assignments/assignment2/FullyConnectedNets.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This mounts your Google Drive to the Colab VM.\n",
    "from google.colab import drive\n",
    "drive.mount('/content/drive')\n",
    "\n",
    "# TODO: Enter the foldername in your Drive where you have saved the unzipped\n",
    "# assignment folder, e.g. 'cs231n/assignments/assignment1/'\n",
    "FOLDERNAME = None\n",
    "assert FOLDERNAME is not None, \"[!] Enter the foldername.\"\n",
    "\n",
    "# Now that we've mounted your Drive, this ensures that\n",
    "# the Python interpreter of the Colab VM can load\n",
    "# python files from within it.\n",
    "import sys\n",
    "sys.path.append('/content/drive/My Drive/{}'.format(FOLDERNAME))\n",
    "\n",
    "# This downloads the CIFAR-10 dataset to your Drive\n",
    "# if it doesn't already exist.\n",
    "%cd /content/drive/My\\ Drive/$FOLDERNAME/cs231n/datasets/\n",
    "!bash get_datasets.sh\n",
    "%cd /content/drive/My\\ Drive/$FOLDERNAME"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Multi-Layer Fully Connected Network\n",
    "In this exercise, you will implement a fully connected network with an arbitrary number of hidden layers."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Read through the `FullyConnectedNet` class in the file `cs231n/classifiers/fc_net.py`.\n",
    "\n",
    "Implement the network initialization, forward pass, and backward pass. Throughout this assignment, you will be implementing layers in `cs231n/layers.py`. You can re-use your implementations for `affine_forward`, `affine_backward`, `relu_forward`, `relu_backward`, and `softmax_loss` from Assignment 1. For right now, don't worry about implementing dropout or batch/layer normalization yet, as you will add those features later.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": [
     "pdf-ignore"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=========== You can safely ignore the message below if you are NOT working on ConvolutionalNetworks.ipynb ===========\n",
      "\tYou will need to compile a Cython extension for a portion of this assignment.\n",
      "\tThe instructions to do this will be given in a section of the notebook below.\n"
     ]
    }
   ],
   "source": [
    "# Setup cell.\n",
    "import time\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from cs231n.classifiers.fc_net import *\n",
    "from cs231n.data_utils import get_CIFAR10_data\n",
    "from cs231n.gradient_check import eval_numerical_gradient, eval_numerical_gradient_array\n",
    "from cs231n.solver import Solver\n",
    "\n",
    "%matplotlib inline\n",
    "plt.rcParams[\"figure.figsize\"] = (10.0, 8.0)  # Set default size of plots.\n",
    "plt.rcParams[\"image.interpolation\"] = \"nearest\"\n",
    "plt.rcParams[\"image.cmap\"] = \"gray\"\n",
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "def rel_error(x, y):\n",
    "    \"\"\"Returns relative error.\"\"\"\n",
    "    return np.max(np.abs(x - y) / (np.maximum(1e-8, np.abs(x) + np.abs(y))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X_train: (49000, 3, 32, 32)\n",
      "y_train: (49000,)\n",
      "X_val: (1000, 3, 32, 32)\n",
      "y_val: (1000,)\n",
      "X_test: (1000, 3, 32, 32)\n",
      "y_test: (1000,)\n"
     ]
    }
   ],
   "source": [
    "# Load the (preprocessed) CIFAR-10 data.\n",
    "data = get_CIFAR10_data()\n",
    "for k, v in list(data.items()):\n",
    "    print(f\"{k}: {v.shape}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initial Loss and Gradient Check\n",
    "\n",
    "As a sanity check, run the following to check the initial loss and to gradient check the network both with and without regularization. This is a good way to see if the initial losses seem reasonable.\n",
    "\n",
    "For gradient checking, you should expect to see errors around 1e-7 or less."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running check with reg =  0\n",
      "<class 'numpy.float64'>\n",
      "Initial loss:  2.3004790897684924\n",
      "W1 relative error: 7.696803870986541e-08\n",
      "W2 relative error: 1.7087519140575808e-05\n",
      "W3 relative error: 2.9508423118300657e-07\n",
      "b1 relative error: 4.660094650186831e-09\n",
      "b2 relative error: 2.085654124402131e-09\n",
      "b3 relative error: 6.598642296022133e-11\n",
      "Running check with reg =  3.14\n",
      "<class 'numpy.float64'>\n",
      "Initial loss:  5.940411485412347\n",
      "W1 relative error: 6.5886401456721494e-09\n",
      "W2 relative error: 5.9116534916234516e-08\n",
      "W3 relative error: 3.797768775322681e-07\n",
      "b1 relative error: 1.1683196894962977e-08\n",
      "b2 relative error: 1.7223751746766738e-09\n",
      "b3 relative error: 2.86824680346369e-10\n"
     ]
    }
   ],
   "source": [
    "np.random.seed(231)\n",
    "N, D, H1, H2, C = 2, 15, 20, 30, 10\n",
    "X = np.random.randn(N, D)\n",
    "y = np.random.randint(C, size=(N,))\n",
    "\n",
    "for reg in [0, 3.14]:\n",
    "    print(\"Running check with reg = \", reg)\n",
    "    model = FullyConnectedNet(\n",
    "        [H1, H2],\n",
    "        input_dim=D,\n",
    "        num_classes=C,\n",
    "        reg=reg,\n",
    "        weight_scale=5e-2,\n",
    "        dtype=np.float64\n",
    "    )\n",
    "\n",
    "    loss, grads = model.loss(X, y)\n",
    "    print(\"Initial loss: \", loss)\n",
    "\n",
    "    # Most of the errors should be on the order of e-7 or smaller.   \n",
    "    # NOTE: It is fine however to see an error for W2 on the order of e-5\n",
    "    # for the check when reg = 0.0\n",
    "    for name in sorted(grads):\n",
    "        f = lambda _: model.loss(X, y)[0]\n",
    "        grad_num = eval_numerical_gradient(f, model.params[name], verbose=False, h=1e-5)\n",
    "        print(f\"{name} relative error: {rel_error(grad_num, grads[name])}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As another sanity check, make sure your network can overfit on a small dataset of 50 images. First, we will try a three-layer network with 100 units in each hidden layer. In the following cell, tweak the **learning rate** and **weight initialization scale** to overfit and achieve 100% training accuracy within 20 epochs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'numpy.float64'>\n",
      "(Iteration 1 / 40) loss: 2.363364\n",
      "(Epoch 0 / 20) train acc: 0.180000; val_acc: 0.108000\n",
      "(Epoch 1 / 20) train acc: 0.320000; val_acc: 0.127000\n",
      "(Epoch 2 / 20) train acc: 0.440000; val_acc: 0.172000\n",
      "(Epoch 3 / 20) train acc: 0.500000; val_acc: 0.184000\n",
      "(Epoch 4 / 20) train acc: 0.540000; val_acc: 0.181000\n",
      "(Epoch 5 / 20) train acc: 0.740000; val_acc: 0.190000\n",
      "(Iteration 11 / 40) loss: 0.839976\n",
      "(Epoch 6 / 20) train acc: 0.740000; val_acc: 0.187000\n",
      "(Epoch 7 / 20) train acc: 0.740000; val_acc: 0.183000\n",
      "(Epoch 8 / 20) train acc: 0.820000; val_acc: 0.177000\n",
      "(Epoch 9 / 20) train acc: 0.860000; val_acc: 0.200000\n",
      "(Epoch 10 / 20) train acc: 0.920000; val_acc: 0.191000\n",
      "(Iteration 21 / 40) loss: 0.337174\n",
      "(Epoch 11 / 20) train acc: 0.960000; val_acc: 0.189000\n",
      "(Epoch 12 / 20) train acc: 0.940000; val_acc: 0.180000\n",
      "(Epoch 13 / 20) train acc: 1.000000; val_acc: 0.199000\n",
      "(Epoch 14 / 20) train acc: 1.000000; val_acc: 0.199000\n",
      "(Epoch 15 / 20) train acc: 1.000000; val_acc: 0.195000\n",
      "(Iteration 31 / 40) loss: 0.075911\n",
      "(Epoch 16 / 20) train acc: 1.000000; val_acc: 0.182000\n",
      "(Epoch 17 / 20) train acc: 1.000000; val_acc: 0.201000\n",
      "(Epoch 18 / 20) train acc: 1.000000; val_acc: 0.207000\n",
      "(Epoch 19 / 20) train acc: 1.000000; val_acc: 0.185000\n",
      "(Epoch 20 / 20) train acc: 1.000000; val_acc: 0.192000\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# TODO: Use a three-layer Net to overfit 50 training examples by \n",
    "# tweaking just the learning rate and initialization scale.\n",
    "\n",
    "num_train = 50\n",
    "small_data = {\n",
    "  \"X_train\": data[\"X_train\"][:num_train],\n",
    "  \"y_train\": data[\"y_train\"][:num_train],\n",
    "  \"X_val\": data[\"X_val\"],\n",
    "  \"y_val\": data[\"y_val\"],\n",
    "}\n",
    "\n",
    "weight_scale = 1e-2   # Experiment with this!\n",
    "learning_rate = 1e-2  # Experiment with this!\n",
    "model = FullyConnectedNet(\n",
    "    [100, 100],\n",
    "    weight_scale=weight_scale,\n",
    "    dtype=np.float64\n",
    ")\n",
    "solver = Solver(\n",
    "    model,\n",
    "    small_data,\n",
    "    print_every=10,\n",
    "    num_epochs=20,\n",
    "    batch_size=25,\n",
    "    update_rule=\"sgd\",\n",
    "    optim_config={\"learning_rate\": learning_rate},\n",
    ")\n",
    "solver.train()\n",
    "\n",
    "plt.plot(solver.loss_history)\n",
    "plt.title(\"Training loss history\")\n",
    "plt.xlabel(\"Iteration\")\n",
    "plt.ylabel(\"Training loss\")\n",
    "plt.grid(linestyle='--', linewidth=0.5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, try to use a five-layer network with 100 units on each layer to overfit on 50 training examples. Again, you will have to adjust the learning rate and weight initialization scale, but you should be able to achieve 100% training accuracy within 20 epochs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'numpy.float64'>\n",
      "(Iteration 1 / 40) loss: 166.501707\n",
      "(Epoch 0 / 20) train acc: 0.220000; val_acc: 0.116000\n",
      "(Epoch 1 / 20) train acc: 0.240000; val_acc: 0.083000\n",
      "(Epoch 2 / 20) train acc: 0.160000; val_acc: 0.104000\n",
      "(Epoch 3 / 20) train acc: 0.520000; val_acc: 0.106000\n",
      "(Epoch 4 / 20) train acc: 0.700000; val_acc: 0.131000\n",
      "(Epoch 5 / 20) train acc: 0.700000; val_acc: 0.116000\n",
      "(Iteration 11 / 40) loss: 4.414592\n",
      "(Epoch 6 / 20) train acc: 0.840000; val_acc: 0.114000\n",
      "(Epoch 7 / 20) train acc: 0.880000; val_acc: 0.108000\n",
      "(Epoch 8 / 20) train acc: 0.900000; val_acc: 0.109000\n",
      "(Epoch 9 / 20) train acc: 0.960000; val_acc: 0.114000\n",
      "(Epoch 10 / 20) train acc: 0.980000; val_acc: 0.127000\n",
      "(Iteration 21 / 40) loss: 0.261098\n",
      "(Epoch 11 / 20) train acc: 1.000000; val_acc: 0.126000\n",
      "(Epoch 12 / 20) train acc: 1.000000; val_acc: 0.124000\n",
      "(Epoch 13 / 20) train acc: 1.000000; val_acc: 0.124000\n",
      "(Epoch 14 / 20) train acc: 1.000000; val_acc: 0.124000\n",
      "(Epoch 15 / 20) train acc: 1.000000; val_acc: 0.125000\n",
      "(Iteration 31 / 40) loss: 0.000594\n",
      "(Epoch 16 / 20) train acc: 1.000000; val_acc: 0.125000\n",
      "(Epoch 17 / 20) train acc: 1.000000; val_acc: 0.125000\n",
      "(Epoch 18 / 20) train acc: 1.000000; val_acc: 0.125000\n",
      "(Epoch 19 / 20) train acc: 1.000000; val_acc: 0.125000\n",
      "(Epoch 20 / 20) train acc: 1.000000; val_acc: 0.125000\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# TODO: Use a five-layer Net to overfit 50 training examples by \n",
    "# tweaking just the learning rate and initialization scale.\n",
    "\n",
    "num_train = 50\n",
    "small_data = {\n",
    "  'X_train': data['X_train'][:num_train],\n",
    "  'y_train': data['y_train'][:num_train],\n",
    "  'X_val': data['X_val'],\n",
    "  'y_val': data['y_val'],\n",
    "}\n",
    "\n",
    "learning_rate = 1e-3  # Experiment with this!\n",
    "weight_scale = 1e-1   # Experiment with this!\n",
    "model = FullyConnectedNet(\n",
    "    [100, 100, 100, 100],\n",
    "    weight_scale=weight_scale,\n",
    "    dtype=np.float64\n",
    ")\n",
    "solver = Solver(\n",
    "    model,\n",
    "    small_data,\n",
    "    print_every=10,\n",
    "    num_epochs=20,\n",
    "    batch_size=25,\n",
    "    update_rule='sgd',\n",
    "    optim_config={'learning_rate': learning_rate},\n",
    ")\n",
    "solver.train()\n",
    "\n",
    "plt.plot(solver.loss_history)\n",
    "plt.title('Training loss history')\n",
    "plt.xlabel('Iteration')\n",
    "plt.ylabel('Training loss')\n",
    "plt.grid(linestyle='--', linewidth=0.5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "pdf-inline"
    ]
   },
   "source": [
    "## Inline Question 1: \n",
    "Did you notice anything about the comparative difficulty of training the three-layer network vs. training the five-layer network? In particular, based on your experience, which network seemed more sensitive to the initialization scale? Why do you think that is the case?\n",
    "\n",
    "## Answer:\n",
    "[FILL THIS IN]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Update rules\n",
    "So far we have used vanilla stochastic gradient descent (SGD) as our update rule. More sophisticated update rules can make it easier to train deep networks. We will implement a few of the most commonly used update rules and compare them to vanilla SGD."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## SGD+Momentum\n",
    "Stochastic gradient descent with momentum is a widely used update rule that tends to make deep networks converge faster than vanilla stochastic gradient descent. See the Momentum Update section at http://cs231n.github.io/neural-networks-3/#sgd for more information.\n",
    "\n",
    "Open the file `cs231n/optim.py` and read the documentation at the top of the file to make sure you understand the API. Implement the SGD+momentum update rule in the function `sgd_momentum` and run the following to check your implementation. You should see errors less than e-8."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "next_w error:  8.882347033505819e-09\n",
      "velocity error:  4.269287743278663e-09\n"
     ]
    }
   ],
   "source": [
    "from cs231n.optim import sgd_momentum\n",
    "\n",
    "N, D = 4, 5\n",
    "w = np.linspace(-0.4, 0.6, num=N*D).reshape(N, D)\n",
    "dw = np.linspace(-0.6, 0.4, num=N*D).reshape(N, D)\n",
    "v = np.linspace(0.6, 0.9, num=N*D).reshape(N, D)\n",
    "\n",
    "config = {\"learning_rate\": 1e-3, \"velocity\": v}\n",
    "next_w, _ = sgd_momentum(w, dw, config=config)\n",
    "\n",
    "expected_next_w = np.asarray([\n",
    "  [ 0.1406,      0.20738947,  0.27417895,  0.34096842,  0.40775789],\n",
    "  [ 0.47454737,  0.54133684,  0.60812632,  0.67491579,  0.74170526],\n",
    "  [ 0.80849474,  0.87528421,  0.94207368,  1.00886316,  1.07565263],\n",
    "  [ 1.14244211,  1.20923158,  1.27602105,  1.34281053,  1.4096    ]])\n",
    "expected_velocity = np.asarray([\n",
    "  [ 0.5406,      0.55475789,  0.56891579, 0.58307368,  0.59723158],\n",
    "  [ 0.61138947,  0.62554737,  0.63970526,  0.65386316,  0.66802105],\n",
    "  [ 0.68217895,  0.69633684,  0.71049474,  0.72465263,  0.73881053],\n",
    "  [ 0.75296842,  0.76712632,  0.78128421,  0.79544211,  0.8096    ]])\n",
    "\n",
    "# Should see relative errors around e-8 or less\n",
    "print(\"next_w error: \", rel_error(next_w, expected_next_w))\n",
    "print(\"velocity error: \", rel_error(expected_velocity, config[\"velocity\"]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Once you have done so, run the following to train a six-layer network with both SGD and SGD+momentum. You should see the SGD+momentum update rule converge faster."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running with  sgd\n",
      "(Iteration 1 / 200) loss: 2.559978\n",
      "(Epoch 0 / 5) train acc: 0.104000; val_acc: 0.107000\n",
      "(Iteration 11 / 200) loss: 2.356069\n",
      "(Iteration 21 / 200) loss: 2.214091\n",
      "(Iteration 31 / 200) loss: 2.205928\n",
      "(Epoch 1 / 5) train acc: 0.225000; val_acc: 0.193000\n",
      "(Iteration 41 / 200) loss: 2.132095\n",
      "(Iteration 51 / 200) loss: 2.118950\n",
      "(Iteration 61 / 200) loss: 2.116443\n",
      "(Iteration 71 / 200) loss: 2.132549\n",
      "(Epoch 2 / 5) train acc: 0.298000; val_acc: 0.260000\n",
      "(Iteration 81 / 200) loss: 1.977227\n",
      "(Iteration 91 / 200) loss: 2.007528\n",
      "(Iteration 101 / 200) loss: 2.004762\n",
      "(Iteration 111 / 200) loss: 1.885307\n",
      "(Epoch 3 / 5) train acc: 0.342000; val_acc: 0.287000\n",
      "(Iteration 121 / 200) loss: 1.891413\n",
      "(Iteration 131 / 200) loss: 1.924095\n",
      "(Iteration 141 / 200) loss: 1.957629\n",
      "(Iteration 151 / 200) loss: 1.964866\n",
      "(Epoch 4 / 5) train acc: 0.320000; val_acc: 0.305000\n",
      "(Iteration 161 / 200) loss: 1.801929\n",
      "(Iteration 171 / 200) loss: 1.971967\n",
      "(Iteration 181 / 200) loss: 1.661503\n",
      "(Iteration 191 / 200) loss: 1.908354\n",
      "(Epoch 5 / 5) train acc: 0.367000; val_acc: 0.320000\n",
      "Running with  sgd_momentum\n",
      "(Iteration 1 / 200) loss: 3.153778\n",
      "(Epoch 0 / 5) train acc: 0.099000; val_acc: 0.088000\n",
      "(Iteration 11 / 200) loss: 2.227203\n",
      "(Iteration 21 / 200) loss: 2.125322\n",
      "(Iteration 31 / 200) loss: 1.933623\n",
      "(Epoch 1 / 5) train acc: 0.300000; val_acc: 0.259000\n",
      "(Iteration 41 / 200) loss: 1.951480\n",
      "(Iteration 51 / 200) loss: 1.778344\n",
      "(Iteration 61 / 200) loss: 1.759060\n",
      "(Iteration 71 / 200) loss: 1.865580\n",
      "(Epoch 2 / 5) train acc: 0.391000; val_acc: 0.325000\n",
      "(Iteration 81 / 200) loss: 1.997256\n",
      "(Iteration 91 / 200) loss: 1.675952\n",
      "(Iteration 101 / 200) loss: 1.539517\n",
      "(Iteration 111 / 200) loss: 1.437328\n",
      "(Epoch 3 / 5) train acc: 0.473000; val_acc: 0.340000\n",
      "(Iteration 121 / 200) loss: 1.660325\n",
      "(Iteration 131 / 200) loss: 1.495063\n",
      "(Iteration 141 / 200) loss: 1.632314\n",
      "(Iteration 151 / 200) loss: 1.686809\n",
      "(Epoch 4 / 5) train acc: 0.495000; val_acc: 0.337000\n",
      "(Iteration 161 / 200) loss: 1.495089\n",
      "(Iteration 171 / 200) loss: 1.432442\n",
      "(Iteration 181 / 200) loss: 1.364615\n",
      "(Iteration 191 / 200) loss: 1.294965\n",
      "(Epoch 5 / 5) train acc: 0.539000; val_acc: 0.368000\n"
     ]
    },
    {
     "data": {
      "image/png": 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79myeffZZCgsLKSkpYdq0aXz11VeA0ety7NgxwAhgfvjhB8rLyykuLubnn3/utvPvTk5W19OnT+eHH36grKyM0tJSvv/+e6ZPn273/qeffjqvvPKKMVwV2L59e7v7uLi41AfXoaGhZGdnk5eXR2VlJQsXLuzciXQCPYTSXtx8cC0rUN2KXktoaKjqJvRqtH91aPdq0f7Vov2r40TXwjr//PNZv349o0aNQgjBv//9b8LCwvjwww957rnncHFxwcvLi48++oi0tDSuv/76+t6Op59+2uYxa2trueqqqygsLERKyd/+9jf8/Px49NFHufzyy/n444+ZMmUKYWFheHt7M3bsWC699FJGjRpFSEgIEyZMOKHn3BG60v/J6nrs2LFcd911TJw4ETCSmIwZM6bduWl1PPLII9x5552MHDkSi8VCv379WLhwYZtDh2+++WZGjhzJ2LFj+fTTT/nHP/7BxIkTiYiIYPDgwcd9TvYi6qLOnsT48ePlli1bVDejKd/9maqElbjeF6+6Jb2S+Pj4bv2PoWmK9q8O7V4t2r9atP+uZf/+/QwZMsSubcvLy3F3dz/BLeoeKisrcXJywtnZmfXr13PrrbfWJ6LoqTiqf0d03RxV7m39/xRCbJVSjm++re6BsxezL841Zapb0WsJCAhQ3YRejfavDu1eLdq/WrR/dZxMdciSk5O55JJLsFgsuLq68r///U91k9rFUf07ouvmOIL7nt/CnoLZB1FVDBaLUVZA06046iTkkwXtXx3avVq0f7Vo/+roiSO0GnPbbbexdu3aJsvuuOMOrr/++hbbDhgwwK75TT2JnuT/RLruyLG7i57kvjV0AGcvZl+EtEBVCZh9VLem11FUVER4eLjqZvRatH91aPdq0f7Vov13PfbWd6utre2G1nSe1157TXUTTig9yf+JdN0T30cV7jsaNOquJHtxswZtlUVq29FLiY6OVt2EXo32rw7tXi3av1q0/67FbDaTl5dn181i47Tnmu5H+1dHd7uXUpKXl4fZbLZ7H90DZy9mo5gfFYXgG6m2Lb2QpKQkPZFdIdq/OrR7tWj/atH+u5bIyEhSU1PJyclpd9vq6uoTnolS0zravzpUuDebzURG2h9ftBvACSHMwCrAzbr9N1LKR5tt4wZ8BIwD8oBLpZSJ1nUPAjcCtcDfpJS/2d26nkR9AKd74FTg6uqqugm9Gu1fHdq9WrR/tWj/XYuLiwv9+vWza9sjR44QGxt7glukaQ3tXx2O4N6eIZSVwBwp5ShgNDBfCDG52TY3AseklP2B/wDPAgghhgKXAcOA+cDrQojWiyv0ZOrmvVUUqm1HLyUoKEh1E3o12r86tHu1aP9q0f7Vod2rRftXhyO4bzeAkwYl1qcu1n/NB0+fC3xoffwNMFcYM2TPBb6QUlZKKY8Ch4GJXdLy7sbsZ/zVAZwS0tPTVTehV6P9q0O7V4v2rxbtXx3avVq0f3U4gnu75sBZe822Av2B16SUG5ttEgGkAEgpa4QQhUCgdfmGRtulWpfZeo2bgZvBGKMdHx9PeHg4ubm5VFVVER0dTVJSEj4+Pjg7O5Ofn09ERARZWVlYLBYiIyNJTk7Gz88PgIKCAqKiokhNTcVkMhEaGkpaWhoBAQHU1NRQVFRUf0xXV1eCgoJIT08nKCiIiooKSkpK6tebzWb8XSW+QGl+BnnJyZSVldWv9/DwwMvLi+zsbMLCwigoKKCioqJ+vZeXF2azmdzc3B51Tn5+fmRmZhISEkJJSUmPPqeysjKOHDlyUp2TI71PZWVllJWVnVTn5CjvU1lZGenp6SfVOTnS+1RWVkZ5eflJdU6O9D65urqSrL9zlZxTVVUVRUVFJ9U5OdL75OXlxcGDB0+qc3KU9wkgOzu7R5xTa4iOpK0UQvgB3wO3Syn3NFq+B5gvpUy1Pk8AJgGPARuklJ9Yl78LLJZSftPW64wfP15u2bLF7nZ1CzWV8K8QmPMwzLhPdWt6HampqR2a3KnpWrR/dWj3atH+1aL9q0O7V4v2r46e5F4IsVVKOb758g6VEZBSFgDLMeazNSYN6Gt9IWfAFyOZSf1yK5HWZY6HsxsWJzedxEQRJSUl7W+kOWFo/+rQ7tWi/atF+1eHdq8W7V8djuC+3QBOCBFs7XlDCOEOnArEN9vsJ+Ba6+OLgGXS6Nr7CbhMCOEmhOgHDAA2dVHbux1h9tVz4BShawGpRftXh3avFu1fLdq/OrR7tWj/6nAE9/b0wPUBlgshdgGbgSVSyoVCiMeFEAus27wLBAohDgN3Aw8ASCn3Al8B+4BfgduklD2ntHwHqXLy0AGcIurGJGvUoP2rQ7tXi/avFu1fHdq9WrR/dTiC+3aTmEgpdwFjbCz/R6PHFcDFrez/JPDkcbSx5+DqDZV6CKUKOlKdXtP1aP/q0O7Vov2rRftXh3avFu1fHY7gvkNz4Ho7Js8A3QOniLqMPxo1aP/q0O7Vov2rRftXh3avFu1fHY7gXgdwHaDc4qKTmCgiMzNTdRN6Ndq/OrR7tWj/atH+1aHdq0X7V4cjuNcBXAdw9Q3WPXCKCAkJUd2EXo32rw7tXi3av1q0f3Vo92rR/tXhCO51ANcBqoRZz4FThCOkdD2Z0f7Vod2rRftXi/avDu1eLdq/OhzBvQ7gOkAlZqipgOoK1U3pdbRVjV5z4tH+1aHdq0X7V4v2rw7tXi3avzocwb0O4DqAb1iU8UD3wnU7jlCT42RG+1eHdq8W7V8t2r86tHu1aP/qcAT3OoDrALnFVcYDncik23GEmhwnM9q/OrR7tWj/atH+1aHdq0X7V4cjuNcBXAdw9g4yHuhEJt2Oh4eH6ib0arR/dWj3atH+1aL9q0O7V4v2rw5HcK8DuA5g9g02HlTqAK678fLyUt2EXo32rw7tXi3av1q0f3Vo92rR/tXhCO51ANcBcktqjAe6B67byc7OVt2EXo32rw7tXi3av1q0f3Vo92rR/tXhCO51ANcBAiNijQc6gOt2wsLCVDehV6P9q0O7V4v2rxbtXx3avVq0f3U4gnsdwHWAggqL8UAnMel2CgoKVDehV6P9q0O7V4v2rxbtXx3avVq0f3U4gnsdwHWA8hoTCJPugVNARYWuvacS7V8d2r1atH+1aP/q0O7Vov2rwxHc6wCuA0THxICbj64DpwBHqMlxMqP9q0O7V4v2rxbtXx3avVq0f3U4gnsdwHWApKQkMPvqHjgFOEJNjpMZ7V8d2r1atH+1aP/q0O7Vov2rwxHc6wCuA3h5eVkDON0D1904QkrXkxntXx3avVq0f7Vo/+rQ7tWi/avDEdzrAK4DmM1m3QOnCLPZrLoJvRrtXx3avVq0f7Vo/+rQ7tWi/avDEdzrAK4D5Obm6gBOEbm5uaqb0KvR/tWh3atF+1eL9q8O7V4t2r86HMG9DuA6QHh4uE5ioojw8HDVTejVaP/q0O7Vov2rRftXh3avFu1fHY7gvt0ATgjRVwixXAixTwixVwhxh41t7hNC7LD+2yOEqBVCBFjXJQohdlvXbTkRJ9Fd6B44dTjCryEnM9q/OrR7tWj/atH+1aHdq0X7V4cjuHe2Y5sa4B4p5TYhhDewVQixREq5r24DKeVzwHMAQohzgLuklPmNjjFbStnzbbRDVVWVEcBVFoPFAibdgdldVFVVqW5Cr0b7V4d2rxbtXy3avzq0e7Vo/+pwBPftRiBSygwp5Tbr42JgPxDRxi6XA593TfN6FtHR0WD2AaQeRtnNOEJNjpMZ7V8d2r1atH+1aP/q0O7Vov2rwxHc29MDV48QIgYYA2xsZb0HMB/4a6PFEvhdCCGBt6SUb7ey783AzQCRkZHEx8cTHh5Obm4uVVVVREdHk5SUhI+PD87OzuTn5xMREUFWVhYWi4XIyEiSk5Px8/MDoKCggKioKFJTUzGZTISGhpKWlkZAQAA1NTUUFRXVH9PV1ZWgoCDS09MJCgqioqKCkpKS+vVmsxk/Pz/27NnDaJzxAhL2biN82BSSkpLw8PDAy8uL7OxswsLCKCgooKKion5/Ly8vzGYzubm5Pe6cMjMzCQkJoaSkhLKysvr1Pe2ctm7dSnh4+El1To70Ph0+fJixY8eeVOfkKO/T1q1biY2NPanOyZHep9TUVMaNG3dSnZMjvU/l5eUEBgaeVOfkKO/TsWPHGDZs2El1To70PlVXV+Pm5nZSnZOjvE/FxcVER0f3iHNqDSGlbHVlswDLC1gJPCml/K6VbS4FrpJSntNoWYSUMk0IEQIsAW6XUq5q67XGjx8vt2zpedPl0tPTCS/YAl9dDbesgbARqpvUa0hPT3eISaUnK9q/OrR7tWj/atH+1aHdq0X7V0dPci+E2CqlHN98uV2TuIQQLsC3wKetBW9WLqPZ8EkpZZr1bzbwPTDR3kb3NJydnY05cKATmXQzzs4d6izWdDHavzq0e7Vo/2rR/tWh3atF+1eHI7i3JwulAN4F9kspX2xjO19gJvBjo2We1sQnCCE8gdOAPcfbaFXk5+db58ABFXoOXHeSn5/f/kaaE4b2rw7tXi3av1q0f3Vo92rR/tXhCO7tCTGnAVcDu4UQO6zLHgKiAKSUb1qXnQ/8LqUsbbRvKPC9EQPiDHwmpfy1C9qthIiICKjOMZ7oHrhuJSKirbw5mhON9q8O7V4t2r9atH91aPdq0f7V4Qju2w3gpJRrAGHHdh8AHzRbdgQY1cm29TiysrLwDg8wnugArlvJysrC29tbdTN6Ldq/OrR7tWj/atH+1aHdq0X7V4cjuNeFzDqAxWIBN+sbqssIdCsWi0V1E3o12r86tHu1aP9q0f7Vod2rRftXhyO41wFcB4iMjAQnF3Dx1D1w3UxkZKTqJvRqtH91aPdq0f7Vov2rQ7tXi/avDkdwrwO4DpCcnGw8MPvoAK6bqXevUYL2rw7tXi3av1q0f3Vo92rR/tXhCO51ANcB6gr3YfbVAVw3U+9eowTtXx3avVq0f7Vo/+rQ7tWi/avDEdzrAK4zmH31HDiNRqPRaDQajUbT7egArgMUFBQYD9z0EMrupt69Rgnavzq0e7Vo/2rR/tWh3atF+1eHI7jXAVwHiIqKMh7oIZTdTr17jRK0f3Vo92rR/tWi/atDu1eL9q8OR3CvA7gOkJqaajww+0CFHkLZndS71yhB+1eHdq8W7V8t2r86tHu1aP/qcAT3OoDrACaTVVddD5yUahvUi6h3r1GC9q8O7V4t2r9atH91aPdq0f7V4Qjue34LexChoaHGAzcfsFRDTYXaBvUi6t1rlKD9q0O7V4v2rxbtXx3avVq0f3U4gnsdwHWAtLQ0AIrwBKCq5JjK5vQq6txr1KD9q0O7V4v2rxbtXx3avVq0f3U4gnsdwHWAgIAAsosq+O+aLAB2JSQpblHvISAgQHUTejXavzq0e7Vo/2rR/tWh3atF+1eHI7jXAVwHyCos5/L/bWBvuR8AxxJ3qW1QL6KmpkZ1E3o12r86tHu1aP9q0f7Vod2rRftXhyO41wGcneSWVHLbtwdIL6jg7msvoxR3PFJXq25Wr6GoSGf9VIn2rw7tXi3av1q0f3Vo92rR/tXhCO51AGcHeSWVXPG/DWSX1PLedROYGBfCIffR9CvaorppvYbo6GjVTejVaP/q0O7Vov2rRftXh3avFu1fHY7gXgdwdlBRY0EgeGxuKFPiAgHIC51KuCWDypyjilvXO0hK0vMNVaL9q0O7V4v2rxbtXx3avVq0f3U4gnsdwNlBhJ87i+6YzsRov/plLgNmA5Cz63dFrepduLq6qm5Cr0b7V4d2rxbtXy3avzq0e7Vo/+pwBPc6gLMTJ5MgKCio/nnUwDFkST9qE5YrbFXvobF7Tfej/atDu1eL9q8W7V8d2r1atH91OIL7dgM4IURfIcRyIcQ+IcReIcQdNraZJYQoFELssP77R6N184UQB4QQh4UQD3T1CXQn6enp9Y+jAj3ZyAiCsteDxaKwVb2Dxu413Y/2rw7tXi3av1q0f3Vo92rR/tXhCO6d7dimBrhHSrlNCOENbBVCLJFS7mu23Wop5dmNFwghnIDXgFOBVGCzEOInG/s6BI0jcpNJkOQ7Ac+i1ZC9F8JGKGzZyY8j/BpyMqP9q0O7V4v2rxbtXx3avVq0f3U4gvt2e+CklBlSym3Wx8XAfiDCzuNPBA5LKY9IKauAL4BzO9tY1VRUVDR9HjkdAEvCCgWt6V00d6/pXrR/dWj3atH+1aL9q0O7V4v2rw5HcN+hOXBCiBhgDLDRxuopQoidQojFQohh1mURQEqjbVKxP/jrcZSUlDR5HhnTn8OWcCoPLlPUot5Dc/ea7kX7V4d2rxbtXy3avzq0e7Vo/+pwBPf2DKEEQAjhBXwL3CmlbF7hbhsQLaUsEUKcCfwADOhIQ4QQNwM3A0RGRhIfH094eDi5ublUVVURHR1NUlISPj4+ODs7k5+fT0REBFlZWVgsFiIjI0lOTsbPzw+AgoICoqKiSE1NxWQyERoaSlpaGgEBAdTU1FBUVFR/TFdXV4KCgkhPTycoKIiKigpKSkrq15vNZvz8/KiuriY/P5+SkhLKysqIC/BnrWUYV6asJj8nk+y8AsLCwigoKKCioqJ+fy8vL8xmM7m5uT3unDIzMwkJCak/p7r1Hh4eeHl5kZ2d3SPOqbq6miNHjpxU5+RI71N1dTVlZWUn1Tk5yvtUXV1Nenr6SXVOjvQ+VVdXU15eflKdkyO9T76+viQnJ59U5+Qo75MQgqKiopPqnBzpfQoJCeHgwYMn1Tk5yvtkNpvJzs7uEefUatwkpbQnuHIBFgK/SSlftGP7RGA8RhD3mJTydOvyBwGklE+3tf/48ePlli09r0h2fHw8gwcPrn9eUV3LHY89wVsu/4HrF0P0VJAS9v8MJVkw6jJw81bY4pOH5u413Yv2rw7tXi3av1q0f3Vo92rR/tXRk9wLIbZKKcc3X95uD5wQQgDvAvtbC96EEGFAlpRSCiEmYgzNzAMKgAFCiH5AGnAZcEWnz0IxZrO56XMXJzIDJmApNmE6sgK8QuGXu+HICmOD5U/BlNtg4s1g9un29p5MNHev6V60f3Vo92rR/tWi/atDu1eL9q8OR3Bvzxy4acDVwJxGZQLOFELcIoS4xbrNRcAeIcRO4GXgMmlQA/wV+A0j+clXUsq9J+A8uoW6LtPGRIeHs1/0hy3vwetTIG0bnPk83LgUIifAsifgpRGw78fub/BJhC33mu5D+1eHdq8W7V8t2r86tHu1aP/qcAT37fbASSnXAKKdbV4FXm1l3SJgUada18PIzMxs8aYODffh9z0jGCa/heEXwulPgXeYsfLKr4yA7oe/wJJHYcgCEG2q1LSCLfea7kP7V4d2rxbtXy3avzq0e7Vo/+pwBPcdykLZ2wkJCWmxbEgfH96oXcD2BUvgovcagrc6IsYawyiPHYX0bd3U0pMPW+413Yf2rw7tXi3av1q0f3Vo92rR/tXhCO51ANcBbKUVHdrHhypc2FYW3PqOQ84BJ1fY/e0JbN3JjSOkdD2Z0f7Vod2rRftXi/avDu1eLdq/OhzBvQ7gOoCtdJ7B3m4Ee7uxP6N5ZYVGuPtB/1Nh73dgqT1xDTyJaSuVqubEo/2rQ7tXi/avFu1fHdq9WrR/dTiCex3AdYDo6Giby4f28WFXagF70gpZFp/Fl5uT2XQ0v+lGwy+A4gxIXt8NLT35aM29pnvQ/tWh3atF+1eL9q8O7V4t2r86HMG9DuA6QFJSks3lw8J9OJhVwtmvrOGGD7Zw/7e7ufTt9Xyw9mjDRoPOABcP2P1NN7X25KI195ruQftXh3avFu1fLdq/OrR7tWj/6nAE9+1modQ04OHhYXP5jaf0IyrAA39PV4K93Qj0dOVfv+znsZ/3kVdaxd2nDkS4esKgM41yAmc+B04u3dx6x6Y195ruQftXh3avFu1fLdq/OrR7tWj/6nAE97oHrgN4eXnZXB7o5cZlE6M4fVgYY6P8iQ705I0rx3Lp+L68suwwD32/m5paC4y4CMrzGwp9a+ymNfea7kH7V4d2rxbtXy3avzq0e7Vo/+pwBPc6gOsA2dnZdm/r7GTimQtH8NfZ/fl8UwqP/rQX4uaA2VcPo+wEHXGv6Xq0f3Vo92rR/tWi/atDu1eL9q8OR3Cvh1B2gLCwsPY3aoQQgntPH0R5dS3vrjnKheMiGTtkAez9HqrLwcX9BLX05KOj7jVdi/avDu1eLdq/WrR/dWj3atH+1eEI7nUPXAcoKCjo1H53nTqQUB83/vHjHmqHXQRVJbDyWSjLb3/ndiirqjGGZ57kdNa9pmvQ/tWh3atF+1eL9q8O7V4t2r86HMG9DuA6QEVFRaf283Jz5uGzhrInrYjPc6Igdhas+Q+8MAi+uhYOLQUpO3TM5LwyHv5hN2MeX8IjP+7pVLscic6613QN2r86tHu1aP9q0f7Vod2rRftXhyO4F7KDgUN3MH78eLllyxbVzWhBeXk57u6dG/YopeTKdzayN72I5ffOIqD4AGz/FHZ9aSQ2GXkZLHiZ5QmFPPrjXi4cG8l1U2Pw9WjIVmmxSLanFPDhukQW7krHySSICvAgOb+MtffPIcTH3FWn2uM4Hvea40f7V4d2rxbtXy3avzq0e7Vo/+roSe6FEFullOObL9c9cB3geOpCCCH454JhlFbW8O9f4yFsBJzxDNwTD7Megl1fUPPheTz1zVoKyqr4z9KDnPLsMp77LZ51h3N5/Od9THt2GRe+sY5l8dn8aXosa+6fw7vXTqDGIvl4Q8+vWXE8OEJNjpMZ7V8d2r1atH+1aP/q0O7Vov2rwxHc6yQmHeB404oOCPXm+mkxvLPmKBeNi2R8TAA4u8Gs+yEgFr6/lTdrj1J16VdI/xheW3GY11ck8NryBFydTcwYEMx9pw9i3tBQfMwNPXPzhoTy6cZkbpvdH7OLU5PXrK614OLk+HG6I6R0PZnR/tWh3atF+1eL9q8O7V4t2r86HMG949/ZdyNm8/EPUbxj3kAi/d25/oPNbElsSGKy2WcuV1Q8QB+XUoYsuoCh/rW8dsVYltw1k7euHsfWh+fxzrXjuWBsZJPgDYxC4vmlVXy/Pa3J8h93pDH6n7+zOfH4k6WopivcazqP9q8O7V4t2r9atH91aPdq0f7V4QjudQDXAXJzc4/7GF5uznx58xSCvdy4+t1NrD6UQ2VNLQ98u4s037GIyz6B0hxIWAZA/xAvTh8WhnezoK0xk/oFMCzch3fXHKVuTuP25GPc980uSqtqeXvVkeNut2q6wr2m82j/6tDu1aL9q0X7V4d2rxbtXx2O4F4HcB0gPDy8a47j586Xf55CdKAHN36whds+3UZCTilPnj8c97hTjGLf1gDOHoQQ3DS9H4ezS1h5MIf0gnL+9NFWwnzMXDEpij/2Z5GSX9YlbVdFV7nXdA7tXx3avVq0f7Vo/+rQ7tWi/avDEdzrAK4DdGVEHuztxpc3T2FouA9L92dz3uhwZg0KAZOTUWYgYXmHSgucNSKcEG833lyZwJ8+2kJFdS3vXDuev87ujxDC4ZOcOMKvIScz2r86tHu1aP9q0f7Vod2rRftXhyO41wFcB6iqqurS4/l6uPDpTZP4x9lD+eeC4Q0r4uZAURrkHrT7WK7OJq6dGsOGI/nsyyji5ctHMzDUm3A/d+YPC+OLTcmUVdV0Wduziyt47rd4Kqpru+yYbdHV7jUdQ/tXh3avFu1fLdq/OrR7tWj/6nAE9+0GcEKIvkKI5UKIfUKIvUKIO2xsc6UQYpcQYrcQYp0QYlSjdYnW5TuEED2vuFsHiI6O7vJjero5c8Mp/ZrUeyN2tvG3A8MoAa6YGEX/EC8ePXsocwaH1i+/dmoMRRU1/LA9vSuajJSSe77ayWvLE1i8J6NLjtkeJ8K9xn60f3Vo92rR/tWi/atDu1eL9q8OR3BvTw9cDXCPlHIoMBm4TQgxtNk2R4GZUsoRwBPA283Wz5ZSjrZViM6R6La6EP7RENi/wwGcv6crS++eyXXT+jVZPiHGn6F9fPhgXUOSk+bUWiRPL9rPB2uPtvs6H29IYvWhXJxNgl92ZXaojZ3FEWpynMxo/+rQ7tWi/atF+1eHdq8W7V8djuC+3QBOSpkhpdxmfVwM7Acimm2zTkp5zPp0AxDZ1Q3tCfj4+HTfi8XNgcQ1UFN53IcSQnDd1BgOZpWw/khei/VSSh7+YTdvrTrCy8sOU2tpfe5dQk4JTy3az8yBwVwzJYZVB3Moqqg+7jYClFbWsGh3Bnd+sZ0Fr64hKa+0fl23ute0QPtXh3avFu1fLdq/OrR7tWj/6nAE9x0q5C2EiAHGABvb2OxGYHGj5xL4XQghgbeklM175+qOfTNwM0BkZCTx8fGEh4eTm5tLVVUV0dHRJCUl4ePjg7OzM/n5+URERJCVlYXFYiEyMpLk5GT8/PwAKCgoICoqitTUVEwmE6GhoaSlpREQEEBNTQ1FRUX1x3R1dSUoKIj09HSCgoKoqKigpKSkfr3ZbMbPz4+MjAzMZjMlJSWUlZXVr/fw8MDLy4vs7GzCwsIoKCigoqKifr2Xlxdms5nc3Fy7z8ndPIiI6jKS136N66B59ecU7e9CVtJBagIGdOicxgVLfNxMvLsqgYDq3Cbn9Onecj7fksHQEDP7siv4cc1OxscEtDinkrJyHlyag4sJ7poazLEqeG+thZ+3JjKlj1On3yevwDAe+GYHm1LLqKo12lkrBde9u4Hn54cxdEAsGRkZVFRUtPs++fr68sX6w5w2MgoXS+UJf5+669rLzMwkJCSkW649W+eUkZGBn5/fSXVOjvI+ZWQYw5RPpnNypPcpLy8Pf3//k+qcHOl9cnFxITk5+aQ6J0d5nyorK/Hy8jqpzsmR3icPDw8OHjx4Up2To7xPUsoec06tIVobUmcjwPICVgJPSim/a2Wb2cDrwClSyjzrsggpZZoQIgRYAtwupVzV1muNHz9ebtnS86bLxcfHM3jw4O55scpieDYGpt4O8x4zllUUwpunQEEyhI2A0VfCiIvBM8iuQz73WzyvLU9geIQP54+JZMGocD7dmMRLSw9x3dQY7jp1IOOeWMKfZsRy//yW5/nS0oO8tPQQr10xlrNG9kFKybRnljE03Id3rp3QqdMsq6rh8v9tJD6jiCsmRXHa0DAmxPizKTGfa97dxCkDgnj32gkcOnjALvd70go5+5U1nDc6nJcuG9OpNmla0q3XvqYJ2r1atH+1aP/q0O7Vov2roye5F0JstTUFza4slEIIF+Bb4NM2greRwDvAuXXBG4CUMs36Nxv4HpjY8eb3DCIiItrfqKtw84bIiU3nwS26DwrTYMb/gckZfn0AXhgE390MeQntHvJvcwfwyNnG9MUnFu5j0lNL+O/SA1w0LpJ/nD0UX3cXJsQEsGx/dot9E3NLeWXZYc4bHc5ZI/sAxtDMM0f0YdXB3E4No6yutXDbp9vYnVrAq1eM5dFzhjElLhBnJxNT44L457nDWHEgh6cW7bfb/c87jUQtP+1M53B2SYfb1BZlVTX8/fvdTYZ22ktVjYX9GUVsPJLHpqP5bEnMZ3vyMapqLF3axhNFt177miZo92rR/tWi/atDu1eL9q8OR3Df7hBKIYQA3gX2SylfbGWbKOA74Gop5cFGyz0Bk5Sy2Pr4NODxLmm5ArKysvD29u6+F4ybA8v/BaW5Rl24XV/CrIdg1v0w5++QtQ+2fwxb3ofd38Coy2HmfeAfY/Nwbs5O3HhKP248pR+Hsoop++YvhJbGE3zhJkwmAcDcISH865f9pOSX0TfAo37fjzckIYAHzxzS5JhnjuzDO2uOsnRfFheMbZj6eDS3lBUHsqmqsVBda6GqVtLX352Zg4IJ8TYjpeSh73az/EAOT50/glOHhtKcKydFcyirhHfXHMWXMv52dts5cCwWyc870xkf7c/e9CJeWXaI/3ZhL9y7q4/y6cZkQrzN3DFvQJvbSilZvCeT3/dmEp9ZzOHsEmpszC38y6w4/s9Gb2dPo9uvfU092r1atH+1aP/q0O7Vov2rwxHc2zMHbhpwNbBbCLHDuuwhIApASvkm8A8gEHjdiPeosXb3hQLfW5c5A59JKX/tyhPoTiyWbu4tqQvgtn0Ea/4DfSfB9Hsa1ocOhflPw7Q7jfVb3oNdX8DlX8KAeW0eekDGQsj5yXhSnAa+RvA1d0go//plP8vis7l2agxg9Dx9tSWF+cPDCPUxNznOmL5+RPi588uujPoALiGnhIveWMexMtu9ciMifAnzNbNkXxZ/mzuAKyZFtdrOh88awpHcUl5am0VISDKXTWx9263Jx0gvrOD+MwazL6OIt1cd4fY5/ekf0vCfMK2gnBUHsrl0fF+cnewvg5hTXMmbK41ezu0px9rcdtPRfJ5ctJ+dKQWEeLsxPMKXOYNDGBTmTZCXG1KCRPLmygS+2pLKXacOxKUDbVFBt1/7mnq0e7Vo/2rR/tWh3atF+1eHI7hvN4CTUq4BRDvb3ATcZGP5EWBUyz0ck8jIbk6uGT4azH7wxz/B1RsueBucbLxl3qFwxjPGfLl3T4MNr7cdwOUehl/uAf9+cOwoJG+AERcB0C/Ik9ggT/5oFMD9sD2d4oqa+ueNMYZRhvHBukQKy6upqK7lmnc34WQS/HbnDPoGuOPiZMJJCPZnFrHiQA7L47P5Y38Wl0+M4q52erKcnUy8ceVY/vzRZh74bjc5xZX8dU5/rD8KNOGnHemYXUzMGxLK9AHBfLw+if/+cZhXLjd64Q5nl3DVOxvJLKpgeXwOr14xBrOLU5uvX8fLfxyiosbC5NgAticXYLHI+l7Leq0llTz43W6W7MsizMfMvy8ayYVjI3Ey2f7vU1lt4aaPtrA8PpvThoXZ1Q5VdPu1r6lHu1eL9q8W7V8d2r1atH91OIL7nv2zfw8jOTm5e1/Q5ASxs4zHZz3f6tDIenwjYNSlcGQ5FGfZ3qamEr65Hpzd4NqfwMXTCOAaMXdICBsS8iiprEFKyUfrExnSx4fx0f42D3nmiD5U10q+25bKte9toqCsig+un8igMG88XJ1xcTJhMgmGhfty2+z+fHPrVPb+cz5PnT/cZiDWHE83Zx6Y5sf5YyJ4YclBHv1pb4tSBzW1FhbtzmDekFA83ZwJ8HTl2qkxLNyVzsGsYvamF3LpW+upsUj+MiuOpfuzuP79zZRU1rT7+gk5JXy2KZkrJkZxwZhICsurOWpjHtxryw+z4kA2950+iOX3zuKS8X1bDd4AZg0KJsTbja+2pLTbBtV0+7WvqUe7V4v2rxbtXx3avVq0f3U4gnsdwHWAurSh3crM/4OzXoCRl9q3/chLQVpgz7e21y95FDJ3wXmvg18U9J3QIoCbMziUqloLOzavYdvBJOIzi7lmSnSrwdZo6zDKxxfuIyGnhLeuHs/wCN82m+nu6mRX8FZHUIA/L1w8iptnxPLR+iTu/moHlkZB3NqEPPJKq1gwKrx+2c3TY/FwceLB73Zz+dsbcHM28dWfJ/N/8wfz0qWj2ZSYzxX/20B+aVWbr/3vX+MxO5v429wBjI32A2BbUsthlKsP5TI5NpDbZvfH3bX9nj1nJxMXjotkWXw2WUUVdppQg5JrXwNo96rR/tWi/atDu1eL9q8OR3CvA7ieTugwmHAT2BvsBA+CPqONuXDNObQUNr4Bk26BQWcYy6KmQNYeo0SBlfEx/vQxVzHxj0uwLLwLH7Mz544Ob3k8K0IIzhkVjpTw/MWjOGWAfWUNOorJJHjozCHcd/ogftyRztOL99ev+3FHGj5mZ2YOCq5f5u/pynXTYtiadIwAT1e+umUKscFeAJw3JoK3rhrHgcxirnlvY5NgsDGbE/P5bW8Wt8yMI9jbjdggL3zMzmxPKWiyXUZhOYezS5gxINjmcVrjkvF9sUj4Zmtqk+XxmUX87fPtvL0qgV2pBdTU9vzx2BqNRqPRaDSaE48O4DpAQUGB6ibYx8hLIWMnZMc3LKuphEX3QuAAOLVRItCoyYCElM31i1ycTPy5z2FcZSWji1Zyw0gzHq5tT5e8+9SBLLlrBueOPjGpVxu7/8usOK6ZEs3/Vh/lg7VHqaiu5fe9WcwfHoabc9Oer1tmxnH3qQP56s9TiPT3aLJu3tBQnjp/BHvSiliyv+WQUyklTy3aT4i3GzdO7wcYQeToKP8WPXCrD+UCdDh47RfkycR+AXy9JYW6mozpBeVc+94mft2byVOL4lnw6lrGPL6Eh77fjb11G7sah7n2u4HC8mrmv7SKLYn53fJ62r1atH+1aP/q0O7Vov2rwxHc6wCuA0RFtZ4BsUcx4iIQTrD7q4Zl618zEpac8awx/62OyAnGtsnrmxzidNZTID1xwsJ1bsvbfUlXZxMDQk9cytXG7oUQPHrOME4dGso/F+7jHz/uoaSyhgWjIkBKWP0CHEsCwNvswt/mDiCkWfbMOs4dHU7fAHfeWJHQIjhavCeT7ckF3HPawCYB7Ji+fhzMKm4yf271oVyCvNwYHNZxB5eO70tiXhkbj+ZTWF7Nde9voqyylp//egqbHprLfy8bzYyBwXy2MZmlNmr0dYbKmtoObe8w1343sD4hl/jMYn7dk9ktr6fdq0X7V4v2rw7tXi3avzocwb0O4DpAampq+xv1BLxCIG427PoaLBYoSodVz8Pgs6H/3KbbunpCn1FN58FVFhOWvYYfLaewy2Mifvs+hZpm88SSN8CbpxiFxbuB5u6dTIKXLxvDqEg/vtqSSpCXG1PiAiHvMPzxOGz/xK7jOjuZuHlGHDtSCth4tKFHparGwrO/xjMw1IuLxvVtss+YKD8sEnZZh1FaLJK1h3OZPiCoQ/P66jhzRB+83Zz5ZEMSt36ylaO5pbx19TgGhXkT4mPm3NER/Pey0UQHevCfJQfb7YWrqbXw655MCsttl3H4ZEMSIx77nQ/XJdrdo+cw1343sOGIcZ1sTW67nERXod2rRftXi/avDu1eLdq/OhzBvQ7gOoDJ5EC6Rl4KhclGz9qSR8FSA6f9y/a2UVMgbUtDkHbwN0RtJSNOvYbw0+6E0mzY90PD9hVF8N2fIHO3UaOuG7Dl3t3ViXevHc/wCB+unxZjZHzM3GWszIlvsX1rXDwukiAvV95YkVC/7LONSSTllfHgGUNaZJIc09fIxlk3D25fRhH5pVVM7+TcP3dXJ84ZHc7CXRmsS8jj2QtHMrV/02M5O5n425wB7Mso4re9rWQYBfalF3HBG+u45ZOt/OPHPS3Wl1bW8NLSgzgJwaM/7eWvn22nqMJ2oNcYk8lEWZWx77gnlrDiQNf0BHYEi0VSXtWxnsMTQV2gvyetkIrqlu0pqqhm09GuG17pUJ87JyHav1q0f3Vo92rR/tXhCO57fgt7EKGhoaqbYD+DzzJKBCx5xBhKOe1vENDP9rZRk6Gmwpg3B7DvR/AKZewpZxAyar4xb27jWw3b//YgFKZCYH/Y8anRy9eco6th9zeda3tVGez93hgOaaU194Febiy8fTp/mRVnLMi0Bi0dCODMLk5cP60fKw/msDe9kKKKav77xyGmxgUya1DLpCS+Hi7EBXvWz4Orn//Wv/PJW66YGIWrs4l7TxtYXxC9OeeODic2yJOXlh5skXSlorqWf/8azzmvriG9oJx5Q0L4cUc625v1En24PpHckio+uWkiD5wxmF/3ZnLOK2vYk1ZIa9RaJGszLMx6bgUvLT1ESWUN761N7PS5dpbXlh9mxGO/ccvHW1lxILtFKYnuoKCsivjMIkZG+lJdK9mb3tLba8sOc+nb67sss6hDfe6chGj/atH+1aHdq0X7V4cjuNcBXAdIS+ue4YJdgqsnDDkH0raCTyScclfr20ZNNv4mr4eqUji0xNjX5AQmE0y82eihS90K8b8YwxOn3QmzHoTCFDi6sunxqivgu5vhp9uhurzjbd/yHnx9XZNhne25rx+6mGUN4PISjMQtdnLV5Gi83Jx5a+UR3liRwLGyah48Y0irQyLHRvmzPaUAKSWrD+Uw2DrcsbMMj/Blxz9O5a9zWi9s7uxk4o55A4jPLGZxo/lXe9IKOevl1by+IoHzx0Sw9O6ZvHTZGIK93Xhi4b76YZLFFdW8veoIswYFMy46gFtmxvHFzZOprLZw4Rvr+HFHS8eHs0tY8OoaHv3lEBH+7nx761T+PCOW1YdySC/oxHt7HCzclUGQlxubEvO57v3NzPj3cr7f3r3DHDYdzUdKuHWm8YPBVhvlJJbFZyMlrDyQY9cxD2eXtNmz6FCfOych2r9atH91aPdq0f7V4QjudQDXAQICAlQ3oWOMucr4e/qTRkDXGl4hEBBnBEyHfoeachh6XsP60ZeDqzesfBZ++huEjTCCt8Fng9kPtn/c9HjbP4bidKgug4T2E6C04PAS4+/BxfWL7HafuRtcvUDWGvPh7MTX3YUrJkWxcFc67645ynmjwxkR2XotuzFR/uSXVhGfWcyWxGOdHj7ZmPYyfQKcPTKc/iFevLT0IDW1Ft5dc5QLXl9HSWUNH984kecvHoWfhytebs7ce9pAtiUXsHBXBgDvrUmkoKyae04dVH+8CTEB/PK3UxgV6ccdX+zghd8P1PfufbM1lXNeWUNGYQVPnhXLd7dOZVy0PxeN64uU8N227gue0grKOZBVzA2nxLD+wTm8cvkY/D1deODb3WTb6OmqrKnlHz/uabNnsTNsOJKPm7OJOUNCiA70aBHApRWUcyi7BIDldgwzPVZaxZn/Xc1zvx1odRuH+9w5ydD+1aL9q0O7V4v2rw5HcK8DuA5QU1PT/kY9iX7T4Z6DMOy89reNmmL0wO39ATyDIXpqwzo3bxh9BRz6DSqL4Py3wdkVXMww8hLYvxDKrHN+qitg9YsQORHcfCF+YcfaXFUKSeuMxwcaAji73JfmQnGG0XsIkL2/7e2bceMp/XA2mUDCPacNanPbuoLeb61MoKrWwikdrP/WWZxMgjvmDuBQdglnvryaJxbuY8bAYBbfMYPpzdpw0bi+DOnjwzOL48kuquCd1Uc4bWhoi8A00MuNT26axKXj+/LKssPc+ulW7v5qB/d+vZNRfX1Z9LfpzI7zre+NjAr0YHJsAN9sTW03CcqOlAKWxbc+Z68xqcfKuOSt9RzILG6xblm8EQzNGRyCm7MT54wK57UrxlJjkbzeaO5iHe+vTeSj9Unc/+2uVmv8NWZXagFfbU5p93w2Hs1jbJQ/bs5OjIvyZ2tSQZN96uYGTojxZ82hXKrbqd+3dH8WVbUWvtue2mpmUIf73DnJ0P7Vov2rQ7tXi/avDkdwrwO4DlBUVKS6CR3H285xvFGToTwf9v/cMHyyMZP+DG4+cOoTEDq0YfmYq6C2EvZ8azyv632b83cYeLoRhNV24D9C4hqorYJBZ0HuQWMoJHa6z9xt/B12PghTh+bBAYT6mHnk7CE8fu4w+gZ4tLntgBBvPF2d+GlnOq7OJibGdN+vNWeN6MPgMG8S88p4/Nxh/O+acQR4urbYzskkePisIaQVlHPxW+sprqzhrlMH2jymq7OJZy4cwSNnD2XJvix+2J7GnfMG8OlNkwnzNbfwf/E4o/TB5sTWMzFuTTrGZW+v5+aPtnLY2ivVGlJK7v92F5uO5vPemqMt1q+Iz6ZvgDtx1kLsANGBnlw4NoLPNiWTWdjQC5dTXMmryw4T5mNmb3oRP+1Mb/O1d6cWcsX/NvJ/3+7iri93tBpIFZZVsy+jiEmxxns9Jtqf3JJKUo81DCVdcSCHCD93bjwlluLKGptDLBvz294sXJwEBWXVLN1nu8eutWtfSsm9X+/kts+2tfkamuPDIT/3TyK0f3Vo92rR/tXhCO51ANcBoqOjVTfhxBE1xfgra2HouS3XB8bBfYdh8i1Nl/cZZQyp3P5xQ+9b1BToNxOGnG0EhcnrWh6vosh28pPDS8HFA079p/Hc2gtnl/u6+W8R4yAgtsMBHMDVU2K4bGL79T+cTIJRfY1yAhNi/HF3dWp3n67CZBJ8fOMklt87i2umxLRZumBa/yDmDQkhKa+Ms0f2YUgfn1a3FUJw4yn9+PqWqXz3l2ncOW9gfQbO5v7PGBGGl5szX21JsXmsg1nF3PDBZkJ9zHi4OvHPn/e22bv16cZk1h7OI8LPnZ93pTepsVdRXcvahFzmDAppca63zxmAxSJ5fUXDcNkXlxygorqWT26ayNA+Pjz/+4FWg7KEnBKufX8Tvu4u3Dorjh92pHPVOxvJL61qse3mRGP+2+TYQADGRRnZSOuCtKoaC+sO5zJzUDDT+gfibBKsaGMeXFlVDasP5XD5xCj6+Jr5eqttl61d+19vSeWbran8siuj24qK90Za819rkbzyxyHu+3onf/54C1f8bwNXvbORgrKW146m89j7vbv6UA6Ld2ec4Nb0Lk7qex4HQPtXhyO41wFcB0hKSlLdhBNHYBx4BIFHIESfYnubxgXAGzPmGiOD5eL/M3rfZj0AQkD/eeBsNoZYNqYwFf4zDFb9u+WxDi2BfjMgaACEDKsP4Oxyn7kHvPuAZxAED4bsjgdwHWGs9Qa++dDF7iDY240IP3e7tn3k7KHMHRzCfae3PSy0jnHR/ozu69dkWXP/Hq7OnD2yD4t2Z1Ba2bSHNa2gnGve3YSrs4lPbpzE3acOZPWh3FbLH6Tkl/H0ov2c0j+Ily8fTVlVLQsb9ZqtP5JHRbWF2YNDWuzbN8CDi8dH8sWmFNILytmbXsgXm1O4ZkoM/UO8efDMwaQeK+fj9S2vn3RrOwXwyU2TuH/+YF69Ygw7Uws5//W1JOQ07TXceDQPV2dTvZtBYUYvbF0AtyUpn9KqWmYNDMbb7MKEmIA2yy2sPJBDZY2F+cPDuHBsJKsO5pBR2DIxjK1rPyW/jMcX7mNiTAABnq68ttz2fM+VB3PsKhPRnUgpueernby67JDqpthFa589m47m88KSgyw/kENibhmF5dWsOZzbpJ6k5vix93v30R/38vAPe+waMq2xj5P6nscB0P7V4QjudQDXAVxdWw5TO2kQwgi85j4KTu0n02jCiIvAyRW2fdjQ+wZG4pS4uUbmysa9L0sfM+bSbXgdKhvNd8pLgGNHjcAPYNAZxry8snz73GfuhtDhxuOQIZB/pEOZKDvKjIHBuDgJ5g1pGVj0JKIDPXn3uglEB7aRyKYdbPm/eHwkZVW1/NLoV++U/DKufncjpVU1fHTDRPoGeHDV5GgGh3nzxMJ9LbItWizG0EkhBM9cOIKxUf4MCPHii80NvVHL47Nxd3Gq7/lqzm2z+yMxeuGeWLgPX3cX7phrZPOcPiCY6QOCeHX54SaFzVPyy7jmvU0UlVfz4Q0T6RdkuDl7ZDhf3DyZ0soarnpnIznFDdfPhiP5jO7rh9nF6G11MglGR/mxzVqqYeWBHFycRH0Nv1mDgonPLLYZlAH8tjcTfw8XJsYEcNG4SCwSvtvWMvNVc/cWizF0EuCFS0Zxw7QYlh/IaVHSYOGudK59bxOvLrM/mU9j0gvKmwxN7Sq+2pLCt9tSeWnpIZLySrv8+F1Na589v+3NxM3ZxKr/m8Vvd83g61umIATEZ7Scw6npPPZ89h/JKeFIbil5pVUczNb+u4qT+p7HAdD+1eEI7nUA1wGCgo4/02CPZuKfYNy1Hd/PI8DISAkNvW91DDkbilIhfbvxPHkj7P4aBs6HikLY+mHDtof/MP72n2v8HXSGMaTz8NL23ddUQu4BYzgnGD1wshZyT9yv/BP7BbD7sdPpH+J9wl6jp2DL/9gof2KDPfl8UzJfbk7m0rfWM/3fy0k7Vs67106oH67p7GTinwuGkVZQzhsrmyYc+XRTMusS8njozCFE+nsghODSCX3ZkVLAgcxipJQsi89mWv/A+sCpOZH+Hlwyvi+fbkxmw5F87j51IL4eLvXr758/mMLyat5YkcCWxHxu/WQrM59bTuqxMv537XiGRzRN6jI2yp8Pb5jIsbIqbvtsG9W1FooqqtmbXtgiiBwX5c/+jCJKK2tYcSCHCTEBeLkZP4DU9RjaGkZZVWPhj/hs5g4JxdnJREyQJ5P6BfD1lqaJVKSUCHefJr0K7609ysaj+fzjnKH0DfDg6ikxeLk5N0nmkl5QzkPfGXNCv9uWRk07yVSaczi7mPkvreKKdzZ0ab297OIKnvxlP6MifXEyCV5a2v29cB0d4mjr2pdSsmRfFtMHBNVnj/VwdSYqwIMDWT1/7oQjYc/37h/7G3q61x7OO5HN6VWc9Pc8PRztXx2O4F4HcB0gPb3tZAi9mrmPwFkvNPS+1TFwPggnIxulxQK/3m8Mc7zwXWOo5obXocZ6Q3V4qVHOICDWeB4+FjxD4MCi9t3nHABLDYRZe+CCB1uXn9hhlK0FFcrJ3N25GnytYMu/EIKLxkWyPbmA+7/dTU5xJfecOpA/7pnJxH5Nk7pMig1kwahw3lyZwE8703lq0X7mv7SKR37Yw/QBQVw+sW/9theMjcTFSfDl5hQOZ5eQeqzc5vDJxtw2uz8uJhMDQry4otkcxuERvpw3OoI3VyZw0ZvrWZeQx59nxrH83lmt9uoNC/fl2QtHsuloPk/+sp8tiflYJExudl5jo/2xSPh1TyYHsoqZObBhOO2AEC/Cfc02h1FuOJJHcUUNpw8Lq1928fimiWGKK6r562fbmf3fjQx/7DcufGMdD32/m3//doB5Q0K5eJxR8N3X3YWrp0SzaHcGR3JKsFiMIYo1FsnDZw0ht6SSVYfsq0kHRhKY697fTGWNhSM5pSzeY3teUXZxRYeHq/3z531U1Fh48dLRXDc1hh92pHEwq/t6THamFDDmiSUsj2+/xEMdtq79velFpBWUc9rQsCbLB4d5E28ji6qm89jzvbtkfxaDw7yJDvRgfUJuN7Sqd6DvedSi/avDEdzrAK4DOEJEroyAWJhwU9PeNzB652KmGfPgdn1h9MTNewzcvOCUO6EoDfZ8YyRASVzdMHwSjCLig+bD4T8I8m89+QbQkIEy1NoDFzTACBw7WErgpCBxLbx5Cmx5v8sO2dq1f82UGP5v/iB+uG0af9wzk9vnDiDS33YGz4fOHIKzSfC3z7fzwdpEAjxdjXlnl49tkpwkwNOV04aF8d32VH7baxQsnz2o7QAu3M+dT/80ifevn4CzU8uPtf+bP4h5Q0J54rzhrH9wDvfPH0wf37bnEJ47OoKbTunHB+sS+fevB3BxEoyxznusY0xf4/nL1vlcsxq1UwjBzEEhrDmUS1VN0x6w3/Zm4uHq1KR+4JkjwvB0deLrLSnsSSvk7FfW8OveTK4e34dLxvfFSQh+2pGOn7sLT18woomzG0/ph6uTiTdWJPC/1UdYfySPx84ZxrVTYwj0dOWbrfbV7CuvquWmDzeTV1LFFzdPJjbYk9eWJ7RIQLPxSB6Tn/qD6z7YbDPhiy3+2J/FL7syuH12f+KCvbhlZhyers68+PtBu/bvCv6wFll/edmhdktG1GHr2v99XxYmAXObDZ8eFOZDYm4pFdWtF2Zvjeziii7r7UzJL+txcx87S3vfu8dKq9iadIxTh4YyNS6IjUfyO9zjrLGNvudRi/avDkdw38HJTr2bioqunw/SKxh8Diy+D359ACLGw4hLjOX950HIUFj7MniFGoW/GwdwAAPPgG0fIRPXQujFrb9G1h5wdjeSsYCRcKWTmSgdmpoq+OVu43HGji47bGvXvpebM3+Z1d+uY4T5mvn0pkkUlFUzKTagzcLll47vyy+7Mnh9RQKDw7wJtyNhy4Q2Sjn08XXnnWvH29XOxjxwxmD2ZRSxLiHPZrZRXw8XBoR4cSi7hD6+ZgaGejVZP3tQMJ9vSmZLUj5T44wvBIvFGH43c2Bwkx5cD1dnzhkVzvfb0/hxZzoBHq58efNkwpzLiIyMrN+3VkpcmgWpQV5uXD4xik82JCEEzB8WxsXjIxFCcO7oCD7ZkMSx0ir8bZSbqKPWIvnbF9vZlVbI21ePZ0yUP3+Z1Z97v97J8gPZzBlslCSpqK7lge92E+DpxoYjeZz18mpevWIs46L9Wz12SWUND/+wh0Gh3vx5pvF/1N/TlRtP6cd//zjE7tTCFvUJTwTrDufiZBJsTy5gw5F8psTZ7oFtjK1r//e9mYyPDiDQq2lip8Fh3lgkHM4uaTE0tznHSqv4Iz6bDUfyWJ+QR1pBOX+eEcuDZw7p2Ek1QkrJB+sSefKX/cwcGMy7103o9LF6Cu197644mE2tRTJ3SCgp+WV8vimZ3WmFLX5s0XQcfc+jFu1fHY7gvt0eOCFEXyHEciHEPiHEXiHEHTa2EUKIl4UQh4UQu4QQYxutu1YIccj6rxMTrHoOJSVt17LStMLgs4y/FYVwxrNGzxoYvXXT7oCc/bDkUXByM3rrGhM7C5zNOCX83vZrZO426tM1rl8XMrj3BXAbXjPO2TMEsvZ12WG76tofE+XP7MEhbQZvAKf0DyLCz52yqtp2h0+eSJydTLx6xVgGh3lz9shwm9vUBS6zBgW3KHMwtX8QLk5NywnsSC0gu7iyyfDJOi6bGEVVrYUpsYEsumM642MCmrg3mUSL4K2OP80whh77e7g26aG7aFwkVbUWft7V+pCQhJwS/vTRFpbsy+LRs4dy6lAjWDt3dDgRfu68uuxwfY/Vf5Yc5GhuKS9fNprvbp2Ks5Pg0rfW26zfV8eryw6TWVTB0xeOwNW5of03Te+Hn4cLz/9+oNV9u4rSyhp2pBRw7ZQYgrxcm5SeaIvm135yXhnxmcWcNqxljc1BYcZ82P0Zbc+Ds1gkl769nnu/3skf+7MYEeHL5NgA3l+X2GrSm3bbWVnDXz/fzj9/3kewtxt/xGe3W3/REWjvs2fp/myCvd0YGeFbH5CvS9Dz4LoCfc+jFu1fHY7g3p4euBrgHinlNiGEN7BVCLFEStn47vAMYID13yTgDWCSECIAeBQYD0jrvj9JKduubttDcYS6ED0S3wgYdCb4REBks16Q4RfCH09A1m6InW1krmyMqwfEzsY/fSUUphnHao6URgDXvH5d8GAjA2Z1BbiYu/aceiLHkmDFs0ZCmYBY2PAG1FaDk0v7+7ZDd1/7JpPgkvF9+c/Sg8xRGMCBMaTz1ztntLp+bLQ/X2xOYebAlu30cnNmUr9A3l97lM2J+YyL8iflWBnOJmEzMB3d14+1988hzMeMqZUafK0R4efOu9dNINzX3KSnbWi4D0P7+PDN1lSumRLTZJ/ckkr+u/QQn21Kxuxs4uGzhnDdtH71612cTNwyM5ZHftzLhiP5eLg68b/VR7h8Yt/6bJsLb5/OvV/v5PGF+xge4dti/qOUkp92pDF3cGh96Y06vM0u3DIzjmcWx7PpaH6LfbuSTYn51FgkcwaHEOTtyr9/PdBuz19eSSU+wU0D99/3GcN6m89/A4gJ9MTN2cSBdubBrT+Sx8GsEp44dxhXTorGZBKk5Jcx54UVvLLsME+dP6JD55aQU8LNH23haG4pD5wxmIvGRTL1mWW8t/Zoh4/V02jr+q+qsbDqQA5njeyDySQI8nJjcJg36xPyuG22fSMDNK1zMtzz3Pf1TtYl5OHiJHAyCcwuTjx6zrAT+lnTVZwM/h0VR3Dfbg+clDJDSrnN+rgY2A80v4s+F/hIGmwA/IQQfYDTgSVSynxr0LYEmN+lZ9CNOEJdiB7L5Z/DWc+3XO7kAlNuMx43Hz5Zx7Q7sFQUw9uzIHlDy/VFaVBR0JCBso7gwSAtkOcY9aaOm8X3gzAZvZyhw8BSDXmdSyHfHBXX/s0zYnntirGMrxuaV1F0wmv7dYZzRobz2DlDW8yHquOZC0dww7R+OJsEH21I4re9WZwyIAhfd9uBdbife33wBh1zP3NgMANCW2ZFvWhcJLtSC0jd+D1YLFgsko/WJzLruRV8timZKyZGsfL/ZnPT9NgW+148vi9BXm68/Mch/u+bXYR4m5sM8/N1d+G/l43GzdnEIhuFlPdlFJFeWGGzxwrg2ikx9PE189D3uzs1d8xe1h3OxdXJxLhof66aHI23mzNvrGz9/8evezKZ9fwKznltHYm5DeUOft9nJMyICmw519PJJBgY6s2BdhKzfLYpGT8PFy4e37f+ve4b4MHlE6P4anNKh8srPPTdbvJLq/j0psncMjOOIC83zh8dwXfbUu2eo2gPUhrlOupqH3YHbV3/m47mU1xZw9whDdfWlLhANifmU1lz4q6l3oKj3/NIKfl5VzreZmdG9fVjcJgPR3NL+dbOOcGqcXT/jowjuO/QHDghRAwwBtjYbFUEkNLoeap1WWvLbR37ZuBmgMjISOLj4wkPDyc3N5eqqiqio6NJSkrCx8cHZ2dn8vPziYiIICsrC4vFQmRkJMnJyfj5+QFQUFBAVFQUqampmEwmQkNDSUtLIyAggJqaGoqKiuqP6erqSlBQEOnp6QQFBVFRUUFJSUn9erPZjJ+fHwUFBeTn51NSUkJZWVn9eg8PD7y8vMjOziYsLIyCggIqKirq13t5eWE2m8nNze1x55SZmUlISIjacxp6CeWphyj0nUxwcbGNcxrNwckvMXTnEzh/cDaZ4+7FZdJN9efUr/oAbkCGDMK9oKD+nCpr/egDVKXt4kiBy0n9PpVt+5rIg4vJH3832RklxPj1xwzk7V+NNAV3yTmVlZV1+7U3LSqMpKQkKioqiDv6Maat75FxzQbMHp496n2aFWGmtLjI5jmVZCVz5XBP/jw5lLSMLIpMXnhSSXx8vF3XXkFBAenp6cd1TtMivZnkdIDIxY+T4fIZt61xZ1t6OVNj/bl+lBdj4sKoKMghPtX2+3TluFD+uzIZgNcvH0l6YgIFzf4/TYj0ZOGOFO6b14+U5OT6c/pi1UEEEOde3uScG79Pj505gD9/vpu/f7GBJy4c0+Y5efgGsuNQMuP79+nQ+7RsbxpDQ81UlhWTmZnJRWNC+WBDGks27uKUkQPqrz03dw+eXhTPD/sLGRhsJqOwksvfXs/Tp4YS6OfNlsR8Lh/pT1FRkc1rL9rPhbVHjlFcXGzzfcovq+a3PRlcOSGS5KMJTd6ny0b48eXmZP757RZeu3qiXddetXBhS2I+l4zwZ5C/IDk5mbKyMq6c0Icvt6Tw+m+7+Mus2C753NtZ4MK/fz3AvDhvXr5yfLd87tXW1tafU1RUFMnJyfWfEV+vi8fN2URfl9L6ayvaXEFljYXlu5KI8ajqMZ8RPeo7185zKi4upqioyGHPSbp5U1FtYU60G7fPH0xSUhLHitxZn5BDfHx8jz8nk8nEwYMHe+W1p/qcKioqyM7O7hHn1CpSSrv+AV7AVuACG+sWAqc0ev4HxrDJe4GHGy1/BLi3vdcaN26c7IkcO3ZMdRN6LceOHZOyLF/Kj86T8lEfKb/9k5S5h42VK/5tLKsoarpTdYWUj/lLufSf3d7ebqWmWsr/jJDytclS1lQZy7r43HvEtf/xhcb7nH9UdUu6la5y//Zrz0r5qI+879FH5OCHF8tPNiRKi8Vi177FFdVy4pNL5D1f7Wh1m2+3psjo+xfK7clN23v2y6vlBa+vbfc1Hvlht4x5YKFcdzi3ze1u/GCTHPDQIplVWG5X26WUMq+kUkbfv1C+vPRg/bKc4go58O+L5F1fbJcHM4vkxiN5cvHudLng1TUy+v6F8tEf98jK6lq5IT5Vjvrnb3Lq03/IF34/IKPvXyh3pxa0+lr/W5Ugo+9fKHOLK2yuf335YRl9/0J5KKvY5vqnFu2TMQ8slPEZRTbXN2fhznQZff9CuSUxr8W6q97ZIMf/a4msqK6x61htkVdSKcc8/ruMvn+hXPDK6uM+nr3UXf9L92XKoY8slk/8vFceK62UFotFTnvmD3n9+5uabF9YXiX7PbBQvvBbfLe18WSlR3zuHwdbk/Jl9P0L5dJ9mfXL3l5p/P/M7MDnhyoc3b8j05PcA1ukjVjJrjICQggX4FvgUynldzY2SQP6NnoeaV3W2nKHJDMzU3UTei2ZmZng7g9XfA3T74G9P8Ar4+DLq+HwEvDvB27Nho45uxlZKXO6KEFCaR58fD5k7Oqa43UVB36BgiSY/feG+W7ObkYphay9XfISPeLaz7Wmm++iYaGOQle5nxFhDNXr71XN4jumc+Wk6BZJV1rDy82Z5ffO4rmLRra6zdzBoTibBL/uaWhvRmE5u9MKmTfE9vDJxjxwxmCiAzy49+udFLeSAn/lwRyW7s+mqtbCJxuT7Wo7wHprUou6eXtgZO68dEJfvtuexqn/WcUlb63nlk+2cSS7hNevHMtjC4bh6mzCVxbzyY2TKK6o5uU/DhHh586w8NbLmtQlMrE1D85ikXyxOZmJ/QLoH+LVYj3ALTPi8HJ15sUl9n1uLT+QjZ+HC6P7tsy6eNP0WHKKK1m403Ytv47wxMJ9FFdUMyU2kCM5pXaXYTheMjMzsVgkz/12ACeT4N21R5nx7+U8sXA/qcfKW1xbPmYXRkT66UQmXUCP+Nw/DlLyjd6LvgENw50nxRpz3zYeze/S17JYJK/8cYjMwq7LXujo/h0ZR3BvTxZKAbwL7JdSvtjKZj8B11izUU4GCqWUGcBvwGlCCH8hhD9wmnWZQxISojaZQm+m3r2TM8z9B9y1B065C46shJSNDQW8mxM8uOtqwS17HBKWGYlRehIb3gS/aBh0RtPlocO6LBOl8mu/ugIKrDfseUfUtqWb6Sr3g7yMG4ubxvsTE+TZztYt8XB1bjPg8/VwYUpcIL/uyai/uf9jv1Ew+9Sh7Z+Dh6szL1wymozCcp5Y2PK6ra618MTCfcQEejB9QBCfbUyye57T2oRcvNycGdUsYck9pw3i6QtG8PLlY/j4xoksvP0U1jwwhzNH9KnfJiQkhOERvnx04yS8zc6cPyaiTQ91AZytgt7rEvJIyivjyklRLdbV4e/pyo3T+/Hb3ix2pxa2eV4Wi2TlwRymDwjGydSyTTMGBDEgxIt31xw9roBrxYFsvt+exq2z+nP6sFCKK2vIKa7s9PE6QkhICL/vyyI+s5jHzx3O4jumMy7an/fWGllPbc09nRYXyI6UAkora7qljceDbBih1KNYtDuDt7YV98i22UvqMSOja6R/QxmaoX188HJzZuORrg3w92UU8cKSg7y/rvVsvB1F+fduL8YR3NvTAzcNuBqYI4TYYf13phDiFiHELdZtFgFHgMPA/4C/AEgp84EngM3Wf49blzkkjpBW9GSlhXuvEJj3qBHInf0fmPWg7R2DB8Oxo0YAcDykb4etHxqP64qGdyVSQtJ6I2tkh9q1A5LXwcSbm5ZQAKPGXmGyUb7hOFF+7ecnYCSyrXvce+gy96VGKQNT5fFfD60xf3gYiXll9Uk8lu7PIibQg7hg271NzRkX7c+ts+L4aktqi6Dj4/VJHM4u4eGzhvKn6bHkllTxyy77epbWHc5lUr+AFkXefd1duHxiFAtGhTN9QDDDI3xbJJep8z+6rx+b/z6Pu08d2OZrBXu5EejparMH7vNNyfh7uNgsIdGYG0/ph7fZud1SB/syisgprmT2oGCb64UQ3HBKP/ZlFPHZpmQsnSgUXlJZw9+/30P/EC9umx1HnLXnMCGnY4lWOktxcTEv/3GIfkGenD2yD4PDfHj/+ol8/qfJ/Pey0YT6tMwwPDUuiBqLZFNiz7/duOGDzfzl022dem9OJD9sT+P7Xdls6caENV1N6rEyAj1dm5StcbYmMtrUxT1we9KMz9W6H626AuXfu70YR3BvTxbKNVJKIaUcKaUcbf23SEr5ppTyTes2Ukp5m5QyTko5Qkq5pdH+70kp+1v/vX8iT+ZE0+ZkQs0JpVX3Zh8Yf4PR22SLEGsmytUvQFEnhxFZLLDoPvAMggGnQeYJGEK55BF4fz4svMsI5uxl45vg4gljrmq5rs5JF/RAKr/2c62ZRJ3dIa93BXBd5r401/hbfuJuyE4bGoYQRgbH0soa1h3OY96QULuHagLcMXcgpw0N5YmF+/jHj3upqbWQV1LJf5YeZPqAIOYOCWH6gCDigj15f21iuz0EaQXlJOaVNRk+2REa+ze7ODXJEGoLIQSDwryJb5aJMqe4kt/2ZnLh2MgmBdxt4W124Zop0fy6N5OEnNZvJJbHGzeLMwbaDuAAzh8TwYgIX/7+/R7O+O9qFu/OqA8WLBZJVlEFqcdav8Ze+P0A6YXlPHvhCNycnYgNrgvgjv8GZ3NiPoez287YuexALvsyirhtdv8mAfiUuEDOHW0zJxrjov1xdTLxyfokSuzohUs9VsaLSw52exCVW1LJioM5LN6Tyf9W96yRBXXv7wdrE9U25DhIPVZOZEDLbLGTYgM4lF1CXknX9SLvSTcCuMPZJR3OItsayr93ezGO4N6uOXAaA0eoC3Gy0mn3cXMhehqs+jf8Z6gxh23vDx07xq4vIHUznPq4cazCFCjrwl/v1rwE616B4CGw/WPY9LZ9+5Vkw55vYfQV4O7Xcn1dANcF8+CUX/t1pSD6zeh1c+C6zL21B+5EBnDB3m5MiA7g1z2ZrD6UQ1WthXlD25//1hhXZxNvXjWOP8+I5eMNSdz44RaeXLSfsqpaHj1nKEIIhBBcN60fu9MK2ZZc0Obx1h02Atdp/QM7dU6d8T8ozJuDmcVNAoKvtqRQY5Fc3sbwycZcN7Ufrk4m3l7Z+o39ioM5jIz0JcjLrdVtzC5O/HjbNF65fAw1Fgu3frqNuS+uZM7zKxj8j1+Z9NQfzHxuRX0PQmMSckr4aH0SV0yMYly0MXeoj48Zdxen4w7gftiexiVvrefWT7a1GoRLKflmfylRAR6cNzrc5ja2cHd14m9z+7PsQDan/2cVa63XQGt8sDaRl/84ZHPY64lk1cEcpIThET78+7cDbE3qGT2G1bUWkvLK8HBx4te9maQXtCwuX1NrUdCyjpGSX0bfRsMn65jUz/gs6MpeuD1pRfQNMF5raRf1win/3u3FOIJ7HcB1AEeoC3Gy0mn37n5w/SL461aYfq9x8//1tbD+dfv2ryiEJf+AyAkw8rKGWnO2hlHWVELqVsg5aPR21Nox/2Lbx7D0UaOg+S1rjILnvz5ozO1rjy3vQW0VTPqz7fW+fcHNB7KPfx6c8ms/9xD4RBr+C5I7PtTUgeky9/UBXEHXHK8VTh8eRnxmMe+uOYqvu0tDHb8OYDIJHjxzCE9fMIK1h3P5blsa10yJpn9IQ6KiC8ZE4G125oN1iW0ea11CHkFergyyUR/PHjrjf3CYN+XVtSRbkygk5pby6rLDzB4UbPdw0mBvNy4Z35fvtqfaTIxQUFbF9uRjzBrU/lwNk0lwzqhwfr9rJi9dOppwPzOD+3hz3dQYHj93GP4eLjzy454WPVDPLI7H3cWJuxoNGzWZBP2CPDlyHEMof9yRxt1f7SDYy41D2SWt3kivOJDD3oxi/tqs980e/jpnAN/cMgU3ZxNXvrORB7/bTVmV7c/kFQeN/xu2gtgTyYoDOQR5ufLpjZOJ8HPnr59t79K6fZ0lKa+UGovkouG+SCn5eEPT/wPZxRXMfG4Fd325w2avpcUiOZytdv5crUWSVlBOpH/LHrgREb6YXUxdlsikptbC/owiThsaRv8QL5bFZ3XJcZV/7/ZiHMG9DuA6gIdHyw8CTfdw3O6D+sOcv8PfdsCQc+C3h2Dfj23vIyUse9IIxs58DkwmCLNm4bMVwK17Gd6ZA69NgOfi4IlAI0tma8T/Aj//DeLmwHlvGglazn/LyB759bVwLLH1fWsqYfO70P9UY3tbCAEhQ7okkYnyaz/3kPEeBvYHWQvHWvlwrSg0vP5yL7w9G5LWdW87TwBd5r4beuAATrcW7N6ceIw5g0M6fOPdmMsnRvHhDRM5d3Q4d85tOvfM082ZS8f3ZfHujBYBjpTGzVtdT+CUuKAODeNsTGf8Dw4zslTGZxZTU2vh7q924OIkeOqCER06zs0zYrFI6hN2NGbVoVwsEma1Mv/NFk4mwXljIvj0psm8fuU4HjpzCNdMieGBM4awPbmAb7Y1FDjedDSfJfuyuHVWXIsevrgQr073wP28M527vtzBxH4B/HrnDHzMzjYzikop+e8fhwjzduH8sbaHSrbHuOgAFt0xnT/PiOWLzcm8uaLl8OuU/DIOZxvnsrsbA7hai2TVoRxmDgzB18OF168cS15JFfd8ZTso6k4OZxvB+Slx/pw6NJTPNyVTUW0kDKq1SO76cgcZheV8vz2NF5ccbLJvTa2Fe7/eybwXVykdFppdXEF1razvFWuMq7MxD66rArgjuaVU1lgYHuHD3CEhbDyST1ErmXTr2JVawEtLD/LD9jR2pRbYzLyr/Hu3F+MI7jtUyLu34+Vl3y+nmq6ny9ybnOCC/8GHC+DbP4FXKERNbrlddjz8ej8cWQHjb4TwMdaGBIN3H9sB3KGlxjDI6fdAeT7s/xkO/gaW2pYJRmoq4bubjeNe8jE4uxrLzT5w2Wfwv9nw+RXwpz/ApeUXEHu/h9JsmHxLy3WNCR0Gu781gtFO3sCC4mtfSiOAG325URYCjEQmQf2bbvf9LbDrS2POo4sH1FQY/qOndn+bu5AucV9VBlXWG+4THMBF+nswIsLX7vIB7TGtfxDTWpm/ds2UGN5de5QHvttFVIAHeaVV5BZXcii7pL4nw9kkOHtkH5v720Nn/A8M9UYIo5TA4exitiUX8N/LRtPH18b/5TboG+DB2SP78OmGJG6b1R9fj4YEKyvis/H3cGFUpF+H29ecC8ZE8PmmZJ5dHM/pQ8PwcXfmyUX7CfMxc8O0fi22jw3yZOGudCqqa9udz9eYpfuyuPPLHYyPCeC96ybg4erMReP68vGGRHKKhxLs3RAoLt6TyY6UAv5+Wiwux/EjgNnFiQfPHMLe9CJ+2JHOXacObBLM1/W+hfuauzWA25FSQEFZdX0APjzCl0fOHsIjP+5lxGO/4WQSmEwCs7MTb1w1ljFRHe/J7ix1wfnQyEC8/YP5bW8WP+5I49IJUby+/DBrD+fxzAUj2JFSwKvLDxMd6MHF4/tSVWPhzi+3s2h3JnHBnjy9OJ4BId7MHtz9Gf1S8o1hn31t9MABTIwJ5KU/DlJYVt3k/1VnqOu5HR7uS6S/B2+tPMKqgzmcPbL1Yb+vLDvMkn1Ne+pumRnHA2cMrn9+st9z7kgpILOwnPnDO//5fKJwBPe6B64DZGd3XXYhTcfoUvcu7nD5F+AbCZ9fZswRKz9mzCnLP2oMYXxjqpF58ozn4Ix/N90/bETLRCaVJZC2BQbNh5EXG8MaR10OtZXGMZuTc8C4oZ5yG7g1+6AIjIML3oHsvbbnw9XWwJr/QNAgY45fW4QMhcpCKDq+8otKr/2SLKgqhsABEGAN4JrPg6sogp1fwIDT4bpFcH+SsW1+z0oM0Bm6xH2ZdQ6Qu/8JD+DASJzhY3ZmxsDOJQ6xl6hAD84ZGc6KAzn8tDOd/RlFWKRk3pAQnjh3GN//ZSp7/nl6u1kf26Iz/t1dnYgO8GDxngxeWnqIs0f2aTXhRnvcMjOO0qpaPt6QWL+srnzAjIG2ywd0FJNJ8Pi5wzhWVsWLSw6wcFcGO1MKuPf0Qbi7tgzQ4kK8kBKO5nZsGOXzvx8wks9YgzeAKydHUV0r+WpLSv12RRXVPPbTXob28WFq59+6JiwYFU5yfhk7m5VmWHkgm6gAD84Y0Yf9GUXdNrdrxYFsTAJmDGjoQb1qcjT/Om84l0zoywVjI1kwKpzy6lreXNm9iZsSskvo42umpCCPybEBDA7z5v21iWw4ksd/lh7k3NHhXDqhL0+cN5xp/QN56PvdrDiQzS2fbGXR7kwePmsIC2+fzrBwH27/fDuHsrp3biE01ICLtDEHDoxEJlIaiXSOlz1pRZhdTMQGezE2yh9/DxeWtTMP7mhuKXMHh7D07hm8edU4BoV6s75ZaYOT/Z7zsZ/2ct/Xu3pkqQpHcK974DpAWFgXfZNoOkyXu/cMhKu+gXdONYK1JggYdx3MecTYrkVjRsLhP4zSBC7WFNZJ68BSA/1mNmwXMsT4m72vZW9R3by0kFayZw48zRgeufpFGHuNceNdx9b3ISceLv20/V61+kQm+4yA1RZl+UaPoE/rv4IpvfbrCngHDQCPADD7tsxEmbYFkDDpZoiZZiwLiLUdPDsYXeK+bvhk0ECjbmJ1ue2e3S7iuqkxXDqhL55uJ/4r5r+XjeaFS0YdVy9NW3TW/6Awb37bm0Wojxv/Oq+VOpV2MKSPD7MHBfPumqPUWmBgqBcSyCutYrYd89/sZVi4L1dNjubjDUks2pPJkD4+nD/GdtAZF2zUETySU8qQPg1FzXNLKnlxyUHunz+4RTmG+Mwiay23YU2ui7hgL6bGBfLZxmRumRmHk0nw/G8HyCmp5H/XjCeic1MXW3D68DAe/mEPP+1IZ3RfPwAqqmtZeziPi8dHMiLCl8oaC4eyS5qc0/GydF8Wyw9k8+g5RmH4OpYfyGZslH+T3h8hBFdNbpo8wcvNmTdXJhgJOWxkVDwRHM4poX+IF2FhYQghuH5aDPd/u5ubPtxCTKAnT54/AiEELk6C168cx4VvrOO69zcjBDx5/nCunGScw/+uGc+CV9dy44db+PG2afh7utp8vcqaWpyEOK7h1s1JPVaOEBDRSgA3uq8frk4mNh7N63CipebsSS9kaB+f+h9TZg8KYfmBbGot0uYPLLUWSXJeGXOHhNA/xJv+Id6sPJjdokeuO75396UXcc17G/n0psn1NSy7g4zCcnakFADGe9Vd17a9OML9vu6B6wAFBQWqm9BrOSHuA2Lhht+M7JKnPw1nvQALXoVb18I5L9kO3sDogZO1TZODHF0JTm5Nh2MGDwKE7TT+WXvBybVhSKAt5j1qzOla81LDsvJjsPwpiJkOg89q/xxDhlpfb0/T5VJC6hZj2OELg+HNacYwu1ZQeu3XlRAIGmAErAFxLWvBJW8EBESMb1gWEGv0wPXAX/c6Qpe4ryshEGSdR3aCe+FMWbvwXPFot7g3biRP3FdZZ/0PCzeKhj930Sj8PGzfuNrLfacPxt/Tlf8sPcitn27jL59uQ4i2ywd0hntOHYS/hys5xZU8dObgVnv3+lkLwTefB/ft1lQ+25jMJ82SXgD8sD0dJ5PgrBEtfyi6anI0aQXlrDiQzfbkY3y8IYlrp8Qwqq9fl332+Lq7MHNQMAt3pVNrnWO2OTGf8upaZg8yirWD7Xlwb6xI4O1VtnvBSitruOGDzby/9mj9cev4YO1R/vTxFj7dmMxbjXrRsosr2JNWZNfQwqunRCOEsOn0RCClJCG7hLhgr3r3546OwM/DhapaC69eMRavRgG4r7sL7183gbFRfrx4yaj64A2gj687b109jsyiCv700RaS81p+xyzencEpzy5n7osr280W2hFSjpUR6m3Gzdn2EF+zixOj+/od9zw4i0WyL72o/voBmDMkhGNl1WxLtv05m15QTlWthX6BnvXLIv09yC2poryqtn5Zd3zvvvzHIXJLqtjQxYXN2+O3PZn1j/emd2/yoOZU1tSy5lBut7s/XnQA1wEqKo6zGLSm05ww90H9YdodMOUvMOEmGHt16zXl6uhjI5HJkZXQd2LTXg1XT/CPgZxWArjgQeDUxtj7sBEw8lKj1luhdQjkqueNm+/Tn7JvTpu7n5G9sXGwmbgW3p4J78w15ukNPA3K8mD3160ept5/ZTF8dilk7ml12y4n95BR687bOp8gsD/kNRsambLReN/MjX45D4yD6lJjCKYD0yXXfn0PnDXhzYkeRrnjM1j/6okZwlpZ0q21ADvr//ppMXz3l6ldEmQNDfdh2T2z2Pf46fz811N44eJRvHHlOAJa6dHoLL4eLrxy+Rj+b/4gpg9ovd0ers5E+LlzpFkAV1fE+OP1SVQ3GoposUh+2pHGjAFBBNooeXDq0FBCvN34YF0iD32/h1BvM/ecZvzY0JWf/QtGhZNdXFmf9XJ5fA6uziYmxwYSG+SJp6sTe5sFcJU1tby67BAv/3G4PpFHY5bsy2JZfDb//HkfF76xjgPW8hH/WriPx37ex6lDQpk/LIxXlh2uD3hXHjD+P86049ro4+vO/OFhfL4pudUsml1JZlEFpVW1xIV41bs3uzjxxpXj+PD6iQwNb9k72TfAg+/+Mo3zx7Qc5TE2yp/nLx7FnvRC5rywgod/2E1WUQVZRRX8+eMt3PrpNoK93BDAle9s5O4vd3RJfbaU/LJWh0/WMSk2gD1phXbVCmyNpPwySiprGB7eEMDNGBiMs0mwdL/t7566occxQY0DOKOtaQUNQe6Jvuc8lFXMr3uNQKqtEhonIqnO4j2ZxAR6YBJGL6BKdiQXcNW7G1l9KKd+mSPc7+sArgM4Ql2Ik5Ue5d4vBly9GwK40lzI2g2xM1tuGzLEdg9c9r7Wh082ZvZDRlKOFU8bN60b3zKKdtcFkfYQOtQYQiklrH0ZPjzH6Nk76wW4J95IohIyDDb9r9Uek3r/+36Eg78a9ee6i7xDRjBmsn5cBcYZtfiqrR+wllqjN7HvpKb7BViTL3T3PLj4X+CLK412dQFdcu3XBXCBdQFcwfEfsy3qfjBI3971x177X3h7Fli6Z65SZ/17m10Y28WJJzxcnRkR6cuF4yKZP/zEDPGZ2j+Iv8zq3+52scGeJDQqJVBQVsWWpHxGRfqSWVTBr41+Yd+UmE96YQXntTIk08XJxGUTo1h9KJf9GUU8tmAY3mbjx62u/OyfNyQUD1cnftqZDsCKg9lMjg3E3dUo0D4s3LdFD9z6hDxKq2opqaxh9aGWPUS/7M4gzMfMS5eOJjm/jLNeXs35b6zjnTVHuW5qDG9cNY7HzxuG2cXEg9/txmKRrDiYQ4i3G8NsBEO2uH5qDEUVNfywPf34JVjJKqrg/NfXtig6nWDNQNk/2KuJ+ylxgUyJ61wtxQWjwll532wum9iXLzalMPO55cx7YSUrDuTwwBmD+emv0/j1zhn8dXZ/ftqZzrwXV7I16fh+ZLJnWN7k2EAsEpbsy2xzu7aoS2AyLKLhvfQxuzApNqDVeXCJVuexNgK4lGMNNfdau/YrqmtZuCu91bljR3NL2Z/RflD0+ooE3F2cGBzmzYFM29u/tvwwc15Y0W5WzY6QW1LJ5sR8FowKJy7Yi72KA7gNR/IRoqE+IPSwe85W0AFcB3CEuhAnKz3KvckEYcMbEpkcXWX87Ter5bYhQ4yEGzWNflEsy4fijPZ7+gD8o2HCn2DHp0bWSmc3Y25eRwgdBrkH4MurYMkjxtDLP682ehzdvI2evEk3G0Fo8nqbh6j3v+tL42/q5o614XjIPdgw9A+siUwkHLPOb8vebyQ5aRHAxRp/u7G3hmNJxrDU+IUNc/eOky659ktzjV5MX+sN9InugcuON/6eiAAu7xBUFhmZXruBHvXZ04OIC/biSE5J/U3kyoM5WCQ8umAY0YEeTerz/bgjDQ9XJ05tY67R5RP74mwSzBsSUl+KArrWv7u1DYv3ZJCQU8KRnFJmNyrDMDzCl33NEpks3Z+Fu4sTfh4u/LKraQBVXFHNygM5nDmiD+eNiWDp3TNZMDqc3akFPHzWEB5bMAwnkyDE28zfzxrCpqP5fLYpmdUHc5g5MNju0hbjov0ZHuHDB+uOdlnCh9WHctmeXMBPO5qe0+FsoycmLsSzS92H+pj513kjWHbPLM4eGc4pA4L49c4Z3DIzDmcnE2YXJ+49fRCL7piOBD49jiGj1bUWMgrLbRbxbszk2ECG9vHh+d8O2uxdtYc96YW4OAkGhDSdPzZ3cCiHsktsDhs9mluKp6tTk6yrdfXqUhsFcK35/3pLCn/9bDtrWhlyescX27n987Y/e5PzyvhpZzpXTopiYr8ADmaV2Ly2Vh7MITGvjKd+sfFDdCdZsi8Li4T5w/swNNyHfXYEmyeS9UdyGdrHp8l8VEf43NcBXAdwhLSiJys9zn3YSGMYocVizH9z82koNdCYkKFGcpPGWROz9hp/Q4fa91rT7wFXLyNRx/S7wbuDE65DhhltOLDYGHp5yUdNhxoCjLjYSA5iK+slVv+FaXB0NTi7Q9o224XK8xJg/WtdN/epuhwKUprWugtsFpilbDD+9p3YdF/fKDA5d18PnKXWCN5qrD2Dadu65LBdcu2X5oBnEJj9jOcnMoArzTVKXMCJCeAKrbXKijv/q3lH6HGfPT2E2GBPSqtqySoyfpxauj+bIC9XRkf6ce2UGLYmHWNXagGVNbX8siuD04aG1meetEUfX3d+uG0aL102pklg09X+zxkZTkFZNU8sNHqJGxdCHxHpQ0W1pb5nUUrJ0n3ZzBgYxPxhYSzZl9XkRn/p/iyqai2cNdLoDQ3wdOXFS0az7/H53DQ9tsnrXjK+L5P6BfDYT3spqqjpUGp9IQTXTe3HwawS1iV0zVylup6jZQea9hIl5JTiY3Ym2MvthFz7UYEePH/xKN64alz9XMrGDAz1ZlK/ALYcRw9cRkEFFonNIt6NcTIJHj5rCGkF5TZrLdrD3rQiBoV5N0lQA9T3Vm5PaXkeibmlRAd6NrnOg73ccHUykXqsIeBrzX/dNbBod0aLdcl5ZexKLeRITkmbQekbKxNwEoI/zYhlUJg3JZU1pBWUN9mm1iLZm1aIt5szX2xOYdXBnFaO1jEW78kkOtCDIX28GRbuQ0ZhhbIC9hXVtWxLLmBybNPeZUf43NcBXAcwm82qm9Br6XHuw0YY86vyjxjz36KnGYW4m1OfibLRr1ftZaBsjmcgnPYvI3HJ5Ns63tb+c2HY+XDdQqNsga1ffV09YczVxpy4opbDdMxmM+z5BpBwyp3GuTeeV1fH2v8aRdK7qocuL8F4zcYBXF0pgbpEJimbwDPEmG/YGCdn8IvuvgBuzX8geR2c87IxxDZta5cctkuu/ZJs8AxuyGZ6IgO4ums9sD9k7OyyoaT1dHMA1+M+e3oIccHGDc6RnBKqay2sPJDN7EEhmEyCi8dH4unqxPtrE1lxIIeiihrObWX4ZGOGR/g2SZABXe9/xsBgfN1dWHEgh5hAjyZBxIhmiUx2pxWSWVTBqUPDOGtkH0qralnZ6Cb2l12Z9PE1M6Zv06GytmrjCSF4+oIRmEwCJ5NotbZha5w9sg+Bnq68vzbR7n1WHMhuNYV/XeKIHSkFTW6eD2eXEBfihRBC2bU/PjqA5Pwysos7Nw+pLgiKtFHEuzlT+wcxb0gory9PIKe4Y3PvpJTsSS9sMv+tjv4hXrg6m2wOD0zMK2sRvJpMggh/9yY9cLb8WyyyPvHKr3syW5S9+MUa1Fkk9QXqm5NRWM43W1O4ZEIkoT5mBoUavYcHms2DO5pbQmlVLQ+cOZi4YE8e/G63zYLjHaGwrJp1h3OZP8zIcDq0j+FO1Ty4HSkFVNVYmNIsgHOEz30dwHWA3Nyuy5Ck6Rg9zn3dHLQDvxhD+WzNfwPjJlY4NQ3gsvaCewB4d2AOy7hrjQDMpRMfKh4BcPEH7Re0nnCjcbO95f0Wq3Jzc2HXV0aWx1GXGQtTNzXdSEpIWG483vpBx9tpizxrBsrARgGcux94BDX0aqZshKhJtgPTgNiWGStPBGlbjXmKwy80/ESM6bIArkuu/dJcI4Bz8zaux4qC9vdJWgcpnQjE66710VcYtQ6b1+w7HmqqGgK34pa/Pp8IetxnTw8hNrghE+XWpGMUVdQw11q43dvswsXj+7JwVzrvrjlKoKcr0zsYsNTR1f5dnU2cYZ0/OKtZGYZ+QV54uDrV904t2ZeFScCcwSFMiQ3E38OlvtejqKKaVQdzOGN4H0x21uKLDfbiX+cO5y+z4lqUWWgPs4sTV0yKYun+LE59cSV3fLGdt1YmtDrXKbuogkUf/4evv/+mxTqLRbI3vYjRff2QkiY9Kwk5JfS3Bueqrv1xMUZAvDWxcz80pVgDuNaKeDfnwTMHU1Fdy3+WdmzYe1pBOQVl1QyLaBnAuTiZGBLmXX8t1VFdayE5v4yYoJZti2wWwNnyfyi7hPzSKk4dGsqxsuoWteN+2Z1OkDVR0MFWgve3Vx3BIuHPM4wfQwdaywc0T2RS90PGhJgAnrt4FBmF5Ty9ON7mMW2RXVzBIz/saZLsaOn+LGossn4Ob11SnH0ZajJRrk/IwyRgQr+AJssd4XNfB3AdIDw8XHUTei09zn3wYGN43sa3jOf9WgngnN2MIK55ABc6zL4skt1JQCwMOM2oM1fT9JfISJdCoxTByEuNXi3PYCNxSGPyj0BhshGc7vmuaxJl1JUQaF5uITDOyERZnAXHElvOf2u8Xf7R4xvSKaVRyiF5o+31VaXw7Z/Auw+c9aLxvoaPNd7n6s79gtyYLrn264ZQCmFfMe/qCmPO5E+3d/y1cvYbQzUHnmE878phlMUZgPW9LOmeHrge99nTQwjzMePh6kRCTil/7M/C1cnE9AENQdq1U2OosUg2Hc3nnFHhna7xdSL8XzjOyJZ42rCmw9GdTIJh4T71N65L9mUxPiaAAE9XnJ1MzB/eh6XWYZRL99UNn2y9fqYtLpnQl3tOG9Spdt86K467Tx1IdKAHm4/m8/TieBa8usbmPKv31x7lYaf3mZb5UYssgkdySymrquWKiVEEerqy3DqMsqiimuziSuJCjABO1bU/PNwXN2dTp4dRpuSX42QS9PG17wfPuGAvrpoczRebklv0QrXFnrQia3ttJ6MZFuHLnrTCJnPLUo+VU2uRxAS2HD4a6e9Oan7De2nLf126//vnD8LT1YlfdjX8kJWUV8qetCJuPKUfLk6CAzYCuLKqGj7flMy5o8Prk7z4mF2I8HNvce67Ugtxd3Eizlqg/MZT+vHZxmS7yz08u/gAH29IYsGra1ls/eHj171Gr/WoSD/AGHbcx9esrAduw5E8hoX7tvhBxRE+93UA1wEcISI/Welx7p3djCCuKM0IZuqGStoiZEjDcEOLxQjm7ElgooJJNxs3+/t+arK4ZttnRsA6/AIjCIicaAxdbEzCMuPv2S9CTXmbZQnsJvcQ+PY1hng2pq4WXIo1qGotgAuINXqBSo9j7H7CH7D0Ufj6WqOMQnOW/csIXs9/0+gdBIgYB5bqlvX3OsFxX/sWC5RZe+DAaGN7Adze74zSEjn7jeGXHSF7v3HNBw8CF48umwsINAyfhG4bQtnjPns6Q1l+lw9lFUJYM1GW8Ed8NpPjApsU6O4X5FlfaPzc0Z2/GToR/ifEBLDp73OZGteyV3B4hC/70otIzC0lPrOY0xolXjnbOoxyxYEcFu3OINzXzBhrUfDuwMPVmb/NHcA7105g3YNzWXXfbJxMgheXHGiyXUllDYs27sZHlBNrSWlxI183fHJEpC8zBwWz8mAOtRaj/hugvAfO1dnEqEi/TgdwqcfK6ONr7tCPBnfMHYCXmzNPLrI/Wce+9EKcTKLVwu/Dwn0oqqhp0quWaC0hYGv+X6S/B3mlVfXlImz5X5+QR4SfO/1DvJk3NJTf9mbWl+yoGz65YLSR3fGgjWB0d2ohFdWWFvUYB4V5t+ix251ayLDwhgLl95w2iNggTx74ble7JS32pRfx3fZULh4XSf8QL279dBuP/bSXVQdzOH1YWJNe66F9fNrNRJlTXMntn29vkTX1eKiormV7SgGTYwNarHOEz30dwHWAqio1kyw1PdR9mHUYZb8ZbfemhQwxeomqyqAgyZg/Vldgu6cRO8cYrvjbQ5BkzUhpseB55BfoP8/oxQHoO8EIoEobDd9IWGb0zg07H/qMNoZiHm8yk9yDRg9mcwJjjd6YhGVGAfU+o2zvf7yZKC0WWPqYEfwUZ8Lyp5uuT9tq1OmbcCPEnNKwPGJcw/rjobwAz90fHV/K/IoCI4mNl3W4mLt/272jUho9y27WYUF1WVbtQUpriYwhYHIy3peu7IGrC+Cczd0WwPXIz56OUF4AL42AnV90+aHjgr3YmnSMIzmlzLWRlOOhMwdz3+mDGH0cQc6J8h/ibbt3Zni4L+XVtbxlLdzdOHPmpH5Gb9wXm5NZdTCXM0bYP3zyRBAV6MH10/rx4870Jj0YX2xKJqjS+L/S15TD9sMpTfbbk1aIq7OJ/iFezBkcQkFZNTtSCurnTNX1wKm89sfF+LM3rbBJcWUw5nXd+MFmFu/OaDUjZ8qxcruHT9bh7+nK3+YOYNXBHFYcsO9Hqz3pRfQP9rI55xGonxvXeBjl0TYDOGstOGvA19y/Mf8trz5Bypkj+hjDKK1JTX7ZlcGYKD8i/NytAVnLOXA7UgoAWvyfHBjqTYJ1PitYE5ikFzEismF4qNnFiacvGEFKfjkvLT1k85zreObXeHzdXXj47KF89ecpXDc1hg/WJVJZY2lRAmVouA8JbSRdqayp5ZZPtvLzznS+3Zpqc5vOsC35GFU1lhYJTMAxPvd1ANcBHKEuxMlKj3QfNsL429rwyTpChgDSSOVfn4Gyh/bAmUxw6Sfg5gUfnm3UhktcjUt5Doy8pGG7yAnG37pkJbXVRobKuDnG83HXQfbe4wtgpDTmTzUuIVBHXVC39zsj+6dzy+LAQEMA19lEJnu/M+r9nf6UcU4b32yo/1dbDT/9DbzCYO6jTffzCQev0OPvfdr5OaHb/2NkIO0spdZfEut74NoZQpm6BTJ2wJy/G0Hc0ZX2v1ZxhlFjsO4HivCxRrkNWxlLO0Oh9Ua0z+huC+CafPaU5rUYXtzjSdva9XMRrcQGeVFmvcGeYyOA6x/izW2z+9udLt8W3f3ZX3fD+vWWVAaEeBHdaKibMYwyjBUHcjo1fPJEcMuMOLzdnPn3b8bcpOpaC++tOcrckIbelIxDTX9E2ZNWxJAwb1xMgun9g3EyCVYcyCYhpxRXJ1N9+n2V37vjo/2psUh2phY0Wf72qgT+iM/m1k+3seDVtaw4kN0ikLOniLctrpkSQ0ygB0/+sr9FchCLRXL759sZ8PdFxD20iH4P/sKy+Owm9d+aMyjMGyeTaNK7lJhXirfZmQBP1xbb17W5rseuuf+D2cUcK6uuDzhmDgzG09WJRbszOJpbyt70ovqetYGh3qQVlLdIOrIjpYC+Ae4EejX9zhwc5k11reSINQNrQk4J5dW1jGwUwAFMig3k8ol9eWf1kRbz++pYfSiHVQdz+Ovs/vi6u+DqbOKxBcN49YoxXD05mgkxTXu8hoX7YJG2i4lLKXn0x71sTTpGoKcrK7ooEyYY9d9szX+DHnrP2QwdwHUAR6gLcbLSI90PPB2ipsCgM9reru5mNnu/dSilMIZf9lRCBsOflhs9bovuhW9vpNbZo2FOExhBk3BqCOBStxi12OoCuBEXGXXHtjZLiFJRaJQGsIfiTOPGs3EGyjrqMlFWFLYsH9AYvyijnZ0J4GqqYNkTEDoChl8E8x41gp+Fdxs9YuteMYZInvV8y7IMQhi9cMfbA1fXe5Wxs/PHqBs+Wtd7avZrO4Db9LaRRXP0FUav4pEOBHD1GVatQ4rDxxhlFXLsn/jeJoWp4BFoFGnvpgCu/rNHSnhzGqx6rltet8uo+xHheIYRt0JciBHcDAr1brdocmfp7s/+uGAv3F2cqLFIm3XrzrbeIHf38MnW8PVw4S+z+7PiQA4bjuTxy64M0gsrODO8YahZZdqe+iCnLnPirMACeCoC3+JDjIvyZ1l8NoezS4gJ8qgfeqjye3dctDWRSaNhlMUV1fy8M4OLx0Xy3EUjyS+t4rr3N3PNe5vqe28qqmvJLq7s1PXo6mzigTOGcCi7hC82N+21fH9dIj/vTOecUeHcOjOO22f35855A/jr7NaL3ptdnBgQ4sWe9KY9cP2CPG3+qNFQC86YB9fc/wZrT1vdkD+zi1HX8Ne9mfy4Iw0weuWA+sySzYdF7kgpYHSzrKlgBJsA8daC3rtSrcNsI/xabPvAGUMI9HLj/m932Qx0n1oUT6S/O1dPaRoEnT0ynCfOG14/JLOOtjJRfrIhiS82p/CXWXFcNzWGXamF5Ja0/yPa6kM5PLM4nq+3pLA9+ZjN7JkbjuQxPMIXH3PLhEI98p6zGTqA6wA+Pq3/0qI5sfRI94FxcMOvDUPTWsO/nzHML3uf0QPnH2P0cPVk3P3gss9h1kNQmktF3HxwbfSF6OppFDOvy0SZsAyEyRhOCka2wxEXGclM6oK2Vc/BC0Pg9SkNvVhtUVcI22YA16jGUmvz3wCcXIwgrjOZKLd+YAx9nfeo0TPp7m+Uc0jdBMseh5XPwpAFRmF0W0SMNbJoHk8yl/Qdxt+6ovGdoT6Aa9wD10qbirNg7/cw5krjPYydaQz7PZZo32vVFfAObhTAQdcNoyxMBd9II4NrSdbxDS21k/rPntJco4cx8/jnNXYrdT8ilHVN/bDGxAYZn2Nzhthf06yjdPdnv5NJ1GfGsxXATewXQHSgBxeP73tcPYtdyXVTYwj1cePZX+N5e9UR+od4EU0m+Pej2smdsMqj9b06KfnlFFfUMN1ptzGcP3MXswYHsze9iG3Jx+gf0vDdpPJ718/Dlf4hXmxJzK9f9uOOdMqra7lqcjQXj+/L8ntn8fBZQ1h9KJdHfjCC1LpaZn3tKCFgi9OHhTKxXwD/WXKQIutN//6MIp5dHM+8ISG8cPEo7j19EHefNog75w0kNrjt7/LhzRKZJOaV2kxgAo1rwRnn0Nz/+iN59A1wb1Lf7swRfSgoq+atlUcYG+VHuJ9x3nUB2YHMhmGUWUUVZBRW2BzSHBfshbNJ1Ad8u1ML8HR1ItbGUE9fdxf+uWAYe9OLWtTP+2FHGvszirjv9EG4OdseWtqcvgHueLs5t8hEuT4hj3/+vI85g0O457RB9Vlj26tHJ6Xkoe938+bKBO77Zhfnv76OEY/9zj1f7aTWmtCnorqWHTbqv9XRI+85m9FuACeEeE8IkS2EsPmtJYS4Twixw/pvjxCiVggRYF2XKITYbV13HGOAegbOzq0XIdWcWBzavZOzMQwwe39DBkpHwGSCWffDXzZQNuMfLddHTjR+3bfUwpHlRo9TXRIPMIYcVpfBL/fAK+ONZB/9Zhg9Mu/Mg+2ftv36Oz4FJ1cIHd5ynZuXMXQR2g7gwJqJslkP3LEk+OOJpnP4GlNZbARoMdONnsg6Rl0G0acYNd+c3ODMNnpj6ubBZexou32tUVnSEMRmdHEAV1loO6nF1g+M5CsT/mQ8rwvI7Z0Hl73fqMnnaf1SDIg1itynd1Eik8JUI6mNV5jRzvL89vc5Tuo/e44dbfrXEZCyIYA7AT1wg8O8ufe0gVw/NabLj12His/+U/oHERvkWZ8pr0l7nEwsu2cWd86z8cOSIswuTtw5byDbkwvYl1HEzdNjEflHIGgANYGDGCRS2GStHVaXYbN/pfXHluKM+mQz+aVV9fX9QP337vhof7YmHavPovnF5mSG9PGpH9bn6mzipumx3D6nP19vTeWzTcmkWLM4tlfEuzWEEDxy1lDySqt4fXkCFdW13PnFDnzcXXj2wpEdDtqHh/uQW1JFdnEllTW1pB0rJ8ZGUAQta8E19l9X/21yv6YBx4yBwXi5OVNeXctZIxuSBUX4uePh6tSkB257cgHQcv4bGC5jgz3rM1HuSitkWIRvq3M8zxgexrwhoby45CBfbErm9RWH+cePe3hqUTwjInw5Z6T9iYuEEAwJb5rIJPVYGbd9to2oQA9eumx0fYbYIC/XJrUYbbEt+Rgp+eU8e+EIlt0zk7evHse1U6L5dlsq//fNLiwWybakY1TVtqz/Vofqa98e7OmB+wD+n73zDo+jvPb/51XvvUu2ijvGvdF7Dy2kAKmkQSop96bnF0hyb0LqJckN4SaBJKRAQgKEAKEFTAcXbIxt3C3JsmzLKitZvb2/P94d7a60K2kljWZndT7Po2d3Z2dn3znz3dGcOec9h0tCvam1/qHWernWejnwVeA5rbX/f9Vzve+vntRII4DmZvsvFoTguN72BYtMGlzzfvc4cBYFC2kK1uC0bI1Jcax9xVwkWumTFiUrTKGXN+836Xs3PAbvuQ9uesGkPf7jk6ZMfbBS+7Wvwra/wGmf8aX+DSdvnkmlTMsfffw5VSNbCTz3fXjhR/DLU2Hv04Hr95yAp24xlRsvuDWwQI1S8LYfG2fo0ttG7+VnRZ8mmkZ59E1A05NRYaK3AxNsoNpxHFCmvQP4mnl3D5u/MNAHm+6GOedDnjctKH+hccjG7cDtDKzIGhMTfiGTjkb44ztGFp7R2syBsyJwMC1plEPnHusmQEv15IvzTBetddDRYKLjHVNfVS0mRvHp8+ZRkGFf01snzv2fu2AeT3z+rJAXr7ExKmKibxbvWlVGVX4qBemJXLW82PyvyZlDUsnJLIytY1ONseP2+lbiYhSZzd607LYjLCxKp8h7DP0jcE7/311Vnk1bdz/7jrez/XAr2w+3cf3akZHPz10wn7Pm53Prwzt4xFtWP9wiJv4sKcvkmpWl3P3iQf7z/jfYfewEP3rX0hHzxsaD1SNu++FWDjV3MqihMkgPOAvTC844of72333sBB6/+W8WSfGxXOCNgF+2xPf/KCZGMb8wPaA1wBt1HuJjjSMUjPmF6ew6eoL+gUF21rexNEh/OwulFN++ajFxMTF85YE3+cHju/nH1nqKM5P47tuXhF3c56TiDHYdOcHAoKazt58b79lM38Agv/7A6qEUx5gYxVnz8nneWzU1FA9uOUxSfAyXLSmmKj+NixYX8a2rTubzF8zn76/X8Y1/bOeVA03ExihWV4xMJwXntT8exnQxtdbPK6Uqxrm964F7JzWiCKa0tNTpIcxYXG/7gkXw5l+9zyO0AuUoBLX/LG8hkxd+DHpwpAOnFFzzK1M8YcHbzMU8GIfr/Q/Bs/9tPtt2BK6/16Q7gokM/etLkF4CZ3wh9KAu++H4CkrkVEFPm7mATcs3jsv2B2DuheYC90/vgLU3wor3w5Y/wNZ7zXy+Fe+DsiD3nQoWwn/sNlUWRyM52ziYEy1k4o3c6RUfgOe+beaRWYVzwqHjuGnmHus93VtR0q4Ws9zirYdNb7UrfupbppSJwh183jgto120Dg6aMa78YODy0pXwyh3mWIUqNuPPxrtg39Ow+19w2qd9y7tbzQ2DzDLTcw+MA1cUJEI7hQxp33Lg+rvN92Y4X8BiTKybB2VrAntRuggnzv1KKeJjI8tBG4u42Bju+fBaevoHSexqMNkPuXNQA33k8kf27D8ALGX74VZW5w+irEjyiSMopTh3YT73bjgUEIFz+v/uam+xi03VLeyobyUpPoarlo8cU2yM4mfXLefyn7/I3zbXkRAbQ0F6+M6WP1+8eAGPvXmER7Yd4YbTKkY0fR8vi4ozUMoUjrF8jsq80GmXZdkpPFlvbkz529+qNHnKnJERoy9dspC3LS2hODMwbXRBYTpPv3Vs6PXWWg+LijNCVs1cWJTOI9uOsPWQh57+wYAKlMEoyUrmyc+fRWfvAMWZSQFtRMJlcUkGXX0DHGzs4H+e3sNbR9u4+4Y1AXoEOHtBPg9sOcy2Og8rZo90vnr7B3lk2xEuPKmI9GFz224+fy7d/QP8cv1+EuJiOLk0c8Q6Fk5rfzxMWYxQKZWCidT5/cdFA08qpTTwf1rrX43y+RuBGwHKysrYtWsXJSUlNDY20tvbS3l5OTU1NWRkZBAXF0dzczOlpaUcO3aMwcFBysrKqK2tJSsrCwCPx8Ps2bOpq6sjJiaGwsJCDh8+TE5ODv39/bS1tQ1tMyEhgby8POrr68nLy6O7u5v29vah95OSksjKymLnzp0sXLiQ9vZ2Ojs7h95PSUkhLS2NhoYGioqK8Hg8dHd3D72flpZGUlISjY2NEbdPR48epaCgIOL36c0336SoqMi1++TpzWCWV+v7O1Io6epy1XE6cOAAy5cvDzxOx3qYn5xDzP5nGIhLoTfnJGp27Rq2T/l0p6fTvmfPyH0qfTezzssh9Zmv0/qHD5Lw7t9QU1tL/qHHyD3yBodP/TapXf14jlQH36dmRUlJFY0HDoy6Tyd6kikBuo/spHqgkOLDj5HZ30V15XsoOPlseh77GtkbfgUbfsVgTDy9cy/jxKLraEqqpHySx2lu0XL0wec5Ulsb8jg1bHqYuJKTScwsDDhOuW+tJyOtkJ39s1gJtO15kXpPfNja4+gBkhOzaaivp62tjcrYFBKBw/t3kB6fP7RPyVsfIjEph76yM6jZtWton7qSF1Dc/jfqt62nLbE4pPbaD22nrK+T3qw5HNi1a+g49ehCSgf7qNvyFO3pc0fXXl8PczfeRQzQdfA1WqveObRPDdtfpgLoSsijvqGDOUDLobc4NlBm63mvvr6eFStW0Fv9BtblTM0bz5G97LKIP5d3vvkkOTHxdBevI/nQa3gaj+Fp73LV/6fe3l6ysrIi5lweyf9zE+LiaG9upnOwhhSgriuRvPxZJAEJLXt468AhttU285lZNdAKg/GpaE8de3ft4tJ56dQ3ZTLoqacrJ4GamhpaW1tZtGiRY/uUnp5OdnIcj71+gC1HujmzIo1jhw4S73+c9CCtTQ3MqprP187K43OP1FGcmciePbsndZxajx7l8+eU88zu47y9StHl/V8wkX0qTY9nW10z7R7jhKXpTnbtOhpce3H9NHX0svXNnSTEmlS+mJgYXtzTSHF6HPG9J6ivbxmxT+vK8ti1a1fAPlXmJtHU0cuWt/YxuzCXrbXNXLGkgNra2qDHKbXfpDD+dr252TMvL4ldfufyYMep7ajRXkdrJ4cm8XvKjzc3Y790/1ZeP9TKjesKWFWcNGKf1swqQQEPvbaXyoz5I7S3rysFT2cfZ5TF09zcPOI4feas2RxtaOTBna0sK0oO6Wt0dnZSVlYWEeeIkGitx/wDKoDtY6xzLfDPYctKvY8FwBvAWeP5vlWrVulIZPfu3U4PYcbiets3H9T6lgytv1Oo9UC/06MJm5D2/9O1Zr/+fP3EN77++2YbT35T685mrb9fqfVdF2s9ODjxbfpzfK/Z/pY/m9d3nqn1HacHbv/gC1q/+n9an2iYmu+0eOWX5rtbDwd/v/mg1rdkav3of4587+drtP7Tu/XuXW9p/V/FWj/6xYmN4a6Ltf7t23yva18zY9rzVOB6v74gcL2AMWZo/eqdo3/PrsfMerWvBf/8ht+MPdZt95t1b6vQ+henBL63+3Hz3qGNWvd2mefP/WDsbU6SIe3/6jytf3ySV0t/sv17p4S7LzXj3ni3GbenzukRhY3rz/1OsOm35ng3V2vddlTrWzL0LV/7tL77xQO6/MuP6Dd+/x9a35qt9V/ebzQdgkiw/cd+v1GXf/kRXf7lR/SGg00jV3j5f7X+0QKt+/u01lo/v6dBP7Xj6DSPcnQ+8+fX9Wnf+7f+6gPb9PJvPTHqug9tqdPlX35E7znaNmT/gYFBvfTWJ/QX798a1ve+sOe4Lv/yI/qlvcf1riNtuvzLj+i/bz4Ucv3apg5d/uVH9OJvPq5P/ubjemBgiv4Hj4OevgE992uP6vIvP6Jvvvd1PTjK//+r/vdFfdX/vhj0vU/8cZNe+e0ndW//QMjPDw4O6ke31WtPZ2/IdSJB+xbAJh3EV5rKKpTXMSx9Umt92PvYADwIjFLvO/IpKytzeggzFtfbPnO2KatfsHDs1LsIJKT9rTTKOedOfONnfRHWfBReuh1+d7lJ7bv0B6On64VD1mwzB6h5v6nqeOQNWPXBwO1XnAHrbhx7Pl24lK40j6HSKDf/HtDw1j8DKypaBUyKl1M2a7ZJE5xoJcqO474CJmDaCMDIVgLNBwKre1pkV5gG7WPNg7NaCAxvkZFVbubfjWce3IZfmaqtq26A47sD50daPeAyyyA+yezHNMyBG9J+y0FTlRM1/qqcTjLQb2xeusp3/G0oZGI3rj/3O0HTflMAKrMM0grQyTksiq3j9y9XA1DR/ZaZi50zx6RNh6jmGgm2t+YozS1IY3V5kPlKdRtNdVhvq5Iz5+VzQZDqoU5ycmkGhz1dbKn1hCxgYuFrJdA1ZP8thzy0dvUNNfAeL/OLTPrhrqMn2HrInO+XjdL6wip80t7Tz8mjFDCxg4S4GJaVZbG0LHPMYjHnLMjnjToPzR2BzbZbu/p4+q0GrlhWQnxsaPdGKcVlS4rJTA6ePgmRof2xmBIHTimVCZwN/MNvWapSKt16DlwEuKz+ciC1tbVOD2HG4nrbx8SY0uxL3uX0SCZESPsveJuZ0xeqlP54UMo4bIuuNH3VVt0AxUsnvr3hxCV4WwkcgNd/D3FJpsXBdFC0BGLighcyGeiDLX+EpExzAeJfqdFbwISS5cb2xcvMsomUzR/uwA0VMfH4lnW3maItOZXBt1F1NlS/EFi5sndYakfDW6ZCZLCeeCUrTDGb31wID30KXvrpyCIl9Vvh0Guw9mNmf/UAHPebt9VaBzHxpqgKmHlw0+DA1dbWmrYLnU2Qv8BcFDeHqETZEkG9gxp3m3lQZat9hYA6p76QyZRydPuIPpGuP/c7QdN+cyMkJhaUQhUuZnniEaqbOolTg6Q3bjW6SC+Gwf6QuogE26/1Vl28bk2Itg3WeWSqKt3awOISk3z91pE2KkO0ELCwmqgfaukcsv/9mw6RkhDLhSeNUjQrCPlpieSkJrDn2Am2HvKQkRQ36vdbhU+AEQ28p4N7PrKW+z9+asg5ehbnLChAa9PrzZ9/vXmE3v5B3r5i8vPXIkH7YzGeNgL3Aq8AC5RSdUqpjyilPq6U+rjfam8HntRad/gtKwReVEq9AWwAHtVaPz6Vg59urJxXYfqJCttf9kM49VNOj2JChLR/wUL45CuQMf6SwUGJiYVrfg1X/hwu/PbkthWMnCpzcfjm3+Ckq31OjN3EJ5s73YeDdFHZ9aipEHjZj42T99bDvves1gPFy43ti5aaAh7hNiTv7zXFPwIcuCzz6B+BswoaBIvAAVSebbaz90l49Zfw6/Phu8Xwl/dBp7daV8NboRvUn///YPl7TRGTfU/BU9+EX50LNS/71tnwK4hPMetZDrx/+4TWOqMzqxhOelFwB+6pb5rjPEVkZWUF2ie7IngEbv+z8NOlEy9aM9VYNw1KV0GK14GzoRLllDA4CP/+tmmU/vS3At6KinP/dNO837RPsShYRMVgDaA5L9eD6m03hW2sQjxt9UE3Ewm2X1aWyT0fXssHg7Wq0Np3ToyU310Q/Ks+jhWBy0tLJCHO9ILLysqivaefh9+o5/KlxaSFWSREKcX8wjR2HzvBlloPy2ZljRlVW+jtH3fyKBUo7SIlIW5cveOWlGaSnRLP+t2BDtyDWw5TlZc6Jc5nJGh/LMZ04LTW12uti7XW8VrrMq31XVrrO7XWd/qt8zut9XXDPndAa73M+7dYa/3fduyAIAhRQnwSrPyAaSA91eRUmYhET5tJn5xO5l5o0g8PvhC4fPNvTcTq5GuMg/TWP33l6eu3mF5n1gWW5dAcfSO877burPu3YoiNh4T0QAfOuggK6cB5+8Hdex08/hUY6IFVHzKVIu88Aw48Z1I+/VsI+FOyAi7/CdzwCPznHvjsG5BWAH94O+x5wjgWb/7N9NlLzoKsCjNG/4bvVg84i2AOXH8PvPILeO3/xrJMeFgRt+zK0A5c7avmcd/TI99zgsObTXQ3p8p3/CPRges5YW4EvPBjc2Nl+9+D9ygUxsfgoNHrMAcucaCTUho5L90bWShbYyr9wrREsieKUoqz5ucHT4lrbzA3tiCiI3BZKQmUeSNrlaEcuBdvhy1/JCZGUZblayXw6LZ6OnsHuHbN7Al994LCdHYdOcGeYydYMUr6pIXV9iBYr7hIITbGaOL5Pcd545CHQ82d7Gs4wWsHm7l6RWnEtfiwi6mcAxf1eDwep4cwYxHbO4vr7Z/jvZjJnQezT53e7z7zP8xF9D8+Zea2gUn7ObDeOKwxsbDoCuNEWfPI6rdCyXLAa/v8RSZ9MNyG3u0N5jF12Ny+5KzgDlx2iBTKtAI452tw9pfhUxvg4y/CFbfDR54yUbV7roSB3vG3yMiugA8/biJ2970HHviYcQrX3mjej4nxzvsb7sD5zUtIL4L2Y4FppQ07TUpY/ZaRKZ4TxOPx+Dm4leavo8F3LC2sqOmB56bkewO3/YaJWHZ5xv+Zus0m+qaUceRi4iNvDlxLNdx1Eex53KRRX/4/xrbVLw6t4vpzz3TTVmd+Szn+Dpz5Xa5IOsK6+ANm/mjOHL9+ikEicC/9jMz7r7F/vJOhaZ95LF4Gx3YG7yn67Pdg58Mjl08zJ3vTKEM6cBt+bVLLYaiZt8fj4d4Nh5hXkMbK2VkT+t75Rel09Q0wqGH5OLbx7tVlPPDJ05iVM/E+etPBBYsKaero5apfvMSZP3iWC35i5mhfHaTNxERww3lHHLgwmD17YndAhMkjtncW19vfiiyt/MDUFUcZLwkpcNUd4KmFp281y17/PahY03sOvHMIlYnC+RUwAa/t4xJ8zeDDwYq4BHXgPL7XzQchrRASQ/cn4pwvw7lfM/PALEpXwk3Pw7L3GAehbM34x5aaBx/8p3Go9z9jonz+EbyiJWZO5OCgKcjRVh/owKUVwWAfdPk1XLXsM9gXPG11AsyePdukUKYVQkKqcT4BPMPmu1nfXbdhypzHIXb+w0QY/B1af177P3jk875m770dxpktXWVeK2XsPZ45cIMDJvV2OnjgJmg7DO/7O6y7CeZdbIo97XhgaBXXn3umG2tO2LAIHMDt5yZQ0e3VRUyM0TQqeASu+gWSm3aYCGmk0uzd1yXvMr/5YzsC3+9shud/AFv/PP1jG8bK8iwS42KCp1AO9BsnunEPnDhGWXYKdS1ddCfmsPWQh2tDzf8bBwsKfRkty8qyxlw/MS6WlUH6q0Uab1tSzMOfPp3ffGA1P3jHUr5y6UJ+/K5lzM6dGsfTDecdceDCoK6uzukhzFjE9s7ievtXnQPnfgNWf8iZ7y8/FU75BGz8Nex9Grb8CRZc6kuRTCswjsxb/wwoYAJ+ti9eZipRWmmW48GKuPinUIJJVQuIwB0MHX0bi8R0ePsv4at1kDc3vM8mZcB7/2Yie5fcFvieNe+v5aCplKcHRkbgIPDi88gbxgFAQc0rE9qd4dTV1Rn7WDcBLAfOv5DJiWOmEM2c800k8tCrU/LdvkFs9H5niDmQW/8Mm+6Gv37QpJEe2WbsZTlwYObBjSeF8pn/gh9UmbmOA/3hjzUc569pLyy+xlfFNiHF/C52/mPIGXX9uWcyaG3SlMOyqTcq5R+BS8qEjDLi6jehju/y3WiJjTPnnmBz4KztDC82FEk07Tc3jhZdaV4PT6Pc92/Qg+bmmcN88LQKHv/cWcHnsZ04YsYJUPMiZdnJNHf0cuezu0mIjeGalROviDjP68DNzkkhN21yzc0jiZgYxdKyLC44qZB3r5nFx8+ewztWTV3lSDecd8SBC4OYGDGXU4jtncX19o9PgrO/aM/8uvFy3v8zF1V/ea+JhKwa5kwuusJEnKzogzcCN2T74mWmEmKIggNBGXLghkXgkrJGplCGmv82XuKTJv65c79mir34U7TEPB7dBq2HzfOAOXBe5zfAgdtmooKFJ0OtX4GUSRATExNoH8vR9Z8HZ0XfTvmEKUgzlWmUgwO+Ag0tB0e+bxVyyKmC3Y/Cfe+FGm8KYslK33qp43Tgdjxo0lAf/wr8+lyoCyOSWbcZvlc6vov+/l6jZ8sRtzj5HUabXhu6/twzGQ6/buadvvnX8X+m+YApBmT9PiwKFpkiRHowMFKeXmwcCH/6e30VVS1HLhJp3m9SmrNmm+q0wwuZ7H3CPHpqw7vxZQOJcbGh0ydb/ZyF6peG5ss9ubeNixYXkpOaMOHvzUyOpyovlXWVORPexkzEDeedyB9hBFFYGFm9RWYSYntnEftPAQkpcPUdJkKSNRvmnBf4vtWKYfPvAgqYDNm+yKrMGEYaZcdxiE0c6bgmZ/vaCPR2mvSdyTpwU03+QuMMHX0zsAecRbrXLtbF50C/cYCLl5mI56ENvpTCSVCYk2G+w3LckrMhMTPQmbKOyexToHQ1HJxCB65hp69QQ7AIXEejKc6z9ka4/HZTROXZ7xpnN93vd5uaN/YcuKb9Zr8u+g6863dm/d9cAM+MswZZ3QYTgRyP09d+zDymDTu3zD3f2Hf734EZfu6xKoke2jD+zzTtN7/l4RegBYuMYw6+/pRgKrsOT6H01JgILkDj3vDGPJ00HTA3xZQy++QfgRscML+FmDjoPTGy7+V42PsU/O3DpsBSb8fY608Uy4HLKofqF4d6wQ1quG6CxUv8ue+mU7jlysVjrygM4YbzjjhwYXD48GGnhzBjEds7i9h/iph9Crz9TrjiZyMvsLLLjfMx0DuUPgl+ti86GVDhNfTuaDQpUsPnT1gplFr7IkmhesA5RXwS5C3wOnDeC5xMvwnqad7ITbv34rNxD/R3G0d39qmmB1q4RV9evRN+f2XA3frje7zpi5Z9lIKcimERuK2QO9c4ylVnG4duIheMwbAu3nPnBe8/Z80Dyp1rUoSvvsO8Hj4fMTXfRLxGY9+/zePc82Hx203BmmXXm3lEr98z9liti31vU+VRsRy44ZGiuERYdDnsegT6e2b2uWdoXmUYUdDm/cFvxlgFhnLnQopfNCa9aGRU3z/qFqkRuMHBwHYJJSvg+G7fnL26TeY3aKVXTiSN8tU7zI2Ev38EfjgX7v9Q8J6ek8W6QbX0WmjczewEsw+FaXGcFmbz7mAUpCeF3YJgpuOG8444cGGQkyMhaKcQ2zuL2H8KWXadb87PcBZdYR696ZPgZ/uEVMibF55T0nF85Pw3MA7cQK9xcsbqAeckxUvN/rbWmbRP/0hifJJZZkUPLMe2eBmUn2aeh5tGufWPJnpmVZQEclSr94mfg5tdEehMHXnDd8wqzzZpatUvhffdoajbZOavzTnXfOfwVDArXdE6fsvfAzc+N3JOYUquieQNa5QdwL6nzXasbSVlmN6MVefCI1/wtUoIRZPXgWvcM/Z+WcctPcid7sXXmKjivqej/9xz7/XwxNeDv2fpsGEndLeNva2BfnNjwb+AiUWh14Eb7tinl5hCQP09vmVep62vYKnvmEYaJ+rNDRtLqyUrAe1zevc+aQpFrbrBvA7mwHW3merA7UEi0wP95ubJqg/BDY+ZGxn7noZ/fXnq96W1zpyT518CQG7TZqryUnn/mpIx+7YJ9uCG8444cGHQ3z+BCd3ClCC2dxax/zSx+BpISAtw8AJsX7QUal4yPYNqXw1eNtufjuMj579BYDNv/xL5kUbREhNhq389cP6bRXqxzxE48gbEJRsnN73IXNjVhOHAtTf4qjxu91VBVMEc3OxKc0E4OAAdTeYOevEy817ZGjOOqUqjrNsAs9aa7+89MXIeW/N+kyaWVe5bVrx0pGNk6SDUPLj+Hqh+AeZeELg8Ng7e9VvImmX6tXkOhR5rozdaM64InPe4pRWNfK/qbEjOge1/H/+559U74bkfjm/dSKGlBnY/ZvQ23DHv64KGt0xkCT2+PmeeGpMmmRPEgctbYNKSF14euNwqpOQ/D65pH6Tk0lOwzNwgcHj+WFCGV9u00kKteXB7n4BZ63w9NIM5cNUvwJY/DqXrBnDsTXPDo+IMqDjd9LFc8k57UkqtFinFyyAhjZiaF/n3f5zNNUsmH30TJoYbrnnEgQuDtrZx3AETbEFs7yxi/2kid46p5jj7lKFFAbZffr1Jf3r6Frj7YvheGTx1S+jtdTSGcOC8ZaK7PMaBS872LYskrEImhzcHpk9a+DfzPvKGSTONiTWvZ58Gta8E9okbjQPrzWNWuSnk4b1oHWzcN9I+2RWmbHlbvS9KYjlwcQlmDt7B50f/vs7msUu0dzabi+myNT4Hcnghk6Z9ZsyxY6RIWZHYUK0Eal8xEdnhDhyYfb/+PnPD4L73BG+T0NNuoiLxqUZT/hGdYJw4Bqjg+oyNh5Ougt3/4kTzsdG3A+YC+Kn/By/8yN65SlPNzn+YxxP1I9tSHNtp5qGt/oh5bVUiHQ3rZkxukGqw8UnwqddMeqo/VhGZNn8Hbj/kzqU9sdA4MZHY6Ns/dRiMvjNnG0e3rd7cjJl/kTdynxHcgbMixfufGfmeFW327xuaO9fMHe5sHrn+ZGitMzeoYuPMub/6RZRS8n/XQdxge3HgwqC8vHzslQRbENs7i9h/Ghk2Xy3A9nMvgJu3wH/ug+v+bCIVr/xv8KiK1qYpcqgUSvBF4CIxfRJMNUkL/wImFpYDNzhoLtgsJwpMGmVXCzTuHt937X/GpBme/WUTUfNeMGf0N41ssWBFK1sO+lK2/L+78mwThQp14as13H2JKfs/Gtbcp7I1vjEML2TSdCB4ytxwxorA7XsaYhNMxCEY+QvgHb8xdn7xf0a+b82VmneBSSEda+7UiSNmTKEcz5PfAX2dVHaOo2jP8z80KcH93cEvxofTWmcaiDtdoGPHgyY9FkZGi49sMY9VZ5vo2XjmwQXrATcW6SXm0T8C17gXcueSPXetd7sRmEbZtB/iknzjByhdYSJwe58yr+ddZM6nWbNDOHDe/ap+cWSrhpqXzef8bxxZzuJUzwu0HDgwv7/ju6D9uPzfdRA32F4cuDCoqakZeyXBFsT2ziL2d46gtk/LN1UrL/y2SZna8eDIdVoPmYva4VX+wNyVBq8DdzByHbiUHHNXHUI7cO3HjFPT0+ar1AkmCgYm5XQstDYX/lXnmghFbMJQGuXA8b0j7WP1gmupNhG47ApfWiqYi24IHYU7tME4lvv/DUe3hx5X3QYzj6d0pSlygwqcezfUQmAcF+wp3nSskA7cv020ISFEqXOABZeYsdQG6bFnXdRaKXrHx3Cc24+NbCHgT/npULAY/eL/mFTVUDQfMGlwqz9sdL3r0dG/F2DbX+HQa7D+trHXtYuWahMtOu3TZtzDHbj6rSaNNHOWceDrNo6dyti8HxLSg0c1QzE8hbLnhElvzZ3DoU5v37BILGQSrNpmyUoTyXzjPsgo8xVuCenA7TG/9b4O81uz0Npo3D/6Br7f2VTao7sVelp957dy7w2Umpfk/66DuMH24sCFQULCxHtxCJNDbO8sYn/nGNX2hYtNlOqN+0a+t/l3oGJGznkBXwSuo8E4epHqwIEvjTLYHLi0IpPKeOBZ89o/CpZdad4fT0Pvhp3GoZhznml6PO8i2PkQ9PcQ33l05PzAjDIz76zZG4Hz/14wjmRSVuh+cNvuM/Pk4lNMpbtQHNpgjnFCqqnOmFkWGIE7cdRcfI4rAueN9ARrJdB62NggWPrkcIqXm30enprauBdQ3qhHzNgO3ImjoztwMTFw1n+Q2FYNbz0cer3nfmCaOZ/9ZVMEYs/jYzcg3/WIedzxgHONqnc8ZB4XX2MchREROK+ulIKy1aaCaLA+gBbVLxnHtOjkkVVnRyMpy0SyLAeuyZeaGJNVZnTaOA6HpWHX+NOVp4Jg1TateXC1L5v0ScsOlgPn7wBrbRy4k642N0n8I7dN+83vZLgDl11u1p1KB26ox6XXgStZbtKQq1+U/7sO4gbbiwMXBnl5QVKRhGlBbO8sYn/nGNP2S98NhzcFXoj2dcGm38KCy7yRm2FYDtyRN0y62/AUwUhiyIELEYEDU3EuJt70urJQyqRR1rw8duTCuniziscsfru5oN32F5QeHHmhGBtnHMojW00kxa9qKGDm4VWcYQqZDP/u/h4T3Vt0OSx/L7x5v3c+2DCsBt7+VQNzKgMdOGse0Hgc8MQME20INgduv9U+YBwOXMlyE+0cMRdvr7lQTs4yEcmxCpm0HwseHfbnpKsZyJ4Dz/8o+DE8vhu2/QXWfsxoYeFlJqocLEJo0VZv5lSu+7ixx0u3jz4Gu9jxIJSuMr/P8tPMsbR00N/jLWCy3Ly2NHAoxDy4bffDH642kberfxneOJQyxYCsOXCWc5I7l7z8ApM2OJbD8sov4I51o9+MmCg97eYGlf+8y8GB4NU2i5cDXqdt3kW+5VmzR/aC6zhuol+lq4yDvP9Z33uWfqxqthax8UbbU+n0D7VImeX7jtmnQM1LzvzfHRwMnA85Q3HDNY84cGFQX18/9kqCLYjtnUXs7xxj2v7kdwLK3H232P53Uxp83U3BP5OQahweq2JbJEfgFlwChUsCnTMLq4fYweehYKGJUvlTflrwAhHD2f+MqdCX4Z1PM/8SE3mw5noFs09OpS9FcngEDozz3HpoZErfnidMIYSl18EpnzDNxjf+ZuTnj+8yF52z1vp9Z1Wg4xTOnCelzHyrYCmU+542c4mC2Xg4lrNavyVweeNeUwEUzJyt0SJwA/3mAnq0CBxATCzH5r/PNGjf8/jI95/9rolinv4583rO+aZx/WhplNZ7qz8MK94PW+/1XURPF80HjPO/+O3m9fC2F8d2mMiyZeuCRaY67fBCJlob5/aBj0LZWvjIkxOrJptePDICl1Nlzj25c0afA/f6PfDE10zUdcsfx1excssfQ7dO8GfXY/CLdfDgTfDyz3zLrfTw4cVakjKMBmMTofIs3/Isbxq2fxqlVcAkb56JvNdv8RUnqX3FpBznzR85pty5U+zAeau6+t+gqjgdGnZy7MCOqfue8fLGvfDTpb7I4AzFDdc84sCFgRs88mhFbO8sYn/nGNP2maXmYmXbX8zFk9bw2p1m/kfFmcE/o5SJlDTsNK8j2YErWQGfeNGkNg7HKpXf3x3cibJSoNZ/P/Tcr74uE6Wbc55vWWIazL/YF+0KFqHMrjDzD2FkBA5MU968BfDUNwMLJGz7i4k8VZ1jLo4XXAqb7hrZn81q4O0fgcuuNKl03d7edM37TRQpWHppMFKDOHAD/bB/vWnePZ7Uu4JF5gLZ34HT2lu50OvA5S8wUZtQqYwdx03kd6wIHJCw8npTZfP5HwY6B3WbTZrrKZ+EVO/8vkRvC45dj4Z2JN562FyY5y+A028GNLz889AD6O00c+X8b5BMFit98qSrzGPxMuOIWmmUVmEcKwIX450HOdyBe/5H8Mx3YMm74f0PBDboDocMfwdun9FTfLI59+TNM+0Ohhf5ABNJfvhmE7m9+Ltw/C1fP8ZQDPTB098yxZeOh+gX2FoH970X7rve9H4sXQUbfu1rmzLkZAa5cbH6I2Zeof9czqAOnNcpzZtv5r6ifZVoa142545gv4fcOeZ3N1WtFVrrzM00/9+C97xd2O1Aeu/+Z4xzfODZsdeNYtxwzSMOXBh0d4/Rc0mwDbG9s4j9nWNctl96rYnM1G00d4+Pvmmib6NdkCdnm4vohPTglSrdgH8PsWBOVMFJJtKy7T64fSk8fevIEuC1rxgH0N+BAzj5GgAG45IhrWDktq1CJpmzfA6EP7FxcNF3zMXeprvNss5mE4Fb8i5f9cVTPmmcsm1/Cfx83SYTBfB3rq3nViGTpv1mHFbrhLFIzRs5B+7wJlNEYe7549tGbLyZZ2U5GWDSEv3n4uUvNBGkUHO2rB5wVgR1FLr7BuCMz5u0x/3PmDS4J74Ov73EpAye+qnADyx8G7TWmqjdcDqbzVwxa15o1mzz29n8++DNnPf9G+44BdZ/D5797zHHOm52PAilq32ORWy8cdSt+ZpHtpq5af69/crWmH2yUgkb3oLnvm/m0F3zq5HR53CwUii1Ng6c9zh2d3ebiJP2piz6s+dJeOBjxtF59x+MHWMTTERzNHY9aubegpmnO5wuD/zfWcb2F9wKH38Bzv+mSf19836zzmiR51M+btb3J5QDF58CGaXGQUzMME7LiaNGt36tXALInWPabfhX7QxGZ7PR6VjR3dY6E/kPKMayAhLSiT3w79E/O9VYxVvA58zOUNxwzSMOXBi0t7c7PYQZi9jeWcT+zjEu2y+6whQi2PYXE31LyjJ35UfDmgeXUxle0YNIIj7JV1HTvwKlRUwMXP4/8MnXTKTrxduNI/eGn7O0/xlz4Tl8vsu8iyAhjd600uD2saJywSJ//tuoOgeeu804HjseMI7N0mt961ScYcb+yh3DIkwbzEW7/3cPOXAHfI/Ben6FIjV/5Bw4Kw208uzxb2d4IRMrxS7PLwIHoefBWXO9xkqhxKv/5e8xF9qP/Sf8bIWZc7X03XDTC4HVP8Gkv6KCp1Huedw4I/690M74vHHgX73DRJk8h0z084Eb4Y/XGOdqybuNA9PeMOZ4x6Rpv4lSWemTFuWnGwetq8VUoLQKmFiUrTERX8vuD99solOX/XDyv9/0YujvMqm93h5w4LW9FVX1T6PsaYe/f9QU2HnPfZCQYqJ/Cy41TtZAX+jv2nS3uemx6ErY+qeRkedXf2luaHzoUXNsYuONNgtPNu9p7a22mTauCC4QvBdc4x6znzEx5mZK5VlmHpwVBZ19WtBNjbuVwBv3mijjby4YvdKsfwsBi9h4WHQFSQef8EUdp4PWQ9B22PwvORBk/u4Mwg3XPOLAhYEb+kJEK2J7ZxH7O8e4bJ+UYeZcbbsf3noEVn7AXFSNhr8D52bSiwFlokKhyJ8P77wLPvkKFC+FB2+ER75gikXsf9bcbR9ePj8+Gc6/hZhTPhF8m1YEbjQHTim46L9MVOH5HxnHseAkX2EWa51TP2XaCtz/QXjok8Z5aNwTmD7p/50tB81FfLg9/ILNgTu0AfIXhZd+ZxUysRxJKx3Nuti35g6FcuCsCNw4LsDLy8tNdOmMz5vvK15mojJX/cJXAt+ftAKYtc5XadKftx4xjmDJSt+yvHmw+Goz3/G/8uH2k+GuC8080rO+CB9/CdZ81KxrpbVOBqvlh5U+ObSjpwHa9CRr2OlLn7QoXW0e6zaalNu6DSZtcSqi55Ydj75porFeJ6W8vNwX5fJ3WHY8YNa79IeBqc3Lrjc3CPaFiBw17TeFfVZ90BSe6fb4mpmD+Z28+ksTIS1d5VuulIlUN+wwkaGm/eHdeArWC65xT+ActznnGgdmyx9NZK44yA0hGL8Dt/tf3hYoCn57aeiWIq11wQs0LX03sX0dwed+2oXVvHzVh0yUtOGt6fvuCMMN1zxjOnBKqbuVUg1KqaC3EJRS5yilWpVSW71/3/R77xKl1G6l1D6l1FemcuBO4Ia+ENGK2N5ZxP7OMW7bL7vOXFShfReco2FFriJ5/tt4yJplUvZG619mUbAIPvAwnHazuQj+zfkm6jE8fdJi3Y0cyArR2LrgJHNR6R9NC0bREljxXhMZrdtgjtPwC8/F1xin49AGc6FX+6rZ/sK3Ba6X6I06NB8wxVn6u8Nr2pyaZ9K/rDS8wUEzJv9CKeOhZIV5PLLVPDbtM6XPrSIwiWkmqhCqkIkVgRuHAzek/zUfhc+8Du9/KNABDsbCtxlnpMXvt9PbYaptLrx8pP0vuBXW3gjnfA2u+Bm8569w8xY47xsmylu8zMxTqpsCB27P48aBzBoWdSlbbb5j411mDtLwlOC0fBP13fWImUNWda7R0lRgNcM++IJ59DopNTU1JsKZmh/Y9Hzz74zTP1w3cy8wNwne+HPw79n8O9N+Y8X7zTyv3Lm+9GKA1/7PnMPO/tLIzy55J6QWmOhr8/7wIs8Q6MD1dZnnAQ6c9xyw/9/mxklsfPDtpJeYCNVohUy6PCYVcck74aNPmZsGf7gG3vxb4HqDAybiFcyBqzyLvqS8qZ17ORY1L5tI5amfNK9ncBqlG655xhOB+x1wyRjrvKC1Xu79+zaAUioW+AVwKXAScL1S6qTJDNZpkpKSnB7CjEVs7yxif+cYt+3nnGfmhC26InjrgOEMReBc7sBd+gN49+/Hv741N+3aP/ku8KvODbl6SPvHxsEl3xufrc/9hknTRJn5b8OJSzAVBP9jF3x+O3xum4kWBqsKmV1p5sBZEYDxNPG2sKI1Vhpl4x5TEGXWuvFvA4zD7F/IpHGvcST9HaP8USpRnjhimlTHjd1racj+So38jlBYju/m3/magO972ji8/umTFtkVcNkP4Jwvm+jQ/It986bAOHEly8cXgevtNFGkYEU/ulrMXL5g7Rrik02hkmA9DS3K1pgG5IP9JjV4qlKfrVTW6hfNo/emwJDtc+f5HJYj28w+rLph5PfHxht97/5XYMl+MNHurX8yaZbpReazqz9s9ufodqPDV38BC94WfN/jEk3Ubt9TJp01HN1DYC+4pv2Ahjw/JzCnyhfhHp5O7U9MjPnu0Ry4/f82x2j+JcY5+/Djxtl98KbANNwTR01KbzAHLiaWzjmXmhYpw+ft2kXtq2acWbONgzzVDtzep+Cui0dPsY0Q3HDNM6YDp7V+HpiIetYC+7TWB7TWvcB9wFVjfCaiycrKcnoIMxaxvbOI/Z1j3LaPjYcb15vUsvEQLQ5cTqVvzlU4LLocbnoOrr5z1DTIKdF+RrGZq3TWf/qiVBMlp8rrwIXRQsAiNd88WoVMDr1mHsONwA0vZNLk10LAIn+hcRAtB8qf9mPjKmACE7R/7hwzp+nFn8DPV5rIzpv3G6cx1NymsShbaxzWYI6ZPzsegMe/Erz5+IH1pnBQqIIxluOQmBn8d2ml1J771alNfbaORd1GEwXMNM7rkO39Wwm8/nsTgVoaYo7tsutMBNFKFbV4659mbtvqD/ute725EbD5t/Dar4wTFyz6ZrH6w2Z9PRie7iGwF9xQC4FhbQKsGznDG3gPJ3fO6CmUux83BYjKvGmvyVkm3XWw39xIsBjeA24YMcuuM3Nmdz40+niG0348/NYYnc2miqi171XnGId+Kp2tPY/DoVcDe1lGKG645ombou2cqpR6A6gH/lNrvQMoBQ75rVMHhLzNp5S6EbgRoKysjF27dlFSUkJjYyO9vb2Ul5dTU1NDRkYGcXFxNDc3U1payrFjxxgcHKSsrIza2toho3s8HmbPnk1dXR0xMTEUFhZy+PBhcnJy6O/vp62tbWibCQkJ5OXlUV9fT15eHt3d3bS3tw+9n5SURFZWFtu3b+ekk06ivb2dzs7OofdTUlJIS0ujoaGBoqIiPB4P3d3dQ++npaWRlJREY2NjxO3T0aNHKSgoiPh92r59OyUlJVG1T246Tvv27WPlypVRtU9uOU7bt2+nqqpqnPvUyuzZmdTt2TPmPuV2x5KHYl8LZKc1ztDjFEdn0grKu7tD7lNdXR2rVq2a/D4lryar+AI4enRS+xQfl0vmiXr6698gJjaR2uZesrRnXMepVCeSDhzavZW8nJPo2f4U6YmZtOgsGsP8n1uZfzIxO/7G8UMHKfQcoqn0IlI6O4f2qSy9nKT+bhr3b6E3tSRgnyoaa4hLy2Xfrl1jHqeuri5yc3PD196lv6bnjQcoPPA34v5lnIL+Jdexb+++CWkvPX42xf3dVL/2T1LmnRnyOA1ue5wsoHPzvdTGnxywT8U7/0VcfBqtKVW019aO2KfsnCWkA335J3G4pmbEPiXPupDeNV8ldfH7aTxwYEp/T/MTs4jp8dCTUcFgbx81NftoaWlh8eLFdA9mUtBxnPrdr1O49V70gsvZV9tAUlLbyHNERyLz8xbQ/crdNBZcMHSc5r76K3R6Gft7iyjv6hrap7y5lxG/5c/ExMbTWXYWh9qSKM/uCrFPHvIrLiFz/z+oaY8j8ejRcZ8jKlOKSATqdrxCXvN2ElE06Sy66+qGtHcs92wKyvbRm7GAo7t2hfw95aeWkdT8KK3NjXja2gOPU0oSJXue4ETx6aj2Dt/vafZ84pLy6N/2D06UXEBzczPlJ/aSDFR7+ino7BxxnPp6M5ifUcnga7+nf8G7xn2OSHvog3DiKPrjL437XJ7d8CrpwImcJTRVVxOXOI+yvg5qXv47sZVnTMm5PL1mC6lA/bb1dJbHRuz/3JqaGk6cOEF5eXlEXEeERGs95h9QAWwP8V4GkOZ9fhmw1/v8ncBv/NZ7P/C/4/m+VatW6UikqanJ6SHMWMT2ziL2dw7bbN/bqXXtBnu2HUVEnPa33a/1LRla375U61+cEt5nmw6Yz77+R/P656u1/tO7JzaOzfeYbe34h3ncdn/g+7WvmeW7/jXysz9epPUDHx/fkKfC/rWvaf3IF7Q+9tbEt9F62OzPK3eMvt7PVpn1vlOodU+7b/ngoNY/Wqj1fe8L/dkuj9bfytH6yW9OfJwT5RenmnH/+bqhRUO2f+sR894/P2ceq18efVsv3m7W+/UF5jg//S3z+oWfjFzX0sktGVoffn3scXoOaf3Yl7Xu6wlj57TW9Vt9er3/w1r/z8nhfd6f1/9gttW4b+R71S+Z97Y/OPK9hz6l9XfLtO7vNa9f+B+zbndb0K9pamrS+rkfmnWaq8c3tr5urb9TYD7TWj++z2it9RPf0PrbeVr3dpnXnc1a35ql9TPfHf82xuKH88y4nvvh1G3TYnDQ/E+bIiLpvA9s0kF8pUlXodRat2mt273PHwPilVJ5wGHAPy5c5l3mWtxQVjRaEds7i9jfOWyzfXwyzFoz9noznIjTvpU611Idfvqr/xy4zmaTShZu+qSFVSVxu7cww/CiElZ6WuOweXCDg94UyvGVgJ8S+89aC2/7MRQsnPg2MkpMqpuVdhqMjiaTajjnPFOWf+9TvveO7zKFZ0brt5eUaeZCnvH5iY9zoliVKP1SE4dsb1UX3fx705w+VI80i9UfgVM+ZeatHXgWXvixKXKz/H0j1y1bYypsLrrSVxxnNDLL4NLbxjV/MgD/XnDDK1CGi6X1YKmAu/9l0lCDFUaaf7Gp3mpVe2yt87Y4SA/6Ne3t7b45s1YPvLGo22TmegJUvzC+z4AZU8kKM98TTIp98fKpmwfX5TG/ewgsiDNVPPVN0yImWMr2BIi4834QJu3AKaWKlDIzWZVSa73bbAI2AvOUUpVKqQTgOiBIUrh7GDWUKdiK2N5ZxP7OIbZ3loizf7bf3Kdw5wElpJk5RB3HzXwnCL+AiYVVyGS3t8z5cAcuOcsU1RleyKSzycwF8m/CPgoRZf+yNXBoY+j3LefujC+Yaoz+JfKt0vpzxmiYXrpqZG+76cAqZOJ3HIdsn10BKtYU3AhWvGQ4iWlwyXfhhkdMYZ6v1sHn3jSVNIejlCny8c7fTsluhMTqBddSbeavTYUDF2we3J7HoeJ009plOFXnGOdu7xPmdbAecH50dnaaIkmzTzXVKMfTl636BUCZfQ3VumA4fV1mfufwuX9V55jzRHfb+LYzGpbTFhPvm4M4FgN949vnYztNddKOhpEN5ydIRJ13QjCeNgL3Aq8AC5RSdUqpjyilPq6U+rh3lXcC271z4H4GWPH3fuDTwBPAW8BftZkb51rc0BciWhHbO4vY3znE9s4ScfZPyfFrARGmA6eUKWTS0WQqKqrYwJ5o4WAVMhnoMaXVE9NGrpO/YGQvOKsH3DiaeEOE2X/WOmirC10g4tCr5gK1bLUpkrP3SV+j6v3/Nk7D8PYBkYLVSsDPgRuyfVyCcSRiEyfWuiAxHVJzQ78fG2+qutqJ1Qvu0KumlcbwojvhkJJroqXDHbim/cY5mR+icHtiuilUY0VmQ/WA8zJk/6XvNpHs9beNXv0STCuIoiWmiM94HbjDm02xlGAOnB7wNTefDFYkvups48yN5ph1eeCpW+B7ZfDqHaNvV2v415d8NxUadk5+rETYeScE46lCeb3WulhrHa+1LtNa36W1vlNrfaf3/f/VWi/WWi/TWp+itX7Z77OPaa3na63naK3/284dmQ7c0BciWhHbO4vY3znE9s4Skfa3UifDjcCBuZDuOG6iRUVLxm74PhpWyluoceQvNBE4/4s1qwfcOB24iLK/lXIcqp1A7WsmtTQ+2TTq7m2H/c8YJ67m5bGjb05SsNBUl8z3ta4IsP2K95nG5uE0fI80smab/oDgSwudCEp5WwkMc+D2eCNr8y8O/dn5F5ubGi01pnH4KA7ckP1PfgeUnwHP3Waqqt5xGrz0U5OO7E9ft4mYVZ4FlWeDpyawF2Ioal8xj8PTqWetM5o4sN78hrs8puXD8BYR4+H4btNKZe6FphroiSMj1+nrhpd/Dj9dZvYvJn5kNdPh7HjARB0v+BagTDRuCoio804IJp1COZNISZnEPzphUojtnUXs7xxie2eJSPtb8+DCbWYMJgLXftTcdZ9o+qSF1Ww6VDSjZLlxYqyLZvBF4MbRxBsizP5FSyEu2Zd+6k9/j0lDs2xacaaJlO78B9S8ZOYljTb/zWlOejt8fkdApCzA9mf+B5z9RQcGNoX49/abTAolmN9e07A5cHv+ZeYIjjY3dZ7XudvxAHR7RnXghuyflAkfehQ+tx0uuQ0SUs2cr92PBn6gboOJiFecCZVnmmXD58EN9MM/Pwcv/cy0bQCoeQUKThrpnMcnmfmOm38L35sF3y+HO0+Hv30k9P6FonGPcXqt3pbB0ij/+gF48hsmgn3T83DKJ8x5KpTD2NMOT3zD/C5P+YRJ9Z2iCFxEnXdCIA5cGKSlBUkREaYFsb2ziP2dQ2zvLBFp/9mnmovEcTpBAaTkmbvofZ0TL2BiYUXgQl0MWxGnfX7FPE6El0IZUfaPjTf7HKyQSf1Wc/FsFfiIjYeFl5uiFrsfN+mH5adP63DDIibGV+TGS0TZfiqwHLjETEgrmNy2cueaCJqVIntkm4myLgiRPmmRN9f8djd55/yN4sCNsH/WLOOofOhfkFEGG+8KfP/gC6BioPxUE/1OzR+ZRrnzIeOQPfX/4CeL4fGvmYhyqMI0p90M8y6EFe+Fi/7LRPas/o/h0LgH8uf7FTcaVsikt9OkGa/7BLzv71C81BSC0YOhU0Ff+LEpDHTZjyAmFgoXQ8Nb4Y8tCG7QvjhwYdDQ0OD0EGYsYntnEfs7h9jeWSLS/ms/BjdvGbuYRDBS8wBvSuNkI3CFi+GqO0xD5mCkF5om6XuHOXCJmSbNcBxEnP1nrTUX69aFu8Uhb2VBf5uedJWpOvj6783cp8mkqzpAxNl+slgOXN68if12/MmdA2hoPmjSZH97qbmh4t+oPBTzLjbpjTBqEZOQ9o+NM8VkDjwbOCeu+gXze0vKNPtXcaZxfqwUZq3h5Z+Z9NGPPWuczdfuNCmNoRrczz0frv0jXPp9OO0zMO8iU8W2o2ns/bTo6zbFRfIWmBs3iRkjixsd3myKG/lX7yxbDQnpxr7DadoPr/yvOffM9v7mChaZtNb+nvGPLQRu0L44cGFQVDS+O4bC1CO2dxaxv3OI7Z0l6uxvRVnSS0a9+z8ulDJ35kermjj3QnOHv8tjXrcfHXf0DSLQ/rPWmoIP9VsDl9e+5o2K+kV2qs42zupAb2SnT4Yg4mw/WYYcuEmmT4Jv3ucLP4I/vQuyyuGjT5s0vrGYd6Hv+Si/wVHtv/IDEBMHm+42r3s7TQuBijN961SeaeaaWU7ewedN9Oy0z0DpSnjHb+Bz2+DKn5ubDeMhf4F5HN4eZDSa95tIWv4Cc87ImzcyhdJqreDf2iY23vyG9j0zsujJa/9nll1wq29ZwSJTdGWsKpdaw/M/GrUgjBu0Lw5cGHg8HqeHMGMR2zuL2N85xPbOEnX2T/WWcp+1ZvJRiPEw70JzUXXgWfP6xPh7wEEE2r/Mm3Za/aJvmdYmAjdrWBpaXCIsuNQ8j+QCJiGIONtPlqxyUxijcPHkt2VVgN3+dxNd/fC/TK/A8VBxhumLp2JHvZkxqv3TC2HRFbDljyYafOg1c2Oh8izfOpVnm8eDz5nHl34KqQWw9FrfOpllxhkcb189y/kdHkEbDWtd67N580emUNZ65+ElZwcun3MutNYGOlu9nfDGfcbp9Ldfgfe4jpVG2XYYnvnOqBUu3aB9ceDCoLu72+khzFjE9s4i9ncOsb2zRJ39U7wRuMmmT46X0tWmmIeVRtl+dNw94CAC7Z+Wby6SX/yJSaUEk7bV2eRL5fLnzC/Aud/wFW9wERFn+8mSnAU3PQdrPjr5bSVlQNW5pjrne/9u0hbHS1yiicjmVJm5WyEY0/6rP2IKoWz3VmJUsYFz2XKqTKT94PNm3uv+f8O6m3zNuidC5iyITxl/Lzfwrqt8xY7y5pu5a1Z/ucEBUxgo2Dw8K6XSP41yx4PQ0wqrPxS4bu4c46AfG6NjmeU8Hgzd6NwN2re58UZ04Ya+ENGK2N5ZxP7OIbZ3lqizf/FSc6c6VK+qqSY2zlyE7XvalD0PMwIXkfZ/x13wq3PgvvfCjc/60r+G99ECkzbm0uqNEWn7yTIV0TeLDzw08c9e8VPoOTHqKmPav+IMM69s013GeStdaXrNWShlbjbse9o4jfGpsGYCFST9iYkxBVzCicA17jHpq9a8VysS17TXNK5v2Gnmigb7/eRUQXal1/m80Szb/FuzjeFFgWLjzfKxInBW+4fG3WZObpAoqBu0LxG4MHBDX4hoRWzvLGJ/5xDbO0vU2T+jBD758sR6yE2UeRdB+zGoft5UagwjAheR9k8rgOv+BB0NpvR59Ysm9WsyvcUikIi0fbSQkmOao4/CmPZXyjhkhzebCFbFGSPXqTzTFB3Z9heTKjk8RXEi5C8MLwJ3fE/gvMPhlSiH5r+FyAqYc56JlvX3mpYkdRth1YeCp4AXnjS2A+efvhkiCucG7YsDFwZuKCsarYjtnUXs7xxie2cR+08BVgGP1/9gHsMoYhKx9i9ZAVf+r+nxtu0+c/EZE12XVBFr+xnCuOy/7DqT0ogOLGBiYc2JU7Fw6ienZmD5800LhZ72wOWDA7D+++CpDVzWtNdX/ARMH8uYOJ8TWPuKSfX079Pnz5zzoK/D9Lnb9FvTkmPZdcHXLVhk5sxZ6ZnBaNpresclZfrmBw7DDdqPrrONzSQlTSJvWJgUYntnEfs7h9jeWcT+U0BagXF43vqneR2GAxfR9l/6Ljj9s+b5dM0pnEYi2vYzgHHZPynTFCWJSw4+hyxrNhSeDMuvD+0ghUueVYlyWBTu8GZY/13TjNvCU2ua2PtH4GLjTWrk8d2mAFDNK2bsoYoqVZ5lHNC3/gnb/gqL3z6y6bhFwUnm8fiu0ONv3GccyvIzQvaYc4P2xYELg8bGRqeHMGMR2zuL2N85xPbOIvafIuZeaNInIawUyoi3//m3wBU/M325ooyIt32UM277X/zfcNPzkJAa/P2PPQOX/3TqBpYfwoGznKGd//AVErHW8Y/Aga8SZeshU9Ak2Pw3i6QM075jw69Nz7rReu1ZDlzDzuDv93WZ78ydZxxDTw20jEyXdIP2xYELg5KScZaIFaYcsb2ziP2dQ2zvLGL/KcK/91UYRUwi3v4xsbDqg6EjAi4m4m0f5Yzb/gmpJq0xFHGJppjQVJFTZVIghxcyqX7B9MFLzIDnvm+WDW8hYJE3H5oP+NpxBIse+jPnPNOOpOAk48yFInMWJKTBsRAOXPMBQJs5wFZ6afXIeXBu0L44cGHgBo88WhHbO4vY3znE9s4i9p8iSleZAgrxqYGV8sZA7O8cYntniVj7x8abPnj+Ebj+XtPMft7FsO7jvihc4x7Te3L4DY68+aZv3Rv3QkL62NVBrRtAqz88ev/KmBhTZCVUBM4qYJI3z8yXS8kLmkYZsbb3Qxy4MOjt7XV6CDMWsb2ziP2dQ2zvLGL/KSIm1jTeDbMfmtjfOcT2zhLR9s+fHzjP7PBm6O8yVS9P+YQvCte4Z2T0DXzLDj4Ps9aM2g8PMHNoP/aM6X03FqNVomzyOnC5c31tFg4+b+bi+RHRtvciDlwYuKEvRLQitncWsb9ziO2dRew/hVz6Q7jhkbA+IvZ3DrG9s0S0/fMWQPNBE3kDbxqiMr3ZUnJ8Ubj6rSEcOL+WG6PNf/OndNX4Kr0WnGRaJ7Q3jHyvcR9klPrmC1aeCSeOQNP+gNUi2vZexIELAzf0hYhWxPbOIvZ3DrG9s4j9p5C4BF8z33Ei9ncOsb2zRLT98xeYOWnNXsen+gVT7dJKlbSicAM9IwuYgClMkl5sno81/y1crCh/sDTKpn0m+mZRebZ5HNZOIKJt70UcuDDIyMhweggzFrG9s4j9nUNs7yxif2cR+zuH2N5ZItr+llN2fDf098ChDSaaZWFF4SB4BA5MFE7FmsjaVFLgnU83PI1Sa5NC6e/A5VSZiNyweXARbXsvU1iWJvqJixNzOYXY3lnE/s4htncWsb+ziP2dQ2zvLBFt/9x5gPIVKenvhoozAtc543OmB6QV5RrOsveYhtqh2h9MlLR8U5zEamVg0dEI3a2B6ZvWPLi9T8Lg4FCKZkTb3otE4MKgubnZ6SHMWMT2ziL2dw6xvbOI/Z1F7O8cYntniWj7J6RA1ixTyGRo/ttpw9ZJhbUfC93CYPn1poedHRQsgiNvBC4bKmAyL3B55VnQ2RSQchnRtvcypgOnlLpbKdWglNoe4v33KqW2KaXeVEq9rJRa5vdetXf5VqXUpqkcuBOUlpY6PYQZi9jeWcT+ziG2dxaxv7OI/Z1DbO8sEW//vAVwfA8cfAGKl5o2IZHCvAvh6LbA4iRDLQTmBq5bcaYppNLXObQo4m3P+CJwvwMuGeX9g8DZWuslwHeAXw17/1yt9XKt9eqJDTFyOHbsmNNDmLGI7Z1F7O8cYntnEfs7i9jfOcT2zhLx9s9fYFIo6zYaJyiSOPmdgIJtf/Uta9oHsYmm2bc/WbPgw48HNAiPeNszDgdOa/08EDKWqLV+WWvd4n35KlA2RWOLOAYHB50ewoxFbO8sYn/nENs7i9jfWcT+ziG2d5aIt3/+AlNlcqAn8hy4zFJTVGXbX3w93pr2maIlY/WcwwW2Z+qLmHwE+Jffaw08qZTSwP9prYdH54ZQSt0I3AhQVlbGrl27KCkpobGxkd7eXsrLy6mpqSEjI4O4uDiam5spLS3l2LFjDA4OUlZWRm1tLVlZWQB4PB5mz55NXV0dMTExFBYWcvjwYXJycujv76etrW1omwkJCeTl5VFfX09eXh7d3d20t7cPvZ+UlERWVhY9PT00NzfT3t5OZ2fn0PspKSmkpaXR0NBAUVERHo+H7u7uoffT0tJISkqisbEx4vbp6NGjFBQURPw+9fT0cODAgajaJzcdp56eHjo7O6Nqn9xynHp6eqivr4+qfXLTcerp6aGrqyuq9slNxykjI4Pa2tqo2ie3HCeAtra2qNonNx2n/Px89uzZE7H7VJleQSKgVQyNKfNo2rUroo5TzpzLSXv6S5zY9SxNyVUU1+8grvhk9u7aNeZxSkxMpKGhISK0F9Jv0sO6j4dwriqAR7TWJ4+yzrnAHcAZWusm77JSrfVhpVQB8BTwGW9Eb1RWr16tN22KvClzu3btYuHChU4PY0YitncWsb9ziO2dRezvLGJ/5xDbO0vE27+rBb5fASUr4Mb1To9mJN1t8KN5sOJ9cMlt8N9FcNrNcMEtY340kmyvlNocbBralFShVEotBX4DXGU5bwBa68PexwbgQWBt8C24A8vjFqYfsb2ziP2dQ2zvLGJ/ZxH7O4fY3lki3v7J2VC6GhZf4/RIgpOUAQsug+0PmPTJwf7AFgKjEPG2ZwocOKXUbOAB4P1a6z1+y1OVUunWc+AiIGglS0EQBEEQBEEQXMTH/g2n3+z0KEKz9FroaobX7jSvc+eOvr6LGE8bgXuBV4AFSqk6pdRHlFIfV0p5W6zzTSAXuGNYu4BC4EWl1BvABuBRrfXjNuzDtOHxeJwewoxFbO8sYn/nENs7i9jfWcT+ziG2dxax/xQw93xIyYUtfzSvx+nAucH245oDN91E6hy4zs5OUlJSnB7GjERs7yxif+cQ2zuL2N9ZxP7OIbZ3FrH/FPHYF2HDr4wj96UD4/pIJNne1jlwM4W6ujqnhzBjEds7i9jfOcT2ziL2dxaxv3OI7Z1F7D9FLL3WPOaOb/4buMP24sCFQUyMmMspxPbOIvZ3DrG9s4j9nUXs7xxie2cR+08RpaugeDmUnzruj7jB9lPdBy6qKSwsdHoIMxaxvbOI/Z1DbO8sYn9nEfs7h9jeWcT+U4RS8LFnIQynzA22j3wXM4I4fPiw00OYsYjtnUXs7xxie2cR+zuL2N85xPbOIvafQsKMqLnB9uLAhUFOTo7TQ5ixiO2dRezvHGJ7ZxH7O4vY3znE9s4i9ncON9heHLgw6O/vd3oIMxaxvbOI/Z1DbO8sYn9nEfs7h9jeWcT+zuEG24sDFwZtbW1OD2HGIrZ3FrG/c4jtnUXs7yxif+cQ2zuL2N853GB7ceDCoLy83OkhzFjE9s4i9ncOsb2ziP2dRezvHGJ7ZxH7O4cbbC8OXBjU1NQ4PYQZi9jeWcT+ziG2dxaxv7OI/Z1DbO8sYn/ncIPtxYELg4SEBKeHMGMR2zuL2N85xPbOIvZ3FrG/c4jtnUXs7xxusL04cGGQl5fn9BBmLGJ7ZxH7O4fY3lnE/s4i9ncOsb2ziP2dww22FwcuDOrr650ewoxFbO8sYn/nENs7i9jfWcT+ziG2dxaxv3O4wfZKa+30GEaglDoORGICah7Q6PQgZihie2cR+zuH2N5ZxP7OIvZ3DrG9s4j9nSOSbF+utc4fvjAiHbhIRSm1SWu92ulxzETE9s4i9ncOsb2ziP2dRezvHGJ7ZxH7O4cbbC8plIIgCIIgCIIgCC5BHDhBEARBEARBEASXIA5cePzK6QHMYMT2ziL2dw6xvbOI/Z1F7O8cYntnEfs7R8TbXubACYIgCIIgCIIguASJwAmCIAiCIAiCILgEceAEQRAEQRAEQRBcgjhw40ApdYlSardSap9S6itOjyfaUUrNUko9q5TaqZTaoZT6rHf5rUqpw0qprd6/y5weazSilKpWSr3ptfEm77IcpdRTSqm93sdsp8cZjSilFvjpe6tSqk0p9TnRvn0ope5WSjUopbb7LQuqd2X4mfd/wTal1ErnRu5+Qtj+h0qpXV77PqiUyvIur1BKdfn9Bu50bOBRQgj7hzzXKKW+6tX+bqXUxc6MOjoIYfu/+Nm9Wim11btctD/FjHKd6Zpzv8yBGwOlVCywB7gQqAM2AtdrrXc6OrAoRilVDBRrrV9XSqUDm4GrgXcD7VrrHzk5vmhHKVUNrNZaN/ot+wHQrLW+zXsTI1tr/WWnxjgT8J57DgPrgA8h2rcFpdRZQDtwj9b6ZO+yoHr3Xsx+BrgMc1x+qrVe59TY3U4I218EPKO17ldKfR/Aa/sK4BFrPWHyhLD/rQQ51yilTgLuBdYCJcDTwHyt9cC0DjpKCGb7Ye//GGjVWn9btD/1jHKdeQMuOfdLBG5s1gL7tNYHtNa9wH3AVQ6PKarRWh/RWr/ufX4CeAsodXZUM56rgN97n/8ec6IT7OV8YL/WusbpgUQzWuvngeZhi0Pp/SrMBZfWWr8KZHkvBIQJEMz2Wusntdb93pevAmXTPrAZQgjth+Iq4D6tdY/W+iCwD3N9JEyA0WyvlFKYG9b3TuugZhCjXGe65twvDtzYlAKH/F7XIc7EtOG987QCeM276NPe8PXdksZnGxp4Uim1WSl1o3dZodb6iPf5UaDQmaHNKK4j8B+4aH/6CKV3+X8wvXwY+Jff60ql1Bal1HNKqTOdGtQMINi5RrQ/fZwJHNNa7/VbJtq3iWHXma4594sDJ0QsSqk04O/A57TWbcAvgTnAcuAI8GPnRhfVnKG1XglcCnzKm+oxhDZ515J7bSNKqQTgSuB+7yLRvkOI3p1BKfV1oB/4k3fREWC21noF8AXgz0qpDKfGF8XIucZ5rifw5p1o3yaCXGcOEennfnHgxuYwMMvvdZl3mWAjSql4zI/qT1rrBwC01se01gNa60Hg10j6hi1orQ97HxuABzF2PmalC3gfG5wb4YzgUuB1rfUxEO07QCi9y/+DaUApdQNwOfBe70UU3tS9Ju/zzcB+YL5jg4xSRjnXiPanAaVUHHAN8BdrmWjfHoJdZ+Kic784cGOzEZinlKr03hW/DnjY4TFFNd7877uAt7TWP/Fb7p9v/HZg+/DPCpNDKZXqndCLUioVuAhj54eBD3pX+yDwD2dGOGMIuAMr2p92Qun9YeAD3opkp2CKDBwJtgFhYiilLgG+BFypte70W57vLeyDUqoKmAcccGaU0cso55qHgeuUUolKqUqM/TdM9/hmABcAu7TWddYC0f7UE+o6Exed++Oc/HI34K2E9WngCSAWuFtrvcPhYUU7pwPvB960yugCXwOuV0otx4S0q4GbnBhclFMIPGjObcQBf9ZaP66U2gj8VSn1EaAGM8FasAGv43whgfr+gWjfHpRS9wLnAHlKqTrgFuA2guv9MUwVsn1AJ6Y6qDBBQtj+q0Ai8JT3PPSq1vrjwFnAt5VSfcAg8HGt9XgLcAhBCGH/c4Kda7TWO5RSfwV2YlJbPyUVKCdOMNtrre9i5NxnEO3bQajrTNec+6WNgCAIgiAIgiAIgkuQFEpBEARBEARBEASXIA6cIAiCIAiCIAiCSxAHThAEQRAEQRAEwSWIAycIgiAIgiAIguASxIETBEEQBEEQBEFwCeLACYIgCK5HKdXufaxQSr1nirf9tWGvX57K7QuCIAhCOIgDJwiCIEQTFUBYDpxSaqyeqAEOnNb6tDDHJAiCIAhThjhwgiAIQjRxG3CmUmqrUurzSqlYpdQPlVIblVLblFI3ASilzlFKvaCUehjTnBil1ENKqc1KqR1KqRu9y24Dkr3b+5N3mRXtU95tb1dKvamUutZv2+uVUn9TSu1SSv1JebtSC4IgCMJkGeuuoyAIgiC4ia8A/6m1vhzA64i1aq3XKKUSgZeUUk96110JnKy1Puh9/WGtdbNSKhnYqJT6u9b6K0qpT2utlwf5rmuA5cAyIM/7mee9760AFgP1wEvA6cCLU72zgiAIwsxDInCCIAhCNHMR8AGl1FbgNSAXmOd9b4Of8wZws1LqDeBVYJbfeqE4A7hXaz2gtT4GPAes8dt2ndZ6ENiKSe0UBEEQhEkjEThBEAQhmlHAZ7TWTwQsVOocoGPY6wuAU7XWnUqp9UDSJL63x+/5APL/VhAEQZgiJAInCIIgRBMngHS/108An1BKxQMopeYrpVKDfC4TaPE6bwuBU/ze67M+P4wXgGu98+zygbOADVOyF4IgCIIQArkjKAiCIEQT24ABbyrk74CfYtIXX/cWEjkOXB3kc48DH1dKvQXsxqRRWvwK2KaUel1r/V6/5Q8CpwJvABr4ktb6qNcBFARBEARbUFprp8cgCIIgCIIgCIIgjANJoRQEQRAEQRAEQXAJ4sAJgiAIgiAIgiC4BHHgBEEQhIhBKfUvpdQHp3pdQRAEQYgWZA6cIAiCMCmUUu1+L1MwJfQHvK9v0lr/afpHJQiCIAjRiThwgiAIwpShlKoGPqq1fjrIe3Fa6/7pH5W7EDsJgiAIoyEplIIgCIItKKXOUUrVKaW+rJQ6CvxWKZWtlHpEKXVcKdXifV7m95n1SqmPep/foJR6USn1I++6B5VSl05w3Uql1PNKqRNKqaeVUr9QSv0xxLjHGmOOUuq3Sql67/sP+b13lVJqq1KqTSm1Xyl1iXd5tVLqAr/1brW+XylVoZTSSqmPKKVqgWe8y+9XSh1VSrV6x77Y7/PJSqkfK6VqvO+/6F32qFLqM8P2Z5tS6u1hHj5BEAQhQhEHThAEQbCTIiAHKAduxPzf+a339WygC/jfUT6/DtOXLQ/4AXCXt59buOv+GdNkOxe4FXj/KN851hj/gEkVXQwUAP8DoJRaC9wDfBHIwjT2rh7le4ZzNrAIuNj7+l/APO93vA74p6L+CFgFnIax75eAQeD3wPuslZRSy4BS4NEwxiEIgiBEMNLIWxAEQbCTQeAWrXWP93UX8HfrTaXUfwPPjvL5Gq31r73r/h64AygEjo53XaVUArAGOF9r3Qu8qJR6ONQXaq2bQo1RKVUMXArkaq1bvKs85338CHC31vop7+vDo+xXMG7VWnf4jeNuvzHcCrQopTKBE8CHgVO01tZ3vOxd72Hg/5RS87TWezGO6l+8+y0IgiBEARKBEwRBEOzkuNa623qhlEpRSv2fN/WvDXgeyFJKxYb4/JCjprXu9D5NC3PdEqDZbxnAoVADHmOMs7zbagny0VnA/lDbHQdDY1JKxSqlbvOmYbbhi+Tlef+Sgn2X19Z/Ad6nlIoBrsdEDAVBEIQoQRw4QRAEwU6GV8r6D2ABsE5rnYFJMwQIlRY5FRwBcpRSKX7LZo2y/mhjPOTdVlaQzx0C5oTYZgcm7dKiKMg6/rZ6D3AVcAGQCVT4jaER6B7lu34PvBc4H+jUWr8SYj1BEATBhYgDJwiCIEwn6Zg0So9SKge4xe4v1FrXAJuAW5VSCUqpU4ErJjJGrfURzNy0O7zFTuKVUpaDdxfwIaXU+UqpGKVUqVJqofe9rcB13vVXA+8cY9jpmHYMTRjH77t+YxgE7gZ+opQq8UbrTlVKJXrffwWTuvpjJPomCIIQdYgDJwiCIEwntwPJmCjSq8Dj0/S97wVOxThE/4VJM+wJse7tjD7G9wN9wC6gAfgcgNZ6A/AhTFGTVszcuHLvZ/4fJmLWAnwLU1RlNO4BajDz6HZ6x+HPfwJvAhuBZuD7BP5PvwdYAgSttCkIgiC4F+kDJwiCIMw4lFJ/AXZprW2PADqBUuoDwI1a6zOcHosgCIIwtUgEThAEQYh6lFJrlFJzvKmNl2Dmlz3k8LBswTvX75PAr5weiyAIgjD1iAMnCIIgzASKgPVAO/Az4BNa6y2OjsgGlFIXA8eBY4ydpikIgiC4EEmhFARBEARBEARBcAkSgRMEQRAEQRAEQXAJcU4PIBh5eXm6oqLC6WGMoL+/n7i4iDSZEAWIvgQ7EX0JdiL6EuxE9CXYTaRqbPPmzY1a6/zhyyNvpEBFRQWbNm1yehgj2LVrFwsXLhx7RUGYAKIvwU5EX4KdiL4EOxF9CXYTqRpTStUEWy4plGFQXl4+9kqCMEFEX4KdiL4EOxF9CXYi+hLsxm0aEwcuDGpqgjrBgjAliL4EOxF9CXYi+hLsRPQl2I3bNCYOXBhkZGQ4PQQhihF9CXYi+hLsRPQl2InoS7Abt2ksIufABaOvr4+6ujq6u7sdG8PAwACtra2Ofb8Q3Yi+nCcpKYmysjLi4+OdHsqUE4mTs4XoQfQl2InoS7Abt2nMNaOtq6sjPT2diooKlFKOjKGrq4vk5GRHvluIfkRfzqK1pqmpibq6OiorK50ezpTT3NxMQUGB08MQohTRl2Anoi/BbtymMdekUHZ3d5Obm+uY8waQkJDg2HcL0Y/oy1mUUuTm5joa5beT0tJSp4cgRDGiL8FORF+C3bhNY65x4ABHnTcwaZyCYBeiL+dx+hxjJ8eOHXN6CEIUI/oS7ET0JdiN2zTmKgdOEARBmBiDg4NOD0GIYkRfgp2IvgS7cZvGXDMHLhKIxsIGQuQg+hLspKyszOkhCFGM6EuwE9GXMGVoDe0N0Lwfmg9Ak3mcdcrnnB5ZWEgEbpx4PB5+/vOfh/25yy67DI/HM/UDcoDf/e53fPrTn3Z6GFOCx+PhjjvuCPtzdh7P3t5eW7YbCrcez9tvv53Ozk6nh+E6amtrnR6CEMWIvgQ7EX0JYWE5aTWvwJY/wr+/DX/9INx5BnyvDH48H357KfzjU/Dyz+Domxw/uNPpUYeFRODGicfj4de//jWf+9znApb39/ePWnr0scces3lkwkSwHLhPfvKTAcudPJ5uK2HrFLfffjvve9/7SElJcXooriIrK8vpIQhRjOhLsBPRlzACraGj0UTSvFE03/OD0HvCt66KhexyyJkD5adDTpV5nlsFmbMhNo6Eo0ed25cJ4Morxm/9cwc769umdJsnlWRwyxWLQ77/la98hQMHDrB8+XLi4+NJSkoiOzubXbt2sWfPHq6++moOHTpEd3c3n/3sZ7nxxhsBqKioYNOmTbS3t3PppZdyxhln8PLLL1NaWso//vGPkGXjf/3rX/OrX/2K3t5e5s6dyx/+8AdSUlI4duwYH//4xzlw4AAAv/zlLznttNO45557+NGPfoRSiqVLl/KHP/wh6Hbvv/9+vvWtbxEbG0tmZibPP/88nZ2d3HDDDWzfvp0FCxZQX1/PL37xC1avXs1vf/tbvve975GVlcWyZctITEycpKWD8K+vwNE3p3abRUvg0ttCvv2Vr3yF/fv3R9Tx1Fpz5513RszxvOGGG0hOTmbLli00NDRw9913c8899/DKK6+wbt06fve73wFw77338t3vfhetNW9729v4/ve/D0BaWhqf+MQneOyxxyguLua73/0uX/rSl6itreX222/nyiuvZGBggK985SusX7+enp4ePvWpT3HTTTexfv16br31VvLy8ti+fTurVq3ij3/8Iz//+c+pr6/n3HPPJS8vj2effZa0tDTa29sB+Nvf/sYjjzzC7373u3GPXxAEQRCECGTISTsw0lFrPgg9fr7AkJNWBbNPhdw5XketCrJmQ2x0TVNxpQPnBLfddhtvvvkmW7duZf369bztbW9j+/btQ/2i7r77bnJycujq6mLNmjW84x3vIDc3N2Abe/fu5d577+XXv/417373u/n73//O+973vqDfd8011/Cxj30MgG984xvcddddfOYzn+Hmm2/m7LPP5sEHH2RgYID29nZ27NjBf/3Xf/Hyyy+Tl5dHc3NzyP349re/zRNPPEFpaelQKuAdd9xBdnY2O3fuZPv27SxfvhyAI0eOcMstt7B582YyMzM599xzWbFixSQtGRncdtttbN++PaKOZ3t7OwMDAxF1PFtaWnjllVd4+OGHufLKK3nppZf4zW9+w5o1a9i6dSsFBQV8+ctfZvPmzWRnZ3PRRRfx0EMPcfXVV9PR0cF5553HD3/4Q97+9rfzjW98g6eeeoqdO3fywQ9+kCuvvJK77rqLzMxMNm7cSE9PD6effjoXXXQRAFu2bGHHjh2UlJRw+umn89JLL3HzzTfzk5/8hGeffZa8vLwxj/NY47dsMxPweDwUFRU5PQwhShF9CXYi+opitIbOpiBRtAPmb7iTljXbOGez1nmjaHOmxElzm8Zc6cCNFimzE/8S42vXrg1o9vuzn/2MBx98EIBDhw6xd+/eERf8lZWVQxeMq1atorq6OuR3bd++nW984xt4PB7a29u5+OKLAXjmmWe45557AIaiLvfccw/vete7hi5oc3JyQm739NNP54YbbuDd734311xzDQAvvvgin/3sZwE4+eSTWbp0KQCvvfYa55xzDvn5+QBce+217NmzZ3QjTYRRImXTRSQcz+TkZGJjYyPqeF5xxRUopViyZAmFhYUsWbIEgMWLF1NdXU1NTU3ANt/73vfy/PPPc/XVV5OQkMAll1wCwJIlS0hMTCQ+Pp4lS5YM2erJJ59k27Zt/O1vfwOgtbWVvXv3kpCQwNq1a4cmri9fvpzq6mrOOOOMUccb7vhnkgM3e/Zsp4cgRDGiL8FORF8uR2vobA6d7tjT6ltXxRhnLGcOlK3xOmh+TlqcPT1z3aYxVzpwTqG1Hnqempo69Hz9+vU8/fTTvPLKK6SkpHDOOecEbQbsn64WGxtLV1dXyO+64YYbeOihh1i2bBm/+93vWL9+/ZTsw5133slrr73Go48+yqpVq9i8efOUbNftRMLx7OvrIzY2Nqxx2308rX2MiYkJ2N+YmBj6+/tHrZwZHx8/dNPD//PWZ8H8pn7+858PObQW69evH2Ff6zPD8b+xMvw4jTX+mURdXR3z5893ehhClCL6EuxE9OUChpy0IOmOTQdCOGlVxknLqfI5ajY6aaPhNo1JFcpxkp6ezokTJ4K+19raSnZ2NikpKezatYtXX3110t934sQJiouL6evr409/+tPQ8vPPP59f/vKXAAwMDNDa2sp5553H/fffT1NTE8CoKXf79+9n3bp1fPvb3yY/P59Dhw5x+umn89e//hWAnTt38uabZj7aunXreO6552hqaqKvr4/7779/0vsVKcjxnJrjuXbtWp577jkaGxsZGBjg3nvv5eyzzx735y+++GJ++ctfDjUx37NnDx0dHaN+ZvixKyws5K233mJwcHAoaiqMJCZGTveCfYi+BDsRfUUQnc1waCO88Rd49rvwt4/Ar86F75fDD6vgrgvgwZvghR9B3UZIzoal74KLvwfv+St8ehN8/Rh89g14/4Pwth/BqZ+E+RdD3lxHnDdwn8YkAjdOcnNzOf300zn55JNJTk6msLBw6L1LLrmEO++8k0WLFrFgwQJOOeWUSX/fd77zHdatW0d+fj7r1q0bumD96U9/yo033shdd91FbGwsv/zlLzn11FP5+te/ztlnn01sbCwrVqwIWaDhi1/8Inv37kVrzfnnn8+yZcuYN28eH/zgBznppJNYuHAhixcvJjMzk+LiYm699VZOPfVUsrKyoirdTI7n1BzP4uJibrvtNs4999yhIiZXXXXVuD//0Y9+lOrqalauXInWmvz8fB566KFRP3PjjTdyySWXUFJSwrPPPsttt93G5ZdfTn5+PqtXrx4qaCIE4q9xQZhqRF+CnYi+phkrkhZsXlq3x29FBVmzTOTs5HcGpjtml0OcDYXvbMJtGlP+aYGRwurVq/WmTZsClr311lssWrTIoREZurq6QlYZdDMDAwP09fWRlJTE/v37ueCCC9i9ezcJCc7cBZmpTJW+5HhOjkg419jBrl27WLhwodPDEKIU0ZdgJ6IvG+hqMamNAQ2tvc+7WvxWVJA5y5Tct5wzy1FzmZM2GpGqMaXUZq316uHLJQIXBtHap6uzs5Nzzz2Xvr4+tNbccccdcrHvAFOlLzmeQjBGK4YjCJNF9CXYiehrgnS1eJ2zII5aMCctpxIWvz3QUcuuiBonbTTcprHo9Ehswo5o5ac+9SleeumlgGWf/exn+dCHPjSp7f73f//3iDlO73rXu/j6178+Yt309HSGRzyFiTGZ4zmavuw8nuFsW3AvM61oizC9iL4EOxF9jUKXx9cXzT+K1rQfuvzn0CvILDOO2UlXD0t3rID4JGfGHyG4TWOuSqFcuHBhQMW56SZaUyiFyED05Txaa3bt2iUplIIQJqIvwU5mvL66WwN7o/k7ap1NgetmlIVId6yY8U7aaESqxlyfQpmUlERTUxO5ubmOOXH+ZcgFYaoRfTmL1pqmpiaSkqLzH1x5ebnTQxCiGNGXYCczQl/drcMKh/g5asGctJxKWHTFyHTHeLkRPBHcpjHXOHBlZWXU1dVx/Phxx8bQ19c3at8rQZgMoi/nSUpKGmoeHm3U1NRE5N1FIToQfQl2EjX66m7zS3EcNi+tszFw3YxS45gtvDww3TGnUpw0G3CbxlzjwMXHx1NZWenoGA4cOEBVVZWjYxCiF9GXYCdSyEawE9GXYCeu0ld3m6/0/nBHrWNYECK9xDhnCy8zDlquNSetEhJSnBn/DMVVGsNFDlwkkJeX5/QQhChG9CXYiehLsBPRl2AnEaevnhPD5qL5FRAZ4aQVG+dswaXeCJrXURMnLaKIOI2NwaQcOKXUJcBPgVjgN1rr24a9fwPwQ+Cwd9H/aq1/M5nvdJL6+noyMjKcHoYQpYi+BDsRfQl2IvoS7MQRfVlOWrB5aR0NgeumFxvnbP4lvihazhyT7piQOr3jFiaE285hE3bglFKxwC+AC4E6YKNS6mGt9c5hq/5Fa/3pSYwxYnCbdy64C9GXYCeiL8FORF+Cndimr552n2PWvD8w3bH9WOC6aUXGOZt/UWC6Y06VOGlRgNvOYZOJwK0F9mmtDwAope4DrgKGO3BRQ3d3t9NDEKIY0ZdgJ6IvwU5EX4KdTEpfvR3DomiWo3YA2o8GrptWaJyzeReOTHdMTJvcTggRjdvOYZNx4EqBQ36v64B1QdZ7h1LqLGAP8Hmt9aEg66CUuhG4EUzFyV27dlFSUkJjYyO9vb2Ul5dTU1NDRkYGcXFxNDc3U1payrFjxxgcHKSsrIza2lqysrIA8Hg8zJ49m7q6OmJiYigsLOTw4cPk5OTQ399PW1vb0DYTEhLIy8ujvr6evLw8uru7aW9vH3o/KSmJrKwsqqurSUlJob29nc7OzqH3U1JSSEtLo6GhgaKiIjweD93d3UPvp6WlkZSURGNjY8Tt09GjRykoKJB9ioB96uzsBIiqfYrG4+TWfTpy5EjAmKNhn6LxOLl1n6qrq8nJyYmqfYrG4+TWfert7aW7uzv0PhXl0bD7NRI76sgZbKarficp3UeI9VQT2xk4J20wtYDu5GJiZp1BT2oZ7QkF5M5fS82JWBLTc0buk6eT8sxYanbtkuMUxftUX19Pbm5uxO1TKCbcyFsp9U7gEq31R72v3w+s80+XVErlAu1a6x6l1E3AtVrr88badrBG3pGANFoW7ET0JdiJ6EuwE9GXYCddXV0kx+ph6Y7e4iHN++HEkcAPpBYEpjj6P09Md2YnhIgmUs9hdjTyPgzM8ntdhq9YCQBaa//Og78BfjCJ73Mct/WIENyF6EuwE9GXYCeiLyEsBvqgywNdzdDVYv46/Z4PWx7XegS6hlV3TM03KY5zzjPFQvzTHZPcU4xCiAzcdg6bjAO3EZinlKrEOG7XAe/xX0EpVay1tm6LXAm8NYnvc5ykpCSnhyBEMaIvwU5EX4KdiL5mKAP9fk7XSMcr+PIW6D0RepsqBpKzITnHPKYX051WQfyspZBb5WtoLU6aMIW47Rw2YQdOa92vlPo08ASmjcDdWusdSqlvA5u01g8DNyulrgT6gWbghikYs2NYOa+CYAeiL8FORF+CnYi+XM5AP3R7xhUN8y3zQE9b6G0OOWLev7QiyF9knqfkBL5n/aXkQEI6xMQEDs/jAdGYYCNuO4dNqg+c1vox4LFhy77p9/yrwFcn8x2RxNGjR113gAX3IPoS7ET0JdiJ6CtCGOiH7tYwomGWI9YaepsqBpKy/ByxAshfEBglS8mB5KzAZYkZIxyxiSL6EuzGbRqblAM30ygoKHB6CEIUI/oS7ET0JdiJ6GuKGRwwjtiYkbBhy7tHccRQgU5WSh7kzhsWDfN7nuJ9TMycMkdsooi+BLtxm8bEgQuD9vZ2cnJynB6GEKWIvgQ7EX0JdiL6CoHliI07NdG7fCxHLCnT53il5BpHzD8NMcAhyzLPk7Icd8QmiuhLsBu3aUwcuDAYrR+DIEwW0ZdgJ6IvwU6iXl/DHbHxOmTdrcAo7Zr8UxNTckwVxRGRsGHzxZIyISZ2uvY8Ioh6fQmO4zaNiQMXBuXl5U4PQYhiRF+CnYi+BDtxjb4GB818L2vu13hTE7s8jO6IZQY6XtmVo6Qm5sxYR2yiuEZfgmtxm8bEgQsDt/WIENyF6EuwE9GXYCfTri/LEfMvTT+uuWIeRnXEEjNNymGKnyMWMjXRep4ljpjNyPlLsBu3aUwcuDBISUlxeghCFCP6EuxE9CXYyYT1NThoStEHOF6ecaQmekAPht5uYkZg2mF2+ejRMGuOWKxcFkUicv4S7MZtGpMzVRikpaU5PQQhihF9CXYi+hLsJC011TdHLMD5CjZfbFhqoh4IveHEjMDKiZmzRo+GpeSY1MTY+OnadWEakPOXYDdu05g4cGHQ0NDgqgo1grsQfQl2IvoSppTeTqh9GQ6shwPryT62c3RHLCE9sDR9ZtkohTpyfKmJ4ogJyPlLsB+3aUwcuDAoKipyeghCFCP6EuxE9CVMisEBOLIV9j9rnLZDr8FAL8QmwKx19Ky6iaSc0tCVE8UREyaBnL8Eu3GbxsSBCwOPx+OqLu2CuxB9CXYi+hLCQmtoPuCNsD0LB5/39SYrXAJrb4Q558LsUyEhlaPV1VRUVDg5YiGKkfOXYDdu05g4cGHQ3d3t9BCEKEb0JdiJ6EsYk45GOPiccdr2r4fWWrM8owwWXQFV50Ll2ZCWP+Kjoi/BTkRfgt24TWPiwIWB23pECO5C9CXYiehLGEFfF9T45rFxdJtZnpgJlWfC6Tcbpy13Dig16qZEX4KdiL4Eu3GbxsSBCwO39YgQ3IXoS7AT0Zdg5rG94UuLrH0NBnogJh5mrYPzvmEctuLlYZfTF30JdiL6EuzGbRoTBy4M3FZiVHAXoi/BTkRfM5SheWzrzTy2rhazvPBkWPsx47CVm3lsk0H0JdiJ6EuwG7dpTBy4MEhKSnJ6CEIUI/oS7ET0NUPobPY5bAfWg6fGLM8ohQVvg6pzoOpsSCuY0q8VfQl2IvoS7MZtGhMHLgwaGxvJy8tzehhClCL6EuxE9BWl9HVB7asmJfLAejiyDdCmAXbFmXDaZ4zTljt3zHlsk0H0JdiJ6EuwG7dpTBy4MCgpKXF6CEIUI/oS7ET0FSUMDsLRN3wRtppX/OaxrYVzv2bSIktWhD2PbTKIvgQ7EX0JduM2jYkDFwaNjY1kZGQ4PQwhShF9CXYi+nIxLdW+BtoHn4euZrO8YDGs+aiJsJWfBonOzeEQfQl2IvoS7MZtGhMHLgx6e3udHoIQxYi+BDsRfbmIzmbjqFlpkS3VZnl6CSy41DhslWdDeqGDgwxE9CXYiehLsBu3aUwcuDBwW48IwV2IvgQ7EX1FMH3dcOhVbwPtZ02pfzQkpJt+bKd8yjhtefNsncc2GURfgp2IvgS7cZvGxIELA7f1iBDchehLsBPRVwQxOGiaZlvz2Gpfgf5uiImDsrVwzleNw1a6alrnsU0G0ZdgJ6IvwW7cpjF3/GeIENyUGyu4D9GXYCeiL4dpqfE10D7wnG8eW/4iWP1hv3ls6U6OcsKIvgQ7EX0JduM2jYkDFwZxcWIuwT5EX4KdiL6mmc5mqH7BlxbZctAsTy+G+RebSpFVZ0N6kaPDnCpEX4KdiL4Eu3Gbxtw1Wodpbm6moGBqwGraNQAAqQtJREFUm58KgoXoS7AT0ZfN9Pd4+7GtN3/1Wxiax1ZxBqz7OMw5F/LmR+w8tskg+hLsRPQl2I3bNCYOXBiUlpY6PQQhihF9CXYi+ppiBgfh2HZfpciaV6C/yzuPbQ2c8xW/eWzxTo/WdkRfgp2IvgS7cZvGxIELg2PHjpGe7s75CULkI/oS7ET0NQV4an0RtgPPQWejWZ6/EFbdYBy2itNdO49tMoi+BDsRfQl24zaNiQMXBoODg04PQYhiRF+CnYi+JkBXCxx8wee0Ne83y9OKYO4FxmGrOgcyip0bY4Qg+hLsRPQl2I3bNCYOXBiUlZU5PQQhihF9CXYi+hoH/T1waIMvLbJ+C+hBSEgz89jWfsw4bPkLo3Ie22QQfQl2IvoS7MZtGhMHLgxqa2td1SNCcBeiL8FORF9BGByEhh2+SpE1L5t5bCoWylbDWV8yDlvZ6hkxj20yiL4EOxF9CXbjNo2JAxcGWVlZTg9BiGJEX4KdiL68tNYZZ+3Aejj4HHQcN8vzFsDKD5hKkeWnQ5K7egI5jehLsBPRl2A3btOYOHCCIAhC9NLlgeoXfWmRTfvM8rRCmHOe3zy2EufGKAiCIAhhIA5cGHg8HoqKoqPpqhB5iL4EO5kx+urvhboNvrTI+tfNPLb4VDOPbfVHjMNWsEjmsU0hM0ZfgiOIvgS7cZvGxIELg9mzZzs9BCGKEX0JdhK1+tIaju3wVYqseQn6Os08ttJVcOZ/mrTI0tUQl+D0aKOWqNWXEBGIvgS7cZvGxIELg7q6OubPn+/0MIQoRfQl2ElU6av1sNdhe9b0Y+toMMvz5sOK93n7sZ0BSZlOjnJGEVX6EiIO0ZdgN27TmDhwYRATE+P0EIQoRvQl2Imr9dXd6p3Htt6kRTbtNctTC3xz2KrOhkx3lYGOJlytLyHiEX0JduM2jYkDFwaFhYVOD0GIYkRfgp24Sl/9vVC30ZcWeXgz6AGITzEVIld/yDuP7SSZxxYhuEpfgusQfQl24zaNiQMXBocPH3ZVjwjBXYi+BDuJaH1pDQ1v+SpFVr8EfR2gYrzz2L4AVedC2RqZxxahRLS+BNcj+hLsxm0aEwcuDHJycpweghDFiL4EO4k4fbXV+yJsB9ZD+zGzPHceLH+Pbx5bcpZjQxTGT8TpS4gqRF+C3bhNY+LAhUF/f7/TQxCiGNGXYCeO66u7zTeP7cB6aNxtlqfkGWdtzrlQeTZkzXJwkMJEcVxfQlQj+hLsxm0aEwcuDNra2igpkWavgj2IvgQ7mXZ9DfRB3SZfWmTdJjOPLS4ZKk6Hle83aZEFJ4HLJo8LI5Hzl2Anoi/BbtymMXHgwqC8vNzpIQhRjOhLsBPb9aU1HN/lqxRZ8xL0tpt5bCUr4YzPm0jbrLUQl2jvWIRpR85fgp2IvgS7cZvGJuXAKaUuAX4KxAK/0VrfFmK9dwB/A9ZorTdN5judpKamxlUTHAV3IfoS7MQWfbUdGTaP7ahZnjMHll3nN48te2q/V4g45Pwl2InoS7Abt2lswg6cUioW+AVwIVAHbFRKPay13jlsvXTgs8BrkxloJJCQINXPBPsQfQl2MiX66jlhKkRaaZHHd5nlKXmmD1vVueYxa/bkv0twFXL+EuxE9CXYjds0NpkI3Fpgn9b6AIBS6j7gKmDnsPW+A3wf+OIkvisiyMvLc3oIQhQj+hLsZEL6GugzPdistMjDm2Cw38xjKz8Nlr/XFB8pWCzz2GY4cv4S7ET0JdiN2zQ2GQeuFDjk97oOWOe/glJqJTBLa/2oUmpUB04pdSNwI0BZWRm7du2ipKSExsZGent7KS8vp6amhoyMDOLi4mhubqa0tJRjx44xODhIWVkZtbW1ZGVlAeDxeJg9ezZ1dXXExMRQWFjI4cOHycnJob+/n7a2tqFtJiQkkJeXR319PXl5eXR3d9Pe3j70flJSEllZWWzfvp2TTjqJ9vZ2Ojs7h95PSUkhLS2NhoYGioqK8Hg8dHd3D72flpZGUlISjY2NEbdPR48epaCgQPYpAvaps7NzaNzRsk/ReJzcuk81NTWkp6ePvk8nTlCR1kPrln+Qfnwzycc2o3rb0SqG3tzFnFj4PtKXXk71QCHJ6Vm+fUpqk+M0w/dp3759rFy5Mqr2KRqPk1v3qbe3l5SUlKjap2g8Tm7ep/r6elatWhVx+xTSb9Jaj+ZXhf6gUu8ELtFaf9T7+v3AOq31p72vY4BngBu01tVKqfXAf45nDtzq1av1pk2RN1WusbHRdR664B5EX4KdhNTXiaNw4DlfWuSJI2Z5TpWZw1Z1LlSeKfPYhFGR85dgJ6IvwW4iVWNKqc1a69XDl08mAncY8G/YU+ZdZpEOnAysV0oBFAEPK6WudGshk+7ubqeHIEQxoi/BTob01XMCal72pUUef8ssT8k1fdiqzjF/2e6qyCU4i5y/BDsRfQl24zaNTcaB2wjMU0pVYhy364D3WG9qrVuBIVc2nAhcpNLe3u70EIQoRvQl2MLgINS/TuKr90HbDqjb4J3HluSdx3a9cdgKl8g8NmHCyPlLsBPRl2A3btPYhB04rXW/UurTwBOYNgJ3a613KKW+DWzSWj88VYOMFNzWI0JwF6IvYcroboP9z8CeJ2Dvk9DZSB4KSpbDaTd7+7Gtg/gkp0cqRAly/hLsRPQl2I3bNDapPnBa68eAx4Yt+2aIdc+ZzHdFAm7rESG4C9GXMCma9huHbc/jJkVysA+SsmDeRTD/YvYOzmL+snVjbkYQJoKcvwQ7EX0JduM2jU3KgZtpJCXJ3WrBPkRfQlgM9EHtKz6nrWmfWZ6/CE79FMy/BMrWQKw5zSdUVzs3ViHqkfOXYCeiL8Fu3KYxceDCwCobKgh2IPoSxqSjCfY9ZRy2ff+GnjaITYDKs2Ddx020LUTxEdGXYCeiL8FORF+C3bhNY+LAhcHRo0ddd4AF9yD6EkagNRzbYRy2PU9A3UZAQ1ohLL7aRNkqz4bEtDE3JfoS7ET0JdiJ6EuwG7dpTBy4MCgoKHB6CEIUI/oSAOjrgoMv+Jy2tjqzvGQFnPMVmH8xFC0Lu2Kk6EuwE9GXYCeiL8Fu3KYxceDCoL29nZycHKeHIUQpoq8ZTOth2PuEcdgOPAf9XRCfCnPONU7bvAshvWhSXyH6EuxE9CXYiehLsBu3aUwcuDDo7Ox0eghCFCP6mkF4e7OZKNvjcPRNszyrHFZ+wETZKs6AuMQp+0rRl2Anoi/BTkRfgt24TWPiwIWB23pECO5C9BXlBOnNhoqF2afAhd8289ny5oNStny96EuwE9GXYCeiL8Fu3KYxceDCwG09IgR3IfqKQkL2ZrvQOGxzzoOU6UnZEH0JdiL6EuxE9CXYjds0Jg5cGKSkpDg9BCGKEX1FAWH2ZptORF+CnYi+BDsRfQl24zaNiQMXBmlpY5fqFoSJIvpyKaF6s1WcCWtvgvkXQXaF06MUfQm2IvoS7ET0JUw1A4OaupZODhzvYP/xds6Ynez0kMJCHLgwaGhocFWFGsFdiL5cwhT2ZptORF+CnYi+BDsRfQkTpbWzj/2N7Rw43sGB4+1DDltNUye9A4ND691yXhELy4sdHGl4iAMXBkVFkyvjLQijIfqKYGzqzTadiL4EOxF9CXYi+hJGo39gkNpmE007MOSsGUetqaN3aL24GMXs3BSq8tI4b2EBVfmpVOWnMSc/jZg+qUIZtXg8Hld1aRfchegrwpiG3mzTiehLsBPRl2Anoi8BoKWjl/1WFM0vqlbb3EnfgB5aLzc1gar8VC5YVDjkpFXlpzI7J4X42OA3Wqur612lMXHgwqC7u9vpIQhRjOjLYRzozTadiL4EOxF9CXYi+po59PZb0bR29ltpj43msaWzb2i9+FhFeW4qcwvSuGhxEVV5VjQtlayUhLC/120aEwcuDNzWI0JwF6IvB3C4N9t0IvoS7ET0JdiJ6Cu60FrT1NE7FEGzomoHGjuobe5kYNAXTctLS6QqP5VLTi5ijjeSVpWXRll2MnEhomkTwW0aEwcuDNzWI0JwF6KvaSKCerNNJ6IvwU5EX4KdiL7cSU//ADVNvmjakKN2vJ227v6h9RLiYqjMTWVhUTqXLbEctTQq81LJTI6flrG6TWPiwIWBlLEV7ET0ZRMR3JttOhF9CXYi+hLsRPQVuWitOX6ix6Q7+s1L23+8g7qWTvyCaRRmJFKVl8YVy0qG0h3n5KdRkpVMbIyzmS5u01h0X7FMMUlJSU4PQYhiRF9TiEt6s00noi/BTkRfgp2Ivpynu2+Ag40dvnL8jb6y/Cd6fNG0pPgYKvPSWFKWydXLS4aqPFbmp5KWGLluh9s0FrmWjEAaGxvJy8tzehhClCL6mgQu7c02nYi+BDsRfQl2IvqaHrTWHGvr8aY6eouIeB21w54utF80rSQziar8NN6+snSogEhVfiolmcnEOBxNmwhu05g4cGFQUlLi9BCEKEb0FSZR0JttOhF9CXYi+hLsRPQ1tXT1DnCg0a/Kozf98eDxDjp6B4bWS0mIpTIvlZWzs3nnqjLjpOWlUpWfSkpCdLkQbtNYdFnfZhobG8nIyHB6GEKUIvoaB1HWm206EX0JdiL6EuxE9BU+g4OaI23dQw6afwGR+lZfyXyloCQzmar8VFavzmGOX9+0oowkVBRUYR4PbtOYOHBh0NvbO/ZKgjBBRF9BiPLebNOJ6EuwC601HV09Tg9DiGLk/BWa9p5+DnojaP6VHg82ttPdNzi0XlpiHFX5qaytzBmq8liVn0plXipJ8bEO7kFk4DaNiQMXBm7rESG4C9GXlxnUm206EX0Jk0FrTcOJHg42dlDd2EF1U6f30fx19w2SklBDVnI8WSkJZKXEe/8SvMv8nyeQnRJPZko8WckJJMRJmrMwOjP9/DUwqKn3dPn1S/NF1Y61+W6exCgoy06hKj+VU6tyqfJWeZyTn0p+euKMiaZNBLdpTBy4MHBbjwjBXcxofc3Q3mzTyYzWlzAuLCfNcswONnZS09TBwcYOapo66erzzY2Jj1XMzkmhIjeV0+fm0dfRSkJqJp6uPjydfXg6e9lzrH3oeb9/LfFhpCbEkpWSQGZyPNmpxqnLTIknO8X/udcp9DqAmcnx4vjNIGbK+autu89X5dG/LH9jB739vmhaRlIcVflpnD43z0TT8lKZU5DG7JwUiaZNELdpTBy4MHBTbqzgPmaUvqQ327Qzo/QlhMTq2WQ5ZQebfBG1mqYOOnsDnbRZOSlU5qZy2pw8KvNSqMhLpSI3dUTfpvr6+pBFALTWdPQO4Ons9Tp0fXi6emnp7KPVu6yls4/WLvN8V2sbrV5HcDyOX7BoX7bXybOifVkp8WQmm3XjY8XxcxvRdP4aGNTUtXQORdP2+5XlP37CF02LjTE3SaryUjlzXt5QAZE5BWnkpiZING2KcZvG5OooDOLixFyCfUS9vqQ3m6NEvb6EIbTWHG/voboxMM3Riqj5O2lx3ovEirxUTqnKodLroBknLYm4cTo7o+lLKUVaYhxpiXGUZYe3H+09/Xg6+2jt6qPFcgC7+vB09AZE+zxdfew60jb0/sAojl9aYlzIaF/QtM+UeDKTxfFzEjeev1o7+9jf2M7+hsCeaTVNnfQO+KJpWSnxzMlP45z5+UPz0ubkpzI7J1WizNOI2zTmrtE6THNzMwUFBU4PQ4hSok5f0pstoog6fc1wtNY0tvd6HbMOapo6qG7sHHreMcxJm5WTQkVuCqdU5RgHLS+VyjCdtNGwQ19KKdKT4klPimdWGJ/zd/xMdM84eK2dJupnRQAt56++tWvo+Sh+H+mJcWbeXkCEL3S0L9vr+E2FfWc6kXr+6hsY5FBz51C64/4GX9pjU4evKEZcjGJ2bgpz8tM4b1EBc/KMo1aVn0ZOaoKDeyBYRKrGQiEOXBiUlpY6PQQhiokKfUlvtoglKvQ1w7CcNGsemomkmahaTVMn7T39Q+taTlp5bgprK00krTw3hcq8VEqzkm13IiJJXwGOXxhTZwcHNe29/Xg6fA5eS2fvUDpnS2cvrd4IX0tnL4dburxRwLEdv6zUUSJ8w6J9Wcni+A3HaX01d/T6yvH7OWq1TZ0Bab65qQlU5adywaJC5hSkUuV11GblpEgEN8JxWmPhIg5cGBw7doz09HSnhyFEKa7Vl/RmcwWu1VeUo7WmqaM3oLLjwSZfRM3fSYuNUczKTqYiL5U1FTlU5PrmpJVmJzt6gRgN+oqJUWQkxZORFM9sUsb9ucFBzYmeflr9on3D5/v5p3rWtXTh8TqGozp+SXFDxVsyk0cWchk5989EAv3nJkYL06Gv3v5BaputOWkm5XG/d26ap7NvaL2E2BjKc1OYV5DGxYuLvCX5U5mTl0ZmSrytYxTsw23nMHHgwmBwcHDslQRhgrhGX9KbzZW4Rl9RiNaa5o7eEZUdq5s6qGns5MQwJ60sO5mK3FRWl+dQ7nXSKiPASRuNmayvmBhFpjdqNjs3TMevuz9ktG/43L+6lq6hdfQojl9GUpxfqwbj3AU8Tx1W3TM5nowId/ymSl9WVNsqGuLf5PpQS1fA3Mn89ESq8lK59ORi5njL8VflT09EW5h+3HYOU3q0s4BDrF69Wm/atMnpYYygs7OTlJTxn5wFIRwiWl+j9Wabf7H0ZnMBEa2vKMDnpPkXDvE9P9Htc9KsXk3GMUuhPNc0063IS6Usgp200RB9TR+W4zcy2jeysMtQpc+uvlEdP6UgIyl+ZIRvlGhfdopJU50Oxy9cffX0D1DT1DlUQGSof9rxdtr8fosJcTFU5aWa+Wh5aUN90yrzU8lIkmjaTCJSz2FKqc1a69XDl0sELgxqa2td1SNCcBcRpy/pzRZVRJy+XIjWmpbOPr+iIR0cbPJF1II5aeW5Kbx9dqm3cIjpm1aWnRJ11eVEX9NHTIwi09sIPRwGBjUnuocXdgke7fN09VHdZFIH27rHdvyGR/uG+vpZz/2ifVkpJk01JgzHL5i+rJYY+493jGhwXdfSGZCeWpiRyJz8NK5cXhLgqA1vhyHMXNx2DhMHLgyysrKcHoIQxTiurzF7s10MZWulN5tLcVxfLqKlozegP9pQRK2xI+DufYyCUm+649XLS01ELc9E1GZFoZM2GqKvyCc2RnmjaQlUkDruzw0Matq6+gKjfV1+/fv8on2eTpMq3NLRG/BbGY5SmMqdoaJ9yfFkp/qqe7b2JrB/25GAeWkHjncEzBFNio+hMi+NpWWZXL2ilDneqFplfippifJ/Sxgdt53DRNGCMJOR3mzCDMXT2eur7NjYOeSgVTd10trlK1gQo6AkK5nKvFSuWl46VNnRSndMjIt1cC8EwX5iYxTZqQlkpybABBy/YNG+QGewz1vlsQNP5+iOH0BJZhJV+Wm8Y2XpUN+0qvw0ijOSworqCYKbEQcuDDweD0VFUk1PsIdp0ddYvdnmXQxV50hvtihkJp6/TDTAW9nRm/Z40Pva30lTCkqzTCTtimXFQ42sK/JSmZUjTtp4mIn6EkYn0PEbP/0Dg7R19+Px9u1r7erlQPUhTl06j8q8VFIS5NJVmHrcdg6TIiZhEKkTHIXowDZ9jdabbf4l0ptthhCt56/Wzr6hsvsHG/3SHpsCS38rBSWZyUPz0CrzUofmpc3KSREnbZJEq76EyED0JdhNpGpMiphMAXV1dcyfP9/pYQhRypTqa9TebF+GeRdJb7YZhpvPX61dfX7z0Dq95fiN09YSwkm7bEkxld4oWkWucdKS4sVJsws360uIfERfgt24TWPiwIVBjEQoBBuZlL6kN5swBpF+/mrt6vOLonkrO3rnpfk7aWDmwFTkpXLpkmLTzNobURMnzTkiXV+CuxF9CXbjNo2JAxcGhYWFTg9BiGLC1tdovdku+JZJj8xfIL3ZBCAyzl9t3X2BlR39+qU1d/QGrFuSmUR5biqXnFw8VNmxMi+V2eKkRSSRoC8hehF9CXbjNo2JAxcGhw8fdlWPCMFdjEtf0ptNmCDTdf460d1HdWOnmZfW6Iui1TR10jTMSSvOTKIiN5WLFxcOFQ2pyE2lPFecNLch/x8FOxF9CXbjNo1NyoFTSl0C/BSIBX6jtb5t2PsfBz4FDADtwI1a652T+U4nycmRC2PBPoLqS3qzCVPEVJ6/TnT3UdPU6avs6J2XVtPUQWN7oJNWlJFERV4KFy0upNxb3dGKpCUniJMWLcj/R8FORF+C3bhNYxO+6lNKxQK/AC4E6oCNSqmHhzlof9Za3+ld/0rgJ8Alkxivo/T3j96bRBAmw5C+pDebYAPhnr/ae/oDGlj7N7QO5qSV56ZwwaLCoaIhFXmplOekipM2Q5D/j4KdiL4Eu3GbxiZz234tsE9rfQBAKXUfcBUw5MBprdv81k8FIq9nQRi0tbVRUlLi9DCEaKRxL/Gv3AUtm6U3m2ALwc5flpNW0xRY2fFgYyeN7T0B6xZmJFKem8r5C42TZs1LK89Nkb5Mgvx/FGxF9CXYjds0Npn/uqXAIb/XdcC64SsppT4FfAFIAM6bxPc5Tnl5udNDEKKNvi5Y/z14+efk60HTm+2cr0hvNmHK0FpzoLGDt9qT+fez+wIKhxw/EeikFaQnUpGXynkL842Tlptq0h7zxEkTRkf+Pwp2IvoS7MZtGrP9P7LW+hfAL5RS7wG+AXww2HpKqRuBGwHKysrYtWsXJSUlNDY20tvbS3l5OTU1NWRkZBAXF0dzczOlpaUcO3aMwcFBysrKqK2tJSsrCzAd1WfPnk1dXR0xMTEUFhZy+PBhcnJy6O/vp62tbWibCQkJ5OXlUV9fT15eHt3d3bS3tw+9n5SURFZWFtu3b+ekk06ivb2dzs7OofdTUlJIS0ujoaGBoqIiPB4P3d3dQ++npaWRlJREY2NjxO3T0aNHKSgokH1yYJ8aNv2D4o3fJaGtBk/VlRya+36yZxt9lWeXU7Nnj+v2KRqPk9v2qaSsjOe3HWBHQzd7WzSbalrwdA8MnWvz0hIoSo1hdUkS84qLSaeLxbPzyUuCwd4uv32KIysrmaNH6+lOKqBRjpPs0yj7tG/fPlauXBlV+xSNx8mt+9Tb20tKSkpU7VM0Hic371N9fT2rVq2KuH0KhdJ6YlmNSqlTgVu11hd7X38VQGv9vRDrxwAtWuvMsba9evVqvWnTpgmNy04OHDhAVVWV08MQ3E5PO/z727DhV5A5C678Kcw5T/QlTIjuvgG21HrYWN3MxupmXq9poaPXOGyzc1JYXZHN2ooccmjn9GXzSU2USJow9cj5S7AT0ZdgN5GqMaXUZq316uHLJ/OffCMwTylVCRwGrgPeM+xL52mt93pfvg3Yi4vJy8tzegiC29n/LPzzZvAcgrU3wvnfHJrbJvoSxoOns5dN1S1DDtubh1vpG9AoBQsK03nHqjLWVOSwpiKHosykoc+1tbWJ8ybYhpy/BDsRfQl24zaNTfi/uda6Xyn1aeAJTBuBu7XWO5RS3wY2aa0fBj6tlLoA6ANaCJE+6Rbq6+vJyMhwehiCG+nywJPfgC1/gNy58KF/QfmpAauIvoRg1Hu6hpy1jQdb2H3sBAAJsTEsLcvko2dWsaYim1XlOWQmx4fejuhLsBHRl2Anoi/BbtymsUndjtVaPwY8NmzZN/2ef3Yy24803OadCxHC7n/BI5+H9mNw+mfhnK9CfPKI1URfgtaa/cfb2XDQRNg2HGzmsKcLgLTEOFaWZ3PFsmLWVOSwbFZWWM2uRV+CnYi+BDsRfQl24zaNST5NGHR3dzs9BMFNdDTB41+GN++HgpPguj9B6aqQq4u+Zh59A4PsqG9j48FmNlQ3s6m6mZbOPgDy0hJZW5nNR8+sZE1FDouKM4iNURP+LtGXYCeiL8FORF+C3bhNY+LAhUF7e7vTQxDcgNaw40F47IvQ7TERtzO+AHEJo35M9BX9dPb2Dys44qGrzxQcqfA2wl5TkcOayhwqclNQauIO23BEX4KdiL4EOxF9CXbjNo2JAxcGbusRITjAiaPw6H/ArkegeDl84B9QdPK4Pir6ij5aOnqHnLUN1S3sONxK/6ApOLKoKINr18zyFhzJpiAjaewNTgLRl2Anoi/BTkRfgt24TWPiwIVBTU0NCxcudHoYQiSiNbxxLzz+Fejrhgu+Bad+GmLH/xMTfbmfupZO79y1FjZVN7O3wdzRS4iLYXlZFjedXcWaihxWlmeTkRS64IgdiL4EOxF9CXYi+hLsxm0aEwcuDJKS7L1DLrgUzyF45HOw72mYdQpc9b+QNy/szYi+3MXgoGbf8XY2HLQqRDZT32py6NMT41hVkc3VK0pZW5nDktLMsAqO2IHoS7AT0ZdgJ6IvwW7cpjFx4MLA6rwuCAAMDsLmu+GpW0wE7tIfwpqPQkzMhDYn+opsevsH2V7fykavw7appgWPt+BIQXoiaypzuMnbf21BUfqkCo7YgehLsBPRl2Anoi/BbtymMXHgwuDo0aOuO8CCTTTth4dvhpoXofJsuPJnkF0xqU2KviKLjp5+Xq9t8TpsLWw51EJ33yAAVXmpXHxSEWsqzfy12TlTW3DEDkRfgp2IvgQ7EX0JduM2jYkDFwYFBQVOD0FwmsEBePWX8Mx/QWw8XPlzWPF+mIKLd9GXszS197CxumWo6MiO+jYGBjUxCk4qyeD6tbNZW5HD6ooc8tMTnR5u2Ii+BDsRfQl2IvoS7MZtGhMHLgza29vJyclxehiCUzTsgn98Cg5vgvmXwOX/AxklU7Z50df0obWmrqVraP7ahupmDhzvACAxLobls7L45DlzhgqOpCW6/1Qp+hLsRPQl2InoS7Abt2nM/Vcl00hnZ6fTQxCcYKAPXrodnvsBJKTBNb+BJe+ckqibP6Iv+xgc1Ow+doJN3nL+Gw82c7TNFBzJSIpjTUUO71o1i7WV2ZxcmklinLMFR+xA9CXYiehLsBPRl2A3btOYOHBh4LYeEcIUcOQNE3U7+iYsfrspVJKWb8tXib6mjt7+Qd487GHDQZMSuam6mbbufgCKMpJYU5nD2ops1lTmML8gnZgIKzhiB6IvwU5EX4KdiL4Eu3GbxsSBCwO39YgQJkFfNzz/A3jxdkjNg2v/CIuusPUrRV8Tp72nn801JrK2obqZNw556Ok3BUfm5KfytqXF3obZOZRlJ0d8wRE7EH0JdiL6EuxE9CXYjds0Jg5cGKSkpDg9BGE6OLTRRN0ad8Py98LF/w3J2bZ/rehr/Bw/0eNNhzRz2HbWtzGoITZGcXJJBu87pdzrsGWTm+a+giN2IPoS7ET0JdiJ6EuwG7dpTBy4MEhLS3N6CIKd9Haa6pKv3gEZpfDev8O8C6bt60VfwdFaU9vc6WuYXd3CwUZTcCQpPoYVs7L59HnzWFuRw4rZWaRGQcEROxB9CXYi+hLsRPQl2I3bNCZXOmHQ0NDgqgo1QhgcfB4e/gy0VMPqj8AFt0JSxrQOQfRlGBjU7DraZvqvedMiG070AJCVEs/q8hyuXzuL1RU5nFySSULcxBqnzzREX4KdiL4EOxF9CXbjNo2JAxcGRUVFTg9BmGq62+DpW2DT3ZBdCTc8ChVnODKUmaqvnv4BttW1DkXYNte0cMJbcKQkM4lT5+SypiKHtZU5zM1PmxEFR+xgpupLmB5EX4KdiL4Eu3GbxsSBCwOPx+OqLu3CGOx9Cv75OThRD6d+Gs79OiQ4lwM9U/TV1t03VHBkY3Uzb9S10ustODKvII0rlpWwtiKHNZU5lGYlOzza6GGm6EtwBtGXYCeiL8Fu3KYxceDCoLu72+khCFNBZzM88TV4417IWwAffhJmrXF6VFGrr4a2bjZUN7OpuoUNB5vZddQUHImLUZxcmskNp1Wwujyb1RU55KQmOD3cqCVa9SVEBqIvwU5EX4LduE1j4sCFgdt6RAhB2PkwPPof0NkEZ33R/MVFRpXCaNCX1pqDjR3GWfNWiKxpMs0xk+NjWVmexc3nm4Ijy2dnkZIgp6DpIhr0JUQuoi/BTkRfgt24TWNy9RQGbusRIfjR3gCPfRF2PgRFS+B9f4PiZU6PKgA36mtgUPPWkbaACpGN7abgSE5qAqvLs3m/t6T/SSUZxMdKwRGncKO+BPcg+hLsRPQl2I3bNCYOXBi4rcSoAGgNb94P//oS9HbAef8PTv8sxMY7PbIRuEFf3X0DbD3kGaoQ+XpNC+09puBIWXYyZ87L8xYcyWZOftqMbJgdqbhBX4J7EX0JdiL6EuzGbRoTBy4MkpKSnB6CEA5t9fDI52HP41C2Bq76BeQvcHpUIYlEfbV29bG5ppkNB1vYWN3Mm3Wt9A6YgiMLCtO5ekXJUIXI4kwpOBLJRKK+hOhB9CXYiehLsBu3aUwcuDBobGwkLy/P6WEIY6E1vH4PPPkNGOiDi78H626CmFinRzYqkaCvo62m4IhVIXL3sRNoDfGxiiWlmXzojArWVuSwqjybrBQpOOImIkFfQvQi+hLsRPQl2I3bNCYOXBiUlJQ4PQRhLFqq4eGb4eBzUHEmXPkzyKlyelTjYrr1pbVm//EO79w183eouQuA1IRYVpZnc9mSYtZU5LB8VhbJCZHtAAujI+cvwU5EX4KdiL4Eu3GbxsSBC4PGxkYyMjKcHoYQjMFB2PAr+Pe3QMXC5f8DK2+AGPcUzbBbX/0Dg+z0KziyqbqFpo5eAHJTE1hTkcMNp1WytiKHRcXpxEnBkahCzl+CnYi+BDsRfQl24zaNiQMXBr29vU4PQQhG4174x6fh0Ksw90K44nbILHN6VGEz1frq6h1gy6EWNnrnr71e20Jn7wAAs3NSOGdBAWsqsllTmUNVXqoUHIly5Pwl2InoS7AT0ZdgN27TmDhwYeC2HhFRz0A/vPJzePZ7EJ8MV98Jy64Dlzoik9WXp7OXTdXGWdtQ3cz2w630DWiUMgVH3rmqjDUVOaypyKEo012TdYXJI+cvwU5EX4KdiL4Eu3GbxsSBCwO39YiIao5uh398Co5shUVXwGU/hvRCp0c1KcLVV72nyzhr3pTIPcfaAUiIjWFpWSYfPbOKtRU5rCzPJjM58tomCNOLnL8EOxF9CXYi+hLsxm0aEwcuDNyUGxu19PfCCz+GF34Eydnwrt/D4qudHtWUMJq+tNbsa2j3qxDZwmGPKTiSlhjHqvJsrlpeyurybJbNyiIpXgqOCIHI+UuwE9GXYCeiL8Fu3KYxceDCIC5OzOUohzebuW4NO2HptXDJbZCS4/Sopgx/ffUNDLKjvo2NB0065KbqZlo6+wDIS0tkbWU2Hz2zkjUVOSwqziA2xp1po8L0IecvwU5EX4KdiL4Eu3Gbxtw1Wodpbm6moKDA6WHMPPq64Nnvwiv/C2lFcP1fYMElTo9qSuns7eff2+s4OuBhY3UzW2o9dPWZgiMVuSlcsKiQNZU5rK3IoTw3RQqOCGEj5y/BTkRfgp2IvgS7cZvGxIELg9LSUqeHMPOoedlE3Zr3w8oPwkXfgaRMp0c1JWiteb22hfs2HOKRbUfo6hsgRsGi4gyuXTPLW3Akm4IMKTgiTB45fwl2IvoS7ET0JdiN2zQmDlwYHDt2jPT0dKeHMTPoaTc93Tb8CrLK4QP/gKpznB7VlNDS0csDWw7zl4217DnWTmpCLFevKGFJtubyU08iI0kKjghTj5y/BDsRfQl2IvoS7MZtGhMHLgwGBwedHsLMYP8z8PBnofUQrPsEnP//ICHV6VFNisFBzasHmrhv4yEe336U3oFBls/K4rZrlnDFshJSE+PYs2ePOG+Cbcj5S7AT0ZdgJ6IvwW7cpjFx4MKgrMx9zaFdRZcHnvw6bPkj5M6DDz8Os09xelSTouFEN3/bXMdfNh6ipqmTjKQ43rNuNteumcWi4sCKR6IvwU5EX4KdiL4EOxF9CXbjNo2JAxcGtbW1ruoR4Sp2PQaPfgHaG+CMz8PZX4F4d879GhjUPL/3OPdtqOXfbzXQP6hZW5nD5y6Yx6UnF4cs8S/6EuxE9CXYiehLsBPRl2A3btOYOHBhkJWV5fQQoo+ORvjXl2H736DwZLj+XihZ4fSoJsRhTxf3bzrE/ZvqOOzpIjc1gQ+fUcm1a2YxJz9tzM+LvgQ7EX0JdiL6EuxE9CXYjds0Jg6c4Axaw44H4LEvQncbnPM1E3mLS3B6ZGHRNzDIv99q4L6NtTy35zgAZ8zN4+tvW8QFiwpJiItxeISCIAiCIAhCNCEOXBh4PB6KioqcHob7OXEUHvkC7H4USlbCVb+AwpOcHlVY1DR1cN/GQ/xtcx3HT/RQmJHIp8+dy7tXz2JWTsqEtin6EuxE9CXYiehLsBPRl2A3btOYOHBhMHv2bKeH4G60hq1/hie+Cv09cOF34JRPQqw7ZNjTP8ATO45x34ZaXt7fRGyM4twFBVy3ZhbnLMgnLnZy0TbRl2Anoi/BTkRfgp2IvgS7cZvG3HHlHCHU1dUxf/58p4fhTjy18M/Pwf5/w+zT4MqfQ95cp0c1LvYeO8G9Gw7xwJY6PJ19lGUn858Xzeedq2ZRlDl1hVZEX4KdiL4EOxF9CXYi+hLsxm0am5QDp5S6BPgpEAv8Rmt927D3vwB8FOgHjgMf1lrXTOY7nSQmRuYzhc3gIGy+G566xUTgLvsRrP4IRLgtO3v7eXTbEe7beIjNNS3ExyouOqmI69bO4vQ5ecTEqCn/TtGXYCeiL8FORF+CnYi+BLtxm8Ym7MAppWKBXwAXAnXARqXUw1rrnX6rbQFWa607lVKfAH4AXDuZATtJYWGh00NwF0374eHPQM1LUHUuXPFTyC53elSjsv1wK/duqOXhrfWc6OmnKj+Vr1+2iGv+f3v3HR/Vdef//3XUG0JIgxCSkAADxmCMC8a9N1ywHce9JLGzXydZO73ZSTZxyqb/dpPdlE02dhInTnCJExvckrgurhSbZgPGgIQk1BGSkEZtzu+PGcQgC6QBHd25o/fz8eCB5s6dmc9l3oz00bn3nONLKMhJd/raype4pHyJS8qXuKR8iWt+y9jhjMAtBLZYa7cCGGOWAFcA/Q2ctfb5qP1fA24+jNfzXHV1ta/WiPBMqA9e+wU89x1ITofLfwbH3Qxm5EetRkJbsIfH3qphyYpK1le3kp6SxKXzJnP9wjJOnDoBM0p1K1/ikvIlLilf4pLyJa75LWOH08CVADuiblcBJx1k/48CTx3oTmPM7cDtEF4NfePGjRQXF9PY2Eh3dzfl5eVUVFSQm5tLSkoKzc3NlJSUUFdXRygUorS0lMrKyv51HFpaWigrK6OqqoqkpCQmTZpEdXU1+fn59Pb20tra2v+caWlpBAIBampqCAQCBINB2tvb++/PyMggLy+PPXv20NzcTHt7Ox0dHf33Z2VlkZOTQ319PUVFRbS0tBAMBvvvz8nJISMjg8bGxrg7ptraWgoLC0fsmKZmdWL/dgeZzRvomnoeO+Z/lkkzjqXuvffi6pgmTZrEK5t28tj6Rv6vYg+dPSGOKMjgi+eWs3CS4chpU2hsbGTTpvpRe5+Sk5OpqqoalfcpEbOnYzr4MVlr2bhxY0IdUyK+T349pj179tDR0ZFQx5SI75NfjykzM5MtW7Yk1DEl4vvk52Pas2cPnZ2dcXdMB+ybrLUHvPNgjDFXA4ustf8SuX0LcJK19s5B9r0ZuBM4y1rbNdRzL1iwwK5cufKQ6nKppqaG4uJir8uIT309sPwn8OIPICMXLv4hHP3BuBt127Wnm0ffrObBFZVsrmsnOy2Zy48t5voTyzimdPyojbYNRvkSl5QvcUn5EpeUL3EtXjNmjFllrV0wcPvhjMBVA1OibpdGtg184fOBrzLM5i2etba2xuWb67mat+CxO6FuXbhpu/iHkB3wuqp+1lpe3drEkjd28PSGWrp7Q8yfksf3r5rHZfOLyUmPj8lYlS9xSfkSl5QvcUn5Etf8lrHD+cl1BTDTGDONcON2PXBj9A7GmOOAXxEeqas/jNeKC+Xl8T0Bx6jrCYZH3F7+abhhu+4BOOoyr6vqV98W5C+rwqNt25s6yM1I4caFZVx34hSOmpzrdXnvo3yJS8qXuKR8iUvKl7jmt4wdcgNnre01xtwJPEN4GYH7rLUbjDHfAlZaax8HfgTkAA9HTk2rtNZePgJ1e6KiosJXFzg6teMNeOwOaNwMx94MF30HMid4XRV9IctL7zaw5I1Knn2nnt6QZeG0fD59/kwuPnoyGanJXpd4QMqXuKR8iUvKl7ikfIlrfsvYYZ07Zq19EnhywLavR319/uE8f7xJS0vzugTvde8Jzy752i9hfCnc/BeY4f3bXNPSyUMrd/DwyiqqWzopyE7jttOncd2JUzhiYo7X5Q2L8iUuKV/ikvIlLilf4prfMhYfF//4RCAQP9d1eWLri7D0U7BrO5z4/+D8b0D6OM/K6ekL8dzGepa8UcmLmxuwwOkzAnzlkqO4YM4k0lL8tSjjmM+XOKV8iUvKl7ikfIlrfsuYGrgY1NTUkJsbf9dOORfcDf/4Oqz6HeRPh488CVNP86yciqY9LFmxg0dWVdHQ1sWk3HTuOGcG1y6YwpT8LM/qOlxjNl8yKpQvcUn5EpeUL3HNbxlTAxcDv3XnI2Lz32HZZ6BtJ5z6STj7K5A2+k1SV28fz2yoY8kblbzyXhNJBs6dXcj1J5Zx9pETSUn212jbYMZkvmTUKF/ikvIlLilf4prfMqYGLgbBYNDrEkZPRzM8fTesXQITj4Jr/wClJ4x6Ge/WtfHnN3bw6JtVtHT0UDohky9cOIurT5hC0fiMUa/HpTGVLxl1ype4pHyJS8qXuOa3jKmBi0F7e7vXJYyOtx+DJ74Anc1w5pfgzC9ASvqovXxndx/L1tawZMUOVlXsIjXZcOGcIq5fOIXTjgiQlBRfi4OPlDGTL/GE8iUuKV/ikvIlrvktY2rgYuC3NSJi1l4PT3we3nkcJs+HWx6Fonmj9vLrq3ezZEUlj71ZQ1tXL9MnZvOVS2Zz1fGlBHJGr4H0SsLnSzylfIlLype4pHyJa37LmBq4GPhtjYhhsxbWPgRPfxm6O+C8b8Cpn4Jk9/FoC/bw2Fs1LFlRyfrqVtJTkrh03mSuX1jGiVMnEFk/cExI2HxJXFC+xCXlS1xSvsQ1v2VMDVwMMjIS65orAHZXhycpeffvULoQrvg5TJzl9CWttayubGHJG5UsW7uTzp4+ZheN45uXz+XKY0sYn5Xq9PXjVULmS+KG8iUuKV/ikvIlrvktY2rgYpCXl+d1CSPH2vCyAP/4OoR6YdH3YeHtkJTs7CVbOrp5dHU1S1ZUsrmunay0ZK44tpjrF5Yxv3T8mBptG0xC5UvijvIlLilf4pLyJa75LWNq4GJQW1vruzd4UM3bwgtyb3sJpp4Bl/835E9z8lLWWl7d2sSSN3bw9IZauntDzJ+Sx/evmsdl84vJSVcE90qYfElcUr7EJeVLXFK+xDW/ZUw/PcegsLDQ6xIOT6gP3vg1PPstMMlw2U/ghI+Ag5GvhrYuHllVxYMrKtne1EFuRgo3nDiF6xeWcdRk/yyUOJp8ny+Ja8qXuKR8iUvKl7jmt4ypgYtBe3s7+fn5XpdxaBo2w+N3wo7XYeaF4eZtfMmIvkRfyPLSuw08+MYO/vlOHb0hy8Jp+Xz6/JlcfPRkMlLdnZ6ZCHydL4l7ype4pHyJS8qXuOa3jKmBi0FHR4fXJcSurxde+Sm88ANIy4IP/BqOuXZER91qWjp5aOUOHl5ZRXVLJ/nZadx2+jSuO3EKR0zMGbHXSXS+zJf4hvIlLilf4pLyJa75LWNq4GLgtzUiqF0Hj90BO9fAnCvgkh9DzsgMEff0hXhuYz1L3qjkxc0NhCycMTPAVy45igvmTCItJWlEXmcs8V2+xFeUL3FJ+RKXlC9xzW8ZUwMXA9+sEdHbBS/9GJb/B2ROgGvvDzdwI6CiaQ8PrtjBw6uqaGjrYlJuOnecM4NrF0xhSn7WiLzGWOWbfIkvKV/ikvIlLilf4prfMqYGLgZZWT5oUKpWhUfdGt6BY66HRd+DrMM7p7ert49nNtSx5I1KXnmviSQD584u5PoTyzj7yImkJGu0bST4Il/iW8qXuKR8iUvKl7jmt4ypgYtBTk4cX8/V0wnP/zu8+nMYNxlufBhmXXhYT/luXRtLVuzg0dVV7OrooXRCJp+/YBbXLJhC0Xh/LXjoB3GdL/E95UtcUr7EJeVLXPNbxtTAxaC+vj4+Z6jZ/nJ4hsnmrXDCrXDBtyDj0Kbq7+zuY9naGpas2MGqil2kJhsunFPE9QuncNoRAZKSxvZi2y7Fbb4kIShf4pLyJS4pX+Ka3zKmBi4GRUVFXpewv642+Oc9sOI3MGEqfHgpTDvzkJ5qffVulqyo5LE3a2jr6mV6IJuvXDKbq44vJZCTPqJly+DiLl+SUJQvcUn5EpeUL3HNbxlTAxeDlpaW+FmlfcuzsPTTsLsKTv5XOPdrkJYd01O0BXt4fE0NS97Ywbrq3aSnJHHJvMlcf+IUFk7LxzhY4FsOLK7yJQlH+RKXlC9xSfkS1/yWMTVwMQgGg16XAJ274JmvwVt/hMAsuO0ZKDtp2A+31rK6soUlb1SybO1OOnv6mF00jm9ePpcrjy1hfFaqw+LlYOIiX5KwlC9xSfkSl5Qvcc1vGVMDFwPP14jY+AQs+xzsaYDTPwdnfRlShzeZSEtHN4+urmbJiko217WTlZbMFccWc/3CMuaXjtdoWxzwPF+S0JQvcUn5EpeUL3HNbxlTAxcDz9aI2NMIT30J1v8FJs2DGx+E4mOHfJi1lte2NrNkRSVPra+luzfE/NLxfO+qeSyeX0xOut7+eOK3NUjEX5QvcUn5EpeUL3HNbxnTT/AxGPUpRq0NN21PfQmCrXDO1+D0z0DywU9zbGjr4pFVVTy4opLtTR3kZqRww4lTuO7EMuYUH9rslOKe36awFX9RvsQl5UtcUr7ENb9lTA1cDDIyRnHts9ad8MTnYNOTUHICXPFzKDzqgLv3hSz/924DS97YwT/fqaM3ZFk4NZ9PnTeTS+ZNJiM1efRql0MyqvmSMUf5EpeUL3FJ+RLX/JYxNXAxaGxsJBAIuH0Ra+HNP8IzX4W+LrjwO+FZJpMGb8BqWjp5aOUOHl5ZRXVLJ/nZadx2+jSuXTCFGYX++m3CWDcq+ZIxS/kSl5QvcUn5Etf8ljE1cDEoLi52+wItlfD4p2Dr81B+Glz+31BwxPt26+kL8dzGepa8UcmLmxsIWThjZoCvXHIUF8yZRFpKkts6xQnn+ZIxTfkSl5QvcUn5Etf8ljE1cDFobGwkN9fBNWShEKy8N7woN8AlP4YFH4Wk/RuxiqY9PLhiBw+vqqKhrYtJuen869kzuO7EKUzJzxr5umRUOcuXCMqXuKV8iUvKl7jmt4ypgYtBd3f3yD9p03vw2J1Q+QoccS4s/inklfXf3dXbxzMb6nhwRSUvb2kiycC5swu57sQyzjlyIinJGm1LFE7yJRKhfIlLype4pHyJa37LmBq4GIzoGhF9vfDaL+D5f4eUdLjiF3DsjRBZj21LfRt/fmMHj66uYldHD6UTMvn8BbO4ZsEUisb760JLGR6/rUEi/qJ8iUvKl7ikfIlrfsuYGrgYjNgaEXVvw2N3QM1qOPJSuOw/YFwRnd19PLFuJ0veqGRlxS5Skw0XzJnE9SeWcfqMAElJWmw7kfltDRLxF+VLXFK+xCXlS1zzW8bUwMXgsM+N7e2G5f8JL/0IMnLh6vtg7lWsr2llybPreOzNGtq6epkeyOYrl8zmquNLCeSkj0zxEvf8dO61+I/yJS4pX+KS8iWu+S1jauBikJJyGP9cNW+Gr3WrWw9HX037ud/hsXe7WfKzl1lXvZv0lCQumTeZ60+cwsJp+Rij0bax5rDyJTIE5UtcUr7EJeVLXPNbxvxVrceam5spLCyM7UE9QXjx+/Dyf2GzJ7L1/P/lV7VHsvQ/19DZ08fsonHcs3gOHziulPFZqW4KF184pHyJDJPyJS4pX+KS8iWu+S1jauBiUFJSEtsDKl8PX+vW9C6bij/A3e3XsnqZJSttJ1ccW8z1C8uYXzpeo20CHEK+RGKgfIlLype4pHyJa37LmBq4GNTV1TFu3Lihd+zeg332W/D6r2hOKeTzfV/hha1HM780l+9dVcbi+cXkpOufXvY37HyJHALlS1xSvsQl5Utc81vG1EXEIBQKDblPy/p/kLTs0+QGq/ld74X8gptZtOAInjyxjDnF/rpAUkbXcPIlcqiUL3FJ+RKXlC9xzW8ZUwMXg9LS0kG394Usr2zYCn//N85oe4KtoSJ+HPgxx55+MS/Nm0xGavIoVyp+dKB8iYwE5UtcUr7EJeVLXPNbxpK8LsBPKisr97u9c3cnP/3nu3z5ez9ixiPnc2rbU7xadBP248v51qf+H1cdX6rmTYZtYL5ERpLyJS4pX+KS8iWu+S1jGoGLQV5eHj19IZ7bWM+SNypZs3krX0v5A59OXk7r+Jn0Xf0Qp5Sd6HWZ4lN5eXlelyAJTPkSl5QvcUn5Etf8lrHDauCMMYuAnwLJwG+std8fcP+ZwE+AY4DrrbWPHM7reamyqYN7X67myY3raWjr4vrs1fxfzn1k9bXCGXeRe8bnISXN6zJFRERERCSBHfIplMaYZODnwMXAHOAGY8ycAbtVAh8B/nSorxMP3q5p5cwfPc8fVtZy+qQ+Xp/xe77f92OyA2WY21+Ec+5W8yaHraWlxesSJIEpX+KS8iUuKV/imt8ydjgjcAuBLdbarQDGmCXAFcDbe3ew1m6P3OevqV0GOGryOL5x2VFc2vcsha9+B3o64fx74JRPQrLOQpWRUVZW5nUJksCUL3FJ+RKXlC9xzW8ZO5xJTEqAHVG3qyLbEo5pq+XW7V+i8PkvwMQj4RMvw+mfVfMmI6qqqsrrEiSBKV/ikvIlLilf4prfMhY3HYgx5nbgdghP5blx40aKi4tpbGyku7ub8vJyKioqyM3NJSUlhebmZkpKSqirqyMUClFaWkplZWX/RYgtLS2UlZVRVVVFUlISkyZNorq6mvz8fHp7e2ltbe1/zrS0NAKBADU1NQQCAYLBIO3t7f33Z4faKKldz/YjP07eBV+gvaOTjo0b++/PysoiJyeH+vp6ioqKaGlpIRgM9t+fk5NDRkYGjY2NcXNMGRkZ5OXlUVtbS2FhIe3t7XR0dOiYPDymrq4uqqqqEuqYEvF98usxtbe3szHqcysRjikR3ye/HlNjYyOlpaUJdUyJ+D759Zj6+vrYsmVLQh1TIr5Pfj6mxsZGpkyZEnfHdMC+yVo73B5r/wcacwpwj7X2osjtuwGstd8bZN/fAcuGO4nJggUL7MqVKw+pLmd6u2jr7PbVKu3iL21tbcqXOKN8iUvKl7ikfIlr8ZoxY8wqa+2CgdsP5xTKFcBMY8w0Y0wacD3w+GE8X3xLSae6utrrKiSBKV/ikvIlLilf4pLyJa75LWOH3MBZa3uBO4FngHeAh6y1G4wx3zLGXA5gjDnRGFMFXAP8yhizYSSK9kp+fr7XJUgCU77EJeVLXFK+xCXlS1zzW8YO6xo4a+2TwJMDtn096usVQOnhvEY86e3t9boESWDKl7ikfIlLype4pHyJa37L2OGcQjnmtLa2el2CJDDlS1xSvsQl5UtcUr7ENb9lTA1cDMrLy70uQRKY8iUuKV/ikvIlLilf4prfMqYGLgYVFRVelyAJTPkSl5QvcUn5EpeUL3HNbxlTAxeDtLQ0r0uQBKZ8iUvKl7ikfIlLype45reMqYGLQSAQ8LoESWDKl7ikfIlLype4pHyJa37LmBq4GNTU1HhdgiQw5UtcUr7EJeVLXFK+xDW/ZcxYa72u4X2MMQ1APJ6MGgAavS5CEpbyJS4pX+KS8iUuKV/iWrxmrNxaO3Hgxrhs4OKVMWaltXaB13VIYlK+xCXlS1xSvsQl5Utc81vGdAqliIiIiIiIT6iBExERERER8Qk1cLH5tdcFSEJTvsQl5UtcUr7EJeVLXPNVxnQNnIiIiIiIiE9oBE5ERERERMQn1MCJiIiIiIj4hBq4YTDGLDLGbDLGbDHG3OV1PZJYjDH3GWPqjTHrva5FEo8xZoox5nljzNvGmA3GmE97XZMkDmNMhjHmDWPMmki+vul1TZJ4jDHJxpg3jTHLvK5FEosxZrsxZp0x5i1jzEqv6xkuXQM3BGNMMrAZuACoAlYAN1hr3/a0MEkYxpgzgXbgfmvt0V7XI4nFGDMZmGytXW2MGQesAq7UZ5iMBGOMAbKtte3GmFRgOfBpa+1rHpcmCcQY8zlgAZBrrb3M63okcRhjtgMLrLXxuIj3AWkEbmgLgS3W2q3W2m5gCXCFxzVJArHWvgQ0e12HJCZr7U5r7erI123AO0CJt1VJorBh7ZGbqZE/+s2wjBhjTClwKfAbr2sRiRdq4IZWAuyIul2FfvgRER8yxkwFjgNe97gUSSCR09veAuqBf1hrlS8ZST8BvgSEPK5DEpMF/m6MWWWMud3rYoZLDZyIyBhgjMkB/gJ8xlrb6nU9kjistX3W2mOBUmChMUangsuIMMZcBtRba1d5XYskrNOttccDFwN3RC5riXtq4IZWDUyJul0a2SYi4guRa5P+AjxgrX3U63okMVlrW4DngUUelyKJ4zTg8sh1SkuAc40xf/S2JEkk1trqyN/1wF8JXzoV99TADW0FMNMYM80YkwZcDzzucU0iIsMSmWTiXuAda+1/eF2PJBZjzERjTF7k60zCE35t9LQoSRjW2ruttaXW2qmEf/56zlp7s8dlSYIwxmRHJvfCGJMNXAj4YkZwNXBDsNb2AncCzxC++P8ha+0Gb6uSRGKM+TPwKnCkMabKGPNRr2uShHIacAvh31y/FflziddFScKYDDxvjFlL+Bee/7DWaqp3EfGDScByY8wa4A3gCWvt0x7XNCxaRkBERERERMQnNAInIiIiIiLiE2rgREREREREfEINnIiIiIiIiE+ogRMREREREfEJNXAiIiIiIiI+oQZOREQSljGmL2r5hLeMMXeN4HNPNcb4Ys0gERFJHCleFyAiIuJQp7X2WK+LEBERGSkagRMRkTHHGLPdGPNDY8w6Y8wbxpgZke1TjTHPGWPWGmOeNcaURbZPMsb81RizJvLn1MhTJRtj/tcYs8EY83djTKZnByUiImOCGjgREUlkmQNOobwu6r7d1tp5wM+An0S2/Tfwe2vtMcADwH9Ftv8X8KK1dj5wPLAhsn0m8HNr7VygBfig06MREZExz1hrva5BRETECWNMu7U2Z5Dt24FzrbVbjTGpQK21tsAY0whMttb2RLbvtNYGjDENQKm1tivqOaYC/7DWzozc/jKQaq39zigcmoiIjFEagRMRkbHKHuDrWHRFfd2Hri0XERHH1MCJiMhYdV3U369Gvn4FuD7y9U3A/0W+fhb4BIAxJtkYM360ihQREYmm3xSKiEgiyzTGvBV1+2lr7d6lBCYYY9YSHkW7IbLtk8BvjTFfBBqAWyPbPw382hjzUcIjbZ8AdrouXkREZCBdAyciImNO5Bq4BdbaRq9rERERiYVOoRQREREREfEJjcCJiIiIiIj4hEbgRERkVBhjbNSC2f9jjPm34ex7CK9zkzHm74dap4iISDzTCJyIiAyLMeZp4A1r7dcHbL8C+BXhddJ6D/J4C8y01m4ZxmsNa9/IWmzbCK+/dsDXFhERSRQagRMRkeH6PXCzMcYM2H4L8IAaKLeMMZo5WkRE1MCJiMiw/Q0oAM7Yu8EYMwG4DLjfGLPQGPOqMabFGLPTGPMzY0zaYE9kjPmdMeY7Ube/GHlMjTHmtgH7XmqMedMY02qM2WGMuSfq7pcif7cYY9qNMacYYz5ijFke9fhTjTErjDG7I3+fGnXfC8aYbxtjXjbGtBlj/m6MCRyg5gnGmGXGmAZjzK7I16VR9+cbY34bOYZdxpi/Rd13hTHmrcgxvGeMWRTZvt0Yc37UfvcYY/4Y+Xpq5FTSjxpjKoHnItsfNsbURo7nJWPM3KjHZxpj/j9jTEXk/uWRbU8YYz454HjWGmM+MNixiohI/FIDJyIiw2Kt7QQeAj4UtflaYKO1dg3h9dE+CwSAU4DzgH8d6nkjzcwXgAuAmcD5A3bZE3nNPOBS4BPGmCsj950Z+TvPWptjrX01+oHGmHzgCeC/CDef/wE8YYwpiNrtRsLrvRUCaZFaBpME/BYoB8qATuBnUff/AcgC5kae6z8jNSwE7ge+GDmGM4HtB3iNwZwFHAVcFLn9FOF/p0JgNfBA1L4/Bk4ATgXygS8BISKjp3t3MsbMB0oI/9uIiIiPqIETEZFY/B642hiTEbn9ocg2rLWrrLWvWWt7rbXbCV8Xd9YwnvNa4LfW2vXW2j3APdF3WmtfsNaus9aGrLVrgT8P83kh3PC9a639Q6SuPwMbgcVR+/zWWrs5qkE9drAnstY2WWv/Yq3tsNa2Af++tw5jzGTgYuDj1tpd1toea+2LkYd+FLjPWvuPyDFUW2s3DrN+gHustXsi9WGtvc9a22at7SL8bzXfGDPeGJME3AZ8OvIafdbaVyL7PQ7MMsbMjDznLcCD1truGOoQEZE4oAZORESGzVq7HGgErjTGHAEsBP4EYIyZFTmtsNYY0wp8l/Bo3FCKgR1Rtyui7zTGnGSMeT5y6uJu4OPDfN69z10xYFsF4dGnvWqjvu4AcgZ7ImNMljHmV5HTE1sJn76ZZ4xJBqYAzdbaXYM8dArw3jDrHUz/v40xJtkY8/3IaZit7BvJC0T+ZAz2WtbaIPAg4WsYk4AbCI8YioiIz6iBExGRWN1PeOTtZuAZa21dZPsvCY9uzbTW5gJfAQZOeDKYnYSbnL3KBtz/J8IjSFOsteOB/4l63qGmUq4hfMpjtDKgehh1DfR54EjgpMjx7T190xBusvKNMXmDPG4HcMQBnnMP4dMu9yoaZJ/oY7wRuILwaabjgalRNTQCwYO81u+Bmwif2tox8HRTERHxBzVwIiISq/sJNxD/j8jpkxHjgFag3RgzG/jEMJ/vIeAjxpg5xpgs4BsD7h9HeHQrGLme7Mao+xoIX+M1/QDP/SThUwdvNMakGGOuA+YAy4ZZ28A6OglPmJIfXae1difha9N+EZnsJNUYs7fBuxe41RhznjEmyRhTEvn3AXgLuD6y/wLg6mHU0AU0EW78vhtVQwi4D/gPY0xxZLTuFGNMeuT+Vwn/W/1/aPRNRMS31MCJiEhMIte3vQJkEx4Z2+sLhJurNuB/CZ+yN5znewr4CeFZFrdE/o72r8C3jDFtwNcJN3x7H9tB+Fq0l0149suTBzx3E+FZMj9PuOn5EnCZtbZxOLUN8BMgk/BI12vA0wPuvwXoITwKWQ98JlLDG4QnSflPYDfwIvtGBf+N8IjZLuCbRE5HPYj7CZ8CWg28Hakj2heAdcAKoBn4Aft/r78fmAf8cYjXERGROKWFvEVERMYIY8yHgNuttad7XYuIiBwajcCJiIiMAZHTU/8V+LXXtYiIyKFTAyciIpLgjDEXEb5esI6hT9MUEZE4plMoRUREREREfEIjcCIiIiIiIj6R4nUBgwkEAnbq1Klel/E+vb29pKTE5T+ZJADlS1xSvsQl5UtcUr7EtXjN2KpVqxqttRMHbo+/SoGpU6eycuVKr8t4n40bNzJ79uyhdxQ5BMqXuKR8iUvKl7ikfIlr8ZoxY0zFYNt1CmUMysvLh95J5BApX+KS8iUuKV/ikvIlrvktY2rgYlBRMWgTLDIilC9xSfkSl5QvcUn5Etf8ljE1cDHIzc31ugRJYMqXuKR8iUvKl7ikfIlrfstYXF4DN5ienh6qqqoIBoOe1dDX18fu3bs9e31JbMrX4cnIyKC0tJTU1FSvS4lL8XhxtiQO5UtcUr7ENb9lzDfVVlVVMW7cOKZOnYoxxpMaOjs7yczM9OS1JfEpX4fOWktTUxNVVVVMmzbN63LiUnNzM4WFhV6XIQlK+RKXlC9xzW8Z880plMFgkIKCAs+aN4C0tDTPXlsSn/J16IwxFBQUeDpCH+9KSkq8LkESmPIlLilf4prfMuabBg7wtHmD8GmcIq4oX4fH68+HeFdXV+d1CZLAlC9xSfkS1/yWMV81cCIicmhCoZDXJUgCU77EJeVLXPNbxnxzDVw80OQI4pLyJS6VlpZ6XYIkMOVLXFK+ZERYC3saoXETNGyCxnfDXze+S9llvwBmeV3hsKmBi0F3d/ewJ5nIycmhvb3dcUUja+rUqaxcuZJAIOB1KaMuHt6vWPIF/ny/3nrrLWpqarjkkku8LmXMqaysZPbs2V6XIQlK+RKXlC+JSagPWirCDVrDpv4mjYZNEGzZt19qNgRmQtkp7GxsYdpMzyqOmS8buG8u3cDbNa0j+pxzinP5xuK5B93Hb1OMxo2n7oLadSP7nEXz4OLvj+xzemws5Outt95i5cqVauA8kJeX53UJksCUL3FJ+ZJB9XRC05b9R9MaNoe39XXt2y97IgSOhKOvgsCsfX9ySyApfDVZZm2tRwdxaBL/J8YRctddd1FcXMynPvUpAO655x5SUlJ4/vnn2bVrFz09PXznO9/hiiuuGPK52tvbueKKKwZ93P3338+Pf/xjjDEcc8wx/OEPf6Curo6Pf/zjbN26FYBf/vKXnHrqqe973j179nDttddSVVVFX18f//Zv/8Z1113Hk08+yec+9zmys7M57bTT2Lp1K8uWLaOpqYkbbriB6upqTjnlFKy1I/gv5q277rqLKVOmcMcddwD+eL/uvvtubrrpphF5v7Zv386iRYs4+eSTeeWVVzjxxBO59dZb+cY3vkF9fT0PPPAACxcupLm5mdtuu42tW7eSlZXFr3/9a4455hjuuecetm3bxtatW6msrOQ///M/ee2113jqqacoKSlh6dKlpKamsmrVKj73uc/R3t5OIBDgd7/7HZMnT+bss8/mpJNO4vnnn6elpYV7772Xk046ia9//et0dnayfPly7r77bt555x1ycnL4whe+AMDRRx/NsmXLAIZVv4iIiCS4jmZo3Bxp1Dbv+7qlEoj8LGSSIK883JjNODfcsAVmhUfYsvI9Ld8Ja23c/TnhhBPsQG+//fb7to2m1atX29NPP73/9lFHHWUrKyvt7t27rbXWNjQ02COOOMKGQiFrrbXZ2dkHfK6enp5BH7d+/Xo7c+ZM29DQYK21tqmpyVpr7bXXXmv/8z//01prbW9vr21paRn0eR955BH7L//yL/23W1pabGdnpy0tLbVbt2611lp7/fXX20svvdRaa+0nP/lJ+81vftNaa+2yZcss0P/afrd69Wp75pln9t/2w/u1c+fOEXu/tm3bZpOTk+3atWttX1+fPf744+2tt95qQ6GQ/dvf/mavuOIKa621d955p73nnnustdY+++yzdv78+dZaa7/xjW/Y0047zXZ3d9u33nrLZmZm2ieffNJaa+2VV15p//rXv9ru7m57yimn2Pr6emuttUuWLLG33nqrtdbas846y37uc5+z1lr7xBNP2PPOO89aa+1vf/tbe8cdd/TX+Y1vfMP+6Ec/6r89d+5cu23btmHXP5DXnxPx7J133vG6BElgype4pHyNAX191u6qsHbzP6x95efWPv4pa+9dZO0Pplv7jdx9f75daO0vTrP24Vutff571q77i7W1663t7jysl4/XjAEr7SC9kkbghum4446jsbGRmpoaGhoamDBhAkVFRXz2s5/lpZdeIikpierqaurq6igqKjroc1lr+cpXvvK+xz333HNcc801/dc05eeHf2Pw3HPPcf/99wOQnJzM+PHjB33eefPm8fnPf54vf/nLXHbZZZxxxhm89dZbTJ8+vX9x4xtuuIFf//rXALz00ks8+uijAFx66aVMmDDh8P+h4sRxxx1HfX29r96vU089lXXr1o3Y+zVt2jTmzZsHwNy5cznvvPMwxjBv3jy2b98OwPLly/nLX/4CwLnnnktTUxOtreHTky+++GJSU1OZN28efX19LFq0qL/u7du3s2nTJtavX88FF1wAQF9fH5MnT+5//auuugqAE044of/1YjGc+mX4ysrKvC5BEpjyJS4pXwmktwua3ts3krZ3NK1pC/R07Nsvc0J4FG32JftG0ybOgvFTICl5xMvyW8bUwMXgAx/4AI888gi1tbVcd911PPDAAzQ0NLBq1SpSU1OZOnXqsBYSPtTHDWXWrFmsXr2aJ598kq997Wucd955XH755Yf9vH51zTXX+Or9Ouuss/qbnpGQnp7e/3VSUlL/7aSkJHp7e4f9+KSkJFJTU/vXWdv7eGstc+fO5dVXXz3o45OTkw/4eikpKftN3Rv973q49cv+qqqqmDXLPzNsib8oX+KS8uVDnS1RszxuDl+b1rgZdm0H27dvv/Fl4cZs6umRJi3SrGWP7gRtfsuY1oGLwdVXX82SJUt45JFHuOaaa9i9ezeFhYWkpqby/PPPU1FRMaznOdDjzj33XB5++GGampoAaG5uBuC8887jl7/8JRAe5di9e/egz1tTU0NWVhY333wzX/ziF1m9ejVHHnkkW7du7R+xePDBB/v3P/PMM/nTn/4EwFNPPcWuXbti/0eJY9ddd52v3q8333xz1N+vM844gwceeACAF154gUAgQG5u7rAee+SRR9LQ0NDfwPX09LBhw4aDPmbcuHG0tbX13546dSqrV68GYPXq1Wzbtu1QDkOGISlJH/fijvIlLilfccpa2F0N7z0Pr/8Kln0OfncZ/HgW/KAc7j0fHrsDXvtluHErOhrO+Dxc9Rv42EvwlZ3w2XVw819g0fdgwa1QfuqoN2/gv4xpBC4G8+fPp62tjZKSEiZPnsxNN93E4sWLmTdvHgsWLBj2FLcHetzcuXP56le/yllnnUVycjLHHXccv/vd7/jpT3/K7bffzr333ktycjK//OUvOeWUU973vOvWreOLX/xi/4jJL3/5SzIzM/nFL37BokWLyM7O5sQTT+zf/xvf+AY33HADc+fO5dRTT/Xd8PFQ5s6d66v362c/+9mov1/33HMPt912G8cccwxZWVn8/ve/H/Zj09LSeOSRR/jUpz7F7t276e3t5TOf+Qxz5x54NtdzzjmH73//+xx77LHcfffdfPCDH+T+++9n7ty5nHTSSb767ZffTJo0yesSJIEpX+KS8uWxvh5o3jZgNC0y82N31BJM6ePDo2kzzt9/NC2vHJLju+XwW8aMjcOZBxcsWGBXrly537Z33nmHo446yqOKwjo7O2NapytetLe3k5OTg7WWO+64g5kzZ/LZz37W67JkgL350vt16OLhcyJebdy4UesoiTPKl7ikfI2SrrbIaY8DZnxs3gqhqEsXckvCszsGjgz/PfHI8Nc5hRC53MJv4jVjxphV1toFA7fHdzscZ/y6Ttf//u//8vvf/57u7m6OO+44Pvaxj3ldkgxib770fokLeyfZEXFB+RKXlK8RZC201w8+mtZavW+/pBTInx4eQZt9WaRJmxm+nT7Ou/od8VvG/NmReCTW0cp169Zxyy237LctPT2d119//bDqaGpq4rzzznvf9meffZaCgoL3bf/sZz+rEZxh8Pr92puvWN6vWLMgY5cmfhGXlC9xSfk6BH290FIRNZoWNaFIMOra/LSccGM29Yzw6Y+BWeHRtPxpkJzqXf2jzG8ZG1YDZ4xZBPwUSAZ+Y639/oD7Pw7cAfQB7cDt1tq3jTFTgXeATZFdX7PWfvxQi7XW9s+E54W+vr6hd4oyb9483nrrrRGvo6CgwMnzjnVev1+x5iuW5x4L4vF08HjS2tpKcXGx12VIglK+xCXl6yC6O6Dp3XCD1rBp32ha0xbo6963X86kcHN29NX7rk0LzILcYt+e9jiS/JaxIRs4Y0wy8HPgAqAKWGGMedxa+3bUbn+y1v5PZP/Lgf8AFkXue89ae+zhFpqRkUFTUxMFBQWeNXHR05qLjDTl69BZa2lqaiIjI8PrUuJWeXm51yVIAlO+xCXlC9jT+P7RtIbNsLty3z4mCSZMDY+gzbxg32haYCZk5nlVuS/4LWPDGYFbCGyx1m4FMMYsAa4A+hs4a21r1P7ZwIj/Kry0tJSqqioaGhpG+qmHraenh9TUsTOcLKNL+To8GRkZlJaWel1G3KqoqIjLC7QlMShf4tKYyVcoFG7I9q6Ztnc0rWETdDbv2y8lM9yUTVkIx9+yb0KRgiMgRb8MPhR+y9hwGrgSYEfU7SrgpIE7GWPuAD4HpAHnRt01zRjzJtAKfM1a+3+DvYgx5nbgdgg3axs3bqS4uJjGxka6u7spLy+nq6uL8ePHk5KSQnNzMyUlJdTV1REKhSgtLaWyspK8vDwAWlpaKCsro6qqiqSkJCZNmkR1dTX5+fn09vbS2tpKeXk5FRUVpKWlEQgEqKmpIRAIEAwGaW9v778/IyODvLw83nnnHY488kja29vp6Ojovz8rK4ucnBzq6+spKiqipaWFYDDYf39OTg4ZGRk0Nja+75gqKirIzc317Jhqa2spLCzUMcXBMUF4nbREOqbRfJ+Kiop47733EuqYRvJ96uzsZOPGjQl1TIn4Pvn1mHbt2kVHR0dCHVMivk9+PSZrLVu2bEmYY9rVsJPSzC7atq0kpWUbeT319NZuIL2tEtPX1f+zcW96Hj3jp5E882J2JU8kvWQeXePK2RXKpnzqtPcfU3IbwWCDsncIx7Rr1y46Ozvj7pgOZMhlBIwxVwOLrLX/Erl9C3CStfbOA+x/I3CRtfbDxph0IMda22SMOQH4GzB3wIjd+wy2jEA8aG1tHfYixyKxUr7EJeVLXFK+xCXf5qtz1/6jaXu/bqkAG4rsZCCvbP910/b+ydZkZKMlXjN2OMsIVANTom6XRrYdyBLglwDW2i6gK/L1KmPMe8AsIP66s2GoqamJyzdXEoPyJS4pX+KS8iUuxXW+rIXdVfvWTIuemn9P1GU/yelQMAOKj4Vjrt3XsOUfAWlZnpUvYXGdsUEMp4FbAcw0xkwj3LhdD9wYvYMxZqa19t3IzUuBdyPbJwLN1to+Y8x0YCawdaSKH22BQMDrEiSBKV/ikvIlLilf4lJc5Ku3O7yg9cDRtMZ3oWfPvv0y8sKN2ayLIhOIzApPz59XDknJnpUvBxcXGYvBkA2ctbbXGHMn8AzhZQTus9ZuMMZ8C1hprX0cuNMYcz7QA+wCPhx5+JnAt4wxPUAI+Li1tvn9r+IPwWDQ6xIkgSlf4pLyJS4pX+LSqOYr2Lr/mml7R9Oat4GNWu4ntzTcmB1/y/6nP2ZP1LT8PuS3z7BhrQNnrX0SeHLAtq9Hff3pAzzuL8BfDqfAeNLe3u51CZLAlC9xSfkSl5QvcWnE82UttNXuP8vj3tMf23bu2y8pNTyzY+FRMOfKfaNpBTMhPWdkaxJP+e0zbFgNnIT5bY0I8RflS1xSvsSZ3m7KJ42HrjZISgn/McmQlOR1ZZIgDvnzq68Xdm2PnPIYtX5a47vQFTWfXtq4cGM2/ZzwlPx7R9MmTIVkLe8zFvjte6QauBj4bY0I8RflS1xSvmRYerugoxk6msLrTnU0Rf7s2vd1//bm8J/uNjIHfTKzr6FLSglf/zOs28mH8Ji9TePA+4f7HDG8TvQ2c7BaU9TEjpAhP7+69+y7Hq1h074mrek9CPXs22/c5HCDdsx1+0bTAkfCuCKd9jjG+e17pBq4GGRkZHhdgiQw5UtcUr7GoN6uqEZrkMZrsIas+yCnEaXnQlY+ZOZDViD8g29WPmTl09zWRf6E8RDqjfwJRX3dC6G+IW5HbbN9+273dMfwHANeM/p6Jc8crIkdTuM4yDaTdGjN5gGb5OE2xzE21CPYxGZkZIRPe9zTELkuLWo0rWEztFZF/ZMnQ/60cD5nLYqamn8mZIw/7FokMfnte6QauBjsXbhPxAXlS1xSvnyuJzigAdvbfEWNjHVE3d85zGYsqyCqGSuArAmRvwsijdrerydAStoBny6ppQXiLWPWDq9xtEM1mwdrHvuGsc8gt+1gjz/A7fc1sTG8Zlw0sRzaSGzU6GZp1x5o2QbBln3PmZoVbsrKT42MpEVG0/KnHzSrIoPx2/dINXAxqK2t9d0bLP6hfIlLylcc6QkOcopi8yAjZVGnLkZPUz5Q+vj+kTByCsMTLmTmRzVo+fs3ZEM0Y4ciLvNlDCSnhP+MVdFN7AGbxqEaweE2m4M1kIfaHO//+l2hZFLmfmD/ha5zS3SKqoyYuPwMO4gx/KkWu8LCQq9LkASmfIlLypcjPZ2DnI44YKRs4KmLB2vGMsbva7RyJkHhnH1N197RsKwBI2NxMMmC8hWnEqSJ7WpuJjs/3+syJIH57TPM3/+jR1l7ezv5+gARR5QvcUn5GoaezvefjjjoKYpR23s6Dvx8GeP3jXzlFEHh3H0jZQNPUczKj5tm7FAoX+KS8iWu+S1jauBi0NFxkG/UIodJ+RKXxly+ujuGeYpi1PbezgM/X0bevsYrtxgmHX3gUxT7R8bGzrfYMZcvGVXKl7jmt4yNne8uI8Bva0SIvyhf4pKv89XdcfBTFAc7TXHIZizSeOUWQ9G8g5yimD/mmrFD4et8SdxTvsQ1v2VM35Fi4Lc1IsRflC9xKS7yZW34lMPBZkx836mL0SNjwQM/Z+aEfSNfuaVQdMyBT1HMKgg3b2rGRlxc5EsSlvIlrvktY/ouFoOsrCyvS5AEpnyJSyOeL2vDi+cONmPiwU5dPGAzZiAzb1/DlVsKRfMPPK19Vr6asTiizy9xSfkS1/yWMX3ni0FOTo7XJUgCU77EpYPma28zNtzFnvdu7+s6wBOayCmJkYYrbwpMnv/+a8b2m9o+L7z+k/iSPr/EJeVLXPNbxtTAxaC+vt5XM9SIvyhf4kRfL2z/P3rWvwjjUg68CHRf9wGewOx/fVheGRQfO2BEbOA1Y3lqxsYYfX6JS8qXuOa3jKmBi0FRUZHXJUgCU75kxPT1QsVy2PBXePtx6GxmEgAmMl393pGx8n3N2AGvGRuvZkyGpM8vcUn5Etf8ljE1cDFoaWnx1Srt4i/KlxyWUB9UvgrrH4V3Hoc9DZCaDUcugrkfoNKUUjbrGDVj4oQ+v8Ql5Utc81vG1MDFIBg8yExoIodJ+ZKYhUKw4/XISNtj0F4LKZkw6yKY+wGYeSGkhS/M7ti4Uc2bOKPPL3FJ+RLX/JYxNXAx8NsaEeIvypcMi7VQtRI2PAob/gZtNZCcDjMvgKOvgpkXQfr7L8ZWvsQl5UtcUr5kJHR297Gro5vmPd3s6uhmV0cPu/aEb186t9Dr8mKiBi4GflsjQvxF+ZIDshZqVodPj3z7Mdi9A5LTYMb5MPebcOTFkD7uoE+hfIlLype4pHzJQJ3dfTR3dLMr0ow179n7dU//7ZaOnsjf3TR3dBPsCR3w+QpMG7OKNYlJQvLbFKPiL8qX7Mda2LkmfHrkhr9CSwUkpcIR58I5X4XZl4QnGBkm5UtcUr7EJeUrcVlr6ezp26/h2hVpzJojI2Th0bJudu3Z15x19Q7ejBkD4zNTyc9KIy8rleK8DOYW5zIhO40JWWnkZ6eSl5VGfuT2hKxUxmemUruzZpSP/PCogYtBRkaG1yVIAlO+BGuhbv2+pq15K5hkmH42nPUlmH1peEr/Q6B8iUvKl7ikfPmDtZaOyGmKu/b00NwRGf2KGh3bt21fc3awZiwvMzXcaGWnUZyXydzi3HDzlR1uviZEmrG9Tdn4zFSSk0zMtfstY2rgYtDY2EggEPC6DElQytcYVv9O+PTIDX+FpnfBJMG0M+G0T8PsxZBdcNgvoXyJS8qXuKR8jb69zdhg14vtPSVx/23h5qx7qGYsO438rDRK8jKZV5Lb35ztHTHb15wdejN2KPyWMTVwMSguLva6BElgytcY07A5MtL2KDRsBAxMPR1O/gQcdTnkTBzRl1O+xCXlS1xSvg6PtZY93X37Xy8WdUpi/4jZgNMVu/sO3IxN2NtwZaUxJT+LY0r3NWf9Tdne0xWz0sgdxWbsUPgtY2rgYtDY2Ehubq7XZUiCUr7GgKb39s0eWbceMFB2Clzy43DTNm6Ss5dWvsQl5UtcUr72sdbS3tXbf71Y9CmJLYM0Z3tHxw7UjCUZyItcC5afHW7G5pfm7TtFcW9Tlr3vdMXcjFSS4rgZOxR+y5gauBh0d3d7XYIkMOUrQTVv23dNW+3a8LYpJ8Gi78OcKyB3dH7rp3yJS8qXuJSo+drbjO29XmxXR9RMivs1Z/uPlvX02UGfLykyMra3+SqLasaiR8P23p+ozdih8FvG1MDFQOuQiEvKVwJpqQyPsm14FGreDG8rWQAX/jvMvRLGl456ScqXuKR8iUt+yJe1lrau3v0bsOhTEge5XqzlIM1YcpLZ75qx8oIsjivLO+DkHflZaYzLSFEzdoj8kLFoauBioHVIxCXly+d2V8PbfwuPtFWtCG+bfCxc8C2YcyVM8Pabg/IlLilf4tJo58taS2uwt3/0a7/p7QfMoLgr6vTF3tCBm7G9TdeErDSmBrI4PjvvfSNi/VPdqxkbdX77DFMDFwM/nRsr/qN8+VDrTnjn8fAMkjteC28rmgfnfR3mfgDyp3tbXxTlS1xSvsSlw8nX3mZs1xDXizVHnb44dDO2r+GaFsjmhPK0/uZssNMVx6WrGYt3fvsMUwMXg5QU/XOJO8qXT7TXw9uPhUfaKl4BLBTOhXO+Fm7aAjO8rnBQype4pHyJS3vzFQpZ2oK9MV0vtqujh74hmrG9DdcRE3P2uz5swoDJO/Ky0sjNSMEYNWOJxm+fYf6q1mPNzc0UFhZ6XYYkKOUrju1pDI+0bfgrbF8ONgSBI+Hsu8KnRxbG/2kXype4pHzJoerpC9G8p5uGti4a2rtoaOuiMfL33q9rmtrY02to6TxwM5aSZPa7PmxGYU7k+rB9py6Gm7B9a42NS1czJmF++wxTAxeDkpISr0uQBKZ8xZmOZti4LHx65LaXwPZB/hFwxudh7lVQeFR4MRyfUL7EJeVLovWFLM17ut/XiPX/3d5FY1s3De1dNO8ZfPa/nPQUAjlpTByXzqyi8RTmZe03ecd+C0Bnp6oZk8Pit8+wYTVwxphFwE+BZOA31trvD7j/48AdQB/QDtxurX07ct/dwEcj933KWvvMyJU/uurq6hg3bpzXZUiCUr7iQGcLbHwiPNK29XkI9cKEqXDap8OnRxbN81XTFk35EpeUr8QXCll2d/a8f5Ss/3Z3f7PWvKeLwQbKMlKTmDgunYk56ZQXZLFg6gQCOelMHJfe/3dh5OvMtOT+x23ZsoUZM+Lz9HRJDH77DBuygTPGJAM/By4AqoAVxpjH9zZoEX+y1v5PZP/Lgf8AFhlj5gDXA3OBYuCfxphZ1tq+ET6OUREKDb4IoshIUL48EmyFTU+Gm7Ytz0KoB8aXwcn/CkdfFZ5J0qdNWzTlS1xSvvxp7wQf7xshG9CgNbaFR9MGm9gjLTkp0oClUZKXwfzS8eEmLaop2/t3dlryIY2SKV/imt8yNpwRuIXAFmvtVgBjzBLgCqC/gbPWtkbtnw3s/R9+BbDEWtsFbDPGbIk836sjUPuoKy0d/bWbZOxQvkZRVxtsfiZ8euSWf0JfF+SWwEkfC58eWXJ8QjRt0ZQvcUn5ih/WWvZ099HY33wNcm1Ze3f/9u7e9//gmpJkKIicvjgxJ52jinIHbcgmjksflUk9lC9xzW8ZG04DVwLsiLpdBZw0cCdjzB3A54A04Nyox7424LGDnmRqjLkduB3C/4gbN26kuLiYxsZGuru7KS8vp6KigtzcXFJSUmhubqakpIS6ujpCoRClpaVUVlaSl5cHQEtLC2VlZVRVVZGUlMSkSZOorq4mPz+f3t5eWltb+58zLS2NQCBATU0NgUCAYDBIe3t7//0ZGRnk5eWxfv165syZQ3t7Ox0dHf33Z2VlkZOTQ319PUVFRbS0tBAMBvvvz8nJISMjg8bGxrg7ptraWgoLC3VMcXBMHR0d/XUnyjHF1ftUmM+uN5ZQsPNF0itfxPR1EcopYveMD7Bn6oWMn3s+1TU7yU/Lp3fnTn8cUwzvU0VFBePGjUuoY/JN9sbAMW3ZsoXjjz8+oY4p3t4nklPZUlVPcs4Etu1soqE1iE0fx7baJtp7Dc0d4ZG03V0hOnve35QlGRifnkzh+ExyUkLMmZhK6ewCUvo6mRIYT15GEmmhLo6ZVU5LfQ0Z6ekHOKYiKioqSOnIwKblsanC/fvU3d1NVlaWL96nRMzeWDimmpoaTjjhhLg7pgMx1g4+m09UY3U1sMha+y+R27cAJ1lr7zzA/jcCF1lrP2yM+RnwmrX2j5H77gWestY+crDXXLBggV25cuVB6/JCbW0tRUVFXpchCUr5cqCnE979e/j0yM3PQE8HZBfC3CvD17RNORmSkryuclQoX+KS8nVounr7aIq6dmzgRB/R15a1d/UO+hz52Wn9k30EcsIjZoONluVnp5Hs07XIlC9xLV4zZoxZZa1dMHD7cEbgqoEpUbdLI9sOZAnwy0N8rIjI4ekJwnvPhk+P3PQU9OyBrADMvz58emT5qZCUPPTziIgcguFMi7+3Mdvd2TPoc+RmpPSfoji3eP/TFydGnb6Yn51GavLY+CWUiOwznAZuBTDTGDONcPN1PXBj9A7GmJnW2ncjNy8F9n79OPAnY8x/EJ7EZCbwxkgU7oWWlpa47M4lMShfh6G3C957HjY8ChufhO42yJwA864Oj7RNPQOSx/aqKcqXuJTo+Ro4Lf77GrKoafF3dXQz2MlNOekp/ZN9HFk0jtMGGy2L3J+eol8yRUv0fIn3/JaxIX+isdb2GmPuBJ4hvIzAfdbaDcaYbwErrbWPA3caY84HeoBdwIcjj91gjHmI8IQnvcAdfp2BEqCsrMzrEiSBKV8x6uuBrS+ET498Zxl07YaM8TD3inDTNu0sSE71usq4oXyJS37MV/S0+NETfRzqtPhTA+Fp8QeevjjYtPgSGz/mS/zFbxkb8ho4L8TrNXCbN29m1qxZXpchCUr5Goa+Xtj+Uvj0yI3LoHMXpOfC7EvDp0dOPxtS0ryuMi4pX+JSvORr77T4B1xAOpZp8celMzH62rIBpzEGDmNafIlNvORLEle8ZuxwroGTiKQxMtmBeEP5OoBQH2xfHhlpexw6miAtB468JDzSNuM8SEn3usq4p3yJS67ztaerN6r5ev/0+MOZFj+Qk05gXNp+0+IP1pyNxrT4Eht9folrfsuYGrgYTJo0yesSJIEpX1FCfVD5arhpe/sx2NMAqVkwa1F4ce0Z50NqptdV+oryJS4dSr46u/sGzLY4+EQfDW1ddPa8/+qLJAP52fsm9DhiYvZ+k3xEj5aNz0wlyaczMIo+v8Q9v2VMDVwMqqurmT17ttdlSIIa8/kKhaDqjfDpkW8/Bu21kJIJsy4Mj7TNvAjSsryu0rfGfL7Eqb35Gmpa/L0TfQw1Lf7EyGjZ8WV5+y0aHT1a5udp8SU2+vwS1/yWMTVwMcjPz/e6BElgYzJf1kLVyshI29+gtRqS02HmBeGmbdYiSM/xusqEMCbzJSMu2NNHZXMHFU0dVDTtCf/d3EFlYxu7Hqw84LT44zNT+9cqO7pk/P7rlkWNmmlafBmMPr/ENb9lTA1cDHp7B/9tochIGDP5shZq3gxP+b/hb7B7BySnhU+LPP+ecNOWket1lQlnzORLDtvuzh4qmzrY3rQn0qztYXtTB5VNHdS2BvfbNzcjhamBbKZOyOCsI8e/f7KPcekUaFp8OUz6/BLX/JYxNXAxaG1tpbi42OsyJEEldL6shdq14ZG2DX+FXdshKQWOOBfO+SoceTFk5nldZUJL6HxJTKy1NLR3RUbROqiMNGgVkWatpWP/UbTCcemUF2Rx2owAUwuyKCvIYmpBNuUFWeRlhWd93bhxo69OPxJ/0eeXuOa3jKmBi0F5ebnXJUgCS7h8WQt1G/Y1bc3vgUkOT/V/xhfCU/9n+euUBT9LuHzJQfX2hdi5Oxg5xXHPfqc8VjZ30NG9b1KQJAMlEzKZWpDNpfMmU16QRXmkQSvLzyIrbegfFZQvcUn5Etf8ljE1cDGoqKjQbxjFmYTJV/07+5q2xs1gkmDqGXDap2D2Ysgu8LrCMSlh8iX9gj19VO3qYHtj5Dq0vac6NndQtauDnr59a5ylpSRRnp9FeUEWpx4RYGog3JyVF2RTkpdJWsrhXXemfIlLype45reMqYGLQVqaFggWd3ydr8Z3w7NHbvgrNLwDGJh6Opz0cTjqcsiZ6HWFY56v8zWGtQbD16P1j6Q1hv+ubOpgZ2sQG7UO9bj0FMoDWcyZnMvFRxdFRtCymRrIYtK4DKfT6Ctf4pLyJa75LWNq4GIQCAS8LkESmO/y1fTevpG2uvWAgbJT4OIfwZwrYJy/1lRJdL7L1xhhraWxvZvKyGmO2yPXpFVEZnps3tO93/6BnPD1aCcfUUB5pDnbO5I2ISvVswWolS9xSfkS1/yWMTVwMaipqSE3V7PjiRu+yNeu7fuatp1rwttKF8Ki74ebtlz/XAA81vgiXwmqL2TZubszMrNj9EhauFnbM+B6tOK8TMoLsrhobhFTC7L6R9LKC7LITo/Pb9vKl7ikfIlrfstYfH4niFN+687FX+I2Xy079jVtNavD20pOgAu/A3OuhLwpnpYnwxO3+UoQXb19VO3q3Lc22t5JQ5o7qGrupLsv1L9vWnISU/IzKS/I5uTp+ZFr08INWumErMO+Hs0Lype4pHyJa37LmBq4GASDwaF3EjlEcZWv3dXw9mPhtdqqVoS3TT4Wzv8mzL0SJkz1sDg5FHGVL59q7+qlomlP/0haZfO+Zq1md+d+16PlpKdQlp/F7KJxXDinKDKzY7hRK8rNINnh9WheUL7EJeVLXPNbxtTAxaC9vd3rEiSBeZ6vttpI0/ZXqHw1vG3SPDjv6+GRtoIjPC1PDo/n+fIBay3Ne7r710OriCxevXdB68b2/a9HK8hOo7wgi4XT8vsbtLL8bKYWZJGfnebZ9WheUL7EJeVLXPNbxtTAxcBva0SIv3iSr/Z6eOdxWP9XqHgZsFA4B875WnikLTBz9GsSJ/T5FRYKWWpbg+GmbJCRtPau3v59jYHi8ZmU5WdxwZxJ/deh7V0fbVxGqodHEl+UL3FJ+RLX/JYxNXAx8NsaEeIvo5avPU3hpm3Do7B9OdgQBGbBWV+GuR+AQmU8EY2lz6/u3hBVu8KThFQ07olMFhIeSduxq5Pu3n3Xo6UmG6ZMCDdlJ07Npyw/KzKzYzZT8jNJT0n28Ej8YyzlS0af8iWu+S1jauBikJGR4XUJksCc5qujGTYuC58eufVFsH2QfwSc8flI0zYnPNwgCSvRPr86unv3TRTS1LHfaY81LZ2Eoq5Hy0pLprwgm5mF4zj/qEn9E4aUF2QxeXxmwl2P5oVEy5fEF+VLXPNbxtTAxSAvL8/rEiSBjXi+Oltg05PhBba3Pg+h3vDkI6d9Oty0Fc1T0zaG+O3zy1pLS0dP//VnFXuvRYuc9tjY3rXf/vnZaZTlZ7GgfAJlx5dSHjWSFsgZW9ejecFv+RJ/Ub7ENb9lTA1cDGpra333Bot/jEi+gq2w6anwSNt7z0JfN4wvg5P/FY6+KjyTpH6QHZPi8fMrFLLUtQX3mywkeiStLdi73/6Tx2dQXpDFebMLKSvIYmpkJK2sIItcXY/mqXjMlyQO5Utc81vG1MDFoLCw0OsSJIEdcr662mHz0+Gm7d1/QF8X5JbAwtvDI20lJ6hpE88+v3r6QlTv6txvJK1/hsfmDrqirkdLSTJMyQ9PEHJ82YTwqY6RkbTSCVlkpOp6tHil74/ikvIlrvktY2rgYtDe3k5+fr7XZUiCiilf3Xvg3b+HT4989+/QG4ScIlhwK8y9CkpPhCT/LQYs7rj8/Ors7qOi+f3T7lc0dVDd0klf1AVpmanJlBdkMX1iNufMLgxPGhIZSZs8PoOUZOXWj/T9UVxSvsQ1v2VMDVwMOjo6vC5BEtiQ+erpDI+wbXgUNj8DPR2QXQjH3RIeaSs7RU2bHNDhfn61dHTvmyykcf9THevb9r8eLS8rlfKCbI6dkscVxxbvmzQkP4uJ49J1PVoC0vdHcUn5Etf8ljE1cDHw2xoR4i+D5qsnGL6WbcNfw9e2dbdDVgHMvz7ctJWfBkk6rUyGNtTnl7WW+rauAZOF7BtJ293Zs9/+RbkZlBVkcdasiUwNZPePpJUVZDE+U9ejjTX6/iguKV/imt8ypgYuBn5bI0L8pT9fvd3hWSPXPxqeRbKrFTInhCchmXsVTD0DkvVfV2JTUVHBjJmzqGkJ9k8WUtm0J7yQdVMHFc17CPbsux4tOclQOiG8iPXl84sj0+6HR9KmTMgiM02/OJB99P1RXFK+xDW/ZUw/BcYgKyvL6xIkUfX1kN+8Gv7237BxKQR3Q8Z4OOry8Ejb9LMgWaMaEptgTx8vbGrgiXU7Wb2tkbr2rfRGXY+WkZpEeX541OyMmQHKA+FJQ8oLsijOyyRV16PJMOn7o7ikfIlrfsuYGrgY5OTkeF2CJKK6t+HP11HYUgnpuTD70kjTdg6kpHldnfhMT1+I5e82snRtDX/fUEd7Vy/52WmcUDqODxRPoCxyLdrUQDaFuh5NRoi+P4pLype45reMqYGLQX19va9mqBEf2PoiPHgzpGZRdfoPKD3rI5Ca4XVV4jN9IcvrW5tYuraGp9bX0tLRQ25GCpfMK2Lx/GJOmV7Alnc3M3v2kV6XKglK3x/FJeVLXPNbxtTAxaCoqMjrEiSRrFkCj90JBTPgpofJYZyaNxm2UMiyunIXS9fU8MS6Whrbu8hOS+aCOZNYPL+YM2ZOJC1l3ymQ+vwSl5QvcUn5Etf8ljE1cDFoaWnx1SrtEqeshZd+DM9/B6adCdf+ATLzaNm+XfmSg7LWsq56N8vW7mTZmhpqdgdJT0ni3NmFLJ5fzDlHFh5wchF9folLype4pHyJa37LmBq4GASDQa9LEL/r64Fln4U3/wDHXA+X/3f/dW7KlxzIpto2lq6pYenaGiqaOkhNNpw5cyJfWjSb8+dMIid96I9y5UtcUr7EJeVLXPNbxobVwBljFgE/BZKB31hrvz/g/s8B/wL0Ag3Abdbaish9fcC6yK6V1trLR6j2Uee3NSIkznS1wUMfDq/rduaX4JyvQNQEEsqXRNva0M6ytTtZuqaGd+vbSTJw2owAd5w9g4vmFjE+K7ZZSZUvcUn5EpeUL3HNbxkbsoEzxiQDPwcuAKqAFcaYx621b0ft9iawwFrbYYz5BPBD4LrIfZ3W2mNHtmxv+G2NCIkjrTvhT9eEZ5y8/L/h+A+9bxflS6p2dYRPj1xbw/rqVoyBE6fm8+0r5nLxvMkEctIP+bmVL3FJ+RKXlC9xzW8ZG84I3EJgi7V2K4AxZglwBdDfwFlrn4/a/zXg5pEsMl74bYpRiRN1b8MD10CwBW56CGacP+huytfYVN8a5Il14ZG21ZUtABw7JY+vXXoUlx4zmcnjM0fkdZQvcUn5EpeUL3HNbxkbTgNXAuyIul0FnHSQ/T8KPBV1O8MYs5Lw6ZXft9b+bbAHGWNuB24HKC0tZePGjRQXF9PY2Eh3dzfl5eVUVFSQm5tLSkoKzc3NlJSUUFdXRygUorS0lMrKyv4LEFtaWigrK6OqqoqkpCQmTZpEdXU1+fn59Pb20tra2v+caWlpBAIBampqCAQCBINB2tvb++/PyMggLy+P+vp6srKyaG9vp6Ojo//+rKwscnJyqK+vp6ioiJaWFoLBYP/9OTk5ZGRk0NjYGHfHVFtbS2FhoY7J0TFl16+k+KUv0ZuUTtuVDxDMmkXrxo2DHlNqaipVVVVxf0yJ+D6N9jFt39nIs5ubeH1nLyu2t2CBWROzuPX4fK45aToZfXvo7u4mLw02btw4IsfU3t7OxgNkT++Tjulwj2nvFNyJdEyJ+D759ZiysrLYsmVLQh1TIr5Pfj6mlpYWCgoK4u6YDsRYaw94Z6SxuhpYZK39l8jtW4CTrLV3DrLvzcCdwFnW2q7IthJrbbUxZjrwHHCetfa9g73mggUL7MqVKw9alxc2btzoq+FV8diAZQLIm3LQ3ZWvxLa7s4e/b6hl6dqdvLylkb6QZfrEbC6fX8xlxxQzo9Dtb/+UL3FJ+RKXlC9xLV4zZoxZZa1dMHD7cEbgqoHonzxLI9sGvsD5wFeJat4ArLXVkb+3GmNeAI4DDtrAxavi4mKvSxA/OMAyAUNRvhJPR3cv/3ynnqVranhxUwPdfSGm5Gdy+5nTWXxMMUdNHoeJmsjGJeVLXFK+xCXlS1zzW8aG08CtAGYaY6YRbtyuB26M3sEYcxzwK8IjdfVR2ycAHdbaLmNMADiN8AQnvtTY2Ehubq7XZUg8O8gyAUNRvhJDsKePFzY1sHRtDc++U0ewJ8Sk3HRuOaWcxfOLmV86ftSatmjKl7ikfIlLype45reMDdnAWWt7jTF3As8QXkbgPmvtBmPMt4CV1trHgR8BOcDDkR9M9i4XcBTwK2NMCEgifA3c24O+kA90d3d7XYLEsyGWCRiK8uVf3b0hXt7SyNI1Nfz97Trau3opyE7jmhOmsHh+MQvKJ5CUNPpN2341Kl/ikPIlLilf4prfMjbkNXBeiNdr4Do7O8nMHJkZ4STBRC8TsPgngy4TMBTly1/6QpbXtjaxdE0NT2+opaWjh9yMFBYdXcTi+cWcMr2AlOQkr8vsp3yJS8qXuKR8iWvxmrHDuQZOIvy2RoSMkmEuEzAU5Sv+hUKWVZW7WLamhifW1dLY3kV2WjIXzJnE4vnFnDFzImkp8dO0RVO+xCXlS1xSvsQ1v2VMDVwM/HRurIySrS/CgzdDahbc+hRMPuaQn0r5ik/WWtZV72bpmhqWrd3Jzt1B0lOSOO+oQhYfU8w5swvJSE32uswhKV/ikvIlLilf4prfMqYGLgYpKfrnkigxLhMwFOUrflhr2VTX1t+0VTR1kJpsOGvWRL68aDbnz5lETrq/3i/lS1xSvsQl5Utc81vG/FWtx5qbmyksLPS6DPHaIS4TMBTly3tbG9pZtnYnS9fU8G59O8lJhlOPKOCOs2dw0dwixmelel3iIVO+xCXlS1xSvsQ1v2VMDVwMSkpKvC5BvHYYywQMRfnyxo7mDp5YF27aNtS0YgycODWfb195NBcfXUQgJ93rEkeE8iUuKV/ikvIlrvktY2rgYlBXV8e4ceO8LkO8EmyFhz9yyMsEDEX5Gj11rUGeWLuTpWtreLOyBYBjp+Txb5fN4dJ5kykan+FtgQ4oX+KS8iUuKV/imt8ypgYuBqFQyOsSxCutO8MzTda/HR51O4RlAoaifLnV1N7FU+trWba2hte3NWMtzJmcy5cWHcniY4qZkp/ldYlOKV/ikvIlLilf4prfMqYGLgalpaVelyBeGKFlAoaifI283Z09/H1DLUvX7uTlLY30hSxHTMzm0+fN5LJjiplRmON1iaNG+RKXlC9xSfkS1/yWMTVwMaisrPTVGhEyAkZwmYChKF8jY09XL/98p46la3by0uYGuvtCTMnP5GNnTueyY4o5avI4zAie+uoXype4pHyJS8qXuOa3jKmBi0FeXp7XJchoGuFlAoaifB26YE8fL2yqZ+manTy7sY5gT4ii3AxuOaWcxfOLmV86fkw2bdGUL3FJ+RKXlC9xzW8ZUwMnMpC18NKP4Pl/H9FlAmRkdfeGeHlLI0vX1PD3t+to7+olkJPGNSdMYfH8YhaUTyApaWw3bSIiIpJ41MDFoKWlhaKiIq/LEJeilwmYfwMs/q8RWyZgKMrX0PpClte2NrF0TQ1Pra9ld2cPuRkpXDpvMovnF3Py9HxSkpO8LjMuKV/ikvIlLilf4prfMqYGLgZlZWVelyAuOV4mYCjK1+BCIcuqyl0sXVPDk+tqaWzvIjstmQvnFnHZMZM5Y+ZE0lLUtA1F+RKXlC9xSfkS1/yWMTVwMaiqqmLWrFlelyEujMIyAUNRvvax1rK2ajfL1tawbO1Odu4Okp6SxHlHFbL4mGLOmV1IRmqy12X6ivIlLilf4pLyJa75LWNq4GKQlKTf8iekUVomYChjPV/WWjbWtrFsbQ1L1+yksrmD1GTDWbMmctfFsznvqEnkpOsj61CN9XyJW8qXuKR8iWt+y5h+GorBpEmTvC5BRtrWF+DBWyAt2/kyAUMZq/na2tDO0jU7Wbq2hi317SQnGU49ooA7z53BRXOKGJ+V6nWJCWGs5ktGh/IlLilf4prfMqYGLgbV1dW+WiNChvDWn+HxOyEwK7xMwHhvF3EcS/na0dzBsrU7Wba2hg01rRgDJ07N59tXHs3FRxcRyEn3usSEM5byJaNP+RKXlC9xzW8ZUwMXg/z8fK9LkJEQp8sEJHq+6lqDPLE2PNL2ZmULAMdOyePfLpvDpfMmUzQ+w9sCE1yi50u8pXyJS8qXuOa3jKmBi0Fvb6/XJcjh8nCZgKEkYr6a2rt4an0tS9fU8Mb2ZqyFOZNz+fKi2Vx2zGSm5Gd5XeKYkYj5kvihfIlLype45reMqYGLQWtrK8XFxV6XIYfK42UChpIo+drd2cMzG8JN2yvvNdEXshwxMZvPnDeLy+ZP5oiJOV6XOCYlSr4kPilf4pLyJa75LWNq4GJQXl7udQlyqFpr4IFrI8sE/AyOv8Xrit7Hz/na09XLP9+pY+manby0uYHuvhBT8jP52JnTWTy/mNlF4zBx1CyPRX7Ol8Q/5UtcUr7ENb9lTA1cDCoqKnx1gaNE1G2ILBOw29NlAobit3wFe/p4YVM9S9fs5NmNdQR7QhTlZvChU8pZPL+YY0rHq2mLI37Ll/iL8iUuKV/imt8ypgYuBmlp8XGtlMQgjpYJGIof8tXdG2L5lgaWrtnJP96uo72rl0BOGtcumMJlxxSzoHwCSUlq2uKRH/Il/qV8iUvKl7jmt4ypgYtBIBDwugSJRZwtEzCUeM1Xb1+I17Y2s3RNDU9vqGV3Zw/jM1O5dN5kFs8v5uTp+aQk+2sBzLEoXvMliUH5EpeUL3HNbxlTAxeDmpoacnNzvS5DhhKnywQMJZ7yFQpZVlXuYumaGp5ct5PG9m6y05K5cG4Ri+dP5vQZE0lLUdPmJ/GUL0k8ype4pHyJa37LmBq4GPitOx+T+npg2WfgzT/G3TIBQ/E6X9Za1lbtZumaGp5Yt5Odu4OkpyRx/lGTuOyYyZwzu5CM1GRPa5RD53W+JLEpX+KS8iWu+S1jauBiEAwGvS5BDibYCg9/GN57Ds76Mpx9d1wtEzAUL/JlrWVjbRtL19SwbO1OKps7SE02nDWrkLsuns15R00iJ10fE4lAn1/ikvIlLilf4prfMqafzGLQ3t7udQlyID5YJmAoo5mv9xraWbZmJ0vX1rClvp3kJMOpRxRw57kzuGhOEeOzUketFhkd+vwSl5QvcUn5Etf8ljE1cDHw2xoRY4ZPlgkYiut87WjuYNnanSxdU8PbO1sxBhZOzecjVx7NxUcXUZCT7vT1xVv6/BKXlC9xSfkS1/yWsWHNQmCMWWSM2WSM2WKMuWuQ+z9njHnbGLPWGPOsMaY86r4PG2Pejfz58EgWP9oqKiq8LkEG2voC3LcIbCi8TIBPmzdwk6/a3UHuXb6NK3/+Mmf88Hl+8PRG0lOT+LfL5vDqXefx4MdO4eaTy9W8jQH6/BKXlC9xSfkS1/yWsSFH4IwxycDPgQuAKmCFMeZxa+3bUbu9CSyw1nYYYz4B/BC4zhiTD3wDWABYYFXksbtG+kBGQ0ZGhtclSDSfLRMwlJHKV1N7F0+tr2Xpmhre2N6MtTBnci5fXjSby46ZzJT8rBF5HfEXfX6JS8qXuKR8iWt+y9hwTqFcCGyx1m4FMMYsAa4A+hs4a+3zUfu/Btwc+foi4B/W2ubIY/8BLAL+fPilj768vDyvSxAYsEzAWXDdHyBjvNdVHbbDydfuzh6e2RBu2l55r4m+kOWIidl85rxZXDZ/MkdMzBm5QsWX9PklLilf4pLyJa75LWPDaeBKgB1Rt6uAkw6y/0eBpw7y2JJYCowntbW1vnuDE46PlwkYSqz52tPVyz/fqWPpmhpe3NxAT5+lLD+Lj581ncuOKWZ20TiMj2bhFLf0+SUuKV/ikvIlrvktYyM6iYkx5mbCp0uedQiPvR24HaC0tJSNGzdSXFxMY2Mj3d3dlJeXU1FRQW5uLikpKTQ3N1NSUkJdXR2hUIjS0lIqKyv7//FbWlooKyujqqqKpKQkJk2aRHV1Nfn5+fT29tLa2tr/nGlpaQQCAWpqaggEAgSDQdrb2/vvz8jIIC8vj87OTpqbm2lvb6ejo6P//qysLHJycqivr6eoqIiWlhaCwWD//Tk5OWRkZNDY2Bh3x1RbW0thYaEvjimdbqa8+lVSKl6i48RP0nzMx2jfstXXxxT9PqWlpVFVVXXQ96mppZUXNzeyoj7EC5sa6eqzFOaksXh2LlctKKcko5euri7K81LZtGmT58eUKNlLhGNKSkpi48aNCXVMifg++fWYOjs76ejoSKhjSsT3ya/HlJOTw5YtWxLqmBLxffLzMXV2dtLZ2Rl3x3TAvslaO1RjdQpwj7X2osjtuwGstd8bsN/5wH8DZ1lr6yPbbgDOttZ+LHL7V8AL1tqDnkK5YMECu3LlyoPW5YXKykrKysq8LmNsil4mYPFPfblMwFAOlK/u3hDLtzSwdM1O/r6hlj3dfQRy0rhk3mQWzy/mhLIJJCVppE0OTp9f4pLyJS4pX+JavGbMGLPKWrtg4PbhjMCtAGYaY6YB1cD1wI0Dnvw44FfAor3NW8QzwHeNMRMity8E7j6E+uPCwTphcShBlgkYSnS+evtCvLa1maVranh6Qy27O3sYn5nK4vnFLJ5fzEnT8klJHtYksiKAPr/ELeVLXFK+xDW/ZWzIBs5a22uMuZNwM5YM3Get3WCM+Raw0lr7OPAjIAd4OHLNTaW19nJrbbMx5tuEm0CAb+2d0MSP/LZGRELY+gI8eAukZYeXCZh8jNcVOTOlrIw3toWbtqfW76SxvZuc9BQunDOJy+ZP5vQZE0lLUdMmh0afX+KS8iUuKV/imt8yNqxr4Ky1TwJPDtj29aivDzgkYq29D7jvUAuMJxUVFcyePdvrMsaOBFsm4EB2NHfwx9cq+MvKCho7+shITeK82ZNYPH8yZx9ZSEZqstclSgLQ55e4pHyJS8qXuOa3jI3oJCaJLitL62eNigRdJiCatZZVFbu47+VtPL2+FmMMJ5Xl8G8nH8H5R00iO13/NWVk6fNLXFK+xCXlS1zzW8b0U2IMcnK0lpZzCbxMAEBPX4gn1+3kvuXbWFO1m/GZqdx+5hF8+NRy0vs6yc/P97pESVD6/BKXlC9xSfkS1/yWMTVwMaivr9cP2C4FW+HhD8N7z8FZX4az74YEWcespaObP71Ryf2vVFDbGmR6IJtvX3k0Hzy+hKy08H/DjRsrlC9xRp9f4pLyJS4pX+Ka3zKmBi4GRUVFXpeQuKKXCbj8ZwmzTMCW+nZ++/I2/rK6imBPiNNnBPjuVUdz9qzC9039r3yJS8qXuKR8iUvKl7jmt4ypgYtBS0uLr1Zp940EWybAWsvyLY3cu3wbL2xqIC0liQ8cW8Ktp09ldlHuAR+nfIlLype4pHyJS8qXuOa3jKmBi0EwGPS6hMSTQMsEBHv6+Nub1dz38jY217UTyEnns+fP4qaTywjkpA/9eOVLHFK+xCXlS1xSvsQ1v2VMDVwM/LZGRNxLkGUC6luD/OG1Ch54vZLmPd0cNTmXH18zn8XzJ5OeMvwlAJQvcUn5EpeUL3FJ+RLX/JYxrQocg4qKCq9LSAzWwgs/gL99HMpPg9ue9mXztr56N5976C1O+8Fz/Oz5LRxfNoE//7+TefJTp3P1CaUxNW+gfIlbype4pHyJS8qXuOa3jGkELgZ+m2I0Lvl8mYC+kOWf79Rx3/JtvL6tmay0ZG46qZwPnzqVaYHsw3pu5UtcUr7EJeVLXFK+xDW/ZUwNXAwyMjK8LsHffLxMQHtXLw+v3MHvXtlORVMHJXmZfPWSo7j2xCmMz0wdkddQvsQl5UtcUr7EJeVLXPNbxtTAxaCxsZFAIOB1Gf7k02UCdjR38PtXtvPgih20dfVyfFkeX7poNhfNnURK8siegax8iUvKl7ikfIlLype45reMqYGLQXFxsdcl+JPPlgmw1rKqYhf3vbyNp9fXYozhknmTue20qRxXNsHZ6ypf4pLyJS4pX+KS8iWu+S1jauBi0NjYSG7ugdfxkkH4aJmAnr4QT67byX3Lt7GmajfjM1O5/cwj+NAp5RTnZTp/feVLXFK+xCXlS1xSvsQ1v2VMDVwMuru7vS7BX976Ezz+ybhfJqClo5s/vVHJ/a9UUNsaZHogm29feTQfPL6ErLTR+y+ifIlLype4pHyJS8qXuOa3jKmBi4Hf1ojwjLXw4g/hhe/CtLPguj9Axnivq3qfLfXt/PblbfxldRXBnhCnzwjw3auO5uxZhSQljf7kKsqXuKR8iUvKl7ikfIlrfsuYGrgYVFRUMHv2bK/LiG9xvkyAtZblWxq5d/k2XtjUQFpKElceW8xtp09jdpG3Q+fKl7ikfIlLype4pHyJa37LmBq4GPjp3FhPxPEyAcGePv72ZjX3vbyNzXXtBHLS+ez5s7jp5DICOelelwcoX+KW8iUuKV/ikvIlrvktY2rgYpCSon+uA2qtCc80Wf9OXC0TUN8a5A+vVfDA65U07+nmqMm5/Pia+SyeP5n0lGSvy9uP8iUuKV/ikvIlLilf4prfMuavaj3W3NxMYWGh12XEnzhcJmBDzW7uXb6NpWtq6A1Zzps9iY+ePo2Tp+dj4mRUcCDlS1xSvsQl5UtcUr7ENb9lTA1cDEpKSrwuIf7E0TIBfSHLs+/Uce/ybby+rZmstGRuOqmcD586lWmBbM/qGi7lS1xSvsQl5UtcUr7ENb9lTA1cDOrq6hg3bpzXZcSPOFkmoL2rl4dX7uB3r2ynoqmDkrxMvnLJbK47sYzxmame1HQolC9xSfkSl5QvcUn5Etf8ljE1cDEIhUJelxAf4mSZgB3NHfz+le08uGIHbV29HF+Wx5cums1FcyeRkpw06vUcLuVLXFK+xCXlS1xSvsQ1v2VMDVwMSkvjcyHqUeXxMgHWWlZV7OK+l7fx9PpajDFcMm8yt502lePKJoxaHS4oX+KS8iUuKV/ikvIlrvktY/4bpvBQZWWl1yV4K9gKf7o23Lyd9WW48pej1rz19IV47K1qrvz5y1z9P6/y8pYmbj/zCP7vS+fw3zcc5/vmDZQvcUv5EpeUL3FJ+RLX/JYxjcDFIC8vz+sSvLN3mYCGjaO6TEBLRzd/eqOS+1+poLY1yPRANt++Yi4fPKGUrLTEiu+Yzpc4p3yJS8qXuKR8iWt+y1hi/QQsbkQvE3DjQzDjPOcvuaW+nd++vI2/rK4i2BPitBkFfPeqozl7ViFJSfG5DICIiIiIiGtq4GLQ0tJCUVGR12WMrlFcJsBay/Itjdy7fBsvbGogLSWJK48t5rbTpzG7KNfZ68aLMZkvGTXKl7ikfIlLype45reMqYGLQVlZmdcljK5RWiYg2NPH396s5r6Xt7G5rp1ATjqfPX8WN51cRiAn3clrxqMxly8ZVcqXuKR8iUvKl7jmt4xpEpMYVFVVeV3C6LAWXvgB/O0TUH4a3Pa0k+atvi3If/x9E6d+/znuenQdyUlJ/Pia+bx81zl8+vyZY6p5gzGUL/GE8iUuKV/ikvIlrvktYxqBi0FS0hjod/t6YOln4K0/wvwbYfFPR3ymyQ01u7l3+TaWrqmhN2Q5b/Ykbjt9KqdML8CYsXt925jIl3hG+RKXlC9xSfkS1/yWsWE1cMaYRcBPgWTgN9ba7w+4/0zgJ8AxwPXW2kei7usD1kVuVlprLx+Buj0xadIkr0twK9gKD30Itj4fXibg7LthhBqqvpDl2XfquHf5Nl7f1kxWWjI3LizjI6dNY1oge0Rew+8SPl/iKeVLXFK+xCXlS1zzW8aGbOCMMcnAz4ELgCpghTHmcWvt21G7VQIfAb4wyFN0WmuPPfxSvVddXc3s2bO9LsMNR8sEtHf18vDKHfzule1UNHVQkpfJVy6ZzXUnljE+M3VEXiNRJHS+xHPKl7ikfIlLype45reMDWcEbiGwxVq7FcAYswS4Auhv4Ky12yP3hRzUGDfy8/O9LsENB8sE7Gju4PevbOfBFTto6+rl+LI8vnTRbC6aO4mUZH8NU4+WhM2XxAXlS1xSvsQl5Utc81vGhtPAlQA7om5XASfF8BoZxpiVQC/wfWvt32J4bFzp7e31uoSRN4LLBFhrWV25i3uXb+Pp9bUYY7hk3mRuO20qx5VNGLmaE1RC5kvihvIlLilf4pLyJa75LWOjMYlJubW22hgzHXjOGLPOWvvewJ2MMbcDtwOUlpayceNGiouLaWxspLu7m/LycioqKsjNzSUlJYXm5mZKSkqoq6sjFApRWlpKZWVl/0rqLS0tlJWVUVVVRVJSEpMmTaK6upr8/Hx6e3tpbW3tf860tDQCgQA1NTUEAgGCwSDt7e3992dkZJCXl8fWrVvJyMigvb2djo6O/vuzsrLIycmhvr6eoqIiWlpaCAaD/ffn5OSQkZFBY2NjXB3TxJp/kvWPL9GXP4O6835G2+40yvM6Yz6miZOKeHTFNh5e28Tmxi5y0pK44fhCrj++iNSePZRMSGHLli2j9j7V1tZSWFjou/epo6ODUCiUUMeUiO+TX4+puro64Y4pEd8nvx7T1q1bycvLS6hjSsT3ya/H1N3d3f89MlGOKRHfJz8fU01NDRMmTIi7YzoQY6094J2RxuoU4B5r7UWR23cDWGu/N8i+vwOWRU9iEsv9ey1YsMCuXLnyoHV5obOzk8zMTK/LOHzWwos/hBe+C9POguv+ABnjY36alo5u/vRGJfe/UkFta5DpgWxuPW0qHzyhlKw0TXAaq4TJl8Ql5UtcUr7EJeVLXIvXjBljVllrFwzcPpyLkVYAM40x04wxacD1wOPDfNEJxpj0yNcB4DSirp3zm4qKCq9LOHx9PfDYneHmbf6NcNMjMTdvW+rb+epf13Hy957lh09v4ojCbO77yAL++bmzuOWUqWreDlFC5EvilvIlLilf4pLyJa75LWND/qRtre01xtwJPEN4GYH7rLUbjDHfAlZaax83xpwI/BWYACw2xnzTWjsXOAr4VWRykyTC18D5toFLSxvZ9dBG3WEsE2CtZfmWRu5dvo0XNjWQlpLElccWc9vp05hdlOu48LHB9/mSuKZ8iUvKl7ikfIlrfsvYsIZKrLVPAk8O2Pb1qK9XAKWDPO4VYN5h1hg3AoGA1yUcukNcJiDY08djb1Vz3/LtbKprI5CTxmfPn8VNJ5cRyEl3XPTY4ut8SdxTvsQl5UtcUr7ENb9lTOe6xaCmpobcXB+ONh3CMgH1bUH++GoFf3y9kuY93cwuGsePrj6Gy48tJj0leRSKHnt8my/xBeVLXFK+xCXlS1zzW8bUwMXAb905AO89Hz5tcpjLBGyo2c29y7exdE0NvSHLebMLue30aZwyvQAzzNMt5dD4Ml/iG8qXuKR8iUvKl7jmt4ypgYtBMBj0uoTYvPUnePyTEDgSbnoIxr/vLFcA+kKWZ9+p497l23h9WzNZacncuLCMj5w2jWmB7FEueuzyXb7EV5QvcUn5EpeUL3HNbxlTAxeD9vZ2r0sYnmEuE9De1csjK3fw21e2U9HUQUleJl+5ZDbXnVjG+MxUDwof23yTL/El5UtcUr7EJeVLXPNbxtTAxaC8vNzrEobW1wNLPwNv/TG8TMDin0LK/jPr7Gju4P5Xt7NkxQ7agr0cX5bHFy86kkVzi0hJHs7KEuKCL/IlvqV8iUvKl7ikfIlrfsuYGrgYVFRUMHv2bK/LOLCDLBNgrWV15S7uXb6Np9fXYozhknmTue20qRxXNsHjwgV8kC/xNeVLXFK+xCXlS1zzW8bUwMUgIyPD6xIO7ADLBPT0hXhy3U7uW76NNVW7yc1I4f+dOZ0PnzKV4rz4W3F+LIvrfInvKV/ikvIlLilf4prfMqYGLgZ5eXlelzC4/mUCWvuXCWjp6OZPb1Ry/ysV1LYGmR7I5ttXzOWDJ5SSlaa3PR7Fbb4kIShf4pLyJS4pX+Ka3zKmn+RjUFtbG39vcPQyAbc9xXvJ0/jt39bxl1XVdPb0cdqMAr571dGcPauQpCQtAxDP4jJfkjCUL3FJ+RKXlC9xzW8ZUwMXg8LCQq9L2F9kmQAbmMUbp/4P//NUJ89vepG0lCSuPLaYW0+bxlGT/bMo4VgXd/mShKJ8iUvKl7ikfIlrfsuYGrgYtLe3k5+f73UZ+y0TUFtwEp8IfpY3l1QRyEnjs+fP4qaTywjkpHtdpcQobvIlCUn5EpeUL3FJ+RLX/JYxNXAx6Ojo8LoE6Ouh89E7ydywhMfN2Xy++jaOKMrmR1dP4/Jji0lPSfa6QjlEcZEvSVjKl7ikfIlLype45reMqYGLgddrRLyzvYqkhz/MkXtW8pPeq1g/4xP8/ozpnDK9AGN0fZvfeZ0vSWzKl7ikfIlLype45reMadXmGFRUVIz6a/aFLH/fUMsnfrkU7ruY6e1v8teyr3DFZ37Gbz6ykFOPCKh5SxBe5EvGDuVLXFK+xCXlS1zzW8Y0AheDrKysUXut9q5eHlm5g9++sp2M5o3cn/4jJqQG6b5qCR+Ye+Go1SGjZzTzJWOP8iUuKV/ikvIlrvktY2rgYpCTk+P8NXY0d3D/q9tZsmIHbcFePlK0ja9mf4+UzHGYmx4jrWie8xrEG6ORLxm7lC9xSfkSl5Qvcc1vGVMDF4P6+nonM9RYa1lduYt7l2/j6fW1GGO4ZN5kvlC4gvKXvwGBI+Gmh2B86Yi/tsQPV/kSAeVL3FK+xCXlS1zzW8bUwMWgqKhoRJ+vpy/Ek+t2ct/L21mzo4XcjBT+35nT+fDJ5RSv+W944bsw/Wy49n7IGD+iry3xZ6TzJRJN+RKXlC9xSfkS1/yWMTVwMWhpaRmRVdpbOrr50xuV3P9KBbWtQaYFsvn2FXO56vhSslMsLP0MvPVHmH8jLP4ppKQd9mtK/BupfIkMRvkSl5QvcUn5Etf8ljE1cDEIBoOH9fj3Gtr57cvb+Muqajp7+jhtRgHfvepozp5VSFKSgWArPPAh2Po8nHUXnH0XaIbJMeNw8yVyMMqXuKR8iUvKl7jmt4ypgYvBoawRYa1l+ZZG7lu+jec3NZCWksSVxxZz62nTOGpy7r4dd1fDn66Fho1wxc/huJtHsHLxA7+tQSL+onyJS8qXuKR8iWt+y5jWgYtBLGtEBHv6eHBFJYt+8n/ccu8brKvezWfOn8krd53LD6+ev3/zVrsefnM+7KqAGx9S8zZG+W0NEvEX5UtcUr7EJeVLXPNbxjQCF4PhTDFa3xbkj69W8MDrlTTt6WZ20Th+dPUxLJ5fTEZq8vsf8N7z8NCHIC0HbnsKtEzAmOW3KWzFX5QvcUn5EpeUL3HNbxlTAxeDjIyMA963oWY39y3fztI1NfSEQpw3u5DbTp/GKdMLMAe6ju3NB2DppyLLBDwM40scVS5+cLB8iRwu5UtcUr7EJeVLXPNbxtTAxaCxsZFAINB/uy9kefadOu57eRuvbW0mKy2ZGxZO4SOnTWNaIPvAT2QtvPhDLRMg+xmYL5GRpHyJS8qXuKR8iWt+y5gauBgUFxcD0N7VyyMrd/DbV7ZT0dRBSV4mX7lkNtctKGN8VurBn6SvB5Z+Gt56QMsEyH725kvEBeVLXFK+xCXlS1zzW8bUwMVg/badPF9VxZIVO2gL9nJcWR5fvOhIFs0tIiV5GPPBBFvD17tpmQAZRGNjI7m5uUPvKHIIlC9xSfkSl5Qvcc1vGVMDNwzVLZ38+xNv8/T6WowxXHx0EbedPo3jyyYM/0m0TIAMobu72+sSJIEpX+KS8iUuKV/imt8ypgZuGLLTklld0cKtp5Tx0TNnUJyXGdsT1K6HB66BrrbwMgEzznNTqPia39YgEX9RvsQl5UtcUr7ENb9lTOvADUNeVhrLv3wO18xKjb15e+95+O3F4a9ve0rNmxyQ39YgEX9RvsQl5UtcUr7ENb9lbFgNnDFmkTFmkzFmizHmrkHuP9MYs9oY02uMuXrAfR82xrwb+fPhkSp8tKUkJ8V+buybD8ADV8P4KfAv/9Qab3JQfjr3WvxH+RKXlC9xSfkS1/yWsSFPoTTGJAM/By4AqoAVxpjHrbVvR+1WCXwE+MKAx+YD3wAWABZYFXnsrpEpf3SlpAzzjFNr4cUfwAvf0zIBMmzDzpfIIVC+xCXlS1xSvsQ1v2VsOCNwC4Et1tqt1tpuYAlwRfQO1trt1tq1QGjAYy8C/mGtbY40bf8AFo1A3Z5obm4eeqe+HnjsjnDzNv9GuPFhNW8yLMPKl8ghUr7EJeVLXFK+xDW/ZWw47WYJsCPqdhVw0jCff7DHlgzzsXGnpGSI0rVMgByGIfMlchiUL3FJ+RKXlC9xzW8Zi5vxQmPM7cDtAKWlpWzcuJHi4mIaGxvp7u6mvLyciooKcnNzSUlJobm5mZKSEurq6giFQpSWllJZWUleXh4ALS0tlJWVUVVVRVJSEpMmTaK6upr8/Hx6e3tpbW3tf860tDQCgQA1NTUEAgGCwSDt7e3992dkZJCXl8fbb7/N7NmzaW9vp6Ojo//+rKwsxtk2Mv/6IdJbt9N02jdpnLyI8mCQiooKcnJyyMjIoLGxMe6Oqba2lsLCwkGPKScnh/r6eoqKimhpaSEYDPbfr2Ma+WPq6uqioKAgoY4pEd8nvx5TVVUVWVlZCXVMifg++fWYtm7dyrHHHptQx5SI75Nfj6mvr4/09PSEOqZEfJ/8fEy1tbUcd9xxcXdMB+ybrLVDNVanAPdYay+K3L4bwFr7vUH2/R2wzFr7SOT2DcDZ1tqPRW7/CnjBWvvng73mggUL7MqVKw9alxc2b97MrFmz3n9H9DIB1/5eM03KITlgvkRGgPIlLilf4pLyJa7Fa8aMMaustQsGbh/ONXArgJnGmGnGmDTgeuDxYb7uM8CFxpgJxpgJwIWRbb5UWlr6/o3vPQf3RS7r0zIBchgGzZfICFG+xCXlS1xSvsQ1v2VsyAbOWtsL3Em48XoHeMhau8EY8y1jzOUAxpgTjTFVwDXAr4wxGyKPbQa+TbgJXAF8K7LNlyorK/ff8OYD4ZG3vDItEyCH7X35EhlBype4pHyJS8qXuOa3jA3rGjhr7ZPAkwO2fT3q6xXAoK2rtfY+4L7DqDFu7D3nVcsEiAv9+RJxQPkSl5QvcUn5Etf8lrG4mcTEN/p6YOmn4a0HwssELP4ppKR5XZWIiIiIiIwBw7kGTiJaG6rCp0y+9UB4mYArf6HmTUZMS0uL1yVIAlO+xCXlS1xSvsQ1v2VMI3DDtbuaGS99Epo2wxU/h+Nu9roiSTBlZWVelyAJTPkSl5QvcUn5Etf8ljGNwA1H4xb4zfnYXRVw40Nq3sSJqqoqr0uQBKZ8iUvKl7ikfIlrfsuYRuCGY9wkmDyf6pkfokzLBIgjSUn6fYq4o3yJS8qXuKR8iWt+y5gauOFIHwc3LmFCW5vXlUgCmzRpktclSAJTvsQl5UtcUr7ENb9lzF/tpseqq6u9LkESmPIlLilf4pLyJS4pX+Ka3zKmBi4G+fn5XpcgCUz5EpeUL3FJ+RKXlC9xzW8ZUwMXg97eXq9LkASmfIlLype4pHyJS8qXuOa3jKmBi0Fra6vXJUgCU77EJeVLXFK+xCXlS1zzW8bUwMWgvLzc6xIkgSlf4pLyJS4pX+KS8iWu+S1jauBiUFFR4XUJksCUL3FJ+RKXlC9xSfkS1/yWMTVwMUhLS/O6BElgype4pHyJS8qXuKR8iWt+y5gauBgEAgGvS5AEpnyJS8qXuKR8iUvKl7jmt4ypgYtBTU2N1yVIAlO+xCXlS1xSvsQl5Utc81vGjLXW6xrexxjTAMTjyagBoNHrIiRhKV/ikvIlLilf4pLyJa7Fa8bKrbUTB26MywYuXhljVlprF3hdhyQm5UtcUr7EJeVLXFK+xDW/ZUynUIqIiIiIiPiEGjgRERERERGfUAMXm197XYAkNOVLXFK+xCXlS1xSvsQ1X2VM18CJiIiIiIj4hEbgREREREREfEINnIiIiIiIiE+ogRsGY8wiY8wmY8wWY8xdXtcjicUYc58xpt4Ys97rWiTxGGOmGGOeN8a8bYzZYIz5tNc1SeIwxmQYY94wxqyJ5OubXtckiccYk2yMedMYs8zrWiSxGGO2G2PWGWPeMsas9Lqe4dI1cEMwxiQDm4ELgCpgBXCDtfZtTwuThGGMORNoB+631h7tdT2SWIwxk4HJ1trVxphxwCrgSn2GyUgwxhgg21rbboxJBZYDn7bWvuZxaZJAjDGfAxYAudbay7yuRxKHMWY7sMBaG4+LeB+QRuCGthDYYq3daq3tBpYAV3hckyQQa+1LQLPXdUhistbutNaujnzdBrwDlHhblSQKG9YeuZka+aPfDMuIMcaUApcCv/G6FpF4oQZuaCXAjqjbVeiHHxHxIWPMVOA44HWPS5EEEjm97S2gHviHtVb5kpH0E+BLQMjjOiQxWeDvxphVxpjbvS5muNTAiYiMAcaYHOAvwGesta1e1yOJw1rbZ609FigFFhpjdCq4jAhjzGVAvbV2lde1SMI63Vp7PHAxcEfkspa4pwZuaNXAlKjbpZFtIiK+ELk26S/AA9baR72uRxKTtbYFeB5Y5HEpkjhOAy6PXKe0BDjXGPNHb0uSRGKtrY78XQ/8lfClU3FPDdzQVgAzjTHTjDFpwPXA4x7XJCIyLJFJJu4F3rHW/ofX9UhiMcZMNMbkRb7OJDzh10ZPi5KEYa2921pbaq2dSvjnr+estTd7XJYkCGNMdmRyL4wx2cCFgC9mBFcDNwRrbS9wJ/AM4Yv/H7LWbvC2Kkkkxpg/A68CRxpjqowxH/W6JkkopwG3EP7N9VuRP5d4XZQkjMnA88aYtYR/4fkPa62mehcRP5gELDfGrAHeAJ6w1j7tcU3DomUEREREREREfEIjcCIiIiIiIj6hBk5ERERERMQn1MCJiIiIiIj4hBo4ERERERERn1ADJyIiIiIi4hNq4EREJGEZY/qilk94yxhz1wg+91RjjC/WDBIRkcSR4nUBIiIiDnVaa4/1uggREZGRohE4EREZc4wx240xPzTGrDPGvGGMmRHZPtUY85wxZq0x5lljTFlk+yRjzF+NMWsif06NPFWyMeZ/jTEbjDF/N8ZkenZQIiIyJqiBExGRRJY54BTK66Lu222tnQf8DPhJZNt/A7+31h4DPAD8V2T7fwEvWmvnA8cDGyLbZwI/t9bOBVqADzo9GhERGfOMtdbrGkRERJwwxrRba3MG2b4dONdau9UYkwrUWmsLjDGNwGRrbU9k+05rbcAY0wCUWmu7op5jKvAPa+3MyO0vA6nW2u+MwqGJiMgYpRE4EREZq+wBvo5FV9TXfejachERcUwNnIiIjFXXRf39auTrV4DrI1/fBPxf5OtngU8AGGOSjTHjR6tIERGRaPpNoYiIJLJMY8xbUbefttbuXUpggjFmLeFRtBsi2z4J/NYY80WgAbg1sv3TwK+NMR8lPNL2CWCn6+JFREQG0jVwIiIy5kSugVtgrW30uhYREZFY6BRKERERERERn9AInIiIiIiIiE9oBE5ERERERMQn1MCJiIiIiIj4hBo4ERERERERn1ADJyIiIiIi4hNq4ERERERERHzi/wfxsGb11degDgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1080x1080 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "num_train = 4000\n",
    "small_data = {\n",
    "  'X_train': data['X_train'][:num_train],\n",
    "  'y_train': data['y_train'][:num_train],\n",
    "  'X_val': data['X_val'],\n",
    "  'y_val': data['y_val'],\n",
    "}\n",
    "\n",
    "solvers = {}\n",
    "\n",
    "for update_rule in ['sgd', 'sgd_momentum']:\n",
    "    print('Running with ', update_rule)\n",
    "    model = FullyConnectedNet(\n",
    "        [100, 100, 100, 100, 100],\n",
    "        weight_scale=5e-2\n",
    "    )\n",
    "\n",
    "    solver = Solver(\n",
    "        model,\n",
    "        small_data,\n",
    "        num_epochs=5,\n",
    "        batch_size=100,\n",
    "        update_rule=update_rule,\n",
    "        optim_config={'learning_rate': 5e-3},\n",
    "        verbose=True,\n",
    "    )\n",
    "    solvers[update_rule] = solver\n",
    "    solver.train()\n",
    "\n",
    "fig, axes = plt.subplots(3, 1, figsize=(15, 15))\n",
    "\n",
    "axes[0].set_title('Training loss')\n",
    "axes[0].set_xlabel('Iteration')\n",
    "axes[1].set_title('Training accuracy')\n",
    "axes[1].set_xlabel('Epoch')\n",
    "axes[2].set_title('Validation accuracy')\n",
    "axes[2].set_xlabel('Epoch')\n",
    "\n",
    "for update_rule, solver in solvers.items():\n",
    "    axes[0].plot(solver.loss_history, label=f\"loss_{update_rule}\")\n",
    "    axes[1].plot(solver.train_acc_history, label=f\"train_acc_{update_rule}\")\n",
    "    axes[2].plot(solver.val_acc_history, label=f\"val_acc_{update_rule}\")\n",
    "    \n",
    "for ax in axes:\n",
    "    ax.legend(loc=\"best\", ncol=4)\n",
    "    ax.grid(linestyle='--', linewidth=0.5)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## RMSProp and Adam\n",
    "RMSProp [1] and Adam [2] are update rules that set per-parameter learning rates by using a running average of the second moments of gradients.\n",
    "\n",
    "In the file `cs231n/optim.py`, implement the RMSProp update rule in the `rmsprop` function and implement the Adam update rule in the `adam` function, and check your implementations using the tests below.\n",
    "\n",
    "**NOTE:** Please implement the _complete_ Adam update rule (with the bias correction mechanism), not the first simplified version mentioned in the course notes. \n",
    "\n",
    "[1] Tijmen Tieleman and Geoffrey Hinton. \"Lecture 6.5-rmsprop: Divide the gradient by a running average of its recent magnitude.\" COURSERA: Neural Networks for Machine Learning 4 (2012).\n",
    "\n",
    "[2] Diederik Kingma and Jimmy Ba, \"Adam: A Method for Stochastic Optimization\", ICLR 2015."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "next_w error:  9.524687511038133e-08\n",
      "cache error:  2.6477955807156126e-09\n"
     ]
    }
   ],
   "source": [
    "# Test RMSProp implementation\n",
    "from cs231n.optim import rmsprop\n",
    "\n",
    "N, D = 4, 5\n",
    "w = np.linspace(-0.4, 0.6, num=N*D).reshape(N, D)\n",
    "dw = np.linspace(-0.6, 0.4, num=N*D).reshape(N, D)\n",
    "cache = np.linspace(0.6, 0.9, num=N*D).reshape(N, D)\n",
    "\n",
    "config = {'learning_rate': 1e-2, 'cache': cache}\n",
    "next_w, _ = rmsprop(w, dw, config=config)\n",
    "\n",
    "expected_next_w = np.asarray([\n",
    "  [-0.39223849, -0.34037513, -0.28849239, -0.23659121, -0.18467247],\n",
    "  [-0.132737,   -0.08078555, -0.02881884,  0.02316247,  0.07515774],\n",
    "  [ 0.12716641,  0.17918792,  0.23122175,  0.28326742,  0.33532447],\n",
    "  [ 0.38739248,  0.43947102,  0.49155973,  0.54365823,  0.59576619]])\n",
    "expected_cache = np.asarray([\n",
    "  [ 0.5976,      0.6126277,   0.6277108,   0.64284931,  0.65804321],\n",
    "  [ 0.67329252,  0.68859723,  0.70395734,  0.71937285,  0.73484377],\n",
    "  [ 0.75037008,  0.7659518,   0.78158892,  0.79728144,  0.81302936],\n",
    "  [ 0.82883269,  0.84469141,  0.86060554,  0.87657507,  0.8926    ]])\n",
    "\n",
    "# You should see relative errors around e-7 or less\n",
    "print('next_w error: ', rel_error(expected_next_w, next_w))\n",
    "print('cache error: ', rel_error(expected_cache, config['cache']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "next_w error:  1.1395691798535431e-07\n",
      "v error:  4.208314038113071e-09\n",
      "m error:  4.214963193114416e-09\n"
     ]
    }
   ],
   "source": [
    "# Test Adam implementation\n",
    "from cs231n.optim import adam\n",
    "\n",
    "N, D = 4, 5\n",
    "w = np.linspace(-0.4, 0.6, num=N*D).reshape(N, D)\n",
    "dw = np.linspace(-0.6, 0.4, num=N*D).reshape(N, D)\n",
    "m = np.linspace(0.6, 0.9, num=N*D).reshape(N, D)\n",
    "v = np.linspace(0.7, 0.5, num=N*D).reshape(N, D)\n",
    "\n",
    "config = {'learning_rate': 1e-2, 'm': m, 'v': v, 't': 5}\n",
    "next_w, _ = adam(w, dw, config=config)\n",
    "\n",
    "expected_next_w = np.asarray([\n",
    "  [-0.40094747, -0.34836187, -0.29577703, -0.24319299, -0.19060977],\n",
    "  [-0.1380274,  -0.08544591, -0.03286534,  0.01971428,  0.0722929],\n",
    "  [ 0.1248705,   0.17744702,  0.23002243,  0.28259667,  0.33516969],\n",
    "  [ 0.38774145,  0.44031188,  0.49288093,  0.54544852,  0.59801459]])\n",
    "expected_v = np.asarray([\n",
    "  [ 0.69966,     0.68908382,  0.67851319,  0.66794809,  0.65738853,],\n",
    "  [ 0.64683452,  0.63628604,  0.6257431,   0.61520571,  0.60467385,],\n",
    "  [ 0.59414753,  0.58362676,  0.57311152,  0.56260183,  0.55209767,],\n",
    "  [ 0.54159906,  0.53110598,  0.52061845,  0.51013645,  0.49966,   ]])\n",
    "expected_m = np.asarray([\n",
    "  [ 0.48,        0.49947368,  0.51894737,  0.53842105,  0.55789474],\n",
    "  [ 0.57736842,  0.59684211,  0.61631579,  0.63578947,  0.65526316],\n",
    "  [ 0.67473684,  0.69421053,  0.71368421,  0.73315789,  0.75263158],\n",
    "  [ 0.77210526,  0.79157895,  0.81105263,  0.83052632,  0.85      ]])\n",
    "\n",
    "# You should see relative errors around e-7 or less\n",
    "print('next_w error: ', rel_error(expected_next_w, next_w))\n",
    "print('v error: ', rel_error(expected_v, config['v']))\n",
    "print('m error: ', rel_error(expected_m, config['m']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Once you have debugged your RMSProp and Adam implementations, run the following to train a pair of deep networks using these new update rules:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running with  adam\n",
      "(Iteration 1 / 200) loss: 3.476928\n",
      "(Epoch 0 / 5) train acc: 0.126000; val_acc: 0.110000\n",
      "(Iteration 11 / 200) loss: 2.027712\n",
      "(Iteration 21 / 200) loss: 2.183358\n",
      "(Iteration 31 / 200) loss: 1.744257\n",
      "(Epoch 1 / 5) train acc: 0.363000; val_acc: 0.330000\n",
      "(Iteration 41 / 200) loss: 1.707951\n",
      "(Iteration 51 / 200) loss: 1.703835\n",
      "(Iteration 61 / 200) loss: 2.094758\n",
      "(Iteration 71 / 200) loss: 1.505614\n",
      "(Epoch 2 / 5) train acc: 0.419000; val_acc: 0.366000\n",
      "(Iteration 81 / 200) loss: 1.593840\n",
      "(Iteration 91 / 200) loss: 1.492122\n",
      "(Iteration 101 / 200) loss: 1.393160\n",
      "(Iteration 111 / 200) loss: 1.441590\n",
      "(Epoch 3 / 5) train acc: 0.494000; val_acc: 0.380000\n",
      "(Iteration 121 / 200) loss: 1.188173\n",
      "(Iteration 131 / 200) loss: 1.484940\n",
      "(Iteration 141 / 200) loss: 1.363281\n",
      "(Iteration 151 / 200) loss: 1.340405\n",
      "(Epoch 4 / 5) train acc: 0.531000; val_acc: 0.370000\n",
      "(Iteration 161 / 200) loss: 1.488828\n",
      "(Iteration 171 / 200) loss: 1.278309\n",
      "(Iteration 181 / 200) loss: 1.123501\n",
      "(Iteration 191 / 200) loss: 1.290712\n",
      "(Epoch 5 / 5) train acc: 0.583000; val_acc: 0.374000\n",
      "\n",
      "Running with  rmsprop\n",
      "(Iteration 1 / 200) loss: 2.589166\n",
      "(Epoch 0 / 5) train acc: 0.119000; val_acc: 0.146000\n",
      "(Iteration 11 / 200) loss: 2.032921\n",
      "(Iteration 21 / 200) loss: 1.897278\n",
      "(Iteration 31 / 200) loss: 1.770793\n",
      "(Epoch 1 / 5) train acc: 0.381000; val_acc: 0.320000\n",
      "(Iteration 41 / 200) loss: 1.895731\n",
      "(Iteration 51 / 200) loss: 1.681091\n",
      "(Iteration 61 / 200) loss: 1.487204\n",
      "(Iteration 71 / 200) loss: 1.629973\n",
      "(Epoch 2 / 5) train acc: 0.429000; val_acc: 0.350000\n",
      "(Iteration 81 / 200) loss: 1.506686\n",
      "(Iteration 91 / 200) loss: 1.610742\n",
      "(Iteration 101 / 200) loss: 1.486124\n",
      "(Iteration 111 / 200) loss: 1.559454\n",
      "(Epoch 3 / 5) train acc: 0.492000; val_acc: 0.359000\n",
      "(Iteration 121 / 200) loss: 1.496860\n",
      "(Iteration 131 / 200) loss: 1.531552\n",
      "(Iteration 141 / 200) loss: 1.550195\n",
      "(Iteration 151 / 200) loss: 1.657838\n",
      "(Epoch 4 / 5) train acc: 0.533000; val_acc: 0.354000\n",
      "(Iteration 161 / 200) loss: 1.603105\n",
      "(Iteration 171 / 200) loss: 1.408064\n",
      "(Iteration 181 / 200) loss: 1.504707\n",
      "(Iteration 191 / 200) loss: 1.385212\n",
      "(Epoch 5 / 5) train acc: 0.528000; val_acc: 0.370000\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "learning_rates = {'rmsprop': 1e-4, 'adam': 1e-3}\n",
    "for update_rule in ['adam', 'rmsprop']:\n",
    "    print('Running with ', update_rule)\n",
    "    model = FullyConnectedNet(\n",
    "        [100, 100, 100, 100, 100],\n",
    "        weight_scale=5e-2\n",
    "    )\n",
    "    solver = Solver(\n",
    "        model,\n",
    "        small_data,\n",
    "        num_epochs=5,\n",
    "        batch_size=100,\n",
    "        update_rule=update_rule,\n",
    "        optim_config={'learning_rate': learning_rates[update_rule]},\n",
    "        verbose=True\n",
    "    )\n",
    "    solvers[update_rule] = solver\n",
    "    solver.train()\n",
    "    print()\n",
    "    \n",
    "fig, axes = plt.subplots(3, 1, figsize=(15, 15))\n",
    "\n",
    "axes[0].set_title('Training loss')\n",
    "axes[0].set_xlabel('Iteration')\n",
    "axes[1].set_title('Training accuracy')\n",
    "axes[1].set_xlabel('Epoch')\n",
    "axes[2].set_title('Validation accuracy')\n",
    "axes[2].set_xlabel('Epoch')\n",
    "\n",
    "for update_rule, solver in solvers.items():\n",
    "    axes[0].plot(solver.loss_history, label=f\"{update_rule}\")\n",
    "    axes[1].plot(solver.train_acc_history, label=f\"{update_rule}\")\n",
    "    axes[2].plot(solver.val_acc_history, label=f\"{update_rule}\")\n",
    "    \n",
    "for ax in axes:\n",
    "    ax.legend(loc='best', ncol=4)\n",
    "    ax.grid(linestyle='--', linewidth=0.5)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "pdf-inline"
    ]
   },
   "source": [
    "## Inline Question 2:\n",
    "\n",
    "AdaGrad, like Adam, is a per-parameter optimization method that uses the following update rule:\n",
    "\n",
    "```\n",
    "cache += dw**2\n",
    "w += - learning_rate * dw / (np.sqrt(cache) + eps)\n",
    "```\n",
    "\n",
    "John notices that when he was training a network with AdaGrad that the updates became very small, and that his network was learning slowly. Using your knowledge of the AdaGrad update rule, why do you think the updates would become very small? Would Adam have the same issue?\n",
    "\n",
    "\n",
    "## Answer: \n",
    "[FILL THIS IN]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Train a Good Model!\n",
    "Train the best fully connected model that you can on CIFAR-10, storing your best model in the `best_model` variable. We require you to get at least 50% accuracy on the validation set using a fully connected network.\n",
    "\n",
    "If you are careful it should be possible to get accuracies above 55%, but we don't require it for this part and won't assign extra credit for doing so. Later in the assignment we will ask you to train the best convolutional network that you can on CIFAR-10, and we would prefer that you spend your effort working on convolutional networks rather than fully connected networks.\n",
    "\n",
    "**Note:** You might find it useful to complete the `BatchNormalization.ipynb` and `Dropout.ipynb` notebooks before completing this part, since those techniques can help you train powerful models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "best_model = None\n",
    "\n",
    "################################################################################\n",
    "# TODO: Train the best FullyConnectedNet that you can on CIFAR-10. You might   #\n",
    "# find batch/layer normalization and dropout useful. Store your best model in  #\n",
    "# the best_model variable.                                                     #\n",
    "################################################################################\n",
    "# *****START OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)*****\n",
    "\n",
    "pass\n",
    "\n",
    "# *****END OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)*****\n",
    "################################################################################\n",
    "#                              END OF YOUR CODE                                #\n",
    "################################################################################"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Test Your Model!\n",
    "Run your best model on the validation and test sets. You should achieve at least 50% accuracy on the validation set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_test_pred = np.argmax(best_model.loss(data['X_test']), axis=1)\n",
    "y_val_pred = np.argmax(best_model.loss(data['X_val']), axis=1)\n",
    "print('Validation set accuracy: ', (y_val_pred == data['y_val']).mean())\n",
    "print('Test set accuracy: ', (y_test_pred == data['y_test']).mean())"
   ]
  }
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