diff --git a/Chapter_4_sush.ipynb b/Chapter_4_sush.ipynb new file mode 100644 index 00000000..da8d0894 --- /dev/null +++ b/Chapter_4_sush.ipynb @@ -0,0 +1,1933 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "name": "Chapter_4_sush.ipynb", + "provenance": [], + "collapsed_sections": [], + "toc_visible": true, + "authorship_tag": "ABX9TyPvpyt5fhU3NTY5MDPBV6HP", + "include_colab_link": true + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + } + }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "view-in-github", + "colab_type": "text" + }, + "source": [ + "\"Open" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "YAexITSKKvaI" + }, + "source": [ + "!pip install git+https://github.com/d2l-ai/d2l-en" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "RDmbK7OHS8s_" + }, + "source": [ + "from d2l import torch as d2l\n", + "import torch\n", + "from torch import nn\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "sns.set()\n", + "plt.style.use('fivethirtyeight')\n", + "%matplotlib inline" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "HptC-hHNRoRw" + }, + "source": [ + "batch_size = 256\n", + "train_iter, test_iter = d2l.load_data_fashion_mnist(batch_size)" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "xHbuXeivR5jZ", + "outputId": "23f00f75-4480-454e-f440-580d13948939" + }, + "source": [ + "num_inputs, num_outputs, num_hiddens = 784, 10, 256\n", + "W1 = nn.Parameter(torch.randn(\n", + " num_inputs, num_hiddens, requires_grad=True) * 0.01)\n", + "b1 = nn.Parameter(torch.zeros(num_hiddens, requires_grad=True))\n", + "W2 = nn.Parameter(torch.randn(\n", + " num_hiddens, num_outputs, requires_grad=True) * 0.01)\n", + "b2 = nn.Parameter(torch.zeros(num_outputs, requires_grad=True))\n", + "params = [W1, b1, W2, b2]\n", + "\n", + "type(params)" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "list" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 4 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "XB0Guueo0Evv" + }, + "source": [ + "def relu(X):\n", + " a = torch.zeros_like(X)\n", + " return torch.max(X, a)\n", + "def net(X):\n", + " X = X.reshape((-1, num_inputs))\n", + " H = relu(X@W1 + b1) # Here '@' stands for matrix multiplication\n", + " return (H@W2 + b2)\n", + "loss = nn.CrossEntropyLoss()" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 261 + }, + "id": "CNrruuEL10-4", + "outputId": "d379e5f6-638e-405f-f27c-0e207336b78f" + }, + "source": [ + "num_epochs, lr = 10, 0.1\n", + "updater = torch.optim.SGD(params, lr=lr)\n", + "d2l.train_ch3(net, train_iter, test_iter, loss, num_epochs, updater)" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/svg+xml": "\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n" + }, + "metadata": { + "tags": [], + "needs_background": "light" + } + } + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 192 + }, + "id": "az34q-zu13zv", + "outputId": "e88b4f02-c1bd-4042-883c-b2c0235daaa5" + }, + "source": [ + "d2l.predict_ch3(net, test_iter)" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/svg+xml": "\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n" + }, + "metadata": { + "tags": [], + "needs_background": "light" + } + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "mBUrZ6PR3vbe" + }, + "source": [ + "from d2l import torch as d2l\n", + "import torch\n", + "from torch import nn\n", + "import numpy as np" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 470 + }, + "id": "U4RnEJ4F-x3g", + "outputId": "dfd21924-0d0f-41d2-fee9-f5947f9588b6" + }, + "source": [ + "net = nn.Sequential(nn.Flatten(),\n", + " nn.Linear(784, 256),\n", + " nn.ReLU(),\n", + " nn.Linear(256, 10))\n", + "\n", + "def init_weights(m):\n", + " if type(m) == nn.Linear:\n", + " torch.nn.init.normal_(m.weight, std=0.01)\n", + "\n", + "net.apply(init_weights)\n", + "\n", + "\n", + "batch_size, lr, num_epochs = 256, 0.1, 10\n", + "loss = nn.CrossEntropyLoss()\n", + "trainer = torch.optim.SGD(net.parameters(), lr=lr)\n", + "train_iter, test_iter = d2l.load_data_fashion_mnist(batch_size)\n", + "d2l.train_ch3(net, train_iter, test_iter, loss, num_epochs, trainer)\n", + "\n", + "print('Train Accuracy',d2l.evaluate_accuracy(net,train_iter))\n", + "print('Test Accuracy ',d2l.evaluate_accuracy(net,test_iter))\n", + "\n", + "\n", + "d2l.predict_ch3(net, test_iter) " + ], + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "text": [ + "Train Accuracy 0.8677166666666667\n", + "Test Accuracy 0.8513\n" + ], + "name": "stdout" + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/svg+xml": "\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n" + }, + "metadata": { + "tags": [], + "needs_background": "light" + } + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/svg+xml": "\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n" + }, + "metadata": { + "tags": [], + "needs_background": "light" + } + } + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 470 + }, + "id": "JP4ZfvsGUHf8", + "outputId": "efc43560-04d0-4239-ea05-c71fa2379e9f" + }, + "source": [ + "net2 = nn.Sequential(nn.Flatten(),\n", + " nn.Linear(784, 256),\n", + " nn.ReLU(),\n", + " nn.Linear(256, 64),\n", + " nn.ReLU(),\n", + " nn.Linear(64, 32),\n", + " nn.ReLU(),\n", + " nn.Linear(32, 10)\n", + " )\n", + "\n", + "def init_weights(m):\n", + " if type(m) == nn.Linear:\n", + " torch.nn.init.normal_(m.weight, std=0.01)\n", + "\n", + "net2.apply(init_weights)\n", + "\n", + "\n", + "batch_size, lr, num_epochs = 256, 0.1, 100\n", + "loss = nn.CrossEntropyLoss()\n", + "trainer = torch.optim.SGD(net2.parameters(), lr=lr)\n", + "train_iter, test_iter = d2l.load_data_fashion_mnist(batch_size)\n", + "d2l.train_ch3(net2, train_iter, test_iter, loss, num_epochs, trainer)\n", + "\n", + "print('Train Accuracy',d2l.evaluate_accuracy(net2,train_iter))\n", + "print('Test Accuracy ',d2l.evaluate_accuracy(net2,test_iter))\n", + "\n", + "\n", + "d2l.predict_ch3(net2, test_iter) " + ], + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "text": [ + "Train Accuracy 0.87805\n", + "Test Accuracy 0.8467\n" + ], + "name": "stdout" + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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" + ], + "image/svg+xml": "\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n" + }, + "metadata": { + "tags": [], + "needs_background": "light" + } + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "PFrqFmu4Oz6z" + }, + "source": [ + "from d2l import torch as d2l\n", + "import torch\n", + "from torch import nn\n", + "import numpy as np\n", + "import math\n", + "from torch.utils import data\n", + "from torchvision import transforms" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "Smrwco3zO21y" + }, + "source": [ + "max_degree = 20 # Maximum degree of the polynomial\n", + "n_train, n_test = 100, 100 # Training and test dataset sizes\n", + "true_w = np.zeros(max_degree) # Allocate lots of empty space\n", + "true_w[0:4] = np.array([5, 1.2, -3.4, 5.6])\n", + "\n", + "features = np.random.normal(size=(n_train + n_test, 1))\n", + "np.random.shuffle(features)\n", + "poly_features = np.power(features, np.arange(max_degree).reshape(1, -1))\n", + "for i in range(max_degree):\n", + " poly_features[:, i] /= math.gamma(i + 1) # `gamma(n)` = (n-1)!\n", + "# Shape of `labels`: (`n_train` + `n_test`,)\n", + "labels = np.dot(poly_features, true_w)\n", + "labels += np.random.normal(scale=0.1, size=labels.shape)" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "S0rAm8ENP1C7", + "outputId": "f7fa5c26-380c-4090-d264-e91b823c750b" + }, + "source": [ + "# Convert from NumPy ndarrays to tensors\n", + "true_w, features, poly_features, labels = [torch.tensor(x, dtype=\n", + " torch.float32) for x in [true_w, features, poly_features, labels]]\n", + "\n", + "features[:2], poly_features[:2, :], labels[:2]" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "(tensor([[0.7074],\n", + " [1.0822]]),\n", + " tensor([[1.0000e+00, 7.0743e-01, 2.5023e-01, 5.9006e-02, 1.0436e-02, 1.4765e-03,\n", + " 1.7409e-04, 1.7594e-05, 1.5558e-06, 1.2229e-07, 8.6511e-09, 5.5637e-10,\n", + " 3.2799e-11, 1.7849e-12, 9.0191e-14, 4.2536e-15, 1.8807e-16, 7.8262e-18,\n", + " 3.0758e-19, 1.1452e-20],\n", + " [1.0000e+00, 1.0822e+00, 5.8556e-01, 2.1123e-01, 5.7147e-02, 1.2369e-02,\n", + " 2.2309e-03, 3.4489e-04, 4.6655e-05, 5.6099e-06, 6.0709e-07, 5.9726e-08,\n", + " 5.3863e-09, 4.4838e-10, 3.4659e-11, 2.5005e-12, 1.6913e-13, 1.0766e-14,\n", + " 6.4728e-16, 3.6867e-17]]),\n", + " tensor([5.3068, 5.3052]))" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 5 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "mM_hjfxzP8vb" + }, + "source": [ + "def evaluate_loss(net, data_iter, loss): #@save\n", + " \"\"\"Evaluate the loss of a model on the given dataset.\"\"\"\n", + " metric = d2l.Accumulator(2) # Sum of losses, no. of examples\n", + " for X, y in data_iter:\n", + " out = net(X)\n", + " y = y.reshape(out.shape)\n", + " l = loss(out, y)\n", + " metric.add(d2l.reduce_sum(l), d2l.size(l))\n", + " return metric[0] / metric[1]" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "msgABldtQNGb" + }, + "source": [ + "def train(train_features, test_features, train_labels, test_labels,\n", + " num_epochs=400):\n", + " loss = nn.MSELoss()\n", + " input_shape = train_features.shape[-1]\n", + " # Switch off the bias since we already catered for it in the polynomial\n", + " # features\n", + " net = nn.Sequential(nn.Linear(input_shape, 1, bias=False))\n", + " batch_size = min(10, train_labels.shape[0])\n", + " train_iter = d2l.load_array((train_features, train_labels.reshape(-1,1)),\n", + " batch_size)\n", + " test_iter = d2l.load_array((test_features, test_labels.reshape(-1,1)),\n", + " batch_size, is_train=False)\n", + " trainer = torch.optim.SGD(net.parameters(), lr=0.01)\n", + " animator = d2l.Animator(xlabel='epoch', ylabel='loss', yscale='log',\n", + " xlim=[1, num_epochs], ylim=[1e-3, 1e2],\n", + " legend=['train', 'test'])\n", + " for epoch in range(num_epochs):\n", + " d2l.train_epoch_ch3(net, train_iter, loss, trainer)\n", + " if epoch == 0 or (epoch + 1) % 20 == 0:\n", + " animator.add(epoch + 1, (evaluate_loss(net, train_iter, loss),\n", + " evaluate_loss(net, test_iter, loss)))\n", + " print('weight:', net[0].weight.data.numpy())" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 284 + }, + "id": "tWsH7GlQQW9T", + "outputId": "edd711a6-408b-4c0f-9f75-866725674b6d" + }, + "source": [ + "# Pick the first four dimensions, i.e., 1, x, x^2/2!, x^3/3! from the\n", + "# polynomial features\n", + "train(poly_features[:n_train, :4], poly_features[n_train:, :4],\n", + " labels[:n_train], labels[n_train:])" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "text": [ + "weight: [[ 4.9902353 1.2391226 -3.3994765 5.4600883]]\n" + ], + "name": "stdout" + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/svg+xml": "\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n" + }, + "metadata": { + "tags": [], + "needs_background": "light" + } + } + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 284 + }, + "id": "Tso7Xq0TRfHk", + "outputId": "6b9ceda4-501d-4400-bf77-9d723345b4d4" + }, + "source": [ + "# Pick the first two dimensions, i.e., 1, x, from the polynomial features\n", + "train(poly_features[:n_train, :2], poly_features[n_train:, :2],\n", + " labels[:n_train], labels[n_train:])" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "text": [ + "weight: [[3.3438766 4.7234397]]\n" + ], + "name": "stdout" + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/svg+xml": "\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n" + }, + "metadata": { + "tags": [], + "needs_background": "light" + } + } + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 335 + }, + "id": "oxnvspC4Rtsd", + "outputId": "0aad196d-0ce4-41a7-c4a0-5cad1c280707" + }, + "source": [ + "# Pick all the dimensions from the polynomial features\n", + "train(poly_features[:n_train, :], poly_features[n_train:, :],\n", + " labels[:n_train], labels[n_train:], num_epochs=1500)" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "text": [ + "weight: [[ 4.9785805 1.2713314 -3.3018856 5.264483 -0.34829667 0.44061425\n", + " 0.06044049 -0.31279543 -0.14870456 -0.2325735 0.19096614 0.21157674\n", + " 0.01430355 -0.05780433 -0.01127242 0.09168547 -0.05965965 -0.04954809\n", + " 0.1855775 0.19902852]]\n" + ], + "name": "stdout" + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/svg+xml": "\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n" + }, + "metadata": { + "tags": [], + "needs_background": "light" + } + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "DUT7EH6KBMJz" + }, + "source": [ + "### generate data set\n", + "n_train, n_test, num_inputs, batch_size = 20, 100, 200, 5\n", + "true_w, true_b = torch.ones((num_inputs, 1)) * 0.01, 0.05\n", + "train_data = d2l.synthetic_data(true_w, true_b, n_train)\n", + "train_iter = d2l.load_array(train_data, batch_size)\n", + "test_data = d2l.synthetic_data(true_w, true_b, n_test)\n", + "test_iter = d2l.load_array(test_data, batch_size, is_train=False)" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "C4QcvEkiIYQa" + }, + "source": [ + "class ch4_weight_decay():\n", + " '''\n", + " Implementation of weight decay from scratch\n", + " lambd: lambda parameter for the model\n", + " train_iter: Torch dataloader class (iterable)\n", + " ep\n", + " '''\n", + " def __init__(self,lambd,train_iter,epoch=100,lr = 0.003):\n", + " self.lambd = lambd\n", + " self.epoch = epoch\n", + " self.lr = lr\n", + " for _iter in train_iter:\n", + " self.w = torch.randn(_iter[0].shape[1],requires_grad = True)\n", + " self.b = torch.tensor([0.0],requires_grad=True)\n", + " break\n", + " self.net = lambda X: d2l.linreg(X, self.w, self.b)\n", + " self.loss_fn = d2l.squared_loss\n", + " self.optim = d2l.sgd\n", + " def model_fit(self,train_iter,show_loss = True):\n", + " '''\n", + " function to fit the model\n", + " trin_iter: Torch iterator \n", + " show_loss = if we want to visualize the graphs\n", + " '''\n", + " #animator = d2l.Animator(xlabel='epochs', ylabel='loss', legend=['Train','Test'], yscale='log')\n", + " for _epoch in range(self.epoch):\n", + " for _iter in train_iter:\n", + " X = _iter[0]\n", + " y = _iter[1]\n", + " y_hat = self.net(_iter[0])\n", + " loss = self.loss_fn(y_hat,y) + 0.5*self.lambd* torch.dot(self.w,self.w)\n", + " loss.sum().backward()\n", + " d2l.sgd([self.w,self.b],self.lr, batch_size = y.shape[0])\n", + " if show_loss:\n", + " if _epoch == 0:\n", + " animator = d2l.Animator(xlabel='epochs', ylabel='loss', legend=['Train','Test'], yscale='log',xlim = [5,self.epoch],figsize= (8,6))\n", + " if (_epoch + 1)%5 == 0:\n", + " animator.add(_epoch+1,(d2l.evaluate_loss(self.net,train_iter,self.loss_fn),d2l.evaluate_loss(self.net,test_iter,self.loss_fn)))\n", + " l2_norm = torch.norm(self.w)\n", + " print(f'L2 norm of w is : {l2_norm}')" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 532 + }, + "id": "DxoBlXQQC_c3", + "outputId": "f84f69c6-9ce6-4864-c5bf-6d54f769013a" + }, + "source": [ + "ch4_1 = ch4_weight_decay(lambd= 0, train_iter=train_iter)\n", + "ch4_1.model_fit(train_iter)" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "text": [ + "L2 norm of w is : 12.525580406188965\n" + ], + "name": "stdout" + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/svg+xml": "\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n" + }, + "metadata": { + "tags": [], + "needs_background": "light" + } + } + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 533 + }, + "id": "vloI6E4Uv0A4", + "outputId": "7c505c9b-5be8-464a-f2b5-7db428dfd21f" + }, + "source": [ + "ch4_1 = ch4_weight_decay(lambd= 3, train_iter=train_iter)\n", + "ch4_1.model_fit(train_iter)" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "text": [ + "L2 norm of w is : 0.362906277179718\n" + ], + "name": "stdout" + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/svg+xml": "\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n" + }, + "metadata": { + "tags": [], + "needs_background": "light" + } + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "OaLmTe6sKIe-" + }, + "source": [ + "class ch4_weight_decay_concise():\n", + " '''\n", + " Implementation of weight decay\n", + " lambd: lambda parameter for the model\n", + " train_iter : Torch dataloader class\n", + " epoch: Number of epcohs\n", + " lr: Regularization parameter\n", + " '''\n", + " def __init__(self,lambd,train_iter,epoch =100, lr = 0.003):\n", + " self.lambd = lambd\n", + " self.epoch = epoch\n", + " self.lr = lr\n", + " for _iter in train_iter:\n", + " self.input_size = _iter[0].shape[1]\n", + " self.net = nn.Sequential(nn.Linear(self.input_size,1))\n", + " for param in self.net.parameters():\n", + " param.data.normal_()\n", + " self.loss_fn = nn.MSELoss()\n", + " self.optim = torch.optim.SGD([{\"params\": self.net[0].weight,'weight_decay': self.lambd},{\"params\": self.net[0].bias}], lr=lr)\n", + " def model_fit(self,train_iter,show_loss = True):\n", + " '''\n", + " function to fit the model\n", + " trin_iter: Torch iterator \n", + " show_loss = if we want to visualize the graphs\n", + " '''\n", + " #animator = d2l.Animator(xlabel='epochs', ylabel='loss', legend=['Train','Test'], yscale='log')\n", + " for _epoch in range(self.epoch):\n", + " for _iter in train_iter:\n", + " X = _iter[0]\n", + " y = _iter[1]\n", + " y_hat = self.net(_iter[0])\n", + " with torch.enable_grad():\n", + " self.optim.zero_grad()\n", + " l = self.loss_fn(self.net(X), y)\n", + " l.backward()\n", + " self.optim.step()\n", + " if show_loss:\n", + " if _epoch == 0:\n", + " animator = d2l.Animator(xlabel='epochs', ylabel='loss', legend=['Train','Test'], yscale='log',xlim = [5,self.epoch],figsize= (8,6))\n", + " if (_epoch + 1)%5 == 0:\n", + " animator.add(_epoch+1,(d2l.evaluate_loss(self.net,train_iter,self.loss_fn),d2l.evaluate_loss(self.net,test_iter,self.loss_fn)))\n", + " print(f'L2 norm of w is : {self.net[0].weight.norm().item()}')\n" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 533 + }, + "id": "Nbgf8mK1n6W0", + "outputId": "9c42810e-6f12-4fb8-a20d-236e36a79c5f" + }, + "source": [ + "ch4_1 = ch4_weight_decay_concise(lambd= 0, train_iter=train_iter)\n", + "ch4_1.model_fit(train_iter)" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "text": [ + "L2 norm of w is : 12.779603958129883\n" + ], + "name": "stdout" + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/svg+xml": "\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n" + }, + "metadata": { + "tags": [], + "needs_background": "light" + } + } + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 532 + }, + "id": "ZTIZXxmCIFaF", + "outputId": "6004ed89-d861-4014-a7d9-835f7a111c8d" + }, + "source": [ + "ch4_1 = ch4_weight_decay_concise(lambd= 3, train_iter=train_iter)\n", + "ch4_1.model_fit(train_iter)" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "text": [ + "L2 norm of w is : 0.3906395435333252\n" + ], + "name": "stdout" + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/svg+xml": "\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n" + }, + "metadata": { + "tags": [], + "needs_background": "light" + } + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "hnx_xUjE9wHU" + }, + "source": [ + "### 4.6 Dropout" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "ybJKbCASHBYO" + }, + "source": [ + "from d2l import torch as d2l\n", + "import torch\n", + "from matplotlib import pyplot as plt\n", + "# plt.style.use('Solarize_Light2')\n", + "# %matplotlib inline" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "TA90GjVVQ_zT", + "outputId": "07fe6df3-f0c8-45bf-c141-7986e310e089" + }, + "source": [ + "# test1 = torch.arange(0,16)\n", + "# test2 = torch.reshape(test1, (2,8))\n", + "# print(test2)\n", + "# def dropout_fn(X,p):\n", + "# '''\n", + "# X: Input tensor for dropout\n", + "# p: probability of dropout\n", + "# '''\n", + "# return ((torch.rand(X.shape) > p) * X) /(1 - p) if p < 1.0 else ((torch.rand(X.shape) > p) * X)\n", + "# test3 = torch.rand(test2.shape) > 0\n", + "# #print(test3)\n", + "# #print(test2)\n", + "# dropout_fn(test2,0.8)\n", + "# X= torch.arange(16, dtype = torch.float32).reshape((2, 8))\n", + "# print(X)\n", + "# print(dropout_fn(X, 0.))\n", + "# print(dropout_fn(X, 0.5))\n", + "# print(dropout_fn(X, 1.))\n", + "# class dropout_model_manual():\n", + "# '''\n", + "# batch_size: batch size of the data iteration\n", + "# num_input\n", + "# num_hidden_layer1\n", + "# num_hidden_layer2\n", + "# num_output\n", + "# dropout_prob\n", + "# '''\n", + "# def __init__(self,batch_size,num_input,num_hidden_layer1, num_hidden_layer2, num_output,dropout_prob, epoch =100, lr = 0.003):\n", + "# self.batch_size = batch_size\n", + "# self.train_iter, self.test_iter = d2l.load_data_fashion_mnist(self.batch_size)\n", + "# self.num_input = num_input\n", + "# self.num_hidden_layer1 = num_hidden_layer1\n", + "# self.num_hidden_layer2 = num_hidden_layer2\n", + "# self.num_output = num_output\n", + "# self.dropout_prob = dropout_prob\n", + " \n", + "# def model_fit()" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "text": [ + "tensor([[ 0, 1, 2, 3, 4, 5, 6, 7],\n", + " [ 8, 9, 10, 11, 12, 13, 14, 15]])\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "pckQkWhLcbVy" + }, + "source": [ + "dropout1, dropout2 = 0.2, 0.5\n", + "num_inputs, num_outputs, num_hiddens1, num_hiddens2 = 784, 10, 256, 256\n", + "\n", + "def dropout_layer(X, dropout):\n", + " assert 0 <= dropout <= 1\n", + " # In this case, all elements are dropped out\n", + " if dropout == 1:\n", + " return torch.zeros_like(X)\n", + " # In this case, all elements are kept\n", + " if dropout == 0:\n", + " return X\n", + " mask = (torch.Tensor(X.shape).uniform_(0, 1) > dropout).float()\n", + " return mask * X / (1.0 - dropout)\n", + "\n", + "class Net(nn.Module):\n", + " def __init__(self, num_inputs, num_outputs, num_hiddens1, num_hiddens2,\n", + " is_training = True):\n", + " super(Net, self).__init__()\n", + "\n", + " self.num_inputs = num_inputs\n", + " self.training = is_training\n", + "\n", + " self.lin1 = nn.Linear(num_inputs, num_hiddens1)\n", + " self.lin2 = nn.Linear(num_hiddens1, num_hiddens2)\n", + " self.lin3 = nn.Linear(num_hiddens2, num_outputs)\n", + "\n", + " self.relu = nn.ReLU()\n", + "\n", + " def forward(self, X):\n", + " H1 = self.relu(self.lin1(X.reshape((-1, self.num_inputs))))\n", + " # Use dropout only when training the model\n", + " if self.training == True:\n", + " # Add a dropout layer after the first fully connected layer\n", + " H1 = dropout_layer(H1, dropout1)\n", + " H2 = self.relu(self.lin2(H1))\n", + " if self.training == True:\n", + " # Add a dropout layer after the second fully connected layer\n", + " H2 = dropout_layer(H2, dropout2)\n", + " out = self.lin3(H2)\n", + " return out\n", + "\n", + "\n", + "net = Net(num_inputs, num_outputs, num_hiddens1, num_hiddens2)" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 264 + }, + "id": "97TQWuLqg59K", + "outputId": "55179cc5-6d1f-41fa-e1e9-179f4a21ed0b" + }, + "source": [ + "num_epochs, lr, batch_size = 10, 0.5, 256\n", + "loss = nn.CrossEntropyLoss()\n", + "train_iter, test_iter = d2l.load_data_fashion_mnist(batch_size)\n", + "trainer = torch.optim.SGD(net.parameters(), lr=lr)\n", + "d2l.train_ch3(net, train_iter, test_iter, loss, num_epochs, trainer)" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/svg+xml": "\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n" + }, + "metadata": { + "tags": [], + "needs_background": "light" + } + } + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "KFyxjLMlDIpH", + "outputId": "83960ae6-43a9-41ac-987b-8fe76a7075e3" + }, + "source": [ + "net = nn.Sequential(nn.Flatten(),\n", + " nn.Linear(784, 256),\n", + " nn.ReLU(),\n", + " # Add a dropout layer after the first fully connected layer\n", + " nn.Dropout(dropout1),\n", + " nn.Linear(256, 256),\n", + " nn.ReLU(),\n", + " # Add a dropout layer after the second fully connected layer\n", + " nn.Dropout(dropout2),\n", + " nn.Linear(256, 10))\n", + "\n", + "def init_weights(m):\n", + " if type(m) == nn.Linear:\n", + " torch.nn.init.normal_(m.weight, std=0.01)\n", + "\n", + "net.apply(init_weights)" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Sequential(\n", + " (0): Flatten(start_dim=1, end_dim=-1)\n", + " (1): Linear(in_features=784, out_features=256, bias=True)\n", + " (2): ReLU()\n", + " (3): Dropout(p=0.2, inplace=False)\n", + " (4): Linear(in_features=256, out_features=256, bias=True)\n", + " (5): ReLU()\n", + " (6): Dropout(p=0.5, inplace=False)\n", + " (7): Linear(in_features=256, out_features=10, bias=True)\n", + ")" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 26 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 264 + }, + "id": "B8soCjT2cdIs", + "outputId": "825f4db8-d2c8-4c6c-94b4-5e6e5bee2ad6" + }, + "source": [ + "num_epochs, lr, batch_size = 10, 0.5, 256\n", + "loss = nn.CrossEntropyLoss()\n", + "train_iter, test_iter = d2l.load_data_fashion_mnist(batch_size)\n", + "trainer = torch.optim.SGD(net.parameters(), lr=lr)\n", + "d2l.train_ch3(net, train_iter, test_iter, loss, num_epochs, trainer)" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/svg+xml": "\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n" + }, + "metadata": { + "tags": [], + "needs_background": "light" + } + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "vsRXx0R-by9i" + }, + "source": [ + "batch_size = 256\n", + "train_iter, test_iter = d2l.load_data_fashion_mnist(batch_size)" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "XaQGLccSAxJD" + }, + "source": [ + "class dropout_model(nn.Module):\n", + " '''\n", + " num_inputs: Number of inputs\n", + " num_layer1: Number of hidden units for layer1\n", + " num_layer2: Number of hidden units for layer2\n", + " num_ouputs: Number of outputs\n", + " dropout1: Dropout for layer 1\n", + " dropout2: Dropout for layer 2\n", + " epochs: Number of epochs\n", + " lr: Learning rate\n", + " '''\n", + " \n", + " def __init__(self,num_inputs,num_layer1,num_layer2,num_ouputs,dropout1 = 0.2,dropout2 = 0.5,epochs = 10, lr = 0.5):\n", + " super(dropout_model, self).__init__()\n", + " self.num_inputs = num_inputs\n", + " self.num_layer1 = num_layer1\n", + " self.num_layer2 = num_layer2\n", + " self.num_ouputs = num_ouputs\n", + " self.dropout1 = dropout1\n", + " self.dropout2 = dropout2\n", + " self.lr = lr\n", + " self.epochs = epochs\n", + " self.model = nn.Sequential(nn.Flatten(),\n", + " nn.Linear(self.num_inputs,self.num_layer1),\n", + " nn.ReLU(),\n", + " nn.Dropout(self.dropout1),\n", + " nn.Linear(self.num_layer1,self.num_layer2),\n", + " nn.ReLU(),\n", + " nn.Dropout(self.dropout2 ),\n", + " nn.Linear(self.num_layer2,self.num_ouputs))\n", + " self.model_loss = nn.CrossEntropyLoss\n", + " self.trainer = torch.optim.SGD\n", + "\n", + " def model_fit(self,train_iter, test_iter):\n", + " '''\n", + " train_iter: train iteration\n", + " test_iter: test iteration\n", + " '''\n", + " if type(self.model) == nn.Linear:\n", + " torch.nn.init.normal_(self.model.weight, std=0.01)\n", + " trainer = self.trainer(self.model.parameters(), lr = self.lr)\n", + " loss = self.model_loss()\n", + " d2l.train_ch3(self.model, train_iter, test_iter, loss, self.epochs, trainer)" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 264 + }, + "id": "iKVqO91lc6ee", + "outputId": "c75a00b1-beeb-4a82-f636-f69ed2f6b82c" + }, + "source": [ + "dropout_test1 = dropout_model(784,256,256,10)\n", + "dropout_test1.model_fit(train_iter,test_iter)" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/svg+xml": "\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n" + }, + "metadata": { + "tags": [], + "needs_background": "light" + } + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "oAkLIYI0GaX7" + }, + "source": [ + "### 4.8 Numerical Stability" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "SH6KYWNaGi0z" + }, + "source": [ + "from d2l import torch as d2l\n", + "import torch\n", + "from matplotlib import pyplot as plt\n", + "plt.style.use('Solarize_Light2')\n", + "%matplotlib inline" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 515 + }, + "id": "cdOsCv7fGFXi", + "outputId": "24d8c33e-a0ef-4d67-bfb6-3f6adf3ce9c3" + }, + "source": [ + "x = torch.arange(-8.0, 8.0, 0.1, requires_grad=True)\n", + "y = torch.sigmoid(x)\n", + "y.backward(torch.ones_like(x))\n", + "fig, axs = plt.subplots(1,1, figsize = (8,6))\n", + "axs.plot(x.detach().numpy(), y.detach().numpy())\n", + "axs.plot(x.detach().numpy(),x.grad.data.numpy())\n", + "axs.set_xlabel('x')\n", + "axs.set_ylabel('sigmoid')\n", + "fig.show()\n" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/svg+xml": "\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n" + }, + "metadata": { + "tags": [], + "needs_background": "light" + } + } + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "ICSpQ0ahKn_F", + "outputId": "1b73cf04-cf64-44f7-a7be-05dcd32bc470" + }, + "source": [ + "M = torch.normal(0, 1, size=(4,4))\n", + "print('a single matrix \\n',M)\n", + "for i in range(100):\n", + " M = torch.mm(M,torch.normal(0, 1, size=(4, 4)))\n", + "\n", + "print('after multiplying 100 matrices\\n', M)" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "text": [ + "a single matrix \n", + " tensor([[-0.5513, 0.5837, 0.1609, -3.0771],\n", + " [ 1.1294, -0.6131, -1.4726, -0.4946],\n", + " [ 0.4827, -1.0457, -0.0111, 1.8005],\n", + " [ 0.4329, -0.6458, 1.6115, 0.7164]])\n", + "after multiplying 100 matrices\n", + " tensor([[ 6.8806e+24, -1.9191e+24, -3.0453e+24, -7.1837e+24],\n", + " [ 3.0670e+24, -8.5543e+23, -1.3574e+24, -3.2021e+24],\n", + " [-1.7558e+24, 4.8973e+23, 7.7711e+23, 1.8332e+24],\n", + " [ 2.0170e+23, -5.6257e+22, -8.9270e+22, -2.1059e+23]])\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "zKDhJRymuGWh" + }, + "source": [ + "# 4.10 Predicting House Prices on Kaggle" + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "clY24TvmuTP5", + "outputId": "aee5aa34-095f-4c6a-9642-5f1f1f686cea" + }, + "source": [ + "import os\n", + "import requests\n", + "import zipfile\n", + "import tarfile\n", + "import hashlib\n", + "from google.colab import drive\n", + "drive.mount(\"/drive\", force_remount=True)\n", + "#@save\n", + "DATA_HUB = dict()\n", + "DATA_URL = 'http://d2l-data.s3-accelerate.amazonaws.com/'" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "text": [ + "Mounted at /drive\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "9gOocWXRu-9m" + }, + "source": [ + "def download(name, cache_dir=os.path.join('..', 'data')): #@save\n", + " \"\"\"Download a file inserted into DATA_HUB, return the local filename.\"\"\"\n", + " assert name in DATA_HUB, f\"{name} does not exist in {DATA_HUB}.\"\n", + " url, sha1_hash = DATA_HUB[name]\n", + " os.makedirs(cache_dir, exist_ok=True)\n", + " fname = os.path.join(cache_dir, url.split('/')[-1])\n", + " if os.path.exists(fname):\n", + " sha1 = hashlib.sha1()\n", + " with open(fname, 'rb') as f:\n", + " while True:\n", + " data = f.read(1048576)\n", + " if not data:\n", + " break\n", + " sha1.update(data)\n", + " if sha1.hexdigest() == sha1_hash:\n", + " return fname # Hit cache\n", + " print(f'Downloading {fname} from {url}...')\n", + " r = requests.get(url, stream=True, verify=True)\n", + " with open(fname, 'wb') as f:\n", + " f.write(r.content)\n", + " return fname" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "OUl99RpovD37" + }, + "source": [ + "def download_extract(name, folder=None): #@save\n", + " \"\"\"Download and extract a zip/tar file.\"\"\"\n", + " fname = download(name)\n", + " base_dir = os.path.dirname(fname)\n", + " data_dir, ext = os.path.splitext(fname)\n", + " if ext == '.zip':\n", + " fp = zipfile.ZipFile(fname, 'r')\n", + " elif ext in ('.tar', '.gz'):\n", + " fp = tarfile.open(fname, 'r')\n", + " else:\n", + " assert False, 'Only zip/tar files can be extracted.'\n", + " fp.extractall(base_dir)\n", + " return os.path.join(base_dir, folder) if folder else data_dir\n", + "\n", + "def download_all(): #@save\n", + " \"\"\"Download all files in the DATA_HUB.\"\"\"\n", + " for name in DATA_HUB:\n", + " download(name)" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "OIO6ZNiiwCiF" + }, + "source": [ + "from d2l import torch as d2l\n", + "import torch\n", + "import torch.nn as nn\n", + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "plt.style.use('Solarize_Light2')\n", + "%matplotlib inline" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "_n5HejQ50Dqt" + }, + "source": [ + "DATA_HUB['kaggle_house_train'] = ( #@save\n", + " DATA_URL + 'kaggle_house_pred_train.csv',\n", + " '585e9cc93e70b39160e7921475f9bcd7d31219ce')\n", + "\n", + "DATA_HUB['kaggle_house_test'] = ( #@save\n", + " DATA_URL + 'kaggle_house_pred_test.csv',\n", + " 'fa19780a7b011d9b009e8bff8e99922a8ee2eb90')" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "7I0FUb1m1FRt", + "outputId": "cca2d033-5291-4804-9f76-82e90111f2f9" + }, + "source": [ + "train_data = pd.read_csv(download('kaggle_house_train'))\n", + "test_data = pd.read_csv(download('kaggle_house_test'))" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "text": [ + "Downloading ../data/kaggle_house_pred_train.csv from http://d2l-data.s3-accelerate.amazonaws.com/kaggle_house_pred_train.csv...\n", + "Downloading ../data/kaggle_house_pred_test.csv from http://d2l-data.s3-accelerate.amazonaws.com/kaggle_house_pred_test.csv...\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "MFbVtn7r1JJu", + "outputId": "7f0f1f3f-27fc-4237-e34d-ea40b927ede4" + }, + "source": [ + "print(train_data.shape)\n", + "print(test_data.shape)" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "text": [ + "(1460, 81)\n", + "(1459, 80)\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 173 + }, + "id": "ug5yQ-kx1Oj4", + "outputId": "c4ede4b9-8aad-44c1-dab8-c19ed609ed3c" + }, + "source": [ + "display(train_data.iloc[0:4, [0, 1, 2, 3, -3, -2, -1]])\n", + "all_features = pd.concat((train_data.iloc[:, 1:-1], test_data.iloc[:, 1:]))" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " Id MSSubClass MSZoning LotFrontage SaleType SaleCondition SalePrice\n", + "0 1 60 RL 65.0 WD Normal 208500\n", + "1 2 20 RL 80.0 WD Normal 181500\n", + "2 3 60 RL 68.0 WD Normal 223500\n", + "3 4 70 RL 60.0 WD Abnorml 140000" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "LRC10NFA2dqV" + }, + "source": [ + "numeric_features = all_features.dtypes[all_features.dtypes != 'object'].index\n", + "all_features[numeric_features] = all_features[numeric_features].apply(\n", + " lambda x: (x - x.mean()) / (x.std()))\n", + "# After standardizing the data all means vanish, hence we can set missing\n", + "# values to 0\n", + "all_features[numeric_features] = all_features[numeric_features].fillna(0)" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "JZZIxOxZ2okU", + "outputId": "6380313e-bd51-49a4-f7b7-fb48b255b8e5" + }, + "source": [ + "# `Dummy_na=True` considers \"na\" (missing value) as a valid feature value, and\n", + "# creates an indicator feature for it\n", + "all_features = pd.get_dummies(all_features, dummy_na=True)\n", + "all_features.shape" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "(2919, 331)" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 11 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "Qhkj734x2uSm" + }, + "source": [ + "n_train = train_data.shape[0]\n", + "train_features = torch.tensor(all_features[:n_train].values, dtype=torch.float32)\n", + "test_features = torch.tensor(all_features[n_train:].values, dtype=torch.float32)\n", + "train_labels = torch.tensor(\n", + " train_data.SalePrice.values.reshape(-1, 1), dtype=torch.float32)" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "D7Q6sISn250z" + }, + "source": [ + "loss = nn.MSELoss()\n", + "in_features = train_features.shape[1]\n", + "\n", + "def get_net():\n", + " net = nn.Sequential(nn.Linear(in_features,1))\n", + " return net" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "-hjUY-7L3AuE" + }, + "source": [ + "def log_rmse(net, features, labels):\n", + " # To further stabilize the value when the logarithm is taken, set the\n", + " # value less than 1 as 1\n", + " clipped_preds = torch.clamp(net(features), 1, float('inf'))\n", + " rmse = torch.sqrt(loss(torch.log(clipped_preds),\n", + " torch.log(labels)))\n", + " return rmse.item()" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "vAvgYHPo3DXM" + }, + "source": [ + "def train(net, train_features, train_labels, test_features, test_labels,\n", + " num_epochs, learning_rate, weight_decay, batch_size):\n", + " train_ls, test_ls = [], []\n", + " train_iter = d2l.load_array((train_features, train_labels), batch_size)\n", + " # The Adam optimization algorithm is used here\n", + " optimizer = torch.optim.Adam(net.parameters(),\n", + " lr = learning_rate,\n", + " weight_decay = weight_decay)\n", + " for epoch in range(num_epochs):\n", + " for X, y in train_iter:\n", + " optimizer.zero_grad()\n", + " l = loss(net(X), y)\n", + " l.backward()\n", + " optimizer.step()\n", + " train_ls.append(log_rmse(net, train_features, train_labels))\n", + " if test_labels is not None:\n", + " test_ls.append(log_rmse(net, test_features, test_labels))\n", + " return train_ls, test_ls" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "YTPd4x4V3GWt" + }, + "source": [ + "def get_k_fold_data(k, i, X, y):\n", + " assert k > 1\n", + " fold_size = X.shape[0] // k\n", + " X_train, y_train = None, None\n", + " for j in range(k):\n", + " idx = slice(j * fold_size, (j + 1) * fold_size)\n", + " X_part, y_part = X[idx, :], y[idx]\n", + " if j == i:\n", + " X_valid, y_valid = X_part, y_part\n", + " elif X_train is None:\n", + " X_train, y_train = X_part, y_part\n", + " else:\n", + " X_train = torch.cat([X_train, X_part], 0)\n", + " y_train = torch.cat([y_train, y_part], 0)\n", + " return X_train, y_train, X_valid, y_valid" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "ucqEJ8zq3QMn" + }, + "source": [ + "def k_fold(k, X_train, y_train, num_epochs, learning_rate, weight_decay,\n", + " batch_size):\n", + " train_l_sum, valid_l_sum = 0, 0\n", + " for i in range(k):\n", + " data = get_k_fold_data(k, i, X_train, y_train)\n", + " net = get_net()\n", + " train_ls, valid_ls = train(net, *data, num_epochs, learning_rate,\n", + " weight_decay, batch_size)\n", + " train_l_sum += train_ls[-1]\n", + " valid_l_sum += valid_ls[-1]\n", + " if i == 0:\n", + " d2l.plot(list(range(1, num_epochs + 1)), [train_ls, valid_ls],\n", + " xlabel='epoch', ylabel='rmse', xlim=[1, num_epochs],\n", + " legend=['train', 'valid'], yscale='log')\n", + " print(f'fold {i + 1}, train log rmse {float(train_ls[-1]):f}, '\n", + " f'valid log rmse {float(valid_ls[-1]):f}')\n", + " return train_l_sum / k, valid_l_sum / k" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 366 + }, + "id": "-x7xw2mv3UTn", + "outputId": "e83409aa-b942-4add-e526-822e315ca63f" + }, + "source": [ + "k, num_epochs, lr, weight_decay, batch_size = 5, 100, 5, 0, 64\n", + "train_l, valid_l = k_fold(k, train_features, train_labels, num_epochs, lr,\n", + " weight_decay, batch_size)\n", + "print(f'{k}-fold validation: avg train log rmse: {float(train_l):f}, '\n", + " f'avg valid log rmse: {float(valid_l):f}')" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "text": [ + "fold 1, train log rmse 0.169071, valid log rmse 0.156702\n", + "fold 2, train log rmse 0.162129, valid log rmse 0.188680\n", + "fold 3, train log rmse 0.164022, valid log rmse 0.168635\n", + "fold 4, train log rmse 0.167654, valid log rmse 0.154539\n", + "fold 5, train log rmse 0.163767, valid log rmse 0.183065\n", + "5-fold validation: avg train log rmse: 0.165329, avg valid log rmse: 0.170324\n" + ], + "name": "stdout" + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/svg+xml": "\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n" + }, + "metadata": { + "tags": [], + "needs_background": "light" + } + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "ChzP1-JB3fy2" + }, + "source": [ + "def train_and_pred(train_features, test_feature, train_labels, test_data,\n", + " num_epochs, lr, weight_decay, batch_size):\n", + " net = get_net()\n", + " train_ls, _ = train(net, train_features, train_labels, None, None,\n", + " num_epochs, lr, weight_decay, batch_size)\n", + " d2l.plot(np.arange(1, num_epochs + 1), [train_ls], xlabel='epoch',\n", + " ylabel='log rmse', xlim=[1, num_epochs], yscale='log')\n", + " print(f'train log rmse {float(train_ls[-1]):f}')\n", + " # Apply the network to the test set\n", + " preds = d2l.numpy(net(test_features))\n", + " # Reformat it to export to Kaggle\n", + " test_data['SalePrice'] = pd.Series(preds.reshape(1, -1)[0])\n", + " submission = pd.concat([test_data['Id'], test_data['SalePrice']], axis=1)\n", + " submission.to_csv('/drive/My Drive/Colab_Notebooks/Dive_into_deep_learning/submission.csv',index=False)\n", + " #submission.to_csv('submission.csv', index=False)" + ], + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 281 + }, + "id": "0JAkMpqk3kZQ", + "outputId": "c77cdd47-1c4f-42f3-fe30-3a679d88f7c5" + }, + "source": [ + "train_and_pred(train_features, test_features, train_labels, test_data,\n", + " num_epochs, lr, weight_decay, batch_size)" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "text": [ + "train log rmse 0.162587\n" + ], + "name": "stdout" + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/svg+xml": "\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n" + }, + "metadata": { + "tags": [], + "needs_background": "light" + } + } + ] + }, + { + "cell_type": "code", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "PQ5zGEfXN2eD", + "outputId": "114c3f0a-7b4f-4ddf-fc48-c6f4e2c272cc" + }, + "source": [ + "slice(1 * 3, 2 * 3)" + ], + "execution_count": null, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "slice(3, 6, None)" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 24 + } + ] + } + ] +} \ No newline at end of file diff --git a/Statistical_Rethinking /Chapter3.ipynb b/Statistical_Rethinking /Chapter3.ipynb new file mode 100644 index 00000000..ad6c12d8 --- /dev/null +++ b/Statistical_Rethinking /Chapter3.ipynb @@ -0,0 +1,217 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "name": "Chapter3.ipynb", + "provenance": [], + "collapsed_sections": [], + "authorship_tag": "ABX9TyOcXctRkeXjufe4n29nc7hz", + "include_colab_link": true + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + } + }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "view-in-github", + "colab_type": "text" + }, + "source": [ + "\"Open" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "kqEJQYOgTT4c", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 51 + }, + "outputId": "c530fff9-0be1-4c33-f2c6-508ecaf581fd" + }, + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "from scipy import stats\n", + "import seaborn as sns\n", + "sns.set()\n", + "plt.style.use('fivethirtyeight')" + ], + "execution_count": 1, + "outputs": [ + { + "output_type": "stream", + "text": [ + "/usr/local/lib/python3.6/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n", + " import pandas.util.testing as tm\n" + ], + "name": "stderr" + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3-PNSBEnUIqb", + "colab_type": "text" + }, + "source": [ + "### Code 3.1\n", + "$Pr(vampire|positive) = \\frac{P(positive|vampire)P(vampire)}{P(positive)} $\n", + "```\n", + "Applying Bayes Theorem\n", + "```" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "sb8lPasXUzaV", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "outputId": "3f426229-0ddf-4b87-8b30-194dc4f7cf63" + }, + "source": [ + "PrPV = 0.95\n", + "PrPM = 0.01\n", + "PrV = 0.001\n", + "PrP = PrPV * PrV + PrPM * (1 - PrV)\n", + "PrVP = PrPV * PrV / PrP\n", + "print(PrVP)" + ], + "execution_count": 2, + "outputs": [ + { + "output_type": "stream", + "text": [ + "0.08683729433272395\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "IJNIay1NgPkN", + "colab_type": "text" + }, + "source": [ + "### Code 3.2" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "R3iqt80TVocQ", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "outputId": "eb8222d0-2f79-432d-d0ee-71de32e36075" + }, + "source": [ + "def posterior_grid_approx(grid_points=5, success=6, tosses=9):\n", + " \"\"\"\n", + " \"\"\"\n", + " # define grid\n", + " p_grid = np.linspace(0, 1, grid_points)\n", + "\n", + " # define prior\n", + " prior = np.repeat(1, grid_points) # uniform\n", + " #prior = (p_grid >= 0.5).astype(int) # truncated\n", + " #prior = np.exp(- 5 * abs(p_grid - 0.5)) # double exp\n", + "\n", + " # compute likelihood at each point in the grid\n", + " likelihood = stats.binom.pmf(success, tosses, p_grid)\n", + "\n", + " # compute product of likelihood and prior\n", + " unstd_posterior = likelihood * prior\n", + "\n", + " # standardize the posterior, so it sums to 1\n", + " posterior = unstd_posterior / unstd_posterior.sum()\n", + " return p_grid, posterior\n", + "np.__version__" + ], + "execution_count": 3, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "'1.18.4'" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 3 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "-iwqcjsTbIDf", + "colab_type": "code", + "colab": {} + }, + "source": [ + "p_grid, posterior = posterior_grid_approx(grid_points=100, success=6, tosses=9)\n", + "samples = np.random.choice(p_grid, p=posterior, size=int(1e4), replace=True)\n" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "YChIV_CWeaXO", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 388 + }, + "outputId": "be101e3f-2b0d-4f68-f750-d5e5f7f378ba" + }, + "source": [ + "fig, (ax0, ax1) = plt.subplots(1,2, figsize=(12,6))\n", + "ax0.plot(samples,'o',alpha=0.2)\n", + "ax0.set_xlabel('sample number')\n", + "ax0.set_ylabel('proportion of water')\n", + "sns.kdeplot(samples,ax =ax1)\n", + "ax1.set_xlabel('proportion of water')\n", + "ax1.set_ylabel('Density')\n", + "fig.show()" + ], + "execution_count": 5, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [], + "needs_background": "light" + } + } + ] + } + ] +} \ No newline at end of file diff --git a/Statistical_Rethinking/Chapter3.ipynb b/Statistical_Rethinking/Chapter3.ipynb new file mode 100644 index 00000000..482cfe5e --- /dev/null +++ b/Statistical_Rethinking/Chapter3.ipynb @@ -0,0 +1,217 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "name": "Chapter3.ipynb", + "provenance": [], + "collapsed_sections": [], + "authorship_tag": "ABX9TyOcXctRkeXjufe4n29nc7hz", + "include_colab_link": true + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + } + }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "view-in-github", + "colab_type": "text" + }, + "source": [ + "\"Open" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "kqEJQYOgTT4c", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 51 + }, + "outputId": "c530fff9-0be1-4c33-f2c6-508ecaf581fd" + }, + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "from scipy import stats\n", + "import seaborn as sns\n", + "sns.set()\n", + "plt.style.use('fivethirtyeight')" + ], + "execution_count": 1, + "outputs": [ + { + "output_type": "stream", + "text": [ + "/usr/local/lib/python3.6/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n", + " import pandas.util.testing as tm\n" + ], + "name": "stderr" + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3-PNSBEnUIqb", + "colab_type": "text" + }, + "source": [ + "### Code 3.1\n", + "$Pr(vampire|positive) = \\frac{P(positive|vampire)P(vampire)}{P(positive)} $\n", + "```\n", + "Applying Bayes Theorem\n", + "```" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "sb8lPasXUzaV", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "outputId": "3f426229-0ddf-4b87-8b30-194dc4f7cf63" + }, + "source": [ + "PrPV = 0.95\n", + "PrPM = 0.01\n", + "PrV = 0.001\n", + "PrP = PrPV * PrV + PrPM * (1 - PrV)\n", + "PrVP = PrPV * PrV / PrP\n", + "print(PrVP)" + ], + "execution_count": 2, + "outputs": [ + { + "output_type": "stream", + "text": [ + "0.08683729433272395\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "IJNIay1NgPkN", + "colab_type": "text" + }, + "source": [ + "### Code 3.2" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "R3iqt80TVocQ", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "outputId": "eb8222d0-2f79-432d-d0ee-71de32e36075" + }, + "source": [ + "def posterior_grid_approx(grid_points=5, success=6, tosses=9):\n", + " \"\"\"\n", + " \"\"\"\n", + " # define grid\n", + " p_grid = np.linspace(0, 1, grid_points)\n", + "\n", + " # define prior\n", + " prior = np.repeat(1, grid_points) # uniform\n", + " #prior = (p_grid >= 0.5).astype(int) # truncated\n", + " #prior = np.exp(- 5 * abs(p_grid - 0.5)) # double exp\n", + "\n", + " # compute likelihood at each point in the grid\n", + " likelihood = stats.binom.pmf(success, tosses, p_grid)\n", + "\n", + " # compute product of likelihood and prior\n", + " unstd_posterior = likelihood * prior\n", + "\n", + " # standardize the posterior, so it sums to 1\n", + " posterior = unstd_posterior / unstd_posterior.sum()\n", + " return p_grid, posterior\n", + "np.__version__" + ], + "execution_count": 3, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "'1.18.4'" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 3 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "-iwqcjsTbIDf", + "colab_type": "code", + "colab": {} + }, + "source": [ + "p_grid, posterior = posterior_grid_approx(grid_points=100, success=6, tosses=9)\n", + "samples = np.random.choice(p_grid, p=posterior, size=int(1e4), replace=True)\n" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "YChIV_CWeaXO", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 388 + }, + "outputId": "be101e3f-2b0d-4f68-f750-d5e5f7f378ba" + }, + "source": [ + "fig, (ax0, ax1) = plt.subplots(1,2, figsize=(12,6))\n", + "ax0.plot(samples,'o',alpha=0.2)\n", + "ax0.set_xlabel('sample number')\n", + "ax0.set_ylabel('proportion of water')\n", + "sns.kdeplot(samples,ax =ax1)\n", + "ax1.set_xlabel('proportion of water')\n", + "ax1.set_ylabel('Density')\n", + "fig.show()" + ], + "execution_count": 5, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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pP0dfvGbOq3BFT06mtd7X35v150UkcMzGpFgslh3yv1/y+PPptbk8PjTu868+OMj7x1ZlUfOtlNeXYq42Uq7WUwJH8JEJn2fGfTy5/7Ecnz2WoeiJniPifFvxwnzE90zszXbecvdyYCYjtxoTcLvqEivN9YZiJKMZCyStRHOuknCy5O6orl3JRt4zwd2tjozEkaw5VjVSvLIYU/Bkb7vzKwmJ0hzJORQ9QZjCK4sxj41425bd/4Z+J9vspa8KnXplXFgKU+ZaKTlXMODB64sxIHhy1OtJ3gAO5UwbFzvylZODLhdWkj3VsdtOpRXtWJEKaCcKpTXlSsKDRYdB35S12Tnr7l+Nkk45ZtWnEir+6mqbv3Esw1AgdhSr0t/fc62UL18Ned+Yx0RG0ko152qSh9fFEGw29uZaKdcbKRNZuaFfAKYbKa6EQU8SKs2bSzEPFh08Sa8ORc+MmZmWoh1rAgcW24pYJ7w4F3Jm2GMks/c8MDsZ4+v7vr/NAs25lQStBe1UESaSlTDlaFFsOxZ2+/vxXv/edC2O+8/LlYZkuK323M/3KlNTUyPAbwIPAxFwHviZcrk8v267/xv4DLDQ+eh3y+Xyv7iNVbVY7jgvzUf81vRaWdXjwx6/9/0jFLy1vyFjWYdPTe7fysfNyLiC7z+W4f99t9X77E+vtO1k5D7mwNy11uq6uS02pzuri9GYt1LMQ4SG8awgTBVRqlB6ZzERW8lINHpNuy+smAf3UyWvt1228+BoYnpF7//dIN/dyHT2W+rV7auRQNJMNJVIca2WMp510Foghdwgu+mXvPXLV/bDarXbzsVQcbTg4EuQAlwJsVK8u5JwNO9sec66+79dSRj0JCcGXKQUNBJFwYdvz4U7Gpfr+3sxVJQygsW26juvekPbNht7F6opDw+6W2Y0X2+lK4TmnZUEwdoM781Yo7QmcAEhEEKQcQQLLcU7K8mer7WdjXFNK2UbO1+IUphrKSYyLr4rEEKSdbYfC7uN3XkvLITX98X680LnvNyJ37S7BA38L+VyeapcLj8OvAP88hbb/nK5XH6y85+diFgOFFprfuHFlTWfHcpK/p/PbJyI3Cn+1vG1iW//5HILre2q7/3K3THqbgP9uu6VhH2JM9iPunQ15qcGXT4y4eM5kCI4OehyesilFu2sriuhJrtJtm2txZp2txU8ObrqQgXgScGRvMSVRmLkSrPK0JVoblX2Sp8cZCfb3ArdvhrOOhzKO+RcQdaTjGUkZ4Y9NOYtfCAF9c6SbqzMStP6usw21Z7r2G1nPdYMZ8xkIusIGonR2B7KO8Rq63PW3X8pVOQ8yLqC4wWHWAnQsBLpHY3L9f1djzVFd7UPADKSDW3bbOxN5h0m1r1N7/ZL10r3zJCH50A11hRcwZG8g9L06qCBsazEAVIFEzmHI3mXWJlvj+SdPV9rOxnji6HGF6zpw/42V2N4dNhlNGdiWhwJj5TcXlu2Ggu7jd3Z71ifzfpi/XnJS/aln+9VyuXyUrlc/krfR98EHrhD1bFY7lq+fD3k+ZlozWf/9uNDTG4TH3K7+fRkBr/vp+xiLeXtSrL1DpZ7mgMj04JVXXepojm1TWzAzbT4N7NC3Ul8Rbcu3W2vN1IW22KNXW0zUXiOWKNF38oSuGupOpKRncRvmgsrMW1Frw0DDtQ1XFhJ1hzHkzDoO5wdWn2j2kwUOW+jzKXLesnJVvKfubbii9fae7In7vbVM2Pm7xfmQ+JUkyjNfCvl3ap5SD1cMD+ksdLMtxV/dqXFdD2lWpU8FDfxnLVWqyVfMttMen3UX7/N+rkSKr4x02aurVAaHhpwOVpwOFIQHC+6nBhwNpyv9XT7aTiQNGMo+OBKwUNFh4wjCCLFd+ajm/bX+v4udPS13bda0/WEL85LnFaTCysRR/LdlY+NltHd85kozbVGQj3WhKnGlSZBZYIm60iUxsj7MrInBerWoeCJzncOrgMPFlwiBYlyOFZwOFpwtryurtVTZpsJjcRMzh4teZwYcHm3FlNeTkDAoyUPKTbWs2sb3B+zcb6lt7zewMRMDXgJcQqp1lxtJEQKPKG3tCC+FTvkncQg3azcrb6XAr42E3KjqRDC9HfJ0xwt3D0PE3eSqakpCfws8EdbbPJfT01N/Qxm9eTny+XyW7etchbLHURpzS+8WF3z2SePBHzfZGaLPe4MRV/yicMBfzW96vL1p1fanB46sCu/9zXiXlv2WllZ2XOFz58/z6lTpzb9rl+XnnWMFv+VhWSNFr8Rs+VbzvX7b7d9/7ZxqnmlL/bBk2zYb7OyZ5rGxjPvwrvVFCmhHmkiZXJ0PDnq0U4UrywkjEVzPHxscsNxumUcyslN67yTNu2133bDcqh4drrN1XqCK+ByPSFOBUcLkgeKLq8vJDQTxZV6TM6VrFTrlAYLNGPNqZLHQwMujUTxZsVIqj5yKFjT38CG9l5YSXi3mjAYSBaaCfUUrtUS3j8WMBxITgy6ONz87Xd/zMhXb0RkXIEL5H3JpWrK9x/L8HDR2fU46+/vJFX8+dWQVnWFJ4+NcLGWEKXw8cM+sy21YYydHHR5eSHiat1Ix/r75sSAw/MzEb4QnB12SYFKW/P5kzlKgVwzfr8+G/FONSHnCgY7MT5DGclUyeOpUb8Xr9Nf34dLDperKdcaCZ4QPFB0qEawEqYMBpLDWQeEZiWCob68LIOe7H1+rODwqclMr592cn0rrXh9KVlz3ESJDWVt1tf7NZZvVu5W358cdHn+RptvzUUMexLP0SyHoBoV/qsPH+PEFhOqnTI4OHjPZxebmpr6N8Ak8KPlclmt+24SuFEul9XU1NRPAr8EPFQul9PuNv33mfPnz9+mWlss7z3/35zD/3Bu7UuS33yyxaOFu+9Z8PdnHP7VhdW6ni6k/MaTt25BbLmz9N+X199n7GRkHd237t0EfW8uR9Q6b5y7KwebrVhstf9226/fthqp3mrGM+P+hrekm5X90nyIRvD0mE81UlxrJLyyEJN1BZ8+mqXoiV4bmotzfOr0sU2PA9zSG9p++re50UwYyzocyq6+qd2u33bLl6fbXKwmJBoE5m1/O1VUQsUzEwFfu95mtp3iCEG9ViVXKDIUSDwpODPk8sZSDBoeGHT5YKc+3foBG/r5D95tECvB+0Y9GrFirqW42kjQGr7/WJbJgrPjlZ9+N61L1QQTpKM5PeRzcnD1QfJm/bXVSsPvX2gihKAYLUJhlFhpIg1LbcUHx3wQZjXm7JDXO0Yt0r3+nG+lDGcc8i5cracM+4L5UBEpODvkMhJIhrPOmpW9bjLBeqw5X0lYbKeMZB3eP+qbiUg13vS6mm8pUqWRAoQQOBKiVHO5mnK86HC6ZMZmO9UkCiKl8KXckEiwv5+2u777++256yG1yAT4j2WdTcuC3V3Tu+Fm5W71/TvVhDjVtFOoxopmonEAVVvkhx4/uufr616fjExNTf1r4Angc+Vy+aZPLlNTU4vA+8vl8uXuZ/txn7mXuNk1cz9z0Nr+6T+e4zt9yQv/7kNZfu0Tw3ewRlsz20x59Hdm6L8YX//xCY4W9i7qOWjnvZ+7oe3r7zMHSqa1Ff0PVOdW4jVypa4Wv9qnxd/KpnQ5VLwwFyExQc3dDNRoTTVhw4P8ervQoi95atRnMdSbSrOemw45lJMcH1iVWK1EivmWWvNQnihNnK7Wq9uGeWUmPOVKxMVqykwz5UIlpp0ayc6HJwI+fjhzS2971z8Y12OzyvLtuZBLtRQh4IGCw1jW6cmtNtv/WseudMCTvQd8YMMD77PX2uQ8wYmix1TJ71jpar40HfZWYh4ecJFCsBBprkSaQKTMhprTQx5jWZeJjKDaJ0HtWh43E72hn2uxJtu5WvKe5IQneaDgMN1U/MiJ3JZtWS8/emrU75OdrbWC3a31dCVUvL0cM9tUSKEBQSPWvLoU8dCAQxwKQpEi0FQizflqQs4RDGckGddMRvqP8f5RY2rw7bkQB+Pu9tpSzPtGXI7mXRINZ4b8NRa120mRLlYTvjbT5qX5iMUw5aMTAbmCGVvdMVkOFQ6KKDXxTKk2KyCR0iy2Ur7WSqnGmgFPcCjnkHEkZ8ZdrjVS6rHmar1rGKB7x3vjquSsrvOxQxlKnVwu66+9Z8aC3vUnxGq/99sxd89l95oe8I0EsuiJfbEqvpld8FaWyrNNxYAnGA4EIxmXRqyYbSrOtwUvzEa3LIe8H5iamvqXwNPA39pqIjI1NTVZLpenO//+ASAFpm9fLS2WO8MrC9GaiYhA8/NPFu9gjbZnIufwzJjPt+dX41v+8lrITz1qH13vNw7mHauP9VmMMxJeWYh7k4+CJ6gmxlq2y3aWrRkJqdK8U405v5IQppq3KgkzjXRDxueu7r+f9WX31+9wTtJIjLVqNdZUI8X1ppHduKwe05cCEL3tum2QGl6cj7iwklCLFZdrCa8uxlRC86b1L660+ZNLzQ0ZnG+WgXuz78+vJHzpWpt3qjEZxwRTv7WU8M5KsmX5S62UmUZKM9HcaKQsttWGzPTfno34y6ttMo7AAS5UjHVsNda0Us1ETq6JyQCopxCmikoM4xlJojRzzZSZtuqd167lceCIDf0MMOCZQOl+qok53lZteXcloVxJmG2kaK15bdHkFdksQ/ZOxkI/F6sJX7jQpJlofKH5+kzIc9fbzLYSXCk4t5wwE8I7tYT5tmIpTMm6MN9OWQrNBLbbZ4MdK+Hu8QVQXkloppqxjKSdwLlKQtdOficWtf31m8xJBPDnV9pMN8wsuTsms45gvqVoK40nwXNgvqloJIpzKzFxCkO+oJnAa4sxYap4ZSEmUZpBz0y8X1mImW2tHm/Ch2ai+fW3G/zJpeaW4/Zmfd5/TWekOVZ3TOyHTe92x+9a9zaS1Xa+uRQz21ZM5CSehDCFRqy4WEtopZoBBwJHHNgs7FNTU2eBnweOAF+fmpp6ZWpq6g86370yNTV1pLPpr09NTb02NTX1KvDPgB8ul8s2MtZy3/Mfyo01f3/PkOLhwbv7wf6z61y1nr3e3mJLy73MgZ+MrLcLPTnoAZrzlRitNSOBpNI2geHbWXR2yzk56DHdSAmEyRD++lKCJyUPDbobMj7vxP6zv37HCi5aG2vVK7WYCysxw4HDaM7hWiMl70oCFyINozmnt123DaGCaqgIHMm1hiLvS4YDSYok1jCclVyoJhvsTW9m27vZ9xkHLtViAiEJHGMT7DvguxvtU/vtcnOuCSzPecamdn1m+ig158R3jQVx4MBKqDhfiWnE8LFDGRoxPFpyWYkVi6FioS2YyDo0Y82JAY9AwlhOcrGa9M5rv+Xx+n5uJoqHBz18ByqRQiljMVxpaz52KLNlW+qxYjiQFANJNdaUOg+Zm9nH7tYK9mszbUoZ01fnqykjGYkrjWXt2ZIHUvBOUzIaCK7WE8IEHh/ySbUxFpjMy16fnSx6G44fK02YwFTJ3bXN9Pr6SSk4WXTxHWNd3H9dFQNB0TcJNhuxZsiX5FwTL1FwJY5j3NE0MJJ1jAU12nzQ9/83FuO+40HJl0RacaGabDlub9bn/dd0W5ljZRy9pt/2wnbH385S2az4OFQixZVaCtpMTAounCp5BzYLe7lcfqNcLouOtW/XtvfvdL57slwuX+/8+zPlcvnxcrn8vnK5/PFyufzNO1tzi+W9ZyVSa/J2APzYobt/Dv59R9auvD93IySx2djvOw78ZGS9XWjRlzw54hGmRooynHX4/MkcIxm5rUVnt5yiLxnPOWQ9iJR5czlVchn2Zc92tWshuhP7z/76FX3JmSGPgiuYaSraCj5yyOcDox5x5wEy55gg3A+Mrm7XbYMjYCVWZFzIOAJfaHzHOAq1U8g7glqkNtib3sy2d7PvfSko+JKsB41E4zrGQtUXG+1T++1yg06ISdeqt9+mtx5rEq3JuaARPVvdaqwIU2OJe6Lo8oFxn+NFjw+M+xRcgZLGZejzJ3MczpuJwXhG8sy43zuv/ZbH6/vZcwSfezDHP5wqkHMF000zafr8ydyGYOH+tiRa40vjVtZMTJtipTe1j92tFexsU1HsJrKMFRlpZIHtRDOUkTw14hOloDTkO0YGxcBYEY9mHVwhen02FMiN9rcll1ODLoGze84GtKwAACAASURBVJvp9fUDI207W3JZidZeVwOe5MGiwwMDLiNZByEET455TOZdTg95REoQaThecHn/sEsz1Tw5smpn6znw5IjHUrT2eGB+3GrR2hWC/nF7sz7vv6a7Frphypp+2wvbHX87S+UTRZdPTWZ4bMSjEilS4GTJ5WxR9SRke7XUtlgs9xe/01k57jKZc/jocLrNHncHT4x4jPT91lYjzUsL0TZ7WO5F7u71ufeY5VD1LHEzzmqMhytgasjl031Wdye26ar15Uw3UqbrCY1UkypjpTuaEbRS82a4a0cKN7f/XG/hWvQlJ4oujwytDbQ+M+RRCY3VbT3RXG2YAOJHhrxeoLHABDHPthRz7YR2ovGlxunob1qxQmLiZrqxGdP1lKv1hFLGISPNW/Uw1ThCMJaTDAaiZ7nab+vrSRgNHI7kXDKdz9sdScp6eYsU8PxsyKvzMSmaBwoeEzmJK2C6kdBMjV5fIHCFkezkPPOAe6QgGM85PDG6qpNfH5Pxm99aoOJLXl2MCVPzgDngmwe70cABzNvlV5eiPgtbwUgntwnQs9v9oQdyWz6E9o+DaqRIlCBSIATkXAiVxpMCITQvzIe9OAZPCF5biphtKgoeHMm7gOytnnWdlfpjH7oyp5IvCCRMNxUzzZRIab4+I0i0ZiTQvH88oBEb2Vo1NgH+w4FxHRvJyE3bknMFrtxoM92VFG1mPbw+TuaVxYiXF+Fo5/y3EsVCO2XQN+2/3lC8MGscvI4UXB4fllxYiVkKFdN1TckHpQWHchKBpp1ovjITUY8135yPGA4cdCdKqqXMjbXbH83UyMQu1RPynXivWpjyymLElVqCIwUzzZSpIbdz/qEWK240FdP1tBer1H/tFX3JGd/vBZjvR1zVesvw0cBZYwCRaGMAccb315yD1bEj+eETOTKOWZW80lEv7Gemd4vFcu+jteY/rpNo/eRUDlfU7lCNdo4Ugk8eCfi9i6urOl+eDvnguM3Gfj9xYFdGunrw8YwkTjVvLcecr8TESlOLzVvRneiu15fzykLE28sRM62UMNFkpObVxTZfvt4m44Av2VX520k5+r8reoI3lmMqoeZEwaEeK16djxkNnJ4VbjURZBxYaKWkqaYWmwfYapiglOJyPUUBw77oxWZoYDiQfPV6iy9Pt2glmplWyjvVhHasO1IqxUxTraljKXA4OehSiRStWNNKFJXOalC/vGU5VFyrJ5SXE4Z9iVCac8sxL8y2uVZPybgOh3KmPdVIkWojgSp6cssy15+fmUjwdiUhTjRLLRO3crEakyr4woUmi23F8YKkvJzw5mKMg6YeK755I+J6Pd0y5mCrceAJyHuC5TDlRktRDc35qYQmLmIl1L0yr1Rj/u3rdRbaipIH5UrCX1xp005U73gXq8mGmJycK7jRSLneTPElzLcU9cjkP5ltJbSSlJyAV+YjhnxBuRKzHCoczGSjOzbW1z9ONWeHXOqx4uX5iJXInNeZplpT7/6+2CxOJu8IamHKi/Mhbyy1uVyLqUaanCN5bjrsja2jeYcXZkN+41yd5dDER8y3jGX11UZCO1K8sxzx4nxIM1acHvT4xkzIy/Nh7zy9Oh/ziSMZKm3N9WbK1aZkOVIUHMlE1uWLV9v88RWTH6YRmwnhC7MhbyzGfOFCk8u1ZEOs0otzEaOBs29Z1NfHVS210t7Y2+zv8Yzk1fmYmVbaO/Zm52Dttce+Z3q3WCz3Pq8uxrzVlzDQEfAPTuXvYI12x6cm1048nr1u7X3vNw7sZKSrB5/IuRR9QSkwWvNKpHlqzOdQTu5Id72+HKNoN29SHyx6DAYunpSUAoflSOM5clflbyfl6P/uSl3xaMnlzLCHwgRcPznqshCmXKjGVMKUsYzmUM7heMFhKGOymY9mJIOBSyXSvH/E48MTAReqq7EZ1dhMAEYDiSMEl+oJRV8yNeSRaBPXcaizQtJfx09NZvjcgzkeG/FopppmCo+PeBtyOFyommDksyWXkaxkLOcymDFyIyHgo4cDnhnzGfBMzMmRvOT7j2UQsGWZ689PquHskEdba6QjGMoIShkTZ1PKmDZUY1OHUkZwsZ4y4AlGs2ZlY6uYg63Gwdlhj4msWcEqeYKJvJEfPT7icbTgcigne2W+XUkYygjaqWYhNCsYw1nJq0tx73hfm2lviMk5Oejy5JhHPVIIKXlgwOXIgMdwIBnwJONZl+N5zZlhj6VQcTjvMuCZ/p3Iyt7YWF//nCsZDByeGvUZ8OCN5RjPMddHf737+2KzOJljAy7DgcNgIJhpapSGTx7J4LuC2XbaG1ujWQcHcDASQs+VjOUcTpY8E+eTKpZizaAvOFnyGAwkjxQ9Ur16np4cdcl6RjZXjxT1VFP0JZ87keMzRzPMNGNqsZmoPVD0mMw7FDOSF+YjShnB28vJhlilvAcLYbpvWdTXx1Uthqo39jb7eyLn8uSoy3wr7R17s3PQf+2tJDuX0VksloPD719cGyvymaMZjtxF2dZvxqeOrI3NfHE+onIATTruZw6UTKsrk3hrWTDXbFP0JBrBlXrKoaykLjTXGinPX2+RcwWBIzdYy66XV/RbAWtgLCNRSoMQPDTgoIFoSXO84DCaMZKTt5ejnt3vzaxsu3KY/pwO62UyXZtST9KxPDUToowre9rxWIEvoC4EpwZdTgnB60vmIfZEweHZ6yGuNA+f0w1jHZp1YCWGSphyvZEQK/AcyaAnGc9Aoo2UK0415eWEw3mzglGPzYPQyaLHpyezfHpyrc3rRE7ysUMZThRd86ZXwXBGMpIVnADqkeLZ6ZCFVsrzN9rkXcFY1uGJEZ+lUHEk75B35Y4yYa+EZqWr2Uy4VEs6wh54p2qsgD807jGcdcm7gsAR+FJ0srqn3GiaJICHcg4rkbGSzbuCnCd5ZmytNOnbcyHjGfOQuNBSVKIUraEYSL73SNAbM+vtmZdCxWggWWprVsKUSCnCRFNLjGyulWou11I+etin4DnMt1Km6ykITdGVnB3x+aEHXF6YN5InB1iKjJWvl4InBY4QfHoy6FnYViPF1XrCa0sJ1cisjv3ZpTYIzYmix0MDDjeaZoUgkIKPTAS8tNBmqaUQUvDggMtUyWPAXbWhHQlW42QcDUuRYqaleKTodCbngrl2yo1GSi1WnCg4LLY1QifcaKVkO0HnDw24vLEcU/IEC6HmfaM+wxmJBK63NLPNmIyA+VBxsaZ5cS7ExUww3z8WcL2VUpBGZne9kaLRNBM4lBM4AupRymJoroXrDcXHJnzKoeJwVnCxqmkkmlTD0ZykmaxK/pZDxUsLIb99vgECJjs3cnMuWGPbvNU49DrX11wr5fXFmKwLrQQu11LeXYkoBYLAcXr2weNZB0dKPnPU3Ii/eK29aexWM4FnxgJKFc2pfcjhY7FY7h+U1hsmIz/+UPYO1ebWmMw7PFpyebuzupNqeH4m5HMP3FvtsGzNgZmM9GczdjABttOp4rERD6U0fz0TMZaVtFNFmEhWwpSjRcGz00aIfSgnGQlM5ugvXw17mcW7VsBPjfkUPBPTAIJunrK482a9lZh4i2Ff4qB5vWIe7gXmwakepWRcwdXa2uO1OnKYk4NuL4N1/+fdt6BSmHqUgk72647l6eMjHgO+MPIgDTnH5HAwcQzG5vZcNcaTsNBOEUISK8VsywS2ozVzLUUthqwLSiverMQ0Es1Dgy4CkzleCphpdDPAm7ZU2qZ+lVDxhQtNShnBZE5STTRfuNDk8ydz5q1ux6Y045qA/3PVGATUY0U71bRije8IrtSMPfJEVm7aB5shhOZaW6J0iitMW+qJmVSMZxwurKQcTuGBgst0I0VjNPdRqmlEGtD81bUWj5R8hn3BSqypRCkXqwkXVhKUVsw0UgTw9nLCQmgSLWYcgQaWw4Q3FmNmm2bMHM5J6h3b4DPDZiVjpiMf0trIbtopVMOU81WJJzS+o/nrGxEDnqCZKAqeJFXGSezbsxEZx8SQJClca6X4jqDkQ7sB1xsJDw+6vdiHaqR4czlGCBjw4LnpkO8uRRQ9ScYRvLEY8+x0i6fHAkYDQSWCX3m1RuDARMbBl8ZOuRYpzgx7jGRMv7dSvaEOQwEsR4r5RsKA65HvOKA1Es10U9FKNEXPoegJGomRLTYSM0aXI8VwRq6W2UwZ8AVSw7mVuJdrI+MK2onieguWQsWgL/AS+MZMxHhW8r4RH9+BKzVF1hVkXTqmBwCambYi6wjOrSQUPIkvTdKJVxZjHhvxer8dz06312So/+NL5ub+1KhP3jG2w5VQbblK170+PWnypyRKU64YF7Q3lyIcYcwSjg7I3thwxdrYj/XxY91+t/EhFotlK749F3GtsboKnnUEnz2W2WaPu5NPHgl6kxGAZ6ftZOR+4sCs5ffLJGYjwYmCg+9qrjYSPGGS/1yuJUxkXHxXIIQk68g11rKbySn6rYAncw6+Y6RarjDOVNVQMZE1DzDjWYfAEVxrKjwpGfAEtVhtaWXbL4fZTKrTLxnSmAfn9ZanGs3JokcpcKjFonfMxZbiWF7SiDVRIhjLOCTaPECXAmN324iNhW3QcYTSwLBvYmOmGzFRogmVSbaXceSmUpcL1XiDzWvJl5Qygq/NtHt168aWXKknRIlgMJCUMg5+x753rpWyFKb47s5kU10EwlS8kxQwThWONpPGAV+iO5PHuWZKrDTzTdV56DZ1WIlSAkdQCVNCBVoLHh50e+eja0d8suhyo5WQaBNW3Ug0WVcyWXB7cqDFttpgG/xoyeVqLSXvmhWMUEE90gwGDonS+I7Ekw5ZV3C5bsrPuqYfC57gxKDDi/NtRgJJWxmTgCiFgieJlWAk43Ak7/ZiH67WE4Qw7ZBCMtcykqmcZ/qhlqQ4wEwrJdLSGAcITaw1yG7uHVhoKd5ZSdbELq2vw+G8y1xbM5KVaIx1b9GTjGcdzi3HlHzz8zOccXGkIO8KbjRiAlew3NZMDXpM5hzqiaaVaEq+Q6zMpMN1QEjIOBIhJVIYp7Ks6zAbCfKuyeR+tZ7ycNEj0WYFT2kT+B8mmrNDPherCcXA5JCJOha541mnM3JE77ejEqaUfEnWE9Ri3fvhrMaKrCu3tW3uvz7nWwrfMeNPoAlTbV6QSEi0QGixpX3wbu2fLRaL5ffW2fn+4PEMBe/ee/T7vnVSra/YfCP3FffeiLxF+u1nm6mRBT1S9IhSaKSak0Wn85BnHgweKbkozRprWVjNHN216e23Ao614IMTPp97MMvxgslYPZ53+ORkho8fzjCWkazEmkiZ/A2uFCQd2eNmVrZdso7Jurydva7WYlPLU62N88+nJjM8kjcTqPGcy9SQy2MjPg8UHU4PuyTAgwMOxwsuEqNZf3DAJVKghbELHs06BK7JrF5wTRyMIwRPjnpoNtryduu33uYVoNjJJN2tWze2pBJpTg+7nBr0eGLIxZMmbiNK4UhO4out+2AzlIajWcWDA66RqjlGDpb3zOrFRw/5ZCQsRibmZjQrcaSxIn5ixGPQlwx2JleuFJwZNiti3fPRtSPOe0bLLzW0UkBrJvMOI4Fkoa16Y2a9bfDxosdnj2cYy5qxcTTvcGzANStrWnO84KKBhwacjq0suBKOF4z86VBGkncdhrMOQ4HkoaLDSNZM1o5nFR85FJB3V2OLbjQVede0w0iYNIWOVfJk3iFRXfcseKjootF4AlIFJwZWzwdojuSdNbFL6+uQdSWnBo28btCX+I7JIv6hMY/JgosvTdb1p8d9/v6pPGMZydVGymhG8o8fK/BA0SHWggeKDh897CMwOXTGsi7DgSROwe30vcRcq24ncWLeMastsdJ8/EiGD4z5HemlIOtIzo54nB5yeWbcZ8CTHMqblaHRrGTQN1bI3cuwKyXsju9maiYWoiMB6475rWyb+6/PrgW345hVlViZrO+OgI8e8hFia/vg3do/WyyWg02iNH94ae1k5EdP3JurCR855NP/GPFuLeVG8+63JrbsjAMj0+qXOOS6+QKUiR+ohIpZZSRJ0/UEBVx2Eh4ddim6knqqeWM5ph6bN5uNjp67i+cInpnwN7Xo7b4trS4rUm0CeS9UIr5+o0071YxnjH3ngG/edIeJ7kQ1rDLXSmkliudnIkYysqcp75doDAaCOIUzQz7VSHGtkfDdpZhSIHllIeK1pYg36oKzQ4IfPJSlFJgA+usNIys6XfKIlWa2lbLQSmmlmqxr3qxnHEk7UaQKlIShjOShosuJokMt0lxYSRAIwhSqcdrrq+v1mKfGjXzttaWEWEM7VQgE9djYvH5pumUslbXpw0eHPOJU8eJ8xExTUwokR3KSYuCw3DbyqCv1FCHgwYLL8YJkOLsxEK/b768sRrzTlAx55iG8mchOMLNG6RTHgfHA4X0jHo+P+Az4CXGKkf+kmsM5E1j/QFH2YoOaieplei94oicxKwWSxBcEQqKFJutALdGMZow0reDJ3rlZCk0ZJ4setchYJTcT8B3z4HqjIXAdMzGNUhMfkXNhOHA4knNYiTTz7YSL1QhfCq43PMazkkjJ3hipzGjaicnQfa5ipG9SwHKkaSzHzLcUjjBxKykpN7RJroeUnBhwyLtGMtXorHRcqqfkXMGRnCTRRkb3xWvtNXFNsGo3DfDmckQt1jw6tLb/sp7k4aLb2w7gWMEx19K662iw5yAmeXM54qvXQ67WU6I0ZamVMN82sRcFP2UoIxEKKp34nrwveP56i9cXI4qB5AePZxnwBNcaCYtthSdBInClZMwz6yGNWPHOiurZb0th7LrfrUEp6K6YmFXEXOcXtGvbvF4y1Y01+dLVNvVUsxKavCCtxMhBj+TN9Y+A642Ua42U6/UYKeHCSkw7Ne1/fNjjUM68IBkMBE+P2UmIxWLZnudvhMy3VwO9i77gbxy99yRaYFb7nxz1eHF+dfX56zMhP/ZQ7g7WyrJfHJi7Wb/EYcI3FqAvLRiXneFAshIqLtcSLtcT0Jp6pHm9owNfahmXoKJrLFvfWkoIpLipVKLfzvN4weS5+IsrLWabJklfqhTLYcpfXWtytWaygZcC83a5K8WYbSa8spBwetjD68RRvLForIP7j9tt32wz4Y2lmFqscYUg1bpnHTvhQzPR/PrbDf7kUnONjevVesoL82bSEqUm90grVmiluFQ1FqMuijBWLLRSphupecPc2X+hrTi3kvDc9Tb1SHMsL6lG8M0bEc1YMddOmaknVMOUt5YiFtspOUfy7dmI1xZNzEqcaq7VE74xG5HzTGzNcqh4ezkx39VMRnVHQyBM3MU3ZqM1FrX9/b7UShHaBLudqyTU45SZRsJyqGjGijRVnFuKaaeavCuZaSpGAkkzMfK0Zqx5dMil0ta9TO3d893N9N6//dGcC1qgNWSlkfRV24pnxnwqbbOC0n9uxrIOz063uVZPqMeKyZykGSvmO5KxMIV3VmJGM5Io1RzKOlTClHerCecrkYk9SMyk7C+vtrneMPt1x8jlJnxjJmY5NMkwtdK8uRzz6kJEojRDvsn/caFqJpMSbSRpkWLIM0YMCpObpuhLHMz4+858zHQjYSzrbLD5XS8l6mZa36r/diI56i9zMudQ9CRLYUqsFNebZtVMdlYx31iMQXRifmLFN2+0mWspjuRdHCn5g3ebfPVGm1psJljLoWY5NHlhNrP3vlhNqIQm3kQrRTNSLLfTXs6c7Symu7Emry/GDGck042Yy7WE2YYxGrjaSGnFRjo33UgpV2KiVLESacrLMd9ZiKiEJj7nCxeaPDfd7l0nW1lMWywWS5c/urx2VeRzD2QJnHs3xuyjE2tfVP31jE1+eL/g/OIv/uKdrsOuCMPwF29lv6wrGM5IVmLFXKWKky0QpsYdaigjacZGmiOFxJGCowUT+N1MNB87HJBqqCfGenWq5NBKNY40WvvHhjd/S/n6coTTCRS/1kipR5orjQSN0dMXfIkjjGVu4MKHJgKeHguMy1SsWA7NSsVDgy7HCy6DviRMTTyC0vDJvmDZbvteXoxoJOYt/cmSx+uLEVKCKwV+0mR0cIDrzYSVSPPEiE/GlQwHkoudCYfSMJRxOJxzGPQlrVSA0ASuxJEmjuNw3mEy5zKeM84/w4EkShUvL8YUPMFE1qGUcXho0GM5Som1eWBeiVPm2mbF5ZEhj6xr3rAf7sQFTOZdphsJjmNiWLQwb6EHO0n/xvOSyZyLFhAqky9jOGtWAibz7oZ+v9FMyTiCar1BkM1wtWEC6z0pKHgS1zErCEMZyYcmAhwJpYzTsWeGkYyRTD0zHoAwD67d83047zCckbQ6D+waOFZweWTIJe9JlBb4Es6O+Jwe9nhmPODdarLm3Ix0+j3VgrPDRsIjhUAKzUjWIZDGsrUYODw65HFy0KfgSa7UElJgLOfwgXEzNj0pkMJYNQ90AsLfWWwxOZJnNHDIeoLZliLjCAIpURiJYarN235HCBopTA15fOxQQKQ0rdTEXXzsUIbDecc4ZwkjdZoccDk75COE6CVyXIkVDxe93nW2HJps8Nv1X3e77a6j/mu3mYBCcyjvUl5OSDUUfCO9yzqQ9cwq3mdPDBi3LmE+e2I04EhOcrmesNBWnB7ykcLELw34gtlmSt4z/aERfGgioOgLXl2MOF5wOJo3krXlSCMFPDzo8uFDAbVIE2s4O+zx4UPBmvq/vmySLOZcSTXWNGONI43sMeMKjhaMzLH7cKA1DGUdWgnEnXOacR3CVDMQSNqpZihwmMy7vf7uH/dLS0uMjIzcys/jGjKZzP+450LucW71PnOvsl9j517kfm270pp/+vUK9b6s6//86SIPF/f/N+N2ESv43b4YmGai+enThVsq615r+35yN7R9/X3mwMi0ulQjxaWmYClOcAScKXkUPMHbyzGHMpK50AQNDweC0UDy4mLMeNbEk1xrJNRjTb1jy3s4Z8p7ecEkh1tv0bsSmuRkQM/2NFVGx9no/ECEqabgCzSS0cDhpYWQ8nJCM9UUXMF8y7zFv1ozNqUFT/DEsEesTbn9mbxPFj0O51weGzJBttfqMd9dihkPBEpDdzFTArWof+lWciTvUo1N+QVXIISRoYQqZiTj82DR5fFh89b39aUY1bH17cqOYmUseQ8POlytJXxrLiFNTUb7sYzDJ49m+eSRDG9WEnIOLIZwrZayGKa8vWzkKJfGfdAwkjGSnp5lstZ8aTrEF4JBXzCScTufQyVSPZ1+V5rVtc9daGsOZQVawOmSx2xTczgreK2S4Hayzh/KClrJqkXqyaLHdMMkP6zEiiFfcmbYZ2rI5ekxkwm7a+fbPd9FXzDor0poPnF4rT1zl1qsSZR52365lqK14noz7dkHd/GkoBEDAk4MOIznXEq+CaY/nHOYaTnkXUHWldQS8zA/HJjJciMx59CXgvkYnGpC1pWdJIxmO4VZ4St4gkaiSFJ4fNQj5wpaiWa6kwDwh09kuLASc24l4nJdk3FMXhelWRO707UKfrdqzmX3GuiXEpVC2euPC1WTcPHdWkx5OelZ41b6rJK7fTvgm1ibfgvdAc9BAo4UHCsIRrIeI4FguqF4MC94Z7HNJw5nOF+JjXNWpLlUixGYlwtLrZSXFyKu1lOKHpQChyv1lKlBExPTjDU3GgnnKzFfnw05MeAwWfB4YMDlB44HDLiwGOqe5W4//VnWz63ELLcV7VTx8kJMPTZuX2buIU0Qu6NZaGluNExSylIgEUjMENe0U9X7HQmVZq6VcizvcLWecKNpruGb2VtbLJaDx8sLMTOt1ft8wRV87+F72/r7eyZ8pKAXz1deSZhvpYxtItW23FscmMlIvz1nIKHkCy5UUmIV8eRoQCAFVxqpccbxjVb/jYqx4p1rpVyspWQd0bPldYSgPah4p5r0tP79Fr2VdoQj6cWpCEyW7BTjQNVOjBwj5wnqEaiskU8FLhQ9wVwzYToVhEpxo2UCxqdKLnFqbEcfKDo9q+J+m1tHsqa+44GkEmsCpRjpPK8oYMBf+/DiSRjwJI6AqBOs27UljlNNn7QfV0KYGDegN5fNA1/SadM3bpjYENVxjApTTaSMO5Dv+OQcwVJbsRwpGrFitp0yHDh4mNidK9WEpyf8NXVrpZqJnKlHNz4D1ur0+62bu/a5c80U33HJShOQ7Tnw1opxT/MlaAEvLSQ8MerRSjVCaP74UpNvzUXkpKAdKy62NUthi4yT42rNBMvl3VUb47lmQqRMPMOTox5xqre0g0ZqFpspILjeTDmcd2l0JoV/da3F0YJLpZ1QS2C+mXK44HKjYeI5XpgLeaTko5WmGSvqoeD4gLH4XQoVGoGD6NlHJ0rTSgSzDbXldoGARmQ+u1ZPqXfkRkfzJoj7K9Mh355tU/Al41mzivWNmYiiJ3h81JyjrlVwK9U0k5RmIjdYOwNrxupcK+VPL7YJXDicdUBovjUb8dXrbR4b8Zhvql7frkRGmndmyCPvwLdmI8oVI+Mb9M24W2ynNGNBxoHlWDDkmno1Y7NqkXNNPp8w1cy1EkIFN+optSilGplxV0vg3VrC8YJDM4YvvNNgLGPc8aoxrCzG+FJQizQPFp2epfH635j+diqleXE+JHCMu1cz1lyumUndeBYaHtyoJ1yqpfjSPCy0FSy2EkYzZvWuFhl5X4qxt75aT9HE5F0zvrqSrW4/WywWC8CfXVkr0fr00eCelmiBeXH6xLDHK4t9cSOzEX/7wXszKN+yyoF5ndZvz5lx4HjBZSQnWGwpLtdicq55a+pJEyQcaaNFf2zE40LVBEz32/I+NOjyyqKxJ42U+v/Ze7NYS6/zTO9Zwz/t+cynRlaxiiwOEklJ1Gi7bVlttUc4AyAgQSPOVQL0RYBcJBe5zH0ugyRoIEGjExgxMjQQ2227YbttTTQlUhOnEqtYrLnOvM8e/2ENufj2OayiJKMDO7bJOh9ACFU63Hv//7/24frW977P+xOI3nYiOM+HdfGtRKERcxVi2QAAIABJREFUOc20Fj9GCJHcalIDdQxUITJuIt1Es1Jo5o1kb2QWtuZyOgyKB9PwU1G/kfjI532iZ5k5MW/vlOIHSJXm8uLvj/T6g8xwuW9JjSCJH8YSrxeaTCvmTWTuAqmWz1uFSK4lO+LuNHCpnzLxkdnC/G6NIFd7mWbUeG6PazIr5uG2VYxdoDAiU1te4I9XCs29qf8JL8HPb+aPIIA/rNN/GN18hM9da2luj2sSHTmsA1ZBCEK0qjxkWqYutYdpI+bl64cNK6mmjpF2Ks/ABcXVw+YYu3yE8x2kmomTZzbIFHemnpb92TjoURVAiYSqnYj/op9ZDutAZhTvjxxaaaYNnOlIEKPSkXcPG7pW8MN3p4EXVjNWWoq7M0eIkUEKt8aOqQucbdvj53GlG/7an9upAr3MstYyjOrA3tzTSmBYR57oJWyXMrVoYkAraBloJbLRL114BBW8Mwuc66Y/Fe3809LHj9Z6kciEpw6B2vNIGvrEhUfS2o9+zgX5Tlzpp9Qe6hCY1NLkDavAJ/ue2xPH5UHCzAVKB4WJTF1gWkfOFJYyBDIDiYKtmWc1kwODu4u117KarblggQujSBNkuqLiMdL4p/2Oefg6j15/3AS6iwbRx0AZgoB+o8jDeqlikBkcYBBQwfY8Mm4CiRLfzbiG9QXqenfmiVFxvpv8O+GtT+qkTurxqz+89Sj69tfPfzw27D+3+WHfSPX39ElO6m+zHptm5MN4znaieWEpZaOlOawjKPjquZzL/YRxE8mN4tfO56wXljNtkcU8jOVdTjX7lWxoXOAnEL2FEULUEYpz1LAgNiVc7BicgtxqlnLDL51OCVGhkdeZ+Ui6yPZwRNZyTct8gJd9aTU5fo+H6+g9H/68p9qWr10SbOr9WnwWv/NMm9+80HoEEfrlMzm/daHF5zZS1luPYon/8+e7fG4jZeYjMw+f30j5nSsdmQ6FiNWK9ZZhJVesFRaiTFdSpTjTtpxtSXPQspJCf6FnWSs0iVY82RWJklGKJig+vZKwkpmfwJde7NlHEMAzL5Kho5C5h9HNR/jc9VzTsoZlC59dT2lZzYsrImlZLQydRPPMUoJW8h4hipSqlYh8ziqZAiklJu4j7PIRzhc+ePZHzx1+Ng567uFK39LESIwi13sYH7xTBnILy5lMVCKKp3sJ01pSKpoQWW8ZzrZk7a7k4ifIjFpgmi1Gcfw8NjL+2p+rg6zJ5wbyfEZNpGMEBX10km8VDFJ5PqWHthGPzuV+8ggqeL1lWE5/8jtwWMVHns3R/Tha60flgkzSjr5TR383a2RzfoTQPfp31nLN2a7hEyspLa3xKLpW8V+91OPpNtyfBc53DF+71CbR0uAr4HTH8tySBRQuKE63LK1EmoeLXctqYThsAoMEMqNZzxffJ6PZKUU6eYQ0/mm/Yx6+zojifMewnEpT3koMF7tGPDtRDkS0EY/PRsvQTQ0tq+laRTuBJxcZPK1E84/P5XxmTbw8EHluOaGXqOPv/V+Htz6pkzqpx6tujBxvPxQQaBR89SNK0fpw/dzmo1Pgk2bk41GPjUzr4aTvo6qC4FY324ZuInSjzYe0hzMXSIyEw31vr+IHOw1bc88bueGz6xnLmZywOx/ZrwOv7YiHwhP5t3dm7FaB9cLy3FJCYRVVUPRTTTcx5FazV8mk4y/uVexXAbeQQwUk+yRRkvC+kiecbos0ZNZ4/s/3Km5OhPz1wkrKlUFyjPp9MG/41v2aW4sT60TL1GQ501woBFX73rhBjdWxx+HolPfaqCFGxS+eyR7RoR9UgV6lOdU2TJrAqA7sVp5nBgn5ohl7f6H1j1GmBJ1E4RYb7spDL5MpwzNLCWfaltxA6SSUblp7nI+stQw3J557M8//8IZjr/KsZobPrqf8k3MFF3uWr5wp+MoZjj/XkT7//szhoqFlZPKyPRfqUTfTXGpHXtrMuTFyHFSRJweajtVMF5SvpfQDPHI3UcwamSq5KOGRMUoujQQ/Sor3kVzMLsIgZS1Jwvm9qWO/juyWkpY+bTwzq1jONFYrnuxaZk6mApUPEBW7ZWA11wwyS+Uaro/lpN85TWbFqLdSaNpWUMLWCN71+aXkeJ2CkJYOysC37tfcPtCc9jXPLFt+6VTB1syxXQbeHzneHTqGlUicnuwmGCOGxzf3G5JFqnmIERdg7iKFlQY9MbKeznbMIyhfrRz7VWTUeIaVNM11EHSwIvJ2FB9LJxEowXwhR7o9doxdoGxgqdCcahmuHoox/c7YcdgE3jqQtbw189weOyof6GaWVQwbLdnsO+BiTxq9rQrec44/ulkzC5EQIsu5oW01Uxf5/l7D9tzJs1x4Z860DZf6kv1TaJF1TV3gtd2G9kK++FRfmuntMvAvfzzh7f2GYS1+rS9uZHQS/UhCeidRRK1pJbDRMtRO7rda0L4OKo9VkbkXgMBaLgnwO6XifKL4p0+32ZkHXJTXGqSaOxPFzMPtiftJxPejqoyTOqmTekzrD28/OhX54sbHBwX+xY0MxSLXGXjrQAiZH5fre1zrsWlGLvcSbo9FvlF62J173ho6zrYNzy8llC7w/Z0G1mAjl03FtIHLLcNf3p3yZ3cqBolis1DcnXr+4NaM//hym3szz04VhN60MLjfmzbUUbGea0II/MmdklOF4lI/4aAKPJh56hDYmkdyIvMImYKhkxPzeQPtBCrliRbe3pfsim6mZaNbBs61DTszz/dCxajyPL+ScuOw4ZWtmiJRgtOdB1BwqWO4PVEsY3hh7tiaB0D9TI/D/EM69O9u14QYjn0SR56AWSMY2YMqHFOJNDCqI00QcpMHbo4Dv9DNeX5J3m9Yidm/9nBn6mgZJVkOk4bv7QTOtS2lk2C4O5MGiDyYeX7nSoeLCxLIh/X5Pmi+fb8+9tzcmzoar+ilcKeEH1+bca5r2C0bHsw8e7OalcJAhGeXUr67XXO5b7nUT449I7uVp/SKfgZX+gkLzzttC++NPGWIdKymDpFhFbnU03xvtyaiaYJn3ATmTaCdat468HxpM2XmIplVQvqyhqtDx5mOYWvmOdM2/HC3ookwrSOrheLG2NFOREJ4zkqz84FHxR7L2F5emP2PPS9Gkyg5rX9nv2GQGLZmgY22rN/DOmIQFPTbB461XKYQTYBVI5Og+zNPFSLtRKFj5LAWDO6vns8fQUp/d7sm03B12JBbhfORUSNN0S+cSrkxFsjBc4vnf3sSeP+wYR5kQmLVIndjEvBepj+ZhsMm4Hxgx3mqsGhmLLgY+f5Og1WKjlG8e+gZ5IrPpAmvbtW8um0Y64oHc/leugDDxlEsqHIhglFC2rpx2PBUP2G3DNybej65LJOyncqTakEfj6pAK4GVNOXbWzUXeoZXHtQM60C+aPb/+FbJJ5ct6y3LZkumFZmG3VmgnSrGVeDmxDGsPK1EEZXm7f2ajVxzfeS5R0M/04yjNOm/crbg9e3m2FczLD3felCxkmk2W/oY33yxbzEoXl5K2B3+nf06PamTOql/wPVhv8jHRaIFEv763JLlzQOZ/ETgla2KX/sYXePjWI8V2nezZfBEbuyN2Y85F/uCXO2nmk6i6SawU4ZHkL13Zo4/uT2nYxSZlU1EJxET8NRHLvVlAzLzIqUZ1ZJv0E0Na4WVsLtUEYAQReIxqgOjGk63LAdNIDWKTmowiuN0Zq0VG4WlmxlWMkMVIlqLLOps27JRiHxjusCAdhPF9UNHO5Wj+p1SdP5aiezk2UFCdBU7LuFSz5JbdYzTvTFqmHt4omt/AtW6f9RozSQcsZPo45Tocx3D7anQmlCC9E2NnE7UUWRohdU8u5zy3HLCpV5CokVLf3sqTWFuFD5KMvqkkTyHZuHr6KYGYyTxu58Y5j7w4oo0SA9jk9Xic+2WnlEjKe65VTw9kMDFqzszziy3KaxQuq4OhWxUJIpfPd/iQldQqVWIfHEjx+jI/anHIdjhz6znXBrYY+zywzjfzZbhyb5lo2W4PhKMay/VrOUarcR8nxrF5zdSfITl3GA1nGkb9kuhJ53vWp5fTimsyItijFxZShnVkX5q2GwZznYtG4U0Pu1E8dyyvN7DSNzCKr69VVE5SBNN0sw4u9whAjfHjl88k3P1oCHXmvXCEFAc1BJ0uF8FnuwlbLRFoueQwMuzbbPwj8j05cXVlE+uJDy3lB5/r5ZzzZsHDRFZO1UQqdnFruHuLHC2bRhkQvPKrWJcexKrSJSiDgprRC6VW0XLKtqJZu7Eu3XkbUmUIrWK1cJysSuN4X4VCEpxvmN5dmC5Owu4EHnvsGQcDEuppg6C0m0bTRki7USmS8po1nJDO9O0rOYzaymtRHFYR1Zyw2pucEECSK0WFHcvVay0DLvzwLCMdFNFajRRwSCXqcuVJZF9HVSRgzrw/HJKP1V8Z6fGauilhm6q2WiZBUjC8PJaxv2ZZx5gNTf8h0+2WcrleltWpjfvjRy5VpzvWV5cTn8q4vsE7fu3Vydo38enPm7Xvl96/uu/OuRh4eZ/98UBg58yOfioXvs7B47Xdz/wyT3RNfzi6f9vMrSP6rX/bdQ/hGt/rNG+S5nmK2cK+oeBV6NF86jcYb0wGC3J0H98e8b//PaUm2NJKb/cM/RzCy4wdZGD2rO/J5qvSz0LMbJRGG6OHX6RoG60+D8GiRhwH8w8uY7slXJibnOReWkf0SoydoFJA90UrFI8NbD4KPr4vSpwuWe5M3UYInengdJHfIRTLcupluWbDyqeaBveGHu2Zh6twKjA2EX2S8/WTHGtqqh8YDkzeMQIfHMRuHhUozrwzkHNK9sNtycOkPyLF1cSznUSdmaeHx1I2NBOGXhpJaEOYv49KANP9S0vr2f8xvmCV7crulYxcnB34vj2VsX7Y5nOXBlIhkcnEcLS/3HNs1878Q+0BTE7rAO1g725Z1inPNEp+aNbc761VTFIFV/YzPnSZk4vURzWgfeGDffm0ioMspqVTHN9pCh3K1CaL21mnOlYWhbeHnp+99qUC13LF9ZTDurAOwcNW7PAcysJP7+ZPzKJOZKE9TPFSysp740bvrcIAIxKUfrAp1dSZk6QwSu5JXbgsIlc6lr2qni8tt4Zeu7OHBu5ZqcUA/t6rglRrvvtg4bdeSA1sFpYlnPNr5wteGElXVCxIj8eisF8XEc+tSoNyaSJPNkz7FSBBxH2K0+m4f2x5+v3Sl7ZrlnLFKfaCUZD4+GpnuEH+/DckkUrRcSyW0YOSsdeFfiF0wlfPVfQSyTo8/2J/wmkdDfRnG3D1EkDtpxqhnXkR/sNWgmQYeYiMxe5M/U8mHrShVE9t+J12p0GzrYMZzvieRJPhOL6xPPpFWmUJ06yz19YTrg7C4tEdGlA788cy5mm9IpDFzGZyOpSHbFGMS+BEChSRfAB1wQcsK00n1lNSTTcmjpGVeDeLHC2rXlxNWEtl5yQ3bnnhzs1bx84xo1k2FgNpUeklyZyuW/59GrG67sVr23XtBLFxV7C2bZlJYM392XalBvFeqHZLkXe90Qv4QsbCaWHayPHrYnjYleQ4p3EUHoxsk8XvqSduecHuw2jJnJr7CmsYntX83ycPLJuT+qkTurxqj++U/GQZZHnliwXuh+v3wefW0/55+9Mj//8V9sn4Ycf9fp4rdB/hzqoAm+MNXkPNIIGfWu/4bnlBKsiE+f5F+9UbJeOeSMG6rmLvDd2tEvoJrA9D9QLg3PpIq9t1yitKGygnWh2S0nULr0kX89CpIkiaZo7OcG+Nw38aL8h0WKe35p5ar8wrUcA8VNstIyY0ltG/j8Pd+aedqKwStLF700dL64mnGkZbk49d6YNC8gVo0XS9P2ZZ+agZQLTJnJrXLNaGJ4bJETg3jQwasQg8d2dmjf3a26OHJUXOUuIkVceVLydNUQFB6VoNJ3z/Pk9jw9wsWdo28hbBzWHTeClFZlMjJrI3EV+/1bFpBZNfccqrg6l8bjYS3hjv8KYSGFgHOCtoUhjQkQwr3OPUhX/7Xdq+plmPZfN7b+5XTJpIp9cTvjuTs14sVEXnHBgO1XMGsVeGekkkfszz6vbFQdVYCUX4/jNkefacEKRaL6wkXGmpRm5yO9dm/G1yy0Gmf6paNpAPCZnRRQ+BL6/Wy/oaAkr2Qdekrn/YG0dNp5CKw4rz41hw8We5VzX8hf3G+6Ma0aNgBbmC8rXpHH4oHljr+b22JFoJdkmiQYV+dFew7AKfPlMTidRvLnvaCWKcaPQPnJn7NkvPe8dagapYtgEbi3kRksZDBuwOrJXwVou072DyuOiTDge/o7MG8+9qWej+EDS9+d3S66P3PFnCj7yza2Kcx3LWi4J7D/cqznVMuzOHXMvzfxAW3bmQn5TKAorPqOdeaDTteLvUpG1TDNrILWC6VVRcX/umfnImpJJ3cxH5g4mGsogVLwAuCBBia1UricgzdusgURFehkYLbJLq0VKOW0ikci7Q0dmNPenHqMFanBj5Ci9pw7SdM0a+Z3QSQITB396p2RaB6oAg1TjY+TaUFj4u6Vcj9UiOxzXQSZFLtL4wKtbElj6ZFcOR97adxLEmRWsLhDdu5Vnr6y4dljRMppURf7kdskggxdS8RYdrduThuSkTurxq4+zROuoPvshlPn3dhuaBer/pD6a9dg5fq6NGgoTudxPKIMYlHMjORjTBh5MBTsK0EmlCTjVVuxXMG0cd6cOJyEaXOqn9DItGOAQSJSgPAujiSi2p46ehf1S0pefW0qISh3r8JUCj9CXRMcuhujaCUZ1VMmGJTXwWxdaDDJJKm9CpPFCGGpbkdMoFL91ocW7Q0diZFM4asAH6KWwU0ZSBU/2Uu7PZZOTG7g98azmYo5/dyiTkN3SszMXr8NGW6RXqREk7b2ZY3vqWco0uTVkiUx3jJKNcy+zpFovgt5E4z4sI/emHudEVoTSPLOUspxpbk0df7VdkijFambIrZGU6gizRv63lWjaieagFClVYhSrhTmW9bxzUPGnd+Q10kRkUi6KHGxYB1oGxi6wlGveHzWSfeJEjpNowdXenQSaEBmkGq3lxH6QK77xoPyZaNqtUja4/UwzyDRFYiSsMMLtsXgKZk1kJdePrK3lTC9CLTWtVKRS96eC3x3XQu/SShqSo2zBmYOpk/C+0QIjfYTFHSxyVq6NGjbbgiXemXkMoCJszQOnO/LzLSuIZlRga9qwWlhmTeTTqxl3JzV7VeDBAr1cGM35TvLId+TayHOpbx9BSg8rT27kWVVeGgGQBvLKwLI9d6gozZhWGqs0G20LSNbMtBFpmlXyrNcKTYiBYS345l84lbJXB/bmgbVMk1nF7bHnUtdytm2YukDl4Nkly71pQ6EVvVQzd0K/AxhVsJRJs994ub/ayH3dbCXsVxIqWvuI1jKNTAy8N244rMRjdVhHrNZstixqsd7t4js8beDMQuL2+gL5fb5rYPEcDbBbhmNqnA/SoHdSTaI1a4Vhuwy0LUycZyk1TFzAahhWnn6mjw8G3jqoaFuNNZo6KpZzhVWaW6V+ZN2e1Emd1ONVpYv82d1H6VK/fu7jQdF6uJ7oGDaKD7avMyfwlZP66NZj14wcVpFcf4B/TYz4HyofeXk9PcaO+iCbo8wonh1kLGWysZs0sJJprgwSTrel6VjNNDGK3rudaH7pTIvnBhZjFFprvno256l+ylouEpT13DJIDWuZIjeatcLSTxWDTKRizy6L7txazemO5XeudHhpNeXLZ3Ke6BnWCyP+g0LziZWUL21mhAgvraa8tCpp1FmiWMrgVFtJ6JqBi51IP9PkWnO+bY4RtC+vZ3xpQ3ToR6nOrUROXQujWMmFAmW1wgcIqIWsTaOUPkbgTp14CK4sWSySu7FcGL52uUUdIvMgSNwzbcNSpnhmkNAxiv1KNlnPLqf8xhMtBqmhEEUc7cX7PL+UUPkFEjbKc1kvzHEa9n4VON81rGeatpXmKddK/AJWMKnLqchiDHChK+St0strpYlCfYiO2rOKrVn4mWjaWROP14nV8s9aITk2LWtoWcWpBQXt4bWVLk7ZtYLN3OACHFSyYTUaBOimIMpGtpVA6eXDdRZ5FUf4WxCUbhMEoduxhl87lxGIzIIEPZ5qaVYyw/mONHurhaVrFE0UrPLXLrf41GrChW5Kx8o9Wys0v3mh4BdOZY98R860DRsfCvxrglDbjr5PUx95qieY3MwoVgvN5b5hVAuBbLNleGEpYS1PyK3GB1ljT/QSfvOJgvVcM24k4+eTKwmrheVXzmVcWbIM68hqrvnV8zlPdA0OxaVewlN9Sy8RVPbPLXteWs3YaBkSrVjJxPj+3CDhbMdKk4dAI3KjWUo0idJYRHJ1vi3kreXMUHlop4pcy6TjVEsaz6VMYxf47QhstLT4aKKEKGZG8OEXu5bCKBoE6/zUQHxThdVstCwdo3iyZ+kksm7bRjGsoZsprvQthRakdz8z/MrZglzDsBLc8Zm2oQmR1qJpXWRyHq/bkzqpk3q86i/vV0zdB/8hO9WSMN6PWyml+Ozao9ORV0+kWh/peuzm+P1MsRfEF/G93Yof7jXMXORUy/D1+yV3Zp53hzXjWjbImVbMnEg9CiuSjHaqSLXIWXqZIkTF2cTyiZUEq9UCt5ox92LEPqwiIQri9qASLK6P0M0MPSUbyd0yoqKim2o+tZqxWYhkZZBpro8cuwvMbdsqmoc2zTMXeGW7YlgGfnzYkGnFFzYLTrcMb+3X7JaBm1NP5QKbaWSQG3ZKz92px2hBy149aCi9mKmfWUp4a7/mBzsVN8aeMi42blo2xr1E0VkYg3dLT+0kLTvViqVcQZSGRhqHyNfvldyeBn64V3NYeTFkt8VfM3GBVqI5ayNVgPfHjsyINCjEwFoBT/XFqL1Tyvs0Ue7lzlyoUrWH823L5b5l7iNGwX4T2JlJunYEMPC0En9D1yrujAN3Z4EHZaSXaFYLTa7FMHxU0ybwxkHD1szz5n5NQDbcuRHfhEKmPM5FHszERzRtAlrLPUgNvHNoyJRCa8Xe3PHe2OEirGaa1OjjKcJSJk1q5SLtxKGioHvrIES3eQW5jcx9wCjNrZlbyIXEkL2Way72Df0s5f7U89pOQxWkuWlZzdw73jt0zL34pj6xnDKsPD6KZO7dQ4fVcL6reXqQUiQ14zrwg72aaSPTqNoHrFK8O3JYBWc7hlkTuXbYcHfqBV6gRQ54Y+S4PxOJ35/ekalfx0ozG0LER8k8SY1gdZcLzZO9hH6uOaw9+1Vgo6X59Kqgg6+NGsaNor3A8EYkD8YoxbNLH+RtbM0c23NDM4YvbmZ87XKbO5OGcRN5datarJ9AJ5HNu4tQ+sCPDmomTWTkZIr0/liznBr6uebZgYRP7teRu1O5LpHkwSCFfmZoJ4rzXcudiePmyKF15Ad7jtNtw7SRCZoPMnF5dkk8KA9mjreGjnuzwF/cK7k9rnkwD7IeUsuplkz3HswdD8rAYR241LNMFg3wjbGniZLVc9gEShexTnFj5MisYqP12J0zndRJPfb1YYnWr50r0Er9jJ/+aNfn11N+/6Fgx1d3av6zv8fPc1J/s3rsmpHLvYRXa8Wbd0p+PKxFbhLh+qhht/T0Us2wknRp74UKNaqhn0kiez+RzduFtqGJistGYSKsF4ZhFY9xqw8WJ5OFiaxkcjr7v70751zHcCZXvD30XB8FLnYMqEjlABWZ1Z53DipujIS89dSgeMSnMHOBnZlQm+6PHW/vVyil+PLpnJYBqzXf36mZLyVMGkkLT4HVluXqgablS2lCAnR05MZImrFLPctaYbgzcby537BVeuZOTr1dgEqL3KtlJD2+9JpeIlOmGGAaIv1UvAa7czEW784Dd2cVOkLtwsLc7CFG3h3WrBWaZwcpd6ee+zPP6ZZmrwwczD1NhH6quDpsGGSKGOFS1/L+xLE19ZxqCYb2sIlc6Fl+8XTOH75fcmvacHMk+n0fIFVw6OAb90oeTDyZ1fgQKT0clo7aKYa1op8quollWAdMjLy+13Bz7DjbscQYeX23oZ8ozrQ1rcTw/thxoWs4qD2jOjKuA00UWZAFSUyfBwyR/Vq8DrWTDfB7VWAlDxgtG/WWgbUs4ZbznGlbtmaeaRM4LEUClABtAz8+qEmNZj03PJh5EgPj2tN4w9xFPjHwvL4tMq7VTPPdfcXOg5LMgouK7YljLUu4Mxa54cvrGbszh0NxWAbWW4aDqsbHyM7cy3toSQovvUcpIdKB4o9v1pLk3pEA0Huzhn/+dsPTA8v21HF3KqSnPAHnYCdGlvMINCik6TjfseRGUzWBWxNHMlPEpYRcS+bPEXK6beHBVFDK748cF3oSrLk990yayEurCzT3ruPZ5YS3JuoYfbvW0tw/8KxkhluTBo2EPY4W97adiIwyBCgdJEXEVdK8b8+g6iWcb0sTMPeBUSWwCfFRwf2p51JPvDAHFQxyWMmkof/xUEJHd+fir2q8UM3eHTbs1wEdYdYEfjAtmTYiHasDpNrxl3cd8wCF1jw9SGh84PdvzskXJLbdMvD+qEETuDMVCeKTeeCgDhyMIv/sE52/h9+uJ3VSJ/X3VSFG/vXtD6euf/wkWkf1Yd/IiYn9o12PXTOylGl6JvKDmScxkt2RWuhGzfbcM3Oez69nfH+3Zq/2VJVsWAapBAei5JT6sIk8NbBoBV86lXOqrVEomiAn5oPsSK6zCA6sIy+sJhxUkTLCaiGI11ET6KSaS/0ETWTScIy8Pd2xxyGMRz6FQycIViF6OUqvONs2NBEKq7nUl/Tmm2OH0YrLfTmJjcBoEplGxanM8HTfclCHRbgddDPNZmG4N3HMXGSzbXFRNlhGidxntTCc64g/xflIFSPr7YSnlqRZmjtJun56KeVsy/DuYUOijlLNNU8XmvtTx9Yil2S1sBRW83Rfc6YTeWO/xipYb1tWC00MkgNRB3huKeHFlYz3DmveGjaMFn6ZXz2lmsQ4AAAgAElEQVSX86nVhCJRfOl0ylvDmjoGUg2tTJEaqGuOaV+fWDU8vZRyUHp2q0DpFecKzRdPSXjkuI68tiMTjKcHKcuZ4u2Dhs1C00TFyCn6ueIfnc65Nmw4006og0wBMsQr0040tZcsi1Et2TFNhEGhmdaBxMDEw2ZiONvWrLUEF/xbF8Ro+FcPav749pTMigdpuTCs54Zh7cktKC2yoLmXBtkaxUtrKX9wa86LqynnleZ7uw0raWSkFEbD51czduaenUpkPV84lS6ejSSumwUooA6BiHgmHsw9VYBURcwCB6yVwkd59gFJib+ynDDfjZQucHVB+Opm4qMIEawRPWiiFTMHyxmsFNJAPbOUYIhsV56WlTyVz5zK6CWK1ycVEZHStazicBbop5rSR063JFXeKnjzoKGbKF5cS9gsDHU7QCLyprmLfHo9YWceGOSaH+zUrGSGOnicl3uZAWkm61wjPphApJ0q2laRWNhUmlmtOdOCsZNmxCjFci6N3riB813DZ1YzWha+fr9iey4TyGcGKU8NEkrneXPf0YTIciZekTrCfi0TkV6mKYxAAQ6bQKHh0kDCR+9MHamGIlFcHiScayLvHDbszuHpQcKFXsLBcE4v1Xx2LaGJJ4nsJ3VSj1O9vtssMsSkuoniF05lf4+f6P/femlFCIjN4pJvT+RQ81TL/PX/4kn9g6zHrhkBiEoSjU+1FIe1hBV2FtSs0kUS5Zj5SLpIj/YetmaSPB7gWFf/c5sZa4Xh37/YAkSC9fpuxXe2Gn582PDcUsIzSym9RImnoW1YLRQXO5pXtmpmLtLUHq0UlQs4JRMAo+H+XFCs4zry0or4DWofuDt2xI6lWBiM94Pj7kRO8QsrKeEtA63U8JXNlKXMcG/a8M7QsVsr5k4kNblV5E42Y+8e1ry53/BndwT7e2PU4AIsqL4UiWSGhCgUoNzAUiZp6FcGCV0Lf3q34itnMr6zU8tGcrdmfx6Ii6wNg0wjhEIEug5860HF67riXNuw0bEoZMI0qgM3x4EXVhL+o40Mj+Lzi1OQEOMCg5oxqiVM77Wdhu/tTNhbJLFXXja/hwsvio6QK6h0YHvq2SkF/RsjuCiZL6OF3+JCR/P/vD/nh7s1My8TiflC8tQgPoP7U8MzA8NOGfntzZTMKrZmmtsTx4NJxE09EfF+zAPYKNdtY2DoYCmVic0XNlPOtC3rueb+LHC6bbjcS/jtCy0Kq7g5biQAsREa26gONA7mVnG2kNybBCgD7M88r2xVjJtAYTXjOlIoCFYzdZ65j6wW4qFYy6UpuDGSvJU6Cjq5CVDHQNUIEtfFyCCTJnxUS95MjIqowDvQSqRp92cCPMi0EK06RjFF8ksqDzUyHWlcxCuYNp5BJiGGWzPHfuXZnkeuDAxqQUMZ1YHrI8d8sfFvW83NiaOfKA5qxbyOx3jpgBCovnJGTgGnDrZHjr0ykGnF8yspl/uSY7JbBrqZSOdKJyb5MkpTlxsIKhKUACcmLhAC3Bh5UiNeocJIQ2CUeEN2Z4CCdmKwSoyUt8ee90bSdHRSw+mWpm2hZQxVaJg2gVkZJaMkRKxSBCWSudXccFAFZk7kbEbB6bagfRsvCOMfDx1rhRjkGx9ZLwyfWk1RNvDc+YIYI3vVSTNyUif1ONW//pBE6ytncjLz8ZRoAeRW4ga+u/OBcf3V7ZrfvvDxo4c9DvVYNiNdA9Yr3hs7CTy0smEeVo6ZlxMFHyRFeraQT4DIbLQRc3vHRr6/W/NkT1LVAf78bsntiaOfCEL17X1JZH95PWN5gebMDNwYC5Fr3Hg0kZ25wyjR1Gvg3YNIO4Gz7ZTSC752s6V5MJXguUSLefrWpKHygdKLZyPGSBMXG/YO3Jp4vvmgEo19FZh5CES2p46yiezWnsYFxg0sZYq9ecOtaWBSyWl2BCon+ODKBxoPiVKc6hg6ieLa0DGuA88tJ4uTesHY7peSyq4XFKGpC+yWMMgD8yYyr2GuoZ8IMevqSDCtVYiMGqFN9VPF7izwelPzqbUPTnfEMCxJ5G8dNEzqwLe352zPIkTJaTk6HLKI30UBwSFBenkkRs+9mfz9ci5ynW9v1XQSxQ93He8Oa+oAIcC2hLwSEd9MRLI73jgQ/8sPdhtmDRxUnhsjT+PAGEEwHwZpXlwU+MEQoS+5IJ6F90dOZFo2YbOlaXw8ToKfNoGZjxxWgakHEyMK8TVY7zi0lkGmGNaSIUOM9FLFTulJ1AJpWynq2ov/xEcmdWCzZXl7gZrtJ5pxEzgoI9vzgDUyzVAI6jcAe2Vg3ISFSR5iFCwvSgz24yaiZrJZrzxYIiiNAmZeXiuGRUOykM0B3JlEjI5Y5agj+Bi4P5Upw9fvlRSJTPMSrdiaO7ZioG01+7Vne+5JjTrGS2skw+ZfvT/jSxsZ3zownFuBQaooveLr9yo2W5on+5a1TLM399ybCla6tZg+TRqYLgz2mZaN/9yDC56OVVRlPM4U2S1lWqqBoWPRLAVujODN/SmZ0RgtsILSBf7t/ZIvny4ofeDuVL7rLQMHteegilglxqxRHfAoUgUtLc3vsArMF8b0vTqgIjTeM64FB46SZvWwDuxNNWcbeb1+9vHdhJzUSZ3UT9Yf3npUovVrH2OJ1lF9bj19pBn5zkkz8pGtx9LleK6IdBLNvBFEbmEVk0Y8CEupbNCOTiWPcj+0lk05kQXJyjJzkdSKwfbaqGFY+WPk6vmOJbWR3Xng1rjhmYHloJTUZKsUHrBK00/NItE8EkJk5ALtRMztzWLz1knh7WFDnkhy86yRDWiuZcoQgX6qaaJ81uXckBjFu4cNcxfZm4vevm9hrTDMg2Kv8tR1YHceKRLFesswcdJ4GSPyGoX8ufHyj7y2IkRYyQ2dBHbngeuHjp/fzJkuSGN3Jp5WouknGo+iXqBUR5VMR/JENoBBSzMQo6B1UyUZEod15FI3Yb3Q7JWeuRf068wFBplhKdNcO2zIteLa2DGs4FTboJQs56MOW4Cscn9ClPea+8iw+QCfWzroLiR4/+Z2ydQLTjW3i59ZvE7gg8yTCPioBWfsIuuF5sZYZDRH9+6ogfUPHVCHKOupDmJanyxIBDEqzncTWlbTTuAbD0o+u57Q+MioCqQISloryZbppYpREzhsAoelBN5NXeSZQYqKCqsjpZdNbCCS23hMCosqMqqEx261SIJCjCQLzG2iZVomgZnSQPggf78zE1/MZmEwROZeJgVWxeP7fKmXAFEajMWEyi+aQ4PcVxc4zsHZqTypgo2WpfRCJLs5duzOBDndAOu5JVEwd9I4qagewUtvtC2d1DBv4PdvzWmZSGoVddRcHiS0UzkAIMJ6oWhCIArVm1QraVgXmT0xSmYJSmAVIYCPkX4qoIqdOeQLPPDcwyBTbBSGwzrigkxaps7TsoY80ZztGOZN5Ht7FW/tNTzRESxyHcSn1DKKeYBk0TCOK4dRsFRoljKZttyfNsxcgAX+u5MY5k5W9yA1DHKRmKb6A0T55d7Hj6BzUid1Uj+9bowcbw/d8Z+Ngq+efQyakbVHZWgnRK2Pbj2Wk5F+Ai+sJHRTeGPPUQXFCysp10dyKjkLckKrCOhcfBwGmEXxTqzkhn6qWS0MqVIcLiQRTYDWwlPVTjRP9xKujxwPZoFfPJPxzz6R8r9fn3JYBxKt+PXzBW8fNNSjyCQGuqmmLANn24ZOZlnLRVZT+cjUwX/6dMH9meOdoWOn9JxuG2o0bQMuRrwT+dmFrmXaiOyjWvg42oliM4/0egl3po79UiYM7UyyVGSDLQb1GCMqgFOyCSfKJjJR8FQ/IbWabqIWCMHI6bbhYs8yyDTXRtI0tVRko8jYKwPfvB8oTGC0mLJkGro5DGtIU81yLt6KKijOtJXkmlhFoRX9LMOi2FukfX95IcX53WvThccm0rGCLg4sMh0UjGTvidZgoqTan28bGhQHpUiozIJ0dbZt2cjgX91saFkFSrG0CJAzQZqwBJlqJAv/w+mWJkRYy6U5agKsZDBaeH4CkC28IpstxUElOS9aw+VBwkZu2C49uVY8t/wBEaowgmX9ypmMT61mfMuVjJ1Qty71U/qpYmvqcApaRhNzRaIiZzqW5dwwSBQ3pxJw2bWw3k+kCTLiCzIoVgqhgo0aSLVmrj1tK41J28I0yLUWVlM58bgMUsMgk2yRjoWNtqVykd25o/RwqpPwy6dS7k3ltD7TgXvKyTRFQRrlnmst96+fSdNZe8EVd62mn2pSrTioA6u55uX1DL1TMXeBiGG/CpxqG/bmjr1K8NKDXJNqeVZLbc1ru55TqUgdn2zbhTxK0U2UIIqDgCG2ysCkCiij6WsobGC/Eg9KbjQxSj7MuImUPrKcGYyOHNYyBaqDXMdKJkSr3UrRywz3ZoHaw9mOZSnVTF3AeWl6M6M41zE8v2x4bbti7GCtiLScTG3e2q9pQmStMLy8nrJZGH64W3P1sCEzmt94ouDuVLxZ01roZ73U8Ezfcn3sseEDRPlS9lieM53UST2W9Qcfkmh9aePx+B3wYRP79/dq8W9+jOVpH9d6rJqRo2C4tw8UahBYTg2n2pGbY8ewDuRGc6ottKJ3hw13pp6t0tFa6MQ7QbCz7VQ09G/uNezMPFMn4XavbssXIbeK5UUQXggAnv/7+pxh7Sk9nOsY1gtFGeQEd70wXFlKuNhNeGO/xiih7Aw1FNYwbCJNCPzF/YqnBwm/fKZgOZPTeOdrDhpIE9lAjRv40V6NAnqZQUXRnu+XkapSbCaB9cJyuqVofOSw8XSslukPkl6ttTQ1Vktad7M4sc6s4Iy7KjLzERciPsL1keNf/nhCd5EIPqwD96aeVMNGy/D0IEEjaeRvHdRMG45TxuMiT2MpheVcM20i23PHg5kn1YrTLcO/d6ngH3/olOez6yl7ZeA72xX3Z47bM9nwzZ2cbmvk9VcLTajltP/ONNDPNJ1UUrs7VtPPNKcKzdVhQ4yRWxNB4JoF2cgvXitBpDlqQQ/bWSSA35s5eonGAB5FbqGdKTnJbwLWaJ7oGJayQDcRYMIzgwS3QCO/N3b83rUp96eO+zNPE6RRfX23xodAYRUbbYOKiiZG9kpPahWfGKQ80bFcPWx4fbvk+v2SJoi34lLfcnlgqSclu2Vge+748aFGK0EBh4W5vkg0dYgkWlN68bksBggoI5IscddAkcoEqfYipZs0gYPqKKldGpn3xoaXVhP+yRMyJn9lq+LuxPOdnZqtmaMwin4m2SMy7RK5ldHgiCQoXBBJ4Q/3a0ZOJkNzH6mDYJg3W4bKaawOvDf26LHY6I0Gq5RIoaKiUwbmTprLcuGX6SeaG6Oa2xPPpPJ0E8PzqynLmeHW2PGD3Yp2Kqjk7Xlg2ESmdSQ3MulRStFNJKMos5p5E3BBMm4kjT0wqaH2keuHDZ9YTlgvDB2rOd/V7MwD92ZhkeUjZLK2leb7uSVpXgqr+MrZAmLkztTRyzQvrqS0Es248bw/9uyVgYigs0sPu3PxnZ2NcGXJPhabkJM6qZP6oD4s0fo4pq7/tDrTNpxtG+5MRctaB/jBXs3n1j++xv2Paz02zchBFfjudk07gb6FYQj87rU5bavYKMTvsFd66iDa9HHjmS+SnXMD80akLDul56D0rOWGdgbD2vOdLSFSjRZ0KtFzi8zDKMN6IZkSmdWUTeC6l03c2Y6lnyh257KhaFvFxa7lGw8qNgrNcqJ4Y79mZxb5+VMpPka+t13zGpFuonl36FjJDbcnju2xnEh3bWSvEQzvxY7h6mFg4gJruZze3500NF7z3CBDpZLb8OZBvTg9Fp2/dzCLkYAkgidKpgsYePOg5lJfTpxvjwOtRGRDM6e4ORLj/mElqfE7i2TxtVzzoPTMmkjXKCa1eHEM4IM0Ld1Myyl7kM1+sgiUszryyoOKF5czLvY+WK6rmeEPbpSSmK1gXkPZyCTCIc1DCLA3DXKCnYILcRF2F9mqBAjQSQyv7QQOKvjsesZ3dip5rUUT4uSymQOxEY8BEW5PIq1EyFCHVcAHeDCLdBJIfGQaxYfw9EAyKWZNoA6ylt47bHjnQNDAGvjL+3OmNQwyOKwAIqO64mLPclBKY5cpCbmMyNq8N/WMqsC9mePmWHRQ/VQ28q9tCzY5OsUEx7wGhbz/yHhprgwULpAbxVYpz6Owi6lOgINGUtczK83d9aEjdGWadG/aMBfVELMatI5oAj/chdtjx3/5Yo9+qrk7ClwbN6xnisMSdstIjI7zXcvuXKRnq7l4ZUZlYLYgkRUGjFa8uVdTuUAVYDnVJETe3HdMmoDzYpb3iNxr5iTg80LbcP1AMd6ueHktofKanXlkKVP84e2SllZYBIG9W3nuTxw7U8+w8fQyRablu7g7Dygl3qm5g/dGjrMtzYWu4eqhZ5AGljLF+2PBcrcTCa5kIW98MHPszx3PrmScbUmIYtGB7+/WtBKNCpEHU2kmPrVqGTeSvVOHyDfvV6RGpGz3pp4LPcudsefr9+f4KBS50ge+vxPYaHme6ltOty3X9w2XJ56DKpw0JCd1Uo9J7ZWeVz4kT/o4I30/XJ9bT7lz44PJ0KvbJ83IR7H+zpqRK1euPA38C2AF2AP+k6tXr777oZ9ZB/4X4Byyn/xz4L+4evWq429Y10YN7URQu0rJKflyrnEBghL99mphqBdNySC3NNGznBsCkbKJKK04rB0KxeleQqYVa7nm7WHNYR14emC5PnJMXVwQjTxXliTMLgCruWaWKHbmntUF2vRcx/LyuuWwdFSLz/qVswXOR24uchE+tWbpZZqNXPPqTs24iRxUjhdWUwxiMm5iwGrFrImcbcvp/3YVeXopYb/yTJtIz0byTNKeL/QNv3quxR/dnlH6yE7pWUkTrixJINvNsWw4e5lIzpYzORVPNYSoeH8syFKIEs6Yar63WzN2gc22Ya8Ug/RMR2oUa4VlbgNVhKfyyL2JZ75AGF9ZSjCID+LetEEnCqM07URxqm3RaL7xoORi74PshN3Ks1ooHpSap/oJN0YNOxG0h46WTSQsJFYRzrcTTrUt+6Vn6jSpDWRGLcItI189l0sytlH82b2Sei6SoiXLcep7iNBNRTZnjUyPEq1YakkoXuoDnURx2Mh9eqZj6KVyMt5LRf6lkUnSuY7hYj/hjT1JZswTOGxgdQECcCHioqKdamoXyBNBC7+0mjKqPTMXGTdCE9toaXxEpgeZ+FjmLpBHSY7P88iw/iAlXiuRGiZasV96egmkRp7FqlZszwJNkHu4UmjWCsP+ItNjNVek1qBcYK+JtFPxMDgvjcxKrvnRfs0zSwlnuxqlLbtl5KmBYqn0jBsBLry8lrHe0ozqyPbcE5HclTzRfGIpZa/0TBrHJMokol8YfIjkRu5jL4XDyjOsxGi+Uig2W5aVwlLNZpBp3hx6vrBh+ezFlNe3a/qJZqcK9AvDP+qlvD9u2JrLBG6jsPz6EwXf3an4zlZFNxVaXWEUh41MHlqZYaMwrBWWnXlg7AKrWaBOYL+O9HJYyQwzJ4GcDsWkDnzpUovVXPP+2PHFzZybE8feXLJBWomiCopOonl2STq/P70zZ78SH9iVpZSVTPHN+yWZkUmpi5EMQy/zVCGSWM1KYei2PXWQ33WfXTv5j/FJndTjUH9ypyI85E18fsnyRPexOWfms2sp/9eHmpGT+ujV3+WK/R+B//7q1av/65UrV/4p8D8Bv/yhn/lvgLevXr36G1euXEmAbwD/AfB7f9M3P6wkfPCo9qtA2yhUonhy8cUNiyC1c73kEUytWiB3D5vI1YOaworH5M2DhrYRM2vlIm2rWM4Ny8DZluGVrcD/y96b/dh25fd9nzXsvc9YdWq6I3kvRxW7m51u9WDJioQMjhUjkR3DcYLkNQYSI4CBPBjIH5CXIHn1Wx4SIAacOI4BS4JjwYLmqeduqUmxSF7yTlW35jrzHtaUh98+VSTVdtxApyX2rR9wwbrFc+rsvdbadX/DdygMjBvB/AN0tWLp4KvbltM68UstpOWjcpxbhXzm149rnsw9fatYeFq3bcNWkXhvGrjb02glRdTtvuHFvuWPjhq+tG1RSvPOWCBmm0PL2MGXigU3b/QZN5HX1jNeXrO8vp7zszcK1EdcWr92VPPO2DLIFMdLIUijFA+mnltdzc2ekPe/sGV560JUiUAUvlxIdAw0UfHCUAMia1xF+Ms3C5ZR8eaG5a0LR1fDaZ3YHVmezD1HS7ioDfcHGqXFT0Jyz8TR8ko/fbWfWVsMvjwwbBSG0ypwWkW2OuJh8srQ8P1zx3zW8LntHK3g5aEGpZg5KQRJiXfGjtfXLW+PpUh4bT3jRiew3bO80Dd8MA3kStS+vrjT4RtHFSGKJJZHJmtKRRYO/v0Xe5CSQJ1oeStKZF0XQfG5keWfPiz5/KZlGcVXozDQNZqDMlJokZl1kTZJFlnX+0NLAj67Yfn+uaitKeDtCymycyuO3TsdzdOZZxkieVRoq8T3JEY04g3igyg9vbmR8c5YcW+gOVgG7vQtr63JZC5TiSYpbvfMJUytibDREV7EsNBMvUD8Njuaxgs8sWuF83K7J/vzha388mylxOXZ++g5B/j6cc3jmefRXIqjs0pML12Un7/VMZCEbP94Hrg7MLzQtxQGvnXiud9XzIPIERcWvnij4KSK/NJ9kbr99acV/86tgj+dePpGIFfrec5JFfmpdVnb3VHGpJFpUd8qFkGkvQ8XngTc6me8uWEv72PuEsNM8XTh+c39ivVMoYymYxVruWaUKawR35KuEZGMF/qaFwfF5e+T1Vn53MaKcK6407eX52bFQ5+3jvM7XU2TFCR5zpY+cW+Q8crQ8mwBLqZLDtt1XMd1/OTHn3Fdf04gWqv4mU/wRr5x0gjv9SfUef4nNX4sxUg78fgS8Ffbb/0j4B/s7u7u7O3tnXzkpQkY7u7ualovMmD/R3EN64W67Dj/yVTxQek5Lj2jXIzcQLwFNImoFP/b3oIHU49PiXt9y72B4aJJfPukoY6Jp4uASqKetPCi9vRkISZnEUkSXIq8deG4qARq8mgaGRSKroF3Jp6U4FcflQwyjVEiHbrwMGtia3QWePvcMamD4PtDzqxJPJo5DkvP0dLzYt+K/KePnFVCKJ84KKzAiI6rKOZ1PvJ20JijKaNc81df7PDlHUnQv33q8Ek6/bWP/NqTkoOFv1SZyoxMdyqfeDwTadXKJx5MGmZNJCHGgPsLB1E67LkW6dEP5yJvbBXMG8+r6zkLb1Ep8ScXYrB4XAamLlK13gqLAF2Er3G8DOzPAjf7gX/2cAnA/jzw7tQzLoWv49vk8KwKVF4geaVPZK3vw2EN42flparXWkf4A3KdiYsq8n99sOTRzBGiom7hXMvoOVlG6hjRLX/id/aXPJ0LSXlYyCTgcBnZb6cJXz+u6GhFP1cUKOokAgKTJrKWa+ZNYOkCv7HvSUomE1MHF0SWDh5MI6GVAn44bzhYqEtzTKtEmWzaBDpWieyvj0wdaBUxWnFewrwRZTgXwKVIQAqBwkA3E7fx4yrwe4c1MSaWXtGESBMSC5c4WjoWrdjAe2OHQpSjCg2PZ455EOhaE0G1nytS1fCN48Rr65Y7fc3+IvD2hXhmuABzH6gD3B02bGaaUadVkyPx3sTz9oVj2TpYTV3k2dwzD6md9IhCWOUVdQhUQZTVMgVdmzhzCYWoSjVOZLsPFp7//o9qFk3CkXg698x9El6XlmeuY0Xqd1gotILHs8De2HG8FAW6JiSWQcjnLw0i0zqI31ASvHJIhg+mnuMyclDCWibeLEYpLmrxZvnVRyWFFlEDo2BUaNYzhdGK96eeo2XgySJwoytSbd85aahTom81mRIo2knpWXhYBE+mYeEi40Z+3vfOamqfqJeK19avZX2v4zqel6h84jf264997z9+jiBaAG9uZnSMTOYBni0jTxaBe4PnZzr0kxA/rt16Edjf29sLAHt7e2F3d/eg/f5Hi5H/Afi/gWdAH/gHe3t7v/+juIDX1jJ+c79ib+x4tBTJzeNl4GAZ8K0j8kGZuN1V+BD5k3NxD8+14sHY8e2Tis2OkEMv6sCfnjt6JrHRMZjW2O/RLFAo6d4+mMhUpPSSZCYFUxeYN9AvoPGJ10YZtY8cL4UMfadnyI14aBwuAo/njsNS3JlHOvEHByWzkOhqzUuDjKdzzzdOaqyC3Iih4VaheH/iWMsVOx3D+xOBhGgNrlF0iWQq8b3Thv/zvTm9TDN3kfVM82Ds+Jf7FZuFKHIdl5G9sWPaRHxSFDpxUUfmXgjaC584qSIdI8lRoWEcEs8WgV6WeLIQSdlhDh2leDAJbBSRt85qjqvIk1ngM5uWRR0ZVxEXI+u5Yn8RGOhAUpCUYqtQvDSw/MpD6QDtjjJijByXgbPKE5Qmxci0/Z1sVGLZRP7wsOJ2XyYSzoEhsvDiZv/y0FB5y1sTz8wHni0CLsmEy0XxP6ljZKeQYuesEohTrqXzXgeYVFB7kQJugtzneSmmkE3Q+CQFbmY03icWKfC1I5FunTtRayIlyhoqxJixarkYAPNGZHNHueLh1HFvYDlYeKxKfDALWCWqXnsXYlzYt4l5lGvTLdH+o7TGEIQT1DPCxykROeWzOkGETCfeHzcsAowrkbsFKWSaCJWCupUvnnkpSCrgJEoReHugWc9hszD82uOa9VzxdOEoPTRBCOGDTHHTK46CTHW+vJNzUgUeTQMGkbV+66KBKMVfiMLF8iFeyu92tBRcOgaMUSiVOJhFXhtpBkbxOCR+76BimClyI4XSxCUO5p7NDsQAJ1G4RK+siXqXj4rvnjmWTeTxzDNxcnbrgMgUR4FNPl2IPO+LA4uP8PvPSo6ryLCd5lz4SO2E+FR6+A9f6LLdUfzOYY2LIl6RgIcTKU7PGxFVaHzkt/cbQkpsFJrGJRZN4KL25MaQId41x4sosshajCSthWdzR6QFdXgAACAASURBVE6icIqNKrJdXDsQX8d1PA/x28/qVtVS4k5P88Wt50vWOzeKn97O+cOjK3jWN46b62LkUxZ/0XbrPwP+GPgrwBD4f3Z3d//23t7eP/lBL37vvfd+0Lf/lbE4VxyMhTPSqSa8XsCTUnO+gOkS3hhEiggPThQ7BqqgqJxg8Ze1IkuOz25EjFMcRsXcQxHhfjeitWLqxeMhRMVQgQpAgpEVYnXTqjTlAbq6oaiXXNRw0SiGJjFp5PW3uonfOddcOMWWBVIi1DCpxOPjVi8xjDI9mARFAjYtrGci77sBGAdnDfSimDzOvSK3kCdHP0GzrPmtD+d8cS1yr5c4nCp+/1iTR0XfJHZMQhtFo+DJRPFSTyYN20pMBZNSzGoYtV4nPghp/qVcOskHU9BRCecEGGro5InH5w3TTNbiK2uR87mmCXBTQ51AeyEVXdSS/N8p4LNFZDZZMCsVKsH357BZJAZJcR4UOkly3Gu9IUKCSSlk8/N54n4XmlRz3ICOMDCwWDoenZT0dOJ0qciiIkYpCHySNTMRZpVI5I50Yu4V1opsbK+AsUssnZhQ3u+C0QkXFVkC3xqMGCB4xU6eOHfQeEVu4E4m8qwmKboWlJfPXQ2cMyXJ5nou56VnYFk6hjEx8bKmVkFQsJ0pLpwQ+DMtAg1KwTxCJznaYyhmhogj/UiLB4lKihwh1teN7KVKsGakMApJfEFWzXadxFF+ZOV1PkHtYGBhBHw2DyxnCzoejpayX94rThvoaritE88uYJTBTpb42mNFYaGrYM0mpl6hg0yACg0bmSivzRu5r5FNWK3IlfjF5K2ZzEvdRM81xFbWsfANpVN0hSePCrK2y6b1F2kxdIvS8cpa5KRUjEs4caCCYqThpC1uN6zA5qpGrqmqHHf6gWdzxXypGCCGNCmTyWYIcLFI/PxWZMsveXKiuAGce8X+GbzSS1QNjJPiM8NIHuGdiWZSgtWKyidu5olHlaJs5Gf3dOJuoXhWJ+ZOpqs3CzkDOsLTqeMra4l74ZTvvneKX/vhoFqvv/76D/X667iO6/jzjx8E0Xoe4Ul/aefjxcjXjhv+01d6f45XdB0/bPy4ipEnwN3d3V3TTkUMcKf9/kfj7wH/1d7eXgQmu7u7/wz494AfWIz8sP+APnpa8ebAcXZ6jB5uczx2vNYT7PZ5E7F9w8QlLpJvpXIVxEiBInnPIsK35obDKrSSvdAoRYYh68C9TLO7kfF4Jh37aZ1IrdngWZNIPuGBRYKpU9zOc76wVQjsahl42iRKF/kwaD6oHfO6NQg0ijfWLZsmcVZ5jtHMg2ahIjaLpAj9XsbrGxm5Eff4MkROysR7k4ZJFAhYTzk6nYJxgpkX87dBzJjGDJVDqSt2ujCOLcu5o3ghi4RF4L/43JDTSj7/ySzQxMTTpqGrxH/FArNaHNurcJXwGQQ/P40wI7KIie1uxqJJzHKDsorPDQ2VT+xNHJnRfHZoeFYKFKnxifcC7C88ISZIkbMazBzqKMn+VkfTNULWfnmYYa0kdDsF/OGJw8WaV3aGmJk4jzcJJiFR1opCK06cTGRe6BiiUrw7ceRK3L8Lo7gzsOzPPQsVeWHNcFFLl7+TKTpZ4mbP8gu3cr5/4YFEE0XedenFqNGRsMrgbaKJMsVogqg0+XZ6YW1bLCj5vjVSnFVA0JrXB4akFG9u53z9pIEU8Uo4Fzd05BWreFIG8ZWpxRunSY6CjI4V4n1KoirlIvzNl3v86djTBOFgdNvpVhUSSy+dd6VEYauJwqfyUfZatYXCegHbucjgZhr2veLblRXJ5E7irYuGun1OYgKdQ5XlLEJku2+4M7A89jWDQuNC5IMm4ZIUrbcLTT8z/PSWOMa/c9HgkiTwXQV3Rxl9J+alwpMImEL4NWezBSbLMEBeaA7mkVlrGt83sN0x3O5pHs4DUSliJ2PmPeu5po5Cpl/LDZUOpCSww5NKIFdOwVMHf7DosXSJk+i50TGMCkMeIqVL1CEyc3CmLL8+VRyXHqIQ9ycNPHYCvUtAU8nGT2OiNoEqKeZe0elbTDdCcCxRlxO7KkFUkDToTLOeizjEeR1IasGr917ARXj9OTA8u47reJ4jpsS/ePJJSd/n87n/Sz+AN3Idn674sRQje3t7x7u7u98F/kvgH7b//c4n+CIAHwJ/Dfj67u5uDvwHwD/9UV3HeqFoYuJhqXmxn+ho+GDmWTSJG32DC4mHM8/SR85qmXLMfSJXiYWT5KGKgdJJp1QBisSHM0/HwGY0fDBVzJyQm2OKjGuBD62gPaWHRsN2N/F0HjmtS0Lr8hxj4rgK+DIwrURWNjmAxPszx6KRz+zYhPWBsyoRWxPBszryvTPHZzcsdYC3zuVhjCmhFCycdLpViGx3FIWBWUh878zxC7kRE7yWlLtWKHIHF02kULJOJ1XkZCmu3hdNpArCkSBJx7hOgm2Xq71yPT9dJM7LwCCT7jsJ3h07hhZcNEyawHfPwqVJ4yhLPJh5TpaBfq5ZtvLKVsNRFZnUwn3oWfEVaQIoHVtIUWIeEq4JKKXItGYrV4Q6ifnkwl/6qaQEh4tEP08oLf4q7888m4UmRSgTJCv+FcdloA4RBbw7CVLYGZmYzRx0G8/7U4NRYpA3aaBynkUQmJFSsmbjWorCFAXSU7RGjbWHBUKScu2f8QoGpeX+Hs0F7nVQypxjGWDRRDZ7moWLnFcw9RGDSAqv5OccItVslJDeZy6xmYtj+LSJLVE68WgRpQhBrsm3fiOxnY6QoEbWziQ5S02EcRWJwELBwCYuqsBj55hUkjQXrXHm1Mnr+1nAalGUq1pPnmkdOKsFKrWWK+Y+EZIs3HElXi4XdWJUKBKRsxK+HxoxYQQezjyFgZMystbR1EHO4sIJPMwDqKuCau4DhyXolOhYOFh6pk1AtbytpYc6ROZNIrfgXcvBiQJ/sxGOl8J3KgMclmIyWXmpeHyUgu67p45RoZl7ueaUZHI1bRKla/lmznGnb8S3xkEvS6znmnfHHhdDq4ImMsYuSgG+crU/qVa8EcWwUGTIZ37+OYNpXMd1PI/x7VPHUXkl7DLMFD9/6/lU0ftkMfLHZ46lj/TstcT5pyV+nDv1d4G/t7u7+y4yAfm7ALu7u/98d3f3K+1r/jvgF3Z3d/8E+C7wLvC//Kgu4LW1jKqFFJGkQzx3iUGu2Cg049apvDCCU1+4SK/lfRgtiYhbPfutm7ZWUGiFT4qFS5Q+MMrFEM1oyLUQiSsvCURhpOvctZrCJE6XgbPSMcw0cy8KRKGFlliFwD9aKIxv+QSZFjWoovW8iEk+p2NE1nPiIttdI27nRjOwcp3zdPX6OolXx6jQPF0G5j7x8pph1oAPERcikcQ8wM/d6nJcBnZ6mpPSYTWcLAMbuSSYK8jqKpHNuKpyPS3fIMLcC3l3LdcobRg3gVGueDJ1zJ2Q9gOartXs9EQe2IdEoQXetnByH9YK96Gw7fcbWDMKHxVnZSC2ErBLl/jKTodcK46Wnqad2IQkP2ck3nL0jJIENsLxUjxSlBI41tAolJLXayXFjw+QaVEyG2YQUZzXga7RnJVSwCkto/Kshe+XXoo610rgFlr2oQlXD+GqgGhrNjSraYliWie6Bp7OPS8MLCkpupkUGSEJQX5oFcuWpG/b96+O69LLtRRacbtvOFh4ekYmSLUX88qulSS+Y+QaQJLflK6uTSNrnpCLdEmmOFbLeoFAqqoAvQyKvHWjb+FvZ1WgMEKWPy8D9weWgKz/IFcYJVClkKTg2xs7pnVimENuDCmJAencJcqQqKO8b+kjhVVYJd4vK0jkpCV5a2RPCysF1rgOdDOF1gqXxCwyJsVWYRhkmnETybWcuYUX93il5RlciWEYJUINjYeFCwRkIma0mF+iYBmEM6bboiwzkFn5WVHEtDirAlk7iUpJoRDI38y1DY/2vTEK1EzJry9ilPs8Kj03O4aNXB7wdMk6uo7ruI6f1PgkROuv3O08t87jO13Dy8MrrlxI0pi5jk9P/Ng4I3t7e+8AP/MDvv8ffeTrB1wpbv3IY6PQvL5uqS8iZRRX5ZeGlrVcUQXFei5eHu8nhVWJRdsp7meG9SJx3nYiY5LkxLad7dyIeaA4QMNmoXhjM4eU+MZxgyESlSSio0K8TjKtGRWG8zqhMby+bpnUYgo3d5LYFUYKkmVLSF7PYNTR3OwZ3joXgvyoryUxQZKujjGMck2tuZQePasVikA9b/0kMsO9vqEwkhQflJFJE3mxb2VyExNnjRCn740yPr+V8awM3OhocmO4P1ScVIlMiUeHizK9WCXQWkkHOLaFSkL4BesdkZndKKSYGuW2TcJEvvVG13DRRF7sGw4W0DGaQQYLJ54bhWm5FEnudWg1mRKi8M2+Zd5EupkW3kSm+MV7XUJKVLPAeFbgY7tm7boPDfjWpf3ZMpCiTDU2Cs2dnuGkEvf52x2D7WqeLCIdHVgGKUBeXrO8NND88ZljkGmsVuz0LduFagnmUhQ+mXkmTWKzo7Gtz0bHwGzlQt92232URLUJ0EHWsJdD1yqGmWJoZRZ3u6dRyVL7yH4VGeYGnwI3e5bz2jFqm2PnlZxf0/6Ovt3P+Fv3O1w0UrQ6n3h1lBHHEBCSeGynTloLByUhZzG0VY1ui7SVM/1qL+72DZNG9iK28C4L9I3GG0nsy/a+e9bQN5r1QgqPm12RD3att8pnNyyllymFVYm1XLNVGJqkOMIwIDEmtU2AxKtDy/ecPJMLDyMDoWcgRR4vJDG/OzAMclg0opC12dH81Eikfdcy2YtcJV5ezzmvAt86rel24Ggh4g8r9/U6yOdOHez0FFYb5k1g3Ihccj/X3OjIeeplwitqgjQLVtNClRQdKwpj/UyehWGmuNFVDHPFtBHZ40kTyTMphl1IuHYiF5BzUweBQm4UltdGOXEKX9zKcOn5TEiu4zqep/izruvPJ0RrFV+9kfPh7KpA++ZJw889p5OiT2P8RSOw//8aF3Xk2dLzuFLs9OF2z3BaigzseqHYLCwpJVCa233N0iXenzpOq8isEShQLnYHfPTf+9MWPrSWSdfZx0RVi6neTkezORL8+rdOa6YNnDeRgZUEzcVIiok/PnUso7BxCyMdX6PEBC6ziZQEKlKGSEgy0Zg1kXEjWWK/NeDbNiJLe1TKZCe1kwatFK5xvDyyvLGR83Tm+eZpQ+Nhs2O42zNMXKSKifVMc69vSIgM6q89KfErlZ8QmTnDWiZd9SbES1iMav+EJNOD3EBPS5e9ZyWR2196jpdgjcIoxcgqlIocLhN1qHEx8XiihCQfEzo3qJSovCTxi4gQ8Q10MiH0Z7kkyYNc8+ZWxnomviwHS4F/dQ3cG1rCpGEa4LiMhJionXSdQ5QEc9g13Bsq3hjlaBJKOZoofhcRxY0uzA1MmsC0EcnhP0K63YnEzW7OICp8kgmEU7KHG4X4kMQkEwjfqlN1Mik4fAAToChgzYqBYh2l8Opo2deUZLpis8T3zx1Vm+De7hpCSORWcbOjmfYNcx9ooqJnYNCBYWboWcV/8lKXz2xkZEbxpZ2cD6cCWytbWeU5ioGB9UwTUyAmmXj0rDiTlz4x96I05tpiRAPzAA+8gPS6Nl12/KOC3CpGSuB2xiD+L+uWgVFs9QxdrfiWj5h6NXES6eplECPN7a7GaJmsjQotUD9ALaSwXPrId84ck0bEAbZ7hozEjULjoiYzkc9sZtzsWqZN5OFMpKZfGmp+4XbB+xPHzCVK5zmpAxenFTHC0CqR024nQ1qJ9G8nRiofmXso54mNIrHdkXNTBTnjVQAfE9Fq1jKFCy2m83Iillg28rDMfUJrUeNrImRWs9mVvfSIdGcdopizRuGbdaz4vXQ0rOWKn7nZ4d+9U/A4JDKj6D2n3dHruI7nJT6Yet4ZX3lBGwW/+JzzxL66k/OPH1wVI9e8kU9XPDfFyEUd+c39inEtukKNjzyYeqoQ6RrFja7morqS2HUB9sYNSw87heK8+rjcae1gSVswaEmIq5h4b+wZFZH7Q0Mn1zQx8WjqLtW0Vrj8MsIHQWReh7liERKEyHHLA7FKXrt0kW6GwMISWBSPZo5ZcyXhqpNI0obgeaGbszduqL2Y/kxb9/XCioHawiW+cVwybpW7AGof+J0D4Wi80Bf/hQ9nDhfFQLAKioEVx2ufxOei9JF3xzL2yBBuwgoS1AocEYJcW0CS2q0Cjks497DVTcyawOOZTB9ymzhcSAKclChYKRRP5o6Zk4JGtbCg5ETp6tAHXIRbfUXpE5u54nAR+KA1NCydpzCKB3PNI99wXK0I2YlJLdc1ysWLJDcJmsROJ2u9NBKFUlgVeTgLrOdwu2v59XPHrJb7q9t7DR7enUTO6oovb2U8niUWLtDPFE/mgRAjLsGkXk0G4KLljBhL654uHf1xIx1zkHs9rxLDPFBoeNaIGtWxU6QIdYpsFgarFJu55ngZAfEt8TGRoqhHVT7wlZ2cszJyWER+ejvnyaxh7iJWyd6sPF4M8GgaLqGCg1wKrdLDyVL2eQXHW3GEFDL1UwgfBqQ4dAHGZaAKV9LHAwvOJ5LRHMwCuVGkKBLIF02g9PJMFVaKnqMk5yOhcEEMIj+YRUZ5QitN2QgfY5gLFwPlufCKVwpFHSP3h5ZZHXk2rzmvAztdw+trmjIq/tF7C768k3NRB96beDxijDqukzyPMbDZ0TKVSFIML5srKBvArE7E5OmZjEkdyYxMVbtGIH+3e4obHcWTRcIHmYJF5NlTSuShB7kUdYuYMMqzZgz7CxETiDFxVsqZCMhkpXJwUcqZ3Opk7K5npCT8lYWDr2xcc0au4zp+kuNXH30covVv3yoYFc83P+IrO58gsR9fmx9+muK5KUbenzrGdeBOz0A/chBgkGnWc4EIFUahVeL+muWntwt++VHJdtfQt2KkdqdnMXjqKInSrOYSbjPIYacwOIRUXBhF1xqUUvzivR6//rhkXnmKDDa0JNVNFNz4VusunWs4T5pRIUnwMoS2ay3J2avrGf1W2ejxXLCQG10pihSwVoiJ3zQkbvctlY/0rOLdiRQi213DfV1jh7k4iKfEnb4l10L8rUKko+Hf2urwaOqIHVEEqoLiZs/Q+AhJcbtrOCoDS5/oWpnWdA10kqxJQBKrQkM3kwnGZq4Y5kLS7WRCpA5JEuDCKEYdjVWCnY9BMbCKXq641TF8MG0oWvLEWgHrbZJbxVbGtlDc6BpeGFhGuWHaBG4PNJmB3GiR+fVgteH1dZg68UYpWvUqo2C9MHStFKSvjTL+9MKxkSu2u5ajZWCYwXqhebYIbHYUdZAJgUWmNCG2/B7gTyeBz21keCyHc8/tnuKoBELkbl+hlby/P5TuuNaiSHWzKyptSkU2tCIlRRUjOmmUhn6ueLVnOCllItDvai4quccXBsJz2Okl3r6AFwjMfGKeoNdRbHY0tweGm13NeqE4rQO3eprtTs7vPqvYKAw/d0tzsPQ8mXsyk8gV3O1pNjoWA3wwc+Q2oTwoI3KytFwSjRSLxsia7nT05TodleLDMirgpzYK7vYsfQu3B4am9akZFIZ7Q2gmUMdA18pzuZ4Lf6IOia3CMG4iJ1Xk9XVLx8i6NwEKIypca7kUmsTEqKP4W3cHTJvAO2PPk+Oawig+t1lwf2h5NG3wMfFoLopZN3qmNW4UUr1WERcTvUwxKgxzl/CVl73QsNY1dBVoLS7tKHhjI2PpZTI5Kgx3Y6JO0DeKnV7iydxxXsuz0enJ+5q2osuMYse0s0Wl2SoUNzqG7587BnkgkWgpISik2HtllPNL9zvcXzOc1bJnX7mRs/GcJyXXcR0/6fHLnyhGfuk5h2gBfG7j4+aHh2VkfxF44dpv5FMRz80uTWpJnJNK7JeKR9Gjkrit9zLFdkfz9pnnDw9rfvdZzcwldnLFo6nn8SJQ+ytVoZ5V9KwkEj4KSbZvE10rHibLII7RFy1j+qIRTkWdZJoxtDAqFC4KYZ2UcEnThETjIlmuGRWWL2/lHJWBwzJwt695MgtMXLzsHq9nmnGMVL5V6QqBzChyFfnuqThnL4MkypPGs48mX9aEIDCUWRO5qKXjS4JJE9lfeJ4uAymJUVxfwws9w2EJD2eBGD37pcDWqiBrElsSczcTTPtaKyN7sISzGs7KxBujyHbH0g/Sjd9fBCZOVIfCQtrqClBJ3LKnDrZyhUsKoxJJtQWIghf6hjom+pnGAtsdzbQOPG6V0NYyxTIospb3s79QBAK3uwqttfAekOmUaZPuTCvOqkRo+SCbhean1m2b/CXGjUzSzqr2mpE/H1WdWmqBDS194mZX8TRJYl4HISNnWlH5yFmT0IIG5EZu2N2wfPVGwbdPGzYLzatrGd87rXn7QiZ3p1XkooIn80ATZJpzt2+ZNonCRDItHAsFbOaaoqsxWvHsvIGOJcbEpE5866ThnzxYghYezJ2BbaFaiYUT3pBSmlERMVrz1RsFXas4qyMP557CJLY6Qhb8YCqqcitRhdzK1GnpxfX9opGicj1X3Opqpi5hlZCtCw0Ppo5Zk1h4mQAoBO4YIgJXbCeJJJg7UW7bzBX7LvBoKmuoWlUvjZDYv7iVc7tveHxSsWgSv/Ko4rR0HCwDx8t2Ihkqfu5WTukShUo8nMsUKPiI0omjMpGSnOuUIKWA0gLldFGaD1sdjVZSSDUtPvF2F/7OGwPWcs3ThedfPK44XDgOS1Fr6xqFUZphHrnRSvEuG5l+ZRqClyaE0Yr1QpNrxVYL1bo3MMSk6GeKRZBi6KyOvDKwzJvEOxeOo2WEheKLdbwuRq7jOn6CY38R+ObJx8nZv3S/++d0NX9xIjfyb8AfHV/Bs7554q6LkU9JPDe7tN4m/29NPIe1wuaJ01oARY9T4runzeU0oXSRB+PA+0gi71NrZoYkPqelFCINohJUKDivIlUUB+m+Ukx9YNpCOE5LSVqUND2ZOZgHgXL4mDithQy+9JE6gfGJGAPfPG3IWhjNo2ngoPRYJYpBVYBnSylMuhZQkVkDTfTsz+Ci4VK9aYYk35sGKkTdRymRDM1aqdkyyNTlqPRc1B4fBW4SteGbJ424PhMFAhQi85bIH5L8cFeLAZ8PMK6SQEra9aoSvD2ObHYiW7nixLeSuFZkbVemfLr9L17e/OHMM2+ulJvQou70dBnoW8V2VzGuAh+eeF5ZyxhmcLCIPJ7DRi775qMUDB44WCZyI0l0avfWRfj2mePlvmGto/lw7pk3gdBTPJg69hcRHyPzFrs/dwJVWsUKqlQBWYCNAmYu8u7EkWmFS5rSR6ZNpHSyJpUXErgKcKEC3zlLrZmluHN//bjh4czTRJlwTGtaxSfZz5MKXPJSZNbizm6NplDiRj538HDu6EdY14mDZWR/WTHMNH2rmFWJRR15d+pkf1qI1sxfwY8Iga8dV9zuZQxzkdydOSluT6soKmptIbK6pxRbGd9aNswXcr4Oy8CkBp0c/UKzaCLLIBO101KqibrloVQe+hnE9qyRRJVr2gSezFLb9UpU7kpq2CooXeJ7pzUnpWFaakYqYnXg+6eBuoUjGuDBxLP0gYFVWK0ZZjBpEoe1PBcrgYTQKsCFKBDC1SRm7oW3lWlpLBBlLy+awD98d87ntwpiTLx1XnNWyXuMgnFMaBJawdJ56nAFb0u0Zqg6kqXEwTyhlZIzXgjUc+oSLsnvHZUL0X3SJP7lk4qfv9Phbk/z/gT+8ftL/vPXery89tz8ar+O63iu4pMQra/uZNzpm3/Fq5+v+MrOx4uRb5w0/M2Xrwu1T0M8Ny2019YyygDnVUBUN0U+dGBV6yMhUp0da8iMEGWrVaKcrqRONZKErQoTVpj7KMnYvBH417IRhZyDuXggaC3TAy2UFUJYdWoTISZikowp14qu1WRG0bTEVymGIqpNqnpWuvtVOyGJLTdgmEuBcF6LwzXq6joVsIwwyJT4agS5r1xfkfG7Gbw/9gyMRmuFXalZ+cis8VitKL28rzDyWXxkHVKS5H5Fq8uUJLcZ8tplI+aPs1qc0quPwJtWPAQNOA8bHZk4ZUbu0bSfF5MUMLlRLa9GJiQ+yjTFavncaVsxrN5vjRRK81bqlVYVqmdlL/aXgW5L/L03sJxVkUJpelaSaaPEqO5K1f3PhlJSUMybSB0Sa5kkjJ12v3w7GTOmlWg2XDqNn1SRnZ5hu2N4OnfodrNn9ZWyWh3ka6slKdZaJgJHSzEt3OlpSg8TFxllijLIVCprq7zSJ4a5YbtrqKL8vfLiwzFxIsDQMSJ20DGacRV5tnQ0AV7oW250xYNlXCVaVWkMsr+G1oRSt2IGGgqr6WWGZYDtnuasEVPAspWwXvpE1spOK9UWiKYtIlueSUythG2UCcNqHbX++C+viHz/8TygEFjig6noJmdKzllmZQpxvEhMXGTmxdzwxYGRojjK539ULayOV/K63VZKejWJtAq0Edjmrb5hfxn4YOZ469zJVIV2r3WrLtdOwxZe/p5U+wy153vuZXpWh8RarjitIm9u5WRKxjQHM49RidIJbG3iIi8MLFVIaK1YszDqKH7v8OMqO9dxHdfxkxOfhGj9jeupyGV89RN+I9+6JrF/auK5aZ+tZH2fLRz7S2gS7K5nFEbxZC6mhYPCioxmlAROt0mcS8J9MG3HdKUc1dEw7EhxooJwRxTw6lAIqB0DWms2O4m8NSiZOuhqiAFudDQbXYsicVZFetaw1dHkRvFsEdjIFRtdw6xJZG2ylhLcHmR0rOfhTIjNXSuJckeLg3SmJdmva7n3jKsOdtco1m1qISitqpOFNSvFyFEl+PWXupoA9IzGqMAyKDY7lju9xN44YHTAtAl+0yZxA0Pr3SKf1TGScFstZGTfFnU7Pc3AwHwW2ezAhZMETyNdcJE81cQUGRWiUmSBeUzEIIncqDDcb31jChU5a4uP9cLSt4Enc/EnSUlhrXhPzB1cu+bq0gAAIABJREFU1LSwGpFM9amdEBnJiF8eWu4PLd8+relmcj99o7nbN+05ESjXJ9O9DnC3r9Fa7q1jNQkxsLvZVUzqSGMjsb1PY0Sla+7FE6VnFV2j+cyW5WtHFXMnErjDPDB3Qiwvkb1KabW+mvt9y8PkBcZUaDZ2cv74rKZ2UBpYKww+RMpWkjbRKq8ZRfCJMiq2Cs3CyblBKe50DVoljpbCGdrsat4YZfy1e13+j/cW/Mm5wyfY6cm9V04giBaZ3qi2MC1aeNJ6ptnINLM6ttNBTUdDSJqBaTk8Ws7RjY5MDpUST42djsYazcJHOjpRq0TPyl5eyki3xV3PSoGzlSdeWzP83qFcx8onpt/yeyZeHogvbGYoJbyUvpXnuYlSoFotxVDp5O+ZMazliq71HJdXPiYbHc16phllmosQqDwcNyIH3Gs5XitlPN0WJa0nqogH5FJsWQ0dq7jTN1w0omj36ijjpaHBqA4fTBxvReFYvTjI+MJ2zvdOG251NcsrUR3WrGJ/+a8rma/jOq7j0xonZeAPjz6eYP/1l66LkVV8ksT+3bOGJiTya4XBv/Dx3BQjIF4Dr6xl+EViajQLL1h5rQV6U/rAINNUIXHRSJGhkUQixCs500zJ1z7JNGRgNV7HS8+FcZPoZe1ERYkhnSg3aba7MpEZ14EqJs5Kh26lW32IHJaJrtbkWjwLDFIcndaBcSVu6pkJklxlYoh3p2+42bXkBt6bgIuBqvX4CMikQiGeBAEoMljT0FNQZOKCXnpYtipRq/s4nHsmPtG00JlRITLBdwaG2is2YmJWR+oILkm3XGAosp5zD8ZfTWYGufhRGCVStys/DN2SchPyXoVIE2slhPOuVmRWkXtRLEtASJHjpee8EqnWiEx7Vh3ulGDsRCqWBNZo7uQaazw9JX93MZKS8FFudQxvbmRMmshvPC15VgbGdcKFyNwHvnMaOC3TJUeh065/buC8lG76pI7kRrFTaJ5VAa0V53XEKEn+e21nPtKaUWYKHwMXVSS0ymGf2ci41TM8nnt8UnTaiUgTpYu+aCVhjYbaRz6cO07LwKSJnFWBrY6BpJg0gYsaZsmh1Eo6NpFXEaskqVVRkel0OSETDkfgcBHo5zJFu9szvNgXaeBBpnlxaDmrAk1KdI1wbaZNwGpNzypu9jT7i8DBIjB1iaXzeFpFNaMEnoaII7gIy9bdPISVoaXmZgbzJnJeCxRxq5vYyjWTOlF7mfCFtiBbqXbFBE/ac3BaKb43W1KFq0nWCpKnkKJ7s2PoZ5qlTzxdiCpbAm50RUxg6qIooZmVT47AIJdBJiRdK/woTWLmI7Opp1ydzyRNh3kLr0tcTQtdI0X60AJKU4VIbIu27a48X6eV5+HUcd5EPpxqUhIuyRujjC/tFHxhK2ctUxwvPYdVJCZ46yJRlopYRW72npuB93Vcx3MV//xxdYlIAPj8ZsZLw+cqjfvXxt2+4U5Pc9A2ZKoAb104fno7//9453X8ecdzdYq3C8NpmThrFClPnNeBSR3ZKcTEr0rioD6p286ukiTQcQXTapBOpkYSoHEFIY+XEJUbheK0Eh+Kjr6qxkOAcRUZI4mZUeKjkVvFhRM+gYswyCKlkqnKZBLZLKQwGVdCxi4MHC3FGLFvIc8E4vV41lBYzShXzHLYn18ZDl5K7kaRCtZa/D/mAYIXIu2ihf281IfDReC9i4A1sJ4L0fuihnfHjteGlog4mkMrVfwRyFhq72/1mStOhQFI4u1yWAYO5oFMwVF5tcZ85LWTRjgFWZsk+yiyrrmR/7cMkoE2IXGybDkYSXwYQA72rJZ96muYNZFgIoP2/VmUBLRpu9bDXPPbByUuCYTvZkfzeOo4rSMJKXKIV8T1mBC3+vazjJJp28kycLKUux4VUDaRmU+kFC+5IjFCGSMXJXRzMfbbyGBaR371wyVP54HYen48DYlxdSWX7Nt1tBFOE8y9QLSWQbgtpMj+MnJRi3JbInG2lOR9VEDZOoUrEjGJcEPpRPXpvJTpgNVyb/M6caebOJgHXEz82mPHYelZKzQny8BRHa4c22OgbzUfTAJ1WzD6kFi2BcCkjtzsCrfKkJg4MfE8X8qNxSSThON5vIQuZZfXkjhfBsooRRNKeEiRK97KJ2MRPgGpa/dLAS8PpTHw9kVDrhXjKtK17bnykYezeCnMkOv2vGgh4Pt45TZ/VkOuEz4kohI1r76BJ0sRHPio/PEqFFJcHlew1ZGLTwjccFFH3qkb1jI4b5LIaNcBlCalxM/eKHjnwjFvIj93q+CFvuaPjhpeWbN0NRx5mJx7/ts3Bz9gRa7jOq7j0x6/8gmI1l+/f62i9cn4yk7OLz+6wi5847i5LkY+BfFcFSOndeBnb+ecnidmVtENIoe71TXsjhSPF569sUdr2F03uJB4uhBi64q3oJJgvbtGCoOFF/L3zZ5io9Cs54azOrCeG5qYuNk13FZQ+sjTuSTAHQvrmWGzo6k81JUn2oSRvIP13JCSwK+6mWLeRNZzxTCHKqQWwgM3e5o7fUsdE/OU2Mw1X7pR8M7YU4WScS1meit+gkmSdL+5WTBtPEsPH84cScFWF9YyzSDXLKNn2khRkBvNjW4iavEyGbvEGyNLUjIVEWJzZC3XKASLf8PCtJIOdkIO2SiHl9cMmdXc7kqX/XELe1oZwkHbhUbWtmNlDRSJyss9J6XY7iYUmqNSBAd2eomLSgqanpFu+eqHWQMqCufB6ETPau6heGfcoICbfcPtnhjroRQxRF5ez8g0HFWRXkvuz4woRmVeOvGrqVMG7PRhszA0ITFtJJF9aWjoWc24jmx3NUuvuD2Qam1cR+ZeisKN3PClGzmj3FCHyLtjx0trlpeHlt9/VtO1ilE3MWt9YXLkjKy4Nhrhz2xloqB11nbKb/UVZQm51qwVUeSfc3GJ10qmeRsdzYsDy3sTx3HdsJZL0dK1wl3oWoGu9XPFO2PPrInc6lp6VpFrgTcuXGJoDffXxIF9QCIP8OJA82zpWXpJqjetppMpOkoKqhs9xXkV2exFQoCiHaPnJjGuV1M0S0ow85FnLjJouRnHVQAn3KKaq0YB7dergnj1y211phRwewA/f7fLi33LN49rniwCo0Jze5BROc9pHZk0iTWreGXdclEF5j4yreX5ly5kYu5lwrTwsh/bHfj8VsHB3LNuFUsj913Hq8lkV8tUxsCloeRmYRjkirmLLJrEVqFxwGc2hbd0Xnk2C7gztMxC4nMblsNl5K0LxzDT/O1XejxdBk4rKbT/8osdXPpB5dlPfuzu7m4B/zvwKtI3eg/4b/b29k4+8boe8L8CX0a25+/v7e396o/5cq/jOn6oGNeR335Wf+x7f+MaovVn4pPFyDdPGv7rP8fruY5/s3iuipFJnegaRdVCXqZNomcS53XkxnrGT2U5pReVq1dHOZMmEWLDIotMnHSA+0Yw5y5K0ruVK+Yh8eXtnGdl4m5f4F+jTPHhPLDT0Uy9JB0+iufDuI6S9EzE0G+F+e5Z8W+ofeDpQj7jo7GCPYZ01W1+d9xcchA+1PDu1OGiuDm/NNQopShaLod1DVuDjO2OwkfN57csXav5/llNHeAkRIJS9KzGGpkINFGM1zKtiBGMVnxuI+PxzKO04tU1y9xJV/hwEVn4iFaKOwOBl81b+VeX4KgMnFSSGBctUTe1SZlW0oX2LWFZKSG8L1zCajmot3uaJ/PIxEOIkSbBIoghnIvt1KotvnIj71mRkKd1IJDQBG70LIPMcHNNkuqZT5z7hFWRiyZxr73fpRPYWNlOjQxSJCkEZjNpWhJ1lMnQqnM+a+D9GNjsRHqZZqcrniPrueH+wBKT8DbeOXccVZ4Ppo7SN5QucVRFni0D2UridSkEo5WjvVVSdIXUQrUCqCaRq0QiMXYiI51INAnyKApMdQCfItsdI94uucYnOFoGTkuRzl1rOTJruZzRWevJsvCJiyqhiPhk0Npyb2AEXhiFlNE3mvfKQKakGFtLYh44b7lCuhPJtKYoNI8nHq1kepEBw0xxb2hZ+MiH00AZwFUQk5cpBC1vK3GpKJVoPV5aNbkmyLTko5MIg9zTMJe17Bgpsp7MPE/ngXEVOa8ChxHmtb805zRaOEUbuSFTClN6WY8ajlTgVs/w4iDnfl/ze0cNR8vA2RK+lxwLH1mzV4T3LLZnUkmBZbUiIzHxoJJikClyrXEhsnSJzCSOy0hsTQ6blDipAieVZ9bA1w+F9zPqaFwU2YdcK0a5YejhvA6YOXx150f8y/PTEQn4n/b29n4LYHd3938G/kfg73zidX8fmO7t7b22u7v7OvC7u7u7r+3t7c1/rFd7HdfxQ8SvPa0+lhO8vm7ZXX+uUrh/o/gz5ofXJPZPRTxXJ1kr+IPDhqNGkVJAEzlYJIYFPFSOTGsaL2SnEAWudFaLLG/HSKK538IvCgtZgomTDui7E89WRzNpEi5G5kExyODBzFN5eHXd0rWKhxOHTwJTcREad9U5LZ0Qc49pVaU+cf3uBzQ8VQvzUB6mwMIncYU38Hge6Vik25oAr3i5VbF6Og/0Ms3p0jNu4Su9DGZ1YFq3BGIrhnNVgL5JaAOVi/zWswqjFWtGZHanVeLFgXBPxAQxMWkkic/bdXMBDgPc6Ios62kSLkreErIrL9LAuk2wV7fa0a00r4K3LyJ52wavgnBDopd1Wq3has3CykwutNLLTWJeC1SpMInKBx5MZFKUafEyOalEsvWkDLJHTWj5KbJPxghHqI6S/Ko2+b1oxKzPtb4zK4+K0zIxDIGOgplLmFI8UmJUfOek5qQMuAShjpzV6dKvZOEjf/CsYuYksS/bxLRsFdgMl+rHWCX7dt5EGi+KUTGJvK4PYGxi0QiEzCcY5ZFxlXg49WwUMMotVQhUTt7XBGhipAwtHFHB05kna6VtT6uA0opMGwzyuQufKL1mYCPndWLawP7c41rBAg0cL+G8jFx0RB5ZpVZ2WUMTEv8ve28Wa1l23vf91lp7OOMdau7qiaTYvFIkWbQkGnEix7HhOIhjx7AB2hngOMlDggCGkTzmJQGSIDCQPARJkLcARoC8mLbhQYBjBYYdR5YFk7JMyiJ52VN1dc11p3PPsKc15OH79t23is1Wm2SL3azzAdVd99Y9+6y91trnft/6/kOTOs6bQSGrTXBcS3csQ/18IvhVJCJdkR4y13gpRJ+PnrdUqMHlsk1YIBQJnwzvLb1AMrkk0RwgC4ikc2p5UskaBOVRnbeJNnqqEHmwEhnnRvku541IHjdeOx9J5swrxq4NKqOs89q5xDvnnqStm42HupJ24nEjZPg6wsglGuXFHDcJH6WwH2cDp+20iFzD8s+OWj63k3P6AvqNHB4engD/4NK3fh34zz/gR/8s8Of1NW8eHBx8Dfi3gK983GPcxja+3/hbd55X0Rpt3cU/IL54LReeryYR7y4DR3Xg2sh9+Au38SONF+q3VUJ4IplR+A5GVG6QJCtz8Pm9gipA1UXaEC6Sy3EmiXVEkpfSSuIXgkCQjitB4j/dBHZyS93JCXPdJWaFGAzuFI5JbsV9XXHyvfSuMwI56bkBlyV5P/yehkXseRllNsisdlHI4M4kSgOzQuRZX5ln3Fl6zrrAxMkb9Um0UzZ5D7GySsgtENjUuhOn+lFmcUnkRN9edmTOcKWwVH2ngEs+CnqqXwdw2WCU2N9jf8+9eyp6X/Ncfi4kSa5BkjqLJKr+0hwkBkhOf4DkVNnJGihyUX1yzqgwAJy1kURilEtRsps71l3ktBbn9U7Vu3Ira13FAQo0LQS+BdJBabVAKp2sb6nzf9QEJrnM/f11oHCiWFYHGW0VxH/CAvPSYI2V4kIT2S4K/Ix+X5jh/sZ5b3gp85R0r/oo81957UwYmOVCwMZYRhmce+leTTPLvJRiOFMBghTlXiZ5/1rHyFlCMnQ+8njt8RHO2sBYYVvTwjHOxCulVi6O0b2V6d48rtRHRGGPVp+D40o6YxHplvSCBq1XtTZd46APYGa1O4IUHd8LmOSTGGnmFkKUZ3GU2YvuYWSQlEbfO1eu2JGaGtZe1nyaGwotyk4bMYm0RgsmhZ9lSqgnDZ00DxfFiP6VaTF0BNs0qNrFJBLda4/yl2QNY5L95BUm2iuIdQmMNTgM50G4J0UGb50/f5TxYsXBwYFFCpG/9QH//Brw3qWv7wKv/m6Maxvb+H5i3UX+3v1nNRz/xFbS9wNjkll+5kr+zPe+tu2OfOLjheqMpGS4PbHctTAuLOsucmtiaZMhYSgM/P5bJa8sHSd14LyTZPj1ecb9SrKzaaaQJwNjY5lOBGaSGXE1H1nHbgk/fSXjwVrwGaV6Cowz+NL1QnCfPmJVarRPTnrSa59Y50jy+TulFYYhmQpJJE59ElL0QvkutycZ81AzcZbrY8fMJX7lgUBedgvYMYZNEG7GTiHQllnueLjxFE4I7794c8Sdc8/1seXnr5V8+7Rh0YgfQkoiizvKLN887nicvBjHJYE01UGSs5Bg7gyNSYxzMEagPtZKIl2pclcXpQCYZI79MvH+Ol6IBoxykSJuohhZJiSB3Cjsx1hJhktgUkDVSiJXWhnH9dKyaAx7hSSCuRVZ3V+6lXHWikDAWZt4bWaZ5AYfE8s2cNJIN6zQJPLK2JIZw2kTOKnl/ka5QHxO1WdGTrYtV0vLwW7OOojr+MQZbk8zfEqcqmDCKDMKo4J3F6LONs9lrxnEWNJHSURtEt7Sranl0SYyyaAwliomfs+VnG+ctJzrQdpMs/upMwQE5rNfGI4aUWfzGF6ZOGIKF52YeSH7ZmTBWeFWvTpzxCjdAGMMB3uZFLwhsltaVj7xU/syHyvdtFOVt3VIkQMCdWy1qBj18reNdMUKA9fHcFRz4XQ/62V3g6yrj73cruz7SjtSl5+TAlmjkYN5brkyyrg2SuwUlocbqZBnarrZK14ZBtL8NJdxWWTf7BVGilgje64Oib3SsglwayzdnZNWuh5XR3JfGEPrRa1tbGV/WuDmVGSyn1Se0qaLAnw3N3jAGsPYxotuXxPUD4ihSOufhdKIGEFIcshwbewojGHRfK/y7IWJ/xVYAf/bD3qhN9988wcfzacgXpT7/KD4pN/73zty1KG8+PqlMjI5eY83T3/wa3/S7/37iTeKnK8zFCS/cviYn6i/O5P6cbz3jxo/int/4403vue/vVDFiDVw2og53slK3K3bEKmjJErvLDy/9rhhksHV0hGTOKLf3wTaJEluRJKAZGCUSyJ91kTGmeWlqeNnruYcLjq+/rTlcSUGizenGfulpXSGs15fFEkwRk6uO3KGcS7JjNHT1d44rY++g5Dx7GnwZZy8B05q4VmMc8soF3LwKLOc1YZ60fL1Y1FVavUCGyUQ7+aWkQ0XEqY3Joafv17iE9Q+cn3sWHbCJfnNo5ZvnrYsm0SbxJBx4yXxvT2zBBxrH8gjOKSbslHDxE0rR74JmJWCo5+QmJWWFBPzwvJ4E2gCrEPgXF+H1eTcSsIW0tBRcBYKhb/0E9MhvJMuCUwoIh2GO8uO8yZR5iIF+AvXSvYKkXlNCt3zKXF/E+lCEhKydjxKIwVk48Xt3RpJoCdapEonJJE5qC5kiMVhvQtJpXqF/P3+JrDswHeyn6oucdYIJKoLwjXor4lCfjIjheu6lcKu8nBzbNkrHU+qjrqDb512hCBF4I0dx3ElMr8POuGVZEqAjwlxm0dgU4WD3VKK0bG1nHaR01bEF+6vBMI2H8GN0nJj4jhrpbDyAXKXeLzu+K06cVxrlyBBmRmmRjow1qg3R+noEDnppO89VvPDNsLTRu7fIt/fKWDdSVcq9WtshudnlAZ539xIByvLZb5GDq6MDV2I3Ft5IiJzXHVyTdUFuCjmG4XhdUH2lLVSPM1Kiw+RJ7XsB2tEohigNjAyjlEmczTLLfuFuN3fXXq6FBllhlfm0rqqAzypPGdaMKQka1pkBhsNlsTayBr3ncW6f/h1sLmVe62izJ8hcdWKMIHwjV5c+MbBwcH/BLwB/InDw8P4AT9yF3gd6IntrwF//3td78N+gf64xJtvvvlC3OcHxafh3v/S/RPEaUriT31+zhe+8IM38z4N9/79xB8xG/7qw6FSeyfMeOONa8/8zI/rvX+U+CTe+wtTjJw2kbMmUvvESWsgRs67xLl6AeQIZ2HTwamFRR3wSU381DfkrJbEv9Bi4c4iYFVJ59bY8LgK/OZhw3GTuDmyXC3hrfPIw7rlD75UUqfEP3ncsl9CbQXX3+jxZ+sT01ww7lWSTkSdBn8CGGBIHwZLATkp3rPw3jIyK+BL13LeX3serw37yWMwHDeReSZwkDrA2EX1mpDE+JWZoeoCd5YdJPgDL5U0PnJcBRqfuGsCtQ8cVVI8zQt4d9Hy9kIMJp2JHFVyer/xQtiNiDlgTAKXEu8MTdAjdDHyxq7j8Ey5FEr8DZoY9jCiaQ4P1yK1miFrtAwwATaXCjiPwFqQKaZF1q1dJ/ZLmcQH68B+0fHFayVvLzreWwcyxDDxyVqgPP34rK7HhVyxwneWDC7kzsGi6b1EZKx5nri/9qy9cGuWbeLOUgoRp+vpk6z3SAudTq8ZumcNFoV0Lift1kn7vvLwdBPZBCnWVp1yDCLkdeC4kmuDzNdGZW8dz34AdAozG2WwMZFlLVLJF5CpCN1G5IpPmshnd0SM4N4m8N5Kkuf6UupXJXiySuwW8n7TXNSo3l8LR6VRySubZF3PakmyfRq6FU0QCNfIcUFcz5H3iggHaL+AZRIp5wbtHkUpJMYZvHcemOeRZSsFcR2G/dDvlfjc/00S9bkUYBlheTbwh3IjruonOt4ArAiUBioDGYGsNPzz0451K52S2ifeX6rpziVOVKNj6SI82kRKvc9NK2vWc8eSPvwl8nofoDEqf43wfM6SSBPvlzmf33kWpvCixMHBwf+AqGT924eHh833+LGvAP8Z8DUlsH8J+Pd+l4a4jW38C0XtE79y71mI1tZ1/cPjS8+R2H/jaUuICWdf3EOaT3q8MMXIW+cdtyaWwsHtceLMWE5aKSZ6jPpEYTzGSLJcZvK91sspapFJInKBvdeT6tfmOT97reTJRtSixk7Uex5X8NLEUPnEu0vPbmF5Yy/TRDVSWlFv8kFOf0eZ46VpogmRoxrwQkwHhQY5ec8uSRLUBBlnD9/oycJqJs7+CG5PHKsghoVVLYlObuFz84z7a89ObtgpEstO7n1nBNdGlpcmOe+vPIWBa1NHmww2whevFvzzEzEbjBimhfAtZpll0wVKZ3BWMCU/sSuF3N1W4G0xycn2pACn5n2ZKn29NnNMM8NRE/ncjuP9TWCt99QinYcrhRQdfQfGGIHPPK4T86hu6spVyJ1g/WHg30wtF3ydaeF4eSpyvMsuEqJ4mVwpDcZYnDMsuwBe+A2zXAUElAvjlDtgjXRkRk4S3wSskUKgsOKrslNYJUALLO5pHZiqy3fP6SANvhSFE5hR4aQ4znWN+y5Q0i7GazPLJiQa7d5cGcE4s6y6KBA4L4pfmZNCrVcay4wUV6VC4wxihBkUgnZ9bHlSRZyDcRiEE5yVwiEZ6bod1YlXZxmvzQzfPBU1qsKquIODZSXFWwt88UrGH3t9zKKFf/So5g6ecRKDz3FmiCSWbeS4kUkoXN99kL+HAC9NZf+ulShUZjLv/9LVkvM28WjVca9KpCivuT0TKeM2RNZe+C9NlMME78X0MyYZX19g9p3HeQ43po7GBwzwaC3zc3VssCYxzQ1dSBw3MgYVFePzM8fVccb7K8/IGqZTQ2Ys1yeGo41nExJ7I1m3EthnMBrNchlrsMKr2jGq2hcETmiRtZwrTyjXPbeTW+a5w3UtmYE/9PLohSOvAxwcHPw08F8B3wF+7eDgAODdw8PDP3VwcPDPgD92eHj4APgfgb98cHDwFrL0/+nh4eHyRzXubWzjw+L/uV+zvKRec3Ns+X03tr4ZHxaf23Hsl4ZT7T4vu8R3Fp6f2n8xD2k+DfHCFCOLRhSU/vGTlkdLwxpRq/Fp8Ckw/S9/5IR1pQeZpSYbuyrZaa0kCONMcech8asPK47rxFGdmLvEKBOC69hBFSJHjXQfbo4Ny04KgqulY5aJN8ftaUbjIz5ZPjfP+Im5wRj4zaOGSiEqTZAFi3BB4h0pfCOzclqcKfxp5EQhysfEsfpxhAhLdeJe+0QV4OWJYafMOGsi6y7ShsRRlXh5krg5tTxaJ6oucXfpCQrrubsSrsE8F5duGyPnTeJpnZhmIou76BLXS8PVseX9daQAgsJebo0djxG52i/sZDysArMC7i899zbqoWGk+PjZqwXvLgWntVM6qspzrEpkAVU30s5WpsmZRV4fEahSilLI9S7bdYCjKhBiwiaBIq3ampMmcL00LINh3YlL+NTKXhg5aFSmNgL7TgjxbYSTRtSduiRiBmUmXYYqiC+Mr+VUfe0j99eBp5V0LhxyD31B0H9MhqjmjZohZ/onpaErdtYBa/EUmToplmsP+6N0oQ5WMfAerBFFsswKj6OpBXLWSJNQRAG0M2iVV5L3cK6ga9J3tDqwm4gx0AaRkm780LUaZYZ5YSmsPGM7uQgF/PLdCpvguE5YEju5Zbd0LNoke8/LSf+Vscj+Pq0VEheUd2LhpWnGXikFV4qRO6vIURXwyfD5/YJAx/4YTo1jnsHdtXQASXBlnLHxniyJPLc1cs0JslaZzpNVGFTVBR5v5JnviwGvctVPNumiUznN4NbEcn8tcshVDJy1kSuFoXSG8y5yUoui27oTeFfhDDNn1ftFBDRi6iWYpQtoGPxSrP5pgxS76yCeNz5AbhKTLDE2cNYOScuLFoeHh7/N99D8ODw8/OKlv6+BL/9ujWsb2/hB4q++s3nm63/n9TF2q6L1oWGM4UvXC37l3tAc/erTdluMfILjhSlGVj7w19+ueLLxrLWj0HcVeii+B8PCAAAgAElEQVSUUShRT3NSRMUFMXrVSVJ0ZSSJ+GkDD9bQRs/LE0dmxOMhBLiRIKXIOwu5/pVSXJwPz5SrMLKct4H314mrI0hEHm4ixiT2iozTJvKwEtfuTTeoRjUMY840SYoMfJKo97T0iSKKH8eVkeOsCTxtpCCYZKIs1nh4UkcClhgTmyAvzkxi0SXeW0pGtJ9bztvIk42oC5EkMV53Ipcagf1S/FmaCO8tRT1q1VlWPl4k0QaBnpx3kaTJ5cMqEFPinXOBE/X4/TaKtOs7Ky+JmDUcN54H60EBCQb4UYckZglJsgv1A9kolMrqenu9/qaFzou/hrXgo3BUvnWW2CnF/yQlUZzKDJwlSdr7LlTtZV/0UJ9M3/+xqkKFKJ204yqS9Gu5j3QBw+r1Pfqks4dDmefySc8gXQwDxKf2MqZFJ+9f5MI7qb2qeWknpSdI90aJ5612cC6TjZL8XG5E/asNw31KEj5I6fZKZD7K/cQg3aioz0og4aP4hcQkSmx1iJw2IhncaiFWZZF76yiy2dq+WrcCU6uVH9IgcKmIJOp3V57zVkQFQAqBszay6hJVa+hS5HEHWZGognQxelhaEyI+qqKaFmGNrl2/Bj6JtO86wlkj65Rd6lodNQNc0uo+PKsFBjrL5T5DkOf2KIkwQ+d1Ljsx4DyuYZonTBHpmsSTTWSay8FG5WXPdgzF6mWopgFWYfgs8B5CnTjvPPvWUDaBv3+/fmG7I9vYxo9TLNrI//3+sxCtL//EFqL1UeIXnitGvva05T/8wvRHOKJtfFi8ML+tHq0jx1VknkuH4Hm8fI/NvgzX6BOOHv5UKQQoJJjm9gI2U3mRi/VJDAathePa04Sh03Jt7HBGJGUdsAmJEzX0S8nwcC1u5rcmGXdWgYhhrFCjHmYEz3JFery68psv/p9b9R/RJGqei4ysT0qY1w7QNIdVIyaLKSVxL8cwzSzHlZfiRmFhIcpJeEDhMTp5TdSTdSV4T7KhMNqESOUTuyoC0gXBvK/bpKpfQrxNSXgWIATzZEQ9qV+3ECO5EaiMRa7x/PlvuvT/LklCO1P50xp1LdefyRCIS6UKTPMCkrEXSkobPZUu7FBEESWxdnCRPPcfczmDAlpfSCWkS9L7oaSkia6+h7m0XpfvwfHd99aHufRvfUHQF0cWKbg6LZp6QvesePaaQZWnFPFHdmncRvdOF4WLYbTAsGZ4Nvr9GxQqVqsh5CwX+FMM0kHqfU4yI+vcK4uh72GswK2MUX6IUUUxJx1JkwZei0EgVbWXAuWoSiokYbgxdhTWMMsMj5vITm7Vj0VEA64Uli7APBMjx8wJD6RwQ4F3+X36gq9V+FZ/jtbvnefXLNf9li6KVcM8d+zksvbn9dDFcxayTLp3EfEEOq7jhcRvE0VA4IOe9T6yS9/vxxr1M2bRwUtTx2kTX3hp321s48chfvm9Srh1Gq/P3HfxIbbxwfH8PH3tyVbe95McL05npEvMS0OTLEUmydUETXCQZCAhCV0Pa4lo4oQkkoVCh9oIhbN8dsfycOVZe4F57JSOayNYNJ5zL0nfOBc+iDUGYwyvzeGkkRSytLA/Bp9EAedqKUo8jWJ3rDFYmxijHhYMcA2HYsaNnLz2sVcO8sD7I8deDskYSmeZ53BtIg7x08zibOKEyLWxY9nC6xMYZ47zLnB3FURdKzNcH2ccnkkPYJRJVyi3hmUnykCZKgjNcsvV0nBcB87byH6ZYQhk1vDyFO4uo8B+gJdnGddHjtLC109arEmMrCSJI+V8rDTbvzHJ+cyO4/1NjesTWj90i0DmoYfcjZ0kfTMHuwYer5VnkcnPpT5pR95rr7TEJGv+0gQebBCY2AgKL3uk94C4Xops8nEj5HJnpJiZ5oYnGzGkM8CtKewWjkrNUca5rOE8s7ROfsjHXlpYuC6990zPW+hP4/tCs0+YHUNXDANThRvtjqR7F9TT5WoGWeEojchUt0GKgCsqlDBz0iWotHs0LqUzsltYdktDaSP7hdzrxdzmygnR4qAO8OrUiSyvhTvLQdb3xtiQG8O4L4ZjGooeJ0m0SVLYvDRxhJSoQ2TRyb97L+tlrXB0fJC5floL3+X33Sh4Wid8jDRWpIV3C4cbJ1IuCmOZSdyaZMxyw2+fdZiUuDG2hChjtcheyCzs57CJw2dCUuha6XT+w9CJ6/cZSOE3cbJWr80zcmN4kODlLHLWJRZqIvr6zHLSJeYOTtvEyBn1eYFp7sTDpw2M84TptEDRbl6/H/pnH90DQfeys8IzmqqHylbadxvb+PTHV9551ujwy5+bbI0OP2L8/LVni5FvnXnO28hO8cKcwX+q4oUpRm5OLCnBqo0XxmGZJr0pSSI1yVEJVigLKT5yZ1h1gvUGSRBemWe8OnM8XgeShXkJn51nLNvAUR0pnOOLu47SGr511lB5OKo8590gN/rq3LKr5gHXJ46jKvDWomPReYKe3HaahQYjSW/PV+iT8F7qtVQvCq8dm0BiJzfcGkuCUzrDogoCbTLw6jxjllneXXZsArx15qkDvHsOhfPizVBYiszQhMT9jaeLIlebGSm6RtaQ2UhIkb3C8LNXcxqfOFezvmlmuTaydDGqSaHlszuOz8wtTTBUPvKk8pw3gdOa4fRHycdNkDW6UsLPXcv5mSs5v/G44XGdJCHXRKw/1S8yLvAs0xJujB03RxlrH0i+BSewpFa7W6WR5DYkeLAS+E53qRAYOSidJabI9ZHh2ijj6aZjExNdkK5SaSUJ3Cksu4UjpO6iI3GldNwYibxx7SXhrzpRO6rC0G0baxFRdwoRjCpNq8l3bqVoiTqmNg5qZAH5e0xyHdd/HcWQM3cQSawUpjQuZP2slbHvjyyfmefiuO4T7609dQd1TMyS4fYsY65tnLtLz8YLp6jRk/5W8YFLLwn+3BlujGGaCehsllvqkOh0oSxy+u8vYY8y3dvnXWQ3N1wfZYToKZ3hcZWoFPZog6xZHeQ6q04wwBsvHT+rz8aijexYuL2fkwGPNgGfIqOUsa/yzXUUkvsok8Jqnll5/jPL0zpyYwyZMTxYi6Je0E5Tp2uWIZ8XBnVXR/bOPBeu1k5u8SmxV2acVJF71mNIrEKi9YkTFT4w+hlUBQhJCsYeltmial4MxUcffXcm9YVR/5llhdPyokv7bmMbPw7xaBP4hw+fFYTbQrQ+euyVloPdjMOF/LJJwG8edfzB2+WHv3AbP5L4HYsRdbL914FfPTw8/NT2uV6fZRzXgTomOY1VIqhDpTH1F/tYC5J1C66Ak1WiSXJqupPD3Q1EPCMSVUzUHeyPLQ9WHSHCoglMnGGeZzzcBOog3BLbQ1g0eTxvAlcKy51VYLew3Fm0HFU9+VxkQ42eyq78s14ioPAjr7CaJD8rfgwCp1qExLVR4mkVlNAsic9RFVk08cI7o1V350rvvwrQWNh0kqDvlKJ0VVk4q7T4sYFFkETulQksPbxz7rk1shzVkTpEps5y1gQebSLTzOAI7JaWf/TQs19Kp2bdBt5fqeM7kux1HkrF2BsrHZimS3zl7Y2oPNXhIlnrz34jsOzUlV2Ly9MmcLwJoiTlDE+88EQyK3yEPrEMcMGP6K8VETnZtYvMC/EHubPsWLRyGt57qvgkCe2yjXRBTBnXXqSeU4q8u4ycN3LBWteeMHBAQDoiJxsZV25lLBHZKx6BJfXQqCYMPBOeG6/30K7lGtbKut7pYG8cqVq5z6qTJBojxoJNSLy5aNnJ4cFGk3oLlsSTTcAkON5EdkrxmTmuBx+cViGIhYPzVmSzAa6VvTpY4qwRdbUnjTigxyTj7N/HRHGlmzoIqpl7f+2ZZWLI2PmBvxWR1zUN7OWwauG4EZ5SF9VMM5fr3GkMD560vDp1rFrZ6++e1+wVhvubpL4oMqcnFcRSJHVrlTXbzRyPahFY8FG6If08W1QiOg6fHQlVojPwtAo83QSujgybLtHFxNgajmrhZJUW1rXC0rTAP6pkPLuFiCH0e6PvisEA0bucmsRLf6/VLPTB2vPT+y+utO82tvHjEn/93Yp4qcH5s1dyDva2z/W/SPzijeKiGAHhjWyLkU9m/I7FyOHhYTw4OPibh4eH89+NAX1c8d7K84dfHvGPHzd0bScnqQoHmRWSYI2twWC5PU3YZHhvLVnqjRHcHGc4Y7g2jby/DDysIjcnGX/gdk5CTo67CD99pWRvZKi6xG5puRUcKQXWQTocVzOYZoaNqub8B2+M+Rt3KpIxXB0njDGct4lZIVAYD0yTJDt9MgSSBDotVkbK0xC8fGJkDdenGSkmXpvnHNWBV3ZyrrmaJ9FyfyUFizVyKr9ohLQLmpRrwjrJ4frY0SXD7XnO7ihyVge6KA72n51n/P5bJSdV4OvHLXfXgVsTyyQT+eK7y8DLE4e10p2pQ+KlqWPRBPZGhgeVJFC99PeyHYjdswx+cs/x8iznt886Xpk6Cpdhreebxx1nYn8i0svKndgt4drIMHGW0zbSmcTrE8fxumWvgN0cjlq5vYnerLXSlQjIfMMA2cucwMmsMbxz3rFXSBJpEsysIbeWRCB3lmWXcAb+4O2CzBreW3Y4E9kvDSklzjrxJek9Lnoeh0WI54WVtSwyKRq6/ufs4FeybEVkoS9IMlTGWbskIYkz/e2p40kdWG+kaJoUSnxWAszNiWW3tLw0dpw2gffXnnlhsFhmuShhnbZCdLkxsZy1iSvjjDZ2tEmVnozMd6nwpODVf8NYXp8LP+q4CiQDL2dwXAf2SuFLNAp/qgKMkXsbO8tE1bVkVgNVSBS6L/tfJ6UV2duJkUKu0oJ8WkghWuSGUSdqXWufyDOLCYlUOM7awF4hzxfAKLfsFFG6LUbu+yd2c2ofcc5yexo5PA1ELdj7562Ngyu6VdjbODOkBJVPfGE3Z5JLZ8gZw51lRxs7siDSzpNC7iMCzhpem8HKp4uCuifU9/fcQ7MMA0fsgieEHArcnhhGCW5OMm7P3Ja8vo1tfMrjeRWtP/O5bVfkXzS+dL3g/3pzmMevPv3Unqf/2MdHhWn9w4ODg3/58PDw1z/W0XyM8XgTuTG2zHJ3ofqkdhgXp857GdQxcH8tp+kJSbAKY1j5BCkyzwxVENWio7rj26eSTF0pRdc6xMRXHzWcd0AUVR6nXYs2aFGR5IT57XM537+3DtyeWJpoqTrB3HvliDijHhZ6BFs4STjL3HF74lSCNnFaBxonTtdthGknBoVPNp7TNlE4KJMhZemiqFk2z6qHZah/iR9OYEcu4Kyc3lZBkuSdAl6fOq6PHW8uPG+ddWRGHLZDgu8sPClFThuBWRlj2SsNT6tADHDagTWedSdKRavnjP1A7v/eMvCoEmPFu+eeIjOMneGVecao8jQRXp9nLNpI4yOlsyzbSGUCJ43KpPrAxhuaOJwu51rA9ZAqY9R4TyWcLXLyve7g3aXHwcW9jJwk8mMLx41Itv7eaxm7heX+OrBXWBLCXXhlmvHOecedVbrgZfT7rdDs0quCVa2O4JmVE/7dmcUaQxMi5226gOQ5C1aPxHv4Tt/lMcj4n9aBpXZD8iQE8tzI9TdBzDDjMvJm5pkVQjavs4Q1gUkmvii9d8kks5w0gUUThDuiXJ2eY5P02bFIJ+u4jkSFClkDpbW8PFFPHwyZTSqwIPDHNsj8TwrDrWnGTiacqkmbuFIEWu16nKrJ4TrCppJ7n2sRnlmBVKYo4gjnnSGGxCZ4Nl6NPPWE8aWZPAuTzBCSyFuvOhjFREyRbNlRB+kEjaxlb2T5vTPL4yqxaANNMMxzKRx+4XrGu8t40dEaZQlnBIL4WycdQQ8RVp3M19VSDjXWXkQZjhtYpMQ8h53SkJR034ZBFQ+e7cr0MMLSwX4JuTE4a9gvLecbOK4CD56RSdvGNrbxaYu3F55/ejSIUBjgT39u8qMb0Kc0fvF5EvvTlpTSlnfzCYyPWoy8B/ydg4ODvwm8zyWhl8PDw//64xjYDzumOfzjRy1vnTWcavbWJ6gnjZxU3ltJom6sGNStGkmEmpi4MY4s2sR7nUC6+sSyh/lUXeDhRuFYSeAdXVCCspJ9gxJNk5Wvuwi7eaCw8M4iDs7hqtRkkNdEhWmN9bBzCTQpMnGGJibO2sDaizxw1QEmsek8lVdjOyO49yctjHNJAHtZ08uPpEfGXTCQpu9vBJrk7ADpIsHhouM7i45ZLlycOkTOGjitoySrURLsI8RXYa3GkSBJYx0EhrP4HjzbKoFvIDWDRG8dEkubSEn8NQoHbRBp1Ajsl+IN0oShW3DUXnLV1vvyWlT1Clj06+gH9az+z6qVufNJxm9M4mgjczvKpVBcdIE7S+kuvLnouDZydDFyeOZ5b6nFDkNHIyAFRZME5tMXDr1S0rKT9R1rwRQ08T/vhj3XX8elZyF8TRj+GP33M5WjXetE9JyDcy9/HNoVMnB4FjjtEnu5oU3wqAosW8+iHXgtCZmnqDK041yKlEq7BT5PbDqBge0VidM2sG4h6fdXrezRoJO/8ZJE37PCcbk+dmTa8Vo1Qzegj6R79VxbB0n5UqI8FwlJ1v/JepDINTr/T9YCPVy0IjZgjah/tUH4FrUPF6aaxRg2TeStRaROUgzOcnFx76IUqm0YFPXOW8hcYOkFnld18oz13Y6TBlGps4PindX172LCKJSte25N++jnIOh/zjuBek2KxCwYeeYifPVJyy/d8nx254WhBG5jGz9W8ZXnuiL/6q2Cl6fPs8e28TvFT+1lTDPD2ssvm6M68t4q8Jn59rPxkxYftZc/Bv4Gkge8Arx66c+nIm5PM+6tg0iSIr/0e0lWlJDroyQZvd7/SEnAPsHGJzpVP+oT1dIOCW0ATcBUulUhQD2HoVdvMqh6kRWPhFWA6+MMq+TcLny3G3R/KhoRSEbVSYHwpBIPjpgGmd+kykMbP8BIjBlkiZug5G++9+L3HaG+4PJBEvKIQExsNjiHLzsxcKuUNK0NJLoEs3KA9NRe3tcqvGfVyRx8WPj+nntejB26FgZRsFq0UsyR9ASc4cS+T0L76KEtl6+dm+eSPAYJ234NSaK6JRKu0uVoonSQPr+b0YaEsxA0oVx2kb3S8rSS98vtsyTkyFDQmkvjGOcyf8aoaaImvSPlRRTmu+Ve+7H299fqTfSn6IX+Y+9G36/v5XkpzSCti4FFE3laBa6Voo3cKE+kf11/7V4at59Dp9C+4xpCEuWsZSdJ/7WRKMb1z0pIwxgyI8XrWRcggcHwxk5OSgJtfF6ktl/DgDzDMaocsxkS/54Dluk6Aoz0++eNzG3/zOUqt+uTzPssH4q5WxPD01q4TLkRaB5J+GNPK+mw9JwuqxPThcQoHzpWheKp+iIqaLcnU4lsY2T8OzkXn0Ufdm7Xo8abTq5DFJhZ6eSz57M7Gb/66Ple4za2sY1PQ6SUvqsY+fK2K/J9hbOG33vtWZ7NV7cSv5/I+Ejl4eHh4X/8cQ/k445pZnl1lnHcCOwoJYE5rJUlapBkcOMFAtElKRYqTcQvvALQ018Uz2+4OGG1ZlA0Mkn9BJL8yZLKoxrBvE8dFM5QWMM4s3x2J+NbZ/7itVNNfnP9/0j9N+aZvP+V0nLaJl6dOVX8Cpw16UL2NVdOyUiLkbOoBY2V+z5VH4jevbxlSMZzBzdHho1PLFp5f4sktnu5YenTBc+j8ZCNYDd3LNuA10Kn1LFuehhSknFfH4kE8IONZMfLD0GU9ElvX7iVVk6DcwM3JzJvjzeBeQF7SDflrFbuQi5JagxD4dWTjXuuhrUyP7kmsRvtXhWIQlobZC5Nrl4ZmWGl8KUrJeyWAlWLyXClSNzbJL6w66jDUBTtlzLHIcFYFZkiUqDMdH+VVjoYRSZrtl/CSStz+NI8o7Dw7TPPXgGLoJ2dNNzLyGkSbvQekKJgx4IthL/URnDx2W5Q3+UwRhLwtddOS4TZyPEzVxzvLQ3HTSQ3kTpXzxStRILuFWPg6sQI1yNBa2EnNwTEFPPliZPT/pSofJBiUZ+FUrtLfYL+01dykjG8MnXcPHXEdRBYn465L7w0b2eS6/iLwUPlZgkra3kU1FzTyRrnVu4xc7Lus8wQERL8JBP1ri7BvjU4m9grLJmxjFzHbiGckpEz/OReztMq8N7KM80tXl1ACyOSvWVmaFMail/dX5NcfEcAro7kcyEgnxPLDubOESaBvJXipO8I9cWyRTx2ylyKyzITSeGYYJ5bxiZxc+y4NbLc31zuJW1jG9v4tMQ/O+54+3z4xZhb+JOf2fJFvt/40vWCX300FCBffdry5Z/YFneftPjIvaqDg4OfBL4M3Dw8PPwLBwcHB0B5eHj4jY9tdD/E2C0NV0aWndJiwiCN20vEdgE2mqWdt5LgnHcC3UGTnRFSSFgjiU8PM8n1JHutHBG8JLQlg+GdQU62p7kkTGsvkqiLJvBwHWgU1jXShNRoYZNZIeo6A1dGlp+5WlBYmOWGb5923Ft57m2iepPIeFpVb+r9CQo9MYUBFtL4IZG9ORG/g7NaEv9xJoTajWLdC00el0G+b5HOzNWxYeISbYwc1SJ/3JN880xO1HtJ4roTeNmyi9wYJz6/m1P5xOrIX8xPDw3ri76Rk7keKaM3IUlz6UR2tg2iRrTqBs+Fpif6h0EtCwZvi77TE5HE22gh0EVVtIILU8jUzz8wLUQGd5oZvnPacdYJNv+oCiK1qwXrURWYFIbdTLxLTutLRZ5Cc4x2EMaZYZwLh6JwIi+7aCMhGUYucXsivBOfIvvKOSq1QC3T0GkqtBNmkCIqs4NZpVPSdEoDEdrzrFJTG0XEoJ+X3EnhkFvL/kiut+648FDJjVzIpYFEv1LY0ySTwnGSWdoINo9kzlC3kTbJz/R8iL7YzK1hnht2C8O9deSkCfz6w8hRI89EoYVE0OopGi5MKT8zd/z01YIrheGfHre8c+55Zw0b4sW8Oy/r2if3Y0Q0wDmghbNWiqZWr/+0kULirdjRRS0YY2ISI/ebxDvnnirI3F8biWBA08Gi9fgEx7XMef/rz4XBu8gYmT+R9TVcyR1disQU6XSP7JVwZWRwFo6rxFk7rFfSQ4CUZL02yMFG5sT3ZpwZzn3i5mRLYN/GNj6N8VfefrYr8m+8MmJvK0jxfccH8Ua28cmLj1SMHBwcfBn434G/Bvz7wF8A5sBfAv7Ixza6H2JcKx02GRyJVQu2UCx9ktPqfrsGhGDdf+0REnDoeQhBTvl7/4cuDao3l6NFChmHFCU9pKU/GW1R3wWedcheaSHjkQSqQQqYlOQU9M6i5eY44/5KiLOPqkijeP1+vD2kq/86hcEnYRKGxMYjSfuDZWKq6l0bNWvMkOSvRSEvOsD+r1WAo01idwyLKl24QLdR58hLwmUSnMYh+UwRHqwTPnYUTowFF7XM4+WPiImVAqOLkoTPdA4S0KXE3fOORou3hRe4W8twkvx8wyUiXZqo813q2I7bodtFlOSuQAoqkLFNMmhdZN16zpvE0kdWCpU7rmRek65zjcC1aiu+ER4pYjukYAHY0a7VeZO4OpbCsfLC9xF1scTUwUkT8bHFGcvIweNKvSQ0Ed6onOuyka5Kq9l2jRLWvSSouZH1rPluyBP6vRQGeNAISCT+xrtrZrljmsGjlRL+dc90DJ2mNooAQACWUZ6NwgjOaSe3PFx34pmTRDIbXZ+UILTCe/B5oouGOouctOnCwT3qs9KEoZByCnEbW7i7CvzUXuRRBfeWnrNK1vAynC1c2g8W2Z9Ha0g2CaQrPse78TJfjW6mwsHjDTzeiDFnF2UcYwvvnAfmhZgnhgSVcpQuew72RdBaC8bMCEzMmMRZ7S88SqyJjJ3lcRWJKdEqHLAfW0I+e2rtFPVeOacBHq09tjPMVwLd/PMHsw9Y6W1sYxuf5Agx8dfffdbo8M9sIVo/UDxfjPzWSacy7tv4JMVH7Yz8t8AfOTw8/PrBwcGf1e99Hfi5j2dYP/w4agJ/6JWCYCJ13XASJZGrewKvwnV8kmTEIyeyk0xOhseZSHWGIDK9TZCkxMYhkZuYgZ/RFwMZMClh7ES9Z6mE6JlCwVK8pPCk3IA2CsTGJzn1vFKIglSGXNuT+MJewW+fNNwaWR4lebc2DEnYRDsJ1ipZ28BEceoGmNnBewLtZtyaO87bwFkrCfI4hynSIeqhTkbnqnTKhUgqM1xYghocrhXutF/AooMiyv2BXMAaWLTwM1ccf/jlCf/oYcU3TjxJk6xrE7haWjIrWH1vwGKYF4arpTjEP1p7puqk+soM7m0ivpNx+TD4kGTAVMnQPZl5qvK3T+tAaIYOCBZ20wA/6uFDZQZv7GRsQiJi2SsMt8aGexuPNQLB6+d6rp2ztVcjQidFqU0D32KvFKM9N5aOSG4ST6qAMaLW9cpMDPralHiw9tLRMRmfmQfOu8TUALpvGg/Xp+AwOOA8JGIA62TuJpl0YQBMI0Vbvy9BiqKoBXWBSOReHVlmheWk8sSUmGSOq5N4QdL2UWFzZuAIYbVz6HoejOFnrxSECCd1wBO5t4rMS4VLdWqaSK8259grDXWXcARxedf5z6K8Z1+g9/Ckl6eOncLwrYXn1WnGLLec5+Krkhi6bZdjJ5f327RDhyI34vRee3nPvhPkjLjSxyiwybWX529kpHvYQwibALPCUJCwYyk06JSD0u9D3SdXJgL3W3cJa2Fj5H4+v5dfyIuPMum61QoTdEnWM8bBD2ii47w1sVRd5KSJvF6ImtcXr+db8vo2tvEpjP/vUcPjaoBYznPDv/nq6Ec4ok9/3Jw4Xps57uovvy7CN05a9n/E49rGs/FRf2PdAHo4Vrr0/09NebloEiMnng+3y8TUZtQ+8s4y0no5cWyQ09oeS++ceFPkzvLKzBGAB6vElTxRjC2Zg7fOpDgBuUb2ATOSGfAhsVRCMpq8hgTzQiEXmlzuFZL0XB9b1l3i6shydZzx2sxR+8S3Tlrub5AgSGwAACAASURBVALfOOpYdlrA6Elx5iRBbLQr0UbxD1GBLSKQdfKzQYuDxJCUPd6IKldvtDRVR+k6Sucj16Q+aMG2SXBu5VR3h4SzlqsjQ7MJVA2cRFH3iUjR5txg4LcO8J3TQBMqro4Mf/IzY+a5kIH/m1/cBeD/+PaSf/K4xYfEfOT4zEzm4TeOGtadmN89aRJVF0Tpi2cJ3D2EaJ4DRpWjjHiR7I/EQNFoEZpQYrwWLTHJ3M5yMMbwSy+N+MaJ587S86QKTDIjUDeFh/VKZC5IkuiVcG4QiOAok1Ov00b2w2kryf08j7w2ywlE6k4c7Ne+5UohH6DWGH7heinFpINvngVeGhm+c+45b0Vu9o2dnKd1xCdoU6DIDLPCkrqOIgePwUQx3ItCb6DMZa5y5c20SRL1iNGujUj5Pq0i4zzKc3HpyS/QDkCQgmfdwToB2jHqQmLRRtZdZNFGUhLYX2agc1K47eaSmJ+0AlfcqDpXZgaRiEYTchgghw5J+O+vA1Unimm1jzypErV/9gPq+egFFVpkrael/OBnZ4531+Giw9PD0YyRPezM8IHX75UQpRgxiKpbz9fpIWS7eiDXBhn3qoPTCs6MVKbXR5bSRjovZonLLrGfa+GskLebY8Npk9grDE0yvHceL8aw6eDpRtamCcJ12YTIsv2gO9/GNrbxSY+vvPNsV+SPvz5m3H8AbuP7ji9dL7i7Gub2q087/mjxIS/Yxu96fNRi5DeAPwf8n5e+9+8C/+SHPqKPKYxJ/NrjlqMqqipW5HElCaFhgGuBktCRhOfUwBUbubOSBKMN8hrbBXyUk+I+ekjJ5WgQdaHL8qIJIRMTBWJjjMBsMit+CiGKeZoziUebIH4MPnBURx6sI50m3F2S02+F8JNZgU955LTaM0DI+vSk/16ftOfI+zWq8NVGScJBeAQLk4Qfo6+x+vr+emUUdaIuJHKXeLgUOJBlOM0Gga0kPxDJPfJep42n8pb768jP7WfcmmX8/fs1qy7y3nlg3UUKa1jUkbdDx+ON50kd6EKkdZbGR85aOYXuIWr9/TZIcXjeSaHWQ4qeVonCCc/Gx6ET0osUgBRPK/X+mBeJX7lXse4iXTQYI+7fjVdy+uX3DHJ6bnQ8IpkrxO5z5UCc1sJVCUnm+BtNx6bnRjg5tV/UgYh4p/goZOqNTxgSv3nsGWWQtCP2nUVLE4VLkxkZz0kdLuBTziQ2yn3wWhwaxQ75BGeddES6JPK2jfJMgsKkGi98oZ47FJDXOCRJ7z1AQD5Q1kGgXO+tOtpuUE7r3cydjqsysHLirTHLRR2qUe6WswMvK1w6IGiDFEIWOA8yp7mFZZbE5T5++AlJg8AuI7J24yBr8bgO1J062Dv9d+16psTFgYPT5y4GLZjCs+IP2rSiitA2cjjQS2P1e81oMXdWRzb6wlUXWbdCZB9bKV4aD4824ouy7NKFollkgLCttGs5NsJ9ubfy/OrDrbTvNrbxaYvaJ/72nWeLkS9vjQ5/KPGL1wv+2iX429eetPzRV36EA9rGd8VHZUX9ReC/Pzg4+H+B6cHBwd8F/jvgv/zYRvZDDoPhpIncGGesI0xySxMkWYg8y/sISMKcKxH4vAUTE12IlKoe1CfnH3Zo0cNygl6/hwk5BviPRxLCQvHfbej5ConSWSGEZ4bHVeS8jRdkbmuVIM8lnkQcOBHPcya+V0SG091eIriLA2eiUQnUyz/fJ3sZg3Rpl1TaWO+7J4L36KzLhOkKgb2UrjdSFP7LN888v+9GyVkTeGvhmWWGvUJY35lNbHzk7kpKoc/v5Zw1cuKuCrTAd2/ohCS+IB2Asf7sUR0kUdR7Ig1j7eFofRLsrHhjjHLHtNBEWQuOy/NsUTnXNMjdGiPv2XiBvjk7eNGUToqPKgxJa78GzsD9deLVqaMNotC0aCN10NaGETWxqyPHSpPoUWapo/AgciPtt35vZHbwOumlhq0dOkAgnh4pCVwpKaRvnF/aU9rR6+eph7f1hUhfxPewpONKEv5pId8bK1ys923xUfbMXikduIQQ8IkyBp8GaWt3aV2i7if0OcwslNYwzj/avu/5LhZ5j9L2HiFD964wWkxfrrwZxtPv58ggw3sBY9SvAwOsKsZh3vq5D31H08j7O8uFLPZOZrk1MRcHBW0Ukn0/D/HS/xPieZNZCMkwzdlK+25jG5+y+Lv3as674cPmxtjyr71U/ghH9OMTX7rxbBtk68T+yYuPKu37bVXT+uPALyPGh798eHi4+jgH98OMmIQnUHlJfOe5pVR/gSJIstkyJNj75bNwj3lp1cRNpGm/fdoKqdbCFSUTX/71nyHmams1bcv0VLnMhuvmVmBaotYkCPeZPjPjzHFt5NgrIk1MLNTnZKcwtCqta3LoukF2FyNclN7BuQpDotgnkRcJs37fINCwlZfXXS9hqQVI7uS6Eyf/3imcre9u9Peyn8upbO+dUVhJ7LoIEwZlr/79SuCVmUi/LtrE2gscxSkP4N7Ks+wis9zwxm7GoyryVE/6Z4Xj2sjwC1dzag9vLlpGFkqXKPRm2yTzXfYqUxZ2SitwrQRnrZgwznK5vy7JibQxwnvoi4UM2C2EizHJpetwdZyTE+iC5zyKqpVhcG+PWsgVGbw+M3TRcNpEJjnsl5ZFG6VDlkROFuCsTaLk1UtBI0lxZuEP3B7xeBO5NrJcHxX8nbs1B3sZ9zaJK2PLODMsmkgTEtdKy7wwXMkc9zaeq2XHz90a8c3TjkUduDkW3kjvPdIXJXu54aRLvDSxVD5Rh8Qsh1lumWbw7UW86GY5qQ0ZKTfHmEFwoeeQFG6AO+ZW5tCHJKaBxeAJkmsxNHWGceG4NhIDyTBKrLpBtW7iRAb5VBUKjHZZQAn/wE5hsSaxbOJFl6yPvkiyDFySqyPhYzURprnF2sjUGRm3MezkkfNueI5eLmTMaw9lUK8gI747TVB4mW7w3AgELOl77hZSTJgoXRmLwPsSsldGyt8KUV67V4jz++uzjL2y5Z1FvOCo5E7gdI8rPShAOCzWwm4m3jtjZ3i8lfbdxjY+VfGV51S0/vRnx2SXTwK38X3Hz17JBdmiH4v31oGnjeGNH+2wtnEpPqqa1v9yeHj4F4G/8tz3/+fDw8P/4mMZ2Q85dkvDbm4oraMwcG/jWSsZN8/0lFpPqxNyall7PQEH3k9CMD6qIk3kGXx4fyLah2WQ++2TImfkfSbq1VA4w8RCFaSwuDm2kAznbRCOBpGNN5w1niYaai8wlGWbFJIjCeFYib59h6fRMWdOIFRRDtHx6bs7QJkZipje5buOauZooVH4Tc8XGBUwt1K0tFHNEBOcJUkQR1ZdzPuT70tJYY6cjNskCd2dpRB4jY7j7aVnkhn+6tsbcps4rSPfPous2kCIsPTxwohufySZXGkN48yw7uJFB2qUw66Dm2NHTPBgHTABVm3kvJV5y4wUYG0UCFcvWdufNBstZHYLw9WRo/KetxaeZQsef7HWuZE1mBQwzcSxvAsiC+sTvL9KjBR+l9u+syGyrTczi4+Re5uER/xDJknUwWa5oQuJ3cLQhMT1seHlaUZM8JN7Gedt5N6q4teWl2B/wGnTMSlgVUZO68iigpMHtchCl4aD3YLvLDraGFmql0VMUhAaA4WJFEqUflLB4yqKzLRWz72pXg+5cnYoShzSAQnKuWkVPnQchK9ljIgmFG6Qf/YKq1q0idPWXxghFspDMkagXH33sdACnKS8iiTKUjlwXEcyK10y66UbFXU+DVoAIXt9nMP1kQOTeLm0XC0dyy6SWXnOjpvA042s4TiTa2UOUrLM84jLDaetPLe5FYWwvgNVWvVeUXjXJINrY8txE6kbeXacGYxRfZQ17LljdRD56/V55OHGkxu4Wjp+6mrOoom8pZC8sUoo94IQ10YZ09gJVyiZrbTvNrbxKYqzJvIr957tZm6NDn94UTrD77ma87Wng57kP19a/pUf4Zi28Wx8VFDxf4RAtZ6PPwd8KoqRz+/kfOuk49cf1NyrDZukxM8EUfHvLZKM72SSpF6GVS3aZwmsfSQ+WEa2SmD8oOjUeySc+N65PXF+CZb1dBPkddrVqH1i7TyLBgqXSFES/RY1KQxqKIgS4PU0v+d3wCA73MOULvgQ+veQJHFbIxj4zAqHoZct7u+z0xPbdeRCCrW/7xyFH4Xh9LnlEtn50pwsdJ4LpIuklAdypHC7ViZ+66RhUUfmI8O6SRw3UkR47XbMMpHE/Qf3a+a5dBhOKoWoJSEopwD3Q7goMHoOR4cUWMbo6bqOubs0RoN0ykyE85SovReYTBAI2uXwOgl1Bec2MS8UUuMhKDxr0yWBJZG4Npa5fVolTpBOTy+j7IFNhNRC5+X4/Kf2HYsm4qzht447vngtZ+zgL79dsfDfDS08UwL4ySYKXwa5udLCvTbxcNPwmZnh7lI9ctLAd5hb4Tat49BNu7hHjTnSHdsorNBYud9+o5w2gxx1D62KqMxtgtDIWDCDx09h4WkthSxG9sRJgiuFPAspyTOZO1nXy122Pjrg4TpR2KEj43R/nbaypmOjz0OSvXreiVpVTIkbI8s4sxyethjE6HPR6booXCwAu6WIXVQhXXRBNmmAW3XI8+fCoDq3W8CdczFf7IUOugR5GDonBpmP3pMm1yK97w59dhb5+tOaSp+7TV/86KFDjGBLkZt+KTMUDn7p1laBZxvb+LTE336vuji1B/jc3PHzzzmHb+MHi1+8XnxXMbKNT058aDFycHDwn/Q/d+nvfXwOOPpYRvUxxH4pkqkWhTZkkhQUUYnLSWRZiZL8FE4kRY1CIKwf/Ar6k+ier9GHYzBX68nUU4XsTDPFpRuVBTWGzApcxFlD4xMrn9jNLRFRr1r5xE4pcp+rkJggSZXXQdgk3Za5enB0EcjU8VwTopEWKf0HXdGfyqIqXAq5eWlqCSFy0kpHyOoJb2FVcUt5EhuVi41JTsZ7/dQQ5cTZK3Rp2Q3mhYXRedSixlklBjOQvG9NLdEYKg/jwmKN4eoEjjtpW/Qn7/sjRwiRVUisg5x4zMp0YaTXd7KcnlrfGDueLDtqK+vZn75fjkznpydk5wpNG+VCkB4pF2EUNOHU2y4VejfKB+PE/bFhoSYTuQXfybgmGSQMP7mfcW/V8Wgt8zbP5b7WXsQMPFKcfmHX8XNXS6qY+MJMjvfvrQPvLgPRDIns82Ccfn9mSNE3zgc4UAY83Mieqrx0C3IGF++UBqGF/oOhZUjm0etNzSB37WPCGNm/ay/FSYlyL/Q1nRbYPRRtr1Sp5txy1AR29GcyC8mKx0wbBebYKuneGlG+erIZZKYvf3h5ZI9dHcucj0vDSZ0ImtAXmRQ8Dvm6ifDKxLJTOppoeH3maH3Gm+cdAZGlTkbnyMha95ys0mlnJ0nB0483hME49eoIvrCb87j2zMsk/ipJnoGohfHYqkmlkfeaFlqcOoF+5cB+afAIpPH/Z+/NYizL7/u+z385y723bu29TPf0cDayuIgUaZGUIMl2aCuxYcXIZgRJAMeB85QggCMkjwkQIH5LHvLiIEEeHCMB7DzEia1YcRQtIU2tpEVSMjksztY9M73VeutuZ/svefj9T93qkSgNYDanCd8fUKjuqrv8zzn/c+u3fJfSKEKM5KVw4JYuMLSwXcgU8MYg8IXrBX/hzmBNXl/HOn6E4v3eIn/llSFKrSFaP8j4wrWc/4HF5f/XxcizFX/SX6y/mr7nV/4Nkt88Bv7a01jU04ppG1j6kPi/kkVnStRzfITrhRLTv1a6rFVccQd6Cder04WriaAluSdniV+RkuJxSmT3CoNWgeuF5s5mhiLyuPLM2shZgiItnah1LX1SY0qJc9AiWdorXTmkKx2dwGEqUrKfkuMoiC/hw1jYLyxHlRMJY586ziRokoHnx5afvZHzB+eeOOuYIJCo3uAxT8nSONdEAiMrHJGtAkqtmDnB+O8WigdLKQwUkkyVFm4NFUd1xCVeSZG66hZJvqoIRwkSVBWK0oDRmo9tWXZzTdMFZilZb7y/NFPcSHCbRRfwITLzQvzdGyhaH3i4CNQ+EJQcwygTKFWT2v1BJfM4KxOJflqQ+OGMrGbRBQotxnI9WZj0vU7/yQLslYrcCDzm0cLhUwIdSdMHBzMX6UKHTQXuIEHBjAKvI0Up0669gcbHyG89bnhv4bhRGka5wkfFvWl3WehdqQUv45LcTZr4JKlmo1ZKaFuJZ0H6mVUylblqbNnDCnsn+90y3SMDA0ROqsjAaGwOdRtRmUwBzhtRDuunPj6sird+j27nhlGmGFnNpI1cLyJzDzvJgX2QSP03B4ajOjK2sm8/s5fx1YcNG5DuW9nwTZC9MbDw4jijrTpe2i947bzj7aknM3JvLjtpNPRFhYqBnVIEAiZtYNHFS1GKnULjUXTBX97rVl1RBfNp2onc612QvT5MRZcBXr/oOG24lNXueTK7OZym9bYezt1qSqiQKVWu5BxcNJFpJ2aLN4eaOgh3qXEhmWVCpgK7heXVMvKx7Wzt1ryOdfwIxUnt+crDJ+fu/9ZLaxWtH3S83/zwO3NRqlzzcp6N+GOLkcPDwy8BHBwc/M3Dw8P/4oezpKcT503g9QsnZmNKPB9maVJRWEn8Hy4Sxl+tcOBGSde2vtI17jv6V8Mhnfe545LbYJXAvZSCizagiUy6QJh13BpmSRbVM09chsbBNCRCeoKVnDeyvja9YfACcTKsoFKhk857D2vJEk6+idLlP6kds25VhDwBNfPwcOn4naPIRRtpvXBiApJs6QjzKAnSog3irC4oIk6q5BaedtHDhXTHM7WaHFUO7s/jE0T6LkGMrib3XQ+DUpFxBruFFCiTVoozHaV4qNO/+2t20QYqF6TI0XJ17i/EwTrXMl2adZBloPuizsvzTep2T5sElenX5AELp1UQSIz9o695HwsPsYpsFZHpRcAnOE3PmYmsoGCLdsUViBFswtDNXSK/W7ioA6dLGGUBreDe3JOnbvzMrYqN909F+vN7NSq/kn6GJIkbpfuukOLQJW+PXs2rvy46vaBLUx+rYdZ5ugQFPKm9+IakKZlHkv0mHWxv+NfD30ISfDiqPHkjho+5luJFxchJHUXNLcoeerDwFFbRRcXQKk4qIXJXqRKLxAS1SrwpI9hrG+D+wjHtghgLtlIEdWElvW0RSN/vHXfcHmnAcNp6YiqYLlxARbVSkkuTtxC5lD1uWcGzQApOjRhLtt2qMOynpDpNUo4qea1FJ+dfpcf0ny26TVNbtYJtVU64JC5CEyLzZtWsOK4iF21H6TWbjxsmTeBLt0t21kXJOtbxzMcv3q2lEZbikzuWg+01ROsHHS9sGK4PNEfJVLIOiu+cd3xmb2048izEB/prdbUQOTg4UAcHB7r/enpL+8HGG9OOgUGgWloSyCwlUlWXYChp+jHMJFmDFea9V+L5ftHnLJVfOborneAnCmovpoADo9jKDQExgQuJjFpdIcv3CV4vPdu45H8ALFlVkIEEiUGgVX1C3SWlH6WEKG/Uk8m2uvJllSSJ92Zi5IcSaFYvL9um5LTuBNoyLuSJwyQlGlOyOkoTIYMknD3p2CBdd6NW58WoJ6V+r3aeVZRzsl2AD8nTJT0wJFiZSse2nWt8EJWxzklC66Nk+YVRbJVKcPVKXnORio6BXal+9X8EAivOS2GFZzK0io1czm1vYPj+sKTCMUHAmlSM9XF1kmJJk6v03rnhsrtNlOdnOkkpq9Xz8qRMNu+EeP8nsQGurrM/LpWObZCtJKt7TkeXrllmkgIWycOmhwMm0YIbpabQmtrLMQ8St0or2C8MTVj53SThq8vj7/fa0IJRYm4ZY2QjUyydFCQWgTNWDjbzXp0sUnWBawNNZuClTYtViT/VyXcXYH8gogUAF06aDwYpUHS6F/v9r9M+jFreY+kjCxcZZZprpZbCxUPrIiZNynQUvlIIqQhI04teyrov9vp7skH26PuvSe/TokicLVZTxH6P1HElohFUMt/M4bSOaCJ1muKZ1EgxBka55qhRNF6O/Y3pChu9jnWs49mNv//2+1W01sT1pxFKqT80HbnKIVnHhxsfVE3rFvC3gD8DbL/v1+YPP+PZi4smkmnFF6/lhGXgd2eAlcQhInjsDRXJjEYpGOrARTJhi04Sgj5JnCdyu0IKBps67FGJtO7QyuuhZPoinhKaVzYt10pxVh9kWhJ5wPkAMUiCnuA9GhgnuMrSrTwampRQay2J+VYmiXPj4NoATuokOWoVmzkUmaFuA5UPBC+QrsjK32BguXQh37QKX1h2c8/cwbyLxFYKg2Vye781MBilOG08Vgs8K6oeLiWjl1xDXsg5mXXSRd7MITMKEyOn7apzfJmEmVWy+uqW5dWtnPfmjkJ79sZCRF4mAvwgg5tDwxev5Xz9WCjYN4cCq6k7GGeR54aWqBRD47nvO1okcRsYwyiDzcKgYuRbJ50UVUjCP1ACbWsCXBsYRi6Qq1QlVlxBnHKZ7O4WwgfyMakvWXmt/tr3tYVRKwWqgYWbA82DRZAiTkmhN8hkdGx8ZJhppm1gN1dMOznXw1LzmWuKb5/5J8jcvRq9UgINnHUrBTUF7JSwYRULF9kpFKe1qHhliZOxkcNOpmkJNE4EGzIFNoc7Q00bFdYobhaKUaY5qT3bmWbuPKWW/b5TSHW6dJEu/X3t15cr4URopdguNLYLbOaKTBt+4nrG21OHImKU4gvXM96YdNQ24ILi5S3LbmG4NTIURvHnbkf+wVtL3pyJ789Lm4affq5kr1C8M/N8+Z2aEOHlzYyTJrDIPMeNOKRnJK+ZBJkaW2iSgcrn9wvOW0nk6y4wc5HNwvDxrYxHC08bvBRaIVwKPfTGhjKZk/Oday6lo89bURFzyEbvoVpdWBWFXeKo9f40lRd+S5agWVrBnZHl3YVjlGvOGjG97IvezCgyrag6cDHShXjJW1rHOtbx7Mbjpec3Hj/pefFvvLiGaD2t+MK1nF96Z6Va9rXjlr/+8dGHuKJ19PFBWY7/I9KU//PAl5Gi5L8CfunpLOsHH1uFoguRuwvHzClJGOKqU3rRiaO21YFxDuNccafQlFZxUnsUYsDXRni4cOJfQTKTU4L9H1lFF2QKMsg0u4VmWnuiUhRGPDG+8kCSv50SXhrbZLwmfAPrI3XqkPsgkK2+M35zqCmtxk0cqu8MR4GEaCSZfG7DUprAOFNkRjHvAkMNRa5xMdA5Lp2jY69ehCTHW5nGWo3xnmWrxN07FSujTLFdQIiKs1Y8LUA2T6FhmBl2Ss1Z4+UcGtiwGq2hBxMVBnwU0nmvYtWnS6URvH3fcXZRvBJ63Pxkkbr6RmRv+4W/PXM0Pkp3WWnGmWKgYdF5jiuHMVLwbVrYGmXcGhm8jzTAcwNDaUQWuEnSX4+WYWXsp+C8C4QQ2Sk0+0PDceF5dxFYJlJ6plICmgqw/VKxX1rpxgN3Z45Hy3gpJmDSseZGCtrXkyeGTQXsyKrLQsJHSZgLI93xwipqHzmqA8e1FGQf3dSctwGthAx+3nqaALlWRBVFXjZNf5SCo1qUvUaZ4qM7Uhi/Ne04rwLXRpaXx5bGi8/IZq75yRsFyy5wtPS8s/Cc1IGTJjBtvEyUlJCwm3QtKif3g1UyZbFJ9MCnqdG8E+ljozwhwlEVhddkYGhkQkJKwv/U9YIQImWm+eROxnYua33tvOOiCewNDdcGhp3SMM51mnApXtq0nG0Gso1c5I7bgNaKa6VMWWovDYZAmrxEWecbU8ebU0dpFHsDzYtji9Wan7qZ8xfvDPnqo5r7i8Drk46HlSfXDh8FAngpDa3S8SMTnp2BognyudJPQ8q0XwiiuBZCUthK93FmZE/1vKIqRDIib88cMxcuoVoWMLZ/X0WIci2sksJkqx+rrmMd63hm4x/eq55QnvzMbsYrW2vxiacVf3gysjY/fFbig+76nwZeODw8XBwcHMTDw8NvHRwc/IfAbwL/09Nb3g8u9gvDe7PAGzPHpIbjSvDtJiZfBJJzcoCLCmZNZFx4hgZuDA3vLDyLNrBTiFP0rJNu7ziTycW8i9wZRXIjyLVl61m0krRlCu7WKygVwKSG328cNiXihYG6lYqv54N0QS7Q0MDDRWC3CIwzeJy6zpqVatY4h6Olo9DwqILrpRYSvI+cNcIyCGnqUqdixyJKUrWHG0PFeeOp2sDDRbw0YRtaeLQQXojSkdYlmBQiU5xpuF4E3psFqi650gdwLogYQJRzdNEK1KuXG+75Dg2SiPnEA7AKXPB866ThD06dFItRCNFzLz4rG7lwUM5b6covPVzM3aVYQO3lur4wVjyuBeplW8eJjgQUhYbXp4FCKUoLD2fymEzLdVEJGjNrgkDdcngwd8w6kXTtp2Iqyj5YdHBzCC+MMs5bL6R8F5k0UbxY0uNjhO6KRHRfyDRdgsFlER+luGo8+Bi4UQj5v4fxxTSJyxS8NhGy9wsbUoCdVbL2TouIwMIlxS9k7/XQtEdVYNEFjjNF5SPGCJn7905qLIrCKm4Mcv7gpGWSZNh8iBxVjqpb+ai8ceEptJyDflK3TNOaoZaicxFW/BMbZOL0yMl+H2RgVOC1c0mwDXBnZHjtrEVrKdC/dKtkUnt+/X7NvA0sXaALIsk76wLfnXS8smV5cWz5J2cdw0wminWIvDnzjDM4q2VaU3dJUjrdY00Sc+iFFnIDJ7X4jCxGgc/s5jxcBP7O4ZwXNw13px3nraftAl2I3F8k2e50fRcethK/49oQTpdSiLSs5LRnfsUJcz1PKkVIv+9NJIcKTpYxQbJkCtSLalRR1m+BQRZQEW4X4rOyU2he3Vxjztexjmc93q+i9W+uietPNT63n12aGgO8fuE4b8KaX/cMxActRnoeJsDk4ODgGjAFbj+VVT2FOGk8tzc16Ix/cJyM6pR4VMSYuBeJC+F6nLgS2czN3HBgDae1yY9CUwAAIABJREFUx0WFUY6bA0lk2igmdpFIFxSf2ssIUfHmRUvlIrul4bxxon6kpXPak817adXNTGA4g5SFdInEbpQkbPulxhCJCq4Xmkx7Jo10m3sZ1YEx3BwqlILrQ0nIdzJNpgRPXrvIDdNyr4PTKnXzrTjNf3KnYGCg9ZFjIGs83glsyCiRJw5JFWm7kPc4byLbmTibVxEGRlGOoHOeoDSPFoEA3BwpNnOB9bQRYvJv6E3vejK2A26U8MLY4iO8s3AMci5dU30tppQkmEuemMUbhWYURKmqdpHCKnYLJdyDoNgrNQ7Ic0NA8YndjAdzz5YVA8vCGO6MNEeVY+Ej26W8nxjvKV4eW87biAsBo+G0iez1k6lU3G2V8MpWxs/dKThvIl8/alh0nsKCtUIQbxIXpp8SiLyzHAskXoqBjczgQuSzm4ZJK6pmN4dw1nhcFCljEAPF0or0qzaaIgZ2B1GcyZXA4DYUmDzBgNLEYWAVxMhZI4T+l8YZe6XmpBKCiNKKj2yI4+CsDWRa5JTvTjuuDzTnKlzybJSKVD6ZWSLHlQcpgIxKHhjdCpJklEy+QpC9d2tomKTjMkqmXkWmWCTm+0e3M2oP540nhkjlI5lRjDLFeRMJRLYLzaITkv9eqS/9aJ4fGVzaFy+OFW/NpFBRgogUZS8SUdwKpCrEpKwWwUfNjZHFKIFAvjcP7OQao2FkNEeNZ69M1+0Kr0YDn71mKLTitYkjj3KPB79S47NKJqNnldwL/XS256VZBTsDKVB77pfWycjUyGdN2/OkgO1M8an9nGuu5idvFHxuP1//cV3HOp7xOKo8v/0+iNa/vi5GnmpsZJpPbFu+fb6So/mnxy0/9/zal+nDjg9ajPwO8JeA/wP4f4D/DaEffP0presHHhdNJFeKz+5l/NJbIh97nFRrQJKlJiVtQ6OonCR28y4w72LicwSmnZB2t62QiZe9ylWAixBZdpHKBc6qQB2lyz9PJFsXknN0aqUGJFHrISNX04eBlZ8vWlh0gcwI9GO/VEyUQilRi1KpSx7wHFWSpN0YKAaZZiOT6cikcZw3no+XkXyYs196nI/MvECOXjtruGglmYKVFKxBoDUxTYG0hr1cUVrNRevINNReJEaHVs7p3MFzI8WsXRVV81YUpkZaNo1m5f1gNewVUozdGlkMklieVCuJ3X6cNEi7dSsX+NzjpWeSFi3Jr2I7GSHGKMaRuYWzDmL0GCUd9XcXnpfHhsZD3QUe1IGmi0y6lLQnyd3aR+7Nvaw/LaPuoUgWQlJP6hy8cdHx1YcKqxTHtSTNVisyIq2RqcEiJGI4gBNZ5YFOiWwqFp4fGr512qY9qdnMpUCZukjdBK4PNPsDy8O5o/KB0ihiVORGM4oRk0FpNfPWc76UoteHREpHCrq93HDaeJFuTgZ+w0yz5SKTJvD6RUc3iWRKsTdQKKUYWs3toeaeDsy7gEcR8dRe5LHbVKzqRKrOFVzfsMzbwKIN3N4w1EHhvefBIlJ18M7CX/qIGCUGkdPWyT6MUPuGVzYtISomjedRHdiwii4EHi8E8je0UjQunKJqA+/OPc5riouaDSty1DeGhlknBWEMwl3peR2LbmV62sPzFHBae37l3YpFF7ho5bPBKCGxD6xi0kjxPLCazUyc24/rwLyFhwvPdmkEurch0M1FF5m0oLw0O1r/pLLXQCdTzrRHQrWCvPWTss7DXEVs4h09N9TEGNkeyDmqvGK30OtCZB3r+BGIf/xu/YQozo/vZbw4XkO0nnZ84Vr+RDHy9XUx8kzEB935f5VVrvyfAv8ZYsj83z2NRT2N2CoUmYazOuBi5KgWMrFGkoJFkAQKYNKIBOxuKQlWGwJHc0m0TOIDnLdw2kqBYLRgx32Ad2adeGoEgfHMiVw0K2gPSLJM6pLGKJAeH6UT2nedewlXTTLlc/L1tdox6PkVaiX5K9KvAs95VEXKVjxMtnLFtJWu8ptLTTn0PFp4tBaCtVHwuBG4SESUmmrkP129MkhsADwcqcCNUhLI41Z4HMNcktrjSs7pbjqeJsDCxcuuceNWUq8hJh+KCFMnCda09QLtSg6GNQLRKpUkaD5ND+oQ6DrJGluXOBVKOvXvzCM7paLzgrc/r5PCVYy4CLVzdBEumsBxLbCoNhHtYyoWGw+LNrKRQdWJtHDPC2ncisR+eT0TFOl3j1s2rcB1xlaxaCNVkEI1Isfba3d0SGJ66gVi5xNc7punLR5oQmDuAscV5NaxaKVImnWRED1LL1AhpUTJjAiLRB5fOPHSaRKsqwkraV1F5M1avFqMlmnY96aOrUxz1nqWHkyIbGZiaHhSRVrvuTHQXHSRaRfEb0NBGyJNBz7J6sYg1zkCg1IJD0RFrEnH7gPey73RBTBOjrsLcq1z5Bz00tCPloGzpuUzOxlBwaIJLLoewiYbqXFy/2xHudZzJ9MP5QNHHZy0gTenUuD4tP/Om1Rsx9W1WHRSRDWul1yGsyZwuuI60iHF3dAJ9+asE3jb0UKeO08QvJMKlk4EBlofUUamoP097xCfnnjldXtfov5ndRRxgYoVbKvnnHS+bxwEnIeoPPs5TBz89/9szn/8Yxt8dn8tV7mOdTzL8Y/uPQnR+ldfWCfEP4z4/PWc//l7KwWzNW/k2YgPVIwcHh5Orvy7Av7mU1vRU4pXNzPenXl+a9IwTokDCUKR/kmGJCONkyQ7Mys/CKOFY7KpJSm9TCZSRqqUJJX3lxGbcP29U3aZfEISyuiJbohNKl0+rH6pWSWtilQ0KUn2eslVnZK/ngjef20Wws9okoLVRSu+KvulYV51dI3Ah44rSWyiWmHe+6THpu8tkrDlyRHaGnmPswTfaRSghXg97SRBGxj5fWGToaGHbZN4OTE5yCPJlEkE3sbBtZFm3gnZeKBgnoxK+iQeVr4vhgQLCpIEdyk5tQkGt3SRodUMNExDFLlhIxOMqGAnUzysQ5qUyLQjJkWj1sv1BjnXw0xORm6uFFKry34pZRyQazTpYK/U4nmiBYcW48qn5irHgPTvRSfnLUQhNY8sGCXKVirB1AojEKcYIovOo6IUzONMcaM0HNUCBey8/OyikeuudTKvTNdm6VZwxN3CXHJUHi47Wi/XY5TBZm6ovFzTrVzMOB9XIcniioSsi30huoIXtaqXs44MDRiU8HpcYCtXPGzlGuR9ayOs1MY6ZE+qtPEVsuaTJmCUZn+guDuVG6SHMfYeI61LZPQEfeuFCOqk2raRSRHp0tQl+V5eyhtHEnwrTa6KJDLQ3wv994DcC9u5TFZUTHyR9D6bBZdQuWslPFgKdM1oWWN/7RUriFbPn+o/F8yVn1ukICnT75vE9SqsGD3uD+H2hqWJigGKnVLxi3eX62JkHet4hmPWBf6/9xkd/vxH1hCtH0Z84Y8gsYcY0WvH+w81Pqi07ynwFURJ68vANw8PD+Mf/6xnK3YKzZdul7w168i14uUNxVkXmaecMQZRHtooFEpH9gpFZjT7A83rkw6tBeKymfw0BqlQEYy64pVNgw+Bt2eSQOZaMcigTjiw0kkCsXDJi0BL0veRDX0JF9odSlKzTKpXfUGSJVjGwoHxQFJk6pAusvPy2lbB0BhGw8jjZaBxEa0VL29aCqN4t4Njr9jNFedtYJiJJK3VKRlPBVeeCoFAgmaVmiY5+VkNUWkGNjK0Al9zQTO2AVPIFCQijvM3B/Co8iJznMdL1ahZJyTf0khy9oktw7iw3J12bGSKJiiWzlEYWV9AIFrjTNa4lRvubFi+PUlGLbkopUUUt0rNpIvcGhrh4XSO0MHACFlhwyZVMjwbRoz0lBLIzTKsirq+QNy0Cp9HciW/11qSy75TPbCSDDc++cMgML+NwjBtA9FHagU6Qbr6Y87TsWnknDw3Mly0nq1csXSJm9NoZolA/sKmkEyWneeiiVwbWl7e0tzZMDyuItcHlo9ua751KlrKG4XwG6ZR9urEraBJt4awVVh+Yj/n25OO1kXO28DLY8tJHRgY4QXdGhqsVlIoAftDw7SNtD7y3EhjtUyOZi4IJyZNeVSEmyPLRq750nbO0Cq+dtzSec/1oaXIAhmR40Z4UDlyH1WJc1FmaTqipJipPfzEvqVxmvcWjUw+Es+jC/LYhUP4Pl6uz1KJlPFZk4pRBS9tat5dBHyaVOZJOEIjXkNdFP7LMDUTJk6ub9M3JOKK15Fnio08ctrI74KTInJgFJ2SIm6ntNTOpXtEivnrhQhMEHuuF5ylxlxEoIyXPieISl5oYauQ91mmfTbO4ALYzTWlEUhhE4U/cm/RM7HWsY51PIvxa/cbmiu36Utjwye21xCtH0Z8dMuymRAjAJM28ubU8dGttejHhxkfdPd/EZHz/bPA3wC2Dw4Ovgp8+fDw8L99Wot7GnFjYLhWRPKBZT8oHi8djyrhTigEbtR6eLiMlNYTgY1ckkIXZaKgE85/kLwx2hB5Z+4uMefFpQQtkBKTzMBzI2kH+9h7E0SUUigC1iQCsFl1Tn1SyuoSXrzv5hZIUeQtTBpJjOcpwTqpvRC8DeRWUXeBb5y0wk3xMCoiWmn2C4VVkYWCeZqwVAmq1kuyGiXTFVQgKsHKv7qVcW1geOui497ciUpTHsl0xCmIqTAqNNzZyHh+w/KRseXehePewiWei5dkP8oxHjWBmeuYtIGjKuHme9UhA/sDzWf3MqZN4EElztrvzB0a8coQbolCEzntIjHIsZRGUSjpiNfJWd63gWkrBUjdCQE7RCkwfZpMWZOmL0b2QwigM8WehVyJQlbPxVg4IBGJZ2nKdDjxgKfxK/lnhZzjXoq5S7/LDFwbaPlw7IQg3ziYd/L8Jj3+cCLeEqVWjHLNx7czPrFj+fG9HBfgcNLy3YkjeI9H3Ohbkt9Jl6YGVhLmhYdq6fjyw0BhxPfjo+m6NqGjC9C4yNt1R0BEAH5sJ+Nj2xkPl4H7c8esDbRBODmf2ym4Xhhen3Y8XMiBHWxn/MR+zlElcsgjC7e3CnYLzT95WHFUxUtSu1YwrRMcMMj5jEZ+F4kYFfnWWcN5k7hHufjaEAPnbeS8ScpYc3mNkYFBASDXysVeZS2g05RCp3FED59SWvb6diYwrlm3ggZqZPIZWCljzZrIVqEodLyUel46uad76erXzh1Gw52R5nPXCprEr/n1BzWNl0JHszI87UUuci3Xa6hgM1fkWrxh6gA2SVn3a3pcB+roGFnFDWDSRW4PzQ/ks3Id61jH04n3Q7R+/oUBat2Z/6GEVorP7+f82oPVZOprR+26GPmQ44PCtN4E3gT+9sHBwceAvwb8J8BfAH4kipHzJvD1o5brpWbHRn5v4siUkJzPGkkeRgrOa0k4LJK0PFx4Seh8UsVJXdAaSVg3M4GpBJ9MD3ORh22dkM57zxCjhKegtTxvGsSwcNZ4LpJXQe1WsLAYV/CRXoYuIGuwCo6W8pp9B7UfU2mSCWKAdhouO/ExyGvrDt7pPPsl3JtLF7t/rmMlNdtvjGkrMKGdTIqut6Ydu4XmpHLMWykWnA+8m4gUG7lIEd9feOYu8NKGZdnGxH+J3J0GFgmX7xLE5XgZcUGKtu7KWhQy9Vl2gd993BAV3B5qOi9mUbOud2+X7ndmhN9za6iY1Y7zTqBMBOi6BMdCkj1jJAk06dxcpHNXKHkcEfbKVDQo4SU0qWO+CHJN+4+yvng866RQ7KE4PU+o6XE4KfyV5+HhaBmYdoEQBD7YG+T1SFYNtC0sW9gpI0p5Ds9bXhxb3rhw3F94Hi4cj5cepRRVF3BBpH77NRqk4AKZ0uUGAoHYQuU848yQKcW0CUw6KcCUAqsjF3XgwVLjArw+7QSOp0UF7o2LQO063lSONojqWGk0h+ct92eOJsLYaq4PNIfnHeetSyIPcm9UnZzPHr4Y0zX36X4qNIQgG6NJRf20hdaJCpf3InN7VXJ54qGuknJV+qpcEh9A7l2VNlnvoG49LKPc/32in6XHwpUbLEXtRDa7d1Q3CJzqarczeriRw7QL/Oajio9v5bgQ2Ugw0f4YdZTnDpCCpl/fOIOzKjIupHtXdfKZ5BI3xxqBoVnlxSw1KrKF5xd+fJN1rGMdz2Z0IfKP36uf+NnPf2TNF/lhxuevP1mMfP2449/76Ie4oHV8YJjWf4RMRn4GeIBAtv5d4KtPb2k/2Hhj2jHKYGgtpYGPb1nennlOW8G2Q491T+ZjCRpVefnjv531qlWScAyiPEZr6WCqpAy1mWlGJtCmRLuwik/vWk5rx6SLFFpTucBLmxajFCeV47mhZtoFLhohcrvEDdlWgjNvkGRnnEuCUhrF40rI6uMSTLfC7Sfjd5LyLSE9L0RwHQxzRaYjdZDCoXawo0nkbkmECw375eqcGC2woxeGhjoEXpt0bBWWrTJSucijpXBECgPXB5rCaqyOZAZ2S4PV8IUbBV99EHm4bC/leksjnd+zOl66ytuw8oHQSvg2IYoS0vWB4tXtgqOlowlByOZBYE6tl/O/P1RsZpZlFyi1Z6NQwg8yiduRrptDJHkN0gUfJD4JCvZyKZZKCzeGFhciszRNCVHO56OlkAt6/kNvfNdPvfpE2F1JYgOrQgSkaMv1ijOwmYtKWhsk4c7gknsD6X2Aj2zkjHKR9x1YKZSmaS0f3815tPDcm3eXa8jMqnBV6byO8955XTOyihc2LZMmcH1kqKeOKhXQt4aWwio2Ms39pccoxVapaD2UVvHTz1l+77imCwLN2xzKhOWs9ryzcDw/smwXWmBeA8P9haOwmnGumLtA7SNlOke2l3uOcizbRTrmKHtjP1NorQgh8nApN5jS4mnSwxV7YQSXIFfXhpqmE8f01sv5G2dyXuadXCvdc1DSddRKpHVdAN0I16nnjVw+XsnUaZDLJOa8gcKvir+h7g1DNTeHIp180QV2CsOn9gr2ysBbs+6Sl3QtcYaOE69ylMvk9drA0nrxVxkagWmR7ouh0WQ6ojSU1qBdy7/8QrHmi6xjHc9w/Maj5hIiBCLd/8Vr63v2hxmff99n5NfWJPYPPT4oTOtvIZOR/xr4vw4PDx8+vSU9nbhohAcCwov48Rs5m4XntKkZGUmOL0gYcS8J/Z2xpfVwf+HYymG3tNwYGB5XnrPa0/rIZm74yIYW/HuMbBWG2kV2C81HxpYIfHo345+ddUTgx3Yy/v7dij+1J8XQRRO4NdRktWCcdksDMXJ37vnYpqFDcVIH9gohKp+0gS9eL3g4d7y78ORa3KNN6vKXVuFjvJQSLi28uGGYtFDHjr2BoUhJzfMa5i7y/MiglEjlHteSQO6UlkntGGeKJir2SsPLY+FBNL7j07sZ40xkX3/jUcOyC5w2gWtDy52RIUZRI/rkbs68i/zsjZy7046ls9Q+8qjytE7gRD6KTLEh+W4o2DCSBL44tpRW8Wjp5fpFIWZv5haN56yN3NmwlxK/GynRzY1mKyqeGxpOpg3XNwtOm8BJLS3/RRewKuKjIsTA1lAxzgxLBz9xzfLm1LNbaH7+IwNiFKWsL+xnfO2kY2Th1+/XhBBRWrNTat6+6FBIUrpTrrgMx40UFTEdW5eI5JWH66USPoGPlEYxzDSOyMsDxXcnno0MIuJMroBbA83cw52xYdFJgTTONLdHhkjkaBkZGJLXimFSdeyUgNZs54oHCzHxnHTw6Z2MB3XkVqm5Nw+MjeJBBy9sGEjGkCjF8yPDm1OHIjLvRLjg5sCAUlQeXtowvHFhuTU0fHpX9nRp4ByRx45IkVilYrEwIj97eyRNga88ammdyEPfGmkukmz24zrwqZ2M+4tAaUQquYcxXC8NTWgYZ5qli7QhkmmRVW4j4GTKcXuo2R9aTuvAnY3IcR2ZtoFxrsiU4r1F4FoJEU0bxA3+BBkVvjQWjs7R0hNi5KKN3B4Zcq3IDBxXgZMqMNAipbwZA3ul5sEyUDt4eVPjo6IwipfHGY2Dj21lfHwnYzNTfGfiuLOhQanLqdArm5Zfu1/zwobh1a2Mb587BjpyWiseVYqbQ01hFPeXMj7dKzV7peHG0PKpbcvr9+fcHKyhButYx7Mcv/y+qchfvFNi+u7hOn4o8flrT35Ofvu8Y9EFRr3x1zp+6PFBi5HnEb7InwH+xsHBQUYitB8eHv6vT2txP8jYKhTfOmv56oOW3zpT/P5iyW5pGPQwJrUicofUiX5n5mh6GU0FCs+8jVx0kkiPc9Aq8tbMJVx+5Lj2NA4eZIrvnTc8Spq5FjjYMezkChUiv3vc8nDhOW8DS++pnUA0Tht3Ce367tQzzrTIy7bwYCkJ9G89jDyuvahDGZg2kuSCcBxigl71k4B35wIFw8Ni7gQKkpR9CgWPlh6jFU3iRwxtJDOeuYtM2sjQKvZLzbSN3JtKIfZr9x3GaHYLw1kdeFR55g08WrYUWrrxuYGjKrCXJJIvGknqFp1n2oiK1rRbTTh6mI5CEmaASevYKWRac1IrPI7z2jNto5B5Effxygkk66LxlJUkax44qgO6g0euZZHGFNu5FjM7H5l1kWkDp3VkaB2DDH7vOEnktp6/feh5sHB0AX77sYKYTB/bQOvARc+7c0+XVLM64PGSS9dxh/zM0JvpCUfHAcd1xGg5Bq0js9azcPB2crKfIftrmZTb7nmB+f3244YYIzcGhtqLZPF57bloRer3ovFMmkgT4KyBURY49cKPOE8co19+r8MCb2dyvk9qwXA9WMhUTkUoMsWjueOsDbw30+RaRAh+80hko62G71jNSRM4rR1zF9jJRaHrtPHMWvjmScd3zjsGVlS1TptI5QOTRqSLjxbJFwbx0wE4ldPM9y46fISHi5WUtdXwXuaYNXCyDOLJgUAAtZY1DYA8Fx6RuNVHHi48x7XwZR7V/U4TP4/NXF5nXsk50sCjRWCQqUu33sLI+o5cZNGtvEJqJ1wUHyG2gS5NZ+7NhGNWJrU8A5zWgV99r+bB0nHRyFTRauF27eaaxgXuTh3fOXPE2FwWciAT22kn489lgrgdVZ79MvLuvOP/fTcwrwx/0EzJNfyZW2vYxzrW8SzGr773pIrWv7L2uPihx25peKEMvFPLB2yI8M3Tjp+5WXzIK/sXNz4oZ+QB8HeBv3twcPA54K8gnJG/DvxIFCNVF/l7ry8JEW7mimMXuTt1bOeSsPkgsJlZlxSleuhNgvUsa2hdZGT9JQSq9tBr/QekKACBl8xaUdrJlZCGGw/fPPVMGpHd/J2jRgjaif8RfJL/TGTyjVRktJ3IqaLBdZHdEt6Z+0v377aWQqTnWvgEF8qQdS8aqBLRfhngImHih0k5axmhrmGkBfYSEQ6BkOYlKS+U5mTpeGfW4SLcGBrenjma1lO1ntMGLhLPRAXhw+B6BSzHbm75yoOK3VyTKfHOqNM5SyJdT8TV/7cRTmu5NlpJwn6yjIQEyxnk8O5c5JQBnIKqjpRpwhJjoG4VW4l4nhm4aOWc9saKGkkup4m7471nYOHtKSgd2Mzk+rw5iewNInu5YtnChUv+JnFVdPRE9fcfk0rv0cvDWmT9zotPx1DJ3lNpXymEV2DUyt187kT69qIWd/uRDUybgNKKoyrgY+SsDpeeJTmy7y6hS6xgYl36qhLPpXWynxYIDAnE0+SEKFLDJlAFOJ2LClWpRfntaBG4MRLlqgdzz4kS0vtFJ1ORLh1jnXhDuZH3PK3Cpd/M5d5N0MYQV/wtkHtCkXhEXuBVvapVGoRIBCjS/bNV9maBkWXnebwUqN/76DvMPSwrgVr1stExEcO3/UrOemQUMy+Faw+b6zlWNp27s0ruO5eK61IJN+n1c8feAHIbuahEuWyRFOWsho0YeeQ83zsX/5cQrnBVQuKwpH3T85yMEq7Mu62odY1zeT8X4b/55hRYFyTrWMezFu/MHYcXK8M9o+DP3lonwB9G/Nh4VYyAOLGvi5EPLz4oZ+QXgH8J+FkkX/ky8J+n7z8S8eUHNXuFwqOYOnh1nHFSeboQ+bFdkSw97wJWRzaiFAYKkZHdLTVvTTuqxCsojeZP38p5a+qYtp7rQ8N7c+mqF0agKIs6SjKSyNI7uZjgXbSBB0vPq1sZLipenzSM8+TI7GFcJO5BgP1MEi9jJRk3KdnIrSRrVinOkAwrDyui9MCKO3OuIpNOJgilTskPktwMMsiS0pJDCpNrpXgW1D6glOaFscKHSG40R5Un05qD7YzGB0ZW8d7cc2/uhUeRJbK9l2TKIGseZoYuKvYKzdAqrDbsDdxlAdgFSeh6qEp35ZpZkv+JFgz9jdIwc5EiE1jOVq5ZOLlmnYfdoWbSBKIHbRQ7uaL1ARUgM5rbGxoXZX2Pl45xufI78XGlXDXOFYpIke6OqBXGRnYSv6MOK6NCF+R64EX6WRkhJveJv0G64wYIWoz+rF7xI0aZ+IIEIjc2DG2ESe3JjcjShiBeHm2XJixKCq5XNi0DoygzjVYCZ7s7dxSZHNOtUhETGfokCbcYpPjVSJHXE+1BuClZ8mwZWVn/skuu47nh9obm0cJRZqIIpZIZxnYBQ6v52E7GpA68NQsYFdktDWMvppKTVhTqNnLYzkQmukMmY9aIe2rjVyafpZb7qOdwDLO0d+NKdUruM1i0q0LFILLAWxo+tpXzyb2M75513HXyGj4pZ8Urx90XJ0YJJ2kr08xc4KgS7s7zG5ZbI80ot/zu44rWCVerCcLpylKjIdOwZYXrU9hVoZRnimEWKbVCoymywDDI8QyzxOdJU8kIFJn44RRhZYpaJHW82gns0ip53sgqjit53nZh2KRjmGkU8PfeWKyLkXWs4xmLX7v/5FTki9dztnL9fR69jqcZnxoHful49f9vnHTf/8HreOrxQWFaPw78n8AvHB4evvUU1/PU4v7SM7TijTBDlK0WLjBtYXcAP3mj4NrA8AdnLW9MHLdGmtorWu+Zd5KAvLRh+NO3St6eeZYucj9J24YY6NJkZa/QHNUiFdyCQKM8ZEingURrAAAgAElEQVRneNaBj0KmbwJcNJLIKCUcg4FQRpgG2EncgudKRWYMmYb7cyEXTzxsFUnNx68Sy4GBnUJ8TiZNEHM5LeThs0putoAkmleN3wYZXB8atnPF27NIrjyLThGV4pPbmlkXeW/ecVw52gAjqxlYhdWSjHWOS1dvhSTBoQV/4XgntbFt4kwMrXSiy0JRJbnTygtEbtbJsQQkUfdJueqskiS9sGLCt5Fpbm9Y7s+Fz3PWBD62mfHGhSPT8HApUKU6SLJrtOL5kaVykWsDzZfbwAA49wKnaVIHP0aYNFId2VSkTGpJphVyklsvHJeNTJLY20PD7597llE697mS41Mq+V4YubZagdNyHjRQKfG/iVFUkzZsZKcwDK3mp67nfPVRw9HC4RKhe6Dg1S3N29PAw4XjvIHcdJQabo8Ms9YzbyUhPtMRi0wIdhOHZeESBFHoSZcdd5VI2eNMHOHnTpJlF2Xdk8ajVGTWSnHUaSlkXYQiihoYscNqeQ/n4azxMr1QMglxUdZQtYHcwlamWKjIvEumlTxpPuiDkNOJYDI5Z2Mr8L2FS/sF8QbaTgVYF2QadNEJIfGNi5YyM2gtBcE87a33T62gN09U5FaxZwzbJeyXln/nlQG/8l7NrPU0PmKUFPt0cj2tEgnoF8eWj20J56NX/JKpl8DoZm0kIDykEOUY2ijiE0WygvcR6jbB5NL5cOl8DKyYqN4aKlwQrleI6R4OIum9ABrj+ehYc3/x/hnQOtaxjg87fvX+k3yRn7u9bhh8WPGJjSc/I79xuiaxf5jxQWFa/8FTXsdTj9tDw2uTjotl4KSFVnvOGyDAWeX55mnDRRN5bmTQSsz6HswD14eajYQdP6o93zptaULA+cislWTgohWo1rkTZ1Wf4Dh90hNZqeyAwI6WSf2o69WytCRgIcE0lIbzVv69cJGRCrw3D0+4uJ8tVzKg/dfMQ1eBjx4f4biW17ZtuExuQBIczaqIcR5ciNxfhNTJlu5203l+45Gn9pFRIj/XHnzwnHUiY9w7kPe+IX10UeRuLVKodV6SyL6TjBKifRUSuZtVNxzk8SGszt1AybqPl7DIvfhcaDivAplRHFeeeeeZpwaHTu95EUH5wL25SzCogCHwcLl6ny7BhTJW0CYfEpcoFSU+XcxhXHEGjIJ7S/+EfG8bpes/IE1SUtveKDG4K7SQ3J2Hu9NAqWWtszbgEyflm6ct9xdS7G7nspa5g2+dhEtHcZeS9goIeI4rKSxbpFhogVgnz4ocnHtyX/aTCJOS3+NK1tqrhvUwpNiBUoF5I88pk1GgC3DqZEJx1sjeXKTHWCWu81x5vzoI5GqkIAYpDlLddwkfS7m17NMgELJFt1Iq67lOWdqzHnEiD+lnsyhrbts0cWu9FAeNwJq+Xyw9vDMLTIrAtdISYyAWgf/73RoX4e7UXUpvd0HWlOnVlGXpIu/OPdN29TMX5f5QyCRj4QIXbbg87v4aVH41oSnjk9PB/jFLJ/vn/iJS2mRQ6mQieHl+vXz+vDGDF8drr5F1rONZii5EvvzgycnIn7+9hgV9WPHRUbhERQDcnXnOm8BOsZ5UfRjxL8xZ/8svDpm1kbMmSGexE6z/1kAxsJpJA1ZLSn99YDiqA4MMpm1g4WIyCYS7s45Cay46gfHkSZJzkLr4y9Qx/X4n1rJSF+rlRHUizhsEjhNIsJ4o8CQXhDyrkce61Cnt+QcqPf4SWx6S/0DKRyJiYjdSq3XEK189NOa0Ccw7L8mxUhitpGAKURzg01RjmDrU80agJjHK+195ecHep9fWJHUpK+vuwuq9C9MXQlKwWHWlQAorrw2LPDc3UiA0YUV4zoxiM9OX/+/C6vyPi8TVCJHaBRSKizaykRlZi09SslfOi9VyjB3yu55E3Ce8INOPkHg7kyr50lw5BxopEoySxFGRuEj0ZG05dpBjuVbKeKL2wlG5N+1oEmQq00r4DFp4P5lKnBAja8u0FBK5WhVU/blvgjyv8wIn6ycDV/Nym4q8zq/Wrq8ca0xTjZ5T1Evh6vR+/USjDQJJHGar89X/TqfzY9JJnicSdsaTcsdX948lmQym+2mZzCVLVtLVmjSFI3l2pJ+pNIHaLTWNW/3B+aPCkmS7I8xamLeBLL1BrmDZeaxWbOdyLLWXx7epGNwrFF2I3J117BayL1xMfB8tDYZhkr5euhUcsG8g9GuG1fW7Glm6juNMXrtyck0jaapKOr4o9+qk8fzUjXWSs451PEvxtaOWabf6INovNZ/ZW6vffVhRGvjEzpPn/5sn6+nIhxUfFKb1Ix+f3c/5yy8O+IdvL3ljKfCOOxuazGo0kYtOVKO6AJ/bz3hr7jBE5l4csu8Mcx5XnrenHZUTSdibA8XSB2atSLCO83jZOS20dHXnqeWpkEQ06xPuIN+DlkKgT17aIDCk2sONQlNYGOeGd+eOzTw5tmcyG1m6SPDyOgMrHfkM4W2gRTb31S3N46Wn9pIQZVqgYU4ewkgLVyRoRfCRWyPxmygN7JWGSRMgRrZzw3Ed2C+08FDS+GKvUCyNeIo8WiZPCCSJXrqVX0hhBULWE4/3EnTIasXBtmbqRJZ2txQI3bKTbnUW5blDmxKwIEaTVapYtNL87E3DpFU8FgtsrpVRJFOVolCKQdERtUIrRW7g9kjMAg+2DN86E/UzF4VErrWsvefBhLAqUDJkHS7CR7ctp0nBataSJHWfTDY94uqdG1nnpA2MCkksVUrsR4kvVFrNc7nmvAu4qMiMZlcHrpWGeUo+dSOqa1qJm/rQKFov8L9FmlCIXLJMekjTnGul7KfNXBGWsme6mHgXFjYyRedj6t7LsTaJLN+kasLHJEiQCpoq8Rd6t3CfpltDI98nUfgxPW/GsirY81SwLDopdAirCUk/VbAqHY8Xz5vzVojiG7m8r0vHN21lCrRpZRJjVBIHSPf90AiUMDdcmhxerUtMukYGgVPGCKNc8cmdjLMm8qldyy/fDzw3NGzmisp3dI0ctw6wXSh2B0aMTLXGh4ALgTqKSaVNcL7bGwarFItOJiwZMg0LUfZ0priEbjbpvunXN87k+pdWs2GDkOO1QVnPKBX3TSoWS634medyXtpcJznrWMezFO+HaP252wV67br+ocbn9sR2oY9vnHZ8aQ2d+1Di+xYjBwcHO4eHh+c/zMU87fjctZwmREq35O1OSeKX1Ie6IOpFN4bw5gUQRT1obA13NizbueG09Tw/ttwZZ7x22nDSCEbfA6VSGC0eGDFBXPyVQmSgpGscErwHJKFrI7Qp8RrksK8VN4eGqRO8ybQNnNZBfBoUlDYSYsSgGdrEXcjBoqm8uJurxM04qaVLipJEsO1SEs+KFKuVJP0mRLYKgaPNu8BxA0dVwzwpTE1bUfo5NYFCK1HqauG9hXhgGC0JqwbGBl7ZtjxcuEunbRcloewStCkgxVJEobTi0zuWv/SRIdcHml+8t+Qbxw0PlqI6RFqj9nJOXZSpVhfAx8B3J5HcCnF3I4MYxY9htzRs5Aq3iIzGJc+NNE0XeVh5Hi8dk06Sd4Ukh0ZLklxYRRsixifi/NBSOY8Pkag0Vitub1h2C4NC8Z1Jgw+wSNwi4HKSoQ3kWrNVakobqXykjLJXpo0k0x64O/VclEEUw6Ioe4UAmY5sFprzyjPvlbGicD6O23ipvhaRQiKykklWaR2LtHdyo3h+JFOv8zZQGMVGpnh+lLGTax4uHYcXMpGJJHGBIAVaoWWyMshE1GDpVzC6rJ/weIHc9QTr0sh1Uml6UyQ+1G6pyY2idlLoTjvhBPXH4UjFRiqM5kl5ygGkBP/2howcFJ7Kw0YBsREYVxVXylPzzosqnpLJ3NjImqeJP9L725SZIreRQkuB/NpEZIW/8hBOK8f9NFoJwIaFYWoI7BeaxkVmXaDxcj1aL8VflyBj2sN5E8iUEsWwBA1QaYIXUj6SGdgbKGoXxfskSTlnWo6rCwGn4Fpp+MxewaNFx+NKvF9e2c4YNA1b20PubBi2ih/NJOfg4OBfA/7R4eGh+xMfvI51/AjFr7yPvL7mi3z48bn9nP/l9eXl/7+xnox8aPHHTUbuAZsABwcHv3J4ePhz/zxvdHBw8DHg7wB7wCnw7x8eHr7+Rzzu3wb+S1aN0p87PDx8/M/z3n3sF4b708BJK2pJy066s71UZohw3nguGsnYuwBlFvmtRzU3B4a9UrM7tLw+EQmfZZugIwpMlEIgS/CQKqxw4BGR0M1dgnekhLWf2PoIygnePRvCe3NHaRVHlSR9m5ng+s8TNv5aCU0M+ETaXTRgtZDoK5emD1fgOSjhTVyFgjSpm3qpWJWMMM4rJxC2hPnv3adzD1sZPF6IyVzvnVD1ECe/ev2Fh7fOHZuF8GgM8nq9BHEOPJqBtZEbg5hgQJr//c0F1waG7100PFpKRu29dM17taQelmYRYvSZCpzUcL0MQvx3EUWktIZJ7TmqIjcVfHykaYMIGRxXji7K8/vCEVYwpaaLjAqZGnQepo0jIkkxKvDpHcu0Fl+L3VLx/NDym487VEo+fbq24whVC40KRAIbFh7XMMgiwcFFuzofcwfLebx0Rwc50HdngTATbGtM04OpF6J8v7fSQ5/gJfU3T5amB3dG0DopMkOM7BZwUUeWbWRsHbtFztvTjpCEBHqInEKUnXoflftNvLzOzgtEKgtPSu0G2UpCRFeyBqvkfHvgjlG8ODZ89yJwdyqTKKtgng6mnyr5tE8XYQVpaoGjGiZNYKtIhVAn8tgmXtmP6fldgCGgEzQsBimKeghZSFCraS0eKsqAikGU82Lknx41XB9o5l1g3qZ7XYkvTWmg6bz4nCiZjj1aJgliVtC8NgB1ZCuLLNoV/8j9/+y9d4xlWX7f9znn3PRixe6a7umJO8O3OTGJBkWbS9KACAIGLMhBoOi/BBuWLcCErb8EWjQsC7BJOUCyZNiWYZK2LJOSFWxBMpNIk1xxRXJ3Ns2+ndAz07GqK718wwn+43duvere2d1e7k5obv2Amq558d5zz3v1C98Qj7WdHJUW+kmIDQNP8GuhiUxLQ6GxMNOef3GwYqfQZ4XNycqxahSXjYgiPPfoTkb+M+B/Go1Gfwf4+fF4/Lvv9AFdxEV8s3Fv5XjhaN2BV8hk5CLe2fjY7v3fkxeKWu9cfK1iZDkajT4IvAh8z2g0av++3hfj8dh/xTPfPP4m8NfH4/EvjEajHwf+B+AT5x8wGo2+C/hLwCfG4/Hd0Wi0wf051jcVh5Xj2kCzmwd6JmHp7JlBYD8VDOdRKTCIJ3uGzVwzbwJV7Vk6+MSljJ4RRa4vn1o2Ck9hg0jjWtjsiHTpwcrT02vPkDY0om4UEKhUiJl125HPNGymIn87qRyJhg0DiVFowpki0dLDpVzTSVsuhHRkqxoud9bQmm6qWDVyXxGTok4qyW/LTVEI7KWfxcTcwzCP0A8HJnITOkmrOLR2Fx/kQpCu4hpmwEYuBZ5FOsQf2TXcW4oXSWIE7+/jZCNRsFUkPDVISJRiVnu+eFpTO8WljuG09gxVOPNk8PE9tIKtjiSSPkjyZYMUgc8MzFn3WSnFhlLshsAHdzLuLC2lE7hZP/HQCUwqSWJNy0GIk6bdzPDEIGFee+6sLNbD5a5iI1dsFAlbueapgeGJvuEfvro6gxI5J9A3lKzRZpw2JVqBUnzfY5qbc8+NhSPV4ifjWatBadYKXQ64PhWDTa1lcraXiDFhGdYJbxYLlTYJb00WDXLtLnUVm7lh0Xg2M+FMNQH2eoY0TqfurURuemkD12cy0SK+x0YBwyjJm7g1/0JruR5nk4d4QCZORhJaXoyi9IFeorjc0TwxSPjAdk7tIVGOuyvHIIemjEWnkv0RWBclrTqZixOH1hj08Z5hKwsclZ7TUvaXY00CT5GJziCDQUzuA7Ab84DSycRkJ5Vp1ePdVKSwE+FfOOVIjaKXCAQrMTI1u9rVrGr5rhgmijTVLBvPZi4Tr4BMhIxfq26VDvb63DcRC8jUabcQGFYIcLUj05KTyktDIX5WtnNDL5OCpHYCDf3OSxmlD8wrh7aB793L+dhu9siSMMfj8UdGo9FHgB8H/u5oNFoAPw/8wng8fu0dPbiLuIg/ZPzaA8T1j+6m7BYXIhPvdLx/KxXxnJio3Vw47q0clzoX1+btjq9VjPw08CmE+gDnvMVitM3Xr3vVRqPRZeDjwI/Em/428NdGo9Gl8Xh8TumZ/wj4mfF4fBdgPB5Pvu4ZfAMxqYIkGAEKo0iNoqMDR3HCca8MZ5jto9JxVHlyo9nMFB2jCEExPq25t/QclA4fAolWJMDcB/LYUW6CyOt61Jni0yBT3F7IFGDaRGIxESYSpzLzBgoTeKyrGGQGGxybqeJeLcdcx6RZ/Dk882jadyk3fOfllE/fqymtqB4FoPbhjDx8uQs359LNrv3aoA/WsqvWRV8TJYVDoqM5YYRHtYT4BnkNW8lzWwJyCeim9UAQ+d3LheHu0lMkYkRYe4ETiUSuSPCmSuHwYhRZeroJbGaGxge6WtGYwLLdfbETXDu5Zo2Dk9Kfkd6HqWez0Dze0+wVhlUT2NSBpwcJv3tQ8dJpw52lxUZITZ5EKFFMFjMNO5FZ/uWT+swjQ4QDAkun2c4C27lmO9OEIEXGk/2EZGmZxWS3Pb7cBPqp5mo3IdHwWM9g8XjkXEOQ7vkwhdNKCru7pSi3RfuSM2WmWQ2zcm2Ip4iFTFgXvR0lye3VvoZaJmLWB24vLaVrzf00daxeMh04WlmuT2UvdVJNP9V0TBC3dBsnaPHa7cZuvA+BeSNrM49wLtsWdIkcQycxvG8z4T0bKZ+9V/P545rXZ46DlTi431l5NlLoWU3PiCpdTkzi1VruuVX9QglJvfUKafdPzyi6iWKig6jEPTAdsUGknXdzRZ3DXi9FBS/n1zgRZ7CB2wuobENiNJuponQio+sDZEbTTwM+KI6bQGW9TGqcmEPauTtzgw/IOu8UIl3tnKzfrJFr2MTjG6ScmTz6IJMV6+Vze1IFmeQQBQa0yCXfWcla5xpKZ/joruIH9wqudjWfuz7hE38EoB/j8fgF4IXRaPQXgB8Cfhb46dFo9NtIE+tvfwNNsIu4iHc8fvXm/XyRH7rwAHpXRG4UH9hK+cy5qdVnjhp+5NpFMfJ2x1ctRsbj8d8YjUb/I/AY8CXgA6wLkG80ngBujcdjF1/bjUaj2/H288XI+4Hro9HoN4E+8PeAvzwej/8w7/kVoVTg1alj0gjZvLaBexWgpIM8qSS5MsAJ4vi9mTsmteYkWL5w3LCsHQelZ+U80wpSFc6w4XMrcCnvYRokEU2UJB/7ixA9SaJ0LLGDGzP5ToRRTetAqp04iqvArVWgSCQpaqwUAlqJl0JjhfR6VDt+545I2mY6SroiUB6DJKu355G07u9XVNLErnw8DoUkpS35vImP0WEtDds+rnpg8gOSsFaxKKus5zVtabxA4mp9zrwPeeHKBq7PGoFeaUnilh6WC0eWwMwFTiM8TbN2MT+tvlICFUTlq/biTJ7viond9bnmv35hyiDXlC6wsoFlLR3xVRNx/bGbHzzcXjhmlcjhqrgWDVKsFannxdOaWe0IoSAznlntOVg5mggnmlXrcxQZWM+NecMgU6Ra0dWi0jZvZOKUKumWn/9z5VkricGaJ8MDjzn/L/FaKy+vX1XgIlSvE8n492pIjaeXQeUdd6drVTAx1vMc2zYpjj4aQbr0Kyf7W6FEISzyUVrH+BZG1/KiBpnj80eOFw5rFjacKVFNG3ChxgaBV4UAdSIFb410P1pIX1voLp2clzlX/Cpk7Q7LODVsuS7n1sPF9zyNjYh+orizqEUtKwQO42c+iUT8oxKU9lROvHqaIAp8mYHjUl7DeuF/tbyT9kv0fLemdnCwCnTjRGcV+Vqt6WgT92rO2kPk1txjTDSb1PJ5c8A8vkcROTeVB2egmzpenjQclY4ferzDHyU139Fo9B5kOvLjyLb6KeAN4D8A/iTwr79zR3cRF/Hw4UPgVx/gi/zQtQuI1rslPrZ7fzHy6cOaH7l2USy+3fE11bQiifDmaDT62Hg8fv1tOB4DfBiZoGTAP0H+AP3cmz34pZe+gnLyNeP2sWI6NXQN7E9XNBGPnYT1pEITkwornct5CUslfInXDysGKUxLhYpKT63+fxFJprMgPgrHDdhGbk8NzGyEKLlz78E5aE2E95gAto7JSCOvaZx0VTWCWcuD3GcUuAjhWcREZxqLiJa3AHL7EsHOW5r7pFQt603QErlbzHv79dnCuR4sPN6sQmyLHOdEWenufK08VLo198MCiZeCaVpJIryXgyeQOsXCiWP21K+LpvPH8maFSHvepZO1fvm44bs3Aw3QzGdUSyhLhWkFBCJUxiLXMguyFieVvFZ5rhpIkYS4o8XMcd/CZ5oV7+870lpR1lomVnYNLTLIdeqksCiFe5GakpMaIV/HaUdP31+IfLV4mIq8LQYWVVQC8w3GyFrrWDQ3UT1sriVJFriccFi0Bm9lvyjkQ0i8dl0Dp0vYymRvza28VhvtBMPFzxIWjqLvSCdOVlyAXMGkFHhZFfkQCytr37AWfmjPuf28qLBWgdNEvpOVvbYK6+dL3L9D6kY+K6SwnQWqRjFp4rEGaOJndRX35NzL/zcBttLoUxKnXpmKBpnnzvvBa2OR4mnphUdmvRQeLQ+njQro+vV5LOP1cG5dtLTvUbq15LL1AgGbzRrsMvDLiyl/9qnwDX8ntvH888//oZ73rY7RaPTngD8DPA/8HeDPjMfjf37u/r8LHLxDh3cRF/ENxwtHDUfnjKiGmeK7L2Vf4xkX8XbGx3Yz/pfxeRL7BW/knYiHlfZ9bTQa/TTwE8AV4DaC4/3L4/H4YeQHbgCPj0YjE6ciBrgabz8fbwC/NB6PK6AajUb/APgevkox8o3+AX39ZslHOzWv3D7Epj0mvmEzrkDp5I98mkgHs5eAUaIc9N7tlL7W3FhZtocJeRdenjZ08kC9FBhWJ9HspIHgFYlWmMYxTDVHlWeYKkwi0qmnlRibLSJxtvUVyAxc7RsyHRgWho5WdCvP0yZwe+GxJjBMBWve+hwMM0Un1RgE6zjMoVxJYu3iT54IBMiX0NUNK5Wi7Dp50kiX1zlRJNrIxIejsWKgmCDJog2SmLUeFkmUfT3fDW6FAHIjPztdw9x6UgVJKhMOPHS1vGcWlYtWBDZy+Jef7PLazFHowMuThoMy0GkTW0FDUTlRwGqTOs05UrtaQ3TyDIrc8H3PDPhH4wN2hgPqoHiqG1BzS1E7DlaSGLeJ9kbH8ORA8/sHQqgJkf/QxAlB5eV1jTFSPG1lXN1OmZ42DAael6eWN+aOpInqaVq63pe6CbXzXOsl/PFrBb9+u+K5jueolCmbUZCtou9GTNDbP12B6E2DFCzm3DmfLypbr4xECUfCaAi2IUlS9joaozXN0saJiHTYu6kCIxDAK4OE3SACDocE0kY+A51E1iHXimt9w6IJfPxSyuePLeXC0kkEZmb9OX8chHe0mRlOSsfCRhf1WMyBTPbSBDYzxcoGKieywT2kwPcBNiLXY1JJkt5Ox7ZykcqdNh7nFduph1I+QwsLtW9Q0a1Dxf2rFbx/02CMRoWAMdDM44HHvb1TaBa1Z9aIdPJuz9A1imtdw2dOGnSU1c20ovIB26yxxu2xteefRkZ/nsAHdlJemzQ0XiZXOkI1E+S4NjuKfmrYCp43Fp5BIs2FfhoLYy+fv1TJBGWYQpYoNjsGnSg2Cs21QcpGevCuKSq+ifgTCCzrH8a/A/fFeDxejkaji6nIRTwy8eBU5F+5kkdPs4t4N8RHH/B6eeHCif0diYctRv5LpCj4dxGVracQxashwvP4mjEejw9Go9FngH8b+IX476cf4IsA/O/Aj45Go5+Px/ZDwC895DF+3Vhaz4snDTdWiiYJ5EYSMx15CGUjE4wGIWF3TWCQC+TlpWXDrIHDlUjcLut1F9oDQYlsawiBVS3J3jCVQmXlg0BZlCQYKysFQ5toKoAAk9qxXWgu5SInnGjopYrDleef75fcXoqUsA+gEpjbgNGBJCrtZEqKhKZV+EJyreMq+hkgHiYhieZtcQSiVOR+eKhcoJuAShS6DhglPhSVD8xrKQYc93evM+T9k8gDaaxATF71Du+k8Mi1wJ50E7vvRBnYIDyaSQP/zxtLljEJbo0HVeQsdIwUDLMg3izerycQbWHVqk0VShLGfqL40knNYQXzmWWQC0HYEUiM5kpP3uuwlIIp03BU+jPlr6AkeXSIgWFAzAV7mWPYN1zpGSa14+WJ5d7KYUNgkCpSE+gaxUZuuFRoBqlmfFqzv3L81n5FkcAT/UwkW11gf+n4Z7cq5k74EgVSHLbFRmGgSCFtp2HhXJc88itC3IdKyeO3ckPmaopOQjdRzKzAwlqfktZzxsU9cn1mBX5lYDtvC0V5vdpBReC0ClzqaJ4eZnzHZs5Lk4YXDiuuT9wZRMrF52kUvVRRO4VSQaSgo3pdHadd3sHCyX2t4lqixPejdvJ7ohR7HWgKKIymSKCXaJmUxXOeNopOEhhmijwJLFZAlNFW8brmCWx3DFu5RqEovedg5ZnW6wnisvEyudPCj6qdxzrFdeeprajlScEo17mJHyqtZA2TeC1aX5NFnLzcmVt8LE53M81ex3Bn3jCJeEqZnHhOao91Mg1UJoo2RM5KqkRIoN0PCoUPbZEcWDrP56eK3UffQfifjcfjX3zwxtFo9JPj8fivAozH4//3qz15NBr9DALjehr40Hg8/vybPOYvAf8+0lQD+O3xePznvvlDv4iL+Mp40F/khy8gQO+qeN9WKvD2mNPcXnoOS3chMPA2x8MWI38K+Mh4PD6K/z8ejUZ/ALzAQxQjMf494H8djUY/hVAyfgJgNBr9Y+CnxuPx7wH/B/BdwBeRPOOfAv/zQ77+19bKRWEAACAASURBVIzrU8sfHDQ4H5g2CuucGOvZaLwGLM5hLRwyGVgsYVq5M0z9ackZN6CFJDUOahvwEUuuI8n8lUmQ7rgBFJys5F/rI1eDtR9EhhxLvfR0TMMzA8O1vuHXb9aUTj4cs4ozkmxjxQRO49nIJGG5vZRi57QR2AoIF8UjE4ypgx0v8KOpl4u/nQvHoQI6SNItXhaBTiJk/toEGicwpfPdeFjLrfo42Ww/vjVS3HWUwF6Oo4RyGjkMjZeixMSu9MJB1UjSuL+U99nM1pwWa2Ear0tbAD4IG2v/3wU4rQOXO4Gb84ZcK6a1F8nlJjB1whfaTOE0Sq1WDhovhaYOAlPKw9r3AtYQpGUNt+aOZe15deooo9HdzMYiLch+SJVlZQx3Fg7rA7tdfeaEfmthqV1gUjtOqsAwh+VSpnKxqS7+NXHNVnWc0rg1HMojU4l2WuLibdaD846FU7jac7QKHKyEs2SRNZ80ohbVuquXFvY6gcoKJHCYydqkcS+nBm5bx1N9w5dOGvY6hs8fl7wx98KDitdEx4O45wLbuefJvuGNmeV2yw3x66lWCLJvauSzdd4lXQONhmolE8VOAqvg6Cea/UXDKsKfMqWi745cW2OksC6jxHVr3JjHz+Uzg4R/emNF42GQBO46WcMUOPVrhTsXwLtAPw3cmstzfTz+EwuDLOCiT1BHy4RtEadDA8+ZkWY/gaUVhS0xuvRo7zmMvirDDOaNGJi62Bip43EsWEMPDbLveikcrGCv8OgAx5UUfD/2ZEo9gd87qPmuy4+umhbCDfmZN7n9LwJ/9SGe//eB/xb4/77O435uPB7/x9/gsV3ERXxDcVp5PnVwf6f9E1cv+CLvpki14n1b6X3Sy587avjBxy+KkbczHrYY+WozxYeeNY7H4y8B3/smt//oud898JPx51sav3W35EpfEzC8cRzwiaYJHqMFItK6Igc4My5so3bwxEDgV3e9P5skJGrtReECpGl0H8848xNoidEbuWZqPHMrnU3noRMTnyxCllKj6Cei9FWkCqMU799O+eWbSxKt6GSB1EUCvF8rXm0XCcMQmCQepTSzxpHGpDUomYZoDcsySsAacRvPjKj0DAtJkBfN/Z32yx1DamBSOo68cAVKJ+vhkMdlWp4zj5yWTkJUW1onsSBJYYjQExtk4qEizioPMtVxkdifGIGmuCAqZNsF3FlKopzF108Q6M7qgevcjROUJ3uaItEsLLxv6PFFzv7Ki0KZhu1BynHl6MQpyuFKRgaNg8wEnsijupU959mBJIOdVIzn/sW9ig/t5nSiwpFSnjJ2yHdzgc8tnWKYKa71Uy51xCSxcp4ND7ejp0uRKIZ5yk7heGUiMtIpsJ3Jew0SdebfMa3FWFE692seAwj3JDcyOdjrGkJZMxwkfO64FlnkBPqxAxRiFZzoKOuMJNObqeZSF+6tPHsd4ZEoBcNcsZ1pah/4wFbCb9yqWDaKvY5mf+kZxCLTOoE4bWbSvf/Xnunzybsrfu+g5m4ZUF5ECtqJQieR42n9eRa1TKs4tw9DUGznmmv9hEntGQRFYn10hdfs5ZqeUZzWnkntaaIvT0AmctsdzXdsZFzraSoP793KuDGznDaBq31wPnC3lOvcyeRaDjOFR7Gwnp2OwL+MgoESc1QPbHTgcSOT1FktHBHvpbjrpfI9YIJi5QMbRfxsaTisYLMQSWqtNCeVPSvyN1LFcR2YV5HDpQXy1ksUSxtQCp7qKYxRaGN4tqv54HaKQzEw8r4vTxu++9KjlfCMRqNPxF+T0Wj0g9z/t+VZYPYwrzMej38rvt639gAv4iL+EPEbd6r7mizv3Uy41n/YtOsi3q740Pb9xchnjy+c2N/ueNhPxS8C/yjyRt5AYFp/Efg/36oD+1bH/tKzmcGdlacJIgXa8yK9W4AY7EXTwiZyIVoceAMcLAPdVNzGtwtJyg2CXT8sPdM6nKlQVU4S8ZbTEIjY8ogX7ydg9VriVsX7l01gAhwsLafVkp0iAQIHK0c0fD4bJ7b8iZMSZo0l07DXUex2NAcrJ9COmJBVHnSEmPRS6V4b5P+NkmPoG421nkGmSZTiXpQu7ieG3sDA3LLXUXzx1KEiH8Ujx5Co6NWSwMf3Mu4uPaeVpXJSjKggx7A6B2kxOsJ/wjnpViSJbMnyIQg2fphpai/Ggc8OU16fO6yVxF9HHoKJL9DPJFm8tfTsesVOAbdWiluzGuvCGVRrf2m5sxK8UD+qGV0rDLMmcFI5NrTCJmJsN61kPzikgNvIDE/2DS9NLK9Oal46tSytFE5P9Q06Sv0uG89R5SkSOFg5/uBexaQJZAouFQl5Ij4k1gXulY6ugWeHciJPDzN+4LGMV2YyjXjxRNS4Pn9U44K4qS+bwEEsaBxSiAxTTeVFoWxeKQa1wNTqWOh500IIhbewjNylzXwNSSPI3nzfZiJk+xCYNLIP90vHM8OUm0vHcSl7YdrAZiqJ/LIRz5wrHUMV5MVenjhO6kAdyf06QuDCuWtvkMLhNO6V2q4VvnIlMEejVFQ+Uzw+SHms0MyawO/uV5xG+OIgE++WpwcJPgQ8innl+PS9kk8fyl7ZyBMKA1e7KRrYLx3HteVK19BPFS+eWI7LgAuB0kOTyvplRvxfOkZmcMsmoFPFh7ZyNlPNqzPLwaLh5lJkrCsr18R6KcZdgGf7KQfGsZdr3lh5CI4QoVqlg0IrCgM2EYikR9bhcifBBc9JFdjrChdt3jjemHtKF7i68nxnIoaSR9W57OfRiXYCngN/69ztAbgL/Iff4vf7t0aj0b8aX/s/HY/Hn/xqD/zDigI8avHtcp5vFm/Vuf+9lzLOp1kf767edev8bjuetzPac7/iEqJcCwC/8/oxP1rcfYeO6u2Jd+K6fy1O48MWI38BKT7+OkI8v4VAqv7zb/bg3q7opfCFYyuO3h4SF5hEedVEgY4ST3O/LiDgfujPykn3d+Uk8ckT8XBYOenaB+T2lsQaELhFHkQydRnVh2bxcc5FiBNrAzuFFBs3555JU4u/g5NEsTXG8/6c10SQhHxqpWu+8gIqsv5coufWieZxKd32WZQP1V465vdWIt2aJ5468gTuLr1g0p1082/MpRNf+rVykUcSV428x825PeOneOR1jF6vxSIWaz7I8x9c53YSoZD/rGxgEA0hfZDu8MqKfLKL7eTKixJWE874yKJ61jhuLaGnFXki1eFrU/GDaD1PQpBzMhpCsMSmPSfRc8aHNZwuiet6d+kIwdO4wJdPPVpJ0rmwgS+fWq52NS/bwF7XsJEqPn9Sc7SSaYailT62Z94dlzqGbiLXdlJ5NjJNbuDL04ZOIr/7AL99t6JINIUOHJVSiKwihiyJIgOvRbf2bioJ/d0IzWpVqFpZ6VUlX71pvEa3l7Jmg8RzayF77LTyTJvArBZeR1DC8/jtOyX7pT+DEAUvvKQsQqS6iDxykcAvvbLgSxMralbxOGwsyhUQGilAvYlGgAGquP9Aro9VYHG8eBK43NH0EsVJ6bk9t5zUnuNyDZmcVDABGm0ptOx3i3BkyhpmGpbOcrWneXliWTjx6ekYOCwdr0xk3/UiZ6MOAo9q+/R3Y6GvY3OgtIGb05ovWjAqUPog0ts15Cm4aEjaOPkOqmxg1nhWsZjOtXwWWwGAmQssa4HUpVq+l0oL1+cyAjMabiwCdfzO2e4oXp8FmhAojGa79OwUjx5EazwePwMwGo1+bjwe/8Rb/HZ/ExFfaUaj0Y8A/2A0Gr3vHAz5vvgjIArwdeOll176tjjPN4u36txDCPz+p/c5D27+Ux98jOffRR33i+su5/6JYcV/9erh2X3X64Lnn3/qnTq0tzzejdf9oYqRqJj1U/HnkYyrvYTPH1tsCOQxCWxVlIhThvZPeDsRaRPltlPfyvLOKrjUEXO8w9ILNCuH6UomDUYLXKWVI20iFtxo0Gns+BuYt1Cq+B4JUZFKC9SlxYr3U8XBKuDdmjNCPMaWbIsTQvjBIrDXEb5GTYQ/+XUymkWlq3ktCXk3ER5MHeT2VcSrD1JxML9Xep4ZphQNvDQR7kzCWvY3iWvT0ZJsTWrPRiLn30QsfpHASSNFj49d4Llbn8N57oeLr4mK9/nAonFs5orGaY5Wlr1Cc30uz0rj81sScuMFlpYl+syYbtVAkSkUYq4YvBy/UUIYr+N0dmVlfXZyuDXnrAho90Aa90mRwL1V4EpXCSQN+cPTRO7JnaXnQzuGS13D4VI4FUG13huSXCsltymEM7CVitBBCEJqT5UieMXljqF0ijxRbGWapQuc1h4dCcxNENf7BEm8fct58ALN0349eYB1kdieVD/yZloOxzI+/0pXiHx5LDAMQibv5oqT2rOdCTfJOSHXz+Lv/YQzrONWYXh1aukYKcJDWHMg2gK89ThpQpTrVbJ3Wshk48Ep4c5Y7/FoHh8k3F1Y9pfiuq5j9SqQLnmdSQ0uwhOVj4T4CGt0AU6qsD5nJ4XjyxNh4WdGCu4QRAyhDPL+RkXp3Qht6xqBUt4rPYVRIgIR4FIG9yLEr4Wj+SD7xhjFTmG4PXdsF4p5E2LBD1kqDQUXoZ1tYyOP07lOAsNMx8+YigWwKOA1Tjgvr0ws33u5x6Mab0MhQmuqG3//5dFodAP4IPAbb/V7X8S3T4wnlpuLdSHSMYrv23u04JPfLvHB7fQ+E72XJpZF4+mlj15j51GNbxvwYi/R/IknCv6v6yv6JpAWmqX1ApnpGk6rwOvBEWIS35KCi5gUtMIKnVS6uu/dysRzwCgaD5XzJMqLG7uL8CeiYpGSL6In+oZ57ZnWHh2JtT7yTdopRhFV5lSQoqCbarYKjQuW01Jub7vGmVoTczspmKg8FVBsFuLgjBcI0nYmMLQigVRrnt9QzBpJCXuZpxeTJoViUEh21zWwX0pXfCMzXOkGDksvU4pm7QGRGXi8p7nS1bw6FeOTZ7cMOsDdhSWguNQNXM41bywdq0o6wq27dpsot18Gm7kUNqnS9FPQxvD9V3KeGRp+8ZUljQv0Es9WJhChxkphmWh5jatdQ6JhEjTOi4Fdx2gyLR31Kr5Py1Nov4HyyH95opeysA0qCNG7QCYNNk5edgohTSfG8MGh5tbScYyQXLqxoHvfVsozw4zfWK3op5p541nGUdAgfsHZ4Lna1aRGsXSyl57rajpGMcwVlwvNRqZ5op/w0qTmg9sJr808+ytF4z2ZUWyowHPDlEnlOa0d3VhoJ1oS8dRwZobZyj23BV8/gV4mxn4qFjYKxcd2DC4obi1lhFXrQKpgtJlS2cBrztNJtBTCBO6Ucj9IERu04kPbKdMmyLRNy/rN6/U1Doi4Qapl79aR2N8qbYV4rFnkwXigSAy7nYSP7+a8qOHG3OGRSVBq1udnfJQ4VoqGcDb5zJU4sXeMVIG1g0IF+qnm8X7CnYU7K/C7Csq2yGkEmtnK+PZS2C0Mw1SzU2g+uV9hfMBozWgzwXrIlg0HKyl2MyWywZu5pp9oMgWhJ8IWs9qzlSuM8vdJaOdpJLM7URFbac8wURRGQxrQSp0V8o91BK4WErjaM48ceX00Gr04Ho/fF3+/wTonuC/G4/GT36L3e3w8Ht+Kv38UUd4afyte+yIuoo1fecB1/fsfyygS9VUefRHvZAxSzbNDwytTSa4C8MUTy3dfvvCDebvi26YY2cgVNiieGSa4VSDrGA5XLpLMNU9vKIpEcVI6SicYkmmU6O0m8Oww4fF+wl4hQJ4rPcP1mePLpw2ntaW2opy1kRl6ThyhlYJhqsiMQmslRnpWEhSlFEUieKZKGrJnBQysu/2HpeekEn+DPIFB7FQvI2FcReJwHd9vq4BLHc1RFciM53LHiPkdcLxsGGaGQao4XFqmVhSVMi2wlGFuyI3iuHQsnKdKhHwNitIFfBCoU5vIB7+WN146T+0N1/oJlwpDN1PMKk8TEnYKScIuFZr8pOaNmcVVARdzJq1i8XcOI79wsJspntvM+I5Nw0d2cu6uGhoXuDW3AjNTknQOctiMx7NyciwZIlCwiG7i90rHXkf8QeoghdnUrScFqZbkeCPVOKJjvF93p9tz3shgmBrhsHjPrSWkRrPX1ZTWs7CB1HmuzxwHq5KXThsOlp5FnL7UAZSTYrRVZ3r/TsbHdnN6Cbwytbx4XPN7BzXT2tNPFbuF5rQKOAKdVJMaMFoTgqP0cLjyZ1LIlZUEPjOyFqs4odN+7e1iIhQu0etJQhPv7xjFaSXrtmq8XA8NG5lwbW4uGw5LOFrKfSquu0YKjt2OwXrP7YXjqHTMapFj1hFyFNw5FbogxXW7b3uJpvZr4rpDSN6DRLNysk8zDa/NGplIqnWTIIkTkDaLlcmCfI5zI/tk6aBpAk0qcC+DYhX3kCJODOO+So2sWwhCNv/opYyN1PD63FK5wKrx3G0cd5f2TEihl3pOK4ETlk4KkMsdxUZhGCZSjGxmUrAbDd1EY4OjdHL9slSzmyrmjcf5QECTJfBENyE3lo4ROeGlCyRKCr3GwxdOPV2jeKwgfl4fufiz537/8W/mhUaj0X+HuLM/BvzKaDQ6Go/HH3hAtfG/GI1G34lssRoxVvyjDRC/iLc9vtJ1/d0Dz7qIr4wPbWe8Ml1L4nz2uL4oRt7G+LYpRnZzw6/dqNAKDkqNdZbgRLno5rzhWW0YporxcaCXRjhHlP3MDTTOc7iyDFJ4spfwwlHDrPKU1jGppPggwLR0MXmTRHNew9NDQ6bgzkIIzS62fpuYPDsEltIEcYLWgIuQEh/J3i0kZ9VE9aMAExunIzpKujqwBk5rTx6J+K9OHJcKxVZu6Cg4Kh2HS84gRS5IQrkE7k0cvVQKKAMcLgOdJOBcQ6IFFlTWUgwBZxOGzAtWf9U0XOsZ7mFJKulC1zZwd+7ZyBR3F4KXb7ys8VH83IeYkIYgUCgboWQr6/jk3RWTOiNT8E9uluwvrUBwnEgxtzCtrWLNNzmtAv3UcbiQTKMT2/GvzxzWrsUJWrgQRDfrCirrWZwKV8YEOccGaGrhWHgHN73luWFCAG7OHYUR+dY6SGL7nmHCSycNlkCuAqv4noHoteElcd/MoYieGa+c1mit+GSUdQohsGg8R6Vcs0QJnOpK15MoJUIMXpLxW3N3pozVaqWvrBSsTTzPEuEW6ThVU/ExNgTm0VBwoOX8v7SQPbcVlaXmNcwbz+tz4TB5t1Yx0249IVMWXp87mTgpJ3ws5Nxrf79BJnFdlRdORvBS/Gzmio7WnDYeHwIdreklMGk8RikGieLVacNxKXt8kMLBcl1Y+SDvs2OksLy1lAIhbeF0EQY2q4XDlRtQeL5wVDGP0swqiDBEW2g/3oM3ZpYrnYDzPhY2UmAu7VpWuWzgy6ciWCAGlIE7S48Pik5PirxhpiPHSHN9anEhMKk8SZySKC/8L+ch1VKMXp+JNGhhDAEhtt+Ln+FWIMKpwKsrzUunlo/vPlpeI60CVvz9m4JKjcfjPw/8+Te5/bxq47/zzbzHRVzE14ul9fzO/v3FyA8/fgHRejfHh3dS/v5r62Lkc+fUtS7irY9vm2LksHJ8dDfh9+7VJCrQzxSpSdkkkGrFtJYk/PseS7m78hyVnmEeuGQAFMZo3ruZcbkr3c1LuWZWO4JSPNY1zBvpigt0SzrXl1KZtnQSISjvdhTWe7RWVC4wqQQqkybSfW8J8iZ2+w2tN0GEn6Ak+UASHYUkS1kC1zoGFQI2BLJEM8w1QwsnxpIaxV7PsEngIBgOVg7nhTOSITKh4GW6oCBNNINM0U2cQMKUYqtjCKVit+uYNSLBmiLTgrar3Enl9yvdlNPakWrFcxuaeysnLUgH/TThmYHm9YUlVY5FEx3ltSTALghHpjAa6z2bucjJ/t+vl3QTRWI03cwLHj9OPXqZrNNOBzpasPu3V4E8hd2oHpZkCldLFbUVOQ4ru5Zy7hiZPM0qOY5eGn0vGkn6HNLZ72bQTzXv385QAXLTcHNuKb3INz/TN+x0DDY49uP0aa8n57iMjt1JKtyRP361y+WuJngxPry7dOzkBktg0YjHhdHCaSgMPDMwzKx0xoepIk9lcyglQgy5UewW4mrfTks6kRhf2bWQwEYu8rmn0cQyT2UvbKSK0zrQT6VATYzick8miIcrkRS2XvhRvloXWCnRiE9LYtxLFNMqcKmjKIx4vBws1/yolHYPx7XOZf/sZIatQg5yu9AMM0M/JtXv28kpNHz2qCbVir2OYWMz5bT0fPao4rAUo8DCQF8FLvUS9jqGIvXcWDRMa7nGez2Dc4HaB54cGLZzzUHpqL1nkCqe39C8MXMyidSwnSv2ugmd6Lr+vXsFN+YOGxSlt+Re+EibqXBHbFQBG+aKjUykezMDj/UE1lW7wPdfyfniccPSyvfM1X4ivKIg0MqNxJOayEcKim4qe2uYaIyCGwvLvHEoJ+c0yDRPDhJY1dxZukdS2reN0Wj0k8Cvjcfjz4xGoz+GKDY64E9/LcWri7iId1P89t2aak0X4am+4T3Db5t065GMD23f78T+2eOLYuTtjIf+dEQZxI8C/fO3j8fjR4LUPqkChVGcVI6JVUxLx0nlCUEgKCvruRGV7I1RXO7Kl8dWprm9dDJ5CIFPHjTsFYpZLTCJ2gVUUKxcOMOINF6I3I2BUAFLS6Y1G7lms0h4sm+4u/QsbIMPQoQdZprcKGonGPenhwn7K8dp5ZnbgA+i0rORafqppptoTkpJ75RWzGvP3dLTS+BqX/PcMOOFo4rKS2e+7Zi7oCgiT2KYKTKtOG3EhE0pMUF8sp9wqdBcnykWtePm0nNzIQVAooQInCXRVySLjvKqVQrzuCCFkg3iIK+UJGJfOqm5MbcxMVU8v5FytZuwX3pSDTdmlldmjtMykBrp9jdOJGSlWBSOSOs8nUTejXNiULlsIDUC52lhUSsLGwk83zUoHPurQD8VV3CIwgVxKlNakR9WAVSzFgfQXtZvI4Pnhgk3F47PHde4yM243E2xvmZZe75w4skmDfNmDZ/byUBrxXdsaKYNgEi0fuawxKF4pp+QabixcJFUHZhb2V/eS/d9Csxrd2aimaVioNgKMsyDKI9ZD88ODU3kTqSZONEvXGA319xcOHZyTemhm3hy1e6LSI6OVuqNk+ReIXKzmRFVs5bsDvLl4Yjcm8itWlhQKjCLPIut3NBJNEtnGQR5vokFtokTPeLEbxIcvUxxtbf+ozCtPTfmlutTuJQnLKysz92VI5lDL9U8M0y53A3sdQw3F45y1TAthVPTrk/wopQXlo5eItwY56WIc05ROTHKdD5QJJq9jqJBMYzCAYNM8bsHNeqo5qj0aAKFVugkYF1ggWJuxZyztDCtArlxaCXXTAM/cCVnkBo+uJ3xhZMGoxT9VLGRal6fiwnmtAlkWvF4R/NUP+G0FuWsVIm622gjYdoE8jji2s4VLgRuLyzzUrG4W/LcRvLIFiOIiW4r8/tXEKPDGfDf8CY+VRdxEe/GeJAv8sPXCpR6JCGU3zbx4QeKkS+eNFgfSPTFdXs74qGKkdFo9NeAfwP4dQTR08abEg3fjaFU4Hf2a24vHHMPvvZMq5hANf7Mu0Mp6ITAvZXFObkxM4rHe5r9lWNZB+56UUCa1T4Sbh2rJnIRorqQ8nBQQtACx8lN4HBlCcBB6ehpKQrmFu6VgZVzPN41aGDhPNdnljROUEKEdKmIae8kcFo5JpUjqMDKS/Lovdz/4onwFGzwrBpABV6fNGinmAYrLuNKpGjvVAEduQTOi9Hfq5OGXppRWc+XJ178D2LxsQjiWVIoSSpPYhHTKySJX9ggsq6poqulk249fPm04frcCtcExbLxfOlU1rdyAU3g5iJObIwUdAsLtRFIU4jQGd1yZFi7sFduDQFKLZywFlNUAQ4baI4tg0ymVoelcEJQcn8ZIoyJtXJa5SHx625+gpzvy1NL7WC3CKys/CysPZPMTZXAz3yEnKFE9jYxgZtezi9EDsWduSdJYNk4eolhZYWMfRQVolpn+CpEKeU4OasdrJynmyhKL+fivBQp1sGXTixGCfE+UYF7ZUDHa6EUHFaebvS/aEJ0jQfurMTzImiBHM1VYLsT1yBIgZe11zSur0aeP6/XqnDtv3eXgZOmYbfQohoWzQKTEOWFI8QrbeS4nAc/t5ys5ICslwTcEJhoxcnKc1h79nItKlRacW/VkBstcDUfOFg6yga6KqBXjoOl5yQeW6YFZjgpoUgClQt0k8C0CmfrsLSeqpYidqcwTGpYOUs1C1TOs7+QTXVYhjOn906CSPXatThAFWQaVSi51l8+bdjMFE8OU/77z88Z5IqeUbwxc7w6EZnnJsj18yFwa2FpXKCbCN/spBKe0eeOaw6WDq9kjx1W4sFyqZD3ndvAb92p+P7HCp55NDuxG+PxeDIajQbAR4AfHo/HbjQa/ew7fWAXcREPGw/yRS5c19/9sdc1XO5oDuLfn9KJqtb7ttKv88yL+FbEw/61+tPAR8bj8Y238mDeylAojitPqjU6yEZrE7T298ysORqJVhxUgg9/vJeglCbV8L4tzReOa4ReGmh8oHYCUfFR9rNtgAQlHVmRmzUsGh9lQANpqugj2Hgi/GXWBDZzzV5uUEqIrJooM+yhCoFCeyoXGKSGMtVMa8noci0kh9JFPknjyOIUQ2YCcl+RylSiYxS3F8I7MEFc2BsnyW/tPKelYz8S/Hutq3pM3gNr1Z9WetR5mbR0jGZSO7zXdDqa08rjvOdeabmcayyy3uIDErg+afjOSxkvHNUkRjwqai9TFhMfm6fwWAfuruQYWylYi/A42uQ3UVIQ+nh7W7BoJJE2WqYU96q1lG2bVLevUbD2cGn5Fpp1MVbGCcnCBrqJZm7FV8XHdVhG3oqO65XFtbFxetONKklaSXGZxILT6MBzGxmfO6rXEx8rx2BYm1OaCIWqLRgtKlitaR5B5GFnJZi0hUEpZTRCLAAAIABJREFUkjgFOqk9XS3iAK3cdAtN05HEXSQypehFaemjlShM5Uauy16hubHwZ0Vby5dof+/H7+3dLhyvwNcwVZ5BIryiTpxCVfE5KbLnBpkk9QZFRNOxdIFOIthBD5w2nkLDUSWSizZIkbWwnk5imNZi2rmq1zyrVllTx3XUWvZ746AxULlAkoCNZo0uwrPmNWjleLxnmNUwbTxXO0mcNArn6d5S1ty6+B0S95FlzWWqAwy1KGJdnzqMFgWu3CgOo9IXkVyfaYEBiiSwOMp3EkMv0cxrz3aq2F/JxHCQaOpGhAYKI82RYfyu6qWa37pb8szwviH2oxI3RqPRvwR8APjNWIgMOW/WcBEX8S6O12aWl6drhlyi4AcuipFHIj68nfIr5wrJzx43F8XI2xQPW4wcAqdv5YG81eGDyF6eVOJ0TUzqQBK+VEkysVmoM6dnFQK9TDFIhXT6RM/QSRS3ckOqAvdQeDydRKR9QWATtZMOZW4k+WnVeh7vJqxcQ9eAR7Hb1XgQuVkv3hgfv5RJchsCNxae3cxzp3RkWg726WFC6UXdq3GBPzgMnFYeo2GYawYBlo0Xz4xM8bFtccueNZ46wOPdlCs90Uo9KMuzxHmnSLjWNdxdOe6tLJM6kBvNZiY+GQ5QqRRcdSTOGhWLkURUlJ4fpvgQuLO0XOunbGSKoBSlU3SrwHMDw/7Ks2o8M6cogscYxXu3M75wYnm6r1jYwFHlOPHSVUaJqlYn1TxjPG8sxYvDx6S/iGtcR/x800RPEC0d+BY955FE7cPbKZ86qNj3/mziUUeCeaajZ4eCw5V0t1NgryNE88IoBgjMCxRPDRImlccoTzeBYaJY2SDmhmENZcsjvCk3clz9VJTdMhWYxPPIleJaz/DqVDNM4LWFJxgowtq7ppes+UOimKVYNIFOAtuZEjPFEChSGCRwKQlknYSt1DONJnyZVjyZwN2VyPEmGgodRLkrUWTGsFvAMJUJlw9wbZCQaYUIqymOyooiFoRNPD4XpJDf6ypyo0VxynmI05fHCkNiAlXjmVhR1bKxIEoN7HUMqYFZIzA/iPcTcCj6SZzMGIXS8HjPcHPhMdqTKrm9dopeohmmAmecN+GMG6X02tMmi9yonVxxUss6bBWKzVRkmo0SzlAnMQxTw7xx7BaGfqYYKsX1WWAzVZwYgUWunExCU6TIngjf/Izz1UkgSxRaSwH+noFi6RV7XSPKZc6ytHC1YygSxXHt6BlR5PIBnttI2cnls6ErRQE8NkhIdcMbc2lYGKV4uh94/1ZG4z37y1aa4ZGL/wT4JaSX8CfjbT8GfOodO6KLuIhvIH711v0QrT+2l53JuV/Euzs+9EAx8rmjhn/zPe/gAX0bxcMWIz8L/G+j0eivAPvn7xiPx69+y4/qLYiNXLGRKi7lhtsmkKSGRHlyF0T+NXDmfq4QT4g6gAuBQlumlebzxxW1FRz60wPDe7dTCq24u3C8cFxRWzgMge1cM0wCkyCvl2rBtqMC1gcOLWzkgScSTdpTJMriEb7GF08a5rXnUtfwZD9hkCY82UiymBjYyTQTGzBKsV86VlaKDDwoL/h1F4uFroFT688cy5OI1X8s8mFSozhYWQ6Wllnl+P2lxXvYKDTfs5fx8qnlUwc1iwijaY3YFJKADjPR597MNFuFyN3eWbr4mMBOnrDdEbWosg7Mm8DSBk4aT+kCdcT/f2q/ROFRKuHZoeFKo/nSpKFxQISjnFYypdkpFNu58CVKL0TuRSPQt1i7nMGs2iTexaT3qLT8/j1P6TzDXBTWjFbsrywLK9K43UQS/G4qU5oikcQ21ZrtQjg2/VicnpaOeysfeSBwoqXT7eP6JBr6iSKNJPRUt4R/maitkOsxb+C4dLw6W4lLfRaT9EjotxECtookdDGuVGfyvcGJYaKNRPUywrm8U2waMeR7akPz7DClcoE7S8eWlwK20BqPlUlTCKwai/UCLesZzfObCe/dyvnyScXMBrYiWbpd59pJ4XAcr88geqpMG5nadBLYKjS9TBPwdLRGGc+kWgsfFCkcVe7MfFMj5wiwjPq/JkIoiyQwTDST0rO0TpzKDejKUfqACwGLSAJfLhQnVX3mD5JEkYTGrqdreSxMKhfYdwK7TJXIXO91tPBTlo5lA0Xq2Eplb82b6JPjYTOXcU/pBN6mic2N+H5GKymKMoXygc8dN+x0DB0jBP9+otFKSOuLJlBZOd9uoukmitemDa9ORJ1tEaXsPCLLncYJkIn4OOs9ISj2uo9m8jMej/8xcPWBm38x/lzERbzr40GI1g+/ixzXL+Jrx4d3Lkjs71Q8bDHyN+K/P/bA7YG1Z927Op4bprx43HCv8pJYK3G6FhUikSutnUi0uiBJRCd23F+aePqpp3agdaCfiLfDrK7YyMQdfdVIgrOycGD9mcRooeW9XjyuqR1sFK1kr+czhxVbuXTTl1YSuysdjQFemwh56lJhWDY+yvB6fFdI9a9MLdenNrp/C/mWSrrniQE8HNeBmbVUVhKuATCtHbfmlo1U8fTQ8Dt3VywjxKSyAt9R2vOF44Y784bKcvYeZZw8a9Zu8XcWnkntybRwE0onpOh7K8WiDnzn5QwbFFrBS5MGH4TcvDyTL4W7S/EAuT5ruLUQCEpHC0ckUZAqSbRrD/00sKjF40ImDFI8+iBrnyCTLkuULW4hVEEKztPa47xAg4xy7BWiUGQjD6WOxPE2uZtUIuv8zEAxLQPTxnNtkKCBzx41rJo1r6Txa1J3oaET4GApfITdAgap4u4ycBQE4z9bCTynRiSaW9+W/QpyZG0qL+eTO+EjaQVLBTYLdCP/ZNlEeVwlZPuVXH6OS1DasR/Aek2mhHsQ8KRRcWvWNIQgRU0VOQ+pEqhaZTwvTWrurRw2CBxRA4vKsV+JoMJmps6gSmj40qmjEydDjZPjv9yFTAVOSsedpRTJxKJ22kDVCGyLuHat8lqGnEuhwWtZo+MlrFJPnsRr5mRf2rSlrwWshcOlY5gpBgnci7ymM2lqZAJWGDmfm/P1hKhxcu4bmWN/4Xh1LsIJneiCflLBRhoNEIPs4yYIbyewhvWtAhgnah+NCxActU94YpBwfSp+OfsLK0W5k7W9s7BnRd5pGSg6nvGpI9OKjgkcVwKhyxO4Yx3zGuE9aQgEXp4plqbiwzsZ3//Yo5sAjUajDWDEA2IpwK+9A4dzERfx0FG7wG/efoAvciHp+8jEh7fv9xX53HFNCOFCfOBtiIcqRsbj8aPZZjsXW7nmWj/hw7seVoEqSwhBsZVJR7LxokZ0eyms5UuFENe998ytGCAOM+F+ZEaxlWsa5zlYefJEsVNoPNL5P1xJ0rjXEbnUgPhCmASeGqQ8M0j5/HHFPe8ovWKno9lFUzrPyiue20qZVFYM/Gygm+poxKbY7RiMgk6iuNzVnEZ8/x0v/iX9THO5q9ktDK9Ma06rwG7XSIJY1zyznQmJWkHZBJ4ZptyYW06bQJrAdmooEoFaVQGeGComdeB4FaFawGYqhm5aKTqJmM/dXHr6qeZyNyUEOb6NXPPGwvFdlzJOKsMTg4QbM0tAJg+ZgX5i2MoNl7oGpTSvzmrmNnCpk/B8FmiiwlA/g81UVKA6RjHaSs+cw1+bO7yyLBrpTqfRsLCJXfYu0O9Icl8kBu891+JrLRw8v5HR2dG8eFIyrYUTUqSaxkrhapTCoRhkmu1CjBNvzJ1wLlJRrXJh7dA9MALzIXbHhwau9RO6iUIpx6Ty2ADdHKoKCi+Gg1pJ117FTrdSbTG25oVkEeqVJSKFe1w7ig7sLyMx3sBGnMBYK+f33EZC6QLHjWevq2mcppcqGieTtaAVfR2EwxGPRZzRNdbDSeW50kvYiCIOidEMEieTQxS7Hc1TQ83tuaOxIuOcGbici2mm0ZpeakiNo5fI+3RSxSA2BE6qWIyxPtfoO8ogfkMNc0UnidLYiMzuMFds5opJXPitzPD/s/dmMbam13ne8w3/sMea69QZ+vTILopsDpZEWaKpMZCcwEFiI7lIHAeJc5HhIkZ8IyCTgwRwkOQmuchgQDYMxRcRkggJggiRHEkRJVkWNZhks5vNfXo4feZTw67a8z99Qy7WX1VUi5Jaho6aRdUCyD5ddbrq3//eu2qtb73v81oFHVMTE3k/fu5azpOl5/6ioXDyfPRSCRIcZJrDwrPhPKWX18wgh/XE4GPguIoME+gmGqsCDTIMlA62W+le6QLzs+wf5NpBNiSJFS/MwMo2aauj2cg1n9vt8auPRSJ5rWuEjFd5jitP4eFabugmmpPS0W0lgVWA9SQyTDVLF6gasFaep52OFnhFAKsU37+XXVbzOvv7+/8m8D8AC34/LOWlj+KaruqqPmx96VB+f53VtY7+fcjYq/r2rReHhr5V58/haSVgnef6l/Pn6WWqP9Yd3t/fvw3cBB5eRjN7iPCZjQQ3ifQ3M+4vHLu54s40cGfSoFo4WJ7I8HJSecaleApqwDQwSCIhRHyUSdkoxe2e5d7CMa+FPNV60lk1sJEbfmA3442TmpPSsdsxrKeKrtVs5SKpcVGxkYJGcVJH7s0k1X1WXRijI4rrXY1SkrEgidSKjcTw4prlzZOGGCOJUayaiOmIDMkHz0sDy6KJHBUieyl84N2p4qj0rFzkRs+w4cCHwEkdeLyIeKQRfK5n2OsoDlPHYSknxxuZ5sWh5cnSCampNUrf6GgaFKs6MK08Byv5Hv/ksGLaBDIj4YupCVQhChrYSoPoYyS3ilfWUjIFSmteH1esJYqOFcnNjb4lhsikjrw4sByuPH9+L+PxylP5yEnpOVx5xpUMSF87aXABFpUQrjQwzD0G2M4kdT5GhQKOy4ajQq6loxRWKRbhjLAUOakc/URQrD2rsUbRte3zoyFp5V2SpUKbL6NRWRRkc4DZSrYy17pCOXi6khwXj6SiGy62LGfggAh0tZjfNRep8DECmZzUZxq8gkzJP4ly3amRoXM9NdxfNJwWgdrJAL2VKiYN1EHRTRSJklA+q9tNYYBZ62UiwsI1bOeGhYvsZhqUEeyhku91WARcjLy8Zrndbo4knTxwsHKULrJqxPitW//JtInnRLQYZQNEbCVqreZupyNT2ffuZEwqz5unNaHdRHTblPREydZrLZVfIre6kcEwkcwUq6hDZCfTuExROsluudUX/9KyjnSN+H0mTWTNKgaJYlzLtijVMC4Cib2QQ4V2yC2bwNK32TodjbGa7Vxzq2d4Z+rItPz3X580fHVc07WK7Y4DcrY6knFyZ+p4f+7Ijfh5mihSs9PS83QlW1iUDNl9I5CIRivyXJEryZwpnYAoqtarNq8vmqFLWH8b+JdHo9H/81FfyFVd1R+3PugX+bGbV0jfy1RaKV7bTPjNw/r8Y6+Pm6th5E+hPiza9zrwM8APAGNga39//zeBf2U0Gj1+htf3J1pKRb4ybnBRAg69h59/ULF0EeeD6N+DSC/en3mRRoWLcLfawcFKJCLDTDYDLnoeLD0nlWdei2zkjIBUevE6fHlcEYNsNnyMvDdzzBvxVnSsYtF4niwja5lGRfEi3Fu0Ho0APhHMaaoCs6bBrwnN6WxDsmoiJ6WggLsYEqM4KqQpr7wYkcsQKYPi0dIxbyJWKQZG8aSOzJUMBuNS/CdWn2FC4cnK0W8F/EZBo6AMgXsLx6yWpl+a58h7c8dmbni0dOdhjcsamnAmo4pMKifNulYsvIQ0rmcy1FngaSn/bdcGMiMEqNKBUZrtjvgdiJG7c0ffap4sPR55jFYpTJsUPy6F+LSqRXZz5nOZV63ZOno2MoEVHBWOk0oaWhvhxEd8eYHhdciWYl6JpOZUSUCeopW3BVC+NdYHMb6vGUXPwuOVJH0/37eSQr/yPJ3JAFGFCzxx4OJ1Bq3crN241F4kSYmRTUnpBLGMEp9GGVpsb3udDfICdA7WujCuHUdFYDNTzBvFysVzX0wTYFzKhumMBDer5LXbS+Q6lgFcKYO4VfC48GQ6Ugfxw6wb+XgTApMqcrNv0EpxUnmmdTwnVPkIkwYsMpQY2ueDC4KZ5oKUlrQ+ltxI6vppKcPbGZr6YBVJrQyAeQKPl561THNYao5Uw7yKnGaaaekYVxekr6qBX3lS8cLA0k/g/lLkeWfbjcPSs2ziuTRRKShqeX2c2cKPShnarJYh4KAM7PXAKtkmNf4MzyvbizrAsoiUzvHOacPduaNjaT1RkhK/cuKZqZ3k7tQOZrGVRLZYb6VEopgb2cJOKrmGbiL37rj0/PKj8jKjfS3wDz/qi7iqq/qnqV/8fX6RK4nWZatPfWAY+dpJw196vvMRXtGfjfqw8qv/CfgqsDEaja4DG8CXgb/zrC7sWZQ6tzjLv6HgpAyEEMkTjdKatfzCVBzChTSpo1ste9v0TarATkfzfD9hXkv2hG9PpDMuzOI+RFZ1oHSerVwzryPzJtCxmtIpNlPDMNUQ5WvmVnHaIoKbIJISq6XZmjSRvoE7k4rdjjR8VilOSs+wXS1aIs/1DNNaHtdGpjku/TkieFIHNjJNJ9HsdA2bHTHvHley1QlBTNs3upphKifvzgeUUkKIavml40IaJqvEtHyrZ6gcHK7EWFJ6GUQ6KSRanZu3E9ViVZEGuHKBZe1JVCQxkBmNQh7XbsdQNm3wIIq7U0cMIpWb1oFX1hO6iSLTYmqfNx6rJDdm5S6CFw3S4ah2a6ARMlMToJsoVq2nZpi2p/S0sqv2tN62cinT4m33uppOuxXR7Un5vBaJ1dkgN0w0e13bUtkAhK7WhIt8j469yDaBi0FEtf9nWx9J6eR7W+T+KyVbj1ktvgffkpw84nWq2scYohjdny49ux1FVILB7dn2751BDaJ8vzNAQelbI1j7+HsWOgnnA02iYO6EdGWVUKxyI5srrRSzWkzYdRAv1CDVDDNDr3X3RziHE9TI92ov4TynJCA+jUUtRvrDlaMKEryYKJE/aS0+oRDE8+WJ9FPF3EPlFTstrSogPougFFarcyhA06KDQ5DnLW3v3crJa7FrL8JCz4ZuuCDvuXaLc4YELhsJQxwXgTrItiI18nOmawW7HBW8Pa3leSk8idHs9Sx1+5ozyGtkVsN6Lo8tKqF0KS2ygY0EUqWY1mfPMRA1iYHdjqUJkV9/+ntPaC9R/dfAf7K/v3/ppcFX9Wernq48b3yT4VkBP3qF9L109akrE/tHUh/26OwLwPXRaNQAjEaj5f7+/k8Cj57ZlT2DChE+u53wT6YiEdFacaNnOC5kS7GZKsDivOOkHYx1hI1MmpXTWhrLzCgGVvMvvdTjzqSm9JH3Zg1laybtWdH0qzMfgVK8PEz5G58e8NOjOW+cOAaJ4s/vJaynhi8dlDzX10zdBQlqr6t4WkR6BiokIHGFkLruucj37SSUHu4vHKOJ5/bA0m/geq6pI6xnmp4VWVftG9YSTVlJ3sELA9M2aJqfuNnl156UvH7SYDQMrGKvZ7g9SMh15NeflLJJSjXP9SyZUbwza3i6Cmyk4gW43hH/hQ+OcRXYyBTTOuDaLnstVVRBEUPAKNH751qz29fUITLINLeH8gPg+YHlzqRm0URSo7k9tNQ+nA9nH1u3lF6+Zs+KzKr08PlrKb99JN/wSSG0rPtzx8oFmgaMbQcTe9HAda00pj7KyX2uFVgJs6tDi+W18kvFR1hrsy02UkOiFa+saR4sGh4sZIs2SOQ+3ehZciu5NDd6lhgCDqijpIun1nG0EiTvIJHhZOUv8ikGqQwLm4lioaOEHip53XWtwmjpkOeNfHw9E0lRE0S6pJT4eoKBzdTggFtdzUEhGNijytNX4KNiI9eMS0eqFVZpOl24MxEpWz/TKCIDq3ChzfmwmpcHhscrGa5dkI58Kzfc7htCkK3Lg1VgmFp6iRDFlIKbfUtuHeNSTP2pUfQTGRoLf0E9M60caqcr8rEbPc28US0JzjJMNO/NGoKVQMPNHJRS7OaCxlpLIlmqGCaKiVEsnKZnAlUUn0cdAv1MpE+dRPHi0OJ84KSO3Oga5kZADHmi2MwiT4pI1YYb9mxLNWsHwk6i2etoKu+JaNYyw0aqMRpWrmGYKJ4UnlwrelaxdIFJE9ntwFpiSBUordhJDcfR07RbpFKJ30yrKAcAaK7l4rHZ61lCFL/Wo6UEqeaJYj2Bl9csi/pSo33/JrAH/OT+/v74mz8xGo1ufzSXdFVX9UfXP/xA6vp3byds5peC73NV31QfTGL/2tUw8qdSH3YYOQU+gWxHzmqfS5Y9spYpGh+5lkeWBJ4uHUelx8dIoqQxboI0LLs6sJbqFlcqJtxO4dBasZ0Zrvc0r49r/vHTisOVIzOKaxaqEFvs5oWhedlEDgrH//7uikfLwKqRxuVo5TlaBsaVx/uI0YrCR0KAR0shSI0Rc6zVmpuZ4lrftgOLGIf/3E7Gw0XDQRF4ZyIJ53mMTGvFYeFZNIG5i5xWgWUNpvYoFXl+mEg2RibN8xunDdNSToW1iux1IyHCWm5YSzWbmUEheSpDq4gdxQuDBK2kwaoDdIzmxYGmZxXrThLqF3WgiVG8DkHISGuZYTvX5FqRaMWnthN++EbGvI68P2twIUG3W6v3pzUHK6D1MhglDeBpDUdl4KjwKBTvbSZ8attyvWt5b+Z4d1pTevFoeIBIm0fRyqqQTAvtJFAvtN6QJlzgc2O7yQm0hvxEEs8lPFNOyj+2lvLZTdjtGVZN5CvjWvwaGjZSzaFVxKj57E7GJzcS7s4cX3wcqZ0jMYqiiUTVmtKjSKMGmWIzM3xuJxVpUyXrhNSK1O13j6pz3LIx0NGK0OafbOWGJkRe6Bsms5rtgeWk9EzPngcXZRPRSp1OK6GtdXLNK2uWFwYJPhSsGs8w0xwUjsOVDGhJm9o+bTyTxlP7wGbH8srAcr0nr5NMC6XtzqTh/31Q8nDhmDeKYQthMEqx01HkVrZflXM0QYhVINdUenmdXOta9rqGH7uZsZFp7i88dYCj0pFb3UISJCm9cIF545kXnlWpUMuaThvWGcMZLUuobk2InJSSiXKja/EhElXkNav5wl7GV45qvnRY8bTwFE6em7WeDHapkeFNK9VimoXolhvD/kbCD17PWTSBpyuBAyzcmawuIs4vkYvNXcTHwEkp26pJFSnD2WtUk1mRNiZaSe5JqulbxWaq+eR2wtOl585EZJLtkpe5E6naMNWXFu0L/LWP+gKu6qr+aeoXHvzeYeQnnru8RLs/y/Xx9QTb+hBBYDWnlShKrurZ1YcdRv4b4Bf39/f/HnAPeB7468B/+qwu7FnUK8OE/+9RyZcnGtU4NjNpnB8sAksnEiClZaOxlkpw22aumNeRJjiaGOmiUCqwrBU/f79kkIrxelJL0KBWMKnaNPf2RHseJYH6/7q3om9FYvFo4Xmw8Axaqc5RCamRQcR5QYOmwNKJ1Mt7Tz8xjE4a/oUXOigFiybw5rimk8BbJ45rXc3dac3Sw3szQbZWTk5yy1bKoxU8mAcqX7M/sPzGk5pfeVyc44y9h3sLz6z2WAP76wkxRN6bNsxqTz81qBjpWsVoUpMaRdfICXkdI89nIk1qgpCwmhiZraSRTlrTchM8O5niqBDfQtlYxmVg1USsForZ6LTmKyc141VLxWrlSu96Ty/x7QZAk6jI8wPLNyYN78xqbnYTHixqprUMU0Xr4bEtKnbuJExRG5HEuCBysXkDjZbNQuXkPqCFllU7kbLdm3s2O+CDJ9WanQ6cFJ4HXjw0Vsvp/WnpOa0DKkZ2ctl4HReeec+c50MMU8VxEam8PDctjZmFA6MiL/Xg7anjVl/z8XXL1yeORwvPYSFB1HXbYM8rqG0UOZuNWOXYyTWjSUNoFC9bcIniN5427HRks3JUROY1bObxPNByVnvuTiNlExgmcH8OZRDPw7SRzdA1C189aogKrndkk3N33rBqHCFkPETxqU3LowXcnXrGpReUcxkpWqpD0urC5rWQ33Ijcr4yyLCZnlHANBysHF/YSzkoAocr+c1QtENV4wNFiGQakT7WgcMW4etayWTRtFI4JUGEuQ1Qy3DRKPFfnBQNKy/oxh+9kXBceEbThsdLL7kmRiR9yxoa73muFzFEFk48JZuZYlJK7s/jheLNkxqtFE9WDqPgtGix2K33Q2nZ5BwXHq0VTeNZVPIaD162WeMi0E/FL3P2M0QrTwxQec3Th44bXYtCMpJqD5X1aA8lDS+tJXzqA4jKy1Kj0eiLH/U1XNVV/XGr8pFf+QDS9y/euhpGLmPlVvHquuXrp+78Y6+PG374SnL3TOvDon1/an9//13grwKfBh4Df3U0Gv3Ss7y4P+nayDTrmUiKulqzkSk+vZWxkTlGkwavI+uZYadjeb6vGSaaO5OG3ATGZWAvs7y6nqAU3Jk0rXxLc31dc1wGHi8c4zqynorsJk9gK9NCKmpEqhGVIrWaQRI5KSOlUfSt4mYvMKkFxZpZaZgbLwMCiAxjmGg+tZ3w+es5szrwcOkYl4EH88BPPJfzjUnDVjfh6LSmZxUxAIjMp9eGo/UzMdJbpbi7cLw/E5KPak2wKycUsEkNL68pdjoG7yMr54lK0YTIJ1o88JOlZ+GCaNozzV7XsNcxzF3kthKZ1N15Q94V+ZRCSFJGRaYNPD+0XO9oXFSMy8CLA0PhFTf7hl97UlF7GQZyZJBZSR+Oaf+8lsJWx6K1ZjtVHK48b01qhqnmVh/ePBF/RHmWlaKEEJZpeKFvqKIk3RsdzgMEtYUtrYgIJSzVmiYJlK3XIdea5waWTCs6ieKk8Gx3DKeVABA+s5nylXHNpAr0Ek03MfyLL+V8/aTmjdOGrUzz117t8+Zpza89LmiCeB8UF+je9cwQlGZ/zXK9b/jkRsJL65afemNBILKWGbY68oAOCocPsNUVR9RWbrBGsZFHOjaKfyLAJ7cSVk1k4QLDVKGNbKuudw3DRDNpneFlAK3Xm2BBAAAgAElEQVQ1X7hu+cq4omzlZ1rLoISGvgVrDIMWXTuvA49WgX/mZkZUMuDNmsCLg4THK09QHhfA6MheRzxBp3UgM5q1viazntMqUjoZWruJ+EzWU83cSVP+fXspj5aecep5Ujhqp+hpuN61HBXiMh9mYmYnSI5I0ZrHu1aR+Lax10KZ+/hGyrjwzJrIbsfwsXVL12oeLCT08fbAtpk4Aa2jAAS0UOM+s5Nzb+ZYuIA1mtTAjZ6mYzUPl76VlllSqwk0HJdixjdKUJ+bmSYilLUnK4fWsJ4oXGjJdMiAuJGq85T6tdS0/hTV5iHJ6+tGNzIuxZ8SFVzvJXzuWkZzxhi+ZLW/v58Bfwv4V4Gt0Wi0tr+//xPAq6PR6L//aK/uqq7qW9c/elqdB5ICXO9qPvMB78FVXZ769Gbye4aRr53UV8PIM64PjVsZjUa/zHdA6NSsDb1L2ia/dIL9POkYruWaF9dSVk1gXAW2MtjtGLY6KV8dyxZg2gQezB0PF9LEN1Fxs2dwAaxW5Dry+Wsp7y4CfQOFjzxaeMY1WBUJMZLZQN+KOX0j0yxcZFFLyN+ZYX67Izr7YSJSsUTLCes/flzx1oljmGqudw2ZhtdPHPfmDW9NxCNxXAJtk5sYGWqS1mhttGjctzLNi4OEr4wbkVB5OYHNtSJNI0elbGzuzx2pUax8wPvIIsC0DJQxEhA50G7PUjrp1o+rwHtTx82e4IfrALd7mlfWE04qOdGe15GDMsgqNCjuLxq+flqTaZi5wIvDlMcrz6KRLYVWcmpeONlylF42GBt9RQyR18cVVRuAJ6Q0z0amCUhT2tHQzRRaadYTySV5YShM4ZcGhi8fNyxr2TokRkzOp1VgkGhu9i2DRPH+wjEpPZMqMKlrtnPNc/2EMiiKVWBeB3IjkqoHC8e8jvQSz8Nlw7wJpFo8ElWIFD4SUfzgjS6zypNbxd25BEcum0ATFbMm8I1JzW889fx0HemkMhT+0PWc0ybydOUYJJIZ8riQe9oxsNczPNezvD93rLtIieLpKtA4T40iRsnj6IbASRXZ6WhUVNQRogs8qiMzF3iuZzBK07MBaxSmpaFpZFitgyfT0Es0oW18NzLNPzqoeLJwfGPiSFuCltGQKENi5L1Xetn2qfb9N60jAws7ueEHr+e8PW2ofeC49LwzqUmNZq+jeHcuSOLb/YT1RHFvGdjraN6biv9FRcH2KiXenVAFdjqGV9cTirZR6LQyvVSLX2TSeO7OHKOp4BvXEskeWdQBZRRdo9jONKsWV7aZyevhoPQ0PmJNpHGRh4uLnzH9RDNMJNBxMzcMEni+b7gzk7DRo5bW9dLAsJsnDJLArZ7h8TKwaALdRBNjYKtjcS4wrgMReW/1nRI/i9F0E0UV5Lpyq8gibOcSbjmtLucwAvy3CD7+XwPO8L5vth+/Gkau6tuyfv6DEq1bV0jfy1yf3kr5mXeL83+/MrE/+/oDh5H9/f3/eDQa/e32z//FH/T3RqPR33oWF/Ys6rQKPFpKYEOqYVFH3p071jORi4zrgJ82gDQ1v3MkCef3Fo5lI5jcaRNxrbekDiK5cUEado1Qc+7NPYWPLKqII55Tqgrkhp+lZnsg04FpHZlX0nQTW1ToUiRMWkVyLSjfp4WnZ2SzcVIG3p013OgY3p81pFpxsBSTbtVmH4QAqt0KqJaC5aIEO2YGls6zkSqK5iLpOzdRpELI1qD0kVkdqEMU9GyMEuCoIj2rOCoCPnqsFtnKcRmoY+TLx6Kr10SqAL9zWNPEQNcaukbMvPfmjju+kQ2EgZMAyzqyqAoOl/E8+K6KMoickadiENzs2xOParcJPoikTQExgVkTz2Vzck8ja2mkiWJ8v7/0PD8Q8tOikUGkaf0+hY80IXJceUofGaRKBtRC8lc6RhrDk6qmZ+F6z6K1YFV//WnJqs2yOC5EfjO0DVpJWN3tgaVnWolWCHStlgyJBE7LyJNVYJhqNJF3V4GjAna6MCQyaQI/e7fg01sJHaN4snS8Mw3kiZDASge/e1hjdhVGw8NS0beeReNaipdICg9Lh2971cqLn2hcCAq5b0Uq+HTlWbR+CRXieb5GjDLwxfa+hhaPVYfAV44bfuugYi3R59KoOshmxWhBXzdBTNpaIV6p0Ca1Kwje85VxhW3vZeVlAEo0/NZhI0GHNiEl8pWxIxAhaqyGkypg9AXieFoLoCLR4lPpWgUqUjWRSS3D4ZNVw/1ZoIlwvauYlp63TmtOWwxwTuSolPuxnol5/RuTmrenktfjAjS1vL81QqED8YCUXgaiWS339WkBCxfwQZFrhTORx4WEQGZGvGJzJ6CGRMuW6MmyEUCAUlgfWDWB2slwZ7W8jwsnA1/XSgbQQeF5b+74zPalPZX9K8ArLSQlAIxGo0f7+/s3P+Lruqqr+pYVY/x9fpG/eOUXudT1waDKN8ZXw8izrj/MkXPrm/783B/yv0tT78waXhka1q3gX08qz3oqUhurFettuvGijiRaUweFQjYUvVSfN6kdIx9rWgzuvIHKRVKruTmwOAQ3W3gJZ4vIZkLR0oLaxg7gtA0oM4q2EZG/U7UDy9nftUpkYx5NE6TZDRHenTWsZ4Z50xoPkGsK7dc8z0g58yW4iFGR0yryvTs5f/mFDi5KM+8jTCtpDnd7knmw0zEYJfkasUXGrhpPbiQVupdIw2c1zBuZHnyAJkpjv9dLKNqthfcQiZQhsteV9OqTylP5QGI0ISqu9QyPV5JDkWi5/jMuUGjvY25l43PmZbBa0ZwTsUTj72OUjIxanqeOleT2pYt8YiOl9jCrI0+XjrzNf8mMBN4ZpbBtzkPpA7NKwv+sgfVM5FlV6+URfG2kZ0X+t2hkSKtb2cxGCkdVpHCBa12BD0zqyG5HE6Ns6qZVYDPTnJSCJiZGlJLHlxl57juJoWPlpO3BQq75/kIa8NwITaqTyKB1Z1KRKkXpFfMmspVr6lbyt5bo8/yM7czwaOlZNf78PWK0BEyWXlLR/RmEoRZJlgucG6bPvs4g1QxSze8eV9zuWzzxfJNnlGCyY5RE8jNalELJa4rIZqYonDzO0gVmZZDrzjS7XcvCyTA8SDSLRoI5Uy3ZM9M6cr1r6Vt53cbY4okb8XZ0jEIRea6nuZYbpk0gN4qTKnBchBbprOilGq3l3uStb2jVyNfy8Ux2adjIRIZodfv+auV7RotXxbY0vUUj75UEec0/WHj6LfTAGsVeV8zwTQioNidHRRlOzza3XaOpvJjYqzZslBY84KKEr1btkJ4qCZJs/ewtxvxSVs0HDsn29/d3EJbHVV3Vt12Npo57i4ufoZmBH75+Jem5zPXBYeTO1FGdneBd1TOpP3AzMhqN/r1v+vNf/9O5nGdb00r04a8NA8ue5YuPazpG8fJ6Qq6laXln5sisUHe2M824DpIIrhSp1iyjeCd6Vk5LF428QHuJ5sW+oZdovn/X8sVHJb1EnQ8OAEN7sbUY5rCdag6rQOVguwsRaU6cl4baGLjRMSitGJee67nhSRHOGySrYIliLYHDdguhVBswZ6ShCY38s2NBBTEQv7aR4IPi5aHhlTXL21PHbzwtOSilgX55oPn89ZynK88wgZPSsJEFtjuWg5UjRsW1rqH08IW9lNePG8ogjXqm4atjx3qiUVqRGdVuKxQHq8BebrjeSzitPbnR9BLJFkmUBFH2rKLwsJYIRWxcwuxCuslmR6Rri1rkaFnbEGYG1juy4Smc4GQTJc1oGmGYWwap5rt3LMNU87KPPJw7olKspZrv3cl4UngKJ6nXXWtwSaR0MlQJOlaRJwI0yK1QqTTS5H7Pbsr/+k5gUsnjyrQn19JITptIkmnWEsXcRTYyw0YqyNlMK7Y6hmUjspztTHFUBgovMqaNNvtEa7mGa3lk7qKABBRs5+Lx2MoNiQbvA9Mm8uqGZcd7fnsV6SeaW31NjJHSKzZzw0aM3O5bvjFtSI3CRZGlpVZjiay8DOiLJrKWwLR9ftJ2A1a14YMdAx8bWjpG8zh4bnU1hZdmuPKy3XBRzOrDRFLqdzqyDZJMGsV2x7CVg1WK48qjUeyvJ2y3WEwX4IWBlYHfaKoQ2epoxkXgxaGlCvCxtYT7C4cLilmAG0PDINV8z07GTi5+pkEqcIST0jOaOhKt6VqBDETEJxSjkL2S9rGXTjZvN7qW3dzQeM+hkq3metb6aFpUNC0VrWfk+cqtYj0zVC6iVaCj5VCjZzX9VHMjiNxuuyN5KIk2LQnLtNsqRxMNOx3N4SqSm8gwTeT9XkYMAghYy+R5MzXsdg0vDsz5YcclrP8N+On9/f2/CeeBu/8dErp7VVf1bVcf3Ir80F5G70wHflWXstYzyU57uJQh00X4xqThM1uXEwxyGerDJrCfjEajzW/x8cPRaLT7J39Zz6bWMsUvPSz52fcMJ2FO6USOcatn2ch1uxnwpFbRMZqnK89R5ai84H4tkFkxnFdekbTJcImWk+5pHXi48rw/b1g50X5nWjEppcktGjnVX8+kedxINLn1PF1JU9FNtOQgOPGsZEaQsZnWLGrPQRFwPtAoReVji4WNPFpJK2UN2BZla5Q8tm4CHQUbHUuoG3pdQ+kjiybw90dLAvBo6dnfyPjxvkFruNm1PJg7TqrAURlZOmlMXbsJcDHyeOnop5rHS8e09hyVAY8MCut5uwkJkceLhtM6nsusbvcjt/qGvICDlSdUgbmXz58hd2sHTxsxM9Oa7zWQJLCTGZat9Cxrjfdn26aIomc1z/UU37WR8u60IdEKyopebrBasfKR1AsG98eey7nZs7w/a3h74jgsAyEKWWk9FcBB46HwghCe1oG5k21ZouR+LJrA66c1J5Wc1q/nirVcs/KB0ousq5/IBmnVDqbT2nNcyKBzvScbj83cokCC+krP6ycN9+ZeBq4k8HARmVWSZr6Ww6vrlvvzhEnl6SSa3Y4mM4qDlVCvFHBcycbn0VJCKztGsZ2DQwaOGwNDVGKGLufymqtWgbrdMGRGpIL9xJBbQVwro0iQx7NoIpMq8KRwLJrIuIw8XHqMliFlkCjWM8mC6SaCwD0jjq2lCjAYTYvUVuzk8N3DlOstbrfy4idRSlLRE2C7axigOS4dh4VjXHlSrUhMZLNrGRhFYUue20zpJYq/sJfx57bTcyzjMNWcFJ6urfj1p4FFGTgqA4mOFD4IvQ64nml6SUSXAasUW5lsf47arJZVkNc4UTZInTa/JiJyQd36aXKjyJV4gB4uAsVMcLzrKdzuJ+z1LJ/eSniwCBws5fTt3WkjckcXJDBUKVCeR8tAwLOdG272NUSLWnoSrVizmjRGbvQMa6lhLbu0m5H/CPivgK8BXeBt4O8C//lHeVFXdVV/UH3QL3Il0frOqNc2k/NhBOCNk6th5FnWhzWw/z4B8v7+fsK5MOhy1HuThr//jQV1o/Atreqpg8Y7Hq3kZmykmrKJvFVWzBuRmxAlXdm00p3GeTYyRekUTQjoCO/PnJxUZ4onxRkVJ/C0EnM6iFSqchBjQMVA2RjWMs0ggQcLKJ2QdZZtwNr+WsJh4RmvGjqJ4ES9j8waSfOuIwyN+ElSBePiQtKUtdhXawRjSwycVjALntTIwPG7hzWZhWu55nDlWTSeV4YJv3lQMa0CVkUOVp5FI9kjjxbScGsNEwLzyjNeeQlxyzVdA4+XzblUpIgwK+UEPWnlJW+eNJxWga1cSzq9F5RtHUQiVgfOk7+9E/N5jLCI0HMwr/05ttV7aIz4XFYentSRzdzz6iDhdw5reklkp2O5O4e7Jw3P9TXlAnqpYjvXvDJMmFTiBXq08kxLwcbGGAkxoNEoJVsSHb1Id3ykZwXJu3LSdG/ncFQ4TitJ7q6CJ1eR0xoCkb0uJCpyuIoM2y2DhDV63p0FXIzsrydYrfmtpxXWKOZVoGvhsIFYi7/JtP3l9Y7hVx6VNCFw2lK7lrXjzlKGnb/8Qpe3Th3vLDXORPE3EJlGMVVvpQpvDG+dNOx2NEdlYFzItiO29x5kOAR46D1bqeLACQ2qiJHHy0hqFMFLKKBtZYMrJ891ksJBKVulWz1JbXchUvnAaam50TMUdeColnuyv5ZQeMW7E8cn1xNOKrgzrdEoMh2ZeShC4Lhw1G3Yp9wP+dxkAXudyNwoilKhFg0/cC3na+OGSRX40Zs5G5lmOzP83N2SkyqwnWlOK8/hKp4PXlaLJO1YeXq29XpFue7awbh0rJxIss4CGgvgpBRYgm4x0XkCs9IxrRSLJnBawPzi9xpHBUyqhu8KRuSPSvwep7Vsk87S35s68rioMYpWsgWL2vPOxOOBrhHi1nHhCLUiX8j9e2V4aT0jrwAj4L9Efr/8n6PR6Gsf7SVd1VV96zqtAl86rH/Px67yRb4z6rXN5PcMmm9cmdifaf2hw8j+/v6v0RJN9/f3f/UDn74F/MazurBnUT/73ophpjhum4J+KvkTy0Y8CIlVbHUNpYPCOYZWybYiUSwqIdqYTNLQo9L0VGS3k/Bo6TgtPXliOKk9Ox3DWmZ4smroWkVQYi7tamkotIaONez1NC8PU+7PNalxPFx6ZrUkT3/+Ws5mrnm69KxcwCrNx4ayiahDRKF4sW+wRr7mvA44pGE2GknU1iLl2u0aikYano1MkyYapWGro1k1kQbF7YHQp45LOfndzA2TWoLv+gk8WHrxtBhF18J6aihcZFJ7nutbbIsodkGIUVpFqkIGuMzARm641tE8nDc8KTy9VhL02lZG6SPfOK3JE9BtkvimFupSVLCZyuCogCJA32qu9wRzWjrZ1HQT6CaRnY7huI48NzDc7IqXJjewl2uOSkmwV0qLfCZEXhwYDgrY60pY4MIFFIqhFWP0d21Z2UhEaGhIazE8KyUynbVME5XC6shORxEQT0ITDLvdQM8q1nIx7T8/MJxUnsyK5M8H3SbLK2ZN5OU1w6Q2PFo61nND1NA3nscF4AXL/PE1Sy/VzJpIbjX/3PMZ92cN95aBXqL4wo0MFyM3Oob7JpJYxXrHcn/uIAoiVmnFZ7dSDpaeJkLXatZSz6wRD0iKSARjkPdFphVRK17s2xaFLAOkA46dZyNXlC1tYC27yLXpZzKg5FZxvZ8gXvfI0smwniWaHR0YpIZOani5a8kMjKtAJ9G8NLQ8XQW0Nrw8tDxaNsyayNIHBoniWi9hXHiqOrDbFZSvNbCRwUZuccBuJmS0d2YNn9vJOK48W10F2tBLBO/sYtOGG2peXTeU7mzTp/nYhiHX8rUjiusdS27kdb90kX4qUsyiETlXrhVrqbxPytZTZbSiJtKzIjlzQe6vVuIZemmomNSe9Uwzrs7yTQy9BFbKM67k4GGro0h1i/slkmtBb0ci8zoSjCTU3+ibSxfQtb+/r4C/B/wbwEMEH38T+M/29/f/AfBvjUajyys+u6rvyPrFh+XvkUR+Yt1yu/+hIaVX9W1cH/SNXCWxP9v6o941fxfpAT+H/KI4qwgccMlQv49XgawdCIrWeAoiy0gapKHCgxL8qixFAk1omy0iKhh2BpprHcNmZpjUgTdOhKiz04FVIxuCWeU5WEkoW2Kgm0g+RaqEgrN0kTdPBAFbR8Xn93I6VvFz90qc93zpoMRHxbWO5jObCQ7N/rrlwcJRu8hvHjW4GMmV4Vpfy5Bg5DFsdwwrF7k3czwtPLnWqEQyNnY7hkcrz+M6UDmR/ZxU4iMIMdI1ivVUGqF5E5mUgUxLtkGqhb4k9CLPqpHT/1u9wNIpVg2My0jHRM7YCH0rDXtuFYNEshjKMuAiHK8817uarhGJnG69MK5FEfcTkcf9wLWU3zyo2EgUaaJJtOJ45eUJVIrPbmWULjCtAz2ricBeR3FSBxofmTrFZOo4KEDhSS08mMtgd6tn+fppI76KnmGzk3KtY1nWnv/j7oqvn1bUUbOVKTpWkMgHRWAaAz5C5QLzlqwWW9rUx9bhesdShkAdoacVT0vP+wuPjrC/YdFETioheE2byJ2JBG1OmshaovjUZsLbU8VublDGsWoCWaI5qSMHpaOfaDSBwlteWU9QWtE3iifLwJOlZ5goDkpFJwuk1rCWGJoYGFjFnalrtxQS1rf0krA+TAU3bVGoVlq0lmpSrc63MLMqUHihRYWWrHWjoyhb43hmNNdyxVEVuNm1jEvH9+ykfGIj4VcfVyyawKQdNpogWOzdbsIX9sTwGULk0Srw2a2Ucs3yD95e8WTuePvU4ZH301nAaGY9UQmsoHRwWkkA4poCZ9rNSRCJV+UjrwwTplUkVYrnuoajFhyQriX0U8XtQYoicn/mCNFJOKKPTFsPTwiWpYtc6yq28oRJLW7+2kecD3zumuT/PC0cA6M5aeS9Mi49TcvsVqZ9Z0QZtu8vIkZJRkFmFT5APxFZ28rJwOdiSxxroJMrtBa55MOl0Ne6VgbdbRN4aWiJ8VJKtP5t4EeA7x+NRr999sH9/f3PAf8L8O8Af+ejubSruqpvXb/w8Eqi9Z1ar218gKh10hBbGfdV/cnXHzqMjEajn97f3zfAXwJ+ZjQaVX/Y3/92r51c8dYkUoTWFMyFJGXloJPASRlIWlRs6eGUyGYuw0bhYJh6TorIaRnIrcN5ADE7TOrItA7SvLWNqY9gI9QxMC49tZcGVSPN/WkVQUXenjk2Us24dLgIG5nCxMjjlWfaBD6/l9FPFIs68uZpQ6plcCh94O2p57WthCIojsvAemrQyAnztPJoBT2rqCI8LTyPFrLlUEq071UZcd4xyORUGA3vzAKpUVgVOamF2mMT8WYcF+InyLTo5b8+kcyQ232DVYEnKzDKM0jk/k7riG8D5Ga1EIwyI4PK/bn4DVyQk+WqEpyOiWK4XzWBr41rVi2latMqjtuEcx8lhf1B6yJuvPgwtjuGpytp7u4tGu4vBbHrEL1h4eD+InBa1+hdafaOi0BEiGiPFjXvzioOSsnSsCrw/gxotf4ooWkJ2rlFKOuWFhbhwdwzSyMdCwerwP02b2M9VUxd5BunIksbpprSeebt1io3iqL2LGoF1G12DRRNYFpDNwZiojFK0skTDXrS8ImNlKKJHC0dxoi07P2FyNlmdaSXik9l5WBeiZxw2XieLGGQidTMRSgbCdxUrRfqXAbVboM6JjBrAuNSNm7DVIhTd+eR9Zz26wZqryVo0Ei2yqOlpwxwWgdK7xmXkUEApSKnpWLpHPtrCTsdzcxFrnWFavez7664P29IlRDYDldnWz8ZfE5LuXdlK2ty7UA4AZLG88ZYCGmbqfhpfuewxmjBcb+78AwTzVoqXq9xEXlhwHlWTu0DCyd+q+M6khs4KhpQcOcUrNEMW1xw6eV9f3dec61j6WhFESKVC5hEnSOqA4LarrjAGKoIjwvJiOlE2Sj5RgIrSxdYNZJIb7QQtCaVl59FLaVvmEp+0dszx4HSfLIJl9Uv8q8Df+ObBxGA0Wj02/v7+/8B8B9yNYxc1bdRuRD5xath5Du2Xhwaeladh1lO6sijpefW1ebrmdQfucsfjUYe+FEu+vZLWz9yo8OyaRG7SHN6VhEZQDIrjWHdZiEkGmatJLRnhbJTR2myDlaOIkR2O5aOUUzqwGYGR2Vk0UR2cmmc6gA9o5g3npMykiDJ7Bu5UG96Fk4Lz1ePa3IrTXmIIiUapJpZJabim13Dk5XHB8GZVlGa4bVUNheLKkoIHZHDwtO1ityoNidBk2p4tBDPSGpEkpO0m5tViyXd61nGhafbvt+aKEbdjpWmrw4yJLQ7JDZzObUNUT7nomrlYHKvQpDT5cZ77s8alIIbPUPXaK51NPNG/B695CLgMG8JWXUQVO/jZWAjg9Ro6gCbqaKfKA4KSa6ufWBWy4nFK+sJ17sGFwNNEExs3fogciXyGIsMEADfmDghN3U0kzpwUjoeLRueLj19qxikFqvkMYFkZ0j6unyN2ssgErw0m3kCqHbAqQJ5InSwrlX0M8MgNZzWAUNkXDnJw1CRQSoUqkEqIXnHhUcp2ca5eGbQh8JdbH/qAFsdw5OVYyPXVFGew8xEInI9VsOs8ecUNw9sZpqVa681QtI+vjOcce1kqMvazYCLMEg0SyevkzNvRRlgmMnXmFcy6FVOBpIbHcFL3eol+AiPFo6NTHJpOqlit2voWS1kMKt467RiUgcmZeQLezmPl45x4dnKNVUUaVKi5T2qtVzDrJH7b4BFLe+jQSL3fu7Ei3Jv3rCWaT62ntBLRCZWeNpMGfneWimMjpTet9siafxTrVi0G9LEGBKjWcuMfP0mkFhF5GKbMa8j64m5oJClgveWbCC5rjN1eUQGuk4qW0B5r4n3q3ZwWnksIg9MrByU+Pb+lk6+VicROZhWCtvihx8v/WX1i3wC+OIf8Lkvtp+/qqv6tqnfOqyZ1BcarY1M8bmdK4Pzd0pppfjkB7cjp5e+Df62rQ874v3PwL8L/I/P8FqeeX1yK+XloeGd00ZO35EmT0XOG/REgdUGrTwGaYpnDnpKZDRaC342N4qIELaudS3XOoa3ThsyrVhoaaIGiSYxsGwiVivKpWOnI5Ko7VwoSoWLHJeBrlGsYmDdGvpGUQRFHSLDRLFuDVopmqhY7wimdVqDUobMSNqzi4ofvJGybDz3FoFZE/n4esJeR3NaBbRSbCWRJZrcxFbKIZkjZyGH65nh05uW4yLyytBwf+UJUeNjIFWaOgbqAHVrSN/rGdYSTRMaVg5WLjLMDNu5SGeUUry0prk/b849Dp/dSvj0VspxEcQ7Yj2RQMdqFCLx8simqpeIvK2MgY+tp7y2mfGlgwoXFM8PLEY5uonisIysZ5pXBpbrXc3SK/7CtZwvjxs8Yp5GSfNnDbjWDGyRgXQ3VwwSy3szMR8vG0HI7nWFhvZoJajeKp5hkhXdxKJxLNqskyyRAbOJEopp2gElO/u+GkBxo6OZ1x6rNdpHbvQ0i0aa0G6q2UgVMRohjUUEA5xFtoBtJygAACAASURBVHORwjVBaEzP9S1FE9lKFXemgVfXNbf7CaUPrJzi42uKN6qK9VyzaAcIogyrVotnpW9jO1wYtrqKGAIPl56NTDDB1zqWKkSeLj1rGcydIhaBvgGdiowoM5I/UgW4NbCMC0dixCfzqS0xUv/ywxWvnzi2cs1mbllPVQsGOJMuiifp+/cUP/FKhxeHlmUDg0xhgFkjmSldG+V1oRV7fcPdqYQ5dgwkETZyIZ3pdtDsWkVqDd+7mzFMJH1+5eBja1YGlUVAacUPX8+IMfL+QugJP3Iz41cftxuUmfhT+qn4iEKE3a5iXDgKH7FK8eLQsp2LfE+1A/31nvid3p00fHYr5c2ThvsLx1EhByEdA9e6mojI8saVpKrvdjWrRmRhnUSzrSJbmeTFnNQB15rmEw0v9GVArEOkn2mqCrayy+cXacuMRqP5t/rEaDSa7+/vX8oHdVXfufVBpO+P38oxZ6dWV/UdUa9tJvzW0QWg4I0Txz97qdL1Lk992GHk+4B/f39//yeBB1zYLRiNRj/0LC7sWZRWsJlrbnRhs28pXORwJcnQ1sBaKsbsbqo5KiK1DwQF/RYfe1pJs1F7TUQzSBTWtObxGNnpGnKjMEZyFXZyw3qqqYNIjJ52DCASnWUjzbppsxoKHymbQOMDIdEk0r2eN3yND/zc+yvePK5JtQxAqdZULnDg5ET47qzBRTHNdoziq8c1B6WnYxTfd81ycxjoh4T78wavFR0gURqrIy6IpOv/vlczLuGkEl9CbiS9OlGwZsTcf9KID2W7HarmTaAJkVu9hJUPHCwcyihe6Bt+/LkuJ6XjzsSxdIKYFc+AYk8ZXhgalk7z4tByuPI8Wjgcin4SGSSKVSO+ljfGNe/NPasm0E81NxPNp7ZSvnsr5fXThtJHihB561Ri2I9Wim6CBP7VEM6GTa05KSUVuwzQjZE7M0/tBO36/NBigXnjebz0F79ctBi7c9N6Jbycqj8/lOc80eIdeLxwGK0YWEXHGuatrGZcStaEVXJPQ4RUR5aNBPxVQZHawLSWxxwAg2ShHBQiq1tLIEnldTGvA4lSZFZzeyAbg8KLR6abKAKK63nk47viRfr6Sc1h4TFKmmGjI5MmEiIcFo6BN7w8NPzYrQ5/5cUev/BgxVfHjtlKCG8RxVoq+TpRyZYl1ee2HXY7ik9tpTxayKDz2qbkhAxSzSc3U7QWednduee4DGxlhq6VHJpEw/fupPzzz3cB+KVHBW+Oax4tAxuZ+HTqJjBusdXWKm70LF0jEr2lD7hGSGd9I++p1EgDr73jp74+Z9kEVk5eO68OE15dT3htUwZBReS9aeDurPn/2XvTGMvSNL/r9y5nuWvc2CMzcqvKqoraurumq5eZ9uwz3VhgMxjQfEDGgISEGCH4hiwBH5AYviAQSHzBlozQYCxskCxs8Ewz455u93RP71U1XUtU7nvscfd7lnfhw3Mqa7rGHgqRJXd1xyOlqjIy8ua5555z4n3e5////Zk7kWBe6FjGdeDm2LG/iIxrxywRoIVSsNk2PD9ImdSRllXEGFnOFJ1EcWNYc3fmCFEgEZ9cSXl+kPBw7nn9uGJYeBKjmFQiXZMgVc1qSwIPU61YyeTZ8WDuZOJl3svsiU3iPdyZBVpG0U01WZN9dKX/sQIc/ulKdnZ2fgX+mWmNZ9qIs/qxqg/6Rf7ihTOJ1k9avfxnTOzVP+M7z+r/b33YB/zfbH59bOu0FOPsM/2EB0M4mjtGTTp3jO+nfR8sPLbyrOWKQy+SCBCJkouyw1yHwLAQT8WwjKg2jz0aszry6kaKc5Hrw5pI5FOrqaQ5I7KSuQvUAcaVZ1IHpnXkUs+w2VJcH8PBOLCUCkY3NvKcwgnxaaOl+eGp48Gi4lyuMNpQ+MCVnmU1h7dOKvqp5vqwZhFAE9DW8N39kswbsrYY8lsGyhB4WIg0rfayAA9NWvnxAgr3Psp3XEa22ooQpTlYxMDpwuFDwIVA6SV3o3biL/B1oJ8ovrVXcH/uuNy1fH4j4/Xjii/fK3hlPWE90ywlhmFRMy5lkeWiEIZAGraAfDaP5tCpPN0EThaeUen5/EbG949rUqXoGni48BzPA6stxULJRGct0xxq8BpOC1CI5C0x78v1rp1WWK1YzzXTUnwRlY8EpXAuMK3fl6pVEaZR3puyiuOFZ7kx6A9Lwd2CGP1LHxjXsmj3QaQ3h3NPP1MQBel2Wku4Ye0jN+tAz0rDlJrI7UkDQFBCfBsVkU4aIRd/TJIaXj8uOd+2LJqQi0kdGGjxovRsZPe0Yq1lWc0kWHFvEdAq4AOMCkCJ1C6EwM2xTPDuTkdUHhbNxOa49JwsYL2lWUrg7hQSHekmMK9kKrKUwY1hhY+RuYrcHNckWrw4qZbjvTVzbGSKO1PxV3SM4qUkQ0fJhfnKg0IwuGXgxZWEo8pxb+qIRCrXyCi1NObXhxX9RBpbpWAlk2vkOASWNLQy8c2spIqyrjlsUMldq7g3dXz/sOIXzuds5oqvPip547hmZ9mylmluTz2jk5LjUj5z3UxUJkXkmRUxwA/LyN7cNwQ5uD1xXOkZvvZwzv0Ggd2yimHp+VvvTHhlLSXTiu224cHEMZwHus1rT0qYqUBZB6yFjtVUIfD2qaNlYW8eqZtpjwviTXLIua9UpKg9WsOlDD6x8rGViRwAf+v/5c/P6qx+LOr2xPHO8H2ht1Hwq9tnzchPWr288qNL5DO870dXH6oZ2d3d/Z8+6gP5qOv6uGarrflLV1qE2QlfGSWSIG3hmSXBzE6rSKU9a7mlivDSsuZkEbg/dwQtD5zECN4zINOU9ZbkfAQU3RS2u5p+ami1FNNQU1SBhYettub5lZR7Y0HbRuDORKQeF7uW3Ci22oYQNdeCJJrnRtNJRRJW+dgcr2Yj14zqwEERudCJPNVPyBrPytV+wusnlWBWE8VSljwOQbx7GvnUiuZnN3O+tV9QAmtI6OAgbeRoKRitsO3IvDHJamCrDYsQWc0MGx2FBoZFxAXFJ1Yy1tuW145KglK83ATOlQEO547lTPOZjZyOhQuFkL7uTz391PCzWxm/eD7hqw8rnNFc7SfcmzomdSCA7HRrhVKB0oNH0U00g0yxvwg8P7A8O0h5Z1izHkVuFlG0rRDGznUs59WEa3WL68ExKWE5hyv9hI6Fwon5uJcqLvdTxpVnKZUE+tsTz/1pjdUiAbIK+pnBKMiM+CFOCkflA6nRZFbyS3KtuDdzPJrWbHcUvdQwLoNgW61kvHQSzWHhSC1CYwpB/AdREs33FoGWcRgliGalBSLgIxiluTQwtIym9IEYYaNtyarAVtsSmwDMVMOsSY58YTmll2lWZp4bo4oyRpYa03lqNEuZZq1tOCkkj+Zc29BNFS4qLnct4zLglWIpt1zVnoMyooxiOYF++r7R72LPstWyHBWBh/PA1Z6hDPDMkqVl4aiIXO4p9ubSjFkNX7rUYrtj+P5hye2J52rfklvFl2ybf3R3wc2xIzNwecnS0YpZiMSgOCkdL6+mZEZxY1zRTmTRXjdwgF4KkzJw0ny+3cRgjIR+ruTitZk5w6OF51zXkBpNP9M8rTVfeSg0rpXMMFYeF0Elcr187nzOaemZVIE80cSo+IXzGTdHjmElk5LcajqJopdqHk1rHsw8f+FczqyObHcDyaJm5mA1V6woOFwEnIa11NLPmqDDqChjJDWeQEMrSwT9Pakl6yY0fqjnepZP5wV1/HjSb3d3d6/88z6GszqrD1sflGj93GbK4OMpjzyrP6deXE4QQbvUzbFnVku211k92frQo++dnZ1/ByGebAMPgN/Z3d39Hz+qA3vSNSob7XWInG/BM6RsZIrDEn5m1VJ4ydh4a1jzha2MmxPP+bZmXNesZoZ+JojTR3ORzYyqwHKm+OXzOak1jArHW6eR/ZnHeXhhOcEgVK1Hc0lZvz6smbrISq755fMtXjss+NqjwLD03JnBwsliai1XrGSWv3Au481Tx2nhKJ0YiQsXWfyp3fpMB4wOrLdEjrTSVY+lJzMPPWQR/WzfcPNEMa0C96aOzGheGogR+ntHNedammrqcEGaKwtMmwA7pWC7regYxfMDy2EhO/YnRc3BIvBw5nhxJdJPNNtthdGaGCO5kYWZAm5NHG0LC694rm9449TzaOa5M3Fc7ho2O4bffLqNUorfeXfKpAqclIEHc8/xIkjQXACtIkYHfDQULtJPhdxUOCF6eRQxRMoQ6afiybnchudXOsxrz/cOaq4sWTqJ4rSIrGTw2rGjYyG3godd+MhO2zLILC8MLEUdOa2FbHa5I4vr48IzLiVTpJ8mfOlizuWueYz9+/ZBybtDzbCMnOsmtC08mjpujBxLmeZg4R/7HaxS1NGwmWv2mknLnYlIs3wzLaq8SMR8hEu9xqMwlwXxlb7l0+spdyYOhfgqQoQrJnBbaxZO8ldA8Zm1hDdPLbcnTkzyRCaNaf2t44pxGdFasM6bLfEktIxiqhUXO5aLXUvHwuvHNf1EcX/mm6lh5KSUBPtREZg4mNWa9UzxxongqLWOKKXJtKZjI51EZGYPZo5RJffUUelpzXls+n9pJaGXarpWsZoLSrvjAj4opk6z3dYcFSJ/W03lnrw5AqMURwv3mLallXh5FHJe13PNsFJEPHszT4xwZ+zoJSLzmlRy7betQinxmLSNYr8IZAa2WobNluULWxn/6O6c7+yV7I4cCw8d3eCGfSQ2RLOWCby6Lt6V09Lz2fWEt0ee87nie8c1zguuWOEZVQ1ZzQVOatkMyJpcktoh9DkPvVTxzJLlcO7JjGJ3pvnqw5Jn+snH1TdyVmf1sagPNiNnFK2fzOommqf7hhtj2TyLwFunjs9ufGwn0D+29aGakZ2dnf8E+GvAfw3cAS4D//HOzs753d3d3/4Ij++J1VKmOFh4bk1kl3Mjk0yH0suEQUIDI2uZLDjuTByT2tA2MNOR/bljVEdCgJVckRlBvX3zoOKF5US8DiGQKEHZfmu/ZOYCRkkDERQcIyb4k0Xgm/sFt8Y1RkfKADoq9udBTO1NMOJ7pKxpJbkPIUaOC8dxKYvSpMn9uD+tKb3hYsdyc+LITGRUieRmUknw3vePaoyKTOrIchaZ1p5hBUToGDhsvDPthhJ18N4iqKGLPVxEOknkToMFvjdxjGpZICvgzZMSBVzqJdTBsZQZdIyclkKLutoXmc3e3HNUOEZVYL2V0DJwc+SpYuTG2PPMkmUl00zKyMwJCtg3i3GFoGStjhwuPKu54k+Oa3KrKZ3kZhzMHP1Mo3zguNK0fKAboY3ku6RGPZZNnZQytZo1PpSOFTPEzEWOS0HznpaBEMWE7nzkxsShFZReYZSnYxVV8FwbOXKr2GqJZl8BezPZOe9aWZDujryQj7SYjid1oGOUyOlipPDyZ9dHDs37i+h5DeiGfmbgwcwD0pQarZjVkUdzz5snFec7Cf1EZF3fODWsLEMv1bgg/qjUWKwWVGzhZYG+cEGCQKNICX2QRPlMJ8yb89pJBA8dYuS7hzXTOtI2hioEhlUQCZyGw6JJYdcRohLplQus55bRwjOuPINM4RGpg9Hw4iCh9nBz4jkuAmupoZMqag8PJl6CIjti6j8tG2N/rqld4Gt7BZe78p4PF5HdcSRF0MWzJkAzIlO/tgm4aCgqobtd7CmO59LohgDWwmEp97hqmsCTsrmHtSClM61JlMJFwVH/7zdn3J06LNK0l04kgT0dcA58AzPopoq3TmpeXElYaZ49isjrp47CeXkGKJhXkVLDSRRvWcuKLGvhRQ6XGGlMXIQQIzdGMsHZaMnzYG/m+cqD4nHi/Fmd1Vk92ZrUga/v/WjKwb9w5hf5ia2XV5LHzQiIVOusGXny9WF/Wv27wJd2d3f/xu7u7u/t7u7+DeAvIkFVH4t6pp9wfSzpxqmCy33L3AU2W4Yb45qFj1Q1vLyScbTwguV0QeQ+WhCdpWsQq1Gx3BhMh4Vn97RikGiskfC3QSYI1ipKQ2CbTI1Ea2ZNDsC7pzUaScQunWKQKiKRce3JtAwGx2XgUtfQfY/KVUXmTkzHqsl5yJtx4bQOzL0kvQ8yg0JhUGJMrwQHvGShZWQaYrU8VH0UPGxAjPK+McdG3sfJDjKFBaoahmVgUgmBq9MkiS9nRqYhwKOZnONFLQSvXiqm3vvzGqtEjnR/KmGDbStp6K1EsdXWfPewYO4Cn1pNpHlbBDpGFsggDZpREoqYGoVCs9oyXBvVrLcMkzqSJzIJaieK00Kahb1CU4bISma4OkiY1bKDP0jh3dOajZZmkGhmtUx3NlqGuxPZzR+kMh0ofOTllZRZHTlaeFYzaRBHdeSTqxm5gRsjx9wFYrMrnici1Sl95LTwdK1gdwsvUwcLHDSeikGmH2fELKWaRIuXyQVphHQU87ZS0DKRRzNP22ou9y2DXHNtVHO+bQTI0KSBp1p25pcyAxG2O5qbo4pUazpG00sVoyowl2iZx7LF1VzIU4cLR+k949rTSzTdRKZciVIspZrTSkhTmiahvMnTqHwUFLCPeBTrLcvURWa1NHill2u5YzVWa/YXTacZ5XXLGCh9JDZY48xoXICJC2LiVhqtNOe7lspLo9dNNDUyEUo0j3HIWsm5iL7BFPuA1bLQH6SGRRAMdY00LkR5H1ZLI77wAaJM6SZV5NmBYb0lSGKl5H5ItWwgDFJFp0ELj0rZ6Zm5SG40L6+kKBW5O6l5fmA5LeQ6MIjxPtEymYuxwWR7obFt5AZrxDtm9Pu5NkaLz6twkdQImayfwNNL9nHi/Fmd1Vk9+frDhyVVeP/3T/UMzy6d8RV+UuvPhB+e4X0/kvqwd1AHOPzA146B1pM9nI+uljPNdscwrQOHHp7qWH7zquXaUJCb/TZsdxNBxmq4OZLd306i2RlkzOqShfPkRqYb7URjFZwWjtMqkvUVr67l3J06qiAm7q7RXO4m7BceFyKbLcWkNpxvW26OHFttQ241W63IYSE7vgHFr26LtnyzI/jff+1qm2kd+Ps3Fzycv0f90lgr6W8+0fSs7Ni+tGK5MfasrRmOCsfMSf7B57ZS9k7mfO58xrtjx8LBING8uJJyZ+p5aillXgcezj2zWrIRtJb8hG6iWctkR36zZThcBBINa7nGI7KWHopxFXDI+44N0eipluVy1/KD45rDQiY/W23LZktS7XOjuNQ11EEWbYlR5Nbwl67kHBVeAv9qT6cFi2axaLXId0Zl5NMrlj98VLGRS5bKZkszqmE5FWrVeq45WgSMUnxhS/Sfu0O4PRFpy3bX8vnNlFmzWF7JDTsmsl9EyVtJFD+3lXJv4mlZuNJLuDutcUFkRhe6lgsdkQ9ttg2JURyXEaMV/8qVFo/mjtsTz8RFXly2tBLDSeEYlpGn+wk3J46uVXQSzaWeZikV18usjnxuw/DmSU0dI1opPtEzHBRCUKoiPDdIuNJPiCHwlYcl65lmraV4dsnyzrCiq+FC1/DqWsL9mcN6OfefXk+pQ2SQyfV2Y1iTG4U14nnZahtujIQsZbXmchdeXElZyzWHReBSTyRfRwvPxEngYMsK2ECmLoq1tuVo4VnLpJEGhSY+liJ2Us2nVizHReS4CFzuWZ5eMsSo6Saa2xNpai/2BFV7WgbeOa3JrWK7K9jsGCPPL1lGTiYfS6nlag9unNb0U0FMHxaBhQu0MrneUqs5lxsu941MMnzkqb7Fas+juWClMyuek6d7ht1RzcwrVlLFJ5dTllLJGvnihYRv7hdyr1hY7lgOCs955dkvIpNaGov1luGXtzO+eKHFvanj0TzwS9sZv/Vyyn/12phOolCF5mpfpkUHM5mSJE0ztJQqApqyltT7uYPtriFGkQp2EsUg1VxdSmgtAiup5OWMyo+nd+SszurHvb78T5FonaVy/+TWnyFqHZ81Ix9Ffdhm5HeBv72zs/PXgbuITOu3gd/7qA7soyit4I3jineHmnfdgqVGxrDZNlzqp6ykmjsTx+uHJYdlYDXTPD+QZOgqBMyJEIUudmWh9c6w4rQS0/T+QozvvVTjo2gNlYpMfWDcpKpP60g3EYnHWstQBTieOWa14HiXW9LgHC4EKbvZMuwsS57EG0cVkchmW3bOVzLNwsFR4TlaBOa1F7TpVHGuYxhkmqe9ZW8hvoy7U89pqbg58axkhtVcgvAmdZM2XUfqENjqGLpWJjTGaDZyw+WepXCRVqL41FrKvann9lQyQKa1TGsWDUVr2Uomw7mOfTxZ6WeaT67KROL22DGuPQ/min4qjcI1J2niv3g+ayZYNWB4dS1FK0XnqOSkWVQGZOFulaKXRG5NPJkVk/vlXkKMkSuJoIjfOY28eVJRLzSXXORwEShDJKC53FM8nHv2Zo6/e70it4YrPcOnVjNWMgk1JEbuzxzjSkIEz7Utzy8r+pniQttQeBjXgT8+KDktAsstzYWOpWsV9yeOb+2VlEFeZ1gGbo9rkqZBerqf8uq65qUy5WLHMHOBk1LOY+FgsyNo6KyRoKVW/s0qRi51LYeLwMWOIbdQeMXlnixQQeRPh4vA8UwxOq5RyKI4s5GDReD7hxWFC2RWs5kbhnnAxSBkt0l4fP1d6FoGqebRzPHt/ZLUyHUdo0znTqrIvME8nesYtjuWcSlJ7wZpZCW2UdFPRdq28IKyrSO8eSKeosxKGOKw8LRT+XzXW9KQHS4iRwtHESIzJzjsOryX9aKYO81qJhOMvdIxKmUist025Imi9EK86TU46E9vJJRN0OZSqjnXtqQmYpSmm3rmtUwXrY5MXWQ1t1glk5eJD+ROJlWjyjfnO3JcQrmoGZWBxEgOUT+FvtUoLcSvezPPasuw1REZ31ERuNw1FMFQR2nUNtqW5UyQwI/mjlkdGVeBaSXNdDdVrLThuSW5l7bamrXcst7WvDCw7FVQhkii1cc1hf2szurHukKMfPmDSN8zv8hPdH3iA83Im6c1odkgPKsnVx+2GfkPgP8eeAMJWq6B/xX4Dz+i43ridWvs+MbDipsThw6wv3C8dRI419a8vJLxzb2CnhVJjVKSHF76yNcfFry6kbKRWw5zTx3h7qTm7VOZLuQWCZ4bygLwYleakdKL3uM4eMa1yCvyRDwC3zko6SaC7ATRlVcerhfwVE+TqMi5TsJ39ksezRxfe1TydN/y4iDhBycVb5/ULGeaTgL3pzKN6BjoJ4prI8ew8Cx85HzHclKIROuojPR15I3jim4CmoiPireOPa1EPBImgomy6B+WMMgCJipuDWs8katLCblRvDCwHBY1dyZODOWIlyM10LNwUngSrTjfNhituDHyHBSezMhCcTnVXBvW2CZAsm1Vg5R1/MPbc64uWVYzxaWu5u9cX6CQDJbZe8ngBvbnNR1r2C8Czw8SDheOaQWByDqG149KEq3oJZpOEnntsOI7BwWf28zpGfjmQcVbJzVLGSwczJxn4TyjJiDycxspD2aeURXJdaCbKv7Jo4KdpYSLHcvDmeOkCKy1NHenHh8juYW7E8esityZVtRBYVVkVIuHRwMXO0YmCnXJYWH49e2cWxPP/ZnnxeWETMMfnZasZpppFTgqPKMi8uKKZVZHcqt4NPO8vJpwOA8UITKtIkYpHjY5IgdzaS6PSkWr8tybwHEReO2o4mc3MwYJvH3qeXfoeHrJ4Lzn/ryRgyHm9ZaJbOSab+2XWCW78cMi8mDmsErOWdsq8iaJ/fppzVpmOC0DiVb4EFnLNbfGjl4i6OPjhee0DEIx83B3Fug1FLmHU2kabk8cPihmlWfq4d6kFlR0kIfV4cIzqz0Wibq/1yS77888DlhUsJZGvnNYsZoppi6iFUwqT6oif/Qo8PIgZatjkAiZKLjjCN5HQTrHiI2K2xPHIIE6yvOgl4op/+9cm/Hz5zIyrTgtAzMvZhsfYbIQAEA/Beel8d+fO26PHddO4eqSobWkSJRIOG8OK9Zzw/2J40ZZY00goEmaYM7TKlA5MCYyKiODXIz2m22htN0Y13SThEUdKTwMy8jFrvm4prCf1Vn9WNfrxzX7i/c1Wl2r+MJm9s/xiM7qo67tjmGQKoaVrNdmLnJ74nm6fybNe5L1YdG+Y+Cv7ezs/NvAGnC0u7sb/vy/9eNVX98r0Cby3FLCDxeixV/KNNYYpj7ybN/y2nFFZhRXlywXupZJE5T29rDmrz7X5V99usU/frDgb787wwNrLcX5tqWfacKoZuoCM2doGfjCZsb9meQkiNRCCDlGq4bYo1jJxZwxreG08qy3FEWAXmbY7hgmLvL79ws22uIS76aaz6xlFC5yXHqKUpFaWE9EytJNNYMcHkwdy5nhtJSmYK0tGNh39+astzTHRWC9behaTcQzc4GLnSZMr45kieGTHY2LYq5PDTzdtfzlp9q0jeL+zPFzmy2+5hac1gGD4qm+TIwUgjxeTTV5oviZtZQ/uFfQNoo6Rp4dpKQavnxvwbAOdJWmmxh+ZTvn4dxxfez4xKqYwxKjeWYpYW8uTaDSgdVckzZBjFf7lvWOYSPXJNpyajzWaB7NPC2rWG2IR/MRnFhFdKrxfARGVWAl17gI5zpCICsc7C0Cn1hNeOvUsZEbzrUNB81E5eklkfC9tJIwrwNWC852KTWc7xiGpYRfTuuAj4rVlmZv5im8eCVSrcgShVESnLecGU6qyCBTdNMEqwWH/AtbOdM6cH3sWM8Nmy2RU53vCtVppaXZ7liM8kybnJrLPctqrnl7WJNaReIj57PIZstyXArk4GrfoDUclZHMSGDj3jyQWs1GLpkoAVhOJJX97tSznClSo5k6yK0iSyyPZo7VTJMaTYiRSx1DHQK3JzVf2Mqpg+zQ5wZ+6XzOo4XnZBHopJpeali4SCDio8iQioYgV8XIK+sp14eOXipm+c2WYVRLs1XHSC+LFE5ReDAq8qULLf7gwYKoFCupIe9EhjOZPh0WnvNdS2bE1+IirGaaKoKqdQAAIABJREFUxMJn11PuzxzPLyfszz0HhQSaXurpJutEMkSmPrLWhJd2rMZoMFrzztCRacXnt1q8flhyXHt6WhMIWMSb1TLw7HLK3In88YWBpQri73hrUnG1b+mniltjz4We4bgIBAzPLVn254alTEh1JIK4JhH531KmUFpzpWe51LNMK/GLlR4+u5rwM2vpmXn9rM7qI6jf/YBE61e3s8fZUmf1k1lKKV5eSfj63vuBh39yUp81I0+4/r+gfZ8FfhM4Dzzc2dn5u7u7u9c+siN7wrU/D2gEh9mxkCaaTCsmTnattwcGrRTn2obttiEiMqQXlwwP5uFxoNEraynvjhzeR04rQbtCI8sCXl1PmbvI59YTuqea3GraRhZyRVAQZef17lQahWf6FpTiuwc1lzuKOzORZAB0jOK4CuwsiSQIRJ5ypWsZZJpLXfsYgZsZWciuZZo9Jb6BhYdOE/SGUty08Mpqwpunjss9KzvDMfJoAVd6hiIotprj22wLxvXzGykxRv7gQclmrlFK8WKa8uKyLOwiIn/rJ2LojhFGtbz/4zLya9s5Pzis2W5r3h45OkZu7pXcsJJrfv5cztSJ/G1vLsni79W0jgxSxSBL0CqhYwAlGQtzF3l5JWHs4MVlOZ4YZcLz2lHFSqbpJQqlYI7QkWg0/ArNvamH6DmqYN1ILkThpJFoGUHWXuxqtFJc6hmmjsfXwl95qk0v0axmiu8cVtybOrpNhkaMkscSmzFuajWtGBsCkyzyt1uakzJwtW95Zkl2sN8zxH/7oKSfKMA8Po8gRvn3PovjMvLZ9YzPrst5+v37xeNjWc8Fg3tzIojYSz0x9r87koX93IEi4kNkNdUcLcSkf7FjeLCQnZ/ttqb08M5poN0QxkCx1ZLI9Ttj2GhpLvYSFh6u9gw+RP74oOI3rrR+RD/93rXz/JI0sV2rRFpnhJ611dJstS07A8u3Dyu2cs09q3hlNeGtoaN0AVdFLnU1RVA83byfCx3Da8cVLy5bvnOoeaoL2ohU7WQGLy1bvnEY+eVzGVqJXOzNU8fzS0amhKnmxTTlhYGczw9+Bvemjo5V/OHDip2+RmnN3Mn04YUly1EpF9R6rriTa9bbcj/+4EjMImstQ+UjT/cMIRoOC5kY1SE+vrb7ieJCx9JLzY/cZ7+2nfE/X5vxwrLl9sSQGSiCaqZHkVc3MqYOnupbQog8mCt+6+Ue167t8exZ8NpZndVHVmdI35/O+mAz8sOTmt+48rGxTH8s6sOiff8N4G8A/yeC9v0E8Nd3dnb+vd3d3f/lIzy+J1abbc1J6amaFOepj9ydObxXjXlZEKKFj7ioMESUVvggaNzfeXfK/jyw2da0rebEiSSm8JHCB47LgEJkLFopXj+u2JsHRrWE9VknC7RxGSWB3Ue0EamKJI8H7sxkYjMsA6dl5Kj0GCK7I0cvE615bmRMuJJpWkZxq5RdfgMMcsOwDpReJDlKKYxG6FwxMq7g7VPHcREYVRWVjxwVnjqKDGqjLYGEx2XgoHGLv7CcsKg9D+eO//aNCg9c6Vl+bjMjac7juIi8eeLxDYVovWXYLwyruX587sdOfBNfPyo5rgLDSqRlkRKlRfq2N/MoFfl7N+dc6VkUgr2dVhISmWjJvJjUkmL/+w88g1woT4NUsz93FEFkYm+PaoZFICpFy2sGHU87le+d1/IZ7C/Ev7A/j0QlWSV1iHxjr2ThAydzx6AlHp3tjmHsJHX8Dx4s+IN7BQ4JP5zVcFJ6Dpowy2kdmLiIKTyFCyxcpFSR3GoyLc1KO5GF6aO5Y1LJpGKrbThceG6OIyqKL+G1Y2mktBFC261RzcOF5394cyzTjcYns5Rp6gATJ+//YOGpakE7W61ZzzTvjh0PZ55pJTSx1ZahjpHTReDhXMAAqYbDhdCcEh0ZNQnrgcCilutMKzgpI90kUMfIzbGQoXqJIKTHdWBWSzM2Khz3Fx6LwsdIZjVHhWdeBooIRJFFTirPo6mn9HK/fOug5s60Zm/mmPnIg0kNSvP2iSKzcK8lnqS9IjBINYelZ1rXDOtAVcH3jysWLvJ/3FnQsWKKH9eeR7Oa1dzwYObZ7hgOFjIVmVQR33hh3jiuOCoDbSMel+8deVyQJrqdwKh05EaRGc24FvRvHSIPpoKtRoHSiqVUcVoEdsc1szpya1yz3tL0Uo1CUXpAiY8MJN9ms63ZL8Q39Oapw8dIGuS1EiNyz2tDx37heO0QqqBYzzT/+EFB/8xXeVZn9ZHVo7nntT9lXlbAF8+Qvj8V9WdM7GdJ7E+8Puxk5L8A/sXd3d2vvfeFnZ2dXwB+B/hYNCM/v5VzYygNR+0jD0rPwkW2cijrwA+ngQttjY+RN48r+gk8v5xyf+KpY6CdSMDa2EWCh0ktjc3pIqAUhBCwRnNSeF5ZTXnztKYOsNmSILtHI9lpL9x7xJ7IpIL7tWMpbfTwReBK1xBi4NsHJUspvLqW8Uf7JS6IN+WkluyDl1byx74U1Zjja+8ogxDAjJJ8g6NFYO4iK6lGRcXuULr71UxxXIhJODdwXIqvo9NMCXIN4zLw+/cWjJvpSwySQ3J75NibO14cJIzrSGoUxwuH0prgI+u54fXDmt98pv343P93r0/41oHQhzygApw4qIY1F9uKSaE5qTzbbUvpAtcafN7DqWO5ZViyihuTmv1F5KmeNITHi0AniTycOb6x57nQMXxiJeGdk5prw5qO1fRt5GABx97x6kZOZmBvFllKRc5VRlgsJDtl6qCXQOFkOvVoIeOoSSnc2spFrvQMPzyuudA13Jk6Hk0DD+c1basxwEkVKOuAQSZuMQq2VUzdgdIFai/TreMi8Owg4VIHvrFf8f2jiis9y3xR83AaWG2JJ+F4If//YOq5NnQYHWkbzWkI3J06LnctJ6VmvWW4OaxItKKlFRWRd4aOV1YTNtua/+16wVZbc66tuDkJvH7kuNqXCdKjuSBv51GQwINUcbFj+MGxp51E1lLYXwgxa2dZ9LNvnlS8sGwpvcABLvUMdyaOwgUicGMsi+mttqH0cGvkMdqRKplIagInhUYrR6ZhJbfcmzhy857XRBrvYSENUMsGxiV0U0mxX8sNrx1W9FPND44rwfoi99L1UWStBTFI83BzBKstkfcNUs2X7y74mfWU/XngU+sJy2ng798uGDa0sJPS8+apI1WRhYf3YnhDgMMZfHYjo2UV9+aeeR0aXHSgpcGhGJYOFTXf2A+YGFlpaSLi97k9lmamCpG21byyJpjxWQ2fWEn5vbsF213D6Njho+L+3JMvKVpKMawC18qatEF91zFyrp3yrf2SpYXmahnOJFpndVYfQf3fHzCuv7qesNHkSp3VT3Z90MT+w7Nm5InXh21GesA3P/C1P0aQvx+Leqpv+bee7/B79+a89kg05au56K2nLnAltXQTRaoVB3Mvqx8Fmx2DVobCR7SWPJAXVi3rbcWNkWNcBIxRPNVOuNyx5FZxfx54ZkkwslVocguUZDpsdS0X25aDhWNaR6ogU4iNluG5ZckimFaBXiIG9K225V/KDe8OK25NPc/2Lb++3WLuIdWG3CpujhzHpee0CLQTxWfWc3yMzOpA7T1ae/JUUThB167nhttTxyBVrOSSV1AGwa4arfnsRk5uFaUP7M09pY9c6Ypf4qQMsoMchAj0S+czvntYsda2+AgGIU+9smY5Kj1PYXmqb9FGJGZVgBRFty25ESHAuFakJvKJlZTMaMog8rKTIvDKRsJyahoUr+ZiV9Ktz3UML6+knJSed4aOrVyz2pKd6ipEXhgknJYRFyOZhYt9y7NL4ldIjOLzmxltq7k+qjgtI+M6cLFt6GWaOkS6VtMqPfMazucaoxTrbfGrtKwit/Lfb9cV3SYbpPKRzCpSbRnVAe8jc6/RKrKSGqZeiGOfWRNM7pW+fRySuJaLYX1YBXqJ5tmBnMmjpmHZmzsezByrLUlUR4NVmuADZYTt1HBSBC72LJWPLGWGtous9C15ItfIZzdSFgFmdWQ1V2jlmAV4sZ+w3qIJz4xstA1XegkPZo5PrkpDMCojSyks55Kz8cyS4fa4Zr+IPLek+IVBxnKuuTtxdFLdBDPCWstwsZtwd+p4ZmCkQQGu9hNmLkgGSARrFZf7ljzR3JvIBOG0jHSsIWl7Zk4M4ku5YH1To3hpNWF1rvneQclqpprP1jAvarZz8Rwt55r9aSBPxevxybWE8y3B8H77oORffqrNVsvw1qlnPdNNIn1kvWVZ1HBYepYyRaOuQgHPLmtaTe7Ks1ZztPDcmtakStHPUrpWjvX6WGSJGx3Lcq7ZbFmmDT77+YGlkyieGyTUQXJxPrMsJLlX1izHZQAyHkwdLavQCl5YSVktHXcm4sHpZSJxa1mZsowdXB/XfHb9zFB7Vmf1pOuDfpGzoMOfnnp+kEjwcfNz4P7MMywDg7ONnydWH7YZ+W+A/3JnZ+c/293dLXZ2dlrAf958/WNTg0zz6kbG125Fnl7PmNQiDzouZEdzZDVP9RNeWk5IE82zSwl/clyiYmRvLl6GrtUczBxvj2oudC1/5WoHBXxjv+TOtKaXiLb9C5sJHSu76y0LW21ZUH9+I+VoEXg095wWEnt9UgnFaDmTf3M91+gYuTkN7M0dxMhKrpnUjusjx+2JkIe+eDFnNTes5SL7ePu04mAeGGSKrz+qHstlBqmYe8cVVIg/ZH8RuNLVTJzgadsRnu2LMTi3ghaNDWJ0fxHYnzuUVqymIr/yRN4de9ZaNbcmnuVUUL00qdV3Jo4/OXXcn3pujWu++qjAe0GfXmwbZj6SlIJr7aaK0klC+MJ7Bpnm0+sp1sBSYnh+kKCI3BhHKhcYOXiqJ5+p93Bv6qid5vrYoZTi3rTmXEtzoWd5cWC5fzDnVCu++rCgaw2bHc0LyylXlxJeWbXcmQR+9/6CdiK0pnGTGbKcGtZzxW9caTGsxCg+qiML51l4RdsitC6rAMX+XIzz5zsWM/Nc7RtOisje3JMnimIRCUjj0U00m/n7D7IIjz0wCvETzOrI/WnJtPbcnXkeTj2dRORwLihikzI4D4KRrUIkVXB35lmpIqVTZC5wPJdgwJeWLUYQUrx+VEtGziIw7USeWbJc6BpSDZd6CS8MLH/z7Sk6UegyYpWEELaNog6KZ5YSnusbXjtxZEZxfVSz7TSvHzlWcglEdD4yn3pGZeTe1LHZ0sSo2Ghrnh1Ybo/dY7BDZkSOdrLwFC7y8nrCrWlA5gmGvSKiiTzdN4Qoi+9MS0jiSsvwXPPDYm8R+PqDAhlmRTZalkQpUhV5tIjcHMvxpAruTD3/5GHBqI5cG9aMSpFe+qixGgrvmdWQaEVuFG0jr3E0j6QmsJIJnnu7a2inil/cylBKNQhrz7sjh1ESEJrVkVPlGaSKhYOVTPNoHuilimf6CcMy8A/vzPmjvZILHdM8BxSzWjPIpAl8pm/Zn2syVbMbayZV4N1hhVGKWd9wAc7yRc7qrD6CKlzkDx/+aOr6l878Ij81lRnFc0uWt4bu8dd+eFrz81tnGz9Pqj5sM/JbwBbwH+3s7JwCy8gm4aOdnZ1//71v2t3dvfTkD/HJ1GkZ+O5BRSeBZQuvn1TszQTJqhWcVpD6wKDwaG1InOdC10juQITlTDGtIj84LPFBkK65hq/cLyQpOsiC6rgIeOD144pLPctx4cm1ZItYrfjKwxILDAvHUfl+wvbMBd48rRlWns9v5BwsJJSvcKJnvzauqTys5poswsNF4Mv3FvzS+RYnpSdGTapF+vF/3VngQ6RtYE7gzlQGPUsAjbk5MdLdtxLxnkQi92ceVKQ90bQS8R7cmjgUMDWaHMW9macIkWEVWM8VezORqT2ceZQOKOBcy/D20FEHRDM/rCDIeZ67yK2pYzUzlEGISgqoQ+C4FI9LojW3RiKPG9WR7x5W3JnUInGLEEPkhyeVBCtqRdvAw4VnXsFSLpjgh/PAWvScloY7C8VMSYBh2wr61ocKF2kmSLExoAdOCvHy+AD7c08/15xUgUwrOoksZltG0U1Ev/9g6ln4QD8xjwlQuyeO08rTspqThePRwjGvJck+1Yo3jit8hNy0eKZJ7u0minEdH4MQTorAnZkjErk2co1nAUYVFA56qUim6gCZDpxUgXsTaYbbiTRoi0JhUkfWlwb4TiI4wtMicHtSMamhk8jrvnFc07HSiCgib53WWODezLHwch12U81pKR6jH55UHBae9ZbkoTycev7BnUKmR1ozqTxHhfit5j7iQhAvSoyclHBjLDtLGy1pou5NPUupoZsoJk6uUd14sgBaWhLoDxeBXqo5l6rHmRrbbcNpFdifeeY+iOEbKELkpJDwxLtzj4+C1B2VnkkZGLvInxxXzF1sQBByfSXGk2gYlxL8WfpA4RUP6kg/FXz0vYkjhsizA5kITivZVMh14O3Tmr1FaPxdUAZPCIpEKx7N5d6bushWW1P7yD+4Pefm2HGuY7jUFlz1t/dnnO9Yznfk/OzNJNckNPfp8TxQI76c0scGNyrZRmd1Vmf1ZOuP9kvm7v1761xb88mVM3z2T1O9vJL8aDNyctaMPMn6sDOmvwr8OvBFhKj1xeb3/+YHfv3Y1vVxTScRrOZyEjleBAKymI2ysU07gSIEThaetlUczj3PDBLmLohZtfKi7XaRT6xkZEbhiWJAtoASGs9qJn6GN44qLnQs6y3NxEUGuab0EipXN4vwxEA7VfgoJKo6wO6pNB4SVmc5LIOQsRJFnmjGDrY7lqmD7xyUdKwms1BFmlC4QGLAK02IYnqfe3BRghQXdSTXYkyeVpGWga22pQpi4LUmopBd5s1MEKWzWnapjYrcmlR0rGK1ZVEqsp5ppi4yqb2ENpaeRIsX4Z1hxWqueW4pwUVpvARN7Jg7SeJOtMjYfIRcKyFfqUivCdw7KsSfs5zJBOhcx3BSeI7mnqKODS5WkLe5USRaxql1iLw7rBjWEqDx7FLKha4lNQ20oArcbaZM51oJCwdZIjvuo0rM2R0LN0eO5UxzvmNZyXRjso7EIIvsceXZaBs2W4baK2Y+sJwpbo9rhnUERNLlo2KzY4koOlbz3cOCuQvEGFnNNMMispprttuGW1NP5RRWKbRSdBNNLxFJHcCsluvDKNBGcbRw9BNNFWgoamK2Pq6k0fnsZsq1Uc1xGbg1rkVSp2Att1gimYmMKvE+lCGSa8Ug00xr+b6lVDF3EY9iJRe/zbwKbLYsSkm6uVVyvCdloJsoFDzOV2lbTeEjy6nIzCaVZynRLLyY5ZdSzf7c07b68TXqgmCPZ07QyL1EM6vlc7vUMQzLyHKm+ctX2swqOC7F69Mz4hXJjSKESFEFxlWkZwWprZWijIp+ppnUIitUKmKNXDeJkWPSQKol76MOsWmaIUTopoqFj9RRsZYbrvQsN0cVdyfSZIFI1NqJop/KeziYvz/aj1FxqZfQtpobI7nfB6lmq2OY1/JsOi5cE6yleXrJkht4NJXcIJTcqz5C9qdk63LWz+qszupJ1j9NonWWuv7TVWcm9o+2PmzOyFc/6gP5qGtURlabVOLcwrm24cHMUQWRXq1nsotZB8XLqwmfXEn4/lHFC8sJV/sdro9q3pgGEhW5siQNxkGhWMsMk9LhA5zvGmJUzJ3s+M5DxCjopYYvXkj45n5BL9FMm8V6ZgKpVnilaBloW3Aeph7+9as53zyoUEjD1DKyCEqUItGatUxzXHomdaRujLArmabygXkt5Kd+qvDR0jaRmYNOEvj0mqCHv75X8dxA5C65gc2W4ZfO5+wO5b2UQK41l/qaO1OPQhZqIUasMvzadsbtaeC5JcNhEWlZTeFkYvRoFtgZWG5PxBdzoQ2tjqGOKcPS83DuCVHxqbWE7Y7hwSxglBdeuxKfzcs9wyAzkv/RJMQvZ4pz7ZSZC+zPA94H8sa/calr0TEy9pHttuXFgebGuOa4jKzYyMVBwkZLmsVLXcP9mWfmZRLxVM9ye+rZahtciJK1YhTn2xqDLBB/ZTvne4cVX9hMeXdUc3siO+4Xu4Z+qlnJpAm42DP4KGSmdiKhgDdKz1KiSKxIuuZOksdzY0iMkmNsGX7zmZSjUmREm21NP9H8/gPPhY5Ga0MIkYV3WOCokgXxcmbIrGJcBpZSRWZF/mNUJEUWqhHFiwPDrM4kHX4e6DQZMBHFUeHRaFbSyM+fy5jUkSJE2qnmU6spNyYymelYeKpnm0Yv8NxAfFZTJymoLy5bjqtIZgSbvdmC/YU0HaM6stWBy13LtZFDI/dLaJpyiAzLyIWuoW3t42v0qX7CdgfGVaDwka0WWKPopJrnB+9navzC+YzZXc9pJY32L27nLOrIw7kHpfjcekZq4N40MEjlehnXHqdkClYFRd+KtIsmZHElh05qGFWeysNGrkFpNtuGVEWikqT5z2xkxBD4zmHN/alj4eHpvqXwoAjcmwbmzqE1XGxZ+lbz4krSIJybkMnmSdxJNMuZ5njhGdcCoXi6Y2kbGFaBldyglcARbAhopekniqXMcDGGx96Wszqrs3oyFWM8Q/qeFZ9c/dFm5I3js2bkSdaHRfsmwH+KTD/OAw8RktZv7+7uVn/e3/1xqaVMdjLbVlE48TWMKjEzd40YRHMtJuvMyA7+s0uWkypwZ+y5P3U8mkv687CKj7MLQEg5K7kswKa1NAZP9SUL5Goji3ntqOTOxFH6yIWeZl7DYhwoY4QQ8VpjlGajrXluybKSa15attQeRqWYsq2S3eFIYB4i7URzrm3/H/beNEbW7Lzv+51z3qX2qt77dt99mZqVHJIzw0UkJWqlCNlmYkRBYMVAAsRREsRAgiAJjFiQnS9BYiCALSeOrS+KE8iWrUg2ZUGyqIUUJXrImcsZDudyau7Wd+m+vXftb73LOScfnuq+9w6H4lCc4aLpB+i56J7qqlPvOW/1ec7z/H9/Lk7FwOsjx/rIsp9ZFsoB75uP2Z9YBoUkPaedR+HZGFnqU1rY+XpAL7MMc8/60LFUNdSMeGb0M8sLuwWFh/lIcboekVgnrVe9gtTC1/Y9w8KTWDkND5QiDsRTwlpPySjWx4KSLQWKDy6X8A4emw14dCYkt561QcHVbjFty4GdiRU4QJ7TiGBuKvx9rVuQWfFsqQSKRiQnz6Cw3hKHmpNTgbVR4FWIdZ7xwJN6oUE57xjkQrg6W5flr7X0hNYjRSUUg8jTdcNKxVA4eM98yEysacaK3MKziyWeXZR1dXknZW1gWakEWO/pHBTcHhZMrGcuNoSRJEC7qSO24gSeObgbaJ6eD4+csi/vpnxuPWVvYpkrGzTiG1MLFE7BasVgEJ+cWqTZSRxlLXSlUeYonGNrAgtlxXxJUzjHbgpYOJhYtiJ430LIf/xIjYXygC9sTrg9tNPX0DRLmqWS4tGZkEHm+dqBtDHupHZq0qnldD9xlAOpQjWjgPP1gFHuuHog+qjZ2HCqZhjljoH1LHjPfMWgJ1YqJ1rawhInrVGPzgYslsQ7RCFVnO3EcW9YoHBc61p2U09mHZESA8/zZUEtA/zRxoRhLhCI842Q5WpAb2+AqgV0M8dS2RBoyL1UFsuBZ3MkMICkkAqoVlJRMwpC64+MO7VWLJQMy2WDUp7a1PhwdYrA1kpxqRXQCBXjQvHDqzEQ88qu6DjujS2DTNEqKaIg5FJTTA4rRhKI9WHBF7dSnt+aoLW4xZe0aJ+2Esd8SUw7qwHsTSxrfcvOxJJYMT+sGwFYtELNfEVTn8jn3HEcx3G8ffFat+D20B59L2aux+0577Z4Y1ve1w+kdbwUHH/mvh3xVjUj/yvwHPDziM/IGeBvAw3gv3lnhvb2xsVGyAvbGfdGGZ2RkI8UYJ3n7lCEq5VQ2qLywrM2sEdI20Hm2E6snNAXYL3lyl7KuUbIzkQMB7sTh4+kenGoHfnYiRJf3ct4fjtjNtScrBiuHEhSowEUDFP5cEtzR6JFe/LDKyVGuZgK3uhbTlQN13qChx1klkao2Eg8Z2qajy1H3BxYrvcLKoHiZFWoSgepo3OQMlsy7CeOdjNkZ6jYOSgIleLxmZCXdzNe3s1433xENQCPZmOQUgCVaa/8fiq4214OL+9NqBrFxVb0AILVsVzRhMCtQcEwd3x4KWYrESRtrGEv9ZSNpx5qOgc5F5uGjy6XaMWaF7Yz5mLNvVAqGZtji8czzGE2UoRK8cJWwuYYyoEIvUeJp6dhLvYE2nOhoemlcLNvOVf3dFOpMDk8p+sBr/YUNvdc62YyVqWIjSK30u7SSxXzkTp6jkdb0AgDuqnnVM0cJQyHawjEGDGxnlZsuKgV6yPLWl/E/EaJl81BZtlJpGWnn4PK7BRRC61IhNGfWRsDsD4SoEFsFLf7Bd3MERnF2XrAlYOU19KcuZJU2e4McoyC/VxMIh0QKI91ggKuBp6txJPn8FhT2qyuHFj+y9UyB6m0hW0nln4qbWi7iWN3AjOLMaFS3B3mdA4KZiPNJLdc6xccZJ4z1fvJX154xlbIULvjglZJc29sKVWkPc16UE4qTGv9gpkYEuv4k82C1aqiEWp6qee1/ZzWkuHe0BEHkFvFjX7Orb6ll+VsJKKrMsgJ5W7qiDR8Zi1hpWJoxkK1mp4McHknJR9pTsdO/GSsZ6ViqBjFzX7OtV5BaBSR9gyAbu6phw6tFJvTuYo11AKpWGwlOY+1Qrwy7CWWx0+ElI1op05WDSer5gjL+8yMrJM7A8udYYFRcH2Qo7xmpSoJ9N7Y02rC9V7G791N6WaOExWhe31+PaERaxZLBqPFcf6l3QmnagGdaa/yuUbIl3cS7o0doYaFkqY3sWTOMB9xtFaP4ziO4+2JN1ZFPn5CSIzH8e6K2ZIctN2ZJqaFh693c943H32PR/YXI95qMvIfAO/tdDp70+877Xb7MvAyPyDJyEyseWYx4pdemVA4eHQ2ZFLA1W56JKJerRoutWKqgQjthC1zAAAgAElEQVRtK6Gil4nBXmQUSmkqoSKathLtpo6Pr5bYHIspWpJ7ZsrSPnKqJoZy48LTDDUYRSMw/PipkOe3J+wkluVyQGQshZNWo/PNgL9ypkI5VDw1J5jPsZV2nE+fq9DpCp1Ka8VPngx5ak56zg8yx2ws7uitWHGyFvJaN2Nj5CgFnp+9WKGfeS73YSXWnK6Fgs5NHNsTaZt6fCbkVE0xLgQrentoqUWGhbJiP5XX9F5RDhWPzIRsJbIpXihprIdaaLgQarRWDAp4bCbkmi5IrOZUXbGTWBxwoWH40HLEuYYsvWcWI671c8435fT3IHWMrDiHn64FbI8tqVO04mnfvoJaYLDe0Yw0j89EbE8cp2sBJyqwm8qGvhEJ1WouVuR9x22vmCuJi/aFZkC7GZJa8cMoGVgb2KPnUFq0N0/N3W8DenANXZu2fzVjxSemjtf/7NqQjbGgak/WItLCM8gdGyPx0GhEmo2kIFAyP5dahvPNgGs92WRKO58mNnK9IyMtgFrBe+Zi1vo5hVI8uxBS0tDNBEfskE1ubMSwsBQoOgcFMxHUQ0HULpQNj84E5N5zrZ8TG8XjrYhbg2nSEypOlKWK98p+RuE8T7QC+rlH6ZCNicN5i9eKmXLAmVrATAQOGGaOfgGnagHPLUS8uJMxzmG2pGnFhtyKFqXwYoy4VBGzxTM1MbUc5LJxf/9ixE7iuN4vSJ3oLbYmBZH2BEgLXNnIe90YWVqxEOG0hpPVkJLx1CPRrlzvgVOKRqx4tCqVhdR61vpQnuK7Ax0wX1aMCkvuPKHW5NahtbQ8RUa0S85DEGieng1pRDHdVD4sfvJUiXqoH8LyHq6TT6yWuLyb8tnbExbKAc1IM18yLJYVj7c0gVH86b2UYS6UvKVywFov59WDjEHqWakofuZMhYPUsjGyDPKchZLhbCOkn1oW4wCN5SD1TJxiuWxYrhiWtD/2GDmO43ib43fvHrdoHYfEe2fDo2QE4OW942Tk7Yq3mox8szrUD1R9aibWlAPNSslzetrTnVppAbk5baG63s+oBYqJU5yqagovLTwVA9cGlnEhrVwnK4bVasBPrpb4/fWUH1uVXvu7o4LtxPHCVoFDNpbLZcONfsG9xApm1MBibPBKnNTSKVFrY2j5V2sjqpHmp0+VqYeysRjljlEBK7WAk7UAjxwEb4wsyxXRBJyoGk6U9ZGo7kxNcLQXmyEfWIj41WsjxgXsJpZx7pkpaQoEOSxoYM9r3YydqcdKqBRLFUUzDghGihMVQ1aIK/zBxHG7L8Ly1YqMB+VR3os433rRzBTiJL9cMZyui0ldxXiu9Sy/cXPM1rhgdyJ+KHNlw2zZsFARcXotkI3ljX7O5lhQrMbAUqzxePq5Z21YcLJmKBlFuxUwyj3r0xPjifXEGrYTy/Wh5q4vOF81lKbI5spU61A2imcX46O2K+89e6nnx0+WuNkv+OfXhry8VzCxjpVKwFxJ45E18GgrPFpXl5oRl5oFi2WNVoob/YJGpBnmgomdKxnKgSRUWnmu7BfgYG0kRjSHpLFBJu7trQCyWsi8NzyzEPJDSxG5V/z4yRJ/76U+qxXN13sFWyPxoQDFQeb5qZMlWlFKuxWyko1oLVW5OyrYSxxr/RQUrA8L9lMnovuqIVaKMBDa082+VAC1UlRDxaMzEZtjCxVDHBpOVARoUAsU9xJPOVTUi/vi9tVawGrVsJeKGeajrfuI68s7GSUtibxCCG7zkcaiqASai03NjUHB9thyZ5BzbyweJNUIAg2B9hRAb+LZTyxRoFgoyz0Sa8FSn6hohrHndC3g9lASwcP/15y2Te5n0EstmfNopZlYON8wzE438o/NhtQC8X25MyqIlWJUSKXt0ZmQc/XgSNvTjCVpvLyb8pWdnBv9nF4uiVFZK37qZIlGpOl0M17cyemmjnBa1l+uaBZKGqUgnuqeUue52Io4UzecrhnO1EUvZTTcG+V8Za9gmFkWSiJqr4eaNHd8ZTfjdWtoro352InScVJyHMfxNsT+xPL89sOd6D957C/yro33zoX81u37yenLexk/QHZ739fxVpORfwF8pt1u/x3gNtKm9T8Bv/ZODeydiqWK5oYSys/uxGG9Y2diyZ20VtVCc4Tnve0c1dBgPdwaFUwshEpOse8lBc2SYDiXKprtxHJzYHHOs5sU5F6hESPBz6wlNCJFM4QC0RUUwELZkE3pXP1MTug1hsb0d1YqckK7N7EiKnf+yI07NhqDeBpE09Pi2Gjmpq2sh9hTpTwvbGc45xlbRTRNvkKj2Bk7qpHCYZmNNFWjeHXiCKYb0cR6krEQsuy0RUYp6KaO1En72kHoCBXsTxT9XFCvoYbPbaQcTAqWygH7E0vhoZtaHAqNELU2RgX7E8fJmmF7JL3wALVQ08s8N/vi9H5oNmQtrI/EwC4tBERwZ2hpRIoXd2F3bKlFCgPsjh1/nExIrMdZaMVweyR0onYrpDCajZHldP3hWyCxssG82S/4lddGbE8Kklycrv/43oRaqLjYDGi3Ql7Zk83lJ1ZLNGNFPVSMc3EIj406olMtVCRh2p5YUgunjSbUnpf2cjzQjGCtL/qNxZJGecfaCLwqOFM35BZe2st5ciqgW6po+oV4fhitRFDuBViQOmmHC7UkWxsHOWWjKJxncyw+LH7qBUMqAvzUeXqJwAfGuVQbIi0i7hv9Aus8exPH+VhTNZA5z+W9Aj+dq5KSqszX9nI2RgUrVcNSxZA7T6dbsFjR7E0s1UBNKykePSw4UzP0Co/CMS4cN/tC6Lo3LBhPD5+UgnEuaGoPlBXUQqFIjQvBGx+ud4VnYyx46WYoY+p0C842xJRyNtZsTsR7xzlPN7VYFN457o1hP/Gs1jXDqbv8TKzYnwihK9SWMw3D81sZn9+Y8KHlmKWS3Pf/5uYEh2drXHBziiT2VrHv4deujzhdCxnkln4mVZUk86TWs+89sYloTtdLAYRG8NMP3sPV0HPloKCbOqrGk2rYnDjC1IGXalgtgMjD796e0EsdP3O28q5LSNrt9t8D/ipwFniq0+l87U0eY4C/D3wSWVL/S6fT+eXv5jiP4wcnPruePgSFeGIm4FTtrW6bjuMvWrx37uEqyMvHIva3Ld7qX6v/Hvgs8A+BF4F/APwh8D+8Q+N6x+KjyyUCFLeH4uFQeMUg99RDaTUaF+IH0ow0uRfcZ2odkyniVCnZGJUCDd5xvVfw0eUS1/p26gMhp62h1pyqBySFxzpBwQbGoLRUW7wH50QjckgUUgoc992etxI5mZ2NpRXqILXMlTX7E3EWnytrBrmc/M7Gmhu9jCT3JIU7wp4qFNVQdCz1UJCnSnn2JgWVADbHBYtlIxoKD5VQU40UZeOZ5J5xZgmV4IuNgqrR4s3CFP0qPGFSa8ErnFNERgz5oqkoNzKChl0fWUa5ox4q7oykPakZa3IPjVjEwR5BBG+MCrYSS8loKoFcm1ALWjXJwWioRdLykk49QcqhZqkcgoLFsuZGv2CYOYxWVEPpw58rGzrdHLwYz00Kd4TXPez9v9gI+cLmhMxPjS4jdSRqzp0nd+IJ0opFo3Gtn3OxEXKhGbKXOQapeLysDy31SLFaCUgLoTRFRjHIBPdrlKyzQebRWjaeo8LjUZSMVHeUUtP6ozrCtn50uUR3Im7vZSP+KL3kPu72YjNgJtbcThQlLb+/PnKcb0acqxt2U0s1AI1na2xJp2CHzZHjmaWI+ZII0J33gJsKppnOjyLzsJdI6+K5mgEtCzZ3jkDJeFqx4WRFk7v7iOuLzYDNiaUeaSoG7g4taQHPLJTYGBUIUUuSoThQR4QpvCCNMwvWek5UAoKpXmJixbV+nHtS55mNDc1QKp6Hr3+jV3Cyani0FXBnIElRoBXp9HlbsYjcKxGMc89+agm159agQCk42whoxJp+7smcI7NycKGUYi91ZN6xNW0xbE4JZ1ZpapFhN/G8epCROZn7UIsZ53JF2ubW+oU4x2vIracWCEXtwXt4pToVSyG461hDXoiHSua8rKNSwImywDSu9Quu9d+VfyR/E/g4omv8ZvHXgIvAJeDDwC+22+2z7/zQjuMHMY4pWsfxYDw9/7Am79WDnPwYYfi2xLdM8acnSf8E+BudTucX3vkhvbNxrhHw6RMFnxlothOP99BuheROnK/Hxf3NyVOzEbFRbI8trdhhlSJEU4s0CyUhcK1UDeca0poyzB2d1DFfUixXBMc5cXCuadhJBBlbDRVLlYBBavFeERrp+y4Zj0JRjzSF99OxyCKPNBTek1g4YcTMrXActSN5FB9ZivjyTs54KoA51Du8uJNNTQ0V7aojLQdsjC1J7vn4iZCbQ2kV6eUerRWfWInZGTtuDAsutBRJ7nFK0YrgTF2wrHg5EV+piOfJIHPkDh6dEbTxxHq0h+VqIOhgrZg42fgtlDSBVoxz2bCXAmmhCbVs9s9XQpwXX5hJUTBf1syUDLlzrA0sXklL26l6QD2AlYrh5qAgVHB+NsAp2SBvjR3eQ6SgETh8oHjvbCREqIn4sHxkKWJ/SlQ71IAc9v5vjR0aARxEgSQ8BkXuBNs7LiQJTApH7wG/i0aseP5eRuLg0kzAI03xFfnaXs5KNUQhLXe5h9N1TT3SXO+J0LufCZmsbAyrFfG3GOWSHD89H5C7+2v4Zy9W+MLmhGEWEBtHJdAP4W4BvnZL1ko90CxWDLMRgFQJ5mLFWt+xl0qL3CPNgM2x40Jd6FadruhoABarhh9Zjrk+sOxMHLMlzXvmI3YnltmSphQIAUtIcooLrZBWBMNc8Vgr4PK+CO5PVAM+slxiPyno55Ks/sSpEisVzdqg4NmFkBd2MhqRoeo8tVBIYM6LAWEjgkdaIecbIaeqhrIRQlolUNRDzcbY8pHlkHUrivfUyev3C0liTzdCPnlaxPuv7BecrBhmYyNGhAo+sRJzc2DZHltKBsqB5mTN0AgR2ITkSyjlGeZybw5z8VEZ56KJqYcKNU0sAq2oT6srh2jquZKhZCS/fGahxG4iOOJyoPhrj1Sphpr1oWVsH76HzzcMByncG3vmygFzJc+rBznOeVaqhpVqwLgHVaPYTuy70om90+l8AaDdbv9ZD/sPgX/S6XQcsNNut38T0UT+b+/8CI/jBykK5/ns+jf6ixzHuzcWy9KqfG8sf4xTK9X3N3qQHMe3H98yGel0Orbdbv8kolf9gY+b/YLLXY03mtWq/CHfSRzjwhJoTTWUCsg497y6l6E0oOBsM+RiI6IZyen0zkQIW1/aSrneL9gYWQrnGRWeWBvqoeNqt2A3KUitnBSfqBrSwjHMxcW8adQUFyqViokV7KhDXMbLgWI3cawNc/ICIgO9kmBrtxPZNGXT9puNUUBuPapsphoCiUOkcS1U3CxgL7HcHVpKgeIg95yuGc43AirBfVO9Rktzsi5u2HsTMWlbrYrp2mJZ2obujS37E0cUiK+DVtI6lXo5pd6dWNRIruXOWJKhQ9H/ilJUQmmnmlhpt8qdGB82I8175kN+eDXmt0pjvJf2pm6qcF4xyCwrtUC0KsqzUpHNfmYdG+MClKISBDRLmsdmQsGj2iFJORChcqBYrhpOVgOu9XImDk7WDB9YiOimjn9+bchrXcvNQU7JiFj+IJV52Z1Ie9vYOhSeTi9nOE0wD1LHTKz59NkqP3yizLV+Lq1qqRggLlfEgDIppGWspOVUP5sSnAKjONcwNGINniMc8/sXIp6YEePNg8zyj17t81rXUg7gw0sxP/dIid1U5nSYO/qZ4/JuKlUUJZWcce7ZSQp6mWKxJDjo2UhhtOOUk9aDuVhTDmQju5c6PIonZkPmYi2AgHrAozP3S9SXd1JS60nva/kwSlq4RoVjmAvlai42WIQctp1Y9hJHqA0XGooTNcPqlEa1VNGERsTYG6OciQUQHcV8ydBNLe2ZiEvN4EhvEij4yImQH1stA/DlnXRaXYDTMxH9zHGtl1MJ5D44JE3l1nO+UZBPMdEv7WRHmhbrZS0PcrmXX+857oWC4p0vG4yGtFBC8EJQxBMr1Ugx/vR4pD3vzlQTFijYHMPdoacSWKJponOxEfAz58q8fz7mWj8/0qB8fKr5OKy6vd7NRXtVjThbF7xyN5siqo1UCTfGlnSicKk41B8jfr9pnObhyslt4NT3aCzH8X0cz29n9LL7Sf1srHlm4Vis/G6P98xF3Bs/rBs5Tka+83irzY//O/B32u32L/6g+Iq8WdzsF/zatTGZh/M1zec3U3InLT2J9dzrWc43DL3CcndUEGjFcwsRMx5e3M4YZClPz0VkzvP1g5y5kmG2ZLg9EBRpoD0nqgGdbsbLe4J/vdAIuLKfszGyTHJHqDXGi5GhUZ7+RAzmuplsgmqIU/RWUkjblJF2HrwYnV3ZS2lE+kh7AbCTWNaHBSeqIYWDMw1zpGd433zEtV5Bbh1fPjDouKCs5Xm/eC/j4ysxm2PHckW8LF7ayxlPEx+PJAgLZXPkKn2IG3bA9X7OyVpAdWqkd2foOV1VHEzEwwUvGNudxDNbgkogVSbnPKdqAQepo5c66qGhnzpmSmL4drhpvNAM+fy9lEHqJAHwnkBDZj2Fd8RanO7nY8WdEQwmnkda0mJ0d2B5dEqE6qdwIla82hXzuo+diPjKbgYonp4Xr5PPrI25sp+TOnEJL6qGF7czAl2QWEWo5QRc47nRzQm9klakmmahbHhhO+OZRflD9cJ2hvMO5cWs72AiruZb44JR4ThZCxjmls3EMlfSPD0X8dJexo2B5QORQmvFfuJ471x0hI691iseGl/uPf/6ZsKfbk54ZlGqWVrD9rggm5pgNozntW5BpCTRuTko2B473j8fcHlPfv7EbMAg99wZFHx4OeKLmxmtkqIRSCvanUHBT50uTRHFb440PkQSR1oSx/rEca4mG/rXD3KWK5KIHEwslQDuDAsyJ8nKZmIxKD66XOKP703YSix5AcPcie9MIdWRM/WASAvbPVSKMw1D4hS91B8lgofo5cSKQP2lvfyhOX5hO+PilGB2uI73M8dmYjnIHLFSOBw7iSd3jrmSpp/CIHXkJU2gpGoaGQRk4AWSsJN4mlNy2NWeaMvKAZQDzziHMICRLYiUHAbEgYAjFAHrQ0svnbBckWpV8oZxVkNJFnuZ4/JOSiVQNEOFc3CyGnBlP6OwsFTWDC10uwWfPF06Rvy+jXH16tXv9RC+K/FueZ9vFm/23v/fGyFw/z76UCPjxvVr38VRfXfieN6/vTjFw+vi89d3eI6Nt3FU3534Xsz7pUuXvun/e6vJyH8NLAP/bbvd3uGI6g+dTuf0dzS672J8YXNCq6SYJDC28EgzZCd1pIVnqWQIlPTDF078RubKGqsUp6sGpRRrg5xbw4LIKC62QtqtiH4qWN/lqpFWL6UoB4puCq2S5nwzpBwYbvQFtduMPB9dLVMLNbf6BQdpQTrxnKwYAiOI37mSYTsp6KVSlSgbGVdqPaPUYYxmMRYKUCWQqoD1ilLAUW/7SkVOVndTe4Q0jrW4atciTTNSrGroZY5mrOTEv4An50KudqfO9KHmVG1q6haKdqARacYWdieWJ+ciIiNVgZOVgPnYc3NQUA41qwEMcit6kEgRGMWpWkCo5YR5ZsrsfpCm9f756CGU7l86W2FnYvnqbo5XmqWKnlK9HCmyGasForNYroqb93YiR/WPzQQ8Nhtyvh7y6y/t0c2h3QpYqQbcHVpqoeZS674L9vVeznbiONcQ/czpWoBSii9uJmg81TBgpaqphZrNUc5uavnISon29DnGhTvq06+GsDZwzJc0M3HIl3YyUudZKhtSr6kEmmEhG+xT9YACxSdWy9zoF2xNRFT/sxcroiuYomPHhUdrmA0F/1tGsaUdOxPHawcFp6pigLc5FlH8Sqz4aqJ5YiVkJ7FsTRyPzYSkznOtb2nPBJTNIZZZcaauuTUseO9CyN7E0c/Fnf5MXRKfPwtpvD9ROKVYqBgeaYUMc8fNoeCi5yqe0GjmS57MeayHc3WFNqKh2EksP3NGxNa/e8dzshqQOQjGObmTKtRMSfPDKyXujiytWJMUnm7m+diJmEAJrvjZhfgIvfxH2/DqQfENcwz374dDbPbX9jLqkbiq76eencSzUFZMrFSKWpGAGaJA7s0TVc0nT1XYTS17qWds4S+dK3EwsXz+nqMRA6kcNszEhsWytNopBBEeB1IVmS+HrNYNhZNk6vwUdV0JFOD4wuaEC9OKJQH80HLMQerYGlvqUcClGdGRLFcNN3oFg0KSt48sh1xqBe868fq3EYcAli9Pv39jpeQb4s/6A/oXJa5evfqueJ9vFm/23r33fPHlLeB+6fdnn1jk0rnyd3l072wcz/u3/94/ESX88p39o+9v2SqXLi28nUN7x+P7cd7fajLyc+/oKL5LsTV2rFY0E2BsPc1I0YgCdiaOUzXDOHdsjB2vd3PGhWNSOA4i6StfrRhCBZ86U2GYO760nbIxKrgzLDiYGrF5r5grBZxvhCjEsG6ppLnZK8TN20r/vfdwZ1AwyC1nGyHKOJZKitWqoR7Kyf7NXkFv4ig8XGiELEaa/Ym0uTQ9fHgxZid1VA18vVuwMcoZ5I7tsaMaiXFa7jyvHeS8dpDzwk7GxCkWQ3GYT62Qvq72CrLC88HlmNWa4WIjkvcRqyNMMAgCd1zAswsxzy6IE/zhY760nXLHQDVQHKSedlNza+gYFo4AOFHWeKV5ai5ikHtOVg0XmyE//i36b2dizXvnYn50pYRSin7muDsq2Bo7tseWi42A1ZphfWg5UzMPjfcQ0XuuEfAj8w6/ENNLPUqJEZ5W8NpBhkIxKhwv7GQMMkdiA0qBphEp5mJNxRguNQNW6iGVAJbKATd6kuhVAsXXD3JqoZxW3x5axoVnuaLZnXiWy+JNUw/EYDEHnJPKzm7i2HUe78DiUa2QJ2cCymHEStXQOSjoZjmPtsSl/XPrKZn1DHNH6kTgnltPkjteK3J6qWViPTsTR6TkdV4bKeYzy8maofCK5xYjvPf8fpHysaX4oWt6q1/w9YOcf+98hSdmwoeu49qUq37YRnSxcd9T41Iz4kOL99dBI1TcGni+tDnhhe2UYeZYKIloe6VqmA0Nw8yxk4o3zlZi+aVX+qyPLbenupFGpGhGIeVA000dzsNMbLjatzw1GwCKXu5phEIG23tAHzETa55seOrl8E3X8N5U3/PgOr7ey2lGisu7GfuJPHaYeeZKmsdnQga5IJ2rBq50LZ7kyAH+xe2MSqg41wj5wELpCOOdO4im866UPFe50MxEikHhMUiSUjHScvZglI1ia+x4cub+2BuRYInPNwI+tBTTzxz/9m7CpJDf/sBCCdfv84HFmNwft2j9GfEvgP+s3W7/f8Ac8GngY9/bIR3H91t0ekLGO4xIw4+dPHZdPw7B+z4Yr+znWOcx+vhz9zuJt5SMdDqdz32nL9Rutx8BfgX5A7AH/PVOp/OmdaK2KBC/AvwfnU7nv/tOX/swDpGoIG1KmfNkXrQZ22PLaGrQdtgDHmjZON0cFCyURGyslGd9JB9S1snju9M2kUDBQSqbr0gLTvXmoCDQgiEdFY7NkScvoFtYcJ67w4JxDvuAVoorqaUVKQZZgUWoW7sTyyu7OctlxUwMWiv+ZDPjTF0SnJ1E2pjmAlHG9iaOr+5lzJQM+weWJ2ZDFmPN3R4k3YILjYBhIWhewf8q7o1ER9KdZBgtiNvKA9qTQ+TtYRxqUSqB9M8HSk3F/7JR7OcOg1C8xhaMFm+QUImfxVvtaT98ncJ5rkwFu/fGBYHSR2Nen/67XDbfMN6D1PG1geaRWU+oBKe7Nbb4smF3UpAU4sbtgF7uaOTSohNozeawoPCewosjdz5F3XYzMTQsnKcZipfMn24WPDoTis9F4dkeWyITUNKCjg6Mwk19UwKjMd7Rt56v7mesVAzOK17aFQBBuxVyomxA+aN2O61gcyQo5nIg1bt7I2mXO1mVNRJrTT9zWC9Y4JoR8tjracGFVnB0XZYq+qFrWjaSoDYizUu7Oe9biI6qCduJGO8tlR9uI3pmUSpYb1wHV7sFn11PsMBirNgqHN2+mAmq6fo+UdHMlxSvdQs+vzHh6fmIM1XDrX7BZ9ZSLrUM82VD4cQdfqGip6QsLRoV5Y80G29cl2+2Pr/ZGj58XKhhf+LEnV4JYjDQgrDu5x5r4fZQwA3NSOOdoLcB5mONAa51C4a5Yz8VLPihbmtnisPOndDGEiuVTpD79kRVUzEPVzEenKMHxx9q8RTqZ44rBznWCkUuDjQ7iSUqHkZAv9ui3W7/feDfR6r4n22323udTueJdrv928AvdDqdF4B/CnwQOPzb83c7nc7N782Ij+P7NX779je6rh/6fh3HuztWq4a5WLM3bV0XbWHBYzPvzs/dtyve0t3Vbrejdrv9d9vt9tV2uz2a/vs/t9vtbwct8Y+Af9jpdB5BEMH/1zd5LTP9f7/5bTz3W4pDJGq/gPlYsZ869hPHfKxZqBh2E4tGcbZuCLT4RIhTecHtQcHFhohnLzYM8yXDvVFBMxJfgJ2xtGC0IkEFL5Y1o9yDU7Qizb2xZ74sz7uZFFOjOWm1emwmBC9EoUh5Ot2MRqynm3zRAYTGsZ85ztUjzjQCUJ6tpGBjVJAWnkYoz11MN1y7E8vVbsa5RkAr0kI90kLxudbLwItAtxpKy1llKlavhuDxjHLeFHl7GBcb4dFjVg/9UFLH4zMR98YW5eTUOTTiej4TKe4OCmLDQ7qQbxWHr3Otl1PSip3UAfqhMV9sGK73ijcd77V+TtmIhmJ9bGlFmnN1w5WDjFhpCufoZp5maGhGhkEu2oi9ScF+ZjlTN1QizSjzBEoSlXvjgrP18Ai3upNINSI24kTuPSxUNHcGGdf6BY3QUA00exNJ/mItlLVAS6uSRZLYcSF+KqkTM8FyoI/wwb0CkTIAACAASURBVOAphUIhy60jLxyZ88TG04qFsuBFL3301Qg8qRcULZ6j6/LR5dJD1xQFE6v44FIMeK5286PreK1vudCUdiGlxJywGnLUkvbGdfClnYzcSgVpbDXNSK7r/sRyd1ig8BxM0b+v7GWcqEgCbbRiuWIIjOCGs+mBQGhE/N5NPU/PhXQzQd4eamneuC7fbH1+szV8+LhWbLg5tLRCQ0kreplgm0sG1voFqRMTyFBrztRDBlOCFkj1g+ncD6cJqlaSnJeNfMBa7xnnlplIMynkd5uxGDZOCrkf3jjOwzl68Oet2DAT6/vzhlDZlioClzjIxPzyEAH9botOp/M3O53OyU6nE3Q6neVOp/PE9OefmiYidDod2+l0/otOp3Nh+vWPv7ejPo7vx/jt28lD3//06WOK1nFIKKV4/xsQvy/u/sBKqb9v4q22af2fQBv4m0h/7RngbwGrwH/6rX653W4vAu8HfmL6o18Ffqndbi90Op2dNzz8fwR+C6hNv962OESi/vpLPKQheL1bsFzWPDEbcbOfo5U62lQ7FM55npwN+ZmzFV7cyVgsG8qBZmOU0009S+WAZuRZqQbEWvq4/+q5Cr9+c8R+4lBacakp7V6v9wqGWSEeHbmnGikWyxoF3B5JstDLPO+bC6mEhtvDnK/uOWYjRT0yfGi5BN5xs6f4ei9nvmJYripmYsHPZoUYM85VDAepY7k0dagONU82HLsoOj3PMoqz9ZDVqqYaSItZL/dH7Vhv1AgcIm8P47A//1pfBO/PLUU8nnvWh5bVaojyggoWRw1wXkhWH1yKH9KFfKs4fJ2r/RyNJ3Mybw+O+fFWwNjypojeXiq0LxAMayNUxMZQCRTlEIZDT6ThdD3gTE1zZSpAdh7aLSGNtZshL+1l7EwcM5HmkVbIj63GrI8t/akh4hOzAdYrGpG09twZFgwzw9iKDqUaCi7YIyL4xGrqRjDFYysYyYWKVHuKB7h1h/hg5xWfPlvi321l3BoWxFpoV8sVQ2LBKDE8bMSGUMO5umF9T1r8APpThPHhdWnF+uia1gPN47OiDaoForc4vI6rVcNS6eG5Omx3erN1oDXMlfXUM8ezXDF477k7soCaYnKFmqaUYrGkpuQsMf57vBnS6RdERqhizyyExEbx1Jwgn5+ckxbIQy3NG9flm63Pb7aGDx/3idUSNwY5+4ljuRpwoiqL1ntxlZ+NNIl1XGjIuhtbyfbU9L/n6oKSHlvPqZrhTF3c33uZk3WhNNnUXGipqmlFmvmSYaGkqISaH1kpvek4W7F+U53Or14bofFoo/ihpZiRlcOD3AsHP3ffcDmO4ziO4y3G5tjyws7DPj0/feovllbkOL6zeP9CxO+tp0ffX97J+bnvLwnGD1y81WTk08CFTqfTnX5/pd1uPw9c4y0kIwg6cb3T6Vg4wgVvTH9+lIy02+33Aj8FfAL4229xbN9WnGsE/JUTjkuXGkc/+4P1CTf7hXgGaMV8LHjcR2ZC0Xo4eM98+FBbSiPSvH8hppsKcWg7dcRGEK6namIsVzGamabhUiukc5CxMbaUDSxWBJXbTR1eefKpWPw9s5pqqNjPnLQehZ6ZyPDUnBjOtWJJHEY5jJwYoJWMZqIsRslrKxS9zDLMHJlzfHknpx5pNseWg0xRqxrO1hVLFc0gF1+LUQFm2vqSTHvcr/VFa7LWLwDF2UbOR5dLnGsER8jRQw2GVnKaPMwdjUg2Z9ZDoBW1ULNYFv1FYBT1SPHiTkYzlut8iKXdGhdHYvZKKN4nyxUz1bGEPNoKudkvRG8zKjhdC5kUlv3U84VNEfpfbJQe2mze7Bd8cXPC1S1Nm4RaoCgc7CSScPQyj8WzPfHsZxm1UPO++YgLjYBAK9aHOZ1uzvpIvDV+dLXMTKy43hcM82GUjWKYexYqciLdiDTnGgGPzNxHyR5MHN45+pmlGogY3yAAgXgKLgiUCJ+DB/bLhy7cSxVpb3t8NuR0PaAWin+FU0AqvjMrZU0tkATQKEVJQTXUzJXk69mF+z3PM7Hm2cWI3ErV6LD15xDlfIg6/p1bCb+/7mhGMiceuDcsSIHXe/lU56TpZY5h7igp2MoFDRxqWU+jQgwaV6qGi82AxbLhiZmQP4wVNwayzhWe3Ym0Dp6pB3zqdJleZo/Gc5jAHq69u0PLvbGT5He6Rh6c+wfX6Bt1Lg8+xzB31EPNUtnw5Gz0UKvf1rhge+IYZJ7NsSd1oHKho22MRSd2ouqphppmLJSz4bRkr/CcrYecrGmMUmwl8t5mYqGvtSLN1rigl9sj00yQitMfbUym5DVp9zrUDR2O/3DeGpEit7AYCF54PxXzxEr47qyMHMdxvB3xO28wOnzffMhK1XyTRx/HuzHeiHg+rox85/FWk5FNoAJ0H/hZGbj3dg2k3W6HwD8G/pNpsvItf+c7QZMd/m4vh693NZsTRaQ8k7Hm8o5iMfacqziuHShOxB7lHVe7oHJ4faApG88wg8/tGvq54mzF0U3h6qZmJvJ8sGVpanhtqHntrrTfdAtBcoYOLt8d0wrlVP5GH5ZjTzly/PFBAM4zKBSJgm0HDePZc4qFpuX6XXh1qNlOFU/ULAdjzXqiuAvEStzQrYe5yFPWnpcORHg7Gzo2JposGXIy9mxkkFqFDT1fGPRZjj0Xa46v7CiUF1H15Z4h0h7jFZOe45Xbmh+aLTjI5f0XTt7fxErLkVKee4mmahzXR4alkqOiFTuRY1BoTlccp8pSqbidwWtDw6myZWMibuH9TDETOg5yTSP0nCnLmL7kFEkBvULmaGOiuXZPupHOVhxOK6plx786UDxZdzRDuJPA72wHBNpRM5rb23vspRrnPa0Q5kLHC7uGbg4LkUdpuJoqJgNP0fM0I8fzBwEV7SlFno0BfH1D83TTcqnq+P3bAfXQUdOSHL4yMvzQTMGtgbRgJVbGAvAne5qv9jSx8iir2Z6IGaMDUg+nSpD0R2wVmkrgGVrP2nhqqlfI+psvP/yaWw7ujqXvbi5yDDJNF//Qe7xY9dzY2OTlXPPJxYKr3YfvgcO17Lzn7kT0UN7JtfzlLcXdsaYaOsYTza3peqkaT2Ll/rg9cnwx1bRC8fZQypOONf2JogdUNexksjaerHtKyYjnu3KdXj0APdFsDzTzkefaQB2ZQZ4KLP/ya0NWSo74gbk9XXbcTr5xvPtlx6vq/tz3cviTl25SNrLW9hy8+sB8fO1N3vNM5HglMTxas8xFsDddn4/W5D6+2dN8blNat0LtKcaaiYJbxYis61hPNVp51ieaeuCJUOx3HX+YaT42W5A6zWaquIfci+upZjn2PN103LgFX8rkvisZz9WRPDYEVkqOe1uK19Y8z83I+/tm83ay7Hn91jpP1t03zPW3iu83sspxHMf3Kt7YovWpY9f143hDvLFN69X9nKTwD3m8Hce3F281GfmnwO+02+1/ANxFKhr/FfB/t9vtHz18UKfT+YNv8vt3gNV2u22miYYBVqY/P4wTwAXgt6eJSAtQ7Xa70el0/sabPemf9w/og1izL++kvG9WNtZ3RwWtxB2d/C42wyNH6wdPXS9MT1a/vJVxRhUYpQiNYDmbEwdKEc+FPDETcipz/P7dhLGFD08N20bF/dc4xNMuV0Sv8MG6I7GOvYkY1RUeZiPNBxZDKoHmxZ2cat3xyZMhufPMOc9JC6/sS2auFCzGmo+dKHNnmFObiCD/zsiyEo+IqnVCA6drYpKYORFn12PNUyslBpmnZOAP1yecCqAWiVmh0WL69NWx5cfOlKgEmisHGRcbsDYs8IjTelDzHGSOJxuQWMHGViLNcqSoGE17eqIwOsi40BC9RSnyNENLzcMgd6w0NFoporIhbolau4TiuWZwNEdX9jPiQPH4Uuk+frhweKO4tBDz714fcmHF04o0NzY2UbV5RgcZgYIPL5dZG+ScCiyr0z6yRqRZmSKSZ2cCktzzsZamGYq7+Nh6ms5TqxlWFmN+dMGxN3XWfiJUvN9AUniqlYCVN5zEv/DqgFOhxRjFcuHYShyvdzOMgo8sxFIZMfB02XCyLpWGzkEBCp6drr9r/fyh11wMFa3UghfPi+1EjPbiRLxALjZDtna2uLCyxFysqZcNlxa+kQZzIXX81q0xrVSIT4fX8jdujKiGivfOh1zZzyhNHLdGlkHheO5EiXKg2Eos55qarcQRVzUlrXhPzXM6c9wa5KwNCmargkn+8HKZxbLiI1ra0nqZ54N1xYfw/O7thP3MsVrTPDYbUtKiBaqUDR87UTqa2+v9gkcWA9YGBWemhoWTqdP5ubo5mvvfePEaj5xZFSzuNA7XBsAjs/5Nn+ORWLE9cVQrAf1xwY+umqNKyanM8Vu3ErbGlqV6wFMnpY1sfWTZmlieOxGzNbIsFo7ci8fKMHc8NaPZ8eJXdMnLfXh7aDld15xpBjwxnZPRTopH8NwlU3BeSW+y0RxVZ/18eDSHh59BMw9Ud/z+Bj/y5LljrO9xHMefM4a543P30od+9qnTxy1ax/FwzJUMZ+uGtSlxrfCyB3tu8Zi49ueNt5qM/OfTf//WG37+89MvkIPq82/2y51OZ7vdbr8E/EfA/zP99ysP6kU6nc5tYP7w+3a7/YtA7e2kaR22Z3z9QNHdSbnYCOlNWxvujux0Q+dplgyD1NEIFeujgn7mHmoFOUSDrg/FHFEraadYLAeMcsECX9kXd+5aqIiMZpBb1gYWpeBsLeBTZ8rkXj2Et/3s3QnjPOdMFKBaCojwHrqZY7FsOFkz3OxbBpllc1xwdyQi5tx5uhM3bSUzeKA6JS7VIs2HZkL+eHNCaeJZ9zCeOCYladUpBYofOREf4Vsv72QsVzT3xo65GDZGQvexHqqzAS/vF1TDjL2J40o3R3kRXi9WDMvlgNkY1oae2Zqmm3tU7nmtm6KQpGq5Iq7bw9zTCBRfHRcMM8etgSXUkDjFkzMa6z2F9wxzMU/0SGvc41HE4zPSz7+TyMb8ENHrvDhgDzLPH6ynVIynGhp8qnhsMWA5KbiXCDkLJX4nc7FiZBVPzgRH13qpYvjcxoSJ9Ryk9wXBNaO4PXAMi8mRFmhxKkLeGgvW9y+fC5iPDZd306OE4qv7Gc/MRdSj+5vEhRjuJZ7zjYDR1NMj0p5rPcvTc4b2TMAw91zeyfi9OwlbieNERVp8FsqGU7WAYSb0p8dn5JoA/JtbY270CkaFpzfQ6IHFe0kAnl14+D44bFNa61vONcxRIgKymS4HMMplbgaFY3dcsJ96ApVSCRXdzHOhbrg9sPQywfAmhaPw4s2zXAl4ajYgNob3Twldh8jleujYSgpuDxxozdm6phUbnFOkQGodL+/Jmnx6LmKloo9wt9uJvE5ipUWuFChOVoQE1ks9r/QVsyfkvR6iiweZrOGVquFMzbCdOPYnBfemFahGrPnLZ8rUQhGXv7TrUCDmkaF6U7Tu3VFBySgy63nPbMi/7ucslCWRHheeF3bl8+TWyHK6arg7tvRSSSjfOyvz/uXtCWsDy62BZbGiOV0LKbynZkQYPyxEN7Q3sXxuPeXLWxkojg5JDiENvdQzeLs+KI/jON6l8QfrqRD7pnGmZnh85q1uk47j3RQfmI9YG9yvor2wkx8nI99BvFW077m34bV+HviVdrv9C8AB8NcB3oBdfMfiIHW8sJ1RDaEZcOTInFjHzb4l1J69RBy6bw8L5sqGL29nnG0EDDN/hL09RJoepO4I8RtpsFPs67Dw7Iwtl5rmCPv6wk5KoBVPzYpQ/WqvYHdieW7p4b7DQ8xoaqE0nZl0mmxsjCwVA5Nc0K1rg4I7I0uoFQsljdFwrVfw6IwQmEDaYzywn8pGOSsgka04B6nFowlzxfWBeHcslfURmrabOnYnnvmSJtRyvT6/kRJpWOvnbCWOnVFBM9aMc8fW+DBpMJQM3BgIwulu4ogC8b1InOf37kz4iVOlqfu2O0Ijh0ZE44V1rA0KVmsBgRJcbFr4qVxYop9Jz36oFAGe1/s53msWyoqtseX5Lcidpz/FqQYWruzn3B456pF4gkQa1gdC5potqW+41s1QMc5hL7N45I/SVuq4O8xZyUNaocY6z+c2UpQXP5NmpHl+K+Pf3k5oxvoIz5tknsu7Gc8slqaaH8dmIrjevcSileJOWgjK1SgmTccr+znX+wWVQOhb68OCfqZIrScyisF+Tu79Q1jY9WHBV/dycYrXnomDV/dyvIdW7KdUrvsO8Zsji9aQ5I6diWKY5zw+KyaB9VAxyMXx/CBz5M7STWVD38sl+UidYz8SjdJ+ajEaJlZm6sbAYRTcGSjOtTRX9uW5AyU6o6u9go1hQdloJoWjn3nGuadRMlztZvz/7L3pk2TXeZ/5nHO33Cqz9qru6gWN7kaB6AbRIAGSokBRFEXZY5FewmNairFCnyZiYmIcExMxMZ/9ZeYfmHCEZ/zFM/aMLI2XsCRLIQoSJJuiSQIEm8JCFFCNpffaK7OyMvNu58yHkzcrl5tZWdXdaAB1fxEIdGVl3nvOe87Juvee3/u8s57FQl7Sis2ceemUx0JBst6MWW/E2EJQdIVZby1FK9LMt28uXQuub4ZcqtjcqkcddHGsDQY60pqb9ZiNZkzZlYQKtpqKP7vdouzKnnWQtLvsiAG0bj8SOW9JGqHBWN+sxxQsTYTAlprv3W5xdsJmwoG9EP7sjs9cu71FR5KzTR0kMHCCwGywUrDN+n2/FpKzBFen3A7y+XbdFHZMqrdvaXqwy5kyZTqa0iha3bWKMmVK9IU5l3/7wcF8eT3LG3kgfWx/sVZWVt5ZWVn58srKylPt/6+0X/9baTciKysr/+Rh7oqs1kKKDm1EKR1E6d39iA6e1TLVvB1LECpNxTUXQ93Y2wRpapJODeJ3P1QorQHF/XpE3pbMF6zOcR1hagRIBK4l8GzYaqkBBGeCGd0NFM3QoE13fU0rhosVmy1fcaZkMZcz1hhXmIT7bV+xWLAo2oL7+yETjmQ3UJRsiScFH+zFPDPlshUKPEsw6VrEaLZbMXN5yWtrQQffmqBpJ3OS3ZaxJ/mRqbWAEEwXbGqB2bWYzUuaMRQc8zQ4jDV36hGuNP/e9TWWgPm8Tdm1sIXEs+Gnmz4znuSDasykZ1FxTI2WIDbV2qu+2f2ZcIwFKUGaJpjT1WrItGcxW7C4vW8Swj0bfr4T8WTFJVCm+jloYq3ZDwWbrYhQaZ6ccPBjzZmCpODAzb2IsiMHYv2leY+7zQihNQULbtdjNhuKxbxD0REgNbuBQmAsfruB5nzZIVCK9abqwfM+O+Ow1YpZ3TV1UlZrETlLUnYsJIKiI6iFxmb1ZMXm+lZIEBsEbKSNle5U0SJon2fXjxFCD2Bhf7zuM+NZOJZACpPH4dmC92shFys2q7Wwsw622kUbJ13JmQmL9aY55s09s7N3seKwH5kK73M5yUZTYVkwm5Ps+gZxPOtJbtRC8o65YQ1ijRQSS0iUFlQ8m1qoEVqYXIjdkP3QwGdzFrgW7IYxczmBI0wy/9p+xIxnsRcpyq5FyQLPhtc2Wry0mGO1FjNXsFBo9kONal+0b7UUlycdhBCcyxva1Y/W/B508eVJh0tli9fWAkBjCwM00Brm8pIP90Jcm5510B2TAbRuHxJ5whVUQ1OXSCnNQsGm5mtKltn12gsUgRI8WXZphAYRXWyvnUnXZjZvnh604phtX1Fr785+sBcjEDxZcXuQz6vVqF1805DJ8hY931GZMmUaX5HS/Mnt3uT1zKKVaZi+2I/33chuRh5EJ+bxWdXXnWJjiQwFCa7NOITaPBUPtebJCYtWbJ5KNto2iXobe1ttI02rvnkS+8Kcy6WKjR9rcxGfl/zdJ/JMunSwr+cmLE4XLGzLFMgpWILTRYnqLbzcwYxenXFoxJpGDM/OOFyumEru9VAznZN8bsqhYAkQgklHMOFJzpYcnpl0mM4ZK0nBFuaiesFloWAx4Qimbc3Tkw4LBUnRMhat+Zyk4MgOvjVB01YcwZmSRd6SeLbAloJfOuXiSlMfQWBoWROO4PyEQ9mR5G3z7wnXoFg15maiYJschoWCRcUW3N6Pmc5bfGnBWHdOFW3OTjicLdrmSW/J4XTJ4WLFYSZnYvKNpVwH3dtS8NVFlxdmD8atYJligNNu257mSL4071GwJJsRWAK+OOfytVMejgUxgmszDldnXAQMxHqpZHNlyiVvG8sSwJUZhylPtHMUbKJ2NXVLmLFLrHGB0j143jNFm8/PeGitudPG+/7dC3kuT9rkHTMn0DCXk0y7km1fEWlzQR0p8GNNxRWdp92bLU3JFlyq2D1xqYaaL8w5LBZM/karnQ+Ut834Vn3dWQf1UOO1ATHTnsV83qJkC+43FI4l+M4TBb52KoclIFDgWRaXJmxOFS1ylsCVkpIjKbs2Z4s2E66FEILFvLkx8SxTWPTipI0QZrfPjzUvzLsobahhT1VMDC0pOF2wmc5Z7Iaa+ZzgybLDhCPYj6FiC4q2xYWyzVLR3IzP5E1tm7m8RU7C6aLsWMxKtlnTtUDRUiYfJNndmM9bFBxJzhLM5MwxpjyLaVdSciWuED3roDsmyTxsKXqOu1S0uDbjMOEYnLAUUHRMHth3LxXwbHNe3a4kP5cXPD3lEMR08rGemXb4/JRDzoJpz2Z50mahaGK6ULB4smIz3bWR6knBXqgI+75Eur+jMmXKNL5+uB6w07V2Jl3BV/vcC5kyJfr8jEP3JeUHezHbrXj4BzKN1IkxQw6ryLxQkDiW4JkphzCGom0sTRXX1NsoOMa+k2BvkwrOyfG6FSpzofdBPWYvMNjRe42IXT9mJmcxk7eYy1ls+wZJO5c3Tzb763d8Ydaj7JqLxwlXAKYac8kR+LHBtZ4qWOyGgmnPouCYi5tQKZ6yBX/vQoEdX/GX95q8fNPn5n7EUtFm0dNcLNsDib8KU2l7y1edPJdTBYsnyw5fbCecv7ru82HN1E6wJVRcq03QAgtzwXumZPGFeYd7+zHvV00OCJg2WgLyNtRj3env6aJFENsGQ9sel1asOyjlF/sSrl+c89jxFe9VA/7wwyaubfI5ThVN/YdYm0rat+sR95sxeVtgIShZJmahAto1ZMAkNT9viZ7zvLrhd+bJE2WT34IwN14CzZvbBuladCRPls3yUcB0+2Yuio0dam8zYK0Zc7pgs1AwuTKfP5fjxTmPVzd8wlgzH0rC2NwUhpFmO1Bc3wrwY40nTSFDW4IjzHgVbIOgvTxpc2HC7IAk+Utgihi+X4vZCcxO3IKncWxTdPL7930mPYOUTubSdstUGN8NFCVHkitCyYFX1wJeXQ+QwLU5FwtBoEzhvbwlON++KZnJWWy3FPOdXSizEzOhJZ4lmC9YzHoWp4vG1vjOTsi71bCdU6FoRqaS/ZRncSovsaVkwpEUXMGkJ7kwYeK7G6jOul0qWYSx5Or0wZp5fYMeGx+YmjNfnDeY5kjB7brJ4fJjTaudZF5yBc+UXIq2mXfN2GCUEx0gmg/myI6vmHBEz0VLcr4XF1xenPPMWmyPF8AbWwG36zETLjRjxXZLsh9plgqSy2WbWGvWGxG7gcKVgq+ecvnm0sET2Vc3fH645vNONSLWpsiqIwX7oeZGLWLCNTs5yXdaWkX6TJkyjVa/RevXzuawZbaWMqWrYJsHVm9sH+xEv74Z8qtnMgz0cXRidkZ6KzIPVqOe8cxFm2ebyuunChbVQJGzTNXrmZzsqeB8qexwv6H4q/s+7+1GSKAVGe/5X91t8ZN1n6ofU/MVvoK1ZswH1ZC/utdirRGzmDfJyK+tBx0vPxzktoSxZsZL7E6K+w3VaePdRgwJGjY2dpw3NgPu7ce8tJhjx1f8wYcN/vSWjy1MMvH71Yi3axa39s1FT3efnp12ub4ZsRdqJmxTQX6zabDDjUhR9WM2W4rd0OyseBI2mzH39kN2WjHVQJEUtv7hvYB7+8a+dKZobFRvbPnc3w/ZbCmqvuYXF7xOv2wpBmxpwyq07/iKV+602PVNXQqpNTVf8fqGz939mEtli9e3QtYaMWHcTr6uh2wHgr3AJHL/dCOgGqiRFbm7K4p3V/ye8SSuMNa3ZqiZcATJyJUdyWYz5k4jJtSKnC0QWnNjN+T1DZNr0z13uufc3UbMTqCwpEE/PzFhsdGKzQ2jMPktVd/ENLGu9bd9p227qoaKSVvQDBTv1CQrO4HZlRNmFyGZS56ElWpkzgtIAb//oc/dfUXBEhQs2PE1N3YjXt8MmPMswgh2mgqtFa0ItpuKry26xBo2fUXJMfM1jo2VLIgVttCs7kb8lzWfmZxFXsI72wGvr/vGimcLbtYi3tgOsIXmxQWHnZYmZ5lio7uBYreleWkxl7KOeyuTJ681Yzpr+35D8dPNgCAyeU/v7EbY0hRdrPqKd7YDNlsmH+ZSxU6thp7EOVmb8zmJIwx5562tgPvNeOC7IWlj1Tc5QRt+TCvS+JHibj0iUprJnORGLeKdndBYPZUBYVR93fOdMOtZbDU0VV9hY3Lbvn+3xVQbCJG0Y9NnaEX6TJkyDZfWmj+62WvR+vXMopXpEPVbtV7NrFrH1onZGemuyFyN4LQ1WOm4EZsLjLmciwbOlQyZaqJdOK4b15p8rhlphDRPc6WESU/ys80AKY2VYzInOesaS9ZqLeJ00WI6J3lx4QBZuloLD55ud+W2gMEFLxboFFpsxPDmVsDTU6Yy9WbToIDLLlybc7hQtnl1w+dGNWTGlZRcAVgsS8lqoNnyTVG57j6t1kKem3PYaj8pLzmSr5yycaR54nt9M2Q+b/H5GZdqEONIh7wUvF83uQ+zBYunJx3Q8MFeiJTw9JTDelMRaUOaut9SXJkyuRhL7QJSpl+CpZLVIU89OzOIUk60WgvZ9WNOF0xy83pTmQt/SzDpCbbbNzKxsgm0ZrulmM4JrAAWijZnSha2gLd2Ql6cd4dW5O6uKN5d+ioR+QAAIABJREFU8Xs6b/HbT7u8vxeyshMhpOA7T5g/WHfqMbf2Y7MDMuuy5yvuNWNsWzPtWZwuWT1zp3OO9nheKJsLYbP/onluxiFQGq0NSenKjNspBNk/F5PYXKrYzHiS61sBTSXRQnOqaPFE2T7AHzuKZqy5u2/yUGINRdvYtmYLEikh7whAcLpoaGIzlsCSgouTDq1IY0lzI/WVRY+CLTkVKH7JzbPWMEnhUx4ULJjOWeQdyc16yOWKy1zOJJDnHcEsFgiJZ0vm8uZJf84RXJl2uTbj8cZ2wJ2GYqEg+bVLeS60d6HSKqsnlcmT11xBJ4n7g72IHV/ia9gJNFemzU6IH2sW8oL3qjG392O+dSbP87Nuz3H6q7YfrE2bvC25vR+x1VJsNGO+fb6QOr7XN0POTxjb5Id7ocFdu4Knpx0+V3H4y7sG6auE4PKUzfKkSfLv/k7Y9GN+YdHhZl3w4V7MbmCqwV+csnm64nTasR8I/l6WvJ4p05H1892og2kFA6X5laWMjJRptL445/Iv3m10fv7xenYzclydmJsRoGNpERsaDZ1K4JfKxhL04tzoys39qgXG259YO5qRJm+ZStLTOYFlS2Y9iRaCCyWTh/LrZ3PUIjr+9nzb758oQQ3/xd2W2TUJFFOuZHnS5n94tsylssO9RowEJtpV4MuOSfp+ayfi5dstrm8ZS0fZERQiybRnUXYFs65mqWDzW0+Vevpxpx53MKsJDamlNDvNmOfbqLor0w4VVzLhCCAibzn4Cv7ekwUEpkbLTzYCqr6pmF2cdLjgSJ6YsNkNjP3rm0teh0xSCxS36hH3GoqvL3n85uUiYC74uselO/ZV31SrL7gghOSCIzs43ksV84TCEqZOQ8k2ib+eBes7ZodBI3h+1ulgjLsrXWvo1HuZcA9wvmV38ML/Qtnmm0u9c+XFBYvTRYsPaiGt2Fzwe5ag4prK6rWg19aTzMUX59o3u54YGpvu6tzD8gHutDG9+xE8UXb42uk8/yneZXbW48rUwdObMNas7EQ0IrPbc27C5FL8xd0WH9ZiNhrgWYKFvI1Wmrv1mIonmMpZ5GxBxZOcLxm88N9+otA5riM071Yhbxnr3qwniRDtXUjNqfZb/fb8ytuCkiP55lIOreFuIybXzneoePRc3PcriV0S//758l7zwAqotClQJYTgx+t+ewdP0IrhS/MeL8wZ1PCvLB0gtpMb9Nv1mHd2DBBiqWRxpx5zvmR15sUzrttBFXdXh+/+7qj6Zofz1Q3NExOGzKM1VEOz+9OINE9POR2rlcEfM/CdMJ+3WCjYLE8qfv/DfXZaipdvtrg5FTObM3k0NVtnNyKZMh1Dv/9hr0Xrl055TDjZWso0Wl/pyyl6bSMgVhors/cdWSfqZgTMBeSbe5Knps1FQrON+H1h3kyqBP/b/7v+P/JpaN/7jZhAKTwbXEtgYYqiLZVs9mODya1FZuchUb/HWwr4s9s+b+60CGNzcbfVjHk90vzue3XmCza5NpkrUgY9erZksVoNKTkSR2jWGoq6r8lJgx69s2+oWQALhcF+dGNW7+9H3GuYfi2VbNb3Y5qxJow1n59xe1CpZVfyg/um+OCMK5j1pHlS3DIXxUXb5Ns4UrBQOMjZSdCoQsBiQRLGmlfumC3yBFOaFvth6GNHik4MHQm2EO2ka5NrYQk6mOD1ZtzBJL9fjbi9HxErQICFYLMZY0lBwZZcm3U6COj+OdCNik7a+1414uZeTN4y1jMhoB5opnKSu/vxQH5Qou58puPEJpmLtoSKI/Hb8yJU9ORA1ALF9S0zTyptLG4yf9YbMZE2idexMijkUCsQsN2KqYUaW5jdlJ9vR9RKutMfITQ/WAvY9WOKjqQVar5/z+dUyeLZaRfXght7EZcrZjdPYxL9y65p27Yfc3c/4nNT7qHrblT8u9dxWmyTnCuEyZlJW3/JcbvRx/UgJmebXZ2cLTqFELs/P6w9lqQn3yvXXhMCzfWtkLJrYAPJWk7wx91tSvoQKc1rGwGbTUWkoBUrPtqLaEYKjU3Nl0PnWKZMmYar/2bkO+czi1amw3WpbNwIW21b7V6oeWsn5PMzGfjgqDpxf7VWayF5S3dwmAnitxt7mva7tOOkoX03W4pzJRtbgCtMQnMtiKm1FC/Ouey2TK5GmicdTHG/j/ZCtDL1BxxpkXMkE67g9a2QHd/sArSUITDlLIMwBYMuvdOIuVCyOFuWrDXNzZHWig9rEbYQHe99dz+6MauR0oh2PkrREZQ9SdGWbLXiAVTqlxc8tv2YzUZsdgE8Q9QqOpKP9sKeHJAkN6cRmaf+QoDWgnMTprL8rh/3YErTYj8MfZzkmCS/dy3BXqA6uRZa08m1WK3FHUxyPVRMe5JYG4TuTF5ya99geSc9Q/0aNgfS5kreMjss660IhNnhipTZZUnQumnqzjE4TmySuag17eR3g6QNlBhAIifzpBtd+9MNn7mCRd426GmlNbtBxGZTUfEkQpqk6aIj2AkUrgWufXB+gcFLe5ZJXK+GmrwjKTrmov1i2aEVKW7WQwoWRDFEaM6XLJqR4oM9A3hI0Lyj1t2o+Kd9ZlQOUNr6S0MfJ2jvS2WLG9UoNadkWHs0uic/KMnX8pUGzBrqXssJ/ri7TUkfVqshNV8xn7fZCTXTOYuKa3aTNpqKs3mVYX0zZTqiPmwI3t6NOj9bAr59PjfiE5kyGQkh+FLfA7AfZVatY+nE3YxUfU2ur9cJDnMY/jfNGpOG9lVasDxp84uLOZ6b9Sh7kqUJC08IXlzwuDLj8N1LBWZyki3f1DPpf/qrtaDkmjoRsTb+/MWCSZre9Q3KM8GOOpbZJagFimuzxm6T4H9fnPW4WHGIFTQjmCtY/J1TUcd7392PbsxqU2kkJsFXY3YibAtOF+0BVOpS0eJ0wZCUqqGm4ll8+3yBa9M21eAATfyNpRwXyjYvzLs4luBeQ1G0D3CrAKHiUEzpMPTxN5ZyTHmy8/svLbjMF2xsKbgy4/J0SXUwwUtFq4NJjrRJ0o+0IXg57YT9SB3gnIfNgbS54kjBk2VDmYoV+AouVCzOlKwOWjdNSY7BcWOTzMVkTtRCg/49V1ADSORknnSja283YuZykm+fL3B1ym4Tp8wu2uWKw1IbFRwqCGN4atLGFQfnV+3K5jnbVAwPtObJCXNDrhF87ZTHS4serQiaCr6+lOO/uVykYJscqIWCxVcXvU5/R627UfFP+0x3bEMtuDrj8OyMY3aNUtZfGvo4mQvzeWPFS+LZ/flh7dHavGc6b7FYtCjYglNFC0sIrs2aNdS9lhP8cT9h74V5l5bCAApygosTNhXHjAmYOikzLhnWN1OmI+rPNnvpR1875TGTy4hImcZTv1Xrh2vZzchxdOJsWhVPsKXMBfzt/Yh6235yvmxTdmUq/rcflbnjm4Jlb++YXY6yayGI2WxGVAPBU5MOL506SFB3+vCxF0aEveIZu1MY2WihaUaaW3XFRiOkFsJH9YjX1gO+dTbHM1MujUhRaFeHBhAYSlIz0pwuWnztVBFbmAunyd308zkSLGFQtbY05C/ahelCZSxOjjQ7C4Hq+7xr+v/FObcTU1/BF+ccvn2+wK6v+MOPGqbCe8HskHx9yWujTw/imlS37lYzNtW6/+xOs5Pg/vSkwxdmPb4w63V8/X/4UYOJ9u6RwFwAJrkWU57kvffWudzGHb+zE/Kf78cm30cJaoFmx48JFNjCVK235QHOOa0djViz3YypeJIzpYPkcKeNPF4sWIQxPQjl9WbMekvx8u1Waj5MN6J3VGySGG+1TG7Ojq86Np4kjwHMTdXaXu9YTSR46vbPZVcym5MsFSy2fY0QitNFp4NBztsmnX4vMjdDXptCdXs/ph5qs1PSPr8jYD1QbLY0W35MEGlOlSxK7RufLy14/OLp3ACuGeigjvvHfhSidhiqu+IJ6HVcdHbOTD4HlLviv+MrXt3wO3kejUjx852IH60H1ALFtGdxqiC5UDFI5DMlK7UPo9rTnR+U1udk3JLvijSb1ZQneXHeJSfBEgJJew4HGl+bApBbIZzOsL6ZMh1Jf7bZ+/f47z6RWbQyja+vZDsjD0UnbmfkUtlhMxAd3KcrYS80TxRnPWsAG5qGUO3Ge360F/H/vFvn5zumKnjBFvznuz7/6U5zAPk5bvsutm1YH9VidvyY2/WQ+03T1rItuNU+5882gx488VojohYYZK5SpmjTTzcC7jfU0DZ0W58mHFPXIooBbSrH13xjQdtqKT437QwgTROs6loj4q3tkL1QdzCyf/Bhg/9rpU6jXVOhEWl+b7WBI8SheNZGZBC0d+oxb26FHdzsG1shf/Bhg1futNhuxtzfN3VhblQjfrwW8MZWiCPp5HokiNT+cSs6gvuNiDd3Q9BtlG1LgzZVvbutPN3t0ElNCF/zQS1ivRkPxKLfkuNZcH0zYi5vdXDN/Ujn7vEYFpu0GL+2HgydtxVH92Ci53OSn22E3G/GaK1Za0Rc34w647rejPnerSZrTcVCu0jfG9shWkMQaTabihvVYABN7QjB7T2TewQGD/1hPeZuPaLSviEftQ7S+nzYujnKZ9Jw2a+tB3xQi3pe327G/OCuqbESRhqtNff3I1Z2A+7sxYeuo6P04bh9TtaqJeD9vZDtlmLGM/P5nbqp65IpU6bxtFoNea9xcBkkBfz6ucyilWl8XZt16f7avb0fc7seDf9AplSduJuRKU9StkwSua/BsSTPz7ksFiSbftyxdAyzUSXe8IWCzZVphzv1iLBdRXp52uWZKZepnGS1FrHRjEcm4Q5r33eeKPDcrLEV7YWaQMFSSXJ5ymUqZzHZ3qH40brPC/NuxwK13jJPVj835XB50sGRggmHztPZYedLrE9CmDyFry/leH4uhyMF80VjTfnKotlpuDJtKmNHWrPRjDtVqddb7UJyjuTKjMti3uJGNSSIYdKVSGn895M5wRvbwUCc+6usO5YpfBcpzaQryTuCvC2Z9ASrVVMsstvXX49G53r0j9tCXjLhSqZcwbmyzamiw8WKzdNTLqeLssfK092OvVAz4UhOlywmXYv9tt2rOxb9lpxmpHluzmExbx2aE9FtK+qPTVqMiw5D5201FD15DAsFm2uzNhvNmC1fs95SPDfndMa1EZqL3EakeXHB42zbXlZyJOcmHHK2IO/IDpo6Of8b2wFLZWmIZkLi2pIvzDosFmxu7sep6+iwPh+2bo7ymWH5HN+/3+p5fctXSMsAD2YLktm8odDlbIP4PmwdHaUPx+1zsla3W4q5vM3FSZuzEw7zeYunSzGbflYBOFOmcfUfPuytLfLSosdcPruhzzS+PEvw/Ey2O/KgOnE2LYB6DBMWRF03rwlit9suk6YE1QnGXpGzBWeKFkIK8pbJzxAa7u7H/GQ9YKlo99Qv6EcGD0MJXyw7LOQtXt8M+cG9FsV2UrbWcLHidAruddc2OFWwuToluLsfc30rYNs3WGCny8s+7HzdVd/7bUQv327RimL+40c+275J+n5uxiFnH9TOSM6d4GnBkCXyfTOsbAvuNAZ3BNJUC1QH5ZvIk4K9UFENTOKzwFRDr4ftBGppEqi7x3SSXvRtyRGcLTlcaMRsNAXnyw4G/GuSt2NNT62Tl2+3Ou1oxJqihanKbpkn0tOe5F5DtRPJnQFLzsu3W505k6gb6ZyMye12GxOU7Bfnei9O02LcP2+7cbdv1ATOjOLD0NgRS45gqWAZmpYnuL6pEJiL8bJrdjqenLC531Lcroe8sxsy40lmHck3Tuf48brPhC06v6+HmqIt+KAWs5CXXGvf0AI9yOUDi5Sxu9VDzZ163LHdJeuje9x/uhmgNANz8Sjo7UTda7Y7bmsNxdWpg9froUYCkYZzRXPjqDHz+HTRQuvjW6CSdr+zE/JhLQIET5QtXlrM8eLc+F/DU57km0t5tBY9OGiAj/aynJFMmY6if/dBo+fnzKKV6Tj68rzLD7tuQH64HvD3nyyM+ESmfp24nZEdX7HmS/YjTcU5QGqutdRIj3qixBueaNqThNrkGTQjzfu1iFuNiKJj8im6bUWH2US6X7+zH7MfaUoWhNrsAigNUgruN2IaMSwVrIG2vV8L+dM7LfwI5nKSvUjzavuY1ZCx7Cr9NqJ6FPPHt/zOMf0I/viWTz2Kh8YFTI5C/wWcQRsPtuOVO62BGN3Zjwm0pvthr680jhDc3Y9whMCRgiiGjYYiUnog16PiCaohnXgmY/7aus/7NZMbY6O5UQt5rxoRaVMfpLv/3UjhgmWwwaEydrb1Zkw90h0Mb5r9Ki02/UjYbsvZvf2YrZYaONao48CgHSkG/vhWi93A1LUJY/jBWsBqNSSMNacKZh28vR22i12aG431pqlgP+tJqqEhNaX9vuwYPHAjVOnjJAVCHFjFHKH58VrA92610DBgu0ve8+ZWmGq3G2a3SrO7jRP/hYLseb3UvsEvOKKTG3WQMyVGfj+Malvyu5u1kNfWA+qRphUZ8t7vrTb4oHb0Lf20PrUUY32HZcqUCd7ZDXlr52DtyYyilemY+nJfEvuPsiT2I+vE3Yys1kLO5dUABvVGNRort6Pf6/30pN2+4Bbca8Tshoo4hjNFh/Nlp8dWdJhNpPv1BNUaKjhbtAlizVYrIi81jSCmHsR854nCQNteXQ/xLEHRFURa4EjJhbLN9++3uNUUY9lV+m1E9/cVrhC4tnkS69oCVwju76uhcWlEhmDlWuYJuVImh2K3pTldtAfOl4avvVS2aEUMoHxLrmAmZzGXlwSxJmgTxvYjnYptvdUUA+jbzVaMBmYLFrf3Y4q2xLPhzr7i8qTT0//+vJq9ULHVVPhKMZ+3ejC8h+FlhyFh01CyaWjjUXkG/XYkVxq89HrD3HQhYNtX5GxJwZY9eN+be2YX5INqzHze6qCa/Vgzl5epv/eVob+9sOCmjlNSUT5p051GTBBrZjxJLVQDtrvkPZOuTLXbHQW9PU78u3HTWpt2uUKykLPYCxR7gaLmKzzrIAl+mEa1LfndO7sRFcfkFOUdSSvWTOYE37/fGnrco/SpGYsj5adlynSS9W/e7yVdfP2Ux3xm0cp0DH25L4n9zZ2Q3UMekmXq1Ym7Gan6mhmXAQzq6aI1Vm5Hv9f7XNnhf3pugs9P22z6mijWXJt1eH7Oo2gf2IrS0KxrDZWKA11rqA6q1bLgcsXh2WnXVGyO4UzJ5m+dz3Otz94y5UmKjmw/sQZLwpNlm8WcZK2h2IsZer5RmNR6qLkybWNJOse9Mm130LdpcXEswXeeKPDbyyUKbWtWwRZ891KhXZOj93xp+Nr5vMWlij2A8v38jMtXFz0qnsVM3tQVuVCxOV+yU7GtezED6FsBPFm2eGHWIdSaUGkKlmAub+LX3f/+vJr5gs3ylM20Zypfd2N4D8PLDkPCpqFk09DGo/IM+vGyGjNOoTLoZVuaeZ4QdLvxvvcbium8xZcWXOZysoNq/taZPPM5mfr7BPF8ccJOHadvLOVQ+mDOJTjlgg2N6KCv3esjiUMaWvko6O1x4t+Nm97yNdN5i99+usjXlzzmCzaRhvmixZcXvA4+ephGtS353bavKLTvFQxG2tgW18a0LR7Wp6sTWcHDTJnGkdaaf/t+r0Xr7z+ZWbQyHU8zOYvPTR7YbZWGH677j7FFnz6duJyRBO1bdiVnsDuYVAUD1Yt3fMXrm34PVjbJJUjyShIv+KWKS9GR7AaKsi17KoRPOJJQad7eCaiHpvqyH8NWK+b1zZDLkwcXs932keRiMYzh6gzYssCVKaeDAO2XsatotlqauYJgIW9TtGE3MMcsxaTiR5PzRUoP4I7B1JtoRKZ2RKK7jZhmNIiq7c+3mfIkF8qlntc+2It4fTMk0kn+hj2Ar13ZDXivGmNJ+MqCx9NTDkrDhCsAiSPhypTD2aLV816gk2uRYFs/bAjCdpyfmTI3cEkNjO4YI8CWg5W5kzHWWvDigtvpa4JnPQwFncRh1rN4Z6fF9U2DGH5pMdex2/RX6C4lGN6+Y/XHuBtNe68REWmrUyG8YEGMuWG4MmWugndaMfcaMT9aDyg5ZifGjzWF9vw7XbTIWeYJf4IR3vYVJQf2Ak0tUHhtSEIyZxuR6iBvv7nU2+/+Cui2EDQiOhflyfpIKsV3o6knXNmu/G7isBdoXt8MqYWK/dBAKMrOwTwdpVFxq3iCL84d5HV1o6GT136yEQzN9RJCs1qNeFsZ/HWCeu4ev2asmfYkjRBKrrn5LtjGtrhQGJ47Nkxp799MQXdnypRpUD/dDPlg78BX6kr49rnsZiTT8fXSosfPu4pnfv9ewN88m82pcXXiHqNdKjs0YzEUk9qNgn3lTmsAK/vKndYALrYbnbrV0OZCvcuucqog2Wop9kKN1Jq3dyJ+vhPx3IxDPVT8dCOgGqhU+8g4VaO72/LMlE2sDd73xm7A3UbMbkvz0mKOs3k91K5yv6FSccc7vuKlxRy7Ld2xW91txPx8O+JzU+6RvPtJO3fb1c89AWFs+m9L0cHXvroe8PZOBNrk5HzvVosfrfmdHIJd3+B2+997pmh1xqg7D+ZiQQ/EuRslPCrGo3IBjoJn/aAW8XurjaGY434c8ExOHop6TZt/3ejeSVuz2zLHSlC+m01NzhJ4AnZbMX9006B8r0w5A7FN1kcQw46veWMr5FzJSp2z4yBslwpmF2vLV5Qd2Vkflyp2Z+yHoalnPYtd3+Sr3KtH+JHibj1irak683RcpY1pWs5S2mv9OVZJjsuOb3bXurHXSVySGDw9aVMNTf5XM1TkLMFuS/PstHukXJhhc7KaFV/PlGks/Zu+xPVvnckxme0qZnoAvXSq90Hs9+9nOyNH0YlbfVOe5OqEGopJ7UbB7vrxAFY2eSKZvKcfnfoLiw5TnuixqyxPuXxl0aPkSN6vKyqe5MqMQ4zg+VmXCQfe2glT7SPjVI3ubsvFisuvnTEFF/dCRT1QfPdSgQtlm4rDULvKpCdTccertZALZbttrzJ2q3qg+LWzOS5V7CN595N2LhYkz8+6uDYECiYcWCpZHXzt/XZBwaenXWJlLtT9mE4OwWLB0KD63zubszpj1J0HM+EwEOdulPCoGI/KBTgKnvX791tM5sRQzHE/DngmJw9FvabNv25075QD371UYCYnOyjfr5xy+cVFD9c2u1uTjmAmL6m4ciC2yfoou5LTBRPbaqhT5+w4CNtQC7604PJrZ3MI6KyP7zxR6Iz9MDT1ph+zWDBFGouuREhBsd32ZJ6Oq7QxTctZSnutP8cqyXE5XZRMOKIHe53EJYnBubLDC/MuJVuQs01fvnupQKj1kXJhhs3JW80seT1TpsMUK82//6A3X+S/zixamR5QX+1LYv/r7Sxv5Cg6cTYtgIoDp/LDMalgdgXSsLLNSHU86t242G40rNKC37xc7EHDLuQki3mL/VC17S3mwq7smgvzLV/32EjSrGCjvPHd+NKlks1SyUZrzZavudBlY0mzUu34ind2QyQw4R7YTLSmE48LZbtjt+pG1SZWnr3AIHH77SX9dpI79ZjzJYs9pdkPFR+1t8q3A80XZj1OFWwaoabiCoQwKF2B5nY9Zi80C9tC87PNkJ1QEcaac0WXot07Rju+7sG2DovzKIxzf1wTJfPkKNaatYZiqdD7uwRznFahe5i6z/luNezYrxLN5y0sKfnVMznea5qxv9Be5i/fbuFIuLUfUw8BIbgwYbEXHlgIi7ag4BxgovdCzfduNxGAH8G9Zsx8XjLlSs6X7dT4pcVlWJy737sXap6bcai4B3FK5nAyDhpYbt8Eaw3Vdm5NNyb5zZrgo9sthEjWZC8iOG1MQwUafehr/Ujgeqg767kVwzNTLlprPqzHPTFIihGeKtg8PeX0zJUbt6OR6Od+DZuTXa6TTJkyDdFfrQXc68rTKliav3E2o2hlejDN5U3eSGLVSvJGMqvWeDpxOyOJDsOkduNcEyW40gTJmuBix0HDJudKcgPSELRpGhdnelh/hik5fk5CTh6gjmuhHvr55Fy1QPH2TkgYY5KO+/qd1vY7+zE39iJe2whYrUZ4lrnpuL8f88qdFlLQE3ehNe/vmcU9k5Pc24/41zca+BrOFSxiDX91P2CjqXrGqB/bOm48hvW1/zjdyNpxrDULBUkt6j1Oki8wrvrjmZNwfdOMVXfbhvVRCvP+SBnEsSvh9Y2QW/WoB9V7dz9Gtiuyv70T4giTTH59K2C7FVOye5HRo9o4Ki5H6U9/bg0M5tYkxws0IxHBaWPqSDp5K6Ne60cCp63n9WbM3f24p7L776022Gqp1Jgcde0Oe/9EBgLKlOlQ/evVXovWL02bHfdMmR5UA1atexnid1yd2BV4mN+/G+fajytNkKwJLnYcNOxRc0ASjYszPUr+QtrxL1UcWkqDhpyleW83HPr55Fyr1ZCcNMjYViwG+p3W9ktli9fWAjZbMUVHIoVJSH+yYrPjKzS6J+5+rGmGpvbDQt5itRqRlyYZerFoaFYIzRvbfs8Y9WJbGTse486TbmTtONaa/rybBHP80uL4T+T643mp4gBmrMYZc/OU34wxaOY8yVb7yr4b1XuxYqPRrNZihDC5ODdqIVLCqaJt7FRdyOhRbRwVl6P0JxmHUbk1yfHyFiMRwWlj2p1DNOq1cXK6VmsxFyt2T2X3yZzBNafF5Khrd9j7z+azgoeZMo1SI1L8/oe9Fq1fnz96nZ9MmdL00mKWN3JcndibkcP8/t04135caWL1SHCx46Bhj5oDkmhcnOlR8hfSjp9QpRzL7Er4sR76+eRcLQUtdYB47e93Wtvn8xYFxxwzUAf44WnXEMe0Fj1xbyl46bTHs9MusdbsR5qnJi00gqIjTX7BhM1WS/WMUXfeTTU6PM7DNCyu3cjaUeOSqD/vJsEcXxiDBJWoP55l11Q992M91phrLbg2c4A3nsxJPj/jkGtYRGUSAAAgAElEQVRXrU/GcSEn0VqwVLQo2oIIkzN1vmhhCYiU7kFGj2rjqLgcpT/JOIzKrek+3ihEcNqYducQjXptnJyupaLFQu5gDOqhpmyLHhT2sO+HccZx2PsrWYmRTJlG6j9+1KLetUO9mJe8OJn5+jM9HP3iYpY3clydyJyRRGn5E/2//+ZSnm8uHXjbE8TnejPiP98zGNxqoJiwBaFSKHpxpOOeq1vdSOFb9YjTJZvnZtwe/O8wfOwob/6bNcGbHzSoh4oJR7JUspCCAaxvoDS2ZABn2n2s1VoI2lx8JTkm/W3rxromasaaC2WLMJZYQpCzBfuhYqUam5wFRwBuJ+4H+Fxz/o1mbC6k290sOpIzZZunph1+66lehHASj8ldzeUxYp/063Y7FyiJUVrOw7C+jbKBGVBAoTO2f3yr2YOLHtam/rnw5IRNNYg7COblKZtvLh2+w1LxTBX2BG8MsN1SBKr3y/LAGmXGqWBLNpsRfgSuLbAkPcjow+Ky3oxZbx1goGc9i00/5t1dU6CzG23tWAaf/OKcNzT3JMmtSWLzO+/tm925yFyYV2sCSopIWxTtdDtkMjf613Va3k+y61L1dWdnZfR69ntiUHJEu4K9OW4tUKxWQ7YDg2MW0Mk9y9uCpycPv6tIO//moZ/KlOlk63dv9Fq0/sHFApaoP6bWZPqsaTZn8cykzdtdeSP/Zc3nv8qw0YfqxO6MHEX93vabtZA/uemz0VK4AmpBzOtbITt+3IMjPU415H6k8JmixTs7IX91rzUWSnVU+3dCk5vRiDT39mO2Wgazu1qNOljfMNa8sxux6+sBr31/LK5M2SMxr6MqXydWrM1mzDu7IbstzWJeDiCW0yre77QMnva4dqdRMdpuxgMxSst5OI4tbhxc9Kj3nyla/Gwz4N9/0GDH1wMI5sPU3+Z+1G+CWU7mbvf7n5tx2ApM5fk5Tw6Ne9o5rm9GzOWtgfyJUfPnsNyT/thopXl7J+RnmwGRgilX8NZ2wN39eKgdcpz8lqPkwAyLwYwnO4jlqh/z082AtaapqrPZUnz/ns9fb0es7Rsk86g5kSlTpuPpfiPmz+/22mb+4cXCY2pNps+q+vNG/uJuZtUaR9nNyBjq97a/sxuxWDRoznq7ONv5kkmm7saRHqcacj9SeDZvcWXKphnpsVCqo9q/GwkKtsHKFhzjYV8sSPYj1cH67gSaK9Mup4vWgNe+PxYVzxqJeR1V+TqxYt2ux2gEz8w4vLiQG0Asp1W8/++vlpjNyWPbnUbFaMtXAzFKy3k4ji1uHFz0qPfP5i3mPFMz5G4jHkAwH6b+NvejfhPMcjJ3u9+fsy2+ddZjecpmN9BD4552jufmHBbz1kD+xKj5c1juSX9s9kLN6YLFrGexFwocS/D0pM2kJ4baIcfJbzlKDsywGEznrQ5i+a2diJJjvjtmPYkfaVQ7h6fsyfau3/A5kSlTpuPp/3u/0V5rRlenHa5OZ97GTA9Xv3y692bklexmZCydSJtWNaSn+vKwqsoCQTVQ/HjdZz4nmS/YnC3ZbPuKWU/SUIKpnOSMJdEINlqKL817HRzpcaoqv7oe8N5uyFxeslhwKNrG9x4pTSM8XoJqggJtxHC6Tdzx2nkCecsU3fvKkoMQgh+v+5iHx+b3YPztH9ZjwOcv7/gsFiTnJoy1ZhgyN9EwO0tigdsLdMeicqsecbZkM2H3Yk3TjnFt1u0/5AMpidEBqrU3RmmY1WGY5GFjnoaLjmLNjVrUsxM06v22JVgsWJwr2R2sbzeCeZjSLGh7oeZcqZ0v5LrtY+lDY3+Yuj/TjYGGg/yJhJhVdiUXyzZv7UQ9NqhRSOW02DRiTcGGRqRptZs/7UkKjsEcp+mwc4z7nsNikOgCdud4r24EeJapRxTEms2WScivBYqLFQdHwHROcql8tO+QTJkypet3b/Qmrv/Di5l1JtPD10uLHpaABHj4bjXidj3iTOlEXm6PrRP3V23HV7y5J8eqqvyjtYD3a8bTfW9fUQ0Ub2+H5C3JbmgufgqWIFCwH2um20mrx0G/diN2K46kFcH7tYj1puLdWggIFgvySNXOE3V8/BapWNSjoEpPFST70QH+N+nvUZG5SZ8TPHLFOcAKr7XUsY73IBoHHXuYDrP09OOi98PRY5uGl7alSURPxgYOj/8wC1qs9ZHQwMdRP4a25Ahq0cHcqgWK61smd6Q7ZkkuU7dGobcLlmC7pdloKmx6McXD1so4SN3jIrMPi0cyz4TWbPoxkdZUgxghBJvNmJaC1WqUWgE+s29lynQ0vbkd8ub2wU6jFPAPnswsWpkevsqu5EvzvQ9Ls92Rw3XibkZWayF5S49VVTlQir1QcalsI6RmvRmTszQTrujkLcx6gm1fsd1UPDftHBv92o3YLXsSP1YIrXhjKyCIBLN5sxtxlGrniRIP+6StU7GoR0GVni3ZaA1CaG7uhcdG5iZ9TvDIfqzxpDnujWp0rOM9iMZBxx6mwyw9/bjom/Vo5Nim4aVdKXEtU3Nl3FyVYRY0TwqOggY+jkblT2itWa2am7HLk05PzDT6SOjtCUfwUT2i6MBiTvdgioetlXHyfo6LzD4sHsk824s0rjQ3JmFsdlQiBaDJ2aRWgM/sW5kyHU39ievfOO2xWMgK82R6NOq3amV5I4frxN2MVH1Nrq/XSVXlfixopMx/RUfyVNkhiM2T2AlHdvIWdkNYnrT5G+dy5Gx5bPRrN2L3hTmXSxWbWMO2r/jctM0L817HPjTqOGlKPOxTDqlY1KOgShMEcMkW3G+oYyNzkz4neOQEN1uyBaeL1sduRRkHHXuYDsPa9uOidwM9cmzT8NJfXnD57eUSMzk5dq5K0q5kXoOxoGnEkdDAx9Go/Ikt36Cbr80e0LSSGGgtjoTeFlLw7IzLtVmXGHowxcPWyjh5P8dFZh8Wj2SeeZbghTmXuZzFTN7Q7S6ULc6WbFwhCFVv24+69jNlOumKlOb3+m5GfiNLXM/0CPUrp3utwa/c9VE6+94epRNnYqt4gq0+l0O3ValgCwSw0vb5ebZgP3LwlfndvUbMejPmdj0mb8OFssPylD3g5T4q+rX7/WVX8uJ8jivTihu1iItle+hxxs1LmfIkV8uayxfSv4SPgiotu6bg3VNTogd7elRPe9Ln7pyFRmRucI7St8PeNyxHaFgMEnTsYeo/byNSfLSnqIWK/TbKtezA+a4k725c9AG2ePgc6X5/ty50Ld0dX43sX8UTrLUU603FjZpJkK64koore1C6j0rD8ieStoVDbFBHQW8D/Pmd1kBF+P54DsMFD/tdksj/MOLTf/xfPp3jTMkijDVPlCPCGHK2oBWbmi9+pDDMreH9yZQp02j95T2ftebBH/2SLfj18w9GX8yUaZSen3Uou4JaYP62bfuKv94KH3qu62dJJ25n5FLZoRmLoVWV1xoRtUCz65skX1cKXlvz+eutED/WvLEVoDTc3AvZbCleXfP5qBYPeLkfVlXl3kri+kj404cZs7Q2zHrWA51/VIzG7ds4CNi0HKEHjVH/ebebMa+vh3y0F3GvHuFHirv1iLWmGorefRgWoHHiNOtZ/GwjpOgIbAzOeWU7xJPioduyjqqHZYPa8U2/6qHCScEUJ+8ZFqtHvZaGHX/Ws4baA4dVgH+c45Up06dNv7vauyvyt5/Id+pWZcr0KGRLwddPZVSto+jErcgpT3J1Qg2tqrzeMr/73JTDszMuT5ZtIq1wLFMg7smKi2cJiq4EAeWcZKUaDni5H1ZV5W4LVf9xjoMdPW7M0tqw6ccPdP5RMRq3b+MgYNNyhB40Rv3n3fIVp0qSWGuKrkRIQdERzOTlUPTuw7AAjROnTT/m2qzNQl4yVzAFKk+XLJqxeui2rKPqYdmgVmshiwVDdnPkIKY4ec+wWD3qtTTs+Jt+PNQeOKwCfEbTypRpPNUCxR981Op57TcuZRatTI9e3+izav35ndaQd2aCE2jTAqg4pFbknvIkpwo2V6cEQvR52IH3qiEzHny4p8lZ0IrhlGWQvmm4z6PaO0ZhcNNePy529DhKa8PDOP+D9m0cBGxajtCDxqj/vAmythnDs9M2Qgi0ZiQaGI6Hzh3VDjjo32TXe+bzFgsFm2emzGsJwveTcGH7MGxQSRyELbhU1JzrQmz3v6db3WPzKNfSqHMfZg98lBa6TJk+y/p3HzR7aHhnihYvLWZWmUyPXr+y1Pu9/aP1gP1QUXQe/9/cT6JO5M1ImhI/97u7BjN6efIgqdaRoBHkLcGNvYidlrFuzOatDtL3cXi5j5qX8qDq97wn+NVxzr/jK17f9FnZiUDA05MOz88Of8o7qm/d7bjXiIi0xWLeGnhfcpy0HKHDULiH5ar0t6/kmNoZ057EjyFnHx0NPO65x40TzTHecwSl1eFRmkda/2LceTNOHw97T/fvaoFitRrSUqP7l1a/ZalkPXAOWaZMmR5c//Ld/Z6ff+NSASmyNZfp0euJCZsnJiw+3DP8+UDBD9YCvjWk7tVJV3aLRq+f+8qUTT00fvNqoGhEiknPwpEghWDPV+SkYD/QbDZjNhoRyxXnsXi5HzZ2dJTSPO+7vuJ+Qx16/h1f8cqdFm9uhRQsQcGCN7ZCXrnTGurJHzdPZT4n+dlGyP1mPBQBm5YjNCxG4+YODEPWPj1lHxsNfJy8hY8LT9vdtqQOzxtbIY7kkeUqHWXe9PaRI8eh+3dVP+anmwF7IVyZcg7NV+qv37LVUg+cQ5YpU6YH09s7IT/Z7LVZ/qPLmUUr08enfqpWZtUaruxmhF4/d8WzeH7WZcKBt3ZCHEvwjaUcZ0o25ydsPj/rUfEszkzYTHuSpZLN+bL1WLzcDxs7OkppnvfFgjTF5w45/2otZNc3tVvyjiBvSya7djiO0rf+PJWFgs21WZuNZjwUAZuWIzQsRuPmDgxD1p6fsI+NBj5O3sLHhaftbltSh2fSE9zejx9ZrtJR5k13H6sRR45D9+/e2okoOZLn51wqrjw0X6m/fstWSz1wDlmmTJkeTP27Il8/5fHERGYGyfTx6RtLWb2RcZWtTAb93GXXJMJu+brj11YavjDrIMSB3zTxpD9OT/e4fvsdX/FmTfDR7daxbDXDPO+N6HBPe9XXhAoKXVZdTwqakRpZM2HcPJX5vIUlJb86ZPuzO0foUAxw+/i1QHF7P6Ieaoq2oOBIXpxL/zyYC88btaiDbD1u3RVHmpvgemgsXqbw5Oi8hXHmwMPMTamHum1hFFTb1dsfJL9imNXpTj0+0rxJ+ji5q1Nzwg4b++Tzd9rt+PlOSMkRnC3ZTNjD85UO4mHaNyxPaJwxOKpNL1OmTIPyY83v3mj2vPZbT2W7Ipk+Xn1t0UMKc/0I8PPdiLv7MaeLWcHNfmV/5Tjwc3drmN981Hs+qUrsJIHm2NjSB+l/xRM40hSMTOQrjSPFkeP3IO0YxwZV8QTrzZi3d0LCGMqOoB5p7u7HfFCLBj7/yp0Wr9xpPRQkrBRwfTMkUpqKI4iU5vpmiPwETLHuuJccUzE8yYmB46+FUVanO/sxgdYPZd4cBRV9Zz9mPzoYg7e3Q9ZaauCcSUySeCTtO2qe0FHbmClTptH6o5tNtrvWzaQr+Pa5/GNsUaaTqElP8kJfbZG/uJtZtdKU3Yzw8fnuH5cSO0ne4tjY0gfp/6Wyw6RnsRsomqGmGSl22xSho8bvQdoxjg3KFHGMEQI8S+Ar0FpwsWLz/futgc/v+jE7vnooSFiNBjRoev5vXn+86o77UsGM5a6v2zs3x18Lo6xOl8oWrYiHMm+Ogoq+VLbQ2jxd9SQIoblRjQbOmcQkrUbIceLxcaG6M2X6rOtfvttbW+S7Fwvk7E/AU51MJ06/vJTVGxlH2c0IH5/v/nGp6hvbSLfylhhpkerXg/R/yjM1E67OODRiTSOGZ2ccvrF0dDvTg7RjnDhMeZKlokXRNnYbWwqemXZYyEnWGmrg86GCUOmRxxxXWguuzTg4FtRCjWPBtRkHrR//H9HuuIdacHXG4dkZh1Cl52eMq2RM6qHGa+9ce9L8PJ+3uFSxH8q8GXcNJBjkZ6YOxqFkC04XrYFzJjFJqxFynHg8jHWaKdNJ1816NHDB91tPFR9TazKddP3K6cG8EaWz7/R+ZTkjbX0cvvvHpWHWJiE0r274Y/vTH6T/U57km0t5vrl0rI8/lHaMiwveCxVzeYurXbjgRqRYKMiBzyfY5yTHZL2p2GnFTHgmuX/Ws9j044EYp+UGVDxBGMMzU27neH+9HTLZfv/jvvFNdiRMu6Hc1b+fbATHynHotzr1I5HPlCxenPMeeN6Mi9ZN3ld2Jc+4Znu9ERkAQpoOqxHyoG1cb8astxQvHzPXK1Omk6b/971Gz17ytRmHZ6c/+Q6GTJ9NfXHOZcIR7LXzKzdaije2Q56byerddCv7q3YClNhJmjEda9P9hkkCPkn+9AfFBb+0mBv4fIJ9/ulmwE5LcXc/ohaA0PDRXsTvrTbYaqmeGKflnry2HjDrWeyHsNaIeGs7ZC/U2EIwl7c+EWPTn9Ow3YxT+3eUdj5sq9Nh5znM3vc47Zj9515rRFzfjJjLWydmjWbK9CCKleZfvddr0coS1zM9TjlS8LVTvQ9PX76dWbX6ld2MnAAldhJX0LE2TXoGzXuS/OkPigu+ULYHPp9gn0uO5E5DUXAkz866zOYt3tmJmMyZ/IfuGKflnhQd2PRjXph3WW8pQg0lR3JlxmUxb30ixqY/p2HLV6n9O0o7H7bV6bDzHGbve5x2zP5zr7cUz805LOatE7NGH1TLy8tPLS8v/5fl5eV32/+/nPKef7K8vLy+vLx8vf3fP30cbc308PWX93xu7x8QL/KW4O9fyG5GMj1efWupl/T5J7eyJPZ+nUibVjXkSPakz4KmPMnVsuZyG3/78u1Wqj/9uHjWj1ujELujxvVBccFpn0+wz7E2iFchTP7Htq+4OGFRCw9imrcEaw3F1an02E95klMFm6tTAtFVKfiTMDb9caqHmrItBvp31HY+TKvTOOc5zvvGrbT+MNv48u1WKk57y9dD538m/hnwT1dWVv7V8vLyPwL+D+BXUt73f6+srPzPH2/TMj1q9Seu/+0nckx+xv+2Z/rk61tnev+evLoRsNWKmclliN9EJ26V7viKN/fkibInpemzgCp+WIjdB43FMMTrtCepRQf42+S4Se7JsPN9Usemv10lR6T273G382HrKJXWH6ZG5Xql2fyqJ3zDZHl5eR74AvA77Zd+B/jC8vLyI77NzfRJ0Foj5g9v9tcWyRLXMz1+nSnZXO3KW9LAy3cyq1a3TtzNyGotJG/pE2VPStNnAVX8sBC7DxqLYXkPT0/Z7LZM/sNhuSfd5/ukjk1/u2Y8mdq/x93Oh62jVFp/mBo2DwQi1eZ3q/nZugk8hs4Cd1ZWVmKA9v/vtl/v128sLy//9fLy8veWl5d/4eNsZKZHo3/x7j5h13OBi2WLX1zIkoQzfTL0N/p2R76XWbV6dOJsWlVfk+u7BfskWGA+biX+9NVayFbb6vHC1KfDrpZmqwoVA/U4knGdPOR4DxqL7s83YnpsPF+c9dj044HjTnpy6Pk+qWPT367pvMV3L7mp/fss6aiV1h+Whs2Dn2wEqRbLvXjIgTL1658B/+vKykq4vLz8LeA/LC8vf25lZWUr7c3vvffex9u6x6RPcz9DBf/8rRzdz1f/zkyT1dXVsT7/ae77gyrr+8ejzyGBA9v39242+Pm7Wzyu8jePY9wvXx5I4evoxN2MVDzBVp+r4ijWkjSv9nEuvh7WcR5EHweq+FH0Mw2BmiB2u9UZ12b/EQb1oLEYlfdwIWWZHXa+o7Tn45xLae1K61+aPglz/jiqeIL1ZsxGM+b9mmbSkzjC0Om+f189dPTyYXEahimeyOzHt4Cl5eVla2VlJV5eXraA0+3XO1pZWbnf9e8/XV5evgVcBf4y7aCj/oB+VvTee+99qvv5b99vsBnsdH4u2oL/8avnqbiHr8lPe98fRFnfP76+P6k0/8vKfbbbtt69WLBTPsdXFz/+chGfxHH/5F8JPGRdKjs0Y3EsC0xarsJxPOMP6zifdD2qfqbZVyY9U5Tuk2ZtetT6tMylT0s70zTrWVzfjCg4EgvNvUbMD+77CHjo6OVx4jTMvnU2f7J2d/u1srKyDlwHfrP90m8CP11ZWdnoft/y8vJS17+vAU8AKx9TMzM9Av2fP9/v+fk3LxXGuhHJlOnjkiUFv9pXjf17tzOrVqITt1qnPMnVCXUsdGdarsJxPOMP6zifdD2qfqbhV7+xlOMbS7nHgmR9nPq0zKVPSzvTtOnHPDfnMJ+3mC3YRDEsFi0QPHT08jhxGoYfrny277vH1X8H/OPl5eV3gX/c/pnl5eU/Wl5efqH9nv9teXn5zeXl5Z8B/xz4re7dkkyfLl3fDPjRetDz2n/7uSxxPdMnT792NkP8DtOJs2kBVBy4fAxLTlquwrie8W7rxbvVkCtTvVcOn8W8lf541QLFrXrEvYZ5yvsgNp1hNqZHbTv7pOlOGzW7Hxm61dmSzYQ9Xq7Mo1S/1ehOPeZ8qddHdJQ5/zgtXlVfs5CTLOYtrkw5FG2fCVtQi+jkkDys9TvOd8ywWGw+8Nk//VpZWXkH+HLK63+r69+//bE2KtMj1f/+Zr3n518+7bE8md2ZZ/r/27vzMDmqcvHj356efclkshGyG0JeCIKRJARUCKJsXhCURZBF5QoGBRWvioKRTRQUf7Kv/kDuZREFFeVyQaIkgFeUsEgg4SVkX0iYSWYms/b0dPf949Qw3Z1Zenqm9/fzPDxkqqu6z6mqrtOn6j3vyT6fmFyO3wc9SRJXN3WzqbWbadUF+VM8Rn7fNh5hyaZcjQ+9KC+C1xqCMfMz5GNK1Oj9tbsrzKrGIK3dESZWFuVUmE62agyE2doWoq07Qm2Jj+5whFW7guzoDGf0XOor1GhrW4gdnbHHOtFzPtMhXulMaTzYNSbT+8KYbLJ+dze/3xA7KHDxHHsqYrJTXVkRh0yIzfBmWbUc64wMQbIpV+NDL2bVlgAR1jQF83p8Q/T+2tza/f5kgNNqSnIqTCdbvbM7yKxRfiIRCIQilBWBzxdhbXN3Rs+lvkKNZo3ys7a5O6kxPZkO8UpnSuPBrjGZ3hfGZJNb3mglHNV3nzO6mGPiJqo1JpscG3d+2rgRxzojQ9BfrPZg4SLNgUhMKs5RpUXMHVtCIBTJ6/EN0fvr3fYwVcU+5owpiQltac6z0LR0ag5EmFDhZ05dCSV+2B2MUF3sY1KVP6PnUvz5Dm5G+0lV/qTG9PT1fuk8d+K/9y6lcSVjy4tG/Ps72DUm0/vCmGyxoz3Eg+/EDlz/xkE1FPnyK8LA5Jf4cSPPvRugvduebFugWpRE4tL7G6sw0LZ9pqL1+1iwV2lOjnHoq65An/WP3l/BPtKRJhPakqspYkdaz3k1qrSIOaXu0W97t0vOkA3lij/WU6r9SZ3v/b1fOkPRhpPSON5g5+9AaZ0H3BcJpLA2Jl/csaqVQNTcOlOr/Xz2AxWZK5AxCdh/dDFTqvxsaXMnb2cInn+3i2OnFvYTvcL7BdeP4cRiD7Ztts6onYy+6vrs1k6e3dqZVDrSoe4Di5nvla3n1UiXK1vrmYzhnr/5tC+MSVZ9R4h74tL5XnxANSVF9lTEZDefz7dHx8NCtawz8r7hxGIPtm2y4V3ZqK+6NgVCNAbCSaUjHeo+sJj5Xtl6Xo10ubK1nskY7vmbT/vCmGT9/PUW2rp7QxPHlRdx9uzKDJbImMTFjxt5enMnkUhhh9pamJZnOCk1E9k2HbOdp0NfdQ2GIULsF6mvVKcjsQ8GSmU7kIFCY7I97Gug8iW7T4db5+GEGiUjn78/Q00LnC/7wphkbG7t5t63Yp+KfOugGiqLs+eabcxADt+7jAp/b+bELW0h3mjs5sAxhfuE2769nuGk1Ew25W8u6quuJUXs8Xg8FfVPNpVtc5B+j122h32lonzDfc9s32fZrJCuFcakwk9fa6Er6lIzpcrPeWLpfE3uqCj2ccSk2BtKT2ws7EF/1hnxDCelZiHFcfdV19FlLntTquufbCrbzR2+fo9dtod9paJ8w33PbN9n2ayQrhXGjLS3moI89E57zLLvzq2hvNg68ya3nDg9NlTrT9YZMTC8lJqFFMfdV10/Prmcj08uT3n9k01l2xKi32OX7alSU1G+4b5ntu+zbFZI1wpjRlIkEuF7/2gm+sHirFHFfH6WjRUxuef4qW429h6rGrtZ29yduQJlWNrGjIjIbOB+YCywEzhXVdfErbMEOAMIAUHgMlV9Ol1lTDql5iDbZruhjh/or66prn+yqWxr/Ax47DKdNnYgw0lr2xyEl+oDexzX4abKzYZUu7ksl68VxmTKnzZ2smxbIGbZknmjKLYMWiYHjS3389GJZTz3bu85/cSmDr5xYE0GS5U56bwddydwm6rOBm4D7upjnX8CC1T1IOA84BERyYrE4fkaXpFL8f/JHoOpFZF+t8v245ps+RoDYd5oKerzuA63ztm+z4wx+aW9O8zlLzXHLDti7zI+Pb2w52Ywue2EaRaq1SMtnRERmQAcDDzsLXoYOFhExkevp6pPq2pPQOjrgA/3JCXj8jW8Ipfi/5M9BrUl9Ltdth/XZMv3zu4gFf5In8d1uHXO9n1mjMkvN65sZXNr7wyHfh9cv7AWn822bnLYv02Pvde+oj7ItrZQP2vnt3SFaU0FtqpqCEBVQyKyzVte38825wJrVXVLf2+6Zs2a/l4aVLLbjvb+owMamqAh6RKMnOagG6TdEnIhSVMrItT2c5M6vt6rG33UFkP0NT0SgeZuGN2UnWMAkjkGDZvWDrhdNh7XaEMtX89x3bR50/vL4o/rcOucyPZDOTdH0lC/35kq50hL9rq27777jnBJjBkZqxqD/OL1lphlF3bfosYAABo5SURBVOxfxf51OfgFNSbK5Co/88eXsKK+9+bvExs7uGBOdQZLlRlZOc+IiCwCrgGOHmi9ZBvQNWvW5E3j2xgIs+G9LvYaAzO8vNWNQdinjzvVfdW7qT5AMBSJydHe3h1mkt/HvnkS155PxztRTfUB1m3cjMyY9v6ydB/XoZybI2moxztT5RxphXiem/zWHY5w0QuNBKOihidUFPG9D4/KXKGMGUEnTq+I6Yz8fkNhdkbS1dJuBiaLiB/A+/8kb3kMETkMeAA4WVU1TeXLWcMNs7L4//w0a1QJHSFfRo9rroQA5ko5jSk0d6xq5ZWG2O/hDYeOprY0d24SGDOQk2bEhmr9fUcXm1sLL6tWWr7Rqvoe8BpwprfoTOBVVY0J0RKRBcAjwKmq+ko6ypbrhptm1eL/81NdWREfrAln9LjmSgrgXCmnMYXk7aYg176yO2bZp6eX8+kZWZHTxpgRMaOmmAXjY28S/m594Q1kT2eY1mLgfhH5IdCIGxOCiDwJ/FBVVwC3AxXAXSLSs905qroyjeXMKSORZtVSjean2hIyGmqXKymAc6WcxhSKrlCE859rpDNqLO/oUh8/O3R05gplTIqcMrOSl+p7s8U9uq7wUvymrTOiqm8BC/tY/qmofy9IV3nyxaxRJax4rwsIU+HFu7cFYb4N7jMZlivnZq6U05hC8ZNXd/OvnbHhWdctHM1elf4MlciY1PnMjAou+2czYe9h/MpdQd5qCrLf6MJpgywWJ8dZmJXJVrlybuZKOY0pBC9sD3DjytaYZSfPqOBz+1h4lslPe1X6WbR3bBTDo+sKK1QrK7NpmaGxMKuhGeqM89ny3rkoV87NXCmnMfmsoTPE+ct3ET1aa1JlEb/4yGibU8TktVNmVvDstt7Z2B9b187lH64pmPO+cH8lmYKUyhnnc2k2e2OMySbhSITFzzXybnvs9fKOw+sK+oaOKQwnTq+gLCoKcX1LiP/d0ZW5AqWZfcNNQUllGldLEWuMMcm5eWUrS7cGYpZdcmA1iyaVZ6hExqRPbWkRx0+NDUX8z7fbMlSa9LPOiCkoqUzjailijTFm6JZt6+TquDS+h04o5fKDbXJDUzjOnV0Z8/fjGzpoKpDICuuMmILSk8Y12kilcU3lextjTD7a0NLNl5btej+TEEBdmY9fLqqjuMiunaZwHDmpjKnVvbFanSH47br2DJYofawzYgpKKmect9nsjTEmcW3BMGf9ZSeNUU+PfcDdR4xhSrXl1zGFpcjn45x9Y5+O3P92O5FI/kdXWGfEFJRUpnG1FLHGGJOYSCTCRS808WZjd8zyJfNGcfQUGydiCtNZ+1YR/UDwjV1BXm3I/3GnduvBFJxUpnG1FLHGGDO4m1a28vsNsXMpnDSjnEsOrM5QiYzJvMlVfo6eXMbTW3qTOdy9upU7x4/JYKlSz27ZGmOMMSZtlm7p5KqXYwesz6kr5raP1RXMvArG9OeLUhXz96PrOtjWFspQadLDOiPGGGOMSYs3dgX50rLYiQ1Hl/p48KixVJfYTxJjjp1azj6jegeyd0fc05F8Zt98Y4wxxqTc1rYQpz/TQEuwtytS5IN7jxzDB0ZZ1Lgx4Aayf+2Amphl92kbLcH8TfNrnRFjjDHGpFRTIMxpzzSwLW6G9avmj+KoyTZg3ZhoZ8yqYExU8pvmrggPvJ2/aX6tM2KMMcaYlGkJhjn1mQZWxWXOOn//Ki46wAasGxOvsriIf98vduzIbW+2EgjlZ5pf64wYY4wxJiXau8OcsXQnK+pj05N+alo51x1SawPWjenH+ftXUdY7dIQtbSHu07bMFSiFrDNijDEp1BgI81J9gKVbOnmpPkBjIH/jfo2JtrsrzOnP7ORv27tilh+2Vym/XFSH32ZYN6ZfEyr8fHF27NORG/7VkpdjR6wzYowxKdIYCLPivS6CoQhjy3wEQxFWvNdlHRKT9xo6Q3z6qQZeiOuIHDyuhEc+OZbKYvv5Ycxgvv2hGqqKezvtDZ1h7ngz/zJr2dXAGGNS5J3dQapKXPyvz+ejsriIqhK33Jh89XZTkOP+u4HXdsae5wfUFfPYMeMYVWo/PYxJxPgKPxfGjau69Y1Wdnbm17wjdkUwxpgUaQ5EqPDHhqJU+H00B/JzEKIxT27q4BNP1PPO7tjB6vPGlfCn48ZRV2Y/O4wZios/WE1dWW87sjsY4Qcv7R5gi9xjVwVjjEmR2jIfHXHZTzpCEWrLLFbe5Je2YJhLX2zi83/ZFTOPCMCivct4/LhxjCn397O1MaY/taVFfOug2HlHHn6nneXbOjNUopFnnRFjjEmRWaNKaAu6jEKRSIT27jBtQbfcmHyxbFsnH3v8Pe5avWemnzP2qeA3R9vs6sYMx1f2r2bO6NiJQb/5v010dOfHU3a7OhhjTIrUlRUxf0IpJX4fOwMRSvw+5k8otVAVkxdW7gpyyp8bOPnpnaxviY1h9/vg+oW13HF4HWV+exJozHCU+n3c+NHRRH+T1reEuOaV5oyVaSQVD76KMcaYZNWVFbFgfFmmi2HMiIhEIizbFuDWN1v5y9ZAn+tMr/Zzx+F1fGSinffGjJRDJpTx5f2quOet3ieQt7/ZxsIJZZw0oyKDJRs+64wYY4wxZkCbW7t5ZG0HD65p2+MpSLTz96viivmjLCzLmBRYMm8UT27qZGt773fwa883sv/oYmaPzt3wX+uMGGOMMWYPDZ0h/rC+g8fWd/D3HV0DrvvRiaVcPb+WeeNL01Q6YwrPqNIi7j2yjhOeaqBn7sPW7ghn/XUXTx4/jvEVuZkkwjojxhhjjAHcrOlPbHQdkGXbAoQGGR+7cEIplxxUzbFTyvH5bGyIMam2cK8yfnxILd95sXe8yJrmbj79VAN/PC43OyTWGTHGGGMKWGcIHt/QwaPr2vnzlk4Cg8ynVuaHE6ZVsHhONQsm2JMQY9Lty/tV8XJ9F79e2/H+stVN3Zz4VAOPHTOOyVW51SGxzogxxhhTYIJhNxD90XXtPLGhgrbQrkG3mT++hNNnVnLaPpWWEc6YDPL5fNz4kTrqO8MxiSTeaurm8Mff447D6zh2ankGSzg01hkxxhhjCkB9R4i/bA3wzJZO/rqtk8ZATwxW/+FVc0YXc8rMSk6ZWcGMGvvJYEy2KC/28eBRYzn7rztZGtUh2RUI87mlO/nC7EounTuKSTnwlMSuLMYYY/KCiMwG7gfGAjuBc1V1Tdw6fuBm4DggAlynqr9Md1lTLRKJsL0jzMv1Xbxc38XydwO82hAkkSnSplf7OXVmBafMrGROXe5m6DEm35UX+3jgqLF8cdkuntocOyP7/W+388jads6ZXcXnZ1Uyd2xJ1o7rss6IMcaYfHEncJuqPiAiZwN3AUfFrXMWMAvYF9dpeVVElqrqhrSWdAgikQjdEQiEInSFIgTC0BYM09QVoSkQpqkrTFMgzPb2MJvautnYEuKtpiDNXYnPzrxXRRGf+UAFp86sZN647P3RYoyJVV7s46FPjOGmla386JXdMUknOkNwz+o27lndxowaPx+dWMa0cDGH1wSYXlPMxIoi/EWZ/65bZ8QYY0zOE5EJwMHA0d6ih4FbRWS8qtZHrfo54B5VDQP1IvIH4DTgZyNVlme2dHL3qlbCQDjiHr+EIxCORN7/OxLpec0t6wq7cRyuwwGBcE/Hw/2deLcicXVlPk6cXsGhpbv43LyZWfGjxBgzdEU+H5ccVMNhe5Xy1ecbWdfHXEAbWkJsaGkHSvnJ2ob3l1cV+6gu8VFTUkR1iY9yvw+fD4p84Pf5KPJBEeD3wVULalPytNQXiaTiEpc6zc3NuVVgY4zJIbW1tTn5i1RE5gH/qaoHRC1bBZytqq9ELVsJnKeqL3l/fxeYoqpf71nH2hljjEmd+HbG0mEYY4wxxhhjMsI6I8YYY/LBZmCyN0C9Z6D6JG95tE3A9Ki/p/WxjjHGmDTJuTEjuRpCYIwxJnVU9T0ReQ04E3jA+/+rceNFAH4LnC8iv8MNYD8ZODx6BWtnjDEmfezJiDHGmHyxGLhYRN4GLvb+RkSeFJH53jr/BawD1gAvAler6vpMFNYYY0wODmAfjkRy0OcKERmLa1T3AbpwDetXVLVeRA7FpbSsADbgBnC+522X1GvZRkSuAK4EDlTVNwqkzuXAL4BPAp3A31X1goHO62RfyyYicgJwDW5mNh9wlar+Lt/qLSI3AKcAM/DOa2/5iNczW/eBSZ0E52BZApwBhIAgcJmqPp3uso60oZzvIiLAq8Dtqvrt9JUyNRKtu4icDizBXWMjwCdVdUc6yzrSEjznJwD3AVOBEuBZ4Ouq2p3m4o6Y/tqSuHWyar6lQnsy0pODfjZwG+5HaK6KAD9VVVHVA4G1wHUiUoQLUfiaV8/ngOsAkn0t24jIwcChwEbv77yvs+enuE7IbO+YL/GWD3ReJ/taVhARH67TfY6qzgXOAe73jl2+1fsPwBF453WUVNQzW/eBSZ1Ejvk/gQWqehBwHvCIiFSksYypktD57v1Auwv3XcwXg9bde2p4JXC0qn4Q+BjQnM5Cpkgix/0yYLV3zh8EzAM+m74ipkR/bUm06PmWDgOuFJEZqS9a3wqmMxKVg/5hb9HDwMEiMj5zpUqequ5S1WVRi17EDcqcB3Sq6gve8juB071/J/ta1hCRMtxF5cKoxXldZwARqQbOBZaoagRAVXcMdF4n+1p6ajQkYaDW+/do4F1gHHlWb1V9QVVjBlKn4vhm8z4wqZHoMVfVp1W13fvzddxd8rFpK2gKDPF8/x7wBPB2moqXUkOo+yXADaq6HUBVm1W1kxw2hLpHgBrvBlcZUApsTVtBU6CvtqQP78+35I2r65lvKSMKpjOCewS3VVVDAN7/t3nLc5r3JboQ+CMuM8z7vWFVbQCKRGTMMF7LJlcDD8TNlpzvdQYXjrcTuEJEVojIMhH5GAOf18m+ljW8jtfpwOMishF3wTyXPK93lFTUM9f2gRm+ZI75ucBaVd2ShvKlUkJ1F5EPAcfiQmHzRaLHfQ4wU0SeE5FXROQH3lPpXJZo3a8BZuNucm0HnlbVv6WzoBkS8/sHl2UwY21AIXVG8tktQCtwa6YLkkoichgwH7g902XJAD8wE5cdaD5wKfA7oDqjpUoxESkGvg+cpKrTgROB35Dn9TYmk0RkEe5H2pmZLks6iEgJcDewuOfHa4Hx40KUjgYWAcfjQmILwWm4p4B7A5OBI0Tk1MwWqfAUUmck0Rz0OcUbqLQv8DlVDROXQ19ExgFhVd01jNeyxSJgf2C9iGwApgBP4+Ie87XOPTYB3XiPnFX1H0AD0EH/5/VA53yufB/mApN67lR5/2/DjZ3J53r3SLYu+bQPzPAlfMy9mz4PACerqqa1lKmRSN33xj19ftJrW76JS/98d3qLOuKGMvfOo6oaUNUW4HHgkLSWdOQlWveLgQe9cKVmXN0/ntaSZkZWzbdUMJ0RdRmSenLQQ/856HOGiPwYN+7hZFUNeItfBiq8EB5wqS1/O8zXsoKqXqeqk1R1hqrOALbgHqv/jDytcw8vhOxZ3J2rniwhE3CxzX2e1wOd8zn0fdgCTPEy3CAi+wN74bLH5XO9gYGvW6l4LfU1MpmQ6DEXkQXAI8CpqvpKekuZGonUXVU3qeq4qLblRlw8/QVpL/AIGsJ3/SHgGBHxeU+JPgH8K30lHXlDqPt6XEYpRKQUl61yj+xTeahnvqUibxzNycCjmSpMoaX23Q+X5q0OaMSlecvJOz8icgDuC/M27u44wHpV/YyIfASXNaKc3nS1O7ztknotG3l3sE5Ql9o37+ssIjOBe3EDSoPA5ar6PwOd18m+lk1E5CzcwNKwt+gKVf1DvtVbRG7GZXGZiHvqtVNVD0hFPbN1H5jU6e+Yi8iTwA9VdYWIvIRLBxo9gPccVV2Z9gKPoETqHrf+lUC15kdq30SOexFwAy48K4yLOPi2F22RsxKs+z645DUTceFqzwLf0NxO7dtfWxJdbz8utP8Yb7PrVTVjTwILqjNijDHGGGOMyR4FE6ZljDHGGGOMyS7WGTHGGGOMMcZkhHVGjDHGGGOMMRlhnRFjjDHGGGNMRlhnxBhjjDHGGJMRxZkugDG5QER+BWxR1R9kuiwDEZEIsK+qvpPpshhjjBkaEbkT2Kqq16T5cy8ErgSqgOmqujOdn28Km3VGjDHGGGPSTES+CHxZVXsm3kVVF2egHCXA/wMOVdWUTXYoIsuAB1T1l6n6DJObLEzLGLMHEbEbFcaYgpLO616WXWP3wk38+2amCzIQb6I+k4ey6ctgTJ9E5FLg68AoYBvwVVX9i4gcAtwE7I+bhf4x4Fuq2uVtFwG+BlyCm4n0RuBXwH8BHwSews243iUiRwIPALcD3wJacTOcP9hPmU4AfoSbrXgVsFhVX+9n3QhwIfAfwHjgQeAiVY14M/3OUtWzvXVnAOuBElXt9u4kvQAcBRyEmx32i8DNwImAAqep6oaoj/yUiHzT21/3AZf2zKQrIucB3/H2xz+BC1R1Y1Q5LwK+ibs2fKCv+hhjTK4QkQ3AXcA5wN7AH4ALVbUz6rp/C66deEZEvgxcD5zuvcVvcNfQwGDthIjUeu91PNAO3AP8WFXD3lOQ83HX3XOBZcC/ASUi0gp0q+ro+JBgETkfuBQYg2sLFqvqNu+1ftuWPvZDWV/1AqYDr3rLmkTkn6p6VNy29wOvq+rPRWQysMX7nNu8GcxfAsYBtbj2dSGuDfmbV94tInItcDhwqIjcCPxKVS/yZkm/BZgH1ANLVPU33uf+Cte2TwcWAScBS+PrZnKfPRkxWU1EBPcDeYGq1gDHAhu8l0O4BmQccBjwCeCrcW9xLO4idyjwXeBu4GxgKq5DcmbUuhO995oMfAG42/v8+DJ9GLgX+AowFtfQ/dG72PfnBGABrkNxuleuRJ2Ba0gnA/sAf8d1MsYAq4Er4tb/DDAfOBh38T7PK/dJwGXAZ3EN1/PAw3HbnoxrSOYMoXzGGJPNzsJdc/cBZgPRY/8m4q6l04ELgMtx7cVc4EPAIX2s3187cQvuB/lM3I/nc4EvRW27EFiHexJxNrAY+LuqVqvq6PhCi8hRwE9wbcbewEbg13GrJdq29FkvVX0bOMBbZ3R8R8SzHDjS+/cirw5HRP39vHfDqwjXNk0HpuE6ErcCqOrluDbnIq++F4lIFfAM8BAwAdfW3S4i0e3P54FrgRpcZ8zkIeuMmGwXAsqAOSJSoqobVHUtgKq+rKovqmq392TgLtyFMdpPVXW3qr4JvAH8WVXXqWoz8D/Ah+PWX6KqAVVdDvw3vXeRol0A3KWq/1DVkKreDwRwF/r+XKeqTaq6Cfd0Y+4Q9sF9qro2qsxrVXWpqnYDv+2jDter6i7vs26kt8O1GPiJqq72tv0xMFdEpkdt+xNv244hlM8YY7LZraq6WVV34X7YRt+ECgNXeNf9DlzH5WpVfU9V64GrcDeDou3RTnghRGcA31fVFq9N+nnctttU9RavzUrkGnsWcK+qvqKqAeD7wGHeE/QeibYtidSrP8uBj4lIEa4T8lPgo95ri7zXUdWdqvqYqraragtuX8e3ydFOADao6n3ePnkVF+FwWtQ6j6vq31Q1rKqdCZbX5BgL0zJZTVXf8UKOrgQOEJGncaFY20RkNm7Q3XygEnc+vxz3Fjui/t3Rx98To/5uVNW2qL83ApP6KNZ04AsicnHUstJ+1u2xPerf7UD1AOvGG6wO8e+1Oerf0XWYDtwkIj+Pet2Hu8O3sY9tjTEmH/R3TQSoj/uRO4ne62Ff6/fXTowDSvrYdnI/5UjEJOCVnj9UtVVEdnrvucFbnGjbMli9+qWqa0WkDdfRORy4Bvh374nQIlzYMCJSCfwCOA6o8zavERG/qob6eOvpwEIRaYpaVowL9ephbVIBsM6IyXqq+hDwkIiMwj39uB53R+cOXKzrmara4nVaTh3GR9WJSFVUQzMN9zQl3mbgWlW9dhif1aMN15HqMbG/FYdgKr0DEafhxtlAb7n7HAfj2SPW2BhjctzUqH9HXxNhz2veNtyP5L6uodB/O9EABL1tV0W9tnWAzxrsettTFgC8sKaxce+ZqMHqNZjluPa1VFW3ishyXJhaHfCat85/AAIsVNXtIjIX10b7vNfj67sZWK6qRw/wudYmFQDrjJis5t15mYwbCNeJexLQk1GjBtgNtHqD4C7EDYAbjqtE5DJcbO8J7DkeA9ygxN+LyFLcYMRKXDztc96j6aF4DbhURKYBzbjH8MP1HRH5B+4O2TdwT48A7gSuEZHXVPVNb7DlMar62xH4TGOMyVZfE5EncE8OLgceGWDdh4EfiMhLuB/CP8QNWo+2RzuhqiER+Q1wrYicixuH8i3ghgE+awcwRURKexKv9FGWh0XkIdz4wB8D/4hLWJKoROo1kOW4uvS0F8u893w+6qlHDa6NbhKRMezZfu7Ajafp8QRwnYicQ+9YmLlAq6quHkLZTI6zMSMm25UB1+HuOm3HDXLr+cH+bdzgthZcB2GgBiYR24FG3N2iB3FZQN6KX0lVV+Cyotzqrf8OLsPVkKnqM7hyv44LMXsimfeJ87j3Xq/h4pn/v/dZv8c9Vfq1iOzG3c07fgQ+zxhjstlDwJ9xA6/X4jIh9udHwArcNXklLkwqev2B2omLcU+71+EGWz+ES3bSn7/inlRsF5GG+BdVdSmwBDeO4l3cAPwzBni/gQxWr8Esx3U2nvP+fgF3I+65qHVuBCpw7fWLuIyV0W4CThWRRhG52bt5dwyuTttw+/Z6XLtvCogvErEnYMb0pGxU1SmZLosxxpiR4aX2/bL3w36473Uk1k4YM+LsyYgxxhhjjDEmI6wzYowxxhhjjMkIC9MyxhhjjDHGZIQ9GTHGGGOMMcZkhHVGjDHGGGOMMRlhnRFjjDHGGGNMRlhnxBhjjDHGGJMR1hkxxhhjjDHGZIR1RowxxhhjjDEZ8X+Uw1YEJmKoMwAAAABJRU5ErkJggg==\n", 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" + ] + }, + "metadata": { + "tags": [], + "needs_background": "light" + } + } + ] + } + ] +} \ No newline at end of file diff --git a/sushmit_02_small_worlds_and_large_worlds_1.ipynb b/sushmit_02_small_worlds_and_large_worlds_1.ipynb new file mode 100644 index 00000000..8c675d4d --- /dev/null +++ b/sushmit_02_small_worlds_and_large_worlds_1.ipynb @@ -0,0 +1,375 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "provenance": [], + "authorship_tag": "ABX9TyPnP75YWyG5BqMWDxpJMezm" + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + }, + "language_info": { + "name": "python" + } + }, + "cells": [ + { + "cell_type": "code", + "execution_count": 40, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "VAf5EBkaSEYy", + "outputId": "80c5a1d1-54f2-4f8d-c0f5-b892451119c6" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Requirement already satisfied: watermark in /usr/local/lib/python3.10/dist-packages (2.4.3)\n", + "Requirement already satisfied: ipython>=6.0 in /usr/local/lib/python3.10/dist-packages (from watermark) (7.34.0)\n", + "Requirement already satisfied: importlib-metadata>=1.4 in /usr/local/lib/python3.10/dist-packages (from watermark) (7.0.0)\n", + "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from watermark) (67.7.2)\n", + "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.10/dist-packages (from importlib-metadata>=1.4->watermark) (3.17.0)\n", + "Requirement already satisfied: jedi>=0.16 in /usr/local/lib/python3.10/dist-packages (from ipython>=6.0->watermark) (0.19.1)\n", + "Requirement already satisfied: decorator in /usr/local/lib/python3.10/dist-packages (from ipython>=6.0->watermark) (4.4.2)\n", + "Requirement already satisfied: pickleshare in /usr/local/lib/python3.10/dist-packages (from ipython>=6.0->watermark) (0.7.5)\n", + "Requirement already satisfied: traitlets>=4.2 in /usr/local/lib/python3.10/dist-packages (from ipython>=6.0->watermark) (5.7.1)\n", + "Requirement already satisfied: prompt-toolkit!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from ipython>=6.0->watermark) (3.0.43)\n", + "Requirement already satisfied: pygments in /usr/local/lib/python3.10/dist-packages (from ipython>=6.0->watermark) (2.16.1)\n", + "Requirement already satisfied: backcall in /usr/local/lib/python3.10/dist-packages (from ipython>=6.0->watermark) (0.2.0)\n", + "Requirement already satisfied: matplotlib-inline in /usr/local/lib/python3.10/dist-packages (from ipython>=6.0->watermark) (0.1.6)\n", + "Requirement already satisfied: pexpect>4.3 in /usr/local/lib/python3.10/dist-packages (from ipython>=6.0->watermark) (4.9.0)\n", + "Requirement already satisfied: parso<0.9.0,>=0.8.3 in /usr/local/lib/python3.10/dist-packages (from jedi>=0.16->ipython>=6.0->watermark) (0.8.3)\n", + "Requirement already satisfied: ptyprocess>=0.5 in /usr/local/lib/python3.10/dist-packages (from pexpect>4.3->ipython>=6.0->watermark) (0.7.0)\n", + "Requirement already satisfied: wcwidth in /usr/local/lib/python3.10/dist-packages (from prompt-toolkit!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0->ipython>=6.0->watermark) (0.2.12)\n", + "Requirement already satisfied: jaxopt in /usr/local/lib/python3.10/dist-packages (0.8.2)\n", + "Requirement already satisfied: jax>=0.2.18 in /usr/local/lib/python3.10/dist-packages (from jaxopt) (0.4.23)\n", + "Requirement already satisfied: jaxlib>=0.1.69 in /usr/local/lib/python3.10/dist-packages (from jaxopt) (0.4.23+cuda12.cudnn89)\n", + "Requirement already satisfied: numpy>=1.18.4 in /usr/local/lib/python3.10/dist-packages (from jaxopt) (1.23.5)\n", + "Requirement already satisfied: scipy>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from jaxopt) (1.11.4)\n", + "Requirement already satisfied: ml-dtypes>=0.2.0 in /usr/local/lib/python3.10/dist-packages (from jax>=0.2.18->jaxopt) (0.2.0)\n", + "Requirement already satisfied: opt-einsum in /usr/local/lib/python3.10/dist-packages (from jax>=0.2.18->jaxopt) (3.3.0)\n" + ] + } + ], + "source": [ + "# Install packages that are not installed in colab\n", + "try:\n", + " import google.colab\n", + " !pip install watermark\n", + " !pip install jaxopt\n", + "except:\n", + " pass" + ] + }, + { + "cell_type": "code", + "source": [ + "%load_ext watermark" + ], + "metadata": { + "id": "Hx65fA0KSZvJ", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "outputId": "e8c0ab87-aff9-40b6-e1dd-2577e5bdd51f" + }, + "execution_count": 41, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "The watermark extension is already loaded. To reload it, use:\n", + " %reload_ext watermark\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import jax\n", + "import jaxopt\n", + "import pandas as pd\n", + "plt.style.use('fivethirtyeight')\n", + "import jax.numpy as jnp\n", + "from tensorflow_probability.substrates import jax as tfp_jax\n", + "import plotly.express as px\n", + "from jax.scipy.optimize import minimize\n", + "tfd_jax = tfp_jax.distributions\n", + "# jax.config.update(\"jax_enable_x64\", True)" + ], + "metadata": { + "id": "1__t38t_SbJk" + }, + "execution_count": 42, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "%watermark -p numpy,tensorflow,tensorflow_probability,scipy,pandas,jax,jaxopt" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "GY8NP1o5YQ4Z", + "outputId": "89f2aa13-0ac3-4615-f1e0-0f605cfaf2f2" + }, + "execution_count": 43, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "numpy : 1.23.5\n", + "tensorflow : 2.15.0\n", + "tensorflow_probability: 0.22.0\n", + "scipy : 1.11.4\n", + "pandas : 1.5.3\n", + "jax : 0.4.23\n", + "jaxopt : 0.8.2\n", + "\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title Calculate the probability of observing 6 W out 9 with 0.5\n", + "W = 6\n", + "L = 3\n", + "tfd_jax.Binomial(total_count = W +L, probs= 0.5).prob(W)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "E1-VWjTefee8", + "outputId": "fe69ec60-762d-47e7-d85d-c82dd66d2dde" + }, + "execution_count": 44, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Array(0.16406271, dtype=float32)" + ] + }, + "metadata": {}, + "execution_count": 44 + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title Grid approximation\n", + "# create a grid\n", + "grid = jnp.linspace(0,1,100)\n", + "# create the prior Uniform distribution\n", + "prior = jnp.ones_like(grid)\n", + "# Likelihood = Binomial\n", + "unstd_post = prior * tfd_jax.Binomial(total_count = W +L,probs=grid).prob(W)\n", + "std_post = unstd_post/unstd_post.sum()\n", + "fig = px.line(x=grid,y=std_post)\n", + "fig.update_layout( autosize=False,\n", + " width=500,\n", + " height=500)\n", + "fig.show()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 517 + }, + "id": "xSkm59yrhIH-", + "outputId": "4f5082f1-c767-471c-d852-eb822192b509" + }, + "execution_count": 45, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "
\n", + "
\n", + "\n", + "" + ] + }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title Quadratic Approximation\n", + "## Approximate using the hessian and normal distb\n", + "## few concepts -- you need BFGS optimizer, grad\n", + "## first we need define the log likehoof\n", + "key = jax.random.PRNGKey(11)\n", + "dist = tfd_jax.JointDistributionNamed(\n", + " {\n", + " \"probability\":tfd_jax.Uniform(low= 0.0, high = 1.0),\n", + " \"water\": lambda probability:tfd_jax.Binomial(total_count = W +L,probs = probability)\n", + " }\n", + ")\n", + "def neg_log_prob(x):\n", + " return tfp_jax.math.value_and_gradient(\n", + " lambda p: -dist.log_prob(\n", + " water=W, probability= jnp.clip(p[-1],0,1)),\n", + " x,\n", + " )\n", + "\n", + "\n", + "optim_results = tfp_jax.optimizer.bfgs_minimize(neg_log_prob,\n", + " initial_position=[0.5],\n", + " tolerance = 1e-6)\n", + "assert(optim_results.converged)\n", + "\n", + "print(optim_results)\n", + "mean = optim_results.position\n", + "std_dev = jnp.sqrt(optim_results.inverse_hessian_estimate)\n", + "quad_approx_dist = tfd_jax.Normal(loc = mean,scale = std_dev)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "bCF30P9cjqg8", + "outputId": "b1121fa6-ebfa-4ec6-b9ac-3d494b2375fe" + }, + "execution_count": 46, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "BfgsOptimizerResults(converged=Array(True, dtype=bool), failed=Array(False, dtype=bool), num_iterations=Array(4, dtype=int32), num_objective_evaluations=Array(13, dtype=int32), position=Array([0.6666667], dtype=float32), objective_value=Array(1.2978106, dtype=float32), objective_gradient=Array([9.536743e-07], dtype=float32), inverse_hessian_estimate=Array([[0.02470744]], dtype=float32))\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "# test_fn = lambda x: -dist.log_prob(water=W, probability= jnp.clip(x,0,1))[0]\n", + "\n", + "# optim_scipy_results = minimize(test_fn,x0 = jnp.array([0.5]),method=\"BFGS\",tol=1e-6)\n", + "# optim_scipy_results" + ], + "metadata": { + "id": "bHDbq5IvCZp6" + }, + "execution_count": 47, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "analytical_solution = tfd_jax.Beta(concentration1 = 1+W, concentration0 = 1+L)\n", + "grid = jnp.linspace(0,1,100)\n", + "df_soln = pd.DataFrame({'x':grid,'analytical_solution':analytical_solution.prob(grid),\n", + " 'quad_approx':quad_approx_dist.prob(grid).reshape(100,)})\n", + "fig = px.line(df_soln, x='x', y=['analytical_solution', 'quad_approx'])\n", + "\n", + "\n", + "fig.update_layout( autosize=False,\n", + " width=500,\n", + " height=500)\n", + "fig.show()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 517 + }, + "id": "eAriwK5x5W4O", + "outputId": "8bc2e36c-65dc-4519-eed3-8c10a3e9a478" + }, + "execution_count": 48, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "
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\n", + "\n", + "" + ] + }, + "metadata": {} + } + ] + } + ] +} \ No newline at end of file diff --git a/sushmit_05_geocentric_models.ipynb b/sushmit_05_geocentric_models.ipynb new file mode 100644 index 00000000..c026ed20 --- /dev/null +++ b/sushmit_05_geocentric_models.ipynb @@ -0,0 +1,7375 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "provenance": [], + "toc_visible": true, + "authorship_tag": "ABX9TyP350hdvp8s6SAVyh8Pgd58", + "include_colab_link": true + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + }, + "language_info": { + "name": "python" + } + }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "view-in-github", + "colab_type": "text" + }, + "source": [ + "\"Open" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "3_nBAHuWmcf5", + "outputId": "96f4887e-8f2a-47e4-8f28-4dbb82580efd" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Requirement already satisfied: watermark in /usr/local/lib/python3.10/dist-packages (2.5.0)\n", + "Requirement already satisfied: ipython>=6.0 in /usr/local/lib/python3.10/dist-packages (from watermark) (7.34.0)\n", + "Requirement already satisfied: importlib-metadata>=1.4 in /usr/local/lib/python3.10/dist-packages (from watermark) (8.4.0)\n", + "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from watermark) (71.0.4)\n", + "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.10/dist-packages (from importlib-metadata>=1.4->watermark) (3.20.2)\n", + "Requirement already satisfied: jedi>=0.16 in /usr/local/lib/python3.10/dist-packages (from ipython>=6.0->watermark) (0.19.1)\n", + "Requirement already satisfied: decorator in /usr/local/lib/python3.10/dist-packages (from ipython>=6.0->watermark) (4.4.2)\n", + 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"import scipy.stats as stats\n", + "import pandas as pd\n", + "# import daft\n", + "import networkx as nx\n", + "import jax\n", + "import jax.numpy as jnp\n", + "from tensorflow_probability.substrates import jax as tfp_jax\n", + "from collections import OrderedDict\n", + "tfd = tfp_jax.distributions\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "plt.style.use('fivethirtyeight')\n", + "import jaxopt\n", + "from jaxopt import ScipyMinimize\n", + "import arviz\n", + "import itertools\n", + "import collections\n", + "import arviz as az\n", + "key = jax.random.PRNGKey(42)\n", + "\n", + "def marginal_test_results(model, results, nll,credib_interval = 0.89, num_of_samples = 10000):\n", + " '''\n", + " model: tfp model like\n", + " results: results from optimizing\n", + " nll: negative log likelihood function\n", + " credib_interval: the interval we are interested in\n", + " num_of_samples: number of samples we want to get from the posterior distribution\n", + " '''\n", + " key = jax.random.PRNGKey(42)\n", + " inv_hessian_matrix = jnp.linalg.inv(jax.hessian(nll)(results.params))\n", + " mean_list = results.params\n", + " sd_list = jnp.diagonal(inv_hessian_matrix)**(1/2)\n", + " low_credib_interval = (1 - credib_interval)/2\n", + " high_credib_interval = 1 - low_credib_interval\n", + " parameter_list = []\n", + " normal_dist = tfp_jax.distributions.Normal(loc=mean_list,scale = sd_list)\n", + " for _parameter in model.parameters['model']:\n", + " if isinstance(model.parameters['model'][_parameter],tfp_jax.distributions.Distribution):\n", + " try:\n", + " _shape = model.parameters['model'][_parameter].event_shape[0]\n", + " parameter_list.extend([_parameter + '_' +str(i) for i in range(0, _shape)])\n", + " except:\n", + " parameter_list.append(_parameter)\n", + "\n", + " df_result = pd.DataFrame({'mean': mean_list,\n", + " 'sd':sd_list,\n", + " 'low': normal_dist.quantile(low_credib_interval),\n", + " 'high':tfp_jax.distributions.Normal(loc=mean_list,scale = sd_list).quantile(high_credib_interval) },\n", + " index = parameter_list)\n", + " post_dist = tfp_jax.distributions.MultivariateNormalFullCovariance(\n", + " loc=results.params,covariance_matrix=inv_hessian_matrix )\n", + " post_samples = post_dist.sample( sample_shape=num_of_samples,seed=key)\n", + " df_post_samples = pd.DataFrame(post_samples,columns = parameter_list)\n", + " return df_result,inv_hessian_matrix,df_post_samples\n", + "credib_interval = 0.89" + ], + "metadata": { + "id": "WQDu_GQ4rb3N" + }, + "execution_count": 2, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.1\n", + "d = pd.read_csv('https://raw.githubusercontent.com/sushmit86/Statiistical_rethinking_jax/main/WaffleDivorce.csv',sep= ';')\n", + "d['A'] = (d.MedianAgeMarriage - d.MedianAgeMarriage.mean())/d.MedianAgeMarriage.std()\n", + "d['D'] = (d.Divorce - d.Divorce.mean())/d.Divorce.std()\n", + "d.head()\n", + "A_arr = jnp.array(d.A)\n", + "D_arr = jnp.array(d.D)" + ], + "metadata": { + "id": "xxjhEIn1LzxX" + }, + "execution_count": 3, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.2\n", + "d.MedianAgeMarriage.std()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "hLvp57P_Uejd", + "outputId": "2a57d658-1da8-4cc8-d628-bf2735f77a46" + }, + "execution_count": 4, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "1.243630301388082" + ] + }, + "metadata": {}, + "execution_count": 4 + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.3\n", + "model5_1 = tfd.JointDistributionNamedAutoBatched(OrderedDict(\n", + " alpha = tfd.Normal(loc=0.0,scale=0.2),\n", + " bA = tfd.Normal(loc=0,scale=0.5),\n", + " sigma = tfd.Exponential(rate = 1.0),\n", + " mu = lambda alpha,bA,sigma: tfd.Deterministic(alpha + bA * A_arr),\n", + " D = lambda mu,sigma: tfd.Sample(tfd.Normal(loc=mu,scale=sigma))\n", + "))\n", + "def nll5_1(parameters):\n", + " samples = model5_1.sample(\n", + " D = D_arr,\n", + " alpha = parameters[0],\n", + " bA = parameters[1],\n", + " sigma = parameters[2],\n", + " seed = jax.random.PRNGKey(42))\n", + " return -1* model5_1.log_prob(samples)\n", + "\n", + "x_arr =jnp.array([-2,2])" + ], + "metadata": { + "id": "snwrwQlBbmrb" + }, + "execution_count": 5, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.4\n", + "prior_samples =model5_1.sample(sample_shape= 50,seed = jax.random.PRNGKey(42))\n", + "fig, ax = plt.subplots(1,1,figsize=(10,4))\n", + "for _alpha,_bA in zip(prior_samples['alpha'],prior_samples['bA']):\n", + " y_arr = _alpha + _bA * x_arr\n", + " ax.plot(x_arr,y_arr,color = 'lightblue',linewidth=1)\n", + "ax.set_xlabel('Median age Marriage (std)')\n", + "ax.set_ylabel('Divorce rate(std)')\n", + "fig.show()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 413 + }, + "id": "jm8kUik65YRR", + "outputId": "44151449-a0f2-4f36-91c2-120f48de8a33" + }, + "execution_count": 6, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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\n" + ], + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "dataframe", + "summary": "{\n \"name\": \"df_result\",\n \"rows\": 3,\n \"fields\": [\n {\n \"column\": \"mean\",\n \"properties\": {\n \"dtype\": \"float32\",\n \"num_unique_values\": 3,\n \"samples\": [\n 0.0,\n -0.5680000185966492,\n 0.7879999876022339\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"sd\",\n \"properties\": {\n \"dtype\": \"float32\",\n \"num_unique_values\": 3,\n \"samples\": [\n 0.09700000286102295,\n 0.10999999940395355,\n 0.07800000160932541\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"low\",\n \"properties\": {\n \"dtype\": \"float32\",\n \"num_unique_values\": 3,\n \"samples\": [\n -0.15600000321865082,\n -0.7440000176429749,\n 0.6639999747276306\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"high\",\n \"properties\": {\n \"dtype\": \"float32\",\n \"num_unique_values\": 3,\n \"samples\": [\n 0.15600000321865082,\n -0.3930000066757202,\n 0.9129999876022339\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" + } + }, + "metadata": {}, + "execution_count": 7 + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.5\n", + "A_seq = np.linspace(-3,3.2,30)\n", + "get_mu_lower = lambda _A: arviz.hdi(np.array(df_post_samples_m_5_1.alpha + df_post_samples_m_5_1.bA * _A),hdi_prob = credib_interval)[0]\n", + "get_mu_upper = lambda _A: arviz.hdi(np.array(df_post_samples_m_5_1.alpha + df_post_samples_m_5_1.bA * _A),hdi_prob = credib_interval)[1]\n", + "vfunc_lower = np.vectorize(get_mu_lower)\n", + "vfunc_upper = np.vectorize(get_mu_upper)\n", + "mu_lower=vfunc_lower(A_seq)\n", + "mu_upper=vfunc_upper(A_seq)\n", + "mean_mu_pred = df_result.loc['alpha','mean'] + df_result.loc['bA','mean'] * A_seq\n", + "\n", + "fig, axs = plt.subplots(1, 1, figsize=(8, 4))\n", + "axs.scatter(d.A,d.D,alpha=0.6,s=20)\n", + "axs.plot(A_seq, mean_mu_pred,linewidth=1.0)\n", + "axs.fill_between(A_seq, mu_lower,mu_upper, alpha=0.2)\n", + "axs.set_xlabel('Median age Marriage (std)')\n", + "axs.set_ylabel('Divorce rate(std)')\n", + "fig.show()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 413 + }, + "id": "75r29GIGxOUo", + "outputId": "dda5b31e-b58a-4e9c-fcf5-1feb60445a1e" + }, + "execution_count": 8, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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+ }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "# @title 5.6\n", + "d['M'] = (d.Marriage - d.Marriage.mean())/d.Marriage.std()\n", + "M_arr = jnp.array(d.M)\n", + "model5_2 = tfd.JointDistributionNamedAutoBatched(OrderedDict(\n", + " alpha = tfd.Normal(loc=0.0,scale=0.2),\n", + " bM = tfd.Normal(loc=0,scale=0.5),\n", + " sigma = tfd.Exponential(rate = 1.0),\n", + " mu = lambda alpha,bM,sigma: tfd.Deterministic(alpha + bM * M_arr),\n", + " D = lambda mu,sigma: tfd.Sample(tfd.Normal(loc=mu,scale=sigma))\n", + " ))\n", + "def nll5_2(parameters):\n", + " samples = model5_2.sample(\n", + " D = D_arr,\n", + " alpha = parameters[0],\n", + " bM = parameters[1],\n", + " sigma = parameters[2],\n", + " seed = jax.random.PRNGKey(42))\n", + " return -1* model5_2.log_prob(samples)" + ], + "metadata": { + "id": "WGZ4rEAzfZgm" + }, + "execution_count": 9, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "optimize_fn = ScipyMinimize(fun= nll5_2,method = 'L-BFGS-B' )\n", + "alpha_start = model5_2.parameters['model']['alpha'].mean()\n", + "bM_start = model5_2.parameters['model']['bM'].mean()\n", + "sigma_start = model5_2.parameters['model']['sigma'].mean()\n", + "results = optimize_fn.run(init_params=jnp.array([alpha_start,bM_start,sigma_start]))\n", + "df_result,cov_matrix,df_post_samples_m_5_2 = marginal_test_results(model5_2,results,nll5_2)\n", + "df_result.round(3)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 143 + }, + "id": "lp2Uz8ualbEt", + "outputId": "347d2d43-6b0d-4223-b434-dccc92158225" + }, + "execution_count": 10, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + " mean sd low high\n", + "alpha 0.00 0.108 -0.173 0.173\n", + "bM 0.35 0.126 0.149 0.551\n", + "sigma 0.91 0.090 0.767 1.054" + ], + "text/html": [ + "\n", + "
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\n" + ], + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "dataframe", + "summary": "{\n \"name\": \"df_result\",\n \"rows\": 3,\n \"fields\": [\n {\n \"column\": \"mean\",\n \"properties\": {\n \"dtype\": \"float32\",\n \"num_unique_values\": 3,\n \"samples\": [\n 0.0,\n 0.3499999940395355,\n 0.9100000262260437\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"sd\",\n \"properties\": {\n \"dtype\": \"float32\",\n \"num_unique_values\": 3,\n \"samples\": [\n 0.1080000028014183,\n 0.12600000202655792,\n 0.09000000357627869\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"low\",\n \"properties\": {\n \"dtype\": \"float32\",\n \"num_unique_values\": 3,\n \"samples\": [\n -0.17299999296665192,\n 0.14900000393390656,\n 0.7670000195503235\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"high\",\n \"properties\": {\n \"dtype\": \"float32\",\n \"num_unique_values\": 3,\n \"samples\": [\n 0.17299999296665192,\n 0.5509999990463257,\n 1.0540000200271606\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" + } + }, + "metadata": {}, + "execution_count": 10 + } + ] + }, + { + "cell_type": "code", + "source": [ + "M_seq = np.linspace(-2,3.2,30)\n", + "get_mu_lower = lambda _M: arviz.hdi(np.array(df_post_samples_m_5_2.alpha + df_post_samples_m_5_2.bM * _M),hdi_prob = credib_interval)[0]\n", + "get_mu_upper = lambda _M: arviz.hdi(np.array(df_post_samples_m_5_2.alpha + df_post_samples_m_5_2.bM * _M),hdi_prob = credib_interval)[1]\n", + "vfunc_lower = np.vectorize(get_mu_lower)\n", + "vfunc_upper = np.vectorize(get_mu_upper)\n", + "mu_lower=vfunc_lower(M_seq)\n", + "mu_upper=vfunc_upper(M_seq)\n", + "mean_mu_pred = df_result.loc['alpha','mean'] + df_result.loc['bM','mean'] * M_seq\n", + "\n", + "fig, axs = plt.subplots(1, 1, figsize=(8, 4))\n", + "axs.scatter(d.M,d.D,alpha=0.6,s=20)\n", + "axs.plot(M_seq, mean_mu_pred,linewidth=1.0)\n", + "axs.fill_between(M_seq, mu_lower,mu_upper, alpha=0.2)\n", + "axs.set_xlabel('Marriage rate (std)')\n", + "axs.set_ylabel('Divorce rate(std)')\n", + "fig.show()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 413 + }, + "id": "EmcLuVgjrRpq", + "outputId": "67877bc8-1604-45cf-b14f-23e438fe9fb1" + }, + "execution_count": 11, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.7\n", + "dag5_1 = nx.DiGraph()\n", + "dag5_1.add_edges_from([(\"A\", \"D\"), (\"A\", \"M\"), (\"M\", \"D\")])\n", + "coordinates = {\"A\": (0, 0), \"D\": (1, 1), \"M\": (2, 0)}\n", + "fig,axs = plt.subplots(1,1,figsize=(6,3))\n", + "options = {\n", + " \"font_size\": 20,\n", + " \"node_size\": 1000,\n", + " \"node_color\": \"white\",\n", + " \"edgecolors\": \"black\",\n", + " \"linewidths\": 5,\n", + " \"width\": 5,\n", + "}\n", + "nx.draw_networkx(dag5_1,coordinates, arrows=True,ax=axs,**options)\n", + "plt.gca().invert_yaxis()\n", + "axs.margins(0.20)\n", + "plt.axis(\"off\")\n", + "plt.show()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 280 + }, + "id": "Q9EGq7Di9UFQ", + "outputId": "8dc09fe4-5f50-411a-cdea-cc122bbb74d3" + }, + "execution_count": 12, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.8\n", + "DMA_dag2 = nx.DiGraph()\n", + "DMA_dag2.add_edges_from([(\"A\", \"D\"), (\"A\", \"M\")])\n", + "conditional_independencies = collections.defaultdict(list)\n", + "for edge in itertools.combinations(sorted(DMA_dag2.nodes), 2):\n", + " remaining = sorted(set(DMA_dag2.nodes) - set(edge))\n", + " for size in range(len(remaining) + 1):\n", + " for subset in itertools.combinations(remaining, size):\n", + " if any(cond.issubset(set(subset)) for cond in conditional_independencies[edge]):\n", + " continue\n", + " if nx.is_d_separator(DMA_dag2, {edge[0]}, {edge[1]}, set(subset)):\n", + " conditional_independencies[edge].append(set(subset))\n", + " print(f\"{edge[0]} _||_ {edge[1]}\" + (f\" | {' '.join(subset)}\" if subset else \"\"))\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "WYz-F9Ij9eAB", + "outputId": "d4cb3b88-7a69-4e44-e756-25d8d90d11c6" + }, + "execution_count": 13, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "D _||_ M | A\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.9\n", + "DMA_dag1 = nx.DiGraph()\n", + "DMA_dag1.add_edges_from([(\"A\", \"D\"), (\"A\", \"M\"), (\"M\", \"D\")])\n", + "conditional_independencies = collections.defaultdict(list)\n", + "for edge in itertools.combinations(sorted(DMA_dag1.nodes), 2):\n", + " remaining = sorted(set(DMA_dag1.nodes) - set(edge))\n", + " for size in range(len(remaining) + 1):\n", + " for subset in itertools.combinations(remaining, size):\n", + " if any(cond.issubset(set(subset)) for cond in conditional_independencies[edge]):\n", + " continue\n", + " if nx.d_separated(DMA_dag1, {edge[0]}, {edge[1]}, set(subset)):\n", + " conditional_independencies[edge].append(set(subset))\n", + " print(f\"{edge[0]} _||_ {edge[1]}\" + (f\" | {' '.join(subset)}\" if subset else \"\"))" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "FEgA62_s-eCu", + "outputId": "c89c89aa-ab09-4735-de60-3b1f7a578293" + }, + "execution_count": 14, + "outputs": [ + { + "output_type": "stream", + "name": "stderr", + "text": [ + ":11: DeprecationWarning: d_separated is deprecated and will be removed in NetworkX v3.5.Please use `is_d_separator(G, x, y, z)`.\n", + " if nx.d_separated(DMA_dag1, {edge[0]}, {edge[1]}, set(subset)):\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.10\n", + "model5_3 = tfd.JointDistributionNamedAutoBatched(OrderedDict(\n", + " alpha = tfd.Normal(loc=0.0,scale=0.2),\n", + " bA = tfd.Normal(loc=0,scale=0.5),\n", + " bM = tfd.Normal(loc=0,scale=0.5),\n", + " sigma = tfd.Exponential(rate = 1.0),\n", + " mu = lambda alpha,bA,bM: tfd.Deterministic(alpha + bM * M_arr + bA * A_arr),\n", + " D = lambda mu,sigma: tfd.Normal(mu,sigma)\n", + "))\n", + "def nll5_3(parameters):\n", + " samples = model5_3.sample(\n", + " D = D_arr,\n", + " alpha = parameters[0],\n", + " bA = parameters[1],\n", + " bM = parameters[2],\n", + " sigma = parameters[3],\n", + " seed = jax.random.PRNGKey(42))\n", + " return -1* model5_3.log_prob(samples)\n", + "\n", + "optimize_fn = ScipyMinimize(fun= nll5_3,method = 'L-BFGS-B' )\n", + "alpha_start = model5_3.parameters['model']['alpha'].mean()\n", + "bA_start = model5_3.parameters['model']['bA'].mean()\n", + "bM_start = model5_3.parameters['model']['bM'].mean()\n", + "sigma_start = model5_3.parameters['model']['sigma'].mean()\n", + "\n", + "results = optimize_fn.run(init_params=jnp.array([alpha_start,bA_start,bM_start,sigma_start]))\n", + "df_result,cov_matrix,df_post_samples_m_5_3 = marginal_test_results(model5_3,results,nll5_3)\n", + "df_result.round(3)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 175 + }, + "id": "TqTwREAykaf_", + "outputId": "c7ba801e-6d93-4835-d49b-3b16f3da6487" + }, + "execution_count": 15, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + " mean sd low high\n", + "alpha 0.000 0.097 -0.155 0.155\n", + "bA -0.613 0.151 -0.855 -0.372\n", + "bM -0.065 0.151 -0.306 0.176\n", + "sigma 0.785 0.078 0.661 0.910" + ], + "text/html": [ + "\n", + "
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meansdlowhigh
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\n" + ], + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "dataframe", + "summary": "{\n \"name\": \"df_result\",\n \"rows\": 4,\n \"fields\": [\n {\n \"column\": \"mean\",\n \"properties\": {\n \"dtype\": \"float32\",\n \"num_unique_values\": 4,\n \"samples\": [\n -0.6129999756813049,\n 0.7850000262260437,\n 0.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"sd\",\n \"properties\": {\n \"dtype\": \"float32\",\n \"num_unique_values\": 3,\n \"samples\": [\n 0.09700000286102295,\n 0.1509999930858612,\n 0.07800000160932541\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"low\",\n \"properties\": {\n \"dtype\": \"float32\",\n \"num_unique_values\": 4,\n \"samples\": [\n -0.8550000190734863,\n 0.6610000133514404,\n -0.1550000011920929\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"high\",\n \"properties\": {\n \"dtype\": \"float32\",\n \"num_unique_values\": 4,\n \"samples\": [\n -0.3720000088214874,\n 0.9100000262260437,\n 0.1550000011920929\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" + } + }, + "metadata": {}, + "execution_count": 15 + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.11\n", + "fig,ax = plt.subplots(1,1,figsize=(12,8))\n", + "az.plot_forest(\n", + "data = [{\"bA\":df_post_samples_m_5_1['bA'].values},{\"bM\":df_post_samples_m_5_2['bM'].values},\n", + " {\"bA\": df_post_samples_m_5_3['bA'], \"bM\":df_post_samples_m_5_3['bM'].values }],\n", + "hdi_prob=0.89,\n", + "model_names=[\"m5.1\",\"m5.2\",\"m5.3\"],\n", + "ax=ax,\n", + ")\n", + "ax.set_title('Estimate')\n", + "plt.show()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 739 + }, + "id": "ixMx0uPiHhMP", + "outputId": "0976de2a-c961-4c51-c595-2a5e4d65f66a" + }, + "execution_count": 16, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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+ }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.12 [complete the simulation]\n", + "age = stats.norm.rvs(size= 100)\n", + "marriage = stats.norm.rvs(loc = -age)\n", + "div = stats.norm.rvs(loc= age)" + ], + "metadata": { + "id": "xcTh9q05h5gu" + }, + "execution_count": 17, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.13\n", + "model5_4 = tfd.JointDistributionNamedAutoBatched(OrderedDict(\n", + " alpha = tfd.Normal(loc=0.0,scale=0.2),\n", + " beta = tfd.Normal(loc=0,scale=0.5),\n", + " sigma = tfd.Exponential(rate = 1.0),\n", + " mu = lambda alpha,beta: tfd.Deterministic(alpha + beta * A_arr),\n", + " M = lambda mu,sigma: tfd.Sample(tfd.Normal(loc=mu,scale=sigma))\n", + "))\n", + "def nll5_4(parameters):\n", + " samples = model5_4.sample(\n", + " M = M_arr,\n", + " alpha = parameters[0],\n", + " beta = parameters[1],\n", + " sigma = parameters[2],\n", + " seed = jax.random.PRNGKey(42))\n", + " return -1* model5_4.log_prob(samples)\n", + "\n", + "optimize_fn = ScipyMinimize(fun= nll5_4,method = 'L-BFGS-B' )\n", + "alpha_start = model5_4.parameters['model']['alpha'].mean()\n", + "beta_start = model5_4.parameters['model']['beta'].mean()\n", + "sigma_start = model5_4.parameters['model']['sigma'].mean()\n", + "results = optimize_fn.run(init_params=jnp.array([alpha_start,beta_start,sigma_start]))\n", + "df_result,cov_matrix,df_post_samples_m_5_4 = marginal_test_results(model5_4,results,nll5_4)\n", + "df_result.round(3)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 143 + }, + "id": "FAcsnuY2ueRD", + "outputId": "49bd7a06-d26e-4a0c-fbca-07dd764f6c4b" + }, + "execution_count": 18, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + " mean sd low high\n", + "alpha -0.000 0.087 -0.139 0.139\n", + "beta -0.695 0.096 -0.848 -0.542\n", + "sigma 0.682 0.068 0.574 0.790" + ], + 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+ }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.23\n", + "A_seq = (np.array([20,30]) - 26.1)/1.24\n", + "fn_mu_M_5_3A = lambda _samples,_A,: _samples[:,0] + _samples[:,1] * _A\n", + "sampled_mu_M = jax.vmap(fn_mu_M_5_3A,in_axes=(None,0),out_axes=1)(post_samples_m_5_3_array,A_seq)\n", + "fn_sample_M = lambda _mu_M,_sigma_M: tfd.Normal(loc=_mu_M,scale=_sigma_M).sample(seed = key)\n", + "M_sim = jax.vmap(fn_sample_M,in_axes=(1,None),out_axes=1)(sampled_mu_M,post_samples_m_5_3_array[:,2])\n", + "M_mean = jnp.mean( M_sim, axis =0)\n", + "\n", + "fn_mu_D_5_3A = lambda _samples,_A,_M: _samples[:,3] + _samples[:,4] * _A + _samples[:,5] * _M\n", + "sampled_mu_D = jax.vmap(fn_mu_D_5_3A,in_axes=(None,0,0),out_axes=1)(post_samples_m_5_3_array,A_seq,M_mean)\n", + "fn_sample_D = lambda _mu_D,_sigma_D: tfd.Normal(loc=_mu_D,scale=_sigma_D).sample(seed = key)\n", + "D_sim = jax.vmap(fn_sample_D,in_axes=(1,None),out_axes=1)(sampled_mu_D,post_samples_m_5_3_array[:,6])\n", + "D_PI = np.apply_along_axis(arviz.hdi, axis=0, arr=np.array(D_sim),hdi_prob=credib_interval).T\n", + "D_mean = jnp.mean( D_sim, axis =0)\n", + "D_mean[1] - D_mean[0]" + ], + "metadata": { + "id": "89c6MZOOQEKz", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "outputId": "589adaae-24e0-4b66-9a71-e827c844d1e0" + }, + "execution_count": 29, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Array(-4.609355, dtype=float32)" + ] + }, + "metadata": {}, + "execution_count": 29 + } + ] + }, + { + "cell_type": "code", + "source": [ + "M_seq = np.linspace(-2,2,30)\n", + "A_seq = np.zeros_like(M_seq)\n", + "A_seq" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "JDZoP7v17GgL", + "outputId": "c8126633-086a-40f2-f5dc-e771a0b97434" + }, + "execution_count": 30, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])" + ] + }, + "metadata": {}, + "execution_count": 30 + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.24\n", + "M_seq = np.linspace(-2,2,30)\n", + "A_seq = np.zeros_like(M_seq)\n", + "sim_data = pd.DataFrame({'M':M_seq,'A':A_seq})\n", + "\n", + "fn_mu_D_5_3A = lambda _samples,_A,_M: _samples[:,3] + _samples[:,4] * _A + _samples[:,5] * _M\n", + "sampled_mu_D = jax.vmap(fn_mu_D_5_3A,in_axes=(None,0,0),out_axes=1)(post_samples_m_5_3_array,A_seq,M_seq)\n", + "\n", + "fn_sample_D = lambda _mu_D,_sigma_D: tfd.Normal(loc=_mu_D,scale=_sigma_D).sample(seed = key)\n", + "D_sim = jax.vmap(fn_sample_D,in_axes=(1,None),out_axes=1)(sampled_mu_D,post_samples_m_5_3_array[:,6])\n", + "D_PI = np.apply_along_axis(arviz.hdi, axis=0, arr=np.array(D_sim),hdi_prob=credib_interval).T\n", + "D_mean = jnp.mean( D_sim, axis =0)\n", + "\n", + "fig,axs = plt.subplots(1,1,figsize=(8,4))\n", + "axs.plot(M_seq,D_mean,linewidth=1.0)\n", + "axs.fill_between(M_seq, D_PI[:,0],D_PI[:,1], alpha=0.2)\n", + "plt.show()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 384 + }, + "id": "sI9NZ59V-HTw", + "outputId": "800fb01f-9f78-443c-c5e4-f2a98dca573c" + }, + "execution_count": 31, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.25\n", + "A_seq = np.linspace(-2,2,30)" + ], + "metadata": { + "id": "WT8-lXDnKpSt" + }, + "execution_count": 32, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.26 and 5.27\n", + "df_result_m5_3A,cov_matrix_m5_3A,df_post_samples_m_5_3A = marginal_test_results(\n", + " model =model_5_3A,results=results_m5_3A,nll=nll_5_3A,credib_interval=0.89)\n", + "post_samples_m_5_3_array = df_post_samples_m_5_3A.to_numpy()\n", + "fn_mu_M_5_3A = lambda _samples,_A,: _samples[:,0] + _samples[:,1] * _A\n", + "sampled_mu_M = jax.vmap(fn_mu_M_5_3A,in_axes=(None,0),out_axes=1)(post_samples_m_5_3_array,A_seq)\n", + "fn_sample_M = lambda _mu_M,_sigma_M: tfd.Normal(loc=_mu_M,scale=_sigma_M).sample(seed = key)\n", + "M_sim = jax.vmap(fn_sample_M,in_axes=(1,None),out_axes=1)(sampled_mu_M,post_samples_m_5_3_array[:,2])\n", + "M_mean = jnp.mean( M_sim, axis =0)\n", + "M_PI = np.apply_along_axis(arviz.hdi, axis=0, arr=np.array(M_sim),hdi_prob=credib_interval).T\n", + "fn_mu_D_5_3A = lambda _samples,_A,_M: _samples[:,3] + _samples[:,4] * _A + _samples[:,5] * _M\n", + "sampled_mu_D = jax.vmap(fn_mu_D_5_3A,in_axes=(None,0,0),out_axes=1)(post_samples_m_5_3_array,A_seq,M_mean)\n", + "fn_sample_D = lambda _mu_D,_sigma_D: tfd.Normal(loc=_mu_D,scale=_sigma_D).sample(seed = key)\n", + "D_sim = jax.vmap(fn_sample_D,in_axes=(1,None),out_axes=1)(sampled_mu_D,post_samples_m_5_3_array[:,6])\n", + "D_PI = np.apply_along_axis(arviz.hdi, axis=0, arr=np.array(D_sim),hdi_prob=credib_interval).T\n", + "D_mean = jnp.mean( D_sim, axis =0)" + ], + "metadata": { + "id": "qkdCXWlySIZA" + }, + "execution_count": 33, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.27\n", + "milk = pd.read_csv('https://raw.githubusercontent.com/sushmit86/Statiistical_rethinking_jax/main/milk.csv',sep= ';')\n", + "d = milk.copy()\n", + "display(d.info())\n", + "d.head()" + ], + "metadata": { + "id": "ybt0Of4oU_wp", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 484 + }, + "outputId": "92e4f0a2-8a6d-4637-91e8-e3d790e332fb" + }, + "execution_count": 34, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "\n", + "RangeIndex: 29 entries, 0 to 28\n", + "Data columns (total 8 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 clade 29 non-null object \n", + " 1 species 29 non-null object \n", + " 2 kcal.per.g 29 non-null float64\n", + " 3 perc.fat 29 non-null float64\n", + " 4 perc.protein 29 non-null float64\n", + " 5 perc.lactose 29 non-null float64\n", + " 6 mass 29 non-null float64\n", + " 7 neocortex.perc 17 non-null float64\n", + "dtypes: float64(6), object(2)\n", + "memory usage: 1.9+ KB\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "None" + ] + }, + "metadata": {} + }, + { + "output_type": "execute_result", + "data": { + "text/plain": [ + " clade species kcal.per.g perc.fat perc.protein \\\n", + "0 Strepsirrhine Eulemur fulvus 0.49 16.60 15.42 \n", + "1 Strepsirrhine E macaco 0.51 19.27 16.91 \n", + "2 Strepsirrhine E mongoz 0.46 14.11 16.85 \n", + "3 Strepsirrhine E rubriventer 0.48 14.91 13.18 \n", + "4 Strepsirrhine Lemur catta 0.60 27.28 19.50 \n", + "\n", + " perc.lactose mass neocortex.perc \n", + "0 67.98 1.95 55.16 \n", + "1 63.82 2.09 NaN \n", + "2 69.04 2.51 NaN \n", + "3 71.91 1.62 NaN \n", + "4 53.22 2.19 NaN " + ], + "text/html": [ + "\n", + "
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cladespecieskcal.per.gperc.fatperc.proteinperc.lactosemassneocortex.perc
0StrepsirrhineEulemur fulvus0.4916.6015.4267.981.9555.16
1StrepsirrhineE macaco0.5119.2716.9163.822.09NaN
2StrepsirrhineE mongoz0.4614.1116.8569.042.51NaN
3StrepsirrhineE rubriventer0.4814.9113.1871.911.62NaN
4StrepsirrhineLemur catta0.6027.2819.5053.222.19NaN
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x.mean())/x.std())\n", + "d[\"N\"] = d['neocortex.perc'].pipe(lambda x: (x - x.mean())/x.std())\n", + "d[\"M\"] = np.log(d['mass']).pipe(lambda x: (x - x.mean())/x.std())" + ], + "metadata": { + "id": "GHNLLrao8qvx" + }, + "execution_count": 35, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.30/5.31\n", + "dcc = d.dropna()\n", + "K_arr = jnp.array(dcc.K)\n", + "N_arr = jnp.array(dcc.N)\n", + "M_arr = jnp.array(dcc.M)\n", + "dcc.info()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "9E5yJZuYD6WE", + "outputId": "ffdb09c9-2a65-4803-cb4d-81429ad59501" + }, + "execution_count": 36, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "\n", + "Index: 17 entries, 0 to 28\n", + "Data columns (total 11 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 clade 17 non-null object \n", + " 1 species 17 non-null object \n", + " 2 kcal.per.g 17 non-null float64\n", + " 3 perc.fat 17 non-null float64\n", + " 4 perc.protein 17 non-null float64\n", + " 5 perc.lactose 17 non-null float64\n", + " 6 mass 17 non-null float64\n", + " 7 neocortex.perc 17 non-null float64\n", + " 8 K 17 non-null float64\n", + " 9 N 17 non-null float64\n", + " 10 M 17 non-null float64\n", + "dtypes: float64(9), object(2)\n", + "memory usage: 1.6+ KB\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.32\n", + "model5_5_draft = tfd.JointDistributionNamedAutoBatched(OrderedDict(\n", + " a = tfd.Normal(loc=0.0,scale=1),\n", + " bN = tfd.Normal(loc= 0.0, scale =1),\n", + " sigma = tfd.Exponential(rate = 1.0),\n", + " mu = lambda a,bN : tfd.Deterministic(a + bN * N_arr),\n", + " K = lambda mu,sigma: tfd.Sample(tfd.Normal(loc=mu,scale=sigma))\n", + "))\n", + "x_seq = jnp.array([-2,2])\n", + "prior_samples =model5_5_draft.sample(sample_shape= 50,seed = jax.random.PRNGKey(42))" + ], + "metadata": { + "id": "8kV9fKQRBDSx" + }, + "execution_count": 37, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.33\n", + "fig,axs = plt.subplots(1,1,figsize=(8,4))\n", + "for _i in range(prior_samples['a'].shape[0]):\n", + " y_seq = prior_samples['a'][_i] + prior_samples['bN'][_i] * x_seq\n", + " axs.plot(x_seq,y_seq,linewidth=1.0)\n", + "axs.set_xlabel('neocortex percent(std)')\n", + "axs.set_ylabel('kcal per gram(std)')\n", + "fig.show()\n", + "plt.show()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 413 + }, + "id": "uu31dtIOLi1z", + "outputId": "26258ca3-511c-41f9-fa57-5be912de1609" + }, + "execution_count": 38, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.34\n", + "model5_5 = tfd.JointDistributionNamedAutoBatched(OrderedDict(\n", + " a = tfd.Normal(loc=0.0,scale=0.2),\n", + " bN = tfd.Normal(loc= 0.0, scale =0.5),\n", + " sigma = tfd.Exponential(rate = 1.0),\n", + " mu = lambda a,bN : tfd.Deterministic(a + bN * N_arr),\n", + " K = lambda mu,sigma: tfd.Sample(tfd.Normal(loc=mu,scale=sigma))\n", + "))\n", + "x_seq = jnp.array([-2,2])\n", + "prior_samples = model5_5.sample(sample_shape= 50,seed = jax.random.PRNGKey(42))\n", + "fig,axs = plt.subplots(1,1,figsize=(8,4))\n", + "for _i in range(prior_samples['a'].shape[0]):\n", + " y_seq = prior_samples['a'][_i] + prior_samples['bN'][_i] * x_seq\n", + " axs.plot(x_seq,y_seq,linewidth=1.0)\n", + "axs.set_xlabel('neocortex percent(std)')\n", + "axs.set_ylabel('kcal per gram(std)')\n", + "fig.show()\n", + "plt.show()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 413 + }, + "id": "PVUc-X_0NoLn", + "outputId": "88d7473e-fec9-4849-8f81-de9dfeb07dd5" + }, + "execution_count": 39, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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+ }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.35\n", + "def nll5_5(parameters):\n", + " samples = model5_5.sample(\n", + " K = K_arr,\n", + " a = parameters[0],\n", + " bN = parameters[1],\n", + " sigma = parameters[2],\n", + " seed = jax.random.PRNGKey(42))\n", + " return -1* model5_5.log_prob(samples)\n", + "\n", + "optimize_fn = ScipyMinimize(fun= nll5_5,method = 'L-BFGS-B' )\n", + "a_start = model5_5.parameters['model']['a'].mean()\n", + "bN_start = model5_5.parameters['model']['bN'].mean()\n", + "sigma_start = model5_5.parameters['model']['sigma'].mean()\n", + "results_m5_5 = optimize_fn.run(init_params=jnp.array([a_start,bN_start,sigma_start]))\n", + "\n", + "df_result_m5_5,cov_matrix_m5_5,df_post_samples_m_5_5 = marginal_test_results(\n", + " model =model5_5,results=results_m5_5,nll=nll5_5,credib_interval=0.89)\n", + "df_result_m5_5.round(3)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 143 + }, + "id": "9Xh06IlRUql4", + "outputId": "c4a214a1-d206-4562-d542-d17d910acafd" + }, + "execution_count": 40, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + " mean sd low high\n", + "a 0.040 0.154 -0.207 0.287\n", + "bN 0.133 0.224 -0.224 0.491\n", + "sigma 1.000 0.165 0.737 1.263" + ], + "text/html": [ + "\n", + "
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meansdlowhigh
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bN0.1330.224-0.2240.491
sigma1.0000.1650.7371.263
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\n" + ], + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "dataframe", + "summary": "{\n \"name\": \"df_result_m5_5\",\n \"rows\": 3,\n \"fields\": [\n {\n \"column\": \"mean\",\n \"properties\": {\n \"dtype\": \"float32\",\n \"num_unique_values\": 3,\n \"samples\": [\n 0.03999999910593033,\n 0.13300000131130219,\n 1.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"sd\",\n \"properties\": {\n \"dtype\": \"float32\",\n \"num_unique_values\": 3,\n \"samples\": [\n 0.15399999916553497,\n 0.2240000069141388,\n 0.16500000655651093\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"low\",\n \"properties\": {\n \"dtype\": \"float32\",\n \"num_unique_values\": 3,\n \"samples\": [\n -0.2070000022649765,\n -0.2240000069141388,\n 0.7369999885559082\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"high\",\n \"properties\": {\n \"dtype\": \"float32\",\n \"num_unique_values\": 3,\n \"samples\": [\n 0.28700000047683716,\n 0.4909999966621399,\n 1.2630000114440918\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" + } + }, + "metadata": {}, + "execution_count": 40 + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.36\n", + "xseq = np.linspace(min(dcc.N) - 0.15, max(dcc.N) + 0.15,30)\n", + "fn_mu_K_5_5 = lambda _samples,_N: _samples[:,0] + _samples[:,1] * _N\n", + "sampled_mu_K = jax.vmap(fn_mu_K_5_5,in_axes=(None,0),out_axes=1)(df_post_samples_m_5_5.to_numpy(),xseq)\n", + "K_PI = np.apply_along_axis(arviz.hdi, axis=0, arr=np.array(sampled_mu_K),hdi_prob=credib_interval).T\n", + "K_mean = jnp.mean(sampled_mu_K,axis=0)\n", + "fig,axs = plt.subplots(1,1, figsize=(8,4))\n", + "axs.plot(xseq,K_mean,linewidth=1.0)\n", + "axs.fill_between(xseq, K_PI[:,0],K_PI[:,1], alpha=0.2)\n", + "axs.set_xlabel('neocortex percent(std)')\n", + "axs.set_ylabel('kcal per gram(std)')\n", + "plt.show()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 420 + }, + "id": "1uAGtKE0VssJ", + "outputId": "5e4d8cfd-8529-4d65-ae72-5bcba37e86a8" + }, + "execution_count": 41, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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+ }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.37\n", + "model5_6 = tfd.JointDistributionNamedAutoBatched(OrderedDict(\n", + " a = tfd.Normal(loc=0.0,scale=0.2),\n", + " bM = tfd.Normal(loc= 0,scale = 0.5),\n", + " sigma = tfd.Exponential(rate = 1.0),\n", + " mu = lambda a,bM : tfd.Deterministic(a + bM * M_arr),\n", + " K = lambda mu,sigma: tfd.Sample(tfd.Normal(loc=mu,scale=sigma))\n", + "))\n", + "def nll5_6(parameters):\n", + " samples = model5_6.sample(\n", + " K = K_arr,\n", + " a = parameters[0],\n", + " bM = parameters[1],\n", + " sigma = parameters[2],\n", + " seed = jax.random.PRNGKey(42))\n", + " return -1* model5_6.log_prob(samples)\n", + "optimize_fn = ScipyMinimize(fun= nll5_6,method = 'L-BFGS-B')\n", + "a_start = model5_6.parameters['model']['a'].mean()\n", + "bM_start = model5_6.parameters['model']['bM'].mean()\n", + "sigma_start = model5_6.parameters['model']['sigma'].mean()\n", + "results_m5_6 = optimize_fn.run(init_params=jnp.array([a_start,bM_start,sigma_start]))\n", + "df_result_m5_6,cov_matrix_m5_6,df_post_samples_m_5_6 = marginal_test_results(\n", + " model =model5_6,results=results_m5_6,nll=nll5_6,credib_interval=0.89)\n", + "df_result_m5_6.round(3)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 143 + }, + "id": "jrUcic52MdEG", + "outputId": "1f7922d5-3c83-4d94-c7b7-203b79bfb16e" + }, + "execution_count": 42, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + " mean sd low high\n", + "a 0.047 0.151 -0.195 0.288\n", + "bM -0.283 0.193 -0.591 0.026\n", + "sigma 0.949 0.157 0.698 1.200" + ], + "text/html": [ + "\n", + "
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bM-0.2830.193-0.5910.026
sigma0.9490.1570.6981.200
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\n" + ], + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "dataframe", + "summary": "{\n \"name\": \"df_result_m5_6\",\n \"rows\": 3,\n \"fields\": [\n {\n \"column\": \"mean\",\n \"properties\": {\n \"dtype\": \"float32\",\n \"num_unique_values\": 3,\n \"samples\": [\n 0.04699999839067459,\n -0.28299999237060547,\n 0.9490000009536743\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"sd\",\n \"properties\": {\n \"dtype\": \"float32\",\n \"num_unique_values\": 3,\n \"samples\": [\n 0.1509999930858612,\n 0.19300000369548798,\n 0.15700000524520874\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"low\",\n \"properties\": {\n \"dtype\": \"float32\",\n \"num_unique_values\": 3,\n \"samples\": [\n -0.19499999284744263,\n -0.5910000205039978,\n 0.6980000138282776\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"high\",\n \"properties\": {\n \"dtype\": \"float32\",\n \"num_unique_values\": 3,\n \"samples\": [\n 0.2879999876022339,\n 0.026000000536441803,\n 1.2000000476837158\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" + } + }, + "metadata": {}, + "execution_count": 42 + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.37 [graph]\n", + "xseq = np.linspace(min(dcc.M) - 0.15, max(dcc.M) + 0.15,30)\n", + "fn_mu_K_5_6 = lambda _samples,_M: _samples[:,0] + _samples[:,1] * _M\n", + "sampled_mu_K = jax.vmap(fn_mu_K_5_6,in_axes=(None,0),out_axes=1)(df_post_samples_m_5_6.to_numpy(),xseq)\n", + "K_PI = np.apply_along_axis(arviz.hdi, axis=0, arr=np.array(sampled_mu_K),hdi_prob=credib_interval).T\n", + "K_mean = jnp.mean(sampled_mu_K,axis=0)\n", + "fig,axs = plt.subplots(1,1, figsize=(8,4))\n", + "axs.plot(xseq,K_mean,linewidth=1.0)\n", + "axs.fill_between(xseq, K_PI[:,0],K_PI[:,1], alpha=0.2)\n", + "axs.set_xlabel('log body mass(std)')\n", + "axs.set_ylabel('kcal per gram(std)')\n", + "plt.show()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 413 + }, + "id": "CTVoC9kevcrs", + "outputId": "3891e4c9-3a66-4a0a-ad08-7b28b6b2e270" + }, + "execution_count": 43, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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+ }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.38 [adding both predictors]\n", + "model5_7 = tfd.JointDistributionNamedAutoBatched(OrderedDict(\n", + " a = tfd.Normal(loc=0.0,scale=0.2),\n", + " bM = tfd.Normal(loc= 0,scale = 0.5),\n", + " bN = tfd.Normal(loc= 0.0, scale =0.5),\n", + " sigma = tfd.Exponential(rate = 1.0),\n", + " mu = lambda a,bM,bN : tfd.Deterministic(a + bM * M_arr + bN * N_arr),\n", + " K = lambda mu,sigma: tfd.Sample(tfd.Normal(loc=mu,scale=sigma))\n", + "))\n", + "def nll_5_7(parameters):\n", + " samples = model5_7.sample(\n", + " K = K_arr,\n", + " a = parameters[0],\n", + " bM = parameters[1],\n", + " bN = parameters[2],\n", + " sigma = parameters[3],\n", + " seed = jax.random.PRNGKey(42))\n", + " return -1* model5_7.log_prob(samples)\n", + "optimize_fn = ScipyMinimize(fun= nll_5_7,method = 'L-BFGS-B')\n", + "a_start = model5_7.parameters['model']['a'].mean()\n", + "bM_start = model5_7.parameters['model']['bM'].mean()\n", + "bN_start = model5_7.parameters['model']['bN'].mean()\n", + "sigma_start = model5_7.parameters['model']['sigma'].mean()\n", + "results_m5_7 = optimize_fn.run(init_params=jnp.array([a_start,bM_start,bN_start,sigma_start]))\n", + "df_result_m5_7,cov_matrix_m5_7,df_post_samples_m_5_7 = marginal_test_results(\n", + " model =model5_7,results=results_m5_7,nll=nll_5_7,credib_interval=0.89)\n", + "df_result_m5_7.round(3)\n" + ], + "metadata": { + "id": "jV_Tkpwo4C40", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 175 + }, + "outputId": "ee657867-5ab8-4a95-ac5f-aea44fb12496" + }, + "execution_count": 44, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + " mean sd low high\n", + "a 0.068 0.134 -0.146 0.282\n", + "bM -0.703 0.221 -1.056 -0.350\n", + "bN 0.675 0.248 0.278 1.072\n", + "sigma 0.738 0.132 0.526 0.950" + ], + "text/html": [ + "\n", + "
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meansdlowhigh
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bM-0.7030.221-1.056-0.350
bN0.6750.2480.2781.072
sigma0.7380.1320.5260.950
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\n" + ], + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "dataframe", + "summary": "{\n \"name\": \"df_result_m5_7\",\n \"rows\": 4,\n \"fields\": [\n {\n \"column\": \"mean\",\n \"properties\": {\n \"dtype\": \"float32\",\n \"num_unique_values\": 4,\n \"samples\": [\n -0.703000009059906,\n 0.7379999756813049,\n 0.06800000369548798\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"sd\",\n \"properties\": {\n \"dtype\": \"float32\",\n \"num_unique_values\": 4,\n \"samples\": [\n 0.22100000083446503,\n 0.13199999928474426,\n 0.1340000033378601\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"low\",\n \"properties\": {\n \"dtype\": \"float32\",\n \"num_unique_values\": 4,\n \"samples\": [\n -1.055999994277954,\n 0.5260000228881836,\n -0.1459999978542328\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"high\",\n \"properties\": {\n \"dtype\": \"float32\",\n \"num_unique_values\": 4,\n \"samples\": [\n -0.3499999940395355,\n 0.949999988079071,\n 0.28200000524520874\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" + } + }, + "metadata": {}, + "execution_count": 44 + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.39\n", + "fig,ax = plt.subplots(1,1,figsize=(12,8))\n", + "az.plot_forest(\n", + "data = [{\"bN\":df_post_samples_m_5_5['bN'].values},{\"bM\":df_post_samples_m_5_6['bM'].values},\n", + " {\"bN\": df_post_samples_m_5_7['bN'], \"bM\":df_post_samples_m_5_7['bM'].values }],\n", + "hdi_prob=0.89,\n", + "model_names=[\"m5.5\",\"m5.6\",\"m5.7\"],\n", + "ax=ax,\n", + ")\n", + "ax.set_title('Estimate')\n", + "plt.show()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 739 + }, + "id": "AtX-E0Q6tQgS", + "outputId": "7ec3eb4e-95a9-49ae-a193-7a572ecbca21" + }, + "execution_count": 45, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.40 [Counterfactual holding N = 0]\n", + "M_seq = np.linspace(dcc.M.min() - 0.15, dcc.M.max() + 0.15,30)\n", + "N_seq = np.zeros_like(M_seq)\n", + "sim_data = pd.DataFrame({'M':M_seq,'N':N_seq})\n", + "fn_mu_K_5_7 = lambda _samples,_M,_N: _samples[:,0] + _samples[:,1] * _M + _samples[:,2] * _N\n", + "sampled_mu_K = jax.vmap(fn_mu_K_5_7,in_axes=(None,0,0),out_axes=1)(df_post_samples_m_5_7.to_numpy(),M_seq,N_seq)\n", + "\n", + "K_PI = np.apply_along_axis(arviz.hdi, axis=0, arr=np.array(sampled_mu_K),hdi_prob=credib_interval).T\n", + "K_mean = jnp.mean(sampled_mu_K,axis=0)\n", + "fig,axs = plt.subplots(1,1, figsize=(8,4))\n", + "axs.plot(M_seq,K_mean,linewidth=1.0)\n", + "axs.fill_between(M_seq, K_PI[:,0],K_PI[:,1], alpha=0.2)\n", + "axs.set_xlabel('log body mass(std)')\n", + "axs.set_ylabel('kcal per gram(std)')\n", + "axs.set_title('Counterfactual holding N = 0')\n", + "plt.show()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 443 + }, + "id": "QCn_buVCu-fm", + "outputId": "7c9f90d5-5db3-4198-a2ed-8b3596a1b80f" + }, + "execution_count": 46, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.40 [Counterfactual holding M = 0]\n", + "N_seq = np.linspace(dcc.N.min() - 0.15, dcc.N.max() + 0.15,30)\n", + "M_seq = np.zeros_like(N_seq)\n", + "sim_data = pd.DataFrame({'M':M_seq,'N':N_seq})\n", + "fn_mu_K_5_7 = lambda _samples,_M,_N: _samples[:,0] + _samples[:,1] * _M + _samples[:,2] * _N\n", + "sampled_mu_K = jax.vmap(fn_mu_K_5_7,in_axes=(None,0,0),out_axes=1)(df_post_samples_m_5_7.to_numpy(),M_seq,N_seq)\n", + "\n", + "K_PI = np.apply_along_axis(arviz.hdi, axis=0, arr=np.array(sampled_mu_K),hdi_prob=credib_interval).T\n", + "K_mean = jnp.mean(sampled_mu_K,axis=0)\n", + "fig,axs = plt.subplots(1,1, figsize=(8,4))\n", + "axs.plot(N_seq,K_mean,linewidth=1.0)\n", + "axs.fill_between(N_seq, K_PI[:,0],K_PI[:,1], alpha=0.2,color ='red')\n", + "axs.set_xlabel('log body mass(std)')\n", + "axs.set_ylabel('kcal per gram(std)')\n", + "axs.set_title('Counterfactual holding M = 0')\n", + "plt.show()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 443 + }, + "id": "QZSDpChWtEC0", + "outputId": "06323092-9e99-4363-a947-1ff8da9b2e6d" + }, + "execution_count": 47, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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+ }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.41\n", + "n = 100\n", + "M = stats.norm.rvs(size=n)\n", + "N = stats.norm.rvs(loc=M,size=n)\n", + "K = stats.norm.rvs(loc= N - M,size=n)\n", + "d_sim = pd.DataFrame({'M':M,'N':N,'K':K})\n" + ], + "metadata": { + "id": "PfRnza7QV8sM" + }, + "execution_count": 48, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.42\n", + "n = 100\n", + "N = stats.norm.rvs(size=n)\n", + "M = stats.norm.rvs(loc=N,size=n)\n", + "K = stats.norm.rvs(loc= N - M,size=n)\n", + "d_sim2 = pd.DataFrame({'M':M,'N':N,'K':K})\n", + "\n", + "n = 100\n", + "U = stats.norm.rvs(size=n)\n", + "N = stats.norm.rvs(loc=U,size=n)\n", + "M = stats.norm.rvs(loc=N,size=n)\n", + "K = stats.norm.rvs(loc= N - M,size=n)\n", + "d_sim3 = pd.DataFrame({'M':M,'N':N,'K':K})" + ], + "metadata": { + "id": "VbBa0dk8WvMA" + }, + "execution_count": 49, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "To do 5.43\n", + "- also apply the models to above simulated data" + ], + "metadata": { + "id": "IXRCMZCHrc2N" + } + }, + { + "cell_type": "code", + "source": [ + "#@title 5.44\n", + "d = pd.read_csv('https://raw.githubusercontent.com/sushmit86/Statiistical_rethinking_jax/main/Howell1.csv',sep= ';')\n", + "d.info()\n", + "d['sex'] = d['male'].map(lambda x: 2 if x ==1 else 1)\n", + "d.head()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 397 + }, + "id": "Yhm8qhzQzx4f", + "outputId": "6fa6bb36-d781-4f1f-c255-1bb29f4c4834" + }, + "execution_count": 50, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "\n", + "RangeIndex: 544 entries, 0 to 543\n", + "Data columns (total 4 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 height 544 non-null float64\n", + " 1 weight 544 non-null float64\n", + " 2 age 544 non-null float64\n", + " 3 male 544 non-null int64 \n", + "dtypes: float64(3), int64(1)\n", + "memory usage: 17.1 KB\n" + ] + }, + { + "output_type": "execute_result", + "data": { + "text/plain": [ + " height weight age male sex\n", + "0 151.765 47.825606 63.0 1 2\n", + "1 139.700 36.485807 63.0 0 1\n", + "2 136.525 31.864838 65.0 0 1\n", + "3 156.845 53.041914 41.0 1 2\n", + "4 145.415 41.276872 51.0 0 1" + ], + "text/html": [ + "\n", + "
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" + ] + }, + "metadata": {} + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "diff_fm 89% HDI [-11.496262 -4.005905]\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.49\n", + "milk = pd.read_csv('https://raw.githubusercontent.com/sushmit86/Statiistical_rethinking_jax/main/milk.csv',sep= ';')\n", + "d = milk.copy()\n", + "display(d.info())\n", + "d.head()\n", + "d.clade.unique()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 329 + }, + "id": "Puz0ejUhszdT", + "outputId": "69b4435a-1d78-40d1-c753-55f19b0ef6ba" + }, + "execution_count": 55, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "\n", + "RangeIndex: 29 entries, 0 to 28\n", + "Data columns (total 8 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 clade 29 non-null object \n", + " 1 species 29 non-null object \n", + " 2 kcal.per.g 29 non-null float64\n", + " 3 perc.fat 29 non-null float64\n", + " 4 perc.protein 29 non-null float64\n", + " 5 perc.lactose 29 non-null float64\n", + " 6 mass 29 non-null float64\n", + " 7 neocortex.perc 17 non-null float64\n", + "dtypes: float64(6), object(2)\n", + "memory usage: 1.9+ KB\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "None" + ] + }, + "metadata": {} + }, + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "array(['Strepsirrhine', 'New World Monkey', 'Old World Monkey', 'Ape'],\n", + " dtype=object)" + ] + }, + "metadata": {}, + "execution_count": 55 + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.50\n", + "d_clade_id_series = d.clade.factorize(sort = True)[0]\n", + "d_clade_id_index = d.clade.factorize(sort = True)[1]\n", + "d['clade_id'] = d_clade_id_series\n", + "d[\"K\"] = d['kcal.per.g'].pipe(lambda x: (x - x.mean())/x.std())\n", + "K_arr = jnp.array(d.K)\n", + "clade_id_arr = jnp.array(d.clade_id)" + ], + "metadata": { + "id": "qwgoAmin0V0P" + }, + "execution_count": 56, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "d_clade_id_index" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "giwPUwRZ50qh", + "outputId": "1a8c3f00-8f09-4f82-cfec-3aa20a044245" + }, + "execution_count": 57, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "Index(['Ape', 'New World Monkey', 'Old World Monkey', 'Strepsirrhine'], dtype='object')" + ] + }, + "metadata": {}, + "execution_count": 57 + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.51\n", + "model_5_9 = tfd.JointDistributionNamedAutoBatched(OrderedDict(\n", + " alpha = tfp_jax.distributions.Sample(tfp_jax.distributions.Normal(loc=0., scale=0.5), sample_shape= 4),\n", + " sigma = tfp_jax.distributions.Exponential(rate = 1.0),\n", + " mu = lambda alpha : tfd.Deterministic(jnp.take(alpha,clade_id_arr)),\n", + " K = lambda mu,sigma: tfd.Sample(tfd.Normal(loc=mu,scale=sigma))\n", + "\n", + "))\n", + "def nll_5_9(parameters):\n", + " samples = model_5_9.sample(\n", + " K = K_arr,\n", + " alpha = parameters[0:4],\n", + " sigma = parameters[4],\n", + " seed = jax.random.PRNGKey(42))\n", + " return -1* model_5_9.log_prob(samples)\n", + "\n", + "optimize_fn = ScipyMinimize(fun= nll_5_9,method = 'L-BFGS-B')\n", + "alpha_start = model_5_9.parameters['model']['alpha'].mean()\n", + "sigma_start = model_5_9.parameters['model']['sigma'].mean()\n", + "results_m5_9 = optimize_fn.run(init_params=jnp.append(alpha_start,sigma_start))\n", + "df_result_m5_9,cov_matrix_m5_9,df_post_samples_m_5_9 = marginal_test_results(\n", + " model =model_5_9,results=results_m5_9,nll=nll_5_9,credib_interval=0.89)\n", + "df_result_m5_9" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 206 + }, + "id": "Mx3ilfSm1dcg", + "outputId": "da68a26e-1325-4669-9111-43a5ca97837a" + }, + "execution_count": 58, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + " mean sd low high\n", + "alpha_0 -0.484496 0.217628 -0.832307 -0.136685\n", + "alpha_1 0.366364 0.217047 0.019481 0.713247\n", + "alpha_2 0.675135 0.257526 0.263558 1.086712\n", + "alpha_3 -0.585466 0.274509 -1.024184 -0.146747\n", + "sigma 0.719606 0.096520 0.565347 0.873864" + ], + "text/html": [ + "\n", + "
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\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "#@title 5.52\n", + "house_series = np.array([1,2,3,1,3,2,1,3,4,1,4,3,3,3,1,4,4,4,2,1,1,2,3,2,3,2,1,2,4]) ## copy the series from R directly\n", + "house_series = house_series - 1\n", + "house_series_arr = jnp.array(house_series)\n", + "\n", + "model5_10 = tfd.JointDistributionNamedAutoBatched(OrderedDict(\n", + " alpha = tfp_jax.distributions.Sample(tfp_jax.distributions.Normal(loc=0., scale=0.5), sample_shape= 4),\n", + " h = tfp_jax.distributions.Sample(tfp_jax.distributions.Normal(loc=0., scale=0.5), sample_shape= 4),\n", + " sigma = tfp_jax.distributions.Exponential(rate = 1.0),\n", + " mu = lambda alpha,h : tfd.Deterministic(jnp.take(alpha,clade_id_arr)+ jnp.take(h,house_series_arr)),\n", + " K = lambda mu,sigma: tfd.Sample(tfd.Normal(loc=mu,scale=sigma))\n", + "\n", + "))\n", + "def nll5_10(parameters):\n", + " samples = model5_10.sample(\n", + " K = K_arr,\n", + " alpha = parameters[0:4],\n", + " h = parameters[4:8],\n", + " sigma = parameters[8],\n", + " seed = jax.random.PRNGKey(42))\n", + " return -1* model5_10.log_prob(samples)\n", + "optimize_fn = ScipyMinimize(fun= nll5_10,method = 'L-BFGS-B')\n", + "alpha_start = model5_10.parameters['model']['alpha'].mean()\n", + "h_start = model5_10.parameters['model']['h'].mean()\n", + "sigma_start = model5_10.parameters['model']['sigma'].mean()\n", + "\n", + "results_m5_10 = optimize_fn.run(init_params=jnp.append(alpha_start,jnp.append(h_start,sigma_start)))\n", + "df_result_m5_10,cov_matrix_m5_10,df_post_samples_m_5_10 = marginal_test_results(\n", + " model =model5_10,results=results_m5_10,nll=nll5_10,credib_interval=0.89)\n", + "df_result_m5_10.round(2)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 332 + }, + "id": "8G7Be1gR61ND", + "outputId": "0de4ae58-2641-403a-f6ab-8eaf7ec2c72b" + }, + "execution_count": 60, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + " mean sd low high\n", + "alpha_0 -0.42 0.26 -0.84 -0.00\n", + "alpha_1 0.38 0.26 -0.03 0.80\n", + "alpha_2 0.57 0.29 0.10 1.03\n", + "alpha_3 -0.51 0.30 -0.98 -0.03\n", + "h_0 -0.10 0.26 -0.52 0.32\n", + "h_1 -0.20 0.28 -0.64 0.24\n", + "h_2 -0.16 0.27 -0.59 0.27\n", + "h_3 0.49 0.29 0.03 0.95\n", + "sigma 0.66 0.09 0.52 0.80" + ], + "text/html": [ + "\n", + "
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