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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Your first neural network\n",
"\n",
"In this project, you'll build your first neural network and use it to predict daily bike rental ridership. We've provided some of the code, but left the implementation of the neural network up to you (for the most part). After you've submitted this project, feel free to explore the data and the model more.\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
"%load_ext autoreload\n",
"%autoreload 2\n",
"%config InlineBackend.figure_format = 'retina'\n",
"\n",
"import numpy as np\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Load and prepare the data\n",
"\n",
"A critical step in working with neural networks is preparing the data correctly. Variables on different scales make it difficult for the network to efficiently learn the correct weights. Below, we've written the code to load and prepare the data. You'll learn more about this soon!"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"data_path = 'Bike-Sharing-Dataset/hour.csv'\n",
"\n",
"rides = pd.read_csv(data_path)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>instant</th>\n",
" <th>dteday</th>\n",
" <th>season</th>\n",
" <th>yr</th>\n",
" <th>mnth</th>\n",
" <th>hr</th>\n",
" <th>holiday</th>\n",
" <th>weekday</th>\n",
" <th>workingday</th>\n",
" <th>weathersit</th>\n",
" <th>temp</th>\n",
" <th>atemp</th>\n",
" <th>hum</th>\n",
" <th>windspeed</th>\n",
" <th>casual</th>\n",
" <th>registered</th>\n",
" <th>cnt</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>2011-01-01</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0.24</td>\n",
" <td>0.2879</td>\n",
" <td>0.81</td>\n",
" <td>0.0</td>\n",
" <td>3</td>\n",
" <td>13</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>2011-01-01</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0.22</td>\n",
" <td>0.2727</td>\n",
" <td>0.80</td>\n",
" <td>0.0</td>\n",
" <td>8</td>\n",
" <td>32</td>\n",
" <td>40</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>2011-01-01</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0.22</td>\n",
" <td>0.2727</td>\n",
" <td>0.80</td>\n",
" <td>0.0</td>\n",
" <td>5</td>\n",
" <td>27</td>\n",
" <td>32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>2011-01-01</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0.24</td>\n",
" <td>0.2879</td>\n",
" <td>0.75</td>\n",
" <td>0.0</td>\n",
" <td>3</td>\n",
" <td>10</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5</td>\n",
" <td>2011-01-01</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>0.24</td>\n",
" <td>0.2879</td>\n",
" <td>0.75</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" instant dteday season yr mnth hr holiday weekday workingday \\\n",
"0 1 2011-01-01 1 0 1 0 0 6 0 \n",
"1 2 2011-01-01 1 0 1 1 0 6 0 \n",
"2 3 2011-01-01 1 0 1 2 0 6 0 \n",
"3 4 2011-01-01 1 0 1 3 0 6 0 \n",
"4 5 2011-01-01 1 0 1 4 0 6 0 \n",
"\n",
" weathersit temp atemp hum windspeed casual registered cnt \n",
"0 1 0.24 0.2879 0.81 0.0 3 13 16 \n",
"1 1 0.22 0.2727 0.80 0.0 8 32 40 \n",
"2 1 0.22 0.2727 0.80 0.0 5 27 32 \n",
"3 1 0.24 0.2879 0.75 0.0 3 10 13 \n",
"4 1 0.24 0.2879 0.75 0.0 0 1 1 "
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"rides.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Checking out the data\n",
"\n",
"This dataset has the number of riders for each hour of each day from January 1 2011 to December 31 2012. The number of riders is split between casual and registered, summed up in the `cnt` column. You can see the first few rows of the data above.\n",
"\n",
"Below is a plot showing the number of bike riders over the first 10 days or so in the data set. (Some days don't have exactly 24 entries in the data set, so it's not exactly 10 days.) You can see the hourly rentals here. This data is pretty complicated! The weekends have lower over all ridership and there are spikes when people are biking to and from work during the week. Looking at the data above, we also have information about temperature, humidity, and windspeed, all of these likely affecting the number of riders. You'll be trying to capture all this with your model."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot:xlabel='dteday'>"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"image/png": {
"height": 261,
"width": 375
},
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"rides[:24*10].plot(x='dteday', y='cnt')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Dummy variables\n",
"Here we have some categorical variables like season, weather, month. To include these in our model, we'll need to make binary dummy variables. This is simple to do with Pandas thanks to `get_dummies()`."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>yr</th>\n",
" <th>holiday</th>\n",
" <th>temp</th>\n",
" <th>hum</th>\n",
" <th>windspeed</th>\n",
" <th>casual</th>\n",
" <th>registered</th>\n",
" <th>cnt</th>\n",
" <th>season_1</th>\n",
" <th>season_2</th>\n",
" <th>...</th>\n",
" <th>hr_21</th>\n",
" <th>hr_22</th>\n",
" <th>hr_23</th>\n",
" <th>weekday_0</th>\n",
" <th>weekday_1</th>\n",
" <th>weekday_2</th>\n",
" <th>weekday_3</th>\n",
" <th>weekday_4</th>\n",
" <th>weekday_5</th>\n",
" <th>weekday_6</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.24</td>\n",
" <td>0.81</td>\n",
" <td>0.0</td>\n",
" <td>3</td>\n",
" <td>13</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.22</td>\n",
" <td>0.80</td>\n",
" <td>0.0</td>\n",
" <td>8</td>\n",
" <td>32</td>\n",
" <td>40</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.22</td>\n",
" <td>0.80</td>\n",
" <td>0.0</td>\n",
" <td>5</td>\n",
" <td>27</td>\n",
" <td>32</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.24</td>\n",
" <td>0.75</td>\n",
" <td>0.0</td>\n",
" <td>3</td>\n",
" <td>10</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0.24</td>\n",
" <td>0.75</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 59 columns</p>\n",
"</div>"
],
"text/plain": [
" yr holiday temp hum windspeed casual registered cnt season_1 \\\n",
"0 0 0 0.24 0.81 0.0 3 13 16 1 \n",
"1 0 0 0.22 0.80 0.0 8 32 40 1 \n",
"2 0 0 0.22 0.80 0.0 5 27 32 1 \n",
"3 0 0 0.24 0.75 0.0 3 10 13 1 \n",
"4 0 0 0.24 0.75 0.0 0 1 1 1 \n",
"\n",
" season_2 ... hr_21 hr_22 hr_23 weekday_0 weekday_1 weekday_2 \\\n",
"0 0 ... 0 0 0 0 0 0 \n",
"1 0 ... 0 0 0 0 0 0 \n",
"2 0 ... 0 0 0 0 0 0 \n",
"3 0 ... 0 0 0 0 0 0 \n",
"4 0 ... 0 0 0 0 0 0 \n",
"\n",
" weekday_3 weekday_4 weekday_5 weekday_6 \n",
"0 0 0 0 1 \n",
"1 0 0 0 1 \n",
"2 0 0 0 1 \n",
"3 0 0 0 1 \n",
"4 0 0 0 1 \n",
"\n",
"[5 rows x 59 columns]"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dummy_fields = ['season', 'weathersit', 'mnth', 'hr', 'weekday']\n",
"for each in dummy_fields:\n",
" dummies = pd.get_dummies(rides[each], prefix=each, drop_first=False)\n",
" rides = pd.concat([rides, dummies], axis=1)\n",
"\n",
"fields_to_drop = ['instant', 'dteday', 'season', 'weathersit', \n",
" 'weekday', 'atemp', 'mnth', 'workingday', 'hr']\n",
"data = rides.drop(fields_to_drop, axis=1)\n",
"data.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Scaling target variables\n",
"To make training the network easier, we'll standardize each of the continuous variables. That is, we'll shift and scale the variables such that they have zero mean and a standard deviation of 1.\n",
"\n",
"The scaling factors are saved so we can go backwards when we use the network for predictions."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"quant_features = ['casual', 'registered', 'cnt', 'temp', 'hum', 'windspeed']\n",
"# Store scalings in a dictionary so we can convert back later\n",
"scaled_features = {}\n",
"for each in quant_features:\n",
" mean, std = data[each].mean(), data[each].std()\n",
" scaled_features[each] = [mean, std]\n",
" data.loc[:, each] = (data[each] - mean)/std"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Splitting the data into training, testing, and validation sets\n",
"\n",
"We'll save the data for the last approximately 21 days to use as a test set after we've trained the network. We'll use this set to make predictions and compare them with the actual number of riders."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"# Save data for approximately the last 21 days \n",
"test_data = data[-21*24:]\n",
"\n",
"# Now remove the test data from the data set \n",
"data = data[:-21*24]\n",
"\n",
"# Separate the data into features and targets\n",
"target_fields = ['cnt', 'casual', 'registered']\n",
"features, targets = data.drop(target_fields, axis=1), data[target_fields]\n",
"test_features, test_targets = test_data.drop(target_fields, axis=1), test_data[target_fields]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We'll split the data into two sets, one for training and one for validating as the network is being trained. Since this is time series data, we'll train on historical data, then try to predict on future data (the validation set)."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"# Hold out the last 60 days or so of the remaining data as a validation set\n",
"train_features, train_targets = features[:-60*24], targets[:-60*24]\n",
"val_features, val_targets = features[-60*24:], targets[-60*24:]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Time to build the network\n",
"\n",
"Below you'll build your network. We've built out the structure. You'll implement both the forward pass and backwards pass through the network. You'll also set the hyperparameters: the learning rate, the number of hidden units, and the number of training passes.\n",
"\n",
"<img src=\"assets/neural_network.png\" width=300px>\n",
"\n",
"The network has two layers, a hidden layer and an output layer. The hidden layer will use the sigmoid function for activations. The output layer has only one node and is used for the regression, the output of the node is the same as the input of the node. That is, the activation function is $f(x)=x$. A function that takes the input signal and generates an output signal, but takes into account the threshold, is called an activation function. We work through each layer of our network calculating the outputs for each neuron. All of the outputs from one layer become inputs to the neurons on the next layer. This process is called *forward propagation*.\n",
"\n",
"We use the weights to propagate signals forward from the input to the output layers in a neural network. We use the weights to also propagate error backwards from the output back into the network to update our weights. This is called *backpropagation*.\n",
"\n",
"> **Hint:** You'll need the derivative of the output activation function ($f(x) = x$) for the backpropagation implementation. If you aren't familiar with calculus, this function is equivalent to the equation $y = x$. What is the slope of that equation? That is the derivative of $f(x)$.\n",
"\n",
"Below, you have these tasks:\n",
"1. Implement the sigmoid function to use as the activation function. Set `self.activation_function` in `__init__` to your sigmoid function.\n",
"2. Implement the forward pass in the `train` method.\n",
"3. Implement the backpropagation algorithm in the `train` method, including calculating the output error.\n",
"4. Implement the forward pass in the `run` method.\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"#############\n",
"# In the my_answers.py file, fill out the TODO sections as specified\n",
"#############\n",
"\n",
"from my_answers import NeuralNetwork"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"def MSE(y, Y):\n",
" return np.mean((y-Y)**2)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Unit tests\n",
"\n",
"Run these unit tests to check the correctness of your network implementation. This will help you be sure your network was implemented correctly befor you starting trying to train it. These tests must all be successful to pass the project."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
".....\n",
"----------------------------------------------------------------------\n",
"Ran 5 tests in 0.004s\n",
"\n",
"OK\n"
]
},
{
"data": {
"text/plain": [
"<unittest.runner.TextTestResult run=5 errors=0 failures=0>"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import unittest\n",
"\n",
"inputs = np.array([[0.5, -0.2, 0.1]])\n",
"targets = np.array([[0.4]])\n",
"test_w_i_h = np.array([[0.1, -0.2],\n",
" [0.4, 0.5],\n",
" [-0.3, 0.2]])\n",
"test_w_h_o = np.array([[0.3],\n",
" [-0.1]])\n",
"\n",
"class TestMethods(unittest.TestCase):\n",
" \n",
" ##########\n",
" # Unit tests for data loading\n",
" ##########\n",
" \n",
" def test_data_path(self):\n",
" # Test that file path to dataset has been unaltered\n",
" self.assertTrue(data_path.lower() == 'bike-sharing-dataset/hour.csv')\n",
" \n",
" def test_data_loaded(self):\n",
" # Test that data frame loaded\n",
" self.assertTrue(isinstance(rides, pd.DataFrame))\n",
" \n",
" ##########\n",
" # Unit tests for network functionality\n",
" ##########\n",
"\n",
" def test_activation(self):\n",
" network = NeuralNetwork(3, 2, 1, 0.5)\n",
" # Test that the activation function is a sigmoid\n",
" self.assertTrue(np.all(network.activation_function(0.5) == 1/(1+np.exp(-0.5))))\n",
"\n",
" def test_train(self):\n",
" # Test that weights are updated correctly on training\n",
" network = NeuralNetwork(3, 2, 1, 0.5)\n",
" network.weights_input_to_hidden = test_w_i_h.copy()\n",
" network.weights_hidden_to_output = test_w_h_o.copy()\n",
" \n",
" network.train(inputs, targets)\n",
" self.assertTrue(np.allclose(network.weights_hidden_to_output, \n",
" np.array([[ 0.37275328], \n",
" [-0.03172939]])))\n",
" self.assertTrue(np.allclose(network.weights_input_to_hidden,\n",
" np.array([[ 0.10562014, -0.20185996], \n",
" [0.39775194, 0.50074398], \n",
" [-0.29887597, 0.19962801]])))\n",
"\n",
" def test_run(self):\n",
" # Test correctness of run method\n",
" network = NeuralNetwork(3, 2, 1, 0.5)\n",
" network.weights_input_to_hidden = test_w_i_h.copy()\n",
" network.weights_hidden_to_output = test_w_h_o.copy()\n",
"\n",
" self.assertTrue(np.allclose(network.run(inputs), 0.09998924))\n",
"\n",
"suite = unittest.TestLoader().loadTestsFromModule(TestMethods())\n",
"unittest.TextTestRunner().run(suite)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Training the network\n",
"\n",
"Here you'll set the hyperparameters for the network. The strategy here is to find hyperparameters such that the error on the training set is low, but you're not overfitting to the data. If you train the network too long or have too many hidden nodes, it can become overly specific to the training set and will fail to generalize to the validation set. That is, the loss on the validation set will start increasing as the training set loss drops.\n",
"\n",
"You'll also be using a method know as Stochastic Gradient Descent (SGD) to train the network. The idea is that for each training pass, you grab a random sample of the data instead of using the whole data set. You use many more training passes than with normal gradient descent, but each pass is much faster. This ends up training the network more efficiently. You'll learn more about SGD later.\n",
"\n",
"### Choose the number of iterations\n",
"This is the number of batches of samples from the training data we'll use to train the network. The more iterations you use, the better the model will fit the data. However, this process can have sharply diminishing returns and can waste computational resources if you use too many iterations. You want to find a number here where the network has a low training loss, and the validation loss is at a minimum. The ideal number of iterations would be a level that stops shortly after the validation loss is no longer decreasing.\n",
"\n",
"### Choose the learning rate\n",
"This scales the size of weight updates. If this is too big, the weights tend to explode and the network fails to fit the data. Normally a good choice to start at is 0.1; however, if you effectively divide the learning rate by n_records, try starting out with a learning rate of 1. In either case, if the network has problems fitting the data, try reducing the learning rate. Note that the lower the learning rate, the smaller the steps are in the weight updates and the longer it takes for the neural network to converge.\n",
"\n",
"### Choose the number of hidden nodes\n",
"In a model where all the weights are optimized, the more hidden nodes you have, the more accurate the predictions of the model will be. (A fully optimized model could have weights of zero, after all.) However, the more hidden nodes you have, the harder it will be to optimize the weights of the model, and the more likely it will be that suboptimal weights will lead to overfitting. With overfitting, the model will memorize the training data instead of learning the true pattern, and won't generalize well to unseen data. \n",
"\n",
"Try a few different numbers and see how it affects the performance. You can look at the losses dictionary for a metric of the network performance. If the number of hidden units is too low, then the model won't have enough space to learn and if it is too high there are too many options for the direction that the learning can take. The trick here is to find the right balance in number of hidden units you choose. You'll generally find that the best number of hidden nodes to use ends up being between the number of input and output nodes."
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Progress: 100.0% ... Training loss: 0.082 ... Validation loss: 0.182"
]
}
],
"source": [
"import sys\n",
"\n",
"####################\n",
"### Set the hyperparameters in you myanswers.py file ###\n",
"####################\n",
"\n",
"from my_answers import iterations, learning_rate, hidden_nodes, output_nodes\n",
"\n",
"\n",
"N_i = train_features.shape[1]\n",
"network = NeuralNetwork(N_i, hidden_nodes, output_nodes, learning_rate)\n",
"\n",
"losses = {'train':[], 'validation':[]}\n",
"for ii in range(iterations):\n",
" # Go through a random batch of 128 records from the training data set\n",
" batch = np.random.choice(train_features.index, size=128)\n",
" #X, y = train_features.ix[batch].values, train_targets.ix[batch]['cnt']\n",
" X, y = train_features.loc[batch].values, train_targets.loc[batch]['cnt']\n",
" \n",
" network.train(X, y)\n",
" \n",
" # Printing out the training progress\n",
" train_loss = MSE(network.run(train_features).T, train_targets['cnt'].values)\n",
" val_loss = MSE(network.run(val_features).T, val_targets['cnt'].values)\n",
" sys.stdout.write(\"\\rProgress: {:2.1f}\".format(100 * ii/float(iterations)) \\\n",
" + \"% ... Training loss: \" + str(train_loss)[:5] \\\n",
" + \" ... Validation loss: \" + str(val_loss)[:5])\n",
" sys.stdout.flush()\n",
" \n",
" losses['train'].append(train_loss)\n",
" losses['validation'].append(val_loss)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"image/png": {
"height": 248,
"width": 368
},
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(losses['train'], label='Training loss')\n",
"plt.plot(losses['validation'], label='Validation loss')\n",
"plt.legend()\n",
"_ = plt.ylim()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Check out your predictions\n",
"\n",
"Here, use the test data to view how well your network is modeling the data. If something is completely wrong here, make sure each step in your network is implemented correctly."
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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88zWRGcCkwKX+DMMwDMMwDMMwy4LKCX8hxASAv0AU6veVlM0u63w90fC94wBMAbhGStnM+JgXadswg1gu4X477gau+jSwPdERwjAMwzAMwzAMs1dQOeEP4E8BrAVwoSHUr8t5ALYDOEkIcVT3zs6iQXcmxRe0x3yx8/UUIcRa8piNAN4GoAng7MJ7v7ewXMb5/efrgf85FTj3tUBF8ywYhmEYhmEYhmHKpIqp/m/pfP2PtA2klLuFEG9GtABwhRDiXAA7ALwU0ai/8wB8R3vMNUKITwF4D4CbhBDnAagD+DMA6wC8Q0q52fLvMr4sl1L/LTdFX7ffDoQ+4NaWdn8YhmEYhmEYhmFGTKWEvxDi8QCORXqoXw8p5flCiOcCOAXAqwBMALgTkbD/jDSMK5BSvlcIcROAtyNaYAgB3ADg41LKH9n8XcYe+vJWVfjrH4Gq7ifDMAzDMAzDMEyJVEr4SylvBSBybH81gD/O+TO+BuBrOXeN0VkOpf76tIGq7icABG1AOIDjLvWeMAzDMAzDMAwzZlSxx59ZDiyHcX76QIiq7ufWW4BPPQH4zJHAni1LvTcMw9hm+2+Byz4EPPSrpd4ThmEYhmH2Ulj4M8OxHHr8l4vj/+v/BOYeBmZ+B9zyg6XeG4ZhbPO9NwFXfhw49/9WdwGSYRiGYZixhoU/MxzLodRfd/yrup/tBXJ7fun2g2GYcth2W/R11318jDMMwzAMsySw8GeGg4poXWBXBV3oV1X4L4fqCYZhhoce4+z4MwzDMAyzBLDwZ4ZjOYjVRKl/YtBDNVCqJ1gUMMzYoSyUVvR8yTAMwzDMWMPCnxkOZZxfVQW17vhXVFSHfny7qq8lwzDDsxxaoxiGYRiGGWtY+DPDsRwuZJdLuF+4DCYkMAwzHOEyaTliGIZhGGasYeHPDMdy6FldLuF+y2ERhWGY4VguY0UZhmGYUhFCKP8ajQb23XdfPPWpT8Wb3vQmXHTRRQgCO38jzjnnHAghcM4551h5PmY88JZ6B5hlynLoWV2W4X4sChgmM1ICP/8CMLsVOPZvgMm1S71HSZZL5RHDMAwzEk499VQAQBAEmJmZwc0334yvf/3r+MpXvoKjjjoK3/zmN/HYxz52ifeSGUdY+DPDsRxc6uVywb0cXkuGqSL3XAlc/L7odmMFcNzfLe3+mEhUHvHiHsMwzN7Maaedlrhv69ateMc73oHvfve7eMELXoDrr78e++233+h3jhlruNSfGY5lMc5vmZTYLoe2CYapIjvuJrfvWbr96MdyqTxiGIZhloz9998f5557Lo4//njcd999+MhHPqJ8f9OmTXjXu96FpzzlKVi3bh0mJiZw+OGH473vfS927typbHv88cfj5JNPBgCcfPLJSnvB5s2bAQAPPvgg/uVf/gXPfvazsWHDBtTrdTzqUY/Ca1/7Wtx6660j+Z2Z0cOOPzMc4TIo9V8uoVrs+DPMcCyHY0dfzOPFPYZhGMaA4zh4//vfjyuuuALf/va3ceaZZ0IIAQD40pe+hO9///t47nOfixe84AUIggA33HADPvWpT+Giiy7CL37xC6xcuRIA8IY3vAFr1qzBBRdcgJe97GU48sgjez9jzZo1AIArr7wSZ5xxBp73vOfhVa96FVasWIHf/va3OO+88/CDH/wAV199NZ7ylKeM+iVgSoaFPzMciuNf0RF0Caetovu5HBZRGKaKLIeJGMvlPMQwDMMsOcceeyw8z8PDDz+MzZs347DDDgMAvO9978PnPvc5uK6rbP+Vr3wFb3rTm/D5z38e//AP/wAgEv4AcMEFF+DlL3957/+UE044AVu3bu0tFnT51a9+hWc/+9n4x3/8R1x00UX2f0FmSWHhzwzHcnDaONWfYcYbuQyCMZdL1gjDMMxScNrqpd6D7Jy2q/Qf0Wg0sM8++2Dr1q3Ytm1bT/gfeuihxu3f+MY34j3veQ8uvvjinvDPQlp+wFOe8hSccMIJuOSSS9But1Gr1fL/Ekxl4R5/ZjiWQ1964oJ7GexnVV9Lhqki4TJYNONwP4ZhGCYHslMZ1i3zB4B2u42zzjoLxx57LNatWwfXdSGEgOM42L17Nx544IHcP+fHP/4xXvKSl+CAAw5ArVbr5QD88Ic/RLPZxPbt2639Tkw1YMefGY5lMc5vmTht7PgzzHDIZbBoxo4/wzAMk5HFxUXs2LEDALDvvvv27v+zP/szfP/738ejH/1ovOxlL8OGDRvQaDQAAJ/+9KfRbDZz/ZzPfOYzeNe73oW1a9fihS98IQ455BBMTU1BCIHzzz8fv/rVr3I/J1N9WPgzw7EcxOpyueAOl0G5MsNUkYILkFt3L+K8TffjmY/eB087dK3FHSPo+5VzgUJKiavvfAS7Ftr4oyfuD8/lQj2GYcaIEZTPLyeuuuoq+L6P/fffHxs3bgQAXH/99fj+97+PF7zgBbjwwguV8vswDPGxj30s18/wfR+nnnoqNmzYgBtuuAEHHHCA8v2f/exnhX8Pppqw8GeGY1mM89NCtKoq/JdD9QTDVJGCpf4fOP83uOSWrXAdgRve/0Ksniqhl7Fg5dEv75vBn3/lFwCAM175ZJz09ENs7RnDMAxTIcIwxIc//GEAwGtf+9re/XfeeScA4KUvfWmi5/7aa6/FwsJC4rm6IYBBkLxG3759O2ZmZvDKV74yIfpnZ2dxww03FPtFmMrC1gEzHMshiX65lPorPf4V3UeGqSKyWKr/JbdsBQAEocTltz9sa69UCmaNfOTCeJ7yP/7Xr23sEcMwDFMxHn74YZx00km44oorcMghh+Cf/umfet/rOv9XXHFF4jFve9vbjM+3zz77AAB+97vfJb633377YWpqCps2bcLs7Gzv/na7jXe9613c2z/GsOPPDIdS6l/R8VSJ+dkVFdUF2yb+8/r78PWf3Ys3HrsRr/iDgyzuGMNUHIttMo/MtQruTAoFx/l5Dq/PMwzDjBOnnXYagMjhn5mZwc0334yrrroKrVYLT3/60/HNb34T69ev721/9NFH49nPfjb+67/+C8cccwyOPfZYbN26FRdddBEe97jH4VGPelTiZzzrWc/C1NQUPv3pT2PHjh3Yf//9AQDveMc7sHr1arzzne/EGWecgSc/+cl42ctehlarhcsvvxw7duzA8573PFx++eUjeS2Y0cLCnxmO5VCevhwd/5ziJQwl/v68mwAA7/7Or/DyIw9UUmAZZqyxmDWysyzhn1iAzHeMr57kUUoMwzDjxOmnnw4AqNfrWLlyJQ499FC87nWvw6te9Sr84R/+IRxtwdd1XfzgBz/A+9//flx44YX4zGc+gwMPPBBvetOb8P73vx9PeMITEj9j7dq1+N73vofTTz8dZ599Nubm5gAAf/7nf47Vq1fjgx/8IPbdd198+ctfxr//+79j9erVeOELX4gPfehDOPXUU8t/EZglgYU/MxzLYQTdcgn3K5BM3taqGHYv+OX0KQPADV8HbrkAOPbdwMZnl/MzGCYPFs9D5Tn+xc5DLPwZhmHGA1mgQnbdunX4/Oc/b/ze5s2bjfefeOKJOPHEE43f8zwP73nPe/Ce97wn8b1zzjkH55xzzrC7ylQYFv7McCwLx18vsa3ofhYIKNO7F7bPNcsR/ou7gB+/FwiawPwjwFu4BIypAMvB8U+ch3I6/mUt5DEMwzAMs1fBzYPMcCyHcX7LpdS/wISEQFs9fmS2JPGysDMS/QCw56FyfgbD5KVgqj9lx6hK/XPu53RdXZ9v+RU9jzEMwzAMU2lY+DPDEQ4vVkeGbodXdj+HFy9BqAv/po09SrIcWjuYvY+Cqf6UR+ZKOnb0807O/ZRQj/GZ+ZIWKBiGYRiGGWtY+DPDsSxK/ZeL4z/8OL9QE/7bR1GuXNUFFGbvw2Kqf3mOf7GWI/0Y38HCn2EYhmGYIWDhzwxHQlRXcKTfcgn3K+L4J0r9y3It7TmrDGMNiwuQO+fbBXcmhYILkPoxXtoCBcMwDMMwYw0Lf2Y4lkNw3nLYR0DLS8g/zo9SWo+/xV5qhrFGgYkYAFD31D+Bc02/6B4lKbgAGWib75wraYGCYRiGYZixhoU/MxwFZ1OPhERvbUUFazi8a5lw/EfRpzzMe73rAeAbrwLOeyPQXrC3X8zeTcFSf33hbNueEo4f/ZjOefyEuuPPpf4MwzAMY5UioxaXEyz8meFYDv3zy6XUv4Co1sP9tpfl+Bft8d90NnDn/wC/+R5w24/t7Rezd6NUy+T/o+3rwr+MVpmipf7aPpY2dpBhGKYEhBAAgLCq5gvDIBb+3c/ruMLCnxkO/SK7iqJ6uZT6Fyij1/+OVjbVf/Zh822GKUI4fPaE7vYDJTn+iQXIYot73OPPMMxyotFoAADm5uaWeE8YJp3u57P7eR1XWPgzw1HwYhYYQVnNcnT8C5f6V9TxVxYOuEeZsUSBfAz92AFGVOqfd3FP28+dXOrPMMwyYuXKlQCALVu2YM+ePQjDcK8pq2aqjZQSYRhiz5492LJlC4D48zqueEu9A8wypeDF7Heu+x0+cuFteOlTHoUPvvxJFneszz5VVfgXSfUP9RnfbbSDEDXX8pqevo9SAnnKoUISmhaw8GcsYfHYAUbl+BfbT3b8GYZZTqxbtw5zc3OYn5/H/fffv9S7wzCpTE1NYd26dUu9G6XCjj8zHAX7Vv/he7/GroU2vv7ze3H7lj0Wd4zuU/GqhJFQoIxedwOBknqAiy6iUJefhT9jiwL5GKZjpxzHv1jIqL6fM2WNHWQYhikBx3Fw8MEHY99998XExMTY91AzywshBCYmJrDvvvvi4IMPhuOMtzSunOMvhHgOgL8BcAyAdQB2APg1gE9LKS/Utj0GwPsBPBPABIA7AXwVwGelNKs8IcTrAbwNwBMABABuBPAJKeWPyvh9xpaEizV82dZd22bxuA0llNbsDaX+Btdy+2wL+62aKLpXKgnxEgCOm/3x1PHnUn/GFpYd/+2lhPsVWzTzA3b8GYZZ3jiOg/Xr12P9+vVLvSsMs1dTqWUNIcT7AVwJ4DgAPwHwSQA/BLAWwPHati8j234fwOcA1AGcCeDclOf/BIBzABwA4EsAvgHgyQB+KIR4u+3fZ6wpOKKKUtqFbMLxr2hPWYGRZCbxUspIv6KZDvTx7PgztlCyJyyU+pch/IuG+3GPP8MwDMMwFqiM4y+E+FMAHwTwPwBeKaXco32/Rm6vQiTcAwDHSymv79z/AQCXAXi1EOIkKeW55DHHAHgvgLsAHC2l3Nm5/+MANgH4hBDiR1LKzeX9lmOClADspfqXNp5KL6kdQ8ffVK78SBkj/UyOfx4CLvVnSoAeLwVHYQIjOnZyT+5Q93O+FWCxHWCilqPihmEYhmGYvZ5KOP5CCAfARwHMA3itLvoBQEpJ1cKrAewL4Nyu6O9ss4io9B8A/kp7ird2vn64K/o7j9mMqFqgAeDkYr/JXoLpwrWAqN5RloO1TML9JBEs0oJ4GU25cl7Hn0v9mRIoUupvWDRrBSWcI/QFyLzHuKFQiV1/hmEYhmHyUgnhj6if/zAAFwLYKYR4sRDiH4QQ7xJCPMuw/Qmdrz8xfO9KRAsIxwgh6DDGfo+5SNuG6YfpwjWnEFyFWfwf93IcKraMrtS/QDtCmQiyn/PNfKLY6PiX8XoWFC+c6s+UQoFxfqaMPb8M4W/Z8Qe4z59hGIZhmPxUpdT/6M7XrQBuQNR330MIcSWAV0spt3Xuelzn6x36E0kpfSHEPQCeCODRAG4VQkwDOBDArJTyIcPP/23n62ML/RZ7C6YL7JwXsx+tfQkvcq/DFrkW75v9uqUd07AQ7vfwnkX4gcSj1kxa2ikNTX1smZnDY3I83KRTto8imTx3qj8Lf6YECkzEMDn+epCeFYr2+BuE/865Eo6hMAR+ezHgeMDvvSDfuE5E+3nzg7vw+ANW2R8nyjAMwzBMYary13m/zte3ApgE8AIAKwE8CcDFiAL8vku2X935uivl+br3rxly+1SEEJtM/wAcMeixY4OFUv8XudcBADaInThg1y8t7JSBgmL1t1v34NgzLscxZ1yGa+7abnHH6D6p+yj07IQBmERBKW5g0TBHLvVnyqBIPobh2GnnHLWXiUSbTM5j3LD9bM7KoCzM/PJ84NsnAd98NfbcfEnux//1NzfhpWddjb/82vWDN2YYhmEYZuRURfh3U4oEImf/UinlrJTyZgCvAHA/gOemlP2b6FoVee2bisa+Vwxjqf/wF8zBQiLSwQ4FHf8PX3hrr+f3tV/6ha29UtH20UXxZPJy+pSLpvpTx5/LlBlLUKFuIdW/FMe/YMuRcYGihP38+ZUX925f89OL+2xp5uKbtwIArrxjG3Yv8uIewzAMw1SNqgj/btje3VLKX9FvSCkXELn+APD0zteuQ78aZlZp2w3aflBFAN2fp5n+Abht0GPHBtMFdgGnTDZLEv66U5ZTrJaS8K2TcPyLB5S1R9GnXCjV30/fjqkWVR2B2UUOX+rvm4R/KCFt/84FFyBHdYzfuz0+D9/58MA/hQr6a7Z7gYU/wzAMw1SNqgj/2ztfZ1K+310Y6DZad7dP9OQLITxEQYE+gLsBQEo5B+ABACuEEAcYnv/wztdEZgBjoGCpv+5g1cMFzDVLEIOJUv98F/TrpusWdyaFgo6/yQ2sYp+y2ovNomBZcPP5wMd/D/j+WwduumQUSPU3BWMC5gWBQhSciDGqygSPnHtyn4e03ZmZ52OcYRiGYapGVYT/lYiE+uFCCJPaelLn6+bO18s6X080bHscgCkA10gpacpZv8e8SNuG6UfBUn/dwZrGIraVEUhX0GnbZxTCXxMBjoVS/7Zt4QIkF00Kpfpzqf+y4GdnAfPbgV99G3jkrqXeGzMFUv1Nxw5QgqgueB4yLVCUkUXgFBD+vrY/LPwZhmEYpnpUQvhLKbcD+A6ikvt/pt8TQrwQwB8hKsPvjuI7D8B2ACcJIY4i204A+FDnv1/QfswXO19PEUKsJY/ZCOBtAJoAzrbw64w/Rsc/+0W3fsE9LRZKmj1f7IJbd/ytlwADiRYJJ2+4nzGZvIKl/iGX+i87aAtOWe04RSmS6p8i/K2L6oLHjnFxz7d/jHuI98sVeSuP1P/PLPDiHsMwDMNUjaqM8wOA9wB4BiJhfhyAawEciijcLwDwZinlDABIKXcLId6MaAHgCiHEuQB2AHgpolF/5yFaSOghpbxGCPGpzs+5SQhxHoA6gD8DsA7AO6SUm8v+JceCguP8dAdrGs1KOv4TNVf5/+4FH6unakX3SqWg4798Sv051X/ZQd+zvO/3qKDHtK1Sf9vHT6LUv5ioBkpoR4Dq8rsFFyB3suPPMAzDMJWjEo4/AEgpH0Yk/M8EcDCAdwI4AcCPATxHSvldbfvzATwXUZvAqwC8A0AbkbA/SRrsWSnlewG8AcAWAG8B8DoANwN4iZTyrDJ+r7GkYI9/wvFHWY5/sRF0+sX1ttnFonuUJNSFf3HHfyQjyXI7/mR7LvVfHihuegmfKQsEAf0cylw5Huml/pZ/11LC/coV/tT9z4L+Ws6UMVKUYRiGYZhCVMnxh5RyByLh/p6M218N4I9z/oyvAfha/r1jephEXw4hGGoX1ivEAu4ow/HXLrClDHtzHrOgO4IP727i9/ZbaWHH6E7Z7/EfyUiyvA4wp/ovPwr0z4+K7XvmsT+9IwwAN9uftfRSf9uOv/raNdttNHI83FjqX0I7jydoqX/OBUhd+HOqP8MwDMNUjso4/swywljqn/1C0ffVi8JVmMe2EkbnyVAVmH5QzMXaVkZVQsLxL16uXEqPv76wUyTcj0v9lwfh8GX0o6LV1haRClQedbHv+KvPF/j5Fr5GdYwXCffTX8ud8+z4MwzDMEzVYOHP5Mck8nNdcKsXvqvEfCk9/rJoiW2YdPytozv+ufcxeV85qf7F+pQ51X8ZoizWVNPxdwpUophK6AH7ZfT6AqTI284zoskdSrhfwQVITvVnGIZhmOrBwp/JT8FxftJXH78S86X0+Ieawy8r6fgXS/U3h/tVr8efVnnsnlsoZ0ICY5dlUOqfqJDJ03KUcpjoo+mKoi9AyoILkED1Hf8ZdvwZhmEYpnKw8GfyU3ScX6C6QavFHHaV0BOqX2CHeed8J3r8Swj3K9rjbywDrnaq//ziIv7p+79m8V91CozKGxWJ4yVP5VHn8zcJ9bi2ffyE2kJC0QVIoJxwP48K/5zj/JLCnx1/hmEYhqkaLPyZ/BQc5ye1cLdVmEPbty8sQj1ELqeTp7vpo+jxt1MGXIbjX6zH35Hxe1GDj29fex+2lLGQwthDcfyr2eOfaI3JsSAVhhKvcy/GTY034yu1jwOdY892cF6gnYdkwQVIoJxwP7dAqT/3+DMMwzBM9WHhz+Sn6Dg/7UK4LgI4gX0RqJfY6s7bIPRxfqPo8XdzjtEyB39VzPEPQ6WFodb5HWcXOd2/0ixHxz/HMe6HEv9S+xpqIsDz3RvxdHFb736b6A5/IntkAN0FyJWYx9975+JP3Svg+2UI/wKl/tp5aNdC29iGxDAMwzDM0lGpcX7MMqHgOL/AT5aBTgazRfbISOKCO6fTtlwdfz+UkFJCiDzDCwdQpMdfCzfrhojZFliMZeh7vFx6/Auk+h/iPIxrg8dbd9ND7fMvcy5AdkX1Z2qfxfPcXwEAPjH/dABPsbJ/XYoIf/1cGUpgz6KP1VM1K/vGMAzDMExx2PFn8lO01N8gGqfCPUX2yEjigjtvb60hqbppuyWhaI9/2kiykmeR5yr91sb31RC9L6VUJjD2kNV3/EVC+Oco9deO7xVYAFBCj39hxx94otjcE/0AsH5xs41dU6BiP+95yHS+4XJ/hmEYhqkWLPyZ/BjH+WW/WA6DETn+eqiWhTTt7bOWL2ZNqf55XsuUba2Lat2lLOD410QAQJaTRcDYg75vVe3xL5Dqrx/fKzEPoJqp/u/yvqfc1w7t/+n2BOnxLxjuB7DwZxiGYZiqwcKfyU/BcX6hn+ztnpZlCH/dact3MSuDNv7K/QHe4/0nGoguYq0n+xesnkirSrYuqguEqJk+Lx4CdvyrjJTqe17RUn838bnMcR7SFs1Wisjxt52YH+qf/5yO/8bwXvyhu0m5T4b2U/MLlfobFiBnSpjUwjAMwzDM8HCPP5OfguP8ZJgU/lPhnPW+9KLC/0mz1+CvaucCiEZdfcw/yf7FbOoiipvt4aNy/Iuk+hsqPGrwS5lFzlgikelQzfcq2eNvwfG3fOwUPQ89JbgleWfOtqUsFAr3Mzj+M+z4MwzDMEylYMefyU9BlzoxZg/AKjFvvy89UWKb72L5xJ3f6t3+a+8HAMoooTck2xcoV+5iXVQXSvVP/o41BGhzuF91KfJ+jxCrpf49x99yuF9irGi+19JFcuFMSvsTMdRxfjnzUEyl/nPs+DMMwzBMlWDhz+SnaKm/QfivxtwInLZ8F7PbvA2J+6wL6sKl/ubXzLqoLuL4G4R/VOpfTReZQfI9q2i4X9Lxz/65T3P8bQv/xFjRnD3+wnSOKOH9KBLuZ3T8udSfYRiGYSoFC38mP6YL1xwXojLF8W/ZvuDW9jNvie0W91HK/xto2RfUpn0qkEzexf4CxfC91GbH37feS81YJDHFYbkI/xyOf6LHvxvuV+4CZG7H37C96RxaFLXUP+dYUVOPP5f6MwzDMEylYOHP5Kdoqb9BCK7CnHWxWjRN29f67B8tHkLbt72Phgv43I6/xKFiC0Au1q2Laoup/kCU7G87PZ2xSEGxOhKkTPai59jPUDvfrOyN8yv3PJR3EUUYyu6F6bxRENXxzz9yUGfnPDv+DMMwDFMlWPgz+TGO88txsWwIplol5ksQq9rFccES28PFA9bFqqntIVefspQ4q/YZ/LTxHnyq9oXe/dZFdREH2Fjq73Oqf5UpMsVhVBhDRvO0HKnCdI3YA8D+ollirGhex99Y6l92j3++18B0vmHHn2EYhmGqBQt/Jj/GHv8cs+dTHH/bvbW6DZX3gltoAVqHO/dbFwWBKZ07x2sJv40/cX8BAHilexW6rr/9VP8Cjr8x1T+w/34z9tCO0a27F5ZoR/pgPA/lmS6ibrsGcwCk9UWzRKhozgVIo/teQrifVyDcz9Ry1LRcHcUwDMMwTDFY+DP5MZb65xGChnA/MWe/t7bgBbfQBMDh4gHrZcBBQfGii+oJRC5b2RMScjmOht+xBt/+PjL20N6zLTvnlmhH+lAwa0Q/dmoiwEoslFB5NHzbhJQSjtHxty+qHRH/3vnD/ZL3hXx8MwzDMEylYOHP5Kdoia1BNK7Agn0HuGC4n95be7iw7/iHvqEPNocwcEK1nHYSTQAjmD5gIdyPU/0rjPZ+5xWCI8G4AJmj8siwALlG7Cl/ukiec6U0u+/GpP+CqI5/8VR/XthjGIZhmGrBwp/JT+FxfsnH14VfQqm/fsGd72LZ0QTrRrEFgb9YeLcoYcHXUgZN5f9THeFfJdcSYXJxw0PAqf5VRvvslyE0C1O0WsawILUWs/bzMRLHTr7wTs8kwi33+EstKNHGOL+0iSMMwzAMwywNLPyZ/BQtsTVctDbQti8EE7Pn8z2/LnZcIbFydnPBnVIJfLul/pOi4/hbD/fTXruCAotT/StOuFwd/zyLZgbhL2bLXzTL5fhL42tvO9XfD6VSWeDkbIsyjfMzLQYwDMMwDLN0sPBn8lOw1F8awt4aaNsv/S44RsvUWzu5sLXIHiUwtT3keS0dXfh3e/xLX0QpKPzhs+NfZbTPoMgpBEeCaeEoT/+84Ty0Bnvsj/PTW45yjuv0DKX+xr7/AuiVBfnH+bHwZxiGYZiqw8KfyU/B8nSTAG+gVYLjX6zH33TxK327I6qKjvMTWhl9XOpfoUUUw+/oIeBxflVGd/yrWOpfNGTUkIy/VsyOIBgz37hOc4+/Xce/HYRKZUHe99sk8ln4MwzDMEy1YOHP5Kew45+8aK2LAO22IeiuCIlZ5DnD/Uzbaz31RTEK/xy9sU6o7k9c6l+hcX5p4X5c6l9dEj3+FXyvii5Appb6VycYM0zr8bf8fuiVBTZ6/E3l/wzDMAzDLB0s/Jn8FO2tTelPDS0H5xXprQXMrpcILDv+BQPKdMd/sizH33qqf8Cp31VGe78FKvheGcfc5Sn1N6T6w36qf5FqmSCUcIW51F9aFNbtQM0SyC38ucefYRiGYSoPC38mPwUd/7SLc79l103Xw/ny9NYCgGMqpzX0BRfBNOEgz2spAnOpf+nipaDj7/E4v2qTCPerYKl/UcffMG1irZhF23ow5vCLZoE0O/62p2IkevzzhvtxqT/DMAzDVB4W/kx+io6gS3H8ZXth2D1K+0Hq//OIVaQ5/iMo9c+xn44cVaq/3jZRPNWfw/0qzHII9yuh8mgNZksIxhz+tQxDGHv8XYRWq3ravg9HxL93XsffNLrPFPjHMAzDMMzSwcKfyY2xPL2gAwwAsl2u45+31N8YqmVwCYsgCy6i6K0Hcal/hXr8DVUS3ONfbUJffc8Sx1IVMJW65wrGNPX477H/udSfz5Ljb3OBIvDV1yKv8DftC/f4MwzDMEy1YOHP5CYoXGJrvjgPynb8q9jjbyz1z+H4p6T6Wx9JViTV31jqz6n+VSbQK1FyVsuMhIL5GKbP5RrMlbBoNnybTBiaU/1dEVptSQi085rpZ/bD5PhzqT/DMAzDVAsW/kxuQr/Y7PnUC1/rjn8x4b8cHH83UeofXcDbDs5rtrQFj8Kp/lzqX2X0Bam8+RgjoWCpv+kzXBdt64tmRSqP9LT9LrZL/X3t/baS6s/Cn2EYhmEqBQt/JjfmJPpiKe8AIC2n+icvuPO5WKZeXMd6qr+pxz/7a6k7/pOIXkPbojrp+OfoU+ZS/2WHr38ul4vjn2tBKvm59MqYNlGgxz+QEq5BhLu2S/21Uaqmn9n38ez4MwzDMEzlYeHP5CYomERvdLkByLZt4a87/vkuRE2OvxPaFf6y4GuZFP4dx996qf/wPf6msWlc6l9t9B7/YYT/PdvncOmtW9HyS1rgKer4G469qBKlZMc/h6gOUxx/z7bjr/f45031N/X4s/BnGIZhmErhLfUOMMsPUxJ9GAaZV5FEmojwLZf66xfMeXv8TcJf2i71N7VNDJ/qP9VJ9W9bvuiWBaonwsCHq91XE751gcXYQ+/xz1vqv322iT8680q0ghDvfP7heM8LH2tz9yIM55Fc5yHDuM4yFqT0BcjU85+BQEq4IsXxt3iM61U5uUv9TY4/h/sxDMMwTKVgx5/JTWgo0U44wn2fwFzqD+ul/tqFZ94ef8P2rmXHv2jbhJtw/MsJ90uIrDwBZYb2iKjUn4VBVUmETuZ0/C/6zRa0Op/Bz1z6W1u7pWCqHDKGZaZhDJ30rS+aJUv78/X4m8ruPQRWKyn0VP+8pf6m0X3cycMwDMMw1YKFP5Mbk+OfVr5vfoIU4W+5f76McX56aX1RjK9bjtcyEe7XFf62Hf/ESLIcpf6GMEivhJJqxh6JUv+c+RhrJmvK/+dbKcd8ARKTB5BSQZOCyfGviwC+bzfPIOn42wn3s+v4a+F+QuZS7iZ3nzM8GIZhGKZaVEb4CyE2CyFkyr8tKY85RghxoRBihxBiXghxkxDib4QQemUxfczrhRDXCiFmhRC7hBBXCCH+pLzfbPwwOf5G5zqNNBFh2fHXy1XzlNhKmTJGy7bwt9zj3yv1ty2qEyPJ8vQpm1P9uce/uiRGduYU/g1P/dNyy4O7i+5SgsAg0E3npjTSzgemMMoiJFqOcjv+KcLfaqq/YdE1x3tuWoQIZXQeZRiGYRimGlStx38XgE8b7p/V7xBCvAzA9wAsAvgOgB0AXgLgTADPBvCnhsd8AsB7AdwP4EsA6gBOAvBDIcQ7pJRnWfktxhyj459DrKZdcDtByeF+OS+4PVOatuUef3NAWR7HX30v4lL/slP984T7car/ciMRyJiz1L87130DHsEX6v+G/S9YC7z5P4GpdbZ2EX7QRkO7L5fjn7aIZzi/FSHh+OeZiCHN5yFPBL1WChuEhkUUGfoQbs2wteHxKdUHoQRcUWjXGIZhGIaxRNWE/4yU8rRBGwkhViES7gGA46WU13fu/wCAywC8WghxkpTyXPKYYxCJ/rsAHC2l3Nm5/+MANgH4hBDiR1LKzXZ/pfHDVJ6eq8ffUGILAMJyqX8inC+H++SH0hhwZVv4m/uUw8ylOKk9/rZFdYEef5Pwj0r92Q2sKonJHbmFf/T1K/VP4InOvcBOAL/5HvD0N9vZQZj7+Y0VNOlPYLxbWs7x0FuOco3zC80tRy5CNC0eP6YqhzAIkFH3I20NIgglXIeVP8MwDMNUgcqU+ufk1QD2BXBuV/QDgJRyEcD7O//9K+0xb+18/XBX9HcesxnA5wA0AJxc1g6PE6ayftPItvQniB/fRHxlKSoU7hc5bYYxWtLyOD9jMnn211Lfn8leqX+5s8jzOKumz0ZNBOz4Vxh9sSaPWAW6o9xkJPq73HmphT2L8Q0iP1epf8oCpG3HPzkaz064n83jx1TFZcpQSH18yqIqj/RjGIZhmOpQNeHfEEL8uRDin4QQ7xJCPC+lX/+EztefGL53JYB5AMcIIWglaL/HXKRtw/TB6LTlKfUnDlhTTPRuO9Yd/+FLbIPQPEbLSxMLw2IQ0HnES7LUP3oNraf6a65lnjBHo/CHzz3+FSbh+Ofs8Q+lxBPEvcp97f2eXHS31J9RMGRUpIaMWm7nKXAeSluAdBGg5dt0/A3noRzVE2mLEDzSj2EYhmGqQ9VK/TcA+Lp23z1CiJOllD8l9z2u8/UO/QmklL4Q4h4ATwTwaAC3CiGmARwIYFZK+ZDh53bnTQ0cNi2E2JTyrSMGPXZcKDrOj15wL4oJrJJ7AABO2Cy+c70dSpbqJ1L++5CWpu3Z7vE3tk1kX1zQWw+m0AQgrY8k08P8cgn/tLFpnOpfWRLvWU7HP5QSxzu/VO7btmcBjyq4X8rPMC1A5jh2nLSWI8sBnrrjb2UBEuEIHP/sr0O/Un+GYRiGYapBlRz/swE8H5H4nwbwZAD/DmAjgIuEEE8h267ufN2V8lzd+9cMuT3TB3OPfw6njVz4NsVk77Zd4W+4Es3hPqWladsW/kVnkeuOvyMkGmgjqFCpv6l0uobA+shBxh76ZzB/qT9wgvtL5b4du+eL7pb6M0wuda5S/5TjLM9nOwOFKo9SHH8HodWKGdNrGRjGcKaRFu7Hwp9hmEFsn23i29f+DvfvtPs3gmGYJJVx/KWUp2t3/QbAW4UQs4hC+U4D8IqMT9dNE8p71TFweynl04w/MKoEeGrOn7csMYm+PKX+tGy45Uyie13r2iz1Ny5E5Lvgrhm2r6H8VP881ROmhYhJNO33zxcq9U++r1zqX20S7Rk5S/29xZ34A/Fb5T6/bbeVp3ipf8q2lkv9E8I/x3koTFuARGC1YsbUjpNnATKtpJ+FP8Mwg3jXuTfi6jsfwWHrp3Hpe54LhwNBGaY0quT4p/HFztfjyH1dh341zKzSthu0/aCKAIZgEqZ5xKpDFg5abuz4uyU7/rl6a0OYQ7Ws9/ibAsqyX3B7hoWIKTSth/sl3NE8Ke+GbW2HkzF2SQRM5kz1Xz1zM1yhfQYtp+UncgiQT/g7KdU7wnJVT5FxfqljRRFaPcaNPf45Kh/SBH5a6B/DMEyXq+98BABwz/Y5PLhrYYn3hmHGm+Ug/B/ufJ0m993e+ZroyRdCeAAOA+ADuBsApJRzAB4AsEIIcYDhZxze+ZrIDGCSmEv9cwhicuHrK8LfojAwOJR5Lrj9MDQ6bdYdf4P4zSX8DQsRk6IMx99uj39dsONfZfSxeHlL/UVgmNBh2Ukv7Pin/E5u6ENaFKz6WNFcjr9MSfW3PBXDHO5XXPhzOw/DMHlwBLv9DFMmy0H4P6vz9W5y32Wdrycatj8OwBSAa6SU1ELu95gXadswfTA6/jmEAQ3VKk34GwRAvhJbGJ22GuyKAnOpfx7hby71t+/4Dy/8TYLPdqkyYxd9sSZPMCYAc4WA5dA841jRXI6/WdjW4Fs9fhytgyyf4w/jAqRtx9+0OJdnATKt1D+t959hGMYE636GKZdKCH8hxBOFEOsM9x8K4KzOf79BvnUegO0AThJCHEW2nwDwoc5/v6A9Xbdl4BQhxFrymI0A3gagiShgkBmA0d0fMlTL96Z6t72SHf9c4X7S3Ftbh2/XxTLsZ57eWg/J92IKzdLH+eUr9Tel+nO4X5XRBXRux98g8kXVHP+UbW23oRTp8Y/C/Uyp/nYXzoyOv5/9/eJwP4ZhhoEXBxlmtFQl3O9PAfyjEOJyAPcA2APgMQBeDGACwIUAPtHdWEq5WwjxZkQLAFcIIc4FsAPASxGN+jsPwHfoD5BSXiOE+BSA9wC4SQhxHoA6gD8DsA7AO6SUm8v8JceF0CAC8jj+VPgHVPhLm45/sR7/IAjgGcZo1dGGH0jU3EJ7F1PQtTSX+rew0/If08Rrl8cBNpX6c7hfpUl8BnMKf1NYnHXH3yj8s++na1g0A6IyemtuupQJx18f79ePtHC/KNW/3HA/meP50xbx0ioBGIZhgOS5gxcLGaZcqiL8L0ck2P8AUWn/NIAZAFcB+DqAr0utvlpKeb4Q4rkATgHwKkQLBHciEvaf0bfvPOa9QoibALwdwFsQxbzfAODjUsoflfOrjSHGMt48vbXxtiER/jVZcrhfHqctxXWvwcdCEGISdpS/aTEij3gxZQ5MoomHSw73y1Xqn+L4tzncr7Ike/zzlfoLw3vu2Hb8TZ+fHPuZ9jvVENgT1QVbjoIgNC5ARo6/zVL/5H4GOXJb2PFnGGYY9OoqvixgmHKphPCXUv4UwE+HeNzVAP4452O+BuBreX8WQzC51Ll6/OPHyxp1/C0Kg4LhfrTMtQ0PtY47WBcB9vg+gFrhXQRgLvXPccFdk348vLLDFBZLKPXXE9pzPL9R+PuQMhIGLo/uqRxSc+fziFUgpdTf8kQM41jRHG0yTsriVc1mO4/h+M7n+JtfMxeh1XYEHufHMMxSoC9g8rQfhimXSvT4M8uLouP8qNMm6yt6t2tWS/2LhvuRdgS4aJE1MpvzyE19xnkWUUw9/pOiZb1/PuGOFiz1r4no8RzwV02SPf45w/1MC295Jn9kwCRM8xw7qaX+Nvvnjeeh7MemsWUCZTj+praJ4qn+LPwZhumHblLwCFCGKRcW/kxupDE4L0+aNtmWOP51m8Lf6PjnCPcjZcmBcOFT4d8yjCobFlOpfw6nrWYS/mhaF9QJlzJXiJpB+Hf2mwP+qknhcD9DWb9jucffPFbURqm/xfwJw+vmIMwcNEpzDALSXhSl+lt0/A2vWy7Hv3Mc17XWIxb+DMP0Qz9HsBfAMOXCwp/Jj8ndH9LxR2O6d7Nsxx95HH9fveBukdJ+v20vi8AkPvL1+JuFv/3gvOHD/UzC3+sElllvSWDsoH0GbfT42y71N4b75dhPN2Vbq6n+afuTUfjTlgvfqfdu10Rg9xg3tk1kX6gJQom/9b6D3zTeiFO8eAAPh/sxDNOPdsil/gwzSlj4M/kxidU8Pf5ERApa6p9SejsUpnC/HBeh9II7FC58ETv+gUXH3xzul8fxT16cT4mm9T+eRRx/0+el+17bLFdmLKL3+Od0/GEQ+Y7lUn/jcZLjc+mQ8410G73bNlP9U4/ljAsUtNQ/EDVIEujh+/Zez6LVE6GUeLt3AeoiwJu9C9FAtIhbyqiu+zcBl34QeOQu+8/NMMxISZT6s+5nmFKpRLgfs8wwXRDmCveLL1hd4vjXYbPU31Rim+NCllxUh3Ai4d+5hg1sOv6GfcrqWkop+5T6V6fH31zq33H8+a98JdGrTnKX+hvec9dmeCdSWmLyjPOjWSPeBEQQHddRqr+d48f3fXMMaMbXkwr/ULgIhQu3c/4MUvr/h8EY7pcn1V97Lxpoo4m6/VJ/vwV8+8+AuW3AvdcAb7zI7vMzDDNS9GsVrhJimHJhx5/JjdHdz+O0kcc79bjHvyHbmUtgB2EKpsrl+GsX3PTyPfQtCn9jUGK21zKUQN0o/FvWS+gTwYh5Wjv6lvrzH/lKoi3s5E/1Nwl/y6X+VqeLTPZu1+BbGzWZ6spnPV+G6nlIOvFafWhzPKKx5Wj4qp6u429d+C/siEQ/AGy7ze5zMwwzcpI9/nxNwDBlwsKfyY9JrOa44Kbuca0xiZaMQqscIQFLF7OB4YI7X6o/dfxd+CIW/kHbYqm/yfHPKDqC0Oz4T4nFRN9cIaSEoyeR55qXnpbqLznVv6powt2G4+/YHudn+gzmcKmVCiBvIr5pMdzPT3PlM76edHFDCg9SxAF/dORoYUx5CTnC/USoVmtNio7wt+3e0cUIy60jDMOMHv0agIU/w5QLC38mP6aL1lxjtOKLt3rNQxNxaBV8O6I6MFy05hmjpZT6C134WxznV6DHPwx8uCL5O0XhfhYFtfH9LlbqD3RKqvmPfDXRPoN52mQAQBjK+j3bwt80zm/IUn86XSQq9bdz/AR+Wo9/xufXHH8Q4W+z1N8kok0VFWkI7b2YKMvxp/vJwn+s2T7bxF985Rd4/Vevxc45i22ATKXQrwFY+DNMubDwZ/JjHOc3XImt69bQhH03PTBctCYC6vqQ6K114n2UVoX/8OXKaa9VA22E0mKwlmkWuYWxaR58dvyril7qn9vxT77nrs3wTqSNFR1uAVJ1/ANrFTN+mis/RLifFC6k45Lv2XP8TeecXKMRtTDISUTtUNYv4unrZrPVgakc/3XD/fjf327HT+/Yhgt++cBS7w5TEolwP+7xZ5hSYeHP5MYo5IZM9Xc8TxmV124uFNq3LsVL/UmqP1z4Iq5KCCz2+BsXIzJecAe+eQGiIaJ9t9WnXNTxT0tzr8Hn1f2qon12nLw9/gZ333aPv7EUPc84Pyr8SdZITQRo+5Z6/NPK5bNe3Oo9/mS6SB5HfhCmqhxT4F8ajlbhMdGZNmLf8SfvCzv+Y82OufgztXOeF3nGFd3x5ypAhikXFv5MfooKQbKtcDy0SKm/35ovtGtdTGWwiT71vk+gO/7xBbe02uOffC2zXtDLlOkC9c5Ft7XgPMN7m2euO902IMKlBntj0xi76ELQyfF+A+bFHs+2419wBB0t9RfE8a/BtzZtIkhz/IcI95PCAxza429z/Knptcz+/PrnZVJE5ybr7p3ycyTP/hpjqBPMC8Tji36dUsoIUIZherDwZ/JjdKmzn6yp0+a4Hlqkfz5sWir1N/TW5nEtQ63ENiCOv0xx2ofBKKiy9vinOf62hb+x1H+48Y1tRy2ptj19IBN3XAz84J3AA5tG/7OXC0VT/Q3uvpdz8WAgBSuP6EKEIKn+nsUFKb9gj79S6u+4AF2AtOl4mxz/AqX+3VR/6+6d/p6H7ASPK/SzwyPexhe9MpEXeRimXLzBmzCMirHfN4/jr5T617Ao6uia8X7LUql/Wv+nlIAQAx8vw/Qe/zCwOM7PIKgy9/intBx0R/zZK/UvVlJNhb/vNIBgFgBQE/5oy/qkBK74V+CnH43+f+81wDuuH93PX05on8E8+RjA0jn+mRfNQgmXHnt1dZyfNcc/TZhmPX6kugAJlNPjb8pkyCP89fd7chThfr3/N+z+DKYS0GOQxeD4ohsUXOrPMOXCjj+TG7PwHy7cz3E9tGG/fz5Mc5KzltGT7SLhTyYPWAz3K9LjT0MGF8lr2O3xt1fqn3yePGFv9P323djxr4863O/Kj8eiHwAe+S1gqbVk3NBbOfI7/snPcA0+pE3nznScZBTUgZRK5ZEgqf42Hf8gLSsg6/GjVR5Rxz/MMW5vIAUWUYDkqMaJzjg/+6X+uuPPff7jCv37xcJ/fAm0RVYO92OYcmHhz+THYpq243ho01F5tsL90i4Is87PDtTe2oCm+gcWhb9JUGUe5xfvxzxix7Jb6m9NVJtK/bM6lmHYG6MYSoHA0XqpR9njf/uFyft2c1q0iWSPf07H3xTuJ2R62N0wFDgPBaGER489Ty31t/W5TK08ytzjH2+XKPW36fgbe/yHH9kZp/oX268E+vtrc6QhUynaLPz3CvRFVn6vGaZcWPgzuTG5vbkcYC3Vnybmh76tHv9iwp+OigqFC+mSHn+Lpf4m4Z+11B+kx39OxI5lw3aidpFwP1Lq7MNRWiZsllRnYnFX8r5d9wF7tpi/tzejl/rndPzTJjm0mvaOHZMwzZo9EUqpth7USCWKsFjqn5rqn/H5qfDXwv3yCPOBFAz3c1NT/S0f38ZSf2YcCbjUf69AP9cO8163/BBzTT4XMEwWWPgzuSla6u/qwp+U0YctO8I/NRk/635KNVRL0lJ/i+F+ykixLpnD/WIRNS+Sjr81UW0sqc4qXEh/PzxF+Eel/iO8oFvcnbxv0znAJ48APvUEYOa+0e1LxdEXdvKP8zN/htste8LfmOietdRfd/xLK/UvuABJha3jAi51/O1d6BYJGY0er5f6l+T4c6n/XkObCEDu+x5fijr+2/Y08eyPXoajP/w/uH7zDpu7xjBjCQt/ZgiKCX+PiF3X0Rx/S6Py0i+4M17M0lJ/qOF+wmapv+F1y+r401T/BRDHX7QBSHui2rA/DsJss8gV4e8gdNUsgpE6/k2D8L/lAgASaM0C//uJ0e1LxdEX93I7/oZSf8Cy8C9Q6h+GgCvI4z06bcK3Nm2i6AKk1Mb5CVLqb1X0Fiz1Twj/brhfqeP8wKn+Yww9BnnE2/iiC/2854xPXnI7tu1pYr4V4DVf+rnNXWOYsYSFP5Mbk1gdvtS/pjj+0pLwL3rBHWq9tWqpfzV6/EEc/7aoAZqbbi/cr8BrSRZQAriQWqn/yBz/9iIw6H175K7R7MsyQB/H50BmW+jpbp8m/C0GYxZx/P0w1Bx/muofWHMYw7QFyKF6/D0IUupvU/ibxi9aSfW3bfknxvlZHhHJVAb694sd//FFX2TN6/jfvX2ud3ukFYTM2LN5+xx++KsHsdger78zLPyZ3BjLeDOXroaRiEAU9ua5bjTirfttW8K/YG+t1NO0ifC36vgXqJ6gCxC+qCmuZR1te+P80i6us1x0K46/C0nea6uLE4Mwuf06jVXl78cywbiQV8AB7tK21MoDICV7ImO4X6LHXw33sxWMGVhsOYJwFcc/Tw/+IBzbqf49x7/QbiXRz2lc6j+2ULHPSe/jS9FS/xUNnkrO2Ge26eMln70K7/j2jTjjotuWeneswsKfyU03pV29L3/PagAHjiMQKP3zthz/tFL/bH9U6OKGFJ7i+NsS/olZ4r0fmFH4k1L/QHiAF4vqBtqljvOL7h9C+LtLFO5n6u/Xae0pfz+WCebFvexC0E0R/oFvsTS7YKl/muNvM9U/fQEy22tJ0/Kl40GQHn+bifamBRNZ4P2e7PT4Wy/R1s/rFicbMNWC/m1gx3980a8B8i7yTLPwZ0rgjq17sKcTGHn9veOVHcHCn8lNEZeaXvAGcOAKgYC4wNKW8Lfp+Dsu4NkX/u0wNAr/rD3+koioyPHX3XRLojpNAGRy/Mk+Slfp8a+jPbrSPOr4r3u0eZs9W0azL8sAY9hbjnae9HC/apT6B1KqwZpknF9d+NaqZYI0cZ7xtRT0GHNcRfjnEeYDf45poSbHwkJaqr91wZYo9WfHf1yhfxu4x3980c8ReRddVzTcwRsxTE58ZZzoEu5ICbDwZ3JTaJyf5gC7jkDoxoIVbTvhX6nCP3NvrRqqBVKVIEI74iUIpXERRWTcRzpWMNCEf0O0lFTkQqSWK2cR/vE2PhzldawLi4sTg6DCf9WBQGN1chsW/j2MFTw5Sr/dlM+Gb+n4BsyLC1nPQ2EolZBROs7PruNfsMefCnLHgyAZGQgDSEsl0KbclqyLKFLKxPs9gY7jbz3cj4X/3kKgpPqP2ZU300M/1+Z2/Ovs+DP2odem1sfSLjEs/JncmETBMMI/hANHaKX+gSXhX7S3VnPaqKgWlspL24G51D+r40/HCvqiBrhVdPy1cD/F8fdHV8JJS/0bq4DVBya3ae4GmrOj2Z+KY3b8hyv9bsvYkQkshvsVyRoJEsKfjvOzmOqfWnmUseVID/cjjr9nMYTQ9FpmDfcLQglPaMJftHrfs0oi1Z+F/7iiXniz4z+uFA33m6qrjv/IzARmrGmRz9G4tRqx8GdyY3SHMvf4qw6w6wglOI8m1RehaKm/6vi7EKTU37Hl+AchHGHIS8g8crB/j3+Z4/z63k8hiyRtqC0TUan/Ejj+E6uA1QeZt2PXH4CNcL9420XE73lg6fgGkBLul1WsBnDpsUeCMWsIrFXLpGeNZOzxJwsoQriAiP9kuwitHT9K20P352UV/lKiBq3HHyUJf/1zycJ/bGkrpbbjdeHNxCRK/XO+1/rmuxf5nMAUxx/jViMW/kxujOXpGR2sUBvv5ojIyYrvtOOmpyZeDyH84XiKYHUszY7204LOMucQxI8PHK3UHy175ZGWUv2jcX7x61gbZaq/7viv2N+83Z6HRrM/FccxCME8Pf4OEYKK8Lfq+A9feRT4assRSOikhwAtv2zHP/9CqXTc6FzUweZ+msP98gQl6qX+I3L8OdxvbFFL/cfrwpuJ0d/bvCJLf/yuBT4nMMUZ53BRFv5MbszCP6M7RMUqHAihOf6WRHXhC26pXnALUkZvy/Fvp874zriPxPEP9XA/YVFUpzr+eXv83UQAobWRg4PQHf+0hSEW/gBSqnpy9fhT4R+/55VJ9ffpecgFHHXahDXhn/KaZS2jp5UTwvEU4e9aEv5BKAs5/n4YJoV/t9S/9B7/8ZqvzMTQvw08zm980auW8p4z9P5rFv6MDca54oiFP5OLMJQp4/wyOv6+6gAD0EZUWRL+RQLpgITjT0v9XUvCP0wT/lkXJ2ipv1NTypUbFsvoU0VK3lR/zVmtCR/BUjn++z7OvB0LfwBpkzuGC/drilj4hxZL/U2LE5nD/QJN+JNzUG0Ejn/qwmRiQ63ySBH+IZoW9tNPmS6ClJGMOmEYvWaUruNvvUSSU/33GujC9cgqw5iRo7+3eUUWO/5MGbDjzzAd0kbQZZ+fTYV/5+OnJFXbuZBLFatZV5OVcD8Pjkcdfzv72E4d9ZWx/1fp8a8plRN1tK2drNJHkuUt9XeUAMLGKMP9mrvi2xOrgKP+ElhzaPSaHfrs+Hvc4w8gpYInj+MPKvzjBSm7jv/wlUd0XGcgXOXY8USApm/HSU5L9Q+GcPzhasJfhFb20w/Mjn/W99vc4x8t8Fg/vhPhfnyRP65QAciO//iinyPyCn99exb+jA3GeZwoz8FgcuGnJNGbA/+S0Av/sOv4e1T4V6PUX9ALTOFC1GLB6kpL4X4WHf/Q4PjbSrcNgsB8osjZ49+WarhfDf4Iw/32xLcbqyLx/44bgPY8cMdPgHuvjr63+8HR7E/FKbK4B2ip/k4DXV0ZWhT+RXr8E46/Q3v8fStOOpC+AJka+qdBw/0gvGjCSAcPARbbNhx/CddUsZVnQoJQf5/I8Zcl9Piz47+30B7jVG0mJpHqn3ORhx1/pgyUiqMxO/+w48/kwg/Mpf5ZU/0lEeRBJ6GazqYWti7k0py/rMKfPt5xFcfflXb+sKQ56ZlHIxLxovf4N4S9VP9Cs8i1MEehVyUsVak/EDmoE6uAlRvi71XB8d9xD7D56uzVKSVQtNSfhgO2Sam/tFjqL0x96ZnPQ/TY0VpQEFgT/mktR2HWBS/6eNdVhL+1Uv8ghCsKOP6hTJT6u0KiDt+6U7vY0hZducd/bKEX2+PmuDExCcc/5zWBvv1uFv6MBWipP/f4M3s1rcBc6p85TVt32gDAo8LfVo+/WaymitjEhmScn1bq71rax6KOvwj1Hn91nF/LmuNfJNxPTU8XZB9rSxnuR1n5qPj2Uvf4z9wHfPZpwDl/DGw6e8l2w5jqn+O98ohT7btxJUr5jn9GsUqOvRBqWr7NcD+Z8prJjD3+/cL9PNhpSQhCmQjnA3K8ltL8+Am0rF8wtdra54dT/ccWdvz3DoqG+7Hjz5RBW3H8R3SdOiJY+DO58MPQ6AYaHUIDVHjLzsfPce07/mkX1ll7a+l+CMeDQ0r9PUuOv5+yj1kvuAV1LZ2a1j/ftiZegrSL60yOf7w40YYakmh18sAgTI5/l5VktN+eLUvqtOOKM+IFlR+9e8l2wzUtPuVy/MlFuxMLf2lRqDmG/ck8VpSGTgovMc7PWo9/2gLkEJVHplR/G45/O5SFKjzClIWDMoR/ooWLS/3HFvrZGTfHjYnR39u81R16qv/MvL2RsczeC21BGTPdz8KfyYcfmC8Sszr+iVAtQCn/tib8U/Ync4ktfbzjwS1B+Ke6n1lFQaLHXx2VZ0u8BKl5CRmen5R2L6KmOP5RAGEFHP/GSqC+MrodNIGFnaPZJxPtuaX72QRTVU/2ahm1Kih0aam/vYuyIo4/yGc61ML9bJb6py5AZlwAEYlwP7XU38o4v0DCM53Tc5X6Jz8bE8K+8E+EQ7LwH1v8MR6nxcToLYl5qzvY8WfKgH6u2PEfEUKIvxBCyM6/N6Vsc4wQ4kIhxA4hxLwQ4iYhxN8IIVzT9p3HvF4Ica0QYlYIsUsIcYUQ4k/K+03GCz+UcIqM86M9/p1Sf6eEUv/UUK2sbjoN1XLcUoR/mqDOuohCS/2lU9d6/FtoWgj+Agr2+PsLvZtNWYdDHX/41nIIBtLP8QeAqXXx7aUU/kQkLyWmxb3U6Q465BhuSReSuOmhxRR24wJk5sojLWTUcSEhoucVEr5eUj4sKceIzHhx60i18kgt9bfT4582qSXrecg39PgDUbJ/3rLdQbDjv/dA28Bsf46Y6qCLqry5IKNM9Z+Zb2HXPC8s7A3QFpRQjlfOSCWFvxDiYACfBTDbZ5uXAbgSwHEAvg/gcwDqAM4EcG7KYz4B4BwABwD4EoBvAHgygB8KId5u7zcYX4IwhCdsXXBHHz+3FotBx5YwSA3Vylrqr5bYurW4XNkzuFvDEKRdtGZ2/LVSf83xt9fjXyAokTj+zYTj71ubPNCXoB0vQAgXqE8nt6lNxrf9xfL3KQ1v6YV/GJondwwze14PdETpPf4Z/zjr4X6AUu5va+xg8VR/ch7Sx/khQLNd4ji/rKX+MpnqD5RU6p8Y58fCfxwJQ6l0XLHjP77o7X553+uk41/OOeHmB3fh6R+5FM/41//BbVt2D34As6xJfC7HaPGxcsJfCCEAnA3gEQBfTNlmFSLhHgA4Xkr5l1LKvwNwJICfAXi1EOIk7THHAHgvgLsA/L6U8t1SyrcBeBqAHQA+IYTYWMovNUakBb1lHedHS/27F9yeV0Kpf1HhTx1/11MWJ2q2Sv3TUv0zLqLQ6ojQqSfG+VXD8Y9FdBM1JSuhBn80oU3KKL+VgBDJbchrt7cL/2i8W/K9lVmPTSKq21AT82nmQ1FMAYTGUEIDoXIe6ohphwp/O/spU8SzzLjglQj3I8VsnrCU6p/q+A+f6g8AkyWU+uvnopDD/cYSPfSVhf/4ojv+ea8J9M9GWan+l9y8FS0/xGI7xCU3by3lZzDVYZzPQZUT/gDeCeAEACcDSGt4fTWAfQGcK6W8vnunlHIRwPs7//0r7TFv7Xz9sJRyJ3nMZkTVAo3Oz2T6kFqenrHUPzAI/1qdCH9pabU21WnLKvzJBbdw4dXtO/5pixBZL7gdpdTfU/qU62hbDCgr0uMfi+hF1LVwv3Yi0bcUFnfFt01l/oDq+LeXUPhTd3yJiOayG0r9s/a56ZMcqPC3WepvDCDMdh5KjPMDoh76LpYWKNIWILMuojiDHH8r4/zMFR5ZK4/SpgJMoGV9nJ/+utkMi2SqQ1EXmFk+6O913pLqUfX4L5LrKVvByUx1GedzUKWEvxDi8QDOAPBvUsor+2x6QufrTwzfuxLAPIBjhBDUPuv3mIu0bZgU6IVXW8buU9ZUf/p42enx95RSf0uiOkWkpN2v4yjzsz1lH2vwrcR8pgV/ZS1Xdmi4n5t0/Esv9c+yiEJEdFPWlJaJGkaU6t8v2K8LddqX0vF3tHgSi2F4WWmnVHhkHUGnl/rTXAdbQk1KaVxszOr40/NQT/g7tDLBt/KHPu01y3weSqT6E8cfoZXFPT+U8ESBcX4pjv8EWtaPb5lw/LnUfxzRxRyP8xtf2qFeUp3v8fqC9GyznBZCXxnvxp/HcUf/DI3Te14Z4S+E8AB8HcDvAPzTgM0f1/l6h/4NKaUP4B4AHoBHd557GsCBAGallKZB3b/tfH1s/j3fu6Cl/oH+8clwMWtK9a9R4W/L8U95nuyp/qrTVvNcNCVxBC04l2lO+jCOf+g2tHA/m6X+dhz/qMc/fq8b8BN/9EthULAfAHgV6fHXhTFtU1jcBZzzJ8B/HA/s3FziLpiPnczhflqpv6O08lgKxkwZQTdcy1F0XNMsAg+BHVcnbbpIxsojupChO/6OpVR/PzCPaM0s/KU0VkGV4fjr5yJpMTOCqQ76Rfc4BWsxKvp7nbmyrPf45Gdj96L9BUG6n3n3kVl+JBakxugc5A3eZGT8M4A/AHCslHJhwLarO193pXy/e/+aIbdPRQixKeVbRwx67DhAw5VCOAikgCs6B4QMMWgtKdTHaAGoNWIX2LVW6p9ywZ1VVGtOm+cItOGh0b3A9ZuF+7FTA74yihcnkeoffy8q9bck/NP2M1OPvxruRx3/OtqjCffL6/i3B51+SkRfdGjuAqb3iW7/96nA5v+Nbv/o3cBffL+UXWinVBlkDaRTHH/pKlM7EgsbQ+KnBBBmbTmCyfEnpf6e8NHyQ0zWUwfEZCJNPKe1AOgkHX+a6m+n1D8q1R9+nF+YMs5vUjSxy/LFkv66seM/nrDjv/egC6qi4X5AVO6/btpu21yLHf+9iuSC1Pi855Vw/IUQT0fk8n9SSvkzG0/Z+Zr3nRqfd7YkFMcejur6ZxCskjh+UkSPrZfi+KeFauXv8YfjoeY5aFFlbUPAkH0Zpm1Cdfzryii4BtrW+tDSHf8sqf6xiF6EOs5vZKX+WRx/JdW/ad5mFOiim+77LRfEt++6rLRdSHu/hyn1Tzr+do7vNOHvZFzYoy0H0lDqX0NgJyOj4HlIGednTPW3IPylOcwxa8hoEErUDK0CE2jlLtsdhF7qnzlwkllW6MKKHf/xRc/5yesFpAl/21AhOJLrFmZJGece/yV3/EmJ/x0APpDxYV2HfnXK91dp2w3aflBFQA8p5dNM93cqAZ466PHLHVrqH0JAwgG6F41ZhD8tsUU33C8WrK6l4Lyi4X70gttxa6g5DuZBncvi4pDuSxte3Ceb1fGnAWROHfDiRRib4X4yrawtr+Mva3BJqn9d+Ink1FLI3eO/hI6//rmipf4jakHw/ZQ2mYzHDl0U8+HCLaHU3w9COAXGipqmi9DpAzX4dipmUj7fMusxTrZzXA90rd5Wj3+QVj2Ro8e/YUr1R8t6SWwy3G/0GRhM+Yxzfy2jor+3ec8Zpu1LEf5hccd/sR1golasiowZDXqpvz59YjlTBcd/BaLe+scDWBRCyO4/AKd2tvlS575Pd/5/e+droie/s5BwGAAfwN0AIKWcA/AAgBVCiAMM+3B452siM4BR0Uv9Q5DRaBkuFGmpZveCu0GEv5fxYnPgz0ntrc04Kk8psXXguQJt2uNvwRWWmkDqkrVP2SVjBaXbUMP9hL1S/9Te7tw9/nU4Sx3ul6nHfykdf73Un+z7iFoQ0mbY625rKn3C/awJ/zTHf6hS/+Q4P8+a4592HsqY6t+nx99Wqn+68M/o+Etzqn+jhHF+eql/5s8ks6xoj/EMbUYlOS+92OMBYM+ifeHfLtjj/7Gf3IYnnnoxPnD+b2zuFlMSXOpfLk0AX0n5d2Nnm6s6/++2AXTrXE80PN9xAKYAXCOlpFfw/R7zIm0bJgXq/obDlPrTC7WO8K83Ruf4Z+2tdbULbs8RSql/aCFtnc749gUtvhmi1N+rA3RUHnxrpf6pZclD9PjT6Qh1+KMZ59eaj2/Xp8zbkAWJpe3x1z5X1PGnolaU5xqk9U2ntnwkNlTD/eh7bq3UP2UEnYMw00g/ZbpIV0y7eql/8c9meo9/1sU9eh6qqT3+IixZ+BdL9Z9Ey8bwE4Wk48/CfxzR3bVxuuhmVPT3Om9bh+mzYSvYmEKvVYZx/D9/xV0IQomv//ze0kYOMvZILD6O0TloyUv9O0F+bzJ9TwhxGqLAv69JKb9MvnUegI8COEkI8Vkp5fWd7ScAfKizzRe0p/sigL8AcIoQ4nwp5c7OYzYCeBuiBYizbfxO4wwt95VCIJTU8c/S458ssW0Q4W9yjoYh7aI1q3hRHf8ahBDwRSwMWs1FTJgemAMqqH1yKGZ1/L2Qlvo3AC9+jobNcL80AZClwqO90KsJWUQdbp2G+9lbnOgLLQf2Ut41ev+Spvpr1Qa0x59CMwksk1rqn/FzCSLGfLiYIO0djrTl+IeopS2QyXDgwogw9fi71PG3U+pfVPhTxz8q9VdT/Zvt4ufLMKXHP2teQtgn1d96eWTC8ecL6HHE1F8rpYQQIuURzHJFf6/znjOMwr+E6wq6n3lFoNQWo7fPNrF6spayNVMFxnnxsQqOf26klLsBvBmAC+AKIcSXhRAfA/BLAM9CtDDwHe0x1wD4FIDHALhJCHGmEOJzAK4HsA7A30opN4/sl1im6D36kpb6Z3CATaX+E/Uags4CggOZzUkeQFqZavYef/2CG4rwbzaLi0P6WlDHP1OfspRwaaq/p4b72ezxT10syeT4x6+TL+oQrjZy0NI+Zt0H+hoBwFzTx+cuvxO/fGjRvP2o0dsMmimxI2kLGBYIUsP98pf6+3BRq8XHjWPJ8Q9DGF1qALkXIKWh1L8m7ATnpe1L1lA6lzw+4fgjQMtCxUz6hIRsz+0H5lT/UsL9dMefw/3GEpOjOkbX3QxBr/rLu1Zo+qyUcV1Be77ztijq+7htzxK2EzKZSC5Ijc8JaMkd/2GRUp4vhHgugFMAvArABIA7AbwHwGekvsQWPea9QoibALwdwFsQ1VTfAODjUsofjWznlzFquJ9e6p+zxLbr+HsOfHhw0XFvgjbglDRGK3OoltZbCyAQXq/autUsXg5OhX9ADsVMvbWh3xtd5ksHjuMpAXU2e/xTL66zCKx2s7c01BZ1wHEgHa9X8m2jZWIgVExrIxjPvvoefOKSO7DNfQRHdnVfu0rCf495uxId/zDFRc0c7kdK/X3pKuGdtqZ2BFKmT78IA8W9T92me7NX6h8fgzX4VkR1uuOf7SKCOv6u6wFhfF60luofhPAMQYl5HH9Tqv+kaNpPYy/Y498OQpx/4wOYrLt48ZMPYAe5opjGvAahhOvw+zVuJML9cuY5mJzYxTJK/cn1VN6qBH1x42EW/pUnOW2Chf9IkFKeBuC0Pt+/GsAf53zOrwH4WqEd24uRkgp3gVDm6/GnZcBd4V9zHczCRaMj/P12E16toKOZ8scja6m/ozhtHeHv1HsDDFpWHH/ijJJFhUxOGxGILdTgOlCFv8VS/2I9/vHrFDidXm+3EbvCQbv8CzryWv37NffD330n3va834v+/9O7AURtCKZ9Hjl6Snlaqb+2gGF1F9JK/Yd0/D1S6u9aCvcLwjA9yC+DYBVh/3F+HgIrZfR0Ec+HA69zbMuMotpVSv1rgB8Lf1up/mkLe5nD/UJzi9YE2vZdEv2CO2ep/wW/fBB/d95NAIDpkz0873H72dozxiKmz804XXgzMfp7nfecYRLhZTj+9Ofk/Sy2fXX7h3cv4TUGk4nktInxOf8sy1J/ZumQZBVM6qX+mUpsaUZAvO4UkFT7ZrP4amhhx5+UrjpeJAhCIgzaLbul/qHI2eNPBGILHhxHKGKwjjZafpjoLRuG1N7unKn+bSfaP0Hc2O5+lgrpm//VQ4v4+MW3Y9O9OwFEbiUALMqKCP+E458m/Ess9U+r8Mg8zk8v9Y9fW8dShkeglfr7ORcgFbHbc/zj/bQV7gdF+JN19qwho0rlkVNOqn/KRXLRVP8JlOH4Fyv1/9vv/qp3++3fvMHKLjH2MZVSc7L/eKJXd1gJ9yvhmoKGveVdnNCrx9jxrz7jPFKUhT+TizDUHP+84/yo4+/EHz/a495qWRD+Ka551lR/pce/03YQOrEwaFvu8Q+UHv8MJxjd8RdCHefXqZ6wUa6cWk6b1/EXndePLFBE89JL7vPXXisA+Okd29DyQyx2LhCaiBcjdu2ZtbJgMhRppf76a01Eqm3ShOBQpf5QS/1dW6X+oVrqT8dhZvpc0gVIQ6m/h8DKgpQggpgK/8xZI7rjr/T420n1lylVGFkXaYIwNPb414VvXawlKiUK9PjPtUaQL8IMRdvg4gajGP3KjJQwlInshrzOqkmQLVqo1tJRx/nldPx14c+Of+UZ51R/Fv5MLkItnC/vOD9IQ6gWNMffhvBPTfXPOEaLiIquQ60IfwuOP3VGAxIcmKm3NqBi1otK5YkYbAgfgLQkDIZP9adC1u84/vp+lrE6n7YPXYE/M9/CfTvneydzWup/w10P4qM/ub3cfUojLdVf7/XPWCo+DGk9/pkdf63Uv04mOXiWUv2jJPr4c0NHbWY6Dw0I97OX6k8uFsmkgSyp/lLKXmsA0OnxJ9knjqVS/7RzYtYe/7RSfwehdcc/MQ4yp/BfM8VJ2ssBk8hnx3/8MC7w5HX8DZ+VslP9844h1rffupsd/6rDqf4M04VeMMNFmFf4K6X+8UUsdbzbreKBb4JcJFBRMEy4n9txAiUpUfctBMApjj8RHdkc//g1asoaHCEAIZTU+gbaVsK/UoV/BiEoiOgODMK/NoqRftTxl13h38Y92+Z691PHfwJtXPjrh8rdpzTSSv114V/iGLO0Xv7MPf5aqX+9Eb/frqUFiyCUSiCd4vhnOMaVHn8nOc6vLuxUotAFSJ98xrIs3AShOmbPlOpv5fhO+SylhidqhKE51d9DaL88Un9vc4b7reERWssCU9+29dGQzJJjElN5F3hG5vgX6fFPlPqz4191TCNFxwUW/kwuaDheKFxImW+cn7Jw4JiFv5VSf2mvxFb0hH8sqgMLixP04l/mHecXqOXrntt5H5Q+fzvJ5Knu5KDXUkqIwBTuFwtBm2MHU9GqIwBg10Ib92yPhf/B+63r3W6IFuZbSzQmLK3UX+/110MALZI2zi8160FDkn1ra6X+HnwrLrBPz0MQauVRlgUpuk1XTOui2sKClFPA8U/0zjue2uMvQkvHd9FwvxB1Q6q/g9D+xZL+3uYMi1w9VV6LDGMPvcwWGK8LbybC9D5Xt8efpvrn7PHXw/24x7/y6NUo47TwyMKfyQd1WIYp9Q/Vx/eeVtDgPAuOPxHPdB+zXHAD6vxsp+sEEkcwsOz40+DATE4bdfzhRY4/kEz2t7DyPXSpPy2xlzV4Xud98FTHv4zRO+p+0Neq4/gvtHE3Ef7PeuxBvdsTaGOuuUT9v1lL/Ut1/FN+94wik1YGhHAh9AoPy2I1hKNVHuVdgEyG+1nr8VeEf75wvzDUzgWOWupvy/FPWwzN6vgHKa67i7AXnmkLoWdEZG0/6bBac/ythw8yVjA6wfxejR2msY1WUv1LuKagDnBRx3/Poo8FzhipNOz4M0wHqbjUjhbuN/jAkFpGQHyblvoXXw1VnDZa6j9MqJYXPV5Qx79tYcVWKfUnyeeZUv31cX6d90Ep9W/Z6fFPE1KDXksS7NfsBhACyj7WLfVS59kPANg138I922d79x+wfnXvdgMtLLSD0Z/oAz+5eNbcHSnAkQp/83PLjMF89PEBvISTbkP406qEAE6hrJE41T8WhVGqv4VSfyKe6Tkuu+NPhb9rSPUPCgdRppb6Z23LSHm8i8B6qb/QXrdEz/8A9KmhMwvlHUfM8Jh6qMfpwpuJKDq20RQOCJQzzk9J9c8ZNGn6PHO5f7XhcD+G6aCm8ucf56eIRSr8yQVtu22jx5+U+tML7iHmZ3d7/KlTHeol2cNgKjdG1h7/+I9GS3qxqKal/sJS/3yaSBno+Mf7uIg6WZyg4X6jLfXvCv8dcy2l1P/AfWmpfyQGFkroE+yLcYygBNpzwOIu9e4SS/3THP+si2ZqaKWrZjoIH20bi1H0PAShOv5ZSv0Dg/BXFih8K66R6vjHCwtZzkNBKOEK7RyhOP4hQll8zBAd0UoXULI6/mkLB24J4X6Jc07OUn/9fLiNS24rSVFByCwPTO9zniqhtDyAMhx/tdQ/3/ObFru53L/acLgfw3SQWjhfkRJbOj6L9rj7Ftx06tj79II7a6m/PkYLgCCiWtpw/MnrVaTUv4UanK6o1kb62U71V+al53H8JalK0Er9R5nq3w33273o95J1a67AhnWx4z+B6LUdeZ9/mphf3J10/HMKnjykzkZPawHQUB1/N+Gk23H81XaCUOYbK6qUjItkuJ+tygS6AEkd/yyLpGGoO/5aj3/ne4WPH/Ja+IJUHmUc55f2WXQRWk9i16e1iJyl/hyytTxg4b93ULTUP+0zUYaZ4Bfo8TdlGTzMyf6VRq/qsB5Uu4Sw8GdyoQp/b4gef3OqP3X8/XZxUeOk9NZm7/Gnwj96vEOEf+hbqEqgfcZuTuGfKPXv/McrITiPCv886enaGL1eAKES7mfHWc2zHzqHrJuC15jq/b+B6PM3P+o+/7QqkuaeSqT6Z62WoQsYgfC0MXkB2n7xP6AhOY5DoZf6D35+RUB2FyAdLdXfwufSSSn1z1KVEEg11T8p/KPvFc3xCHwq/OPXwM0a5phyLnQRWp+9nhjTmrH9pEtL2x92/KuJSRDyOL/xo2i4X5oYKyM3qE1+Vu4ef8Pi7NbdvOhYZfRF4nFaeGThz+RDKZF1hij1p48nIpJcdLctO/5KiW1Gh4jOCHe96PFOLRas0kKpv7KIQnr83dyOPw33Ux1/K6X+5GJbmZeet8ff6ZxuXN3xL1lg+8lUf8ph66eV163r+M+N2vE3lvoj6vMfYap/muOf9diRtP9e6I6/j1bGyoF+qAGCzhCl/uT1c5NjJj1LPf7KAqRDx/lldfyp8Nd7/KPnKFyZIGlrRs4FSPQv9bct1vTcgbw9/lzqvzww9VDn7atmqo+pZD7POSNtYbGcHn/i+Fvp8edzT5XRF5VY+DN7LVIrkVXC/bJccNMLN+rEkwvawC/uZlLHXknTztzjT4V/0vGXNoQX2RfhaoJ0UGVCargfcdOFrVL/+DnayPFattUef8+0j7YWJ/qhvVY6Rx68prNP0f7VRAAXAeZHnbqbq9Tfz+RsD7UbBXv8B5X6W/lMkn2MQkbztRw55DMhap1FH5f2+Nsp9acLkLSdJ8trGTn+Wqm/iH9Pr+f4F9xPsoji05DRjMIfWttFF1eUEJBZUPgnS/354ruK6KO0gHy938zywCSg81QJpfXa224fDEKp/LnNe14z9/iz419VpJSJ95iFP7P3QkWBk7/UX5jGaGm3bff4q2na2Q5eU4+/R+aRCyul/kT4Ox4CmaN6Qulbp+F+eo+/hXF+NCiRlvoP3eOvBhCW2uNPkvJ96URCVOOZj94HEAKoTfbua6A9euGfWuq/Ox7rRymp3D+1xz9j6Tft+Q4Tpf52xjeq4/zyjxV1wvj4dWqN7o3efTVLo/JouB+t6pEZ9jHQHX+hOf7CTo9/WGSsKKC8375WuWRbrOkTTxKl/wNgx395YBJ/49Rjy0QYsxzyOP7k8S4Z2bFoOZhXXzDMG+5namngc091Mb1f43T+YeHP5IOO83NUxz/LxawbLPRuB14stARxBW30z9OL1kC54B4i1b9T6u/WYlGNsPg+Kvvi6OJlwH4G6mx6xxCcZ6t/ni5Q5HL89R5/o+NfsvCn0w8Mbv9EzcHvH7Qm+o+njkKcb4661D/lQmBxJlnqD5RW7p/a45+51J84/iJKou+eJ1wh0WwV3+9Ac/xlzsojlzj+Ts/xVxcobHwu6XmELm5mK/VH0vE3hvsVvMgNi5X60wUo34mPIReh/XF+lh1/vviuJm1T2vsYXXgzEcYshyF7/Kfr8aK+7WuKpPAvXuo/O+rrCyYzxhaUnIs9VYaFP5MLPdVfko9QWokwxQ1iIRa4REg7VPjbLfVXS2zzp2k7nSwCr0Ycfwuiiwpqx1Ffy1yOP9Ic/5aVcmW6oNOU5LUc9H4rPf7mcX7WAgjT0BZIdJ526FrUvc7rThaiJtDG3MhL/VNEyPyOZKk/UF6yf9r7OoTwD4ULCIGALBi1LQj/kDr+IueiGQCHvHY94U9Eta3sCSqeJe3xz/Ba+kGAWmKcn9qOABS/yKXn9NCljn3+VP/AVYW/lFHZpC0SPf45w/0Swn+WhX8VKZr2ziwPTM5qHuFPt51uxOdG28Jfb0nIG1pqEv6ltzgyQ1P0c1l1WPgz+QjVHn/qtAUpTiGFCv/QnSTfIMK/XVwYKE4bLfXPND87gCPig1x0hX8jFtXCRpk1EdTCraniZZAwCNRxfrGoJq61aFsqVzY7/mGOUv9F6vjr4/zKTPVXHP9ksN8zDtsn/g9x/CdEa/Tj/NIc/4WdKY5/OcI/9X3NOjqNCslOa0VAJni0WhZ6G2nLUEL4Z6g8CuPXulfJQ1o9JkTx7IkwVFP5QzdfuF/Lp+0MAnCclFT/gscPXURxaMBhfsc/0Bx/wO4Fk9D2KW+pvy4IHuZk7Upi+syw4z9+mN7nPKX+dDGo4Tm966AglEaxPSx65kTeRSjT35LSxxgzQ2P67IzTwiMLfyYfiuPvICRhU1ncdC9Lqb8FQaOM0aIX3Bn2kYYLtmXkWAJArR4Lf9dCqT91qxytbSLXqDxJS/1J/7wl11KmjPMbWPqt9PinOf5ll/qrr5POMx9NhH9Ve/zTHP+SSv3T3tfs4/y0Un+oJeQtG46/UurvaqX+Gc5DMt4Hr9F532vxSMdJNAt/LvVwPimo8B/8WtLXqZdNQSaheLZK/emCrcgZMgpAUMffSVYM2LxgcrXXzSlY6r970bfeD8wUZ9x7bJkIU4ijlNkXeWj5tesITHjx9ajN6wr985h7nJ/h88yOf3Uxhk6O0fmHhT+TCyX4y/GU8vSBDjA04e+mCX+7jj91sTKV+pMLYeok1onwd6QF0UVL/V03XzJ5MLjUfwItK39caECZ6vgPuOjWevwn653HkqqEmih5nJ/fP9H/KQevjv+jvXYj7/Gnpf60H3z+kZRwv5JG+qW9r8OU+nd+Dxqw6bcsjMLU2gnocZoaTkjwiFiNHf9Y+E/ZEP4Jxz8+D2Vy/NuGtHwi/LvPXbwygSyiuB58ma9tQsl0IO1b3UUPmwF/RR1/0wX4di73rxxFx7wxy4O0sXhZ32u6GOQ5Dhq1+Pxoc0FPbz0xLVj0g0v9lxfs+DMMRaqOvySOf5ihx78Wxi6wJELL8ez1+Evdacs5P9v3tXFkHWqk1N+x0F8tlFJ/T3P8B5xkNEHruSbH3844P/qa0XL5PI7/IupY0ei8lqTUvwG/3D+Agbr40GWf6TpOf+kT0fBIyr82EWHkPf401HLlo+LbC2mOfzkLE6nva+ZS/6RgDclCRstCK4/UHH+6aBZkWYAkC3dud0GvHgv/CVF80Szsdx7KcOHYItNNwm6rhNLjbyfVn2aNJCa1ZBnRSsMB3XJL/ROOv8x+Hg7C5IgmAJiZLykrgxkaY9p7zr5qpvqYshyA7OcMunDgOgKNETn+eaoSosebSv250qiqmM4/49RqlGx6ZZh+aBeJoeL4Zyn1jy9m1VJ/4soXLPWPnDZ6wU17/Afvo6SOP+lNrhPh7+W44EyDulVO3gtuTfhPdFe6qWstWthhRfiTUn9JhPIg4dmm4X41TPccf63Hf0Sl/l3H/8+OOhgfffXvJ7etqa/d6Hv8Sb/xqgOAXb+Lbs9uBfyF5PalOf5ppf75e75jxz8Wvb6FHn+phfvRUv9MC5BE+Nd6pf7x+WgKi4UvzAItJJRWHmVy/Ju0ZSIp/B1bpf5SreLKVXkEtdQ/NDn+Fg9vfdKAK4PoKlyIlEfEpPX8jrylhxkIh/vtHaS9p1mrhOgCgeeK+DoIQNOi45/mANedwecdAMaQZXb8q8u4n3/Y8WfyQUWBcJULrkyl/sTxpxfa1PGXBR3/qLc23hfad5rFwQoUxz8+RBqNeH9dG4nqVPh7uuM/4I+CEu7nYaLW2c+a6lrbENWCXLlT13xgSbXS41+LU3cTqf6jEv7Rz2/UUk57eqn/yFP9qeO/Ib4987vB29sk5X3NXFatiPLoNaeLb37bwrGjhfuFNHsik/CP96GX3VGb7t03iVbh0Dy91J86/lleS1p5JLvCnyxERon/svjxo7RvuUqOR2rbR8rj6eKGIyQEwtwzr/thHDGYcUEqbcLJyBf4mIGYSsBttoww1SDt3JBVZNHtdMd/0WJocNGe77Zv6PG3GD7I2IVT/RmGQC9YpTaCLovjT0v9aaq/49E+/GLCIAzVRGp6wZ3FtQx92uNPwrTqqlNdNDWWvpauk7PHnwpaWcOEl3T8G5ZG5dH9XAR5n/wBwtNXHf8VRuHvW12ZTxAkw/2oK6Cgl/o3lzDcb8WG9O265Aw2y0p6qX+2z7s0CH86UjNoW3D8A1X4S7oAmUFU10Ad/06JP1mInBRNNAse34nKo5yp/m3SEhGX+jsAaa9yIAsvUNBSfaGHjGYq9ScLFI6nLE64CK32ZhtHDGasEEtz2Njxrx4m4TdOjhsTYRJYQJ5wP9rjL5Qef5ul9Kae/jwLmqZrxXYgx6p8fJwwvbfjdP5h4c/kQ3P8lR7/QUIk8Hsl8qEUSj+6S4R/0TFlfhimOm1ZhH9AS1fJISKIMKyheBo0ddIdfZxfDse/CS92sTXX2o6bbnb8BzrORMguoo6pXo+/Hu43olT/zr5TV0CBCv+lLvWvTwETq9O3Bcpz/FMyHbKUfQNQS/27jj8Rvb6NHn9luoinOP5ZSv3r1PGf6Aj+OnX8m2j5YaEZ9IlU/5zhfu22GmDYQ+nzD4pf4Pbp8c/yWgq6COPUtADCsNRSfwCZF8C41H/5YLrwZpE0fqSG+2V2/NVU/7J6/E37mbbvJtLOPez6VxPTgtQ4VRyx8GfyQS/+NZdaDjqJkT7leTTgusS58qigLO74u0pvbb5QLXqxSx1/6lQ3RBsLRYU/6a0VWqp/OKh/Xu/xNzn+FmaRA1BEijISb9D7RN5v1fGPn6NuqSohfR9yCH+tTWJJS/3dBjC1T/q2+vY2IUKQTnHIGu4nFFEefS4lCX0L0sYW5kDv8Q+VBcgMwh/xZ7dh7PGP9rHIxaN+HsobMkqFv6Rj9sjzWMnI6JPbEmQQ1UrAnuMpCxOu5VJ/PdwPQHbhbyi3BYAFLvWvHDzOb+8gSDk3ZBX+quPvaKX+5ff4ZyVN4JdqejBDY+zxH6NwURb+TD60i0Tq+MtBYrU137u5gDocUp7r1WgffrELsUDK1FL/TOOpfHO4n16ivtgqWupPU/31ZPJBjr/aux6H+8UCy1aPv5NW6j9Q+Ktl9tOGcX71JQj3U5L8KSRsMurxH7XjTwSxVwcm1/XfvqRUf7og5Q/j+IfJcD8qVmXbgvBXXGYXIOXpg6ZNyKANT3QS56VAvXvuoe+/aEMgLPTZDKSEK+j5MmePP2mJkPQ8VFOregov7mnhfnSxM/AHf8Zoq4B064lSf5uOf/d9U8j496KVUr3Ajn/1MF14s+M/fqSV+g8zzs91tHA/q6n+hvGSuVL9zdtysn81MU4VsfmHbIlh4c/kgl7kQThqie2g3vx2LPwXZQMeSUSlpf6iqPBPhGrlK7ENaKkydfxpiTp8C45//HjheFoyef/XgPbXt2QtXumuqeLVSv88ec2o8B9c6k97/OtxuJ+nCv+RjfPr9finlfqriyZL2uPvTVTC8fdFvkWz6PHJUn+6aBYMyobIgHoecpVS+EHHTqsZV6K0UIPTrTxyHEX8TxYU1UGQXuovskwXacf7GZC0fGUfRfF2Hn2cX5hjESV6vO740wwCez3+6dkTGYV/iuM/8rGdzEC4x3/vIK0aKLPjH2g9/qMs9c8hBNPGFnKyfzUpWuFRdVj4M/mgF6yOh4CUoA5M4ycXsguoK+nqruL4F0z1D0LFGZIudS2zjPOjoVrkENFK1IsKf0cb56eORhzgWhKRKN06nO4iiiZebfSQUZHii/j5B5b6E8dyMaXUf7Tj/Dqp/mmOP100WYoef7JIAbcOTBkcf1JGPYoef58c3yLrhY6h1B80vNOC4x9qP0NpORqwn7rwV6hP9W5OolnIkdF7/JEz3E+SsYeK8Cef0wZaFnr81VR/xfHP0HalOP5OLZFBYMsp8dP+vhTs8edS/+phTFEfox5bJiLV8R861T8+d5Vd6p/P8edS/+XEuE8VYeHP5EJI9SIxpMJ/oBCkwr+hnKRrRPg7RYU/EQUBHIDuY5Ye/zYdlUcWJFzN8S/oFCVL/bPPIpd6WXjvttrjXzTxG1ADtXxSPSFyOv69cD9a6i9G2eMf7Xv6OL94v5ZknB91wr2GudR/n9+Lb5eU6q84/oowzvZZSqS8A4rjLy0sWKhi08s1VrS9SIS/qKvfrBHhL5rFSv0Tqf55Hf+4Qiokx4xe6l/0GHf03BbavpXh2FT/JtSUUn8HIWzlV7XTxkBmTfXncL9lg8lNDTgIbexIE89D9fi7Qqnms1rqb9iftEULE62UbdnxrybGVH/u8Wf2WqhYdVzV8R8o/EmpP+rKSdpThH8xQRP6aiq/IKWnWZw2n2QRtB1ywU0dfxFgsVVsgUKQdgSRKFfOI/wnjLcnbLiBUEVK4OSozNB6/E3j/GrwrSxOZNmHgY6/R53UKB8hrUSvFGiqvzdhdvzXPSa+XZLjT4VcoARjZi31p3Pdo8cL6vhbKPWn4X5SuLkqj9rESW/rjj8V/gVL/UOpthypjn+GrBGyUBp6KaX+KLY4AWgho4lwv8H76dLzgJsM97M1/7idljeQ8XPZ5nF+ywZjj+34XHczHdL+vmZ1V9VUf0f5225zTLBpP3M5/innHhb+1cS0qGPr71gVYOHP5EIR5Y6niNU8jv+8VB1/KvyF9AuN0aI9vpHjT0byZQnVWoyFv0+FvxCKUGg2i5UsK6X+nhqqFeZw0wVxqvVZ9NZL/R0iQHI5/jXS40+mI5Rd6k9DEDs9/qmOv+akAsC8xYuHgQwq9W+sBqbXk+3LEv5koUfUjPf3fbwmygHtMxoUL/WnwlkKV8kiGHQeapNS/3bC8afJ/ouFHX8aMiqo448M5zca7ufG+6W2pFiomEn0+GfPSwDU91u46jg/T4TWSiSDNMc/c7hfiHXYjS/WzsSZtc9hEtHrO/KWHmYgxlL/MQrXYiJMTjqAzFVCaqq/UP62lx3ul6fHn0v9lxdGx5+FP7PXovT4q07b4J5vmurfUIJYHOKGefALCVZfEf6u4vjLLOF+rRThD9UBbZKS4WFQSv0dT0lQDwflJRDX1FGEv1qubrvUP3CzhzBKn/b41zHVTdxVpiNUaJyf1iYBAPOjDPjTS/31cL81hyivXVmp/lRU01aerOF+iZ5vAA5tR7ER7hfofem08qj/8/uK8Nd7/Kd7NydFsXDM/qX+GUroyfEjaynCHxbC/bSQUTUvYfBnjC60OF5NWWh1EFq7YPLTPu8ZW8Nafoh/rv0/nOheh1e4V+ON7k8AsONfRcw91UuwI0yppDn+WUV1ItW/JMe/qANMP8/T9Xgf2fGvJsb3m3v8mb0WesEqvJw9/uo4P6XkWgl8C7BYQLDKQC/1p+Jl8MEbtEiJraM6gtQBbbWKCX+HlAE7rqsEqQ0shyauqVNLCf4Sdsb50ZaEkISMDerxl8SxdGsTcQChNhax6YeFKjz6kqvU3+D4j9INpE64qcd/zSFquXhZjj9xgENy7GQRq9GDko6/8hnN2JPdD0kdf8dTpw/4/SsKAlLq7/dx/CfRLLQAqU8XoY5/lvOQ0Fs/Uvax6OKe8r66ntLjHwxoOQKgCG+31jCE+1kq9S/o+LcDiZe71/T+/2fu5QBQOKuFsY/pM8OO//iRtiiY9a3u5/gvWk31L+YA0x7/XuUj0keMMkuLseJojHqNWPgzuXBC6g65ijDI1eMvG2rJtUMd/6CQC6yU+gsXgowNzNLjH7ZSxmhBdfzbBUv9qePvuDXV8R/wWlLR7dbMjn/DxoxvAIKIlICU+osBThsV/k7d7Fg2RBtSllhGFSTD/dLH+ZmE/ygdf1rq30iW+o9K+BMhSDMdhir175wflHGdFkr91XF+2nSRQY4/Ob59p0+4X0FRHYT6dBHaNjH4c+UEZGGxZu7xnxAtC2NF9R5/2r6VQVSTc5Xr1ZVSfwcWS/2L9vhrF+8LiM6VPM6vepjnaC/BjjClkhaYltVdTTr+pNS/ZMc/T9gbPfesIMK/1HwjZmi41J9hCEognaum+g8sudTH+dGSa1cT/gVOiFT4h3AhRL5wv5AI1lAT/lIR/gUdf6kuoih9ygNGnjkhKfWvpYX7RWX0Rd10WuovycJCQvjP7wC+8Wrg66+MbhOBV2sQ4W8Q2KX1uuUa55cs9Z9rjtDx9zXHf2Cpf3Hn3IRDhGAo8pWnR9vRue7RZ5ouTg1aMMqEkjXiKM59r1pmYQb41p9Fn8n5Hb3vB+T4VsILAUX4T4kmFgstQJLKCQg45L1z5eDPlROQHA+l1F89fopWpaiLuR58GjKapS2DvBderZ4I97OVhhykLUJkTfX3zcKfx/lVD3OpP4ukcSOtpD/re00nPUSOPyn1t5rqb6/Hf8UEdfz5M11FTAs9PM6P2WsRehAULbEd5A71Geenl/oXcvx93fGPf04W8aKmaas9/rT0v11wHjkV1I42P7tvuF/g99zXQArU6+Q90PrUQykLr1Q6SjI5EXD6Pt7wNeDO/wbuuhS46O+VUmWvkeL4d4V/WSF62mQBIFuP/5I4/sGAcX6rD1IqY7L2NueFuunKGLnMjn8yI8C+8FfPQwFt5+m+jld/GrjjJ9Fn8pL3x99WhL96fKMeC/+iIx0DfQHSyyn8/TThr+5j8bGi6jg/OsJxYMgo1EVIr1ZXxvl5Fh3/djtlX3KE+1HmZfTec49/9TCV+o+T48ZEpDr+GfWw6vg7yt/2Raup/gV7/MkixHSdOP7c419JirZ2VJ3KCH8hxEeFEJcKIe4TQiwIIXYIIW4UQpwqhNgn5THHCCEu7Gw7L4S4SQjxN0KIFEsPEEK8XghxrRBiVgixSwhxhRDiT8r7zcYLIdNL/Qc7/qTHX2qOPy31F36hHv+QChc4ivDP0ltLhb+Spg01oMsnvcLDoDj+eo9/PxeLJtWjpqxyQwhFnDfQLlzu7xDBR8eKJQTctV+Ob//6u3DIftZpqb9bBxC1XzSEDwfhiBz/6DM2URvc499AJ9xvpKX+5PPkNpTpBwCAyTUjKfWnCz1hwVJ/uNFrTYU/FYpDIzXhr/T4d57/uq/E9/3ym72btMc/Ifyp44/FQqJaBup5CIrwH7z44dIcD7IgoS9QFS1Vp6X+jqu2TWBQyCjU9zty/NVwP1s9/ql5AxkXktraYnLs+LPwrxrjHq7FRKSJqaznDKXH3xXK3/byU/2L9/iz8K8m5laj8XmvKiP8AbwbwDSA/wbwbwC+CcAHcBqAm4QQB9ONhRAvA3AlgOMAfB/A5wDUAZwJ4FzTDxBCfALAOQAOAPAlAN8A8GQAPxRCvN32LzSWaAnQMleqv+r4KwIs4fgXCfejpcpqqX8m8ULHaNW0Un8i/IPCjn/8WrpeTZtF3kccaeXrE3rpuiJgi6V+h6GEQ0aPSfLcju5arv8943MsyDpWTBBhJoT1ZPJUlB7/Tql/6jg/tb8bAOZGWQaspPp3Pmcbn9PZoXXAgUeNpNSfLu6Fbn7h7xBRKw2l/p70U9OcM0Mcf6kL/+6CSH2F8aG0jSbsU+o/iVah958uQAbCVcL9sjj+bjg4I2NS2HD86chBVfhncfyp8K/V1VJ/m+F+QdoiRMYefyzuUv7bnbgw1yo2Ppaxj6mMepzCtZiItDF3Wc8Zeo8/NZPsCv9iYW/091xJS/1Z+FcS40LPGJ1/vMGbjIxVUsqEhSqE+DCAfwLwPgB/3blvFSLhHgA4Xkp5fef+DwC4DMCrhRAnSSnPJc9zDID3ArgLwNFSyp2d+z8OYBOATwghfiSl3Fzer7j80fvS1R7/AePdWnPoxuwtoIG64virF4tF5qcnSmwVxz/DidYnvfueKvzpAkVhx18p9VfFS9+AMvK9FmrJsLraBNCMLnIbBcflBVJNJpdODYEUcIWMBEMYxGFeKRfgm8LDMdXQTjXeRK8CJBL+Iyj174T7pZb6kzC9fcRuAMD8KHv8Ay3cDwBe/nngl98Gfu8FURn6CIQ/FaV5R9ABaql/N9xPkJaZOtpY9EOscIdfd1YWnRxX7dXvvi6NFcCe5GPVDA/d8aeiulnITdezRqjj72UQ/rUwxfHXFs1aQYh2EKI25OupVh6pIaODpotIKZX3olabUEr9bTr+fmq4X7ZjtLa4Xfn/tIhe31BGIiG1EogZOcbSal6cGTvSzg1Z3+tEqj8xQeyW+tvr8Z9u8Di/qmM6/3CPfwmYRH+H/+x8PZzc92oA+wI4tyv6yXN0mzn/Snuet3a+frgr+juP2YyoWqAB4OShdn4vQnWHXMDN7viHrbjUvy0acGnavhbuVyRUi+5HKBwt3C9DmjbtrU0I/1goBGk9pxlxtNeS5iXIfiW22mz6xAUrTfYXxUr9g1DCIwsUcGtow9BPDQBz24zP8YPwGKxoaPuoO/5lpdvS6gjpQQigniaQJtf2Wk5WigVMYnG0id/K+LbOe7jmEOD4fwAOelr0fzfltbcIFfiSZjpkLfVXRHnnM61U9PjFMx306SKK4995z3VR3zn/SLKwlxD+9enezUk0MdcsUOpPW46Eo4T7ecgn/D3q+Cul/tE2RVpSHC3V37iIkkLTD+HRsaReLRHuZ0uwFQ33qy0+ovx/2olfXy73rxZGx3+MemyZiPRxfkOm+tfKcvyLlfqrwp+W+vN5p4qYwxzH5/xTGeHfh5d0vt5E7juh8/Unhu2vBDAP4BghBL2q6/eYi7RtmBSUoDfHU3rzB43zo8Lf13rn6fPU4GOhZSnVX7hwnHyl/sr87Jq2n0RUhwPmhQ/8OURQu25NyUvou6hAHX/pJR1srQe4SF6CH0p4QnVwU4X/7MOJx7eki58ERyuBNol9FK3y0m0DdZGk4TkQQpi3FQJYsX/vv+vFrtEKAqXUv2HeZiSp/uR3plMckOG1kFJ9fNf9JQK7Loq18kQ/h/4MTynZF93XRSvtxszvoocqYxP1cX7x8T6FJhbaw1d80PFzoXAjUdz9sRl6/Gsy3k9XCcck4X6d6RNFPqd61ohS6j/A8V9sB+oihlNTxvm5Isx8ET+IsKDjX9eFv4hf35G29DADKRqmxiwP0t7TrCKL9l3rjr9NUd029nxn20cppdIqsKLOpf5VZ9zPP1Uq9QcACCH+FsAKAKsBHAXgWESi/wyy2eM6X+/QHy+l9IUQ9wB4IoBHA7hVCDEN4EAAs1LKhww/9redr4/NsH+bUr51xKDHjgPUDXQcT3HyBgl/SYR/4OpOevxRrMEvNEYtpKnicKPKhN5ODD54hRKqpQp/6toNGrk3CFpC77iuMiqw76ICWZhoGR1/NaSuyLivyPGnF/Ye2mT6QE98Bj6wsAM614VHYDdWKKvcAJbG8UctfZRfl5X7A7vvBwDsi12jEwRSmkv9dahQLSnVXxHu5Oc5WRx/ZVHKhdOtriDPU0e7cBkmbScQruZSd8MD51Whh5l7gf2OAMhxKxOl/qTHX7SKOf5auJ+n5RwMohY2uxmYqE2QvAJtnB+AQsc4Xcx1tEktg4V/iGmQz21tAiAVVi5Ca05JkPb3JWOPf6Olnp+mwI5/FZEpk2jG6cKbiaDvc91zekJ4uB5/R8nvKWJ4JH5OgZ5vKvprrlD2kYV/NSnyfi8HKif8AfwtgP3J/38C4A1SSlpHvLrzVbN0enTvXzPk9kwKSqm/40HQlPEBQqSv8FdS/YNCgksN9/PUHn8MPtG6ZH62qwl/UaOOv4VS/86FvePowr9fqX/8c5umHv+E8C/Q46+V+jtpjr8usjr8VxCF060w9fh3GF2Pfy29v78Lcfz3FTOYLyD8chH6cf6E0FpoKKaxdZZxU4R/ph5/MrljEQ243eoKvdS/4AUPbSeQjodQkP0MWlGQaHtOfdDOe6OvZIFF6q08WsBjEUEtlbGGLrw6Ef4ZSv3rstU7P3gN2uOfDKEsVuqvLqLQ6olBPf6L7QCrBHmdJ9Yk8lps9UYWTfWfbKnnqEnE53ke6VcdUvu+WfiPHdSxbxDhn/WcQQP2PEcoQcdWHf8CDjAt86+5jtJqyKn+1cRU4TFOPf6VE/5Syg0AIITYH8AxiJz+G4UQfyKlvCHj03RrefO+UwO3l1I+zfgDo0qAp+b8ecsOVysLVceLDbiYJan+gTelfk9L9S9yIUYrD6TW45+l1F8Zo1VT99MhAV2yQKm/lLKXKg0Aruf1gtCAQeF+Wqp/nx7/CVFsFrkfhpik4X6JHv/Oaz2nlflPrMHt3uPwg+3HAACm+vT4N0R7NOP8pKE6QmfFfr2b+4pdmBmV408/S2ll/sDIw/2EUuqfZSIGndxRhyN6yrV3fx1+YcffoY6/cJOl/qaFqJlI+It+r3VdF/52wv2kcBXHvwY/qvJIaTuRUqJBHOkaFf7KolnxsZO68KcLkMGAxaVFP8BqKvwn1yil/jbD/cJUxz/bMTqpOf4TchHRn3zBwr9CFB3xxiwfqIva8JxeFmvWKqFEqn9Jjr+px9/UBz7osTXXUcYvs+NfTcxhjuNz/qlsj7+UcquU8vsA/hDAPgD+H/l216FfnXhgxCptu0HbD6oIYDrQi3/hurkcfyoKQt1pc9RwvyKl/rrT5pJS/0zCP0zprQXgkDLbQW5YP4JQTcsXTk1JUO+7qKCLWb18nYpqK6X+qjBoSZPwJwU5G58D/MNmfPZRZ/QWCRKOP01PR7M8x9/Q498XzfEfWQkwOTaWWvgrOR5U+GcahUmEv2zAccp3/I2l/ibhv3Nz9DUwhCj2di4W2FMFU/2VcD+4qHse2pIcq30Ea9MPe2X8QPo4vwlRvNRfzxpRFiAHBJgutkOsQrrjb7XUP+0ckVH4T7V3Kv/3EKDeqbwo8voxdkkd8TZGjhsTQRdzqBOeNRdESfV3Ncffaqr/8I5/q4/jX1q2EVOIce/xr6zw7yKlvBfALQCeKIRY37n79s7XRE++EMIDcBgAH8DdneeYA/AAgBVCiAMMP6Y7MSCRGcCo0ARox/HguNkToIUflwHLmu74a+P8Cjn+xKEWLhzy3DKDePGo8K+r++nWaEnx8I5/oDn+cBy11L/fa6mM8/OSc+lpqr+VUn8a6JiS6j9HRmVN7wsI1UXrG+43sh5/w2ulQxz//TAzuh5/unAytT59uxGk+isOcC2v4x8f45Hj3/kP7fEXxR1/ZSyno7rUImirn8cuXcefvG5OH+E/gRYWCrz/quPvoOaJ9GBMjaYf9kQ9AHWsqJKPEX2+iyxQubrj79Lz0ADh32xhlSCLVhOrEz3+1sL90s6JgyrNOkz7yQwSG60SjF2KBr4xywf6nlInfLgef9XxLz3Vf4ge/7orlDHWnOpfTUyl/nnGN1adygv/Do/qfO0eJZd1vp5o2PY4AFMArpFSUmXW7zEv0rZhUlBH0KnCXwxwXgR1NfW0fC3Vv1i4Hy31d1GjjngG4U/HaNUaamWCRx3/AsIrDAFHkJOL0KonMo7zMwbWaaK6yGsZBCFqJNXfcT34SrhfV/gT4Tq9LwBglvzcgeF+oyj1zxLup/f4j0oQ0FaJFfunbzeKUn9lPFssjDOF+7VjN72Jejyyk6b6o3hrh6M5/iE5dpywBcwnRR523htNHSALdqKm9/jTVP/FQuF+CNTKI89xzMeOgaYfoEEcf7ogAU89doCCpf5Qj2/pkMqjAec4fz520efEdFTmT1P9LY7zC9MEfkbHf4W/M3HfdKfPn8P9+nPT/TP4y3Ouwx+deSVO+OQV+MD5v8FN98+U8rNM/dRAdheYWT6kOf5Zhb+e6q/3z0tL554iqf5t8reu5jlK1SGX+lcTU6n/GOn+agh/IcQRQogNhvsdIcSHAeyHSMh3/3KfB2A7gJOEEEeR7ScAfKjz3y9oT/fFztdThBBryWM2AngbgCaAsy38OmMNdf0c11NGVIkBpf5OQMuZNeHvqqX+hQSXMj9bLfXPIvw9GV/s1iamle+59VgoiLA19B8WPww1J91TRF3/Hn/V8e8b7ifahS5qfXKxHcCBcFxzjz8d5bciEv50waFvuJ9ol/MHMAyV9hPja6WjCP9doxP+htfPyAhS/RXhTxx/J6/jLxtxj79W6l841Z+61I4LOLQSJ6XHv7kbWNgJhxw/Qm85qsfH+6RoYaHAftJSfyk81F0HLdOxY6DZDnv9+wCUJH96e9JCqT91/B2vpjj+fRcgAYTzM73bC+7K7pPEz43AYo9/sVL/lf5M4r5J0XX8udS/H39/3k249LaHcfvWPbh72xy+/vN78bLPXY2Lb95i/WelOWvs+I8f1EmnTnjWxUI91d9xdEfdznVFkZ7vRLhfCfvH2MW0+MiOv31OBHCfEOJSIcR/CCH+VQjxVURj9v4JwBYAb+5uLKXc3fm/C+AKIcSXhRAfA/BLAM9CtDDwHfoDpJTXAPgUgMcAuEkIcaYQ4nMArgewDsDfSik3l/trLn+Ui0THhfBo6nefi6cw1ELzdMeflPqLEHPN4UWNXurvKT3+gy/k65I6/lqPP/l963L4XuUwhFbq7yo9/n3dXM3F7jfObwKtYn3KJMcggAvXEZp4SSn1hyr8+4X7lZbqT/v7ZQ2AyOD403C/GcwXqJbIxWxGx3/Eqf70OM2W6j843K+GwILjT4W/p/bqp/X4A8DMvVFFQPd56umO/ySa9saK5iz1bwVhrwwdgLpQqrUjABYdf0etPBrk+MuFmd7tBbczclBojn/p4X4Z/lb4TUzJucTd3ZF+Rc6Rw/KT3zyEk8++FpfdtnXkPzsP2/Y0cduWPYn7pQQuv+1hwyOKkVZCzY5/fsJQ4l8vuhXv/s4vsXX34uAHjBh6bqBOeHbHXx2VBwATHg34s3Ncm0v9s/0NS/T4s/CvPCaRzz3+9vkfAP+BKMTvlQD+DsCrAOwAcDqAJ0opb6EPkFKeD+C5AK7sbPsOAG0A7wFwkjRYsVLK9wJ4A6KFhLcAeB2AmwG8REp5Vgm/19iRcPxJz3HfUn8/FgTzsoG63vMthJLM3WwO3z8PxWlz4dJ9zOD414njX9ccf1qyXCvQqxxIqTqoeql/94K7vQBc92XgjovJ96ig7Z/q3yjYpxz41PF34TkCbRru17novuvee+L7eqX+8WszeJxfCX8AtVF+AHKF+63HLswXWIDKxSy5+J/O6PiPINyvkOOPOnqVl7THH+3CwUtC60unlUdO0ALmDT3+ALBnixLe6QwY59f0h3espZbqX3MdNdyvX6l/swlPdGZaw1Gnp2jHDjC88JdSqgs9bk2pnsCAAFO5EJfPN72u40+Ev7Ao/MM0xz/D705bkQjTYmlK/Zt+gL/97k24/PZtePu3bqx0q8F1m+O2mRUND3/3R4/r/b+MBZM0J5Ud//z8753b8e8/vRvfv/EBnH315qXenQRKqf8Qwl/v8QeAKXJtaatiz+wAD9fjT80HLvWvJqbFx3E6/1RinJ+U8jeIyu3zPu5qAH+c8zFfA/C1vD+LiXC1hHcl7K6f8NecQKMAc7yekGy2hhf+iTFaddqnnGF+NumtrU2mjx2so42FdoA1Q+yjH4aoa46/MIm6a84CLu90r5z8E+DQZykX45Hjr72WWqr/jiIjyUipry9cOI7uWrZx17ZZzD7yUG8ZccZZjTVQy2f79fg3RAtzpQv/6OcPHOdXm4RsrIJo7kZdBKi1RzTogwqTJe7x9xThH4vMbD3+8XG+CHOqf13YSPXXhT8JIQy1Un+3Hovs2YfhEsff1R1/txbljYRtuEL2pmKsnKghN9oCpKcdO6HfTl15by/G7nQLdUzSsX9am4xAOHRLQigBl0yxFa6nLjIMctMX4+Oj6XWG6Wg9/rbmH6eW+mc5DlKE/1KF+929ba6XgTLfCnDF7Q/jRU825Q4vPdfeEwv/NxyzEY/df2Xv/2VURKU5qePkuI2Kh2bi8/FDuxb6bLk0+AWFf0AEmtcV/qS60FYLTxEHODHOj3v8K4+pwmOczj9VcfyZZQK9+HccTyl97yuqFSewYSy5psncrQLCH0QUSMeDS1xLTw64SJRSGaPV0B1/bR75sE6NqdSftk30Lrh/+tH4vnNfG30N1FL/ZLhfvI8TolXITQrIRXUALyFeELSwdfci9hG7e3d95IpH8M1f3KtcTE8NaEewOXon3jcq/KPXdqDjDyjCe004M5o/ztTxJ+0GCUaQ6k8X91wyRk4Z85cGqexZkKTU31WPm6IlmHqpv6AhhGFbCfcL1scOJeZU4e/pwh8A6mop/dBuuib8hRBoi/gc57fTz3F+Mz5fthxt8oDjqDkeaA/dkuCHIVwS3gnH0yqPBuS2LM70brdrHeGvlfrbckrSS/0z/O677jfe3Qv3a4+2x/+OrWrp/I9//dBIf34efn53vIj29MPWYboev79lTD1JC/cbpwvvUUEFTNqYxKUkrdQ/62Kh3uMPAFN1KvztXFcUcYCVcL9EqX91K332Zkzv7Tidf1j4M7nQE6BdL6Pj34ovZBdl3RiyRi84W0VK/XXHn1QleIMcf5+kkssaJvSWBMXx94d22hLj/LSxg6J7kUvTvBd2RGWtpLx2j5zsH+6HdqGLM+r4h8KFIwTaWjL5/KKP9Yidvx/d7eOU7/+m9/8D10zGzm8Xrcd/sYxxfjQLodOekEX4Cy3ZfyRluLPU8e8n/Mt1/ENtfKPbiBe+ahmqZVTHvw63J/zj/a6huOOvCH9XXTRztB7/X7cO7N2e37kFXj/HH1COuSk0h7941M5DQNQu0yWr8G+LRnIDbeGsyAKkHjKqLEAOEv7N+Lhv11f3nqOLi8DaqE5ZJNzvoZuMd3fD/QpNbxiC27We+UtvfbiS5f4z8y3c3lmkcB2Bpx26FlMN+6XUlLQL7HG68B4VLSJY0xZUlhLqpFMDI6uo1lP9AWCqZv/z2TI6wEP0+Oup/hVcjGGKhTkuB1j4M7lw+qT6Z3f86+aQNSJ82+3h3UzdafOo44/+F4lBi44jqynjYaJ9pCFlwzuXYSj7Ov69CQkbnqQ+8L5rFZG4DWsw0WecX1SqXKDUf6Dj30ZzfjcmRLTdgqxjHvFrdOCaSXzmNX+QfGIlRK2F+TIcfy0EEVBnBadCA/4wU4qrlUDp8c8q/O07/vqClCDu96BjB4DW0tNAb73Heqq/NlaUHONu2FbCJn/y8Jre7d/dd69S9WN0/Gmfvxg+4E/SyqOO8PdFfOz4faqaFOGvO/76PhaoSkgsQDqu8hkTYf/PmNeKK32CnvBXHX9bAVsyReDLLAtgD/2qd3NGxotZXcd/1KX+d2ydVf6/0I7K/avG9Zt3omu+PunA1ZhueKrjX0KpfztFUNkaC7k3QV3+rGF0o6SUHv8ySv0NiyZZF1L0Hn/F8S/D8GAKY3pvx2nhsRI9/szywZEB0LmYd1wPXuZSf1UQmJxX6vi3W01IKSGESGw3EBL2JB0XNaXU3+/7vK3FWXQl6SLqWKVvR0v9RRsLreFO3H4olZJqaOXKPeHva+Lgth8pInG7XD0w1b/IH7+Qpvobe/xbCPbEF6zb5Wq84PH7Y64Z4KiNa/HW5z4m2d8PqLPIRauc9HxDuN9EzlL/aKRfycI/DNQwur7hfjn6r4cg0Bx/QRZosgl/Os6vjrqTTPWvo13c8Vcqj2pK5ZGj9fjfIQ/q3Z5sPoKapKX+WoYHkAj4G7aqRwn364hhH/H7F/Rx/MNWfL70jcKf9vm3hl6cCgKZcPydrFVcAGqt2PEPGuZSf1uiWqaE+MnQx8C/Eltix/+68Ai80N0EIE71X+pSfwD44U0PVq7Pn47re8Zh6wCgdMefiizXEb0L7nFy3EYFLTOvpuOfUuo/RKp/z/EvpdTfTo//pOMrZhI7/tUkLdNhaE1SMVj4M7lwFcffVS643azCXzbQMJX6kx5/Dz4W2yEm6xkcWg3FGRIeHFLqXxM+/FD2Rr/otBbme8K/JerJDTTncuhS/1D2Uruj/XSV6ome8G9rgTy3/gByYk3vQnebXJ1cRKGOvyjm+FPxEorOOD8lmbwNSUSrs2I9vvz6owc/cU1fnCjD8Y9fu67wnzItQugQx3+D2FG+Gzj/CNB1sCfXAp7hc9fFyd5/PQyBtiDleA340oEnwujYDwPF0U2ghfv1QukcGu4XYLHgYore40/D/WpkHCfqK/Bgc33vv1PtHXCJ8NfHdUaPUYX/0I5/mHT8A+Ghm6UX9EnMD4jjbxb+2uKELcdfmy4iBlSV1PxYwMqGyfEPhj5H6tDQVopMub/H7MPAnqiHfl428JtwYyz8O6n+oyz1n2/5+N2O+cT9/3PLw5iZb2HNVJ/jf4TcsXUPvndDnI3w/COi82LZjr9a/u30zr88zi8/7ZCW+ldPZNJwPuqEZ13kGZjqb+m4bhVK9Y9e9/d6/4m/vuuHCC5/I4DnRc/L4X6VJHWkqARSpMOygkv9mVy4Wqk/TfXvL/xJj39qqT8V/sHwJdb6BbcySszv+wew1SRp2kbhr4X7DV3qrz3OcZQQwl71hK8J/5nfAdtu6/13l7vW0D+vlfoX+ONHS/1DYS71Dxficl+/thKZ8NQe/1JcdZI4vltGQmntVIZ09n0e07v5ZOee8kXBLCnx7ZfoD4yk1F9x/D0v8+x5AInpHb3PpuMgpGXuA8bEDYKeaxzXhefVEErDX+SpddguV/f+O93egRpIqX/DVOoffzanxPCiWigtR9HvHjjU8U9/DcI2dfwN+5io6imwAKk7/vQ8NKCqpOHHx76cXNN5EBX+0l7vOjln0vd6YKk/6e+/VR6CuKaLOP4jLPX/LSnzf8y+03jKQdHnsxWEuOCXD45sPwbx0YtuQ1fbHPfYffGMR+8DQBVWc60AhsnJhUgLfBs3x//BmQVcfef2UkuIlVL/Cr5+aan+WcP9FMffNTn+Zab6Z+zx90PU0cY7vPPhIkB905cw0TnvlDLGmClMWiWG6XOwHGHhz+TC1cL9vBrt8e9z8dSKL3bmMJEyzo+66cHwbgJ1/LWe1Rp8tP30PyrtxfiCu2UK1SLP1UAbi0NeMPptMiavE/jlkoUPJ83xh+rC7fHWJp/cYqm/9GmPfzfcTxOCzSGEf81eVUIqCzO9m7sQ9fWunszgph38jN7Np4i7sLCQdOesovT3x2X+v3lgF373iPazlVJ/H7B90R1IeGRxz3VrQwv/RZrqDyAk8+GDIlM7oJb6C6eGes1V97P7MyfWYQdWIugIxalgN6YQ53jUTY5/Le4Bn0Rz6FnltMcfncTpQGQr9ZckDDV0+y9ONES7UOWRo/T4q6X+g4LzJojjL3rCXw33s+X400quJmmZSKsE6PHQL3s3bw43KhkkvXF+Iyz1p2X+j91/JV591MG9/393030j249+3PrQblx6W7QgKQTwjyce0fte3XN65cpBKK2LF7X8OxZx4+T475xr4QWf+in+75d/gc9dfmdpP0ct9a+eaFEWedyiPf7dVH91YcoGhVL9A4nDhDq1YxWi83sQyrHqHR8X0hz/cXmvWPgzuXAUUeApifluvx7gZiz8Z+WkWfiTcD8PwfBOq9Lj7yXK8/v1VbWJ429M066rwV9D9/9S96pzGBqdtna66Nwtp+DUDMLFYql/GNJSfw+eK+D3Ef6ysSLbEycc/xKEPxk1trsT6LUmi+O/cgO21R4V7Ztoo7bt1/b3jUJnjHcc//NvfAB/8tmr8EefvlKZow0hFGFlu9w/Kv2mpf41tOj7Pcip18Z20mIUSY7Dfon2WVDGiroe6q6DpkH4+94UQjjYgXhBilYt1SdMwt/Owpla6h/tW0j63wM9v4MQtuPFidDrL/yLtCPoFR5wXEX4uwPGn04GsYh1JjuLkIkefzuimpb0LyJH5Qvp7/+N3Ig5Gb+e051S/1E6/rrwf+nvP6rndv7mgd245cHdaQ8dGXc+HP+9Pu7wffGER61Svq8GqNl97dLLv6snXIdl0707e6/blXdsG7D18Kjj/KonWpS2DpJVlFVgGVP9ieNv67g2XTOmicPEdmGIw8UDyn37ePH5ncv9q0fauYaFP7PXoSfRO25NCffrOyqPiMNZTJrT1R1VoA97wSjofoik499P+PvN+IRs7K2tx8J2BRaHL/WnvfOdw9BY6k8EgM42udo4FlFP9fdDOfQfF2kY59eC2uPvNEmfb129QEzFkrjqi8HxX5uxf/beqSf3bq/cer3V3UpAHf9OvsBXr74HQJT2/bqv/kKd91tiub9e+l2v1Yd3/FHv9V0CgCSOvywq/LXFiZonjI5/t0yelvt3aUkXjdqg4MkCC2ehKqgBICTnuLDdR1ST1zF0DechS+P8gkDCFarj7+lBiX2YosJ/qiP8Sam/I0Is2BrnR17PBSL8ZZ8FFABKov/N4WFYMDj+o+zxp4n+j91/JVZP1fBHT9zQu++i3zxkethIoX/X1q9Ifv6mqatquc8/NfBtPK65AQC7FtrG27ahvelVS/UPQ6m8pzR3KbPjrwVBAhUJ95Oy12rY8kMc7tyvfHsfj+QP+aM79zDZSFskY+HP7HXobiAcF7U6GaOFPiewFnX8J8zp6okef0sX3FqwWLuPWKehWoFjEImN2DlcgYWhL7h9JTSvI/xJuJ8r29HvEaRf1G7H6uQoP0BJUJ9AJNSGdi1pj7/T6fGXqhB02ySheiJrj/8Iwv2I478rj+MP4MHVR/Zur33kBpt7lUTp8d8P8y0fN90f5xMstkN8/vK74m1KTPYPggCuII5bzUNbCXPM0eMvG0qpv+L4DxJrA3BJGb3juqi5jlH4t/oI/ybqyXGdQHJRykLLURzuR4R/v9fAp8J/wMjBzjjMYXqtk46/Nhqxn+MfhpiScYVUbXpN5zniz4uHAAu2FvXIez5PXPu+wt9vATs3AwACKXCHPAhNJ17Y6Y7zW2gHIyslf3Amfm8P3Sd6H//4SbHwv+y2pR/rR0cwTtaTx0gZ4qoLddvG1fGfGZHw94PqlvrT8YyeI5S/FVlHN5pT/enUieLnnkBboOiS+nmUEvj6K4CPbgSuOQvtQCYc/7UOO/5Vhn6u6IJUFXMyhoGFP5OZQJ89LxzUanGolgOpim4KcYXTHX9S6i+CAhfcWqm/4/T66AGg3cdt9FsDQrWI8J8WC0PPqKZlq0Fn3zy6iCJ9wE93+wFgm1yTHOUHKGXA9U6Q2bAXZ1IL92vUnIQD7LXjRR1nIqvjr47za/qh/dVU4vh3S/1XT2YT/tvWHNm7ve/ML6330itQ4T+9H67bvDOxyRd/elfsrJWY7B/4avZEzXMTYY598bVwP5q351LHv1ilguL4O7VI+Muk8G922nUeQfJz2YZnHs1jaVFKDHL8+7VNkEofaWrn0cb5BaEcajRU4pzuuFrLUZ9zcGtPdM4HMCcbaHSDEpVSf2lPGJJ9oX36iZGnlIW4TWYnVqINr7cYBADTTvzYxRE5b1t2x+/thtXRvhx7+PqecLn5wd3Yurv/ub9s6HtGhVTvvgbto7br+KeF+42R7h+Z41/lUv8gVN16z8nv+He3q8GH50eLkLYXpdIWTFL3cfsdwN2XR5N6rv0PtIMQjxWq47/WjQ0mDvirHnRRh5pr7Pgzex2hPvrJiXpr21rptxHS4z+X2uOvhfsN7fhr4X6A0pfer784JKFaganEVnf8LZT6y67wr2nC3xDsR0kv9SeOvyjq+KvJ5HVXE4Khj5ofv7fuZNJZNULE1WTBqoRUqOOPaUzWXPNCiYGF1Y/BThm1dUy1dwKPlBfAhDk11f+aO7cnNmn6Ie7tBv2VWOofasJfn+LQ16UGtFT/hlLqTydihAMWtQZBs0aEF52HWgbHf1H0KfVHSttHTc2fsFN5FO2bJMK/Xxq9Q6d5eKYcD3UfgeFGV5lS/WnlkdOvfUtrpemdi7Rwv2EXR3Voqf88yKJsv8/S/CO9mztkdO5uO3G1xAoRf55LH9uJ6By3ZzF6TWuuwLpO69HKiRqO3riut91Pby+v7zsLtJLNdM6kI/1sjUzrQsu3abjfODn+u4nYb/qhtWNEh4r9qr1+vubWu0MIfz+UWI9duKbxDhx69pHAvT+znuqf5vKmur97tpDbDyFsL2Kj2KJsssahpf7Vel8YbfGxlj90suqw8GcyY3KHap5Q3HSl9HjnvcCFfw/85r+Sjr9J+FtKo0/0+APw6SixjGO0jCW2XiOaxY2obaC12F+cpyEDEu7XKfWnQYme9NWgNJkUKdvkavNYRK3HHyjg+Cvhfi4aniawghbqQVzu62UV/qRUudERLtYDtsg4v11yOnOZPwBMNer4VRiP9aMjFK0zT8L7ptbhmrseMW720K7OZ80tz/H3tUoUIQR8Up7eHpTGr4ztrCmjJgURlDQ7Yhhoqb/r1lDXP5cd5mW02GAU/iLl8+CpbvrQpep0AbJzjNOcg5Cch4JQ4pOX3I63f+sG3LdjHoKK2Zqp1N8g/IcQD8ZzOqk88vqV+mutNL1zkTLOL7To+Mf72X1fAUD0W4yaixfRdnYCHn2yaNId5wfYF7AmtuyK39f9Vk4ox8fzjogneix1uT9d0J40CH81Ob1Ex1+56Lb6Y5YU3eUvy/VvVdnx1/rz6bGQZ5zfP3jfxr5iV7RY+o1XaaX+xY/ptGyE1HA/GtYbtLDPrt/AE+pzrBJkehQL/0ohpVSOlQY7/szeTBgiMfqp5qpl9IoQ+eE7gWv/HTjvZEU4zWLCLFgn1vRurhJzBVL9iRvYcZ+oePH7iJewNUD4A/BrJLmeLGjk2kWlhN7k+LeVct8H5T4J8b8d2cL9gOHDq6grKZ2o1F99v1toBIY+30F4DQDRH/qG8OEgtDZ6p4fmSK7JGOwHANMNF9tBxCJZRLAOES57ghp+82D0sxwBvIj0/j7UFQ0lCn/6fndbUNq5hD8d56f2+AuPOv4Fe/yV6SLpPf7znWNGeS+7u5om/OmoPLSH/1zKpOMfEjdckvyOs6++B5+97E786KaH8G+X/hZOQIS/yfHXWmUADLVAYaricpXzUJ/fnbbSYDp2hkmpv4MQC0PmDySQQ5T6Gxx/340XHadE/DqPYqSfqcy/ywlH7Ne7fdWd25dUECwopf4Gx79h11WlKLPdlRFv4yOQRiX82xXu8acVCJ7rKKX+uRLzaXBee06ZOGHjmiL3TPdZddHukJnrEpusFvEC+TAtWnsLUkp8+X/vxnv/81e4b0fJY5U7UG3vCMDjHn9mbyYRBCUMF9zU5br7ivj2jjicbFZOKiv5PbrjoACsxtzwFxTU8e9caAdkH/vOzyZOm/QMpf4AQiL8RWtI4W8Y50d7/D0EmntaxwNyvfIc2+Qac1aCVjkBAAvDXtSGao9/XX+/gzamwlj416czOv5CaAsUJST7a47kmoz9/UDkaO2WsUAoVfgTAfjrLQu9OIEnH7QGj90/bi2JHf8SU/3byQWprMcOAK3Uvw6XCH+HHE9Bn2kVWaBBosKtoeYKtJB8f+e6wt/g+PsiZSHIUuXRwFL/To//w7sX8aEf39q7/7xN98MhnwnjyE6D4z/M4p4f6oGtnroAieyOf1zqr4b7SWmpnJWm+lPHP8hW6r+zJ/zJaydHW+pPe/c3rFKF/2P2XYED10T7Ntv0cde2WSwV9LUY5PjP2i71TxnxNi4X3QAwM6+et8sS/r6S6l+t10/v8R823C+A+vlUx/lZKPXPm/A+pwr/Q3cnhf9KkB7/kto8xoEf3fQQPvTjW/G9G+7HGReVWHVJUBakHEdrQRmPRRoW/kxmgiBUEr/huKinOf59gqtSS/2J8F8jZod2qR3FaeuU+pML7r7ihYZqmZw26MJ/uIsz2q/aLfWvK8JfDfdbQCMh/LfLlFR/t4aum14TAVwEw1dPJBx/Fy0t1X9Sxn/EJlasyf7cWnq69VL/hOOfR/i72IMRCX9yrGwjnSOP3W8FHrUmfo0emjE4/pZT/WlrR/e4Vqpl+h07UiYWq2h2nlOjCxbtQuOlaOWR63mp4X6zQfQztxmEfztN+FPHXxQI95PqImm0s+prAAAfufBWUFxHKI6/qE8hgZKREb0nw+ynqcc/0XKUgqTHlySOv6M6/oCdNh5BPpvd7AYAEH0mn1Dh3w14lN4EetVGaPX2cTSl/vG+7q8JfyEEDls/TbZduoA/NdV/UI+/ZcdfKbOl4X7VEq5FSDj+86Mo9a+WaOnX45/1vfZDqV5/Apiq2S71z9njP6vmc2ycuymxyUrEZgk7/iqb7t2BEz99Jd769U14x7dv7N3/418/NJJzgD4iUg2dLP3HjwQW/kxmwpD2/zqAEKi5KT3+ux9AGrNy0hyyNrmmd3MNZgs4bclwv1BQ4Z++KCGUUC2z4y/rsfB3hnT8AzrOr/P61bx4QoKLUAlEXJQ1PCD3UZ4jNdxPiESy/7AX3lIZO+ih4amOv/RbWEFWrxtZS/0BLaCsQEm1ifZCz0lvSReLqOcq9V8qx39XO/4js3Kihg2r49fowa7jP6JU/67jT8vT+7XJIGhHScaIXnMfnnIxJ0i4Xx3t4dtPtLGijuuh7mkhox12hdFrZXL8g9Qef3Uc5tCCMExWHknlvYsWu354kzq3PQgl/MX4wtCpDyr1j96zYap6wlAd3wjhKAuQNUTPefODu3Dcxy7HKz5/dc+1DuZiUb1brEDNNYX7Rc89TP5AAhlfddFk/r49/gbHv+a5QD0W2FOdkX7WK44MUMf/AK3UH1AXA7YsYbI/fS2Mjr+S6m93wSQt1X+cHP9dC+pnbWYEpf5+KO203FhCd/zp34qs73UQSARSvQaaUtpQyiv1z+r4m5gm10zc46/y+cvvwm1b9uAnN29JfO/u7eVXQSUXpMZvpCgLfyYzgU/Famf2vCOUOd894TDzu9TnmcNEBsd/zmpvbSAyliu3B/TWApAk2d/xh+w7UtLyo9evXlMT81vz8Vi3yPGPw58A4BGkhPsBCfEydACTtoiiC//Ab2EF4sWSzOP8gMRIMmvzvoGE2w+IXI7/dMPF7iVw/He14uNi5YSHRxFx0HMAy0z1NyxIUYEc9BNZmtsPQEv1V6d2zA75fkcuNc3xiMb5mcL9dvvRz3wEq7BHqsez75gX9vQFqaF7vyXtne8cp54q/LfPNo0XkAHJGnEHCf8ijr+fXMz16vFnzu0I/2/+4nf43Y553Pi7Gbzy89egHYQIdsULFjtEnEhPe/w9Ee2TFcefnNdbTvz7Z3X8uz3+NddRwkW7FRPDTmjJA3Xx9zcIf7oY8NASOv70tTD1+K9olOj40x5/6vhXSLQWQUqppPoDo+nxB6q1eNLX8c/4Xhsdf+up/maxlxqWOJtB+Mt4YZdT/VXu3j6X+j3TqGPb0L/HnitAYkY43I/Z+wgD7SIRUXlioCTmdy7CBgr//o7/aswOfUHhkDJ60bngDpxs4kUoJbbmcD/RiB3/Wnu4FUja4y87pf41Vyiu5eKe+CQnvQnsmYiD3mbkNNrwsM+KwX3KDbSHX/kOaal/reOsEuHfmsd0ZyRWCAGQaoiBaCPJhm5HMEGE+m4ZuXv5evzd3uOi59ttbdcSkJaOXS3q+Hs4YE38Gj20azFybFxVPNpECfcTBuHfp1pGCfbrhK8JWutPFizq8DE35PEdSL0v3U3t8Z9pR/f58PD37bfg7jA+hn45+QzzD9BaUIZ1/OkoPOEmS/1l4OOROfPr2e3bBwCnYSr1tzPOT2pTHACg5sXHt4cQCAPcviWubHpgZgGfuPh2SDK2apdLhH9ppf7xc7SJ8HeyCv9Oqn/dcxTHf1p0Hf8RCP8+Pf6AuhiwdUmFP5ljbRD+aqq/bcef9Pgr4/zyX3RX0U1dbIcJF7k04e+rr1mVyv1pq5frCCUPJqvAinr8VRkz4bm9FrPFdlhYrNHSby9Lv/fcNvP9hGmSi1TFz+hSoi+KUa7bvCP1e7agCz2u4yiOPwt/Zq+DlvqH5KNDw7/aXWGQIvxn5QQgHNRIUmYPvcd/6HF+NPirk6ZNxEvYJ3/AISLMqRkuuKG62p6fvjrZj9Dk+GuienF2Jt7em4Sz5pDe/7fJNQCAE0nquwIV/qI9/Mo32U8IDw3PVZ1VMopuHpOAk+OUQgTWJJp2yoG70OAxRBf5a/OW+o/C8Q9DZXFlRzM+LlZN1LCi4WFlp6y26YfYtqep9NzbLvUPjaX+WfMxkuMn6cUcrUKpizZmhxT+YYjECDr92Oky047vuyh8Bk5ofQrPaZ6JFzY/hitXv8z8A6ioLtDjr4T7dV1wWuoftrBjzvx6dpP6AcAb6Ph3hP8Qx7jSctTZx1rNRVPJ8Uh+xr70v3ejPfNg7/+7PJI/4tCFg47jb+XYJrkoXgNBpy1KyEA9TwVt4OJTgB+9G9i5uXd31/Gvu45W6h+9B8MuROWBOv4m4X8Aue+hJSz1p9VXo071p05qnVwnSJmvz/+Tl9yOJ576E5z+w5ut7l9RZhaS1x/9xE4R2po4rdJIP9Xx10PUsqf66zjSV9pTip576CLNQbU9WIvdnZ9t2EcpU4X/ThmbIpOShb8JPwixgwRfnvLHj8e/nXRk7/+b7i3f8dcXerwhPpdVh4U/k5nQUOoPAIEgPTCtAcK/E+ynOIFdqPDHnJ1Qrd4YLSr8owu9G3+3Ex+/6GY8cMFpwAVvB+Z3KGWjwjQ/G6rwpzPs8yDDZEl1zVHFS2tuJn6ANwl54NN6juUFwTH4g0PW4DH7pjjsxHmP8hKK9ymH3XF+pLXDWSDC35lGLojAaoh2eaX+Hed+dZ5S/7qnOf4lCX/q2Lt17CGu7cqJ6LNwAAn4e/pHLsVP75oxP94CigMskn3pQZ9FMzXRPxL5tExOLfX3h3bSA8MIusS0iQ472sn77pP747fyIDxuw8rE96Kd00In28FQf/BN5yHhxYtPImhhx1x8wb+S9E1Tx9+bMBxXZFFyqlNxM8zCmcnxT07uaGGnlkIeSijCf3eN5I+Qvwe94DwLxzZ1/B23hibIQh5ZsMWN3wB+dhZw/VcV4d/t8Z9uuMaFE+vhohpBKLFtNv77st+qZKvJhso4/tlT/a1WakEvtdUEYY5y/89edifagcTZV28uzVEfBtO+6Cn/tkiU+ud0/P0gxJV3bMPDe+x/Fvv1+Gc534ahRCijdiyFxd1quX/BBb2uEHySuBuXiL/GtY234Qlis3kfF3el/k3+Tbixd3syoKX+nOrfZcd8qzfVaO1UDW8+7tE48Ukbeq3B9z4yj4dLXhBNlvrzOD9mL0YJ9yN9nEr//IAe/zmZUuYPqOP8xOzQDozi+JvGaLVbaPoB3njOdWhddRYOvPFM4MavY/GiD8AN4wsz11RiC8CbjAVDIxyux18GyVJ/x1GDEv25eHVT1CZx2P5rcWLro3he85M4K3gFXvXUg9J/wOr4eweK7UOLLEFT492kwHIX4lLaRcf8eqVSK7PUf6Z3cxjHf7LuYhdx/CV5PqvQMmW3gT2LRAhORJ/ZA1arju9CSERZv577IQgNC1Khcuz0+aNLxFe3x18t9VdD44Z1/E1J9DXXUadNdNjeNJ9r1k3X8f8d92jzDzCU0Q/jGqmVR8lSfxG0sWOuiT90rsMXa2fiL/bfnPi5ALButSE3w+BYD3OMh0GywkMf0SqDNmYSqeMSU63tvf/N1kn+iCHcz4aodmigo+OiiZSWl83/a3x8t9R/5URNC0fsVEyU3ONP8xzWTtWMAbdVCfej75c51Z8mp5fX469feOcpAafc+8hwC/RlYErwH12pfz7hcuoPbsbrvnotXn7W1aW/z46ywDP48d1FoEmhHSfNXcrCVNEWnu5iycdr/446fNREgM/X/s2c9t+nzP9meVjv9kQ411sU5R7/mEdm4/P4+hXR9ULDc/GUg9b07tfDcG2TyJ4YogWl6rDwZzITErFKHf/QFJyXIvz3pI3yA4DGasjOmKVVYgGLi8OtghtL/R211P/h3U2489txSu1bvfsnfv0NeAEJqjPNzwbgTsYX4pPh/FAnA7XHn4h9csHtz8cus6hPYeP6abRQwz3yAADAS37/Uek/gLQFHCS2DX9Rq4wkS6b6O2H8HjXdnI6/wVm1hsHxzxPuV/ccLDgjcPypg+7VsWcxvrjqOv50pB8ApdViYdGuOJBEQHU/l9LN1iajlvp3HP8yevz12fPCTQ33e6SVvA8ATnvpE7HPipRwv5raJgMMKW5C9diJdpUI/7CNmT178B/1M3Giex3+7uF/QHRqlNhXzPS2m1qlTvMAoPaod1Lph1lIURZ6Ou+3qy1AtlvNhCO5CvO9xYk52YCskWOF9Pi7Fkv9BSnrdTxPFf7U8b8/OTfbdyawgOh9XTnhmcP9Snb8lWA/Q5k/AOwzXe+1we1aGH4aS1EU4W9M9Y/vK7PHf9gLb718+p4+gWGjxiTyRxXul7fH/5u/iK7jHty1iAt++eCArfMRKL3Uekn14P3sfha6C589mnu0gD87pf4bxdbefRudrebQvz7BfnfLDcpEqG4oMgv/mO2kIormVx17eNxK9uEf34KLfl2e+NezJzyXhT+zFxMaykIBVfj7fisSM3vMfyTm5CQaphF0AOA4kBNr4v+2hxNbjsnxJ+JFBi3sWmjj77zvJB57aPOO3m2vYRb+gqT6T2NBmXmcmTDptAGAT15L2YwD5bzGJJ5+2DrsuzISK284ZmP/0nVF+G8futxNEEdQuh6EEMprSWm5OYL9AEO4n0VHgTj0u5E/3A8AwhopBW/uiZrLbZNw/JPCf8Mq9XNIne17ttgNu5GGnm/pkEC6rvDffBXwrZOAX58XP1gJ94teayel1L8Of+gMDz3VP3L8hbHUfy6M9n2i5uCkow8GALzm6YfgJb9/QPoPsBSc52gjB6NdVYV/SJLxBSQOrM3iILENq0T0WvqNNcCK/ZNPTi4gpzqO1zDHjyTtW5JcDtDXcmZ2Dt3rnem6i8fuvwL7ibga6WG5BhPEYaOp/m6v1N+u4++6nlrh0RX+e7YaF53nvXico+74T3YXMEru8VeC/QyJ/kBU9bXfyqV1/aWUykKxSfhPK6X+5TnBruOogjBjqT8L/wg9RLBIqfKvH7C7+K33Uudd4On+Lt1Wpx56qX/BSoXufs5BPWaN+9hnlN/v5AaAXN+uEtFC+VDXj2MKFf7rycL8yc/eiMcfEBluoQT+/rybhq4YHISN7Imqw8KfyYw0jPoCDKX+ux9QR1kRZjGJibRSfwCCJPvXW7uHmjtrLvVXxcue3TN4pZssCa1L0lubUuoPIvxXiIWh3CxTqT+gOv6OIvynMVX3cMnfHIfvvOWZOOXFj+//A3TH30ZAmZN0LSltr4DjL1p23a2CPf4AMNmoY3dnBJyABMj7YQ1aqu/VzaX+muNPRVmzadvxpwtSyUWznuN/3l8Cd1wEfO8vgblOyTd1/Ds9/k4p4X4BnM7s+RACcJzEdJEu8539WDVRw7++8sm45V/+CB95xZPMGSNdqOOPruM/RKm/cuxE5zxBxvmJsA25Z6vymKdMbccTxL29/3sHPBkw7SuZLNJ1/IdZSFHGN9IFXHJ7x+5YNK2ZquOEI/bHfqQi4WGsVcvWDeF+RS9upZTKed11Pa3Hv3McPXC98fFzbiz8V+mOf4GMhDxsHZDo30Ud6beQul1ZNP2w12dbd53/n733DpfdKq/G15Y0/ZQ57fZu+7oXjBvGGNN7SYBgSAECISQQQkjyJV96hwRSSPnBF1IIpBBqEnqNaaYZ3Hu7vZ1+po/K/v2hkfa7NZJG0khz7rXPeh4/njNnZo6uRmWvd613vdDU/mVimj3UXngJoWQBj2hV75jyd/noQgML9Q7ma+m2RiXBKIm/144+TKo/neyRBrw9/vR7jlJjd44F2hYFAOispWv1722M42ITz/sci/Vgq/9SYTsYyYcah32/zIrAnolYqPVb/QF7LfSh11+FTT3hq9Yx8MDJdI9HB94ef22jx38Dj2dYAWRVtvrrwOrhwM+ooxis+ANgpM9/gtcS2aAUv95a2qdsdNFeOYkcC78hBBL/PCH+aCcirNwv8Rvy6DRNFxe2fNHelqlKHlfvm7FnUYeBEP/tbCFx1ZtxsiDp7UMaUEZhUoU8CjzKaqrjtIg1fxUVlPNqcLZEAMoFzXULeD8zNRDizwMUf68tuDouSJ/eTZv4k3Ye5lM0c1oB6mKUG47f1tsYGu7XS/VXqNVfDvdLbPU3/J1HptJ/XDoFiPGi7VYp57Vw0g/4K/4Jzh+/AiQtmimWDqUhE/9X7mnjfEYU6y0XB2xj0Q3RKzIdKkzUk2RkEOeRKbUcie9qmRD/qUoOzzx/EzbDo/jTa7riF+433LltcfFZgF1A8bX6H/En/muKWHBPeHv8RxTuR/tXHeeWH6SRfuug+NP9UAy4V1dIEGXaVn/DQwjTUPz/+7ZjuPpPvoLr/vSruOdYhqNZIyCI+CcROQZhWKs/xQMpE3/6PedUxUOwBm+n85o+q3/Kir8epPj79vgHK/5mZTNQ8CH+7Q3i74Aq/t5r5OxYwVX9AWCpnqwVeBC8Pf4Ki9eCciZgg/hvIDKsgEWi5VX8A/r7AaDOS+EEzBPwl6Qa6tfjz6lKbXbRromFa537qy+5YjTFP4maJff40wkJYt8Uzbr7OF+KaaP3Kv5Jq8qkBxi9fakGEf98zG2Uevz1xNZvX1CrP6/EtvkDtqpV4xmP9DNl4u/cdPKq4qqo52wac0Xf2bECNk+J409PWfG3SI+/24KiykWzvvFuq0d6G0Os/txH8SfnYA5m4jBHKZCOZo0o8ndsqXn39457IhLUnEuqc8yECjOZ4u9TgKRWf8XSUWjLCtGTqkt45S5ynG2+KODDmWT3r6CdqJBiSsVcWoAUj5frhPiX87h81xQurYrj7iSfkl1cfuF+Q6rpumlJ7R2MecL9nAKaT38/AKwwavXXPFb/nuKfcniZF7SoNxFyPEoj/dYh2Z9+V1Q5pUiTWHlBF9c5b+hbRMXNTzAwLY6OYeGD3z4w9DYCwOGlJv7gU/fgC3efGPxiAj/ir5s83Ywb2Kn3XoXSN5AuBHTscq1jYLmRHtkKU/wjhftZHAxWv9W/4yX+w197AFFEduCv+AcT/2qlCBSJ86hn9U913XOGY4GQ+ZlK/zpzmjy3lNEkjPAe/0z+5MixQfw3EBk8INyPk4WeZXSBlWDFvxEW7gf0jfRLspj1U9ooeYGpS6Py7uG7ccgiqdQAbrf2QZsMCM+TbLbJrP6UUHNaOCGKf8kSC+5COSapLk3BytnvqbAOct2V+NsIQKHE32ckGQXPD6H4Z2n1RwXVGIn+Dsp5FWvImPiTsDyTENeJkjgmtlVL+P0XX4hnnLcJ//iaK6DlBTEw9JStq9Jx6djTyYLH7Np5BxQLD9r/91H8lYBU/zz0lBR/6jySyZSpiuNrIk7hhzEfN0r8bfXLGlFyhPhzXUrGBwBl8WFsaz8kntgSQPwBT7J/MuLPfcL9AMAg+3KlJlv9FYXhhXvF93qKV+Vxf7THv+eqGvbcNiwuK/6Kgg73KP6WCRz9oe/7l7i4No0Xc9L3W3JdHdkq/mtSG48/oQbWf6SfNMrPJ9EfAAqa6H3VTZ7qLPLQHv+E4X4U3tGUSfG2/7wN//StR/GzH/oBjq5Eb8kIsvWnbffXfdTJuIq/d3ffdSy9e6BXWc0TF2OU48mweL/NHwDaayjl03OkuD3+fVZ/n20MSfWfKucAH6t/bUPxdxHU4+9AIv4pFqEo5GkTClTiYHO/c86BtXTDLkeJDeK/gcjwG/1kPybE1ewCZLa7F7biH5H4s3qii6IqKW29xSFRG7nVhd5cEducG8cXrSvcn79pXoif7P5fFHxCjQBIiv84ayVb1JKbBleo4i8Ws2Nc9EyXyzH75xmDNSlU/4lOsosUI8SA9YipEkD86U0tEiTFv5Oy1X/FfbjKKxgLWWgHYaygYY1nbPUnir/BxH71KtQ/9aQ9+MfXXolLd1aRo8Q/das/IYK+RbNu/35Y6AViSuF+4Vb/YcL9pLGiNGTUY/U3CPEPI1q+8EycSOJOYCTnhLnhfmIxo1g6Jo1l+U3HbhWz5xUNmDsv+A9QxZ+1k+1PnzBHQM5tWWuI69BULydjllj9T/IpPGGXuG7Lqf49tSyFkVreEY59iv/iw4DeK1Iw+R6zaInzuE/xZ6Mh/jS/I6wQtXm9Ff8Bif6APaazkpHqb4ZabYcn/ntmY95LA/CDg+Ic+Nr9wYTPiyCC3z8yczj4je6LM87PtHjf/k4z4M+b6k/bSqLMtu8aVr/NHwA6q9Kx2RrW6t/bTm94LJ1ohLVjwId/HLj/s+K5a3/Bffhu/RW2+OCn+G/0+LuQiL9PO9QoiL/3+kMEf/G7A98Mbes43RF/NbyBxy0ke3qQ4q/rEunyooZSoIoAQLb6ozG01V9xQrXoGC2jC4uQl9L4FN7TeBlMKDjFq/ig+RxAzUkXGQlSj3/CcD+qpNMiCtmXToAZAJQrMdV0AMrULmDhHgDAtH4ClsUlO10UMN5v9Q8i/qwQk/inoKoGgij+a7yMTUFFnBBsq5ZGqvjrhGyFEdVcQRADM1PF3yH+tE1G71f85++3/+8zzk863KRwPyNZTzoAiyr+0rkjkymdib8XZq32hffYTHCO+yn+ao66J3QpHR+AnJ0wu1/aZ33wjPRbTrA/abgfDyjm1hpNAFUAEM6ZmtjO/WefgxuvFkVG2epvb9OwwXmGxd0igv03VE+4X1suOG+6EDh5p/vjskGDouRwv+KIxvmttfrzO/ywdb17/CMo/oDd57/WK8w3uiaqAZ1xcUHt6F6rbdRwrbBsIO9s+zQQNXsAkAm+pjD335S24m/4qPtReucd+BVP7kqR+HvT02kLaEcfvJ3NrukW7SS011Aupmj17+2HHOT1yQSvizXVd98H3Pdp+Y2XvxY3n1BxywMH8E/m8/ATlTyQ3wj3C4Os+PevM6n9fzGjHn/dY/WXFf/eMfvQlzP526PCBvHfQGTIwV/iwsrJgtsyuxLxX+EVVJmwijZ4EU87d1PwHyGp/lVWT1QNlSyhPbIKT5q21RIBP+OT02icLOMdxo+7z73qiTsD+xu9idrtBISVSz3+pHDC/AlKJRHx3+0+3o55NLpGvF5nyIq/E+4X1OOvlGISf0Jcxlg703C/oJCqMOyaLmNthD3+OlEww4hBnhB/y0iX+NOCFPcpmvla/VcO2Wq/j+IvFZqkHv/k4X40a0RuOZKP7bYi9tPEMIo/6ybKyFBA3TL2vqTnDjN1KR2/D0H9/Q48in+iBSTZlzwgZLTeFAWdmbwJ3P954OTd7nNvftF1ALVlErU9PcXfa/X3UfzpcTm2CSC5iZoh8lICx/ll3ePf6Z/Y4Qeq+J9ahxR6eh0uhxD/rJL9KTlNMuYNCFf8hwm4C4IVI+17jRD87VMlHFy0z6+0ib93lB8Qr8ffbx+mGYzo7fGnTtAooc4t3XDzOSR0aihPppnq38vdYfIxPsXqMCyOvMKApUflN531DGDmLNw0eyP+/p5HAADVcg7QCPF3Ff+NcX6APbmFkvnBVv9sro30uPSGTrrn+fiWTP72qLBh9d9AZAT1g0qKv6mDE7X1EJdJ/v5d2/DyJ+4I/iNSuF8yxZ8qbUrPXsw8qiXrihtYvjLZ18v2lqefHfwHtILbA5tjJjqdZvBrgxAQ7udVLR2UKzF7/IG+ZP8kbRN+QYm5XA4G7790aKXJvudCIbk76ukRf84l9bmJojxuLCJ2TpdHmurfpcS/EEwMCpT46ylXvX0UYOaZPd8/1pADiw8BBu3x9wv3SynVX/cfK+o9d2qG+HnndEw5UlL89YThfmLxqjjBmKTHn/EBxD+svx/o6/HvGlZsUsN9Mh0AuQDpEH8FFp5/51uB/3ilfAyMb5Y/1Dfcb9hkbQsaowVd1dPj35HPz8I4cOmr3R8/0blabG7QOL/Mrf403C+4EEXdKeuR+C2n+ocr/g7STPY3+3psExB/M3h7siD+ceZ7U4K/i1yXUu/x9yH5fsWAIHhHIgLAYor2au/YRknxj2D1b3RMlOHjiOkL90sn1T8P+fupoi6+9yZxG73or4Gf+DjAmBSGOOW1+rs9/tmMcjzTsNrS3SLLWEHzvfbMjFHin32Pv6owqH6OI2/A8RmGDeK/gcjgAVZ/eVSeDqMp7KvHFbky9pqnDZihLYX7JUv1V0CJvx956UIl6pBWruJFl4ogvxdcvBXbq2Lh74e2Im7YRjP+mBvJ6q/4F1EolHz49vjCk+y/luAGoxCrv5OXUNAUGOi/KGvlmMS/PO0+rLIGml0jnZFGZhfoEY4uV2FBCexVDYOt+JP9njHx7/BoVv9SiZDYlBV/P6u/4lGp+xR/wO7zp+F+vNfjHxbul3BBRs8davXnHlv8ki724cXbYx6bRPEvpBHu1zt3qNW/iC6mEaCgqQXg/BeF/wHJeWQfB3GLKX7jGwE5aLLRshfXb1I/hbmF7/lsh8fpI/X496z+qYf7eVP92/JxWZwAnvX7wHVvR/el/4AHra0AgLzWm5bho/h3DSsWgYsLqvSGKf6Vgth/9bSuiTFAizRRFf80+5S9oW9JiH+YVTzNIEIHVsB39N+3HcUvf+R2PNibOW5ZXCL4tCC5mnaPv8+/c1jFv94xYrkbwtCn+OfiKf7Nrtmf6A/Y4X456kZJJ9W/gH7F3w1QbJKQ1h1XwBnDs0y+06lyTh7n56b6myM/x09HDLL5A8B0Rdw/0yxCUfT3+Ptcf7p179vOKGwQ/w1EBg8IgqJklXsU/1p5p/QZpbFq+B/xhPslUTxUSfF3kujFBYNZumT9LFSm8Lon78HsWB4XbJ3A77/kwoF/Q1eF2ma2EhBCKdyPOCYCFH+qUEUGIf472Xwyxd/qJy+FnIKuT5dQvlKN9+GeIo/Fo93wB8LHcp6G4m+FZFckBrH6tzm1+gcTgyJR/GGle/Oj57hzXCqeoplvAWT+AcllIaz+5DXEdZOHMcQ4P3/FH55zZ6lrb7+mMJy7Je7ECY/VP4niT4iqkzVCif80q0NlAQu+Z/4eML0v/A/QHn9mH/NxC6VBij+9JuW4gfPZQfyS9rH+D5g5213kuqCp/imG+6kS8c9JDpk+q39hwrb7P/N3sbJPFFBcpZ0Q/7IiFudZjfTjnEvX37DCnqYqbmsS59k7EbxodcV+DiuYVkgrXJp9yl5CmEzxF/+GsYKGs+Yqvr9LC37bdarWxts/cjs+/sMj+Nl//QEA4GSt7RY2quUc5oidOW3l18/ZMGyPP+d2MSoNyOnpstW/a1gDyXCza/in+nfWJDfK0EXH3n7sU/xZHaZTSGkuil+UZ9yHK2SChB3uV3V/nuxds02Lox0h0+CxjvlauM0fGE24X3+Pv4/i39kg/kODMTbDGHsDY+yTjLGHGGMtxtgqY+ybjLHXM8Z8t5Mxdi1j7LOMsSXGWJMxdgdj7G2MscC7FWPsNYyx7zHG6r2/cRNj7IXZ/eseOwhaJEpzvk0dakcQA32ChD4BUjCeL9II90O/PV0hpEOxdBQI8S+OVXH5ril8/zefic/+4lMCLzoUukaIfzu+4g8amseC+5Rd5BIo/uNb3YczbE1SnKJCUvx7ZCCvKn0JtwBQqAxh9Wf295HKItcQ9j9HFSwk6PEfK2jgpELfqS2HvDohSLhfO6LiXyCKPzO76aqUnBL/3ux5QlYVvx5/oF/x9x3nR63+ZmKywElfOlX8aY4HADR77QbnbB6PX/jR5FT/JMelXwEylxt8bcHe64Gr3zT4daTH37G8xi6mRLD652DgJ9UvIdcbzYdtTwB2XGlb+v220yfcb9gZ5Xa4Hw1L9FP8iXuCTF5Zkwh37z2kkFohAWFZkey2boleYcd1EIIxaqMfcfgXLX6EhftNZRS0RRfemsKkHtuoxJUWkJ970Rb86nPEdIwsFH+/cL97j9fca/Mj8w20ddPt5weA3dNl6Tq/lnJbh6/VP8a/PahAktb4OW+qP2MM+Rh9/s2u6Z/q316Tjtthszt057z1KP5V2D3+sCzZ6l8STkY6OnK6kpdcWpOKWKdsBPwNHuUH2IVb53rQ7JpoD3lf8UOkHv++dsczC6cF8QfwCgDvB3A1gO8C+CsAHwdwEYB/APAR5vGHM8ZeAuDrAK4H8EkAfwcgD+AvAXzY748wxt4N4AMAtvb+3r8CuBjApxhjb0n53/SYQ1C4H13QK3oDak+F7HIVuaqs+NMFmS+8in+CC6LK+5U2afa82UXJEoGDxXH7b4a2IHhg5gTx15tJFH95EesgyOpPe44jg4zXG0Mr0Q2bEn+HWBU0tY/4m5yhODEb78Mlxb8BgKejuEnEv6f4a/EVfwAojoubuN7IgPgTxb9liW0MI/5UNc7DSLcPWOrx71f8FW4EEP8HJdXDGYMojfOTUv31RD3pgJzqT/MxuCovFpx2g4u2xQydBHzG+aWTj6Hm/S2MR2eeBLz0vcD1/wd45b96rBIBkFL9e1b/mOeP7PAg1yFyTdeYiXOVw+JNT/8t4A1fBn79MHDVz/R/KNn2NMP9VI+Doq/H36v490CV1HE/xX8ExJ+2WUUJmqSK5ahJAV1Mhyn+c2Tc1nyKIYRexT8OGfR7XV5TkNfEdSiNHn+vGu1nf/fa/+8/UcMhQvx3zVSksY5JWvHC4K/4D2f1B9JzJtBtuXT1f4H3XYfXal90nxuU7N/sGigz/x5/6kZJK9W/wOR/9xTr9fi3VwDnWl+YAMj9klr9q+WcVHCk150N4g8sEuI/E2D1Z4xJBccsVP9IPf5nuNX/dEn1fwDAiwF8hnPB2hhjvwHgewBeBuBHYRcDwBibgE3cTQA3cM5v6T3/2wC+CuDljLEbOecfJp91LYBfBvAwgCs558u9598F4AcA3s0Y+zTn/EDG/9YzFrLiL27GjKjU+Y5Y/K+igolpT4I/qXj6glqh0EA9gUpNlSEnRVshoVqm3sUUE+qkEjeUDoBFnAtmK4HiL4X70SJK/wXPhAJVDbZ+B0IrwoQKFSaKTJfSuaOCEn9HtSzkFOhcAwinO8g3Y64cN0CtAOQqgN5AjpkYQyudhbcuFgNtntzqDwDj1VmgV9cxSQtLaiA9+k1TXI5Dx895QvLW2jomywmODx/IUxz6R9ApvuF+AFYPST38x7ltd5TG+Xm2G7DVTHdEXEQEWv09504LNnm/KG5/PyAV2grQUUsyzk/KGglX/M3yZuCyV/v+LhBU8WeO4h9zARnB6p+HgbPZUfGeufN7vwg438nnOCNJhyX+umWhJE1r8VH82/6Kv6/F3ifcD8jO6l+TiP/gc1VW/Edr9afX4DDiv4kQ/1O19MYOyhZw2R0RVeGjpDWvKsipYr0SZ5Z9ELyf4VeQ8Drs7ji6ihOrYt2xe7osFYHouMc04Ev8YxQ9gol/Woq/2IevePS3AQC/gTvxH7gWNZR7AX/B50qza/qn+nfrKBNmM6xjxnXqeKz+k6jbDhSq9hObv2Vx2epfygMdSvzFto/a1XM6YmFAor+DmUreLTQuNbrYNiCPKy68oZNyj3/vnNiw+g8PzvlXOeefoqS/9/wJAO/r/XgD+dXLAcwB+LBD+nuvbwP4rd6PP+f5M44n8Y8d0t97zwHYboECgNcN9y95bEMO9/NX/IsdcRFc4xVMzsyRT2A20QuDloep2Ce9xix0O43w1/tADtVyxmiJC4mld9wZqgD6w6migCy6uZ8COgg+BAuQlTYHhlLs76ONAsbQJVkE7UZ8Z4IqWf1FuJ+3x/9BvkOqskeG5PBopGT17+/xLyWw+gPA1LRwMShZ2LtMojaa0RR/SrALTE81DVoe59cj/prcJuOr+LdXgcYpAHah6lRv7rsSGO4n5n/H30Z/5xHrI/49xX/7kIo/S6b4Kz6p/jlVhc77yRRLMh6IjsOEfczHJ/7+Y0W5IvblVraIyV4QFfLjwIQIQvUFuZ5paVn9TS4vvLWCzzg/cn4WqeJPiL8zLYMo/rRPeNgCRRDWIvb3O6CKPx0DOArQ7yrM6r9pPJuxg95wLZr2HrUXmpLWQk5BXlV8f5cUXlLtd9x4rft3HlmRrP67ZspSESjtHn8/q353yHA/IBvFn2KK2feXQe6OVtd0gzm9mFTEGmBoq7/b4+8zzs/kgf39tbbhTosaK2i2c4UUS4ukaJFWMeVMhmT1Hw8m/rTPP4uAP9qCoqneViPH6p9gzX8a4bQg/gPgXGXomfH03v8/7/P6rwNoAriWMUaPnrD3fM7zmg34gY7zI7ZQGqpV7Ariv4oK5jZtgysNl6YiWVgt0l/bbSVQqaklVHPStGW7spOoam90fGLA6HuSXARIcYIqZMynx99Ui33PRQXNIugmIP6KT59y3ifV/6CyU57ZHhV9I/1SuAFSxX+IcD8AmJsVjpWcngHxJ4p/QyL+YYq/OJZzMBJlNwTBT/GXevy5LiurPphnMzB7x4dk9fdsN5BM6QgKGaUtCQDQ5AUwBpy/NQHx12RimKjH30/x15hvPoY6mYT4U8XfPo7qMdXhwOkipAB5HiM2/9lzBhchpVR/+1psWHwowmVYlnvM2B+cd9t47BfIqf7fP67j8JJ9jZds9qV+qz9dgKc5lo4iaqK/g/VU/NtRif9ENlZ/qripCnODDoFoY968ryuoCnI0OC4Fq7/3WG77bJeXIN9xZBWHlrw9/tTqn32PfxzFv5N5j7+zffJ2Ouf5oO+60TX8U/0BVCCI/7CtcHpIuJ9hycT/m8c4fv3jd+CeY2tSf/9UxafgyDcUfwpK/OcCrP6AN+Av5alG8E4VUaASzmI9Rqz+pzXxZ4xpAH6q9yMl7Of2/v+A9z2ccwPAo7DbGPb1PqcCYDuAOuf8uM+ferD3//0pbPZjFpZFL8TE6q+JRUpRF33Qq7yCzZs2A1f/rL2QfvIvRvo7nBB/vROf+EtWfx/ykoOBcXJjGJg74Pc3iuI9SpKLAN2XCu1T7r/gWUn6+3uQswjiE1fJ6t8jVn49/kdzu5NtYKnqPqyy+tCjdwDIin+vDzgp8d+8SThWylZD/t7SACH+dVMcB6GqICG4+Z7VPzVQItgj1dSernKP4u+Tu3oSQvUICvdz1JMkvY2UrEpZIx7i30YBe2crKCdxokg9/noKqf6O4q9A9xmFmZ/c2vfcQEg9/kmt/kTxp/kiRPE/Xzkonp+NcIuUFH+xD4ZR/Q2TI8+IG0Ut9PX4m2TaxB99+Siuf9f/4hsPznt6/PsX4HmyAG9lZvUXn+sWH0KwvuF+4nsKG+dHE+lTJf4exa00rNVfy17x93MieK37D5ys4b4T4tq5e6YiHQtpK/5+JD+NHv+0ChRBSrrjwBnk7gi0+gOocLFuHLZwZpj2KFGNydtTRa/Hn4zyO65X8OHvH8Yr//7bOLAo3KpTTjsbWY8V+Ea4H0Ucq7+DNENFHXgzRjTS4+8Ww85wxf906fEPwjthB/x9lnP+BfK807QZJGE6z1cTvj4QjLEfBPzqvIDnHzugFluyuFPIgr5MFP+2OmZbFp/3p8Cz/xhQIx5uhPgbQxJ/R2mjin8BXYwzSvzjK4K5klDbmB5/GyXFny64fYg/yyVX/KUsggFKrR9oMjlziX9/qv/J4p5kG+gJ+BvWlgdAUvzdcL+EVv9dsxOY55OYY71LxNIjtuqZFki4X82IavX3Kv4pLhqkVP+eWyYvbsIaNwAytQObLgRO3il9xEkmiiVKQLifE5SUhNTQHn/acuS1+jdRwJaJhOcOVfwTjvNTuemanRRNEH+/UZjFqQH2eT8Q4u+k+sdeQPoUegBIRZptjPSwzkUg/qQYpJLFcqtrYrI0WO32g2FZkuLGtHxfj7/eWHWPhjpK4Bz4yC1HsGdG2Gvd84pmOPAOGCxwKJmF+/m2G4RAtvqPlhS0ovb4exR/znmsgNwgGB6rv9zjn8Dqr6lSQGAa4X5e14BfUctbkLW42K6CpmDTeAErxAmSpnML8P93xkr1DyL+KW2nQ7AKHiXdKWIOTPXvmO51z4u8UYOmMNtpZFroGKbUMhIHusX71H7AbklYsCxJ8V+Cvd6qtQ38+3cPuc+7OTZqzr7OchMqTGgwYEDbIP6QFf+ZEOI/XRG/yyLcTzeDrz9u4OQZTvxPW8WfMfZW2GF89wH4ybhv7/0/bopLinOxHoOQFolE8ScLblrFNApV8fqopB8AI8TfTED8qdVf7Vn9NUI6pphQ6DtKSbKmRkWuJAg1M+JvI5MUf2pX7l8UsqAQrSggbgYrAfGXAsqccX6aIu1jAFgt70m2fWWRmj/FaumoCQa1+g+n+G+dLOEuvtf9uXvolpBXJwAZ57emR7X60175dHv8peOyd85qeXE+9in+my/s+4zjRPGnwTh+9up0rf79qf5RgtR8QYptBXQTtaDIBUh7O4JGYZZntsffRnJuV9II95MKkAH7LZLi32/1B4ZT/HWTS8ogyxVl4m92wchxWeP2NfPbDy96wv1671EUqcDskI/MrP5+kwVCMFYg48hGTfx1m5C8P/duXP+F5wFH/bWOcl5znQld00rtOmR6rLa0aBtV8fem+svhfulb/Tt+xD9kf+yeKUNRmHQs1DuG73SAxNvoZ/WPOA4RyD7cLyg0zwkqHWT1b+omSsyf+LFOTSqeDaP664blS/yraMA0ZeK/zMU1+Yv3nHQfTznhu4x5CrZOi9bjm/hzzj3j/EKs/uR3tJ0iLdAe/+cd/FO84uaX4CnKHQDIMblh9U8fjLE3A3gPgHsAPI1zvuR5iSM5BcU1T3heN+j1gxwBLjjnT/T7D3aB4jENHpBEzwIWiayYIE0bAMsLgmDq/hXdMGh+4X7ErjzNxAKxqw2YMhCAAiH+mhmf+HO6jQFKm/tUPrnVnxFywBJUKaVwPzLObxc7Jb0uXxwQ2hgEqce/kY6aYKTX468qDA9rgux00ib+RPFf0wVJjmz1Z+la/f16/LWcV/GnxP+Cvs84DqL4UwEw513w8Ng96QDkrBFK/D2J+S0UIpEsX/j0+MddlEtZIz3ikVOZPRHD+9qJ4cL9HJUsrmLNJKt/+HQRAMDsuf7PU5ACAi1+DENgTY/qxlRvuF8bqi4WYzXY399CvYNbD6+4z0vHAylEOZbh7Kz+NGcgSo+/eM3IiX/XxHXKXXiW+kOUa48C//z8wNfOScn+6dj9+3v8h1P87XF+aVv95WuB33aFEeRd0/a5m1MV11Vh8eGD6KRt9Pl3GnHC/QJ7/LNW/O3jaOA4v44hW/1p21m3nlq7jGFZKKD//QWmw2g3gEa/4u+FlDzvEyz6eO/xb3RN9xwqaIr03XkxXc7W6u8UpM5iR3HZyU9ionkQb9U+AaB3nhsdKZT5TMRpR/wZY28D8LcA7oJN+k/4vOz+3v/75IdeLsBe2GGAjwAA57wB4CiAMcaYXzOl493tywzYAEHA6Cfmo1IDgFaZ9n1+EBRCdK1uq29m7iBQlckZg6cRu/I0BHHRc/H7+wEgV5J7taKGDjlgdIAFVfx9iL+WlFRDziJIMoJEHo0oUv2pa6LL1eQES0r1r6ejJuiijaMz5Dg/ADhaEV087NitybfLD6THv2X1HBWeEVZ9UD09/mkq/pwS/16Pv2T1l8P9/uNgf+HsBO3xl6z+eVFMYBbyMBIp6dLseek65E31L0QiWb6Qevx7Pacxz3Fp7nzvvFYV1heM2UBJIvGRQYk/S2j1p4W9AQVIi2nA9N6+5/vA/BX/Yc5t3TCQZ3LbUZcS/04dmmXvA4MraEEcs7cT4j8hEX8y0q/3HY/E6h8p1V/sw1Enfje7Ji5gB8QTRhtYOez7Won4r6VD/CXFX5WJf1TXCCWtBU1BjvTpxkm2D0Jfqn8Eqz/FbtJ+Ivf5p/dd+6n7cYINaYGEHrOpKf697yHPEir+XdNVzAEAFTJBqtuQyONQ1x7vRBGCTm0RnFr9+QSu2iuve0s5Fa+6cpd4glx3ykmv248xLNSo2l8IbRmSw/0yIP6945LyhB3MznFo6+YZP8oPOM2IP2Ps1wD8JYDbYJP+UwEv/Wrv/8/1+d31AMoAbuac0ztR2Hue53nNBnwQpPirmv9CpjCRkPiTimgB3dgWUV+rf76/vxgArITEn3nsWnFvLH7KKgAwrb+3Sc0lt/qrZeG6oIpY5PdL7omeXVmTLxsH+ZZ0iD/q6ajXvop/8kvd0qSws5cW7wbMFG/SpHLsEJlqeQBZlYh/2lZ/elza20GJfxktwLL/Xper+P/u7L9BH+MB4X5AX1/6sOF+fECqf2Krv6fHH4hnF+WcSxMx1F7bBGMMOpO3aUWZQiLQVP/E4X7+Vn/vvgSARmVXcAsAhaT4i2vxMOe2pYvzxGA55DRFDvdrzLsP6yhh35y/k0tqoaGKP3MU/9Mx1X+0pMDXTn/Xx8XjTg34p+cBf3c1Li4IO/N8Pb47zw+UsKoKQ0GLb/UPC/dLw+rv7T/32y76nb/qqp3S73ZOiWNPTvZP71rua/VPOM6Phq2lp/j3FN6kPf5dwz1v7TcS4q83MUbWJMM4KXTTkoJFpd/VF2DURbhfJ1/FK6+Qv+vfeMH52EUKPX4Fx2EnD5zpWGxQ4h9s8weAmbGMib/jRCE8YQarYLDs87x7Zvf3A6cR8WeM/TbsML8fAHgG53wh5OUfA7AA4EbG2BXkM4oA/qj343s973lf7/+/yRibIu/ZA+DNADoA/nmYf8NjHTzAFqoE2EIrE7O+zw+Ex2YbixxwjhyjKnVPYfQh1ADAEwT7AeizLcdWXSmhVoJVS/tvJbf65wnxzxnxiT/t8XfIS0FTcKe1x33+0+Y1kRazviiJ4lAWir9D/MNCqgYhP7kVx7i9narZBuZT7Oohir8T+ibZAv0ghfuZ6Y6BsvqPyxzp8VdIDEoNZZzgM7Agk/ujhPirXuLvOW+S9fj7FyBpcQ+wU/0TF6Q8qf5APFJocTnRnpGME8PT47+qzSARCPGvJOwVlbNGSAHS55quT50d7UPpvQEWnOicYQpUnBTzDJbDRDEnW/0bYrlQRwkvusQ/LHEigPi7lttRpPpH6fFPibQkQbNrSu1wAIC7PiYe3/RO4NDNwPx9eN2pP3WfTkvx947TksK1Eozzy6tZWP0HE3/6nf/cU8+WtmH/ZiE4TGSgpgMBVv84Pf7k30iT1NPv8Zc/rxzV6u9N9a+Q9Wa3IfX4D0OsjRDFn68dByfXHqUyg+detMV1dDzz/M34iat3yW/KU+Lfy7oZ8Tl+umG+Fi3RH5AV/8UMiL8oSInPzjMTk2jYVv/HgOJ/WqT6M8ZeA+APAJgAvgHgrT5WjwOc8w8AAOd8jTH2M7ALADcxxj4MYAnAi2GP+vsYgP+kb+ac38wY+wsAbwdwB2PsYwDyAF4JYBrAL3DOD2TyD3yMgAUkQPupQwAwOZWQ+HuCteptA5siCvPcMl0aYnEGtbcIVXL+25g0h4AqlyWWRPEnpICGYfm1TVQS7kcAubIobBStJnTTkoKOBkHzG+eXU/Fb+k/jr3N/i4N8M95rvhhvCenJCoXH6p96j38KVv/Z8QLusM7CNrUXNXLsVmDLRUNtoguJ+Nvf/fapAcRfk8P90rX6+zg8cjmYnEFlslpU5yXo0HCST2Grk/yeq2C1WwF6BSPFe6jRRQ/rJApdksb5EbKa85w7HWjJrf7acKTQtDgUOv6JXC9NJp8rjVxC4q8V3IToAtOhwRhqnB8GFCCV6YgjOxmDna9rHy8KOCywoY5Ti5wnBsujWvYQf6LC1HgJ1++fxQduPtBXbBgPsPo733Eq40R94BswGIJKSjblJGjpJqa8xP/EncD8A/ZUhwfEgKUdzXvcx2n1+Jsp9PhTtbiQU1MP94s0zo8o4zNjeXz4jdfgNz5xJ87bMo5r9olzXlL8U7yW+6f6R1f86T6kKmtax6Po8ZfJWypWf72JcUr8h3DN6JbVV5xwoNWOQGkJq782PodKQcPHf+5aPHSqjiv3TPfb1r1OIz76c/x0gxzsF078p8p5MAZwbheT465pB8HJ7/A6UWbZqt3ud4Yn+gOnCfGH3ZMPACqAtwW85msAPuD8wDn/L8bYUwH8JoCXASgCeAg2sf9r7tMYzjn/ZcbYHQDeAuCNACwAPwTwLs75p1P5lzyGwS3/haxfEj0ATM1sSvaHSNpykXVjkQPLMt0OWgMK8k6PcYArQS0lVPwJgSmjg5W4xJ/2UhM10M/qHylJO+jv0ORvtFBrG1LFdBCkHv+cSCa/nZ+Np3b/yv1dOlb/Rjo2QkL8HXJQTDjKB7DnVd9h7cVz1e/bTxy7Fbg87qCRAJBwP8e6vGOQ4k/npDMLtWY6FltAPi45meKgQ4PquRHWYJ8DR/msIP6TO2AK92+/1T8nnzeJFmQB00W8N38TaiR11Rc5+RoExOv/tjiHBn813WA5aX5Mq0AWrHHAmK3698YrltGOX0iRMh2o4t9/TS/M7In+uYrmtoRoMNGFMhSp4WT6hankUC3n3VGdXtRQxtbxIp66fw7/c/sx6XeB4X6sC/DhXAlhWJPC/aKk+q+f1b+lm5jxEn8AuPuTwA2/FhhsNZ9WuB9R/HMqS5TqL1n9VQUayRoxLA7L4nL+SEx4XQPe7eoYIqxMVRjKeRWX75rC5992fd9n0eJkqoq/D/FPmupPx6ul1Y7gZ6kGoln9Oee21T9PjrmyV/EX9/yhiL9p9ZFAB6XaQWi9FkqDK6hM2AWd2bFCMIHtC7ndCPeTiP94+PpUVRiqpRyWm/Z3stzsYtN48pHXXgSFTs6xVazoFtBNML77NMNpYfXnnP8e55wN+O8Gn/d9i3P+fM75FOe8xDm/mHP+l5xGpve/518451dyziuc83HO+VM3SH80yKRggEoNYHom4YLWM2ap1ol+ozEN8VqThmgFEP/iWDX25gGQLt4ldOLfDEm4H5PyEny2cwjiT0d+jbFW7MW3RPx7ZKDg0y8flsIaCq/in4rVv7/H32+bo2J2vIA7+T7xxMm7En9WH4z+Hv+Bij9j4GSkX6vdCnlxPCiEVCuqIP5+s+frveT0o5wsuCZ3wOSyYifBk42RxIIpKf5EPfcS/2U+lrwFhc557y0A4gQRGhaXR14qwYp/t5SwQAp4kv3jF1KowwMDevyLcxEVf8DH7o+hzm1OzmmT5TBVzss9/gR1XsLceAG//rzzsN1TRJN7/Pstt1mMhwK8Vv+4Pf7ZuBD8YFocXcPqV/wB4L5P2f+3/L/HU7V0CpA03E9VmNSmlXScH2NMtvsPqfoPsvp7wxzDwspoMSrNHn/v5AEgXo8//TfOZmD1NwdZ/UOIf8ewYHF4FP9gq/9Qqf4mD+zxn1m71328jDHMjkdoy5SmifR6/B/nxJ+m8w9S/IFsA/6CClJzWLXHdj4GFP/Tgvhv4MwA7fGnir8WYKNPmurv7b2MQw4skxJ/cngHhFIVxpIGa4lFY4W1YyvVLKDH37clYS7CCK0gkAyD8Z7iHwcauSkrJNXfi+Q9/nScXx21VgoXcUPu8WfMf5ujYnYsj0c5Gbe2cmiYrZNBFf8eufaSFV+Q47ndTlPx7yeCmsJ8Z8/XuL2dNMwPkzukKRxhin+JJQv3C5ouklMZflV/I47wWbxL/zGsYDySuuoL4rwRI5eiEzDT4lKPPyXVXuJvlhMWSAGgQAL+WDt2ryht35JbjvqvQ6y6q++5QFBXSq94OJTiT1RmS8ljspRDh/lfc9pqBcWcim3VEj78xmvc8+lJ+2bkYFKfBfjKCBT/KO6osZRsynHhFLdoorWLE3cCywcA038fpWX114kq7e3xTzLOz7n2pxnw5w3Oa+mmdN2LU+ihv89a8U+a6j9FiFa9Y0jFmaQwgsb5OVb/kCKP474qjcLq71H8TUXsiy1NkfezzMelKReB8LS7AaMt7p2OoIr/TATiP1MRr0mb+AeFTs6y1V6q/wbx38DjCVK4H0lu9lkkmlAktTkWqNUf3Xi9tYZ4bRTFXykl7PH3WJZj9/hTxV+l+1K+6HW0cfmGFhfU6s/asRUFmsqtOT3+Prb5YULUeG9f5pkJM43gFKr48xyKmhqquAzC3FgBJ/g0TN77jNpxqTd/KCTp8QckYmrqnVT6VgFAoePdesUFxlhfIB1gW6pvvHInvm5d4j73G7fPSEpTn5uWFszQQS1Rqr+/Sp3XFHzUvAHXdf4af2e+FEA0ddUXnskiANDSYxQgLS65ZWTF37NN45uTbSMgKf5jaMXuUQ8M98v5LL4md/Y/F/jB/Yr/UDZ6XZwnppK3094L/tNOzJwohuycLuPLb38q/uWnr8I/vvYK+YXS5Ab781ea6RN/y+IS8YjijqqsE/F3/tY0EyM7sfNq8fi+z2Rq9bcsDtqkqTB5IkvUkZrecX4AUg34877f4rLCTotcg4qPkuKfcY+/kZD4l3Jq6sUoh2B5g/OcCSXtkO+o2TWgwELRVWUZUCYF6G4ztXA/7zi/xphwPhUsITIsYSIa8fdxGqU1KeFMhdzjP7gVdaoi7qGpK/6mf/bEHFuxj8numR/ut0H8NxAZUl/6AHt6Wx3vhTwlgKe/Ns5F2zQp8aeKf8DFJGmqf95j9Y95w5YIlhLsnmhMnJV8PwJS8vcYWvFuMJwjR8hLuOI/RFwIUf0L3dXhSaxnnN8wo/wAe1a1AQ3HyXx6rB4Z6jNd0HF+PLriz1Qa8GekFkoWZP32U/zrvIQr9kxD3fdUvKr7m3ht9//gPxqXS6/pt/rLCnWiBQ85xy1yHcr7BPwkD/fr7/GPpfhzLhXN5HA/eZuU8a3JthHw7M8OuqYVi9QEfd/ea3qLlaTzdCBIqqPqWv2HWNwSZ4zVU9zKZX/i753UUsqreOr+OZTznmPYT/FvdmGloGZS1LuGS2YreRVahCAq2p/c6BjwiSzKBPW2gQK6qDhj0hQNuOzV4gX3floOhITttAFstXpYQign+jMwxqRCc9TJGlKqf+9+5Wwn4G+DjwO/exQtSkiZDoMUf3KNSnNCi6/VP8axTYsneU2R7vFpEFWXYHl7/H0U/2bXwF988X780n/ehiPLzf5E/1xZWpNBb6Q2GcMw5XC/zvguWLx/TbYYVfH3iEb29pkjO8dPRywQq/9cJKt/dop/kBNlFo7iv0H8N/B4gqQOiUNHy/Xf2Ix8QkINeBK1ddTjhPuRHn+LBH/RRa2EYsLtVPNuf3GOmWg0Y/ZZS4o/KaJ4iL8RdYRWEPp6/GPcAMn3bXAFWm87/Yh/4h5/AEzq828MP9OWjPPrID9Uoj8ATJZyyKlM7mVfOTjUZ7rwKP4TRS1a2wSx+ueYkdo4IL8ef6AXSOdBDSVsmSjiZ67fh29bF+Im6zJwcktRGHwSjWW1I9F3LQXSBYf7AUMclz6j3mKN8wux+luea1G+Ogzxpz3+9oI5Vj+rNMWBEH/PdWg1vzleAVKy+qeg+Buy1R8AqpWCb58/i3pNJ9/xpGpvm8WRyIUSBloUjtoSVdBUt5BlWHzgTPO0UOsYmKI2//IMcO4LRIjmoW/3zbHeOyuOwftPrGEYUAu51iPq8ji/+FZ/QfzTU/x9iT+5Pnh7/MMwkVGPv5+tP86/27sPx1MeOxgUolb2hPs9dKqGF//tt/DXX30In7z1KN7z5Qf7E/1zJZn4d5vStX+Y7dUtWfFnhXGcQrXvdfdYeyKRVnoPrKj2dc20eOQ2lsciFmpU8Y9i9Scj/eppW/0Devx7Vn/eGe4adzpgg/hvIDp4gNXfxxaqlKrJ/46nv7YeI9zPkhR/QviYf59yYsWfMRiqWDh2WvGqgFKPf0heAhumvx+QiP84mvEWFpYclOiot/5W/4TKKiD3+bP68IsfQqY7yA1N/BljmKkUcISTlou0+vwl4q9h+5S/itkHz0i/OMFzYVACiKDB/BT/MjZPFPDU/XP45M9fi/fceBnec+Nl2Dppq+VPP88ntM4zDWP4VH86zk++nY0XtH7HQVRI7Ub28RinuBIW7meRIkqXqyhNDtHKQxX/3oI5zj4NVPy9zqNSzOKEj9U/VtHRA04V/17Ra6qcc3MxKLSo7VtkAV7NiW1bTdnuL/V7x8icSCuVPA7qbQPTNNivPAuMzQFz5/We6FclL9wm9vfdx4ZbFBue/n4AQ6f6O/erNMP9/Ag0JW6S1X+devz9bP1xFP+OZzLCeMrbGaSs0nA/y+J4zT99Hw+dEuuru46todkx3LF/9gaWpfMZ3UZqkzEM05LC/dRcURYBeriVnx27x98pOAKP34C/tm66xVZVYZiM4NLLMtzPKer59fhbHLDaZ36P/+kyzm8DZwBYjHC//NSO5H+Iqm0xrf6BxB+2apnjns9KqvgDsLQSYNgXgW4r3sVA8ZmXDvQXUYrbLki8fQDkHn+047UkkBAnHSrKPRKVz9DqP4O14RcVNNyPD6/4A7bd/0gzA+IvhfvlowX7AVLrSh5GauFACvyPS+8IOsBW/Df3SP4Tdk3hCbvs7/E5F27BAydruGCrz7lFp2GwDppdE6bF4xH0gKwRauUFhrD5Az6KP4+l+JsWR475Xy8tRWzXPKqYKA+xnbTHv7cQjlOgUMi+ZCFW/24l5vWcflYKij+Twv3sa+RUOd8b1ym7rfKVarQPpYo/If7LzS52zUQswEUAXZhWS9FHqY4VNXdkVaNjRFLChkWj4yX+vYDesc3AqXt833Phlgo+2Xt8z7DEn9jTnWtCMSDV37S4v6sI/an+QNrhfjGs/gOuQ7QYlG6Pv1+qfwzFP2Orf5Di71r9DRNLzS6Orsjn95GlJhpdExMgY9WKVYlQQ/em+ie/P3p7/LW8TfyfiAfd5yzOcBffF21UMrnujHuIf6TCwWMMi+T6OFPJizGbJ+6yR4he9KPA5gul98yMZUf8g8f5rQAArE4Nw68o1xcbiv8GokOy+g8g/jsu6XsuMjzj/OJY/c0w4u9X5xpLHqzFSYXZiEn8abifQqz+UORFQmXb+ck2zoGag9FbKGvMQiuGM8Hy5CUoAcRfU9hQqfkYF4n5m9jK8IsfPd0ef8AOnDkiWf1TIP6WJanXOlTsiBLsB/gQ/3TUAhZQkOoLpAPQUcek5GQHxZyKS3ZU/XuZ8/39jbGVjoACpLfHf6hilKK656LCuL2PYxBqi2yjBSa1JNBixTyvJg8gBHwV/zjHApPCHINdXDxOsB8g/Xvzin2ta+lmYos1Jf68d+xPlnLooP/eU4o6opVcvyfIAjztZH8aejc3EX1hXyGZBKNSA2sdQ070dwLTQu6TF20Sx+89x4dV/OUef8BL/O3j584jq7j6T76C5/zV130LSl2PWg2kbPU3+kk1LQxSd8ug65CspGds9Y+RbdD15CTQ7UyjJcFxd+RZgOKvW1Lom4Nax8CxlRYmWEM8WZyUisp9Vv8hU/1pj38u36/4P8B3oDA2Fa2ATbZzXBHXtaFbHM9QLBGrvpvob1nAf7wK+Ma7gX99WV+YMi2wLDZSClruIciJMoM1MFiPCcV/g/hvIDIkWygdo+U3+mnLxcn/kCdRO5bVn/T4cyYf3t4+Zc6U4RLzCYkxO42QF/aDUWWVFFHKHiKlTO9Jtm0EhiZuNHpjNfr7dHFBpkUT782tmBsuNR8k3GwzWx4+4Mgzzq/o05oQF7NjXqv/4aE/U1L7eQ4AS6T452CgEUONDv1YQgRpj793BB0AmOVN8b932t/YI6qxF7uS4k/H+cnn+1CEGvBMIIiXmG+S65C3AMnJOKhTvBrJ2hgI2srDbAUsTqFUCRgrmsvLBFWbjkn8yf1hsiC+l8SEgZwrDvGfKud9e/wrkxFDCMl9ZowS/2a6CpJE/GOo9mMppZLHQb1tYIoq/s5s9LHg++R50+L7ve9EbSg1nfb4u4o/KSq3DTsE7Wc+eAsW6h08cLKO//e1h/s+w1m8MyacQLRgPbzi33+OUTdCLU64n0SoUwz38yluJE31L4y8x9/OtVio+Z+L952oYRJkzVWqesL9mulZ/T09/lqhn/jfap0d/dym1x1C/FfSGGV8BoLeEyYd90v9BLDaE1dqx4H7Pyu9J0urv+jxlz9XYxamUAffIP4beFwhYJGo5X3sTZsvSv53vOP8YixkuRWs+HvJi1GckZwLccHIjcaKSfzpglshCuDs9nOwXLRttUe2Pmeo7XNg5gQ5sFrRFRnLDCYvFH7W/1jwEP+hVQ9pnF86iv/ceCF9xV/KIugl+kdV/EmxLc+y7/H3U/ypUyMyiELtzDCOq2ayoB5/L/GP0U/ti4rIKJhjq+7s6Cig1yHLc5vVyTaf4lWU80Oc4xVxTM7APrfjkEQW8H1rHsW/NLc33naRa9pkURSHkrp5FKNf8Z+q5NwRmBTjE9PRPjRoAZ5yj/88US3jWHnTSiWPg3qf1b+n+Fd88jp6qGo6tvVafrqGhUfm490LKWiPv3M+a6riknfObSX7xJq4xt96aEX6DK/a7xQnaSvQsD3+fjZ6On5uTcp1CCf+Ix3nlzTVX1VTzyJwtoWq6YBNsArQ0dZNX8UfsEMkJxi1+k/KPf56E5W8uO4mdcxYFodpcRRIj7+WK+IUkwtht0Xt7wfk9ixy3UmbwJ4poMe8WwRfekR+0Q8/JP04I6X6p3u9DurxB+w+/41xfht4XCFo5rNXHeqqFaC6G4nh6fGPY9OS7OnMS/w9iv9YAuJCoBQI8e/GJf7kpkwW3FAUTL31G8CrP4Idr/vnobbP3TZyo+Hd6NVKqloaYcQ/wniqUBACmb7in0NpGGLVw+xYASf4DExnjE/teJ/9LDboKL8egYmu+Mvj/FLr8acFKXJcWkr/4jWXJI3ez+of8/vm1HlE2mS8BaihFX9PC0oc8mUawQXIRZIIfYBvGc4tQ4j/bG/2ehyHlGT1V4KJ/8SWuMRf/JsniOKfuM/f6lf8q26Pv4yp6Zm+53xBx2oRdWc5ZcWfJlb3kQPOgVv/FfjS7wDNJelX0hzylM7vQah3DEyDFIcjWP3RbeCCbSLP457j0V1lXvgp/gAk15Y3/XzMY6X3S/S3H6u+r0kC/3A/avWnin94AbKcF8G5HcOSRhEOAz+SnzTVP6cxuUCRao9///lWRttW/AOIf5/iX6za7UVkIpS3fz4JdKcdgZJALY/lvLx2vNWKQfzJ+pZed9IuOJ4pWPULwvQS/4e/Krkspyriur+c8gjWICcKYPf5sxhr6NMVG8R/A9EhJUATxV+TF1/t6fOkHs/Y8Kb6x7jJUOLPPYe3V/HXJpL39wOAWhTqJbrNWHNYqdKmqh5iWp4G9j9Htq4Ng7xQ/NGJftGyqNWfjUbx34R0Ff9OWlb/8QJ0aDgBR03kwOqR4T7Uk+gPAFurxaBXy/D0+Kel+KtSuJ/4G5anaNbieVSrEQkWBQ336xH/uP2XQYp/qj3+gER25rASS/GXskY8LUdf0m7A580r8QXzCnzEvGG4bSStSjPMJlxx1DhFGisq9hfzXL8nZpOH+00Q5S1pUU8lE0bgWv1zvsS/OhOxoOszshHITvHXYODyIx8CvvHnAj9k+wAAyDBJREFUdnCq3gY+/gbgv98MfOs9wKffJr1vjPb4j8jqX/Na/V3iH9IS123gAprsfzR5nz9V0jVC/Aukz997rfOO7OwQGz6dQJMnir+fYh8HvuF+ktWf9viHFyAZY6nb6AF/kk8dFXHen1cVqYCRiuJv+iv+AFBhHXQMM9At0+yanh7/am9DRTGvwNtuQaVrWImKPb7bqBawVpCL3g/x7dgyEfHe7Rlp62C9Ff+OYfYFKY4CvkGYXuIPDtz2b+5PBU11z3vT4qmOwQzq8QeAWaxC2VD8N/B4Aguw+lOCAADatiGC/QCpaluEHkvNDFP8u9zTPz8xnOKvEttykbfRijhqCAAYGfXFlCEJyiAUBfFX4ij+I7P6i+9hC1vG2jALb84BQw73K6SR6t/r30t1pB8l/jwHTWGYrURUDajVP+Y5Eoaoiv9JPoVNkxHdCRRU8e9Z/eMuIllAATKnpZjqD0jEfxNbidUnygn5sDznzoJZxpv0X8LP6m/HGoYs7hELtmv1j7Gdco8/aTnavAMPKbbKf0v5OqkoEAmk2DFREN9LUsXfL9yvWurv8b+rcBlYOWqPvzgWZeKfTY//85Xv4uzb/hT4yh8A3/t74BNvAO76mHjhPf8NLD3q/ihZ/Uc1zi9BuB+6DWmCx30nkitigYo/adc6siyTEy8J7xBHAA2dTTfcb4DiL5GZwedOFiP9fK3+scL9vKn+6W5j0Lx0gCj+pMf/8l1V6TV9Pf6AVFhmKYz0c/ahrPgXoBbH8ev6G/BD62z8bPdtsKC4E24Gglx3CoT4p+00ioNW18TT3nUTnvzOr+Lfv5vSxKKIoEGYQvF/tP+Fj3xN+lEO+Etv3znFMb/jcpatQtGTtzKdLtgg/huIjKAFN1R58VXeeelwfyhHU/27sRaylPh7F9xt7iGAQ1r9ZRLTjnUzVAMIVhZQyMhCNUa10iSLbTNk8qe3tzo2ipMwVJtEllkHenMl+WeZ9ug1wJ6RbkFJpcd/z6z9XR9Ns89fGuWXw+aJohhlMwh94X4pKf4B4X5e4n8KVbevNxZyw1v96SQEqeUo7XC/cZn4x7sOiUWDt8c/jnNgICSrv634J+3xV8h1nCkKpt7yFXznun/E/p//cPztIveH8UIKPf4WWdj12lyq5RwUyOTmzh2vjv6h5D6T56JYmFWq/09rnxNPfuE3gHs/1f/i773ffShb/UcV7qfH7vGH3sBWci0YZmwjVaRl4i+Op4dPyfcw7zHlHUPn93jYcD+/99MWBF/7cgio4j/M/qPwczXEyTbIepyfY6P3U1YraPel+l++Sy7o9fX4A56RfnLAX5JzSPdV/PMYK2j4sPl0/Gj3D/AF6yoAwObIPf5iG/OWKGKtp+L/nUcWcWzVvgb+161HR/q3fYtkfYo/gIX7pR+zCvhzimNFnxaUrWwJqtnue/5Mwwbx30BkBPX4w9ujumnIEXRU8Wc66h0jcg8PVdq8qf5ty0P8k4STUXhITJxFLVX8Fa/VP2VolPgb0auVlhHsnqAYWvFnDJ2iWFgqjRPJP0uXE/0BedGYFFsmiijnVZn4p2z13xqHSFOrP0tvnB+1+iukhYd7inun+BR2zyRQq0n7ijN+Lk5POuC5DqnBxH94qz/t8V+OtY+lAqTn3EmV+Ber7rV4grViF0oVqbVD3s6Z6Rlc88yXY2Js3Pu2CB8s9v14fnjFnxJ/1msFm6rkcYkiLxDVc58b/UPJ9TtnicXccopWf920sNRT8pZ5hP1464fcdqyxgvg+Rkb8g8L9ytPSpAYJ3YaUo9KO4Xzzgir+9HymxdtHFuR7WB/x9xnl5/28YcP9/N7vOP46homTvfBBxqIFOlbL4vqaHvEfTvHv0FR/VZXH+aWwjaYb7uej+LM2OoYc7nfZzqq01Ozr8Qfk9shuE5UhzyHfkYNaoS9XAgC2JFD8c9bpofjTySNpj8cbhDVvkYxzf8W/uQg0Ft0fZ6jiX09v34X1+O9nYs0Xlnt1umOD+G8gMliALRSAPH9+84XD/SGixDhVt2bExYSktHkWKi0v8Q+zL0YBJTGsE6tXmfbWKhlb/bWyIP45oxE5i8AKGUlGURhW8QdgEEWp0Dw5xAfJ/f0AUEqB+DPGsHe2glO8Kp5snBruQz3hfpEXDkCf4p8WmVSCiL9X8edV7J4pIzakQLWEir80VjS4x39oq/9Qin+I82gIYtQHRQHKohg1jVqs7VTDrunDgFx7xwhpS9qLqVLFv9fmUsmr+IT1VPfpvzFeinO3TnrfGgzS468RFWc1xQX4UqML53KbC8oaed67gJlz7MedNeA77wMAjBXSJVpRUG8bmPKz+iuq5C6R0G1I19g4LW9eGBHC/R6Z9yj+nuuHRFhz2Vj9u4ZPqn/v3314qQnnn7FtshSp8Fwtiet5psQ/aY9/BuP8nCJEoOLvCffbVi1JffS+ir+U7J+C1d/wKU70FH8vNifo8VcN8W9IO50+DmiWwqhDBun5O1nK2QTfaUnNjwFbSOvwwgPuw6wU/7DQyQuUg+5jw+sgPoOwQfw3EBmMBkF5x8y98kPA3qcCL/tHabZ0IhDF3zn5opKDsHF+nbSJvyekJVaolqS0ZUv81ZIg/hU0pYVRGHhIEYViaMUfgDUmwnKKnSEINVX8uaP4p3OZ2zc3JhP/2hAFCqCvxz+W4q/RVH89PcVfKkgR4uzJ8ajn5yQrcmSQYpkTbBQ38I2NKtXfE+6nmzxy4rZFe/w9zqNhbcZ9IMFrs2w1Zo8/be0Ycn9JH+yv+Ce3+ov3OYo/Ywz/obwQXzSfiH8xnoX3GD+K/Ztj3HsclRCA2lmB0yKUpuJPlbRNSkDo3f5nA9e+Rfz8zb8A1o5h84Q4x+n4uixhddaQY/axa2klqQiPsQC7f7cuEexhCltGQLgfJc/ecYFeohyk+BdGZPV/mGzfvrlorihapEyr8ORn9ddNHqnwzzkfYPVPr8c/79vj30FLNyUld268gF3TYs014dfj36f4k21OQvzdVH/yXq3Qd+9TmD35JxLIuGrF7Ljuz+V1tPrT61TaKfmDILXFlHKyzX96LzB3rviZ2P2nxyjxT8+loIf2+Itr+Ibiv4HHBejoJ3jJ6rnPA17zP8DFLx/+DxFSU2AGFFiRF7Oy1V/exv3bPPOdx1NU/NGOpVxSxV/VMg73K1DiHz2LQA73C+vxH2IcWQ9sQhD/Smch+Qd5gv2AdKz+AHDWXAXzlPjXhyT+kuKvYUucsDxC0gopKv4qWeDQ49Kr+LOk506f1Z/HtmDSVH9GClKqJx+hXBjye6fEP2b/PC1AehX/v3rlZe7jv331E4bYwB48yf6xevxpy1Ga1yEyFYAIM1KQUxxIqf7k/nB/Zxpv1H8Zv2u8Dga0eKM78xV3Ec6MNiq91pO1ti5ZzocBXVBLSrqD2XOBqT3AZT8BbOo55fQm8KXfxfYpcT0YVdo2a5PiRNHjngjq8+82JcXfO24vDoJ7/MOt/pTMBo3zo/epLMf5PUq2b99sNOI/Kqs/4D/mz+81zi5VFQZVYVJxIo0e/7D09Apr2zm9vdeMFTQUc6pE/CelVH8/xb8pFSuSFMd9XQlqoa+NbG680Hf/CYSieEQjex2w1OzGmgyVJuZrHbxS/V/8kfaP2MIXUk3JHwTJ6l/SPMR/HzC7X/y88KD7kFr9F9K0+oc4USg2iP8GHheQFP8QBXj4P8SkqmicvlXZ6i8f3lumxuQXDx3uR9RL1onVqyxZqr3uibRBFnAzbC3yDZBTqz8LJgVbo86eD4FW3eY+njDSIf7OqK80xvkBtuI/D7IYrg9p9Zd6/GMq/qogP6mG+9HjUg1W/HPV7Qn/QM5tC1IZRwF6bKu/rPgHH5dDt3iUptz9PM5aKKEdeXqC3OMvX4eefeEWvOfGy/CeGy/D8y7a6n1rfFSo4r+W3OqfpvNIsvoP3+OvcrGwUzR/ZY2Sp0hgTNp3u4q27Zbz9Kz1gvhzTFor/S/Y/2z7/6oGPO9PxfN3fgTbtVX3x2MrrcxJAeccapcS/wn5BUEOuW5DKq4OY/WnBRdN9Vf8vTAsLhU+u9I4v1GG+9l/l7Yi7Jsb63udHyYJqU7Lah1I/CP0+fu5Jsbymttj3+iaQxfHTD81vQc65g4AZnvq7osu3QabX3NZ8fcZ54duA5X8kFZ/J9WfUcW/3+ofeZSfA9JmVM3Z33fXsNLNf4mBytLd+NPc+/ET2lfwq7n/HGnQoBTuV/Qo/lN7ZeI/LxT/bWTd+d+3HcViPR3VP6wgRaFvEP8NPB7Aslok+kEi/jHIAVHauKc40Td/MxfzYu0FqdpWYlv9abhfihZbP0yKGdzb2UL0IopByYu8L//8FfbkhnJexduftR/DojAliP+UuZh8kav7KP5xVMAQ7JutYIFT4n8SGGYxLhUptHg9/nScH0vR6g/qRKHEXz5Gx2cTEn9AWpyV0Imv+EfsS58ctsefsb6RfrWIxT0eEu6nKgwvuWw7XnLZ9ugqURgo8cdq4pYjNSOrf4V8bPIe/36rvxexF9+A6GEHsLsg+m3TSvZ3emfL6CDPfRam5z5fPN77FGCbcICM1w+5ymJbt1IdWeWHjmGhZAkypZBWCABSS4mEbh05VXGt+abFExNrqkZrxDUyyLVFjys6zi8fNM4vRsidH8KIP1X890ZV/EvpK/5BroYowYZ+rglFYRgjRDp2NosHRkgvteO+ceDY6K/fP4f/+JlrsGecId9rSeFqQazlyDg/dBuy1T/B9jrfs1fx91r9N8Um/mI7t5bEvl6vZP+nrX7Sffwj6rdGGjQojfPrs/p7FX9B/J9+3iZs75H/5aaO3//UPalsj31ccuk7b6v9LWQbiv8GzijU2jqOLDdx7/F46pDUl561Sk0qosU4ir9Fe2s929haSmXTXHhsy8nH+WW8L6u73Ic72EJ0xZ8EanlT/V/2xB348tuvx82//vTovW0hyE0KIrkJS8lVI4P2+DuKf1o9/hW0UESN945NSwday8k/kFj9O7EVfxruZ0ZWogd+bEC4n1fxn96yO/kfIYseu/UkZqp/iOL/huvs2fPPumCzpAgkBulr3oSVRIq/twCZOiSr/2mi+JP7QyUFxV8jij/LiesNLTr+4Usviv/BZN/tyAvCltbC11H8Z9iq/IvzXgg8/beB3dfKz5NrNdaOuQtbwFb9s0S9Y2Cckb8RQ/EHkErAnxnY4x9+DafHldybLrYpzXA/v5yclqv4x+/xlxT/lIg/LaLQAogRhfgHjESkFvdh7eBuiJpfjz/zJ/4AcPW+GfzPz1zs/syc/n5A7vHXG9L2Jkv19wn30woYT1Hx31QU+3q9kv2Lunx9WkrROh+GrmG5542qMLvg8+CXxAtm9wMzZwGOa27lMNC1C7TlvIY/+hFxzf+f24/hrqOe62wCGKaFHEworHf+KDk0C/1FTyOk/fV0x5m75RtIjJ/90A9w88P2WIwP/vRVuH5/QCXfg9Bwv7RBFP8iizGiKmzB3RyCpPmB9mmxeMolVfzVrN0T49tgQoEKC5vYCu5u1AHMDHybbFfu38azNw0Z4khBevw3sRWsNHWU8wn2i5/in1KPfzmvYdtkEfOtSbFArp+yR10lgN5twVnu6chhLk4BRZXD/ZppWP05R44Qf430fEtWRwA7tw7RJpOXz5u4oUs0kI55jsvfeuEF+Jnr92FT1JnKg0BGftrJ/hEV/5Ae/9ThQ/w552DeMas+kFqOMrL6Uwd+Ugu9xsX7FHJveP11e1HMKdgyWcKVexKchySpfktOOMJWU7JbO8R/FsRCv/Uy4MZ/83/DuHA+oXYM26t7cN8JOxvg6HILl+yoprJdfqi3DYyDJKUXPMS/ErBO0O33FHKqey63u2aicM3AHv8B7VpUNZRS/QlpHUW432pTd50ZBU3Btoi5LZMZ9/iX86pb7IjS4x8UkDhezAG9ee+LjS4OLzVx2a5qonu1INX91/8+xX9cLjxPcOLepFkUktW/iWpZvC9JeJ5u+If7ecf50SDOSCDbuakorsHrofi3uia28JMAuV00VuYBDNkKGwE1yeavgd3xn0B7xX5iag+w8yq7iDy1F1h6GAAHFh8CttpJ/087dxNuOHcON90/DwC49/gaLtoeY7KLD0yLyy4UrYhOYQZoyqNjNxT/DZxRSJrOKi24syarkuIf3cpshVj9h1Jn/UAu3mV0IlvfTItLlupUF9x+UDUsa0K5tFYOR3ob7fEPS/VPBSRvYTOWsbo8n+xzqOKfMvEHnD7/qnhiiIC/ekMsstVcEVqcsYjElp2HgUYavYHELWNyJjlRysaK9NJdES2svpCcMtHPGwdyy1H/d7t5ohiJ9EaCZPVfRj2qsyLE6p86iCthFqswLR45YE2a4pCR4l8i//y1tpGojUci/jmxmK8UNLzx+rPw4ku3+b1tMAjx36yK8L20bPUO8Z8madCBBBoAJsi/Y+3YSAP+6h3DMyLNQ/xzASS210JXytNk/xSs/hF7/AGZLHcCw/3SJP7+4/weWRCEdO9sBUrEVp5JKdV/eOLPOZe2kboxorgdgoondO34hn/5Pl79D9/Fy9/77UTndNi8dGfUq4M+V2GbKLu0JYVa/fWmmw0AJAuA0/0Uf59xfpFH+bnbKdaOMwVxT1kPxX9hZRXnsKPSc8bywYBXpwt63k4WVeC77xO/vPpN4j5C7f4n7pQ+Y+eU2JdptDwalmzzh1ZAt9g/ynRjnN8GziiMk0p8nEC60Sr+4kIfx+rPzRCrf7eGVEFuMiV0Ivf/dg1LIv5Ic352AFYLQlFXViMSf6mIkvE25suYV20Ck2Mmtn7+jYCR4Cao0755+6Y/dMgbwb6+ZP/kAX+1urCE5gsxFw50nB8z0DUsfOKHR/D5u44nz0cg37cBVbLaMk/RbKhReeS8Kcd0ygCe61DW+RhE8Z+LkZhvkiIKZxnfZgl5dcYNRd2ntLVDynQYFuT+kGOWew6aFk9UpKJWf1UbMpuFoiz23Zwi7g80jX8YOD3+M0mJf3W0xH8c5G94Ff9y/+IXgGv1p6p8Yqs/If6q1OMvn0OTqONd2vvw69p/QIUpOUmC1Oo0rf5Bqf5J+vsBSMp0Goq/7mmZkKz+cRX/AOLvEOl7jq/hVMzzhXMuxvn5pfp7FP85r4PLUYWBEMW/IRUMFhKEvxm+4X79Pf5DEf+8+OylxujS9B3UD98JjXmO59UjAIAPfecgXv7em/GVe4ecYBQAOsr3Keo9wMID9g/5ceCyHxcv7Cn8AID//WNJxKPTe9IQQPqJfxF6yc/qv0H8N3AGIaniP9IFt0YUf9aNvp1hiv/Tf0s8fubvDbFxPeRlAhN1GzuGKRP/rIkBgHpREH+1Fo34W6QHPSzVPy38z+wb3cfVk98GvvHu+B9CA/OcHv8B/aFxcMO5c5gnAX+HDj2a+LMaTbFILBRj9qNLPf72cff2j9yON/3rD3HTAwndEh7irxDV/JQ14feOZPCE+zW7ZqS+UwcKHeeXdQGS9vjHsPpjlEUzzzg/IDrxl0JG0yxA0s+yTFnRTEBsJMU/n1IbByDvO2LHP1Vr+706Nnyt/pWQNisP8ac5FUeXMyb+bQPjYYr/zqtF+OA5zxHPOz3+JES1nZD408T5nBKs+L8z9368Qvs63qR9Ck9TbpN7/KlaTa79lMBGCbgLQ5DVP0l/P+Dt8R9e9aXbR4MXgWF7/P3XfVbMYrND+hksFFj/taocEO7ngir+tMffo/jPEMU/iYvHTfUfMM4vVjAv4En1J4r/Olj9zaO39T2Xqx3BwcUGfvu/7sItB5fxB59OJzjPC1qwu45/X/zislfL158rXg+Ueq1ca0eBz/6q+6uxISc3UDgFKSl3QivALMvEv8M1mGcwfT5zt3wDiUEv3muxrP4jHEFHEveL6EY/ocOI/9VvAq75eeDJvwhc8+bht1Gy+rcjL7Y7hgWFVliz3pcAmmURnldoHA15JYE0GjF74v/Q5ufiL/SXiyfu/2z8DzGy6/EH7J6yCZJof/Pt98QirRTNpljIF4cg/l7F5I8/c2+i7aHnjulR/BtXvhWrvAyTM/xe5beTfb6DnNwiAyBWOCEbZcgoaUHZhOhWfy5ljWSt+ItFyTRqYLAiOxMCwxyHBb32ctOez9xDkj7/HCH+6rDTWCiIW2LCEmQiroLph1bXdO8Jc0pExX+cjHesHR+51V/u8ff0yioK8PovA7/wQ+D5fyae74VtpTHST1b8xfWnQD5bgYXnqYIkPF35oZzqb5BxfpLiLz5vaMXfj/gbJg4sCuK/ZyY68a/kxfW2rVuJCycOpAKKyjwTDWKm+pP30vM46PWRti+kvx8Axjzhfn3hea0V8Zha/T2K/0xFFAySjHtznBNyj3++X/Efj3lNIqJRVRNkf2kdrP75+Tv7nis1j+HTdxx3fz642MxknCg9by/sku0497nyC8c3Ay96j/j5zo8CJ+4CAJTJdzHsOETf9hOtCMtzzZbaPc9AbBD/xyEmJMU/2ez57K3+YsFTgB7d6k8ttl4FqzAOPPcdwLP+QBqHlhjUsowOahEXtB3dgkb25Sis/p0xQVYrzWjEX0omH0FxYqqcw8fNp4gnGgvxP0Tv7/EvpKj4M8bwjKtEonC+PY8fHlpJ9FntpiADpXLMoERq9fcsnuKqLw44KfQYUKSF93Ouvhh/ct7H8ZYt/4bX/fTPJfp8F5JTxl7gRW2TAeQCZObOI6L4z7C1yIRaCvfLusdfK7gkLcdMTKIRaX/qpiUR/1wumx7/NBT/HFmIKRkR/wrJsZhfG574U2vxthyZOR6Z+J/A9glxn8o61b82qMcfsKdozJwF5Ml8+l6PfxrEXyfhfrTHn7ZrXcHul95zkk8HKv75jML9/Ihuq2tKxZkdpPd4EBhj0jmSNATT3T6P4k+JvxFhlGGw1d//ehuX+If19wPAGGk5yasKztvquT9KPf7U6i+P85uu5OEY15abeuzv3QmbHKT4BxVEAkEU/wlVfPZ6KP7jy/1q/njnOL54j2zvTzIVYRCcUM4prGFHtxeep2i2u8iLC15sT0NxcOdHAQBjxOo/7Db6jpjUCkBFnmgijXU+A7FB/B+H2N59FDcot+JlytfBY/Qoj3TBTRZ3hVg9/iMco6Xl3eKCxix02tHsoR3DlCy2yHo7ARjjYkzUePt4yCsJBqT6p42pch4LIBfUxjwQl8RSxZ+nr/gDQHVup/t4Diu4/2TC7IjGovuwPBUwKisI5PzLeYh/0vn1JglzNKFKAXk5VcGfvupavPfnXoDdMZQsX/go/rEmYvCM7Ol+IDbSSdaIMQqT9viPoBeQENioBYqOJ2uEKdn0+MMypEyIZIq/+PeoGVn9i11xPqZh9aeugU0kODCU+OeKQLnXCsBNzLFVV3FdbqY0vSMAfan+xZDFrYdgAUCJFFg7KSv+tF3rOeot0nvKrB2J+MvhfsOpl34EcqWp4/ASJf7ExbVyCFg+EPqZNNl/2JF+LaJ8FnOqVEShkxOC0CVZSUE9/hR+4w3DYAwg/rTl5MLtEyh4pzrQHv8Qq7+qMEwPkeyvG72Z7rQdQc1jopjD66/bi1JOxa8/77z4YbLkHjiuEMV/1MTfsjDbeLDv6bHWCdx+eEV6biWlSScUjuJ/lXKfeHLb5fL1heIJPyEe3/UJgHNposSw10ff41Irgo17FH9ela4nZxrO3C3fQGJcde878YH8u/Dn+fdhcu2ByO9jUj/o6BT/IutGVtoYmT0/CrJKL+BmtxHyQgHvgnsUVn9rUpDVyU404j/ScD8A1XIOHeRR473v3jJiT2LQO2LB0EYOe2crfTN3hwZJep9jq3jgRDLir3bEv606G3N0Dhnn552DnDR4z5QU/wyPyXw/8Y+XNZLR7Hk/lKbch5NonJ4FSEAik7NYi7Sdbd30OI9S3E6P1T9NxV9LU/EngXVqewmAvfBLw+pPAwLlcL+AkDwHpM9fqR/H1qr492bZ51/v6HKPvzfcj0IrimwaswOYRiqKvyGF0pFwP5f4cTyH2PwBYAztkHF+JGQypXA/0+Jw6hOMATMVm1h2Tct1eSiM9H0/+CXgb68E3nMp8MjXAj932HOEgp7/YwXN828fcpyf3+tjKum+wX6k0DRBClCX7xLXYBeBir88zg+A1OcfN9lftyzZUafk7JYXAL/9wgtw1+8/B2966lmxPhOAdG6NkdGEo0z1f+hUHW/75y8jx/v/5jbWnxOUBfF3jvNrFNKeuOe64Dec9QzR2rF6CPi7q3D199+KrbCLtpGn7gTA7F1/vD3+6ri8PpvnkxvEfwNnFixHUQCgtZciv48qbUzLeMHt6fGPHFZFxrmZasy+6SQglUneaUiKRRDWI9xPq26Hwe2/UzUXpfT7QBAi2Nc2kQGmewuoRU4WnDHt/vccEvY0XSngz15+SXqj3RxIxD+Z4m9aHGVdEP+ZTVtDXu0Dn3C//eww9rDjiRe1tLXDzJT4C5twqWf1jzPST8oa8RnnlyoKk+C9AcfjrIVWRFcP3ZejaOXBGCH+bDXS9dIuQGbUcuQJ95ugNuaY4xsBmSBo+RSJf77sqoTM7GJGs4lbk/TnJ8U8sfpXrRXxi6B0fAfjnoA/Mgv+SIZ2f1vxJ5/vZ/V3wJhHXW1Idvyk4/zo/VPzCfe7gB3EDibfE8ZYKzjVn6jVaYX7eUnxrpl+S//miaJNDOrzwL+9XDjRbvv3wM+t0oC/IUlWgyiflYIq5RtEUfyDRiJOBCj+8Xv87ddLBKs8466FyqwDrXdf8yX+QT3+RIiBbgsxUp9/I15BzzC5XJzQZLeRGnFcYx9Ica/SPuE+HqXi/56vPIiHHxJtM/dbO6D3RtTNsBqKkPdVFkWJtbjEX8vbln8HCw9g05Ev4U3a/wAAmkNb/XvHpUfx1yY2weLiu55HVTovzjScuVu+geQgC49CJ7qiKgVBZa74Jwv3Y4a4WOlqigvEoL/n6VduRLAadfTRj/OrlIo4gWnxRG9cSyhouN8IttEZabQISvzjJdSvrInq+dMv3Ikr90yHvDohKrNuYNsMq+GRE8uxg2+Or7YwBVEwKE9uCnm1DzQa7mfgBuVWfLHwa7ip8MvYWu8P64kCk4xPzJT4+1j9azFu2BJZzbrlSFFg5sXxyKnFNASGMcLJA0Bfsn90xT8j55Gnx39iCDWTcy6pblqaVn9AStk/Z0wUdk6tDWf3F4o/R8VcIX9vkOJPioBrx6Vk/5Or6Uwb8EOtY0RX/IE+u7+k+CcM2aKj5lS13+p/ueJjS0ZLCgmTEukzGOfn/fzd0/3Ef3u1ZLepfeoX5V8c+Gbg52al+FcKmuSeGK7HPx3ib/qF+2klO4fJ+Vs91f8Ju6r9HxCpx99+/ywZBRh3pJ9uehR/NYVsKACYJGHLrRNuDsFiozt0/kRU/PDgMrYx0d50lM/iOBfrpe2eAtuw7Sd+WGsbqKKG85VD9hNM9e/vp7jo5X1PXaAcBJBmj79c7CkW8liCODZtxT9lQWmE2CD+j0OoRB0q6tGJPxtlb61E/PXIxEA1ieKvpLxA9AO5UU2gmai3dhRW/0pBw1FOFpwrBwe/acRW/6lej6MUnBKT+DPi+Ng2lwHpB+zvi1qEW4uSuhcFh5aamGK073cAGfDCo/jfqN7k/vyk5v/G+6weLEJWzSzt6T5W/zgp1vJ0keyPS4soSgpdcIbAIHkJyLodAfAQ/4g9/rolZ42kuS+9qf6EMMTt8TcsWXVjWsoFXbLv9pXE9ePkkAF/DvGfQAOqc8zmx6VgL19MCFKAtaPYPCHuY2m0IASh4U31D1P8gXDin9jqT8L9AhR/L8ZYSyLKUqo/Hecn9fgnJ1fSqDxNwS6fzJNt1RLwyE3A/Z+Rf1E/CRj+ymmV9KKvDKmuNvqs/mSiQcxxfoUMwv2c4oMcopaXSPw4s89Ft/C18BDwv+8A3v904OC3xPukHn+q+Pes/hUy0i+u1X+A4p8YEzvch8raUcz1xhVynu05TlHQFGxhwvF7nM9gXhUCRB/xz0jx38uE4wGbLgAKY8FvAGxHwG7ZFbCP2e2rw6b6+4f7FVHUVGldOs+r0vXkTMOZu+UbSIzchDi5x4xkiv8orf4FFl3xVyjxH4HiD9I2McVqkXqV1yPcb6yg4QSp5kYh1FKf8ggI1lTZz+ofj/irprhpFopDhtCFgI0Lu/9+5QgeOFEPeXU/jpxadkcWmVAHq2tekB7/Ejq4VrlbbI8RPbeDwiIOj0xn1BKrf6W3D+KEQzHJ6p/9cckJ8Vc7K5HeQxX/zN1RQLIef8Pb459Vqr8xVGK5aRjQeuNPLc7Sd0iRIt7OgiC+wwb8OcR/Nk5/P9A30m8zGWV2ckgXQhga7S7G6Pz0WIp/XbL6Jw33kxR/2uPfI/DnOcogwRhkq39H91f88yml+nut/nt8rP7bq0Xgpnf2v9nSgYX7+58HUk31p4W/iqfHP7biT8f5pd7jTxX/ojRCUipCLT4MvPda4GvvBI7+AE4WB9Q8UBXBxX3E37IwO0SPv2FayLNsFX+sHcM2Mr3jxGq20zvcP9vWsZUo/vmZnVgriF72XewUynlxTi83sgn3m2Rk7TQWEnzqQFGB13wK+KV7XIFwhtUwiXr0sd8BCOrxL+ZU3M13A7DvQffyXchtWP03cCYhT2zFY9SCOAAauUgraV0AA/8YCfeDjmbXjNQ/r5JUd0sbQY8/If4zbA31CGO0Osbox/lVChoanBRCuhGIqkX+LSMoTkyUcmAMWBjC6p8zxWKhUIk5Ii8Odl3rPnyZ+vXYff4Lp465j1u5KhA3h4BY/Xcp89IYrvP4AXAjvmogKf7I8JikxL/XUxyHKEij3dIYyzkASln0mOb0tZBXCtAJCZkHEAIy8Wer0RT/rtkfXJUW6P3B6Hp6/OMtIPWuWAh3ocU/VwaB7LvtOXFdnB9SeXNcQJsZKa6TfJBATMg9/puIVXlYF0IYVleWoDD7HmvmKoOdaB5bNU3eT6r4B/X4FzQVDBbOZYf73jOGFhpd0yXzx0g7BA12k1TvIaz+suLPsNuH+D/RvAM4/B37ByUHbLlE/LI3f9wLSvyHtVWHhftFKXpkbfV3lVVKsFRZ8Z9gTfzVKy+zf/j+P9ohkg6YAuy8BnjFB6QAViiKnD3RrWFmjPT4x7X6Wxkp/vmKyCYwuzibtBgdW8muuOeAc47Vli5Z/X/k+qtwIrfb/flF6rfxY1eIUOiVVjaK/xTIWrQU0aWpKHbxZFoEK57FjkVqtQ2DHtDjX9AU/Jl+I/6f8QL8gv4LOMQ3byj+GzizkJ8QC50q1iRrXBhKXCzAlEJ2aiqAvnA/IFr/DrV6s1z/DTl1ELVoGhEV/64JlZEixggUwfGihgYo8R88gYBRq3/WvdSwg3ImS7mhrP4FS3z/pUo1pS3zARkr8zzl+zh89FjIi/uxuihCCI3iTMgrAxBSeCswHa0j8fv8JcU/y0IPaY8ZS6D4F7lYvLF89uc4Jf4FfTVSnoNpUsV/9Fb/KK1R3U7TJXo6cum2JFC7Zrc2VP+y2RXfd5dlcB0iPf6bVLEIHdZyu9B7/w6akF3dGfBqAi/xJ4p/GmMG/aCbFlaXBQlgg2z+QL/iT9TBpOF+VPGnI+gKmoKdbB4V1v+djPUs4Yv1LiyL48CCuLftmxXHoaz4Jx/nJxF/VcGu6f610OWHPyB+eMJPAOc+T/x80p/4V8vp9fg3SLr5WEFDhcw6j0KORtXj77VU0/aSX3rKZrzksm12a8QdHxave9YfAr/6MPD6LwDnvaD/w2lGxuoRzI4N1+NfkHr8U2wfJS09+4uioHwiwxwPBy3dhG5ySfHXpnbgn2pXugF/Vyv34cmVo+7vs0n1NzBFFf9yzPbM2bPdh3vZCbR1K5JAGATnvUXpuCxAURjm2TTeYfw4PmNdAwAbqf4bOLPAKkLxn8FatFFanKNEUj5zpQzVVKBvnB+ASDYeSvyVwgiIP1k0TrNo+1LXxX40oaavYPmgoCloMrFPzXY8xX8kI8lg2/0XKfGvn4r8XsviKJLiVGkspn0+DrZegvr0hQBsor318Kdivb25Ioi/UkmX+AOAfuj7ob/3A1WprSzD/QgpHEug+Be4WBhlXoAEoJLFyBivRypSWAZ1JYwi1Z9e06Mp/ga5BnSVlNuiiKsDnbpkEaaj16LAIBNIdGRB/EXRZJqJDIdhwv04565jQEqhp7bkIFDiXzuOzePiXM/K6n9wsYkyF64hhSalB4G43bB2LJUef5MkzlPFf6qSx5UlUlzdeY370LmG/M1XH8TJWtv929VyDlOkv5sqdHHnzlN0PDb42bG8ZIkGOKqLt4ofr3sbsPki8fMJ/6LsZGap/hrGyEjbKNcGOcBQ/Nsqef9rWSem1d8pnshW/7zUXnLVFtWeyHP/Z4Fmj6BO7ACe9OZwgji1RzxeelRyfSzGTM03TMuj+KfoMCN2/9054Qo6NgKrv1NY2kp6/DG5Ay+87kp81hLhehceFlMo0u7x55xjpdmVrf4lnwkOYZg5x324T7GvD8Oo/iJ7Qlb8AYDWE4o5ZRTL9sxwWhB/xtjLGWN/wxj7BmNsjTHGGWP/OuA91zLGPssYW2KMNRljdzDG3sZYMENhjL2GMfY9xlidMbbKGLuJMfbC9P9FpzlIn+FMRLIKs+va07tcRS7NkUp+IJaqQgzFXzXFwkjNj8LqLyv+UbbR7AhFQh/FyEEAjDEY5G/prcHWdIW2TYxoO6fKXsU/+ji/Rtdwe8YBQC1mW5yyLvtJ9/FT6p+P9d7umlABqQMnMga12hz5QeyP5MThka3iLxZ3rtU/6kKccxRJH3I+6wIkIIVHVdGIdI7TVguWdVsUIF3TZ1m0Hn96HUqd+BNXB7p1TA6hZprdjIk/uYZPWoT4D6H4r7UMlzztUWMS/8KEsCvrTczlxL9/od4dStEKwiPz9XjBfgAwu188nr8/nXC/gB7/nKrgly4i38f2J7otcgVmIA8d//bdQ/joLWJazd5ZuSgY1+4eBOoWyGsKGGPYRZL9p1ETY4ULE0B1N7CFEP+Td9kpbh6kqfjLVn8VY4Wc7++CEKT4KwHj65Ir/h6CRRP62z0V/IcfFM9d9urBDklK/JcPYJaO80sQ7ucIT/Y2prgOIoo/JeCjUPxXWzoUWNgM0oY0sQ03XrUTP9jySvepLYc+gynY38Nyyor/WtuAYfFkVn8Hs4T4OwF/nWTXHoAcl54e/74/O5ai82MdcFoQfwC/BeAtAC4DcDT8pQBj7CUAvg7gegCfBPB3APIA/hLAhwPe824AHwCwFcD7AfwrgIsBfIox9pZh/wFnFEpTsHqzqausgVqzOeANkKzhLRSyD7YgycdxrP60x18dgRpIVY9pVotUTecdcaHTldEQagCwNLE/jNbgXmXNEMeFro3APQFb8U/a41/vGKjQcCqqOmaAyhU3otuzxV2AR2HWorkTVps6ivqK+3MhCfH3uRm1uVjc5U/e2vf7QaAqtZXlFAfyvTg23cjE3+y6I+i6XEWhMIIbMFEhJlkjkvNIoS1H+RFch4pV8F6P/jhrQW8PbuUxyWv0TBX/mpzqH7PH3yIOKT0Tq784/yrGivt4GOI/XxfXod2qsNNGIv6MSap/oXkS0z3l2rR47FnkUfDwfCPeKD8AmDtPPJ6/N51wP9O/xx8AdnQfET9suUgqLjkFxL/4kgg29RL/tML9vFZ/ANhDkv3PLxEyVd1lf5/VPeKcaC4CNZJk3kOa4/wannF+Y+T8iyL0UNWUZjcEIWmPf95LsGjBqbMGHLkFePgr4rkn/PjgD5/aKx4vy4r/Qr0Ta/SublqYiFsQiwqi+M9xURw8Pgri39Qxi1XkWO88LU0DuRI2TxTxB29+LbDtcgCAYnXxFMVuTRn2mPRiuee+qA5j9Z/pJ/7DjPQL6vH3YoP4p4NfArAfwASAnwt7IWNsAjZxNwHcwDl/Pef8V2EXDb4N4OWMsRs977kWwC8DeBjAJZzzX+KcvxnAEwEsAXg3Y2xPqv+i0xmKiroiLmDt1QiqKiH+DRSzn2FJTjbnJIxCqlVLXDRzxVFY/b3uicEXR4sobcaIlHQAsEjmgdkZbPVXSVCeOaLtrJbziVP9a23DXQACGDwWZkio5SncBdFj1n7o65Hed3i5iWkyyo/FHeUH2GqXp9/wV/WfhcHtS3px9WF51nEEUJXayDLcj/b4w+nxj0gUPAVIqjJmBmJ7rrJ6pIWzOmrizxgsolxrnaWQF9uwuhleh6ji36ljrKDB4XFNEsQWBdTqb2Ri9RfF22JX7LdhrP60aLAdtMd/t8+rfUD7lD0Bf6cyCPhLpPhvOl88nr9fIv7pKP6eNcZJMbkEmy+yRyP24Ix+o9gXovgPE+7nl3hPA/4uqpDrrlPoURRg84XieZ8+fzrOL24InRfeVP9xavWPQIyOLov9uXVycFEwFcVfLciKf2sF+Nz/ET+f90JZzQ+CR/GvFDT32OwYVixiaJjcbSWxNzhF4k9G+k10hWhwfERWfxrsJ00ZAID9z3UfXqfYrSnLKVv9nbaLKoax+otwvz3sJBRYaA5h9ffNnshtEP9MwDn/X875gzxaKe7lAOYAfJhzfgv5jDZs5wDQXzx4U+//f8w5XybvOQDbLVAA8LqEm39GoqZW3cfdtcFKJScp8C1eyD7RkiwcncTyKBfsHCH+Wobj3FyQxfYUapFCtZz5sgBgjGLyQA8WUeF4FOJPyIs5MsU/h1VU3IAZdNYAPdoCvN5oIN+rYBtQ0xu9E4I7NWHhNB/5RqT3zNc6mAJptSgn6PFnDLj6Z8GZgh+yC/GCzh/jU9a1uJ/b4WEMHDh2W6yP5F1xXHZYhq08+QrQcxyVWBcqTGkEVyh0cUw2UZRmTGcGshiZQDTFXyNFMzYK5xEgKdfF9mLIC21kWoD0hPsxxuRk/xjq0SgVf7W16CrNa20D7YQE1hkbpsHAjEUK65M7At7hAbEBoyYH/GXR5//wfF0mz1EIztQeUXysHUfFEveUpOF+QT3+6NSB5Uftx0wF5s6V1giXbuovVO6dlQu/VKwwLA4rYctEV0r1d4i/OMfPyZOiG3V4SIWS+/o+d7qcd10Ja20jkogQBLpWGvco/lEElMOE+O+YGnzv75rxzhPDcnr8PcoqPe6+//7e6D7Y9/Jn/2G0D/cQf0Ce7hDH7q9bluyESVPxJ66eUvO42zN+qtYZypESBastHVtof/+E57p01tPch09W7wJgTwFIs83IV/GPa/UvVd3rd4Hp2M7mh1L8w3r8KebGR9C+lyFOC+IfE0/v/d+vqfbrAJoArmWM0ZJM2Hs+53nN4wKtnFjMRrEo6yQIqomiHbqSJTxj8oD4xD9fzFbxBeAJ94tm9aeq5ah65wFI9lveGWwF1sx1IP6VPDgULIEohs1off7NulBa2kp5JKGJD5Qucx/nj9wc6T2rLR3TdLZ3EuIPAM/+Q7DfPIkLf/Mb+Idffz1+4ppduN0SFXB30RQVpCDVUTKsaDPWZ9NtR1T86XWojTy0USTr0h5/Vo90HdJo1sgoQkYBKGQG8ri1MpC00kJP6o6evKz4A8mtzCZV/LMg/qR4y5oLmCWBcElH+jnv28KWoPRaUzC+Nfo4sHFZ8d+c4Ug/zjkenm/EtzQrqtTnP9F42H3c6g6v+Evn9ql7xePZ/fZ+JNeQq7b1Hxf75uSCG2NMEix0Kxm50iXF377HPPvCzZgq56Aw4KopQmQo8Z8jxP9UP/FXFIYdVXEeHl1JrvyGhvsNuH5xznFkWRwLO6cjEP9Uevzz8nFHMmfwpLcA0/uiffgUcdUsHwQsUx7pF6NVRje57IShTqZhQYqASu2YqyJzPvwo0UEYqPhvu9wtwmxni9jHjoNzDFWM8mKp5yCQe/yr8T+I2P3PYseH6vF3ClJyj38/8b9w22Tfc2cSzkTif27v/w94f8E5NwA8CkADsA8AGGMVANsB1Dnnx30+78He//f7/K4PjLEf+P0H4LyBbz6N0MkL4m/VBxMrmgLfYiMgq8T+PN1TR6OQ6jwX1dx8aQRKW2ESVi8IbZy10GpFyEsgBMscxcjBHhSiwjF9MPHPEeJvjciZ4AQcJUn27zQEme6OKDvh6NglrjuhuPxApDDCtbbuHtMA4ve1UWh5FDQVWydLmCjmcBtPTvwZOS67WZ/jZAE1jlZkxV8m/hkHjDqgPf4Rw/1yZKykOooCJABGlOtZtjpYVafXobTPb0nxt78zKdk/SoG0B6kFJQvinyuKQoVlYO+42G9Jx+c5C/eddJTfZIRRfg48I/02ZzjSb6nRxWpLd511AKJbmufOdR+Orz3kPk7qlKCKoqT4U2u8Y5knx9gTNvW3/NC+ewdU9U9q95cS73sK/exYATf/+jPwnf/7DOxSAsIcN9FMhH7iDwDbp8R5eGRpCOJPyE9fj/+A69d8veM6NiaKmlSwA4DXX7e37z1Je/z7CFYxgFCR8bkDURgXLh5LB9aOScW8hRiKv2Fabg6N/dnZKP5YO4btE2I/p2H3X2p08cFvH8DrP/B9/NZ/3Sl9R2stXRrlJzmMAHu0656nuD8Ku3+KxD+NHn8AmBEFoR1sfrhUf9+ClF2Qec+NlyGvKrhkxyReeWWMa/lpiDOR+DtXhqAGVuf5asLXPy6gF8QJxiIoqmZLnJwdNoL+lsKEa9Uusw6K6AzureUceTLjuzAK4q8oMAqCGCjNwRZbSrD4iJR0AMiXBdli3cFWf4n4j6hAMdXrc1yQ+vyjKf6dJiH+6mi2t1gZx+2UbB/81sD3rDZ1TDFK/BP0+PtgvJiTFP/lB7+D7x8Y3OvtgEuKf8akmrhPKqwdOdyvK12HRkT8pR7/aMQ/T4i/NiLiD6L4z2JtsKpOnEc8beLvGecHJFf8LV0s1A0lI4slcW7tKwtinbSfXozyo/39EYL9HPQR/+wU/4fn7eNA7vGPqGgRMlteHZ7403A/dSDxF/ez/VX5c1SFoZTvLwbIAX/JbMt+4X4AUMqrdkvGyiHxYknxp8T/ft9kf2qrp6p7XMip/p4e/wGq7WFScPBT+9/ytLPxczechQu3iXt0N6Y13XQt1eRaquaBgt9xx+IVzYD+ZH+i+C/EyE/IVPHPlYTbj5vYPyb2+7ABfyfX2njGn9+E3/nvu/GV+07hX79zCF+6R4wQXh1E/AHJ7n9dL+AvzZF+y40uNBiixYgpAd//AJBjYxtblIpecWGGWP1fctl23Po7z8J/v/nJ0nl/JuLM3np/OHeLuFf1SK/nnD/R7z8A/iXc0xRGSSx01NZgsmqQnvD2KBR/xiRCNIMIwXlmFypJ/C6NIvEbgFkU+1KJEKqlkLR8nhud1b9YERdVRR+8qNAsavUfTZ+yS/xBbgD//grgYz8NDLBm6oT4GyPa3slSDt+1yILuka8NfI9t9R+yx98HEyUND/IdaHD7uJ8yF/Cuj/xv5PcrxPptZGn1BzwBf63I4X509vzIiL9X8Y9AWvM0ZHQdevxn2OpAcs2MDAt7lPjrDcCyMFEiyf4xiD8nPf5mFoo/IO27nQVREEma7O+Qix0s5ig/B9TqXzuOuXGi+Kfc4//IvH1Oyb3MERfghMwWloQJM3m4X0CPvzfYD5CuIXlTdrAF9SKnEfCnG+Kz+wgA58HEf2yzKCJ2a8Ba/wCrHVTxX06u+srhfqrc4z+gcCnZ/H36+6cqefzac8/Da67d4z4XeSpLD4ZfiJpW9G8xmdhmtwHEgUT8H03e429amKCKf9TzIirI8fGCjuhEPr4y3Dn+tfvn+9T5O48K7XO1peNSRqZkkJA8F/tucB8+UbHP7ZUUFf/FRhdVkPO2WLVDMOOCtExsYwuRMniCEKb4A7Z7JvM25xHgTCT+ztEbdAZOeF436PWDHAGPSXBCqnPtCAnQdMGdtRrooCL3+Q8cA0XIbBsF34p/FuCEuEXZl3TUFx+h1X9sXJwCNHwsCHmi+GNEBYotvQRhKdkfAO76OHD0Fp93CFAbuDUiJ8VkOYdvWheLJ+7+BGCEk4W1VtcT7jeE1Z9gopiDBQV3cWHFrK7cGX18ETkus7f6yyP9oi4cKfFPffZ8EHIl12JeYDrarcFtMgVOiH8pRZUoDBLxH6z4U+cR0r4OKYqYRQ8A3bpk9Y+l+JsjIP7kfrgtR4l/sgW400ecXPEnCpxX8U/Z6n+s10suK5tRrf6ib11dut99nJT4m36p/px7iL+j+NPRbzX8+NVi/774UuKYIKBEPWmAWsfH6u+iuSTWIflxyS0ExmTV36fPnxL/pD3+psWl/V/Je3r8BzgnDy/R/v7g+wANVk3a45+nir9W8CfWcc4bBx7FX+rxj6H4G5aVXao/AFzySvfhU05+EE9gdufxsIr/EZ9j56FTYs2h1Q5jp2JfmwytDGy9tP9DpvfZ04MAzLAaiuhgpZWu4j85rM0fkK6VW9nSkFZ/p8ffU5B6jOFMJP7O3aWvJ58xpgHYC8AA8AgAcM4bAI4CGGOMbfW+B4CTDNGXGfBYBh0hVuhGIP7EFjqq/mm6GJtma1hrDTihSeJ3C3mUcxmOJCNgpEBR6C6HvNKGShR/jGLUVw8VQvzzZtPXaujCMqH18hIsztK3Agdge7UEhQF3Wv19hFh8qP85ArMlFH86wSBLTJZy+I51Po7w3rHaWgbu+0zoezqNFTF9QC2nVlQZ76k6t1pixOClysORE7YpEUx9rrsXHsU/qjWYzp4fGfFnDN2cOHeMRvg5zjlHkbQc5UsjsvpXNrkPZyJY/eUCZAbXIU+fP7X6DyziEkg9/plZ/cW9ZrMqFshJrf6Oqrg9qeJfmXMX3WgtYXNZXKvTtvo7Pd+TjKpvEQnO1B63JU+pHUe5N56zrVux5qU7oOF+LklfPWxPdwFs943TBiG1k9Twq885Fxdvn8SemTLe+gwR+EUhkdWExF/3GefnYuWgeFzd1R8wO6DPPw3FXwr2y6tQFIZKXiO/N0PT2QdZ/R3kh3BP+IeoFfyJdSLiT9YPywcwSxT/hUYcxZ/LTpg0rf4AcNUbgd1PBgAo3MTv5v4FAHBibbge/6M+x86DpwTJ3rV2q/u4semJgOpTUFVUYFwU0LayJSw30g33kwSQuKP8HBCr/3a2gGbCYFEgKHTyzB7d54czkfh/tff/5/r87noAZQA3c87p3THsPc/zvOZxAXVcLBJLxmCySlPgO6Mi/lTBQi2C4k+IPy+gmB/N4a2Ni+0sRSii0LT8kcz47mFqfAzdXhCdCjNcmZbmpY8oPR22grKtWsKnrCfhl7o/Jyv3S4+GvlcaUTii/TpRyoFDwUeNp4onb/1Q+JtIDoRRTEftd7YFgNTnfxl7OLK6KoX7qVn3+JNU/xg9/ib5jvURTsQw8mJBajXCW6N0k6MEmuo/KuIvyOtcBKs/LUCyfAb70kPMJhL2+INY/bmSldWftJWRNpwkVn/OuUv8ZcV/d8A7fKAokt1/TkwhxmK9AyPFcV+OAjxLTY+kiBQKVZO2c4e24j6Oa/8GAhR/r83fIdOUhHVqqJbz+NQvXIf//ZUbcPYm/3MuFau/1OPvIfZBNn8HNNl//t6+X6fR40+tzpWe0q8oTFL9w1TRwwOs/g7yQxRRhOLv6aXOFcWISAdx+/sBWfFfelTu8Y9xTuumR/FPc5wfYJPrH3mf++PF7FGoMHFsSKv/0ZX+Y+fQUtMtsJ/Tut19vrvzycEfNEnV9EWsxLluD8BSo4sqLTbGHeXngGzjFiyh0U5eGI06zu9Mx5lI/D8GYAHAjYyxK5wnGWNFAH/U+/G9nvc4Z9ZvMsamyHv2AHgzgA6Af85qg09H5CcEWa0Yg7scOCGC+siIv0fxH0D8dVqcQL6/Gp8RKPEf52sDRxnRUV8sPzqr/1QljwbId9cNsSyT3zVRxFgxowW3D3bPlMGh4JPWU3D/Zb8hftGbyRsESvxZfjT26omeyv5R86mwnHiRh/9XXgB6wFpiEW8lvdn5bov9Hd3JRcrtucrh6OrqKEMnE6b6Wx2SQ5B1cYLALFTFNrRWQl/bNkyUGVl8jOoc96T6DyT+WRcgJWJWl4j/QPcWATdGEe4n9t2kteI+TkL8ax3DJUIzIGM7xzfH+yBCqHON49jUG+ln8eFGvXlh93xzzDGyDhiLSPwBYHyL+3CHJv69SQL+KKl2e/xP+AT7AfLx1RXFmrAe3EJOrAmStiPQgkGf1X8g8RdTEDB/f/+vxwruumW5qSfqV254gv38HofZ/SXiH2L1zw9h9XecHVJ7iXMN8pLrRIo/KbKtHpZ7/GMo/kbWij9g//vG7GuDyjg2YxknhrT6+xUOOAce7uV5XGzc6T6v7r0u+IOojR5LqYb7LTW6npDjhGuhXAntvP1ejVnQGicHvCEYrhNlQ/HPHoyxlzLGPsAY+wCAX+89/STnOcbYu53Xcs7XAPwMABXATYyxf2CM/RmA2wA8CXZh4D/p53PObwbwFwDOAnAHY+wvGWN/B+AWANMAfoVzfiDLf+PphuKkWIRMmiuD37AuVn9Pj/+AxWKX9N52WGFkIRzM40wY1AdF++uVEVnSAWCmkkeDjkALS/YnJLDJC66NfBTYNS1IyAGLLEAHEH+F/HuUESWpO/blY5jF3YUn9J7loSF/alsQf1ZOaG/zgVOEOMWrYvvQwGrUmzUl/llnOhAVvBIj3I+TMZTmiCY3AAAnvbpKeyX0tW3dRAmEMI4qx4MUSquoD/zeaQFSySKA0EPM5FT/6AtITnr8rawUf9JWNkYccPMJ+ukdtV+DgZLTK8oU2QERBVKy/3FJxX7g5OCpLFFR7xgYQ0tsq1aKR3AI8d+uiuJBEmLtr/hHIP4dQiBCMEeU35Orbfzg4DI+dfuxWMQ1KNUfwGDiv4ko/qfu62u3UxSGbVVxj05S4Kl7RvmJxyp5jf9ayjAtiTTuCFP8h3BPOK+f8gu59dr9kxD/8a2iVaYxj5m82Cdxevx108J4lj3+DkhA3Va2iFO1dmJXj2VxaRzgU84R17YHT9bBlw9iB+wRyU1eQHnPlcEfNkGt/ov44aHlRC08XnQNC7W2gUka7pfU6g+gUxFF0kLzROLPCRwz+RjDaUH8AVwG4DW9/57Te24fee7l9MWc8/8C8FQAXwfwMgC/AEAH8HYAN3KfI5Nz/ssAXgvgBIA3AvgpAHcDeBHn/G9T/vec9ihX52Bx+8Y6gRpgDqgsE1JljKjfW7JfYrDi3yGjvrpZp5JTkErlNFsbmHxKE7/V4git/pU8mpzsl8iK/2iJ/+4Zsdi4r0MS75fDrf6MkEJ1RIFqlMw8yPaIX4SMyKSjFNVSeinBjqLaRQ4tbiscOWaiVlsLe5vYLtIqkzlZpT3+McL9OFH8U589HwKFFGiUTrhDqt0xUabEf1TtPFoBeq8YkmMmOo2V0JfnyNQOJYtt9Iz0my4nS9ZmEvHPvse/0F123eSLjW7sBbhDLORQsPH+fu9BkIj/UezfLM6ZB05GI7pRUGsbsto/vjneto4J4r9FXXEfD3K++YH2+Guqn9V/OOK/lZDqbzy0gFe872b8wn/cin/+Vvi9haITRvwbpLWDFERcjG0WoZfdGtDuv5YMa/f3Jvq7f5q49oJGIx9fbbvFl7nxAoq54IDkYaz+jithCjTcrXev9wb8JSH+iiqp1VPdE+4hvdzUI5/ThkHGzQHZKP6AtK3b2SIsnnyiyHy9446qnCrncMkOsT8fPFVD91ExcviHfD+KxRBiKyXmL+Kuo2u47fBKou2icJwDUuFnCPejURHXyrH28cSf4xz7RXr/3lD8swHn/Pc45yzkvz0+7/kW5/z5nPMpznmJc34x5/wvOeeBdxvO+b9wzq/knFc45+Oc86dyzj+d6T/uNMV4uYhVkMWezw1Igk4ttiNSsKRwvxrWWjqskFAanSj++qhGfQF927k8QGmTiP+oRn3BDvppEcW/0wj5zqnij6KUyJ01dpNAoTtrFcBR+Rrz7kxwP6iG+P5zxdET/3mTnBfEzk9hWhw5g6TrltMj/jS4ag1iW1prg3MnAG/Pd8bHJSGFY2ijrZvRlASdEv/RKf5qRRD/vB5+rex0W9CYvbDUofkHJ2UEoyC2kw/IIsiZtACZwb70hPtRu+1SDLstiNV/FMRfaS64RQrOgYUYRQpAvF62CCdQCiXifwznbBb788EUiX+9Y2AOK+KJsbgtCYLgbmbiuhc1VJSCKv6aogDdJrD0cO8ZJvfIJyH+k6JY+O/fPQTnz73jc9GnMdOCRtk7OYi6gUrV/jczJrd81PttycMG/NUlq7+49oxTq3/vNXccWcHNDy24LoZP3yFI086p8MLqMFZ/l/j7Wb29RWdCPmOBFAy02hGp8Bj1+pO3xDls5Sp2QSELSLPobdEgabI/PWa2T5VwziZxnjx4so7uKRGS/KDmH4LpQkrMt+8nH/z2waBXR8aSQ/xp4cfvfIkIk2znRGcIq7/JocEQIxyZAhRSHuF4GuC0IP4bGD0qeVUi/nojnBwoRE0dGfH3zKW2eHgoTZeogZmnklPQLALUsDpI8efiwqyNyJIO2L2PHfLd1WshBIao0k1eGCnx30UU/wPLHbnivxJ809EIcc2XM7LkeUCJ/yl9MPGvtXWpr1FJcS4wbW1Z4+Lc7tSjEX+a8q4Uslb8xfczxlqwuKz2BYFJOQSjU/xzZHJHUV8JfW23SUafstGqBWaR2CWb4d87LUBqWQQQesL9ZipJiT8N98u+xx+NBcyNi+8t7kg/Z5Tf0BZhet1besSj+Kdo9fcq/nH6+wGJ+NMCQhKrvxOuBfSs/vP3AbxHKmfOkvMyPBkSUbB1cvh1QTOU+JP9SEf5UdDCSq3fljws8Zd7/Ini7+nxv/mhBbz4b7+FV//Dd/Gkd3wVP/2B7+PPviAKINedQ84JHwwzzq/WMZCTCJYqCFbH41BLqrjSMM2Vg1LhMWoxr2iKda+Vz3BN4VHWAUh2/Tg4RtpDtldLUovQF+85CX1FFHfq+VmEQgr3s+8nn7njOBZitEv4Yam3/1MZ5weAkcJJVR+ux18uRkzbQauPMTz2/kUbiATGGBqE+Hdqg4g/UdpGNNNdtvrbleG1kFAao02LE+ul+K8NTD4tWuKiqY3Q6g/IRZtw4i++79bIrf5inxxZaoF7ZvIGIU+yEwqV0VRpaWDZCZ0ccwHEf7WlY2wE1kGq+OsDLN8OVNrznbXi7+nxB6KlgFPib42qdx5AnmSijJmroeOw9DYl/iPuDySLJ6Xtfww6yHPxfeeyGDnoUfynKPFvdkP3IQUtSGXWZkbyZNBcxOZxsa1xx+c5bQzjw6aBz5KJxQv34xyygH94vh55/w1CvWNgE1Hqh1H8Z7lYR3SSEH+LhPuprD/Rn2JIxT8pqOJfynvuizT4Mwrx91H86Qi9R+bjF3ikcX403K9IFX8dX773lPvzQr2Dr953yo0cuHLPFH7+BjEdxg95VRQV4k5wqLcNVOFR+x2CNch9GhWSYHAYMxVRQHCKc4OQJ8SfZ9XfD3iIv634Jw34o7kQ23rEn3bu/OBuUdxpF8KLO1Tx36Ha14iuaeGm++eD3hEJ/op/cuKvTAniP2Um3zbD4ukEDp7m2CD+j2PUFbGQMAYp/ga12I6IrJLF2DSzq8BrIaTaJIq/5R0JkyVIKEkVdSw3wi/YBWS84A6BReZ1t0Ks/tY69viPFTRXHeyaFhoVYvULGOlnmBaKxElRKI/G6p9TFVR6qs8yJ99lM5j4ZxkW9IKL7ZCbNS4Wj0bAtnhBx0wqWRekaKp/rxAShSjQ69DIQvMAKGNyYn5YKrYuZY2MzpUAAApxJuQ64df0AiH+mTiP8rIim1MVN4CSc0ROiFYNmi+T0XGpFYTiyE3sLotti63499SwodPAp/fZVlMAWDmMqma4ToSOYeHwUrJxbxSWxW2rv6T4xyT+pMd/2hLXmkSKv2T1Z55gPw/x9zhKooAG5yWFRKxDFf+A4jPt/fch/udtEfeEu49Fy2ehqEdI9a+1Ddx3wv+z981V8Pc/eUVofz8wXI9/vWNgOqi/OxPif0hO9o+s+BNimuVYVon429ftpFZ/r+JfzKm4cJs4pjaxFfexXhrg7inPAqq938Z4HeXe2jVJQYrCcXzJ4/ySh/vlCPHfZCUn/qbJ5eOSFoQfQ9gg/o9jNAjxH2z1H+GoLwfFSbe/u8I6KKITSvwpWbVGaAOGlkdXtRekKuPo1IKJlmVxlKjSNkKrPwBwouR2GsGLim5T/K6rlKCNaDSiA2r3X8iRXtcAxb/eMVBhZExiViE8PnDs/iuU+Aco/mstAxOUEKQ8F/h3XnQB3vqMczAxJVwovBVtIUXD3tQR9vhXeouJKKqRRPxHOApTHpUXHjRqdCjxH63ir42J731QFkGRC9UrX8oi1V9W/AFghqSqR7X7a7TNLMuiM3GY7SqKv3kqpuK/0Pt3jQ1b4NMKwNTe3g8cWHwI+0mffxoBfw6JlXv8k1v9q5bIlRg+1V8JDvYD+sf5RcgI2RJg9e8j8CFoSoo/eR/n0Yj/AKv/WXMV10Z/fLUdK4UekK3+VPGnxfta28C9x8U9/i9+7FK87ycux9+9+nJ88uefLLlzgjBMj38f8acE69IbxeMLXhrrcyV4iP8sufZEtaqXLUJMU2zL64OP4p/U6n90WSb+APDuV1yKF1y8FXPjBcwR4t8qDrD6K0pfsj8APLoQEgwdAYL4p6OuF2dFW8dmPp948oBucUxhg/hv4DGMlipunFZzJfS1KrFRW6NS/BnzSfYPVtqsLnUljFZp6+bFTUGvBYdqdU0LJTLjO/MQNQ8YWYx3W8HEn05IMNTR7ktADvg7zMlCKYD419qGSyABjC5JHcLuH4X4r7b0/rTvFLF5ooi3P2s/5ubI4j2KgsK51POdCRGkoD3+Maz+Gs0hyI3w3CFkaAarWA11HpGQ0RGfO7kxsVAZt9ZCxySWyPmSzyIM06cHe5oQiqjztDUS2mlm+Z2Te832nPib7/nKg3j7f96Gz9xxPNJsel/FP2mBj859X3hADuo6NXyfv6MOD6X4l6aAnsOuZDVdVTBJuB/t8dcYgkf5AXZopnOf55YU/BmEgqZidqyf1MYpbMvhfsQJ16kBTrZ0rgxoAeR5gNVfUxWcvzW56k/dSEGK/6MLDSz3sogqeRUvvWw7nnvRVrzgkq1Sbk0YhiH+tbaBqpToT0jf9b8K7HkKsPvJwPPf3f/mqOgj/vF7/Ask3C9TMaE8655DVdZABa3Eij+1+m/v5UWct2UCf/fjl+Nzb30y5iDO9fL0tr7392GiP39gWOK/3OgC4JhGgOsjJvKTW9HldhFumtXRaSYripqWhamUcgdOZ2wQ/8cxKPE3B9iBaXAaHyVZ9Un2D4LVFRe8UQZ/AYBJ0rTNZjDx7+iWPOprlOQFgEpuXmYreOHYJb+zRpie7mAX6fN/UCdV6YCRfn3Efz0Uf0Qj/jTcL6u5wHRM4KDxcwAAMsqvzXMo5DMOc6Q9/j2rfxRSpZJ2BJZ1ACEFLUAOUPwtQvyNEVv9GdnOKdQCCxSGaaEIsfjNZVHokazYNnmZThDwR4m/kcvQIUVcHdu5rMR+4tajePO//xDP/auvoxkSMAsE9PgnvR7NktTthQekZP80FH+HJFIVMDbxZ0x6j5MXMKzin2+fFNfR/Lj/WDe6X9vRCLKf6t/oGJFVQvr9S+F+UYL9ADnV30fxByBZs+86Fs/6Xu+I/T4W0ON/ywHh8Dx3yzgUJeaoSQB5NUWrP1VWK7PAaz8NvO6zwNiAHvQwjG8FlN6/uXEKm0ri+43iougaFkpE8U9z9G4fFMUTpLeI4yspEP+qfP+ZVRrIMfv4WEMZL7w8PMcBgK/if2CxETphaxCWmjoqaKPIevenXHm4VgpFwUkmjpWVYw+FvDgYxobiv4HHOjoaIR00lMYHtP+Xj7C3FqRnddCCm1b82agCCHuwaLUyJE27Y5goSTO+R0uqNZIpYIYkIRstcfHjIy5OALLif1eT9H6tHPa1dNpWf7LQHmFxyiH+TRRgsR5hNloSmXaw1tbTUQIHIEfGz6l6BIJAzp0WCigN6O8cGrTHP47iT0fQjXAUJgoT0CHajhq1YJLBKfEfcQFSyhth9cBCaUc3UKbOoyzOccmKbV9rqOoWVfHPkYAtU8uQ+G+5xH149iMfAkP/8XhgsYlvPxw+JtH5dw09zg8AZoniP38/ziXJ/t97dGnogL9aGoo/INn9N/XaBoYN9yss3it+sflCSAllDui2rh6J9Df8Av4Mi0cmr4Gp/nSUX5gtfIz2+J/yfclF28X77z4aT/EPsvrTIsAxoiaftzXZsZlTxfdhWjzWsVhvG9kTLFWTwum2QfR+R7n21DsGxkiRnmV0r3bhSfY/VWvDiFlQqbV11HrFvIKmSIVW+wWi0DQ+swMX74hQzCAFib15+zrR1i2cWEtWmADsfJcZRo7ryoCWgwhYLIjtPP7oPYk+Y6PHfwOPeXQ1asUMqSobXajcvpjoXIWSy2ikkh+o4o81rLWC1RZOidaIiT8jliA1JE270+2iwOx/gwUGaKPtAZbG3IUQf5NMSBh1cQIAdpMe/weWLdcGB7Pja+mstXVUpILK6LIThDWSoUNaPvxU/36rfzaLibw0dz4e8W+igELWxD9XdoPLikyHBiMSUaA5BMooiT9jqGtin3bXgkcG8fXKGgEka+J0iOLfJiMH28hlM7JIUvx9rP4R+2zzRPHP1G125etdB1Z5+T68auIOAMAFWydwxW7x3R8KCdUzTAvLTUfxpwW+hGqhlOz/IC7ZUXX34fHVNm5+eCHZ5/ZQbxtQYGGG2H+l0YZRQVTszT3Fv9FJQvyJ4r/gIf5+mNknHi89HOlvbAvo84+6vc0gqz9V/MNmkkvhfv6K/0XbCPGPqfjLqf7iOh4U0Hv+lmRuFMZYYrt/qOKfJohLZAsXRZYo155623CDZwFkdq924bHUWxyYj5nvQCeQbJksSiN+AUjHGxuPWOAjxZMn5g65jw8MYfdfbnYxS6855eGJvz6xx328evSBRJ/Rl+o/RPvB6YwN4v84hk7mkiq0Wu0FmeneQgEFLWNSQEEWIYMUf4UQfzZqJZ301ua6K4Gv04mS3kbBX8XIEMUyWYDqwcSfBiWyLNNsA0DD/Q4utcClcVv9jop6u+MqmBbYSBPfaU9kS6UuGn/iP4rFRHFc3LCkZOIgkHyMNs9nr/gzJqW+V9COpPhLs+dHHIzZyot9aqz5K3UApH058jYZcp5MsXog8acjB9vIqPjoE+43TUZqRbX650zaZpZhC09lFrjqDe6Pf1T9LD731uvwqV+4Ds84XyySw4j/clN3DUnTGlm0p2H1X3wQebOJl1wmrLcfvSWayh2EesfADNagst5Gl6aDe9PDML7Vfeikhh9diT91wCQ9/mrtqPjFzNn+b5gmVuXFaMR/a9W/GEeV8jC0ghR/aZRfSKGnNC0s6O1VX2fY/i1j9lQD2C6TUKejB8Gp/v7tW0kVfwAoqPGJvzNJYiRj06oi9G26K0hvlB7/WsfTljdSxd8u6B2Lafefr4lrzqZxn8lW1GFCC1Bh2HmV+/Cq7ndwBbPHAT4yDPFv6B7Ff4iWjh6Km8U1wop4LfDCsCw5d2BD8d/AYw1GPmIfMFEDGygiN8qEd1KV3MKWQ3v8mRT8NdoFd2GcpmmvBPYL0t759qhnfAMojYkFqBoShkRVy5Eqqz3MjRXcRVWtbcAsEru/T4ZCsy5uIrpSzEbBDAAl/g2Sm+FH/Ne8Pf4ZLSYKY2J/VXhjcP+8R/EfNMopFRBiOIbWYOJvWciTJHptlD3+ADoFsTjlARZdAIBOFf8RE3+iUEyxYMW/2xLbmNl1yEfxn4kb7sc58oT4F8cy7LMFgGvf6gbGKafuwvnlNagKwy4aNhpC/Ol88GmNZo4kPM9LVWFnN7vAO7bjbcvvAGDfX75w94nQoMlBqLeN4fr7fd7n9PgnCQCjir/aIK6aIHVyhhL/aH29W4MU/wHZDQCgm5bbEsAY3PR9ANF7/BUFqJDwVZ+Av4Km4hzS1hHH7k/D/YKs/hTnJlT8ATngr2NGc0w4+3kkBGtKEP/xxkH38Xy9MzDToV/xzzg3iBD/H1W/ibPY0djJ/nT06Jwf8aeZElHP9a2XStMVfi/3QSiwcNfRVdx5ZDVRu9FqS5cdHykQ/9ld54mPaxxKlOxvehX/DeK/gccaTEL8tW7IjYXOdOcF5LQRHjaTYj7nNrYQrvhL/b+jVvzFgnvCqgUmGhvEQt9dB+JfGa+6jzUzRJEh3/molVXAthHSxXZLyqPoV/wXFkUxQB/V1IkeJsuC+NdZOPFvNBui1YNpmbV6MGI1nWCN0IIZAA/xL2av+APSQmqMteIVJ3gh+wBC758vikWA0gq2WDOi4PERtxxJij/qWA0g11Tx72R1HfKOW4Mn3C9Ksrbeggr7uOjwHKpjGV/XK7P2QtfB4oMAIF2LwhR/Oh98Mi3SQO3+ACYf+RReNWeTmI5h4dN3HEv80bWO4envjznKz4GP4v/oQgM4/D3gC78pj+ULAOdcmkKhNElxbSxAnaROgIhWf78efyCa4k9t/pW8Jlupo/b4A3IhI6CIeAFR4h86FT3IsRGg+PtZ/bdXS5goJr+OJrH6O46EkRCsTRe4D3Pzd7n7oGtYAx1H9Y4xkiBeF2c9HVDt6+MOtoCP5X8fp04ej/URsuLvc12nRaY4Rb5n/6G7VrlIOYBXqF/Dh79/GC/622/inZ+7d8CbZXQNq+c0ou1Fw1v9N+8W3/VW83iiDALd9Ewa2Ej138BjDRa5OeW6IYo/Jf4ojFbx9wSehKkbKiH+yoiJP/NYbFda/jcVOuO7M+IZ3wAwNi6+87zZCqyK0nnpuXUg/oC82F5j5KbrY/VfXCbPjTiMkCr+g5L9zaY4z6z8eHatHuTcnkBzsCo4aqs/IJGhSFZ/KYAwL6ttI4BVEqqEFjK5g547owyZtP9eGTqzlZ4C09Fo+Ld5GIT464qPMpTKtoT3+Eey+pM2sxpKqJZHkC9DyeSCrSJ7iX/QdZMmaktq4TDOnv3P6Xvq54pfdB//z23JiX9qij8hshcqB8FgoVavw/r3G4Fv/y3w8TeEvNlGSzfhiIfFnAIlCkmRrP6P+Aa/ehGk+Ncj9PhTm38p77lGRu3xB+RCRkCy/95Z0u62GL1tItjq30/8n3rucEprIuLfcyRMBY3zSxNbLhaPT9yJbRPiux80Ls8m/imdw1FQ3Qn82Iegq/Y2TrE6Jh/5TKyPoMR/oOIf1eoP2FkJT36b++Ovav+JCdi84EPfORi5TQaAuzaeTTncT5neY7d5AtjOFnDXofkB7+iHaXFUpXF+G4r/Bh5j4IWq+zivR1T8UZQu9pmDprKyxdBwP0r8tVHb04nFtooaVpr+RIuO+tJHPOoLAAoVQQgraOHzd/kvOhTSNpEvrQ/xpwF/SxbZBh/iv7IiSDbLYiZ5CKTAMpMcdz7baZGRUzxLBYESfxahR7TP6j+Cc5wQw3HWCp05D0C6DrVG1Y5AMUbaeTrBij89dzJJyx8AGjCp1/zVRJNch7pZXYe0guhltnTA6GB2TCxGI1n9O0J9afAipkZB/GcJ8e8p/pPlHCZ6amFbtwJDtz56y2H38URaWR5Pegvwmk8BL/5b96md81/DHmYT4+8dWMKJhDO/6x0duxkl2AkV/61PcANY97MjeJn6DVzMHoHS6hXITt0D6AOIFp0/n1eBWgSrf2VW7NtuDWgMXuxvr5ak6QgOmpEU/4BRfoCnx78a/kFj4VZ/QB5pezDEZULBOUeDuhII2a94iL+qMPzcUyOMc2suBRZUkoz0G6niX90l7oXtFVwwJv7mIOJfaxsYkyZzjGBdce5zcfx8UiRbi5fhMZD4U3dJ3CLfk38RVm89PsvW8FbtEwDs6+GX7w0Ou/XCWRun3eOPXBG1vH1eqYzj8CP3xf8Mo+MWbC2mJg9lPc2xQfwfx1DIXNKCWQesgIW3x2KbV0cYSDe+FbyX/j3HVtFuBfcN5kjwV7446lAt0VM9xepusrMXNC1fV0dP/KkCWWYd/J+P3YGDi/37NEdUy2Il40p3AOjC54RBCJSP1b+2Koh/rrR+xP+UQb5TH8Wf01nTWS4kCNGYQAOrAcejCy/x9y5qswD5929nC+gEtMe48Fr9R6z4q2SxXuoGj+xUaQvNOkzE0AviWmQ2/LeTthzpWTmPGJOP8U4dUxXhjlludgfPgqbEHyVMlUfQ3jFDAvUWHnQf0sBRvz7/2w6v4PsH7HM+p7L0pncwBuy9Hrj8J4Gzn2U/BY5fm/4aAJuTfebOeJZgB61WC69Qvyae2PaEZNtYmQGe/Fb3x1/TPozr1Lvk19TCt7FGiPeWQsee4ALYDq6gayVjwDRJ9o8Q6qUoDB/52Sfhn157BZ53kVA96zGt/n2uKKnHf5DVf7DiT0faHoqo+HcMy+25zquKJNJ4BZvnX7wVO6cHXJ9u/hvgz/YC//gswOi/hyS1+hfQxRjrrdcULTsbPWPSmM4nkFT6Qf3zfYp/YTQkcHyzyCXINaMTagA4NZD4J+jxd5AvQ3n2H7o//pT6RXfc4WfuiH79cYl/ylZ/AOhKyf73x36/QtaWer468vDtUWGD+D+OUcjnsMYJUWkH2P2J3XLk4X6qBj4m+gdL7eALYU5K/F5HxZ/VsRqg+NPQvPUm/hW0UesYeMdn+yujdGxasTxaIu2ALnyOdsi+8tisV5u6pAbnSqMtVFAV86QeTPxNi4N1BPFXSxkuJHJFdJldkMgzE/X6gB5Rsv/avIDiKCZ3EJLxevWz6OqDXAnimBxZACFBblIs1itG8MhOjYaMrkMwJidBmK1Vf8XfGtV1iKbwd9ZQ0FSM95RH0+IDW1A4If4js/pLSfqCSA7q8//Hbz7qPn7RxVuhdMk5l5ZN+Jo3uQ+fYn3PffzJW4/EDgIDgLMXvoItvTC+dmEWOP/Fybftul8Cxu2JA3NsFW/rKYIuBhB/qvjvyJF9N2jsGA34i9jnP1nO4ennbZau3bF7/L3WedrjP9DqT3v8A4i/NNmmESmsjBYv6Cg/B/s3C5fV25+1v+/3ffjib9n/P/J94I7/7Pt1Uqt/ldr8S9PZEixi99/PxTk6KDG/1tYxNspwvx4mNwniP2UsYGVQ0Z6AKv6bi6bsQgGiuWjCcOGPojlhF9ryzMQ5zJ688cV7Tgaueb1wRLEZyfGRDvEvbBJurfbJh2GYFlCfB8xorQisLYi/WXxs9vcDG8T/cY1SXsUayMI0kPjTcL8RW/0BsKro85/sngxUiXKWuOgVRm1PJz1qU6hjJWBBSxfcxroQf7FfymgD4LjlYL8qSMemlcbWR/GnC58DTbLg91joDy83UYHYXjbivmpqP5YKFB7if2ylhQoXhEHJuGewQyYMtNaCFWoAMEmPf4sVkBuFq+eKn0ZbtY/Hs5Tj2H3sc+Gvp1Z/Xhy54l+YFAulCTOY+OdMsVhU12EUZmlSOBPWFk/6EgZOrP6mmmHWCP3390j89Fj0ZP9mXdyT2qw0mnvP1F6A9UjT6mG34LRrWlxXDi3KJHu1qeOzRHV/wzWbAd4jiVoJUFNyKux9qnsNH2sdw27Fbjm56+ganvSOr+JXP3q7vdiNAs5x/dLH3B+PnfPjyUb5OchXgKf9RvDv18KzCCjx3q7RwMEBvcg0kyFisr8DSt6pRT4IoVb/pIr/KX9LcrWcl9pLqJobBKldwifM709fdgleetk2/P1PPhF7Z2PeJ+/6eN9T+QTj/GodQ050z7qPmhD/HR1xfAwqlDVaXUyCuCFHZPtWJsW4zi1sOdZ0DCfVfy87jnM/+nTbrXHvp+xfdmpi4oxaGNyO4gfGUN4pwk+vnxLrikv/4It4+0duG+jiWnGJf8pWfwDjW0XRdot5DEe/8l7g3WcDf3elmzMTBq0t7uu8tEH8N/AYRDGnYpVT4r/i/8KubAMeqeIPgJFk/61YDOyvpKO+Rk78CxMwe4vFMutgrRagsJJ9aa4H8Vdzbi+mxiwUoGOh3pWDtjhHkYubYiXrEVoB2FYtQXVmGbeCFf9DS01hGwRksjEC5DXFDfhb4sHhfoeXmrL9N2Pi380J4t9trIS+Vg57K8lp1VmhVMUdO17t/njl4X8KD+daj5GDBOUpsVif5MFhqNR5pK6D4l+cFIuoorGKw0v9C1wuXYcybEegBGfFttnGCfhr1sQ5pKsj2pdanowB467qH6b433ZkxbVYX7htAhdMk/MnTaVQzQE7r3Z/fN32w9KvP/qDI3j7R26PNmJr4QHs69p22A7XsHLBTwy/fRe+FJbqHxZpDSD+ktVfIefXIGVSCviLN7+7Qsh7FMW/FWb1j9Pjv+1ykX9x9BbgwDd9X7aHkPMoAX+S4p/vJ/5P2DWFv7rxCXj2hRGC3XTPdePQt/vIkzzOL7riP9KRaYT4z9YfcB8P6vE3m0vIMfv77mrjQG5EYczjgvhvZkt4ZD4a8e8aFpabOjQY+Jvc30CtHwO4Zbs2jI5wbwD2OZX0Hk+mjNwwsyL96hM/PIrvPBIcfAsAy00dDBamkW64HwCwGdH2s4edwPgP32f/sPQI8OAXBr4/3yVrtspjM9gP2CD+j2sUcyrWKPH32oIcEKt/E0WpyjsSTNKAvwVc/Sdfwbu/4Onf4RwFCOJfLI14wc0YOpogyN1aQPgXmfFtautA/AGpcu0kOj9wktyIzS5U2DdxnasYr4y+TxkAcqqC7VV7Hy1LhFpWrw8tNeWbyDpUamd6KuZqCPE/tNTEuBQWlC3xNwjx1xvBCjUg93wbWSrAHty3+yfQ4DZRmG0fCFcFPeF+o1b8K1OCgEzxGizDnyjkSZvMuozCJAvpaVbDPcf7ixScFFEyvQ75jFubkYh/uIrZbojz2hhlUKKkIveP9PP2+N95ZMV9/IRdVYC09KRe4Ntznfvwxk2H8cbr9+HSnVX3uf+5/Rj++VuP+rzRgwVBgr5jXYBiNUbKdxAK49DP6p9CAADzxw6EvpWq1ZtArleDepGp1Z/8m6JAUvwjEP+g4DwA8RT/ia3Apa8SP9/0Tt+X0WPOL4unb/sCEv0ToeFZwxht4P7PSk8VEvb4jyTR38Hsue6YvGLjCCZ6f3uQ4q81hC2+W0pHkY6E8jSMXpveBGvhyMlo6fQLPUHsLdp/4SLlgPjF8gHgT7YDP/iAeG6Ylh5C/C8pnsRLL9sm/freE+FthStNHZNoQGO946UwaQfBpgGSz3KVch+m2yLTAYe+O/DtBX3FfaymVIw4HbFB/B/HKOVUrCKC4u8J1Rq14g+i+G9jdjXxH775iKxqmDo0QlaLxdGPytPzVffx7Q886ntjYWRfWtr6EGraw3p2r0frQUr8PQTLb/7vqLBz2iYlSyCqWbNfSZdGUsUZU5MSZiv2jWtFKqTJ23lwqemZC5xtz6BFCgtmcyX8tUQBNkY4bYKVq3iIi8IeVg8Hv5iO8+P5kSv+Wr6AlV5hR2Ec9RX/vJE8F0pSbj0mYpCFdBV13HOsf2LLyK5DPmos7aseZF/uNMj4y9wI96UU8Nc/0u/h+bpk+779iNjOS3ZUASnEM23i/xT3YfHozfiN55+P//r5a/Hqq3e5z0dK2V4VieGH+Vxq1/n8Za/wfX75+MHQ91G1eiYO8d90PqD0Winm75OTywdgLKbVv0W+8/5xfivi8aAefwB4yi8L1f/AN4AD3+p7CW1388uV8KJBtq+vMBEXfhMS7viI9GPScL8ZRookWSv+Wh6YO8/98QLFJoMnVtuhtvRCW/z7jXLCaRdJwBjaJfH3Vk6GnzcO5msdlNDGm9RP9f/SIq2nF78CeMbvJN++uXPdh+rig/irl+zBHz9TbO/D8+GW+pVm12PzT/H7nzsPVi8TrMI895ZD3w59K+ccZV0cl7nxDeK/gccgijlFtvoHKv7rOM4PACZFj/92Zleh27olqy6eGd99N+URoDAhLhSNlVN4+Xu/jZpnjBpdcPPcOhF/cuHez+zF3wMnidW7TR0eBV/L4Kiwedwu4KxwSvz7rf5zdCGRdCTVEHAU/xWEK/5jac32jgCtXHUfry4Hj58D5DGTo3SiFDQFRzm5wa4EE386gq7FCtCU0SfurihCyWsu+YdyFSTiP3qrP3W8zLI13HM8nPjzXJaKPw1eewQAsIXMUR9ktzWa5LweZQuPz0i/rdWiG0y42OjiZz54C9q6TRbvIIr/pTuqsuKfdoFv22V20j1gt0+8/xlg33kvXnftHvclg/ar/V5xrh3lc8MrxD2wc57t+7yxejT0fZT4T1kr4heDCrn5CrDzKvHzIzcN2EKBciGe1Z+G+5Vp4dHoijUIU6UsnUBM7wUuvVH8/LV3And/EvjYTwNHfgAA2D0d1+ovtm94xd+H+D/0ZWBJuEkS9fi3DTdQEgAwvjX4xWmBJPtfnrePe93k+OZDC74TOgCgSEa2WnET8IcEJ/ukuRBSDCc4VetgDzuJIuutOZnPGvjqNwE/+v7hFPaZswH07r1LDwN/tg+v+tZzcI1yDwDg4VPhxH+52cWMZPNP0U2hKFDOf6H/707eJU2J8aKtW6iS7VI3rP4beCzCq/jXVxdcu5AEUhCooTSa4C8KQvx3KMLmTe3pnPSjtVHo778bAYoT4gJWRR1HV1r4n9tl67JinA7E/3z3oZPKSvdlsy4ufm1WhLIOBMvB3IR9g6qh5GYoQG9IM6H7FP8R36QBQfwbKMJkvQWX3uzbTlnxz5b4T1QFoa6vLkIP6cGkPd+WNjq3TB/xXz0U+FqTFKS6o8oh8GBFFYuBj3z1O3joVP9CokiyRvIjHi0JAKgKh9RudgJ3D1D8keV1SBq1Zivn2yZFoeH4Srjd1miJ/auMKFUbgKz4H7sN4Bw5VcH/ea4omn7roUX82efvx8m1Nk6u2d95Kafi7E1j2Vr91RywS/T54+gtwBf+L7a3REjc8QFqJgBwcq4d5bPDK8QOckUcvOgtfU9P6sEkC5CJ/6RBirtRruf7niYexyD+8cP9CPGn4oLX5h/12vSUXxEE7dGvAx99rR2i928vB1rL0gjJKFZ/2i7hl+ofC37EHxz43vvdnyTFP2qPf8fAZkr8J0ZB/EWf/xNygkj/1D99Dze8+ybc61McrXQF8WeDAiZTRmFKuOBytUOw5h8Mz7+BrfjvYsTtctbTgQt/RPx8wUuA57xj+AkKuRJQFe4icAsKN/GLqj3FY7Dir2cS7OciiPhzy55OEYBaW/eETm6E+23gMQhvuN+/3XQHrvmTr+Cuo56e0Jogr6f41Oit/hPiIrhDXQJgXwAfJJXFTouMI0PeDYUbKcpijNYUs7ftjsPyvlTJqK9MF9xhIIr/OYqt+NN92SLEv8PWKYegB0fxBxiaKumb7PX5mxbH0ZUW5uhM2PUg/hWngs7Q1shCn+QRHFxsYkIaD5Qt8S+MieOxbNVDb8h0zOQoW1CKOdVD/I8EvtYgin9ms+cHYK0g+hlPHX4Qb/iXW/pS80tE8S+sB/GfFef3Wew4Tqw2+0L0FHIdyrQAWd0t7My140C3EUvxp+P81FGO6dx6qZ3GDwAL9wPHbgUWH8ZPXj6LX3m26HH96C2H8b1HxTl+0fYJ+95DlaUs5n9TottD+cBX3RT4rmENnJjAlwUBmlfmUnXy7f7RPwTe9E3gl0XP/Sa2jK/c4++SATyJ9JT4R2nd2neDePzw/w4kSQ6omy2a4k9S/WmhJE5/P8X0XrnX30FrCbjpnZ6RfhGs/h0D57FD+Ovc3+C62uejb4fvhxHiT8QC3Poh9/hONs5PlzMcRqH4bxWK/7k4IP3KtDj+7bv9dvpxcgxqk6Ml/vkpIXb9kfL3UP7uCuDLvxf6nlO1NnYx0uIztQd4/ruBS14JPOktwI/8P0BJ6Rwnff4OnqTeAwYLC/Vu6AjCfuKfsqV+95NhkZG2EkL6/NfaBrYwkh+1Di2jo8IG8X8co+hR/Md5HYbF8ek7PPN218TPJ/jUyEO1UJpyrY15q+WOWKEqdacuTtjWepFVYrGtwt6224kFFPAQ//w6Ef9NXsWfY6nRxWLP7dFsiv2qjzDozQ+bJ8TfrzFq97e/74OLDeimhU2S4j96q/8sGVG2ovYT2dWmjtWWPtJUf7oAnWBN3H20X9VwsF4tKHGs/pZn8sB6YP95F7mPd7FTOLDYlMctmQbyzCYHJmcoFNdhOysz7rWozDrYiqU+RYtehzIdf6lq9gLUwdIj2FaNTvwZCZbNlUdI/IsTtkLm4P1PA/7mcuDvrsKbr5lxCVmtY+DdXxRBs5fsqNoPpB7/DIo/V/w0cPlr5OceuQnbqsRNMSC8jOZprBZSXuQqiq2yjm+2E9EBFJiB2x98JPAtVPEvE5t1pELutieIAkvtGPD9f+gb++qHyjBWf0nxXxGPo/T3U1z/y/627O+9H5tbj7rrrZWmPnBWer1j4Pdy/4IXq9/Giw/+CXDy7njbIn0YIf6XvlK4YDprNgm1LORVsd1xevwlxX8UBGvzhe7D7fpB5CHvx+8+0n+sTBriudzkCIoTFH7FkG/9VWhBq0/xn95rk+of/XvgOX9sK/VpgYhHFBeyAwCAh0MmESw3u5iVMh5SJv5qDsq5z3N/XONkPRPS51/vGNgKUnCc2BH42jMdG8T/cYxSXpVOiglmn6zOLFAXNUr8p0ev+DMm2f33MFs1uJ+kh+rLQilcVNapN4dYg6Z7iv+Dp+rSCCDVHNGCOwyVOZcYVFgH22Evspw+/059xX2psR4jBwk2TYheNCngr6ekf+mek6igjbIT5KIVM1fS/TBdEdt5UiEL1WVbSTi8bBPrUab6y9MbVn0t3y709XGiFDQVxyTFP6SfkTiP1rT1seFt2SOKZrt76sp3yKLRJOOumiiisA4tRwCkhdnZylF891F5YVswaO98xq4ET8DfFmL1P7Ha7nNMUFDiXyiPeKzo5T/Z/9zaUbB7/hsvv1zcj2jv9SU7etuYpdUfsPMOXvzXwK+QufVHvod9E2JfHgtro+g2obTsRa7OVbQL2QVZWYTErIUElTnEv4Au8kbv3q5o0aa0qBqwV4Qe4rO/AvzNE0MLiYA33G+IcX6U+Med9z69D7i21xoxuQvYfoX9mJtQvvv/Yd+cyAu470TINRxAo63jGuVe8cR33muHHZK+/Migiv/YZuCaN4mfv/8PwMdeB1r7iGr1X5ce/+KkW4BUYbotjg4enq9LRRXdtKSAycLUiIl/UPtDyNSbU17iTwuuaYMERFNcp9wFILjPn3NuK/5Z9fg7uPqN4IoGCwy/q5MC6ZFbANP/PK+1OrLiP7HN93WPBWwQ/8cxipqCNaL4T/T6j+dp0nJ7zR3n1+Y5rKKC3KgVf0Dq0XJubI/MN2D0bjbmirggLqvrRfzF3z2vKKzodx8Ti+yKQW54cRcIaYExKeX2HMW+Cf7LzQew2tTRWTjg/q6eH716TiGs/sCiSQolvYC/z911wtPfv2n4HrYEmCGK/2GQG9nKAQAikXmUqf6o7nYfvki5GfWDtwa+VMqeGGFBqpBTcMSr+AcQQXVNLOKXcutkw5va6z50Fll0bnGHuGVaKKxLDgEAaWF2FjuGr90vJ51Xu8ISaoxvR6agAX+LD2GsoLkJ8l0z3JKuGUI5Ko6N+Hq5+8n+i+cHv4QffeKOvsuMqjBcsadHUiWrf4YFvrE5YHPv3mgZuEYVff7HVkLcFKSl5jifRqmY0jgtH+SqYgHNa8cluzyFY/Xvy2uJak/e/1z559YS8PV3hb6lLFn94/b4997LOXD7h8WLSgE24zA88/eBn/8u8ObvAs/6ffH8wZvxgolH8P7cn+PFyrdw34BRaWh5Qlxv/ZBdAPnry4A7Phpvmyjxr8wBl78WOI/0T9/zX7hg7evuj52Iir/ZqWOiVwDnSi77VH8HZA15AR13B8DiwHcfFdfxRsfAJqy4P7NRFCcoxgNI5/HbA99yeKnZb/XPCjNBxP9OAHKf/3Kjiw9861F879EltHQTXdPCDkaOrfEMWjO3PQHs7ffiLy/6L3zSegqO8t4xpjeAk3f6vqW7egp5Zp/fDWVstGGyI8YG8X8co5RXscjFosSpdknE36P2A0xKch0ZSA/fM/K2fa1rWm7fW3NRkIJ2cfQ93gBEpR7ANeYPiN1fEP/Zrqg0G5N7RrZpfdhEiH8v2f/zd5/Ay953M5rHRV8mp2rdOoAq/icMokQ3l3B8tYXbDq94+vvXhxBSq/8BgxDZnuLvqIKjTPXHvhvQ3XwZACDPTPzMwjvAdX8yQHu+lSxT3j0oaApWUUGd9wo8eqNvGoIDrSbIyvK6Ef897sOd7BQAju88suiq1t01sfCqs3Vy9ABSn//Z7BjuOLoqglstC1VdFAKsrIk/DfjrJfvLAX/BBDVvCuJfHq+mvmmhYMy21HvxyE3YPqbgyWfJKvn/fd552O5Y7bO2+lOcdYP78NKuKO6FKv5SsN8cZsayI/7qpDi+NmMJDwWogY7iv4PFtPk7uPRVwJPfJhdabvs39xrsB6r41yNY/RtSj39P7r7pncCdhFSf+4LIm+yCMfuenC8DO64E1N73sfQw3nD0t/Es9Qd4V+7vceBI+GSEUt3H4eC4T77yB4Fqpy+8xF/VgB/7IHCJmESwf1kQ/6hW/xIZk2eNbRldoX7Lpe7Di5X+Y+LbpIBbaxvrGxgcpPgHEP9HFxp44MSqfO5kSfx3XiXuMZe+2n36SuUBFNCViP+vffwO/N6n7sGP/b9v41V//x0AwLkKOU5pfkSaGNuE6a22+PEDi2QSHPqO78utFbG+WM2tr+CVNTaI/+MYRU3FAS4W0LvZSSiw5NnKxFp0EnYle72J/2X8XhRgq0TO/Hl9RdwQ2eQ6WXQ2XwBsuxwAoHEdL1XtubzuqKfWMsYse3tbPL++4SFE8b9hWtibHjpVhzEviP/49vOwnijmVDewatGSe/w/f5fd8tGn+K8DZojV/74uUTBW7AWGUPxHF+4HVUPu5e9HC3ZR4hwcxuL3PuL/UtKCohRGR1iLORUA8wT8+S1e68i17eO0y1U0CxnYA6OgPA3k7eNwjLUxjRpO1To40CvsmAsPuy89xtbx/CbhS2crR8E58PUHegvu+glosAnAEh/D5GQ1222RFH97/2yV+vyDCWrBEk6U8YkESuqwuObNwHVvB675eWE51xvAwW/hF55+NjSFoZJX8bevfgLe8JRegcOygAOCEGV+nSf3xn2r34ETfhuan0BH+WEWWyayI/7Uyr2FLUstehQO8XbGggGQerMHQtVstfz/HgZ2X2c/ZxnAey4B/vVlwMl7+t5SzClwcoC7hhU6+QSQrf7lnGoXKb/x5+IFT3wtcPHLo2+zH7SCnVngbGOvLafAdLSP+quVDsYbITPfVw8B9382+nZ4iT8AKCpw9Rvdp3cv3QwGe59FIf6cc4zpJC1/lGsgovjfOPMg/ueFwAded6X73LcfFsS/WVtx58B3kRu9OzPAYdA9epvv85++/Ri2YhG5nmKNyiZ7zGVWUHPAm74B/MIPgZf+f24RoMB0PEW5E3cdXcOptTZWml185T5RZL79yCom0MA2x1Kv5uX7Q8rYM2Pvg+9bJJMggPhjTXCIemGdxMMRYYP4P46hKAwdbQzz3L6oFZiB7WweS42uuIj3Kf5ATlsH+2p1Z29+KJCHjisUO1Dp/hN2ZVEh21meXsdQDtIX+kr1JgAc/33bMXz8B0fw0H3ipn2Ib8J5W9fJ6g9IxP/J4yfx+uuEhXk3RPLy9rNiLLwyghPwt8yJ9aq1hC/ebaurczQoZh0S/QFgspRzJ0k80CE9qcsH7OdO1jCGJsYdxV/JZa8EAmBz+/G58R9zf27d9yXf12lE8VdHSPyd4KpjnBZLfIg/KQYc5bPI51IaPRYXjAHTe9wfRZ+/vWhcOyKs1guFdbwOzQniv4/Zxdub7rcX8vNHSHECc7h0ZzXbbeldt+0/eCsw/wC2Rkz2L1niuByvrgPxVzXgmb8LPPcdwCXiPMKDX8LV+2bww995Fr77m8/ECy8hxeYDXwdWeop6sQrsfWq227jrWncCwXj9Udyg3AYAOBqq+At16yifwRYSopo6iHq5BUtSKC9FrWf1d/qEAQBn9U8viIQbfk3++aEvA//1JtuWf/j7bgGKMSYl+zcH2P37rP5HfwhYvd7wufOA5/95Ogr2rmt8n84vPwAzZEzjVDvcEYDvvi/a37csoPH/t3feYXJV9eN+z8zsbC/JbrJJNmWTkN4LBAgECAiEFqqIhSJNBSlWsHwVKyoqYBdB7ChiAX8URUWaQEAglARCCukhvWy2ZGfO749zZ+6d2dlNm7n3np3P+zz32Sl3dt+9c+897XM+xzN67M28PnBauiOgfM9WJimTP6AjsfepEu2dSRqS7kCD8mMpvxSehn982zImP/pejtx4LzGn3F68fmc6wXG7d+popK//0wdjuTviEjka/lpr7n95LUMjPs3vTxErNY12pWDsKemX3x19jPU72jj2lse46YHXu5yvo5WnfG8YbToRCkRqOcwuI/45phOWtLjfeWt5783oD9LwL3rKS6Is0+7Nd6QyDeh0WKhnxH+9NhUv35P7pfAsYZSqHNyzYCVbWzoob3NvejWNw7p81DcmnpOuhI2LrGSiUyh+/N6Xue3eR9K7tVYPy8hY7zueQpANr/Gu0c53S2fG/KuGIcGO+IMb7r/Vm9xv9+Z0BbK/N1FQQA3/SETRt9KMrK/WntHo7Wtoa29n4eptmQmF6g8xoyc+0Db8hPTjmrVPdS30EnuIJd3GV6TU3+R+wN5H/Le5ocmrdT8nUiAguoT7w08fX8Y7O9poWedmeI/1yz0P0hdqh5pEl0A/tYNadvGfNzeybXcHby1xRz5bKwYV/ljWDjHL4wEk2uHPV9BU7Vb21nYz4t/emaDSkxOjyu9Q/2xGneg+ftPcy2vKSjLCxQH436/cx5PPh5IC3+fjFWak2eG62J8A3XNW/6yOtMbaAjrWNacfTows540NuUP9W9o7qWY3U1UqYaGC4cce2N9sPhrGnZH52rqX4fsz4c4TzAoNt0+DxQ9S6Q3330uCv9Y9nuR+8ajpyEoxbLbpKMoH3TT8m5OrWbG5+4zp9XtyNPxHneguqfn2U7C+56gBwEQyaOd/LavNbIhGInDIu9JP50bNMdiXEf9d7Z0Z5bWvc+drBsEhJ2S8FF/0p4yOzxfeNm6J7e5A0o5YQDmjjroegLVVE+nQ5h5d3ro+s0MGeGPDTpa8s6trRn8/meYOeM2NvEg/trG7I8GfX3TPx9RxHhPxLNnbf3xBtQb3KUcpWKyHslM707B2rU9HYnqJt7gDXh2VPud08Blp+Bc5ZSURlibdk3yE0/BPh/t7RtI36L4oRbqH1Hc8vf/HxEzDf932Nj5+78vUdro3w8Ymn296XspqYdzp6adzIm4h670xNw4r0LymfaWir5v8LdHBtLJ1xGMRhqh3iCrTMNwc7YcKaslBD6kEf+/ouvRryc3L0knB+meM+Ac3N6veafi3E2dPheOhEyxevIg9Cc0hEU+lrJvlcArBjMOPY5s2o/i1ic20rXk1c4dNb6Kc8ODVuoGyeAHDfrMoLTFF0BpvZ0muEf+shr/vS4p68TT8h0fNNb18UwsX3PEMaou7XFnDsMJWanokEslIwDRSrWV76x4uvOs5Vi93OyfK6ocW3kUpmP9DE9YJsPZF5mz+ffrt9d2M+G/bsSudbKmTKCoW7NKiDJud7kxhy1LYuaHrPq1bYdED7vNcKwMUgtnXpueFT40s5d3Rx3hnZ1v3jbFtmQ3/go74D52FdhqeEyJvs3Fd1+u7M5GkdU+CWZFFxJTjPHCyWZryQFAKzvuFSZjn7eTe7FkFYcsy+OtHqIu7x2j3Xub5e5f8qyzNavh7wvMPmiGzcr48Wq3usjSnl8ZOd6Bm7Rn3wMcWwfvuzaiT8NajuT/8yh/hF6fD6/fnDvP3Mspt+KciTPal4b9pV3vmUn5+jvgrBe/9A1zg3ntYv5BZQ9wIt+dTDf+dbiNwVzyghv8JX4TrX2PF/D/xum52X8+a55+KfBzmV2K/XNSPNPdHIKaSfKCi67J53z5vMl8/exJjvCP+jYUtI0tjUQbVlpMkwv+Sno74HOH+FW3ud56o6r0Z/UEa/kWPGfF3T/LhTsM/neBvhzfUvw8l0Uhwmaqbj0qvdzue5TQ4Sd2eWbySKmdkqF2X0DSowMmq9oZnzuUHh67n8qNNR0RqGUKAAcMDbBSkaJqeflj6zkvMGNonw3FXZYCREx76O5XSV5Nuh45a/0p6nvKgmKciFNCIP0CDJ0HW7go3zHv5W2aEdbTy9nT71/EzemAtC0vcxEbLnvt/mTusdzsCFiWHUl7iX7GQasB7R/x1jt54bw/9Gt0QmhH/80Yk0lM8lm5sobHT7dw5ZNxkv80y8YT7T3SyWC9cvZ22Te6x7DfYp6iEARNh7ufST8eu+DVltHNE5DV2bnkn50d2bHcbCLtVRSCrdWRQUpbZuFvzfNd9nv+5iWoAGDg1s9FZSGoGwsxL0k+/WXIHP4vdwoYt23Pv7+lIW6MbCht9Vlqdkfh2VMv/2N6auY56KqP+UZ6Ocm+E3wERiZiEeWf9pPt9WrdylHIbUntL8Jc5xz+W2fD3lKcHTUXfjASdKUZF1vTY8G9KuvW1eONYd0mykce7O+Wa4/z2f+FPl8Pyx+G+S2H9Qve9XA3/kXPTdbGpkWU0sXGflvNbvaU1s+Hvd7b8SBTGnOwuMZro4Jga95g9v8JMQ1CeTr3WeED5ZABqBzO9uYHFuHWfHctfyNjlDSfy0bel/LrDM+p/aemj1OJG9jRUxRnZr4oLDhvKOYM996QCj/gDDHPC/Z/3hvu//VSX/ara3e9c1wTchigw0vAvcsqyQv3dEX9nFGanN9S/bzCJ/VKU1cLQI9JPbxxleg69a29uivSlLB7Q/N8UnjC9hq0v8dl5Y7n57Ek0R9wbi/I7FCsX3krs2hc5YmR9uuMHQHnn5gZI/2rToN5CTTqbu0q0pRvSjZFwNPy9S/ot3eOOEmxZswQgM9TfxxF/pRQdw9x5xsm3/pW5g2d5m0V6qK+N6ng0glJkLOmnFz8Iz2ZV1kM14u9eu4PZwNfPMo27GlpoUOZc7KCEhoHBrojhHTW8cpC7jneTJ/Nz/yE+XuOHfyRd0Y+3bWRx2SX8Lv5VvrDxetjTNSx9y1Y32Vab8m+liR4Z7DZgWb0g8732XfD099znh17mj1OKoz4GNW6H4/HRF9HP/KjrfpuWwA5z72zXMdbqBgYUMtQfUJ5ovdmRV7n07gUZmb93tu8BNHMinganpwP9oGickJlnoWYwHHp5+unczifSj3ta0k9rzW5vqH/HJjchWElFzob6QZEVlg7QX21jwevLunScANC6Lb2SUJsuoaLB03jx1JtY9ayZw5+ibQf8+QrQzmuJDnjkM+77uRr+5XUZ38+50cf3acR/9dbdWQ3/gOZSD3aT+k3UbjLjV9fsoG1PguhutxHdXhZgwx9TR99ZPzH9fPeSxzPeX+qskpExkt4ngPrl+PnpJIiVrev4VeVtxDHn6TnTB5sBQ62p3OYebz8b/s8mPYMtr/0lc8lVyFjpJlIXYH4eH5CGf5FTVhJlubfhH3Ea/ju6jvhv0H2IB1nhhowQs7lR01PvLUh2ljR0+Yjv9B3hFpZt22HjYt5z2FCmV23N3CdoBnlGKNakGv7uiH91k3+N057wjkb9t80NTZ4cMWHVDZ71doMM9Z8zyq0gPLnZDR9MbF4BkBXq7+9Uj5GHu+svD295ibZWd+505oj/MDN31SeUUmgNL+lDWJQ0322EJDz0KXj1PndHT2jy6hCN+LNlOefMGMzwhsqMaJktpYP3ff3xQuFpODRtfY5vnWlGPAYpt0Ed6eNDqH+KaEnOxvAwvYbkwq6rTby4xP3Ok/GQrKnc5G34Z434L7jDrB0PUDcUprwHX6luhCsf55nqk9Iv1S2+p2tOj1f+mH747+Q0dDRO34o4BcWbnyf6Cs+/vYVzf/R0OnS+pT3B4ZFFjIg411BJRWZj9WA54YtQUmlWZjjv7oycCDPanqGcNipppXL5w7z20E/53a9+zNsbNmf8io5EMp2oLBZRxDd4Qq4HTM7f/P4Ux3wSjrwG5n2TjgY3yW7ynUWc+YOn2OpMdUvRudmdZvS2bqQ87kmaVj8SKpy6UetW2ORpfD18Y0bHKrD3UH+Aae9PPzwv9h869uTojMhi9dZWGglwxD+FpwOvcuNLjOhnyuuORJJX1mwn3uo2Ajsrgm34A5SNcq+fPhsXQKf57hNJzbJNLQxT6xmVql9ES/2LNPISr4DTb0s/nZx4jS9X3cfYAdVcPsep7+5cB23bzOPSGqgtfAN7WCqzvx7DO3GnvGvfAS/91t0pmaBPwu0QL+kzpOBeQSIN/yKnrCTCKt2PPU7ykIFqCxW0mTn+iU5oMTfApFa8Qx9KogGHW472VGrWPUFjRYQBuCP+HRUhyMapVOYcvVXPQEeL24scKckYmQmMgW74NxteYcYjZ/H+2D/TL9UNDj6xH7jJ/QAWJt0Ok8lqGRGSVCe2uTsH2PA/e3oTZ041oZWrtOvRP7meSlrdNXYjMd87foaPmsgqZSpZlaqdzS97lnXa4Gn466HphHt+0VAVJ0mE93fcyP+SnhHox7/tNlrCNOJf5ybOY+daottXcsWcERkN/866EET01I90M+p3tnJe/dv87rJZDIl4kkPV+lzBmXFJzpc7n/5hRgNVa80rb7lTEiqq6gpttm94RgpNRndnBLhjd+Zo/5xPFjRbdbdU1vO/SZ9nh5PIqmb322x+/d/u+1pnrDl/f+II+leXESl03p6mGSRKTOdNk9rMdbH7YPfm9JzqXe17+GD0IXf/KRfkNyli03T41FK47hUYcqiJAnA6X0t1G7eU/JjHSj/GtKevYsKzn+SCpZ9m/c8vyvgV3oz/FfEorP1f5u/PN+V94MQvw6wriQ90R0ZHR9awfFMLdz65PGP3jg1u/oI1akDmlEylMhMGrnLC/V+/H176tft6rkZ+dw3/saeyp9QkBR6sNjG+5bm9/kurt2SP+Aff8Gf1AmYOc1cMWbB8M4O2u1M49tQEP+Vx2pRpvJ00dYpS3UZi5bMArNnaSkdnkpMinuijkXOhNKCO0glnwQk3pZ+erx7l4SsnudMgVz3r7tt/nC/Tt4b1NSP+mgi3t3imvDz7YzfyZdc7RJ1lKTfraqqqQtLRXCCKruGvlBqslLpLKbVWKdWulFqhlLpVKRXAWkHBU14SpZMYKz0NleFqHRt3tsGuDenwr83UsIdYcBn9U/Qbm66sqvYdPJt8D9+Ne8IZgypIsvGOVqx8BrZ4Cum6ofkfHTgQymoyEoBF1r2U8XZYQv1Tyf0AFmpPwz+yjHq2E8WpkJX36XYZHD9QSvGNcyczqn9VRmb/YyIL+UTMM6JZfwjECjzCloMXq9xw19jrzmj6zg3p0Z0WXeqMFPnb8L/wiGYiCjZTy8Udn2K3dr7Dd16DFU9ARwvsNo3VDh3lHfoEO+IfLTFZw1Ms+TtnT29iUpk7SlbTFI5OM0a5HaUs+TtHNEWpxAmrj5VDhc+JqyrrYealXV6Ob14My/+Tfv7Kmu0c2+omIatqbPbDbu/UNkG1M296Twu8s8g8Xvh72O2MENcONQ3XgHjvUWP4Z9Q9P1954Pu0pULU171kEhMCu3QZ/0xOL3iYPwDRGNERc9JPr4v9iQdKP8erS8wo9Z5Nyzgh4mlIz/pQ/h1Kyt0GkVIw6Zz0W6dGn8tcFhaY1fYEHW+4K/F4w/wrSqJmPnyKfCb2y4Vn+d1RzhS3F1dtzdilc9OS9OP10Rz1IO9gxAPXwm1TzLz+FJPOgzNzLPfnHSDwEitly8iz0k9v2PoFuOvkjCjRbLZv3UC5ckarYxW+LGmbk8aJbufttpUc1ehOU9j45gLqOkwn7g5dwe7Gmbl+g6+MH1jD87Gp6efvvPQwQHq6zElRT/TRuNMIlNnXQn8nQmXPbneVk9Zt8Mhn3f2a/DmuqSX9AP6UOJrt2nm+ZZmb6HKHG425TtdTXRaC+nkBKaqGv1JqJPACcAnwHPBdYBlwLfBfpVRA6TuDI1XJ9yb4G6HWmRF/T0b/1FJ+gc7xB1Nge5dVyqK0bwhG0iFHw98NwwtFmH+K7kYqVDSYBDE5aKwtTS+Z5U3wN0at4tyoOz8zDMe1NBblqFENvJEcQqc210oftYtLYm4F0s/5/V6WDjg5/bh+9b/MnGTP/P439BA0Ecp8Hk2/5vhRvHbTyVxw2FB2UMUfE24DgWd+BFtXpJ+u1Q0kiQQ74g8ZkUcs+TulsShnDXOz09eEZJqMd2oUSx7JDOmtGxJMwrwTvwLHfJpnxn2WX3d6RmCeuj398Jnnn+es6JPp55HDrvDTsGey5/lrbc7TFId/OJjRfoe6ijijTv5I+vms1if43C8epqNlOzz6xfTrjyRn0k68sBn9vcy60m1sYUaJD3nNREkMeO1nRJzVZF6rOCwjMWXBmH6R24njsE73zXiefPBGSJgQ9taOToardZwUWcAV6j5Y6clc3s3ye3nD0/A/Pfpfzog8xWtrd6A9UTLxJW4U1+p4c9ffkT11YusK6HTuWTVNcMq3YNQJpvE/+XyY9G6Y9y0YfXKXX5WibdL7SWrPPWTlf+HRL2TusyfBrY++yZ1PLmfSVjeiMNlnRHAJO6MlGZ01R+5xk701rPlH+vG/klOpqAg+v0gkomhpOsp9YZmJ4lm6cRf92MqMiNPpoyIwel4Ahh6UgsM9HXfP3WGihx/8pNvALu8Ls6/xRWdYfWX6NNtNGb9PeJKGLrzH/PTUz9fpvlSXBXf/9oOiavgDPwT6A9dorc/UWt+gtZ6L6QAYA3w1ULsAKHPCepd6Gv5zIgtNVv+FniWXtOkTCXyOP8DEs7t9q7qfj3NWe2LgZDOiBiYj+RPfdt8LQQM1zci57uOBU91e2FlXBjIqnYvSWJRvnjuZuWP7s4NKliXNdI4SleDTJfe4O3rmHAbJ1CF1bKGGq/dck7EEYRqf5/eniA+axBtJ0zEWS7bBGw91md8P+D7in/qbEwbVAHB3wtOofuNB+JU7qrTKiaSoLQ+4YPY2qJc/Ds/dQcM6d8Q6nTU6aIYdaeY2g6noP/hJ9z2/w/xTxCvguM/Q9K6ruSsxz204LP0nLPkHaM0hr96aXtZtc/8jYFge53sfLN5w/ye+A799N2xylkiMV4fiPjTx0GPZWGU6n8pVBzetuoTNtx8Lyx5L73Of08FW0Iz+XkYcC9e9ys6j3NUdTmj5G50v38vQ5W5E1NP93u2PT1V/uOZ/rDjx5/yscx5f33MBc9tvYWbbj9JTJcq2L4Xnfmr2X/EUD8dv4Cfx7/LBDs/84FkfMlF8haRpOmCukwa1g9vjP+Dk9kdYm1oKc+1LlG0y9/I2XcJLFUd1/R0Dp2R0vKQpqYSz7zARcwBTL4Czfwrn3AGzrugxV8nQsdO5uerTPONNnPbKvbDiSTONoHUbn/3zq9z66BK+8rdXOT/pdk5EZ1y4X4cg73gSPtY/+UUu6GeiMo/HDZv/R/LQ9PrzQTNo6onpe2X/XYtg1zss3biLi2J/d3caNvvAl8DMJ5POc6PJtq+Ev10Lr3iiHk+/zbfEjlWlMT44e3h6mvKfEp5ovTcegrbtaE/9fIkebCJ6ejEhaMX5g1JqBHAisAL4QdbbXwBagA8opSopIsqcSv4/Eu7I71nRJzmh5W9ugQc8kDA92oGH+oNZ1u/cu+Doj3d5q3FwCObWgulR9nZQeMPovWvqBs2kd8PJ3zCjcJc8CJf/E25cAyd/PWizDE6ZNJC7Lj6UyYNrM8L905TVwWSfk2l1w+TBdQA8nDyM49q/zR86j8ncoX8wYeCD+5Tz18SR7guP3JhxjS/SpvIaVBj9eKfhv0wP4unYYe4bu9zVMH6ZODFj38Do0+xm8e5sgwc/YRJ5gsnh0Tih24/6SqwUDvWE1nvnWNYFm8BoSN8Kov1G8/vEse6LvzmXzt+9NyPTetVJn+v64SAZ7qk4bl8JSzwV72nvM1OogkYpGs67laRTxatU7Qxsd0e1/jPgYp5OmkzhA2p9nB5V1Y/q4z/BgogJH48qTezPlxHRJoz+6cR41vT1sZOnpJwBh87na4kP8JPE6bRSxiZqub3TU3Y/djOseJLmRy+nVGUlsGsYYxIHFpqaQXDez6HSnZJ5Q+x3vLlshXny4q/Srz+UPAxVUdf1d8TiJlkgmE6AD/wZrl0In3wLmmcfkJZSiunzLuY9HZ/n8YSTUE4n4e5T4Q8foON7h7H4RRO5c0zkZUY6yaN3UUlk2vsO6G/mjSOuSoekq+QevrT7q3woej9jIyapaLsuITb6RJrqgh/xB5g14RBeceo+UZJ03jmPQ5f+gKtjf3V3mnBWN5/2mZLyzCldL3rySEx6N4w/w1edz582ntduOpkTxvVnsR6SHgBhz2749bmojYsBM93xj7FTCp/zJGBC0IrzjdTQ5t+11knvG1rrncBTQAVQ4JitcJEa8X9Bj+HphEkgE1NJvhy7K73P1iHv4v6kaTAEntwvxcRz4Pj/gyv+k/FyNEzLcMz9vDvalmLsaZkVx6CJRExY1pEfhbjjGlRimH1gREMlv+g8KZ2MMs2Mi81IYghorq+gxpkj1kI5n+q8gt/XXWrOhQGTegydLCSD+1Rwf3I2bdoZLW/ZmDG37QVnndvygBr+4wbUkCpvr265lMQo9zjpaJxrOq7mH8mZxCKK0Y0BzQ314h31T1HTBOf/2qzDHRaO/0LXpcFiZTDlvcH4eJg7rj+3dL47PcIKEHvTHRV8NHo0pSNzjF4GyaBpZsTKWboqTaQEQjQlQQ07EnXUdRmv7SGGPv127qlyR1t9G/FPiyn+1Xx9l3t4Qitu6ryQap+jecpKojTXZ5bTv0icxNKkM0++fQfcfSqxDrNU5y5dRoKoWTr23DtNI8cPJpwFH32BLaVmmb461cJx9x8O32iGBT9L7/b7xHFUdrek8dzPwmfWwpWPm2i/PsMOutw8cfwAxjRWc2vnOV3ei+/ewB/iN/Gdkh/y7RI3f8DjVScHX88oq4H3/QGqnAjCxG5u8EQQPp6cxPvmFH65uX2luqyEf9W7uUNiW9/i7BbXt23I0TA94CgKL7Ov7bqsYEklvOtLgejEYxHGD6oFFPd7B0BWu0kpv995Fm2lwSWI9otiavinJl2+2c37qcwoPkwuCw/lcfcUuC3HjZvKfrw16yukwsxCEervZdBUONZZc3b8/MKH3O0PNQNhjicqIVpqRtaFA2ZEvype1KO4cM8N7HCStOhYGRx2+V4+6R9KqazwQMXGyR+GTy2DK5/wr6KYxZA+5azW/fjQnuvYgKdhWt6XmyIfYZE2of6lJcFc4+XxKCP6mcrgFl3NwqN/DBc9AEd9jFfm/Snd+TiqsTrY5H4pvKMrsXI49ka4+nkYE0zHTrdEY2YJsxHHmRUlxs+Hq56FobP2+tFCM3dMfzZTm7Ps+U3n8dzV/4YArPaBGRfDNS/B3M+ZueIzL4X33WtWUggR6tgb2T38JDp0lIcTh3J8+7d4pPRE1u9w81H4Nsffw5AxM7h8z8dZrd3ld3+ZOJE39NB0Phc/GTMgsyNxDzG+3Nl1ysZuXcp7Oj7HbbMeh+tf93/ZtLIaFk/OuiZa3SR/K5KNPJMc1/MxjOc3qDUSUXx63hheZDSPJbomAqxU7ZwdfZJ6ZdZNb9clvDr4/Lw6HDC1g+HCv5qEnB5adZy/9b2QQ5vDlfN72NEXcHXHR2nXmZ1jb+ohxC/4daC5RbpQWmWmjChPfWLOJ0y9OCBS0wkfSHaNKlqebOTOxLxeP78foHenLswk1T2/vZv3U6/X9fRLlFIvdPNWSNI47x9lnqW7ntXjeCo5idkRk/BrR9/JLD3yZu743670PqEI9c/m2E/DUdeH66aX4vCrYPkTZh7wvJuhb0imIlhKar3d/yYncFrHV7mw/Gku+8AHfVkPdn+YOqSOJ5a4y6Yd2tw3v8tTHQD9qkspjUV4rHMax7bdwounrqOMDph5CX/4+rPgrI4Q1Ig/mOzFb71j7jevrt1BzcjpPBQZyKa1HYAZcZsYdJh/isEzTYN645smxDtk52AGpdUmtDexJzS5OwAmNJli+c7EPPaoOF88LMnSTa3c8tYgHknO5Ow+4Y0+oqKvWbYvzMTiVFz4e77yt1f42VMmhPmup1awbpun4e9HVv8sDhvel88kp3J8+y2cFX2KobVRbtliIjuqAsioPWZANQ+9uj7jtceS0/hHYjrviprVBtbER3D1zot4VY/gon61ga3M03f6fP7zzB0cE12Y8XqrjnNz5wWAotLnzpO5Yxv55QcP4zt/+Tgvb/8LS5MDWRpp5vbId9Lh/QCrdQOf2XMphw8IUQdZ/7Fw2aNw36Xot5/mUWZxc+I9fHX+aZlLIoaAUycP5GsPHssZLU2cHX2CKtrYQQWP15/P73JN7wiaIYeZqaQP32AiXY+4KlCdVMN/pW5kAeM5lNcB2NH/UC5edQEdlPT6jP5QXA3/vZG6wnWPe/UyshN5fb/Pp1mw+U+8mRzMkEPew0/vW+FdXjn4rP7dEaLKbAYlZXDhX4K26DWMaHAbAit1I/f3vZjLhh3ZwyeCYYozzx/M9JgwJAhSStHUp5xlG1topYxlIy9k/KAatNa0dbqzn4IcTZ88uJb7X14LwB+fX8Vtj77Jpl0dGftMCEvDH8Izp3JfUCp098mq0hj9qkvZuLOdX3aewKWzj+WBF1bzyJtmTfKwzK+1GqW44tjR/Py/q0kkNc8t35J+qzQWCaThf0j/Ko4e1cATSzZxT+I4cJUCGfEfOyD31KGr91zDb8a/ysxJ4/nwv+pZuKMFgOENwaWCGtm/mgv09bxnzyPsppQnkxPZpqvYRTntmOu7otT/e/jRo/qx8+TD+MhvnO8vCSfyTaaqt7i6eTWPrezknsRxtBPn3D7hmJaXproRLv4bqrODOUSZndRUdDddIkBKY1E+cPgwvvtoO1/vdHMkfHJqSFaRycWsK+DQy3pMEukXTXXl1FWUsG33Hj7a9mEembOC2hEzWZCcztu/NGO6QXQ8+k3w34R/pEb0a7t5vyZrv5xorWfk2oDF+RL1k+xKfv+Bg7m181weTB7OTx7PbPRDSEf8haIhu8JVVxGuhkyKQ5v7pnuOjxndPxyh6cAQT4Vr9dbdAHQkkiSS5kIviapAr/HTJg8i5kz0f3n19i6NfoCJTd3dwgUb8V7Tyza1sMYzGj1IGv55oX91GceN6Tp39ZwZgymNBXNv+tL8iTmnDgbxnY8ZkNmZOH6ged5OnPtK56MnnM2yze3p95sDbPiXRCMMHdCfHyXOMLkIdBObqU03+oHAhq9mH9JA1JMYLUGU12PjmfL+m/lF4qS0YxDTS/aJWJzSWDSUjf4U7zt8aMZ18/7Dh/KhY0IUQZGLEDT6wQx+pAYO1lPP402XwdhT2NmeSO9TDKH+4fg2/MFZb6fbOfyjnJ/d5QDolWQ3SEb17zm0MnRz/IWiIjtCpW1Pops9g6W2ooR7rjicL54+nm+c4/M80B4Y3MetVK/a2gpAi6fQ8ztENJsBtWXMm9TzHMBxA0M04i8cNMM9idVWbGph7bbW9HNp+OeP8w/NXMUhouDKOcEtLTu8oZKrjj0k/bwkqrj6uEOYMdT/edVD+1ZQ5sltMn+qu7zxmxt2sWlXB7vaOwETkVBfGWyH8yWzu04ZnOTpEJ3ZHExy0dryEqYPrct47YiR9fStjKePaUNVPMNV2D8aqkr51rmTmTa0ji+cPp4vz5+Y0dki9MxUT/TlD/79Fp2JJMs2taRfa6gK52BSPglvt1b++bfz80SlVMSb2V8pVQ3MBlqBZ4KQC4pk1pD+kL49h2DJiL8QJlqcylgYmTColgmDwlXB8V7fqRF/7zHsNhu0j1x8ZDMPOOH+2URU8J0TQn7xjp6u2NTC2u1uw7+pLqQjgxZy3Jh+9K8u5Z2dZuT6tMmDGFYf3Mg1wNVzD6EiHmVzSwfvOXRIYCPp0YjizKlN3LNgFWMHVHPalEF8/SETxPnm+p2s2Ow2DJobKgKf+33mtCaUghvue4XWPQmG1Vdw74eO4N4XVlMWi3D82OAykx87pj8LVrgJB+eMMgkcv3bWJE6eMIApQ+q6dOAL+8f8qU3Mn9oUtIaVfODwZn7+1Ap2dyRYvH4nv3l2JS+udM/XqSGYllloiqYVp7VeCvwdaAayM0zcBFQCv9Rat1BEtGeNmPar7nlN33hMehaFYLn4yOb046uOO6T7HYUueEf839ywk2RSs7vDO+IffIVs+tA6pgx2O0wuPrI5vczfRZ7vXugdZIf6exPPDayVEf98EYtG0vfLmrIY1xwf/L0zGlFcPmcEN8wbG2j4PJiG6QNXH8VfrprNoNqy9JKsO9s7eWbp5vR+QXeWpJg/tYlHrpvDl+dP4DeXzaKsxMz/Pm/mkEDXIT9mdL/M584Uk8rSGPMmDZQoHiFQBtSWZdQbb/n7Gzz1lpuIedqQcK3kUAiKbejkI8DTwO1KqeOBRcAs4DhMiP9nA3QLhHZPUi8wcwF7IrTJ/YSi4foTRrMnkaRPRZyTJgwIWscqhnpG/J96azMX3PEMVx7jhvuGYW6jUorbL5jGzQ8tZtLgWj58zEhOnNDI0o0tnD1NRjl6G96G/3PLt9CRMGVSXUWJRHfkmYuObGbGsD70qYxL4sQsIhHFJE+H45gB1emR67+/viH9+vCQNPwBhtZX8IEjmoPWyGD8wBrGDaxh0bodzBjWh+b6kCXyE4qeS48azu8XrGLllt3sbHMjHusr4wzp2/vvi0VVqmqtlyqlZgJfAk4GTgHWAbcDN2mtt/T0+d7I3LH9+cr/WwSYkbb+NT2P+EuovxA0tRUlfPWs8Mybt4nxA2sYP7CG19eZpfGeXb4lI4FnGEb8wYyq/ej9M9LPjxzZwJEjG3r4hGArwzwNA29H9CAZ7S8Ikhxz3xjV6Db8X1nj5nwOOjIh7EQiit9eNotnl2/hiBH1gU+LEIRsykqivHfWUG5+KDMn+7ShdUVxvhZdK05rvUprfYnWeqDWOq61Hqa1vrYYG/0AI/pV8e3zpvDeWUO59fxpVJfGKO0hgV+JJPcTBGuJRSPc9+EjOdOTvGrpxl3px2GY4y8UF2UlUQblWFJOQoKFIBnTmHuJPxnB3jt9KuOcPHEAtRW9P0O6YCdnTBlEdht/WgCJRYNAWnEC58wYzNfOmsTQepO0pqdRfwn1FwS7KY9HOc6T/Glzi7tknoRWC0EwvF/XUVRJ7CcEyejuGv4y4i8I1jOorpzDsla/mFYEif1AGv5CDnqa5x+TZUMEwXqqumnghyXUXygumnPMm5YRfyFIRjd2Xdp4ZL/KwJfyEwQhP5w2ZVDG88nS8BeKlf49ZPbfsruj2/cEQbCD6rLcIZgS6i8EwZgBXUdXpeEvBEl9Vdd60E1nTCyKOcCCUAycMXkQdc50lCNG1Hc7INLbkIa/0IWeGv6rt7Z2+54gCHZQXdbdiH9xFHxCuDhzWhMnjGtML9sYj0aY2Vwc8y2F8DL7kPr043kTB3DUKEkwKgi9hdqKEn53+eF87tRx3PaeqUHr+IbU8oQu9K/pPtR/XI6RGUEQ7KK7hn9FXEL9Bf+pKSvhZxfNZPOudp5/eysj+1UxULL6CwFz+dEjeGX1dkY1VnPzOZOD1hEEIc+Mc5afLCak4S90oV/WiP81x4/it8+upE9FCR88anhAVoIg5IvuQv2LJdRNCCf1VaWcNGFA0BqCAMCxY/rz8hdOlPB+QRB6DVLLE7qQ3fA/fmx/rj1+FAqzRqsgCHbTXQO/Qhr+giAIaaTRLwhCb0Lm+AtdyJ7jP7C2jGhESaNfEHoJ0YjK2fivkqz+giAIgiAIvRJp+Atd8C7nF42onNltBUGwm1wN/wrJ6i8IgiAIgtArkYa/0IWGqjiHOhmVT544gKiM9AtCryNXgj9Zzk8QBEEQBKF3IrU8oQtKKX5z2eEsWreDiU21QesIglAAcjb8JdRfEARBEAShVyINfyEn8ViEKUPqgtYQBKFA5MrsXynJ/QRBEARBEHolEuovCIJQhOQe8ZeGvyAIgiAIQm9EGv6CIAhFSK4R/4oSCfUXBEEQBEHojUjDXxAEoQjJHvGviEdlyU5BEARBEIReijT8BUEQipDq0uyGv4T5C4IgCIIg9Fak4S8IglCEZI/4V0lGf0EQBEEQhF6LNPwFQRCKkOw5/jLiLwiCIAiC0HuRhr8gCEIRkj3iXykj/oIgCIIgCL0WafgLgiAUIdkj/rKUnyAIgiAIQu9FGv6CIAhFSJcRfwn1FwRBEARB6LVIw18QBKEIkVB/QRAEQRCE4kEa/oIgCEWIJPcTBEEQBEEoHqThLwiCUIR0Xc5PGv6CIAiCIAi9FWn4C4IgFCEl0QhlJW4RUCGh/oIgCIIgCL0WafgLgiAUKd5wfxnxFwRBEARB6L1Iw18QBKFI8Yb7yxx/QRAEQRCE3os0/AVBEIoU74h/ZVxC/QVBEARBEHor0vAXBEEoUvpXl6Yf9/M8FgRBEARBEHoXEtspCIJQpHzomJG8vbmFCYNqmTGsT9A6giAIgiAIQoGQhr8gCEKRMmNYH/5+/TFBawiCIAiCIAgFRkL9BUEQBEEQBEEQBKEXIw1/QRAEQRAEQRAEQejFSMNfEARBEARBEARBEHox0vAXBEEQBEEQBEEQhF5M4A1/pVSJUupapdTPlVIvKaU6lFJaKXXZPnz2IqXUc0qpXUqp7Uqpx5RSp/Wwf7lS6ial1BtKqTal1DtKqT8opcbl978SBEEQBEEQBEEQhHAQeMMfqARuBS4GBgDr9+VDSqlbgLuBgcAdwK+BScADSqmrc+xfCvwD+D9gB3Ab8ChwFvC8UmrWwf0bgiAIgiAIgiAIghA+wtDw3w2cAgzSWg8A7trbB5RSRwIfB5YCk7XW12utrwJmAFuAW5RSzVkf+xgwG/gjMEtr/Wmt9XuBc4EK4C6lVBiOhyAIgiAIgiAIgiDkjcAbulrrDq31Q1rrdfvxsQ85P7+qtd7q+V0rgB8ApcAlqdeVUsrzmU9prZOez/wVeAIYD8iC1oIgCIIgCIIgCEKvIvCG/wEy1/n5cI73HsraB2AkMBR4U2u9fB8/IwiCIAiCIAiCIAjWEwtaYH9RSlUCTcCubqIEljg/R3teG+P8fLObX5vrM939/Re6eWvs3j4rCIIgCIIgCIIgCH5j44h/rfNzezfvp16vO8jPCIIgCIIgCIIgCIL15GXEXym1Ahi2Hx/5jdb6/fn42z2g92Nfta+f0VrPyPkLTCTA9P34m4IgCIIgCIIgCIJQcPIV6r8UaNuP/dcexN9Kjc7XdvN+rtH9vX2mJsdnBEEQBEEQBEEQBMF68tLw11ofn4/fs49/q0UptQZoUkoNzDHPf5Tz0zuf/w3nZ3dz+HN9RhAEQRAEQRAEQRCsx8Y5/gD/cn6enOO9eVn7gIlIWAmMVkoN38fPCIIgCIIgCIIgCIL12Nrw/7Hz87NKqT6pF5VSzcBVQDvw89TrWmvt+cw3lVIRz2fmA0cDrwP/Kay2IAiCIAiCIAiCIPiLMm3igCWUugF3ObypwBTgadxl9p7UWv8s6zPfBj4GrAb+CMSB84F64KNa6+9n7V+KGdE/Enge+CcwFDgP6ADmaq2fPYj/YXN5eXnfcePGHeivEARBEARBEARBEELKokWLaG1t3aK1rg/aZX8JS8P/MeCYHnb5hdb64hyfuwi4GhgPJIH/Ad/SWv+tm79TDtwAvBfT6N8BPAZ8QWv9+oH/B6CUWo5JErjiYH6P5aQ6bxYHatEz4pg/bPC0wRHs8LTBEezwFMf8YYOnDY5gh6cNjmCHpzjmDxs8bXAEOzynAAmtdWnQIvtLKBr+Qu/AWdKw2yUPw4A45g8bPG1wBDs8bXAEOzzFMX/Y4GmDI9jhaYMj2OEpjvnDBk8bHMEOTxscu8PWOf6CIAiCIAiCIAiCIOwD0vAXBEEQBEEQBEEQhF6MNPwFQRAEQRAEQRAEoRcjDX9BEARBEARBEARB6MVIw18QBEEQBEEQBEEQejGS1V8QBEEQBEEQBEEQejEy4i8IgiAIgiAIgiAIvRhp+AuCIAiCIAiCIAhCL0Ya/oIgCIIgCIIgCILQi5GGvyAIgiAIgiAIgiD0YqThLwiCIAiCIAiCIAi9GGn4C4IgCIIgCIIgCEIvRhr+giAIgiAIgiAIgtCLkYa/IAiCIAiCIAiCIPRipOEvCIKwDyilVNAOe8MSx8agHQRBEGwh7Pf1sPuBlDuCkEIa/oJQBIS1YFZK1QTtsDeUUu8G0FrroF16Qil1JnCyUqoyaJfuUErdDzyslKoL2qUnlFKlSqmo89iKcjKs17gXW46lkD/CeF7aUO6AHWWPlDv5xbayJ4zXdy5sOJZ+EQtaQBC8KKVUyAu50cBQoA54HNiqtd4TqFQWSqmjgGnACODfwBNa661hO7ZKqT8DS5VS39BabwzaJxdKqYeAyUqp5VrrBUH7dIdS6i7gbOAJ4AWgJVijrjiVr9OAVUAz8FIIz8mLgSOBMcArSqlvaa3fDqHnJKAJqAKeBbZorVuUUhGtdTJYO4NS6hTM99wPWAAsCOt1DuEue2wod8COsseGcgfsKHuk3MkfNpQ9NpQ7YFfZE8j3q7WWTbZAN+BrwCWe5ypop248vwOsAJLO9iLwIaAyaDeP4w+ADR7Hrc7xDY2j4/kVj+NXgYagnXI4Pgi0AdcD1UH79OD5F2Cnc36OdF5Tzs9I0H6Ox8NAB/C0853/IGinHI6/ArYBu53rJgk8AvQN2i3L88fAGs/1sxq4FxgRtJvH8dfAdo9jElgEnACUBu3n8Qx92WNDueN4hr7ssaHccTxDX/ZIuZNXz9CXPTaUO45n6MueoMudwA+AbMW9OTeOJPAMcK7n9VBVwID7nYL4v8AXgX85N+olwGFB+zmOf3UKjd8DJwKXAouBZcCQoP08nhHgJ0ACM1IQukoY8BDQ6lS8aj2vh+28/JxT+bqxp0pCkN6eY/lh4DBgM7AOmBb08fM4/tY5jt8GpgDDgH8C7cCkoP08nn92Kof3Ae8DbgKec66hDcAJIXD8HbDLqSie7Hje7zjuBD4BDAiBZ+jLHhvKHccz9GWPDeWO4xn6skfKnbx6hr7ssaHccTxDX/aEodwJ/IuSrXg34OPOBbDYuVhfAc7zvB+Kgg643anU3Aj0c14bAHzD8f9hCBx/7NzYPu1xjAI3O45HZ+0faI88cC6m9/gjwMuO41fCUAkDHsCELH4c6JP13ihgKlALVATsWYUJ+30OaHReKwOGOwXz94DbgOlBfd+YkatW4GOpY+k4JYHLgv6uHZ8POZWam7yVWKfisA6Y5TyPOT8DuS8Bn3KO201Z1/ghwGO4o6zznfd8/86BU51r59s5rp3PAeud8+Hzqf8hoGMZ+rLHhnLHcbKm7AlzueP4hb7skXInr56hL3tsKHecvxv6sics5Y7v/7hssmmtAeYAbwFrgcOB65yLdmGYKmDAKc4N4+5U5QCIOj9HOBfvE4AKyhW4DBN29T2gPuu9HzgFyHTg/c7Nscl5L8gK2PGYELyRzuMXcUdgBjr71ACH+Oz175SH57Uq4FhMaGOb58Z9NwGOZgGTnILsJs/xugx4k8wwtxZMpXxgAMcyNXJV43n9HMdrGdAc1PHz+NwNbMxx7XzWOUc/BtwJ3EGAo6yYkYu1nvtQJPUTtwKZxIQ5zvTu46NjqmIzx+MW87x/BbDSOSc/HJBj6MseLCh3HBeryh5CWu44f9eKsgcpd/LpejchL3uwoNxx/maoyx5CVO74fhLJJpvW6QpDEjjNeT4I+ExQF0I3jhFM7+EeYIzXBZMYMwa8ihlBqMGpmAXkuCO7MMOEXK7H9MYu9RTIbwGjAz62jcA7wMXO8zOB/zl+N2JGNpZi5kLV+ej1F8fhnzghYZhQwXWYENsngCcxiYKSwFMEVwGb6FwvX3aenw5swcxnPBeYDdzqvNYCXJs6Z3xwOxPTm/0pnMqX9+8Cf8RUGOY5z4O4dhQm+c9S5xpu8Lx3nHNttwKvOT+TznX2Pr+OY+rvAAOBTc61W+F5L9UYPNS5T/3T8XyJAEY1MCMrSeBdqWOc47u/yjmO23DCbv28DxHysgcLyp0sT2vKHkJa7jguf8GCsgcpd/LhGfqyB4vKHccl1GUPISp3fP9yZJMttWFGNao9zxt7uBBiAfjFncrAZ5znXW62wKPA2wEfxzq6VhCPw8wHbQeuxYwaNGMSn6Ru0P0DdC4BXgd+7nltPiZTbCp0rBWfwvKyCoe7HYe/Y+aqrsVUskY6hWGJU+A97ux3KwEkjcGM/G0Cnsc0AO53rpvSrP2uco7lVnwayXJ8pgFVWedlarTgCufYPRjUOehx/b3j8h1MRuVLnfOwAzgfE8Jaghu6vBWn8eKz5+OYynQq/DN1LKOYEcvFQB/g/zme873H3ifHy52//Ue6jmJ5r7FvOvs9RADJywhx2YMl5Y7jUYdFZQ8hK3eyv18sKHuQciefvqEve7Cg3HH+XujLHkJS7vj2D8smW2qjh17WXBeCd39MpcK30DGnIGnO8XqqQHkY02MbzfIcQ9Y8Ix9cU04KE2aZBI7Psd9/MHMyA0ly4yk47gEe854TwCWYCmPSKUh8qyBmfX+/wB2legYo8x5j5/Fsp0B8loAyVzsVhw5MWOMq4Gup/yXr/7nT+V8u9Os83Ms+tcAbmPDVd+3r5wp0Hh6NO+rn3c727uc8/pXz3sd99FSYyt8tzt9+HDPqVuK8/z5Msrd/O9/7qc5+3w/gfKx2rpdNwHuAeDfHXGHCrJfh4wgRIS97PPdwa8qdLK/Qlj2EtNxx/r43JDn0ZQ/hLHf2OgpOCMqdrHMxtGUPlpQ7nntPaMseemjEE0C5E0EQfEZrnejhvQ2YwuKrmF7uz2NCyVBKfQD4OXCLUirmgypa6x1a6xU53oqmdsH0xFek/i+l1MnAD4FPK6WiOT5bELRzl3B+fhI4VGv9T6VUxPGqcHZ9DajErAvtO9pd7/VFYIpSapjWOqGUGgB8CVMBWw3MA65USg30ySuR+r601hdhsu12AFdprductWq15yNLMDfrcfh8LFPfKSZL9RbM9z0Ak7kYzGmQUEqVOs8fdX7WFtot6xh1QSkV1VpvxyQFi2NGBPf6uXzjOQ//iwlR/RymAL4K+AfwUGp9YqVUmbPv352f5T56am3WbP8uJpz2KEwSsEeVUv8B7sIk17rIuQe9hZkDXueXI5jvFTPC92ugAnM8j/DeA51jGXe+65cxI8Hj/XJ0romc9Z4wlD2ee7gV5Y5SSkG4y56UQ1jLHcetM3WvDnPZo5QqcR6GsdxJOo45r++wlDvO3wx92WNLuaO11s49ObRlj3N957wnB1LuFKqHQzbZsjf2o2cV0wv2WcyNZCEmedA6zPycCUF7kjnystrz+omYHtw2YHwQjmT2Fqrs/TEFyFJ8WNZkL54XYCo3fYF6zAjWZuCDzo3vv5ge5M9RwDlt2Y5Zx+/9ZI3+kNlzvBxTKMYL5dfTscT0cn8dd/3s13Dn0JZ49vuWc6znBPV959j3cExluxUnKZAf294cMSMcq3DniHrPh9swcxpP8dPTc84NxowILnK+7zcxywM1efbtg0m0dGcB3UYDJzn3u7FZ7/XFHel7CbN+cnmOc/J3mGRLTX579nQ/weeyZ38cCbDc2RdPAi579tEx8HKnB89Sz+NAy569XOOhKHcO8Pr2vdzpwTO77hFY2bOX7zsU5Y7zd47EdJB8Bjg/671QlD3dOe7lvPSt3Cn4CS9bcW/A93ESkjjP96dhUAfcgAkNTGJ6mCeGyRPTo73IeZyqfG0HJofI0Vvp+QAmuc0vcObBBeWJWa92Daan823n+/2I5/1zMcvF5L0iuzdHugkJzjqWH3HOy294CxW/PHEr1v0woxjrgU5Mr3ezZ78zMZXt5ylACOtBXuOp+XaXZR/foBwxla+dwGk4lQbn9TMwlYUFOMtY+fx9pyr9lUADJky0P1lLe2HCb1uB9+7v97GPjrdgRhxTYakvAR/N2qcRM2qZxITWXo0nXBETFroGM8+ytkDHcq+ePXy2Dh/KngN1xMdy5yA9fSt79uaIe78MrNzZR8+cYcH4WPbs4zUedLlzMNe3L+XOPn7fkax9fS979vH7DrTccX7n951r1zst4qtZ+wRa9uyLYw+frcOPciffv1A22VIb8Afc3sEzPK/vbcTNeyO8xilUNlO4gni/PXHXVf0XZq7Q2ZhssjsoTKP/QI+lt8c45bgKGBH0sXQKj3XO/ssxS8NkN8DzPn8xT8fyLEzv91vAsKCOJW5jsB8mXDVVeC/DJAy6D5MgamMhrp+DOJapSnhqXuBSCjQ3eV8dPU7vw4ysvIRZjuow4AuYSsQWYFyA33eujh/v/fJ0TEbolynAfHTgr5gRvOcxI1CPYEaZ1wOnOvuk7o2NmFGLdzD38BcxIyB3Ot/3JrJGlvz07OZzvpU9B+KIz+XOQR5L38qe/XEkoHInj8eyoGXPPl7jqdwIQZU7B3ocfSt39seTAMueffy+IzlcfSt3nL/xZ0yD+LeYjpDzMNNdNuFGm6TqQ4GUPfvi2M3n/G3zFOqEl624N+ATuD1uSUxv5XzP+/sSTn8xJpRsCwUK7z9QT9yC70nnwn7RueAL0eg/qGOJCQv8FKZBsQGYFPSx9BQeZ2MSFH3CW6Dsy/kR4Hl5HSaT7TsULgLlQI5lFWYe3m8x4WJJ5/v+G07m7bAdS2e//2FGAgvRUN1vR0z4769xl1FKba+G7T7keb8EU1Fc5JyXhQhJ/x5mGaQbcNd07o8JT8wY1cCtgNViRv7u9xzHHZgR1UJ1oOyzZw+/42IKWPYcqCM+ljv5OJb4UPbs53kZSLmTx/PyOgpY9hzgsfS73Dno4+h8pmDlzoF64nPZk4fru+DljvN3foqJaLoR6Ot5/UbHs0uyUMzo+Zn4VPbsryO5p3JdTIHbPFpLw1+2AmxOIbDCuRGMAD7unPhvs4+VWcwyJg87N6VCNVTz4fkX5zObKUyj/6AcMclLUje+pyncCNsBeWKSVY0gRy9yWBw9r0/EJLdJAi8UovA4UM8cx3UYMBkz560QYbX5uHZSo5fzgFFhcPSch/2AK4HfYOYDXkfh5gPm41he63zmyUKcl5gRsrWYREPZSyXNwlSgX8UkzYrk8nWunyMwychqC3Qs99szx+8oaNmTJ8e/UMByJx+e+FD27Kejd9Tct3InT8ey4GVPnq7xQpc7+bh2ClruHOyxxKeyJ0/HsqDljvM3LsYk3fwenga1896PMffAcZjOvPnkmKZJgcuePDkWvM2T/luF/OWyFd+G6TW/EtNrNd/z2ufZ/8rsOcDIMHpiRjLimNCoRRQmnO2gjyWm1/Ojzu8pVEKlvHzn3RUuYXHEVGZuwiR9GhxGT7qpkIXJMcfvK8RcwAN2LOR5WMhjCbyLwsyljQI/cnxG5jpemGWUlpNjvrFfx/NgPbN+V0HKnnwcSwpc7uTrWFLgsidf33ehz888HcuClj35usZ7uj8F7Zjj9xUqqvCAPS29Vxak3HF+dxy4G1MONme9dyJm6tA2TPh+alT/MZzOUPxJunywjt4OyYK1eTK8/DjJZCuuDZMAZD5mqQ/vzaS7ymz2za/gF2s+PJ3X6ilQoq88OmasrRtGz0L75fFYxgt9fhbDsbTEMe55XMgK7cF6lhX4OEYxjbf0Wt1Z75dgKjKrujte+FChzZNnQZJ05tPRea3Q5U6+PAtW9hTTeem8VrCyx4ZjaYNjHj1LunsvRI6l+fbqxnUwMMXrAMwGnsDkQ7gamANMAO7BlJkP+eGWL0c/zssMXz//mGy9f2MvPb90U5l13jtGPO1ytMXTBkdbPMWxKD37kGPU1lPJeQCTDKoMT1ZyCjDH13ZPGxxt8bTB0RZPcSwuT0sccy0PWgH8ELMk44lZ+w/ATIVJAkeIYzfOQfxR2Yp7w63MrgTmOa9d6Lx2V9B+Nnna4GiLpw2OtniKY3F5YuZyr8GzxBMmzPEl4Oag/WzytMHRFk8bHG3xFMfi8gyzIzAFmOE8TnWelzk/v+GUjceKYzduQR4Y2Yp3A/4PdyTrVtz1dLtk5xRP+x1t8bTB0RZPcSwOT0zY6CPASs9rBV9bvjd62uBoi6cNjrZ4imNxeYbZkdzJeL2vPYSZV1/vp5dNjoGeXLIV54bb+5VaMiQJbKVAS6P1Zk8bHG3xtMHRFk9xLB5PTKLTfwBvOM9PxiwzF4pKrE2eNjja4mmDoy2e4lhcnjY4elwjnseXYJaU/AWeSIWgt7A5RhAEH1FKRbTWSefpatxK7Gyt9avBmWVig6cNjmCHpw2OYIenOOaPsHsqpZTzMAHElVJnY8IYRwJHa60XBibnwQZPGxzBDk8bHMEOT3HMHzZ42uCYwls+KqXOBD6GWTrvJq317iDdUoTRMRWCIAi+opS6AvgiJnHI0Vrr14I1yo0NnjY4gh2eNjiCHZ7imD/C7KmUimFGh6Zgln8aBRwVpgoi2OFpgyPY4WmDI9jhKY75wwZPGxxTKKVKMVnzPwTUAnPD0CnuJWyOsaD+sGAvWaNQB/L5wcAZQCNmCYyCVGJt8LTB0fk7ofe0wdH5O6H3FMf8YYPnwToCnZh124dSwAqiDZ42OIIdnjY4gh2e4pg/bPC0wREO3NOJTBiKCZmfA/wXOF1rvTjPilY47g8S6i/sF1lhK4cqpeYppZr289dsAL4PjCpUr5cNnjY4gh2eNjiCHZ7imD9s8MyDYxL4D2bVgWP8qCCG1dMGR1s8bXC0xVMci8vTBseD9dQmXH0n8EvgeuDcQjf6w+q43+gQJD6QzY6NzAQV12MySy/HJP6IBOVlo6cNjrZ42uBoi6c4FpdnvhyBQUBDMXva4GiLpw2OtniKY3F52uCYZ88IEC1WxwP6v4IWkM2+DbOudAK4Fzg1aB+bPW1wtMXTBkdbPMWxuDxtcLTF0wZHWzxtcLTFUxyLy9MGR1s8bXDcr/8naAHZ7NqAs4HdwM+AQ4L2sdnTBkdbPG1wtMVTHIvL0wZHWzxtcLTF0wZHWzzFsbg8bXC0xdMGx/3dJLmfsE84SSoiwKmYnq8faa3fCtaqKzZ42uAIdnja4Ah2eIpj/rDB0wZHsMPTBkeww9MGR7DDUxzzhw2eNjiCHZ42OB4ospyfsM8opWqABcAurfWMbvaJaK2TSqm41rrDX8O0Q+g9bXB0HELvaYOj4xB6T3HMHzZ42uDoOITe0wZHxyH0njY4Og6h9xTH/GGDpw2OjkPoPW1wPBAkq7+wPyhnq1RKlSuH9JvuBRAFLldK9RdPqx1t8bTB0RZPcSwuTxscbfG0wdEWTxscbfEUx+LytMHRFk8bHPcbafgL+4RSKgK0A68Bo4FTtINzLXjXufwmcC3QIJ52OtriaYOjLZ7iWFyeNjja4mmDoy2eNjja4imOxeVpg6MtnjY4HijS8BcycE72Lmitk1rrNuAB56UfKKXmpj6WugCUUqcBJwFLgLXF7GmDoy2eNjja4imOxeVpg6MtnjY42uJpg6MtnuJYXJ42ONriaYNj3tEhyDAoWzg2MtesnADMA94LHAnEPe99G0gCO4ALgZFAHLgKWAisB8YUs6cNjrZ42uBoi6c4FpenDY62eNrgaIunDY62eIpjcXna4GiLpw2OBfm/gxaQLRxb1gXwSWCNc6KntvuA0zz7fNXzXqtzQSSBN4GJxexpg6MtnjY42uIpjsXlaYOjLZ42ONriaYOjLZ7iWFyeNjja4mmDY8G+n6AFZAvXBtzonMwPAGcBxwI3YdaxXAac49n3TOBbwD+B3wDXAIPF0x5HWzxtcLTFUxyLy9MGR1s8bXC0xdMGR1s8xbG4PG1wtMXTBse8/89BC8gWng04HtgE/AEY73l9PrAdWA0MyPG5qHja52iLpw2OtniKY3F52uBoi6cNjrZ42uBoi6c4FpenDY62eNrgWJD/O2gB2cKzATdgQlhOcJ4rTA/XG8A6oNl5PQZUevZRqcfiaY+jLZ42ONriKY7F5WmDoy2eNjja4mmDoy2e4lhcnjY42uJpg2NB/u+gBWQLfkudyMAjwCrP62cBi4ENqQvAeX0UcDVQKp72OdriaYOjLZ7iWFyeNjja4mmDoy2eNjja4imOxeVpg6MtnjY4FvT/D1pANp+/cE8PVeoxTpIL4G5gJ3AY8K5cF4Cz372YLJaDitnTBkdbPG1wtMVTHIvL0wZHWzxtcLTF0wZHWzzFsbg8bXC0xdMGR7+3wAVk8/kLh0ZnqwEqst67CpPk4kHMmpTrc1wAHwRWAd8DyorZ0wZHWzxtcLTFUxyLy9MGR1s8bXC0xdMGR1s8xbG4PG1wtMXTBke/t8AFZPPpi4a5wM3Oib0dWA78BXiXZ5864GHnQmgBDs/6HWdh1qx8LfviKCZPGxxt8bTB0RZPcSwuTxscbfG0wdEWTxscbfEUx+LytMHRFk8bHIPaAheQzYcvGb4BrAUSmF6thcBG3DUprweqnX3nA09hEl581znxpwK3YHq9NgITitXTBkdbPG1wtMVTHIvL0wZHWzxtcLTF0wZHWzzFsbg8bXC0xdMGxyC3wAVkK/AXDH8EtmB6uibjhKoA050TO3Uh/B8m2UUUOA34m+e9JKbH7FFgbLF62uBoi6cNjrZ4imNxedrgaIunDY62eNrgaIunOBaXpw2Otnja4Bj0FriAbAX8cs28lV3AZ4FG57V41j4f85zoVzqvKaAUOBczB+ZG4Aigvlg9bXC0xdMGR1s8xbG4PG1wtMXTBkdbPG1wtMVTHIvL0wZHWzxtcAzDFriAbAX6YuEB5wL4OFDnvObNbhn1PL7BuQjagVniaZ+jLZ42ONriKY7F5WmDoy2eNjja4mmDoy2e4lhcnjY42uJpg2NYtsAFZCvAlwr/ck7qb3tei+TYL+J5fLfzmU90t38xetrgaIunDY62eIpjcXna4GiLpw2Otnja4GiLpzgWl6cNjrZ42uAYpi2C0BvZ7fy8Uik10XmssnfSWieVUhGllAKedF4+IfVe4TWt8LTBEezwtMER7PAUx/xhg6cNjmCHpw2OYIenDY5gh6c45g8bPG1wBDs8bXAMDdLw70U4JzNa69OAnwMVwHNKqZla64RSqsv3rbVOatPd9Tzm4tkmnnY42uJpg6MtnuJYXJ42ONriaYOjLZ42ONriKY7F5WmDoy2eNjiGEWn49yK01jp1omutL8WEspQBjzsXQjL7QvA874u5aFaJpx2Otnja4GiLpzgWl6cNjrZ42uBoi6cNjrZ4imNxedrgaIunDY6hRIdgvoFs+d3InMdyF2Yey25gpvd9MhNf/BbYBEzJfq+YPW1wtMXTBkdbPMWxuDxtcLTF0wZHWzxtcLTFUxyLy9MGR1s8bXAM0xa4gGwF+mL3fiGUeN6/CFgL/AyoEk/7HG3xtMHRFk9xLC5PGxxt8bTB0RZPGxxt8RTH4vK0wdEWTxscw7IFLiBbAb/c7i+EwzyvzwNeAhYBzeJpr6MtnjY42uIpjsXlaYOjLZ42ONriaYOjLZ7iWFyeNjja4mmDYxi2wAVkK/AXnPtCaAGmAzOBF4HNwATxtN/RFk8bHG3xFMfi8rTB0RZPGxxt8bTB0RZPcSwuTxscbfG0wTHoLXAB2Xz4knNfCDuAJc7PSUE72uJpg6MtnjY42uIpjsXlaYOjLZ42ONriaYOjLZ7iWFyeNjja4mmDY6DHJ2gB2Xz6ojMvhJ85F8ImYGLQbrZ52uBoi6cNjrZ4imNxedrgaIunDY62eNrgaIunOBaXpw2Otnja4BjUppyDIhQBSqmI1jrpPP4J8AOt9cKAtbpgg6cNjmCHpw2OYIenOOYPGzxtcAQ7PG1wBDs8bXAEOzzFMX/Y4GmDI9jhaYNjEEjDv8jwXghhxgZPGxzBDk8bHMEOT3HMHzZ42uAIdnja4Ah2eNrgCHZ4imP+sMHTBkeww9MGR7+Rhr8gCIIgCIIgCIIg9GIiQQsIgiAIgiAIgiAIglA4pOEvCIIgCIIgCIIgCL0YafgLgiAIgiAIgiAIQi9GGv6CIAiCIAiCIAiC0IuRhr8gCIIgCIIgCIIg9GKk4S8IgiAIgiAIgiAIvRhp+AuCIAiCIAiCIAhCL0Ya/oIgCIIgCIIgCILQi5GGvyAIgiAIgiAIgiD0YqThLwiCIAiCIAiCIAi9GGn4C4IgCIIgCIIgCEIvRhr+giAIgiAIgiAIgtCLkYa/IAiCIAiCIAiCIPRipOEvCIIgCIIgCIIgCL0YafgLgiAIgiAIgiAIQi9GGv6CIAiCIAiCIAiC0Iv5/9PgQOBTgkpcAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 576x288 with 1 Axes>"
]
},
"metadata": {
"image/png": {
"height": 270,
"width": 511
},
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"fig, ax = plt.subplots(figsize=(8,4))\n",
"\n",
"mean, std = scaled_features['cnt']\n",
"predictions = network.run(test_features).T*std + mean\n",
"ax.plot(predictions[0], label='Prediction')\n",
"ax.plot((test_targets['cnt']*std + mean).values, label='Data')\n",
"ax.set_xlim(right=len(predictions))\n",
"ax.legend()\n",
"\n",
"#dates = pd.to_datetime(rides.ix[test_data.index]['dteday'])\n",
"dates = pd.to_datetime(rides.loc[test_data.index]['dteday'])\n",
"dates = dates.apply(lambda d: d.strftime('%b %d'))\n",
"ax.set_xticks(np.arange(len(dates))[12::24])\n",
"_ = ax.set_xticklabels(dates[12::24], rotation=45)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## OPTIONAL: Thinking about your results(this question will not be evaluated in the rubric).\n",
" \n",
"Answer these questions about your results. How well does the model predict the data? Where does it fail? Why does it fail where it does?\n",
"\n",
"> **Note:** You can edit the text in this cell by double clicking on it. When you want to render the text, press control + enter\n",
"\n",
"#### Your answer below"
]
}
],
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