyPtVPUR2JAuJdi4ZiaxuPRUJZnQLqZzfrYY4+NBx54IN04WYJLx9wSHqailkfi7LB2ZAcnHhFELB2YRRgq7kMWqqBUVmyvbH+IuWS5uNJlqaMYkFIwla00baTcrbsCFrUmBISAEGgLgWbZerEJMGaicrsYXiZKovysG3fykrBNzdMTpLplj9n2eQZVziqrrFL28bbqgQWqI1Q+rcikPgF1RjJKRWWVp1bZrFNk3JSyIZ/NOhtV11LXhzvvvNMTLJKL6ogjjnDPm+effz7fbcNrVEEQRrQpFhIqFtrG1RiPFqhsVmyvbH+wlWmWcDHV07F3CMgGpHfYqmUhIAQ6QKCTbL2Nus0zCEX1kqsqXi3YhlShMu1Xaa9MXTZzjGATQ9DqGdxyiaOBfQtGqRhlJrJX165lsybOCO6y2Oasv/76qYvKx2RUa6qbumdTrqIHH3zQjUpNbRb23nvvcMkll3g9AvlBMECUUT/LpGE3BKMpGj0ExICMHvbqWQgIgSYIpLfdbmbrLcMgPPbYYz4qMhJXpTLtV22zVf2FFlrI43cUSTOKnmWM55xzjktnMEo1dYZLKKjLPQxFMfiEqZl55plrTSRmrKzHTDLuNNuTjhiQxBCSyylLxAAhoi5uxTASVbNik+fqPe95T7ZJnfcZAalg+gy4uhMCQqAcAskTpVW2Xrw8Xn755aaNJsaATbUVXXfddcHyMgU2dqjb7bfqv537eHwQwj1PSDSSJCB7j4jAMB9Faghwh5lBcpAlVCELLrhgKMuY0cfiiy/uKhJSTmQJBiirqsney5+zDmYzEsyepu7W73//e/d2QsVVNSs2qS3M1iYsscQSdW3qor8IiAHpL97qTQgIgZIIlM3WiyslETLPOOOMQAAqjoQgxy6Ct1woid7zGYK5xxt6IoJ58fZ/1FFHpSJ31Wy3/V122cXjj9Qa69GJeYTUzSN1Q8Zt5lTEoBEF9dxzzx3hhtrNbNZmnO/SCRgES2zoTI0ZpboNSopiypqQpdqSRKZhjzged9xxwQxYgyXxrN2zZJxhqaWW8kiutcKSJ2CCezTZrEWjiEBZc1XVa46AvGCa46O7QqCqFwyItcrWSx17W48rrriie0rYhhRN3+8utnhaZDMfZzMEm5rFMzDbT29cbbXV4g477BAteJVnpMZTJEvttk8beKBMnDgx2maXbbLpeTteMGYHEk06EfHsSXTRRRdFS2bnuJBV2yQ76Vbd8bDDDhvhhtutbNZ4poArLrRgzdHib0STRNXGYHFb/B5ZvZvhRIZq1hDPFcZM1mrcaRtRo6zY1Mc7xyQnjR5tWC4vmIbQtHNDbrjtoFb0jBiQIlRUJgRmINAOA5KeJpbHLbfcEnHjbESmgqjdgnHJE5thctnknkkHfONjM2OzMomJu3Lmn0vXVdvnOZM8RNyJq1A7DAjtW4TQaJ4mVbqq1aXPPIGXGXhGkwj5PPL3q1ybGigSewWciwhsd95556JbI8qI9QHD1S4xr+WWWy6aNKVyE2JAKkPW7AG54Y6i8EldCwEhUBIBbBXI42EbQMMnsokJZ5999hH1sANplJGYzMPYKyRbkREPW0E77ZNNuijDdVH7nZaRZA3VU952o0y72HbkCSxQ09hmPSIrdr5uq2s8dLBTaZThGdWKSWlaNeP3F1lkkY5CxxOynlDtyYumVKeq1BMEZAPSE1jVqBAQAoOOQDLOxF10PBBeJ2eeeaYbfWLHMlaIuCIwmMQo6TVh2/P/2zsPuDmK+v8PVUDEEHqTYAClROlVQteE0MUgJoBUKaKA9N4DP6Q36QgoTYpIhyAdAhY6iEE6CR1UJIAw/+97ZPa/d7d3t3vtuXuez/f1uuzt7OzM7Hsvz3535lswMO5EX+2+lv7Qvtxw+8Nd1DWIgAgUIkBmVYwhEbP5CMaM5Ivp1GxFocEWqMyMyznnnJPbw6RA022rirfMGmus0bb20w2PHTu26ixYup6+d4aAFJDOcFYvIiACXUSAafzTTjstfOKwiCnRXyR6mPSX62nVdVRbgmtV+2qnGAEpIMV4qbYIiEA/IMBMR6/PdvSD26BLGOAEZAMywH8AunwREAEREAER6AsCUkD6grr6FAEREAEREIEBTkBLMC38ATz//PNu9OjRLWxRTYlA/yFA9Elkiy22qIi+2X+usvkriVFLMZJNu/4237JaaJYAbs6S1hGYiighrWtu4LZE/ggLBDRwAejKBxwBMqpiR0E4bIkIDAQCxEbZd9993TLLLDMQLrfd1zhZCki7Eat9EeinBEaOHBlyrFxwwQX99Ap1WSIgAm0kMFk2IG2kq6ZFQAREQAREQASyCUgByeaiUhEQAREQAREQgTYSkALSRrhqWgREQAREQAREIJuAFJBsLioVAREQAREQARFoIwEpIG2Eq6ZFQAREQAREQASyCUgByeaiUhEQAREQAREQgTYSkALSRrhqWgREQAREQAREIJuAFJBsLioVAREQAREQARFoIwEpIG2Eq6ZFQAREQAREQASyCUgByeaiUhEQAREQAREQgTYSkALSRrhqWgREQAREQAREIJuAFJBsLioVAREQAREQARFoIwEpIG2Eq6ZFQAREQAREQASyCUgByeaiUhEQAREQAREQgTYSkALSRrhqWgREQAREQAREIJuAFJBsLioVAREQAREQARFoIwEpIG2Eq6ZFQAREQAREQASyCUgByeaiUhEQAREQAREQgTYSkALSRrhqWgREQAREQAREIJuAFJBsLioVAREQAREQARFoIwEpIG2Eq6ZFQAREQAREQASyCUgByeaiUhEQAREQAREQgTYSkALSRrhqWgREQAREQAREIJuAFJBsLioVAREQAREQARFoIwEpIG2Eq6ZFQAREQAREQASyCUgByeaiUhEQAREQAREQgTYSkALSRrhqWgREQAREQAREIJuAFJBsLioVAREQAREQARFoIwEpIG2Eq6ZFQAREQAREQASyCUgByeaiUhEQAREQAREQgTYSkALSRrhqWgREQAREQAREIJuAFJBsLioVAREQAREQARFoIwEpIG2Eq6ZFQAREQAREQASyCUzlTbIPqVQEREAE/kdg/PjxbtSoUe6zzz5LkHz++eduqqmmCp9YON1007kJEya4YcOGxSJtRUAERCCLwORps0pVJgIiIAJpAkOGDHEff/xxuqjq9/nnn7/qMR0QAREQgUhASzCRhLYiIAJVCQwdOtQttdRSJbMd5ZWnmWYaN2LECDfrrLOWH9K+CIiACFQQkAJSgUQFIiACWQS23nprN/XU1f9ksCQzduzYrFNVJgIiIAIVBGQDUoFEBSIgAlkEJk2a5Oabbz5XzWxshhlmcO+8846baaaZsk5XmQiIgAikCUyu/jqTrqbvIiACA57APPPM44YPH545CzLttNO6TTbZRMrHgP+VCIAI5CcgBSQ/K9UUgQFPYMstt8xk8N///lfLL5lkVCgCIlCNgJZgqpFRuQiIQAWB999/380xxxwOhSMts8wyi3v77bcdbrgSERABEchBQEswOSCpigiIwBcEBg0aFDxd8HiJgtKxxRZbSPmIQLQVARHIRUBLMLkwqZIIiEAkwDIMHi9RPv30UzdmzJi4q60IiIAI5CKgJZhcmFRJBEQgEvjoo4/c4MGD3ZQpU0LRXHPN5fCQISqqRAREQARyEtASTE5QqiYCIvAFgRlnnNFtuummDs8Xll+22morKR/6dYiACBQmoCWYwsh0ggiIAEsuGKKy/IL9h0QEREAEihJQLpiixNpU/95773WTJ09uU+tqVgRaS4CkdAQcm3nmmd3EiRPDp7U9qDURaA8B8hotv/zy7WlcrRYiIBuQQrjaV5mp7HLXxvb1ppZFQAREYGASWGCBBdzLL788MC++u65a2XC75X7wRnnFFVe40aNHd8uQNA4RqCCwyCKLuG233dbtv//+FcdU8P8JkDfn3XffdX/4wx/+f6G+9TmBU045xR133HF9Pg4N4H8EZAOiX4IIiIAIiIAIiEDHCUgB6ThydSgCIiACIiACIiAFRL8BERABERABERCBjhOQAtJx5OpQBERABERABERACoh+AyIgAiIgAiIgAh0nIAWk48jVoQiIgAiIgAiIgAKR6TcgAiLQUQL/+Mc/3FFHHeWOOOIIN//883e0717p7E9/+pObddZZ3cMPPxyGTJ6d73//+xUZhwlg+OqrryaXNd9887nhw4cn+936hXxCv//9793rr7/uFl10Ubf++utnDvWdd95x55xzTuL2/Ze//MXNPvvs7mtf+1pmfRX2FgHNgPTW/dJoRaDnCfAQufDCC90TTzzR89fSjgsgdsjbb7/tvv71r7sllljCHXTQQSHc/c9+9rOK7pZccsmggPzoRz9yzz77rPvmN79ZUafbCq677jq30korOZSQ3Xffvarywbi33357R+yOKN/61rfcuHHj3D333BOLtO1hAlJAevjmaegi0IsENttsM/fWW2+5kSNH9unwL7744j7tP6vzE0880b3yyituxIgRIcEfD9ztttsuVP3Vr37lzj///JLTmCXZa6+9Qlj8Qw891M0555wlx7ttZ++993YoS5deeqnbZptt3NRTV38EnXvuue6pp54quQQSIJ5++unu2GOPlQJbQqY3d6rf/d68Ho1aBESgBwgwjd6X8sc//tEdcMABfTmEir6ffPJJd8YZZ7idd9655BjLLzvuuGPIPrzrrru6CRMmVBwnv0mth3nJCX20w8zHL3/5yzCjMWzYsJqjeO6559xf//rXzNmRaaaZxu25556BSc1GdLDrCUgB6fpbpAGKQP8i8PnnnzsUgEceeSS5MN76mWrnGA/io48+2l1yySVhP1YiV9Ktt97q7rvvPvfGG28E24D99tsveSBPmjQpPMBPPvnk5M2ZftjnE/N/ULbRRhu5f/3rX+7ss88uCZd+7bXXuquuuip22dHtvvvuG2YHUDjKZa211nInnHCC+/jjj92mm25akbiSmYFy4fpI73DYYYeFmRMYpwWet99+uxs/frz7z3/+E+pil8PDv1yw1bjggguC3Q71i8prr70WZjwWXHDBZEanWhtkWGbZqVbI9HXWWSfcv2uuuaZaMyrvAQJSQHrgJmmIItBfCDz99NNu8803dzxQ//znP4fLwuZh2WWXDfYAp556qmMZ4qGHHnJbbbVV8hDC0JLzWJo4/vjjw0PssccecyyjfOc733FXX321m2eeecISxB577BHOp/E111zT/fOf/3SUYSOBsGzB0saXvvQl941vfMORnCzKbrvtVjEDEY+1c4vSddNNN4Xrq9YPNiDkmEEZYBmLB3U1gc2qq64ajFaZNXn//ffd4osvHnhxznvvvee23HJL993vfjfY4+ywww7uwQcfdGeeeaZbY401Qh6b2DYKG0rM0ksv7RZbbDG38cYbO9osIjfffHMYA7mEWILBWBZl5OCDD664DpQgbEO+8pWv1OyC60NRlfQwAS/pCgL21uPtbaUrxqJBiEA1AgsvvLA/5phjqh3OVf744497+5PpzzrrrKS+zWSEsjvuuCMpW2aZZbwpJsn+xIkTQ50f/OAHSdnkyZP9HHPM4c2bxtsD2duDPNQ577zzkjrXX399KLPZk6TMHqLeFI9kP34xxcfbDEvcbXhrypM3z47c5//mN78JYzQPoYpz4H355ZeH8ilTpvgVVlgh1N1pp52SuqZQJd9tlsSbMao/5JBDkjK+2IPfTz/99N7sKkK5GYGGdkxJC+wojKxMKQx1bBbFmzGs//e//x32+cdsUsJ5prAkZfW+mDFpOMdsWEJVrsOWwEKZKYfJ6XfddZc3ZSfZ59hcc82V7Ke/2IyZt5kfz/XmFZsJ86ao5q2ueu0lMEkzID2sPGroItCLBJh5KJcZZ5wxFKW9OHhjj8smHPzyl78c6iy11FJhyz/2cHK8vTND8sILLyTleb5kLXWsuOKKYeYgz/mtrPPMM8+E5uaee+6azcKOZQfqZRmlcvItt9wSZnvwNEnL9773PffJJ58khqwzzDBDMHQdOnRosC+hLsyRyP2yyy4L3ir77LNPmPVg5sOUPsc5phCGunn+wfNpuummC7Na1Oc6jjzyyDCjctppp4U+mKXBwPTAAw/M06T76le/6lhGKjKOXA2rUscIVC4cdqxrdSQCIiAC1QlgbGgvYNUrfHGEOBIInjU8lPJKlgKS99xW12PsjAeloJ6wfMGSE8tLKAS44qaFZS5k5plnThe71VZbLexHZafk4Bc7MEcid7xQWNrCOLYZ4b7wSduqYDSLwsd4nn/++WDjsvzyyzubhUm6+vvf/+5stiQoXYMGDQpLd/FgvD6Uz6g4xWPa9gYBKSC9cZ80ShEQgSoEXnrppXCEuBkErsor3aSAMPPDQ//DDz+sUByyrmeVVVZxzBz85Cc/CUapcQaJuoMHDw6nYNMRlQ4KsLlgFgIbmLyCQvK3v/0t2GlwbqOCkogtCTMr6SBizKQg2HughGEUm5YPPvggGMhi/0JMFGyHomDHgqRteOIxbXuDgJZgeuM+aZQiIAJVCNx5553BiJVlifiGzVtzLUH5+Oyzz2pV6eixOIvx5ptvVvSLsSneL+WCa67ZgQSjVB7UUZhVQMqDdWHoSlsrr7xyrFp3++1vfzsoRSz3pIXlEgxW8wrGswjGxWlhtoZouCglN9xwQ1hKY0YjfnBJNhufsI8HVFrweuI+LrTQQulife8hAlJAeuhmaagi0B8IxIcp0T6j4KmCYKMQhePUjcsBsTwdQRX3Ttx5o8smb9pDLCaGGW06ZkbwfIlutcSVwM0XYVkBWwbCwjP9z8wDwgMPL41OixnchmBi6WuLY+Bh/OKLL8bdki1eQ3gBpQWlgQc+Cki05eA47st4oaC4IGZYGtiWM+cYUUoRPI+YYSDYGd5HLJdceeWVoQ28aKLQ5nrrrRfco2NZeovSw5guuuii5H5iv0EoeYKKNTIbBRO8ePIsW6XHou9dRMD+c0u6gID9B5QXTBfcBw2hNoFmvWDwMjEX0uD9YG/93t56PZ4PeFrYn0WPt4S92XozfvSzzDJLKMMrAg8Xyqmz+uqrB0+M/fffP3jJmD1EyaDxgDF7AW82An6LLbbwd999d/CSMddOb8sJoa4tBwQPCurZQzw5H28SU2C8PRyTska+FPWCoQ8zyvScF8UUj+ApMtNMM/nZZpvNc714rpQLnkBmmFtSTD2zD/G2bOHtoe9hMmrUKG8KSaiHV4stawSeNnPk8XoxZc5vsskmocyUGG/5aEJdm6XwptiFcvhz38yotKQ/W0oJxy1WSUl5egemZszqTanxtnzk8WayOCzpKhXfLXJqphcMni8wsSWbinNqFcgLphadjh+bhDYq6QICUkC64CZoCHUJNKuA1O2gRoWogFjsB28zFh6XVZvRyDyDB7DNqoRj9obvbbmlop4tIyR14kHcQ3m4NSuNKCCMmQc9ikBRscBsmadwjffff7+3IGSZx4sU2oyDt1mlzFPgRhgBSzCXeTxdCF8zLs28J+l6tb7bLIy3YHK1qmQekwKSiaWvCuWG20WTURqKCIhATgI2KxDW/qtN3TMtHwNZYTyZFaYcr4xYJ3aLe6jFyoi7Hd0yZvKfkNMlLhXlHUC1HDBcIwarrcg6jBFr2oA0PTaWyjB6ZRmmnsDXFNnMe1LvXI6zrGZxUxwuwpLeJiAvmN6+f8noWc/Fypx13rgenhwcYF9I803Mg6Jrw1jVE0OhXPgjTrwJ1s9tWaD8sPY7RIBw4QgGkP1Vhg8fHuxesLkgb0qW4tSN1/7www87C5iWGAG3a4zY9ZANl7Dwac+fdvWndttLQEao7eXbsdZ5cOKqhvHdQJUbb7zRLbfcciFUtE1nF8ZAnAHiCRAeGkPE3/72t8FrAONF8pTw9kcG13JL/sId6YTCBDA4ZGYAIQbGhRdeWGKwWrjBLj5h3XXXdQT+wkizV4TcLJ1QCJg9wZA1uhr3Ch+NM5uAFJBsLj1XSm4IC9Hc9jeQdoNpNEU61v5k2MQLolFhOh8PAnJhIFj521p+iMzIuHAZJBonsQhIWtbLQsyFrNmebr2meeedN8S9YJaKHDJmLBliWnTreJsdFy7FfbUU1OzY23k+3kvVlt3a2a/abg8BKSDt4donrTJd2ytTtlmAWEJqNEU6sxN8cMFsVqots/AQZO2ZBGYofL26Bk38C2Z4mFXoFeFhzAxV+qMHUa/cPY1TBLIJyAYkm0tPlL777rvud7/7XXiQsPRgpswVbwcPPPBAmKomi+Wvf/3r8HbPTAlCfgb88FlbJw4BPvXpP+rEHyAsMrERzJUxpEInDLQlo6qYbq3WFsGCyF1BACSmlolmiKJBtk6E1OIoDpSRIp3+SZHOw36DDTYIdVr1D3ElMPLbdtttg01HI+1ipHjOOeeE2SbWoc3NMzTDmzkKyS677OLI/GkJ19wvfvGLZEaqGh9OZqqdFOfMrmBngg0L8Sl4y49BpeJYSbFO1lTiMRCfgXsWI0HmYY0ty5gxY5wlfQuZY+G94YYbhrgYsQ9tRUAERKAjBPrK/0b9lhKwB0GhOCBmCe4tb4I3BSPESMCf3h6OwY2Plu3t1ptFevDNx98flzXiCeDnj5BlcvTo0d6CMAWffuIf2NKDt4d0OH7ppZd6C9nsbV3Xk3XTHtpJe2TjxLUxSr22cJmzH3OIRRDPOfzww0NZzFBqdhbe0muHzKamjHj2GxFiJdCXKWcVp5vyEY6l4z5UVLICroc2qmUnJiaFvZF7UxgCe+IswJbMnMQ3IIYC55uSFZqvxQf3SFPCQn1TBEKsBlNiQsZO2jMFMxnio48+6m2ZyRP3wiJmejNSDLEuTLFM6tRjjVtm5ECMBVib8pScX+9LX7rh1htbNx1vxA23m8bfX8ciN9yuurOKA9Itt6OoAmJvxp4HSBTiIRDMiTgCUfC150FIWnOCAPHQsrV/zwOLIE88jKIQoIm6Y8eOjUXhO+MixXkUM9AM9Sw0cyjK01azKdJj33m2tRQQgi+R9jzGh6jWXj0FhPNQ2OA1YcKE0IzNKoR9m+0J+zZDEbZ5+ORJM0/shDwp1vOwRpFh7DE1ehhozn9stiWcy/n61GZgy6Fi1IW/EwKYSbqCwCQtwdhf0V4Tcl/Ygy/xCmD8TKWTSdIeLsnlsIyBWARER1Ipciog9hbgSH6Fe2kUjDfJqWAzHyHzJXYQLAmQW4Nlkyj77bdfcIMjzDOJsPK0Fc/Ns+U62iVcT6vCbOP2jNAmElmzjITEtPJ5+MQ2stLM49pImnmWXIh/kJViHW8dUyZCNtHQec5/GmHN74FlJ5aHJNUJkFae3wj/XyTdQ4DlS5ZIJd1BQApId9yHQqOI9hMxgVU8ufyBEg1SY4pt6pneGx5mBCcqFzJn8rDjQRftRMrrEACKoEZ4UeRtKz5gy9vK2i+/hqw6fV1GHApsNAhihW0NElnHLWV5+WADkyXRowfWzaRYz2qbskZY81vC28jCaFdrVuVGgMRq2GiJU3f9HF5//fVgy9Zdoxq4o5EXTA/e+5i4i1mQcqn3UOE46bhJ4FWeDRQDSKRWum4iHpLEi9TnzbZVPnb2640/65xOl8UsowQ7Sysc5eNolk86zXyMe0C0ybQ0kmI9nt8LrONYtRUBEeh/BKSA9OA95Q0UYSmmEcGzAm8KAmylBU8NQjqjXFQTHoCkOl9//fVDlTxtMW2P9FqK9DDosn/MrsZZwrSwXFWeorysatjNwyfrPMrSaeZpB4nKT9ixf8pTrOdhHRWPcgU0tqmtCIiACHSCgBSQTlBucR+4TWJjcMkllyQPJKYWcZXFdRYXUFw7Y4rxdNpzhkL6a9xJOT8KuSdQLjiWXrKhHewPohCFcvXVV08UkDxtsZQwpIkU6bHvPFvcYZEsZYcAViwt3XXXXaFOtX/MgygcSkdThQPuxLi9wg5XWTNmS5qIrN95552kjC95+MQT0qnYy9PM502xnoc1wZwQ7jfLRPxeJCIgAiLQaQKyAek08Rb0x1suhlTmRhuUAWYsME4kFggPYGJ/8JZLLgnEXDND8idiVJCYi0BaxIEg0idLCGuuuWYIb00I8m222aZkhBw/88wzQ9wPcxkNSo2l7k7q5GmLsRx00EGO/BbYrRDfw1x7Q+wPlnPMCyREMGW9nBgbyy67rDviiCPcbrvtlvRT74tlAw1xOFASEIz/zKMnxB6J57KkYSnGQ3/mchyLky1r9scff3xgQ+G+++4bwrHzHW4Y8RLbozwOCgagMTIqjKkTbWjy8KF9hDgezK4wC3XbbbcFBXHttdf+30H7lxkXSzEfEn6ZB1RQMjGqI4ZIjJqZlzXtWop2Z27YztyIkz70RQREQAQ6RWAqewPCVUzSxwR40JPHBaWiiGCgiGEohp5Y3fOAyivc+ueeey4sx7Csw5t9WlASCLZlMT8cygdeM9WihNZri3aZlSAgGcabbJlpKbeh+OCDD0JZeZbS9Lia+Y79TLVraKbdeufW4oMSxqyEpZl3u+++u0OZYsYoLpWUtw2jp556KgRwq5bltB5rxsOsGYHligh2QgRyM3fnIqcNuLpbb711MEJNK+sDDkIXXjA5nUjWyW9f0ucEJmsGpM/vQXMDiK61tFJE+aA+Dzje0PNIjLZZrW6etshOGzPUMqOQJWnXYGYT6smOO+7o0u6r9er3hfLBmPLwoR7K5ELmDl1LYJTlxZQ+px5rxlNU+Ui3r+/tJcBMHcbgZJlFuF/f//73K/LfEMmYZdco3FMy6na7sLzJMiaKAMuG0aasfNwsaTIrGhVe7NRmn332oHyX19V+7xGQAtJ796xjIyZEO7YPRWdWWjVAlobqSVoBq1e3W48PhDTz3cq+G8fFrAkKOkuR2BYRcwW3b2YkzzrrrJIhs6RJdmay5x5yyCEuvWRXUrGLdq677roQw4jZPj7ls6DpobIkia1SVEAsAGBYmiUWTS8oWulr0fcMAjYVK+kCAvaGUzX0d18Mj1DsljckRHIkNHijodH7Yuy91KfFXQkRZ+2/Zohka0tenqin3Sp9HYo9HXa+1YyIFGy2VS1pttFQ7CeccII/44wzSsZgS3NJRFWz2yk5xg5RkEkFYF5NFce6rcDswEJ6BzN8rjs0m/nwtuQX/g6lK9tLkR85cqTP00b6PL4rFHs5kT7dnyQvmAylTEUuTIkSkAyjVmwT8i7ViF0xAkRQtfwxgfNASDNfjE5pbctb03C25NKWKve6IUMwLtWmfITkj+kRsvzCUiPG57vuumuIglx+fIjZDNWaSUjX76vvzHxgGI8dRgwlUG0s2KYRJiBraQbbsT333DMwqXa+ynuDgJZgeuM+dXyUaVuMjnc+gDrEeyV6sPTXy242g2+tbMn1MjY3myG4FRmU895XvK5IFYDCUS5rrbVWSInw85//PGSQRlmde+65k2ox/ktSYF9qcacey6sodSguK6+8smPpx3JCuR/+8IfBLiPdFrYat9xyS7A3saSRhZd6cCvHw47AeXiR1RIM1PGaw7vs0EMPzay6zjrrhOUbvN7IqC3pTQKaAenN+6ZRi0BPECBtAA8sbBp4eyeM/eKLL+4uvvjiMH68f3A7tgSAwZaBQmx/8FaijFk4BINM1v/x1GI2DqNoSywYynDvxmCZuDbENMF9GzdrHmR52sdjaMSIEaEfjDhp37JAh33e2g844IDgyh4K2vQPsx+4VMdxZHVjWa0d3jUoA5tttlm4vqx6lNXjzswmbvjEtbnwwgvdDjvsEGwtcLmHHS7pUVBSDjvsMLf00kuH1AMbb7xxuJfxeJ4tYQO493hRoWTBGWUE13/uU1pwwcc2pJ4nHL8rZmclPUygT1eA1HlCoNtsQJKB6YsIpAgUsQFpZQZfhmAPPk823rSQvZn/O2QBjlKesZlj9ifap+0nrr/++lB26623htOqZQg2A+xcGZRj33Fb1AaELM2M0YxNYxPJ1hISenPRD/umLHmLMRPqmlFqUofszFHycjdPlNCOKXzelIBweuRisyFh32ZRgm0SHKLYDEY4z4xDY1HdrRmThnNiBmauwxS7UEb26SgWJNCbshN3PcewRcsSW8rxNvNTyGZKNiBZJPusTDYgPaw7augi0NUEmLKvlsGX2DJMsReV8uUJ4t+w/FCesZmy8rD1efrKap839npv43narlUnRhtOL6tk1WcGiGUH6hGYLothXu64anO9Q4cODQzpj9kp5OWXXw7byy67zOEyi5cNM1h8iFvDOQQQzCu4zzILZopZOIXrOPLII8OMCjZQ9MEMCVmEDzzwwFzNskzMMlKRceRqWJU6RkA2IB1DrY5EYGAR6KsMvumMzUWJlysgRc9vtD4BBek7xsmp1Q7LF6REYKkKhaA8K3Yz3GMaBnsnDkMg4B3LWBjHNiMoC3zStirYnpDjCOWLiLzmAeSWX355Z7MwSVfkXmKJDKVr0KBBDluYKDHuEXZAUXGKx7TtDQJSQHrjPmmUItBzBNIZfFdbbbVk/Kz98zZcK+tyUrnsSx4FIWZsJltxUcnTftE289QntxMPfeJ+xAdrrfMIRMfMwU9+8pNghBltVjinldxRSDBMxU6De9aoEGwMWxJmVjAqjsJMCsIME0rY7bffHg+FLVF/iZOD/QuzXGkFJOZ9qhcksaRB7XQVgam7ajQajAiIQL8h0MoMvkBBOciTwZfAVbw1RxfO+NZNWTWJikee9qu10Ux5nMWwWCQVzfDwR6kqF1xzCU6GUSoP6ih5ucf6tbYkQUQpKs/8zHIJBqt5BeNZhKBpaWG2hnQCKCU33HBD8LJhRiN+dt5555CDiX2z10mfGnIncd/qRQ4uOUk7XUVACkhX3Q4NRgT6D4FWZvCFCksB2B8QFZQp+5iBGDuAaENBvfKMzc1kCM6bQZl+m5FlllkmhOFPZ0SO7fHwffGLDM2xLG5PPfVU953vfCeJLQ79AABAAElEQVTuhm1e7kQ4ZtYFe5woMXM2NhnI5ptvHjyO8DQiUSOcSW6J8oMXTRT211tvvZDHKJalt7j5ooRcZIkP4/IO941Q8mSMjgpg+px632GCF0+eZat6bel4HxGwH4OkCwjYf8CuioTaBUg0hC4kUMQLhuHjaWF2Ct6mz709fIInyqhRo7xNxZdcHR4qtsbvbfnBW5htf/fdd3t7M/bmjultCSDUtSn84PVAPXvwhjJbgvC2TOB/+tOfessQ7C2Ghbdsy97ceAu3b2HMg1cGXiGWOTmcb8pM8LI599xzS9qrt1PUC4b2zCjTc14UUzyCpwhRTmebbTZv4cgDz3g8bk0p85YPKe6GbT3ueLXYska4XjNo9Xi9WKwOb2HfQ5kpMd7y0YS2bJbCmxIXyu0x5W22xptRaUl/tpQSjhPJtZqYwuHNmNWbUuNt+chb9mt/9tlnV6seyrmnWV4wePrAxJZsap5fflBeMOVE+nR/EtqopAsISAHpgpugIdQlUFQBiQ3alL2///77vWVVjkUVWx6aUXGwt/LM0OK0E+vQAAqI2SaEtlBqbCmiot1YUK99Qprz0C+XWm2W1437jSggjI8HPYpAUbEMypmn5OGeeWJGoc04JIpZ+WHcaq+44gpvCebKD1XsozyYcWnm/a2oXKXAZmH8RhttVOVo9WIpINXZ9MERueH20cSTuhWBAUUADwgMJ1nvryZMpUd3Vwwes0KL006sU94Oxoi1sh3Xa59lADxMyqVWm+V1m9lnfDbTEqJ/mjJUqCmCuWVJHu5Z52WVYTycNiBN18FGBdsblmHqCZF/TZHNvL/1zuU4rt0EocNFWNLbBGQD0tv3T6MXgQFNIJ2xuT+AIMPr6NGjHTYXRZWQvrz+hx9+2FnAtBI323aMx5bG3Lhx45wlbUyi1bajH7XZGQJSQDrDWb2IgAi0mABvwbfddlswaiSPikUzbXEPfdPcuuuuGwJ/YaTZK0JulrQrcLvGzewJhqzR1bhd/ajdzhBQHJDOcFYvIiACLSaAm60ZtCatEl2zv0i9iKj95TqLXgeeUJL+Q0AKSP+5l7oSERhQBLBvkIiACPQuAS3B9O6908hFQAREQAREoGcJSAHp2VungYuACIiACIhA7xKYCt/f3h1+/xl5TMykvAb95572xyu5+eab3ZAhQ0IW0/54fa26JrxCiDBaHqW0Ve2rncYIkNzOYqaE8PWNtaCzWkhgshSQFtJspqk99tjDWQCiZprQuSLQUQKPPfaYwythscUW62i/6kwEmiFA3p1DDjmkmSZ0bmsISAFpDUe1IgIDj8DIkSNDfhZiMkhEQAREoCCBybIBKUhM1UVABERABERABJonIAWkeYZqQQREQAREQAREoCABKSAFgam6CIiACIiACIhA8wSkgDTPUC2IgAiIgAiIgAgUJCAFpCAwVRcBERABERABEWiegBSQ5hmqBREQAREQAREQgYIEpIAUBKbqIiACIiACIiACzROQAtI8Q7UgAiIgAiIgAiJQkIAUkILAVF0EREAEREAERKB5AlJAmmeoFkRABERABERABAoSkAJSEJiqi4AIiIAIiIAINE9ACkjzDNWCCIiACIiACIhAQQJSQAoCU3UREAEREAEREIHmCUgBaZ6hWhABERABERABEShIQApIQWCqLgIiIAIiIAIi0DwBKSDNM1QLIiACIiACIiACBQlIASkITNVFQAREQAREQASaJyAFpHmGakEEREAEREAERKAgASkgBYGpugiIgAiIgAiIQPMEpIA0z1AtiIAIiIAIiIAIFCQgBaQgMFUXAREQAREQARFonoAUkOYZqgUREAEREAEREIGCBKSAFASm6iIgAiIgAiIgAs0TkALSPEO1IAIiIAIiIAIiUJCAFJCCwFRdBERABERABESgeQJSQJpnqBZEQAREQAREQAQKEpACUhCYqouACIiACIiACDRPQApI8wzVggiIgAiIgAiIQEECUkAKAlN1ERABERABERCB5glIAWmeoVoQAREQAREQAREoSEAKSEFgqi4CIiACIiACItA8ASkgzTNUCyIgAiIgAiIgAgUJSAEpCEzVRUAEREAEREAEmicwlTdpvhm1IAIi0J8JjB8/3o0aNcp99tlnyWV+/vnnbqqppgqfWDjddNO5CRMmuGHDhsUibUVABEQgi8DkabNKVSYCIiACaQJDhgxxH3/8cbqo6vf555+/6jEdEAEREIFIQEswkYS2IiACVQkMHTrULbXUUiWzHeWVp5lmGjdixAg366yzlh/SvgiIgAhUEJACUoFEBSIgAlkEtt56azf11NX/ZLAkM3bs2KxTVSYCIiACFQRkA1KBRAUiIAJZBCZNmuTmm28+V81sbIYZZnDvvPOOm2mmmbJOV5kIiIAIpAlMrv46k66m7yIgAgOewDzzzOOGDx+eOQsy7bTTuk022UTKx4D/lQiACOQnIAUkPyvVFIEBT2DLLbfMZPDf//5Xyy+ZZFQoAiJQjYCWYKqRUbkIiEAFgffff9/NMcccDoUjLbPMMot7++23HW64EhEQARHIQUBLMDkgqYoIiMAXBAYNGhQ8XfB4iYLSscUWW0j5iEC0FQERyEVASzC5MKmSCIhAJMAyDB4vUT799FM3ZsyYuKutCIiACOQioCWYXJhUSQREIBL46KOP3ODBg92UKVNC0VxzzeXwkCEqqkQEREAEchLQEkxOUKomAiLwBYEZZ5zRbbrppg7PF5ZfttpqKykf+nWIgAgUJqAlmMLIdIIIiABLLhiisvyC/YdEBERABIoSUC6YosS6sP4///lPd/vtt5esy3fhMDWkfkSApHQEHJt55pndxIkTw6cfXZ4upYsJYAC93nrrOQLfSXqbgGxAevv+hdGfeeaZbtddd+0HV6JLEAEREIH6BK655poQ+K5+TdXoYgLKhtvFNyf30HgbnXvuuYMhYO6TVHFAEjj99NPdUUcd5SZPnjwgrz/vRf/5z392yy23nHv++efd17/+9bynqV4HCGDszN88Se8TkA1I799DXYEIiIAIiIAI9BwBKSA9d8s0YBEQAREQARHofQJSQHr/HuoKREAEREAERKDnCEgB6blbpgGLgAiIgAiIQO8TkALS+/dQVyACIiACIiACPUdACkjP3TINWAREQAREQAR6n4ACkfX+PdQViEDHCZx44okhENQuu+zS8b57oUOixD788MPu3//+t3vnnXfCkL/5zW+6pZdeumT477//vrv55ptLykaMGOFmnXXWkrJu3HnsscfcPffc46affno3atQoN//881cMk2s/55xz3P77758cu/baaxXDI6ExsL9oBmRg339dvQg0ROCCCy5wF198cUPn9veTPvjgA3f88ce7YcOGuVVXXdU9++yz7kc/+pFbc8013XPPPVdy+V/96lfdN77xDTdu3LgQn2WeeeZxgwYNKqnTbTtvv/2223777YNSsdFGG7mf/OQnmcoH46beKaecUnIJJC/cYYcdQij/kgPaGXAEpIAMuFuuCxaB5glMmDDB/fGPf2y+oSZaeOutt9wtt9zSRAutP/W1115zW265pWNm6Ctf+Yr78pe/7A4//PAwS4BisvHGG7t//etfSccE1VpmmWXc5ptvHj5rrLFGVyf2e/HFF91iiy3mPv74Y3fTTTe5r33ta8m1lH8599xz3VNPPVVe7FZZZRX3/e9/3+24444Vx1QwsAhIARlY91tXKwItIcCDlay4fSVEwmRWgQdiN8mee+4ZlheY2UjLwgsv7L773e+6Z555JmQP9t6nD7vZZput65ddPvnkEzd69Gg3ePBg96tf/apk/OU7zPT89a9/deuvv375obDPMhN1uk2BzBysCttGQApI29CqYRHovwTefPNNxzJMFGweSIg4fvx495///MddccUV7ogjjqhYcnj11VcduYt4AN91111hGp/w8B999FFo6g9/+IM7+eST3XnnnRf2mS0444wzQhltIrx9M2Nwxx13uHvvvdedffbZSRoC7AuuuuqqUK/T/2DzceONN7rNNtusoutpp53WXX755W7o0KHuuuuuC8st6UpTTz2141Muf/nLX8ISBks0t956a+CWrvPKK6+E459//rl78skn3dFHH+0uueSSisSUr7/+erhf3BPuUSNy4IEHukceecTts88+YWanWhtkSD7ooIPccccdV61KKN99993dfvvtVzHWmifpYP8iYH8IJD1O4NRTT/WWC6bHr0LD7wSB0047zdsafMNdmaLhL7zwQm/LC0k77777rv/hD3/IK70fM2aMt5kJ//Of/zwcN5sGb4aIob9LL73Um3Glt5kTv9NOO/ltt93WW1bTcN4KK6zg7Q071FtiiSW8GTQmY7Rsz36WWWbxK6+8cigzw01v0/vhvL333tvbUpB/7733wrH55pvP22xCcm6jX/70pz+F9i0XTO4mbFnBr7POOpn1v/Wtb4XyJ554wlsGYW9LL96UraSuKVHeFLFkny977LGHtxkHzxhMEfG0YUs03mwwQr3rr7/ezzHHHGGcJ510kt9mm228zTiE/WOOOSZp68477/RmcxHauPLKK0P/tkSUHM/7BbamSIV7a/Ys3mbB/GqrreYtb05JE6Z8+Pvvvz+UcQ3Vfm+mFIWx/v73vy85v94OvzNTMutV0/HuJzAJjVrS4wSkgPT4Dezg8JtVQOJQN91005IHi81ghIcJDyZ7Aw7VeEDysEg/aMeOHRsevva2HpvyBx98cKhn0/qhzGYQShQQCs1OIlFA2H/00UfDOeeffz67iTz00EP+vvvuS/Yb/dKIArLIIov4rbbaKrPLqIBw8Oqrrw4MbJnG/+1vfwv1yxWQX//610HpQtmKQl14wjCKzSCEMpsNikWB1bLLLhv2bQbJWzI9b944yfHtttsunPPggw8mZfW+2MxVOGeppZZKFErGg4KJQsVxxGa1/GGHHZY0V0sBoRIK6SGHHJLUz/NFCkgeSj1RZ1LlnJ/dXYkIiIAI1CLwpS99qeTwDDPMEIwnWWJguQFZfPHFw/bll18OW/7BdoTjNsuRlDENTxkunUUFI860rLjiisHzJF3Wie/YR/zjH/9weLHUE1PeHMsZWUap8VyWoXDbTduSLLroom6hhRZyNpPkbFYoVI12ONSNAvfI/LLLLgvLWyyb7LrrruFDJmTu08SJE+MpdbcsBSEY0WIDgjAe3LFxNT7rrLMcLsUsp3FteYXrwy5GMjAJKA7IwLzvumoRaDuBaaaZJvRh72I1+5ppppmCGydeLUWlXAEpen6r6tsyVEgRHxWCeu1ii0EcDWxebNbEYZQZBV48lPEWKRdb8nAvvPBCcO21Zavyw2Ef7pE5XigoRdjRNCNREZp99tlLmrFlsbCPq7HNdrjll1/e2cxXUufvf/+7mzJlirvmmmuCe/Faa62VHOOLzZ447IIkA5OAFJCBed911SLQNQQwKuWt/Hvf+17hMXWLAmI2WOEBm3axrXUxjJuZDGZsMEq15YwwO8E5HCMQGQafePtERY5jtszDJrfHDOfSNoah0003XTi3kX+Y7UDM3qPkdNxwaReXYxRIDJHTwiwPRsk/+9nPwqxXuQJitjvJTFn6PH0fGAS0BDMw7rOuUgS6loDZIoS35OiyyXIMb821JCoePKC7RVhWwjuoXJiN4CFcLmZYG5SPrGUIFBOUGVxZ08JSyJxzzunMriNdXPX7t7/9bffhhx9WuM2yXII3Ul5BwUJBNBubklOY4UC5IeDaDTfcEGYzmNGIn5133tmZoWzYx4snLXjuvPHGG2E5KF2u7wOHgBSQgXOvdaUi0DICzFrwdov7LYIdAA9abCGiEDETiS62sZxz0uv+ZpTpVl999SRmBPEyONe8bcLDky0hvbGx4I0ZibYWKC/0+/jjj4dyHnjEB+kLYXnEvFwqup40aZIjQFmWUkUU1N/85jcVLrjHHnusw84Gl9ooPLC5Xo7FWZFoC1LOnfsDF9yVF1hgAbfXXnuF6KxwN0+YEASMgGlRaJclHYKHVZMTTjjB4fb7wAMPJFUIRkdgsh//+MdJWd4vMOG3sOGGG+Y9RfX6GwH7kUp6nIC8YHr8BnZw+M16wdibvOf3hqur/S30ZtzoTTHwNsUe9nEHx+vFHi5+k002CWX2Fu7xKkEsbLe3h6f/6U9/6nGhxX13gw028LjaRsFzY6WVVgrn2sPNm/2Ax+vG3sCD+22st/baa4c6eN689NJLoRhvkyFDhnjchZuRRrxgcEe22Qlvxp1J17iLDh8+PIxz3XXX9bjEZonF76hww7UYJ+FaLF6Gx1UVDxuz5UhOx+MEDxfug4U896boeDM6Dd4zlB1m3ih4JD399NPellBCPcqXXHLJ4JKbNGRfLKx+OG5h4GuyM7sVD3c8Vxgzbr+401YT7nE1N9xf/vKX3mZOqp1atZxrkBtuVTy9dEBuuL10t6qNVQpINTIqLyfQrAJS3l7RfRQQsxkIp5mnhrdZlKpN2HJGcgw333KxGYHE/TMes1kGb2//cbfhbSMKCJ3hSmzeJg31a8sRFedxjWbg6c0exHNtzYhFjU0Utax24E18ljyCgonC1ahwXcstt5y32ZTCTUgBKYysW0+YJCNU+zVLREAEOk+ApYFagu1AFNx8ywU7EAuOVVJc7h5ccrADOyRZs2BswXajPPNtve6x7SgXrpFlmlbIggsuWLMZllZslqZmnXhw3nnnjV8b2hKyngy50YumoUZ0Us8TkALS87ewNRfA2jBhpDFay/tHqDU9t64V/oDedtttwSqfa6jmplitR+wLsnJTYCRIBk88EDAclDROAGNM1v2xGcEFs78J4dQvuugit9tuu4WMr7il9oJgS8Lv3CKttn24hGi3QGmOeCiSgU1ARqgD+/6Hq7dQzyGfhq3X9qxPvoX+dhbWOxgukofCbAjc//3f/xW6u6RBJ4iTReYMhoy//e1vg4U/ngikFMflcOTIkRWeAIU6GcCVMbZEQbT5YLfvvvs6i2baL2kwC3POOecEpbVXLhDFuhPKBzwskmv49AobjbN9BKSAtI9tz7RMVERbmw/jjVEse2bwNlCCHPHmiaeErXOHJGXEUSAiI54TeYXpbmaA4h9ivAQIEkU7ZqTnzJgvRPIklgFJzyTFCOBmS8AqZppImtaqpYVio+hc7Vqp6js3iu7rqXzZrPtGqBF1ioAUkE6R7vJ+YibOuO3y4ZYMDxdCs6gProkoEWalH9wPmeonmFNRqbbMwro3b/E8OMl4SphrSX4CTPEzyxQ/eaOG5u9BNUVABHqJgGxAeulutXis5N4gJTpTxpbsK7TOAzwtpPHGLoLAQgQb4uEehQc8cQBQWjAmI6w0URfNtTLkiYj1CM6EfQlbZlvoKx1IqVYfsY1aW/JcxLgIsR5v2+SnYCYkCrEliHNgWVgbnh6P0+vYl5COfosttojNu1rXkZcVyxN33313WJ7gmsjxkbbJqdVHMhB9EQEREIEeIKAZkB64Se0YIssKBDn6xS9+ERQGclMgaQUE5cJiCTis+Qk2RCIqElohTKOzREHQKAJFYf3PTATRFVnCIDcGQsRFbDN+8IMfhGBILJfExFYcr9UHx/NI2lsi1idgEsoHtiBRCHl9wAEHhEBMsayRLTymn376cL0oFkit68jLinawXyFJmMV+CEod+1Fq9RHraCsCIiACPUOgWx2ENa78BIrGAbnppptCMKh0DAbSf9uP1pvhZeg4TxrvPCnYiTthUS6TiyFoVZE+khMLfiE4lWUULTmLlOS2hFIS9Kqkwhc7pBCHxRVXXJF1OJQR8Io6EyZM8K1iRWwES/blTdFI+j3qqKPC9zx9JCfV+ML9IA4HY9dHDHr1N6BAZDX+k/fOIcUBsf+AA07GjRsX3ODStg7RZTXOgKTTeEdA6TTezCzkScHOEgJLCli+n3TSSSGdeIwhkKeP2HeRrUWNDKG68YxJC6ngWxWmGzdShDbzXEceVrDHvoTw2XhRbLTRRmHWiH7y9EG9PIL769lnn52n6oCtg/Hyfvvt50xha3i5bsDCa/OFjx49us09qPlOEZANSKdId1E/pAHHiDItUfGIZY2m8Y62GKaEh6bwGCEPBXkkSNONO+s222wTjjXaRxxj1pbkWNhmkO+iXcKyEg8oMoCyNIVdSSMpz8tZMd7TTz89LFex3IW9DUavxCBpJSuWj1gSk1QnELO+snyYtleqfoaOiIAIFCUgG5CixHq8PjYLBIOypYPMK4mKCA/HmMY7s2LOQgxUjz/+eEcmTB7SGIASiAhpVR9xKCgG2KzgMtvOiJgY7yJkB+X6WnkdSy21VLCR2WWXXYKBMAa72NO0so/IS1sREAER6EsCUkD6kn4f9E2cD97aeaMmFXY1aVUa7/PPP9+ZbUPw5CCgF2/1TGsjreqDtlCq8IZhhgV3zyhkIn3uuefibtNbZlgs8VdYSrK8H6G9Vl0HGUwxDGZmxZKOBc8hxo/hbqv6aBqAGhABERCBFhGQAtIikL3UDFEoEcJF89BDQTCDy1B23333hYBeedJ450nBzgP79ttvD23PNNNMwZPGDC3Dfp4+QsU6/1jGz7CkRLuXX355WMZgKQPPHjx1FlpoodAC0+rYutxlrse1hGBmSDqNPDNHKAJ4/TC7gp2JZYQN9fJcRx5WLFuh1MTlK/rimvjk6SMMRv+IgAiIQK8Q6B2DWY20GoGiXjC0Y8si3hQCb8aRISslqbFJsU4mT3OTDV3VSuONR0meFOyk7TZDVI/3Bd4vnBPbp5NafYRB5PiHlO72/y3zQ7r4KFdffbW3JaaSlO7xGFuLpOrN8NDbDERoizTipgSEz6hRo/yPf/zjcB2kpC+XWteRlxVeRbZMFVLUY+XPPYJflFp9xDr1ttyHaunR6507kI43mg13IDHqq2vl/7q8YPqKfkv7nTQVzfWKsqRxZhNgSeOYY45xTNcXEd7q8WyZf/75Q84TfgoYKJbLSy+9FOKDNBJamj5Y9iEIGTMH6eWRdD/N9JFup953km6lvX/q1S96vNnrgBczUtyXaryb6YOZIXPtDe0XvbaBVJ/ZMksX78iTJCPU7rrz2KmZAlJhSN9do9RochCYLC+YHJT6axUUA5QPxGJDVL3Memm8q55oB2JumaxU4+nzsvrAELOe7Ljjjg7DzbzSTuWDMWRdR96xUS/yqqZ8UKfZPmhD0nkCNqsSkh3GZU5GgJs6ge3SgjH1zTffnC5yI0aMKInqW3KwS3ZYlsQwG5fzKAQdZAmx1u851tV24BGQAjLw7nnPXLEFE6s71qwoqHVPUgUR6DAB0hSg5GMHRUoDMjVjo8SM4MMPP1ySuoAy4sHYkp/77LPPgkEy+XO6VUizcOihhzpmjfDYSisgFrAv2JqRsmD48OHdegkaVx8RkALSR+DVbX0CilVRn1Gv1XjrrbfCg4o3+nYILthkMO4mOfHEE8NDOc7oEbzu8MMPd8cee6yzaMTBMBu3eLyfEJYYcL/G8BgFhNQG3Sovv/yyGzZsWFCgYuyU9FiZ0WPZb4MNNggzONSViEAkIC+YSEJbERCBthLgYUok2uhl1OrOyJVDrp9ukieffDLMYOy8884Vw1p44YWDV9UzzzwTlKZyczy8rNLJFCsa6IICllb4DBkypOpoiGGz5557OpZLJSKQJqAZkDQNfRcBEcgkwFr+vffeG+Kt8HaOi3AMWsfyAsaahHgnRorlrQnB4HCPJvgcb/K4e48ZM8bdcccdDnsgzt1www0dS2jjx48PIe0XWWSR4N5MlNlNNtnErbjiimEsedpH+SB0Pe0SZp5w/7x1I9dee63DuLcvZtRweUfpiqzCgL74h9kB3MaXX355R6JEjIMPPvjgpApB7vikBbaWy8mhtCywwALhPrCNwnXCgvNqZaimficzK6+zzjohwSKu7JtuumkcrrYDnQBeMJLeJtCIG25vX7FG3yiBRtxwSc5n+Te8KRnBhZpEfLYs4N9+++1kGEsssYQ3g+Zk37yNvBn8ensIhjIzrAzuz/b31u+9997eHpLeZge8PYyCy7MpIx5XZ1umCK7I9nD2v/vd75L26rVvQe682VZ4U2hC2+xHmW+++YKLedzPs22FG+4TTzwRrs2MTjO7hCNCPVPegou4KVtJXVOkvC1fJPuPPvqotyUMjzu5eZV5XOc5j0SSiNlfBBduGJuy503x8ZYPKbhd496Nm3mUO++801sG63A/LW1BaAf2jcr+++8frpUxVBObAfGmvFY7nLuc65Mbbm5c3VxxEkGPJD1OQApIj9/ADg6/qALCww1FAgUiioXoDw8bSzAYi7zlFipRQDjAwyYqIOzzAOXhYdFx2Q0yceLEUGazE7HImwtyUCRQaGwWJZTnad/y53ibDUjaiV8eeughX00JiHXKt61QQMi8zPWSATpLogLCsRijxgxQPXyRtAJiM0ghnk46Lgx1UDLMdd5bZGN2fZ4M1a3KrBw6/OKfPAqIRSn2KJZcSzMiBaQZel117qTS+T27sxIREAERiAROPvnk4Cqajt+y6KKLhuiyl156qSOuSlFJL0dgkImkXalJvmdv5+7VV191L7zwQqHm023HE1nKwfOk08IyCTL33HPX7ZpliQMPPDAxSmWpJS233HKLe/bZZx1ZqNOC2+snn3ziSHmA5Mm6nM6sbIEHHZ90put0+638zm+IJSJTOlvZrNrqYQKyAenhm6ehi0A7Cdi7UrA1WGWVVSq6WW211YJywEOR8PZFJEtJKD8fJQfBawbbkLySp+28bTVbj7EznrRbaq02ccslUzU2L3jypD2FLApuOBU7m7RwH5Co7KSPxe8YgSLcT6SVmZVDgzn/iWNHsVx88cVznqVq/ZmAZkD6893VtYlAEwR4eOKF8cgjjwR30HRTUSloxEsjj5JAtFekaBTSPG2nr6Od3wkyxkP/ww8/zNUNY2dWifMwSiWxYpTBgweHrw8++GAsCluC0hFfpMh96KvMyu+9914Yc9potuRitDPgCEgBGXC3XBcsAvkJsHzBcgCZjNOCVwzeLFFBwKNjypQp6SoV36NygDtuPTEjSbfssssmyxd528/Tdr2+W3V8ySWXDE2RhqBcUEzI4FwuROpF+WC5Ij2rET2C7rnnnpJTcPPF2wiPl7zSV5mVSRXBbyAmh8w7XtXrvwSkgPTfe6srE4GmCRAsixw+l1xySdIWuWp4E+dYnN7HLde8YtyFF14Y3vjZmteFw6U2vvnikotwLg/gxx9/PGnTPEGS76+99lqYdTnuuOOSsrztY8tAn7gFx5kHYnDgCttpwV2ZyKfpa4tj4GHMdWYpbURBNQPWEhdclIatt97aoYAQ/CsKYd2ZjYoxNvJkXc6bWZk211tvPffGG2/E7qpu4z3Oup54EvFfuI95l6Tiedr2YwL2h0DS4wTkBdPjN7CDwy/qBcPQLP6HHzJkiN9999295fvwZp/gzzjjjJJR41lhBpLB62OxxRbzFu8huNiakWRJ9uG111471LEw+96WWbw9iMP+6quv7rfbbjuPN4XNfASvkHQHedrHtRcvCwtb7vk/EQVvE8ZvBpCxqO62FV4wdHLkkUcGXukOcSG1sOThutddd12PS2yWHH300SVuuHi4kK0al+SLLrrIn3feecF12RSScHrerMtUzpNZeejQoWGMJ5xwQtbwQhkeSyeddJK32bBQl9/GbbfdVlEfzxeybd9+++0Vx4oW2ONYbrhFoXVnfbnhdud9KTYqKSDFeA3k2o0oIPCyWQ9vBqfe7EG8veVWRUh8iig8MMuFdswIMSmOCggPW5uxCC6r1Kkm9drHXZgYJGlhvEVdP1ulgMDADGq9zXakh5T7u80+VNTlGu+//37/yiuvVBwrWmCzEkERzDoPbldccUVQOrOOFykj1ogFiityStW6UkCqoum1A3LD7ceTW7o0EWgZAdbuWRogRT1LMtUknRwwa6qddiwwWObpLFdgH0CdalKvfWwnYk6V2AbjtVgZcbejWxice+65IVkbS1dFJSuLNNeIZ1LMZF20zXR9jFirZao1pS0sl7EM04zgKcWSEu6/EhFIE5ANSJqGvouACHSUQDTEtLf6jvbbyc7IAmuRZN1ee+3lGlFCOjnWdF9k6T3mmGMcBsCNCt5M48aNcxdccIGbccYZG21G5/VTAo3/svopEF2WCIhAZwhglEgad8QigTqzHQn5YvpqtqKdV222HiFrLIG4euX6yN/SrHCtZq9Sc1ar2T50fu8SkALSu/dOIxeBniZAwjizSQmfeCHEtOivkician+79uj51N+uS9fTGgJSQFrDUa2IgAgUJMDbca/MBhS8NFUXARHIQUA2IDkgqYoIiIAIiIAIiEBrCUgBaS1PtSYCIiACIiACIpCDgJZgckDqhSp4EWBpLxGBWgTIRKrfSi1C/zsWI3v+9Kc/dTGJWv2zVEMERKAIgamIXFLkBNXtPgJk0MRdTrey++5Nfx4RvztsOPBekYhApwgQ/p+/d8op0ynibetnshSQtrFVwyLQvwmMHDnS4eVAjAeJCIiACBQkMFk2IAWJqboIiIAIiIAIiEDzBKSANM9QLYiACIiACIiACBQkIAWkIDBVFwEREAEREAERaJ6AFJDmGaoFERABERABERCBggSkgBQEpuoiIAIiIAIiIALNE5AC0jxDtSACIiACIiACIlCQgBSQgsBUXQREQAREQAREoHkCUkCaZ6gWREAEREAEREAEChKQAlIQmKqLgAiIgAiIgAg0T0AKSPMM1YIIiIAIiIAIiEBBAlJACgJTdREQAREQAREQgeYJSAFpnqFaEAEREAEREAERKEhACkhBYKouAiIgAiIgAiLQPAEpIM0zVAsiIAIiIAIiIAIFCUgBKQhM1UVABERABERABJonIAWkeYZqQQREQAREQAREoCABKSAFgam6CIiACIiACIhA8wSkgDTPUC2IgAiIgAiIgAgUJCAFpCAwVRcBERABERABEWiegBSQ5hmqBREQAREQAREQgYIEpIAUBKbqIiACIiACIiACzROQAtI8Q7UgAiIgAiIgAiJQkIAUkILAVF0EREAEREAERKB5AlJAmmeoFkRABERABERABAoSkAJSEJiqi4AIiIAIiIAINE9ACkjzDNWCCIiACIiACIhAQQJSQAoCU3UREAEREAEREIHmCUgBaZ6hWhABERABERABEShIQApIQWCqLgIiIAIiIAIi0DwBKSDNM1QLIiACIiACIiACBQlIASkITNVFQAREQAREQASaJyAFpHmGakEEREAEREAERKAgASkgBYGpugiIgAiIgAiIQPMEpvImzTejFkRABPozgfHjx7tRo0a5zz77LLnMzz//3E011VThEwunm246N2HCBDds2LBYpK0IiIAIZBGYPG1WqcpEQAREIE1gyJAh7uOPP04XVf0+//zzVz2mAyIgAiIQCWgJJpLQVgREoCqBoUOHuqWWWqpktqO88jTTTONGjBjhZp111vJD2hcBERCBCgJSQCqQqEAERCCLwNZbb+2mnrr6nwyWZMaOHZt1qspEQAREoIKAbEAqkKhABEQgi8CkSZPcfPPN56qZjc0wwwzunXfecTPNNFPW6SoTAREQgTSBydVfZ9LV9F0ERGDAE5hnnnnc8OHDM2dBpp12WrfJJptI+RjwvxIBEIH8BKSA5GelmiIw4AlsueWWmQz++9//avklk4wKRUAEqhHQEkw1MioXARGoIPD++++7OeaYw6FwpGWWWWZxb7/9tsMNVyICIiACOQhoCSYHJFURARH4gsCgQYOCpwseL1FQOrbYYgspHxGItiIgArkIaAkmFyZVEgERiARYhsHjJcqnn37qxowZE3e1FQEREIFcBLQEkwuTKomACEQCH330kRs8eLCbMmVKKJprrrkcHjJERZWIgAiIQE4CWoLJCUrVREAEviAw44wzuk033dTh+cLyy1ZbbSXlQ78OERCBwgS0BFMYmU4QARFgyQVDVJZfsP+QiIAIiEBRAsoFU5RYgfp//vOf3T/+8Y8CZ6iqCPQGAZLSEXBs5plndhMnTgyf3hi5RikC+QksscQSbvHFF89/gmoWIiAbkEK4ilVeeOGF3fPPP1/sJNUWAREQARHoCgLf+c533L333tsVY+mHg1A23HbeVN4S/+///s/tvffe7exGbYtAzxJgKec///mPu/baa3v2Gjox8DPOOMMdccQR7o033uhEd+rDCOy5557uwQcfFIs2EpANSBvhqmkREAEREAEREIFsAlJAsrmoVAREQAREQAREoI0EpIC0Ea6aFgEREAEREAERyCYgBSSbi0pFQAREQAREQATaSEAKSBvhqmkREAEREAEREIFsAlJAsrmoVAREQAREQAREoI0EFIisjXDVtAiIQPsJEOzvqKOOCm6q888/f/s77MEe/vSnP4WAWvfdd5975513whV885vfdEsvvXTJ1bz//vvu5ptvLikbMWKEm3XWWUvKum3n97//vfve977nZphhhmRof/nLX9zss8/uvva1ryVl+tJdBDQD0l33Q6MRAREoSIAHzYUXXuieeOKJgmcOjOp/+MMf3Ntvvx0i16666qru2WefdT/60Y/cmmuu6Z577rkSCF/96lfdN77xDTdu3Lig1M0zzzxu0KBBJXW6aefGG290yy23nNt4440dSRLT8q1vfStcxz333JMu1vcuIiAFpItuhoYiAiJQnMBmm23m3nrrLTdy5MjiJ7fwDMZwyy23tLDF5ps68cQT3SuvvOKYxUC+/OUvu8MPP9xNP/307oMPPggP7n/9619JR2Q0XmaZZdzmm28ePmussUbXJhp8+eWX3bBhw9yiiy6ajD/9hWSJp59+ujv22GOlnKbBdNF3KSBddDM0FBEQgcYIMNXel0LUY2YVXnzxxb4cRknfTz75pCOC6s4771xSzg5pIr773e+6Z555JmQz9t6X1Jltttm6ftmFpRU+Q4YMKRl7emeaaaYJEU133HHHdLG+dwkB2YB0yY3QMERABBoj8Pnnn7u77747JMZbfvnlQyNk6v3jH//opp56arfyyis7liH+9re/uR/+8IfJGzN1xo8fH2YFFllkEYcdAfYkm2yyiVtxxRVDO5xHPieS7m2//faO2YKLL744ZAFmeYKZgo8//tgRUv6OO+5wc845Z5gx2HDDDR3HCTFPPz/4wQ8au7gmztp3332DUsSsRrkwO3D55Zc7eF133XVhueXggw9OqsGNT7mw3EVuFMLnM1OCEhPbz8M8tvf666+H2aJXX33VsSy09tprx0Mt366zzjpu9913d9dcc43bdNNNW96+GmycQOUvrPG2dKYIiIAIdJTA008/HZSAtdZay5F9GnnvvffclltuGR6O2IbssMMOIafHmWee6dawJYV3333X8eBDeWBp4vjjj3fbbbede+yxx4JyQQKyq6++OrS1wQYbuPPOOy8sW1Dwla98JcwYHHrooe6UU04JdaZMmZIsccw333zBhmLGGWcMx3bbbbfMGYhwsI3/MPtx0003JePK6grDUpQPlCuu54YbbsiqlpSRG+W4445zMIHbPvvs4+COUWse5rEhFMPDDjssGMAutthiYRlo1113jYfbskXJOfroo9vSthptgoBNvUnaRMCmBr0lo2tT62pWBHqfgC1beDMgbOpCHn/8cdYP/FlnnZW0YwaJocwMLf2nn34ayq+//vpQZrMaYX/ixIlh32YnkvMmT57s55hjDm/eNMl5ZmMS9pNK9sXe/r3NrCRFjz76aGjr/PPPT8r48tBDD3nzPCkpa2THbBm8za7kPvU3v/lNGI/N6GSeYwaaSbkpW95mMbwZoHqbJQrlZ599tqfPKL/+9a/9LLPM4s1LJhaFunAfO3ZsKMvD3GaQ/Ne//nX/73//O2nHlL8wVkv8lpQV+bL//vuH802xrHqaKYveZn28zVZVrVN+YI899vArrbRSebH2W0dgkmZAmlDedKoIiEDfE/jSl75UMQjcMVkaGDp0qGO5AVl88cXDFuNFBINMZKmllgpb/plrrrnCjAkzJC+88EJSnvdLXI6I9VnK4e2704JtBzL33HPX7ZpliQMPPDDTKDWefPLJJzvcdvGSiYLx50ILLeQuvfRS989//jO4wNZjftlllwVvFWZPmPXgY0pfuE+mEMamW75l3CwRtbOPlg96ADQoG5ABcJN1iSIgAs5hkIjYC1xNHNGrAq8WbEOKSLkCUuTcVtZl7IwlHRejVvtHHHFEWILC5mWrrbYqWbqBFwrNKqusUtHEaqutFhQ1XHtXWGGFiuPlzJ966qlgG4NxbCeFZSYExTIqop3sX31lE9AMSDYXlYqACAxQAi+99FK4clsqKEygWxQQZitQHD788MNc18C4mcngPOxCon0LJ3MMe5FHHnnE4e2Tlqig5Q1UhkKCMbAti6Wbaft3bFSQBRZYoO19qYP8BKSA5GelmiIgAgOAwJ133umWXXbZZPmCJRwMTWtJVDzKH9C1zmnnsSWXXDI0/+abb1Z0g2KCF0u5mI1HUD5YrohLOLEOS0l4AP31r3+NRWGLVwyeP3mVtW9/+9tBKfrVr35V0g4RWDESbpdMmjQpKFIsGUm6h4AUkO65FxqJCIhAAwRwg0WI9hnFjBzDDMAnn3wSi5Lj5REz0xFUX3vttfCmj7dHFFxNaRuPGmYU2OL5gctufLPG5RYxQ8rQrxnGhn1icBAfpNOCi+xMM82UGYCLhzHXmaVUEQXVDFgrXHAJ5oWtzSWXXJJcCu7PXC/HmNnIwxzPI2Yh9tprr+B9hKJz5ZVXOuJ04LkUhXZZ0jn33HNjUdVtvAdZ1xNPIj4L9zHvklQ8T9s2EzBtWNImAkPkBdMmsmq2vxBo1gsGLxO8VOzPpLe3fm+upMHD4mc/+1koMyNMj9eLPXC9xfcIZfYW7i03ircHcdhfffXVPZ4YeFPYzIfHKyQteG7gDUEf5jbqLZ6EN8NNb7lHvD0gk6oWyyLUwfPGlnFCOd4m/B0wA8ikXiNfinrB0MeRRx7pzZ6jpLurrrrKDx8+PIxz3XXX9TbbU3I87pjLaokXDOUW/yNci8XU8BYzJbRtthzhFLxa8jCnsrlOe7OzCWOI981mUkI78R+LtRKOWxj4quzwWDrppJOCdxDtcK233XZbbCLZ4vligdX87bffnpTl+SIvmDyUmqozCW1d0iYCUkDaBFbN9hsCzSogzYCICggPW5vZ8Lis2lt91SZtOSM5hstpuXCuGTmWFNtbeSHXz5KTUzuNKCCMkQc9ylcj8sYbb1ScxjWawak3exDPtTUjNiuRKGpZ7cB7p512yjpUqMxmWPxGG21U6BwqSwEpjKzoCXLDNc1ZIgIiMMAJsFyBfUC05cjCYfFBkuKsqXzOJRBZWli2IO9KXwhjZAmDIGMslxQVbDvKhWtkmYYEcFnuz+X1a+0vuOCCNTPVPvDAA85maWo1UfcY3jksKeH+K+k+ArIB6b570vIRsVa97bbbBhe0ljee0WCn+8sYQlJEtkz++MSPBYbLNMBLTsjxBXsAwm63Q0ge1k5jvPIxd7q/8v77cj8aYmIA2V/Fllvc6NGjg81FI0pIX3EhrgjGsM2ETsebiay+F1xwgYuRafvqetRvNgHFAcnm0q9KY7py8lFYhMe2X1un+6t2Qbz9EDba5gWTKuQC4W23GeGt8oorrnAW/bKZZjLP5Y8lMQt22WWXzOOtLux0f60ef6PtYZTIzABC2HVCgpPPpa9mKxq9jjznMYtA1lgCcfXK9eGRQ9j8ZoRrveiii2rOajXTvs5tnoBmQJpn2HUtkCwrLe1OV97p/tLXVus7b/e4VPImxIcImHgwNCO4WVrI7xC0iZwWzUg5N9qaMGFCSKLWTLvVzu10f9XG0Q3l8847rzvttNOCFws5ZEhAN91003XD0NoyBiKi9ory0SoAeCbVWlJrVT9qp3ECUkAaZ9eVZ/JQPOCAAyrG1q505Z3ur+LCqhQQ3hlXSNKOx7TduP9lrd1XaSKzmIyp5jUR/rARnrpRqcaN8ODtmC7udH+NcunUeTyMzcOi5KOHVafoqx8R+B8BLcF02S/hueeec+ZaGB6e5JDgzaxczIXQ3XPPPcGPf7311ktyWfCQMWvv8HC0ZFKOtzyWIFj7Tacrp97DDz8cmjX3tJBmnJ277rorvIFjfLbNNtuE48RMoJxlFXz98dWPhnZ5+wsN2T8EMiJDJ77/KAP45acjExZJ5x3brLbl7ZbZBNrHuPCQQw5xW2+9dcUbUdF06QRQYibBPARC9lByS6DkZAlxEYgqSeRHpsDNbTOsa1fjRhsEjiIrKTY7nM9yD7EsSI0+cuRIR4Ap1sctOViwZWGNPEajrPbbydtf+hq439XSrlPvlVdeCenNyfZKRloUMxQ9ljGy0rin29Z3ERABEQgEivrNqH5+AkXdcPFpt3XP4ApoibCCz70ZJJZ0eNBBB3lLZe3NgM6TgZMMj/jlIxal0JvSErJ52kMn7FvuhSROQjpb6IYbbohhhLeAP0n7uNjZwzpxJST+gSkbnraIY0BcAbNcD30X7Y+x2kM4xFjAve6Xv/ylN1sHT5ZNhEyWZp8RxmQPMY975s9//nNvycG8TaV6C/wU6uX955ZbbvF77723t9Tq3qbWQ7vrrLNORUwBro8YAXnEAlZ5C6QUqhIHAX72AM481ZQsb8qhtxTvIavqFltsEfp5/vnnM+8TfC+88EJv6d7DNcdGTVH0pviFmBOxjK0pQt4SeSVFtX47Wb+Lav3RIO6HZrjoGaspIp5YFvwuzfg29EdWWTLGcv30a8qqX3/99cP+Mccck4wpz5e+dMPNM75uqdOIG263jL1XxyE33LbfOcUBaSfiogqIvUmXPFRIU85DLAoBknhgpoWASOYSlxRxjr31J/t8yUpXzsPF3lS9ZcFM6uKXv8MOOyT7lhsi1CHgDxJTjvNQjJKnPwIBWY4Jb7MQ8bSw5eFjU+EeJQkhbgEPtVop1EPFgv8wbvqnbbOKLzm7SLp0i9bobSYpnG+2IEEZQ4lKpyjnIA93y7DqzznnnKQvszMI1xpTwWdxozL3E6UrLTZz481wtqSf7bff3nO/otT77eTtL0/adfrcb7/9Ak/zBopDCCnqCeRVRPgN2NJHaIv7o091Biii4lOdTzvYLL300kV+zqpbjMAkLcHYr7ZbhKWOmCKcaW2muZluj2IBk9yoUaPibtj+7ne/q0gQVb6WneWvT+6GESNGBBc1m1EJKcvxiCAkchR7a3eEdCZFOWGOWcZB/v73v7vll18+VqtY1ijvz2YjHB4pFk0yOYcvLEn89re/deeff7474YQTcqXzLmkg5w75JzA0JH4B7rj28EzOJMdFHsFV0xQZx9IWwjIDYbZp67zzznO/+MUvkmZYZqJu+l7BkSWotCFg+X2igXJ2lJGynCUXkoXxnXb4EEchSr3fDvXy9Fcv7TpZTPFQiHYqJC+LQpbRW2+9Ne7m3hJTwmarctcfiBX5P8T/dX5rks4Q4P8cWYUl7SMgBaR9bAu3jG2FhRIONgAYOg4dOjQ8OGkI7wtSWePRkhYeKiTLSkvWgyZ9PH7nYcZD0qbUnb0hB8+Oww8/PB4OD1mUD+wnMN6MSkd5PIF6/aFMITElduyAVN5IeeKreJwtdieIKdZh2+g/uN5iH4OS1YhwHjk0uC9RYqZR7E1sGSwZqy27BEUyHbiKc9LKB/v1uFEHgTsflB/u2eWXXx5sLf539H//1vrtxHr1+oMx96KRtOv0wb1q5D4xdlzEJdUJRNsgcarOqNVHyEdDzh9J+wiUPrna149azkHg4IMPDrMMvEXyhkl8gij8YefBb1P4znJWxOLMbb0HTTwJo0ZmQniwoWCwnxazQ3G29u9467U1foeRY5bU62/w4MHhNP5DR6WDAt7gcX3Mm8o7q+8iZbytW2jqIqeEunDH8BRFqlyJQiHkPmHMGpVD6qOcmO1MMLSt1mE9bunzUDx+/OMfh+RfN998s7OcHunDrtZvJ1as1x/H02nXo/LH+dHQtVP3Ko5ZWxEQgf5LQG64XXJvedgfddRRbuzYscn0dnqmgVkOgiXhIUOk0bQQahhvFYSHSN6U4NRlGcGSNIUlEFuPTzfrWJr59NNPg/LBgfR4YsU8/cVlDjx30vLkk0+G9ldeeeV0cdu+oyQwC1JU8PAgM2e58kE7loArNJd2ycXjBWF5KS28TTEGJA+39LlkEcVjyQzjnBmFJrMt1Kn326FO3v5alXadPiUiIAIiUIuAFJBadDp4DJdLhOl17D5wgeSBTappjrHmT+RGZkLMSDO8kfMmzFsxZXFNnuA7xMBASTFD0/AmnpWuPF4a7p7MfuBKah4YsThseYtn2QGbBsKPxxDhr7/+uovhq/P0hw0GLrBcD8HAotx3333hzTranXCdXEueFOqxjawtMzUsiZj3R3KY5Suux7yIkjK+1EuXznjMsyPTHZrzCXVNdNn7778/fCgzDyNnxmvBbsOSabnx48c78xYJrrW4TSNZ3CjnXn3wwQchaiX7UbhHlrHV4YJtBqixOGzz/Hby9pcn7TqdRtuk8nvF+GEmEQEREIG6BOyPhaRNBIZYGm7LPZK7dVMGglstHg24WZrRWfCcWGuttRI3VNJ/k6Labqw3Y8BQL90BLrO45lLn1FNP9VnpytP1+U6/eGmUiyWDCp4eZhgZUpmb8hDSlds0fHAZpX7e/vBwsWUEv8QSS3gLj+zNmM6b/YmnTcQeornTeYcTavzDtVgeicAIj5p9993XH3fccYn7cPrUWunSyQZqy1KhHdxMcalNC949NvPhzXA41LHlLG9xP0IVsqKS7txmHsIHN9Z0ptRybrhVc79wCebe7rPPPr48G6nNdHi8WbKk3m+nSH+10q7Ttxm8eq6VceKNQ1ZZM+4Nv0fKbOYsuB5njbO8TG645USy9+WGm82lnaVyw20n3dD2pKnY2B8NSRsILGQBsMjpUcTCn5mO9EwEb5TlnhEshdjDLLx5ZwV94g2a8nQ7tS6PpFzV8qPQF8s70TuHnwvLMmmDyiL9UZfZCIJWtTMvDdyYbeG6MHKsJtRjeSJ9PdXqNlLOTBEMox1Muo0i3OJ5te5Vvd9Okf64z8wk0SZLSuW/wTieZrcELuOa4tJUs+311/OxwzriiCNCALz+eo3ddl177rlnsLnCdk3SFgKTZYTaFq6NN1quNGT94Ue54AFeTcgiWUSqKR+0QV9R+WA/62FdpD/qZnlZ0HYeyZOkjSUdi8ORGE7WajeLb636RY8R7ruaFOEW26h1r+r9dor0x33GbVnSPwiwdIebNMue0bMDo2yWCtOCwszSblpw1+9242PstHDrZ6kyCtF8SUFR629lrKtt3xCQAtI33NVrgwSwf6kn5e6v9erruAj0ZwJ4zuFthvJKegdbFg6zKSikpGRIe4ZRhuKJbRnG7My81FKi+5rbjTfeGGzjiPNj0ZRLFBCMtUkVQDwjbLUk3UdACkj33RONqAYBxUGoAUeHChPAvXqrrbYqfF7eE9rdfr1xkBGaWYE4c8hsJrF+MDZmSY74P+RMirNnzHwRNA+vKxSQNdZYo14XfXacJVaWB1GgUEDKBc9Bs50J+bCYwYneaeX1tN93BOQF03fs1bMIiEAfEjDD3MzM0a0aUrvbrzdO3NyZwcDTq1zweiMZJIHnUMDKTQFx+e72ZReWVvgMGTKk/PKSfWLZYMsRPe2SA/rSFQQ0A9IVt0GDEAERKEKgVrZelhxwQSduCy7LGNIyE4HxNO7IvN2jHGRljrY8PsFtmpkCgq9hW4BLO1mpiZGCW/o111wT2jIvJ2deXaEtot8iZCfmoVitfdzZyXCM+ztRhtsp5v3liO3DrEa5MDuAyz8RdsnYTAwigtlFwfaLT7nU4g47xxpbjgAAB5NJREFUrpvziO3DfSATtCWZLFnmoU1c+QkvjzE9y0Jrr712eVct27cklMEtn/vG/ZF0D4HKX1j3jE0jEQEREIEKArzRmlt1mFrHQNJclp25qifGlRtssEHImRLTCrC8wFs+cXROOeWU0B5v99gIYISMzYMlcAwPQ5QT2jz++OND3BUUC5QXy6ocIt6iwMw555whIBxBARHskoiLQpA4ch4hWe1TzsP+gAMOcFdeeSW7bRNmP4jfw7VUE8bIeFDUYHPDDTdUqxrKa3EnXtGWW24ZZlUsq7OzpJbBg4TYQWvYMg72GVFQUsxVOxjAElyRZSAi/bZTUHLIpSXpMgI29SZpEwGbGiwUB6RNw1CzItC1BIrGAcmbrdfC4ntz8y65brNt8PZmnpQRU6U8c/TEiRNDfBOzNUrqkQ3aDJtDezaL4u3hHuoQyyaK5VMKZZZGIRaFmC3l7RPvxiIXe1NYknp5vhSNA0If9qjxNnuT2Tzxb6KQZdtmSULsHJuxCMWWnsHTZ5Q83PNks7bZqBBDBg5RLMBeGKu5u8aiQltLTRHONyWn6nmmeIb4SMTuySuKA5KXVMP1JmkGpMsUQg1HBESgOoF62XpjhNbqLZQeKV+eiC7nuHFHYamEN3qWCwh7X0Sy2mdZJBp9FmmrSN2Y4HHuueeuexrLEgceeGBilMqSVbnk4Y6xK9dLEk2WeBBcfxEMRhGyURNXiFkrZj34ELmZc0z5C3Xa8Q/ePSwRtbOPdoy7v7cpG5D+fod1fSLQTwjYe1ZT2XqzMJQrCFl1KIuuqqRnLxpPpVqb7SxnnFxbOi5Grf4IcsZyE3YbLFell26a4R4TGtIGQhBClrEwju2kxDxOKJFRKepk/+orm4BmQLK5qFQERKDLCPBAxW7hkUceqUi42Gi23rwKyEsvvRRokD26iORtv0ibeeoSZIyHPvmP8gjjvPTSSx3nYRcSbWU4t5XcUUgwTMUguJOCjQqCrY+kewhIAemee6GRiIAI1CGQN1svSwBTpkyp2RoP1ryZo++880637LLLOpY04vJCK9uvOdAGDi655JLhrDfffLPibBQTwt+Xi+WWCsoHMzxxCSfWycs91q+2JTElSpHluiqpQgTWmOyy5ECLdvBe4n6THkPSPQSkgHTPvdBIREAE6hDIm62XGBe4vOKRwQOPLSHIcamNb8PVMgQzhCeeeCIZyWuvvRZmXfC8QViOGWKxJ3BjZWYEz5errroqHCMDM7l/kKz2CZi1wgorOEvoF+q06x+CiRH5NH0dsS8exlxTlgKFR5AZsFa44ObhTlZmlJvyDMn0i90HgpcRsxB77bVX8DRC0cEjiDgdeNFEIf8KnHBZrifxfmZdTzz3xRdfDB46eZek4nnatpmA/WAkbSJgf6TkBdMmtmq2fxAo6gXDVdfL1ksdvC1WWmml4B1hrp7eYkB4M7b0li/Ek1EaMXfQkszRlJHZ1/7k+tVXX93jnYGHhc18eDxF0oIHDBmnzbbAW6hvf/fddwcvmd13391HT5Ks9qPHSRxDus1a34t6wdDWkUce6c2eo6RZU5S8hSUP10i2ZpvZKTked8xltcQLhvJa3Itks3766ae9KXFhDLC22Rpv8UVi12Frrs/hOIzNeLTkWNzBO+mkk07y5hYd6nKtt912WzycbPF8Icv07bffnpTl+SIvmDyUmqozCY1V0iYCUkDaBFbN9hsCjSggXLzNMnibefBmD+LtzbcqD1uCSI7hJlouNvVf4hIbFRAewDZzEtxY6StLaC+609pbv7flnIpq5e1TwUKgV9SrV9CIAsL4eNDbbEe95jOPv/HGGxXleblXnJhRYLMS3maQMo78r4h7t9NOO1U9nveAzbB4CzqXt3pSTwpIgqJdXybJC6bNM0xqXgREoPUEWM/Pk603nZgwa/q9lkcLSxi1bAZoL7ZJsrcsyWofW4tOCGNjCYMgYxbXo2JZpd4YCLhWLnm5l5+Xtb/gggtmFSdlDzzwgCPabDPC8hhLSrj/SrqPgGxAuu+eaEQiIAJ9RCAaZ2IU2R+ELLCjR48ONhfRNqUXrot4LihvzYROxz5n3Lhx7oILLnAzzjhjL1z2gBujZkAG3C3XBYuACGQRwFCR2QLEbDUcYcLHjBnjpp9++qzqPVPGLAKZYAnE1SvXwiwRIdybEa71oosuCt4vzbSjc9tHQApI+9iqZREQgR4iMO+887rTTjstfOKwqy2txOO9ss0TEbVXriXvOPFCknQ3ASkg3X1/NDoREIEOEeCNuVdmCDqERN2IQFsJyAakrXjVuAiIgAiIgAiIQBYBKSBZVFQmAiIgAiIgAiLQVgJT4eDb1h4GcOO48GFMlcddcABj0qUPYAITJkwIxpGrrrrqAKZQ/9LJ4moBvNyGG25Yv7JqtITAo48+6iyAmSMqq6QtBCZLAWkL1/81eswxxzh+xBIREAEREIHeI7Dmmmu6nXfeufcG3hsjlgLSG/dJoxQBERABERCBfkVgsmxA+tX91MWIgAiIgAiIQG8QkALSG/dJoxQBERABERCBfkVACki/up26GBEQAREQARHoDQJSQHrjPmmUIiACIiACItCvCPw/KBOr3rbbzhQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image('model_plot.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Network Architecture/Shapes\n",
    "\n",
    "Above, we have created our convolutional neural network and made some assumptions about the (image) input data Let's examine in more detail how each of these layers affects the shape and where the number of parameters comes from."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Input Image Layer\n",
    "\n",
    "We start with the input layer, which takes images of size $m \\times n = 150 \\times 150$. We have color images so we also have 3 color channels. The shape of the input layer is therefore $(150, 150, 3)$. \n",
    "\n",
    "We will need to create an image transformer that will adjust the size of images being fed to the neural network, since we have some not-quite-square images."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### First Convolution Layer\n",
    "\n",
    "Once we have sized an image correctly, we have an image with dimensions $(m,n,3)$. The convolution layer applies a convolution kernel to the entire image; the entire $m \\times n$ image is covered with a window of size $k \\times k$, which leads to an image of size $(m - k + 1, n - k + 1)$.\n",
    "\n",
    "If we specify that the convolution layer should have $c$ output filters, we will get an output from the first convolution layer that has dimensions $(m-k+1, n-k+1, c)$. Each convolution kernel (which is learned from the data by the model) is the same for the entire image. However, each color channel has its own kernel associated with it. Images with 3 color channels will have 3 kernel functions to learn per image.\n",
    "\n",
    "In terms of the concrete example, we have an image of size $150 \\times 150$ and our first convolution layer uses a kernel window of size $3 \\times 3$, for a final output image of size $(150 - 3 + 1, 150 - 3 + 1) = (148, 148)$.\n",
    "\n",
    "The convolution layer was specified to use 32 filters, so the final dimensionality of the data leaving the first convolution layer is $(148, 148, 32)$.\n",
    "\n",
    "This layer has 896 parameters that the model learns. This number comes from having one 3x3 kernel (9), per color channel (3), per convolution filter (32), for a total of $9 \\times 3 \\times 32 = 864$. In addition, there are 32 more weights, for a total of 896."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 14,
     "metadata": {
      "image/png": {
       "width": 600
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Source:\n",
    "# Book \"Deep Learning\" (Ian Goodfellow, Yoshua Bengio, Aaron Courville)\n",
    "\n",
    "Image('img/input_kernel_output.png', width=600)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Sidebar: What happened to the color channel information?**\n",
    "\n",
    "First, let's revisit (mathematical) definition of convolution:\n",
    "\n",
    "$$\n",
    "g(x) = \\int f(x) w(x) dx\n",
    "$$\n",
    "\n",
    "where $f(x)$ is a function that is an input to the convolution process, $g(x)$ is a function that is the output of the convolution process (the \"feature map\"), and $w(x)$ is a weight function (a convolution kernel).\n",
    "\n",
    "The discrete form of the convolution is the summation:\n",
    "\n",
    "$$\n",
    "g_j^n = \\sum_{k=0}^{K=3} f_{k}^{n-1} w_{kj}^{n}\n",
    "$$\n",
    "\n",
    "where $g$ is the output feature map, $f$ is the input to the layer, and $w$ is the kernel function; and the subscript $k$ indexes which color channel, $n$ indexes which layer, and $j$ indexes which feature map.\n",
    "\n",
    "From the summation above, we can see that the output of the convolution from each of the three color channels are combined additively. Each of the feature maps combines information from all three color channels.\n",
    "\n",
    "While it seems like we would lose information about the contributions of different color channels by adding together each channel's contribution to the feature map, we actually have separate kernel functions for each color channel, and those kernel functions are learned, so contributions from different color channels are weighted differently based on the learned kernel."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 15,
     "metadata": {
      "image/png": {
       "width": 500
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Source:\n",
    "# \"Large-Scale Visual Recognition\" (presentation by Marc'Aurelio Ranzato, Facebook AI Research)\n",
    "# https://tinyurl.com/y5xtvhbc\n",
    "\n",
    "Image('img/conv_channels.png',width=500)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### First Activation Layer\n",
    "\n",
    "After the input data passes through the convolution layer, it now has dimensionality $(148, 148, 32)$.\n",
    "\n",
    "The activation layer translates the linear operations occurring in the convolution layer (the summation shown above) into a nonlinear output signal.\n",
    "\n",
    "The example above uses the ReLU function (rectified linear unit), which is the function:\n",
    "\n",
    "$$\n",
    "f(x_i) = \\max(0, x_i)\n",
    "$$\n",
    "\n",
    "These activation function layers are functional mappings without any parameters to set.\n",
    "\n",
    "**Sidebar: Why use ReLU? What are the other options?** \n",
    "\n",
    "Rectified linear units are recommended in the literature for convolutional neural networks because they don't introduce strong non-linearities, and they can avoid some problems with larger networks with training slowing down or completely stopping (see the [vanishing gradient problem](https://en.wikipedia.org/wiki/Vanishing_gradient_problem)).\n",
    "\n",
    "Before ReLU units were common in convolutional neural networks, the tanh and sigmoid functions were popular. These suffer from the vanishing gradient problem. Gradient here refers to the gradient of the error function with respect to a particular weight in the network. These gradients are multiplied together as we move backwards through a network to reach the particular weight in the network, which is used to update the weight's value. However, the gradient of the tanh and sigmoid functions take on values between 0 and 1, and due to back-propagation, the gradients are multiplied together, causing their values to vanish. A zero gradient value will prevent a weight in the network from updating."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### First Pooling Layer\n",
    "\n",
    "Each of the convolution steps in this network use max pooling. The max pooling step allows the network to become insensitive to the exact location of the features the network is learning to identify. The max pooling step can also be thought of as a \"blurring\" of the filters that result from the convolution and activation layers. It does this by dividing the entire image into square regions, and then taking the maximum value in those square regions.\n",
    "\n",
    "The pooling layer in the example above is applied with a 2x2 window. With a 2x2 window the stride is also 2, so the size of the original filter is cut in half by the max pooling layer. The dimensions of the 148 square are cut in half, 148 / 2 = 74, resulting in a 74 x 74 block.\n",
    "\n",
    "The dimensionality of the data leaving the first max pooling layer is $(74,74,32)$.\n",
    "\n",
    "Like the activation layers, the max pooling layers do not have any parameters."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Second Convolution Layer\n",
    "\n",
    "The second convolutional layer takes the result of the prior max pooling layer as an input. When this layer is created, a number of convolutional filters must be specified. We denote this $c_2$ (for number of convolutional filters for the second group of convolutional layers).\n",
    "\n",
    "Like the prior convolution layer, we are starting with data of dimensions $(m_1, n_1, c)$ (where $m_1, n_1$ is the width, height of the output of the first convolutional layers, c is the number of filters from the prior convolutional layer). The convolution layer applies a convolution kernel of size $k \\times k$ (it does not have to be same size as kernel applied in prior convolution layers, we just continue using $k$ for convenience).\n",
    "\n",
    "The dimensionality of the convolution result will be $(m_1 - k + 1, n_1 - k + 1, c_2)$.\n",
    "\n",
    "In our specific example, the input dimensionality (output from the first convlutional layers) was $(74, 74, 32)$. \n",
    "\n",
    "The kernel window we use is $3 \\times 3$ ($k = 3$, the same as the prior convolutional layers). The number of output filters is $c_2 = 32$. This makes the output dimensionality of the 2D convolution layer $(72, 72, 32)$.\n",
    "\n",
    "**Sidebar: What happened to color channel information in the second convolution layer?** We already saw how color channel information (third dimension) was treated - each color channel had its own kernel that was learned by the model, and in the end the output filters are an additive contribution from the separate convolution of each of the three channels.\n",
    "\n",
    "In a similar manner, the 32 output filters from the first convolutional layers can be thought of as 32 \"channels\" that similarly each have their own kernel function that is learned (different for each of the 32 channels), and that each contribute additively to the final convolution filter.\n",
    "\n",
    "The number of parameters in this layer is 9248. This number comes from having one 3 x 3 kernel (9 parameters), per channel (x32), per convolution filter (x32), for a total of $9 \\times 32 \\times 32 = 9216$. Additionally there are 32 more weights (one per output filter), for a total of 9248."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Second Activation Layer\n",
    "\n",
    "The second activation layer maps input values to output values. The second activation layer uses the ReLU function (rectified linear unit). This is the same activation function used in the first activation layer.\n",
    "\n",
    "The activation layer maps a single input value to a single output value, so there is no change in dimensionality in this layer. The input dimensionality is $(72, 72, 32)$ and the output dimensionality is $(72, 72, 32)$."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Second Max Pooling Layer\n",
    "\n",
    "The second max pooling layer works the same way as the first - the output filters are divided into squares of size 2 x 2 and the final value that represents the square is the maximum value in that square. This divides the dimensions of each filter in half.\n",
    "\n",
    "72/2 = 36 so the input dimensionality is $(72, 72, 32)$ and the output dimensionality is $(36, 36, 32)$."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Third Convolution Layer\n",
    "\n",
    "The third convolution layer has an input dimensionality that is the same as the prior layer, $(36, 36, 32)$.\n",
    "\n",
    "The third convolution layer applies a kernel of size $3 \\times 3$ and has 64 filters (twice the number of the prior two layers).\n",
    "\n",
    "The output dimensionality is therefore $(36 - 3 + 1, 36 - 3 + 1, 64) = (34, 34, 64)$.\n",
    "\n",
    "The number of parameters in the third layer is 18496. This comes from having one 3 x 3 filter (9 parameters), per (input) channel (x32), per (output) convolution filter (x64), for a total of $9 \\times 32 \\times 64 = 18432$ plus an additional 64 parameters (due to the 64 filterS), for a total of $18432 + 64 = 18496$."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Third Activation Layer\n",
    "\n",
    "The third activation layer is identical to the first and second - it uses the ReLU function to perform a nonlinear mapping of inputs to outputs. This layer does not change the dimensionality, so the input and output dimensionality are both $(34, 34, 64)$.\n",
    "\n",
    "This layer does not have any parameters."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Third Max Pooling Layer\n",
    "\n",
    "Like the first two max pooling layers, the third max pooling layer uses windows of size 2 x 2 to perform pooling. The first two input dimensions are cut in half, so the input dimensionality is $(34, 34, 64)$ and the output dimensionality is $(17, 17, 64)$.\n",
    "\n",
    "This layer does not have any parameters."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Flatten\n",
    "\n",
    "The flatten layer flattens the multidimensional output of the prior layer to a single dimension. The input dimensionality is $(17, 17, 64)$ and the output dimensionality is $(17 \\times 17 \\times 64, 1) = (18496,1)$.\n",
    "\n",
    "This layer does not have any parameters, because it is only reshaping the outputs of the prior layer.\n",
    "\n",
    "### Dense (64)\n",
    "\n",
    "Now we create a dense connection between the prior 18496 neurons and a flat layer of 64 neurons, leading to $(18496 \\times 64) + 64 = 1,183,744 + 64 = 1,183,808$ individual weights (parameters to be fit).\n",
    "\n",
    "### Dense (1)\n",
    "\n",
    "Now we create a dense connection between the flat layer of 64 neurons and a flat layer of 1 neuron, leading to $(64 \\times 1) + 1 = 64 + 1 = 65$ individual weights (parameters to be fit)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Image Transformer\n",
    "\n",
    "Not all of the images are the correct size (the image above was 280 x 300 instead of the 150 x 150 image our CNN model expects). To deal with this, we can use an `ImageDataGenerator` object to generate data from a folder full of images. The `ImageDataGenerator` also allows us to specify a target image size.\n",
    "\n",
    "We can also add parameters to the `ImageDataGenerator` that allows us to generate multiple training images from a single image, via transformations - sharing, zooming, and horizontally flipping. This also helps to keep the model flexible in its ability to recognize particular shapes unique to cats or dogs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# this is the augmentation configuration we will use for training\n",
    "train_datagen = ImageDataGenerator(\n",
    "    rescale=1. / 255,\n",
    "    shear_range=0.2,\n",
    "    zoom_range=0.2,\n",
    "    horizontal_flip=True)\n",
    "\n",
    "# this is the augmentation configuration we will use for testing:\n",
    "# only rescaling\n",
    "test_datagen = ImageDataGenerator(rescale=1. / 255)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 20 images belonging to 1 classes.\n"
     ]
    }
   ],
   "source": [
    "train_generator = train_datagen.flow_from_directory(\n",
    "    'train',\n",
    "    target_size=(img_width, img_height),\n",
    "    batch_size=batch_size,\n",
    "    class_mode='binary')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 9 images belonging to 1 classes.\n"
     ]
    }
   ],
   "source": [
    "validation_generator = test_datagen.flow_from_directory(\n",
    "    'test',\n",
    "    target_size=(img_width, img_height),\n",
    "    batch_size=batch_size,\n",
    "    class_mode='binary')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "if not os.path.exists('first_try.h5'):\n",
    "    history = model.fit_generator(\n",
    "        train_generator,\n",
    "        steps_per_epoch=nb_train_samples // batch_size,\n",
    "        epochs=epochs,\n",
    "        validation_data=validation_generator,\n",
    "        validation_steps=nb_validation_samples // batch_size)\n",
    "\n",
    "else:\n",
    "    model.load_weights('first_try.h5')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualization of Convolutional Filters\n",
    "\n",
    "Courtesy of the [keras blog](https://blog.keras.io/how-convolutional-neural-networks-see-the-world.html)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "input_img = 'train/data/cat.1.jpg'\n",
    "layer_name = 'conv2d_3'\n",
    "filter_index = 11  # can be any integer from 0 to 511, as there are 512 filters in that layer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "layer_dict = dict([(layer.name, layer) for layer in model.layers])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "# build a loss function that maximizes the activation\n",
    "# of the nth filter of the layer considered\n",
    "layer_output = layer_dict[layer_name].output\n",
    "loss = K.mean(layer_output[:, :, :, filter_index])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "# compute the gradient of the input picture wrt this loss\n",
    "grads = K.gradients(loss, input_img)[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensor(\"Mean_3:0\", shape=(), dtype=float32)\n"
     ]
    }
   ],
   "source": [
    "print(loss)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Tried to convert 'x' to a tensor and failed. Error: None values not supported.",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m~/.pyenv/versions/miniconda3-4.3.30/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py\u001b[0m in \u001b[0;36m_apply_op_helper\u001b[0;34m(self, op_type_name, name, **keywords)\u001b[0m\n\u001b[1;32m    510\u001b[0m                 \u001b[0mas_ref\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0minput_arg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_ref\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 511\u001b[0;31m                 preferred_dtype=default_dtype)\n\u001b[0m\u001b[1;32m    512\u001b[0m           \u001b[0;32mexcept\u001b[0m \u001b[0mTypeError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/miniconda3-4.3.30/lib/python3.6/site-packages/tensorflow/python/framework/ops.py\u001b[0m in \u001b[0;36minternal_convert_to_tensor\u001b[0;34m(value, dtype, name, as_ref, preferred_dtype, ctx, accept_symbolic_tensors)\u001b[0m\n\u001b[1;32m   1174\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mret\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1175\u001b[0;31m       \u001b[0mret\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconversion_func\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mas_ref\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mas_ref\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1176\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/miniconda3-4.3.30/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py\u001b[0m in \u001b[0;36m_constant_tensor_conversion_function\u001b[0;34m(v, dtype, name, as_ref)\u001b[0m\n\u001b[1;32m    303\u001b[0m   \u001b[0m_\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mas_ref\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 304\u001b[0;31m   \u001b[0;32mreturn\u001b[0m \u001b[0mconstant\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    305\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/miniconda3-4.3.30/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py\u001b[0m in \u001b[0;36mconstant\u001b[0;34m(value, dtype, shape, name)\u001b[0m\n\u001b[1;32m    244\u001b[0m   return _constant_impl(value, dtype, shape, name, verify_shape=False,\n\u001b[0;32m--> 245\u001b[0;31m                         allow_broadcast=True)\n\u001b[0m\u001b[1;32m    246\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/miniconda3-4.3.30/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py\u001b[0m in \u001b[0;36m_constant_impl\u001b[0;34m(value, dtype, shape, name, verify_shape, allow_broadcast)\u001b[0m\n\u001b[1;32m    282\u001b[0m           \u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mshape\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mverify_shape\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mverify_shape\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 283\u001b[0;31m           allow_broadcast=allow_broadcast))\n\u001b[0m\u001b[1;32m    284\u001b[0m   \u001b[0mdtype_value\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mattr_value_pb2\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mAttrValue\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtensor_value\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtensor\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/miniconda3-4.3.30/lib/python3.6/site-packages/tensorflow/python/framework/tensor_util.py\u001b[0m in \u001b[0;36mmake_tensor_proto\u001b[0;34m(values, dtype, shape, verify_shape, allow_broadcast)\u001b[0m\n\u001b[1;32m    453\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mvalues\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 454\u001b[0;31m       \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"None values not supported.\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    455\u001b[0m     \u001b[0;31m# if dtype is provided, forces numpy array to be the type\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: None values not supported.",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m~/.pyenv/versions/miniconda3-4.3.30/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py\u001b[0m in \u001b[0;36m_apply_op_helper\u001b[0;34m(self, op_type_name, name, **keywords)\u001b[0m\n\u001b[1;32m    524\u001b[0m               observed = ops.internal_convert_to_tensor(\n\u001b[0;32m--> 525\u001b[0;31m                   values, as_ref=input_arg.is_ref).dtype.name\n\u001b[0m\u001b[1;32m    526\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mValueError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/miniconda3-4.3.30/lib/python3.6/site-packages/tensorflow/python/framework/ops.py\u001b[0m in \u001b[0;36minternal_convert_to_tensor\u001b[0;34m(value, dtype, name, as_ref, preferred_dtype, ctx, accept_symbolic_tensors)\u001b[0m\n\u001b[1;32m   1174\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mret\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1175\u001b[0;31m       \u001b[0mret\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconversion_func\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mas_ref\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mas_ref\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1176\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/miniconda3-4.3.30/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py\u001b[0m in \u001b[0;36m_constant_tensor_conversion_function\u001b[0;34m(v, dtype, name, as_ref)\u001b[0m\n\u001b[1;32m    303\u001b[0m   \u001b[0m_\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mas_ref\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 304\u001b[0;31m   \u001b[0;32mreturn\u001b[0m \u001b[0mconstant\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    305\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/miniconda3-4.3.30/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py\u001b[0m in \u001b[0;36mconstant\u001b[0;34m(value, dtype, shape, name)\u001b[0m\n\u001b[1;32m    244\u001b[0m   return _constant_impl(value, dtype, shape, name, verify_shape=False,\n\u001b[0;32m--> 245\u001b[0;31m                         allow_broadcast=True)\n\u001b[0m\u001b[1;32m    246\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/miniconda3-4.3.30/lib/python3.6/site-packages/tensorflow/python/framework/constant_op.py\u001b[0m in \u001b[0;36m_constant_impl\u001b[0;34m(value, dtype, shape, name, verify_shape, allow_broadcast)\u001b[0m\n\u001b[1;32m    282\u001b[0m           \u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mshape\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mverify_shape\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mverify_shape\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 283\u001b[0;31m           allow_broadcast=allow_broadcast))\n\u001b[0m\u001b[1;32m    284\u001b[0m   \u001b[0mdtype_value\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mattr_value_pb2\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mAttrValue\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtensor_value\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtensor\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/miniconda3-4.3.30/lib/python3.6/site-packages/tensorflow/python/framework/tensor_util.py\u001b[0m in \u001b[0;36mmake_tensor_proto\u001b[0;34m(values, dtype, shape, verify_shape, allow_broadcast)\u001b[0m\n\u001b[1;32m    453\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mvalues\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 454\u001b[0;31m       \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"None values not supported.\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    455\u001b[0m     \u001b[0;31m# if dtype is provided, forces numpy array to be the type\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: None values not supported.",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-36-0814c2ea5eec>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# normalization trick: we normalize the gradient\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mgrads\u001b[0m \u001b[0;34m/=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mK\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msqrt\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mK\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmean\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mK\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msquare\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgrads\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;36m1e-5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/.pyenv/versions/miniconda3-4.3.30/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py\u001b[0m in \u001b[0;36msquare\u001b[0;34m(x)\u001b[0m\n\u001b[1;32m   1468\u001b[0m         \u001b[0mA\u001b[0m \u001b[0mtensor\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1469\u001b[0m     \"\"\"\n\u001b[0;32m-> 1470\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mtf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msquare\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1471\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1472\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/miniconda3-4.3.30/lib/python3.6/site-packages/tensorflow/python/ops/gen_math_ops.py\u001b[0m in \u001b[0;36msquare\u001b[0;34m(x, name)\u001b[0m\n\u001b[1;32m   9387\u001b[0m   \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   9388\u001b[0m     _, _, _op = _op_def_lib._apply_op_helper(\n\u001b[0;32m-> 9389\u001b[0;31m         \"Square\", x=x, name=name)\n\u001b[0m\u001b[1;32m   9390\u001b[0m   \u001b[0;32mexcept\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mTypeError\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   9391\u001b[0m     result = _dispatch.dispatch(\n",
      "\u001b[0;32m~/.pyenv/versions/miniconda3-4.3.30/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py\u001b[0m in \u001b[0;36m_apply_op_helper\u001b[0;34m(self, op_type_name, name, **keywords)\u001b[0m\n\u001b[1;32m    527\u001b[0m               raise ValueError(\n\u001b[1;32m    528\u001b[0m                   \u001b[0;34m\"Tried to convert '%s' to a tensor and failed. Error: %s\"\u001b[0m \u001b[0;34m%\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 529\u001b[0;31m                   (input_name, err))\n\u001b[0m\u001b[1;32m    530\u001b[0m             prefix = (\"Input '%s' of '%s' Op has type %s that does not match\" %\n\u001b[1;32m    531\u001b[0m                       (input_name, op_type_name, observed))\n",
      "\u001b[0;31mValueError\u001b[0m: Tried to convert 'x' to a tensor and failed. Error: None values not supported."
     ]
    }
   ],
   "source": [
    "# normalization trick: we normalize the gradient\n",
    "grads /= (K.sqrt(K.mean(K.square(grads))) + 1e-5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "Can not convert a NoneType into a Tensor or Operation.",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-37-e58d209785cf>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# this function returns the loss and grads given the input picture\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0miterate\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mK\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfunction\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0minput_img\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mloss\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgrads\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/.pyenv/versions/miniconda3-4.3.30/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py\u001b[0m in \u001b[0;36mfunction\u001b[0;34m(inputs, outputs, updates, **kwargs)\u001b[0m\n\u001b[1;32m   2742\u001b[0m                 \u001b[0mmsg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'Invalid argument \"%s\" passed to K.function with TensorFlow backend'\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2743\u001b[0m                 \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2744\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mFunction\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minputs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moutputs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mupdates\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mupdates\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2745\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2746\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/miniconda3-4.3.30/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, inputs, outputs, updates, name, **session_kwargs)\u001b[0m\n\u001b[1;32m   2544\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minputs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minputs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2545\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moutputs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moutputs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2546\u001b[0;31m         \u001b[0;32mwith\u001b[0m \u001b[0mtf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontrol_dependencies\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moutputs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2547\u001b[0m             \u001b[0mupdates_ops\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2548\u001b[0m             \u001b[0;32mfor\u001b[0m \u001b[0mupdate\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mupdates\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/miniconda3-4.3.30/lib/python3.6/site-packages/tensorflow/python/framework/ops.py\u001b[0m in \u001b[0;36mcontrol_dependencies\u001b[0;34m(control_inputs)\u001b[0m\n\u001b[1;32m   5026\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mNullContextmanager\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5027\u001b[0m   \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 5028\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mget_default_graph\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontrol_dependencies\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcontrol_inputs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   5029\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5030\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/miniconda3-4.3.30/lib/python3.6/site-packages/tensorflow/python/framework/ops.py\u001b[0m in \u001b[0;36mcontrol_dependencies\u001b[0;34m(self, control_inputs)\u001b[0m\n\u001b[1;32m   4526\u001b[0m       \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mIndexedSlices\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4527\u001b[0m         \u001b[0mc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mop\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4528\u001b[0;31m       \u001b[0mc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mas_graph_element\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   4529\u001b[0m       \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mTensor\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4530\u001b[0m         \u001b[0mc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mop\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/miniconda3-4.3.30/lib/python3.6/site-packages/tensorflow/python/framework/ops.py\u001b[0m in \u001b[0;36mas_graph_element\u001b[0;34m(self, obj, allow_tensor, allow_operation)\u001b[0m\n\u001b[1;32m   3476\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3477\u001b[0m     \u001b[0;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_lock\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3478\u001b[0;31m       \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_as_graph_element_locked\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mallow_tensor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mallow_operation\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3479\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3480\u001b[0m   \u001b[0;32mdef\u001b[0m \u001b[0m_as_graph_element_locked\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mallow_tensor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mallow_operation\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/miniconda3-4.3.30/lib/python3.6/site-packages/tensorflow/python/framework/ops.py\u001b[0m in \u001b[0;36m_as_graph_element_locked\u001b[0;34m(self, obj, allow_tensor, allow_operation)\u001b[0m\n\u001b[1;32m   3565\u001b[0m       \u001b[0;31m# We give up!\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3566\u001b[0m       raise TypeError(\"Can not convert a %s into a %s.\" % (type(obj).__name__,\n\u001b[0;32m-> 3567\u001b[0;31m                                                            types_str))\n\u001b[0m\u001b[1;32m   3568\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3569\u001b[0m   \u001b[0;32mdef\u001b[0m \u001b[0mget_operations\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mTypeError\u001b[0m: Can not convert a NoneType into a Tensor or Operation."
     ]
    }
   ],
   "source": [
    "# this function returns the loss and grads given the input picture\n",
    "iterate = K.function([input_img], [loss, grads])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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